In [1]:

    

import numpy as np
import math
import multiprocessing as mp

import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.optim as optim
from torchvision import datasets, transforms
from torch.autograd import Variable
from collections import namedtuple

from PIL import Image
import os
import os.path
import errno
import codecs
import copy


    

In [2]:

    

torch.manual_seed(0)
np.random.seed(0)
print("torch.cuda.device_count()", torch.cuda.device_count())
print("torch.cuda.current_device()", torch.cuda.current_device())
torch.cuda.set_device(1)
print("torch.cuda.current_device()", torch.cuda.current_device())


    

    




torch.cuda.device_count() 4
torch.cuda.current_device() 0
torch.cuda.current_device() 1

In [3]:

    

def compute_ranks(x):
  """
  Returns ranks in [0, len(x))
  Note: This is different from scipy.stats.rankdata, which returns ranks in [1, len(x)].
  (https://github.com/openai/evolution-strategies-starter/blob/master/es_distributed/es.py)
  """
  assert x.ndim == 1
  ranks = np.empty(len(x), dtype=int)
  ranks[x.argsort()] = np.arange(len(x))
  return ranks

def compute_centered_ranks(x):
  """
  https://github.com/openai/evolution-strategies-starter/blob/master/es_distributed/es.py
  """
  y = compute_ranks(x.ravel()).reshape(x.shape).astype(np.float32)
  y /= (x.size - 1)
  y -= .5
  return y

def compute_weight_decay(weight_decay, model_param_list):
  model_param_grid = np.array(model_param_list)
  return - weight_decay * np.mean(model_param_grid * model_param_grid, axis=1)

class CMAES:
  '''CMA-ES wrapper.'''
  def __init__(self, num_params,      # number of model parameters
               sigma_init=0.10,       # initial standard deviation
               popsize=255):          # population size

    self.num_params = num_params
    self.sigma_init = sigma_init
    self.popsize = popsize

    self.solutions = None

    import cma
    self.es = cma.CMAEvolutionStrategy( self.num_params * [0],
                                        self.sigma_init,
                                        {'popsize': self.popsize})

  def rms_stdev(self):
    sigma = self.es.result()[6]
    return np.mean(np.sqrt(sigma*sigma))

  def ask