If only a few labeled training examples are available, it can often be beneficial to use pre-training, i.e., first train the neural network on an different task with more training data so that the weights of the network already capture e.g. basic image statistics, and then fine tune the network with the given labeled examples for the real task.
In this notebook we compare pre-training on different tasks, with different network architectures (i.e. different number of hidden units) and different numbers of training samples on the CIFAR10 dataset.
In [1]:
from __future__ import unicode_literals, division, print_function, absolute_import
from builtins import range
from copy import deepcopy
import random
random.seed(28)
import numpy as np
np.random.seed(28)
import matplotlib.pyplot as plt
import torch
import torch.nn as nn
import torch.optim as optim
from torch.utils.data.sampler import SubsetRandomSampler
torch.manual_seed(28)
torch.cuda.manual_seed(28)
torch.backends.cudnn.deterministic = True
import torchvision
from torchvision import datasets, transforms
from simec_torch import Dense
from utils_plotting import get_colors
%matplotlib inline
%load_ext autoreload
%autoreload 2
# set this to True if you want to save the figures
savefigs = False
In [2]:
## basic FFNN for classification
class FFNN(nn.Module):
def __init__(self, hu_pow=7):
super(FFNN, self).__init__()
self.nn = nn.Sequential(
Dense(3*32*32, 2**hu_pow, activation=torch.tanh),
Dense(2**hu_pow, 32, activation=torch.tanh))
def forward(self, x):
return self.nn(x)
## classifier based on FFNN
class CLF(nn.Module):
def __init__(self, ffnn, n_classes=5):
super(CLF, self).__init__()
self.ffnn = ffnn
self.lastlayer = nn.Sequential(
nn.Linear(32, n_classes),
nn.LogSoftmax(dim=1)
)
def forward(self, x):
x = x.view(-1, 3*32*32)
x = self.ffnn(x)
x = self.lastlayer(x)
return x
In [3]:
use_cuda = torch.cuda.is_available()
device = torch.device("cuda" if use_cuda else "cpu")
kwargs = {'num_workers': 1, 'pin_memory': True} if use_cuda else {}
img_transform = transforms.Compose([
transforms.ToTensor(),
transforms.Normalize(mean=[0.4914, 0.4822, 0.4465],
std=[0.2023, 0.1994, 0.2010])
])
# load the data (with artificial split for validation)
train_dataset = datasets.CIFAR10('./data/cifar10', train=True, download=True, transform=img_transform)
test_dataset = datasets.CIFAR10('./data/cifar10', train=False, transform=img_transform)
# get indices for training and test data and split for two tasks
np.random.seed(15)
indices = np.random.permutation(len(train_dataset))
indices_t1_train = [i for i in indices if train_dataset.targets[i] < 5]
indices_t2_train = [i for i in indices if train_dataset.targets[i] >= 5]
indices_test = np.random.permutation(len(test_dataset))
indices_t1_test = [i for i in indices_test if test_dataset.targets[i] < 5]
indices_t2_test = [i for i in indices_test if test_dataset.targets[i] >= 5]
# get some loaders
n_valid = 5000
# test on real task
test_loader_t2 = torch.utils.data.DataLoader(
test_dataset, batch_size=128, sampler=SubsetRandomSampler(indices_t2_test), **kwargs
)
# always use the same validation set
valid_loader_t2 = torch.utils.data.DataLoader(
train_dataset, batch_size=128, sampler=SubsetRandomSampler(indices_t2_train[-n_valid:]), **kwargs
)
Files already downloaded and verified
In [4]:
def imshow(img):
img = img / 5 + 0.5 # unnormalize
npimg = img.numpy()
plt.figure(figsize=(10, 5))
plt.imshow(np.transpose(npimg, (1, 2, 0)))
plt.axis("off")
classes = ('plane', 'car', 'bird', 'cat',
'deer', 'dog', 'frog', 'horse', 'ship', 'truck')
# get some random training images
image_loader = torch.utils.data.DataLoader(
train_dataset, batch_size=500, sampler=SubsetRandomSampler(indices), **kwargs
)
dataiter = iter(image_loader)
images, labels = dataiter.next()
labels = list(labels.numpy())
image_idx = [labels.index(i) for i in range(10)]
# show images
imshow(torchvision.utils.make_grid([images[i] for i in image_idx], nrow=10))
# print labels
# plt.title(' '.join('%10s ' % classes[labels[i]] for i in image_idx))
if savefigs: plt.savefig("cifar10.png", dpi=300, bbox_inches="tight")
Clipping input data to the valid range for imshow with RGB data ([0..1] for floats or [0..255] for integers).
In [5]:
n_training_examples = [25, 50, 100, 250, 500, 750, 1000, 2500, 5000, 10000, 15000, 20000]
def plot_mean_std(test_accs, c, label):
data_mean = np.array([t[0] for t in test_accs])
data_std = np.array([t[1] for t in test_accs])
plt.plot(n_training_examples, data_mean, color=c, linewidth=1.8, label=label)
if np.max(data_std) > 0:
plt.plot(n_training_examples, data_mean+data_std, "--", color=c, linewidth=0.5, alpha=0.5)
plt.plot(n_training_examples, data_mean-data_std, "--", color=c, linewidth=0.5, alpha=0.5)
plt.fill_between(n_training_examples, data_mean+data_std, data_mean-data_std, color=c, alpha=0.05)
def plot_all(test_accuracies, title="", ylabel="Test"):
colors = get_colors(10)
plt.figure()
plot_mean_std(test_accuracies["B"], c="k", label="no pretraining")
plot_mean_std(test_accuracies["BnB"], c=colors[6], label="pretr. on B")
plot_mean_std(test_accuracies["ABnB"], c=colors[7], label="pretr. on A & B")
plot_mean_std(test_accuracies["AnB"], c=colors[8], label="pretr. on A")
if title:
plt.title(title)
plt.xlabel("Number of training examples for classifier")
plt.xticks([25, 5000, 10000, 20000], [25, 5000, 10000, 20000])
plt.ylabel("%s accuracy" % ylabel.title())
if ylabel.lower() == "test":
plt.ylim(0.55, 0.72)
elif ylabel.lower() == "train":
plt.ylim(0.55, 1.05)
else:
plt.ylabel("Generalization error")
l = plt.legend(bbox_to_anchor=(1.02, 1), loc=2, borderaxespad=0.);
print("n_training_examples =", n_training_examples)
print("%s_accuracies =" % ylabel.lower(), test_accuracies)
if savefigs: plt.savefig('img_%s_%s.pdf' % (ylabel.lower(), title.replace(" ", "_")), dpi=300, bbox_inches="tight", bbox_extra_artists=[l])
In [6]:
def test_clf(model, test_loader):
criterion = nn.NLLLoss(reduction="sum")
model.eval()
test_loss = 0
correct = 0
with torch.no_grad():
for data, target in test_loader:
if target.min() > 4:
target -= 5
data, target = data.to(device), target.to(device)
output = model(data)
test_loss += criterion(output, target).item() # sum up batch loss
pred = output.max(1, keepdim=True)[1] # get the index of the max log-probability
correct += pred.eq(target.view_as(pred)).sum().item()
test_loss /= len(test_loader.sampler)
print('Test set: Average loss: {:.4f}, Accuracy: {}/{} ({:.0f}%)'.format(
test_loss, correct, len(test_loader.sampler),
100. * correct / len(test_loader.sampler)))
return correct / len(test_loader.sampler)
def train_clf_epoch(model, epoch, train_loader, optimizer, lr_scheduler):
criterion = nn.NLLLoss()
model.train()
running_loss = 0.
for batch_idx, (data, target) in enumerate(train_loader):
# for t1 the loss still expects the labels to be between 0 and 4
if target.min() > 4:
target -= 5
data, target = data.to(device), target.to(device)
optimizer.zero_grad()
output = model(data)
loss = criterion(output, target)
running_loss += loss.item()
loss.backward()
optimizer.step()
print('[epoch %d] loss: %.7f' % (epoch + 1, running_loss / (batch_idx + 1)))
lr_scheduler.step(running_loss)
def train_clf(model, train_loader, valid_loader, n_epochs=25):
print("Validation accuracy before training:")
_ = test_clf(model, valid_loader)
optimizer = optim.Adam(model.parameters(), lr=0.00005)
lr_scheduler = optim.lr_scheduler.ReduceLROnPlateau(optimizer, patience=0, eps=0., verbose=True)
best_acc = 0
best_model = None
for epoch in range(n_epochs):
train_clf_epoch(model, epoch, train_loader, optimizer, lr_scheduler)
val_acc = test_clf(model, valid_loader)
if val_acc >= best_acc:
best_acc = val_acc
best_model = deepcopy(model.state_dict())
model.load_state_dict(best_model)
print("Validation:")
_ = test_clf(model, valid_loader)
return model
def train_clf_t2_ntrain(n_train, hu_pow=1, ffnn_dict=None, frozen=False):
test_accs = []
train_accs = []
gen_err = []
for seed in [11, 12, 13]:
print("## seed:", seed)
# get train_loader with specific number of training examples
np.random.seed(seed)
indices = np.random.permutation(indices_t2_train[:-n_valid])[:n_train]
train_loader = torch.utils.data.DataLoader(
train_dataset, batch_size=32, sampler=SubsetRandomSampler(indices), **kwargs
)
# pretrained ffnn?
ffnn = FFNN(hu_pow)
if ffnn_dict is not None:
ffnn.load_state_dict(ffnn_dict)
if frozen:
for p in ffnn.parameters():
p.requires_grad = False
# do the actual training
model = train_clf(CLF(ffnn).to(device), train_loader, valid_loader_t2)
print("Test")
test_accs.append(test_clf(model, test_loader_t2))
train_accs.append(test_clf(model, train_loader))
gen_err.append(train_accs[-1] - test_accs[-1])
del ffnn, model, train_loader
torch.cuda.empty_cache()
return np.mean(test_accs), np.std(test_accs), np.mean(train_accs), np.std(train_accs), np.mean(gen_err), np.std(gen_err)
def pretrain_t2(hu_pow=1):
# CLF pretraining on T2
train_loader = torch.utils.data.DataLoader(
train_dataset, batch_size=32, sampler=SubsetRandomSampler(indices_t2_train[:-n_valid]), **kwargs
)
ffnn = FFNN(hu_pow)
model = train_clf(CLF(ffnn).to(device), train_loader, valid_loader_t2)
_ = test_clf(model, test_loader_t2)
sd = deepcopy(model.ffnn.state_dict())
del ffnn, model, train_loader
torch.cuda.empty_cache()
# return the ffnn state
return sd
def pretrain_t1(hu_pow=1):
# CLF pretraining on T1
valid_loader = torch.utils.data.DataLoader(
train_dataset, batch_size=128, sampler=SubsetRandomSampler(indices_t1_train[-n_valid:]), **kwargs
)
train_loader = torch.utils.data.DataLoader(
train_dataset, batch_size=32, sampler=SubsetRandomSampler(indices_t1_train[:-n_valid]), **kwargs
)
test_loader = torch.utils.data.DataLoader(
test_dataset, batch_size=128, sampler=SubsetRandomSampler(indices_t1_test), **kwargs
)
ffnn = FFNN(hu_pow)
model = train_clf(CLF(ffnn).to(device), train_loader, valid_loader)
_ = test_clf(model, test_loader)
sd = deepcopy(model.ffnn.state_dict())
del ffnn, model, train_loader, valid_loader, test_loader
torch.cuda.empty_cache()
# return the ffnn state
return sd
def pretrain_t1t2(hu_pow=1):
# CLF pretraining on T1 + T2
valid_loader = torch.utils.data.DataLoader(
train_dataset, batch_size=128, sampler=SubsetRandomSampler(indices[-n_valid:]), **kwargs
)
train_loader = torch.utils.data.DataLoader(
train_dataset, batch_size=32, sampler=SubsetRandomSampler(indices[:len(indices_t2_train)]), **kwargs
)
test_loader = torch.utils.data.DataLoader(
test_dataset, batch_size=128, sampler=SubsetRandomSampler(indices_test), **kwargs
)
ffnn = FFNN(hu_pow)
model = train_clf(CLF(ffnn, n_classes=10).to(device), train_loader, valid_loader)
_ = test_clf(model, test_loader)
sd = deepcopy(model.ffnn.state_dict())
del ffnn, model, train_loader, valid_loader, test_loader
torch.cuda.empty_cache()
# return the ffnn state
return sd
def train_all_ntrain(hu_pow=1, ffnn_dict=None, frozen=False):
# with or without pretraining (depending on ffnn_dict), do all ntrain trainings
test_accuracies = []
train_accuracies = []
gen_errors = []
for n_train in n_training_examples:
print(n_train)
test_mean, test_std, train_mean, train_std, gen_mean, gen_std = train_clf_t2_ntrain(n_train, hu_pow, ffnn_dict, frozen)
test_accuracies.append((test_mean, test_std))
train_accuracies.append((train_mean, train_std))
gen_errors.append((gen_mean, gen_std))
torch.cuda.empty_cache()
return test_accuracies, train_accuracies, gen_errors
def do_all_hl(hu_pow=1):
# for a certain number of hl, do the whole pretraining and fine tuning for all configs
print("#### Training for %i hu" % 2**hu_pow)
# no pretraining
print("## No Pre-Training")
test_accuracies_B, train_accuracies_B, gen_errors_B = train_all_ntrain(hu_pow)
print("test_accuracies_B =", test_accuracies_B)
print("train_accuracies_B =", train_accuracies_B)
print("gen_errors_B =", gen_errors_B)
torch.cuda.empty_cache()
# pretraining on T2
print("## Pre-Training BnB")
ffnn_dict = pretrain_t2(hu_pow)
test_accuracies_BnB, train_accuracies_BnB, gen_errors_BnB = train_all_ntrain(hu_pow, ffnn_dict)
print("test_accuracies_BnB =", test_accuracies_BnB)
print("train_accuracies_BnB =", train_accuracies_BnB)
print("gen_errors_BnB =", gen_errors_BnB)
torch.cuda.empty_cache()
# pretraining on T1
print("## Pre-Training AnB")
ffnn_dict = pretrain_t1(hu_pow)
test_accuracies_AnB, train_accuracies_AnB, gen_errors_AnB = train_all_ntrain(hu_pow, ffnn_dict)
print("test_accuracies_AnB =", test_accuracies_AnB)
print("train_accuracies_AnB =", train_accuracies_AnB)
print("gen_errors_AnB =", gen_errors_AnB)
torch.cuda.empty_cache()
# pretraining on T1 and T2
print("## Pre-Training ABnB")
ffnn_dict = pretrain_t1t2(hu_pow)
test_accuracies_ABnB, train_accuracies_ABnB, gen_errors_ABnB = train_all_ntrain(hu_pow, ffnn_dict)
print("test_accuracies_ABnB =", test_accuracies_ABnB)
print("train_accuracies_ABnB =", train_accuracies_ABnB)
print("gen_errors_ABnB =", gen_errors_ABnB)
torch.cuda.empty_cache()
# save and plot results
test_accuracies = { "B": test_accuracies_B,
"AnB": test_accuracies_AnB,
"BnB": test_accuracies_BnB,
"ABnB": test_accuracies_ABnB}
train_accuracies = { "B": train_accuracies_B,
"AnB": train_accuracies_AnB,
"BnB": train_accuracies_BnB,
"ABnB": train_accuracies_ABnB}
gen_errors = { "B": gen_errors_B,
"AnB": gen_errors_AnB,
"BnB": gen_errors_BnB,
"ABnB": gen_errors_ABnB}
plot_all(test_accuracies, "$2^{%i}$ hidden units" % (hu_pow))
plot_all(train_accuracies, "$2^{%i}$ hidden units" % (hu_pow), "Train")
plot_all(gen_errors, "$2^{%i}$ hidden units" % (hu_pow), "generr")
return test_accuracies, train_accuracies, gen_errors
In [7]:
results_test = {}
results_train = {}
results_generr = {}
n_hus = [7, 9, 11, 13]
results_test[n_hus[0]], results_train[n_hus[0]], results_generr[n_hus[0]] = do_all_hl(n_hus[0])
#### Training for 128 hu
## No Pre-Training
25
## seed: 11
Validation accuracy before training:
Test set: Average loss: 1.6339, Accuracy: 933/5000 (19%)
[epoch 1] loss: 1.6221858
Test set: Average loss: 1.6172, Accuracy: 1102/5000 (22%)
[epoch 2] loss: 1.5581599
Test set: Average loss: 1.6021, Accuracy: 1248/5000 (25%)
[epoch 3] loss: 1.4975702
Test set: Average loss: 1.5885, Accuracy: 1375/5000 (28%)
[epoch 4] loss: 1.4407657
Test set: Average loss: 1.5763, Accuracy: 1481/5000 (30%)
[epoch 5] loss: 1.3878071
Test set: Average loss: 1.5655, Accuracy: 1551/5000 (31%)
[epoch 6] loss: 1.3385679
Test set: Average loss: 1.5559, Accuracy: 1596/5000 (32%)
[epoch 7] loss: 1.2928232
Test set: Average loss: 1.5474, Accuracy: 1638/5000 (33%)
[epoch 8] loss: 1.2502923
Test set: Average loss: 1.5399, Accuracy: 1681/5000 (34%)
[epoch 9] loss: 1.2106700
Test set: Average loss: 1.5333, Accuracy: 1710/5000 (34%)
[epoch 10] loss: 1.1736581
Test set: Average loss: 1.5275, Accuracy: 1732/5000 (35%)
[epoch 11] loss: 1.1389924
Test set: Average loss: 1.5223, Accuracy: 1746/5000 (35%)
[epoch 12] loss: 1.1064517
Test set: Average loss: 1.5177, Accuracy: 1762/5000 (35%)
[epoch 13] loss: 1.0758567
Test set: Average loss: 1.5137, Accuracy: 1767/5000 (35%)
[epoch 14] loss: 1.0470612
Test set: Average loss: 1.5101, Accuracy: 1778/5000 (36%)
[epoch 15] loss: 1.0199420
Test set: Average loss: 1.5069, Accuracy: 1791/5000 (36%)
[epoch 16] loss: 0.9943899
Test set: Average loss: 1.5040, Accuracy: 1804/5000 (36%)
[epoch 17] loss: 0.9703012
Test set: Average loss: 1.5015, Accuracy: 1813/5000 (36%)
[epoch 18] loss: 0.9475713
Test set: Average loss: 1.4991, Accuracy: 1827/5000 (37%)
[epoch 19] loss: 0.9260939
Test set: Average loss: 1.4970, Accuracy: 1842/5000 (37%)
[epoch 20] loss: 0.9057623
Test set: Average loss: 1.4950, Accuracy: 1842/5000 (37%)
[epoch 21] loss: 0.8864757
Test set: Average loss: 1.4931, Accuracy: 1857/5000 (37%)
[epoch 22] loss: 0.8681431
Test set: Average loss: 1.4913, Accuracy: 1860/5000 (37%)
[epoch 23] loss: 0.8506881
Test set: Average loss: 1.4895, Accuracy: 1864/5000 (37%)
[epoch 24] loss: 0.8340505
Test set: Average loss: 1.4878, Accuracy: 1875/5000 (38%)
[epoch 25] loss: 0.8181837
Test set: Average loss: 1.4861, Accuracy: 1886/5000 (38%)
Validation:
Test set: Average loss: 1.4861, Accuracy: 1886/5000 (38%)
Test
Test set: Average loss: 1.4930, Accuracy: 1840/5000 (37%)
Test set: Average loss: 0.8031, Accuracy: 24/25 (96%)
## seed: 12
Validation accuracy before training:
Test set: Average loss: 1.6541, Accuracy: 827/5000 (17%)
[epoch 1] loss: 1.6973382
Test set: Average loss: 1.6195, Accuracy: 999/5000 (20%)
[epoch 2] loss: 1.6032932
Test set: Average loss: 1.5888, Accuracy: 1271/5000 (25%)
[epoch 3] loss: 1.5153362
Test set: Average loss: 1.5624, Accuracy: 1398/5000 (28%)
[epoch 4] loss: 1.4346205
Test set: Average loss: 1.5400, Accuracy: 1457/5000 (29%)
[epoch 5] loss: 1.3616142
Test set: Average loss: 1.5214, Accuracy: 1500/5000 (30%)
[epoch 6] loss: 1.2962375
Test set: Average loss: 1.5061, Accuracy: 1536/5000 (31%)
[epoch 7] loss: 1.2380476
Test set: Average loss: 1.4935, Accuracy: 1571/5000 (31%)
[epoch 8] loss: 1.1863803
Test set: Average loss: 1.4832, Accuracy: 1587/5000 (32%)
[epoch 9] loss: 1.1404603
Test set: Average loss: 1.4749, Accuracy: 1601/5000 (32%)
[epoch 10] loss: 1.0994946
Test set: Average loss: 1.4680, Accuracy: 1609/5000 (32%)
[epoch 11] loss: 1.0627420
Test set: Average loss: 1.4624, Accuracy: 1636/5000 (33%)
[epoch 12] loss: 1.0295504
Test set: Average loss: 1.4577, Accuracy: 1657/5000 (33%)
[epoch 13] loss: 0.9993694
Test set: Average loss: 1.4539, Accuracy: 1672/5000 (33%)
[epoch 14] loss: 0.9717424
Test set: Average loss: 1.4507, Accuracy: 1690/5000 (34%)
[epoch 15] loss: 0.9462956
Test set: Average loss: 1.4480, Accuracy: 1695/5000 (34%)
[epoch 16] loss: 0.9227222
Test set: Average loss: 1.4457, Accuracy: 1720/5000 (34%)
[epoch 17] loss: 0.9007688
Test set: Average loss: 1.4438, Accuracy: 1732/5000 (35%)
[epoch 18] loss: 0.8802258
Test set: Average loss: 1.4422, Accuracy: 1750/5000 (35%)
[epoch 19] loss: 0.8609182
Test set: Average loss: 1.4408, Accuracy: 1780/5000 (36%)
[epoch 20] loss: 0.8427004
Test set: Average loss: 1.4397, Accuracy: 1800/5000 (36%)
[epoch 21] loss: 0.8254522
Test set: Average loss: 1.4387, Accuracy: 1828/5000 (37%)
[epoch 22] loss: 0.8090758
Test set: Average loss: 1.4378, Accuracy: 1847/5000 (37%)
[epoch 23] loss: 0.7934924
Test set: Average loss: 1.4371, Accuracy: 1866/5000 (37%)
[epoch 24] loss: 0.7786391
Test set: Average loss: 1.4365, Accuracy: 1876/5000 (38%)
[epoch 25] loss: 0.7644661
Test set: Average loss: 1.4359, Accuracy: 1875/5000 (38%)
Validation:
Test set: Average loss: 1.4365, Accuracy: 1876/5000 (38%)
Test
Test set: Average loss: 1.4494, Accuracy: 1863/5000 (37%)
Test set: Average loss: 0.7645, Accuracy: 24/25 (96%)
## seed: 13
Validation accuracy before training:
Test set: Average loss: 1.6057, Accuracy: 1206/5000 (24%)
[epoch 1] loss: 1.6241275
Test set: Average loss: 1.5883, Accuracy: 1328/5000 (27%)
[epoch 2] loss: 1.5592531
Test set: Average loss: 1.5724, Accuracy: 1426/5000 (29%)
[epoch 3] loss: 1.4972672
Test set: Average loss: 1.5579, Accuracy: 1536/5000 (31%)
[epoch 4] loss: 1.4386127
Test set: Average loss: 1.5448, Accuracy: 1678/5000 (34%)
[epoch 5] loss: 1.3834746
Test set: Average loss: 1.5330, Accuracy: 1791/5000 (36%)
[epoch 6] loss: 1.3318486
Test set: Average loss: 1.5225, Accuracy: 1867/5000 (37%)
[epoch 7] loss: 1.2836193
Test set: Average loss: 1.5131, Accuracy: 1936/5000 (39%)
[epoch 8] loss: 1.2386127
Test set: Average loss: 1.5046, Accuracy: 1974/5000 (39%)
[epoch 9] loss: 1.1966299
Test set: Average loss: 1.4971, Accuracy: 2002/5000 (40%)
[epoch 10] loss: 1.1574683
Test set: Average loss: 1.4904, Accuracy: 2030/5000 (41%)
[epoch 11] loss: 1.1209309
Test set: Average loss: 1.4844, Accuracy: 2044/5000 (41%)
[epoch 12] loss: 1.0868272
Test set: Average loss: 1.4791, Accuracy: 2058/5000 (41%)
[epoch 13] loss: 1.0549688
Test set: Average loss: 1.4743, Accuracy: 2058/5000 (41%)
[epoch 14] loss: 1.0251653
Test set: Average loss: 1.4700, Accuracy: 2070/5000 (41%)
[epoch 15] loss: 0.9972286
Test set: Average loss: 1.4661, Accuracy: 2069/5000 (41%)
[epoch 16] loss: 0.9709784
Test set: Average loss: 1.4626, Accuracy: 2057/5000 (41%)
[epoch 17] loss: 0.9462481
Test set: Average loss: 1.4595, Accuracy: 2055/5000 (41%)
[epoch 18] loss: 0.9228888
Test set: Average loss: 1.4567, Accuracy: 2055/5000 (41%)
[epoch 19] loss: 0.9007732
Test set: Average loss: 1.4541, Accuracy: 2057/5000 (41%)
[epoch 20] loss: 0.8797984
Test set: Average loss: 1.4518, Accuracy: 2059/5000 (41%)
[epoch 21] loss: 0.8598871
Test set: Average loss: 1.4496, Accuracy: 2059/5000 (41%)
[epoch 22] loss: 0.8409835
Test set: Average loss: 1.4477, Accuracy: 2049/5000 (41%)
[epoch 23] loss: 0.8230413
Test set: Average loss: 1.4460, Accuracy: 2049/5000 (41%)
[epoch 24] loss: 0.8060124
Test set: Average loss: 1.4444, Accuracy: 2051/5000 (41%)
[epoch 25] loss: 0.7898414
Test set: Average loss: 1.4429, Accuracy: 2050/5000 (41%)
Validation:
Test set: Average loss: 1.4700, Accuracy: 2070/5000 (41%)
Test
Test set: Average loss: 1.4764, Accuracy: 2018/5000 (40%)
Test set: Average loss: 0.9972, Accuracy: 24/25 (96%)
50
## seed: 11
Validation accuracy before training:
Test set: Average loss: 1.6412, Accuracy: 904/5000 (18%)
[epoch 1] loss: 1.6170573
Test set: Average loss: 1.5950, Accuracy: 1100/5000 (22%)
[epoch 2] loss: 1.4962387
Test set: Average loss: 1.5588, Accuracy: 1275/5000 (26%)
[epoch 3] loss: 1.4262106
Test set: Average loss: 1.5332, Accuracy: 1378/5000 (28%)
[epoch 4] loss: 1.3404750
Test set: Average loss: 1.5142, Accuracy: 1455/5000 (29%)
[epoch 5] loss: 1.3014157
Test set: Average loss: 1.4983, Accuracy: 1533/5000 (31%)
[epoch 6] loss: 1.2105374
Test set: Average loss: 1.4863, Accuracy: 1573/5000 (31%)
[epoch 7] loss: 1.1957593
Test set: Average loss: 1.4767, Accuracy: 1606/5000 (32%)
[epoch 8] loss: 1.1302058
Test set: Average loss: 1.4679, Accuracy: 1649/5000 (33%)
[epoch 9] loss: 1.1088701
Test set: Average loss: 1.4600, Accuracy: 1679/5000 (34%)
[epoch 10] loss: 1.0701986
Test set: Average loss: 1.4529, Accuracy: 1726/5000 (35%)
[epoch 11] loss: 1.0423809
Test set: Average loss: 1.4464, Accuracy: 1775/5000 (36%)
[epoch 12] loss: 0.9885863
Test set: Average loss: 1.4415, Accuracy: 1793/5000 (36%)
[epoch 13] loss: 0.9606667
Test set: Average loss: 1.4368, Accuracy: 1825/5000 (36%)
[epoch 14] loss: 0.9214023
Test set: Average loss: 1.4325, Accuracy: 1845/5000 (37%)
[epoch 15] loss: 0.9092874
Test set: Average loss: 1.4294, Accuracy: 1867/5000 (37%)
[epoch 16] loss: 0.8869039
Test set: Average loss: 1.4272, Accuracy: 1879/5000 (38%)
[epoch 17] loss: 0.8545061
Test set: Average loss: 1.4259, Accuracy: 1898/5000 (38%)
[epoch 18] loss: 0.8548108
Epoch 17: reducing learning rate of group 0 to 5.0000e-06.
Test set: Average loss: 1.4252, Accuracy: 1903/5000 (38%)
[epoch 19] loss: 0.8042983
Test set: Average loss: 1.4252, Accuracy: 1902/5000 (38%)
[epoch 20] loss: 0.8075487
Epoch 19: reducing learning rate of group 0 to 5.0000e-07.
Test set: Average loss: 1.4252, Accuracy: 1902/5000 (38%)
[epoch 21] loss: 0.8186505
Epoch 20: reducing learning rate of group 0 to 5.0000e-08.
Test set: Average loss: 1.4252, Accuracy: 1901/5000 (38%)
[epoch 22] loss: 0.8307075
Epoch 21: reducing learning rate of group 0 to 5.0000e-09.
Test set: Average loss: 1.4252, Accuracy: 1901/5000 (38%)
[epoch 23] loss: 0.8205253
Epoch 22: reducing learning rate of group 0 to 5.0000e-10.
Test set: Average loss: 1.4252, Accuracy: 1901/5000 (38%)
[epoch 24] loss: 0.8311288
Epoch 23: reducing learning rate of group 0 to 5.0000e-11.
Test set: Average loss: 1.4252, Accuracy: 1901/5000 (38%)
[epoch 25] loss: 0.8303146
Epoch 24: reducing learning rate of group 0 to 5.0000e-12.
Test set: Average loss: 1.4252, Accuracy: 1901/5000 (38%)
Validation:
Test set: Average loss: 1.4252, Accuracy: 1903/5000 (38%)
Test
Test set: Average loss: 1.4335, Accuracy: 1930/5000 (39%)
Test set: Average loss: 0.8279, Accuracy: 45/50 (90%)
## seed: 12
Validation accuracy before training:
Test set: Average loss: 1.6446, Accuracy: 884/5000 (18%)
[epoch 1] loss: 1.6659222
Test set: Average loss: 1.6024, Accuracy: 1215/5000 (24%)
[epoch 2] loss: 1.5802913
Test set: Average loss: 1.5712, Accuracy: 1521/5000 (30%)
[epoch 3] loss: 1.4433174
Test set: Average loss: 1.5499, Accuracy: 1646/5000 (33%)
[epoch 4] loss: 1.3731436
Test set: Average loss: 1.5354, Accuracy: 1719/5000 (34%)
[epoch 5] loss: 1.3420309
Test set: Average loss: 1.5255, Accuracy: 1770/5000 (35%)
[epoch 6] loss: 1.2716166
Test set: Average loss: 1.5180, Accuracy: 1799/5000 (36%)
[epoch 7] loss: 1.2200587
Test set: Average loss: 1.5124, Accuracy: 1827/5000 (37%)
[epoch 8] loss: 1.2274762
Epoch 7: reducing learning rate of group 0 to 5.0000e-06.
Test set: Average loss: 1.5083, Accuracy: 1852/5000 (37%)
[epoch 9] loss: 1.1598668
Test set: Average loss: 1.5079, Accuracy: 1854/5000 (37%)
[epoch 10] loss: 1.1588120
Test set: Average loss: 1.5075, Accuracy: 1858/5000 (37%)
[epoch 11] loss: 1.1354863
Test set: Average loss: 1.5071, Accuracy: 1860/5000 (37%)
[epoch 12] loss: 1.1683472
Epoch 11: reducing learning rate of group 0 to 5.0000e-07.
Test set: Average loss: 1.5066, Accuracy: 1861/5000 (37%)
[epoch 13] loss: 1.1697410
Epoch 12: reducing learning rate of group 0 to 5.0000e-08.
Test set: Average loss: 1.5066, Accuracy: 1861/5000 (37%)
[epoch 14] loss: 1.1523836
Epoch 13: reducing learning rate of group 0 to 5.0000e-09.
Test set: Average loss: 1.5066, Accuracy: 1861/5000 (37%)
[epoch 15] loss: 1.1491589
Epoch 14: reducing learning rate of group 0 to 5.0000e-10.
Test set: Average loss: 1.5066, Accuracy: 1861/5000 (37%)
[epoch 16] loss: 1.1612384
Epoch 15: reducing learning rate of group 0 to 5.0000e-11.
Test set: Average loss: 1.5066, Accuracy: 1861/5000 (37%)
[epoch 17] loss: 1.1434022
Epoch 16: reducing learning rate of group 0 to 5.0000e-12.
Test set: Average loss: 1.5066, Accuracy: 1861/5000 (37%)
[epoch 18] loss: 1.1728315
Epoch 17: reducing learning rate of group 0 to 5.0000e-13.
Test set: Average loss: 1.5066, Accuracy: 1861/5000 (37%)
[epoch 19] loss: 1.1447875
Epoch 18: reducing learning rate of group 0 to 5.0000e-14.
Test set: Average loss: 1.5066, Accuracy: 1861/5000 (37%)
[epoch 20] loss: 1.1467108
Epoch 19: reducing learning rate of group 0 to 5.0000e-15.
Test set: Average loss: 1.5066, Accuracy: 1861/5000 (37%)
[epoch 21] loss: 1.1767588
Epoch 20: reducing learning rate of group 0 to 5.0000e-16.
Test set: Average loss: 1.5066, Accuracy: 1861/5000 (37%)
[epoch 22] loss: 1.1669543
Epoch 21: reducing learning rate of group 0 to 5.0000e-17.
Test set: Average loss: 1.5066, Accuracy: 1861/5000 (37%)
[epoch 23] loss: 1.1725330
Epoch 22: reducing learning rate of group 0 to 5.0000e-18.
Test set: Average loss: 1.5066, Accuracy: 1861/5000 (37%)
[epoch 24] loss: 1.1556773
Epoch 23: reducing learning rate of group 0 to 5.0000e-19.
Test set: Average loss: 1.5066, Accuracy: 1861/5000 (37%)
[epoch 25] loss: 1.1262386
Test set: Average loss: 1.5066, Accuracy: 1861/5000 (37%)
Validation:
Test set: Average loss: 1.5066, Accuracy: 1861/5000 (37%)
Test
Test set: Average loss: 1.5120, Accuracy: 1843/5000 (37%)
Test set: Average loss: 1.1579, Accuracy: 34/50 (68%)
## seed: 13
Validation accuracy before training:
Test set: Average loss: 1.6459, Accuracy: 912/5000 (18%)
[epoch 1] loss: 1.6380026
Test set: Average loss: 1.5878, Accuracy: 1425/5000 (28%)
[epoch 2] loss: 1.5337726
Test set: Average loss: 1.5450, Accuracy: 1765/5000 (35%)
[epoch 3] loss: 1.4207811
Test set: Average loss: 1.5134, Accuracy: 1884/5000 (38%)
[epoch 4] loss: 1.3578823
Test set: Average loss: 1.4872, Accuracy: 1944/5000 (39%)
[epoch 5] loss: 1.3038372
Test set: Average loss: 1.4666, Accuracy: 1983/5000 (40%)
[epoch 6] loss: 1.2615991
Test set: Average loss: 1.4496, Accuracy: 1997/5000 (40%)
[epoch 7] loss: 1.2124362
Test set: Average loss: 1.4362, Accuracy: 2030/5000 (41%)
[epoch 8] loss: 1.1669207
Test set: Average loss: 1.4248, Accuracy: 2055/5000 (41%)
[epoch 9] loss: 1.1647376
Test set: Average loss: 1.4149, Accuracy: 2080/5000 (42%)
[epoch 10] loss: 1.1007268
Test set: Average loss: 1.4064, Accuracy: 2111/5000 (42%)
[epoch 11] loss: 1.0846180
Test set: Average loss: 1.3994, Accuracy: 2130/5000 (43%)
[epoch 12] loss: 1.0558830
Test set: Average loss: 1.3934, Accuracy: 2149/5000 (43%)
[epoch 13] loss: 1.0350015
Test set: Average loss: 1.3878, Accuracy: 2163/5000 (43%)
[epoch 14] loss: 1.0139821
Test set: Average loss: 1.3823, Accuracy: 2184/5000 (44%)
[epoch 15] loss: 0.9800670
Test set: Average loss: 1.3775, Accuracy: 2205/5000 (44%)
[epoch 16] loss: 0.9725971
Test set: Average loss: 1.3733, Accuracy: 2214/5000 (44%)
[epoch 17] loss: 0.9616703
Test set: Average loss: 1.3692, Accuracy: 2224/5000 (44%)
[epoch 18] loss: 0.9170679
Test set: Average loss: 1.3657, Accuracy: 2240/5000 (45%)
[epoch 19] loss: 0.9175113
Epoch 18: reducing learning rate of group 0 to 5.0000e-06.
Test set: Average loss: 1.3624, Accuracy: 2252/5000 (45%)
[epoch 20] loss: 0.9043649
Test set: Average loss: 1.3621, Accuracy: 2251/5000 (45%)
[epoch 21] loss: 0.8940055
Test set: Average loss: 1.3618, Accuracy: 2247/5000 (45%)
[epoch 22] loss: 0.8835341
Test set: Average loss: 1.3615, Accuracy: 2252/5000 (45%)
[epoch 23] loss: 0.9082312
Epoch 22: reducing learning rate of group 0 to 5.0000e-07.
Test set: Average loss: 1.3612, Accuracy: 2259/5000 (45%)
[epoch 24] loss: 0.9117727
Epoch 23: reducing learning rate of group 0 to 5.0000e-08.
Test set: Average loss: 1.3611, Accuracy: 2259/5000 (45%)
[epoch 25] loss: 0.9000694
Epoch 24: reducing learning rate of group 0 to 5.0000e-09.
Test set: Average loss: 1.3611, Accuracy: 2259/5000 (45%)
Validation:
Test set: Average loss: 1.3611, Accuracy: 2259/5000 (45%)
Test
Test set: Average loss: 1.3736, Accuracy: 2183/5000 (44%)
Test set: Average loss: 0.8937, Accuracy: 43/50 (86%)
100
## seed: 11
Validation accuracy before training:
Test set: Average loss: 1.6120, Accuracy: 947/5000 (19%)
[epoch 1] loss: 1.6387306
Test set: Average loss: 1.5476, Accuracy: 1500/5000 (30%)
[epoch 2] loss: 1.4942034
Test set: Average loss: 1.5111, Accuracy: 1559/5000 (31%)
[epoch 3] loss: 1.4239208
Test set: Average loss: 1.4871, Accuracy: 1627/5000 (33%)
[epoch 4] loss: 1.3280252
Test set: Average loss: 1.4691, Accuracy: 1679/5000 (34%)
[epoch 5] loss: 1.2835650
Test set: Average loss: 1.4555, Accuracy: 1741/5000 (35%)
[epoch 6] loss: 1.2661514
Test set: Average loss: 1.4410, Accuracy: 1799/5000 (36%)
[epoch 7] loss: 1.2017828
Test set: Average loss: 1.4288, Accuracy: 1822/5000 (36%)
[epoch 8] loss: 1.1885149
Test set: Average loss: 1.4201, Accuracy: 1845/5000 (37%)
[epoch 9] loss: 1.1849679
Test set: Average loss: 1.4101, Accuracy: 1879/5000 (38%)
[epoch 10] loss: 1.1114257
Test set: Average loss: 1.4002, Accuracy: 1927/5000 (39%)
[epoch 11] loss: 1.1088152
Test set: Average loss: 1.3932, Accuracy: 1964/5000 (39%)
[epoch 12] loss: 1.0663403
Test set: Average loss: 1.3819, Accuracy: 2069/5000 (41%)
[epoch 13] loss: 1.0610526
Test set: Average loss: 1.3749, Accuracy: 2109/5000 (42%)
[epoch 14] loss: 0.9761462
Test set: Average loss: 1.3706, Accuracy: 2150/5000 (43%)
[epoch 15] loss: 0.9731187
Test set: Average loss: 1.3658, Accuracy: 2184/5000 (44%)
[epoch 16] loss: 0.9870557
Epoch 15: reducing learning rate of group 0 to 5.0000e-06.
Test set: Average loss: 1.3610, Accuracy: 2205/5000 (44%)
[epoch 17] loss: 0.9972160
Epoch 16: reducing learning rate of group 0 to 5.0000e-07.
Test set: Average loss: 1.3608, Accuracy: 2204/5000 (44%)
[epoch 18] loss: 1.0244927
Epoch 17: reducing learning rate of group 0 to 5.0000e-08.
Test set: Average loss: 1.3607, Accuracy: 2203/5000 (44%)
[epoch 19] loss: 1.0570348
Epoch 18: reducing learning rate of group 0 to 5.0000e-09.
Test set: Average loss: 1.3607, Accuracy: 2203/5000 (44%)
[epoch 20] loss: 0.9795914
Epoch 19: reducing learning rate of group 0 to 5.0000e-10.
Test set: Average loss: 1.3607, Accuracy: 2203/5000 (44%)
[epoch 21] loss: 0.9267879
Test set: Average loss: 1.3607, Accuracy: 2203/5000 (44%)
[epoch 22] loss: 0.9729076
Epoch 21: reducing learning rate of group 0 to 5.0000e-11.
Test set: Average loss: 1.3607, Accuracy: 2203/5000 (44%)
[epoch 23] loss: 0.9250403
Test set: Average loss: 1.3607, Accuracy: 2203/5000 (44%)
[epoch 24] loss: 0.9255576
Epoch 23: reducing learning rate of group 0 to 5.0000e-12.
Test set: Average loss: 1.3607, Accuracy: 2203/5000 (44%)
[epoch 25] loss: 0.9385718
Epoch 24: reducing learning rate of group 0 to 5.0000e-13.
Test set: Average loss: 1.3607, Accuracy: 2203/5000 (44%)
Validation:
Test set: Average loss: 1.3610, Accuracy: 2205/5000 (44%)
Test
Test set: Average loss: 1.3735, Accuracy: 2147/5000 (43%)
Test set: Average loss: 0.9602, Accuracy: 86/100 (86%)
## seed: 12
Validation accuracy before training:
Test set: Average loss: 1.6227, Accuracy: 950/5000 (19%)
[epoch 1] loss: 1.6268596
Test set: Average loss: 1.5602, Accuracy: 1539/5000 (31%)
[epoch 2] loss: 1.4749154
Test set: Average loss: 1.5218, Accuracy: 1822/5000 (36%)
[epoch 3] loss: 1.3382522
Test set: Average loss: 1.4964, Accuracy: 1939/5000 (39%)
[epoch 4] loss: 1.3281118
Test set: Average loss: 1.4790, Accuracy: 1983/5000 (40%)
[epoch 5] loss: 1.3228425
Test set: Average loss: 1.4687, Accuracy: 1996/5000 (40%)
[epoch 6] loss: 1.2261851
Test set: Average loss: 1.4620, Accuracy: 2012/5000 (40%)
[epoch 7] loss: 1.1944214
Test set: Average loss: 1.4564, Accuracy: 2039/5000 (41%)
[epoch 8] loss: 1.1987806
Epoch 7: reducing learning rate of group 0 to 5.0000e-06.
Test set: Average loss: 1.4504, Accuracy: 2059/5000 (41%)
[epoch 9] loss: 1.1620832
Test set: Average loss: 1.4500, Accuracy: 2059/5000 (41%)
[epoch 10] loss: 1.1151844
Test set: Average loss: 1.4494, Accuracy: 2062/5000 (41%)
[epoch 11] loss: 1.1170120
Epoch 10: reducing learning rate of group 0 to 5.0000e-07.
Test set: Average loss: 1.4486, Accuracy: 2067/5000 (41%)
[epoch 12] loss: 1.1691719
Epoch 11: reducing learning rate of group 0 to 5.0000e-08.
Test set: Average loss: 1.4486, Accuracy: 2068/5000 (41%)
[epoch 13] loss: 1.1368267
Epoch 12: reducing learning rate of group 0 to 5.0000e-09.
Test set: Average loss: 1.4486, Accuracy: 2068/5000 (41%)
[epoch 14] loss: 1.1145408
Test set: Average loss: 1.4486, Accuracy: 2068/5000 (41%)
[epoch 15] loss: 1.1395492
Epoch 14: reducing learning rate of group 0 to 5.0000e-10.
Test set: Average loss: 1.4486, Accuracy: 2068/5000 (41%)
[epoch 16] loss: 1.1157406
Epoch 15: reducing learning rate of group 0 to 5.0000e-11.
Test set: Average loss: 1.4486, Accuracy: 2068/5000 (41%)
[epoch 17] loss: 1.1520917
Epoch 16: reducing learning rate of group 0 to 5.0000e-12.
Test set: Average loss: 1.4486, Accuracy: 2068/5000 (41%)
[epoch 18] loss: 1.1865352
Epoch 17: reducing learning rate of group 0 to 5.0000e-13.
Test set: Average loss: 1.4486, Accuracy: 2068/5000 (41%)
[epoch 19] loss: 1.1492510
Epoch 18: reducing learning rate of group 0 to 5.0000e-14.
Test set: Average loss: 1.4486, Accuracy: 2068/5000 (41%)
[epoch 20] loss: 1.1581230
Epoch 19: reducing learning rate of group 0 to 5.0000e-15.
Test set: Average loss: 1.4486, Accuracy: 2068/5000 (41%)
[epoch 21] loss: 1.1149082
Epoch 20: reducing learning rate of group 0 to 5.0000e-16.
Test set: Average loss: 1.4486, Accuracy: 2068/5000 (41%)
[epoch 22] loss: 1.1318890
Epoch 21: reducing learning rate of group 0 to 5.0000e-17.
Test set: Average loss: 1.4486, Accuracy: 2068/5000 (41%)
[epoch 23] loss: 1.1243130
Epoch 22: reducing learning rate of group 0 to 5.0000e-18.
Test set: Average loss: 1.4486, Accuracy: 2068/5000 (41%)
[epoch 24] loss: 1.1180725
Epoch 23: reducing learning rate of group 0 to 5.0000e-19.
Test set: Average loss: 1.4486, Accuracy: 2068/5000 (41%)
[epoch 25] loss: 1.1773598
Epoch 24: reducing learning rate of group 0 to 5.0000e-20.
Test set: Average loss: 1.4486, Accuracy: 2068/5000 (41%)
Validation:
Test set: Average loss: 1.4486, Accuracy: 2068/5000 (41%)
Test
Test set: Average loss: 1.4505, Accuracy: 2011/5000 (40%)
Test set: Average loss: 1.1442, Accuracy: 71/100 (71%)
## seed: 13
Validation accuracy before training:
Test set: Average loss: 1.6117, Accuracy: 1056/5000 (21%)
[epoch 1] loss: 1.6050397
Test set: Average loss: 1.5336, Accuracy: 1697/5000 (34%)
[epoch 2] loss: 1.4629723
Test set: Average loss: 1.4884, Accuracy: 1950/5000 (39%)
[epoch 3] loss: 1.3944776
Test set: Average loss: 1.4563, Accuracy: 2054/5000 (41%)
[epoch 4] loss: 1.3291361
Test set: Average loss: 1.4366, Accuracy: 2138/5000 (43%)
[epoch 5] loss: 1.2227042
Test set: Average loss: 1.4239, Accuracy: 2192/5000 (44%)
[epoch 6] loss: 1.2118002
Test set: Average loss: 1.4108, Accuracy: 2231/5000 (45%)
[epoch 7] loss: 1.2259256
Epoch 6: reducing learning rate of group 0 to 5.0000e-06.
Test set: Average loss: 1.3993, Accuracy: 2266/5000 (45%)
[epoch 8] loss: 1.2245359
Epoch 7: reducing learning rate of group 0 to 5.0000e-07.
Test set: Average loss: 1.3982, Accuracy: 2273/5000 (45%)
[epoch 9] loss: 1.1497771
Test set: Average loss: 1.3981, Accuracy: 2274/5000 (45%)
[epoch 10] loss: 1.1806574
Epoch 9: reducing learning rate of group 0 to 5.0000e-08.
Test set: Average loss: 1.3980, Accuracy: 2274/5000 (45%)
[epoch 11] loss: 1.2612261
Epoch 10: reducing learning rate of group 0 to 5.0000e-09.
Test set: Average loss: 1.3980, Accuracy: 2274/5000 (45%)
[epoch 12] loss: 1.0899896
Test set: Average loss: 1.3980, Accuracy: 2274/5000 (45%)
[epoch 13] loss: 1.1517724
Epoch 12: reducing learning rate of group 0 to 5.0000e-10.
Test set: Average loss: 1.3980, Accuracy: 2274/5000 (45%)
[epoch 14] loss: 1.1818117
Epoch 13: reducing learning rate of group 0 to 5.0000e-11.
Test set: Average loss: 1.3980, Accuracy: 2274/5000 (45%)
[epoch 15] loss: 1.1628439
Epoch 14: reducing learning rate of group 0 to 5.0000e-12.
Test set: Average loss: 1.3980, Accuracy: 2274/5000 (45%)
[epoch 16] loss: 1.2106155
Epoch 15: reducing learning rate of group 0 to 5.0000e-13.
Test set: Average loss: 1.3980, Accuracy: 2274/5000 (45%)
[epoch 17] loss: 1.1380984
Epoch 16: reducing learning rate of group 0 to 5.0000e-14.
Test set: Average loss: 1.3980, Accuracy: 2274/5000 (45%)
[epoch 18] loss: 1.1396783
Epoch 17: reducing learning rate of group 0 to 5.0000e-15.
Test set: Average loss: 1.3980, Accuracy: 2274/5000 (45%)
[epoch 19] loss: 1.1411664
Epoch 18: reducing learning rate of group 0 to 5.0000e-16.
Test set: Average loss: 1.3980, Accuracy: 2274/5000 (45%)
[epoch 20] loss: 1.2156292
Epoch 19: reducing learning rate of group 0 to 5.0000e-17.
Test set: Average loss: 1.3980, Accuracy: 2274/5000 (45%)
[epoch 21] loss: 1.1272731
Epoch 20: reducing learning rate of group 0 to 5.0000e-18.
Test set: Average loss: 1.3980, Accuracy: 2274/5000 (45%)
[epoch 22] loss: 1.1425960
Epoch 21: reducing learning rate of group 0 to 5.0000e-19.
Test set: Average loss: 1.3980, Accuracy: 2274/5000 (45%)
[epoch 23] loss: 1.1352541
Epoch 22: reducing learning rate of group 0 to 5.0000e-20.
Test set: Average loss: 1.3980, Accuracy: 2274/5000 (45%)
[epoch 24] loss: 1.1439047
Epoch 23: reducing learning rate of group 0 to 5.0000e-21.
Test set: Average loss: 1.3980, Accuracy: 2274/5000 (45%)
[epoch 25] loss: 1.1590315
Epoch 24: reducing learning rate of group 0 to 5.0000e-22.
Test set: Average loss: 1.3980, Accuracy: 2274/5000 (45%)
Validation:
Test set: Average loss: 1.3980, Accuracy: 2274/5000 (45%)
Test
Test set: Average loss: 1.4072, Accuracy: 2275/5000 (46%)
Test set: Average loss: 1.1659, Accuracy: 61/100 (61%)
250
## seed: 11
Validation accuracy before training:
Test set: Average loss: 1.6464, Accuracy: 1053/5000 (21%)
[epoch 1] loss: 1.6047772
Test set: Average loss: 1.4965, Accuracy: 1928/5000 (39%)
[epoch 2] loss: 1.4357052
Test set: Average loss: 1.4252, Accuracy: 2145/5000 (43%)
[epoch 3] loss: 1.3540891
Test set: Average loss: 1.3862, Accuracy: 2253/5000 (45%)
[epoch 4] loss: 1.2870409
Test set: Average loss: 1.3612, Accuracy: 2325/5000 (46%)
[epoch 5] loss: 1.2365799
Test set: Average loss: 1.3427, Accuracy: 2406/5000 (48%)
[epoch 6] loss: 1.1923542
Test set: Average loss: 1.3279, Accuracy: 2474/5000 (49%)
[epoch 7] loss: 1.1503570
Test set: Average loss: 1.3154, Accuracy: 2499/5000 (50%)
[epoch 8] loss: 1.1227833
Test set: Average loss: 1.3054, Accuracy: 2521/5000 (50%)
[epoch 9] loss: 1.0869998
Test set: Average loss: 1.3026, Accuracy: 2500/5000 (50%)
[epoch 10] loss: 1.0571408
Test set: Average loss: 1.2959, Accuracy: 2557/5000 (51%)
[epoch 11] loss: 1.0312234
Test set: Average loss: 1.2903, Accuracy: 2562/5000 (51%)
[epoch 12] loss: 1.0056532
Test set: Average loss: 1.2864, Accuracy: 2550/5000 (51%)
[epoch 13] loss: 0.9814039
Test set: Average loss: 1.2789, Accuracy: 2588/5000 (52%)
[epoch 14] loss: 0.9576718
Test set: Average loss: 1.2785, Accuracy: 2552/5000 (51%)
[epoch 15] loss: 0.9327837
Test set: Average loss: 1.2742, Accuracy: 2563/5000 (51%)
[epoch 16] loss: 0.9135385
Test set: Average loss: 1.2719, Accuracy: 2576/5000 (52%)
[epoch 17] loss: 0.8922074
Test set: Average loss: 1.2683, Accuracy: 2584/5000 (52%)
[epoch 18] loss: 0.8761485
Test set: Average loss: 1.2687, Accuracy: 2562/5000 (51%)
[epoch 19] loss: 0.8532996
Test set: Average loss: 1.2658, Accuracy: 2580/5000 (52%)
[epoch 20] loss: 0.8376150
Test set: Average loss: 1.2628, Accuracy: 2556/5000 (51%)
[epoch 21] loss: 0.8183778
Test set: Average loss: 1.2592, Accuracy: 2592/5000 (52%)
[epoch 22] loss: 0.8004547
Test set: Average loss: 1.2612, Accuracy: 2583/5000 (52%)
[epoch 23] loss: 0.7810344
Test set: Average loss: 1.2598, Accuracy: 2572/5000 (51%)
[epoch 24] loss: 0.7644511
Test set: Average loss: 1.2562, Accuracy: 2590/5000 (52%)
[epoch 25] loss: 0.7483186
Test set: Average loss: 1.2570, Accuracy: 2588/5000 (52%)
Validation:
Test set: Average loss: 1.2592, Accuracy: 2592/5000 (52%)
Test
Test set: Average loss: 1.2685, Accuracy: 2532/5000 (51%)
Test set: Average loss: 0.8035, Accuracy: 214/250 (86%)
## seed: 12
Validation accuracy before training:
Test set: Average loss: 1.6399, Accuracy: 888/5000 (18%)
[epoch 1] loss: 1.5984462
Test set: Average loss: 1.5088, Accuracy: 1882/5000 (38%)
[epoch 2] loss: 1.4616641
Test set: Average loss: 1.4486, Accuracy: 2103/5000 (42%)
[epoch 3] loss: 1.3867145
Test set: Average loss: 1.4091, Accuracy: 2288/5000 (46%)
[epoch 4] loss: 1.3249114
Test set: Average loss: 1.3824, Accuracy: 2375/5000 (48%)
[epoch 5] loss: 1.2710047
Test set: Average loss: 1.3657, Accuracy: 2439/5000 (49%)
[epoch 6] loss: 1.2292648
Test set: Average loss: 1.3543, Accuracy: 2481/5000 (50%)
[epoch 7] loss: 1.1904760
Test set: Average loss: 1.3445, Accuracy: 2501/5000 (50%)
[epoch 8] loss: 1.1551440
Test set: Average loss: 1.3365, Accuracy: 2524/5000 (50%)
[epoch 9] loss: 1.1225501
Test set: Average loss: 1.3238, Accuracy: 2518/5000 (50%)
[epoch 10] loss: 1.0928717
Test set: Average loss: 1.3156, Accuracy: 2538/5000 (51%)
[epoch 11] loss: 1.0699988
Test set: Average loss: 1.3126, Accuracy: 2549/5000 (51%)
[epoch 12] loss: 1.0405770
Test set: Average loss: 1.3068, Accuracy: 2560/5000 (51%)
[epoch 13] loss: 1.0147501
Test set: Average loss: 1.3005, Accuracy: 2569/5000 (51%)
[epoch 14] loss: 0.9924606
Test set: Average loss: 1.2961, Accuracy: 2556/5000 (51%)
[epoch 15] loss: 0.9714189
Test set: Average loss: 1.2928, Accuracy: 2558/5000 (51%)
[epoch 16] loss: 0.9491566
Test set: Average loss: 1.2879, Accuracy: 2561/5000 (51%)
[epoch 17] loss: 0.9272027
Test set: Average loss: 1.2844, Accuracy: 2578/5000 (52%)
[epoch 18] loss: 0.9063585
Test set: Average loss: 1.2826, Accuracy: 2554/5000 (51%)
[epoch 19] loss: 0.8870306
Test set: Average loss: 1.2755, Accuracy: 2573/5000 (51%)
[epoch 20] loss: 0.8680385
Test set: Average loss: 1.2747, Accuracy: 2571/5000 (51%)
[epoch 21] loss: 0.8477765
Test set: Average loss: 1.2722, Accuracy: 2573/5000 (51%)
[epoch 22] loss: 0.8285829
Test set: Average loss: 1.2697, Accuracy: 2573/5000 (51%)
[epoch 23] loss: 0.8115456
Test set: Average loss: 1.2669, Accuracy: 2581/5000 (52%)
[epoch 24] loss: 0.7968461
Test set: Average loss: 1.2660, Accuracy: 2573/5000 (51%)
[epoch 25] loss: 0.7770647
Test set: Average loss: 1.2681, Accuracy: 2556/5000 (51%)
Validation:
Test set: Average loss: 1.2669, Accuracy: 2581/5000 (52%)
Test
Test set: Average loss: 1.2667, Accuracy: 2613/5000 (52%)
Test set: Average loss: 0.7988, Accuracy: 222/250 (89%)
## seed: 13
Validation accuracy before training:
Test set: Average loss: 1.6722, Accuracy: 504/5000 (10%)
[epoch 1] loss: 1.5751800
Test set: Average loss: 1.5020, Accuracy: 1735/5000 (35%)
[epoch 2] loss: 1.4092125
Test set: Average loss: 1.4313, Accuracy: 1930/5000 (39%)
[epoch 3] loss: 1.3160550
Test set: Average loss: 1.3910, Accuracy: 2060/5000 (41%)
[epoch 4] loss: 1.2517264
Test set: Average loss: 1.3643, Accuracy: 2254/5000 (45%)
[epoch 5] loss: 1.2027007
Test set: Average loss: 1.3450, Accuracy: 2345/5000 (47%)
[epoch 6] loss: 1.1603773
Test set: Average loss: 1.3310, Accuracy: 2428/5000 (49%)
[epoch 7] loss: 1.1273355
Test set: Average loss: 1.3196, Accuracy: 2443/5000 (49%)
[epoch 8] loss: 1.0935899
Test set: Average loss: 1.3124, Accuracy: 2477/5000 (50%)
[epoch 9] loss: 1.0650875
Test set: Average loss: 1.3037, Accuracy: 2484/5000 (50%)
[epoch 10] loss: 1.0332784
Test set: Average loss: 1.2961, Accuracy: 2496/5000 (50%)
[epoch 11] loss: 1.0109206
Test set: Average loss: 1.2902, Accuracy: 2508/5000 (50%)
[epoch 12] loss: 0.9897072
Test set: Average loss: 1.2869, Accuracy: 2515/5000 (50%)
[epoch 13] loss: 0.9648547
Test set: Average loss: 1.2791, Accuracy: 2550/5000 (51%)
[epoch 14] loss: 0.9473313
Test set: Average loss: 1.2758, Accuracy: 2550/5000 (51%)
[epoch 15] loss: 0.9242977
Test set: Average loss: 1.2770, Accuracy: 2547/5000 (51%)
[epoch 16] loss: 0.9078462
Test set: Average loss: 1.2748, Accuracy: 2544/5000 (51%)
[epoch 17] loss: 0.8894319
Test set: Average loss: 1.2706, Accuracy: 2564/5000 (51%)
[epoch 18] loss: 0.8720867
Test set: Average loss: 1.2678, Accuracy: 2577/5000 (52%)
[epoch 19] loss: 0.8493742
Test set: Average loss: 1.2664, Accuracy: 2577/5000 (52%)
[epoch 20] loss: 0.8344448
Test set: Average loss: 1.2633, Accuracy: 2577/5000 (52%)
[epoch 21] loss: 0.8178158
Test set: Average loss: 1.2614, Accuracy: 2586/5000 (52%)
[epoch 22] loss: 0.8010274
Test set: Average loss: 1.2632, Accuracy: 2595/5000 (52%)
[epoch 23] loss: 0.7877586
Test set: Average loss: 1.2611, Accuracy: 2586/5000 (52%)
[epoch 24] loss: 0.7696192
Test set: Average loss: 1.2613, Accuracy: 2592/5000 (52%)
[epoch 25] loss: 0.7556724
Test set: Average loss: 1.2600, Accuracy: 2589/5000 (52%)
Validation:
Test set: Average loss: 1.2632, Accuracy: 2595/5000 (52%)
Test
Test set: Average loss: 1.2756, Accuracy: 2581/5000 (52%)
Test set: Average loss: 0.7895, Accuracy: 227/250 (91%)
500
## seed: 11
Validation accuracy before training:
Test set: Average loss: 1.6136, Accuracy: 952/5000 (19%)
[epoch 1] loss: 1.4965698
Test set: Average loss: 1.3996, Accuracy: 2221/5000 (44%)
[epoch 2] loss: 1.3359981
Test set: Average loss: 1.3418, Accuracy: 2349/5000 (47%)
[epoch 3] loss: 1.2548407
Test set: Average loss: 1.3092, Accuracy: 2493/5000 (50%)
[epoch 4] loss: 1.1975501
Test set: Average loss: 1.2846, Accuracy: 2582/5000 (52%)
[epoch 5] loss: 1.1495383
Test set: Average loss: 1.2657, Accuracy: 2624/5000 (52%)
[epoch 6] loss: 1.1084759
Test set: Average loss: 1.2529, Accuracy: 2681/5000 (54%)
[epoch 7] loss: 1.0790430
Test set: Average loss: 1.2411, Accuracy: 2693/5000 (54%)
[epoch 8] loss: 1.0565458
Test set: Average loss: 1.2318, Accuracy: 2724/5000 (54%)
[epoch 9] loss: 1.0174994
Test set: Average loss: 1.2294, Accuracy: 2688/5000 (54%)
[epoch 10] loss: 0.9959709
Test set: Average loss: 1.2155, Accuracy: 2723/5000 (54%)
[epoch 11] loss: 0.9690656
Test set: Average loss: 1.2118, Accuracy: 2730/5000 (55%)
[epoch 12] loss: 0.9490018
Test set: Average loss: 1.2047, Accuracy: 2732/5000 (55%)
[epoch 13] loss: 0.9252376
Test set: Average loss: 1.2000, Accuracy: 2727/5000 (55%)
[epoch 14] loss: 0.9034670
Test set: Average loss: 1.1997, Accuracy: 2725/5000 (54%)
[epoch 15] loss: 0.8828435
Test set: Average loss: 1.1934, Accuracy: 2751/5000 (55%)
[epoch 16] loss: 0.8692458
Test set: Average loss: 1.1900, Accuracy: 2740/5000 (55%)
[epoch 17] loss: 0.8442358
Test set: Average loss: 1.1910, Accuracy: 2740/5000 (55%)
[epoch 18] loss: 0.8248258
Test set: Average loss: 1.1844, Accuracy: 2736/5000 (55%)
[epoch 19] loss: 0.8051196
Test set: Average loss: 1.1840, Accuracy: 2771/5000 (55%)
[epoch 20] loss: 0.7883814
Test set: Average loss: 1.1798, Accuracy: 2753/5000 (55%)
[epoch 21] loss: 0.7717423
Test set: Average loss: 1.1819, Accuracy: 2737/5000 (55%)
[epoch 22] loss: 0.7536591
Test set: Average loss: 1.1798, Accuracy: 2742/5000 (55%)
[epoch 23] loss: 0.7384058
Test set: Average loss: 1.1796, Accuracy: 2725/5000 (54%)
[epoch 24] loss: 0.7165014
Test set: Average loss: 1.1741, Accuracy: 2736/5000 (55%)
[epoch 25] loss: 0.7004194
Test set: Average loss: 1.1780, Accuracy: 2731/5000 (55%)
Validation:
Test set: Average loss: 1.1840, Accuracy: 2771/5000 (55%)
Test
Test set: Average loss: 1.1910, Accuracy: 2740/5000 (55%)
Test set: Average loss: 0.7860, Accuracy: 416/500 (83%)
## seed: 12
Validation accuracy before training:
Test set: Average loss: 1.6112, Accuracy: 1145/5000 (23%)
[epoch 1] loss: 1.5003983
Test set: Average loss: 1.3857, Accuracy: 2289/5000 (46%)
[epoch 2] loss: 1.3267462
Test set: Average loss: 1.3174, Accuracy: 2422/5000 (48%)
[epoch 3] loss: 1.2464443
Test set: Average loss: 1.2796, Accuracy: 2567/5000 (51%)
[epoch 4] loss: 1.1958509
Test set: Average loss: 1.2555, Accuracy: 2666/5000 (53%)
[epoch 5] loss: 1.1529684
Test set: Average loss: 1.2390, Accuracy: 2713/5000 (54%)
[epoch 6] loss: 1.1104323
Test set: Average loss: 1.2242, Accuracy: 2736/5000 (55%)
[epoch 7] loss: 1.0796195
Test set: Average loss: 1.2109, Accuracy: 2752/5000 (55%)
[epoch 8] loss: 1.0473175
Test set: Average loss: 1.2017, Accuracy: 2766/5000 (55%)
[epoch 9] loss: 1.0223291
Test set: Average loss: 1.1985, Accuracy: 2780/5000 (56%)
[epoch 10] loss: 0.9958621
Test set: Average loss: 1.1869, Accuracy: 2798/5000 (56%)
[epoch 11] loss: 0.9696733
Test set: Average loss: 1.1822, Accuracy: 2792/5000 (56%)
[epoch 12] loss: 0.9501407
Test set: Average loss: 1.1751, Accuracy: 2826/5000 (57%)
[epoch 13] loss: 0.9268085
Test set: Average loss: 1.1714, Accuracy: 2804/5000 (56%)
[epoch 14] loss: 0.9023103
Test set: Average loss: 1.1683, Accuracy: 2814/5000 (56%)
[epoch 15] loss: 0.8826878
Test set: Average loss: 1.1612, Accuracy: 2820/5000 (56%)
[epoch 16] loss: 0.8632778
Test set: Average loss: 1.1592, Accuracy: 2833/5000 (57%)
[epoch 17] loss: 0.8422253
Test set: Average loss: 1.1574, Accuracy: 2808/5000 (56%)
[epoch 18] loss: 0.8200783
Test set: Average loss: 1.1528, Accuracy: 2836/5000 (57%)
[epoch 19] loss: 0.8072964
Test set: Average loss: 1.1536, Accuracy: 2813/5000 (56%)
[epoch 20] loss: 0.7904415
Test set: Average loss: 1.1494, Accuracy: 2816/5000 (56%)
[epoch 21] loss: 0.7671453
Test set: Average loss: 1.1463, Accuracy: 2824/5000 (56%)
[epoch 22] loss: 0.7593878
Test set: Average loss: 1.1440, Accuracy: 2816/5000 (56%)
[epoch 23] loss: 0.7349589
Test set: Average loss: 1.1434, Accuracy: 2821/5000 (56%)
[epoch 24] loss: 0.7196720
Test set: Average loss: 1.1381, Accuracy: 2848/5000 (57%)
[epoch 25] loss: 0.7032311
Test set: Average loss: 1.1457, Accuracy: 2801/5000 (56%)
Validation:
Test set: Average loss: 1.1381, Accuracy: 2848/5000 (57%)
Test
Test set: Average loss: 1.1509, Accuracy: 2780/5000 (56%)
Test set: Average loss: 0.6991, Accuracy: 435/500 (87%)
## seed: 13
Validation accuracy before training:
Test set: Average loss: 1.6140, Accuracy: 937/5000 (19%)
[epoch 1] loss: 1.4999698
Test set: Average loss: 1.4241, Accuracy: 2092/5000 (42%)
[epoch 2] loss: 1.3329145
Test set: Average loss: 1.3650, Accuracy: 2303/5000 (46%)
[epoch 3] loss: 1.2657546
Test set: Average loss: 1.3308, Accuracy: 2438/5000 (49%)
[epoch 4] loss: 1.2062469
Test set: Average loss: 1.3090, Accuracy: 2498/5000 (50%)
[epoch 5] loss: 1.1581044
Test set: Average loss: 1.2837, Accuracy: 2584/5000 (52%)
[epoch 6] loss: 1.1181898
Test set: Average loss: 1.2716, Accuracy: 2579/5000 (52%)
[epoch 7] loss: 1.0869356
Test set: Average loss: 1.2583, Accuracy: 2614/5000 (52%)
[epoch 8] loss: 1.0512108
Test set: Average loss: 1.2488, Accuracy: 2622/5000 (52%)
[epoch 9] loss: 1.0285561
Test set: Average loss: 1.2400, Accuracy: 2634/5000 (53%)
[epoch 10] loss: 0.9998483
Test set: Average loss: 1.2300, Accuracy: 2663/5000 (53%)
[epoch 11] loss: 0.9796842
Test set: Average loss: 1.2236, Accuracy: 2682/5000 (54%)
[epoch 12] loss: 0.9537850
Test set: Average loss: 1.2131, Accuracy: 2714/5000 (54%)
[epoch 13] loss: 0.9244506
Test set: Average loss: 1.2105, Accuracy: 2714/5000 (54%)
[epoch 14] loss: 0.9004513
Test set: Average loss: 1.2026, Accuracy: 2734/5000 (55%)
[epoch 15] loss: 0.8828555
Test set: Average loss: 1.2013, Accuracy: 2736/5000 (55%)
[epoch 16] loss: 0.8608836
Test set: Average loss: 1.1969, Accuracy: 2724/5000 (54%)
[epoch 17] loss: 0.8440499
Test set: Average loss: 1.1888, Accuracy: 2754/5000 (55%)
[epoch 18] loss: 0.8195074
Test set: Average loss: 1.1862, Accuracy: 2752/5000 (55%)
[epoch 19] loss: 0.7998237
Test set: Average loss: 1.1874, Accuracy: 2739/5000 (55%)
[epoch 20] loss: 0.7843983
Test set: Average loss: 1.1838, Accuracy: 2731/5000 (55%)
[epoch 21] loss: 0.7634175
Test set: Average loss: 1.1799, Accuracy: 2753/5000 (55%)
[epoch 22] loss: 0.7450848
Test set: Average loss: 1.1780, Accuracy: 2754/5000 (55%)
[epoch 23] loss: 0.7282601
Test set: Average loss: 1.1763, Accuracy: 2743/5000 (55%)
[epoch 24] loss: 0.7124340
Test set: Average loss: 1.1751, Accuracy: 2758/5000 (55%)
[epoch 25] loss: 0.6922293
Test set: Average loss: 1.1711, Accuracy: 2765/5000 (55%)
Validation:
Test set: Average loss: 1.1711, Accuracy: 2765/5000 (55%)
Test
Test set: Average loss: 1.1841, Accuracy: 2733/5000 (55%)
Test set: Average loss: 0.6777, Accuracy: 451/500 (90%)
750
## seed: 11
Validation accuracy before training:
Test set: Average loss: 1.6024, Accuracy: 1223/5000 (24%)
[epoch 1] loss: 1.4460218
Test set: Average loss: 1.3578, Accuracy: 2318/5000 (46%)
[epoch 2] loss: 1.2763535
Test set: Average loss: 1.2959, Accuracy: 2484/5000 (50%)
[epoch 3] loss: 1.2089892
Test set: Average loss: 1.2614, Accuracy: 2608/5000 (52%)
[epoch 4] loss: 1.1460310
Test set: Average loss: 1.2385, Accuracy: 2694/5000 (54%)
[epoch 5] loss: 1.1083825
Test set: Average loss: 1.2262, Accuracy: 2688/5000 (54%)
[epoch 6] loss: 1.0726889
Test set: Average loss: 1.2108, Accuracy: 2722/5000 (54%)
[epoch 7] loss: 1.0437465
Test set: Average loss: 1.1997, Accuracy: 2753/5000 (55%)
[epoch 8] loss: 1.0109468
Test set: Average loss: 1.1900, Accuracy: 2774/5000 (55%)
[epoch 9] loss: 0.9899182
Test set: Average loss: 1.1829, Accuracy: 2778/5000 (56%)
[epoch 10] loss: 0.9559642
Test set: Average loss: 1.1742, Accuracy: 2793/5000 (56%)
[epoch 11] loss: 0.9386286
Test set: Average loss: 1.1699, Accuracy: 2792/5000 (56%)
[epoch 12] loss: 0.9153944
Test set: Average loss: 1.1627, Accuracy: 2815/5000 (56%)
[epoch 13] loss: 0.8899420
Test set: Average loss: 1.1586, Accuracy: 2823/5000 (56%)
[epoch 14] loss: 0.8669437
Test set: Average loss: 1.1576, Accuracy: 2819/5000 (56%)
[epoch 15] loss: 0.8536626
Test set: Average loss: 1.1515, Accuracy: 2834/5000 (57%)
[epoch 16] loss: 0.8305054
Test set: Average loss: 1.1467, Accuracy: 2822/5000 (56%)
[epoch 17] loss: 0.8056511
Test set: Average loss: 1.1449, Accuracy: 2829/5000 (57%)
[epoch 18] loss: 0.7889286
Test set: Average loss: 1.1418, Accuracy: 2857/5000 (57%)
[epoch 19] loss: 0.7716626
Test set: Average loss: 1.1393, Accuracy: 2842/5000 (57%)
[epoch 20] loss: 0.7505469
Test set: Average loss: 1.1366, Accuracy: 2835/5000 (57%)
[epoch 21] loss: 0.7344505
Test set: Average loss: 1.1358, Accuracy: 2830/5000 (57%)
[epoch 22] loss: 0.7203938
Test set: Average loss: 1.1327, Accuracy: 2848/5000 (57%)
[epoch 23] loss: 0.7028024
Test set: Average loss: 1.1344, Accuracy: 2852/5000 (57%)
[epoch 24] loss: 0.6876278
Test set: Average loss: 1.1338, Accuracy: 2818/5000 (56%)
[epoch 25] loss: 0.6733809
Test set: Average loss: 1.1283, Accuracy: 2857/5000 (57%)
Validation:
Test set: Average loss: 1.1283, Accuracy: 2857/5000 (57%)
Test
Test set: Average loss: 1.1332, Accuracy: 2808/5000 (56%)
Test set: Average loss: 0.6531, Accuracy: 643/750 (86%)
## seed: 12
Validation accuracy before training:
Test set: Average loss: 1.6091, Accuracy: 1016/5000 (20%)
[epoch 1] loss: 1.4613425
Test set: Average loss: 1.3483, Accuracy: 2294/5000 (46%)
[epoch 2] loss: 1.2993669
Test set: Average loss: 1.2863, Accuracy: 2540/5000 (51%)
[epoch 3] loss: 1.2258922
Test set: Average loss: 1.2541, Accuracy: 2660/5000 (53%)
[epoch 4] loss: 1.1847268
Test set: Average loss: 1.2306, Accuracy: 2751/5000 (55%)
[epoch 5] loss: 1.1413787
Test set: Average loss: 1.2149, Accuracy: 2779/5000 (56%)
[epoch 6] loss: 1.1125806
Test set: Average loss: 1.2007, Accuracy: 2831/5000 (57%)
[epoch 7] loss: 1.0800891
Test set: Average loss: 1.1913, Accuracy: 2839/5000 (57%)
[epoch 8] loss: 1.0491975
Test set: Average loss: 1.1838, Accuracy: 2859/5000 (57%)
[epoch 9] loss: 1.0242011
Test set: Average loss: 1.1758, Accuracy: 2853/5000 (57%)
[epoch 10] loss: 0.9955245
Test set: Average loss: 1.1635, Accuracy: 2897/5000 (58%)
[epoch 11] loss: 0.9808739
Test set: Average loss: 1.1614, Accuracy: 2877/5000 (58%)
[epoch 12] loss: 0.9469997
Test set: Average loss: 1.1528, Accuracy: 2901/5000 (58%)
[epoch 13] loss: 0.9281072
Test set: Average loss: 1.1491, Accuracy: 2901/5000 (58%)
[epoch 14] loss: 0.9053085
Test set: Average loss: 1.1460, Accuracy: 2894/5000 (58%)
[epoch 15] loss: 0.8876435
Test set: Average loss: 1.1405, Accuracy: 2909/5000 (58%)
[epoch 16] loss: 0.8704295
Test set: Average loss: 1.1383, Accuracy: 2910/5000 (58%)
[epoch 17] loss: 0.8432830
Test set: Average loss: 1.1334, Accuracy: 2916/5000 (58%)
[epoch 18] loss: 0.8257795
Test set: Average loss: 1.1295, Accuracy: 2913/5000 (58%)
[epoch 19] loss: 0.8037809
Test set: Average loss: 1.1277, Accuracy: 2926/5000 (59%)
[epoch 20] loss: 0.7853292
Test set: Average loss: 1.1229, Accuracy: 2939/5000 (59%)
[epoch 21] loss: 0.7744272
Test set: Average loss: 1.1289, Accuracy: 2890/5000 (58%)
[epoch 22] loss: 0.7556362
Test set: Average loss: 1.1177, Accuracy: 2914/5000 (58%)
[epoch 23] loss: 0.7360921
Test set: Average loss: 1.1185, Accuracy: 2930/5000 (59%)
[epoch 24] loss: 0.7190819
Test set: Average loss: 1.1193, Accuracy: 2920/5000 (58%)
[epoch 25] loss: 0.7005739
Test set: Average loss: 1.1196, Accuracy: 2891/5000 (58%)
Validation:
Test set: Average loss: 1.1229, Accuracy: 2939/5000 (59%)
Test
Test set: Average loss: 1.1351, Accuracy: 2860/5000 (57%)
Test set: Average loss: 0.7657, Accuracy: 613/750 (82%)
## seed: 13
Validation accuracy before training:
Test set: Average loss: 1.6167, Accuracy: 1145/5000 (23%)
[epoch 1] loss: 1.4541249
Test set: Average loss: 1.3673, Accuracy: 2331/5000 (47%)
[epoch 2] loss: 1.2884986
Test set: Average loss: 1.3037, Accuracy: 2521/5000 (50%)
[epoch 3] loss: 1.2182836
Test set: Average loss: 1.2738, Accuracy: 2589/5000 (52%)
[epoch 4] loss: 1.1716050
Test set: Average loss: 1.2535, Accuracy: 2641/5000 (53%)
[epoch 5] loss: 1.1315279
Test set: Average loss: 1.2334, Accuracy: 2692/5000 (54%)
[epoch 6] loss: 1.0910242
Test set: Average loss: 1.2203, Accuracy: 2712/5000 (54%)
[epoch 7] loss: 1.0692478
Test set: Average loss: 1.2113, Accuracy: 2736/5000 (55%)
[epoch 8] loss: 1.0301934
Test set: Average loss: 1.1993, Accuracy: 2768/5000 (55%)
[epoch 9] loss: 1.0146457
Test set: Average loss: 1.1922, Accuracy: 2765/5000 (55%)
[epoch 10] loss: 0.9767608
Test set: Average loss: 1.1844, Accuracy: 2774/5000 (55%)
[epoch 11] loss: 0.9583209
Test set: Average loss: 1.1801, Accuracy: 2807/5000 (56%)
[epoch 12] loss: 0.9356458
Test set: Average loss: 1.1722, Accuracy: 2811/5000 (56%)
[epoch 13] loss: 0.9093639
Test set: Average loss: 1.1665, Accuracy: 2828/5000 (57%)
[epoch 14] loss: 0.8915784
Test set: Average loss: 1.1634, Accuracy: 2817/5000 (56%)
[epoch 15] loss: 0.8685548
Test set: Average loss: 1.1621, Accuracy: 2818/5000 (56%)
[epoch 16] loss: 0.8479612
Test set: Average loss: 1.1560, Accuracy: 2836/5000 (57%)
[epoch 17] loss: 0.8257858
Test set: Average loss: 1.1580, Accuracy: 2817/5000 (56%)
[epoch 18] loss: 0.8033006
Test set: Average loss: 1.1500, Accuracy: 2824/5000 (56%)
[epoch 19] loss: 0.7897622
Test set: Average loss: 1.1478, Accuracy: 2836/5000 (57%)
[epoch 20] loss: 0.7653004
Test set: Average loss: 1.1479, Accuracy: 2831/5000 (57%)
[epoch 21] loss: 0.7484928
Test set: Average loss: 1.1488, Accuracy: 2815/5000 (56%)
[epoch 22] loss: 0.7382359
Test set: Average loss: 1.1422, Accuracy: 2838/5000 (57%)
[epoch 23] loss: 0.7116722
Test set: Average loss: 1.1486, Accuracy: 2808/5000 (56%)
[epoch 24] loss: 0.6981041
Test set: Average loss: 1.1424, Accuracy: 2822/5000 (56%)
[epoch 25] loss: 0.6762203
Test set: Average loss: 1.1421, Accuracy: 2834/5000 (57%)
Validation:
Test set: Average loss: 1.1422, Accuracy: 2838/5000 (57%)
Test
Test set: Average loss: 1.1541, Accuracy: 2792/5000 (56%)
Test set: Average loss: 0.7075, Accuracy: 641/750 (85%)
1000
## seed: 11
Validation accuracy before training:
Test set: Average loss: 1.6299, Accuracy: 980/5000 (20%)
[epoch 1] loss: 1.4374110
Test set: Average loss: 1.3469, Accuracy: 2289/5000 (46%)
[epoch 2] loss: 1.2616364
Test set: Average loss: 1.2840, Accuracy: 2519/5000 (50%)
[epoch 3] loss: 1.1870578
Test set: Average loss: 1.2518, Accuracy: 2634/5000 (53%)
[epoch 4] loss: 1.1431273
Test set: Average loss: 1.2299, Accuracy: 2689/5000 (54%)
[epoch 5] loss: 1.1088398
Test set: Average loss: 1.2144, Accuracy: 2727/5000 (55%)
[epoch 6] loss: 1.0682763
Test set: Average loss: 1.2005, Accuracy: 2778/5000 (56%)
[epoch 7] loss: 1.0447299
Test set: Average loss: 1.1928, Accuracy: 2787/5000 (56%)
[epoch 8] loss: 0.9995711
Test set: Average loss: 1.1843, Accuracy: 2814/5000 (56%)
[epoch 9] loss: 0.9802115
Test set: Average loss: 1.1766, Accuracy: 2809/5000 (56%)
[epoch 10] loss: 0.9553760
Test set: Average loss: 1.1702, Accuracy: 2828/5000 (57%)
[epoch 11] loss: 0.9358394
Test set: Average loss: 1.1656, Accuracy: 2811/5000 (56%)
[epoch 12] loss: 0.9117041
Test set: Average loss: 1.1628, Accuracy: 2820/5000 (56%)
[epoch 13] loss: 0.8845527
Test set: Average loss: 1.1580, Accuracy: 2822/5000 (56%)
[epoch 14] loss: 0.8678091
Test set: Average loss: 1.1530, Accuracy: 2842/5000 (57%)
[epoch 15] loss: 0.8432686
Test set: Average loss: 1.1507, Accuracy: 2845/5000 (57%)
[epoch 16] loss: 0.8253334
Test set: Average loss: 1.1475, Accuracy: 2856/5000 (57%)
[epoch 17] loss: 0.8091631
Test set: Average loss: 1.1454, Accuracy: 2846/5000 (57%)
[epoch 18] loss: 0.7846420
Test set: Average loss: 1.1415, Accuracy: 2855/5000 (57%)
[epoch 19] loss: 0.7614373
Test set: Average loss: 1.1392, Accuracy: 2850/5000 (57%)
[epoch 20] loss: 0.7533566
Test set: Average loss: 1.1380, Accuracy: 2872/5000 (57%)
[epoch 21] loss: 0.7275573
Test set: Average loss: 1.1373, Accuracy: 2855/5000 (57%)
[epoch 22] loss: 0.7130070
Test set: Average loss: 1.1346, Accuracy: 2859/5000 (57%)
[epoch 23] loss: 0.6979379
Test set: Average loss: 1.1358, Accuracy: 2862/5000 (57%)
[epoch 24] loss: 0.6741432
Test set: Average loss: 1.1433, Accuracy: 2833/5000 (57%)
[epoch 25] loss: 0.6539581
Test set: Average loss: 1.1310, Accuracy: 2868/5000 (57%)
Validation:
Test set: Average loss: 1.1380, Accuracy: 2872/5000 (57%)
Test
Test set: Average loss: 1.1447, Accuracy: 2838/5000 (57%)
Test set: Average loss: 0.7254, Accuracy: 817/1000 (82%)
## seed: 12
Validation accuracy before training:
Test set: Average loss: 1.6823, Accuracy: 610/5000 (12%)
[epoch 1] loss: 1.4769819
Test set: Average loss: 1.3316, Accuracy: 2399/5000 (48%)
[epoch 2] loss: 1.2916620
Test set: Average loss: 1.2675, Accuracy: 2584/5000 (52%)
[epoch 3] loss: 1.2142199
Test set: Average loss: 1.2347, Accuracy: 2714/5000 (54%)
[epoch 4] loss: 1.1690381
Test set: Average loss: 1.2145, Accuracy: 2752/5000 (55%)
[epoch 5] loss: 1.1395751
Test set: Average loss: 1.1969, Accuracy: 2817/5000 (56%)
[epoch 6] loss: 1.0913245
Test set: Average loss: 1.1849, Accuracy: 2818/5000 (56%)
[epoch 7] loss: 1.0630413
Test set: Average loss: 1.1742, Accuracy: 2854/5000 (57%)
[epoch 8] loss: 1.0306344
Test set: Average loss: 1.1625, Accuracy: 2850/5000 (57%)
[epoch 9] loss: 1.0087802
Test set: Average loss: 1.1600, Accuracy: 2870/5000 (57%)
[epoch 10] loss: 0.9826771
Test set: Average loss: 1.1481, Accuracy: 2899/5000 (58%)
[epoch 11] loss: 0.9608514
Test set: Average loss: 1.1430, Accuracy: 2875/5000 (58%)
[epoch 12] loss: 0.9426382
Test set: Average loss: 1.1406, Accuracy: 2898/5000 (58%)
[epoch 13] loss: 0.9221591
Test set: Average loss: 1.1396, Accuracy: 2888/5000 (58%)
[epoch 14] loss: 0.9059277
Test set: Average loss: 1.1250, Accuracy: 2940/5000 (59%)
[epoch 15] loss: 0.8727009
Test set: Average loss: 1.1330, Accuracy: 2879/5000 (58%)
[epoch 16] loss: 0.8500694
Test set: Average loss: 1.1185, Accuracy: 2946/5000 (59%)
[epoch 17] loss: 0.8284925
Test set: Average loss: 1.1144, Accuracy: 2932/5000 (59%)
[epoch 18] loss: 0.8134585
Test set: Average loss: 1.1123, Accuracy: 2924/5000 (58%)
[epoch 19] loss: 0.7935930
Test set: Average loss: 1.1135, Accuracy: 2917/5000 (58%)
[epoch 20] loss: 0.7790238
Test set: Average loss: 1.1100, Accuracy: 2916/5000 (58%)
[epoch 21] loss: 0.7602227
Test set: Average loss: 1.1094, Accuracy: 2939/5000 (59%)
[epoch 22] loss: 0.7436460
Test set: Average loss: 1.1076, Accuracy: 2930/5000 (59%)
[epoch 23] loss: 0.7191671
Test set: Average loss: 1.1140, Accuracy: 2892/5000 (58%)
[epoch 24] loss: 0.7089386
Test set: Average loss: 1.1029, Accuracy: 2942/5000 (59%)
[epoch 25] loss: 0.6816887
Test set: Average loss: 1.1060, Accuracy: 2927/5000 (59%)
Validation:
Test set: Average loss: 1.1185, Accuracy: 2946/5000 (59%)
Test
Test set: Average loss: 1.1292, Accuracy: 2879/5000 (58%)
Test set: Average loss: 0.8259, Accuracy: 776/1000 (78%)
## seed: 13
Validation accuracy before training:
Test set: Average loss: 1.6575, Accuracy: 748/5000 (15%)
[epoch 1] loss: 1.4411705
Test set: Average loss: 1.3477, Accuracy: 2347/5000 (47%)
[epoch 2] loss: 1.2796110
Test set: Average loss: 1.2844, Accuracy: 2523/5000 (50%)
[epoch 3] loss: 1.2063830
Test set: Average loss: 1.2538, Accuracy: 2586/5000 (52%)
[epoch 4] loss: 1.1674687
Test set: Average loss: 1.2266, Accuracy: 2690/5000 (54%)
[epoch 5] loss: 1.1241770
Test set: Average loss: 1.2103, Accuracy: 2712/5000 (54%)
[epoch 6] loss: 1.0868544
Test set: Average loss: 1.2005, Accuracy: 2748/5000 (55%)
[epoch 7] loss: 1.0544798
Test set: Average loss: 1.1847, Accuracy: 2785/5000 (56%)
[epoch 8] loss: 1.0238218
Test set: Average loss: 1.1730, Accuracy: 2798/5000 (56%)
[epoch 9] loss: 1.0028264
Test set: Average loss: 1.1651, Accuracy: 2828/5000 (57%)
[epoch 10] loss: 0.9680797
Test set: Average loss: 1.1504, Accuracy: 2883/5000 (58%)
[epoch 11] loss: 0.9555056
Test set: Average loss: 1.1535, Accuracy: 2793/5000 (56%)
[epoch 12] loss: 0.9231209
Test set: Average loss: 1.1405, Accuracy: 2901/5000 (58%)
[epoch 13] loss: 0.8942540
Test set: Average loss: 1.1322, Accuracy: 2910/5000 (58%)
[epoch 14] loss: 0.8787566
Test set: Average loss: 1.1321, Accuracy: 2887/5000 (58%)
[epoch 15] loss: 0.8646032
Test set: Average loss: 1.1269, Accuracy: 2892/5000 (58%)
[epoch 16] loss: 0.8307072
Test set: Average loss: 1.1234, Accuracy: 2912/5000 (58%)
[epoch 17] loss: 0.8169201
Test set: Average loss: 1.1241, Accuracy: 2876/5000 (58%)
[epoch 18] loss: 0.7949874
Test set: Average loss: 1.1178, Accuracy: 2906/5000 (58%)
[epoch 19] loss: 0.7760941
Test set: Average loss: 1.1151, Accuracy: 2912/5000 (58%)
[epoch 20] loss: 0.7565530
Test set: Average loss: 1.1092, Accuracy: 2925/5000 (58%)
[epoch 21] loss: 0.7340770
Test set: Average loss: 1.1155, Accuracy: 2914/5000 (58%)
[epoch 22] loss: 0.7240770
Test set: Average loss: 1.1110, Accuracy: 2912/5000 (58%)
[epoch 23] loss: 0.7073049
Test set: Average loss: 1.1072, Accuracy: 2914/5000 (58%)
[epoch 24] loss: 0.6853738
Test set: Average loss: 1.1188, Accuracy: 2880/5000 (58%)
[epoch 25] loss: 0.6729371
Test set: Average loss: 1.1092, Accuracy: 2913/5000 (58%)
Validation:
Test set: Average loss: 1.1092, Accuracy: 2925/5000 (58%)
Test
Test set: Average loss: 1.1233, Accuracy: 2864/5000 (57%)
Test set: Average loss: 0.7312, Accuracy: 823/1000 (82%)
2500
## seed: 11
Validation accuracy before training:
Test set: Average loss: 1.6145, Accuracy: 1012/5000 (20%)
[epoch 1] loss: 1.3679776
Test set: Average loss: 1.2746, Accuracy: 2610/5000 (52%)
[epoch 2] loss: 1.2286833
Test set: Average loss: 1.2234, Accuracy: 2755/5000 (55%)
[epoch 3] loss: 1.1765590
Test set: Average loss: 1.1908, Accuracy: 2819/5000 (56%)
[epoch 4] loss: 1.1271935
Test set: Average loss: 1.1714, Accuracy: 2870/5000 (57%)
[epoch 5] loss: 1.0951558
Test set: Average loss: 1.1499, Accuracy: 2925/5000 (58%)
[epoch 6] loss: 1.0674258
Test set: Average loss: 1.1344, Accuracy: 2939/5000 (59%)
[epoch 7] loss: 1.0350233
Test set: Average loss: 1.1251, Accuracy: 2959/5000 (59%)
[epoch 8] loss: 1.0080411
Test set: Average loss: 1.1127, Accuracy: 2992/5000 (60%)
[epoch 9] loss: 0.9759934
Test set: Average loss: 1.1033, Accuracy: 2994/5000 (60%)
[epoch 10] loss: 0.9517176
Test set: Average loss: 1.0899, Accuracy: 3028/5000 (61%)
[epoch 11] loss: 0.9243756
Test set: Average loss: 1.0829, Accuracy: 3025/5000 (60%)
[epoch 12] loss: 0.9105513
Test set: Average loss: 1.0789, Accuracy: 3042/5000 (61%)
[epoch 13] loss: 0.8789477
Test set: Average loss: 1.0686, Accuracy: 3039/5000 (61%)
[epoch 14] loss: 0.8558870
Test set: Average loss: 1.0665, Accuracy: 3034/5000 (61%)
[epoch 15] loss: 0.8384496
Test set: Average loss: 1.0579, Accuracy: 3029/5000 (61%)
[epoch 16] loss: 0.8165247
Test set: Average loss: 1.0502, Accuracy: 3061/5000 (61%)
[epoch 17] loss: 0.8021117
Test set: Average loss: 1.0525, Accuracy: 3040/5000 (61%)
[epoch 18] loss: 0.7735982
Test set: Average loss: 1.0488, Accuracy: 3043/5000 (61%)
[epoch 19] loss: 0.7532785
Test set: Average loss: 1.0393, Accuracy: 3081/5000 (62%)
[epoch 20] loss: 0.7330641
Test set: Average loss: 1.0446, Accuracy: 3063/5000 (61%)
[epoch 21] loss: 0.7128070
Test set: Average loss: 1.0409, Accuracy: 3071/5000 (61%)
[epoch 22] loss: 0.6888274
Test set: Average loss: 1.0384, Accuracy: 3077/5000 (62%)
[epoch 23] loss: 0.6756230
Test set: Average loss: 1.0383, Accuracy: 3069/5000 (61%)
[epoch 24] loss: 0.6539116
Test set: Average loss: 1.0373, Accuracy: 3055/5000 (61%)
[epoch 25] loss: 0.6309240
Test set: Average loss: 1.0314, Accuracy: 3055/5000 (61%)
Validation:
Test set: Average loss: 1.0393, Accuracy: 3081/5000 (62%)
Test
Test set: Average loss: 1.0447, Accuracy: 3039/5000 (61%)
Test set: Average loss: 0.7217, Accuracy: 1976/2500 (79%)
## seed: 12
Validation accuracy before training:
Test set: Average loss: 1.6289, Accuracy: 1202/5000 (24%)
[epoch 1] loss: 1.3616903
Test set: Average loss: 1.2596, Accuracy: 2669/5000 (53%)
[epoch 2] loss: 1.2035816
Test set: Average loss: 1.2034, Accuracy: 2793/5000 (56%)
[epoch 3] loss: 1.1438496
Test set: Average loss: 1.1737, Accuracy: 2855/5000 (57%)
[epoch 4] loss: 1.0955658
Test set: Average loss: 1.1495, Accuracy: 2919/5000 (58%)
[epoch 5] loss: 1.0575176
Test set: Average loss: 1.1315, Accuracy: 2951/5000 (59%)
[epoch 6] loss: 1.0236509
Test set: Average loss: 1.1114, Accuracy: 2954/5000 (59%)
[epoch 7] loss: 0.9968373
Test set: Average loss: 1.1041, Accuracy: 3006/5000 (60%)
[epoch 8] loss: 0.9640896
Test set: Average loss: 1.0947, Accuracy: 2986/5000 (60%)
[epoch 9] loss: 0.9397536
Test set: Average loss: 1.0807, Accuracy: 3012/5000 (60%)
[epoch 10] loss: 0.9147646
Test set: Average loss: 1.0723, Accuracy: 3042/5000 (61%)
[epoch 11] loss: 0.8865642
Test set: Average loss: 1.0656, Accuracy: 3059/5000 (61%)
[epoch 12] loss: 0.8607516
Test set: Average loss: 1.0575, Accuracy: 3061/5000 (61%)
[epoch 13] loss: 0.8382622
Test set: Average loss: 1.0534, Accuracy: 3068/5000 (61%)
[epoch 14] loss: 0.8180066
Test set: Average loss: 1.0491, Accuracy: 3067/5000 (61%)
[epoch 15] loss: 0.7955597
Test set: Average loss: 1.0497, Accuracy: 3066/5000 (61%)
[epoch 16] loss: 0.7691138
Test set: Average loss: 1.0396, Accuracy: 3070/5000 (61%)
[epoch 17] loss: 0.7516198
Test set: Average loss: 1.0361, Accuracy: 3092/5000 (62%)
[epoch 18] loss: 0.7329225
Test set: Average loss: 1.0393, Accuracy: 3067/5000 (61%)
[epoch 19] loss: 0.7065190
Test set: Average loss: 1.0307, Accuracy: 3103/5000 (62%)
[epoch 20] loss: 0.6865375
Test set: Average loss: 1.0337, Accuracy: 3097/5000 (62%)
[epoch 21] loss: 0.6704134
Test set: Average loss: 1.0303, Accuracy: 3086/5000 (62%)
[epoch 22] loss: 0.6578293
Test set: Average loss: 1.0297, Accuracy: 3082/5000 (62%)
[epoch 23] loss: 0.6323229
Test set: Average loss: 1.0302, Accuracy: 3072/5000 (61%)
[epoch 24] loss: 0.6145056
Test set: Average loss: 1.0300, Accuracy: 3091/5000 (62%)
[epoch 25] loss: 0.5868570
Test set: Average loss: 1.0322, Accuracy: 3076/5000 (62%)
Validation:
Test set: Average loss: 1.0307, Accuracy: 3103/5000 (62%)
Test
Test set: Average loss: 1.0453, Accuracy: 3022/5000 (60%)
Test set: Average loss: 0.6784, Accuracy: 2001/2500 (80%)
## seed: 13
Validation accuracy before training:
Test set: Average loss: 1.6150, Accuracy: 1082/5000 (22%)
[epoch 1] loss: 1.3378658
Test set: Average loss: 1.2537, Accuracy: 2577/5000 (52%)
[epoch 2] loss: 1.1950943
Test set: Average loss: 1.2028, Accuracy: 2757/5000 (55%)
[epoch 3] loss: 1.1336716
Test set: Average loss: 1.1730, Accuracy: 2818/5000 (56%)
[epoch 4] loss: 1.0925779
Test set: Average loss: 1.1445, Accuracy: 2867/5000 (57%)
[epoch 5] loss: 1.0491413
Test set: Average loss: 1.1256, Accuracy: 2919/5000 (58%)
[epoch 6] loss: 1.0199994
Test set: Average loss: 1.1112, Accuracy: 2961/5000 (59%)
[epoch 7] loss: 0.9951050
Test set: Average loss: 1.1009, Accuracy: 2974/5000 (59%)
[epoch 8] loss: 0.9660481
Test set: Average loss: 1.0900, Accuracy: 2972/5000 (59%)
[epoch 9] loss: 0.9386700
Test set: Average loss: 1.0753, Accuracy: 3019/5000 (60%)
[epoch 10] loss: 0.9108927
Test set: Average loss: 1.0714, Accuracy: 3007/5000 (60%)
[epoch 11] loss: 0.8938256
Test set: Average loss: 1.0630, Accuracy: 3034/5000 (61%)
[epoch 12] loss: 0.8694793
Test set: Average loss: 1.0631, Accuracy: 3044/5000 (61%)
[epoch 13] loss: 0.8442032
Test set: Average loss: 1.0579, Accuracy: 3027/5000 (61%)
[epoch 14] loss: 0.8294124
Test set: Average loss: 1.0579, Accuracy: 3026/5000 (61%)
[epoch 15] loss: 0.8080378
Test set: Average loss: 1.0432, Accuracy: 3061/5000 (61%)
[epoch 16] loss: 0.7859831
Test set: Average loss: 1.0388, Accuracy: 3081/5000 (62%)
[epoch 17] loss: 0.7544552
Test set: Average loss: 1.0373, Accuracy: 3067/5000 (61%)
[epoch 18] loss: 0.7383657
Test set: Average loss: 1.0372, Accuracy: 3059/5000 (61%)
[epoch 19] loss: 0.7281223
Test set: Average loss: 1.0334, Accuracy: 3079/5000 (62%)
[epoch 20] loss: 0.7019718
Test set: Average loss: 1.0317, Accuracy: 3058/5000 (61%)
[epoch 21] loss: 0.6789575
Test set: Average loss: 1.0445, Accuracy: 3021/5000 (60%)
[epoch 22] loss: 0.6602584
Test set: Average loss: 1.0345, Accuracy: 3055/5000 (61%)
[epoch 23] loss: 0.6444645
Test set: Average loss: 1.0342, Accuracy: 3069/5000 (61%)
[epoch 24] loss: 0.6250320
Test set: Average loss: 1.0383, Accuracy: 3034/5000 (61%)
[epoch 25] loss: 0.6109570
Test set: Average loss: 1.0356, Accuracy: 3042/5000 (61%)
Validation:
Test set: Average loss: 1.0388, Accuracy: 3081/5000 (62%)
Test
Test set: Average loss: 1.0566, Accuracy: 3015/5000 (60%)
Test set: Average loss: 0.7488, Accuracy: 1937/2500 (77%)
5000
## seed: 11
Validation accuracy before training:
Test set: Average loss: 1.6220, Accuracy: 1000/5000 (20%)
[epoch 1] loss: 1.2838684
Test set: Average loss: 1.1864, Accuracy: 2838/5000 (57%)
[epoch 2] loss: 1.1417265
Test set: Average loss: 1.1303, Accuracy: 2951/5000 (59%)
[epoch 3] loss: 1.0803213
Test set: Average loss: 1.1023, Accuracy: 2977/5000 (60%)
[epoch 4] loss: 1.0384925
Test set: Average loss: 1.0742, Accuracy: 3051/5000 (61%)
[epoch 5] loss: 1.0015588
Test set: Average loss: 1.0573, Accuracy: 3107/5000 (62%)
[epoch 6] loss: 0.9711436
Test set: Average loss: 1.0444, Accuracy: 3103/5000 (62%)
[epoch 7] loss: 0.9409150
Test set: Average loss: 1.0387, Accuracy: 3109/5000 (62%)
[epoch 8] loss: 0.9150904
Test set: Average loss: 1.0278, Accuracy: 3118/5000 (62%)
[epoch 9] loss: 0.8881342
Test set: Average loss: 1.0194, Accuracy: 3142/5000 (63%)
[epoch 10] loss: 0.8640800
Test set: Average loss: 1.0104, Accuracy: 3148/5000 (63%)
[epoch 11] loss: 0.8388485
Test set: Average loss: 0.9986, Accuracy: 3152/5000 (63%)
[epoch 12] loss: 0.8170977
Test set: Average loss: 0.9981, Accuracy: 3140/5000 (63%)
[epoch 13] loss: 0.7951996
Test set: Average loss: 0.9925, Accuracy: 3148/5000 (63%)
[epoch 14] loss: 0.7699095
Test set: Average loss: 0.9879, Accuracy: 3158/5000 (63%)
[epoch 15] loss: 0.7477720
Test set: Average loss: 0.9922, Accuracy: 3176/5000 (64%)
[epoch 16] loss: 0.7259962
Test set: Average loss: 0.9853, Accuracy: 3162/5000 (63%)
[epoch 17] loss: 0.7022726
Test set: Average loss: 0.9790, Accuracy: 3173/5000 (63%)
[epoch 18] loss: 0.6803991
Test set: Average loss: 0.9818, Accuracy: 3167/5000 (63%)
[epoch 19] loss: 0.6577780
Test set: Average loss: 0.9800, Accuracy: 3174/5000 (63%)
[epoch 20] loss: 0.6383586
Test set: Average loss: 0.9788, Accuracy: 3183/5000 (64%)
[epoch 21] loss: 0.6152268
Test set: Average loss: 0.9790, Accuracy: 3189/5000 (64%)
[epoch 22] loss: 0.5917435
Test set: Average loss: 0.9842, Accuracy: 3187/5000 (64%)
[epoch 23] loss: 0.5693070
Test set: Average loss: 0.9818, Accuracy: 3166/5000 (63%)
[epoch 24] loss: 0.5509184
Test set: Average loss: 0.9788, Accuracy: 3206/5000 (64%)
[epoch 25] loss: 0.5288567
Test set: Average loss: 0.9835, Accuracy: 3186/5000 (64%)
Validation:
Test set: Average loss: 0.9788, Accuracy: 3206/5000 (64%)
Test
Test set: Average loss: 0.9806, Accuracy: 3146/5000 (63%)
Test set: Average loss: 0.5135, Accuracy: 4313/5000 (86%)
## seed: 12
Validation accuracy before training:
Test set: Average loss: 1.6205, Accuracy: 1081/5000 (22%)
[epoch 1] loss: 1.3092852
Test set: Average loss: 1.2066, Accuracy: 2779/5000 (56%)
[epoch 2] loss: 1.1579481
Test set: Average loss: 1.1387, Accuracy: 2932/5000 (59%)
[epoch 3] loss: 1.0906661
Test set: Average loss: 1.1032, Accuracy: 3026/5000 (61%)
[epoch 4] loss: 1.0411185
Test set: Average loss: 1.0759, Accuracy: 3045/5000 (61%)
[epoch 5] loss: 1.0039451
Test set: Average loss: 1.0526, Accuracy: 3107/5000 (62%)
[epoch 6] loss: 0.9678167
Test set: Average loss: 1.0412, Accuracy: 3114/5000 (62%)
[epoch 7] loss: 0.9401063
Test set: Average loss: 1.0330, Accuracy: 3111/5000 (62%)
[epoch 8] loss: 0.9129565
Test set: Average loss: 1.0195, Accuracy: 3141/5000 (63%)
[epoch 9] loss: 0.8866432
Test set: Average loss: 1.0109, Accuracy: 3145/5000 (63%)
[epoch 10] loss: 0.8569821
Test set: Average loss: 1.0054, Accuracy: 3165/5000 (63%)
[epoch 11] loss: 0.8365263
Test set: Average loss: 1.0008, Accuracy: 3149/5000 (63%)
[epoch 12] loss: 0.8091220
Test set: Average loss: 0.9987, Accuracy: 3146/5000 (63%)
[epoch 13] loss: 0.7855497
Test set: Average loss: 0.9875, Accuracy: 3176/5000 (64%)
[epoch 14] loss: 0.7650346
Test set: Average loss: 0.9839, Accuracy: 3155/5000 (63%)
[epoch 15] loss: 0.7419395
Test set: Average loss: 0.9872, Accuracy: 3151/5000 (63%)
[epoch 16] loss: 0.7169223
Test set: Average loss: 0.9779, Accuracy: 3187/5000 (64%)
[epoch 17] loss: 0.6960262
Test set: Average loss: 0.9763, Accuracy: 3181/5000 (64%)
[epoch 18] loss: 0.6743785
Test set: Average loss: 0.9802, Accuracy: 3176/5000 (64%)
[epoch 19] loss: 0.6525467
Test set: Average loss: 0.9702, Accuracy: 3194/5000 (64%)
[epoch 20] loss: 0.6257860
Test set: Average loss: 0.9787, Accuracy: 3170/5000 (63%)
[epoch 21] loss: 0.6059191
Test set: Average loss: 0.9678, Accuracy: 3200/5000 (64%)
[epoch 22] loss: 0.5894950
Test set: Average loss: 0.9740, Accuracy: 3195/5000 (64%)
[epoch 23] loss: 0.5640725
Test set: Average loss: 0.9819, Accuracy: 3170/5000 (63%)
[epoch 24] loss: 0.5426092
Test set: Average loss: 0.9728, Accuracy: 3188/5000 (64%)
[epoch 25] loss: 0.5185663
Test set: Average loss: 0.9775, Accuracy: 3152/5000 (63%)
Validation:
Test set: Average loss: 0.9678, Accuracy: 3200/5000 (64%)
Test
Test set: Average loss: 0.9845, Accuracy: 3125/5000 (62%)
Test set: Average loss: 0.5706, Accuracy: 4176/5000 (84%)
## seed: 13
Validation accuracy before training:
Test set: Average loss: 1.6116, Accuracy: 984/5000 (20%)
[epoch 1] loss: 1.2956447
Test set: Average loss: 1.2067, Accuracy: 2852/5000 (57%)
[epoch 2] loss: 1.1434561
Test set: Average loss: 1.1395, Accuracy: 2962/5000 (59%)
[epoch 3] loss: 1.0766636
Test set: Average loss: 1.1071, Accuracy: 3011/5000 (60%)
[epoch 4] loss: 1.0254568
Test set: Average loss: 1.0757, Accuracy: 3063/5000 (61%)
[epoch 5] loss: 0.9840536
Test set: Average loss: 1.0518, Accuracy: 3094/5000 (62%)
[epoch 6] loss: 0.9477499
Test set: Average loss: 1.0351, Accuracy: 3120/5000 (62%)
[epoch 7] loss: 0.9153356
Test set: Average loss: 1.0233, Accuracy: 3112/5000 (62%)
[epoch 8] loss: 0.8887394
Test set: Average loss: 1.0112, Accuracy: 3144/5000 (63%)
[epoch 9] loss: 0.8642521
Test set: Average loss: 1.0021, Accuracy: 3143/5000 (63%)
[epoch 10] loss: 0.8341727
Test set: Average loss: 0.9977, Accuracy: 3149/5000 (63%)
[epoch 11] loss: 0.8124841
Test set: Average loss: 0.9886, Accuracy: 3147/5000 (63%)
[epoch 12] loss: 0.7893193
Test set: Average loss: 0.9877, Accuracy: 3158/5000 (63%)
[epoch 13] loss: 0.7665450
Test set: Average loss: 0.9848, Accuracy: 3145/5000 (63%)
[epoch 14] loss: 0.7413471
Test set: Average loss: 0.9825, Accuracy: 3165/5000 (63%)
[epoch 15] loss: 0.7224331
Test set: Average loss: 0.9784, Accuracy: 3183/5000 (64%)
[epoch 16] loss: 0.6975693
Test set: Average loss: 0.9783, Accuracy: 3152/5000 (63%)
[epoch 17] loss: 0.6762422
Test set: Average loss: 0.9780, Accuracy: 3189/5000 (64%)
[epoch 18] loss: 0.6559277
Test set: Average loss: 0.9750, Accuracy: 3175/5000 (64%)
[epoch 19] loss: 0.6365445
Test set: Average loss: 0.9783, Accuracy: 3169/5000 (63%)
[epoch 20] loss: 0.6118403
Test set: Average loss: 0.9747, Accuracy: 3184/5000 (64%)
[epoch 21] loss: 0.5887254
Test set: Average loss: 0.9815, Accuracy: 3167/5000 (63%)
[epoch 22] loss: 0.5678078
Test set: Average loss: 0.9764, Accuracy: 3187/5000 (64%)
[epoch 23] loss: 0.5482872
Test set: Average loss: 0.9738, Accuracy: 3185/5000 (64%)
[epoch 24] loss: 0.5255152
Test set: Average loss: 0.9797, Accuracy: 3190/5000 (64%)
[epoch 25] loss: 0.5092500
Test set: Average loss: 0.9801, Accuracy: 3199/5000 (64%)
Validation:
Test set: Average loss: 0.9801, Accuracy: 3199/5000 (64%)
Test
Test set: Average loss: 0.9865, Accuracy: 3158/5000 (63%)
Test set: Average loss: 0.4769, Accuracy: 4341/5000 (87%)
10000
## seed: 11
Validation accuracy before training:
Test set: Average loss: 1.6297, Accuracy: 793/5000 (16%)
[epoch 1] loss: 1.2514130
Test set: Average loss: 1.1538, Accuracy: 2897/5000 (58%)
[epoch 2] loss: 1.1059809
Test set: Average loss: 1.0903, Accuracy: 3035/5000 (61%)
[epoch 3] loss: 1.0403523
Test set: Average loss: 1.0499, Accuracy: 3115/5000 (62%)
[epoch 4] loss: 0.9939829
Test set: Average loss: 1.0240, Accuracy: 3137/5000 (63%)
[epoch 5] loss: 0.9551450
Test set: Average loss: 1.0014, Accuracy: 3177/5000 (64%)
[epoch 6] loss: 0.9236702
Test set: Average loss: 0.9853, Accuracy: 3205/5000 (64%)
[epoch 7] loss: 0.8900792
Test set: Average loss: 0.9749, Accuracy: 3223/5000 (64%)
[epoch 8] loss: 0.8611324
Test set: Average loss: 0.9726, Accuracy: 3178/5000 (64%)
[epoch 9] loss: 0.8354412
Test set: Average loss: 0.9548, Accuracy: 3227/5000 (65%)
[epoch 10] loss: 0.8075648
Test set: Average loss: 0.9430, Accuracy: 3269/5000 (65%)
[epoch 11] loss: 0.7817653
Test set: Average loss: 0.9454, Accuracy: 3257/5000 (65%)
[epoch 12] loss: 0.7571144
Test set: Average loss: 0.9407, Accuracy: 3272/5000 (65%)
[epoch 13] loss: 0.7328185
Test set: Average loss: 0.9435, Accuracy: 3252/5000 (65%)
[epoch 14] loss: 0.7086080
Test set: Average loss: 0.9323, Accuracy: 3266/5000 (65%)
[epoch 15] loss: 0.6845207
Test set: Average loss: 0.9233, Accuracy: 3306/5000 (66%)
[epoch 16] loss: 0.6584048
Test set: Average loss: 0.9295, Accuracy: 3291/5000 (66%)
[epoch 17] loss: 0.6346136
Test set: Average loss: 0.9240, Accuracy: 3310/5000 (66%)
[epoch 18] loss: 0.6084702
Test set: Average loss: 0.9265, Accuracy: 3277/5000 (66%)
[epoch 19] loss: 0.5856466
Test set: Average loss: 0.9169, Accuracy: 3332/5000 (67%)
[epoch 20] loss: 0.5626977
Test set: Average loss: 0.9185, Accuracy: 3327/5000 (67%)
[epoch 21] loss: 0.5394662
Test set: Average loss: 0.9213, Accuracy: 3334/5000 (67%)
[epoch 22] loss: 0.5166189
Test set: Average loss: 0.9307, Accuracy: 3315/5000 (66%)
[epoch 23] loss: 0.4906109
Test set: Average loss: 0.9278, Accuracy: 3353/5000 (67%)
[epoch 24] loss: 0.4668862
Test set: Average loss: 0.9298, Accuracy: 3338/5000 (67%)
[epoch 25] loss: 0.4458771
Test set: Average loss: 0.9414, Accuracy: 3333/5000 (67%)
Validation:
Test set: Average loss: 0.9278, Accuracy: 3353/5000 (67%)
Test
Test set: Average loss: 0.9350, Accuracy: 3294/5000 (66%)
Test set: Average loss: 0.4530, Accuracy: 8767/10000 (88%)
## seed: 12
Validation accuracy before training:
Test set: Average loss: 1.6376, Accuracy: 1090/5000 (22%)
[epoch 1] loss: 1.2514505
Test set: Average loss: 1.1483, Accuracy: 2965/5000 (59%)
[epoch 2] loss: 1.1041472
Test set: Average loss: 1.0909, Accuracy: 3036/5000 (61%)
[epoch 3] loss: 1.0402550
Test set: Average loss: 1.0536, Accuracy: 3113/5000 (62%)
[epoch 4] loss: 0.9939251
Test set: Average loss: 1.0137, Accuracy: 3193/5000 (64%)
[epoch 5] loss: 0.9517982
Test set: Average loss: 0.9990, Accuracy: 3204/5000 (64%)
[epoch 6] loss: 0.9190797
Test set: Average loss: 0.9814, Accuracy: 3239/5000 (65%)
[epoch 7] loss: 0.8876114
Test set: Average loss: 0.9726, Accuracy: 3243/5000 (65%)
[epoch 8] loss: 0.8597756
Test set: Average loss: 0.9633, Accuracy: 3258/5000 (65%)
[epoch 9] loss: 0.8319830
Test set: Average loss: 0.9561, Accuracy: 3242/5000 (65%)
[epoch 10] loss: 0.8039623
Test set: Average loss: 0.9464, Accuracy: 3273/5000 (65%)
[epoch 11] loss: 0.7792625
Test set: Average loss: 0.9409, Accuracy: 3258/5000 (65%)
[epoch 12] loss: 0.7514256
Test set: Average loss: 0.9331, Accuracy: 3272/5000 (65%)
[epoch 13] loss: 0.7250406
Test set: Average loss: 0.9274, Accuracy: 3273/5000 (65%)
[epoch 14] loss: 0.7002778
Test set: Average loss: 0.9197, Accuracy: 3303/5000 (66%)
[epoch 15] loss: 0.6747130
Test set: Average loss: 0.9244, Accuracy: 3281/5000 (66%)
[epoch 16] loss: 0.6521530
Test set: Average loss: 0.9269, Accuracy: 3280/5000 (66%)
[epoch 17] loss: 0.6267789
Test set: Average loss: 0.9168, Accuracy: 3310/5000 (66%)
[epoch 18] loss: 0.6018754
Test set: Average loss: 0.9209, Accuracy: 3301/5000 (66%)
[epoch 19] loss: 0.5771606
Test set: Average loss: 0.9241, Accuracy: 3305/5000 (66%)
[epoch 20] loss: 0.5545333
Test set: Average loss: 0.9230, Accuracy: 3307/5000 (66%)
[epoch 21] loss: 0.5308918
Test set: Average loss: 0.9247, Accuracy: 3292/5000 (66%)
[epoch 22] loss: 0.5055559
Test set: Average loss: 0.9203, Accuracy: 3318/5000 (66%)
[epoch 23] loss: 0.4807544
Test set: Average loss: 0.9303, Accuracy: 3290/5000 (66%)
[epoch 24] loss: 0.4563711
Test set: Average loss: 0.9298, Accuracy: 3301/5000 (66%)
[epoch 25] loss: 0.4356067
Test set: Average loss: 0.9425, Accuracy: 3280/5000 (66%)
Validation:
Test set: Average loss: 0.9203, Accuracy: 3318/5000 (66%)
Test
Test set: Average loss: 0.9309, Accuracy: 3313/5000 (66%)
Test set: Average loss: 0.4625, Accuracy: 8740/10000 (87%)
## seed: 13
Validation accuracy before training:
Test set: Average loss: 1.6070, Accuracy: 1354/5000 (27%)
[epoch 1] loss: 1.2499141
Test set: Average loss: 1.1631, Accuracy: 2898/5000 (58%)
[epoch 2] loss: 1.1116709
Test set: Average loss: 1.1005, Accuracy: 3033/5000 (61%)
[epoch 3] loss: 1.0455764
Test set: Average loss: 1.0509, Accuracy: 3106/5000 (62%)
[epoch 4] loss: 0.9938700
Test set: Average loss: 1.0251, Accuracy: 3121/5000 (62%)
[epoch 5] loss: 0.9537523
Test set: Average loss: 0.9971, Accuracy: 3191/5000 (64%)
[epoch 6] loss: 0.9141839
Test set: Average loss: 0.9854, Accuracy: 3191/5000 (64%)
[epoch 7] loss: 0.8819697
Test set: Average loss: 0.9674, Accuracy: 3208/5000 (64%)
[epoch 8] loss: 0.8515266
Test set: Average loss: 0.9550, Accuracy: 3241/5000 (65%)
[epoch 9] loss: 0.8204814
Test set: Average loss: 0.9417, Accuracy: 3250/5000 (65%)
[epoch 10] loss: 0.7897501
Test set: Average loss: 0.9401, Accuracy: 3250/5000 (65%)
[epoch 11] loss: 0.7628328
Test set: Average loss: 0.9294, Accuracy: 3288/5000 (66%)
[epoch 12] loss: 0.7370082
Test set: Average loss: 0.9241, Accuracy: 3279/5000 (66%)
[epoch 13] loss: 0.7095711
Test set: Average loss: 0.9225, Accuracy: 3285/5000 (66%)
[epoch 14] loss: 0.6835248
Test set: Average loss: 0.9149, Accuracy: 3317/5000 (66%)
[epoch 15] loss: 0.6571501
Test set: Average loss: 0.9120, Accuracy: 3334/5000 (67%)
[epoch 16] loss: 0.6325108
Test set: Average loss: 0.9065, Accuracy: 3335/5000 (67%)
[epoch 17] loss: 0.6067064
Test set: Average loss: 0.9080, Accuracy: 3333/5000 (67%)
[epoch 18] loss: 0.5821090
Test set: Average loss: 0.9073, Accuracy: 3330/5000 (67%)
[epoch 19] loss: 0.5581596
Test set: Average loss: 0.9165, Accuracy: 3312/5000 (66%)
[epoch 20] loss: 0.5346178
Test set: Average loss: 0.9147, Accuracy: 3305/5000 (66%)
[epoch 21] loss: 0.5101369
Test set: Average loss: 0.9114, Accuracy: 3342/5000 (67%)
[epoch 22] loss: 0.4835710
Test set: Average loss: 0.9142, Accuracy: 3340/5000 (67%)
[epoch 23] loss: 0.4617331
Test set: Average loss: 0.9144, Accuracy: 3334/5000 (67%)
[epoch 24] loss: 0.4373939
Test set: Average loss: 0.9309, Accuracy: 3326/5000 (67%)
[epoch 25] loss: 0.4151133
Test set: Average loss: 0.9238, Accuracy: 3337/5000 (67%)
Validation:
Test set: Average loss: 0.9114, Accuracy: 3342/5000 (67%)
Test
Test set: Average loss: 0.9266, Accuracy: 3283/5000 (66%)
Test set: Average loss: 0.4672, Accuracy: 8711/10000 (87%)
15000
## seed: 11
Validation accuracy before training:
Test set: Average loss: 1.6018, Accuracy: 1195/5000 (24%)
[epoch 1] loss: 1.1700269
Test set: Average loss: 1.0825, Accuracy: 3053/5000 (61%)
[epoch 2] loss: 1.0355136
Test set: Average loss: 1.0220, Accuracy: 3164/5000 (63%)
[epoch 3] loss: 0.9771692
Test set: Average loss: 0.9853, Accuracy: 3209/5000 (64%)
[epoch 4] loss: 0.9323426
Test set: Average loss: 0.9724, Accuracy: 3210/5000 (64%)
[epoch 5] loss: 0.8958540
Test set: Average loss: 0.9508, Accuracy: 3249/5000 (65%)
[epoch 6] loss: 0.8631838
Test set: Average loss: 0.9356, Accuracy: 3274/5000 (65%)
[epoch 7] loss: 0.8322189
Test set: Average loss: 0.9175, Accuracy: 3316/5000 (66%)
[epoch 8] loss: 0.8052558
Test set: Average loss: 0.9054, Accuracy: 3347/5000 (67%)
[epoch 9] loss: 0.7777235
Test set: Average loss: 0.9018, Accuracy: 3359/5000 (67%)
[epoch 10] loss: 0.7494123
Test set: Average loss: 0.8957, Accuracy: 3365/5000 (67%)
[epoch 11] loss: 0.7244847
Test set: Average loss: 0.8873, Accuracy: 3386/5000 (68%)
[epoch 12] loss: 0.6987110
Test set: Average loss: 0.8892, Accuracy: 3356/5000 (67%)
[epoch 13] loss: 0.6728719
Test set: Average loss: 0.8906, Accuracy: 3367/5000 (67%)
[epoch 14] loss: 0.6463236
Test set: Average loss: 0.8801, Accuracy: 3399/5000 (68%)
[epoch 15] loss: 0.6211523
Test set: Average loss: 0.8800, Accuracy: 3404/5000 (68%)
[epoch 16] loss: 0.5958505
Test set: Average loss: 0.8904, Accuracy: 3388/5000 (68%)
[epoch 17] loss: 0.5706458
Test set: Average loss: 0.8894, Accuracy: 3374/5000 (67%)
[epoch 18] loss: 0.5445440
Test set: Average loss: 0.8911, Accuracy: 3376/5000 (68%)
[epoch 19] loss: 0.5219844
Test set: Average loss: 0.8961, Accuracy: 3365/5000 (67%)
[epoch 20] loss: 0.4951075
Test set: Average loss: 0.8851, Accuracy: 3419/5000 (68%)
[epoch 21] loss: 0.4729664
Test set: Average loss: 0.8962, Accuracy: 3393/5000 (68%)
[epoch 22] loss: 0.4484961
Test set: Average loss: 0.8951, Accuracy: 3392/5000 (68%)
[epoch 23] loss: 0.4240485
Test set: Average loss: 0.9068, Accuracy: 3381/5000 (68%)
[epoch 24] loss: 0.4000969
Test set: Average loss: 0.9160, Accuracy: 3384/5000 (68%)
[epoch 25] loss: 0.3786823
Test set: Average loss: 0.9223, Accuracy: 3392/5000 (68%)
Validation:
Test set: Average loss: 0.8851, Accuracy: 3419/5000 (68%)
Test
Test set: Average loss: 0.9072, Accuracy: 3309/5000 (66%)
Test set: Average loss: 0.4549, Accuracy: 13048/15000 (87%)
## seed: 12
Validation accuracy before training:
Test set: Average loss: 1.5961, Accuracy: 1367/5000 (27%)
[epoch 1] loss: 1.2044502
Test set: Average loss: 1.1024, Accuracy: 3006/5000 (60%)
[epoch 2] loss: 1.0650834
Test set: Average loss: 1.0418, Accuracy: 3131/5000 (63%)
[epoch 3] loss: 1.0021633
Test set: Average loss: 1.0036, Accuracy: 3204/5000 (64%)
[epoch 4] loss: 0.9540133
Test set: Average loss: 0.9729, Accuracy: 3238/5000 (65%)
[epoch 5] loss: 0.9169361
Test set: Average loss: 0.9545, Accuracy: 3259/5000 (65%)
[epoch 6] loss: 0.8806423
Test set: Average loss: 0.9383, Accuracy: 3272/5000 (65%)
[epoch 7] loss: 0.8491932
Test set: Average loss: 0.9228, Accuracy: 3289/5000 (66%)
[epoch 8] loss: 0.8178831
Test set: Average loss: 0.9120, Accuracy: 3323/5000 (66%)
[epoch 9] loss: 0.7901388
Test set: Average loss: 0.9043, Accuracy: 3326/5000 (67%)
[epoch 10] loss: 0.7605781
Test set: Average loss: 0.8908, Accuracy: 3356/5000 (67%)
[epoch 11] loss: 0.7327355
Test set: Average loss: 0.8947, Accuracy: 3335/5000 (67%)
[epoch 12] loss: 0.7083040
Test set: Average loss: 0.8821, Accuracy: 3366/5000 (67%)
[epoch 13] loss: 0.6817377
Test set: Average loss: 0.8770, Accuracy: 3371/5000 (67%)
[epoch 14] loss: 0.6531569
Test set: Average loss: 0.8753, Accuracy: 3383/5000 (68%)
[epoch 15] loss: 0.6279829
Test set: Average loss: 0.8765, Accuracy: 3372/5000 (67%)
[epoch 16] loss: 0.6013600
Test set: Average loss: 0.8825, Accuracy: 3356/5000 (67%)
[epoch 17] loss: 0.5761760
Test set: Average loss: 0.8738, Accuracy: 3361/5000 (67%)
[epoch 18] loss: 0.5503908
Test set: Average loss: 0.8713, Accuracy: 3386/5000 (68%)
[epoch 19] loss: 0.5263064
Test set: Average loss: 0.8847, Accuracy: 3341/5000 (67%)
[epoch 20] loss: 0.5019694
Test set: Average loss: 0.8832, Accuracy: 3355/5000 (67%)
[epoch 21] loss: 0.4790401
Test set: Average loss: 0.8971, Accuracy: 3362/5000 (67%)
[epoch 22] loss: 0.4537924
Test set: Average loss: 0.8955, Accuracy: 3358/5000 (67%)
[epoch 23] loss: 0.4290148
Test set: Average loss: 0.8991, Accuracy: 3382/5000 (68%)
[epoch 24] loss: 0.4065694
Test set: Average loss: 0.9187, Accuracy: 3374/5000 (67%)
[epoch 25] loss: 0.3845929
Test set: Average loss: 0.9234, Accuracy: 3340/5000 (67%)
Validation:
Test set: Average loss: 0.8713, Accuracy: 3386/5000 (68%)
Test
Test set: Average loss: 0.8803, Accuracy: 3367/5000 (67%)
Test set: Average loss: 0.5112, Accuracy: 12668/15000 (84%)
## seed: 13
Validation accuracy before training:
Test set: Average loss: 1.6373, Accuracy: 837/5000 (17%)
[epoch 1] loss: 1.1943559
Test set: Average loss: 1.1019, Accuracy: 2996/5000 (60%)
[epoch 2] loss: 1.0565582
Test set: Average loss: 1.0353, Accuracy: 3109/5000 (62%)
[epoch 3] loss: 0.9920986
Test set: Average loss: 0.9951, Accuracy: 3184/5000 (64%)
[epoch 4] loss: 0.9443832
Test set: Average loss: 0.9742, Accuracy: 3216/5000 (64%)
[epoch 5] loss: 0.9049811
Test set: Average loss: 0.9488, Accuracy: 3253/5000 (65%)
[epoch 6] loss: 0.8705407
Test set: Average loss: 0.9339, Accuracy: 3279/5000 (66%)
[epoch 7] loss: 0.8374414
Test set: Average loss: 0.9238, Accuracy: 3286/5000 (66%)
[epoch 8] loss: 0.8073444
Test set: Average loss: 0.9080, Accuracy: 3311/5000 (66%)
[epoch 9] loss: 0.7768649
Test set: Average loss: 0.9051, Accuracy: 3326/5000 (67%)
[epoch 10] loss: 0.7507128
Test set: Average loss: 0.8973, Accuracy: 3341/5000 (67%)
[epoch 11] loss: 0.7241284
Test set: Average loss: 0.8945, Accuracy: 3343/5000 (67%)
[epoch 12] loss: 0.6962153
Test set: Average loss: 0.8902, Accuracy: 3366/5000 (67%)
[epoch 13] loss: 0.6709935
Test set: Average loss: 0.8873, Accuracy: 3370/5000 (67%)
[epoch 14] loss: 0.6438150
Test set: Average loss: 0.8810, Accuracy: 3356/5000 (67%)
[epoch 15] loss: 0.6176967
Test set: Average loss: 0.8817, Accuracy: 3399/5000 (68%)
[epoch 16] loss: 0.5922457
Test set: Average loss: 0.8871, Accuracy: 3360/5000 (67%)
[epoch 17] loss: 0.5656680
Test set: Average loss: 0.8951, Accuracy: 3369/5000 (67%)
[epoch 18] loss: 0.5407778
Test set: Average loss: 0.8963, Accuracy: 3355/5000 (67%)
[epoch 19] loss: 0.5157027
Test set: Average loss: 0.8878, Accuracy: 3371/5000 (67%)
[epoch 20] loss: 0.4896124
Test set: Average loss: 0.8952, Accuracy: 3373/5000 (67%)
[epoch 21] loss: 0.4653589
Test set: Average loss: 0.8950, Accuracy: 3360/5000 (67%)
[epoch 22] loss: 0.4405842
Test set: Average loss: 0.9200, Accuracy: 3329/5000 (67%)
[epoch 23] loss: 0.4180739
Test set: Average loss: 0.9144, Accuracy: 3348/5000 (67%)
[epoch 24] loss: 0.3932554
Test set: Average loss: 0.9353, Accuracy: 3328/5000 (67%)
[epoch 25] loss: 0.3727688
Test set: Average loss: 0.9306, Accuracy: 3354/5000 (67%)
Validation:
Test set: Average loss: 0.8817, Accuracy: 3399/5000 (68%)
Test
Test set: Average loss: 0.8894, Accuracy: 3327/5000 (67%)
Test set: Average loss: 0.5782, Accuracy: 12329/15000 (82%)
20000
## seed: 11
Validation accuracy before training:
Test set: Average loss: 1.6480, Accuracy: 764/5000 (15%)
[epoch 1] loss: 1.1735654
Test set: Average loss: 1.0742, Accuracy: 3087/5000 (62%)
[epoch 2] loss: 1.0306615
Test set: Average loss: 1.0082, Accuracy: 3171/5000 (63%)
[epoch 3] loss: 0.9672114
Test set: Average loss: 0.9741, Accuracy: 3208/5000 (64%)
[epoch 4] loss: 0.9226576
Test set: Average loss: 0.9526, Accuracy: 3254/5000 (65%)
[epoch 5] loss: 0.8825911
Test set: Average loss: 0.9345, Accuracy: 3263/5000 (65%)
[epoch 6] loss: 0.8489010
Test set: Average loss: 0.9211, Accuracy: 3278/5000 (66%)
[epoch 7] loss: 0.8179646
Test set: Average loss: 0.9090, Accuracy: 3289/5000 (66%)
[epoch 8] loss: 0.7873543
Test set: Average loss: 0.8905, Accuracy: 3361/5000 (67%)
[epoch 9] loss: 0.7583268
Test set: Average loss: 0.8977, Accuracy: 3311/5000 (66%)
[epoch 10] loss: 0.7309253
Test set: Average loss: 0.8748, Accuracy: 3382/5000 (68%)
[epoch 11] loss: 0.7049668
Test set: Average loss: 0.8667, Accuracy: 3402/5000 (68%)
[epoch 12] loss: 0.6801163
Test set: Average loss: 0.8741, Accuracy: 3388/5000 (68%)
[epoch 13] loss: 0.6528184
Test set: Average loss: 0.8710, Accuracy: 3413/5000 (68%)
[epoch 14] loss: 0.6270317
Test set: Average loss: 0.8658, Accuracy: 3438/5000 (69%)
[epoch 15] loss: 0.6011121
Test set: Average loss: 0.8606, Accuracy: 3421/5000 (68%)
[epoch 16] loss: 0.5756763
Test set: Average loss: 0.8658, Accuracy: 3406/5000 (68%)
[epoch 17] loss: 0.5500576
Test set: Average loss: 0.8751, Accuracy: 3410/5000 (68%)
[epoch 18] loss: 0.5278631
Test set: Average loss: 0.8750, Accuracy: 3403/5000 (68%)
[epoch 19] loss: 0.5038797
Test set: Average loss: 0.8721, Accuracy: 3397/5000 (68%)
[epoch 20] loss: 0.4777741
Test set: Average loss: 0.9044, Accuracy: 3389/5000 (68%)
[epoch 21] loss: 0.4570251
Test set: Average loss: 0.9099, Accuracy: 3371/5000 (67%)
[epoch 22] loss: 0.4322073
Test set: Average loss: 0.9005, Accuracy: 3399/5000 (68%)
[epoch 23] loss: 0.4113917
Test set: Average loss: 0.9242, Accuracy: 3352/5000 (67%)
[epoch 24] loss: 0.3891080
Test set: Average loss: 0.9265, Accuracy: 3403/5000 (68%)
[epoch 25] loss: 0.3694204
Test set: Average loss: 0.9410, Accuracy: 3397/5000 (68%)
Validation:
Test set: Average loss: 0.8658, Accuracy: 3438/5000 (69%)
Test
Test set: Average loss: 0.8735, Accuracy: 3364/5000 (67%)
Test set: Average loss: 0.5885, Accuracy: 16209/20000 (81%)
## seed: 12
Validation accuracy before training:
Test set: Average loss: 1.6238, Accuracy: 1092/5000 (22%)
[epoch 1] loss: 1.1404277
Test set: Average loss: 1.0502, Accuracy: 3068/5000 (61%)
[epoch 2] loss: 1.0083194
Test set: Average loss: 0.9895, Accuracy: 3187/5000 (64%)
[epoch 3] loss: 0.9503644
Test set: Average loss: 0.9626, Accuracy: 3232/5000 (65%)
[epoch 4] loss: 0.9065962
Test set: Average loss: 0.9417, Accuracy: 3255/5000 (65%)
[epoch 5] loss: 0.8705454
Test set: Average loss: 0.9186, Accuracy: 3307/5000 (66%)
[epoch 6] loss: 0.8375521
Test set: Average loss: 0.9105, Accuracy: 3315/5000 (66%)
[epoch 7] loss: 0.8047911
Test set: Average loss: 0.8945, Accuracy: 3349/5000 (67%)
[epoch 8] loss: 0.7745917
Test set: Average loss: 0.8871, Accuracy: 3379/5000 (68%)
[epoch 9] loss: 0.7473529
Test set: Average loss: 0.8796, Accuracy: 3380/5000 (68%)
[epoch 10] loss: 0.7179471
Test set: Average loss: 0.8710, Accuracy: 3397/5000 (68%)
[epoch 11] loss: 0.6929312
Test set: Average loss: 0.8648, Accuracy: 3412/5000 (68%)
[epoch 12] loss: 0.6654327
Test set: Average loss: 0.8662, Accuracy: 3405/5000 (68%)
[epoch 13] loss: 0.6387258
Test set: Average loss: 0.8713, Accuracy: 3377/5000 (68%)
[epoch 14] loss: 0.6123640
Test set: Average loss: 0.8589, Accuracy: 3401/5000 (68%)
[epoch 15] loss: 0.5867701
Test set: Average loss: 0.8583, Accuracy: 3440/5000 (69%)
[epoch 16] loss: 0.5625103
Test set: Average loss: 0.8636, Accuracy: 3428/5000 (69%)
[epoch 17] loss: 0.5372813
Test set: Average loss: 0.8638, Accuracy: 3442/5000 (69%)
[epoch 18] loss: 0.5101986
Test set: Average loss: 0.8720, Accuracy: 3429/5000 (69%)
[epoch 19] loss: 0.4859631
Test set: Average loss: 0.8771, Accuracy: 3430/5000 (69%)
[epoch 20] loss: 0.4615794
Test set: Average loss: 0.8872, Accuracy: 3428/5000 (69%)
[epoch 21] loss: 0.4370142
Test set: Average loss: 0.8973, Accuracy: 3412/5000 (68%)
[epoch 22] loss: 0.4162486
Test set: Average loss: 0.8999, Accuracy: 3429/5000 (69%)
[epoch 23] loss: 0.3927655
Test set: Average loss: 0.9127, Accuracy: 3415/5000 (68%)
[epoch 24] loss: 0.3705720
Test set: Average loss: 0.9272, Accuracy: 3406/5000 (68%)
[epoch 25] loss: 0.3511008
Test set: Average loss: 0.9517, Accuracy: 3375/5000 (68%)
Validation:
Test set: Average loss: 0.8638, Accuracy: 3442/5000 (69%)
Test
Test set: Average loss: 0.8856, Accuracy: 3359/5000 (67%)
Test set: Average loss: 0.4951, Accuracy: 16941/20000 (85%)
## seed: 13
Validation accuracy before training:
Test set: Average loss: 1.6200, Accuracy: 1055/5000 (21%)
[epoch 1] loss: 1.1711443
Test set: Average loss: 1.0760, Accuracy: 3073/5000 (61%)
[epoch 2] loss: 1.0277336
Test set: Average loss: 1.0128, Accuracy: 3167/5000 (63%)
[epoch 3] loss: 0.9656248
Test set: Average loss: 0.9725, Accuracy: 3224/5000 (64%)
[epoch 4] loss: 0.9187463
Test set: Average loss: 0.9517, Accuracy: 3252/5000 (65%)
[epoch 5] loss: 0.8801285
Test set: Average loss: 0.9394, Accuracy: 3238/5000 (65%)
[epoch 6] loss: 0.8468377
Test set: Average loss: 0.9159, Accuracy: 3312/5000 (66%)
[epoch 7] loss: 0.8155356
Test set: Average loss: 0.9077, Accuracy: 3327/5000 (67%)
[epoch 8] loss: 0.7873183
Test set: Average loss: 0.8946, Accuracy: 3339/5000 (67%)
[epoch 9] loss: 0.7584227
Test set: Average loss: 0.8909, Accuracy: 3336/5000 (67%)
[epoch 10] loss: 0.7296924
Test set: Average loss: 0.8864, Accuracy: 3350/5000 (67%)
[epoch 11] loss: 0.7040121
Test set: Average loss: 0.8768, Accuracy: 3400/5000 (68%)
[epoch 12] loss: 0.6776377
Test set: Average loss: 0.8767, Accuracy: 3384/5000 (68%)
[epoch 13] loss: 0.6502005
Test set: Average loss: 0.8776, Accuracy: 3394/5000 (68%)
[epoch 14] loss: 0.6246801
Test set: Average loss: 0.8703, Accuracy: 3403/5000 (68%)
[epoch 15] loss: 0.5990683
Test set: Average loss: 0.8692, Accuracy: 3427/5000 (69%)
[epoch 16] loss: 0.5725122
Test set: Average loss: 0.8767, Accuracy: 3398/5000 (68%)
[epoch 17] loss: 0.5476005
Test set: Average loss: 0.8740, Accuracy: 3407/5000 (68%)
[epoch 18] loss: 0.5237498
Test set: Average loss: 0.8758, Accuracy: 3425/5000 (68%)
[epoch 19] loss: 0.4996032
Test set: Average loss: 0.8946, Accuracy: 3388/5000 (68%)
[epoch 20] loss: 0.4740080
Test set: Average loss: 0.8932, Accuracy: 3389/5000 (68%)
[epoch 21] loss: 0.4512500
Test set: Average loss: 0.8954, Accuracy: 3416/5000 (68%)
[epoch 22] loss: 0.4282206
Test set: Average loss: 0.9103, Accuracy: 3412/5000 (68%)
[epoch 23] loss: 0.4069652
Test set: Average loss: 0.9176, Accuracy: 3399/5000 (68%)
[epoch 24] loss: 0.3837853
Test set: Average loss: 0.9190, Accuracy: 3384/5000 (68%)
[epoch 25] loss: 0.3620967
Test set: Average loss: 0.9374, Accuracy: 3381/5000 (68%)
Validation:
Test set: Average loss: 0.8692, Accuracy: 3427/5000 (69%)
Test
Test set: Average loss: 0.8869, Accuracy: 3371/5000 (67%)
Test set: Average loss: 0.5594, Accuracy: 16518/20000 (83%)
## Pre-Training BnB
Validation accuracy before training:
Test set: Average loss: 1.6186, Accuracy: 1151/5000 (23%)
[epoch 1] loss: 1.1797077
Test set: Average loss: 1.0803, Accuracy: 3073/5000 (61%)
[epoch 2] loss: 1.0398168
Test set: Average loss: 1.0189, Accuracy: 3145/5000 (63%)
[epoch 3] loss: 0.9754214
Test set: Average loss: 0.9766, Accuracy: 3227/5000 (65%)
[epoch 4] loss: 0.9274103
Test set: Average loss: 0.9521, Accuracy: 3237/5000 (65%)
[epoch 5] loss: 0.8884989
Test set: Average loss: 0.9326, Accuracy: 3277/5000 (66%)
[epoch 6] loss: 0.8508841
Test set: Average loss: 0.9202, Accuracy: 3290/5000 (66%)
[epoch 7] loss: 0.8174724
Test set: Average loss: 0.9052, Accuracy: 3305/5000 (66%)
[epoch 8] loss: 0.7863105
Test set: Average loss: 0.8977, Accuracy: 3326/5000 (67%)
[epoch 9] loss: 0.7567483
Test set: Average loss: 0.8847, Accuracy: 3377/5000 (68%)
[epoch 10] loss: 0.7280602
Test set: Average loss: 0.8749, Accuracy: 3394/5000 (68%)
[epoch 11] loss: 0.6994053
Test set: Average loss: 0.8724, Accuracy: 3392/5000 (68%)
[epoch 12] loss: 0.6728378
Test set: Average loss: 0.8680, Accuracy: 3386/5000 (68%)
[epoch 13] loss: 0.6456452
Test set: Average loss: 0.8700, Accuracy: 3395/5000 (68%)
[epoch 14] loss: 0.6197828
Test set: Average loss: 0.8679, Accuracy: 3413/5000 (68%)
[epoch 15] loss: 0.5928017
Test set: Average loss: 0.8745, Accuracy: 3397/5000 (68%)
[epoch 16] loss: 0.5667017
Test set: Average loss: 0.8782, Accuracy: 3388/5000 (68%)
[epoch 17] loss: 0.5424560
Test set: Average loss: 0.8799, Accuracy: 3420/5000 (68%)
[epoch 18] loss: 0.5170202
Test set: Average loss: 0.8905, Accuracy: 3397/5000 (68%)
[epoch 19] loss: 0.4925975
Test set: Average loss: 0.8858, Accuracy: 3416/5000 (68%)
[epoch 20] loss: 0.4679862
Test set: Average loss: 0.8942, Accuracy: 3402/5000 (68%)
[epoch 21] loss: 0.4455321
Test set: Average loss: 0.9043, Accuracy: 3407/5000 (68%)
[epoch 22] loss: 0.4228486
Test set: Average loss: 0.9230, Accuracy: 3365/5000 (67%)
[epoch 23] loss: 0.3997039
Test set: Average loss: 0.9274, Accuracy: 3399/5000 (68%)
[epoch 24] loss: 0.3785241
Test set: Average loss: 0.9424, Accuracy: 3383/5000 (68%)
[epoch 25] loss: 0.3570373
Test set: Average loss: 0.9585, Accuracy: 3352/5000 (67%)
Validation:
Test set: Average loss: 0.8799, Accuracy: 3420/5000 (68%)
Test set: Average loss: 0.8831, Accuracy: 3395/5000 (68%)
25
## seed: 11
Validation accuracy before training:
Test set: Average loss: 1.5617, Accuracy: 1550/5000 (31%)
[epoch 1] loss: 1.5475806
Test set: Average loss: 1.5571, Accuracy: 1578/5000 (32%)
[epoch 2] loss: 1.5082332
Test set: Average loss: 1.5526, Accuracy: 1605/5000 (32%)
[epoch 3] loss: 1.4700924
Test set: Average loss: 1.5483, Accuracy: 1616/5000 (32%)
[epoch 4] loss: 1.4334157
Test set: Average loss: 1.5442, Accuracy: 1634/5000 (33%)
[epoch 5] loss: 1.3983418
Test set: Average loss: 1.5402, Accuracy: 1651/5000 (33%)
[epoch 6] loss: 1.3649449
Test set: Average loss: 1.5363, Accuracy: 1670/5000 (33%)
[epoch 7] loss: 1.3332630
Test set: Average loss: 1.5325, Accuracy: 1688/5000 (34%)
[epoch 8] loss: 1.3032968
Test set: Average loss: 1.5288, Accuracy: 1714/5000 (34%)
[epoch 9] loss: 1.2749946
Test set: Average loss: 1.5253, Accuracy: 1720/5000 (34%)
[epoch 10] loss: 1.2482504
Test set: Average loss: 1.5219, Accuracy: 1745/5000 (35%)
[epoch 11] loss: 1.2229216
Test set: Average loss: 1.5186, Accuracy: 1757/5000 (35%)
[epoch 12] loss: 1.1988629
Test set: Average loss: 1.5155, Accuracy: 1779/5000 (36%)
[epoch 13] loss: 1.1759582
Test set: Average loss: 1.5125, Accuracy: 1800/5000 (36%)
[epoch 14] loss: 1.1541349
Test set: Average loss: 1.5096, Accuracy: 1828/5000 (37%)
[epoch 15] loss: 1.1333542
Test set: Average loss: 1.5069, Accuracy: 1850/5000 (37%)
[epoch 16] loss: 1.1135898
Test set: Average loss: 1.5042, Accuracy: 1871/5000 (37%)
[epoch 17] loss: 1.0948117
Test set: Average loss: 1.5017, Accuracy: 1883/5000 (38%)
[epoch 18] loss: 1.0769840
Test set: Average loss: 1.4993, Accuracy: 1895/5000 (38%)
[epoch 19] loss: 1.0600702
Test set: Average loss: 1.4970, Accuracy: 1908/5000 (38%)
[epoch 20] loss: 1.0440360
Test set: Average loss: 1.4948, Accuracy: 1923/5000 (38%)
[epoch 21] loss: 1.0288455
Test set: Average loss: 1.4926, Accuracy: 1933/5000 (39%)
[epoch 22] loss: 1.0144563
Test set: Average loss: 1.4906, Accuracy: 1949/5000 (39%)
[epoch 23] loss: 1.0008166
Test set: Average loss: 1.4886, Accuracy: 1957/5000 (39%)
[epoch 24] loss: 0.9878698
Test set: Average loss: 1.4868, Accuracy: 1963/5000 (39%)
[epoch 25] loss: 0.9755608
Test set: Average loss: 1.4850, Accuracy: 1963/5000 (39%)
Validation:
Test set: Average loss: 1.4850, Accuracy: 1963/5000 (39%)
Test
Test set: Average loss: 1.4911, Accuracy: 1907/5000 (38%)
Test set: Average loss: 0.9638, Accuracy: 25/25 (100%)
## seed: 12
Validation accuracy before training:
Test set: Average loss: 1.6229, Accuracy: 976/5000 (20%)
[epoch 1] loss: 1.6048840
Test set: Average loss: 1.6159, Accuracy: 1008/5000 (20%)
[epoch 2] loss: 1.5664345
Test set: Average loss: 1.6091, Accuracy: 1026/5000 (21%)
[epoch 3] loss: 1.5291739
Test set: Average loss: 1.6025, Accuracy: 1063/5000 (21%)
[epoch 4] loss: 1.4932039
Test set: Average loss: 1.5959, Accuracy: 1084/5000 (22%)
[epoch 5] loss: 1.4585223
Test set: Average loss: 1.5894, Accuracy: 1111/5000 (22%)
[epoch 6] loss: 1.4250983
Test set: Average loss: 1.5829, Accuracy: 1136/5000 (23%)
[epoch 7] loss: 1.3928844
Test set: Average loss: 1.5766, Accuracy: 1179/5000 (24%)
[epoch 8] loss: 1.3618277
Test set: Average loss: 1.5704, Accuracy: 1206/5000 (24%)
[epoch 9] loss: 1.3319032
Test set: Average loss: 1.5643, Accuracy: 1235/5000 (25%)
[epoch 10] loss: 1.3031268
Test set: Average loss: 1.5583, Accuracy: 1270/5000 (25%)
[epoch 11] loss: 1.2755175
Test set: Average loss: 1.5524, Accuracy: 1307/5000 (26%)
[epoch 12] loss: 1.2490624
Test set: Average loss: 1.5467, Accuracy: 1335/5000 (27%)
[epoch 13] loss: 1.2237306
Test set: Average loss: 1.5412, Accuracy: 1383/5000 (28%)
[epoch 14] loss: 1.1995208
Test set: Average loss: 1.5358, Accuracy: 1422/5000 (28%)
[epoch 15] loss: 1.1764772
Test set: Average loss: 1.5306, Accuracy: 1470/5000 (29%)
[epoch 16] loss: 1.1546562
Test set: Average loss: 1.5255, Accuracy: 1500/5000 (30%)
[epoch 17] loss: 1.1340758
Test set: Average loss: 1.5207, Accuracy: 1525/5000 (30%)
[epoch 18] loss: 1.1147020
Test set: Average loss: 1.5162, Accuracy: 1558/5000 (31%)
[epoch 19] loss: 1.0964646
Test set: Average loss: 1.5119, Accuracy: 1588/5000 (32%)
[epoch 20] loss: 1.0792736
Test set: Average loss: 1.5078, Accuracy: 1608/5000 (32%)
[epoch 21] loss: 1.0630300
Test set: Average loss: 1.5040, Accuracy: 1632/5000 (33%)
[epoch 22] loss: 1.0476326
Test set: Average loss: 1.5005, Accuracy: 1645/5000 (33%)
[epoch 23] loss: 1.0329874
Test set: Average loss: 1.4972, Accuracy: 1668/5000 (33%)
[epoch 24] loss: 1.0190121
Test set: Average loss: 1.4941, Accuracy: 1696/5000 (34%)
[epoch 25] loss: 1.0056425
Test set: Average loss: 1.4912, Accuracy: 1712/5000 (34%)
Validation:
Test set: Average loss: 1.4912, Accuracy: 1712/5000 (34%)
Test
Test set: Average loss: 1.4957, Accuracy: 1690/5000 (34%)
Test set: Average loss: 0.9928, Accuracy: 24/25 (96%)
## seed: 13
Validation accuracy before training:
Test set: Average loss: 1.7350, Accuracy: 688/5000 (14%)
[epoch 1] loss: 1.7454007
Test set: Average loss: 1.7276, Accuracy: 705/5000 (14%)
[epoch 2] loss: 1.7064755
Test set: Average loss: 1.7202, Accuracy: 718/5000 (14%)
[epoch 3] loss: 1.6679476
Test set: Average loss: 1.7129, Accuracy: 732/5000 (15%)
[epoch 4] loss: 1.6302047
Test set: Average loss: 1.7055, Accuracy: 756/5000 (15%)
[epoch 5] loss: 1.5936607
Test set: Average loss: 1.6982, Accuracy: 778/5000 (16%)
[epoch 6] loss: 1.5587106
Test set: Average loss: 1.6910, Accuracy: 800/5000 (16%)
[epoch 7] loss: 1.5256531
Test set: Average loss: 1.6840, Accuracy: 823/5000 (16%)
[epoch 8] loss: 1.4946421
Test set: Average loss: 1.6770, Accuracy: 853/5000 (17%)
[epoch 9] loss: 1.4656780
Test set: Average loss: 1.6702, Accuracy: 887/5000 (18%)
[epoch 10] loss: 1.4386281
Test set: Average loss: 1.6635, Accuracy: 910/5000 (18%)
[epoch 11] loss: 1.4132850
Test set: Average loss: 1.6569, Accuracy: 954/5000 (19%)
[epoch 12] loss: 1.3894360
Test set: Average loss: 1.6505, Accuracy: 998/5000 (20%)
[epoch 13] loss: 1.3669078
Test set: Average loss: 1.6443, Accuracy: 1022/5000 (20%)
[epoch 14] loss: 1.3455651
Test set: Average loss: 1.6383, Accuracy: 1060/5000 (21%)
[epoch 15] loss: 1.3252872
Test set: Average loss: 1.6325, Accuracy: 1091/5000 (22%)
[epoch 16] loss: 1.3059518
Test set: Average loss: 1.6268, Accuracy: 1128/5000 (23%)
[epoch 17] loss: 1.2874420
Test set: Average loss: 1.6214, Accuracy: 1160/5000 (23%)
[epoch 18] loss: 1.2696606
Test set: Average loss: 1.6162, Accuracy: 1181/5000 (24%)
[epoch 19] loss: 1.2525419
Test set: Average loss: 1.6112, Accuracy: 1215/5000 (24%)
[epoch 20] loss: 1.2360435
Test set: Average loss: 1.6063, Accuracy: 1237/5000 (25%)
[epoch 21] loss: 1.2201333
Test set: Average loss: 1.6017, Accuracy: 1270/5000 (25%)
[epoch 22] loss: 1.2047805
Test set: Average loss: 1.5973, Accuracy: 1304/5000 (26%)
[epoch 23] loss: 1.1899534
Test set: Average loss: 1.5930, Accuracy: 1335/5000 (27%)
[epoch 24] loss: 1.1756253
Test set: Average loss: 1.5890, Accuracy: 1356/5000 (27%)
[epoch 25] loss: 1.1617725
Test set: Average loss: 1.5851, Accuracy: 1379/5000 (28%)
Validation:
Test set: Average loss: 1.5851, Accuracy: 1379/5000 (28%)
Test
Test set: Average loss: 1.5906, Accuracy: 1319/5000 (26%)
Test set: Average loss: 1.1484, Accuracy: 21/25 (84%)
50
## seed: 11
Validation accuracy before training:
Test set: Average loss: 1.5124, Accuracy: 1926/5000 (39%)
[epoch 1] loss: 1.4326680
Test set: Average loss: 1.4990, Accuracy: 1958/5000 (39%)
[epoch 2] loss: 1.3633156
Test set: Average loss: 1.4875, Accuracy: 1989/5000 (40%)
[epoch 3] loss: 1.3307073
Test set: Average loss: 1.4773, Accuracy: 2013/5000 (40%)
[epoch 4] loss: 1.2910377
Test set: Average loss: 1.4685, Accuracy: 2028/5000 (41%)
[epoch 5] loss: 1.2490000
Test set: Average loss: 1.4610, Accuracy: 2038/5000 (41%)
[epoch 6] loss: 1.2341793
Test set: Average loss: 1.4544, Accuracy: 2041/5000 (41%)
[epoch 7] loss: 1.1888431
Test set: Average loss: 1.4482, Accuracy: 2048/5000 (41%)
[epoch 8] loss: 1.1455225
Test set: Average loss: 1.4426, Accuracy: 2053/5000 (41%)
[epoch 9] loss: 1.1411310
Test set: Average loss: 1.4373, Accuracy: 2057/5000 (41%)
[epoch 10] loss: 1.1149133
Test set: Average loss: 1.4326, Accuracy: 2056/5000 (41%)
[epoch 11] loss: 1.0802903
Test set: Average loss: 1.4282, Accuracy: 2076/5000 (42%)
[epoch 12] loss: 1.0514168
Test set: Average loss: 1.4242, Accuracy: 2083/5000 (42%)
[epoch 13] loss: 1.0573305
Epoch 12: reducing learning rate of group 0 to 5.0000e-06.
Test set: Average loss: 1.4206, Accuracy: 2090/5000 (42%)
[epoch 14] loss: 1.0182979
Test set: Average loss: 1.4203, Accuracy: 2090/5000 (42%)
[epoch 15] loss: 1.0218436
Epoch 14: reducing learning rate of group 0 to 5.0000e-07.
Test set: Average loss: 1.4199, Accuracy: 2094/5000 (42%)
[epoch 16] loss: 1.0257072
Epoch 15: reducing learning rate of group 0 to 5.0000e-08.
Test set: Average loss: 1.4199, Accuracy: 2094/5000 (42%)
[epoch 17] loss: 1.0262394
Epoch 16: reducing learning rate of group 0 to 5.0000e-09.
Test set: Average loss: 1.4199, Accuracy: 2094/5000 (42%)
[epoch 18] loss: 1.0435623
Epoch 17: reducing learning rate of group 0 to 5.0000e-10.
Test set: Average loss: 1.4199, Accuracy: 2094/5000 (42%)
[epoch 19] loss: 1.0210228
Epoch 18: reducing learning rate of group 0 to 5.0000e-11.
Test set: Average loss: 1.4199, Accuracy: 2094/5000 (42%)
[epoch 20] loss: 1.0316303
Epoch 19: reducing learning rate of group 0 to 5.0000e-12.
Test set: Average loss: 1.4199, Accuracy: 2094/5000 (42%)
[epoch 21] loss: 1.0332733
Epoch 20: reducing learning rate of group 0 to 5.0000e-13.
Test set: Average loss: 1.4199, Accuracy: 2094/5000 (42%)
[epoch 22] loss: 1.0096845
Test set: Average loss: 1.4199, Accuracy: 2094/5000 (42%)
[epoch 23] loss: 1.0036551
Test set: Average loss: 1.4199, Accuracy: 2094/5000 (42%)
[epoch 24] loss: 1.0043332
Epoch 23: reducing learning rate of group 0 to 5.0000e-14.
Test set: Average loss: 1.4199, Accuracy: 2094/5000 (42%)
[epoch 25] loss: 1.0294735
Epoch 24: reducing learning rate of group 0 to 5.0000e-15.
Test set: Average loss: 1.4199, Accuracy: 2094/5000 (42%)
Validation:
Test set: Average loss: 1.4199, Accuracy: 2094/5000 (42%)
Test
Test set: Average loss: 1.4236, Accuracy: 2073/5000 (41%)
Test set: Average loss: 1.0274, Accuracy: 36/50 (72%)
## seed: 12
Validation accuracy before training:
Test set: Average loss: 1.6439, Accuracy: 1110/5000 (22%)
[epoch 1] loss: 1.6279087
Test set: Average loss: 1.6280, Accuracy: 1181/5000 (24%)
[epoch 2] loss: 1.5665637
Test set: Average loss: 1.6145, Accuracy: 1244/5000 (25%)
[epoch 3] loss: 1.5290592
Test set: Average loss: 1.6023, Accuracy: 1298/5000 (26%)
[epoch 4] loss: 1.4797144
Test set: Average loss: 1.5904, Accuracy: 1363/5000 (27%)
[epoch 5] loss: 1.4234129
Test set: Average loss: 1.5793, Accuracy: 1408/5000 (28%)
[epoch 6] loss: 1.4021909
Test set: Average loss: 1.5691, Accuracy: 1448/5000 (29%)
[epoch 7] loss: 1.3472804
Test set: Average loss: 1.5595, Accuracy: 1502/5000 (30%)
[epoch 8] loss: 1.3361173
Test set: Average loss: 1.5507, Accuracy: 1562/5000 (31%)
[epoch 9] loss: 1.3094700
Test set: Average loss: 1.5426, Accuracy: 1604/5000 (32%)
[epoch 10] loss: 1.2683755
Test set: Average loss: 1.5353, Accuracy: 1649/5000 (33%)
[epoch 11] loss: 1.2357145
Test set: Average loss: 1.5285, Accuracy: 1677/5000 (34%)
[epoch 12] loss: 1.2407138
Epoch 11: reducing learning rate of group 0 to 5.0000e-06.
Test set: Average loss: 1.5222, Accuracy: 1716/5000 (34%)
[epoch 13] loss: 1.2148446
Test set: Average loss: 1.5216, Accuracy: 1720/5000 (34%)
[epoch 14] loss: 1.2309765
Epoch 13: reducing learning rate of group 0 to 5.0000e-07.
Test set: Average loss: 1.5211, Accuracy: 1732/5000 (35%)
[epoch 15] loss: 1.2114019
Test set: Average loss: 1.5210, Accuracy: 1732/5000 (35%)
[epoch 16] loss: 1.2067239
Test set: Average loss: 1.5209, Accuracy: 1732/5000 (35%)
[epoch 17] loss: 1.2119175
Epoch 16: reducing learning rate of group 0 to 5.0000e-08.
Test set: Average loss: 1.5209, Accuracy: 1733/5000 (35%)
[epoch 18] loss: 1.2294748
Epoch 17: reducing learning rate of group 0 to 5.0000e-09.
Test set: Average loss: 1.5209, Accuracy: 1734/5000 (35%)
[epoch 19] loss: 1.1845745
Test set: Average loss: 1.5209, Accuracy: 1734/5000 (35%)
[epoch 20] loss: 1.2161145
Epoch 19: reducing learning rate of group 0 to 5.0000e-10.
Test set: Average loss: 1.5209, Accuracy: 1734/5000 (35%)
[epoch 21] loss: 1.1869274
Epoch 20: reducing learning rate of group 0 to 5.0000e-11.
Test set: Average loss: 1.5209, Accuracy: 1734/5000 (35%)
[epoch 22] loss: 1.2196496
Epoch 21: reducing learning rate of group 0 to 5.0000e-12.
Test set: Average loss: 1.5209, Accuracy: 1734/5000 (35%)
[epoch 23] loss: 1.2360478
Epoch 22: reducing learning rate of group 0 to 5.0000e-13.
Test set: Average loss: 1.5209, Accuracy: 1734/5000 (35%)
[epoch 24] loss: 1.2206387
Epoch 23: reducing learning rate of group 0 to 5.0000e-14.
Test set: Average loss: 1.5209, Accuracy: 1734/5000 (35%)
[epoch 25] loss: 1.2122398
Epoch 24: reducing learning rate of group 0 to 5.0000e-15.
Test set: Average loss: 1.5209, Accuracy: 1734/5000 (35%)
Validation:
Test set: Average loss: 1.5209, Accuracy: 1734/5000 (35%)
Test
Test set: Average loss: 1.5278, Accuracy: 1679/5000 (34%)
Test set: Average loss: 1.2108, Accuracy: 34/50 (68%)
## seed: 13
Validation accuracy before training:
Test set: Average loss: 1.7559, Accuracy: 683/5000 (14%)
[epoch 1] loss: 1.7814206
Test set: Average loss: 1.7343, Accuracy: 723/5000 (14%)
[epoch 2] loss: 1.7260445
Test set: Average loss: 1.7165, Accuracy: 752/5000 (15%)
[epoch 3] loss: 1.6494607
Test set: Average loss: 1.6986, Accuracy: 795/5000 (16%)
[epoch 4] loss: 1.6076436
Test set: Average loss: 1.6818, Accuracy: 849/5000 (17%)
[epoch 5] loss: 1.5383638
Test set: Average loss: 1.6661, Accuracy: 919/5000 (18%)
[epoch 6] loss: 1.4875141
Test set: Average loss: 1.6512, Accuracy: 997/5000 (20%)
[epoch 7] loss: 1.4592890
Test set: Average loss: 1.6374, Accuracy: 1072/5000 (21%)
[epoch 8] loss: 1.4186898
Test set: Average loss: 1.6249, Accuracy: 1144/5000 (23%)
[epoch 9] loss: 1.3817707
Test set: Average loss: 1.6131, Accuracy: 1209/5000 (24%)
[epoch 10] loss: 1.3229644
Test set: Average loss: 1.6018, Accuracy: 1281/5000 (26%)
[epoch 11] loss: 1.3070660
Test set: Average loss: 1.5911, Accuracy: 1347/5000 (27%)
[epoch 12] loss: 1.2664788
Test set: Average loss: 1.5813, Accuracy: 1394/5000 (28%)
[epoch 13] loss: 1.2386913
Test set: Average loss: 1.5723, Accuracy: 1438/5000 (29%)
[epoch 14] loss: 1.2135784
Test set: Average loss: 1.5638, Accuracy: 1495/5000 (30%)
[epoch 15] loss: 1.1735127
Test set: Average loss: 1.5560, Accuracy: 1529/5000 (31%)
[epoch 16] loss: 1.1609400
Test set: Average loss: 1.5491, Accuracy: 1564/5000 (31%)
[epoch 17] loss: 1.1290093
Test set: Average loss: 1.5425, Accuracy: 1598/5000 (32%)
[epoch 18] loss: 1.1256208
Test set: Average loss: 1.5363, Accuracy: 1628/5000 (33%)
[epoch 19] loss: 1.0907519
Test set: Average loss: 1.5305, Accuracy: 1645/5000 (33%)
[epoch 20] loss: 1.0728128
Test set: Average loss: 1.5252, Accuracy: 1672/5000 (33%)
[epoch 21] loss: 1.0307616
Test set: Average loss: 1.5202, Accuracy: 1697/5000 (34%)
[epoch 22] loss: 1.0183032
Test set: Average loss: 1.5155, Accuracy: 1718/5000 (34%)
[epoch 23] loss: 1.0184556
Epoch 22: reducing learning rate of group 0 to 5.0000e-06.
Test set: Average loss: 1.5111, Accuracy: 1739/5000 (35%)
[epoch 24] loss: 0.9923122
Test set: Average loss: 1.5107, Accuracy: 1741/5000 (35%)
[epoch 25] loss: 1.0035827
Epoch 24: reducing learning rate of group 0 to 5.0000e-07.
Test set: Average loss: 1.5103, Accuracy: 1740/5000 (35%)
Validation:
Test set: Average loss: 1.5107, Accuracy: 1741/5000 (35%)
Test
Test set: Average loss: 1.5183, Accuracy: 1707/5000 (34%)
Test set: Average loss: 0.9989, Accuracy: 44/50 (88%)
100
## seed: 11
Validation accuracy before training:
Test set: Average loss: 1.6875, Accuracy: 787/5000 (16%)
[epoch 1] loss: 1.6664025
Test set: Average loss: 1.6575, Accuracy: 979/5000 (20%)
[epoch 2] loss: 1.5816182
Test set: Average loss: 1.6354, Accuracy: 1159/5000 (23%)
[epoch 3] loss: 1.5064435
Test set: Average loss: 1.6148, Accuracy: 1318/5000 (26%)
[epoch 4] loss: 1.4425151
Test set: Average loss: 1.5958, Accuracy: 1432/5000 (29%)
[epoch 5] loss: 1.4344887
Test set: Average loss: 1.5791, Accuracy: 1555/5000 (31%)
[epoch 6] loss: 1.3713067
Test set: Average loss: 1.5653, Accuracy: 1634/5000 (33%)
[epoch 7] loss: 1.3539754
Test set: Average loss: 1.5540, Accuracy: 1686/5000 (34%)
[epoch 8] loss: 1.3164683
Test set: Average loss: 1.5438, Accuracy: 1722/5000 (34%)
[epoch 9] loss: 1.3006663
Test set: Average loss: 1.5348, Accuracy: 1779/5000 (36%)
[epoch 10] loss: 1.2861579
Test set: Average loss: 1.5264, Accuracy: 1825/5000 (36%)
[epoch 11] loss: 1.2199320
Test set: Average loss: 1.5198, Accuracy: 1878/5000 (38%)
[epoch 12] loss: 1.2197068
Test set: Average loss: 1.5135, Accuracy: 1914/5000 (38%)
[epoch 13] loss: 1.1853555
Test set: Average loss: 1.5073, Accuracy: 1950/5000 (39%)
[epoch 14] loss: 1.1739526
Test set: Average loss: 1.5004, Accuracy: 1969/5000 (39%)
[epoch 15] loss: 1.1787743
Epoch 14: reducing learning rate of group 0 to 5.0000e-06.
Test set: Average loss: 1.4944, Accuracy: 1995/5000 (40%)
[epoch 16] loss: 1.1978033
Epoch 15: reducing learning rate of group 0 to 5.0000e-07.
Test set: Average loss: 1.4939, Accuracy: 1993/5000 (40%)
[epoch 17] loss: 1.1935944
Epoch 16: reducing learning rate of group 0 to 5.0000e-08.
Test set: Average loss: 1.4938, Accuracy: 1992/5000 (40%)
[epoch 18] loss: 1.1838221
Epoch 17: reducing learning rate of group 0 to 5.0000e-09.
Test set: Average loss: 1.4938, Accuracy: 1992/5000 (40%)
[epoch 19] loss: 1.1998366
Epoch 18: reducing learning rate of group 0 to 5.0000e-10.
Test set: Average loss: 1.4938, Accuracy: 1992/5000 (40%)
[epoch 20] loss: 1.1493008
Test set: Average loss: 1.4938, Accuracy: 1992/5000 (40%)
[epoch 21] loss: 1.1000515
Test set: Average loss: 1.4938, Accuracy: 1992/5000 (40%)
[epoch 22] loss: 1.1826910
Epoch 21: reducing learning rate of group 0 to 5.0000e-11.
Test set: Average loss: 1.4938, Accuracy: 1992/5000 (40%)
[epoch 23] loss: 1.1357990
Epoch 22: reducing learning rate of group 0 to 5.0000e-12.
Test set: Average loss: 1.4938, Accuracy: 1992/5000 (40%)
[epoch 24] loss: 1.1257573
Epoch 23: reducing learning rate of group 0 to 5.0000e-13.
Test set: Average loss: 1.4938, Accuracy: 1992/5000 (40%)
[epoch 25] loss: 1.1334418
Epoch 24: reducing learning rate of group 0 to 5.0000e-14.
Test set: Average loss: 1.4938, Accuracy: 1992/5000 (40%)
Validation:
Test set: Average loss: 1.4944, Accuracy: 1995/5000 (40%)
Test
Test set: Average loss: 1.5040, Accuracy: 1944/5000 (39%)
Test set: Average loss: 1.1594, Accuracy: 72/100 (72%)
## seed: 12
Validation accuracy before training:
Test set: Average loss: 1.6326, Accuracy: 1087/5000 (22%)
[epoch 1] loss: 1.5973053
Test set: Average loss: 1.6083, Accuracy: 1269/5000 (25%)
[epoch 2] loss: 1.5766703
Test set: Average loss: 1.5898, Accuracy: 1380/5000 (28%)
[epoch 3] loss: 1.4709285
Test set: Average loss: 1.5734, Accuracy: 1469/5000 (29%)
[epoch 4] loss: 1.4492471
Test set: Average loss: 1.5584, Accuracy: 1537/5000 (31%)
[epoch 5] loss: 1.3526558
Test set: Average loss: 1.5442, Accuracy: 1607/5000 (32%)
[epoch 6] loss: 1.3981825
Epoch 5: reducing learning rate of group 0 to 5.0000e-06.
Test set: Average loss: 1.5315, Accuracy: 1668/5000 (33%)
[epoch 7] loss: 1.3225463
Test set: Average loss: 1.5302, Accuracy: 1678/5000 (34%)
[epoch 8] loss: 1.3423528
Epoch 7: reducing learning rate of group 0 to 5.0000e-07.
Test set: Average loss: 1.5288, Accuracy: 1689/5000 (34%)
[epoch 9] loss: 1.3934437
Epoch 8: reducing learning rate of group 0 to 5.0000e-08.
Test set: Average loss: 1.5286, Accuracy: 1689/5000 (34%)
[epoch 10] loss: 1.4059203
Epoch 9: reducing learning rate of group 0 to 5.0000e-09.
Test set: Average loss: 1.5286, Accuracy: 1689/5000 (34%)
[epoch 11] loss: 1.3222798
Test set: Average loss: 1.5286, Accuracy: 1689/5000 (34%)
[epoch 12] loss: 1.3717814
Epoch 11: reducing learning rate of group 0 to 5.0000e-10.
Test set: Average loss: 1.5286, Accuracy: 1689/5000 (34%)
[epoch 13] loss: 1.3378349
Epoch 12: reducing learning rate of group 0 to 5.0000e-11.
Test set: Average loss: 1.5286, Accuracy: 1689/5000 (34%)
[epoch 14] loss: 1.3382907
Epoch 13: reducing learning rate of group 0 to 5.0000e-12.
Test set: Average loss: 1.5286, Accuracy: 1689/5000 (34%)
[epoch 15] loss: 1.3396642
Epoch 14: reducing learning rate of group 0 to 5.0000e-13.
Test set: Average loss: 1.5286, Accuracy: 1689/5000 (34%)
[epoch 16] loss: 1.3322961
Epoch 15: reducing learning rate of group 0 to 5.0000e-14.
Test set: Average loss: 1.5286, Accuracy: 1689/5000 (34%)
[epoch 17] loss: 1.2994465
Test set: Average loss: 1.5286, Accuracy: 1689/5000 (34%)
[epoch 18] loss: 1.3492271
Epoch 17: reducing learning rate of group 0 to 5.0000e-15.
Test set: Average loss: 1.5286, Accuracy: 1689/5000 (34%)
[epoch 19] loss: 1.3970428
Epoch 18: reducing learning rate of group 0 to 5.0000e-16.
Test set: Average loss: 1.5286, Accuracy: 1689/5000 (34%)
[epoch 20] loss: 1.3339716
Epoch 19: reducing learning rate of group 0 to 5.0000e-17.
Test set: Average loss: 1.5286, Accuracy: 1689/5000 (34%)
[epoch 21] loss: 1.3704039
Epoch 20: reducing learning rate of group 0 to 5.0000e-18.
Test set: Average loss: 1.5286, Accuracy: 1689/5000 (34%)
[epoch 22] loss: 1.3721820
Epoch 21: reducing learning rate of group 0 to 5.0000e-19.
Test set: Average loss: 1.5286, Accuracy: 1689/5000 (34%)
[epoch 23] loss: 1.3310869
Epoch 22: reducing learning rate of group 0 to 5.0000e-20.
Test set: Average loss: 1.5286, Accuracy: 1689/5000 (34%)
[epoch 24] loss: 1.3135657
Epoch 23: reducing learning rate of group 0 to 5.0000e-21.
Test set: Average loss: 1.5286, Accuracy: 1689/5000 (34%)
[epoch 25] loss: 1.3647844
Epoch 24: reducing learning rate of group 0 to 5.0000e-22.
Test set: Average loss: 1.5286, Accuracy: 1689/5000 (34%)
Validation:
Test set: Average loss: 1.5286, Accuracy: 1689/5000 (34%)
Test
Test set: Average loss: 1.5303, Accuracy: 1612/5000 (32%)
Test set: Average loss: 1.3321, Accuracy: 61/100 (61%)
## seed: 13
Validation accuracy before training:
Test set: Average loss: 1.6718, Accuracy: 644/5000 (13%)
[epoch 1] loss: 1.6317462
Test set: Average loss: 1.6489, Accuracy: 762/5000 (15%)
[epoch 2] loss: 1.5352804
Test set: Average loss: 1.6284, Accuracy: 909/5000 (18%)
[epoch 3] loss: 1.5149220
Test set: Average loss: 1.6100, Accuracy: 1033/5000 (21%)
[epoch 4] loss: 1.4869729
Test set: Average loss: 1.5934, Accuracy: 1157/5000 (23%)
[epoch 5] loss: 1.4147576
Test set: Average loss: 1.5774, Accuracy: 1295/5000 (26%)
[epoch 6] loss: 1.4153510
Epoch 5: reducing learning rate of group 0 to 5.0000e-06.
Test set: Average loss: 1.5616, Accuracy: 1373/5000 (27%)
[epoch 7] loss: 1.3696275
Test set: Average loss: 1.5602, Accuracy: 1384/5000 (28%)
[epoch 8] loss: 1.3585598
Test set: Average loss: 1.5589, Accuracy: 1397/5000 (28%)
[epoch 9] loss: 1.3432553
Test set: Average loss: 1.5576, Accuracy: 1402/5000 (28%)
[epoch 10] loss: 1.3046945
Test set: Average loss: 1.5563, Accuracy: 1408/5000 (28%)
[epoch 11] loss: 1.3606060
Epoch 10: reducing learning rate of group 0 to 5.0000e-07.
Test set: Average loss: 1.5551, Accuracy: 1419/5000 (28%)
[epoch 12] loss: 1.3663684
Epoch 11: reducing learning rate of group 0 to 5.0000e-08.
Test set: Average loss: 1.5549, Accuracy: 1421/5000 (28%)
[epoch 13] loss: 1.3730429
Epoch 12: reducing learning rate of group 0 to 5.0000e-09.
Test set: Average loss: 1.5549, Accuracy: 1421/5000 (28%)
[epoch 14] loss: 1.3940772
Epoch 13: reducing learning rate of group 0 to 5.0000e-10.
Test set: Average loss: 1.5549, Accuracy: 1421/5000 (28%)
[epoch 15] loss: 1.3419831
Epoch 14: reducing learning rate of group 0 to 5.0000e-11.
Test set: Average loss: 1.5549, Accuracy: 1421/5000 (28%)
[epoch 16] loss: 1.3303519
Epoch 15: reducing learning rate of group 0 to 5.0000e-12.
Test set: Average loss: 1.5549, Accuracy: 1421/5000 (28%)
[epoch 17] loss: 1.3509676
Epoch 16: reducing learning rate of group 0 to 5.0000e-13.
Test set: Average loss: 1.5549, Accuracy: 1421/5000 (28%)
[epoch 18] loss: 1.4014442
Epoch 17: reducing learning rate of group 0 to 5.0000e-14.
Test set: Average loss: 1.5549, Accuracy: 1421/5000 (28%)
[epoch 19] loss: 1.3807798
Epoch 18: reducing learning rate of group 0 to 5.0000e-15.
Test set: Average loss: 1.5549, Accuracy: 1421/5000 (28%)
[epoch 20] loss: 1.3438941
Epoch 19: reducing learning rate of group 0 to 5.0000e-16.
Test set: Average loss: 1.5549, Accuracy: 1421/5000 (28%)
[epoch 21] loss: 1.3129411
Epoch 20: reducing learning rate of group 0 to 5.0000e-17.
Test set: Average loss: 1.5549, Accuracy: 1421/5000 (28%)
[epoch 22] loss: 1.3651591
Epoch 21: reducing learning rate of group 0 to 5.0000e-18.
Test set: Average loss: 1.5549, Accuracy: 1421/5000 (28%)
[epoch 23] loss: 1.3874209
Epoch 22: reducing learning rate of group 0 to 5.0000e-19.
Test set: Average loss: 1.5549, Accuracy: 1421/5000 (28%)
[epoch 24] loss: 1.3528818
Epoch 23: reducing learning rate of group 0 to 5.0000e-20.
Test set: Average loss: 1.5549, Accuracy: 1421/5000 (28%)
[epoch 25] loss: 1.3272347
Epoch 24: reducing learning rate of group 0 to 5.0000e-21.
Test set: Average loss: 1.5549, Accuracy: 1421/5000 (28%)
Validation:
Test set: Average loss: 1.5549, Accuracy: 1421/5000 (28%)
Test
Test set: Average loss: 1.5671, Accuracy: 1393/5000 (28%)
Test set: Average loss: 1.3533, Accuracy: 54/100 (54%)
250
## seed: 11
Validation accuracy before training:
Test set: Average loss: 1.6352, Accuracy: 653/5000 (13%)
[epoch 1] loss: 1.6187073
Test set: Average loss: 1.5714, Accuracy: 997/5000 (20%)
[epoch 2] loss: 1.5296350
Test set: Average loss: 1.5218, Accuracy: 1411/5000 (28%)
[epoch 3] loss: 1.4641100
Test set: Average loss: 1.4890, Accuracy: 1608/5000 (32%)
[epoch 4] loss: 1.4143307
Test set: Average loss: 1.4629, Accuracy: 1750/5000 (35%)
[epoch 5] loss: 1.3661209
Test set: Average loss: 1.4402, Accuracy: 1876/5000 (38%)
[epoch 6] loss: 1.3255224
Test set: Average loss: 1.4202, Accuracy: 1992/5000 (40%)
[epoch 7] loss: 1.2848183
Test set: Average loss: 1.4039, Accuracy: 2078/5000 (42%)
[epoch 8] loss: 1.2533086
Test set: Average loss: 1.3890, Accuracy: 2163/5000 (43%)
[epoch 9] loss: 1.2180940
Test set: Average loss: 1.3759, Accuracy: 2230/5000 (45%)
[epoch 10] loss: 1.1857771
Test set: Average loss: 1.3641, Accuracy: 2300/5000 (46%)
[epoch 11] loss: 1.1583533
Test set: Average loss: 1.3519, Accuracy: 2350/5000 (47%)
[epoch 12] loss: 1.1316033
Test set: Average loss: 1.3424, Accuracy: 2395/5000 (48%)
[epoch 13] loss: 1.1071690
Test set: Average loss: 1.3338, Accuracy: 2443/5000 (49%)
[epoch 14] loss: 1.0819347
Test set: Average loss: 1.3248, Accuracy: 2461/5000 (49%)
[epoch 15] loss: 1.0607760
Test set: Average loss: 1.3174, Accuracy: 2484/5000 (50%)
[epoch 16] loss: 1.0396404
Test set: Average loss: 1.3097, Accuracy: 2512/5000 (50%)
[epoch 17] loss: 1.0195509
Test set: Average loss: 1.3038, Accuracy: 2517/5000 (50%)
[epoch 18] loss: 0.9975272
Test set: Average loss: 1.2982, Accuracy: 2538/5000 (51%)
[epoch 19] loss: 0.9791908
Test set: Average loss: 1.2919, Accuracy: 2563/5000 (51%)
[epoch 20] loss: 0.9621700
Test set: Average loss: 1.2861, Accuracy: 2589/5000 (52%)
[epoch 21] loss: 0.9456500
Test set: Average loss: 1.2813, Accuracy: 2590/5000 (52%)
[epoch 22] loss: 0.9287428
Test set: Average loss: 1.2772, Accuracy: 2591/5000 (52%)
[epoch 23] loss: 0.9124917
Test set: Average loss: 1.2720, Accuracy: 2621/5000 (52%)
[epoch 24] loss: 0.8973050
Test set: Average loss: 1.2681, Accuracy: 2624/5000 (52%)
[epoch 25] loss: 0.8823376
Test set: Average loss: 1.2647, Accuracy: 2633/5000 (53%)
Validation:
Test set: Average loss: 1.2647, Accuracy: 2633/5000 (53%)
Test
Test set: Average loss: 1.2708, Accuracy: 2607/5000 (52%)
Test set: Average loss: 0.8721, Accuracy: 218/250 (87%)
## seed: 12
Validation accuracy before training:
Test set: Average loss: 1.7333, Accuracy: 513/5000 (10%)
[epoch 1] loss: 1.7514176
Test set: Average loss: 1.6784, Accuracy: 698/5000 (14%)
[epoch 2] loss: 1.6506101
Test set: Average loss: 1.6138, Accuracy: 1081/5000 (22%)
[epoch 3] loss: 1.5618886
Test set: Average loss: 1.5590, Accuracy: 1430/5000 (29%)
[epoch 4] loss: 1.4865463
Test set: Average loss: 1.5225, Accuracy: 1649/5000 (33%)
[epoch 5] loss: 1.4383688
Test set: Average loss: 1.4966, Accuracy: 1756/5000 (35%)
[epoch 6] loss: 1.3955821
Test set: Average loss: 1.4764, Accuracy: 1843/5000 (37%)
[epoch 7] loss: 1.3540594
Test set: Average loss: 1.4601, Accuracy: 1923/5000 (38%)
[epoch 8] loss: 1.3169696
Test set: Average loss: 1.4465, Accuracy: 1987/5000 (40%)
[epoch 9] loss: 1.2814197
Test set: Average loss: 1.4324, Accuracy: 2043/5000 (41%)
[epoch 10] loss: 1.2496913
Test set: Average loss: 1.4208, Accuracy: 2093/5000 (42%)
[epoch 11] loss: 1.2172638
Test set: Average loss: 1.4087, Accuracy: 2129/5000 (43%)
[epoch 12] loss: 1.1914216
Test set: Average loss: 1.3987, Accuracy: 2167/5000 (43%)
[epoch 13] loss: 1.1613203
Test set: Average loss: 1.3898, Accuracy: 2207/5000 (44%)
[epoch 14] loss: 1.1364468
Test set: Average loss: 1.3811, Accuracy: 2222/5000 (44%)
[epoch 15] loss: 1.1111272
Test set: Average loss: 1.3726, Accuracy: 2263/5000 (45%)
[epoch 16] loss: 1.0879081
Test set: Average loss: 1.3656, Accuracy: 2280/5000 (46%)
[epoch 17] loss: 1.0662608
Test set: Average loss: 1.3599, Accuracy: 2309/5000 (46%)
[epoch 18] loss: 1.0450384
Test set: Average loss: 1.3523, Accuracy: 2340/5000 (47%)
[epoch 19] loss: 1.0261449
Test set: Average loss: 1.3464, Accuracy: 2361/5000 (47%)
[epoch 20] loss: 1.0068052
Test set: Average loss: 1.3412, Accuracy: 2376/5000 (48%)
[epoch 21] loss: 0.9892102
Test set: Average loss: 1.3368, Accuracy: 2386/5000 (48%)
[epoch 22] loss: 0.9704356
Test set: Average loss: 1.3313, Accuracy: 2404/5000 (48%)
[epoch 23] loss: 0.9551458
Test set: Average loss: 1.3270, Accuracy: 2408/5000 (48%)
[epoch 24] loss: 0.9380231
Test set: Average loss: 1.3227, Accuracy: 2423/5000 (48%)
[epoch 25] loss: 0.9208485
Test set: Average loss: 1.3199, Accuracy: 2440/5000 (49%)
Validation:
Test set: Average loss: 1.3199, Accuracy: 2440/5000 (49%)
Test
Test set: Average loss: 1.3213, Accuracy: 2412/5000 (48%)
Test set: Average loss: 0.9087, Accuracy: 224/250 (90%)
## seed: 13
Validation accuracy before training:
Test set: Average loss: 1.6080, Accuracy: 1270/5000 (25%)
[epoch 1] loss: 1.5999067
Test set: Average loss: 1.5569, Accuracy: 1421/5000 (28%)
[epoch 2] loss: 1.5053255
Test set: Average loss: 1.5092, Accuracy: 1589/5000 (32%)
[epoch 3] loss: 1.4285994
Test set: Average loss: 1.4714, Accuracy: 1751/5000 (35%)
[epoch 4] loss: 1.3646533
Test set: Average loss: 1.4414, Accuracy: 1867/5000 (37%)
[epoch 5] loss: 1.3059521
Test set: Average loss: 1.4178, Accuracy: 1950/5000 (39%)
[epoch 6] loss: 1.2581052
Test set: Average loss: 1.3977, Accuracy: 2053/5000 (41%)
[epoch 7] loss: 1.2199118
Test set: Average loss: 1.3808, Accuracy: 2138/5000 (43%)
[epoch 8] loss: 1.1802515
Test set: Average loss: 1.3665, Accuracy: 2211/5000 (44%)
[epoch 9] loss: 1.1512372
Test set: Average loss: 1.3542, Accuracy: 2273/5000 (45%)
[epoch 10] loss: 1.1187471
Test set: Average loss: 1.3422, Accuracy: 2341/5000 (47%)
[epoch 11] loss: 1.0929422
Test set: Average loss: 1.3326, Accuracy: 2389/5000 (48%)
[epoch 12] loss: 1.0685236
Test set: Average loss: 1.3241, Accuracy: 2417/5000 (48%)
[epoch 13] loss: 1.0417828
Test set: Average loss: 1.3146, Accuracy: 2493/5000 (50%)
[epoch 14] loss: 1.0213402
Test set: Average loss: 1.3072, Accuracy: 2528/5000 (51%)
[epoch 15] loss: 1.0012071
Test set: Average loss: 1.3006, Accuracy: 2540/5000 (51%)
[epoch 16] loss: 0.9769390
Test set: Average loss: 1.2950, Accuracy: 2537/5000 (51%)
[epoch 17] loss: 0.9596773
Test set: Average loss: 1.2882, Accuracy: 2554/5000 (51%)
[epoch 18] loss: 0.9403833
Test set: Average loss: 1.2825, Accuracy: 2575/5000 (52%)
[epoch 19] loss: 0.9224791
Test set: Average loss: 1.2781, Accuracy: 2592/5000 (52%)
[epoch 20] loss: 0.9045754
Test set: Average loss: 1.2730, Accuracy: 2622/5000 (52%)
[epoch 21] loss: 0.8880982
Test set: Average loss: 1.2687, Accuracy: 2644/5000 (53%)
[epoch 22] loss: 0.8754784
Test set: Average loss: 1.2648, Accuracy: 2636/5000 (53%)
[epoch 23] loss: 0.8575552
Test set: Average loss: 1.2613, Accuracy: 2650/5000 (53%)
[epoch 24] loss: 0.8423290
Test set: Average loss: 1.2566, Accuracy: 2671/5000 (53%)
[epoch 25] loss: 0.8254632
Test set: Average loss: 1.2539, Accuracy: 2672/5000 (53%)
Validation:
Test set: Average loss: 1.2539, Accuracy: 2672/5000 (53%)
Test
Test set: Average loss: 1.2708, Accuracy: 2604/5000 (52%)
Test set: Average loss: 0.8164, Accuracy: 235/250 (94%)
500
## seed: 11
Validation accuracy before training:
Test set: Average loss: 1.7275, Accuracy: 655/5000 (13%)
[epoch 1] loss: 1.6746793
Test set: Average loss: 1.5883, Accuracy: 1237/5000 (25%)
[epoch 2] loss: 1.5190807
Test set: Average loss: 1.4890, Accuracy: 1720/5000 (34%)
[epoch 3] loss: 1.4148135
Test set: Average loss: 1.4286, Accuracy: 2082/5000 (42%)
[epoch 4] loss: 1.3469856
Test set: Average loss: 1.3898, Accuracy: 2271/5000 (45%)
[epoch 5] loss: 1.2865212
Test set: Average loss: 1.3615, Accuracy: 2405/5000 (48%)
[epoch 6] loss: 1.2388084
Test set: Average loss: 1.3420, Accuracy: 2447/5000 (49%)
[epoch 7] loss: 1.1988792
Test set: Average loss: 1.3251, Accuracy: 2502/5000 (50%)
[epoch 8] loss: 1.1638992
Test set: Average loss: 1.3092, Accuracy: 2565/5000 (51%)
[epoch 9] loss: 1.1347052
Test set: Average loss: 1.2975, Accuracy: 2592/5000 (52%)
[epoch 10] loss: 1.1083911
Test set: Average loss: 1.2868, Accuracy: 2613/5000 (52%)
[epoch 11] loss: 1.0777021
Test set: Average loss: 1.2760, Accuracy: 2639/5000 (53%)
[epoch 12] loss: 1.0524963
Test set: Average loss: 1.2671, Accuracy: 2661/5000 (53%)
[epoch 13] loss: 1.0317245
Test set: Average loss: 1.2596, Accuracy: 2668/5000 (53%)
[epoch 14] loss: 1.0078307
Test set: Average loss: 1.2513, Accuracy: 2687/5000 (54%)
[epoch 15] loss: 0.9841271
Test set: Average loss: 1.2457, Accuracy: 2692/5000 (54%)
[epoch 16] loss: 0.9617444
Test set: Average loss: 1.2385, Accuracy: 2716/5000 (54%)
[epoch 17] loss: 0.9427373
Test set: Average loss: 1.2316, Accuracy: 2723/5000 (54%)
[epoch 18] loss: 0.9215065
Test set: Average loss: 1.2257, Accuracy: 2724/5000 (54%)
[epoch 19] loss: 0.8988683
Test set: Average loss: 1.2199, Accuracy: 2749/5000 (55%)
[epoch 20] loss: 0.8836597
Test set: Average loss: 1.2146, Accuracy: 2750/5000 (55%)
[epoch 21] loss: 0.8635976
Test set: Average loss: 1.2105, Accuracy: 2762/5000 (55%)
[epoch 22] loss: 0.8446221
Test set: Average loss: 1.2064, Accuracy: 2749/5000 (55%)
[epoch 23] loss: 0.8283478
Test set: Average loss: 1.2004, Accuracy: 2761/5000 (55%)
[epoch 24] loss: 0.8121476
Test set: Average loss: 1.1979, Accuracy: 2759/5000 (55%)
[epoch 25] loss: 0.7941116
Test set: Average loss: 1.1934, Accuracy: 2768/5000 (55%)
Validation:
Test set: Average loss: 1.1934, Accuracy: 2768/5000 (55%)
Test
Test set: Average loss: 1.2020, Accuracy: 2780/5000 (56%)
Test set: Average loss: 0.7794, Accuracy: 436/500 (87%)
## seed: 12
Validation accuracy before training:
Test set: Average loss: 1.6889, Accuracy: 921/5000 (18%)
[epoch 1] loss: 1.6327065
Test set: Average loss: 1.5548, Accuracy: 1579/5000 (32%)
[epoch 2] loss: 1.4930755
Test set: Average loss: 1.4755, Accuracy: 1942/5000 (39%)
[epoch 3] loss: 1.4100572
Test set: Average loss: 1.4276, Accuracy: 2067/5000 (41%)
[epoch 4] loss: 1.3395134
Test set: Average loss: 1.3936, Accuracy: 2179/5000 (44%)
[epoch 5] loss: 1.2854262
Test set: Average loss: 1.3658, Accuracy: 2300/5000 (46%)
[epoch 6] loss: 1.2379660
Test set: Average loss: 1.3420, Accuracy: 2371/5000 (47%)
[epoch 7] loss: 1.1994842
Test set: Average loss: 1.3235, Accuracy: 2410/5000 (48%)
[epoch 8] loss: 1.1617752
Test set: Average loss: 1.3062, Accuracy: 2491/5000 (50%)
[epoch 9] loss: 1.1269969
Test set: Average loss: 1.2917, Accuracy: 2552/5000 (51%)
[epoch 10] loss: 1.0984523
Test set: Average loss: 1.2791, Accuracy: 2579/5000 (52%)
[epoch 11] loss: 1.0658821
Test set: Average loss: 1.2678, Accuracy: 2627/5000 (53%)
[epoch 12] loss: 1.0422185
Test set: Average loss: 1.2555, Accuracy: 2653/5000 (53%)
[epoch 13] loss: 1.0138616
Test set: Average loss: 1.2457, Accuracy: 2669/5000 (53%)
[epoch 14] loss: 0.9918182
Test set: Average loss: 1.2357, Accuracy: 2715/5000 (54%)
[epoch 15] loss: 0.9670929
Test set: Average loss: 1.2291, Accuracy: 2738/5000 (55%)
[epoch 16] loss: 0.9465073
Test set: Average loss: 1.2198, Accuracy: 2755/5000 (55%)
[epoch 17] loss: 0.9218282
Test set: Average loss: 1.2148, Accuracy: 2759/5000 (55%)
[epoch 18] loss: 0.9030729
Test set: Average loss: 1.2073, Accuracy: 2792/5000 (56%)
[epoch 19] loss: 0.8849220
Test set: Average loss: 1.2001, Accuracy: 2800/5000 (56%)
[epoch 20] loss: 0.8621363
Test set: Average loss: 1.1934, Accuracy: 2825/5000 (56%)
[epoch 21] loss: 0.8430615
Test set: Average loss: 1.1889, Accuracy: 2828/5000 (57%)
[epoch 22] loss: 0.8263348
Test set: Average loss: 1.1847, Accuracy: 2811/5000 (56%)
[epoch 23] loss: 0.8070322
Test set: Average loss: 1.1770, Accuracy: 2859/5000 (57%)
[epoch 24] loss: 0.7922109
Test set: Average loss: 1.1733, Accuracy: 2842/5000 (57%)
[epoch 25] loss: 0.7729328
Test set: Average loss: 1.1693, Accuracy: 2860/5000 (57%)
Validation:
Test set: Average loss: 1.1693, Accuracy: 2860/5000 (57%)
Test
Test set: Average loss: 1.1753, Accuracy: 2790/5000 (56%)
Test set: Average loss: 0.7593, Accuracy: 452/500 (90%)
## seed: 13
Validation accuracy before training:
Test set: Average loss: 1.5222, Accuracy: 2007/5000 (40%)
[epoch 1] loss: 1.4615081
Test set: Average loss: 1.4712, Accuracy: 2173/5000 (43%)
[epoch 2] loss: 1.3727533
Test set: Average loss: 1.4303, Accuracy: 2211/5000 (44%)
[epoch 3] loss: 1.3120464
Test set: Average loss: 1.3999, Accuracy: 2252/5000 (45%)
[epoch 4] loss: 1.2633478
Test set: Average loss: 1.3767, Accuracy: 2293/5000 (46%)
[epoch 5] loss: 1.2270309
Test set: Average loss: 1.3585, Accuracy: 2323/5000 (46%)
[epoch 6] loss: 1.1971340
Test set: Average loss: 1.3434, Accuracy: 2363/5000 (47%)
[epoch 7] loss: 1.1584875
Test set: Average loss: 1.3288, Accuracy: 2428/5000 (49%)
[epoch 8] loss: 1.1363753
Test set: Average loss: 1.3173, Accuracy: 2453/5000 (49%)
[epoch 9] loss: 1.1091790
Test set: Average loss: 1.3065, Accuracy: 2493/5000 (50%)
[epoch 10] loss: 1.0824091
Test set: Average loss: 1.2963, Accuracy: 2542/5000 (51%)
[epoch 11] loss: 1.0604572
Test set: Average loss: 1.2876, Accuracy: 2543/5000 (51%)
[epoch 12] loss: 1.0377117
Test set: Average loss: 1.2776, Accuracy: 2582/5000 (52%)
[epoch 13] loss: 1.0207817
Test set: Average loss: 1.2703, Accuracy: 2608/5000 (52%)
[epoch 14] loss: 0.9946957
Test set: Average loss: 1.2620, Accuracy: 2621/5000 (52%)
[epoch 15] loss: 0.9796536
Test set: Average loss: 1.2539, Accuracy: 2639/5000 (53%)
[epoch 16] loss: 0.9564397
Test set: Average loss: 1.2481, Accuracy: 2649/5000 (53%)
[epoch 17] loss: 0.9362891
Test set: Average loss: 1.2438, Accuracy: 2640/5000 (53%)
[epoch 18] loss: 0.9169608
Test set: Average loss: 1.2347, Accuracy: 2676/5000 (54%)
[epoch 19] loss: 0.9018752
Test set: Average loss: 1.2302, Accuracy: 2679/5000 (54%)
[epoch 20] loss: 0.8845624
Test set: Average loss: 1.2237, Accuracy: 2703/5000 (54%)
[epoch 21] loss: 0.8672771
Test set: Average loss: 1.2186, Accuracy: 2707/5000 (54%)
[epoch 22] loss: 0.8478229
Test set: Average loss: 1.2140, Accuracy: 2737/5000 (55%)
[epoch 23] loss: 0.8323542
Test set: Average loss: 1.2090, Accuracy: 2737/5000 (55%)
[epoch 24] loss: 0.8183684
Test set: Average loss: 1.2055, Accuracy: 2736/5000 (55%)
[epoch 25] loss: 0.8023261
Test set: Average loss: 1.1992, Accuracy: 2761/5000 (55%)
Validation:
Test set: Average loss: 1.1992, Accuracy: 2761/5000 (55%)
Test
Test set: Average loss: 1.2046, Accuracy: 2742/5000 (55%)
Test set: Average loss: 0.7884, Accuracy: 445/500 (89%)
750
## seed: 11
Validation accuracy before training:
Test set: Average loss: 1.6910, Accuracy: 836/5000 (17%)
[epoch 1] loss: 1.6705202
Test set: Average loss: 1.5526, Accuracy: 1768/5000 (35%)
[epoch 2] loss: 1.4954939
Test set: Average loss: 1.4659, Accuracy: 2138/5000 (43%)
[epoch 3] loss: 1.3937819
Test set: Average loss: 1.4084, Accuracy: 2290/5000 (46%)
[epoch 4] loss: 1.3211023
Test set: Average loss: 1.3689, Accuracy: 2382/5000 (48%)
[epoch 5] loss: 1.2645193
Test set: Average loss: 1.3385, Accuracy: 2429/5000 (49%)
[epoch 6] loss: 1.2177523
Test set: Average loss: 1.3151, Accuracy: 2499/5000 (50%)
[epoch 7] loss: 1.1787389
Test set: Average loss: 1.2978, Accuracy: 2559/5000 (51%)
[epoch 8] loss: 1.1425197
Test set: Average loss: 1.2820, Accuracy: 2593/5000 (52%)
[epoch 9] loss: 1.1154484
Test set: Average loss: 1.2681, Accuracy: 2622/5000 (52%)
[epoch 10] loss: 1.0830911
Test set: Average loss: 1.2563, Accuracy: 2658/5000 (53%)
[epoch 11] loss: 1.0595175
Test set: Average loss: 1.2471, Accuracy: 2667/5000 (53%)
[epoch 12] loss: 1.0386053
Test set: Average loss: 1.2387, Accuracy: 2679/5000 (54%)
[epoch 13] loss: 1.0129304
Test set: Average loss: 1.2301, Accuracy: 2701/5000 (54%)
[epoch 14] loss: 0.9881556
Test set: Average loss: 1.2222, Accuracy: 2716/5000 (54%)
[epoch 15] loss: 0.9624397
Test set: Average loss: 1.2142, Accuracy: 2731/5000 (55%)
[epoch 16] loss: 0.9464318
Test set: Average loss: 1.2077, Accuracy: 2765/5000 (55%)
[epoch 17] loss: 0.9239030
Test set: Average loss: 1.2010, Accuracy: 2761/5000 (55%)
[epoch 18] loss: 0.9029306
Test set: Average loss: 1.1960, Accuracy: 2775/5000 (56%)
[epoch 19] loss: 0.8737804
Test set: Average loss: 1.1912, Accuracy: 2786/5000 (56%)
[epoch 20] loss: 0.8651312
Test set: Average loss: 1.1828, Accuracy: 2786/5000 (56%)
[epoch 21] loss: 0.8429560
Test set: Average loss: 1.1800, Accuracy: 2806/5000 (56%)
[epoch 22] loss: 0.8260029
Test set: Average loss: 1.1747, Accuracy: 2805/5000 (56%)
[epoch 23] loss: 0.8052803
Test set: Average loss: 1.1715, Accuracy: 2814/5000 (56%)
[epoch 24] loss: 0.7877895
Test set: Average loss: 1.1668, Accuracy: 2816/5000 (56%)
[epoch 25] loss: 0.7713705
Test set: Average loss: 1.1618, Accuracy: 2839/5000 (57%)
Validation:
Test set: Average loss: 1.1618, Accuracy: 2839/5000 (57%)
Test
Test set: Average loss: 1.1749, Accuracy: 2821/5000 (56%)
Test set: Average loss: 0.7528, Accuracy: 636/750 (85%)
## seed: 12
Validation accuracy before training:
Test set: Average loss: 1.8867, Accuracy: 322/5000 (6%)
[epoch 1] loss: 1.8706218
Test set: Average loss: 1.7147, Accuracy: 902/5000 (18%)
[epoch 2] loss: 1.6947801
Test set: Average loss: 1.5945, Accuracy: 1466/5000 (29%)
[epoch 3] loss: 1.5647262
Test set: Average loss: 1.5193, Accuracy: 1820/5000 (36%)
[epoch 4] loss: 1.4824770
Test set: Average loss: 1.4690, Accuracy: 1978/5000 (40%)
[epoch 5] loss: 1.4093187
Test set: Average loss: 1.4303, Accuracy: 2097/5000 (42%)
[epoch 6] loss: 1.3568519
Test set: Average loss: 1.4016, Accuracy: 2164/5000 (43%)
[epoch 7] loss: 1.3146876
Test set: Average loss: 1.3784, Accuracy: 2234/5000 (45%)
[epoch 8] loss: 1.2729116
Test set: Average loss: 1.3610, Accuracy: 2313/5000 (46%)
[epoch 9] loss: 1.2394099
Test set: Average loss: 1.3449, Accuracy: 2382/5000 (48%)
[epoch 10] loss: 1.2084522
Test set: Average loss: 1.3315, Accuracy: 2426/5000 (49%)
[epoch 11] loss: 1.1787596
Test set: Average loss: 1.3168, Accuracy: 2449/5000 (49%)
[epoch 12] loss: 1.1513738
Test set: Average loss: 1.3062, Accuracy: 2515/5000 (50%)
[epoch 13] loss: 1.1177894
Test set: Average loss: 1.2941, Accuracy: 2542/5000 (51%)
[epoch 14] loss: 1.0978408
Test set: Average loss: 1.2836, Accuracy: 2581/5000 (52%)
[epoch 15] loss: 1.0747121
Test set: Average loss: 1.2749, Accuracy: 2611/5000 (52%)
[epoch 16] loss: 1.0496485
Test set: Average loss: 1.2660, Accuracy: 2636/5000 (53%)
[epoch 17] loss: 1.0232151
Test set: Average loss: 1.2574, Accuracy: 2659/5000 (53%)
[epoch 18] loss: 1.0066763
Test set: Average loss: 1.2488, Accuracy: 2694/5000 (54%)
[epoch 19] loss: 0.9845265
Test set: Average loss: 1.2410, Accuracy: 2722/5000 (54%)
[epoch 20] loss: 0.9584269
Test set: Average loss: 1.2364, Accuracy: 2726/5000 (55%)
[epoch 21] loss: 0.9367835
Test set: Average loss: 1.2273, Accuracy: 2760/5000 (55%)
[epoch 22] loss: 0.9168885
Test set: Average loss: 1.2217, Accuracy: 2765/5000 (55%)
[epoch 23] loss: 0.9013541
Test set: Average loss: 1.2160, Accuracy: 2770/5000 (55%)
[epoch 24] loss: 0.8810816
Test set: Average loss: 1.2106, Accuracy: 2784/5000 (56%)
[epoch 25] loss: 0.8630082
Test set: Average loss: 1.2039, Accuracy: 2810/5000 (56%)
Validation:
Test set: Average loss: 1.2039, Accuracy: 2810/5000 (56%)
Test
Test set: Average loss: 1.2119, Accuracy: 2780/5000 (56%)
Test set: Average loss: 0.8429, Accuracy: 617/750 (82%)
## seed: 13
Validation accuracy before training:
Test set: Average loss: 1.5725, Accuracy: 1220/5000 (24%)
[epoch 1] loss: 1.4836743
Test set: Average loss: 1.4364, Accuracy: 1944/5000 (39%)
[epoch 2] loss: 1.3500544
Test set: Average loss: 1.3717, Accuracy: 2198/5000 (44%)
[epoch 3] loss: 1.2726297
Test set: Average loss: 1.3341, Accuracy: 2359/5000 (47%)
[epoch 4] loss: 1.2163558
Test set: Average loss: 1.3086, Accuracy: 2463/5000 (49%)
[epoch 5] loss: 1.1740526
Test set: Average loss: 1.2873, Accuracy: 2506/5000 (50%)
[epoch 6] loss: 1.1377542
Test set: Average loss: 1.2714, Accuracy: 2556/5000 (51%)
[epoch 7] loss: 1.1093647
Test set: Average loss: 1.2569, Accuracy: 2606/5000 (52%)
[epoch 8] loss: 1.0729413
Test set: Average loss: 1.2426, Accuracy: 2676/5000 (54%)
[epoch 9] loss: 1.0487377
Test set: Average loss: 1.2314, Accuracy: 2703/5000 (54%)
[epoch 10] loss: 1.0224376
Test set: Average loss: 1.2196, Accuracy: 2750/5000 (55%)
[epoch 11] loss: 0.9919007
Test set: Average loss: 1.2109, Accuracy: 2771/5000 (55%)
[epoch 12] loss: 0.9683483
Test set: Average loss: 1.2011, Accuracy: 2783/5000 (56%)
[epoch 13] loss: 0.9426992
Test set: Average loss: 1.1928, Accuracy: 2809/5000 (56%)
[epoch 14] loss: 0.9232196
Test set: Average loss: 1.1850, Accuracy: 2819/5000 (56%)
[epoch 15] loss: 0.8981841
Test set: Average loss: 1.1774, Accuracy: 2833/5000 (57%)
[epoch 16] loss: 0.8789528
Test set: Average loss: 1.1716, Accuracy: 2846/5000 (57%)
[epoch 17] loss: 0.8577674
Test set: Average loss: 1.1657, Accuracy: 2859/5000 (57%)
[epoch 18] loss: 0.8361341
Test set: Average loss: 1.1600, Accuracy: 2860/5000 (57%)
[epoch 19] loss: 0.8215337
Test set: Average loss: 1.1548, Accuracy: 2871/5000 (57%)
[epoch 20] loss: 0.8005067
Test set: Average loss: 1.1490, Accuracy: 2887/5000 (58%)
[epoch 21] loss: 0.7836004
Test set: Average loss: 1.1452, Accuracy: 2897/5000 (58%)
[epoch 22] loss: 0.7695261
Test set: Average loss: 1.1407, Accuracy: 2897/5000 (58%)
[epoch 23] loss: 0.7472083
Test set: Average loss: 1.1371, Accuracy: 2900/5000 (58%)
[epoch 24] loss: 0.7305583
Test set: Average loss: 1.1324, Accuracy: 2921/5000 (58%)
[epoch 25] loss: 0.7144018
Test set: Average loss: 1.1291, Accuracy: 2909/5000 (58%)
Validation:
Test set: Average loss: 1.1324, Accuracy: 2921/5000 (58%)
Test
Test set: Average loss: 1.1572, Accuracy: 2832/5000 (57%)
Test set: Average loss: 0.7145, Accuracy: 674/750 (90%)
1000
## seed: 11
Validation accuracy before training:
Test set: Average loss: 1.6689, Accuracy: 677/5000 (14%)
[epoch 1] loss: 1.5265040
Test set: Average loss: 1.4473, Accuracy: 1764/5000 (35%)
[epoch 2] loss: 1.3651883
Test set: Average loss: 1.3740, Accuracy: 2126/5000 (43%)
[epoch 3] loss: 1.2884896
Test set: Average loss: 1.3321, Accuracy: 2307/5000 (46%)
[epoch 4] loss: 1.2451013
Test set: Average loss: 1.3022, Accuracy: 2444/5000 (49%)
[epoch 5] loss: 1.1828656
Test set: Average loss: 1.2793, Accuracy: 2538/5000 (51%)
[epoch 6] loss: 1.1465836
Test set: Average loss: 1.2617, Accuracy: 2604/5000 (52%)
[epoch 7] loss: 1.1153848
Test set: Average loss: 1.2457, Accuracy: 2666/5000 (53%)
[epoch 8] loss: 1.0845609
Test set: Average loss: 1.2325, Accuracy: 2710/5000 (54%)
[epoch 9] loss: 1.0572520
Test set: Average loss: 1.2200, Accuracy: 2727/5000 (55%)
[epoch 10] loss: 1.0332321
Test set: Average loss: 1.2109, Accuracy: 2738/5000 (55%)
[epoch 11] loss: 1.0021765
Test set: Average loss: 1.2019, Accuracy: 2758/5000 (55%)
[epoch 12] loss: 0.9821085
Test set: Average loss: 1.1944, Accuracy: 2774/5000 (55%)
[epoch 13] loss: 0.9504782
Test set: Average loss: 1.1853, Accuracy: 2798/5000 (56%)
[epoch 14] loss: 0.9253271
Test set: Average loss: 1.1775, Accuracy: 2819/5000 (56%)
[epoch 15] loss: 0.8996695
Test set: Average loss: 1.1706, Accuracy: 2821/5000 (56%)
[epoch 16] loss: 0.8804488
Test set: Average loss: 1.1629, Accuracy: 2837/5000 (57%)
[epoch 17] loss: 0.8575297
Test set: Average loss: 1.1575, Accuracy: 2844/5000 (57%)
[epoch 18] loss: 0.8340512
Test set: Average loss: 1.1504, Accuracy: 2860/5000 (57%)
[epoch 19] loss: 0.8180572
Test set: Average loss: 1.1460, Accuracy: 2869/5000 (57%)
[epoch 20] loss: 0.7917952
Test set: Average loss: 1.1402, Accuracy: 2867/5000 (57%)
[epoch 21] loss: 0.7745409
Test set: Average loss: 1.1338, Accuracy: 2885/5000 (58%)
[epoch 22] loss: 0.7526103
Test set: Average loss: 1.1311, Accuracy: 2871/5000 (57%)
[epoch 23] loss: 0.7325844
Test set: Average loss: 1.1266, Accuracy: 2908/5000 (58%)
[epoch 24] loss: 0.7186679
Test set: Average loss: 1.1225, Accuracy: 2897/5000 (58%)
[epoch 25] loss: 0.6972161
Test set: Average loss: 1.1193, Accuracy: 2889/5000 (58%)
Validation:
Test set: Average loss: 1.1266, Accuracy: 2908/5000 (58%)
Test
Test set: Average loss: 1.1271, Accuracy: 2900/5000 (58%)
Test set: Average loss: 0.7145, Accuracy: 884/1000 (88%)
## seed: 12
Validation accuracy before training:
Test set: Average loss: 1.6346, Accuracy: 1327/5000 (27%)
[epoch 1] loss: 1.5355153
Test set: Average loss: 1.4405, Accuracy: 2075/5000 (42%)
[epoch 2] loss: 1.3688941
Test set: Average loss: 1.3536, Accuracy: 2429/5000 (49%)
[epoch 3] loss: 1.2857800
Test set: Average loss: 1.3047, Accuracy: 2620/5000 (52%)
[epoch 4] loss: 1.2228287
Test set: Average loss: 1.2704, Accuracy: 2756/5000 (55%)
[epoch 5] loss: 1.1721925
Test set: Average loss: 1.2434, Accuracy: 2806/5000 (56%)
[epoch 6] loss: 1.1357137
Test set: Average loss: 1.2233, Accuracy: 2886/5000 (58%)
[epoch 7] loss: 1.0944600
Test set: Average loss: 1.2052, Accuracy: 2903/5000 (58%)
[epoch 8] loss: 1.0636521
Test set: Average loss: 1.1910, Accuracy: 2927/5000 (59%)
[epoch 9] loss: 1.0349847
Test set: Average loss: 1.1776, Accuracy: 2967/5000 (59%)
[epoch 10] loss: 1.0015846
Test set: Average loss: 1.1671, Accuracy: 2967/5000 (59%)
[epoch 11] loss: 0.9771549
Test set: Average loss: 1.1568, Accuracy: 2991/5000 (60%)
[epoch 12] loss: 0.9491873
Test set: Average loss: 1.1474, Accuracy: 2988/5000 (60%)
[epoch 13] loss: 0.9364207
Test set: Average loss: 1.1385, Accuracy: 3018/5000 (60%)
[epoch 14] loss: 0.9083415
Test set: Average loss: 1.1318, Accuracy: 3018/5000 (60%)
[epoch 15] loss: 0.8833071
Test set: Average loss: 1.1252, Accuracy: 3033/5000 (61%)
[epoch 16] loss: 0.8542633
Test set: Average loss: 1.1182, Accuracy: 3035/5000 (61%)
[epoch 17] loss: 0.8441358
Test set: Average loss: 1.1113, Accuracy: 3050/5000 (61%)
[epoch 18] loss: 0.8234346
Test set: Average loss: 1.1060, Accuracy: 3056/5000 (61%)
[epoch 19] loss: 0.7995232
Test set: Average loss: 1.1002, Accuracy: 3067/5000 (61%)
[epoch 20] loss: 0.7791908
Test set: Average loss: 1.0961, Accuracy: 3072/5000 (61%)
[epoch 21] loss: 0.7648273
Test set: Average loss: 1.0904, Accuracy: 3076/5000 (62%)
[epoch 22] loss: 0.7447711
Test set: Average loss: 1.0857, Accuracy: 3076/5000 (62%)
[epoch 23] loss: 0.7254264
Test set: Average loss: 1.0807, Accuracy: 3082/5000 (62%)
[epoch 24] loss: 0.7024337
Test set: Average loss: 1.0803, Accuracy: 3058/5000 (61%)
[epoch 25] loss: 0.6865902
Test set: Average loss: 1.0739, Accuracy: 3083/5000 (62%)
Validation:
Test set: Average loss: 1.0739, Accuracy: 3083/5000 (62%)
Test
Test set: Average loss: 1.0808, Accuracy: 3010/5000 (60%)
Test set: Average loss: 0.6699, Accuracy: 885/1000 (88%)
## seed: 13
Validation accuracy before training:
Test set: Average loss: 1.5577, Accuracy: 1260/5000 (25%)
[epoch 1] loss: 1.4859150
Test set: Average loss: 1.4196, Accuracy: 1965/5000 (39%)
[epoch 2] loss: 1.3299684
Test set: Average loss: 1.3408, Accuracy: 2393/5000 (48%)
[epoch 3] loss: 1.2391988
Test set: Average loss: 1.2942, Accuracy: 2535/5000 (51%)
[epoch 4] loss: 1.1648426
Test set: Average loss: 1.2613, Accuracy: 2621/5000 (52%)
[epoch 5] loss: 1.1140058
Test set: Average loss: 1.2351, Accuracy: 2700/5000 (54%)
[epoch 6] loss: 1.0837100
Test set: Average loss: 1.2147, Accuracy: 2771/5000 (55%)
[epoch 7] loss: 1.0308008
Test set: Average loss: 1.1986, Accuracy: 2803/5000 (56%)
[epoch 8] loss: 1.0027120
Test set: Average loss: 1.1842, Accuracy: 2820/5000 (56%)
[epoch 9] loss: 0.9718678
Test set: Average loss: 1.1724, Accuracy: 2870/5000 (57%)
[epoch 10] loss: 0.9388208
Test set: Average loss: 1.1620, Accuracy: 2880/5000 (58%)
[epoch 11] loss: 0.9084696
Test set: Average loss: 1.1488, Accuracy: 2891/5000 (58%)
[epoch 12] loss: 0.8874943
Test set: Average loss: 1.1420, Accuracy: 2918/5000 (58%)
[epoch 13] loss: 0.8615512
Test set: Average loss: 1.1317, Accuracy: 2955/5000 (59%)
[epoch 14] loss: 0.8275628
Test set: Average loss: 1.1263, Accuracy: 2939/5000 (59%)
[epoch 15] loss: 0.8055674
Test set: Average loss: 1.1197, Accuracy: 2941/5000 (59%)
[epoch 16] loss: 0.7943703
Test set: Average loss: 1.1119, Accuracy: 2953/5000 (59%)
[epoch 17] loss: 0.7698147
Test set: Average loss: 1.1054, Accuracy: 2973/5000 (59%)
[epoch 18] loss: 0.7499690
Test set: Average loss: 1.0997, Accuracy: 2983/5000 (60%)
[epoch 19] loss: 0.7249973
Test set: Average loss: 1.1010, Accuracy: 2966/5000 (59%)
[epoch 20] loss: 0.7052024
Test set: Average loss: 1.0907, Accuracy: 2977/5000 (60%)
[epoch 21] loss: 0.6956335
Test set: Average loss: 1.0893, Accuracy: 2986/5000 (60%)
[epoch 22] loss: 0.6708235
Test set: Average loss: 1.0854, Accuracy: 2982/5000 (60%)
[epoch 23] loss: 0.6488000
Test set: Average loss: 1.0808, Accuracy: 2983/5000 (60%)
[epoch 24] loss: 0.6318660
Test set: Average loss: 1.0766, Accuracy: 2990/5000 (60%)
[epoch 25] loss: 0.6156268
Test set: Average loss: 1.0763, Accuracy: 2985/5000 (60%)
Validation:
Test set: Average loss: 1.0766, Accuracy: 2990/5000 (60%)
Test
Test set: Average loss: 1.0899, Accuracy: 2929/5000 (59%)
Test set: Average loss: 0.6138, Accuracy: 908/1000 (91%)
2500
## seed: 11
Validation accuracy before training:
Test set: Average loss: 1.7592, Accuracy: 379/5000 (8%)
[epoch 1] loss: 1.5021565
Test set: Average loss: 1.3819, Accuracy: 2204/5000 (44%)
[epoch 2] loss: 1.2920968
Test set: Average loss: 1.2920, Accuracy: 2481/5000 (50%)
[epoch 3] loss: 1.2085713
Test set: Average loss: 1.2380, Accuracy: 2660/5000 (53%)
[epoch 4] loss: 1.1460972
Test set: Average loss: 1.2019, Accuracy: 2798/5000 (56%)
[epoch 5] loss: 1.0875383
Test set: Average loss: 1.1751, Accuracy: 2858/5000 (57%)
[epoch 6] loss: 1.0521546
Test set: Average loss: 1.1526, Accuracy: 2936/5000 (59%)
[epoch 7] loss: 1.0148881
Test set: Average loss: 1.1353, Accuracy: 2946/5000 (59%)
[epoch 8] loss: 0.9739416
Test set: Average loss: 1.1209, Accuracy: 2991/5000 (60%)
[epoch 9] loss: 0.9438473
Test set: Average loss: 1.1025, Accuracy: 3008/5000 (60%)
[epoch 10] loss: 0.9099748
Test set: Average loss: 1.0894, Accuracy: 3029/5000 (61%)
[epoch 11] loss: 0.8817486
Test set: Average loss: 1.0789, Accuracy: 3028/5000 (61%)
[epoch 12] loss: 0.8534141
Test set: Average loss: 1.0657, Accuracy: 3067/5000 (61%)
[epoch 13] loss: 0.8213475
Test set: Average loss: 1.0569, Accuracy: 3074/5000 (61%)
[epoch 14] loss: 0.7915775
Test set: Average loss: 1.0505, Accuracy: 3079/5000 (62%)
[epoch 15] loss: 0.7672902
Test set: Average loss: 1.0403, Accuracy: 3098/5000 (62%)
[epoch 16] loss: 0.7413050
Test set: Average loss: 1.0343, Accuracy: 3104/5000 (62%)
[epoch 17] loss: 0.7140827
Test set: Average loss: 1.0283, Accuracy: 3110/5000 (62%)
[epoch 18] loss: 0.6899606
Test set: Average loss: 1.0204, Accuracy: 3115/5000 (62%)
[epoch 19] loss: 0.6686206
Test set: Average loss: 1.0200, Accuracy: 3099/5000 (62%)
[epoch 20] loss: 0.6466880
Test set: Average loss: 1.0147, Accuracy: 3109/5000 (62%)
[epoch 21] loss: 0.6254148
Test set: Average loss: 1.0115, Accuracy: 3110/5000 (62%)
[epoch 22] loss: 0.6045006
Test set: Average loss: 1.0113, Accuracy: 3112/5000 (62%)
[epoch 23] loss: 0.5807075
Test set: Average loss: 1.0036, Accuracy: 3123/5000 (62%)
[epoch 24] loss: 0.5680222
Test set: Average loss: 0.9998, Accuracy: 3124/5000 (62%)
[epoch 25] loss: 0.5401615
Test set: Average loss: 0.9967, Accuracy: 3122/5000 (62%)
Validation:
Test set: Average loss: 0.9998, Accuracy: 3124/5000 (62%)
Test
Test set: Average loss: 1.0054, Accuracy: 3133/5000 (63%)
Test set: Average loss: 0.5352, Accuracy: 2226/2500 (89%)
## seed: 12
Validation accuracy before training:
Test set: Average loss: 1.6261, Accuracy: 1336/5000 (27%)
[epoch 1] loss: 1.4479684
Test set: Average loss: 1.3390, Accuracy: 2398/5000 (48%)
[epoch 2] loss: 1.2631677
Test set: Average loss: 1.2645, Accuracy: 2649/5000 (53%)
[epoch 3] loss: 1.1855217
Test set: Average loss: 1.2203, Accuracy: 2765/5000 (55%)
[epoch 4] loss: 1.1265713
Test set: Average loss: 1.1865, Accuracy: 2849/5000 (57%)
[epoch 5] loss: 1.0813367
Test set: Average loss: 1.1601, Accuracy: 2895/5000 (58%)
[epoch 6] loss: 1.0477601
Test set: Average loss: 1.1370, Accuracy: 2962/5000 (59%)
[epoch 7] loss: 1.0018064
Test set: Average loss: 1.1194, Accuracy: 3000/5000 (60%)
[epoch 8] loss: 0.9654135
Test set: Average loss: 1.1038, Accuracy: 3023/5000 (60%)
[epoch 9] loss: 0.9337567
Test set: Average loss: 1.0896, Accuracy: 3034/5000 (61%)
[epoch 10] loss: 0.9041476
Test set: Average loss: 1.0799, Accuracy: 3051/5000 (61%)
[epoch 11] loss: 0.8731839
Test set: Average loss: 1.0641, Accuracy: 3103/5000 (62%)
[epoch 12] loss: 0.8431587
Test set: Average loss: 1.0555, Accuracy: 3098/5000 (62%)
[epoch 13] loss: 0.8183417
Test set: Average loss: 1.0425, Accuracy: 3119/5000 (62%)
[epoch 14] loss: 0.7906812
Test set: Average loss: 1.0359, Accuracy: 3114/5000 (62%)
[epoch 15] loss: 0.7648123
Test set: Average loss: 1.0283, Accuracy: 3140/5000 (63%)
[epoch 16] loss: 0.7365770
Test set: Average loss: 1.0204, Accuracy: 3147/5000 (63%)
[epoch 17] loss: 0.7149398
Test set: Average loss: 1.0131, Accuracy: 3176/5000 (64%)
[epoch 18] loss: 0.6930061
Test set: Average loss: 1.0065, Accuracy: 3169/5000 (63%)
[epoch 19] loss: 0.6645303
Test set: Average loss: 1.0015, Accuracy: 3175/5000 (64%)
[epoch 20] loss: 0.6404183
Test set: Average loss: 0.9934, Accuracy: 3182/5000 (64%)
[epoch 21] loss: 0.6171221
Test set: Average loss: 0.9922, Accuracy: 3197/5000 (64%)
[epoch 22] loss: 0.5993779
Test set: Average loss: 0.9854, Accuracy: 3186/5000 (64%)
[epoch 23] loss: 0.5743839
Test set: Average loss: 0.9809, Accuracy: 3194/5000 (64%)
[epoch 24] loss: 0.5479137
Test set: Average loss: 0.9801, Accuracy: 3175/5000 (64%)
[epoch 25] loss: 0.5287028
Test set: Average loss: 0.9774, Accuracy: 3182/5000 (64%)
Validation:
Test set: Average loss: 0.9922, Accuracy: 3197/5000 (64%)
Test
Test set: Average loss: 1.0027, Accuracy: 3122/5000 (62%)
Test set: Average loss: 0.5931, Accuracy: 2192/2500 (88%)
## seed: 13
Validation accuracy before training:
Test set: Average loss: 1.8376, Accuracy: 375/5000 (8%)
[epoch 1] loss: 1.5525348
Test set: Average loss: 1.4041, Accuracy: 2074/5000 (41%)
[epoch 2] loss: 1.3140639
Test set: Average loss: 1.3127, Accuracy: 2439/5000 (49%)
[epoch 3] loss: 1.2282014
Test set: Average loss: 1.2587, Accuracy: 2619/5000 (52%)
[epoch 4] loss: 1.1624079
Test set: Average loss: 1.2216, Accuracy: 2728/5000 (55%)
[epoch 5] loss: 1.1080057
Test set: Average loss: 1.1912, Accuracy: 2798/5000 (56%)
[epoch 6] loss: 1.0691801
Test set: Average loss: 1.1688, Accuracy: 2858/5000 (57%)
[epoch 7] loss: 1.0232529
Test set: Average loss: 1.1501, Accuracy: 2913/5000 (58%)
[epoch 8] loss: 0.9945712
Test set: Average loss: 1.1331, Accuracy: 2944/5000 (59%)
[epoch 9] loss: 0.9575818
Test set: Average loss: 1.1188, Accuracy: 2944/5000 (59%)
[epoch 10] loss: 0.9302601
Test set: Average loss: 1.1079, Accuracy: 2966/5000 (59%)
[epoch 11] loss: 0.8993214
Test set: Average loss: 1.0955, Accuracy: 3004/5000 (60%)
[epoch 12] loss: 0.8697627
Test set: Average loss: 1.0847, Accuracy: 3005/5000 (60%)
[epoch 13] loss: 0.8435721
Test set: Average loss: 1.0755, Accuracy: 3024/5000 (60%)
[epoch 14] loss: 0.8156220
Test set: Average loss: 1.0684, Accuracy: 3033/5000 (61%)
[epoch 15] loss: 0.7935035
Test set: Average loss: 1.0591, Accuracy: 3047/5000 (61%)
[epoch 16] loss: 0.7653862
Test set: Average loss: 1.0547, Accuracy: 3052/5000 (61%)
[epoch 17] loss: 0.7438120
Test set: Average loss: 1.0479, Accuracy: 3049/5000 (61%)
[epoch 18] loss: 0.7163953
Test set: Average loss: 1.0419, Accuracy: 3071/5000 (61%)
[epoch 19] loss: 0.6929911
Test set: Average loss: 1.0376, Accuracy: 3072/5000 (61%)
[epoch 20] loss: 0.6682512
Test set: Average loss: 1.0327, Accuracy: 3097/5000 (62%)
[epoch 21] loss: 0.6504600
Test set: Average loss: 1.0274, Accuracy: 3099/5000 (62%)
[epoch 22] loss: 0.6229818
Test set: Average loss: 1.0274, Accuracy: 3103/5000 (62%)
[epoch 23] loss: 0.5993267
Test set: Average loss: 1.0246, Accuracy: 3089/5000 (62%)
[epoch 24] loss: 0.5772763
Test set: Average loss: 1.0224, Accuracy: 3087/5000 (62%)
[epoch 25] loss: 0.5558386
Test set: Average loss: 1.0179, Accuracy: 3088/5000 (62%)
Validation:
Test set: Average loss: 1.0274, Accuracy: 3103/5000 (62%)
Test
Test set: Average loss: 1.0537, Accuracy: 2985/5000 (60%)
Test set: Average loss: 0.5983, Accuracy: 2177/2500 (87%)
5000
## seed: 11
Validation accuracy before training:
Test set: Average loss: 1.5779, Accuracy: 1576/5000 (32%)
[epoch 1] loss: 1.3254240
Test set: Average loss: 1.2313, Accuracy: 2825/5000 (56%)
[epoch 2] loss: 1.1446188
Test set: Average loss: 1.1574, Accuracy: 2985/5000 (60%)
[epoch 3] loss: 1.0570132
Test set: Average loss: 1.1074, Accuracy: 3079/5000 (62%)
[epoch 4] loss: 0.9953206
Test set: Average loss: 1.0712, Accuracy: 3147/5000 (63%)
[epoch 5] loss: 0.9392481
Test set: Average loss: 1.0439, Accuracy: 3183/5000 (64%)
[epoch 6] loss: 0.8927270
Test set: Average loss: 1.0215, Accuracy: 3219/5000 (64%)
[epoch 7] loss: 0.8486556
Test set: Average loss: 1.0027, Accuracy: 3249/5000 (65%)
[epoch 8] loss: 0.8074720
Test set: Average loss: 0.9867, Accuracy: 3243/5000 (65%)
[epoch 9] loss: 0.7715413
Test set: Average loss: 0.9719, Accuracy: 3277/5000 (66%)
[epoch 10] loss: 0.7331226
Test set: Average loss: 0.9630, Accuracy: 3271/5000 (65%)
[epoch 11] loss: 0.7002798
Test set: Average loss: 0.9512, Accuracy: 3280/5000 (66%)
[epoch 12] loss: 0.6699082
Test set: Average loss: 0.9462, Accuracy: 3285/5000 (66%)
[epoch 13] loss: 0.6361022
Test set: Average loss: 0.9406, Accuracy: 3273/5000 (65%)
[epoch 14] loss: 0.6068137
Test set: Average loss: 0.9312, Accuracy: 3290/5000 (66%)
[epoch 15] loss: 0.5778880
Test set: Average loss: 0.9358, Accuracy: 3270/5000 (65%)
[epoch 16] loss: 0.5494934
Test set: Average loss: 0.9285, Accuracy: 3290/5000 (66%)
[epoch 17] loss: 0.5224496
Test set: Average loss: 0.9229, Accuracy: 3305/5000 (66%)
[epoch 18] loss: 0.4962975
Test set: Average loss: 0.9206, Accuracy: 3285/5000 (66%)
[epoch 19] loss: 0.4705888
Test set: Average loss: 0.9225, Accuracy: 3287/5000 (66%)
[epoch 20] loss: 0.4463895
Test set: Average loss: 0.9235, Accuracy: 3280/5000 (66%)
[epoch 21] loss: 0.4238905
Test set: Average loss: 0.9204, Accuracy: 3299/5000 (66%)
[epoch 22] loss: 0.4011834
Test set: Average loss: 0.9264, Accuracy: 3276/5000 (66%)
[epoch 23] loss: 0.3797992
Test set: Average loss: 0.9313, Accuracy: 3283/5000 (66%)
[epoch 24] loss: 0.3585884
Test set: Average loss: 0.9292, Accuracy: 3272/5000 (65%)
[epoch 25] loss: 0.3395082
Test set: Average loss: 0.9344, Accuracy: 3286/5000 (66%)
Validation:
Test set: Average loss: 0.9229, Accuracy: 3305/5000 (66%)
Test
Test set: Average loss: 0.9224, Accuracy: 3293/5000 (66%)
Test set: Average loss: 0.4877, Accuracy: 4471/5000 (89%)
## seed: 12
Validation accuracy before training:
Test set: Average loss: 1.6965, Accuracy: 991/5000 (20%)
[epoch 1] loss: 1.4212425
Test set: Average loss: 1.2943, Accuracy: 2525/5000 (50%)
[epoch 2] loss: 1.2171174
Test set: Average loss: 1.2047, Accuracy: 2676/5000 (54%)
[epoch 3] loss: 1.1254410
Test set: Average loss: 1.1494, Accuracy: 2857/5000 (57%)
[epoch 4] loss: 1.0535684
Test set: Average loss: 1.1111, Accuracy: 2988/5000 (60%)
[epoch 5] loss: 0.9998267
Test set: Average loss: 1.0813, Accuracy: 3087/5000 (62%)
[epoch 6] loss: 0.9486847
Test set: Average loss: 1.0546, Accuracy: 3108/5000 (62%)
[epoch 7] loss: 0.9053270
Test set: Average loss: 1.0390, Accuracy: 3156/5000 (63%)
[epoch 8] loss: 0.8637666
Test set: Average loss: 1.0198, Accuracy: 3152/5000 (63%)
[epoch 9] loss: 0.8254839
Test set: Average loss: 1.0026, Accuracy: 3174/5000 (63%)
[epoch 10] loss: 0.7922187
Test set: Average loss: 0.9887, Accuracy: 3211/5000 (64%)
[epoch 11] loss: 0.7573040
Test set: Average loss: 0.9807, Accuracy: 3209/5000 (64%)
[epoch 12] loss: 0.7291142
Test set: Average loss: 0.9704, Accuracy: 3217/5000 (64%)
[epoch 13] loss: 0.6949783
Test set: Average loss: 0.9654, Accuracy: 3215/5000 (64%)
[epoch 14] loss: 0.6652759
Test set: Average loss: 0.9610, Accuracy: 3221/5000 (64%)
[epoch 15] loss: 0.6349928
Test set: Average loss: 0.9567, Accuracy: 3228/5000 (65%)
[epoch 16] loss: 0.6067339
Test set: Average loss: 0.9505, Accuracy: 3241/5000 (65%)
[epoch 17] loss: 0.5807616
Test set: Average loss: 0.9461, Accuracy: 3256/5000 (65%)
[epoch 18] loss: 0.5528560
Test set: Average loss: 0.9480, Accuracy: 3230/5000 (65%)
[epoch 19] loss: 0.5267276
Test set: Average loss: 0.9462, Accuracy: 3244/5000 (65%)
[epoch 20] loss: 0.5039877
Test set: Average loss: 0.9427, Accuracy: 3263/5000 (65%)
[epoch 21] loss: 0.4797662
Test set: Average loss: 0.9499, Accuracy: 3267/5000 (65%)
[epoch 22] loss: 0.4569815
Test set: Average loss: 0.9495, Accuracy: 3240/5000 (65%)
[epoch 23] loss: 0.4346907
Test set: Average loss: 0.9493, Accuracy: 3250/5000 (65%)
[epoch 24] loss: 0.4119441
Test set: Average loss: 0.9480, Accuracy: 3239/5000 (65%)
[epoch 25] loss: 0.3903619
Test set: Average loss: 0.9476, Accuracy: 3247/5000 (65%)
Validation:
Test set: Average loss: 0.9499, Accuracy: 3267/5000 (65%)
Test
Test set: Average loss: 0.9661, Accuracy: 3212/5000 (64%)
Test set: Average loss: 0.4519, Accuracy: 4478/5000 (90%)
## seed: 13
Validation accuracy before training:
Test set: Average loss: 1.6362, Accuracy: 1080/5000 (22%)
[epoch 1] loss: 1.3458788
Test set: Average loss: 1.2545, Accuracy: 2755/5000 (55%)
[epoch 2] loss: 1.1592664
Test set: Average loss: 1.1690, Accuracy: 2944/5000 (59%)
[epoch 3] loss: 1.0698886
Test set: Average loss: 1.1152, Accuracy: 3058/5000 (61%)
[epoch 4] loss: 1.0052427
Test set: Average loss: 1.0787, Accuracy: 3094/5000 (62%)
[epoch 5] loss: 0.9499911
Test set: Average loss: 1.0502, Accuracy: 3157/5000 (63%)
[epoch 6] loss: 0.8995550
Test set: Average loss: 1.0273, Accuracy: 3200/5000 (64%)
[epoch 7] loss: 0.8593711
Test set: Average loss: 1.0085, Accuracy: 3192/5000 (64%)
[epoch 8] loss: 0.8165951
Test set: Average loss: 0.9919, Accuracy: 3222/5000 (64%)
[epoch 9] loss: 0.7818134
Test set: Average loss: 0.9764, Accuracy: 3231/5000 (65%)
[epoch 10] loss: 0.7460902
Test set: Average loss: 0.9670, Accuracy: 3245/5000 (65%)
[epoch 11] loss: 0.7129748
Test set: Average loss: 0.9542, Accuracy: 3260/5000 (65%)
[epoch 12] loss: 0.6819140
Test set: Average loss: 0.9501, Accuracy: 3261/5000 (65%)
[epoch 13] loss: 0.6491612
Test set: Average loss: 0.9468, Accuracy: 3262/5000 (65%)
[epoch 14] loss: 0.6209766
Test set: Average loss: 0.9397, Accuracy: 3259/5000 (65%)
[epoch 15] loss: 0.5944727
Test set: Average loss: 0.9345, Accuracy: 3269/5000 (65%)
[epoch 16] loss: 0.5649631
Test set: Average loss: 0.9284, Accuracy: 3280/5000 (66%)
[epoch 17] loss: 0.5365837
Test set: Average loss: 0.9283, Accuracy: 3288/5000 (66%)
[epoch 18] loss: 0.5112704
Test set: Average loss: 0.9284, Accuracy: 3264/5000 (65%)
[epoch 19] loss: 0.4865801
Test set: Average loss: 0.9252, Accuracy: 3264/5000 (65%)
[epoch 20] loss: 0.4605315
Test set: Average loss: 0.9275, Accuracy: 3281/5000 (66%)
[epoch 21] loss: 0.4382247
Test set: Average loss: 0.9274, Accuracy: 3288/5000 (66%)
[epoch 22] loss: 0.4152658
Test set: Average loss: 0.9334, Accuracy: 3264/5000 (65%)
[epoch 23] loss: 0.3914050
Test set: Average loss: 0.9367, Accuracy: 3241/5000 (65%)
[epoch 24] loss: 0.3707496
Test set: Average loss: 0.9436, Accuracy: 3253/5000 (65%)
[epoch 25] loss: 0.3471717
Test set: Average loss: 0.9351, Accuracy: 3282/5000 (66%)
Validation:
Test set: Average loss: 0.9274, Accuracy: 3288/5000 (66%)
Test
Test set: Average loss: 0.9338, Accuracy: 3270/5000 (65%)
Test set: Average loss: 0.4056, Accuracy: 4607/5000 (92%)
10000
## seed: 11
Validation accuracy before training:
Test set: Average loss: 1.5686, Accuracy: 1565/5000 (31%)
[epoch 1] loss: 1.2882242
Test set: Average loss: 1.1932, Accuracy: 2881/5000 (58%)
[epoch 2] loss: 1.1001318
Test set: Average loss: 1.1031, Accuracy: 3089/5000 (62%)
[epoch 3] loss: 1.0009172
Test set: Average loss: 1.0417, Accuracy: 3190/5000 (64%)
[epoch 4] loss: 0.9248985
Test set: Average loss: 0.9976, Accuracy: 3254/5000 (65%)
[epoch 5] loss: 0.8613760
Test set: Average loss: 0.9669, Accuracy: 3279/5000 (66%)
[epoch 6] loss: 0.8059290
Test set: Average loss: 0.9408, Accuracy: 3307/5000 (66%)
[epoch 7] loss: 0.7598193
Test set: Average loss: 0.9248, Accuracy: 3327/5000 (67%)
[epoch 8] loss: 0.7142569
Test set: Average loss: 0.9131, Accuracy: 3337/5000 (67%)
[epoch 9] loss: 0.6746621
Test set: Average loss: 0.9115, Accuracy: 3310/5000 (66%)
[epoch 10] loss: 0.6381059
Test set: Average loss: 0.8965, Accuracy: 3346/5000 (67%)
[epoch 11] loss: 0.6030868
Test set: Average loss: 0.8926, Accuracy: 3343/5000 (67%)
[epoch 12] loss: 0.5695084
Test set: Average loss: 0.8895, Accuracy: 3353/5000 (67%)
[epoch 13] loss: 0.5395649
Test set: Average loss: 0.8927, Accuracy: 3336/5000 (67%)
[epoch 14] loss: 0.5082883
Test set: Average loss: 0.8861, Accuracy: 3366/5000 (67%)
[epoch 15] loss: 0.4799226
Test set: Average loss: 0.8945, Accuracy: 3346/5000 (67%)
[epoch 16] loss: 0.4513176
Test set: Average loss: 0.8966, Accuracy: 3336/5000 (67%)
[epoch 17] loss: 0.4263162
Test set: Average loss: 0.9041, Accuracy: 3338/5000 (67%)
[epoch 18] loss: 0.3983121
Test set: Average loss: 0.9092, Accuracy: 3339/5000 (67%)
[epoch 19] loss: 0.3759071
Test set: Average loss: 0.9208, Accuracy: 3297/5000 (66%)
[epoch 20] loss: 0.3507457
Test set: Average loss: 0.9201, Accuracy: 3338/5000 (67%)
[epoch 21] loss: 0.3275891
Test set: Average loss: 0.9389, Accuracy: 3315/5000 (66%)
[epoch 22] loss: 0.3063036
Test set: Average loss: 0.9491, Accuracy: 3312/5000 (66%)
[epoch 23] loss: 0.2853268
Test set: Average loss: 0.9512, Accuracy: 3345/5000 (67%)
[epoch 24] loss: 0.2657222
Test set: Average loss: 0.9700, Accuracy: 3319/5000 (66%)
[epoch 25] loss: 0.2468255
Test set: Average loss: 0.9760, Accuracy: 3294/5000 (66%)
Validation:
Test set: Average loss: 0.8861, Accuracy: 3366/5000 (67%)
Test
Test set: Average loss: 0.9023, Accuracy: 3323/5000 (66%)
Test set: Average loss: 0.4680, Accuracy: 8789/10000 (88%)
## seed: 12
Validation accuracy before training:
Test set: Average loss: 1.6646, Accuracy: 909/5000 (18%)
[epoch 1] loss: 1.3212066
Test set: Average loss: 1.2057, Accuracy: 2867/5000 (57%)
[epoch 2] loss: 1.1239718
Test set: Average loss: 1.1132, Accuracy: 3075/5000 (62%)
[epoch 3] loss: 1.0299854
Test set: Average loss: 1.0571, Accuracy: 3155/5000 (63%)
[epoch 4] loss: 0.9595561
Test set: Average loss: 1.0141, Accuracy: 3208/5000 (64%)
[epoch 5] loss: 0.8993244
Test set: Average loss: 0.9872, Accuracy: 3241/5000 (65%)
[epoch 6] loss: 0.8492766
Test set: Average loss: 0.9581, Accuracy: 3285/5000 (66%)
[epoch 7] loss: 0.8020086
Test set: Average loss: 0.9458, Accuracy: 3282/5000 (66%)
[epoch 8] loss: 0.7578118
Test set: Average loss: 0.9246, Accuracy: 3309/5000 (66%)
[epoch 9] loss: 0.7199147
Test set: Average loss: 0.9136, Accuracy: 3324/5000 (66%)
[epoch 10] loss: 0.6815704
Test set: Average loss: 0.9065, Accuracy: 3342/5000 (67%)
[epoch 11] loss: 0.6460191
Test set: Average loss: 0.9030, Accuracy: 3332/5000 (67%)
[epoch 12] loss: 0.6119500
Test set: Average loss: 0.9006, Accuracy: 3345/5000 (67%)
[epoch 13] loss: 0.5802445
Test set: Average loss: 0.8954, Accuracy: 3344/5000 (67%)
[epoch 14] loss: 0.5490046
Test set: Average loss: 0.8940, Accuracy: 3348/5000 (67%)
[epoch 15] loss: 0.5194217
Test set: Average loss: 0.8935, Accuracy: 3346/5000 (67%)
[epoch 16] loss: 0.4913821
Test set: Average loss: 0.8939, Accuracy: 3379/5000 (68%)
[epoch 17] loss: 0.4638162
Test set: Average loss: 0.8951, Accuracy: 3370/5000 (67%)
[epoch 18] loss: 0.4389965
Test set: Average loss: 0.8995, Accuracy: 3376/5000 (68%)
[epoch 19] loss: 0.4132664
Test set: Average loss: 0.9089, Accuracy: 3358/5000 (67%)
[epoch 20] loss: 0.3881781
Test set: Average loss: 0.9056, Accuracy: 3358/5000 (67%)
[epoch 21] loss: 0.3646812
Test set: Average loss: 0.9182, Accuracy: 3347/5000 (67%)
[epoch 22] loss: 0.3433054
Test set: Average loss: 0.9274, Accuracy: 3338/5000 (67%)
[epoch 23] loss: 0.3193249
Test set: Average loss: 0.9380, Accuracy: 3343/5000 (67%)
[epoch 24] loss: 0.2987962
Test set: Average loss: 0.9528, Accuracy: 3296/5000 (66%)
[epoch 25] loss: 0.2804301
Test set: Average loss: 0.9556, Accuracy: 3322/5000 (66%)
Validation:
Test set: Average loss: 0.8939, Accuracy: 3379/5000 (68%)
Test
Test set: Average loss: 0.9039, Accuracy: 3324/5000 (66%)
Test set: Average loss: 0.4586, Accuracy: 8747/10000 (87%)
## seed: 13
Validation accuracy before training:
Test set: Average loss: 1.7959, Accuracy: 397/5000 (8%)
[epoch 1] loss: 1.3468859
Test set: Average loss: 1.1940, Accuracy: 2754/5000 (55%)
[epoch 2] loss: 1.1150735
Test set: Average loss: 1.0976, Accuracy: 3033/5000 (61%)
[epoch 3] loss: 1.0205818
Test set: Average loss: 1.0439, Accuracy: 3118/5000 (62%)
[epoch 4] loss: 0.9498556
Test set: Average loss: 1.0077, Accuracy: 3220/5000 (64%)
[epoch 5] loss: 0.8939050
Test set: Average loss: 0.9803, Accuracy: 3253/5000 (65%)
[epoch 6] loss: 0.8460136
Test set: Average loss: 0.9614, Accuracy: 3223/5000 (64%)
[epoch 7] loss: 0.8025319
Test set: Average loss: 0.9407, Accuracy: 3309/5000 (66%)
[epoch 8] loss: 0.7620895
Test set: Average loss: 0.9336, Accuracy: 3280/5000 (66%)
[epoch 9] loss: 0.7249249
Test set: Average loss: 0.9152, Accuracy: 3328/5000 (67%)
[epoch 10] loss: 0.6908588
Test set: Average loss: 0.9119, Accuracy: 3315/5000 (66%)
[epoch 11] loss: 0.6569095
Test set: Average loss: 0.9062, Accuracy: 3323/5000 (66%)
[epoch 12] loss: 0.6239838
Test set: Average loss: 0.9017, Accuracy: 3319/5000 (66%)
[epoch 13] loss: 0.5925396
Test set: Average loss: 0.9032, Accuracy: 3352/5000 (67%)
[epoch 14] loss: 0.5608163
Test set: Average loss: 0.8969, Accuracy: 3345/5000 (67%)
[epoch 15] loss: 0.5333618
Test set: Average loss: 0.9016, Accuracy: 3366/5000 (67%)
[epoch 16] loss: 0.5064890
Test set: Average loss: 0.8956, Accuracy: 3360/5000 (67%)
[epoch 17] loss: 0.4792553
Test set: Average loss: 0.8986, Accuracy: 3357/5000 (67%)
[epoch 18] loss: 0.4528547
Test set: Average loss: 0.9137, Accuracy: 3334/5000 (67%)
[epoch 19] loss: 0.4300601
Test set: Average loss: 0.9069, Accuracy: 3335/5000 (67%)
[epoch 20] loss: 0.4039290
Test set: Average loss: 0.9202, Accuracy: 3332/5000 (67%)
[epoch 21] loss: 0.3804195
Test set: Average loss: 0.9210, Accuracy: 3324/5000 (66%)
[epoch 22] loss: 0.3555129
Test set: Average loss: 0.9294, Accuracy: 3331/5000 (67%)
[epoch 23] loss: 0.3355282
Test set: Average loss: 0.9521, Accuracy: 3322/5000 (66%)
[epoch 24] loss: 0.3145575
Test set: Average loss: 0.9455, Accuracy: 3330/5000 (67%)
[epoch 25] loss: 0.2941167
Test set: Average loss: 0.9655, Accuracy: 3299/5000 (66%)
Validation:
Test set: Average loss: 0.9016, Accuracy: 3366/5000 (67%)
Test
Test set: Average loss: 0.9280, Accuracy: 3274/5000 (65%)
Test set: Average loss: 0.4990, Accuracy: 8643/10000 (86%)
15000
## seed: 11
Validation accuracy before training:
Test set: Average loss: 1.6108, Accuracy: 1560/5000 (31%)
[epoch 1] loss: 1.2152523
Test set: Average loss: 1.1098, Accuracy: 3162/5000 (63%)
[epoch 2] loss: 1.0083444
Test set: Average loss: 1.0236, Accuracy: 3229/5000 (65%)
[epoch 3] loss: 0.9097476
Test set: Average loss: 0.9723, Accuracy: 3278/5000 (66%)
[epoch 4] loss: 0.8358989
Test set: Average loss: 0.9404, Accuracy: 3296/5000 (66%)
[epoch 5] loss: 0.7739412
Test set: Average loss: 0.9163, Accuracy: 3330/5000 (67%)
[epoch 6] loss: 0.7187757
Test set: Average loss: 0.8978, Accuracy: 3350/5000 (67%)
[epoch 7] loss: 0.6731459
Test set: Average loss: 0.8840, Accuracy: 3362/5000 (67%)
[epoch 8] loss: 0.6289004
Test set: Average loss: 0.8759, Accuracy: 3392/5000 (68%)
[epoch 9] loss: 0.5904834
Test set: Average loss: 0.8709, Accuracy: 3392/5000 (68%)
[epoch 10] loss: 0.5556657
Test set: Average loss: 0.8756, Accuracy: 3371/5000 (67%)
[epoch 11] loss: 0.5239328
Test set: Average loss: 0.8769, Accuracy: 3401/5000 (68%)
[epoch 12] loss: 0.4925319
Test set: Average loss: 0.8782, Accuracy: 3423/5000 (68%)
[epoch 13] loss: 0.4637486
Test set: Average loss: 0.9014, Accuracy: 3368/5000 (67%)
[epoch 14] loss: 0.4372148
Test set: Average loss: 0.8938, Accuracy: 3393/5000 (68%)
[epoch 15] loss: 0.4118101
Test set: Average loss: 0.9047, Accuracy: 3370/5000 (67%)
[epoch 16] loss: 0.3878321
Test set: Average loss: 0.9187, Accuracy: 3372/5000 (67%)
[epoch 17] loss: 0.3628882
Test set: Average loss: 0.9327, Accuracy: 3361/5000 (67%)
[epoch 18] loss: 0.3400582
Test set: Average loss: 0.9374, Accuracy: 3363/5000 (67%)
[epoch 19] loss: 0.3190156
Test set: Average loss: 0.9463, Accuracy: 3377/5000 (68%)
[epoch 20] loss: 0.2986464
Test set: Average loss: 0.9599, Accuracy: 3371/5000 (67%)
[epoch 21] loss: 0.2801977
Test set: Average loss: 0.9702, Accuracy: 3379/5000 (68%)
[epoch 22] loss: 0.2618330
Test set: Average loss: 0.9811, Accuracy: 3376/5000 (68%)
[epoch 23] loss: 0.2441514
Test set: Average loss: 1.0113, Accuracy: 3318/5000 (66%)
[epoch 24] loss: 0.2275800
Test set: Average loss: 1.0176, Accuracy: 3344/5000 (67%)
[epoch 25] loss: 0.2124231
Test set: Average loss: 1.0319, Accuracy: 3360/5000 (67%)
Validation:
Test set: Average loss: 0.8782, Accuracy: 3423/5000 (68%)
Test
Test set: Average loss: 0.8900, Accuracy: 3372/5000 (67%)
Test set: Average loss: 0.4539, Accuracy: 13116/15000 (87%)
## seed: 12
Validation accuracy before training:
Test set: Average loss: 1.7231, Accuracy: 706/5000 (14%)
[epoch 1] loss: 1.2598745
Test set: Average loss: 1.1288, Accuracy: 2963/5000 (59%)
[epoch 2] loss: 1.0476931
Test set: Average loss: 1.0452, Accuracy: 3144/5000 (63%)
[epoch 3] loss: 0.9538902
Test set: Average loss: 0.9910, Accuracy: 3246/5000 (65%)
[epoch 4] loss: 0.8823763
Test set: Average loss: 0.9583, Accuracy: 3268/5000 (65%)
[epoch 5] loss: 0.8247473
Test set: Average loss: 0.9342, Accuracy: 3291/5000 (66%)
[epoch 6] loss: 0.7740585
Test set: Average loss: 0.9110, Accuracy: 3353/5000 (67%)
[epoch 7] loss: 0.7285587
Test set: Average loss: 0.8991, Accuracy: 3329/5000 (67%)
[epoch 8] loss: 0.6876418
Test set: Average loss: 0.8976, Accuracy: 3381/5000 (68%)
[epoch 9] loss: 0.6488879
Test set: Average loss: 0.8871, Accuracy: 3368/5000 (67%)
[epoch 10] loss: 0.6148650
Test set: Average loss: 0.8830, Accuracy: 3379/5000 (68%)
[epoch 11] loss: 0.5811022
Test set: Average loss: 0.8940, Accuracy: 3369/5000 (67%)
[epoch 12] loss: 0.5505154
Test set: Average loss: 0.8802, Accuracy: 3386/5000 (68%)
[epoch 13] loss: 0.5207040
Test set: Average loss: 0.8857, Accuracy: 3401/5000 (68%)
[epoch 14] loss: 0.4923117
Test set: Average loss: 0.8897, Accuracy: 3374/5000 (67%)
[epoch 15] loss: 0.4637448
Test set: Average loss: 0.8952, Accuracy: 3360/5000 (67%)
[epoch 16] loss: 0.4371775
Test set: Average loss: 0.8993, Accuracy: 3353/5000 (67%)
[epoch 17] loss: 0.4126311
Test set: Average loss: 0.9124, Accuracy: 3349/5000 (67%)
[epoch 18] loss: 0.3886467
Test set: Average loss: 0.9260, Accuracy: 3322/5000 (66%)
[epoch 19] loss: 0.3640644
Test set: Average loss: 0.9317, Accuracy: 3329/5000 (67%)
[epoch 20] loss: 0.3410301
Test set: Average loss: 0.9421, Accuracy: 3318/5000 (66%)
[epoch 21] loss: 0.3205944
Test set: Average loss: 0.9597, Accuracy: 3351/5000 (67%)
[epoch 22] loss: 0.3002906
Test set: Average loss: 0.9634, Accuracy: 3311/5000 (66%)
[epoch 23] loss: 0.2809497
Test set: Average loss: 0.9936, Accuracy: 3316/5000 (66%)
[epoch 24] loss: 0.2627377
Test set: Average loss: 0.9987, Accuracy: 3294/5000 (66%)
[epoch 25] loss: 0.2435526
Test set: Average loss: 1.0157, Accuracy: 3311/5000 (66%)
Validation:
Test set: Average loss: 0.8857, Accuracy: 3401/5000 (68%)
Test
Test set: Average loss: 0.9032, Accuracy: 3341/5000 (67%)
Test set: Average loss: 0.4831, Accuracy: 12894/15000 (86%)
## seed: 13
Validation accuracy before training:
Test set: Average loss: 1.5707, Accuracy: 1555/5000 (31%)
[epoch 1] loss: 1.1903087
Test set: Average loss: 1.1032, Accuracy: 3085/5000 (62%)
[epoch 2] loss: 0.9968608
Test set: Average loss: 1.0149, Accuracy: 3211/5000 (64%)
[epoch 3] loss: 0.8960757
Test set: Average loss: 0.9629, Accuracy: 3295/5000 (66%)
[epoch 4] loss: 0.8189821
Test set: Average loss: 0.9288, Accuracy: 3324/5000 (66%)
[epoch 5] loss: 0.7543698
Test set: Average loss: 0.9036, Accuracy: 3345/5000 (67%)
[epoch 6] loss: 0.6986448
Test set: Average loss: 0.8811, Accuracy: 3370/5000 (67%)
[epoch 7] loss: 0.6496164
Test set: Average loss: 0.8795, Accuracy: 3352/5000 (67%)
[epoch 8] loss: 0.6054323
Test set: Average loss: 0.8732, Accuracy: 3357/5000 (67%)
[epoch 9] loss: 0.5655743
Test set: Average loss: 0.8703, Accuracy: 3380/5000 (68%)
[epoch 10] loss: 0.5295629
Test set: Average loss: 0.8702, Accuracy: 3368/5000 (67%)
[epoch 11] loss: 0.4963608
Test set: Average loss: 0.8756, Accuracy: 3361/5000 (67%)
[epoch 12] loss: 0.4646743
Test set: Average loss: 0.8848, Accuracy: 3347/5000 (67%)
[epoch 13] loss: 0.4345704
Test set: Average loss: 0.8845, Accuracy: 3388/5000 (68%)
[epoch 14] loss: 0.4060362
Test set: Average loss: 0.8930, Accuracy: 3372/5000 (67%)
[epoch 15] loss: 0.3802886
Test set: Average loss: 0.9110, Accuracy: 3355/5000 (67%)
[epoch 16] loss: 0.3547229
Test set: Average loss: 0.9134, Accuracy: 3369/5000 (67%)
[epoch 17] loss: 0.3319976
Test set: Average loss: 0.9287, Accuracy: 3341/5000 (67%)
[epoch 18] loss: 0.3077804
Test set: Average loss: 0.9419, Accuracy: 3322/5000 (66%)
[epoch 19] loss: 0.2876689
Test set: Average loss: 0.9596, Accuracy: 3327/5000 (67%)
[epoch 20] loss: 0.2665315
Test set: Average loss: 0.9830, Accuracy: 3313/5000 (66%)
[epoch 21] loss: 0.2461122
Test set: Average loss: 0.9818, Accuracy: 3328/5000 (67%)
[epoch 22] loss: 0.2290551
Test set: Average loss: 0.9929, Accuracy: 3311/5000 (66%)
[epoch 23] loss: 0.2118584
Test set: Average loss: 1.0204, Accuracy: 3301/5000 (66%)
[epoch 24] loss: 0.1954531
Test set: Average loss: 1.0336, Accuracy: 3299/5000 (66%)
[epoch 25] loss: 0.1811507
Test set: Average loss: 1.0563, Accuracy: 3286/5000 (66%)
Validation:
Test set: Average loss: 0.8845, Accuracy: 3388/5000 (68%)
Test
Test set: Average loss: 0.8907, Accuracy: 3397/5000 (68%)
Test set: Average loss: 0.3933, Accuracy: 13503/15000 (90%)
20000
## seed: 11
Validation accuracy before training:
Test set: Average loss: 1.6030, Accuracy: 868/5000 (17%)
[epoch 1] loss: 1.1595640
Test set: Average loss: 1.0620, Accuracy: 3144/5000 (63%)
[epoch 2] loss: 0.9482848
Test set: Average loss: 0.9810, Accuracy: 3268/5000 (65%)
[epoch 3] loss: 0.8459618
Test set: Average loss: 0.9306, Accuracy: 3318/5000 (66%)
[epoch 4] loss: 0.7710444
Test set: Average loss: 0.9040, Accuracy: 3363/5000 (67%)
[epoch 5] loss: 0.7101655
Test set: Average loss: 0.8923, Accuracy: 3388/5000 (68%)
[epoch 6] loss: 0.6603773
Test set: Average loss: 0.8751, Accuracy: 3380/5000 (68%)
[epoch 7] loss: 0.6155441
Test set: Average loss: 0.8666, Accuracy: 3401/5000 (68%)
[epoch 8] loss: 0.5767062
Test set: Average loss: 0.8745, Accuracy: 3404/5000 (68%)
[epoch 9] loss: 0.5405588
Test set: Average loss: 0.8801, Accuracy: 3396/5000 (68%)
[epoch 10] loss: 0.5081904
Test set: Average loss: 0.8777, Accuracy: 3403/5000 (68%)
[epoch 11] loss: 0.4779438
Test set: Average loss: 0.9007, Accuracy: 3369/5000 (67%)
[epoch 12] loss: 0.4491185
Test set: Average loss: 0.8989, Accuracy: 3394/5000 (68%)
[epoch 13] loss: 0.4225058
Test set: Average loss: 0.9122, Accuracy: 3366/5000 (67%)
[epoch 14] loss: 0.3976214
Test set: Average loss: 0.9117, Accuracy: 3399/5000 (68%)
[epoch 15] loss: 0.3758276
Test set: Average loss: 0.9237, Accuracy: 3398/5000 (68%)
[epoch 16] loss: 0.3516084
Test set: Average loss: 0.9500, Accuracy: 3344/5000 (67%)
[epoch 17] loss: 0.3302905
Test set: Average loss: 0.9599, Accuracy: 3380/5000 (68%)
[epoch 18] loss: 0.3101801
Test set: Average loss: 0.9751, Accuracy: 3353/5000 (67%)
[epoch 19] loss: 0.2894618
Test set: Average loss: 0.9847, Accuracy: 3364/5000 (67%)
[epoch 20] loss: 0.2714769
Test set: Average loss: 1.0106, Accuracy: 3330/5000 (67%)
[epoch 21] loss: 0.2528303
Test set: Average loss: 1.0322, Accuracy: 3328/5000 (67%)
[epoch 22] loss: 0.2360781
Test set: Average loss: 1.0541, Accuracy: 3342/5000 (67%)
[epoch 23] loss: 0.2217029
Test set: Average loss: 1.0964, Accuracy: 3268/5000 (65%)
[epoch 24] loss: 0.2079751
Test set: Average loss: 1.0913, Accuracy: 3321/5000 (66%)
[epoch 25] loss: 0.1904447
Test set: Average loss: 1.1334, Accuracy: 3291/5000 (66%)
Validation:
Test set: Average loss: 0.8745, Accuracy: 3404/5000 (68%)
Test
Test set: Average loss: 0.8893, Accuracy: 3338/5000 (67%)
Test set: Average loss: 0.5380, Accuracy: 16824/20000 (84%)
## seed: 12
Validation accuracy before training:
Test set: Average loss: 1.4935, Accuracy: 1764/5000 (35%)
[epoch 1] loss: 1.1281923
Test set: Average loss: 1.0420, Accuracy: 3192/5000 (64%)
[epoch 2] loss: 0.9265367
Test set: Average loss: 0.9580, Accuracy: 3294/5000 (66%)
[epoch 3] loss: 0.8278677
Test set: Average loss: 0.9226, Accuracy: 3322/5000 (66%)
[epoch 4] loss: 0.7547745
Test set: Average loss: 0.8958, Accuracy: 3335/5000 (67%)
[epoch 5] loss: 0.6975659
Test set: Average loss: 0.8787, Accuracy: 3359/5000 (67%)
[epoch 6] loss: 0.6476998
Test set: Average loss: 0.8676, Accuracy: 3388/5000 (68%)
[epoch 7] loss: 0.6047788
Test set: Average loss: 0.8716, Accuracy: 3389/5000 (68%)
[epoch 8] loss: 0.5659319
Test set: Average loss: 0.8702, Accuracy: 3399/5000 (68%)
[epoch 9] loss: 0.5313696
Test set: Average loss: 0.8753, Accuracy: 3389/5000 (68%)
[epoch 10] loss: 0.4995978
Test set: Average loss: 0.8778, Accuracy: 3391/5000 (68%)
[epoch 11] loss: 0.4698260
Test set: Average loss: 0.8924, Accuracy: 3361/5000 (67%)
[epoch 12] loss: 0.4418327
Test set: Average loss: 0.8988, Accuracy: 3379/5000 (68%)
[epoch 13] loss: 0.4147432
Test set: Average loss: 0.9135, Accuracy: 3377/5000 (68%)
[epoch 14] loss: 0.3924397
Test set: Average loss: 0.9259, Accuracy: 3353/5000 (67%)
[epoch 15] loss: 0.3677636
Test set: Average loss: 0.9302, Accuracy: 3369/5000 (67%)
[epoch 16] loss: 0.3457850
Test set: Average loss: 0.9534, Accuracy: 3359/5000 (67%)
[epoch 17] loss: 0.3254246
Test set: Average loss: 0.9631, Accuracy: 3350/5000 (67%)
[epoch 18] loss: 0.3051350
Test set: Average loss: 0.9835, Accuracy: 3327/5000 (67%)
[epoch 19] loss: 0.2876406
Test set: Average loss: 1.0052, Accuracy: 3334/5000 (67%)
[epoch 20] loss: 0.2683348
Test set: Average loss: 1.0206, Accuracy: 3322/5000 (66%)
[epoch 21] loss: 0.2520448
Test set: Average loss: 1.0430, Accuracy: 3339/5000 (67%)
[epoch 22] loss: 0.2371818
Test set: Average loss: 1.0517, Accuracy: 3329/5000 (67%)
[epoch 23] loss: 0.2202382
Test set: Average loss: 1.0672, Accuracy: 3311/5000 (66%)
[epoch 24] loss: 0.2062424
Test set: Average loss: 1.1010, Accuracy: 3291/5000 (66%)
[epoch 25] loss: 0.1929191
Test set: Average loss: 1.1205, Accuracy: 3262/5000 (65%)
Validation:
Test set: Average loss: 0.8702, Accuracy: 3399/5000 (68%)
Test
Test set: Average loss: 0.8759, Accuracy: 3372/5000 (67%)
Test set: Average loss: 0.5229, Accuracy: 16901/20000 (85%)
## seed: 13
Validation accuracy before training:
Test set: Average loss: 1.5795, Accuracy: 1433/5000 (29%)
[epoch 1] loss: 1.1445854
Test set: Average loss: 1.0686, Accuracy: 3141/5000 (63%)
[epoch 2] loss: 0.9336193
Test set: Average loss: 0.9813, Accuracy: 3253/5000 (65%)
[epoch 3] loss: 0.8272971
Test set: Average loss: 0.9315, Accuracy: 3339/5000 (67%)
[epoch 4] loss: 0.7506452
Test set: Average loss: 0.9086, Accuracy: 3347/5000 (67%)
[epoch 5] loss: 0.6904261
Test set: Average loss: 0.8874, Accuracy: 3383/5000 (68%)
[epoch 6] loss: 0.6391541
Test set: Average loss: 0.8779, Accuracy: 3410/5000 (68%)
[epoch 7] loss: 0.5952417
Test set: Average loss: 0.8725, Accuracy: 3404/5000 (68%)
[epoch 8] loss: 0.5552441
Test set: Average loss: 0.8764, Accuracy: 3401/5000 (68%)
[epoch 9] loss: 0.5193438
Test set: Average loss: 0.8807, Accuracy: 3396/5000 (68%)
[epoch 10] loss: 0.4870342
Test set: Average loss: 0.8950, Accuracy: 3387/5000 (68%)
[epoch 11] loss: 0.4564732
Test set: Average loss: 0.9057, Accuracy: 3379/5000 (68%)
[epoch 12] loss: 0.4294662
Test set: Average loss: 0.9151, Accuracy: 3371/5000 (67%)
[epoch 13] loss: 0.4017431
Test set: Average loss: 0.9207, Accuracy: 3354/5000 (67%)
[epoch 14] loss: 0.3764805
Test set: Average loss: 0.9358, Accuracy: 3352/5000 (67%)
[epoch 15] loss: 0.3523338
Test set: Average loss: 0.9455, Accuracy: 3352/5000 (67%)
[epoch 16] loss: 0.3335987
Test set: Average loss: 0.9603, Accuracy: 3345/5000 (67%)
[epoch 17] loss: 0.3105207
Test set: Average loss: 0.9768, Accuracy: 3326/5000 (67%)
[epoch 18] loss: 0.2898644
Test set: Average loss: 1.0085, Accuracy: 3304/5000 (66%)
[epoch 19] loss: 0.2720186
Test set: Average loss: 1.0146, Accuracy: 3311/5000 (66%)
[epoch 20] loss: 0.2533851
Test set: Average loss: 1.0314, Accuracy: 3306/5000 (66%)
[epoch 21] loss: 0.2368522
Test set: Average loss: 1.0438, Accuracy: 3309/5000 (66%)
[epoch 22] loss: 0.2209832
Test set: Average loss: 1.0707, Accuracy: 3273/5000 (65%)
[epoch 23] loss: 0.2040208
Test set: Average loss: 1.0874, Accuracy: 3273/5000 (65%)
[epoch 24] loss: 0.1911630
Test set: Average loss: 1.1152, Accuracy: 3242/5000 (65%)
[epoch 25] loss: 0.1772939
Test set: Average loss: 1.1488, Accuracy: 3281/5000 (66%)
Validation:
Test set: Average loss: 0.8779, Accuracy: 3410/5000 (68%)
Test
Test set: Average loss: 0.8835, Accuracy: 3388/5000 (68%)
Test set: Average loss: 0.5872, Accuracy: 16558/20000 (83%)
## Pre-Training AnB
Validation accuracy before training:
Test set: Average loss: 1.6072, Accuracy: 945/5000 (19%)
[epoch 1] loss: 1.2757209
Test set: Average loss: 1.2267, Accuracy: 2659/5000 (53%)
[epoch 2] loss: 1.1779781
Test set: Average loss: 1.1892, Accuracy: 2671/5000 (53%)
[epoch 3] loss: 1.1326573
Test set: Average loss: 1.1636, Accuracy: 2783/5000 (56%)
[epoch 4] loss: 1.0967593
Test set: Average loss: 1.1463, Accuracy: 2803/5000 (56%)
[epoch 5] loss: 1.0649630
Test set: Average loss: 1.1353, Accuracy: 2863/5000 (57%)
[epoch 6] loss: 1.0360396
Test set: Average loss: 1.1151, Accuracy: 2877/5000 (58%)
[epoch 7] loss: 1.0077258
Test set: Average loss: 1.1083, Accuracy: 2913/5000 (58%)
[epoch 8] loss: 0.9815573
Test set: Average loss: 1.1041, Accuracy: 2896/5000 (58%)
[epoch 9] loss: 0.9572636
Test set: Average loss: 1.0934, Accuracy: 2951/5000 (59%)
[epoch 10] loss: 0.9319001
Test set: Average loss: 1.0918, Accuracy: 2953/5000 (59%)
[epoch 11] loss: 0.9068900
Test set: Average loss: 1.0830, Accuracy: 2963/5000 (59%)
[epoch 12] loss: 0.8819104
Test set: Average loss: 1.0788, Accuracy: 2988/5000 (60%)
[epoch 13] loss: 0.8569538
Test set: Average loss: 1.0788, Accuracy: 2951/5000 (59%)
[epoch 14] loss: 0.8323701
Test set: Average loss: 1.0786, Accuracy: 2991/5000 (60%)
[epoch 15] loss: 0.8101015
Test set: Average loss: 1.0742, Accuracy: 2984/5000 (60%)
[epoch 16] loss: 0.7869279
Test set: Average loss: 1.0815, Accuracy: 2985/5000 (60%)
[epoch 17] loss: 0.7617036
Test set: Average loss: 1.0912, Accuracy: 2963/5000 (59%)
[epoch 18] loss: 0.7375307
Test set: Average loss: 1.0862, Accuracy: 2953/5000 (59%)
[epoch 19] loss: 0.7145475
Test set: Average loss: 1.0990, Accuracy: 2929/5000 (59%)
[epoch 20] loss: 0.6921788
Test set: Average loss: 1.1007, Accuracy: 2966/5000 (59%)
[epoch 21] loss: 0.6700756
Test set: Average loss: 1.1036, Accuracy: 2937/5000 (59%)
[epoch 22] loss: 0.6487836
Test set: Average loss: 1.1540, Accuracy: 2886/5000 (58%)
[epoch 23] loss: 0.6248348
Test set: Average loss: 1.1340, Accuracy: 2939/5000 (59%)
[epoch 24] loss: 0.6048285
Test set: Average loss: 1.1350, Accuracy: 2924/5000 (58%)
[epoch 25] loss: 0.5793455
Test set: Average loss: 1.1649, Accuracy: 2898/5000 (58%)
Validation:
Test set: Average loss: 1.0786, Accuracy: 2991/5000 (60%)
Test set: Average loss: 1.0395, Accuracy: 2962/5000 (59%)
25
## seed: 11
Validation accuracy before training:
Test set: Average loss: 1.6706, Accuracy: 999/5000 (20%)
[epoch 1] loss: 1.6308408
Test set: Average loss: 1.6632, Accuracy: 1019/5000 (20%)
[epoch 2] loss: 1.5836821
Test set: Average loss: 1.6560, Accuracy: 1034/5000 (21%)
[epoch 3] loss: 1.5384080
Test set: Average loss: 1.6490, Accuracy: 1044/5000 (21%)
[epoch 4] loss: 1.4954176
Test set: Average loss: 1.6424, Accuracy: 1047/5000 (21%)
[epoch 5] loss: 1.4548486
Test set: Average loss: 1.6361, Accuracy: 1076/5000 (22%)
[epoch 6] loss: 1.4166405
Test set: Average loss: 1.6301, Accuracy: 1087/5000 (22%)
[epoch 7] loss: 1.3806480
Test set: Average loss: 1.6245, Accuracy: 1109/5000 (22%)
[epoch 8] loss: 1.3467423
Test set: Average loss: 1.6193, Accuracy: 1138/5000 (23%)
[epoch 9] loss: 1.3148451
Test set: Average loss: 1.6144, Accuracy: 1165/5000 (23%)
[epoch 10] loss: 1.2849022
Test set: Average loss: 1.6098, Accuracy: 1182/5000 (24%)
[epoch 11] loss: 1.2568386
Test set: Average loss: 1.6054, Accuracy: 1205/5000 (24%)
[epoch 12] loss: 1.2305367
Test set: Average loss: 1.6013, Accuracy: 1227/5000 (25%)
[epoch 13] loss: 1.2058407
Test set: Average loss: 1.5974, Accuracy: 1240/5000 (25%)
[epoch 14] loss: 1.1825807
Test set: Average loss: 1.5937, Accuracy: 1252/5000 (25%)
[epoch 15] loss: 1.1605977
Test set: Average loss: 1.5901, Accuracy: 1269/5000 (25%)
[epoch 16] loss: 1.1397587
Test set: Average loss: 1.5866, Accuracy: 1286/5000 (26%)
[epoch 17] loss: 1.1199588
Test set: Average loss: 1.5833, Accuracy: 1298/5000 (26%)
[epoch 18] loss: 1.1011157
Test set: Average loss: 1.5800, Accuracy: 1322/5000 (26%)
[epoch 19] loss: 1.0831668
Test set: Average loss: 1.5769, Accuracy: 1344/5000 (27%)
[epoch 20] loss: 1.0660650
Test set: Average loss: 1.5738, Accuracy: 1356/5000 (27%)
[epoch 21] loss: 1.0497721
Test set: Average loss: 1.5708, Accuracy: 1376/5000 (28%)
[epoch 22] loss: 1.0342517
Test set: Average loss: 1.5678, Accuracy: 1390/5000 (28%)
[epoch 23] loss: 1.0194576
Test set: Average loss: 1.5650, Accuracy: 1412/5000 (28%)
[epoch 24] loss: 1.0053338
Test set: Average loss: 1.5622, Accuracy: 1421/5000 (28%)
[epoch 25] loss: 0.9918154
Test set: Average loss: 1.5594, Accuracy: 1441/5000 (29%)
Validation:
Test set: Average loss: 1.5594, Accuracy: 1441/5000 (29%)
Test
Test set: Average loss: 1.5603, Accuracy: 1445/5000 (29%)
Test set: Average loss: 0.9788, Accuracy: 23/25 (92%)
## seed: 12
Validation accuracy before training:
Test set: Average loss: 1.6563, Accuracy: 788/5000 (16%)
[epoch 1] loss: 1.6716303
Test set: Average loss: 1.6452, Accuracy: 829/5000 (17%)
[epoch 2] loss: 1.6251773
Test set: Average loss: 1.6346, Accuracy: 887/5000 (18%)
[epoch 3] loss: 1.5795965
Test set: Average loss: 1.6244, Accuracy: 939/5000 (19%)
[epoch 4] loss: 1.5354952
Test set: Average loss: 1.6148, Accuracy: 998/5000 (20%)
[epoch 5] loss: 1.4933696
Test set: Average loss: 1.6058, Accuracy: 1061/5000 (21%)
[epoch 6] loss: 1.4536127
Test set: Average loss: 1.5973, Accuracy: 1107/5000 (22%)
[epoch 7] loss: 1.4164743
Test set: Average loss: 1.5895, Accuracy: 1166/5000 (23%)
[epoch 8] loss: 1.3820145
Test set: Average loss: 1.5823, Accuracy: 1193/5000 (24%)
[epoch 9] loss: 1.3501221
Test set: Average loss: 1.5757, Accuracy: 1221/5000 (24%)
[epoch 10] loss: 1.3205811
Test set: Average loss: 1.5696, Accuracy: 1255/5000 (25%)
[epoch 11] loss: 1.2931390
Test set: Average loss: 1.5640, Accuracy: 1290/5000 (26%)
[epoch 12] loss: 1.2675418
Test set: Average loss: 1.5588, Accuracy: 1338/5000 (27%)
[epoch 13] loss: 1.2435461
Test set: Average loss: 1.5540, Accuracy: 1368/5000 (27%)
[epoch 14] loss: 1.2209255
Test set: Average loss: 1.5496, Accuracy: 1397/5000 (28%)
[epoch 15] loss: 1.1994786
Test set: Average loss: 1.5454, Accuracy: 1415/5000 (28%)
[epoch 16] loss: 1.1790432
Test set: Average loss: 1.5415, Accuracy: 1441/5000 (29%)
[epoch 17] loss: 1.1595027
Test set: Average loss: 1.5378, Accuracy: 1461/5000 (29%)
[epoch 18] loss: 1.1407807
Test set: Average loss: 1.5343, Accuracy: 1484/5000 (30%)
[epoch 19] loss: 1.1228309
Test set: Average loss: 1.5310, Accuracy: 1519/5000 (30%)
[epoch 20] loss: 1.1056254
Test set: Average loss: 1.5277, Accuracy: 1539/5000 (31%)
[epoch 21] loss: 1.0891420
Test set: Average loss: 1.5247, Accuracy: 1562/5000 (31%)
[epoch 22] loss: 1.0733573
Test set: Average loss: 1.5217, Accuracy: 1580/5000 (32%)
[epoch 23] loss: 1.0582454
Test set: Average loss: 1.5188, Accuracy: 1592/5000 (32%)
[epoch 24] loss: 1.0437776
Test set: Average loss: 1.5160, Accuracy: 1607/5000 (32%)
[epoch 25] loss: 1.0299244
Test set: Average loss: 1.5133, Accuracy: 1624/5000 (32%)
Validation:
Test set: Average loss: 1.5133, Accuracy: 1624/5000 (32%)
Test
Test set: Average loss: 1.5127, Accuracy: 1612/5000 (32%)
Test set: Average loss: 1.0167, Accuracy: 21/25 (84%)
## seed: 13
Validation accuracy before training:
Test set: Average loss: 1.7457, Accuracy: 531/5000 (11%)
[epoch 1] loss: 1.7161847
Test set: Average loss: 1.7337, Accuracy: 561/5000 (11%)
[epoch 2] loss: 1.6741937
Test set: Average loss: 1.7220, Accuracy: 593/5000 (12%)
[epoch 3] loss: 1.6334941
Test set: Average loss: 1.7108, Accuracy: 652/5000 (13%)
[epoch 4] loss: 1.5943451
Test set: Average loss: 1.6999, Accuracy: 707/5000 (14%)
[epoch 5] loss: 1.5569118
Test set: Average loss: 1.6894, Accuracy: 760/5000 (15%)
[epoch 6] loss: 1.5212543
Test set: Average loss: 1.6793, Accuracy: 807/5000 (16%)
[epoch 7] loss: 1.4873463
Test set: Average loss: 1.6695, Accuracy: 842/5000 (17%)
[epoch 8] loss: 1.4551462
Test set: Average loss: 1.6602, Accuracy: 887/5000 (18%)
[epoch 9] loss: 1.4246254
Test set: Average loss: 1.6512, Accuracy: 917/5000 (18%)
[epoch 10] loss: 1.3957771
Test set: Average loss: 1.6426, Accuracy: 981/5000 (20%)
[epoch 11] loss: 1.3685991
Test set: Average loss: 1.6344, Accuracy: 1038/5000 (21%)
[epoch 12] loss: 1.3430793
Test set: Average loss: 1.6266, Accuracy: 1087/5000 (22%)
[epoch 13] loss: 1.3191857
Test set: Average loss: 1.6191, Accuracy: 1126/5000 (23%)
[epoch 14] loss: 1.2968445
Test set: Average loss: 1.6121, Accuracy: 1179/5000 (24%)
[epoch 15] loss: 1.2759193
Test set: Average loss: 1.6054, Accuracy: 1208/5000 (24%)
[epoch 16] loss: 1.2562195
Test set: Average loss: 1.5992, Accuracy: 1252/5000 (25%)
[epoch 17] loss: 1.2375458
Test set: Average loss: 1.5932, Accuracy: 1286/5000 (26%)
[epoch 18] loss: 1.2197345
Test set: Average loss: 1.5877, Accuracy: 1309/5000 (26%)
[epoch 19] loss: 1.2026792
Test set: Average loss: 1.5824, Accuracy: 1329/5000 (27%)
[epoch 20] loss: 1.1863284
Test set: Average loss: 1.5774, Accuracy: 1352/5000 (27%)
[epoch 21] loss: 1.1706656
Test set: Average loss: 1.5727, Accuracy: 1376/5000 (28%)
[epoch 22] loss: 1.1556685
Test set: Average loss: 1.5682, Accuracy: 1394/5000 (28%)
[epoch 23] loss: 1.1412747
Test set: Average loss: 1.5638, Accuracy: 1416/5000 (28%)
[epoch 24] loss: 1.1273866
Test set: Average loss: 1.5596, Accuracy: 1435/5000 (29%)
[epoch 25] loss: 1.1139020
Test set: Average loss: 1.5556, Accuracy: 1457/5000 (29%)
Validation:
Test set: Average loss: 1.5556, Accuracy: 1457/5000 (29%)
Test
Test set: Average loss: 1.5492, Accuracy: 1461/5000 (29%)
Test set: Average loss: 1.1007, Accuracy: 21/25 (84%)
50
## seed: 11
Validation accuracy before training:
Test set: Average loss: 1.6447, Accuracy: 974/5000 (19%)
[epoch 1] loss: 1.6022022
Test set: Average loss: 1.6311, Accuracy: 1040/5000 (21%)
[epoch 2] loss: 1.5365452
Test set: Average loss: 1.6168, Accuracy: 1103/5000 (22%)
[epoch 3] loss: 1.4967976
Test set: Average loss: 1.6040, Accuracy: 1154/5000 (23%)
[epoch 4] loss: 1.4532205
Test set: Average loss: 1.5922, Accuracy: 1230/5000 (25%)
[epoch 5] loss: 1.4164335
Test set: Average loss: 1.5812, Accuracy: 1264/5000 (25%)
[epoch 6] loss: 1.3721308
Test set: Average loss: 1.5712, Accuracy: 1316/5000 (26%)
[epoch 7] loss: 1.3410364
Test set: Average loss: 1.5619, Accuracy: 1366/5000 (27%)
[epoch 8] loss: 1.3182425
Test set: Average loss: 1.5535, Accuracy: 1395/5000 (28%)
[epoch 9] loss: 1.2775377
Test set: Average loss: 1.5455, Accuracy: 1427/5000 (29%)
[epoch 10] loss: 1.2543064
Test set: Average loss: 1.5383, Accuracy: 1452/5000 (29%)
[epoch 11] loss: 1.2123592
Test set: Average loss: 1.5318, Accuracy: 1476/5000 (30%)
[epoch 12] loss: 1.1674630
Test set: Average loss: 1.5257, Accuracy: 1507/5000 (30%)
[epoch 13] loss: 1.1786413
Epoch 12: reducing learning rate of group 0 to 5.0000e-06.
Test set: Average loss: 1.5201, Accuracy: 1530/5000 (31%)
[epoch 14] loss: 1.1791594
Epoch 13: reducing learning rate of group 0 to 5.0000e-07.
Test set: Average loss: 1.5196, Accuracy: 1531/5000 (31%)
[epoch 15] loss: 1.1594865
Test set: Average loss: 1.5195, Accuracy: 1531/5000 (31%)
[epoch 16] loss: 1.1433457
Test set: Average loss: 1.5195, Accuracy: 1531/5000 (31%)
[epoch 17] loss: 1.1639726
Epoch 16: reducing learning rate of group 0 to 5.0000e-08.
Test set: Average loss: 1.5194, Accuracy: 1531/5000 (31%)
[epoch 18] loss: 1.1536040
Epoch 17: reducing learning rate of group 0 to 5.0000e-09.
Test set: Average loss: 1.5194, Accuracy: 1531/5000 (31%)
[epoch 19] loss: 1.1472760
Epoch 18: reducing learning rate of group 0 to 5.0000e-10.
Test set: Average loss: 1.5194, Accuracy: 1531/5000 (31%)
[epoch 20] loss: 1.1644460
Epoch 19: reducing learning rate of group 0 to 5.0000e-11.
Test set: Average loss: 1.5194, Accuracy: 1531/5000 (31%)
[epoch 21] loss: 1.1634560
Epoch 20: reducing learning rate of group 0 to 5.0000e-12.
Test set: Average loss: 1.5194, Accuracy: 1531/5000 (31%)
[epoch 22] loss: 1.1390086
Test set: Average loss: 1.5194, Accuracy: 1531/5000 (31%)
[epoch 23] loss: 1.1637473
Epoch 22: reducing learning rate of group 0 to 5.0000e-13.
Test set: Average loss: 1.5194, Accuracy: 1531/5000 (31%)
[epoch 24] loss: 1.1641502
Epoch 23: reducing learning rate of group 0 to 5.0000e-14.
Test set: Average loss: 1.5194, Accuracy: 1531/5000 (31%)
[epoch 25] loss: 1.1563054
Epoch 24: reducing learning rate of group 0 to 5.0000e-15.
Test set: Average loss: 1.5194, Accuracy: 1531/5000 (31%)
Validation:
Test set: Average loss: 1.5194, Accuracy: 1531/5000 (31%)
Test
Test set: Average loss: 1.5179, Accuracy: 1490/5000 (30%)
Test set: Average loss: 1.1495, Accuracy: 34/50 (68%)
## seed: 12
Validation accuracy before training:
Test set: Average loss: 1.7544, Accuracy: 842/5000 (17%)
[epoch 1] loss: 1.8336269
Test set: Average loss: 1.7382, Accuracy: 876/5000 (18%)
[epoch 2] loss: 1.7947304
Test set: Average loss: 1.7250, Accuracy: 886/5000 (18%)
[epoch 3] loss: 1.7129429
Test set: Average loss: 1.7117, Accuracy: 916/5000 (18%)
[epoch 4] loss: 1.6378260
Test set: Average loss: 1.6988, Accuracy: 944/5000 (19%)
[epoch 5] loss: 1.6045356
Test set: Average loss: 1.6868, Accuracy: 963/5000 (19%)
[epoch 6] loss: 1.5313068
Test set: Average loss: 1.6756, Accuracy: 1002/5000 (20%)
[epoch 7] loss: 1.4985461
Test set: Average loss: 1.6649, Accuracy: 1035/5000 (21%)
[epoch 8] loss: 1.4509532
Test set: Average loss: 1.6545, Accuracy: 1060/5000 (21%)
[epoch 9] loss: 1.4023536
Test set: Average loss: 1.6448, Accuracy: 1101/5000 (22%)
[epoch 10] loss: 1.3602370
Test set: Average loss: 1.6360, Accuracy: 1148/5000 (23%)
[epoch 11] loss: 1.3282616
Test set: Average loss: 1.6276, Accuracy: 1203/5000 (24%)
[epoch 12] loss: 1.3304234
Epoch 11: reducing learning rate of group 0 to 5.0000e-06.
Test set: Average loss: 1.6196, Accuracy: 1248/5000 (25%)
[epoch 13] loss: 1.2802533
Test set: Average loss: 1.6189, Accuracy: 1249/5000 (25%)
[epoch 14] loss: 1.2603082
Test set: Average loss: 1.6182, Accuracy: 1250/5000 (25%)
[epoch 15] loss: 1.2902563
Epoch 14: reducing learning rate of group 0 to 5.0000e-07.
Test set: Average loss: 1.6176, Accuracy: 1251/5000 (25%)
[epoch 16] loss: 1.2609856
Epoch 15: reducing learning rate of group 0 to 5.0000e-08.
Test set: Average loss: 1.6175, Accuracy: 1251/5000 (25%)
[epoch 17] loss: 1.2836332
Epoch 16: reducing learning rate of group 0 to 5.0000e-09.
Test set: Average loss: 1.6175, Accuracy: 1251/5000 (25%)
[epoch 18] loss: 1.2639551
Epoch 17: reducing learning rate of group 0 to 5.0000e-10.
Test set: Average loss: 1.6175, Accuracy: 1251/5000 (25%)
[epoch 19] loss: 1.2610921
Epoch 18: reducing learning rate of group 0 to 5.0000e-11.
Test set: Average loss: 1.6175, Accuracy: 1251/5000 (25%)
[epoch 20] loss: 1.2727028
Epoch 19: reducing learning rate of group 0 to 5.0000e-12.
Test set: Average loss: 1.6175, Accuracy: 1251/5000 (25%)
[epoch 21] loss: 1.2582715
Test set: Average loss: 1.6175, Accuracy: 1251/5000 (25%)
[epoch 22] loss: 1.2714899
Epoch 21: reducing learning rate of group 0 to 5.0000e-13.
Test set: Average loss: 1.6175, Accuracy: 1251/5000 (25%)
[epoch 23] loss: 1.2519433
Test set: Average loss: 1.6175, Accuracy: 1251/5000 (25%)
[epoch 24] loss: 1.2633858
Epoch 23: reducing learning rate of group 0 to 5.0000e-14.
Test set: Average loss: 1.6175, Accuracy: 1251/5000 (25%)
[epoch 25] loss: 1.2453890
Test set: Average loss: 1.6175, Accuracy: 1251/5000 (25%)
Validation:
Test set: Average loss: 1.6175, Accuracy: 1251/5000 (25%)
Test
Test set: Average loss: 1.6191, Accuracy: 1223/5000 (24%)
Test set: Average loss: 1.2667, Accuracy: 29/50 (58%)
## seed: 13
Validation accuracy before training:
Test set: Average loss: 1.6904, Accuracy: 842/5000 (17%)
[epoch 1] loss: 1.7328702
Test set: Average loss: 1.6711, Accuracy: 945/5000 (19%)
[epoch 2] loss: 1.6600788
Test set: Average loss: 1.6535, Accuracy: 1057/5000 (21%)
[epoch 3] loss: 1.5982994
Test set: Average loss: 1.6389, Accuracy: 1138/5000 (23%)
[epoch 4] loss: 1.5167212
Test set: Average loss: 1.6254, Accuracy: 1180/5000 (24%)
[epoch 5] loss: 1.5192439
Epoch 4: reducing learning rate of group 0 to 5.0000e-06.
Test set: Average loss: 1.6133, Accuracy: 1226/5000 (25%)
[epoch 6] loss: 1.4645609
Test set: Average loss: 1.6122, Accuracy: 1232/5000 (25%)
[epoch 7] loss: 1.4637001
Test set: Average loss: 1.6111, Accuracy: 1240/5000 (25%)
[epoch 8] loss: 1.4524914
Test set: Average loss: 1.6100, Accuracy: 1248/5000 (25%)
[epoch 9] loss: 1.4474130
Test set: Average loss: 1.6089, Accuracy: 1255/5000 (25%)
[epoch 10] loss: 1.4453831
Test set: Average loss: 1.6078, Accuracy: 1259/5000 (25%)
[epoch 11] loss: 1.4312384
Test set: Average loss: 1.6067, Accuracy: 1266/5000 (25%)
[epoch 12] loss: 1.4233966
Test set: Average loss: 1.6056, Accuracy: 1265/5000 (25%)
[epoch 13] loss: 1.4395214
Epoch 12: reducing learning rate of group 0 to 5.0000e-07.
Test set: Average loss: 1.6045, Accuracy: 1270/5000 (25%)
[epoch 14] loss: 1.4215117
Test set: Average loss: 1.6044, Accuracy: 1272/5000 (25%)
[epoch 15] loss: 1.4263098
Epoch 14: reducing learning rate of group 0 to 5.0000e-08.
Test set: Average loss: 1.6043, Accuracy: 1272/5000 (25%)
[epoch 16] loss: 1.3965112
Test set: Average loss: 1.6043, Accuracy: 1272/5000 (25%)
[epoch 17] loss: 1.4212644
Epoch 16: reducing learning rate of group 0 to 5.0000e-09.
Test set: Average loss: 1.6043, Accuracy: 1272/5000 (25%)
[epoch 18] loss: 1.4275162
Epoch 17: reducing learning rate of group 0 to 5.0000e-10.
Test set: Average loss: 1.6043, Accuracy: 1272/5000 (25%)
[epoch 19] loss: 1.4201584
Epoch 18: reducing learning rate of group 0 to 5.0000e-11.
Test set: Average loss: 1.6043, Accuracy: 1272/5000 (25%)
[epoch 20] loss: 1.4263897
Epoch 19: reducing learning rate of group 0 to 5.0000e-12.
Test set: Average loss: 1.6043, Accuracy: 1272/5000 (25%)
[epoch 21] loss: 1.4368604
Epoch 20: reducing learning rate of group 0 to 5.0000e-13.
Test set: Average loss: 1.6043, Accuracy: 1272/5000 (25%)
[epoch 22] loss: 1.4021899
Epoch 21: reducing learning rate of group 0 to 5.0000e-14.
Test set: Average loss: 1.6043, Accuracy: 1272/5000 (25%)
[epoch 23] loss: 1.4384947
Epoch 22: reducing learning rate of group 0 to 5.0000e-15.
Test set: Average loss: 1.6043, Accuracy: 1272/5000 (25%)
[epoch 24] loss: 1.4164188
Epoch 23: reducing learning rate of group 0 to 5.0000e-16.
Test set: Average loss: 1.6043, Accuracy: 1272/5000 (25%)
[epoch 25] loss: 1.4194486
Epoch 24: reducing learning rate of group 0 to 5.0000e-17.
Test set: Average loss: 1.6043, Accuracy: 1272/5000 (25%)
Validation:
Test set: Average loss: 1.6043, Accuracy: 1272/5000 (25%)
Test
Test set: Average loss: 1.6004, Accuracy: 1243/5000 (25%)
Test set: Average loss: 1.4225, Accuracy: 26/50 (52%)
100
## seed: 11
Validation accuracy before training:
Test set: Average loss: 1.6807, Accuracy: 933/5000 (19%)
[epoch 1] loss: 1.6029186
Test set: Average loss: 1.6261, Accuracy: 1086/5000 (22%)
[epoch 2] loss: 1.5222308
Test set: Average loss: 1.5824, Accuracy: 1219/5000 (24%)
[epoch 3] loss: 1.4499297
Test set: Average loss: 1.5520, Accuracy: 1354/5000 (27%)
[epoch 4] loss: 1.4181841
Test set: Average loss: 1.5317, Accuracy: 1436/5000 (29%)
[epoch 5] loss: 1.3651770
Test set: Average loss: 1.5163, Accuracy: 1481/5000 (30%)
[epoch 6] loss: 1.3008501
Test set: Average loss: 1.5028, Accuracy: 1525/5000 (30%)
[epoch 7] loss: 1.2720674
Test set: Average loss: 1.4900, Accuracy: 1560/5000 (31%)
[epoch 8] loss: 1.2643121
Test set: Average loss: 1.4791, Accuracy: 1602/5000 (32%)
[epoch 9] loss: 1.2408860
Test set: Average loss: 1.4686, Accuracy: 1633/5000 (33%)
[epoch 10] loss: 1.1517822
Test set: Average loss: 1.4584, Accuracy: 1658/5000 (33%)
[epoch 11] loss: 1.1908831
Epoch 10: reducing learning rate of group 0 to 5.0000e-06.
Test set: Average loss: 1.4490, Accuracy: 1687/5000 (34%)
[epoch 12] loss: 1.1474380
Test set: Average loss: 1.4482, Accuracy: 1691/5000 (34%)
[epoch 13] loss: 1.1783715
Epoch 12: reducing learning rate of group 0 to 5.0000e-07.
Test set: Average loss: 1.4475, Accuracy: 1698/5000 (34%)
[epoch 14] loss: 1.1366190
Test set: Average loss: 1.4474, Accuracy: 1698/5000 (34%)
[epoch 15] loss: 1.1003131
Test set: Average loss: 1.4474, Accuracy: 1698/5000 (34%)
[epoch 16] loss: 1.1631296
Epoch 15: reducing learning rate of group 0 to 5.0000e-08.
Test set: Average loss: 1.4473, Accuracy: 1698/5000 (34%)
[epoch 17] loss: 1.1692515
Epoch 16: reducing learning rate of group 0 to 5.0000e-09.
Test set: Average loss: 1.4473, Accuracy: 1698/5000 (34%)
[epoch 18] loss: 1.2090156
Epoch 17: reducing learning rate of group 0 to 5.0000e-10.
Test set: Average loss: 1.4473, Accuracy: 1698/5000 (34%)
[epoch 19] loss: 1.1415346
Epoch 18: reducing learning rate of group 0 to 5.0000e-11.
Test set: Average loss: 1.4473, Accuracy: 1698/5000 (34%)
[epoch 20] loss: 1.1538261
Epoch 19: reducing learning rate of group 0 to 5.0000e-12.
Test set: Average loss: 1.4473, Accuracy: 1698/5000 (34%)
[epoch 21] loss: 1.1336942
Epoch 20: reducing learning rate of group 0 to 5.0000e-13.
Test set: Average loss: 1.4473, Accuracy: 1698/5000 (34%)
[epoch 22] loss: 1.1892692
Epoch 21: reducing learning rate of group 0 to 5.0000e-14.
Test set: Average loss: 1.4473, Accuracy: 1698/5000 (34%)
[epoch 23] loss: 1.1881096
Epoch 22: reducing learning rate of group 0 to 5.0000e-15.
Test set: Average loss: 1.4473, Accuracy: 1698/5000 (34%)
[epoch 24] loss: 1.1107739
Epoch 23: reducing learning rate of group 0 to 5.0000e-16.
Test set: Average loss: 1.4473, Accuracy: 1698/5000 (34%)
[epoch 25] loss: 1.1571169
Epoch 24: reducing learning rate of group 0 to 5.0000e-17.
Test set: Average loss: 1.4473, Accuracy: 1698/5000 (34%)
Validation:
Test set: Average loss: 1.4473, Accuracy: 1698/5000 (34%)
Test
Test set: Average loss: 1.4529, Accuracy: 1670/5000 (33%)
Test set: Average loss: 1.1526, Accuracy: 69/100 (69%)
## seed: 12
Validation accuracy before training:
Test set: Average loss: 1.6866, Accuracy: 794/5000 (16%)
[epoch 1] loss: 1.6706929
Test set: Average loss: 1.6505, Accuracy: 895/5000 (18%)
[epoch 2] loss: 1.5780961
Test set: Average loss: 1.6184, Accuracy: 1097/5000 (22%)
[epoch 3] loss: 1.6102410
Epoch 2: reducing learning rate of group 0 to 5.0000e-06.
Test set: Average loss: 1.5899, Accuracy: 1283/5000 (26%)
[epoch 4] loss: 1.4734114
Test set: Average loss: 1.5875, Accuracy: 1302/5000 (26%)
[epoch 5] loss: 1.5229200
Epoch 4: reducing learning rate of group 0 to 5.0000e-07.
Test set: Average loss: 1.5853, Accuracy: 1325/5000 (26%)
[epoch 6] loss: 1.5268331
Epoch 5: reducing learning rate of group 0 to 5.0000e-08.
Test set: Average loss: 1.5851, Accuracy: 1327/5000 (27%)
[epoch 7] loss: 1.4646258
Test set: Average loss: 1.5851, Accuracy: 1327/5000 (27%)
[epoch 8] loss: 1.4755377
Epoch 7: reducing learning rate of group 0 to 5.0000e-09.
Test set: Average loss: 1.5850, Accuracy: 1327/5000 (27%)
[epoch 9] loss: 1.4960738
Epoch 8: reducing learning rate of group 0 to 5.0000e-10.
Test set: Average loss: 1.5850, Accuracy: 1327/5000 (27%)
[epoch 10] loss: 1.4710402
Epoch 9: reducing learning rate of group 0 to 5.0000e-11.
Test set: Average loss: 1.5850, Accuracy: 1327/5000 (27%)
[epoch 11] loss: 1.4510300
Test set: Average loss: 1.5850, Accuracy: 1327/5000 (27%)
[epoch 12] loss: 1.4888268
Epoch 11: reducing learning rate of group 0 to 5.0000e-12.
Test set: Average loss: 1.5850, Accuracy: 1327/5000 (27%)
[epoch 13] loss: 1.4944305
Epoch 12: reducing learning rate of group 0 to 5.0000e-13.
Test set: Average loss: 1.5850, Accuracy: 1327/5000 (27%)
[epoch 14] loss: 1.5065921
Epoch 13: reducing learning rate of group 0 to 5.0000e-14.
Test set: Average loss: 1.5850, Accuracy: 1327/5000 (27%)
[epoch 15] loss: 1.4830147
Epoch 14: reducing learning rate of group 0 to 5.0000e-15.
Test set: Average loss: 1.5850, Accuracy: 1327/5000 (27%)
[epoch 16] loss: 1.4356771
Test set: Average loss: 1.5850, Accuracy: 1327/5000 (27%)
[epoch 17] loss: 1.5077027
Epoch 16: reducing learning rate of group 0 to 5.0000e-16.
Test set: Average loss: 1.5850, Accuracy: 1327/5000 (27%)
[epoch 18] loss: 1.4575215
Epoch 17: reducing learning rate of group 0 to 5.0000e-17.
Test set: Average loss: 1.5850, Accuracy: 1327/5000 (27%)
[epoch 19] loss: 1.4858356
Epoch 18: reducing learning rate of group 0 to 5.0000e-18.
Test set: Average loss: 1.5850, Accuracy: 1327/5000 (27%)
[epoch 20] loss: 1.4586720
Epoch 19: reducing learning rate of group 0 to 5.0000e-19.
Test set: Average loss: 1.5850, Accuracy: 1327/5000 (27%)
[epoch 21] loss: 1.4878134
Epoch 20: reducing learning rate of group 0 to 5.0000e-20.
Test set: Average loss: 1.5850, Accuracy: 1327/5000 (27%)
[epoch 22] loss: 1.5098861
Epoch 21: reducing learning rate of group 0 to 5.0000e-21.
Test set: Average loss: 1.5850, Accuracy: 1327/5000 (27%)
[epoch 23] loss: 1.5194806
Epoch 22: reducing learning rate of group 0 to 5.0000e-22.
Test set: Average loss: 1.5850, Accuracy: 1327/5000 (27%)
[epoch 24] loss: 1.5032384
Epoch 23: reducing learning rate of group 0 to 5.0000e-23.
Test set: Average loss: 1.5850, Accuracy: 1327/5000 (27%)
[epoch 25] loss: 1.4993205
Epoch 24: reducing learning rate of group 0 to 5.0000e-24.
Test set: Average loss: 1.5850, Accuracy: 1327/5000 (27%)
Validation:
Test set: Average loss: 1.5850, Accuracy: 1327/5000 (27%)
Test
Test set: Average loss: 1.5815, Accuracy: 1352/5000 (27%)
Test set: Average loss: 1.4902, Accuracy: 35/100 (35%)
## seed: 13
Validation accuracy before training:
Test set: Average loss: 1.7060, Accuracy: 854/5000 (17%)
[epoch 1] loss: 1.7846039
Test set: Average loss: 1.6730, Accuracy: 1023/5000 (20%)
[epoch 2] loss: 1.7247038
Test set: Average loss: 1.6464, Accuracy: 1145/5000 (23%)
[epoch 3] loss: 1.6559267
Test set: Average loss: 1.6250, Accuracy: 1218/5000 (24%)
[epoch 4] loss: 1.5496650
Test set: Average loss: 1.6091, Accuracy: 1292/5000 (26%)
[epoch 5] loss: 1.4682779
Test set: Average loss: 1.5957, Accuracy: 1351/5000 (27%)
[epoch 6] loss: 1.4461221
Test set: Average loss: 1.5840, Accuracy: 1417/5000 (28%)
[epoch 7] loss: 1.4739564
Epoch 6: reducing learning rate of group 0 to 5.0000e-06.
Test set: Average loss: 1.5736, Accuracy: 1470/5000 (29%)
[epoch 8] loss: 1.4071969
Test set: Average loss: 1.5726, Accuracy: 1476/5000 (30%)
[epoch 9] loss: 1.4841306
Epoch 8: reducing learning rate of group 0 to 5.0000e-07.
Test set: Average loss: 1.5717, Accuracy: 1475/5000 (30%)
[epoch 10] loss: 1.4121224
Epoch 9: reducing learning rate of group 0 to 5.0000e-08.
Test set: Average loss: 1.5716, Accuracy: 1475/5000 (30%)
[epoch 11] loss: 1.5110479
Epoch 10: reducing learning rate of group 0 to 5.0000e-09.
Test set: Average loss: 1.5716, Accuracy: 1475/5000 (30%)
[epoch 12] loss: 1.4429525
Epoch 11: reducing learning rate of group 0 to 5.0000e-10.
Test set: Average loss: 1.5716, Accuracy: 1475/5000 (30%)
[epoch 13] loss: 1.5119534
Epoch 12: reducing learning rate of group 0 to 5.0000e-11.
Test set: Average loss: 1.5716, Accuracy: 1475/5000 (30%)
[epoch 14] loss: 1.4118224
Epoch 13: reducing learning rate of group 0 to 5.0000e-12.
Test set: Average loss: 1.5716, Accuracy: 1475/5000 (30%)
[epoch 15] loss: 1.4379421
Epoch 14: reducing learning rate of group 0 to 5.0000e-13.
Test set: Average loss: 1.5716, Accuracy: 1475/5000 (30%)
[epoch 16] loss: 1.4295796
Epoch 15: reducing learning rate of group 0 to 5.0000e-14.
Test set: Average loss: 1.5716, Accuracy: 1475/5000 (30%)
[epoch 17] loss: 1.4454566
Epoch 16: reducing learning rate of group 0 to 5.0000e-15.
Test set: Average loss: 1.5716, Accuracy: 1475/5000 (30%)
[epoch 18] loss: 1.5220525
Epoch 17: reducing learning rate of group 0 to 5.0000e-16.
Test set: Average loss: 1.5716, Accuracy: 1475/5000 (30%)
[epoch 19] loss: 1.3936691
Test set: Average loss: 1.5716, Accuracy: 1475/5000 (30%)
[epoch 20] loss: 1.4292071
Epoch 19: reducing learning rate of group 0 to 5.0000e-17.
Test set: Average loss: 1.5716, Accuracy: 1475/5000 (30%)
[epoch 21] loss: 1.5242296
Epoch 20: reducing learning rate of group 0 to 5.0000e-18.
Test set: Average loss: 1.5716, Accuracy: 1475/5000 (30%)
[epoch 22] loss: 1.4075741
Epoch 21: reducing learning rate of group 0 to 5.0000e-19.
Test set: Average loss: 1.5716, Accuracy: 1475/5000 (30%)
[epoch 23] loss: 1.4767630
Epoch 22: reducing learning rate of group 0 to 5.0000e-20.
Test set: Average loss: 1.5716, Accuracy: 1475/5000 (30%)
[epoch 24] loss: 1.4829314
Epoch 23: reducing learning rate of group 0 to 5.0000e-21.
Test set: Average loss: 1.5716, Accuracy: 1475/5000 (30%)
[epoch 25] loss: 1.4364168
Epoch 24: reducing learning rate of group 0 to 5.0000e-22.
Test set: Average loss: 1.5716, Accuracy: 1475/5000 (30%)
Validation:
Test set: Average loss: 1.5726, Accuracy: 1476/5000 (30%)
Test
Test set: Average loss: 1.5780, Accuracy: 1475/5000 (30%)
Test set: Average loss: 1.4522, Accuracy: 48/100 (48%)
250
## seed: 11
Validation accuracy before training:
Test set: Average loss: 1.6922, Accuracy: 742/5000 (15%)
[epoch 1] loss: 1.6578873
Test set: Average loss: 1.6416, Accuracy: 911/5000 (18%)
[epoch 2] loss: 1.5702333
Test set: Average loss: 1.5951, Accuracy: 1165/5000 (23%)
[epoch 3] loss: 1.5061186
Test set: Average loss: 1.5591, Accuracy: 1373/5000 (27%)
[epoch 4] loss: 1.4540995
Test set: Average loss: 1.5313, Accuracy: 1539/5000 (31%)
[epoch 5] loss: 1.4109377
Test set: Average loss: 1.5082, Accuracy: 1675/5000 (34%)
[epoch 6] loss: 1.3707591
Test set: Average loss: 1.4902, Accuracy: 1771/5000 (35%)
[epoch 7] loss: 1.3320881
Test set: Average loss: 1.4752, Accuracy: 1853/5000 (37%)
[epoch 8] loss: 1.2987592
Test set: Average loss: 1.4603, Accuracy: 1936/5000 (39%)
[epoch 9] loss: 1.2694781
Test set: Average loss: 1.4481, Accuracy: 1999/5000 (40%)
[epoch 10] loss: 1.2431657
Test set: Average loss: 1.4379, Accuracy: 2036/5000 (41%)
[epoch 11] loss: 1.2172810
Test set: Average loss: 1.4276, Accuracy: 2068/5000 (41%)
[epoch 12] loss: 1.1935750
Test set: Average loss: 1.4182, Accuracy: 2105/5000 (42%)
[epoch 13] loss: 1.1723126
Test set: Average loss: 1.4103, Accuracy: 2133/5000 (43%)
[epoch 14] loss: 1.1483633
Test set: Average loss: 1.4017, Accuracy: 2166/5000 (43%)
[epoch 15] loss: 1.1239905
Test set: Average loss: 1.3948, Accuracy: 2187/5000 (44%)
[epoch 16] loss: 1.1055625
Test set: Average loss: 1.3876, Accuracy: 2218/5000 (44%)
[epoch 17] loss: 1.0860284
Test set: Average loss: 1.3810, Accuracy: 2235/5000 (45%)
[epoch 18] loss: 1.0658718
Test set: Average loss: 1.3761, Accuracy: 2243/5000 (45%)
[epoch 19] loss: 1.0505151
Test set: Average loss: 1.3695, Accuracy: 2264/5000 (45%)
[epoch 20] loss: 1.0304265
Test set: Average loss: 1.3647, Accuracy: 2283/5000 (46%)
[epoch 21] loss: 1.0125225
Test set: Average loss: 1.3601, Accuracy: 2303/5000 (46%)
[epoch 22] loss: 0.9954916
Test set: Average loss: 1.3564, Accuracy: 2313/5000 (46%)
[epoch 23] loss: 0.9794226
Test set: Average loss: 1.3521, Accuracy: 2332/5000 (47%)
[epoch 24] loss: 0.9631279
Test set: Average loss: 1.3474, Accuracy: 2335/5000 (47%)
[epoch 25] loss: 0.9478086
Test set: Average loss: 1.3444, Accuracy: 2346/5000 (47%)
Validation:
Test set: Average loss: 1.3444, Accuracy: 2346/5000 (47%)
Test
Test set: Average loss: 1.3545, Accuracy: 2333/5000 (47%)
Test set: Average loss: 0.9369, Accuracy: 219/250 (88%)
## seed: 12
Validation accuracy before training:
Test set: Average loss: 1.6875, Accuracy: 722/5000 (14%)
[epoch 1] loss: 1.6282678
Test set: Average loss: 1.6146, Accuracy: 1115/5000 (22%)
[epoch 2] loss: 1.5368015
Test set: Average loss: 1.5587, Accuracy: 1496/5000 (30%)
[epoch 3] loss: 1.4664603
Test set: Average loss: 1.5223, Accuracy: 1701/5000 (34%)
[epoch 4] loss: 1.4112569
Test set: Average loss: 1.4932, Accuracy: 1843/5000 (37%)
[epoch 5] loss: 1.3628254
Test set: Average loss: 1.4708, Accuracy: 1960/5000 (39%)
[epoch 6] loss: 1.3208585
Test set: Average loss: 1.4518, Accuracy: 2029/5000 (41%)
[epoch 7] loss: 1.2851452
Test set: Average loss: 1.4342, Accuracy: 2103/5000 (42%)
[epoch 8] loss: 1.2495962
Test set: Average loss: 1.4202, Accuracy: 2144/5000 (43%)
[epoch 9] loss: 1.2216738
Test set: Average loss: 1.4075, Accuracy: 2199/5000 (44%)
[epoch 10] loss: 1.1934294
Test set: Average loss: 1.3954, Accuracy: 2231/5000 (45%)
[epoch 11] loss: 1.1689514
Test set: Average loss: 1.3842, Accuracy: 2267/5000 (45%)
[epoch 12] loss: 1.1438133
Test set: Average loss: 1.3743, Accuracy: 2300/5000 (46%)
[epoch 13] loss: 1.1199648
Test set: Average loss: 1.3659, Accuracy: 2319/5000 (46%)
[epoch 14] loss: 1.0981830
Test set: Average loss: 1.3577, Accuracy: 2329/5000 (47%)
[epoch 15] loss: 1.0739983
Test set: Average loss: 1.3495, Accuracy: 2348/5000 (47%)
[epoch 16] loss: 1.0526821
Test set: Average loss: 1.3419, Accuracy: 2371/5000 (47%)
[epoch 17] loss: 1.0327463
Test set: Average loss: 1.3352, Accuracy: 2395/5000 (48%)
[epoch 18] loss: 1.0130780
Test set: Average loss: 1.3281, Accuracy: 2420/5000 (48%)
[epoch 19] loss: 0.9914398
Test set: Average loss: 1.3220, Accuracy: 2436/5000 (49%)
[epoch 20] loss: 0.9734136
Test set: Average loss: 1.3160, Accuracy: 2451/5000 (49%)
[epoch 21] loss: 0.9539128
Test set: Average loss: 1.3105, Accuracy: 2465/5000 (49%)
[epoch 22] loss: 0.9368013
Test set: Average loss: 1.3043, Accuracy: 2486/5000 (50%)
[epoch 23] loss: 0.9209805
Test set: Average loss: 1.2989, Accuracy: 2483/5000 (50%)
[epoch 24] loss: 0.9023506
Test set: Average loss: 1.2960, Accuracy: 2487/5000 (50%)
[epoch 25] loss: 0.8862236
Test set: Average loss: 1.2901, Accuracy: 2500/5000 (50%)
Validation:
Test set: Average loss: 1.2901, Accuracy: 2500/5000 (50%)
Test
Test set: Average loss: 1.2893, Accuracy: 2485/5000 (50%)
Test set: Average loss: 0.8744, Accuracy: 224/250 (90%)
## seed: 13
Validation accuracy before training:
Test set: Average loss: 1.7460, Accuracy: 918/5000 (18%)
[epoch 1] loss: 1.6615786
Test set: Average loss: 1.6508, Accuracy: 1229/5000 (25%)
[epoch 2] loss: 1.5316740
Test set: Average loss: 1.5768, Accuracy: 1509/5000 (30%)
[epoch 3] loss: 1.4393601
Test set: Average loss: 1.5233, Accuracy: 1724/5000 (34%)
[epoch 4] loss: 1.3765512
Test set: Average loss: 1.4846, Accuracy: 1887/5000 (38%)
[epoch 5] loss: 1.3168865
Test set: Average loss: 1.4559, Accuracy: 1974/5000 (39%)
[epoch 6] loss: 1.2713163
Test set: Average loss: 1.4346, Accuracy: 2053/5000 (41%)
[epoch 7] loss: 1.2272806
Test set: Average loss: 1.4161, Accuracy: 2119/5000 (42%)
[epoch 8] loss: 1.1958138
Test set: Average loss: 1.4009, Accuracy: 2186/5000 (44%)
[epoch 9] loss: 1.1617206
Test set: Average loss: 1.3875, Accuracy: 2236/5000 (45%)
[epoch 10] loss: 1.1290180
Test set: Average loss: 1.3762, Accuracy: 2254/5000 (45%)
[epoch 11] loss: 1.1032612
Test set: Average loss: 1.3665, Accuracy: 2289/5000 (46%)
[epoch 12] loss: 1.0774091
Test set: Average loss: 1.3574, Accuracy: 2303/5000 (46%)
[epoch 13] loss: 1.0511804
Test set: Average loss: 1.3494, Accuracy: 2339/5000 (47%)
[epoch 14] loss: 1.0279841
Test set: Average loss: 1.3415, Accuracy: 2367/5000 (47%)
[epoch 15] loss: 1.0059143
Test set: Average loss: 1.3339, Accuracy: 2387/5000 (48%)
[epoch 16] loss: 0.9877756
Test set: Average loss: 1.3274, Accuracy: 2407/5000 (48%)
[epoch 17] loss: 0.9656093
Test set: Average loss: 1.3219, Accuracy: 2429/5000 (49%)
[epoch 18] loss: 0.9486645
Test set: Average loss: 1.3176, Accuracy: 2432/5000 (49%)
[epoch 19] loss: 0.9289061
Test set: Average loss: 1.3119, Accuracy: 2454/5000 (49%)
[epoch 20] loss: 0.9108589
Test set: Average loss: 1.3071, Accuracy: 2459/5000 (49%)
[epoch 21] loss: 0.8910256
Test set: Average loss: 1.3034, Accuracy: 2466/5000 (49%)
[epoch 22] loss: 0.8792194
Test set: Average loss: 1.2990, Accuracy: 2465/5000 (49%)
[epoch 23] loss: 0.8580882
Test set: Average loss: 1.2947, Accuracy: 2482/5000 (50%)
[epoch 24] loss: 0.8402633
Test set: Average loss: 1.2909, Accuracy: 2496/5000 (50%)
[epoch 25] loss: 0.8295317
Test set: Average loss: 1.2872, Accuracy: 2501/5000 (50%)
Validation:
Test set: Average loss: 1.2872, Accuracy: 2501/5000 (50%)
Test
Test set: Average loss: 1.3011, Accuracy: 2464/5000 (49%)
Test set: Average loss: 0.8171, Accuracy: 220/250 (88%)
500
## seed: 11
Validation accuracy before training:
Test set: Average loss: 1.7152, Accuracy: 680/5000 (14%)
[epoch 1] loss: 1.6211261
Test set: Average loss: 1.5737, Accuracy: 1304/5000 (26%)
[epoch 2] loss: 1.4760032
Test set: Average loss: 1.4865, Accuracy: 1816/5000 (36%)
[epoch 3] loss: 1.4006340
Test set: Average loss: 1.4343, Accuracy: 2055/5000 (41%)
[epoch 4] loss: 1.3373234
Test set: Average loss: 1.3986, Accuracy: 2226/5000 (45%)
[epoch 5] loss: 1.2900249
Test set: Average loss: 1.3740, Accuracy: 2327/5000 (47%)
[epoch 6] loss: 1.2490743
Test set: Average loss: 1.3536, Accuracy: 2401/5000 (48%)
[epoch 7] loss: 1.2188610
Test set: Average loss: 1.3385, Accuracy: 2452/5000 (49%)
[epoch 8] loss: 1.1808563
Test set: Average loss: 1.3238, Accuracy: 2501/5000 (50%)
[epoch 9] loss: 1.1559576
Test set: Average loss: 1.3120, Accuracy: 2530/5000 (51%)
[epoch 10] loss: 1.1308854
Test set: Average loss: 1.3011, Accuracy: 2562/5000 (51%)
[epoch 11] loss: 1.1031677
Test set: Average loss: 1.2909, Accuracy: 2582/5000 (52%)
[epoch 12] loss: 1.0844215
Test set: Average loss: 1.2829, Accuracy: 2603/5000 (52%)
[epoch 13] loss: 1.0600679
Test set: Average loss: 1.2753, Accuracy: 2619/5000 (52%)
[epoch 14] loss: 1.0372688
Test set: Average loss: 1.2680, Accuracy: 2649/5000 (53%)
[epoch 15] loss: 1.0221204
Test set: Average loss: 1.2608, Accuracy: 2653/5000 (53%)
[epoch 16] loss: 0.9984352
Test set: Average loss: 1.2542, Accuracy: 2665/5000 (53%)
[epoch 17] loss: 0.9757039
Test set: Average loss: 1.2490, Accuracy: 2666/5000 (53%)
[epoch 18] loss: 0.9588203
Test set: Average loss: 1.2434, Accuracy: 2686/5000 (54%)
[epoch 19] loss: 0.9408130
Test set: Average loss: 1.2377, Accuracy: 2704/5000 (54%)
[epoch 20] loss: 0.9214574
Test set: Average loss: 1.2327, Accuracy: 2707/5000 (54%)
[epoch 21] loss: 0.9081620
Test set: Average loss: 1.2291, Accuracy: 2716/5000 (54%)
[epoch 22] loss: 0.8871041
Test set: Average loss: 1.2237, Accuracy: 2736/5000 (55%)
[epoch 23] loss: 0.8715593
Test set: Average loss: 1.2200, Accuracy: 2736/5000 (55%)
[epoch 24] loss: 0.8558710
Test set: Average loss: 1.2164, Accuracy: 2747/5000 (55%)
[epoch 25] loss: 0.8405217
Test set: Average loss: 1.2118, Accuracy: 2747/5000 (55%)
Validation:
Test set: Average loss: 1.2118, Accuracy: 2747/5000 (55%)
Test
Test set: Average loss: 1.2249, Accuracy: 2669/5000 (53%)
Test set: Average loss: 0.8256, Accuracy: 420/500 (84%)
## seed: 12
Validation accuracy before training:
Test set: Average loss: 1.6665, Accuracy: 915/5000 (18%)
[epoch 1] loss: 1.6256121
Test set: Average loss: 1.5542, Accuracy: 1666/5000 (33%)
[epoch 2] loss: 1.5124062
Test set: Average loss: 1.4848, Accuracy: 1944/5000 (39%)
[epoch 3] loss: 1.4356750
Test set: Average loss: 1.4415, Accuracy: 2090/5000 (42%)
[epoch 4] loss: 1.3729193
Test set: Average loss: 1.4085, Accuracy: 2185/5000 (44%)
[epoch 5] loss: 1.3266540
Test set: Average loss: 1.3816, Accuracy: 2275/5000 (46%)
[epoch 6] loss: 1.2838377
Test set: Average loss: 1.3602, Accuracy: 2355/5000 (47%)
[epoch 7] loss: 1.2500052
Test set: Average loss: 1.3427, Accuracy: 2408/5000 (48%)
[epoch 8] loss: 1.2145918
Test set: Average loss: 1.3255, Accuracy: 2463/5000 (49%)
[epoch 9] loss: 1.1833767
Test set: Average loss: 1.3125, Accuracy: 2502/5000 (50%)
[epoch 10] loss: 1.1564858
Test set: Average loss: 1.3011, Accuracy: 2537/5000 (51%)
[epoch 11] loss: 1.1274101
Test set: Average loss: 1.2910, Accuracy: 2557/5000 (51%)
[epoch 12] loss: 1.0989643
Test set: Average loss: 1.2811, Accuracy: 2615/5000 (52%)
[epoch 13] loss: 1.0749634
Test set: Average loss: 1.2730, Accuracy: 2629/5000 (53%)
[epoch 14] loss: 1.0560903
Test set: Average loss: 1.2634, Accuracy: 2653/5000 (53%)
[epoch 15] loss: 1.0336280
Test set: Average loss: 1.2573, Accuracy: 2666/5000 (53%)
[epoch 16] loss: 1.0104446
Test set: Average loss: 1.2511, Accuracy: 2680/5000 (54%)
[epoch 17] loss: 0.9902781
Test set: Average loss: 1.2436, Accuracy: 2702/5000 (54%)
[epoch 18] loss: 0.9663640
Test set: Average loss: 1.2372, Accuracy: 2730/5000 (55%)
[epoch 19] loss: 0.9464287
Test set: Average loss: 1.2333, Accuracy: 2721/5000 (54%)
[epoch 20] loss: 0.9289634
Test set: Average loss: 1.2264, Accuracy: 2718/5000 (54%)
[epoch 21] loss: 0.9115190
Test set: Average loss: 1.2219, Accuracy: 2746/5000 (55%)
[epoch 22] loss: 0.8941812
Test set: Average loss: 1.2162, Accuracy: 2739/5000 (55%)
[epoch 23] loss: 0.8768049
Test set: Average loss: 1.2118, Accuracy: 2739/5000 (55%)
[epoch 24] loss: 0.8577829
Test set: Average loss: 1.2088, Accuracy: 2759/5000 (55%)
[epoch 25] loss: 0.8407409
Test set: Average loss: 1.2032, Accuracy: 2762/5000 (55%)
Validation:
Test set: Average loss: 1.2032, Accuracy: 2762/5000 (55%)
Test
Test set: Average loss: 1.2134, Accuracy: 2721/5000 (54%)
Test set: Average loss: 0.8255, Accuracy: 423/500 (85%)
## seed: 13
Validation accuracy before training:
Test set: Average loss: 1.6548, Accuracy: 714/5000 (14%)
[epoch 1] loss: 1.5827999
Test set: Average loss: 1.5276, Accuracy: 1300/5000 (26%)
[epoch 2] loss: 1.4424823
Test set: Average loss: 1.4543, Accuracy: 1771/5000 (35%)
[epoch 3] loss: 1.3512946
Test set: Average loss: 1.4070, Accuracy: 1976/5000 (40%)
[epoch 4] loss: 1.2912700
Test set: Average loss: 1.3743, Accuracy: 2107/5000 (42%)
[epoch 5] loss: 1.2424050
Test set: Average loss: 1.3495, Accuracy: 2217/5000 (44%)
[epoch 6] loss: 1.1972749
Test set: Average loss: 1.3279, Accuracy: 2294/5000 (46%)
[epoch 7] loss: 1.1592722
Test set: Average loss: 1.3104, Accuracy: 2362/5000 (47%)
[epoch 8] loss: 1.1300896
Test set: Average loss: 1.2983, Accuracy: 2386/5000 (48%)
[epoch 9] loss: 1.0989851
Test set: Average loss: 1.2856, Accuracy: 2428/5000 (49%)
[epoch 10] loss: 1.0720931
Test set: Average loss: 1.2741, Accuracy: 2455/5000 (49%)
[epoch 11] loss: 1.0493470
Test set: Average loss: 1.2666, Accuracy: 2483/5000 (50%)
[epoch 12] loss: 1.0245257
Test set: Average loss: 1.2572, Accuracy: 2498/5000 (50%)
[epoch 13] loss: 0.9997328
Test set: Average loss: 1.2509, Accuracy: 2507/5000 (50%)
[epoch 14] loss: 0.9802078
Test set: Average loss: 1.2448, Accuracy: 2524/5000 (50%)
[epoch 15] loss: 0.9610908
Test set: Average loss: 1.2384, Accuracy: 2535/5000 (51%)
[epoch 16] loss: 0.9362993
Test set: Average loss: 1.2322, Accuracy: 2553/5000 (51%)
[epoch 17] loss: 0.9249922
Test set: Average loss: 1.2287, Accuracy: 2546/5000 (51%)
[epoch 18] loss: 0.9044223
Test set: Average loss: 1.2245, Accuracy: 2568/5000 (51%)
[epoch 19] loss: 0.8862688
Test set: Average loss: 1.2196, Accuracy: 2567/5000 (51%)
[epoch 20] loss: 0.8659310
Test set: Average loss: 1.2178, Accuracy: 2569/5000 (51%)
[epoch 21] loss: 0.8506486
Test set: Average loss: 1.2132, Accuracy: 2588/5000 (52%)
[epoch 22] loss: 0.8320863
Test set: Average loss: 1.2100, Accuracy: 2601/5000 (52%)
[epoch 23] loss: 0.8203984
Test set: Average loss: 1.2072, Accuracy: 2606/5000 (52%)
[epoch 24] loss: 0.8022325
Test set: Average loss: 1.2045, Accuracy: 2602/5000 (52%)
[epoch 25] loss: 0.7880003
Test set: Average loss: 1.2029, Accuracy: 2606/5000 (52%)
Validation:
Test set: Average loss: 1.2029, Accuracy: 2606/5000 (52%)
Test
Test set: Average loss: 1.2207, Accuracy: 2542/5000 (51%)
Test set: Average loss: 0.7741, Accuracy: 424/500 (85%)
750
## seed: 11
Validation accuracy before training:
Test set: Average loss: 1.6103, Accuracy: 1052/5000 (21%)
[epoch 1] loss: 1.5171146
Test set: Average loss: 1.4544, Accuracy: 2004/5000 (40%)
[epoch 2] loss: 1.3729046
Test set: Average loss: 1.3874, Accuracy: 2252/5000 (45%)
[epoch 3] loss: 1.2949970
Test set: Average loss: 1.3474, Accuracy: 2388/5000 (48%)
[epoch 4] loss: 1.2359854
Test set: Average loss: 1.3174, Accuracy: 2462/5000 (49%)
[epoch 5] loss: 1.1885922
Test set: Average loss: 1.2954, Accuracy: 2539/5000 (51%)
[epoch 6] loss: 1.1502067
Test set: Average loss: 1.2776, Accuracy: 2585/5000 (52%)
[epoch 7] loss: 1.1172782
Test set: Average loss: 1.2621, Accuracy: 2628/5000 (53%)
[epoch 8] loss: 1.0852767
Test set: Average loss: 1.2473, Accuracy: 2670/5000 (53%)
[epoch 9] loss: 1.0504537
Test set: Average loss: 1.2362, Accuracy: 2713/5000 (54%)
[epoch 10] loss: 1.0251841
Test set: Average loss: 1.2248, Accuracy: 2737/5000 (55%)
[epoch 11] loss: 0.9987265
Test set: Average loss: 1.2164, Accuracy: 2736/5000 (55%)
[epoch 12] loss: 0.9705061
Test set: Average loss: 1.2071, Accuracy: 2772/5000 (55%)
[epoch 13] loss: 0.9481203
Test set: Average loss: 1.2002, Accuracy: 2767/5000 (55%)
[epoch 14] loss: 0.9221942
Test set: Average loss: 1.1935, Accuracy: 2779/5000 (56%)
[epoch 15] loss: 0.9009825
Test set: Average loss: 1.1854, Accuracy: 2791/5000 (56%)
[epoch 16] loss: 0.8772545
Test set: Average loss: 1.1814, Accuracy: 2811/5000 (56%)
[epoch 17] loss: 0.8598806
Test set: Average loss: 1.1757, Accuracy: 2810/5000 (56%)
[epoch 18] loss: 0.8365076
Test set: Average loss: 1.1705, Accuracy: 2825/5000 (56%)
[epoch 19] loss: 0.8169509
Test set: Average loss: 1.1663, Accuracy: 2849/5000 (57%)
[epoch 20] loss: 0.7997358
Test set: Average loss: 1.1618, Accuracy: 2858/5000 (57%)
[epoch 21] loss: 0.7846157
Test set: Average loss: 1.1578, Accuracy: 2861/5000 (57%)
[epoch 22] loss: 0.7651362
Test set: Average loss: 1.1550, Accuracy: 2865/5000 (57%)
[epoch 23] loss: 0.7393321
Test set: Average loss: 1.1516, Accuracy: 2879/5000 (58%)
[epoch 24] loss: 0.7249876
Test set: Average loss: 1.1490, Accuracy: 2881/5000 (58%)
[epoch 25] loss: 0.7086626
Test set: Average loss: 1.1450, Accuracy: 2874/5000 (57%)
Validation:
Test set: Average loss: 1.1490, Accuracy: 2881/5000 (58%)
Test
Test set: Average loss: 1.1581, Accuracy: 2801/5000 (56%)
Test set: Average loss: 0.7083, Accuracy: 645/750 (86%)
## seed: 12
Validation accuracy before training:
Test set: Average loss: 1.6356, Accuracy: 1049/5000 (21%)
[epoch 1] loss: 1.5619390
Test set: Average loss: 1.4898, Accuracy: 1822/5000 (36%)
[epoch 2] loss: 1.4252187
Test set: Average loss: 1.4184, Accuracy: 2093/5000 (42%)
[epoch 3] loss: 1.3531016
Test set: Average loss: 1.3741, Accuracy: 2271/5000 (45%)
[epoch 4] loss: 1.2941945
Test set: Average loss: 1.3433, Accuracy: 2364/5000 (47%)
[epoch 5] loss: 1.2432170
Test set: Average loss: 1.3182, Accuracy: 2441/5000 (49%)
[epoch 6] loss: 1.2012725
Test set: Average loss: 1.2969, Accuracy: 2510/5000 (50%)
[epoch 7] loss: 1.1687085
Test set: Average loss: 1.2767, Accuracy: 2567/5000 (51%)
[epoch 8] loss: 1.1304901
Test set: Average loss: 1.2599, Accuracy: 2632/5000 (53%)
[epoch 9] loss: 1.0979803
Test set: Average loss: 1.2461, Accuracy: 2670/5000 (53%)
[epoch 10] loss: 1.0678627
Test set: Average loss: 1.2338, Accuracy: 2685/5000 (54%)
[epoch 11] loss: 1.0364432
Test set: Average loss: 1.2225, Accuracy: 2718/5000 (54%)
[epoch 12] loss: 1.0114631
Test set: Average loss: 1.2108, Accuracy: 2739/5000 (55%)
[epoch 13] loss: 0.9898496
Test set: Average loss: 1.2013, Accuracy: 2763/5000 (55%)
[epoch 14] loss: 0.9645442
Test set: Average loss: 1.1937, Accuracy: 2781/5000 (56%)
[epoch 15] loss: 0.9370312
Test set: Average loss: 1.1839, Accuracy: 2822/5000 (56%)
[epoch 16] loss: 0.9172674
Test set: Average loss: 1.1769, Accuracy: 2826/5000 (57%)
[epoch 17] loss: 0.9009997
Test set: Average loss: 1.1698, Accuracy: 2849/5000 (57%)
[epoch 18] loss: 0.8755449
Test set: Average loss: 1.1635, Accuracy: 2864/5000 (57%)
[epoch 19] loss: 0.8540381
Test set: Average loss: 1.1586, Accuracy: 2869/5000 (57%)
[epoch 20] loss: 0.8337250
Test set: Average loss: 1.1497, Accuracy: 2900/5000 (58%)
[epoch 21] loss: 0.8146206
Test set: Average loss: 1.1468, Accuracy: 2897/5000 (58%)
[epoch 22] loss: 0.7935065
Test set: Average loss: 1.1403, Accuracy: 2905/5000 (58%)
[epoch 23] loss: 0.7773377
Test set: Average loss: 1.1378, Accuracy: 2909/5000 (58%)
[epoch 24] loss: 0.7588772
Test set: Average loss: 1.1316, Accuracy: 2921/5000 (58%)
[epoch 25] loss: 0.7425236
Test set: Average loss: 1.1294, Accuracy: 2932/5000 (59%)
Validation:
Test set: Average loss: 1.1294, Accuracy: 2932/5000 (59%)
Test
Test set: Average loss: 1.1379, Accuracy: 2822/5000 (56%)
Test set: Average loss: 0.7244, Accuracy: 649/750 (87%)
## seed: 13
Validation accuracy before training:
Test set: Average loss: 1.7066, Accuracy: 629/5000 (13%)
[epoch 1] loss: 1.6085263
Test set: Average loss: 1.5063, Accuracy: 1656/5000 (33%)
[epoch 2] loss: 1.4346300
Test set: Average loss: 1.4265, Accuracy: 1982/5000 (40%)
[epoch 3] loss: 1.3521324
Test set: Average loss: 1.3817, Accuracy: 2151/5000 (43%)
[epoch 4] loss: 1.2882446
Test set: Average loss: 1.3490, Accuracy: 2258/5000 (45%)
[epoch 5] loss: 1.2446104
Test set: Average loss: 1.3248, Accuracy: 2337/5000 (47%)
[epoch 6] loss: 1.2019685
Test set: Average loss: 1.3053, Accuracy: 2403/5000 (48%)
[epoch 7] loss: 1.1688240
Test set: Average loss: 1.2887, Accuracy: 2447/5000 (49%)
[epoch 8] loss: 1.1353804
Test set: Average loss: 1.2765, Accuracy: 2490/5000 (50%)
[epoch 9] loss: 1.1086236
Test set: Average loss: 1.2645, Accuracy: 2508/5000 (50%)
[epoch 10] loss: 1.0864333
Test set: Average loss: 1.2554, Accuracy: 2539/5000 (51%)
[epoch 11] loss: 1.0606034
Test set: Average loss: 1.2460, Accuracy: 2559/5000 (51%)
[epoch 12] loss: 1.0434699
Test set: Average loss: 1.2389, Accuracy: 2574/5000 (51%)
[epoch 13] loss: 1.0122491
Test set: Average loss: 1.2317, Accuracy: 2619/5000 (52%)
[epoch 14] loss: 0.9970531
Test set: Average loss: 1.2253, Accuracy: 2638/5000 (53%)
[epoch 15] loss: 0.9711872
Test set: Average loss: 1.2190, Accuracy: 2646/5000 (53%)
[epoch 16] loss: 0.9569684
Test set: Average loss: 1.2129, Accuracy: 2671/5000 (53%)
[epoch 17] loss: 0.9367265
Test set: Average loss: 1.2086, Accuracy: 2680/5000 (54%)
[epoch 18] loss: 0.9135475
Test set: Average loss: 1.2032, Accuracy: 2685/5000 (54%)
[epoch 19] loss: 0.8977688
Test set: Average loss: 1.1985, Accuracy: 2694/5000 (54%)
[epoch 20] loss: 0.8836099
Test set: Average loss: 1.1956, Accuracy: 2717/5000 (54%)
[epoch 21] loss: 0.8634814
Test set: Average loss: 1.1899, Accuracy: 2728/5000 (55%)
[epoch 22] loss: 0.8462526
Test set: Average loss: 1.1860, Accuracy: 2729/5000 (55%)
[epoch 23] loss: 0.8280760
Test set: Average loss: 1.1820, Accuracy: 2757/5000 (55%)
[epoch 24] loss: 0.8094629
Test set: Average loss: 1.1781, Accuracy: 2783/5000 (56%)
[epoch 25] loss: 0.7931481
Test set: Average loss: 1.1742, Accuracy: 2786/5000 (56%)
Validation:
Test set: Average loss: 1.1742, Accuracy: 2786/5000 (56%)
Test
Test set: Average loss: 1.1900, Accuracy: 2718/5000 (54%)
Test set: Average loss: 0.7762, Accuracy: 627/750 (84%)
1000
## seed: 11
Validation accuracy before training:
Test set: Average loss: 1.7098, Accuracy: 814/5000 (16%)
[epoch 1] loss: 1.5938704
Test set: Average loss: 1.4990, Accuracy: 1715/5000 (34%)
[epoch 2] loss: 1.4125665
Test set: Average loss: 1.4187, Accuracy: 2094/5000 (42%)
[epoch 3] loss: 1.3256232
Test set: Average loss: 1.3690, Accuracy: 2286/5000 (46%)
[epoch 4] loss: 1.2618063
Test set: Average loss: 1.3333, Accuracy: 2425/5000 (48%)
[epoch 5] loss: 1.2128933
Test set: Average loss: 1.3052, Accuracy: 2513/5000 (50%)
[epoch 6] loss: 1.1667779
Test set: Average loss: 1.2832, Accuracy: 2598/5000 (52%)
[epoch 7] loss: 1.1310958
Test set: Average loss: 1.2638, Accuracy: 2648/5000 (53%)
[epoch 8] loss: 1.1035806
Test set: Average loss: 1.2473, Accuracy: 2680/5000 (54%)
[epoch 9] loss: 1.0625940
Test set: Average loss: 1.2328, Accuracy: 2692/5000 (54%)
[epoch 10] loss: 1.0337098
Test set: Average loss: 1.2215, Accuracy: 2728/5000 (55%)
[epoch 11] loss: 1.0057937
Test set: Average loss: 1.2077, Accuracy: 2773/5000 (55%)
[epoch 12] loss: 0.9852521
Test set: Average loss: 1.1976, Accuracy: 2779/5000 (56%)
[epoch 13] loss: 0.9588300
Test set: Average loss: 1.1883, Accuracy: 2810/5000 (56%)
[epoch 14] loss: 0.9305873
Test set: Average loss: 1.1789, Accuracy: 2825/5000 (56%)
[epoch 15] loss: 0.9094179
Test set: Average loss: 1.1726, Accuracy: 2831/5000 (57%)
[epoch 16] loss: 0.8852081
Test set: Average loss: 1.1670, Accuracy: 2842/5000 (57%)
[epoch 17] loss: 0.8681954
Test set: Average loss: 1.1588, Accuracy: 2859/5000 (57%)
[epoch 18] loss: 0.8448916
Test set: Average loss: 1.1548, Accuracy: 2852/5000 (57%)
[epoch 19] loss: 0.8245720
Test set: Average loss: 1.1490, Accuracy: 2877/5000 (58%)
[epoch 20] loss: 0.8029938
Test set: Average loss: 1.1430, Accuracy: 2885/5000 (58%)
[epoch 21] loss: 0.7767225
Test set: Average loss: 1.1390, Accuracy: 2893/5000 (58%)
[epoch 22] loss: 0.7606904
Test set: Average loss: 1.1352, Accuracy: 2901/5000 (58%)
[epoch 23] loss: 0.7467383
Test set: Average loss: 1.1324, Accuracy: 2891/5000 (58%)
[epoch 24] loss: 0.7271604
Test set: Average loss: 1.1275, Accuracy: 2909/5000 (58%)
[epoch 25] loss: 0.7042364
Test set: Average loss: 1.1251, Accuracy: 2907/5000 (58%)
Validation:
Test set: Average loss: 1.1275, Accuracy: 2909/5000 (58%)
Test
Test set: Average loss: 1.1372, Accuracy: 2858/5000 (57%)
Test set: Average loss: 0.7054, Accuracy: 860/1000 (86%)
## seed: 12
Validation accuracy before training:
Test set: Average loss: 1.6225, Accuracy: 1116/5000 (22%)
[epoch 1] loss: 1.5239966
Test set: Average loss: 1.4421, Accuracy: 2127/5000 (43%)
[epoch 2] loss: 1.3844637
Test set: Average loss: 1.3719, Accuracy: 2347/5000 (47%)
[epoch 3] loss: 1.3098460
Test set: Average loss: 1.3318, Accuracy: 2465/5000 (49%)
[epoch 4] loss: 1.2585664
Test set: Average loss: 1.3038, Accuracy: 2527/5000 (51%)
[epoch 5] loss: 1.2127123
Test set: Average loss: 1.2811, Accuracy: 2585/5000 (52%)
[epoch 6] loss: 1.1801292
Test set: Average loss: 1.2633, Accuracy: 2645/5000 (53%)
[epoch 7] loss: 1.1491266
Test set: Average loss: 1.2479, Accuracy: 2667/5000 (53%)
[epoch 8] loss: 1.1151534
Test set: Average loss: 1.2355, Accuracy: 2723/5000 (54%)
[epoch 9] loss: 1.0850752
Test set: Average loss: 1.2230, Accuracy: 2728/5000 (55%)
[epoch 10] loss: 1.0553839
Test set: Average loss: 1.2124, Accuracy: 2769/5000 (55%)
[epoch 11] loss: 1.0426879
Test set: Average loss: 1.2015, Accuracy: 2796/5000 (56%)
[epoch 12] loss: 1.0078759
Test set: Average loss: 1.1937, Accuracy: 2795/5000 (56%)
[epoch 13] loss: 0.9942654
Test set: Average loss: 1.1842, Accuracy: 2826/5000 (57%)
[epoch 14] loss: 0.9604535
Test set: Average loss: 1.1766, Accuracy: 2844/5000 (57%)
[epoch 15] loss: 0.9332808
Test set: Average loss: 1.1702, Accuracy: 2849/5000 (57%)
[epoch 16] loss: 0.9157437
Test set: Average loss: 1.1645, Accuracy: 2839/5000 (57%)
[epoch 17] loss: 0.8960592
Test set: Average loss: 1.1555, Accuracy: 2855/5000 (57%)
[epoch 18] loss: 0.8757691
Test set: Average loss: 1.1504, Accuracy: 2855/5000 (57%)
[epoch 19] loss: 0.8569427
Test set: Average loss: 1.1449, Accuracy: 2871/5000 (57%)
[epoch 20] loss: 0.8407631
Test set: Average loss: 1.1393, Accuracy: 2870/5000 (57%)
[epoch 21] loss: 0.8092829
Test set: Average loss: 1.1323, Accuracy: 2892/5000 (58%)
[epoch 22] loss: 0.7886267
Test set: Average loss: 1.1291, Accuracy: 2871/5000 (57%)
[epoch 23] loss: 0.7704477
Test set: Average loss: 1.1257, Accuracy: 2896/5000 (58%)
[epoch 24] loss: 0.7508891
Test set: Average loss: 1.1212, Accuracy: 2897/5000 (58%)
[epoch 25] loss: 0.7352732
Test set: Average loss: 1.1173, Accuracy: 2902/5000 (58%)
Validation:
Test set: Average loss: 1.1173, Accuracy: 2902/5000 (58%)
Test
Test set: Average loss: 1.1287, Accuracy: 2860/5000 (57%)
Test set: Average loss: 0.7155, Accuracy: 855/1000 (86%)
## seed: 13
Validation accuracy before training:
Test set: Average loss: 1.6041, Accuracy: 1191/5000 (24%)
[epoch 1] loss: 1.4975616
Test set: Average loss: 1.4415, Accuracy: 2024/5000 (40%)
[epoch 2] loss: 1.3630668
Test set: Average loss: 1.3753, Accuracy: 2281/5000 (46%)
[epoch 3] loss: 1.2924227
Test set: Average loss: 1.3351, Accuracy: 2430/5000 (49%)
[epoch 4] loss: 1.2310377
Test set: Average loss: 1.3056, Accuracy: 2507/5000 (50%)
[epoch 5] loss: 1.1945336
Test set: Average loss: 1.2843, Accuracy: 2542/5000 (51%)
[epoch 6] loss: 1.1479408
Test set: Average loss: 1.2660, Accuracy: 2588/5000 (52%)
[epoch 7] loss: 1.1164577
Test set: Average loss: 1.2498, Accuracy: 2636/5000 (53%)
[epoch 8] loss: 1.0799482
Test set: Average loss: 1.2348, Accuracy: 2675/5000 (54%)
[epoch 9] loss: 1.0516292
Test set: Average loss: 1.2222, Accuracy: 2697/5000 (54%)
[epoch 10] loss: 1.0279373
Test set: Average loss: 1.2125, Accuracy: 2730/5000 (55%)
[epoch 11] loss: 1.0048195
Test set: Average loss: 1.2025, Accuracy: 2740/5000 (55%)
[epoch 12] loss: 0.9751373
Test set: Average loss: 1.1933, Accuracy: 2743/5000 (55%)
[epoch 13] loss: 0.9553733
Test set: Average loss: 1.1851, Accuracy: 2772/5000 (55%)
[epoch 14] loss: 0.9237321
Test set: Average loss: 1.1779, Accuracy: 2778/5000 (56%)
[epoch 15] loss: 0.8986595
Test set: Average loss: 1.1711, Accuracy: 2801/5000 (56%)
[epoch 16] loss: 0.8840198
Test set: Average loss: 1.1644, Accuracy: 2813/5000 (56%)
[epoch 17] loss: 0.8590313
Test set: Average loss: 1.1573, Accuracy: 2835/5000 (57%)
[epoch 18] loss: 0.8339837
Test set: Average loss: 1.1530, Accuracy: 2834/5000 (57%)
[epoch 19] loss: 0.8180604
Test set: Average loss: 1.1487, Accuracy: 2848/5000 (57%)
[epoch 20] loss: 0.7992363
Test set: Average loss: 1.1417, Accuracy: 2866/5000 (57%)
[epoch 21] loss: 0.7764973
Test set: Average loss: 1.1384, Accuracy: 2858/5000 (57%)
[epoch 22] loss: 0.7579199
Test set: Average loss: 1.1333, Accuracy: 2879/5000 (58%)
[epoch 23] loss: 0.7416825
Test set: Average loss: 1.1333, Accuracy: 2871/5000 (57%)
[epoch 24] loss: 0.7234376
Test set: Average loss: 1.1257, Accuracy: 2881/5000 (58%)
[epoch 25] loss: 0.7047801
Test set: Average loss: 1.1226, Accuracy: 2880/5000 (58%)
Validation:
Test set: Average loss: 1.1257, Accuracy: 2881/5000 (58%)
Test
Test set: Average loss: 1.1518, Accuracy: 2840/5000 (57%)
Test set: Average loss: 0.7039, Accuracy: 858/1000 (86%)
2500
## seed: 11
Validation accuracy before training:
Test set: Average loss: 1.5848, Accuracy: 1300/5000 (26%)
[epoch 1] loss: 1.4285115
Test set: Average loss: 1.3351, Accuracy: 2456/5000 (49%)
[epoch 2] loss: 1.2683225
Test set: Average loss: 1.2621, Accuracy: 2655/5000 (53%)
[epoch 3] loss: 1.1926803
Test set: Average loss: 1.2205, Accuracy: 2754/5000 (55%)
[epoch 4] loss: 1.1437856
Test set: Average loss: 1.1907, Accuracy: 2843/5000 (57%)
[epoch 5] loss: 1.1013814
Test set: Average loss: 1.1705, Accuracy: 2868/5000 (57%)
[epoch 6] loss: 1.0681716
Test set: Average loss: 1.1513, Accuracy: 2891/5000 (58%)
[epoch 7] loss: 1.0270208
Test set: Average loss: 1.1347, Accuracy: 2937/5000 (59%)
[epoch 8] loss: 0.9949899
Test set: Average loss: 1.1212, Accuracy: 2942/5000 (59%)
[epoch 9] loss: 0.9706652
Test set: Average loss: 1.1087, Accuracy: 2946/5000 (59%)
[epoch 10] loss: 0.9394718
Test set: Average loss: 1.0976, Accuracy: 2972/5000 (59%)
[epoch 11] loss: 0.9153658
Test set: Average loss: 1.0891, Accuracy: 2970/5000 (59%)
[epoch 12] loss: 0.8822777
Test set: Average loss: 1.0787, Accuracy: 2994/5000 (60%)
[epoch 13] loss: 0.8554093
Test set: Average loss: 1.0728, Accuracy: 2983/5000 (60%)
[epoch 14] loss: 0.8257932
Test set: Average loss: 1.0642, Accuracy: 3023/5000 (60%)
[epoch 15] loss: 0.8108036
Test set: Average loss: 1.0565, Accuracy: 3039/5000 (61%)
[epoch 16] loss: 0.7900901
Test set: Average loss: 1.0565, Accuracy: 3029/5000 (61%)
[epoch 17] loss: 0.7567209
Test set: Average loss: 1.0462, Accuracy: 3052/5000 (61%)
[epoch 18] loss: 0.7326569
Test set: Average loss: 1.0405, Accuracy: 3052/5000 (61%)
[epoch 19] loss: 0.7142522
Test set: Average loss: 1.0364, Accuracy: 3065/5000 (61%)
[epoch 20] loss: 0.6930270
Test set: Average loss: 1.0344, Accuracy: 3071/5000 (61%)
[epoch 21] loss: 0.6741727
Test set: Average loss: 1.0286, Accuracy: 3076/5000 (62%)
[epoch 22] loss: 0.6446238
Test set: Average loss: 1.0248, Accuracy: 3083/5000 (62%)
[epoch 23] loss: 0.6262149
Test set: Average loss: 1.0203, Accuracy: 3079/5000 (62%)
[epoch 24] loss: 0.6045050
Test set: Average loss: 1.0201, Accuracy: 3067/5000 (61%)
[epoch 25] loss: 0.5860103
Test set: Average loss: 1.0206, Accuracy: 3075/5000 (62%)
Validation:
Test set: Average loss: 1.0248, Accuracy: 3083/5000 (62%)
Test
Test set: Average loss: 1.0303, Accuracy: 3036/5000 (61%)
Test set: Average loss: 0.6182, Accuracy: 2119/2500 (85%)
## seed: 12
Validation accuracy before training:
Test set: Average loss: 1.6016, Accuracy: 1176/5000 (24%)
[epoch 1] loss: 1.4711699
Test set: Average loss: 1.3826, Accuracy: 2144/5000 (43%)
[epoch 2] loss: 1.3392878
Test set: Average loss: 1.3160, Accuracy: 2438/5000 (49%)
[epoch 3] loss: 1.2688762
Test set: Average loss: 1.2730, Accuracy: 2604/5000 (52%)
[epoch 4] loss: 1.2149304
Test set: Average loss: 1.2449, Accuracy: 2671/5000 (53%)
[epoch 5] loss: 1.1687642
Test set: Average loss: 1.2153, Accuracy: 2764/5000 (55%)
[epoch 6] loss: 1.1304147
Test set: Average loss: 1.1946, Accuracy: 2815/5000 (56%)
[epoch 7] loss: 1.0964217
Test set: Average loss: 1.1718, Accuracy: 2875/5000 (58%)
[epoch 8] loss: 1.0552748
Test set: Average loss: 1.1551, Accuracy: 2931/5000 (59%)
[epoch 9] loss: 1.0199864
Test set: Average loss: 1.1379, Accuracy: 2957/5000 (59%)
[epoch 10] loss: 0.9881757
Test set: Average loss: 1.1239, Accuracy: 2972/5000 (59%)
[epoch 11] loss: 0.9572443
Test set: Average loss: 1.1089, Accuracy: 3000/5000 (60%)
[epoch 12] loss: 0.9286866
Test set: Average loss: 1.0991, Accuracy: 3025/5000 (60%)
[epoch 13] loss: 0.9002403
Test set: Average loss: 1.0861, Accuracy: 3050/5000 (61%)
[epoch 14] loss: 0.8779515
Test set: Average loss: 1.0769, Accuracy: 3066/5000 (61%)
[epoch 15] loss: 0.8437852
Test set: Average loss: 1.0661, Accuracy: 3089/5000 (62%)
[epoch 16] loss: 0.8168468
Test set: Average loss: 1.0586, Accuracy: 3092/5000 (62%)
[epoch 17] loss: 0.7944811
Test set: Average loss: 1.0532, Accuracy: 3092/5000 (62%)
[epoch 18] loss: 0.7671883
Test set: Average loss: 1.0424, Accuracy: 3113/5000 (62%)
[epoch 19] loss: 0.7473652
Test set: Average loss: 1.0400, Accuracy: 3096/5000 (62%)
[epoch 20] loss: 0.7219503
Test set: Average loss: 1.0359, Accuracy: 3089/5000 (62%)
[epoch 21] loss: 0.6963662
Test set: Average loss: 1.0278, Accuracy: 3117/5000 (62%)
[epoch 22] loss: 0.6768187
Test set: Average loss: 1.0272, Accuracy: 3110/5000 (62%)
[epoch 23] loss: 0.6656278
Test set: Average loss: 1.0262, Accuracy: 3090/5000 (62%)
[epoch 24] loss: 0.6326628
Test set: Average loss: 1.0201, Accuracy: 3125/5000 (62%)
[epoch 25] loss: 0.6106342
Test set: Average loss: 1.0191, Accuracy: 3092/5000 (62%)
Validation:
Test set: Average loss: 1.0201, Accuracy: 3125/5000 (62%)
Test
Test set: Average loss: 1.0363, Accuracy: 3007/5000 (60%)
Test set: Average loss: 0.6049, Accuracy: 2160/2500 (86%)
## seed: 13
Validation accuracy before training:
Test set: Average loss: 1.7191, Accuracy: 839/5000 (17%)
[epoch 1] loss: 1.4889416
Test set: Average loss: 1.3885, Accuracy: 2333/5000 (47%)
[epoch 2] loss: 1.3119399
Test set: Average loss: 1.3005, Accuracy: 2586/5000 (52%)
[epoch 3] loss: 1.2229973
Test set: Average loss: 1.2485, Accuracy: 2687/5000 (54%)
[epoch 4] loss: 1.1566874
Test set: Average loss: 1.2113, Accuracy: 2783/5000 (56%)
[epoch 5] loss: 1.1094885
Test set: Average loss: 1.1833, Accuracy: 2853/5000 (57%)
[epoch 6] loss: 1.0703704
Test set: Average loss: 1.1617, Accuracy: 2863/5000 (57%)
[epoch 7] loss: 1.0303330
Test set: Average loss: 1.1448, Accuracy: 2901/5000 (58%)
[epoch 8] loss: 1.0059797
Test set: Average loss: 1.1280, Accuracy: 2933/5000 (59%)
[epoch 9] loss: 0.9716694
Test set: Average loss: 1.1180, Accuracy: 2950/5000 (59%)
[epoch 10] loss: 0.9426443
Test set: Average loss: 1.1045, Accuracy: 2981/5000 (60%)
[epoch 11] loss: 0.9161302
Test set: Average loss: 1.0960, Accuracy: 2988/5000 (60%)
[epoch 12] loss: 0.8895381
Test set: Average loss: 1.0884, Accuracy: 2993/5000 (60%)
[epoch 13] loss: 0.8636274
Test set: Average loss: 1.0788, Accuracy: 3005/5000 (60%)
[epoch 14] loss: 0.8406724
Test set: Average loss: 1.0741, Accuracy: 3005/5000 (60%)
[epoch 15] loss: 0.8125518
Test set: Average loss: 1.0723, Accuracy: 2998/5000 (60%)
[epoch 16] loss: 0.7956669
Test set: Average loss: 1.0614, Accuracy: 3028/5000 (61%)
[epoch 17] loss: 0.7696100
Test set: Average loss: 1.0540, Accuracy: 3052/5000 (61%)
[epoch 18] loss: 0.7443793
Test set: Average loss: 1.0522, Accuracy: 3030/5000 (61%)
[epoch 19] loss: 0.7201476
Test set: Average loss: 1.0484, Accuracy: 3058/5000 (61%)
[epoch 20] loss: 0.7015536
Test set: Average loss: 1.0433, Accuracy: 3048/5000 (61%)
[epoch 21] loss: 0.6790036
Test set: Average loss: 1.0415, Accuracy: 3048/5000 (61%)
[epoch 22] loss: 0.6645453
Test set: Average loss: 1.0418, Accuracy: 3048/5000 (61%)
[epoch 23] loss: 0.6451725
Test set: Average loss: 1.0372, Accuracy: 3076/5000 (62%)
[epoch 24] loss: 0.6127865
Test set: Average loss: 1.0368, Accuracy: 3066/5000 (61%)
[epoch 25] loss: 0.5959198
Test set: Average loss: 1.0373, Accuracy: 3050/5000 (61%)
Validation:
Test set: Average loss: 1.0372, Accuracy: 3076/5000 (62%)
Test
Test set: Average loss: 1.0651, Accuracy: 3024/5000 (60%)
Test set: Average loss: 0.6118, Accuracy: 2123/2500 (85%)
5000
## seed: 11
Validation accuracy before training:
Test set: Average loss: 1.5314, Accuracy: 1613/5000 (32%)
[epoch 1] loss: 1.3311037
Test set: Average loss: 1.2515, Accuracy: 2688/5000 (54%)
[epoch 2] loss: 1.1934401
Test set: Average loss: 1.1830, Accuracy: 2890/5000 (58%)
[epoch 3] loss: 1.1175158
Test set: Average loss: 1.1382, Accuracy: 2990/5000 (60%)
[epoch 4] loss: 1.0625616
Test set: Average loss: 1.1098, Accuracy: 3030/5000 (61%)
[epoch 5] loss: 1.0144030
Test set: Average loss: 1.0779, Accuracy: 3107/5000 (62%)
[epoch 6] loss: 0.9746038
Test set: Average loss: 1.0564, Accuracy: 3133/5000 (63%)
[epoch 7] loss: 0.9357958
Test set: Average loss: 1.0399, Accuracy: 3142/5000 (63%)
[epoch 8] loss: 0.8981669
Test set: Average loss: 1.0265, Accuracy: 3149/5000 (63%)
[epoch 9] loss: 0.8656534
Test set: Average loss: 1.0114, Accuracy: 3173/5000 (63%)
[epoch 10] loss: 0.8336471
Test set: Average loss: 1.0024, Accuracy: 3192/5000 (64%)
[epoch 11] loss: 0.8052180
Test set: Average loss: 0.9920, Accuracy: 3199/5000 (64%)
[epoch 12] loss: 0.7745625
Test set: Average loss: 0.9903, Accuracy: 3186/5000 (64%)
[epoch 13] loss: 0.7467519
Test set: Average loss: 0.9789, Accuracy: 3203/5000 (64%)
[epoch 14] loss: 0.7173027
Test set: Average loss: 0.9724, Accuracy: 3237/5000 (65%)
[epoch 15] loss: 0.6892766
Test set: Average loss: 0.9686, Accuracy: 3229/5000 (65%)
[epoch 16] loss: 0.6649688
Test set: Average loss: 0.9598, Accuracy: 3243/5000 (65%)
[epoch 17] loss: 0.6382450
Test set: Average loss: 0.9604, Accuracy: 3224/5000 (64%)
[epoch 18] loss: 0.6121264
Test set: Average loss: 0.9568, Accuracy: 3232/5000 (65%)
[epoch 19] loss: 0.5891827
Test set: Average loss: 0.9524, Accuracy: 3236/5000 (65%)
[epoch 20] loss: 0.5617772
Test set: Average loss: 0.9526, Accuracy: 3241/5000 (65%)
[epoch 21] loss: 0.5400455
Test set: Average loss: 0.9534, Accuracy: 3230/5000 (65%)
[epoch 22] loss: 0.5163018
Test set: Average loss: 0.9541, Accuracy: 3209/5000 (64%)
[epoch 23] loss: 0.4955433
Test set: Average loss: 0.9585, Accuracy: 3214/5000 (64%)
[epoch 24] loss: 0.4724383
Test set: Average loss: 0.9576, Accuracy: 3235/5000 (65%)
[epoch 25] loss: 0.4513067
Test set: Average loss: 0.9545, Accuracy: 3216/5000 (64%)
Validation:
Test set: Average loss: 0.9598, Accuracy: 3243/5000 (65%)
Test
Test set: Average loss: 0.9627, Accuracy: 3195/5000 (64%)
Test set: Average loss: 0.6331, Accuracy: 4082/5000 (82%)
## seed: 12
Validation accuracy before training:
Test set: Average loss: 1.6521, Accuracy: 949/5000 (19%)
[epoch 1] loss: 1.3752195
Test set: Average loss: 1.2645, Accuracy: 2589/5000 (52%)
[epoch 2] loss: 1.2012444
Test set: Average loss: 1.1753, Accuracy: 2882/5000 (58%)
[epoch 3] loss: 1.1188006
Test set: Average loss: 1.1239, Accuracy: 3001/5000 (60%)
[epoch 4] loss: 1.0641078
Test set: Average loss: 1.0889, Accuracy: 3046/5000 (61%)
[epoch 5] loss: 1.0129350
Test set: Average loss: 1.0620, Accuracy: 3077/5000 (62%)
[epoch 6] loss: 0.9705338
Test set: Average loss: 1.0405, Accuracy: 3134/5000 (63%)
[epoch 7] loss: 0.9333724
Test set: Average loss: 1.0249, Accuracy: 3131/5000 (63%)
[epoch 8] loss: 0.8990604
Test set: Average loss: 1.0070, Accuracy: 3169/5000 (63%)
[epoch 9] loss: 0.8661519
Test set: Average loss: 0.9989, Accuracy: 3174/5000 (63%)
[epoch 10] loss: 0.8346050
Test set: Average loss: 0.9873, Accuracy: 3208/5000 (64%)
[epoch 11] loss: 0.8062193
Test set: Average loss: 0.9817, Accuracy: 3191/5000 (64%)
[epoch 12] loss: 0.7759171
Test set: Average loss: 0.9699, Accuracy: 3202/5000 (64%)
[epoch 13] loss: 0.7498479
Test set: Average loss: 0.9633, Accuracy: 3209/5000 (64%)
[epoch 14] loss: 0.7206295
Test set: Average loss: 0.9661, Accuracy: 3169/5000 (63%)
[epoch 15] loss: 0.6948152
Test set: Average loss: 0.9561, Accuracy: 3210/5000 (64%)
[epoch 16] loss: 0.6700437
Test set: Average loss: 0.9539, Accuracy: 3220/5000 (64%)
[epoch 17] loss: 0.6429620
Test set: Average loss: 0.9442, Accuracy: 3238/5000 (65%)
[epoch 18] loss: 0.6180773
Test set: Average loss: 0.9476, Accuracy: 3220/5000 (64%)
[epoch 19] loss: 0.5937514
Test set: Average loss: 0.9441, Accuracy: 3226/5000 (65%)
[epoch 20] loss: 0.5698223
Test set: Average loss: 0.9414, Accuracy: 3242/5000 (65%)
[epoch 21] loss: 0.5449259
Test set: Average loss: 0.9456, Accuracy: 3213/5000 (64%)
[epoch 22] loss: 0.5248349
Test set: Average loss: 0.9463, Accuracy: 3210/5000 (64%)
[epoch 23] loss: 0.4993939
Test set: Average loss: 0.9414, Accuracy: 3240/5000 (65%)
[epoch 24] loss: 0.4760950
Test set: Average loss: 0.9458, Accuracy: 3211/5000 (64%)
[epoch 25] loss: 0.4559152
Test set: Average loss: 0.9440, Accuracy: 3230/5000 (65%)
Validation:
Test set: Average loss: 0.9414, Accuracy: 3242/5000 (65%)
Test
Test set: Average loss: 0.9602, Accuracy: 3187/5000 (64%)
Test set: Average loss: 0.5361, Accuracy: 4280/5000 (86%)
## seed: 13
Validation accuracy before training:
Test set: Average loss: 1.6276, Accuracy: 1028/5000 (21%)
[epoch 1] loss: 1.3897166
Test set: Average loss: 1.2854, Accuracy: 2660/5000 (53%)
[epoch 2] loss: 1.2062636
Test set: Average loss: 1.1927, Accuracy: 2888/5000 (58%)
[epoch 3] loss: 1.1180491
Test set: Average loss: 1.1393, Accuracy: 2970/5000 (59%)
[epoch 4] loss: 1.0591717
Test set: Average loss: 1.1058, Accuracy: 2997/5000 (60%)
[epoch 5] loss: 1.0087735
Test set: Average loss: 1.0766, Accuracy: 3049/5000 (61%)
[epoch 6] loss: 0.9659694
Test set: Average loss: 1.0544, Accuracy: 3060/5000 (61%)
[epoch 7] loss: 0.9260086
Test set: Average loss: 1.0386, Accuracy: 3103/5000 (62%)
[epoch 8] loss: 0.8927476
Test set: Average loss: 1.0254, Accuracy: 3128/5000 (63%)
[epoch 9] loss: 0.8579799
Test set: Average loss: 1.0124, Accuracy: 3140/5000 (63%)
[epoch 10] loss: 0.8292102
Test set: Average loss: 1.0016, Accuracy: 3152/5000 (63%)
[epoch 11] loss: 0.7969282
Test set: Average loss: 0.9921, Accuracy: 3143/5000 (63%)
[epoch 12] loss: 0.7682004
Test set: Average loss: 0.9854, Accuracy: 3154/5000 (63%)
[epoch 13] loss: 0.7394200
Test set: Average loss: 0.9772, Accuracy: 3179/5000 (64%)
[epoch 14] loss: 0.7127092
Test set: Average loss: 0.9724, Accuracy: 3186/5000 (64%)
[epoch 15] loss: 0.6840356
Test set: Average loss: 0.9650, Accuracy: 3186/5000 (64%)
[epoch 16] loss: 0.6584919
Test set: Average loss: 0.9620, Accuracy: 3202/5000 (64%)
[epoch 17] loss: 0.6338479
Test set: Average loss: 0.9596, Accuracy: 3198/5000 (64%)
[epoch 18] loss: 0.6109202
Test set: Average loss: 0.9559, Accuracy: 3205/5000 (64%)
[epoch 19] loss: 0.5857500
Test set: Average loss: 0.9583, Accuracy: 3193/5000 (64%)
[epoch 20] loss: 0.5631930
Test set: Average loss: 0.9549, Accuracy: 3209/5000 (64%)
[epoch 21] loss: 0.5383798
Test set: Average loss: 0.9574, Accuracy: 3202/5000 (64%)
[epoch 22] loss: 0.5163389
Test set: Average loss: 0.9592, Accuracy: 3206/5000 (64%)
[epoch 23] loss: 0.4947003
Test set: Average loss: 0.9603, Accuracy: 3198/5000 (64%)
[epoch 24] loss: 0.4735704
Test set: Average loss: 0.9606, Accuracy: 3199/5000 (64%)
[epoch 25] loss: 0.4508820
Test set: Average loss: 0.9609, Accuracy: 3211/5000 (64%)
Validation:
Test set: Average loss: 0.9609, Accuracy: 3211/5000 (64%)
Test
Test set: Average loss: 0.9795, Accuracy: 3183/5000 (64%)
Test set: Average loss: 0.4259, Accuracy: 4501/5000 (90%)
10000
## seed: 11
Validation accuracy before training:
Test set: Average loss: 1.7839, Accuracy: 730/5000 (15%)
[epoch 1] loss: 1.3702223
Test set: Average loss: 1.2341, Accuracy: 2708/5000 (54%)
[epoch 2] loss: 1.1689907
Test set: Average loss: 1.1459, Accuracy: 2902/5000 (58%)
[epoch 3] loss: 1.0880057
Test set: Average loss: 1.0983, Accuracy: 3031/5000 (61%)
[epoch 4] loss: 1.0311227
Test set: Average loss: 1.0641, Accuracy: 3085/5000 (62%)
[epoch 5] loss: 0.9860949
Test set: Average loss: 1.0384, Accuracy: 3124/5000 (62%)
[epoch 6] loss: 0.9465855
Test set: Average loss: 1.0155, Accuracy: 3168/5000 (63%)
[epoch 7] loss: 0.9092511
Test set: Average loss: 0.9998, Accuracy: 3177/5000 (64%)
[epoch 8] loss: 0.8744967
Test set: Average loss: 0.9859, Accuracy: 3201/5000 (64%)
[epoch 9] loss: 0.8442912
Test set: Average loss: 0.9766, Accuracy: 3203/5000 (64%)
[epoch 10] loss: 0.8115690
Test set: Average loss: 0.9655, Accuracy: 3223/5000 (64%)
[epoch 11] loss: 0.7839999
Test set: Average loss: 0.9561, Accuracy: 3260/5000 (65%)
[epoch 12] loss: 0.7527146
Test set: Average loss: 0.9512, Accuracy: 3269/5000 (65%)
[epoch 13] loss: 0.7256259
Test set: Average loss: 0.9422, Accuracy: 3300/5000 (66%)
[epoch 14] loss: 0.6978423
Test set: Average loss: 0.9450, Accuracy: 3268/5000 (65%)
[epoch 15] loss: 0.6684658
Test set: Average loss: 0.9431, Accuracy: 3279/5000 (66%)
[epoch 16] loss: 0.6437230
Test set: Average loss: 0.9425, Accuracy: 3273/5000 (65%)
[epoch 17] loss: 0.6167354
Test set: Average loss: 0.9432, Accuracy: 3256/5000 (65%)
[epoch 18] loss: 0.5913091
Test set: Average loss: 0.9343, Accuracy: 3295/5000 (66%)
[epoch 19] loss: 0.5633207
Test set: Average loss: 0.9368, Accuracy: 3306/5000 (66%)
[epoch 20] loss: 0.5405569
Test set: Average loss: 0.9404, Accuracy: 3286/5000 (66%)
[epoch 21] loss: 0.5115956
Test set: Average loss: 0.9439, Accuracy: 3316/5000 (66%)
[epoch 22] loss: 0.4897466
Test set: Average loss: 0.9467, Accuracy: 3293/5000 (66%)
[epoch 23] loss: 0.4629801
Test set: Average loss: 0.9593, Accuracy: 3264/5000 (65%)
[epoch 24] loss: 0.4406700
Test set: Average loss: 0.9624, Accuracy: 3245/5000 (65%)
[epoch 25] loss: 0.4152626
Test set: Average loss: 0.9734, Accuracy: 3262/5000 (65%)
Validation:
Test set: Average loss: 0.9439, Accuracy: 3316/5000 (66%)
Test
Test set: Average loss: 0.9546, Accuracy: 3209/5000 (64%)
Test set: Average loss: 0.4728, Accuracy: 8731/10000 (87%)
## seed: 12
Validation accuracy before training:
Test set: Average loss: 1.6188, Accuracy: 1203/5000 (24%)
[epoch 1] loss: 1.3076728
Test set: Average loss: 1.1900, Accuracy: 2816/5000 (56%)
[epoch 2] loss: 1.1357298
Test set: Average loss: 1.1078, Accuracy: 3000/5000 (60%)
[epoch 3] loss: 1.0560253
Test set: Average loss: 1.0597, Accuracy: 3096/5000 (62%)
[epoch 4] loss: 0.9977683
Test set: Average loss: 1.0213, Accuracy: 3169/5000 (63%)
[epoch 5] loss: 0.9496855
Test set: Average loss: 0.9965, Accuracy: 3211/5000 (64%)
[epoch 6] loss: 0.9073981
Test set: Average loss: 0.9755, Accuracy: 3243/5000 (65%)
[epoch 7] loss: 0.8693457
Test set: Average loss: 0.9569, Accuracy: 3252/5000 (65%)
[epoch 8] loss: 0.8344269
Test set: Average loss: 0.9468, Accuracy: 3261/5000 (65%)
[epoch 9] loss: 0.8016162
Test set: Average loss: 0.9315, Accuracy: 3263/5000 (65%)
[epoch 10] loss: 0.7687130
Test set: Average loss: 0.9221, Accuracy: 3266/5000 (65%)
[epoch 11] loss: 0.7382799
Test set: Average loss: 0.9164, Accuracy: 3272/5000 (65%)
[epoch 12] loss: 0.7095244
Test set: Average loss: 0.9100, Accuracy: 3297/5000 (66%)
[epoch 13] loss: 0.6822370
Test set: Average loss: 0.9030, Accuracy: 3310/5000 (66%)
[epoch 14] loss: 0.6506083
Test set: Average loss: 0.8969, Accuracy: 3313/5000 (66%)
[epoch 15] loss: 0.6252078
Test set: Average loss: 0.8988, Accuracy: 3296/5000 (66%)
[epoch 16] loss: 0.5977026
Test set: Average loss: 0.8903, Accuracy: 3334/5000 (67%)
[epoch 17] loss: 0.5718289
Test set: Average loss: 0.8881, Accuracy: 3338/5000 (67%)
[epoch 18] loss: 0.5455816
Test set: Average loss: 0.8962, Accuracy: 3320/5000 (66%)
[epoch 19] loss: 0.5214026
Test set: Average loss: 0.8961, Accuracy: 3324/5000 (66%)
[epoch 20] loss: 0.4974527
Test set: Average loss: 0.8917, Accuracy: 3343/5000 (67%)
[epoch 21] loss: 0.4730304
Test set: Average loss: 0.8970, Accuracy: 3357/5000 (67%)
[epoch 22] loss: 0.4478171
Test set: Average loss: 0.8960, Accuracy: 3324/5000 (66%)
[epoch 23] loss: 0.4269222
Test set: Average loss: 0.9144, Accuracy: 3332/5000 (67%)
[epoch 24] loss: 0.4032217
Test set: Average loss: 0.9023, Accuracy: 3342/5000 (67%)
[epoch 25] loss: 0.3833767
Test set: Average loss: 0.9096, Accuracy: 3348/5000 (67%)
Validation:
Test set: Average loss: 0.8970, Accuracy: 3357/5000 (67%)
Test
Test set: Average loss: 0.9164, Accuracy: 3345/5000 (67%)
Test set: Average loss: 0.4438, Accuracy: 8790/10000 (88%)
## seed: 13
Validation accuracy before training:
Test set: Average loss: 1.7628, Accuracy: 661/5000 (13%)
[epoch 1] loss: 1.3559522
Test set: Average loss: 1.2234, Accuracy: 2710/5000 (54%)
[epoch 2] loss: 1.1612046
Test set: Average loss: 1.1290, Accuracy: 2934/5000 (59%)
[epoch 3] loss: 1.0734785
Test set: Average loss: 1.0710, Accuracy: 3086/5000 (62%)
[epoch 4] loss: 1.0086317
Test set: Average loss: 1.0363, Accuracy: 3104/5000 (62%)
[epoch 5] loss: 0.9559869
Test set: Average loss: 1.0051, Accuracy: 3196/5000 (64%)
[epoch 6] loss: 0.9112786
Test set: Average loss: 0.9846, Accuracy: 3201/5000 (64%)
[epoch 7] loss: 0.8715273
Test set: Average loss: 0.9660, Accuracy: 3240/5000 (65%)
[epoch 8] loss: 0.8348480
Test set: Average loss: 0.9532, Accuracy: 3250/5000 (65%)
[epoch 9] loss: 0.7995298
Test set: Average loss: 0.9477, Accuracy: 3236/5000 (65%)
[epoch 10] loss: 0.7663318
Test set: Average loss: 0.9337, Accuracy: 3272/5000 (65%)
[epoch 11] loss: 0.7355676
Test set: Average loss: 0.9295, Accuracy: 3268/5000 (65%)
[epoch 12] loss: 0.7042912
Test set: Average loss: 0.9317, Accuracy: 3264/5000 (65%)
[epoch 13] loss: 0.6760524
Test set: Average loss: 0.9254, Accuracy: 3266/5000 (65%)
[epoch 14] loss: 0.6480141
Test set: Average loss: 0.9210, Accuracy: 3286/5000 (66%)
[epoch 15] loss: 0.6200387
Test set: Average loss: 0.9232, Accuracy: 3289/5000 (66%)
[epoch 16] loss: 0.5918277
Test set: Average loss: 0.9253, Accuracy: 3302/5000 (66%)
[epoch 17] loss: 0.5674068
Test set: Average loss: 0.9353, Accuracy: 3285/5000 (66%)
[epoch 18] loss: 0.5414650
Test set: Average loss: 0.9286, Accuracy: 3312/5000 (66%)
[epoch 19] loss: 0.5135160
Test set: Average loss: 0.9333, Accuracy: 3316/5000 (66%)
[epoch 20] loss: 0.4905347
Test set: Average loss: 0.9343, Accuracy: 3283/5000 (66%)
[epoch 21] loss: 0.4660751
Test set: Average loss: 0.9372, Accuracy: 3296/5000 (66%)
[epoch 22] loss: 0.4418566
Test set: Average loss: 0.9502, Accuracy: 3302/5000 (66%)
[epoch 23] loss: 0.4177943
Test set: Average loss: 0.9477, Accuracy: 3323/5000 (66%)
[epoch 24] loss: 0.3958848
Test set: Average loss: 0.9662, Accuracy: 3289/5000 (66%)
[epoch 25] loss: 0.3724035
Test set: Average loss: 0.9737, Accuracy: 3313/5000 (66%)
Validation:
Test set: Average loss: 0.9477, Accuracy: 3323/5000 (66%)
Test
Test set: Average loss: 0.9632, Accuracy: 3239/5000 (65%)
Test set: Average loss: 0.3828, Accuracy: 9008/10000 (90%)
15000
## seed: 11
Validation accuracy before training:
Test set: Average loss: 1.7950, Accuracy: 503/5000 (10%)
[epoch 1] loss: 1.2987799
Test set: Average loss: 1.1689, Accuracy: 2870/5000 (57%)
[epoch 2] loss: 1.1124318
Test set: Average loss: 1.0822, Accuracy: 3055/5000 (61%)
[epoch 3] loss: 1.0302569
Test set: Average loss: 1.0316, Accuracy: 3140/5000 (63%)
[epoch 4] loss: 0.9713965
Test set: Average loss: 1.0015, Accuracy: 3160/5000 (63%)
[epoch 5] loss: 0.9243819
Test set: Average loss: 0.9693, Accuracy: 3230/5000 (65%)
[epoch 6] loss: 0.8820699
Test set: Average loss: 0.9508, Accuracy: 3247/5000 (65%)
[epoch 7] loss: 0.8433089
Test set: Average loss: 0.9390, Accuracy: 3259/5000 (65%)
[epoch 8] loss: 0.8102019
Test set: Average loss: 0.9234, Accuracy: 3292/5000 (66%)
[epoch 9] loss: 0.7769745
Test set: Average loss: 0.9151, Accuracy: 3269/5000 (65%)
[epoch 10] loss: 0.7449750
Test set: Average loss: 0.9089, Accuracy: 3291/5000 (66%)
[epoch 11] loss: 0.7149738
Test set: Average loss: 0.9063, Accuracy: 3314/5000 (66%)
[epoch 12] loss: 0.6868832
Test set: Average loss: 0.8957, Accuracy: 3343/5000 (67%)
[epoch 13] loss: 0.6577039
Test set: Average loss: 0.8892, Accuracy: 3338/5000 (67%)
[epoch 14] loss: 0.6314260
Test set: Average loss: 0.8972, Accuracy: 3337/5000 (67%)
[epoch 15] loss: 0.6047921
Test set: Average loss: 0.8962, Accuracy: 3332/5000 (67%)
[epoch 16] loss: 0.5791578
Test set: Average loss: 0.8900, Accuracy: 3348/5000 (67%)
[epoch 17] loss: 0.5531285
Test set: Average loss: 0.8977, Accuracy: 3352/5000 (67%)
[epoch 18] loss: 0.5288612
Test set: Average loss: 0.9020, Accuracy: 3321/5000 (66%)
[epoch 19] loss: 0.5050196
Test set: Average loss: 0.9112, Accuracy: 3340/5000 (67%)
[epoch 20] loss: 0.4827075
Test set: Average loss: 0.9063, Accuracy: 3349/5000 (67%)
[epoch 21] loss: 0.4596821
Test set: Average loss: 0.9134, Accuracy: 3351/5000 (67%)
[epoch 22] loss: 0.4360702
Test set: Average loss: 0.9238, Accuracy: 3339/5000 (67%)
[epoch 23] loss: 0.4141684
Test set: Average loss: 0.9394, Accuracy: 3333/5000 (67%)
[epoch 24] loss: 0.3935905
Test set: Average loss: 0.9355, Accuracy: 3333/5000 (67%)
[epoch 25] loss: 0.3708533
Test set: Average loss: 0.9430, Accuracy: 3338/5000 (67%)
Validation:
Test set: Average loss: 0.8977, Accuracy: 3352/5000 (67%)
Test
Test set: Average loss: 0.9093, Accuracy: 3340/5000 (67%)
Test set: Average loss: 0.5184, Accuracy: 12541/15000 (84%)
## seed: 12
Validation accuracy before training:
Test set: Average loss: 1.5823, Accuracy: 1355/5000 (27%)
[epoch 1] loss: 1.2548387
Test set: Average loss: 1.1289, Accuracy: 2990/5000 (60%)
[epoch 2] loss: 1.0724521
Test set: Average loss: 1.0415, Accuracy: 3163/5000 (63%)
[epoch 3] loss: 0.9919355
Test set: Average loss: 0.9930, Accuracy: 3231/5000 (65%)
[epoch 4] loss: 0.9353995
Test set: Average loss: 0.9597, Accuracy: 3260/5000 (65%)
[epoch 5] loss: 0.8891733
Test set: Average loss: 0.9438, Accuracy: 3270/5000 (65%)
[epoch 6] loss: 0.8496279
Test set: Average loss: 0.9213, Accuracy: 3317/5000 (66%)
[epoch 7] loss: 0.8125953
Test set: Average loss: 0.9112, Accuracy: 3319/5000 (66%)
[epoch 8] loss: 0.7782956
Test set: Average loss: 0.8976, Accuracy: 3346/5000 (67%)
[epoch 9] loss: 0.7467628
Test set: Average loss: 0.8871, Accuracy: 3378/5000 (68%)
[epoch 10] loss: 0.7152225
Test set: Average loss: 0.8881, Accuracy: 3371/5000 (67%)
[epoch 11] loss: 0.6860003
Test set: Average loss: 0.8838, Accuracy: 3378/5000 (68%)
[epoch 12] loss: 0.6591958
Test set: Average loss: 0.8871, Accuracy: 3363/5000 (67%)
[epoch 13] loss: 0.6309381
Test set: Average loss: 0.8753, Accuracy: 3382/5000 (68%)
[epoch 14] loss: 0.6041687
Test set: Average loss: 0.8829, Accuracy: 3365/5000 (67%)
[epoch 15] loss: 0.5781240
Test set: Average loss: 0.8870, Accuracy: 3369/5000 (67%)
[epoch 16] loss: 0.5524415
Test set: Average loss: 0.8788, Accuracy: 3403/5000 (68%)
[epoch 17] loss: 0.5290867
Test set: Average loss: 0.8874, Accuracy: 3378/5000 (68%)
[epoch 18] loss: 0.5028701
Test set: Average loss: 0.8876, Accuracy: 3379/5000 (68%)
[epoch 19] loss: 0.4801506
Test set: Average loss: 0.8972, Accuracy: 3358/5000 (67%)
[epoch 20] loss: 0.4561687
Test set: Average loss: 0.9046, Accuracy: 3364/5000 (67%)
[epoch 21] loss: 0.4343386
Test set: Average loss: 0.9089, Accuracy: 3357/5000 (67%)
[epoch 22] loss: 0.4106527
Test set: Average loss: 0.9182, Accuracy: 3349/5000 (67%)
[epoch 23] loss: 0.3885056
Test set: Average loss: 0.9351, Accuracy: 3338/5000 (67%)
[epoch 24] loss: 0.3687030
Test set: Average loss: 0.9391, Accuracy: 3334/5000 (67%)
[epoch 25] loss: 0.3485377
Test set: Average loss: 0.9403, Accuracy: 3351/5000 (67%)
Validation:
Test set: Average loss: 0.8788, Accuracy: 3403/5000 (68%)
Test
Test set: Average loss: 0.8987, Accuracy: 3331/5000 (67%)
Test set: Average loss: 0.5153, Accuracy: 12633/15000 (84%)
## seed: 13
Validation accuracy before training:
Test set: Average loss: 1.6103, Accuracy: 1319/5000 (26%)
[epoch 1] loss: 1.2570277
Test set: Average loss: 1.1317, Accuracy: 3040/5000 (61%)
[epoch 2] loss: 1.0683074
Test set: Average loss: 1.0438, Accuracy: 3175/5000 (64%)
[epoch 3] loss: 0.9887884
Test set: Average loss: 0.9993, Accuracy: 3230/5000 (65%)
[epoch 4] loss: 0.9345658
Test set: Average loss: 0.9657, Accuracy: 3273/5000 (65%)
[epoch 5] loss: 0.8882313
Test set: Average loss: 0.9444, Accuracy: 3286/5000 (66%)
[epoch 6] loss: 0.8497374
Test set: Average loss: 0.9280, Accuracy: 3317/5000 (66%)
[epoch 7] loss: 0.8151487
Test set: Average loss: 0.9166, Accuracy: 3318/5000 (66%)
[epoch 8] loss: 0.7827742
Test set: Average loss: 0.9059, Accuracy: 3322/5000 (66%)
[epoch 9] loss: 0.7518331
Test set: Average loss: 0.9014, Accuracy: 3330/5000 (67%)
[epoch 10] loss: 0.7224844
Test set: Average loss: 0.8914, Accuracy: 3329/5000 (67%)
[epoch 11] loss: 0.6953273
Test set: Average loss: 0.8908, Accuracy: 3339/5000 (67%)
[epoch 12] loss: 0.6665159
Test set: Average loss: 0.8913, Accuracy: 3329/5000 (67%)
[epoch 13] loss: 0.6401004
Test set: Average loss: 0.8868, Accuracy: 3361/5000 (67%)
[epoch 14] loss: 0.6130309
Test set: Average loss: 0.8963, Accuracy: 3326/5000 (67%)
[epoch 15] loss: 0.5888019
Test set: Average loss: 0.8903, Accuracy: 3342/5000 (67%)
[epoch 16] loss: 0.5627786
Test set: Average loss: 0.8920, Accuracy: 3348/5000 (67%)
[epoch 17] loss: 0.5379553
Test set: Average loss: 0.8908, Accuracy: 3335/5000 (67%)
[epoch 18] loss: 0.5136317
Test set: Average loss: 0.9012, Accuracy: 3351/5000 (67%)
[epoch 19] loss: 0.4912909
Test set: Average loss: 0.8982, Accuracy: 3357/5000 (67%)
[epoch 20] loss: 0.4660098
Test set: Average loss: 0.9112, Accuracy: 3352/5000 (67%)
[epoch 21] loss: 0.4442568
Test set: Average loss: 0.9186, Accuracy: 3342/5000 (67%)
[epoch 22] loss: 0.4212429
Test set: Average loss: 0.9434, Accuracy: 3323/5000 (66%)
[epoch 23] loss: 0.4007343
Test set: Average loss: 0.9364, Accuracy: 3347/5000 (67%)
[epoch 24] loss: 0.3785272
Test set: Average loss: 0.9613, Accuracy: 3307/5000 (66%)
[epoch 25] loss: 0.3586555
Test set: Average loss: 0.9654, Accuracy: 3345/5000 (67%)
Validation:
Test set: Average loss: 0.8868, Accuracy: 3361/5000 (67%)
Test
Test set: Average loss: 0.8991, Accuracy: 3304/5000 (66%)
Test set: Average loss: 0.6005, Accuracy: 12097/15000 (81%)
20000
## seed: 11
Validation accuracy before training:
Test set: Average loss: 1.6081, Accuracy: 1155/5000 (23%)
[epoch 1] loss: 1.2151324
Test set: Average loss: 1.1158, Accuracy: 2959/5000 (59%)
[epoch 2] loss: 1.0608910
Test set: Average loss: 1.0372, Accuracy: 3104/5000 (62%)
[epoch 3] loss: 0.9805724
Test set: Average loss: 0.9875, Accuracy: 3198/5000 (64%)
[epoch 4] loss: 0.9216783
Test set: Average loss: 0.9542, Accuracy: 3250/5000 (65%)
[epoch 5] loss: 0.8729388
Test set: Average loss: 0.9288, Accuracy: 3284/5000 (66%)
[epoch 6] loss: 0.8298744
Test set: Average loss: 0.9136, Accuracy: 3305/5000 (66%)
[epoch 7] loss: 0.7914724
Test set: Average loss: 0.8960, Accuracy: 3335/5000 (67%)
[epoch 8] loss: 0.7562004
Test set: Average loss: 0.8940, Accuracy: 3328/5000 (67%)
[epoch 9] loss: 0.7250674
Test set: Average loss: 0.8798, Accuracy: 3404/5000 (68%)
[epoch 10] loss: 0.6945306
Test set: Average loss: 0.8723, Accuracy: 3383/5000 (68%)
[epoch 11] loss: 0.6645371
Test set: Average loss: 0.8691, Accuracy: 3402/5000 (68%)
[epoch 12] loss: 0.6357963
Test set: Average loss: 0.8698, Accuracy: 3387/5000 (68%)
[epoch 13] loss: 0.6099691
Test set: Average loss: 0.8670, Accuracy: 3428/5000 (69%)
[epoch 14] loss: 0.5825692
Test set: Average loss: 0.8694, Accuracy: 3425/5000 (68%)
[epoch 15] loss: 0.5589270
Test set: Average loss: 0.8755, Accuracy: 3419/5000 (68%)
[epoch 16] loss: 0.5340019
Test set: Average loss: 0.8769, Accuracy: 3428/5000 (69%)
[epoch 17] loss: 0.5102549
Test set: Average loss: 0.8858, Accuracy: 3422/5000 (68%)
[epoch 18] loss: 0.4878390
Test set: Average loss: 0.8934, Accuracy: 3397/5000 (68%)
[epoch 19] loss: 0.4653071
Test set: Average loss: 0.9058, Accuracy: 3402/5000 (68%)
[epoch 20] loss: 0.4432735
Test set: Average loss: 0.8998, Accuracy: 3414/5000 (68%)
[epoch 21] loss: 0.4227295
Test set: Average loss: 0.9096, Accuracy: 3402/5000 (68%)
[epoch 22] loss: 0.4022423
Test set: Average loss: 0.9223, Accuracy: 3389/5000 (68%)
[epoch 23] loss: 0.3816541
Test set: Average loss: 0.9386, Accuracy: 3385/5000 (68%)
[epoch 24] loss: 0.3628664
Test set: Average loss: 0.9484, Accuracy: 3395/5000 (68%)
[epoch 25] loss: 0.3437489
Test set: Average loss: 0.9692, Accuracy: 3371/5000 (67%)
Validation:
Test set: Average loss: 0.8769, Accuracy: 3428/5000 (69%)
Test
Test set: Average loss: 0.8939, Accuracy: 3362/5000 (67%)
Test set: Average loss: 0.4989, Accuracy: 16809/20000 (84%)
## seed: 12
Validation accuracy before training:
Test set: Average loss: 1.6271, Accuracy: 1108/5000 (22%)
[epoch 1] loss: 1.2361596
Test set: Average loss: 1.1140, Accuracy: 2986/5000 (60%)
[epoch 2] loss: 1.0571239
Test set: Average loss: 1.0245, Accuracy: 3134/5000 (63%)
[epoch 3] loss: 0.9728468
Test set: Average loss: 0.9783, Accuracy: 3218/5000 (64%)
[epoch 4] loss: 0.9136473
Test set: Average loss: 0.9411, Accuracy: 3261/5000 (65%)
[epoch 5] loss: 0.8662213
Test set: Average loss: 0.9200, Accuracy: 3304/5000 (66%)
[epoch 6] loss: 0.8241885
Test set: Average loss: 0.9001, Accuracy: 3344/5000 (67%)
[epoch 7] loss: 0.7890158
Test set: Average loss: 0.8927, Accuracy: 3325/5000 (66%)
[epoch 8] loss: 0.7558492
Test set: Average loss: 0.8769, Accuracy: 3367/5000 (67%)
[epoch 9] loss: 0.7235867
Test set: Average loss: 0.8746, Accuracy: 3364/5000 (67%)
[epoch 10] loss: 0.6965758
Test set: Average loss: 0.8699, Accuracy: 3367/5000 (67%)
[epoch 11] loss: 0.6674370
Test set: Average loss: 0.8706, Accuracy: 3369/5000 (67%)
[epoch 12] loss: 0.6408134
Test set: Average loss: 0.8700, Accuracy: 3366/5000 (67%)
[epoch 13] loss: 0.6137884
Test set: Average loss: 0.8594, Accuracy: 3394/5000 (68%)
[epoch 14] loss: 0.5885584
Test set: Average loss: 0.8633, Accuracy: 3382/5000 (68%)
[epoch 15] loss: 0.5633546
Test set: Average loss: 0.8757, Accuracy: 3394/5000 (68%)
[epoch 16] loss: 0.5391985
Test set: Average loss: 0.8695, Accuracy: 3402/5000 (68%)
[epoch 17] loss: 0.5150724
Test set: Average loss: 0.8805, Accuracy: 3391/5000 (68%)
[epoch 18] loss: 0.4924889
Test set: Average loss: 0.8838, Accuracy: 3353/5000 (67%)
[epoch 19] loss: 0.4702442
Test set: Average loss: 0.8978, Accuracy: 3357/5000 (67%)
[epoch 20] loss: 0.4488917
Test set: Average loss: 0.9015, Accuracy: 3349/5000 (67%)
[epoch 21] loss: 0.4262209
Test set: Average loss: 0.9096, Accuracy: 3370/5000 (67%)
[epoch 22] loss: 0.4043713
Test set: Average loss: 0.9286, Accuracy: 3344/5000 (67%)
[epoch 23] loss: 0.3840910
Test set: Average loss: 0.9366, Accuracy: 3355/5000 (67%)
[epoch 24] loss: 0.3640702
Test set: Average loss: 0.9572, Accuracy: 3333/5000 (67%)
[epoch 25] loss: 0.3449653
Test set: Average loss: 0.9571, Accuracy: 3352/5000 (67%)
Validation:
Test set: Average loss: 0.8695, Accuracy: 3402/5000 (68%)
Test
Test set: Average loss: 0.8782, Accuracy: 3373/5000 (67%)
Test set: Average loss: 0.5018, Accuracy: 16821/20000 (84%)
## seed: 13
Validation accuracy before training:
Test set: Average loss: 1.6198, Accuracy: 1245/5000 (25%)
[epoch 1] loss: 1.2339006
Test set: Average loss: 1.1204, Accuracy: 3027/5000 (61%)
[epoch 2] loss: 1.0595913
Test set: Average loss: 1.0337, Accuracy: 3184/5000 (64%)
[epoch 3] loss: 0.9777030
Test set: Average loss: 0.9812, Accuracy: 3237/5000 (65%)
[epoch 4] loss: 0.9182632
Test set: Average loss: 0.9507, Accuracy: 3295/5000 (66%)
[epoch 5] loss: 0.8707147
Test set: Average loss: 0.9257, Accuracy: 3321/5000 (66%)
[epoch 6] loss: 0.8294308
Test set: Average loss: 0.9079, Accuracy: 3321/5000 (66%)
[epoch 7] loss: 0.7916458
Test set: Average loss: 0.8953, Accuracy: 3353/5000 (67%)
[epoch 8] loss: 0.7566359
Test set: Average loss: 0.8881, Accuracy: 3359/5000 (67%)
[epoch 9] loss: 0.7243877
Test set: Average loss: 0.8837, Accuracy: 3344/5000 (67%)
[epoch 10] loss: 0.6956671
Test set: Average loss: 0.8729, Accuracy: 3381/5000 (68%)
[epoch 11] loss: 0.6660590
Test set: Average loss: 0.8804, Accuracy: 3371/5000 (67%)
[epoch 12] loss: 0.6399418
Test set: Average loss: 0.8899, Accuracy: 3374/5000 (67%)
[epoch 13] loss: 0.6142079
Test set: Average loss: 0.8872, Accuracy: 3351/5000 (67%)
[epoch 14] loss: 0.5888840
Test set: Average loss: 0.8724, Accuracy: 3397/5000 (68%)
[epoch 15] loss: 0.5616889
Test set: Average loss: 0.8829, Accuracy: 3396/5000 (68%)
[epoch 16] loss: 0.5382074
Test set: Average loss: 0.8899, Accuracy: 3379/5000 (68%)
[epoch 17] loss: 0.5152365
Test set: Average loss: 0.8947, Accuracy: 3372/5000 (67%)
[epoch 18] loss: 0.4906369
Test set: Average loss: 0.8965, Accuracy: 3374/5000 (67%)
[epoch 19] loss: 0.4676665
Test set: Average loss: 0.9038, Accuracy: 3371/5000 (67%)
[epoch 20] loss: 0.4466366
Test set: Average loss: 0.9148, Accuracy: 3384/5000 (68%)
[epoch 21] loss: 0.4249684
Test set: Average loss: 0.9199, Accuracy: 3371/5000 (67%)
[epoch 22] loss: 0.4049531
Test set: Average loss: 0.9460, Accuracy: 3335/5000 (67%)
[epoch 23] loss: 0.3842472
Test set: Average loss: 0.9471, Accuracy: 3370/5000 (67%)
[epoch 24] loss: 0.3629464
Test set: Average loss: 0.9591, Accuracy: 3341/5000 (67%)
[epoch 25] loss: 0.3439783
Test set: Average loss: 0.9699, Accuracy: 3328/5000 (67%)
Validation:
Test set: Average loss: 0.8724, Accuracy: 3397/5000 (68%)
Test
Test set: Average loss: 0.8743, Accuracy: 3380/5000 (68%)
Test set: Average loss: 0.5453, Accuracy: 16545/20000 (83%)
## Pre-Training ABnB
Validation accuracy before training:
Test set: Average loss: 2.3053, Accuracy: 569/5000 (11%)
[epoch 1] loss: 1.9647628
Test set: Average loss: 1.8839, Accuracy: 1823/5000 (36%)
[epoch 2] loss: 1.8255615
Test set: Average loss: 1.8158, Accuracy: 1955/5000 (39%)
[epoch 3] loss: 1.7553622
Test set: Average loss: 1.7710, Accuracy: 1988/5000 (40%)
[epoch 4] loss: 1.7016769
Test set: Average loss: 1.7436, Accuracy: 2039/5000 (41%)
[epoch 5] loss: 1.6575239
Test set: Average loss: 1.7137, Accuracy: 2088/5000 (42%)
[epoch 6] loss: 1.6184519
Test set: Average loss: 1.6972, Accuracy: 2113/5000 (42%)
[epoch 7] loss: 1.5835638
Test set: Average loss: 1.6778, Accuracy: 2142/5000 (43%)
[epoch 8] loss: 1.5507017
Test set: Average loss: 1.6639, Accuracy: 2143/5000 (43%)
[epoch 9] loss: 1.5186546
Test set: Average loss: 1.6540, Accuracy: 2164/5000 (43%)
[epoch 10] loss: 1.4890347
Test set: Average loss: 1.6464, Accuracy: 2175/5000 (44%)
[epoch 11] loss: 1.4614999
Test set: Average loss: 1.6419, Accuracy: 2172/5000 (43%)
[epoch 12] loss: 1.4335335
Test set: Average loss: 1.6356, Accuracy: 2160/5000 (43%)
[epoch 13] loss: 1.4067695
Test set: Average loss: 1.6305, Accuracy: 2209/5000 (44%)
[epoch 14] loss: 1.3802044
Test set: Average loss: 1.6367, Accuracy: 2181/5000 (44%)
[epoch 15] loss: 1.3552583
Test set: Average loss: 1.6313, Accuracy: 2183/5000 (44%)
[epoch 16] loss: 1.3314992
Test set: Average loss: 1.6182, Accuracy: 2202/5000 (44%)
[epoch 17] loss: 1.3073646
Test set: Average loss: 1.6191, Accuracy: 2217/5000 (44%)
[epoch 18] loss: 1.2804909
Test set: Average loss: 1.6241, Accuracy: 2184/5000 (44%)
[epoch 19] loss: 1.2570309
Test set: Average loss: 1.6273, Accuracy: 2193/5000 (44%)
[epoch 20] loss: 1.2333148
Test set: Average loss: 1.6266, Accuracy: 2206/5000 (44%)
[epoch 21] loss: 1.2088387
Test set: Average loss: 1.6232, Accuracy: 2238/5000 (45%)
[epoch 22] loss: 1.1853641
Test set: Average loss: 1.6362, Accuracy: 2212/5000 (44%)
[epoch 23] loss: 1.1624063
Test set: Average loss: 1.6343, Accuracy: 2236/5000 (45%)
[epoch 24] loss: 1.1393861
Test set: Average loss: 1.6391, Accuracy: 2215/5000 (44%)
[epoch 25] loss: 1.1167285
Test set: Average loss: 1.6502, Accuracy: 2207/5000 (44%)
Validation:
Test set: Average loss: 1.6232, Accuracy: 2238/5000 (45%)
Test set: Average loss: 1.5994, Accuracy: 4507/10000 (45%)
25
## seed: 11
Validation accuracy before training:
Test set: Average loss: 1.7513, Accuracy: 797/5000 (16%)
[epoch 1] loss: 1.7223053
Test set: Average loss: 1.7447, Accuracy: 803/5000 (16%)
[epoch 2] loss: 1.6763698
Test set: Average loss: 1.7382, Accuracy: 825/5000 (16%)
[epoch 3] loss: 1.6314996
Test set: Average loss: 1.7317, Accuracy: 842/5000 (17%)
[epoch 4] loss: 1.5881119
Test set: Average loss: 1.7252, Accuracy: 859/5000 (17%)
[epoch 5] loss: 1.5465184
Test set: Average loss: 1.7188, Accuracy: 886/5000 (18%)
[epoch 6] loss: 1.5069187
Test set: Average loss: 1.7125, Accuracy: 909/5000 (18%)
[epoch 7] loss: 1.4693925
Test set: Average loss: 1.7062, Accuracy: 929/5000 (19%)
[epoch 8] loss: 1.4339048
Test set: Average loss: 1.7001, Accuracy: 948/5000 (19%)
[epoch 9] loss: 1.4003328
Test set: Average loss: 1.6941, Accuracy: 965/5000 (19%)
[epoch 10] loss: 1.3685215
Test set: Average loss: 1.6882, Accuracy: 995/5000 (20%)
[epoch 11] loss: 1.3383342
Test set: Average loss: 1.6825, Accuracy: 1016/5000 (20%)
[epoch 12] loss: 1.3096699
Test set: Average loss: 1.6770, Accuracy: 1029/5000 (21%)
[epoch 13] loss: 1.2824471
Test set: Average loss: 1.6716, Accuracy: 1054/5000 (21%)
[epoch 14] loss: 1.2565873
Test set: Average loss: 1.6665, Accuracy: 1075/5000 (22%)
[epoch 15] loss: 1.2320189
Test set: Average loss: 1.6615, Accuracy: 1099/5000 (22%)
[epoch 16] loss: 1.2086895
Test set: Average loss: 1.6567, Accuracy: 1125/5000 (22%)
[epoch 17] loss: 1.1865742
Test set: Average loss: 1.6521, Accuracy: 1150/5000 (23%)
[epoch 18] loss: 1.1656677
Test set: Average loss: 1.6477, Accuracy: 1165/5000 (23%)
[epoch 19] loss: 1.1459590
Test set: Average loss: 1.6436, Accuracy: 1181/5000 (24%)
[epoch 20] loss: 1.1274102
Test set: Average loss: 1.6396, Accuracy: 1206/5000 (24%)
[epoch 21] loss: 1.1099463
Test set: Average loss: 1.6359, Accuracy: 1235/5000 (25%)
[epoch 22] loss: 1.0934612
Test set: Average loss: 1.6323, Accuracy: 1257/5000 (25%)
[epoch 23] loss: 1.0778308
Test set: Average loss: 1.6291, Accuracy: 1277/5000 (26%)
[epoch 24] loss: 1.0629312
Test set: Average loss: 1.6260, Accuracy: 1296/5000 (26%)
[epoch 25] loss: 1.0486538
Test set: Average loss: 1.6231, Accuracy: 1310/5000 (26%)
Validation:
Test set: Average loss: 1.6231, Accuracy: 1310/5000 (26%)
Test
Test set: Average loss: 1.6258, Accuracy: 1340/5000 (27%)
Test set: Average loss: 1.0349, Accuracy: 22/25 (88%)
## seed: 12
Validation accuracy before training:
Test set: Average loss: 1.7284, Accuracy: 895/5000 (18%)
[epoch 1] loss: 1.7814090
Test set: Average loss: 1.7191, Accuracy: 944/5000 (19%)
[epoch 2] loss: 1.7316955
Test set: Average loss: 1.7097, Accuracy: 976/5000 (20%)
[epoch 3] loss: 1.6825418
Test set: Average loss: 1.7004, Accuracy: 1018/5000 (20%)
[epoch 4] loss: 1.6349363
Test set: Average loss: 1.6912, Accuracy: 1067/5000 (21%)
[epoch 5] loss: 1.5895526
Test set: Average loss: 1.6821, Accuracy: 1107/5000 (22%)
[epoch 6] loss: 1.5466793
Test set: Average loss: 1.6732, Accuracy: 1150/5000 (23%)
[epoch 7] loss: 1.5063453
Test set: Average loss: 1.6645, Accuracy: 1204/5000 (24%)
[epoch 8] loss: 1.4684403
Test set: Average loss: 1.6561, Accuracy: 1240/5000 (25%)
[epoch 9] loss: 1.4327590
Test set: Average loss: 1.6480, Accuracy: 1272/5000 (25%)
[epoch 10] loss: 1.3990539
Test set: Average loss: 1.6401, Accuracy: 1316/5000 (26%)
[epoch 11] loss: 1.3671150
Test set: Average loss: 1.6326, Accuracy: 1344/5000 (27%)
[epoch 12] loss: 1.3368161
Test set: Average loss: 1.6253, Accuracy: 1365/5000 (27%)
[epoch 13] loss: 1.3080870
Test set: Average loss: 1.6183, Accuracy: 1386/5000 (28%)
[epoch 14] loss: 1.2808417
Test set: Average loss: 1.6116, Accuracy: 1412/5000 (28%)
[epoch 15] loss: 1.2549434
Test set: Average loss: 1.6052, Accuracy: 1428/5000 (29%)
[epoch 16] loss: 1.2302283
Test set: Average loss: 1.5991, Accuracy: 1456/5000 (29%)
[epoch 17] loss: 1.2065470
Test set: Average loss: 1.5932, Accuracy: 1464/5000 (29%)
[epoch 18] loss: 1.1837838
Test set: Average loss: 1.5876, Accuracy: 1485/5000 (30%)
[epoch 19] loss: 1.1618565
Test set: Average loss: 1.5823, Accuracy: 1511/5000 (30%)
[epoch 20] loss: 1.1407024
Test set: Average loss: 1.5771, Accuracy: 1528/5000 (31%)
[epoch 21] loss: 1.1202692
Test set: Average loss: 1.5722, Accuracy: 1545/5000 (31%)
[epoch 22] loss: 1.1005149
Test set: Average loss: 1.5674, Accuracy: 1567/5000 (31%)
[epoch 23] loss: 1.0814170
Test set: Average loss: 1.5629, Accuracy: 1589/5000 (32%)
[epoch 24] loss: 1.0629797
Test set: Average loss: 1.5585, Accuracy: 1616/5000 (32%)
[epoch 25] loss: 1.0452363
Test set: Average loss: 1.5543, Accuracy: 1627/5000 (33%)
Validation:
Test set: Average loss: 1.5543, Accuracy: 1627/5000 (33%)
Test
Test set: Average loss: 1.5553, Accuracy: 1635/5000 (33%)
Test set: Average loss: 1.0282, Accuracy: 23/25 (92%)
## seed: 13
Validation accuracy before training:
Test set: Average loss: 1.6410, Accuracy: 1255/5000 (25%)
[epoch 1] loss: 1.7038710
Test set: Average loss: 1.6346, Accuracy: 1292/5000 (26%)
[epoch 2] loss: 1.6597621
Test set: Average loss: 1.6283, Accuracy: 1336/5000 (27%)
[epoch 3] loss: 1.6164005
Test set: Average loss: 1.6222, Accuracy: 1387/5000 (28%)
[epoch 4] loss: 1.5741235
Test set: Average loss: 1.6163, Accuracy: 1419/5000 (28%)
[epoch 5] loss: 1.5332282
Test set: Average loss: 1.6105, Accuracy: 1440/5000 (29%)
[epoch 6] loss: 1.4939042
Test set: Average loss: 1.6050, Accuracy: 1479/5000 (30%)
[epoch 7] loss: 1.4562144
Test set: Average loss: 1.5997, Accuracy: 1506/5000 (30%)
[epoch 8] loss: 1.4201331
Test set: Average loss: 1.5947, Accuracy: 1546/5000 (31%)
[epoch 9] loss: 1.3856076
Test set: Average loss: 1.5900, Accuracy: 1563/5000 (31%)
[epoch 10] loss: 1.3526027
Test set: Average loss: 1.5855, Accuracy: 1592/5000 (32%)
[epoch 11] loss: 1.3211048
Test set: Average loss: 1.5814, Accuracy: 1613/5000 (32%)
[epoch 12] loss: 1.2910984
Test set: Average loss: 1.5775, Accuracy: 1633/5000 (33%)
[epoch 13] loss: 1.2625400
Test set: Average loss: 1.5738, Accuracy: 1646/5000 (33%)
[epoch 14] loss: 1.2353600
Test set: Average loss: 1.5704, Accuracy: 1659/5000 (33%)
[epoch 15] loss: 1.2094914
Test set: Average loss: 1.5672, Accuracy: 1673/5000 (33%)
[epoch 16] loss: 1.1848888
Test set: Average loss: 1.5642, Accuracy: 1690/5000 (34%)
[epoch 17] loss: 1.1615299
Test set: Average loss: 1.5613, Accuracy: 1693/5000 (34%)
[epoch 18] loss: 1.1393973
Test set: Average loss: 1.5586, Accuracy: 1697/5000 (34%)
[epoch 19] loss: 1.1184632
Test set: Average loss: 1.5560, Accuracy: 1720/5000 (34%)
[epoch 20] loss: 1.0986810
Test set: Average loss: 1.5535, Accuracy: 1725/5000 (34%)
[epoch 21] loss: 1.0799897
Test set: Average loss: 1.5511, Accuracy: 1736/5000 (35%)
[epoch 22] loss: 1.0623171
Test set: Average loss: 1.5488, Accuracy: 1743/5000 (35%)
[epoch 23] loss: 1.0455891
Test set: Average loss: 1.5465, Accuracy: 1757/5000 (35%)
[epoch 24] loss: 1.0297303
Test set: Average loss: 1.5443, Accuracy: 1772/5000 (35%)
[epoch 25] loss: 1.0146674
Test set: Average loss: 1.5422, Accuracy: 1786/5000 (36%)
Validation:
Test set: Average loss: 1.5422, Accuracy: 1786/5000 (36%)
Test
Test set: Average loss: 1.5440, Accuracy: 1731/5000 (35%)
Test set: Average loss: 1.0003, Accuracy: 23/25 (92%)
50
## seed: 11
Validation accuracy before training:
Test set: Average loss: 1.8241, Accuracy: 364/5000 (7%)
[epoch 1] loss: 1.8874196
Test set: Average loss: 1.8017, Accuracy: 390/5000 (8%)
[epoch 2] loss: 1.8310636
Test set: Average loss: 1.7797, Accuracy: 417/5000 (8%)
[epoch 3] loss: 1.7677135
Test set: Average loss: 1.7582, Accuracy: 462/5000 (9%)
[epoch 4] loss: 1.7044626
Test set: Average loss: 1.7371, Accuracy: 553/5000 (11%)
[epoch 5] loss: 1.6486621
Test set: Average loss: 1.7174, Accuracy: 626/5000 (13%)
[epoch 6] loss: 1.6054851
Test set: Average loss: 1.6986, Accuracy: 722/5000 (14%)
[epoch 7] loss: 1.5570750
Test set: Average loss: 1.6817, Accuracy: 800/5000 (16%)
[epoch 8] loss: 1.5024751
Test set: Average loss: 1.6660, Accuracy: 883/5000 (18%)
[epoch 9] loss: 1.4496346
Test set: Average loss: 1.6520, Accuracy: 984/5000 (20%)
[epoch 10] loss: 1.4168177
Test set: Average loss: 1.6398, Accuracy: 1048/5000 (21%)
[epoch 11] loss: 1.3981659
Test set: Average loss: 1.6286, Accuracy: 1118/5000 (22%)
[epoch 12] loss: 1.3676380
Test set: Average loss: 1.6187, Accuracy: 1158/5000 (23%)
[epoch 13] loss: 1.3167440
Test set: Average loss: 1.6098, Accuracy: 1201/5000 (24%)
[epoch 14] loss: 1.3104910
Test set: Average loss: 1.6016, Accuracy: 1246/5000 (25%)
[epoch 15] loss: 1.2782044
Test set: Average loss: 1.5940, Accuracy: 1301/5000 (26%)
[epoch 16] loss: 1.2572457
Test set: Average loss: 1.5871, Accuracy: 1326/5000 (27%)
[epoch 17] loss: 1.2185686
Test set: Average loss: 1.5807, Accuracy: 1358/5000 (27%)
[epoch 18] loss: 1.1932457
Test set: Average loss: 1.5747, Accuracy: 1383/5000 (28%)
[epoch 19] loss: 1.1919016
Test set: Average loss: 1.5693, Accuracy: 1402/5000 (28%)
[epoch 20] loss: 1.1541611
Test set: Average loss: 1.5644, Accuracy: 1424/5000 (28%)
[epoch 21] loss: 1.1346168
Test set: Average loss: 1.5597, Accuracy: 1442/5000 (29%)
[epoch 22] loss: 1.1167766
Test set: Average loss: 1.5554, Accuracy: 1459/5000 (29%)
[epoch 23] loss: 1.0977092
Test set: Average loss: 1.5512, Accuracy: 1480/5000 (30%)
[epoch 24] loss: 1.0856769
Test set: Average loss: 1.5470, Accuracy: 1502/5000 (30%)
[epoch 25] loss: 1.0930238
Epoch 24: reducing learning rate of group 0 to 5.0000e-06.
Test set: Average loss: 1.5431, Accuracy: 1519/5000 (30%)
Validation:
Test set: Average loss: 1.5431, Accuracy: 1519/5000 (30%)
Test
Test set: Average loss: 1.5492, Accuracy: 1464/5000 (29%)
Test set: Average loss: 1.0527, Accuracy: 43/50 (86%)
## seed: 12
Validation accuracy before training:
Test set: Average loss: 1.5228, Accuracy: 1687/5000 (34%)
[epoch 1] loss: 1.5390146
Test set: Average loss: 1.5114, Accuracy: 1730/5000 (35%)
[epoch 2] loss: 1.4944735
Test set: Average loss: 1.5018, Accuracy: 1748/5000 (35%)
[epoch 3] loss: 1.4331288
Test set: Average loss: 1.4942, Accuracy: 1777/5000 (36%)
[epoch 4] loss: 1.3917370
Test set: Average loss: 1.4872, Accuracy: 1801/5000 (36%)
[epoch 5] loss: 1.3622646
Test set: Average loss: 1.4808, Accuracy: 1825/5000 (36%)
[epoch 6] loss: 1.3283228
Test set: Average loss: 1.4752, Accuracy: 1847/5000 (37%)
[epoch 7] loss: 1.2686839
Test set: Average loss: 1.4701, Accuracy: 1869/5000 (37%)
[epoch 8] loss: 1.2372195
Test set: Average loss: 1.4657, Accuracy: 1881/5000 (38%)
[epoch 9] loss: 1.2081041
Test set: Average loss: 1.4619, Accuracy: 1872/5000 (37%)
[epoch 10] loss: 1.1896225
Test set: Average loss: 1.4582, Accuracy: 1882/5000 (38%)
[epoch 11] loss: 1.1541542
Test set: Average loss: 1.4548, Accuracy: 1915/5000 (38%)
[epoch 12] loss: 1.1423154
Test set: Average loss: 1.4519, Accuracy: 1934/5000 (39%)
[epoch 13] loss: 1.0969052
Test set: Average loss: 1.4491, Accuracy: 1941/5000 (39%)
[epoch 14] loss: 1.0693991
Test set: Average loss: 1.4462, Accuracy: 1976/5000 (40%)
[epoch 15] loss: 1.0626352
Test set: Average loss: 1.4435, Accuracy: 1978/5000 (40%)
[epoch 16] loss: 1.0466439
Test set: Average loss: 1.4412, Accuracy: 1987/5000 (40%)
[epoch 17] loss: 1.0216044
Test set: Average loss: 1.4390, Accuracy: 1996/5000 (40%)
[epoch 18] loss: 1.0029713
Test set: Average loss: 1.4369, Accuracy: 2010/5000 (40%)
[epoch 19] loss: 0.9823977
Test set: Average loss: 1.4351, Accuracy: 2024/5000 (40%)
[epoch 20] loss: 0.9888206
Epoch 19: reducing learning rate of group 0 to 5.0000e-06.
Test set: Average loss: 1.4335, Accuracy: 2039/5000 (41%)
[epoch 21] loss: 0.9674569
Test set: Average loss: 1.4334, Accuracy: 2040/5000 (41%)
[epoch 22] loss: 0.9491839
Test set: Average loss: 1.4332, Accuracy: 2041/5000 (41%)
[epoch 23] loss: 0.9658265
Epoch 22: reducing learning rate of group 0 to 5.0000e-07.
Test set: Average loss: 1.4331, Accuracy: 2041/5000 (41%)
[epoch 24] loss: 0.9559581
Epoch 23: reducing learning rate of group 0 to 5.0000e-08.
Test set: Average loss: 1.4330, Accuracy: 2042/5000 (41%)
[epoch 25] loss: 0.9463080
Test set: Average loss: 1.4330, Accuracy: 2042/5000 (41%)
Validation:
Test set: Average loss: 1.4330, Accuracy: 2042/5000 (41%)
Test
Test set: Average loss: 1.4340, Accuracy: 1985/5000 (40%)
Test set: Average loss: 0.9597, Accuracy: 48/50 (96%)
## seed: 13
Validation accuracy before training:
Test set: Average loss: 1.6596, Accuracy: 884/5000 (18%)
[epoch 1] loss: 1.7010643
Test set: Average loss: 1.6427, Accuracy: 981/5000 (20%)
[epoch 2] loss: 1.6068258
Test set: Average loss: 1.6257, Accuracy: 1073/5000 (21%)
[epoch 3] loss: 1.5560166
Test set: Average loss: 1.6107, Accuracy: 1163/5000 (23%)
[epoch 4] loss: 1.5330771
Test set: Average loss: 1.5965, Accuracy: 1250/5000 (25%)
[epoch 5] loss: 1.4669312
Test set: Average loss: 1.5837, Accuracy: 1349/5000 (27%)
[epoch 6] loss: 1.4324607
Test set: Average loss: 1.5715, Accuracy: 1418/5000 (28%)
[epoch 7] loss: 1.3845178
Test set: Average loss: 1.5606, Accuracy: 1485/5000 (30%)
[epoch 8] loss: 1.3386089
Test set: Average loss: 1.5502, Accuracy: 1560/5000 (31%)
[epoch 9] loss: 1.3403879
Epoch 8: reducing learning rate of group 0 to 5.0000e-06.
Test set: Average loss: 1.5402, Accuracy: 1629/5000 (33%)
[epoch 10] loss: 1.3224847
Test set: Average loss: 1.5392, Accuracy: 1637/5000 (33%)
[epoch 11] loss: 1.3231368
Epoch 10: reducing learning rate of group 0 to 5.0000e-07.
Test set: Average loss: 1.5383, Accuracy: 1652/5000 (33%)
[epoch 12] loss: 1.3076010
Test set: Average loss: 1.5382, Accuracy: 1652/5000 (33%)
[epoch 13] loss: 1.3106062
Epoch 12: reducing learning rate of group 0 to 5.0000e-08.
Test set: Average loss: 1.5381, Accuracy: 1655/5000 (33%)
[epoch 14] loss: 1.2922044
Test set: Average loss: 1.5381, Accuracy: 1655/5000 (33%)
[epoch 15] loss: 1.3168898
Epoch 14: reducing learning rate of group 0 to 5.0000e-09.
Test set: Average loss: 1.5381, Accuracy: 1655/5000 (33%)
[epoch 16] loss: 1.3000773
Epoch 15: reducing learning rate of group 0 to 5.0000e-10.
Test set: Average loss: 1.5381, Accuracy: 1655/5000 (33%)
[epoch 17] loss: 1.3261711
Epoch 16: reducing learning rate of group 0 to 5.0000e-11.
Test set: Average loss: 1.5381, Accuracy: 1655/5000 (33%)
[epoch 18] loss: 1.3017774
Epoch 17: reducing learning rate of group 0 to 5.0000e-12.
Test set: Average loss: 1.5381, Accuracy: 1655/5000 (33%)
[epoch 19] loss: 1.2992887
Epoch 18: reducing learning rate of group 0 to 5.0000e-13.
Test set: Average loss: 1.5381, Accuracy: 1655/5000 (33%)
[epoch 20] loss: 1.3077507
Epoch 19: reducing learning rate of group 0 to 5.0000e-14.
Test set: Average loss: 1.5381, Accuracy: 1655/5000 (33%)
[epoch 21] loss: 1.3259481
Epoch 20: reducing learning rate of group 0 to 5.0000e-15.
Test set: Average loss: 1.5381, Accuracy: 1655/5000 (33%)
[epoch 22] loss: 1.2974928
Epoch 21: reducing learning rate of group 0 to 5.0000e-16.
Test set: Average loss: 1.5381, Accuracy: 1655/5000 (33%)
[epoch 23] loss: 1.3151577
Epoch 22: reducing learning rate of group 0 to 5.0000e-17.
Test set: Average loss: 1.5381, Accuracy: 1655/5000 (33%)
[epoch 24] loss: 1.3024155
Epoch 23: reducing learning rate of group 0 to 5.0000e-18.
Test set: Average loss: 1.5381, Accuracy: 1655/5000 (33%)
[epoch 25] loss: 1.3172858
Epoch 24: reducing learning rate of group 0 to 5.0000e-19.
Test set: Average loss: 1.5381, Accuracy: 1655/5000 (33%)
Validation:
Test set: Average loss: 1.5381, Accuracy: 1655/5000 (33%)
Test
Test set: Average loss: 1.5410, Accuracy: 1656/5000 (33%)
Test set: Average loss: 1.3091, Accuracy: 33/50 (66%)
100
## seed: 11
Validation accuracy before training:
Test set: Average loss: 1.7847, Accuracy: 473/5000 (9%)
[epoch 1] loss: 1.8969234
Test set: Average loss: 1.7436, Accuracy: 532/5000 (11%)
[epoch 2] loss: 1.7361220
Test set: Average loss: 1.7083, Accuracy: 678/5000 (14%)
[epoch 3] loss: 1.6968781
Test set: Average loss: 1.6795, Accuracy: 829/5000 (17%)
[epoch 4] loss: 1.6672189
Test set: Average loss: 1.6549, Accuracy: 998/5000 (20%)
[epoch 5] loss: 1.5822649
Test set: Average loss: 1.6321, Accuracy: 1156/5000 (23%)
[epoch 6] loss: 1.5268362
Test set: Average loss: 1.6104, Accuracy: 1274/5000 (25%)
[epoch 7] loss: 1.4742319
Test set: Average loss: 1.5897, Accuracy: 1384/5000 (28%)
[epoch 8] loss: 1.4618845
Test set: Average loss: 1.5719, Accuracy: 1470/5000 (29%)
[epoch 9] loss: 1.3780194
Test set: Average loss: 1.5558, Accuracy: 1556/5000 (31%)
[epoch 10] loss: 1.4524456
Epoch 9: reducing learning rate of group 0 to 5.0000e-06.
Test set: Average loss: 1.5422, Accuracy: 1616/5000 (32%)
[epoch 11] loss: 1.3182687
Test set: Average loss: 1.5410, Accuracy: 1625/5000 (32%)
[epoch 12] loss: 1.3218856
Epoch 11: reducing learning rate of group 0 to 5.0000e-07.
Test set: Average loss: 1.5399, Accuracy: 1628/5000 (33%)
[epoch 13] loss: 1.4062797
Epoch 12: reducing learning rate of group 0 to 5.0000e-08.
Test set: Average loss: 1.5398, Accuracy: 1630/5000 (33%)
[epoch 14] loss: 1.3306876
Epoch 13: reducing learning rate of group 0 to 5.0000e-09.
Test set: Average loss: 1.5398, Accuracy: 1630/5000 (33%)
[epoch 15] loss: 1.3117549
Test set: Average loss: 1.5398, Accuracy: 1630/5000 (33%)
[epoch 16] loss: 1.3255379
Epoch 15: reducing learning rate of group 0 to 5.0000e-10.
Test set: Average loss: 1.5398, Accuracy: 1630/5000 (33%)
[epoch 17] loss: 1.3497771
Epoch 16: reducing learning rate of group 0 to 5.0000e-11.
Test set: Average loss: 1.5398, Accuracy: 1630/5000 (33%)
[epoch 18] loss: 1.3363073
Epoch 17: reducing learning rate of group 0 to 5.0000e-12.
Test set: Average loss: 1.5398, Accuracy: 1630/5000 (33%)
[epoch 19] loss: 1.3304140
Epoch 18: reducing learning rate of group 0 to 5.0000e-13.
Test set: Average loss: 1.5398, Accuracy: 1630/5000 (33%)
[epoch 20] loss: 1.3923737
Epoch 19: reducing learning rate of group 0 to 5.0000e-14.
Test set: Average loss: 1.5398, Accuracy: 1630/5000 (33%)
[epoch 21] loss: 1.3658367
Epoch 20: reducing learning rate of group 0 to 5.0000e-15.
Test set: Average loss: 1.5398, Accuracy: 1630/5000 (33%)
[epoch 22] loss: 1.3304283
Epoch 21: reducing learning rate of group 0 to 5.0000e-16.
Test set: Average loss: 1.5398, Accuracy: 1630/5000 (33%)
[epoch 23] loss: 1.3746248
Epoch 22: reducing learning rate of group 0 to 5.0000e-17.
Test set: Average loss: 1.5398, Accuracy: 1630/5000 (33%)
[epoch 24] loss: 1.3534956
Epoch 23: reducing learning rate of group 0 to 5.0000e-18.
Test set: Average loss: 1.5398, Accuracy: 1630/5000 (33%)
[epoch 25] loss: 1.3734601
Epoch 24: reducing learning rate of group 0 to 5.0000e-19.
Test set: Average loss: 1.5398, Accuracy: 1630/5000 (33%)
Validation:
Test set: Average loss: 1.5398, Accuracy: 1630/5000 (33%)
Test
Test set: Average loss: 1.5393, Accuracy: 1588/5000 (32%)
Test set: Average loss: 1.3503, Accuracy: 55/100 (55%)
## seed: 12
Validation accuracy before training:
Test set: Average loss: 1.6636, Accuracy: 930/5000 (19%)
[epoch 1] loss: 1.6187858
Test set: Average loss: 1.6394, Accuracy: 1036/5000 (21%)
[epoch 2] loss: 1.5669875
Test set: Average loss: 1.6179, Accuracy: 1157/5000 (23%)
[epoch 3] loss: 1.5159140
Test set: Average loss: 1.5988, Accuracy: 1270/5000 (25%)
[epoch 4] loss: 1.4808334
Test set: Average loss: 1.5841, Accuracy: 1348/5000 (27%)
[epoch 5] loss: 1.4184673
Test set: Average loss: 1.5731, Accuracy: 1425/5000 (28%)
[epoch 6] loss: 1.3731010
Test set: Average loss: 1.5640, Accuracy: 1487/5000 (30%)
[epoch 7] loss: 1.3166640
Test set: Average loss: 1.5562, Accuracy: 1517/5000 (30%)
[epoch 8] loss: 1.2459413
Test set: Average loss: 1.5466, Accuracy: 1581/5000 (32%)
[epoch 9] loss: 1.2543346
Epoch 8: reducing learning rate of group 0 to 5.0000e-06.
Test set: Average loss: 1.5364, Accuracy: 1637/5000 (33%)
[epoch 10] loss: 1.2636534
Epoch 9: reducing learning rate of group 0 to 5.0000e-07.
Test set: Average loss: 1.5354, Accuracy: 1638/5000 (33%)
[epoch 11] loss: 1.2335524
Test set: Average loss: 1.5353, Accuracy: 1638/5000 (33%)
[epoch 12] loss: 1.2243668
Test set: Average loss: 1.5352, Accuracy: 1638/5000 (33%)
[epoch 13] loss: 1.3058510
Epoch 12: reducing learning rate of group 0 to 5.0000e-08.
Test set: Average loss: 1.5351, Accuracy: 1638/5000 (33%)
[epoch 14] loss: 1.2336205
Epoch 13: reducing learning rate of group 0 to 5.0000e-09.
Test set: Average loss: 1.5351, Accuracy: 1639/5000 (33%)
[epoch 15] loss: 1.2783599
Epoch 14: reducing learning rate of group 0 to 5.0000e-10.
Test set: Average loss: 1.5351, Accuracy: 1639/5000 (33%)
[epoch 16] loss: 1.2705004
Epoch 15: reducing learning rate of group 0 to 5.0000e-11.
Test set: Average loss: 1.5351, Accuracy: 1639/5000 (33%)
[epoch 17] loss: 1.2751644
Epoch 16: reducing learning rate of group 0 to 5.0000e-12.
Test set: Average loss: 1.5351, Accuracy: 1639/5000 (33%)
[epoch 18] loss: 1.2833309
Epoch 17: reducing learning rate of group 0 to 5.0000e-13.
Test set: Average loss: 1.5351, Accuracy: 1639/5000 (33%)
[epoch 19] loss: 1.3209810
Epoch 18: reducing learning rate of group 0 to 5.0000e-14.
Test set: Average loss: 1.5351, Accuracy: 1639/5000 (33%)
[epoch 20] loss: 1.2194125
Test set: Average loss: 1.5351, Accuracy: 1639/5000 (33%)
[epoch 21] loss: 1.2825639
Epoch 20: reducing learning rate of group 0 to 5.0000e-15.
Test set: Average loss: 1.5351, Accuracy: 1639/5000 (33%)
[epoch 22] loss: 1.3177849
Epoch 21: reducing learning rate of group 0 to 5.0000e-16.
Test set: Average loss: 1.5351, Accuracy: 1639/5000 (33%)
[epoch 23] loss: 1.2452751
Epoch 22: reducing learning rate of group 0 to 5.0000e-17.
Test set: Average loss: 1.5351, Accuracy: 1639/5000 (33%)
[epoch 24] loss: 1.2832735
Epoch 23: reducing learning rate of group 0 to 5.0000e-18.
Test set: Average loss: 1.5351, Accuracy: 1639/5000 (33%)
[epoch 25] loss: 1.2932315
Epoch 24: reducing learning rate of group 0 to 5.0000e-19.
Test set: Average loss: 1.5351, Accuracy: 1639/5000 (33%)
Validation:
Test set: Average loss: 1.5351, Accuracy: 1639/5000 (33%)
Test
Test set: Average loss: 1.5358, Accuracy: 1565/5000 (31%)
Test set: Average loss: 1.2609, Accuracy: 61/100 (61%)
## seed: 13
Validation accuracy before training:
Test set: Average loss: 1.7753, Accuracy: 451/5000 (9%)
[epoch 1] loss: 1.7677090
Test set: Average loss: 1.7448, Accuracy: 485/5000 (10%)
[epoch 2] loss: 1.7270626
Test set: Average loss: 1.7147, Accuracy: 553/5000 (11%)
[epoch 3] loss: 1.6493487
Test set: Average loss: 1.6895, Accuracy: 675/5000 (14%)
[epoch 4] loss: 1.6308623
Test set: Average loss: 1.6673, Accuracy: 788/5000 (16%)
[epoch 5] loss: 1.5365649
Test set: Average loss: 1.6465, Accuracy: 920/5000 (18%)
[epoch 6] loss: 1.5040930
Test set: Average loss: 1.6283, Accuracy: 1014/5000 (20%)
[epoch 7] loss: 1.4725868
Test set: Average loss: 1.6124, Accuracy: 1109/5000 (22%)
[epoch 8] loss: 1.4224493
Test set: Average loss: 1.5973, Accuracy: 1207/5000 (24%)
[epoch 9] loss: 1.3324997
Test set: Average loss: 1.5843, Accuracy: 1293/5000 (26%)
[epoch 10] loss: 1.2841889
Test set: Average loss: 1.5729, Accuracy: 1347/5000 (27%)
[epoch 11] loss: 1.3320585
Epoch 10: reducing learning rate of group 0 to 5.0000e-06.
Test set: Average loss: 1.5625, Accuracy: 1390/5000 (28%)
[epoch 12] loss: 1.4289998
Epoch 11: reducing learning rate of group 0 to 5.0000e-07.
Test set: Average loss: 1.5614, Accuracy: 1392/5000 (28%)
[epoch 13] loss: 1.2896163
Epoch 12: reducing learning rate of group 0 to 5.0000e-08.
Test set: Average loss: 1.5613, Accuracy: 1392/5000 (28%)
[epoch 14] loss: 1.2947803
Epoch 13: reducing learning rate of group 0 to 5.0000e-09.
Test set: Average loss: 1.5613, Accuracy: 1392/5000 (28%)
[epoch 15] loss: 1.3549713
Epoch 14: reducing learning rate of group 0 to 5.0000e-10.
Test set: Average loss: 1.5613, Accuracy: 1392/5000 (28%)
[epoch 16] loss: 1.3135129
Epoch 15: reducing learning rate of group 0 to 5.0000e-11.
Test set: Average loss: 1.5613, Accuracy: 1392/5000 (28%)
[epoch 17] loss: 1.3059858
Epoch 16: reducing learning rate of group 0 to 5.0000e-12.
Test set: Average loss: 1.5613, Accuracy: 1392/5000 (28%)
[epoch 18] loss: 1.2418478
Test set: Average loss: 1.5613, Accuracy: 1392/5000 (28%)
[epoch 19] loss: 1.2800679
Epoch 18: reducing learning rate of group 0 to 5.0000e-13.
Test set: Average loss: 1.5613, Accuracy: 1392/5000 (28%)
[epoch 20] loss: 1.3098913
Epoch 19: reducing learning rate of group 0 to 5.0000e-14.
Test set: Average loss: 1.5613, Accuracy: 1392/5000 (28%)
[epoch 21] loss: 1.2914894
Epoch 20: reducing learning rate of group 0 to 5.0000e-15.
Test set: Average loss: 1.5613, Accuracy: 1392/5000 (28%)
[epoch 22] loss: 1.3518889
Epoch 21: reducing learning rate of group 0 to 5.0000e-16.
Test set: Average loss: 1.5613, Accuracy: 1392/5000 (28%)
[epoch 23] loss: 1.2619895
Epoch 22: reducing learning rate of group 0 to 5.0000e-17.
Test set: Average loss: 1.5613, Accuracy: 1392/5000 (28%)
[epoch 24] loss: 1.3032842
Epoch 23: reducing learning rate of group 0 to 5.0000e-18.
Test set: Average loss: 1.5613, Accuracy: 1392/5000 (28%)
[epoch 25] loss: 1.2748987
Epoch 24: reducing learning rate of group 0 to 5.0000e-19.
Test set: Average loss: 1.5613, Accuracy: 1392/5000 (28%)
Validation:
Test set: Average loss: 1.5613, Accuracy: 1392/5000 (28%)
Test
Test set: Average loss: 1.5653, Accuracy: 1405/5000 (28%)
Test set: Average loss: 1.2945, Accuracy: 58/100 (58%)
250
## seed: 11
Validation accuracy before training:
Test set: Average loss: 1.6176, Accuracy: 859/5000 (17%)
[epoch 1] loss: 1.6086760
Test set: Average loss: 1.5608, Accuracy: 1145/5000 (23%)
[epoch 2] loss: 1.5167297
Test set: Average loss: 1.5241, Accuracy: 1338/5000 (27%)
[epoch 3] loss: 1.4562386
Test set: Average loss: 1.4948, Accuracy: 1470/5000 (29%)
[epoch 4] loss: 1.4025147
Test set: Average loss: 1.4726, Accuracy: 1560/5000 (31%)
[epoch 5] loss: 1.3562697
Test set: Average loss: 1.4536, Accuracy: 1638/5000 (33%)
[epoch 6] loss: 1.3175423
Test set: Average loss: 1.4370, Accuracy: 1720/5000 (34%)
[epoch 7] loss: 1.2827758
Test set: Average loss: 1.4227, Accuracy: 1781/5000 (36%)
[epoch 8] loss: 1.2521236
Test set: Average loss: 1.4106, Accuracy: 1827/5000 (37%)
[epoch 9] loss: 1.2207855
Test set: Average loss: 1.3995, Accuracy: 1870/5000 (37%)
[epoch 10] loss: 1.1932963
Test set: Average loss: 1.3902, Accuracy: 1901/5000 (38%)
[epoch 11] loss: 1.1690687
Test set: Average loss: 1.3814, Accuracy: 1946/5000 (39%)
[epoch 12] loss: 1.1474910
Test set: Average loss: 1.3734, Accuracy: 1981/5000 (40%)
[epoch 13] loss: 1.1188541
Test set: Average loss: 1.3663, Accuracy: 2006/5000 (40%)
[epoch 14] loss: 1.1027660
Test set: Average loss: 1.3596, Accuracy: 2046/5000 (41%)
[epoch 15] loss: 1.0806305
Test set: Average loss: 1.3526, Accuracy: 2091/5000 (42%)
[epoch 16] loss: 1.0631662
Test set: Average loss: 1.3463, Accuracy: 2116/5000 (42%)
[epoch 17] loss: 1.0432217
Test set: Average loss: 1.3413, Accuracy: 2129/5000 (43%)
[epoch 18] loss: 1.0275761
Test set: Average loss: 1.3363, Accuracy: 2156/5000 (43%)
[epoch 19] loss: 1.0088066
Test set: Average loss: 1.3313, Accuracy: 2194/5000 (44%)
[epoch 20] loss: 0.9929388
Test set: Average loss: 1.3274, Accuracy: 2213/5000 (44%)
[epoch 21] loss: 0.9742745
Test set: Average loss: 1.3226, Accuracy: 2243/5000 (45%)
[epoch 22] loss: 0.9628151
Test set: Average loss: 1.3182, Accuracy: 2272/5000 (45%)
[epoch 23] loss: 0.9457567
Test set: Average loss: 1.3149, Accuracy: 2274/5000 (45%)
[epoch 24] loss: 0.9296797
Test set: Average loss: 1.3107, Accuracy: 2283/5000 (46%)
[epoch 25] loss: 0.9201722
Test set: Average loss: 1.3062, Accuracy: 2313/5000 (46%)
Validation:
Test set: Average loss: 1.3062, Accuracy: 2313/5000 (46%)
Test
Test set: Average loss: 1.3114, Accuracy: 2256/5000 (45%)
Test set: Average loss: 0.9066, Accuracy: 209/250 (84%)
## seed: 12
Validation accuracy before training:
Test set: Average loss: 1.7111, Accuracy: 763/5000 (15%)
[epoch 1] loss: 1.6903770
Test set: Average loss: 1.6398, Accuracy: 955/5000 (19%)
[epoch 2] loss: 1.5668156
Test set: Average loss: 1.5878, Accuracy: 1261/5000 (25%)
[epoch 3] loss: 1.4849781
Test set: Average loss: 1.5465, Accuracy: 1484/5000 (30%)
[epoch 4] loss: 1.4106850
Test set: Average loss: 1.5101, Accuracy: 1710/5000 (34%)
[epoch 5] loss: 1.3486179
Test set: Average loss: 1.4810, Accuracy: 1824/5000 (36%)
[epoch 6] loss: 1.3025338
Test set: Average loss: 1.4577, Accuracy: 1902/5000 (38%)
[epoch 7] loss: 1.2509178
Test set: Average loss: 1.4387, Accuracy: 1960/5000 (39%)
[epoch 8] loss: 1.2099904
Test set: Average loss: 1.4241, Accuracy: 2023/5000 (40%)
[epoch 9] loss: 1.1688912
Test set: Average loss: 1.4096, Accuracy: 2083/5000 (42%)
[epoch 10] loss: 1.1351455
Test set: Average loss: 1.3953, Accuracy: 2134/5000 (43%)
[epoch 11] loss: 1.0982242
Test set: Average loss: 1.3832, Accuracy: 2175/5000 (44%)
[epoch 12] loss: 1.0662308
Test set: Average loss: 1.3709, Accuracy: 2227/5000 (45%)
[epoch 13] loss: 1.0363023
Test set: Average loss: 1.3604, Accuracy: 2255/5000 (45%)
[epoch 14] loss: 1.0104707
Test set: Average loss: 1.3524, Accuracy: 2286/5000 (46%)
[epoch 15] loss: 0.9832129
Test set: Average loss: 1.3441, Accuracy: 2314/5000 (46%)
[epoch 16] loss: 0.9560276
Test set: Average loss: 1.3350, Accuracy: 2347/5000 (47%)
[epoch 17] loss: 0.9326734
Test set: Average loss: 1.3273, Accuracy: 2369/5000 (47%)
[epoch 18] loss: 0.9122461
Test set: Average loss: 1.3204, Accuracy: 2385/5000 (48%)
[epoch 19] loss: 0.8881200
Test set: Average loss: 1.3133, Accuracy: 2409/5000 (48%)
[epoch 20] loss: 0.8682882
Test set: Average loss: 1.3075, Accuracy: 2434/5000 (49%)
[epoch 21] loss: 0.8473020
Test set: Average loss: 1.3003, Accuracy: 2462/5000 (49%)
[epoch 22] loss: 0.8301712
Test set: Average loss: 1.2949, Accuracy: 2473/5000 (49%)
[epoch 23] loss: 0.8100605
Test set: Average loss: 1.2891, Accuracy: 2479/5000 (50%)
[epoch 24] loss: 0.7902423
Test set: Average loss: 1.2834, Accuracy: 2495/5000 (50%)
[epoch 25] loss: 0.7731488
Test set: Average loss: 1.2782, Accuracy: 2513/5000 (50%)
Validation:
Test set: Average loss: 1.2782, Accuracy: 2513/5000 (50%)
Test
Test set: Average loss: 1.2703, Accuracy: 2486/5000 (50%)
Test set: Average loss: 0.7626, Accuracy: 241/250 (96%)
## seed: 13
Validation accuracy before training:
Test set: Average loss: 1.8074, Accuracy: 681/5000 (14%)
[epoch 1] loss: 1.8245020
Test set: Average loss: 1.7216, Accuracy: 861/5000 (17%)
[epoch 2] loss: 1.6898135
Test set: Average loss: 1.6485, Accuracy: 1084/5000 (22%)
[epoch 3] loss: 1.5861772
Test set: Average loss: 1.5915, Accuracy: 1277/5000 (26%)
[epoch 4] loss: 1.5072382
Test set: Average loss: 1.5456, Accuracy: 1425/5000 (28%)
[epoch 5] loss: 1.4351680
Test set: Average loss: 1.5100, Accuracy: 1549/5000 (31%)
[epoch 6] loss: 1.3783488
Test set: Average loss: 1.4806, Accuracy: 1656/5000 (33%)
[epoch 7] loss: 1.3265168
Test set: Average loss: 1.4574, Accuracy: 1748/5000 (35%)
[epoch 8] loss: 1.2803962
Test set: Average loss: 1.4385, Accuracy: 1816/5000 (36%)
[epoch 9] loss: 1.2385208
Test set: Average loss: 1.4228, Accuracy: 1902/5000 (38%)
[epoch 10] loss: 1.2016875
Test set: Average loss: 1.4097, Accuracy: 1960/5000 (39%)
[epoch 11] loss: 1.1694243
Test set: Average loss: 1.3973, Accuracy: 2022/5000 (40%)
[epoch 12] loss: 1.1366533
Test set: Average loss: 1.3860, Accuracy: 2066/5000 (41%)
[epoch 13] loss: 1.1156097
Test set: Average loss: 1.3761, Accuracy: 2123/5000 (42%)
[epoch 14] loss: 1.0838120
Test set: Average loss: 1.3684, Accuracy: 2166/5000 (43%)
[epoch 15] loss: 1.0567544
Test set: Average loss: 1.3605, Accuracy: 2198/5000 (44%)
[epoch 16] loss: 1.0343997
Test set: Average loss: 1.3528, Accuracy: 2238/5000 (45%)
[epoch 17] loss: 1.0154085
Test set: Average loss: 1.3455, Accuracy: 2280/5000 (46%)
[epoch 18] loss: 0.9945245
Test set: Average loss: 1.3387, Accuracy: 2303/5000 (46%)
[epoch 19] loss: 0.9725429
Test set: Average loss: 1.3333, Accuracy: 2347/5000 (47%)
[epoch 20] loss: 0.9575295
Test set: Average loss: 1.3277, Accuracy: 2356/5000 (47%)
[epoch 21] loss: 0.9366731
Test set: Average loss: 1.3227, Accuracy: 2370/5000 (47%)
[epoch 22] loss: 0.9189128
Test set: Average loss: 1.3174, Accuracy: 2386/5000 (48%)
[epoch 23] loss: 0.9033766
Test set: Average loss: 1.3128, Accuracy: 2419/5000 (48%)
[epoch 24] loss: 0.8893216
Test set: Average loss: 1.3085, Accuracy: 2446/5000 (49%)
[epoch 25] loss: 0.8720024
Test set: Average loss: 1.3051, Accuracy: 2472/5000 (49%)
Validation:
Test set: Average loss: 1.3051, Accuracy: 2472/5000 (49%)
Test
Test set: Average loss: 1.3096, Accuracy: 2435/5000 (49%)
Test set: Average loss: 0.8613, Accuracy: 225/250 (90%)
500
## seed: 11
Validation accuracy before training:
Test set: Average loss: 1.6579, Accuracy: 953/5000 (19%)
[epoch 1] loss: 1.6137608
Test set: Average loss: 1.5412, Accuracy: 1570/5000 (31%)
[epoch 2] loss: 1.4910952
Test set: Average loss: 1.4748, Accuracy: 1901/5000 (38%)
[epoch 3] loss: 1.4133324
Test set: Average loss: 1.4325, Accuracy: 2061/5000 (41%)
[epoch 4] loss: 1.3551549
Test set: Average loss: 1.4017, Accuracy: 2192/5000 (44%)
[epoch 5] loss: 1.3078036
Test set: Average loss: 1.3760, Accuracy: 2293/5000 (46%)
[epoch 6] loss: 1.2618901
Test set: Average loss: 1.3551, Accuracy: 2378/5000 (48%)
[epoch 7] loss: 1.2221990
Test set: Average loss: 1.3380, Accuracy: 2428/5000 (49%)
[epoch 8] loss: 1.1846443
Test set: Average loss: 1.3222, Accuracy: 2485/5000 (50%)
[epoch 9] loss: 1.1552085
Test set: Average loss: 1.3088, Accuracy: 2530/5000 (51%)
[epoch 10] loss: 1.1245483
Test set: Average loss: 1.2966, Accuracy: 2548/5000 (51%)
[epoch 11] loss: 1.0953896
Test set: Average loss: 1.2861, Accuracy: 2588/5000 (52%)
[epoch 12] loss: 1.0652765
Test set: Average loss: 1.2750, Accuracy: 2641/5000 (53%)
[epoch 13] loss: 1.0446754
Test set: Average loss: 1.2653, Accuracy: 2679/5000 (54%)
[epoch 14] loss: 1.0177322
Test set: Average loss: 1.2567, Accuracy: 2687/5000 (54%)
[epoch 15] loss: 0.9986088
Test set: Average loss: 1.2480, Accuracy: 2706/5000 (54%)
[epoch 16] loss: 0.9741673
Test set: Average loss: 1.2418, Accuracy: 2728/5000 (55%)
[epoch 17] loss: 0.9523979
Test set: Average loss: 1.2333, Accuracy: 2765/5000 (55%)
[epoch 18] loss: 0.9331939
Test set: Average loss: 1.2284, Accuracy: 2759/5000 (55%)
[epoch 19] loss: 0.9104267
Test set: Average loss: 1.2223, Accuracy: 2774/5000 (55%)
[epoch 20] loss: 0.8928541
Test set: Average loss: 1.2147, Accuracy: 2791/5000 (56%)
[epoch 21] loss: 0.8718000
Test set: Average loss: 1.2110, Accuracy: 2811/5000 (56%)
[epoch 22] loss: 0.8551266
Test set: Average loss: 1.2047, Accuracy: 2816/5000 (56%)
[epoch 23] loss: 0.8376797
Test set: Average loss: 1.1986, Accuracy: 2817/5000 (56%)
[epoch 24] loss: 0.8181472
Test set: Average loss: 1.1940, Accuracy: 2820/5000 (56%)
[epoch 25] loss: 0.8000663
Test set: Average loss: 1.1908, Accuracy: 2825/5000 (56%)
Validation:
Test set: Average loss: 1.1908, Accuracy: 2825/5000 (56%)
Test
Test set: Average loss: 1.1985, Accuracy: 2817/5000 (56%)
Test set: Average loss: 0.7878, Accuracy: 441/500 (88%)
## seed: 12
Validation accuracy before training:
Test set: Average loss: 1.5609, Accuracy: 1551/5000 (31%)
[epoch 1] loss: 1.5042261
Test set: Average loss: 1.4809, Accuracy: 1861/5000 (37%)
[epoch 2] loss: 1.4000774
Test set: Average loss: 1.4272, Accuracy: 2101/5000 (42%)
[epoch 3] loss: 1.3310503
Test set: Average loss: 1.3920, Accuracy: 2220/5000 (44%)
[epoch 4] loss: 1.2724177
Test set: Average loss: 1.3629, Accuracy: 2335/5000 (47%)
[epoch 5] loss: 1.2223995
Test set: Average loss: 1.3395, Accuracy: 2422/5000 (48%)
[epoch 6] loss: 1.1782450
Test set: Average loss: 1.3197, Accuracy: 2495/5000 (50%)
[epoch 7] loss: 1.1417896
Test set: Average loss: 1.3012, Accuracy: 2550/5000 (51%)
[epoch 8] loss: 1.1109660
Test set: Average loss: 1.2869, Accuracy: 2604/5000 (52%)
[epoch 9] loss: 1.0785965
Test set: Average loss: 1.2725, Accuracy: 2644/5000 (53%)
[epoch 10] loss: 1.0515895
Test set: Average loss: 1.2621, Accuracy: 2658/5000 (53%)
[epoch 11] loss: 1.0221789
Test set: Average loss: 1.2498, Accuracy: 2685/5000 (54%)
[epoch 12] loss: 0.9982113
Test set: Average loss: 1.2385, Accuracy: 2703/5000 (54%)
[epoch 13] loss: 0.9744772
Test set: Average loss: 1.2308, Accuracy: 2709/5000 (54%)
[epoch 14] loss: 0.9518482
Test set: Average loss: 1.2218, Accuracy: 2730/5000 (55%)
[epoch 15] loss: 0.9287118
Test set: Average loss: 1.2135, Accuracy: 2753/5000 (55%)
[epoch 16] loss: 0.9079948
Test set: Average loss: 1.2068, Accuracy: 2766/5000 (55%)
[epoch 17] loss: 0.8870468
Test set: Average loss: 1.1977, Accuracy: 2802/5000 (56%)
[epoch 18] loss: 0.8667931
Test set: Average loss: 1.1919, Accuracy: 2794/5000 (56%)
[epoch 19] loss: 0.8430117
Test set: Average loss: 1.1862, Accuracy: 2810/5000 (56%)
[epoch 20] loss: 0.8275644
Test set: Average loss: 1.1789, Accuracy: 2817/5000 (56%)
[epoch 21] loss: 0.8087034
Test set: Average loss: 1.1758, Accuracy: 2818/5000 (56%)
[epoch 22] loss: 0.7870196
Test set: Average loss: 1.1683, Accuracy: 2840/5000 (57%)
[epoch 23] loss: 0.7730764
Test set: Average loss: 1.1640, Accuracy: 2842/5000 (57%)
[epoch 24] loss: 0.7575935
Test set: Average loss: 1.1581, Accuracy: 2846/5000 (57%)
[epoch 25] loss: 0.7407126
Test set: Average loss: 1.1552, Accuracy: 2850/5000 (57%)
Validation:
Test set: Average loss: 1.1552, Accuracy: 2850/5000 (57%)
Test
Test set: Average loss: 1.1628, Accuracy: 2821/5000 (56%)
Test set: Average loss: 0.7276, Accuracy: 456/500 (91%)
## seed: 13
Validation accuracy before training:
Test set: Average loss: 1.5612, Accuracy: 1628/5000 (33%)
[epoch 1] loss: 1.5098924
Test set: Average loss: 1.4818, Accuracy: 1931/5000 (39%)
[epoch 2] loss: 1.3942941
Test set: Average loss: 1.4273, Accuracy: 2061/5000 (41%)
[epoch 3] loss: 1.3191978
Test set: Average loss: 1.3891, Accuracy: 2142/5000 (43%)
[epoch 4] loss: 1.2608432
Test set: Average loss: 1.3643, Accuracy: 2191/5000 (44%)
[epoch 5] loss: 1.2114337
Test set: Average loss: 1.3387, Accuracy: 2271/5000 (45%)
[epoch 6] loss: 1.1707768
Test set: Average loss: 1.3226, Accuracy: 2302/5000 (46%)
[epoch 7] loss: 1.1368058
Test set: Average loss: 1.3076, Accuracy: 2342/5000 (47%)
[epoch 8] loss: 1.1049710
Test set: Average loss: 1.2941, Accuracy: 2391/5000 (48%)
[epoch 9] loss: 1.0747948
Test set: Average loss: 1.2856, Accuracy: 2417/5000 (48%)
[epoch 10] loss: 1.0508233
Test set: Average loss: 1.2741, Accuracy: 2448/5000 (49%)
[epoch 11] loss: 1.0258889
Test set: Average loss: 1.2649, Accuracy: 2478/5000 (50%)
[epoch 12] loss: 1.0022323
Test set: Average loss: 1.2570, Accuracy: 2482/5000 (50%)
[epoch 13] loss: 0.9767391
Test set: Average loss: 1.2506, Accuracy: 2497/5000 (50%)
[epoch 14] loss: 0.9607305
Test set: Average loss: 1.2419, Accuracy: 2531/5000 (51%)
[epoch 15] loss: 0.9330939
Test set: Average loss: 1.2359, Accuracy: 2556/5000 (51%)
[epoch 16] loss: 0.9123998
Test set: Average loss: 1.2288, Accuracy: 2585/5000 (52%)
[epoch 17] loss: 0.8954769
Test set: Average loss: 1.2237, Accuracy: 2593/5000 (52%)
[epoch 18] loss: 0.8769672
Test set: Average loss: 1.2176, Accuracy: 2617/5000 (52%)
[epoch 19] loss: 0.8606950
Test set: Average loss: 1.2132, Accuracy: 2639/5000 (53%)
[epoch 20] loss: 0.8442857
Test set: Average loss: 1.2088, Accuracy: 2638/5000 (53%)
[epoch 21] loss: 0.8280836
Test set: Average loss: 1.2049, Accuracy: 2654/5000 (53%)
[epoch 22] loss: 0.8063373
Test set: Average loss: 1.2002, Accuracy: 2668/5000 (53%)
[epoch 23] loss: 0.7926903
Test set: Average loss: 1.1952, Accuracy: 2693/5000 (54%)
[epoch 24] loss: 0.7774838
Test set: Average loss: 1.1921, Accuracy: 2691/5000 (54%)
[epoch 25] loss: 0.7605368
Test set: Average loss: 1.1894, Accuracy: 2712/5000 (54%)
Validation:
Test set: Average loss: 1.1894, Accuracy: 2712/5000 (54%)
Test
Test set: Average loss: 1.2009, Accuracy: 2704/5000 (54%)
Test set: Average loss: 0.7490, Accuracy: 434/500 (87%)
750
## seed: 11
Validation accuracy before training:
Test set: Average loss: 1.7269, Accuracy: 578/5000 (12%)
[epoch 1] loss: 1.6407893
Test set: Average loss: 1.5522, Accuracy: 1488/5000 (30%)
[epoch 2] loss: 1.4680503
Test set: Average loss: 1.4611, Accuracy: 1944/5000 (39%)
[epoch 3] loss: 1.3719015
Test set: Average loss: 1.4106, Accuracy: 2141/5000 (43%)
[epoch 4] loss: 1.3039133
Test set: Average loss: 1.3732, Accuracy: 2330/5000 (47%)
[epoch 5] loss: 1.2566123
Test set: Average loss: 1.3467, Accuracy: 2415/5000 (48%)
[epoch 6] loss: 1.2051266
Test set: Average loss: 1.3236, Accuracy: 2477/5000 (50%)
[epoch 7] loss: 1.1695546
Test set: Average loss: 1.3036, Accuracy: 2543/5000 (51%)
[epoch 8] loss: 1.1300681
Test set: Average loss: 1.2859, Accuracy: 2613/5000 (52%)
[epoch 9] loss: 1.1023655
Test set: Average loss: 1.2708, Accuracy: 2665/5000 (53%)
[epoch 10] loss: 1.0717029
Test set: Average loss: 1.2570, Accuracy: 2712/5000 (54%)
[epoch 11] loss: 1.0397943
Test set: Average loss: 1.2446, Accuracy: 2732/5000 (55%)
[epoch 12] loss: 1.0134373
Test set: Average loss: 1.2337, Accuracy: 2756/5000 (55%)
[epoch 13] loss: 0.9888987
Test set: Average loss: 1.2230, Accuracy: 2786/5000 (56%)
[epoch 14] loss: 0.9631636
Test set: Average loss: 1.2135, Accuracy: 2805/5000 (56%)
[epoch 15] loss: 0.9464258
Test set: Average loss: 1.2049, Accuracy: 2828/5000 (57%)
[epoch 16] loss: 0.9171441
Test set: Average loss: 1.1975, Accuracy: 2844/5000 (57%)
[epoch 17] loss: 0.8944302
Test set: Average loss: 1.1888, Accuracy: 2863/5000 (57%)
[epoch 18] loss: 0.8717617
Test set: Average loss: 1.1824, Accuracy: 2870/5000 (57%)
[epoch 19] loss: 0.8539883
Test set: Average loss: 1.1761, Accuracy: 2878/5000 (58%)
[epoch 20] loss: 0.8364252
Test set: Average loss: 1.1701, Accuracy: 2891/5000 (58%)
[epoch 21] loss: 0.8125123
Test set: Average loss: 1.1650, Accuracy: 2890/5000 (58%)
[epoch 22] loss: 0.7983761
Test set: Average loss: 1.1598, Accuracy: 2903/5000 (58%)
[epoch 23] loss: 0.7791285
Test set: Average loss: 1.1541, Accuracy: 2908/5000 (58%)
[epoch 24] loss: 0.7603658
Test set: Average loss: 1.1499, Accuracy: 2927/5000 (59%)
[epoch 25] loss: 0.7461860
Test set: Average loss: 1.1448, Accuracy: 2931/5000 (59%)
Validation:
Test set: Average loss: 1.1448, Accuracy: 2931/5000 (59%)
Test
Test set: Average loss: 1.1492, Accuracy: 2901/5000 (58%)
Test set: Average loss: 0.7293, Accuracy: 645/750 (86%)
## seed: 12
Validation accuracy before training:
Test set: Average loss: 1.7097, Accuracy: 833/5000 (17%)
[epoch 1] loss: 1.6460752
Test set: Average loss: 1.5589, Accuracy: 1496/5000 (30%)
[epoch 2] loss: 1.4921932
Test set: Average loss: 1.4739, Accuracy: 1935/5000 (39%)
[epoch 3] loss: 1.4013716
Test set: Average loss: 1.4241, Accuracy: 2151/5000 (43%)
[epoch 4] loss: 1.3330998
Test set: Average loss: 1.3908, Accuracy: 2288/5000 (46%)
[epoch 5] loss: 1.2799962
Test set: Average loss: 1.3594, Accuracy: 2414/5000 (48%)
[epoch 6] loss: 1.2388290
Test set: Average loss: 1.3363, Accuracy: 2485/5000 (50%)
[epoch 7] loss: 1.1939187
Test set: Average loss: 1.3164, Accuracy: 2562/5000 (51%)
[epoch 8] loss: 1.1606200
Test set: Average loss: 1.2974, Accuracy: 2615/5000 (52%)
[epoch 9] loss: 1.1265086
Test set: Average loss: 1.2851, Accuracy: 2661/5000 (53%)
[epoch 10] loss: 1.0941323
Test set: Average loss: 1.2698, Accuracy: 2715/5000 (54%)
[epoch 11] loss: 1.0630501
Test set: Average loss: 1.2570, Accuracy: 2766/5000 (55%)
[epoch 12] loss: 1.0368677
Test set: Average loss: 1.2473, Accuracy: 2798/5000 (56%)
[epoch 13] loss: 1.0074058
Test set: Average loss: 1.2355, Accuracy: 2827/5000 (57%)
[epoch 14] loss: 0.9845469
Test set: Average loss: 1.2272, Accuracy: 2849/5000 (57%)
[epoch 15] loss: 0.9642711
Test set: Average loss: 1.2176, Accuracy: 2864/5000 (57%)
[epoch 16] loss: 0.9422160
Test set: Average loss: 1.2096, Accuracy: 2887/5000 (58%)
[epoch 17] loss: 0.9173881
Test set: Average loss: 1.2014, Accuracy: 2906/5000 (58%)
[epoch 18] loss: 0.8884642
Test set: Average loss: 1.1950, Accuracy: 2898/5000 (58%)
[epoch 19] loss: 0.8696215
Test set: Average loss: 1.1855, Accuracy: 2918/5000 (58%)
[epoch 20] loss: 0.8464386
Test set: Average loss: 1.1806, Accuracy: 2915/5000 (58%)
[epoch 21] loss: 0.8284626
Test set: Average loss: 1.1719, Accuracy: 2925/5000 (58%)
[epoch 22] loss: 0.8083063
Test set: Average loss: 1.1700, Accuracy: 2922/5000 (58%)
[epoch 23] loss: 0.7918693
Test set: Average loss: 1.1619, Accuracy: 2933/5000 (59%)
[epoch 24] loss: 0.7716722
Test set: Average loss: 1.1563, Accuracy: 2936/5000 (59%)
[epoch 25] loss: 0.7509504
Test set: Average loss: 1.1533, Accuracy: 2944/5000 (59%)
Validation:
Test set: Average loss: 1.1533, Accuracy: 2944/5000 (59%)
Test
Test set: Average loss: 1.1562, Accuracy: 2906/5000 (58%)
Test set: Average loss: 0.7340, Accuracy: 665/750 (89%)
## seed: 13
Validation accuracy before training:
Test set: Average loss: 1.5971, Accuracy: 1476/5000 (30%)
[epoch 1] loss: 1.5420428
Test set: Average loss: 1.4822, Accuracy: 1981/5000 (40%)
[epoch 2] loss: 1.4121308
Test set: Average loss: 1.4136, Accuracy: 2294/5000 (46%)
[epoch 3] loss: 1.3292714
Test set: Average loss: 1.3665, Accuracy: 2473/5000 (49%)
[epoch 4] loss: 1.2665411
Test set: Average loss: 1.3343, Accuracy: 2585/5000 (52%)
[epoch 5] loss: 1.2182489
Test set: Average loss: 1.3099, Accuracy: 2629/5000 (53%)
[epoch 6] loss: 1.1771183
Test set: Average loss: 1.2895, Accuracy: 2679/5000 (54%)
[epoch 7] loss: 1.1443575
Test set: Average loss: 1.2725, Accuracy: 2715/5000 (54%)
[epoch 8] loss: 1.1038877
Test set: Average loss: 1.2578, Accuracy: 2755/5000 (55%)
[epoch 9] loss: 1.0774354
Test set: Average loss: 1.2445, Accuracy: 2751/5000 (55%)
[epoch 10] loss: 1.0479271
Test set: Average loss: 1.2335, Accuracy: 2785/5000 (56%)
[epoch 11] loss: 1.0237244
Test set: Average loss: 1.2225, Accuracy: 2807/5000 (56%)
[epoch 12] loss: 0.9945496
Test set: Average loss: 1.2133, Accuracy: 2815/5000 (56%)
[epoch 13] loss: 0.9720806
Test set: Average loss: 1.2046, Accuracy: 2831/5000 (57%)
[epoch 14] loss: 0.9531251
Test set: Average loss: 1.1971, Accuracy: 2846/5000 (57%)
[epoch 15] loss: 0.9258876
Test set: Average loss: 1.1907, Accuracy: 2854/5000 (57%)
[epoch 16] loss: 0.9081316
Test set: Average loss: 1.1848, Accuracy: 2860/5000 (57%)
[epoch 17] loss: 0.8942609
Test set: Average loss: 1.1782, Accuracy: 2859/5000 (57%)
[epoch 18] loss: 0.8649716
Test set: Average loss: 1.1720, Accuracy: 2871/5000 (57%)
[epoch 19] loss: 0.8523309
Test set: Average loss: 1.1678, Accuracy: 2868/5000 (57%)
[epoch 20] loss: 0.8279478
Test set: Average loss: 1.1623, Accuracy: 2894/5000 (58%)
[epoch 21] loss: 0.8090924
Test set: Average loss: 1.1571, Accuracy: 2905/5000 (58%)
[epoch 22] loss: 0.7903681
Test set: Average loss: 1.1528, Accuracy: 2904/5000 (58%)
[epoch 23] loss: 0.7814491
Test set: Average loss: 1.1493, Accuracy: 2903/5000 (58%)
[epoch 24] loss: 0.7567246
Test set: Average loss: 1.1446, Accuracy: 2913/5000 (58%)
[epoch 25] loss: 0.7407270
Test set: Average loss: 1.1394, Accuracy: 2914/5000 (58%)
Validation:
Test set: Average loss: 1.1394, Accuracy: 2914/5000 (58%)
Test
Test set: Average loss: 1.1505, Accuracy: 2885/5000 (58%)
Test set: Average loss: 0.7273, Accuracy: 665/750 (89%)
1000
## seed: 11
Validation accuracy before training:
Test set: Average loss: 1.5922, Accuracy: 1502/5000 (30%)
[epoch 1] loss: 1.4733036
Test set: Average loss: 1.4151, Accuracy: 2232/5000 (45%)
[epoch 2] loss: 1.3294633
Test set: Average loss: 1.3505, Accuracy: 2458/5000 (49%)
[epoch 3] loss: 1.2630079
Test set: Average loss: 1.3107, Accuracy: 2611/5000 (52%)
[epoch 4] loss: 1.1994336
Test set: Average loss: 1.2825, Accuracy: 2713/5000 (54%)
[epoch 5] loss: 1.1625518
Test set: Average loss: 1.2593, Accuracy: 2783/5000 (56%)
[epoch 6] loss: 1.1162140
Test set: Average loss: 1.2399, Accuracy: 2835/5000 (57%)
[epoch 7] loss: 1.0845688
Test set: Average loss: 1.2242, Accuracy: 2873/5000 (57%)
[epoch 8] loss: 1.0500920
Test set: Average loss: 1.2089, Accuracy: 2884/5000 (58%)
[epoch 9] loss: 1.0180848
Test set: Average loss: 1.1996, Accuracy: 2900/5000 (58%)
[epoch 10] loss: 0.9925252
Test set: Average loss: 1.1862, Accuracy: 2932/5000 (59%)
[epoch 11] loss: 0.9669303
Test set: Average loss: 1.1754, Accuracy: 2951/5000 (59%)
[epoch 12] loss: 0.9365805
Test set: Average loss: 1.1660, Accuracy: 2954/5000 (59%)
[epoch 13] loss: 0.9153718
Test set: Average loss: 1.1579, Accuracy: 2960/5000 (59%)
[epoch 14] loss: 0.8892857
Test set: Average loss: 1.1522, Accuracy: 2963/5000 (59%)
[epoch 15] loss: 0.8712716
Test set: Average loss: 1.1453, Accuracy: 2972/5000 (59%)
[epoch 16] loss: 0.8508044
Test set: Average loss: 1.1380, Accuracy: 2981/5000 (60%)
[epoch 17] loss: 0.8253328
Test set: Average loss: 1.1321, Accuracy: 2985/5000 (60%)
[epoch 18] loss: 0.8125533
Test set: Average loss: 1.1270, Accuracy: 2994/5000 (60%)
[epoch 19] loss: 0.7897955
Test set: Average loss: 1.1225, Accuracy: 2997/5000 (60%)
[epoch 20] loss: 0.7688058
Test set: Average loss: 1.1161, Accuracy: 2997/5000 (60%)
[epoch 21] loss: 0.7473308
Test set: Average loss: 1.1124, Accuracy: 3010/5000 (60%)
[epoch 22] loss: 0.7320824
Test set: Average loss: 1.1083, Accuracy: 3008/5000 (60%)
[epoch 23] loss: 0.7092002
Test set: Average loss: 1.1031, Accuracy: 3004/5000 (60%)
[epoch 24] loss: 0.6897678
Test set: Average loss: 1.1005, Accuracy: 3003/5000 (60%)
[epoch 25] loss: 0.6734428
Test set: Average loss: 1.0967, Accuracy: 2997/5000 (60%)
Validation:
Test set: Average loss: 1.1124, Accuracy: 3010/5000 (60%)
Test
Test set: Average loss: 1.1183, Accuracy: 2918/5000 (58%)
Test set: Average loss: 0.7288, Accuracy: 849/1000 (85%)
## seed: 12
Validation accuracy before training:
Test set: Average loss: 1.6133, Accuracy: 1359/5000 (27%)
[epoch 1] loss: 1.5127091
Test set: Average loss: 1.4473, Accuracy: 2122/5000 (42%)
[epoch 2] loss: 1.3754316
Test set: Average loss: 1.3752, Accuracy: 2396/5000 (48%)
[epoch 3] loss: 1.2978229
Test set: Average loss: 1.3304, Accuracy: 2588/5000 (52%)
[epoch 4] loss: 1.2446890
Test set: Average loss: 1.2979, Accuracy: 2680/5000 (54%)
[epoch 5] loss: 1.1941707
Test set: Average loss: 1.2720, Accuracy: 2762/5000 (55%)
[epoch 6] loss: 1.1489310
Test set: Average loss: 1.2523, Accuracy: 2804/5000 (56%)
[epoch 7] loss: 1.1146296
Test set: Average loss: 1.2341, Accuracy: 2865/5000 (57%)
[epoch 8] loss: 1.0875629
Test set: Average loss: 1.2180, Accuracy: 2906/5000 (58%)
[epoch 9] loss: 1.0542448
Test set: Average loss: 1.2030, Accuracy: 2950/5000 (59%)
[epoch 10] loss: 1.0195186
Test set: Average loss: 1.1908, Accuracy: 2966/5000 (59%)
[epoch 11] loss: 0.9947431
Test set: Average loss: 1.1800, Accuracy: 2975/5000 (60%)
[epoch 12] loss: 0.9689699
Test set: Average loss: 1.1658, Accuracy: 3016/5000 (60%)
[epoch 13] loss: 0.9478157
Test set: Average loss: 1.1577, Accuracy: 3021/5000 (60%)
[epoch 14] loss: 0.9228339
Test set: Average loss: 1.1473, Accuracy: 3049/5000 (61%)
[epoch 15] loss: 0.9013866
Test set: Average loss: 1.1424, Accuracy: 3035/5000 (61%)
[epoch 16] loss: 0.8756515
Test set: Average loss: 1.1345, Accuracy: 3037/5000 (61%)
[epoch 17] loss: 0.8524430
Test set: Average loss: 1.1226, Accuracy: 3065/5000 (61%)
[epoch 18] loss: 0.8355065
Test set: Average loss: 1.1187, Accuracy: 3069/5000 (61%)
[epoch 19] loss: 0.8124262
Test set: Average loss: 1.1136, Accuracy: 3076/5000 (62%)
[epoch 20] loss: 0.7876172
Test set: Average loss: 1.1069, Accuracy: 3069/5000 (61%)
[epoch 21] loss: 0.7783512
Test set: Average loss: 1.0995, Accuracy: 3090/5000 (62%)
[epoch 22] loss: 0.7542203
Test set: Average loss: 1.0927, Accuracy: 3095/5000 (62%)
[epoch 23] loss: 0.7304921
Test set: Average loss: 1.0882, Accuracy: 3106/5000 (62%)
[epoch 24] loss: 0.7133204
Test set: Average loss: 1.0845, Accuracy: 3097/5000 (62%)
[epoch 25] loss: 0.6938756
Test set: Average loss: 1.0764, Accuracy: 3120/5000 (62%)
Validation:
Test set: Average loss: 1.0764, Accuracy: 3120/5000 (62%)
Test
Test set: Average loss: 1.0917, Accuracy: 3015/5000 (60%)
Test set: Average loss: 0.6780, Accuracy: 896/1000 (90%)
## seed: 13
Validation accuracy before training:
Test set: Average loss: 1.5682, Accuracy: 1439/5000 (29%)
[epoch 1] loss: 1.4693941
Test set: Average loss: 1.4163, Accuracy: 2094/5000 (42%)
[epoch 2] loss: 1.3337210
Test set: Average loss: 1.3465, Accuracy: 2414/5000 (48%)
[epoch 3] loss: 1.2556343
Test set: Average loss: 1.3038, Accuracy: 2546/5000 (51%)
[epoch 4] loss: 1.1991995
Test set: Average loss: 1.2736, Accuracy: 2599/5000 (52%)
[epoch 5] loss: 1.1631431
Test set: Average loss: 1.2509, Accuracy: 2673/5000 (53%)
[epoch 6] loss: 1.1149159
Test set: Average loss: 1.2326, Accuracy: 2722/5000 (54%)
[epoch 7] loss: 1.0969652
Test set: Average loss: 1.2171, Accuracy: 2752/5000 (55%)
[epoch 8] loss: 1.0583538
Test set: Average loss: 1.2030, Accuracy: 2807/5000 (56%)
[epoch 9] loss: 1.0242997
Test set: Average loss: 1.1926, Accuracy: 2824/5000 (56%)
[epoch 10] loss: 0.9981967
Test set: Average loss: 1.1793, Accuracy: 2842/5000 (57%)
[epoch 11] loss: 0.9747399
Test set: Average loss: 1.1707, Accuracy: 2884/5000 (58%)
[epoch 12] loss: 0.9504872
Test set: Average loss: 1.1614, Accuracy: 2915/5000 (58%)
[epoch 13] loss: 0.9263615
Test set: Average loss: 1.1517, Accuracy: 2907/5000 (58%)
[epoch 14] loss: 0.9060729
Test set: Average loss: 1.1436, Accuracy: 2950/5000 (59%)
[epoch 15] loss: 0.8824021
Test set: Average loss: 1.1379, Accuracy: 2939/5000 (59%)
[epoch 16] loss: 0.8580795
Test set: Average loss: 1.1289, Accuracy: 2977/5000 (60%)
[epoch 17] loss: 0.8376428
Test set: Average loss: 1.1249, Accuracy: 2975/5000 (60%)
[epoch 18] loss: 0.8213273
Test set: Average loss: 1.1192, Accuracy: 2974/5000 (59%)
[epoch 19] loss: 0.8020397
Test set: Average loss: 1.1111, Accuracy: 2987/5000 (60%)
[epoch 20] loss: 0.7772507
Test set: Average loss: 1.1066, Accuracy: 2995/5000 (60%)
[epoch 21] loss: 0.7590004
Test set: Average loss: 1.1006, Accuracy: 3009/5000 (60%)
[epoch 22] loss: 0.7432844
Test set: Average loss: 1.0971, Accuracy: 3002/5000 (60%)
[epoch 23] loss: 0.7213823
Test set: Average loss: 1.0914, Accuracy: 3013/5000 (60%)
[epoch 24] loss: 0.7005950
Test set: Average loss: 1.0879, Accuracy: 3019/5000 (60%)
[epoch 25] loss: 0.6878976
Test set: Average loss: 1.0838, Accuracy: 3028/5000 (61%)
Validation:
Test set: Average loss: 1.0838, Accuracy: 3028/5000 (61%)
Test
Test set: Average loss: 1.1016, Accuracy: 2942/5000 (59%)
Test set: Average loss: 0.6688, Accuracy: 885/1000 (88%)
2500
## seed: 11
Validation accuracy before training:
Test set: Average loss: 1.5498, Accuracy: 1725/5000 (34%)
[epoch 1] loss: 1.3829653
Test set: Average loss: 1.3078, Accuracy: 2783/5000 (56%)
[epoch 2] loss: 1.2229689
Test set: Average loss: 1.2334, Accuracy: 2934/5000 (59%)
[epoch 3] loss: 1.1457852
Test set: Average loss: 1.1854, Accuracy: 3041/5000 (61%)
[epoch 4] loss: 1.0845652
Test set: Average loss: 1.1532, Accuracy: 3078/5000 (62%)
[epoch 5] loss: 1.0447111
Test set: Average loss: 1.1288, Accuracy: 3102/5000 (62%)
[epoch 6] loss: 0.9977761
Test set: Average loss: 1.1092, Accuracy: 3124/5000 (62%)
[epoch 7] loss: 0.9618580
Test set: Average loss: 1.0910, Accuracy: 3105/5000 (62%)
[epoch 8] loss: 0.9203308
Test set: Average loss: 1.0779, Accuracy: 3114/5000 (62%)
[epoch 9] loss: 0.8951455
Test set: Average loss: 1.0660, Accuracy: 3116/5000 (62%)
[epoch 10] loss: 0.8663050
Test set: Average loss: 1.0507, Accuracy: 3139/5000 (63%)
[epoch 11] loss: 0.8256922
Test set: Average loss: 1.0398, Accuracy: 3170/5000 (63%)
[epoch 12] loss: 0.8062572
Test set: Average loss: 1.0305, Accuracy: 3175/5000 (64%)
[epoch 13] loss: 0.7727288
Test set: Average loss: 1.0210, Accuracy: 3176/5000 (64%)
[epoch 14] loss: 0.7441175
Test set: Average loss: 1.0138, Accuracy: 3190/5000 (64%)
[epoch 15] loss: 0.7189967
Test set: Average loss: 1.0066, Accuracy: 3194/5000 (64%)
[epoch 16] loss: 0.6923015
Test set: Average loss: 1.0013, Accuracy: 3194/5000 (64%)
[epoch 17] loss: 0.6720280
Test set: Average loss: 0.9955, Accuracy: 3189/5000 (64%)
[epoch 18] loss: 0.6480997
Test set: Average loss: 0.9891, Accuracy: 3203/5000 (64%)
[epoch 19] loss: 0.6260835
Test set: Average loss: 0.9915, Accuracy: 3193/5000 (64%)
[epoch 20] loss: 0.6026715
Test set: Average loss: 0.9825, Accuracy: 3188/5000 (64%)
[epoch 21] loss: 0.5739369
Test set: Average loss: 0.9801, Accuracy: 3222/5000 (64%)
[epoch 22] loss: 0.5561590
Test set: Average loss: 0.9753, Accuracy: 3221/5000 (64%)
[epoch 23] loss: 0.5332767
Test set: Average loss: 0.9751, Accuracy: 3191/5000 (64%)
[epoch 24] loss: 0.5119950
Test set: Average loss: 0.9745, Accuracy: 3202/5000 (64%)
[epoch 25] loss: 0.4904801
Test set: Average loss: 0.9675, Accuracy: 3208/5000 (64%)
Validation:
Test set: Average loss: 0.9801, Accuracy: 3222/5000 (64%)
Test
Test set: Average loss: 0.9860, Accuracy: 3168/5000 (63%)
Test set: Average loss: 0.5508, Accuracy: 2212/2500 (88%)
## seed: 12
Validation accuracy before training:
Test set: Average loss: 1.5405, Accuracy: 1582/5000 (32%)
[epoch 1] loss: 1.4181855
Test set: Average loss: 1.3270, Accuracy: 2562/5000 (51%)
[epoch 2] loss: 1.2542334
Test set: Average loss: 1.2500, Accuracy: 2810/5000 (56%)
[epoch 3] loss: 1.1672912
Test set: Average loss: 1.2015, Accuracy: 2914/5000 (58%)
[epoch 4] loss: 1.1015307
Test set: Average loss: 1.1690, Accuracy: 2947/5000 (59%)
[epoch 5] loss: 1.0596589
Test set: Average loss: 1.1412, Accuracy: 3000/5000 (60%)
[epoch 6] loss: 1.0079066
Test set: Average loss: 1.1185, Accuracy: 3043/5000 (61%)
[epoch 7] loss: 0.9675716
Test set: Average loss: 1.1015, Accuracy: 3047/5000 (61%)
[epoch 8] loss: 0.9307063
Test set: Average loss: 1.0843, Accuracy: 3065/5000 (61%)
[epoch 9] loss: 0.8993082
Test set: Average loss: 1.0686, Accuracy: 3086/5000 (62%)
[epoch 10] loss: 0.8650206
Test set: Average loss: 1.0536, Accuracy: 3112/5000 (62%)
[epoch 11] loss: 0.8332646
Test set: Average loss: 1.0437, Accuracy: 3119/5000 (62%)
[epoch 12] loss: 0.8116893
Test set: Average loss: 1.0336, Accuracy: 3131/5000 (63%)
[epoch 13] loss: 0.7777103
Test set: Average loss: 1.0233, Accuracy: 3144/5000 (63%)
[epoch 14] loss: 0.7505934
Test set: Average loss: 1.0187, Accuracy: 3159/5000 (63%)
[epoch 15] loss: 0.7251789
Test set: Average loss: 1.0110, Accuracy: 3154/5000 (63%)
[epoch 16] loss: 0.6983507
Test set: Average loss: 1.0007, Accuracy: 3176/5000 (64%)
[epoch 17] loss: 0.6755962
Test set: Average loss: 0.9964, Accuracy: 3160/5000 (63%)
[epoch 18] loss: 0.6491454
Test set: Average loss: 0.9907, Accuracy: 3166/5000 (63%)
[epoch 19] loss: 0.6305197
Test set: Average loss: 0.9886, Accuracy: 3176/5000 (64%)
[epoch 20] loss: 0.6051779
Test set: Average loss: 0.9840, Accuracy: 3158/5000 (63%)
[epoch 21] loss: 0.5827592
Test set: Average loss: 0.9795, Accuracy: 3166/5000 (63%)
[epoch 22] loss: 0.5609352
Test set: Average loss: 0.9763, Accuracy: 3166/5000 (63%)
[epoch 23] loss: 0.5484981
Test set: Average loss: 0.9762, Accuracy: 3153/5000 (63%)
[epoch 24] loss: 0.5210972
Test set: Average loss: 0.9726, Accuracy: 3181/5000 (64%)
[epoch 25] loss: 0.4997301
Test set: Average loss: 0.9743, Accuracy: 3161/5000 (63%)
Validation:
Test set: Average loss: 0.9726, Accuracy: 3181/5000 (64%)
Test
Test set: Average loss: 0.9893, Accuracy: 3121/5000 (62%)
Test set: Average loss: 0.4985, Accuracy: 2279/2500 (91%)
## seed: 13
Validation accuracy before training:
Test set: Average loss: 1.5972, Accuracy: 1259/5000 (25%)
[epoch 1] loss: 1.4188475
Test set: Average loss: 1.3281, Accuracy: 2320/5000 (46%)
[epoch 2] loss: 1.2519860
Test set: Average loss: 1.2537, Accuracy: 2588/5000 (52%)
[epoch 3] loss: 1.1672626
Test set: Average loss: 1.2070, Accuracy: 2731/5000 (55%)
[epoch 4] loss: 1.1081872
Test set: Average loss: 1.1738, Accuracy: 2808/5000 (56%)
[epoch 5] loss: 1.0580433
Test set: Average loss: 1.1508, Accuracy: 2849/5000 (57%)
[epoch 6] loss: 1.0258246
Test set: Average loss: 1.1292, Accuracy: 2899/5000 (58%)
[epoch 7] loss: 0.9872850
Test set: Average loss: 1.1101, Accuracy: 2936/5000 (59%)
[epoch 8] loss: 0.9497258
Test set: Average loss: 1.0954, Accuracy: 2983/5000 (60%)
[epoch 9] loss: 0.9168873
Test set: Average loss: 1.0802, Accuracy: 3003/5000 (60%)
[epoch 10] loss: 0.8834451
Test set: Average loss: 1.0719, Accuracy: 3016/5000 (60%)
[epoch 11] loss: 0.8589779
Test set: Average loss: 1.0601, Accuracy: 3041/5000 (61%)
[epoch 12] loss: 0.8309261
Test set: Average loss: 1.0498, Accuracy: 3056/5000 (61%)
[epoch 13] loss: 0.8026034
Test set: Average loss: 1.0389, Accuracy: 3095/5000 (62%)
[epoch 14] loss: 0.7757066
Test set: Average loss: 1.0345, Accuracy: 3071/5000 (61%)
[epoch 15] loss: 0.7576199
Test set: Average loss: 1.0232, Accuracy: 3106/5000 (62%)
[epoch 16] loss: 0.7330127
Test set: Average loss: 1.0205, Accuracy: 3097/5000 (62%)
[epoch 17] loss: 0.7047198
Test set: Average loss: 1.0124, Accuracy: 3108/5000 (62%)
[epoch 18] loss: 0.6855256
Test set: Average loss: 1.0082, Accuracy: 3123/5000 (62%)
[epoch 19] loss: 0.6608513
Test set: Average loss: 1.0038, Accuracy: 3126/5000 (63%)
[epoch 20] loss: 0.6400385
Test set: Average loss: 0.9980, Accuracy: 3144/5000 (63%)
[epoch 21] loss: 0.6203095
Test set: Average loss: 0.9937, Accuracy: 3135/5000 (63%)
[epoch 22] loss: 0.5947947
Test set: Average loss: 0.9900, Accuracy: 3148/5000 (63%)
[epoch 23] loss: 0.5755020
Test set: Average loss: 0.9890, Accuracy: 3150/5000 (63%)
[epoch 24] loss: 0.5533513
Test set: Average loss: 0.9834, Accuracy: 3155/5000 (63%)
[epoch 25] loss: 0.5338508
Test set: Average loss: 0.9814, Accuracy: 3145/5000 (63%)
Validation:
Test set: Average loss: 0.9834, Accuracy: 3155/5000 (63%)
Test
Test set: Average loss: 1.0093, Accuracy: 3072/5000 (61%)
Test set: Average loss: 0.5287, Accuracy: 2213/2500 (89%)
5000
## seed: 11
Validation accuracy before training:
Test set: Average loss: 1.7000, Accuracy: 596/5000 (12%)
[epoch 1] loss: 1.4053976
Test set: Average loss: 1.2688, Accuracy: 2570/5000 (51%)
[epoch 2] loss: 1.2031419
Test set: Average loss: 1.1854, Accuracy: 2789/5000 (56%)
[epoch 3] loss: 1.1202375
Test set: Average loss: 1.1375, Accuracy: 2920/5000 (58%)
[epoch 4] loss: 1.0607275
Test set: Average loss: 1.1044, Accuracy: 3023/5000 (60%)
[epoch 5] loss: 1.0112741
Test set: Average loss: 1.0817, Accuracy: 3036/5000 (61%)
[epoch 6] loss: 0.9716649
Test set: Average loss: 1.0561, Accuracy: 3118/5000 (62%)
[epoch 7] loss: 0.9320504
Test set: Average loss: 1.0391, Accuracy: 3135/5000 (63%)
[epoch 8] loss: 0.8940418
Test set: Average loss: 1.0257, Accuracy: 3155/5000 (63%)
[epoch 9] loss: 0.8607754
Test set: Average loss: 1.0124, Accuracy: 3162/5000 (63%)
[epoch 10] loss: 0.8313440
Test set: Average loss: 0.9989, Accuracy: 3199/5000 (64%)
[epoch 11] loss: 0.8017893
Test set: Average loss: 0.9918, Accuracy: 3206/5000 (64%)
[epoch 12] loss: 0.7714213
Test set: Average loss: 0.9841, Accuracy: 3212/5000 (64%)
[epoch 13] loss: 0.7446509
Test set: Average loss: 0.9766, Accuracy: 3214/5000 (64%)
[epoch 14] loss: 0.7163854
Test set: Average loss: 0.9693, Accuracy: 3211/5000 (64%)
[epoch 15] loss: 0.6895025
Test set: Average loss: 0.9637, Accuracy: 3230/5000 (65%)
[epoch 16] loss: 0.6624119
Test set: Average loss: 0.9590, Accuracy: 3241/5000 (65%)
[epoch 17] loss: 0.6379848
Test set: Average loss: 0.9557, Accuracy: 3239/5000 (65%)
[epoch 18] loss: 0.6114493
Test set: Average loss: 0.9484, Accuracy: 3260/5000 (65%)
[epoch 19] loss: 0.5861138
Test set: Average loss: 0.9470, Accuracy: 3272/5000 (65%)
[epoch 20] loss: 0.5607869
Test set: Average loss: 0.9448, Accuracy: 3267/5000 (65%)
[epoch 21] loss: 0.5386498
Test set: Average loss: 0.9421, Accuracy: 3252/5000 (65%)
[epoch 22] loss: 0.5155208
Test set: Average loss: 0.9440, Accuracy: 3257/5000 (65%)
[epoch 23] loss: 0.4929526
Test set: Average loss: 0.9444, Accuracy: 3260/5000 (65%)
[epoch 24] loss: 0.4697047
Test set: Average loss: 0.9430, Accuracy: 3262/5000 (65%)
[epoch 25] loss: 0.4482567
Test set: Average loss: 0.9470, Accuracy: 3260/5000 (65%)
Validation:
Test set: Average loss: 0.9470, Accuracy: 3272/5000 (65%)
Test
Test set: Average loss: 0.9549, Accuracy: 3231/5000 (65%)
Test set: Average loss: 0.5540, Accuracy: 4259/5000 (85%)
## seed: 12
Validation accuracy before training:
Test set: Average loss: 1.6093, Accuracy: 1096/5000 (22%)
[epoch 1] loss: 1.3565934
Test set: Average loss: 1.2529, Accuracy: 2659/5000 (53%)
[epoch 2] loss: 1.1722099
Test set: Average loss: 1.1708, Accuracy: 2870/5000 (57%)
[epoch 3] loss: 1.0913045
Test set: Average loss: 1.1223, Accuracy: 2989/5000 (60%)
[epoch 4] loss: 1.0332758
Test set: Average loss: 1.0902, Accuracy: 3046/5000 (61%)
[epoch 5] loss: 0.9859674
Test set: Average loss: 1.0653, Accuracy: 3089/5000 (62%)
[epoch 6] loss: 0.9426048
Test set: Average loss: 1.0401, Accuracy: 3129/5000 (63%)
[epoch 7] loss: 0.9039866
Test set: Average loss: 1.0228, Accuracy: 3147/5000 (63%)
[epoch 8] loss: 0.8671313
Test set: Average loss: 1.0101, Accuracy: 3156/5000 (63%)
[epoch 9] loss: 0.8327066
Test set: Average loss: 0.9924, Accuracy: 3180/5000 (64%)
[epoch 10] loss: 0.8014951
Test set: Average loss: 0.9800, Accuracy: 3199/5000 (64%)
[epoch 11] loss: 0.7687112
Test set: Average loss: 0.9697, Accuracy: 3205/5000 (64%)
[epoch 12] loss: 0.7392540
Test set: Average loss: 0.9636, Accuracy: 3209/5000 (64%)
[epoch 13] loss: 0.7131751
Test set: Average loss: 0.9521, Accuracy: 3253/5000 (65%)
[epoch 14] loss: 0.6833822
Test set: Average loss: 0.9508, Accuracy: 3249/5000 (65%)
[epoch 15] loss: 0.6569186
Test set: Average loss: 0.9443, Accuracy: 3247/5000 (65%)
[epoch 16] loss: 0.6294076
Test set: Average loss: 0.9412, Accuracy: 3259/5000 (65%)
[epoch 17] loss: 0.6058438
Test set: Average loss: 0.9376, Accuracy: 3270/5000 (65%)
[epoch 18] loss: 0.5817057
Test set: Average loss: 0.9373, Accuracy: 3275/5000 (66%)
[epoch 19] loss: 0.5572128
Test set: Average loss: 0.9365, Accuracy: 3268/5000 (65%)
[epoch 20] loss: 0.5346736
Test set: Average loss: 0.9373, Accuracy: 3258/5000 (65%)
[epoch 21] loss: 0.5080498
Test set: Average loss: 0.9310, Accuracy: 3276/5000 (66%)
[epoch 22] loss: 0.4873485
Test set: Average loss: 0.9368, Accuracy: 3259/5000 (65%)
[epoch 23] loss: 0.4621330
Test set: Average loss: 0.9384, Accuracy: 3264/5000 (65%)
[epoch 24] loss: 0.4395323
Test set: Average loss: 0.9435, Accuracy: 3239/5000 (65%)
[epoch 25] loss: 0.4221941
Test set: Average loss: 0.9449, Accuracy: 3270/5000 (65%)
Validation:
Test set: Average loss: 0.9310, Accuracy: 3276/5000 (66%)
Test
Test set: Average loss: 0.9354, Accuracy: 3231/5000 (65%)
Test set: Average loss: 0.4761, Accuracy: 4415/5000 (88%)
## seed: 13
Validation accuracy before training:
Test set: Average loss: 1.7859, Accuracy: 830/5000 (17%)
[epoch 1] loss: 1.4384197
Test set: Average loss: 1.3092, Accuracy: 2448/5000 (49%)
[epoch 2] loss: 1.2112046
Test set: Average loss: 1.2088, Accuracy: 2721/5000 (54%)
[epoch 3] loss: 1.1179882
Test set: Average loss: 1.1548, Accuracy: 2856/5000 (57%)
[epoch 4] loss: 1.0514071
Test set: Average loss: 1.1175, Accuracy: 2931/5000 (59%)
[epoch 5] loss: 1.0001167
Test set: Average loss: 1.0873, Accuracy: 3026/5000 (61%)
[epoch 6] loss: 0.9529036
Test set: Average loss: 1.0654, Accuracy: 3067/5000 (61%)
[epoch 7] loss: 0.9152393
Test set: Average loss: 1.0453, Accuracy: 3085/5000 (62%)
[epoch 8] loss: 0.8746605
Test set: Average loss: 1.0290, Accuracy: 3122/5000 (62%)
[epoch 9] loss: 0.8409352
Test set: Average loss: 1.0226, Accuracy: 3115/5000 (62%)
[epoch 10] loss: 0.8098148
Test set: Average loss: 1.0053, Accuracy: 3153/5000 (63%)
[epoch 11] loss: 0.7750027
Test set: Average loss: 0.9999, Accuracy: 3148/5000 (63%)
[epoch 12] loss: 0.7446121
Test set: Average loss: 0.9928, Accuracy: 3160/5000 (63%)
[epoch 13] loss: 0.7170664
Test set: Average loss: 0.9824, Accuracy: 3176/5000 (64%)
[epoch 14] loss: 0.6883762
Test set: Average loss: 0.9749, Accuracy: 3212/5000 (64%)
[epoch 15] loss: 0.6621645
Test set: Average loss: 0.9718, Accuracy: 3202/5000 (64%)
[epoch 16] loss: 0.6357645
Test set: Average loss: 0.9723, Accuracy: 3183/5000 (64%)
[epoch 17] loss: 0.6084813
Test set: Average loss: 0.9636, Accuracy: 3224/5000 (64%)
[epoch 18] loss: 0.5853718
Test set: Average loss: 0.9652, Accuracy: 3218/5000 (64%)
[epoch 19] loss: 0.5607299
Test set: Average loss: 0.9589, Accuracy: 3235/5000 (65%)
[epoch 20] loss: 0.5326387
Test set: Average loss: 0.9611, Accuracy: 3215/5000 (64%)
[epoch 21] loss: 0.5123062
Test set: Average loss: 0.9630, Accuracy: 3202/5000 (64%)
[epoch 22] loss: 0.4893701
Test set: Average loss: 0.9631, Accuracy: 3211/5000 (64%)
[epoch 23] loss: 0.4668424
Test set: Average loss: 0.9594, Accuracy: 3215/5000 (64%)
[epoch 24] loss: 0.4467006
Test set: Average loss: 0.9605, Accuracy: 3218/5000 (64%)
[epoch 25] loss: 0.4244741
Test set: Average loss: 0.9663, Accuracy: 3213/5000 (64%)
Validation:
Test set: Average loss: 0.9589, Accuracy: 3235/5000 (65%)
Test
Test set: Average loss: 0.9766, Accuracy: 3187/5000 (64%)
Test set: Average loss: 0.5256, Accuracy: 4323/5000 (86%)
10000
## seed: 11
Validation accuracy before training:
Test set: Average loss: 1.7185, Accuracy: 868/5000 (17%)
[epoch 1] loss: 1.3072389
Test set: Average loss: 1.1895, Accuracy: 2834/5000 (57%)
[epoch 2] loss: 1.1191410
Test set: Average loss: 1.1082, Accuracy: 2984/5000 (60%)
[epoch 3] loss: 1.0361564
Test set: Average loss: 1.0616, Accuracy: 3081/5000 (62%)
[epoch 4] loss: 0.9742481
Test set: Average loss: 1.0235, Accuracy: 3145/5000 (63%)
[epoch 5] loss: 0.9217722
Test set: Average loss: 0.9988, Accuracy: 3181/5000 (64%)
[epoch 6] loss: 0.8780809
Test set: Average loss: 0.9762, Accuracy: 3220/5000 (64%)
[epoch 7] loss: 0.8359090
Test set: Average loss: 0.9616, Accuracy: 3262/5000 (65%)
[epoch 8] loss: 0.7987577
Test set: Average loss: 0.9462, Accuracy: 3286/5000 (66%)
[epoch 9] loss: 0.7635920
Test set: Average loss: 0.9333, Accuracy: 3305/5000 (66%)
[epoch 10] loss: 0.7298587
Test set: Average loss: 0.9262, Accuracy: 3303/5000 (66%)
[epoch 11] loss: 0.6986208
Test set: Average loss: 0.9208, Accuracy: 3302/5000 (66%)
[epoch 12] loss: 0.6700132
Test set: Average loss: 0.9141, Accuracy: 3329/5000 (67%)
[epoch 13] loss: 0.6394617
Test set: Average loss: 0.9083, Accuracy: 3321/5000 (66%)
[epoch 14] loss: 0.6107854
Test set: Average loss: 0.9075, Accuracy: 3309/5000 (66%)
[epoch 15] loss: 0.5847379
Test set: Average loss: 0.9096, Accuracy: 3296/5000 (66%)
[epoch 16] loss: 0.5588318
Test set: Average loss: 0.9095, Accuracy: 3305/5000 (66%)
[epoch 17] loss: 0.5325033
Test set: Average loss: 0.9091, Accuracy: 3314/5000 (66%)
[epoch 18] loss: 0.5054455
Test set: Average loss: 0.9102, Accuracy: 3290/5000 (66%)
[epoch 19] loss: 0.4814173
Test set: Average loss: 0.9211, Accuracy: 3298/5000 (66%)
[epoch 20] loss: 0.4580232
Test set: Average loss: 0.9137, Accuracy: 3303/5000 (66%)
[epoch 21] loss: 0.4335783
Test set: Average loss: 0.9217, Accuracy: 3299/5000 (66%)
[epoch 22] loss: 0.4118992
Test set: Average loss: 0.9297, Accuracy: 3301/5000 (66%)
[epoch 23] loss: 0.3890954
Test set: Average loss: 0.9347, Accuracy: 3297/5000 (66%)
[epoch 24] loss: 0.3680731
Test set: Average loss: 0.9409, Accuracy: 3289/5000 (66%)
[epoch 25] loss: 0.3477248
Test set: Average loss: 0.9517, Accuracy: 3276/5000 (66%)
Validation:
Test set: Average loss: 0.9141, Accuracy: 3329/5000 (67%)
Test
Test set: Average loss: 0.9247, Accuracy: 3281/5000 (66%)
Test set: Average loss: 0.6329, Accuracy: 8083/10000 (81%)
## seed: 12
Validation accuracy before training:
Test set: Average loss: 1.5562, Accuracy: 1588/5000 (32%)
[epoch 1] loss: 1.2642777
Test set: Average loss: 1.1766, Accuracy: 2977/5000 (60%)
[epoch 2] loss: 1.0949697
Test set: Average loss: 1.0915, Accuracy: 3148/5000 (63%)
[epoch 3] loss: 1.0044580
Test set: Average loss: 1.0328, Accuracy: 3202/5000 (64%)
[epoch 4] loss: 0.9350520
Test set: Average loss: 0.9980, Accuracy: 3243/5000 (65%)
[epoch 5] loss: 0.8771735
Test set: Average loss: 0.9711, Accuracy: 3280/5000 (66%)
[epoch 6] loss: 0.8266013
Test set: Average loss: 0.9473, Accuracy: 3300/5000 (66%)
[epoch 7] loss: 0.7810244
Test set: Average loss: 0.9306, Accuracy: 3334/5000 (67%)
[epoch 8] loss: 0.7419031
Test set: Average loss: 0.9172, Accuracy: 3348/5000 (67%)
[epoch 9] loss: 0.7032928
Test set: Average loss: 0.9144, Accuracy: 3324/5000 (66%)
[epoch 10] loss: 0.6685427
Test set: Average loss: 0.9020, Accuracy: 3368/5000 (67%)
[epoch 11] loss: 0.6355480
Test set: Average loss: 0.8950, Accuracy: 3368/5000 (67%)
[epoch 12] loss: 0.6047573
Test set: Average loss: 0.9005, Accuracy: 3348/5000 (67%)
[epoch 13] loss: 0.5751066
Test set: Average loss: 0.8942, Accuracy: 3359/5000 (67%)
[epoch 14] loss: 0.5461599
Test set: Average loss: 0.8922, Accuracy: 3362/5000 (67%)
[epoch 15] loss: 0.5194521
Test set: Average loss: 0.8973, Accuracy: 3332/5000 (67%)
[epoch 16] loss: 0.4922383
Test set: Average loss: 0.9044, Accuracy: 3337/5000 (67%)
[epoch 17] loss: 0.4677154
Test set: Average loss: 0.9030, Accuracy: 3357/5000 (67%)
[epoch 18] loss: 0.4421448
Test set: Average loss: 0.9142, Accuracy: 3341/5000 (67%)
[epoch 19] loss: 0.4170380
Test set: Average loss: 0.9106, Accuracy: 3366/5000 (67%)
[epoch 20] loss: 0.3961026
Test set: Average loss: 0.9169, Accuracy: 3332/5000 (67%)
[epoch 21] loss: 0.3734503
Test set: Average loss: 0.9235, Accuracy: 3340/5000 (67%)
[epoch 22] loss: 0.3515633
Test set: Average loss: 0.9277, Accuracy: 3338/5000 (67%)
[epoch 23] loss: 0.3295116
Test set: Average loss: 0.9362, Accuracy: 3334/5000 (67%)
[epoch 24] loss: 0.3097630
Test set: Average loss: 0.9576, Accuracy: 3313/5000 (66%)
[epoch 25] loss: 0.2907369
Test set: Average loss: 0.9608, Accuracy: 3335/5000 (67%)
Validation:
Test set: Average loss: 0.8950, Accuracy: 3368/5000 (67%)
Test
Test set: Average loss: 0.9064, Accuracy: 3310/5000 (66%)
Test set: Average loss: 0.5980, Accuracy: 8262/10000 (83%)
## seed: 13
Validation accuracy before training:
Test set: Average loss: 1.6226, Accuracy: 1396/5000 (28%)
[epoch 1] loss: 1.2982792
Test set: Average loss: 1.1889, Accuracy: 2799/5000 (56%)
[epoch 2] loss: 1.1056850
Test set: Average loss: 1.1005, Accuracy: 3030/5000 (61%)
[epoch 3] loss: 1.0153553
Test set: Average loss: 1.0491, Accuracy: 3115/5000 (62%)
[epoch 4] loss: 0.9473160
Test set: Average loss: 1.0036, Accuracy: 3226/5000 (65%)
[epoch 5] loss: 0.8912301
Test set: Average loss: 0.9812, Accuracy: 3235/5000 (65%)
[epoch 6] loss: 0.8415540
Test set: Average loss: 0.9555, Accuracy: 3263/5000 (65%)
[epoch 7] loss: 0.7983734
Test set: Average loss: 0.9364, Accuracy: 3297/5000 (66%)
[epoch 8] loss: 0.7584647
Test set: Average loss: 0.9320, Accuracy: 3266/5000 (65%)
[epoch 9] loss: 0.7224063
Test set: Average loss: 0.9132, Accuracy: 3298/5000 (66%)
[epoch 10] loss: 0.6898786
Test set: Average loss: 0.9043, Accuracy: 3330/5000 (67%)
[epoch 11] loss: 0.6589271
Test set: Average loss: 0.8986, Accuracy: 3330/5000 (67%)
[epoch 12] loss: 0.6288778
Test set: Average loss: 0.8961, Accuracy: 3333/5000 (67%)
[epoch 13] loss: 0.5994542
Test set: Average loss: 0.8959, Accuracy: 3322/5000 (66%)
[epoch 14] loss: 0.5712568
Test set: Average loss: 0.8901, Accuracy: 3324/5000 (66%)
[epoch 15] loss: 0.5460009
Test set: Average loss: 0.8938, Accuracy: 3317/5000 (66%)
[epoch 16] loss: 0.5232097
Test set: Average loss: 0.8879, Accuracy: 3327/5000 (67%)
[epoch 17] loss: 0.4965513
Test set: Average loss: 0.8974, Accuracy: 3305/5000 (66%)
[epoch 18] loss: 0.4731488
Test set: Average loss: 0.8970, Accuracy: 3323/5000 (66%)
[epoch 19] loss: 0.4497884
Test set: Average loss: 0.9102, Accuracy: 3303/5000 (66%)
[epoch 20] loss: 0.4287509
Test set: Average loss: 0.9101, Accuracy: 3311/5000 (66%)
[epoch 21] loss: 0.4070786
Test set: Average loss: 0.9156, Accuracy: 3330/5000 (67%)
[epoch 22] loss: 0.3842912
Test set: Average loss: 0.9186, Accuracy: 3307/5000 (66%)
[epoch 23] loss: 0.3641134
Test set: Average loss: 0.9245, Accuracy: 3318/5000 (66%)
[epoch 24] loss: 0.3452181
Test set: Average loss: 0.9253, Accuracy: 3317/5000 (66%)
[epoch 25] loss: 0.3265229
Test set: Average loss: 0.9495, Accuracy: 3311/5000 (66%)
Validation:
Test set: Average loss: 0.8961, Accuracy: 3333/5000 (67%)
Test
Test set: Average loss: 0.9205, Accuracy: 3250/5000 (65%)
Test set: Average loss: 0.5987, Accuracy: 8128/10000 (81%)
15000
## seed: 11
Validation accuracy before training:
Test set: Average loss: 1.6668, Accuracy: 765/5000 (15%)
[epoch 1] loss: 1.2690163
Test set: Average loss: 1.1443, Accuracy: 2965/5000 (59%)
[epoch 2] loss: 1.0684335
Test set: Average loss: 1.0511, Accuracy: 3130/5000 (63%)
[epoch 3] loss: 0.9766285
Test set: Average loss: 0.9968, Accuracy: 3239/5000 (65%)
[epoch 4] loss: 0.9092776
Test set: Average loss: 0.9600, Accuracy: 3283/5000 (66%)
[epoch 5] loss: 0.8551651
Test set: Average loss: 0.9322, Accuracy: 3338/5000 (67%)
[epoch 6] loss: 0.8081366
Test set: Average loss: 0.9112, Accuracy: 3344/5000 (67%)
[epoch 7] loss: 0.7679884
Test set: Average loss: 0.8990, Accuracy: 3367/5000 (67%)
[epoch 8] loss: 0.7311067
Test set: Average loss: 0.8853, Accuracy: 3369/5000 (67%)
[epoch 9] loss: 0.6970291
Test set: Average loss: 0.8799, Accuracy: 3386/5000 (68%)
[epoch 10] loss: 0.6655339
Test set: Average loss: 0.8729, Accuracy: 3395/5000 (68%)
[epoch 11] loss: 0.6358241
Test set: Average loss: 0.8706, Accuracy: 3391/5000 (68%)
[epoch 12] loss: 0.6077442
Test set: Average loss: 0.8733, Accuracy: 3410/5000 (68%)
[epoch 13] loss: 0.5809689
Test set: Average loss: 0.8732, Accuracy: 3397/5000 (68%)
[epoch 14] loss: 0.5554151
Test set: Average loss: 0.8751, Accuracy: 3412/5000 (68%)
[epoch 15] loss: 0.5296059
Test set: Average loss: 0.8748, Accuracy: 3415/5000 (68%)
[epoch 16] loss: 0.5047152
Test set: Average loss: 0.8809, Accuracy: 3415/5000 (68%)
[epoch 17] loss: 0.4812364
Test set: Average loss: 0.8868, Accuracy: 3401/5000 (68%)
[epoch 18] loss: 0.4587795
Test set: Average loss: 0.8947, Accuracy: 3404/5000 (68%)
[epoch 19] loss: 0.4368525
Test set: Average loss: 0.8953, Accuracy: 3402/5000 (68%)
[epoch 20] loss: 0.4132398
Test set: Average loss: 0.9106, Accuracy: 3407/5000 (68%)
[epoch 21] loss: 0.3918976
Test set: Average loss: 0.9181, Accuracy: 3372/5000 (67%)
[epoch 22] loss: 0.3722256
Test set: Average loss: 0.9271, Accuracy: 3395/5000 (68%)
[epoch 23] loss: 0.3496212
Test set: Average loss: 0.9434, Accuracy: 3380/5000 (68%)
[epoch 24] loss: 0.3332644
Test set: Average loss: 0.9536, Accuracy: 3384/5000 (68%)
[epoch 25] loss: 0.3133234
Test set: Average loss: 0.9662, Accuracy: 3356/5000 (67%)
Validation:
Test set: Average loss: 0.8809, Accuracy: 3415/5000 (68%)
Test
Test set: Average loss: 0.9004, Accuracy: 3305/5000 (66%)
Test set: Average loss: 0.4677, Accuracy: 12977/15000 (87%)
## seed: 12
Validation accuracy before training:
Test set: Average loss: 1.7561, Accuracy: 807/5000 (16%)
[epoch 1] loss: 1.3316557
Test set: Average loss: 1.1815, Accuracy: 2859/5000 (57%)
[epoch 2] loss: 1.1104919
Test set: Average loss: 1.0777, Accuracy: 3094/5000 (62%)
[epoch 3] loss: 1.0167230
Test set: Average loss: 1.0240, Accuracy: 3192/5000 (64%)
[epoch 4] loss: 0.9516676
Test set: Average loss: 0.9850, Accuracy: 3239/5000 (65%)
[epoch 5] loss: 0.8986704
Test set: Average loss: 0.9588, Accuracy: 3269/5000 (65%)
[epoch 6] loss: 0.8527346
Test set: Average loss: 0.9409, Accuracy: 3276/5000 (66%)
[epoch 7] loss: 0.8139699
Test set: Average loss: 0.9215, Accuracy: 3320/5000 (66%)
[epoch 8] loss: 0.7773547
Test set: Average loss: 0.9099, Accuracy: 3333/5000 (67%)
[epoch 9] loss: 0.7426943
Test set: Average loss: 0.9026, Accuracy: 3333/5000 (67%)
[epoch 10] loss: 0.7103158
Test set: Average loss: 0.8911, Accuracy: 3331/5000 (67%)
[epoch 11] loss: 0.6808196
Test set: Average loss: 0.8910, Accuracy: 3348/5000 (67%)
[epoch 12] loss: 0.6516669
Test set: Average loss: 0.8851, Accuracy: 3373/5000 (67%)
[epoch 13] loss: 0.6228930
Test set: Average loss: 0.8798, Accuracy: 3360/5000 (67%)
[epoch 14] loss: 0.5976007
Test set: Average loss: 0.8772, Accuracy: 3369/5000 (67%)
[epoch 15] loss: 0.5723327
Test set: Average loss: 0.8879, Accuracy: 3346/5000 (67%)
[epoch 16] loss: 0.5466187
Test set: Average loss: 0.8853, Accuracy: 3360/5000 (67%)
[epoch 17] loss: 0.5233159
Test set: Average loss: 0.8836, Accuracy: 3359/5000 (67%)
[epoch 18] loss: 0.4987184
Test set: Average loss: 0.8978, Accuracy: 3335/5000 (67%)
[epoch 19] loss: 0.4745567
Test set: Average loss: 0.8925, Accuracy: 3370/5000 (67%)
[epoch 20] loss: 0.4530372
Test set: Average loss: 0.9019, Accuracy: 3343/5000 (67%)
[epoch 21] loss: 0.4296131
Test set: Average loss: 0.9076, Accuracy: 3342/5000 (67%)
[epoch 22] loss: 0.4073953
Test set: Average loss: 0.9197, Accuracy: 3357/5000 (67%)
[epoch 23] loss: 0.3876181
Test set: Average loss: 0.9310, Accuracy: 3350/5000 (67%)
[epoch 24] loss: 0.3666132
Test set: Average loss: 0.9323, Accuracy: 3333/5000 (67%)
[epoch 25] loss: 0.3460744
Test set: Average loss: 0.9585, Accuracy: 3303/5000 (66%)
Validation:
Test set: Average loss: 0.8851, Accuracy: 3373/5000 (67%)
Test
Test set: Average loss: 0.8931, Accuracy: 3342/5000 (67%)
Test set: Average loss: 0.6184, Accuracy: 12000/15000 (80%)
## seed: 13
Validation accuracy before training:
Test set: Average loss: 1.8085, Accuracy: 485/5000 (10%)
[epoch 1] loss: 1.2796544
Test set: Average loss: 1.1532, Accuracy: 2905/5000 (58%)
[epoch 2] loss: 1.0855838
Test set: Average loss: 1.0710, Accuracy: 3069/5000 (61%)
[epoch 3] loss: 1.0038233
Test set: Average loss: 1.0297, Accuracy: 3104/5000 (62%)
[epoch 4] loss: 0.9432158
Test set: Average loss: 0.9883, Accuracy: 3189/5000 (64%)
[epoch 5] loss: 0.8931719
Test set: Average loss: 0.9618, Accuracy: 3218/5000 (64%)
[epoch 6] loss: 0.8477089
Test set: Average loss: 0.9471, Accuracy: 3250/5000 (65%)
[epoch 7] loss: 0.8067866
Test set: Average loss: 0.9272, Accuracy: 3258/5000 (65%)
[epoch 8] loss: 0.7692052
Test set: Average loss: 0.9160, Accuracy: 3274/5000 (65%)
[epoch 9] loss: 0.7350192
Test set: Average loss: 0.9047, Accuracy: 3300/5000 (66%)
[epoch 10] loss: 0.7022364
Test set: Average loss: 0.8999, Accuracy: 3309/5000 (66%)
[epoch 11] loss: 0.6697201
Test set: Average loss: 0.8960, Accuracy: 3320/5000 (66%)
[epoch 12] loss: 0.6422434
Test set: Average loss: 0.8935, Accuracy: 3322/5000 (66%)
[epoch 13] loss: 0.6123576
Test set: Average loss: 0.8957, Accuracy: 3327/5000 (67%)
[epoch 14] loss: 0.5864515
Test set: Average loss: 0.8946, Accuracy: 3330/5000 (67%)
[epoch 15] loss: 0.5607442
Test set: Average loss: 0.8938, Accuracy: 3351/5000 (67%)
[epoch 16] loss: 0.5350443
Test set: Average loss: 0.9002, Accuracy: 3349/5000 (67%)
[epoch 17] loss: 0.5099907
Test set: Average loss: 0.9022, Accuracy: 3334/5000 (67%)
[epoch 18] loss: 0.4865128
Test set: Average loss: 0.9034, Accuracy: 3328/5000 (67%)
[epoch 19] loss: 0.4625998
Test set: Average loss: 0.9119, Accuracy: 3348/5000 (67%)
[epoch 20] loss: 0.4400600
Test set: Average loss: 0.9182, Accuracy: 3325/5000 (66%)
[epoch 21] loss: 0.4177695
Test set: Average loss: 0.9207, Accuracy: 3352/5000 (67%)
[epoch 22] loss: 0.3968771
Test set: Average loss: 0.9345, Accuracy: 3345/5000 (67%)
[epoch 23] loss: 0.3765003
Test set: Average loss: 0.9436, Accuracy: 3335/5000 (67%)
[epoch 24] loss: 0.3556799
Test set: Average loss: 0.9523, Accuracy: 3352/5000 (67%)
[epoch 25] loss: 0.3347449
Test set: Average loss: 0.9667, Accuracy: 3334/5000 (67%)
Validation:
Test set: Average loss: 0.9523, Accuracy: 3352/5000 (67%)
Test
Test set: Average loss: 0.9616, Accuracy: 3270/5000 (65%)
Test set: Average loss: 0.3209, Accuracy: 13851/15000 (92%)
20000
## seed: 11
Validation accuracy before training:
Test set: Average loss: 1.4788, Accuracy: 1654/5000 (33%)
[epoch 1] loss: 1.1244201
Test set: Average loss: 1.0463, Accuracy: 3129/5000 (63%)
[epoch 2] loss: 0.9565011
Test set: Average loss: 0.9719, Accuracy: 3225/5000 (64%)
[epoch 3] loss: 0.8746562
Test set: Average loss: 0.9257, Accuracy: 3286/5000 (66%)
[epoch 4] loss: 0.8156700
Test set: Average loss: 0.8987, Accuracy: 3349/5000 (67%)
[epoch 5] loss: 0.7679715
Test set: Average loss: 0.8811, Accuracy: 3390/5000 (68%)
[epoch 6] loss: 0.7260045
Test set: Average loss: 0.8774, Accuracy: 3362/5000 (67%)
[epoch 7] loss: 0.6912960
Test set: Average loss: 0.8595, Accuracy: 3408/5000 (68%)
[epoch 8] loss: 0.6600356
Test set: Average loss: 0.8550, Accuracy: 3408/5000 (68%)
[epoch 9] loss: 0.6283041
Test set: Average loss: 0.8602, Accuracy: 3409/5000 (68%)
[epoch 10] loss: 0.5999365
Test set: Average loss: 0.8475, Accuracy: 3428/5000 (69%)
[epoch 11] loss: 0.5719735
Test set: Average loss: 0.8527, Accuracy: 3445/5000 (69%)
[epoch 12] loss: 0.5458010
Test set: Average loss: 0.8542, Accuracy: 3437/5000 (69%)
[epoch 13] loss: 0.5209491
Test set: Average loss: 0.8634, Accuracy: 3442/5000 (69%)
[epoch 14] loss: 0.4979455
Test set: Average loss: 0.8736, Accuracy: 3409/5000 (68%)
[epoch 15] loss: 0.4726998
Test set: Average loss: 0.8639, Accuracy: 3455/5000 (69%)
[epoch 16] loss: 0.4504641
Test set: Average loss: 0.8827, Accuracy: 3410/5000 (68%)
[epoch 17] loss: 0.4280302
Test set: Average loss: 0.8819, Accuracy: 3418/5000 (68%)
[epoch 18] loss: 0.4059970
Test set: Average loss: 0.8951, Accuracy: 3408/5000 (68%)
[epoch 19] loss: 0.3865318
Test set: Average loss: 0.9011, Accuracy: 3426/5000 (69%)
[epoch 20] loss: 0.3664868
Test set: Average loss: 0.9085, Accuracy: 3422/5000 (68%)
[epoch 21] loss: 0.3470483
Test set: Average loss: 0.9204, Accuracy: 3395/5000 (68%)
[epoch 22] loss: 0.3273906
Test set: Average loss: 0.9326, Accuracy: 3400/5000 (68%)
[epoch 23] loss: 0.3094143
Test set: Average loss: 0.9532, Accuracy: 3396/5000 (68%)
[epoch 24] loss: 0.2925355
Test set: Average loss: 0.9625, Accuracy: 3415/5000 (68%)
[epoch 25] loss: 0.2749186
Test set: Average loss: 0.9820, Accuracy: 3363/5000 (67%)
Validation:
Test set: Average loss: 0.8639, Accuracy: 3455/5000 (69%)
Test
Test set: Average loss: 0.8903, Accuracy: 3383/5000 (68%)
Test set: Average loss: 0.4312, Accuracy: 17471/20000 (87%)
## seed: 12
Validation accuracy before training:
Test set: Average loss: 1.7141, Accuracy: 615/5000 (12%)
[epoch 1] loss: 1.2613898
Test set: Average loss: 1.1249, Accuracy: 2979/5000 (60%)
[epoch 2] loss: 1.0516025
Test set: Average loss: 1.0294, Accuracy: 3161/5000 (63%)
[epoch 3] loss: 0.9591681
Test set: Average loss: 0.9827, Accuracy: 3214/5000 (64%)
[epoch 4] loss: 0.8939628
Test set: Average loss: 0.9474, Accuracy: 3257/5000 (65%)
[epoch 5] loss: 0.8388803
Test set: Average loss: 0.9239, Accuracy: 3302/5000 (66%)
[epoch 6] loss: 0.7922429
Test set: Average loss: 0.9046, Accuracy: 3335/5000 (67%)
[epoch 7] loss: 0.7538953
Test set: Average loss: 0.8925, Accuracy: 3342/5000 (67%)
[epoch 8] loss: 0.7157779
Test set: Average loss: 0.8816, Accuracy: 3349/5000 (67%)
[epoch 9] loss: 0.6838484
Test set: Average loss: 0.8757, Accuracy: 3377/5000 (68%)
[epoch 10] loss: 0.6537703
Test set: Average loss: 0.8770, Accuracy: 3378/5000 (68%)
[epoch 11] loss: 0.6235470
Test set: Average loss: 0.8834, Accuracy: 3358/5000 (67%)
[epoch 12] loss: 0.5968326
Test set: Average loss: 0.8759, Accuracy: 3391/5000 (68%)
[epoch 13] loss: 0.5704915
Test set: Average loss: 0.8750, Accuracy: 3395/5000 (68%)
[epoch 14] loss: 0.5438707
Test set: Average loss: 0.8803, Accuracy: 3374/5000 (67%)
[epoch 15] loss: 0.5193303
Test set: Average loss: 0.8837, Accuracy: 3380/5000 (68%)
[epoch 16] loss: 0.4939352
Test set: Average loss: 0.8958, Accuracy: 3371/5000 (67%)
[epoch 17] loss: 0.4715397
Test set: Average loss: 0.9032, Accuracy: 3368/5000 (67%)
[epoch 18] loss: 0.4479485
Test set: Average loss: 0.9051, Accuracy: 3404/5000 (68%)
[epoch 19] loss: 0.4267195
Test set: Average loss: 0.9244, Accuracy: 3328/5000 (67%)
[epoch 20] loss: 0.4049837
Test set: Average loss: 0.9235, Accuracy: 3344/5000 (67%)
[epoch 21] loss: 0.3847070
Test set: Average loss: 0.9423, Accuracy: 3377/5000 (68%)
[epoch 22] loss: 0.3656191
Test set: Average loss: 0.9610, Accuracy: 3338/5000 (67%)
[epoch 23] loss: 0.3454162
Test set: Average loss: 0.9834, Accuracy: 3328/5000 (67%)
[epoch 24] loss: 0.3274227
Test set: Average loss: 0.9828, Accuracy: 3352/5000 (67%)
[epoch 25] loss: 0.3077310
Test set: Average loss: 1.0079, Accuracy: 3338/5000 (67%)
Validation:
Test set: Average loss: 0.9051, Accuracy: 3404/5000 (68%)
Test
Test set: Average loss: 0.9437, Accuracy: 3326/5000 (67%)
Test set: Average loss: 0.4115, Accuracy: 17618/20000 (88%)
## seed: 13
Validation accuracy before training:
Test set: Average loss: 1.7897, Accuracy: 609/5000 (12%)
[epoch 1] loss: 1.2691808
Test set: Average loss: 1.1241, Accuracy: 3036/5000 (61%)
[epoch 2] loss: 1.0515738
Test set: Average loss: 1.0364, Accuracy: 3157/5000 (63%)
[epoch 3] loss: 0.9639067
Test set: Average loss: 0.9876, Accuracy: 3219/5000 (64%)
[epoch 4] loss: 0.8982236
Test set: Average loss: 0.9454, Accuracy: 3288/5000 (66%)
[epoch 5] loss: 0.8451199
Test set: Average loss: 0.9220, Accuracy: 3331/5000 (67%)
[epoch 6] loss: 0.7988414
Test set: Average loss: 0.9045, Accuracy: 3335/5000 (67%)
[epoch 7] loss: 0.7587474
Test set: Average loss: 0.8896, Accuracy: 3342/5000 (67%)
[epoch 8] loss: 0.7233366
Test set: Average loss: 0.8820, Accuracy: 3371/5000 (67%)
[epoch 9] loss: 0.6907397
Test set: Average loss: 0.8799, Accuracy: 3360/5000 (67%)
[epoch 10] loss: 0.6609477
Test set: Average loss: 0.8722, Accuracy: 3391/5000 (68%)
[epoch 11] loss: 0.6326604
Test set: Average loss: 0.8651, Accuracy: 3386/5000 (68%)
[epoch 12] loss: 0.6044159
Test set: Average loss: 0.8700, Accuracy: 3381/5000 (68%)
[epoch 13] loss: 0.5784393
Test set: Average loss: 0.8772, Accuracy: 3398/5000 (68%)
[epoch 14] loss: 0.5534915
Test set: Average loss: 0.8820, Accuracy: 3384/5000 (68%)
[epoch 15] loss: 0.5290345
Test set: Average loss: 0.8800, Accuracy: 3415/5000 (68%)
[epoch 16] loss: 0.5044305
Test set: Average loss: 0.8848, Accuracy: 3399/5000 (68%)
[epoch 17] loss: 0.4809348
Test set: Average loss: 0.8926, Accuracy: 3409/5000 (68%)
[epoch 18] loss: 0.4579307
Test set: Average loss: 0.9014, Accuracy: 3386/5000 (68%)
[epoch 19] loss: 0.4374833
Test set: Average loss: 0.9257, Accuracy: 3363/5000 (67%)
[epoch 20] loss: 0.4164466
Test set: Average loss: 0.9129, Accuracy: 3393/5000 (68%)
[epoch 21] loss: 0.3945920
Test set: Average loss: 0.9164, Accuracy: 3397/5000 (68%)
[epoch 22] loss: 0.3741812
Test set: Average loss: 0.9383, Accuracy: 3398/5000 (68%)
[epoch 23] loss: 0.3540905
Test set: Average loss: 0.9492, Accuracy: 3371/5000 (67%)
[epoch 24] loss: 0.3342286
Test set: Average loss: 0.9532, Accuracy: 3362/5000 (67%)
[epoch 25] loss: 0.3166925
Test set: Average loss: 0.9693, Accuracy: 3377/5000 (68%)
Validation:
Test set: Average loss: 0.8800, Accuracy: 3415/5000 (68%)
Test
Test set: Average loss: 0.8845, Accuracy: 3379/5000 (68%)
Test set: Average loss: 0.4919, Accuracy: 17006/20000 (85%)
n_training_examples = [25, 50, 100, 250, 500, 750, 1000, 2500, 5000, 10000, 15000, 20000]
test_accuracies = {'B': [(0.38139999999999996, 0.015809701662797656), (0.3970666666666666, 0.028842715236645496), (0.4288666666666667, 0.02155880846016826), (0.5150666666666667, 0.006661998365522331), (0.5502, 0.004140853374205232), (0.564, 0.0058057442818872425), (0.5720666666666666, 0.00338755893757666), (0.6050666666666668, 0.0020154955277108012), (0.6286, 0.0027276363393971886), (0.6593333333333334, 0.0024783507060588098), (0.6668666666666666, 0.004847909056719406), (0.6729333333333333, 0.000984321537348923)], 'AnB': [(0.30119999999999997, 0.015047480409246826), (0.2637333333333333, 0.02428515779007599), (0.2998, 0.02618549216646502), (0.48546666666666666, 0.013450485327881496), (0.5288, 0.015036843640427585), (0.5560666666666667, 0.008980472642845102), (0.5705333333333332, 0.0017987650084309492), (0.6044666666666667, 0.002379542439676599), (0.6376666666666667, 0.0009977753031397067), (0.6528666666666667, 0.01166799992381823), (0.665, 0.0030594117081556606), (0.6743333333333333, 0.0014817407180595414)], 'BnB': [(0.3277333333333334, 0.04855576404735305), (0.3639333333333333, 0.03589961312078758), (0.32993333333333336, 0.04530322529602303), (0.5082, 0.018244999314880782), (0.5541333333333334, 0.004135483311805577), (0.5622, 0.0044751163858235635), (0.5892666666666666, 0.009309970760188007), (0.616, 0.013465016400534649), (0.6516666666666667, 0.006816320284598008), (0.6614, 0.004667618950457102), (0.674, 0.004581120678029189), (0.6732, 0.004169732205629844)], 'ABnB': [(0.31373333333333336, 0.03327474851728993), (0.3403333333333333, 0.04302691664011676), (0.3038666666666667, 0.01627786499787022), (0.47846666666666665, 0.01972499823968447), (0.5561333333333334, 0.010847221866552884), (0.5794666666666667, 0.0017913371790059629), (0.5916666666666667, 0.008249983164965972), (0.6240666666666667, 0.007838934167914001), (0.6432666666666667, 0.004148359782961093), (0.6560666666666667, 0.00489988662000346), (0.6611333333333334, 0.005879531349426478), (0.6725333333333333, 0.005195724738239637)]}
n_training_examples = [25, 50, 100, 250, 500, 750, 1000, 2500, 5000, 10000, 15000, 20000]
train_accuracies = {'B': [(0.96, 0.0), (0.8133333333333334, 0.09568466729604881), (0.7266666666666666, 0.10274023338281628), (0.884, 0.021416504538945367), (0.868, 0.028612351645166605), (0.843111111111111, 0.018260123185932547), (0.8053333333333333, 0.020885933597094022), (0.7885333333333334, 0.01053417718138861), (0.8553333333333333, 0.01441881486885179), (0.8739333333333335, 0.0022866763848190196), (0.8454444444444444, 0.019579303761943886), (0.8278, 0.01500216651020777)], 'AnB': [(0.8666666666666667, 0.03771236166328257), (0.5933333333333334, 0.06599663291074445), (0.5066666666666667, 0.14007934259633795), (0.884, 0.008640987597877155), (0.8446666666666666, 0.0033993463423951926), (0.8537777777777777, 0.012757955639473177), (0.8576666666666667, 0.0020548046676563273), (0.8536, 0.007382863039950467), (0.8575333333333334, 0.034228383283792733), (0.8843, 0.0119132978921316), (0.8282444444444444, 0.015601456089056711), (0.83625, 0.006368673331236242)], 'BnB': [(0.9333333333333332, 0.0679869268479038), (0.7599999999999999, 0.08640987597877146), (0.6233333333333334, 0.07408703590297622), (0.9026666666666667, 0.02815828277592381), (0.8886666666666666, 0.01309792180292568), (0.8564444444444445, 0.03159621793275771), (0.8923333333333333, 0.01108552609887727), (0.8793333333333333, 0.008199728992811604), (0.9037333333333333, 0.012505287770468238), (0.8726333333333334, 0.006136955452194726), (0.8780666666666667, 0.016776438504309803), (0.83805, 0.007347221697122431)], 'ABnB': [(0.9066666666666667, 0.018856180831641284), (0.8266666666666667, 0.12472191289246469), (0.5800000000000001, 0.024494897427831758), (0.8999999999999999, 0.052255781179374475), (0.8873333333333333, 0.018354533197248286), (0.8777777777777778, 0.012570787221094207), (0.8766666666666666, 0.02007209228976615), (0.8938666666666667, 0.01254042352642931), (0.8664666666666667, 0.012805554350445834), (0.8157666666666668, 0.0076027772703284235), (0.8628444444444444, 0.05040383093416119), (0.8682500000000001, 0.01304243075503953)]}
n_training_examples = [25, 50, 100, 250, 500, 750, 1000, 2500, 5000, 10000, 15000, 20000]
generr_accuracies = {'B': [(0.5785999999999999, 0.01580970166279762), (0.41626666666666673, 0.08286476264908316), (0.2978, 0.11273520597695588), (0.3689333333333334, 0.017408299425529454), (0.31779999999999997, 0.029272512703900275), (0.27911111111111114, 0.02388548813003148), (0.23326666666666665, 0.023383945109602167), (0.18346666666666667, 0.009898596982513297), (0.22673333333333334, 0.011763597333393444), (0.2146, 0.0026545558322752525), (0.17857777777777775, 0.02168695346555812), (0.15486666666666668, 0.015512593450340768)], 'AnB': [(0.5654666666666667, 0.047951178875555896), (0.32960000000000006, 0.0453381370003959), (0.20686666666666664, 0.11389425895198675), (0.39853333333333335, 0.009069117315863153), (0.31586666666666663, 0.016877861897237556), (0.2977111111111111, 0.003783916580919545), (0.28713333333333335, 0.0029948103260288234), (0.24913333333333332, 0.009661377863546252), (0.21986666666666665, 0.035202398908155214), (0.2314333333333333, 0.01755492966535486), (0.1632444444444444, 0.012844405997635646), (0.16191666666666668, 0.007570703768841816)], 'BnB': [(0.6056, 0.020835226580641374), (0.3960666666666666, 0.10202343957259145), (0.29340000000000005, 0.02878934988266783), (0.3944666666666666, 0.031102554378843017), (0.33453333333333335, 0.013227580613584988), (0.29424444444444436, 0.027780746508026196), (0.3030666666666667, 0.016016935481615154), (0.26333333333333336, 0.00874274302239036), (0.25206666666666666, 0.013007006658805921), (0.21123333333333336, 0.0021746008573733737), (0.20406666666666665, 0.01234215900435936), (0.16484999999999997, 0.010358651778424956)], 'ABnB': [(0.5929333333333334, 0.015595155943076928), (0.4863333333333333, 0.1114060840149924), (0.27613333333333334, 0.030934913752730685), (0.4215333333333333, 0.03401581331609691), (0.3312, 0.012251802588462915), (0.29831111111111114, 0.013201159694661378), (0.285, 0.01393700111214749), (0.2698, 0.014795494809794866), (0.22320000000000004, 0.01304760514424008), (0.15969999999999998, 0.00540431926024606), (0.2017111111111111, 0.05628268158957581), (0.19571666666666668, 0.016842423288298585)]}
In [8]:
results_test[n_hus[1]], results_train[n_hus[1]], results_generr[n_hus[1]] = do_all_hl(n_hus[1])
#### Training for 512 hu
## No Pre-Training
25
## seed: 11
Validation accuracy before training:
Test set: Average loss: 1.6294, Accuracy: 983/5000 (20%)
[epoch 1] loss: 1.6398996
Test set: Average loss: 1.5957, Accuracy: 1164/5000 (23%)
[epoch 2] loss: 1.5007390
Test set: Average loss: 1.5690, Accuracy: 1347/5000 (27%)
[epoch 3] loss: 1.3751215
Test set: Average loss: 1.5485, Accuracy: 1482/5000 (30%)
[epoch 4] loss: 1.2643269
Test set: Average loss: 1.5329, Accuracy: 1553/5000 (31%)
[epoch 5] loss: 1.1675833
Test set: Average loss: 1.5208, Accuracy: 1600/5000 (32%)
[epoch 6] loss: 1.0831263
Test set: Average loss: 1.5114, Accuracy: 1636/5000 (33%)
[epoch 7] loss: 1.0089759
Test set: Average loss: 1.5038, Accuracy: 1680/5000 (34%)
[epoch 8] loss: 0.9433078
Test set: Average loss: 1.4974, Accuracy: 1714/5000 (34%)
[epoch 9] loss: 0.8846000
Test set: Average loss: 1.4919, Accuracy: 1747/5000 (35%)
[epoch 10] loss: 0.8316692
Test set: Average loss: 1.4870, Accuracy: 1775/5000 (36%)
[epoch 11] loss: 0.7836497
Test set: Average loss: 1.4827, Accuracy: 1791/5000 (36%)
[epoch 12] loss: 0.7399434
Test set: Average loss: 1.4789, Accuracy: 1804/5000 (36%)
[epoch 13] loss: 0.7001465
Test set: Average loss: 1.4756, Accuracy: 1827/5000 (37%)
[epoch 14] loss: 0.6639595
Test set: Average loss: 1.4727, Accuracy: 1844/5000 (37%)
[epoch 15] loss: 0.6311018
Test set: Average loss: 1.4704, Accuracy: 1862/5000 (37%)
[epoch 16] loss: 0.6012676
Test set: Average loss: 1.4686, Accuracy: 1876/5000 (38%)
[epoch 17] loss: 0.5741298
Test set: Average loss: 1.4674, Accuracy: 1881/5000 (38%)
[epoch 18] loss: 0.5493715
Test set: Average loss: 1.4666, Accuracy: 1892/5000 (38%)
[epoch 19] loss: 0.5267141
Test set: Average loss: 1.4663, Accuracy: 1908/5000 (38%)
[epoch 20] loss: 0.5059252
Test set: Average loss: 1.4665, Accuracy: 1904/5000 (38%)
[epoch 21] loss: 0.4868135
Test set: Average loss: 1.4670, Accuracy: 1901/5000 (38%)
[epoch 22] loss: 0.4692183
Test set: Average loss: 1.4678, Accuracy: 1900/5000 (38%)
[epoch 23] loss: 0.4529990
Test set: Average loss: 1.4688, Accuracy: 1891/5000 (38%)
[epoch 24] loss: 0.4380308
Test set: Average loss: 1.4700, Accuracy: 1892/5000 (38%)
[epoch 25] loss: 0.4242007
Test set: Average loss: 1.4712, Accuracy: 1895/5000 (38%)
Validation:
Test set: Average loss: 1.4663, Accuracy: 1908/5000 (38%)
Test
Test set: Average loss: 1.4803, Accuracy: 1821/5000 (36%)
Test set: Average loss: 0.5059, Accuracy: 25/25 (100%)
## seed: 12
Validation accuracy before training:
Test set: Average loss: 1.6391, Accuracy: 959/5000 (19%)
[epoch 1] loss: 1.6294016
Test set: Average loss: 1.5881, Accuracy: 1487/5000 (30%)
[epoch 2] loss: 1.4635891
Test set: Average loss: 1.5514, Accuracy: 1623/5000 (32%)
[epoch 3] loss: 1.3261966
Test set: Average loss: 1.5256, Accuracy: 1726/5000 (35%)
[epoch 4] loss: 1.2140619
Test set: Average loss: 1.5073, Accuracy: 1796/5000 (36%)
[epoch 5] loss: 1.1217413
Test set: Average loss: 1.4940, Accuracy: 1826/5000 (37%)
[epoch 6] loss: 1.0446588
Test set: Average loss: 1.4841, Accuracy: 1867/5000 (37%)
[epoch 7] loss: 0.9794264
Test set: Average loss: 1.4764, Accuracy: 1877/5000 (38%)
[epoch 8] loss: 0.9234377
Test set: Average loss: 1.4704, Accuracy: 1897/5000 (38%)
[epoch 9] loss: 0.8746329
Test set: Average loss: 1.4654, Accuracy: 1907/5000 (38%)
[epoch 10] loss: 0.8314335
Test set: Average loss: 1.4611, Accuracy: 1908/5000 (38%)
[epoch 11] loss: 0.7927071
Test set: Average loss: 1.4573, Accuracy: 1907/5000 (38%)
[epoch 12] loss: 0.7576891
Test set: Average loss: 1.4538, Accuracy: 1924/5000 (38%)
[epoch 13] loss: 0.7258764
Test set: Average loss: 1.4507, Accuracy: 1934/5000 (39%)
[epoch 14] loss: 0.6969088
Test set: Average loss: 1.4477, Accuracy: 1943/5000 (39%)
[epoch 15] loss: 0.6704843
Test set: Average loss: 1.4449, Accuracy: 1940/5000 (39%)
[epoch 16] loss: 0.6463168
Test set: Average loss: 1.4424, Accuracy: 1940/5000 (39%)
[epoch 17] loss: 0.6241351
Test set: Average loss: 1.4400, Accuracy: 1950/5000 (39%)
[epoch 18] loss: 0.6036974
Test set: Average loss: 1.4379, Accuracy: 1958/5000 (39%)
[epoch 19] loss: 0.5848028
Test set: Average loss: 1.4359, Accuracy: 1964/5000 (39%)
[epoch 20] loss: 0.5672931
Test set: Average loss: 1.4343, Accuracy: 1967/5000 (39%)
[epoch 21] loss: 0.5510460
Test set: Average loss: 1.4328, Accuracy: 1965/5000 (39%)
[epoch 22] loss: 0.5359628
Test set: Average loss: 1.4317, Accuracy: 1969/5000 (39%)
[epoch 23] loss: 0.5219494
Test set: Average loss: 1.4308, Accuracy: 1973/5000 (39%)
[epoch 24] loss: 0.5089015
Test set: Average loss: 1.4302, Accuracy: 1979/5000 (40%)
[epoch 25] loss: 0.4967016
Test set: Average loss: 1.4298, Accuracy: 1984/5000 (40%)
Validation:
Test set: Average loss: 1.4298, Accuracy: 1984/5000 (40%)
Test
Test set: Average loss: 1.4478, Accuracy: 1963/5000 (39%)
Test set: Average loss: 0.4852, Accuracy: 25/25 (100%)
## seed: 13
Validation accuracy before training:
Test set: Average loss: 1.6245, Accuracy: 1083/5000 (22%)
[epoch 1] loss: 1.6205413
Test set: Average loss: 1.5746, Accuracy: 1377/5000 (28%)
[epoch 2] loss: 1.4701827
Test set: Average loss: 1.5369, Accuracy: 1586/5000 (32%)
[epoch 3] loss: 1.3388505
Test set: Average loss: 1.5089, Accuracy: 1750/5000 (35%)
[epoch 4] loss: 1.2246710
Test set: Average loss: 1.4880, Accuracy: 1820/5000 (36%)
[epoch 5] loss: 1.1249527
Test set: Average loss: 1.4722, Accuracy: 1864/5000 (37%)
[epoch 6] loss: 1.0373999
Test set: Average loss: 1.4600, Accuracy: 1880/5000 (38%)
[epoch 7] loss: 0.9602933
Test set: Average loss: 1.4505, Accuracy: 1893/5000 (38%)
[epoch 8] loss: 0.8923160
Test set: Average loss: 1.4430, Accuracy: 1903/5000 (38%)
[epoch 9] loss: 0.8323637
Test set: Average loss: 1.4370, Accuracy: 1919/5000 (38%)
[epoch 10] loss: 0.7794478
Test set: Average loss: 1.4322, Accuracy: 1935/5000 (39%)
[epoch 11] loss: 0.7326616
Test set: Average loss: 1.4284, Accuracy: 1945/5000 (39%)
[epoch 12] loss: 0.6911566
Test set: Average loss: 1.4254, Accuracy: 1939/5000 (39%)
[epoch 13] loss: 0.6541435
Test set: Average loss: 1.4230, Accuracy: 1938/5000 (39%)
[epoch 14] loss: 0.6209322
Test set: Average loss: 1.4211, Accuracy: 1937/5000 (39%)
[epoch 15] loss: 0.5909682
Test set: Average loss: 1.4198, Accuracy: 1933/5000 (39%)
[epoch 16] loss: 0.5638276
Test set: Average loss: 1.4188, Accuracy: 1940/5000 (39%)
[epoch 17] loss: 0.5391843
Test set: Average loss: 1.4183, Accuracy: 1940/5000 (39%)
[epoch 18] loss: 0.5167716
Test set: Average loss: 1.4182, Accuracy: 1940/5000 (39%)
[epoch 19] loss: 0.4963500
Test set: Average loss: 1.4183, Accuracy: 1947/5000 (39%)
[epoch 20] loss: 0.4776919
Test set: Average loss: 1.4187, Accuracy: 1945/5000 (39%)
[epoch 21] loss: 0.4605834
Test set: Average loss: 1.4193, Accuracy: 1951/5000 (39%)
[epoch 22] loss: 0.4448397
Test set: Average loss: 1.4201, Accuracy: 1967/5000 (39%)
[epoch 23] loss: 0.4303172
Test set: Average loss: 1.4209, Accuracy: 1967/5000 (39%)
[epoch 24] loss: 0.4169113
Test set: Average loss: 1.4218, Accuracy: 1959/5000 (39%)
[epoch 25] loss: 0.4045425
Test set: Average loss: 1.4228, Accuracy: 1960/5000 (39%)
Validation:
Test set: Average loss: 1.4209, Accuracy: 1967/5000 (39%)
Test
Test set: Average loss: 1.4280, Accuracy: 1910/5000 (38%)
Test set: Average loss: 0.4169, Accuracy: 25/25 (100%)
50
## seed: 11
Validation accuracy before training:
Test set: Average loss: 1.6302, Accuracy: 837/5000 (17%)
[epoch 1] loss: 1.5856776
Test set: Average loss: 1.5358, Accuracy: 1456/5000 (29%)
[epoch 2] loss: 1.3951727
Test set: Average loss: 1.4935, Accuracy: 1560/5000 (31%)
[epoch 3] loss: 1.2423961
Test set: Average loss: 1.4676, Accuracy: 1611/5000 (32%)
[epoch 4] loss: 1.1774579
Test set: Average loss: 1.4500, Accuracy: 1677/5000 (34%)
[epoch 5] loss: 1.0504357
Test set: Average loss: 1.4346, Accuracy: 1720/5000 (34%)
[epoch 6] loss: 0.9979576
Test set: Average loss: 1.4220, Accuracy: 1796/5000 (36%)
[epoch 7] loss: 0.9043089
Test set: Average loss: 1.4129, Accuracy: 1835/5000 (37%)
[epoch 8] loss: 0.8799956
Test set: Average loss: 1.4080, Accuracy: 1875/5000 (38%)
[epoch 9] loss: 0.8194996
Test set: Average loss: 1.4060, Accuracy: 1887/5000 (38%)
[epoch 10] loss: 0.7824776
Test set: Average loss: 1.4052, Accuracy: 1911/5000 (38%)
[epoch 11] loss: 0.7406251
Test set: Average loss: 1.4054, Accuracy: 1910/5000 (38%)
[epoch 12] loss: 0.7062769
Test set: Average loss: 1.4065, Accuracy: 1925/5000 (38%)
[epoch 13] loss: 0.6682979
Test set: Average loss: 1.4080, Accuracy: 1913/5000 (38%)
[epoch 14] loss: 0.6572289
Test set: Average loss: 1.4093, Accuracy: 1910/5000 (38%)
[epoch 15] loss: 0.6145761
Test set: Average loss: 1.4117, Accuracy: 1914/5000 (38%)
[epoch 16] loss: 0.5896147
Test set: Average loss: 1.4138, Accuracy: 1907/5000 (38%)
[epoch 17] loss: 0.5551677
Test set: Average loss: 1.4148, Accuracy: 1908/5000 (38%)
[epoch 18] loss: 0.5382254
Test set: Average loss: 1.4164, Accuracy: 1913/5000 (38%)
[epoch 19] loss: 0.5204682
Test set: Average loss: 1.4180, Accuracy: 1923/5000 (38%)
[epoch 20] loss: 0.5054998
Test set: Average loss: 1.4188, Accuracy: 1929/5000 (39%)
[epoch 21] loss: 0.5029185
Test set: Average loss: 1.4202, Accuracy: 1927/5000 (39%)
[epoch 22] loss: 0.4645511
Test set: Average loss: 1.4214, Accuracy: 1925/5000 (38%)
[epoch 23] loss: 0.4625830
Test set: Average loss: 1.4228, Accuracy: 1925/5000 (38%)
[epoch 24] loss: 0.4517629
Test set: Average loss: 1.4234, Accuracy: 1937/5000 (39%)
[epoch 25] loss: 0.4434632
Test set: Average loss: 1.4245, Accuracy: 1945/5000 (39%)
Validation:
Test set: Average loss: 1.4245, Accuracy: 1945/5000 (39%)
Test
Test set: Average loss: 1.4205, Accuracy: 1951/5000 (39%)
Test set: Average loss: 0.4311, Accuracy: 50/50 (100%)
## seed: 12
Validation accuracy before training:
Test set: Average loss: 1.6318, Accuracy: 876/5000 (18%)
[epoch 1] loss: 1.5824564
Test set: Average loss: 1.5571, Accuracy: 1399/5000 (28%)
[epoch 2] loss: 1.3495969
Test set: Average loss: 1.5133, Accuracy: 1609/5000 (32%)
[epoch 3] loss: 1.2455499
Test set: Average loss: 1.4968, Accuracy: 1666/5000 (33%)
[epoch 4] loss: 1.1330004
Test set: Average loss: 1.4837, Accuracy: 1701/5000 (34%)
[epoch 5] loss: 1.0515088
Test set: Average loss: 1.4772, Accuracy: 1743/5000 (35%)
[epoch 6] loss: 0.9789051
Test set: Average loss: 1.4728, Accuracy: 1769/5000 (35%)
[epoch 7] loss: 0.9331170
Test set: Average loss: 1.4676, Accuracy: 1820/5000 (36%)
[epoch 8] loss: 0.8893935
Test set: Average loss: 1.4632, Accuracy: 1826/5000 (37%)
[epoch 9] loss: 0.8311774
Test set: Average loss: 1.4581, Accuracy: 1878/5000 (38%)
[epoch 10] loss: 0.7952718
Test set: Average loss: 1.4540, Accuracy: 1911/5000 (38%)
[epoch 11] loss: 0.7539811
Test set: Average loss: 1.4501, Accuracy: 1928/5000 (39%)
[epoch 12] loss: 0.7170182
Test set: Average loss: 1.4473, Accuracy: 1968/5000 (39%)
[epoch 13] loss: 0.6959983
Test set: Average loss: 1.4472, Accuracy: 1985/5000 (40%)
[epoch 14] loss: 0.6696663
Test set: Average loss: 1.4475, Accuracy: 1995/5000 (40%)
[epoch 15] loss: 0.6560584
Test set: Average loss: 1.4477, Accuracy: 2010/5000 (40%)
[epoch 16] loss: 0.6142949
Test set: Average loss: 1.4485, Accuracy: 2022/5000 (40%)
[epoch 17] loss: 0.5872963
Test set: Average loss: 1.4497, Accuracy: 2023/5000 (40%)
[epoch 18] loss: 0.5847451
Test set: Average loss: 1.4493, Accuracy: 2022/5000 (40%)
[epoch 19] loss: 0.5653303
Test set: Average loss: 1.4477, Accuracy: 2027/5000 (41%)
[epoch 20] loss: 0.5375126
Test set: Average loss: 1.4444, Accuracy: 2041/5000 (41%)
[epoch 21] loss: 0.5250742
Test set: Average loss: 1.4400, Accuracy: 2060/5000 (41%)
[epoch 22] loss: 0.5028962
Test set: Average loss: 1.4364, Accuracy: 2076/5000 (42%)
[epoch 23] loss: 0.4931792
Test set: Average loss: 1.4355, Accuracy: 2074/5000 (41%)
[epoch 24] loss: 0.4874282
Test set: Average loss: 1.4354, Accuracy: 2077/5000 (42%)
[epoch 25] loss: 0.4640639
Test set: Average loss: 1.4354, Accuracy: 2065/5000 (41%)
Validation:
Test set: Average loss: 1.4354, Accuracy: 2077/5000 (42%)
Test
Test set: Average loss: 1.4405, Accuracy: 2116/5000 (42%)
Test set: Average loss: 0.4749, Accuracy: 50/50 (100%)
## seed: 13
Validation accuracy before training:
Test set: Average loss: 1.6314, Accuracy: 776/5000 (16%)
[epoch 1] loss: 1.6084003
Test set: Average loss: 1.5433, Accuracy: 1582/5000 (32%)
[epoch 2] loss: 1.4098511
Test set: Average loss: 1.4936, Accuracy: 1771/5000 (35%)
[epoch 3] loss: 1.2832270
Test set: Average loss: 1.4630, Accuracy: 1930/5000 (39%)
[epoch 4] loss: 1.1612636
Test set: Average loss: 1.4403, Accuracy: 2022/5000 (40%)
[epoch 5] loss: 1.0801458
Test set: Average loss: 1.4225, Accuracy: 2078/5000 (42%)
[epoch 6] loss: 1.0203575
Test set: Average loss: 1.4087, Accuracy: 2139/5000 (43%)
[epoch 7] loss: 0.9721288
Test set: Average loss: 1.3971, Accuracy: 2187/5000 (44%)
[epoch 8] loss: 0.9216114
Test set: Average loss: 1.3876, Accuracy: 2233/5000 (45%)
[epoch 9] loss: 0.8810652
Test set: Average loss: 1.3794, Accuracy: 2269/5000 (45%)
[epoch 10] loss: 0.8282197
Test set: Average loss: 1.3720, Accuracy: 2294/5000 (46%)
[epoch 11] loss: 0.7928513
Test set: Average loss: 1.3668, Accuracy: 2302/5000 (46%)
[epoch 12] loss: 0.7590639
Test set: Average loss: 1.3641, Accuracy: 2303/5000 (46%)
[epoch 13] loss: 0.7333866
Test set: Average loss: 1.3625, Accuracy: 2302/5000 (46%)
[epoch 14] loss: 0.6935290
Test set: Average loss: 1.3612, Accuracy: 2302/5000 (46%)
[epoch 15] loss: 0.6798384
Test set: Average loss: 1.3602, Accuracy: 2307/5000 (46%)
[epoch 16] loss: 0.6491446
Test set: Average loss: 1.3598, Accuracy: 2303/5000 (46%)
[epoch 17] loss: 0.6453786
Test set: Average loss: 1.3590, Accuracy: 2309/5000 (46%)
[epoch 18] loss: 0.6216214
Test set: Average loss: 1.3581, Accuracy: 2312/5000 (46%)
[epoch 19] loss: 0.6042722
Test set: Average loss: 1.3568, Accuracy: 2317/5000 (46%)
[epoch 20] loss: 0.5725254
Test set: Average loss: 1.3554, Accuracy: 2317/5000 (46%)
[epoch 21] loss: 0.5583854
Test set: Average loss: 1.3546, Accuracy: 2318/5000 (46%)
[epoch 22] loss: 0.5417939
Test set: Average loss: 1.3537, Accuracy: 2322/5000 (46%)
[epoch 23] loss: 0.5348731
Test set: Average loss: 1.3532, Accuracy: 2318/5000 (46%)
[epoch 24] loss: 0.5279661
Test set: Average loss: 1.3530, Accuracy: 2314/5000 (46%)
[epoch 25] loss: 0.5023626
Test set: Average loss: 1.3530, Accuracy: 2315/5000 (46%)
Validation:
Test set: Average loss: 1.3537, Accuracy: 2322/5000 (46%)
Test
Test set: Average loss: 1.3680, Accuracy: 2288/5000 (46%)
Test set: Average loss: 0.5356, Accuracy: 50/50 (100%)
100
## seed: 11
Validation accuracy before training:
Test set: Average loss: 1.6241, Accuracy: 946/5000 (19%)
[epoch 1] loss: 1.5996981
Test set: Average loss: 1.4845, Accuracy: 1912/5000 (38%)
[epoch 2] loss: 1.3109976
Test set: Average loss: 1.4366, Accuracy: 1997/5000 (40%)
[epoch 3] loss: 1.1913936
Test set: Average loss: 1.4166, Accuracy: 2009/5000 (40%)
[epoch 4] loss: 1.1425679
Test set: Average loss: 1.4072, Accuracy: 1986/5000 (40%)
[epoch 5] loss: 1.1098128
Test set: Average loss: 1.4074, Accuracy: 1934/5000 (39%)
[epoch 6] loss: 1.0024914
Test set: Average loss: 1.4032, Accuracy: 1954/5000 (39%)
[epoch 7] loss: 0.9336567
Test set: Average loss: 1.4005, Accuracy: 1970/5000 (39%)
[epoch 8] loss: 0.9738812
Epoch 7: reducing learning rate of group 0 to 5.0000e-06.
Test set: Average loss: 1.3950, Accuracy: 2005/5000 (40%)
[epoch 9] loss: 0.9416373
Epoch 8: reducing learning rate of group 0 to 5.0000e-07.
Test set: Average loss: 1.3941, Accuracy: 2009/5000 (40%)
[epoch 10] loss: 0.9047675
Test set: Average loss: 1.3939, Accuracy: 2011/5000 (40%)
[epoch 11] loss: 0.8551131
Test set: Average loss: 1.3938, Accuracy: 2012/5000 (40%)
[epoch 12] loss: 0.9287594
Epoch 11: reducing learning rate of group 0 to 5.0000e-08.
Test set: Average loss: 1.3936, Accuracy: 2015/5000 (40%)
[epoch 13] loss: 0.8798064
Epoch 12: reducing learning rate of group 0 to 5.0000e-09.
Test set: Average loss: 1.3936, Accuracy: 2015/5000 (40%)
[epoch 14] loss: 0.8512895
Test set: Average loss: 1.3936, Accuracy: 2015/5000 (40%)
[epoch 15] loss: 0.9423248
Epoch 14: reducing learning rate of group 0 to 5.0000e-10.
Test set: Average loss: 1.3936, Accuracy: 2015/5000 (40%)
[epoch 16] loss: 0.9397828
Epoch 15: reducing learning rate of group 0 to 5.0000e-11.
Test set: Average loss: 1.3936, Accuracy: 2015/5000 (40%)
[epoch 17] loss: 0.9438496
Epoch 16: reducing learning rate of group 0 to 5.0000e-12.
Test set: Average loss: 1.3936, Accuracy: 2015/5000 (40%)
[epoch 18] loss: 0.8838063
Epoch 17: reducing learning rate of group 0 to 5.0000e-13.
Test set: Average loss: 1.3936, Accuracy: 2015/5000 (40%)
[epoch 19] loss: 1.0079089
Epoch 18: reducing learning rate of group 0 to 5.0000e-14.
Test set: Average loss: 1.3936, Accuracy: 2015/5000 (40%)
[epoch 20] loss: 0.9404762
Epoch 19: reducing learning rate of group 0 to 5.0000e-15.
Test set: Average loss: 1.3936, Accuracy: 2015/5000 (40%)
[epoch 21] loss: 0.9242013
Epoch 20: reducing learning rate of group 0 to 5.0000e-16.
Test set: Average loss: 1.3936, Accuracy: 2015/5000 (40%)
[epoch 22] loss: 0.9557844
Epoch 21: reducing learning rate of group 0 to 5.0000e-17.
Test set: Average loss: 1.3936, Accuracy: 2015/5000 (40%)
[epoch 23] loss: 0.8734948
Epoch 22: reducing learning rate of group 0 to 5.0000e-18.
Test set: Average loss: 1.3936, Accuracy: 2015/5000 (40%)
[epoch 24] loss: 0.8799165
Epoch 23: reducing learning rate of group 0 to 5.0000e-19.
Test set: Average loss: 1.3936, Accuracy: 2015/5000 (40%)
[epoch 25] loss: 0.9340353
Epoch 24: reducing learning rate of group 0 to 5.0000e-20.
Test set: Average loss: 1.3936, Accuracy: 2015/5000 (40%)
Validation:
Test set: Average loss: 1.3936, Accuracy: 2015/5000 (40%)
Test
Test set: Average loss: 1.4094, Accuracy: 1941/5000 (39%)
Test set: Average loss: 0.8912, Accuracy: 82/100 (82%)
## seed: 12
Validation accuracy before training:
Test set: Average loss: 1.5871, Accuracy: 1227/5000 (25%)
[epoch 1] loss: 1.5274837
Test set: Average loss: 1.4793, Accuracy: 1751/5000 (35%)
[epoch 2] loss: 1.2905994
Test set: Average loss: 1.4421, Accuracy: 1841/5000 (37%)
[epoch 3] loss: 1.1610743
Test set: Average loss: 1.4181, Accuracy: 1941/5000 (39%)
[epoch 4] loss: 1.1398463
Test set: Average loss: 1.4040, Accuracy: 1992/5000 (40%)
[epoch 5] loss: 1.0726686
Test set: Average loss: 1.3941, Accuracy: 2016/5000 (40%)
[epoch 6] loss: 0.9795179
Test set: Average loss: 1.3816, Accuracy: 2069/5000 (41%)
[epoch 7] loss: 0.9668684
Test set: Average loss: 1.3723, Accuracy: 2095/5000 (42%)
[epoch 8] loss: 0.8634666
Test set: Average loss: 1.3658, Accuracy: 2124/5000 (42%)
[epoch 9] loss: 0.9251318
Epoch 8: reducing learning rate of group 0 to 5.0000e-06.
Test set: Average loss: 1.3624, Accuracy: 2133/5000 (43%)
[epoch 10] loss: 0.9194778
Epoch 9: reducing learning rate of group 0 to 5.0000e-07.
Test set: Average loss: 1.3621, Accuracy: 2134/5000 (43%)
[epoch 11] loss: 0.8898745
Epoch 10: reducing learning rate of group 0 to 5.0000e-08.
Test set: Average loss: 1.3620, Accuracy: 2134/5000 (43%)
[epoch 12] loss: 0.8113071
Test set: Average loss: 1.3620, Accuracy: 2134/5000 (43%)
[epoch 13] loss: 0.8453797
Epoch 12: reducing learning rate of group 0 to 5.0000e-09.
Test set: Average loss: 1.3620, Accuracy: 2134/5000 (43%)
[epoch 14] loss: 0.7970396
Test set: Average loss: 1.3620, Accuracy: 2134/5000 (43%)
[epoch 15] loss: 0.8103886
Epoch 14: reducing learning rate of group 0 to 5.0000e-10.
Test set: Average loss: 1.3620, Accuracy: 2134/5000 (43%)
[epoch 16] loss: 0.8047890
Epoch 15: reducing learning rate of group 0 to 5.0000e-11.
Test set: Average loss: 1.3620, Accuracy: 2134/5000 (43%)
[epoch 17] loss: 0.8733665
Epoch 16: reducing learning rate of group 0 to 5.0000e-12.
Test set: Average loss: 1.3620, Accuracy: 2134/5000 (43%)
[epoch 18] loss: 0.9254666
Epoch 17: reducing learning rate of group 0 to 5.0000e-13.
Test set: Average loss: 1.3620, Accuracy: 2134/5000 (43%)
[epoch 19] loss: 0.8562478
Epoch 18: reducing learning rate of group 0 to 5.0000e-14.
Test set: Average loss: 1.3620, Accuracy: 2134/5000 (43%)
[epoch 20] loss: 0.8581643
Epoch 19: reducing learning rate of group 0 to 5.0000e-15.
Test set: Average loss: 1.3620, Accuracy: 2134/5000 (43%)
[epoch 21] loss: 0.8022254
Epoch 20: reducing learning rate of group 0 to 5.0000e-16.
Test set: Average loss: 1.3620, Accuracy: 2134/5000 (43%)
[epoch 22] loss: 0.9045701
Epoch 21: reducing learning rate of group 0 to 5.0000e-17.
Test set: Average loss: 1.3620, Accuracy: 2134/5000 (43%)
[epoch 23] loss: 0.8229158
Epoch 22: reducing learning rate of group 0 to 5.0000e-18.
Test set: Average loss: 1.3620, Accuracy: 2134/5000 (43%)
[epoch 24] loss: 0.8245636
Epoch 23: reducing learning rate of group 0 to 5.0000e-19.
Test set: Average loss: 1.3620, Accuracy: 2134/5000 (43%)
[epoch 25] loss: 0.8102147
Epoch 24: reducing learning rate of group 0 to 5.0000e-20.
Test set: Average loss: 1.3620, Accuracy: 2134/5000 (43%)
Validation:
Test set: Average loss: 1.3620, Accuracy: 2134/5000 (43%)
Test
Test set: Average loss: 1.3669, Accuracy: 2072/5000 (41%)
Test set: Average loss: 0.8494, Accuracy: 77/100 (77%)
## seed: 13
Validation accuracy before training:
Test set: Average loss: 1.6081, Accuracy: 1097/5000 (22%)
[epoch 1] loss: 1.4733073
Test set: Average loss: 1.4701, Accuracy: 1885/5000 (38%)
[epoch 2] loss: 1.2340238
Test set: Average loss: 1.4259, Accuracy: 1898/5000 (38%)
[epoch 3] loss: 1.2106412
Test set: Average loss: 1.4045, Accuracy: 1987/5000 (40%)
[epoch 4] loss: 1.1866457
Test set: Average loss: 1.3883, Accuracy: 2083/5000 (42%)
[epoch 5] loss: 1.0542102
Test set: Average loss: 1.3748, Accuracy: 2196/5000 (44%)
[epoch 6] loss: 1.0116897
Test set: Average loss: 1.3685, Accuracy: 2236/5000 (45%)
[epoch 7] loss: 1.0207085
Epoch 6: reducing learning rate of group 0 to 5.0000e-06.
Test set: Average loss: 1.3633, Accuracy: 2238/5000 (45%)
[epoch 8] loss: 0.9690778
Test set: Average loss: 1.3628, Accuracy: 2231/5000 (45%)
[epoch 9] loss: 0.8724197
Test set: Average loss: 1.3619, Accuracy: 2225/5000 (44%)
[epoch 10] loss: 0.9562372
Epoch 9: reducing learning rate of group 0 to 5.0000e-07.
Test set: Average loss: 1.3608, Accuracy: 2227/5000 (45%)
[epoch 11] loss: 0.9793760
Epoch 10: reducing learning rate of group 0 to 5.0000e-08.
Test set: Average loss: 1.3606, Accuracy: 2227/5000 (45%)
[epoch 12] loss: 0.9632209
Epoch 11: reducing learning rate of group 0 to 5.0000e-09.
Test set: Average loss: 1.3606, Accuracy: 2226/5000 (45%)
[epoch 13] loss: 0.8897594
Epoch 12: reducing learning rate of group 0 to 5.0000e-10.
Test set: Average loss: 1.3606, Accuracy: 2226/5000 (45%)
[epoch 14] loss: 0.8808621
Epoch 13: reducing learning rate of group 0 to 5.0000e-11.
Test set: Average loss: 1.3606, Accuracy: 2226/5000 (45%)
[epoch 15] loss: 0.8975927
Epoch 14: reducing learning rate of group 0 to 5.0000e-12.
Test set: Average loss: 1.3606, Accuracy: 2226/5000 (45%)
[epoch 16] loss: 0.8856090
Epoch 15: reducing learning rate of group 0 to 5.0000e-13.
Test set: Average loss: 1.3606, Accuracy: 2226/5000 (45%)
[epoch 17] loss: 0.8711508
Test set: Average loss: 1.3606, Accuracy: 2226/5000 (45%)
[epoch 18] loss: 0.9403014
Epoch 17: reducing learning rate of group 0 to 5.0000e-14.
Test set: Average loss: 1.3606, Accuracy: 2226/5000 (45%)
[epoch 19] loss: 0.9589891
Epoch 18: reducing learning rate of group 0 to 5.0000e-15.
Test set: Average loss: 1.3606, Accuracy: 2226/5000 (45%)
[epoch 20] loss: 0.9539529
Epoch 19: reducing learning rate of group 0 to 5.0000e-16.
Test set: Average loss: 1.3606, Accuracy: 2226/5000 (45%)
[epoch 21] loss: 0.9029560
Epoch 20: reducing learning rate of group 0 to 5.0000e-17.
Test set: Average loss: 1.3606, Accuracy: 2226/5000 (45%)
[epoch 22] loss: 1.0083645
Epoch 21: reducing learning rate of group 0 to 5.0000e-18.
Test set: Average loss: 1.3606, Accuracy: 2226/5000 (45%)
[epoch 23] loss: 0.9532997
Epoch 22: reducing learning rate of group 0 to 5.0000e-19.
Test set: Average loss: 1.3606, Accuracy: 2226/5000 (45%)
[epoch 24] loss: 0.8915029
Epoch 23: reducing learning rate of group 0 to 5.0000e-20.
Test set: Average loss: 1.3606, Accuracy: 2226/5000 (45%)
[epoch 25] loss: 0.9688419
Epoch 24: reducing learning rate of group 0 to 5.0000e-21.
Test set: Average loss: 1.3606, Accuracy: 2226/5000 (45%)
Validation:
Test set: Average loss: 1.3633, Accuracy: 2238/5000 (45%)
Test
Test set: Average loss: 1.3819, Accuracy: 2147/5000 (43%)
Test set: Average loss: 0.9491, Accuracy: 73/100 (73%)
250
## seed: 11
Validation accuracy before training:
Test set: Average loss: 1.6552, Accuracy: 825/5000 (16%)
[epoch 1] loss: 1.5585337
Test set: Average loss: 1.4273, Accuracy: 2060/5000 (41%)
[epoch 2] loss: 1.3271799
Test set: Average loss: 1.3566, Accuracy: 2261/5000 (45%)
[epoch 3] loss: 1.2275444
Test set: Average loss: 1.3202, Accuracy: 2345/5000 (47%)
[epoch 4] loss: 1.1439376
Test set: Average loss: 1.2951, Accuracy: 2461/5000 (49%)
[epoch 5] loss: 1.0877908
Test set: Average loss: 1.2820, Accuracy: 2543/5000 (51%)
[epoch 6] loss: 1.0355314
Test set: Average loss: 1.2717, Accuracy: 2542/5000 (51%)
[epoch 7] loss: 0.9927098
Test set: Average loss: 1.2673, Accuracy: 2552/5000 (51%)
[epoch 8] loss: 0.9554188
Test set: Average loss: 1.2616, Accuracy: 2578/5000 (52%)
[epoch 9] loss: 0.9180267
Test set: Average loss: 1.2539, Accuracy: 2591/5000 (52%)
[epoch 10] loss: 0.8905783
Test set: Average loss: 1.2493, Accuracy: 2617/5000 (52%)
[epoch 11] loss: 0.8569407
Test set: Average loss: 1.2480, Accuracy: 2612/5000 (52%)
[epoch 12] loss: 0.8237647
Test set: Average loss: 1.2482, Accuracy: 2609/5000 (52%)
[epoch 13] loss: 0.7987312
Test set: Average loss: 1.2479, Accuracy: 2612/5000 (52%)
[epoch 14] loss: 0.7746444
Test set: Average loss: 1.2396, Accuracy: 2666/5000 (53%)
[epoch 15] loss: 0.7490405
Test set: Average loss: 1.2395, Accuracy: 2656/5000 (53%)
[epoch 16] loss: 0.7271680
Test set: Average loss: 1.2416, Accuracy: 2625/5000 (52%)
[epoch 17] loss: 0.7001111
Test set: Average loss: 1.2415, Accuracy: 2635/5000 (53%)
[epoch 18] loss: 0.6784342
Test set: Average loss: 1.2390, Accuracy: 2662/5000 (53%)
[epoch 19] loss: 0.6560714
Test set: Average loss: 1.2385, Accuracy: 2639/5000 (53%)
[epoch 20] loss: 0.6400668
Test set: Average loss: 1.2427, Accuracy: 2626/5000 (53%)
[epoch 21] loss: 0.6172998
Test set: Average loss: 1.2407, Accuracy: 2631/5000 (53%)
[epoch 22] loss: 0.5990516
Test set: Average loss: 1.2388, Accuracy: 2630/5000 (53%)
[epoch 23] loss: 0.5825677
Test set: Average loss: 1.2389, Accuracy: 2628/5000 (53%)
[epoch 24] loss: 0.5652138
Test set: Average loss: 1.2395, Accuracy: 2607/5000 (52%)
[epoch 25] loss: 0.5479195
Test set: Average loss: 1.2445, Accuracy: 2591/5000 (52%)
Validation:
Test set: Average loss: 1.2396, Accuracy: 2666/5000 (53%)
Test
Test set: Average loss: 1.2457, Accuracy: 2577/5000 (52%)
Test set: Average loss: 0.7521, Accuracy: 214/250 (86%)
## seed: 12
Validation accuracy before training:
Test set: Average loss: 1.6261, Accuracy: 1138/5000 (23%)
[epoch 1] loss: 1.4985954
Test set: Average loss: 1.3940, Accuracy: 2172/5000 (43%)
[epoch 2] loss: 1.2838266
Test set: Average loss: 1.3317, Accuracy: 2246/5000 (45%)
[epoch 3] loss: 1.1702041
Test set: Average loss: 1.2956, Accuracy: 2368/5000 (47%)
[epoch 4] loss: 1.0980945
Test set: Average loss: 1.2788, Accuracy: 2442/5000 (49%)
[epoch 5] loss: 1.0393340
Test set: Average loss: 1.2642, Accuracy: 2480/5000 (50%)
[epoch 6] loss: 0.9849927
Test set: Average loss: 1.2525, Accuracy: 2525/5000 (50%)
[epoch 7] loss: 0.9343408
Test set: Average loss: 1.2372, Accuracy: 2576/5000 (52%)
[epoch 8] loss: 0.8973407
Test set: Average loss: 1.2341, Accuracy: 2567/5000 (51%)
[epoch 9] loss: 0.8632182
Test set: Average loss: 1.2332, Accuracy: 2561/5000 (51%)
[epoch 10] loss: 0.8263620
Test set: Average loss: 1.2303, Accuracy: 2561/5000 (51%)
[epoch 11] loss: 0.7994785
Test set: Average loss: 1.2236, Accuracy: 2583/5000 (52%)
[epoch 12] loss: 0.7689439
Test set: Average loss: 1.2196, Accuracy: 2590/5000 (52%)
[epoch 13] loss: 0.7401604
Test set: Average loss: 1.2130, Accuracy: 2620/5000 (52%)
[epoch 14] loss: 0.7172983
Test set: Average loss: 1.2184, Accuracy: 2589/5000 (52%)
[epoch 15] loss: 0.6876897
Test set: Average loss: 1.2191, Accuracy: 2588/5000 (52%)
[epoch 16] loss: 0.6673110
Test set: Average loss: 1.2140, Accuracy: 2600/5000 (52%)
[epoch 17] loss: 0.6472046
Test set: Average loss: 1.2143, Accuracy: 2599/5000 (52%)
[epoch 18] loss: 0.6258153
Test set: Average loss: 1.2210, Accuracy: 2587/5000 (52%)
[epoch 19] loss: 0.6066347
Test set: Average loss: 1.2126, Accuracy: 2593/5000 (52%)
[epoch 20] loss: 0.5873230
Test set: Average loss: 1.2192, Accuracy: 2566/5000 (51%)
[epoch 21] loss: 0.5709687
Test set: Average loss: 1.2105, Accuracy: 2605/5000 (52%)
[epoch 22] loss: 0.5530377
Test set: Average loss: 1.2143, Accuracy: 2577/5000 (52%)
[epoch 23] loss: 0.5347888
Test set: Average loss: 1.2168, Accuracy: 2579/5000 (52%)
[epoch 24] loss: 0.5224269
Test set: Average loss: 1.2163, Accuracy: 2589/5000 (52%)
[epoch 25] loss: 0.5045308
Test set: Average loss: 1.2122, Accuracy: 2582/5000 (52%)
Validation:
Test set: Average loss: 1.2130, Accuracy: 2620/5000 (52%)
Test
Test set: Average loss: 1.2088, Accuracy: 2633/5000 (53%)
Test set: Average loss: 0.7192, Accuracy: 224/250 (90%)
## seed: 13
Validation accuracy before training:
Test set: Average loss: 1.6199, Accuracy: 898/5000 (18%)
[epoch 1] loss: 1.5333648
Test set: Average loss: 1.3882, Accuracy: 2166/5000 (43%)
[epoch 2] loss: 1.2854341
Test set: Average loss: 1.3280, Accuracy: 2401/5000 (48%)
[epoch 3] loss: 1.1767656
Test set: Average loss: 1.2969, Accuracy: 2459/5000 (49%)
[epoch 4] loss: 1.0962198
Test set: Average loss: 1.2779, Accuracy: 2531/5000 (51%)
[epoch 5] loss: 1.0343131
Test set: Average loss: 1.2701, Accuracy: 2540/5000 (51%)
[epoch 6] loss: 0.9884867
Test set: Average loss: 1.2642, Accuracy: 2550/5000 (51%)
[epoch 7] loss: 0.9431627
Test set: Average loss: 1.2543, Accuracy: 2578/5000 (52%)
[epoch 8] loss: 0.9056988
Test set: Average loss: 1.2501, Accuracy: 2608/5000 (52%)
[epoch 9] loss: 0.8766431
Test set: Average loss: 1.2487, Accuracy: 2605/5000 (52%)
[epoch 10] loss: 0.8384369
Test set: Average loss: 1.2492, Accuracy: 2607/5000 (52%)
[epoch 11] loss: 0.8125487
Test set: Average loss: 1.2443, Accuracy: 2620/5000 (52%)
[epoch 12] loss: 0.7855638
Test set: Average loss: 1.2461, Accuracy: 2595/5000 (52%)
[epoch 13] loss: 0.7565473
Test set: Average loss: 1.2475, Accuracy: 2588/5000 (52%)
[epoch 14] loss: 0.7297684
Test set: Average loss: 1.2461, Accuracy: 2603/5000 (52%)
[epoch 15] loss: 0.7089705
Test set: Average loss: 1.2398, Accuracy: 2630/5000 (53%)
[epoch 16] loss: 0.6797089
Test set: Average loss: 1.2424, Accuracy: 2629/5000 (53%)
[epoch 17] loss: 0.6605714
Test set: Average loss: 1.2454, Accuracy: 2599/5000 (52%)
[epoch 18] loss: 0.6345890
Test set: Average loss: 1.2447, Accuracy: 2611/5000 (52%)
[epoch 19] loss: 0.6162531
Test set: Average loss: 1.2420, Accuracy: 2625/5000 (52%)
[epoch 20] loss: 0.5966830
Test set: Average loss: 1.2492, Accuracy: 2600/5000 (52%)
[epoch 21] loss: 0.5779049
Test set: Average loss: 1.2468, Accuracy: 2604/5000 (52%)
[epoch 22] loss: 0.5607108
Test set: Average loss: 1.2467, Accuracy: 2618/5000 (52%)
[epoch 23] loss: 0.5413038
Test set: Average loss: 1.2499, Accuracy: 2609/5000 (52%)
[epoch 24] loss: 0.5262530
Test set: Average loss: 1.2534, Accuracy: 2586/5000 (52%)
[epoch 25] loss: 0.5047220
Test set: Average loss: 1.2493, Accuracy: 2612/5000 (52%)
Validation:
Test set: Average loss: 1.2398, Accuracy: 2630/5000 (53%)
Test
Test set: Average loss: 1.2520, Accuracy: 2628/5000 (53%)
Test set: Average loss: 0.6853, Accuracy: 232/250 (93%)
500
## seed: 11
Validation accuracy before training:
Test set: Average loss: 1.6452, Accuracy: 905/5000 (18%)
[epoch 1] loss: 1.4602938
Test set: Average loss: 1.3409, Accuracy: 2278/5000 (46%)
[epoch 2] loss: 1.2452528
Test set: Average loss: 1.2795, Accuracy: 2504/5000 (50%)
[epoch 3] loss: 1.1436413
Test set: Average loss: 1.2535, Accuracy: 2557/5000 (51%)
[epoch 4] loss: 1.0753614
Test set: Average loss: 1.2364, Accuracy: 2607/5000 (52%)
[epoch 5] loss: 1.0260562
Test set: Average loss: 1.2236, Accuracy: 2664/5000 (53%)
[epoch 6] loss: 0.9760091
Test set: Average loss: 1.2155, Accuracy: 2639/5000 (53%)
[epoch 7] loss: 0.9407208
Test set: Average loss: 1.2116, Accuracy: 2652/5000 (53%)
[epoch 8] loss: 0.9095462
Test set: Average loss: 1.2029, Accuracy: 2688/5000 (54%)
[epoch 9] loss: 0.8787582
Test set: Average loss: 1.2001, Accuracy: 2694/5000 (54%)
[epoch 10] loss: 0.8385789
Test set: Average loss: 1.1989, Accuracy: 2686/5000 (54%)
[epoch 11] loss: 0.8122715
Test set: Average loss: 1.1980, Accuracy: 2662/5000 (53%)
[epoch 12] loss: 0.7848617
Test set: Average loss: 1.1943, Accuracy: 2680/5000 (54%)
[epoch 13] loss: 0.7592657
Test set: Average loss: 1.1918, Accuracy: 2671/5000 (53%)
[epoch 14] loss: 0.7317394
Test set: Average loss: 1.1905, Accuracy: 2683/5000 (54%)
[epoch 15] loss: 0.7099023
Test set: Average loss: 1.1883, Accuracy: 2691/5000 (54%)
[epoch 16] loss: 0.6888961
Test set: Average loss: 1.1919, Accuracy: 2680/5000 (54%)
[epoch 17] loss: 0.6671172
Test set: Average loss: 1.1902, Accuracy: 2678/5000 (54%)
[epoch 18] loss: 0.6447223
Test set: Average loss: 1.1887, Accuracy: 2665/5000 (53%)
[epoch 19] loss: 0.6226740
Test set: Average loss: 1.1952, Accuracy: 2663/5000 (53%)
[epoch 20] loss: 0.6052283
Test set: Average loss: 1.1888, Accuracy: 2694/5000 (54%)
[epoch 21] loss: 0.5839790
Test set: Average loss: 1.1921, Accuracy: 2668/5000 (53%)
[epoch 22] loss: 0.5638770
Test set: Average loss: 1.1931, Accuracy: 2668/5000 (53%)
[epoch 23] loss: 0.5461366
Test set: Average loss: 1.1948, Accuracy: 2662/5000 (53%)
[epoch 24] loss: 0.5292656
Test set: Average loss: 1.1929, Accuracy: 2665/5000 (53%)
[epoch 25] loss: 0.5128054
Test set: Average loss: 1.1945, Accuracy: 2661/5000 (53%)
Validation:
Test set: Average loss: 1.1888, Accuracy: 2694/5000 (54%)
Test
Test set: Average loss: 1.1971, Accuracy: 2687/5000 (54%)
Test set: Average loss: 0.5804, Accuracy: 465/500 (93%)
## seed: 12
Validation accuracy before training:
Test set: Average loss: 1.6352, Accuracy: 862/5000 (17%)
[epoch 1] loss: 1.4619023
Test set: Average loss: 1.3192, Accuracy: 2381/5000 (48%)
[epoch 2] loss: 1.2441713
Test set: Average loss: 1.2583, Accuracy: 2583/5000 (52%)
[epoch 3] loss: 1.1471256
Test set: Average loss: 1.2304, Accuracy: 2613/5000 (52%)
[epoch 4] loss: 1.0903084
Test set: Average loss: 1.2022, Accuracy: 2753/5000 (55%)
[epoch 5] loss: 1.0335444
Test set: Average loss: 1.1989, Accuracy: 2708/5000 (54%)
[epoch 6] loss: 0.9893398
Test set: Average loss: 1.1901, Accuracy: 2746/5000 (55%)
[epoch 7] loss: 0.9474298
Test set: Average loss: 1.1767, Accuracy: 2800/5000 (56%)
[epoch 8] loss: 0.9151559
Test set: Average loss: 1.1700, Accuracy: 2796/5000 (56%)
[epoch 9] loss: 0.8872456
Test set: Average loss: 1.1696, Accuracy: 2803/5000 (56%)
[epoch 10] loss: 0.8490574
Test set: Average loss: 1.1618, Accuracy: 2810/5000 (56%)
[epoch 11] loss: 0.8215360
Test set: Average loss: 1.1627, Accuracy: 2796/5000 (56%)
[epoch 12] loss: 0.7973644
Test set: Average loss: 1.1573, Accuracy: 2821/5000 (56%)
[epoch 13] loss: 0.7675415
Test set: Average loss: 1.1521, Accuracy: 2824/5000 (56%)
[epoch 14] loss: 0.7408971
Test set: Average loss: 1.1529, Accuracy: 2797/5000 (56%)
[epoch 15] loss: 0.7176292
Test set: Average loss: 1.1509, Accuracy: 2798/5000 (56%)
[epoch 16] loss: 0.6900399
Test set: Average loss: 1.1521, Accuracy: 2783/5000 (56%)
[epoch 17] loss: 0.6716993
Test set: Average loss: 1.1481, Accuracy: 2781/5000 (56%)
[epoch 18] loss: 0.6441175
Test set: Average loss: 1.1491, Accuracy: 2780/5000 (56%)
[epoch 19] loss: 0.6209447
Test set: Average loss: 1.1461, Accuracy: 2794/5000 (56%)
[epoch 20] loss: 0.6003462
Test set: Average loss: 1.1479, Accuracy: 2777/5000 (56%)
[epoch 21] loss: 0.5784590
Test set: Average loss: 1.1427, Accuracy: 2807/5000 (56%)
[epoch 22] loss: 0.5597450
Test set: Average loss: 1.1443, Accuracy: 2808/5000 (56%)
[epoch 23] loss: 0.5425155
Test set: Average loss: 1.1504, Accuracy: 2764/5000 (55%)
[epoch 24] loss: 0.5236644
Test set: Average loss: 1.1412, Accuracy: 2801/5000 (56%)
[epoch 25] loss: 0.5050217
Test set: Average loss: 1.1472, Accuracy: 2779/5000 (56%)
Validation:
Test set: Average loss: 1.1521, Accuracy: 2824/5000 (56%)
Test
Test set: Average loss: 1.1650, Accuracy: 2749/5000 (55%)
Test set: Average loss: 0.7362, Accuracy: 429/500 (86%)
## seed: 13
Validation accuracy before training:
Test set: Average loss: 1.5978, Accuracy: 1201/5000 (24%)
[epoch 1] loss: 1.3800294
Test set: Average loss: 1.3091, Accuracy: 2319/5000 (46%)
[epoch 2] loss: 1.1736107
Test set: Average loss: 1.2524, Accuracy: 2518/5000 (50%)
[epoch 3] loss: 1.0811300
Test set: Average loss: 1.2319, Accuracy: 2583/5000 (52%)
[epoch 4] loss: 1.0236069
Test set: Average loss: 1.2169, Accuracy: 2629/5000 (53%)
[epoch 5] loss: 0.9693821
Test set: Average loss: 1.2070, Accuracy: 2643/5000 (53%)
[epoch 6] loss: 0.9358061
Test set: Average loss: 1.1946, Accuracy: 2710/5000 (54%)
[epoch 7] loss: 0.8930645
Test set: Average loss: 1.1878, Accuracy: 2711/5000 (54%)
[epoch 8] loss: 0.8612807
Test set: Average loss: 1.1800, Accuracy: 2725/5000 (54%)
[epoch 9] loss: 0.8267581
Test set: Average loss: 1.1805, Accuracy: 2736/5000 (55%)
[epoch 10] loss: 0.7921865
Test set: Average loss: 1.1730, Accuracy: 2761/5000 (55%)
[epoch 11] loss: 0.7638725
Test set: Average loss: 1.1689, Accuracy: 2758/5000 (55%)
[epoch 12] loss: 0.7379736
Test set: Average loss: 1.1695, Accuracy: 2751/5000 (55%)
[epoch 13] loss: 0.7132433
Test set: Average loss: 1.1684, Accuracy: 2766/5000 (55%)
[epoch 14] loss: 0.6882078
Test set: Average loss: 1.1679, Accuracy: 2770/5000 (55%)
[epoch 15] loss: 0.6677495
Test set: Average loss: 1.1685, Accuracy: 2750/5000 (55%)
[epoch 16] loss: 0.6422181
Test set: Average loss: 1.1653, Accuracy: 2787/5000 (56%)
[epoch 17] loss: 0.6156202
Test set: Average loss: 1.1681, Accuracy: 2750/5000 (55%)
[epoch 18] loss: 0.5984072
Test set: Average loss: 1.1653, Accuracy: 2802/5000 (56%)
[epoch 19] loss: 0.5772364
Test set: Average loss: 1.1679, Accuracy: 2771/5000 (55%)
[epoch 20] loss: 0.5583889
Test set: Average loss: 1.1691, Accuracy: 2753/5000 (55%)
[epoch 21] loss: 0.5397351
Test set: Average loss: 1.1683, Accuracy: 2770/5000 (55%)
[epoch 22] loss: 0.5195866
Test set: Average loss: 1.1707, Accuracy: 2774/5000 (55%)
[epoch 23] loss: 0.5022107
Test set: Average loss: 1.1737, Accuracy: 2762/5000 (55%)
[epoch 24] loss: 0.4840409
Test set: Average loss: 1.1714, Accuracy: 2777/5000 (56%)
[epoch 25] loss: 0.4674704
Test set: Average loss: 1.1727, Accuracy: 2770/5000 (55%)
Validation:
Test set: Average loss: 1.1653, Accuracy: 2802/5000 (56%)
Test
Test set: Average loss: 1.1827, Accuracy: 2764/5000 (55%)
Test set: Average loss: 0.5747, Accuracy: 461/500 (92%)
750
## seed: 11
Validation accuracy before training:
Test set: Average loss: 1.5970, Accuracy: 1395/5000 (28%)
[epoch 1] loss: 1.3978212
Test set: Average loss: 1.3022, Accuracy: 2368/5000 (47%)
[epoch 2] loss: 1.1819812
Test set: Average loss: 1.2367, Accuracy: 2643/5000 (53%)
[epoch 3] loss: 1.0960607
Test set: Average loss: 1.2088, Accuracy: 2689/5000 (54%)
[epoch 4] loss: 1.0330337
Test set: Average loss: 1.1888, Accuracy: 2747/5000 (55%)
[epoch 5] loss: 0.9828868
Test set: Average loss: 1.1814, Accuracy: 2783/5000 (56%)
[epoch 6] loss: 0.9375991
Test set: Average loss: 1.1759, Accuracy: 2776/5000 (56%)
[epoch 7] loss: 0.8985466
Test set: Average loss: 1.1629, Accuracy: 2800/5000 (56%)
[epoch 8] loss: 0.8649445
Test set: Average loss: 1.1618, Accuracy: 2809/5000 (56%)
[epoch 9] loss: 0.8319343
Test set: Average loss: 1.1576, Accuracy: 2811/5000 (56%)
[epoch 10] loss: 0.7973700
Test set: Average loss: 1.1477, Accuracy: 2833/5000 (57%)
[epoch 11] loss: 0.7704937
Test set: Average loss: 1.1491, Accuracy: 2824/5000 (56%)
[epoch 12] loss: 0.7358840
Test set: Average loss: 1.1433, Accuracy: 2832/5000 (57%)
[epoch 13] loss: 0.7143891
Test set: Average loss: 1.1389, Accuracy: 2854/5000 (57%)
[epoch 14] loss: 0.6910417
Test set: Average loss: 1.1449, Accuracy: 2818/5000 (56%)
[epoch 15] loss: 0.6677136
Test set: Average loss: 1.1412, Accuracy: 2807/5000 (56%)
[epoch 16] loss: 0.6390596
Test set: Average loss: 1.1417, Accuracy: 2832/5000 (57%)
[epoch 17] loss: 0.6129547
Test set: Average loss: 1.1394, Accuracy: 2818/5000 (56%)
[epoch 18] loss: 0.6052706
Test set: Average loss: 1.1331, Accuracy: 2841/5000 (57%)
[epoch 19] loss: 0.5676997
Test set: Average loss: 1.1399, Accuracy: 2832/5000 (57%)
[epoch 20] loss: 0.5455690
Test set: Average loss: 1.1369, Accuracy: 2835/5000 (57%)
[epoch 21] loss: 0.5293557
Test set: Average loss: 1.1422, Accuracy: 2811/5000 (56%)
[epoch 22] loss: 0.5029910
Test set: Average loss: 1.1363, Accuracy: 2828/5000 (57%)
[epoch 23] loss: 0.4883223
Test set: Average loss: 1.1394, Accuracy: 2815/5000 (56%)
[epoch 24] loss: 0.4710492
Test set: Average loss: 1.1460, Accuracy: 2800/5000 (56%)
[epoch 25] loss: 0.4505106
Test set: Average loss: 1.1384, Accuracy: 2837/5000 (57%)
Validation:
Test set: Average loss: 1.1389, Accuracy: 2854/5000 (57%)
Test
Test set: Average loss: 1.1452, Accuracy: 2814/5000 (56%)
Test set: Average loss: 0.6808, Accuracy: 639/750 (85%)
## seed: 12
Validation accuracy before training:
Test set: Average loss: 1.6285, Accuracy: 741/5000 (15%)
[epoch 1] loss: 1.4342224
Test set: Average loss: 1.2866, Accuracy: 2501/5000 (50%)
[epoch 2] loss: 1.2151426
Test set: Average loss: 1.2293, Accuracy: 2677/5000 (54%)
[epoch 3] loss: 1.1293051
Test set: Average loss: 1.2010, Accuracy: 2810/5000 (56%)
[epoch 4] loss: 1.0716503
Test set: Average loss: 1.1805, Accuracy: 2846/5000 (57%)
[epoch 5] loss: 1.0319023
Test set: Average loss: 1.1718, Accuracy: 2847/5000 (57%)
[epoch 6] loss: 0.9795552
Test set: Average loss: 1.1641, Accuracy: 2836/5000 (57%)
[epoch 7] loss: 0.9465007
Test set: Average loss: 1.1614, Accuracy: 2869/5000 (57%)
[epoch 8] loss: 0.9149609
Test set: Average loss: 1.1504, Accuracy: 2891/5000 (58%)
[epoch 9] loss: 0.8804393
Test set: Average loss: 1.1502, Accuracy: 2863/5000 (57%)
[epoch 10] loss: 0.8444084
Test set: Average loss: 1.1416, Accuracy: 2920/5000 (58%)
[epoch 11] loss: 0.8123628
Test set: Average loss: 1.1367, Accuracy: 2919/5000 (58%)
[epoch 12] loss: 0.7822083
Test set: Average loss: 1.1378, Accuracy: 2901/5000 (58%)
[epoch 13] loss: 0.7523709
Test set: Average loss: 1.1342, Accuracy: 2901/5000 (58%)
[epoch 14] loss: 0.7379584
Test set: Average loss: 1.1277, Accuracy: 2918/5000 (58%)
[epoch 15] loss: 0.7015399
Test set: Average loss: 1.1335, Accuracy: 2861/5000 (57%)
[epoch 16] loss: 0.6838216
Test set: Average loss: 1.1397, Accuracy: 2885/5000 (58%)
[epoch 17] loss: 0.6483265
Test set: Average loss: 1.1405, Accuracy: 2841/5000 (57%)
[epoch 18] loss: 0.6233312
Test set: Average loss: 1.1289, Accuracy: 2893/5000 (58%)
[epoch 19] loss: 0.6023934
Test set: Average loss: 1.1425, Accuracy: 2840/5000 (57%)
[epoch 20] loss: 0.5844911
Test set: Average loss: 1.1299, Accuracy: 2890/5000 (58%)
[epoch 21] loss: 0.5544020
Test set: Average loss: 1.1309, Accuracy: 2890/5000 (58%)
[epoch 22] loss: 0.5326705
Test set: Average loss: 1.1370, Accuracy: 2883/5000 (58%)
[epoch 23] loss: 0.5127310
Test set: Average loss: 1.1321, Accuracy: 2865/5000 (57%)
[epoch 24] loss: 0.4946217
Test set: Average loss: 1.1319, Accuracy: 2903/5000 (58%)
[epoch 25] loss: 0.4792588
Test set: Average loss: 1.1345, Accuracy: 2870/5000 (57%)
Validation:
Test set: Average loss: 1.1416, Accuracy: 2920/5000 (58%)
Test
Test set: Average loss: 1.1494, Accuracy: 2828/5000 (57%)
Test set: Average loss: 0.8069, Accuracy: 601/750 (80%)
## seed: 13
Validation accuracy before training:
Test set: Average loss: 1.6392, Accuracy: 897/5000 (18%)
[epoch 1] loss: 1.3924635
Test set: Average loss: 1.3004, Accuracy: 2362/5000 (47%)
[epoch 2] loss: 1.1995032
Test set: Average loss: 1.2358, Accuracy: 2586/5000 (52%)
[epoch 3] loss: 1.1149545
Test set: Average loss: 1.2121, Accuracy: 2696/5000 (54%)
[epoch 4] loss: 1.0566572
Test set: Average loss: 1.1976, Accuracy: 2714/5000 (54%)
[epoch 5] loss: 1.0109860
Test set: Average loss: 1.1808, Accuracy: 2757/5000 (55%)
[epoch 6] loss: 0.9694758
Test set: Average loss: 1.1772, Accuracy: 2782/5000 (56%)
[epoch 7] loss: 0.9409840
Test set: Average loss: 1.1626, Accuracy: 2778/5000 (56%)
[epoch 8] loss: 0.9038036
Test set: Average loss: 1.1642, Accuracy: 2785/5000 (56%)
[epoch 9] loss: 0.8628334
Test set: Average loss: 1.1555, Accuracy: 2822/5000 (56%)
[epoch 10] loss: 0.8343474
Test set: Average loss: 1.1501, Accuracy: 2819/5000 (56%)
[epoch 11] loss: 0.8008807
Test set: Average loss: 1.1521, Accuracy: 2812/5000 (56%)
[epoch 12] loss: 0.7718920
Test set: Average loss: 1.1467, Accuracy: 2806/5000 (56%)
[epoch 13] loss: 0.7494082
Test set: Average loss: 1.1497, Accuracy: 2797/5000 (56%)
[epoch 14] loss: 0.7255725
Test set: Average loss: 1.1439, Accuracy: 2835/5000 (57%)
[epoch 15] loss: 0.6924076
Test set: Average loss: 1.1441, Accuracy: 2817/5000 (56%)
[epoch 16] loss: 0.6628151
Test set: Average loss: 1.1458, Accuracy: 2822/5000 (56%)
[epoch 17] loss: 0.6461694
Test set: Average loss: 1.1407, Accuracy: 2836/5000 (57%)
[epoch 18] loss: 0.6221513
Test set: Average loss: 1.1555, Accuracy: 2771/5000 (55%)
[epoch 19] loss: 0.5961056
Test set: Average loss: 1.1424, Accuracy: 2812/5000 (56%)
[epoch 20] loss: 0.5691049
Test set: Average loss: 1.1459, Accuracy: 2809/5000 (56%)
[epoch 21] loss: 0.5472799
Test set: Average loss: 1.1454, Accuracy: 2823/5000 (56%)
[epoch 22] loss: 0.5292736
Test set: Average loss: 1.1469, Accuracy: 2822/5000 (56%)
[epoch 23] loss: 0.5078203
Test set: Average loss: 1.1424, Accuracy: 2835/5000 (57%)
[epoch 24] loss: 0.4900816
Test set: Average loss: 1.1551, Accuracy: 2797/5000 (56%)
[epoch 25] loss: 0.4717859
Test set: Average loss: 1.1480, Accuracy: 2809/5000 (56%)
Validation:
Test set: Average loss: 1.1407, Accuracy: 2836/5000 (57%)
Test
Test set: Average loss: 1.1496, Accuracy: 2798/5000 (56%)
Test set: Average loss: 0.6143, Accuracy: 679/750 (91%)
1000
## seed: 11
Validation accuracy before training:
Test set: Average loss: 1.6083, Accuracy: 1187/5000 (24%)
[epoch 1] loss: 1.3661503
Test set: Average loss: 1.2724, Accuracy: 2517/5000 (50%)
[epoch 2] loss: 1.1617041
Test set: Average loss: 1.2192, Accuracy: 2696/5000 (54%)
[epoch 3] loss: 1.0912786
Test set: Average loss: 1.1916, Accuracy: 2754/5000 (55%)
[epoch 4] loss: 1.0427513
Test set: Average loss: 1.1742, Accuracy: 2789/5000 (56%)
[epoch 5] loss: 0.9912833
Test set: Average loss: 1.1615, Accuracy: 2834/5000 (57%)
[epoch 6] loss: 0.9543853
Test set: Average loss: 1.1576, Accuracy: 2830/5000 (57%)
[epoch 7] loss: 0.9003936
Test set: Average loss: 1.1538, Accuracy: 2839/5000 (57%)
[epoch 8] loss: 0.8776999
Test set: Average loss: 1.1465, Accuracy: 2845/5000 (57%)
[epoch 9] loss: 0.8391663
Test set: Average loss: 1.1373, Accuracy: 2855/5000 (57%)
[epoch 10] loss: 0.8197465
Test set: Average loss: 1.1390, Accuracy: 2876/5000 (58%)
[epoch 11] loss: 0.7914822
Test set: Average loss: 1.1262, Accuracy: 2887/5000 (58%)
[epoch 12] loss: 0.7479137
Test set: Average loss: 1.1329, Accuracy: 2848/5000 (57%)
[epoch 13] loss: 0.7350573
Test set: Average loss: 1.1239, Accuracy: 2889/5000 (58%)
[epoch 14] loss: 0.7021689
Test set: Average loss: 1.1196, Accuracy: 2880/5000 (58%)
[epoch 15] loss: 0.6742150
Test set: Average loss: 1.1228, Accuracy: 2868/5000 (57%)
[epoch 16] loss: 0.6475729
Test set: Average loss: 1.1100, Accuracy: 2906/5000 (58%)
[epoch 17] loss: 0.6299824
Test set: Average loss: 1.1157, Accuracy: 2878/5000 (58%)
[epoch 18] loss: 0.6011492
Test set: Average loss: 1.1121, Accuracy: 2867/5000 (57%)
[epoch 19] loss: 0.5908023
Test set: Average loss: 1.1140, Accuracy: 2889/5000 (58%)
[epoch 20] loss: 0.5656283
Test set: Average loss: 1.1174, Accuracy: 2882/5000 (58%)
[epoch 21] loss: 0.5285846
Test set: Average loss: 1.1115, Accuracy: 2878/5000 (58%)
[epoch 22] loss: 0.5132487
Test set: Average loss: 1.1126, Accuracy: 2880/5000 (58%)
[epoch 23] loss: 0.4884155
Test set: Average loss: 1.1158, Accuracy: 2868/5000 (57%)
[epoch 24] loss: 0.4731593
Test set: Average loss: 1.1141, Accuracy: 2882/5000 (58%)
[epoch 25] loss: 0.4517535
Test set: Average loss: 1.1131, Accuracy: 2874/5000 (57%)
Validation:
Test set: Average loss: 1.1100, Accuracy: 2906/5000 (58%)
Test
Test set: Average loss: 1.1186, Accuracy: 2886/5000 (58%)
Test set: Average loss: 0.6161, Accuracy: 869/1000 (87%)
## seed: 12
Validation accuracy before training:
Test set: Average loss: 1.6332, Accuracy: 812/5000 (16%)
[epoch 1] loss: 1.3604533
Test set: Average loss: 1.2511, Accuracy: 2570/5000 (51%)
[epoch 2] loss: 1.1666753
Test set: Average loss: 1.2023, Accuracy: 2814/5000 (56%)
[epoch 3] loss: 1.0892988
Test set: Average loss: 1.1696, Accuracy: 2886/5000 (58%)
[epoch 4] loss: 1.0257089
Test set: Average loss: 1.1644, Accuracy: 2858/5000 (57%)
[epoch 5] loss: 0.9919803
Test set: Average loss: 1.1412, Accuracy: 2968/5000 (59%)
[epoch 6] loss: 0.9489922
Test set: Average loss: 1.1362, Accuracy: 2943/5000 (59%)
[epoch 7] loss: 0.9224857
Test set: Average loss: 1.1291, Accuracy: 2930/5000 (59%)
[epoch 8] loss: 0.8757504
Test set: Average loss: 1.1183, Accuracy: 2977/5000 (60%)
[epoch 9] loss: 0.8550629
Test set: Average loss: 1.1179, Accuracy: 2953/5000 (59%)
[epoch 10] loss: 0.8143810
Test set: Average loss: 1.1135, Accuracy: 2976/5000 (60%)
[epoch 11] loss: 0.7848595
Test set: Average loss: 1.1065, Accuracy: 3004/5000 (60%)
[epoch 12] loss: 0.7522093
Test set: Average loss: 1.1083, Accuracy: 2963/5000 (59%)
[epoch 13] loss: 0.7202313
Test set: Average loss: 1.1139, Accuracy: 2945/5000 (59%)
[epoch 14] loss: 0.7040244
Test set: Average loss: 1.1028, Accuracy: 2972/5000 (59%)
[epoch 15] loss: 0.6713891
Test set: Average loss: 1.1014, Accuracy: 2989/5000 (60%)
[epoch 16] loss: 0.6443210
Test set: Average loss: 1.1041, Accuracy: 2946/5000 (59%)
[epoch 17] loss: 0.6236711
Test set: Average loss: 1.1001, Accuracy: 2979/5000 (60%)
[epoch 18] loss: 0.6020300
Test set: Average loss: 1.1076, Accuracy: 2957/5000 (59%)
[epoch 19] loss: 0.5733274
Test set: Average loss: 1.1068, Accuracy: 2944/5000 (59%)
[epoch 20] loss: 0.5455499
Test set: Average loss: 1.0996, Accuracy: 2992/5000 (60%)
[epoch 21] loss: 0.5162927
Test set: Average loss: 1.1021, Accuracy: 2967/5000 (59%)
[epoch 22] loss: 0.5044827
Test set: Average loss: 1.1081, Accuracy: 2968/5000 (59%)
[epoch 23] loss: 0.5026524
Test set: Average loss: 1.1109, Accuracy: 2939/5000 (59%)
[epoch 24] loss: 0.4557751
Test set: Average loss: 1.1102, Accuracy: 2940/5000 (59%)
[epoch 25] loss: 0.4442335
Test set: Average loss: 1.1072, Accuracy: 2967/5000 (59%)
Validation:
Test set: Average loss: 1.1065, Accuracy: 3004/5000 (60%)
Test
Test set: Average loss: 1.1160, Accuracy: 2917/5000 (58%)
Test set: Average loss: 0.7464, Accuracy: 811/1000 (81%)
## seed: 13
Validation accuracy before training:
Test set: Average loss: 1.6270, Accuracy: 935/5000 (19%)
[epoch 1] loss: 1.3672586
Test set: Average loss: 1.2812, Accuracy: 2379/5000 (48%)
[epoch 2] loss: 1.1779289
Test set: Average loss: 1.2114, Accuracy: 2646/5000 (53%)
[epoch 3] loss: 1.0963307
Test set: Average loss: 1.1882, Accuracy: 2743/5000 (55%)
[epoch 4] loss: 1.0488731
Test set: Average loss: 1.1698, Accuracy: 2771/5000 (55%)
[epoch 5] loss: 1.0026818
Test set: Average loss: 1.1590, Accuracy: 2783/5000 (56%)
[epoch 6] loss: 0.9640443
Test set: Average loss: 1.1458, Accuracy: 2842/5000 (57%)
[epoch 7] loss: 0.9326830
Test set: Average loss: 1.1419, Accuracy: 2877/5000 (58%)
[epoch 8] loss: 0.8979785
Test set: Average loss: 1.1338, Accuracy: 2876/5000 (58%)
[epoch 9] loss: 0.8528564
Test set: Average loss: 1.1307, Accuracy: 2858/5000 (57%)
[epoch 10] loss: 0.8286506
Test set: Average loss: 1.1349, Accuracy: 2867/5000 (57%)
[epoch 11] loss: 0.8008218
Test set: Average loss: 1.1304, Accuracy: 2865/5000 (57%)
[epoch 12] loss: 0.7740861
Test set: Average loss: 1.1175, Accuracy: 2886/5000 (58%)
[epoch 13] loss: 0.7425526
Test set: Average loss: 1.1191, Accuracy: 2873/5000 (57%)
[epoch 14] loss: 0.7191085
Test set: Average loss: 1.1173, Accuracy: 2874/5000 (57%)
[epoch 15] loss: 0.6932483
Test set: Average loss: 1.1139, Accuracy: 2900/5000 (58%)
[epoch 16] loss: 0.6712996
Test set: Average loss: 1.1292, Accuracy: 2851/5000 (57%)
[epoch 17] loss: 0.6383469
Test set: Average loss: 1.1244, Accuracy: 2843/5000 (57%)
[epoch 18] loss: 0.6177609
Test set: Average loss: 1.1174, Accuracy: 2895/5000 (58%)
[epoch 19] loss: 0.6023353
Test set: Average loss: 1.1262, Accuracy: 2820/5000 (56%)
[epoch 20] loss: 0.5663707
Test set: Average loss: 1.1175, Accuracy: 2893/5000 (58%)
[epoch 21] loss: 0.5402001
Test set: Average loss: 1.1180, Accuracy: 2874/5000 (57%)
[epoch 22] loss: 0.5196543
Test set: Average loss: 1.1238, Accuracy: 2855/5000 (57%)
[epoch 23] loss: 0.5054229
Test set: Average loss: 1.1324, Accuracy: 2811/5000 (56%)
[epoch 24] loss: 0.4918937
Test set: Average loss: 1.1286, Accuracy: 2847/5000 (57%)
[epoch 25] loss: 0.4567662
Test set: Average loss: 1.1308, Accuracy: 2865/5000 (57%)
Validation:
Test set: Average loss: 1.1139, Accuracy: 2900/5000 (58%)
Test
Test set: Average loss: 1.1349, Accuracy: 2872/5000 (57%)
Test set: Average loss: 0.6557, Accuracy: 877/1000 (88%)
2500
## seed: 11
Validation accuracy before training:
Test set: Average loss: 1.6534, Accuracy: 896/5000 (18%)
[epoch 1] loss: 1.3156698
Test set: Average loss: 1.2035, Accuracy: 2771/5000 (55%)
[epoch 2] loss: 1.1455036
Test set: Average loss: 1.1587, Accuracy: 2839/5000 (57%)
[epoch 3] loss: 1.0704656
Test set: Average loss: 1.1352, Accuracy: 2894/5000 (58%)
[epoch 4] loss: 1.0327430
Test set: Average loss: 1.1101, Accuracy: 3029/5000 (61%)
[epoch 5] loss: 0.9933278
Test set: Average loss: 1.0931, Accuracy: 3042/5000 (61%)
[epoch 6] loss: 0.9491101
Test set: Average loss: 1.0808, Accuracy: 3063/5000 (61%)
[epoch 7] loss: 0.9084175
Test set: Average loss: 1.0711, Accuracy: 3068/5000 (61%)
[epoch 8] loss: 0.8783001
Test set: Average loss: 1.0667, Accuracy: 3052/5000 (61%)
[epoch 9] loss: 0.8542327
Test set: Average loss: 1.0639, Accuracy: 3051/5000 (61%)
[epoch 10] loss: 0.8327308
Test set: Average loss: 1.0506, Accuracy: 3089/5000 (62%)
[epoch 11] loss: 0.7824879
Test set: Average loss: 1.0525, Accuracy: 3082/5000 (62%)
[epoch 12] loss: 0.7510750
Test set: Average loss: 1.0456, Accuracy: 3083/5000 (62%)
[epoch 13] loss: 0.7303125
Test set: Average loss: 1.0491, Accuracy: 3078/5000 (62%)
[epoch 14] loss: 0.7010541
Test set: Average loss: 1.0388, Accuracy: 3098/5000 (62%)
[epoch 15] loss: 0.6694867
Test set: Average loss: 1.0441, Accuracy: 3076/5000 (62%)
[epoch 16] loss: 0.6382100
Test set: Average loss: 1.0354, Accuracy: 3083/5000 (62%)
[epoch 17] loss: 0.6137656
Test set: Average loss: 1.0391, Accuracy: 3079/5000 (62%)
[epoch 18] loss: 0.5812936
Test set: Average loss: 1.0313, Accuracy: 3095/5000 (62%)
[epoch 19] loss: 0.5563477
Test set: Average loss: 1.0346, Accuracy: 3091/5000 (62%)
[epoch 20] loss: 0.5248489
Test set: Average loss: 1.0324, Accuracy: 3102/5000 (62%)
[epoch 21] loss: 0.5014939
Test set: Average loss: 1.0416, Accuracy: 3067/5000 (61%)
[epoch 22] loss: 0.4723435
Test set: Average loss: 1.0389, Accuracy: 3090/5000 (62%)
[epoch 23] loss: 0.4489556
Test set: Average loss: 1.0588, Accuracy: 3035/5000 (61%)
[epoch 24] loss: 0.4173941
Test set: Average loss: 1.0415, Accuracy: 3088/5000 (62%)
[epoch 25] loss: 0.3969340
Test set: Average loss: 1.0424, Accuracy: 3092/5000 (62%)
Validation:
Test set: Average loss: 1.0324, Accuracy: 3102/5000 (62%)
Test
Test set: Average loss: 1.0378, Accuracy: 3020/5000 (60%)
Test set: Average loss: 0.4914, Accuracy: 2239/2500 (90%)
## seed: 12
Validation accuracy before training:
Test set: Average loss: 1.6476, Accuracy: 869/5000 (17%)
[epoch 1] loss: 1.2868893
Test set: Average loss: 1.1926, Accuracy: 2757/5000 (55%)
[epoch 2] loss: 1.1270846
Test set: Average loss: 1.1487, Accuracy: 2894/5000 (58%)
[epoch 3] loss: 1.0604621
Test set: Average loss: 1.1240, Accuracy: 2916/5000 (58%)
[epoch 4] loss: 1.0045322
Test set: Average loss: 1.1018, Accuracy: 2970/5000 (59%)
[epoch 5] loss: 0.9583826
Test set: Average loss: 1.0881, Accuracy: 3021/5000 (60%)
[epoch 6] loss: 0.9137506
Test set: Average loss: 1.0738, Accuracy: 3032/5000 (61%)
[epoch 7] loss: 0.8823251
Test set: Average loss: 1.0769, Accuracy: 3023/5000 (60%)
[epoch 8] loss: 0.8518798
Test set: Average loss: 1.0664, Accuracy: 3024/5000 (60%)
[epoch 9] loss: 0.8171874
Test set: Average loss: 1.0474, Accuracy: 3066/5000 (61%)
[epoch 10] loss: 0.7860287
Test set: Average loss: 1.0469, Accuracy: 3094/5000 (62%)
[epoch 11] loss: 0.7632937
Test set: Average loss: 1.0490, Accuracy: 3055/5000 (61%)
[epoch 12] loss: 0.7246048
Test set: Average loss: 1.0437, Accuracy: 3065/5000 (61%)
[epoch 13] loss: 0.6947242
Test set: Average loss: 1.0361, Accuracy: 3074/5000 (61%)
[epoch 14] loss: 0.6591856
Test set: Average loss: 1.0394, Accuracy: 3087/5000 (62%)
[epoch 15] loss: 0.6272185
Test set: Average loss: 1.0321, Accuracy: 3072/5000 (61%)
[epoch 16] loss: 0.5957334
Test set: Average loss: 1.0230, Accuracy: 3084/5000 (62%)
[epoch 17] loss: 0.5657075
Test set: Average loss: 1.0248, Accuracy: 3077/5000 (62%)
[epoch 18] loss: 0.5329071
Test set: Average loss: 1.0405, Accuracy: 3061/5000 (61%)
[epoch 19] loss: 0.5056315
Test set: Average loss: 1.0258, Accuracy: 3102/5000 (62%)
[epoch 20] loss: 0.4735710
Test set: Average loss: 1.0282, Accuracy: 3084/5000 (62%)
[epoch 21] loss: 0.4440508
Test set: Average loss: 1.0295, Accuracy: 3094/5000 (62%)
[epoch 22] loss: 0.4204389
Test set: Average loss: 1.0349, Accuracy: 3086/5000 (62%)
[epoch 23] loss: 0.3941545
Test set: Average loss: 1.0308, Accuracy: 3066/5000 (61%)
[epoch 24] loss: 0.3687888
Test set: Average loss: 1.0410, Accuracy: 3077/5000 (62%)
[epoch 25] loss: 0.3383198
Test set: Average loss: 1.0364, Accuracy: 3073/5000 (61%)
Validation:
Test set: Average loss: 1.0258, Accuracy: 3102/5000 (62%)
Test
Test set: Average loss: 1.0377, Accuracy: 3050/5000 (61%)
Test set: Average loss: 0.4654, Accuracy: 2276/2500 (91%)
## seed: 13
Validation accuracy before training:
Test set: Average loss: 1.6359, Accuracy: 987/5000 (20%)
[epoch 1] loss: 1.3091902
Test set: Average loss: 1.2224, Accuracy: 2779/5000 (56%)
[epoch 2] loss: 1.1351875
Test set: Average loss: 1.1617, Accuracy: 2938/5000 (59%)
[epoch 3] loss: 1.0736216
Test set: Average loss: 1.1748, Accuracy: 2848/5000 (57%)
[epoch 4] loss: 1.0212087
Test set: Average loss: 1.1144, Accuracy: 2998/5000 (60%)
[epoch 5] loss: 0.9757933
Test set: Average loss: 1.1069, Accuracy: 3006/5000 (60%)
[epoch 6] loss: 0.9429326
Test set: Average loss: 1.0915, Accuracy: 3030/5000 (61%)
[epoch 7] loss: 0.8970576
Test set: Average loss: 1.0835, Accuracy: 3008/5000 (60%)
[epoch 8] loss: 0.8648667
Test set: Average loss: 1.0745, Accuracy: 3044/5000 (61%)
[epoch 9] loss: 0.8274294
Test set: Average loss: 1.0676, Accuracy: 3047/5000 (61%)
[epoch 10] loss: 0.8068528
Test set: Average loss: 1.0733, Accuracy: 3024/5000 (60%)
[epoch 11] loss: 0.7751110
Test set: Average loss: 1.0566, Accuracy: 3035/5000 (61%)
[epoch 12] loss: 0.7451124
Test set: Average loss: 1.0532, Accuracy: 3067/5000 (61%)
[epoch 13] loss: 0.7060572
Test set: Average loss: 1.0501, Accuracy: 3071/5000 (61%)
[epoch 14] loss: 0.6747377
Test set: Average loss: 1.0448, Accuracy: 3080/5000 (62%)
[epoch 15] loss: 0.6467123
Test set: Average loss: 1.0480, Accuracy: 3061/5000 (61%)
[epoch 16] loss: 0.6209014
Test set: Average loss: 1.0373, Accuracy: 3065/5000 (61%)
[epoch 17] loss: 0.5911522
Test set: Average loss: 1.0413, Accuracy: 3051/5000 (61%)
[epoch 18] loss: 0.5638870
Test set: Average loss: 1.0497, Accuracy: 3070/5000 (61%)
[epoch 19] loss: 0.5307635
Test set: Average loss: 1.0420, Accuracy: 3055/5000 (61%)
[epoch 20] loss: 0.5010278
Test set: Average loss: 1.0402, Accuracy: 3063/5000 (61%)
[epoch 21] loss: 0.4727209
Test set: Average loss: 1.0415, Accuracy: 3072/5000 (61%)
[epoch 22] loss: 0.4466301
Test set: Average loss: 1.0479, Accuracy: 3057/5000 (61%)
[epoch 23] loss: 0.4269504
Test set: Average loss: 1.0426, Accuracy: 3076/5000 (62%)
[epoch 24] loss: 0.4003064
Test set: Average loss: 1.0474, Accuracy: 3079/5000 (62%)
[epoch 25] loss: 0.3707116
Test set: Average loss: 1.0457, Accuracy: 3088/5000 (62%)
Validation:
Test set: Average loss: 1.0457, Accuracy: 3088/5000 (62%)
Test
Test set: Average loss: 1.0790, Accuracy: 3028/5000 (61%)
Test set: Average loss: 0.3366, Accuracy: 2369/2500 (95%)
5000
## seed: 11
Validation accuracy before training:
Test set: Average loss: 1.6287, Accuracy: 762/5000 (15%)
[epoch 1] loss: 1.1888783
Test set: Average loss: 1.1069, Accuracy: 2904/5000 (58%)
[epoch 2] loss: 1.0574435
Test set: Average loss: 1.0683, Accuracy: 3008/5000 (60%)
[epoch 3] loss: 1.0012609
Test set: Average loss: 1.0427, Accuracy: 3069/5000 (61%)
[epoch 4] loss: 0.9553717
Test set: Average loss: 1.0344, Accuracy: 3078/5000 (62%)
[epoch 5] loss: 0.9167632
Test set: Average loss: 1.0143, Accuracy: 3133/5000 (63%)
[epoch 6] loss: 0.8791116
Test set: Average loss: 1.0115, Accuracy: 3116/5000 (62%)
[epoch 7] loss: 0.8427375
Test set: Average loss: 1.0062, Accuracy: 3098/5000 (62%)
[epoch 8] loss: 0.8132705
Test set: Average loss: 0.9948, Accuracy: 3150/5000 (63%)
[epoch 9] loss: 0.7786464
Test set: Average loss: 0.9864, Accuracy: 3141/5000 (63%)
[epoch 10] loss: 0.7384688
Test set: Average loss: 0.9834, Accuracy: 3167/5000 (63%)
[epoch 11] loss: 0.7091968
Test set: Average loss: 0.9760, Accuracy: 3194/5000 (64%)
[epoch 12] loss: 0.6708874
Test set: Average loss: 0.9736, Accuracy: 3179/5000 (64%)
[epoch 13] loss: 0.6368315
Test set: Average loss: 0.9667, Accuracy: 3205/5000 (64%)
[epoch 14] loss: 0.6004944
Test set: Average loss: 0.9672, Accuracy: 3217/5000 (64%)
[epoch 15] loss: 0.5649142
Test set: Average loss: 0.9681, Accuracy: 3199/5000 (64%)
[epoch 16] loss: 0.5334563
Test set: Average loss: 0.9739, Accuracy: 3170/5000 (63%)
[epoch 17] loss: 0.4977764
Test set: Average loss: 0.9712, Accuracy: 3181/5000 (64%)
[epoch 18] loss: 0.4570112
Test set: Average loss: 0.9747, Accuracy: 3199/5000 (64%)
[epoch 19] loss: 0.4237855
Test set: Average loss: 0.9715, Accuracy: 3206/5000 (64%)
[epoch 20] loss: 0.3920902
Test set: Average loss: 0.9879, Accuracy: 3148/5000 (63%)
[epoch 21] loss: 0.3600322
Test set: Average loss: 0.9718, Accuracy: 3211/5000 (64%)
[epoch 22] loss: 0.3230789
Test set: Average loss: 0.9938, Accuracy: 3155/5000 (63%)
[epoch 23] loss: 0.2942233
Test set: Average loss: 0.9927, Accuracy: 3197/5000 (64%)
[epoch 24] loss: 0.2642089
Test set: Average loss: 0.9935, Accuracy: 3201/5000 (64%)
[epoch 25] loss: 0.2386525
Test set: Average loss: 0.9965, Accuracy: 3197/5000 (64%)
Validation:
Test set: Average loss: 0.9672, Accuracy: 3217/5000 (64%)
Test
Test set: Average loss: 0.9593, Accuracy: 3187/5000 (64%)
Test set: Average loss: 0.5473, Accuracy: 4266/5000 (85%)
## seed: 12
Validation accuracy before training:
Test set: Average loss: 1.6008, Accuracy: 1108/5000 (22%)
[epoch 1] loss: 1.2279325
Test set: Average loss: 1.1484, Accuracy: 2914/5000 (58%)
[epoch 2] loss: 1.0903444
Test set: Average loss: 1.0859, Accuracy: 3053/5000 (61%)
[epoch 3] loss: 1.0266673
Test set: Average loss: 1.0616, Accuracy: 3083/5000 (62%)
[epoch 4] loss: 0.9786251
Test set: Average loss: 1.0352, Accuracy: 3144/5000 (63%)
[epoch 5] loss: 0.9312693
Test set: Average loss: 1.0218, Accuracy: 3174/5000 (63%)
[epoch 6] loss: 0.8892715
Test set: Average loss: 1.0079, Accuracy: 3158/5000 (63%)
[epoch 7] loss: 0.8565969
Test set: Average loss: 1.0139, Accuracy: 3145/5000 (63%)
[epoch 8] loss: 0.8176964
Test set: Average loss: 0.9878, Accuracy: 3191/5000 (64%)
[epoch 9] loss: 0.7861285
Test set: Average loss: 0.9911, Accuracy: 3177/5000 (64%)
[epoch 10] loss: 0.7506992
Test set: Average loss: 0.9899, Accuracy: 3158/5000 (63%)
[epoch 11] loss: 0.7176402
Test set: Average loss: 0.9782, Accuracy: 3179/5000 (64%)
[epoch 12] loss: 0.6843790
Test set: Average loss: 0.9761, Accuracy: 3210/5000 (64%)
[epoch 13] loss: 0.6472964
Test set: Average loss: 0.9594, Accuracy: 3213/5000 (64%)
[epoch 14] loss: 0.6123160
Test set: Average loss: 0.9586, Accuracy: 3216/5000 (64%)
[epoch 15] loss: 0.5708927
Test set: Average loss: 0.9496, Accuracy: 3250/5000 (65%)
[epoch 16] loss: 0.5347211
Test set: Average loss: 0.9604, Accuracy: 3239/5000 (65%)
[epoch 17] loss: 0.5046867
Test set: Average loss: 0.9515, Accuracy: 3259/5000 (65%)
[epoch 18] loss: 0.4702635
Test set: Average loss: 0.9442, Accuracy: 3257/5000 (65%)
[epoch 19] loss: 0.4313626
Test set: Average loss: 0.9549, Accuracy: 3248/5000 (65%)
[epoch 20] loss: 0.3976377
Test set: Average loss: 0.9823, Accuracy: 3177/5000 (64%)
[epoch 21] loss: 0.3624933
Test set: Average loss: 0.9618, Accuracy: 3241/5000 (65%)
[epoch 22] loss: 0.3319825
Test set: Average loss: 0.9546, Accuracy: 3256/5000 (65%)
[epoch 23] loss: 0.3013592
Test set: Average loss: 0.9801, Accuracy: 3216/5000 (64%)
[epoch 24] loss: 0.2741015
Test set: Average loss: 0.9730, Accuracy: 3226/5000 (65%)
[epoch 25] loss: 0.2424443
Test set: Average loss: 0.9634, Accuracy: 3267/5000 (65%)
Validation:
Test set: Average loss: 0.9634, Accuracy: 3267/5000 (65%)
Test
Test set: Average loss: 0.9966, Accuracy: 3181/5000 (64%)
Test set: Average loss: 0.2069, Accuracy: 4895/5000 (98%)
## seed: 13
Validation accuracy before training:
Test set: Average loss: 1.6143, Accuracy: 1140/5000 (23%)
[epoch 1] loss: 1.2143201
Test set: Average loss: 1.1374, Accuracy: 2935/5000 (59%)
[epoch 2] loss: 1.0687563
Test set: Average loss: 1.0984, Accuracy: 3002/5000 (60%)
[epoch 3] loss: 1.0063546
Test set: Average loss: 1.0599, Accuracy: 3076/5000 (62%)
[epoch 4] loss: 0.9578787
Test set: Average loss: 1.0440, Accuracy: 3095/5000 (62%)
[epoch 5] loss: 0.9153543
Test set: Average loss: 1.0289, Accuracy: 3121/5000 (62%)
[epoch 6] loss: 0.8778119
Test set: Average loss: 1.0191, Accuracy: 3110/5000 (62%)
[epoch 7] loss: 0.8399297
Test set: Average loss: 1.0203, Accuracy: 3098/5000 (62%)
[epoch 8] loss: 0.8068947
Test set: Average loss: 1.0007, Accuracy: 3141/5000 (63%)
[epoch 9] loss: 0.7696304
Test set: Average loss: 0.9892, Accuracy: 3156/5000 (63%)
[epoch 10] loss: 0.7362091
Test set: Average loss: 0.9875, Accuracy: 3163/5000 (63%)
[epoch 11] loss: 0.6985057
Test set: Average loss: 0.9928, Accuracy: 3168/5000 (63%)
[epoch 12] loss: 0.6679305
Test set: Average loss: 0.9839, Accuracy: 3150/5000 (63%)
[epoch 13] loss: 0.6305543
Test set: Average loss: 0.9801, Accuracy: 3167/5000 (63%)
[epoch 14] loss: 0.5939564
Test set: Average loss: 0.9831, Accuracy: 3185/5000 (64%)
[epoch 15] loss: 0.5597638
Test set: Average loss: 0.9730, Accuracy: 3185/5000 (64%)
[epoch 16] loss: 0.5237917
Test set: Average loss: 0.9826, Accuracy: 3150/5000 (63%)
[epoch 17] loss: 0.4903315
Test set: Average loss: 0.9815, Accuracy: 3177/5000 (64%)
[epoch 18] loss: 0.4556735
Test set: Average loss: 0.9860, Accuracy: 3139/5000 (63%)
[epoch 19] loss: 0.4198795
Test set: Average loss: 0.9753, Accuracy: 3188/5000 (64%)
[epoch 20] loss: 0.3872016
Test set: Average loss: 0.9770, Accuracy: 3171/5000 (63%)
[epoch 21] loss: 0.3571876
Test set: Average loss: 0.9897, Accuracy: 3178/5000 (64%)
[epoch 22] loss: 0.3230935
Test set: Average loss: 0.9829, Accuracy: 3197/5000 (64%)
[epoch 23] loss: 0.2948823
Test set: Average loss: 0.9832, Accuracy: 3217/5000 (64%)
[epoch 24] loss: 0.2677532
Test set: Average loss: 0.9978, Accuracy: 3163/5000 (63%)
[epoch 25] loss: 0.2407865
Test set: Average loss: 0.9934, Accuracy: 3197/5000 (64%)
Validation:
Test set: Average loss: 0.9832, Accuracy: 3217/5000 (64%)
Test
Test set: Average loss: 0.9974, Accuracy: 3225/5000 (64%)
Test set: Average loss: 0.2552, Accuracy: 4815/5000 (96%)
10000
## seed: 11
Validation accuracy before training:
Test set: Average loss: 1.5956, Accuracy: 1178/5000 (24%)
[epoch 1] loss: 1.1872618
Test set: Average loss: 1.1004, Accuracy: 3013/5000 (60%)
[epoch 2] loss: 1.0530503
Test set: Average loss: 1.0461, Accuracy: 3125/5000 (62%)
[epoch 3] loss: 0.9882509
Test set: Average loss: 1.0130, Accuracy: 3186/5000 (64%)
[epoch 4] loss: 0.9377088
Test set: Average loss: 0.9928, Accuracy: 3190/5000 (64%)
[epoch 5] loss: 0.8904494
Test set: Average loss: 0.9701, Accuracy: 3218/5000 (64%)
[epoch 6] loss: 0.8501048
Test set: Average loss: 0.9537, Accuracy: 3256/5000 (65%)
[epoch 7] loss: 0.8087033
Test set: Average loss: 0.9473, Accuracy: 3258/5000 (65%)
[epoch 8] loss: 0.7700317
Test set: Average loss: 0.9310, Accuracy: 3292/5000 (66%)
[epoch 9] loss: 0.7266682
Test set: Average loss: 0.9296, Accuracy: 3289/5000 (66%)
[epoch 10] loss: 0.6856485
Test set: Average loss: 0.9298, Accuracy: 3289/5000 (66%)
[epoch 11] loss: 0.6457164
Test set: Average loss: 0.9090, Accuracy: 3306/5000 (66%)
[epoch 12] loss: 0.5996159
Test set: Average loss: 0.9090, Accuracy: 3305/5000 (66%)
[epoch 13] loss: 0.5568790
Test set: Average loss: 0.8996, Accuracy: 3322/5000 (66%)
[epoch 14] loss: 0.5126459
Test set: Average loss: 0.8924, Accuracy: 3371/5000 (67%)
[epoch 15] loss: 0.4676781
Test set: Average loss: 0.9063, Accuracy: 3335/5000 (67%)
[epoch 16] loss: 0.4229266
Test set: Average loss: 0.9054, Accuracy: 3378/5000 (68%)
[epoch 17] loss: 0.3816412
Test set: Average loss: 0.9102, Accuracy: 3363/5000 (67%)
[epoch 18] loss: 0.3392201
Test set: Average loss: 0.9131, Accuracy: 3359/5000 (67%)
[epoch 19] loss: 0.3023108
Test set: Average loss: 0.9302, Accuracy: 3335/5000 (67%)
[epoch 20] loss: 0.2652663
Test set: Average loss: 0.9478, Accuracy: 3329/5000 (67%)
[epoch 21] loss: 0.2328274
Test set: Average loss: 0.9481, Accuracy: 3326/5000 (67%)
[epoch 22] loss: 0.2024296
Test set: Average loss: 0.9594, Accuracy: 3295/5000 (66%)
[epoch 23] loss: 0.1705694
Test set: Average loss: 0.9677, Accuracy: 3327/5000 (67%)
[epoch 24] loss: 0.1448956
Test set: Average loss: 0.9902, Accuracy: 3311/5000 (66%)
[epoch 25] loss: 0.1254317
Test set: Average loss: 0.9978, Accuracy: 3335/5000 (67%)
Validation:
Test set: Average loss: 0.9054, Accuracy: 3378/5000 (68%)
Test
Test set: Average loss: 0.9126, Accuracy: 3336/5000 (67%)
Test set: Average loss: 0.3691, Accuracy: 9168/10000 (92%)
## seed: 12
Validation accuracy before training:
Test set: Average loss: 1.6363, Accuracy: 889/5000 (18%)
[epoch 1] loss: 1.1748873
Test set: Average loss: 1.0937, Accuracy: 3000/5000 (60%)
[epoch 2] loss: 1.0413663
Test set: Average loss: 1.0277, Accuracy: 3144/5000 (63%)
[epoch 3] loss: 0.9785607
Test set: Average loss: 0.9970, Accuracy: 3204/5000 (64%)
[epoch 4] loss: 0.9323009
Test set: Average loss: 0.9867, Accuracy: 3211/5000 (64%)
[epoch 5] loss: 0.8863039
Test set: Average loss: 0.9669, Accuracy: 3238/5000 (65%)
[epoch 6] loss: 0.8467778
Test set: Average loss: 0.9508, Accuracy: 3266/5000 (65%)
[epoch 7] loss: 0.8065040
Test set: Average loss: 0.9361, Accuracy: 3310/5000 (66%)
[epoch 8] loss: 0.7647077
Test set: Average loss: 0.9243, Accuracy: 3293/5000 (66%)
[epoch 9] loss: 0.7270672
Test set: Average loss: 0.9140, Accuracy: 3317/5000 (66%)
[epoch 10] loss: 0.6849888
Test set: Average loss: 0.9142, Accuracy: 3287/5000 (66%)
[epoch 11] loss: 0.6430961
Test set: Average loss: 0.9197, Accuracy: 3282/5000 (66%)
[epoch 12] loss: 0.6012387
Test set: Average loss: 0.9225, Accuracy: 3264/5000 (65%)
[epoch 13] loss: 0.5609271
Test set: Average loss: 0.8956, Accuracy: 3337/5000 (67%)
[epoch 14] loss: 0.5199201
Test set: Average loss: 0.9019, Accuracy: 3307/5000 (66%)
[epoch 15] loss: 0.4776419
Test set: Average loss: 0.8965, Accuracy: 3359/5000 (67%)
[epoch 16] loss: 0.4366066
Test set: Average loss: 0.8936, Accuracy: 3353/5000 (67%)
[epoch 17] loss: 0.3914947
Test set: Average loss: 0.9180, Accuracy: 3290/5000 (66%)
[epoch 18] loss: 0.3520768
Test set: Average loss: 0.9166, Accuracy: 3327/5000 (67%)
[epoch 19] loss: 0.3123399
Test set: Average loss: 0.9078, Accuracy: 3358/5000 (67%)
[epoch 20] loss: 0.2759010
Test set: Average loss: 0.9297, Accuracy: 3305/5000 (66%)
[epoch 21] loss: 0.2443195
Test set: Average loss: 0.9386, Accuracy: 3328/5000 (67%)
[epoch 22] loss: 0.2130384
Test set: Average loss: 0.9538, Accuracy: 3321/5000 (66%)
[epoch 23] loss: 0.1834673
Test set: Average loss: 0.9540, Accuracy: 3327/5000 (67%)
[epoch 24] loss: 0.1569972
Test set: Average loss: 0.9655, Accuracy: 3319/5000 (66%)
[epoch 25] loss: 0.1330309
Test set: Average loss: 0.9680, Accuracy: 3334/5000 (67%)
Validation:
Test set: Average loss: 0.8965, Accuracy: 3359/5000 (67%)
Test
Test set: Average loss: 0.9168, Accuracy: 3320/5000 (66%)
Test set: Average loss: 0.4205, Accuracy: 8983/10000 (90%)
## seed: 13
Validation accuracy before training:
Test set: Average loss: 1.6450, Accuracy: 922/5000 (18%)
[epoch 1] loss: 1.1644209
Test set: Average loss: 1.0830, Accuracy: 3001/5000 (60%)
[epoch 2] loss: 1.0289508
Test set: Average loss: 1.0323, Accuracy: 3109/5000 (62%)
[epoch 3] loss: 0.9652520
Test set: Average loss: 0.9968, Accuracy: 3181/5000 (64%)
[epoch 4] loss: 0.9152127
Test set: Average loss: 0.9719, Accuracy: 3242/5000 (65%)
[epoch 5] loss: 0.8723743
Test set: Average loss: 0.9578, Accuracy: 3225/5000 (64%)
[epoch 6] loss: 0.8315572
Test set: Average loss: 0.9465, Accuracy: 3264/5000 (65%)
[epoch 7] loss: 0.7881987
Test set: Average loss: 0.9334, Accuracy: 3265/5000 (65%)
[epoch 8] loss: 0.7483570
Test set: Average loss: 0.9351, Accuracy: 3268/5000 (65%)
[epoch 9] loss: 0.7080801
Test set: Average loss: 0.9186, Accuracy: 3306/5000 (66%)
[epoch 10] loss: 0.6642416
Test set: Average loss: 0.9114, Accuracy: 3313/5000 (66%)
[epoch 11] loss: 0.6216582
Test set: Average loss: 0.9023, Accuracy: 3321/5000 (66%)
[epoch 12] loss: 0.5765877
Test set: Average loss: 0.9061, Accuracy: 3296/5000 (66%)
[epoch 13] loss: 0.5383463
Test set: Average loss: 0.8988, Accuracy: 3345/5000 (67%)
[epoch 14] loss: 0.4923629
Test set: Average loss: 0.9091, Accuracy: 3297/5000 (66%)
[epoch 15] loss: 0.4497622
Test set: Average loss: 0.8966, Accuracy: 3336/5000 (67%)
[epoch 16] loss: 0.4082034
Test set: Average loss: 0.8998, Accuracy: 3346/5000 (67%)
[epoch 17] loss: 0.3686552
Test set: Average loss: 0.9300, Accuracy: 3324/5000 (66%)
[epoch 18] loss: 0.3300712
Test set: Average loss: 0.9054, Accuracy: 3346/5000 (67%)
[epoch 19] loss: 0.2916347
Test set: Average loss: 0.9261, Accuracy: 3321/5000 (66%)
[epoch 20] loss: 0.2601875
Test set: Average loss: 0.9295, Accuracy: 3337/5000 (67%)
[epoch 21] loss: 0.2286902
Test set: Average loss: 0.9371, Accuracy: 3338/5000 (67%)
[epoch 22] loss: 0.1978396
Test set: Average loss: 0.9523, Accuracy: 3341/5000 (67%)
[epoch 23] loss: 0.1710817
Test set: Average loss: 0.9620, Accuracy: 3367/5000 (67%)
[epoch 24] loss: 0.1470408
Test set: Average loss: 0.9893, Accuracy: 3321/5000 (66%)
[epoch 25] loss: 0.1265413
Test set: Average loss: 0.9792, Accuracy: 3339/5000 (67%)
Validation:
Test set: Average loss: 0.9620, Accuracy: 3367/5000 (67%)
Test
Test set: Average loss: 0.9934, Accuracy: 3313/5000 (66%)
Test set: Average loss: 0.1432, Accuracy: 9818/10000 (98%)
15000
## seed: 11
Validation accuracy before training:
Test set: Average loss: 1.5874, Accuracy: 1257/5000 (25%)
[epoch 1] loss: 1.1554197
Test set: Average loss: 1.0675, Accuracy: 3113/5000 (62%)
[epoch 2] loss: 1.0267970
Test set: Average loss: 1.0109, Accuracy: 3182/5000 (64%)
[epoch 3] loss: 0.9629056
Test set: Average loss: 0.9872, Accuracy: 3219/5000 (64%)
[epoch 4] loss: 0.9116576
Test set: Average loss: 0.9585, Accuracy: 3221/5000 (64%)
[epoch 5] loss: 0.8642731
Test set: Average loss: 0.9357, Accuracy: 3307/5000 (66%)
[epoch 6] loss: 0.8200263
Test set: Average loss: 0.9175, Accuracy: 3334/5000 (67%)
[epoch 7] loss: 0.7746379
Test set: Average loss: 0.9095, Accuracy: 3310/5000 (66%)
[epoch 8] loss: 0.7298459
Test set: Average loss: 0.8875, Accuracy: 3391/5000 (68%)
[epoch 9] loss: 0.6864395
Test set: Average loss: 0.8775, Accuracy: 3394/5000 (68%)
[epoch 10] loss: 0.6412730
Test set: Average loss: 0.8716, Accuracy: 3401/5000 (68%)
[epoch 11] loss: 0.5940132
Test set: Average loss: 0.8661, Accuracy: 3407/5000 (68%)
[epoch 12] loss: 0.5479981
Test set: Average loss: 0.8695, Accuracy: 3419/5000 (68%)
[epoch 13] loss: 0.5006745
Test set: Average loss: 0.8722, Accuracy: 3421/5000 (68%)
[epoch 14] loss: 0.4551602
Test set: Average loss: 0.8649, Accuracy: 3415/5000 (68%)
[epoch 15] loss: 0.4087259
Test set: Average loss: 0.8754, Accuracy: 3444/5000 (69%)
[epoch 16] loss: 0.3644529
Test set: Average loss: 0.8731, Accuracy: 3428/5000 (69%)
[epoch 17] loss: 0.3228128
Test set: Average loss: 0.8880, Accuracy: 3389/5000 (68%)
[epoch 18] loss: 0.2830114
Test set: Average loss: 0.9100, Accuracy: 3439/5000 (69%)
[epoch 19] loss: 0.2461704
Test set: Average loss: 0.9124, Accuracy: 3396/5000 (68%)
[epoch 20] loss: 0.2126470
Test set: Average loss: 0.9231, Accuracy: 3402/5000 (68%)
[epoch 21] loss: 0.1795556
Test set: Average loss: 0.9362, Accuracy: 3396/5000 (68%)
[epoch 22] loss: 0.1515268
Test set: Average loss: 0.9611, Accuracy: 3356/5000 (67%)
[epoch 23] loss: 0.1267542
Test set: Average loss: 0.9912, Accuracy: 3375/5000 (68%)
[epoch 24] loss: 0.1076265
Test set: Average loss: 1.0096, Accuracy: 3367/5000 (67%)
[epoch 25] loss: 0.0889060
Test set: Average loss: 1.0182, Accuracy: 3398/5000 (68%)
Validation:
Test set: Average loss: 0.8754, Accuracy: 3444/5000 (69%)
Test
Test set: Average loss: 0.8862, Accuracy: 3400/5000 (68%)
Test set: Average loss: 0.3546, Accuracy: 13748/15000 (92%)
## seed: 12
Validation accuracy before training:
Test set: Average loss: 1.6268, Accuracy: 878/5000 (18%)
[epoch 1] loss: 1.1478102
Test set: Average loss: 1.0630, Accuracy: 3089/5000 (62%)
[epoch 2] loss: 1.0191660
Test set: Average loss: 1.0121, Accuracy: 3166/5000 (63%)
[epoch 3] loss: 0.9547076
Test set: Average loss: 0.9727, Accuracy: 3232/5000 (65%)
[epoch 4] loss: 0.9039605
Test set: Average loss: 0.9524, Accuracy: 3241/5000 (65%)
[epoch 5] loss: 0.8528519
Test set: Average loss: 0.9269, Accuracy: 3281/5000 (66%)
[epoch 6] loss: 0.8088864
Test set: Average loss: 0.9293, Accuracy: 3264/5000 (65%)
[epoch 7] loss: 0.7643005
Test set: Average loss: 0.9006, Accuracy: 3358/5000 (67%)
[epoch 8] loss: 0.7174708
Test set: Average loss: 0.8878, Accuracy: 3347/5000 (67%)
[epoch 9] loss: 0.6725807
Test set: Average loss: 0.8791, Accuracy: 3375/5000 (68%)
[epoch 10] loss: 0.6257543
Test set: Average loss: 0.8685, Accuracy: 3396/5000 (68%)
[epoch 11] loss: 0.5796774
Test set: Average loss: 0.8669, Accuracy: 3386/5000 (68%)
[epoch 12] loss: 0.5345717
Test set: Average loss: 0.8547, Accuracy: 3447/5000 (69%)
[epoch 13] loss: 0.4879690
Test set: Average loss: 0.8587, Accuracy: 3431/5000 (69%)
[epoch 14] loss: 0.4409502
Test set: Average loss: 0.8802, Accuracy: 3396/5000 (68%)
[epoch 15] loss: 0.3946166
Test set: Average loss: 0.8786, Accuracy: 3416/5000 (68%)
[epoch 16] loss: 0.3541917
Test set: Average loss: 0.8814, Accuracy: 3414/5000 (68%)
[epoch 17] loss: 0.3117635
Test set: Average loss: 0.8932, Accuracy: 3411/5000 (68%)
[epoch 18] loss: 0.2730866
Test set: Average loss: 0.8884, Accuracy: 3431/5000 (69%)
[epoch 19] loss: 0.2369405
Test set: Average loss: 0.9364, Accuracy: 3386/5000 (68%)
[epoch 20] loss: 0.2055508
Test set: Average loss: 0.9268, Accuracy: 3399/5000 (68%)
[epoch 21] loss: 0.1731951
Test set: Average loss: 0.9587, Accuracy: 3360/5000 (67%)
[epoch 22] loss: 0.1463712
Test set: Average loss: 0.9779, Accuracy: 3363/5000 (67%)
[epoch 23] loss: 0.1237453
Test set: Average loss: 0.9644, Accuracy: 3418/5000 (68%)
[epoch 24] loss: 0.1068491
Test set: Average loss: 1.0181, Accuracy: 3353/5000 (67%)
[epoch 25] loss: 0.0859191
Test set: Average loss: 1.0203, Accuracy: 3368/5000 (67%)
Validation:
Test set: Average loss: 0.8547, Accuracy: 3447/5000 (69%)
Test
Test set: Average loss: 0.8599, Accuracy: 3419/5000 (68%)
Test set: Average loss: 0.4693, Accuracy: 13128/15000 (88%)
## seed: 13
Validation accuracy before training:
Test set: Average loss: 1.6351, Accuracy: 1008/5000 (20%)
[epoch 1] loss: 1.1794114
Test set: Average loss: 1.0777, Accuracy: 3109/5000 (62%)
[epoch 2] loss: 1.0312429
Test set: Average loss: 1.0196, Accuracy: 3178/5000 (64%)
[epoch 3] loss: 0.9620255
Test set: Average loss: 0.9826, Accuracy: 3230/5000 (65%)
[epoch 4] loss: 0.9085847
Test set: Average loss: 0.9488, Accuracy: 3254/5000 (65%)
[epoch 5] loss: 0.8563124
Test set: Average loss: 0.9307, Accuracy: 3303/5000 (66%)
[epoch 6] loss: 0.8094655
Test set: Average loss: 0.8989, Accuracy: 3340/5000 (67%)
[epoch 7] loss: 0.7642603
Test set: Average loss: 0.9020, Accuracy: 3339/5000 (67%)
[epoch 8] loss: 0.7186311
Test set: Average loss: 0.9016, Accuracy: 3342/5000 (67%)
[epoch 9] loss: 0.6726335
Test set: Average loss: 0.8722, Accuracy: 3392/5000 (68%)
[epoch 10] loss: 0.6283717
Test set: Average loss: 0.8784, Accuracy: 3411/5000 (68%)
[epoch 11] loss: 0.5825017
Test set: Average loss: 0.8651, Accuracy: 3406/5000 (68%)
[epoch 12] loss: 0.5376241
Test set: Average loss: 0.8651, Accuracy: 3428/5000 (69%)
[epoch 13] loss: 0.4919401
Test set: Average loss: 0.8777, Accuracy: 3394/5000 (68%)
[epoch 14] loss: 0.4470126
Test set: Average loss: 0.8622, Accuracy: 3432/5000 (69%)
[epoch 15] loss: 0.4014588
Test set: Average loss: 0.8654, Accuracy: 3444/5000 (69%)
[epoch 16] loss: 0.3586994
Test set: Average loss: 0.8718, Accuracy: 3451/5000 (69%)
[epoch 17] loss: 0.3178591
Test set: Average loss: 0.8745, Accuracy: 3462/5000 (69%)
[epoch 18] loss: 0.2808142
Test set: Average loss: 0.9031, Accuracy: 3409/5000 (68%)
[epoch 19] loss: 0.2422690
Test set: Average loss: 0.9109, Accuracy: 3432/5000 (69%)
[epoch 20] loss: 0.2105957
Test set: Average loss: 0.9224, Accuracy: 3444/5000 (69%)
[epoch 21] loss: 0.1784258
Test set: Average loss: 0.9720, Accuracy: 3357/5000 (67%)
[epoch 22] loss: 0.1549011
Test set: Average loss: 0.9488, Accuracy: 3398/5000 (68%)
[epoch 23] loss: 0.1286062
Test set: Average loss: 0.9941, Accuracy: 3395/5000 (68%)
[epoch 24] loss: 0.1073714
Test set: Average loss: 0.9776, Accuracy: 3427/5000 (69%)
[epoch 25] loss: 0.0896816
Test set: Average loss: 0.9973, Accuracy: 3439/5000 (69%)
Validation:
Test set: Average loss: 0.8745, Accuracy: 3462/5000 (69%)
Test
Test set: Average loss: 0.9017, Accuracy: 3377/5000 (68%)
Test set: Average loss: 0.2665, Accuracy: 14184/15000 (95%)
20000
## seed: 11
Validation accuracy before training:
Test set: Average loss: 1.6163, Accuracy: 977/5000 (20%)
[epoch 1] loss: 1.1135340
Test set: Average loss: 1.0221, Accuracy: 3151/5000 (63%)
[epoch 2] loss: 0.9811583
Test set: Average loss: 0.9817, Accuracy: 3187/5000 (64%)
[epoch 3] loss: 0.9158864
Test set: Average loss: 0.9350, Accuracy: 3283/5000 (66%)
[epoch 4] loss: 0.8617010
Test set: Average loss: 0.9296, Accuracy: 3315/5000 (66%)
[epoch 5] loss: 0.8135324
Test set: Average loss: 0.8884, Accuracy: 3361/5000 (67%)
[epoch 6] loss: 0.7660055
Test set: Average loss: 0.8668, Accuracy: 3447/5000 (69%)
[epoch 7] loss: 0.7194966
Test set: Average loss: 0.8611, Accuracy: 3409/5000 (68%)
[epoch 8] loss: 0.6746980
Test set: Average loss: 0.8501, Accuracy: 3449/5000 (69%)
[epoch 9] loss: 0.6297682
Test set: Average loss: 0.8500, Accuracy: 3456/5000 (69%)
[epoch 10] loss: 0.5848601
Test set: Average loss: 0.8350, Accuracy: 3492/5000 (70%)
[epoch 11] loss: 0.5386280
Test set: Average loss: 0.8389, Accuracy: 3482/5000 (70%)
[epoch 12] loss: 0.4919896
Test set: Average loss: 0.8341, Accuracy: 3476/5000 (70%)
[epoch 13] loss: 0.4438796
Test set: Average loss: 0.8361, Accuracy: 3490/5000 (70%)
[epoch 14] loss: 0.3994722
Test set: Average loss: 0.8422, Accuracy: 3499/5000 (70%)
[epoch 15] loss: 0.3572363
Test set: Average loss: 0.8519, Accuracy: 3501/5000 (70%)
[epoch 16] loss: 0.3125629
Test set: Average loss: 0.8558, Accuracy: 3491/5000 (70%)
[epoch 17] loss: 0.2738584
Test set: Average loss: 0.8687, Accuracy: 3480/5000 (70%)
[epoch 18] loss: 0.2357701
Test set: Average loss: 0.8892, Accuracy: 3469/5000 (69%)
[epoch 19] loss: 0.2037106
Test set: Average loss: 0.9136, Accuracy: 3463/5000 (69%)
[epoch 20] loss: 0.1714735
Test set: Average loss: 0.9259, Accuracy: 3457/5000 (69%)
[epoch 21] loss: 0.1476872
Test set: Average loss: 0.9747, Accuracy: 3414/5000 (68%)
[epoch 22] loss: 0.1278360
Test set: Average loss: 0.9878, Accuracy: 3405/5000 (68%)
[epoch 23] loss: 0.1013765
Test set: Average loss: 1.0005, Accuracy: 3448/5000 (69%)
[epoch 24] loss: 0.0849581
Test set: Average loss: 1.0092, Accuracy: 3462/5000 (69%)
[epoch 25] loss: 0.0711214
Test set: Average loss: 1.0495, Accuracy: 3466/5000 (69%)
Validation:
Test set: Average loss: 0.8519, Accuracy: 3501/5000 (70%)
Test
Test set: Average loss: 0.8773, Accuracy: 3396/5000 (68%)
Test set: Average loss: 0.3021, Accuracy: 18598/20000 (93%)
## seed: 12
Validation accuracy before training:
Test set: Average loss: 1.6205, Accuracy: 1002/5000 (20%)
[epoch 1] loss: 1.1241424
Test set: Average loss: 1.0451, Accuracy: 3103/5000 (62%)
[epoch 2] loss: 0.9972833
Test set: Average loss: 0.9837, Accuracy: 3208/5000 (64%)
[epoch 3] loss: 0.9295757
Test set: Average loss: 0.9473, Accuracy: 3268/5000 (65%)
[epoch 4] loss: 0.8746626
Test set: Average loss: 0.9161, Accuracy: 3289/5000 (66%)
[epoch 5] loss: 0.8242068
Test set: Average loss: 0.9003, Accuracy: 3367/5000 (67%)
[epoch 6] loss: 0.7743027
Test set: Average loss: 0.8797, Accuracy: 3365/5000 (67%)
[epoch 7] loss: 0.7308368
Test set: Average loss: 0.8642, Accuracy: 3392/5000 (68%)
[epoch 8] loss: 0.6814430
Test set: Average loss: 0.8580, Accuracy: 3416/5000 (68%)
[epoch 9] loss: 0.6335602
Test set: Average loss: 0.8429, Accuracy: 3438/5000 (69%)
[epoch 10] loss: 0.5867933
Test set: Average loss: 0.8376, Accuracy: 3442/5000 (69%)
[epoch 11] loss: 0.5395141
Test set: Average loss: 0.8303, Accuracy: 3488/5000 (70%)
[epoch 12] loss: 0.4890922
Test set: Average loss: 0.8259, Accuracy: 3510/5000 (70%)
[epoch 13] loss: 0.4432131
Test set: Average loss: 0.8355, Accuracy: 3482/5000 (70%)
[epoch 14] loss: 0.3989589
Test set: Average loss: 0.8489, Accuracy: 3494/5000 (70%)
[epoch 15] loss: 0.3548000
Test set: Average loss: 0.8539, Accuracy: 3486/5000 (70%)
[epoch 16] loss: 0.3114529
Test set: Average loss: 0.8674, Accuracy: 3474/5000 (69%)
[epoch 17] loss: 0.2731536
Test set: Average loss: 0.8621, Accuracy: 3499/5000 (70%)
[epoch 18] loss: 0.2357545
Test set: Average loss: 0.8860, Accuracy: 3474/5000 (69%)
[epoch 19] loss: 0.2015051
Test set: Average loss: 0.9060, Accuracy: 3484/5000 (70%)
[epoch 20] loss: 0.1715616
Test set: Average loss: 0.9453, Accuracy: 3391/5000 (68%)
[epoch 21] loss: 0.1443582
Test set: Average loss: 0.9552, Accuracy: 3427/5000 (69%)
[epoch 22] loss: 0.1228017
Test set: Average loss: 0.9781, Accuracy: 3428/5000 (69%)
[epoch 23] loss: 0.0981208
Test set: Average loss: 0.9923, Accuracy: 3427/5000 (69%)
[epoch 24] loss: 0.0839666
Test set: Average loss: 1.0248, Accuracy: 3429/5000 (69%)
[epoch 25] loss: 0.0675742
Test set: Average loss: 1.0490, Accuracy: 3440/5000 (69%)
Validation:
Test set: Average loss: 0.8259, Accuracy: 3510/5000 (70%)
Test
Test set: Average loss: 0.8461, Accuracy: 3475/5000 (70%)
Test set: Average loss: 0.4266, Accuracy: 17696/20000 (88%)
## seed: 13
Validation accuracy before training:
Test set: Average loss: 1.6222, Accuracy: 914/5000 (18%)
[epoch 1] loss: 1.1073230
Test set: Average loss: 1.0248, Accuracy: 3156/5000 (63%)
[epoch 2] loss: 0.9783479
Test set: Average loss: 0.9689, Accuracy: 3230/5000 (65%)
[epoch 3] loss: 0.9168433
Test set: Average loss: 0.9418, Accuracy: 3275/5000 (66%)
[epoch 4] loss: 0.8648431
Test set: Average loss: 0.9068, Accuracy: 3344/5000 (67%)
[epoch 5] loss: 0.8177732
Test set: Average loss: 0.8973, Accuracy: 3340/5000 (67%)
[epoch 6] loss: 0.7722915
Test set: Average loss: 0.8792, Accuracy: 3401/5000 (68%)
[epoch 7] loss: 0.7267179
Test set: Average loss: 0.8691, Accuracy: 3386/5000 (68%)
[epoch 8] loss: 0.6820736
Test set: Average loss: 0.8586, Accuracy: 3432/5000 (69%)
[epoch 9] loss: 0.6358600
Test set: Average loss: 0.8382, Accuracy: 3482/5000 (70%)
[epoch 10] loss: 0.5872945
Test set: Average loss: 0.8375, Accuracy: 3494/5000 (70%)
[epoch 11] loss: 0.5420207
Test set: Average loss: 0.8339, Accuracy: 3490/5000 (70%)
[epoch 12] loss: 0.4970647
Test set: Average loss: 0.8376, Accuracy: 3498/5000 (70%)
[epoch 13] loss: 0.4475808
Test set: Average loss: 0.8438, Accuracy: 3489/5000 (70%)
[epoch 14] loss: 0.4023538
Test set: Average loss: 0.8605, Accuracy: 3482/5000 (70%)
[epoch 15] loss: 0.3586023
Test set: Average loss: 0.8533, Accuracy: 3478/5000 (70%)
[epoch 16] loss: 0.3161659
Test set: Average loss: 0.8642, Accuracy: 3466/5000 (69%)
[epoch 17] loss: 0.2723413
Test set: Average loss: 0.8829, Accuracy: 3459/5000 (69%)
[epoch 18] loss: 0.2383115
Test set: Average loss: 0.9068, Accuracy: 3466/5000 (69%)
[epoch 19] loss: 0.2055226
Test set: Average loss: 0.9064, Accuracy: 3455/5000 (69%)
[epoch 20] loss: 0.1751943
Test set: Average loss: 0.9241, Accuracy: 3430/5000 (69%)
[epoch 21] loss: 0.1475291
Test set: Average loss: 0.9594, Accuracy: 3402/5000 (68%)
[epoch 22] loss: 0.1216947
Test set: Average loss: 1.0192, Accuracy: 3378/5000 (68%)
[epoch 23] loss: 0.1038819
Test set: Average loss: 1.0092, Accuracy: 3424/5000 (68%)
[epoch 24] loss: 0.0819766
Test set: Average loss: 1.0291, Accuracy: 3416/5000 (68%)
[epoch 25] loss: 0.0745892
Test set: Average loss: 1.0488, Accuracy: 3419/5000 (68%)
Validation:
Test set: Average loss: 0.8376, Accuracy: 3498/5000 (70%)
Test
Test set: Average loss: 0.8564, Accuracy: 3435/5000 (69%)
Test set: Average loss: 0.4386, Accuracy: 17497/20000 (87%)
## Pre-Training BnB
Validation accuracy before training:
Test set: Average loss: 1.6187, Accuracy: 1131/5000 (23%)
[epoch 1] loss: 1.1180346
Test set: Average loss: 1.0322, Accuracy: 3147/5000 (63%)
[epoch 2] loss: 0.9899270
Test set: Average loss: 0.9866, Accuracy: 3188/5000 (64%)
[epoch 3] loss: 0.9247509
Test set: Average loss: 0.9585, Accuracy: 3246/5000 (65%)
[epoch 4] loss: 0.8727337
Test set: Average loss: 0.9196, Accuracy: 3308/5000 (66%)
[epoch 5] loss: 0.8220314
Test set: Average loss: 0.8943, Accuracy: 3358/5000 (67%)
[epoch 6] loss: 0.7744212
Test set: Average loss: 0.8842, Accuracy: 3411/5000 (68%)
[epoch 7] loss: 0.7283000
Test set: Average loss: 0.8609, Accuracy: 3403/5000 (68%)
[epoch 8] loss: 0.6822820
Test set: Average loss: 0.8523, Accuracy: 3442/5000 (69%)
[epoch 9] loss: 0.6342879
Test set: Average loss: 0.8391, Accuracy: 3470/5000 (69%)
[epoch 10] loss: 0.5877394
Test set: Average loss: 0.8361, Accuracy: 3474/5000 (69%)
[epoch 11] loss: 0.5377995
Test set: Average loss: 0.8287, Accuracy: 3507/5000 (70%)
[epoch 12] loss: 0.4916349
Test set: Average loss: 0.8364, Accuracy: 3486/5000 (70%)
[epoch 13] loss: 0.4439794
Test set: Average loss: 0.8378, Accuracy: 3486/5000 (70%)
[epoch 14] loss: 0.3994560
Test set: Average loss: 0.8435, Accuracy: 3484/5000 (70%)
[epoch 15] loss: 0.3556829
Test set: Average loss: 0.8754, Accuracy: 3418/5000 (68%)
[epoch 16] loss: 0.3150768
Test set: Average loss: 0.8733, Accuracy: 3446/5000 (69%)
[epoch 17] loss: 0.2737179
Test set: Average loss: 0.8832, Accuracy: 3437/5000 (69%)
[epoch 18] loss: 0.2375673
Test set: Average loss: 0.8907, Accuracy: 3470/5000 (69%)
[epoch 19] loss: 0.2072198
Test set: Average loss: 0.9223, Accuracy: 3460/5000 (69%)
[epoch 20] loss: 0.1763402
Test set: Average loss: 0.9408, Accuracy: 3456/5000 (69%)
[epoch 21] loss: 0.1496493
Test set: Average loss: 0.9666, Accuracy: 3444/5000 (69%)
[epoch 22] loss: 0.1270986
Test set: Average loss: 0.9970, Accuracy: 3399/5000 (68%)
[epoch 23] loss: 0.1056362
Test set: Average loss: 1.0284, Accuracy: 3394/5000 (68%)
[epoch 24] loss: 0.0850579
Test set: Average loss: 1.0349, Accuracy: 3396/5000 (68%)
[epoch 25] loss: 0.0737121
Test set: Average loss: 1.0784, Accuracy: 3371/5000 (67%)
Validation:
Test set: Average loss: 0.8287, Accuracy: 3507/5000 (70%)
Test set: Average loss: 0.8473, Accuracy: 3456/5000 (69%)
25
## seed: 11
Validation accuracy before training:
Test set: Average loss: 1.5438, Accuracy: 1560/5000 (31%)
[epoch 1] loss: 1.6017389
Test set: Average loss: 1.5346, Accuracy: 1620/5000 (32%)
[epoch 2] loss: 1.5326009
Test set: Average loss: 1.5259, Accuracy: 1663/5000 (33%)
[epoch 3] loss: 1.4667749
Test set: Average loss: 1.5178, Accuracy: 1692/5000 (34%)
[epoch 4] loss: 1.4047638
Test set: Average loss: 1.5102, Accuracy: 1723/5000 (34%)
[epoch 5] loss: 1.3469526
Test set: Average loss: 1.5031, Accuracy: 1754/5000 (35%)
[epoch 6] loss: 1.2934395
Test set: Average loss: 1.4965, Accuracy: 1773/5000 (35%)
[epoch 7] loss: 1.2440355
Test set: Average loss: 1.4903, Accuracy: 1794/5000 (36%)
[epoch 8] loss: 1.1983936
Test set: Average loss: 1.4846, Accuracy: 1804/5000 (36%)
[epoch 9] loss: 1.1561393
Test set: Average loss: 1.4793, Accuracy: 1818/5000 (36%)
[epoch 10] loss: 1.1169338
Test set: Average loss: 1.4744, Accuracy: 1843/5000 (37%)
[epoch 11] loss: 1.0804731
Test set: Average loss: 1.4699, Accuracy: 1852/5000 (37%)
[epoch 12] loss: 1.0464659
Test set: Average loss: 1.4658, Accuracy: 1864/5000 (37%)
[epoch 13] loss: 1.0146255
Test set: Average loss: 1.4620, Accuracy: 1889/5000 (38%)
[epoch 14] loss: 0.9846768
Test set: Average loss: 1.4586, Accuracy: 1906/5000 (38%)
[epoch 15] loss: 0.9563746
Test set: Average loss: 1.4555, Accuracy: 1916/5000 (38%)
[epoch 16] loss: 0.9295204
Test set: Average loss: 1.4527, Accuracy: 1941/5000 (39%)
[epoch 17] loss: 0.9039688
Test set: Average loss: 1.4502, Accuracy: 1959/5000 (39%)
[epoch 18] loss: 0.8796259
Test set: Average loss: 1.4479, Accuracy: 1977/5000 (40%)
[epoch 19] loss: 0.8564339
Test set: Average loss: 1.4457, Accuracy: 1991/5000 (40%)
[epoch 20] loss: 0.8343582
Test set: Average loss: 1.4438, Accuracy: 1998/5000 (40%)
[epoch 21] loss: 0.8133745
Test set: Average loss: 1.4420, Accuracy: 2004/5000 (40%)
[epoch 22] loss: 0.7934619
Test set: Average loss: 1.4402, Accuracy: 2007/5000 (40%)
[epoch 23] loss: 0.7745964
Test set: Average loss: 1.4385, Accuracy: 2013/5000 (40%)
[epoch 24] loss: 0.7567441
Test set: Average loss: 1.4369, Accuracy: 2023/5000 (40%)
[epoch 25] loss: 0.7398533
Test set: Average loss: 1.4353, Accuracy: 2014/5000 (40%)
Validation:
Test set: Average loss: 1.4369, Accuracy: 2023/5000 (40%)
Test
Test set: Average loss: 1.4498, Accuracy: 1991/5000 (40%)
Test set: Average loss: 0.7399, Accuracy: 25/25 (100%)
## seed: 12
Validation accuracy before training:
Test set: Average loss: 1.7127, Accuracy: 1054/5000 (21%)
[epoch 1] loss: 1.7777356
Test set: Average loss: 1.6991, Accuracy: 1121/5000 (22%)
[epoch 2] loss: 1.6992406
Test set: Average loss: 1.6858, Accuracy: 1180/5000 (24%)
[epoch 3] loss: 1.6214666
Test set: Average loss: 1.6729, Accuracy: 1223/5000 (24%)
[epoch 4] loss: 1.5455384
Test set: Average loss: 1.6603, Accuracy: 1254/5000 (25%)
[epoch 5] loss: 1.4725592
Test set: Average loss: 1.6481, Accuracy: 1289/5000 (26%)
[epoch 6] loss: 1.4036326
Test set: Average loss: 1.6364, Accuracy: 1337/5000 (27%)
[epoch 7] loss: 1.3396950
Test set: Average loss: 1.6250, Accuracy: 1346/5000 (27%)
[epoch 8] loss: 1.2812544
Test set: Average loss: 1.6141, Accuracy: 1368/5000 (27%)
[epoch 9] loss: 1.2283332
Test set: Average loss: 1.6037, Accuracy: 1400/5000 (28%)
[epoch 10] loss: 1.1806108
Test set: Average loss: 1.5938, Accuracy: 1433/5000 (29%)
[epoch 11] loss: 1.1375384
Test set: Average loss: 1.5846, Accuracy: 1460/5000 (29%)
[epoch 12] loss: 1.0984226
Test set: Average loss: 1.5759, Accuracy: 1492/5000 (30%)
[epoch 13] loss: 1.0625482
Test set: Average loss: 1.5679, Accuracy: 1536/5000 (31%)
[epoch 14] loss: 1.0292929
Test set: Average loss: 1.5605, Accuracy: 1571/5000 (31%)
[epoch 15] loss: 0.9981776
Test set: Average loss: 1.5538, Accuracy: 1605/5000 (32%)
[epoch 16] loss: 0.9688514
Test set: Average loss: 1.5476, Accuracy: 1629/5000 (33%)
[epoch 17] loss: 0.9410551
Test set: Average loss: 1.5420, Accuracy: 1649/5000 (33%)
[epoch 18] loss: 0.9145904
Test set: Average loss: 1.5369, Accuracy: 1674/5000 (33%)
[epoch 19] loss: 0.8893073
Test set: Average loss: 1.5323, Accuracy: 1686/5000 (34%)
[epoch 20] loss: 0.8650995
Test set: Average loss: 1.5281, Accuracy: 1696/5000 (34%)
[epoch 21] loss: 0.8419117
Test set: Average loss: 1.5243, Accuracy: 1715/5000 (34%)
[epoch 22] loss: 0.8197381
Test set: Average loss: 1.5208, Accuracy: 1722/5000 (34%)
[epoch 23] loss: 0.7986120
Test set: Average loss: 1.5176, Accuracy: 1738/5000 (35%)
[epoch 24] loss: 0.7785813
Test set: Average loss: 1.5147, Accuracy: 1748/5000 (35%)
[epoch 25] loss: 0.7596822
Test set: Average loss: 1.5121, Accuracy: 1761/5000 (35%)
Validation:
Test set: Average loss: 1.5121, Accuracy: 1761/5000 (35%)
Test
Test set: Average loss: 1.5221, Accuracy: 1683/5000 (34%)
Test set: Average loss: 0.7419, Accuracy: 25/25 (100%)
## seed: 13
Validation accuracy before training:
Test set: Average loss: 1.6120, Accuracy: 862/5000 (17%)
[epoch 1] loss: 1.6418539
Test set: Average loss: 1.5996, Accuracy: 946/5000 (19%)
[epoch 2] loss: 1.5684627
Test set: Average loss: 1.5881, Accuracy: 1052/5000 (21%)
[epoch 3] loss: 1.4983227
Test set: Average loss: 1.5772, Accuracy: 1127/5000 (23%)
[epoch 4] loss: 1.4325145
Test set: Average loss: 1.5672, Accuracy: 1207/5000 (24%)
[epoch 5] loss: 1.3716887
Test set: Average loss: 1.5580, Accuracy: 1283/5000 (26%)
[epoch 6] loss: 1.3159653
Test set: Average loss: 1.5494, Accuracy: 1355/5000 (27%)
[epoch 7] loss: 1.2650633
Test set: Average loss: 1.5416, Accuracy: 1410/5000 (28%)
[epoch 8] loss: 1.2184854
Test set: Average loss: 1.5343, Accuracy: 1453/5000 (29%)
[epoch 9] loss: 1.1756389
Test set: Average loss: 1.5276, Accuracy: 1488/5000 (30%)
[epoch 10] loss: 1.1359286
Test set: Average loss: 1.5213, Accuracy: 1523/5000 (30%)
[epoch 11] loss: 1.0988426
Test set: Average loss: 1.5154, Accuracy: 1552/5000 (31%)
[epoch 12] loss: 1.0640073
Test set: Average loss: 1.5099, Accuracy: 1575/5000 (32%)
[epoch 13] loss: 1.0311893
Test set: Average loss: 1.5047, Accuracy: 1613/5000 (32%)
[epoch 14] loss: 1.0002514
Test set: Average loss: 1.4997, Accuracy: 1633/5000 (33%)
[epoch 15] loss: 0.9711029
Test set: Average loss: 1.4949, Accuracy: 1663/5000 (33%)
[epoch 16] loss: 0.9436675
Test set: Average loss: 1.4903, Accuracy: 1694/5000 (34%)
[epoch 17] loss: 0.9178660
Test set: Average loss: 1.4858, Accuracy: 1710/5000 (34%)
[epoch 18] loss: 0.8936019
Test set: Average loss: 1.4816, Accuracy: 1737/5000 (35%)
[epoch 19] loss: 0.8707599
Test set: Average loss: 1.4775, Accuracy: 1764/5000 (35%)
[epoch 20] loss: 0.8492088
Test set: Average loss: 1.4735, Accuracy: 1779/5000 (36%)
[epoch 21] loss: 0.8288141
Test set: Average loss: 1.4697, Accuracy: 1800/5000 (36%)
[epoch 22] loss: 0.8094555
Test set: Average loss: 1.4660, Accuracy: 1841/5000 (37%)
[epoch 23] loss: 0.7910424
Test set: Average loss: 1.4626, Accuracy: 1864/5000 (37%)
[epoch 24] loss: 0.7735192
Test set: Average loss: 1.4592, Accuracy: 1874/5000 (37%)
[epoch 25] loss: 0.7568560
Test set: Average loss: 1.4560, Accuracy: 1886/5000 (38%)
Validation:
Test set: Average loss: 1.4560, Accuracy: 1886/5000 (38%)
Test
Test set: Average loss: 1.4546, Accuracy: 1934/5000 (39%)
Test set: Average loss: 0.7410, Accuracy: 25/25 (100%)
50
## seed: 11
Validation accuracy before training:
Test set: Average loss: 1.9658, Accuracy: 269/5000 (5%)
[epoch 1] loss: 2.0406172
Test set: Average loss: 1.9215, Accuracy: 295/5000 (6%)
[epoch 2] loss: 1.8942125
Test set: Average loss: 1.8767, Accuracy: 331/5000 (7%)
[epoch 3] loss: 1.7735863
Test set: Average loss: 1.8344, Accuracy: 409/5000 (8%)
[epoch 4] loss: 1.6512368
Test set: Average loss: 1.7943, Accuracy: 496/5000 (10%)
[epoch 5] loss: 1.5361875
Test set: Average loss: 1.7571, Accuracy: 581/5000 (12%)
[epoch 6] loss: 1.4472156
Test set: Average loss: 1.7231, Accuracy: 714/5000 (14%)
[epoch 7] loss: 1.3689644
Test set: Average loss: 1.6923, Accuracy: 806/5000 (16%)
[epoch 8] loss: 1.2812918
Test set: Average loss: 1.6651, Accuracy: 897/5000 (18%)
[epoch 9] loss: 1.2058592
Test set: Average loss: 1.6416, Accuracy: 974/5000 (19%)
[epoch 10] loss: 1.2039011
Test set: Average loss: 1.6219, Accuracy: 1051/5000 (21%)
[epoch 11] loss: 1.1189665
Test set: Average loss: 1.6055, Accuracy: 1108/5000 (22%)
[epoch 12] loss: 1.0809699
Test set: Average loss: 1.5916, Accuracy: 1153/5000 (23%)
[epoch 13] loss: 1.0365431
Test set: Average loss: 1.5798, Accuracy: 1206/5000 (24%)
[epoch 14] loss: 1.0076760
Test set: Average loss: 1.5699, Accuracy: 1260/5000 (25%)
[epoch 15] loss: 0.9929679
Test set: Average loss: 1.5619, Accuracy: 1294/5000 (26%)
[epoch 16] loss: 0.9413669
Test set: Average loss: 1.5549, Accuracy: 1334/5000 (27%)
[epoch 17] loss: 0.8964144
Test set: Average loss: 1.5494, Accuracy: 1374/5000 (27%)
[epoch 18] loss: 0.8686966
Test set: Average loss: 1.5447, Accuracy: 1399/5000 (28%)
[epoch 19] loss: 0.8321182
Test set: Average loss: 1.5403, Accuracy: 1416/5000 (28%)
[epoch 20] loss: 0.8422987
Epoch 19: reducing learning rate of group 0 to 5.0000e-06.
Test set: Average loss: 1.5369, Accuracy: 1422/5000 (28%)
[epoch 21] loss: 0.8094255
Test set: Average loss: 1.5366, Accuracy: 1428/5000 (29%)
[epoch 22] loss: 0.8078368
Test set: Average loss: 1.5362, Accuracy: 1431/5000 (29%)
[epoch 23] loss: 0.7718062
Test set: Average loss: 1.5359, Accuracy: 1434/5000 (29%)
[epoch 24] loss: 0.7959192
Epoch 23: reducing learning rate of group 0 to 5.0000e-07.
Test set: Average loss: 1.5356, Accuracy: 1434/5000 (29%)
[epoch 25] loss: 0.8076129
Epoch 24: reducing learning rate of group 0 to 5.0000e-08.
Test set: Average loss: 1.5355, Accuracy: 1434/5000 (29%)
Validation:
Test set: Average loss: 1.5355, Accuracy: 1434/5000 (29%)
Test
Test set: Average loss: 1.5390, Accuracy: 1423/5000 (28%)
Test set: Average loss: 0.7886, Accuracy: 48/50 (96%)
## seed: 12
Validation accuracy before training:
Test set: Average loss: 1.7850, Accuracy: 734/5000 (15%)
[epoch 1] loss: 1.8164632
Test set: Average loss: 1.7582, Accuracy: 824/5000 (16%)
[epoch 2] loss: 1.7007908
Test set: Average loss: 1.7323, Accuracy: 938/5000 (19%)
[epoch 3] loss: 1.6202843
Test set: Average loss: 1.7074, Accuracy: 1038/5000 (21%)
[epoch 4] loss: 1.5405340
Test set: Average loss: 1.6841, Accuracy: 1113/5000 (22%)
[epoch 5] loss: 1.4698086
Test set: Average loss: 1.6605, Accuracy: 1162/5000 (23%)
[epoch 6] loss: 1.3654453
Test set: Average loss: 1.6372, Accuracy: 1229/5000 (25%)
[epoch 7] loss: 1.3302068
Test set: Average loss: 1.6147, Accuracy: 1305/5000 (26%)
[epoch 8] loss: 1.2646299
Test set: Average loss: 1.5942, Accuracy: 1349/5000 (27%)
[epoch 9] loss: 1.1934695
Test set: Average loss: 1.5763, Accuracy: 1430/5000 (29%)
[epoch 10] loss: 1.1780521
Test set: Average loss: 1.5605, Accuracy: 1478/5000 (30%)
[epoch 11] loss: 1.1180098
Test set: Average loss: 1.5457, Accuracy: 1545/5000 (31%)
[epoch 12] loss: 1.0799503
Test set: Average loss: 1.5322, Accuracy: 1618/5000 (32%)
[epoch 13] loss: 1.0365722
Test set: Average loss: 1.5197, Accuracy: 1682/5000 (34%)
[epoch 14] loss: 0.9824464
Test set: Average loss: 1.5084, Accuracy: 1739/5000 (35%)
[epoch 15] loss: 0.9786945
Test set: Average loss: 1.4982, Accuracy: 1786/5000 (36%)
[epoch 16] loss: 0.9226542
Test set: Average loss: 1.4891, Accuracy: 1822/5000 (36%)
[epoch 17] loss: 0.9018247
Test set: Average loss: 1.4808, Accuracy: 1848/5000 (37%)
[epoch 18] loss: 0.8650050
Test set: Average loss: 1.4736, Accuracy: 1874/5000 (37%)
[epoch 19] loss: 0.8226147
Test set: Average loss: 1.4669, Accuracy: 1911/5000 (38%)
[epoch 20] loss: 0.8255533
Epoch 19: reducing learning rate of group 0 to 5.0000e-06.
Test set: Average loss: 1.4613, Accuracy: 1940/5000 (39%)
[epoch 21] loss: 0.8131195
Test set: Average loss: 1.4608, Accuracy: 1941/5000 (39%)
[epoch 22] loss: 0.8139803
Epoch 21: reducing learning rate of group 0 to 5.0000e-07.
Test set: Average loss: 1.4603, Accuracy: 1942/5000 (39%)
[epoch 23] loss: 0.8067621
Test set: Average loss: 1.4603, Accuracy: 1942/5000 (39%)
[epoch 24] loss: 0.8103759
Epoch 23: reducing learning rate of group 0 to 5.0000e-08.
Test set: Average loss: 1.4602, Accuracy: 1943/5000 (39%)
[epoch 25] loss: 0.8142810
Epoch 24: reducing learning rate of group 0 to 5.0000e-09.
Test set: Average loss: 1.4602, Accuracy: 1943/5000 (39%)
Validation:
Test set: Average loss: 1.4602, Accuracy: 1943/5000 (39%)
Test
Test set: Average loss: 1.4657, Accuracy: 1968/5000 (39%)
Test set: Average loss: 0.8064, Accuracy: 48/50 (96%)
## seed: 13
Validation accuracy before training:
Test set: Average loss: 1.4346, Accuracy: 1719/5000 (34%)
[epoch 1] loss: 1.4379662
Test set: Average loss: 1.4097, Accuracy: 1824/5000 (36%)
[epoch 2] loss: 1.2902880
Test set: Average loss: 1.3945, Accuracy: 1888/5000 (38%)
[epoch 3] loss: 1.2535647
Test set: Average loss: 1.3826, Accuracy: 1953/5000 (39%)
[epoch 4] loss: 1.1816144
Test set: Average loss: 1.3720, Accuracy: 2004/5000 (40%)
[epoch 5] loss: 1.1027907
Test set: Average loss: 1.3625, Accuracy: 2032/5000 (41%)
[epoch 6] loss: 1.0606009
Test set: Average loss: 1.3544, Accuracy: 2070/5000 (41%)
[epoch 7] loss: 1.0256034
Test set: Average loss: 1.3465, Accuracy: 2103/5000 (42%)
[epoch 8] loss: 0.9570880
Test set: Average loss: 1.3390, Accuracy: 2107/5000 (42%)
[epoch 9] loss: 0.9215765
Test set: Average loss: 1.3319, Accuracy: 2144/5000 (43%)
[epoch 10] loss: 0.8750086
Test set: Average loss: 1.3250, Accuracy: 2161/5000 (43%)
[epoch 11] loss: 0.8347279
Test set: Average loss: 1.3187, Accuracy: 2179/5000 (44%)
[epoch 12] loss: 0.8257544
Test set: Average loss: 1.3129, Accuracy: 2205/5000 (44%)
[epoch 13] loss: 0.8151518
Test set: Average loss: 1.3078, Accuracy: 2229/5000 (45%)
[epoch 14] loss: 0.7626121
Test set: Average loss: 1.3032, Accuracy: 2260/5000 (45%)
[epoch 15] loss: 0.7345577
Test set: Average loss: 1.2991, Accuracy: 2292/5000 (46%)
[epoch 16] loss: 0.7217135
Test set: Average loss: 1.2954, Accuracy: 2298/5000 (46%)
[epoch 17] loss: 0.6908787
Test set: Average loss: 1.2917, Accuracy: 2303/5000 (46%)
[epoch 18] loss: 0.6567715
Test set: Average loss: 1.2883, Accuracy: 2321/5000 (46%)
[epoch 19] loss: 0.6653513
Epoch 18: reducing learning rate of group 0 to 5.0000e-06.
Test set: Average loss: 1.2854, Accuracy: 2339/5000 (47%)
[epoch 20] loss: 0.6385995
Test set: Average loss: 1.2852, Accuracy: 2343/5000 (47%)
[epoch 21] loss: 0.6263939
Test set: Average loss: 1.2849, Accuracy: 2346/5000 (47%)
[epoch 22] loss: 0.6445024
Epoch 21: reducing learning rate of group 0 to 5.0000e-07.
Test set: Average loss: 1.2847, Accuracy: 2347/5000 (47%)
[epoch 23] loss: 0.6294781
Epoch 22: reducing learning rate of group 0 to 5.0000e-08.
Test set: Average loss: 1.2846, Accuracy: 2348/5000 (47%)
[epoch 24] loss: 0.6281813
Epoch 23: reducing learning rate of group 0 to 5.0000e-09.
Test set: Average loss: 1.2846, Accuracy: 2348/5000 (47%)
[epoch 25] loss: 0.6346996
Epoch 24: reducing learning rate of group 0 to 5.0000e-10.
Test set: Average loss: 1.2846, Accuracy: 2348/5000 (47%)
Validation:
Test set: Average loss: 1.2846, Accuracy: 2348/5000 (47%)
Test
Test set: Average loss: 1.2942, Accuracy: 2318/5000 (46%)
Test set: Average loss: 0.6325, Accuracy: 48/50 (96%)
100
## seed: 11
Validation accuracy before training:
Test set: Average loss: 1.7114, Accuracy: 801/5000 (16%)
[epoch 1] loss: 1.6149125
Test set: Average loss: 1.6598, Accuracy: 939/5000 (19%)
[epoch 2] loss: 1.4949951
Test set: Average loss: 1.6266, Accuracy: 1047/5000 (21%)
[epoch 3] loss: 1.4215720
Test set: Average loss: 1.5997, Accuracy: 1143/5000 (23%)
[epoch 4] loss: 1.3750212
Test set: Average loss: 1.5777, Accuracy: 1238/5000 (25%)
[epoch 5] loss: 1.2832509
Test set: Average loss: 1.5505, Accuracy: 1328/5000 (27%)
[epoch 6] loss: 1.2616271
Test set: Average loss: 1.5244, Accuracy: 1458/5000 (29%)
[epoch 7] loss: 1.1753027
Test set: Average loss: 1.5026, Accuracy: 1574/5000 (31%)
[epoch 8] loss: 1.1171788
Test set: Average loss: 1.4832, Accuracy: 1666/5000 (33%)
[epoch 9] loss: 1.1054418
Test set: Average loss: 1.4677, Accuracy: 1731/5000 (35%)
[epoch 10] loss: 1.0808514
Test set: Average loss: 1.4529, Accuracy: 1785/5000 (36%)
[epoch 11] loss: 1.0210783
Test set: Average loss: 1.4397, Accuracy: 1850/5000 (37%)
[epoch 12] loss: 1.0040391
Test set: Average loss: 1.4272, Accuracy: 1906/5000 (38%)
[epoch 13] loss: 0.9338752
Test set: Average loss: 1.4141, Accuracy: 1953/5000 (39%)
[epoch 14] loss: 0.9505323
Epoch 13: reducing learning rate of group 0 to 5.0000e-06.
Test set: Average loss: 1.4018, Accuracy: 2005/5000 (40%)
[epoch 15] loss: 0.9365004
Epoch 14: reducing learning rate of group 0 to 5.0000e-07.
Test set: Average loss: 1.4008, Accuracy: 2007/5000 (40%)
[epoch 16] loss: 0.9056314
Test set: Average loss: 1.4007, Accuracy: 2007/5000 (40%)
[epoch 17] loss: 0.9097075
Epoch 16: reducing learning rate of group 0 to 5.0000e-08.
Test set: Average loss: 1.4006, Accuracy: 2009/5000 (40%)
[epoch 18] loss: 0.9159736
Epoch 17: reducing learning rate of group 0 to 5.0000e-09.
Test set: Average loss: 1.4006, Accuracy: 2009/5000 (40%)
[epoch 19] loss: 0.9217724
Epoch 18: reducing learning rate of group 0 to 5.0000e-10.
Test set: Average loss: 1.4006, Accuracy: 2009/5000 (40%)
[epoch 20] loss: 0.8817463
Test set: Average loss: 1.4006, Accuracy: 2009/5000 (40%)
[epoch 21] loss: 0.9307033
Epoch 20: reducing learning rate of group 0 to 5.0000e-11.
Test set: Average loss: 1.4006, Accuracy: 2009/5000 (40%)
[epoch 22] loss: 0.8932657
Epoch 21: reducing learning rate of group 0 to 5.0000e-12.
Test set: Average loss: 1.4006, Accuracy: 2009/5000 (40%)
[epoch 23] loss: 0.9361461
Epoch 22: reducing learning rate of group 0 to 5.0000e-13.
Test set: Average loss: 1.4006, Accuracy: 2009/5000 (40%)
[epoch 24] loss: 0.9142238
Epoch 23: reducing learning rate of group 0 to 5.0000e-14.
Test set: Average loss: 1.4006, Accuracy: 2009/5000 (40%)
[epoch 25] loss: 0.9273629
Epoch 24: reducing learning rate of group 0 to 5.0000e-15.
Test set: Average loss: 1.4006, Accuracy: 2009/5000 (40%)
Validation:
Test set: Average loss: 1.4006, Accuracy: 2009/5000 (40%)
Test
Test set: Average loss: 1.4207, Accuracy: 1903/5000 (38%)
Test set: Average loss: 0.9122, Accuracy: 90/100 (90%)
## seed: 12
Validation accuracy before training:
Test set: Average loss: 1.8330, Accuracy: 483/5000 (10%)
[epoch 1] loss: 1.8733286
Test set: Average loss: 1.7696, Accuracy: 620/5000 (12%)
[epoch 2] loss: 1.6797506
Test set: Average loss: 1.7278, Accuracy: 743/5000 (15%)
[epoch 3] loss: 1.6888596
Epoch 2: reducing learning rate of group 0 to 5.0000e-06.
Test set: Average loss: 1.6912, Accuracy: 890/5000 (18%)
[epoch 4] loss: 1.4822654
Test set: Average loss: 1.6876, Accuracy: 907/5000 (18%)
[epoch 5] loss: 1.5040699
Epoch 4: reducing learning rate of group 0 to 5.0000e-07.
Test set: Average loss: 1.6843, Accuracy: 918/5000 (18%)
[epoch 6] loss: 1.5285646
Epoch 5: reducing learning rate of group 0 to 5.0000e-08.
Test set: Average loss: 1.6840, Accuracy: 919/5000 (18%)
[epoch 7] loss: 1.4490083
Test set: Average loss: 1.6840, Accuracy: 919/5000 (18%)
[epoch 8] loss: 1.4823934
Epoch 7: reducing learning rate of group 0 to 5.0000e-09.
Test set: Average loss: 1.6839, Accuracy: 919/5000 (18%)
[epoch 9] loss: 1.5128802
Epoch 8: reducing learning rate of group 0 to 5.0000e-10.
Test set: Average loss: 1.6839, Accuracy: 919/5000 (18%)
[epoch 10] loss: 1.4862804
Epoch 9: reducing learning rate of group 0 to 5.0000e-11.
Test set: Average loss: 1.6839, Accuracy: 919/5000 (18%)
[epoch 11] loss: 1.4963488
Epoch 10: reducing learning rate of group 0 to 5.0000e-12.
Test set: Average loss: 1.6839, Accuracy: 919/5000 (18%)
[epoch 12] loss: 1.4521761
Epoch 11: reducing learning rate of group 0 to 5.0000e-13.
Test set: Average loss: 1.6839, Accuracy: 919/5000 (18%)
[epoch 13] loss: 1.5737647
Epoch 12: reducing learning rate of group 0 to 5.0000e-14.
Test set: Average loss: 1.6839, Accuracy: 919/5000 (18%)
[epoch 14] loss: 1.4840721
Epoch 13: reducing learning rate of group 0 to 5.0000e-15.
Test set: Average loss: 1.6839, Accuracy: 919/5000 (18%)
[epoch 15] loss: 1.4864139
Epoch 14: reducing learning rate of group 0 to 5.0000e-16.
Test set: Average loss: 1.6839, Accuracy: 919/5000 (18%)
[epoch 16] loss: 1.4817547
Epoch 15: reducing learning rate of group 0 to 5.0000e-17.
Test set: Average loss: 1.6839, Accuracy: 919/5000 (18%)
[epoch 17] loss: 1.4940185
Epoch 16: reducing learning rate of group 0 to 5.0000e-18.
Test set: Average loss: 1.6839, Accuracy: 919/5000 (18%)
[epoch 18] loss: 1.5019715
Epoch 17: reducing learning rate of group 0 to 5.0000e-19.
Test set: Average loss: 1.6839, Accuracy: 919/5000 (18%)
[epoch 19] loss: 1.5041592
Epoch 18: reducing learning rate of group 0 to 5.0000e-20.
Test set: Average loss: 1.6839, Accuracy: 919/5000 (18%)
[epoch 20] loss: 1.4727557
Epoch 19: reducing learning rate of group 0 to 5.0000e-21.
Test set: Average loss: 1.6839, Accuracy: 919/5000 (18%)
[epoch 21] loss: 1.4936599
Epoch 20: reducing learning rate of group 0 to 5.0000e-22.
Test set: Average loss: 1.6839, Accuracy: 919/5000 (18%)
[epoch 22] loss: 1.5063842
Epoch 21: reducing learning rate of group 0 to 5.0000e-23.
Test set: Average loss: 1.6839, Accuracy: 919/5000 (18%)
[epoch 23] loss: 1.4902049
Epoch 22: reducing learning rate of group 0 to 5.0000e-24.
Test set: Average loss: 1.6839, Accuracy: 919/5000 (18%)
[epoch 24] loss: 1.4927065
Epoch 23: reducing learning rate of group 0 to 5.0000e-25.
Test set: Average loss: 1.6839, Accuracy: 919/5000 (18%)
[epoch 25] loss: 1.4886377
Epoch 24: reducing learning rate of group 0 to 5.0000e-26.
Test set: Average loss: 1.6839, Accuracy: 919/5000 (18%)
Validation:
Test set: Average loss: 1.6839, Accuracy: 919/5000 (18%)
Test
Test set: Average loss: 1.6836, Accuracy: 954/5000 (19%)
Test set: Average loss: 1.4936, Accuracy: 42/100 (42%)
## seed: 13
Validation accuracy before training:
Test set: Average loss: 1.6201, Accuracy: 1014/5000 (20%)
[epoch 1] loss: 1.6614015
Test set: Average loss: 1.5862, Accuracy: 1093/5000 (22%)
[epoch 2] loss: 1.5517305
Test set: Average loss: 1.5575, Accuracy: 1165/5000 (23%)
[epoch 3] loss: 1.4043200
Test set: Average loss: 1.5342, Accuracy: 1266/5000 (25%)
[epoch 4] loss: 1.3988542
Test set: Average loss: 1.5134, Accuracy: 1363/5000 (27%)
[epoch 5] loss: 1.3624754
Test set: Average loss: 1.4942, Accuracy: 1431/5000 (29%)
[epoch 6] loss: 1.2613109
Test set: Average loss: 1.4779, Accuracy: 1512/5000 (30%)
[epoch 7] loss: 1.1671636
Test set: Average loss: 1.4643, Accuracy: 1585/5000 (32%)
[epoch 8] loss: 1.2056213
Epoch 7: reducing learning rate of group 0 to 5.0000e-06.
Test set: Average loss: 1.4526, Accuracy: 1662/5000 (33%)
[epoch 9] loss: 1.1850635
Epoch 8: reducing learning rate of group 0 to 5.0000e-07.
Test set: Average loss: 1.4516, Accuracy: 1668/5000 (33%)
[epoch 10] loss: 1.2227634
Epoch 9: reducing learning rate of group 0 to 5.0000e-08.
Test set: Average loss: 1.4515, Accuracy: 1667/5000 (33%)
[epoch 11] loss: 1.1730013
Epoch 10: reducing learning rate of group 0 to 5.0000e-09.
Test set: Average loss: 1.4515, Accuracy: 1667/5000 (33%)
[epoch 12] loss: 1.1353943
Test set: Average loss: 1.4515, Accuracy: 1667/5000 (33%)
[epoch 13] loss: 1.1492588
Epoch 12: reducing learning rate of group 0 to 5.0000e-10.
Test set: Average loss: 1.4515, Accuracy: 1667/5000 (33%)
[epoch 14] loss: 1.1567684
Epoch 13: reducing learning rate of group 0 to 5.0000e-11.
Test set: Average loss: 1.4515, Accuracy: 1667/5000 (33%)
[epoch 15] loss: 1.1438091
Epoch 14: reducing learning rate of group 0 to 5.0000e-12.
Test set: Average loss: 1.4515, Accuracy: 1667/5000 (33%)
[epoch 16] loss: 1.1956536
Epoch 15: reducing learning rate of group 0 to 5.0000e-13.
Test set: Average loss: 1.4515, Accuracy: 1667/5000 (33%)
[epoch 17] loss: 1.1468101
Epoch 16: reducing learning rate of group 0 to 5.0000e-14.
Test set: Average loss: 1.4515, Accuracy: 1667/5000 (33%)
[epoch 18] loss: 1.1709553
Epoch 17: reducing learning rate of group 0 to 5.0000e-15.
Test set: Average loss: 1.4515, Accuracy: 1667/5000 (33%)
[epoch 19] loss: 1.1697771
Epoch 18: reducing learning rate of group 0 to 5.0000e-16.
Test set: Average loss: 1.4515, Accuracy: 1667/5000 (33%)
[epoch 20] loss: 1.1592022
Epoch 19: reducing learning rate of group 0 to 5.0000e-17.
Test set: Average loss: 1.4515, Accuracy: 1667/5000 (33%)
[epoch 21] loss: 1.1726227
Epoch 20: reducing learning rate of group 0 to 5.0000e-18.
Test set: Average loss: 1.4515, Accuracy: 1667/5000 (33%)
[epoch 22] loss: 1.1465086
Epoch 21: reducing learning rate of group 0 to 5.0000e-19.
Test set: Average loss: 1.4515, Accuracy: 1667/5000 (33%)
[epoch 23] loss: 1.1817017
Epoch 22: reducing learning rate of group 0 to 5.0000e-20.
Test set: Average loss: 1.4515, Accuracy: 1667/5000 (33%)
[epoch 24] loss: 1.1493917
Epoch 23: reducing learning rate of group 0 to 5.0000e-21.
Test set: Average loss: 1.4515, Accuracy: 1667/5000 (33%)
[epoch 25] loss: 1.1646091
Epoch 24: reducing learning rate of group 0 to 5.0000e-22.
Test set: Average loss: 1.4515, Accuracy: 1667/5000 (33%)
Validation:
Test set: Average loss: 1.4516, Accuracy: 1668/5000 (33%)
Test
Test set: Average loss: 1.4574, Accuracy: 1637/5000 (33%)
Test set: Average loss: 1.1569, Accuracy: 69/100 (69%)
250
## seed: 11
Validation accuracy before training:
Test set: Average loss: 1.7070, Accuracy: 1350/5000 (27%)
[epoch 1] loss: 1.5922990
Test set: Average loss: 1.6097, Accuracy: 1566/5000 (31%)
[epoch 2] loss: 1.4383121
Test set: Average loss: 1.5163, Accuracy: 1832/5000 (37%)
[epoch 3] loss: 1.3331802
Test set: Average loss: 1.4506, Accuracy: 2083/5000 (42%)
[epoch 4] loss: 1.2511791
Test set: Average loss: 1.4092, Accuracy: 2274/5000 (45%)
[epoch 5] loss: 1.1900456
Test set: Average loss: 1.3760, Accuracy: 2398/5000 (48%)
[epoch 6] loss: 1.1302161
Test set: Average loss: 1.3530, Accuracy: 2464/5000 (49%)
[epoch 7] loss: 1.0762556
Test set: Average loss: 1.3309, Accuracy: 2509/5000 (50%)
[epoch 8] loss: 1.0293604
Test set: Average loss: 1.3122, Accuracy: 2562/5000 (51%)
[epoch 9] loss: 0.9841438
Test set: Average loss: 1.2950, Accuracy: 2633/5000 (53%)
[epoch 10] loss: 0.9449506
Test set: Average loss: 1.2813, Accuracy: 2654/5000 (53%)
[epoch 11] loss: 0.9104810
Test set: Average loss: 1.2690, Accuracy: 2696/5000 (54%)
[epoch 12] loss: 0.8759101
Test set: Average loss: 1.2594, Accuracy: 2724/5000 (54%)
[epoch 13] loss: 0.8442231
Test set: Average loss: 1.2512, Accuracy: 2753/5000 (55%)
[epoch 14] loss: 0.8158468
Test set: Average loss: 1.2441, Accuracy: 2759/5000 (55%)
[epoch 15] loss: 0.7885908
Test set: Average loss: 1.2385, Accuracy: 2768/5000 (55%)
[epoch 16] loss: 0.7620290
Test set: Average loss: 1.2310, Accuracy: 2792/5000 (56%)
[epoch 17] loss: 0.7390289
Test set: Average loss: 1.2280, Accuracy: 2789/5000 (56%)
[epoch 18] loss: 0.7173362
Test set: Average loss: 1.2244, Accuracy: 2778/5000 (56%)
[epoch 19] loss: 0.6961213
Test set: Average loss: 1.2191, Accuracy: 2787/5000 (56%)
[epoch 20] loss: 0.6772078
Test set: Average loss: 1.2145, Accuracy: 2792/5000 (56%)
[epoch 21] loss: 0.6575655
Test set: Average loss: 1.2130, Accuracy: 2782/5000 (56%)
[epoch 22] loss: 0.6396662
Test set: Average loss: 1.2109, Accuracy: 2777/5000 (56%)
[epoch 23] loss: 0.6239349
Test set: Average loss: 1.2072, Accuracy: 2785/5000 (56%)
[epoch 24] loss: 0.6048012
Test set: Average loss: 1.2042, Accuracy: 2793/5000 (56%)
[epoch 25] loss: 0.5885411
Test set: Average loss: 1.2022, Accuracy: 2804/5000 (56%)
Validation:
Test set: Average loss: 1.2022, Accuracy: 2804/5000 (56%)
Test
Test set: Average loss: 1.2144, Accuracy: 2746/5000 (55%)
Test set: Average loss: 0.5781, Accuracy: 242/250 (97%)
## seed: 12
Validation accuracy before training:
Test set: Average loss: 1.8491, Accuracy: 555/5000 (11%)
[epoch 1] loss: 1.8871729
Test set: Average loss: 1.7477, Accuracy: 908/5000 (18%)
[epoch 2] loss: 1.7093033
Test set: Average loss: 1.6610, Accuracy: 1235/5000 (25%)
[epoch 3] loss: 1.5727342
Test set: Average loss: 1.5984, Accuracy: 1466/5000 (29%)
[epoch 4] loss: 1.4712276
Test set: Average loss: 1.5523, Accuracy: 1639/5000 (33%)
[epoch 5] loss: 1.3893608
Test set: Average loss: 1.5178, Accuracy: 1765/5000 (35%)
[epoch 6] loss: 1.3188833
Test set: Average loss: 1.4911, Accuracy: 1834/5000 (37%)
[epoch 7] loss: 1.2509757
Test set: Average loss: 1.4661, Accuracy: 1916/5000 (38%)
[epoch 8] loss: 1.1996284
Test set: Average loss: 1.4441, Accuracy: 1969/5000 (39%)
[epoch 9] loss: 1.1467731
Test set: Average loss: 1.4264, Accuracy: 2033/5000 (41%)
[epoch 10] loss: 1.0996238
Test set: Average loss: 1.4099, Accuracy: 2082/5000 (42%)
[epoch 11] loss: 1.0593107
Test set: Average loss: 1.3968, Accuracy: 2126/5000 (43%)
[epoch 12] loss: 1.0247682
Test set: Average loss: 1.3828, Accuracy: 2167/5000 (43%)
[epoch 13] loss: 0.9870217
Test set: Average loss: 1.3743, Accuracy: 2188/5000 (44%)
[epoch 14] loss: 0.9569106
Test set: Average loss: 1.3642, Accuracy: 2221/5000 (44%)
[epoch 15] loss: 0.9222525
Test set: Average loss: 1.3554, Accuracy: 2247/5000 (45%)
[epoch 16] loss: 0.8967011
Test set: Average loss: 1.3493, Accuracy: 2262/5000 (45%)
[epoch 17] loss: 0.8681005
Test set: Average loss: 1.3397, Accuracy: 2308/5000 (46%)
[epoch 18] loss: 0.8422363
Test set: Average loss: 1.3332, Accuracy: 2321/5000 (46%)
[epoch 19] loss: 0.8189895
Test set: Average loss: 1.3259, Accuracy: 2351/5000 (47%)
[epoch 20] loss: 0.7953203
Test set: Average loss: 1.3219, Accuracy: 2364/5000 (47%)
[epoch 21] loss: 0.7735879
Test set: Average loss: 1.3173, Accuracy: 2377/5000 (48%)
[epoch 22] loss: 0.7523591
Test set: Average loss: 1.3124, Accuracy: 2400/5000 (48%)
[epoch 23] loss: 0.7336049
Test set: Average loss: 1.3057, Accuracy: 2418/5000 (48%)
[epoch 24] loss: 0.7124556
Test set: Average loss: 1.3031, Accuracy: 2426/5000 (49%)
[epoch 25] loss: 0.6948142
Test set: Average loss: 1.2978, Accuracy: 2438/5000 (49%)
Validation:
Test set: Average loss: 1.2978, Accuracy: 2438/5000 (49%)
Test
Test set: Average loss: 1.2908, Accuracy: 2470/5000 (49%)
Test set: Average loss: 0.6823, Accuracy: 234/250 (94%)
## seed: 13
Validation accuracy before training:
Test set: Average loss: 1.6346, Accuracy: 1056/5000 (21%)
[epoch 1] loss: 1.5509461
Test set: Average loss: 1.5319, Accuracy: 1766/5000 (35%)
[epoch 2] loss: 1.4009712
Test set: Average loss: 1.4687, Accuracy: 2077/5000 (42%)
[epoch 3] loss: 1.2983958
Test set: Average loss: 1.4219, Accuracy: 2241/5000 (45%)
[epoch 4] loss: 1.2207872
Test set: Average loss: 1.3860, Accuracy: 2379/5000 (48%)
[epoch 5] loss: 1.1499530
Test set: Average loss: 1.3597, Accuracy: 2466/5000 (49%)
[epoch 6] loss: 1.0938505
Test set: Average loss: 1.3390, Accuracy: 2542/5000 (51%)
[epoch 7] loss: 1.0416373
Test set: Average loss: 1.3204, Accuracy: 2605/5000 (52%)
[epoch 8] loss: 0.9975795
Test set: Average loss: 1.3060, Accuracy: 2621/5000 (52%)
[epoch 9] loss: 0.9577221
Test set: Average loss: 1.2943, Accuracy: 2656/5000 (53%)
[epoch 10] loss: 0.9233968
Test set: Average loss: 1.2837, Accuracy: 2668/5000 (53%)
[epoch 11] loss: 0.8888963
Test set: Average loss: 1.2748, Accuracy: 2686/5000 (54%)
[epoch 12] loss: 0.8589603
Test set: Average loss: 1.2671, Accuracy: 2702/5000 (54%)
[epoch 13] loss: 0.8309444
Test set: Average loss: 1.2587, Accuracy: 2711/5000 (54%)
[epoch 14] loss: 0.8054197
Test set: Average loss: 1.2522, Accuracy: 2716/5000 (54%)
[epoch 15] loss: 0.7801440
Test set: Average loss: 1.2457, Accuracy: 2737/5000 (55%)
[epoch 16] loss: 0.7590863
Test set: Average loss: 1.2408, Accuracy: 2743/5000 (55%)
[epoch 17] loss: 0.7351832
Test set: Average loss: 1.2358, Accuracy: 2754/5000 (55%)
[epoch 18] loss: 0.7165646
Test set: Average loss: 1.2315, Accuracy: 2751/5000 (55%)
[epoch 19] loss: 0.6955111
Test set: Average loss: 1.2274, Accuracy: 2761/5000 (55%)
[epoch 20] loss: 0.6767881
Test set: Average loss: 1.2241, Accuracy: 2757/5000 (55%)
[epoch 21] loss: 0.6605681
Test set: Average loss: 1.2206, Accuracy: 2765/5000 (55%)
[epoch 22] loss: 0.6416737
Test set: Average loss: 1.2182, Accuracy: 2775/5000 (56%)
[epoch 23] loss: 0.6273796
Test set: Average loss: 1.2153, Accuracy: 2770/5000 (55%)
[epoch 24] loss: 0.6093591
Test set: Average loss: 1.2132, Accuracy: 2774/5000 (55%)
[epoch 25] loss: 0.5956812
Test set: Average loss: 1.2104, Accuracy: 2765/5000 (55%)
Validation:
Test set: Average loss: 1.2182, Accuracy: 2775/5000 (56%)
Test
Test set: Average loss: 1.2381, Accuracy: 2708/5000 (54%)
Test set: Average loss: 0.6305, Accuracy: 243/250 (97%)
500
## seed: 11
Validation accuracy before training:
Test set: Average loss: 1.7298, Accuracy: 587/5000 (12%)
[epoch 1] loss: 1.6272224
Test set: Average loss: 1.5270, Accuracy: 1343/5000 (27%)
[epoch 2] loss: 1.4097431
Test set: Average loss: 1.4175, Accuracy: 1819/5000 (36%)
[epoch 3] loss: 1.2750257
Test set: Average loss: 1.3536, Accuracy: 2140/5000 (43%)
[epoch 4] loss: 1.1829780
Test set: Average loss: 1.3148, Accuracy: 2338/5000 (47%)
[epoch 5] loss: 1.1169389
Test set: Average loss: 1.2856, Accuracy: 2479/5000 (50%)
[epoch 6] loss: 1.0592613
Test set: Average loss: 1.2618, Accuracy: 2594/5000 (52%)
[epoch 7] loss: 1.0119676
Test set: Average loss: 1.2451, Accuracy: 2609/5000 (52%)
[epoch 8] loss: 0.9640020
Test set: Average loss: 1.2289, Accuracy: 2682/5000 (54%)
[epoch 9] loss: 0.9236652
Test set: Average loss: 1.2168, Accuracy: 2702/5000 (54%)
[epoch 10] loss: 0.8866393
Test set: Average loss: 1.2064, Accuracy: 2745/5000 (55%)
[epoch 11] loss: 0.8539188
Test set: Average loss: 1.1970, Accuracy: 2761/5000 (55%)
[epoch 12] loss: 0.8261140
Test set: Average loss: 1.1878, Accuracy: 2783/5000 (56%)
[epoch 13] loss: 0.7925306
Test set: Average loss: 1.1823, Accuracy: 2788/5000 (56%)
[epoch 14] loss: 0.7682489
Test set: Average loss: 1.1765, Accuracy: 2799/5000 (56%)
[epoch 15] loss: 0.7416892
Test set: Average loss: 1.1704, Accuracy: 2815/5000 (56%)
[epoch 16] loss: 0.7169526
Test set: Average loss: 1.1664, Accuracy: 2817/5000 (56%)
[epoch 17] loss: 0.6953509
Test set: Average loss: 1.1610, Accuracy: 2818/5000 (56%)
[epoch 18] loss: 0.6731862
Test set: Average loss: 1.1582, Accuracy: 2810/5000 (56%)
[epoch 19] loss: 0.6496333
Test set: Average loss: 1.1558, Accuracy: 2824/5000 (56%)
[epoch 20] loss: 0.6353966
Test set: Average loss: 1.1500, Accuracy: 2836/5000 (57%)
[epoch 21] loss: 0.6153868
Test set: Average loss: 1.1492, Accuracy: 2820/5000 (56%)
[epoch 22] loss: 0.5956649
Test set: Average loss: 1.1456, Accuracy: 2828/5000 (57%)
[epoch 23] loss: 0.5761954
Test set: Average loss: 1.1447, Accuracy: 2829/5000 (57%)
[epoch 24] loss: 0.5585876
Test set: Average loss: 1.1393, Accuracy: 2843/5000 (57%)
[epoch 25] loss: 0.5401488
Test set: Average loss: 1.1392, Accuracy: 2839/5000 (57%)
Validation:
Test set: Average loss: 1.1393, Accuracy: 2843/5000 (57%)
Test
Test set: Average loss: 1.1446, Accuracy: 2803/5000 (56%)
Test set: Average loss: 0.5450, Accuracy: 487/500 (97%)
## seed: 12
Validation accuracy before training:
Test set: Average loss: 1.6247, Accuracy: 889/5000 (18%)
[epoch 1] loss: 1.5323802
Test set: Average loss: 1.4546, Accuracy: 2096/5000 (42%)
[epoch 2] loss: 1.3410075
Test set: Average loss: 1.3677, Accuracy: 2367/5000 (47%)
[epoch 3] loss: 1.2303779
Test set: Average loss: 1.3104, Accuracy: 2506/5000 (50%)
[epoch 4] loss: 1.1532683
Test set: Average loss: 1.2703, Accuracy: 2584/5000 (52%)
[epoch 5] loss: 1.0833819
Test set: Average loss: 1.2501, Accuracy: 2637/5000 (53%)
[epoch 6] loss: 1.0295231
Test set: Average loss: 1.2229, Accuracy: 2729/5000 (55%)
[epoch 7] loss: 0.9822741
Test set: Average loss: 1.2066, Accuracy: 2754/5000 (55%)
[epoch 8] loss: 0.9410465
Test set: Average loss: 1.1916, Accuracy: 2788/5000 (56%)
[epoch 9] loss: 0.9067274
Test set: Average loss: 1.1774, Accuracy: 2844/5000 (57%)
[epoch 10] loss: 0.8728129
Test set: Average loss: 1.1654, Accuracy: 2860/5000 (57%)
[epoch 11] loss: 0.8451099
Test set: Average loss: 1.1579, Accuracy: 2857/5000 (57%)
[epoch 12] loss: 0.8159943
Test set: Average loss: 1.1495, Accuracy: 2894/5000 (58%)
[epoch 13] loss: 0.7901850
Test set: Average loss: 1.1404, Accuracy: 2900/5000 (58%)
[epoch 14] loss: 0.7609161
Test set: Average loss: 1.1333, Accuracy: 2924/5000 (58%)
[epoch 15] loss: 0.7361396
Test set: Average loss: 1.1283, Accuracy: 2922/5000 (58%)
[epoch 16] loss: 0.7130908
Test set: Average loss: 1.1222, Accuracy: 2929/5000 (59%)
[epoch 17] loss: 0.6929589
Test set: Average loss: 1.1159, Accuracy: 2952/5000 (59%)
[epoch 18] loss: 0.6741565
Test set: Average loss: 1.1127, Accuracy: 2942/5000 (59%)
[epoch 19] loss: 0.6506878
Test set: Average loss: 1.1063, Accuracy: 2962/5000 (59%)
[epoch 20] loss: 0.6382987
Test set: Average loss: 1.1045, Accuracy: 2966/5000 (59%)
[epoch 21] loss: 0.6143276
Test set: Average loss: 1.0968, Accuracy: 2987/5000 (60%)
[epoch 22] loss: 0.5957020
Test set: Average loss: 1.0953, Accuracy: 2979/5000 (60%)
[epoch 23] loss: 0.5806325
Test set: Average loss: 1.0928, Accuracy: 2986/5000 (60%)
[epoch 24] loss: 0.5637734
Test set: Average loss: 1.0877, Accuracy: 3000/5000 (60%)
[epoch 25] loss: 0.5466046
Test set: Average loss: 1.0861, Accuracy: 2990/5000 (60%)
Validation:
Test set: Average loss: 1.0877, Accuracy: 3000/5000 (60%)
Test
Test set: Average loss: 1.1036, Accuracy: 2937/5000 (59%)
Test set: Average loss: 0.5501, Accuracy: 476/500 (95%)
## seed: 13
Validation accuracy before training:
Test set: Average loss: 1.5928, Accuracy: 1518/5000 (30%)
[epoch 1] loss: 1.4793693
Test set: Average loss: 1.4379, Accuracy: 1860/5000 (37%)
[epoch 2] loss: 1.2991638
Test set: Average loss: 1.3606, Accuracy: 2151/5000 (43%)
[epoch 3] loss: 1.1872119
Test set: Average loss: 1.3126, Accuracy: 2368/5000 (47%)
[epoch 4] loss: 1.1150743
Test set: Average loss: 1.2848, Accuracy: 2492/5000 (50%)
[epoch 5] loss: 1.0573478
Test set: Average loss: 1.2639, Accuracy: 2575/5000 (52%)
[epoch 6] loss: 1.0099273
Test set: Average loss: 1.2480, Accuracy: 2647/5000 (53%)
[epoch 7] loss: 0.9679494
Test set: Average loss: 1.2345, Accuracy: 2705/5000 (54%)
[epoch 8] loss: 0.9294645
Test set: Average loss: 1.2217, Accuracy: 2734/5000 (55%)
[epoch 9] loss: 0.8883399
Test set: Average loss: 1.2109, Accuracy: 2763/5000 (55%)
[epoch 10] loss: 0.8542148
Test set: Average loss: 1.2015, Accuracy: 2794/5000 (56%)
[epoch 11] loss: 0.8234453
Test set: Average loss: 1.1926, Accuracy: 2811/5000 (56%)
[epoch 12] loss: 0.7964623
Test set: Average loss: 1.1877, Accuracy: 2808/5000 (56%)
[epoch 13] loss: 0.7728695
Test set: Average loss: 1.1791, Accuracy: 2831/5000 (57%)
[epoch 14] loss: 0.7439157
Test set: Average loss: 1.1714, Accuracy: 2848/5000 (57%)
[epoch 15] loss: 0.7206491
Test set: Average loss: 1.1666, Accuracy: 2857/5000 (57%)
[epoch 16] loss: 0.6949401
Test set: Average loss: 1.1607, Accuracy: 2886/5000 (58%)
[epoch 17] loss: 0.6712463
Test set: Average loss: 1.1557, Accuracy: 2869/5000 (57%)
[epoch 18] loss: 0.6522623
Test set: Average loss: 1.1539, Accuracy: 2886/5000 (58%)
[epoch 19] loss: 0.6322500
Test set: Average loss: 1.1471, Accuracy: 2901/5000 (58%)
[epoch 20] loss: 0.6124063
Test set: Average loss: 1.1455, Accuracy: 2892/5000 (58%)
[epoch 21] loss: 0.5960295
Test set: Average loss: 1.1420, Accuracy: 2905/5000 (58%)
[epoch 22] loss: 0.5765929
Test set: Average loss: 1.1397, Accuracy: 2905/5000 (58%)
[epoch 23] loss: 0.5644304
Test set: Average loss: 1.1367, Accuracy: 2905/5000 (58%)
[epoch 24] loss: 0.5447783
Test set: Average loss: 1.1346, Accuracy: 2917/5000 (58%)
[epoch 25] loss: 0.5240393
Test set: Average loss: 1.1307, Accuracy: 2918/5000 (58%)
Validation:
Test set: Average loss: 1.1307, Accuracy: 2918/5000 (58%)
Test
Test set: Average loss: 1.1488, Accuracy: 2865/5000 (57%)
Test set: Average loss: 0.5129, Accuracy: 479/500 (96%)
750
## seed: 11
Validation accuracy before training:
Test set: Average loss: 1.7483, Accuracy: 862/5000 (17%)
[epoch 1] loss: 1.6342335
Test set: Average loss: 1.4990, Accuracy: 1678/5000 (34%)
[epoch 2] loss: 1.3845012
Test set: Average loss: 1.4031, Accuracy: 2156/5000 (43%)
[epoch 3] loss: 1.2574975
Test set: Average loss: 1.3477, Accuracy: 2308/5000 (46%)
[epoch 4] loss: 1.1693714
Test set: Average loss: 1.3091, Accuracy: 2512/5000 (50%)
[epoch 5] loss: 1.1022116
Test set: Average loss: 1.2874, Accuracy: 2557/5000 (51%)
[epoch 6] loss: 1.0480414
Test set: Average loss: 1.2645, Accuracy: 2641/5000 (53%)
[epoch 7] loss: 0.9925781
Test set: Average loss: 1.2487, Accuracy: 2686/5000 (54%)
[epoch 8] loss: 0.9541444
Test set: Average loss: 1.2331, Accuracy: 2719/5000 (54%)
[epoch 9] loss: 0.9182774
Test set: Average loss: 1.2263, Accuracy: 2723/5000 (54%)
[epoch 10] loss: 0.8802583
Test set: Average loss: 1.2102, Accuracy: 2759/5000 (55%)
[epoch 11] loss: 0.8481470
Test set: Average loss: 1.2113, Accuracy: 2727/5000 (55%)
[epoch 12] loss: 0.8181402
Test set: Average loss: 1.1963, Accuracy: 2785/5000 (56%)
[epoch 13] loss: 0.7807770
Test set: Average loss: 1.1911, Accuracy: 2792/5000 (56%)
[epoch 14] loss: 0.7615102
Test set: Average loss: 1.1832, Accuracy: 2813/5000 (56%)
[epoch 15] loss: 0.7292820
Test set: Average loss: 1.1765, Accuracy: 2829/5000 (57%)
[epoch 16] loss: 0.7053068
Test set: Average loss: 1.1686, Accuracy: 2858/5000 (57%)
[epoch 17] loss: 0.6819647
Test set: Average loss: 1.1670, Accuracy: 2849/5000 (57%)
[epoch 18] loss: 0.6589100
Test set: Average loss: 1.1631, Accuracy: 2851/5000 (57%)
[epoch 19] loss: 0.6349554
Test set: Average loss: 1.1622, Accuracy: 2848/5000 (57%)
[epoch 20] loss: 0.6069305
Test set: Average loss: 1.1540, Accuracy: 2868/5000 (57%)
[epoch 21] loss: 0.5889655
Test set: Average loss: 1.1491, Accuracy: 2890/5000 (58%)
[epoch 22] loss: 0.5702094
Test set: Average loss: 1.1463, Accuracy: 2871/5000 (57%)
[epoch 23] loss: 0.5512364
Test set: Average loss: 1.1441, Accuracy: 2879/5000 (58%)
[epoch 24] loss: 0.5281555
Test set: Average loss: 1.1427, Accuracy: 2890/5000 (58%)
[epoch 25] loss: 0.5110744
Test set: Average loss: 1.1391, Accuracy: 2896/5000 (58%)
Validation:
Test set: Average loss: 1.1391, Accuracy: 2896/5000 (58%)
Test
Test set: Average loss: 1.1476, Accuracy: 2867/5000 (57%)
Test set: Average loss: 0.4934, Accuracy: 721/750 (96%)
## seed: 12
Validation accuracy before training:
Test set: Average loss: 1.6704, Accuracy: 1113/5000 (22%)
[epoch 1] loss: 1.5789241
Test set: Average loss: 1.4859, Accuracy: 1766/5000 (35%)
[epoch 2] loss: 1.3888956
Test set: Average loss: 1.3946, Accuracy: 2149/5000 (43%)
[epoch 3] loss: 1.2766935
Test set: Average loss: 1.3349, Accuracy: 2399/5000 (48%)
[epoch 4] loss: 1.1942077
Test set: Average loss: 1.2925, Accuracy: 2524/5000 (50%)
[epoch 5] loss: 1.1266168
Test set: Average loss: 1.2644, Accuracy: 2612/5000 (52%)
[epoch 6] loss: 1.0729483
Test set: Average loss: 1.2439, Accuracy: 2702/5000 (54%)
[epoch 7] loss: 1.0326907
Test set: Average loss: 1.2259, Accuracy: 2760/5000 (55%)
[epoch 8] loss: 0.9842716
Test set: Average loss: 1.2108, Accuracy: 2810/5000 (56%)
[epoch 9] loss: 0.9451204
Test set: Average loss: 1.1978, Accuracy: 2856/5000 (57%)
[epoch 10] loss: 0.9109127
Test set: Average loss: 1.1866, Accuracy: 2894/5000 (58%)
[epoch 11] loss: 0.8748285
Test set: Average loss: 1.1751, Accuracy: 2907/5000 (58%)
[epoch 12] loss: 0.8458432
Test set: Average loss: 1.1673, Accuracy: 2952/5000 (59%)
[epoch 13] loss: 0.8142459
Test set: Average loss: 1.1566, Accuracy: 2953/5000 (59%)
[epoch 14] loss: 0.7824649
Test set: Average loss: 1.1504, Accuracy: 2978/5000 (60%)
[epoch 15] loss: 0.7549250
Test set: Average loss: 1.1407, Accuracy: 3001/5000 (60%)
[epoch 16] loss: 0.7325821
Test set: Average loss: 1.1368, Accuracy: 3001/5000 (60%)
[epoch 17] loss: 0.7042273
Test set: Average loss: 1.1277, Accuracy: 3001/5000 (60%)
[epoch 18] loss: 0.6793534
Test set: Average loss: 1.1231, Accuracy: 3026/5000 (61%)
[epoch 19] loss: 0.6658542
Test set: Average loss: 1.1201, Accuracy: 3007/5000 (60%)
[epoch 20] loss: 0.6343783
Test set: Average loss: 1.1126, Accuracy: 3028/5000 (61%)
[epoch 21] loss: 0.6106011
Test set: Average loss: 1.1085, Accuracy: 3044/5000 (61%)
[epoch 22] loss: 0.5917666
Test set: Average loss: 1.1028, Accuracy: 3043/5000 (61%)
[epoch 23] loss: 0.5696160
Test set: Average loss: 1.1000, Accuracy: 3072/5000 (61%)
[epoch 24] loss: 0.5539608
Test set: Average loss: 1.0950, Accuracy: 3054/5000 (61%)
[epoch 25] loss: 0.5351460
Test set: Average loss: 1.0912, Accuracy: 3074/5000 (61%)
Validation:
Test set: Average loss: 1.0912, Accuracy: 3074/5000 (61%)
Test
Test set: Average loss: 1.1029, Accuracy: 2984/5000 (60%)
Test set: Average loss: 0.5156, Accuracy: 722/750 (96%)
## seed: 13
Validation accuracy before training:
Test set: Average loss: 1.5484, Accuracy: 1213/5000 (24%)
[epoch 1] loss: 1.4034629
Test set: Average loss: 1.3387, Accuracy: 2338/5000 (47%)
[epoch 2] loss: 1.1977374
Test set: Average loss: 1.2655, Accuracy: 2576/5000 (52%)
[epoch 3] loss: 1.1064878
Test set: Average loss: 1.2245, Accuracy: 2715/5000 (54%)
[epoch 4] loss: 1.0361770
Test set: Average loss: 1.1988, Accuracy: 2816/5000 (56%)
[epoch 5] loss: 0.9764445
Test set: Average loss: 1.1777, Accuracy: 2879/5000 (58%)
[epoch 6] loss: 0.9249755
Test set: Average loss: 1.1605, Accuracy: 2944/5000 (59%)
[epoch 7] loss: 0.8889485
Test set: Average loss: 1.1495, Accuracy: 2960/5000 (59%)
[epoch 8] loss: 0.8472611
Test set: Average loss: 1.1374, Accuracy: 2991/5000 (60%)
[epoch 9] loss: 0.8082656
Test set: Average loss: 1.1293, Accuracy: 3000/5000 (60%)
[epoch 10] loss: 0.7797112
Test set: Average loss: 1.1208, Accuracy: 3018/5000 (60%)
[epoch 11] loss: 0.7447660
Test set: Average loss: 1.1111, Accuracy: 3044/5000 (61%)
[epoch 12] loss: 0.7129059
Test set: Average loss: 1.1031, Accuracy: 3069/5000 (61%)
[epoch 13] loss: 0.6886875
Test set: Average loss: 1.0975, Accuracy: 3043/5000 (61%)
[epoch 14] loss: 0.6599062
Test set: Average loss: 1.0936, Accuracy: 3060/5000 (61%)
[epoch 15] loss: 0.6354320
Test set: Average loss: 1.0895, Accuracy: 3066/5000 (61%)
[epoch 16] loss: 0.6061729
Test set: Average loss: 1.0818, Accuracy: 3072/5000 (61%)
[epoch 17] loss: 0.5867326
Test set: Average loss: 1.0817, Accuracy: 3053/5000 (61%)
[epoch 18] loss: 0.5632185
Test set: Average loss: 1.0738, Accuracy: 3059/5000 (61%)
[epoch 19] loss: 0.5412377
Test set: Average loss: 1.0709, Accuracy: 3058/5000 (61%)
[epoch 20] loss: 0.5251633
Test set: Average loss: 1.0680, Accuracy: 3061/5000 (61%)
[epoch 21] loss: 0.5036297
Test set: Average loss: 1.0672, Accuracy: 3053/5000 (61%)
[epoch 22] loss: 0.4852926
Test set: Average loss: 1.0606, Accuracy: 3068/5000 (61%)
[epoch 23] loss: 0.4630782
Test set: Average loss: 1.0624, Accuracy: 3054/5000 (61%)
[epoch 24] loss: 0.4472430
Test set: Average loss: 1.0573, Accuracy: 3063/5000 (61%)
[epoch 25] loss: 0.4295362
Test set: Average loss: 1.0577, Accuracy: 3053/5000 (61%)
Validation:
Test set: Average loss: 1.0818, Accuracy: 3072/5000 (61%)
Test
Test set: Average loss: 1.0988, Accuracy: 3027/5000 (61%)
Test set: Average loss: 0.5886, Accuracy: 700/750 (93%)
1000
## seed: 11
Validation accuracy before training:
Test set: Average loss: 1.7100, Accuracy: 716/5000 (14%)
[epoch 1] loss: 1.4931899
Test set: Average loss: 1.3810, Accuracy: 1903/5000 (38%)
[epoch 2] loss: 1.2330539
Test set: Average loss: 1.2783, Accuracy: 2376/5000 (48%)
[epoch 3] loss: 1.1306188
Test set: Average loss: 1.2241, Accuracy: 2630/5000 (53%)
[epoch 4] loss: 1.0510943
Test set: Average loss: 1.1874, Accuracy: 2764/5000 (55%)
[epoch 5] loss: 0.9867480
Test set: Average loss: 1.1597, Accuracy: 2840/5000 (57%)
[epoch 6] loss: 0.9323557
Test set: Average loss: 1.1402, Accuracy: 2903/5000 (58%)
[epoch 7] loss: 0.8786260
Test set: Average loss: 1.1246, Accuracy: 2934/5000 (59%)
[epoch 8] loss: 0.8383145
Test set: Average loss: 1.1112, Accuracy: 2967/5000 (59%)
[epoch 9] loss: 0.7987665
Test set: Average loss: 1.1020, Accuracy: 3001/5000 (60%)
[epoch 10] loss: 0.7679619
Test set: Average loss: 1.0964, Accuracy: 3003/5000 (60%)
[epoch 11] loss: 0.7352540
Test set: Average loss: 1.0867, Accuracy: 3016/5000 (60%)
[epoch 12] loss: 0.7121913
Test set: Average loss: 1.0785, Accuracy: 3025/5000 (60%)
[epoch 13] loss: 0.6790481
Test set: Average loss: 1.0716, Accuracy: 3040/5000 (61%)
[epoch 14] loss: 0.6460941
Test set: Average loss: 1.0671, Accuracy: 3051/5000 (61%)
[epoch 15] loss: 0.6171229
Test set: Average loss: 1.0657, Accuracy: 3055/5000 (61%)
[epoch 16] loss: 0.5913666
Test set: Average loss: 1.0599, Accuracy: 3058/5000 (61%)
[epoch 17] loss: 0.5717444
Test set: Average loss: 1.0538, Accuracy: 3073/5000 (61%)
[epoch 18] loss: 0.5459578
Test set: Average loss: 1.0506, Accuracy: 3060/5000 (61%)
[epoch 19] loss: 0.5279745
Test set: Average loss: 1.0516, Accuracy: 3050/5000 (61%)
[epoch 20] loss: 0.4996880
Test set: Average loss: 1.0456, Accuracy: 3069/5000 (61%)
[epoch 21] loss: 0.4793537
Test set: Average loss: 1.0436, Accuracy: 3041/5000 (61%)
[epoch 22] loss: 0.4662886
Test set: Average loss: 1.0408, Accuracy: 3063/5000 (61%)
[epoch 23] loss: 0.4394569
Test set: Average loss: 1.0467, Accuracy: 3048/5000 (61%)
[epoch 24] loss: 0.4216955
Test set: Average loss: 1.0417, Accuracy: 3058/5000 (61%)
[epoch 25] loss: 0.4017283
Test set: Average loss: 1.0411, Accuracy: 3061/5000 (61%)
Validation:
Test set: Average loss: 1.0538, Accuracy: 3073/5000 (61%)
Test
Test set: Average loss: 1.0620, Accuracy: 3012/5000 (60%)
Test set: Average loss: 0.5458, Accuracy: 921/1000 (92%)
## seed: 12
Validation accuracy before training:
Test set: Average loss: 1.6777, Accuracy: 993/5000 (20%)
[epoch 1] loss: 1.4757716
Test set: Average loss: 1.3728, Accuracy: 2315/5000 (46%)
[epoch 2] loss: 1.2487829
Test set: Average loss: 1.2718, Accuracy: 2618/5000 (52%)
[epoch 3] loss: 1.1358923
Test set: Average loss: 1.2238, Accuracy: 2761/5000 (55%)
[epoch 4] loss: 1.0620355
Test set: Average loss: 1.1890, Accuracy: 2894/5000 (58%)
[epoch 5] loss: 0.9933530
Test set: Average loss: 1.1666, Accuracy: 2918/5000 (58%)
[epoch 6] loss: 0.9482711
Test set: Average loss: 1.1449, Accuracy: 2980/5000 (60%)
[epoch 7] loss: 0.8965399
Test set: Average loss: 1.1311, Accuracy: 2997/5000 (60%)
[epoch 8] loss: 0.8570670
Test set: Average loss: 1.1178, Accuracy: 3035/5000 (61%)
[epoch 9] loss: 0.8195727
Test set: Average loss: 1.1045, Accuracy: 3060/5000 (61%)
[epoch 10] loss: 0.7805374
Test set: Average loss: 1.0972, Accuracy: 3080/5000 (62%)
[epoch 11] loss: 0.7461666
Test set: Average loss: 1.0856, Accuracy: 3095/5000 (62%)
[epoch 12] loss: 0.7216038
Test set: Average loss: 1.0781, Accuracy: 3114/5000 (62%)
[epoch 13] loss: 0.6870540
Test set: Average loss: 1.0731, Accuracy: 3104/5000 (62%)
[epoch 14] loss: 0.6534376
Test set: Average loss: 1.0678, Accuracy: 3105/5000 (62%)
[epoch 15] loss: 0.6252181
Test set: Average loss: 1.0575, Accuracy: 3147/5000 (63%)
[epoch 16] loss: 0.5963787
Test set: Average loss: 1.0537, Accuracy: 3136/5000 (63%)
[epoch 17] loss: 0.5799494
Test set: Average loss: 1.0492, Accuracy: 3122/5000 (62%)
[epoch 18] loss: 0.5537445
Test set: Average loss: 1.0448, Accuracy: 3136/5000 (63%)
[epoch 19] loss: 0.5307883
Test set: Average loss: 1.0435, Accuracy: 3123/5000 (62%)
[epoch 20] loss: 0.5004664
Test set: Average loss: 1.0362, Accuracy: 3146/5000 (63%)
[epoch 21] loss: 0.4799373
Test set: Average loss: 1.0306, Accuracy: 3159/5000 (63%)
[epoch 22] loss: 0.4596827
Test set: Average loss: 1.0260, Accuracy: 3180/5000 (64%)
[epoch 23] loss: 0.4380797
Test set: Average loss: 1.0235, Accuracy: 3174/5000 (63%)
[epoch 24] loss: 0.4233467
Test set: Average loss: 1.0223, Accuracy: 3158/5000 (63%)
[epoch 25] loss: 0.3990323
Test set: Average loss: 1.0192, Accuracy: 3176/5000 (64%)
Validation:
Test set: Average loss: 1.0260, Accuracy: 3180/5000 (64%)
Test
Test set: Average loss: 1.0434, Accuracy: 3094/5000 (62%)
Test set: Average loss: 0.4371, Accuracy: 974/1000 (97%)
## seed: 13
Validation accuracy before training:
Test set: Average loss: 1.5449, Accuracy: 1567/5000 (31%)
[epoch 1] loss: 1.4309818
Test set: Average loss: 1.3397, Accuracy: 2268/5000 (45%)
[epoch 2] loss: 1.2414837
Test set: Average loss: 1.2719, Accuracy: 2569/5000 (51%)
[epoch 3] loss: 1.1589139
Test set: Average loss: 1.2330, Accuracy: 2683/5000 (54%)
[epoch 4] loss: 1.0860255
Test set: Average loss: 1.2063, Accuracy: 2816/5000 (56%)
[epoch 5] loss: 1.0376625
Test set: Average loss: 1.1830, Accuracy: 2861/5000 (57%)
[epoch 6] loss: 0.9918068
Test set: Average loss: 1.1686, Accuracy: 2936/5000 (59%)
[epoch 7] loss: 0.9486815
Test set: Average loss: 1.1505, Accuracy: 2941/5000 (59%)
[epoch 8] loss: 0.9093857
Test set: Average loss: 1.1370, Accuracy: 2987/5000 (60%)
[epoch 9] loss: 0.8885435
Test set: Average loss: 1.1301, Accuracy: 2980/5000 (60%)
[epoch 10] loss: 0.8381026
Test set: Average loss: 1.1167, Accuracy: 3023/5000 (60%)
[epoch 11] loss: 0.8092708
Test set: Average loss: 1.1096, Accuracy: 3015/5000 (60%)
[epoch 12] loss: 0.7763208
Test set: Average loss: 1.0993, Accuracy: 3033/5000 (61%)
[epoch 13] loss: 0.7467391
Test set: Average loss: 1.0915, Accuracy: 3064/5000 (61%)
[epoch 14] loss: 0.7150911
Test set: Average loss: 1.0868, Accuracy: 3056/5000 (61%)
[epoch 15] loss: 0.6894610
Test set: Average loss: 1.0810, Accuracy: 3070/5000 (61%)
[epoch 16] loss: 0.6668116
Test set: Average loss: 1.0799, Accuracy: 3060/5000 (61%)
[epoch 17] loss: 0.6501610
Test set: Average loss: 1.0699, Accuracy: 3074/5000 (61%)
[epoch 18] loss: 0.6170401
Test set: Average loss: 1.0619, Accuracy: 3095/5000 (62%)
[epoch 19] loss: 0.5930423
Test set: Average loss: 1.0574, Accuracy: 3076/5000 (62%)
[epoch 20] loss: 0.5726984
Test set: Average loss: 1.0514, Accuracy: 3115/5000 (62%)
[epoch 21] loss: 0.5517389
Test set: Average loss: 1.0490, Accuracy: 3101/5000 (62%)
[epoch 22] loss: 0.5351597
Test set: Average loss: 1.0437, Accuracy: 3121/5000 (62%)
[epoch 23] loss: 0.5038965
Test set: Average loss: 1.0407, Accuracy: 3108/5000 (62%)
[epoch 24] loss: 0.4893948
Test set: Average loss: 1.0383, Accuracy: 3102/5000 (62%)
[epoch 25] loss: 0.4700521
Test set: Average loss: 1.0378, Accuracy: 3096/5000 (62%)
Validation:
Test set: Average loss: 1.0437, Accuracy: 3121/5000 (62%)
Test
Test set: Average loss: 1.0578, Accuracy: 3074/5000 (61%)
Test set: Average loss: 0.5105, Accuracy: 955/1000 (96%)
2500
## seed: 11
Validation accuracy before training:
Test set: Average loss: 1.9465, Accuracy: 264/5000 (5%)
[epoch 1] loss: 1.5378056
Test set: Average loss: 1.3304, Accuracy: 2281/5000 (46%)
[epoch 2] loss: 1.2383180
Test set: Average loss: 1.2167, Accuracy: 2622/5000 (52%)
[epoch 3] loss: 1.1063982
Test set: Average loss: 1.1687, Accuracy: 2763/5000 (55%)
[epoch 4] loss: 1.0360782
Test set: Average loss: 1.1363, Accuracy: 2826/5000 (57%)
[epoch 5] loss: 0.9761527
Test set: Average loss: 1.1114, Accuracy: 2911/5000 (58%)
[epoch 6] loss: 0.9262268
Test set: Average loss: 1.0921, Accuracy: 2972/5000 (59%)
[epoch 7] loss: 0.8724953
Test set: Average loss: 1.0759, Accuracy: 3028/5000 (61%)
[epoch 8] loss: 0.8278630
Test set: Average loss: 1.0602, Accuracy: 3070/5000 (61%)
[epoch 9] loss: 0.7861190
Test set: Average loss: 1.0525, Accuracy: 3072/5000 (61%)
[epoch 10] loss: 0.7439100
Test set: Average loss: 1.0415, Accuracy: 3107/5000 (62%)
[epoch 11] loss: 0.7053857
Test set: Average loss: 1.0313, Accuracy: 3115/5000 (62%)
[epoch 12] loss: 0.6720949
Test set: Average loss: 1.0211, Accuracy: 3108/5000 (62%)
[epoch 13] loss: 0.6342474
Test set: Average loss: 1.0151, Accuracy: 3145/5000 (63%)
[epoch 14] loss: 0.5966653
Test set: Average loss: 1.0135, Accuracy: 3136/5000 (63%)
[epoch 15] loss: 0.5669287
Test set: Average loss: 1.0063, Accuracy: 3151/5000 (63%)
[epoch 16] loss: 0.5388145
Test set: Average loss: 0.9968, Accuracy: 3170/5000 (63%)
[epoch 17] loss: 0.5110272
Test set: Average loss: 0.9947, Accuracy: 3163/5000 (63%)
[epoch 18] loss: 0.4709424
Test set: Average loss: 0.9883, Accuracy: 3194/5000 (64%)
[epoch 19] loss: 0.4431301
Test set: Average loss: 0.9891, Accuracy: 3156/5000 (63%)
[epoch 20] loss: 0.4152859
Test set: Average loss: 0.9933, Accuracy: 3155/5000 (63%)
[epoch 21] loss: 0.3879083
Test set: Average loss: 0.9845, Accuracy: 3172/5000 (63%)
[epoch 22] loss: 0.3600258
Test set: Average loss: 0.9932, Accuracy: 3136/5000 (63%)
[epoch 23] loss: 0.3373459
Test set: Average loss: 0.9947, Accuracy: 3134/5000 (63%)
[epoch 24] loss: 0.3137846
Test set: Average loss: 0.9848, Accuracy: 3168/5000 (63%)
[epoch 25] loss: 0.2923441
Test set: Average loss: 0.9863, Accuracy: 3179/5000 (64%)
Validation:
Test set: Average loss: 0.9883, Accuracy: 3194/5000 (64%)
Test
Test set: Average loss: 0.9993, Accuracy: 3129/5000 (63%)
Test set: Average loss: 0.4404, Accuracy: 2334/2500 (93%)
## seed: 12
Validation accuracy before training:
Test set: Average loss: 1.3516, Accuracy: 2178/5000 (44%)
[epoch 1] loss: 1.1348061
Test set: Average loss: 1.1297, Accuracy: 3078/5000 (62%)
[epoch 2] loss: 0.9845631
Test set: Average loss: 1.0757, Accuracy: 3196/5000 (64%)
[epoch 3] loss: 0.8974240
Test set: Average loss: 1.0423, Accuracy: 3225/5000 (64%)
[epoch 4] loss: 0.8374055
Test set: Average loss: 1.0154, Accuracy: 3257/5000 (65%)
[epoch 5] loss: 0.7819547
Test set: Average loss: 0.9999, Accuracy: 3278/5000 (66%)
[epoch 6] loss: 0.7347276
Test set: Average loss: 0.9866, Accuracy: 3291/5000 (66%)
[epoch 7] loss: 0.6950598
Test set: Average loss: 0.9730, Accuracy: 3315/5000 (66%)
[epoch 8] loss: 0.6474572
Test set: Average loss: 0.9624, Accuracy: 3311/5000 (66%)
[epoch 9] loss: 0.6079546
Test set: Average loss: 0.9554, Accuracy: 3317/5000 (66%)
[epoch 10] loss: 0.5677291
Test set: Average loss: 0.9440, Accuracy: 3309/5000 (66%)
[epoch 11] loss: 0.5292577
Test set: Average loss: 0.9402, Accuracy: 3320/5000 (66%)
[epoch 12] loss: 0.4983225
Test set: Average loss: 0.9320, Accuracy: 3352/5000 (67%)
[epoch 13] loss: 0.4652267
Test set: Average loss: 0.9305, Accuracy: 3312/5000 (66%)
[epoch 14] loss: 0.4340785
Test set: Average loss: 0.9243, Accuracy: 3332/5000 (67%)
[epoch 15] loss: 0.4110757
Test set: Average loss: 0.9220, Accuracy: 3336/5000 (67%)
[epoch 16] loss: 0.3765523
Test set: Average loss: 0.9160, Accuracy: 3330/5000 (67%)
[epoch 17] loss: 0.3472480
Test set: Average loss: 0.9091, Accuracy: 3354/5000 (67%)
[epoch 18] loss: 0.3244437
Test set: Average loss: 0.9119, Accuracy: 3346/5000 (67%)
[epoch 19] loss: 0.3016210
Test set: Average loss: 0.9068, Accuracy: 3347/5000 (67%)
[epoch 20] loss: 0.2788298
Test set: Average loss: 0.9127, Accuracy: 3330/5000 (67%)
[epoch 21] loss: 0.2582649
Test set: Average loss: 0.9081, Accuracy: 3333/5000 (67%)
[epoch 22] loss: 0.2388288
Test set: Average loss: 0.9078, Accuracy: 3338/5000 (67%)
[epoch 23] loss: 0.2237363
Test set: Average loss: 0.9107, Accuracy: 3320/5000 (66%)
[epoch 24] loss: 0.2057588
Test set: Average loss: 0.9113, Accuracy: 3297/5000 (66%)
[epoch 25] loss: 0.1892401
Test set: Average loss: 0.9096, Accuracy: 3315/5000 (66%)
Validation:
Test set: Average loss: 0.9091, Accuracy: 3354/5000 (67%)
Test
Test set: Average loss: 0.9293, Accuracy: 3260/5000 (65%)
Test set: Average loss: 0.3197, Accuracy: 2441/2500 (98%)
## seed: 13
Validation accuracy before training:
Test set: Average loss: 1.6528, Accuracy: 1189/5000 (24%)
[epoch 1] loss: 1.3076790
Test set: Average loss: 1.1964, Accuracy: 2906/5000 (58%)
[epoch 2] loss: 1.0782995
Test set: Average loss: 1.1312, Accuracy: 3048/5000 (61%)
[epoch 3] loss: 0.9830856
Test set: Average loss: 1.0943, Accuracy: 3134/5000 (63%)
[epoch 4] loss: 0.9196658
Test set: Average loss: 1.0723, Accuracy: 3138/5000 (63%)
[epoch 5] loss: 0.8605683
Test set: Average loss: 1.0485, Accuracy: 3178/5000 (64%)
[epoch 6] loss: 0.8129875
Test set: Average loss: 1.0362, Accuracy: 3207/5000 (64%)
[epoch 7] loss: 0.7662174
Test set: Average loss: 1.0239, Accuracy: 3213/5000 (64%)
[epoch 8] loss: 0.7241220
Test set: Average loss: 1.0148, Accuracy: 3225/5000 (64%)
[epoch 9] loss: 0.6881716
Test set: Average loss: 1.0106, Accuracy: 3203/5000 (64%)
[epoch 10] loss: 0.6450065
Test set: Average loss: 1.0002, Accuracy: 3221/5000 (64%)
[epoch 11] loss: 0.6120008
Test set: Average loss: 0.9925, Accuracy: 3226/5000 (65%)
[epoch 12] loss: 0.5847461
Test set: Average loss: 0.9858, Accuracy: 3243/5000 (65%)
[epoch 13] loss: 0.5438470
Test set: Average loss: 0.9876, Accuracy: 3216/5000 (64%)
[epoch 14] loss: 0.5158637
Test set: Average loss: 0.9733, Accuracy: 3260/5000 (65%)
[epoch 15] loss: 0.4849955
Test set: Average loss: 0.9729, Accuracy: 3247/5000 (65%)
[epoch 16] loss: 0.4517077
Test set: Average loss: 0.9720, Accuracy: 3237/5000 (65%)
[epoch 17] loss: 0.4214441
Test set: Average loss: 0.9704, Accuracy: 3236/5000 (65%)
[epoch 18] loss: 0.3918285
Test set: Average loss: 0.9663, Accuracy: 3247/5000 (65%)
[epoch 19] loss: 0.3643265
Test set: Average loss: 0.9648, Accuracy: 3254/5000 (65%)
[epoch 20] loss: 0.3391837
Test set: Average loss: 0.9699, Accuracy: 3217/5000 (64%)
[epoch 21] loss: 0.3169823
Test set: Average loss: 0.9644, Accuracy: 3242/5000 (65%)
[epoch 22] loss: 0.2959163
Test set: Average loss: 0.9602, Accuracy: 3241/5000 (65%)
[epoch 23] loss: 0.2736568
Test set: Average loss: 0.9614, Accuracy: 3228/5000 (65%)
[epoch 24] loss: 0.2552719
Test set: Average loss: 0.9631, Accuracy: 3242/5000 (65%)
[epoch 25] loss: 0.2354264
Test set: Average loss: 0.9631, Accuracy: 3230/5000 (65%)
Validation:
Test set: Average loss: 0.9733, Accuracy: 3260/5000 (65%)
Test
Test set: Average loss: 0.9999, Accuracy: 3166/5000 (63%)
Test set: Average loss: 0.4741, Accuracy: 2314/2500 (93%)
5000
## seed: 11
Validation accuracy before training:
Test set: Average loss: 1.7964, Accuracy: 436/5000 (9%)
[epoch 1] loss: 1.4021796
Test set: Average loss: 1.2572, Accuracy: 2712/5000 (54%)
[epoch 2] loss: 1.1789668
Test set: Average loss: 1.1728, Accuracy: 2956/5000 (59%)
[epoch 3] loss: 1.0815382
Test set: Average loss: 1.1197, Accuracy: 3065/5000 (61%)
[epoch 4] loss: 1.0070781
Test set: Average loss: 1.0790, Accuracy: 3116/5000 (62%)
[epoch 5] loss: 0.9416016
Test set: Average loss: 1.0486, Accuracy: 3173/5000 (63%)
[epoch 6] loss: 0.8825499
Test set: Average loss: 1.0222, Accuracy: 3182/5000 (64%)
[epoch 7] loss: 0.8291761
Test set: Average loss: 1.0044, Accuracy: 3238/5000 (65%)
[epoch 8] loss: 0.7766705
Test set: Average loss: 0.9833, Accuracy: 3239/5000 (65%)
[epoch 9] loss: 0.7272543
Test set: Average loss: 0.9779, Accuracy: 3236/5000 (65%)
[epoch 10] loss: 0.6822752
Test set: Average loss: 0.9552, Accuracy: 3257/5000 (65%)
[epoch 11] loss: 0.6367542
Test set: Average loss: 0.9466, Accuracy: 3280/5000 (66%)
[epoch 12] loss: 0.5949518
Test set: Average loss: 0.9396, Accuracy: 3269/5000 (65%)
[epoch 13] loss: 0.5544139
Test set: Average loss: 0.9320, Accuracy: 3265/5000 (65%)
[epoch 14] loss: 0.5109389
Test set: Average loss: 0.9256, Accuracy: 3287/5000 (66%)
[epoch 15] loss: 0.4707328
Test set: Average loss: 0.9254, Accuracy: 3306/5000 (66%)
[epoch 16] loss: 0.4332549
Test set: Average loss: 0.9151, Accuracy: 3287/5000 (66%)
[epoch 17] loss: 0.3977866
Test set: Average loss: 0.9224, Accuracy: 3271/5000 (65%)
[epoch 18] loss: 0.3654350
Test set: Average loss: 0.9112, Accuracy: 3301/5000 (66%)
[epoch 19] loss: 0.3347605
Test set: Average loss: 0.9144, Accuracy: 3296/5000 (66%)
[epoch 20] loss: 0.3068074
Test set: Average loss: 0.9208, Accuracy: 3285/5000 (66%)
[epoch 21] loss: 0.2732992
Test set: Average loss: 0.9159, Accuracy: 3303/5000 (66%)
[epoch 22] loss: 0.2482837
Test set: Average loss: 0.9153, Accuracy: 3294/5000 (66%)
[epoch 23] loss: 0.2220882
Test set: Average loss: 0.9258, Accuracy: 3289/5000 (66%)
[epoch 24] loss: 0.2007764
Test set: Average loss: 0.9234, Accuracy: 3305/5000 (66%)
[epoch 25] loss: 0.1799882
Test set: Average loss: 0.9225, Accuracy: 3298/5000 (66%)
Validation:
Test set: Average loss: 0.9254, Accuracy: 3306/5000 (66%)
Test
Test set: Average loss: 0.9246, Accuracy: 3318/5000 (66%)
Test set: Average loss: 0.4353, Accuracy: 4563/5000 (91%)
## seed: 12
Validation accuracy before training:
Test set: Average loss: 1.7783, Accuracy: 670/5000 (13%)
[epoch 1] loss: 1.3424702
Test set: Average loss: 1.1878, Accuracy: 2748/5000 (55%)
[epoch 2] loss: 1.0912323
Test set: Average loss: 1.1015, Accuracy: 3027/5000 (61%)
[epoch 3] loss: 0.9921038
Test set: Average loss: 1.0520, Accuracy: 3152/5000 (63%)
[epoch 4] loss: 0.9213223
Test set: Average loss: 1.0200, Accuracy: 3231/5000 (65%)
[epoch 5] loss: 0.8588387
Test set: Average loss: 0.9913, Accuracy: 3268/5000 (65%)
[epoch 6] loss: 0.8035641
Test set: Average loss: 0.9714, Accuracy: 3311/5000 (66%)
[epoch 7] loss: 0.7523198
Test set: Average loss: 0.9534, Accuracy: 3338/5000 (67%)
[epoch 8] loss: 0.7048580
Test set: Average loss: 0.9431, Accuracy: 3349/5000 (67%)
[epoch 9] loss: 0.6544483
Test set: Average loss: 0.9245, Accuracy: 3376/5000 (68%)
[epoch 10] loss: 0.6133572
Test set: Average loss: 0.9172, Accuracy: 3365/5000 (67%)
[epoch 11] loss: 0.5688528
Test set: Average loss: 0.9095, Accuracy: 3373/5000 (67%)
[epoch 12] loss: 0.5285335
Test set: Average loss: 0.9021, Accuracy: 3389/5000 (68%)
[epoch 13] loss: 0.4870902
Test set: Average loss: 0.8959, Accuracy: 3380/5000 (68%)
[epoch 14] loss: 0.4491471
Test set: Average loss: 0.8885, Accuracy: 3415/5000 (68%)
[epoch 15] loss: 0.4116210
Test set: Average loss: 0.8854, Accuracy: 3410/5000 (68%)
[epoch 16] loss: 0.3755589
Test set: Average loss: 0.8839, Accuracy: 3392/5000 (68%)
[epoch 17] loss: 0.3415012
Test set: Average loss: 0.8824, Accuracy: 3398/5000 (68%)
[epoch 18] loss: 0.3100466
Test set: Average loss: 0.8858, Accuracy: 3400/5000 (68%)
[epoch 19] loss: 0.2793203
Test set: Average loss: 0.8858, Accuracy: 3395/5000 (68%)
[epoch 20] loss: 0.2536612
Test set: Average loss: 0.8986, Accuracy: 3363/5000 (67%)
[epoch 21] loss: 0.2268418
Test set: Average loss: 0.8971, Accuracy: 3361/5000 (67%)
[epoch 22] loss: 0.2019986
Test set: Average loss: 0.9014, Accuracy: 3357/5000 (67%)
[epoch 23] loss: 0.1805505
Test set: Average loss: 0.9090, Accuracy: 3353/5000 (67%)
[epoch 24] loss: 0.1599687
Test set: Average loss: 0.9121, Accuracy: 3362/5000 (67%)
[epoch 25] loss: 0.1425485
Test set: Average loss: 0.9112, Accuracy: 3369/5000 (67%)
Validation:
Test set: Average loss: 0.8885, Accuracy: 3415/5000 (68%)
Test
Test set: Average loss: 0.9055, Accuracy: 3322/5000 (66%)
Test set: Average loss: 0.4038, Accuracy: 4716/5000 (94%)
## seed: 13
Validation accuracy before training:
Test set: Average loss: 1.4904, Accuracy: 1568/5000 (31%)
[epoch 1] loss: 1.1690543
Test set: Average loss: 1.1135, Accuracy: 3053/5000 (61%)
[epoch 2] loss: 0.9777987
Test set: Average loss: 1.0515, Accuracy: 3155/5000 (63%)
[epoch 3] loss: 0.8862807
Test set: Average loss: 1.0078, Accuracy: 3240/5000 (65%)
[epoch 4] loss: 0.8169699
Test set: Average loss: 0.9825, Accuracy: 3262/5000 (65%)
[epoch 5] loss: 0.7563437
Test set: Average loss: 0.9682, Accuracy: 3290/5000 (66%)
[epoch 6] loss: 0.6990737
Test set: Average loss: 0.9441, Accuracy: 3333/5000 (67%)
[epoch 7] loss: 0.6486737
Test set: Average loss: 0.9307, Accuracy: 3337/5000 (67%)
[epoch 8] loss: 0.5956704
Test set: Average loss: 0.9203, Accuracy: 3362/5000 (67%)
[epoch 9] loss: 0.5493094
Test set: Average loss: 0.9141, Accuracy: 3350/5000 (67%)
[epoch 10] loss: 0.5048531
Test set: Average loss: 0.9074, Accuracy: 3368/5000 (67%)
[epoch 11] loss: 0.4605500
Test set: Average loss: 0.8985, Accuracy: 3377/5000 (68%)
[epoch 12] loss: 0.4197646
Test set: Average loss: 0.8981, Accuracy: 3376/5000 (68%)
[epoch 13] loss: 0.3840910
Test set: Average loss: 0.8965, Accuracy: 3367/5000 (67%)
[epoch 14] loss: 0.3462468
Test set: Average loss: 0.8908, Accuracy: 3383/5000 (68%)
[epoch 15] loss: 0.3108429
Test set: Average loss: 0.8992, Accuracy: 3364/5000 (67%)
[epoch 16] loss: 0.2810336
Test set: Average loss: 0.8907, Accuracy: 3388/5000 (68%)
[epoch 17] loss: 0.2521662
Test set: Average loss: 0.9009, Accuracy: 3332/5000 (67%)
[epoch 18] loss: 0.2269478
Test set: Average loss: 0.8969, Accuracy: 3364/5000 (67%)
[epoch 19] loss: 0.2027516
Test set: Average loss: 0.8992, Accuracy: 3358/5000 (67%)
[epoch 20] loss: 0.1802245
Test set: Average loss: 0.9037, Accuracy: 3358/5000 (67%)
[epoch 21] loss: 0.1597293
Test set: Average loss: 0.9057, Accuracy: 3360/5000 (67%)
[epoch 22] loss: 0.1417080
Test set: Average loss: 0.9165, Accuracy: 3349/5000 (67%)
[epoch 23] loss: 0.1264890
Test set: Average loss: 0.9169, Accuracy: 3362/5000 (67%)
[epoch 24] loss: 0.1143792
Test set: Average loss: 0.9325, Accuracy: 3346/5000 (67%)
[epoch 25] loss: 0.1003128
Test set: Average loss: 0.9328, Accuracy: 3355/5000 (67%)
Validation:
Test set: Average loss: 0.8907, Accuracy: 3388/5000 (68%)
Test
Test set: Average loss: 0.9031, Accuracy: 3343/5000 (67%)
Test set: Average loss: 0.2472, Accuracy: 4882/5000 (98%)
10000
## seed: 11
Validation accuracy before training:
Test set: Average loss: 1.8061, Accuracy: 475/5000 (10%)
[epoch 1] loss: 1.2090506
Test set: Average loss: 1.0887, Accuracy: 3033/5000 (61%)
[epoch 2] loss: 0.9781076
Test set: Average loss: 1.0190, Accuracy: 3179/5000 (64%)
[epoch 3] loss: 0.8804054
Test set: Average loss: 0.9759, Accuracy: 3296/5000 (66%)
[epoch 4] loss: 0.8011403
Test set: Average loss: 0.9464, Accuracy: 3312/5000 (66%)
[epoch 5] loss: 0.7299272
Test set: Average loss: 0.9210, Accuracy: 3366/5000 (67%)
[epoch 6] loss: 0.6658027
Test set: Average loss: 0.9007, Accuracy: 3390/5000 (68%)
[epoch 7] loss: 0.6043441
Test set: Average loss: 0.8992, Accuracy: 3385/5000 (68%)
[epoch 8] loss: 0.5486023
Test set: Average loss: 0.8754, Accuracy: 3427/5000 (69%)
[epoch 9] loss: 0.4914252
Test set: Average loss: 0.8754, Accuracy: 3399/5000 (68%)
[epoch 10] loss: 0.4427247
Test set: Average loss: 0.8732, Accuracy: 3424/5000 (68%)
[epoch 11] loss: 0.3939462
Test set: Average loss: 0.8760, Accuracy: 3454/5000 (69%)
[epoch 12] loss: 0.3487725
Test set: Average loss: 0.8682, Accuracy: 3429/5000 (69%)
[epoch 13] loss: 0.3092727
Test set: Average loss: 0.8791, Accuracy: 3449/5000 (69%)
[epoch 14] loss: 0.2713154
Test set: Average loss: 0.8840, Accuracy: 3432/5000 (69%)
[epoch 15] loss: 0.2368170
Test set: Average loss: 0.8857, Accuracy: 3445/5000 (69%)
[epoch 16] loss: 0.2055188
Test set: Average loss: 0.8979, Accuracy: 3421/5000 (68%)
[epoch 17] loss: 0.1772692
Test set: Average loss: 0.9314, Accuracy: 3396/5000 (68%)
[epoch 18] loss: 0.1548725
Test set: Average loss: 0.9187, Accuracy: 3403/5000 (68%)
[epoch 19] loss: 0.1352441
Test set: Average loss: 0.9409, Accuracy: 3383/5000 (68%)
[epoch 20] loss: 0.1124970
Test set: Average loss: 0.9448, Accuracy: 3419/5000 (68%)
[epoch 21] loss: 0.0961823
Test set: Average loss: 0.9567, Accuracy: 3412/5000 (68%)
[epoch 22] loss: 0.0824521
Test set: Average loss: 0.9707, Accuracy: 3409/5000 (68%)
[epoch 23] loss: 0.0703475
Test set: Average loss: 0.9854, Accuracy: 3427/5000 (69%)
[epoch 24] loss: 0.0588110
Test set: Average loss: 0.9972, Accuracy: 3397/5000 (68%)
[epoch 25] loss: 0.0487424
Test set: Average loss: 1.0022, Accuracy: 3415/5000 (68%)
Validation:
Test set: Average loss: 0.8760, Accuracy: 3454/5000 (69%)
Test
Test set: Average loss: 0.8925, Accuracy: 3362/5000 (67%)
Test set: Average loss: 0.3471, Accuracy: 9374/10000 (94%)
## seed: 12
Validation accuracy before training:
Test set: Average loss: 1.7035, Accuracy: 952/5000 (19%)
[epoch 1] loss: 1.2427086
Test set: Average loss: 1.1104, Accuracy: 3001/5000 (60%)
[epoch 2] loss: 1.0173039
Test set: Average loss: 1.0311, Accuracy: 3187/5000 (64%)
[epoch 3] loss: 0.9133282
Test set: Average loss: 0.9788, Accuracy: 3280/5000 (66%)
[epoch 4] loss: 0.8328188
Test set: Average loss: 0.9415, Accuracy: 3330/5000 (67%)
[epoch 5] loss: 0.7623305
Test set: Average loss: 0.9169, Accuracy: 3374/5000 (67%)
[epoch 6] loss: 0.6974266
Test set: Average loss: 0.9000, Accuracy: 3366/5000 (67%)
[epoch 7] loss: 0.6368745
Test set: Average loss: 0.8814, Accuracy: 3400/5000 (68%)
[epoch 8] loss: 0.5779259
Test set: Average loss: 0.8687, Accuracy: 3427/5000 (69%)
[epoch 9] loss: 0.5235931
Test set: Average loss: 0.8611, Accuracy: 3403/5000 (68%)
[epoch 10] loss: 0.4705235
Test set: Average loss: 0.8574, Accuracy: 3410/5000 (68%)
[epoch 11] loss: 0.4227682
Test set: Average loss: 0.8509, Accuracy: 3413/5000 (68%)
[epoch 12] loss: 0.3790177
Test set: Average loss: 0.8507, Accuracy: 3434/5000 (69%)
[epoch 13] loss: 0.3335276
Test set: Average loss: 0.8534, Accuracy: 3451/5000 (69%)
[epoch 14] loss: 0.2956874
Test set: Average loss: 0.8575, Accuracy: 3425/5000 (68%)
[epoch 15] loss: 0.2576521
Test set: Average loss: 0.8662, Accuracy: 3447/5000 (69%)
[epoch 16] loss: 0.2234859
Test set: Average loss: 0.8800, Accuracy: 3393/5000 (68%)
[epoch 17] loss: 0.1940596
Test set: Average loss: 0.8754, Accuracy: 3427/5000 (69%)
[epoch 18] loss: 0.1692153
Test set: Average loss: 0.8935, Accuracy: 3387/5000 (68%)
[epoch 19] loss: 0.1431284
Test set: Average loss: 0.9157, Accuracy: 3365/5000 (67%)
[epoch 20] loss: 0.1217729
Test set: Average loss: 0.9273, Accuracy: 3364/5000 (67%)
[epoch 21] loss: 0.1034328
Test set: Average loss: 0.9292, Accuracy: 3386/5000 (68%)
[epoch 22] loss: 0.0869161
Test set: Average loss: 0.9564, Accuracy: 3367/5000 (67%)
[epoch 23] loss: 0.0720523
Test set: Average loss: 0.9496, Accuracy: 3400/5000 (68%)
[epoch 24] loss: 0.0601301
Test set: Average loss: 0.9771, Accuracy: 3379/5000 (68%)
[epoch 25] loss: 0.0510128
Test set: Average loss: 0.9936, Accuracy: 3394/5000 (68%)
Validation:
Test set: Average loss: 0.8534, Accuracy: 3451/5000 (69%)
Test
Test set: Average loss: 0.8743, Accuracy: 3399/5000 (68%)
Test set: Average loss: 0.2888, Accuracy: 9505/10000 (95%)
## seed: 13
Validation accuracy before training:
Test set: Average loss: 1.6979, Accuracy: 763/5000 (15%)
[epoch 1] loss: 1.1640289
Test set: Average loss: 1.0681, Accuracy: 3118/5000 (62%)
[epoch 2] loss: 0.9487069
Test set: Average loss: 0.9919, Accuracy: 3276/5000 (66%)
[epoch 3] loss: 0.8491400
Test set: Average loss: 0.9543, Accuracy: 3303/5000 (66%)
[epoch 4] loss: 0.7679170
Test set: Average loss: 0.9268, Accuracy: 3318/5000 (66%)
[epoch 5] loss: 0.6976833
Test set: Average loss: 0.9020, Accuracy: 3368/5000 (67%)
[epoch 6] loss: 0.6319561
Test set: Average loss: 0.8858, Accuracy: 3399/5000 (68%)
[epoch 7] loss: 0.5709121
Test set: Average loss: 0.8809, Accuracy: 3389/5000 (68%)
[epoch 8] loss: 0.5119755
Test set: Average loss: 0.8731, Accuracy: 3393/5000 (68%)
[epoch 9] loss: 0.4592665
Test set: Average loss: 0.8661, Accuracy: 3411/5000 (68%)
[epoch 10] loss: 0.4115161
Test set: Average loss: 0.8629, Accuracy: 3422/5000 (68%)
[epoch 11] loss: 0.3648493
Test set: Average loss: 0.8633, Accuracy: 3425/5000 (68%)
[epoch 12] loss: 0.3222606
Test set: Average loss: 0.8793, Accuracy: 3396/5000 (68%)
[epoch 13] loss: 0.2826238
Test set: Average loss: 0.8747, Accuracy: 3417/5000 (68%)
[epoch 14] loss: 0.2474000
Test set: Average loss: 0.8783, Accuracy: 3425/5000 (68%)
[epoch 15] loss: 0.2135230
Test set: Average loss: 0.8827, Accuracy: 3426/5000 (69%)
[epoch 16] loss: 0.1892958
Test set: Average loss: 0.9006, Accuracy: 3409/5000 (68%)
[epoch 17] loss: 0.1580665
Test set: Average loss: 0.9130, Accuracy: 3404/5000 (68%)
[epoch 18] loss: 0.1363803
Test set: Average loss: 0.9219, Accuracy: 3410/5000 (68%)
[epoch 19] loss: 0.1145662
Test set: Average loss: 0.9347, Accuracy: 3407/5000 (68%)
[epoch 20] loss: 0.1021176
Test set: Average loss: 0.9443, Accuracy: 3396/5000 (68%)
[epoch 21] loss: 0.0823829
Test set: Average loss: 0.9567, Accuracy: 3410/5000 (68%)
[epoch 22] loss: 0.0689700
Test set: Average loss: 0.9751, Accuracy: 3385/5000 (68%)
[epoch 23] loss: 0.0611108
Test set: Average loss: 1.0225, Accuracy: 3335/5000 (67%)
[epoch 24] loss: 0.0498953
Test set: Average loss: 0.9972, Accuracy: 3398/5000 (68%)
[epoch 25] loss: 0.0406106
Test set: Average loss: 1.0147, Accuracy: 3367/5000 (67%)
Validation:
Test set: Average loss: 0.8827, Accuracy: 3426/5000 (69%)
Test
Test set: Average loss: 0.9047, Accuracy: 3403/5000 (68%)
Test set: Average loss: 0.1830, Accuracy: 9771/10000 (98%)
15000
## seed: 11
Validation accuracy before training:
Test set: Average loss: 1.5963, Accuracy: 1138/5000 (23%)
[epoch 1] loss: 1.1294870
Test set: Average loss: 1.0543, Accuracy: 3184/5000 (64%)
[epoch 2] loss: 0.9103179
Test set: Average loss: 0.9670, Accuracy: 3345/5000 (67%)
[epoch 3] loss: 0.7926345
Test set: Average loss: 0.9145, Accuracy: 3389/5000 (68%)
[epoch 4] loss: 0.7010489
Test set: Average loss: 0.8848, Accuracy: 3411/5000 (68%)
[epoch 5] loss: 0.6235328
Test set: Average loss: 0.8610, Accuracy: 3454/5000 (69%)
[epoch 6] loss: 0.5544759
Test set: Average loss: 0.8560, Accuracy: 3445/5000 (69%)
[epoch 7] loss: 0.4918719
Test set: Average loss: 0.8546, Accuracy: 3446/5000 (69%)
[epoch 8] loss: 0.4370384
Test set: Average loss: 0.8461, Accuracy: 3464/5000 (69%)
[epoch 9] loss: 0.3835741
Test set: Average loss: 0.8570, Accuracy: 3444/5000 (69%)
[epoch 10] loss: 0.3350369
Test set: Average loss: 0.8586, Accuracy: 3457/5000 (69%)
[epoch 11] loss: 0.2916188
Test set: Average loss: 0.8688, Accuracy: 3477/5000 (70%)
[epoch 12] loss: 0.2509618
Test set: Average loss: 0.8857, Accuracy: 3424/5000 (68%)
[epoch 13] loss: 0.2170900
Test set: Average loss: 0.9005, Accuracy: 3424/5000 (68%)
[epoch 14] loss: 0.1859382
Test set: Average loss: 0.9122, Accuracy: 3416/5000 (68%)
[epoch 15] loss: 0.1575561
Test set: Average loss: 0.9242, Accuracy: 3442/5000 (69%)
[epoch 16] loss: 0.1318448
Test set: Average loss: 0.9445, Accuracy: 3434/5000 (69%)
[epoch 17] loss: 0.1104829
Test set: Average loss: 0.9594, Accuracy: 3433/5000 (69%)
[epoch 18] loss: 0.0934991
Test set: Average loss: 0.9912, Accuracy: 3399/5000 (68%)
[epoch 19] loss: 0.0785854
Test set: Average loss: 1.0200, Accuracy: 3374/5000 (67%)
[epoch 20] loss: 0.0668607
Test set: Average loss: 1.0318, Accuracy: 3416/5000 (68%)
[epoch 21] loss: 0.0553315
Test set: Average loss: 1.0506, Accuracy: 3380/5000 (68%)
[epoch 22] loss: 0.0421631
Test set: Average loss: 1.0669, Accuracy: 3422/5000 (68%)
[epoch 23] loss: 0.0457547
Epoch 22: reducing learning rate of group 0 to 5.0000e-06.
Test set: Average loss: 1.2105, Accuracy: 3291/5000 (66%)
[epoch 24] loss: 0.0331475
Test set: Average loss: 1.0804, Accuracy: 3451/5000 (69%)
[epoch 25] loss: 0.0252824
Test set: Average loss: 1.0808, Accuracy: 3447/5000 (69%)
Validation:
Test set: Average loss: 0.8688, Accuracy: 3477/5000 (70%)
Test
Test set: Average loss: 0.8880, Accuracy: 3437/5000 (69%)
Test set: Average loss: 0.2453, Accuracy: 14371/15000 (96%)
## seed: 12
Validation accuracy before training:
Test set: Average loss: 1.7251, Accuracy: 819/5000 (16%)
[epoch 1] loss: 1.1134317
Test set: Average loss: 1.0319, Accuracy: 3186/5000 (64%)
[epoch 2] loss: 0.9033108
Test set: Average loss: 0.9560, Accuracy: 3310/5000 (66%)
[epoch 3] loss: 0.7986426
Test set: Average loss: 0.9176, Accuracy: 3374/5000 (67%)
[epoch 4] loss: 0.7124518
Test set: Average loss: 0.8883, Accuracy: 3387/5000 (68%)
[epoch 5] loss: 0.6362829
Test set: Average loss: 0.8772, Accuracy: 3412/5000 (68%)
[epoch 6] loss: 0.5662739
Test set: Average loss: 0.8533, Accuracy: 3452/5000 (69%)
[epoch 7] loss: 0.5050374
Test set: Average loss: 0.8517, Accuracy: 3454/5000 (69%)
[epoch 8] loss: 0.4437562
Test set: Average loss: 0.8500, Accuracy: 3468/5000 (69%)
[epoch 9] loss: 0.3926086
Test set: Average loss: 0.8554, Accuracy: 3491/5000 (70%)
[epoch 10] loss: 0.3418727
Test set: Average loss: 0.8636, Accuracy: 3486/5000 (70%)
[epoch 11] loss: 0.2993540
Test set: Average loss: 0.8628, Accuracy: 3479/5000 (70%)
[epoch 12] loss: 0.2590581
Test set: Average loss: 0.9010, Accuracy: 3403/5000 (68%)
[epoch 13] loss: 0.2219965
Test set: Average loss: 0.8956, Accuracy: 3452/5000 (69%)
[epoch 14] loss: 0.1928803
Test set: Average loss: 0.9034, Accuracy: 3410/5000 (68%)
[epoch 15] loss: 0.1630110
Test set: Average loss: 0.9204, Accuracy: 3454/5000 (69%)
[epoch 16] loss: 0.1357443
Test set: Average loss: 0.9512, Accuracy: 3419/5000 (68%)
[epoch 17] loss: 0.1164056
Test set: Average loss: 0.9657, Accuracy: 3384/5000 (68%)
[epoch 18] loss: 0.0966425
Test set: Average loss: 0.9897, Accuracy: 3390/5000 (68%)
[epoch 19] loss: 0.0818730
Test set: Average loss: 1.0026, Accuracy: 3399/5000 (68%)
[epoch 20] loss: 0.0655061
Test set: Average loss: 1.0374, Accuracy: 3362/5000 (67%)
[epoch 21] loss: 0.0599322
Test set: Average loss: 1.0464, Accuracy: 3383/5000 (68%)
[epoch 22] loss: 0.0467920
Test set: Average loss: 1.0765, Accuracy: 3391/5000 (68%)
[epoch 23] loss: 0.0431055
Test set: Average loss: 1.0893, Accuracy: 3366/5000 (67%)
[epoch 24] loss: 0.0325237
Test set: Average loss: 1.1382, Accuracy: 3347/5000 (67%)
[epoch 25] loss: 0.0279987
Test set: Average loss: 1.1535, Accuracy: 3338/5000 (67%)
Validation:
Test set: Average loss: 0.8554, Accuracy: 3491/5000 (70%)
Test
Test set: Average loss: 0.8720, Accuracy: 3421/5000 (68%)
Test set: Average loss: 0.3366, Accuracy: 13870/15000 (92%)
## seed: 13
Validation accuracy before training:
Test set: Average loss: 1.5877, Accuracy: 916/5000 (18%)
[epoch 1] loss: 1.0839235
Test set: Average loss: 1.0122, Accuracy: 3222/5000 (64%)
[epoch 2] loss: 0.8755581
Test set: Average loss: 0.9421, Accuracy: 3347/5000 (67%)
[epoch 3] loss: 0.7707074
Test set: Average loss: 0.9050, Accuracy: 3391/5000 (68%)
[epoch 4] loss: 0.6860901
Test set: Average loss: 0.8647, Accuracy: 3455/5000 (69%)
[epoch 5] loss: 0.6108841
Test set: Average loss: 0.8531, Accuracy: 3455/5000 (69%)
[epoch 6] loss: 0.5455932
Test set: Average loss: 0.8416, Accuracy: 3474/5000 (69%)
[epoch 7] loss: 0.4840074
Test set: Average loss: 0.8472, Accuracy: 3499/5000 (70%)
[epoch 8] loss: 0.4286332
Test set: Average loss: 0.8351, Accuracy: 3481/5000 (70%)
[epoch 9] loss: 0.3783517
Test set: Average loss: 0.8396, Accuracy: 3469/5000 (69%)
[epoch 10] loss: 0.3291364
Test set: Average loss: 0.8531, Accuracy: 3454/5000 (69%)
[epoch 11] loss: 0.2850710
Test set: Average loss: 0.8601, Accuracy: 3488/5000 (70%)
[epoch 12] loss: 0.2458503
Test set: Average loss: 0.8661, Accuracy: 3468/5000 (69%)
[epoch 13] loss: 0.2095597
Test set: Average loss: 0.8746, Accuracy: 3455/5000 (69%)
[epoch 14] loss: 0.1794754
Test set: Average loss: 0.9022, Accuracy: 3455/5000 (69%)
[epoch 15] loss: 0.1512002
Test set: Average loss: 0.9118, Accuracy: 3427/5000 (69%)
[epoch 16] loss: 0.1257555
Test set: Average loss: 0.9322, Accuracy: 3421/5000 (68%)
[epoch 17] loss: 0.1069515
Test set: Average loss: 0.9444, Accuracy: 3419/5000 (68%)
[epoch 18] loss: 0.0860919
Test set: Average loss: 0.9606, Accuracy: 3453/5000 (69%)
[epoch 19] loss: 0.0695880
Test set: Average loss: 1.0000, Accuracy: 3440/5000 (69%)
[epoch 20] loss: 0.0610233
Test set: Average loss: 1.0104, Accuracy: 3437/5000 (69%)
[epoch 21] loss: 0.0471182
Test set: Average loss: 1.0445, Accuracy: 3393/5000 (68%)
[epoch 22] loss: 0.0386892
Test set: Average loss: 1.0770, Accuracy: 3407/5000 (68%)
[epoch 23] loss: 0.0317063
Test set: Average loss: 1.0758, Accuracy: 3438/5000 (69%)
[epoch 24] loss: 0.0309281
Test set: Average loss: 1.1574, Accuracy: 3362/5000 (67%)
[epoch 25] loss: 0.0351875
Epoch 24: reducing learning rate of group 0 to 5.0000e-06.
Test set: Average loss: 1.1397, Accuracy: 3392/5000 (68%)
Validation:
Test set: Average loss: 0.8472, Accuracy: 3499/5000 (70%)
Test
Test set: Average loss: 0.8528, Accuracy: 3427/5000 (69%)
Test set: Average loss: 0.4263, Accuracy: 13524/15000 (90%)
20000
## seed: 11
Validation accuracy before training:
Test set: Average loss: 1.5157, Accuracy: 1749/5000 (35%)
[epoch 1] loss: 1.0403072
Test set: Average loss: 0.9894, Accuracy: 3324/5000 (66%)
[epoch 2] loss: 0.8293470
Test set: Average loss: 0.9118, Accuracy: 3411/5000 (68%)
[epoch 3] loss: 0.7154520
Test set: Average loss: 0.8761, Accuracy: 3426/5000 (69%)
[epoch 4] loss: 0.6245977
Test set: Average loss: 0.8482, Accuracy: 3471/5000 (69%)
[epoch 5] loss: 0.5476166
Test set: Average loss: 0.8308, Accuracy: 3487/5000 (70%)
[epoch 6] loss: 0.4816451
Test set: Average loss: 0.8397, Accuracy: 3445/5000 (69%)
[epoch 7] loss: 0.4211125
Test set: Average loss: 0.8396, Accuracy: 3491/5000 (70%)
[epoch 8] loss: 0.3687681
Test set: Average loss: 0.8425, Accuracy: 3474/5000 (69%)
[epoch 9] loss: 0.3187098
Test set: Average loss: 0.8738, Accuracy: 3413/5000 (68%)
[epoch 10] loss: 0.2763144
Test set: Average loss: 0.8725, Accuracy: 3421/5000 (68%)
[epoch 11] loss: 0.2362288
Test set: Average loss: 0.9143, Accuracy: 3405/5000 (68%)
[epoch 12] loss: 0.2003836
Test set: Average loss: 0.9039, Accuracy: 3434/5000 (69%)
[epoch 13] loss: 0.1714914
Test set: Average loss: 0.9192, Accuracy: 3420/5000 (68%)
[epoch 14] loss: 0.1421040
Test set: Average loss: 0.9732, Accuracy: 3352/5000 (67%)
[epoch 15] loss: 0.1176357
Test set: Average loss: 0.9652, Accuracy: 3418/5000 (68%)
[epoch 16] loss: 0.1003895
Test set: Average loss: 0.9791, Accuracy: 3409/5000 (68%)
[epoch 17] loss: 0.0803284
Test set: Average loss: 1.0249, Accuracy: 3397/5000 (68%)
[epoch 18] loss: 0.0691024
Test set: Average loss: 1.0405, Accuracy: 3405/5000 (68%)
[epoch 19] loss: 0.0557879
Test set: Average loss: 1.0979, Accuracy: 3374/5000 (67%)
[epoch 20] loss: 0.0459366
Test set: Average loss: 1.1122, Accuracy: 3365/5000 (67%)
[epoch 21] loss: 0.0429277
Test set: Average loss: 1.1266, Accuracy: 3387/5000 (68%)
[epoch 22] loss: 0.0281839
Test set: Average loss: 1.1521, Accuracy: 3383/5000 (68%)
[epoch 23] loss: 0.0327776
Epoch 22: reducing learning rate of group 0 to 5.0000e-06.
Test set: Average loss: 1.3376, Accuracy: 3244/5000 (65%)
[epoch 24] loss: 0.0280178
Test set: Average loss: 1.1815, Accuracy: 3388/5000 (68%)
[epoch 25] loss: 0.0165913
Test set: Average loss: 1.1796, Accuracy: 3381/5000 (68%)
Validation:
Test set: Average loss: 0.8396, Accuracy: 3491/5000 (70%)
Test
Test set: Average loss: 0.8490, Accuracy: 3458/5000 (69%)
Test set: Average loss: 0.3680, Accuracy: 18268/20000 (91%)
## seed: 12
Validation accuracy before training:
Test set: Average loss: 1.7147, Accuracy: 614/5000 (12%)
[epoch 1] loss: 1.0853404
Test set: Average loss: 1.0098, Accuracy: 3207/5000 (64%)
[epoch 2] loss: 0.8733847
Test set: Average loss: 0.9295, Accuracy: 3350/5000 (67%)
[epoch 3] loss: 0.7601870
Test set: Average loss: 0.8822, Accuracy: 3443/5000 (69%)
[epoch 4] loss: 0.6725082
Test set: Average loss: 0.8610, Accuracy: 3433/5000 (69%)
[epoch 5] loss: 0.5964911
Test set: Average loss: 0.8357, Accuracy: 3492/5000 (70%)
[epoch 6] loss: 0.5255992
Test set: Average loss: 0.8346, Accuracy: 3494/5000 (70%)
[epoch 7] loss: 0.4638157
Test set: Average loss: 0.8314, Accuracy: 3493/5000 (70%)
[epoch 8] loss: 0.4086013
Test set: Average loss: 0.8321, Accuracy: 3520/5000 (70%)
[epoch 9] loss: 0.3558454
Test set: Average loss: 0.8616, Accuracy: 3452/5000 (69%)
[epoch 10] loss: 0.3090594
Test set: Average loss: 0.8563, Accuracy: 3468/5000 (69%)
[epoch 11] loss: 0.2670045
Test set: Average loss: 0.8939, Accuracy: 3452/5000 (69%)
[epoch 12] loss: 0.2319451
Test set: Average loss: 0.8932, Accuracy: 3451/5000 (69%)
[epoch 13] loss: 0.1934433
Test set: Average loss: 0.9116, Accuracy: 3452/5000 (69%)
[epoch 14] loss: 0.1659732
Test set: Average loss: 0.9154, Accuracy: 3466/5000 (69%)
[epoch 15] loss: 0.1400149
Test set: Average loss: 0.9426, Accuracy: 3453/5000 (69%)
[epoch 16] loss: 0.1175095
Test set: Average loss: 0.9943, Accuracy: 3388/5000 (68%)
[epoch 17] loss: 0.0959833
Test set: Average loss: 0.9852, Accuracy: 3409/5000 (68%)
[epoch 18] loss: 0.0813543
Test set: Average loss: 1.0201, Accuracy: 3426/5000 (69%)
[epoch 19] loss: 0.0626578
Test set: Average loss: 1.0493, Accuracy: 3393/5000 (68%)
[epoch 20] loss: 0.0583069
Test set: Average loss: 1.0905, Accuracy: 3434/5000 (69%)
[epoch 21] loss: 0.0501791
Test set: Average loss: 1.0954, Accuracy: 3399/5000 (68%)
[epoch 22] loss: 0.0425372
Test set: Average loss: 1.1376, Accuracy: 3396/5000 (68%)
[epoch 23] loss: 0.0308062
Test set: Average loss: 1.1382, Accuracy: 3422/5000 (68%)
[epoch 24] loss: 0.0296516
Test set: Average loss: 1.2248, Accuracy: 3333/5000 (67%)
[epoch 25] loss: 0.0240861
Test set: Average loss: 1.2195, Accuracy: 3374/5000 (67%)
Validation:
Test set: Average loss: 0.8321, Accuracy: 3520/5000 (70%)
Test
Test set: Average loss: 0.8505, Accuracy: 3449/5000 (69%)
Test set: Average loss: 0.3484, Accuracy: 18468/20000 (92%)
## seed: 13
Validation accuracy before training:
Test set: Average loss: 1.6267, Accuracy: 840/5000 (17%)
[epoch 1] loss: 1.0553739
Test set: Average loss: 0.9915, Accuracy: 3310/5000 (66%)
[epoch 2] loss: 0.8437867
Test set: Average loss: 0.9190, Accuracy: 3402/5000 (68%)
[epoch 3] loss: 0.7293021
Test set: Average loss: 0.8774, Accuracy: 3456/5000 (69%)
[epoch 4] loss: 0.6373893
Test set: Average loss: 0.8512, Accuracy: 3475/5000 (70%)
[epoch 5] loss: 0.5602923
Test set: Average loss: 0.8467, Accuracy: 3469/5000 (69%)
[epoch 6] loss: 0.4898171
Test set: Average loss: 0.8385, Accuracy: 3488/5000 (70%)
[epoch 7] loss: 0.4310083
Test set: Average loss: 0.8445, Accuracy: 3467/5000 (69%)
[epoch 8] loss: 0.3749048
Test set: Average loss: 0.8644, Accuracy: 3445/5000 (69%)
[epoch 9] loss: 0.3239868
Test set: Average loss: 0.8490, Accuracy: 3508/5000 (70%)
[epoch 10] loss: 0.2813687
Test set: Average loss: 0.8702, Accuracy: 3451/5000 (69%)
[epoch 11] loss: 0.2408574
Test set: Average loss: 0.8970, Accuracy: 3466/5000 (69%)
[epoch 12] loss: 0.2042341
Test set: Average loss: 0.9061, Accuracy: 3440/5000 (69%)
[epoch 13] loss: 0.1722292
Test set: Average loss: 0.9149, Accuracy: 3465/5000 (69%)
[epoch 14] loss: 0.1431512
Test set: Average loss: 0.9453, Accuracy: 3423/5000 (68%)
[epoch 15] loss: 0.1199982
Test set: Average loss: 0.9720, Accuracy: 3439/5000 (69%)
[epoch 16] loss: 0.0998119
Test set: Average loss: 0.9996, Accuracy: 3437/5000 (69%)
[epoch 17] loss: 0.0829068
Test set: Average loss: 1.0119, Accuracy: 3444/5000 (69%)
[epoch 18] loss: 0.0658229
Test set: Average loss: 1.0788, Accuracy: 3381/5000 (68%)
[epoch 19] loss: 0.0530777
Test set: Average loss: 1.1187, Accuracy: 3337/5000 (67%)
[epoch 20] loss: 0.0511031
Test set: Average loss: 1.0868, Accuracy: 3454/5000 (69%)
[epoch 21] loss: 0.0399920
Test set: Average loss: 1.1105, Accuracy: 3442/5000 (69%)
[epoch 22] loss: 0.0265295
Test set: Average loss: 1.1526, Accuracy: 3422/5000 (68%)
[epoch 23] loss: 0.0545050
Epoch 22: reducing learning rate of group 0 to 5.0000e-06.
Test set: Average loss: 1.1773, Accuracy: 3409/5000 (68%)
[epoch 24] loss: 0.0203267
Test set: Average loss: 1.1595, Accuracy: 3433/5000 (69%)
[epoch 25] loss: 0.0159755
Test set: Average loss: 1.1604, Accuracy: 3431/5000 (69%)
Validation:
Test set: Average loss: 0.8490, Accuracy: 3508/5000 (70%)
Test
Test set: Average loss: 0.8715, Accuracy: 3452/5000 (69%)
Test set: Average loss: 0.2717, Accuracy: 18901/20000 (95%)
## Pre-Training AnB
Validation accuracy before training:
Test set: Average loss: 1.6157, Accuracy: 1028/5000 (21%)
[epoch 1] loss: 1.2600612
Test set: Average loss: 1.2195, Accuracy: 2624/5000 (52%)
[epoch 2] loss: 1.1608159
Test set: Average loss: 1.1820, Accuracy: 2716/5000 (54%)
[epoch 3] loss: 1.1047852
Test set: Average loss: 1.1525, Accuracy: 2831/5000 (57%)
[epoch 4] loss: 1.0549919
Test set: Average loss: 1.1244, Accuracy: 2896/5000 (58%)
[epoch 5] loss: 1.0099391
Test set: Average loss: 1.1178, Accuracy: 2895/5000 (58%)
[epoch 6] loss: 0.9659928
Test set: Average loss: 1.1104, Accuracy: 2917/5000 (58%)
[epoch 7] loss: 0.9213880
Test set: Average loss: 1.0738, Accuracy: 2976/5000 (60%)
[epoch 8] loss: 0.8761172
Test set: Average loss: 1.0594, Accuracy: 3020/5000 (60%)
[epoch 9] loss: 0.8331243
Test set: Average loss: 1.0731, Accuracy: 2963/5000 (59%)
[epoch 10] loss: 0.7881744
Test set: Average loss: 1.0871, Accuracy: 2984/5000 (60%)
[epoch 11] loss: 0.7426082
Test set: Average loss: 1.0625, Accuracy: 3013/5000 (60%)
[epoch 12] loss: 0.6977449
Test set: Average loss: 1.0719, Accuracy: 3018/5000 (60%)
[epoch 13] loss: 0.6496517
Test set: Average loss: 1.0581, Accuracy: 3023/5000 (60%)
[epoch 14] loss: 0.6024628
Test set: Average loss: 1.0722, Accuracy: 3003/5000 (60%)
[epoch 15] loss: 0.5577560
Test set: Average loss: 1.0952, Accuracy: 3004/5000 (60%)
[epoch 16] loss: 0.5147473
Test set: Average loss: 1.0808, Accuracy: 2991/5000 (60%)
[epoch 17] loss: 0.4703794
Test set: Average loss: 1.1091, Accuracy: 2982/5000 (60%)
[epoch 18] loss: 0.4296414
Test set: Average loss: 1.1401, Accuracy: 2979/5000 (60%)
[epoch 19] loss: 0.3859318
Test set: Average loss: 1.1549, Accuracy: 2963/5000 (59%)
[epoch 20] loss: 0.3495931
Test set: Average loss: 1.2015, Accuracy: 2938/5000 (59%)
[epoch 21] loss: 0.3091693
Test set: Average loss: 1.2109, Accuracy: 2920/5000 (58%)
[epoch 22] loss: 0.2767561
Test set: Average loss: 1.2292, Accuracy: 2922/5000 (58%)
[epoch 23] loss: 0.2439069
Test set: Average loss: 1.2607, Accuracy: 2924/5000 (58%)
[epoch 24] loss: 0.2130484
Test set: Average loss: 1.2931, Accuracy: 2895/5000 (58%)
[epoch 25] loss: 0.1913149
Test set: Average loss: 1.3356, Accuracy: 2832/5000 (57%)
Validation:
Test set: Average loss: 1.0581, Accuracy: 3023/5000 (60%)
Test set: Average loss: 1.0277, Accuracy: 3047/5000 (61%)
25
## seed: 11
Validation accuracy before training:
Test set: Average loss: 1.7348, Accuracy: 463/5000 (9%)
[epoch 1] loss: 1.7217755
Test set: Average loss: 1.7238, Accuracy: 482/5000 (10%)
[epoch 2] loss: 1.6331077
Test set: Average loss: 1.7133, Accuracy: 501/5000 (10%)
[epoch 3] loss: 1.5496206
Test set: Average loss: 1.7034, Accuracy: 528/5000 (11%)
[epoch 4] loss: 1.4726818
Test set: Average loss: 1.6940, Accuracy: 569/5000 (11%)
[epoch 5] loss: 1.4027437
Test set: Average loss: 1.6852, Accuracy: 612/5000 (12%)
[epoch 6] loss: 1.3395344
Test set: Average loss: 1.6770, Accuracy: 668/5000 (13%)
[epoch 7] loss: 1.2823485
Test set: Average loss: 1.6694, Accuracy: 710/5000 (14%)
[epoch 8] loss: 1.2303166
Test set: Average loss: 1.6622, Accuracy: 748/5000 (15%)
[epoch 9] loss: 1.1826255
Test set: Average loss: 1.6554, Accuracy: 801/5000 (16%)
[epoch 10] loss: 1.1386393
Test set: Average loss: 1.6490, Accuracy: 838/5000 (17%)
[epoch 11] loss: 1.0979121
Test set: Average loss: 1.6430, Accuracy: 885/5000 (18%)
[epoch 12] loss: 1.0601280
Test set: Average loss: 1.6373, Accuracy: 913/5000 (18%)
[epoch 13] loss: 1.0250293
Test set: Average loss: 1.6319, Accuracy: 945/5000 (19%)
[epoch 14] loss: 0.9923652
Test set: Average loss: 1.6266, Accuracy: 973/5000 (19%)
[epoch 15] loss: 0.9618739
Test set: Average loss: 1.6216, Accuracy: 1002/5000 (20%)
[epoch 16] loss: 0.9332914
Test set: Average loss: 1.6168, Accuracy: 1037/5000 (21%)
[epoch 17] loss: 0.9063691
Test set: Average loss: 1.6121, Accuracy: 1064/5000 (21%)
[epoch 18] loss: 0.8808869
Test set: Average loss: 1.6076, Accuracy: 1093/5000 (22%)
[epoch 19] loss: 0.8566622
Test set: Average loss: 1.6032, Accuracy: 1115/5000 (22%)
[epoch 20] loss: 0.8335515
Test set: Average loss: 1.5988, Accuracy: 1131/5000 (23%)
[epoch 21] loss: 0.8114519
Test set: Average loss: 1.5946, Accuracy: 1163/5000 (23%)
[epoch 22] loss: 0.7902948
Test set: Average loss: 1.5904, Accuracy: 1183/5000 (24%)
[epoch 23] loss: 0.7700351
Test set: Average loss: 1.5864, Accuracy: 1205/5000 (24%)
[epoch 24] loss: 0.7506372
Test set: Average loss: 1.5824, Accuracy: 1226/5000 (25%)
[epoch 25] loss: 0.7320656
Test set: Average loss: 1.5785, Accuracy: 1241/5000 (25%)
Validation:
Test set: Average loss: 1.5785, Accuracy: 1241/5000 (25%)
Test
Test set: Average loss: 1.5843, Accuracy: 1230/5000 (25%)
Test set: Average loss: 0.7143, Accuracy: 25/25 (100%)
## seed: 12
Validation accuracy before training:
Test set: Average loss: 1.6817, Accuracy: 871/5000 (17%)
[epoch 1] loss: 1.6641133
Test set: Average loss: 1.6620, Accuracy: 935/5000 (19%)
[epoch 2] loss: 1.5658329
Test set: Average loss: 1.6447, Accuracy: 1006/5000 (20%)
[epoch 3] loss: 1.4773511
Test set: Average loss: 1.6297, Accuracy: 1099/5000 (22%)
[epoch 4] loss: 1.3993548
Test set: Average loss: 1.6166, Accuracy: 1180/5000 (24%)
[epoch 5] loss: 1.3303677
Test set: Average loss: 1.6050, Accuracy: 1243/5000 (25%)
[epoch 6] loss: 1.2686620
Test set: Average loss: 1.5947, Accuracy: 1295/5000 (26%)
[epoch 7] loss: 1.2129883
Test set: Average loss: 1.5854, Accuracy: 1355/5000 (27%)
[epoch 8] loss: 1.1625450
Test set: Average loss: 1.5770, Accuracy: 1409/5000 (28%)
[epoch 9] loss: 1.1167595
Test set: Average loss: 1.5693, Accuracy: 1457/5000 (29%)
[epoch 10] loss: 1.0751522
Test set: Average loss: 1.5623, Accuracy: 1493/5000 (30%)
[epoch 11] loss: 1.0372962
Test set: Average loss: 1.5558, Accuracy: 1518/5000 (30%)
[epoch 12] loss: 1.0028058
Test set: Average loss: 1.5499, Accuracy: 1552/5000 (31%)
[epoch 13] loss: 0.9713284
Test set: Average loss: 1.5445, Accuracy: 1570/5000 (31%)
[epoch 14] loss: 0.9425365
Test set: Average loss: 1.5396, Accuracy: 1601/5000 (32%)
[epoch 15] loss: 0.9161220
Test set: Average loss: 1.5351, Accuracy: 1633/5000 (33%)
[epoch 16] loss: 0.8917971
Test set: Average loss: 1.5309, Accuracy: 1645/5000 (33%)
[epoch 17] loss: 0.8692968
Test set: Average loss: 1.5271, Accuracy: 1651/5000 (33%)
[epoch 18] loss: 0.8483834
Test set: Average loss: 1.5235, Accuracy: 1666/5000 (33%)
[epoch 19] loss: 0.8288475
Test set: Average loss: 1.5203, Accuracy: 1676/5000 (34%)
[epoch 20] loss: 0.8105078
Test set: Average loss: 1.5172, Accuracy: 1706/5000 (34%)
[epoch 21] loss: 0.7932091
Test set: Average loss: 1.5144, Accuracy: 1733/5000 (35%)
[epoch 22] loss: 0.7768182
Test set: Average loss: 1.5118, Accuracy: 1745/5000 (35%)
[epoch 23] loss: 0.7612236
Test set: Average loss: 1.5093, Accuracy: 1761/5000 (35%)
[epoch 24] loss: 0.7463349
Test set: Average loss: 1.5070, Accuracy: 1775/5000 (36%)
[epoch 25] loss: 0.7320817
Test set: Average loss: 1.5049, Accuracy: 1782/5000 (36%)
Validation:
Test set: Average loss: 1.5049, Accuracy: 1782/5000 (36%)
Test
Test set: Average loss: 1.5053, Accuracy: 1794/5000 (36%)
Test set: Average loss: 0.7184, Accuracy: 25/25 (100%)
## seed: 13
Validation accuracy before training:
Test set: Average loss: 1.5480, Accuracy: 1489/5000 (30%)
[epoch 1] loss: 1.5620531
Test set: Average loss: 1.5286, Accuracy: 1562/5000 (31%)
[epoch 2] loss: 1.4776583
Test set: Average loss: 1.5115, Accuracy: 1660/5000 (33%)
[epoch 3] loss: 1.3971916
Test set: Average loss: 1.4965, Accuracy: 1738/5000 (35%)
[epoch 4] loss: 1.3211093
Test set: Average loss: 1.4834, Accuracy: 1786/5000 (36%)
[epoch 5] loss: 1.2501210
Test set: Average loss: 1.4720, Accuracy: 1812/5000 (36%)
[epoch 6] loss: 1.1849761
Test set: Average loss: 1.4621, Accuracy: 1843/5000 (37%)
[epoch 7] loss: 1.1260453
Test set: Average loss: 1.4534, Accuracy: 1855/5000 (37%)
[epoch 8] loss: 1.0731630
Test set: Average loss: 1.4458, Accuracy: 1888/5000 (38%)
[epoch 9] loss: 1.0258085
Test set: Average loss: 1.4389, Accuracy: 1913/5000 (38%)
[epoch 10] loss: 0.9833610
Test set: Average loss: 1.4327, Accuracy: 1931/5000 (39%)
[epoch 11] loss: 0.9452139
Test set: Average loss: 1.4271, Accuracy: 1935/5000 (39%)
[epoch 12] loss: 0.9107887
Test set: Average loss: 1.4220, Accuracy: 1953/5000 (39%)
[epoch 13] loss: 0.8795389
Test set: Average loss: 1.4173, Accuracy: 1963/5000 (39%)
[epoch 14] loss: 0.8509680
Test set: Average loss: 1.4130, Accuracy: 1974/5000 (39%)
[epoch 15] loss: 0.8246514
Test set: Average loss: 1.4090, Accuracy: 1991/5000 (40%)
[epoch 16] loss: 0.8002396
Test set: Average loss: 1.4053, Accuracy: 1995/5000 (40%)
[epoch 17] loss: 0.7774541
Test set: Average loss: 1.4020, Accuracy: 2002/5000 (40%)
[epoch 18] loss: 0.7560747
Test set: Average loss: 1.3989, Accuracy: 2009/5000 (40%)
[epoch 19] loss: 0.7359287
Test set: Average loss: 1.3961, Accuracy: 2009/5000 (40%)
[epoch 20] loss: 0.7168797
Test set: Average loss: 1.3935, Accuracy: 2015/5000 (40%)
[epoch 21] loss: 0.6988209
Test set: Average loss: 1.3912, Accuracy: 2020/5000 (40%)
[epoch 22] loss: 0.6816696
Test set: Average loss: 1.3890, Accuracy: 2027/5000 (41%)
[epoch 23] loss: 0.6653690
Test set: Average loss: 1.3870, Accuracy: 2039/5000 (41%)
[epoch 24] loss: 0.6498863
Test set: Average loss: 1.3852, Accuracy: 2050/5000 (41%)
[epoch 25] loss: 0.6352083
Test set: Average loss: 1.3835, Accuracy: 2058/5000 (41%)
Validation:
Test set: Average loss: 1.3835, Accuracy: 2058/5000 (41%)
Test
Test set: Average loss: 1.3865, Accuracy: 1942/5000 (39%)
Test set: Average loss: 0.6213, Accuracy: 25/25 (100%)
50
## seed: 11
Validation accuracy before training:
Test set: Average loss: 1.6931, Accuracy: 828/5000 (17%)
[epoch 1] loss: 1.7549706
Test set: Average loss: 1.6565, Accuracy: 971/5000 (19%)
[epoch 2] loss: 1.6038721
Test set: Average loss: 1.6203, Accuracy: 1168/5000 (23%)
[epoch 3] loss: 1.5081283
Test set: Average loss: 1.5883, Accuracy: 1376/5000 (28%)
[epoch 4] loss: 1.4017029
Test set: Average loss: 1.5608, Accuracy: 1532/5000 (31%)
[epoch 5] loss: 1.3515761
Test set: Average loss: 1.5378, Accuracy: 1667/5000 (33%)
[epoch 6] loss: 1.2627758
Test set: Average loss: 1.5191, Accuracy: 1762/5000 (35%)
[epoch 7] loss: 1.1907139
Test set: Average loss: 1.5038, Accuracy: 1814/5000 (36%)
[epoch 8] loss: 1.1424918
Test set: Average loss: 1.4908, Accuracy: 1855/5000 (37%)
[epoch 9] loss: 1.0785015
Test set: Average loss: 1.4804, Accuracy: 1893/5000 (38%)
[epoch 10] loss: 1.0371751
Test set: Average loss: 1.4715, Accuracy: 1911/5000 (38%)
[epoch 11] loss: 1.0044116
Test set: Average loss: 1.4641, Accuracy: 1946/5000 (39%)
[epoch 12] loss: 0.9426819
Test set: Average loss: 1.4574, Accuracy: 1976/5000 (40%)
[epoch 13] loss: 0.9315952
Test set: Average loss: 1.4506, Accuracy: 1987/5000 (40%)
[epoch 14] loss: 0.8908248
Test set: Average loss: 1.4449, Accuracy: 2012/5000 (40%)
[epoch 15] loss: 0.8573146
Test set: Average loss: 1.4399, Accuracy: 2016/5000 (40%)
[epoch 16] loss: 0.8376027
Test set: Average loss: 1.4353, Accuracy: 2039/5000 (41%)
[epoch 17] loss: 0.8115632
Test set: Average loss: 1.4313, Accuracy: 2054/5000 (41%)
[epoch 18] loss: 0.8078417
Test set: Average loss: 1.4273, Accuracy: 2080/5000 (42%)
[epoch 19] loss: 0.7622720
Test set: Average loss: 1.4236, Accuracy: 2088/5000 (42%)
[epoch 20] loss: 0.7524206
Test set: Average loss: 1.4198, Accuracy: 2099/5000 (42%)
[epoch 21] loss: 0.7370719
Test set: Average loss: 1.4161, Accuracy: 2105/5000 (42%)
[epoch 22] loss: 0.7034137
Test set: Average loss: 1.4126, Accuracy: 2119/5000 (42%)
[epoch 23] loss: 0.7029648
Test set: Average loss: 1.4092, Accuracy: 2118/5000 (42%)
[epoch 24] loss: 0.6934181
Test set: Average loss: 1.4068, Accuracy: 2121/5000 (42%)
[epoch 25] loss: 0.6821003
Test set: Average loss: 1.4048, Accuracy: 2125/5000 (42%)
Validation:
Test set: Average loss: 1.4048, Accuracy: 2125/5000 (42%)
Test
Test set: Average loss: 1.4130, Accuracy: 2113/5000 (42%)
Test set: Average loss: 0.6569, Accuracy: 49/50 (98%)
## seed: 12
Validation accuracy before training:
Test set: Average loss: 1.6432, Accuracy: 1185/5000 (24%)
[epoch 1] loss: 1.6174116
Test set: Average loss: 1.6083, Accuracy: 1334/5000 (27%)
[epoch 2] loss: 1.4766468
Test set: Average loss: 1.5815, Accuracy: 1464/5000 (29%)
[epoch 3] loss: 1.3651840
Test set: Average loss: 1.5609, Accuracy: 1554/5000 (31%)
[epoch 4] loss: 1.2888112
Test set: Average loss: 1.5442, Accuracy: 1634/5000 (33%)
[epoch 5] loss: 1.2240469
Test set: Average loss: 1.5303, Accuracy: 1720/5000 (34%)
[epoch 6] loss: 1.1486734
Test set: Average loss: 1.5196, Accuracy: 1780/5000 (36%)
[epoch 7] loss: 1.0723870
Test set: Average loss: 1.5111, Accuracy: 1819/5000 (36%)
[epoch 8] loss: 1.0216447
Test set: Average loss: 1.5036, Accuracy: 1846/5000 (37%)
[epoch 9] loss: 0.9777629
Test set: Average loss: 1.4970, Accuracy: 1880/5000 (38%)
[epoch 10] loss: 0.9299668
Test set: Average loss: 1.4905, Accuracy: 1891/5000 (38%)
[epoch 11] loss: 0.8991604
Test set: Average loss: 1.4846, Accuracy: 1913/5000 (38%)
[epoch 12] loss: 0.8700839
Test set: Average loss: 1.4789, Accuracy: 1911/5000 (38%)
[epoch 13] loss: 0.8356109
Test set: Average loss: 1.4737, Accuracy: 1937/5000 (39%)
[epoch 14] loss: 0.7974723
Test set: Average loss: 1.4691, Accuracy: 1940/5000 (39%)
[epoch 15] loss: 0.7835244
Test set: Average loss: 1.4651, Accuracy: 1951/5000 (39%)
[epoch 16] loss: 0.7556080
Test set: Average loss: 1.4616, Accuracy: 1961/5000 (39%)
[epoch 17] loss: 0.7201101
Test set: Average loss: 1.4583, Accuracy: 1974/5000 (39%)
[epoch 18] loss: 0.7036088
Test set: Average loss: 1.4555, Accuracy: 1981/5000 (40%)
[epoch 19] loss: 0.6872029
Test set: Average loss: 1.4527, Accuracy: 1988/5000 (40%)
[epoch 20] loss: 0.6621484
Test set: Average loss: 1.4500, Accuracy: 2004/5000 (40%)
[epoch 21] loss: 0.6721928
Epoch 20: reducing learning rate of group 0 to 5.0000e-06.
Test set: Average loss: 1.4472, Accuracy: 2007/5000 (40%)
[epoch 22] loss: 0.6285317
Test set: Average loss: 1.4470, Accuracy: 2003/5000 (40%)
[epoch 23] loss: 0.6318679
Epoch 22: reducing learning rate of group 0 to 5.0000e-07.
Test set: Average loss: 1.4468, Accuracy: 2002/5000 (40%)
[epoch 24] loss: 0.6352627
Epoch 23: reducing learning rate of group 0 to 5.0000e-08.
Test set: Average loss: 1.4468, Accuracy: 2002/5000 (40%)
[epoch 25] loss: 0.6377084
Epoch 24: reducing learning rate of group 0 to 5.0000e-09.
Test set: Average loss: 1.4468, Accuracy: 2002/5000 (40%)
Validation:
Test set: Average loss: 1.4472, Accuracy: 2007/5000 (40%)
Test
Test set: Average loss: 1.4637, Accuracy: 1997/5000 (40%)
Test set: Average loss: 0.6401, Accuracy: 50/50 (100%)
## seed: 13
Validation accuracy before training:
Test set: Average loss: 1.7212, Accuracy: 656/5000 (13%)
[epoch 1] loss: 1.6952681
Test set: Average loss: 1.6863, Accuracy: 775/5000 (16%)
[epoch 2] loss: 1.5463943
Test set: Average loss: 1.6541, Accuracy: 943/5000 (19%)
[epoch 3] loss: 1.4611318
Test set: Average loss: 1.6267, Accuracy: 1093/5000 (22%)
[epoch 4] loss: 1.3960850
Test set: Average loss: 1.6028, Accuracy: 1209/5000 (24%)
[epoch 5] loss: 1.2943298
Test set: Average loss: 1.5826, Accuracy: 1345/5000 (27%)
[epoch 6] loss: 1.2505068
Test set: Average loss: 1.5656, Accuracy: 1452/5000 (29%)
[epoch 7] loss: 1.1716725
Test set: Average loss: 1.5507, Accuracy: 1522/5000 (30%)
[epoch 8] loss: 1.0994628
Test set: Average loss: 1.5370, Accuracy: 1603/5000 (32%)
[epoch 9] loss: 1.0836635
Test set: Average loss: 1.5249, Accuracy: 1665/5000 (33%)
[epoch 10] loss: 1.0350025
Test set: Average loss: 1.5133, Accuracy: 1702/5000 (34%)
[epoch 11] loss: 1.0174294
Test set: Average loss: 1.5024, Accuracy: 1758/5000 (35%)
[epoch 12] loss: 0.9742821
Test set: Average loss: 1.4923, Accuracy: 1798/5000 (36%)
[epoch 13] loss: 0.9336206
Test set: Average loss: 1.4824, Accuracy: 1832/5000 (37%)
[epoch 14] loss: 0.9117102
Test set: Average loss: 1.4731, Accuracy: 1869/5000 (37%)
[epoch 15] loss: 0.8722799
Test set: Average loss: 1.4641, Accuracy: 1898/5000 (38%)
[epoch 16] loss: 0.8507449
Test set: Average loss: 1.4560, Accuracy: 1922/5000 (38%)
[epoch 17] loss: 0.7993299
Test set: Average loss: 1.4487, Accuracy: 1948/5000 (39%)
[epoch 18] loss: 0.7875143
Test set: Average loss: 1.4422, Accuracy: 1966/5000 (39%)
[epoch 19] loss: 0.7778023
Test set: Average loss: 1.4364, Accuracy: 1981/5000 (40%)
[epoch 20] loss: 0.7692085
Test set: Average loss: 1.4309, Accuracy: 2005/5000 (40%)
[epoch 21] loss: 0.7402983
Test set: Average loss: 1.4259, Accuracy: 2022/5000 (40%)
[epoch 22] loss: 0.6984598
Test set: Average loss: 1.4210, Accuracy: 2030/5000 (41%)
[epoch 23] loss: 0.7017823
Epoch 22: reducing learning rate of group 0 to 5.0000e-06.
Test set: Average loss: 1.4167, Accuracy: 2033/5000 (41%)
[epoch 24] loss: 0.6871808
Test set: Average loss: 1.4163, Accuracy: 2036/5000 (41%)
[epoch 25] loss: 0.6745267
Test set: Average loss: 1.4159, Accuracy: 2037/5000 (41%)
Validation:
Test set: Average loss: 1.4159, Accuracy: 2037/5000 (41%)
Test
Test set: Average loss: 1.4244, Accuracy: 1995/5000 (40%)
Test set: Average loss: 0.6830, Accuracy: 47/50 (94%)
100
## seed: 11
Validation accuracy before training:
Test set: Average loss: 1.6399, Accuracy: 1091/5000 (22%)
[epoch 1] loss: 1.6295649
Test set: Average loss: 1.5886, Accuracy: 1366/5000 (27%)
[epoch 2] loss: 1.4724689
Test set: Average loss: 1.5462, Accuracy: 1614/5000 (32%)
[epoch 3] loss: 1.4163414
Test set: Average loss: 1.5177, Accuracy: 1785/5000 (36%)
[epoch 4] loss: 1.2901819
Test set: Average loss: 1.4975, Accuracy: 1884/5000 (38%)
[epoch 5] loss: 1.2541082
Test set: Average loss: 1.4807, Accuracy: 1936/5000 (39%)
[epoch 6] loss: 1.2318630
Test set: Average loss: 1.4669, Accuracy: 2008/5000 (40%)
[epoch 7] loss: 1.1429012
Test set: Average loss: 1.4552, Accuracy: 2072/5000 (41%)
[epoch 8] loss: 1.1148145
Test set: Average loss: 1.4447, Accuracy: 2126/5000 (43%)
[epoch 9] loss: 1.0476090
Test set: Average loss: 1.4361, Accuracy: 2142/5000 (43%)
[epoch 10] loss: 1.0715063
Epoch 9: reducing learning rate of group 0 to 5.0000e-06.
Test set: Average loss: 1.4294, Accuracy: 2128/5000 (43%)
[epoch 11] loss: 1.0268040
Test set: Average loss: 1.4288, Accuracy: 2129/5000 (43%)
[epoch 12] loss: 0.9794928
Test set: Average loss: 1.4283, Accuracy: 2127/5000 (43%)
[epoch 13] loss: 0.9712867
Test set: Average loss: 1.4277, Accuracy: 2124/5000 (42%)
[epoch 14] loss: 0.9987256
Epoch 13: reducing learning rate of group 0 to 5.0000e-07.
Test set: Average loss: 1.4272, Accuracy: 2124/5000 (42%)
[epoch 15] loss: 1.0092645
Epoch 14: reducing learning rate of group 0 to 5.0000e-08.
Test set: Average loss: 1.4272, Accuracy: 2124/5000 (42%)
[epoch 16] loss: 0.9877408
Epoch 15: reducing learning rate of group 0 to 5.0000e-09.
Test set: Average loss: 1.4271, Accuracy: 2124/5000 (42%)
[epoch 17] loss: 0.9966792
Epoch 16: reducing learning rate of group 0 to 5.0000e-10.
Test set: Average loss: 1.4271, Accuracy: 2124/5000 (42%)
[epoch 18] loss: 1.0163204
Epoch 17: reducing learning rate of group 0 to 5.0000e-11.
Test set: Average loss: 1.4271, Accuracy: 2124/5000 (42%)
[epoch 19] loss: 0.9609567
Test set: Average loss: 1.4271, Accuracy: 2124/5000 (42%)
[epoch 20] loss: 0.9900959
Epoch 19: reducing learning rate of group 0 to 5.0000e-12.
Test set: Average loss: 1.4271, Accuracy: 2124/5000 (42%)
[epoch 21] loss: 1.0557127
Epoch 20: reducing learning rate of group 0 to 5.0000e-13.
Test set: Average loss: 1.4271, Accuracy: 2124/5000 (42%)
[epoch 22] loss: 0.9883209
Epoch 21: reducing learning rate of group 0 to 5.0000e-14.
Test set: Average loss: 1.4271, Accuracy: 2124/5000 (42%)
[epoch 23] loss: 0.9749352
Epoch 22: reducing learning rate of group 0 to 5.0000e-15.
Test set: Average loss: 1.4271, Accuracy: 2124/5000 (42%)
[epoch 24] loss: 0.9670764
Epoch 23: reducing learning rate of group 0 to 5.0000e-16.
Test set: Average loss: 1.4271, Accuracy: 2124/5000 (42%)
[epoch 25] loss: 1.0196178
Epoch 24: reducing learning rate of group 0 to 5.0000e-17.
Test set: Average loss: 1.4271, Accuracy: 2124/5000 (42%)
Validation:
Test set: Average loss: 1.4361, Accuracy: 2142/5000 (43%)
Test
Test set: Average loss: 1.4405, Accuracy: 2109/5000 (42%)
Test set: Average loss: 1.0466, Accuracy: 80/100 (80%)
## seed: 12
Validation accuracy before training:
Test set: Average loss: 1.6636, Accuracy: 901/5000 (18%)
[epoch 1] loss: 1.6695961
Test set: Average loss: 1.6107, Accuracy: 1118/5000 (22%)
[epoch 2] loss: 1.5105411
Test set: Average loss: 1.5840, Accuracy: 1277/5000 (26%)
[epoch 3] loss: 1.3686212
Test set: Average loss: 1.5643, Accuracy: 1437/5000 (29%)
[epoch 4] loss: 1.3351293
Test set: Average loss: 1.5492, Accuracy: 1515/5000 (30%)
[epoch 5] loss: 1.1750696
Test set: Average loss: 1.5337, Accuracy: 1602/5000 (32%)
[epoch 6] loss: 1.1459679
Test set: Average loss: 1.5190, Accuracy: 1660/5000 (33%)
[epoch 7] loss: 1.1344230
Test set: Average loss: 1.5058, Accuracy: 1704/5000 (34%)
[epoch 8] loss: 1.1053751
Test set: Average loss: 1.4940, Accuracy: 1756/5000 (35%)
[epoch 9] loss: 1.0244217
Test set: Average loss: 1.4808, Accuracy: 1813/5000 (36%)
[epoch 10] loss: 1.0089823
Test set: Average loss: 1.4683, Accuracy: 1862/5000 (37%)
[epoch 11] loss: 0.9365633
Test set: Average loss: 1.4578, Accuracy: 1898/5000 (38%)
[epoch 12] loss: 0.9894337
Epoch 11: reducing learning rate of group 0 to 5.0000e-06.
Test set: Average loss: 1.4493, Accuracy: 1918/5000 (38%)
[epoch 13] loss: 0.9333009
Test set: Average loss: 1.4487, Accuracy: 1919/5000 (38%)
[epoch 14] loss: 0.9202932
Test set: Average loss: 1.4479, Accuracy: 1920/5000 (38%)
[epoch 15] loss: 0.9992667
Epoch 14: reducing learning rate of group 0 to 5.0000e-07.
Test set: Average loss: 1.4470, Accuracy: 1923/5000 (38%)
[epoch 16] loss: 0.9239787
Epoch 15: reducing learning rate of group 0 to 5.0000e-08.
Test set: Average loss: 1.4470, Accuracy: 1923/5000 (38%)
[epoch 17] loss: 0.9312354
Epoch 16: reducing learning rate of group 0 to 5.0000e-09.
Test set: Average loss: 1.4469, Accuracy: 1923/5000 (38%)
[epoch 18] loss: 0.9391806
Epoch 17: reducing learning rate of group 0 to 5.0000e-10.
Test set: Average loss: 1.4469, Accuracy: 1923/5000 (38%)
[epoch 19] loss: 0.8996424
Test set: Average loss: 1.4469, Accuracy: 1923/5000 (38%)
[epoch 20] loss: 0.9071552
Epoch 19: reducing learning rate of group 0 to 5.0000e-11.
Test set: Average loss: 1.4469, Accuracy: 1923/5000 (38%)
[epoch 21] loss: 0.9483156
Epoch 20: reducing learning rate of group 0 to 5.0000e-12.
Test set: Average loss: 1.4469, Accuracy: 1923/5000 (38%)
[epoch 22] loss: 0.9490472
Epoch 21: reducing learning rate of group 0 to 5.0000e-13.
Test set: Average loss: 1.4469, Accuracy: 1923/5000 (38%)
[epoch 23] loss: 0.9274793
Epoch 22: reducing learning rate of group 0 to 5.0000e-14.
Test set: Average loss: 1.4469, Accuracy: 1923/5000 (38%)
[epoch 24] loss: 0.9028692
Epoch 23: reducing learning rate of group 0 to 5.0000e-15.
Test set: Average loss: 1.4469, Accuracy: 1923/5000 (38%)
[epoch 25] loss: 0.9163559
Epoch 24: reducing learning rate of group 0 to 5.0000e-16.
Test set: Average loss: 1.4469, Accuracy: 1923/5000 (38%)
Validation:
Test set: Average loss: 1.4469, Accuracy: 1923/5000 (38%)
Test
Test set: Average loss: 1.4399, Accuracy: 1948/5000 (39%)
Test set: Average loss: 0.9304, Accuracy: 84/100 (84%)
## seed: 13
Validation accuracy before training:
Test set: Average loss: 1.6353, Accuracy: 1091/5000 (22%)
[epoch 1] loss: 1.6484062
Test set: Average loss: 1.5712, Accuracy: 1418/5000 (28%)
[epoch 2] loss: 1.4956146
Test set: Average loss: 1.5311, Accuracy: 1645/5000 (33%)
[epoch 3] loss: 1.3913726
Test set: Average loss: 1.5055, Accuracy: 1772/5000 (35%)
[epoch 4] loss: 1.3349675
Test set: Average loss: 1.4872, Accuracy: 1841/5000 (37%)
[epoch 5] loss: 1.2018326
Test set: Average loss: 1.4720, Accuracy: 1870/5000 (37%)
[epoch 6] loss: 1.2877636
Epoch 5: reducing learning rate of group 0 to 5.0000e-06.
Test set: Average loss: 1.4584, Accuracy: 1897/5000 (38%)
[epoch 7] loss: 1.1537856
Test set: Average loss: 1.4570, Accuracy: 1902/5000 (38%)
[epoch 8] loss: 1.1367831
Test set: Average loss: 1.4555, Accuracy: 1904/5000 (38%)
[epoch 9] loss: 1.1547056
Epoch 8: reducing learning rate of group 0 to 5.0000e-07.
Test set: Average loss: 1.4541, Accuracy: 1905/5000 (38%)
[epoch 10] loss: 1.2054752
Epoch 9: reducing learning rate of group 0 to 5.0000e-08.
Test set: Average loss: 1.4540, Accuracy: 1906/5000 (38%)
[epoch 11] loss: 1.1251891
Test set: Average loss: 1.4540, Accuracy: 1906/5000 (38%)
[epoch 12] loss: 1.1777686
Epoch 11: reducing learning rate of group 0 to 5.0000e-09.
Test set: Average loss: 1.4540, Accuracy: 1906/5000 (38%)
[epoch 13] loss: 1.1858730
Epoch 12: reducing learning rate of group 0 to 5.0000e-10.
Test set: Average loss: 1.4540, Accuracy: 1906/5000 (38%)
[epoch 14] loss: 1.1676475
Epoch 13: reducing learning rate of group 0 to 5.0000e-11.
Test set: Average loss: 1.4540, Accuracy: 1906/5000 (38%)
[epoch 15] loss: 1.2407824
Epoch 14: reducing learning rate of group 0 to 5.0000e-12.
Test set: Average loss: 1.4540, Accuracy: 1906/5000 (38%)
[epoch 16] loss: 1.2099721
Epoch 15: reducing learning rate of group 0 to 5.0000e-13.
Test set: Average loss: 1.4540, Accuracy: 1906/5000 (38%)
[epoch 17] loss: 1.1409698
Epoch 16: reducing learning rate of group 0 to 5.0000e-14.
Test set: Average loss: 1.4540, Accuracy: 1906/5000 (38%)
[epoch 18] loss: 1.1671617
Epoch 17: reducing learning rate of group 0 to 5.0000e-15.
Test set: Average loss: 1.4540, Accuracy: 1906/5000 (38%)
[epoch 19] loss: 1.1110338
Test set: Average loss: 1.4540, Accuracy: 1906/5000 (38%)
[epoch 20] loss: 1.1748244
Epoch 19: reducing learning rate of group 0 to 5.0000e-16.
Test set: Average loss: 1.4540, Accuracy: 1906/5000 (38%)
[epoch 21] loss: 1.1985893
Epoch 20: reducing learning rate of group 0 to 5.0000e-17.
Test set: Average loss: 1.4540, Accuracy: 1906/5000 (38%)
[epoch 22] loss: 1.2129620
Epoch 21: reducing learning rate of group 0 to 5.0000e-18.
Test set: Average loss: 1.4540, Accuracy: 1906/5000 (38%)
[epoch 23] loss: 1.1776108
Epoch 22: reducing learning rate of group 0 to 5.0000e-19.
Test set: Average loss: 1.4540, Accuracy: 1906/5000 (38%)
[epoch 24] loss: 1.1798629
Epoch 23: reducing learning rate of group 0 to 5.0000e-20.
Test set: Average loss: 1.4540, Accuracy: 1906/5000 (38%)
[epoch 25] loss: 1.1570569
Epoch 24: reducing learning rate of group 0 to 5.0000e-21.
Test set: Average loss: 1.4540, Accuracy: 1906/5000 (38%)
Validation:
Test set: Average loss: 1.4540, Accuracy: 1906/5000 (38%)
Test
Test set: Average loss: 1.4484, Accuracy: 1931/5000 (39%)
Test set: Average loss: 1.1838, Accuracy: 58/100 (58%)
250
## seed: 11
Validation accuracy before training:
Test set: Average loss: 1.5454, Accuracy: 1570/5000 (31%)
[epoch 1] loss: 1.5100197
Test set: Average loss: 1.4515, Accuracy: 1916/5000 (38%)
[epoch 2] loss: 1.3577955
Test set: Average loss: 1.4034, Accuracy: 2015/5000 (40%)
[epoch 3] loss: 1.2665279
Test set: Average loss: 1.3678, Accuracy: 2153/5000 (43%)
[epoch 4] loss: 1.1820385
Test set: Average loss: 1.3421, Accuracy: 2218/5000 (44%)
[epoch 5] loss: 1.1182073
Test set: Average loss: 1.3225, Accuracy: 2274/5000 (45%)
[epoch 6] loss: 1.0584299
Test set: Average loss: 1.3063, Accuracy: 2311/5000 (46%)
[epoch 7] loss: 1.0110534
Test set: Average loss: 1.2935, Accuracy: 2336/5000 (47%)
[epoch 8] loss: 0.9641276
Test set: Average loss: 1.2833, Accuracy: 2362/5000 (47%)
[epoch 9] loss: 0.9257147
Test set: Average loss: 1.2714, Accuracy: 2422/5000 (48%)
[epoch 10] loss: 0.8859790
Test set: Average loss: 1.2652, Accuracy: 2431/5000 (49%)
[epoch 11] loss: 0.8518323
Test set: Average loss: 1.2584, Accuracy: 2448/5000 (49%)
[epoch 12] loss: 0.8229685
Test set: Average loss: 1.2525, Accuracy: 2468/5000 (49%)
[epoch 13] loss: 0.7936277
Test set: Average loss: 1.2476, Accuracy: 2475/5000 (50%)
[epoch 14] loss: 0.7661905
Test set: Average loss: 1.2434, Accuracy: 2498/5000 (50%)
[epoch 15] loss: 0.7414308
Test set: Average loss: 1.2406, Accuracy: 2511/5000 (50%)
[epoch 16] loss: 0.7203250
Test set: Average loss: 1.2376, Accuracy: 2517/5000 (50%)
[epoch 17] loss: 0.6929149
Test set: Average loss: 1.2338, Accuracy: 2530/5000 (51%)
[epoch 18] loss: 0.6734695
Test set: Average loss: 1.2305, Accuracy: 2548/5000 (51%)
[epoch 19] loss: 0.6549408
Test set: Average loss: 1.2293, Accuracy: 2545/5000 (51%)
[epoch 20] loss: 0.6366219
Test set: Average loss: 1.2256, Accuracy: 2564/5000 (51%)
[epoch 21] loss: 0.6169333
Test set: Average loss: 1.2245, Accuracy: 2564/5000 (51%)
[epoch 22] loss: 0.6004049
Test set: Average loss: 1.2234, Accuracy: 2569/5000 (51%)
[epoch 23] loss: 0.5839463
Test set: Average loss: 1.2216, Accuracy: 2579/5000 (52%)
[epoch 24] loss: 0.5681129
Test set: Average loss: 1.2189, Accuracy: 2588/5000 (52%)
[epoch 25] loss: 0.5546801
Test set: Average loss: 1.2171, Accuracy: 2596/5000 (52%)
Validation:
Test set: Average loss: 1.2171, Accuracy: 2596/5000 (52%)
Test
Test set: Average loss: 1.2211, Accuracy: 2604/5000 (52%)
Test set: Average loss: 0.5420, Accuracy: 244/250 (98%)
## seed: 12
Validation accuracy before training:
Test set: Average loss: 1.6072, Accuracy: 1214/5000 (24%)
[epoch 1] loss: 1.5496517
Test set: Average loss: 1.5065, Accuracy: 1911/5000 (38%)
[epoch 2] loss: 1.4096012
Test set: Average loss: 1.4381, Accuracy: 2141/5000 (43%)
[epoch 3] loss: 1.3133568
Test set: Average loss: 1.3948, Accuracy: 2226/5000 (45%)
[epoch 4] loss: 1.2378896
Test set: Average loss: 1.3688, Accuracy: 2283/5000 (46%)
[epoch 5] loss: 1.1771692
Test set: Average loss: 1.3493, Accuracy: 2312/5000 (46%)
[epoch 6] loss: 1.1292669
Test set: Average loss: 1.3351, Accuracy: 2323/5000 (46%)
[epoch 7] loss: 1.0787281
Test set: Average loss: 1.3254, Accuracy: 2353/5000 (47%)
[epoch 8] loss: 1.0392523
Test set: Average loss: 1.3122, Accuracy: 2396/5000 (48%)
[epoch 9] loss: 1.0009048
Test set: Average loss: 1.3035, Accuracy: 2420/5000 (48%)
[epoch 10] loss: 0.9649950
Test set: Average loss: 1.2951, Accuracy: 2440/5000 (49%)
[epoch 11] loss: 0.9335102
Test set: Average loss: 1.2893, Accuracy: 2457/5000 (49%)
[epoch 12] loss: 0.9033160
Test set: Average loss: 1.2843, Accuracy: 2449/5000 (49%)
[epoch 13] loss: 0.8737838
Test set: Average loss: 1.2789, Accuracy: 2459/5000 (49%)
[epoch 14] loss: 0.8488279
Test set: Average loss: 1.2733, Accuracy: 2473/5000 (49%)
[epoch 15] loss: 0.8257045
Test set: Average loss: 1.2687, Accuracy: 2463/5000 (49%)
[epoch 16] loss: 0.8003429
Test set: Average loss: 1.2644, Accuracy: 2471/5000 (49%)
[epoch 17] loss: 0.7777785
Test set: Average loss: 1.2594, Accuracy: 2488/5000 (50%)
[epoch 18] loss: 0.7583173
Test set: Average loss: 1.2584, Accuracy: 2479/5000 (50%)
[epoch 19] loss: 0.7364990
Test set: Average loss: 1.2544, Accuracy: 2480/5000 (50%)
[epoch 20] loss: 0.7185044
Test set: Average loss: 1.2496, Accuracy: 2510/5000 (50%)
[epoch 21] loss: 0.6983798
Test set: Average loss: 1.2468, Accuracy: 2529/5000 (51%)
[epoch 22] loss: 0.6801763
Test set: Average loss: 1.2461, Accuracy: 2516/5000 (50%)
[epoch 23] loss: 0.6632213
Test set: Average loss: 1.2440, Accuracy: 2510/5000 (50%)
[epoch 24] loss: 0.6438867
Test set: Average loss: 1.2409, Accuracy: 2526/5000 (51%)
[epoch 25] loss: 0.6300513
Test set: Average loss: 1.2377, Accuracy: 2531/5000 (51%)
Validation:
Test set: Average loss: 1.2377, Accuracy: 2531/5000 (51%)
Test
Test set: Average loss: 1.2364, Accuracy: 2545/5000 (51%)
Test set: Average loss: 0.6171, Accuracy: 238/250 (95%)
## seed: 13
Validation accuracy before training:
Test set: Average loss: 1.6149, Accuracy: 916/5000 (18%)
[epoch 1] loss: 1.5597206
Test set: Average loss: 1.5103, Accuracy: 1519/5000 (30%)
[epoch 2] loss: 1.4030389
Test set: Average loss: 1.4373, Accuracy: 1910/5000 (38%)
[epoch 3] loss: 1.3021143
Test set: Average loss: 1.3911, Accuracy: 2083/5000 (42%)
[epoch 4] loss: 1.2222437
Test set: Average loss: 1.3611, Accuracy: 2217/5000 (44%)
[epoch 5] loss: 1.1596826
Test set: Average loss: 1.3382, Accuracy: 2320/5000 (46%)
[epoch 6] loss: 1.0998600
Test set: Average loss: 1.3228, Accuracy: 2360/5000 (47%)
[epoch 7] loss: 1.0547355
Test set: Average loss: 1.3081, Accuracy: 2394/5000 (48%)
[epoch 8] loss: 1.0077882
Test set: Average loss: 1.2981, Accuracy: 2422/5000 (48%)
[epoch 9] loss: 0.9714220
Test set: Average loss: 1.2901, Accuracy: 2445/5000 (49%)
[epoch 10] loss: 0.9353269
Test set: Average loss: 1.2821, Accuracy: 2467/5000 (49%)
[epoch 11] loss: 0.9044264
Test set: Average loss: 1.2767, Accuracy: 2463/5000 (49%)
[epoch 12] loss: 0.8734360
Test set: Average loss: 1.2706, Accuracy: 2486/5000 (50%)
[epoch 13] loss: 0.8447210
Test set: Average loss: 1.2644, Accuracy: 2516/5000 (50%)
[epoch 14] loss: 0.8225308
Test set: Average loss: 1.2596, Accuracy: 2518/5000 (50%)
[epoch 15] loss: 0.7986037
Test set: Average loss: 1.2567, Accuracy: 2537/5000 (51%)
[epoch 16] loss: 0.7745403
Test set: Average loss: 1.2532, Accuracy: 2551/5000 (51%)
[epoch 17] loss: 0.7550370
Test set: Average loss: 1.2509, Accuracy: 2548/5000 (51%)
[epoch 18] loss: 0.7339528
Test set: Average loss: 1.2483, Accuracy: 2554/5000 (51%)
[epoch 19] loss: 0.7147868
Test set: Average loss: 1.2452, Accuracy: 2556/5000 (51%)
[epoch 20] loss: 0.6962486
Test set: Average loss: 1.2429, Accuracy: 2567/5000 (51%)
[epoch 21] loss: 0.6820433
Test set: Average loss: 1.2409, Accuracy: 2569/5000 (51%)
[epoch 22] loss: 0.6637487
Test set: Average loss: 1.2390, Accuracy: 2574/5000 (51%)
[epoch 23] loss: 0.6450863
Test set: Average loss: 1.2378, Accuracy: 2582/5000 (52%)
[epoch 24] loss: 0.6343883
Test set: Average loss: 1.2371, Accuracy: 2566/5000 (51%)
[epoch 25] loss: 0.6156996
Test set: Average loss: 1.2351, Accuracy: 2574/5000 (51%)
Validation:
Test set: Average loss: 1.2378, Accuracy: 2582/5000 (52%)
Test
Test set: Average loss: 1.2525, Accuracy: 2556/5000 (51%)
Test set: Average loss: 0.6351, Accuracy: 239/250 (96%)
500
## seed: 11
Validation accuracy before training:
Test set: Average loss: 1.6406, Accuracy: 1006/5000 (20%)
[epoch 1] loss: 1.5319954
Test set: Average loss: 1.4391, Accuracy: 2073/5000 (41%)
[epoch 2] loss: 1.3372272
Test set: Average loss: 1.3643, Accuracy: 2208/5000 (44%)
[epoch 3] loss: 1.2393775
Test set: Average loss: 1.3206, Accuracy: 2363/5000 (47%)
[epoch 4] loss: 1.1649680
Test set: Average loss: 1.2912, Accuracy: 2472/5000 (49%)
[epoch 5] loss: 1.0994956
Test set: Average loss: 1.2717, Accuracy: 2521/5000 (50%)
[epoch 6] loss: 1.0471658
Test set: Average loss: 1.2557, Accuracy: 2568/5000 (51%)
[epoch 7] loss: 1.0032941
Test set: Average loss: 1.2426, Accuracy: 2588/5000 (52%)
[epoch 8] loss: 0.9608506
Test set: Average loss: 1.2327, Accuracy: 2609/5000 (52%)
[epoch 9] loss: 0.9234144
Test set: Average loss: 1.2245, Accuracy: 2637/5000 (53%)
[epoch 10] loss: 0.8891721
Test set: Average loss: 1.2157, Accuracy: 2659/5000 (53%)
[epoch 11] loss: 0.8545849
Test set: Average loss: 1.2105, Accuracy: 2656/5000 (53%)
[epoch 12] loss: 0.8295402
Test set: Average loss: 1.2032, Accuracy: 2683/5000 (54%)
[epoch 13] loss: 0.8005834
Test set: Average loss: 1.1966, Accuracy: 2708/5000 (54%)
[epoch 14] loss: 0.7754338
Test set: Average loss: 1.1925, Accuracy: 2706/5000 (54%)
[epoch 15] loss: 0.7500933
Test set: Average loss: 1.1895, Accuracy: 2706/5000 (54%)
[epoch 16] loss: 0.7264723
Test set: Average loss: 1.1854, Accuracy: 2719/5000 (54%)
[epoch 17] loss: 0.7043556
Test set: Average loss: 1.1823, Accuracy: 2715/5000 (54%)
[epoch 18] loss: 0.6840479
Test set: Average loss: 1.1768, Accuracy: 2741/5000 (55%)
[epoch 19] loss: 0.6601362
Test set: Average loss: 1.1756, Accuracy: 2738/5000 (55%)
[epoch 20] loss: 0.6435550
Test set: Average loss: 1.1746, Accuracy: 2743/5000 (55%)
[epoch 21] loss: 0.6244247
Test set: Average loss: 1.1704, Accuracy: 2743/5000 (55%)
[epoch 22] loss: 0.6020585
Test set: Average loss: 1.1671, Accuracy: 2761/5000 (55%)
[epoch 23] loss: 0.5858330
Test set: Average loss: 1.1660, Accuracy: 2761/5000 (55%)
[epoch 24] loss: 0.5672322
Test set: Average loss: 1.1622, Accuracy: 2760/5000 (55%)
[epoch 25] loss: 0.5505703
Test set: Average loss: 1.1617, Accuracy: 2761/5000 (55%)
Validation:
Test set: Average loss: 1.1617, Accuracy: 2761/5000 (55%)
Test
Test set: Average loss: 1.1611, Accuracy: 2744/5000 (55%)
Test set: Average loss: 0.5384, Accuracy: 480/500 (96%)
## seed: 12
Validation accuracy before training:
Test set: Average loss: 1.6578, Accuracy: 920/5000 (18%)
[epoch 1] loss: 1.5786722
Test set: Average loss: 1.4532, Accuracy: 1956/5000 (39%)
[epoch 2] loss: 1.3794520
Test set: Average loss: 1.3628, Accuracy: 2246/5000 (45%)
[epoch 3] loss: 1.2609076
Test set: Average loss: 1.3158, Accuracy: 2429/5000 (49%)
[epoch 4] loss: 1.1804471
Test set: Average loss: 1.2848, Accuracy: 2521/5000 (50%)
[epoch 5] loss: 1.1120042
Test set: Average loss: 1.2686, Accuracy: 2554/5000 (51%)
[epoch 6] loss: 1.0555340
Test set: Average loss: 1.2499, Accuracy: 2616/5000 (52%)
[epoch 7] loss: 1.0127905
Test set: Average loss: 1.2401, Accuracy: 2629/5000 (53%)
[epoch 8] loss: 0.9628390
Test set: Average loss: 1.2301, Accuracy: 2655/5000 (53%)
[epoch 9] loss: 0.9222404
Test set: Average loss: 1.2172, Accuracy: 2681/5000 (54%)
[epoch 10] loss: 0.8886503
Test set: Average loss: 1.2114, Accuracy: 2702/5000 (54%)
[epoch 11] loss: 0.8545375
Test set: Average loss: 1.2032, Accuracy: 2734/5000 (55%)
[epoch 12] loss: 0.8205541
Test set: Average loss: 1.1987, Accuracy: 2712/5000 (54%)
[epoch 13] loss: 0.7939136
Test set: Average loss: 1.1898, Accuracy: 2765/5000 (55%)
[epoch 14] loss: 0.7595067
Test set: Average loss: 1.1857, Accuracy: 2771/5000 (55%)
[epoch 15] loss: 0.7335718
Test set: Average loss: 1.1794, Accuracy: 2799/5000 (56%)
[epoch 16] loss: 0.7118956
Test set: Average loss: 1.1766, Accuracy: 2787/5000 (56%)
[epoch 17] loss: 0.6837724
Test set: Average loss: 1.1712, Accuracy: 2806/5000 (56%)
[epoch 18] loss: 0.6640440
Test set: Average loss: 1.1653, Accuracy: 2826/5000 (57%)
[epoch 19] loss: 0.6399166
Test set: Average loss: 1.1651, Accuracy: 2798/5000 (56%)
[epoch 20] loss: 0.6158759
Test set: Average loss: 1.1607, Accuracy: 2812/5000 (56%)
[epoch 21] loss: 0.5921637
Test set: Average loss: 1.1566, Accuracy: 2829/5000 (57%)
[epoch 22] loss: 0.5770663
Test set: Average loss: 1.1528, Accuracy: 2829/5000 (57%)
[epoch 23] loss: 0.5508861
Test set: Average loss: 1.1526, Accuracy: 2829/5000 (57%)
[epoch 24] loss: 0.5326038
Test set: Average loss: 1.1472, Accuracy: 2837/5000 (57%)
[epoch 25] loss: 0.5166928
Test set: Average loss: 1.1475, Accuracy: 2828/5000 (57%)
Validation:
Test set: Average loss: 1.1472, Accuracy: 2837/5000 (57%)
Test
Test set: Average loss: 1.1542, Accuracy: 2797/5000 (56%)
Test set: Average loss: 0.5189, Accuracy: 481/500 (96%)
## seed: 13
Validation accuracy before training:
Test set: Average loss: 1.5564, Accuracy: 1297/5000 (26%)
[epoch 1] loss: 1.4632000
Test set: Average loss: 1.3960, Accuracy: 2166/5000 (43%)
[epoch 2] loss: 1.2718909
Test set: Average loss: 1.3283, Accuracy: 2363/5000 (47%)
[epoch 3] loss: 1.1711689
Test set: Average loss: 1.2908, Accuracy: 2469/5000 (49%)
[epoch 4] loss: 1.0894487
Test set: Average loss: 1.2630, Accuracy: 2555/5000 (51%)
[epoch 5] loss: 1.0340850
Test set: Average loss: 1.2467, Accuracy: 2592/5000 (52%)
[epoch 6] loss: 0.9751866
Test set: Average loss: 1.2315, Accuracy: 2644/5000 (53%)
[epoch 7] loss: 0.9277377
Test set: Average loss: 1.2209, Accuracy: 2666/5000 (53%)
[epoch 8] loss: 0.8869215
Test set: Average loss: 1.2155, Accuracy: 2696/5000 (54%)
[epoch 9] loss: 0.8499384
Test set: Average loss: 1.2031, Accuracy: 2730/5000 (55%)
[epoch 10] loss: 0.8174666
Test set: Average loss: 1.2004, Accuracy: 2720/5000 (54%)
[epoch 11] loss: 0.7828805
Test set: Average loss: 1.1909, Accuracy: 2745/5000 (55%)
[epoch 12] loss: 0.7575865
Test set: Average loss: 1.1889, Accuracy: 2746/5000 (55%)
[epoch 13] loss: 0.7296815
Test set: Average loss: 1.1872, Accuracy: 2761/5000 (55%)
[epoch 14] loss: 0.7046530
Test set: Average loss: 1.1800, Accuracy: 2775/5000 (56%)
[epoch 15] loss: 0.6761393
Test set: Average loss: 1.1775, Accuracy: 2775/5000 (56%)
[epoch 16] loss: 0.6496722
Test set: Average loss: 1.1743, Accuracy: 2778/5000 (56%)
[epoch 17] loss: 0.6274197
Test set: Average loss: 1.1727, Accuracy: 2786/5000 (56%)
[epoch 18] loss: 0.6087942
Test set: Average loss: 1.1697, Accuracy: 2791/5000 (56%)
[epoch 19] loss: 0.5900353
Test set: Average loss: 1.1682, Accuracy: 2795/5000 (56%)
[epoch 20] loss: 0.5669237
Test set: Average loss: 1.1639, Accuracy: 2795/5000 (56%)
[epoch 21] loss: 0.5434443
Test set: Average loss: 1.1644, Accuracy: 2803/5000 (56%)
[epoch 22] loss: 0.5296959
Test set: Average loss: 1.1614, Accuracy: 2806/5000 (56%)
[epoch 23] loss: 0.5132061
Test set: Average loss: 1.1634, Accuracy: 2807/5000 (56%)
[epoch 24] loss: 0.4940778
Test set: Average loss: 1.1609, Accuracy: 2812/5000 (56%)
[epoch 25] loss: 0.4818523
Test set: Average loss: 1.1579, Accuracy: 2825/5000 (56%)
Validation:
Test set: Average loss: 1.1579, Accuracy: 2825/5000 (56%)
Test
Test set: Average loss: 1.1636, Accuracy: 2809/5000 (56%)
Test set: Average loss: 0.4657, Accuracy: 485/500 (97%)
750
## seed: 11
Validation accuracy before training:
Test set: Average loss: 1.6679, Accuracy: 918/5000 (18%)
[epoch 1] loss: 1.5200132
Test set: Average loss: 1.4036, Accuracy: 2053/5000 (41%)
[epoch 2] loss: 1.2941741
Test set: Average loss: 1.3188, Accuracy: 2334/5000 (47%)
[epoch 3] loss: 1.1851736
Test set: Average loss: 1.2775, Accuracy: 2460/5000 (49%)
[epoch 4] loss: 1.1042902
Test set: Average loss: 1.2487, Accuracy: 2580/5000 (52%)
[epoch 5] loss: 1.0442736
Test set: Average loss: 1.2262, Accuracy: 2628/5000 (53%)
[epoch 6] loss: 0.9897147
Test set: Average loss: 1.2137, Accuracy: 2684/5000 (54%)
[epoch 7] loss: 0.9453281
Test set: Average loss: 1.1993, Accuracy: 2717/5000 (54%)
[epoch 8] loss: 0.8969593
Test set: Average loss: 1.1898, Accuracy: 2748/5000 (55%)
[epoch 9] loss: 0.8638620
Test set: Average loss: 1.1799, Accuracy: 2774/5000 (55%)
[epoch 10] loss: 0.8320794
Test set: Average loss: 1.1743, Accuracy: 2794/5000 (56%)
[epoch 11] loss: 0.7956209
Test set: Average loss: 1.1653, Accuracy: 2820/5000 (56%)
[epoch 12] loss: 0.7673117
Test set: Average loss: 1.1601, Accuracy: 2826/5000 (57%)
[epoch 13] loss: 0.7379344
Test set: Average loss: 1.1562, Accuracy: 2841/5000 (57%)
[epoch 14] loss: 0.7105758
Test set: Average loss: 1.1484, Accuracy: 2857/5000 (57%)
[epoch 15] loss: 0.6800945
Test set: Average loss: 1.1443, Accuracy: 2842/5000 (57%)
[epoch 16] loss: 0.6571864
Test set: Average loss: 1.1403, Accuracy: 2863/5000 (57%)
[epoch 17] loss: 0.6315405
Test set: Average loss: 1.1365, Accuracy: 2858/5000 (57%)
[epoch 18] loss: 0.6043379
Test set: Average loss: 1.1354, Accuracy: 2878/5000 (58%)
[epoch 19] loss: 0.5824123
Test set: Average loss: 1.1294, Accuracy: 2894/5000 (58%)
[epoch 20] loss: 0.5603662
Test set: Average loss: 1.1315, Accuracy: 2880/5000 (58%)
[epoch 21] loss: 0.5393810
Test set: Average loss: 1.1243, Accuracy: 2904/5000 (58%)
[epoch 22] loss: 0.5196121
Test set: Average loss: 1.1219, Accuracy: 2915/5000 (58%)
[epoch 23] loss: 0.4991883
Test set: Average loss: 1.1241, Accuracy: 2890/5000 (58%)
[epoch 24] loss: 0.4869727
Test set: Average loss: 1.1222, Accuracy: 2892/5000 (58%)
[epoch 25] loss: 0.4644850
Test set: Average loss: 1.1198, Accuracy: 2893/5000 (58%)
Validation:
Test set: Average loss: 1.1219, Accuracy: 2915/5000 (58%)
Test
Test set: Average loss: 1.1261, Accuracy: 2863/5000 (57%)
Test set: Average loss: 0.5021, Accuracy: 707/750 (94%)
## seed: 12
Validation accuracy before training:
Test set: Average loss: 1.6428, Accuracy: 974/5000 (19%)
[epoch 1] loss: 1.5394484
Test set: Average loss: 1.4195, Accuracy: 2136/5000 (43%)
[epoch 2] loss: 1.3370977
Test set: Average loss: 1.3456, Accuracy: 2411/5000 (48%)
[epoch 3] loss: 1.2439958
Test set: Average loss: 1.3033, Accuracy: 2556/5000 (51%)
[epoch 4] loss: 1.1674259
Test set: Average loss: 1.2765, Accuracy: 2665/5000 (53%)
[epoch 5] loss: 1.1097051
Test set: Average loss: 1.2554, Accuracy: 2719/5000 (54%)
[epoch 6] loss: 1.0520989
Test set: Average loss: 1.2368, Accuracy: 2774/5000 (55%)
[epoch 7] loss: 1.0070550
Test set: Average loss: 1.2208, Accuracy: 2820/5000 (56%)
[epoch 8] loss: 0.9605366
Test set: Average loss: 1.2093, Accuracy: 2840/5000 (57%)
[epoch 9] loss: 0.9187358
Test set: Average loss: 1.1986, Accuracy: 2858/5000 (57%)
[epoch 10] loss: 0.8843119
Test set: Average loss: 1.1900, Accuracy: 2856/5000 (57%)
[epoch 11] loss: 0.8540692
Test set: Average loss: 1.1818, Accuracy: 2881/5000 (58%)
[epoch 12] loss: 0.8213986
Test set: Average loss: 1.1737, Accuracy: 2889/5000 (58%)
[epoch 13] loss: 0.7901476
Test set: Average loss: 1.1683, Accuracy: 2901/5000 (58%)
[epoch 14] loss: 0.7559302
Test set: Average loss: 1.1600, Accuracy: 2903/5000 (58%)
[epoch 15] loss: 0.7307807
Test set: Average loss: 1.1558, Accuracy: 2917/5000 (58%)
[epoch 16] loss: 0.6999111
Test set: Average loss: 1.1516, Accuracy: 2929/5000 (59%)
[epoch 17] loss: 0.6773438
Test set: Average loss: 1.1479, Accuracy: 2935/5000 (59%)
[epoch 18] loss: 0.6519256
Test set: Average loss: 1.1418, Accuracy: 2940/5000 (59%)
[epoch 19] loss: 0.6282293
Test set: Average loss: 1.1396, Accuracy: 2948/5000 (59%)
[epoch 20] loss: 0.6058884
Test set: Average loss: 1.1356, Accuracy: 2959/5000 (59%)
[epoch 21] loss: 0.5875953
Test set: Average loss: 1.1365, Accuracy: 2959/5000 (59%)
[epoch 22] loss: 0.5623258
Test set: Average loss: 1.1290, Accuracy: 2976/5000 (60%)
[epoch 23] loss: 0.5426096
Test set: Average loss: 1.1263, Accuracy: 2982/5000 (60%)
[epoch 24] loss: 0.5245950
Test set: Average loss: 1.1273, Accuracy: 2969/5000 (59%)
[epoch 25] loss: 0.5038147
Test set: Average loss: 1.1256, Accuracy: 2978/5000 (60%)
Validation:
Test set: Average loss: 1.1263, Accuracy: 2982/5000 (60%)
Test
Test set: Average loss: 1.1258, Accuracy: 2921/5000 (58%)
Test set: Average loss: 0.5241, Accuracy: 728/750 (97%)
## seed: 13
Validation accuracy before training:
Test set: Average loss: 1.6546, Accuracy: 889/5000 (18%)
[epoch 1] loss: 1.4842271
Test set: Average loss: 1.3915, Accuracy: 1945/5000 (39%)
[epoch 2] loss: 1.2700341
Test set: Average loss: 1.3111, Accuracy: 2294/5000 (46%)
[epoch 3] loss: 1.1675908
Test set: Average loss: 1.2755, Accuracy: 2428/5000 (49%)
[epoch 4] loss: 1.1026025
Test set: Average loss: 1.2480, Accuracy: 2540/5000 (51%)
[epoch 5] loss: 1.0438679
Test set: Average loss: 1.2296, Accuracy: 2572/5000 (51%)
[epoch 6] loss: 0.9918919
Test set: Average loss: 1.2160, Accuracy: 2615/5000 (52%)
[epoch 7] loss: 0.9415242
Test set: Average loss: 1.2034, Accuracy: 2664/5000 (53%)
[epoch 8] loss: 0.9051645
Test set: Average loss: 1.1925, Accuracy: 2675/5000 (54%)
[epoch 9] loss: 0.8646685
Test set: Average loss: 1.1817, Accuracy: 2721/5000 (54%)
[epoch 10] loss: 0.8339877
Test set: Average loss: 1.1757, Accuracy: 2714/5000 (54%)
[epoch 11] loss: 0.8036049
Test set: Average loss: 1.1658, Accuracy: 2765/5000 (55%)
[epoch 12] loss: 0.7684799
Test set: Average loss: 1.1626, Accuracy: 2744/5000 (55%)
[epoch 13] loss: 0.7407484
Test set: Average loss: 1.1544, Accuracy: 2770/5000 (55%)
[epoch 14] loss: 0.7135405
Test set: Average loss: 1.1476, Accuracy: 2791/5000 (56%)
[epoch 15] loss: 0.6828557
Test set: Average loss: 1.1454, Accuracy: 2801/5000 (56%)
[epoch 16] loss: 0.6544407
Test set: Average loss: 1.1392, Accuracy: 2823/5000 (56%)
[epoch 17] loss: 0.6298414
Test set: Average loss: 1.1415, Accuracy: 2792/5000 (56%)
[epoch 18] loss: 0.6084920
Test set: Average loss: 1.1340, Accuracy: 2831/5000 (57%)
[epoch 19] loss: 0.5805526
Test set: Average loss: 1.1319, Accuracy: 2803/5000 (56%)
[epoch 20] loss: 0.5586038
Test set: Average loss: 1.1277, Accuracy: 2842/5000 (57%)
[epoch 21] loss: 0.5348638
Test set: Average loss: 1.1270, Accuracy: 2838/5000 (57%)
[epoch 22] loss: 0.5155401
Test set: Average loss: 1.1272, Accuracy: 2830/5000 (57%)
[epoch 23] loss: 0.4955823
Test set: Average loss: 1.1223, Accuracy: 2843/5000 (57%)
[epoch 24] loss: 0.4780354
Test set: Average loss: 1.1216, Accuracy: 2833/5000 (57%)
[epoch 25] loss: 0.4571276
Test set: Average loss: 1.1209, Accuracy: 2826/5000 (57%)
Validation:
Test set: Average loss: 1.1223, Accuracy: 2843/5000 (57%)
Test
Test set: Average loss: 1.1414, Accuracy: 2802/5000 (56%)
Test set: Average loss: 0.4779, Accuracy: 719/750 (96%)
1000
## seed: 11
Validation accuracy before training:
Test set: Average loss: 1.5071, Accuracy: 1419/5000 (28%)
[epoch 1] loss: 1.3666331
Test set: Average loss: 1.2969, Accuracy: 2425/5000 (48%)
[epoch 2] loss: 1.1892984
Test set: Average loss: 1.2403, Accuracy: 2573/5000 (51%)
[epoch 3] loss: 1.1039203
Test set: Average loss: 1.2071, Accuracy: 2691/5000 (54%)
[epoch 4] loss: 1.0381253
Test set: Average loss: 1.1859, Accuracy: 2743/5000 (55%)
[epoch 5] loss: 0.9818883
Test set: Average loss: 1.1694, Accuracy: 2798/5000 (56%)
[epoch 6] loss: 0.9318438
Test set: Average loss: 1.1576, Accuracy: 2815/5000 (56%)
[epoch 7] loss: 0.8894285
Test set: Average loss: 1.1453, Accuracy: 2853/5000 (57%)
[epoch 8] loss: 0.8498604
Test set: Average loss: 1.1364, Accuracy: 2874/5000 (57%)
[epoch 9] loss: 0.8183431
Test set: Average loss: 1.1270, Accuracy: 2887/5000 (58%)
[epoch 10] loss: 0.7911687
Test set: Average loss: 1.1204, Accuracy: 2912/5000 (58%)
[epoch 11] loss: 0.7514697
Test set: Average loss: 1.1123, Accuracy: 2928/5000 (59%)
[epoch 12] loss: 0.7247416
Test set: Average loss: 1.1053, Accuracy: 2916/5000 (58%)
[epoch 13] loss: 0.6949104
Test set: Average loss: 1.1016, Accuracy: 2936/5000 (59%)
[epoch 14] loss: 0.6672810
Test set: Average loss: 1.0966, Accuracy: 2928/5000 (59%)
[epoch 15] loss: 0.6421679
Test set: Average loss: 1.0907, Accuracy: 2951/5000 (59%)
[epoch 16] loss: 0.6163841
Test set: Average loss: 1.0870, Accuracy: 2951/5000 (59%)
[epoch 17] loss: 0.5897141
Test set: Average loss: 1.0841, Accuracy: 2964/5000 (59%)
[epoch 18] loss: 0.5662496
Test set: Average loss: 1.0785, Accuracy: 2965/5000 (59%)
[epoch 19] loss: 0.5459125
Test set: Average loss: 1.0754, Accuracy: 2972/5000 (59%)
[epoch 20] loss: 0.5255474
Test set: Average loss: 1.0731, Accuracy: 2973/5000 (59%)
[epoch 21] loss: 0.5033941
Test set: Average loss: 1.0686, Accuracy: 2989/5000 (60%)
[epoch 22] loss: 0.4827939
Test set: Average loss: 1.0687, Accuracy: 2973/5000 (59%)
[epoch 23] loss: 0.4625753
Test set: Average loss: 1.0648, Accuracy: 2996/5000 (60%)
[epoch 24] loss: 0.4468715
Test set: Average loss: 1.0631, Accuracy: 2999/5000 (60%)
[epoch 25] loss: 0.4286104
Test set: Average loss: 1.0600, Accuracy: 2992/5000 (60%)
Validation:
Test set: Average loss: 1.0631, Accuracy: 2999/5000 (60%)
Test
Test set: Average loss: 1.0700, Accuracy: 2945/5000 (59%)
Test set: Average loss: 0.4267, Accuracy: 967/1000 (97%)
## seed: 12
Validation accuracy before training:
Test set: Average loss: 1.6513, Accuracy: 826/5000 (17%)
[epoch 1] loss: 1.4984943
Test set: Average loss: 1.3655, Accuracy: 2320/5000 (46%)
[epoch 2] loss: 1.2930256
Test set: Average loss: 1.2896, Accuracy: 2542/5000 (51%)
[epoch 3] loss: 1.1951944
Test set: Average loss: 1.2459, Accuracy: 2689/5000 (54%)
[epoch 4] loss: 1.1203790
Test set: Average loss: 1.2147, Accuracy: 2766/5000 (55%)
[epoch 5] loss: 1.0668025
Test set: Average loss: 1.1930, Accuracy: 2841/5000 (57%)
[epoch 6] loss: 1.0192349
Test set: Average loss: 1.1787, Accuracy: 2874/5000 (57%)
[epoch 7] loss: 0.9750263
Test set: Average loss: 1.1641, Accuracy: 2887/5000 (58%)
[epoch 8] loss: 0.9297217
Test set: Average loss: 1.1485, Accuracy: 2944/5000 (59%)
[epoch 9] loss: 0.8982256
Test set: Average loss: 1.1389, Accuracy: 2960/5000 (59%)
[epoch 10] loss: 0.8572334
Test set: Average loss: 1.1318, Accuracy: 2959/5000 (59%)
[epoch 11] loss: 0.8268198
Test set: Average loss: 1.1226, Accuracy: 2982/5000 (60%)
[epoch 12] loss: 0.7914959
Test set: Average loss: 1.1121, Accuracy: 3000/5000 (60%)
[epoch 13] loss: 0.7609095
Test set: Average loss: 1.1085, Accuracy: 2988/5000 (60%)
[epoch 14] loss: 0.7401185
Test set: Average loss: 1.1049, Accuracy: 2983/5000 (60%)
[epoch 15] loss: 0.7098956
Test set: Average loss: 1.0990, Accuracy: 3009/5000 (60%)
[epoch 16] loss: 0.6776433
Test set: Average loss: 1.0883, Accuracy: 3041/5000 (61%)
[epoch 17] loss: 0.6505445
Test set: Average loss: 1.0827, Accuracy: 3052/5000 (61%)
[epoch 18] loss: 0.6242452
Test set: Average loss: 1.0845, Accuracy: 3003/5000 (60%)
[epoch 19] loss: 0.6049822
Test set: Average loss: 1.0751, Accuracy: 3044/5000 (61%)
[epoch 20] loss: 0.5763536
Test set: Average loss: 1.0685, Accuracy: 3053/5000 (61%)
[epoch 21] loss: 0.5550659
Test set: Average loss: 1.0682, Accuracy: 3063/5000 (61%)
[epoch 22] loss: 0.5361566
Test set: Average loss: 1.0740, Accuracy: 3005/5000 (60%)
[epoch 23] loss: 0.5158721
Test set: Average loss: 1.0630, Accuracy: 3056/5000 (61%)
[epoch 24] loss: 0.4913780
Test set: Average loss: 1.0579, Accuracy: 3071/5000 (61%)
[epoch 25] loss: 0.4681512
Test set: Average loss: 1.0580, Accuracy: 3065/5000 (61%)
Validation:
Test set: Average loss: 1.0579, Accuracy: 3071/5000 (61%)
Test
Test set: Average loss: 1.0706, Accuracy: 2980/5000 (60%)
Test set: Average loss: 0.4693, Accuracy: 949/1000 (95%)
## seed: 13
Validation accuracy before training:
Test set: Average loss: 1.7316, Accuracy: 671/5000 (13%)
[epoch 1] loss: 1.5458174
Test set: Average loss: 1.4116, Accuracy: 1976/5000 (40%)
[epoch 2] loss: 1.3280019
Test set: Average loss: 1.3246, Accuracy: 2277/5000 (46%)
[epoch 3] loss: 1.2195287
Test set: Average loss: 1.2711, Accuracy: 2479/5000 (50%)
[epoch 4] loss: 1.1378666
Test set: Average loss: 1.2374, Accuracy: 2597/5000 (52%)
[epoch 5] loss: 1.0822905
Test set: Average loss: 1.2140, Accuracy: 2669/5000 (53%)
[epoch 6] loss: 1.0303820
Test set: Average loss: 1.1972, Accuracy: 2702/5000 (54%)
[epoch 7] loss: 0.9787935
Test set: Average loss: 1.1799, Accuracy: 2753/5000 (55%)
[epoch 8] loss: 0.9365104
Test set: Average loss: 1.1644, Accuracy: 2808/5000 (56%)
[epoch 9] loss: 0.9011663
Test set: Average loss: 1.1533, Accuracy: 2833/5000 (57%)
[epoch 10] loss: 0.8710053
Test set: Average loss: 1.1423, Accuracy: 2875/5000 (58%)
[epoch 11] loss: 0.8389527
Test set: Average loss: 1.1338, Accuracy: 2887/5000 (58%)
[epoch 12] loss: 0.7977988
Test set: Average loss: 1.1261, Accuracy: 2906/5000 (58%)
[epoch 13] loss: 0.7664215
Test set: Average loss: 1.1184, Accuracy: 2913/5000 (58%)
[epoch 14] loss: 0.7369355
Test set: Average loss: 1.1114, Accuracy: 2945/5000 (59%)
[epoch 15] loss: 0.7061860
Test set: Average loss: 1.1063, Accuracy: 2947/5000 (59%)
[epoch 16] loss: 0.6806075
Test set: Average loss: 1.1012, Accuracy: 2945/5000 (59%)
[epoch 17] loss: 0.6596236
Test set: Average loss: 1.0997, Accuracy: 2947/5000 (59%)
[epoch 18] loss: 0.6289397
Test set: Average loss: 1.0927, Accuracy: 2970/5000 (59%)
[epoch 19] loss: 0.5993145
Test set: Average loss: 1.0858, Accuracy: 2971/5000 (59%)
[epoch 20] loss: 0.5790523
Test set: Average loss: 1.0844, Accuracy: 2990/5000 (60%)
[epoch 21] loss: 0.5500300
Test set: Average loss: 1.0784, Accuracy: 2996/5000 (60%)
[epoch 22] loss: 0.5345940
Test set: Average loss: 1.0772, Accuracy: 2981/5000 (60%)
[epoch 23] loss: 0.5087555
Test set: Average loss: 1.0746, Accuracy: 2995/5000 (60%)
[epoch 24] loss: 0.4897961
Test set: Average loss: 1.0676, Accuracy: 3007/5000 (60%)
[epoch 25] loss: 0.4640788
Test set: Average loss: 1.0712, Accuracy: 2986/5000 (60%)
Validation:
Test set: Average loss: 1.0676, Accuracy: 3007/5000 (60%)
Test
Test set: Average loss: 1.0864, Accuracy: 2943/5000 (59%)
Test set: Average loss: 0.4667, Accuracy: 967/1000 (97%)
2500
## seed: 11
Validation accuracy before training:
Test set: Average loss: 1.6344, Accuracy: 1038/5000 (21%)
[epoch 1] loss: 1.3391425
Test set: Average loss: 1.2403, Accuracy: 2560/5000 (51%)
[epoch 2] loss: 1.1540035
Test set: Average loss: 1.1725, Accuracy: 2761/5000 (55%)
[epoch 3] loss: 1.0816582
Test set: Average loss: 1.1371, Accuracy: 2862/5000 (57%)
[epoch 4] loss: 1.0112270
Test set: Average loss: 1.1133, Accuracy: 2910/5000 (58%)
[epoch 5] loss: 0.9617412
Test set: Average loss: 1.0928, Accuracy: 2979/5000 (60%)
[epoch 6] loss: 0.9218282
Test set: Average loss: 1.0783, Accuracy: 2996/5000 (60%)
[epoch 7] loss: 0.8744211
Test set: Average loss: 1.0641, Accuracy: 3037/5000 (61%)
[epoch 8] loss: 0.8315954
Test set: Average loss: 1.0547, Accuracy: 3060/5000 (61%)
[epoch 9] loss: 0.8020920
Test set: Average loss: 1.0421, Accuracy: 3076/5000 (62%)
[epoch 10] loss: 0.7652747
Test set: Average loss: 1.0337, Accuracy: 3096/5000 (62%)
[epoch 11] loss: 0.7244189
Test set: Average loss: 1.0263, Accuracy: 3095/5000 (62%)
[epoch 12] loss: 0.6870436
Test set: Average loss: 1.0205, Accuracy: 3092/5000 (62%)
[epoch 13] loss: 0.6541605
Test set: Average loss: 1.0130, Accuracy: 3115/5000 (62%)
[epoch 14] loss: 0.6236343
Test set: Average loss: 1.0047, Accuracy: 3122/5000 (62%)
[epoch 15] loss: 0.5956667
Test set: Average loss: 0.9979, Accuracy: 3133/5000 (63%)
[epoch 16] loss: 0.5641685
Test set: Average loss: 0.9933, Accuracy: 3139/5000 (63%)
[epoch 17] loss: 0.5339142
Test set: Average loss: 0.9886, Accuracy: 3151/5000 (63%)
[epoch 18] loss: 0.4982318
Test set: Average loss: 0.9906, Accuracy: 3100/5000 (62%)
[epoch 19] loss: 0.4681043
Test set: Average loss: 0.9912, Accuracy: 3125/5000 (62%)
[epoch 20] loss: 0.4429110
Test set: Average loss: 0.9845, Accuracy: 3141/5000 (63%)
[epoch 21] loss: 0.4169146
Test set: Average loss: 0.9811, Accuracy: 3148/5000 (63%)
[epoch 22] loss: 0.3909216
Test set: Average loss: 0.9846, Accuracy: 3143/5000 (63%)
[epoch 23] loss: 0.3663350
Test set: Average loss: 0.9824, Accuracy: 3136/5000 (63%)
[epoch 24] loss: 0.3432993
Test set: Average loss: 0.9882, Accuracy: 3139/5000 (63%)
[epoch 25] loss: 0.3198708
Test set: Average loss: 0.9779, Accuracy: 3136/5000 (63%)
Validation:
Test set: Average loss: 0.9886, Accuracy: 3151/5000 (63%)
Test
Test set: Average loss: 0.9942, Accuracy: 3101/5000 (62%)
Test set: Average loss: 0.4963, Accuracy: 2295/2500 (92%)
## seed: 12
Validation accuracy before training:
Test set: Average loss: 1.6792, Accuracy: 1232/5000 (25%)
[epoch 1] loss: 1.4229774
Test set: Average loss: 1.3029, Accuracy: 2480/5000 (50%)
[epoch 2] loss: 1.2155031
Test set: Average loss: 1.2317, Accuracy: 2732/5000 (55%)
[epoch 3] loss: 1.1288645
Test set: Average loss: 1.1926, Accuracy: 2788/5000 (56%)
[epoch 4] loss: 1.0604551
Test set: Average loss: 1.1600, Accuracy: 2868/5000 (57%)
[epoch 5] loss: 1.0075861
Test set: Average loss: 1.1398, Accuracy: 2927/5000 (59%)
[epoch 6] loss: 0.9610921
Test set: Average loss: 1.1217, Accuracy: 2981/5000 (60%)
[epoch 7] loss: 0.9096095
Test set: Average loss: 1.1087, Accuracy: 2980/5000 (60%)
[epoch 8] loss: 0.8700920
Test set: Average loss: 1.0935, Accuracy: 3026/5000 (61%)
[epoch 9] loss: 0.8349924
Test set: Average loss: 1.0812, Accuracy: 3040/5000 (61%)
[epoch 10] loss: 0.7939661
Test set: Average loss: 1.0717, Accuracy: 3057/5000 (61%)
[epoch 11] loss: 0.7461410
Test set: Average loss: 1.0655, Accuracy: 3062/5000 (61%)
[epoch 12] loss: 0.7113475
Test set: Average loss: 1.0567, Accuracy: 3089/5000 (62%)
[epoch 13] loss: 0.6784075
Test set: Average loss: 1.0463, Accuracy: 3089/5000 (62%)
[epoch 14] loss: 0.6419813
Test set: Average loss: 1.0397, Accuracy: 3083/5000 (62%)
[epoch 15] loss: 0.6043380
Test set: Average loss: 1.0453, Accuracy: 3052/5000 (61%)
[epoch 16] loss: 0.5690327
Test set: Average loss: 1.0285, Accuracy: 3097/5000 (62%)
[epoch 17] loss: 0.5377789
Test set: Average loss: 1.0262, Accuracy: 3093/5000 (62%)
[epoch 18] loss: 0.5054431
Test set: Average loss: 1.0228, Accuracy: 3105/5000 (62%)
[epoch 19] loss: 0.4762798
Test set: Average loss: 1.0178, Accuracy: 3109/5000 (62%)
[epoch 20] loss: 0.4422536
Test set: Average loss: 1.0217, Accuracy: 3100/5000 (62%)
[epoch 21] loss: 0.4174422
Test set: Average loss: 1.0227, Accuracy: 3088/5000 (62%)
[epoch 22] loss: 0.3825364
Test set: Average loss: 1.0072, Accuracy: 3119/5000 (62%)
[epoch 23] loss: 0.3568840
Test set: Average loss: 1.0189, Accuracy: 3098/5000 (62%)
[epoch 24] loss: 0.3344410
Test set: Average loss: 1.0133, Accuracy: 3114/5000 (62%)
[epoch 25] loss: 0.3088880
Test set: Average loss: 1.0111, Accuracy: 3122/5000 (62%)
Validation:
Test set: Average loss: 1.0111, Accuracy: 3122/5000 (62%)
Test
Test set: Average loss: 1.0236, Accuracy: 3085/5000 (62%)
Test set: Average loss: 0.2836, Accuracy: 2439/2500 (98%)
## seed: 13
Validation accuracy before training:
Test set: Average loss: 1.6039, Accuracy: 1177/5000 (24%)
[epoch 1] loss: 1.3424214
Test set: Average loss: 1.2477, Accuracy: 2629/5000 (53%)
[epoch 2] loss: 1.1465214
Test set: Average loss: 1.1837, Accuracy: 2758/5000 (55%)
[epoch 3] loss: 1.0691743
Test set: Average loss: 1.1497, Accuracy: 2831/5000 (57%)
[epoch 4] loss: 1.0103156
Test set: Average loss: 1.1211, Accuracy: 2928/5000 (59%)
[epoch 5] loss: 0.9479010
Test set: Average loss: 1.1034, Accuracy: 2959/5000 (59%)
[epoch 6] loss: 0.9036522
Test set: Average loss: 1.0901, Accuracy: 2971/5000 (59%)
[epoch 7] loss: 0.8598511
Test set: Average loss: 1.0696, Accuracy: 3003/5000 (60%)
[epoch 8] loss: 0.8099446
Test set: Average loss: 1.0601, Accuracy: 3000/5000 (60%)
[epoch 9] loss: 0.7695103
Test set: Average loss: 1.0451, Accuracy: 3059/5000 (61%)
[epoch 10] loss: 0.7328710
Test set: Average loss: 1.0366, Accuracy: 3065/5000 (61%)
[epoch 11] loss: 0.6911559
Test set: Average loss: 1.0320, Accuracy: 3070/5000 (61%)
[epoch 12] loss: 0.6591206
Test set: Average loss: 1.0270, Accuracy: 3082/5000 (62%)
[epoch 13] loss: 0.6227810
Test set: Average loss: 1.0133, Accuracy: 3126/5000 (63%)
[epoch 14] loss: 0.5877448
Test set: Average loss: 1.0101, Accuracy: 3149/5000 (63%)
[epoch 15] loss: 0.5516487
Test set: Average loss: 1.0041, Accuracy: 3132/5000 (63%)
[epoch 16] loss: 0.5209500
Test set: Average loss: 1.0030, Accuracy: 3134/5000 (63%)
[epoch 17] loss: 0.4893558
Test set: Average loss: 0.9993, Accuracy: 3133/5000 (63%)
[epoch 18] loss: 0.4622648
Test set: Average loss: 0.9951, Accuracy: 3158/5000 (63%)
[epoch 19] loss: 0.4285534
Test set: Average loss: 0.9930, Accuracy: 3156/5000 (63%)
[epoch 20] loss: 0.4001921
Test set: Average loss: 0.9949, Accuracy: 3131/5000 (63%)
[epoch 21] loss: 0.3737986
Test set: Average loss: 0.9920, Accuracy: 3158/5000 (63%)
[epoch 22] loss: 0.3471831
Test set: Average loss: 0.9908, Accuracy: 3150/5000 (63%)
[epoch 23] loss: 0.3241584
Test set: Average loss: 0.9918, Accuracy: 3139/5000 (63%)
[epoch 24] loss: 0.3019823
Test set: Average loss: 0.9917, Accuracy: 3148/5000 (63%)
[epoch 25] loss: 0.2799385
Test set: Average loss: 0.9951, Accuracy: 3153/5000 (63%)
Validation:
Test set: Average loss: 0.9920, Accuracy: 3158/5000 (63%)
Test
Test set: Average loss: 1.0161, Accuracy: 3075/5000 (62%)
Test set: Average loss: 0.3433, Accuracy: 2406/2500 (96%)
5000
## seed: 11
Validation accuracy before training:
Test set: Average loss: 1.7485, Accuracy: 609/5000 (12%)
[epoch 1] loss: 1.3154016
Test set: Average loss: 1.1994, Accuracy: 2733/5000 (55%)
[epoch 2] loss: 1.1319441
Test set: Average loss: 1.1345, Accuracy: 2915/5000 (58%)
[epoch 3] loss: 1.0493020
Test set: Average loss: 1.0949, Accuracy: 3042/5000 (61%)
[epoch 4] loss: 0.9869459
Test set: Average loss: 1.0655, Accuracy: 3129/5000 (63%)
[epoch 5] loss: 0.9289400
Test set: Average loss: 1.0483, Accuracy: 3079/5000 (62%)
[epoch 6] loss: 0.8755848
Test set: Average loss: 1.0301, Accuracy: 3144/5000 (63%)
[epoch 7] loss: 0.8275894
Test set: Average loss: 1.0082, Accuracy: 3182/5000 (64%)
[epoch 8] loss: 0.7803669
Test set: Average loss: 0.9958, Accuracy: 3196/5000 (64%)
[epoch 9] loss: 0.7348568
Test set: Average loss: 0.9809, Accuracy: 3238/5000 (65%)
[epoch 10] loss: 0.6876398
Test set: Average loss: 0.9723, Accuracy: 3223/5000 (64%)
[epoch 11] loss: 0.6416131
Test set: Average loss: 0.9690, Accuracy: 3211/5000 (64%)
[epoch 12] loss: 0.5980249
Test set: Average loss: 0.9634, Accuracy: 3225/5000 (64%)
[epoch 13] loss: 0.5562221
Test set: Average loss: 0.9584, Accuracy: 3240/5000 (65%)
[epoch 14] loss: 0.5141347
Test set: Average loss: 0.9538, Accuracy: 3235/5000 (65%)
[epoch 15] loss: 0.4753566
Test set: Average loss: 0.9509, Accuracy: 3255/5000 (65%)
[epoch 16] loss: 0.4356099
Test set: Average loss: 0.9558, Accuracy: 3238/5000 (65%)
[epoch 17] loss: 0.3978878
Test set: Average loss: 0.9466, Accuracy: 3238/5000 (65%)
[epoch 18] loss: 0.3614628
Test set: Average loss: 0.9506, Accuracy: 3239/5000 (65%)
[epoch 19] loss: 0.3279545
Test set: Average loss: 0.9534, Accuracy: 3227/5000 (65%)
[epoch 20] loss: 0.2948364
Test set: Average loss: 0.9539, Accuracy: 3262/5000 (65%)
[epoch 21] loss: 0.2651767
Test set: Average loss: 0.9637, Accuracy: 3230/5000 (65%)
[epoch 22] loss: 0.2388923
Test set: Average loss: 0.9692, Accuracy: 3249/5000 (65%)
[epoch 23] loss: 0.2129519
Test set: Average loss: 0.9709, Accuracy: 3239/5000 (65%)
[epoch 24] loss: 0.1908197
Test set: Average loss: 0.9740, Accuracy: 3232/5000 (65%)
[epoch 25] loss: 0.1709402
Test set: Average loss: 0.9898, Accuracy: 3236/5000 (65%)
Validation:
Test set: Average loss: 0.9539, Accuracy: 3262/5000 (65%)
Test
Test set: Average loss: 0.9608, Accuracy: 3196/5000 (64%)
Test set: Average loss: 0.2601, Accuracy: 4849/5000 (97%)
## seed: 12
Validation accuracy before training:
Test set: Average loss: 1.8234, Accuracy: 590/5000 (12%)
[epoch 1] loss: 1.3611275
Test set: Average loss: 1.2237, Accuracy: 2629/5000 (53%)
[epoch 2] loss: 1.1557148
Test set: Average loss: 1.1525, Accuracy: 2846/5000 (57%)
[epoch 3] loss: 1.0696451
Test set: Average loss: 1.1058, Accuracy: 2959/5000 (59%)
[epoch 4] loss: 1.0067893
Test set: Average loss: 1.0774, Accuracy: 3009/5000 (60%)
[epoch 5] loss: 0.9465144
Test set: Average loss: 1.0557, Accuracy: 3085/5000 (62%)
[epoch 6] loss: 0.8971440
Test set: Average loss: 1.0342, Accuracy: 3097/5000 (62%)
[epoch 7] loss: 0.8486632
Test set: Average loss: 1.0218, Accuracy: 3124/5000 (62%)
[epoch 8] loss: 0.8010325
Test set: Average loss: 1.0099, Accuracy: 3152/5000 (63%)
[epoch 9] loss: 0.7586182
Test set: Average loss: 0.9990, Accuracy: 3135/5000 (63%)
[epoch 10] loss: 0.7154300
Test set: Average loss: 0.9921, Accuracy: 3168/5000 (63%)
[epoch 11] loss: 0.6700399
Test set: Average loss: 0.9787, Accuracy: 3181/5000 (64%)
[epoch 12] loss: 0.6273944
Test set: Average loss: 0.9721, Accuracy: 3203/5000 (64%)
[epoch 13] loss: 0.5848534
Test set: Average loss: 0.9737, Accuracy: 3190/5000 (64%)
[epoch 14] loss: 0.5443976
Test set: Average loss: 0.9591, Accuracy: 3213/5000 (64%)
[epoch 15] loss: 0.5020048
Test set: Average loss: 0.9605, Accuracy: 3206/5000 (64%)
[epoch 16] loss: 0.4607222
Test set: Average loss: 0.9542, Accuracy: 3214/5000 (64%)
[epoch 17] loss: 0.4236275
Test set: Average loss: 0.9581, Accuracy: 3211/5000 (64%)
[epoch 18] loss: 0.3881845
Test set: Average loss: 0.9563, Accuracy: 3241/5000 (65%)
[epoch 19] loss: 0.3525159
Test set: Average loss: 0.9598, Accuracy: 3227/5000 (65%)
[epoch 20] loss: 0.3170186
Test set: Average loss: 0.9585, Accuracy: 3251/5000 (65%)
[epoch 21] loss: 0.2862519
Test set: Average loss: 0.9574, Accuracy: 3258/5000 (65%)
[epoch 22] loss: 0.2584850
Test set: Average loss: 0.9625, Accuracy: 3231/5000 (65%)
[epoch 23] loss: 0.2322143
Test set: Average loss: 0.9686, Accuracy: 3231/5000 (65%)
[epoch 24] loss: 0.2086419
Test set: Average loss: 0.9642, Accuracy: 3242/5000 (65%)
[epoch 25] loss: 0.1858482
Test set: Average loss: 0.9738, Accuracy: 3257/5000 (65%)
Validation:
Test set: Average loss: 0.9574, Accuracy: 3258/5000 (65%)
Test
Test set: Average loss: 0.9699, Accuracy: 3169/5000 (63%)
Test set: Average loss: 0.2544, Accuracy: 4863/5000 (97%)
## seed: 13
Validation accuracy before training:
Test set: Average loss: 1.7910, Accuracy: 587/5000 (12%)
[epoch 1] loss: 1.3382482
Test set: Average loss: 1.2185, Accuracy: 2629/5000 (53%)
[epoch 2] loss: 1.1427510
Test set: Average loss: 1.1484, Accuracy: 2854/5000 (57%)
[epoch 3] loss: 1.0527312
Test set: Average loss: 1.1031, Accuracy: 2969/5000 (59%)
[epoch 4] loss: 0.9873350
Test set: Average loss: 1.0757, Accuracy: 3030/5000 (61%)
[epoch 5] loss: 0.9298361
Test set: Average loss: 1.0549, Accuracy: 3061/5000 (61%)
[epoch 6] loss: 0.8805713
Test set: Average loss: 1.0339, Accuracy: 3112/5000 (62%)
[epoch 7] loss: 0.8297105
Test set: Average loss: 1.0169, Accuracy: 3190/5000 (64%)
[epoch 8] loss: 0.7835177
Test set: Average loss: 1.0104, Accuracy: 3163/5000 (63%)
[epoch 9] loss: 0.7377406
Test set: Average loss: 0.9918, Accuracy: 3213/5000 (64%)
[epoch 10] loss: 0.6947112
Test set: Average loss: 0.9794, Accuracy: 3224/5000 (64%)
[epoch 11] loss: 0.6506791
Test set: Average loss: 0.9805, Accuracy: 3223/5000 (64%)
[epoch 12] loss: 0.6091874
Test set: Average loss: 0.9651, Accuracy: 3236/5000 (65%)
[epoch 13] loss: 0.5688670
Test set: Average loss: 0.9620, Accuracy: 3235/5000 (65%)
[epoch 14] loss: 0.5250755
Test set: Average loss: 0.9574, Accuracy: 3234/5000 (65%)
[epoch 15] loss: 0.4852011
Test set: Average loss: 0.9542, Accuracy: 3255/5000 (65%)
[epoch 16] loss: 0.4469604
Test set: Average loss: 0.9643, Accuracy: 3226/5000 (65%)
[epoch 17] loss: 0.4106850
Test set: Average loss: 0.9468, Accuracy: 3259/5000 (65%)
[epoch 18] loss: 0.3744530
Test set: Average loss: 0.9466, Accuracy: 3257/5000 (65%)
[epoch 19] loss: 0.3399906
Test set: Average loss: 0.9490, Accuracy: 3272/5000 (65%)
[epoch 20] loss: 0.3078141
Test set: Average loss: 0.9574, Accuracy: 3257/5000 (65%)
[epoch 21] loss: 0.2765090
Test set: Average loss: 0.9610, Accuracy: 3223/5000 (64%)
[epoch 22] loss: 0.2484066
Test set: Average loss: 0.9569, Accuracy: 3240/5000 (65%)
[epoch 23] loss: 0.2233962
Test set: Average loss: 0.9712, Accuracy: 3245/5000 (65%)
[epoch 24] loss: 0.2007595
Test set: Average loss: 0.9677, Accuracy: 3235/5000 (65%)
[epoch 25] loss: 0.1773734
Test set: Average loss: 0.9712, Accuracy: 3241/5000 (65%)
Validation:
Test set: Average loss: 0.9490, Accuracy: 3272/5000 (65%)
Test
Test set: Average loss: 0.9588, Accuracy: 3201/5000 (64%)
Test set: Average loss: 0.3011, Accuracy: 4802/5000 (96%)
10000
## seed: 11
Validation accuracy before training:
Test set: Average loss: 1.5382, Accuracy: 1389/5000 (28%)
[epoch 1] loss: 1.1854687
Test set: Average loss: 1.0963, Accuracy: 2978/5000 (60%)
[epoch 2] loss: 1.0242147
Test set: Average loss: 1.0307, Accuracy: 3123/5000 (62%)
[epoch 3] loss: 0.9380144
Test set: Average loss: 0.9905, Accuracy: 3232/5000 (65%)
[epoch 4] loss: 0.8697397
Test set: Average loss: 0.9629, Accuracy: 3271/5000 (65%)
[epoch 5] loss: 0.8065336
Test set: Average loss: 0.9392, Accuracy: 3263/5000 (65%)
[epoch 6] loss: 0.7483621
Test set: Average loss: 0.9244, Accuracy: 3295/5000 (66%)
[epoch 7] loss: 0.6947075
Test set: Average loss: 0.9119, Accuracy: 3336/5000 (67%)
[epoch 8] loss: 0.6413503
Test set: Average loss: 0.9046, Accuracy: 3307/5000 (66%)
[epoch 9] loss: 0.5892569
Test set: Average loss: 0.8974, Accuracy: 3317/5000 (66%)
[epoch 10] loss: 0.5399432
Test set: Average loss: 0.8972, Accuracy: 3337/5000 (67%)
[epoch 11] loss: 0.4933802
Test set: Average loss: 0.9009, Accuracy: 3311/5000 (66%)
[epoch 12] loss: 0.4454606
Test set: Average loss: 0.8952, Accuracy: 3351/5000 (67%)
[epoch 13] loss: 0.4037663
Test set: Average loss: 0.8985, Accuracy: 3354/5000 (67%)
[epoch 14] loss: 0.3604579
Test set: Average loss: 0.9038, Accuracy: 3338/5000 (67%)
[epoch 15] loss: 0.3215693
Test set: Average loss: 0.9124, Accuracy: 3337/5000 (67%)
[epoch 16] loss: 0.2854111
Test set: Average loss: 0.9271, Accuracy: 3327/5000 (67%)
[epoch 17] loss: 0.2488972
Test set: Average loss: 0.9275, Accuracy: 3342/5000 (67%)
[epoch 18] loss: 0.2154729
Test set: Average loss: 0.9381, Accuracy: 3351/5000 (67%)
[epoch 19] loss: 0.1858885
Test set: Average loss: 0.9483, Accuracy: 3339/5000 (67%)
[epoch 20] loss: 0.1615189
Test set: Average loss: 0.9649, Accuracy: 3311/5000 (66%)
[epoch 21] loss: 0.1379221
Test set: Average loss: 0.9737, Accuracy: 3338/5000 (67%)
[epoch 22] loss: 0.1167051
Test set: Average loss: 0.9897, Accuracy: 3337/5000 (67%)
[epoch 23] loss: 0.0992108
Test set: Average loss: 0.9970, Accuracy: 3332/5000 (67%)
[epoch 24] loss: 0.0833981
Test set: Average loss: 1.0218, Accuracy: 3303/5000 (66%)
[epoch 25] loss: 0.0694087
Test set: Average loss: 1.0309, Accuracy: 3317/5000 (66%)
Validation:
Test set: Average loss: 0.8985, Accuracy: 3354/5000 (67%)
Test
Test set: Average loss: 0.9074, Accuracy: 3309/5000 (66%)
Test set: Average loss: 0.3505, Accuracy: 9242/10000 (92%)
## seed: 12
Validation accuracy before training:
Test set: Average loss: 1.6384, Accuracy: 1297/5000 (26%)
[epoch 1] loss: 1.2558967
Test set: Average loss: 1.1345, Accuracy: 3004/5000 (60%)
[epoch 2] loss: 1.0714161
Test set: Average loss: 1.0629, Accuracy: 3155/5000 (63%)
[epoch 3] loss: 0.9828069
Test set: Average loss: 1.0231, Accuracy: 3189/5000 (64%)
[epoch 4] loss: 0.9127884
Test set: Average loss: 0.9848, Accuracy: 3259/5000 (65%)
[epoch 5] loss: 0.8503672
Test set: Average loss: 0.9637, Accuracy: 3274/5000 (65%)
[epoch 6] loss: 0.7903257
Test set: Average loss: 0.9417, Accuracy: 3317/5000 (66%)
[epoch 7] loss: 0.7359536
Test set: Average loss: 0.9284, Accuracy: 3318/5000 (66%)
[epoch 8] loss: 0.6818112
Test set: Average loss: 0.9152, Accuracy: 3309/5000 (66%)
[epoch 9] loss: 0.6283603
Test set: Average loss: 0.9080, Accuracy: 3334/5000 (67%)
[epoch 10] loss: 0.5743754
Test set: Average loss: 0.9015, Accuracy: 3336/5000 (67%)
[epoch 11] loss: 0.5255425
Test set: Average loss: 0.8991, Accuracy: 3342/5000 (67%)
[epoch 12] loss: 0.4749083
Test set: Average loss: 0.8864, Accuracy: 3374/5000 (67%)
[epoch 13] loss: 0.4277449
Test set: Average loss: 0.8914, Accuracy: 3364/5000 (67%)
[epoch 14] loss: 0.3826605
Test set: Average loss: 0.8986, Accuracy: 3348/5000 (67%)
[epoch 15] loss: 0.3404780
Test set: Average loss: 0.8943, Accuracy: 3376/5000 (68%)
[epoch 16] loss: 0.2993240
Test set: Average loss: 0.9067, Accuracy: 3375/5000 (68%)
[epoch 17] loss: 0.2644555
Test set: Average loss: 0.9219, Accuracy: 3354/5000 (67%)
[epoch 18] loss: 0.2277529
Test set: Average loss: 0.9217, Accuracy: 3343/5000 (67%)
[epoch 19] loss: 0.1965802
Test set: Average loss: 0.9289, Accuracy: 3357/5000 (67%)
[epoch 20] loss: 0.1684354
Test set: Average loss: 0.9390, Accuracy: 3333/5000 (67%)
[epoch 21] loss: 0.1435740
Test set: Average loss: 0.9607, Accuracy: 3338/5000 (67%)
[epoch 22] loss: 0.1229842
Test set: Average loss: 0.9741, Accuracy: 3331/5000 (67%)
[epoch 23] loss: 0.1057624
Test set: Average loss: 0.9848, Accuracy: 3302/5000 (66%)
[epoch 24] loss: 0.0873459
Test set: Average loss: 1.0034, Accuracy: 3327/5000 (67%)
[epoch 25] loss: 0.0755239
Test set: Average loss: 1.0060, Accuracy: 3344/5000 (67%)
Validation:
Test set: Average loss: 0.8943, Accuracy: 3376/5000 (68%)
Test
Test set: Average loss: 0.8952, Accuracy: 3357/5000 (67%)
Test set: Average loss: 0.2878, Accuracy: 9545/10000 (95%)
## seed: 13
Validation accuracy before training:
Test set: Average loss: 1.5871, Accuracy: 1308/5000 (26%)
[epoch 1] loss: 1.2062178
Test set: Average loss: 1.1046, Accuracy: 2984/5000 (60%)
[epoch 2] loss: 1.0362636
Test set: Average loss: 1.0374, Accuracy: 3122/5000 (62%)
[epoch 3] loss: 0.9525565
Test set: Average loss: 0.9919, Accuracy: 3209/5000 (64%)
[epoch 4] loss: 0.8846815
Test set: Average loss: 0.9697, Accuracy: 3235/5000 (65%)
[epoch 5] loss: 0.8230084
Test set: Average loss: 0.9392, Accuracy: 3297/5000 (66%)
[epoch 6] loss: 0.7658404
Test set: Average loss: 0.9313, Accuracy: 3270/5000 (65%)
[epoch 7] loss: 0.7119436
Test set: Average loss: 0.9134, Accuracy: 3297/5000 (66%)
[epoch 8] loss: 0.6576687
Test set: Average loss: 0.8991, Accuracy: 3330/5000 (67%)
[epoch 9] loss: 0.6073518
Test set: Average loss: 0.8944, Accuracy: 3343/5000 (67%)
[epoch 10] loss: 0.5566745
Test set: Average loss: 0.8837, Accuracy: 3372/5000 (67%)
[epoch 11] loss: 0.5095062
Test set: Average loss: 0.8854, Accuracy: 3351/5000 (67%)
[epoch 12] loss: 0.4598307
Test set: Average loss: 0.8801, Accuracy: 3377/5000 (68%)
[epoch 13] loss: 0.4141717
Test set: Average loss: 0.8893, Accuracy: 3363/5000 (67%)
[epoch 14] loss: 0.3714338
Test set: Average loss: 0.8851, Accuracy: 3365/5000 (67%)
[epoch 15] loss: 0.3306851
Test set: Average loss: 0.8878, Accuracy: 3374/5000 (67%)
[epoch 16] loss: 0.2893135
Test set: Average loss: 0.8980, Accuracy: 3368/5000 (67%)
[epoch 17] loss: 0.2545720
Test set: Average loss: 0.9110, Accuracy: 3371/5000 (67%)
[epoch 18] loss: 0.2204093
Test set: Average loss: 0.9103, Accuracy: 3355/5000 (67%)
[epoch 19] loss: 0.1909182
Test set: Average loss: 0.9250, Accuracy: 3367/5000 (67%)
[epoch 20] loss: 0.1631937
Test set: Average loss: 0.9556, Accuracy: 3324/5000 (66%)
[epoch 21] loss: 0.1381219
Test set: Average loss: 0.9488, Accuracy: 3342/5000 (67%)
[epoch 22] loss: 0.1162373
Test set: Average loss: 0.9679, Accuracy: 3336/5000 (67%)
[epoch 23] loss: 0.0983970
Test set: Average loss: 0.9755, Accuracy: 3359/5000 (67%)
[epoch 24] loss: 0.0829165
Test set: Average loss: 1.0023, Accuracy: 3340/5000 (67%)
[epoch 25] loss: 0.0700373
Test set: Average loss: 1.0052, Accuracy: 3342/5000 (67%)
Validation:
Test set: Average loss: 0.8801, Accuracy: 3377/5000 (68%)
Test
Test set: Average loss: 0.9021, Accuracy: 3298/5000 (66%)
Test set: Average loss: 0.4080, Accuracy: 9101/10000 (91%)
15000
## seed: 11
Validation accuracy before training:
Test set: Average loss: 1.6520, Accuracy: 952/5000 (19%)
[epoch 1] loss: 1.1618984
Test set: Average loss: 1.0586, Accuracy: 3042/5000 (61%)
[epoch 2] loss: 0.9914045
Test set: Average loss: 0.9886, Accuracy: 3190/5000 (64%)
[epoch 3] loss: 0.9050346
Test set: Average loss: 0.9509, Accuracy: 3261/5000 (65%)
[epoch 4] loss: 0.8350939
Test set: Average loss: 0.9255, Accuracy: 3271/5000 (65%)
[epoch 5] loss: 0.7725190
Test set: Average loss: 0.8957, Accuracy: 3351/5000 (67%)
[epoch 6] loss: 0.7141201
Test set: Average loss: 0.8793, Accuracy: 3388/5000 (68%)
[epoch 7] loss: 0.6600968
Test set: Average loss: 0.8694, Accuracy: 3418/5000 (68%)
[epoch 8] loss: 0.6053044
Test set: Average loss: 0.8589, Accuracy: 3423/5000 (68%)
[epoch 9] loss: 0.5498860
Test set: Average loss: 0.8649, Accuracy: 3414/5000 (68%)
[epoch 10] loss: 0.5000542
Test set: Average loss: 0.8629, Accuracy: 3444/5000 (69%)
[epoch 11] loss: 0.4504637
Test set: Average loss: 0.8602, Accuracy: 3429/5000 (69%)
[epoch 12] loss: 0.4034286
Test set: Average loss: 0.8667, Accuracy: 3445/5000 (69%)
[epoch 13] loss: 0.3580824
Test set: Average loss: 0.8764, Accuracy: 3429/5000 (69%)
[epoch 14] loss: 0.3157787
Test set: Average loss: 0.8944, Accuracy: 3428/5000 (69%)
[epoch 15] loss: 0.2762457
Test set: Average loss: 0.8894, Accuracy: 3438/5000 (69%)
[epoch 16] loss: 0.2406992
Test set: Average loss: 0.9171, Accuracy: 3404/5000 (68%)
[epoch 17] loss: 0.2081669
Test set: Average loss: 0.9228, Accuracy: 3402/5000 (68%)
[epoch 18] loss: 0.1777849
Test set: Average loss: 0.9576, Accuracy: 3357/5000 (67%)
[epoch 19] loss: 0.1505312
Test set: Average loss: 0.9616, Accuracy: 3412/5000 (68%)
[epoch 20] loss: 0.1290296
Test set: Average loss: 0.9916, Accuracy: 3378/5000 (68%)
[epoch 21] loss: 0.1074976
Test set: Average loss: 1.0098, Accuracy: 3366/5000 (67%)
[epoch 22] loss: 0.0885344
Test set: Average loss: 1.0323, Accuracy: 3374/5000 (67%)
[epoch 23] loss: 0.0715729
Test set: Average loss: 1.0431, Accuracy: 3373/5000 (67%)
[epoch 24] loss: 0.0621901
Test set: Average loss: 1.0815, Accuracy: 3351/5000 (67%)
[epoch 25] loss: 0.0504402
Test set: Average loss: 1.1046, Accuracy: 3359/5000 (67%)
Validation:
Test set: Average loss: 0.8667, Accuracy: 3445/5000 (69%)
Test
Test set: Average loss: 0.8755, Accuracy: 3386/5000 (68%)
Test set: Average loss: 0.3492, Accuracy: 13892/15000 (93%)
## seed: 12
Validation accuracy before training:
Test set: Average loss: 1.7234, Accuracy: 1069/5000 (21%)
[epoch 1] loss: 1.1819518
Test set: Average loss: 1.0660, Accuracy: 3065/5000 (61%)
[epoch 2] loss: 1.0083363
Test set: Average loss: 0.9993, Accuracy: 3173/5000 (63%)
[epoch 3] loss: 0.9228240
Test set: Average loss: 0.9550, Accuracy: 3256/5000 (65%)
[epoch 4] loss: 0.8539542
Test set: Average loss: 0.9242, Accuracy: 3305/5000 (66%)
[epoch 5] loss: 0.7911439
Test set: Average loss: 0.8998, Accuracy: 3346/5000 (67%)
[epoch 6] loss: 0.7335148
Test set: Average loss: 0.8812, Accuracy: 3363/5000 (67%)
[epoch 7] loss: 0.6793267
Test set: Average loss: 0.8623, Accuracy: 3400/5000 (68%)
[epoch 8] loss: 0.6234884
Test set: Average loss: 0.8718, Accuracy: 3383/5000 (68%)
[epoch 9] loss: 0.5710860
Test set: Average loss: 0.8442, Accuracy: 3428/5000 (69%)
[epoch 10] loss: 0.5204472
Test set: Average loss: 0.8399, Accuracy: 3473/5000 (69%)
[epoch 11] loss: 0.4700581
Test set: Average loss: 0.8431, Accuracy: 3453/5000 (69%)
[epoch 12] loss: 0.4188071
Test set: Average loss: 0.8468, Accuracy: 3461/5000 (69%)
[epoch 13] loss: 0.3754907
Test set: Average loss: 0.8469, Accuracy: 3454/5000 (69%)
[epoch 14] loss: 0.3282696
Test set: Average loss: 0.8600, Accuracy: 3435/5000 (69%)
[epoch 15] loss: 0.2890311
Test set: Average loss: 0.8574, Accuracy: 3458/5000 (69%)
[epoch 16] loss: 0.2476514
Test set: Average loss: 0.8740, Accuracy: 3443/5000 (69%)
[epoch 17] loss: 0.2130073
Test set: Average loss: 0.8752, Accuracy: 3455/5000 (69%)
[epoch 18] loss: 0.1819640
Test set: Average loss: 0.9182, Accuracy: 3366/5000 (67%)
[epoch 19] loss: 0.1511571
Test set: Average loss: 0.9185, Accuracy: 3451/5000 (69%)
[epoch 20] loss: 0.1275588
Test set: Average loss: 0.9283, Accuracy: 3458/5000 (69%)
[epoch 21] loss: 0.1042658
Test set: Average loss: 0.9607, Accuracy: 3416/5000 (68%)
[epoch 22] loss: 0.0871723
Test set: Average loss: 0.9760, Accuracy: 3389/5000 (68%)
[epoch 23] loss: 0.0710538
Test set: Average loss: 1.0038, Accuracy: 3377/5000 (68%)
[epoch 24] loss: 0.0606998
Test set: Average loss: 1.0236, Accuracy: 3395/5000 (68%)
[epoch 25] loss: 0.0496096
Test set: Average loss: 1.0259, Accuracy: 3418/5000 (68%)
Validation:
Test set: Average loss: 0.8399, Accuracy: 3473/5000 (69%)
Test
Test set: Average loss: 0.8672, Accuracy: 3385/5000 (68%)
Test set: Average loss: 0.4584, Accuracy: 13205/15000 (88%)
## seed: 13
Validation accuracy before training:
Test set: Average loss: 1.7189, Accuracy: 597/5000 (12%)
[epoch 1] loss: 1.2204063
Test set: Average loss: 1.0959, Accuracy: 3042/5000 (61%)
[epoch 2] loss: 1.0309473
Test set: Average loss: 1.0160, Accuracy: 3176/5000 (64%)
[epoch 3] loss: 0.9438880
Test set: Average loss: 0.9804, Accuracy: 3225/5000 (64%)
[epoch 4] loss: 0.8773610
Test set: Average loss: 0.9401, Accuracy: 3288/5000 (66%)
[epoch 5] loss: 0.8175004
Test set: Average loss: 0.9179, Accuracy: 3330/5000 (67%)
[epoch 6] loss: 0.7606526
Test set: Average loss: 0.8912, Accuracy: 3355/5000 (67%)
[epoch 7] loss: 0.7070667
Test set: Average loss: 0.8753, Accuracy: 3417/5000 (68%)
[epoch 8] loss: 0.6529615
Test set: Average loss: 0.8754, Accuracy: 3393/5000 (68%)
[epoch 9] loss: 0.6000082
Test set: Average loss: 0.8589, Accuracy: 3424/5000 (68%)
[epoch 10] loss: 0.5507624
Test set: Average loss: 0.8467, Accuracy: 3450/5000 (69%)
[epoch 11] loss: 0.4993325
Test set: Average loss: 0.8406, Accuracy: 3471/5000 (69%)
[epoch 12] loss: 0.4510760
Test set: Average loss: 0.8460, Accuracy: 3434/5000 (69%)
[epoch 13] loss: 0.4044602
Test set: Average loss: 0.8484, Accuracy: 3445/5000 (69%)
[epoch 14] loss: 0.3594766
Test set: Average loss: 0.8467, Accuracy: 3464/5000 (69%)
[epoch 15] loss: 0.3158961
Test set: Average loss: 0.8636, Accuracy: 3431/5000 (69%)
[epoch 16] loss: 0.2761591
Test set: Average loss: 0.8671, Accuracy: 3445/5000 (69%)
[epoch 17] loss: 0.2392063
Test set: Average loss: 0.8761, Accuracy: 3444/5000 (69%)
[epoch 18] loss: 0.2039168
Test set: Average loss: 0.8894, Accuracy: 3421/5000 (68%)
[epoch 19] loss: 0.1729708
Test set: Average loss: 0.9168, Accuracy: 3393/5000 (68%)
[epoch 20] loss: 0.1479479
Test set: Average loss: 0.9297, Accuracy: 3424/5000 (68%)
[epoch 21] loss: 0.1209133
Test set: Average loss: 0.9518, Accuracy: 3413/5000 (68%)
[epoch 22] loss: 0.1032661
Test set: Average loss: 0.9720, Accuracy: 3411/5000 (68%)
[epoch 23] loss: 0.0852809
Test set: Average loss: 0.9811, Accuracy: 3408/5000 (68%)
[epoch 24] loss: 0.0715477
Test set: Average loss: 0.9985, Accuracy: 3397/5000 (68%)
[epoch 25] loss: 0.0558098
Test set: Average loss: 1.0213, Accuracy: 3400/5000 (68%)
Validation:
Test set: Average loss: 0.8406, Accuracy: 3471/5000 (69%)
Test
Test set: Average loss: 0.8692, Accuracy: 3378/5000 (68%)
Test set: Average loss: 0.4402, Accuracy: 13217/15000 (88%)
20000
## seed: 11
Validation accuracy before training:
Test set: Average loss: 1.6352, Accuracy: 1069/5000 (21%)
[epoch 1] loss: 1.1421911
Test set: Average loss: 1.0384, Accuracy: 3140/5000 (63%)
[epoch 2] loss: 0.9727951
Test set: Average loss: 0.9722, Accuracy: 3257/5000 (65%)
[epoch 3] loss: 0.8836654
Test set: Average loss: 0.9269, Accuracy: 3329/5000 (67%)
[epoch 4] loss: 0.8123102
Test set: Average loss: 0.8891, Accuracy: 3381/5000 (68%)
[epoch 5] loss: 0.7468022
Test set: Average loss: 0.8692, Accuracy: 3407/5000 (68%)
[epoch 6] loss: 0.6873629
Test set: Average loss: 0.8645, Accuracy: 3443/5000 (69%)
[epoch 7] loss: 0.6305916
Test set: Average loss: 0.8412, Accuracy: 3475/5000 (70%)
[epoch 8] loss: 0.5744018
Test set: Average loss: 0.8318, Accuracy: 3457/5000 (69%)
[epoch 9] loss: 0.5190505
Test set: Average loss: 0.8276, Accuracy: 3494/5000 (70%)
[epoch 10] loss: 0.4663830
Test set: Average loss: 0.8351, Accuracy: 3491/5000 (70%)
[epoch 11] loss: 0.4186315
Test set: Average loss: 0.8440, Accuracy: 3480/5000 (70%)
[epoch 12] loss: 0.3702619
Test set: Average loss: 0.8544, Accuracy: 3478/5000 (70%)
[epoch 13] loss: 0.3248855
Test set: Average loss: 0.8589, Accuracy: 3488/5000 (70%)
[epoch 14] loss: 0.2818129
Test set: Average loss: 0.8720, Accuracy: 3510/5000 (70%)
[epoch 15] loss: 0.2444683
Test set: Average loss: 0.9057, Accuracy: 3443/5000 (69%)
[epoch 16] loss: 0.2079359
Test set: Average loss: 0.9264, Accuracy: 3465/5000 (69%)
[epoch 17] loss: 0.1757744
Test set: Average loss: 0.9490, Accuracy: 3439/5000 (69%)
[epoch 18] loss: 0.1494193
Test set: Average loss: 0.9541, Accuracy: 3448/5000 (69%)
[epoch 19] loss: 0.1257037
Test set: Average loss: 1.0023, Accuracy: 3451/5000 (69%)
[epoch 20] loss: 0.1034698
Test set: Average loss: 1.0087, Accuracy: 3431/5000 (69%)
[epoch 21] loss: 0.0863618
Test set: Average loss: 1.0336, Accuracy: 3421/5000 (68%)
[epoch 22] loss: 0.0719428
Test set: Average loss: 1.0477, Accuracy: 3402/5000 (68%)
[epoch 23] loss: 0.0592596
Test set: Average loss: 1.0804, Accuracy: 3427/5000 (69%)
[epoch 24] loss: 0.0472618
Test set: Average loss: 1.1310, Accuracy: 3417/5000 (68%)
[epoch 25] loss: 0.0374707
Test set: Average loss: 1.1616, Accuracy: 3387/5000 (68%)
Validation:
Test set: Average loss: 0.8720, Accuracy: 3510/5000 (70%)
Test
Test set: Average loss: 0.8943, Accuracy: 3418/5000 (68%)
Test set: Average loss: 0.2311, Accuracy: 19104/20000 (96%)
## seed: 12
Validation accuracy before training:
Test set: Average loss: 1.6462, Accuracy: 783/5000 (16%)
[epoch 1] loss: 1.1498916
Test set: Average loss: 1.0445, Accuracy: 3139/5000 (63%)
[epoch 2] loss: 0.9786361
Test set: Average loss: 0.9655, Accuracy: 3268/5000 (65%)
[epoch 3] loss: 0.8886371
Test set: Average loss: 0.9198, Accuracy: 3336/5000 (67%)
[epoch 4] loss: 0.8169149
Test set: Average loss: 0.8897, Accuracy: 3383/5000 (68%)
[epoch 5] loss: 0.7524051
Test set: Average loss: 0.8755, Accuracy: 3390/5000 (68%)
[epoch 6] loss: 0.6923167
Test set: Average loss: 0.8616, Accuracy: 3418/5000 (68%)
[epoch 7] loss: 0.6355295
Test set: Average loss: 0.8426, Accuracy: 3460/5000 (69%)
[epoch 8] loss: 0.5814904
Test set: Average loss: 0.8420, Accuracy: 3456/5000 (69%)
[epoch 9] loss: 0.5266968
Test set: Average loss: 0.8537, Accuracy: 3434/5000 (69%)
[epoch 10] loss: 0.4736179
Test set: Average loss: 0.8468, Accuracy: 3465/5000 (69%)
[epoch 11] loss: 0.4233473
Test set: Average loss: 0.8408, Accuracy: 3497/5000 (70%)
[epoch 12] loss: 0.3752608
Test set: Average loss: 0.8494, Accuracy: 3514/5000 (70%)
[epoch 13] loss: 0.3272209
Test set: Average loss: 0.8629, Accuracy: 3461/5000 (69%)
[epoch 14] loss: 0.2858695
Test set: Average loss: 0.8803, Accuracy: 3453/5000 (69%)
[epoch 15] loss: 0.2491275
Test set: Average loss: 0.8956, Accuracy: 3460/5000 (69%)
[epoch 16] loss: 0.2112212
Test set: Average loss: 0.9197, Accuracy: 3419/5000 (68%)
[epoch 17] loss: 0.1776427
Test set: Average loss: 0.9376, Accuracy: 3439/5000 (69%)
[epoch 18] loss: 0.1506243
Test set: Average loss: 0.9542, Accuracy: 3461/5000 (69%)
[epoch 19] loss: 0.1253079
Test set: Average loss: 0.9865, Accuracy: 3428/5000 (69%)
[epoch 20] loss: 0.1053422
Test set: Average loss: 1.0118, Accuracy: 3432/5000 (69%)
[epoch 21] loss: 0.0879590
Test set: Average loss: 1.0346, Accuracy: 3439/5000 (69%)
[epoch 22] loss: 0.0729911
Test set: Average loss: 1.0629, Accuracy: 3421/5000 (68%)
[epoch 23] loss: 0.0597546
Test set: Average loss: 1.0823, Accuracy: 3453/5000 (69%)
[epoch 24] loss: 0.0493321
Test set: Average loss: 1.1106, Accuracy: 3414/5000 (68%)
[epoch 25] loss: 0.0451813
Test set: Average loss: 1.1808, Accuracy: 3360/5000 (67%)
Validation:
Test set: Average loss: 0.8494, Accuracy: 3514/5000 (70%)
Test
Test set: Average loss: 0.8633, Accuracy: 3422/5000 (68%)
Test set: Average loss: 0.3186, Accuracy: 18540/20000 (93%)
## seed: 13
Validation accuracy before training:
Test set: Average loss: 1.5506, Accuracy: 1226/5000 (25%)
[epoch 1] loss: 1.1404552
Test set: Average loss: 1.0403, Accuracy: 3111/5000 (62%)
[epoch 2] loss: 0.9736912
Test set: Average loss: 0.9724, Accuracy: 3215/5000 (64%)
[epoch 3] loss: 0.8826388
Test set: Average loss: 0.9210, Accuracy: 3299/5000 (66%)
[epoch 4] loss: 0.8094333
Test set: Average loss: 0.8828, Accuracy: 3382/5000 (68%)
[epoch 5] loss: 0.7466032
Test set: Average loss: 0.8659, Accuracy: 3398/5000 (68%)
[epoch 6] loss: 0.6866897
Test set: Average loss: 0.8469, Accuracy: 3432/5000 (69%)
[epoch 7] loss: 0.6316005
Test set: Average loss: 0.8377, Accuracy: 3472/5000 (69%)
[epoch 8] loss: 0.5792607
Test set: Average loss: 0.8349, Accuracy: 3461/5000 (69%)
[epoch 9] loss: 0.5283978
Test set: Average loss: 0.8316, Accuracy: 3469/5000 (69%)
[epoch 10] loss: 0.4781335
Test set: Average loss: 0.8391, Accuracy: 3461/5000 (69%)
[epoch 11] loss: 0.4313043
Test set: Average loss: 0.8409, Accuracy: 3492/5000 (70%)
[epoch 12] loss: 0.3859024
Test set: Average loss: 0.8411, Accuracy: 3494/5000 (70%)
[epoch 13] loss: 0.3439420
Test set: Average loss: 0.8681, Accuracy: 3474/5000 (69%)
[epoch 14] loss: 0.3032156
Test set: Average loss: 0.8645, Accuracy: 3481/5000 (70%)
[epoch 15] loss: 0.2670906
Test set: Average loss: 0.8798, Accuracy: 3494/5000 (70%)
[epoch 16] loss: 0.2299555
Test set: Average loss: 0.8879, Accuracy: 3468/5000 (69%)
[epoch 17] loss: 0.1995601
Test set: Average loss: 0.9058, Accuracy: 3472/5000 (69%)
[epoch 18] loss: 0.1703367
Test set: Average loss: 0.9443, Accuracy: 3455/5000 (69%)
[epoch 19] loss: 0.1427943
Test set: Average loss: 0.9563, Accuracy: 3453/5000 (69%)
[epoch 20] loss: 0.1235891
Test set: Average loss: 0.9688, Accuracy: 3479/5000 (70%)
[epoch 21] loss: 0.0993838
Test set: Average loss: 0.9913, Accuracy: 3449/5000 (69%)
[epoch 22] loss: 0.0853041
Test set: Average loss: 1.0203, Accuracy: 3434/5000 (69%)
[epoch 23] loss: 0.0681013
Test set: Average loss: 1.0526, Accuracy: 3406/5000 (68%)
[epoch 24] loss: 0.0584980
Test set: Average loss: 1.0715, Accuracy: 3416/5000 (68%)
[epoch 25] loss: 0.0461573
Test set: Average loss: 1.1022, Accuracy: 3453/5000 (69%)
Validation:
Test set: Average loss: 0.8798, Accuracy: 3494/5000 (70%)
Test
Test set: Average loss: 0.8988, Accuracy: 3434/5000 (69%)
Test set: Average loss: 0.2157, Accuracy: 19160/20000 (96%)
## Pre-Training ABnB
Validation accuracy before training:
Test set: Average loss: 2.3269, Accuracy: 464/5000 (9%)
[epoch 1] loss: 1.9136724
Test set: Average loss: 1.8378, Accuracy: 1903/5000 (38%)
[epoch 2] loss: 1.7746441
Test set: Average loss: 1.7721, Accuracy: 2038/5000 (41%)
[epoch 3] loss: 1.6996394
Test set: Average loss: 1.7303, Accuracy: 2071/5000 (41%)
[epoch 4] loss: 1.6360109
Test set: Average loss: 1.7005, Accuracy: 2148/5000 (43%)
[epoch 5] loss: 1.5801003
Test set: Average loss: 1.6742, Accuracy: 2188/5000 (44%)
[epoch 6] loss: 1.5247744
Test set: Average loss: 1.6488, Accuracy: 2205/5000 (44%)
[epoch 7] loss: 1.4729469
Test set: Average loss: 1.6321, Accuracy: 2230/5000 (45%)
[epoch 8] loss: 1.4197488
Test set: Average loss: 1.6208, Accuracy: 2244/5000 (45%)
[epoch 9] loss: 1.3672078
Test set: Average loss: 1.6051, Accuracy: 2246/5000 (45%)
[epoch 10] loss: 1.3153967
Test set: Average loss: 1.5951, Accuracy: 2281/5000 (46%)
[epoch 11] loss: 1.2635657
Test set: Average loss: 1.6002, Accuracy: 2255/5000 (45%)
[epoch 12] loss: 1.2102820
Test set: Average loss: 1.5959, Accuracy: 2265/5000 (45%)
[epoch 13] loss: 1.1578619
Test set: Average loss: 1.5890, Accuracy: 2250/5000 (45%)
[epoch 14] loss: 1.1027380
Test set: Average loss: 1.5911, Accuracy: 2275/5000 (46%)
[epoch 15] loss: 1.0485065
Test set: Average loss: 1.5927, Accuracy: 2300/5000 (46%)
[epoch 16] loss: 0.9937562
Test set: Average loss: 1.5893, Accuracy: 2267/5000 (45%)
[epoch 17] loss: 0.9385484
Test set: Average loss: 1.5996, Accuracy: 2284/5000 (46%)
[epoch 18] loss: 0.8867276
Test set: Average loss: 1.6235, Accuracy: 2210/5000 (44%)
[epoch 19] loss: 0.8318681
Test set: Average loss: 1.6215, Accuracy: 2235/5000 (45%)
[epoch 20] loss: 0.7810492
Test set: Average loss: 1.6395, Accuracy: 2233/5000 (45%)
[epoch 21] loss: 0.7287173
Test set: Average loss: 1.6707, Accuracy: 2223/5000 (44%)
[epoch 22] loss: 0.6802191
Test set: Average loss: 1.6740, Accuracy: 2251/5000 (45%)
[epoch 23] loss: 0.6312706
Test set: Average loss: 1.6875, Accuracy: 2241/5000 (45%)
[epoch 24] loss: 0.5843158
Test set: Average loss: 1.7132, Accuracy: 2208/5000 (44%)
[epoch 25] loss: 0.5418192
Test set: Average loss: 1.7523, Accuracy: 2164/5000 (43%)
Validation:
Test set: Average loss: 1.5927, Accuracy: 2300/5000 (46%)
Test set: Average loss: 1.5748, Accuracy: 4617/10000 (46%)
25
## seed: 11
Validation accuracy before training:
Test set: Average loss: 1.7296, Accuracy: 901/5000 (18%)
[epoch 1] loss: 1.7852697
Test set: Average loss: 1.7172, Accuracy: 944/5000 (19%)
[epoch 2] loss: 1.6981312
Test set: Average loss: 1.7048, Accuracy: 977/5000 (20%)
[epoch 3] loss: 1.6145651
Test set: Average loss: 1.6926, Accuracy: 1000/5000 (20%)
[epoch 4] loss: 1.5356774
Test set: Average loss: 1.6807, Accuracy: 1024/5000 (20%)
[epoch 5] loss: 1.4619844
Test set: Average loss: 1.6693, Accuracy: 1043/5000 (21%)
[epoch 6] loss: 1.3936470
Test set: Average loss: 1.6585, Accuracy: 1085/5000 (22%)
[epoch 7] loss: 1.3306262
Test set: Average loss: 1.6483, Accuracy: 1130/5000 (23%)
[epoch 8] loss: 1.2727430
Test set: Average loss: 1.6387, Accuracy: 1165/5000 (23%)
[epoch 9] loss: 1.2197040
Test set: Average loss: 1.6297, Accuracy: 1198/5000 (24%)
[epoch 10] loss: 1.1711231
Test set: Average loss: 1.6212, Accuracy: 1230/5000 (25%)
[epoch 11] loss: 1.1265639
Test set: Average loss: 1.6134, Accuracy: 1268/5000 (25%)
[epoch 12] loss: 1.0855926
Test set: Average loss: 1.6060, Accuracy: 1297/5000 (26%)
[epoch 13] loss: 1.0478138
Test set: Average loss: 1.5992, Accuracy: 1328/5000 (27%)
[epoch 14] loss: 1.0128818
Test set: Average loss: 1.5929, Accuracy: 1358/5000 (27%)
[epoch 15] loss: 0.9805022
Test set: Average loss: 1.5870, Accuracy: 1388/5000 (28%)
[epoch 16] loss: 0.9504287
Test set: Average loss: 1.5815, Accuracy: 1409/5000 (28%)
[epoch 17] loss: 0.9224534
Test set: Average loss: 1.5764, Accuracy: 1424/5000 (28%)
[epoch 18] loss: 0.8963958
Test set: Average loss: 1.5716, Accuracy: 1458/5000 (29%)
[epoch 19] loss: 0.8720913
Test set: Average loss: 1.5672, Accuracy: 1470/5000 (29%)
[epoch 20] loss: 0.8493897
Test set: Average loss: 1.5630, Accuracy: 1489/5000 (30%)
[epoch 21] loss: 0.8281541
Test set: Average loss: 1.5590, Accuracy: 1500/5000 (30%)
[epoch 22] loss: 0.8082595
Test set: Average loss: 1.5553, Accuracy: 1522/5000 (30%)
[epoch 23] loss: 0.7895917
Test set: Average loss: 1.5517, Accuracy: 1532/5000 (31%)
[epoch 24] loss: 0.7720445
Test set: Average loss: 1.5483, Accuracy: 1542/5000 (31%)
[epoch 25] loss: 0.7555193
Test set: Average loss: 1.5450, Accuracy: 1561/5000 (31%)
Validation:
Test set: Average loss: 1.5450, Accuracy: 1561/5000 (31%)
Test
Test set: Average loss: 1.5563, Accuracy: 1567/5000 (31%)
Test set: Average loss: 0.7399, Accuracy: 24/25 (96%)
## seed: 12
Validation accuracy before training:
Test set: Average loss: 1.6645, Accuracy: 834/5000 (17%)
[epoch 1] loss: 1.6694837
Test set: Average loss: 1.6459, Accuracy: 923/5000 (18%)
[epoch 2] loss: 1.5720201
Test set: Average loss: 1.6288, Accuracy: 994/5000 (20%)
[epoch 3] loss: 1.4800817
Test set: Average loss: 1.6132, Accuracy: 1100/5000 (22%)
[epoch 4] loss: 1.3950728
Test set: Average loss: 1.5991, Accuracy: 1171/5000 (23%)
[epoch 5] loss: 1.3177341
Test set: Average loss: 1.5863, Accuracy: 1248/5000 (25%)
[epoch 6] loss: 1.2481656
Test set: Average loss: 1.5747, Accuracy: 1339/5000 (27%)
[epoch 7] loss: 1.1859704
Test set: Average loss: 1.5641, Accuracy: 1410/5000 (28%)
[epoch 8] loss: 1.1304225
Test set: Average loss: 1.5544, Accuracy: 1469/5000 (29%)
[epoch 9] loss: 1.0806304
Test set: Average loss: 1.5455, Accuracy: 1529/5000 (31%)
[epoch 10] loss: 1.0356836
Test set: Average loss: 1.5372, Accuracy: 1577/5000 (32%)
[epoch 11] loss: 0.9947646
Test set: Average loss: 1.5294, Accuracy: 1625/5000 (32%)
[epoch 12] loss: 0.9572256
Test set: Average loss: 1.5220, Accuracy: 1662/5000 (33%)
[epoch 13] loss: 0.9226204
Test set: Average loss: 1.5151, Accuracy: 1699/5000 (34%)
[epoch 14] loss: 0.8906790
Test set: Average loss: 1.5085, Accuracy: 1727/5000 (35%)
[epoch 15] loss: 0.8612304
Test set: Average loss: 1.5024, Accuracy: 1749/5000 (35%)
[epoch 16] loss: 0.8341217
Test set: Average loss: 1.4965, Accuracy: 1775/5000 (36%)
[epoch 17] loss: 0.8091754
Test set: Average loss: 1.4911, Accuracy: 1805/5000 (36%)
[epoch 18] loss: 0.7861878
Test set: Average loss: 1.4860, Accuracy: 1818/5000 (36%)
[epoch 19] loss: 0.7649429
Test set: Average loss: 1.4812, Accuracy: 1831/5000 (37%)
[epoch 20] loss: 0.7452257
Test set: Average loss: 1.4768, Accuracy: 1846/5000 (37%)
[epoch 21] loss: 0.7268323
Test set: Average loss: 1.4727, Accuracy: 1863/5000 (37%)
[epoch 22] loss: 0.7095749
Test set: Average loss: 1.4690, Accuracy: 1880/5000 (38%)
[epoch 23] loss: 0.6932883
Test set: Average loss: 1.4655, Accuracy: 1881/5000 (38%)
[epoch 24] loss: 0.6778336
Test set: Average loss: 1.4623, Accuracy: 1895/5000 (38%)
[epoch 25] loss: 0.6631032
Test set: Average loss: 1.4593, Accuracy: 1901/5000 (38%)
Validation:
Test set: Average loss: 1.4593, Accuracy: 1901/5000 (38%)
Test
Test set: Average loss: 1.4725, Accuracy: 1866/5000 (37%)
Test set: Average loss: 0.6490, Accuracy: 25/25 (100%)
## seed: 13
Validation accuracy before training:
Test set: Average loss: 1.8523, Accuracy: 339/5000 (7%)
[epoch 1] loss: 1.8887706
Test set: Average loss: 1.8355, Accuracy: 355/5000 (7%)
[epoch 2] loss: 1.7844720
Test set: Average loss: 1.8190, Accuracy: 379/5000 (8%)
[epoch 3] loss: 1.6837590
Test set: Average loss: 1.8028, Accuracy: 413/5000 (8%)
[epoch 4] loss: 1.5888245
Test set: Average loss: 1.7869, Accuracy: 435/5000 (9%)
[epoch 5] loss: 1.5008258
Test set: Average loss: 1.7713, Accuracy: 466/5000 (9%)
[epoch 6] loss: 1.4200748
Test set: Average loss: 1.7562, Accuracy: 513/5000 (10%)
[epoch 7] loss: 1.3463670
Test set: Average loss: 1.7417, Accuracy: 555/5000 (11%)
[epoch 8] loss: 1.2792732
Test set: Average loss: 1.7276, Accuracy: 598/5000 (12%)
[epoch 9] loss: 1.2183106
Test set: Average loss: 1.7143, Accuracy: 646/5000 (13%)
[epoch 10] loss: 1.1629896
Test set: Average loss: 1.7016, Accuracy: 690/5000 (14%)
[epoch 11] loss: 1.1128128
Test set: Average loss: 1.6896, Accuracy: 740/5000 (15%)
[epoch 12] loss: 1.0672824
Test set: Average loss: 1.6782, Accuracy: 781/5000 (16%)
[epoch 13] loss: 1.0259233
Test set: Average loss: 1.6676, Accuracy: 834/5000 (17%)
[epoch 14] loss: 0.9882895
Test set: Average loss: 1.6575, Accuracy: 891/5000 (18%)
[epoch 15] loss: 0.9539522
Test set: Average loss: 1.6481, Accuracy: 927/5000 (19%)
[epoch 16] loss: 0.9224808
Test set: Average loss: 1.6392, Accuracy: 964/5000 (19%)
[epoch 17] loss: 0.8934511
Test set: Average loss: 1.6308, Accuracy: 1012/5000 (20%)
[epoch 18] loss: 0.8664874
Test set: Average loss: 1.6229, Accuracy: 1052/5000 (21%)
[epoch 19] loss: 0.8413053
Test set: Average loss: 1.6154, Accuracy: 1104/5000 (22%)
[epoch 20] loss: 0.8177247
Test set: Average loss: 1.6083, Accuracy: 1150/5000 (23%)
[epoch 21] loss: 0.7956429
Test set: Average loss: 1.6015, Accuracy: 1175/5000 (24%)
[epoch 22] loss: 0.7749915
Test set: Average loss: 1.5951, Accuracy: 1209/5000 (24%)
[epoch 23] loss: 0.7557047
Test set: Average loss: 1.5890, Accuracy: 1237/5000 (25%)
[epoch 24] loss: 0.7377071
Test set: Average loss: 1.5832, Accuracy: 1258/5000 (25%)
[epoch 25] loss: 0.7209120
Test set: Average loss: 1.5776, Accuracy: 1283/5000 (26%)
Validation:
Test set: Average loss: 1.5776, Accuracy: 1283/5000 (26%)
Test
Test set: Average loss: 1.5834, Accuracy: 1300/5000 (26%)
Test set: Average loss: 0.7052, Accuracy: 24/25 (96%)
50
## seed: 11
Validation accuracy before training:
Test set: Average loss: 1.7094, Accuracy: 1119/5000 (22%)
[epoch 1] loss: 1.6135023
Test set: Average loss: 1.6744, Accuracy: 1185/5000 (24%)
[epoch 2] loss: 1.4976028
Test set: Average loss: 1.6447, Accuracy: 1272/5000 (25%)
[epoch 3] loss: 1.4389889
Test set: Average loss: 1.6174, Accuracy: 1364/5000 (27%)
[epoch 4] loss: 1.3320694
Test set: Average loss: 1.5929, Accuracy: 1431/5000 (29%)
[epoch 5] loss: 1.2727421
Test set: Average loss: 1.5716, Accuracy: 1503/5000 (30%)
[epoch 6] loss: 1.1536973
Test set: Average loss: 1.5528, Accuracy: 1553/5000 (31%)
[epoch 7] loss: 1.1402012
Test set: Average loss: 1.5370, Accuracy: 1609/5000 (32%)
[epoch 8] loss: 1.0886463
Test set: Average loss: 1.5227, Accuracy: 1637/5000 (33%)
[epoch 9] loss: 1.0222491
Test set: Average loss: 1.5103, Accuracy: 1693/5000 (34%)
[epoch 10] loss: 0.9841790
Test set: Average loss: 1.4992, Accuracy: 1734/5000 (35%)
[epoch 11] loss: 0.9105446
Test set: Average loss: 1.4895, Accuracy: 1768/5000 (35%)
[epoch 12] loss: 0.9138902
Epoch 11: reducing learning rate of group 0 to 5.0000e-06.
Test set: Average loss: 1.4811, Accuracy: 1799/5000 (36%)
[epoch 13] loss: 0.8768419
Test set: Average loss: 1.4804, Accuracy: 1800/5000 (36%)
[epoch 14] loss: 0.8777925
Epoch 13: reducing learning rate of group 0 to 5.0000e-07.
Test set: Average loss: 1.4797, Accuracy: 1803/5000 (36%)
[epoch 15] loss: 0.8625680
Test set: Average loss: 1.4797, Accuracy: 1803/5000 (36%)
[epoch 16] loss: 0.8868034
Epoch 15: reducing learning rate of group 0 to 5.0000e-08.
Test set: Average loss: 1.4796, Accuracy: 1803/5000 (36%)
[epoch 17] loss: 0.8661413
Epoch 16: reducing learning rate of group 0 to 5.0000e-09.
Test set: Average loss: 1.4796, Accuracy: 1803/5000 (36%)
[epoch 18] loss: 0.8907513
Epoch 17: reducing learning rate of group 0 to 5.0000e-10.
Test set: Average loss: 1.4796, Accuracy: 1803/5000 (36%)
[epoch 19] loss: 0.8889853
Epoch 18: reducing learning rate of group 0 to 5.0000e-11.
Test set: Average loss: 1.4796, Accuracy: 1803/5000 (36%)
[epoch 20] loss: 0.8502528
Test set: Average loss: 1.4796, Accuracy: 1803/5000 (36%)
[epoch 21] loss: 0.8687481
Epoch 20: reducing learning rate of group 0 to 5.0000e-12.
Test set: Average loss: 1.4796, Accuracy: 1803/5000 (36%)
[epoch 22] loss: 0.8957753
Epoch 21: reducing learning rate of group 0 to 5.0000e-13.
Test set: Average loss: 1.4796, Accuracy: 1803/5000 (36%)
[epoch 23] loss: 0.8536289
Epoch 22: reducing learning rate of group 0 to 5.0000e-14.
Test set: Average loss: 1.4796, Accuracy: 1803/5000 (36%)
[epoch 24] loss: 0.8632472
Epoch 23: reducing learning rate of group 0 to 5.0000e-15.
Test set: Average loss: 1.4796, Accuracy: 1803/5000 (36%)
[epoch 25] loss: 0.8575124
Epoch 24: reducing learning rate of group 0 to 5.0000e-16.
Test set: Average loss: 1.4796, Accuracy: 1803/5000 (36%)
Validation:
Test set: Average loss: 1.4796, Accuracy: 1803/5000 (36%)
Test
Test set: Average loss: 1.4756, Accuracy: 1759/5000 (35%)
Test set: Average loss: 0.8675, Accuracy: 44/50 (88%)
## seed: 12
Validation accuracy before training:
Test set: Average loss: 1.6884, Accuracy: 844/5000 (17%)
[epoch 1] loss: 1.6297305
Test set: Average loss: 1.6556, Accuracy: 1054/5000 (21%)
[epoch 2] loss: 1.5278023
Test set: Average loss: 1.6321, Accuracy: 1254/5000 (25%)
[epoch 3] loss: 1.4421901
Test set: Average loss: 1.6108, Accuracy: 1454/5000 (29%)
[epoch 4] loss: 1.3161882
Test set: Average loss: 1.5916, Accuracy: 1600/5000 (32%)
[epoch 5] loss: 1.2706923
Test set: Average loss: 1.5751, Accuracy: 1699/5000 (34%)
[epoch 6] loss: 1.2015207
Test set: Average loss: 1.5612, Accuracy: 1796/5000 (36%)
[epoch 7] loss: 1.1590898
Test set: Average loss: 1.5482, Accuracy: 1865/5000 (37%)
[epoch 8] loss: 1.1235198
Test set: Average loss: 1.5368, Accuracy: 1911/5000 (38%)
[epoch 9] loss: 1.0441781
Test set: Average loss: 1.5268, Accuracy: 1937/5000 (39%)
[epoch 10] loss: 0.9941010
Test set: Average loss: 1.5182, Accuracy: 1967/5000 (39%)
[epoch 11] loss: 0.9802066
Test set: Average loss: 1.5103, Accuracy: 1993/5000 (40%)
[epoch 12] loss: 0.9263058
Test set: Average loss: 1.5036, Accuracy: 2018/5000 (40%)
[epoch 13] loss: 0.9029863
Test set: Average loss: 1.4973, Accuracy: 2037/5000 (41%)
[epoch 14] loss: 0.8779385
Test set: Average loss: 1.4916, Accuracy: 2048/5000 (41%)
[epoch 15] loss: 0.8684211
Test set: Average loss: 1.4868, Accuracy: 2049/5000 (41%)
[epoch 16] loss: 0.8289422
Test set: Average loss: 1.4821, Accuracy: 2057/5000 (41%)
[epoch 17] loss: 0.8034607
Test set: Average loss: 1.4779, Accuracy: 2067/5000 (41%)
[epoch 18] loss: 0.7732407
Test set: Average loss: 1.4745, Accuracy: 2072/5000 (41%)
[epoch 19] loss: 0.7521650
Test set: Average loss: 1.4713, Accuracy: 2086/5000 (42%)
[epoch 20] loss: 0.7266663
Test set: Average loss: 1.4684, Accuracy: 2096/5000 (42%)
[epoch 21] loss: 0.7208312
Test set: Average loss: 1.4656, Accuracy: 2101/5000 (42%)
[epoch 22] loss: 0.7259027
Epoch 21: reducing learning rate of group 0 to 5.0000e-06.
Test set: Average loss: 1.4629, Accuracy: 2103/5000 (42%)
[epoch 23] loss: 0.6904280
Test set: Average loss: 1.4627, Accuracy: 2103/5000 (42%)
[epoch 24] loss: 0.7090748
Epoch 23: reducing learning rate of group 0 to 5.0000e-07.
Test set: Average loss: 1.4624, Accuracy: 2105/5000 (42%)
[epoch 25] loss: 0.6910743
Epoch 24: reducing learning rate of group 0 to 5.0000e-08.
Test set: Average loss: 1.4624, Accuracy: 2105/5000 (42%)
Validation:
Test set: Average loss: 1.4624, Accuracy: 2105/5000 (42%)
Test
Test set: Average loss: 1.4596, Accuracy: 2153/5000 (43%)
Test set: Average loss: 0.6958, Accuracy: 49/50 (98%)
## seed: 13
Validation accuracy before training:
Test set: Average loss: 1.5506, Accuracy: 1462/5000 (29%)
[epoch 1] loss: 1.5616457
Test set: Average loss: 1.5228, Accuracy: 1571/5000 (31%)
[epoch 2] loss: 1.4541685
Test set: Average loss: 1.4992, Accuracy: 1673/5000 (33%)
[epoch 3] loss: 1.3469849
Test set: Average loss: 1.4793, Accuracy: 1771/5000 (35%)
[epoch 4] loss: 1.2635875
Test set: Average loss: 1.4627, Accuracy: 1856/5000 (37%)
[epoch 5] loss: 1.2086874
Test set: Average loss: 1.4479, Accuracy: 1928/5000 (39%)
[epoch 6] loss: 1.1229017
Test set: Average loss: 1.4353, Accuracy: 1991/5000 (40%)
[epoch 7] loss: 1.0993160
Test set: Average loss: 1.4243, Accuracy: 2042/5000 (41%)
[epoch 8] loss: 1.0380315
Test set: Average loss: 1.4146, Accuracy: 2086/5000 (42%)
[epoch 9] loss: 0.9949277
Test set: Average loss: 1.4062, Accuracy: 2118/5000 (42%)
[epoch 10] loss: 0.9621817
Test set: Average loss: 1.3988, Accuracy: 2146/5000 (43%)
[epoch 11] loss: 0.9162613
Test set: Average loss: 1.3923, Accuracy: 2175/5000 (44%)
[epoch 12] loss: 0.8780346
Test set: Average loss: 1.3864, Accuracy: 2199/5000 (44%)
[epoch 13] loss: 0.8441026
Test set: Average loss: 1.3813, Accuracy: 2212/5000 (44%)
[epoch 14] loss: 0.8084398
Test set: Average loss: 1.3763, Accuracy: 2217/5000 (44%)
[epoch 15] loss: 0.7793732
Test set: Average loss: 1.3720, Accuracy: 2231/5000 (45%)
[epoch 16] loss: 0.7797776
Epoch 15: reducing learning rate of group 0 to 5.0000e-06.
Test set: Average loss: 1.3682, Accuracy: 2234/5000 (45%)
[epoch 17] loss: 0.7569329
Test set: Average loss: 1.3678, Accuracy: 2237/5000 (45%)
[epoch 18] loss: 0.7481247
Test set: Average loss: 1.3674, Accuracy: 2239/5000 (45%)
[epoch 19] loss: 0.7663335
Epoch 18: reducing learning rate of group 0 to 5.0000e-07.
Test set: Average loss: 1.3671, Accuracy: 2243/5000 (45%)
[epoch 20] loss: 0.7407330
Test set: Average loss: 1.3671, Accuracy: 2244/5000 (45%)
[epoch 21] loss: 0.7438294
Epoch 20: reducing learning rate of group 0 to 5.0000e-08.
Test set: Average loss: 1.3670, Accuracy: 2243/5000 (45%)
[epoch 22] loss: 0.7537564
Epoch 21: reducing learning rate of group 0 to 5.0000e-09.
Test set: Average loss: 1.3670, Accuracy: 2243/5000 (45%)
[epoch 23] loss: 0.7598524
Epoch 22: reducing learning rate of group 0 to 5.0000e-10.
Test set: Average loss: 1.3670, Accuracy: 2243/5000 (45%)
[epoch 24] loss: 0.7330171
Test set: Average loss: 1.3670, Accuracy: 2243/5000 (45%)
[epoch 25] loss: 0.7513966
Epoch 24: reducing learning rate of group 0 to 5.0000e-11.
Test set: Average loss: 1.3670, Accuracy: 2243/5000 (45%)
Validation:
Test set: Average loss: 1.3671, Accuracy: 2244/5000 (45%)
Test
Test set: Average loss: 1.3754, Accuracy: 2200/5000 (44%)
Test set: Average loss: 0.7470, Accuracy: 47/50 (94%)
100
## seed: 11
Validation accuracy before training:
Test set: Average loss: 1.7355, Accuracy: 788/5000 (16%)
[epoch 1] loss: 1.6485452
Test set: Average loss: 1.6696, Accuracy: 1075/5000 (22%)
[epoch 2] loss: 1.5200337
Test set: Average loss: 1.6230, Accuracy: 1288/5000 (26%)
[epoch 3] loss: 1.3922989
Test set: Average loss: 1.5878, Accuracy: 1466/5000 (29%)
[epoch 4] loss: 1.3832748
Test set: Average loss: 1.5570, Accuracy: 1563/5000 (31%)
[epoch 5] loss: 1.2514769
Test set: Average loss: 1.5312, Accuracy: 1639/5000 (33%)
[epoch 6] loss: 1.2637564
Epoch 5: reducing learning rate of group 0 to 5.0000e-06.
Test set: Average loss: 1.5101, Accuracy: 1722/5000 (34%)
[epoch 7] loss: 1.1571847
Test set: Average loss: 1.5084, Accuracy: 1726/5000 (35%)
[epoch 8] loss: 1.2340277
Epoch 7: reducing learning rate of group 0 to 5.0000e-07.
Test set: Average loss: 1.5069, Accuracy: 1733/5000 (35%)
[epoch 9] loss: 1.1797782
Epoch 8: reducing learning rate of group 0 to 5.0000e-08.
Test set: Average loss: 1.5068, Accuracy: 1733/5000 (35%)
[epoch 10] loss: 1.1860565
Epoch 9: reducing learning rate of group 0 to 5.0000e-09.
Test set: Average loss: 1.5068, Accuracy: 1733/5000 (35%)
[epoch 11] loss: 1.1569332
Test set: Average loss: 1.5068, Accuracy: 1733/5000 (35%)
[epoch 12] loss: 1.1444333
Test set: Average loss: 1.5068, Accuracy: 1733/5000 (35%)
[epoch 13] loss: 1.1866524
Epoch 12: reducing learning rate of group 0 to 5.0000e-10.
Test set: Average loss: 1.5068, Accuracy: 1733/5000 (35%)
[epoch 14] loss: 1.2030290
Epoch 13: reducing learning rate of group 0 to 5.0000e-11.
Test set: Average loss: 1.5068, Accuracy: 1733/5000 (35%)
[epoch 15] loss: 1.1685248
Epoch 14: reducing learning rate of group 0 to 5.0000e-12.
Test set: Average loss: 1.5068, Accuracy: 1733/5000 (35%)
[epoch 16] loss: 1.1907383
Epoch 15: reducing learning rate of group 0 to 5.0000e-13.
Test set: Average loss: 1.5068, Accuracy: 1733/5000 (35%)
[epoch 17] loss: 1.2030813
Epoch 16: reducing learning rate of group 0 to 5.0000e-14.
Test set: Average loss: 1.5068, Accuracy: 1733/5000 (35%)
[epoch 18] loss: 1.2213073
Epoch 17: reducing learning rate of group 0 to 5.0000e-15.
Test set: Average loss: 1.5068, Accuracy: 1733/5000 (35%)
[epoch 19] loss: 1.1930428
Epoch 18: reducing learning rate of group 0 to 5.0000e-16.
Test set: Average loss: 1.5068, Accuracy: 1733/5000 (35%)
[epoch 20] loss: 1.1703032
Epoch 19: reducing learning rate of group 0 to 5.0000e-17.
Test set: Average loss: 1.5068, Accuracy: 1733/5000 (35%)
[epoch 21] loss: 1.1401907
Test set: Average loss: 1.5068, Accuracy: 1733/5000 (35%)
[epoch 22] loss: 1.1568786
Epoch 21: reducing learning rate of group 0 to 5.0000e-18.
Test set: Average loss: 1.5068, Accuracy: 1733/5000 (35%)
[epoch 23] loss: 1.1492090
Epoch 22: reducing learning rate of group 0 to 5.0000e-19.
Test set: Average loss: 1.5068, Accuracy: 1733/5000 (35%)
[epoch 24] loss: 1.2573962
Epoch 23: reducing learning rate of group 0 to 5.0000e-20.
Test set: Average loss: 1.5068, Accuracy: 1733/5000 (35%)
[epoch 25] loss: 1.1720488
Epoch 24: reducing learning rate of group 0 to 5.0000e-21.
Test set: Average loss: 1.5068, Accuracy: 1733/5000 (35%)
Validation:
Test set: Average loss: 1.5068, Accuracy: 1733/5000 (35%)
Test
Test set: Average loss: 1.5113, Accuracy: 1676/5000 (34%)
Test set: Average loss: 1.1852, Accuracy: 64/100 (64%)
## seed: 12
Validation accuracy before training:
Test set: Average loss: 1.8110, Accuracy: 592/5000 (12%)
[epoch 1] loss: 1.8394021
Test set: Average loss: 1.7417, Accuracy: 729/5000 (15%)
[epoch 2] loss: 1.6446703
Test set: Average loss: 1.6859, Accuracy: 962/5000 (19%)
[epoch 3] loss: 1.5164261
Test set: Average loss: 1.6424, Accuracy: 1157/5000 (23%)
[epoch 4] loss: 1.4033132
Test set: Average loss: 1.6030, Accuracy: 1325/5000 (26%)
[epoch 5] loss: 1.2754205
Test set: Average loss: 1.5709, Accuracy: 1460/5000 (29%)
[epoch 6] loss: 1.2985376
Epoch 5: reducing learning rate of group 0 to 5.0000e-06.
Test set: Average loss: 1.5489, Accuracy: 1571/5000 (31%)
[epoch 7] loss: 1.2291768
Test set: Average loss: 1.5470, Accuracy: 1571/5000 (31%)
[epoch 8] loss: 1.2391412
Epoch 7: reducing learning rate of group 0 to 5.0000e-07.
Test set: Average loss: 1.5451, Accuracy: 1585/5000 (32%)
[epoch 9] loss: 1.2795703
Epoch 8: reducing learning rate of group 0 to 5.0000e-08.
Test set: Average loss: 1.5449, Accuracy: 1587/5000 (32%)
[epoch 10] loss: 1.1821487
Test set: Average loss: 1.5449, Accuracy: 1587/5000 (32%)
[epoch 11] loss: 1.1760411
Test set: Average loss: 1.5448, Accuracy: 1588/5000 (32%)
[epoch 12] loss: 1.1524511
Test set: Average loss: 1.5448, Accuracy: 1588/5000 (32%)
[epoch 13] loss: 1.2269254
Epoch 12: reducing learning rate of group 0 to 5.0000e-09.
Test set: Average loss: 1.5448, Accuracy: 1588/5000 (32%)
[epoch 14] loss: 1.1689659
Epoch 13: reducing learning rate of group 0 to 5.0000e-10.
Test set: Average loss: 1.5448, Accuracy: 1588/5000 (32%)
[epoch 15] loss: 1.1673759
Epoch 14: reducing learning rate of group 0 to 5.0000e-11.
Test set: Average loss: 1.5448, Accuracy: 1588/5000 (32%)
[epoch 16] loss: 1.1936943
Epoch 15: reducing learning rate of group 0 to 5.0000e-12.
Test set: Average loss: 1.5448, Accuracy: 1588/5000 (32%)
[epoch 17] loss: 1.1476271
Test set: Average loss: 1.5448, Accuracy: 1588/5000 (32%)
[epoch 18] loss: 1.1571063
Epoch 17: reducing learning rate of group 0 to 5.0000e-13.
Test set: Average loss: 1.5448, Accuracy: 1588/5000 (32%)
[epoch 19] loss: 1.1895508
Epoch 18: reducing learning rate of group 0 to 5.0000e-14.
Test set: Average loss: 1.5448, Accuracy: 1588/5000 (32%)
[epoch 20] loss: 1.1805852
Epoch 19: reducing learning rate of group 0 to 5.0000e-15.
Test set: Average loss: 1.5448, Accuracy: 1588/5000 (32%)
[epoch 21] loss: 1.1875484
Epoch 20: reducing learning rate of group 0 to 5.0000e-16.
Test set: Average loss: 1.5448, Accuracy: 1588/5000 (32%)
[epoch 22] loss: 1.1949179
Epoch 21: reducing learning rate of group 0 to 5.0000e-17.
Test set: Average loss: 1.5448, Accuracy: 1588/5000 (32%)
[epoch 23] loss: 1.2155010
Epoch 22: reducing learning rate of group 0 to 5.0000e-18.
Test set: Average loss: 1.5448, Accuracy: 1588/5000 (32%)
[epoch 24] loss: 1.1835102
Epoch 23: reducing learning rate of group 0 to 5.0000e-19.
Test set: Average loss: 1.5448, Accuracy: 1588/5000 (32%)
[epoch 25] loss: 1.2132853
Epoch 24: reducing learning rate of group 0 to 5.0000e-20.
Test set: Average loss: 1.5448, Accuracy: 1588/5000 (32%)
Validation:
Test set: Average loss: 1.5448, Accuracy: 1588/5000 (32%)
Test
Test set: Average loss: 1.5480, Accuracy: 1510/5000 (30%)
Test set: Average loss: 1.1980, Accuracy: 65/100 (65%)
## seed: 13
Validation accuracy before training:
Test set: Average loss: 1.8514, Accuracy: 523/5000 (10%)
[epoch 1] loss: 1.7975481
Test set: Average loss: 1.7671, Accuracy: 782/5000 (16%)
[epoch 2] loss: 1.6543015
Test set: Average loss: 1.7096, Accuracy: 1019/5000 (20%)
[epoch 3] loss: 1.4772888
Test set: Average loss: 1.6611, Accuracy: 1201/5000 (24%)
[epoch 4] loss: 1.4499764
Test set: Average loss: 1.6211, Accuracy: 1365/5000 (27%)
[epoch 5] loss: 1.3522195
Test set: Average loss: 1.5891, Accuracy: 1470/5000 (29%)
[epoch 6] loss: 1.3406786
Test set: Average loss: 1.5630, Accuracy: 1569/5000 (31%)
[epoch 7] loss: 1.2280866
Test set: Average loss: 1.5411, Accuracy: 1651/5000 (33%)
[epoch 8] loss: 1.1383443
Test set: Average loss: 1.5228, Accuracy: 1708/5000 (34%)
[epoch 9] loss: 1.1569061
Epoch 8: reducing learning rate of group 0 to 5.0000e-06.
Test set: Average loss: 1.5073, Accuracy: 1755/5000 (35%)
[epoch 10] loss: 1.1138148
Test set: Average loss: 1.5061, Accuracy: 1755/5000 (35%)
[epoch 11] loss: 1.1108701
Test set: Average loss: 1.5050, Accuracy: 1755/5000 (35%)
[epoch 12] loss: 1.1303642
Epoch 11: reducing learning rate of group 0 to 5.0000e-07.
Test set: Average loss: 1.5039, Accuracy: 1756/5000 (35%)
[epoch 13] loss: 1.1086106
Test set: Average loss: 1.5038, Accuracy: 1755/5000 (35%)
[epoch 14] loss: 1.1433408
Epoch 13: reducing learning rate of group 0 to 5.0000e-08.
Test set: Average loss: 1.5037, Accuracy: 1755/5000 (35%)
[epoch 15] loss: 1.0873499
Test set: Average loss: 1.5037, Accuracy: 1755/5000 (35%)
[epoch 16] loss: 1.0724272
Test set: Average loss: 1.5037, Accuracy: 1755/5000 (35%)
[epoch 17] loss: 1.1919075
Epoch 16: reducing learning rate of group 0 to 5.0000e-09.
Test set: Average loss: 1.5037, Accuracy: 1755/5000 (35%)
[epoch 18] loss: 1.0836716
Epoch 17: reducing learning rate of group 0 to 5.0000e-10.
Test set: Average loss: 1.5037, Accuracy: 1755/5000 (35%)
[epoch 19] loss: 1.2073099
Epoch 18: reducing learning rate of group 0 to 5.0000e-11.
Test set: Average loss: 1.5037, Accuracy: 1755/5000 (35%)
[epoch 20] loss: 1.1513188
Epoch 19: reducing learning rate of group 0 to 5.0000e-12.
Test set: Average loss: 1.5037, Accuracy: 1755/5000 (35%)
[epoch 21] loss: 1.1226788
Epoch 20: reducing learning rate of group 0 to 5.0000e-13.
Test set: Average loss: 1.5037, Accuracy: 1755/5000 (35%)
[epoch 22] loss: 1.1728562
Epoch 21: reducing learning rate of group 0 to 5.0000e-14.
Test set: Average loss: 1.5037, Accuracy: 1755/5000 (35%)
[epoch 23] loss: 1.1181915
Epoch 22: reducing learning rate of group 0 to 5.0000e-15.
Test set: Average loss: 1.5037, Accuracy: 1755/5000 (35%)
[epoch 24] loss: 1.0611495
Test set: Average loss: 1.5037, Accuracy: 1755/5000 (35%)
[epoch 25] loss: 1.0735085
Epoch 24: reducing learning rate of group 0 to 5.0000e-16.
Test set: Average loss: 1.5037, Accuracy: 1755/5000 (35%)
Validation:
Test set: Average loss: 1.5039, Accuracy: 1756/5000 (35%)
Test
Test set: Average loss: 1.5060, Accuracy: 1732/5000 (35%)
Test set: Average loss: 1.1159, Accuracy: 65/100 (65%)
250
## seed: 11
Validation accuracy before training:
Test set: Average loss: 1.7479, Accuracy: 790/5000 (16%)
[epoch 1] loss: 1.6364579
Test set: Average loss: 1.5834, Accuracy: 1418/5000 (28%)
[epoch 2] loss: 1.4458438
Test set: Average loss: 1.4833, Accuracy: 1837/5000 (37%)
[epoch 3] loss: 1.3188215
Test set: Average loss: 1.4240, Accuracy: 2103/5000 (42%)
[epoch 4] loss: 1.2326703
Test set: Average loss: 1.3807, Accuracy: 2287/5000 (46%)
[epoch 5] loss: 1.1565848
Test set: Average loss: 1.3511, Accuracy: 2401/5000 (48%)
[epoch 6] loss: 1.0939902
Test set: Average loss: 1.3300, Accuracy: 2495/5000 (50%)
[epoch 7] loss: 1.0402002
Test set: Average loss: 1.3118, Accuracy: 2535/5000 (51%)
[epoch 8] loss: 0.9951602
Test set: Average loss: 1.2960, Accuracy: 2579/5000 (52%)
[epoch 9] loss: 0.9508549
Test set: Average loss: 1.2847, Accuracy: 2597/5000 (52%)
[epoch 10] loss: 0.9115086
Test set: Average loss: 1.2747, Accuracy: 2626/5000 (53%)
[epoch 11] loss: 0.8771372
Test set: Average loss: 1.2666, Accuracy: 2652/5000 (53%)
[epoch 12] loss: 0.8464719
Test set: Average loss: 1.2588, Accuracy: 2672/5000 (53%)
[epoch 13] loss: 0.8143763
Test set: Average loss: 1.2537, Accuracy: 2680/5000 (54%)
[epoch 14] loss: 0.7829064
Test set: Average loss: 1.2482, Accuracy: 2693/5000 (54%)
[epoch 15] loss: 0.7607510
Test set: Average loss: 1.2432, Accuracy: 2707/5000 (54%)
[epoch 16] loss: 0.7362138
Test set: Average loss: 1.2369, Accuracy: 2724/5000 (54%)
[epoch 17] loss: 0.7127340
Test set: Average loss: 1.2348, Accuracy: 2727/5000 (55%)
[epoch 18] loss: 0.6931886
Test set: Average loss: 1.2321, Accuracy: 2724/5000 (54%)
[epoch 19] loss: 0.6701476
Test set: Average loss: 1.2285, Accuracy: 2740/5000 (55%)
[epoch 20] loss: 0.6503757
Test set: Average loss: 1.2248, Accuracy: 2753/5000 (55%)
[epoch 21] loss: 0.6319599
Test set: Average loss: 1.2233, Accuracy: 2743/5000 (55%)
[epoch 22] loss: 0.6159949
Test set: Average loss: 1.2226, Accuracy: 2738/5000 (55%)
[epoch 23] loss: 0.5981089
Test set: Average loss: 1.2179, Accuracy: 2748/5000 (55%)
[epoch 24] loss: 0.5828701
Test set: Average loss: 1.2157, Accuracy: 2757/5000 (55%)
[epoch 25] loss: 0.5686970
Test set: Average loss: 1.2149, Accuracy: 2746/5000 (55%)
Validation:
Test set: Average loss: 1.2157, Accuracy: 2757/5000 (55%)
Test
Test set: Average loss: 1.2214, Accuracy: 2710/5000 (54%)
Test set: Average loss: 0.5721, Accuracy: 241/250 (96%)
## seed: 12
Validation accuracy before training:
Test set: Average loss: 1.6429, Accuracy: 1085/5000 (22%)
[epoch 1] loss: 1.6372770
Test set: Average loss: 1.5420, Accuracy: 1663/5000 (33%)
[epoch 2] loss: 1.4742569
Test set: Average loss: 1.4901, Accuracy: 1885/5000 (38%)
[epoch 3] loss: 1.3712609
Test set: Average loss: 1.4524, Accuracy: 2001/5000 (40%)
[epoch 4] loss: 1.2898239
Test set: Average loss: 1.4216, Accuracy: 2095/5000 (42%)
[epoch 5] loss: 1.2192801
Test set: Average loss: 1.3950, Accuracy: 2148/5000 (43%)
[epoch 6] loss: 1.1581087
Test set: Average loss: 1.3719, Accuracy: 2221/5000 (44%)
[epoch 7] loss: 1.1063176
Test set: Average loss: 1.3549, Accuracy: 2269/5000 (45%)
[epoch 8] loss: 1.0597103
Test set: Average loss: 1.3388, Accuracy: 2321/5000 (46%)
[epoch 9] loss: 1.0149058
Test set: Average loss: 1.3266, Accuracy: 2368/5000 (47%)
[epoch 10] loss: 0.9794450
Test set: Average loss: 1.3154, Accuracy: 2399/5000 (48%)
[epoch 11] loss: 0.9428504
Test set: Average loss: 1.3056, Accuracy: 2432/5000 (49%)
[epoch 12] loss: 0.9086186
Test set: Average loss: 1.2963, Accuracy: 2476/5000 (50%)
[epoch 13] loss: 0.8794623
Test set: Average loss: 1.2883, Accuracy: 2511/5000 (50%)
[epoch 14] loss: 0.8517294
Test set: Average loss: 1.2808, Accuracy: 2546/5000 (51%)
[epoch 15] loss: 0.8244827
Test set: Average loss: 1.2761, Accuracy: 2547/5000 (51%)
[epoch 16] loss: 0.7998544
Test set: Average loss: 1.2703, Accuracy: 2556/5000 (51%)
[epoch 17] loss: 0.7784127
Test set: Average loss: 1.2652, Accuracy: 2570/5000 (51%)
[epoch 18] loss: 0.7562502
Test set: Average loss: 1.2608, Accuracy: 2586/5000 (52%)
[epoch 19] loss: 0.7339369
Test set: Average loss: 1.2557, Accuracy: 2607/5000 (52%)
[epoch 20] loss: 0.7171605
Test set: Average loss: 1.2508, Accuracy: 2619/5000 (52%)
[epoch 21] loss: 0.6968134
Test set: Average loss: 1.2459, Accuracy: 2628/5000 (53%)
[epoch 22] loss: 0.6760505
Test set: Average loss: 1.2435, Accuracy: 2635/5000 (53%)
[epoch 23] loss: 0.6600400
Test set: Average loss: 1.2412, Accuracy: 2637/5000 (53%)
[epoch 24] loss: 0.6443154
Test set: Average loss: 1.2369, Accuracy: 2644/5000 (53%)
[epoch 25] loss: 0.6274928
Test set: Average loss: 1.2331, Accuracy: 2663/5000 (53%)
Validation:
Test set: Average loss: 1.2331, Accuracy: 2663/5000 (53%)
Test
Test set: Average loss: 1.2287, Accuracy: 2618/5000 (52%)
Test set: Average loss: 0.6165, Accuracy: 241/250 (96%)
## seed: 13
Validation accuracy before training:
Test set: Average loss: 1.5421, Accuracy: 1387/5000 (28%)
[epoch 1] loss: 1.4822321
Test set: Average loss: 1.4449, Accuracy: 2088/5000 (42%)
[epoch 2] loss: 1.3277549
Test set: Average loss: 1.3866, Accuracy: 2333/5000 (47%)
[epoch 3] loss: 1.2250025
Test set: Average loss: 1.3509, Accuracy: 2504/5000 (50%)
[epoch 4] loss: 1.1471872
Test set: Average loss: 1.3240, Accuracy: 2549/5000 (51%)
[epoch 5] loss: 1.0854852
Test set: Average loss: 1.3055, Accuracy: 2598/5000 (52%)
[epoch 6] loss: 1.0294102
Test set: Average loss: 1.2912, Accuracy: 2629/5000 (53%)
[epoch 7] loss: 0.9843421
Test set: Average loss: 1.2786, Accuracy: 2664/5000 (53%)
[epoch 8] loss: 0.9446198
Test set: Average loss: 1.2684, Accuracy: 2692/5000 (54%)
[epoch 9] loss: 0.9062902
Test set: Average loss: 1.2608, Accuracy: 2717/5000 (54%)
[epoch 10] loss: 0.8728951
Test set: Average loss: 1.2538, Accuracy: 2715/5000 (54%)
[epoch 11] loss: 0.8424622
Test set: Average loss: 1.2474, Accuracy: 2715/5000 (54%)
[epoch 12] loss: 0.8163698
Test set: Average loss: 1.2421, Accuracy: 2726/5000 (55%)
[epoch 13] loss: 0.7883188
Test set: Average loss: 1.2368, Accuracy: 2730/5000 (55%)
[epoch 14] loss: 0.7638986
Test set: Average loss: 1.2332, Accuracy: 2727/5000 (55%)
[epoch 15] loss: 0.7408750
Test set: Average loss: 1.2287, Accuracy: 2737/5000 (55%)
[epoch 16] loss: 0.7190836
Test set: Average loss: 1.2249, Accuracy: 2732/5000 (55%)
[epoch 17] loss: 0.7008095
Test set: Average loss: 1.2222, Accuracy: 2734/5000 (55%)
[epoch 18] loss: 0.6820299
Test set: Average loss: 1.2195, Accuracy: 2733/5000 (55%)
[epoch 19] loss: 0.6664272
Test set: Average loss: 1.2163, Accuracy: 2736/5000 (55%)
[epoch 20] loss: 0.6498871
Test set: Average loss: 1.2147, Accuracy: 2740/5000 (55%)
[epoch 21] loss: 0.6320939
Test set: Average loss: 1.2126, Accuracy: 2736/5000 (55%)
[epoch 22] loss: 0.6146292
Test set: Average loss: 1.2095, Accuracy: 2745/5000 (55%)
[epoch 23] loss: 0.6000916
Test set: Average loss: 1.2075, Accuracy: 2746/5000 (55%)
[epoch 24] loss: 0.5880451
Test set: Average loss: 1.2060, Accuracy: 2744/5000 (55%)
[epoch 25] loss: 0.5726275
Test set: Average loss: 1.2034, Accuracy: 2742/5000 (55%)
Validation:
Test set: Average loss: 1.2075, Accuracy: 2746/5000 (55%)
Test
Test set: Average loss: 1.2235, Accuracy: 2724/5000 (54%)
Test set: Average loss: 0.5909, Accuracy: 245/250 (98%)
500
## seed: 11
Validation accuracy before training:
Test set: Average loss: 1.6367, Accuracy: 951/5000 (19%)
[epoch 1] loss: 1.5772884
Test set: Average loss: 1.4801, Accuracy: 1671/5000 (33%)
[epoch 2] loss: 1.3934142
Test set: Average loss: 1.4045, Accuracy: 1966/5000 (39%)
[epoch 3] loss: 1.2832063
Test set: Average loss: 1.3588, Accuracy: 2143/5000 (43%)
[epoch 4] loss: 1.2119827
Test set: Average loss: 1.3266, Accuracy: 2251/5000 (45%)
[epoch 5] loss: 1.1520777
Test set: Average loss: 1.3003, Accuracy: 2356/5000 (47%)
[epoch 6] loss: 1.0926072
Test set: Average loss: 1.2859, Accuracy: 2357/5000 (47%)
[epoch 7] loss: 1.0503689
Test set: Average loss: 1.2701, Accuracy: 2442/5000 (49%)
[epoch 8] loss: 1.0044910
Test set: Average loss: 1.2561, Accuracy: 2506/5000 (50%)
[epoch 9] loss: 0.9639251
Test set: Average loss: 1.2464, Accuracy: 2521/5000 (50%)
[epoch 10] loss: 0.9307975
Test set: Average loss: 1.2375, Accuracy: 2564/5000 (51%)
[epoch 11] loss: 0.8976052
Test set: Average loss: 1.2281, Accuracy: 2578/5000 (52%)
[epoch 12] loss: 0.8737658
Test set: Average loss: 1.2216, Accuracy: 2596/5000 (52%)
[epoch 13] loss: 0.8430333
Test set: Average loss: 1.2163, Accuracy: 2606/5000 (52%)
[epoch 14] loss: 0.8092761
Test set: Average loss: 1.2115, Accuracy: 2598/5000 (52%)
[epoch 15] loss: 0.7881913
Test set: Average loss: 1.2053, Accuracy: 2617/5000 (52%)
[epoch 16] loss: 0.7620767
Test set: Average loss: 1.2008, Accuracy: 2627/5000 (53%)
[epoch 17] loss: 0.7358388
Test set: Average loss: 1.1963, Accuracy: 2643/5000 (53%)
[epoch 18] loss: 0.7123548
Test set: Average loss: 1.1922, Accuracy: 2663/5000 (53%)
[epoch 19] loss: 0.6937920
Test set: Average loss: 1.1879, Accuracy: 2665/5000 (53%)
[epoch 20] loss: 0.6754519
Test set: Average loss: 1.1835, Accuracy: 2688/5000 (54%)
[epoch 21] loss: 0.6546864
Test set: Average loss: 1.1824, Accuracy: 2688/5000 (54%)
[epoch 22] loss: 0.6365101
Test set: Average loss: 1.1785, Accuracy: 2701/5000 (54%)
[epoch 23] loss: 0.6150131
Test set: Average loss: 1.1763, Accuracy: 2696/5000 (54%)
[epoch 24] loss: 0.5957284
Test set: Average loss: 1.1721, Accuracy: 2716/5000 (54%)
[epoch 25] loss: 0.5806483
Test set: Average loss: 1.1711, Accuracy: 2721/5000 (54%)
Validation:
Test set: Average loss: 1.1711, Accuracy: 2721/5000 (54%)
Test
Test set: Average loss: 1.1806, Accuracy: 2736/5000 (55%)
Test set: Average loss: 0.5670, Accuracy: 479/500 (96%)
## seed: 12
Validation accuracy before training:
Test set: Average loss: 1.7000, Accuracy: 794/5000 (16%)
[epoch 1] loss: 1.6334470
Test set: Average loss: 1.5459, Accuracy: 1535/5000 (31%)
[epoch 2] loss: 1.4334949
Test set: Average loss: 1.4456, Accuracy: 1975/5000 (40%)
[epoch 3] loss: 1.2939105
Test set: Average loss: 1.3801, Accuracy: 2222/5000 (44%)
[epoch 4] loss: 1.1965493
Test set: Average loss: 1.3404, Accuracy: 2367/5000 (47%)
[epoch 5] loss: 1.1239965
Test set: Average loss: 1.3102, Accuracy: 2474/5000 (49%)
[epoch 6] loss: 1.0634008
Test set: Average loss: 1.2886, Accuracy: 2541/5000 (51%)
[epoch 7] loss: 1.0110994
Test set: Average loss: 1.2736, Accuracy: 2565/5000 (51%)
[epoch 8] loss: 0.9652888
Test set: Average loss: 1.2588, Accuracy: 2613/5000 (52%)
[epoch 9] loss: 0.9241546
Test set: Average loss: 1.2480, Accuracy: 2644/5000 (53%)
[epoch 10] loss: 0.8848453
Test set: Average loss: 1.2370, Accuracy: 2685/5000 (54%)
[epoch 11] loss: 0.8523882
Test set: Average loss: 1.2291, Accuracy: 2708/5000 (54%)
[epoch 12] loss: 0.8212899
Test set: Average loss: 1.2181, Accuracy: 2746/5000 (55%)
[epoch 13] loss: 0.7938748
Test set: Average loss: 1.2150, Accuracy: 2739/5000 (55%)
[epoch 14] loss: 0.7601960
Test set: Average loss: 1.2077, Accuracy: 2756/5000 (55%)
[epoch 15] loss: 0.7360415
Test set: Average loss: 1.1979, Accuracy: 2776/5000 (56%)
[epoch 16] loss: 0.7102153
Test set: Average loss: 1.1960, Accuracy: 2771/5000 (55%)
[epoch 17] loss: 0.6860161
Test set: Average loss: 1.1909, Accuracy: 2788/5000 (56%)
[epoch 18] loss: 0.6632830
Test set: Average loss: 1.1831, Accuracy: 2796/5000 (56%)
[epoch 19] loss: 0.6393798
Test set: Average loss: 1.1804, Accuracy: 2814/5000 (56%)
[epoch 20] loss: 0.6187211
Test set: Average loss: 1.1788, Accuracy: 2816/5000 (56%)
[epoch 21] loss: 0.6003212
Test set: Average loss: 1.1733, Accuracy: 2822/5000 (56%)
[epoch 22] loss: 0.5816682
Test set: Average loss: 1.1679, Accuracy: 2843/5000 (57%)
[epoch 23] loss: 0.5650746
Test set: Average loss: 1.1683, Accuracy: 2822/5000 (56%)
[epoch 24] loss: 0.5462396
Test set: Average loss: 1.1636, Accuracy: 2847/5000 (57%)
[epoch 25] loss: 0.5279690
Test set: Average loss: 1.1602, Accuracy: 2857/5000 (57%)
Validation:
Test set: Average loss: 1.1602, Accuracy: 2857/5000 (57%)
Test
Test set: Average loss: 1.1653, Accuracy: 2812/5000 (56%)
Test set: Average loss: 0.5153, Accuracy: 486/500 (97%)
## seed: 13
Validation accuracy before training:
Test set: Average loss: 1.6774, Accuracy: 821/5000 (16%)
[epoch 1] loss: 1.5519174
Test set: Average loss: 1.4811, Accuracy: 1767/5000 (35%)
[epoch 2] loss: 1.3217851
Test set: Average loss: 1.3921, Accuracy: 2002/5000 (40%)
[epoch 3] loss: 1.1946582
Test set: Average loss: 1.3369, Accuracy: 2204/5000 (44%)
[epoch 4] loss: 1.1124608
Test set: Average loss: 1.3036, Accuracy: 2341/5000 (47%)
[epoch 5] loss: 1.0444212
Test set: Average loss: 1.2776, Accuracy: 2424/5000 (48%)
[epoch 6] loss: 0.9936139
Test set: Average loss: 1.2624, Accuracy: 2477/5000 (50%)
[epoch 7] loss: 0.9476327
Test set: Average loss: 1.2440, Accuracy: 2582/5000 (52%)
[epoch 8] loss: 0.9133164
Test set: Average loss: 1.2326, Accuracy: 2614/5000 (52%)
[epoch 9] loss: 0.8722838
Test set: Average loss: 1.2220, Accuracy: 2646/5000 (53%)
[epoch 10] loss: 0.8398193
Test set: Average loss: 1.2141, Accuracy: 2655/5000 (53%)
[epoch 11] loss: 0.8075857
Test set: Average loss: 1.2045, Accuracy: 2682/5000 (54%)
[epoch 12] loss: 0.7772317
Test set: Average loss: 1.1989, Accuracy: 2702/5000 (54%)
[epoch 13] loss: 0.7506379
Test set: Average loss: 1.1908, Accuracy: 2730/5000 (55%)
[epoch 14] loss: 0.7301091
Test set: Average loss: 1.1840, Accuracy: 2743/5000 (55%)
[epoch 15] loss: 0.7027234
Test set: Average loss: 1.1815, Accuracy: 2739/5000 (55%)
[epoch 16] loss: 0.6804975
Test set: Average loss: 1.1748, Accuracy: 2769/5000 (55%)
[epoch 17] loss: 0.6578907
Test set: Average loss: 1.1709, Accuracy: 2759/5000 (55%)
[epoch 18] loss: 0.6352781
Test set: Average loss: 1.1665, Accuracy: 2776/5000 (56%)
[epoch 19] loss: 0.6161252
Test set: Average loss: 1.1632, Accuracy: 2783/5000 (56%)
[epoch 20] loss: 0.5987277
Test set: Average loss: 1.1588, Accuracy: 2798/5000 (56%)
[epoch 21] loss: 0.5805355
Test set: Average loss: 1.1552, Accuracy: 2795/5000 (56%)
[epoch 22] loss: 0.5614904
Test set: Average loss: 1.1530, Accuracy: 2796/5000 (56%)
[epoch 23] loss: 0.5432894
Test set: Average loss: 1.1487, Accuracy: 2807/5000 (56%)
[epoch 24] loss: 0.5279867
Test set: Average loss: 1.1457, Accuracy: 2811/5000 (56%)
[epoch 25] loss: 0.5161464
Test set: Average loss: 1.1440, Accuracy: 2810/5000 (56%)
Validation:
Test set: Average loss: 1.1457, Accuracy: 2811/5000 (56%)
Test
Test set: Average loss: 1.1659, Accuracy: 2777/5000 (56%)
Test set: Average loss: 0.5160, Accuracy: 484/500 (97%)
750
## seed: 11
Validation accuracy before training:
Test set: Average loss: 1.6681, Accuracy: 889/5000 (18%)
[epoch 1] loss: 1.5458193
Test set: Average loss: 1.4423, Accuracy: 2146/5000 (43%)
[epoch 2] loss: 1.3011778
Test set: Average loss: 1.3450, Accuracy: 2408/5000 (48%)
[epoch 3] loss: 1.1750859
Test set: Average loss: 1.2939, Accuracy: 2572/5000 (51%)
[epoch 4] loss: 1.0945770
Test set: Average loss: 1.2571, Accuracy: 2676/5000 (54%)
[epoch 5] loss: 1.0248680
Test set: Average loss: 1.2320, Accuracy: 2743/5000 (55%)
[epoch 6] loss: 0.9713350
Test set: Average loss: 1.2131, Accuracy: 2772/5000 (55%)
[epoch 7] loss: 0.9175918
Test set: Average loss: 1.1963, Accuracy: 2813/5000 (56%)
[epoch 8] loss: 0.8692914
Test set: Average loss: 1.1805, Accuracy: 2844/5000 (57%)
[epoch 9] loss: 0.8318329
Test set: Average loss: 1.1704, Accuracy: 2850/5000 (57%)
[epoch 10] loss: 0.7948275
Test set: Average loss: 1.1591, Accuracy: 2865/5000 (57%)
[epoch 11] loss: 0.7600915
Test set: Average loss: 1.1497, Accuracy: 2899/5000 (58%)
[epoch 12] loss: 0.7266578
Test set: Average loss: 1.1426, Accuracy: 2888/5000 (58%)
[epoch 13] loss: 0.6966454
Test set: Average loss: 1.1366, Accuracy: 2898/5000 (58%)
[epoch 14] loss: 0.6732783
Test set: Average loss: 1.1282, Accuracy: 2932/5000 (59%)
[epoch 15] loss: 0.6437628
Test set: Average loss: 1.1235, Accuracy: 2929/5000 (59%)
[epoch 16] loss: 0.6125208
Test set: Average loss: 1.1181, Accuracy: 2929/5000 (59%)
[epoch 17] loss: 0.5903883
Test set: Average loss: 1.1157, Accuracy: 2931/5000 (59%)
[epoch 18] loss: 0.5684358
Test set: Average loss: 1.1078, Accuracy: 2938/5000 (59%)
[epoch 19] loss: 0.5417069
Test set: Average loss: 1.1030, Accuracy: 2950/5000 (59%)
[epoch 20] loss: 0.5218646
Test set: Average loss: 1.1025, Accuracy: 2937/5000 (59%)
[epoch 21] loss: 0.5048397
Test set: Average loss: 1.0971, Accuracy: 2948/5000 (59%)
[epoch 22] loss: 0.4794222
Test set: Average loss: 1.0948, Accuracy: 2947/5000 (59%)
[epoch 23] loss: 0.4599532
Test set: Average loss: 1.0908, Accuracy: 2952/5000 (59%)
[epoch 24] loss: 0.4412510
Test set: Average loss: 1.0871, Accuracy: 2961/5000 (59%)
[epoch 25] loss: 0.4250015
Test set: Average loss: 1.0848, Accuracy: 2964/5000 (59%)
Validation:
Test set: Average loss: 1.0848, Accuracy: 2964/5000 (59%)
Test
Test set: Average loss: 1.0947, Accuracy: 2932/5000 (59%)
Test set: Average loss: 0.4091, Accuracy: 730/750 (97%)
## seed: 12
Validation accuracy before training:
Test set: Average loss: 1.6928, Accuracy: 677/5000 (14%)
[epoch 1] loss: 1.5966291
Test set: Average loss: 1.4538, Accuracy: 1829/5000 (37%)
[epoch 2] loss: 1.3695628
Test set: Average loss: 1.3561, Accuracy: 2298/5000 (46%)
[epoch 3] loss: 1.2541902
Test set: Average loss: 1.3019, Accuracy: 2430/5000 (49%)
[epoch 4] loss: 1.1693923
Test set: Average loss: 1.2635, Accuracy: 2542/5000 (51%)
[epoch 5] loss: 1.0978354
Test set: Average loss: 1.2344, Accuracy: 2637/5000 (53%)
[epoch 6] loss: 1.0405187
Test set: Average loss: 1.2138, Accuracy: 2686/5000 (54%)
[epoch 7] loss: 0.9822968
Test set: Average loss: 1.1983, Accuracy: 2732/5000 (55%)
[epoch 8] loss: 0.9417735
Test set: Average loss: 1.1821, Accuracy: 2784/5000 (56%)
[epoch 9] loss: 0.8964434
Test set: Average loss: 1.1724, Accuracy: 2803/5000 (56%)
[epoch 10] loss: 0.8609797
Test set: Average loss: 1.1625, Accuracy: 2811/5000 (56%)
[epoch 11] loss: 0.8320119
Test set: Average loss: 1.1526, Accuracy: 2858/5000 (57%)
[epoch 12] loss: 0.7956342
Test set: Average loss: 1.1459, Accuracy: 2849/5000 (57%)
[epoch 13] loss: 0.7710310
Test set: Average loss: 1.1395, Accuracy: 2874/5000 (57%)
[epoch 14] loss: 0.7420855
Test set: Average loss: 1.1327, Accuracy: 2900/5000 (58%)
[epoch 15] loss: 0.7165253
Test set: Average loss: 1.1269, Accuracy: 2881/5000 (58%)
[epoch 16] loss: 0.6860129
Test set: Average loss: 1.1225, Accuracy: 2907/5000 (58%)
[epoch 17] loss: 0.6673546
Test set: Average loss: 1.1182, Accuracy: 2934/5000 (59%)
[epoch 18] loss: 0.6377273
Test set: Average loss: 1.1122, Accuracy: 2923/5000 (58%)
[epoch 19] loss: 0.6134816
Test set: Average loss: 1.1112, Accuracy: 2939/5000 (59%)
[epoch 20] loss: 0.5924959
Test set: Average loss: 1.1051, Accuracy: 2944/5000 (59%)
[epoch 21] loss: 0.5761947
Test set: Average loss: 1.1001, Accuracy: 2962/5000 (59%)
[epoch 22] loss: 0.5532385
Test set: Average loss: 1.0988, Accuracy: 2977/5000 (60%)
[epoch 23] loss: 0.5370638
Test set: Average loss: 1.0968, Accuracy: 2964/5000 (59%)
[epoch 24] loss: 0.5109736
Test set: Average loss: 1.0944, Accuracy: 2976/5000 (60%)
[epoch 25] loss: 0.5032352
Test set: Average loss: 1.0916, Accuracy: 2986/5000 (60%)
Validation:
Test set: Average loss: 1.0916, Accuracy: 2986/5000 (60%)
Test
Test set: Average loss: 1.0986, Accuracy: 2958/5000 (59%)
Test set: Average loss: 0.4798, Accuracy: 729/750 (97%)
## seed: 13
Validation accuracy before training:
Test set: Average loss: 1.7175, Accuracy: 706/5000 (14%)
[epoch 1] loss: 1.5389803
Test set: Average loss: 1.4162, Accuracy: 2067/5000 (41%)
[epoch 2] loss: 1.2909448
Test set: Average loss: 1.3263, Accuracy: 2274/5000 (45%)
[epoch 3] loss: 1.1693444
Test set: Average loss: 1.2772, Accuracy: 2402/5000 (48%)
[epoch 4] loss: 1.0936243
Test set: Average loss: 1.2444, Accuracy: 2516/5000 (50%)
[epoch 5] loss: 1.0392169
Test set: Average loss: 1.2203, Accuracy: 2553/5000 (51%)
[epoch 6] loss: 0.9806271
Test set: Average loss: 1.2008, Accuracy: 2628/5000 (53%)
[epoch 7] loss: 0.9354460
Test set: Average loss: 1.1873, Accuracy: 2670/5000 (53%)
[epoch 8] loss: 0.8977381
Test set: Average loss: 1.1725, Accuracy: 2728/5000 (55%)
[epoch 9] loss: 0.8579681
Test set: Average loss: 1.1618, Accuracy: 2759/5000 (55%)
[epoch 10] loss: 0.8281570
Test set: Average loss: 1.1520, Accuracy: 2797/5000 (56%)
[epoch 11] loss: 0.7885153
Test set: Average loss: 1.1438, Accuracy: 2805/5000 (56%)
[epoch 12] loss: 0.7607218
Test set: Average loss: 1.1367, Accuracy: 2839/5000 (57%)
[epoch 13] loss: 0.7359616
Test set: Average loss: 1.1311, Accuracy: 2844/5000 (57%)
[epoch 14] loss: 0.7041998
Test set: Average loss: 1.1237, Accuracy: 2867/5000 (57%)
[epoch 15] loss: 0.6813932
Test set: Average loss: 1.1199, Accuracy: 2868/5000 (57%)
[epoch 16] loss: 0.6585575
Test set: Average loss: 1.1141, Accuracy: 2895/5000 (58%)
[epoch 17] loss: 0.6307186
Test set: Average loss: 1.1114, Accuracy: 2890/5000 (58%)
[epoch 18] loss: 0.6045770
Test set: Average loss: 1.1051, Accuracy: 2919/5000 (58%)
[epoch 19] loss: 0.5861380
Test set: Average loss: 1.1002, Accuracy: 2923/5000 (58%)
[epoch 20] loss: 0.5637936
Test set: Average loss: 1.0952, Accuracy: 2937/5000 (59%)
[epoch 21] loss: 0.5452047
Test set: Average loss: 1.0929, Accuracy: 2946/5000 (59%)
[epoch 22] loss: 0.5245545
Test set: Average loss: 1.0910, Accuracy: 2953/5000 (59%)
[epoch 23] loss: 0.5072557
Test set: Average loss: 1.0890, Accuracy: 2947/5000 (59%)
[epoch 24] loss: 0.4890643
Test set: Average loss: 1.0847, Accuracy: 2961/5000 (59%)
[epoch 25] loss: 0.4667449
Test set: Average loss: 1.0818, Accuracy: 2961/5000 (59%)
Validation:
Test set: Average loss: 1.0818, Accuracy: 2961/5000 (59%)
Test
Test set: Average loss: 1.0953, Accuracy: 2911/5000 (58%)
Test set: Average loss: 0.4526, Accuracy: 724/750 (97%)
1000
## seed: 11
Validation accuracy before training:
Test set: Average loss: 1.5939, Accuracy: 1108/5000 (22%)
[epoch 1] loss: 1.4496094
Test set: Average loss: 1.3579, Accuracy: 2348/5000 (47%)
[epoch 2] loss: 1.2329989
Test set: Average loss: 1.2831, Accuracy: 2560/5000 (51%)
[epoch 3] loss: 1.1262669
Test set: Average loss: 1.2390, Accuracy: 2715/5000 (54%)
[epoch 4] loss: 1.0585103
Test set: Average loss: 1.2108, Accuracy: 2789/5000 (56%)
[epoch 5] loss: 0.9840545
Test set: Average loss: 1.1883, Accuracy: 2863/5000 (57%)
[epoch 6] loss: 0.9424134
Test set: Average loss: 1.1711, Accuracy: 2877/5000 (58%)
[epoch 7] loss: 0.8908989
Test set: Average loss: 1.1574, Accuracy: 2927/5000 (59%)
[epoch 8] loss: 0.8523251
Test set: Average loss: 1.1464, Accuracy: 2946/5000 (59%)
[epoch 9] loss: 0.8220395
Test set: Average loss: 1.1371, Accuracy: 2939/5000 (59%)
[epoch 10] loss: 0.7850444
Test set: Average loss: 1.1260, Accuracy: 2984/5000 (60%)
[epoch 11] loss: 0.7527861
Test set: Average loss: 1.1178, Accuracy: 2988/5000 (60%)
[epoch 12] loss: 0.7166272
Test set: Average loss: 1.1179, Accuracy: 2977/5000 (60%)
[epoch 13] loss: 0.6889439
Test set: Average loss: 1.1026, Accuracy: 3010/5000 (60%)
[epoch 14] loss: 0.6675603
Test set: Average loss: 1.0967, Accuracy: 2997/5000 (60%)
[epoch 15] loss: 0.6327247
Test set: Average loss: 1.0911, Accuracy: 3027/5000 (61%)
[epoch 16] loss: 0.6048499
Test set: Average loss: 1.0858, Accuracy: 3031/5000 (61%)
[epoch 17] loss: 0.5831640
Test set: Average loss: 1.0816, Accuracy: 3037/5000 (61%)
[epoch 18] loss: 0.5584846
Test set: Average loss: 1.0778, Accuracy: 3035/5000 (61%)
[epoch 19] loss: 0.5369391
Test set: Average loss: 1.0767, Accuracy: 3045/5000 (61%)
[epoch 20] loss: 0.5137930
Test set: Average loss: 1.0738, Accuracy: 3016/5000 (60%)
[epoch 21] loss: 0.4927960
Test set: Average loss: 1.0684, Accuracy: 3045/5000 (61%)
[epoch 22] loss: 0.4719328
Test set: Average loss: 1.0639, Accuracy: 3053/5000 (61%)
[epoch 23] loss: 0.4503369
Test set: Average loss: 1.0631, Accuracy: 3041/5000 (61%)
[epoch 24] loss: 0.4336279
Test set: Average loss: 1.0569, Accuracy: 3086/5000 (62%)
[epoch 25] loss: 0.4137537
Test set: Average loss: 1.0561, Accuracy: 3062/5000 (61%)
Validation:
Test set: Average loss: 1.0569, Accuracy: 3086/5000 (62%)
Test
Test set: Average loss: 1.0645, Accuracy: 3049/5000 (61%)
Test set: Average loss: 0.4180, Accuracy: 980/1000 (98%)
## seed: 12
Validation accuracy before training:
Test set: Average loss: 1.5902, Accuracy: 1184/5000 (24%)
[epoch 1] loss: 1.4168939
Test set: Average loss: 1.3325, Accuracy: 2357/5000 (47%)
[epoch 2] loss: 1.2011732
Test set: Average loss: 1.2482, Accuracy: 2650/5000 (53%)
[epoch 3] loss: 1.0957012
Test set: Average loss: 1.2033, Accuracy: 2783/5000 (56%)
[epoch 4] loss: 1.0186086
Test set: Average loss: 1.1735, Accuracy: 2855/5000 (57%)
[epoch 5] loss: 0.9462693
Test set: Average loss: 1.1470, Accuracy: 2959/5000 (59%)
[epoch 6] loss: 0.8877944
Test set: Average loss: 1.1330, Accuracy: 3003/5000 (60%)
[epoch 7] loss: 0.8466811
Test set: Average loss: 1.1131, Accuracy: 3034/5000 (61%)
[epoch 8] loss: 0.7958961
Test set: Average loss: 1.1051, Accuracy: 3060/5000 (61%)
[epoch 9] loss: 0.7622538
Test set: Average loss: 1.0883, Accuracy: 3088/5000 (62%)
[epoch 10] loss: 0.7309053
Test set: Average loss: 1.0835, Accuracy: 3092/5000 (62%)
[epoch 11] loss: 0.6891723
Test set: Average loss: 1.0720, Accuracy: 3105/5000 (62%)
[epoch 12] loss: 0.6565583
Test set: Average loss: 1.0637, Accuracy: 3116/5000 (62%)
[epoch 13] loss: 0.6303484
Test set: Average loss: 1.0557, Accuracy: 3129/5000 (63%)
[epoch 14] loss: 0.6091130
Test set: Average loss: 1.0511, Accuracy: 3137/5000 (63%)
[epoch 15] loss: 0.5755338
Test set: Average loss: 1.0514, Accuracy: 3122/5000 (62%)
[epoch 16] loss: 0.5475939
Test set: Average loss: 1.0428, Accuracy: 3147/5000 (63%)
[epoch 17] loss: 0.5180023
Test set: Average loss: 1.0404, Accuracy: 3138/5000 (63%)
[epoch 18] loss: 0.4980304
Test set: Average loss: 1.0351, Accuracy: 3145/5000 (63%)
[epoch 19] loss: 0.4754505
Test set: Average loss: 1.0342, Accuracy: 3151/5000 (63%)
[epoch 20] loss: 0.4559852
Test set: Average loss: 1.0325, Accuracy: 3154/5000 (63%)
[epoch 21] loss: 0.4365083
Test set: Average loss: 1.0232, Accuracy: 3154/5000 (63%)
[epoch 22] loss: 0.4191685
Test set: Average loss: 1.0239, Accuracy: 3153/5000 (63%)
[epoch 23] loss: 0.3937018
Test set: Average loss: 1.0233, Accuracy: 3148/5000 (63%)
[epoch 24] loss: 0.3797806
Test set: Average loss: 1.0185, Accuracy: 3160/5000 (63%)
[epoch 25] loss: 0.3608442
Test set: Average loss: 1.0196, Accuracy: 3136/5000 (63%)
Validation:
Test set: Average loss: 1.0185, Accuracy: 3160/5000 (63%)
Test
Test set: Average loss: 1.0396, Accuracy: 3041/5000 (61%)
Test set: Average loss: 0.3615, Accuracy: 984/1000 (98%)
## seed: 13
Validation accuracy before training:
Test set: Average loss: 1.6656, Accuracy: 1298/5000 (26%)
[epoch 1] loss: 1.4777979
Test set: Average loss: 1.3686, Accuracy: 2285/5000 (46%)
[epoch 2] loss: 1.2367288
Test set: Average loss: 1.2762, Accuracy: 2595/5000 (52%)
[epoch 3] loss: 1.1178266
Test set: Average loss: 1.2266, Accuracy: 2763/5000 (55%)
[epoch 4] loss: 1.0452523
Test set: Average loss: 1.2012, Accuracy: 2812/5000 (56%)
[epoch 5] loss: 0.9854314
Test set: Average loss: 1.1739, Accuracy: 2877/5000 (58%)
[epoch 6] loss: 0.9332650
Test set: Average loss: 1.1588, Accuracy: 2926/5000 (59%)
[epoch 7] loss: 0.8831473
Test set: Average loss: 1.1422, Accuracy: 2965/5000 (59%)
[epoch 8] loss: 0.8463539
Test set: Average loss: 1.1310, Accuracy: 2992/5000 (60%)
[epoch 9] loss: 0.8005825
Test set: Average loss: 1.1256, Accuracy: 2982/5000 (60%)
[epoch 10] loss: 0.7661392
Test set: Average loss: 1.1105, Accuracy: 3011/5000 (60%)
[epoch 11] loss: 0.7352713
Test set: Average loss: 1.1094, Accuracy: 3008/5000 (60%)
[epoch 12] loss: 0.7016972
Test set: Average loss: 1.0965, Accuracy: 3050/5000 (61%)
[epoch 13] loss: 0.6757197
Test set: Average loss: 1.0902, Accuracy: 3090/5000 (62%)
[epoch 14] loss: 0.6399758
Test set: Average loss: 1.0861, Accuracy: 3066/5000 (61%)
[epoch 15] loss: 0.6104457
Test set: Average loss: 1.0792, Accuracy: 3087/5000 (62%)
[epoch 16] loss: 0.5876070
Test set: Average loss: 1.0733, Accuracy: 3107/5000 (62%)
[epoch 17] loss: 0.5632141
Test set: Average loss: 1.0690, Accuracy: 3092/5000 (62%)
[epoch 18] loss: 0.5340148
Test set: Average loss: 1.0706, Accuracy: 3074/5000 (61%)
[epoch 19] loss: 0.5170123
Test set: Average loss: 1.0627, Accuracy: 3096/5000 (62%)
[epoch 20] loss: 0.4883831
Test set: Average loss: 1.0601, Accuracy: 3076/5000 (62%)
[epoch 21] loss: 0.4725629
Test set: Average loss: 1.0560, Accuracy: 3111/5000 (62%)
[epoch 22] loss: 0.4476996
Test set: Average loss: 1.0546, Accuracy: 3098/5000 (62%)
[epoch 23] loss: 0.4294483
Test set: Average loss: 1.0532, Accuracy: 3095/5000 (62%)
[epoch 24] loss: 0.4107914
Test set: Average loss: 1.0504, Accuracy: 3102/5000 (62%)
[epoch 25] loss: 0.3926812
Test set: Average loss: 1.0459, Accuracy: 3102/5000 (62%)
Validation:
Test set: Average loss: 1.0560, Accuracy: 3111/5000 (62%)
Test
Test set: Average loss: 1.0752, Accuracy: 2997/5000 (60%)
Test set: Average loss: 0.4505, Accuracy: 972/1000 (97%)
2500
## seed: 11
Validation accuracy before training:
Test set: Average loss: 1.6969, Accuracy: 1258/5000 (25%)
[epoch 1] loss: 1.4240472
Test set: Average loss: 1.2742, Accuracy: 2578/5000 (52%)
[epoch 2] loss: 1.1639839
Test set: Average loss: 1.1794, Accuracy: 2869/5000 (57%)
[epoch 3] loss: 1.0632533
Test set: Average loss: 1.1407, Accuracy: 2930/5000 (59%)
[epoch 4] loss: 0.9922435
Test set: Average loss: 1.1077, Accuracy: 2983/5000 (60%)
[epoch 5] loss: 0.9359247
Test set: Average loss: 1.0906, Accuracy: 3041/5000 (61%)
[epoch 6] loss: 0.8850238
Test set: Average loss: 1.0683, Accuracy: 3089/5000 (62%)
[epoch 7] loss: 0.8326603
Test set: Average loss: 1.0552, Accuracy: 3115/5000 (62%)
[epoch 8] loss: 0.7939870
Test set: Average loss: 1.0450, Accuracy: 3128/5000 (63%)
[epoch 9] loss: 0.7494014
Test set: Average loss: 1.0299, Accuracy: 3147/5000 (63%)
[epoch 10] loss: 0.7122821
Test set: Average loss: 1.0223, Accuracy: 3172/5000 (63%)
[epoch 11] loss: 0.6750296
Test set: Average loss: 1.0094, Accuracy: 3188/5000 (64%)
[epoch 12] loss: 0.6410558
Test set: Average loss: 0.9996, Accuracy: 3181/5000 (64%)
[epoch 13] loss: 0.6048843
Test set: Average loss: 0.9953, Accuracy: 3188/5000 (64%)
[epoch 14] loss: 0.5699775
Test set: Average loss: 0.9887, Accuracy: 3200/5000 (64%)
[epoch 15] loss: 0.5412060
Test set: Average loss: 0.9843, Accuracy: 3186/5000 (64%)
[epoch 16] loss: 0.5079597
Test set: Average loss: 0.9840, Accuracy: 3187/5000 (64%)
[epoch 17] loss: 0.4798454
Test set: Average loss: 0.9761, Accuracy: 3201/5000 (64%)
[epoch 18] loss: 0.4505472
Test set: Average loss: 0.9826, Accuracy: 3165/5000 (63%)
[epoch 19] loss: 0.4210202
Test set: Average loss: 0.9747, Accuracy: 3187/5000 (64%)
[epoch 20] loss: 0.3956979
Test set: Average loss: 0.9686, Accuracy: 3196/5000 (64%)
[epoch 21] loss: 0.3747854
Test set: Average loss: 0.9690, Accuracy: 3193/5000 (64%)
[epoch 22] loss: 0.3490916
Test set: Average loss: 0.9707, Accuracy: 3194/5000 (64%)
[epoch 23] loss: 0.3268537
Test set: Average loss: 0.9702, Accuracy: 3195/5000 (64%)
[epoch 24] loss: 0.3050848
Test set: Average loss: 0.9818, Accuracy: 3173/5000 (63%)
[epoch 25] loss: 0.2839482
Test set: Average loss: 0.9690, Accuracy: 3202/5000 (64%)
Validation:
Test set: Average loss: 0.9690, Accuracy: 3202/5000 (64%)
Test
Test set: Average loss: 0.9673, Accuracy: 3133/5000 (63%)
Test set: Average loss: 0.2619, Accuracy: 2456/2500 (98%)
## seed: 12
Validation accuracy before training:
Test set: Average loss: 1.5831, Accuracy: 1247/5000 (25%)
[epoch 1] loss: 1.3428147
Test set: Average loss: 1.2460, Accuracy: 2533/5000 (51%)
[epoch 2] loss: 1.1492422
Test set: Average loss: 1.1816, Accuracy: 2733/5000 (55%)
[epoch 3] loss: 1.0591706
Test set: Average loss: 1.1450, Accuracy: 2857/5000 (57%)
[epoch 4] loss: 1.0014033
Test set: Average loss: 1.1235, Accuracy: 2901/5000 (58%)
[epoch 5] loss: 0.9405162
Test set: Average loss: 1.0939, Accuracy: 2982/5000 (60%)
[epoch 6] loss: 0.8954677
Test set: Average loss: 1.0759, Accuracy: 3059/5000 (61%)
[epoch 7] loss: 0.8510358
Test set: Average loss: 1.0591, Accuracy: 3126/5000 (63%)
[epoch 8] loss: 0.8082128
Test set: Average loss: 1.0486, Accuracy: 3131/5000 (63%)
[epoch 9] loss: 0.7683667
Test set: Average loss: 1.0318, Accuracy: 3146/5000 (63%)
[epoch 10] loss: 0.7312093
Test set: Average loss: 1.0245, Accuracy: 3149/5000 (63%)
[epoch 11] loss: 0.6966680
Test set: Average loss: 1.0153, Accuracy: 3172/5000 (63%)
[epoch 12] loss: 0.6622009
Test set: Average loss: 1.0018, Accuracy: 3199/5000 (64%)
[epoch 13] loss: 0.6266503
Test set: Average loss: 0.9917, Accuracy: 3189/5000 (64%)
[epoch 14] loss: 0.5912719
Test set: Average loss: 0.9855, Accuracy: 3212/5000 (64%)
[epoch 15] loss: 0.5589085
Test set: Average loss: 0.9788, Accuracy: 3205/5000 (64%)
[epoch 16] loss: 0.5247805
Test set: Average loss: 0.9719, Accuracy: 3215/5000 (64%)
[epoch 17] loss: 0.5004077
Test set: Average loss: 0.9672, Accuracy: 3218/5000 (64%)
[epoch 18] loss: 0.4678885
Test set: Average loss: 0.9660, Accuracy: 3204/5000 (64%)
[epoch 19] loss: 0.4360741
Test set: Average loss: 0.9562, Accuracy: 3226/5000 (65%)
[epoch 20] loss: 0.4081484
Test set: Average loss: 0.9553, Accuracy: 3232/5000 (65%)
[epoch 21] loss: 0.3844463
Test set: Average loss: 0.9527, Accuracy: 3254/5000 (65%)
[epoch 22] loss: 0.3594924
Test set: Average loss: 0.9515, Accuracy: 3257/5000 (65%)
[epoch 23] loss: 0.3360567
Test set: Average loss: 0.9494, Accuracy: 3241/5000 (65%)
[epoch 24] loss: 0.3135620
Test set: Average loss: 0.9461, Accuracy: 3274/5000 (65%)
[epoch 25] loss: 0.2934100
Test set: Average loss: 0.9460, Accuracy: 3250/5000 (65%)
Validation:
Test set: Average loss: 0.9461, Accuracy: 3274/5000 (65%)
Test
Test set: Average loss: 0.9587, Accuracy: 3207/5000 (64%)
Test set: Average loss: 0.2895, Accuracy: 2449/2500 (98%)
## seed: 13
Validation accuracy before training:
Test set: Average loss: 1.8036, Accuracy: 460/5000 (9%)
[epoch 1] loss: 1.4384980
Test set: Average loss: 1.2948, Accuracy: 2440/5000 (49%)
[epoch 2] loss: 1.2048413
Test set: Average loss: 1.2157, Accuracy: 2738/5000 (55%)
[epoch 3] loss: 1.1146880
Test set: Average loss: 1.1704, Accuracy: 2880/5000 (58%)
[epoch 4] loss: 1.0418033
Test set: Average loss: 1.1434, Accuracy: 2930/5000 (59%)
[epoch 5] loss: 0.9908033
Test set: Average loss: 1.1173, Accuracy: 3004/5000 (60%)
[epoch 6] loss: 0.9435593
Test set: Average loss: 1.1017, Accuracy: 3045/5000 (61%)
[epoch 7] loss: 0.8900528
Test set: Average loss: 1.0860, Accuracy: 3082/5000 (62%)
[epoch 8] loss: 0.8558213
Test set: Average loss: 1.0680, Accuracy: 3115/5000 (62%)
[epoch 9] loss: 0.8144205
Test set: Average loss: 1.0551, Accuracy: 3118/5000 (62%)
[epoch 10] loss: 0.7763833
Test set: Average loss: 1.0429, Accuracy: 3135/5000 (63%)
[epoch 11] loss: 0.7398392
Test set: Average loss: 1.0357, Accuracy: 3150/5000 (63%)
[epoch 12] loss: 0.7006373
Test set: Average loss: 1.0217, Accuracy: 3171/5000 (63%)
[epoch 13] loss: 0.6638629
Test set: Average loss: 1.0165, Accuracy: 3169/5000 (63%)
[epoch 14] loss: 0.6302571
Test set: Average loss: 1.0140, Accuracy: 3167/5000 (63%)
[epoch 15] loss: 0.5946167
Test set: Average loss: 1.0011, Accuracy: 3193/5000 (64%)
[epoch 16] loss: 0.5608185
Test set: Average loss: 0.9973, Accuracy: 3201/5000 (64%)
[epoch 17] loss: 0.5375124
Test set: Average loss: 0.9918, Accuracy: 3195/5000 (64%)
[epoch 18] loss: 0.5063308
Test set: Average loss: 0.9882, Accuracy: 3201/5000 (64%)
[epoch 19] loss: 0.4739428
Test set: Average loss: 0.9907, Accuracy: 3166/5000 (63%)
[epoch 20] loss: 0.4480641
Test set: Average loss: 0.9811, Accuracy: 3208/5000 (64%)
[epoch 21] loss: 0.4182698
Test set: Average loss: 0.9764, Accuracy: 3207/5000 (64%)
[epoch 22] loss: 0.3939155
Test set: Average loss: 0.9754, Accuracy: 3190/5000 (64%)
[epoch 23] loss: 0.3682717
Test set: Average loss: 0.9819, Accuracy: 3179/5000 (64%)
[epoch 24] loss: 0.3424042
Test set: Average loss: 0.9732, Accuracy: 3199/5000 (64%)
[epoch 25] loss: 0.3183416
Test set: Average loss: 0.9764, Accuracy: 3193/5000 (64%)
Validation:
Test set: Average loss: 0.9811, Accuracy: 3208/5000 (64%)
Test
Test set: Average loss: 1.0009, Accuracy: 3162/5000 (63%)
Test set: Average loss: 0.4126, Accuracy: 2343/2500 (94%)
5000
## seed: 11
Validation accuracy before training:
Test set: Average loss: 1.6414, Accuracy: 1090/5000 (22%)
[epoch 1] loss: 1.3176582
Test set: Average loss: 1.1968, Accuracy: 2723/5000 (54%)
[epoch 2] loss: 1.0966342
Test set: Average loss: 1.1139, Accuracy: 2982/5000 (60%)
[epoch 3] loss: 0.9979308
Test set: Average loss: 1.0662, Accuracy: 3078/5000 (62%)
[epoch 4] loss: 0.9271359
Test set: Average loss: 1.0337, Accuracy: 3140/5000 (63%)
[epoch 5] loss: 0.8656399
Test set: Average loss: 1.0102, Accuracy: 3189/5000 (64%)
[epoch 6] loss: 0.8077391
Test set: Average loss: 0.9894, Accuracy: 3213/5000 (64%)
[epoch 7] loss: 0.7588983
Test set: Average loss: 0.9773, Accuracy: 3217/5000 (64%)
[epoch 8] loss: 0.7089713
Test set: Average loss: 0.9649, Accuracy: 3245/5000 (65%)
[epoch 9] loss: 0.6602751
Test set: Average loss: 0.9485, Accuracy: 3278/5000 (66%)
[epoch 10] loss: 0.6179185
Test set: Average loss: 0.9453, Accuracy: 3245/5000 (65%)
[epoch 11] loss: 0.5703340
Test set: Average loss: 0.9325, Accuracy: 3288/5000 (66%)
[epoch 12] loss: 0.5304160
Test set: Average loss: 0.9271, Accuracy: 3304/5000 (66%)
[epoch 13] loss: 0.4920565
Test set: Average loss: 0.9212, Accuracy: 3313/5000 (66%)
[epoch 14] loss: 0.4487518
Test set: Average loss: 0.9212, Accuracy: 3298/5000 (66%)
[epoch 15] loss: 0.4115889
Test set: Average loss: 0.9165, Accuracy: 3318/5000 (66%)
[epoch 16] loss: 0.3761953
Test set: Average loss: 0.9152, Accuracy: 3313/5000 (66%)
[epoch 17] loss: 0.3443679
Test set: Average loss: 0.9134, Accuracy: 3307/5000 (66%)
[epoch 18] loss: 0.3124796
Test set: Average loss: 0.9214, Accuracy: 3308/5000 (66%)
[epoch 19] loss: 0.2852497
Test set: Average loss: 0.9179, Accuracy: 3300/5000 (66%)
[epoch 20] loss: 0.2595442
Test set: Average loss: 0.9171, Accuracy: 3310/5000 (66%)
[epoch 21] loss: 0.2321529
Test set: Average loss: 0.9181, Accuracy: 3329/5000 (67%)
[epoch 22] loss: 0.2082450
Test set: Average loss: 0.9250, Accuracy: 3311/5000 (66%)
[epoch 23] loss: 0.1890787
Test set: Average loss: 0.9277, Accuracy: 3301/5000 (66%)
[epoch 24] loss: 0.1688789
Test set: Average loss: 0.9300, Accuracy: 3293/5000 (66%)
[epoch 25] loss: 0.1513943
Test set: Average loss: 0.9327, Accuracy: 3299/5000 (66%)
Validation:
Test set: Average loss: 0.9181, Accuracy: 3329/5000 (67%)
Test
Test set: Average loss: 0.9121, Accuracy: 3312/5000 (66%)
Test set: Average loss: 0.2059, Accuracy: 4915/5000 (98%)
## seed: 12
Validation accuracy before training:
Test set: Average loss: 1.7906, Accuracy: 899/5000 (18%)
[epoch 1] loss: 1.3127134
Test set: Average loss: 1.1643, Accuracy: 2900/5000 (58%)
[epoch 2] loss: 1.0754149
Test set: Average loss: 1.0860, Accuracy: 3093/5000 (62%)
[epoch 3] loss: 0.9738323
Test set: Average loss: 1.0452, Accuracy: 3148/5000 (63%)
[epoch 4] loss: 0.9036811
Test set: Average loss: 1.0213, Accuracy: 3197/5000 (64%)
[epoch 5] loss: 0.8439786
Test set: Average loss: 0.9972, Accuracy: 3218/5000 (64%)
[epoch 6] loss: 0.7882760
Test set: Average loss: 0.9822, Accuracy: 3241/5000 (65%)
[epoch 7] loss: 0.7385099
Test set: Average loss: 0.9647, Accuracy: 3263/5000 (65%)
[epoch 8] loss: 0.6866943
Test set: Average loss: 0.9555, Accuracy: 3265/5000 (65%)
[epoch 9] loss: 0.6386644
Test set: Average loss: 0.9484, Accuracy: 3274/5000 (65%)
[epoch 10] loss: 0.5938364
Test set: Average loss: 0.9329, Accuracy: 3312/5000 (66%)
[epoch 11] loss: 0.5506465
Test set: Average loss: 0.9293, Accuracy: 3301/5000 (66%)
[epoch 12] loss: 0.5069653
Test set: Average loss: 0.9233, Accuracy: 3312/5000 (66%)
[epoch 13] loss: 0.4657369
Test set: Average loss: 0.9166, Accuracy: 3301/5000 (66%)
[epoch 14] loss: 0.4262260
Test set: Average loss: 0.9139, Accuracy: 3319/5000 (66%)
[epoch 15] loss: 0.3897451
Test set: Average loss: 0.9088, Accuracy: 3319/5000 (66%)
[epoch 16] loss: 0.3547885
Test set: Average loss: 0.9082, Accuracy: 3319/5000 (66%)
[epoch 17] loss: 0.3236486
Test set: Average loss: 0.9085, Accuracy: 3303/5000 (66%)
[epoch 18] loss: 0.2906509
Test set: Average loss: 0.9115, Accuracy: 3330/5000 (67%)
[epoch 19] loss: 0.2625907
Test set: Average loss: 0.9144, Accuracy: 3316/5000 (66%)
[epoch 20] loss: 0.2363047
Test set: Average loss: 0.9117, Accuracy: 3331/5000 (67%)
[epoch 21] loss: 0.2119202
Test set: Average loss: 0.9153, Accuracy: 3341/5000 (67%)
[epoch 22] loss: 0.1897334
Test set: Average loss: 0.9272, Accuracy: 3288/5000 (66%)
[epoch 23] loss: 0.1698573
Test set: Average loss: 0.9315, Accuracy: 3297/5000 (66%)
[epoch 24] loss: 0.1513757
Test set: Average loss: 0.9281, Accuracy: 3300/5000 (66%)
[epoch 25] loss: 0.1350363
Test set: Average loss: 0.9316, Accuracy: 3336/5000 (67%)
Validation:
Test set: Average loss: 0.9153, Accuracy: 3341/5000 (67%)
Test
Test set: Average loss: 0.9265, Accuracy: 3276/5000 (66%)
Test set: Average loss: 0.1875, Accuracy: 4910/5000 (98%)
## seed: 13
Validation accuracy before training:
Test set: Average loss: 1.4251, Accuracy: 2034/5000 (41%)
[epoch 1] loss: 1.1267916
Test set: Average loss: 1.0914, Accuracy: 3100/5000 (62%)
[epoch 2] loss: 0.9639333
Test set: Average loss: 1.0333, Accuracy: 3188/5000 (64%)
[epoch 3] loss: 0.8829664
Test set: Average loss: 1.0018, Accuracy: 3242/5000 (65%)
[epoch 4] loss: 0.8104395
Test set: Average loss: 0.9802, Accuracy: 3246/5000 (65%)
[epoch 5] loss: 0.7492184
Test set: Average loss: 0.9502, Accuracy: 3303/5000 (66%)
[epoch 6] loss: 0.6961465
Test set: Average loss: 0.9342, Accuracy: 3328/5000 (67%)
[epoch 7] loss: 0.6430950
Test set: Average loss: 0.9215, Accuracy: 3335/5000 (67%)
[epoch 8] loss: 0.5963605
Test set: Average loss: 0.9184, Accuracy: 3341/5000 (67%)
[epoch 9] loss: 0.5494034
Test set: Average loss: 0.9001, Accuracy: 3362/5000 (67%)
[epoch 10] loss: 0.5068685
Test set: Average loss: 0.9019, Accuracy: 3352/5000 (67%)
[epoch 11] loss: 0.4656233
Test set: Average loss: 0.8901, Accuracy: 3377/5000 (68%)
[epoch 12] loss: 0.4257472
Test set: Average loss: 0.8926, Accuracy: 3355/5000 (67%)
[epoch 13] loss: 0.3896657
Test set: Average loss: 0.8894, Accuracy: 3373/5000 (67%)
[epoch 14] loss: 0.3548031
Test set: Average loss: 0.8829, Accuracy: 3358/5000 (67%)
[epoch 15] loss: 0.3198162
Test set: Average loss: 0.8806, Accuracy: 3402/5000 (68%)
[epoch 16] loss: 0.2918607
Test set: Average loss: 0.8822, Accuracy: 3376/5000 (68%)
[epoch 17] loss: 0.2617296
Test set: Average loss: 0.8824, Accuracy: 3392/5000 (68%)
[epoch 18] loss: 0.2358861
Test set: Average loss: 0.8840, Accuracy: 3388/5000 (68%)
[epoch 19] loss: 0.2111464
Test set: Average loss: 0.8931, Accuracy: 3368/5000 (67%)
[epoch 20] loss: 0.1888291
Test set: Average loss: 0.8945, Accuracy: 3372/5000 (67%)
[epoch 21] loss: 0.1677589
Test set: Average loss: 0.9042, Accuracy: 3336/5000 (67%)
[epoch 22] loss: 0.1511580
Test set: Average loss: 0.9006, Accuracy: 3373/5000 (67%)
[epoch 23] loss: 0.1339201
Test set: Average loss: 0.9071, Accuracy: 3368/5000 (67%)
[epoch 24] loss: 0.1191405
Test set: Average loss: 0.9128, Accuracy: 3341/5000 (67%)
[epoch 25] loss: 0.1058713
Test set: Average loss: 0.9209, Accuracy: 3361/5000 (67%)
Validation:
Test set: Average loss: 0.8806, Accuracy: 3402/5000 (68%)
Test
Test set: Average loss: 0.8961, Accuracy: 3334/5000 (67%)
Test set: Average loss: 0.2863, Accuracy: 4820/5000 (96%)
10000
## seed: 11
Validation accuracy before training:
Test set: Average loss: 1.6206, Accuracy: 976/5000 (20%)
[epoch 1] loss: 1.1912584
Test set: Average loss: 1.0967, Accuracy: 3083/5000 (62%)
[epoch 2] loss: 0.9909788
Test set: Average loss: 1.0224, Accuracy: 3193/5000 (64%)
[epoch 3] loss: 0.8953193
Test set: Average loss: 0.9737, Accuracy: 3295/5000 (66%)
[epoch 4] loss: 0.8175809
Test set: Average loss: 0.9416, Accuracy: 3316/5000 (66%)
[epoch 5] loss: 0.7501460
Test set: Average loss: 0.9268, Accuracy: 3327/5000 (67%)
[epoch 6] loss: 0.6899126
Test set: Average loss: 0.9076, Accuracy: 3382/5000 (68%)
[epoch 7] loss: 0.6302290
Test set: Average loss: 0.9013, Accuracy: 3360/5000 (67%)
[epoch 8] loss: 0.5750702
Test set: Average loss: 0.8831, Accuracy: 3391/5000 (68%)
[epoch 9] loss: 0.5247161
Test set: Average loss: 0.8735, Accuracy: 3380/5000 (68%)
[epoch 10] loss: 0.4757456
Test set: Average loss: 0.8795, Accuracy: 3383/5000 (68%)
[epoch 11] loss: 0.4272283
Test set: Average loss: 0.8690, Accuracy: 3406/5000 (68%)
[epoch 12] loss: 0.3827730
Test set: Average loss: 0.8701, Accuracy: 3420/5000 (68%)
[epoch 13] loss: 0.3414344
Test set: Average loss: 0.8770, Accuracy: 3385/5000 (68%)
[epoch 14] loss: 0.3002233
Test set: Average loss: 0.8719, Accuracy: 3406/5000 (68%)
[epoch 15] loss: 0.2656664
Test set: Average loss: 0.8845, Accuracy: 3375/5000 (68%)
[epoch 16] loss: 0.2310979
Test set: Average loss: 0.8890, Accuracy: 3399/5000 (68%)
[epoch 17] loss: 0.1995393
Test set: Average loss: 0.9017, Accuracy: 3377/5000 (68%)
[epoch 18] loss: 0.1734110
Test set: Average loss: 0.9096, Accuracy: 3395/5000 (68%)
[epoch 19] loss: 0.1465826
Test set: Average loss: 0.9237, Accuracy: 3388/5000 (68%)
[epoch 20] loss: 0.1268141
Test set: Average loss: 0.9318, Accuracy: 3387/5000 (68%)
[epoch 21] loss: 0.1074946
Test set: Average loss: 0.9537, Accuracy: 3352/5000 (67%)
[epoch 22] loss: 0.0905392
Test set: Average loss: 1.0091, Accuracy: 3311/5000 (66%)
[epoch 23] loss: 0.0794616
Test set: Average loss: 0.9975, Accuracy: 3344/5000 (67%)
[epoch 24] loss: 0.0661115
Test set: Average loss: 0.9973, Accuracy: 3349/5000 (67%)
[epoch 25] loss: 0.0550021
Test set: Average loss: 1.0149, Accuracy: 3354/5000 (67%)
Validation:
Test set: Average loss: 0.8701, Accuracy: 3420/5000 (68%)
Test
Test set: Average loss: 0.8874, Accuracy: 3358/5000 (67%)
Test set: Average loss: 0.3342, Accuracy: 9385/10000 (94%)
## seed: 12
Validation accuracy before training:
Test set: Average loss: 1.7632, Accuracy: 461/5000 (9%)
[epoch 1] loss: 1.2821651
Test set: Average loss: 1.1379, Accuracy: 2967/5000 (59%)
[epoch 2] loss: 1.0380887
Test set: Average loss: 1.0513, Accuracy: 3145/5000 (63%)
[epoch 3] loss: 0.9318805
Test set: Average loss: 0.9924, Accuracy: 3225/5000 (64%)
[epoch 4] loss: 0.8494339
Test set: Average loss: 0.9559, Accuracy: 3299/5000 (66%)
[epoch 5] loss: 0.7774318
Test set: Average loss: 0.9250, Accuracy: 3339/5000 (67%)
[epoch 6] loss: 0.7151021
Test set: Average loss: 0.9063, Accuracy: 3371/5000 (67%)
[epoch 7] loss: 0.6553431
Test set: Average loss: 0.8970, Accuracy: 3377/5000 (68%)
[epoch 8] loss: 0.5972248
Test set: Average loss: 0.8883, Accuracy: 3369/5000 (67%)
[epoch 9] loss: 0.5446756
Test set: Average loss: 0.8818, Accuracy: 3389/5000 (68%)
[epoch 10] loss: 0.4941196
Test set: Average loss: 0.8701, Accuracy: 3424/5000 (68%)
[epoch 11] loss: 0.4462003
Test set: Average loss: 0.8672, Accuracy: 3404/5000 (68%)
[epoch 12] loss: 0.4010136
Test set: Average loss: 0.8642, Accuracy: 3418/5000 (68%)
[epoch 13] loss: 0.3537079
Test set: Average loss: 0.8716, Accuracy: 3405/5000 (68%)
[epoch 14] loss: 0.3140051
Test set: Average loss: 0.8752, Accuracy: 3438/5000 (69%)
[epoch 15] loss: 0.2762349
Test set: Average loss: 0.8755, Accuracy: 3389/5000 (68%)
[epoch 16] loss: 0.2405969
Test set: Average loss: 0.8895, Accuracy: 3412/5000 (68%)
[epoch 17] loss: 0.2085334
Test set: Average loss: 0.8913, Accuracy: 3404/5000 (68%)
[epoch 18] loss: 0.1800043
Test set: Average loss: 0.9034, Accuracy: 3394/5000 (68%)
[epoch 19] loss: 0.1536969
Test set: Average loss: 0.9157, Accuracy: 3404/5000 (68%)
[epoch 20] loss: 0.1317005
Test set: Average loss: 0.9309, Accuracy: 3375/5000 (68%)
[epoch 21] loss: 0.1098549
Test set: Average loss: 0.9447, Accuracy: 3382/5000 (68%)
[epoch 22] loss: 0.0946025
Test set: Average loss: 0.9518, Accuracy: 3386/5000 (68%)
[epoch 23] loss: 0.0783954
Test set: Average loss: 0.9664, Accuracy: 3356/5000 (67%)
[epoch 24] loss: 0.0667697
Test set: Average loss: 0.9925, Accuracy: 3359/5000 (67%)
[epoch 25] loss: 0.0551039
Test set: Average loss: 1.0027, Accuracy: 3398/5000 (68%)
Validation:
Test set: Average loss: 0.8752, Accuracy: 3438/5000 (69%)
Test
Test set: Average loss: 0.8861, Accuracy: 3391/5000 (68%)
Test set: Average loss: 0.2702, Accuracy: 9575/10000 (96%)
## seed: 13
Validation accuracy before training:
Test set: Average loss: 1.6740, Accuracy: 920/5000 (18%)
[epoch 1] loss: 1.2209832
Test set: Average loss: 1.1015, Accuracy: 3036/5000 (61%)
[epoch 2] loss: 1.0097902
Test set: Average loss: 1.0301, Accuracy: 3193/5000 (64%)
[epoch 3] loss: 0.9174427
Test set: Average loss: 0.9825, Accuracy: 3286/5000 (66%)
[epoch 4] loss: 0.8421109
Test set: Average loss: 0.9608, Accuracy: 3272/5000 (65%)
[epoch 5] loss: 0.7777602
Test set: Average loss: 0.9279, Accuracy: 3325/5000 (66%)
[epoch 6] loss: 0.7160764
Test set: Average loss: 0.9062, Accuracy: 3371/5000 (67%)
[epoch 7] loss: 0.6596041
Test set: Average loss: 0.8962, Accuracy: 3360/5000 (67%)
[epoch 8] loss: 0.6052491
Test set: Average loss: 0.8816, Accuracy: 3397/5000 (68%)
[epoch 9] loss: 0.5520825
Test set: Average loss: 0.8819, Accuracy: 3353/5000 (67%)
[epoch 10] loss: 0.5039804
Test set: Average loss: 0.8684, Accuracy: 3410/5000 (68%)
[epoch 11] loss: 0.4570784
Test set: Average loss: 0.8724, Accuracy: 3393/5000 (68%)
[epoch 12] loss: 0.4128712
Test set: Average loss: 0.8685, Accuracy: 3388/5000 (68%)
[epoch 13] loss: 0.3713364
Test set: Average loss: 0.8591, Accuracy: 3426/5000 (69%)
[epoch 14] loss: 0.3312658
Test set: Average loss: 0.8686, Accuracy: 3405/5000 (68%)
[epoch 15] loss: 0.2931438
Test set: Average loss: 0.8719, Accuracy: 3393/5000 (68%)
[epoch 16] loss: 0.2595532
Test set: Average loss: 0.8828, Accuracy: 3405/5000 (68%)
[epoch 17] loss: 0.2265935
Test set: Average loss: 0.8805, Accuracy: 3398/5000 (68%)
[epoch 18] loss: 0.1985267
Test set: Average loss: 0.8961, Accuracy: 3391/5000 (68%)
[epoch 19] loss: 0.1728189
Test set: Average loss: 0.9087, Accuracy: 3396/5000 (68%)
[epoch 20] loss: 0.1492771
Test set: Average loss: 0.9079, Accuracy: 3383/5000 (68%)
[epoch 21] loss: 0.1252972
Test set: Average loss: 0.9256, Accuracy: 3360/5000 (67%)
[epoch 22] loss: 0.1073932
Test set: Average loss: 0.9379, Accuracy: 3344/5000 (67%)
[epoch 23] loss: 0.0924129
Test set: Average loss: 0.9477, Accuracy: 3388/5000 (68%)
[epoch 24] loss: 0.0779887
Test set: Average loss: 0.9578, Accuracy: 3379/5000 (68%)
[epoch 25] loss: 0.0639908
Test set: Average loss: 0.9819, Accuracy: 3340/5000 (67%)
Validation:
Test set: Average loss: 0.8591, Accuracy: 3426/5000 (69%)
Test
Test set: Average loss: 0.8709, Accuracy: 3372/5000 (67%)
Test set: Average loss: 0.3201, Accuracy: 9435/10000 (94%)
15000
## seed: 11
Validation accuracy before training:
Test set: Average loss: 1.5839, Accuracy: 1333/5000 (27%)
[epoch 1] loss: 1.1531297
Test set: Average loss: 1.0555, Accuracy: 3213/5000 (64%)
[epoch 2] loss: 0.9500593
Test set: Average loss: 0.9746, Accuracy: 3298/5000 (66%)
[epoch 3] loss: 0.8440594
Test set: Average loss: 0.9279, Accuracy: 3337/5000 (67%)
[epoch 4] loss: 0.7589409
Test set: Average loss: 0.8914, Accuracy: 3379/5000 (68%)
[epoch 5] loss: 0.6866107
Test set: Average loss: 0.8684, Accuracy: 3413/5000 (68%)
[epoch 6] loss: 0.6206879
Test set: Average loss: 0.8519, Accuracy: 3444/5000 (69%)
[epoch 7] loss: 0.5596888
Test set: Average loss: 0.8466, Accuracy: 3452/5000 (69%)
[epoch 8] loss: 0.5010800
Test set: Average loss: 0.8369, Accuracy: 3443/5000 (69%)
[epoch 9] loss: 0.4480410
Test set: Average loss: 0.8439, Accuracy: 3474/5000 (69%)
[epoch 10] loss: 0.3972673
Test set: Average loss: 0.8380, Accuracy: 3458/5000 (69%)
[epoch 11] loss: 0.3527563
Test set: Average loss: 0.8462, Accuracy: 3466/5000 (69%)
[epoch 12] loss: 0.3074846
Test set: Average loss: 0.8479, Accuracy: 3475/5000 (70%)
[epoch 13] loss: 0.2674996
Test set: Average loss: 0.8570, Accuracy: 3479/5000 (70%)
[epoch 14] loss: 0.2320433
Test set: Average loss: 0.8900, Accuracy: 3404/5000 (68%)
[epoch 15] loss: 0.1993949
Test set: Average loss: 0.8917, Accuracy: 3410/5000 (68%)
[epoch 16] loss: 0.1690191
Test set: Average loss: 0.9089, Accuracy: 3392/5000 (68%)
[epoch 17] loss: 0.1413630
Test set: Average loss: 0.9403, Accuracy: 3375/5000 (68%)
[epoch 18] loss: 0.1212973
Test set: Average loss: 0.9365, Accuracy: 3412/5000 (68%)
[epoch 19] loss: 0.1036886
Test set: Average loss: 0.9612, Accuracy: 3404/5000 (68%)
[epoch 20] loss: 0.0865254
Test set: Average loss: 0.9811, Accuracy: 3388/5000 (68%)
[epoch 21] loss: 0.0691937
Test set: Average loss: 1.0125, Accuracy: 3390/5000 (68%)
[epoch 22] loss: 0.0584243
Test set: Average loss: 1.0389, Accuracy: 3392/5000 (68%)
[epoch 23] loss: 0.0464376
Test set: Average loss: 1.0511, Accuracy: 3407/5000 (68%)
[epoch 24] loss: 0.0393253
Test set: Average loss: 1.0801, Accuracy: 3382/5000 (68%)
[epoch 25] loss: 0.0347867
Test set: Average loss: 1.0924, Accuracy: 3409/5000 (68%)
Validation:
Test set: Average loss: 0.8570, Accuracy: 3479/5000 (70%)
Test
Test set: Average loss: 0.8883, Accuracy: 3413/5000 (68%)
Test set: Average loss: 0.2243, Accuracy: 14415/15000 (96%)
## seed: 12
Validation accuracy before training:
Test set: Average loss: 1.9249, Accuracy: 378/5000 (8%)
[epoch 1] loss: 1.2290676
Test set: Average loss: 1.0991, Accuracy: 3019/5000 (60%)
[epoch 2] loss: 1.0168504
Test set: Average loss: 1.0158, Accuracy: 3200/5000 (64%)
[epoch 3] loss: 0.9140413
Test set: Average loss: 0.9664, Accuracy: 3273/5000 (65%)
[epoch 4] loss: 0.8359380
Test set: Average loss: 0.9350, Accuracy: 3309/5000 (66%)
[epoch 5] loss: 0.7676795
Test set: Average loss: 0.9112, Accuracy: 3325/5000 (66%)
[epoch 6] loss: 0.7066103
Test set: Average loss: 0.8956, Accuracy: 3347/5000 (67%)
[epoch 7] loss: 0.6503860
Test set: Average loss: 0.8831, Accuracy: 3388/5000 (68%)
[epoch 8] loss: 0.5938180
Test set: Average loss: 0.8719, Accuracy: 3414/5000 (68%)
[epoch 9] loss: 0.5401394
Test set: Average loss: 0.8723, Accuracy: 3423/5000 (68%)
[epoch 10] loss: 0.4892761
Test set: Average loss: 0.8644, Accuracy: 3417/5000 (68%)
[epoch 11] loss: 0.4386156
Test set: Average loss: 0.8732, Accuracy: 3407/5000 (68%)
[epoch 12] loss: 0.3911638
Test set: Average loss: 0.8660, Accuracy: 3456/5000 (69%)
[epoch 13] loss: 0.3483453
Test set: Average loss: 0.8710, Accuracy: 3438/5000 (69%)
[epoch 14] loss: 0.3053627
Test set: Average loss: 0.8863, Accuracy: 3409/5000 (68%)
[epoch 15] loss: 0.2660825
Test set: Average loss: 0.9133, Accuracy: 3360/5000 (67%)
[epoch 16] loss: 0.2304900
Test set: Average loss: 0.9099, Accuracy: 3417/5000 (68%)
[epoch 17] loss: 0.1974641
Test set: Average loss: 0.9201, Accuracy: 3398/5000 (68%)
[epoch 18] loss: 0.1664470
Test set: Average loss: 0.9450, Accuracy: 3382/5000 (68%)
[epoch 19] loss: 0.1417819
Test set: Average loss: 0.9629, Accuracy: 3391/5000 (68%)
[epoch 20] loss: 0.1188872
Test set: Average loss: 0.9807, Accuracy: 3358/5000 (67%)
[epoch 21] loss: 0.0984433
Test set: Average loss: 0.9883, Accuracy: 3396/5000 (68%)
[epoch 22] loss: 0.0823110
Test set: Average loss: 1.0126, Accuracy: 3365/5000 (67%)
[epoch 23] loss: 0.0654819
Test set: Average loss: 1.0438, Accuracy: 3343/5000 (67%)
[epoch 24] loss: 0.0557677
Test set: Average loss: 1.0680, Accuracy: 3363/5000 (67%)
[epoch 25] loss: 0.0458191
Test set: Average loss: 1.0877, Accuracy: 3359/5000 (67%)
Validation:
Test set: Average loss: 0.8660, Accuracy: 3456/5000 (69%)
Test
Test set: Average loss: 0.8765, Accuracy: 3435/5000 (69%)
Test set: Average loss: 0.3403, Accuracy: 13884/15000 (93%)
## seed: 13
Validation accuracy before training:
Test set: Average loss: 1.5430, Accuracy: 1637/5000 (33%)
[epoch 1] loss: 1.0761406
Test set: Average loss: 1.0022, Accuracy: 3255/5000 (65%)
[epoch 2] loss: 0.8926878
Test set: Average loss: 0.9344, Accuracy: 3364/5000 (67%)
[epoch 3] loss: 0.7988279
Test set: Average loss: 0.8956, Accuracy: 3408/5000 (68%)
[epoch 4] loss: 0.7226106
Test set: Average loss: 0.8698, Accuracy: 3455/5000 (69%)
[epoch 5] loss: 0.6553444
Test set: Average loss: 0.8486, Accuracy: 3478/5000 (70%)
[epoch 6] loss: 0.5944278
Test set: Average loss: 0.8366, Accuracy: 3460/5000 (69%)
[epoch 7] loss: 0.5364478
Test set: Average loss: 0.8359, Accuracy: 3468/5000 (69%)
[epoch 8] loss: 0.4828859
Test set: Average loss: 0.8283, Accuracy: 3478/5000 (70%)
[epoch 9] loss: 0.4310368
Test set: Average loss: 0.8255, Accuracy: 3479/5000 (70%)
[epoch 10] loss: 0.3829957
Test set: Average loss: 0.8216, Accuracy: 3512/5000 (70%)
[epoch 11] loss: 0.3380260
Test set: Average loss: 0.8278, Accuracy: 3507/5000 (70%)
[epoch 12] loss: 0.2976651
Test set: Average loss: 0.8513, Accuracy: 3475/5000 (70%)
[epoch 13] loss: 0.2589104
Test set: Average loss: 0.8445, Accuracy: 3484/5000 (70%)
[epoch 14] loss: 0.2230245
Test set: Average loss: 0.8702, Accuracy: 3483/5000 (70%)
[epoch 15] loss: 0.1921770
Test set: Average loss: 0.8737, Accuracy: 3467/5000 (69%)
[epoch 16] loss: 0.1634558
Test set: Average loss: 0.8881, Accuracy: 3465/5000 (69%)
[epoch 17] loss: 0.1378702
Test set: Average loss: 0.9140, Accuracy: 3454/5000 (69%)
[epoch 18] loss: 0.1157203
Test set: Average loss: 0.9413, Accuracy: 3409/5000 (68%)
[epoch 19] loss: 0.0982052
Test set: Average loss: 0.9412, Accuracy: 3461/5000 (69%)
[epoch 20] loss: 0.0794426
Test set: Average loss: 0.9647, Accuracy: 3424/5000 (68%)
[epoch 21] loss: 0.0661668
Test set: Average loss: 0.9696, Accuracy: 3435/5000 (69%)
[epoch 22] loss: 0.0558435
Test set: Average loss: 1.0049, Accuracy: 3421/5000 (68%)
[epoch 23] loss: 0.0452948
Test set: Average loss: 1.0269, Accuracy: 3438/5000 (69%)
[epoch 24] loss: 0.0439468
Test set: Average loss: 1.0610, Accuracy: 3362/5000 (67%)
[epoch 25] loss: 0.0333010
Test set: Average loss: 1.0840, Accuracy: 3408/5000 (68%)
Validation:
Test set: Average loss: 0.8216, Accuracy: 3512/5000 (70%)
Test
Test set: Average loss: 0.8424, Accuracy: 3416/5000 (68%)
Test set: Average loss: 0.3274, Accuracy: 13962/15000 (93%)
20000
## seed: 11
Validation accuracy before training:
Test set: Average loss: 1.6064, Accuracy: 1184/5000 (24%)
[epoch 1] loss: 1.0716558
Test set: Average loss: 0.9985, Accuracy: 3252/5000 (65%)
[epoch 2] loss: 0.8846402
Test set: Average loss: 0.9248, Accuracy: 3353/5000 (67%)
[epoch 3] loss: 0.7839024
Test set: Average loss: 0.8861, Accuracy: 3362/5000 (67%)
[epoch 4] loss: 0.7012649
Test set: Average loss: 0.8568, Accuracy: 3435/5000 (69%)
[epoch 5] loss: 0.6283234
Test set: Average loss: 0.8378, Accuracy: 3458/5000 (69%)
[epoch 6] loss: 0.5633669
Test set: Average loss: 0.8428, Accuracy: 3436/5000 (69%)
[epoch 7] loss: 0.5018588
Test set: Average loss: 0.8318, Accuracy: 3464/5000 (69%)
[epoch 8] loss: 0.4463419
Test set: Average loss: 0.8314, Accuracy: 3490/5000 (70%)
[epoch 9] loss: 0.3925078
Test set: Average loss: 0.8380, Accuracy: 3476/5000 (70%)
[epoch 10] loss: 0.3450625
Test set: Average loss: 0.8384, Accuracy: 3472/5000 (69%)
[epoch 11] loss: 0.2997305
Test set: Average loss: 0.8507, Accuracy: 3462/5000 (69%)
[epoch 12] loss: 0.2588384
Test set: Average loss: 0.8709, Accuracy: 3437/5000 (69%)
[epoch 13] loss: 0.2227738
Test set: Average loss: 0.8870, Accuracy: 3458/5000 (69%)
[epoch 14] loss: 0.1891606
Test set: Average loss: 0.9171, Accuracy: 3411/5000 (68%)
[epoch 15] loss: 0.1582648
Test set: Average loss: 0.9344, Accuracy: 3426/5000 (69%)
[epoch 16] loss: 0.1320575
Test set: Average loss: 0.9486, Accuracy: 3443/5000 (69%)
[epoch 17] loss: 0.1100099
Test set: Average loss: 0.9711, Accuracy: 3432/5000 (69%)
[epoch 18] loss: 0.0913922
Test set: Average loss: 0.9926, Accuracy: 3403/5000 (68%)
[epoch 19] loss: 0.0737514
Test set: Average loss: 1.0253, Accuracy: 3397/5000 (68%)
[epoch 20] loss: 0.0618548
Test set: Average loss: 1.0507, Accuracy: 3425/5000 (68%)
[epoch 21] loss: 0.0471620
Test set: Average loss: 1.0798, Accuracy: 3412/5000 (68%)
[epoch 22] loss: 0.0402249
Test set: Average loss: 1.1172, Accuracy: 3397/5000 (68%)
[epoch 23] loss: 0.0310900
Test set: Average loss: 1.1290, Accuracy: 3405/5000 (68%)
[epoch 24] loss: 0.0436268
Epoch 23: reducing learning rate of group 0 to 5.0000e-06.
Test set: Average loss: 1.2278, Accuracy: 3344/5000 (67%)
[epoch 25] loss: 0.0262283
Test set: Average loss: 1.1631, Accuracy: 3421/5000 (68%)
Validation:
Test set: Average loss: 0.8314, Accuracy: 3490/5000 (70%)
Test
Test set: Average loss: 0.8496, Accuracy: 3423/5000 (68%)
Test set: Average loss: 0.3843, Accuracy: 18189/20000 (91%)
## seed: 12
Validation accuracy before training:
Test set: Average loss: 1.7162, Accuracy: 555/5000 (11%)
[epoch 1] loss: 1.1571603
Test set: Average loss: 1.0393, Accuracy: 3198/5000 (64%)
[epoch 2] loss: 0.9423540
Test set: Average loss: 0.9581, Accuracy: 3297/5000 (66%)
[epoch 3] loss: 0.8369425
Test set: Average loss: 0.9044, Accuracy: 3376/5000 (68%)
[epoch 4] loss: 0.7537951
Test set: Average loss: 0.8762, Accuracy: 3398/5000 (68%)
[epoch 5] loss: 0.6817258
Test set: Average loss: 0.8483, Accuracy: 3453/5000 (69%)
[epoch 6] loss: 0.6150898
Test set: Average loss: 0.8349, Accuracy: 3455/5000 (69%)
[epoch 7] loss: 0.5562130
Test set: Average loss: 0.8357, Accuracy: 3452/5000 (69%)
[epoch 8] loss: 0.5027123
Test set: Average loss: 0.8267, Accuracy: 3451/5000 (69%)
[epoch 9] loss: 0.4468744
Test set: Average loss: 0.8238, Accuracy: 3471/5000 (69%)
[epoch 10] loss: 0.3988993
Test set: Average loss: 0.8364, Accuracy: 3453/5000 (69%)
[epoch 11] loss: 0.3527794
Test set: Average loss: 0.8372, Accuracy: 3476/5000 (70%)
[epoch 12] loss: 0.3103613
Test set: Average loss: 0.8472, Accuracy: 3440/5000 (69%)
[epoch 13] loss: 0.2706509
Test set: Average loss: 0.8641, Accuracy: 3454/5000 (69%)
[epoch 14] loss: 0.2354798
Test set: Average loss: 0.8855, Accuracy: 3457/5000 (69%)
[epoch 15] loss: 0.2018733
Test set: Average loss: 0.8946, Accuracy: 3448/5000 (69%)
[epoch 16] loss: 0.1707270
Test set: Average loss: 0.9093, Accuracy: 3419/5000 (68%)
[epoch 17] loss: 0.1467677
Test set: Average loss: 0.9310, Accuracy: 3426/5000 (69%)
[epoch 18] loss: 0.1231658
Test set: Average loss: 0.9608, Accuracy: 3430/5000 (69%)
[epoch 19] loss: 0.1028253
Test set: Average loss: 0.9957, Accuracy: 3387/5000 (68%)
[epoch 20] loss: 0.0873744
Test set: Average loss: 1.0246, Accuracy: 3383/5000 (68%)
[epoch 21] loss: 0.0723544
Test set: Average loss: 1.0487, Accuracy: 3388/5000 (68%)
[epoch 22] loss: 0.0599174
Test set: Average loss: 1.0552, Accuracy: 3379/5000 (68%)
[epoch 23] loss: 0.0500209
Test set: Average loss: 1.0728, Accuracy: 3440/5000 (69%)
[epoch 24] loss: 0.0489954
Test set: Average loss: 1.1368, Accuracy: 3381/5000 (68%)
[epoch 25] loss: 0.0332663
Test set: Average loss: 1.1643, Accuracy: 3356/5000 (67%)
Validation:
Test set: Average loss: 0.8372, Accuracy: 3476/5000 (70%)
Test
Test set: Average loss: 0.8678, Accuracy: 3435/5000 (69%)
Test set: Average loss: 0.2988, Accuracy: 18621/20000 (93%)
## seed: 13
Validation accuracy before training:
Test set: Average loss: 1.8010, Accuracy: 668/5000 (13%)
[epoch 1] loss: 1.1666235
Test set: Average loss: 1.0435, Accuracy: 3161/5000 (63%)
[epoch 2] loss: 0.9581524
Test set: Average loss: 0.9607, Accuracy: 3329/5000 (67%)
[epoch 3] loss: 0.8564995
Test set: Average loss: 0.9087, Accuracy: 3390/5000 (68%)
[epoch 4] loss: 0.7753324
Test set: Average loss: 0.8753, Accuracy: 3419/5000 (68%)
[epoch 5] loss: 0.7023522
Test set: Average loss: 0.8519, Accuracy: 3470/5000 (69%)
[epoch 6] loss: 0.6379720
Test set: Average loss: 0.8338, Accuracy: 3468/5000 (69%)
[epoch 7] loss: 0.5779866
Test set: Average loss: 0.8264, Accuracy: 3467/5000 (69%)
[epoch 8] loss: 0.5221469
Test set: Average loss: 0.8195, Accuracy: 3507/5000 (70%)
[epoch 9] loss: 0.4688785
Test set: Average loss: 0.8171, Accuracy: 3525/5000 (70%)
[epoch 10] loss: 0.4176463
Test set: Average loss: 0.8245, Accuracy: 3516/5000 (70%)
[epoch 11] loss: 0.3708631
Test set: Average loss: 0.8306, Accuracy: 3476/5000 (70%)
[epoch 12] loss: 0.3268770
Test set: Average loss: 0.8367, Accuracy: 3473/5000 (69%)
[epoch 13] loss: 0.2854844
Test set: Average loss: 0.8417, Accuracy: 3480/5000 (70%)
[epoch 14] loss: 0.2479582
Test set: Average loss: 0.8520, Accuracy: 3492/5000 (70%)
[epoch 15] loss: 0.2121496
Test set: Average loss: 0.8808, Accuracy: 3482/5000 (70%)
[epoch 16] loss: 0.1808045
Test set: Average loss: 0.8847, Accuracy: 3458/5000 (69%)
[epoch 17] loss: 0.1531778
Test set: Average loss: 0.9201, Accuracy: 3419/5000 (68%)
[epoch 18] loss: 0.1288494
Test set: Average loss: 0.9317, Accuracy: 3433/5000 (69%)
[epoch 19] loss: 0.1069472
Test set: Average loss: 0.9534, Accuracy: 3429/5000 (69%)
[epoch 20] loss: 0.0859046
Test set: Average loss: 0.9915, Accuracy: 3410/5000 (68%)
[epoch 21] loss: 0.0718098
Test set: Average loss: 0.9977, Accuracy: 3424/5000 (68%)
[epoch 22] loss: 0.0625667
Test set: Average loss: 1.0330, Accuracy: 3419/5000 (68%)
[epoch 23] loss: 0.0494930
Test set: Average loss: 1.0542, Accuracy: 3411/5000 (68%)
[epoch 24] loss: 0.0457030
Test set: Average loss: 1.0799, Accuracy: 3444/5000 (69%)
[epoch 25] loss: 0.0308081
Test set: Average loss: 1.1040, Accuracy: 3438/5000 (69%)
Validation:
Test set: Average loss: 0.8171, Accuracy: 3525/5000 (70%)
Test
Test set: Average loss: 0.8356, Accuracy: 3480/5000 (70%)
Test set: Average loss: 0.4096, Accuracy: 17868/20000 (89%)
n_training_examples = [25, 50, 100, 250, 500, 750, 1000, 2500, 5000, 10000, 15000, 20000]
test_accuracies = {'B': [(0.3796, 0.011717792738680202), (0.42366666666666664, 0.027517913357585015), (0.4106666666666667, 0.01702573215916296), (0.5225333333333332, 0.005060522590492886), (0.5466666666666666, 0.0066659999666633185), (0.5626666666666668, 0.0024513035081133666), (0.5783333333333334, 0.0037606146069787886), (0.6065333333333333, 0.0025368396787253896), (0.6395333333333334, 0.00389643711898734), (0.6646, 0.0019252705437591683), (0.6797333333333334, 0.0034344658326376553), (0.6870666666666668, 0.006450495243691641)], 'AnB': [(0.3310666666666667, 0.06135304031224171), (0.40700000000000003, 0.011032074449833378), (0.3992, 0.01604078136085231), (0.5136666666666666, 0.0051233669484909115), (0.5566666666666666, 0.005648205221326715), (0.5724, 0.009717338455907925), (0.5912000000000001, 0.003398038649966567), (0.6174000000000001, 0.002141650453894527), (0.6377333333333334, 0.0028110891523077173), (0.6642666666666667, 0.005123366948490894), (0.6766, 0.000711805216802113), (0.6849333333333333, 0.001359738536958064)], 'BnB': [(0.3738666666666666, 0.026759338972071448), (0.3806, 0.07365233646441004), (0.29960000000000003, 0.07994014427474264), (0.5282666666666667, 0.02442803489617798), (0.5736666666666667, 0.010951204905803258), (0.5918666666666667, 0.013521669850856281), (0.612, 0.006981881312845877), (0.637, 0.011028448062473106), (0.6655333333333333, 0.0021929178937864684), (0.6776, 0.0036914315199752224), (0.6856666666666666, 0.0013199326582148817), (0.6906, 0.0007483314773547949)], 'ABnB': [(0.31553333333333333, 0.046238319846445775), (0.40746666666666664, 0.039548900813493604), (0.3278666666666667, 0.018853352192352662), (0.5367999999999999, 0.00940354543066959), (0.555, 0.006211816696157946), (0.5867333333333333, 0.0038447655614123094), (0.6058, 0.004572380853195241), (0.6334666666666666, 0.00608896999134954), (0.6614666666666666, 0.004781445620544274), (0.6747333333333333, 0.00270472837001346), (0.6842666666666668, 0.0019482185594936858), (0.6891999999999999, 0.004907137658554093)]}
n_training_examples = [25, 50, 100, 250, 500, 750, 1000, 2500, 5000, 10000, 15000, 20000]
train_accuracies = {'B': [(1.0, 0.0), (1.0, 0.0), (0.7733333333333333, 0.036817870057290855), (0.8933333333333334, 0.029454296045832724), (0.9033333333333333, 0.03222145592958555), (0.8528888888888888, 0.04246247435554199), (0.8523333333333335, 0.029408993333483676), (0.9178666666666667, 0.02187560792806049), (0.9317333333333333, 0.05591429950280063), (0.9323, 0.03580735492418657), (0.9124444444444443, 0.02888574341850157), (0.8965166666666667, 0.02395253408073741)], 'AnB': [(1.0, 0.0), (0.9733333333333333, 0.024944382578492966), (0.7400000000000001, 0.11430952132988166), (0.9613333333333333, 0.010498677165349092), (0.964, 0.0043204937989385775), (0.9573333333333333, 0.011469767022723513), (0.961, 0.008485281374238578), (0.9520000000000001, 0.024638181751095185), (0.9676, 0.005217917847826523), (0.9296000000000001, 0.018524038436582877), (0.8958666666666666, 0.021404257105123347), (0.9467333333333334, 0.014000317456718196)], 'BnB': [(1.0, 0.0), (0.96, 0.0), (0.6699999999999999, 0.19646882704388502), (0.9586666666666667, 0.016110727964792727), (0.9613333333333333, 0.009285592184789422), (0.9524444444444443, 0.013524554715291503), (0.9500000000000001, 0.021924111536540437), (0.9452000000000002, 0.022302167308731857), (0.9440666666666666, 0.026053449334439843), (0.9550000000000001, 0.01651686007286694), (0.9281111111111112, 0.023180728479482826), (0.9272833333333333, 0.01320961350263089)], 'ABnB': [(0.9733333333333333, 0.018856180831641284), (0.9333333333333332, 0.0410960933531265), (0.6466666666666666, 0.004714045207910321), (0.9693333333333333, 0.007542472332656513), (0.9659999999999999, 0.005887840577551903), (0.9702222222222222, 0.0034995590551163513), (0.9786666666666667, 0.004988876515698593), (0.9664000000000001, 0.02067913602321593), (0.9763333333333333, 0.008730533902472538), (0.9465, 0.008041558721209886), (0.9391333333333334, 0.015607120881899457), (0.9113000000000001, 0.015426114222317976)]}
n_training_examples = [25, 50, 100, 250, 500, 750, 1000, 2500, 5000, 10000, 15000, 20000]
generr_accuracies = {'B': [(0.6204, 0.011717792738680198), (0.5763333333333333, 0.027517913357585015), (0.3626666666666667, 0.05379475397801867), (0.3708, 0.02524915840181612), (0.35666666666666674, 0.03557764591550276), (0.2902222222222222, 0.0449131287687962), (0.27399999999999997, 0.033104682448257955), (0.3113333333333333, 0.02198019310399453), (0.29219999999999996, 0.05496350304217032), (0.2677, 0.036947801017110656), (0.2327111111111111, 0.03228329843780977), (0.20945, 0.029179016433046497)], 'AnB': [(0.6689333333333334, 0.06135304031224173), (0.5663333333333332, 0.02513819581610603), (0.3408, 0.10804307782855258), (0.44766666666666666, 0.005377318621353532), (0.4073333333333333, 0.003564017707899665), (0.3849333333333333, 0.01156354424713961), (0.36979999999999996, 0.011880516262632135), (0.3346, 0.026420194296535103), (0.3298666666666667, 0.007611103000806688), (0.26533333333333337, 0.013469554145883545), (0.21926666666666664, 0.020996719320461068), (0.26180000000000003, 0.013577432256014632)], 'BnB': [(0.6261333333333333, 0.02675933897207146), (0.5794, 0.07365233646441006), (0.3704, 0.11860196738109649), (0.43039999999999995, 0.009471360338761668), (0.3876666666666666, 0.020011552219211363), (0.3605777777777777, 0.024778744375765036), (0.3379999999999999, 0.015022649566571124), (0.3082, 0.013067006798294206), (0.27853333333333335, 0.02400574005431945), (0.27740000000000004, 0.013704743704279897), (0.24244444444444438, 0.022279858589439747), (0.23668333333333333, 0.013587024038479558)], 'ABnB': [(0.6578, 0.03091536834650363), (0.5258666666666666, 0.020234843436233694), (0.31880000000000003, 0.02065332902948094), (0.4325333333333334, 0.00774481905677743), (0.411, 0.0012328828005937977), (0.3834888888888888, 0.0026790453431432266), (0.3728666666666666, 0.0022939534045447233), (0.33293333333333336, 0.021151096635609413), (0.3148666666666667, 0.012746066931497801), (0.27176666666666666, 0.005402057221302093), (0.25486666666666663, 0.017041387528276265), (0.2221, 0.01914379795129481)]}
In [9]:
results_test[n_hus[2]], results_train[n_hus[2]], results_generr[n_hus[2]] = do_all_hl(n_hus[2])
#### Training for 2048 hu
## No Pre-Training
25
## seed: 11
Validation accuracy before training:
Test set: Average loss: 1.5879, Accuracy: 1491/5000 (30%)
[epoch 1] loss: 1.6420064
Test set: Average loss: 1.5160, Accuracy: 1632/5000 (33%)
[epoch 2] loss: 1.3638262
Test set: Average loss: 1.4808, Accuracy: 1672/5000 (33%)
[epoch 3] loss: 1.1580976
Test set: Average loss: 1.4632, Accuracy: 1712/5000 (34%)
[epoch 4] loss: 1.0033888
Test set: Average loss: 1.4531, Accuracy: 1777/5000 (36%)
[epoch 5] loss: 0.8808917
Test set: Average loss: 1.4462, Accuracy: 1849/5000 (37%)
[epoch 6] loss: 0.7806616
Test set: Average loss: 1.4411, Accuracy: 1894/5000 (38%)
[epoch 7] loss: 0.6975546
Test set: Average loss: 1.4370, Accuracy: 1912/5000 (38%)
[epoch 8] loss: 0.6284734
Test set: Average loss: 1.4337, Accuracy: 1931/5000 (39%)
[epoch 9] loss: 0.5709471
Test set: Average loss: 1.4310, Accuracy: 1952/5000 (39%)
[epoch 10] loss: 0.5228691
Test set: Average loss: 1.4292, Accuracy: 1977/5000 (40%)
[epoch 11] loss: 0.4826351
Test set: Average loss: 1.4283, Accuracy: 1978/5000 (40%)
[epoch 12] loss: 0.4488840
Test set: Average loss: 1.4285, Accuracy: 1996/5000 (40%)
[epoch 13] loss: 0.4203511
Test set: Average loss: 1.4297, Accuracy: 2005/5000 (40%)
[epoch 14] loss: 0.3959196
Test set: Average loss: 1.4317, Accuracy: 2007/5000 (40%)
[epoch 15] loss: 0.3747028
Test set: Average loss: 1.4344, Accuracy: 2014/5000 (40%)
[epoch 16] loss: 0.3560916
Test set: Average loss: 1.4375, Accuracy: 2011/5000 (40%)
[epoch 17] loss: 0.3397097
Test set: Average loss: 1.4410, Accuracy: 2000/5000 (40%)
[epoch 18] loss: 0.3252938
Test set: Average loss: 1.4447, Accuracy: 1997/5000 (40%)
[epoch 19] loss: 0.3125972
Test set: Average loss: 1.4485, Accuracy: 1999/5000 (40%)
[epoch 20] loss: 0.3013797
Test set: Average loss: 1.4524, Accuracy: 1984/5000 (40%)
[epoch 21] loss: 0.2914328
Test set: Average loss: 1.4563, Accuracy: 1984/5000 (40%)
[epoch 22] loss: 0.2825875
Test set: Average loss: 1.4600, Accuracy: 1973/5000 (39%)
[epoch 23] loss: 0.2747036
Test set: Average loss: 1.4635, Accuracy: 1964/5000 (39%)
[epoch 24] loss: 0.2676598
Test set: Average loss: 1.4667, Accuracy: 1953/5000 (39%)
[epoch 25] loss: 0.2613504
Test set: Average loss: 1.4696, Accuracy: 1950/5000 (39%)
Validation:
Test set: Average loss: 1.4344, Accuracy: 2014/5000 (40%)
Test
Test set: Average loss: 1.4484, Accuracy: 1951/5000 (39%)
Test set: Average loss: 0.3561, Accuracy: 25/25 (100%)
## seed: 12
Validation accuracy before training:
Test set: Average loss: 1.6467, Accuracy: 883/5000 (18%)
[epoch 1] loss: 1.6511821
Test set: Average loss: 1.5436, Accuracy: 1656/5000 (33%)
[epoch 2] loss: 1.3036026
Test set: Average loss: 1.4933, Accuracy: 1837/5000 (37%)
[epoch 3] loss: 1.0726131
Test set: Average loss: 1.4695, Accuracy: 1865/5000 (37%)
[epoch 4] loss: 0.9167514
Test set: Average loss: 1.4578, Accuracy: 1901/5000 (38%)
[epoch 5] loss: 0.8041561
Test set: Average loss: 1.4520, Accuracy: 1910/5000 (38%)
[epoch 6] loss: 0.7176225
Test set: Average loss: 1.4492, Accuracy: 1923/5000 (38%)
[epoch 7] loss: 0.6482784
Test set: Average loss: 1.4478, Accuracy: 1932/5000 (39%)
[epoch 8] loss: 0.5910942
Test set: Average loss: 1.4473, Accuracy: 1940/5000 (39%)
[epoch 9] loss: 0.5429564
Test set: Average loss: 1.4471, Accuracy: 1942/5000 (39%)
[epoch 10] loss: 0.5020780
Test set: Average loss: 1.4472, Accuracy: 1939/5000 (39%)
[epoch 11] loss: 0.4674048
Test set: Average loss: 1.4477, Accuracy: 1945/5000 (39%)
[epoch 12] loss: 0.4379214
Test set: Average loss: 1.4486, Accuracy: 1944/5000 (39%)
[epoch 13] loss: 0.4125507
Test set: Average loss: 1.4498, Accuracy: 1949/5000 (39%)
[epoch 14] loss: 0.3904009
Test set: Average loss: 1.4514, Accuracy: 1940/5000 (39%)
[epoch 15] loss: 0.3708755
Test set: Average loss: 1.4532, Accuracy: 1938/5000 (39%)
[epoch 16] loss: 0.3536066
Test set: Average loss: 1.4550, Accuracy: 1950/5000 (39%)
[epoch 17] loss: 0.3383411
Test set: Average loss: 1.4568, Accuracy: 1953/5000 (39%)
[epoch 18] loss: 0.3248602
Test set: Average loss: 1.4584, Accuracy: 1960/5000 (39%)
[epoch 19] loss: 0.3129591
Test set: Average loss: 1.4598, Accuracy: 1962/5000 (39%)
[epoch 20] loss: 0.3024612
Test set: Average loss: 1.4609, Accuracy: 1972/5000 (39%)
[epoch 21] loss: 0.2932182
Test set: Average loss: 1.4619, Accuracy: 1973/5000 (39%)
[epoch 22] loss: 0.2850726
Test set: Average loss: 1.4627, Accuracy: 1975/5000 (40%)
[epoch 23] loss: 0.2778278
Test set: Average loss: 1.4636, Accuracy: 1976/5000 (40%)
[epoch 24] loss: 0.2712787
Test set: Average loss: 1.4644, Accuracy: 1982/5000 (40%)
[epoch 25] loss: 0.2652612
Test set: Average loss: 1.4653, Accuracy: 1974/5000 (39%)
Validation:
Test set: Average loss: 1.4644, Accuracy: 1982/5000 (40%)
Test
Test set: Average loss: 1.4922, Accuracy: 1904/5000 (38%)
Test set: Average loss: 0.2653, Accuracy: 25/25 (100%)
## seed: 13
Validation accuracy before training:
Test set: Average loss: 1.6272, Accuracy: 1236/5000 (25%)
[epoch 1] loss: 1.6302533
Test set: Average loss: 1.5492, Accuracy: 1668/5000 (33%)
[epoch 2] loss: 1.3486946
Test set: Average loss: 1.4990, Accuracy: 1883/5000 (38%)
[epoch 3] loss: 1.1277966
Test set: Average loss: 1.4672, Accuracy: 1970/5000 (39%)
[epoch 4] loss: 0.9608602
Test set: Average loss: 1.4462, Accuracy: 2016/5000 (40%)
[epoch 5] loss: 0.8334184
Test set: Average loss: 1.4318, Accuracy: 2048/5000 (41%)
[epoch 6] loss: 0.7342190
Test set: Average loss: 1.4218, Accuracy: 2063/5000 (41%)
[epoch 7] loss: 0.6563081
Test set: Average loss: 1.4147, Accuracy: 2073/5000 (41%)
[epoch 8] loss: 0.5941446
Test set: Average loss: 1.4099, Accuracy: 2081/5000 (42%)
[epoch 9] loss: 0.5433902
Test set: Average loss: 1.4066, Accuracy: 2089/5000 (42%)
[epoch 10] loss: 0.5012326
Test set: Average loss: 1.4044, Accuracy: 2099/5000 (42%)
[epoch 11] loss: 0.4659435
Test set: Average loss: 1.4032, Accuracy: 2111/5000 (42%)
[epoch 12] loss: 0.4363325
Test set: Average loss: 1.4029, Accuracy: 2109/5000 (42%)
[epoch 13] loss: 0.4114136
Test set: Average loss: 1.4033, Accuracy: 2113/5000 (42%)
[epoch 14] loss: 0.3903046
Test set: Average loss: 1.4043, Accuracy: 2111/5000 (42%)
[epoch 15] loss: 0.3722540
Test set: Average loss: 1.4057, Accuracy: 2122/5000 (42%)
[epoch 16] loss: 0.3566804
Test set: Average loss: 1.4075, Accuracy: 2121/5000 (42%)
[epoch 17] loss: 0.3431624
Test set: Average loss: 1.4094, Accuracy: 2116/5000 (42%)
[epoch 18] loss: 0.3313904
Test set: Average loss: 1.4113, Accuracy: 2118/5000 (42%)
[epoch 19] loss: 0.3211135
Test set: Average loss: 1.4131, Accuracy: 2113/5000 (42%)
[epoch 20] loss: 0.3121119
Test set: Average loss: 1.4147, Accuracy: 2102/5000 (42%)
[epoch 21] loss: 0.3041886
Test set: Average loss: 1.4162, Accuracy: 2096/5000 (42%)
[epoch 22] loss: 0.2971709
Test set: Average loss: 1.4176, Accuracy: 2099/5000 (42%)
[epoch 23] loss: 0.2909114
Test set: Average loss: 1.4189, Accuracy: 2098/5000 (42%)
[epoch 24] loss: 0.2852889
Test set: Average loss: 1.4201, Accuracy: 2097/5000 (42%)
[epoch 25] loss: 0.2802049
Test set: Average loss: 1.4212, Accuracy: 2097/5000 (42%)
Validation:
Test set: Average loss: 1.4057, Accuracy: 2122/5000 (42%)
Test
Test set: Average loss: 1.4167, Accuracy: 2084/5000 (42%)
Test set: Average loss: 0.3567, Accuracy: 25/25 (100%)
50
## seed: 11
Validation accuracy before training:
Test set: Average loss: 1.6387, Accuracy: 976/5000 (20%)
[epoch 1] loss: 1.5750771
Test set: Average loss: 1.4689, Accuracy: 1598/5000 (32%)
[epoch 2] loss: 1.2150828
Test set: Average loss: 1.4349, Accuracy: 1641/5000 (33%)
[epoch 3] loss: 1.1016639
Test set: Average loss: 1.4153, Accuracy: 1736/5000 (35%)
[epoch 4] loss: 0.9286054
Test set: Average loss: 1.4026, Accuracy: 1785/5000 (36%)
[epoch 5] loss: 0.7902971
Test set: Average loss: 1.3894, Accuracy: 1898/5000 (38%)
[epoch 6] loss: 0.7185958
Test set: Average loss: 1.3792, Accuracy: 2001/5000 (40%)
[epoch 7] loss: 0.6573155
Test set: Average loss: 1.3760, Accuracy: 2050/5000 (41%)
[epoch 8] loss: 0.5800641
Test set: Average loss: 1.3752, Accuracy: 2093/5000 (42%)
[epoch 9] loss: 0.5419040
Test set: Average loss: 1.3761, Accuracy: 2113/5000 (42%)
[epoch 10] loss: 0.5126863
Test set: Average loss: 1.3807, Accuracy: 2124/5000 (42%)
[epoch 11] loss: 0.4744118
Test set: Average loss: 1.3883, Accuracy: 2094/5000 (42%)
[epoch 12] loss: 0.4250457
Test set: Average loss: 1.3964, Accuracy: 2058/5000 (41%)
[epoch 13] loss: 0.4274956
Epoch 12: reducing learning rate of group 0 to 5.0000e-06.
Test set: Average loss: 1.4038, Accuracy: 2034/5000 (41%)
[epoch 14] loss: 0.3960823
Test set: Average loss: 1.4044, Accuracy: 2033/5000 (41%)
[epoch 15] loss: 0.4014319
Epoch 14: reducing learning rate of group 0 to 5.0000e-07.
Test set: Average loss: 1.4047, Accuracy: 2032/5000 (41%)
[epoch 16] loss: 0.4008453
Epoch 15: reducing learning rate of group 0 to 5.0000e-08.
Test set: Average loss: 1.4047, Accuracy: 2033/5000 (41%)
[epoch 17] loss: 0.4058716
Epoch 16: reducing learning rate of group 0 to 5.0000e-09.
Test set: Average loss: 1.4047, Accuracy: 2033/5000 (41%)
[epoch 18] loss: 0.4026280
Epoch 17: reducing learning rate of group 0 to 5.0000e-10.
Test set: Average loss: 1.4047, Accuracy: 2033/5000 (41%)
[epoch 19] loss: 0.4009408
Epoch 18: reducing learning rate of group 0 to 5.0000e-11.
Test set: Average loss: 1.4047, Accuracy: 2033/5000 (41%)
[epoch 20] loss: 0.3943039
Test set: Average loss: 1.4047, Accuracy: 2033/5000 (41%)
[epoch 21] loss: 0.4004826
Epoch 20: reducing learning rate of group 0 to 5.0000e-12.
Test set: Average loss: 1.4047, Accuracy: 2033/5000 (41%)
[epoch 22] loss: 0.4024977
Epoch 21: reducing learning rate of group 0 to 5.0000e-13.
Test set: Average loss: 1.4047, Accuracy: 2033/5000 (41%)
[epoch 23] loss: 0.4084934
Epoch 22: reducing learning rate of group 0 to 5.0000e-14.
Test set: Average loss: 1.4047, Accuracy: 2033/5000 (41%)
[epoch 24] loss: 0.4058425
Epoch 23: reducing learning rate of group 0 to 5.0000e-15.
Test set: Average loss: 1.4047, Accuracy: 2033/5000 (41%)
[epoch 25] loss: 0.3923530
Test set: Average loss: 1.4047, Accuracy: 2033/5000 (41%)
Validation:
Test set: Average loss: 1.3807, Accuracy: 2124/5000 (42%)
Test
Test set: Average loss: 1.3845, Accuracy: 2142/5000 (43%)
Test set: Average loss: 0.4841, Accuracy: 50/50 (100%)
## seed: 12
Validation accuracy before training:
Test set: Average loss: 1.6330, Accuracy: 794/5000 (16%)
[epoch 1] loss: 1.5723228
Test set: Average loss: 1.5090, Accuracy: 1813/5000 (36%)
[epoch 2] loss: 1.2453314
Test set: Average loss: 1.4782, Accuracy: 1935/5000 (39%)
[epoch 3] loss: 1.0864150
Test set: Average loss: 1.4656, Accuracy: 1958/5000 (39%)
[epoch 4] loss: 0.9640232
Test set: Average loss: 1.4529, Accuracy: 1994/5000 (40%)
[epoch 5] loss: 0.8943756
Test set: Average loss: 1.4456, Accuracy: 1990/5000 (40%)
[epoch 6] loss: 0.7837923
Test set: Average loss: 1.4384, Accuracy: 2011/5000 (40%)
[epoch 7] loss: 0.7302614
Test set: Average loss: 1.4341, Accuracy: 2022/5000 (40%)
[epoch 8] loss: 0.6841777
Test set: Average loss: 1.4304, Accuracy: 2038/5000 (41%)
[epoch 9] loss: 0.6441619
Test set: Average loss: 1.4262, Accuracy: 2050/5000 (41%)
[epoch 10] loss: 0.5961978
Test set: Average loss: 1.4239, Accuracy: 2069/5000 (41%)
[epoch 11] loss: 0.5871880
Test set: Average loss: 1.4247, Accuracy: 2072/5000 (41%)
[epoch 12] loss: 0.5438923
Test set: Average loss: 1.4270, Accuracy: 2083/5000 (42%)
[epoch 13] loss: 0.5345210
Test set: Average loss: 1.4303, Accuracy: 2086/5000 (42%)
[epoch 14] loss: 0.5081573
Test set: Average loss: 1.4325, Accuracy: 2090/5000 (42%)
[epoch 15] loss: 0.4853105
Test set: Average loss: 1.4326, Accuracy: 2098/5000 (42%)
[epoch 16] loss: 0.4658108
Test set: Average loss: 1.4343, Accuracy: 2102/5000 (42%)
[epoch 17] loss: 0.4573987
Test set: Average loss: 1.4365, Accuracy: 2102/5000 (42%)
[epoch 18] loss: 0.4414410
Test set: Average loss: 1.4393, Accuracy: 2097/5000 (42%)
[epoch 19] loss: 0.4383194
Test set: Average loss: 1.4428, Accuracy: 2091/5000 (42%)
[epoch 20] loss: 0.4180550
Test set: Average loss: 1.4462, Accuracy: 2080/5000 (42%)
[epoch 21] loss: 0.4166949
Test set: Average loss: 1.4478, Accuracy: 2074/5000 (41%)
[epoch 22] loss: 0.4015865
Test set: Average loss: 1.4488, Accuracy: 2071/5000 (41%)
[epoch 23] loss: 0.4003189
Test set: Average loss: 1.4489, Accuracy: 2075/5000 (42%)
[epoch 24] loss: 0.3933529
Test set: Average loss: 1.4495, Accuracy: 2077/5000 (42%)
[epoch 25] loss: 0.3782184
Test set: Average loss: 1.4503, Accuracy: 2077/5000 (42%)
Validation:
Test set: Average loss: 1.4365, Accuracy: 2102/5000 (42%)
Test
Test set: Average loss: 1.4434, Accuracy: 2099/5000 (42%)
Test set: Average loss: 0.4453, Accuracy: 50/50 (100%)
## seed: 13
Validation accuracy before training:
Test set: Average loss: 1.6157, Accuracy: 1191/5000 (24%)
[epoch 1] loss: 1.5894328
Test set: Average loss: 1.4849, Accuracy: 1939/5000 (39%)
[epoch 2] loss: 1.2569050
Test set: Average loss: 1.4267, Accuracy: 2080/5000 (42%)
[epoch 3] loss: 1.0619351
Test set: Average loss: 1.3978, Accuracy: 2145/5000 (43%)
[epoch 4] loss: 0.9622977
Test set: Average loss: 1.3821, Accuracy: 2192/5000 (44%)
[epoch 5] loss: 0.8632443
Test set: Average loss: 1.3706, Accuracy: 2215/5000 (44%)
[epoch 6] loss: 0.7858117
Test set: Average loss: 1.3634, Accuracy: 2242/5000 (45%)
[epoch 7] loss: 0.7268710
Test set: Average loss: 1.3595, Accuracy: 2267/5000 (45%)
[epoch 8] loss: 0.6873653
Test set: Average loss: 1.3561, Accuracy: 2295/5000 (46%)
[epoch 9] loss: 0.6318273
Test set: Average loss: 1.3550, Accuracy: 2302/5000 (46%)
[epoch 10] loss: 0.5869902
Test set: Average loss: 1.3557, Accuracy: 2281/5000 (46%)
[epoch 11] loss: 0.5541734
Test set: Average loss: 1.3570, Accuracy: 2290/5000 (46%)
[epoch 12] loss: 0.5345155
Test set: Average loss: 1.3586, Accuracy: 2293/5000 (46%)
[epoch 13] loss: 0.5166663
Test set: Average loss: 1.3607, Accuracy: 2303/5000 (46%)
[epoch 14] loss: 0.4906219
Test set: Average loss: 1.3632, Accuracy: 2289/5000 (46%)
[epoch 15] loss: 0.4727241
Test set: Average loss: 1.3661, Accuracy: 2278/5000 (46%)
[epoch 16] loss: 0.4518408
Test set: Average loss: 1.3687, Accuracy: 2266/5000 (45%)
[epoch 17] loss: 0.4317349
Test set: Average loss: 1.3707, Accuracy: 2259/5000 (45%)
[epoch 18] loss: 0.4212461
Test set: Average loss: 1.3725, Accuracy: 2260/5000 (45%)
[epoch 19] loss: 0.4106755
Test set: Average loss: 1.3733, Accuracy: 2268/5000 (45%)
[epoch 20] loss: 0.4011462
Test set: Average loss: 1.3736, Accuracy: 2258/5000 (45%)
[epoch 21] loss: 0.3923087
Test set: Average loss: 1.3730, Accuracy: 2264/5000 (45%)
[epoch 22] loss: 0.3787835
Test set: Average loss: 1.3731, Accuracy: 2269/5000 (45%)
[epoch 23] loss: 0.3637066
Test set: Average loss: 1.3736, Accuracy: 2257/5000 (45%)
[epoch 24] loss: 0.3580935
Test set: Average loss: 1.3743, Accuracy: 2263/5000 (45%)
[epoch 25] loss: 0.3502296
Test set: Average loss: 1.3757, Accuracy: 2263/5000 (45%)
Validation:
Test set: Average loss: 1.3607, Accuracy: 2303/5000 (46%)
Test
Test set: Average loss: 1.3723, Accuracy: 2287/5000 (46%)
Test set: Average loss: 0.4952, Accuracy: 50/50 (100%)
100
## seed: 11
Validation accuracy before training:
Test set: Average loss: 1.6192, Accuracy: 1053/5000 (21%)
[epoch 1] loss: 1.5052817
Test set: Average loss: 1.4302, Accuracy: 1711/5000 (34%)
[epoch 2] loss: 1.2399900
Test set: Average loss: 1.4048, Accuracy: 1814/5000 (36%)
[epoch 3] loss: 1.0446781
Test set: Average loss: 1.3961, Accuracy: 1917/5000 (38%)
[epoch 4] loss: 0.9534953
Test set: Average loss: 1.3737, Accuracy: 1991/5000 (40%)
[epoch 5] loss: 0.8581154
Test set: Average loss: 1.3523, Accuracy: 2079/5000 (42%)
[epoch 6] loss: 0.7446215
Test set: Average loss: 1.3302, Accuracy: 2202/5000 (44%)
[epoch 7] loss: 0.7217786
Test set: Average loss: 1.3174, Accuracy: 2299/5000 (46%)
[epoch 8] loss: 0.6968142
Test set: Average loss: 1.3123, Accuracy: 2296/5000 (46%)
[epoch 9] loss: 0.6463325
Test set: Average loss: 1.3174, Accuracy: 2272/5000 (45%)
[epoch 10] loss: 0.6052477
Test set: Average loss: 1.3309, Accuracy: 2204/5000 (44%)
[epoch 11] loss: 0.5465543
Test set: Average loss: 1.3380, Accuracy: 2186/5000 (44%)
[epoch 12] loss: 0.5670513
Epoch 11: reducing learning rate of group 0 to 5.0000e-06.
Test set: Average loss: 1.3390, Accuracy: 2202/5000 (44%)
[epoch 13] loss: 0.5406877
Test set: Average loss: 1.3394, Accuracy: 2201/5000 (44%)
[epoch 14] loss: 0.5795979
Epoch 13: reducing learning rate of group 0 to 5.0000e-07.
Test set: Average loss: 1.3377, Accuracy: 2210/5000 (44%)
[epoch 15] loss: 0.5429696
Epoch 14: reducing learning rate of group 0 to 5.0000e-08.
Test set: Average loss: 1.3376, Accuracy: 2217/5000 (44%)
[epoch 16] loss: 0.5600136
Epoch 15: reducing learning rate of group 0 to 5.0000e-09.
Test set: Average loss: 1.3376, Accuracy: 2218/5000 (44%)
[epoch 17] loss: 0.5679438
Epoch 16: reducing learning rate of group 0 to 5.0000e-10.
Test set: Average loss: 1.3376, Accuracy: 2218/5000 (44%)
[epoch 18] loss: 0.5082035
Test set: Average loss: 1.3376, Accuracy: 2218/5000 (44%)
[epoch 19] loss: 0.5570132
Epoch 18: reducing learning rate of group 0 to 5.0000e-11.
Test set: Average loss: 1.3376, Accuracy: 2218/5000 (44%)
[epoch 20] loss: 0.5215861
Epoch 19: reducing learning rate of group 0 to 5.0000e-12.
Test set: Average loss: 1.3376, Accuracy: 2218/5000 (44%)
[epoch 21] loss: 0.5235283
Epoch 20: reducing learning rate of group 0 to 5.0000e-13.
Test set: Average loss: 1.3376, Accuracy: 2218/5000 (44%)
[epoch 22] loss: 0.5320379
Epoch 21: reducing learning rate of group 0 to 5.0000e-14.
Test set: Average loss: 1.3376, Accuracy: 2218/5000 (44%)
[epoch 23] loss: 0.5385415
Epoch 22: reducing learning rate of group 0 to 5.0000e-15.
Test set: Average loss: 1.3376, Accuracy: 2218/5000 (44%)
[epoch 24] loss: 0.5152157
Epoch 23: reducing learning rate of group 0 to 5.0000e-16.
Test set: Average loss: 1.3376, Accuracy: 2218/5000 (44%)
[epoch 25] loss: 0.5724860
Epoch 24: reducing learning rate of group 0 to 5.0000e-17.
Test set: Average loss: 1.3376, Accuracy: 2218/5000 (44%)
Validation:
Test set: Average loss: 1.3174, Accuracy: 2299/5000 (46%)
Test
Test set: Average loss: 1.3305, Accuracy: 2267/5000 (45%)
Test set: Average loss: 0.7192, Accuracy: 88/100 (88%)
## seed: 12
Validation accuracy before training:
Test set: Average loss: 1.6375, Accuracy: 945/5000 (19%)
[epoch 1] loss: 1.5285404
Test set: Average loss: 1.4489, Accuracy: 2079/5000 (42%)
[epoch 2] loss: 1.0702820
Test set: Average loss: 1.4120, Accuracy: 2130/5000 (43%)
[epoch 3] loss: 0.9749257
Test set: Average loss: 1.3868, Accuracy: 2142/5000 (43%)
[epoch 4] loss: 0.9189762
Test set: Average loss: 1.3744, Accuracy: 2179/5000 (44%)
[epoch 5] loss: 0.8086253
Test set: Average loss: 1.3643, Accuracy: 2217/5000 (44%)
[epoch 6] loss: 0.8713104
Epoch 5: reducing learning rate of group 0 to 5.0000e-06.
Test set: Average loss: 1.3599, Accuracy: 2242/5000 (45%)
[epoch 7] loss: 0.6859186
Test set: Average loss: 1.3596, Accuracy: 2246/5000 (45%)
[epoch 8] loss: 0.7004640
Epoch 7: reducing learning rate of group 0 to 5.0000e-07.
Test set: Average loss: 1.3591, Accuracy: 2245/5000 (45%)
[epoch 9] loss: 0.7445453
Epoch 8: reducing learning rate of group 0 to 5.0000e-08.
Test set: Average loss: 1.3590, Accuracy: 2245/5000 (45%)
[epoch 10] loss: 0.6681581
Test set: Average loss: 1.3590, Accuracy: 2246/5000 (45%)
[epoch 11] loss: 0.7329160
Epoch 10: reducing learning rate of group 0 to 5.0000e-09.
Test set: Average loss: 1.3590, Accuracy: 2246/5000 (45%)
[epoch 12] loss: 0.7172096
Epoch 11: reducing learning rate of group 0 to 5.0000e-10.
Test set: Average loss: 1.3590, Accuracy: 2246/5000 (45%)
[epoch 13] loss: 0.7852479
Epoch 12: reducing learning rate of group 0 to 5.0000e-11.
Test set: Average loss: 1.3590, Accuracy: 2246/5000 (45%)
[epoch 14] loss: 0.8064291
Epoch 13: reducing learning rate of group 0 to 5.0000e-12.
Test set: Average loss: 1.3590, Accuracy: 2246/5000 (45%)
[epoch 15] loss: 0.7853509
Epoch 14: reducing learning rate of group 0 to 5.0000e-13.
Test set: Average loss: 1.3590, Accuracy: 2246/5000 (45%)
[epoch 16] loss: 0.6921412
Epoch 15: reducing learning rate of group 0 to 5.0000e-14.
Test set: Average loss: 1.3590, Accuracy: 2246/5000 (45%)
[epoch 17] loss: 0.6872482
Epoch 16: reducing learning rate of group 0 to 5.0000e-15.
Test set: Average loss: 1.3590, Accuracy: 2246/5000 (45%)
[epoch 18] loss: 0.7592781
Epoch 17: reducing learning rate of group 0 to 5.0000e-16.
Test set: Average loss: 1.3590, Accuracy: 2246/5000 (45%)
[epoch 19] loss: 0.8112155
Epoch 18: reducing learning rate of group 0 to 5.0000e-17.
Test set: Average loss: 1.3590, Accuracy: 2246/5000 (45%)
[epoch 20] loss: 0.7603697
Epoch 19: reducing learning rate of group 0 to 5.0000e-18.
Test set: Average loss: 1.3590, Accuracy: 2246/5000 (45%)
[epoch 21] loss: 0.8077704
Epoch 20: reducing learning rate of group 0 to 5.0000e-19.
Test set: Average loss: 1.3590, Accuracy: 2246/5000 (45%)
[epoch 22] loss: 0.7951185
Epoch 21: reducing learning rate of group 0 to 5.0000e-20.
Test set: Average loss: 1.3590, Accuracy: 2246/5000 (45%)
[epoch 23] loss: 0.7599919
Epoch 22: reducing learning rate of group 0 to 5.0000e-21.
Test set: Average loss: 1.3590, Accuracy: 2246/5000 (45%)
[epoch 24] loss: 0.7952770
Epoch 23: reducing learning rate of group 0 to 5.0000e-22.
Test set: Average loss: 1.3590, Accuracy: 2246/5000 (45%)
[epoch 25] loss: 0.7293440
Epoch 24: reducing learning rate of group 0 to 5.0000e-23.
Test set: Average loss: 1.3590, Accuracy: 2246/5000 (45%)
Validation:
Test set: Average loss: 1.3590, Accuracy: 2246/5000 (45%)
Test
Test set: Average loss: 1.3638, Accuracy: 2197/5000 (44%)
Test set: Average loss: 0.7586, Accuracy: 81/100 (81%)
## seed: 13
Validation accuracy before training:
Test set: Average loss: 1.6498, Accuracy: 816/5000 (16%)
[epoch 1] loss: 1.5123172
Test set: Average loss: 1.4275, Accuracy: 2067/5000 (41%)
[epoch 2] loss: 1.1497673
Test set: Average loss: 1.3970, Accuracy: 2097/5000 (42%)
[epoch 3] loss: 1.1167823
Test set: Average loss: 1.3582, Accuracy: 2240/5000 (45%)
[epoch 4] loss: 0.9947224
Test set: Average loss: 1.3353, Accuracy: 2305/5000 (46%)
[epoch 5] loss: 0.8828428
Test set: Average loss: 1.3213, Accuracy: 2363/5000 (47%)
[epoch 6] loss: 0.8606558
Test set: Average loss: 1.3159, Accuracy: 2378/5000 (48%)
[epoch 7] loss: 0.7858141
Test set: Average loss: 1.3210, Accuracy: 2374/5000 (47%)
[epoch 8] loss: 0.7429360
Test set: Average loss: 1.3238, Accuracy: 2371/5000 (47%)
[epoch 9] loss: 0.7427280
Test set: Average loss: 1.3214, Accuracy: 2394/5000 (48%)
[epoch 10] loss: 0.6607555
Test set: Average loss: 1.3162, Accuracy: 2427/5000 (49%)
[epoch 11] loss: 0.6207615
Test set: Average loss: 1.3101, Accuracy: 2445/5000 (49%)
[epoch 12] loss: 0.5745088
Test set: Average loss: 1.3140, Accuracy: 2432/5000 (49%)
[epoch 13] loss: 0.5831333
Epoch 12: reducing learning rate of group 0 to 5.0000e-06.
Test set: Average loss: 1.3180, Accuracy: 2405/5000 (48%)
[epoch 14] loss: 0.5589813
Test set: Average loss: 1.3177, Accuracy: 2402/5000 (48%)
[epoch 15] loss: 0.5792804
Epoch 14: reducing learning rate of group 0 to 5.0000e-07.
Test set: Average loss: 1.3177, Accuracy: 2405/5000 (48%)
[epoch 16] loss: 0.5320697
Test set: Average loss: 1.3177, Accuracy: 2405/5000 (48%)
[epoch 17] loss: 0.6721735
Epoch 16: reducing learning rate of group 0 to 5.0000e-08.
Test set: Average loss: 1.3176, Accuracy: 2403/5000 (48%)
[epoch 18] loss: 0.5783079
Epoch 17: reducing learning rate of group 0 to 5.0000e-09.
Test set: Average loss: 1.3176, Accuracy: 2404/5000 (48%)
[epoch 19] loss: 0.5938163
Epoch 18: reducing learning rate of group 0 to 5.0000e-10.
Test set: Average loss: 1.3176, Accuracy: 2404/5000 (48%)
[epoch 20] loss: 0.5472475
Epoch 19: reducing learning rate of group 0 to 5.0000e-11.
Test set: Average loss: 1.3176, Accuracy: 2404/5000 (48%)
[epoch 21] loss: 0.6094245
Epoch 20: reducing learning rate of group 0 to 5.0000e-12.
Test set: Average loss: 1.3176, Accuracy: 2404/5000 (48%)
[epoch 22] loss: 0.5571928
Epoch 21: reducing learning rate of group 0 to 5.0000e-13.
Test set: Average loss: 1.3176, Accuracy: 2404/5000 (48%)
[epoch 23] loss: 0.5735058
Epoch 22: reducing learning rate of group 0 to 5.0000e-14.
Test set: Average loss: 1.3176, Accuracy: 2404/5000 (48%)
[epoch 24] loss: 0.5435967
Epoch 23: reducing learning rate of group 0 to 5.0000e-15.
Test set: Average loss: 1.3176, Accuracy: 2404/5000 (48%)
[epoch 25] loss: 0.5502266
Epoch 24: reducing learning rate of group 0 to 5.0000e-16.
Test set: Average loss: 1.3176, Accuracy: 2404/5000 (48%)
Validation:
Test set: Average loss: 1.3101, Accuracy: 2445/5000 (49%)
Test
Test set: Average loss: 1.3229, Accuracy: 2424/5000 (48%)
Test set: Average loss: 0.6045, Accuracy: 95/100 (95%)
250
## seed: 11
Validation accuracy before training:
Test set: Average loss: 1.6370, Accuracy: 842/5000 (17%)
[epoch 1] loss: 1.5171768
Test set: Average loss: 1.3187, Accuracy: 2312/5000 (46%)
[epoch 2] loss: 1.1771975
Test set: Average loss: 1.2832, Accuracy: 2422/5000 (48%)
[epoch 3] loss: 1.0434969
Test set: Average loss: 1.2609, Accuracy: 2578/5000 (52%)
[epoch 4] loss: 0.9450633
Test set: Average loss: 1.2560, Accuracy: 2554/5000 (51%)
[epoch 5] loss: 0.8687724
Test set: Average loss: 1.2537, Accuracy: 2560/5000 (51%)
[epoch 6] loss: 0.8037420
Test set: Average loss: 1.2454, Accuracy: 2605/5000 (52%)
[epoch 7] loss: 0.7534201
Test set: Average loss: 1.2568, Accuracy: 2557/5000 (51%)
[epoch 8] loss: 0.7074630
Test set: Average loss: 1.2408, Accuracy: 2632/5000 (53%)
[epoch 9] loss: 0.6628300
Test set: Average loss: 1.2528, Accuracy: 2577/5000 (52%)
[epoch 10] loss: 0.6256766
Test set: Average loss: 1.2445, Accuracy: 2602/5000 (52%)
[epoch 11] loss: 0.5928045
Test set: Average loss: 1.2485, Accuracy: 2585/5000 (52%)
[epoch 12] loss: 0.5636639
Test set: Average loss: 1.2559, Accuracy: 2559/5000 (51%)
[epoch 13] loss: 0.5306520
Test set: Average loss: 1.2508, Accuracy: 2577/5000 (52%)
[epoch 14] loss: 0.5073379
Test set: Average loss: 1.2518, Accuracy: 2582/5000 (52%)
[epoch 15] loss: 0.4866692
Test set: Average loss: 1.2542, Accuracy: 2561/5000 (51%)
[epoch 16] loss: 0.4658765
Test set: Average loss: 1.2628, Accuracy: 2553/5000 (51%)
[epoch 17] loss: 0.4401599
Test set: Average loss: 1.2512, Accuracy: 2583/5000 (52%)
[epoch 18] loss: 0.4190304
Test set: Average loss: 1.2680, Accuracy: 2550/5000 (51%)
[epoch 19] loss: 0.4054791
Test set: Average loss: 1.2616, Accuracy: 2573/5000 (51%)
[epoch 20] loss: 0.3838712
Test set: Average loss: 1.2695, Accuracy: 2549/5000 (51%)
[epoch 21] loss: 0.3684406
Test set: Average loss: 1.2654, Accuracy: 2555/5000 (51%)
[epoch 22] loss: 0.3539221
Test set: Average loss: 1.2706, Accuracy: 2549/5000 (51%)
[epoch 23] loss: 0.3423376
Test set: Average loss: 1.2708, Accuracy: 2550/5000 (51%)
[epoch 24] loss: 0.3311427
Test set: Average loss: 1.2846, Accuracy: 2523/5000 (50%)
[epoch 25] loss: 0.3154125
Test set: Average loss: 1.2716, Accuracy: 2555/5000 (51%)
Validation:
Test set: Average loss: 1.2408, Accuracy: 2632/5000 (53%)
Test
Test set: Average loss: 1.2516, Accuracy: 2524/5000 (50%)
Test set: Average loss: 0.6702, Accuracy: 220/250 (88%)
## seed: 12
Validation accuracy before training:
Test set: Average loss: 1.6009, Accuracy: 1164/5000 (23%)
[epoch 1] loss: 1.4405670
Test set: Average loss: 1.3340, Accuracy: 2152/5000 (43%)
[epoch 2] loss: 1.1601722
Test set: Average loss: 1.2719, Accuracy: 2371/5000 (47%)
[epoch 3] loss: 1.0174609
Test set: Average loss: 1.2412, Accuracy: 2504/5000 (50%)
[epoch 4] loss: 0.9125731
Test set: Average loss: 1.2152, Accuracy: 2591/5000 (52%)
[epoch 5] loss: 0.8494976
Test set: Average loss: 1.2200, Accuracy: 2558/5000 (51%)
[epoch 6] loss: 0.7894174
Test set: Average loss: 1.2241, Accuracy: 2528/5000 (51%)
[epoch 7] loss: 0.7411033
Test set: Average loss: 1.2144, Accuracy: 2564/5000 (51%)
[epoch 8] loss: 0.6978543
Test set: Average loss: 1.2123, Accuracy: 2552/5000 (51%)
[epoch 9] loss: 0.6503974
Test set: Average loss: 1.2095, Accuracy: 2558/5000 (51%)
[epoch 10] loss: 0.6171690
Test set: Average loss: 1.2090, Accuracy: 2594/5000 (52%)
[epoch 11] loss: 0.5836894
Test set: Average loss: 1.2130, Accuracy: 2542/5000 (51%)
[epoch 12] loss: 0.5533679
Test set: Average loss: 1.2094, Accuracy: 2570/5000 (51%)
[epoch 13] loss: 0.5278547
Test set: Average loss: 1.2097, Accuracy: 2590/5000 (52%)
[epoch 14] loss: 0.5022552
Test set: Average loss: 1.2106, Accuracy: 2587/5000 (52%)
[epoch 15] loss: 0.4799700
Test set: Average loss: 1.2158, Accuracy: 2551/5000 (51%)
[epoch 16] loss: 0.4623460
Test set: Average loss: 1.2063, Accuracy: 2586/5000 (52%)
[epoch 17] loss: 0.4394907
Test set: Average loss: 1.2187, Accuracy: 2554/5000 (51%)
[epoch 18] loss: 0.4228156
Test set: Average loss: 1.2210, Accuracy: 2536/5000 (51%)
[epoch 19] loss: 0.4046640
Test set: Average loss: 1.2221, Accuracy: 2555/5000 (51%)
[epoch 20] loss: 0.3917528
Test set: Average loss: 1.2209, Accuracy: 2567/5000 (51%)
[epoch 21] loss: 0.3785886
Test set: Average loss: 1.2205, Accuracy: 2560/5000 (51%)
[epoch 22] loss: 0.3626461
Test set: Average loss: 1.2293, Accuracy: 2531/5000 (51%)
[epoch 23] loss: 0.3509941
Test set: Average loss: 1.2330, Accuracy: 2534/5000 (51%)
[epoch 24] loss: 0.3405533
Test set: Average loss: 1.2278, Accuracy: 2572/5000 (51%)
[epoch 25] loss: 0.3293465
Test set: Average loss: 1.2321, Accuracy: 2550/5000 (51%)
Validation:
Test set: Average loss: 1.2090, Accuracy: 2594/5000 (52%)
Test
Test set: Average loss: 1.2060, Accuracy: 2615/5000 (52%)
Test set: Average loss: 0.5886, Accuracy: 235/250 (94%)
## seed: 13
Validation accuracy before training:
Test set: Average loss: 1.6549, Accuracy: 821/5000 (16%)
[epoch 1] loss: 1.4639404
Test set: Average loss: 1.3290, Accuracy: 2358/5000 (47%)
[epoch 2] loss: 1.1509466
Test set: Average loss: 1.2765, Accuracy: 2471/5000 (49%)
[epoch 3] loss: 1.0144030
Test set: Average loss: 1.2641, Accuracy: 2516/5000 (50%)
[epoch 4] loss: 0.9190766
Test set: Average loss: 1.2612, Accuracy: 2519/5000 (50%)
[epoch 5] loss: 0.8493224
Test set: Average loss: 1.2567, Accuracy: 2547/5000 (51%)
[epoch 6] loss: 0.7941528
Test set: Average loss: 1.2489, Accuracy: 2558/5000 (51%)
[epoch 7] loss: 0.7426432
Test set: Average loss: 1.2496, Accuracy: 2568/5000 (51%)
[epoch 8] loss: 0.6947901
Test set: Average loss: 1.2551, Accuracy: 2544/5000 (51%)
[epoch 9] loss: 0.6539383
Test set: Average loss: 1.2495, Accuracy: 2585/5000 (52%)
[epoch 10] loss: 0.6220958
Test set: Average loss: 1.2589, Accuracy: 2548/5000 (51%)
[epoch 11] loss: 0.5882115
Test set: Average loss: 1.2521, Accuracy: 2575/5000 (52%)
[epoch 12] loss: 0.5605039
Test set: Average loss: 1.2531, Accuracy: 2576/5000 (52%)
[epoch 13] loss: 0.5315635
Test set: Average loss: 1.2587, Accuracy: 2568/5000 (51%)
[epoch 14] loss: 0.5087334
Test set: Average loss: 1.2602, Accuracy: 2569/5000 (51%)
[epoch 15] loss: 0.4866606
Test set: Average loss: 1.2597, Accuracy: 2577/5000 (52%)
[epoch 16] loss: 0.4621163
Test set: Average loss: 1.2657, Accuracy: 2561/5000 (51%)
[epoch 17] loss: 0.4415826
Test set: Average loss: 1.2642, Accuracy: 2567/5000 (51%)
[epoch 18] loss: 0.4258050
Test set: Average loss: 1.2669, Accuracy: 2560/5000 (51%)
[epoch 19] loss: 0.4084829
Test set: Average loss: 1.2662, Accuracy: 2568/5000 (51%)
[epoch 20] loss: 0.3921672
Test set: Average loss: 1.2703, Accuracy: 2558/5000 (51%)
[epoch 21] loss: 0.3763946
Test set: Average loss: 1.2723, Accuracy: 2552/5000 (51%)
[epoch 22] loss: 0.3694585
Test set: Average loss: 1.2711, Accuracy: 2576/5000 (52%)
[epoch 23] loss: 0.3534724
Test set: Average loss: 1.2744, Accuracy: 2572/5000 (51%)
[epoch 24] loss: 0.3429590
Test set: Average loss: 1.2803, Accuracy: 2552/5000 (51%)
[epoch 25] loss: 0.3309082
Test set: Average loss: 1.2780, Accuracy: 2555/5000 (51%)
Validation:
Test set: Average loss: 1.2495, Accuracy: 2585/5000 (52%)
Test
Test set: Average loss: 1.2673, Accuracy: 2572/5000 (51%)
Test set: Average loss: 0.6261, Accuracy: 232/250 (93%)
500
## seed: 11
Validation accuracy before training:
Test set: Average loss: 1.6485, Accuracy: 832/5000 (17%)
[epoch 1] loss: 1.3603016
Test set: Average loss: 1.2537, Accuracy: 2480/5000 (50%)
[epoch 2] loss: 1.0964942
Test set: Average loss: 1.2143, Accuracy: 2637/5000 (53%)
[epoch 3] loss: 0.9960506
Test set: Average loss: 1.1993, Accuracy: 2671/5000 (53%)
[epoch 4] loss: 0.9254634
Test set: Average loss: 1.1850, Accuracy: 2697/5000 (54%)
[epoch 5] loss: 0.8619793
Test set: Average loss: 1.1794, Accuracy: 2731/5000 (55%)
[epoch 6] loss: 0.8094705
Test set: Average loss: 1.1710, Accuracy: 2745/5000 (55%)
[epoch 7] loss: 0.7574684
Test set: Average loss: 1.1719, Accuracy: 2752/5000 (55%)
[epoch 8] loss: 0.7187375
Test set: Average loss: 1.1787, Accuracy: 2740/5000 (55%)
[epoch 9] loss: 0.6854296
Test set: Average loss: 1.1652, Accuracy: 2742/5000 (55%)
[epoch 10] loss: 0.6437306
Test set: Average loss: 1.1756, Accuracy: 2727/5000 (55%)
[epoch 11] loss: 0.6184666
Test set: Average loss: 1.1717, Accuracy: 2766/5000 (55%)
[epoch 12] loss: 0.5860250
Test set: Average loss: 1.1671, Accuracy: 2750/5000 (55%)
[epoch 13] loss: 0.5546172
Test set: Average loss: 1.1771, Accuracy: 2693/5000 (54%)
[epoch 14] loss: 0.5306446
Test set: Average loss: 1.1734, Accuracy: 2723/5000 (54%)
[epoch 15] loss: 0.5051294
Test set: Average loss: 1.1744, Accuracy: 2747/5000 (55%)
[epoch 16] loss: 0.4784047
Test set: Average loss: 1.1730, Accuracy: 2746/5000 (55%)
[epoch 17] loss: 0.4577511
Test set: Average loss: 1.1717, Accuracy: 2743/5000 (55%)
[epoch 18] loss: 0.4426603
Test set: Average loss: 1.1808, Accuracy: 2712/5000 (54%)
[epoch 19] loss: 0.4234115
Test set: Average loss: 1.1868, Accuracy: 2673/5000 (53%)
[epoch 20] loss: 0.3979897
Test set: Average loss: 1.1817, Accuracy: 2709/5000 (54%)
[epoch 21] loss: 0.3799677
Test set: Average loss: 1.1817, Accuracy: 2715/5000 (54%)
[epoch 22] loss: 0.3675644
Test set: Average loss: 1.1820, Accuracy: 2727/5000 (55%)
[epoch 23] loss: 0.3477321
Test set: Average loss: 1.1894, Accuracy: 2693/5000 (54%)
[epoch 24] loss: 0.3309679
Test set: Average loss: 1.1860, Accuracy: 2733/5000 (55%)
[epoch 25] loss: 0.3186133
Test set: Average loss: 1.1961, Accuracy: 2681/5000 (54%)
Validation:
Test set: Average loss: 1.1717, Accuracy: 2766/5000 (55%)
Test
Test set: Average loss: 1.1787, Accuracy: 2718/5000 (54%)
Test set: Average loss: 0.5824, Accuracy: 457/500 (91%)
## seed: 12
Validation accuracy before training:
Test set: Average loss: 1.6511, Accuracy: 855/5000 (17%)
[epoch 1] loss: 1.4479114
Test set: Average loss: 1.3264, Accuracy: 2269/5000 (45%)
[epoch 2] loss: 1.1866002
Test set: Average loss: 1.2344, Accuracy: 2515/5000 (50%)
[epoch 3] loss: 1.0465042
Test set: Average loss: 1.2202, Accuracy: 2611/5000 (52%)
[epoch 4] loss: 0.9656221
Test set: Average loss: 1.2000, Accuracy: 2644/5000 (53%)
[epoch 5] loss: 0.9030129
Test set: Average loss: 1.1991, Accuracy: 2665/5000 (53%)
[epoch 6] loss: 0.8498559
Test set: Average loss: 1.1852, Accuracy: 2690/5000 (54%)
[epoch 7] loss: 0.7966246
Test set: Average loss: 1.1905, Accuracy: 2676/5000 (54%)
[epoch 8] loss: 0.7694640
Test set: Average loss: 1.1896, Accuracy: 2692/5000 (54%)
[epoch 9] loss: 0.7215008
Test set: Average loss: 1.1798, Accuracy: 2708/5000 (54%)
[epoch 10] loss: 0.6793459
Test set: Average loss: 1.1855, Accuracy: 2696/5000 (54%)
[epoch 11] loss: 0.6417709
Test set: Average loss: 1.1808, Accuracy: 2691/5000 (54%)
[epoch 12] loss: 0.6169361
Test set: Average loss: 1.1861, Accuracy: 2708/5000 (54%)
[epoch 13] loss: 0.5914284
Test set: Average loss: 1.1801, Accuracy: 2741/5000 (55%)
[epoch 14] loss: 0.5631294
Test set: Average loss: 1.1801, Accuracy: 2725/5000 (54%)
[epoch 15] loss: 0.5368094
Test set: Average loss: 1.1740, Accuracy: 2751/5000 (55%)
[epoch 16] loss: 0.5112703
Test set: Average loss: 1.1837, Accuracy: 2707/5000 (54%)
[epoch 17] loss: 0.4785534
Test set: Average loss: 1.1736, Accuracy: 2734/5000 (55%)
[epoch 18] loss: 0.4616976
Test set: Average loss: 1.1922, Accuracy: 2710/5000 (54%)
[epoch 19] loss: 0.4468899
Test set: Average loss: 1.1805, Accuracy: 2732/5000 (55%)
[epoch 20] loss: 0.4271935
Test set: Average loss: 1.1821, Accuracy: 2722/5000 (54%)
[epoch 21] loss: 0.4044689
Test set: Average loss: 1.1895, Accuracy: 2725/5000 (54%)
[epoch 22] loss: 0.3892020
Test set: Average loss: 1.1900, Accuracy: 2715/5000 (54%)
[epoch 23] loss: 0.3777617
Test set: Average loss: 1.2167, Accuracy: 2673/5000 (53%)
[epoch 24] loss: 0.3626296
Test set: Average loss: 1.1853, Accuracy: 2745/5000 (55%)
[epoch 25] loss: 0.3458791
Test set: Average loss: 1.1815, Accuracy: 2757/5000 (55%)
Validation:
Test set: Average loss: 1.1815, Accuracy: 2757/5000 (55%)
Test
Test set: Average loss: 1.2001, Accuracy: 2655/5000 (53%)
Test set: Average loss: 0.3245, Accuracy: 493/500 (99%)
## seed: 13
Validation accuracy before training:
Test set: Average loss: 1.6359, Accuracy: 800/5000 (16%)
[epoch 1] loss: 1.3666513
Test set: Average loss: 1.2812, Accuracy: 2476/5000 (50%)
[epoch 2] loss: 1.0912126
Test set: Average loss: 1.2395, Accuracy: 2567/5000 (51%)
[epoch 3] loss: 0.9921097
Test set: Average loss: 1.2110, Accuracy: 2675/5000 (54%)
[epoch 4] loss: 0.9119644
Test set: Average loss: 1.2000, Accuracy: 2717/5000 (54%)
[epoch 5] loss: 0.8531323
Test set: Average loss: 1.1929, Accuracy: 2747/5000 (55%)
[epoch 6] loss: 0.8022673
Test set: Average loss: 1.1843, Accuracy: 2776/5000 (56%)
[epoch 7] loss: 0.7593132
Test set: Average loss: 1.1814, Accuracy: 2799/5000 (56%)
[epoch 8] loss: 0.7195605
Test set: Average loss: 1.1850, Accuracy: 2768/5000 (55%)
[epoch 9] loss: 0.6799913
Test set: Average loss: 1.1810, Accuracy: 2789/5000 (56%)
[epoch 10] loss: 0.6447523
Test set: Average loss: 1.1836, Accuracy: 2792/5000 (56%)
[epoch 11] loss: 0.6099711
Test set: Average loss: 1.1876, Accuracy: 2772/5000 (55%)
[epoch 12] loss: 0.5803925
Test set: Average loss: 1.1762, Accuracy: 2819/5000 (56%)
[epoch 13] loss: 0.5517697
Test set: Average loss: 1.1914, Accuracy: 2768/5000 (55%)
[epoch 14] loss: 0.5292146
Test set: Average loss: 1.1996, Accuracy: 2720/5000 (54%)
[epoch 15] loss: 0.5018939
Test set: Average loss: 1.1832, Accuracy: 2790/5000 (56%)
[epoch 16] loss: 0.4727791
Test set: Average loss: 1.1851, Accuracy: 2789/5000 (56%)
[epoch 17] loss: 0.4529898
Test set: Average loss: 1.1899, Accuracy: 2766/5000 (55%)
[epoch 18] loss: 0.4333047
Test set: Average loss: 1.1936, Accuracy: 2753/5000 (55%)
[epoch 19] loss: 0.4172770
Test set: Average loss: 1.1975, Accuracy: 2747/5000 (55%)
[epoch 20] loss: 0.3953026
Test set: Average loss: 1.2019, Accuracy: 2750/5000 (55%)
[epoch 21] loss: 0.3795957
Test set: Average loss: 1.1893, Accuracy: 2798/5000 (56%)
[epoch 22] loss: 0.3640565
Test set: Average loss: 1.2080, Accuracy: 2749/5000 (55%)
[epoch 23] loss: 0.3488987
Test set: Average loss: 1.1980, Accuracy: 2762/5000 (55%)
[epoch 24] loss: 0.3323724
Test set: Average loss: 1.2074, Accuracy: 2755/5000 (55%)
[epoch 25] loss: 0.3201465
Test set: Average loss: 1.2133, Accuracy: 2730/5000 (55%)
Validation:
Test set: Average loss: 1.1762, Accuracy: 2819/5000 (56%)
Test
Test set: Average loss: 1.1941, Accuracy: 2783/5000 (56%)
Test set: Average loss: 0.5495, Accuracy: 473/500 (95%)
750
## seed: 11
Validation accuracy before training:
Test set: Average loss: 1.5969, Accuracy: 1199/5000 (24%)
[epoch 1] loss: 1.3140224
Test set: Average loss: 1.2338, Accuracy: 2532/5000 (51%)
[epoch 2] loss: 1.0868071
Test set: Average loss: 1.1888, Accuracy: 2729/5000 (55%)
[epoch 3] loss: 0.9964844
Test set: Average loss: 1.1671, Accuracy: 2784/5000 (56%)
[epoch 4] loss: 0.9268935
Test set: Average loss: 1.1553, Accuracy: 2853/5000 (57%)
[epoch 5] loss: 0.8909172
Test set: Average loss: 1.1470, Accuracy: 2878/5000 (58%)
[epoch 6] loss: 0.8324722
Test set: Average loss: 1.1485, Accuracy: 2824/5000 (56%)
[epoch 7] loss: 0.7929603
Test set: Average loss: 1.1414, Accuracy: 2875/5000 (58%)
[epoch 8] loss: 0.7479610
Test set: Average loss: 1.1409, Accuracy: 2861/5000 (57%)
[epoch 9] loss: 0.7097646
Test set: Average loss: 1.1384, Accuracy: 2858/5000 (57%)
[epoch 10] loss: 0.6745541
Test set: Average loss: 1.1347, Accuracy: 2873/5000 (57%)
[epoch 11] loss: 0.6419907
Test set: Average loss: 1.1359, Accuracy: 2849/5000 (57%)
[epoch 12] loss: 0.6150982
Test set: Average loss: 1.1329, Accuracy: 2840/5000 (57%)
[epoch 13] loss: 0.5856518
Test set: Average loss: 1.1297, Accuracy: 2859/5000 (57%)
[epoch 14] loss: 0.5574329
Test set: Average loss: 1.1271, Accuracy: 2870/5000 (57%)
[epoch 15] loss: 0.5331502
Test set: Average loss: 1.1375, Accuracy: 2846/5000 (57%)
[epoch 16] loss: 0.5083385
Test set: Average loss: 1.1327, Accuracy: 2861/5000 (57%)
[epoch 17] loss: 0.4823567
Test set: Average loss: 1.1367, Accuracy: 2832/5000 (57%)
[epoch 18] loss: 0.4556233
Test set: Average loss: 1.1300, Accuracy: 2838/5000 (57%)
[epoch 19] loss: 0.4394420
Test set: Average loss: 1.1314, Accuracy: 2841/5000 (57%)
[epoch 20] loss: 0.4145230
Test set: Average loss: 1.1460, Accuracy: 2804/5000 (56%)
[epoch 21] loss: 0.4012748
Test set: Average loss: 1.1453, Accuracy: 2794/5000 (56%)
[epoch 22] loss: 0.3795284
Test set: Average loss: 1.1374, Accuracy: 2816/5000 (56%)
[epoch 23] loss: 0.3564056
Test set: Average loss: 1.1464, Accuracy: 2801/5000 (56%)
[epoch 24] loss: 0.3417000
Test set: Average loss: 1.1393, Accuracy: 2829/5000 (57%)
[epoch 25] loss: 0.3270076
Test set: Average loss: 1.1472, Accuracy: 2823/5000 (56%)
Validation:
Test set: Average loss: 1.1470, Accuracy: 2878/5000 (58%)
Test
Test set: Average loss: 1.1509, Accuracy: 2833/5000 (57%)
Test set: Average loss: 0.8269, Accuracy: 587/750 (78%)
## seed: 12
Validation accuracy before training:
Test set: Average loss: 1.6217, Accuracy: 987/5000 (20%)
[epoch 1] loss: 1.3591731
Test set: Average loss: 1.2455, Accuracy: 2625/5000 (52%)
[epoch 2] loss: 1.1290699
Test set: Average loss: 1.1880, Accuracy: 2808/5000 (56%)
[epoch 3] loss: 1.0228021
Test set: Average loss: 1.1717, Accuracy: 2848/5000 (57%)
[epoch 4] loss: 0.9684819
Test set: Average loss: 1.1484, Accuracy: 2915/5000 (58%)
[epoch 5] loss: 0.9089940
Test set: Average loss: 1.1502, Accuracy: 2909/5000 (58%)
[epoch 6] loss: 0.8510777
Test set: Average loss: 1.1335, Accuracy: 2930/5000 (59%)
[epoch 7] loss: 0.8004324
Test set: Average loss: 1.1369, Accuracy: 2910/5000 (58%)
[epoch 8] loss: 0.7532720
Test set: Average loss: 1.1326, Accuracy: 2962/5000 (59%)
[epoch 9] loss: 0.7133059
Test set: Average loss: 1.1384, Accuracy: 2897/5000 (58%)
[epoch 10] loss: 0.6810058
Test set: Average loss: 1.1244, Accuracy: 2927/5000 (59%)
[epoch 11] loss: 0.6471649
Test set: Average loss: 1.1376, Accuracy: 2847/5000 (57%)
[epoch 12] loss: 0.6113589
Test set: Average loss: 1.1183, Accuracy: 2944/5000 (59%)
[epoch 13] loss: 0.5774846
Test set: Average loss: 1.1227, Accuracy: 2909/5000 (58%)
[epoch 14] loss: 0.5484793
Test set: Average loss: 1.1234, Accuracy: 2889/5000 (58%)
[epoch 15] loss: 0.5153337
Test set: Average loss: 1.1199, Accuracy: 2938/5000 (59%)
[epoch 16] loss: 0.4862307
Test set: Average loss: 1.1145, Accuracy: 2946/5000 (59%)
[epoch 17] loss: 0.4663170
Test set: Average loss: 1.1406, Accuracy: 2835/5000 (57%)
[epoch 18] loss: 0.4431501
Test set: Average loss: 1.1233, Accuracy: 2919/5000 (58%)
[epoch 19] loss: 0.4117287
Test set: Average loss: 1.1346, Accuracy: 2851/5000 (57%)
[epoch 20] loss: 0.3939197
Test set: Average loss: 1.1348, Accuracy: 2855/5000 (57%)
[epoch 21] loss: 0.3773614
Test set: Average loss: 1.1221, Accuracy: 2909/5000 (58%)
[epoch 22] loss: 0.3533903
Test set: Average loss: 1.1368, Accuracy: 2866/5000 (57%)
[epoch 23] loss: 0.3350103
Test set: Average loss: 1.1363, Accuracy: 2907/5000 (58%)
[epoch 24] loss: 0.3229467
Test set: Average loss: 1.1431, Accuracy: 2861/5000 (57%)
[epoch 25] loss: 0.3002277
Test set: Average loss: 1.1284, Accuracy: 2900/5000 (58%)
Validation:
Test set: Average loss: 1.1326, Accuracy: 2962/5000 (59%)
Test
Test set: Average loss: 1.1420, Accuracy: 2873/5000 (57%)
Test set: Average loss: 0.7115, Accuracy: 639/750 (85%)
## seed: 13
Validation accuracy before training:
Test set: Average loss: 1.6035, Accuracy: 1128/5000 (23%)
[epoch 1] loss: 1.3325180
Test set: Average loss: 1.2418, Accuracy: 2592/5000 (52%)
[epoch 2] loss: 1.0989762
Test set: Average loss: 1.1891, Accuracy: 2694/5000 (54%)
[epoch 3] loss: 1.0145083
Test set: Average loss: 1.1716, Accuracy: 2738/5000 (55%)
[epoch 4] loss: 0.9480112
Test set: Average loss: 1.1546, Accuracy: 2808/5000 (56%)
[epoch 5] loss: 0.9003347
Test set: Average loss: 1.1525, Accuracy: 2805/5000 (56%)
[epoch 6] loss: 0.8516998
Test set: Average loss: 1.1573, Accuracy: 2779/5000 (56%)
[epoch 7] loss: 0.8120475
Test set: Average loss: 1.1618, Accuracy: 2730/5000 (55%)
[epoch 8] loss: 0.7666131
Test set: Average loss: 1.1398, Accuracy: 2858/5000 (57%)
[epoch 9] loss: 0.7220918
Test set: Average loss: 1.1425, Accuracy: 2826/5000 (57%)
[epoch 10] loss: 0.6844019
Test set: Average loss: 1.1407, Accuracy: 2844/5000 (57%)
[epoch 11] loss: 0.6565638
Test set: Average loss: 1.1464, Accuracy: 2809/5000 (56%)
[epoch 12] loss: 0.6222006
Test set: Average loss: 1.1414, Accuracy: 2857/5000 (57%)
[epoch 13] loss: 0.5890044
Test set: Average loss: 1.1446, Accuracy: 2817/5000 (56%)
[epoch 14] loss: 0.5663973
Test set: Average loss: 1.1401, Accuracy: 2856/5000 (57%)
[epoch 15] loss: 0.5390592
Test set: Average loss: 1.1593, Accuracy: 2792/5000 (56%)
[epoch 16] loss: 0.5138706
Test set: Average loss: 1.1537, Accuracy: 2792/5000 (56%)
[epoch 17] loss: 0.4883434
Test set: Average loss: 1.1559, Accuracy: 2787/5000 (56%)
[epoch 18] loss: 0.4644283
Test set: Average loss: 1.1531, Accuracy: 2816/5000 (56%)
[epoch 19] loss: 0.4378243
Test set: Average loss: 1.1503, Accuracy: 2813/5000 (56%)
[epoch 20] loss: 0.4153658
Test set: Average loss: 1.1593, Accuracy: 2786/5000 (56%)
[epoch 21] loss: 0.3915465
Test set: Average loss: 1.1619, Accuracy: 2784/5000 (56%)
[epoch 22] loss: 0.3706510
Test set: Average loss: 1.1644, Accuracy: 2775/5000 (56%)
[epoch 23] loss: 0.3496765
Test set: Average loss: 1.1676, Accuracy: 2773/5000 (55%)
[epoch 24] loss: 0.3383444
Test set: Average loss: 1.1792, Accuracy: 2740/5000 (55%)
[epoch 25] loss: 0.3168473
Test set: Average loss: 1.1666, Accuracy: 2799/5000 (56%)
Validation:
Test set: Average loss: 1.1398, Accuracy: 2858/5000 (57%)
Test
Test set: Average loss: 1.1557, Accuracy: 2806/5000 (56%)
Test set: Average loss: 0.7203, Accuracy: 649/750 (87%)
1000
## seed: 11
Validation accuracy before training:
Test set: Average loss: 1.5972, Accuracy: 977/5000 (20%)
[epoch 1] loss: 1.2913773
Test set: Average loss: 1.2241, Accuracy: 2549/5000 (51%)
[epoch 2] loss: 1.0732048
Test set: Average loss: 1.1657, Accuracy: 2816/5000 (56%)
[epoch 3] loss: 0.9853700
Test set: Average loss: 1.1560, Accuracy: 2791/5000 (56%)
[epoch 4] loss: 0.9185229
Test set: Average loss: 1.1398, Accuracy: 2891/5000 (58%)
[epoch 5] loss: 0.8722303
Test set: Average loss: 1.1390, Accuracy: 2854/5000 (57%)
[epoch 6] loss: 0.8164210
Test set: Average loss: 1.1388, Accuracy: 2835/5000 (57%)
[epoch 7] loss: 0.7709379
Test set: Average loss: 1.1267, Accuracy: 2889/5000 (58%)
[epoch 8] loss: 0.7240457
Test set: Average loss: 1.1234, Accuracy: 2878/5000 (58%)
[epoch 9] loss: 0.6922314
Test set: Average loss: 1.1169, Accuracy: 2913/5000 (58%)
[epoch 10] loss: 0.6578367
Test set: Average loss: 1.1230, Accuracy: 2863/5000 (57%)
[epoch 11] loss: 0.6204313
Test set: Average loss: 1.1220, Accuracy: 2883/5000 (58%)
[epoch 12] loss: 0.5877448
Test set: Average loss: 1.1166, Accuracy: 2890/5000 (58%)
[epoch 13] loss: 0.5567414
Test set: Average loss: 1.1100, Accuracy: 2921/5000 (58%)
[epoch 14] loss: 0.5313032
Test set: Average loss: 1.1119, Accuracy: 2920/5000 (58%)
[epoch 15] loss: 0.4974040
Test set: Average loss: 1.1222, Accuracy: 2861/5000 (57%)
[epoch 16] loss: 0.4716389
Test set: Average loss: 1.1173, Accuracy: 2896/5000 (58%)
[epoch 17] loss: 0.4456421
Test set: Average loss: 1.1226, Accuracy: 2873/5000 (57%)
[epoch 18] loss: 0.4198737
Test set: Average loss: 1.1215, Accuracy: 2887/5000 (58%)
[epoch 19] loss: 0.3955101
Test set: Average loss: 1.1225, Accuracy: 2877/5000 (58%)
[epoch 20] loss: 0.3655437
Test set: Average loss: 1.1278, Accuracy: 2872/5000 (57%)
[epoch 21] loss: 0.3458094
Test set: Average loss: 1.1526, Accuracy: 2801/5000 (56%)
[epoch 22] loss: 0.3314852
Test set: Average loss: 1.1321, Accuracy: 2849/5000 (57%)
[epoch 23] loss: 0.3076052
Test set: Average loss: 1.1331, Accuracy: 2886/5000 (58%)
[epoch 24] loss: 0.2887958
Test set: Average loss: 1.1260, Accuracy: 2911/5000 (58%)
[epoch 25] loss: 0.2722229
Test set: Average loss: 1.1516, Accuracy: 2832/5000 (57%)
Validation:
Test set: Average loss: 1.1100, Accuracy: 2921/5000 (58%)
Test
Test set: Average loss: 1.1183, Accuracy: 2862/5000 (57%)
Test set: Average loss: 0.5096, Accuracy: 920/1000 (92%)
## seed: 12
Validation accuracy before training:
Test set: Average loss: 1.6043, Accuracy: 1146/5000 (23%)
[epoch 1] loss: 1.3193414
Test set: Average loss: 1.1987, Accuracy: 2721/5000 (54%)
[epoch 2] loss: 1.1050418
Test set: Average loss: 1.1619, Accuracy: 2824/5000 (56%)
[epoch 3] loss: 0.9958364
Test set: Average loss: 1.1540, Accuracy: 2849/5000 (57%)
[epoch 4] loss: 0.9496351
Test set: Average loss: 1.1294, Accuracy: 2930/5000 (59%)
[epoch 5] loss: 0.8947746
Test set: Average loss: 1.1307, Accuracy: 2906/5000 (58%)
[epoch 6] loss: 0.8375720
Test set: Average loss: 1.1254, Accuracy: 2898/5000 (58%)
[epoch 7] loss: 0.7996234
Test set: Average loss: 1.1252, Accuracy: 2885/5000 (58%)
[epoch 8] loss: 0.7577870
Test set: Average loss: 1.1165, Accuracy: 2922/5000 (58%)
[epoch 9] loss: 0.7201619
Test set: Average loss: 1.1087, Accuracy: 2953/5000 (59%)
[epoch 10] loss: 0.6690689
Test set: Average loss: 1.1162, Accuracy: 2916/5000 (58%)
[epoch 11] loss: 0.6524576
Test set: Average loss: 1.1036, Accuracy: 2971/5000 (59%)
[epoch 12] loss: 0.6020810
Test set: Average loss: 1.0983, Accuracy: 2953/5000 (59%)
[epoch 13] loss: 0.5811385
Test set: Average loss: 1.1228, Accuracy: 2867/5000 (57%)
[epoch 14] loss: 0.5451909
Test set: Average loss: 1.1283, Accuracy: 2842/5000 (57%)
[epoch 15] loss: 0.5185899
Test set: Average loss: 1.1096, Accuracy: 2940/5000 (59%)
[epoch 16] loss: 0.4872815
Test set: Average loss: 1.1190, Accuracy: 2922/5000 (58%)
[epoch 17] loss: 0.4580662
Test set: Average loss: 1.1156, Accuracy: 2910/5000 (58%)
[epoch 18] loss: 0.4350749
Test set: Average loss: 1.1233, Accuracy: 2904/5000 (58%)
[epoch 19] loss: 0.4064441
Test set: Average loss: 1.1304, Accuracy: 2880/5000 (58%)
[epoch 20] loss: 0.3862614
Test set: Average loss: 1.1058, Accuracy: 2953/5000 (59%)
[epoch 21] loss: 0.3591465
Test set: Average loss: 1.1261, Accuracy: 2915/5000 (58%)
[epoch 22] loss: 0.3442757
Test set: Average loss: 1.1215, Accuracy: 2903/5000 (58%)
[epoch 23] loss: 0.3229945
Test set: Average loss: 1.1286, Accuracy: 2882/5000 (58%)
[epoch 24] loss: 0.2989082
Test set: Average loss: 1.1344, Accuracy: 2879/5000 (58%)
[epoch 25] loss: 0.2903137
Test set: Average loss: 1.1513, Accuracy: 2814/5000 (56%)
Validation:
Test set: Average loss: 1.1036, Accuracy: 2971/5000 (59%)
Test
Test set: Average loss: 1.1178, Accuracy: 2873/5000 (57%)
Test set: Average loss: 0.6010, Accuracy: 876/1000 (88%)
## seed: 13
Validation accuracy before training:
Test set: Average loss: 1.6137, Accuracy: 1007/5000 (20%)
[epoch 1] loss: 1.3213630
Test set: Average loss: 1.2346, Accuracy: 2619/5000 (52%)
[epoch 2] loss: 1.1055758
Test set: Average loss: 1.1946, Accuracy: 2724/5000 (54%)
[epoch 3] loss: 1.0215140
Test set: Average loss: 1.1538, Accuracy: 2852/5000 (57%)
[epoch 4] loss: 0.9481508
Test set: Average loss: 1.1480, Accuracy: 2885/5000 (58%)
[epoch 5] loss: 0.9052946
Test set: Average loss: 1.1333, Accuracy: 2933/5000 (59%)
[epoch 6] loss: 0.8526833
Test set: Average loss: 1.1270, Accuracy: 2936/5000 (59%)
[epoch 7] loss: 0.7895854
Test set: Average loss: 1.1295, Accuracy: 2913/5000 (58%)
[epoch 8] loss: 0.7525203
Test set: Average loss: 1.1260, Accuracy: 2908/5000 (58%)
[epoch 9] loss: 0.7116701
Test set: Average loss: 1.1216, Accuracy: 2927/5000 (59%)
[epoch 10] loss: 0.6843978
Test set: Average loss: 1.1254, Accuracy: 2904/5000 (58%)
[epoch 11] loss: 0.6410635
Test set: Average loss: 1.1157, Accuracy: 2941/5000 (59%)
[epoch 12] loss: 0.6142543
Test set: Average loss: 1.1169, Accuracy: 2923/5000 (58%)
[epoch 13] loss: 0.5768413
Test set: Average loss: 1.1170, Accuracy: 2932/5000 (59%)
[epoch 14] loss: 0.5480075
Test set: Average loss: 1.1197, Accuracy: 2885/5000 (58%)
[epoch 15] loss: 0.5225008
Test set: Average loss: 1.1220, Accuracy: 2898/5000 (58%)
[epoch 16] loss: 0.4798571
Test set: Average loss: 1.1222, Accuracy: 2897/5000 (58%)
[epoch 17] loss: 0.4586241
Test set: Average loss: 1.1207, Accuracy: 2892/5000 (58%)
[epoch 18] loss: 0.4402870
Test set: Average loss: 1.1189, Accuracy: 2923/5000 (58%)
[epoch 19] loss: 0.4027656
Test set: Average loss: 1.1310, Accuracy: 2869/5000 (57%)
[epoch 20] loss: 0.3780233
Test set: Average loss: 1.1277, Accuracy: 2883/5000 (58%)
[epoch 21] loss: 0.3611441
Test set: Average loss: 1.1321, Accuracy: 2889/5000 (58%)
[epoch 22] loss: 0.3401468
Test set: Average loss: 1.1471, Accuracy: 2861/5000 (57%)
[epoch 23] loss: 0.3225875
Test set: Average loss: 1.1418, Accuracy: 2864/5000 (57%)
[epoch 24] loss: 0.3023938
Test set: Average loss: 1.1567, Accuracy: 2815/5000 (56%)
[epoch 25] loss: 0.2790476
Test set: Average loss: 1.1406, Accuracy: 2864/5000 (57%)
Validation:
Test set: Average loss: 1.1157, Accuracy: 2941/5000 (59%)
Test
Test set: Average loss: 1.1318, Accuracy: 2875/5000 (58%)
Test set: Average loss: 0.5968, Accuracy: 893/1000 (89%)
2500
## seed: 11
Validation accuracy before training:
Test set: Average loss: 1.5803, Accuracy: 1623/5000 (32%)
[epoch 1] loss: 1.2340189
Test set: Average loss: 1.1480, Accuracy: 2870/5000 (57%)
[epoch 2] loss: 1.0670309
Test set: Average loss: 1.1117, Accuracy: 2950/5000 (59%)
[epoch 3] loss: 0.9951216
Test set: Average loss: 1.0890, Accuracy: 2972/5000 (59%)
[epoch 4] loss: 0.9413681
Test set: Average loss: 1.0784, Accuracy: 3011/5000 (60%)
[epoch 5] loss: 0.8943635
Test set: Average loss: 1.0611, Accuracy: 3077/5000 (62%)
[epoch 6] loss: 0.8534200
Test set: Average loss: 1.0527, Accuracy: 3066/5000 (61%)
[epoch 7] loss: 0.8084204
Test set: Average loss: 1.0473, Accuracy: 3055/5000 (61%)
[epoch 8] loss: 0.7615976
Test set: Average loss: 1.0397, Accuracy: 3083/5000 (62%)
[epoch 9] loss: 0.7217232
Test set: Average loss: 1.0564, Accuracy: 3017/5000 (60%)
[epoch 10] loss: 0.6956402
Test set: Average loss: 1.0398, Accuracy: 3050/5000 (61%)
[epoch 11] loss: 0.6494745
Test set: Average loss: 1.0296, Accuracy: 3085/5000 (62%)
[epoch 12] loss: 0.6037469
Test set: Average loss: 1.0251, Accuracy: 3092/5000 (62%)
[epoch 13] loss: 0.5622804
Test set: Average loss: 1.0331, Accuracy: 3067/5000 (61%)
[epoch 14] loss: 0.5250573
Test set: Average loss: 1.0203, Accuracy: 3099/5000 (62%)
[epoch 15] loss: 0.4920466
Test set: Average loss: 1.0264, Accuracy: 3089/5000 (62%)
[epoch 16] loss: 0.4535446
Test set: Average loss: 1.0378, Accuracy: 3088/5000 (62%)
[epoch 17] loss: 0.4219207
Test set: Average loss: 1.0257, Accuracy: 3095/5000 (62%)
[epoch 18] loss: 0.3928841
Test set: Average loss: 1.0378, Accuracy: 3080/5000 (62%)
[epoch 19] loss: 0.3659092
Test set: Average loss: 1.0476, Accuracy: 3048/5000 (61%)
[epoch 20] loss: 0.3242201
Test set: Average loss: 1.0452, Accuracy: 3084/5000 (62%)
[epoch 21] loss: 0.2916189
Test set: Average loss: 1.0511, Accuracy: 3052/5000 (61%)
[epoch 22] loss: 0.2623034
Test set: Average loss: 1.0475, Accuracy: 3093/5000 (62%)
[epoch 23] loss: 0.2384782
Test set: Average loss: 1.0517, Accuracy: 3078/5000 (62%)
[epoch 24] loss: 0.2177507
Test set: Average loss: 1.0672, Accuracy: 3063/5000 (61%)
[epoch 25] loss: 0.1971168
Test set: Average loss: 1.0720, Accuracy: 3043/5000 (61%)
Validation:
Test set: Average loss: 1.0203, Accuracy: 3099/5000 (62%)
Test
Test set: Average loss: 1.0277, Accuracy: 3091/5000 (62%)
Test set: Average loss: 0.4711, Accuracy: 2271/2500 (91%)
## seed: 12
Validation accuracy before training:
Test set: Average loss: 1.6261, Accuracy: 1001/5000 (20%)
[epoch 1] loss: 1.2399294
Test set: Average loss: 1.1528, Accuracy: 2881/5000 (58%)
[epoch 2] loss: 1.0627918
Test set: Average loss: 1.1246, Accuracy: 2960/5000 (59%)
[epoch 3] loss: 0.9994706
Test set: Average loss: 1.1029, Accuracy: 2984/5000 (60%)
[epoch 4] loss: 0.9383994
Test set: Average loss: 1.0840, Accuracy: 3001/5000 (60%)
[epoch 5] loss: 0.8980134
Test set: Average loss: 1.0735, Accuracy: 3066/5000 (61%)
[epoch 6] loss: 0.8571703
Test set: Average loss: 1.0500, Accuracy: 3107/5000 (62%)
[epoch 7] loss: 0.8075726
Test set: Average loss: 1.0555, Accuracy: 3052/5000 (61%)
[epoch 8] loss: 0.7691923
Test set: Average loss: 1.0510, Accuracy: 3073/5000 (61%)
[epoch 9] loss: 0.7230092
Test set: Average loss: 1.0457, Accuracy: 3087/5000 (62%)
[epoch 10] loss: 0.6819264
Test set: Average loss: 1.0459, Accuracy: 3087/5000 (62%)
[epoch 11] loss: 0.6435784
Test set: Average loss: 1.0306, Accuracy: 3097/5000 (62%)
[epoch 12] loss: 0.6047909
Test set: Average loss: 1.0296, Accuracy: 3106/5000 (62%)
[epoch 13] loss: 0.5672114
Test set: Average loss: 1.0330, Accuracy: 3089/5000 (62%)
[epoch 14] loss: 0.5275499
Test set: Average loss: 1.0436, Accuracy: 3079/5000 (62%)
[epoch 15] loss: 0.4882352
Test set: Average loss: 1.0272, Accuracy: 3100/5000 (62%)
[epoch 16] loss: 0.4544692
Test set: Average loss: 1.0284, Accuracy: 3086/5000 (62%)
[epoch 17] loss: 0.4181565
Test set: Average loss: 1.0591, Accuracy: 3025/5000 (60%)
[epoch 18] loss: 0.3806467
Test set: Average loss: 1.0307, Accuracy: 3063/5000 (61%)
[epoch 19] loss: 0.3475889
Test set: Average loss: 1.0672, Accuracy: 3011/5000 (60%)
[epoch 20] loss: 0.3237635
Test set: Average loss: 1.0496, Accuracy: 3059/5000 (61%)
[epoch 21] loss: 0.2961321
Test set: Average loss: 1.0417, Accuracy: 3073/5000 (61%)
[epoch 22] loss: 0.2619357
Test set: Average loss: 1.0676, Accuracy: 3029/5000 (61%)
[epoch 23] loss: 0.2413308
Test set: Average loss: 1.0531, Accuracy: 3053/5000 (61%)
[epoch 24] loss: 0.2148922
Test set: Average loss: 1.0494, Accuracy: 3067/5000 (61%)
[epoch 25] loss: 0.1939252
Test set: Average loss: 1.0567, Accuracy: 3049/5000 (61%)
Validation:
Test set: Average loss: 1.0500, Accuracy: 3107/5000 (62%)
Test
Test set: Average loss: 1.0544, Accuracy: 3031/5000 (61%)
Test set: Average loss: 0.7905, Accuracy: 1930/2500 (77%)
## seed: 13
Validation accuracy before training:
Test set: Average loss: 1.6069, Accuracy: 999/5000 (20%)
[epoch 1] loss: 1.2356789
Test set: Average loss: 1.1657, Accuracy: 2826/5000 (57%)
[epoch 2] loss: 1.0749982
Test set: Average loss: 1.1184, Accuracy: 2935/5000 (59%)
[epoch 3] loss: 1.0043124
Test set: Average loss: 1.1038, Accuracy: 2976/5000 (60%)
[epoch 4] loss: 0.9557724
Test set: Average loss: 1.0833, Accuracy: 2970/5000 (59%)
[epoch 5] loss: 0.9054160
Test set: Average loss: 1.0713, Accuracy: 3015/5000 (60%)
[epoch 6] loss: 0.8515966
Test set: Average loss: 1.0664, Accuracy: 3070/5000 (61%)
[epoch 7] loss: 0.8191677
Test set: Average loss: 1.0501, Accuracy: 3093/5000 (62%)
[epoch 8] loss: 0.7702424
Test set: Average loss: 1.0473, Accuracy: 3068/5000 (61%)
[epoch 9] loss: 0.7253998
Test set: Average loss: 1.0409, Accuracy: 3082/5000 (62%)
[epoch 10] loss: 0.6935205
Test set: Average loss: 1.0441, Accuracy: 3084/5000 (62%)
[epoch 11] loss: 0.6543664
Test set: Average loss: 1.0477, Accuracy: 3055/5000 (61%)
[epoch 12] loss: 0.6300815
Test set: Average loss: 1.0307, Accuracy: 3099/5000 (62%)
[epoch 13] loss: 0.5862968
Test set: Average loss: 1.0369, Accuracy: 3110/5000 (62%)
[epoch 14] loss: 0.5533639
Test set: Average loss: 1.0338, Accuracy: 3096/5000 (62%)
[epoch 15] loss: 0.5115318
Test set: Average loss: 1.0399, Accuracy: 3069/5000 (61%)
[epoch 16] loss: 0.4654490
Test set: Average loss: 1.0225, Accuracy: 3094/5000 (62%)
[epoch 17] loss: 0.4333500
Test set: Average loss: 1.0372, Accuracy: 3097/5000 (62%)
[epoch 18] loss: 0.3999995
Test set: Average loss: 1.0327, Accuracy: 3099/5000 (62%)
[epoch 19] loss: 0.3685350
Test set: Average loss: 1.0494, Accuracy: 3057/5000 (61%)
[epoch 20] loss: 0.3390312
Test set: Average loss: 1.0404, Accuracy: 3074/5000 (61%)
[epoch 21] loss: 0.3106281
Test set: Average loss: 1.0435, Accuracy: 3070/5000 (61%)
[epoch 22] loss: 0.2807999
Test set: Average loss: 1.0519, Accuracy: 3047/5000 (61%)
[epoch 23] loss: 0.2592002
Test set: Average loss: 1.0593, Accuracy: 3070/5000 (61%)
[epoch 24] loss: 0.2335799
Test set: Average loss: 1.0553, Accuracy: 3062/5000 (61%)
[epoch 25] loss: 0.2152620
Test set: Average loss: 1.0489, Accuracy: 3104/5000 (62%)
Validation:
Test set: Average loss: 1.0369, Accuracy: 3110/5000 (62%)
Test
Test set: Average loss: 1.0652, Accuracy: 3023/5000 (60%)
Test set: Average loss: 0.5525, Accuracy: 2176/2500 (87%)
5000
## seed: 11
Validation accuracy before training:
Test set: Average loss: 1.6559, Accuracy: 758/5000 (15%)
[epoch 1] loss: 1.1796178
Test set: Average loss: 1.1051, Accuracy: 2949/5000 (59%)
[epoch 2] loss: 1.0418608
Test set: Average loss: 1.0698, Accuracy: 3019/5000 (60%)
[epoch 3] loss: 0.9771966
Test set: Average loss: 1.0343, Accuracy: 3095/5000 (62%)
[epoch 4] loss: 0.9222073
Test set: Average loss: 1.0210, Accuracy: 3119/5000 (62%)
[epoch 5] loss: 0.8819184
Test set: Average loss: 1.0129, Accuracy: 3119/5000 (62%)
[epoch 6] loss: 0.8309081
Test set: Average loss: 0.9980, Accuracy: 3161/5000 (63%)
[epoch 7] loss: 0.7866067
Test set: Average loss: 1.0095, Accuracy: 3135/5000 (63%)
[epoch 8] loss: 0.7401087
Test set: Average loss: 0.9873, Accuracy: 3186/5000 (64%)
[epoch 9] loss: 0.6943086
Test set: Average loss: 0.9669, Accuracy: 3215/5000 (64%)
[epoch 10] loss: 0.6448137
Test set: Average loss: 0.9698, Accuracy: 3204/5000 (64%)
[epoch 11] loss: 0.6010382
Test set: Average loss: 0.9833, Accuracy: 3141/5000 (63%)
[epoch 12] loss: 0.5499515
Test set: Average loss: 0.9716, Accuracy: 3207/5000 (64%)
[epoch 13] loss: 0.5040938
Test set: Average loss: 0.9749, Accuracy: 3216/5000 (64%)
[epoch 14] loss: 0.4527518
Test set: Average loss: 0.9663, Accuracy: 3196/5000 (64%)
[epoch 15] loss: 0.4028222
Test set: Average loss: 0.9698, Accuracy: 3221/5000 (64%)
[epoch 16] loss: 0.3688789
Test set: Average loss: 0.9709, Accuracy: 3241/5000 (65%)
[epoch 17] loss: 0.3194111
Test set: Average loss: 0.9873, Accuracy: 3170/5000 (63%)
[epoch 18] loss: 0.2826670
Test set: Average loss: 0.9940, Accuracy: 3189/5000 (64%)
[epoch 19] loss: 0.2425327
Test set: Average loss: 0.9976, Accuracy: 3227/5000 (65%)
[epoch 20] loss: 0.2086679
Test set: Average loss: 1.0152, Accuracy: 3180/5000 (64%)
[epoch 21] loss: 0.1837414
Test set: Average loss: 1.0163, Accuracy: 3197/5000 (64%)
[epoch 22] loss: 0.1545816
Test set: Average loss: 1.0228, Accuracy: 3197/5000 (64%)
[epoch 23] loss: 0.1356115
Test set: Average loss: 1.0241, Accuracy: 3192/5000 (64%)
[epoch 24] loss: 0.1166610
Test set: Average loss: 1.0287, Accuracy: 3208/5000 (64%)
[epoch 25] loss: 0.0982894
Test set: Average loss: 1.0293, Accuracy: 3196/5000 (64%)
Validation:
Test set: Average loss: 0.9709, Accuracy: 3241/5000 (65%)
Test
Test set: Average loss: 0.9622, Accuracy: 3225/5000 (64%)
Test set: Average loss: 0.3121, Accuracy: 4712/5000 (94%)
## seed: 12
Validation accuracy before training:
Test set: Average loss: 1.6221, Accuracy: 1067/5000 (21%)
[epoch 1] loss: 1.2117205
Test set: Average loss: 1.1239, Accuracy: 3003/5000 (60%)
[epoch 2] loss: 1.0618693
Test set: Average loss: 1.0785, Accuracy: 3034/5000 (61%)
[epoch 3] loss: 0.9874452
Test set: Average loss: 1.0655, Accuracy: 3075/5000 (62%)
[epoch 4] loss: 0.9335105
Test set: Average loss: 1.0213, Accuracy: 3184/5000 (64%)
[epoch 5] loss: 0.8818152
Test set: Average loss: 1.0137, Accuracy: 3188/5000 (64%)
[epoch 6] loss: 0.8292091
Test set: Average loss: 0.9943, Accuracy: 3222/5000 (64%)
[epoch 7] loss: 0.7753461
Test set: Average loss: 1.0120, Accuracy: 3149/5000 (63%)
[epoch 8] loss: 0.7294253
Test set: Average loss: 0.9854, Accuracy: 3201/5000 (64%)
[epoch 9] loss: 0.6804295
Test set: Average loss: 0.9710, Accuracy: 3228/5000 (65%)
[epoch 10] loss: 0.6337619
Test set: Average loss: 0.9728, Accuracy: 3219/5000 (64%)
[epoch 11] loss: 0.5846700
Test set: Average loss: 0.9682, Accuracy: 3225/5000 (64%)
[epoch 12] loss: 0.5298436
Test set: Average loss: 0.9604, Accuracy: 3249/5000 (65%)
[epoch 13] loss: 0.4818826
Test set: Average loss: 0.9664, Accuracy: 3243/5000 (65%)
[epoch 14] loss: 0.4334354
Test set: Average loss: 0.9598, Accuracy: 3265/5000 (65%)
[epoch 15] loss: 0.3856199
Test set: Average loss: 0.9759, Accuracy: 3211/5000 (64%)
[epoch 16] loss: 0.3402327
Test set: Average loss: 0.9769, Accuracy: 3219/5000 (64%)
[epoch 17] loss: 0.3015897
Test set: Average loss: 0.9830, Accuracy: 3223/5000 (64%)
[epoch 18] loss: 0.2614040
Test set: Average loss: 0.9868, Accuracy: 3216/5000 (64%)
[epoch 19] loss: 0.2272236
Test set: Average loss: 0.9698, Accuracy: 3283/5000 (66%)
[epoch 20] loss: 0.1943449
Test set: Average loss: 0.9800, Accuracy: 3248/5000 (65%)
[epoch 21] loss: 0.1680378
Test set: Average loss: 0.9906, Accuracy: 3276/5000 (66%)
[epoch 22] loss: 0.1418812
Test set: Average loss: 1.0309, Accuracy: 3192/5000 (64%)
[epoch 23] loss: 0.1235660
Test set: Average loss: 1.0022, Accuracy: 3279/5000 (66%)
[epoch 24] loss: 0.1044217
Test set: Average loss: 1.0193, Accuracy: 3246/5000 (65%)
[epoch 25] loss: 0.0904345
Test set: Average loss: 1.0239, Accuracy: 3261/5000 (65%)
Validation:
Test set: Average loss: 0.9698, Accuracy: 3283/5000 (66%)
Test
Test set: Average loss: 1.0067, Accuracy: 3191/5000 (64%)
Test set: Average loss: 0.1859, Accuracy: 4912/5000 (98%)
## seed: 13
Validation accuracy before training:
Test set: Average loss: 1.6094, Accuracy: 1120/5000 (22%)
[epoch 1] loss: 1.1788233
Test set: Average loss: 1.1220, Accuracy: 2916/5000 (58%)
[epoch 2] loss: 1.0409372
Test set: Average loss: 1.0776, Accuracy: 3060/5000 (61%)
[epoch 3] loss: 0.9675404
Test set: Average loss: 1.0600, Accuracy: 3070/5000 (61%)
[epoch 4] loss: 0.9123135
Test set: Average loss: 1.0409, Accuracy: 3070/5000 (61%)
[epoch 5] loss: 0.8596034
Test set: Average loss: 1.0221, Accuracy: 3074/5000 (61%)
[epoch 6] loss: 0.8119701
Test set: Average loss: 1.0036, Accuracy: 3149/5000 (63%)
[epoch 7] loss: 0.7640009
Test set: Average loss: 1.0104, Accuracy: 3130/5000 (63%)
[epoch 8] loss: 0.7181099
Test set: Average loss: 0.9893, Accuracy: 3170/5000 (63%)
[epoch 9] loss: 0.6671813
Test set: Average loss: 0.9715, Accuracy: 3192/5000 (64%)
[epoch 10] loss: 0.6199736
Test set: Average loss: 0.9851, Accuracy: 3184/5000 (64%)
[epoch 11] loss: 0.5749584
Test set: Average loss: 0.9823, Accuracy: 3162/5000 (63%)
[epoch 12] loss: 0.5194278
Test set: Average loss: 0.9728, Accuracy: 3197/5000 (64%)
[epoch 13] loss: 0.4769166
Test set: Average loss: 0.9741, Accuracy: 3189/5000 (64%)
[epoch 14] loss: 0.4266334
Test set: Average loss: 0.9709, Accuracy: 3213/5000 (64%)
[epoch 15] loss: 0.3844390
Test set: Average loss: 0.9843, Accuracy: 3209/5000 (64%)
[epoch 16] loss: 0.3404472
Test set: Average loss: 0.9648, Accuracy: 3235/5000 (65%)
[epoch 17] loss: 0.2973615
Test set: Average loss: 0.9804, Accuracy: 3205/5000 (64%)
[epoch 18] loss: 0.2659415
Test set: Average loss: 0.9955, Accuracy: 3184/5000 (64%)
[epoch 19] loss: 0.2287724
Test set: Average loss: 0.9941, Accuracy: 3210/5000 (64%)
[epoch 20] loss: 0.1992968
Test set: Average loss: 0.9873, Accuracy: 3225/5000 (64%)
[epoch 21] loss: 0.1687431
Test set: Average loss: 1.0037, Accuracy: 3208/5000 (64%)
[epoch 22] loss: 0.1427685
Test set: Average loss: 1.0066, Accuracy: 3213/5000 (64%)
[epoch 23] loss: 0.1249131
Test set: Average loss: 1.0192, Accuracy: 3215/5000 (64%)
[epoch 24] loss: 0.1112232
Test set: Average loss: 1.0302, Accuracy: 3189/5000 (64%)
[epoch 25] loss: 0.0911338
Test set: Average loss: 1.0392, Accuracy: 3212/5000 (64%)
Validation:
Test set: Average loss: 0.9648, Accuracy: 3235/5000 (65%)
Test
Test set: Average loss: 0.9748, Accuracy: 3231/5000 (65%)
Test set: Average loss: 0.2825, Accuracy: 4788/5000 (96%)
10000
## seed: 11
Validation accuracy before training:
Test set: Average loss: 1.6270, Accuracy: 948/5000 (19%)
[epoch 1] loss: 1.1628685
Test set: Average loss: 1.0828, Accuracy: 3063/5000 (61%)
[epoch 2] loss: 1.0242540
Test set: Average loss: 1.0311, Accuracy: 3167/5000 (63%)
[epoch 3] loss: 0.9540137
Test set: Average loss: 1.0089, Accuracy: 3175/5000 (64%)
[epoch 4] loss: 0.8993637
Test set: Average loss: 0.9807, Accuracy: 3220/5000 (64%)
[epoch 5] loss: 0.8428458
Test set: Average loss: 0.9683, Accuracy: 3242/5000 (65%)
[epoch 6] loss: 0.7870699
Test set: Average loss: 0.9439, Accuracy: 3290/5000 (66%)
[epoch 7] loss: 0.7324007
Test set: Average loss: 0.9420, Accuracy: 3273/5000 (65%)
[epoch 8] loss: 0.6748290
Test set: Average loss: 0.9282, Accuracy: 3288/5000 (66%)
[epoch 9] loss: 0.6148764
Test set: Average loss: 0.9286, Accuracy: 3305/5000 (66%)
[epoch 10] loss: 0.5560352
Test set: Average loss: 0.9083, Accuracy: 3317/5000 (66%)
[epoch 11] loss: 0.4941326
Test set: Average loss: 0.8975, Accuracy: 3359/5000 (67%)
[epoch 12] loss: 0.4364545
Test set: Average loss: 0.8842, Accuracy: 3414/5000 (68%)
[epoch 13] loss: 0.3702732
Test set: Average loss: 0.9593, Accuracy: 3265/5000 (65%)
[epoch 14] loss: 0.3131400
Test set: Average loss: 0.9073, Accuracy: 3368/5000 (67%)
[epoch 15] loss: 0.2636990
Test set: Average loss: 0.9323, Accuracy: 3324/5000 (66%)
[epoch 16] loss: 0.2126096
Test set: Average loss: 0.9315, Accuracy: 3324/5000 (66%)
[epoch 17] loss: 0.1747246
Test set: Average loss: 0.9502, Accuracy: 3331/5000 (67%)
[epoch 18] loss: 0.1413989
Test set: Average loss: 0.9505, Accuracy: 3364/5000 (67%)
[epoch 19] loss: 0.1142583
Test set: Average loss: 0.9494, Accuracy: 3366/5000 (67%)
[epoch 20] loss: 0.0915838
Test set: Average loss: 0.9692, Accuracy: 3374/5000 (67%)
[epoch 21] loss: 0.0687116
Test set: Average loss: 0.9809, Accuracy: 3383/5000 (68%)
[epoch 22] loss: 0.0575522
Test set: Average loss: 1.0123, Accuracy: 3350/5000 (67%)
[epoch 23] loss: 0.0552091
Test set: Average loss: 1.0232, Accuracy: 3368/5000 (67%)
[epoch 24] loss: 0.0385572
Test set: Average loss: 1.0416, Accuracy: 3363/5000 (67%)
[epoch 25] loss: 0.0279329
Test set: Average loss: 1.0523, Accuracy: 3356/5000 (67%)
Validation:
Test set: Average loss: 0.8842, Accuracy: 3414/5000 (68%)
Test
Test set: Average loss: 0.8932, Accuracy: 3381/5000 (68%)
Test set: Average loss: 0.3537, Accuracy: 9253/10000 (93%)
## seed: 12
Validation accuracy before training:
Test set: Average loss: 1.6285, Accuracy: 779/5000 (16%)
[epoch 1] loss: 1.1475157
Test set: Average loss: 1.0652, Accuracy: 3071/5000 (61%)
[epoch 2] loss: 1.0152091
Test set: Average loss: 1.0144, Accuracy: 3166/5000 (63%)
[epoch 3] loss: 0.9472963
Test set: Average loss: 0.9971, Accuracy: 3169/5000 (63%)
[epoch 4] loss: 0.8906939
Test set: Average loss: 0.9785, Accuracy: 3210/5000 (64%)
[epoch 5] loss: 0.8330334
Test set: Average loss: 0.9457, Accuracy: 3294/5000 (66%)
[epoch 6] loss: 0.7799498
Test set: Average loss: 0.9330, Accuracy: 3306/5000 (66%)
[epoch 7] loss: 0.7264385
Test set: Average loss: 0.9318, Accuracy: 3285/5000 (66%)
[epoch 8] loss: 0.6709350
Test set: Average loss: 0.9078, Accuracy: 3351/5000 (67%)
[epoch 9] loss: 0.6128139
Test set: Average loss: 0.9125, Accuracy: 3349/5000 (67%)
[epoch 10] loss: 0.5533908
Test set: Average loss: 0.8984, Accuracy: 3356/5000 (67%)
[epoch 11] loss: 0.4941248
Test set: Average loss: 0.9084, Accuracy: 3304/5000 (66%)
[epoch 12] loss: 0.4376515
Test set: Average loss: 0.8844, Accuracy: 3394/5000 (68%)
[epoch 13] loss: 0.3750687
Test set: Average loss: 0.9028, Accuracy: 3328/5000 (67%)
[epoch 14] loss: 0.3270659
Test set: Average loss: 0.8980, Accuracy: 3397/5000 (68%)
[epoch 15] loss: 0.2731128
Test set: Average loss: 0.9104, Accuracy: 3344/5000 (67%)
[epoch 16] loss: 0.2221009
Test set: Average loss: 0.9162, Accuracy: 3374/5000 (67%)
[epoch 17] loss: 0.1812985
Test set: Average loss: 0.9418, Accuracy: 3328/5000 (67%)
[epoch 18] loss: 0.1522731
Test set: Average loss: 0.9461, Accuracy: 3345/5000 (67%)
[epoch 19] loss: 0.1218489
Test set: Average loss: 0.9685, Accuracy: 3315/5000 (66%)
[epoch 20] loss: 0.0969771
Test set: Average loss: 0.9709, Accuracy: 3362/5000 (67%)
[epoch 21] loss: 0.0764179
Test set: Average loss: 0.9825, Accuracy: 3346/5000 (67%)
[epoch 22] loss: 0.0617183
Test set: Average loss: 0.9949, Accuracy: 3341/5000 (67%)
[epoch 23] loss: 0.0510660
Test set: Average loss: 1.0443, Accuracy: 3299/5000 (66%)
[epoch 24] loss: 0.0479322
Test set: Average loss: 1.0234, Accuracy: 3367/5000 (67%)
[epoch 25] loss: 0.0316738
Test set: Average loss: 1.0453, Accuracy: 3328/5000 (67%)
Validation:
Test set: Average loss: 0.8980, Accuracy: 3397/5000 (68%)
Test
Test set: Average loss: 0.9231, Accuracy: 3335/5000 (67%)
Test set: Average loss: 0.2721, Accuracy: 9536/10000 (95%)
## seed: 13
Validation accuracy before training:
Test set: Average loss: 1.6214, Accuracy: 922/5000 (18%)
[epoch 1] loss: 1.1584755
Test set: Average loss: 1.0732, Accuracy: 3069/5000 (61%)
[epoch 2] loss: 1.0125443
Test set: Average loss: 1.0330, Accuracy: 3119/5000 (62%)
[epoch 3] loss: 0.9450704
Test set: Average loss: 1.0007, Accuracy: 3182/5000 (64%)
[epoch 4] loss: 0.8813316
Test set: Average loss: 0.9832, Accuracy: 3211/5000 (64%)
[epoch 5] loss: 0.8280267
Test set: Average loss: 0.9520, Accuracy: 3277/5000 (66%)
[epoch 6] loss: 0.7718919
Test set: Average loss: 0.9573, Accuracy: 3255/5000 (65%)
[epoch 7] loss: 0.7155036
Test set: Average loss: 0.9425, Accuracy: 3218/5000 (64%)
[epoch 8] loss: 0.6565038
Test set: Average loss: 0.9206, Accuracy: 3297/5000 (66%)
[epoch 9] loss: 0.5977251
Test set: Average loss: 0.9159, Accuracy: 3319/5000 (66%)
[epoch 10] loss: 0.5402894
Test set: Average loss: 0.8982, Accuracy: 3354/5000 (67%)
[epoch 11] loss: 0.4774079
Test set: Average loss: 0.8978, Accuracy: 3357/5000 (67%)
[epoch 12] loss: 0.4211533
Test set: Average loss: 0.9120, Accuracy: 3299/5000 (66%)
[epoch 13] loss: 0.3619305
Test set: Average loss: 0.9122, Accuracy: 3333/5000 (67%)
[epoch 14] loss: 0.3064492
Test set: Average loss: 0.9055, Accuracy: 3344/5000 (67%)
[epoch 15] loss: 0.2580021
Test set: Average loss: 0.9143, Accuracy: 3355/5000 (67%)
[epoch 16] loss: 0.2107120
Test set: Average loss: 0.9238, Accuracy: 3352/5000 (67%)
[epoch 17] loss: 0.1696933
Test set: Average loss: 0.9382, Accuracy: 3323/5000 (66%)
[epoch 18] loss: 0.1389662
Test set: Average loss: 0.9491, Accuracy: 3340/5000 (67%)
[epoch 19] loss: 0.1146560
Test set: Average loss: 0.9565, Accuracy: 3361/5000 (67%)
[epoch 20] loss: 0.0871840
Test set: Average loss: 0.9716, Accuracy: 3364/5000 (67%)
[epoch 21] loss: 0.0724386
Test set: Average loss: 0.9987, Accuracy: 3351/5000 (67%)
[epoch 22] loss: 0.0556223
Test set: Average loss: 1.0126, Accuracy: 3350/5000 (67%)
[epoch 23] loss: 0.0463231
Test set: Average loss: 1.0139, Accuracy: 3394/5000 (68%)
[epoch 24] loss: 0.0357462
Test set: Average loss: 1.0360, Accuracy: 3372/5000 (67%)
[epoch 25] loss: 0.0346885
Test set: Average loss: 1.0498, Accuracy: 3362/5000 (67%)
Validation:
Test set: Average loss: 1.0139, Accuracy: 3394/5000 (68%)
Test
Test set: Average loss: 1.0253, Accuracy: 3347/5000 (67%)
Test set: Average loss: 0.0356, Accuracy: 9989/10000 (100%)
15000
## seed: 11
Validation accuracy before training:
Test set: Average loss: 1.6297, Accuracy: 822/5000 (16%)
[epoch 1] loss: 1.1145098
Test set: Average loss: 1.0549, Accuracy: 3055/5000 (61%)
[epoch 2] loss: 0.9906573
Test set: Average loss: 1.0022, Accuracy: 3150/5000 (63%)
[epoch 3] loss: 0.9173596
Test set: Average loss: 0.9548, Accuracy: 3284/5000 (66%)
[epoch 4] loss: 0.8556831
Test set: Average loss: 0.9365, Accuracy: 3276/5000 (66%)
[epoch 5] loss: 0.8002006
Test set: Average loss: 0.9139, Accuracy: 3316/5000 (66%)
[epoch 6] loss: 0.7380650
Test set: Average loss: 0.8967, Accuracy: 3335/5000 (67%)
[epoch 7] loss: 0.6791465
Test set: Average loss: 0.8722, Accuracy: 3397/5000 (68%)
[epoch 8] loss: 0.6165326
Test set: Average loss: 0.8646, Accuracy: 3421/5000 (68%)
[epoch 9] loss: 0.5506370
Test set: Average loss: 0.8705, Accuracy: 3428/5000 (69%)
[epoch 10] loss: 0.4870936
Test set: Average loss: 0.8596, Accuracy: 3435/5000 (69%)
[epoch 11] loss: 0.4228588
Test set: Average loss: 0.8511, Accuracy: 3458/5000 (69%)
[epoch 12] loss: 0.3586275
Test set: Average loss: 0.8769, Accuracy: 3420/5000 (68%)
[epoch 13] loss: 0.2982617
Test set: Average loss: 0.8703, Accuracy: 3451/5000 (69%)
[epoch 14] loss: 0.2446889
Test set: Average loss: 0.8793, Accuracy: 3444/5000 (69%)
[epoch 15] loss: 0.1985495
Test set: Average loss: 0.8981, Accuracy: 3410/5000 (68%)
[epoch 16] loss: 0.1583507
Test set: Average loss: 0.9028, Accuracy: 3460/5000 (69%)
[epoch 17] loss: 0.1271753
Test set: Average loss: 0.9357, Accuracy: 3434/5000 (69%)
[epoch 18] loss: 0.0967082
Test set: Average loss: 0.9327, Accuracy: 3448/5000 (69%)
[epoch 19] loss: 0.0725274
Test set: Average loss: 0.9664, Accuracy: 3426/5000 (69%)
[epoch 20] loss: 0.0632172
Test set: Average loss: 0.9913, Accuracy: 3428/5000 (69%)
[epoch 21] loss: 0.0534986
Test set: Average loss: 1.0223, Accuracy: 3396/5000 (68%)
[epoch 22] loss: 0.0392734
Test set: Average loss: 1.0226, Accuracy: 3430/5000 (69%)
[epoch 23] loss: 0.0311484
Test set: Average loss: 1.0839, Accuracy: 3380/5000 (68%)
[epoch 24] loss: 0.0211159
Test set: Average loss: 1.0976, Accuracy: 3401/5000 (68%)
[epoch 25] loss: 0.0423059
Epoch 24: reducing learning rate of group 0 to 5.0000e-06.
Test set: Average loss: 1.1595, Accuracy: 3304/5000 (66%)
Validation:
Test set: Average loss: 0.9028, Accuracy: 3460/5000 (69%)
Test
Test set: Average loss: 0.9366, Accuracy: 3407/5000 (68%)
Test set: Average loss: 0.1185, Accuracy: 14782/15000 (99%)
## seed: 12
Validation accuracy before training:
Test set: Average loss: 1.6348, Accuracy: 742/5000 (15%)
[epoch 1] loss: 1.1150916
Test set: Average loss: 1.0400, Accuracy: 3105/5000 (62%)
[epoch 2] loss: 0.9898562
Test set: Average loss: 0.9900, Accuracy: 3224/5000 (64%)
[epoch 3] loss: 0.9206680
Test set: Average loss: 0.9609, Accuracy: 3267/5000 (65%)
[epoch 4] loss: 0.8584976
Test set: Average loss: 0.9297, Accuracy: 3303/5000 (66%)
[epoch 5] loss: 0.8035046
Test set: Average loss: 0.9002, Accuracy: 3359/5000 (67%)
[epoch 6] loss: 0.7421995
Test set: Average loss: 0.8822, Accuracy: 3405/5000 (68%)
[epoch 7] loss: 0.6820232
Test set: Average loss: 0.8757, Accuracy: 3404/5000 (68%)
[epoch 8] loss: 0.6182619
Test set: Average loss: 0.8542, Accuracy: 3432/5000 (69%)
[epoch 9] loss: 0.5558417
Test set: Average loss: 0.8590, Accuracy: 3408/5000 (68%)
[epoch 10] loss: 0.4911673
Test set: Average loss: 0.8359, Accuracy: 3462/5000 (69%)
[epoch 11] loss: 0.4221389
Test set: Average loss: 0.8430, Accuracy: 3475/5000 (70%)
[epoch 12] loss: 0.3609511
Test set: Average loss: 0.8594, Accuracy: 3430/5000 (69%)
[epoch 13] loss: 0.2966473
Test set: Average loss: 0.8788, Accuracy: 3426/5000 (69%)
[epoch 14] loss: 0.2454652
Test set: Average loss: 0.8633, Accuracy: 3491/5000 (70%)
[epoch 15] loss: 0.1948898
Test set: Average loss: 0.8764, Accuracy: 3486/5000 (70%)
[epoch 16] loss: 0.1531137
Test set: Average loss: 0.8956, Accuracy: 3464/5000 (69%)
[epoch 17] loss: 0.1181160
Test set: Average loss: 0.9151, Accuracy: 3458/5000 (69%)
[epoch 18] loss: 0.0954083
Test set: Average loss: 0.9426, Accuracy: 3439/5000 (69%)
[epoch 19] loss: 0.0692756
Test set: Average loss: 0.9577, Accuracy: 3447/5000 (69%)
[epoch 20] loss: 0.0566129
Test set: Average loss: 0.9791, Accuracy: 3438/5000 (69%)
[epoch 21] loss: 0.0420568
Test set: Average loss: 0.9962, Accuracy: 3461/5000 (69%)
[epoch 22] loss: 0.0561686
Epoch 21: reducing learning rate of group 0 to 5.0000e-06.
Test set: Average loss: 1.1011, Accuracy: 3373/5000 (67%)
[epoch 23] loss: 0.0277900
Test set: Average loss: 1.0109, Accuracy: 3440/5000 (69%)
[epoch 24] loss: 0.0222103
Test set: Average loss: 1.0124, Accuracy: 3447/5000 (69%)
[epoch 25] loss: 0.0200279
Test set: Average loss: 1.0132, Accuracy: 3459/5000 (69%)
Validation:
Test set: Average loss: 0.8633, Accuracy: 3491/5000 (70%)
Test
Test set: Average loss: 0.8845, Accuracy: 3455/5000 (69%)
Test set: Average loss: 0.1885, Accuracy: 14507/15000 (97%)
## seed: 13
Validation accuracy before training:
Test set: Average loss: 1.6270, Accuracy: 831/5000 (17%)
[epoch 1] loss: 1.1115551
Test set: Average loss: 1.0285, Accuracy: 3144/5000 (63%)
[epoch 2] loss: 0.9834487
Test set: Average loss: 0.9841, Accuracy: 3217/5000 (64%)
[epoch 3] loss: 0.9128271
Test set: Average loss: 0.9705, Accuracy: 3250/5000 (65%)
[epoch 4] loss: 0.8520107
Test set: Average loss: 0.9217, Accuracy: 3337/5000 (67%)
[epoch 5] loss: 0.7904245
Test set: Average loss: 0.9054, Accuracy: 3362/5000 (67%)
[epoch 6] loss: 0.7325121
Test set: Average loss: 0.8817, Accuracy: 3375/5000 (68%)
[epoch 7] loss: 0.6713601
Test set: Average loss: 0.8808, Accuracy: 3380/5000 (68%)
[epoch 8] loss: 0.6108303
Test set: Average loss: 0.8702, Accuracy: 3399/5000 (68%)
[epoch 9] loss: 0.5453836
Test set: Average loss: 0.8480, Accuracy: 3458/5000 (69%)
[epoch 10] loss: 0.4785309
Test set: Average loss: 0.8527, Accuracy: 3422/5000 (68%)
[epoch 11] loss: 0.4158063
Test set: Average loss: 0.8467, Accuracy: 3471/5000 (69%)
[epoch 12] loss: 0.3477017
Test set: Average loss: 0.8721, Accuracy: 3426/5000 (69%)
[epoch 13] loss: 0.2912591
Test set: Average loss: 0.8853, Accuracy: 3443/5000 (69%)
[epoch 14] loss: 0.2400994
Test set: Average loss: 0.8825, Accuracy: 3446/5000 (69%)
[epoch 15] loss: 0.1897684
Test set: Average loss: 0.8898, Accuracy: 3441/5000 (69%)
[epoch 16] loss: 0.1514526
Test set: Average loss: 0.9090, Accuracy: 3444/5000 (69%)
[epoch 17] loss: 0.1172467
Test set: Average loss: 0.9253, Accuracy: 3458/5000 (69%)
[epoch 18] loss: 0.0938775
Test set: Average loss: 0.9540, Accuracy: 3434/5000 (69%)
[epoch 19] loss: 0.0734752
Test set: Average loss: 1.0139, Accuracy: 3370/5000 (67%)
[epoch 20] loss: 0.0580104
Test set: Average loss: 0.9904, Accuracy: 3444/5000 (69%)
[epoch 21] loss: 0.0422794
Test set: Average loss: 1.0155, Accuracy: 3413/5000 (68%)
[epoch 22] loss: 0.0375892
Test set: Average loss: 1.1542, Accuracy: 3303/5000 (66%)
[epoch 23] loss: 0.0589115
Epoch 22: reducing learning rate of group 0 to 5.0000e-06.
Test set: Average loss: 1.0455, Accuracy: 3434/5000 (69%)
[epoch 24] loss: 0.0182400
Test set: Average loss: 1.0260, Accuracy: 3444/5000 (69%)
[epoch 25] loss: 0.0160494
Test set: Average loss: 1.0293, Accuracy: 3459/5000 (69%)
Validation:
Test set: Average loss: 0.8467, Accuracy: 3471/5000 (69%)
Test
Test set: Average loss: 0.8704, Accuracy: 3421/5000 (68%)
Test set: Average loss: 0.3425, Accuracy: 13742/15000 (92%)
20000
## seed: 11
Validation accuracy before training:
Test set: Average loss: 1.6301, Accuracy: 1019/5000 (20%)
[epoch 1] loss: 1.0847259
Test set: Average loss: 1.0177, Accuracy: 3136/5000 (63%)
[epoch 2] loss: 0.9603950
Test set: Average loss: 0.9723, Accuracy: 3215/5000 (64%)
[epoch 3] loss: 0.8892458
Test set: Average loss: 0.9252, Accuracy: 3292/5000 (66%)
[epoch 4] loss: 0.8266754
Test set: Average loss: 0.8982, Accuracy: 3337/5000 (67%)
[epoch 5] loss: 0.7683224
Test set: Average loss: 0.8693, Accuracy: 3430/5000 (69%)
[epoch 6] loss: 0.7050395
Test set: Average loss: 0.8696, Accuracy: 3387/5000 (68%)
[epoch 7] loss: 0.6421270
Test set: Average loss: 0.8635, Accuracy: 3434/5000 (69%)
[epoch 8] loss: 0.5789859
Test set: Average loss: 0.8328, Accuracy: 3468/5000 (69%)
[epoch 9] loss: 0.5086553
Test set: Average loss: 0.8265, Accuracy: 3463/5000 (69%)
[epoch 10] loss: 0.4433456
Test set: Average loss: 0.8346, Accuracy: 3500/5000 (70%)
[epoch 11] loss: 0.3778910
Test set: Average loss: 0.8469, Accuracy: 3476/5000 (70%)
[epoch 12] loss: 0.3158095
Test set: Average loss: 0.8551, Accuracy: 3464/5000 (69%)
[epoch 13] loss: 0.2537058
Test set: Average loss: 0.8764, Accuracy: 3450/5000 (69%)
[epoch 14] loss: 0.2074647
Test set: Average loss: 0.8846, Accuracy: 3475/5000 (70%)
[epoch 15] loss: 0.1651660
Test set: Average loss: 0.9094, Accuracy: 3454/5000 (69%)
[epoch 16] loss: 0.1277303
Test set: Average loss: 0.9192, Accuracy: 3484/5000 (70%)
[epoch 17] loss: 0.1016424
Test set: Average loss: 0.9717, Accuracy: 3455/5000 (69%)
[epoch 18] loss: 0.0724792
Test set: Average loss: 0.9654, Accuracy: 3480/5000 (70%)
[epoch 19] loss: 0.0590170
Test set: Average loss: 1.0362, Accuracy: 3442/5000 (69%)
[epoch 20] loss: 0.0538494
Test set: Average loss: 1.0591, Accuracy: 3429/5000 (69%)
[epoch 21] loss: 0.0499652
Test set: Average loss: 1.1002, Accuracy: 3393/5000 (68%)
[epoch 22] loss: 0.0368818
Test set: Average loss: 1.0782, Accuracy: 3468/5000 (69%)
[epoch 23] loss: 0.0258442
Test set: Average loss: 1.1027, Accuracy: 3479/5000 (70%)
[epoch 24] loss: 0.0381120
Epoch 23: reducing learning rate of group 0 to 5.0000e-06.
Test set: Average loss: 1.1271, Accuracy: 3453/5000 (69%)
[epoch 25] loss: 0.0133913
Test set: Average loss: 1.1085, Accuracy: 3478/5000 (70%)
Validation:
Test set: Average loss: 0.8346, Accuracy: 3500/5000 (70%)
Test
Test set: Average loss: 0.8516, Accuracy: 3434/5000 (69%)
Test set: Average loss: 0.3725, Accuracy: 18127/20000 (91%)
## seed: 12
Validation accuracy before training:
Test set: Average loss: 1.6020, Accuracy: 1118/5000 (22%)
[epoch 1] loss: 1.1018954
Test set: Average loss: 1.0249, Accuracy: 3120/5000 (62%)
[epoch 2] loss: 0.9707609
Test set: Average loss: 0.9781, Accuracy: 3183/5000 (64%)
[epoch 3] loss: 0.8962471
Test set: Average loss: 0.9340, Accuracy: 3273/5000 (65%)
[epoch 4] loss: 0.8285454
Test set: Average loss: 0.9164, Accuracy: 3278/5000 (66%)
[epoch 5] loss: 0.7701470
Test set: Average loss: 0.8821, Accuracy: 3371/5000 (67%)
[epoch 6] loss: 0.7051368
Test set: Average loss: 0.8565, Accuracy: 3437/5000 (69%)
[epoch 7] loss: 0.6397950
Test set: Average loss: 0.8610, Accuracy: 3424/5000 (68%)
[epoch 8] loss: 0.5708796
Test set: Average loss: 0.8439, Accuracy: 3467/5000 (69%)
[epoch 9] loss: 0.5069856
Test set: Average loss: 0.8471, Accuracy: 3450/5000 (69%)
[epoch 10] loss: 0.4349647
Test set: Average loss: 0.8371, Accuracy: 3460/5000 (69%)
[epoch 11] loss: 0.3709058
Test set: Average loss: 0.8472, Accuracy: 3501/5000 (70%)
[epoch 12] loss: 0.3075322
Test set: Average loss: 0.8558, Accuracy: 3533/5000 (71%)
[epoch 13] loss: 0.2512622
Test set: Average loss: 0.8758, Accuracy: 3474/5000 (69%)
[epoch 14] loss: 0.2024019
Test set: Average loss: 0.8830, Accuracy: 3487/5000 (70%)
[epoch 15] loss: 0.1572685
Test set: Average loss: 0.8895, Accuracy: 3525/5000 (70%)
[epoch 16] loss: 0.1232591
Test set: Average loss: 0.9355, Accuracy: 3464/5000 (69%)
[epoch 17] loss: 0.0901003
Test set: Average loss: 0.9613, Accuracy: 3471/5000 (69%)
[epoch 18] loss: 0.0722020
Test set: Average loss: 0.9822, Accuracy: 3461/5000 (69%)
[epoch 19] loss: 0.0646787
Test set: Average loss: 1.0581, Accuracy: 3420/5000 (68%)
[epoch 20] loss: 0.0542015
Test set: Average loss: 1.0128, Accuracy: 3478/5000 (70%)
[epoch 21] loss: 0.0373678
Test set: Average loss: 1.0780, Accuracy: 3438/5000 (69%)
[epoch 22] loss: 0.0414124
Epoch 21: reducing learning rate of group 0 to 5.0000e-06.
Test set: Average loss: 1.1112, Accuracy: 3439/5000 (69%)
[epoch 23] loss: 0.0203322
Test set: Average loss: 1.0519, Accuracy: 3499/5000 (70%)
[epoch 24] loss: 0.0144893
Test set: Average loss: 1.0507, Accuracy: 3507/5000 (70%)
[epoch 25] loss: 0.0126115
Test set: Average loss: 1.0537, Accuracy: 3506/5000 (70%)
Validation:
Test set: Average loss: 0.8558, Accuracy: 3533/5000 (71%)
Test
Test set: Average loss: 0.8696, Accuracy: 3499/5000 (70%)
Test set: Average loss: 0.2470, Accuracy: 18949/20000 (95%)
## seed: 13
Validation accuracy before training:
Test set: Average loss: 1.6276, Accuracy: 971/5000 (19%)
[epoch 1] loss: 1.0830324
Test set: Average loss: 1.0188, Accuracy: 3140/5000 (63%)
[epoch 2] loss: 0.9594941
Test set: Average loss: 0.9686, Accuracy: 3245/5000 (65%)
[epoch 3] loss: 0.8893497
Test set: Average loss: 0.9183, Accuracy: 3366/5000 (67%)
[epoch 4] loss: 0.8218680
Test set: Average loss: 0.8865, Accuracy: 3407/5000 (68%)
[epoch 5] loss: 0.7597781
Test set: Average loss: 0.8755, Accuracy: 3414/5000 (68%)
[epoch 6] loss: 0.6952400
Test set: Average loss: 0.8618, Accuracy: 3424/5000 (68%)
[epoch 7] loss: 0.6291694
Test set: Average loss: 0.8562, Accuracy: 3398/5000 (68%)
[epoch 8] loss: 0.5649226
Test set: Average loss: 0.8369, Accuracy: 3472/5000 (69%)
[epoch 9] loss: 0.4983650
Test set: Average loss: 0.8469, Accuracy: 3476/5000 (70%)
[epoch 10] loss: 0.4292709
Test set: Average loss: 0.8394, Accuracy: 3489/5000 (70%)
[epoch 11] loss: 0.3662986
Test set: Average loss: 0.8364, Accuracy: 3493/5000 (70%)
[epoch 12] loss: 0.3091626
Test set: Average loss: 0.8573, Accuracy: 3493/5000 (70%)
[epoch 13] loss: 0.2492040
Test set: Average loss: 0.8937, Accuracy: 3467/5000 (69%)
[epoch 14] loss: 0.2013629
Test set: Average loss: 0.8774, Accuracy: 3491/5000 (70%)
[epoch 15] loss: 0.1546186
Test set: Average loss: 0.9109, Accuracy: 3467/5000 (69%)
[epoch 16] loss: 0.1219297
Test set: Average loss: 0.9453, Accuracy: 3471/5000 (69%)
[epoch 17] loss: 0.0936362
Test set: Average loss: 0.9729, Accuracy: 3439/5000 (69%)
[epoch 18] loss: 0.0761740
Test set: Average loss: 0.9796, Accuracy: 3511/5000 (70%)
[epoch 19] loss: 0.0632565
Test set: Average loss: 1.0157, Accuracy: 3466/5000 (69%)
[epoch 20] loss: 0.0453001
Test set: Average loss: 1.0358, Accuracy: 3477/5000 (70%)
[epoch 21] loss: 0.0385148
Test set: Average loss: 1.0772, Accuracy: 3470/5000 (69%)
[epoch 22] loss: 0.0446034
Epoch 21: reducing learning rate of group 0 to 5.0000e-06.
Test set: Average loss: 1.1250, Accuracy: 3435/5000 (69%)
[epoch 23] loss: 0.0200462
Test set: Average loss: 1.0584, Accuracy: 3481/5000 (70%)
[epoch 24] loss: 0.0146638
Test set: Average loss: 1.0579, Accuracy: 3494/5000 (70%)
[epoch 25] loss: 0.0127704
Test set: Average loss: 1.0617, Accuracy: 3493/5000 (70%)
Validation:
Test set: Average loss: 0.9796, Accuracy: 3511/5000 (70%)
Test
Test set: Average loss: 0.9908, Accuracy: 3490/5000 (70%)
Test set: Average loss: 0.0608, Accuracy: 19836/20000 (99%)
## Pre-Training BnB
Validation accuracy before training:
Test set: Average loss: 1.6576, Accuracy: 763/5000 (15%)
[epoch 1] loss: 1.0884546
Test set: Average loss: 1.0180, Accuracy: 3139/5000 (63%)
[epoch 2] loss: 0.9653594
Test set: Average loss: 0.9617, Accuracy: 3281/5000 (66%)
[epoch 3] loss: 0.8930766
Test set: Average loss: 0.9344, Accuracy: 3287/5000 (66%)
[epoch 4] loss: 0.8312031
Test set: Average loss: 0.9025, Accuracy: 3343/5000 (67%)
[epoch 5] loss: 0.7655037
Test set: Average loss: 0.8831, Accuracy: 3398/5000 (68%)
[epoch 6] loss: 0.7039804
Test set: Average loss: 0.8564, Accuracy: 3438/5000 (69%)
[epoch 7] loss: 0.6395757
Test set: Average loss: 0.8420, Accuracy: 3481/5000 (70%)
[epoch 8] loss: 0.5725036
Test set: Average loss: 0.8414, Accuracy: 3449/5000 (69%)
[epoch 9] loss: 0.5045020
Test set: Average loss: 0.8426, Accuracy: 3494/5000 (70%)
[epoch 10] loss: 0.4394547
Test set: Average loss: 0.8563, Accuracy: 3436/5000 (69%)
[epoch 11] loss: 0.3730944
Test set: Average loss: 0.8531, Accuracy: 3448/5000 (69%)
[epoch 12] loss: 0.3086191
Test set: Average loss: 0.8452, Accuracy: 3499/5000 (70%)
[epoch 13] loss: 0.2530877
Test set: Average loss: 0.8768, Accuracy: 3468/5000 (69%)
[epoch 14] loss: 0.2009516
Test set: Average loss: 0.8851, Accuracy: 3495/5000 (70%)
[epoch 15] loss: 0.1565756
Test set: Average loss: 0.9104, Accuracy: 3494/5000 (70%)
[epoch 16] loss: 0.1203875
Test set: Average loss: 0.9259, Accuracy: 3488/5000 (70%)
[epoch 17] loss: 0.0921024
Test set: Average loss: 0.9549, Accuracy: 3479/5000 (70%)
[epoch 18] loss: 0.0687319
Test set: Average loss: 0.9821, Accuracy: 3485/5000 (70%)
[epoch 19] loss: 0.0597058
Test set: Average loss: 1.0137, Accuracy: 3485/5000 (70%)
[epoch 20] loss: 0.0529797
Test set: Average loss: 1.0338, Accuracy: 3496/5000 (70%)
[epoch 21] loss: 0.0429565
Test set: Average loss: 1.0894, Accuracy: 3435/5000 (69%)
[epoch 22] loss: 0.0405193
Test set: Average loss: 1.0794, Accuracy: 3497/5000 (70%)
[epoch 23] loss: 0.0200045
Test set: Average loss: 1.0893, Accuracy: 3510/5000 (70%)
[epoch 24] loss: 0.0171817
Test set: Average loss: 1.1916, Accuracy: 3428/5000 (69%)
[epoch 25] loss: 0.0694143
Epoch 24: reducing learning rate of group 0 to 5.0000e-06.
Test set: Average loss: 1.1788, Accuracy: 3458/5000 (69%)
Validation:
Test set: Average loss: 1.0893, Accuracy: 3510/5000 (70%)
Test set: Average loss: 1.1145, Accuracy: 3459/5000 (69%)
25
## seed: 11
Validation accuracy before training:
Test set: Average loss: 1.7043, Accuracy: 517/5000 (10%)
[epoch 1] loss: 1.7136976
Test set: Average loss: 1.6857, Accuracy: 610/5000 (12%)
[epoch 2] loss: 1.5661067
Test set: Average loss: 1.6686, Accuracy: 770/5000 (15%)
[epoch 3] loss: 1.4324772
Test set: Average loss: 1.6531, Accuracy: 934/5000 (19%)
[epoch 4] loss: 1.3121186
Test set: Average loss: 1.6395, Accuracy: 1102/5000 (22%)
[epoch 5] loss: 1.2057198
Test set: Average loss: 1.6279, Accuracy: 1227/5000 (25%)
[epoch 6] loss: 1.1184323
Test set: Average loss: 1.6181, Accuracy: 1290/5000 (26%)
[epoch 7] loss: 1.0461571
Test set: Average loss: 1.6100, Accuracy: 1357/5000 (27%)
[epoch 8] loss: 0.9828514
Test set: Average loss: 1.6031, Accuracy: 1405/5000 (28%)
[epoch 9] loss: 0.9261232
Test set: Average loss: 1.5969, Accuracy: 1442/5000 (29%)
[epoch 10] loss: 0.8752407
Test set: Average loss: 1.5912, Accuracy: 1488/5000 (30%)
[epoch 11] loss: 0.8295940
Test set: Average loss: 1.5855, Accuracy: 1531/5000 (31%)
[epoch 12] loss: 0.7887015
Test set: Average loss: 1.5799, Accuracy: 1561/5000 (31%)
[epoch 13] loss: 0.7524729
Test set: Average loss: 1.5744, Accuracy: 1587/5000 (32%)
[epoch 14] loss: 0.7207288
Test set: Average loss: 1.5692, Accuracy: 1614/5000 (32%)
[epoch 15] loss: 0.6927946
Test set: Average loss: 1.5643, Accuracy: 1626/5000 (33%)
[epoch 16] loss: 0.6679353
Test set: Average loss: 1.5599, Accuracy: 1643/5000 (33%)
[epoch 17] loss: 0.6455433
Test set: Average loss: 1.5560, Accuracy: 1653/5000 (33%)
[epoch 18] loss: 0.6249374
Test set: Average loss: 1.5527, Accuracy: 1650/5000 (33%)
[epoch 19] loss: 0.6054686
Test set: Average loss: 1.5499, Accuracy: 1653/5000 (33%)
[epoch 20] loss: 0.5867725
Test set: Average loss: 1.5477, Accuracy: 1668/5000 (33%)
[epoch 21] loss: 0.5688351
Test set: Average loss: 1.5460, Accuracy: 1680/5000 (34%)
[epoch 22] loss: 0.5518539
Test set: Average loss: 1.5447, Accuracy: 1692/5000 (34%)
[epoch 23] loss: 0.5360516
Test set: Average loss: 1.5439, Accuracy: 1697/5000 (34%)
[epoch 24] loss: 0.5215570
Test set: Average loss: 1.5434, Accuracy: 1693/5000 (34%)
[epoch 25] loss: 0.5083743
Test set: Average loss: 1.5434, Accuracy: 1684/5000 (34%)
Validation:
Test set: Average loss: 1.5439, Accuracy: 1697/5000 (34%)
Test
Test set: Average loss: 1.5516, Accuracy: 1667/5000 (33%)
Test set: Average loss: 0.5216, Accuracy: 25/25 (100%)
## seed: 12
Validation accuracy before training:
Test set: Average loss: 1.7285, Accuracy: 808/5000 (16%)
[epoch 1] loss: 1.8125162
Test set: Average loss: 1.6937, Accuracy: 979/5000 (20%)
[epoch 2] loss: 1.6341881
Test set: Average loss: 1.6613, Accuracy: 1132/5000 (23%)
[epoch 3] loss: 1.4692857
Test set: Average loss: 1.6311, Accuracy: 1304/5000 (26%)
[epoch 4] loss: 1.3242555
Test set: Average loss: 1.6032, Accuracy: 1432/5000 (29%)
[epoch 5] loss: 1.1998367
Test set: Average loss: 1.5780, Accuracy: 1521/5000 (30%)
[epoch 6] loss: 1.0960131
Test set: Average loss: 1.5558, Accuracy: 1591/5000 (32%)
[epoch 7] loss: 1.0110706
Test set: Average loss: 1.5367, Accuracy: 1645/5000 (33%)
[epoch 8] loss: 0.9409624
Test set: Average loss: 1.5204, Accuracy: 1699/5000 (34%)
[epoch 9] loss: 0.8820809
Test set: Average loss: 1.5065, Accuracy: 1753/5000 (35%)
[epoch 10] loss: 0.8315332
Test set: Average loss: 1.4946, Accuracy: 1784/5000 (36%)
[epoch 11] loss: 0.7868371
Test set: Average loss: 1.4844, Accuracy: 1817/5000 (36%)
[epoch 12] loss: 0.7463863
Test set: Average loss: 1.4755, Accuracy: 1843/5000 (37%)
[epoch 13] loss: 0.7093887
Test set: Average loss: 1.4678, Accuracy: 1868/5000 (37%)
[epoch 14] loss: 0.6753774
Test set: Average loss: 1.4612, Accuracy: 1888/5000 (38%)
[epoch 15] loss: 0.6441029
Test set: Average loss: 1.4557, Accuracy: 1908/5000 (38%)
[epoch 16] loss: 0.6154553
Test set: Average loss: 1.4511, Accuracy: 1938/5000 (39%)
[epoch 17] loss: 0.5893352
Test set: Average loss: 1.4475, Accuracy: 1954/5000 (39%)
[epoch 18] loss: 0.5656434
Test set: Average loss: 1.4448, Accuracy: 1964/5000 (39%)
[epoch 19] loss: 0.5442966
Test set: Average loss: 1.4427, Accuracy: 1956/5000 (39%)
[epoch 20] loss: 0.5252028
Test set: Average loss: 1.4411, Accuracy: 1963/5000 (39%)
[epoch 21] loss: 0.5081540
Test set: Average loss: 1.4399, Accuracy: 1975/5000 (40%)
[epoch 22] loss: 0.4928273
Test set: Average loss: 1.4387, Accuracy: 1981/5000 (40%)
[epoch 23] loss: 0.4789128
Test set: Average loss: 1.4375, Accuracy: 1983/5000 (40%)
[epoch 24] loss: 0.4661236
Test set: Average loss: 1.4359, Accuracy: 1988/5000 (40%)
[epoch 25] loss: 0.4541681
Test set: Average loss: 1.4341, Accuracy: 1988/5000 (40%)
Validation:
Test set: Average loss: 1.4341, Accuracy: 1988/5000 (40%)
Test
Test set: Average loss: 1.4328, Accuracy: 1981/5000 (40%)
Test set: Average loss: 0.4428, Accuracy: 25/25 (100%)
## seed: 13
Validation accuracy before training:
Test set: Average loss: 1.7202, Accuracy: 536/5000 (11%)
[epoch 1] loss: 1.7394507
Test set: Average loss: 1.7017, Accuracy: 590/5000 (12%)
[epoch 2] loss: 1.5720477
Test set: Average loss: 1.6854, Accuracy: 670/5000 (13%)
[epoch 3] loss: 1.4292035
Test set: Average loss: 1.6704, Accuracy: 735/5000 (15%)
[epoch 4] loss: 1.3115821
Test set: Average loss: 1.6566, Accuracy: 843/5000 (17%)
[epoch 5] loss: 1.2146760
Test set: Average loss: 1.6437, Accuracy: 937/5000 (19%)
[epoch 6] loss: 1.1335149
Test set: Average loss: 1.6316, Accuracy: 1003/5000 (20%)
[epoch 7] loss: 1.0632977
Test set: Average loss: 1.6205, Accuracy: 1076/5000 (22%)
[epoch 8] loss: 1.0013922
Test set: Average loss: 1.6104, Accuracy: 1140/5000 (23%)
[epoch 9] loss: 0.9468525
Test set: Average loss: 1.6012, Accuracy: 1175/5000 (24%)
[epoch 10] loss: 0.8980711
Test set: Average loss: 1.5931, Accuracy: 1200/5000 (24%)
[epoch 11] loss: 0.8537244
Test set: Average loss: 1.5858, Accuracy: 1232/5000 (25%)
[epoch 12] loss: 0.8135607
Test set: Average loss: 1.5793, Accuracy: 1259/5000 (25%)
[epoch 13] loss: 0.7776338
Test set: Average loss: 1.5736, Accuracy: 1291/5000 (26%)
[epoch 14] loss: 0.7455792
Test set: Average loss: 1.5686, Accuracy: 1310/5000 (26%)
[epoch 15] loss: 0.7166968
Test set: Average loss: 1.5642, Accuracy: 1333/5000 (27%)
[epoch 16] loss: 0.6903697
Test set: Average loss: 1.5603, Accuracy: 1352/5000 (27%)
[epoch 17] loss: 0.6662382
Test set: Average loss: 1.5570, Accuracy: 1379/5000 (28%)
[epoch 18] loss: 0.6441100
Test set: Average loss: 1.5540, Accuracy: 1388/5000 (28%)
[epoch 19] loss: 0.6238381
Test set: Average loss: 1.5514, Accuracy: 1399/5000 (28%)
[epoch 20] loss: 0.6052547
Test set: Average loss: 1.5492, Accuracy: 1415/5000 (28%)
[epoch 21] loss: 0.5881598
Test set: Average loss: 1.5472, Accuracy: 1418/5000 (28%)
[epoch 22] loss: 0.5723759
Test set: Average loss: 1.5455, Accuracy: 1432/5000 (29%)
[epoch 23] loss: 0.5578002
Test set: Average loss: 1.5439, Accuracy: 1446/5000 (29%)
[epoch 24] loss: 0.5443540
Test set: Average loss: 1.5426, Accuracy: 1459/5000 (29%)
[epoch 25] loss: 0.5318976
Test set: Average loss: 1.5413, Accuracy: 1466/5000 (29%)
Validation:
Test set: Average loss: 1.5413, Accuracy: 1466/5000 (29%)
Test
Test set: Average loss: 1.5548, Accuracy: 1415/5000 (28%)
Test set: Average loss: 0.5203, Accuracy: 25/25 (100%)
50
## seed: 11
Validation accuracy before training:
Test set: Average loss: 1.6550, Accuracy: 1108/5000 (22%)
[epoch 1] loss: 1.6587147
Test set: Average loss: 1.6185, Accuracy: 1215/5000 (24%)
[epoch 2] loss: 1.4737662
Test set: Average loss: 1.5861, Accuracy: 1344/5000 (27%)
[epoch 3] loss: 1.3302611
Test set: Average loss: 1.5578, Accuracy: 1496/5000 (30%)
[epoch 4] loss: 1.2242714
Test set: Average loss: 1.5333, Accuracy: 1617/5000 (32%)
[epoch 5] loss: 1.1534971
Test set: Average loss: 1.5126, Accuracy: 1699/5000 (34%)
[epoch 6] loss: 1.0556722
Test set: Average loss: 1.4954, Accuracy: 1756/5000 (35%)
[epoch 7] loss: 1.0033173
Test set: Average loss: 1.4812, Accuracy: 1846/5000 (37%)
[epoch 8] loss: 0.9352449
Test set: Average loss: 1.4703, Accuracy: 1852/5000 (37%)
[epoch 9] loss: 0.8849850
Test set: Average loss: 1.4605, Accuracy: 1888/5000 (38%)
[epoch 10] loss: 0.8258109
Test set: Average loss: 1.4521, Accuracy: 1913/5000 (38%)
[epoch 11] loss: 0.7761300
Test set: Average loss: 1.4444, Accuracy: 1944/5000 (39%)
[epoch 12] loss: 0.7544479
Test set: Average loss: 1.4376, Accuracy: 1967/5000 (39%)
[epoch 13] loss: 0.7073970
Test set: Average loss: 1.4317, Accuracy: 1997/5000 (40%)
[epoch 14] loss: 0.6828982
Test set: Average loss: 1.4265, Accuracy: 2002/5000 (40%)
[epoch 15] loss: 0.6445834
Test set: Average loss: 1.4224, Accuracy: 1996/5000 (40%)
[epoch 16] loss: 0.6332156
Test set: Average loss: 1.4193, Accuracy: 1992/5000 (40%)
[epoch 17] loss: 0.5919471
Test set: Average loss: 1.4172, Accuracy: 1994/5000 (40%)
[epoch 18] loss: 0.5795271
Test set: Average loss: 1.4156, Accuracy: 1997/5000 (40%)
[epoch 19] loss: 0.5723408
Test set: Average loss: 1.4148, Accuracy: 1993/5000 (40%)
[epoch 20] loss: 0.5550075
Test set: Average loss: 1.4140, Accuracy: 1997/5000 (40%)
[epoch 21] loss: 0.5299456
Test set: Average loss: 1.4134, Accuracy: 2011/5000 (40%)
[epoch 22] loss: 0.5178717
Test set: Average loss: 1.4127, Accuracy: 2021/5000 (40%)
[epoch 23] loss: 0.5047613
Test set: Average loss: 1.4117, Accuracy: 2027/5000 (41%)
[epoch 24] loss: 0.4887716
Test set: Average loss: 1.4106, Accuracy: 2046/5000 (41%)
[epoch 25] loss: 0.4700061
Test set: Average loss: 1.4095, Accuracy: 2044/5000 (41%)
Validation:
Test set: Average loss: 1.4106, Accuracy: 2046/5000 (41%)
Test
Test set: Average loss: 1.4191, Accuracy: 2044/5000 (41%)
Test set: Average loss: 0.4810, Accuracy: 50/50 (100%)
## seed: 12
Validation accuracy before training:
Test set: Average loss: 1.6888, Accuracy: 774/5000 (15%)
[epoch 1] loss: 1.6884311
Test set: Average loss: 1.6466, Accuracy: 1062/5000 (21%)
[epoch 2] loss: 1.5180738
Test set: Average loss: 1.6122, Accuracy: 1274/5000 (25%)
[epoch 3] loss: 1.3468778
Test set: Average loss: 1.5825, Accuracy: 1438/5000 (29%)
[epoch 4] loss: 1.2217152
Test set: Average loss: 1.5551, Accuracy: 1569/5000 (31%)
[epoch 5] loss: 1.0981162
Test set: Average loss: 1.5287, Accuracy: 1648/5000 (33%)
[epoch 6] loss: 0.9988998
Test set: Average loss: 1.5058, Accuracy: 1696/5000 (34%)
[epoch 7] loss: 0.9428841
Test set: Average loss: 1.4875, Accuracy: 1754/5000 (35%)
[epoch 8] loss: 0.8624465
Test set: Average loss: 1.4744, Accuracy: 1787/5000 (36%)
[epoch 9] loss: 0.8199587
Test set: Average loss: 1.4653, Accuracy: 1819/5000 (36%)
[epoch 10] loss: 0.7658041
Test set: Average loss: 1.4596, Accuracy: 1859/5000 (37%)
[epoch 11] loss: 0.7181018
Test set: Average loss: 1.4555, Accuracy: 1876/5000 (38%)
[epoch 12] loss: 0.6857669
Test set: Average loss: 1.4526, Accuracy: 1895/5000 (38%)
[epoch 13] loss: 0.6590233
Test set: Average loss: 1.4500, Accuracy: 1909/5000 (38%)
[epoch 14] loss: 0.6365785
Test set: Average loss: 1.4478, Accuracy: 1921/5000 (38%)
[epoch 15] loss: 0.6084597
Test set: Average loss: 1.4454, Accuracy: 1926/5000 (39%)
[epoch 16] loss: 0.5987591
Test set: Average loss: 1.4433, Accuracy: 1925/5000 (38%)
[epoch 17] loss: 0.5585871
Test set: Average loss: 1.4412, Accuracy: 1931/5000 (39%)
[epoch 18] loss: 0.5410754
Test set: Average loss: 1.4396, Accuracy: 1942/5000 (39%)
[epoch 19] loss: 0.5334053
Test set: Average loss: 1.4381, Accuracy: 1950/5000 (39%)
[epoch 20] loss: 0.5204238
Test set: Average loss: 1.4368, Accuracy: 1960/5000 (39%)
[epoch 21] loss: 0.5029721
Test set: Average loss: 1.4355, Accuracy: 1972/5000 (39%)
[epoch 22] loss: 0.4907256
Test set: Average loss: 1.4345, Accuracy: 1979/5000 (40%)
[epoch 23] loss: 0.4605747
Test set: Average loss: 1.4337, Accuracy: 1992/5000 (40%)
[epoch 24] loss: 0.4760085
Epoch 23: reducing learning rate of group 0 to 5.0000e-06.
Test set: Average loss: 1.4332, Accuracy: 1994/5000 (40%)
[epoch 25] loss: 0.4545956
Test set: Average loss: 1.4331, Accuracy: 1997/5000 (40%)
Validation:
Test set: Average loss: 1.4331, Accuracy: 1997/5000 (40%)
Test
Test set: Average loss: 1.4382, Accuracy: 1960/5000 (39%)
Test set: Average loss: 0.4577, Accuracy: 50/50 (100%)
## seed: 13
Validation accuracy before training:
Test set: Average loss: 1.8076, Accuracy: 720/5000 (14%)
[epoch 1] loss: 1.8277029
Test set: Average loss: 1.7569, Accuracy: 787/5000 (16%)
[epoch 2] loss: 1.6085049
Test set: Average loss: 1.7110, Accuracy: 896/5000 (18%)
[epoch 3] loss: 1.4717094
Test set: Average loss: 1.6730, Accuracy: 1029/5000 (21%)
[epoch 4] loss: 1.3796487
Test set: Average loss: 1.6436, Accuracy: 1163/5000 (23%)
[epoch 5] loss: 1.2706979
Test set: Average loss: 1.6191, Accuracy: 1288/5000 (26%)
[epoch 6] loss: 1.1539711
Test set: Average loss: 1.5967, Accuracy: 1392/5000 (28%)
[epoch 7] loss: 1.0754343
Test set: Average loss: 1.5766, Accuracy: 1516/5000 (30%)
[epoch 8] loss: 1.0103315
Test set: Average loss: 1.5584, Accuracy: 1593/5000 (32%)
[epoch 9] loss: 0.9671361
Test set: Average loss: 1.5420, Accuracy: 1640/5000 (33%)
[epoch 10] loss: 0.9217499
Test set: Average loss: 1.5277, Accuracy: 1701/5000 (34%)
[epoch 11] loss: 0.8556839
Test set: Average loss: 1.5156, Accuracy: 1751/5000 (35%)
[epoch 12] loss: 0.8168012
Test set: Average loss: 1.5050, Accuracy: 1785/5000 (36%)
[epoch 13] loss: 0.7952760
Test set: Average loss: 1.4959, Accuracy: 1804/5000 (36%)
[epoch 14] loss: 0.7546992
Test set: Average loss: 1.4878, Accuracy: 1823/5000 (36%)
[epoch 15] loss: 0.7327794
Test set: Average loss: 1.4809, Accuracy: 1834/5000 (37%)
[epoch 16] loss: 0.7142214
Test set: Average loss: 1.4750, Accuracy: 1845/5000 (37%)
[epoch 17] loss: 0.6593960
Test set: Average loss: 1.4698, Accuracy: 1859/5000 (37%)
[epoch 18] loss: 0.6466107
Test set: Average loss: 1.4654, Accuracy: 1864/5000 (37%)
[epoch 19] loss: 0.6387896
Test set: Average loss: 1.4613, Accuracy: 1881/5000 (38%)
[epoch 20] loss: 0.6103108
Test set: Average loss: 1.4577, Accuracy: 1890/5000 (38%)
[epoch 21] loss: 0.5816814
Test set: Average loss: 1.4544, Accuracy: 1890/5000 (38%)
[epoch 22] loss: 0.5865129
Epoch 21: reducing learning rate of group 0 to 5.0000e-06.
Test set: Average loss: 1.4515, Accuracy: 1894/5000 (38%)
[epoch 23] loss: 0.5702909
Test set: Average loss: 1.4513, Accuracy: 1892/5000 (38%)
[epoch 24] loss: 0.5790665
Epoch 23: reducing learning rate of group 0 to 5.0000e-07.
Test set: Average loss: 1.4510, Accuracy: 1894/5000 (38%)
[epoch 25] loss: 0.5716302
Epoch 24: reducing learning rate of group 0 to 5.0000e-08.
Test set: Average loss: 1.4510, Accuracy: 1894/5000 (38%)
Validation:
Test set: Average loss: 1.4510, Accuracy: 1894/5000 (38%)
Test
Test set: Average loss: 1.4546, Accuracy: 1861/5000 (37%)
Test set: Average loss: 0.5731, Accuracy: 48/50 (96%)
100
## seed: 11
Validation accuracy before training:
Test set: Average loss: 1.8125, Accuracy: 497/5000 (10%)
[epoch 1] loss: 1.8928872
Test set: Average loss: 1.7285, Accuracy: 770/5000 (15%)
[epoch 2] loss: 1.6422466
Test set: Average loss: 1.6615, Accuracy: 997/5000 (20%)
[epoch 3] loss: 1.4174278
Test set: Average loss: 1.6062, Accuracy: 1172/5000 (23%)
[epoch 4] loss: 1.3185714
Test set: Average loss: 1.5644, Accuracy: 1329/5000 (27%)
[epoch 5] loss: 1.2312074
Test set: Average loss: 1.5321, Accuracy: 1516/5000 (30%)
[epoch 6] loss: 1.2295007
Test set: Average loss: 1.5092, Accuracy: 1581/5000 (32%)
[epoch 7] loss: 1.1295494
Test set: Average loss: 1.4910, Accuracy: 1627/5000 (33%)
[epoch 8] loss: 1.0008789
Test set: Average loss: 1.4764, Accuracy: 1691/5000 (34%)
[epoch 9] loss: 0.9664499
Test set: Average loss: 1.4657, Accuracy: 1728/5000 (35%)
[epoch 10] loss: 0.9587016
Test set: Average loss: 1.4584, Accuracy: 1765/5000 (35%)
[epoch 11] loss: 0.8722514
Test set: Average loss: 1.4529, Accuracy: 1787/5000 (36%)
[epoch 12] loss: 0.8997723
Epoch 11: reducing learning rate of group 0 to 5.0000e-06.
Test set: Average loss: 1.4464, Accuracy: 1814/5000 (36%)
[epoch 13] loss: 0.9067768
Epoch 12: reducing learning rate of group 0 to 5.0000e-07.
Test set: Average loss: 1.4457, Accuracy: 1812/5000 (36%)
[epoch 14] loss: 0.8530293
Test set: Average loss: 1.4456, Accuracy: 1812/5000 (36%)
[epoch 15] loss: 0.8355239
Test set: Average loss: 1.4455, Accuracy: 1813/5000 (36%)
[epoch 16] loss: 0.8671344
Epoch 15: reducing learning rate of group 0 to 5.0000e-08.
Test set: Average loss: 1.4454, Accuracy: 1816/5000 (36%)
[epoch 17] loss: 0.8246021
Test set: Average loss: 1.4453, Accuracy: 1817/5000 (36%)
[epoch 18] loss: 0.8710625
Epoch 17: reducing learning rate of group 0 to 5.0000e-09.
Test set: Average loss: 1.4453, Accuracy: 1817/5000 (36%)
[epoch 19] loss: 0.8498887
Epoch 18: reducing learning rate of group 0 to 5.0000e-10.
Test set: Average loss: 1.4453, Accuracy: 1817/5000 (36%)
[epoch 20] loss: 0.8464078
Epoch 19: reducing learning rate of group 0 to 5.0000e-11.
Test set: Average loss: 1.4453, Accuracy: 1817/5000 (36%)
[epoch 21] loss: 0.8219992
Test set: Average loss: 1.4453, Accuracy: 1817/5000 (36%)
[epoch 22] loss: 0.8315323
Epoch 21: reducing learning rate of group 0 to 5.0000e-12.
Test set: Average loss: 1.4453, Accuracy: 1817/5000 (36%)
[epoch 23] loss: 0.8477223
Epoch 22: reducing learning rate of group 0 to 5.0000e-13.
Test set: Average loss: 1.4453, Accuracy: 1817/5000 (36%)
[epoch 24] loss: 0.8890593
Epoch 23: reducing learning rate of group 0 to 5.0000e-14.
Test set: Average loss: 1.4453, Accuracy: 1817/5000 (36%)
[epoch 25] loss: 0.8638039
Epoch 24: reducing learning rate of group 0 to 5.0000e-15.
Test set: Average loss: 1.4453, Accuracy: 1817/5000 (36%)
Validation:
Test set: Average loss: 1.4453, Accuracy: 1817/5000 (36%)
Test
Test set: Average loss: 1.4633, Accuracy: 1752/5000 (35%)
Test set: Average loss: 0.8384, Accuracy: 86/100 (86%)
## seed: 12
Validation accuracy before training:
Test set: Average loss: 1.7030, Accuracy: 999/5000 (20%)
[epoch 1] loss: 1.5877936
Test set: Average loss: 1.6257, Accuracy: 1264/5000 (25%)
[epoch 2] loss: 1.4665281
Test set: Average loss: 1.5705, Accuracy: 1585/5000 (32%)
[epoch 3] loss: 1.2746108
Test set: Average loss: 1.5376, Accuracy: 1797/5000 (36%)
[epoch 4] loss: 1.2089983
Test set: Average loss: 1.5150, Accuracy: 1921/5000 (38%)
[epoch 5] loss: 1.0975947
Test set: Average loss: 1.4941, Accuracy: 2007/5000 (40%)
[epoch 6] loss: 1.1029454
Epoch 5: reducing learning rate of group 0 to 5.0000e-06.
Test set: Average loss: 1.4801, Accuracy: 2045/5000 (41%)
[epoch 7] loss: 1.0242186
Test set: Average loss: 1.4792, Accuracy: 2051/5000 (41%)
[epoch 8] loss: 1.0187087
Test set: Average loss: 1.4784, Accuracy: 2055/5000 (41%)
[epoch 9] loss: 0.9841598
Test set: Average loss: 1.4776, Accuracy: 2059/5000 (41%)
[epoch 10] loss: 1.0045117
Epoch 9: reducing learning rate of group 0 to 5.0000e-07.
Test set: Average loss: 1.4771, Accuracy: 2058/5000 (41%)
[epoch 11] loss: 0.9937014
Epoch 10: reducing learning rate of group 0 to 5.0000e-08.
Test set: Average loss: 1.4770, Accuracy: 2056/5000 (41%)
[epoch 12] loss: 1.0075136
Epoch 11: reducing learning rate of group 0 to 5.0000e-09.
Test set: Average loss: 1.4770, Accuracy: 2056/5000 (41%)
[epoch 13] loss: 1.0032462
Epoch 12: reducing learning rate of group 0 to 5.0000e-10.
Test set: Average loss: 1.4770, Accuracy: 2056/5000 (41%)
[epoch 14] loss: 0.9544411
Test set: Average loss: 1.4770, Accuracy: 2056/5000 (41%)
[epoch 15] loss: 0.9663425
Epoch 14: reducing learning rate of group 0 to 5.0000e-11.
Test set: Average loss: 1.4770, Accuracy: 2056/5000 (41%)
[epoch 16] loss: 1.0527357
Epoch 15: reducing learning rate of group 0 to 5.0000e-12.
Test set: Average loss: 1.4770, Accuracy: 2056/5000 (41%)
[epoch 17] loss: 1.0067228
Epoch 16: reducing learning rate of group 0 to 5.0000e-13.
Test set: Average loss: 1.4770, Accuracy: 2056/5000 (41%)
[epoch 18] loss: 1.0128200
Epoch 17: reducing learning rate of group 0 to 5.0000e-14.
Test set: Average loss: 1.4770, Accuracy: 2056/5000 (41%)
[epoch 19] loss: 1.0285442
Epoch 18: reducing learning rate of group 0 to 5.0000e-15.
Test set: Average loss: 1.4770, Accuracy: 2056/5000 (41%)
[epoch 20] loss: 0.9829872
Epoch 19: reducing learning rate of group 0 to 5.0000e-16.
Test set: Average loss: 1.4770, Accuracy: 2056/5000 (41%)
[epoch 21] loss: 0.9431799
Test set: Average loss: 1.4770, Accuracy: 2056/5000 (41%)
[epoch 22] loss: 0.9994226
Epoch 21: reducing learning rate of group 0 to 5.0000e-17.
Test set: Average loss: 1.4770, Accuracy: 2056/5000 (41%)
[epoch 23] loss: 0.9572153
Epoch 22: reducing learning rate of group 0 to 5.0000e-18.
Test set: Average loss: 1.4770, Accuracy: 2056/5000 (41%)
[epoch 24] loss: 0.9564868
Epoch 23: reducing learning rate of group 0 to 5.0000e-19.
Test set: Average loss: 1.4770, Accuracy: 2056/5000 (41%)
[epoch 25] loss: 1.0286900
Epoch 24: reducing learning rate of group 0 to 5.0000e-20.
Test set: Average loss: 1.4770, Accuracy: 2056/5000 (41%)
Validation:
Test set: Average loss: 1.4776, Accuracy: 2059/5000 (41%)
Test
Test set: Average loss: 1.4809, Accuracy: 2001/5000 (40%)
Test set: Average loss: 1.0049, Accuracy: 83/100 (83%)
## seed: 13
Validation accuracy before training:
Test set: Average loss: 1.6447, Accuracy: 965/5000 (19%)
[epoch 1] loss: 1.6988120
Test set: Average loss: 1.5638, Accuracy: 1350/5000 (27%)
[epoch 2] loss: 1.3948456
Test set: Average loss: 1.5130, Accuracy: 1757/5000 (35%)
[epoch 3] loss: 1.2720302
Test set: Average loss: 1.4744, Accuracy: 2010/5000 (40%)
[epoch 4] loss: 1.2125669
Test set: Average loss: 1.4406, Accuracy: 2137/5000 (43%)
[epoch 5] loss: 1.1226065
Test set: Average loss: 1.4116, Accuracy: 2220/5000 (44%)
[epoch 6] loss: 1.0146910
Test set: Average loss: 1.3846, Accuracy: 2288/5000 (46%)
[epoch 7] loss: 0.9043189
Test set: Average loss: 1.3620, Accuracy: 2364/5000 (47%)
[epoch 8] loss: 0.9223748
Epoch 7: reducing learning rate of group 0 to 5.0000e-06.
Test set: Average loss: 1.3458, Accuracy: 2404/5000 (48%)
[epoch 9] loss: 0.8214634
Test set: Average loss: 1.3445, Accuracy: 2405/5000 (48%)
[epoch 10] loss: 0.8839266
Epoch 9: reducing learning rate of group 0 to 5.0000e-07.
Test set: Average loss: 1.3433, Accuracy: 2407/5000 (48%)
[epoch 11] loss: 0.8435194
Epoch 10: reducing learning rate of group 0 to 5.0000e-08.
Test set: Average loss: 1.3432, Accuracy: 2408/5000 (48%)
[epoch 12] loss: 0.8196486
Test set: Average loss: 1.3432, Accuracy: 2408/5000 (48%)
[epoch 13] loss: 0.8110991
Test set: Average loss: 1.3432, Accuracy: 2408/5000 (48%)
[epoch 14] loss: 0.8680475
Epoch 13: reducing learning rate of group 0 to 5.0000e-09.
Test set: Average loss: 1.3432, Accuracy: 2408/5000 (48%)
[epoch 15] loss: 0.7767549
Test set: Average loss: 1.3432, Accuracy: 2408/5000 (48%)
[epoch 16] loss: 0.8538594
Epoch 15: reducing learning rate of group 0 to 5.0000e-10.
Test set: Average loss: 1.3432, Accuracy: 2408/5000 (48%)
[epoch 17] loss: 0.8047387
Epoch 16: reducing learning rate of group 0 to 5.0000e-11.
Test set: Average loss: 1.3432, Accuracy: 2408/5000 (48%)
[epoch 18] loss: 0.8908876
Epoch 17: reducing learning rate of group 0 to 5.0000e-12.
Test set: Average loss: 1.3432, Accuracy: 2408/5000 (48%)
[epoch 19] loss: 0.8963065
Epoch 18: reducing learning rate of group 0 to 5.0000e-13.
Test set: Average loss: 1.3432, Accuracy: 2408/5000 (48%)
[epoch 20] loss: 0.7832982
Epoch 19: reducing learning rate of group 0 to 5.0000e-14.
Test set: Average loss: 1.3432, Accuracy: 2408/5000 (48%)
[epoch 21] loss: 0.7909575
Epoch 20: reducing learning rate of group 0 to 5.0000e-15.
Test set: Average loss: 1.3432, Accuracy: 2408/5000 (48%)
[epoch 22] loss: 0.8307038
Epoch 21: reducing learning rate of group 0 to 5.0000e-16.
Test set: Average loss: 1.3432, Accuracy: 2408/5000 (48%)
[epoch 23] loss: 0.8203425
Epoch 22: reducing learning rate of group 0 to 5.0000e-17.
Test set: Average loss: 1.3432, Accuracy: 2408/5000 (48%)
[epoch 24] loss: 0.8075072
Epoch 23: reducing learning rate of group 0 to 5.0000e-18.
Test set: Average loss: 1.3432, Accuracy: 2408/5000 (48%)
[epoch 25] loss: 0.8346032
Epoch 24: reducing learning rate of group 0 to 5.0000e-19.
Test set: Average loss: 1.3432, Accuracy: 2408/5000 (48%)
Validation:
Test set: Average loss: 1.3432, Accuracy: 2408/5000 (48%)
Test
Test set: Average loss: 1.3489, Accuracy: 2397/5000 (48%)
Test set: Average loss: 0.8280, Accuracy: 90/100 (90%)
250
## seed: 11
Validation accuracy before training:
Test set: Average loss: 1.6838, Accuracy: 757/5000 (15%)
[epoch 1] loss: 1.5482231
Test set: Average loss: 1.5160, Accuracy: 1307/5000 (26%)
[epoch 2] loss: 1.2808951
Test set: Average loss: 1.4338, Accuracy: 1682/5000 (34%)
[epoch 3] loss: 1.1294835
Test set: Average loss: 1.3813, Accuracy: 1896/5000 (38%)
[epoch 4] loss: 1.0202930
Test set: Average loss: 1.3391, Accuracy: 2111/5000 (42%)
[epoch 5] loss: 0.9303780
Test set: Average loss: 1.3092, Accuracy: 2263/5000 (45%)
[epoch 6] loss: 0.8657160
Test set: Average loss: 1.2884, Accuracy: 2386/5000 (48%)
[epoch 7] loss: 0.8081783
Test set: Average loss: 1.2709, Accuracy: 2502/5000 (50%)
[epoch 8] loss: 0.7593708
Test set: Average loss: 1.2560, Accuracy: 2567/5000 (51%)
[epoch 9] loss: 0.7226922
Test set: Average loss: 1.2445, Accuracy: 2585/5000 (52%)
[epoch 10] loss: 0.6798122
Test set: Average loss: 1.2379, Accuracy: 2585/5000 (52%)
[epoch 11] loss: 0.6508543
Test set: Average loss: 1.2321, Accuracy: 2602/5000 (52%)
[epoch 12] loss: 0.6220350
Test set: Average loss: 1.2238, Accuracy: 2616/5000 (52%)
[epoch 13] loss: 0.5974714
Test set: Average loss: 1.2186, Accuracy: 2616/5000 (52%)
[epoch 14] loss: 0.5739387
Test set: Average loss: 1.2141, Accuracy: 2630/5000 (53%)
[epoch 15] loss: 0.5556894
Test set: Average loss: 1.2095, Accuracy: 2633/5000 (53%)
[epoch 16] loss: 0.5371884
Test set: Average loss: 1.2064, Accuracy: 2627/5000 (53%)
[epoch 17] loss: 0.5197497
Test set: Average loss: 1.2042, Accuracy: 2635/5000 (53%)
[epoch 18] loss: 0.5035074
Test set: Average loss: 1.2008, Accuracy: 2649/5000 (53%)
[epoch 19] loss: 0.4893450
Test set: Average loss: 1.1967, Accuracy: 2676/5000 (54%)
[epoch 20] loss: 0.4748946
Test set: Average loss: 1.1944, Accuracy: 2678/5000 (54%)
[epoch 21] loss: 0.4611342
Test set: Average loss: 1.1929, Accuracy: 2680/5000 (54%)
[epoch 22] loss: 0.4510011
Test set: Average loss: 1.1898, Accuracy: 2680/5000 (54%)
[epoch 23] loss: 0.4361447
Test set: Average loss: 1.1879, Accuracy: 2693/5000 (54%)
[epoch 24] loss: 0.4279217
Test set: Average loss: 1.1852, Accuracy: 2690/5000 (54%)
[epoch 25] loss: 0.4175345
Test set: Average loss: 1.1841, Accuracy: 2695/5000 (54%)
Validation:
Test set: Average loss: 1.1841, Accuracy: 2695/5000 (54%)
Test
Test set: Average loss: 1.1974, Accuracy: 2600/5000 (52%)
Test set: Average loss: 0.4113, Accuracy: 250/250 (100%)
## seed: 12
Validation accuracy before training:
Test set: Average loss: 1.6406, Accuracy: 1194/5000 (24%)
[epoch 1] loss: 1.6775711
Test set: Average loss: 1.4964, Accuracy: 1789/5000 (36%)
[epoch 2] loss: 1.4129115
Test set: Average loss: 1.4320, Accuracy: 2024/5000 (40%)
[epoch 3] loss: 1.2449107
Test set: Average loss: 1.3806, Accuracy: 2203/5000 (44%)
[epoch 4] loss: 1.1171870
Test set: Average loss: 1.3397, Accuracy: 2358/5000 (47%)
[epoch 5] loss: 1.0193581
Test set: Average loss: 1.3186, Accuracy: 2424/5000 (48%)
[epoch 6] loss: 0.9468134
Test set: Average loss: 1.2977, Accuracy: 2481/5000 (50%)
[epoch 7] loss: 0.8861721
Test set: Average loss: 1.2853, Accuracy: 2506/5000 (50%)
[epoch 8] loss: 0.8305494
Test set: Average loss: 1.2748, Accuracy: 2530/5000 (51%)
[epoch 9] loss: 0.7886609
Test set: Average loss: 1.2676, Accuracy: 2556/5000 (51%)
[epoch 10] loss: 0.7470851
Test set: Average loss: 1.2576, Accuracy: 2605/5000 (52%)
[epoch 11] loss: 0.7122661
Test set: Average loss: 1.2522, Accuracy: 2621/5000 (52%)
[epoch 12] loss: 0.6798905
Test set: Average loss: 1.2472, Accuracy: 2616/5000 (52%)
[epoch 13] loss: 0.6505730
Test set: Average loss: 1.2393, Accuracy: 2632/5000 (53%)
[epoch 14] loss: 0.6268152
Test set: Average loss: 1.2366, Accuracy: 2623/5000 (52%)
[epoch 15] loss: 0.6027371
Test set: Average loss: 1.2325, Accuracy: 2626/5000 (53%)
[epoch 16] loss: 0.5804167
Test set: Average loss: 1.2261, Accuracy: 2625/5000 (52%)
[epoch 17] loss: 0.5595669
Test set: Average loss: 1.2233, Accuracy: 2627/5000 (53%)
[epoch 18] loss: 0.5385481
Test set: Average loss: 1.2221, Accuracy: 2622/5000 (52%)
[epoch 19] loss: 0.5205184
Test set: Average loss: 1.2183, Accuracy: 2640/5000 (53%)
[epoch 20] loss: 0.5045826
Test set: Average loss: 1.2159, Accuracy: 2643/5000 (53%)
[epoch 21] loss: 0.4913703
Test set: Average loss: 1.2126, Accuracy: 2664/5000 (53%)
[epoch 22] loss: 0.4751525
Test set: Average loss: 1.2106, Accuracy: 2667/5000 (53%)
[epoch 23] loss: 0.4619576
Test set: Average loss: 1.2091, Accuracy: 2667/5000 (53%)
[epoch 24] loss: 0.4504222
Test set: Average loss: 1.2074, Accuracy: 2673/5000 (53%)
[epoch 25] loss: 0.4392663
Test set: Average loss: 1.2049, Accuracy: 2665/5000 (53%)
Validation:
Test set: Average loss: 1.2074, Accuracy: 2673/5000 (53%)
Test
Test set: Average loss: 1.2094, Accuracy: 2722/5000 (54%)
Test set: Average loss: 0.4418, Accuracy: 248/250 (99%)
## seed: 13
Validation accuracy before training:
Test set: Average loss: 1.8177, Accuracy: 421/5000 (8%)
[epoch 1] loss: 1.8379741
Test set: Average loss: 1.6389, Accuracy: 1156/5000 (23%)
[epoch 2] loss: 1.5309358
Test set: Average loss: 1.5090, Accuracy: 1675/5000 (34%)
[epoch 3] loss: 1.3261131
Test set: Average loss: 1.4374, Accuracy: 1910/5000 (38%)
[epoch 4] loss: 1.1791657
Test set: Average loss: 1.3998, Accuracy: 2050/5000 (41%)
[epoch 5] loss: 1.0735238
Test set: Average loss: 1.3728, Accuracy: 2186/5000 (44%)
[epoch 6] loss: 0.9916769
Test set: Average loss: 1.3512, Accuracy: 2283/5000 (46%)
[epoch 7] loss: 0.9202357
Test set: Average loss: 1.3357, Accuracy: 2315/5000 (46%)
[epoch 8] loss: 0.8631387
Test set: Average loss: 1.3224, Accuracy: 2350/5000 (47%)
[epoch 9] loss: 0.8123928
Test set: Average loss: 1.3114, Accuracy: 2393/5000 (48%)
[epoch 10] loss: 0.7667945
Test set: Average loss: 1.3000, Accuracy: 2424/5000 (48%)
[epoch 11] loss: 0.7256009
Test set: Average loss: 1.2918, Accuracy: 2439/5000 (49%)
[epoch 12] loss: 0.6904798
Test set: Average loss: 1.2857, Accuracy: 2453/5000 (49%)
[epoch 13] loss: 0.6592452
Test set: Average loss: 1.2782, Accuracy: 2477/5000 (50%)
[epoch 14] loss: 0.6300729
Test set: Average loss: 1.2731, Accuracy: 2488/5000 (50%)
[epoch 15] loss: 0.6041918
Test set: Average loss: 1.2680, Accuracy: 2500/5000 (50%)
[epoch 16] loss: 0.5842308
Test set: Average loss: 1.2646, Accuracy: 2510/5000 (50%)
[epoch 17] loss: 0.5623010
Test set: Average loss: 1.2613, Accuracy: 2521/5000 (50%)
[epoch 18] loss: 0.5434454
Test set: Average loss: 1.2585, Accuracy: 2527/5000 (51%)
[epoch 19] loss: 0.5273697
Test set: Average loss: 1.2553, Accuracy: 2541/5000 (51%)
[epoch 20] loss: 0.5096503
Test set: Average loss: 1.2537, Accuracy: 2539/5000 (51%)
[epoch 21] loss: 0.4958749
Test set: Average loss: 1.2529, Accuracy: 2535/5000 (51%)
[epoch 22] loss: 0.4798668
Test set: Average loss: 1.2518, Accuracy: 2545/5000 (51%)
[epoch 23] loss: 0.4693072
Test set: Average loss: 1.2507, Accuracy: 2534/5000 (51%)
[epoch 24] loss: 0.4571878
Test set: Average loss: 1.2491, Accuracy: 2534/5000 (51%)
[epoch 25] loss: 0.4430411
Test set: Average loss: 1.2471, Accuracy: 2553/5000 (51%)
Validation:
Test set: Average loss: 1.2471, Accuracy: 2553/5000 (51%)
Test
Test set: Average loss: 1.2621, Accuracy: 2551/5000 (51%)
Test set: Average loss: 0.4356, Accuracy: 247/250 (99%)
500
## seed: 11
Validation accuracy before training:
Test set: Average loss: 1.5860, Accuracy: 1497/5000 (30%)
[epoch 1] loss: 1.4805856
Test set: Average loss: 1.3550, Accuracy: 2453/5000 (49%)
[epoch 2] loss: 1.1933694
Test set: Average loss: 1.2777, Accuracy: 2699/5000 (54%)
[epoch 3] loss: 1.0430645
Test set: Average loss: 1.2380, Accuracy: 2810/5000 (56%)
[epoch 4] loss: 0.9381177
Test set: Average loss: 1.2143, Accuracy: 2852/5000 (57%)
[epoch 5] loss: 0.8595334
Test set: Average loss: 1.1930, Accuracy: 2901/5000 (58%)
[epoch 6] loss: 0.7972443
Test set: Average loss: 1.1775, Accuracy: 2940/5000 (59%)
[epoch 7] loss: 0.7449437
Test set: Average loss: 1.1668, Accuracy: 2974/5000 (59%)
[epoch 8] loss: 0.7011275
Test set: Average loss: 1.1563, Accuracy: 2995/5000 (60%)
[epoch 9] loss: 0.6614209
Test set: Average loss: 1.1500, Accuracy: 3003/5000 (60%)
[epoch 10] loss: 0.6242107
Test set: Average loss: 1.1412, Accuracy: 3006/5000 (60%)
[epoch 11] loss: 0.5943697
Test set: Average loss: 1.1376, Accuracy: 3014/5000 (60%)
[epoch 12] loss: 0.5653164
Test set: Average loss: 1.1302, Accuracy: 3030/5000 (61%)
[epoch 13] loss: 0.5418764
Test set: Average loss: 1.1257, Accuracy: 3037/5000 (61%)
[epoch 14] loss: 0.5186846
Test set: Average loss: 1.1207, Accuracy: 3042/5000 (61%)
[epoch 15] loss: 0.4944627
Test set: Average loss: 1.1182, Accuracy: 3048/5000 (61%)
[epoch 16] loss: 0.4742063
Test set: Average loss: 1.1148, Accuracy: 3053/5000 (61%)
[epoch 17] loss: 0.4551406
Test set: Average loss: 1.1102, Accuracy: 3052/5000 (61%)
[epoch 18] loss: 0.4383815
Test set: Average loss: 1.1079, Accuracy: 3054/5000 (61%)
[epoch 19] loss: 0.4207971
Test set: Average loss: 1.1048, Accuracy: 3059/5000 (61%)
[epoch 20] loss: 0.4044102
Test set: Average loss: 1.1029, Accuracy: 3072/5000 (61%)
[epoch 21] loss: 0.3922497
Test set: Average loss: 1.1011, Accuracy: 3064/5000 (61%)
[epoch 22] loss: 0.3811501
Test set: Average loss: 1.0982, Accuracy: 3071/5000 (61%)
[epoch 23] loss: 0.3657280
Test set: Average loss: 1.0944, Accuracy: 3076/5000 (62%)
[epoch 24] loss: 0.3521690
Test set: Average loss: 1.0927, Accuracy: 3073/5000 (61%)
[epoch 25] loss: 0.3411401
Test set: Average loss: 1.0914, Accuracy: 3072/5000 (61%)
Validation:
Test set: Average loss: 1.0944, Accuracy: 3076/5000 (62%)
Test
Test set: Average loss: 1.1130, Accuracy: 2974/5000 (59%)
Test set: Average loss: 0.3560, Accuracy: 498/500 (100%)
## seed: 12
Validation accuracy before training:
Test set: Average loss: 1.8313, Accuracy: 310/5000 (6%)
[epoch 1] loss: 1.6818938
Test set: Average loss: 1.4505, Accuracy: 1809/5000 (36%)
[epoch 2] loss: 1.3218014
Test set: Average loss: 1.3495, Accuracy: 2225/5000 (44%)
[epoch 3] loss: 1.1576754
Test set: Average loss: 1.2954, Accuracy: 2445/5000 (49%)
[epoch 4] loss: 1.0485701
Test set: Average loss: 1.2611, Accuracy: 2559/5000 (51%)
[epoch 5] loss: 0.9610917
Test set: Average loss: 1.2397, Accuracy: 2643/5000 (53%)
[epoch 6] loss: 0.8983883
Test set: Average loss: 1.2244, Accuracy: 2672/5000 (53%)
[epoch 7] loss: 0.8433390
Test set: Average loss: 1.2089, Accuracy: 2710/5000 (54%)
[epoch 8] loss: 0.7924464
Test set: Average loss: 1.1987, Accuracy: 2760/5000 (55%)
[epoch 9] loss: 0.7448871
Test set: Average loss: 1.1902, Accuracy: 2794/5000 (56%)
[epoch 10] loss: 0.7087070
Test set: Average loss: 1.1799, Accuracy: 2827/5000 (57%)
[epoch 11] loss: 0.6754024
Test set: Average loss: 1.1741, Accuracy: 2822/5000 (56%)
[epoch 12] loss: 0.6416319
Test set: Average loss: 1.1662, Accuracy: 2848/5000 (57%)
[epoch 13] loss: 0.6135628
Test set: Average loss: 1.1630, Accuracy: 2861/5000 (57%)
[epoch 14] loss: 0.5867869
Test set: Average loss: 1.1562, Accuracy: 2880/5000 (58%)
[epoch 15] loss: 0.5639757
Test set: Average loss: 1.1511, Accuracy: 2890/5000 (58%)
[epoch 16] loss: 0.5406508
Test set: Average loss: 1.1506, Accuracy: 2897/5000 (58%)
[epoch 17] loss: 0.5205365
Test set: Average loss: 1.1437, Accuracy: 2912/5000 (58%)
[epoch 18] loss: 0.5035946
Test set: Average loss: 1.1411, Accuracy: 2914/5000 (58%)
[epoch 19] loss: 0.4849560
Test set: Average loss: 1.1414, Accuracy: 2912/5000 (58%)
[epoch 20] loss: 0.4674301
Test set: Average loss: 1.1360, Accuracy: 2921/5000 (58%)
[epoch 21] loss: 0.4499228
Test set: Average loss: 1.1332, Accuracy: 2926/5000 (59%)
[epoch 22] loss: 0.4337120
Test set: Average loss: 1.1324, Accuracy: 2937/5000 (59%)
[epoch 23] loss: 0.4221175
Test set: Average loss: 1.1292, Accuracy: 2933/5000 (59%)
[epoch 24] loss: 0.4073324
Test set: Average loss: 1.1292, Accuracy: 2926/5000 (59%)
[epoch 25] loss: 0.3933593
Test set: Average loss: 1.1280, Accuracy: 2925/5000 (58%)
Validation:
Test set: Average loss: 1.1324, Accuracy: 2937/5000 (59%)
Test
Test set: Average loss: 1.1371, Accuracy: 2850/5000 (57%)
Test set: Average loss: 0.4235, Accuracy: 494/500 (99%)
## seed: 13
Validation accuracy before training:
Test set: Average loss: 1.7910, Accuracy: 745/5000 (15%)
[epoch 1] loss: 1.6427893
Test set: Average loss: 1.4725, Accuracy: 1794/5000 (36%)
[epoch 2] loss: 1.2810431
Test set: Average loss: 1.3692, Accuracy: 2184/5000 (44%)
[epoch 3] loss: 1.0978396
Test set: Average loss: 1.3100, Accuracy: 2372/5000 (47%)
[epoch 4] loss: 0.9789275
Test set: Average loss: 1.2771, Accuracy: 2455/5000 (49%)
[epoch 5] loss: 0.8923246
Test set: Average loss: 1.2567, Accuracy: 2520/5000 (50%)
[epoch 6] loss: 0.8187627
Test set: Average loss: 1.2412, Accuracy: 2590/5000 (52%)
[epoch 7] loss: 0.7566437
Test set: Average loss: 1.2308, Accuracy: 2619/5000 (52%)
[epoch 8] loss: 0.7134103
Test set: Average loss: 1.2241, Accuracy: 2643/5000 (53%)
[epoch 9] loss: 0.6687481
Test set: Average loss: 1.2165, Accuracy: 2680/5000 (54%)
[epoch 10] loss: 0.6328622
Test set: Average loss: 1.2078, Accuracy: 2709/5000 (54%)
[epoch 11] loss: 0.6002069
Test set: Average loss: 1.2055, Accuracy: 2708/5000 (54%)
[epoch 12] loss: 0.5708236
Test set: Average loss: 1.2001, Accuracy: 2725/5000 (54%)
[epoch 13] loss: 0.5461398
Test set: Average loss: 1.1933, Accuracy: 2739/5000 (55%)
[epoch 14] loss: 0.5239661
Test set: Average loss: 1.1902, Accuracy: 2752/5000 (55%)
[epoch 15] loss: 0.4996097
Test set: Average loss: 1.1872, Accuracy: 2763/5000 (55%)
[epoch 16] loss: 0.4799714
Test set: Average loss: 1.1822, Accuracy: 2779/5000 (56%)
[epoch 17] loss: 0.4585385
Test set: Average loss: 1.1768, Accuracy: 2794/5000 (56%)
[epoch 18] loss: 0.4455832
Test set: Average loss: 1.1742, Accuracy: 2808/5000 (56%)
[epoch 19] loss: 0.4272833
Test set: Average loss: 1.1736, Accuracy: 2813/5000 (56%)
[epoch 20] loss: 0.4126192
Test set: Average loss: 1.1680, Accuracy: 2820/5000 (56%)
[epoch 21] loss: 0.3972745
Test set: Average loss: 1.1687, Accuracy: 2828/5000 (57%)
[epoch 22] loss: 0.3851567
Test set: Average loss: 1.1642, Accuracy: 2833/5000 (57%)
[epoch 23] loss: 0.3717604
Test set: Average loss: 1.1643, Accuracy: 2833/5000 (57%)
[epoch 24] loss: 0.3583621
Test set: Average loss: 1.1581, Accuracy: 2853/5000 (57%)
[epoch 25] loss: 0.3477614
Test set: Average loss: 1.1590, Accuracy: 2856/5000 (57%)
Validation:
Test set: Average loss: 1.1590, Accuracy: 2856/5000 (57%)
Test
Test set: Average loss: 1.1718, Accuracy: 2822/5000 (56%)
Test set: Average loss: 0.3387, Accuracy: 497/500 (99%)
750
## seed: 11
Validation accuracy before training:
Test set: Average loss: 1.6309, Accuracy: 890/5000 (18%)
[epoch 1] loss: 1.3877331
Test set: Average loss: 1.3329, Accuracy: 2457/5000 (49%)
[epoch 2] loss: 1.0975036
Test set: Average loss: 1.2460, Accuracy: 2729/5000 (55%)
[epoch 3] loss: 0.9503805
Test set: Average loss: 1.2036, Accuracy: 2871/5000 (57%)
[epoch 4] loss: 0.8638156
Test set: Average loss: 1.1788, Accuracy: 2915/5000 (58%)
[epoch 5] loss: 0.7998819
Test set: Average loss: 1.1615, Accuracy: 2929/5000 (59%)
[epoch 6] loss: 0.7449201
Test set: Average loss: 1.1501, Accuracy: 2948/5000 (59%)
[epoch 7] loss: 0.6951554
Test set: Average loss: 1.1395, Accuracy: 2979/5000 (60%)
[epoch 8] loss: 0.6602330
Test set: Average loss: 1.1296, Accuracy: 3013/5000 (60%)
[epoch 9] loss: 0.6281449
Test set: Average loss: 1.1210, Accuracy: 3012/5000 (60%)
[epoch 10] loss: 0.5974353
Test set: Average loss: 1.1146, Accuracy: 3016/5000 (60%)
[epoch 11] loss: 0.5682397
Test set: Average loss: 1.1083, Accuracy: 3058/5000 (61%)
[epoch 12] loss: 0.5447474
Test set: Average loss: 1.1021, Accuracy: 3051/5000 (61%)
[epoch 13] loss: 0.5196615
Test set: Average loss: 1.0973, Accuracy: 3083/5000 (62%)
[epoch 14] loss: 0.4952127
Test set: Average loss: 1.0934, Accuracy: 3081/5000 (62%)
[epoch 15] loss: 0.4754710
Test set: Average loss: 1.0863, Accuracy: 3074/5000 (61%)
[epoch 16] loss: 0.4565718
Test set: Average loss: 1.0829, Accuracy: 3089/5000 (62%)
[epoch 17] loss: 0.4395377
Test set: Average loss: 1.0787, Accuracy: 3108/5000 (62%)
[epoch 18] loss: 0.4231631
Test set: Average loss: 1.0741, Accuracy: 3109/5000 (62%)
[epoch 19] loss: 0.4040625
Test set: Average loss: 1.0710, Accuracy: 3111/5000 (62%)
[epoch 20] loss: 0.3891200
Test set: Average loss: 1.0682, Accuracy: 3131/5000 (63%)
[epoch 21] loss: 0.3759629
Test set: Average loss: 1.0655, Accuracy: 3138/5000 (63%)
[epoch 22] loss: 0.3619529
Test set: Average loss: 1.0645, Accuracy: 3110/5000 (62%)
[epoch 23] loss: 0.3474928
Test set: Average loss: 1.0616, Accuracy: 3135/5000 (63%)
[epoch 24] loss: 0.3347867
Test set: Average loss: 1.0589, Accuracy: 3125/5000 (62%)
[epoch 25] loss: 0.3222001
Test set: Average loss: 1.0561, Accuracy: 3120/5000 (62%)
Validation:
Test set: Average loss: 1.0655, Accuracy: 3138/5000 (63%)
Test
Test set: Average loss: 1.0793, Accuracy: 3051/5000 (61%)
Test set: Average loss: 0.3639, Accuracy: 746/750 (99%)
## seed: 12
Validation accuracy before training:
Test set: Average loss: 1.6511, Accuracy: 996/5000 (20%)
[epoch 1] loss: 1.5219141
Test set: Average loss: 1.3684, Accuracy: 2103/5000 (42%)
[epoch 2] loss: 1.2019520
Test set: Average loss: 1.2677, Accuracy: 2504/5000 (50%)
[epoch 3] loss: 1.0372322
Test set: Average loss: 1.2244, Accuracy: 2618/5000 (52%)
[epoch 4] loss: 0.9351907
Test set: Average loss: 1.1960, Accuracy: 2760/5000 (55%)
[epoch 5] loss: 0.8582402
Test set: Average loss: 1.1757, Accuracy: 2817/5000 (56%)
[epoch 6] loss: 0.7961876
Test set: Average loss: 1.1610, Accuracy: 2853/5000 (57%)
[epoch 7] loss: 0.7341529
Test set: Average loss: 1.1455, Accuracy: 2899/5000 (58%)
[epoch 8] loss: 0.6911478
Test set: Average loss: 1.1343, Accuracy: 2938/5000 (59%)
[epoch 9] loss: 0.6525319
Test set: Average loss: 1.1243, Accuracy: 2955/5000 (59%)
[epoch 10] loss: 0.6121343
Test set: Average loss: 1.1167, Accuracy: 2969/5000 (59%)
[epoch 11] loss: 0.5804954
Test set: Average loss: 1.1079, Accuracy: 3004/5000 (60%)
[epoch 12] loss: 0.5447629
Test set: Average loss: 1.0997, Accuracy: 3014/5000 (60%)
[epoch 13] loss: 0.5187127
Test set: Average loss: 1.0955, Accuracy: 3013/5000 (60%)
[epoch 14] loss: 0.4923955
Test set: Average loss: 1.0896, Accuracy: 3019/5000 (60%)
[epoch 15] loss: 0.4671896
Test set: Average loss: 1.0819, Accuracy: 3049/5000 (61%)
[epoch 16] loss: 0.4432782
Test set: Average loss: 1.0799, Accuracy: 3050/5000 (61%)
[epoch 17] loss: 0.4204336
Test set: Average loss: 1.0749, Accuracy: 3058/5000 (61%)
[epoch 18] loss: 0.4021400
Test set: Average loss: 1.0706, Accuracy: 3059/5000 (61%)
[epoch 19] loss: 0.3843744
Test set: Average loss: 1.0675, Accuracy: 3063/5000 (61%)
[epoch 20] loss: 0.3684112
Test set: Average loss: 1.0649, Accuracy: 3061/5000 (61%)
[epoch 21] loss: 0.3537277
Test set: Average loss: 1.0616, Accuracy: 3067/5000 (61%)
[epoch 22] loss: 0.3387828
Test set: Average loss: 1.0590, Accuracy: 3073/5000 (61%)
[epoch 23] loss: 0.3260398
Test set: Average loss: 1.0567, Accuracy: 3061/5000 (61%)
[epoch 24] loss: 0.3107745
Test set: Average loss: 1.0539, Accuracy: 3068/5000 (61%)
[epoch 25] loss: 0.3001118
Test set: Average loss: 1.0519, Accuracy: 3058/5000 (61%)
Validation:
Test set: Average loss: 1.0590, Accuracy: 3073/5000 (61%)
Test
Test set: Average loss: 1.0805, Accuracy: 2978/5000 (60%)
Test set: Average loss: 0.3277, Accuracy: 749/750 (100%)
## seed: 13
Validation accuracy before training:
Test set: Average loss: 1.6204, Accuracy: 1183/5000 (24%)
[epoch 1] loss: 1.3948485
Test set: Average loss: 1.3199, Accuracy: 2541/5000 (51%)
[epoch 2] loss: 1.0780061
Test set: Average loss: 1.2382, Accuracy: 2720/5000 (54%)
[epoch 3] loss: 0.9322229
Test set: Average loss: 1.1948, Accuracy: 2869/5000 (57%)
[epoch 4] loss: 0.8208998
Test set: Average loss: 1.1644, Accuracy: 2911/5000 (58%)
[epoch 5] loss: 0.7374919
Test set: Average loss: 1.1390, Accuracy: 2944/5000 (59%)
[epoch 6] loss: 0.6766388
Test set: Average loss: 1.1240, Accuracy: 2974/5000 (59%)
[epoch 7] loss: 0.6224680
Test set: Average loss: 1.1139, Accuracy: 2983/5000 (60%)
[epoch 8] loss: 0.5767704
Test set: Average loss: 1.1033, Accuracy: 3013/5000 (60%)
[epoch 9] loss: 0.5411845
Test set: Average loss: 1.0969, Accuracy: 2994/5000 (60%)
[epoch 10] loss: 0.5082369
Test set: Average loss: 1.0890, Accuracy: 3003/5000 (60%)
[epoch 11] loss: 0.4793305
Test set: Average loss: 1.0877, Accuracy: 3002/5000 (60%)
[epoch 12] loss: 0.4533647
Test set: Average loss: 1.0819, Accuracy: 3025/5000 (60%)
[epoch 13] loss: 0.4293969
Test set: Average loss: 1.0759, Accuracy: 3026/5000 (61%)
[epoch 14] loss: 0.4103143
Test set: Average loss: 1.0740, Accuracy: 3038/5000 (61%)
[epoch 15] loss: 0.3873929
Test set: Average loss: 1.0678, Accuracy: 3049/5000 (61%)
[epoch 16] loss: 0.3709538
Test set: Average loss: 1.0679, Accuracy: 3059/5000 (61%)
[epoch 17] loss: 0.3539151
Test set: Average loss: 1.0630, Accuracy: 3058/5000 (61%)
[epoch 18] loss: 0.3383252
Test set: Average loss: 1.0609, Accuracy: 3063/5000 (61%)
[epoch 19] loss: 0.3238059
Test set: Average loss: 1.0571, Accuracy: 3061/5000 (61%)
[epoch 20] loss: 0.3078979
Test set: Average loss: 1.0564, Accuracy: 3072/5000 (61%)
[epoch 21] loss: 0.2954488
Test set: Average loss: 1.0529, Accuracy: 3073/5000 (61%)
[epoch 22] loss: 0.2841155
Test set: Average loss: 1.0534, Accuracy: 3077/5000 (62%)
[epoch 23] loss: 0.2725984
Test set: Average loss: 1.0516, Accuracy: 3077/5000 (62%)
[epoch 24] loss: 0.2627352
Test set: Average loss: 1.0489, Accuracy: 3072/5000 (61%)
[epoch 25] loss: 0.2540104
Test set: Average loss: 1.0505, Accuracy: 3082/5000 (62%)
Validation:
Test set: Average loss: 1.0505, Accuracy: 3082/5000 (62%)
Test
Test set: Average loss: 1.0731, Accuracy: 3009/5000 (60%)
Test set: Average loss: 0.2465, Accuracy: 748/750 (100%)
1000
## seed: 11
Validation accuracy before training:
Test set: Average loss: 1.7016, Accuracy: 938/5000 (19%)
[epoch 1] loss: 1.4084938
Test set: Average loss: 1.3049, Accuracy: 2530/5000 (51%)
[epoch 2] loss: 1.0836867
Test set: Average loss: 1.2204, Accuracy: 2759/5000 (55%)
[epoch 3] loss: 0.9564938
Test set: Average loss: 1.1818, Accuracy: 2853/5000 (57%)
[epoch 4] loss: 0.8661323
Test set: Average loss: 1.1592, Accuracy: 2931/5000 (59%)
[epoch 5] loss: 0.8095397
Test set: Average loss: 1.1446, Accuracy: 2947/5000 (59%)
[epoch 6] loss: 0.7504350
Test set: Average loss: 1.1270, Accuracy: 3015/5000 (60%)
[epoch 7] loss: 0.7032011
Test set: Average loss: 1.1175, Accuracy: 3038/5000 (61%)
[epoch 8] loss: 0.6606792
Test set: Average loss: 1.1084, Accuracy: 3045/5000 (61%)
[epoch 9] loss: 0.6272145
Test set: Average loss: 1.0993, Accuracy: 3076/5000 (62%)
[epoch 10] loss: 0.5933549
Test set: Average loss: 1.0929, Accuracy: 3076/5000 (62%)
[epoch 11] loss: 0.5654787
Test set: Average loss: 1.0839, Accuracy: 3086/5000 (62%)
[epoch 12] loss: 0.5320772
Test set: Average loss: 1.0778, Accuracy: 3110/5000 (62%)
[epoch 13] loss: 0.5082687
Test set: Average loss: 1.0715, Accuracy: 3106/5000 (62%)
[epoch 14] loss: 0.4856221
Test set: Average loss: 1.0674, Accuracy: 3120/5000 (62%)
[epoch 15] loss: 0.4643295
Test set: Average loss: 1.0606, Accuracy: 3128/5000 (63%)
[epoch 16] loss: 0.4401206
Test set: Average loss: 1.0553, Accuracy: 3143/5000 (63%)
[epoch 17] loss: 0.4166220
Test set: Average loss: 1.0512, Accuracy: 3140/5000 (63%)
[epoch 18] loss: 0.3986788
Test set: Average loss: 1.0474, Accuracy: 3147/5000 (63%)
[epoch 19] loss: 0.3836945
Test set: Average loss: 1.0435, Accuracy: 3151/5000 (63%)
[epoch 20] loss: 0.3633266
Test set: Average loss: 1.0401, Accuracy: 3159/5000 (63%)
[epoch 21] loss: 0.3496952
Test set: Average loss: 1.0405, Accuracy: 3139/5000 (63%)
[epoch 22] loss: 0.3348204
Test set: Average loss: 1.0334, Accuracy: 3171/5000 (63%)
[epoch 23] loss: 0.3159014
Test set: Average loss: 1.0314, Accuracy: 3172/5000 (63%)
[epoch 24] loss: 0.3025560
Test set: Average loss: 1.0336, Accuracy: 3162/5000 (63%)
[epoch 25] loss: 0.2903356
Test set: Average loss: 1.0298, Accuracy: 3156/5000 (63%)
Validation:
Test set: Average loss: 1.0314, Accuracy: 3172/5000 (63%)
Test
Test set: Average loss: 1.0487, Accuracy: 3083/5000 (62%)
Test set: Average loss: 0.3054, Accuracy: 998/1000 (100%)
## seed: 12
Validation accuracy before training:
Test set: Average loss: 1.9303, Accuracy: 290/5000 (6%)
[epoch 1] loss: 1.6768314
Test set: Average loss: 1.4495, Accuracy: 1857/5000 (37%)
[epoch 2] loss: 1.3116233
Test set: Average loss: 1.3401, Accuracy: 2283/5000 (46%)
[epoch 3] loss: 1.1597555
Test set: Average loss: 1.2866, Accuracy: 2502/5000 (50%)
[epoch 4] loss: 1.0459749
Test set: Average loss: 1.2554, Accuracy: 2652/5000 (53%)
[epoch 5] loss: 0.9630055
Test set: Average loss: 1.2198, Accuracy: 2745/5000 (55%)
[epoch 6] loss: 0.8853679
Test set: Average loss: 1.2066, Accuracy: 2810/5000 (56%)
[epoch 7] loss: 0.8272403
Test set: Average loss: 1.1843, Accuracy: 2849/5000 (57%)
[epoch 8] loss: 0.7751445
Test set: Average loss: 1.1737, Accuracy: 2858/5000 (57%)
[epoch 9] loss: 0.7281232
Test set: Average loss: 1.1640, Accuracy: 2903/5000 (58%)
[epoch 10] loss: 0.6891880
Test set: Average loss: 1.1517, Accuracy: 2926/5000 (59%)
[epoch 11] loss: 0.6479424
Test set: Average loss: 1.1420, Accuracy: 2943/5000 (59%)
[epoch 12] loss: 0.6129749
Test set: Average loss: 1.1385, Accuracy: 2949/5000 (59%)
[epoch 13] loss: 0.5744950
Test set: Average loss: 1.1279, Accuracy: 2955/5000 (59%)
[epoch 14] loss: 0.5462437
Test set: Average loss: 1.1223, Accuracy: 2997/5000 (60%)
[epoch 15] loss: 0.5202915
Test set: Average loss: 1.1136, Accuracy: 2990/5000 (60%)
[epoch 16] loss: 0.4895582
Test set: Average loss: 1.1075, Accuracy: 3012/5000 (60%)
[epoch 17] loss: 0.4648249
Test set: Average loss: 1.1039, Accuracy: 2991/5000 (60%)
[epoch 18] loss: 0.4429291
Test set: Average loss: 1.0976, Accuracy: 3002/5000 (60%)
[epoch 19] loss: 0.4203791
Test set: Average loss: 1.0971, Accuracy: 3014/5000 (60%)
[epoch 20] loss: 0.3982940
Test set: Average loss: 1.0938, Accuracy: 2997/5000 (60%)
[epoch 21] loss: 0.3835590
Test set: Average loss: 1.0893, Accuracy: 3018/5000 (60%)
[epoch 22] loss: 0.3638921
Test set: Average loss: 1.0878, Accuracy: 3022/5000 (60%)
[epoch 23] loss: 0.3476636
Test set: Average loss: 1.0833, Accuracy: 3030/5000 (61%)
[epoch 24] loss: 0.3316761
Test set: Average loss: 1.0803, Accuracy: 3022/5000 (60%)
[epoch 25] loss: 0.3174582
Test set: Average loss: 1.0810, Accuracy: 3017/5000 (60%)
Validation:
Test set: Average loss: 1.0833, Accuracy: 3030/5000 (61%)
Test
Test set: Average loss: 1.0904, Accuracy: 2970/5000 (59%)
Test set: Average loss: 0.3348, Accuracy: 994/1000 (99%)
## seed: 13
Validation accuracy before training:
Test set: Average loss: 1.5865, Accuracy: 1159/5000 (23%)
[epoch 1] loss: 1.3656923
Test set: Average loss: 1.3007, Accuracy: 2457/5000 (49%)
[epoch 2] loss: 1.0745735
Test set: Average loss: 1.2129, Accuracy: 2740/5000 (55%)
[epoch 3] loss: 0.9450153
Test set: Average loss: 1.1725, Accuracy: 2891/5000 (58%)
[epoch 4] loss: 0.8596837
Test set: Average loss: 1.1479, Accuracy: 2949/5000 (59%)
[epoch 5] loss: 0.7841939
Test set: Average loss: 1.1266, Accuracy: 3013/5000 (60%)
[epoch 6] loss: 0.7331325
Test set: Average loss: 1.1154, Accuracy: 3005/5000 (60%)
[epoch 7] loss: 0.6841010
Test set: Average loss: 1.1035, Accuracy: 3053/5000 (61%)
[epoch 8] loss: 0.6357848
Test set: Average loss: 1.0905, Accuracy: 3082/5000 (62%)
[epoch 9] loss: 0.5936404
Test set: Average loss: 1.0803, Accuracy: 3092/5000 (62%)
[epoch 10] loss: 0.5566561
Test set: Average loss: 1.0727, Accuracy: 3100/5000 (62%)
[epoch 11] loss: 0.5257660
Test set: Average loss: 1.0669, Accuracy: 3109/5000 (62%)
[epoch 12] loss: 0.4921197
Test set: Average loss: 1.0642, Accuracy: 3103/5000 (62%)
[epoch 13] loss: 0.4699215
Test set: Average loss: 1.0590, Accuracy: 3114/5000 (62%)
[epoch 14] loss: 0.4423363
Test set: Average loss: 1.0521, Accuracy: 3114/5000 (62%)
[epoch 15] loss: 0.4163031
Test set: Average loss: 1.0495, Accuracy: 3116/5000 (62%)
[epoch 16] loss: 0.3954498
Test set: Average loss: 1.0458, Accuracy: 3115/5000 (62%)
[epoch 17] loss: 0.3714576
Test set: Average loss: 1.0419, Accuracy: 3128/5000 (63%)
[epoch 18] loss: 0.3546410
Test set: Average loss: 1.0372, Accuracy: 3134/5000 (63%)
[epoch 19] loss: 0.3363165
Test set: Average loss: 1.0332, Accuracy: 3131/5000 (63%)
[epoch 20] loss: 0.3190368
Test set: Average loss: 1.0315, Accuracy: 3135/5000 (63%)
[epoch 21] loss: 0.3037798
Test set: Average loss: 1.0277, Accuracy: 3132/5000 (63%)
[epoch 22] loss: 0.2882430
Test set: Average loss: 1.0292, Accuracy: 3136/5000 (63%)
[epoch 23] loss: 0.2749688
Test set: Average loss: 1.0216, Accuracy: 3151/5000 (63%)
[epoch 24] loss: 0.2627836
Test set: Average loss: 1.0245, Accuracy: 3138/5000 (63%)
[epoch 25] loss: 0.2509770
Test set: Average loss: 1.0204, Accuracy: 3132/5000 (63%)
Validation:
Test set: Average loss: 1.0216, Accuracy: 3151/5000 (63%)
Test
Test set: Average loss: 1.0490, Accuracy: 3084/5000 (62%)
Test set: Average loss: 0.2647, Accuracy: 996/1000 (100%)
2500
## seed: 11
Validation accuracy before training:
Test set: Average loss: 1.7744, Accuracy: 893/5000 (18%)
[epoch 1] loss: 1.3602658
Test set: Average loss: 1.2266, Accuracy: 2707/5000 (54%)
[epoch 2] loss: 1.0751463
Test set: Average loss: 1.1532, Accuracy: 2935/5000 (59%)
[epoch 3] loss: 0.9497482
Test set: Average loss: 1.1146, Accuracy: 3026/5000 (61%)
[epoch 4] loss: 0.8608674
Test set: Average loss: 1.0918, Accuracy: 3066/5000 (61%)
[epoch 5] loss: 0.7852067
Test set: Average loss: 1.0632, Accuracy: 3116/5000 (62%)
[epoch 6] loss: 0.7234589
Test set: Average loss: 1.0486, Accuracy: 3150/5000 (63%)
[epoch 7] loss: 0.6649159
Test set: Average loss: 1.0246, Accuracy: 3180/5000 (64%)
[epoch 8] loss: 0.6116703
Test set: Average loss: 1.0124, Accuracy: 3191/5000 (64%)
[epoch 9] loss: 0.5615463
Test set: Average loss: 0.9965, Accuracy: 3229/5000 (65%)
[epoch 10] loss: 0.5154077
Test set: Average loss: 0.9935, Accuracy: 3203/5000 (64%)
[epoch 11] loss: 0.4765755
Test set: Average loss: 0.9823, Accuracy: 3229/5000 (65%)
[epoch 12] loss: 0.4370015
Test set: Average loss: 0.9723, Accuracy: 3245/5000 (65%)
[epoch 13] loss: 0.4048314
Test set: Average loss: 0.9647, Accuracy: 3247/5000 (65%)
[epoch 14] loss: 0.3699263
Test set: Average loss: 0.9597, Accuracy: 3225/5000 (64%)
[epoch 15] loss: 0.3372378
Test set: Average loss: 0.9537, Accuracy: 3264/5000 (65%)
[epoch 16] loss: 0.3098473
Test set: Average loss: 0.9519, Accuracy: 3245/5000 (65%)
[epoch 17] loss: 0.2835267
Test set: Average loss: 0.9495, Accuracy: 3276/5000 (66%)
[epoch 18] loss: 0.2585233
Test set: Average loss: 0.9441, Accuracy: 3266/5000 (65%)
[epoch 19] loss: 0.2380313
Test set: Average loss: 0.9453, Accuracy: 3263/5000 (65%)
[epoch 20] loss: 0.2180825
Test set: Average loss: 0.9410, Accuracy: 3289/5000 (66%)
[epoch 21] loss: 0.2002116
Test set: Average loss: 0.9416, Accuracy: 3273/5000 (65%)
[epoch 22] loss: 0.1845831
Test set: Average loss: 0.9376, Accuracy: 3266/5000 (65%)
[epoch 23] loss: 0.1739579
Test set: Average loss: 0.9409, Accuracy: 3265/5000 (65%)
[epoch 24] loss: 0.1577918
Test set: Average loss: 0.9427, Accuracy: 3280/5000 (66%)
[epoch 25] loss: 0.1442770
Test set: Average loss: 0.9406, Accuracy: 3288/5000 (66%)
Validation:
Test set: Average loss: 0.9410, Accuracy: 3289/5000 (66%)
Test
Test set: Average loss: 0.9552, Accuracy: 3190/5000 (64%)
Test set: Average loss: 0.2025, Accuracy: 2488/2500 (100%)
## seed: 12
Validation accuracy before training:
Test set: Average loss: 1.9740, Accuracy: 219/5000 (4%)
[epoch 1] loss: 1.5319574
Test set: Average loss: 1.2958, Accuracy: 2410/5000 (48%)
[epoch 2] loss: 1.1634947
Test set: Average loss: 1.1853, Accuracy: 2756/5000 (55%)
[epoch 3] loss: 1.0168636
Test set: Average loss: 1.1377, Accuracy: 2901/5000 (58%)
[epoch 4] loss: 0.9251026
Test set: Average loss: 1.1047, Accuracy: 2995/5000 (60%)
[epoch 5] loss: 0.8417128
Test set: Average loss: 1.0810, Accuracy: 3040/5000 (61%)
[epoch 6] loss: 0.7724358
Test set: Average loss: 1.0654, Accuracy: 3079/5000 (62%)
[epoch 7] loss: 0.7148088
Test set: Average loss: 1.0448, Accuracy: 3127/5000 (63%)
[epoch 8] loss: 0.6580207
Test set: Average loss: 1.0344, Accuracy: 3130/5000 (63%)
[epoch 9] loss: 0.6087265
Test set: Average loss: 1.0230, Accuracy: 3153/5000 (63%)
[epoch 10] loss: 0.5698981
Test set: Average loss: 1.0133, Accuracy: 3161/5000 (63%)
[epoch 11] loss: 0.5216731
Test set: Average loss: 1.0060, Accuracy: 3175/5000 (64%)
[epoch 12] loss: 0.4814574
Test set: Average loss: 0.9998, Accuracy: 3183/5000 (64%)
[epoch 13] loss: 0.4485562
Test set: Average loss: 0.9892, Accuracy: 3180/5000 (64%)
[epoch 14] loss: 0.4124217
Test set: Average loss: 0.9923, Accuracy: 3188/5000 (64%)
[epoch 15] loss: 0.3804695
Test set: Average loss: 0.9828, Accuracy: 3190/5000 (64%)
[epoch 16] loss: 0.3541334
Test set: Average loss: 0.9816, Accuracy: 3192/5000 (64%)
[epoch 17] loss: 0.3251794
Test set: Average loss: 0.9779, Accuracy: 3199/5000 (64%)
[epoch 18] loss: 0.2999621
Test set: Average loss: 0.9809, Accuracy: 3193/5000 (64%)
[epoch 19] loss: 0.2797618
Test set: Average loss: 0.9743, Accuracy: 3201/5000 (64%)
[epoch 20] loss: 0.2576370
Test set: Average loss: 0.9746, Accuracy: 3200/5000 (64%)
[epoch 21] loss: 0.2358259
Test set: Average loss: 0.9701, Accuracy: 3229/5000 (65%)
[epoch 22] loss: 0.2169951
Test set: Average loss: 0.9679, Accuracy: 3206/5000 (64%)
[epoch 23] loss: 0.1989663
Test set: Average loss: 0.9692, Accuracy: 3220/5000 (64%)
[epoch 24] loss: 0.1826885
Test set: Average loss: 0.9758, Accuracy: 3219/5000 (64%)
[epoch 25] loss: 0.1687932
Test set: Average loss: 0.9743, Accuracy: 3212/5000 (64%)
Validation:
Test set: Average loss: 0.9701, Accuracy: 3229/5000 (65%)
Test
Test set: Average loss: 0.9749, Accuracy: 3206/5000 (64%)
Test set: Average loss: 0.2177, Accuracy: 2481/2500 (99%)
## seed: 13
Validation accuracy before training:
Test set: Average loss: 1.6474, Accuracy: 1105/5000 (22%)
[epoch 1] loss: 1.3173745
Test set: Average loss: 1.2078, Accuracy: 2858/5000 (57%)
[epoch 2] loss: 1.0397872
Test set: Average loss: 1.1291, Accuracy: 3028/5000 (61%)
[epoch 3] loss: 0.9098027
Test set: Average loss: 1.0884, Accuracy: 3100/5000 (62%)
[epoch 4] loss: 0.8169117
Test set: Average loss: 1.0603, Accuracy: 3137/5000 (63%)
[epoch 5] loss: 0.7531924
Test set: Average loss: 1.0373, Accuracy: 3159/5000 (63%)
[epoch 6] loss: 0.6906462
Test set: Average loss: 1.0179, Accuracy: 3201/5000 (64%)
[epoch 7] loss: 0.6274134
Test set: Average loss: 1.0041, Accuracy: 3212/5000 (64%)
[epoch 8] loss: 0.5758909
Test set: Average loss: 0.9908, Accuracy: 3220/5000 (64%)
[epoch 9] loss: 0.5251417
Test set: Average loss: 0.9782, Accuracy: 3243/5000 (65%)
[epoch 10] loss: 0.4805894
Test set: Average loss: 0.9695, Accuracy: 3253/5000 (65%)
[epoch 11] loss: 0.4402887
Test set: Average loss: 0.9589, Accuracy: 3254/5000 (65%)
[epoch 12] loss: 0.4027627
Test set: Average loss: 0.9512, Accuracy: 3276/5000 (66%)
[epoch 13] loss: 0.3727262
Test set: Average loss: 0.9410, Accuracy: 3298/5000 (66%)
[epoch 14] loss: 0.3373022
Test set: Average loss: 0.9349, Accuracy: 3301/5000 (66%)
[epoch 15] loss: 0.3099889
Test set: Average loss: 0.9339, Accuracy: 3283/5000 (66%)
[epoch 16] loss: 0.2812897
Test set: Average loss: 0.9280, Accuracy: 3302/5000 (66%)
[epoch 17] loss: 0.2569956
Test set: Average loss: 0.9264, Accuracy: 3295/5000 (66%)
[epoch 18] loss: 0.2365585
Test set: Average loss: 0.9281, Accuracy: 3285/5000 (66%)
[epoch 19] loss: 0.2177329
Test set: Average loss: 0.9233, Accuracy: 3303/5000 (66%)
[epoch 20] loss: 0.1986240
Test set: Average loss: 0.9195, Accuracy: 3304/5000 (66%)
[epoch 21] loss: 0.1834650
Test set: Average loss: 0.9239, Accuracy: 3300/5000 (66%)
[epoch 22] loss: 0.1681286
Test set: Average loss: 0.9199, Accuracy: 3305/5000 (66%)
[epoch 23] loss: 0.1548201
Test set: Average loss: 0.9201, Accuracy: 3310/5000 (66%)
[epoch 24] loss: 0.1417287
Test set: Average loss: 0.9186, Accuracy: 3328/5000 (67%)
[epoch 25] loss: 0.1311707
Test set: Average loss: 0.9234, Accuracy: 3310/5000 (66%)
Validation:
Test set: Average loss: 0.9186, Accuracy: 3328/5000 (67%)
Test
Test set: Average loss: 0.9379, Accuracy: 3261/5000 (65%)
Test set: Average loss: 0.1321, Accuracy: 2499/2500 (100%)
5000
## seed: 11
Validation accuracy before training:
Test set: Average loss: 1.5907, Accuracy: 965/5000 (19%)
[epoch 1] loss: 1.1076215
Test set: Average loss: 1.0902, Accuracy: 3085/5000 (62%)
[epoch 2] loss: 0.8531924
Test set: Average loss: 1.0315, Accuracy: 3228/5000 (65%)
[epoch 3] loss: 0.7273436
Test set: Average loss: 0.9907, Accuracy: 3290/5000 (66%)
[epoch 4] loss: 0.6305663
Test set: Average loss: 0.9617, Accuracy: 3318/5000 (66%)
[epoch 5] loss: 0.5511113
Test set: Average loss: 0.9422, Accuracy: 3338/5000 (67%)
[epoch 6] loss: 0.4823847
Test set: Average loss: 0.9224, Accuracy: 3360/5000 (67%)
[epoch 7] loss: 0.4222381
Test set: Average loss: 0.9107, Accuracy: 3354/5000 (67%)
[epoch 8] loss: 0.3699486
Test set: Average loss: 0.8950, Accuracy: 3386/5000 (68%)
[epoch 9] loss: 0.3241846
Test set: Average loss: 0.8909, Accuracy: 3384/5000 (68%)
[epoch 10] loss: 0.2836454
Test set: Average loss: 0.8919, Accuracy: 3372/5000 (67%)
[epoch 11] loss: 0.2470327
Test set: Average loss: 0.8771, Accuracy: 3421/5000 (68%)
[epoch 12] loss: 0.2155262
Test set: Average loss: 0.8768, Accuracy: 3398/5000 (68%)
[epoch 13] loss: 0.1873612
Test set: Average loss: 0.8770, Accuracy: 3402/5000 (68%)
[epoch 14] loss: 0.1635159
Test set: Average loss: 0.8724, Accuracy: 3414/5000 (68%)
[epoch 15] loss: 0.1411260
Test set: Average loss: 0.8769, Accuracy: 3417/5000 (68%)
[epoch 16] loss: 0.1229546
Test set: Average loss: 0.8798, Accuracy: 3441/5000 (69%)
[epoch 17] loss: 0.1074583
Test set: Average loss: 0.8804, Accuracy: 3440/5000 (69%)
[epoch 18] loss: 0.0935545
Test set: Average loss: 0.8827, Accuracy: 3437/5000 (69%)
[epoch 19] loss: 0.0826270
Test set: Average loss: 0.8849, Accuracy: 3423/5000 (68%)
[epoch 20] loss: 0.0723278
Test set: Average loss: 0.8903, Accuracy: 3439/5000 (69%)
[epoch 21] loss: 0.0643822
Test set: Average loss: 0.8999, Accuracy: 3436/5000 (69%)
[epoch 22] loss: 0.0570682
Test set: Average loss: 0.9080, Accuracy: 3416/5000 (68%)
[epoch 23] loss: 0.0506741
Test set: Average loss: 0.9084, Accuracy: 3433/5000 (69%)
[epoch 24] loss: 0.0452680
Test set: Average loss: 0.9175, Accuracy: 3433/5000 (69%)
[epoch 25] loss: 0.0405024
Test set: Average loss: 0.9283, Accuracy: 3430/5000 (69%)
Validation:
Test set: Average loss: 0.8798, Accuracy: 3441/5000 (69%)
Test
Test set: Average loss: 0.8809, Accuracy: 3398/5000 (68%)
Test set: Average loss: 0.1114, Accuracy: 4996/5000 (100%)
## seed: 12
Validation accuracy before training:
Test set: Average loss: 1.6238, Accuracy: 1530/5000 (31%)
[epoch 1] loss: 1.0795719
Test set: Average loss: 1.0807, Accuracy: 3099/5000 (62%)
[epoch 2] loss: 0.8398789
Test set: Average loss: 1.0250, Accuracy: 3219/5000 (64%)
[epoch 3] loss: 0.7183729
Test set: Average loss: 0.9892, Accuracy: 3271/5000 (65%)
[epoch 4] loss: 0.6201962
Test set: Average loss: 0.9590, Accuracy: 3349/5000 (67%)
[epoch 5] loss: 0.5340236
Test set: Average loss: 0.9381, Accuracy: 3358/5000 (67%)
[epoch 6] loss: 0.4594185
Test set: Average loss: 0.9215, Accuracy: 3396/5000 (68%)
[epoch 7] loss: 0.3950734
Test set: Average loss: 0.9058, Accuracy: 3399/5000 (68%)
[epoch 8] loss: 0.3382996
Test set: Average loss: 0.9005, Accuracy: 3400/5000 (68%)
[epoch 9] loss: 0.2898693
Test set: Average loss: 0.8889, Accuracy: 3453/5000 (69%)
[epoch 10] loss: 0.2486017
Test set: Average loss: 0.8815, Accuracy: 3460/5000 (69%)
[epoch 11] loss: 0.2139444
Test set: Average loss: 0.8783, Accuracy: 3444/5000 (69%)
[epoch 12] loss: 0.1833987
Test set: Average loss: 0.8802, Accuracy: 3442/5000 (69%)
[epoch 13] loss: 0.1580574
Test set: Average loss: 0.8763, Accuracy: 3460/5000 (69%)
[epoch 14] loss: 0.1362884
Test set: Average loss: 0.8736, Accuracy: 3434/5000 (69%)
[epoch 15] loss: 0.1183992
Test set: Average loss: 0.8764, Accuracy: 3463/5000 (69%)
[epoch 16] loss: 0.1026667
Test set: Average loss: 0.8760, Accuracy: 3473/5000 (69%)
[epoch 17] loss: 0.0896498
Test set: Average loss: 0.8844, Accuracy: 3454/5000 (69%)
[epoch 18] loss: 0.0786640
Test set: Average loss: 0.8810, Accuracy: 3469/5000 (69%)
[epoch 19] loss: 0.0691438
Test set: Average loss: 0.8828, Accuracy: 3474/5000 (69%)
[epoch 20] loss: 0.0611882
Test set: Average loss: 0.8881, Accuracy: 3459/5000 (69%)
[epoch 21] loss: 0.0540921
Test set: Average loss: 0.8921, Accuracy: 3481/5000 (70%)
[epoch 22] loss: 0.0480223
Test set: Average loss: 0.8974, Accuracy: 3469/5000 (69%)
[epoch 23] loss: 0.0427960
Test set: Average loss: 0.9042, Accuracy: 3458/5000 (69%)
[epoch 24] loss: 0.0380664
Test set: Average loss: 0.9108, Accuracy: 3451/5000 (69%)
[epoch 25] loss: 0.0341012
Test set: Average loss: 0.9152, Accuracy: 3477/5000 (70%)
Validation:
Test set: Average loss: 0.8921, Accuracy: 3481/5000 (70%)
Test
Test set: Average loss: 0.9271, Accuracy: 3402/5000 (68%)
Test set: Average loss: 0.0492, Accuracy: 4999/5000 (100%)
## seed: 13
Validation accuracy before training:
Test set: Average loss: 1.7570, Accuracy: 618/5000 (12%)
[epoch 1] loss: 1.1943477
Test set: Average loss: 1.0951, Accuracy: 3051/5000 (61%)
[epoch 2] loss: 0.9138821
Test set: Average loss: 1.0374, Accuracy: 3147/5000 (63%)
[epoch 3] loss: 0.7898115
Test set: Average loss: 1.0070, Accuracy: 3241/5000 (65%)
[epoch 4] loss: 0.6911774
Test set: Average loss: 0.9753, Accuracy: 3267/5000 (65%)
[epoch 5] loss: 0.6078103
Test set: Average loss: 0.9559, Accuracy: 3304/5000 (66%)
[epoch 6] loss: 0.5369315
Test set: Average loss: 0.9510, Accuracy: 3248/5000 (65%)
[epoch 7] loss: 0.4753154
Test set: Average loss: 0.9237, Accuracy: 3333/5000 (67%)
[epoch 8] loss: 0.4134075
Test set: Average loss: 0.9155, Accuracy: 3345/5000 (67%)
[epoch 9] loss: 0.3614820
Test set: Average loss: 0.9077, Accuracy: 3339/5000 (67%)
[epoch 10] loss: 0.3150537
Test set: Average loss: 0.8961, Accuracy: 3335/5000 (67%)
[epoch 11] loss: 0.2739244
Test set: Average loss: 0.8929, Accuracy: 3357/5000 (67%)
[epoch 12] loss: 0.2376008
Test set: Average loss: 0.8899, Accuracy: 3351/5000 (67%)
[epoch 13] loss: 0.2047071
Test set: Average loss: 0.8936, Accuracy: 3358/5000 (67%)
[epoch 14] loss: 0.1764810
Test set: Average loss: 0.8834, Accuracy: 3371/5000 (67%)
[epoch 15] loss: 0.1517252
Test set: Average loss: 0.8876, Accuracy: 3353/5000 (67%)
[epoch 16] loss: 0.1311720
Test set: Average loss: 0.8939, Accuracy: 3344/5000 (67%)
[epoch 17] loss: 0.1139605
Test set: Average loss: 0.8931, Accuracy: 3369/5000 (67%)
[epoch 18] loss: 0.0982622
Test set: Average loss: 0.8958, Accuracy: 3373/5000 (67%)
[epoch 19] loss: 0.0853658
Test set: Average loss: 0.9070, Accuracy: 3361/5000 (67%)
[epoch 20] loss: 0.0746519
Test set: Average loss: 0.9015, Accuracy: 3367/5000 (67%)
[epoch 21] loss: 0.0653648
Test set: Average loss: 0.9070, Accuracy: 3359/5000 (67%)
[epoch 22] loss: 0.0575277
Test set: Average loss: 0.9120, Accuracy: 3376/5000 (68%)
[epoch 23] loss: 0.0506230
Test set: Average loss: 0.9163, Accuracy: 3377/5000 (68%)
[epoch 24] loss: 0.0448113
Test set: Average loss: 0.9201, Accuracy: 3364/5000 (67%)
[epoch 25] loss: 0.0397332
Test set: Average loss: 0.9349, Accuracy: 3363/5000 (67%)
Validation:
Test set: Average loss: 0.9163, Accuracy: 3377/5000 (68%)
Test
Test set: Average loss: 0.9253, Accuracy: 3409/5000 (68%)
Test set: Average loss: 0.0456, Accuracy: 5000/5000 (100%)
10000
## seed: 11
Validation accuracy before training:
Test set: Average loss: 1.7071, Accuracy: 605/5000 (12%)
[epoch 1] loss: 1.0900539
Test set: Average loss: 1.0453, Accuracy: 3150/5000 (63%)
[epoch 2] loss: 0.8138555
Test set: Average loss: 0.9646, Accuracy: 3333/5000 (67%)
[epoch 3] loss: 0.6496809
Test set: Average loss: 0.9120, Accuracy: 3423/5000 (68%)
[epoch 4] loss: 0.5136997
Test set: Average loss: 0.8809, Accuracy: 3466/5000 (69%)
[epoch 5] loss: 0.3986374
Test set: Average loss: 0.8569, Accuracy: 3493/5000 (70%)
[epoch 6] loss: 0.3064625
Test set: Average loss: 0.8410, Accuracy: 3523/5000 (70%)
[epoch 7] loss: 0.2345710
Test set: Average loss: 0.8407, Accuracy: 3493/5000 (70%)
[epoch 8] loss: 0.1787667
Test set: Average loss: 0.8417, Accuracy: 3493/5000 (70%)
[epoch 9] loss: 0.1373108
Test set: Average loss: 0.8321, Accuracy: 3517/5000 (70%)
[epoch 10] loss: 0.1063171
Test set: Average loss: 0.8362, Accuracy: 3521/5000 (70%)
[epoch 11] loss: 0.0835490
Test set: Average loss: 0.8427, Accuracy: 3509/5000 (70%)
[epoch 12] loss: 0.0698595
Test set: Average loss: 0.8684, Accuracy: 3496/5000 (70%)
[epoch 13] loss: 0.0529330
Test set: Average loss: 0.8637, Accuracy: 3532/5000 (71%)
[epoch 14] loss: 0.0420189
Test set: Average loss: 0.8796, Accuracy: 3518/5000 (70%)
[epoch 15] loss: 0.0345618
Test set: Average loss: 0.8893, Accuracy: 3511/5000 (70%)
[epoch 16] loss: 0.0272859
Test set: Average loss: 0.8993, Accuracy: 3542/5000 (71%)
[epoch 17] loss: 0.0226211
Test set: Average loss: 0.9188, Accuracy: 3533/5000 (71%)
[epoch 18] loss: 0.0186533
Test set: Average loss: 0.9186, Accuracy: 3547/5000 (71%)
[epoch 19] loss: 0.0154450
Test set: Average loss: 0.9355, Accuracy: 3530/5000 (71%)
[epoch 20] loss: 0.0129804
Test set: Average loss: 0.9479, Accuracy: 3542/5000 (71%)
[epoch 21] loss: 0.0109242
Test set: Average loss: 0.9637, Accuracy: 3554/5000 (71%)
[epoch 22] loss: 0.0091945
Test set: Average loss: 0.9832, Accuracy: 3533/5000 (71%)
[epoch 23] loss: 0.0077417
Test set: Average loss: 0.9906, Accuracy: 3543/5000 (71%)
[epoch 24] loss: 0.0065899
Test set: Average loss: 1.0032, Accuracy: 3561/5000 (71%)
[epoch 25] loss: 0.0055805
Test set: Average loss: 1.0170, Accuracy: 3547/5000 (71%)
Validation:
Test set: Average loss: 1.0032, Accuracy: 3561/5000 (71%)
Test
Test set: Average loss: 1.0239, Accuracy: 3511/5000 (70%)
Test set: Average loss: 0.0058, Accuracy: 10000/10000 (100%)
## seed: 12
Validation accuracy before training:
Test set: Average loss: 1.6302, Accuracy: 800/5000 (16%)
[epoch 1] loss: 0.9827685
Test set: Average loss: 1.0070, Accuracy: 3260/5000 (65%)
[epoch 2] loss: 0.7228905
Test set: Average loss: 0.9438, Accuracy: 3375/5000 (68%)
[epoch 3] loss: 0.5750688
Test set: Average loss: 0.9026, Accuracy: 3421/5000 (68%)
[epoch 4] loss: 0.4560160
Test set: Average loss: 0.8742, Accuracy: 3490/5000 (70%)
[epoch 5] loss: 0.3585407
Test set: Average loss: 0.8594, Accuracy: 3474/5000 (69%)
[epoch 6] loss: 0.2813567
Test set: Average loss: 0.8524, Accuracy: 3482/5000 (70%)
[epoch 7] loss: 0.2173404
Test set: Average loss: 0.8490, Accuracy: 3496/5000 (70%)
[epoch 8] loss: 0.1680778
Test set: Average loss: 0.8476, Accuracy: 3491/5000 (70%)
[epoch 9] loss: 0.1300846
Test set: Average loss: 0.8484, Accuracy: 3500/5000 (70%)
[epoch 10] loss: 0.1013933
Test set: Average loss: 0.8635, Accuracy: 3493/5000 (70%)
[epoch 11] loss: 0.0803169
Test set: Average loss: 0.8778, Accuracy: 3484/5000 (70%)
[epoch 12] loss: 0.0648695
Test set: Average loss: 0.8774, Accuracy: 3511/5000 (70%)
[epoch 13] loss: 0.0506716
Test set: Average loss: 0.8893, Accuracy: 3505/5000 (70%)
[epoch 14] loss: 0.0408281
Test set: Average loss: 0.8958, Accuracy: 3505/5000 (70%)
[epoch 15] loss: 0.0332475
Test set: Average loss: 0.9097, Accuracy: 3503/5000 (70%)
[epoch 16] loss: 0.0271942
Test set: Average loss: 0.9206, Accuracy: 3511/5000 (70%)
[epoch 17] loss: 0.0225251
Test set: Average loss: 0.9418, Accuracy: 3496/5000 (70%)
[epoch 18] loss: 0.0188145
Test set: Average loss: 0.9502, Accuracy: 3524/5000 (70%)
[epoch 19] loss: 0.0155638
Test set: Average loss: 0.9507, Accuracy: 3514/5000 (70%)
[epoch 20] loss: 0.0130115
Test set: Average loss: 0.9704, Accuracy: 3509/5000 (70%)
[epoch 21] loss: 0.0108951
Test set: Average loss: 0.9785, Accuracy: 3522/5000 (70%)
[epoch 22] loss: 0.0091767
Test set: Average loss: 0.9963, Accuracy: 3510/5000 (70%)
[epoch 23] loss: 0.0077445
Test set: Average loss: 1.0081, Accuracy: 3511/5000 (70%)
[epoch 24] loss: 0.0065491
Test set: Average loss: 1.0230, Accuracy: 3509/5000 (70%)
[epoch 25] loss: 0.0055412
Test set: Average loss: 1.0420, Accuracy: 3509/5000 (70%)
Validation:
Test set: Average loss: 0.9502, Accuracy: 3524/5000 (70%)
Test
Test set: Average loss: 0.9720, Accuracy: 3451/5000 (69%)
Test set: Average loss: 0.0168, Accuracy: 10000/10000 (100%)
## seed: 13
Validation accuracy before training:
Test set: Average loss: 1.6196, Accuracy: 677/5000 (14%)
[epoch 1] loss: 0.9637552
Test set: Average loss: 1.0075, Accuracy: 3305/5000 (66%)
[epoch 2] loss: 0.6967664
Test set: Average loss: 0.9393, Accuracy: 3392/5000 (68%)
[epoch 3] loss: 0.5404031
Test set: Average loss: 0.8960, Accuracy: 3461/5000 (69%)
[epoch 4] loss: 0.4175276
Test set: Average loss: 0.8680, Accuracy: 3488/5000 (70%)
[epoch 5] loss: 0.3206277
Test set: Average loss: 0.8456, Accuracy: 3511/5000 (70%)
[epoch 6] loss: 0.2442114
Test set: Average loss: 0.8403, Accuracy: 3497/5000 (70%)
[epoch 7] loss: 0.1852922
Test set: Average loss: 0.8464, Accuracy: 3482/5000 (70%)
[epoch 8] loss: 0.1418382
Test set: Average loss: 0.8414, Accuracy: 3483/5000 (70%)
[epoch 9] loss: 0.1089995
Test set: Average loss: 0.8534, Accuracy: 3483/5000 (70%)
[epoch 10] loss: 0.0854069
Test set: Average loss: 0.8495, Accuracy: 3506/5000 (70%)
[epoch 11] loss: 0.0672862
Test set: Average loss: 0.8604, Accuracy: 3499/5000 (70%)
[epoch 12] loss: 0.0536330
Test set: Average loss: 0.8674, Accuracy: 3510/5000 (70%)
[epoch 13] loss: 0.0430161
Test set: Average loss: 0.8821, Accuracy: 3495/5000 (70%)
[epoch 14] loss: 0.0348035
Test set: Average loss: 0.9002, Accuracy: 3496/5000 (70%)
[epoch 15] loss: 0.0284338
Test set: Average loss: 0.9043, Accuracy: 3522/5000 (70%)
[epoch 16] loss: 0.0230849
Test set: Average loss: 0.9206, Accuracy: 3498/5000 (70%)
[epoch 17] loss: 0.0190177
Test set: Average loss: 0.9266, Accuracy: 3528/5000 (71%)
[epoch 18] loss: 0.0156844
Test set: Average loss: 0.9422, Accuracy: 3488/5000 (70%)
[epoch 19] loss: 0.0466472
Epoch 18: reducing learning rate of group 0 to 5.0000e-06.
Test set: Average loss: 1.0719, Accuracy: 3293/5000 (66%)
[epoch 20] loss: 0.0455948
Epoch 19: reducing learning rate of group 0 to 5.0000e-07.
Test set: Average loss: 0.9715, Accuracy: 3429/5000 (69%)
[epoch 21] loss: 0.0272671
Epoch 20: reducing learning rate of group 0 to 5.0000e-08.
Test set: Average loss: 0.9715, Accuracy: 3427/5000 (69%)
[epoch 22] loss: 0.0267340
Epoch 21: reducing learning rate of group 0 to 5.0000e-09.
Test set: Average loss: 0.9715, Accuracy: 3428/5000 (69%)
[epoch 23] loss: 0.0266639
Epoch 22: reducing learning rate of group 0 to 5.0000e-10.
Test set: Average loss: 0.9715, Accuracy: 3428/5000 (69%)
[epoch 24] loss: 0.0266480
Epoch 23: reducing learning rate of group 0 to 5.0000e-11.
Test set: Average loss: 0.9715, Accuracy: 3428/5000 (69%)
[epoch 25] loss: 0.0266447
Epoch 24: reducing learning rate of group 0 to 5.0000e-12.
Test set: Average loss: 0.9715, Accuracy: 3428/5000 (69%)
Validation:
Test set: Average loss: 0.9266, Accuracy: 3528/5000 (71%)
Test
Test set: Average loss: 0.9504, Accuracy: 3509/5000 (70%)
Test set: Average loss: 0.0166, Accuracy: 10000/10000 (100%)
15000
## seed: 11
Validation accuracy before training:
Test set: Average loss: 1.7656, Accuracy: 446/5000 (9%)
[epoch 1] loss: 1.0966325
Test set: Average loss: 1.0424, Accuracy: 3209/5000 (64%)
[epoch 2] loss: 0.7892489
Test set: Average loss: 0.9477, Accuracy: 3380/5000 (68%)
[epoch 3] loss: 0.5908194
Test set: Average loss: 0.8863, Accuracy: 3458/5000 (69%)
[epoch 4] loss: 0.4332559
Test set: Average loss: 0.8514, Accuracy: 3473/5000 (69%)
[epoch 5] loss: 0.3110187
Test set: Average loss: 0.8351, Accuracy: 3509/5000 (70%)
[epoch 6] loss: 0.2207824
Test set: Average loss: 0.8328, Accuracy: 3501/5000 (70%)
[epoch 7] loss: 0.1613485
Test set: Average loss: 0.8366, Accuracy: 3492/5000 (70%)
[epoch 8] loss: 0.1157253
Test set: Average loss: 0.8389, Accuracy: 3531/5000 (71%)
[epoch 9] loss: 0.0828319
Test set: Average loss: 0.8648, Accuracy: 3518/5000 (70%)
[epoch 10] loss: 0.0615287
Test set: Average loss: 0.8733, Accuracy: 3507/5000 (70%)
[epoch 11] loss: 0.0464193
Test set: Average loss: 0.8842, Accuracy: 3527/5000 (71%)
[epoch 12] loss: 0.0347280
Test set: Average loss: 0.9371, Accuracy: 3479/5000 (70%)
[epoch 13] loss: 0.0667939
Epoch 12: reducing learning rate of group 0 to 5.0000e-06.
Test set: Average loss: 0.9370, Accuracy: 3480/5000 (70%)
[epoch 14] loss: 0.0263258
Test set: Average loss: 0.9255, Accuracy: 3516/5000 (70%)
[epoch 15] loss: 0.0234443
Test set: Average loss: 0.9277, Accuracy: 3505/5000 (70%)
[epoch 16] loss: 0.0218308
Test set: Average loss: 0.9293, Accuracy: 3513/5000 (70%)
[epoch 17] loss: 0.0205127
Test set: Average loss: 0.9320, Accuracy: 3510/5000 (70%)
[epoch 18] loss: 0.0192794
Test set: Average loss: 0.9360, Accuracy: 3505/5000 (70%)
[epoch 19] loss: 0.0181507
Test set: Average loss: 0.9389, Accuracy: 3517/5000 (70%)
[epoch 20] loss: 0.0170664
Test set: Average loss: 0.9422, Accuracy: 3504/5000 (70%)
[epoch 21] loss: 0.0160212
Test set: Average loss: 0.9469, Accuracy: 3513/5000 (70%)
[epoch 22] loss: 0.0150258
Test set: Average loss: 0.9520, Accuracy: 3514/5000 (70%)
[epoch 23] loss: 0.0140819
Test set: Average loss: 0.9559, Accuracy: 3521/5000 (70%)
[epoch 24] loss: 0.0131611
Test set: Average loss: 0.9620, Accuracy: 3518/5000 (70%)
[epoch 25] loss: 0.0123041
Test set: Average loss: 0.9668, Accuracy: 3512/5000 (70%)
Validation:
Test set: Average loss: 0.8389, Accuracy: 3531/5000 (71%)
Test
Test set: Average loss: 0.8521, Accuracy: 3491/5000 (70%)
Test set: Average loss: 0.0897, Accuracy: 14984/15000 (100%)
## seed: 12
Validation accuracy before training:
Test set: Average loss: 1.8471, Accuracy: 839/5000 (17%)
[epoch 1] loss: 1.0095506
Test set: Average loss: 0.9866, Accuracy: 3321/5000 (66%)
[epoch 2] loss: 0.7054798
Test set: Average loss: 0.9139, Accuracy: 3421/5000 (68%)
[epoch 3] loss: 0.5269813
Test set: Average loss: 0.8727, Accuracy: 3456/5000 (69%)
[epoch 4] loss: 0.3887617
Test set: Average loss: 0.8434, Accuracy: 3493/5000 (70%)
[epoch 5] loss: 0.2857378
Test set: Average loss: 0.8481, Accuracy: 3479/5000 (70%)
[epoch 6] loss: 0.2122549
Test set: Average loss: 0.8282, Accuracy: 3523/5000 (70%)
[epoch 7] loss: 0.1560656
Test set: Average loss: 0.8311, Accuracy: 3512/5000 (70%)
[epoch 8] loss: 0.1164256
Test set: Average loss: 0.8477, Accuracy: 3532/5000 (71%)
[epoch 9] loss: 0.0866853
Test set: Average loss: 0.8476, Accuracy: 3550/5000 (71%)
[epoch 10] loss: 0.0681269
Test set: Average loss: 0.8714, Accuracy: 3516/5000 (70%)
[epoch 11] loss: 0.0601595
Test set: Average loss: 0.8894, Accuracy: 3529/5000 (71%)
[epoch 12] loss: 0.0366052
Test set: Average loss: 0.9000, Accuracy: 3541/5000 (71%)
[epoch 13] loss: 0.0470862
Epoch 12: reducing learning rate of group 0 to 5.0000e-06.
Test set: Average loss: 0.9857, Accuracy: 3385/5000 (68%)
[epoch 14] loss: 0.0338328
Test set: Average loss: 0.9158, Accuracy: 3558/5000 (71%)
[epoch 15] loss: 0.0264919
Test set: Average loss: 0.9166, Accuracy: 3562/5000 (71%)
[epoch 16] loss: 0.0238001
Test set: Average loss: 0.9187, Accuracy: 3560/5000 (71%)
[epoch 17] loss: 0.0218583
Test set: Average loss: 0.9234, Accuracy: 3562/5000 (71%)
[epoch 18] loss: 0.0202555
Test set: Average loss: 0.9249, Accuracy: 3563/5000 (71%)
[epoch 19] loss: 0.0188683
Test set: Average loss: 0.9283, Accuracy: 3562/5000 (71%)
[epoch 20] loss: 0.0176406
Test set: Average loss: 0.9314, Accuracy: 3566/5000 (71%)
[epoch 21] loss: 0.0165072
Test set: Average loss: 0.9374, Accuracy: 3563/5000 (71%)
[epoch 22] loss: 0.0154470
Test set: Average loss: 0.9431, Accuracy: 3559/5000 (71%)
[epoch 23] loss: 0.0144530
Test set: Average loss: 0.9470, Accuracy: 3558/5000 (71%)
[epoch 24] loss: 0.0135364
Test set: Average loss: 0.9494, Accuracy: 3563/5000 (71%)
[epoch 25] loss: 0.0126636
Test set: Average loss: 0.9541, Accuracy: 3555/5000 (71%)
Validation:
Test set: Average loss: 0.9314, Accuracy: 3566/5000 (71%)
Test
Test set: Average loss: 0.9604, Accuracy: 3509/5000 (70%)
Test set: Average loss: 0.0167, Accuracy: 14999/15000 (100%)
## seed: 13
Validation accuracy before training:
Test set: Average loss: 1.7822, Accuracy: 604/5000 (12%)
[epoch 1] loss: 1.0564803
Test set: Average loss: 1.0232, Accuracy: 3247/5000 (65%)
[epoch 2] loss: 0.7507707
Test set: Average loss: 0.9300, Accuracy: 3432/5000 (69%)
[epoch 3] loss: 0.5569041
Test set: Average loss: 0.8815, Accuracy: 3454/5000 (69%)
[epoch 4] loss: 0.4048558
Test set: Average loss: 0.8467, Accuracy: 3495/5000 (70%)
[epoch 5] loss: 0.2845691
Test set: Average loss: 0.8472, Accuracy: 3489/5000 (70%)
[epoch 6] loss: 0.1994151
Test set: Average loss: 0.8420, Accuracy: 3487/5000 (70%)
[epoch 7] loss: 0.1411438
Test set: Average loss: 0.8294, Accuracy: 3541/5000 (71%)
[epoch 8] loss: 0.1010288
Test set: Average loss: 0.8514, Accuracy: 3533/5000 (71%)
[epoch 9] loss: 0.0719707
Test set: Average loss: 0.8579, Accuracy: 3543/5000 (71%)
[epoch 10] loss: 0.0529492
Test set: Average loss: 0.8726, Accuracy: 3537/5000 (71%)
[epoch 11] loss: 0.0618747
Epoch 10: reducing learning rate of group 0 to 5.0000e-06.
Test set: Average loss: 0.9358, Accuracy: 3440/5000 (69%)
[epoch 12] loss: 0.0372923
Test set: Average loss: 0.8890, Accuracy: 3520/5000 (70%)
[epoch 13] loss: 0.0321008
Test set: Average loss: 0.8884, Accuracy: 3545/5000 (71%)
[epoch 14] loss: 0.0296222
Test set: Average loss: 0.8900, Accuracy: 3549/5000 (71%)
[epoch 15] loss: 0.0276993
Test set: Average loss: 0.8935, Accuracy: 3538/5000 (71%)
[epoch 16] loss: 0.0260062
Test set: Average loss: 0.8947, Accuracy: 3559/5000 (71%)
[epoch 17] loss: 0.0244462
Test set: Average loss: 0.9014, Accuracy: 3546/5000 (71%)
[epoch 18] loss: 0.0229960
Test set: Average loss: 0.9022, Accuracy: 3560/5000 (71%)
[epoch 19] loss: 0.0215913
Test set: Average loss: 0.9063, Accuracy: 3553/5000 (71%)
[epoch 20] loss: 0.0202848
Test set: Average loss: 0.9109, Accuracy: 3549/5000 (71%)
[epoch 21] loss: 0.0190119
Test set: Average loss: 0.9119, Accuracy: 3556/5000 (71%)
[epoch 22] loss: 0.0178101
Test set: Average loss: 0.9180, Accuracy: 3551/5000 (71%)
[epoch 23] loss: 0.0166704
Test set: Average loss: 0.9231, Accuracy: 3555/5000 (71%)
[epoch 24] loss: 0.0155837
Test set: Average loss: 0.9267, Accuracy: 3559/5000 (71%)
[epoch 25] loss: 0.0145709
Test set: Average loss: 0.9334, Accuracy: 3547/5000 (71%)
Validation:
Test set: Average loss: 0.9022, Accuracy: 3560/5000 (71%)
Test
Test set: Average loss: 0.9139, Accuracy: 3526/5000 (71%)
Test set: Average loss: 0.0219, Accuracy: 14999/15000 (100%)
20000
## seed: 11
Validation accuracy before training:
Test set: Average loss: 1.5301, Accuracy: 1394/5000 (28%)
[epoch 1] loss: 0.8674367
Test set: Average loss: 0.9452, Accuracy: 3389/5000 (68%)
[epoch 2] loss: 0.5531202
Test set: Average loss: 0.8632, Accuracy: 3501/5000 (70%)
[epoch 3] loss: 0.3587001
Test set: Average loss: 0.8308, Accuracy: 3551/5000 (71%)
[epoch 4] loss: 0.2273712
Test set: Average loss: 0.8208, Accuracy: 3545/5000 (71%)
[epoch 5] loss: 0.1445701
Test set: Average loss: 0.8209, Accuracy: 3536/5000 (71%)
[epoch 6] loss: 0.0946908
Test set: Average loss: 0.8463, Accuracy: 3542/5000 (71%)
[epoch 7] loss: 0.0674855
Test set: Average loss: 0.9030, Accuracy: 3457/5000 (69%)
[epoch 8] loss: 0.0519989
Test set: Average loss: 0.8793, Accuracy: 3568/5000 (71%)
[epoch 9] loss: 0.0285884
Test set: Average loss: 0.8981, Accuracy: 3562/5000 (71%)
[epoch 10] loss: 0.0192961
Test set: Average loss: 0.9231, Accuracy: 3580/5000 (72%)
[epoch 11] loss: 0.0139839
Test set: Average loss: 0.9528, Accuracy: 3566/5000 (71%)
[epoch 12] loss: 0.0557272
Epoch 11: reducing learning rate of group 0 to 5.0000e-06.
Test set: Average loss: 1.2109, Accuracy: 3259/5000 (65%)
[epoch 13] loss: 0.0324245
Epoch 12: reducing learning rate of group 0 to 5.0000e-07.
Test set: Average loss: 0.9978, Accuracy: 3516/5000 (70%)
[epoch 14] loss: 0.0200027
Epoch 13: reducing learning rate of group 0 to 5.0000e-08.
Test set: Average loss: 0.9976, Accuracy: 3526/5000 (71%)
[epoch 15] loss: 0.0194865
Epoch 14: reducing learning rate of group 0 to 5.0000e-09.
Test set: Average loss: 0.9977, Accuracy: 3526/5000 (71%)
[epoch 16] loss: 0.0194346
Epoch 15: reducing learning rate of group 0 to 5.0000e-10.
Test set: Average loss: 0.9977, Accuracy: 3526/5000 (71%)
[epoch 17] loss: 0.0194293
Epoch 16: reducing learning rate of group 0 to 5.0000e-11.
Test set: Average loss: 0.9977, Accuracy: 3526/5000 (71%)
[epoch 18] loss: 0.0194291
Epoch 17: reducing learning rate of group 0 to 5.0000e-12.
Test set: Average loss: 0.9977, Accuracy: 3526/5000 (71%)
[epoch 19] loss: 0.0194291
Epoch 18: reducing learning rate of group 0 to 5.0000e-13.
Test set: Average loss: 0.9977, Accuracy: 3526/5000 (71%)
[epoch 20] loss: 0.0194291
Epoch 19: reducing learning rate of group 0 to 5.0000e-14.
Test set: Average loss: 0.9977, Accuracy: 3526/5000 (71%)
[epoch 21] loss: 0.0194291
Epoch 20: reducing learning rate of group 0 to 5.0000e-15.
Test set: Average loss: 0.9977, Accuracy: 3526/5000 (71%)
[epoch 22] loss: 0.0194291
Epoch 21: reducing learning rate of group 0 to 5.0000e-16.
Test set: Average loss: 0.9977, Accuracy: 3526/5000 (71%)
[epoch 23] loss: 0.0194291
Epoch 22: reducing learning rate of group 0 to 5.0000e-17.
Test set: Average loss: 0.9977, Accuracy: 3526/5000 (71%)
[epoch 24] loss: 0.0194291
Epoch 23: reducing learning rate of group 0 to 5.0000e-18.
Test set: Average loss: 0.9977, Accuracy: 3526/5000 (71%)
[epoch 25] loss: 0.0194291
Epoch 24: reducing learning rate of group 0 to 5.0000e-19.
Test set: Average loss: 0.9977, Accuracy: 3526/5000 (71%)
Validation:
Test set: Average loss: 0.9231, Accuracy: 3580/5000 (72%)
Test
Test set: Average loss: 0.9490, Accuracy: 3526/5000 (71%)
Test set: Average loss: 0.0150, Accuracy: 20000/20000 (100%)
## seed: 12
Validation accuracy before training:
Test set: Average loss: 1.5934, Accuracy: 1425/5000 (28%)
[epoch 1] loss: 0.8805318
Test set: Average loss: 0.9566, Accuracy: 3427/5000 (69%)
[epoch 2] loss: 0.5509345
Test set: Average loss: 0.8819, Accuracy: 3492/5000 (70%)
[epoch 3] loss: 0.3524828
Test set: Average loss: 0.8457, Accuracy: 3507/5000 (70%)
[epoch 4] loss: 0.2222444
Test set: Average loss: 0.8274, Accuracy: 3544/5000 (71%)
[epoch 5] loss: 0.1416252
Test set: Average loss: 0.8374, Accuracy: 3534/5000 (71%)
[epoch 6] loss: 0.0923905
Test set: Average loss: 0.8620, Accuracy: 3529/5000 (71%)
[epoch 7] loss: 0.0623993
Test set: Average loss: 0.8867, Accuracy: 3533/5000 (71%)
[epoch 8] loss: 0.0451698
Test set: Average loss: 0.8988, Accuracy: 3566/5000 (71%)
[epoch 9] loss: 0.0276757
Test set: Average loss: 0.9361, Accuracy: 3524/5000 (70%)
[epoch 10] loss: 0.0657572
Epoch 9: reducing learning rate of group 0 to 5.0000e-06.
Test set: Average loss: 0.9782, Accuracy: 3473/5000 (69%)
[epoch 11] loss: 0.0233306
Test set: Average loss: 0.9552, Accuracy: 3521/5000 (70%)
[epoch 12] loss: 0.0191152
Test set: Average loss: 0.9550, Accuracy: 3531/5000 (71%)
[epoch 13] loss: 0.0170776
Test set: Average loss: 0.9571, Accuracy: 3539/5000 (71%)
[epoch 14] loss: 0.0154213
Test set: Average loss: 0.9601, Accuracy: 3535/5000 (71%)
[epoch 15] loss: 0.0139959
Test set: Average loss: 0.9631, Accuracy: 3533/5000 (71%)
[epoch 16] loss: 0.0127127
Test set: Average loss: 0.9688, Accuracy: 3530/5000 (71%)
[epoch 17] loss: 0.0115363
Test set: Average loss: 0.9743, Accuracy: 3540/5000 (71%)
[epoch 18] loss: 0.0104819
Test set: Average loss: 0.9783, Accuracy: 3535/5000 (71%)
[epoch 19] loss: 0.0095085
Test set: Average loss: 0.9824, Accuracy: 3551/5000 (71%)
[epoch 20] loss: 0.0086083
Test set: Average loss: 0.9899, Accuracy: 3549/5000 (71%)
[epoch 21] loss: 0.0078034
Test set: Average loss: 0.9982, Accuracy: 3544/5000 (71%)
[epoch 22] loss: 0.0070900
Test set: Average loss: 1.0029, Accuracy: 3554/5000 (71%)
[epoch 23] loss: 0.0064332
Test set: Average loss: 1.0144, Accuracy: 3550/5000 (71%)
[epoch 24] loss: 0.0058302
Test set: Average loss: 1.0224, Accuracy: 3541/5000 (71%)
[epoch 25] loss: 0.0052888
Test set: Average loss: 1.0317, Accuracy: 3558/5000 (71%)
Validation:
Test set: Average loss: 0.8988, Accuracy: 3566/5000 (71%)
Test
Test set: Average loss: 0.9270, Accuracy: 3484/5000 (70%)
Test set: Average loss: 0.0314, Accuracy: 19997/20000 (100%)
## seed: 13
Validation accuracy before training:
Test set: Average loss: 1.5071, Accuracy: 1817/5000 (36%)
[epoch 1] loss: 0.8786670
Test set: Average loss: 0.9398, Accuracy: 3401/5000 (68%)
[epoch 2] loss: 0.5749976
Test set: Average loss: 0.8713, Accuracy: 3467/5000 (69%)
[epoch 3] loss: 0.3881939
Test set: Average loss: 0.8272, Accuracy: 3535/5000 (71%)
[epoch 4] loss: 0.2586716
Test set: Average loss: 0.8278, Accuracy: 3503/5000 (70%)
[epoch 5] loss: 0.1686442
Test set: Average loss: 0.8261, Accuracy: 3524/5000 (70%)
[epoch 6] loss: 0.1096585
Test set: Average loss: 0.8330, Accuracy: 3563/5000 (71%)
[epoch 7] loss: 0.0736721
Test set: Average loss: 0.8630, Accuracy: 3566/5000 (71%)
[epoch 8] loss: 0.0511134
Test set: Average loss: 0.8761, Accuracy: 3561/5000 (71%)
[epoch 9] loss: 0.0454275
Test set: Average loss: 0.9372, Accuracy: 3474/5000 (69%)
[epoch 10] loss: 0.0451010
Test set: Average loss: 0.9352, Accuracy: 3538/5000 (71%)
[epoch 11] loss: 0.0165070
Test set: Average loss: 0.9509, Accuracy: 3546/5000 (71%)
[epoch 12] loss: 0.0116487
Test set: Average loss: 0.9738, Accuracy: 3563/5000 (71%)
[epoch 13] loss: 0.0085578
Test set: Average loss: 0.9992, Accuracy: 3557/5000 (71%)
[epoch 14] loss: 0.0062888
Test set: Average loss: 1.0196, Accuracy: 3588/5000 (72%)
[epoch 15] loss: 0.0046425
Test set: Average loss: 1.0503, Accuracy: 3585/5000 (72%)
[epoch 16] loss: 0.0034230
Test set: Average loss: 1.0722, Accuracy: 3565/5000 (71%)
[epoch 17] loss: 0.0373247
Epoch 16: reducing learning rate of group 0 to 5.0000e-06.
Test set: Average loss: 1.2533, Accuracy: 3245/5000 (65%)
[epoch 18] loss: 0.0526771
Epoch 17: reducing learning rate of group 0 to 5.0000e-07.
Test set: Average loss: 1.0897, Accuracy: 3493/5000 (70%)
[epoch 19] loss: 0.0195727
Epoch 18: reducing learning rate of group 0 to 5.0000e-08.
Test set: Average loss: 1.0915, Accuracy: 3502/5000 (70%)
[epoch 20] loss: 0.0185120
Epoch 19: reducing learning rate of group 0 to 5.0000e-09.
Test set: Average loss: 1.0918, Accuracy: 3502/5000 (70%)
[epoch 21] loss: 0.0184063
Epoch 20: reducing learning rate of group 0 to 5.0000e-10.
Test set: Average loss: 1.0918, Accuracy: 3502/5000 (70%)
[epoch 22] loss: 0.0183955
Epoch 21: reducing learning rate of group 0 to 5.0000e-11.
Test set: Average loss: 1.0918, Accuracy: 3501/5000 (70%)
[epoch 23] loss: 0.0183952
Epoch 22: reducing learning rate of group 0 to 5.0000e-12.
Test set: Average loss: 1.0918, Accuracy: 3501/5000 (70%)
[epoch 24] loss: 0.0183952
Epoch 23: reducing learning rate of group 0 to 5.0000e-13.
Test set: Average loss: 1.0918, Accuracy: 3501/5000 (70%)
[epoch 25] loss: 0.0183952
Epoch 24: reducing learning rate of group 0 to 5.0000e-14.
Test set: Average loss: 1.0918, Accuracy: 3501/5000 (70%)
Validation:
Test set: Average loss: 1.0196, Accuracy: 3588/5000 (72%)
Test
Test set: Average loss: 1.0446, Accuracy: 3516/5000 (70%)
Test set: Average loss: 0.0051, Accuracy: 20000/20000 (100%)
## Pre-Training AnB
Validation accuracy before training:
Test set: Average loss: 1.6238, Accuracy: 934/5000 (19%)
[epoch 1] loss: 1.2438060
Test set: Average loss: 1.2181, Accuracy: 2659/5000 (53%)
[epoch 2] loss: 1.1423233
Test set: Average loss: 1.1705, Accuracy: 2768/5000 (55%)
[epoch 3] loss: 1.0811741
Test set: Average loss: 1.1420, Accuracy: 2825/5000 (56%)
[epoch 4] loss: 1.0239331
Test set: Average loss: 1.1116, Accuracy: 2892/5000 (58%)
[epoch 5] loss: 0.9647601
Test set: Average loss: 1.1025, Accuracy: 2932/5000 (59%)
[epoch 6] loss: 0.9095757
Test set: Average loss: 1.0791, Accuracy: 2963/5000 (59%)
[epoch 7] loss: 0.8502419
Test set: Average loss: 1.0680, Accuracy: 2998/5000 (60%)
[epoch 8] loss: 0.7933390
Test set: Average loss: 1.0866, Accuracy: 2971/5000 (59%)
[epoch 9] loss: 0.7290124
Test set: Average loss: 1.0621, Accuracy: 2972/5000 (59%)
[epoch 10] loss: 0.6678783
Test set: Average loss: 1.0667, Accuracy: 3018/5000 (60%)
[epoch 11] loss: 0.5972909
Test set: Average loss: 1.0829, Accuracy: 2937/5000 (59%)
[epoch 12] loss: 0.5388196
Test set: Average loss: 1.0770, Accuracy: 2986/5000 (60%)
[epoch 13] loss: 0.4714071
Test set: Average loss: 1.0782, Accuracy: 3014/5000 (60%)
[epoch 14] loss: 0.4101104
Test set: Average loss: 1.1089, Accuracy: 2998/5000 (60%)
[epoch 15] loss: 0.3441316
Test set: Average loss: 1.1303, Accuracy: 2958/5000 (59%)
[epoch 16] loss: 0.2945001
Test set: Average loss: 1.1615, Accuracy: 2950/5000 (59%)
[epoch 17] loss: 0.2448341
Test set: Average loss: 1.2330, Accuracy: 2890/5000 (58%)
[epoch 18] loss: 0.1995546
Test set: Average loss: 1.2093, Accuracy: 2940/5000 (59%)
[epoch 19] loss: 0.1561362
Test set: Average loss: 1.2711, Accuracy: 2910/5000 (58%)
[epoch 20] loss: 0.1329547
Test set: Average loss: 1.2853, Accuracy: 2948/5000 (59%)
[epoch 21] loss: 0.1057411
Test set: Average loss: 1.3079, Accuracy: 2973/5000 (59%)
[epoch 22] loss: 0.0865001
Test set: Average loss: 1.3947, Accuracy: 2896/5000 (58%)
[epoch 23] loss: 0.0863307
Test set: Average loss: 1.4544, Accuracy: 2860/5000 (57%)
[epoch 24] loss: 0.0663306
Test set: Average loss: 1.4305, Accuracy: 2910/5000 (58%)
[epoch 25] loss: 0.0601047
Test set: Average loss: 1.4792, Accuracy: 2958/5000 (59%)
Validation:
Test set: Average loss: 1.0667, Accuracy: 3018/5000 (60%)
Test set: Average loss: 1.0351, Accuracy: 3050/5000 (61%)
25
## seed: 11
Validation accuracy before training:
Test set: Average loss: 1.6658, Accuracy: 1107/5000 (22%)
[epoch 1] loss: 1.7066405
Test set: Average loss: 1.6506, Accuracy: 1150/5000 (23%)
[epoch 2] loss: 1.5438596
Test set: Average loss: 1.6378, Accuracy: 1214/5000 (24%)
[epoch 3] loss: 1.4007229
Test set: Average loss: 1.6267, Accuracy: 1247/5000 (25%)
[epoch 4] loss: 1.2784414
Test set: Average loss: 1.6166, Accuracy: 1288/5000 (26%)
[epoch 5] loss: 1.1734649
Test set: Average loss: 1.6073, Accuracy: 1311/5000 (26%)
[epoch 6] loss: 1.0826305
Test set: Average loss: 1.5986, Accuracy: 1365/5000 (27%)
[epoch 7] loss: 1.0038451
Test set: Average loss: 1.5907, Accuracy: 1414/5000 (28%)
[epoch 8] loss: 0.9354892
Test set: Average loss: 1.5834, Accuracy: 1434/5000 (29%)
[epoch 9] loss: 0.8763722
Test set: Average loss: 1.5769, Accuracy: 1457/5000 (29%)
[epoch 10] loss: 0.8254928
Test set: Average loss: 1.5711, Accuracy: 1498/5000 (30%)
[epoch 11] loss: 0.7817565
Test set: Average loss: 1.5658, Accuracy: 1524/5000 (30%)
[epoch 12] loss: 0.7439421
Test set: Average loss: 1.5609, Accuracy: 1552/5000 (31%)
[epoch 13] loss: 0.7107672
Test set: Average loss: 1.5564, Accuracy: 1569/5000 (31%)
[epoch 14] loss: 0.6810188
Test set: Average loss: 1.5520, Accuracy: 1593/5000 (32%)
[epoch 15] loss: 0.6536817
Test set: Average loss: 1.5478, Accuracy: 1606/5000 (32%)
[epoch 16] loss: 0.6279610
Test set: Average loss: 1.5436, Accuracy: 1618/5000 (32%)
[epoch 17] loss: 0.6033336
Test set: Average loss: 1.5395, Accuracy: 1647/5000 (33%)
[epoch 18] loss: 0.5796949
Test set: Average loss: 1.5353, Accuracy: 1664/5000 (33%)
[epoch 19] loss: 0.5573442
Test set: Average loss: 1.5312, Accuracy: 1685/5000 (34%)
[epoch 20] loss: 0.5366262
Test set: Average loss: 1.5271, Accuracy: 1710/5000 (34%)
[epoch 21] loss: 0.5176232
Test set: Average loss: 1.5230, Accuracy: 1720/5000 (34%)
[epoch 22] loss: 0.5002306
Test set: Average loss: 1.5189, Accuracy: 1738/5000 (35%)
[epoch 23] loss: 0.4843322
Test set: Average loss: 1.5149, Accuracy: 1739/5000 (35%)
[epoch 24] loss: 0.4698121
Test set: Average loss: 1.5109, Accuracy: 1757/5000 (35%)
[epoch 25] loss: 0.4565242
Test set: Average loss: 1.5070, Accuracy: 1771/5000 (35%)
Validation:
Test set: Average loss: 1.5070, Accuracy: 1771/5000 (35%)
Test
Test set: Average loss: 1.5140, Accuracy: 1772/5000 (35%)
Test set: Average loss: 0.4443, Accuracy: 25/25 (100%)
## seed: 12
Validation accuracy before training:
Test set: Average loss: 1.6696, Accuracy: 982/5000 (20%)
[epoch 1] loss: 1.6962296
Test set: Average loss: 1.6331, Accuracy: 1142/5000 (23%)
[epoch 2] loss: 1.5122099
Test set: Average loss: 1.6019, Accuracy: 1302/5000 (26%)
[epoch 3] loss: 1.3567231
Test set: Average loss: 1.5768, Accuracy: 1433/5000 (29%)
[epoch 4] loss: 1.2320644
Test set: Average loss: 1.5568, Accuracy: 1518/5000 (30%)
[epoch 5] loss: 1.1284882
Test set: Average loss: 1.5407, Accuracy: 1591/5000 (32%)
[epoch 6] loss: 1.0375960
Test set: Average loss: 1.5276, Accuracy: 1647/5000 (33%)
[epoch 7] loss: 0.9562307
Test set: Average loss: 1.5166, Accuracy: 1697/5000 (34%)
[epoch 8] loss: 0.8839146
Test set: Average loss: 1.5073, Accuracy: 1727/5000 (35%)
[epoch 9] loss: 0.8201079
Test set: Average loss: 1.4992, Accuracy: 1765/5000 (35%)
[epoch 10] loss: 0.7636624
Test set: Average loss: 1.4923, Accuracy: 1772/5000 (35%)
[epoch 11] loss: 0.7135060
Test set: Average loss: 1.4864, Accuracy: 1796/5000 (36%)
[epoch 12] loss: 0.6688190
Test set: Average loss: 1.4813, Accuracy: 1817/5000 (36%)
[epoch 13] loss: 0.6290494
Test set: Average loss: 1.4770, Accuracy: 1835/5000 (37%)
[epoch 14] loss: 0.5940260
Test set: Average loss: 1.4734, Accuracy: 1856/5000 (37%)
[epoch 15] loss: 0.5636628
Test set: Average loss: 1.4704, Accuracy: 1858/5000 (37%)
[epoch 16] loss: 0.5375320
Test set: Average loss: 1.4679, Accuracy: 1881/5000 (38%)
[epoch 17] loss: 0.5148972
Test set: Average loss: 1.4659, Accuracy: 1887/5000 (38%)
[epoch 18] loss: 0.4950008
Test set: Average loss: 1.4642, Accuracy: 1903/5000 (38%)
[epoch 19] loss: 0.4772229
Test set: Average loss: 1.4629, Accuracy: 1916/5000 (38%)
[epoch 20] loss: 0.4611044
Test set: Average loss: 1.4619, Accuracy: 1935/5000 (39%)
[epoch 21] loss: 0.4463249
Test set: Average loss: 1.4612, Accuracy: 1949/5000 (39%)
[epoch 22] loss: 0.4326407
Test set: Average loss: 1.4607, Accuracy: 1954/5000 (39%)
[epoch 23] loss: 0.4198162
Test set: Average loss: 1.4603, Accuracy: 1960/5000 (39%)
[epoch 24] loss: 0.4076363
Test set: Average loss: 1.4601, Accuracy: 1961/5000 (39%)
[epoch 25] loss: 0.3960014
Test set: Average loss: 1.4600, Accuracy: 1969/5000 (39%)
Validation:
Test set: Average loss: 1.4600, Accuracy: 1969/5000 (39%)
Test
Test set: Average loss: 1.4618, Accuracy: 1936/5000 (39%)
Test set: Average loss: 0.3850, Accuracy: 25/25 (100%)
## seed: 13
Validation accuracy before training:
Test set: Average loss: 1.6813, Accuracy: 950/5000 (19%)
[epoch 1] loss: 1.6479247
Test set: Average loss: 1.6484, Accuracy: 1081/5000 (22%)
[epoch 2] loss: 1.4778214
Test set: Average loss: 1.6216, Accuracy: 1222/5000 (24%)
[epoch 3] loss: 1.3339952
Test set: Average loss: 1.5997, Accuracy: 1342/5000 (27%)
[epoch 4] loss: 1.2122155
Test set: Average loss: 1.5815, Accuracy: 1419/5000 (28%)
[epoch 5] loss: 1.1073014
Test set: Average loss: 1.5661, Accuracy: 1472/5000 (29%)
[epoch 6] loss: 1.0160426
Test set: Average loss: 1.5528, Accuracy: 1526/5000 (31%)
[epoch 7] loss: 0.9370733
Test set: Average loss: 1.5412, Accuracy: 1593/5000 (32%)
[epoch 8] loss: 0.8694179
Test set: Average loss: 1.5310, Accuracy: 1628/5000 (33%)
[epoch 9] loss: 0.8114613
Test set: Average loss: 1.5220, Accuracy: 1674/5000 (33%)
[epoch 10] loss: 0.7616072
Test set: Average loss: 1.5141, Accuracy: 1698/5000 (34%)
[epoch 11] loss: 0.7186565
Test set: Average loss: 1.5070, Accuracy: 1724/5000 (34%)
[epoch 12] loss: 0.6813995
Test set: Average loss: 1.5007, Accuracy: 1754/5000 (35%)
[epoch 13] loss: 0.6486048
Test set: Average loss: 1.4950, Accuracy: 1768/5000 (35%)
[epoch 14] loss: 0.6193607
Test set: Average loss: 1.4899, Accuracy: 1787/5000 (36%)
[epoch 15] loss: 0.5931243
Test set: Average loss: 1.4855, Accuracy: 1805/5000 (36%)
[epoch 16] loss: 0.5695440
Test set: Average loss: 1.4816, Accuracy: 1821/5000 (36%)
[epoch 17] loss: 0.5483032
Test set: Average loss: 1.4783, Accuracy: 1833/5000 (37%)
[epoch 18] loss: 0.5290952
Test set: Average loss: 1.4756, Accuracy: 1845/5000 (37%)
[epoch 19] loss: 0.5116416
Test set: Average loss: 1.4733, Accuracy: 1854/5000 (37%)
[epoch 20] loss: 0.4956880
Test set: Average loss: 1.4714, Accuracy: 1860/5000 (37%)
[epoch 21] loss: 0.4810183
Test set: Average loss: 1.4699, Accuracy: 1867/5000 (37%)
[epoch 22] loss: 0.4675145
Test set: Average loss: 1.4686, Accuracy: 1874/5000 (37%)
[epoch 23] loss: 0.4551570
Test set: Average loss: 1.4676, Accuracy: 1868/5000 (37%)
[epoch 24] loss: 0.4439217
Test set: Average loss: 1.4668, Accuracy: 1874/5000 (37%)
[epoch 25] loss: 0.4337190
Test set: Average loss: 1.4662, Accuracy: 1880/5000 (38%)
Validation:
Test set: Average loss: 1.4662, Accuracy: 1880/5000 (38%)
Test
Test set: Average loss: 1.4776, Accuracy: 1868/5000 (37%)
Test set: Average loss: 0.4244, Accuracy: 25/25 (100%)
50
## seed: 11
Validation accuracy before training:
Test set: Average loss: 1.8133, Accuracy: 481/5000 (10%)
[epoch 1] loss: 1.8439698
Test set: Average loss: 1.7654, Accuracy: 595/5000 (12%)
[epoch 2] loss: 1.6109837
Test set: Average loss: 1.7199, Accuracy: 705/5000 (14%)
[epoch 3] loss: 1.4657766
Test set: Average loss: 1.6775, Accuracy: 874/5000 (17%)
[epoch 4] loss: 1.3436514
Test set: Average loss: 1.6406, Accuracy: 1043/5000 (21%)
[epoch 5] loss: 1.2005022
Test set: Average loss: 1.6090, Accuracy: 1190/5000 (24%)
[epoch 6] loss: 1.1124376
Test set: Average loss: 1.5819, Accuracy: 1346/5000 (27%)
[epoch 7] loss: 1.0348246
Test set: Average loss: 1.5617, Accuracy: 1458/5000 (29%)
[epoch 8] loss: 0.9586884
Test set: Average loss: 1.5459, Accuracy: 1550/5000 (31%)
[epoch 9] loss: 0.8968873
Test set: Average loss: 1.5326, Accuracy: 1613/5000 (32%)
[epoch 10] loss: 0.8454508
Test set: Average loss: 1.5227, Accuracy: 1644/5000 (33%)
[epoch 11] loss: 0.8040206
Test set: Average loss: 1.5148, Accuracy: 1686/5000 (34%)
[epoch 12] loss: 0.7459381
Test set: Average loss: 1.5083, Accuracy: 1722/5000 (34%)
[epoch 13] loss: 0.7260196
Test set: Average loss: 1.5029, Accuracy: 1742/5000 (35%)
[epoch 14] loss: 0.6857101
Test set: Average loss: 1.4979, Accuracy: 1767/5000 (35%)
[epoch 15] loss: 0.6739467
Test set: Average loss: 1.4940, Accuracy: 1783/5000 (36%)
[epoch 16] loss: 0.6458584
Test set: Average loss: 1.4901, Accuracy: 1808/5000 (36%)
[epoch 17] loss: 0.6196249
Test set: Average loss: 1.4870, Accuracy: 1826/5000 (37%)
[epoch 18] loss: 0.6025289
Test set: Average loss: 1.4843, Accuracy: 1835/5000 (37%)
[epoch 19] loss: 0.5719067
Test set: Average loss: 1.4819, Accuracy: 1849/5000 (37%)
[epoch 20] loss: 0.5605633
Test set: Average loss: 1.4800, Accuracy: 1861/5000 (37%)
[epoch 21] loss: 0.5469123
Test set: Average loss: 1.4783, Accuracy: 1873/5000 (37%)
[epoch 22] loss: 0.5185036
Test set: Average loss: 1.4765, Accuracy: 1878/5000 (38%)
[epoch 23] loss: 0.5302148
Epoch 22: reducing learning rate of group 0 to 5.0000e-06.
Test set: Average loss: 1.4750, Accuracy: 1887/5000 (38%)
[epoch 24] loss: 0.5013950
Test set: Average loss: 1.4749, Accuracy: 1889/5000 (38%)
[epoch 25] loss: 0.4951068
Test set: Average loss: 1.4747, Accuracy: 1887/5000 (38%)
Validation:
Test set: Average loss: 1.4749, Accuracy: 1889/5000 (38%)
Test
Test set: Average loss: 1.4878, Accuracy: 1875/5000 (38%)
Test set: Average loss: 0.5100, Accuracy: 50/50 (100%)
## seed: 12
Validation accuracy before training:
Test set: Average loss: 1.6394, Accuracy: 1158/5000 (23%)
[epoch 1] loss: 1.6307309
Test set: Average loss: 1.6148, Accuracy: 1309/5000 (26%)
[epoch 2] loss: 1.4423150
Test set: Average loss: 1.5947, Accuracy: 1431/5000 (29%)
[epoch 3] loss: 1.2798148
Test set: Average loss: 1.5798, Accuracy: 1552/5000 (31%)
[epoch 4] loss: 1.1904512
Test set: Average loss: 1.5697, Accuracy: 1638/5000 (33%)
[epoch 5] loss: 1.1156543
Test set: Average loss: 1.5621, Accuracy: 1717/5000 (34%)
[epoch 6] loss: 1.0419669
Test set: Average loss: 1.5554, Accuracy: 1779/5000 (36%)
[epoch 7] loss: 0.9711588
Test set: Average loss: 1.5498, Accuracy: 1806/5000 (36%)
[epoch 8] loss: 0.8933621
Test set: Average loss: 1.5441, Accuracy: 1834/5000 (37%)
[epoch 9] loss: 0.8549252
Test set: Average loss: 1.5389, Accuracy: 1840/5000 (37%)
[epoch 10] loss: 0.8200678
Test set: Average loss: 1.5340, Accuracy: 1867/5000 (37%)
[epoch 11] loss: 0.7902447
Test set: Average loss: 1.5291, Accuracy: 1876/5000 (38%)
[epoch 12] loss: 0.7363498
Test set: Average loss: 1.5241, Accuracy: 1891/5000 (38%)
[epoch 13] loss: 0.7062238
Test set: Average loss: 1.5193, Accuracy: 1906/5000 (38%)
[epoch 14] loss: 0.6872100
Test set: Average loss: 1.5149, Accuracy: 1925/5000 (38%)
[epoch 15] loss: 0.6449167
Test set: Average loss: 1.5110, Accuracy: 1937/5000 (39%)
[epoch 16] loss: 0.6349136
Test set: Average loss: 1.5079, Accuracy: 1956/5000 (39%)
[epoch 17] loss: 0.6316037
Test set: Average loss: 1.5050, Accuracy: 1972/5000 (39%)
[epoch 18] loss: 0.5946155
Test set: Average loss: 1.5019, Accuracy: 1983/5000 (40%)
[epoch 19] loss: 0.5983149
Epoch 18: reducing learning rate of group 0 to 5.0000e-06.
Test set: Average loss: 1.4991, Accuracy: 2002/5000 (40%)
[epoch 20] loss: 0.5843603
Test set: Average loss: 1.4988, Accuracy: 2003/5000 (40%)
[epoch 21] loss: 0.5679054
Test set: Average loss: 1.4985, Accuracy: 2003/5000 (40%)
[epoch 22] loss: 0.5711204
Epoch 21: reducing learning rate of group 0 to 5.0000e-07.
Test set: Average loss: 1.4982, Accuracy: 2004/5000 (40%)
[epoch 23] loss: 0.5843814
Epoch 22: reducing learning rate of group 0 to 5.0000e-08.
Test set: Average loss: 1.4982, Accuracy: 2004/5000 (40%)
[epoch 24] loss: 0.5527320
Test set: Average loss: 1.4982, Accuracy: 2004/5000 (40%)
[epoch 25] loss: 0.5601953
Epoch 24: reducing learning rate of group 0 to 5.0000e-09.
Test set: Average loss: 1.4982, Accuracy: 2004/5000 (40%)
Validation:
Test set: Average loss: 1.4982, Accuracy: 2004/5000 (40%)
Test
Test set: Average loss: 1.5034, Accuracy: 1995/5000 (40%)
Test set: Average loss: 0.5691, Accuracy: 49/50 (98%)
## seed: 13
Validation accuracy before training:
Test set: Average loss: 1.6465, Accuracy: 1135/5000 (23%)
[epoch 1] loss: 1.6337427
Test set: Average loss: 1.5909, Accuracy: 1365/5000 (27%)
[epoch 2] loss: 1.4499480
Test set: Average loss: 1.5509, Accuracy: 1547/5000 (31%)
[epoch 3] loss: 1.2901614
Test set: Average loss: 1.5202, Accuracy: 1675/5000 (34%)
[epoch 4] loss: 1.1756577
Test set: Average loss: 1.4968, Accuracy: 1774/5000 (35%)
[epoch 5] loss: 1.0789068
Test set: Average loss: 1.4780, Accuracy: 1848/5000 (37%)
[epoch 6] loss: 0.9831196
Test set: Average loss: 1.4622, Accuracy: 1907/5000 (38%)
[epoch 7] loss: 0.9346841
Test set: Average loss: 1.4490, Accuracy: 1940/5000 (39%)
[epoch 8] loss: 0.8647051
Test set: Average loss: 1.4387, Accuracy: 1969/5000 (39%)
[epoch 9] loss: 0.8137963
Test set: Average loss: 1.4299, Accuracy: 2011/5000 (40%)
[epoch 10] loss: 0.7499317
Test set: Average loss: 1.4223, Accuracy: 2034/5000 (41%)
[epoch 11] loss: 0.7111920
Test set: Average loss: 1.4158, Accuracy: 2049/5000 (41%)
[epoch 12] loss: 0.7103601
Test set: Average loss: 1.4105, Accuracy: 2063/5000 (41%)
[epoch 13] loss: 0.6687676
Test set: Average loss: 1.4059, Accuracy: 2081/5000 (42%)
[epoch 14] loss: 0.6499355
Test set: Average loss: 1.4019, Accuracy: 2103/5000 (42%)
[epoch 15] loss: 0.6460523
Test set: Average loss: 1.3981, Accuracy: 2118/5000 (42%)
[epoch 16] loss: 0.5777432
Test set: Average loss: 1.3947, Accuracy: 2126/5000 (43%)
[epoch 17] loss: 0.5758756
Test set: Average loss: 1.3917, Accuracy: 2147/5000 (43%)
[epoch 18] loss: 0.5769132
Epoch 17: reducing learning rate of group 0 to 5.0000e-06.
Test set: Average loss: 1.3890, Accuracy: 2159/5000 (43%)
[epoch 19] loss: 0.5400734
Test set: Average loss: 1.3887, Accuracy: 2160/5000 (43%)
[epoch 20] loss: 0.5223580
Test set: Average loss: 1.3885, Accuracy: 2160/5000 (43%)
[epoch 21] loss: 0.5466018
Epoch 20: reducing learning rate of group 0 to 5.0000e-07.
Test set: Average loss: 1.3883, Accuracy: 2162/5000 (43%)
[epoch 22] loss: 0.5257459
Epoch 21: reducing learning rate of group 0 to 5.0000e-08.
Test set: Average loss: 1.3883, Accuracy: 2163/5000 (43%)
[epoch 23] loss: 0.5431827
Epoch 22: reducing learning rate of group 0 to 5.0000e-09.
Test set: Average loss: 1.3883, Accuracy: 2163/5000 (43%)
[epoch 24] loss: 0.5464813
Epoch 23: reducing learning rate of group 0 to 5.0000e-10.
Test set: Average loss: 1.3883, Accuracy: 2163/5000 (43%)
[epoch 25] loss: 0.5454586
Epoch 24: reducing learning rate of group 0 to 5.0000e-11.
Test set: Average loss: 1.3883, Accuracy: 2163/5000 (43%)
Validation:
Test set: Average loss: 1.3883, Accuracy: 2163/5000 (43%)
Test
Test set: Average loss: 1.4028, Accuracy: 2140/5000 (43%)
Test set: Average loss: 0.5390, Accuracy: 49/50 (98%)
100
## seed: 11
Validation accuracy before training:
Test set: Average loss: 1.6401, Accuracy: 944/5000 (19%)
[epoch 1] loss: 1.5491829
Test set: Average loss: 1.5473, Accuracy: 1203/5000 (24%)
[epoch 2] loss: 1.3779366
Test set: Average loss: 1.4989, Accuracy: 1472/5000 (29%)
[epoch 3] loss: 1.1340939
Test set: Average loss: 1.4731, Accuracy: 1578/5000 (32%)
[epoch 4] loss: 1.0525934
Test set: Average loss: 1.4564, Accuracy: 1611/5000 (32%)
[epoch 5] loss: 1.0183701
Test set: Average loss: 1.4439, Accuracy: 1642/5000 (33%)
[epoch 6] loss: 0.8634888
Test set: Average loss: 1.4319, Accuracy: 1682/5000 (34%)
[epoch 7] loss: 0.8791583
Epoch 6: reducing learning rate of group 0 to 5.0000e-06.
Test set: Average loss: 1.4230, Accuracy: 1717/5000 (34%)
[epoch 8] loss: 0.8968891
Epoch 7: reducing learning rate of group 0 to 5.0000e-07.
Test set: Average loss: 1.4222, Accuracy: 1723/5000 (34%)
[epoch 9] loss: 0.8019012
Test set: Average loss: 1.4221, Accuracy: 1726/5000 (35%)
[epoch 10] loss: 0.8683567
Epoch 9: reducing learning rate of group 0 to 5.0000e-08.
Test set: Average loss: 1.4220, Accuracy: 1730/5000 (35%)
[epoch 11] loss: 0.8572328
Epoch 10: reducing learning rate of group 0 to 5.0000e-09.
Test set: Average loss: 1.4220, Accuracy: 1730/5000 (35%)
[epoch 12] loss: 0.8323349
Epoch 11: reducing learning rate of group 0 to 5.0000e-10.
Test set: Average loss: 1.4220, Accuracy: 1730/5000 (35%)
[epoch 13] loss: 0.8395660
Epoch 12: reducing learning rate of group 0 to 5.0000e-11.
Test set: Average loss: 1.4220, Accuracy: 1730/5000 (35%)
[epoch 14] loss: 0.8393609
Epoch 13: reducing learning rate of group 0 to 5.0000e-12.
Test set: Average loss: 1.4220, Accuracy: 1730/5000 (35%)
[epoch 15] loss: 0.8092786
Epoch 14: reducing learning rate of group 0 to 5.0000e-13.
Test set: Average loss: 1.4220, Accuracy: 1730/5000 (35%)
[epoch 16] loss: 0.8623682
Epoch 15: reducing learning rate of group 0 to 5.0000e-14.
Test set: Average loss: 1.4220, Accuracy: 1730/5000 (35%)
[epoch 17] loss: 0.8824748
Epoch 16: reducing learning rate of group 0 to 5.0000e-15.
Test set: Average loss: 1.4220, Accuracy: 1730/5000 (35%)
[epoch 18] loss: 0.8637108
Epoch 17: reducing learning rate of group 0 to 5.0000e-16.
Test set: Average loss: 1.4220, Accuracy: 1730/5000 (35%)
[epoch 19] loss: 0.8590993
Epoch 18: reducing learning rate of group 0 to 5.0000e-17.
Test set: Average loss: 1.4220, Accuracy: 1730/5000 (35%)
[epoch 20] loss: 0.8192881
Epoch 19: reducing learning rate of group 0 to 5.0000e-18.
Test set: Average loss: 1.4220, Accuracy: 1730/5000 (35%)
[epoch 21] loss: 0.7802383
Test set: Average loss: 1.4220, Accuracy: 1730/5000 (35%)
[epoch 22] loss: 0.8379343
Epoch 21: reducing learning rate of group 0 to 5.0000e-19.
Test set: Average loss: 1.4220, Accuracy: 1730/5000 (35%)
[epoch 23] loss: 0.8859710
Epoch 22: reducing learning rate of group 0 to 5.0000e-20.
Test set: Average loss: 1.4220, Accuracy: 1730/5000 (35%)
[epoch 24] loss: 0.8232704
Epoch 23: reducing learning rate of group 0 to 5.0000e-21.
Test set: Average loss: 1.4220, Accuracy: 1730/5000 (35%)
[epoch 25] loss: 0.8612315
Epoch 24: reducing learning rate of group 0 to 5.0000e-22.
Test set: Average loss: 1.4220, Accuracy: 1730/5000 (35%)
Validation:
Test set: Average loss: 1.4220, Accuracy: 1730/5000 (35%)
Test
Test set: Average loss: 1.4293, Accuracy: 1749/5000 (35%)
Test set: Average loss: 0.8322, Accuracy: 81/100 (81%)
## seed: 12
Validation accuracy before training:
Test set: Average loss: 1.7509, Accuracy: 569/5000 (11%)
[epoch 1] loss: 1.7153506
Test set: Average loss: 1.6512, Accuracy: 931/5000 (19%)
[epoch 2] loss: 1.4596268
Test set: Average loss: 1.6008, Accuracy: 1236/5000 (25%)
[epoch 3] loss: 1.2201074
Test set: Average loss: 1.5572, Accuracy: 1440/5000 (29%)
[epoch 4] loss: 1.1369187
Test set: Average loss: 1.5214, Accuracy: 1616/5000 (32%)
[epoch 5] loss: 1.0912482
Test set: Average loss: 1.4928, Accuracy: 1757/5000 (35%)
[epoch 6] loss: 0.9905397
Test set: Average loss: 1.4696, Accuracy: 1862/5000 (37%)
[epoch 7] loss: 0.9211862
Test set: Average loss: 1.4548, Accuracy: 1929/5000 (39%)
[epoch 8] loss: 0.9222462
Epoch 7: reducing learning rate of group 0 to 5.0000e-06.
Test set: Average loss: 1.4459, Accuracy: 1976/5000 (40%)
[epoch 9] loss: 0.9096025
Test set: Average loss: 1.4453, Accuracy: 1975/5000 (40%)
[epoch 10] loss: 0.8737943
Test set: Average loss: 1.4446, Accuracy: 1972/5000 (39%)
[epoch 11] loss: 0.8057777
Test set: Average loss: 1.4441, Accuracy: 1980/5000 (40%)
[epoch 12] loss: 0.9466485
Epoch 11: reducing learning rate of group 0 to 5.0000e-07.
Test set: Average loss: 1.4438, Accuracy: 1983/5000 (40%)
[epoch 13] loss: 0.9307094
Epoch 12: reducing learning rate of group 0 to 5.0000e-08.
Test set: Average loss: 1.4438, Accuracy: 1984/5000 (40%)
[epoch 14] loss: 0.9135724
Epoch 13: reducing learning rate of group 0 to 5.0000e-09.
Test set: Average loss: 1.4437, Accuracy: 1984/5000 (40%)
[epoch 15] loss: 0.8837233
Epoch 14: reducing learning rate of group 0 to 5.0000e-10.
Test set: Average loss: 1.4437, Accuracy: 1984/5000 (40%)
[epoch 16] loss: 0.8757482
Epoch 15: reducing learning rate of group 0 to 5.0000e-11.
Test set: Average loss: 1.4437, Accuracy: 1984/5000 (40%)
[epoch 17] loss: 0.8337527
Epoch 16: reducing learning rate of group 0 to 5.0000e-12.
Test set: Average loss: 1.4437, Accuracy: 1984/5000 (40%)
[epoch 18] loss: 0.8366393
Epoch 17: reducing learning rate of group 0 to 5.0000e-13.
Test set: Average loss: 1.4437, Accuracy: 1984/5000 (40%)
[epoch 19] loss: 0.8445196
Epoch 18: reducing learning rate of group 0 to 5.0000e-14.
Test set: Average loss: 1.4437, Accuracy: 1984/5000 (40%)
[epoch 20] loss: 0.8984096
Epoch 19: reducing learning rate of group 0 to 5.0000e-15.
Test set: Average loss: 1.4437, Accuracy: 1984/5000 (40%)
[epoch 21] loss: 0.9158173
Epoch 20: reducing learning rate of group 0 to 5.0000e-16.
Test set: Average loss: 1.4437, Accuracy: 1984/5000 (40%)
[epoch 22] loss: 0.8158489
Epoch 21: reducing learning rate of group 0 to 5.0000e-17.
Test set: Average loss: 1.4437, Accuracy: 1984/5000 (40%)
[epoch 23] loss: 0.8055473
Test set: Average loss: 1.4437, Accuracy: 1984/5000 (40%)
[epoch 24] loss: 0.8460626
Epoch 23: reducing learning rate of group 0 to 5.0000e-18.
Test set: Average loss: 1.4437, Accuracy: 1984/5000 (40%)
[epoch 25] loss: 0.8779206
Epoch 24: reducing learning rate of group 0 to 5.0000e-19.
Test set: Average loss: 1.4437, Accuracy: 1984/5000 (40%)
Validation:
Test set: Average loss: 1.4437, Accuracy: 1984/5000 (40%)
Test
Test set: Average loss: 1.4479, Accuracy: 1955/5000 (39%)
Test set: Average loss: 0.8622, Accuracy: 88/100 (88%)
## seed: 13
Validation accuracy before training:
Test set: Average loss: 1.6046, Accuracy: 1446/5000 (29%)
[epoch 1] loss: 1.5344875
Test set: Average loss: 1.5016, Accuracy: 1824/5000 (36%)
[epoch 2] loss: 1.3042230
Test set: Average loss: 1.4525, Accuracy: 1970/5000 (39%)
[epoch 3] loss: 1.2726118
Test set: Average loss: 1.4208, Accuracy: 2090/5000 (42%)
[epoch 4] loss: 1.0830025
Test set: Average loss: 1.3998, Accuracy: 2162/5000 (43%)
[epoch 5] loss: 0.9778109
Test set: Average loss: 1.3833, Accuracy: 2216/5000 (44%)
[epoch 6] loss: 0.9191561
Test set: Average loss: 1.3699, Accuracy: 2267/5000 (45%)
[epoch 7] loss: 0.8726643
Test set: Average loss: 1.3572, Accuracy: 2299/5000 (46%)
[epoch 8] loss: 0.8064249
Test set: Average loss: 1.3479, Accuracy: 2333/5000 (47%)
[epoch 9] loss: 0.7886029
Test set: Average loss: 1.3419, Accuracy: 2351/5000 (47%)
[epoch 10] loss: 0.7555824
Test set: Average loss: 1.3386, Accuracy: 2338/5000 (47%)
[epoch 11] loss: 0.7723931
Epoch 10: reducing learning rate of group 0 to 5.0000e-06.
Test set: Average loss: 1.3363, Accuracy: 2350/5000 (47%)
[epoch 12] loss: 0.7076599
Test set: Average loss: 1.3359, Accuracy: 2350/5000 (47%)
[epoch 13] loss: 0.7454882
Epoch 12: reducing learning rate of group 0 to 5.0000e-07.
Test set: Average loss: 1.3355, Accuracy: 2353/5000 (47%)
[epoch 14] loss: 0.7481299
Epoch 13: reducing learning rate of group 0 to 5.0000e-08.
Test set: Average loss: 1.3354, Accuracy: 2353/5000 (47%)
[epoch 15] loss: 0.6987112
Test set: Average loss: 1.3354, Accuracy: 2353/5000 (47%)
[epoch 16] loss: 0.6829659
Test set: Average loss: 1.3354, Accuracy: 2353/5000 (47%)
[epoch 17] loss: 0.7323359
Epoch 16: reducing learning rate of group 0 to 5.0000e-09.
Test set: Average loss: 1.3354, Accuracy: 2353/5000 (47%)
[epoch 18] loss: 0.6726622
Test set: Average loss: 1.3354, Accuracy: 2353/5000 (47%)
[epoch 19] loss: 0.6569997
Test set: Average loss: 1.3354, Accuracy: 2353/5000 (47%)
[epoch 20] loss: 0.7065215
Epoch 19: reducing learning rate of group 0 to 5.0000e-10.
Test set: Average loss: 1.3354, Accuracy: 2353/5000 (47%)
[epoch 21] loss: 0.7147050
Epoch 20: reducing learning rate of group 0 to 5.0000e-11.
Test set: Average loss: 1.3354, Accuracy: 2353/5000 (47%)
[epoch 22] loss: 0.6994330
Epoch 21: reducing learning rate of group 0 to 5.0000e-12.
Test set: Average loss: 1.3354, Accuracy: 2353/5000 (47%)
[epoch 23] loss: 0.6646634
Epoch 22: reducing learning rate of group 0 to 5.0000e-13.
Test set: Average loss: 1.3354, Accuracy: 2353/5000 (47%)
[epoch 24] loss: 0.6788681
Epoch 23: reducing learning rate of group 0 to 5.0000e-14.
Test set: Average loss: 1.3354, Accuracy: 2353/5000 (47%)
[epoch 25] loss: 0.6926391
Epoch 24: reducing learning rate of group 0 to 5.0000e-15.
Test set: Average loss: 1.3354, Accuracy: 2353/5000 (47%)
Validation:
Test set: Average loss: 1.3354, Accuracy: 2353/5000 (47%)
Test
Test set: Average loss: 1.3509, Accuracy: 2380/5000 (48%)
Test set: Average loss: 0.6979, Accuracy: 94/100 (94%)
250
## seed: 11
Validation accuracy before training:
Test set: Average loss: 1.6304, Accuracy: 1004/5000 (20%)
[epoch 1] loss: 1.5765257
Test set: Average loss: 1.4350, Accuracy: 2157/5000 (43%)
[epoch 2] loss: 1.3211512
Test set: Average loss: 1.3409, Accuracy: 2395/5000 (48%)
[epoch 3] loss: 1.1727342
Test set: Average loss: 1.2982, Accuracy: 2476/5000 (50%)
[epoch 4] loss: 1.0693785
Test set: Average loss: 1.2719, Accuracy: 2550/5000 (51%)
[epoch 5] loss: 0.9838786
Test set: Average loss: 1.2546, Accuracy: 2618/5000 (52%)
[epoch 6] loss: 0.9142786
Test set: Average loss: 1.2438, Accuracy: 2685/5000 (54%)
[epoch 7] loss: 0.8583813
Test set: Average loss: 1.2348, Accuracy: 2690/5000 (54%)
[epoch 8] loss: 0.8063032
Test set: Average loss: 1.2284, Accuracy: 2704/5000 (54%)
[epoch 9] loss: 0.7619328
Test set: Average loss: 1.2226, Accuracy: 2729/5000 (55%)
[epoch 10] loss: 0.7236998
Test set: Average loss: 1.2184, Accuracy: 2709/5000 (54%)
[epoch 11] loss: 0.6884048
Test set: Average loss: 1.2149, Accuracy: 2727/5000 (55%)
[epoch 12] loss: 0.6546211
Test set: Average loss: 1.2109, Accuracy: 2727/5000 (55%)
[epoch 13] loss: 0.6251119
Test set: Average loss: 1.2083, Accuracy: 2737/5000 (55%)
[epoch 14] loss: 0.5995105
Test set: Average loss: 1.2052, Accuracy: 2739/5000 (55%)
[epoch 15] loss: 0.5751613
Test set: Average loss: 1.2034, Accuracy: 2725/5000 (54%)
[epoch 16] loss: 0.5490503
Test set: Average loss: 1.2000, Accuracy: 2743/5000 (55%)
[epoch 17] loss: 0.5269035
Test set: Average loss: 1.1988, Accuracy: 2733/5000 (55%)
[epoch 18] loss: 0.5065541
Test set: Average loss: 1.1983, Accuracy: 2734/5000 (55%)
[epoch 19] loss: 0.4858772
Test set: Average loss: 1.1970, Accuracy: 2731/5000 (55%)
[epoch 20] loss: 0.4702430
Test set: Average loss: 1.1957, Accuracy: 2726/5000 (55%)
[epoch 21] loss: 0.4524198
Test set: Average loss: 1.1923, Accuracy: 2726/5000 (55%)
[epoch 22] loss: 0.4388421
Test set: Average loss: 1.1919, Accuracy: 2740/5000 (55%)
[epoch 23] loss: 0.4251876
Test set: Average loss: 1.1920, Accuracy: 2735/5000 (55%)
[epoch 24] loss: 0.4117374
Test set: Average loss: 1.1929, Accuracy: 2727/5000 (55%)
[epoch 25] loss: 0.3992008
Test set: Average loss: 1.1914, Accuracy: 2734/5000 (55%)
Validation:
Test set: Average loss: 1.2000, Accuracy: 2743/5000 (55%)
Test
Test set: Average loss: 1.2139, Accuracy: 2672/5000 (53%)
Test set: Average loss: 0.5327, Accuracy: 242/250 (97%)
## seed: 12
Validation accuracy before training:
Test set: Average loss: 1.6710, Accuracy: 971/5000 (19%)
[epoch 1] loss: 1.6022236
Test set: Average loss: 1.5110, Accuracy: 1821/5000 (36%)
[epoch 2] loss: 1.3747343
Test set: Average loss: 1.4304, Accuracy: 2059/5000 (41%)
[epoch 3] loss: 1.2402501
Test set: Average loss: 1.3780, Accuracy: 2237/5000 (45%)
[epoch 4] loss: 1.1361084
Test set: Average loss: 1.3425, Accuracy: 2354/5000 (47%)
[epoch 5] loss: 1.0566396
Test set: Average loss: 1.3185, Accuracy: 2447/5000 (49%)
[epoch 6] loss: 0.9889661
Test set: Average loss: 1.2998, Accuracy: 2502/5000 (50%)
[epoch 7] loss: 0.9311242
Test set: Average loss: 1.2889, Accuracy: 2536/5000 (51%)
[epoch 8] loss: 0.8774206
Test set: Average loss: 1.2773, Accuracy: 2565/5000 (51%)
[epoch 9] loss: 0.8345784
Test set: Average loss: 1.2684, Accuracy: 2583/5000 (52%)
[epoch 10] loss: 0.7912083
Test set: Average loss: 1.2595, Accuracy: 2608/5000 (52%)
[epoch 11] loss: 0.7520080
Test set: Average loss: 1.2529, Accuracy: 2625/5000 (52%)
[epoch 12] loss: 0.7195944
Test set: Average loss: 1.2455, Accuracy: 2635/5000 (53%)
[epoch 13] loss: 0.6863828
Test set: Average loss: 1.2403, Accuracy: 2643/5000 (53%)
[epoch 14] loss: 0.6554058
Test set: Average loss: 1.2358, Accuracy: 2630/5000 (53%)
[epoch 15] loss: 0.6293791
Test set: Average loss: 1.2304, Accuracy: 2648/5000 (53%)
[epoch 16] loss: 0.6040868
Test set: Average loss: 1.2273, Accuracy: 2639/5000 (53%)
[epoch 17] loss: 0.5804855
Test set: Average loss: 1.2219, Accuracy: 2663/5000 (53%)
[epoch 18] loss: 0.5594855
Test set: Average loss: 1.2192, Accuracy: 2665/5000 (53%)
[epoch 19] loss: 0.5391782
Test set: Average loss: 1.2168, Accuracy: 2652/5000 (53%)
[epoch 20] loss: 0.5186297
Test set: Average loss: 1.2144, Accuracy: 2661/5000 (53%)
[epoch 21] loss: 0.4977683
Test set: Average loss: 1.2104, Accuracy: 2662/5000 (53%)
[epoch 22] loss: 0.4823354
Test set: Average loss: 1.2113, Accuracy: 2648/5000 (53%)
[epoch 23] loss: 0.4655173
Test set: Average loss: 1.2063, Accuracy: 2664/5000 (53%)
[epoch 24] loss: 0.4503093
Test set: Average loss: 1.2022, Accuracy: 2679/5000 (54%)
[epoch 25] loss: 0.4371906
Test set: Average loss: 1.2005, Accuracy: 2677/5000 (54%)
Validation:
Test set: Average loss: 1.2022, Accuracy: 2679/5000 (54%)
Test
Test set: Average loss: 1.1971, Accuracy: 2682/5000 (54%)
Test set: Average loss: 0.4407, Accuracy: 250/250 (100%)
## seed: 13
Validation accuracy before training:
Test set: Average loss: 1.6590, Accuracy: 1241/5000 (25%)
[epoch 1] loss: 1.5854492
Test set: Average loss: 1.4580, Accuracy: 1979/5000 (40%)
[epoch 2] loss: 1.3004204
Test set: Average loss: 1.3702, Accuracy: 2221/5000 (44%)
[epoch 3] loss: 1.1603986
Test set: Average loss: 1.3226, Accuracy: 2366/5000 (47%)
[epoch 4] loss: 1.0471084
Test set: Average loss: 1.3002, Accuracy: 2445/5000 (49%)
[epoch 5] loss: 0.9639523
Test set: Average loss: 1.2851, Accuracy: 2468/5000 (49%)
[epoch 6] loss: 0.8907508
Test set: Average loss: 1.2716, Accuracy: 2528/5000 (51%)
[epoch 7] loss: 0.8356566
Test set: Average loss: 1.2612, Accuracy: 2564/5000 (51%)
[epoch 8] loss: 0.7818357
Test set: Average loss: 1.2523, Accuracy: 2591/5000 (52%)
[epoch 9] loss: 0.7373919
Test set: Average loss: 1.2478, Accuracy: 2600/5000 (52%)
[epoch 10] loss: 0.6985299
Test set: Average loss: 1.2431, Accuracy: 2621/5000 (52%)
[epoch 11] loss: 0.6662797
Test set: Average loss: 1.2387, Accuracy: 2622/5000 (52%)
[epoch 12] loss: 0.6327287
Test set: Average loss: 1.2344, Accuracy: 2625/5000 (52%)
[epoch 13] loss: 0.6044878
Test set: Average loss: 1.2300, Accuracy: 2642/5000 (53%)
[epoch 14] loss: 0.5800802
Test set: Average loss: 1.2262, Accuracy: 2661/5000 (53%)
[epoch 15] loss: 0.5525654
Test set: Average loss: 1.2254, Accuracy: 2642/5000 (53%)
[epoch 16] loss: 0.5319020
Test set: Average loss: 1.2234, Accuracy: 2642/5000 (53%)
[epoch 17] loss: 0.5112735
Test set: Average loss: 1.2201, Accuracy: 2661/5000 (53%)
[epoch 18] loss: 0.4912543
Test set: Average loss: 1.2204, Accuracy: 2668/5000 (53%)
[epoch 19] loss: 0.4717815
Test set: Average loss: 1.2188, Accuracy: 2658/5000 (53%)
[epoch 20] loss: 0.4577131
Test set: Average loss: 1.2160, Accuracy: 2676/5000 (54%)
[epoch 21] loss: 0.4386537
Test set: Average loss: 1.2160, Accuracy: 2683/5000 (54%)
[epoch 22] loss: 0.4242149
Test set: Average loss: 1.2135, Accuracy: 2687/5000 (54%)
[epoch 23] loss: 0.4098239
Test set: Average loss: 1.2134, Accuracy: 2694/5000 (54%)
[epoch 24] loss: 0.3956481
Test set: Average loss: 1.2143, Accuracy: 2688/5000 (54%)
[epoch 25] loss: 0.3874075
Test set: Average loss: 1.2136, Accuracy: 2683/5000 (54%)
Validation:
Test set: Average loss: 1.2134, Accuracy: 2694/5000 (54%)
Test
Test set: Average loss: 1.2317, Accuracy: 2657/5000 (53%)
Test set: Average loss: 0.4002, Accuracy: 246/250 (98%)
500
## seed: 11
Validation accuracy before training:
Test set: Average loss: 1.5336, Accuracy: 1638/5000 (33%)
[epoch 1] loss: 1.4306207
Test set: Average loss: 1.3309, Accuracy: 2290/5000 (46%)
[epoch 2] loss: 1.1962295
Test set: Average loss: 1.2599, Accuracy: 2582/5000 (52%)
[epoch 3] loss: 1.0667138
Test set: Average loss: 1.2304, Accuracy: 2701/5000 (54%)
[epoch 4] loss: 0.9817403
Test set: Average loss: 1.2157, Accuracy: 2727/5000 (55%)
[epoch 5] loss: 0.9156413
Test set: Average loss: 1.1992, Accuracy: 2795/5000 (56%)
[epoch 6] loss: 0.8559067
Test set: Average loss: 1.1924, Accuracy: 2786/5000 (56%)
[epoch 7] loss: 0.8080643
Test set: Average loss: 1.1834, Accuracy: 2803/5000 (56%)
[epoch 8] loss: 0.7624482
Test set: Average loss: 1.1749, Accuracy: 2838/5000 (57%)
[epoch 9] loss: 0.7217650
Test set: Average loss: 1.1711, Accuracy: 2856/5000 (57%)
[epoch 10] loss: 0.6839358
Test set: Average loss: 1.1639, Accuracy: 2859/5000 (57%)
[epoch 11] loss: 0.6509294
Test set: Average loss: 1.1613, Accuracy: 2862/5000 (57%)
[epoch 12] loss: 0.6181985
Test set: Average loss: 1.1550, Accuracy: 2864/5000 (57%)
[epoch 13] loss: 0.5946184
Test set: Average loss: 1.1499, Accuracy: 2880/5000 (58%)
[epoch 14] loss: 0.5633459
Test set: Average loss: 1.1479, Accuracy: 2873/5000 (57%)
[epoch 15] loss: 0.5387204
Test set: Average loss: 1.1480, Accuracy: 2848/5000 (57%)
[epoch 16] loss: 0.5161240
Test set: Average loss: 1.1400, Accuracy: 2882/5000 (58%)
[epoch 17] loss: 0.4915549
Test set: Average loss: 1.1403, Accuracy: 2865/5000 (57%)
[epoch 18] loss: 0.4721982
Test set: Average loss: 1.1368, Accuracy: 2867/5000 (57%)
[epoch 19] loss: 0.4500554
Test set: Average loss: 1.1347, Accuracy: 2867/5000 (57%)
[epoch 20] loss: 0.4292112
Test set: Average loss: 1.1344, Accuracy: 2862/5000 (57%)
[epoch 21] loss: 0.4139045
Test set: Average loss: 1.1307, Accuracy: 2863/5000 (57%)
[epoch 22] loss: 0.3961149
Test set: Average loss: 1.1325, Accuracy: 2858/5000 (57%)
[epoch 23] loss: 0.3781332
Test set: Average loss: 1.1288, Accuracy: 2876/5000 (58%)
[epoch 24] loss: 0.3630473
Test set: Average loss: 1.1289, Accuracy: 2874/5000 (57%)
[epoch 25] loss: 0.3476424
Test set: Average loss: 1.1267, Accuracy: 2880/5000 (58%)
Validation:
Test set: Average loss: 1.1400, Accuracy: 2882/5000 (58%)
Test
Test set: Average loss: 1.1501, Accuracy: 2869/5000 (57%)
Test set: Average loss: 0.4947, Accuracy: 490/500 (98%)
## seed: 12
Validation accuracy before training:
Test set: Average loss: 1.7894, Accuracy: 524/5000 (10%)
[epoch 1] loss: 1.6706573
Test set: Average loss: 1.4774, Accuracy: 1769/5000 (35%)
[epoch 2] loss: 1.3501568
Test set: Average loss: 1.3641, Accuracy: 2243/5000 (45%)
[epoch 3] loss: 1.1977833
Test set: Average loss: 1.3133, Accuracy: 2440/5000 (49%)
[epoch 4] loss: 1.0892501
Test set: Average loss: 1.2831, Accuracy: 2539/5000 (51%)
[epoch 5] loss: 1.0051815
Test set: Average loss: 1.2566, Accuracy: 2630/5000 (53%)
[epoch 6] loss: 0.9361137
Test set: Average loss: 1.2404, Accuracy: 2670/5000 (53%)
[epoch 7] loss: 0.8774238
Test set: Average loss: 1.2235, Accuracy: 2726/5000 (55%)
[epoch 8] loss: 0.8255379
Test set: Average loss: 1.2129, Accuracy: 2722/5000 (54%)
[epoch 9] loss: 0.7822663
Test set: Average loss: 1.2014, Accuracy: 2766/5000 (55%)
[epoch 10] loss: 0.7362916
Test set: Average loss: 1.1969, Accuracy: 2774/5000 (55%)
[epoch 11] loss: 0.6979154
Test set: Average loss: 1.1860, Accuracy: 2804/5000 (56%)
[epoch 12] loss: 0.6654468
Test set: Average loss: 1.1828, Accuracy: 2808/5000 (56%)
[epoch 13] loss: 0.6360052
Test set: Average loss: 1.1783, Accuracy: 2815/5000 (56%)
[epoch 14] loss: 0.6045855
Test set: Average loss: 1.1678, Accuracy: 2848/5000 (57%)
[epoch 15] loss: 0.5784332
Test set: Average loss: 1.1671, Accuracy: 2845/5000 (57%)
[epoch 16] loss: 0.5493891
Test set: Average loss: 1.1661, Accuracy: 2837/5000 (57%)
[epoch 17] loss: 0.5248754
Test set: Average loss: 1.1587, Accuracy: 2854/5000 (57%)
[epoch 18] loss: 0.5070519
Test set: Average loss: 1.1564, Accuracy: 2863/5000 (57%)
[epoch 19] loss: 0.4843255
Test set: Average loss: 1.1558, Accuracy: 2846/5000 (57%)
[epoch 20] loss: 0.4602502
Test set: Average loss: 1.1519, Accuracy: 2863/5000 (57%)
[epoch 21] loss: 0.4426037
Test set: Average loss: 1.1500, Accuracy: 2866/5000 (57%)
[epoch 22] loss: 0.4205536
Test set: Average loss: 1.1458, Accuracy: 2873/5000 (57%)
[epoch 23] loss: 0.4049409
Test set: Average loss: 1.1467, Accuracy: 2873/5000 (57%)
[epoch 24] loss: 0.3884792
Test set: Average loss: 1.1445, Accuracy: 2876/5000 (58%)
[epoch 25] loss: 0.3748163
Test set: Average loss: 1.1418, Accuracy: 2878/5000 (58%)
Validation:
Test set: Average loss: 1.1418, Accuracy: 2878/5000 (58%)
Test
Test set: Average loss: 1.1551, Accuracy: 2772/5000 (55%)
Test set: Average loss: 0.3614, Accuracy: 494/500 (99%)
## seed: 13
Validation accuracy before training:
Test set: Average loss: 1.7660, Accuracy: 458/5000 (9%)
[epoch 1] loss: 1.4992806
Test set: Average loss: 1.3927, Accuracy: 1974/5000 (39%)
[epoch 2] loss: 1.1870602
Test set: Average loss: 1.2959, Accuracy: 2319/5000 (46%)
[epoch 3] loss: 1.0469392
Test set: Average loss: 1.2556, Accuracy: 2414/5000 (48%)
[epoch 4] loss: 0.9534753
Test set: Average loss: 1.2325, Accuracy: 2486/5000 (50%)
[epoch 5] loss: 0.8771719
Test set: Average loss: 1.2145, Accuracy: 2550/5000 (51%)
[epoch 6] loss: 0.8225098
Test set: Average loss: 1.2013, Accuracy: 2592/5000 (52%)
[epoch 7] loss: 0.7685676
Test set: Average loss: 1.1900, Accuracy: 2632/5000 (53%)
[epoch 8] loss: 0.7184022
Test set: Average loss: 1.1803, Accuracy: 2676/5000 (54%)
[epoch 9] loss: 0.6819826
Test set: Average loss: 1.1746, Accuracy: 2679/5000 (54%)
[epoch 10] loss: 0.6401896
Test set: Average loss: 1.1672, Accuracy: 2705/5000 (54%)
[epoch 11] loss: 0.6052796
Test set: Average loss: 1.1610, Accuracy: 2733/5000 (55%)
[epoch 12] loss: 0.5748686
Test set: Average loss: 1.1577, Accuracy: 2738/5000 (55%)
[epoch 13] loss: 0.5432218
Test set: Average loss: 1.1517, Accuracy: 2766/5000 (55%)
[epoch 14] loss: 0.5208593
Test set: Average loss: 1.1481, Accuracy: 2779/5000 (56%)
[epoch 15] loss: 0.4901563
Test set: Average loss: 1.1437, Accuracy: 2790/5000 (56%)
[epoch 16] loss: 0.4706975
Test set: Average loss: 1.1409, Accuracy: 2806/5000 (56%)
[epoch 17] loss: 0.4475552
Test set: Average loss: 1.1396, Accuracy: 2815/5000 (56%)
[epoch 18] loss: 0.4283638
Test set: Average loss: 1.1392, Accuracy: 2790/5000 (56%)
[epoch 19] loss: 0.4106511
Test set: Average loss: 1.1351, Accuracy: 2831/5000 (57%)
[epoch 20] loss: 0.3903773
Test set: Average loss: 1.1336, Accuracy: 2809/5000 (56%)
[epoch 21] loss: 0.3736375
Test set: Average loss: 1.1313, Accuracy: 2834/5000 (57%)
[epoch 22] loss: 0.3584419
Test set: Average loss: 1.1279, Accuracy: 2844/5000 (57%)
[epoch 23] loss: 0.3449574
Test set: Average loss: 1.1294, Accuracy: 2834/5000 (57%)
[epoch 24] loss: 0.3291967
Test set: Average loss: 1.1253, Accuracy: 2842/5000 (57%)
[epoch 25] loss: 0.3180846
Test set: Average loss: 1.1282, Accuracy: 2832/5000 (57%)
Validation:
Test set: Average loss: 1.1279, Accuracy: 2844/5000 (57%)
Test
Test set: Average loss: 1.1392, Accuracy: 2825/5000 (56%)
Test set: Average loss: 0.3470, Accuracy: 493/500 (99%)
750
## seed: 11
Validation accuracy before training:
Test set: Average loss: 1.6665, Accuracy: 1054/5000 (21%)
[epoch 1] loss: 1.4771034
Test set: Average loss: 1.3630, Accuracy: 2386/5000 (48%)
[epoch 2] loss: 1.2217458
Test set: Average loss: 1.2804, Accuracy: 2602/5000 (52%)
[epoch 3] loss: 1.0900696
Test set: Average loss: 1.2468, Accuracy: 2682/5000 (54%)
[epoch 4] loss: 0.9981403
Test set: Average loss: 1.2231, Accuracy: 2725/5000 (54%)
[epoch 5] loss: 0.9239915
Test set: Average loss: 1.2024, Accuracy: 2791/5000 (56%)
[epoch 6] loss: 0.8609079
Test set: Average loss: 1.1911, Accuracy: 2841/5000 (57%)
[epoch 7] loss: 0.8074475
Test set: Average loss: 1.1807, Accuracy: 2845/5000 (57%)
[epoch 8] loss: 0.7604269
Test set: Average loss: 1.1700, Accuracy: 2866/5000 (57%)
[epoch 9] loss: 0.7151239
Test set: Average loss: 1.1667, Accuracy: 2881/5000 (58%)
[epoch 10] loss: 0.6786605
Test set: Average loss: 1.1583, Accuracy: 2873/5000 (57%)
[epoch 11] loss: 0.6411436
Test set: Average loss: 1.1527, Accuracy: 2886/5000 (58%)
[epoch 12] loss: 0.6073830
Test set: Average loss: 1.1415, Accuracy: 2913/5000 (58%)
[epoch 13] loss: 0.5777858
Test set: Average loss: 1.1391, Accuracy: 2910/5000 (58%)
[epoch 14] loss: 0.5491233
Test set: Average loss: 1.1306, Accuracy: 2939/5000 (59%)
[epoch 15] loss: 0.5241938
Test set: Average loss: 1.1303, Accuracy: 2918/5000 (58%)
[epoch 16] loss: 0.4984350
Test set: Average loss: 1.1243, Accuracy: 2927/5000 (59%)
[epoch 17] loss: 0.4739100
Test set: Average loss: 1.1265, Accuracy: 2926/5000 (59%)
[epoch 18] loss: 0.4502800
Test set: Average loss: 1.1187, Accuracy: 2931/5000 (59%)
[epoch 19] loss: 0.4276139
Test set: Average loss: 1.1145, Accuracy: 2950/5000 (59%)
[epoch 20] loss: 0.4072957
Test set: Average loss: 1.1116, Accuracy: 2928/5000 (59%)
[epoch 21] loss: 0.3887845
Test set: Average loss: 1.1096, Accuracy: 2943/5000 (59%)
[epoch 22] loss: 0.3680033
Test set: Average loss: 1.1089, Accuracy: 2953/5000 (59%)
[epoch 23] loss: 0.3525292
Test set: Average loss: 1.1060, Accuracy: 2938/5000 (59%)
[epoch 24] loss: 0.3379727
Test set: Average loss: 1.1059, Accuracy: 2961/5000 (59%)
[epoch 25] loss: 0.3215527
Test set: Average loss: 1.1043, Accuracy: 2936/5000 (59%)
Validation:
Test set: Average loss: 1.1059, Accuracy: 2961/5000 (59%)
Test
Test set: Average loss: 1.1118, Accuracy: 2915/5000 (58%)
Test set: Average loss: 0.3240, Accuracy: 745/750 (99%)
## seed: 12
Validation accuracy before training:
Test set: Average loss: 1.8285, Accuracy: 612/5000 (12%)
[epoch 1] loss: 1.5962631
Test set: Average loss: 1.4334, Accuracy: 1986/5000 (40%)
[epoch 2] loss: 1.3083112
Test set: Average loss: 1.3400, Accuracy: 2309/5000 (46%)
[epoch 3] loss: 1.1734873
Test set: Average loss: 1.2925, Accuracy: 2490/5000 (50%)
[epoch 4] loss: 1.0778640
Test set: Average loss: 1.2605, Accuracy: 2586/5000 (52%)
[epoch 5] loss: 1.0015077
Test set: Average loss: 1.2398, Accuracy: 2641/5000 (53%)
[epoch 6] loss: 0.9413195
Test set: Average loss: 1.2219, Accuracy: 2734/5000 (55%)
[epoch 7] loss: 0.8754874
Test set: Average loss: 1.2089, Accuracy: 2748/5000 (55%)
[epoch 8] loss: 0.8186697
Test set: Average loss: 1.1969, Accuracy: 2790/5000 (56%)
[epoch 9] loss: 0.7661455
Test set: Average loss: 1.1921, Accuracy: 2782/5000 (56%)
[epoch 10] loss: 0.7222998
Test set: Average loss: 1.1772, Accuracy: 2843/5000 (57%)
[epoch 11] loss: 0.6732904
Test set: Average loss: 1.1718, Accuracy: 2855/5000 (57%)
[epoch 12] loss: 0.6365412
Test set: Average loss: 1.1663, Accuracy: 2842/5000 (57%)
[epoch 13] loss: 0.5988382
Test set: Average loss: 1.1611, Accuracy: 2880/5000 (58%)
[epoch 14] loss: 0.5650848
Test set: Average loss: 1.1520, Accuracy: 2895/5000 (58%)
[epoch 15] loss: 0.5333902
Test set: Average loss: 1.1549, Accuracy: 2896/5000 (58%)
[epoch 16] loss: 0.4978142
Test set: Average loss: 1.1497, Accuracy: 2894/5000 (58%)
[epoch 17] loss: 0.4670513
Test set: Average loss: 1.1474, Accuracy: 2906/5000 (58%)
[epoch 18] loss: 0.4473973
Test set: Average loss: 1.1403, Accuracy: 2927/5000 (59%)
[epoch 19] loss: 0.4188350
Test set: Average loss: 1.1415, Accuracy: 2921/5000 (58%)
[epoch 20] loss: 0.3968675
Test set: Average loss: 1.1394, Accuracy: 2931/5000 (59%)
[epoch 21] loss: 0.3726842
Test set: Average loss: 1.1353, Accuracy: 2926/5000 (59%)
[epoch 22] loss: 0.3569049
Test set: Average loss: 1.1362, Accuracy: 2931/5000 (59%)
[epoch 23] loss: 0.3355632
Test set: Average loss: 1.1332, Accuracy: 2926/5000 (59%)
[epoch 24] loss: 0.3206961
Test set: Average loss: 1.1320, Accuracy: 2929/5000 (59%)
[epoch 25] loss: 0.3045399
Test set: Average loss: 1.1356, Accuracy: 2908/5000 (58%)
Validation:
Test set: Average loss: 1.1362, Accuracy: 2931/5000 (59%)
Test
Test set: Average loss: 1.1393, Accuracy: 2858/5000 (57%)
Test set: Average loss: 0.3391, Accuracy: 743/750 (99%)
## seed: 13
Validation accuracy before training:
Test set: Average loss: 1.7843, Accuracy: 459/5000 (9%)
[epoch 1] loss: 1.5146754
Test set: Average loss: 1.3677, Accuracy: 2122/5000 (42%)
[epoch 2] loss: 1.2222429
Test set: Average loss: 1.2905, Accuracy: 2397/5000 (48%)
[epoch 3] loss: 1.1021319
Test set: Average loss: 1.2439, Accuracy: 2583/5000 (52%)
[epoch 4] loss: 1.0213217
Test set: Average loss: 1.2234, Accuracy: 2624/5000 (52%)
[epoch 5] loss: 0.9392898
Test set: Average loss: 1.2039, Accuracy: 2693/5000 (54%)
[epoch 6] loss: 0.8875879
Test set: Average loss: 1.1870, Accuracy: 2734/5000 (55%)
[epoch 7] loss: 0.8278800
Test set: Average loss: 1.1817, Accuracy: 2753/5000 (55%)
[epoch 8] loss: 0.7766457
Test set: Average loss: 1.1684, Accuracy: 2760/5000 (55%)
[epoch 9] loss: 0.7390464
Test set: Average loss: 1.1668, Accuracy: 2764/5000 (55%)
[epoch 10] loss: 0.6940695
Test set: Average loss: 1.1511, Accuracy: 2806/5000 (56%)
[epoch 11] loss: 0.6511721
Test set: Average loss: 1.1462, Accuracy: 2807/5000 (56%)
[epoch 12] loss: 0.6154445
Test set: Average loss: 1.1437, Accuracy: 2828/5000 (57%)
[epoch 13] loss: 0.5872598
Test set: Average loss: 1.1357, Accuracy: 2839/5000 (57%)
[epoch 14] loss: 0.5543315
Test set: Average loss: 1.1318, Accuracy: 2854/5000 (57%)
[epoch 15] loss: 0.5260861
Test set: Average loss: 1.1297, Accuracy: 2862/5000 (57%)
[epoch 16] loss: 0.5001427
Test set: Average loss: 1.1253, Accuracy: 2867/5000 (57%)
[epoch 17] loss: 0.4770834
Test set: Average loss: 1.1238, Accuracy: 2861/5000 (57%)
[epoch 18] loss: 0.4492843
Test set: Average loss: 1.1205, Accuracy: 2878/5000 (58%)
[epoch 19] loss: 0.4254273
Test set: Average loss: 1.1230, Accuracy: 2881/5000 (58%)
[epoch 20] loss: 0.4027889
Test set: Average loss: 1.1217, Accuracy: 2875/5000 (58%)
[epoch 21] loss: 0.3859861
Test set: Average loss: 1.1205, Accuracy: 2872/5000 (57%)
[epoch 22] loss: 0.3651678
Test set: Average loss: 1.1220, Accuracy: 2872/5000 (57%)
[epoch 23] loss: 0.3467653
Test set: Average loss: 1.1178, Accuracy: 2900/5000 (58%)
[epoch 24] loss: 0.3294574
Test set: Average loss: 1.1187, Accuracy: 2880/5000 (58%)
[epoch 25] loss: 0.3119206
Test set: Average loss: 1.1200, Accuracy: 2886/5000 (58%)
Validation:
Test set: Average loss: 1.1178, Accuracy: 2900/5000 (58%)
Test
Test set: Average loss: 1.1412, Accuracy: 2822/5000 (56%)
Test set: Average loss: 0.3318, Accuracy: 740/750 (99%)
1000
## seed: 11
Validation accuracy before training:
Test set: Average loss: 1.7141, Accuracy: 843/5000 (17%)
[epoch 1] loss: 1.4095860
Test set: Average loss: 1.2996, Accuracy: 2374/5000 (47%)
[epoch 2] loss: 1.1625956
Test set: Average loss: 1.2407, Accuracy: 2554/5000 (51%)
[epoch 3] loss: 1.0541664
Test set: Average loss: 1.2133, Accuracy: 2640/5000 (53%)
[epoch 4] loss: 0.9797507
Test set: Average loss: 1.1961, Accuracy: 2693/5000 (54%)
[epoch 5] loss: 0.9101790
Test set: Average loss: 1.1734, Accuracy: 2800/5000 (56%)
[epoch 6] loss: 0.8497458
Test set: Average loss: 1.1582, Accuracy: 2838/5000 (57%)
[epoch 7] loss: 0.7978379
Test set: Average loss: 1.1546, Accuracy: 2844/5000 (57%)
[epoch 8] loss: 0.7642129
Test set: Average loss: 1.1424, Accuracy: 2868/5000 (57%)
[epoch 9] loss: 0.7224236
Test set: Average loss: 1.1352, Accuracy: 2904/5000 (58%)
[epoch 10] loss: 0.6757127
Test set: Average loss: 1.1268, Accuracy: 2915/5000 (58%)
[epoch 11] loss: 0.6467364
Test set: Average loss: 1.1216, Accuracy: 2919/5000 (58%)
[epoch 12] loss: 0.6199986
Test set: Average loss: 1.1167, Accuracy: 2935/5000 (59%)
[epoch 13] loss: 0.5789747
Test set: Average loss: 1.1087, Accuracy: 2958/5000 (59%)
[epoch 14] loss: 0.5565329
Test set: Average loss: 1.1071, Accuracy: 2956/5000 (59%)
[epoch 15] loss: 0.5240630
Test set: Average loss: 1.1032, Accuracy: 2959/5000 (59%)
[epoch 16] loss: 0.4984426
Test set: Average loss: 1.0989, Accuracy: 2964/5000 (59%)
[epoch 17] loss: 0.4676367
Test set: Average loss: 1.0949, Accuracy: 2966/5000 (59%)
[epoch 18] loss: 0.4452505
Test set: Average loss: 1.0895, Accuracy: 2978/5000 (60%)
[epoch 19] loss: 0.4249521
Test set: Average loss: 1.0933, Accuracy: 2977/5000 (60%)
[epoch 20] loss: 0.3996986
Test set: Average loss: 1.0876, Accuracy: 2978/5000 (60%)
[epoch 21] loss: 0.3789064
Test set: Average loss: 1.0872, Accuracy: 2975/5000 (60%)
[epoch 22] loss: 0.3619513
Test set: Average loss: 1.0834, Accuracy: 2981/5000 (60%)
[epoch 23] loss: 0.3434222
Test set: Average loss: 1.0837, Accuracy: 3004/5000 (60%)
[epoch 24] loss: 0.3221332
Test set: Average loss: 1.0815, Accuracy: 2982/5000 (60%)
[epoch 25] loss: 0.3096118
Test set: Average loss: 1.0827, Accuracy: 2996/5000 (60%)
Validation:
Test set: Average loss: 1.0837, Accuracy: 3004/5000 (60%)
Test
Test set: Average loss: 1.0906, Accuracy: 2928/5000 (59%)
Test set: Average loss: 0.3251, Accuracy: 983/1000 (98%)
## seed: 12
Validation accuracy before training:
Test set: Average loss: 1.6254, Accuracy: 1431/5000 (29%)
[epoch 1] loss: 1.4377086
Test set: Average loss: 1.2991, Accuracy: 2480/5000 (50%)
[epoch 2] loss: 1.1944631
Test set: Average loss: 1.2400, Accuracy: 2634/5000 (53%)
[epoch 3] loss: 1.0663681
Test set: Average loss: 1.2017, Accuracy: 2753/5000 (55%)
[epoch 4] loss: 0.9849030
Test set: Average loss: 1.1886, Accuracy: 2815/5000 (56%)
[epoch 5] loss: 0.9134895
Test set: Average loss: 1.1640, Accuracy: 2873/5000 (57%)
[epoch 6] loss: 0.8541929
Test set: Average loss: 1.1568, Accuracy: 2903/5000 (58%)
[epoch 7] loss: 0.7938712
Test set: Average loss: 1.1446, Accuracy: 2915/5000 (58%)
[epoch 8] loss: 0.7501711
Test set: Average loss: 1.1319, Accuracy: 2942/5000 (59%)
[epoch 9] loss: 0.7011013
Test set: Average loss: 1.1329, Accuracy: 2917/5000 (58%)
[epoch 10] loss: 0.6703018
Test set: Average loss: 1.1198, Accuracy: 2980/5000 (60%)
[epoch 11] loss: 0.6195876
Test set: Average loss: 1.1197, Accuracy: 2969/5000 (59%)
[epoch 12] loss: 0.5829637
Test set: Average loss: 1.1083, Accuracy: 2997/5000 (60%)
[epoch 13] loss: 0.5514509
Test set: Average loss: 1.1129, Accuracy: 2973/5000 (59%)
[epoch 14] loss: 0.5241411
Test set: Average loss: 1.1067, Accuracy: 2992/5000 (60%)
[epoch 15] loss: 0.4902680
Test set: Average loss: 1.1029, Accuracy: 2984/5000 (60%)
[epoch 16] loss: 0.4638198
Test set: Average loss: 1.1017, Accuracy: 2972/5000 (59%)
[epoch 17] loss: 0.4366078
Test set: Average loss: 1.1003, Accuracy: 2973/5000 (59%)
[epoch 18] loss: 0.4127027
Test set: Average loss: 1.0991, Accuracy: 2964/5000 (59%)
[epoch 19] loss: 0.3875317
Test set: Average loss: 1.0948, Accuracy: 2997/5000 (60%)
[epoch 20] loss: 0.3691407
Test set: Average loss: 1.0920, Accuracy: 2997/5000 (60%)
[epoch 21] loss: 0.3470209
Test set: Average loss: 1.0939, Accuracy: 2986/5000 (60%)
[epoch 22] loss: 0.3263459
Test set: Average loss: 1.0942, Accuracy: 2992/5000 (60%)
[epoch 23] loss: 0.3055632
Test set: Average loss: 1.0947, Accuracy: 2996/5000 (60%)
[epoch 24] loss: 0.2854781
Test set: Average loss: 1.0921, Accuracy: 2997/5000 (60%)
[epoch 25] loss: 0.2720912
Test set: Average loss: 1.0954, Accuracy: 2988/5000 (60%)
Validation:
Test set: Average loss: 1.0921, Accuracy: 2997/5000 (60%)
Test
Test set: Average loss: 1.1063, Accuracy: 2940/5000 (59%)
Test set: Average loss: 0.2683, Accuracy: 989/1000 (99%)
## seed: 13
Validation accuracy before training:
Test set: Average loss: 1.6658, Accuracy: 976/5000 (20%)
[epoch 1] loss: 1.4634297
Test set: Average loss: 1.3194, Accuracy: 2329/5000 (47%)
[epoch 2] loss: 1.1872546
Test set: Average loss: 1.2551, Accuracy: 2546/5000 (51%)
[epoch 3] loss: 1.0705074
Test set: Average loss: 1.2143, Accuracy: 2722/5000 (54%)
[epoch 4] loss: 0.9741602
Test set: Average loss: 1.1863, Accuracy: 2786/5000 (56%)
[epoch 5] loss: 0.9050023
Test set: Average loss: 1.1663, Accuracy: 2855/5000 (57%)
[epoch 6] loss: 0.8423105
Test set: Average loss: 1.1584, Accuracy: 2846/5000 (57%)
[epoch 7] loss: 0.7896845
Test set: Average loss: 1.1472, Accuracy: 2881/5000 (58%)
[epoch 8] loss: 0.7474448
Test set: Average loss: 1.1336, Accuracy: 2915/5000 (58%)
[epoch 9] loss: 0.6939671
Test set: Average loss: 1.1267, Accuracy: 2927/5000 (59%)
[epoch 10] loss: 0.6489465
Test set: Average loss: 1.1203, Accuracy: 2938/5000 (59%)
[epoch 11] loss: 0.6158733
Test set: Average loss: 1.1152, Accuracy: 2928/5000 (59%)
[epoch 12] loss: 0.5805255
Test set: Average loss: 1.1161, Accuracy: 2935/5000 (59%)
[epoch 13] loss: 0.5482779
Test set: Average loss: 1.1068, Accuracy: 2958/5000 (59%)
[epoch 14] loss: 0.5151957
Test set: Average loss: 1.1009, Accuracy: 2970/5000 (59%)
[epoch 15] loss: 0.4854047
Test set: Average loss: 1.1024, Accuracy: 2951/5000 (59%)
[epoch 16] loss: 0.4525453
Test set: Average loss: 1.1017, Accuracy: 2960/5000 (59%)
[epoch 17] loss: 0.4292444
Test set: Average loss: 1.1008, Accuracy: 2958/5000 (59%)
[epoch 18] loss: 0.4015168
Test set: Average loss: 1.1004, Accuracy: 2942/5000 (59%)
[epoch 19] loss: 0.3800158
Test set: Average loss: 1.0982, Accuracy: 2947/5000 (59%)
[epoch 20] loss: 0.3582962
Test set: Average loss: 1.0945, Accuracy: 2942/5000 (59%)
[epoch 21] loss: 0.3395614
Test set: Average loss: 1.0934, Accuracy: 2950/5000 (59%)
[epoch 22] loss: 0.3190915
Test set: Average loss: 1.0951, Accuracy: 2949/5000 (59%)
[epoch 23] loss: 0.3029173
Test set: Average loss: 1.0967, Accuracy: 2948/5000 (59%)
[epoch 24] loss: 0.2848429
Test set: Average loss: 1.0980, Accuracy: 2939/5000 (59%)
[epoch 25] loss: 0.2698781
Test set: Average loss: 1.1021, Accuracy: 2932/5000 (59%)
Validation:
Test set: Average loss: 1.1009, Accuracy: 2970/5000 (59%)
Test
Test set: Average loss: 1.1217, Accuracy: 2927/5000 (59%)
Test set: Average loss: 0.4819, Accuracy: 964/1000 (96%)
2500
## seed: 11
Validation accuracy before training:
Test set: Average loss: 1.7123, Accuracy: 919/5000 (18%)
[epoch 1] loss: 1.2857315
Test set: Average loss: 1.1805, Accuracy: 2681/5000 (54%)
[epoch 2] loss: 1.0659454
Test set: Average loss: 1.1149, Accuracy: 2922/5000 (58%)
[epoch 3] loss: 0.9586381
Test set: Average loss: 1.0776, Accuracy: 3015/5000 (60%)
[epoch 4] loss: 0.8775596
Test set: Average loss: 1.0657, Accuracy: 3012/5000 (60%)
[epoch 5] loss: 0.8141533
Test set: Average loss: 1.0366, Accuracy: 3055/5000 (61%)
[epoch 6] loss: 0.7557649
Test set: Average loss: 1.0287, Accuracy: 3078/5000 (62%)
[epoch 7] loss: 0.6991119
Test set: Average loss: 1.0127, Accuracy: 3148/5000 (63%)
[epoch 8] loss: 0.6462108
Test set: Average loss: 1.0024, Accuracy: 3188/5000 (64%)
[epoch 9] loss: 0.6033903
Test set: Average loss: 0.9942, Accuracy: 3195/5000 (64%)
[epoch 10] loss: 0.5487729
Test set: Average loss: 0.9845, Accuracy: 3205/5000 (64%)
[epoch 11] loss: 0.5031811
Test set: Average loss: 0.9810, Accuracy: 3172/5000 (63%)
[epoch 12] loss: 0.4649743
Test set: Average loss: 0.9820, Accuracy: 3182/5000 (64%)
[epoch 13] loss: 0.4254150
Test set: Average loss: 0.9735, Accuracy: 3199/5000 (64%)
[epoch 14] loss: 0.3866000
Test set: Average loss: 0.9713, Accuracy: 3177/5000 (64%)
[epoch 15] loss: 0.3509190
Test set: Average loss: 0.9655, Accuracy: 3235/5000 (65%)
[epoch 16] loss: 0.3146969
Test set: Average loss: 0.9710, Accuracy: 3205/5000 (64%)
[epoch 17] loss: 0.2833106
Test set: Average loss: 0.9682, Accuracy: 3228/5000 (65%)
[epoch 18] loss: 0.2561536
Test set: Average loss: 0.9669, Accuracy: 3213/5000 (64%)
[epoch 19] loss: 0.2323330
Test set: Average loss: 0.9676, Accuracy: 3197/5000 (64%)
[epoch 20] loss: 0.2103376
Test set: Average loss: 0.9723, Accuracy: 3194/5000 (64%)
[epoch 21] loss: 0.1912074
Test set: Average loss: 0.9706, Accuracy: 3196/5000 (64%)
[epoch 22] loss: 0.1725486
Test set: Average loss: 0.9709, Accuracy: 3202/5000 (64%)
[epoch 23] loss: 0.1541691
Test set: Average loss: 0.9788, Accuracy: 3209/5000 (64%)
[epoch 24] loss: 0.1397675
Test set: Average loss: 0.9792, Accuracy: 3205/5000 (64%)
[epoch 25] loss: 0.1270369
Test set: Average loss: 0.9767, Accuracy: 3212/5000 (64%)
Validation:
Test set: Average loss: 0.9655, Accuracy: 3235/5000 (65%)
Test
Test set: Average loss: 0.9840, Accuracy: 3148/5000 (63%)
Test set: Average loss: 0.3106, Accuracy: 2446/2500 (98%)
## seed: 12
Validation accuracy before training:
Test set: Average loss: 1.7793, Accuracy: 527/5000 (11%)
[epoch 1] loss: 1.3651109
Test set: Average loss: 1.2395, Accuracy: 2533/5000 (51%)
[epoch 2] loss: 1.1164657
Test set: Average loss: 1.1706, Accuracy: 2771/5000 (55%)
[epoch 3] loss: 1.0200287
Test set: Average loss: 1.1405, Accuracy: 2850/5000 (57%)
[epoch 4] loss: 0.9366189
Test set: Average loss: 1.1116, Accuracy: 2940/5000 (59%)
[epoch 5] loss: 0.8658878
Test set: Average loss: 1.0926, Accuracy: 3005/5000 (60%)
[epoch 6] loss: 0.8030785
Test set: Average loss: 1.0761, Accuracy: 3038/5000 (61%)
[epoch 7] loss: 0.7460606
Test set: Average loss: 1.0627, Accuracy: 3077/5000 (62%)
[epoch 8] loss: 0.6837513
Test set: Average loss: 1.0503, Accuracy: 3088/5000 (62%)
[epoch 9] loss: 0.6345279
Test set: Average loss: 1.0461, Accuracy: 3078/5000 (62%)
[epoch 10] loss: 0.5779740
Test set: Average loss: 1.0407, Accuracy: 3083/5000 (62%)
[epoch 11] loss: 0.5313526
Test set: Average loss: 1.0323, Accuracy: 3094/5000 (62%)
[epoch 12] loss: 0.4890200
Test set: Average loss: 1.0196, Accuracy: 3107/5000 (62%)
[epoch 13] loss: 0.4461306
Test set: Average loss: 1.0177, Accuracy: 3105/5000 (62%)
[epoch 14] loss: 0.4014742
Test set: Average loss: 1.0227, Accuracy: 3085/5000 (62%)
[epoch 15] loss: 0.3658894
Test set: Average loss: 1.0178, Accuracy: 3101/5000 (62%)
[epoch 16] loss: 0.3347121
Test set: Average loss: 1.0142, Accuracy: 3128/5000 (63%)
[epoch 17] loss: 0.2970520
Test set: Average loss: 1.0150, Accuracy: 3135/5000 (63%)
[epoch 18] loss: 0.2666821
Test set: Average loss: 1.0167, Accuracy: 3113/5000 (62%)
[epoch 19] loss: 0.2409273
Test set: Average loss: 1.0113, Accuracy: 3156/5000 (63%)
[epoch 20] loss: 0.2175529
Test set: Average loss: 1.0193, Accuracy: 3104/5000 (62%)
[epoch 21] loss: 0.1962245
Test set: Average loss: 1.0136, Accuracy: 3126/5000 (63%)
[epoch 22] loss: 0.1777554
Test set: Average loss: 1.0215, Accuracy: 3107/5000 (62%)
[epoch 23] loss: 0.1611864
Test set: Average loss: 1.0174, Accuracy: 3142/5000 (63%)
[epoch 24] loss: 0.1448647
Test set: Average loss: 1.0273, Accuracy: 3109/5000 (62%)
[epoch 25] loss: 0.1303626
Test set: Average loss: 1.0349, Accuracy: 3133/5000 (63%)
Validation:
Test set: Average loss: 1.0113, Accuracy: 3156/5000 (63%)
Test
Test set: Average loss: 1.0207, Accuracy: 3110/5000 (62%)
Test set: Average loss: 0.2165, Accuracy: 2466/2500 (99%)
## seed: 13
Validation accuracy before training:
Test set: Average loss: 1.7102, Accuracy: 766/5000 (15%)
[epoch 1] loss: 1.3464227
Test set: Average loss: 1.2348, Accuracy: 2604/5000 (52%)
[epoch 2] loss: 1.1245667
Test set: Average loss: 1.1643, Accuracy: 2817/5000 (56%)
[epoch 3] loss: 1.0251831
Test set: Average loss: 1.1346, Accuracy: 2907/5000 (58%)
[epoch 4] loss: 0.9526681
Test set: Average loss: 1.1108, Accuracy: 2963/5000 (59%)
[epoch 5] loss: 0.8913055
Test set: Average loss: 1.0956, Accuracy: 3001/5000 (60%)
[epoch 6] loss: 0.8391456
Test set: Average loss: 1.0797, Accuracy: 3009/5000 (60%)
[epoch 7] loss: 0.7785790
Test set: Average loss: 1.0640, Accuracy: 3059/5000 (61%)
[epoch 8] loss: 0.7244543
Test set: Average loss: 1.0530, Accuracy: 3072/5000 (61%)
[epoch 9] loss: 0.6731574
Test set: Average loss: 1.0440, Accuracy: 3057/5000 (61%)
[epoch 10] loss: 0.6291212
Test set: Average loss: 1.0303, Accuracy: 3107/5000 (62%)
[epoch 11] loss: 0.5809122
Test set: Average loss: 1.0246, Accuracy: 3124/5000 (62%)
[epoch 12] loss: 0.5397766
Test set: Average loss: 1.0146, Accuracy: 3124/5000 (62%)
[epoch 13] loss: 0.4911401
Test set: Average loss: 1.0144, Accuracy: 3123/5000 (62%)
[epoch 14] loss: 0.4504617
Test set: Average loss: 1.0100, Accuracy: 3128/5000 (63%)
[epoch 15] loss: 0.4139396
Test set: Average loss: 1.0035, Accuracy: 3146/5000 (63%)
[epoch 16] loss: 0.3748936
Test set: Average loss: 1.0052, Accuracy: 3128/5000 (63%)
[epoch 17] loss: 0.3358658
Test set: Average loss: 1.0054, Accuracy: 3131/5000 (63%)
[epoch 18] loss: 0.3083210
Test set: Average loss: 1.0012, Accuracy: 3121/5000 (62%)
[epoch 19] loss: 0.2843039
Test set: Average loss: 1.0049, Accuracy: 3096/5000 (62%)
[epoch 20] loss: 0.2545582
Test set: Average loss: 1.0050, Accuracy: 3121/5000 (62%)
[epoch 21] loss: 0.2263492
Test set: Average loss: 1.0024, Accuracy: 3127/5000 (63%)
[epoch 22] loss: 0.2018217
Test set: Average loss: 1.0044, Accuracy: 3126/5000 (63%)
[epoch 23] loss: 0.1824191
Test set: Average loss: 1.0121, Accuracy: 3119/5000 (62%)
[epoch 24] loss: 0.1643787
Test set: Average loss: 1.0050, Accuracy: 3123/5000 (62%)
[epoch 25] loss: 0.1492808
Test set: Average loss: 1.0057, Accuracy: 3134/5000 (63%)
Validation:
Test set: Average loss: 1.0035, Accuracy: 3146/5000 (63%)
Test
Test set: Average loss: 1.0276, Accuracy: 3066/5000 (61%)
Test set: Average loss: 0.3671, Accuracy: 2402/2500 (96%)
5000
## seed: 11
Validation accuracy before training:
Test set: Average loss: 1.6606, Accuracy: 1050/5000 (21%)
[epoch 1] loss: 1.2428199
Test set: Average loss: 1.1265, Accuracy: 2892/5000 (58%)
[epoch 2] loss: 1.0333083
Test set: Average loss: 1.0599, Accuracy: 3074/5000 (61%)
[epoch 3] loss: 0.9313600
Test set: Average loss: 1.0297, Accuracy: 3136/5000 (63%)
[epoch 4] loss: 0.8510177
Test set: Average loss: 1.0071, Accuracy: 3162/5000 (63%)
[epoch 5] loss: 0.7749582
Test set: Average loss: 0.9923, Accuracy: 3168/5000 (63%)
[epoch 6] loss: 0.7042558
Test set: Average loss: 0.9723, Accuracy: 3214/5000 (64%)
[epoch 7] loss: 0.6404307
Test set: Average loss: 0.9554, Accuracy: 3236/5000 (65%)
[epoch 8] loss: 0.5801819
Test set: Average loss: 0.9495, Accuracy: 3232/5000 (65%)
[epoch 9] loss: 0.5179435
Test set: Average loss: 0.9366, Accuracy: 3251/5000 (65%)
[epoch 10] loss: 0.4623473
Test set: Average loss: 0.9392, Accuracy: 3255/5000 (65%)
[epoch 11] loss: 0.4097060
Test set: Average loss: 0.9370, Accuracy: 3263/5000 (65%)
[epoch 12] loss: 0.3611528
Test set: Average loss: 0.9355, Accuracy: 3257/5000 (65%)
[epoch 13] loss: 0.3204214
Test set: Average loss: 0.9248, Accuracy: 3295/5000 (66%)
[epoch 14] loss: 0.2746480
Test set: Average loss: 0.9257, Accuracy: 3295/5000 (66%)
[epoch 15] loss: 0.2388668
Test set: Average loss: 0.9270, Accuracy: 3304/5000 (66%)
[epoch 16] loss: 0.2054433
Test set: Average loss: 0.9284, Accuracy: 3303/5000 (66%)
[epoch 17] loss: 0.1782312
Test set: Average loss: 0.9329, Accuracy: 3292/5000 (66%)
[epoch 18] loss: 0.1510480
Test set: Average loss: 0.9363, Accuracy: 3298/5000 (66%)
[epoch 19] loss: 0.1290311
Test set: Average loss: 0.9418, Accuracy: 3298/5000 (66%)
[epoch 20] loss: 0.1126133
Test set: Average loss: 0.9547, Accuracy: 3293/5000 (66%)
[epoch 21] loss: 0.0981674
Test set: Average loss: 0.9527, Accuracy: 3286/5000 (66%)
[epoch 22] loss: 0.0832874
Test set: Average loss: 0.9606, Accuracy: 3310/5000 (66%)
[epoch 23] loss: 0.0708751
Test set: Average loss: 0.9614, Accuracy: 3310/5000 (66%)
[epoch 24] loss: 0.0625194
Test set: Average loss: 0.9739, Accuracy: 3294/5000 (66%)
[epoch 25] loss: 0.0548600
Test set: Average loss: 0.9839, Accuracy: 3283/5000 (66%)
Validation:
Test set: Average loss: 0.9614, Accuracy: 3310/5000 (66%)
Test
Test set: Average loss: 0.9652, Accuracy: 3271/5000 (65%)
Test set: Average loss: 0.0614, Accuracy: 4998/5000 (100%)
## seed: 12
Validation accuracy before training:
Test set: Average loss: 1.6026, Accuracy: 1048/5000 (21%)
[epoch 1] loss: 1.2150691
Test set: Average loss: 1.1204, Accuracy: 2909/5000 (58%)
[epoch 2] loss: 1.0321949
Test set: Average loss: 1.0633, Accuracy: 3054/5000 (61%)
[epoch 3] loss: 0.9377052
Test set: Average loss: 1.0246, Accuracy: 3138/5000 (63%)
[epoch 4] loss: 0.8566449
Test set: Average loss: 0.9967, Accuracy: 3198/5000 (64%)
[epoch 5] loss: 0.7870247
Test set: Average loss: 0.9735, Accuracy: 3246/5000 (65%)
[epoch 6] loss: 0.7155845
Test set: Average loss: 0.9511, Accuracy: 3283/5000 (66%)
[epoch 7] loss: 0.6528900
Test set: Average loss: 0.9355, Accuracy: 3304/5000 (66%)
[epoch 8] loss: 0.5880052
Test set: Average loss: 0.9327, Accuracy: 3288/5000 (66%)
[epoch 9] loss: 0.5300788
Test set: Average loss: 0.9192, Accuracy: 3334/5000 (67%)
[epoch 10] loss: 0.4691213
Test set: Average loss: 0.9115, Accuracy: 3320/5000 (66%)
[epoch 11] loss: 0.4143233
Test set: Average loss: 0.9052, Accuracy: 3333/5000 (67%)
[epoch 12] loss: 0.3651959
Test set: Average loss: 0.9046, Accuracy: 3313/5000 (66%)
[epoch 13] loss: 0.3159207
Test set: Average loss: 0.9000, Accuracy: 3351/5000 (67%)
[epoch 14] loss: 0.2719482
Test set: Average loss: 0.8984, Accuracy: 3333/5000 (67%)
[epoch 15] loss: 0.2330788
Test set: Average loss: 0.9110, Accuracy: 3316/5000 (66%)
[epoch 16] loss: 0.1974437
Test set: Average loss: 0.9198, Accuracy: 3316/5000 (66%)
[epoch 17] loss: 0.1688676
Test set: Average loss: 0.9150, Accuracy: 3329/5000 (67%)
[epoch 18] loss: 0.1432830
Test set: Average loss: 0.9187, Accuracy: 3339/5000 (67%)
[epoch 19] loss: 0.1205301
Test set: Average loss: 0.9144, Accuracy: 3356/5000 (67%)
[epoch 20] loss: 0.1028894
Test set: Average loss: 0.9265, Accuracy: 3354/5000 (67%)
[epoch 21] loss: 0.0875132
Test set: Average loss: 0.9296, Accuracy: 3362/5000 (67%)
[epoch 22] loss: 0.0749822
Test set: Average loss: 0.9507, Accuracy: 3322/5000 (66%)
[epoch 23] loss: 0.0650779
Test set: Average loss: 0.9511, Accuracy: 3366/5000 (67%)
[epoch 24] loss: 0.0561387
Test set: Average loss: 0.9477, Accuracy: 3362/5000 (67%)
[epoch 25] loss: 0.0485669
Test set: Average loss: 0.9570, Accuracy: 3349/5000 (67%)
Validation:
Test set: Average loss: 0.9511, Accuracy: 3366/5000 (67%)
Test
Test set: Average loss: 0.9773, Accuracy: 3262/5000 (65%)
Test set: Average loss: 0.0571, Accuracy: 4995/5000 (100%)
## seed: 13
Validation accuracy before training:
Test set: Average loss: 1.6275, Accuracy: 1101/5000 (22%)
[epoch 1] loss: 1.2139590
Test set: Average loss: 1.1306, Accuracy: 2898/5000 (58%)
[epoch 2] loss: 1.0156306
Test set: Average loss: 1.0702, Accuracy: 3051/5000 (61%)
[epoch 3] loss: 0.9202348
Test set: Average loss: 1.0330, Accuracy: 3114/5000 (62%)
[epoch 4] loss: 0.8384328
Test set: Average loss: 1.0102, Accuracy: 3156/5000 (63%)
[epoch 5] loss: 0.7631060
Test set: Average loss: 0.9888, Accuracy: 3198/5000 (64%)
[epoch 6] loss: 0.6966121
Test set: Average loss: 0.9725, Accuracy: 3231/5000 (65%)
[epoch 7] loss: 0.6307809
Test set: Average loss: 0.9619, Accuracy: 3246/5000 (65%)
[epoch 8] loss: 0.5686202
Test set: Average loss: 0.9458, Accuracy: 3265/5000 (65%)
[epoch 9] loss: 0.5088306
Test set: Average loss: 0.9449, Accuracy: 3288/5000 (66%)
[epoch 10] loss: 0.4527172
Test set: Average loss: 0.9321, Accuracy: 3282/5000 (66%)
[epoch 11] loss: 0.3980829
Test set: Average loss: 0.9364, Accuracy: 3288/5000 (66%)
[epoch 12] loss: 0.3493520
Test set: Average loss: 0.9435, Accuracy: 3268/5000 (65%)
[epoch 13] loss: 0.3051937
Test set: Average loss: 0.9504, Accuracy: 3253/5000 (65%)
[epoch 14] loss: 0.2630508
Test set: Average loss: 0.9339, Accuracy: 3326/5000 (67%)
[epoch 15] loss: 0.2230236
Test set: Average loss: 0.9403, Accuracy: 3296/5000 (66%)
[epoch 16] loss: 0.1920457
Test set: Average loss: 0.9386, Accuracy: 3325/5000 (66%)
[epoch 17] loss: 0.1638548
Test set: Average loss: 0.9456, Accuracy: 3297/5000 (66%)
[epoch 18] loss: 0.1391174
Test set: Average loss: 0.9669, Accuracy: 3255/5000 (65%)
[epoch 19] loss: 0.1167570
Test set: Average loss: 0.9760, Accuracy: 3266/5000 (65%)
[epoch 20] loss: 0.1007330
Test set: Average loss: 0.9608, Accuracy: 3308/5000 (66%)
[epoch 21] loss: 0.0863078
Test set: Average loss: 0.9805, Accuracy: 3292/5000 (66%)
[epoch 22] loss: 0.0731110
Test set: Average loss: 0.9883, Accuracy: 3269/5000 (65%)
[epoch 23] loss: 0.0628828
Test set: Average loss: 0.9863, Accuracy: 3318/5000 (66%)
[epoch 24] loss: 0.0541429
Test set: Average loss: 0.9921, Accuracy: 3296/5000 (66%)
[epoch 25] loss: 0.0465540
Test set: Average loss: 1.0066, Accuracy: 3292/5000 (66%)
Validation:
Test set: Average loss: 0.9339, Accuracy: 3326/5000 (67%)
Test
Test set: Average loss: 0.9404, Accuracy: 3284/5000 (66%)
Test set: Average loss: 0.2231, Accuracy: 4919/5000 (98%)
10000
## seed: 11
Validation accuracy before training:
Test set: Average loss: 1.7122, Accuracy: 795/5000 (16%)
[epoch 1] loss: 1.2011436
Test set: Average loss: 1.0860, Accuracy: 3102/5000 (62%)
[epoch 2] loss: 1.0043011
Test set: Average loss: 1.0174, Accuracy: 3190/5000 (64%)
[epoch 3] loss: 0.8975922
Test set: Average loss: 0.9736, Accuracy: 3246/5000 (65%)
[epoch 4] loss: 0.8082512
Test set: Average loss: 0.9389, Accuracy: 3300/5000 (66%)
[epoch 5] loss: 0.7253622
Test set: Average loss: 0.9154, Accuracy: 3305/5000 (66%)
[epoch 6] loss: 0.6452299
Test set: Average loss: 0.9087, Accuracy: 3351/5000 (67%)
[epoch 7] loss: 0.5718600
Test set: Average loss: 0.8890, Accuracy: 3342/5000 (67%)
[epoch 8] loss: 0.4941553
Test set: Average loss: 0.8919, Accuracy: 3340/5000 (67%)
[epoch 9] loss: 0.4244030
Test set: Average loss: 0.8873, Accuracy: 3359/5000 (67%)
[epoch 10] loss: 0.3560929
Test set: Average loss: 0.8775, Accuracy: 3409/5000 (68%)
[epoch 11] loss: 0.2957729
Test set: Average loss: 0.8910, Accuracy: 3391/5000 (68%)
[epoch 12] loss: 0.2403881
Test set: Average loss: 0.8948, Accuracy: 3380/5000 (68%)
[epoch 13] loss: 0.1977378
Test set: Average loss: 0.9076, Accuracy: 3380/5000 (68%)
[epoch 14] loss: 0.1553721
Test set: Average loss: 0.9182, Accuracy: 3340/5000 (67%)
[epoch 15] loss: 0.1265597
Test set: Average loss: 0.9145, Accuracy: 3385/5000 (68%)
[epoch 16] loss: 0.0988381
Test set: Average loss: 0.9356, Accuracy: 3330/5000 (67%)
[epoch 17] loss: 0.0789751
Test set: Average loss: 0.9430, Accuracy: 3379/5000 (68%)
[epoch 18] loss: 0.0624256
Test set: Average loss: 0.9596, Accuracy: 3361/5000 (67%)
[epoch 19] loss: 0.0521133
Test set: Average loss: 0.9834, Accuracy: 3355/5000 (67%)
[epoch 20] loss: 0.0409347
Test set: Average loss: 1.0013, Accuracy: 3345/5000 (67%)
[epoch 21] loss: 0.0342374
Test set: Average loss: 1.0061, Accuracy: 3359/5000 (67%)
[epoch 22] loss: 0.0262958
Test set: Average loss: 1.0296, Accuracy: 3346/5000 (67%)
[epoch 23] loss: 0.0462843
Epoch 22: reducing learning rate of group 0 to 5.0000e-06.
Test set: Average loss: 1.0808, Accuracy: 3295/5000 (66%)
[epoch 24] loss: 0.0243237
Test set: Average loss: 1.0153, Accuracy: 3396/5000 (68%)
[epoch 25] loss: 0.0200146
Test set: Average loss: 1.0164, Accuracy: 3393/5000 (68%)
Validation:
Test set: Average loss: 0.8775, Accuracy: 3409/5000 (68%)
Test
Test set: Average loss: 0.8869, Accuracy: 3372/5000 (67%)
Test set: Average loss: 0.2861, Accuracy: 9602/10000 (96%)
## seed: 12
Validation accuracy before training:
Test set: Average loss: 1.7737, Accuracy: 618/5000 (12%)
[epoch 1] loss: 1.1984774
Test set: Average loss: 1.0733, Accuracy: 3098/5000 (62%)
[epoch 2] loss: 1.0020898
Test set: Average loss: 1.0177, Accuracy: 3163/5000 (63%)
[epoch 3] loss: 0.9057277
Test set: Average loss: 0.9780, Accuracy: 3253/5000 (65%)
[epoch 4] loss: 0.8236869
Test set: Average loss: 0.9468, Accuracy: 3293/5000 (66%)
[epoch 5] loss: 0.7471198
Test set: Average loss: 0.9218, Accuracy: 3335/5000 (67%)
[epoch 6] loss: 0.6732251
Test set: Average loss: 0.8932, Accuracy: 3419/5000 (68%)
[epoch 7] loss: 0.5981068
Test set: Average loss: 0.8845, Accuracy: 3383/5000 (68%)
[epoch 8] loss: 0.5274549
Test set: Average loss: 0.8708, Accuracy: 3391/5000 (68%)
[epoch 9] loss: 0.4549647
Test set: Average loss: 0.8798, Accuracy: 3375/5000 (68%)
[epoch 10] loss: 0.3914527
Test set: Average loss: 0.8649, Accuracy: 3433/5000 (69%)
[epoch 11] loss: 0.3257643
Test set: Average loss: 0.8678, Accuracy: 3395/5000 (68%)
[epoch 12] loss: 0.2723519
Test set: Average loss: 0.8780, Accuracy: 3370/5000 (67%)
[epoch 13] loss: 0.2235430
Test set: Average loss: 0.8718, Accuracy: 3427/5000 (69%)
[epoch 14] loss: 0.1786280
Test set: Average loss: 0.8832, Accuracy: 3392/5000 (68%)
[epoch 15] loss: 0.1437115
Test set: Average loss: 0.9025, Accuracy: 3381/5000 (68%)
[epoch 16] loss: 0.1134952
Test set: Average loss: 0.9171, Accuracy: 3363/5000 (67%)
[epoch 17] loss: 0.0889678
Test set: Average loss: 0.9395, Accuracy: 3378/5000 (68%)
[epoch 18] loss: 0.0714849
Test set: Average loss: 0.9402, Accuracy: 3371/5000 (67%)
[epoch 19] loss: 0.0546332
Test set: Average loss: 0.9390, Accuracy: 3407/5000 (68%)
[epoch 20] loss: 0.0441098
Test set: Average loss: 0.9701, Accuracy: 3378/5000 (68%)
[epoch 21] loss: 0.0408474
Test set: Average loss: 0.9889, Accuracy: 3395/5000 (68%)
[epoch 22] loss: 0.0280003
Test set: Average loss: 0.9826, Accuracy: 3404/5000 (68%)
[epoch 23] loss: 0.0217672
Test set: Average loss: 0.9896, Accuracy: 3418/5000 (68%)
[epoch 24] loss: 0.0178470
Test set: Average loss: 1.0171, Accuracy: 3363/5000 (67%)
[epoch 25] loss: 0.0149235
Test set: Average loss: 1.0308, Accuracy: 3389/5000 (68%)
Validation:
Test set: Average loss: 0.8649, Accuracy: 3433/5000 (69%)
Test
Test set: Average loss: 0.8874, Accuracy: 3371/5000 (67%)
Test set: Average loss: 0.3263, Accuracy: 9432/10000 (94%)
## seed: 13
Validation accuracy before training:
Test set: Average loss: 1.6584, Accuracy: 1096/5000 (22%)
[epoch 1] loss: 1.1492685
Test set: Average loss: 1.0428, Accuracy: 3123/5000 (62%)
[epoch 2] loss: 0.9637399
Test set: Average loss: 1.0069, Accuracy: 3148/5000 (63%)
[epoch 3] loss: 0.8682555
Test set: Average loss: 0.9524, Accuracy: 3264/5000 (65%)
[epoch 4] loss: 0.7773279
Test set: Average loss: 0.9211, Accuracy: 3318/5000 (66%)
[epoch 5] loss: 0.7004336
Test set: Average loss: 0.8948, Accuracy: 3391/5000 (68%)
[epoch 6] loss: 0.6243271
Test set: Average loss: 0.8853, Accuracy: 3375/5000 (68%)
[epoch 7] loss: 0.5531792
Test set: Average loss: 0.8770, Accuracy: 3394/5000 (68%)
[epoch 8] loss: 0.4818889
Test set: Average loss: 0.8715, Accuracy: 3377/5000 (68%)
[epoch 9] loss: 0.4167319
Test set: Average loss: 0.8588, Accuracy: 3403/5000 (68%)
[epoch 10] loss: 0.3568708
Test set: Average loss: 0.8608, Accuracy: 3424/5000 (68%)
[epoch 11] loss: 0.2977041
Test set: Average loss: 0.8701, Accuracy: 3404/5000 (68%)
[epoch 12] loss: 0.2468064
Test set: Average loss: 0.8846, Accuracy: 3369/5000 (67%)
[epoch 13] loss: 0.2013662
Test set: Average loss: 0.8698, Accuracy: 3415/5000 (68%)
[epoch 14] loss: 0.1603652
Test set: Average loss: 0.8880, Accuracy: 3399/5000 (68%)
[epoch 15] loss: 0.1278402
Test set: Average loss: 0.9019, Accuracy: 3402/5000 (68%)
[epoch 16] loss: 0.1047847
Test set: Average loss: 0.8939, Accuracy: 3446/5000 (69%)
[epoch 17] loss: 0.0823270
Test set: Average loss: 0.9145, Accuracy: 3404/5000 (68%)
[epoch 18] loss: 0.0616729
Test set: Average loss: 0.9273, Accuracy: 3438/5000 (69%)
[epoch 19] loss: 0.0494189
Test set: Average loss: 0.9411, Accuracy: 3429/5000 (69%)
[epoch 20] loss: 0.0409147
Test set: Average loss: 0.9534, Accuracy: 3416/5000 (68%)
[epoch 21] loss: 0.0411254
Epoch 20: reducing learning rate of group 0 to 5.0000e-06.
Test set: Average loss: 0.9880, Accuracy: 3402/5000 (68%)
[epoch 22] loss: 0.0248267
Test set: Average loss: 0.9607, Accuracy: 3440/5000 (69%)
[epoch 23] loss: 0.0233339
Test set: Average loss: 0.9615, Accuracy: 3434/5000 (69%)
[epoch 24] loss: 0.0223499
Test set: Average loss: 0.9617, Accuracy: 3438/5000 (69%)
[epoch 25] loss: 0.0215128
Test set: Average loss: 0.9647, Accuracy: 3445/5000 (69%)
Validation:
Test set: Average loss: 0.8939, Accuracy: 3446/5000 (69%)
Test
Test set: Average loss: 0.9173, Accuracy: 3405/5000 (68%)
Test set: Average loss: 0.0782, Accuracy: 9969/10000 (100%)
15000
## seed: 11
Validation accuracy before training:
Test set: Average loss: 1.9079, Accuracy: 389/5000 (8%)
[epoch 1] loss: 1.1533398
Test set: Average loss: 1.0430, Accuracy: 3092/5000 (62%)
[epoch 2] loss: 0.9782378
Test set: Average loss: 0.9788, Accuracy: 3208/5000 (64%)
[epoch 3] loss: 0.8827048
Test set: Average loss: 0.9329, Accuracy: 3283/5000 (66%)
[epoch 4] loss: 0.7994528
Test set: Average loss: 0.8994, Accuracy: 3367/5000 (67%)
[epoch 5] loss: 0.7165584
Test set: Average loss: 0.8832, Accuracy: 3367/5000 (67%)
[epoch 6] loss: 0.6319777
Test set: Average loss: 0.8524, Accuracy: 3427/5000 (69%)
[epoch 7] loss: 0.5529944
Test set: Average loss: 0.8466, Accuracy: 3413/5000 (68%)
[epoch 8] loss: 0.4749403
Test set: Average loss: 0.8556, Accuracy: 3424/5000 (68%)
[epoch 9] loss: 0.3999812
Test set: Average loss: 0.8489, Accuracy: 3449/5000 (69%)
[epoch 10] loss: 0.3338293
Test set: Average loss: 0.8431, Accuracy: 3445/5000 (69%)
[epoch 11] loss: 0.2684980
Test set: Average loss: 0.8476, Accuracy: 3424/5000 (68%)
[epoch 12] loss: 0.2164817
Test set: Average loss: 0.8611, Accuracy: 3427/5000 (69%)
[epoch 13] loss: 0.1672345
Test set: Average loss: 0.8845, Accuracy: 3450/5000 (69%)
[epoch 14] loss: 0.1282721
Test set: Average loss: 0.9177, Accuracy: 3393/5000 (68%)
[epoch 15] loss: 0.0997423
Test set: Average loss: 0.9124, Accuracy: 3433/5000 (69%)
[epoch 16] loss: 0.0746707
Test set: Average loss: 0.9189, Accuracy: 3464/5000 (69%)
[epoch 17] loss: 0.0568299
Test set: Average loss: 0.9469, Accuracy: 3465/5000 (69%)
[epoch 18] loss: 0.0473023
Test set: Average loss: 0.9750, Accuracy: 3448/5000 (69%)
[epoch 19] loss: 0.0444810
Test set: Average loss: 1.0045, Accuracy: 3428/5000 (69%)
[epoch 20] loss: 0.0234256
Test set: Average loss: 1.0199, Accuracy: 3409/5000 (68%)
[epoch 21] loss: 0.0181826
Test set: Average loss: 1.0436, Accuracy: 3445/5000 (69%)
[epoch 22] loss: 0.0623228
Epoch 21: reducing learning rate of group 0 to 5.0000e-06.
Test set: Average loss: 1.0779, Accuracy: 3397/5000 (68%)
[epoch 23] loss: 0.0215836
Epoch 22: reducing learning rate of group 0 to 5.0000e-07.
Test set: Average loss: 1.0472, Accuracy: 3431/5000 (69%)
[epoch 24] loss: 0.0170425
Test set: Average loss: 1.0455, Accuracy: 3434/5000 (69%)
[epoch 25] loss: 0.0166690
Test set: Average loss: 1.0461, Accuracy: 3430/5000 (69%)
Validation:
Test set: Average loss: 0.9469, Accuracy: 3465/5000 (69%)
Test
Test set: Average loss: 0.9746, Accuracy: 3420/5000 (68%)
Test set: Average loss: 0.0448, Accuracy: 14961/15000 (100%)
## seed: 12
Validation accuracy before training:
Test set: Average loss: 1.7394, Accuracy: 824/5000 (16%)
[epoch 1] loss: 1.1898517
Test set: Average loss: 1.0688, Accuracy: 3051/5000 (61%)
[epoch 2] loss: 0.9882471
Test set: Average loss: 0.9773, Accuracy: 3267/5000 (65%)
[epoch 3] loss: 0.8786382
Test set: Average loss: 0.9318, Accuracy: 3292/5000 (66%)
[epoch 4] loss: 0.7847104
Test set: Average loss: 0.9066, Accuracy: 3314/5000 (66%)
[epoch 5] loss: 0.6993316
Test set: Average loss: 0.8735, Accuracy: 3405/5000 (68%)
[epoch 6] loss: 0.6130826
Test set: Average loss: 0.8614, Accuracy: 3396/5000 (68%)
[epoch 7] loss: 0.5346639
Test set: Average loss: 0.8564, Accuracy: 3448/5000 (69%)
[epoch 8] loss: 0.4537697
Test set: Average loss: 0.8491, Accuracy: 3444/5000 (69%)
[epoch 9] loss: 0.3775330
Test set: Average loss: 0.8375, Accuracy: 3477/5000 (70%)
[epoch 10] loss: 0.3072430
Test set: Average loss: 0.8501, Accuracy: 3469/5000 (69%)
[epoch 11] loss: 0.2475053
Test set: Average loss: 0.8675, Accuracy: 3435/5000 (69%)
[epoch 12] loss: 0.1944360
Test set: Average loss: 0.8859, Accuracy: 3436/5000 (69%)
[epoch 13] loss: 0.1482573
Test set: Average loss: 0.8973, Accuracy: 3425/5000 (68%)
[epoch 14] loss: 0.1118760
Test set: Average loss: 0.9144, Accuracy: 3424/5000 (68%)
[epoch 15] loss: 0.0870685
Test set: Average loss: 0.9259, Accuracy: 3440/5000 (69%)
[epoch 16] loss: 0.0679665
Test set: Average loss: 0.9326, Accuracy: 3446/5000 (69%)
[epoch 17] loss: 0.0487851
Test set: Average loss: 0.9616, Accuracy: 3444/5000 (69%)
[epoch 18] loss: 0.0414368
Test set: Average loss: 1.0011, Accuracy: 3445/5000 (69%)
[epoch 19] loss: 0.0352797
Test set: Average loss: 1.0941, Accuracy: 3326/5000 (67%)
[epoch 20] loss: 0.0403096
Epoch 19: reducing learning rate of group 0 to 5.0000e-06.
Test set: Average loss: 1.0512, Accuracy: 3404/5000 (68%)
[epoch 21] loss: 0.0189556
Test set: Average loss: 1.0173, Accuracy: 3456/5000 (69%)
[epoch 22] loss: 0.0154146
Test set: Average loss: 1.0141, Accuracy: 3458/5000 (69%)
[epoch 23] loss: 0.0139466
Test set: Average loss: 1.0153, Accuracy: 3462/5000 (69%)
[epoch 24] loss: 0.0128996
Test set: Average loss: 1.0188, Accuracy: 3465/5000 (69%)
[epoch 25] loss: 0.0120423
Test set: Average loss: 1.0206, Accuracy: 3473/5000 (69%)
Validation:
Test set: Average loss: 0.8375, Accuracy: 3477/5000 (70%)
Test
Test set: Average loss: 0.8518, Accuracy: 3453/5000 (69%)
Test set: Average loss: 0.3020, Accuracy: 14167/15000 (94%)
## seed: 13
Validation accuracy before training:
Test set: Average loss: 1.7302, Accuracy: 702/5000 (14%)
[epoch 1] loss: 1.1574027
Test set: Average loss: 1.0396, Accuracy: 3118/5000 (62%)
[epoch 2] loss: 0.9732934
Test set: Average loss: 0.9683, Accuracy: 3243/5000 (65%)
[epoch 3] loss: 0.8750528
Test set: Average loss: 0.9309, Accuracy: 3313/5000 (66%)
[epoch 4] loss: 0.7933854
Test set: Average loss: 0.9004, Accuracy: 3350/5000 (67%)
[epoch 5] loss: 0.7141052
Test set: Average loss: 0.8729, Accuracy: 3401/5000 (68%)
[epoch 6] loss: 0.6361997
Test set: Average loss: 0.8595, Accuracy: 3439/5000 (69%)
[epoch 7] loss: 0.5598335
Test set: Average loss: 0.8475, Accuracy: 3452/5000 (69%)
[epoch 8] loss: 0.4832304
Test set: Average loss: 0.8327, Accuracy: 3482/5000 (70%)
[epoch 9] loss: 0.4101615
Test set: Average loss: 0.8355, Accuracy: 3477/5000 (70%)
[epoch 10] loss: 0.3425667
Test set: Average loss: 0.8380, Accuracy: 3480/5000 (70%)
[epoch 11] loss: 0.2800775
Test set: Average loss: 0.8364, Accuracy: 3487/5000 (70%)
[epoch 12] loss: 0.2266520
Test set: Average loss: 0.8453, Accuracy: 3485/5000 (70%)
[epoch 13] loss: 0.1752157
Test set: Average loss: 0.8588, Accuracy: 3473/5000 (69%)
[epoch 14] loss: 0.1364935
Test set: Average loss: 0.8797, Accuracy: 3468/5000 (69%)
[epoch 15] loss: 0.1067436
Test set: Average loss: 0.8924, Accuracy: 3450/5000 (69%)
[epoch 16] loss: 0.0787686
Test set: Average loss: 0.8944, Accuracy: 3492/5000 (70%)
[epoch 17] loss: 0.0629224
Test set: Average loss: 0.9136, Accuracy: 3470/5000 (69%)
[epoch 18] loss: 0.0475551
Test set: Average loss: 0.9485, Accuracy: 3453/5000 (69%)
[epoch 19] loss: 0.0361622
Test set: Average loss: 0.9802, Accuracy: 3426/5000 (69%)
[epoch 20] loss: 0.0426864
Epoch 19: reducing learning rate of group 0 to 5.0000e-06.
Test set: Average loss: 1.0086, Accuracy: 3468/5000 (69%)
[epoch 21] loss: 0.0216397
Test set: Average loss: 0.9723, Accuracy: 3488/5000 (70%)
[epoch 22] loss: 0.0181928
Test set: Average loss: 0.9719, Accuracy: 3484/5000 (70%)
[epoch 23] loss: 0.0167325
Test set: Average loss: 0.9719, Accuracy: 3490/5000 (70%)
[epoch 24] loss: 0.0156398
Test set: Average loss: 0.9740, Accuracy: 3499/5000 (70%)
[epoch 25] loss: 0.0146739
Test set: Average loss: 0.9791, Accuracy: 3491/5000 (70%)
Validation:
Test set: Average loss: 0.9740, Accuracy: 3499/5000 (70%)
Test
Test set: Average loss: 1.0026, Accuracy: 3433/5000 (69%)
Test set: Average loss: 0.0148, Accuracy: 14998/15000 (100%)
20000
## seed: 11
Validation accuracy before training:
Test set: Average loss: 1.6881, Accuracy: 951/5000 (19%)
[epoch 1] loss: 1.1180247
Test set: Average loss: 1.0109, Accuracy: 3217/5000 (64%)
[epoch 2] loss: 0.9343659
Test set: Average loss: 0.9353, Accuracy: 3345/5000 (67%)
[epoch 3] loss: 0.8295312
Test set: Average loss: 0.9026, Accuracy: 3341/5000 (67%)
[epoch 4] loss: 0.7384399
Test set: Average loss: 0.8620, Accuracy: 3428/5000 (69%)
[epoch 5] loss: 0.6548959
Test set: Average loss: 0.8454, Accuracy: 3443/5000 (69%)
[epoch 6] loss: 0.5723647
Test set: Average loss: 0.8286, Accuracy: 3476/5000 (70%)
[epoch 7] loss: 0.4914710
Test set: Average loss: 0.8374, Accuracy: 3461/5000 (69%)
[epoch 8] loss: 0.4108839
Test set: Average loss: 0.8301, Accuracy: 3476/5000 (70%)
[epoch 9] loss: 0.3367900
Test set: Average loss: 0.8355, Accuracy: 3477/5000 (70%)
[epoch 10] loss: 0.2685915
Test set: Average loss: 0.8392, Accuracy: 3479/5000 (70%)
[epoch 11] loss: 0.2115529
Test set: Average loss: 0.8831, Accuracy: 3436/5000 (69%)
[epoch 12] loss: 0.1597750
Test set: Average loss: 0.8908, Accuracy: 3470/5000 (69%)
[epoch 13] loss: 0.1234207
Test set: Average loss: 0.9115, Accuracy: 3435/5000 (69%)
[epoch 14] loss: 0.0894377
Test set: Average loss: 0.9244, Accuracy: 3491/5000 (70%)
[epoch 15] loss: 0.0710276
Test set: Average loss: 1.0117, Accuracy: 3400/5000 (68%)
[epoch 16] loss: 0.0528488
Test set: Average loss: 0.9797, Accuracy: 3495/5000 (70%)
[epoch 17] loss: 0.0429813
Test set: Average loss: 1.0154, Accuracy: 3432/5000 (69%)
[epoch 18] loss: 0.0478730
Epoch 17: reducing learning rate of group 0 to 5.0000e-06.
Test set: Average loss: 1.0366, Accuracy: 3469/5000 (69%)
[epoch 19] loss: 0.0217865
Test set: Average loss: 1.0093, Accuracy: 3501/5000 (70%)
[epoch 20] loss: 0.0170531
Test set: Average loss: 1.0073, Accuracy: 3503/5000 (70%)
[epoch 21] loss: 0.0151332
Test set: Average loss: 1.0080, Accuracy: 3511/5000 (70%)
[epoch 22] loss: 0.0137749
Test set: Average loss: 1.0141, Accuracy: 3509/5000 (70%)
[epoch 23] loss: 0.0126189
Test set: Average loss: 1.0169, Accuracy: 3514/5000 (70%)
[epoch 24] loss: 0.0116079
Test set: Average loss: 1.0223, Accuracy: 3512/5000 (70%)
[epoch 25] loss: 0.0106946
Test set: Average loss: 1.0275, Accuracy: 3517/5000 (70%)
Validation:
Test set: Average loss: 1.0275, Accuracy: 3517/5000 (70%)
Test
Test set: Average loss: 1.0406, Accuracy: 3489/5000 (70%)
Test set: Average loss: 0.0098, Accuracy: 19996/20000 (100%)
## seed: 12
Validation accuracy before training:
Test set: Average loss: 1.8323, Accuracy: 658/5000 (13%)
[epoch 1] loss: 1.1360701
Test set: Average loss: 1.0163, Accuracy: 3167/5000 (63%)
[epoch 2] loss: 0.9469517
Test set: Average loss: 0.9584, Accuracy: 3259/5000 (65%)
[epoch 3] loss: 0.8443312
Test set: Average loss: 0.9019, Accuracy: 3383/5000 (68%)
[epoch 4] loss: 0.7531756
Test set: Average loss: 0.8742, Accuracy: 3413/5000 (68%)
[epoch 5] loss: 0.6660849
Test set: Average loss: 0.8643, Accuracy: 3425/5000 (68%)
[epoch 6] loss: 0.5808366
Test set: Average loss: 0.8318, Accuracy: 3505/5000 (70%)
[epoch 7] loss: 0.4991192
Test set: Average loss: 0.8329, Accuracy: 3502/5000 (70%)
[epoch 8] loss: 0.4151050
Test set: Average loss: 0.8330, Accuracy: 3496/5000 (70%)
[epoch 9] loss: 0.3418421
Test set: Average loss: 0.8393, Accuracy: 3484/5000 (70%)
[epoch 10] loss: 0.2700052
Test set: Average loss: 0.8518, Accuracy: 3462/5000 (69%)
[epoch 11] loss: 0.2110205
Test set: Average loss: 0.8720, Accuracy: 3489/5000 (70%)
[epoch 12] loss: 0.1612048
Test set: Average loss: 0.8991, Accuracy: 3446/5000 (69%)
[epoch 13] loss: 0.1227707
Test set: Average loss: 0.9046, Accuracy: 3498/5000 (70%)
[epoch 14] loss: 0.0887337
Test set: Average loss: 0.9271, Accuracy: 3464/5000 (69%)
[epoch 15] loss: 0.0676151
Test set: Average loss: 0.9721, Accuracy: 3465/5000 (69%)
[epoch 16] loss: 0.0506568
Test set: Average loss: 0.9852, Accuracy: 3473/5000 (69%)
[epoch 17] loss: 0.0420300
Test set: Average loss: 1.0429, Accuracy: 3417/5000 (68%)
[epoch 18] loss: 0.0472882
Epoch 17: reducing learning rate of group 0 to 5.0000e-06.
Test set: Average loss: 1.0786, Accuracy: 3380/5000 (68%)
[epoch 19] loss: 0.0275549
Test set: Average loss: 1.0202, Accuracy: 3473/5000 (69%)
[epoch 20] loss: 0.0188756
Test set: Average loss: 1.0210, Accuracy: 3466/5000 (69%)
[epoch 21] loss: 0.0160499
Test set: Average loss: 1.0233, Accuracy: 3487/5000 (70%)
[epoch 22] loss: 0.0142026
Test set: Average loss: 1.0240, Accuracy: 3484/5000 (70%)
[epoch 23] loss: 0.0127643
Test set: Average loss: 1.0304, Accuracy: 3491/5000 (70%)
[epoch 24] loss: 0.0116160
Test set: Average loss: 1.0329, Accuracy: 3506/5000 (70%)
[epoch 25] loss: 0.0106459
Test set: Average loss: 1.0415, Accuracy: 3502/5000 (70%)
Validation:
Test set: Average loss: 1.0329, Accuracy: 3506/5000 (70%)
Test
Test set: Average loss: 1.0377, Accuracy: 3459/5000 (69%)
Test set: Average loss: 0.0106, Accuracy: 19997/20000 (100%)
## seed: 13
Validation accuracy before training:
Test set: Average loss: 1.6908, Accuracy: 903/5000 (18%)
[epoch 1] loss: 1.1159122
Test set: Average loss: 1.0111, Accuracy: 3173/5000 (63%)
[epoch 2] loss: 0.9265937
Test set: Average loss: 0.9304, Accuracy: 3308/5000 (66%)
[epoch 3] loss: 0.8202489
Test set: Average loss: 0.8907, Accuracy: 3381/5000 (68%)
[epoch 4] loss: 0.7296536
Test set: Average loss: 0.8622, Accuracy: 3429/5000 (69%)
[epoch 5] loss: 0.6465427
Test set: Average loss: 0.8324, Accuracy: 3467/5000 (69%)
[epoch 6] loss: 0.5640559
Test set: Average loss: 0.8299, Accuracy: 3492/5000 (70%)
[epoch 7] loss: 0.4802666
Test set: Average loss: 0.8321, Accuracy: 3473/5000 (69%)
[epoch 8] loss: 0.4060892
Test set: Average loss: 0.8070, Accuracy: 3513/5000 (70%)
[epoch 9] loss: 0.3324731
Test set: Average loss: 0.8403, Accuracy: 3443/5000 (69%)
[epoch 10] loss: 0.2678257
Test set: Average loss: 0.8324, Accuracy: 3524/5000 (70%)
[epoch 11] loss: 0.2064884
Test set: Average loss: 0.8753, Accuracy: 3425/5000 (68%)
[epoch 12] loss: 0.1584559
Test set: Average loss: 0.8654, Accuracy: 3515/5000 (70%)
[epoch 13] loss: 0.1217742
Test set: Average loss: 0.8820, Accuracy: 3500/5000 (70%)
[epoch 14] loss: 0.0915037
Test set: Average loss: 0.9058, Accuracy: 3518/5000 (70%)
[epoch 15] loss: 0.0722531
Test set: Average loss: 0.9789, Accuracy: 3422/5000 (68%)
[epoch 16] loss: 0.0524119
Test set: Average loss: 0.9412, Accuracy: 3500/5000 (70%)
[epoch 17] loss: 0.0431613
Test set: Average loss: 1.0521, Accuracy: 3397/5000 (68%)
[epoch 18] loss: 0.0410890
Test set: Average loss: 1.0053, Accuracy: 3486/5000 (70%)
[epoch 19] loss: 0.0192209
Test set: Average loss: 1.0429, Accuracy: 3490/5000 (70%)
[epoch 20] loss: 0.0118409
Test set: Average loss: 1.0710, Accuracy: 3453/5000 (69%)
[epoch 21] loss: 0.0699429
Epoch 20: reducing learning rate of group 0 to 5.0000e-06.
Test set: Average loss: 1.1258, Accuracy: 3435/5000 (69%)
[epoch 22] loss: 0.0189236
Epoch 21: reducing learning rate of group 0 to 5.0000e-07.
Test set: Average loss: 1.0757, Accuracy: 3454/5000 (69%)
[epoch 23] loss: 0.0141163
Epoch 22: reducing learning rate of group 0 to 5.0000e-08.
Test set: Average loss: 1.0735, Accuracy: 3453/5000 (69%)
[epoch 24] loss: 0.0138363
Epoch 23: reducing learning rate of group 0 to 5.0000e-09.
Test set: Average loss: 1.0733, Accuracy: 3456/5000 (69%)
[epoch 25] loss: 0.0138035
Epoch 24: reducing learning rate of group 0 to 5.0000e-10.
Test set: Average loss: 1.0733, Accuracy: 3458/5000 (69%)
Validation:
Test set: Average loss: 0.8324, Accuracy: 3524/5000 (70%)
Test
Test set: Average loss: 0.8459, Accuracy: 3486/5000 (70%)
Test set: Average loss: 0.2021, Accuracy: 19316/20000 (97%)
## Pre-Training ABnB
Validation accuracy before training:
Test set: Average loss: 2.3157, Accuracy: 611/5000 (12%)
[epoch 1] loss: 1.8943458
Test set: Average loss: 1.8235, Accuracy: 1955/5000 (39%)
[epoch 2] loss: 1.7491048
Test set: Average loss: 1.7564, Accuracy: 2062/5000 (41%)
[epoch 3] loss: 1.6629612
Test set: Average loss: 1.7226, Accuracy: 2100/5000 (42%)
[epoch 4] loss: 1.5855191
Test set: Average loss: 1.6827, Accuracy: 2172/5000 (43%)
[epoch 5] loss: 1.5090346
Test set: Average loss: 1.6422, Accuracy: 2232/5000 (45%)
[epoch 6] loss: 1.4346921
Test set: Average loss: 1.6154, Accuracy: 2255/5000 (45%)
[epoch 7] loss: 1.3562414
Test set: Average loss: 1.5932, Accuracy: 2306/5000 (46%)
[epoch 8] loss: 1.2792335
Test set: Average loss: 1.5733, Accuracy: 2314/5000 (46%)
[epoch 9] loss: 1.1968212
Test set: Average loss: 1.5768, Accuracy: 2314/5000 (46%)
[epoch 10] loss: 1.1120344
Test set: Average loss: 1.5829, Accuracy: 2297/5000 (46%)
[epoch 11] loss: 1.0265409
Test set: Average loss: 1.5722, Accuracy: 2339/5000 (47%)
[epoch 12] loss: 0.9375442
Test set: Average loss: 1.5712, Accuracy: 2333/5000 (47%)
[epoch 13] loss: 0.8474184
Test set: Average loss: 1.5758, Accuracy: 2302/5000 (46%)
[epoch 14] loss: 0.7606909
Test set: Average loss: 1.5849, Accuracy: 2323/5000 (46%)
[epoch 15] loss: 0.6711611
Test set: Average loss: 1.5962, Accuracy: 2343/5000 (47%)
[epoch 16] loss: 0.5868577
Test set: Average loss: 1.6264, Accuracy: 2284/5000 (46%)
[epoch 17] loss: 0.5130126
Test set: Average loss: 1.6473, Accuracy: 2313/5000 (46%)
[epoch 18] loss: 0.4359151
Test set: Average loss: 1.6744, Accuracy: 2271/5000 (45%)
[epoch 19] loss: 0.3699357
Test set: Average loss: 1.6766, Accuracy: 2314/5000 (46%)
[epoch 20] loss: 0.3095356
Test set: Average loss: 1.7175, Accuracy: 2289/5000 (46%)
[epoch 21] loss: 0.2600560
Test set: Average loss: 1.7827, Accuracy: 2274/5000 (45%)
[epoch 22] loss: 0.2149673
Test set: Average loss: 1.7950, Accuracy: 2284/5000 (46%)
[epoch 23] loss: 0.1734857
Test set: Average loss: 1.8322, Accuracy: 2272/5000 (45%)
[epoch 24] loss: 0.1468800
Test set: Average loss: 1.8618, Accuracy: 2285/5000 (46%)
[epoch 25] loss: 0.1313415
Test set: Average loss: 1.9966, Accuracy: 2216/5000 (44%)
Validation:
Test set: Average loss: 1.5962, Accuracy: 2343/5000 (47%)
Test set: Average loss: 1.5839, Accuracy: 4659/10000 (47%)
25
## seed: 11
Validation accuracy before training:
Test set: Average loss: 1.4739, Accuracy: 1883/5000 (38%)
[epoch 1] loss: 1.4360646
Test set: Average loss: 1.4564, Accuracy: 1971/5000 (39%)
[epoch 2] loss: 1.2813022
Test set: Average loss: 1.4417, Accuracy: 2016/5000 (40%)
[epoch 3] loss: 1.1521701
Test set: Average loss: 1.4290, Accuracy: 2047/5000 (41%)
[epoch 4] loss: 1.0456778
Test set: Average loss: 1.4178, Accuracy: 2068/5000 (41%)
[epoch 5] loss: 0.9578767
Test set: Average loss: 1.4079, Accuracy: 2070/5000 (41%)
[epoch 6] loss: 0.8853773
Test set: Average loss: 1.3992, Accuracy: 2085/5000 (42%)
[epoch 7] loss: 0.8251436
Test set: Average loss: 1.3915, Accuracy: 2102/5000 (42%)
[epoch 8] loss: 0.7744413
Test set: Average loss: 1.3848, Accuracy: 2105/5000 (42%)
[epoch 9] loss: 0.7310390
Test set: Average loss: 1.3789, Accuracy: 2120/5000 (42%)
[epoch 10] loss: 0.6933231
Test set: Average loss: 1.3737, Accuracy: 2139/5000 (43%)
[epoch 11] loss: 0.6601840
Test set: Average loss: 1.3693, Accuracy: 2142/5000 (43%)
[epoch 12] loss: 0.6308521
Test set: Average loss: 1.3656, Accuracy: 2134/5000 (43%)
[epoch 13] loss: 0.6047920
Test set: Average loss: 1.3624, Accuracy: 2137/5000 (43%)
[epoch 14] loss: 0.5816104
Test set: Average loss: 1.3599, Accuracy: 2139/5000 (43%)
[epoch 15] loss: 0.5609505
Test set: Average loss: 1.3578, Accuracy: 2138/5000 (43%)
[epoch 16] loss: 0.5424491
Test set: Average loss: 1.3562, Accuracy: 2133/5000 (43%)
[epoch 17] loss: 0.5257744
Test set: Average loss: 1.3548, Accuracy: 2144/5000 (43%)
[epoch 18] loss: 0.5106516
Test set: Average loss: 1.3535, Accuracy: 2153/5000 (43%)
[epoch 19] loss: 0.4968514
Test set: Average loss: 1.3524, Accuracy: 2149/5000 (43%)
[epoch 20] loss: 0.4842156
Test set: Average loss: 1.3514, Accuracy: 2154/5000 (43%)
[epoch 21] loss: 0.4726936
Test set: Average loss: 1.3503, Accuracy: 2146/5000 (43%)
[epoch 22] loss: 0.4622749
Test set: Average loss: 1.3492, Accuracy: 2155/5000 (43%)
[epoch 23] loss: 0.4528655
Test set: Average loss: 1.3480, Accuracy: 2161/5000 (43%)
[epoch 24] loss: 0.4442849
Test set: Average loss: 1.3467, Accuracy: 2166/5000 (43%)
[epoch 25] loss: 0.4363645
Test set: Average loss: 1.3453, Accuracy: 2168/5000 (43%)
Validation:
Test set: Average loss: 1.3453, Accuracy: 2168/5000 (43%)
Test
Test set: Average loss: 1.3568, Accuracy: 2153/5000 (43%)
Test set: Average loss: 0.4290, Accuracy: 25/25 (100%)
## seed: 12
Validation accuracy before training:
Test set: Average loss: 1.5414, Accuracy: 1479/5000 (30%)
[epoch 1] loss: 1.6120938
Test set: Average loss: 1.5203, Accuracy: 1579/5000 (32%)
[epoch 2] loss: 1.4271805
Test set: Average loss: 1.5028, Accuracy: 1650/5000 (33%)
[epoch 3] loss: 1.2697132
Test set: Average loss: 1.4879, Accuracy: 1744/5000 (35%)
[epoch 4] loss: 1.1383348
Test set: Average loss: 1.4749, Accuracy: 1832/5000 (37%)
[epoch 5] loss: 1.0290201
Test set: Average loss: 1.4630, Accuracy: 1903/5000 (38%)
[epoch 6] loss: 0.9366673
Test set: Average loss: 1.4518, Accuracy: 1969/5000 (39%)
[epoch 7] loss: 0.8579404
Test set: Average loss: 1.4415, Accuracy: 1996/5000 (40%)
[epoch 8] loss: 0.7910022
Test set: Average loss: 1.4319, Accuracy: 2028/5000 (41%)
[epoch 9] loss: 0.7342963
Test set: Average loss: 1.4233, Accuracy: 2060/5000 (41%)
[epoch 10] loss: 0.6864616
Test set: Average loss: 1.4155, Accuracy: 2088/5000 (42%)
[epoch 11] loss: 0.6461377
Test set: Average loss: 1.4087, Accuracy: 2110/5000 (42%)
[epoch 12] loss: 0.6118771
Test set: Average loss: 1.4028, Accuracy: 2126/5000 (43%)
[epoch 13] loss: 0.5823841
Test set: Average loss: 1.3977, Accuracy: 2135/5000 (43%)
[epoch 14] loss: 0.5567083
Test set: Average loss: 1.3933, Accuracy: 2133/5000 (43%)
[epoch 15] loss: 0.5342231
Test set: Average loss: 1.3897, Accuracy: 2144/5000 (43%)
[epoch 16] loss: 0.5144423
Test set: Average loss: 1.3866, Accuracy: 2158/5000 (43%)
[epoch 17] loss: 0.4969052
Test set: Average loss: 1.3841, Accuracy: 2159/5000 (43%)
[epoch 18] loss: 0.4812261
Test set: Average loss: 1.3820, Accuracy: 2159/5000 (43%)
[epoch 19] loss: 0.4671533
Test set: Average loss: 1.3803, Accuracy: 2160/5000 (43%)
[epoch 20] loss: 0.4545389
Test set: Average loss: 1.3790, Accuracy: 2166/5000 (43%)
[epoch 21] loss: 0.4432812
Test set: Average loss: 1.3780, Accuracy: 2187/5000 (44%)
[epoch 22] loss: 0.4332672
Test set: Average loss: 1.3772, Accuracy: 2184/5000 (44%)
[epoch 23] loss: 0.4243311
Test set: Average loss: 1.3767, Accuracy: 2185/5000 (44%)
[epoch 24] loss: 0.4162654
Test set: Average loss: 1.3763, Accuracy: 2188/5000 (44%)
[epoch 25] loss: 0.4088641
Test set: Average loss: 1.3762, Accuracy: 2191/5000 (44%)
Validation:
Test set: Average loss: 1.3762, Accuracy: 2191/5000 (44%)
Test
Test set: Average loss: 1.3860, Accuracy: 2137/5000 (43%)
Test set: Average loss: 0.4020, Accuracy: 25/25 (100%)
## seed: 13
Validation accuracy before training:
Test set: Average loss: 1.5514, Accuracy: 1879/5000 (38%)
[epoch 1] loss: 1.4913206
Test set: Average loss: 1.5333, Accuracy: 1954/5000 (39%)
[epoch 2] loss: 1.3102353
Test set: Average loss: 1.5178, Accuracy: 2006/5000 (40%)
[epoch 3] loss: 1.1626003
Test set: Average loss: 1.5047, Accuracy: 2057/5000 (41%)
[epoch 4] loss: 1.0438133
Test set: Average loss: 1.4937, Accuracy: 2081/5000 (42%)
[epoch 5] loss: 0.9471607
Test set: Average loss: 1.4844, Accuracy: 2100/5000 (42%)
[epoch 6] loss: 0.8676406
Test set: Average loss: 1.4764, Accuracy: 2121/5000 (42%)
[epoch 7] loss: 0.8020554
Test set: Average loss: 1.4694, Accuracy: 2140/5000 (43%)
[epoch 8] loss: 0.7479821
Test set: Average loss: 1.4634, Accuracy: 2134/5000 (43%)
[epoch 9] loss: 0.7032946
Test set: Average loss: 1.4582, Accuracy: 2137/5000 (43%)
[epoch 10] loss: 0.6660606
Test set: Average loss: 1.4535, Accuracy: 2148/5000 (43%)
[epoch 11] loss: 0.6344697
Test set: Average loss: 1.4495, Accuracy: 2155/5000 (43%)
[epoch 12] loss: 0.6070080
Test set: Average loss: 1.4459, Accuracy: 2164/5000 (43%)
[epoch 13] loss: 0.5826614
Test set: Average loss: 1.4427, Accuracy: 2174/5000 (43%)
[epoch 14] loss: 0.5608587
Test set: Average loss: 1.4400, Accuracy: 2187/5000 (44%)
[epoch 15] loss: 0.5412672
Test set: Average loss: 1.4377, Accuracy: 2178/5000 (44%)
[epoch 16] loss: 0.5236248
Test set: Average loss: 1.4356, Accuracy: 2181/5000 (44%)
[epoch 17] loss: 0.5076839
Test set: Average loss: 1.4337, Accuracy: 2183/5000 (44%)
[epoch 18] loss: 0.4932092
Test set: Average loss: 1.4318, Accuracy: 2177/5000 (44%)
[epoch 19] loss: 0.4799729
Test set: Average loss: 1.4301, Accuracy: 2175/5000 (44%)
[epoch 20] loss: 0.4677573
Test set: Average loss: 1.4283, Accuracy: 2171/5000 (43%)
[epoch 21] loss: 0.4563746
Test set: Average loss: 1.4265, Accuracy: 2167/5000 (43%)
[epoch 22] loss: 0.4456664
Test set: Average loss: 1.4246, Accuracy: 2165/5000 (43%)
[epoch 23] loss: 0.4354814
Test set: Average loss: 1.4227, Accuracy: 2165/5000 (43%)
[epoch 24] loss: 0.4256750
Test set: Average loss: 1.4207, Accuracy: 2169/5000 (43%)
[epoch 25] loss: 0.4161803
Test set: Average loss: 1.4187, Accuracy: 2167/5000 (43%)
Validation:
Test set: Average loss: 1.4400, Accuracy: 2187/5000 (44%)
Test
Test set: Average loss: 1.4479, Accuracy: 2197/5000 (44%)
Test set: Average loss: 0.5413, Accuracy: 25/25 (100%)
50
## seed: 11
Validation accuracy before training:
Test set: Average loss: 1.6292, Accuracy: 1210/5000 (24%)
[epoch 1] loss: 1.6579840
Test set: Average loss: 1.5754, Accuracy: 1466/5000 (29%)
[epoch 2] loss: 1.4396958
Test set: Average loss: 1.5397, Accuracy: 1600/5000 (32%)
[epoch 3] loss: 1.3141626
Test set: Average loss: 1.5133, Accuracy: 1682/5000 (34%)
[epoch 4] loss: 1.1852496
Test set: Average loss: 1.4924, Accuracy: 1725/5000 (34%)
[epoch 5] loss: 1.0905229
Test set: Average loss: 1.4748, Accuracy: 1777/5000 (36%)
[epoch 6] loss: 1.0069027
Test set: Average loss: 1.4607, Accuracy: 1807/5000 (36%)
[epoch 7] loss: 0.9255342
Test set: Average loss: 1.4492, Accuracy: 1846/5000 (37%)
[epoch 8] loss: 0.8584638
Test set: Average loss: 1.4404, Accuracy: 1856/5000 (37%)
[epoch 9] loss: 0.8261623
Test set: Average loss: 1.4326, Accuracy: 1899/5000 (38%)
[epoch 10] loss: 0.7917752
Test set: Average loss: 1.4258, Accuracy: 1936/5000 (39%)
[epoch 11] loss: 0.7296264
Test set: Average loss: 1.4195, Accuracy: 1958/5000 (39%)
[epoch 12] loss: 0.7217692
Test set: Average loss: 1.4137, Accuracy: 1967/5000 (39%)
[epoch 13] loss: 0.6629938
Test set: Average loss: 1.4083, Accuracy: 1981/5000 (40%)
[epoch 14] loss: 0.6411200
Test set: Average loss: 1.4033, Accuracy: 2014/5000 (40%)
[epoch 15] loss: 0.6096869
Test set: Average loss: 1.3992, Accuracy: 2025/5000 (40%)
[epoch 16] loss: 0.6093969
Test set: Average loss: 1.3957, Accuracy: 2038/5000 (41%)
[epoch 17] loss: 0.5723530
Test set: Average loss: 1.3926, Accuracy: 2055/5000 (41%)
[epoch 18] loss: 0.5532522
Test set: Average loss: 1.3898, Accuracy: 2063/5000 (41%)
[epoch 19] loss: 0.5392139
Test set: Average loss: 1.3875, Accuracy: 2075/5000 (42%)
[epoch 20] loss: 0.5282545
Test set: Average loss: 1.3855, Accuracy: 2097/5000 (42%)
[epoch 21] loss: 0.5093959
Test set: Average loss: 1.3843, Accuracy: 2108/5000 (42%)
[epoch 22] loss: 0.4956917
Test set: Average loss: 1.3833, Accuracy: 2127/5000 (43%)
[epoch 23] loss: 0.4970719
Epoch 22: reducing learning rate of group 0 to 5.0000e-06.
Test set: Average loss: 1.3825, Accuracy: 2148/5000 (43%)
[epoch 24] loss: 0.4578035
Test set: Average loss: 1.3824, Accuracy: 2152/5000 (43%)
[epoch 25] loss: 0.4748292
Epoch 24: reducing learning rate of group 0 to 5.0000e-07.
Test set: Average loss: 1.3823, Accuracy: 2149/5000 (43%)
Validation:
Test set: Average loss: 1.3824, Accuracy: 2152/5000 (43%)
Test
Test set: Average loss: 1.3888, Accuracy: 2144/5000 (43%)
Test set: Average loss: 0.4678, Accuracy: 50/50 (100%)
## seed: 12
Validation accuracy before training:
Test set: Average loss: 1.5979, Accuracy: 1171/5000 (23%)
[epoch 1] loss: 1.5919350
Test set: Average loss: 1.5278, Accuracy: 1430/5000 (29%)
[epoch 2] loss: 1.3297818
Test set: Average loss: 1.4900, Accuracy: 1615/5000 (32%)
[epoch 3] loss: 1.1292275
Test set: Average loss: 1.4691, Accuracy: 1707/5000 (34%)
[epoch 4] loss: 1.0248514
Test set: Average loss: 1.4530, Accuracy: 1776/5000 (36%)
[epoch 5] loss: 0.9234563
Test set: Average loss: 1.4411, Accuracy: 1806/5000 (36%)
[epoch 6] loss: 0.8563571
Test set: Average loss: 1.4316, Accuracy: 1861/5000 (37%)
[epoch 7] loss: 0.7832316
Test set: Average loss: 1.4242, Accuracy: 1909/5000 (38%)
[epoch 8] loss: 0.7272319
Test set: Average loss: 1.4178, Accuracy: 1972/5000 (39%)
[epoch 9] loss: 0.6889741
Test set: Average loss: 1.4126, Accuracy: 2012/5000 (40%)
[epoch 10] loss: 0.6522638
Test set: Average loss: 1.4082, Accuracy: 2044/5000 (41%)
[epoch 11] loss: 0.5937254
Test set: Average loss: 1.4046, Accuracy: 2062/5000 (41%)
[epoch 12] loss: 0.5748032
Test set: Average loss: 1.4018, Accuracy: 2088/5000 (42%)
[epoch 13] loss: 0.5571998
Test set: Average loss: 1.3993, Accuracy: 2096/5000 (42%)
[epoch 14] loss: 0.5321598
Test set: Average loss: 1.3970, Accuracy: 2113/5000 (42%)
[epoch 15] loss: 0.5101279
Test set: Average loss: 1.3949, Accuracy: 2127/5000 (43%)
[epoch 16] loss: 0.4941505
Test set: Average loss: 1.3928, Accuracy: 2148/5000 (43%)
[epoch 17] loss: 0.4850748
Test set: Average loss: 1.3908, Accuracy: 2156/5000 (43%)
[epoch 18] loss: 0.4609910
Test set: Average loss: 1.3886, Accuracy: 2174/5000 (43%)
[epoch 19] loss: 0.4525701
Test set: Average loss: 1.3866, Accuracy: 2172/5000 (43%)
[epoch 20] loss: 0.4484834
Test set: Average loss: 1.3847, Accuracy: 2178/5000 (44%)
[epoch 21] loss: 0.4218364
Test set: Average loss: 1.3829, Accuracy: 2175/5000 (44%)
[epoch 22] loss: 0.4116410
Test set: Average loss: 1.3813, Accuracy: 2173/5000 (43%)
[epoch 23] loss: 0.3936640
Test set: Average loss: 1.3801, Accuracy: 2174/5000 (43%)
[epoch 24] loss: 0.3965892
Epoch 23: reducing learning rate of group 0 to 5.0000e-06.
Test set: Average loss: 1.3793, Accuracy: 2174/5000 (43%)
[epoch 25] loss: 0.3937794
Epoch 24: reducing learning rate of group 0 to 5.0000e-07.
Test set: Average loss: 1.3793, Accuracy: 2174/5000 (43%)
Validation:
Test set: Average loss: 1.3847, Accuracy: 2178/5000 (44%)
Test
Test set: Average loss: 1.4059, Accuracy: 2195/5000 (44%)
Test set: Average loss: 0.4268, Accuracy: 50/50 (100%)
## seed: 13
Validation accuracy before training:
Test set: Average loss: 1.7362, Accuracy: 842/5000 (17%)
[epoch 1] loss: 1.7172588
Test set: Average loss: 1.6810, Accuracy: 1038/5000 (21%)
[epoch 2] loss: 1.4528062
Test set: Average loss: 1.6375, Accuracy: 1208/5000 (24%)
[epoch 3] loss: 1.2516986
Test set: Average loss: 1.5979, Accuracy: 1365/5000 (27%)
[epoch 4] loss: 1.1088624
Test set: Average loss: 1.5632, Accuracy: 1502/5000 (30%)
[epoch 5] loss: 0.9877667
Test set: Average loss: 1.5338, Accuracy: 1637/5000 (33%)
[epoch 6] loss: 0.8812051
Test set: Average loss: 1.5103, Accuracy: 1760/5000 (35%)
[epoch 7] loss: 0.7693412
Test set: Average loss: 1.4925, Accuracy: 1847/5000 (37%)
[epoch 8] loss: 0.7394772
Test set: Average loss: 1.4783, Accuracy: 1905/5000 (38%)
[epoch 9] loss: 0.6913792
Test set: Average loss: 1.4660, Accuracy: 1968/5000 (39%)
[epoch 10] loss: 0.6629745
Test set: Average loss: 1.4556, Accuracy: 2006/5000 (40%)
[epoch 11] loss: 0.6163640
Test set: Average loss: 1.4465, Accuracy: 2043/5000 (41%)
[epoch 12] loss: 0.5803948
Test set: Average loss: 1.4386, Accuracy: 2067/5000 (41%)
[epoch 13] loss: 0.5577886
Test set: Average loss: 1.4324, Accuracy: 2087/5000 (42%)
[epoch 14] loss: 0.5303785
Test set: Average loss: 1.4271, Accuracy: 2100/5000 (42%)
[epoch 15] loss: 0.5215831
Test set: Average loss: 1.4232, Accuracy: 2110/5000 (42%)
[epoch 16] loss: 0.4962021
Test set: Average loss: 1.4194, Accuracy: 2126/5000 (43%)
[epoch 17] loss: 0.4728540
Test set: Average loss: 1.4158, Accuracy: 2136/5000 (43%)
[epoch 18] loss: 0.4793796
Epoch 17: reducing learning rate of group 0 to 5.0000e-06.
Test set: Average loss: 1.4128, Accuracy: 2146/5000 (43%)
[epoch 19] loss: 0.4521762
Test set: Average loss: 1.4126, Accuracy: 2148/5000 (43%)
[epoch 20] loss: 0.4478436
Test set: Average loss: 1.4123, Accuracy: 2149/5000 (43%)
[epoch 21] loss: 0.4419013
Test set: Average loss: 1.4121, Accuracy: 2148/5000 (43%)
[epoch 22] loss: 0.4452073
Epoch 21: reducing learning rate of group 0 to 5.0000e-07.
Test set: Average loss: 1.4118, Accuracy: 2148/5000 (43%)
[epoch 23] loss: 0.4275242
Test set: Average loss: 1.4118, Accuracy: 2148/5000 (43%)
[epoch 24] loss: 0.4491928
Epoch 23: reducing learning rate of group 0 to 5.0000e-08.
Test set: Average loss: 1.4118, Accuracy: 2148/5000 (43%)
[epoch 25] loss: 0.4443084
Epoch 24: reducing learning rate of group 0 to 5.0000e-09.
Test set: Average loss: 1.4118, Accuracy: 2148/5000 (43%)
Validation:
Test set: Average loss: 1.4123, Accuracy: 2149/5000 (43%)
Test
Test set: Average loss: 1.4216, Accuracy: 2135/5000 (43%)
Test set: Average loss: 0.4436, Accuracy: 49/50 (98%)
100
## seed: 11
Validation accuracy before training:
Test set: Average loss: 1.7671, Accuracy: 970/5000 (19%)
[epoch 1] loss: 1.6654955
Test set: Average loss: 1.6488, Accuracy: 1501/5000 (30%)
[epoch 2] loss: 1.2989394
Test set: Average loss: 1.5733, Accuracy: 1742/5000 (35%)
[epoch 3] loss: 1.1231999
Test set: Average loss: 1.5211, Accuracy: 1837/5000 (37%)
[epoch 4] loss: 0.9697849
Test set: Average loss: 1.4866, Accuracy: 1918/5000 (38%)
[epoch 5] loss: 0.9336864
Test set: Average loss: 1.4566, Accuracy: 1994/5000 (40%)
[epoch 6] loss: 0.8495884
Test set: Average loss: 1.4292, Accuracy: 2069/5000 (41%)
[epoch 7] loss: 0.7717425
Test set: Average loss: 1.4076, Accuracy: 2137/5000 (43%)
[epoch 8] loss: 0.7628991
Test set: Average loss: 1.3909, Accuracy: 2191/5000 (44%)
[epoch 9] loss: 0.6809499
Test set: Average loss: 1.3791, Accuracy: 2216/5000 (44%)
[epoch 10] loss: 0.7081599
Epoch 9: reducing learning rate of group 0 to 5.0000e-06.
Test set: Average loss: 1.3727, Accuracy: 2225/5000 (44%)
[epoch 11] loss: 0.6526398
Test set: Average loss: 1.3727, Accuracy: 2222/5000 (44%)
[epoch 12] loss: 0.6441591
Test set: Average loss: 1.3729, Accuracy: 2228/5000 (45%)
[epoch 13] loss: 0.6179275
Test set: Average loss: 1.3731, Accuracy: 2232/5000 (45%)
[epoch 14] loss: 0.6703043
Epoch 13: reducing learning rate of group 0 to 5.0000e-07.
Test set: Average loss: 1.3733, Accuracy: 2233/5000 (45%)
[epoch 15] loss: 0.6383946
Epoch 14: reducing learning rate of group 0 to 5.0000e-08.
Test set: Average loss: 1.3733, Accuracy: 2236/5000 (45%)
[epoch 16] loss: 0.6545390
Epoch 15: reducing learning rate of group 0 to 5.0000e-09.
Test set: Average loss: 1.3733, Accuracy: 2236/5000 (45%)
[epoch 17] loss: 0.6830653
Epoch 16: reducing learning rate of group 0 to 5.0000e-10.
Test set: Average loss: 1.3733, Accuracy: 2236/5000 (45%)
[epoch 18] loss: 0.6372641
Epoch 17: reducing learning rate of group 0 to 5.0000e-11.
Test set: Average loss: 1.3733, Accuracy: 2236/5000 (45%)
[epoch 19] loss: 0.6691891
Epoch 18: reducing learning rate of group 0 to 5.0000e-12.
Test set: Average loss: 1.3733, Accuracy: 2236/5000 (45%)
[epoch 20] loss: 0.6402397
Epoch 19: reducing learning rate of group 0 to 5.0000e-13.
Test set: Average loss: 1.3733, Accuracy: 2236/5000 (45%)
[epoch 21] loss: 0.6703758
Epoch 20: reducing learning rate of group 0 to 5.0000e-14.
Test set: Average loss: 1.3733, Accuracy: 2236/5000 (45%)
[epoch 22] loss: 0.6115612
Test set: Average loss: 1.3733, Accuracy: 2236/5000 (45%)
[epoch 23] loss: 0.6155546
Epoch 22: reducing learning rate of group 0 to 5.0000e-15.
Test set: Average loss: 1.3733, Accuracy: 2236/5000 (45%)
[epoch 24] loss: 0.6256831
Epoch 23: reducing learning rate of group 0 to 5.0000e-16.
Test set: Average loss: 1.3733, Accuracy: 2236/5000 (45%)
[epoch 25] loss: 0.6759662
Epoch 24: reducing learning rate of group 0 to 5.0000e-17.
Test set: Average loss: 1.3733, Accuracy: 2236/5000 (45%)
Validation:
Test set: Average loss: 1.3733, Accuracy: 2236/5000 (45%)
Test
Test set: Average loss: 1.3823, Accuracy: 2213/5000 (44%)
Test set: Average loss: 0.6317, Accuracy: 93/100 (93%)
## seed: 12
Validation accuracy before training:
Test set: Average loss: 1.7069, Accuracy: 793/5000 (16%)
[epoch 1] loss: 1.7561718
Test set: Average loss: 1.6569, Accuracy: 929/5000 (19%)
[epoch 2] loss: 1.4494466
Test set: Average loss: 1.6131, Accuracy: 1174/5000 (23%)
[epoch 3] loss: 1.3349690
Test set: Average loss: 1.5761, Accuracy: 1385/5000 (28%)
[epoch 4] loss: 1.1975862
Test set: Average loss: 1.5476, Accuracy: 1506/5000 (30%)
[epoch 5] loss: 1.0307405
Test set: Average loss: 1.5273, Accuracy: 1609/5000 (32%)
[epoch 6] loss: 0.9755158
Test set: Average loss: 1.5064, Accuracy: 1688/5000 (34%)
[epoch 7] loss: 0.9097376
Test set: Average loss: 1.4885, Accuracy: 1756/5000 (35%)
[epoch 8] loss: 0.8928335
Test set: Average loss: 1.4740, Accuracy: 1800/5000 (36%)
[epoch 9] loss: 0.8142948
Test set: Average loss: 1.4617, Accuracy: 1830/5000 (37%)
[epoch 10] loss: 0.8289929
Epoch 9: reducing learning rate of group 0 to 5.0000e-06.
Test set: Average loss: 1.4522, Accuracy: 1864/5000 (37%)
[epoch 11] loss: 0.7746437
Test set: Average loss: 1.4508, Accuracy: 1869/5000 (37%)
[epoch 12] loss: 0.7461624
Test set: Average loss: 1.4493, Accuracy: 1875/5000 (38%)
[epoch 13] loss: 0.6959643
Test set: Average loss: 1.4479, Accuracy: 1881/5000 (38%)
[epoch 14] loss: 0.6830546
Test set: Average loss: 1.4466, Accuracy: 1892/5000 (38%)
[epoch 15] loss: 0.7116854
Epoch 14: reducing learning rate of group 0 to 5.0000e-07.
Test set: Average loss: 1.4450, Accuracy: 1896/5000 (38%)
[epoch 16] loss: 0.6943852
Epoch 15: reducing learning rate of group 0 to 5.0000e-08.
Test set: Average loss: 1.4448, Accuracy: 1897/5000 (38%)
[epoch 17] loss: 0.7008910
Epoch 16: reducing learning rate of group 0 to 5.0000e-09.
Test set: Average loss: 1.4448, Accuracy: 1897/5000 (38%)
[epoch 18] loss: 0.6968731
Epoch 17: reducing learning rate of group 0 to 5.0000e-10.
Test set: Average loss: 1.4448, Accuracy: 1897/5000 (38%)
[epoch 19] loss: 0.7135612
Epoch 18: reducing learning rate of group 0 to 5.0000e-11.
Test set: Average loss: 1.4448, Accuracy: 1897/5000 (38%)
[epoch 20] loss: 0.6826208
Test set: Average loss: 1.4448, Accuracy: 1897/5000 (38%)
[epoch 21] loss: 0.6817871
Test set: Average loss: 1.4448, Accuracy: 1897/5000 (38%)
[epoch 22] loss: 0.7157912
Epoch 21: reducing learning rate of group 0 to 5.0000e-12.
Test set: Average loss: 1.4448, Accuracy: 1897/5000 (38%)
[epoch 23] loss: 0.6977821
Epoch 22: reducing learning rate of group 0 to 5.0000e-13.
Test set: Average loss: 1.4448, Accuracy: 1897/5000 (38%)
[epoch 24] loss: 0.7189746
Epoch 23: reducing learning rate of group 0 to 5.0000e-14.
Test set: Average loss: 1.4448, Accuracy: 1897/5000 (38%)
[epoch 25] loss: 0.7468036
Epoch 24: reducing learning rate of group 0 to 5.0000e-15.
Test set: Average loss: 1.4448, Accuracy: 1897/5000 (38%)
Validation:
Test set: Average loss: 1.4448, Accuracy: 1897/5000 (38%)
Test
Test set: Average loss: 1.4451, Accuracy: 1923/5000 (38%)
Test set: Average loss: 0.7035, Accuracy: 95/100 (95%)
## seed: 13
Validation accuracy before training:
Test set: Average loss: 1.5595, Accuracy: 1206/5000 (24%)
[epoch 1] loss: 1.6139125
Test set: Average loss: 1.4575, Accuracy: 1605/5000 (32%)
[epoch 2] loss: 1.3439074
Test set: Average loss: 1.3977, Accuracy: 1898/5000 (38%)
[epoch 3] loss: 1.2326412
Test set: Average loss: 1.3599, Accuracy: 2099/5000 (42%)
[epoch 4] loss: 1.0265070
Test set: Average loss: 1.3350, Accuracy: 2195/5000 (44%)
[epoch 5] loss: 0.9520164
Test set: Average loss: 1.3162, Accuracy: 2246/5000 (45%)
[epoch 6] loss: 0.8885431
Test set: Average loss: 1.3022, Accuracy: 2306/5000 (46%)
[epoch 7] loss: 0.8724144
Test set: Average loss: 1.2911, Accuracy: 2375/5000 (48%)
[epoch 8] loss: 0.7279331
Test set: Average loss: 1.2825, Accuracy: 2425/5000 (48%)
[epoch 9] loss: 0.7365607
Epoch 8: reducing learning rate of group 0 to 5.0000e-06.
Test set: Average loss: 1.2744, Accuracy: 2461/5000 (49%)
[epoch 10] loss: 0.7229773
Test set: Average loss: 1.2735, Accuracy: 2469/5000 (49%)
[epoch 11] loss: 0.7066707
Test set: Average loss: 1.2727, Accuracy: 2473/5000 (49%)
[epoch 12] loss: 0.7075457
Epoch 11: reducing learning rate of group 0 to 5.0000e-07.
Test set: Average loss: 1.2721, Accuracy: 2478/5000 (50%)
[epoch 13] loss: 0.6699019
Test set: Average loss: 1.2720, Accuracy: 2477/5000 (50%)
[epoch 14] loss: 0.7076067
Epoch 13: reducing learning rate of group 0 to 5.0000e-08.
Test set: Average loss: 1.2720, Accuracy: 2480/5000 (50%)
[epoch 15] loss: 0.6399330
Test set: Average loss: 1.2720, Accuracy: 2480/5000 (50%)
[epoch 16] loss: 0.6850749
Epoch 15: reducing learning rate of group 0 to 5.0000e-09.
Test set: Average loss: 1.2720, Accuracy: 2480/5000 (50%)
[epoch 17] loss: 0.7529894
Epoch 16: reducing learning rate of group 0 to 5.0000e-10.
Test set: Average loss: 1.2720, Accuracy: 2480/5000 (50%)
[epoch 18] loss: 0.6632910
Epoch 17: reducing learning rate of group 0 to 5.0000e-11.
Test set: Average loss: 1.2720, Accuracy: 2480/5000 (50%)
[epoch 19] loss: 0.6835201
Epoch 18: reducing learning rate of group 0 to 5.0000e-12.
Test set: Average loss: 1.2720, Accuracy: 2480/5000 (50%)
[epoch 20] loss: 0.7211563
Epoch 19: reducing learning rate of group 0 to 5.0000e-13.
Test set: Average loss: 1.2720, Accuracy: 2480/5000 (50%)
[epoch 21] loss: 0.6929294
Epoch 20: reducing learning rate of group 0 to 5.0000e-14.
Test set: Average loss: 1.2720, Accuracy: 2480/5000 (50%)
[epoch 22] loss: 0.6888830
Epoch 21: reducing learning rate of group 0 to 5.0000e-15.
Test set: Average loss: 1.2720, Accuracy: 2480/5000 (50%)
[epoch 23] loss: 0.6251874
Test set: Average loss: 1.2720, Accuracy: 2480/5000 (50%)
[epoch 24] loss: 0.6685604
Epoch 23: reducing learning rate of group 0 to 5.0000e-16.
Test set: Average loss: 1.2720, Accuracy: 2480/5000 (50%)
[epoch 25] loss: 0.6721058
Epoch 24: reducing learning rate of group 0 to 5.0000e-17.
Test set: Average loss: 1.2720, Accuracy: 2480/5000 (50%)
Validation:
Test set: Average loss: 1.2720, Accuracy: 2480/5000 (50%)
Test
Test set: Average loss: 1.2834, Accuracy: 2469/5000 (49%)
Test set: Average loss: 0.6820, Accuracy: 96/100 (96%)
250
## seed: 11
Validation accuracy before training:
Test set: Average loss: 1.7160, Accuracy: 872/5000 (17%)
[epoch 1] loss: 1.7368438
Test set: Average loss: 1.5656, Accuracy: 1561/5000 (31%)
[epoch 2] loss: 1.4515909
Test set: Average loss: 1.4821, Accuracy: 1967/5000 (39%)
[epoch 3] loss: 1.2826531
Test set: Average loss: 1.4213, Accuracy: 2221/5000 (44%)
[epoch 4] loss: 1.1585548
Test set: Average loss: 1.3831, Accuracy: 2357/5000 (47%)
[epoch 5] loss: 1.0614567
Test set: Average loss: 1.3572, Accuracy: 2441/5000 (49%)
[epoch 6] loss: 0.9815119
Test set: Average loss: 1.3414, Accuracy: 2464/5000 (49%)
[epoch 7] loss: 0.9095048
Test set: Average loss: 1.3259, Accuracy: 2488/5000 (50%)
[epoch 8] loss: 0.8488121
Test set: Average loss: 1.3141, Accuracy: 2524/5000 (50%)
[epoch 9] loss: 0.7976629
Test set: Average loss: 1.3028, Accuracy: 2554/5000 (51%)
[epoch 10] loss: 0.7519984
Test set: Average loss: 1.2958, Accuracy: 2571/5000 (51%)
[epoch 11] loss: 0.7145697
Test set: Average loss: 1.2892, Accuracy: 2594/5000 (52%)
[epoch 12] loss: 0.6778828
Test set: Average loss: 1.2826, Accuracy: 2594/5000 (52%)
[epoch 13] loss: 0.6430638
Test set: Average loss: 1.2778, Accuracy: 2621/5000 (52%)
[epoch 14] loss: 0.6169300
Test set: Average loss: 1.2751, Accuracy: 2625/5000 (52%)
[epoch 15] loss: 0.5921922
Test set: Average loss: 1.2695, Accuracy: 2647/5000 (53%)
[epoch 16] loss: 0.5673345
Test set: Average loss: 1.2669, Accuracy: 2649/5000 (53%)
[epoch 17] loss: 0.5427540
Test set: Average loss: 1.2645, Accuracy: 2641/5000 (53%)
[epoch 18] loss: 0.5260645
Test set: Average loss: 1.2607, Accuracy: 2647/5000 (53%)
[epoch 19] loss: 0.5079509
Test set: Average loss: 1.2584, Accuracy: 2642/5000 (53%)
[epoch 20] loss: 0.4899983
Test set: Average loss: 1.2586, Accuracy: 2642/5000 (53%)
[epoch 21] loss: 0.4748245
Test set: Average loss: 1.2569, Accuracy: 2650/5000 (53%)
[epoch 22] loss: 0.4601785
Test set: Average loss: 1.2540, Accuracy: 2659/5000 (53%)
[epoch 23] loss: 0.4463887
Test set: Average loss: 1.2532, Accuracy: 2648/5000 (53%)
[epoch 24] loss: 0.4331036
Test set: Average loss: 1.2528, Accuracy: 2645/5000 (53%)
[epoch 25] loss: 0.4219172
Test set: Average loss: 1.2502, Accuracy: 2654/5000 (53%)
Validation:
Test set: Average loss: 1.2540, Accuracy: 2659/5000 (53%)
Test
Test set: Average loss: 1.2706, Accuracy: 2556/5000 (51%)
Test set: Average loss: 0.4503, Accuracy: 249/250 (100%)
## seed: 12
Validation accuracy before training:
Test set: Average loss: 1.9286, Accuracy: 337/5000 (7%)
[epoch 1] loss: 1.8617723
Test set: Average loss: 1.6459, Accuracy: 1231/5000 (25%)
[epoch 2] loss: 1.4739031
Test set: Average loss: 1.4891, Accuracy: 1906/5000 (38%)
[epoch 3] loss: 1.2557563
Test set: Average loss: 1.4020, Accuracy: 2089/5000 (42%)
[epoch 4] loss: 1.1052968
Test set: Average loss: 1.3593, Accuracy: 2156/5000 (43%)
[epoch 5] loss: 0.9884938
Test set: Average loss: 1.3386, Accuracy: 2200/5000 (44%)
[epoch 6] loss: 0.8977188
Test set: Average loss: 1.3183, Accuracy: 2246/5000 (45%)
[epoch 7] loss: 0.8239491
Test set: Average loss: 1.3039, Accuracy: 2286/5000 (46%)
[epoch 8] loss: 0.7628140
Test set: Average loss: 1.2941, Accuracy: 2319/5000 (46%)
[epoch 9] loss: 0.7070878
Test set: Average loss: 1.2848, Accuracy: 2374/5000 (47%)
[epoch 10] loss: 0.6625527
Test set: Average loss: 1.2770, Accuracy: 2401/5000 (48%)
[epoch 11] loss: 0.6257415
Test set: Average loss: 1.2710, Accuracy: 2435/5000 (49%)
[epoch 12] loss: 0.5921496
Test set: Average loss: 1.2695, Accuracy: 2447/5000 (49%)
[epoch 13] loss: 0.5594262
Test set: Average loss: 1.2645, Accuracy: 2440/5000 (49%)
[epoch 14] loss: 0.5334569
Test set: Average loss: 1.2619, Accuracy: 2450/5000 (49%)
[epoch 15] loss: 0.5086819
Test set: Average loss: 1.2562, Accuracy: 2474/5000 (49%)
[epoch 16] loss: 0.4853846
Test set: Average loss: 1.2532, Accuracy: 2482/5000 (50%)
[epoch 17] loss: 0.4656581
Test set: Average loss: 1.2528, Accuracy: 2490/5000 (50%)
[epoch 18] loss: 0.4466027
Test set: Average loss: 1.2468, Accuracy: 2510/5000 (50%)
[epoch 19] loss: 0.4313030
Test set: Average loss: 1.2453, Accuracy: 2505/5000 (50%)
[epoch 20] loss: 0.4142683
Test set: Average loss: 1.2442, Accuracy: 2511/5000 (50%)
[epoch 21] loss: 0.4003103
Test set: Average loss: 1.2423, Accuracy: 2523/5000 (50%)
[epoch 22] loss: 0.3862272
Test set: Average loss: 1.2387, Accuracy: 2514/5000 (50%)
[epoch 23] loss: 0.3746891
Test set: Average loss: 1.2368, Accuracy: 2537/5000 (51%)
[epoch 24] loss: 0.3610646
Test set: Average loss: 1.2345, Accuracy: 2534/5000 (51%)
[epoch 25] loss: 0.3490023
Test set: Average loss: 1.2324, Accuracy: 2542/5000 (51%)
Validation:
Test set: Average loss: 1.2324, Accuracy: 2542/5000 (51%)
Test
Test set: Average loss: 1.2249, Accuracy: 2578/5000 (52%)
Test set: Average loss: 0.3425, Accuracy: 249/250 (100%)
## seed: 13
Validation accuracy before training:
Test set: Average loss: 1.5469, Accuracy: 1967/5000 (39%)
[epoch 1] loss: 1.4605936
Test set: Average loss: 1.3934, Accuracy: 2178/5000 (44%)
[epoch 2] loss: 1.1719400
Test set: Average loss: 1.3142, Accuracy: 2426/5000 (49%)
[epoch 3] loss: 1.0142822
Test set: Average loss: 1.2682, Accuracy: 2611/5000 (52%)
[epoch 4] loss: 0.9010367
Test set: Average loss: 1.2371, Accuracy: 2700/5000 (54%)
[epoch 5] loss: 0.8191283
Test set: Average loss: 1.2163, Accuracy: 2743/5000 (55%)
[epoch 6] loss: 0.7543066
Test set: Average loss: 1.2027, Accuracy: 2791/5000 (56%)
[epoch 7] loss: 0.7001907
Test set: Average loss: 1.1951, Accuracy: 2779/5000 (56%)
[epoch 8] loss: 0.6581337
Test set: Average loss: 1.1879, Accuracy: 2795/5000 (56%)
[epoch 9] loss: 0.6223563
Test set: Average loss: 1.1805, Accuracy: 2812/5000 (56%)
[epoch 10] loss: 0.5905881
Test set: Average loss: 1.1774, Accuracy: 2814/5000 (56%)
[epoch 11] loss: 0.5644261
Test set: Average loss: 1.1735, Accuracy: 2806/5000 (56%)
[epoch 12] loss: 0.5411705
Test set: Average loss: 1.1715, Accuracy: 2807/5000 (56%)
[epoch 13] loss: 0.5181916
Test set: Average loss: 1.1684, Accuracy: 2821/5000 (56%)
[epoch 14] loss: 0.4995788
Test set: Average loss: 1.1673, Accuracy: 2828/5000 (57%)
[epoch 15] loss: 0.4813051
Test set: Average loss: 1.1650, Accuracy: 2821/5000 (56%)
[epoch 16] loss: 0.4645495
Test set: Average loss: 1.1621, Accuracy: 2833/5000 (57%)
[epoch 17] loss: 0.4496824
Test set: Average loss: 1.1609, Accuracy: 2820/5000 (56%)
[epoch 18] loss: 0.4361038
Test set: Average loss: 1.1575, Accuracy: 2823/5000 (56%)
[epoch 19] loss: 0.4224413
Test set: Average loss: 1.1565, Accuracy: 2826/5000 (57%)
[epoch 20] loss: 0.4094221
Test set: Average loss: 1.1582, Accuracy: 2811/5000 (56%)
[epoch 21] loss: 0.3985966
Test set: Average loss: 1.1551, Accuracy: 2821/5000 (56%)
[epoch 22] loss: 0.3883721
Test set: Average loss: 1.1526, Accuracy: 2830/5000 (57%)
[epoch 23] loss: 0.3772600
Test set: Average loss: 1.1518, Accuracy: 2823/5000 (56%)
[epoch 24] loss: 0.3674846
Test set: Average loss: 1.1506, Accuracy: 2822/5000 (56%)
[epoch 25] loss: 0.3590612
Test set: Average loss: 1.1488, Accuracy: 2816/5000 (56%)
Validation:
Test set: Average loss: 1.1621, Accuracy: 2833/5000 (57%)
Test
Test set: Average loss: 1.1827, Accuracy: 2809/5000 (56%)
Test set: Average loss: 0.4533, Accuracy: 249/250 (100%)
500
## seed: 11
Validation accuracy before training:
Test set: Average loss: 1.8051, Accuracy: 627/5000 (13%)
[epoch 1] loss: 1.6220050
Test set: Average loss: 1.4236, Accuracy: 2085/5000 (42%)
[epoch 2] loss: 1.2522508
Test set: Average loss: 1.3157, Accuracy: 2468/5000 (49%)
[epoch 3] loss: 1.0771648
Test set: Average loss: 1.2656, Accuracy: 2626/5000 (53%)
[epoch 4] loss: 0.9582240
Test set: Average loss: 1.2388, Accuracy: 2685/5000 (54%)
[epoch 5] loss: 0.8699519
Test set: Average loss: 1.2220, Accuracy: 2731/5000 (55%)
[epoch 6] loss: 0.7995931
Test set: Average loss: 1.2075, Accuracy: 2765/5000 (55%)
[epoch 7] loss: 0.7421040
Test set: Average loss: 1.1973, Accuracy: 2798/5000 (56%)
[epoch 8] loss: 0.6925791
Test set: Average loss: 1.1890, Accuracy: 2799/5000 (56%)
[epoch 9] loss: 0.6467685
Test set: Average loss: 1.1833, Accuracy: 2801/5000 (56%)
[epoch 10] loss: 0.6100544
Test set: Average loss: 1.1765, Accuracy: 2825/5000 (56%)
[epoch 11] loss: 0.5750036
Test set: Average loss: 1.1717, Accuracy: 2822/5000 (56%)
[epoch 12] loss: 0.5438390
Test set: Average loss: 1.1678, Accuracy: 2823/5000 (56%)
[epoch 13] loss: 0.5158989
Test set: Average loss: 1.1630, Accuracy: 2831/5000 (57%)
[epoch 14] loss: 0.4906144
Test set: Average loss: 1.1600, Accuracy: 2827/5000 (57%)
[epoch 15] loss: 0.4671478
Test set: Average loss: 1.1561, Accuracy: 2842/5000 (57%)
[epoch 16] loss: 0.4469336
Test set: Average loss: 1.1524, Accuracy: 2842/5000 (57%)
[epoch 17] loss: 0.4237006
Test set: Average loss: 1.1514, Accuracy: 2839/5000 (57%)
[epoch 18] loss: 0.4041776
Test set: Average loss: 1.1476, Accuracy: 2849/5000 (57%)
[epoch 19] loss: 0.3882149
Test set: Average loss: 1.1451, Accuracy: 2862/5000 (57%)
[epoch 20] loss: 0.3720962
Test set: Average loss: 1.1433, Accuracy: 2853/5000 (57%)
[epoch 21] loss: 0.3545844
Test set: Average loss: 1.1410, Accuracy: 2859/5000 (57%)
[epoch 22] loss: 0.3410174
Test set: Average loss: 1.1395, Accuracy: 2873/5000 (57%)
[epoch 23] loss: 0.3257268
Test set: Average loss: 1.1380, Accuracy: 2863/5000 (57%)
[epoch 24] loss: 0.3144618
Test set: Average loss: 1.1365, Accuracy: 2869/5000 (57%)
[epoch 25] loss: 0.3037238
Test set: Average loss: 1.1344, Accuracy: 2874/5000 (57%)
Validation:
Test set: Average loss: 1.1344, Accuracy: 2874/5000 (57%)
Test
Test set: Average loss: 1.1380, Accuracy: 2842/5000 (57%)
Test set: Average loss: 0.2931, Accuracy: 496/500 (99%)
## seed: 12
Validation accuracy before training:
Test set: Average loss: 1.6049, Accuracy: 1071/5000 (21%)
[epoch 1] loss: 1.4873703
Test set: Average loss: 1.3883, Accuracy: 2102/5000 (42%)
[epoch 2] loss: 1.2190875
Test set: Average loss: 1.3090, Accuracy: 2458/5000 (49%)
[epoch 3] loss: 1.0768098
Test set: Average loss: 1.2661, Accuracy: 2594/5000 (52%)
[epoch 4] loss: 0.9794271
Test set: Average loss: 1.2351, Accuracy: 2703/5000 (54%)
[epoch 5] loss: 0.9049766
Test set: Average loss: 1.2132, Accuracy: 2792/5000 (56%)
[epoch 6] loss: 0.8424837
Test set: Average loss: 1.1980, Accuracy: 2811/5000 (56%)
[epoch 7] loss: 0.7884165
Test set: Average loss: 1.1831, Accuracy: 2858/5000 (57%)
[epoch 8] loss: 0.7447695
Test set: Average loss: 1.1728, Accuracy: 2870/5000 (57%)
[epoch 9] loss: 0.7061005
Test set: Average loss: 1.1619, Accuracy: 2893/5000 (58%)
[epoch 10] loss: 0.6651302
Test set: Average loss: 1.1544, Accuracy: 2898/5000 (58%)
[epoch 11] loss: 0.6321315
Test set: Average loss: 1.1467, Accuracy: 2907/5000 (58%)
[epoch 12] loss: 0.6038123
Test set: Average loss: 1.1404, Accuracy: 2901/5000 (58%)
[epoch 13] loss: 0.5756921
Test set: Average loss: 1.1346, Accuracy: 2946/5000 (59%)
[epoch 14] loss: 0.5489171
Test set: Average loss: 1.1293, Accuracy: 2954/5000 (59%)
[epoch 15] loss: 0.5279994
Test set: Average loss: 1.1241, Accuracy: 2958/5000 (59%)
[epoch 16] loss: 0.5030479
Test set: Average loss: 1.1198, Accuracy: 2956/5000 (59%)
[epoch 17] loss: 0.4861792
Test set: Average loss: 1.1152, Accuracy: 2966/5000 (59%)
[epoch 18] loss: 0.4665168
Test set: Average loss: 1.1125, Accuracy: 2954/5000 (59%)
[epoch 19] loss: 0.4490642
Test set: Average loss: 1.1087, Accuracy: 2972/5000 (59%)
[epoch 20] loss: 0.4343883
Test set: Average loss: 1.1047, Accuracy: 2967/5000 (59%)
[epoch 21] loss: 0.4185860
Test set: Average loss: 1.1028, Accuracy: 2966/5000 (59%)
[epoch 22] loss: 0.4032416
Test set: Average loss: 1.1003, Accuracy: 2964/5000 (59%)
[epoch 23] loss: 0.3893455
Test set: Average loss: 1.0960, Accuracy: 2972/5000 (59%)
[epoch 24] loss: 0.3762197
Test set: Average loss: 1.0953, Accuracy: 2973/5000 (59%)
[epoch 25] loss: 0.3636849
Test set: Average loss: 1.0931, Accuracy: 2980/5000 (60%)
Validation:
Test set: Average loss: 1.0931, Accuracy: 2980/5000 (60%)
Test
Test set: Average loss: 1.1049, Accuracy: 2894/5000 (58%)
Test set: Average loss: 0.3536, Accuracy: 497/500 (99%)
## seed: 13
Validation accuracy before training:
Test set: Average loss: 1.6950, Accuracy: 672/5000 (13%)
[epoch 1] loss: 1.5108908
Test set: Average loss: 1.3893, Accuracy: 2231/5000 (45%)
[epoch 2] loss: 1.1783062
Test set: Average loss: 1.2998, Accuracy: 2495/5000 (50%)
[epoch 3] loss: 1.0257997
Test set: Average loss: 1.2595, Accuracy: 2586/5000 (52%)
[epoch 4] loss: 0.9119149
Test set: Average loss: 1.2281, Accuracy: 2719/5000 (54%)
[epoch 5] loss: 0.8304948
Test set: Average loss: 1.2091, Accuracy: 2780/5000 (56%)
[epoch 6] loss: 0.7653237
Test set: Average loss: 1.1993, Accuracy: 2804/5000 (56%)
[epoch 7] loss: 0.7096843
Test set: Average loss: 1.1851, Accuracy: 2852/5000 (57%)
[epoch 8] loss: 0.6607083
Test set: Average loss: 1.1770, Accuracy: 2862/5000 (57%)
[epoch 9] loss: 0.6176396
Test set: Average loss: 1.1698, Accuracy: 2875/5000 (58%)
[epoch 10] loss: 0.5784675
Test set: Average loss: 1.1624, Accuracy: 2891/5000 (58%)
[epoch 11] loss: 0.5454803
Test set: Average loss: 1.1586, Accuracy: 2890/5000 (58%)
[epoch 12] loss: 0.5159897
Test set: Average loss: 1.1524, Accuracy: 2906/5000 (58%)
[epoch 13] loss: 0.4878723
Test set: Average loss: 1.1467, Accuracy: 2918/5000 (58%)
[epoch 14] loss: 0.4642367
Test set: Average loss: 1.1467, Accuracy: 2912/5000 (58%)
[epoch 15] loss: 0.4405908
Test set: Average loss: 1.1405, Accuracy: 2920/5000 (58%)
[epoch 16] loss: 0.4216336
Test set: Average loss: 1.1384, Accuracy: 2923/5000 (58%)
[epoch 17] loss: 0.4056457
Test set: Average loss: 1.1338, Accuracy: 2929/5000 (59%)
[epoch 18] loss: 0.3867875
Test set: Average loss: 1.1327, Accuracy: 2918/5000 (58%)
[epoch 19] loss: 0.3722144
Test set: Average loss: 1.1294, Accuracy: 2927/5000 (59%)
[epoch 20] loss: 0.3566284
Test set: Average loss: 1.1270, Accuracy: 2941/5000 (59%)
[epoch 21] loss: 0.3436671
Test set: Average loss: 1.1274, Accuracy: 2914/5000 (58%)
[epoch 22] loss: 0.3320662
Test set: Average loss: 1.1231, Accuracy: 2939/5000 (59%)
[epoch 23] loss: 0.3192853
Test set: Average loss: 1.1242, Accuracy: 2919/5000 (58%)
[epoch 24] loss: 0.3081036
Test set: Average loss: 1.1197, Accuracy: 2941/5000 (59%)
[epoch 25] loss: 0.2981239
Test set: Average loss: 1.1207, Accuracy: 2934/5000 (59%)
Validation:
Test set: Average loss: 1.1197, Accuracy: 2941/5000 (59%)
Test
Test set: Average loss: 1.1340, Accuracy: 2900/5000 (58%)
Test set: Average loss: 0.3000, Accuracy: 497/500 (99%)
750
## seed: 11
Validation accuracy before training:
Test set: Average loss: 1.8792, Accuracy: 378/5000 (8%)
[epoch 1] loss: 1.6659223
Test set: Average loss: 1.4281, Accuracy: 1985/5000 (40%)
[epoch 2] loss: 1.2975172
Test set: Average loss: 1.3225, Accuracy: 2368/5000 (47%)
[epoch 3] loss: 1.1348903
Test set: Average loss: 1.2762, Accuracy: 2485/5000 (50%)
[epoch 4] loss: 1.0406950
Test set: Average loss: 1.2467, Accuracy: 2579/5000 (52%)
[epoch 5] loss: 0.9464739
Test set: Average loss: 1.2297, Accuracy: 2613/5000 (52%)
[epoch 6] loss: 0.8850746
Test set: Average loss: 1.2117, Accuracy: 2679/5000 (54%)
[epoch 7] loss: 0.8200517
Test set: Average loss: 1.2008, Accuracy: 2689/5000 (54%)
[epoch 8] loss: 0.7628302
Test set: Average loss: 1.1906, Accuracy: 2750/5000 (55%)
[epoch 9] loss: 0.7234197
Test set: Average loss: 1.1817, Accuracy: 2763/5000 (55%)
[epoch 10] loss: 0.6764314
Test set: Average loss: 1.1762, Accuracy: 2776/5000 (56%)
[epoch 11] loss: 0.6375602
Test set: Average loss: 1.1670, Accuracy: 2815/5000 (56%)
[epoch 12] loss: 0.6051413
Test set: Average loss: 1.1611, Accuracy: 2824/5000 (56%)
[epoch 13] loss: 0.5725981
Test set: Average loss: 1.1568, Accuracy: 2848/5000 (57%)
[epoch 14] loss: 0.5409999
Test set: Average loss: 1.1508, Accuracy: 2849/5000 (57%)
[epoch 15] loss: 0.5168735
Test set: Average loss: 1.1495, Accuracy: 2866/5000 (57%)
[epoch 16] loss: 0.4923752
Test set: Average loss: 1.1455, Accuracy: 2863/5000 (57%)
[epoch 17] loss: 0.4680388
Test set: Average loss: 1.1413, Accuracy: 2873/5000 (57%)
[epoch 18] loss: 0.4419184
Test set: Average loss: 1.1421, Accuracy: 2873/5000 (57%)
[epoch 19] loss: 0.4233990
Test set: Average loss: 1.1383, Accuracy: 2868/5000 (57%)
[epoch 20] loss: 0.4034098
Test set: Average loss: 1.1378, Accuracy: 2876/5000 (58%)
[epoch 21] loss: 0.3864023
Test set: Average loss: 1.1349, Accuracy: 2878/5000 (58%)
[epoch 22] loss: 0.3658755
Test set: Average loss: 1.1324, Accuracy: 2880/5000 (58%)
[epoch 23] loss: 0.3503419
Test set: Average loss: 1.1290, Accuracy: 2901/5000 (58%)
[epoch 24] loss: 0.3375514
Test set: Average loss: 1.1277, Accuracy: 2889/5000 (58%)
[epoch 25] loss: 0.3190760
Test set: Average loss: 1.1295, Accuracy: 2872/5000 (57%)
Validation:
Test set: Average loss: 1.1290, Accuracy: 2901/5000 (58%)
Test
Test set: Average loss: 1.1256, Accuracy: 2874/5000 (57%)
Test set: Average loss: 0.3363, Accuracy: 747/750 (100%)
## seed: 12
Validation accuracy before training:
Test set: Average loss: 1.6646, Accuracy: 1124/5000 (22%)
[epoch 1] loss: 1.4922858
Test set: Average loss: 1.3429, Accuracy: 2344/5000 (47%)
[epoch 2] loss: 1.1791173
Test set: Average loss: 1.2510, Accuracy: 2667/5000 (53%)
[epoch 3] loss: 1.0324198
Test set: Average loss: 1.2092, Accuracy: 2776/5000 (56%)
[epoch 4] loss: 0.9398797
Test set: Average loss: 1.1847, Accuracy: 2886/5000 (58%)
[epoch 5] loss: 0.8640400
Test set: Average loss: 1.1697, Accuracy: 2886/5000 (58%)
[epoch 6] loss: 0.7998285
Test set: Average loss: 1.1549, Accuracy: 2919/5000 (58%)
[epoch 7] loss: 0.7442411
Test set: Average loss: 1.1455, Accuracy: 2926/5000 (59%)
[epoch 8] loss: 0.6969250
Test set: Average loss: 1.1327, Accuracy: 2960/5000 (59%)
[epoch 9] loss: 0.6560864
Test set: Average loss: 1.1270, Accuracy: 2954/5000 (59%)
[epoch 10] loss: 0.6121363
Test set: Average loss: 1.1169, Accuracy: 2997/5000 (60%)
[epoch 11] loss: 0.5812371
Test set: Average loss: 1.1105, Accuracy: 2993/5000 (60%)
[epoch 12] loss: 0.5448240
Test set: Average loss: 1.1037, Accuracy: 3010/5000 (60%)
[epoch 13] loss: 0.5200619
Test set: Average loss: 1.1036, Accuracy: 3003/5000 (60%)
[epoch 14] loss: 0.4917970
Test set: Average loss: 1.0942, Accuracy: 3002/5000 (60%)
[epoch 15] loss: 0.4656632
Test set: Average loss: 1.0930, Accuracy: 2999/5000 (60%)
[epoch 16] loss: 0.4412576
Test set: Average loss: 1.0903, Accuracy: 3000/5000 (60%)
[epoch 17] loss: 0.4202413
Test set: Average loss: 1.0850, Accuracy: 3011/5000 (60%)
[epoch 18] loss: 0.3995522
Test set: Average loss: 1.0830, Accuracy: 3034/5000 (61%)
[epoch 19] loss: 0.3812403
Test set: Average loss: 1.0838, Accuracy: 2999/5000 (60%)
[epoch 20] loss: 0.3638938
Test set: Average loss: 1.0776, Accuracy: 3029/5000 (61%)
[epoch 21] loss: 0.3465695
Test set: Average loss: 1.0787, Accuracy: 3016/5000 (60%)
[epoch 22] loss: 0.3300454
Test set: Average loss: 1.0759, Accuracy: 3025/5000 (60%)
[epoch 23] loss: 0.3144906
Test set: Average loss: 1.0742, Accuracy: 3020/5000 (60%)
[epoch 24] loss: 0.3013682
Test set: Average loss: 1.0759, Accuracy: 3012/5000 (60%)
[epoch 25] loss: 0.2888803
Test set: Average loss: 1.0747, Accuracy: 3002/5000 (60%)
Validation:
Test set: Average loss: 1.0830, Accuracy: 3034/5000 (61%)
Test
Test set: Average loss: 1.1049, Accuracy: 2960/5000 (59%)
Test set: Average loss: 0.3830, Accuracy: 742/750 (99%)
## seed: 13
Validation accuracy before training:
Test set: Average loss: 1.7986, Accuracy: 472/5000 (9%)
[epoch 1] loss: 1.5691662
Test set: Average loss: 1.3782, Accuracy: 2050/5000 (41%)
[epoch 2] loss: 1.1817443
Test set: Average loss: 1.2736, Accuracy: 2407/5000 (48%)
[epoch 3] loss: 1.0219220
Test set: Average loss: 1.2258, Accuracy: 2559/5000 (51%)
[epoch 4] loss: 0.9094037
Test set: Average loss: 1.1994, Accuracy: 2677/5000 (54%)
[epoch 5] loss: 0.8250235
Test set: Average loss: 1.1810, Accuracy: 2704/5000 (54%)
[epoch 6] loss: 0.7565014
Test set: Average loss: 1.1720, Accuracy: 2765/5000 (55%)
[epoch 7] loss: 0.6973263
Test set: Average loss: 1.1557, Accuracy: 2795/5000 (56%)
[epoch 8] loss: 0.6477687
Test set: Average loss: 1.1514, Accuracy: 2816/5000 (56%)
[epoch 9] loss: 0.6004712
Test set: Average loss: 1.1396, Accuracy: 2851/5000 (57%)
[epoch 10] loss: 0.5693676
Test set: Average loss: 1.1343, Accuracy: 2860/5000 (57%)
[epoch 11] loss: 0.5288203
Test set: Average loss: 1.1303, Accuracy: 2883/5000 (58%)
[epoch 12] loss: 0.4939186
Test set: Average loss: 1.1275, Accuracy: 2868/5000 (57%)
[epoch 13] loss: 0.4657184
Test set: Average loss: 1.1251, Accuracy: 2859/5000 (57%)
[epoch 14] loss: 0.4419777
Test set: Average loss: 1.1213, Accuracy: 2870/5000 (57%)
[epoch 15] loss: 0.4143810
Test set: Average loss: 1.1177, Accuracy: 2884/5000 (58%)
[epoch 16] loss: 0.3952856
Test set: Average loss: 1.1142, Accuracy: 2890/5000 (58%)
[epoch 17] loss: 0.3754192
Test set: Average loss: 1.1143, Accuracy: 2877/5000 (58%)
[epoch 18] loss: 0.3533609
Test set: Average loss: 1.1130, Accuracy: 2899/5000 (58%)
[epoch 19] loss: 0.3377332
Test set: Average loss: 1.1120, Accuracy: 2888/5000 (58%)
[epoch 20] loss: 0.3200149
Test set: Average loss: 1.1104, Accuracy: 2902/5000 (58%)
[epoch 21] loss: 0.3026733
Test set: Average loss: 1.1086, Accuracy: 2917/5000 (58%)
[epoch 22] loss: 0.2891907
Test set: Average loss: 1.1093, Accuracy: 2916/5000 (58%)
[epoch 23] loss: 0.2758794
Test set: Average loss: 1.1088, Accuracy: 2916/5000 (58%)
[epoch 24] loss: 0.2639136
Test set: Average loss: 1.1097, Accuracy: 2905/5000 (58%)
[epoch 25] loss: 0.2508680
Test set: Average loss: 1.1096, Accuracy: 2908/5000 (58%)
Validation:
Test set: Average loss: 1.1086, Accuracy: 2917/5000 (58%)
Test
Test set: Average loss: 1.1265, Accuracy: 2856/5000 (57%)
Test set: Average loss: 0.2912, Accuracy: 744/750 (99%)
1000
## seed: 11
Validation accuracy before training:
Test set: Average loss: 1.5841, Accuracy: 1043/5000 (21%)
[epoch 1] loss: 1.3589664
Test set: Average loss: 1.2689, Accuracy: 2384/5000 (48%)
[epoch 2] loss: 1.0928231
Test set: Average loss: 1.1930, Accuracy: 2693/5000 (54%)
[epoch 3] loss: 0.9652779
Test set: Average loss: 1.1594, Accuracy: 2787/5000 (56%)
[epoch 4] loss: 0.8747244
Test set: Average loss: 1.1381, Accuracy: 2824/5000 (56%)
[epoch 5] loss: 0.8069467
Test set: Average loss: 1.1216, Accuracy: 2891/5000 (58%)
[epoch 6] loss: 0.7530681
Test set: Average loss: 1.1134, Accuracy: 2887/5000 (58%)
[epoch 7] loss: 0.7002820
Test set: Average loss: 1.0994, Accuracy: 2935/5000 (59%)
[epoch 8] loss: 0.6580753
Test set: Average loss: 1.0924, Accuracy: 2927/5000 (59%)
[epoch 9] loss: 0.6167483
Test set: Average loss: 1.0856, Accuracy: 2959/5000 (59%)
[epoch 10] loss: 0.5804788
Test set: Average loss: 1.0790, Accuracy: 2977/5000 (60%)
[epoch 11] loss: 0.5473093
Test set: Average loss: 1.0741, Accuracy: 2988/5000 (60%)
[epoch 12] loss: 0.5133406
Test set: Average loss: 1.0732, Accuracy: 2980/5000 (60%)
[epoch 13] loss: 0.4866462
Test set: Average loss: 1.0646, Accuracy: 3002/5000 (60%)
[epoch 14] loss: 0.4622988
Test set: Average loss: 1.0611, Accuracy: 3010/5000 (60%)
[epoch 15] loss: 0.4422911
Test set: Average loss: 1.0572, Accuracy: 3013/5000 (60%)
[epoch 16] loss: 0.4162782
Test set: Average loss: 1.0553, Accuracy: 3024/5000 (60%)
[epoch 17] loss: 0.3966777
Test set: Average loss: 1.0485, Accuracy: 3040/5000 (61%)
[epoch 18] loss: 0.3751885
Test set: Average loss: 1.0489, Accuracy: 3024/5000 (60%)
[epoch 19] loss: 0.3561313
Test set: Average loss: 1.0443, Accuracy: 3065/5000 (61%)
[epoch 20] loss: 0.3406815
Test set: Average loss: 1.0435, Accuracy: 3053/5000 (61%)
[epoch 21] loss: 0.3199534
Test set: Average loss: 1.0416, Accuracy: 3077/5000 (62%)
[epoch 22] loss: 0.3055176
Test set: Average loss: 1.0423, Accuracy: 3045/5000 (61%)
[epoch 23] loss: 0.2896334
Test set: Average loss: 1.0403, Accuracy: 3065/5000 (61%)
[epoch 24] loss: 0.2757850
Test set: Average loss: 1.0407, Accuracy: 3056/5000 (61%)
[epoch 25] loss: 0.2623887
Test set: Average loss: 1.0386, Accuracy: 3058/5000 (61%)
Validation:
Test set: Average loss: 1.0416, Accuracy: 3077/5000 (62%)
Test
Test set: Average loss: 1.0549, Accuracy: 3017/5000 (60%)
Test set: Average loss: 0.3073, Accuracy: 997/1000 (100%)
## seed: 12
Validation accuracy before training:
Test set: Average loss: 1.8358, Accuracy: 492/5000 (10%)
[epoch 1] loss: 1.5370795
Test set: Average loss: 1.3522, Accuracy: 2381/5000 (48%)
[epoch 2] loss: 1.1673854
Test set: Average loss: 1.2571, Accuracy: 2608/5000 (52%)
[epoch 3] loss: 1.0228179
Test set: Average loss: 1.2136, Accuracy: 2743/5000 (55%)
[epoch 4] loss: 0.9227988
Test set: Average loss: 1.1841, Accuracy: 2844/5000 (57%)
[epoch 5] loss: 0.8352123
Test set: Average loss: 1.1622, Accuracy: 2888/5000 (58%)
[epoch 6] loss: 0.7701341
Test set: Average loss: 1.1518, Accuracy: 2919/5000 (58%)
[epoch 7] loss: 0.7144228
Test set: Average loss: 1.1466, Accuracy: 2936/5000 (59%)
[epoch 8] loss: 0.6651882
Test set: Average loss: 1.1290, Accuracy: 2958/5000 (59%)
[epoch 9] loss: 0.6283278
Test set: Average loss: 1.1221, Accuracy: 2963/5000 (59%)
[epoch 10] loss: 0.5861840
Test set: Average loss: 1.1148, Accuracy: 2997/5000 (60%)
[epoch 11] loss: 0.5435825
Test set: Average loss: 1.1043, Accuracy: 3016/5000 (60%)
[epoch 12] loss: 0.5154156
Test set: Average loss: 1.1074, Accuracy: 2981/5000 (60%)
[epoch 13] loss: 0.4881658
Test set: Average loss: 1.0994, Accuracy: 2996/5000 (60%)
[epoch 14] loss: 0.4541303
Test set: Average loss: 1.0928, Accuracy: 3003/5000 (60%)
[epoch 15] loss: 0.4282007
Test set: Average loss: 1.0929, Accuracy: 3005/5000 (60%)
[epoch 16] loss: 0.4042505
Test set: Average loss: 1.0847, Accuracy: 3020/5000 (60%)
[epoch 17] loss: 0.3821067
Test set: Average loss: 1.0843, Accuracy: 3019/5000 (60%)
[epoch 18] loss: 0.3625664
Test set: Average loss: 1.0866, Accuracy: 2997/5000 (60%)
[epoch 19] loss: 0.3403274
Test set: Average loss: 1.0797, Accuracy: 3020/5000 (60%)
[epoch 20] loss: 0.3261266
Test set: Average loss: 1.0810, Accuracy: 3005/5000 (60%)
[epoch 21] loss: 0.3100105
Test set: Average loss: 1.0758, Accuracy: 3016/5000 (60%)
[epoch 22] loss: 0.2908393
Test set: Average loss: 1.0751, Accuracy: 3014/5000 (60%)
[epoch 23] loss: 0.2761339
Test set: Average loss: 1.0773, Accuracy: 3005/5000 (60%)
[epoch 24] loss: 0.2610226
Test set: Average loss: 1.0753, Accuracy: 3003/5000 (60%)
[epoch 25] loss: 0.2480000
Test set: Average loss: 1.0794, Accuracy: 3006/5000 (60%)
Validation:
Test set: Average loss: 1.0797, Accuracy: 3020/5000 (60%)
Test
Test set: Average loss: 1.0947, Accuracy: 2921/5000 (58%)
Test set: Average loss: 0.3253, Accuracy: 993/1000 (99%)
## seed: 13
Validation accuracy before training:
Test set: Average loss: 1.7418, Accuracy: 984/5000 (20%)
[epoch 1] loss: 1.4521340
Test set: Average loss: 1.2977, Accuracy: 2564/5000 (51%)
[epoch 2] loss: 1.1256516
Test set: Average loss: 1.2086, Accuracy: 2847/5000 (57%)
[epoch 3] loss: 0.9710901
Test set: Average loss: 1.1663, Accuracy: 2962/5000 (59%)
[epoch 4] loss: 0.8775282
Test set: Average loss: 1.1465, Accuracy: 2980/5000 (60%)
[epoch 5] loss: 0.7997691
Test set: Average loss: 1.1271, Accuracy: 3042/5000 (61%)
[epoch 6] loss: 0.7277281
Test set: Average loss: 1.1123, Accuracy: 3034/5000 (61%)
[epoch 7] loss: 0.6748481
Test set: Average loss: 1.1009, Accuracy: 3073/5000 (61%)
[epoch 8] loss: 0.6196375
Test set: Average loss: 1.0931, Accuracy: 3081/5000 (62%)
[epoch 9] loss: 0.5805673
Test set: Average loss: 1.0862, Accuracy: 3078/5000 (62%)
[epoch 10] loss: 0.5385406
Test set: Average loss: 1.0776, Accuracy: 3103/5000 (62%)
[epoch 11] loss: 0.5117275
Test set: Average loss: 1.0704, Accuracy: 3114/5000 (62%)
[epoch 12] loss: 0.4755743
Test set: Average loss: 1.0680, Accuracy: 3123/5000 (62%)
[epoch 13] loss: 0.4438971
Test set: Average loss: 1.0601, Accuracy: 3131/5000 (63%)
[epoch 14] loss: 0.4198353
Test set: Average loss: 1.0560, Accuracy: 3121/5000 (62%)
[epoch 15] loss: 0.3966720
Test set: Average loss: 1.0574, Accuracy: 3125/5000 (62%)
[epoch 16] loss: 0.3697739
Test set: Average loss: 1.0496, Accuracy: 3130/5000 (63%)
[epoch 17] loss: 0.3459671
Test set: Average loss: 1.0520, Accuracy: 3122/5000 (62%)
[epoch 18] loss: 0.3273115
Test set: Average loss: 1.0497, Accuracy: 3139/5000 (63%)
[epoch 19] loss: 0.3102008
Test set: Average loss: 1.0457, Accuracy: 3130/5000 (63%)
[epoch 20] loss: 0.2953841
Test set: Average loss: 1.0456, Accuracy: 3120/5000 (62%)
[epoch 21] loss: 0.2804322
Test set: Average loss: 1.0429, Accuracy: 3113/5000 (62%)
[epoch 22] loss: 0.2615622
Test set: Average loss: 1.0403, Accuracy: 3123/5000 (62%)
[epoch 23] loss: 0.2490986
Test set: Average loss: 1.0443, Accuracy: 3112/5000 (62%)
[epoch 24] loss: 0.2382858
Test set: Average loss: 1.0421, Accuracy: 3116/5000 (62%)
[epoch 25] loss: 0.2261592
Test set: Average loss: 1.0412, Accuracy: 3109/5000 (62%)
Validation:
Test set: Average loss: 1.0497, Accuracy: 3139/5000 (63%)
Test
Test set: Average loss: 1.0689, Accuracy: 3035/5000 (61%)
Test set: Average loss: 0.3129, Accuracy: 987/1000 (99%)
2500
## seed: 11
Validation accuracy before training:
Test set: Average loss: 1.6745, Accuracy: 1114/5000 (22%)
[epoch 1] loss: 1.3103427
Test set: Average loss: 1.1893, Accuracy: 2781/5000 (56%)
[epoch 2] loss: 1.0476799
Test set: Average loss: 1.1288, Accuracy: 2978/5000 (60%)
[epoch 3] loss: 0.9350857
Test set: Average loss: 1.0954, Accuracy: 3073/5000 (61%)
[epoch 4] loss: 0.8441695
Test set: Average loss: 1.0753, Accuracy: 3112/5000 (62%)
[epoch 5] loss: 0.7673343
Test set: Average loss: 1.0521, Accuracy: 3144/5000 (63%)
[epoch 6] loss: 0.7112154
Test set: Average loss: 1.0329, Accuracy: 3180/5000 (64%)
[epoch 7] loss: 0.6421958
Test set: Average loss: 1.0187, Accuracy: 3192/5000 (64%)
[epoch 8] loss: 0.5823748
Test set: Average loss: 1.0072, Accuracy: 3180/5000 (64%)
[epoch 9] loss: 0.5352727
Test set: Average loss: 0.9972, Accuracy: 3208/5000 (64%)
[epoch 10] loss: 0.4870013
Test set: Average loss: 0.9821, Accuracy: 3244/5000 (65%)
[epoch 11] loss: 0.4404483
Test set: Average loss: 0.9878, Accuracy: 3221/5000 (64%)
[epoch 12] loss: 0.4050710
Test set: Average loss: 0.9698, Accuracy: 3253/5000 (65%)
[epoch 13] loss: 0.3685880
Test set: Average loss: 0.9710, Accuracy: 3237/5000 (65%)
[epoch 14] loss: 0.3316428
Test set: Average loss: 0.9585, Accuracy: 3270/5000 (65%)
[epoch 15] loss: 0.3008297
Test set: Average loss: 0.9542, Accuracy: 3278/5000 (66%)
[epoch 16] loss: 0.2744459
Test set: Average loss: 0.9501, Accuracy: 3289/5000 (66%)
[epoch 17] loss: 0.2486878
Test set: Average loss: 0.9532, Accuracy: 3286/5000 (66%)
[epoch 18] loss: 0.2234646
Test set: Average loss: 0.9524, Accuracy: 3279/5000 (66%)
[epoch 19] loss: 0.2013299
Test set: Average loss: 0.9483, Accuracy: 3266/5000 (65%)
[epoch 20] loss: 0.1825775
Test set: Average loss: 0.9441, Accuracy: 3279/5000 (66%)
[epoch 21] loss: 0.1664344
Test set: Average loss: 0.9442, Accuracy: 3259/5000 (65%)
[epoch 22] loss: 0.1516507
Test set: Average loss: 0.9480, Accuracy: 3247/5000 (65%)
[epoch 23] loss: 0.1383847
Test set: Average loss: 0.9490, Accuracy: 3267/5000 (65%)
[epoch 24] loss: 0.1262098
Test set: Average loss: 0.9529, Accuracy: 3274/5000 (65%)
[epoch 25] loss: 0.1162847
Test set: Average loss: 0.9604, Accuracy: 3262/5000 (65%)
Validation:
Test set: Average loss: 0.9501, Accuracy: 3289/5000 (66%)
Test
Test set: Average loss: 0.9574, Accuracy: 3232/5000 (65%)
Test set: Average loss: 0.2441, Accuracy: 2472/2500 (99%)
## seed: 12
Validation accuracy before training:
Test set: Average loss: 1.6567, Accuracy: 1081/5000 (22%)
[epoch 1] loss: 1.2878480
Test set: Average loss: 1.1772, Accuracy: 2752/5000 (55%)
[epoch 2] loss: 1.0322097
Test set: Average loss: 1.1132, Accuracy: 2927/5000 (59%)
[epoch 3] loss: 0.9185367
Test set: Average loss: 1.0842, Accuracy: 3001/5000 (60%)
[epoch 4] loss: 0.8430748
Test set: Average loss: 1.0562, Accuracy: 3064/5000 (61%)
[epoch 5] loss: 0.7704371
Test set: Average loss: 1.0416, Accuracy: 3087/5000 (62%)
[epoch 6] loss: 0.7014177
Test set: Average loss: 1.0258, Accuracy: 3132/5000 (63%)
[epoch 7] loss: 0.6377846
Test set: Average loss: 1.0094, Accuracy: 3154/5000 (63%)
[epoch 8] loss: 0.5871767
Test set: Average loss: 0.9943, Accuracy: 3196/5000 (64%)
[epoch 9] loss: 0.5325480
Test set: Average loss: 0.9909, Accuracy: 3194/5000 (64%)
[epoch 10] loss: 0.4878081
Test set: Average loss: 0.9765, Accuracy: 3200/5000 (64%)
[epoch 11] loss: 0.4429439
Test set: Average loss: 0.9693, Accuracy: 3218/5000 (64%)
[epoch 12] loss: 0.4042976
Test set: Average loss: 0.9633, Accuracy: 3239/5000 (65%)
[epoch 13] loss: 0.3685240
Test set: Average loss: 0.9591, Accuracy: 3232/5000 (65%)
[epoch 14] loss: 0.3343071
Test set: Average loss: 0.9529, Accuracy: 3236/5000 (65%)
[epoch 15] loss: 0.3072311
Test set: Average loss: 0.9530, Accuracy: 3244/5000 (65%)
[epoch 16] loss: 0.2757625
Test set: Average loss: 0.9528, Accuracy: 3241/5000 (65%)
[epoch 17] loss: 0.2495141
Test set: Average loss: 0.9495, Accuracy: 3237/5000 (65%)
[epoch 18] loss: 0.2281683
Test set: Average loss: 0.9454, Accuracy: 3239/5000 (65%)
[epoch 19] loss: 0.2104122
Test set: Average loss: 0.9445, Accuracy: 3257/5000 (65%)
[epoch 20] loss: 0.1912101
Test set: Average loss: 0.9445, Accuracy: 3239/5000 (65%)
[epoch 21] loss: 0.1723450
Test set: Average loss: 0.9457, Accuracy: 3257/5000 (65%)
[epoch 22] loss: 0.1574876
Test set: Average loss: 0.9455, Accuracy: 3256/5000 (65%)
[epoch 23] loss: 0.1414299
Test set: Average loss: 0.9460, Accuracy: 3244/5000 (65%)
[epoch 24] loss: 0.1292384
Test set: Average loss: 0.9473, Accuracy: 3240/5000 (65%)
[epoch 25] loss: 0.1194764
Test set: Average loss: 0.9520, Accuracy: 3261/5000 (65%)
Validation:
Test set: Average loss: 0.9520, Accuracy: 3261/5000 (65%)
Test
Test set: Average loss: 0.9746, Accuracy: 3189/5000 (64%)
Test set: Average loss: 0.1105, Accuracy: 2498/2500 (100%)
## seed: 13
Validation accuracy before training:
Test set: Average loss: 1.9306, Accuracy: 400/5000 (8%)
[epoch 1] loss: 1.4224309
Test set: Average loss: 1.2618, Accuracy: 2527/5000 (51%)
[epoch 2] loss: 1.1429015
Test set: Average loss: 1.1832, Accuracy: 2771/5000 (55%)
[epoch 3] loss: 1.0262956
Test set: Average loss: 1.1406, Accuracy: 2954/5000 (59%)
[epoch 4] loss: 0.9308781
Test set: Average loss: 1.1152, Accuracy: 2999/5000 (60%)
[epoch 5] loss: 0.8599341
Test set: Average loss: 1.0919, Accuracy: 3019/5000 (60%)
[epoch 6] loss: 0.7904705
Test set: Average loss: 1.0667, Accuracy: 3075/5000 (62%)
[epoch 7] loss: 0.7271625
Test set: Average loss: 1.0556, Accuracy: 3079/5000 (62%)
[epoch 8] loss: 0.6759828
Test set: Average loss: 1.0388, Accuracy: 3132/5000 (63%)
[epoch 9] loss: 0.6207921
Test set: Average loss: 1.0234, Accuracy: 3161/5000 (63%)
[epoch 10] loss: 0.5649991
Test set: Average loss: 1.0132, Accuracy: 3171/5000 (63%)
[epoch 11] loss: 0.5117928
Test set: Average loss: 1.0094, Accuracy: 3188/5000 (64%)
[epoch 12] loss: 0.4715399
Test set: Average loss: 0.9982, Accuracy: 3185/5000 (64%)
[epoch 13] loss: 0.4310556
Test set: Average loss: 0.9911, Accuracy: 3206/5000 (64%)
[epoch 14] loss: 0.3912553
Test set: Average loss: 0.9850, Accuracy: 3207/5000 (64%)
[epoch 15] loss: 0.3536800
Test set: Average loss: 0.9846, Accuracy: 3198/5000 (64%)
[epoch 16] loss: 0.3196780
Test set: Average loss: 0.9716, Accuracy: 3233/5000 (65%)
[epoch 17] loss: 0.2891184
Test set: Average loss: 0.9745, Accuracy: 3223/5000 (64%)
[epoch 18] loss: 0.2633717
Test set: Average loss: 0.9679, Accuracy: 3223/5000 (64%)
[epoch 19] loss: 0.2394633
Test set: Average loss: 0.9664, Accuracy: 3232/5000 (65%)
[epoch 20] loss: 0.2157543
Test set: Average loss: 0.9742, Accuracy: 3211/5000 (64%)
[epoch 21] loss: 0.1962483
Test set: Average loss: 0.9756, Accuracy: 3228/5000 (65%)
[epoch 22] loss: 0.1771102
Test set: Average loss: 0.9672, Accuracy: 3229/5000 (65%)
[epoch 23] loss: 0.1608034
Test set: Average loss: 0.9651, Accuracy: 3251/5000 (65%)
[epoch 24] loss: 0.1462708
Test set: Average loss: 0.9658, Accuracy: 3223/5000 (64%)
[epoch 25] loss: 0.1332538
Test set: Average loss: 0.9684, Accuracy: 3231/5000 (65%)
Validation:
Test set: Average loss: 0.9651, Accuracy: 3251/5000 (65%)
Test
Test set: Average loss: 0.9988, Accuracy: 3142/5000 (63%)
Test set: Average loss: 0.1464, Accuracy: 2497/2500 (100%)
5000
## seed: 11
Validation accuracy before training:
Test set: Average loss: 1.6249, Accuracy: 1090/5000 (22%)
[epoch 1] loss: 1.2109178
Test set: Average loss: 1.1179, Accuracy: 3021/5000 (60%)
[epoch 2] loss: 0.9840046
Test set: Average loss: 1.0646, Accuracy: 3127/5000 (63%)
[epoch 3] loss: 0.8705950
Test set: Average loss: 1.0222, Accuracy: 3175/5000 (64%)
[epoch 4] loss: 0.7758470
Test set: Average loss: 0.9984, Accuracy: 3206/5000 (64%)
[epoch 5] loss: 0.6913961
Test set: Average loss: 0.9739, Accuracy: 3257/5000 (65%)
[epoch 6] loss: 0.6208911
Test set: Average loss: 0.9614, Accuracy: 3262/5000 (65%)
[epoch 7] loss: 0.5497946
Test set: Average loss: 0.9436, Accuracy: 3290/5000 (66%)
[epoch 8] loss: 0.4862338
Test set: Average loss: 0.9374, Accuracy: 3283/5000 (66%)
[epoch 9] loss: 0.4301640
Test set: Average loss: 0.9258, Accuracy: 3316/5000 (66%)
[epoch 10] loss: 0.3760373
Test set: Average loss: 0.9166, Accuracy: 3332/5000 (67%)
[epoch 11] loss: 0.3280444
Test set: Average loss: 0.9199, Accuracy: 3317/5000 (66%)
[epoch 12] loss: 0.2865295
Test set: Average loss: 0.9135, Accuracy: 3323/5000 (66%)
[epoch 13] loss: 0.2499739
Test set: Average loss: 0.9108, Accuracy: 3327/5000 (67%)
[epoch 14] loss: 0.2170147
Test set: Average loss: 0.9063, Accuracy: 3329/5000 (67%)
[epoch 15] loss: 0.1866096
Test set: Average loss: 0.9142, Accuracy: 3330/5000 (67%)
[epoch 16] loss: 0.1632519
Test set: Average loss: 0.9206, Accuracy: 3314/5000 (66%)
[epoch 17] loss: 0.1422336
Test set: Average loss: 0.9246, Accuracy: 3322/5000 (66%)
[epoch 18] loss: 0.1230041
Test set: Average loss: 0.9370, Accuracy: 3322/5000 (66%)
[epoch 19] loss: 0.1080127
Test set: Average loss: 0.9300, Accuracy: 3357/5000 (67%)
[epoch 20] loss: 0.0927031
Test set: Average loss: 0.9344, Accuracy: 3344/5000 (67%)
[epoch 21] loss: 0.0826438
Test set: Average loss: 0.9413, Accuracy: 3339/5000 (67%)
[epoch 22] loss: 0.0712500
Test set: Average loss: 0.9525, Accuracy: 3339/5000 (67%)
[epoch 23] loss: 0.0618523
Test set: Average loss: 0.9582, Accuracy: 3357/5000 (67%)
[epoch 24] loss: 0.0547796
Test set: Average loss: 0.9647, Accuracy: 3334/5000 (67%)
[epoch 25] loss: 0.0482941
Test set: Average loss: 0.9731, Accuracy: 3324/5000 (66%)
Validation:
Test set: Average loss: 0.9582, Accuracy: 3357/5000 (67%)
Test
Test set: Average loss: 0.9539, Accuracy: 3369/5000 (67%)
Test set: Average loss: 0.0547, Accuracy: 4998/5000 (100%)
## seed: 12
Validation accuracy before training:
Test set: Average loss: 1.7608, Accuracy: 627/5000 (13%)
[epoch 1] loss: 1.2399512
Test set: Average loss: 1.1239, Accuracy: 2932/5000 (59%)
[epoch 2] loss: 0.9824969
Test set: Average loss: 1.0594, Accuracy: 3126/5000 (63%)
[epoch 3] loss: 0.8633812
Test set: Average loss: 1.0194, Accuracy: 3189/5000 (64%)
[epoch 4] loss: 0.7651117
Test set: Average loss: 0.9924, Accuracy: 3256/5000 (65%)
[epoch 5] loss: 0.6819876
Test set: Average loss: 0.9685, Accuracy: 3265/5000 (65%)
[epoch 6] loss: 0.6039771
Test set: Average loss: 0.9477, Accuracy: 3318/5000 (66%)
[epoch 7] loss: 0.5397111
Test set: Average loss: 0.9348, Accuracy: 3334/5000 (67%)
[epoch 8] loss: 0.4761137
Test set: Average loss: 0.9206, Accuracy: 3376/5000 (68%)
[epoch 9] loss: 0.4142043
Test set: Average loss: 0.9123, Accuracy: 3383/5000 (68%)
[epoch 10] loss: 0.3619915
Test set: Average loss: 0.9051, Accuracy: 3380/5000 (68%)
[epoch 11] loss: 0.3118717
Test set: Average loss: 0.8986, Accuracy: 3383/5000 (68%)
[epoch 12] loss: 0.2715264
Test set: Average loss: 0.9006, Accuracy: 3374/5000 (67%)
[epoch 13] loss: 0.2311244
Test set: Average loss: 0.8939, Accuracy: 3386/5000 (68%)
[epoch 14] loss: 0.2012290
Test set: Average loss: 0.8967, Accuracy: 3400/5000 (68%)
[epoch 15] loss: 0.1709685
Test set: Average loss: 0.8952, Accuracy: 3394/5000 (68%)
[epoch 16] loss: 0.1462772
Test set: Average loss: 0.8960, Accuracy: 3410/5000 (68%)
[epoch 17] loss: 0.1258627
Test set: Average loss: 0.8979, Accuracy: 3417/5000 (68%)
[epoch 18] loss: 0.1087202
Test set: Average loss: 0.9033, Accuracy: 3396/5000 (68%)
[epoch 19] loss: 0.0941799
Test set: Average loss: 0.9026, Accuracy: 3402/5000 (68%)
[epoch 20] loss: 0.0810451
Test set: Average loss: 0.9060, Accuracy: 3392/5000 (68%)
[epoch 21] loss: 0.0703831
Test set: Average loss: 0.9109, Accuracy: 3418/5000 (68%)
[epoch 22] loss: 0.0617928
Test set: Average loss: 0.9163, Accuracy: 3395/5000 (68%)
[epoch 23] loss: 0.0533244
Test set: Average loss: 0.9194, Accuracy: 3425/5000 (68%)
[epoch 24] loss: 0.0469149
Test set: Average loss: 0.9249, Accuracy: 3417/5000 (68%)
[epoch 25] loss: 0.0413695
Test set: Average loss: 0.9325, Accuracy: 3418/5000 (68%)
Validation:
Test set: Average loss: 0.9194, Accuracy: 3425/5000 (68%)
Test
Test set: Average loss: 0.9483, Accuracy: 3314/5000 (66%)
Test set: Average loss: 0.0471, Accuracy: 4999/5000 (100%)
## seed: 13
Validation accuracy before training:
Test set: Average loss: 1.9123, Accuracy: 432/5000 (9%)
[epoch 1] loss: 1.3085091
Test set: Average loss: 1.1702, Accuracy: 2775/5000 (56%)
[epoch 2] loss: 1.0368317
Test set: Average loss: 1.0878, Accuracy: 3027/5000 (61%)
[epoch 3] loss: 0.9127009
Test set: Average loss: 1.0524, Accuracy: 3120/5000 (62%)
[epoch 4] loss: 0.8145765
Test set: Average loss: 1.0104, Accuracy: 3215/5000 (64%)
[epoch 5] loss: 0.7287571
Test set: Average loss: 0.9892, Accuracy: 3236/5000 (65%)
[epoch 6] loss: 0.6493048
Test set: Average loss: 0.9650, Accuracy: 3291/5000 (66%)
[epoch 7] loss: 0.5786299
Test set: Average loss: 0.9469, Accuracy: 3319/5000 (66%)
[epoch 8] loss: 0.5138376
Test set: Average loss: 0.9493, Accuracy: 3271/5000 (65%)
[epoch 9] loss: 0.4489593
Test set: Average loss: 0.9320, Accuracy: 3308/5000 (66%)
[epoch 10] loss: 0.3926197
Test set: Average loss: 0.9174, Accuracy: 3324/5000 (66%)
[epoch 11] loss: 0.3417062
Test set: Average loss: 0.9199, Accuracy: 3321/5000 (66%)
[epoch 12] loss: 0.2926183
Test set: Average loss: 0.9131, Accuracy: 3318/5000 (66%)
[epoch 13] loss: 0.2511712
Test set: Average loss: 0.9083, Accuracy: 3335/5000 (67%)
[epoch 14] loss: 0.2177527
Test set: Average loss: 0.9065, Accuracy: 3339/5000 (67%)
[epoch 15] loss: 0.1852462
Test set: Average loss: 0.9115, Accuracy: 3334/5000 (67%)
[epoch 16] loss: 0.1593293
Test set: Average loss: 0.9268, Accuracy: 3313/5000 (66%)
[epoch 17] loss: 0.1352279
Test set: Average loss: 0.9164, Accuracy: 3319/5000 (66%)
[epoch 18] loss: 0.1159184
Test set: Average loss: 0.9313, Accuracy: 3326/5000 (67%)
[epoch 19] loss: 0.0999870
Test set: Average loss: 0.9251, Accuracy: 3317/5000 (66%)
[epoch 20] loss: 0.0856779
Test set: Average loss: 0.9306, Accuracy: 3345/5000 (67%)
[epoch 21] loss: 0.0739477
Test set: Average loss: 0.9347, Accuracy: 3319/5000 (66%)
[epoch 22] loss: 0.0647645
Test set: Average loss: 0.9378, Accuracy: 3312/5000 (66%)
[epoch 23] loss: 0.0568206
Test set: Average loss: 0.9441, Accuracy: 3315/5000 (66%)
[epoch 24] loss: 0.0498209
Test set: Average loss: 0.9558, Accuracy: 3314/5000 (66%)
[epoch 25] loss: 0.0436520
Test set: Average loss: 0.9676, Accuracy: 3299/5000 (66%)
Validation:
Test set: Average loss: 0.9306, Accuracy: 3345/5000 (67%)
Test
Test set: Average loss: 0.9276, Accuracy: 3345/5000 (67%)
Test set: Average loss: 0.0746, Accuracy: 4997/5000 (100%)
10000
## seed: 11
Validation accuracy before training:
Test set: Average loss: 1.6331, Accuracy: 1044/5000 (21%)
[epoch 1] loss: 1.1206432
Test set: Average loss: 1.0519, Accuracy: 3158/5000 (63%)
[epoch 2] loss: 0.9068914
Test set: Average loss: 0.9875, Accuracy: 3317/5000 (66%)
[epoch 3] loss: 0.7893285
Test set: Average loss: 0.9432, Accuracy: 3350/5000 (67%)
[epoch 4] loss: 0.6843599
Test set: Average loss: 0.9114, Accuracy: 3401/5000 (68%)
[epoch 5] loss: 0.5883679
Test set: Average loss: 0.8921, Accuracy: 3428/5000 (69%)
[epoch 6] loss: 0.5012337
Test set: Average loss: 0.8710, Accuracy: 3446/5000 (69%)
[epoch 7] loss: 0.4221590
Test set: Average loss: 0.8533, Accuracy: 3465/5000 (69%)
[epoch 8] loss: 0.3495430
Test set: Average loss: 0.8487, Accuracy: 3448/5000 (69%)
[epoch 9] loss: 0.2870433
Test set: Average loss: 0.8388, Accuracy: 3477/5000 (70%)
[epoch 10] loss: 0.2338232
Test set: Average loss: 0.8474, Accuracy: 3489/5000 (70%)
[epoch 11] loss: 0.1883725
Test set: Average loss: 0.8500, Accuracy: 3449/5000 (69%)
[epoch 12] loss: 0.1511415
Test set: Average loss: 0.8495, Accuracy: 3516/5000 (70%)
[epoch 13] loss: 0.1176054
Test set: Average loss: 0.8570, Accuracy: 3476/5000 (70%)
[epoch 14] loss: 0.0951346
Test set: Average loss: 0.8656, Accuracy: 3475/5000 (70%)
[epoch 15] loss: 0.0751694
Test set: Average loss: 0.8733, Accuracy: 3471/5000 (69%)
[epoch 16] loss: 0.0644387
Test set: Average loss: 0.8852, Accuracy: 3461/5000 (69%)
[epoch 17] loss: 0.0539628
Test set: Average loss: 0.9057, Accuracy: 3467/5000 (69%)
[epoch 18] loss: 0.0397107
Test set: Average loss: 0.9175, Accuracy: 3462/5000 (69%)
[epoch 19] loss: 0.0304998
Test set: Average loss: 0.9258, Accuracy: 3475/5000 (70%)
[epoch 20] loss: 0.0242081
Test set: Average loss: 0.9366, Accuracy: 3478/5000 (70%)
[epoch 21] loss: 0.0197861
Test set: Average loss: 0.9468, Accuracy: 3487/5000 (70%)
[epoch 22] loss: 0.0164909
Test set: Average loss: 0.9612, Accuracy: 3491/5000 (70%)
[epoch 23] loss: 0.0136068
Test set: Average loss: 0.9692, Accuracy: 3480/5000 (70%)
[epoch 24] loss: 0.0114076
Test set: Average loss: 0.9789, Accuracy: 3489/5000 (70%)
[epoch 25] loss: 0.0095284
Test set: Average loss: 1.0045, Accuracy: 3467/5000 (69%)
Validation:
Test set: Average loss: 0.8495, Accuracy: 3516/5000 (70%)
Test
Test set: Average loss: 0.8695, Accuracy: 3402/5000 (68%)
Test set: Average loss: 0.1189, Accuracy: 9953/10000 (100%)
## seed: 12
Validation accuracy before training:
Test set: Average loss: 1.6211, Accuracy: 1243/5000 (25%)
[epoch 1] loss: 1.1159658
Test set: Average loss: 1.0344, Accuracy: 3184/5000 (64%)
[epoch 2] loss: 0.8874704
Test set: Average loss: 0.9650, Accuracy: 3337/5000 (67%)
[epoch 3] loss: 0.7614655
Test set: Average loss: 0.9222, Accuracy: 3372/5000 (67%)
[epoch 4] loss: 0.6555653
Test set: Average loss: 0.8944, Accuracy: 3385/5000 (68%)
[epoch 5] loss: 0.5626653
Test set: Average loss: 0.8673, Accuracy: 3413/5000 (68%)
[epoch 6] loss: 0.4814601
Test set: Average loss: 0.8583, Accuracy: 3418/5000 (68%)
[epoch 7] loss: 0.4052744
Test set: Average loss: 0.8475, Accuracy: 3434/5000 (69%)
[epoch 8] loss: 0.3391411
Test set: Average loss: 0.8536, Accuracy: 3421/5000 (68%)
[epoch 9] loss: 0.2789880
Test set: Average loss: 0.8453, Accuracy: 3431/5000 (69%)
[epoch 10] loss: 0.2265842
Test set: Average loss: 0.8421, Accuracy: 3443/5000 (69%)
[epoch 11] loss: 0.1826373
Test set: Average loss: 0.8340, Accuracy: 3473/5000 (69%)
[epoch 12] loss: 0.1451888
Test set: Average loss: 0.8496, Accuracy: 3444/5000 (69%)
[epoch 13] loss: 0.1169076
Test set: Average loss: 0.8576, Accuracy: 3429/5000 (69%)
[epoch 14] loss: 0.0912211
Test set: Average loss: 0.8638, Accuracy: 3470/5000 (69%)
[epoch 15] loss: 0.0726870
Test set: Average loss: 0.8732, Accuracy: 3469/5000 (69%)
[epoch 16] loss: 0.0575219
Test set: Average loss: 0.8779, Accuracy: 3475/5000 (70%)
[epoch 17] loss: 0.0462451
Test set: Average loss: 0.8992, Accuracy: 3453/5000 (69%)
[epoch 18] loss: 0.0384314
Test set: Average loss: 0.9031, Accuracy: 3460/5000 (69%)
[epoch 19] loss: 0.0298795
Test set: Average loss: 0.9174, Accuracy: 3470/5000 (69%)
[epoch 20] loss: 0.0231819
Test set: Average loss: 0.9308, Accuracy: 3478/5000 (70%)
[epoch 21] loss: 0.0188955
Test set: Average loss: 0.9417, Accuracy: 3474/5000 (69%)
[epoch 22] loss: 0.0156807
Test set: Average loss: 0.9533, Accuracy: 3473/5000 (69%)
[epoch 23] loss: 0.0129389
Test set: Average loss: 0.9616, Accuracy: 3492/5000 (70%)
[epoch 24] loss: 0.0107354
Test set: Average loss: 0.9771, Accuracy: 3478/5000 (70%)
[epoch 25] loss: 0.0089235
Test set: Average loss: 0.9914, Accuracy: 3481/5000 (70%)
Validation:
Test set: Average loss: 0.9616, Accuracy: 3492/5000 (70%)
Test
Test set: Average loss: 0.9935, Accuracy: 3443/5000 (69%)
Test set: Average loss: 0.0114, Accuracy: 10000/10000 (100%)
## seed: 13
Validation accuracy before training:
Test set: Average loss: 1.5574, Accuracy: 1262/5000 (25%)
[epoch 1] loss: 1.0526042
Test set: Average loss: 1.0229, Accuracy: 3161/5000 (63%)
[epoch 2] loss: 0.8427499
Test set: Average loss: 0.9604, Accuracy: 3310/5000 (66%)
[epoch 3] loss: 0.7242137
Test set: Average loss: 0.9203, Accuracy: 3363/5000 (67%)
[epoch 4] loss: 0.6215797
Test set: Average loss: 0.8978, Accuracy: 3362/5000 (67%)
[epoch 5] loss: 0.5263949
Test set: Average loss: 0.8841, Accuracy: 3403/5000 (68%)
[epoch 6] loss: 0.4414599
Test set: Average loss: 0.8680, Accuracy: 3412/5000 (68%)
[epoch 7] loss: 0.3655699
Test set: Average loss: 0.8548, Accuracy: 3444/5000 (69%)
[epoch 8] loss: 0.2976949
Test set: Average loss: 0.8497, Accuracy: 3439/5000 (69%)
[epoch 9] loss: 0.2428169
Test set: Average loss: 0.8702, Accuracy: 3423/5000 (68%)
[epoch 10] loss: 0.1940963
Test set: Average loss: 0.8846, Accuracy: 3395/5000 (68%)
[epoch 11] loss: 0.1532471
Test set: Average loss: 0.8646, Accuracy: 3434/5000 (69%)
[epoch 12] loss: 0.1212418
Test set: Average loss: 0.8776, Accuracy: 3446/5000 (69%)
[epoch 13] loss: 0.0955410
Test set: Average loss: 0.8823, Accuracy: 3457/5000 (69%)
[epoch 14] loss: 0.0753022
Test set: Average loss: 0.8930, Accuracy: 3449/5000 (69%)
[epoch 15] loss: 0.0589487
Test set: Average loss: 0.9106, Accuracy: 3423/5000 (68%)
[epoch 16] loss: 0.0460217
Test set: Average loss: 0.9167, Accuracy: 3425/5000 (68%)
[epoch 17] loss: 0.0371942
Test set: Average loss: 0.9312, Accuracy: 3443/5000 (69%)
[epoch 18] loss: 0.0297280
Test set: Average loss: 0.9517, Accuracy: 3470/5000 (69%)
[epoch 19] loss: 0.0236658
Test set: Average loss: 0.9520, Accuracy: 3467/5000 (69%)
[epoch 20] loss: 0.0193083
Test set: Average loss: 0.9651, Accuracy: 3456/5000 (69%)
[epoch 21] loss: 0.0160440
Test set: Average loss: 0.9842, Accuracy: 3456/5000 (69%)
[epoch 22] loss: 0.0135102
Test set: Average loss: 0.9897, Accuracy: 3445/5000 (69%)
[epoch 23] loss: 0.0118120
Test set: Average loss: 1.0023, Accuracy: 3471/5000 (69%)
[epoch 24] loss: 0.0090953
Test set: Average loss: 1.0290, Accuracy: 3444/5000 (69%)
[epoch 25] loss: 0.0076403
Test set: Average loss: 1.0355, Accuracy: 3457/5000 (69%)
Validation:
Test set: Average loss: 1.0023, Accuracy: 3471/5000 (69%)
Test
Test set: Average loss: 1.0276, Accuracy: 3428/5000 (69%)
Test set: Average loss: 0.0094, Accuracy: 10000/10000 (100%)
15000
## seed: 11
Validation accuracy before training:
Test set: Average loss: 1.5731, Accuracy: 1141/5000 (23%)
[epoch 1] loss: 1.0113987
Test set: Average loss: 0.9925, Accuracy: 3227/5000 (65%)
[epoch 2] loss: 0.7991858
Test set: Average loss: 0.9151, Accuracy: 3387/5000 (68%)
[epoch 3] loss: 0.6648080
Test set: Average loss: 0.8787, Accuracy: 3419/5000 (68%)
[epoch 4] loss: 0.5514439
Test set: Average loss: 0.8500, Accuracy: 3471/5000 (69%)
[epoch 5] loss: 0.4548808
Test set: Average loss: 0.8361, Accuracy: 3474/5000 (69%)
[epoch 6] loss: 0.3681266
Test set: Average loss: 0.8219, Accuracy: 3488/5000 (70%)
[epoch 7] loss: 0.2938854
Test set: Average loss: 0.8274, Accuracy: 3525/5000 (70%)
[epoch 8] loss: 0.2338532
Test set: Average loss: 0.8334, Accuracy: 3494/5000 (70%)
[epoch 9] loss: 0.1826290
Test set: Average loss: 0.8616, Accuracy: 3431/5000 (69%)
[epoch 10] loss: 0.1403352
Test set: Average loss: 0.8496, Accuracy: 3484/5000 (70%)
[epoch 11] loss: 0.1080300
Test set: Average loss: 0.8615, Accuracy: 3491/5000 (70%)
[epoch 12] loss: 0.0823640
Test set: Average loss: 0.8807, Accuracy: 3475/5000 (70%)
[epoch 13] loss: 0.0631753
Test set: Average loss: 0.8856, Accuracy: 3515/5000 (70%)
[epoch 14] loss: 0.0491509
Test set: Average loss: 0.9318, Accuracy: 3446/5000 (69%)
[epoch 15] loss: 0.0596067
Epoch 14: reducing learning rate of group 0 to 5.0000e-06.
Test set: Average loss: 0.9439, Accuracy: 3480/5000 (70%)
[epoch 16] loss: 0.0277733
Test set: Average loss: 0.9256, Accuracy: 3490/5000 (70%)
[epoch 17] loss: 0.0246841
Test set: Average loss: 0.9260, Accuracy: 3491/5000 (70%)
[epoch 18] loss: 0.0230084
Test set: Average loss: 0.9283, Accuracy: 3486/5000 (70%)
[epoch 19] loss: 0.0216837
Test set: Average loss: 0.9308, Accuracy: 3480/5000 (70%)
[epoch 20] loss: 0.0204239
Test set: Average loss: 0.9344, Accuracy: 3486/5000 (70%)
[epoch 21] loss: 0.0192935
Test set: Average loss: 0.9402, Accuracy: 3489/5000 (70%)
[epoch 22] loss: 0.0181846
Test set: Average loss: 0.9410, Accuracy: 3499/5000 (70%)
[epoch 23] loss: 0.0171250
Test set: Average loss: 0.9461, Accuracy: 3497/5000 (70%)
[epoch 24] loss: 0.0162054
Test set: Average loss: 0.9483, Accuracy: 3485/5000 (70%)
[epoch 25] loss: 0.0152458
Test set: Average loss: 0.9508, Accuracy: 3509/5000 (70%)
Validation:
Test set: Average loss: 0.8274, Accuracy: 3525/5000 (70%)
Test
Test set: Average loss: 0.8467, Accuracy: 3464/5000 (69%)
Test set: Average loss: 0.2329, Accuracy: 14558/15000 (97%)
## seed: 12
Validation accuracy before training:
Test set: Average loss: 1.7332, Accuracy: 567/5000 (11%)
[epoch 1] loss: 1.0670903
Test set: Average loss: 0.9968, Accuracy: 3318/5000 (66%)
[epoch 2] loss: 0.8345485
Test set: Average loss: 0.9329, Accuracy: 3337/5000 (67%)
[epoch 3] loss: 0.7019917
Test set: Average loss: 0.8876, Accuracy: 3424/5000 (68%)
[epoch 4] loss: 0.5906711
Test set: Average loss: 0.8559, Accuracy: 3466/5000 (69%)
[epoch 5] loss: 0.4931189
Test set: Average loss: 0.8460, Accuracy: 3442/5000 (69%)
[epoch 6] loss: 0.4078283
Test set: Average loss: 0.8270, Accuracy: 3503/5000 (70%)
[epoch 7] loss: 0.3301859
Test set: Average loss: 0.8261, Accuracy: 3497/5000 (70%)
[epoch 8] loss: 0.2651647
Test set: Average loss: 0.8291, Accuracy: 3458/5000 (69%)
[epoch 9] loss: 0.2085697
Test set: Average loss: 0.8430, Accuracy: 3490/5000 (70%)
[epoch 10] loss: 0.1603945
Test set: Average loss: 0.8737, Accuracy: 3428/5000 (69%)
[epoch 11] loss: 0.1241249
Test set: Average loss: 0.8565, Accuracy: 3503/5000 (70%)
[epoch 12] loss: 0.0962977
Test set: Average loss: 0.8755, Accuracy: 3465/5000 (69%)
[epoch 13] loss: 0.0697893
Test set: Average loss: 0.8692, Accuracy: 3516/5000 (70%)
[epoch 14] loss: 0.0551976
Test set: Average loss: 0.9124, Accuracy: 3459/5000 (69%)
[epoch 15] loss: 0.0511579
Test set: Average loss: 0.9242, Accuracy: 3504/5000 (70%)
[epoch 16] loss: 0.0391175
Test set: Average loss: 0.9356, Accuracy: 3470/5000 (69%)
[epoch 17] loss: 0.0301229
Test set: Average loss: 1.0618, Accuracy: 3323/5000 (66%)
[epoch 18] loss: 0.0410227
Epoch 17: reducing learning rate of group 0 to 5.0000e-06.
Test set: Average loss: 1.0196, Accuracy: 3455/5000 (69%)
[epoch 19] loss: 0.0204875
Test set: Average loss: 0.9691, Accuracy: 3496/5000 (70%)
[epoch 20] loss: 0.0160414
Test set: Average loss: 0.9671, Accuracy: 3500/5000 (70%)
[epoch 21] loss: 0.0144141
Test set: Average loss: 0.9684, Accuracy: 3509/5000 (70%)
[epoch 22] loss: 0.0132570
Test set: Average loss: 0.9723, Accuracy: 3504/5000 (70%)
[epoch 23] loss: 0.0122897
Test set: Average loss: 0.9732, Accuracy: 3516/5000 (70%)
[epoch 24] loss: 0.0114499
Test set: Average loss: 0.9778, Accuracy: 3514/5000 (70%)
[epoch 25] loss: 0.0106804
Test set: Average loss: 0.9786, Accuracy: 3521/5000 (70%)
Validation:
Test set: Average loss: 0.9786, Accuracy: 3521/5000 (70%)
Test
Test set: Average loss: 1.0222, Accuracy: 3450/5000 (69%)
Test set: Average loss: 0.0101, Accuracy: 15000/15000 (100%)
## seed: 13
Validation accuracy before training:
Test set: Average loss: 1.5498, Accuracy: 1511/5000 (30%)
[epoch 1] loss: 1.0248917
Test set: Average loss: 0.9896, Accuracy: 3245/5000 (65%)
[epoch 2] loss: 0.8071375
Test set: Average loss: 0.9141, Accuracy: 3366/5000 (67%)
[epoch 3] loss: 0.6718872
Test set: Average loss: 0.8689, Accuracy: 3410/5000 (68%)
[epoch 4] loss: 0.5558434
Test set: Average loss: 0.8589, Accuracy: 3408/5000 (68%)
[epoch 5] loss: 0.4550836
Test set: Average loss: 0.8366, Accuracy: 3456/5000 (69%)
[epoch 6] loss: 0.3655942
Test set: Average loss: 0.8437, Accuracy: 3459/5000 (69%)
[epoch 7] loss: 0.2899828
Test set: Average loss: 0.8289, Accuracy: 3461/5000 (69%)
[epoch 8] loss: 0.2306724
Test set: Average loss: 0.8377, Accuracy: 3478/5000 (70%)
[epoch 9] loss: 0.1782161
Test set: Average loss: 0.8522, Accuracy: 3477/5000 (70%)
[epoch 10] loss: 0.1393133
Test set: Average loss: 0.8603, Accuracy: 3471/5000 (69%)
[epoch 11] loss: 0.1039666
Test set: Average loss: 0.8686, Accuracy: 3500/5000 (70%)
[epoch 12] loss: 0.0800327
Test set: Average loss: 0.9172, Accuracy: 3434/5000 (69%)
[epoch 13] loss: 0.0603982
Test set: Average loss: 0.8966, Accuracy: 3516/5000 (70%)
[epoch 14] loss: 0.0444935
Test set: Average loss: 0.9583, Accuracy: 3442/5000 (69%)
[epoch 15] loss: 0.0450304
Epoch 14: reducing learning rate of group 0 to 5.0000e-06.
Test set: Average loss: 1.0628, Accuracy: 3307/5000 (66%)
[epoch 16] loss: 0.0322382
Test set: Average loss: 0.9262, Accuracy: 3511/5000 (70%)
[epoch 17] loss: 0.0243612
Test set: Average loss: 0.9287, Accuracy: 3514/5000 (70%)
[epoch 18] loss: 0.0220349
Test set: Average loss: 0.9303, Accuracy: 3514/5000 (70%)
[epoch 19] loss: 0.0204017
Test set: Average loss: 0.9311, Accuracy: 3520/5000 (70%)
[epoch 20] loss: 0.0190621
Test set: Average loss: 0.9355, Accuracy: 3511/5000 (70%)
[epoch 21] loss: 0.0178962
Test set: Average loss: 0.9381, Accuracy: 3515/5000 (70%)
[epoch 22] loss: 0.0168676
Test set: Average loss: 0.9390, Accuracy: 3537/5000 (71%)
[epoch 23] loss: 0.0158719
Test set: Average loss: 0.9434, Accuracy: 3515/5000 (70%)
[epoch 24] loss: 0.0149263
Test set: Average loss: 0.9483, Accuracy: 3510/5000 (70%)
[epoch 25] loss: 0.0140369
Test set: Average loss: 0.9523, Accuracy: 3521/5000 (70%)
Validation:
Test set: Average loss: 0.9390, Accuracy: 3537/5000 (71%)
Test
Test set: Average loss: 0.9662, Accuracy: 3465/5000 (69%)
Test set: Average loss: 0.0159, Accuracy: 14998/15000 (100%)
20000
## seed: 11
Validation accuracy before training:
Test set: Average loss: 1.5148, Accuracy: 1526/5000 (31%)
[epoch 1] loss: 0.9767292
Test set: Average loss: 0.9520, Accuracy: 3368/5000 (67%)
[epoch 2] loss: 0.7511717
Test set: Average loss: 0.8716, Accuracy: 3467/5000 (69%)
[epoch 3] loss: 0.6118490
Test set: Average loss: 0.8381, Accuracy: 3500/5000 (70%)
[epoch 4] loss: 0.4942958
Test set: Average loss: 0.8120, Accuracy: 3559/5000 (71%)
[epoch 5] loss: 0.3934773
Test set: Average loss: 0.8154, Accuracy: 3517/5000 (70%)
[epoch 6] loss: 0.3073012
Test set: Average loss: 0.8282, Accuracy: 3480/5000 (70%)
[epoch 7] loss: 0.2375544
Test set: Average loss: 0.8334, Accuracy: 3475/5000 (70%)
[epoch 8] loss: 0.1824231
Test set: Average loss: 0.8403, Accuracy: 3516/5000 (70%)
[epoch 9] loss: 0.1347996
Test set: Average loss: 0.8527, Accuracy: 3480/5000 (70%)
[epoch 10] loss: 0.0987332
Test set: Average loss: 0.8841, Accuracy: 3485/5000 (70%)
[epoch 11] loss: 0.0751661
Test set: Average loss: 0.8966, Accuracy: 3481/5000 (70%)
[epoch 12] loss: 0.0594200
Test set: Average loss: 0.9734, Accuracy: 3414/5000 (68%)
[epoch 13] loss: 0.0536591
Test set: Average loss: 0.9460, Accuracy: 3460/5000 (69%)
[epoch 14] loss: 0.0363965
Test set: Average loss: 1.0012, Accuracy: 3445/5000 (69%)
[epoch 15] loss: 0.0254003
Test set: Average loss: 1.0013, Accuracy: 3472/5000 (69%)
[epoch 16] loss: 0.0424526
Epoch 15: reducing learning rate of group 0 to 5.0000e-06.
Test set: Average loss: 1.1267, Accuracy: 3393/5000 (68%)
[epoch 17] loss: 0.0257828
Epoch 16: reducing learning rate of group 0 to 5.0000e-07.
Test set: Average loss: 1.0178, Accuracy: 3502/5000 (70%)
[epoch 18] loss: 0.0162682
Test set: Average loss: 1.0172, Accuracy: 3503/5000 (70%)
[epoch 19] loss: 0.0157044
Test set: Average loss: 1.0170, Accuracy: 3501/5000 (70%)
[epoch 20] loss: 0.0151275
Test set: Average loss: 1.0171, Accuracy: 3505/5000 (70%)
[epoch 21] loss: 0.0145370
Test set: Average loss: 1.0180, Accuracy: 3503/5000 (70%)
[epoch 22] loss: 0.0139684
Test set: Average loss: 1.0175, Accuracy: 3500/5000 (70%)
[epoch 23] loss: 0.0134101
Test set: Average loss: 1.0183, Accuracy: 3503/5000 (70%)
[epoch 24] loss: 0.0128956
Test set: Average loss: 1.0180, Accuracy: 3506/5000 (70%)
[epoch 25] loss: 0.0124221
Test set: Average loss: 1.0177, Accuracy: 3511/5000 (70%)
Validation:
Test set: Average loss: 0.8120, Accuracy: 3559/5000 (71%)
Test
Test set: Average loss: 0.8345, Accuracy: 3497/5000 (70%)
Test set: Average loss: 0.3953, Accuracy: 18380/20000 (92%)
## seed: 12
Validation accuracy before training:
Test set: Average loss: 1.7512, Accuracy: 893/5000 (18%)
[epoch 1] loss: 1.1037861
Test set: Average loss: 1.0157, Accuracy: 3242/5000 (65%)
[epoch 2] loss: 0.8646093
Test set: Average loss: 0.9299, Accuracy: 3364/5000 (67%)
[epoch 3] loss: 0.7211429
Test set: Average loss: 0.8767, Accuracy: 3448/5000 (69%)
[epoch 4] loss: 0.5989922
Test set: Average loss: 0.8411, Accuracy: 3475/5000 (70%)
[epoch 5] loss: 0.4910396
Test set: Average loss: 0.8262, Accuracy: 3506/5000 (70%)
[epoch 6] loss: 0.3980197
Test set: Average loss: 0.8086, Accuracy: 3541/5000 (71%)
[epoch 7] loss: 0.3150373
Test set: Average loss: 0.8168, Accuracy: 3498/5000 (70%)
[epoch 8] loss: 0.2449423
Test set: Average loss: 0.8246, Accuracy: 3527/5000 (71%)
[epoch 9] loss: 0.1858966
Test set: Average loss: 0.8305, Accuracy: 3540/5000 (71%)
[epoch 10] loss: 0.1384477
Test set: Average loss: 0.8632, Accuracy: 3496/5000 (70%)
[epoch 11] loss: 0.1069193
Test set: Average loss: 0.8832, Accuracy: 3472/5000 (69%)
[epoch 12] loss: 0.0788620
Test set: Average loss: 0.9042, Accuracy: 3499/5000 (70%)
[epoch 13] loss: 0.0592168
Test set: Average loss: 0.9271, Accuracy: 3477/5000 (70%)
[epoch 14] loss: 0.0476535
Test set: Average loss: 0.9823, Accuracy: 3458/5000 (69%)
[epoch 15] loss: 0.0519110
Epoch 14: reducing learning rate of group 0 to 5.0000e-06.
Test set: Average loss: 1.0170, Accuracy: 3462/5000 (69%)
[epoch 16] loss: 0.0236734
Test set: Average loss: 0.9583, Accuracy: 3506/5000 (70%)
[epoch 17] loss: 0.0191558
Test set: Average loss: 0.9550, Accuracy: 3517/5000 (70%)
[epoch 18] loss: 0.0172511
Test set: Average loss: 0.9592, Accuracy: 3516/5000 (70%)
[epoch 19] loss: 0.0158305
Test set: Average loss: 0.9612, Accuracy: 3524/5000 (70%)
[epoch 20] loss: 0.0146006
Test set: Average loss: 0.9660, Accuracy: 3523/5000 (70%)
[epoch 21] loss: 0.0135047
Test set: Average loss: 0.9735, Accuracy: 3526/5000 (71%)
[epoch 22] loss: 0.0125479
Test set: Average loss: 0.9730, Accuracy: 3530/5000 (71%)
[epoch 23] loss: 0.0115761
Test set: Average loss: 0.9841, Accuracy: 3531/5000 (71%)
[epoch 24] loss: 0.0107240
Test set: Average loss: 0.9848, Accuracy: 3533/5000 (71%)
[epoch 25] loss: 0.0099032
Test set: Average loss: 0.9915, Accuracy: 3525/5000 (70%)
Validation:
Test set: Average loss: 0.8086, Accuracy: 3541/5000 (71%)
Test
Test set: Average loss: 0.8278, Accuracy: 3455/5000 (69%)
Test set: Average loss: 0.3171, Accuracy: 18836/20000 (94%)
## seed: 13
Validation accuracy before training:
Test set: Average loss: 1.5982, Accuracy: 1206/5000 (24%)
[epoch 1] loss: 1.0265840
Test set: Average loss: 0.9742, Accuracy: 3332/5000 (67%)
[epoch 2] loss: 0.8043973
Test set: Average loss: 0.8984, Accuracy: 3397/5000 (68%)
[epoch 3] loss: 0.6605144
Test set: Average loss: 0.8614, Accuracy: 3439/5000 (69%)
[epoch 4] loss: 0.5440260
Test set: Average loss: 0.8243, Accuracy: 3488/5000 (70%)
[epoch 5] loss: 0.4392359
Test set: Average loss: 0.8258, Accuracy: 3480/5000 (70%)
[epoch 6] loss: 0.3514985
Test set: Average loss: 0.8227, Accuracy: 3513/5000 (70%)
[epoch 7] loss: 0.2757054
Test set: Average loss: 0.8336, Accuracy: 3470/5000 (69%)
[epoch 8] loss: 0.2130941
Test set: Average loss: 0.8227, Accuracy: 3530/5000 (71%)
[epoch 9] loss: 0.1645106
Test set: Average loss: 0.8427, Accuracy: 3499/5000 (70%)
[epoch 10] loss: 0.1241102
Test set: Average loss: 0.8608, Accuracy: 3519/5000 (70%)
[epoch 11] loss: 0.0903341
Test set: Average loss: 0.8902, Accuracy: 3498/5000 (70%)
[epoch 12] loss: 0.0722337
Test set: Average loss: 0.9264, Accuracy: 3476/5000 (70%)
[epoch 13] loss: 0.0499805
Test set: Average loss: 0.9350, Accuracy: 3471/5000 (69%)
[epoch 14] loss: 0.0408214
Test set: Average loss: 0.9676, Accuracy: 3439/5000 (69%)
[epoch 15] loss: 0.0559608
Epoch 14: reducing learning rate of group 0 to 5.0000e-06.
Test set: Average loss: 1.0196, Accuracy: 3455/5000 (69%)
[epoch 16] loss: 0.0232406
Test set: Average loss: 0.9808, Accuracy: 3480/5000 (70%)
[epoch 17] loss: 0.0181962
Test set: Average loss: 0.9798, Accuracy: 3480/5000 (70%)
[epoch 18] loss: 0.0162464
Test set: Average loss: 0.9820, Accuracy: 3481/5000 (70%)
[epoch 19] loss: 0.0147992
Test set: Average loss: 0.9848, Accuracy: 3492/5000 (70%)
[epoch 20] loss: 0.0135920
Test set: Average loss: 0.9900, Accuracy: 3483/5000 (70%)
[epoch 21] loss: 0.0125068
Test set: Average loss: 0.9965, Accuracy: 3483/5000 (70%)
[epoch 22] loss: 0.0115258
Test set: Average loss: 1.0000, Accuracy: 3495/5000 (70%)
[epoch 23] loss: 0.0106519
Test set: Average loss: 1.0049, Accuracy: 3499/5000 (70%)
[epoch 24] loss: 0.0098361
Test set: Average loss: 1.0071, Accuracy: 3508/5000 (70%)
[epoch 25] loss: 0.0090519
Test set: Average loss: 1.0185, Accuracy: 3494/5000 (70%)
Validation:
Test set: Average loss: 0.8227, Accuracy: 3530/5000 (71%)
Test
Test set: Average loss: 0.8426, Accuracy: 3476/5000 (70%)
Test set: Average loss: 0.1597, Accuracy: 19611/20000 (98%)
n_training_examples = [25, 50, 100, 250, 500, 750, 1000, 2500, 5000, 10000, 15000, 20000]
test_accuracies = {'B': [(0.3959333333333333, 0.015245837318939073), (0.43520000000000003, 0.016085604330166342), (0.45920000000000005, 0.018982799231585065), (0.5140666666666667, 0.007433856483832747), (0.5437333333333333, 0.010451581485859219), (0.5674666666666667, 0.005504745427558125), (0.574, 0.0011430952132987942), (0.6096666666666667, 0.006069230227595209), (0.6431333333333332, 0.0035226252836327823), (0.6708666666666666, 0.0038964371189873204), (0.6855333333333333, 0.004030991055421564), (0.6948666666666666, 0.005751135153650588)], 'AnB': [(0.3717333333333333, 0.013455440865645719), (0.40066666666666667, 0.021669230617526673), (0.4056, 0.052545091746676646), (0.5340666666666666, 0.0020548046676563273), (0.5644, 0.00793137230664823), (0.573, 0.007657675887630638), (0.5863333333333333, 0.0011813363431112643), (0.6216, 0.006701243665668867), (0.6544666666666666, 0.0018061622912192382), (0.6765333333333334, 0.003159465496286095), (0.6870666666666666, 0.002714569742866955), (0.6956000000000001, 0.0026981475126464237)], 'BnB': [(0.3375333333333333, 0.04630603512382473), (0.391, 0.014958609561052133), (0.41, 0.053117981889375276), (0.5248666666666667, 0.014379924277346603), (0.5764, 0.01321009714826756), (0.6025333333333333, 0.005982938705649197), (0.6091333333333333, 0.010701194118207373), (0.6438, 0.00608166643829359), (0.6806, 0.0009092121131323798), (0.6980666666666666, 0.005564969801255778), (0.7017333333333333, 0.0028581268146968043), (0.7017333333333333, 0.003582674358011874)], 'ABnB': [(0.4324666666666667, 0.005073679357450793), (0.4316, 0.005283937925449163), (0.4403333333333333, 0.04460951567646627), (0.5295333333333333, 0.02288658025034661), (0.5757333333333333, 0.005208539995899874), (0.5793333333333334, 0.009076465293395983), (0.5982000000000001, 0.010007996802557421), (0.6375333333333333, 0.007350888079378957), (0.6685333333333333, 0.004502838610871549), (0.6848666666666666, 0.00338755893757666), (0.6919333333333334, 0.0013695092389449483), (0.6952000000000002, 0.00342928563989648)]}
n_training_examples = [25, 50, 100, 250, 500, 750, 1000, 2500, 5000, 10000, 15000, 20000]
train_accuracies = {'B': [(1.0, 0.0), (1.0, 0.0), (0.8799999999999999, 0.05715476066494078), (0.9159999999999999, 0.02592296279363143), (0.9486666666666667, 0.02945429604583268), (0.8333333333333334, 0.03623789708558135), (0.8963333333333333, 0.01811690432226827), (0.8502666666666667, 0.057476101313695765), (0.9608, 0.016485953617145332), (0.9592666666666667, 0.03031307015500446), (0.9562444444444443, 0.029333754205734884), (0.9485333333333333, 0.03489322602199778)], 'AnB': [(1.0, 0.0), (0.9866666666666667, 0.009428090415820642), (0.8766666666666666, 0.053124591501697384), (0.984, 0.013063945294843629), (0.9846666666666666, 0.003399346342395193), (0.9902222222222222, 0.002739739556875075), (0.9786666666666667, 0.010656244908763863), (0.9752000000000001, 0.010693300083073854), (0.9941333333333334, 0.007310874700669476), (0.9667666666666667, 0.02240927387390218), (0.9805777777777779, 0.025554260836768095), (0.9884833333333333, 0.016039551808645486)], 'BnB': [(1.0, 0.0), (0.9866666666666667, 0.018856180831641284), (0.8633333333333333, 0.02867441755680878), (0.9933333333333333, 0.004988876515698593), (0.9926666666666666, 0.003399346342395193), (0.9968888888888889, 0.001662958838566191), (0.996, 0.0016329931618554536), (0.9957333333333334, 0.002963481436119089), (0.9996666666666667, 0.00033993463423953233), (1.0, 0.0), (0.9996, 0.00047140452079103207), (0.99995, 7.071067811864697e-05)], 'ABnB': [(1.0, 0.0), (0.9933333333333333, 0.009428090415820642), (0.9466666666666667, 0.012472191289246433), (0.996, 0.0), (0.9933333333333333, 0.0009428090415820641), (0.9924444444444444, 0.002739739556875117), (0.9923333333333333, 0.0041096093353126546), (0.9956, 0.004811098280711651), (0.9996, 0.00016329931618557254), (0.9984333333333333, 0.0022156012477178664), (0.9901333333333334, 0.013859399805293255), (0.9471166666666667, 0.02540735895147091)]}
n_training_examples = [25, 50, 100, 250, 500, 750, 1000, 2500, 5000, 10000, 15000, 20000]
generr_accuracies = {'B': [(0.6040666666666666, 0.015245837318939099), (0.5648000000000001, 0.016085604330166387), (0.4208, 0.038837438981820925), (0.4019333333333333, 0.018954213838147507), (0.4049333333333333, 0.03624227120673068), (0.26586666666666664, 0.03686640546421431), (0.32233333333333336, 0.019108346053201178), (0.2406, 0.05382143315322125), (0.3176666666666667, 0.01961314751781459), (0.2884, 0.0328478309786202), (0.2707111111111111, 0.029696855218634587), (0.2536666666666667, 0.030609539181256713)], 'AnB': [(0.6282666666666666, 0.013455440865645693), (0.586, 0.03001110905425965), (0.4710666666666667, 0.012775323435783869), (0.44993333333333335, 0.012391753530294081), (0.42026666666666673, 0.011198015697236514), (0.4172222222222222, 0.005043318523392625), (0.39233333333333337, 0.009821518325708243), (0.35359999999999997, 0.007652450587883618), (0.33966666666666673, 0.008970073702162252), (0.29023333333333334, 0.01940177540558822), (0.2935111111111111, 0.028032908351030623), (0.29288333333333333, 0.01734763832789804)], 'BnB': [(0.6624666666666666, 0.04630603512382476), (0.5956666666666667, 0.00883075434049789), (0.45333333333333337, 0.039963427725303514), (0.46846666666666664, 0.014782271664245502), (0.41626666666666673, 0.01165885452730622), (0.39435555555555557, 0.007638951514894777), (0.3868666666666667, 0.009329999404549249), (0.3519333333333334, 0.004034297405441908), (0.31906666666666667, 0.0006182412330330306), (0.30193333333333333, 0.005564969801255778), (0.29786666666666667, 0.0024567367696917753), (0.29821666666666663, 0.0035138614403847105)], 'ABnB': [(0.5675333333333333, 0.005073679357450794), (0.5617333333333333, 0.0074481914284982974), (0.5063333333333333, 0.04265374804424834), (0.46646666666666664, 0.02288658025034661), (0.4176, 0.004270831300812501), (0.41311111111111104, 0.011157768704769599), (0.3941333333333333, 0.011763597333393456), (0.3580666666666667, 0.01167142760000773), (0.3310666666666667, 0.004596617113583523), (0.31356666666666666, 0.0015456030825826026), (0.2982000000000001, 0.01452854151381062), (0.2519166666666667, 0.02685393618985657)]}
In [8]:
results_test[n_hus[3]], results_train[n_hus[3]], results_generr[n_hus[3]] = do_all_hl(n_hus[3])
#### Training for 8192 hu
## No Pre-Training
test_accuracies_B = [(0.39093333333333335, 0.016468420959183945), (0.4261333333333333, 0.020708345070419205), (0.4408666666666667, 0.01621713771155549), (0.5168666666666667, 0.014286901537966709), (0.5510666666666667, 0.0029318177903061046), (0.569, 0.004868949236402741), (0.5768, 0.0040431011200150494), (0.6058666666666667, 0.004413111776916091), (0.6326666666666667, 0.004401009985093048), (0.6715333333333332, 0.0028767265347188526), (0.6880000000000001, 0.0017048949136725885), (0.6962666666666667, 0.001463633226673339)]
train_accuracies_B = [(1.0, 0.0), (0.9866666666666667, 0.018856180831641284), (0.86, 0.11860297916438133), (0.8773333333333334, 0.1029865147590801), (0.9226666666666666, 0.04631294515455574), (0.9053333333333334, 0.013063945294843629), (0.8879999999999999, 0.0659140854951858), (0.8921333333333333, 0.05611638699069008), (0.916, 0.06428457565129186), (0.9748000000000001, 0.03493145669259538), (0.9862000000000001, 0.019139100950284645), (0.9996499999999999, 4.0824829046381805e-05)]
gen_errors_B = [(0.6090666666666666, 0.016468420959183935), (0.5605333333333333, 0.025550646871567797), (0.41913333333333336, 0.13336789552045708), (0.36046666666666666, 0.09312276246379769), (0.37159999999999993, 0.04338325329740347), (0.3363333333333333, 0.01257404734628697), (0.31120000000000003, 0.06282738256524772), (0.28626666666666667, 0.060477286829207416), (0.2833333333333333, 0.06731603738255014), (0.3032666666666667, 0.03367197977877484), (0.2982, 0.01744230701696526), (0.30338333333333334, 0.0014619241506392219)]
## Pre-Training BnB
test_accuracies_BnB = [(0.39953333333333335, 0.042587739498070966), (0.4463333333333333, 0.019491080581184376), (0.4762, 0.026086522701706836), (0.5416666666666666, 0.010309003616041463), (0.5926666666666666, 0.005327496806401896), (0.6148, 0.01592984620139191), (0.6195333333333334, 0.01806383741684538), (0.6565333333333334, 0.010621152898291639), (0.6878000000000001, 0.0054869542249473), (0.703, 0.0015748015748023767), (0.7042666666666667, 0.004828618389928507), (0.7028666666666666, 0.0027390184778898967)]
train_accuracies_BnB = [(1.0, 0.0), (0.9933333333333333, 0.009428090415820642), (0.9433333333333334, 0.036817870057290855), (0.9973333333333333, 0.0018856180831641283), (0.992, 0.005656854249492386), (0.9928888888888888, 0.002739739556875117), (0.9963333333333333, 0.0016996731711975965), (0.9965333333333334, 0.00405736641458745), (0.9998, 0.00016329931618552722), (0.9996333333333333, 0.0005185449728701301), (0.9975333333333333, 0.003394112549695421), (0.9982333333333333, 0.0024631732018317704)]
gen_errors_BnB = [(0.6004666666666666, 0.04258773949807096), (0.547, 0.028290398842481343), (0.46713333333333334, 0.047188228287242194), (0.45566666666666666, 0.011483708266738408), (0.3993333333333333, 0.008492087820763277), (0.37808888888888886, 0.013250557873184705), (0.37679999999999997, 0.016434110867339334), (0.34, 0.008081254028098997), (0.312, 0.0053241587754937585), (0.2966333333333333, 0.0014704496666742043), (0.2932666666666667, 0.0019482185594936858), (0.2953666666666667, 0.004572441604025378)]
## Pre-Training AnB
test_accuracies_AnB = [(0.39093333333333335, 0.009721911106133184), (0.3781999999999999, 0.025556734272333518), (0.3970666666666667, 0.007950401806757264), (0.5034, 0.0024055491403558254), (0.5653333333333334, 0.005881798666696727), (0.5717333333333333, 0.013462375553948682), (0.5832, 0.011329018786579301), (0.6258666666666666, 0.0051493257379540275), (0.6516000000000001, 0.0057410800377629655), (0.6782, 0.004982636517614615), (0.6846, 0.0036914315199752428), (0.7004, 0.0023720595832876367)]
train_accuracies_AnB = [(1.0, 0.0), (0.9733333333333333, 0.009428090415820642), (0.9033333333333333, 0.023570226039551605), (0.9893333333333333, 0.0018856180831641283), (0.988, 0.002828427124746193), (0.9795555555555556, 0.012988123729957734), (0.988, 0.00509901951359279), (0.9966666666666666, 0.0019955506062794433), (0.9996, 0.0002828427124746402), (0.9993333333333334, 0.0008730533902472614), (0.9895111111111111, 0.009616703575254931), (0.9922166666666667, 0.010795240720902084)]
gen_errors_AnB = [(0.6090666666666666, 0.009721911106133206), (0.5951333333333333, 0.023679151636454822), (0.5062666666666668, 0.01601693548161515), (0.4859333333333333, 0.003689022755268515), (0.4226666666666666, 0.0037853518844208817), (0.40782222222222225, 0.006541114036577122), (0.4048, 0.009441751249988896), (0.3708, 0.0031874754901018566), (0.34800000000000003, 0.005564171097297444), (0.3211333333333333, 0.0058459862774005635), (0.30491111111111113, 0.005935288899538718), (0.29181666666666667, 0.010922631957952698)]
## Pre-Training ABnB
Validation accuracy before training:
Test set: Average loss: 2.2935, Accuracy: 563/5000 (11%)
[epoch 1] loss: 1.9358119
Test set: Average loss: 1.8776, Accuracy: 1877/5000 (38%)
[epoch 2] loss: 1.7999231
Test set: Average loss: 1.7959, Accuracy: 2039/5000 (41%)
[epoch 3] loss: 1.7083108
Test set: Average loss: 1.7549, Accuracy: 2050/5000 (41%)
[epoch 4] loss: 1.6259785
Test set: Average loss: 1.7194, Accuracy: 2091/5000 (42%)
[epoch 5] loss: 1.5403633
Test set: Average loss: 1.6894, Accuracy: 2134/5000 (43%)
[epoch 6] loss: 1.4502598
Test set: Average loss: 1.6657, Accuracy: 2154/5000 (43%)
[epoch 7] loss: 1.3540350
Test set: Average loss: 1.6255, Accuracy: 2265/5000 (45%)
[epoch 8] loss: 1.2518992
Test set: Average loss: 1.6103, Accuracy: 2268/5000 (45%)
[epoch 9] loss: 1.1418665
Test set: Average loss: 1.5924, Accuracy: 2320/5000 (46%)
[epoch 10] loss: 1.0300938
Test set: Average loss: 1.5900, Accuracy: 2299/5000 (46%)
[epoch 11] loss: 0.9074527
Test set: Average loss: 1.6036, Accuracy: 2300/5000 (46%)
[epoch 12] loss: 0.7893107
Test set: Average loss: 1.5893, Accuracy: 2354/5000 (47%)
[epoch 13] loss: 0.6674310
Test set: Average loss: 1.6226, Accuracy: 2333/5000 (47%)
[epoch 14] loss: 0.5610113
Test set: Average loss: 1.6301, Accuracy: 2292/5000 (46%)
[epoch 15] loss: 0.4579182
Test set: Average loss: 1.6697, Accuracy: 2316/5000 (46%)
[epoch 16] loss: 0.3652642
Test set: Average loss: 1.7114, Accuracy: 2288/5000 (46%)
[epoch 17] loss: 0.2920352
Test set: Average loss: 1.7153, Accuracy: 2290/5000 (46%)
[epoch 18] loss: 0.2279795
Test set: Average loss: 1.7923, Accuracy: 2303/5000 (46%)
[epoch 19] loss: 0.1852471
Test set: Average loss: 1.7959, Accuracy: 2297/5000 (46%)
[epoch 20] loss: 0.1494973
Test set: Average loss: 1.8253, Accuracy: 2299/5000 (46%)
[epoch 21] loss: 0.1153085
Test set: Average loss: 1.8965, Accuracy: 2241/5000 (45%)
[epoch 22] loss: 0.1025480
Test set: Average loss: 1.9555, Accuracy: 2265/5000 (45%)
[epoch 23] loss: 0.0832724
Test set: Average loss: 1.9703, Accuracy: 2279/5000 (46%)
[epoch 24] loss: 0.0805673
Test set: Average loss: 2.0205, Accuracy: 2241/5000 (45%)
[epoch 25] loss: 0.0758368
Test set: Average loss: 2.0890, Accuracy: 2215/5000 (44%)
Validation:
Test set: Average loss: 1.5893, Accuracy: 2354/5000 (47%)
Test set: Average loss: 1.5794, Accuracy: 4698/10000 (47%)
25
## seed: 11
Validation accuracy before training:
Test set: Average loss: 1.5860, Accuracy: 1022/5000 (20%)
[epoch 1] loss: 1.4996928
Test set: Average loss: 1.5493, Accuracy: 1231/5000 (25%)
[epoch 2] loss: 1.2311341
Test set: Average loss: 1.5183, Accuracy: 1377/5000 (28%)
[epoch 3] loss: 1.0441809
Test set: Average loss: 1.4921, Accuracy: 1516/5000 (30%)
[epoch 4] loss: 0.9224097
Test set: Average loss: 1.4692, Accuracy: 1618/5000 (32%)
[epoch 5] loss: 0.8289979
Test set: Average loss: 1.4491, Accuracy: 1714/5000 (34%)
[epoch 6] loss: 0.7551755
Test set: Average loss: 1.4326, Accuracy: 1811/5000 (36%)
[epoch 7] loss: 0.7047367
Test set: Average loss: 1.4195, Accuracy: 1871/5000 (37%)
[epoch 8] loss: 0.6702849
Test set: Average loss: 1.4094, Accuracy: 1919/5000 (38%)
[epoch 9] loss: 0.6421086
Test set: Average loss: 1.4014, Accuracy: 1954/5000 (39%)
[epoch 10] loss: 0.6160333
Test set: Average loss: 1.3951, Accuracy: 2003/5000 (40%)
[epoch 11] loss: 0.5919961
Test set: Average loss: 1.3901, Accuracy: 2035/5000 (41%)
[epoch 12] loss: 0.5700307
Test set: Average loss: 1.3863, Accuracy: 2041/5000 (41%)
[epoch 13] loss: 0.5495759
Test set: Average loss: 1.3836, Accuracy: 2051/5000 (41%)
[epoch 14] loss: 0.5300792
Test set: Average loss: 1.3819, Accuracy: 2039/5000 (41%)
[epoch 15] loss: 0.5113301
Test set: Average loss: 1.3813, Accuracy: 2033/5000 (41%)
[epoch 16] loss: 0.4939744
Test set: Average loss: 1.3816, Accuracy: 2007/5000 (40%)
[epoch 17] loss: 0.4780592
Test set: Average loss: 1.3826, Accuracy: 1988/5000 (40%)
[epoch 18] loss: 0.4617316
Test set: Average loss: 1.3840, Accuracy: 1965/5000 (39%)
[epoch 19] loss: 0.4449934
Test set: Average loss: 1.3855, Accuracy: 1931/5000 (39%)
[epoch 20] loss: 0.4306548
Test set: Average loss: 1.3865, Accuracy: 1905/5000 (38%)
[epoch 21] loss: 0.4200281
Test set: Average loss: 1.3868, Accuracy: 1910/5000 (38%)
[epoch 22] loss: 0.4114937
Test set: Average loss: 1.3862, Accuracy: 1904/5000 (38%)
[epoch 23] loss: 0.4035996
Test set: Average loss: 1.3851, Accuracy: 1906/5000 (38%)
[epoch 24] loss: 0.3962035
Test set: Average loss: 1.3835, Accuracy: 1907/5000 (38%)
[epoch 25] loss: 0.3889985
Test set: Average loss: 1.3817, Accuracy: 1910/5000 (38%)
Validation:
Test set: Average loss: 1.3836, Accuracy: 2051/5000 (41%)
Test
Test set: Average loss: 1.3956, Accuracy: 1987/5000 (40%)
Test set: Average loss: 0.5301, Accuracy: 25/25 (100%)
## seed: 12
Validation accuracy before training:
Test set: Average loss: 1.6603, Accuracy: 1174/5000 (23%)
[epoch 1] loss: 1.7064542
Test set: Average loss: 1.6067, Accuracy: 1391/5000 (28%)
[epoch 2] loss: 1.4035171
Test set: Average loss: 1.5641, Accuracy: 1565/5000 (31%)
[epoch 3] loss: 1.1808516
Test set: Average loss: 1.5316, Accuracy: 1707/5000 (34%)
[epoch 4] loss: 1.0112796
Test set: Average loss: 1.5061, Accuracy: 1818/5000 (36%)
[epoch 5] loss: 0.8824117
Test set: Average loss: 1.4860, Accuracy: 1909/5000 (38%)
[epoch 6] loss: 0.7837281
Test set: Average loss: 1.4710, Accuracy: 1979/5000 (40%)
[epoch 7] loss: 0.7084966
Test set: Average loss: 1.4604, Accuracy: 2019/5000 (40%)
[epoch 8] loss: 0.6516299
Test set: Average loss: 1.4536, Accuracy: 2040/5000 (41%)
[epoch 9] loss: 0.6082962
Test set: Average loss: 1.4497, Accuracy: 2044/5000 (41%)
[epoch 10] loss: 0.5735153
Test set: Average loss: 1.4476, Accuracy: 2064/5000 (41%)
[epoch 11] loss: 0.5452011
Test set: Average loss: 1.4468, Accuracy: 2079/5000 (42%)
[epoch 12] loss: 0.5214943
Test set: Average loss: 1.4468, Accuracy: 2074/5000 (41%)
[epoch 13] loss: 0.5011607
Test set: Average loss: 1.4471, Accuracy: 2079/5000 (42%)
[epoch 14] loss: 0.4846945
Test set: Average loss: 1.4475, Accuracy: 2094/5000 (42%)
[epoch 15] loss: 0.4719523
Test set: Average loss: 1.4479, Accuracy: 2104/5000 (42%)
[epoch 16] loss: 0.4612647
Test set: Average loss: 1.4483, Accuracy: 2111/5000 (42%)
[epoch 17] loss: 0.4510811
Test set: Average loss: 1.4486, Accuracy: 2110/5000 (42%)
[epoch 18] loss: 0.4408393
Test set: Average loss: 1.4489, Accuracy: 2112/5000 (42%)
[epoch 19] loss: 0.4312773
Test set: Average loss: 1.4494, Accuracy: 2123/5000 (42%)
[epoch 20] loss: 0.4226625
Test set: Average loss: 1.4502, Accuracy: 2115/5000 (42%)
[epoch 21] loss: 0.4146555
Test set: Average loss: 1.4511, Accuracy: 2111/5000 (42%)
[epoch 22] loss: 0.4074113
Test set: Average loss: 1.4521, Accuracy: 2115/5000 (42%)
[epoch 23] loss: 0.4009481
Test set: Average loss: 1.4531, Accuracy: 2117/5000 (42%)
[epoch 24] loss: 0.3954134
Test set: Average loss: 1.4542, Accuracy: 2117/5000 (42%)
[epoch 25] loss: 0.3909864
Test set: Average loss: 1.4551, Accuracy: 2114/5000 (42%)
Validation:
Test set: Average loss: 1.4494, Accuracy: 2123/5000 (42%)
Test
Test set: Average loss: 1.4516, Accuracy: 2111/5000 (42%)
Test set: Average loss: 0.4227, Accuracy: 25/25 (100%)
## seed: 13
Validation accuracy before training:
Test set: Average loss: 1.4700, Accuracy: 1806/5000 (36%)
[epoch 1] loss: 1.2979486
Test set: Average loss: 1.4315, Accuracy: 1987/5000 (40%)
[epoch 2] loss: 1.0273898
Test set: Average loss: 1.3996, Accuracy: 2128/5000 (43%)
[epoch 3] loss: 0.8617583
Test set: Average loss: 1.3749, Accuracy: 2219/5000 (44%)
[epoch 4] loss: 0.7568039
Test set: Average loss: 1.3551, Accuracy: 2300/5000 (46%)
[epoch 5] loss: 0.6846021
Test set: Average loss: 1.3393, Accuracy: 2352/5000 (47%)
[epoch 6] loss: 0.6294575
Test set: Average loss: 1.3271, Accuracy: 2418/5000 (48%)
[epoch 7] loss: 0.5846361
Test set: Average loss: 1.3184, Accuracy: 2454/5000 (49%)
[epoch 8] loss: 0.5471363
Test set: Average loss: 1.3124, Accuracy: 2443/5000 (49%)
[epoch 9] loss: 0.5176756
Test set: Average loss: 1.3085, Accuracy: 2439/5000 (49%)
[epoch 10] loss: 0.4951263
Test set: Average loss: 1.3061, Accuracy: 2442/5000 (49%)
[epoch 11] loss: 0.4766500
Test set: Average loss: 1.3047, Accuracy: 2437/5000 (49%)
[epoch 12] loss: 0.4593849
Test set: Average loss: 1.3041, Accuracy: 2427/5000 (49%)
[epoch 13] loss: 0.4430491
Test set: Average loss: 1.3041, Accuracy: 2416/5000 (48%)
[epoch 14] loss: 0.4274434
Test set: Average loss: 1.3043, Accuracy: 2411/5000 (48%)
[epoch 15] loss: 0.4121159
Test set: Average loss: 1.3048, Accuracy: 2418/5000 (48%)
[epoch 16] loss: 0.3976270
Test set: Average loss: 1.3052, Accuracy: 2406/5000 (48%)
[epoch 17] loss: 0.3846745
Test set: Average loss: 1.3056, Accuracy: 2398/5000 (48%)
[epoch 18] loss: 0.3737344
Test set: Average loss: 1.3059, Accuracy: 2396/5000 (48%)
[epoch 19] loss: 0.3647235
Test set: Average loss: 1.3063, Accuracy: 2397/5000 (48%)
[epoch 20] loss: 0.3568069
Test set: Average loss: 1.3068, Accuracy: 2387/5000 (48%)
[epoch 21] loss: 0.3494799
Test set: Average loss: 1.3074, Accuracy: 2384/5000 (48%)
[epoch 22] loss: 0.3425928
Test set: Average loss: 1.3080, Accuracy: 2386/5000 (48%)
[epoch 23] loss: 0.3362636
Test set: Average loss: 1.3086, Accuracy: 2382/5000 (48%)
[epoch 24] loss: 0.3306718
Test set: Average loss: 1.3090, Accuracy: 2376/5000 (48%)
[epoch 25] loss: 0.3255239
Test set: Average loss: 1.3092, Accuracy: 2384/5000 (48%)
Validation:
Test set: Average loss: 1.3184, Accuracy: 2454/5000 (49%)
Test
Test set: Average loss: 1.3316, Accuracy: 2372/5000 (47%)
Test set: Average loss: 0.5471, Accuracy: 23/25 (92%)
50
## seed: 11
Validation accuracy before training:
Test set: Average loss: 1.6323, Accuracy: 1196/5000 (24%)
[epoch 1] loss: 1.7157229
Test set: Average loss: 1.5591, Accuracy: 1429/5000 (29%)
[epoch 2] loss: 1.3459669
Test set: Average loss: 1.5135, Accuracy: 1597/5000 (32%)
[epoch 3] loss: 1.1476617
Test set: Average loss: 1.4777, Accuracy: 1694/5000 (34%)
[epoch 4] loss: 1.0191714
Test set: Average loss: 1.4451, Accuracy: 1780/5000 (36%)
[epoch 5] loss: 0.9177566
Test set: Average loss: 1.4169, Accuracy: 1869/5000 (37%)
[epoch 6] loss: 0.8483555
Test set: Average loss: 1.3940, Accuracy: 1965/5000 (39%)
[epoch 7] loss: 0.7669667
Test set: Average loss: 1.3780, Accuracy: 2034/5000 (41%)
[epoch 8] loss: 0.7229138
Test set: Average loss: 1.3664, Accuracy: 2104/5000 (42%)
[epoch 9] loss: 0.6935985
Test set: Average loss: 1.3582, Accuracy: 2137/5000 (43%)
[epoch 10] loss: 0.6370088
Test set: Average loss: 1.3519, Accuracy: 2167/5000 (43%)
[epoch 11] loss: 0.6161346
Test set: Average loss: 1.3467, Accuracy: 2184/5000 (44%)
[epoch 12] loss: 0.5719965
Test set: Average loss: 1.3421, Accuracy: 2199/5000 (44%)
[epoch 13] loss: 0.5616738
Test set: Average loss: 1.3384, Accuracy: 2214/5000 (44%)
[epoch 14] loss: 0.5209021
Test set: Average loss: 1.3356, Accuracy: 2216/5000 (44%)
[epoch 15] loss: 0.5287748
Epoch 14: reducing learning rate of group 0 to 5.0000e-06.
Test set: Average loss: 1.3333, Accuracy: 2216/5000 (44%)
[epoch 16] loss: 0.4947310
Test set: Average loss: 1.3331, Accuracy: 2214/5000 (44%)
[epoch 17] loss: 0.5053857
Epoch 16: reducing learning rate of group 0 to 5.0000e-07.
Test set: Average loss: 1.3329, Accuracy: 2216/5000 (44%)
[epoch 18] loss: 0.4909814
Test set: Average loss: 1.3329, Accuracy: 2216/5000 (44%)
[epoch 19] loss: 0.5004295
Epoch 18: reducing learning rate of group 0 to 5.0000e-08.
Test set: Average loss: 1.3329, Accuracy: 2215/5000 (44%)
[epoch 20] loss: 0.4975992
Epoch 19: reducing learning rate of group 0 to 5.0000e-09.
Test set: Average loss: 1.3329, Accuracy: 2216/5000 (44%)
[epoch 21] loss: 0.5028720
Epoch 20: reducing learning rate of group 0 to 5.0000e-10.
Test set: Average loss: 1.3329, Accuracy: 2216/5000 (44%)
[epoch 22] loss: 0.4991602
Epoch 21: reducing learning rate of group 0 to 5.0000e-11.
Test set: Average loss: 1.3329, Accuracy: 2216/5000 (44%)
[epoch 23] loss: 0.4916634
Epoch 22: reducing learning rate of group 0 to 5.0000e-12.
Test set: Average loss: 1.3329, Accuracy: 2216/5000 (44%)
[epoch 24] loss: 0.4986034
Epoch 23: reducing learning rate of group 0 to 5.0000e-13.
Test set: Average loss: 1.3329, Accuracy: 2216/5000 (44%)
[epoch 25] loss: 0.4862083
Test set: Average loss: 1.3329, Accuracy: 2216/5000 (44%)
Validation:
Test set: Average loss: 1.3329, Accuracy: 2216/5000 (44%)
Test
Test set: Average loss: 1.3495, Accuracy: 2229/5000 (45%)
Test set: Average loss: 0.5021, Accuracy: 50/50 (100%)
## seed: 12
Validation accuracy before training:
Test set: Average loss: 1.7747, Accuracy: 704/5000 (14%)
[epoch 1] loss: 1.7139125
Test set: Average loss: 1.6692, Accuracy: 981/5000 (20%)
[epoch 2] loss: 1.2970801
Test set: Average loss: 1.5691, Accuracy: 1368/5000 (27%)
[epoch 3] loss: 1.0333468
Test set: Average loss: 1.4984, Accuracy: 1684/5000 (34%)
[epoch 4] loss: 0.8761077
Test set: Average loss: 1.4538, Accuracy: 1891/5000 (38%)
[epoch 5] loss: 0.7678394
Test set: Average loss: 1.4277, Accuracy: 1997/5000 (40%)
[epoch 6] loss: 0.7057763
Test set: Average loss: 1.4135, Accuracy: 2057/5000 (41%)
[epoch 7] loss: 0.6546351
Test set: Average loss: 1.4054, Accuracy: 2098/5000 (42%)
[epoch 8] loss: 0.6032367
Test set: Average loss: 1.4000, Accuracy: 2123/5000 (42%)
[epoch 9] loss: 0.5713032
Test set: Average loss: 1.3967, Accuracy: 2130/5000 (43%)
[epoch 10] loss: 0.5329474
Test set: Average loss: 1.3942, Accuracy: 2137/5000 (43%)
[epoch 11] loss: 0.5067827
Test set: Average loss: 1.3918, Accuracy: 2137/5000 (43%)
[epoch 12] loss: 0.4945004
Test set: Average loss: 1.3894, Accuracy: 2152/5000 (43%)
[epoch 13] loss: 0.4671081
Test set: Average loss: 1.3876, Accuracy: 2162/5000 (43%)
[epoch 14] loss: 0.4577177
Test set: Average loss: 1.3867, Accuracy: 2167/5000 (43%)
[epoch 15] loss: 0.4478671
Test set: Average loss: 1.3861, Accuracy: 2165/5000 (43%)
[epoch 16] loss: 0.4146807
Test set: Average loss: 1.3862, Accuracy: 2164/5000 (43%)
[epoch 17] loss: 0.4102789
Test set: Average loss: 1.3861, Accuracy: 2168/5000 (43%)
[epoch 18] loss: 0.3862524
Test set: Average loss: 1.3861, Accuracy: 2162/5000 (43%)
[epoch 19] loss: 0.3904331
Epoch 18: reducing learning rate of group 0 to 5.0000e-06.
Test set: Average loss: 1.3857, Accuracy: 2167/5000 (43%)
[epoch 20] loss: 0.3900391
Epoch 19: reducing learning rate of group 0 to 5.0000e-07.
Test set: Average loss: 1.3856, Accuracy: 2170/5000 (43%)
[epoch 21] loss: 0.3762243
Test set: Average loss: 1.3856, Accuracy: 2171/5000 (43%)
[epoch 22] loss: 0.3792742
Epoch 21: reducing learning rate of group 0 to 5.0000e-08.
Test set: Average loss: 1.3856, Accuracy: 2171/5000 (43%)
[epoch 23] loss: 0.3980740
Epoch 22: reducing learning rate of group 0 to 5.0000e-09.
Test set: Average loss: 1.3856, Accuracy: 2171/5000 (43%)
[epoch 24] loss: 0.3779379
Epoch 23: reducing learning rate of group 0 to 5.0000e-10.
Test set: Average loss: 1.3856, Accuracy: 2171/5000 (43%)
[epoch 25] loss: 0.3877640
Epoch 24: reducing learning rate of group 0 to 5.0000e-11.
Test set: Average loss: 1.3856, Accuracy: 2171/5000 (43%)
Validation:
Test set: Average loss: 1.3856, Accuracy: 2171/5000 (43%)
Test
Test set: Average loss: 1.4042, Accuracy: 2184/5000 (44%)
Test set: Average loss: 0.3835, Accuracy: 50/50 (100%)
## seed: 13
Validation accuracy before training:
Test set: Average loss: 1.8123, Accuracy: 506/5000 (10%)
[epoch 1] loss: 1.7602909
Test set: Average loss: 1.6858, Accuracy: 846/5000 (17%)
[epoch 2] loss: 1.3630066
Test set: Average loss: 1.5862, Accuracy: 1417/5000 (28%)
[epoch 3] loss: 1.1441114
Test set: Average loss: 1.5172, Accuracy: 1748/5000 (35%)
[epoch 4] loss: 0.9748846
Test set: Average loss: 1.4740, Accuracy: 1935/5000 (39%)
[epoch 5] loss: 0.8466148
Test set: Average loss: 1.4449, Accuracy: 2029/5000 (41%)
[epoch 6] loss: 0.7994261
Test set: Average loss: 1.4258, Accuracy: 2070/5000 (41%)
[epoch 7] loss: 0.7476962
Test set: Average loss: 1.4119, Accuracy: 2107/5000 (42%)
[epoch 8] loss: 0.6653973
Test set: Average loss: 1.4015, Accuracy: 2128/5000 (43%)
[epoch 9] loss: 0.6340663
Test set: Average loss: 1.3940, Accuracy: 2155/5000 (43%)
[epoch 10] loss: 0.5960047
Test set: Average loss: 1.3881, Accuracy: 2173/5000 (43%)
[epoch 11] loss: 0.5546769
Test set: Average loss: 1.3840, Accuracy: 2197/5000 (44%)
[epoch 12] loss: 0.5214798
Test set: Average loss: 1.3810, Accuracy: 2212/5000 (44%)
[epoch 13] loss: 0.5239948
Epoch 12: reducing learning rate of group 0 to 5.0000e-06.
Test set: Average loss: 1.3784, Accuracy: 2215/5000 (44%)
[epoch 14] loss: 0.5036896
Test set: Average loss: 1.3782, Accuracy: 2215/5000 (44%)
[epoch 15] loss: 0.5063898
Epoch 14: reducing learning rate of group 0 to 5.0000e-07.
Test set: Average loss: 1.3779, Accuracy: 2214/5000 (44%)
[epoch 16] loss: 0.5059725
Epoch 15: reducing learning rate of group 0 to 5.0000e-08.
Test set: Average loss: 1.3779, Accuracy: 2215/5000 (44%)
[epoch 17] loss: 0.4960009
Test set: Average loss: 1.3779, Accuracy: 2215/5000 (44%)
[epoch 18] loss: 0.4807033
Test set: Average loss: 1.3779, Accuracy: 2215/5000 (44%)
[epoch 19] loss: 0.4914667
Epoch 18: reducing learning rate of group 0 to 5.0000e-09.
Test set: Average loss: 1.3779, Accuracy: 2215/5000 (44%)
[epoch 20] loss: 0.4955980
Epoch 19: reducing learning rate of group 0 to 5.0000e-10.
Test set: Average loss: 1.3779, Accuracy: 2215/5000 (44%)
[epoch 21] loss: 0.4787344
Test set: Average loss: 1.3779, Accuracy: 2215/5000 (44%)
[epoch 22] loss: 0.4809717
Epoch 21: reducing learning rate of group 0 to 5.0000e-11.
Test set: Average loss: 1.3779, Accuracy: 2215/5000 (44%)
[epoch 23] loss: 0.4922803
Epoch 22: reducing learning rate of group 0 to 5.0000e-12.
Test set: Average loss: 1.3779, Accuracy: 2215/5000 (44%)
[epoch 24] loss: 0.4897672
Epoch 23: reducing learning rate of group 0 to 5.0000e-13.
Test set: Average loss: 1.3779, Accuracy: 2215/5000 (44%)
[epoch 25] loss: 0.4921352
Epoch 24: reducing learning rate of group 0 to 5.0000e-14.
Test set: Average loss: 1.3779, Accuracy: 2215/5000 (44%)
Validation:
Test set: Average loss: 1.3779, Accuracy: 2215/5000 (44%)
Test
Test set: Average loss: 1.3874, Accuracy: 2207/5000 (44%)
Test set: Average loss: 0.4925, Accuracy: 48/50 (96%)
100
## seed: 11
Validation accuracy before training:
Test set: Average loss: 1.6910, Accuracy: 855/5000 (17%)
[epoch 1] loss: 1.5288449
Test set: Average loss: 1.5803, Accuracy: 1438/5000 (29%)
[epoch 2] loss: 1.2984132
Test set: Average loss: 1.5225, Accuracy: 1611/5000 (32%)
[epoch 3] loss: 1.0986320
Test set: Average loss: 1.4878, Accuracy: 1652/5000 (33%)
[epoch 4] loss: 0.9639573
Test set: Average loss: 1.4607, Accuracy: 1741/5000 (35%)
[epoch 5] loss: 0.8085947
Test set: Average loss: 1.4386, Accuracy: 1853/5000 (37%)
[epoch 6] loss: 0.8305256
Epoch 5: reducing learning rate of group 0 to 5.0000e-06.
Test set: Average loss: 1.4262, Accuracy: 1910/5000 (38%)
[epoch 7] loss: 0.7531688
Test set: Average loss: 1.4254, Accuracy: 1914/5000 (38%)
[epoch 8] loss: 0.7096684
Test set: Average loss: 1.4242, Accuracy: 1925/5000 (38%)
[epoch 9] loss: 0.7695224
Epoch 8: reducing learning rate of group 0 to 5.0000e-07.
Test set: Average loss: 1.4228, Accuracy: 1928/5000 (39%)
[epoch 10] loss: 0.7337472
Epoch 9: reducing learning rate of group 0 to 5.0000e-08.
Test set: Average loss: 1.4226, Accuracy: 1928/5000 (39%)
[epoch 11] loss: 0.7209174
Epoch 10: reducing learning rate of group 0 to 5.0000e-09.
Test set: Average loss: 1.4226, Accuracy: 1928/5000 (39%)
[epoch 12] loss: 0.7122145
Epoch 11: reducing learning rate of group 0 to 5.0000e-10.
Test set: Average loss: 1.4226, Accuracy: 1928/5000 (39%)
[epoch 13] loss: 0.6949266
Test set: Average loss: 1.4226, Accuracy: 1928/5000 (39%)
[epoch 14] loss: 0.7850474
Epoch 13: reducing learning rate of group 0 to 5.0000e-11.
Test set: Average loss: 1.4226, Accuracy: 1928/5000 (39%)
[epoch 15] loss: 0.7338854
Epoch 14: reducing learning rate of group 0 to 5.0000e-12.
Test set: Average loss: 1.4226, Accuracy: 1928/5000 (39%)
[epoch 16] loss: 0.8013330
Epoch 15: reducing learning rate of group 0 to 5.0000e-13.
Test set: Average loss: 1.4226, Accuracy: 1928/5000 (39%)
[epoch 17] loss: 0.7896908
Epoch 16: reducing learning rate of group 0 to 5.0000e-14.
Test set: Average loss: 1.4226, Accuracy: 1928/5000 (39%)
[epoch 18] loss: 0.7484100
Epoch 17: reducing learning rate of group 0 to 5.0000e-15.
Test set: Average loss: 1.4226, Accuracy: 1928/5000 (39%)
[epoch 19] loss: 0.7569707
Epoch 18: reducing learning rate of group 0 to 5.0000e-16.
Test set: Average loss: 1.4226, Accuracy: 1928/5000 (39%)
[epoch 20] loss: 0.7121266
Epoch 19: reducing learning rate of group 0 to 5.0000e-17.
Test set: Average loss: 1.4226, Accuracy: 1928/5000 (39%)
[epoch 21] loss: 0.7790699
Epoch 20: reducing learning rate of group 0 to 5.0000e-18.
Test set: Average loss: 1.4226, Accuracy: 1928/5000 (39%)
[epoch 22] loss: 0.6934247
Test set: Average loss: 1.4226, Accuracy: 1928/5000 (39%)
[epoch 23] loss: 0.6937114
Epoch 22: reducing learning rate of group 0 to 5.0000e-19.
Test set: Average loss: 1.4226, Accuracy: 1928/5000 (39%)
[epoch 24] loss: 0.7351748
Epoch 23: reducing learning rate of group 0 to 5.0000e-20.
Test set: Average loss: 1.4226, Accuracy: 1928/5000 (39%)
[epoch 25] loss: 0.7370153
Epoch 24: reducing learning rate of group 0 to 5.0000e-21.
Test set: Average loss: 1.4226, Accuracy: 1928/5000 (39%)
Validation:
Test set: Average loss: 1.4226, Accuracy: 1928/5000 (39%)
Test
Test set: Average loss: 1.4455, Accuracy: 1907/5000 (38%)
Test set: Average loss: 0.7323, Accuracy: 90/100 (90%)
## seed: 12
Validation accuracy before training:
Test set: Average loss: 1.7254, Accuracy: 835/5000 (17%)
[epoch 1] loss: 1.7696081
Test set: Average loss: 1.5740, Accuracy: 1463/5000 (29%)
[epoch 2] loss: 1.3088107
Test set: Average loss: 1.5012, Accuracy: 1753/5000 (35%)
[epoch 3] loss: 1.0235586
Test set: Average loss: 1.4447, Accuracy: 1972/5000 (39%)
[epoch 4] loss: 0.9422729
Test set: Average loss: 1.4103, Accuracy: 2078/5000 (42%)
[epoch 5] loss: 0.9011756
Test set: Average loss: 1.3913, Accuracy: 2122/5000 (42%)
[epoch 6] loss: 0.7494278
Test set: Average loss: 1.3812, Accuracy: 2161/5000 (43%)
[epoch 7] loss: 0.7341993
Test set: Average loss: 1.3771, Accuracy: 2180/5000 (44%)
[epoch 8] loss: 0.6425199
Test set: Average loss: 1.3709, Accuracy: 2200/5000 (44%)
[epoch 9] loss: 0.6054434
Test set: Average loss: 1.3643, Accuracy: 2203/5000 (44%)
[epoch 10] loss: 0.5809552
Test set: Average loss: 1.3588, Accuracy: 2207/5000 (44%)
[epoch 11] loss: 0.5838198
Epoch 10: reducing learning rate of group 0 to 5.0000e-06.
Test set: Average loss: 1.3550, Accuracy: 2223/5000 (44%)
[epoch 12] loss: 0.5578632
Test set: Average loss: 1.3548, Accuracy: 2222/5000 (44%)
[epoch 13] loss: 0.5828255
Epoch 12: reducing learning rate of group 0 to 5.0000e-07.
Test set: Average loss: 1.3546, Accuracy: 2222/5000 (44%)
[epoch 14] loss: 0.5769582
Epoch 13: reducing learning rate of group 0 to 5.0000e-08.
Test set: Average loss: 1.3546, Accuracy: 2222/5000 (44%)
[epoch 15] loss: 0.5455141
Test set: Average loss: 1.3546, Accuracy: 2222/5000 (44%)
[epoch 16] loss: 0.5851114
Epoch 15: reducing learning rate of group 0 to 5.0000e-09.
Test set: Average loss: 1.3546, Accuracy: 2222/5000 (44%)
[epoch 17] loss: 0.5866942
Epoch 16: reducing learning rate of group 0 to 5.0000e-10.
Test set: Average loss: 1.3546, Accuracy: 2222/5000 (44%)
[epoch 18] loss: 0.5407230
Test set: Average loss: 1.3546, Accuracy: 2222/5000 (44%)
[epoch 19] loss: 0.5955454
Epoch 18: reducing learning rate of group 0 to 5.0000e-11.
Test set: Average loss: 1.3546, Accuracy: 2222/5000 (44%)
[epoch 20] loss: 0.5603812
Epoch 19: reducing learning rate of group 0 to 5.0000e-12.
Test set: Average loss: 1.3546, Accuracy: 2222/5000 (44%)
[epoch 21] loss: 0.5218691
Test set: Average loss: 1.3546, Accuracy: 2222/5000 (44%)
[epoch 22] loss: 0.5684317
Epoch 21: reducing learning rate of group 0 to 5.0000e-13.
Test set: Average loss: 1.3546, Accuracy: 2222/5000 (44%)
[epoch 23] loss: 0.5765377
Epoch 22: reducing learning rate of group 0 to 5.0000e-14.
Test set: Average loss: 1.3546, Accuracy: 2222/5000 (44%)
[epoch 24] loss: 0.5569461
Epoch 23: reducing learning rate of group 0 to 5.0000e-15.
Test set: Average loss: 1.3546, Accuracy: 2222/5000 (44%)
[epoch 25] loss: 0.5621375
Epoch 24: reducing learning rate of group 0 to 5.0000e-16.
Test set: Average loss: 1.3546, Accuracy: 2222/5000 (44%)
Validation:
Test set: Average loss: 1.3550, Accuracy: 2223/5000 (44%)
Test
Test set: Average loss: 1.3708, Accuracy: 2119/5000 (42%)
Test set: Average loss: 0.5636, Accuracy: 96/100 (96%)
## seed: 13
Validation accuracy before training:
Test set: Average loss: 1.5250, Accuracy: 1706/5000 (34%)
[epoch 1] loss: 1.4332034
Test set: Average loss: 1.4001, Accuracy: 2025/5000 (40%)
[epoch 2] loss: 1.0687959
Test set: Average loss: 1.3409, Accuracy: 2328/5000 (47%)
[epoch 3] loss: 0.9714901
Test set: Average loss: 1.3110, Accuracy: 2441/5000 (49%)
[epoch 4] loss: 0.7492681
Test set: Average loss: 1.2963, Accuracy: 2518/5000 (50%)
[epoch 5] loss: 0.6756447
Test set: Average loss: 1.2887, Accuracy: 2565/5000 (51%)
[epoch 6] loss: 0.6275140
Test set: Average loss: 1.2859, Accuracy: 2555/5000 (51%)
[epoch 7] loss: 0.5805653
Test set: Average loss: 1.2830, Accuracy: 2544/5000 (51%)
[epoch 8] loss: 0.5496252
Test set: Average loss: 1.2775, Accuracy: 2550/5000 (51%)
[epoch 9] loss: 0.4843435
Test set: Average loss: 1.2728, Accuracy: 2559/5000 (51%)
[epoch 10] loss: 0.4582891
Test set: Average loss: 1.2682, Accuracy: 2576/5000 (52%)
[epoch 11] loss: 0.4600537
Epoch 10: reducing learning rate of group 0 to 5.0000e-06.
Test set: Average loss: 1.2615, Accuracy: 2608/5000 (52%)
[epoch 12] loss: 0.4173390
Test set: Average loss: 1.2608, Accuracy: 2612/5000 (52%)
[epoch 13] loss: 0.4025665
Test set: Average loss: 1.2603, Accuracy: 2609/5000 (52%)
[epoch 14] loss: 0.4388798
Epoch 13: reducing learning rate of group 0 to 5.0000e-07.
Test set: Average loss: 1.2596, Accuracy: 2612/5000 (52%)
[epoch 15] loss: 0.4474449
Epoch 14: reducing learning rate of group 0 to 5.0000e-08.
Test set: Average loss: 1.2596, Accuracy: 2612/5000 (52%)
[epoch 16] loss: 0.4241288
Epoch 15: reducing learning rate of group 0 to 5.0000e-09.
Test set: Average loss: 1.2595, Accuracy: 2612/5000 (52%)
[epoch 17] loss: 0.4177889
Epoch 16: reducing learning rate of group 0 to 5.0000e-10.
Test set: Average loss: 1.2595, Accuracy: 2612/5000 (52%)
[epoch 18] loss: 0.4488771
Epoch 17: reducing learning rate of group 0 to 5.0000e-11.
Test set: Average loss: 1.2595, Accuracy: 2612/5000 (52%)
[epoch 19] loss: 0.4176044
Epoch 18: reducing learning rate of group 0 to 5.0000e-12.
Test set: Average loss: 1.2595, Accuracy: 2612/5000 (52%)
[epoch 20] loss: 0.4951437
Epoch 19: reducing learning rate of group 0 to 5.0000e-13.
Test set: Average loss: 1.2595, Accuracy: 2612/5000 (52%)
[epoch 21] loss: 0.4028525
Epoch 20: reducing learning rate of group 0 to 5.0000e-14.
Test set: Average loss: 1.2595, Accuracy: 2612/5000 (52%)
[epoch 22] loss: 0.4481593
Epoch 21: reducing learning rate of group 0 to 5.0000e-15.
Test set: Average loss: 1.2595, Accuracy: 2612/5000 (52%)
[epoch 23] loss: 0.4296760
Epoch 22: reducing learning rate of group 0 to 5.0000e-16.
Test set: Average loss: 1.2595, Accuracy: 2612/5000 (52%)
[epoch 24] loss: 0.4424298
Epoch 23: reducing learning rate of group 0 to 5.0000e-17.
Test set: Average loss: 1.2595, Accuracy: 2612/5000 (52%)
[epoch 25] loss: 0.4903677
Epoch 24: reducing learning rate of group 0 to 5.0000e-18.
Test set: Average loss: 1.2595, Accuracy: 2612/5000 (52%)
Validation:
Test set: Average loss: 1.2595, Accuracy: 2612/5000 (52%)
Test
Test set: Average loss: 1.2751, Accuracy: 2612/5000 (52%)
Test set: Average loss: 0.4386, Accuracy: 98/100 (98%)
250
## seed: 11
Validation accuracy before training:
Test set: Average loss: 1.5615, Accuracy: 1335/5000 (27%)
[epoch 1] loss: 1.4318891
Test set: Average loss: 1.3453, Accuracy: 2321/5000 (46%)
[epoch 2] loss: 1.0797881
Test set: Average loss: 1.2828, Accuracy: 2429/5000 (49%)
[epoch 3] loss: 0.9219168
Test set: Average loss: 1.2448, Accuracy: 2575/5000 (52%)
[epoch 4] loss: 0.8060532
Test set: Average loss: 1.2278, Accuracy: 2633/5000 (53%)
[epoch 5] loss: 0.7275382
Test set: Average loss: 1.2237, Accuracy: 2628/5000 (53%)
[epoch 6] loss: 0.6696231
Test set: Average loss: 1.2151, Accuracy: 2649/5000 (53%)
[epoch 7] loss: 0.6240587
Test set: Average loss: 1.2063, Accuracy: 2691/5000 (54%)
[epoch 8] loss: 0.5863120
Test set: Average loss: 1.2066, Accuracy: 2641/5000 (53%)
[epoch 9] loss: 0.5529956
Test set: Average loss: 1.2038, Accuracy: 2652/5000 (53%)
[epoch 10] loss: 0.5231005
Test set: Average loss: 1.1960, Accuracy: 2693/5000 (54%)
[epoch 11] loss: 0.4980751
Test set: Average loss: 1.1935, Accuracy: 2709/5000 (54%)
[epoch 12] loss: 0.4781616
Test set: Average loss: 1.1949, Accuracy: 2689/5000 (54%)
[epoch 13] loss: 0.4609141
Test set: Average loss: 1.1939, Accuracy: 2672/5000 (53%)
[epoch 14] loss: 0.4437665
Test set: Average loss: 1.1912, Accuracy: 2711/5000 (54%)
[epoch 15] loss: 0.4289720
Test set: Average loss: 1.1912, Accuracy: 2723/5000 (54%)
[epoch 16] loss: 0.4159280
Test set: Average loss: 1.1903, Accuracy: 2731/5000 (55%)
[epoch 17] loss: 0.4037305
Test set: Average loss: 1.1917, Accuracy: 2719/5000 (54%)
[epoch 18] loss: 0.3935203
Test set: Average loss: 1.1892, Accuracy: 2740/5000 (55%)
[epoch 19] loss: 0.3849404
Test set: Average loss: 1.1898, Accuracy: 2737/5000 (55%)
[epoch 20] loss: 0.3740116
Test set: Average loss: 1.1896, Accuracy: 2735/5000 (55%)
[epoch 21] loss: 0.3657833
Test set: Average loss: 1.1914, Accuracy: 2738/5000 (55%)
[epoch 22] loss: 0.3586072
Test set: Average loss: 1.1913, Accuracy: 2739/5000 (55%)
[epoch 23] loss: 0.3496169
Test set: Average loss: 1.1919, Accuracy: 2742/5000 (55%)
[epoch 24] loss: 0.3417353
Test set: Average loss: 1.1910, Accuracy: 2743/5000 (55%)
[epoch 25] loss: 0.3317356
Test set: Average loss: 1.1941, Accuracy: 2720/5000 (54%)
Validation:
Test set: Average loss: 1.1910, Accuracy: 2743/5000 (55%)
Test
Test set: Average loss: 1.2003, Accuracy: 2687/5000 (54%)
Test set: Average loss: 0.3352, Accuracy: 250/250 (100%)
## seed: 12
Validation accuracy before training:
Test set: Average loss: 1.7166, Accuracy: 1308/5000 (26%)
[epoch 1] loss: 1.6606709
Test set: Average loss: 1.5019, Accuracy: 1801/5000 (36%)
[epoch 2] loss: 1.2317414
Test set: Average loss: 1.3910, Accuracy: 2212/5000 (44%)
[epoch 3] loss: 1.0255417
Test set: Average loss: 1.3437, Accuracy: 2381/5000 (48%)
[epoch 4] loss: 0.8853288
Test set: Average loss: 1.3100, Accuracy: 2466/5000 (49%)
[epoch 5] loss: 0.7713291
Test set: Average loss: 1.2951, Accuracy: 2495/5000 (50%)
[epoch 6] loss: 0.7014126
Test set: Average loss: 1.2803, Accuracy: 2546/5000 (51%)
[epoch 7] loss: 0.6368383
Test set: Average loss: 1.2723, Accuracy: 2563/5000 (51%)
[epoch 8] loss: 0.5887223
Test set: Average loss: 1.2664, Accuracy: 2583/5000 (52%)
[epoch 9] loss: 0.5462825
Test set: Average loss: 1.2645, Accuracy: 2576/5000 (52%)
[epoch 10] loss: 0.5132232
Test set: Average loss: 1.2590, Accuracy: 2578/5000 (52%)
[epoch 11] loss: 0.4891536
Test set: Average loss: 1.2557, Accuracy: 2579/5000 (52%)
[epoch 12] loss: 0.4597994
Test set: Average loss: 1.2542, Accuracy: 2588/5000 (52%)
[epoch 13] loss: 0.4353708
Test set: Average loss: 1.2488, Accuracy: 2608/5000 (52%)
[epoch 14] loss: 0.4162939
Test set: Average loss: 1.2502, Accuracy: 2603/5000 (52%)
[epoch 15] loss: 0.3944812
Test set: Average loss: 1.2513, Accuracy: 2607/5000 (52%)
[epoch 16] loss: 0.3771479
Test set: Average loss: 1.2478, Accuracy: 2614/5000 (52%)
[epoch 17] loss: 0.3608873
Test set: Average loss: 1.2469, Accuracy: 2620/5000 (52%)
[epoch 18] loss: 0.3488301
Test set: Average loss: 1.2483, Accuracy: 2605/5000 (52%)
[epoch 19] loss: 0.3334153
Test set: Average loss: 1.2476, Accuracy: 2614/5000 (52%)
[epoch 20] loss: 0.3226850
Test set: Average loss: 1.2468, Accuracy: 2605/5000 (52%)
[epoch 21] loss: 0.3112307
Test set: Average loss: 1.2464, Accuracy: 2591/5000 (52%)
[epoch 22] loss: 0.3008909
Test set: Average loss: 1.2454, Accuracy: 2594/5000 (52%)
[epoch 23] loss: 0.2924931
Test set: Average loss: 1.2435, Accuracy: 2603/5000 (52%)
[epoch 24] loss: 0.2816158
Test set: Average loss: 1.2430, Accuracy: 2611/5000 (52%)
[epoch 25] loss: 0.2736880
Test set: Average loss: 1.2428, Accuracy: 2609/5000 (52%)
Validation:
Test set: Average loss: 1.2469, Accuracy: 2620/5000 (52%)
Test
Test set: Average loss: 1.2467, Accuracy: 2595/5000 (52%)
Test set: Average loss: 0.3511, Accuracy: 249/250 (100%)
## seed: 13
Validation accuracy before training:
Test set: Average loss: 1.8152, Accuracy: 522/5000 (10%)
[epoch 1] loss: 1.7317548
Test set: Average loss: 1.5342, Accuracy: 1675/5000 (34%)
[epoch 2] loss: 1.2528162
Test set: Average loss: 1.3976, Accuracy: 2302/5000 (46%)
[epoch 3] loss: 1.0268553
Test set: Average loss: 1.3330, Accuracy: 2486/5000 (50%)
[epoch 4] loss: 0.8813597
Test set: Average loss: 1.3066, Accuracy: 2529/5000 (51%)
[epoch 5] loss: 0.7728436
Test set: Average loss: 1.2950, Accuracy: 2533/5000 (51%)
[epoch 6] loss: 0.6954745
Test set: Average loss: 1.2853, Accuracy: 2542/5000 (51%)
[epoch 7] loss: 0.6330876
Test set: Average loss: 1.2781, Accuracy: 2566/5000 (51%)
[epoch 8] loss: 0.5771171
Test set: Average loss: 1.2717, Accuracy: 2587/5000 (52%)
[epoch 9] loss: 0.5386585
Test set: Average loss: 1.2683, Accuracy: 2603/5000 (52%)
[epoch 10] loss: 0.5096881
Test set: Average loss: 1.2647, Accuracy: 2621/5000 (52%)
[epoch 11] loss: 0.4809432
Test set: Average loss: 1.2631, Accuracy: 2610/5000 (52%)
[epoch 12] loss: 0.4550491
Test set: Average loss: 1.2601, Accuracy: 2614/5000 (52%)
[epoch 13] loss: 0.4368779
Test set: Average loss: 1.2567, Accuracy: 2627/5000 (53%)
[epoch 14] loss: 0.4162316
Test set: Average loss: 1.2579, Accuracy: 2605/5000 (52%)
[epoch 15] loss: 0.4001929
Test set: Average loss: 1.2554, Accuracy: 2612/5000 (52%)
[epoch 16] loss: 0.3882944
Test set: Average loss: 1.2594, Accuracy: 2600/5000 (52%)
[epoch 17] loss: 0.3732253
Test set: Average loss: 1.2559, Accuracy: 2607/5000 (52%)
[epoch 18] loss: 0.3603687
Test set: Average loss: 1.2537, Accuracy: 2614/5000 (52%)
[epoch 19] loss: 0.3484419
Test set: Average loss: 1.2571, Accuracy: 2595/5000 (52%)
[epoch 20] loss: 0.3360104
Test set: Average loss: 1.2564, Accuracy: 2598/5000 (52%)
[epoch 21] loss: 0.3255599
Test set: Average loss: 1.2542, Accuracy: 2616/5000 (52%)
[epoch 22] loss: 0.3153033
Test set: Average loss: 1.2549, Accuracy: 2613/5000 (52%)
[epoch 23] loss: 0.3076830
Test set: Average loss: 1.2529, Accuracy: 2620/5000 (52%)
[epoch 24] loss: 0.2992287
Test set: Average loss: 1.2536, Accuracy: 2632/5000 (53%)
[epoch 25] loss: 0.2900726
Test set: Average loss: 1.2532, Accuracy: 2620/5000 (52%)
Validation:
Test set: Average loss: 1.2536, Accuracy: 2632/5000 (53%)
Test
Test set: Average loss: 1.2709, Accuracy: 2617/5000 (52%)
Test set: Average loss: 0.2930, Accuracy: 248/250 (99%)
500
## seed: 11
Validation accuracy before training:
Test set: Average loss: 1.8229, Accuracy: 869/5000 (17%)
[epoch 1] loss: 1.6012398
Test set: Average loss: 1.3489, Accuracy: 2221/5000 (44%)
[epoch 2] loss: 1.1380962
Test set: Average loss: 1.2531, Accuracy: 2471/5000 (49%)
[epoch 3] loss: 0.9653989
Test set: Average loss: 1.2143, Accuracy: 2586/5000 (52%)
[epoch 4] loss: 0.8517543
Test set: Average loss: 1.1940, Accuracy: 2649/5000 (53%)
[epoch 5] loss: 0.7633143
Test set: Average loss: 1.1821, Accuracy: 2687/5000 (54%)
[epoch 6] loss: 0.6972543
Test set: Average loss: 1.1691, Accuracy: 2751/5000 (55%)
[epoch 7] loss: 0.6469144
Test set: Average loss: 1.1600, Accuracy: 2767/5000 (55%)
[epoch 8] loss: 0.6043134
Test set: Average loss: 1.1519, Accuracy: 2806/5000 (56%)
[epoch 9] loss: 0.5657656
Test set: Average loss: 1.1444, Accuracy: 2824/5000 (56%)
[epoch 10] loss: 0.5329146
Test set: Average loss: 1.1376, Accuracy: 2825/5000 (56%)
[epoch 11] loss: 0.5022803
Test set: Average loss: 1.1336, Accuracy: 2843/5000 (57%)
[epoch 12] loss: 0.4786967
Test set: Average loss: 1.1321, Accuracy: 2846/5000 (57%)
[epoch 13] loss: 0.4525306
Test set: Average loss: 1.1268, Accuracy: 2853/5000 (57%)
[epoch 14] loss: 0.4328145
Test set: Average loss: 1.1238, Accuracy: 2868/5000 (57%)
[epoch 15] loss: 0.4143879
Test set: Average loss: 1.1240, Accuracy: 2857/5000 (57%)
[epoch 16] loss: 0.3931911
Test set: Average loss: 1.1202, Accuracy: 2884/5000 (58%)
[epoch 17] loss: 0.3765260
Test set: Average loss: 1.1158, Accuracy: 2884/5000 (58%)
[epoch 18] loss: 0.3600753
Test set: Average loss: 1.1146, Accuracy: 2875/5000 (58%)
[epoch 19] loss: 0.3435128
Test set: Average loss: 1.1098, Accuracy: 2893/5000 (58%)
[epoch 20] loss: 0.3321747
Test set: Average loss: 1.1068, Accuracy: 2889/5000 (58%)
[epoch 21] loss: 0.3181250
Test set: Average loss: 1.1100, Accuracy: 2876/5000 (58%)
[epoch 22] loss: 0.3061457
Test set: Average loss: 1.1035, Accuracy: 2902/5000 (58%)
[epoch 23] loss: 0.2952078
Test set: Average loss: 1.1078, Accuracy: 2894/5000 (58%)
[epoch 24] loss: 0.2829635
Test set: Average loss: 1.1034, Accuracy: 2891/5000 (58%)
[epoch 25] loss: 0.2735777
Test set: Average loss: 1.1023, Accuracy: 2892/5000 (58%)
Validation:
Test set: Average loss: 1.1035, Accuracy: 2902/5000 (58%)
Test
Test set: Average loss: 1.1176, Accuracy: 2891/5000 (58%)
Test set: Average loss: 0.2976, Accuracy: 499/500 (100%)
## seed: 12
Validation accuracy before training:
Test set: Average loss: 1.5278, Accuracy: 1518/5000 (30%)
[epoch 1] loss: 1.3048210
Test set: Average loss: 1.2350, Accuracy: 2741/5000 (55%)
[epoch 2] loss: 0.9860003
Test set: Average loss: 1.1800, Accuracy: 2873/5000 (57%)
[epoch 3] loss: 0.8449724
Test set: Average loss: 1.1530, Accuracy: 2945/5000 (59%)
[epoch 4] loss: 0.7453889
Test set: Average loss: 1.1403, Accuracy: 2979/5000 (60%)
[epoch 5] loss: 0.6688037
Test set: Average loss: 1.1263, Accuracy: 3018/5000 (60%)
[epoch 6] loss: 0.6138658
Test set: Average loss: 1.1194, Accuracy: 3023/5000 (60%)
[epoch 7] loss: 0.5659902
Test set: Average loss: 1.1133, Accuracy: 3023/5000 (60%)
[epoch 8] loss: 0.5267329
Test set: Average loss: 1.1035, Accuracy: 3050/5000 (61%)
[epoch 9] loss: 0.4946728
Test set: Average loss: 1.0997, Accuracy: 3040/5000 (61%)
[epoch 10] loss: 0.4681077
Test set: Average loss: 1.0937, Accuracy: 3057/5000 (61%)
[epoch 11] loss: 0.4443786
Test set: Average loss: 1.0827, Accuracy: 3090/5000 (62%)
[epoch 12] loss: 0.4226900
Test set: Average loss: 1.0837, Accuracy: 3065/5000 (61%)
[epoch 13] loss: 0.4044662
Test set: Average loss: 1.0821, Accuracy: 3064/5000 (61%)
[epoch 14] loss: 0.3876759
Test set: Average loss: 1.0757, Accuracy: 3072/5000 (61%)
[epoch 15] loss: 0.3692358
Test set: Average loss: 1.0738, Accuracy: 3079/5000 (62%)
[epoch 16] loss: 0.3528354
Test set: Average loss: 1.0699, Accuracy: 3078/5000 (62%)
[epoch 17] loss: 0.3401223
Test set: Average loss: 1.0684, Accuracy: 3072/5000 (61%)
[epoch 18] loss: 0.3261639
Test set: Average loss: 1.0666, Accuracy: 3065/5000 (61%)
[epoch 19] loss: 0.3146351
Test set: Average loss: 1.0641, Accuracy: 3071/5000 (61%)
[epoch 20] loss: 0.3019963
Test set: Average loss: 1.0628, Accuracy: 3057/5000 (61%)
[epoch 21] loss: 0.2911056
Test set: Average loss: 1.0610, Accuracy: 3062/5000 (61%)
[epoch 22] loss: 0.2799735
Test set: Average loss: 1.0613, Accuracy: 3051/5000 (61%)
[epoch 23] loss: 0.2703356
Test set: Average loss: 1.0591, Accuracy: 3067/5000 (61%)
[epoch 24] loss: 0.2620035
Test set: Average loss: 1.0557, Accuracy: 3065/5000 (61%)
[epoch 25] loss: 0.2527367
Test set: Average loss: 1.0569, Accuracy: 3046/5000 (61%)
Validation:
Test set: Average loss: 1.0827, Accuracy: 3090/5000 (62%)
Test
Test set: Average loss: 1.0940, Accuracy: 3021/5000 (60%)
Test set: Average loss: 0.4275, Accuracy: 497/500 (99%)
## seed: 13
Validation accuracy before training:
Test set: Average loss: 1.7528, Accuracy: 760/5000 (15%)
[epoch 1] loss: 1.5278084
Test set: Average loss: 1.3753, Accuracy: 2174/5000 (43%)
[epoch 2] loss: 1.1412274
Test set: Average loss: 1.2748, Accuracy: 2487/5000 (50%)
[epoch 3] loss: 0.9768419
Test set: Average loss: 1.2370, Accuracy: 2574/5000 (51%)
[epoch 4] loss: 0.8686586
Test set: Average loss: 1.2131, Accuracy: 2690/5000 (54%)
[epoch 5] loss: 0.7779441
Test set: Average loss: 1.1950, Accuracy: 2750/5000 (55%)
[epoch 6] loss: 0.7091445
Test set: Average loss: 1.1917, Accuracy: 2743/5000 (55%)
[epoch 7] loss: 0.6567471
Test set: Average loss: 1.1793, Accuracy: 2790/5000 (56%)
[epoch 8] loss: 0.6160674
Test set: Average loss: 1.1767, Accuracy: 2791/5000 (56%)
[epoch 9] loss: 0.5762671
Test set: Average loss: 1.1667, Accuracy: 2792/5000 (56%)
[epoch 10] loss: 0.5412932
Test set: Average loss: 1.1572, Accuracy: 2827/5000 (57%)
[epoch 11] loss: 0.5106295
Test set: Average loss: 1.1589, Accuracy: 2811/5000 (56%)
[epoch 12] loss: 0.4851937
Test set: Average loss: 1.1494, Accuracy: 2828/5000 (57%)
[epoch 13] loss: 0.4611916
Test set: Average loss: 1.1455, Accuracy: 2840/5000 (57%)
[epoch 14] loss: 0.4413483
Test set: Average loss: 1.1466, Accuracy: 2820/5000 (56%)
[epoch 15] loss: 0.4191566
Test set: Average loss: 1.1421, Accuracy: 2846/5000 (57%)
[epoch 16] loss: 0.4034097
Test set: Average loss: 1.1415, Accuracy: 2853/5000 (57%)
[epoch 17] loss: 0.3855473
Test set: Average loss: 1.1386, Accuracy: 2854/5000 (57%)
[epoch 18] loss: 0.3714625
Test set: Average loss: 1.1357, Accuracy: 2873/5000 (57%)
[epoch 19] loss: 0.3561129
Test set: Average loss: 1.1366, Accuracy: 2851/5000 (57%)
[epoch 20] loss: 0.3410420
Test set: Average loss: 1.1289, Accuracy: 2890/5000 (58%)
[epoch 21] loss: 0.3280880
Test set: Average loss: 1.1321, Accuracy: 2896/5000 (58%)
[epoch 22] loss: 0.3149979
Test set: Average loss: 1.1277, Accuracy: 2906/5000 (58%)
[epoch 23] loss: 0.3060445
Test set: Average loss: 1.1308, Accuracy: 2894/5000 (58%)
[epoch 24] loss: 0.2936374
Test set: Average loss: 1.1277, Accuracy: 2896/5000 (58%)
[epoch 25] loss: 0.2845849
Test set: Average loss: 1.1291, Accuracy: 2887/5000 (58%)
Validation:
Test set: Average loss: 1.1277, Accuracy: 2906/5000 (58%)
Test
Test set: Average loss: 1.1345, Accuracy: 2844/5000 (57%)
Test set: Average loss: 0.3075, Accuracy: 497/500 (99%)
750
## seed: 11
Validation accuracy before training:
Test set: Average loss: 1.5148, Accuracy: 1366/5000 (27%)
[epoch 1] loss: 1.2690031
Test set: Average loss: 1.2272, Accuracy: 2522/5000 (50%)
[epoch 2] loss: 0.9889792
Test set: Average loss: 1.1774, Accuracy: 2782/5000 (56%)
[epoch 3] loss: 0.8701405
Test set: Average loss: 1.1581, Accuracy: 2878/5000 (58%)
[epoch 4] loss: 0.7844031
Test set: Average loss: 1.1388, Accuracy: 2934/5000 (59%)
[epoch 5] loss: 0.7112277
Test set: Average loss: 1.1322, Accuracy: 2964/5000 (59%)
[epoch 6] loss: 0.6584665
Test set: Average loss: 1.1172, Accuracy: 2986/5000 (60%)
[epoch 7] loss: 0.6084677
Test set: Average loss: 1.1054, Accuracy: 3023/5000 (60%)
[epoch 8] loss: 0.5672774
Test set: Average loss: 1.1061, Accuracy: 3004/5000 (60%)
[epoch 9] loss: 0.5284131
Test set: Average loss: 1.0933, Accuracy: 3050/5000 (61%)
[epoch 10] loss: 0.4950649
Test set: Average loss: 1.0900, Accuracy: 3027/5000 (61%)
[epoch 11] loss: 0.4662452
Test set: Average loss: 1.0839, Accuracy: 3052/5000 (61%)
[epoch 12] loss: 0.4377448
Test set: Average loss: 1.0794, Accuracy: 3050/5000 (61%)
[epoch 13] loss: 0.4148224
Test set: Average loss: 1.0746, Accuracy: 3070/5000 (61%)
[epoch 14] loss: 0.3938913
Test set: Average loss: 1.0726, Accuracy: 3061/5000 (61%)
[epoch 15] loss: 0.3704659
Test set: Average loss: 1.0703, Accuracy: 3050/5000 (61%)
[epoch 16] loss: 0.3506946
Test set: Average loss: 1.0716, Accuracy: 3036/5000 (61%)
[epoch 17] loss: 0.3348737
Test set: Average loss: 1.0685, Accuracy: 3051/5000 (61%)
[epoch 18] loss: 0.3192506
Test set: Average loss: 1.0649, Accuracy: 3044/5000 (61%)
[epoch 19] loss: 0.3021858
Test set: Average loss: 1.0643, Accuracy: 3050/5000 (61%)
[epoch 20] loss: 0.2892401
Test set: Average loss: 1.0646, Accuracy: 3048/5000 (61%)
[epoch 21] loss: 0.2730213
Test set: Average loss: 1.0634, Accuracy: 3050/5000 (61%)
[epoch 22] loss: 0.2625226
Test set: Average loss: 1.0659, Accuracy: 3032/5000 (61%)
[epoch 23] loss: 0.2488626
Test set: Average loss: 1.0621, Accuracy: 3051/5000 (61%)
[epoch 24] loss: 0.2389351
Test set: Average loss: 1.0581, Accuracy: 3037/5000 (61%)
[epoch 25] loss: 0.2288941
Test set: Average loss: 1.0608, Accuracy: 3046/5000 (61%)
Validation:
Test set: Average loss: 1.0746, Accuracy: 3070/5000 (61%)
Test
Test set: Average loss: 1.0788, Accuracy: 3055/5000 (61%)
Test set: Average loss: 0.3965, Accuracy: 740/750 (99%)
## seed: 12
Validation accuracy before training:
Test set: Average loss: 1.7398, Accuracy: 852/5000 (17%)
[epoch 1] loss: 1.5095091
Test set: Average loss: 1.3235, Accuracy: 2495/5000 (50%)
[epoch 2] loss: 1.1426258
Test set: Average loss: 1.2495, Accuracy: 2780/5000 (56%)
[epoch 3] loss: 0.9824766
Test set: Average loss: 1.2096, Accuracy: 2865/5000 (57%)
[epoch 4] loss: 0.8757612
Test set: Average loss: 1.1997, Accuracy: 2869/5000 (57%)
[epoch 5] loss: 0.7872293
Test set: Average loss: 1.1810, Accuracy: 2919/5000 (58%)
[epoch 6] loss: 0.7161169
Test set: Average loss: 1.1648, Accuracy: 2932/5000 (59%)
[epoch 7] loss: 0.6550682
Test set: Average loss: 1.1571, Accuracy: 2936/5000 (59%)
[epoch 8] loss: 0.6033073
Test set: Average loss: 1.1432, Accuracy: 2960/5000 (59%)
[epoch 9] loss: 0.5653768
Test set: Average loss: 1.1401, Accuracy: 2931/5000 (59%)
[epoch 10] loss: 0.5242902
Test set: Average loss: 1.1327, Accuracy: 2943/5000 (59%)
[epoch 11] loss: 0.4963973
Test set: Average loss: 1.1242, Accuracy: 2952/5000 (59%)
[epoch 12] loss: 0.4619653
Test set: Average loss: 1.1200, Accuracy: 2961/5000 (59%)
[epoch 13] loss: 0.4359519
Test set: Average loss: 1.1236, Accuracy: 2948/5000 (59%)
[epoch 14] loss: 0.4153403
Test set: Average loss: 1.1204, Accuracy: 2940/5000 (59%)
[epoch 15] loss: 0.3926278
Test set: Average loss: 1.1139, Accuracy: 2964/5000 (59%)
[epoch 16] loss: 0.3694354
Test set: Average loss: 1.1112, Accuracy: 2958/5000 (59%)
[epoch 17] loss: 0.3425251
Test set: Average loss: 1.1133, Accuracy: 2924/5000 (58%)
[epoch 18] loss: 0.3266894
Test set: Average loss: 1.1072, Accuracy: 2953/5000 (59%)
[epoch 19] loss: 0.3069449
Test set: Average loss: 1.1067, Accuracy: 2948/5000 (59%)
[epoch 20] loss: 0.2884886
Test set: Average loss: 1.1061, Accuracy: 2931/5000 (59%)
[epoch 21] loss: 0.2712687
Test set: Average loss: 1.1000, Accuracy: 2967/5000 (59%)
[epoch 22] loss: 0.2564227
Test set: Average loss: 1.1063, Accuracy: 2922/5000 (58%)
[epoch 23] loss: 0.2454155
Test set: Average loss: 1.1053, Accuracy: 2943/5000 (59%)
[epoch 24] loss: 0.2319283
Test set: Average loss: 1.1015, Accuracy: 2937/5000 (59%)
[epoch 25] loss: 0.2224993
Test set: Average loss: 1.1010, Accuracy: 2948/5000 (59%)
Validation:
Test set: Average loss: 1.1000, Accuracy: 2967/5000 (59%)
Test
Test set: Average loss: 1.1154, Accuracy: 2951/5000 (59%)
Test set: Average loss: 0.2592, Accuracy: 748/750 (100%)
## seed: 13
Validation accuracy before training:
Test set: Average loss: 1.6939, Accuracy: 898/5000 (18%)
[epoch 1] loss: 1.3934342
Test set: Average loss: 1.2583, Accuracy: 2604/5000 (52%)
[epoch 2] loss: 1.0358974
Test set: Average loss: 1.1959, Accuracy: 2821/5000 (56%)
[epoch 3] loss: 0.8868025
Test set: Average loss: 1.1613, Accuracy: 2938/5000 (59%)
[epoch 4] loss: 0.7870076
Test set: Average loss: 1.1495, Accuracy: 2950/5000 (59%)
[epoch 5] loss: 0.7072006
Test set: Average loss: 1.1304, Accuracy: 3010/5000 (60%)
[epoch 6] loss: 0.6372075
Test set: Average loss: 1.1191, Accuracy: 3016/5000 (60%)
[epoch 7] loss: 0.5903522
Test set: Average loss: 1.1101, Accuracy: 3043/5000 (61%)
[epoch 8] loss: 0.5431823
Test set: Average loss: 1.1015, Accuracy: 3046/5000 (61%)
[epoch 9] loss: 0.5078677
Test set: Average loss: 1.1005, Accuracy: 3034/5000 (61%)
[epoch 10] loss: 0.4777771
Test set: Average loss: 1.0912, Accuracy: 3030/5000 (61%)
[epoch 11] loss: 0.4470714
Test set: Average loss: 1.0824, Accuracy: 3062/5000 (61%)
[epoch 12] loss: 0.4210007
Test set: Average loss: 1.0792, Accuracy: 3065/5000 (61%)
[epoch 13] loss: 0.3981820
Test set: Average loss: 1.0756, Accuracy: 3058/5000 (61%)
[epoch 14] loss: 0.3766247
Test set: Average loss: 1.0708, Accuracy: 3078/5000 (62%)
[epoch 15] loss: 0.3558543
Test set: Average loss: 1.0698, Accuracy: 3079/5000 (62%)
[epoch 16] loss: 0.3401986
Test set: Average loss: 1.0659, Accuracy: 3085/5000 (62%)
[epoch 17] loss: 0.3240117
Test set: Average loss: 1.0661, Accuracy: 3084/5000 (62%)
[epoch 18] loss: 0.3070661
Test set: Average loss: 1.0666, Accuracy: 3081/5000 (62%)
[epoch 19] loss: 0.2907068
Test set: Average loss: 1.0630, Accuracy: 3080/5000 (62%)
[epoch 20] loss: 0.2768264
Test set: Average loss: 1.0608, Accuracy: 3075/5000 (62%)
[epoch 21] loss: 0.2641230
Test set: Average loss: 1.0626, Accuracy: 3052/5000 (61%)
[epoch 22] loss: 0.2507752
Test set: Average loss: 1.0598, Accuracy: 3054/5000 (61%)
[epoch 23] loss: 0.2390597
Test set: Average loss: 1.0630, Accuracy: 3051/5000 (61%)
[epoch 24] loss: 0.2272155
Test set: Average loss: 1.0603, Accuracy: 3049/5000 (61%)
[epoch 25] loss: 0.2175796
Test set: Average loss: 1.0616, Accuracy: 3051/5000 (61%)
Validation:
Test set: Average loss: 1.0659, Accuracy: 3085/5000 (62%)
Test
Test set: Average loss: 1.0857, Accuracy: 2990/5000 (60%)
Test set: Average loss: 0.3242, Accuracy: 746/750 (99%)
1000
## seed: 11
Validation accuracy before training:
Test set: Average loss: 1.8103, Accuracy: 452/5000 (9%)
[epoch 1] loss: 1.3580377
Test set: Average loss: 1.2361, Accuracy: 2587/5000 (52%)
[epoch 2] loss: 1.0304789
Test set: Average loss: 1.1771, Accuracy: 2785/5000 (56%)
[epoch 3] loss: 0.9026277
Test set: Average loss: 1.1569, Accuracy: 2854/5000 (57%)
[epoch 4] loss: 0.7977990
Test set: Average loss: 1.1403, Accuracy: 2878/5000 (58%)
[epoch 5] loss: 0.7347477
Test set: Average loss: 1.1219, Accuracy: 2936/5000 (59%)
[epoch 6] loss: 0.6675145
Test set: Average loss: 1.1125, Accuracy: 2939/5000 (59%)
[epoch 7] loss: 0.6219484
Test set: Average loss: 1.1133, Accuracy: 2940/5000 (59%)
[epoch 8] loss: 0.5766499
Test set: Average loss: 1.0952, Accuracy: 3003/5000 (60%)
[epoch 9] loss: 0.5358381
Test set: Average loss: 1.0865, Accuracy: 3027/5000 (61%)
[epoch 10] loss: 0.5062304
Test set: Average loss: 1.0799, Accuracy: 3058/5000 (61%)
[epoch 11] loss: 0.4678610
Test set: Average loss: 1.0766, Accuracy: 3054/5000 (61%)
[epoch 12] loss: 0.4422934
Test set: Average loss: 1.0645, Accuracy: 3080/5000 (62%)
[epoch 13] loss: 0.4152972
Test set: Average loss: 1.0633, Accuracy: 3081/5000 (62%)
[epoch 14] loss: 0.3900274
Test set: Average loss: 1.0608, Accuracy: 3095/5000 (62%)
[epoch 15] loss: 0.3698531
Test set: Average loss: 1.0550, Accuracy: 3096/5000 (62%)
[epoch 16] loss: 0.3447741
Test set: Average loss: 1.0530, Accuracy: 3095/5000 (62%)
[epoch 17] loss: 0.3268254
Test set: Average loss: 1.0498, Accuracy: 3097/5000 (62%)
[epoch 18] loss: 0.3106644
Test set: Average loss: 1.0478, Accuracy: 3113/5000 (62%)
[epoch 19] loss: 0.2914124
Test set: Average loss: 1.0463, Accuracy: 3113/5000 (62%)
[epoch 20] loss: 0.2764505
Test set: Average loss: 1.0496, Accuracy: 3106/5000 (62%)
[epoch 21] loss: 0.2651306
Test set: Average loss: 1.0371, Accuracy: 3129/5000 (63%)
[epoch 22] loss: 0.2516181
Test set: Average loss: 1.0420, Accuracy: 3115/5000 (62%)
[epoch 23] loss: 0.2379829
Test set: Average loss: 1.0373, Accuracy: 3124/5000 (62%)
[epoch 24] loss: 0.2246426
Test set: Average loss: 1.0373, Accuracy: 3136/5000 (63%)
[epoch 25] loss: 0.2147756
Test set: Average loss: 1.0350, Accuracy: 3140/5000 (63%)
Validation:
Test set: Average loss: 1.0350, Accuracy: 3140/5000 (63%)
Test
Test set: Average loss: 1.0355, Accuracy: 3039/5000 (61%)
Test set: Average loss: 0.2072, Accuracy: 997/1000 (100%)
## seed: 12
Validation accuracy before training:
Test set: Average loss: 1.9805, Accuracy: 591/5000 (12%)
[epoch 1] loss: 1.4724741
Test set: Average loss: 1.2539, Accuracy: 2577/5000 (52%)
[epoch 2] loss: 1.0891452
Test set: Average loss: 1.1771, Accuracy: 2838/5000 (57%)
[epoch 3] loss: 0.9286054
Test set: Average loss: 1.1354, Accuracy: 2929/5000 (59%)
[epoch 4] loss: 0.8021262
Test set: Average loss: 1.1202, Accuracy: 2974/5000 (59%)
[epoch 5] loss: 0.7132795
Test set: Average loss: 1.1048, Accuracy: 3008/5000 (60%)
[epoch 6] loss: 0.6507542
Test set: Average loss: 1.0888, Accuracy: 3042/5000 (61%)
[epoch 7] loss: 0.5877902
Test set: Average loss: 1.0804, Accuracy: 3065/5000 (61%)
[epoch 8] loss: 0.5376881
Test set: Average loss: 1.0762, Accuracy: 3051/5000 (61%)
[epoch 9] loss: 0.4966340
Test set: Average loss: 1.0689, Accuracy: 3082/5000 (62%)
[epoch 10] loss: 0.4551820
Test set: Average loss: 1.0647, Accuracy: 3074/5000 (61%)
[epoch 11] loss: 0.4236969
Test set: Average loss: 1.0638, Accuracy: 3078/5000 (62%)
[epoch 12] loss: 0.3949584
Test set: Average loss: 1.0540, Accuracy: 3093/5000 (62%)
[epoch 13] loss: 0.3686583
Test set: Average loss: 1.0536, Accuracy: 3120/5000 (62%)
[epoch 14] loss: 0.3433082
Test set: Average loss: 1.0467, Accuracy: 3109/5000 (62%)
[epoch 15] loss: 0.3208977
Test set: Average loss: 1.0456, Accuracy: 3106/5000 (62%)
[epoch 16] loss: 0.3047572
Test set: Average loss: 1.0475, Accuracy: 3105/5000 (62%)
[epoch 17] loss: 0.2879757
Test set: Average loss: 1.0435, Accuracy: 3099/5000 (62%)
[epoch 18] loss: 0.2717665
Test set: Average loss: 1.0451, Accuracy: 3096/5000 (62%)
[epoch 19] loss: 0.2555903
Test set: Average loss: 1.0429, Accuracy: 3113/5000 (62%)
[epoch 20] loss: 0.2414798
Test set: Average loss: 1.0442, Accuracy: 3099/5000 (62%)
[epoch 21] loss: 0.2273171
Test set: Average loss: 1.0431, Accuracy: 3095/5000 (62%)
[epoch 22] loss: 0.2155893
Test set: Average loss: 1.0400, Accuracy: 3107/5000 (62%)
[epoch 23] loss: 0.2034819
Test set: Average loss: 1.0385, Accuracy: 3117/5000 (62%)
[epoch 24] loss: 0.1905098
Test set: Average loss: 1.0459, Accuracy: 3110/5000 (62%)
[epoch 25] loss: 0.1788565
Test set: Average loss: 1.0448, Accuracy: 3101/5000 (62%)
Validation:
Test set: Average loss: 1.0536, Accuracy: 3120/5000 (62%)
Test
Test set: Average loss: 1.0696, Accuracy: 3048/5000 (61%)
Test set: Average loss: 0.3473, Accuracy: 977/1000 (98%)
## seed: 13
Validation accuracy before training:
Test set: Average loss: 1.7391, Accuracy: 829/5000 (17%)
[epoch 1] loss: 1.4019290
Test set: Average loss: 1.2510, Accuracy: 2595/5000 (52%)
[epoch 2] loss: 1.0527453
Test set: Average loss: 1.1922, Accuracy: 2755/5000 (55%)
[epoch 3] loss: 0.9108430
Test set: Average loss: 1.1552, Accuracy: 2854/5000 (57%)
[epoch 4] loss: 0.7944127
Test set: Average loss: 1.1359, Accuracy: 2912/5000 (58%)
[epoch 5] loss: 0.7162162
Test set: Average loss: 1.1221, Accuracy: 2928/5000 (59%)
[epoch 6] loss: 0.6516754
Test set: Average loss: 1.1100, Accuracy: 2965/5000 (59%)
[epoch 7] loss: 0.6004385
Test set: Average loss: 1.0983, Accuracy: 3007/5000 (60%)
[epoch 8] loss: 0.5531718
Test set: Average loss: 1.0985, Accuracy: 2974/5000 (59%)
[epoch 9] loss: 0.5073876
Test set: Average loss: 1.0909, Accuracy: 2984/5000 (60%)
[epoch 10] loss: 0.4685681
Test set: Average loss: 1.0881, Accuracy: 2982/5000 (60%)
[epoch 11] loss: 0.4381342
Test set: Average loss: 1.0832, Accuracy: 2993/5000 (60%)
[epoch 12] loss: 0.4071884
Test set: Average loss: 1.0776, Accuracy: 3022/5000 (60%)
[epoch 13] loss: 0.3806437
Test set: Average loss: 1.0821, Accuracy: 2999/5000 (60%)
[epoch 14] loss: 0.3549735
Test set: Average loss: 1.0834, Accuracy: 2977/5000 (60%)
[epoch 15] loss: 0.3328666
Test set: Average loss: 1.0759, Accuracy: 3003/5000 (60%)
[epoch 16] loss: 0.3077883
Test set: Average loss: 1.0751, Accuracy: 2998/5000 (60%)
[epoch 17] loss: 0.2891133
Test set: Average loss: 1.0783, Accuracy: 3010/5000 (60%)
[epoch 18] loss: 0.2724481
Test set: Average loss: 1.0756, Accuracy: 2975/5000 (60%)
[epoch 19] loss: 0.2538737
Test set: Average loss: 1.0750, Accuracy: 2985/5000 (60%)
[epoch 20] loss: 0.2424333
Test set: Average loss: 1.0695, Accuracy: 3019/5000 (60%)
[epoch 21] loss: 0.2256790
Test set: Average loss: 1.0789, Accuracy: 2981/5000 (60%)
[epoch 22] loss: 0.2130861
Test set: Average loss: 1.0762, Accuracy: 2996/5000 (60%)
[epoch 23] loss: 0.2009184
Test set: Average loss: 1.0762, Accuracy: 2979/5000 (60%)
[epoch 24] loss: 0.1892965
Test set: Average loss: 1.0750, Accuracy: 3022/5000 (60%)
[epoch 25] loss: 0.1780003
Test set: Average loss: 1.0802, Accuracy: 2987/5000 (60%)
Validation:
Test set: Average loss: 1.0750, Accuracy: 3022/5000 (60%)
Test
Test set: Average loss: 1.1120, Accuracy: 2945/5000 (59%)
Test set: Average loss: 0.1809, Accuracy: 997/1000 (100%)
2500
## seed: 11
Validation accuracy before training:
Test set: Average loss: 1.7523, Accuracy: 637/5000 (13%)
[epoch 1] loss: 1.2647371
Test set: Average loss: 1.1702, Accuracy: 2919/5000 (58%)
[epoch 2] loss: 0.9835482
Test set: Average loss: 1.1126, Accuracy: 3038/5000 (61%)
[epoch 3] loss: 0.8514039
Test set: Average loss: 1.0760, Accuracy: 3108/5000 (62%)
[epoch 4] loss: 0.7354135
Test set: Average loss: 1.0593, Accuracy: 3116/5000 (62%)
[epoch 5] loss: 0.6491570
Test set: Average loss: 1.0381, Accuracy: 3198/5000 (64%)
[epoch 6] loss: 0.5809781
Test set: Average loss: 1.0251, Accuracy: 3196/5000 (64%)
[epoch 7] loss: 0.5158563
Test set: Average loss: 1.0117, Accuracy: 3211/5000 (64%)
[epoch 8] loss: 0.4527860
Test set: Average loss: 1.0036, Accuracy: 3210/5000 (64%)
[epoch 9] loss: 0.4048279
Test set: Average loss: 0.9952, Accuracy: 3237/5000 (65%)
[epoch 10] loss: 0.3590954
Test set: Average loss: 0.9826, Accuracy: 3264/5000 (65%)
[epoch 11] loss: 0.3185674
Test set: Average loss: 0.9770, Accuracy: 3283/5000 (66%)
[epoch 12] loss: 0.2826259
Test set: Average loss: 0.9743, Accuracy: 3251/5000 (65%)
[epoch 13] loss: 0.2555760
Test set: Average loss: 0.9762, Accuracy: 3238/5000 (65%)
[epoch 14] loss: 0.2260623
Test set: Average loss: 0.9635, Accuracy: 3295/5000 (66%)
[epoch 15] loss: 0.2015114
Test set: Average loss: 0.9677, Accuracy: 3264/5000 (65%)
[epoch 16] loss: 0.1822140
Test set: Average loss: 0.9682, Accuracy: 3243/5000 (65%)
[epoch 17] loss: 0.1648495
Test set: Average loss: 0.9635, Accuracy: 3276/5000 (66%)
[epoch 18] loss: 0.1496563
Test set: Average loss: 0.9672, Accuracy: 3259/5000 (65%)
[epoch 19] loss: 0.1369618
Test set: Average loss: 0.9763, Accuracy: 3238/5000 (65%)
[epoch 20] loss: 0.1233297
Test set: Average loss: 0.9726, Accuracy: 3263/5000 (65%)
[epoch 21] loss: 0.1129497
Test set: Average loss: 0.9690, Accuracy: 3272/5000 (65%)
[epoch 22] loss: 0.1038753
Test set: Average loss: 0.9736, Accuracy: 3271/5000 (65%)
[epoch 23] loss: 0.0949060
Test set: Average loss: 0.9779, Accuracy: 3262/5000 (65%)
[epoch 24] loss: 0.0892363
Test set: Average loss: 0.9843, Accuracy: 3256/5000 (65%)
[epoch 25] loss: 0.0808607
Test set: Average loss: 0.9832, Accuracy: 3256/5000 (65%)
Validation:
Test set: Average loss: 0.9635, Accuracy: 3295/5000 (66%)
Test
Test set: Average loss: 0.9618, Accuracy: 3251/5000 (65%)
Test set: Average loss: 0.2040, Accuracy: 2485/2500 (99%)
## seed: 12
Validation accuracy before training:
Test set: Average loss: 1.7762, Accuracy: 864/5000 (17%)
[epoch 1] loss: 1.2179560
Test set: Average loss: 1.1205, Accuracy: 3000/5000 (60%)
[epoch 2] loss: 0.9306101
Test set: Average loss: 1.0656, Accuracy: 3113/5000 (62%)
[epoch 3] loss: 0.7982394
Test set: Average loss: 1.0333, Accuracy: 3179/5000 (64%)
[epoch 4] loss: 0.6977627
Test set: Average loss: 1.0178, Accuracy: 3188/5000 (64%)
[epoch 5] loss: 0.6186409
Test set: Average loss: 1.0015, Accuracy: 3221/5000 (64%)
[epoch 6] loss: 0.5484330
Test set: Average loss: 0.9853, Accuracy: 3233/5000 (65%)
[epoch 7] loss: 0.4899070
Test set: Average loss: 0.9820, Accuracy: 3233/5000 (65%)
[epoch 8] loss: 0.4417492
Test set: Average loss: 0.9799, Accuracy: 3234/5000 (65%)
[epoch 9] loss: 0.3969269
Test set: Average loss: 0.9613, Accuracy: 3253/5000 (65%)
[epoch 10] loss: 0.3501913
Test set: Average loss: 0.9622, Accuracy: 3236/5000 (65%)
[epoch 11] loss: 0.3132937
Test set: Average loss: 0.9594, Accuracy: 3230/5000 (65%)
[epoch 12] loss: 0.2809687
Test set: Average loss: 0.9487, Accuracy: 3256/5000 (65%)
[epoch 13] loss: 0.2526930
Test set: Average loss: 0.9529, Accuracy: 3257/5000 (65%)
[epoch 14] loss: 0.2262349
Test set: Average loss: 0.9459, Accuracy: 3243/5000 (65%)
[epoch 15] loss: 0.2013521
Test set: Average loss: 0.9531, Accuracy: 3240/5000 (65%)
[epoch 16] loss: 0.1804744
Test set: Average loss: 0.9452, Accuracy: 3270/5000 (65%)
[epoch 17] loss: 0.1620820
Test set: Average loss: 0.9484, Accuracy: 3262/5000 (65%)
[epoch 18] loss: 0.1461568
Test set: Average loss: 0.9472, Accuracy: 3258/5000 (65%)
[epoch 19] loss: 0.1327923
Test set: Average loss: 0.9478, Accuracy: 3276/5000 (66%)
[epoch 20] loss: 0.1205878
Test set: Average loss: 0.9573, Accuracy: 3263/5000 (65%)
[epoch 21] loss: 0.1106268
Test set: Average loss: 0.9529, Accuracy: 3277/5000 (66%)
[epoch 22] loss: 0.1010051
Test set: Average loss: 0.9593, Accuracy: 3265/5000 (65%)
[epoch 23] loss: 0.0918497
Test set: Average loss: 0.9600, Accuracy: 3267/5000 (65%)
[epoch 24] loss: 0.0840853
Test set: Average loss: 0.9681, Accuracy: 3250/5000 (65%)
[epoch 25] loss: 0.0778875
Test set: Average loss: 0.9701, Accuracy: 3252/5000 (65%)
Validation:
Test set: Average loss: 0.9529, Accuracy: 3277/5000 (66%)
Test
Test set: Average loss: 0.9788, Accuracy: 3224/5000 (64%)
Test set: Average loss: 0.1018, Accuracy: 2498/2500 (100%)
## seed: 13
Validation accuracy before training:
Test set: Average loss: 1.7487, Accuracy: 585/5000 (12%)
[epoch 1] loss: 1.1981460
Test set: Average loss: 1.1291, Accuracy: 2924/5000 (58%)
[epoch 2] loss: 0.9365107
Test set: Average loss: 1.0815, Accuracy: 3063/5000 (61%)
[epoch 3] loss: 0.8165728
Test set: Average loss: 1.0517, Accuracy: 3138/5000 (63%)
[epoch 4] loss: 0.7067913
Test set: Average loss: 1.0275, Accuracy: 3161/5000 (63%)
[epoch 5] loss: 0.6189056
Test set: Average loss: 1.0184, Accuracy: 3195/5000 (64%)
[epoch 6] loss: 0.5530830
Test set: Average loss: 1.0042, Accuracy: 3224/5000 (64%)
[epoch 7] loss: 0.4838931
Test set: Average loss: 0.9946, Accuracy: 3225/5000 (64%)
[epoch 8] loss: 0.4321288
Test set: Average loss: 0.9870, Accuracy: 3242/5000 (65%)
[epoch 9] loss: 0.3760406
Test set: Average loss: 0.9821, Accuracy: 3239/5000 (65%)
[epoch 10] loss: 0.3313647
Test set: Average loss: 0.9761, Accuracy: 3257/5000 (65%)
[epoch 11] loss: 0.2952535
Test set: Average loss: 0.9777, Accuracy: 3264/5000 (65%)
[epoch 12] loss: 0.2631215
Test set: Average loss: 0.9745, Accuracy: 3262/5000 (65%)
[epoch 13] loss: 0.2346683
Test set: Average loss: 0.9795, Accuracy: 3260/5000 (65%)
[epoch 14] loss: 0.2087984
Test set: Average loss: 0.9734, Accuracy: 3271/5000 (65%)
[epoch 15] loss: 0.1870989
Test set: Average loss: 0.9903, Accuracy: 3227/5000 (65%)
[epoch 16] loss: 0.1671500
Test set: Average loss: 0.9754, Accuracy: 3272/5000 (65%)
[epoch 17] loss: 0.1505178
Test set: Average loss: 0.9777, Accuracy: 3267/5000 (65%)
[epoch 18] loss: 0.1325286
Test set: Average loss: 0.9813, Accuracy: 3266/5000 (65%)
[epoch 19] loss: 0.1188121
Test set: Average loss: 0.9826, Accuracy: 3274/5000 (65%)
[epoch 20] loss: 0.1070840
Test set: Average loss: 0.9859, Accuracy: 3263/5000 (65%)
[epoch 21] loss: 0.0975142
Test set: Average loss: 0.9926, Accuracy: 3251/5000 (65%)
[epoch 22] loss: 0.0881975
Test set: Average loss: 0.9935, Accuracy: 3251/5000 (65%)
[epoch 23] loss: 0.0802981
Test set: Average loss: 0.9984, Accuracy: 3264/5000 (65%)
[epoch 24] loss: 0.0733348
Test set: Average loss: 0.9989, Accuracy: 3252/5000 (65%)
[epoch 25] loss: 0.0672174
Test set: Average loss: 1.0042, Accuracy: 3251/5000 (65%)
Validation:
Test set: Average loss: 0.9826, Accuracy: 3274/5000 (65%)
Test
Test set: Average loss: 1.0097, Accuracy: 3197/5000 (64%)
Test set: Average loss: 0.1086, Accuracy: 2495/2500 (100%)
5000
## seed: 11
Validation accuracy before training:
Test set: Average loss: 1.7882, Accuracy: 619/5000 (12%)
[epoch 1] loss: 1.1641926
Test set: Average loss: 1.0890, Accuracy: 2964/5000 (59%)
[epoch 2] loss: 0.9236720
Test set: Average loss: 1.0345, Accuracy: 3111/5000 (62%)
[epoch 3] loss: 0.7994021
Test set: Average loss: 0.9986, Accuracy: 3196/5000 (64%)
[epoch 4] loss: 0.6965246
Test set: Average loss: 0.9754, Accuracy: 3202/5000 (64%)
[epoch 5] loss: 0.6035364
Test set: Average loss: 0.9510, Accuracy: 3311/5000 (66%)
[epoch 6] loss: 0.5238479
Test set: Average loss: 0.9458, Accuracy: 3261/5000 (65%)
[epoch 7] loss: 0.4538583
Test set: Average loss: 0.9224, Accuracy: 3317/5000 (66%)
[epoch 8] loss: 0.3892262
Test set: Average loss: 0.9302, Accuracy: 3279/5000 (66%)
[epoch 9] loss: 0.3307330
Test set: Average loss: 0.9065, Accuracy: 3342/5000 (67%)
[epoch 10] loss: 0.2775632
Test set: Average loss: 0.9084, Accuracy: 3307/5000 (66%)
[epoch 11] loss: 0.2317152
Test set: Average loss: 0.9192, Accuracy: 3287/5000 (66%)
[epoch 12] loss: 0.1955709
Test set: Average loss: 0.9096, Accuracy: 3326/5000 (67%)
[epoch 13] loss: 0.1660059
Test set: Average loss: 0.9264, Accuracy: 3303/5000 (66%)
[epoch 14] loss: 0.1427778
Test set: Average loss: 0.9316, Accuracy: 3301/5000 (66%)
[epoch 15] loss: 0.1202271
Test set: Average loss: 0.9228, Accuracy: 3326/5000 (67%)
[epoch 16] loss: 0.1033194
Test set: Average loss: 0.9323, Accuracy: 3319/5000 (66%)
[epoch 17] loss: 0.0907026
Test set: Average loss: 0.9335, Accuracy: 3310/5000 (66%)
[epoch 18] loss: 0.0780764
Test set: Average loss: 0.9372, Accuracy: 3330/5000 (67%)
[epoch 19] loss: 0.0676076
Test set: Average loss: 0.9481, Accuracy: 3333/5000 (67%)
[epoch 20] loss: 0.0593854
Test set: Average loss: 0.9524, Accuracy: 3317/5000 (66%)
[epoch 21] loss: 0.0518836
Test set: Average loss: 0.9526, Accuracy: 3322/5000 (66%)
[epoch 22] loss: 0.0458227
Test set: Average loss: 0.9755, Accuracy: 3309/5000 (66%)
[epoch 23] loss: 0.0403417
Test set: Average loss: 0.9758, Accuracy: 3318/5000 (66%)
[epoch 24] loss: 0.0357974
Test set: Average loss: 0.9845, Accuracy: 3333/5000 (67%)
[epoch 25] loss: 0.0319175
Test set: Average loss: 0.9944, Accuracy: 3321/5000 (66%)
Validation:
Test set: Average loss: 0.9065, Accuracy: 3342/5000 (67%)
Test
Test set: Average loss: 0.9059, Accuracy: 3360/5000 (67%)
Test set: Average loss: 0.2799, Accuracy: 4908/5000 (98%)
## seed: 12
Validation accuracy before training:
Test set: Average loss: 1.6571, Accuracy: 1074/5000 (21%)
[epoch 1] loss: 1.1369292
Test set: Average loss: 1.0643, Accuracy: 3104/5000 (62%)
[epoch 2] loss: 0.9046625
Test set: Average loss: 1.0186, Accuracy: 3210/5000 (64%)
[epoch 3] loss: 0.7761589
Test set: Average loss: 0.9770, Accuracy: 3277/5000 (66%)
[epoch 4] loss: 0.6694122
Test set: Average loss: 0.9568, Accuracy: 3255/5000 (65%)
[epoch 5] loss: 0.5792498
Test set: Average loss: 0.9353, Accuracy: 3301/5000 (66%)
[epoch 6] loss: 0.4965955
Test set: Average loss: 0.9181, Accuracy: 3344/5000 (67%)
[epoch 7] loss: 0.4213013
Test set: Average loss: 0.9038, Accuracy: 3367/5000 (67%)
[epoch 8] loss: 0.3539273
Test set: Average loss: 0.8958, Accuracy: 3370/5000 (67%)
[epoch 9] loss: 0.3000186
Test set: Average loss: 0.8833, Accuracy: 3408/5000 (68%)
[epoch 10] loss: 0.2478030
Test set: Average loss: 0.8882, Accuracy: 3365/5000 (67%)
[epoch 11] loss: 0.2057636
Test set: Average loss: 0.8732, Accuracy: 3402/5000 (68%)
[epoch 12] loss: 0.1714526
Test set: Average loss: 0.8853, Accuracy: 3404/5000 (68%)
[epoch 13] loss: 0.1429298
Test set: Average loss: 0.8835, Accuracy: 3413/5000 (68%)
[epoch 14] loss: 0.1196982
Test set: Average loss: 0.8798, Accuracy: 3415/5000 (68%)
[epoch 15] loss: 0.1014867
Test set: Average loss: 0.8967, Accuracy: 3375/5000 (68%)
[epoch 16] loss: 0.0860221
Test set: Average loss: 0.8922, Accuracy: 3419/5000 (68%)
[epoch 17] loss: 0.0738884
Test set: Average loss: 0.8970, Accuracy: 3416/5000 (68%)
[epoch 18] loss: 0.0639538
Test set: Average loss: 0.9022, Accuracy: 3415/5000 (68%)
[epoch 19] loss: 0.0556790
Test set: Average loss: 0.9110, Accuracy: 3408/5000 (68%)
[epoch 20] loss: 0.0488965
Test set: Average loss: 0.9189, Accuracy: 3407/5000 (68%)
[epoch 21] loss: 0.0430556
Test set: Average loss: 0.9246, Accuracy: 3415/5000 (68%)
[epoch 22] loss: 0.0381563
Test set: Average loss: 0.9304, Accuracy: 3430/5000 (69%)
[epoch 23] loss: 0.0339059
Test set: Average loss: 0.9333, Accuracy: 3424/5000 (68%)
[epoch 24] loss: 0.0303181
Test set: Average loss: 0.9455, Accuracy: 3435/5000 (69%)
[epoch 25] loss: 0.0271264
Test set: Average loss: 0.9533, Accuracy: 3426/5000 (69%)
Validation:
Test set: Average loss: 0.9455, Accuracy: 3435/5000 (69%)
Test
Test set: Average loss: 0.9713, Accuracy: 3363/5000 (67%)
Test set: Average loss: 0.0280, Accuracy: 5000/5000 (100%)
## seed: 13
Validation accuracy before training:
Test set: Average loss: 1.6220, Accuracy: 1054/5000 (21%)
[epoch 1] loss: 1.0791493
Test set: Average loss: 1.0565, Accuracy: 3115/5000 (62%)
[epoch 2] loss: 0.8310519
Test set: Average loss: 1.0058, Accuracy: 3211/5000 (64%)
[epoch 3] loss: 0.6928353
Test set: Average loss: 0.9664, Accuracy: 3281/5000 (66%)
[epoch 4] loss: 0.5844131
Test set: Average loss: 0.9406, Accuracy: 3330/5000 (67%)
[epoch 5] loss: 0.4886504
Test set: Average loss: 0.9285, Accuracy: 3361/5000 (67%)
[epoch 6] loss: 0.4062390
Test set: Average loss: 0.9108, Accuracy: 3359/5000 (67%)
[epoch 7] loss: 0.3354412
Test set: Average loss: 0.9071, Accuracy: 3335/5000 (67%)
[epoch 8] loss: 0.2793456
Test set: Average loss: 0.8988, Accuracy: 3376/5000 (68%)
[epoch 9] loss: 0.2291831
Test set: Average loss: 0.8952, Accuracy: 3379/5000 (68%)
[epoch 10] loss: 0.1889918
Test set: Average loss: 0.8948, Accuracy: 3381/5000 (68%)
[epoch 11] loss: 0.1563231
Test set: Average loss: 0.8934, Accuracy: 3402/5000 (68%)
[epoch 12] loss: 0.1290333
Test set: Average loss: 0.8946, Accuracy: 3408/5000 (68%)
[epoch 13] loss: 0.1071584
Test set: Average loss: 0.9033, Accuracy: 3376/5000 (68%)
[epoch 14] loss: 0.0910571
Test set: Average loss: 0.9214, Accuracy: 3373/5000 (67%)
[epoch 15] loss: 0.0771624
Test set: Average loss: 0.9084, Accuracy: 3399/5000 (68%)
[epoch 16] loss: 0.0655557
Test set: Average loss: 0.9184, Accuracy: 3397/5000 (68%)
[epoch 17] loss: 0.0562410
Test set: Average loss: 0.9192, Accuracy: 3390/5000 (68%)
[epoch 18] loss: 0.0489314
Test set: Average loss: 0.9245, Accuracy: 3405/5000 (68%)
[epoch 19] loss: 0.0425997
Test set: Average loss: 0.9327, Accuracy: 3416/5000 (68%)
[epoch 20] loss: 0.0376049
Test set: Average loss: 0.9450, Accuracy: 3381/5000 (68%)
[epoch 21] loss: 0.0331554
Test set: Average loss: 0.9478, Accuracy: 3414/5000 (68%)
[epoch 22] loss: 0.0293784
Test set: Average loss: 0.9599, Accuracy: 3382/5000 (68%)
[epoch 23] loss: 0.0260488
Test set: Average loss: 0.9632, Accuracy: 3401/5000 (68%)
[epoch 24] loss: 0.0233055
Test set: Average loss: 0.9675, Accuracy: 3382/5000 (68%)
[epoch 25] loss: 0.0208946
Test set: Average loss: 0.9769, Accuracy: 3393/5000 (68%)
Validation:
Test set: Average loss: 0.9327, Accuracy: 3416/5000 (68%)
Test
Test set: Average loss: 0.9433, Accuracy: 3394/5000 (68%)
Test set: Average loss: 0.0389, Accuracy: 5000/5000 (100%)
10000
## seed: 11
Validation accuracy before training:
Test set: Average loss: 1.9029, Accuracy: 489/5000 (10%)
[epoch 1] loss: 1.1698861
Test set: Average loss: 1.0775, Accuracy: 3011/5000 (60%)
[epoch 2] loss: 0.9302870
Test set: Average loss: 0.9968, Accuracy: 3231/5000 (65%)
[epoch 3] loss: 0.7845479
Test set: Average loss: 0.9439, Accuracy: 3281/5000 (66%)
[epoch 4] loss: 0.6582430
Test set: Average loss: 0.9076, Accuracy: 3348/5000 (67%)
[epoch 5] loss: 0.5484348
Test set: Average loss: 0.9021, Accuracy: 3355/5000 (67%)
[epoch 6] loss: 0.4461379
Test set: Average loss: 0.8825, Accuracy: 3415/5000 (68%)
[epoch 7] loss: 0.3583009
Test set: Average loss: 0.8747, Accuracy: 3387/5000 (68%)
[epoch 8] loss: 0.2790359
Test set: Average loss: 0.8708, Accuracy: 3453/5000 (69%)
[epoch 9] loss: 0.2141262
Test set: Average loss: 0.8757, Accuracy: 3395/5000 (68%)
[epoch 10] loss: 0.1638982
Test set: Average loss: 0.8708, Accuracy: 3442/5000 (69%)
[epoch 11] loss: 0.1255622
Test set: Average loss: 0.8797, Accuracy: 3422/5000 (68%)
[epoch 12] loss: 0.1056574
Test set: Average loss: 0.9066, Accuracy: 3415/5000 (68%)
[epoch 13] loss: 0.0745470
Test set: Average loss: 0.9008, Accuracy: 3437/5000 (69%)
[epoch 14] loss: 0.0560904
Test set: Average loss: 0.9354, Accuracy: 3393/5000 (68%)
[epoch 15] loss: 0.0491079
Test set: Average loss: 0.9424, Accuracy: 3411/5000 (68%)
[epoch 16] loss: 0.0475612
Test set: Average loss: 0.9450, Accuracy: 3444/5000 (69%)
[epoch 17] loss: 0.0276492
Test set: Average loss: 0.9563, Accuracy: 3454/5000 (69%)
[epoch 18] loss: 0.0211421
Test set: Average loss: 0.9632, Accuracy: 3472/5000 (69%)
[epoch 19] loss: 0.0175923
Test set: Average loss: 0.9754, Accuracy: 3482/5000 (70%)
[epoch 20] loss: 0.0155594
Test set: Average loss: 0.9992, Accuracy: 3463/5000 (69%)
[epoch 21] loss: 0.0124956
Test set: Average loss: 1.0132, Accuracy: 3485/5000 (70%)
[epoch 22] loss: 0.0099855
Test set: Average loss: 1.0308, Accuracy: 3468/5000 (69%)
[epoch 23] loss: 0.0083648
Test set: Average loss: 1.0340, Accuracy: 3492/5000 (70%)
[epoch 24] loss: 0.0070211
Test set: Average loss: 1.0528, Accuracy: 3501/5000 (70%)
[epoch 25] loss: 0.0059586
Test set: Average loss: 1.0642, Accuracy: 3482/5000 (70%)
Validation:
Test set: Average loss: 1.0528, Accuracy: 3501/5000 (70%)
Test
Test set: Average loss: 1.0727, Accuracy: 3447/5000 (69%)
Test set: Average loss: 0.0063, Accuracy: 10000/10000 (100%)
## seed: 12
Validation accuracy before training:
Test set: Average loss: 1.6278, Accuracy: 1439/5000 (29%)
[epoch 1] loss: 1.0518640
Test set: Average loss: 0.9850, Accuracy: 3320/5000 (66%)
[epoch 2] loss: 0.8205051
Test set: Average loss: 0.9370, Accuracy: 3378/5000 (68%)
[epoch 3] loss: 0.6800582
Test set: Average loss: 0.9028, Accuracy: 3393/5000 (68%)
[epoch 4] loss: 0.5580432
Test set: Average loss: 0.8693, Accuracy: 3425/5000 (68%)
[epoch 5] loss: 0.4510949
Test set: Average loss: 0.8717, Accuracy: 3445/5000 (69%)
[epoch 6] loss: 0.3603445
Test set: Average loss: 0.8692, Accuracy: 3392/5000 (68%)
[epoch 7] loss: 0.2815711
Test set: Average loss: 0.8604, Accuracy: 3441/5000 (69%)
[epoch 8] loss: 0.2147216
Test set: Average loss: 0.8481, Accuracy: 3483/5000 (70%)
[epoch 9] loss: 0.1655945
Test set: Average loss: 0.8807, Accuracy: 3458/5000 (69%)
[epoch 10] loss: 0.1237269
Test set: Average loss: 0.8613, Accuracy: 3488/5000 (70%)
[epoch 11] loss: 0.0963555
Test set: Average loss: 0.8741, Accuracy: 3500/5000 (70%)
[epoch 12] loss: 0.0709104
Test set: Average loss: 0.8786, Accuracy: 3488/5000 (70%)
[epoch 13] loss: 0.0520800
Test set: Average loss: 0.8970, Accuracy: 3467/5000 (69%)
[epoch 14] loss: 0.0398985
Test set: Average loss: 0.9166, Accuracy: 3469/5000 (69%)
[epoch 15] loss: 0.0320250
Test set: Average loss: 0.9137, Accuracy: 3493/5000 (70%)
[epoch 16] loss: 0.0253651
Test set: Average loss: 0.9202, Accuracy: 3510/5000 (70%)
[epoch 17] loss: 0.0206291
Test set: Average loss: 0.9329, Accuracy: 3522/5000 (70%)
[epoch 18] loss: 0.0168210
Test set: Average loss: 0.9561, Accuracy: 3503/5000 (70%)
[epoch 19] loss: 0.0138870
Test set: Average loss: 0.9653, Accuracy: 3505/5000 (70%)
[epoch 20] loss: 0.0114745
Test set: Average loss: 0.9755, Accuracy: 3506/5000 (70%)
[epoch 21] loss: 0.0095514
Test set: Average loss: 0.9965, Accuracy: 3494/5000 (70%)
[epoch 22] loss: 0.0079680
Test set: Average loss: 1.0052, Accuracy: 3496/5000 (70%)
[epoch 23] loss: 0.0066698
Test set: Average loss: 1.0275, Accuracy: 3500/5000 (70%)
[epoch 24] loss: 0.0056195
Test set: Average loss: 1.0379, Accuracy: 3499/5000 (70%)
[epoch 25] loss: 0.0047452
Test set: Average loss: 1.0534, Accuracy: 3508/5000 (70%)
Validation:
Test set: Average loss: 0.9329, Accuracy: 3522/5000 (70%)
Test
Test set: Average loss: 0.9522, Accuracy: 3446/5000 (69%)
Test set: Average loss: 0.0176, Accuracy: 9998/10000 (100%)
## seed: 13
Validation accuracy before training:
Test set: Average loss: 1.7359, Accuracy: 645/5000 (13%)
[epoch 1] loss: 1.0656905
Test set: Average loss: 1.0255, Accuracy: 3189/5000 (64%)
[epoch 2] loss: 0.8185101
Test set: Average loss: 0.9589, Accuracy: 3310/5000 (66%)
[epoch 3] loss: 0.6701378
Test set: Average loss: 0.9184, Accuracy: 3374/5000 (67%)
[epoch 4] loss: 0.5394202
Test set: Average loss: 0.8870, Accuracy: 3409/5000 (68%)
[epoch 5] loss: 0.4310035
Test set: Average loss: 0.8612, Accuracy: 3445/5000 (69%)
[epoch 6] loss: 0.3362168
Test set: Average loss: 0.8515, Accuracy: 3436/5000 (69%)
[epoch 7] loss: 0.2660392
Test set: Average loss: 0.8515, Accuracy: 3440/5000 (69%)
[epoch 8] loss: 0.2017781
Test set: Average loss: 0.8523, Accuracy: 3455/5000 (69%)
[epoch 9] loss: 0.1540824
Test set: Average loss: 0.8577, Accuracy: 3460/5000 (69%)
[epoch 10] loss: 0.1185211
Test set: Average loss: 0.8734, Accuracy: 3452/5000 (69%)
[epoch 11] loss: 0.0895491
Test set: Average loss: 0.8861, Accuracy: 3438/5000 (69%)
[epoch 12] loss: 0.0686227
Test set: Average loss: 0.8885, Accuracy: 3444/5000 (69%)
[epoch 13] loss: 0.0509734
Test set: Average loss: 0.8948, Accuracy: 3454/5000 (69%)
[epoch 14] loss: 0.0420021
Test set: Average loss: 0.9263, Accuracy: 3458/5000 (69%)
[epoch 15] loss: 0.0726841
Epoch 14: reducing learning rate of group 0 to 5.0000e-06.
Test set: Average loss: 0.9751, Accuracy: 3377/5000 (68%)
[epoch 16] loss: 0.0412458
Test set: Average loss: 0.9230, Accuracy: 3465/5000 (69%)
[epoch 17] loss: 0.0331605
Test set: Average loss: 0.9229, Accuracy: 3474/5000 (69%)
[epoch 18] loss: 0.0305236
Test set: Average loss: 0.9234, Accuracy: 3480/5000 (70%)
[epoch 19] loss: 0.0286479
Test set: Average loss: 0.9240, Accuracy: 3480/5000 (70%)
[epoch 20] loss: 0.0270620
Test set: Average loss: 0.9254, Accuracy: 3481/5000 (70%)
[epoch 21] loss: 0.0256574
Test set: Average loss: 0.9253, Accuracy: 3484/5000 (70%)
[epoch 22] loss: 0.0243526
Test set: Average loss: 0.9299, Accuracy: 3482/5000 (70%)
[epoch 23] loss: 0.0231459
Test set: Average loss: 0.9301, Accuracy: 3486/5000 (70%)
[epoch 24] loss: 0.0219894
Test set: Average loss: 0.9338, Accuracy: 3496/5000 (70%)
[epoch 25] loss: 0.0209139
Test set: Average loss: 0.9368, Accuracy: 3494/5000 (70%)
Validation:
Test set: Average loss: 0.9338, Accuracy: 3496/5000 (70%)
Test
Test set: Average loss: 0.9637, Accuracy: 3437/5000 (69%)
Test set: Average loss: 0.0211, Accuracy: 10000/10000 (100%)
15000
## seed: 11
Validation accuracy before training:
Test set: Average loss: 1.9231, Accuracy: 379/5000 (8%)
[epoch 1] loss: 1.1130889
Test set: Average loss: 1.0383, Accuracy: 3206/5000 (64%)
[epoch 2] loss: 0.8714108
Test set: Average loss: 0.9796, Accuracy: 3271/5000 (65%)
[epoch 3] loss: 0.7147952
Test set: Average loss: 0.9137, Accuracy: 3364/5000 (67%)
[epoch 4] loss: 0.5813737
Test set: Average loss: 0.8657, Accuracy: 3456/5000 (69%)
[epoch 5] loss: 0.4605393
Test set: Average loss: 0.8745, Accuracy: 3408/5000 (68%)
[epoch 6] loss: 0.3508031
Test set: Average loss: 0.8558, Accuracy: 3423/5000 (68%)
[epoch 7] loss: 0.2611579
Test set: Average loss: 0.8406, Accuracy: 3489/5000 (70%)
[epoch 8] loss: 0.1932372
Test set: Average loss: 0.8804, Accuracy: 3457/5000 (69%)
[epoch 9] loss: 0.1344120
Test set: Average loss: 0.8837, Accuracy: 3466/5000 (69%)
[epoch 10] loss: 0.0990945
Test set: Average loss: 0.8773, Accuracy: 3507/5000 (70%)
[epoch 11] loss: 0.0673687
Test set: Average loss: 0.9044, Accuracy: 3459/5000 (69%)
[epoch 12] loss: 0.0509925
Test set: Average loss: 0.9245, Accuracy: 3474/5000 (69%)
[epoch 13] loss: 0.0564991
Epoch 12: reducing learning rate of group 0 to 5.0000e-06.
Test set: Average loss: 0.9817, Accuracy: 3395/5000 (68%)
[epoch 14] loss: 0.0321154
Test set: Average loss: 0.9289, Accuracy: 3518/5000 (70%)
[epoch 15] loss: 0.0248875
Test set: Average loss: 0.9279, Accuracy: 3523/5000 (70%)
[epoch 16] loss: 0.0224934
Test set: Average loss: 0.9303, Accuracy: 3531/5000 (71%)
[epoch 17] loss: 0.0207655
Test set: Average loss: 0.9322, Accuracy: 3527/5000 (71%)
[epoch 18] loss: 0.0192838
Test set: Average loss: 0.9348, Accuracy: 3533/5000 (71%)
[epoch 19] loss: 0.0178960
Test set: Average loss: 0.9413, Accuracy: 3513/5000 (70%)
[epoch 20] loss: 0.0166333
Test set: Average loss: 0.9412, Accuracy: 3536/5000 (71%)
[epoch 21] loss: 0.0154664
Test set: Average loss: 0.9475, Accuracy: 3533/5000 (71%)
[epoch 22] loss: 0.0143056
Test set: Average loss: 0.9496, Accuracy: 3536/5000 (71%)
[epoch 23] loss: 0.0132148
Test set: Average loss: 0.9604, Accuracy: 3519/5000 (70%)
[epoch 24] loss: 0.0122046
Test set: Average loss: 0.9597, Accuracy: 3530/5000 (71%)
[epoch 25] loss: 0.0112514
Test set: Average loss: 0.9659, Accuracy: 3531/5000 (71%)
Validation:
Test set: Average loss: 0.9496, Accuracy: 3536/5000 (71%)
Test
Test set: Average loss: 0.9776, Accuracy: 3477/5000 (70%)
Test set: Average loss: 0.0133, Accuracy: 14999/15000 (100%)
## seed: 12
Validation accuracy before training:
Test set: Average loss: 1.6083, Accuracy: 1317/5000 (26%)
[epoch 1] loss: 1.0162018
Test set: Average loss: 0.9794, Accuracy: 3306/5000 (66%)
[epoch 2] loss: 0.8026856
Test set: Average loss: 0.9109, Accuracy: 3405/5000 (68%)
[epoch 3] loss: 0.6569744
Test set: Average loss: 0.8772, Accuracy: 3422/5000 (68%)
[epoch 4] loss: 0.5238685
Test set: Average loss: 0.8355, Accuracy: 3487/5000 (70%)
[epoch 5] loss: 0.4049746
Test set: Average loss: 0.8368, Accuracy: 3479/5000 (70%)
[epoch 6] loss: 0.3073819
Test set: Average loss: 0.8304, Accuracy: 3528/5000 (71%)
[epoch 7] loss: 0.2284618
Test set: Average loss: 0.8438, Accuracy: 3476/5000 (70%)
[epoch 8] loss: 0.1692868
Test set: Average loss: 0.8572, Accuracy: 3476/5000 (70%)
[epoch 9] loss: 0.1242426
Test set: Average loss: 0.8856, Accuracy: 3462/5000 (69%)
[epoch 10] loss: 0.0909998
Test set: Average loss: 0.9224, Accuracy: 3407/5000 (68%)
[epoch 11] loss: 0.0687183
Test set: Average loss: 0.9535, Accuracy: 3407/5000 (68%)
[epoch 12] loss: 0.0694216
Epoch 11: reducing learning rate of group 0 to 5.0000e-06.
Test set: Average loss: 0.9880, Accuracy: 3397/5000 (68%)
[epoch 13] loss: 0.0405917
Test set: Average loss: 0.8987, Accuracy: 3514/5000 (70%)
[epoch 14] loss: 0.0326027
Test set: Average loss: 0.8978, Accuracy: 3519/5000 (70%)
[epoch 15] loss: 0.0298287
Test set: Average loss: 0.8992, Accuracy: 3526/5000 (71%)
[epoch 16] loss: 0.0277026
Test set: Average loss: 0.9001, Accuracy: 3515/5000 (70%)
[epoch 17] loss: 0.0257902
Test set: Average loss: 0.9045, Accuracy: 3518/5000 (70%)
[epoch 18] loss: 0.0240534
Test set: Average loss: 0.9070, Accuracy: 3530/5000 (71%)
[epoch 19] loss: 0.0224772
Test set: Average loss: 0.9106, Accuracy: 3531/5000 (71%)
[epoch 20] loss: 0.0209394
Test set: Average loss: 0.9172, Accuracy: 3525/5000 (70%)
[epoch 21] loss: 0.0194459
Test set: Average loss: 0.9230, Accuracy: 3520/5000 (70%)
[epoch 22] loss: 0.0180817
Test set: Average loss: 0.9215, Accuracy: 3534/5000 (71%)
[epoch 23] loss: 0.0168568
Test set: Average loss: 0.9280, Accuracy: 3532/5000 (71%)
[epoch 24] loss: 0.0156258
Test set: Average loss: 0.9302, Accuracy: 3549/5000 (71%)
[epoch 25] loss: 0.0144535
Test set: Average loss: 0.9398, Accuracy: 3537/5000 (71%)
Validation:
Test set: Average loss: 0.9302, Accuracy: 3549/5000 (71%)
Test
Test set: Average loss: 0.9625, Accuracy: 3494/5000 (70%)
Test set: Average loss: 0.0146, Accuracy: 14999/15000 (100%)
## seed: 13
Validation accuracy before training:
Test set: Average loss: 1.7754, Accuracy: 665/5000 (13%)
[epoch 1] loss: 1.0776593
Test set: Average loss: 1.0128, Accuracy: 3182/5000 (64%)
[epoch 2] loss: 0.8450723
Test set: Average loss: 0.9378, Accuracy: 3370/5000 (67%)
[epoch 3] loss: 0.6920445
Test set: Average loss: 0.8997, Accuracy: 3397/5000 (68%)
[epoch 4] loss: 0.5575391
Test set: Average loss: 0.8629, Accuracy: 3474/5000 (69%)
[epoch 5] loss: 0.4348701
Test set: Average loss: 0.8459, Accuracy: 3481/5000 (70%)
[epoch 6] loss: 0.3274938
Test set: Average loss: 0.8542, Accuracy: 3478/5000 (70%)
[epoch 7] loss: 0.2469291
Test set: Average loss: 0.8397, Accuracy: 3495/5000 (70%)
[epoch 8] loss: 0.1771152
Test set: Average loss: 0.8465, Accuracy: 3514/5000 (70%)
[epoch 9] loss: 0.1308049
Test set: Average loss: 0.8671, Accuracy: 3501/5000 (70%)
[epoch 10] loss: 0.0932737
Test set: Average loss: 0.8787, Accuracy: 3477/5000 (70%)
[epoch 11] loss: 0.0752470
Test set: Average loss: 0.9001, Accuracy: 3491/5000 (70%)
[epoch 12] loss: 0.0566516
Test set: Average loss: 0.9296, Accuracy: 3464/5000 (69%)
[epoch 13] loss: 0.0531384
Test set: Average loss: 0.9701, Accuracy: 3457/5000 (69%)
[epoch 14] loss: 0.0437327
Test set: Average loss: 0.9885, Accuracy: 3448/5000 (69%)
[epoch 15] loss: 0.0415632
Test set: Average loss: 0.9979, Accuracy: 3460/5000 (69%)
[epoch 16] loss: 0.0337175
Test set: Average loss: 1.0281, Accuracy: 3456/5000 (69%)
[epoch 17] loss: 0.0303391
Test set: Average loss: 1.0870, Accuracy: 3384/5000 (68%)
[epoch 18] loss: 0.0190289
Test set: Average loss: 1.0228, Accuracy: 3482/5000 (70%)
[epoch 19] loss: 0.0130097
Test set: Average loss: 1.1049, Accuracy: 3433/5000 (69%)
[epoch 20] loss: 0.0535276
Epoch 19: reducing learning rate of group 0 to 5.0000e-06.
Test set: Average loss: 1.1271, Accuracy: 3404/5000 (68%)
[epoch 21] loss: 0.0141056
Epoch 20: reducing learning rate of group 0 to 5.0000e-07.
Test set: Average loss: 1.0808, Accuracy: 3492/5000 (70%)
[epoch 22] loss: 0.0096467
Test set: Average loss: 1.0818, Accuracy: 3490/5000 (70%)
[epoch 23] loss: 0.0094029
Test set: Average loss: 1.0825, Accuracy: 3491/5000 (70%)
[epoch 24] loss: 0.0091756
Test set: Average loss: 1.0827, Accuracy: 3488/5000 (70%)
[epoch 25] loss: 0.0089323
Test set: Average loss: 1.0824, Accuracy: 3486/5000 (70%)
Validation:
Test set: Average loss: 0.8465, Accuracy: 3514/5000 (70%)
Test
Test set: Average loss: 0.8629, Accuracy: 3438/5000 (69%)
Test set: Average loss: 0.1285, Accuracy: 14849/15000 (99%)
20000
## seed: 11
Validation accuracy before training:
Test set: Average loss: 1.7773, Accuracy: 613/5000 (12%)
[epoch 1] loss: 1.1049775
Test set: Average loss: 1.0055, Accuracy: 3222/5000 (64%)
[epoch 2] loss: 0.8412517
Test set: Average loss: 0.9135, Accuracy: 3417/5000 (68%)
[epoch 3] loss: 0.6793115
Test set: Average loss: 0.8579, Accuracy: 3487/5000 (70%)
[epoch 4] loss: 0.5370532
Test set: Average loss: 0.8221, Accuracy: 3509/5000 (70%)
[epoch 5] loss: 0.4129746
Test set: Average loss: 0.8219, Accuracy: 3519/5000 (70%)
[epoch 6] loss: 0.3042497
Test set: Average loss: 0.8202, Accuracy: 3559/5000 (71%)
[epoch 7] loss: 0.2237798
Test set: Average loss: 0.8323, Accuracy: 3535/5000 (71%)
[epoch 8] loss: 0.1555815
Test set: Average loss: 0.8591, Accuracy: 3495/5000 (70%)
[epoch 9] loss: 0.1141429
Test set: Average loss: 0.8784, Accuracy: 3513/5000 (70%)
[epoch 10] loss: 0.0844407
Test set: Average loss: 0.9026, Accuracy: 3504/5000 (70%)
[epoch 11] loss: 0.0629800
Test set: Average loss: 0.9332, Accuracy: 3483/5000 (70%)
[epoch 12] loss: 0.0624609
Test set: Average loss: 0.9453, Accuracy: 3480/5000 (70%)
[epoch 13] loss: 0.0443466
Test set: Average loss: 1.0026, Accuracy: 3475/5000 (70%)
[epoch 14] loss: 0.0390349
Test set: Average loss: 1.0353, Accuracy: 3434/5000 (69%)
[epoch 15] loss: 0.0313959
Test set: Average loss: 1.0639, Accuracy: 3435/5000 (69%)
[epoch 16] loss: 0.0380589
Epoch 15: reducing learning rate of group 0 to 5.0000e-06.
Test set: Average loss: 1.0521, Accuracy: 3489/5000 (70%)
[epoch 17] loss: 0.0126109
Test set: Average loss: 1.0154, Accuracy: 3528/5000 (71%)
[epoch 18] loss: 0.0090904
Test set: Average loss: 1.0121, Accuracy: 3527/5000 (71%)
[epoch 19] loss: 0.0079684
Test set: Average loss: 1.0135, Accuracy: 3543/5000 (71%)
[epoch 20] loss: 0.0071275
Test set: Average loss: 1.0173, Accuracy: 3538/5000 (71%)
[epoch 21] loss: 0.0063672
Test set: Average loss: 1.0214, Accuracy: 3538/5000 (71%)
[epoch 22] loss: 0.0056616
Test set: Average loss: 1.0256, Accuracy: 3544/5000 (71%)
[epoch 23] loss: 0.0050688
Test set: Average loss: 1.0270, Accuracy: 3544/5000 (71%)
[epoch 24] loss: 0.0045142
Test set: Average loss: 1.0352, Accuracy: 3558/5000 (71%)
[epoch 25] loss: 0.0040305
Test set: Average loss: 1.0379, Accuracy: 3543/5000 (71%)
Validation:
Test set: Average loss: 0.8202, Accuracy: 3559/5000 (71%)
Test
Test set: Average loss: 0.8329, Accuracy: 3516/5000 (70%)
Test set: Average loss: 0.2260, Accuracy: 19197/20000 (96%)
## seed: 12
Validation accuracy before training:
Test set: Average loss: 1.6924, Accuracy: 907/5000 (18%)
[epoch 1] loss: 0.9658045
Test set: Average loss: 0.9451, Accuracy: 3326/5000 (67%)
[epoch 2] loss: 0.7300561
Test set: Average loss: 0.8843, Accuracy: 3446/5000 (69%)
[epoch 3] loss: 0.5726703
Test set: Average loss: 0.8477, Accuracy: 3463/5000 (69%)
[epoch 4] loss: 0.4399128
Test set: Average loss: 0.8265, Accuracy: 3489/5000 (70%)
[epoch 5] loss: 0.3321486
Test set: Average loss: 0.8427, Accuracy: 3502/5000 (70%)
[epoch 6] loss: 0.2442491
Test set: Average loss: 0.8401, Accuracy: 3529/5000 (71%)
[epoch 7] loss: 0.1741380
Test set: Average loss: 0.8522, Accuracy: 3487/5000 (70%)
[epoch 8] loss: 0.1275459
Test set: Average loss: 0.8921, Accuracy: 3442/5000 (69%)
[epoch 9] loss: 0.0930638
Test set: Average loss: 0.9408, Accuracy: 3424/5000 (68%)
[epoch 10] loss: 0.0702031
Test set: Average loss: 0.9930, Accuracy: 3413/5000 (68%)
[epoch 11] loss: 0.0628607
Test set: Average loss: 0.9516, Accuracy: 3498/5000 (70%)
[epoch 12] loss: 0.0518019
Test set: Average loss: 1.0043, Accuracy: 3409/5000 (68%)
[epoch 13] loss: 0.0466891
Test set: Average loss: 1.1002, Accuracy: 3340/5000 (67%)
[epoch 14] loss: 0.0284902
Test set: Average loss: 1.0530, Accuracy: 3465/5000 (69%)
[epoch 15] loss: 0.0295116
Epoch 14: reducing learning rate of group 0 to 5.0000e-06.
Test set: Average loss: 1.1568, Accuracy: 3369/5000 (67%)
[epoch 16] loss: 0.0142495
Test set: Average loss: 1.0270, Accuracy: 3500/5000 (70%)
[epoch 17] loss: 0.0085679
Test set: Average loss: 1.0240, Accuracy: 3500/5000 (70%)
[epoch 18] loss: 0.0075674
Test set: Average loss: 1.0245, Accuracy: 3509/5000 (70%)
[epoch 19] loss: 0.0068724
Test set: Average loss: 1.0262, Accuracy: 3517/5000 (70%)
[epoch 20] loss: 0.0062679
Test set: Average loss: 1.0281, Accuracy: 3524/5000 (70%)
[epoch 21] loss: 0.0057224
Test set: Average loss: 1.0330, Accuracy: 3528/5000 (71%)
[epoch 22] loss: 0.0052039
Test set: Average loss: 1.0368, Accuracy: 3525/5000 (70%)
[epoch 23] loss: 0.0047204
Test set: Average loss: 1.0460, Accuracy: 3517/5000 (70%)
[epoch 24] loss: 0.0042693
Test set: Average loss: 1.0537, Accuracy: 3529/5000 (71%)
[epoch 25] loss: 0.0038619
Test set: Average loss: 1.0608, Accuracy: 3523/5000 (70%)
Validation:
Test set: Average loss: 1.0537, Accuracy: 3529/5000 (71%)
Test
Test set: Average loss: 1.0810, Accuracy: 3510/5000 (70%)
Test set: Average loss: 0.0039, Accuracy: 20000/20000 (100%)
## seed: 13
Validation accuracy before training:
Test set: Average loss: 1.7716, Accuracy: 977/5000 (20%)
[epoch 1] loss: 1.0026896
Test set: Average loss: 0.9498, Accuracy: 3302/5000 (66%)
[epoch 2] loss: 0.7567555
Test set: Average loss: 0.8845, Accuracy: 3394/5000 (68%)
[epoch 3] loss: 0.6045921
Test set: Average loss: 0.8402, Accuracy: 3464/5000 (69%)
[epoch 4] loss: 0.4727421
Test set: Average loss: 0.8438, Accuracy: 3476/5000 (70%)
[epoch 5] loss: 0.3615597
Test set: Average loss: 0.8330, Accuracy: 3463/5000 (69%)
[epoch 6] loss: 0.2694399
Test set: Average loss: 0.8367, Accuracy: 3503/5000 (70%)
[epoch 7] loss: 0.2009223
Test set: Average loss: 0.8687, Accuracy: 3472/5000 (69%)
[epoch 8] loss: 0.1436075
Test set: Average loss: 0.8502, Accuracy: 3527/5000 (71%)
[epoch 9] loss: 0.1076314
Test set: Average loss: 0.9090, Accuracy: 3470/5000 (69%)
[epoch 10] loss: 0.0767821
Test set: Average loss: 0.9650, Accuracy: 3432/5000 (69%)
[epoch 11] loss: 0.0701712
Test set: Average loss: 0.9711, Accuracy: 3468/5000 (69%)
[epoch 12] loss: 0.0543886
Test set: Average loss: 0.9916, Accuracy: 3474/5000 (69%)
[epoch 13] loss: 0.0441273
Test set: Average loss: 1.0883, Accuracy: 3367/5000 (67%)
[epoch 14] loss: 0.0496764
Epoch 13: reducing learning rate of group 0 to 5.0000e-06.
Test set: Average loss: 1.0405, Accuracy: 3473/5000 (69%)
[epoch 15] loss: 0.0175795
Test set: Average loss: 1.0036, Accuracy: 3506/5000 (70%)
[epoch 16] loss: 0.0136974
Test set: Average loss: 0.9976, Accuracy: 3516/5000 (70%)
[epoch 17] loss: 0.0122658
Test set: Average loss: 1.0000, Accuracy: 3527/5000 (71%)
[epoch 18] loss: 0.0111369
Test set: Average loss: 1.0040, Accuracy: 3506/5000 (70%)
[epoch 19] loss: 0.0101207
Test set: Average loss: 1.0053, Accuracy: 3538/5000 (71%)
[epoch 20] loss: 0.0091929
Test set: Average loss: 1.0105, Accuracy: 3526/5000 (71%)
[epoch 21] loss: 0.0083230
Test set: Average loss: 1.0098, Accuracy: 3546/5000 (71%)
[epoch 22] loss: 0.0075507
Test set: Average loss: 1.0189, Accuracy: 3548/5000 (71%)
[epoch 23] loss: 0.0068027
Test set: Average loss: 1.0233, Accuracy: 3541/5000 (71%)
[epoch 24] loss: 0.0061282
Test set: Average loss: 1.0312, Accuracy: 3547/5000 (71%)
[epoch 25] loss: 0.0055468
Test set: Average loss: 1.0355, Accuracy: 3554/5000 (71%)
Validation:
Test set: Average loss: 1.0355, Accuracy: 3554/5000 (71%)
Test
Test set: Average loss: 1.0662, Accuracy: 3532/5000 (71%)
Test set: Average loss: 0.0051, Accuracy: 19999/20000 (100%)
test_accuracies_ABnB = [(0.43133333333333335, 0.032091674240456135), (0.44133333333333336, 0.0036745370078721594), (0.4425333333333333, 0.059067494350860075), (0.5266000000000001, 0.007845168364456338), (0.5837333333333333, 0.014972270665763707), (0.5997333333333333, 0.008579562278396792), (0.6021333333333333, 0.009315697624022727), (0.6447999999999999, 0.004409081537009734), (0.6744666666666667, 0.0030739045022395756), (0.6886666666666666, 0.0008993825042154746), (0.6939333333333334, 0.00468852025933793), (0.7038666666666668, 0.001857118436957904)]
train_accuracies_ABnB = [(0.9733333333333333, 0.03771236166328251), (0.9866666666666667, 0.018856180831641284), (0.9466666666666667, 0.033993463423951875), (0.996, 0.0032659863237109073), (0.9953333333333333, 0.0018856180831641283), (0.9928888888888889, 0.004532461789860233), (0.9903333333333334, 0.009428090415820642), (0.9970666666666667, 0.002223110933404404), (0.9938666666666668, 0.00867384318255497), (0.9999333333333333, 9.428090415819597e-05), (0.9965999999999999, 0.004714045207910321), (0.9866, 0.018915117410861267)]
gen_errors_ABnB = [(0.542, 0.06891289187566187), (0.5453333333333333, 0.019257091046042122), (0.5041333333333333, 0.03367940353127148), (0.4694, 0.005905929224093347), (0.41159999999999997, 0.015571769327857365), (0.39315555555555565, 0.013083926620188183), (0.38820000000000005, 0.016589956801229707), (0.3522666666666667, 0.00622753741235027), (0.3194, 0.0073774430981653075), (0.31126666666666664, 0.0009428090415820641), (0.3026666666666667, 0.001407914138796175), (0.28273333333333334, 0.01853295862930571)]
n_training_examples = [25, 50, 100, 250, 500, 750, 1000, 2500, 5000, 10000, 15000, 20000]
test_accuracies = {'B': [(0.39093333333333335, 0.016468420959183945), (0.4261333333333333, 0.020708345070419205), (0.4408666666666667, 0.01621713771155549), (0.5168666666666667, 0.014286901537966709), (0.5510666666666667, 0.0029318177903061046), (0.569, 0.004868949236402741), (0.5768, 0.0040431011200150494), (0.6058666666666667, 0.004413111776916091), (0.6326666666666667, 0.004401009985093048), (0.6715333333333332, 0.0028767265347188526), (0.6880000000000001, 0.0017048949136725885), (0.6962666666666667, 0.001463633226673339)], 'AnB': [(0.39093333333333335, 0.009721911106133184), (0.3781999999999999, 0.025556734272333518), (0.3970666666666667, 0.007950401806757264), (0.5034, 0.0024055491403558254), (0.5653333333333334, 0.005881798666696727), (0.5717333333333333, 0.013462375553948682), (0.5832, 0.011329018786579301), (0.6258666666666666, 0.0051493257379540275), (0.6516000000000001, 0.0057410800377629655), (0.6782, 0.004982636517614615), (0.6846, 0.0036914315199752428), (0.7004, 0.0023720595832876367)], 'BnB': [(0.39953333333333335, 0.042587739498070966), (0.4463333333333333, 0.019491080581184376), (0.4762, 0.026086522701706836), (0.5416666666666666, 0.010309003616041463), (0.5926666666666666, 0.005327496806401896), (0.6148, 0.01592984620139191), (0.6195333333333334, 0.01806383741684538), (0.6565333333333334, 0.010621152898291639), (0.6878000000000001, 0.0054869542249473), (0.703, 0.0015748015748023767), (0.7042666666666667, 0.004828618389928507), (0.7028666666666666, 0.0027390184778898967)], 'ABnB': [(0.43133333333333335, 0.032091674240456135), (0.44133333333333336, 0.0036745370078721594), (0.4425333333333333, 0.059067494350860075), (0.5266000000000001, 0.007845168364456338), (0.5837333333333333, 0.014972270665763707), (0.5997333333333333, 0.008579562278396792), (0.6021333333333333, 0.009315697624022727), (0.6447999999999999, 0.004409081537009734), (0.6744666666666667, 0.0030739045022395756), (0.6886666666666666, 0.0008993825042154746), (0.6939333333333334, 0.00468852025933793), (0.7038666666666668, 0.001857118436957904)]}
n_training_examples = [25, 50, 100, 250, 500, 750, 1000, 2500, 5000, 10000, 15000, 20000]
train_accuracies = {'B': [(1.0, 0.0), (0.9866666666666667, 0.018856180831641284), (0.86, 0.11860297916438133), (0.8773333333333334, 0.1029865147590801), (0.9226666666666666, 0.04631294515455574), (0.9053333333333334, 0.013063945294843629), (0.8879999999999999, 0.0659140854951858), (0.8921333333333333, 0.05611638699069008), (0.916, 0.06428457565129186), (0.9748000000000001, 0.03493145669259538), (0.9862000000000001, 0.019139100950284645), (0.9996499999999999, 4.0824829046381805e-05)], 'AnB': [(1.0, 0.0), (0.9733333333333333, 0.009428090415820642), (0.9033333333333333, 0.023570226039551605), (0.9893333333333333, 0.0018856180831641283), (0.988, 0.002828427124746193), (0.9795555555555556, 0.012988123729957734), (0.988, 0.00509901951359279), (0.9966666666666666, 0.0019955506062794433), (0.9996, 0.0002828427124746402), (0.9993333333333334, 0.0008730533902472614), (0.9895111111111111, 0.009616703575254931), (0.9922166666666667, 0.010795240720902084)], 'BnB': [(1.0, 0.0), (0.9933333333333333, 0.009428090415820642), (0.9433333333333334, 0.036817870057290855), (0.9973333333333333, 0.0018856180831641283), (0.992, 0.005656854249492386), (0.9928888888888888, 0.002739739556875117), (0.9963333333333333, 0.0016996731711975965), (0.9965333333333334, 0.00405736641458745), (0.9998, 0.00016329931618552722), (0.9996333333333333, 0.0005185449728701301), (0.9975333333333333, 0.003394112549695421), (0.9982333333333333, 0.0024631732018317704)], 'ABnB': [(0.9733333333333333, 0.03771236166328251), (0.9866666666666667, 0.018856180831641284), (0.9466666666666667, 0.033993463423951875), (0.996, 0.0032659863237109073), (0.9953333333333333, 0.0018856180831641283), (0.9928888888888889, 0.004532461789860233), (0.9903333333333334, 0.009428090415820642), (0.9970666666666667, 0.002223110933404404), (0.9938666666666668, 0.00867384318255497), (0.9999333333333333, 9.428090415819597e-05), (0.9965999999999999, 0.004714045207910321), (0.9866, 0.018915117410861267)]}
n_training_examples = [25, 50, 100, 250, 500, 750, 1000, 2500, 5000, 10000, 15000, 20000]
generr_accuracies = {'B': [(0.6090666666666666, 0.016468420959183935), (0.5605333333333333, 0.025550646871567797), (0.41913333333333336, 0.13336789552045708), (0.36046666666666666, 0.09312276246379769), (0.37159999999999993, 0.04338325329740347), (0.3363333333333333, 0.01257404734628697), (0.31120000000000003, 0.06282738256524772), (0.28626666666666667, 0.060477286829207416), (0.2833333333333333, 0.06731603738255014), (0.3032666666666667, 0.03367197977877484), (0.2982, 0.01744230701696526), (0.30338333333333334, 0.0014619241506392219)], 'AnB': [(0.6090666666666666, 0.009721911106133206), (0.5951333333333333, 0.023679151636454822), (0.5062666666666668, 0.01601693548161515), (0.4859333333333333, 0.003689022755268515), (0.4226666666666666, 0.0037853518844208817), (0.40782222222222225, 0.006541114036577122), (0.4048, 0.009441751249988896), (0.3708, 0.0031874754901018566), (0.34800000000000003, 0.005564171097297444), (0.3211333333333333, 0.0058459862774005635), (0.30491111111111113, 0.005935288899538718), (0.29181666666666667, 0.010922631957952698)], 'BnB': [(0.6004666666666666, 0.04258773949807096), (0.547, 0.028290398842481343), (0.46713333333333334, 0.047188228287242194), (0.45566666666666666, 0.011483708266738408), (0.3993333333333333, 0.008492087820763277), (0.37808888888888886, 0.013250557873184705), (0.37679999999999997, 0.016434110867339334), (0.34, 0.008081254028098997), (0.312, 0.0053241587754937585), (0.2966333333333333, 0.0014704496666742043), (0.2932666666666667, 0.0019482185594936858), (0.2953666666666667, 0.004572441604025378)], 'ABnB': [(0.542, 0.06891289187566187), (0.5453333333333333, 0.019257091046042122), (0.5041333333333333, 0.03367940353127148), (0.4694, 0.005905929224093347), (0.41159999999999997, 0.015571769327857365), (0.39315555555555565, 0.013083926620188183), (0.38820000000000005, 0.016589956801229707), (0.3522666666666667, 0.00622753741235027), (0.3194, 0.0073774430981653075), (0.31126666666666664, 0.0009428090415820641), (0.3026666666666667, 0.001407914138796175), (0.28273333333333334, 0.01853295862930571)]}
In [7]:
results_test = {}
results_train = {}
results_generr = {}
n_hus = [7, 9, 11, 13]
n_training_examples = [25, 50, 100, 250, 500, 750, 1000, 2500, 5000, 10000, 15000, 20000]
results_test[7] = {'B': [(0.38139999999999996, 0.015809701662797656), (0.3970666666666666, 0.028842715236645496), (0.4288666666666667, 0.02155880846016826), (0.5150666666666667, 0.006661998365522331), (0.5502, 0.004140853374205232), (0.564, 0.0058057442818872425), (0.5720666666666666, 0.00338755893757666), (0.6050666666666668, 0.0020154955277108012), (0.6286, 0.0027276363393971886), (0.6593333333333334, 0.0024783507060588098), (0.6668666666666666, 0.004847909056719406), (0.6729333333333333, 0.000984321537348923)], 'AnB': [(0.30119999999999997, 0.015047480409246826), (0.2637333333333333, 0.02428515779007599), (0.2998, 0.02618549216646502), (0.48546666666666666, 0.013450485327881496), (0.5288, 0.015036843640427585), (0.5560666666666667, 0.008980472642845102), (0.5705333333333332, 0.0017987650084309492), (0.6044666666666667, 0.002379542439676599), (0.6376666666666667, 0.0009977753031397067), (0.6528666666666667, 0.01166799992381823), (0.665, 0.0030594117081556606), (0.6743333333333333, 0.0014817407180595414)], 'BnB': [(0.3277333333333334, 0.04855576404735305), (0.3639333333333333, 0.03589961312078758), (0.32993333333333336, 0.04530322529602303), (0.5082, 0.018244999314880782), (0.5541333333333334, 0.004135483311805577), (0.5622, 0.0044751163858235635), (0.5892666666666666, 0.009309970760188007), (0.616, 0.013465016400534649), (0.6516666666666667, 0.006816320284598008), (0.6614, 0.004667618950457102), (0.674, 0.004581120678029189), (0.6732, 0.004169732205629844)], 'ABnB': [(0.31373333333333336, 0.03327474851728993), (0.3403333333333333, 0.04302691664011676), (0.3038666666666667, 0.01627786499787022), (0.47846666666666665, 0.01972499823968447), (0.5561333333333334, 0.010847221866552884), (0.5794666666666667, 0.0017913371790059629), (0.5916666666666667, 0.008249983164965972), (0.6240666666666667, 0.007838934167914001), (0.6432666666666667, 0.004148359782961093), (0.6560666666666667, 0.00489988662000346), (0.6611333333333334, 0.005879531349426478), (0.6725333333333333, 0.005195724738239637)]}
results_train[7] = {'B': [(0.96, 0.0), (0.8133333333333334, 0.09568466729604881), (0.7266666666666666, 0.10274023338281628), (0.884, 0.021416504538945367), (0.868, 0.028612351645166605), (0.843111111111111, 0.018260123185932547), (0.8053333333333333, 0.020885933597094022), (0.7885333333333334, 0.01053417718138861), (0.8553333333333333, 0.01441881486885179), (0.8739333333333335, 0.0022866763848190196), (0.8454444444444444, 0.019579303761943886), (0.8278, 0.01500216651020777)], 'AnB': [(0.8666666666666667, 0.03771236166328257), (0.5933333333333334, 0.06599663291074445), (0.5066666666666667, 0.14007934259633795), (0.884, 0.008640987597877155), (0.8446666666666666, 0.0033993463423951926), (0.8537777777777777, 0.012757955639473177), (0.8576666666666667, 0.0020548046676563273), (0.8536, 0.007382863039950467), (0.8575333333333334, 0.034228383283792733), (0.8843, 0.0119132978921316), (0.8282444444444444, 0.015601456089056711), (0.83625, 0.006368673331236242)], 'BnB': [(0.9333333333333332, 0.0679869268479038), (0.7599999999999999, 0.08640987597877146), (0.6233333333333334, 0.07408703590297622), (0.9026666666666667, 0.02815828277592381), (0.8886666666666666, 0.01309792180292568), (0.8564444444444445, 0.03159621793275771), (0.8923333333333333, 0.01108552609887727), (0.8793333333333333, 0.008199728992811604), (0.9037333333333333, 0.012505287770468238), (0.8726333333333334, 0.006136955452194726), (0.8780666666666667, 0.016776438504309803), (0.83805, 0.007347221697122431)], 'ABnB': [(0.9066666666666667, 0.018856180831641284), (0.8266666666666667, 0.12472191289246469), (0.5800000000000001, 0.024494897427831758), (0.8999999999999999, 0.052255781179374475), (0.8873333333333333, 0.018354533197248286), (0.8777777777777778, 0.012570787221094207), (0.8766666666666666, 0.02007209228976615), (0.8938666666666667, 0.01254042352642931), (0.8664666666666667, 0.012805554350445834), (0.8157666666666668, 0.0076027772703284235), (0.8628444444444444, 0.05040383093416119), (0.8682500000000001, 0.01304243075503953)]}
results_generr[7] = {'B': [(0.5785999999999999, 0.01580970166279762), (0.41626666666666673, 0.08286476264908316), (0.2978, 0.11273520597695588), (0.3689333333333334, 0.017408299425529454), (0.31779999999999997, 0.029272512703900275), (0.27911111111111114, 0.02388548813003148), (0.23326666666666665, 0.023383945109602167), (0.18346666666666667, 0.009898596982513297), (0.22673333333333334, 0.011763597333393444), (0.2146, 0.0026545558322752525), (0.17857777777777775, 0.02168695346555812), (0.15486666666666668, 0.015512593450340768)], 'AnB': [(0.5654666666666667, 0.047951178875555896), (0.32960000000000006, 0.0453381370003959), (0.20686666666666664, 0.11389425895198675), (0.39853333333333335, 0.009069117315863153), (0.31586666666666663, 0.016877861897237556), (0.2977111111111111, 0.003783916580919545), (0.28713333333333335, 0.0029948103260288234), (0.24913333333333332, 0.009661377863546252), (0.21986666666666665, 0.035202398908155214), (0.2314333333333333, 0.01755492966535486), (0.1632444444444444, 0.012844405997635646), (0.16191666666666668, 0.007570703768841816)], 'BnB': [(0.6056, 0.020835226580641374), (0.3960666666666666, 0.10202343957259145), (0.29340000000000005, 0.02878934988266783), (0.3944666666666666, 0.031102554378843017), (0.33453333333333335, 0.013227580613584988), (0.29424444444444436, 0.027780746508026196), (0.3030666666666667, 0.016016935481615154), (0.26333333333333336, 0.00874274302239036), (0.25206666666666666, 0.013007006658805921), (0.21123333333333336, 0.0021746008573733737), (0.20406666666666665, 0.01234215900435936), (0.16484999999999997, 0.010358651778424956)], 'ABnB': [(0.5929333333333334, 0.015595155943076928), (0.4863333333333333, 0.1114060840149924), (0.27613333333333334, 0.030934913752730685), (0.4215333333333333, 0.03401581331609691), (0.3312, 0.012251802588462915), (0.29831111111111114, 0.013201159694661378), (0.285, 0.01393700111214749), (0.2698, 0.014795494809794866), (0.22320000000000004, 0.01304760514424008), (0.15969999999999998, 0.00540431926024606), (0.2017111111111111, 0.05628268158957581), (0.19571666666666668, 0.016842423288298585)]}
results_test[9] = {'B': [(0.3796, 0.011717792738680202), (0.42366666666666664, 0.027517913357585015), (0.4106666666666667, 0.01702573215916296), (0.5225333333333332, 0.005060522590492886), (0.5466666666666666, 0.0066659999666633185), (0.5626666666666668, 0.0024513035081133666), (0.5783333333333334, 0.0037606146069787886), (0.6065333333333333, 0.0025368396787253896), (0.6395333333333334, 0.00389643711898734), (0.6646, 0.0019252705437591683), (0.6797333333333334, 0.0034344658326376553), (0.6870666666666668, 0.006450495243691641)], 'AnB': [(0.3310666666666667, 0.06135304031224171), (0.40700000000000003, 0.011032074449833378), (0.3992, 0.01604078136085231), (0.5136666666666666, 0.0051233669484909115), (0.5566666666666666, 0.005648205221326715), (0.5724, 0.009717338455907925), (0.5912000000000001, 0.003398038649966567), (0.6174000000000001, 0.002141650453894527), (0.6377333333333334, 0.0028110891523077173), (0.6642666666666667, 0.005123366948490894), (0.6766, 0.000711805216802113), (0.6849333333333333, 0.001359738536958064)], 'BnB': [(0.3738666666666666, 0.026759338972071448), (0.3806, 0.07365233646441004), (0.29960000000000003, 0.07994014427474264), (0.5282666666666667, 0.02442803489617798), (0.5736666666666667, 0.010951204905803258), (0.5918666666666667, 0.013521669850856281), (0.612, 0.006981881312845877), (0.637, 0.011028448062473106), (0.6655333333333333, 0.0021929178937864684), (0.6776, 0.0036914315199752224), (0.6856666666666666, 0.0013199326582148817), (0.6906, 0.0007483314773547949)], 'ABnB': [(0.31553333333333333, 0.046238319846445775), (0.40746666666666664, 0.039548900813493604), (0.3278666666666667, 0.018853352192352662), (0.5367999999999999, 0.00940354543066959), (0.555, 0.006211816696157946), (0.5867333333333333, 0.0038447655614123094), (0.6058, 0.004572380853195241), (0.6334666666666666, 0.00608896999134954), (0.6614666666666666, 0.004781445620544274), (0.6747333333333333, 0.00270472837001346), (0.6842666666666668, 0.0019482185594936858), (0.6891999999999999, 0.004907137658554093)]}
results_train[9] = {'B': [(1.0, 0.0), (1.0, 0.0), (0.7733333333333333, 0.036817870057290855), (0.8933333333333334, 0.029454296045832724), (0.9033333333333333, 0.03222145592958555), (0.8528888888888888, 0.04246247435554199), (0.8523333333333335, 0.029408993333483676), (0.9178666666666667, 0.02187560792806049), (0.9317333333333333, 0.05591429950280063), (0.9323, 0.03580735492418657), (0.9124444444444443, 0.02888574341850157), (0.8965166666666667, 0.02395253408073741)], 'AnB': [(1.0, 0.0), (0.9733333333333333, 0.024944382578492966), (0.7400000000000001, 0.11430952132988166), (0.9613333333333333, 0.010498677165349092), (0.964, 0.0043204937989385775), (0.9573333333333333, 0.011469767022723513), (0.961, 0.008485281374238578), (0.9520000000000001, 0.024638181751095185), (0.9676, 0.005217917847826523), (0.9296000000000001, 0.018524038436582877), (0.8958666666666666, 0.021404257105123347), (0.9467333333333334, 0.014000317456718196)], 'BnB': [(1.0, 0.0), (0.96, 0.0), (0.6699999999999999, 0.19646882704388502), (0.9586666666666667, 0.016110727964792727), (0.9613333333333333, 0.009285592184789422), (0.9524444444444443, 0.013524554715291503), (0.9500000000000001, 0.021924111536540437), (0.9452000000000002, 0.022302167308731857), (0.9440666666666666, 0.026053449334439843), (0.9550000000000001, 0.01651686007286694), (0.9281111111111112, 0.023180728479482826), (0.9272833333333333, 0.01320961350263089)], 'ABnB': [(0.9733333333333333, 0.018856180831641284), (0.9333333333333332, 0.0410960933531265), (0.6466666666666666, 0.004714045207910321), (0.9693333333333333, 0.007542472332656513), (0.9659999999999999, 0.005887840577551903), (0.9702222222222222, 0.0034995590551163513), (0.9786666666666667, 0.004988876515698593), (0.9664000000000001, 0.02067913602321593), (0.9763333333333333, 0.008730533902472538), (0.9465, 0.008041558721209886), (0.9391333333333334, 0.015607120881899457), (0.9113000000000001, 0.015426114222317976)]}
results_generr[9] = {'B': [(0.6204, 0.011717792738680198), (0.5763333333333333, 0.027517913357585015), (0.3626666666666667, 0.05379475397801867), (0.3708, 0.02524915840181612), (0.35666666666666674, 0.03557764591550276), (0.2902222222222222, 0.0449131287687962), (0.27399999999999997, 0.033104682448257955), (0.3113333333333333, 0.02198019310399453), (0.29219999999999996, 0.05496350304217032), (0.2677, 0.036947801017110656), (0.2327111111111111, 0.03228329843780977), (0.20945, 0.029179016433046497)], 'AnB': [(0.6689333333333334, 0.06135304031224173), (0.5663333333333332, 0.02513819581610603), (0.3408, 0.10804307782855258), (0.44766666666666666, 0.005377318621353532), (0.4073333333333333, 0.003564017707899665), (0.3849333333333333, 0.01156354424713961), (0.36979999999999996, 0.011880516262632135), (0.3346, 0.026420194296535103), (0.3298666666666667, 0.007611103000806688), (0.26533333333333337, 0.013469554145883545), (0.21926666666666664, 0.020996719320461068), (0.26180000000000003, 0.013577432256014632)], 'BnB': [(0.6261333333333333, 0.02675933897207146), (0.5794, 0.07365233646441006), (0.3704, 0.11860196738109649), (0.43039999999999995, 0.009471360338761668), (0.3876666666666666, 0.020011552219211363), (0.3605777777777777, 0.024778744375765036), (0.3379999999999999, 0.015022649566571124), (0.3082, 0.013067006798294206), (0.27853333333333335, 0.02400574005431945), (0.27740000000000004, 0.013704743704279897), (0.24244444444444438, 0.022279858589439747), (0.23668333333333333, 0.013587024038479558)], 'ABnB': [(0.6578, 0.03091536834650363), (0.5258666666666666, 0.020234843436233694), (0.31880000000000003, 0.02065332902948094), (0.4325333333333334, 0.00774481905677743), (0.411, 0.0012328828005937977), (0.3834888888888888, 0.0026790453431432266), (0.3728666666666666, 0.0022939534045447233), (0.33293333333333336, 0.021151096635609413), (0.3148666666666667, 0.012746066931497801), (0.27176666666666666, 0.005402057221302093), (0.25486666666666663, 0.017041387528276265), (0.2221, 0.01914379795129481)]}
results_test[11] = {'B': [(0.3959333333333333, 0.015245837318939073), (0.43520000000000003, 0.016085604330166342), (0.45920000000000005, 0.018982799231585065), (0.5140666666666667, 0.007433856483832747), (0.5437333333333333, 0.010451581485859219), (0.5674666666666667, 0.005504745427558125), (0.574, 0.0011430952132987942), (0.6096666666666667, 0.006069230227595209), (0.6431333333333332, 0.0035226252836327823), (0.6708666666666666, 0.0038964371189873204), (0.6855333333333333, 0.004030991055421564), (0.6948666666666666, 0.005751135153650588)], 'AnB': [(0.3717333333333333, 0.013455440865645719), (0.40066666666666667, 0.021669230617526673), (0.4056, 0.052545091746676646), (0.5340666666666666, 0.0020548046676563273), (0.5644, 0.00793137230664823), (0.573, 0.007657675887630638), (0.5863333333333333, 0.0011813363431112643), (0.6216, 0.006701243665668867), (0.6544666666666666, 0.0018061622912192382), (0.6765333333333334, 0.003159465496286095), (0.6870666666666666, 0.002714569742866955), (0.6956000000000001, 0.0026981475126464237)], 'BnB': [(0.3375333333333333, 0.04630603512382473), (0.391, 0.014958609561052133), (0.41, 0.053117981889375276), (0.5248666666666667, 0.014379924277346603), (0.5764, 0.01321009714826756), (0.6025333333333333, 0.005982938705649197), (0.6091333333333333, 0.010701194118207373), (0.6438, 0.00608166643829359), (0.6806, 0.0009092121131323798), (0.6980666666666666, 0.005564969801255778), (0.7017333333333333, 0.0028581268146968043), (0.7017333333333333, 0.003582674358011874)], 'ABnB': [(0.4324666666666667, 0.005073679357450793), (0.4316, 0.005283937925449163), (0.4403333333333333, 0.04460951567646627), (0.5295333333333333, 0.02288658025034661), (0.5757333333333333, 0.005208539995899874), (0.5793333333333334, 0.009076465293395983), (0.5982000000000001, 0.010007996802557421), (0.6375333333333333, 0.007350888079378957), (0.6685333333333333, 0.004502838610871549), (0.6848666666666666, 0.00338755893757666), (0.6919333333333334, 0.0013695092389449483), (0.6952000000000002, 0.00342928563989648)]}
results_train[11] = {'B': [(1.0, 0.0), (1.0, 0.0), (0.8799999999999999, 0.05715476066494078), (0.9159999999999999, 0.02592296279363143), (0.9486666666666667, 0.02945429604583268), (0.8333333333333334, 0.03623789708558135), (0.8963333333333333, 0.01811690432226827), (0.8502666666666667, 0.057476101313695765), (0.9608, 0.016485953617145332), (0.9592666666666667, 0.03031307015500446), (0.9562444444444443, 0.029333754205734884), (0.9485333333333333, 0.03489322602199778)], 'AnB': [(1.0, 0.0), (0.9866666666666667, 0.009428090415820642), (0.8766666666666666, 0.053124591501697384), (0.984, 0.013063945294843629), (0.9846666666666666, 0.003399346342395193), (0.9902222222222222, 0.002739739556875075), (0.9786666666666667, 0.010656244908763863), (0.9752000000000001, 0.010693300083073854), (0.9941333333333334, 0.007310874700669476), (0.9667666666666667, 0.02240927387390218), (0.9805777777777779, 0.025554260836768095), (0.9884833333333333, 0.016039551808645486)], 'BnB': [(1.0, 0.0), (0.9866666666666667, 0.018856180831641284), (0.8633333333333333, 0.02867441755680878), (0.9933333333333333, 0.004988876515698593), (0.9926666666666666, 0.003399346342395193), (0.9968888888888889, 0.001662958838566191), (0.996, 0.0016329931618554536), (0.9957333333333334, 0.002963481436119089), (0.9996666666666667, 0.00033993463423953233), (1.0, 0.0), (0.9996, 0.00047140452079103207), (0.99995, 7.071067811864697e-05)], 'ABnB': [(1.0, 0.0), (0.9933333333333333, 0.009428090415820642), (0.9466666666666667, 0.012472191289246433), (0.996, 0.0), (0.9933333333333333, 0.0009428090415820641), (0.9924444444444444, 0.002739739556875117), (0.9923333333333333, 0.0041096093353126546), (0.9956, 0.004811098280711651), (0.9996, 0.00016329931618557254), (0.9984333333333333, 0.0022156012477178664), (0.9901333333333334, 0.013859399805293255), (0.9471166666666667, 0.02540735895147091)]}
results_generr[11] = {'B': [(0.6040666666666666, 0.015245837318939099), (0.5648000000000001, 0.016085604330166387), (0.4208, 0.038837438981820925), (0.4019333333333333, 0.018954213838147507), (0.4049333333333333, 0.03624227120673068), (0.26586666666666664, 0.03686640546421431), (0.32233333333333336, 0.019108346053201178), (0.2406, 0.05382143315322125), (0.3176666666666667, 0.01961314751781459), (0.2884, 0.0328478309786202), (0.2707111111111111, 0.029696855218634587), (0.2536666666666667, 0.030609539181256713)], 'AnB': [(0.6282666666666666, 0.013455440865645693), (0.586, 0.03001110905425965), (0.4710666666666667, 0.012775323435783869), (0.44993333333333335, 0.012391753530294081), (0.42026666666666673, 0.011198015697236514), (0.4172222222222222, 0.005043318523392625), (0.39233333333333337, 0.009821518325708243), (0.35359999999999997, 0.007652450587883618), (0.33966666666666673, 0.008970073702162252), (0.29023333333333334, 0.01940177540558822), (0.2935111111111111, 0.028032908351030623), (0.29288333333333333, 0.01734763832789804)], 'BnB': [(0.6624666666666666, 0.04630603512382476), (0.5956666666666667, 0.00883075434049789), (0.45333333333333337, 0.039963427725303514), (0.46846666666666664, 0.014782271664245502), (0.41626666666666673, 0.01165885452730622), (0.39435555555555557, 0.007638951514894777), (0.3868666666666667, 0.009329999404549249), (0.3519333333333334, 0.004034297405441908), (0.31906666666666667, 0.0006182412330330306), (0.30193333333333333, 0.005564969801255778), (0.29786666666666667, 0.0024567367696917753), (0.29821666666666663, 0.0035138614403847105)], 'ABnB': [(0.5675333333333333, 0.005073679357450794), (0.5617333333333333, 0.0074481914284982974), (0.5063333333333333, 0.04265374804424834), (0.46646666666666664, 0.02288658025034661), (0.4176, 0.004270831300812501), (0.41311111111111104, 0.011157768704769599), (0.3941333333333333, 0.011763597333393456), (0.3580666666666667, 0.01167142760000773), (0.3310666666666667, 0.004596617113583523), (0.31356666666666666, 0.0015456030825826026), (0.2982000000000001, 0.01452854151381062), (0.2519166666666667, 0.02685393618985657)]}
results_test[13] = {'B': [(0.39093333333333335, 0.016468420959183945), (0.4261333333333333, 0.020708345070419205), (0.4408666666666667, 0.01621713771155549), (0.5168666666666667, 0.014286901537966709), (0.5510666666666667, 0.0029318177903061046), (0.569, 0.004868949236402741), (0.5768, 0.0040431011200150494), (0.6058666666666667, 0.004413111776916091), (0.6326666666666667, 0.004401009985093048), (0.6715333333333332, 0.0028767265347188526), (0.6880000000000001, 0.0017048949136725885), (0.6962666666666667, 0.001463633226673339)], 'AnB': [(0.39093333333333335, 0.009721911106133184), (0.3781999999999999, 0.025556734272333518), (0.3970666666666667, 0.007950401806757264), (0.5034, 0.0024055491403558254), (0.5653333333333334, 0.005881798666696727), (0.5717333333333333, 0.013462375553948682), (0.5832, 0.011329018786579301), (0.6258666666666666, 0.0051493257379540275), (0.6516000000000001, 0.0057410800377629655), (0.6782, 0.004982636517614615), (0.6846, 0.0036914315199752428), (0.7004, 0.0023720595832876367)], 'BnB': [(0.39953333333333335, 0.042587739498070966), (0.4463333333333333, 0.019491080581184376), (0.4762, 0.026086522701706836), (0.5416666666666666, 0.010309003616041463), (0.5926666666666666, 0.005327496806401896), (0.6148, 0.01592984620139191), (0.6195333333333334, 0.01806383741684538), (0.6565333333333334, 0.010621152898291639), (0.6878000000000001, 0.0054869542249473), (0.703, 0.0015748015748023767), (0.7042666666666667, 0.004828618389928507), (0.7028666666666666, 0.0027390184778898967)], 'ABnB': [(0.43133333333333335, 0.032091674240456135), (0.44133333333333336, 0.0036745370078721594), (0.4425333333333333, 0.059067494350860075), (0.5266000000000001, 0.007845168364456338), (0.5837333333333333, 0.014972270665763707), (0.5997333333333333, 0.008579562278396792), (0.6021333333333333, 0.009315697624022727), (0.6447999999999999, 0.004409081537009734), (0.6744666666666667, 0.0030739045022395756), (0.6886666666666666, 0.0008993825042154746), (0.6939333333333334, 0.00468852025933793), (0.7038666666666668, 0.001857118436957904)]}
results_train[13] = {'B': [(1.0, 0.0), (0.9866666666666667, 0.018856180831641284), (0.86, 0.11860297916438133), (0.8773333333333334, 0.1029865147590801), (0.9226666666666666, 0.04631294515455574), (0.9053333333333334, 0.013063945294843629), (0.8879999999999999, 0.0659140854951858), (0.8921333333333333, 0.05611638699069008), (0.916, 0.06428457565129186), (0.9748000000000001, 0.03493145669259538), (0.9862000000000001, 0.019139100950284645), (0.9996499999999999, 4.0824829046381805e-05)], 'AnB': [(1.0, 0.0), (0.9733333333333333, 0.009428090415820642), (0.9033333333333333, 0.023570226039551605), (0.9893333333333333, 0.0018856180831641283), (0.988, 0.002828427124746193), (0.9795555555555556, 0.012988123729957734), (0.988, 0.00509901951359279), (0.9966666666666666, 0.0019955506062794433), (0.9996, 0.0002828427124746402), (0.9993333333333334, 0.0008730533902472614), (0.9895111111111111, 0.009616703575254931), (0.9922166666666667, 0.010795240720902084)], 'BnB': [(1.0, 0.0), (0.9933333333333333, 0.009428090415820642), (0.9433333333333334, 0.036817870057290855), (0.9973333333333333, 0.0018856180831641283), (0.992, 0.005656854249492386), (0.9928888888888888, 0.002739739556875117), (0.9963333333333333, 0.0016996731711975965), (0.9965333333333334, 0.00405736641458745), (0.9998, 0.00016329931618552722), (0.9996333333333333, 0.0005185449728701301), (0.9975333333333333, 0.003394112549695421), (0.9982333333333333, 0.0024631732018317704)], 'ABnB': [(0.9733333333333333, 0.03771236166328251), (0.9866666666666667, 0.018856180831641284), (0.9466666666666667, 0.033993463423951875), (0.996, 0.0032659863237109073), (0.9953333333333333, 0.0018856180831641283), (0.9928888888888889, 0.004532461789860233), (0.9903333333333334, 0.009428090415820642), (0.9970666666666667, 0.002223110933404404), (0.9938666666666668, 0.00867384318255497), (0.9999333333333333, 9.428090415819597e-05), (0.9965999999999999, 0.004714045207910321), (0.9866, 0.018915117410861267)]}
results_generr[13] = {'B': [(0.6090666666666666, 0.016468420959183935), (0.5605333333333333, 0.025550646871567797), (0.41913333333333336, 0.13336789552045708), (0.36046666666666666, 0.09312276246379769), (0.37159999999999993, 0.04338325329740347), (0.3363333333333333, 0.01257404734628697), (0.31120000000000003, 0.06282738256524772), (0.28626666666666667, 0.060477286829207416), (0.2833333333333333, 0.06731603738255014), (0.3032666666666667, 0.03367197977877484), (0.2982, 0.01744230701696526), (0.30338333333333334, 0.0014619241506392219)], 'AnB': [(0.6090666666666666, 0.009721911106133206), (0.5951333333333333, 0.023679151636454822), (0.5062666666666668, 0.01601693548161515), (0.4859333333333333, 0.003689022755268515), (0.4226666666666666, 0.0037853518844208817), (0.40782222222222225, 0.006541114036577122), (0.4048, 0.009441751249988896), (0.3708, 0.0031874754901018566), (0.34800000000000003, 0.005564171097297444), (0.3211333333333333, 0.0058459862774005635), (0.30491111111111113, 0.005935288899538718), (0.29181666666666667, 0.010922631957952698)], 'BnB': [(0.6004666666666666, 0.04258773949807096), (0.547, 0.028290398842481343), (0.46713333333333334, 0.047188228287242194), (0.45566666666666666, 0.011483708266738408), (0.3993333333333333, 0.008492087820763277), (0.37808888888888886, 0.013250557873184705), (0.37679999999999997, 0.016434110867339334), (0.34, 0.008081254028098997), (0.312, 0.0053241587754937585), (0.2966333333333333, 0.0014704496666742043), (0.2932666666666667, 0.0019482185594936858), (0.2953666666666667, 0.004572441604025378)], 'ABnB': [(0.542, 0.06891289187566187), (0.5453333333333333, 0.019257091046042122), (0.5041333333333333, 0.03367940353127148), (0.4694, 0.005905929224093347), (0.41159999999999997, 0.015571769327857365), (0.39315555555555565, 0.013083926620188183), (0.38820000000000005, 0.016589956801229707), (0.3522666666666667, 0.00622753741235027), (0.3194, 0.0073774430981653075), (0.31126666666666664, 0.0009428090415820641), (0.3026666666666667, 0.001407914138796175), (0.28273333333333334, 0.01853295862930571)]}
for hu_pow in n_hus:
plot_all(results_test[hu_pow], "$2^{%i}$ hidden units" % (hu_pow))
plot_all(results_train[hu_pow], "$2^{%i}$ hidden units" % (hu_pow), "Train")
plot_all(results_generr[hu_pow], "$2^{%i}$ hidden units" % (hu_pow), "generr")
n_training_examples = [25, 50, 100, 250, 500, 750, 1000, 2500, 5000, 10000, 15000, 20000]
test_accuracies = {'B': [(0.38139999999999996, 0.015809701662797656), (0.3970666666666666, 0.028842715236645496), (0.4288666666666667, 0.02155880846016826), (0.5150666666666667, 0.006661998365522331), (0.5502, 0.004140853374205232), (0.564, 0.0058057442818872425), (0.5720666666666666, 0.00338755893757666), (0.6050666666666668, 0.0020154955277108012), (0.6286, 0.0027276363393971886), (0.6593333333333334, 0.0024783507060588098), (0.6668666666666666, 0.004847909056719406), (0.6729333333333333, 0.000984321537348923)], 'AnB': [(0.30119999999999997, 0.015047480409246826), (0.2637333333333333, 0.02428515779007599), (0.2998, 0.02618549216646502), (0.48546666666666666, 0.013450485327881496), (0.5288, 0.015036843640427585), (0.5560666666666667, 0.008980472642845102), (0.5705333333333332, 0.0017987650084309492), (0.6044666666666667, 0.002379542439676599), (0.6376666666666667, 0.0009977753031397067), (0.6528666666666667, 0.01166799992381823), (0.665, 0.0030594117081556606), (0.6743333333333333, 0.0014817407180595414)], 'BnB': [(0.3277333333333334, 0.04855576404735305), (0.3639333333333333, 0.03589961312078758), (0.32993333333333336, 0.04530322529602303), (0.5082, 0.018244999314880782), (0.5541333333333334, 0.004135483311805577), (0.5622, 0.0044751163858235635), (0.5892666666666666, 0.009309970760188007), (0.616, 0.013465016400534649), (0.6516666666666667, 0.006816320284598008), (0.6614, 0.004667618950457102), (0.674, 0.004581120678029189), (0.6732, 0.004169732205629844)], 'ABnB': [(0.31373333333333336, 0.03327474851728993), (0.3403333333333333, 0.04302691664011676), (0.3038666666666667, 0.01627786499787022), (0.47846666666666665, 0.01972499823968447), (0.5561333333333334, 0.010847221866552884), (0.5794666666666667, 0.0017913371790059629), (0.5916666666666667, 0.008249983164965972), (0.6240666666666667, 0.007838934167914001), (0.6432666666666667, 0.004148359782961093), (0.6560666666666667, 0.00489988662000346), (0.6611333333333334, 0.005879531349426478), (0.6725333333333333, 0.005195724738239637)]}
n_training_examples = [25, 50, 100, 250, 500, 750, 1000, 2500, 5000, 10000, 15000, 20000]
train_accuracies = {'B': [(0.96, 0.0), (0.8133333333333334, 0.09568466729604881), (0.7266666666666666, 0.10274023338281628), (0.884, 0.021416504538945367), (0.868, 0.028612351645166605), (0.843111111111111, 0.018260123185932547), (0.8053333333333333, 0.020885933597094022), (0.7885333333333334, 0.01053417718138861), (0.8553333333333333, 0.01441881486885179), (0.8739333333333335, 0.0022866763848190196), (0.8454444444444444, 0.019579303761943886), (0.8278, 0.01500216651020777)], 'AnB': [(0.8666666666666667, 0.03771236166328257), (0.5933333333333334, 0.06599663291074445), (0.5066666666666667, 0.14007934259633795), (0.884, 0.008640987597877155), (0.8446666666666666, 0.0033993463423951926), (0.8537777777777777, 0.012757955639473177), (0.8576666666666667, 0.0020548046676563273), (0.8536, 0.007382863039950467), (0.8575333333333334, 0.034228383283792733), (0.8843, 0.0119132978921316), (0.8282444444444444, 0.015601456089056711), (0.83625, 0.006368673331236242)], 'BnB': [(0.9333333333333332, 0.0679869268479038), (0.7599999999999999, 0.08640987597877146), (0.6233333333333334, 0.07408703590297622), (0.9026666666666667, 0.02815828277592381), (0.8886666666666666, 0.01309792180292568), (0.8564444444444445, 0.03159621793275771), (0.8923333333333333, 0.01108552609887727), (0.8793333333333333, 0.008199728992811604), (0.9037333333333333, 0.012505287770468238), (0.8726333333333334, 0.006136955452194726), (0.8780666666666667, 0.016776438504309803), (0.83805, 0.007347221697122431)], 'ABnB': [(0.9066666666666667, 0.018856180831641284), (0.8266666666666667, 0.12472191289246469), (0.5800000000000001, 0.024494897427831758), (0.8999999999999999, 0.052255781179374475), (0.8873333333333333, 0.018354533197248286), (0.8777777777777778, 0.012570787221094207), (0.8766666666666666, 0.02007209228976615), (0.8938666666666667, 0.01254042352642931), (0.8664666666666667, 0.012805554350445834), (0.8157666666666668, 0.0076027772703284235), (0.8628444444444444, 0.05040383093416119), (0.8682500000000001, 0.01304243075503953)]}
n_training_examples = [25, 50, 100, 250, 500, 750, 1000, 2500, 5000, 10000, 15000, 20000]
generr_accuracies = {'B': [(0.5785999999999999, 0.01580970166279762), (0.41626666666666673, 0.08286476264908316), (0.2978, 0.11273520597695588), (0.3689333333333334, 0.017408299425529454), (0.31779999999999997, 0.029272512703900275), (0.27911111111111114, 0.02388548813003148), (0.23326666666666665, 0.023383945109602167), (0.18346666666666667, 0.009898596982513297), (0.22673333333333334, 0.011763597333393444), (0.2146, 0.0026545558322752525), (0.17857777777777775, 0.02168695346555812), (0.15486666666666668, 0.015512593450340768)], 'AnB': [(0.5654666666666667, 0.047951178875555896), (0.32960000000000006, 0.0453381370003959), (0.20686666666666664, 0.11389425895198675), (0.39853333333333335, 0.009069117315863153), (0.31586666666666663, 0.016877861897237556), (0.2977111111111111, 0.003783916580919545), (0.28713333333333335, 0.0029948103260288234), (0.24913333333333332, 0.009661377863546252), (0.21986666666666665, 0.035202398908155214), (0.2314333333333333, 0.01755492966535486), (0.1632444444444444, 0.012844405997635646), (0.16191666666666668, 0.007570703768841816)], 'BnB': [(0.6056, 0.020835226580641374), (0.3960666666666666, 0.10202343957259145), (0.29340000000000005, 0.02878934988266783), (0.3944666666666666, 0.031102554378843017), (0.33453333333333335, 0.013227580613584988), (0.29424444444444436, 0.027780746508026196), (0.3030666666666667, 0.016016935481615154), (0.26333333333333336, 0.00874274302239036), (0.25206666666666666, 0.013007006658805921), (0.21123333333333336, 0.0021746008573733737), (0.20406666666666665, 0.01234215900435936), (0.16484999999999997, 0.010358651778424956)], 'ABnB': [(0.5929333333333334, 0.015595155943076928), (0.4863333333333333, 0.1114060840149924), (0.27613333333333334, 0.030934913752730685), (0.4215333333333333, 0.03401581331609691), (0.3312, 0.012251802588462915), (0.29831111111111114, 0.013201159694661378), (0.285, 0.01393700111214749), (0.2698, 0.014795494809794866), (0.22320000000000004, 0.01304760514424008), (0.15969999999999998, 0.00540431926024606), (0.2017111111111111, 0.05628268158957581), (0.19571666666666668, 0.016842423288298585)]}
n_training_examples = [25, 50, 100, 250, 500, 750, 1000, 2500, 5000, 10000, 15000, 20000]
test_accuracies = {'B': [(0.3796, 0.011717792738680202), (0.42366666666666664, 0.027517913357585015), (0.4106666666666667, 0.01702573215916296), (0.5225333333333332, 0.005060522590492886), (0.5466666666666666, 0.0066659999666633185), (0.5626666666666668, 0.0024513035081133666), (0.5783333333333334, 0.0037606146069787886), (0.6065333333333333, 0.0025368396787253896), (0.6395333333333334, 0.00389643711898734), (0.6646, 0.0019252705437591683), (0.6797333333333334, 0.0034344658326376553), (0.6870666666666668, 0.006450495243691641)], 'AnB': [(0.3310666666666667, 0.06135304031224171), (0.40700000000000003, 0.011032074449833378), (0.3992, 0.01604078136085231), (0.5136666666666666, 0.0051233669484909115), (0.5566666666666666, 0.005648205221326715), (0.5724, 0.009717338455907925), (0.5912000000000001, 0.003398038649966567), (0.6174000000000001, 0.002141650453894527), (0.6377333333333334, 0.0028110891523077173), (0.6642666666666667, 0.005123366948490894), (0.6766, 0.000711805216802113), (0.6849333333333333, 0.001359738536958064)], 'BnB': [(0.3738666666666666, 0.026759338972071448), (0.3806, 0.07365233646441004), (0.29960000000000003, 0.07994014427474264), (0.5282666666666667, 0.02442803489617798), (0.5736666666666667, 0.010951204905803258), (0.5918666666666667, 0.013521669850856281), (0.612, 0.006981881312845877), (0.637, 0.011028448062473106), (0.6655333333333333, 0.0021929178937864684), (0.6776, 0.0036914315199752224), (0.6856666666666666, 0.0013199326582148817), (0.6906, 0.0007483314773547949)], 'ABnB': [(0.31553333333333333, 0.046238319846445775), (0.40746666666666664, 0.039548900813493604), (0.3278666666666667, 0.018853352192352662), (0.5367999999999999, 0.00940354543066959), (0.555, 0.006211816696157946), (0.5867333333333333, 0.0038447655614123094), (0.6058, 0.004572380853195241), (0.6334666666666666, 0.00608896999134954), (0.6614666666666666, 0.004781445620544274), (0.6747333333333333, 0.00270472837001346), (0.6842666666666668, 0.0019482185594936858), (0.6891999999999999, 0.004907137658554093)]}
n_training_examples = [25, 50, 100, 250, 500, 750, 1000, 2500, 5000, 10000, 15000, 20000]
train_accuracies = {'B': [(1.0, 0.0), (1.0, 0.0), (0.7733333333333333, 0.036817870057290855), (0.8933333333333334, 0.029454296045832724), (0.9033333333333333, 0.03222145592958555), (0.8528888888888888, 0.04246247435554199), (0.8523333333333335, 0.029408993333483676), (0.9178666666666667, 0.02187560792806049), (0.9317333333333333, 0.05591429950280063), (0.9323, 0.03580735492418657), (0.9124444444444443, 0.02888574341850157), (0.8965166666666667, 0.02395253408073741)], 'AnB': [(1.0, 0.0), (0.9733333333333333, 0.024944382578492966), (0.7400000000000001, 0.11430952132988166), (0.9613333333333333, 0.010498677165349092), (0.964, 0.0043204937989385775), (0.9573333333333333, 0.011469767022723513), (0.961, 0.008485281374238578), (0.9520000000000001, 0.024638181751095185), (0.9676, 0.005217917847826523), (0.9296000000000001, 0.018524038436582877), (0.8958666666666666, 0.021404257105123347), (0.9467333333333334, 0.014000317456718196)], 'BnB': [(1.0, 0.0), (0.96, 0.0), (0.6699999999999999, 0.19646882704388502), (0.9586666666666667, 0.016110727964792727), (0.9613333333333333, 0.009285592184789422), (0.9524444444444443, 0.013524554715291503), (0.9500000000000001, 0.021924111536540437), (0.9452000000000002, 0.022302167308731857), (0.9440666666666666, 0.026053449334439843), (0.9550000000000001, 0.01651686007286694), (0.9281111111111112, 0.023180728479482826), (0.9272833333333333, 0.01320961350263089)], 'ABnB': [(0.9733333333333333, 0.018856180831641284), (0.9333333333333332, 0.0410960933531265), (0.6466666666666666, 0.004714045207910321), (0.9693333333333333, 0.007542472332656513), (0.9659999999999999, 0.005887840577551903), (0.9702222222222222, 0.0034995590551163513), (0.9786666666666667, 0.004988876515698593), (0.9664000000000001, 0.02067913602321593), (0.9763333333333333, 0.008730533902472538), (0.9465, 0.008041558721209886), (0.9391333333333334, 0.015607120881899457), (0.9113000000000001, 0.015426114222317976)]}
n_training_examples = [25, 50, 100, 250, 500, 750, 1000, 2500, 5000, 10000, 15000, 20000]
generr_accuracies = {'B': [(0.6204, 0.011717792738680198), (0.5763333333333333, 0.027517913357585015), (0.3626666666666667, 0.05379475397801867), (0.3708, 0.02524915840181612), (0.35666666666666674, 0.03557764591550276), (0.2902222222222222, 0.0449131287687962), (0.27399999999999997, 0.033104682448257955), (0.3113333333333333, 0.02198019310399453), (0.29219999999999996, 0.05496350304217032), (0.2677, 0.036947801017110656), (0.2327111111111111, 0.03228329843780977), (0.20945, 0.029179016433046497)], 'AnB': [(0.6689333333333334, 0.06135304031224173), (0.5663333333333332, 0.02513819581610603), (0.3408, 0.10804307782855258), (0.44766666666666666, 0.005377318621353532), (0.4073333333333333, 0.003564017707899665), (0.3849333333333333, 0.01156354424713961), (0.36979999999999996, 0.011880516262632135), (0.3346, 0.026420194296535103), (0.3298666666666667, 0.007611103000806688), (0.26533333333333337, 0.013469554145883545), (0.21926666666666664, 0.020996719320461068), (0.26180000000000003, 0.013577432256014632)], 'BnB': [(0.6261333333333333, 0.02675933897207146), (0.5794, 0.07365233646441006), (0.3704, 0.11860196738109649), (0.43039999999999995, 0.009471360338761668), (0.3876666666666666, 0.020011552219211363), (0.3605777777777777, 0.024778744375765036), (0.3379999999999999, 0.015022649566571124), (0.3082, 0.013067006798294206), (0.27853333333333335, 0.02400574005431945), (0.27740000000000004, 0.013704743704279897), (0.24244444444444438, 0.022279858589439747), (0.23668333333333333, 0.013587024038479558)], 'ABnB': [(0.6578, 0.03091536834650363), (0.5258666666666666, 0.020234843436233694), (0.31880000000000003, 0.02065332902948094), (0.4325333333333334, 0.00774481905677743), (0.411, 0.0012328828005937977), (0.3834888888888888, 0.0026790453431432266), (0.3728666666666666, 0.0022939534045447233), (0.33293333333333336, 0.021151096635609413), (0.3148666666666667, 0.012746066931497801), (0.27176666666666666, 0.005402057221302093), (0.25486666666666663, 0.017041387528276265), (0.2221, 0.01914379795129481)]}
n_training_examples = [25, 50, 100, 250, 500, 750, 1000, 2500, 5000, 10000, 15000, 20000]
test_accuracies = {'B': [(0.3959333333333333, 0.015245837318939073), (0.43520000000000003, 0.016085604330166342), (0.45920000000000005, 0.018982799231585065), (0.5140666666666667, 0.007433856483832747), (0.5437333333333333, 0.010451581485859219), (0.5674666666666667, 0.005504745427558125), (0.574, 0.0011430952132987942), (0.6096666666666667, 0.006069230227595209), (0.6431333333333332, 0.0035226252836327823), (0.6708666666666666, 0.0038964371189873204), (0.6855333333333333, 0.004030991055421564), (0.6948666666666666, 0.005751135153650588)], 'AnB': [(0.3717333333333333, 0.013455440865645719), (0.40066666666666667, 0.021669230617526673), (0.4056, 0.052545091746676646), (0.5340666666666666, 0.0020548046676563273), (0.5644, 0.00793137230664823), (0.573, 0.007657675887630638), (0.5863333333333333, 0.0011813363431112643), (0.6216, 0.006701243665668867), (0.6544666666666666, 0.0018061622912192382), (0.6765333333333334, 0.003159465496286095), (0.6870666666666666, 0.002714569742866955), (0.6956000000000001, 0.0026981475126464237)], 'BnB': [(0.3375333333333333, 0.04630603512382473), (0.391, 0.014958609561052133), (0.41, 0.053117981889375276), (0.5248666666666667, 0.014379924277346603), (0.5764, 0.01321009714826756), (0.6025333333333333, 0.005982938705649197), (0.6091333333333333, 0.010701194118207373), (0.6438, 0.00608166643829359), (0.6806, 0.0009092121131323798), (0.6980666666666666, 0.005564969801255778), (0.7017333333333333, 0.0028581268146968043), (0.7017333333333333, 0.003582674358011874)], 'ABnB': [(0.4324666666666667, 0.005073679357450793), (0.4316, 0.005283937925449163), (0.4403333333333333, 0.04460951567646627), (0.5295333333333333, 0.02288658025034661), (0.5757333333333333, 0.005208539995899874), (0.5793333333333334, 0.009076465293395983), (0.5982000000000001, 0.010007996802557421), (0.6375333333333333, 0.007350888079378957), (0.6685333333333333, 0.004502838610871549), (0.6848666666666666, 0.00338755893757666), (0.6919333333333334, 0.0013695092389449483), (0.6952000000000002, 0.00342928563989648)]}
n_training_examples = [25, 50, 100, 250, 500, 750, 1000, 2500, 5000, 10000, 15000, 20000]
train_accuracies = {'B': [(1.0, 0.0), (1.0, 0.0), (0.8799999999999999, 0.05715476066494078), (0.9159999999999999, 0.02592296279363143), (0.9486666666666667, 0.02945429604583268), (0.8333333333333334, 0.03623789708558135), (0.8963333333333333, 0.01811690432226827), (0.8502666666666667, 0.057476101313695765), (0.9608, 0.016485953617145332), (0.9592666666666667, 0.03031307015500446), (0.9562444444444443, 0.029333754205734884), (0.9485333333333333, 0.03489322602199778)], 'AnB': [(1.0, 0.0), (0.9866666666666667, 0.009428090415820642), (0.8766666666666666, 0.053124591501697384), (0.984, 0.013063945294843629), (0.9846666666666666, 0.003399346342395193), (0.9902222222222222, 0.002739739556875075), (0.9786666666666667, 0.010656244908763863), (0.9752000000000001, 0.010693300083073854), (0.9941333333333334, 0.007310874700669476), (0.9667666666666667, 0.02240927387390218), (0.9805777777777779, 0.025554260836768095), (0.9884833333333333, 0.016039551808645486)], 'BnB': [(1.0, 0.0), (0.9866666666666667, 0.018856180831641284), (0.8633333333333333, 0.02867441755680878), (0.9933333333333333, 0.004988876515698593), (0.9926666666666666, 0.003399346342395193), (0.9968888888888889, 0.001662958838566191), (0.996, 0.0016329931618554536), (0.9957333333333334, 0.002963481436119089), (0.9996666666666667, 0.00033993463423953233), (1.0, 0.0), (0.9996, 0.00047140452079103207), (0.99995, 7.071067811864697e-05)], 'ABnB': [(1.0, 0.0), (0.9933333333333333, 0.009428090415820642), (0.9466666666666667, 0.012472191289246433), (0.996, 0.0), (0.9933333333333333, 0.0009428090415820641), (0.9924444444444444, 0.002739739556875117), (0.9923333333333333, 0.0041096093353126546), (0.9956, 0.004811098280711651), (0.9996, 0.00016329931618557254), (0.9984333333333333, 0.0022156012477178664), (0.9901333333333334, 0.013859399805293255), (0.9471166666666667, 0.02540735895147091)]}
n_training_examples = [25, 50, 100, 250, 500, 750, 1000, 2500, 5000, 10000, 15000, 20000]
generr_accuracies = {'B': [(0.6040666666666666, 0.015245837318939099), (0.5648000000000001, 0.016085604330166387), (0.4208, 0.038837438981820925), (0.4019333333333333, 0.018954213838147507), (0.4049333333333333, 0.03624227120673068), (0.26586666666666664, 0.03686640546421431), (0.32233333333333336, 0.019108346053201178), (0.2406, 0.05382143315322125), (0.3176666666666667, 0.01961314751781459), (0.2884, 0.0328478309786202), (0.2707111111111111, 0.029696855218634587), (0.2536666666666667, 0.030609539181256713)], 'AnB': [(0.6282666666666666, 0.013455440865645693), (0.586, 0.03001110905425965), (0.4710666666666667, 0.012775323435783869), (0.44993333333333335, 0.012391753530294081), (0.42026666666666673, 0.011198015697236514), (0.4172222222222222, 0.005043318523392625), (0.39233333333333337, 0.009821518325708243), (0.35359999999999997, 0.007652450587883618), (0.33966666666666673, 0.008970073702162252), (0.29023333333333334, 0.01940177540558822), (0.2935111111111111, 0.028032908351030623), (0.29288333333333333, 0.01734763832789804)], 'BnB': [(0.6624666666666666, 0.04630603512382476), (0.5956666666666667, 0.00883075434049789), (0.45333333333333337, 0.039963427725303514), (0.46846666666666664, 0.014782271664245502), (0.41626666666666673, 0.01165885452730622), (0.39435555555555557, 0.007638951514894777), (0.3868666666666667, 0.009329999404549249), (0.3519333333333334, 0.004034297405441908), (0.31906666666666667, 0.0006182412330330306), (0.30193333333333333, 0.005564969801255778), (0.29786666666666667, 0.0024567367696917753), (0.29821666666666663, 0.0035138614403847105)], 'ABnB': [(0.5675333333333333, 0.005073679357450794), (0.5617333333333333, 0.0074481914284982974), (0.5063333333333333, 0.04265374804424834), (0.46646666666666664, 0.02288658025034661), (0.4176, 0.004270831300812501), (0.41311111111111104, 0.011157768704769599), (0.3941333333333333, 0.011763597333393456), (0.3580666666666667, 0.01167142760000773), (0.3310666666666667, 0.004596617113583523), (0.31356666666666666, 0.0015456030825826026), (0.2982000000000001, 0.01452854151381062), (0.2519166666666667, 0.02685393618985657)]}
n_training_examples = [25, 50, 100, 250, 500, 750, 1000, 2500, 5000, 10000, 15000, 20000]
test_accuracies = {'B': [(0.39093333333333335, 0.016468420959183945), (0.4261333333333333, 0.020708345070419205), (0.4408666666666667, 0.01621713771155549), (0.5168666666666667, 0.014286901537966709), (0.5510666666666667, 0.0029318177903061046), (0.569, 0.004868949236402741), (0.5768, 0.0040431011200150494), (0.6058666666666667, 0.004413111776916091), (0.6326666666666667, 0.004401009985093048), (0.6715333333333332, 0.0028767265347188526), (0.6880000000000001, 0.0017048949136725885), (0.6962666666666667, 0.001463633226673339)], 'AnB': [(0.39093333333333335, 0.009721911106133184), (0.3781999999999999, 0.025556734272333518), (0.3970666666666667, 0.007950401806757264), (0.5034, 0.0024055491403558254), (0.5653333333333334, 0.005881798666696727), (0.5717333333333333, 0.013462375553948682), (0.5832, 0.011329018786579301), (0.6258666666666666, 0.0051493257379540275), (0.6516000000000001, 0.0057410800377629655), (0.6782, 0.004982636517614615), (0.6846, 0.0036914315199752428), (0.7004, 0.0023720595832876367)], 'BnB': [(0.39953333333333335, 0.042587739498070966), (0.4463333333333333, 0.019491080581184376), (0.4762, 0.026086522701706836), (0.5416666666666666, 0.010309003616041463), (0.5926666666666666, 0.005327496806401896), (0.6148, 0.01592984620139191), (0.6195333333333334, 0.01806383741684538), (0.6565333333333334, 0.010621152898291639), (0.6878000000000001, 0.0054869542249473), (0.703, 0.0015748015748023767), (0.7042666666666667, 0.004828618389928507), (0.7028666666666666, 0.0027390184778898967)], 'ABnB': [(0.43133333333333335, 0.032091674240456135), (0.44133333333333336, 0.0036745370078721594), (0.4425333333333333, 0.059067494350860075), (0.5266000000000001, 0.007845168364456338), (0.5837333333333333, 0.014972270665763707), (0.5997333333333333, 0.008579562278396792), (0.6021333333333333, 0.009315697624022727), (0.6447999999999999, 0.004409081537009734), (0.6744666666666667, 0.0030739045022395756), (0.6886666666666666, 0.0008993825042154746), (0.6939333333333334, 0.00468852025933793), (0.7038666666666668, 0.001857118436957904)]}
n_training_examples = [25, 50, 100, 250, 500, 750, 1000, 2500, 5000, 10000, 15000, 20000]
train_accuracies = {'B': [(1.0, 0.0), (0.9866666666666667, 0.018856180831641284), (0.86, 0.11860297916438133), (0.8773333333333334, 0.1029865147590801), (0.9226666666666666, 0.04631294515455574), (0.9053333333333334, 0.013063945294843629), (0.8879999999999999, 0.0659140854951858), (0.8921333333333333, 0.05611638699069008), (0.916, 0.06428457565129186), (0.9748000000000001, 0.03493145669259538), (0.9862000000000001, 0.019139100950284645), (0.9996499999999999, 4.0824829046381805e-05)], 'AnB': [(1.0, 0.0), (0.9733333333333333, 0.009428090415820642), (0.9033333333333333, 0.023570226039551605), (0.9893333333333333, 0.0018856180831641283), (0.988, 0.002828427124746193), (0.9795555555555556, 0.012988123729957734), (0.988, 0.00509901951359279), (0.9966666666666666, 0.0019955506062794433), (0.9996, 0.0002828427124746402), (0.9993333333333334, 0.0008730533902472614), (0.9895111111111111, 0.009616703575254931), (0.9922166666666667, 0.010795240720902084)], 'BnB': [(1.0, 0.0), (0.9933333333333333, 0.009428090415820642), (0.9433333333333334, 0.036817870057290855), (0.9973333333333333, 0.0018856180831641283), (0.992, 0.005656854249492386), (0.9928888888888888, 0.002739739556875117), (0.9963333333333333, 0.0016996731711975965), (0.9965333333333334, 0.00405736641458745), (0.9998, 0.00016329931618552722), (0.9996333333333333, 0.0005185449728701301), (0.9975333333333333, 0.003394112549695421), (0.9982333333333333, 0.0024631732018317704)], 'ABnB': [(0.9733333333333333, 0.03771236166328251), (0.9866666666666667, 0.018856180831641284), (0.9466666666666667, 0.033993463423951875), (0.996, 0.0032659863237109073), (0.9953333333333333, 0.0018856180831641283), (0.9928888888888889, 0.004532461789860233), (0.9903333333333334, 0.009428090415820642), (0.9970666666666667, 0.002223110933404404), (0.9938666666666668, 0.00867384318255497), (0.9999333333333333, 9.428090415819597e-05), (0.9965999999999999, 0.004714045207910321), (0.9866, 0.018915117410861267)]}
n_training_examples = [25, 50, 100, 250, 500, 750, 1000, 2500, 5000, 10000, 15000, 20000]
generr_accuracies = {'B': [(0.6090666666666666, 0.016468420959183935), (0.5605333333333333, 0.025550646871567797), (0.41913333333333336, 0.13336789552045708), (0.36046666666666666, 0.09312276246379769), (0.37159999999999993, 0.04338325329740347), (0.3363333333333333, 0.01257404734628697), (0.31120000000000003, 0.06282738256524772), (0.28626666666666667, 0.060477286829207416), (0.2833333333333333, 0.06731603738255014), (0.3032666666666667, 0.03367197977877484), (0.2982, 0.01744230701696526), (0.30338333333333334, 0.0014619241506392219)], 'AnB': [(0.6090666666666666, 0.009721911106133206), (0.5951333333333333, 0.023679151636454822), (0.5062666666666668, 0.01601693548161515), (0.4859333333333333, 0.003689022755268515), (0.4226666666666666, 0.0037853518844208817), (0.40782222222222225, 0.006541114036577122), (0.4048, 0.009441751249988896), (0.3708, 0.0031874754901018566), (0.34800000000000003, 0.005564171097297444), (0.3211333333333333, 0.0058459862774005635), (0.30491111111111113, 0.005935288899538718), (0.29181666666666667, 0.010922631957952698)], 'BnB': [(0.6004666666666666, 0.04258773949807096), (0.547, 0.028290398842481343), (0.46713333333333334, 0.047188228287242194), (0.45566666666666666, 0.011483708266738408), (0.3993333333333333, 0.008492087820763277), (0.37808888888888886, 0.013250557873184705), (0.37679999999999997, 0.016434110867339334), (0.34, 0.008081254028098997), (0.312, 0.0053241587754937585), (0.2966333333333333, 0.0014704496666742043), (0.2932666666666667, 0.0019482185594936858), (0.2953666666666667, 0.004572441604025378)], 'ABnB': [(0.542, 0.06891289187566187), (0.5453333333333333, 0.019257091046042122), (0.5041333333333333, 0.03367940353127148), (0.4694, 0.005905929224093347), (0.41159999999999997, 0.015571769327857365), (0.39315555555555565, 0.013083926620188183), (0.38820000000000005, 0.016589956801229707), (0.3522666666666667, 0.00622753741235027), (0.3194, 0.0073774430981653075), (0.31126666666666664, 0.0009428090415820641), (0.3026666666666667, 0.001407914138796175), (0.28273333333333334, 0.01853295862930571)]}
In [8]:
# create overview plot with differences
colors = get_colors(len(n_hus))
plt.figure()
for i, n in enumerate(n_hus):
plot_mean_std(results_test[n]["B"], c=colors[i], label="$2^{%i}$ hu" % (n))
plt.xlabel("Number of training examples for classifier")
plt.xticks([25, 5000, 10000, 20000], [25, 5000, 10000, 20000])
plt.ylabel("Test accuracy")
plt.ylim(0.55, 0.72)
plt.title("Performance without pretraining")
l = plt.legend(bbox_to_anchor=(1.02, 1), loc=2, borderaxespad=0.);
if savefigs: plt.savefig('fig_pretr_acc_nopt.pdf', dpi=300, bbox_inches="tight", bbox_extra_artists=[l])
for case in ["BnB", "ABnB", "AnB"]:
plt.figure()
plt.plot([25, 20000], [0, 0], "--k", linewidth=0.5)
for i, n in enumerate(n_hus):
v = [results_test[n][case][k][0] - results_test[n]["B"][k][0] for k in range(len(results_test[n]["B"]))]
plt.plot(n_training_examples, v, color=colors[i], label="$2^{%i}$ hu" % (n))
plt.xlabel("Number of training examples for classifier")
plt.xticks([25, 5000, 10000, 20000], [25, 5000, 10000, 20000])
plt.ylabel("Avg. test accuracy gain")
plt.title("Improvements over no pretraining: %s" % case)
plt.ylim(-0.01, 0.06)
l = plt.legend(bbox_to_anchor=(1.02, 1), loc=2, borderaxespad=0.);
if savefigs: plt.savefig('img_acc_%s.pdf' % case, dpi=300, bbox_inches="tight", bbox_extra_artists=[l])
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Content source: cod3licious/simec
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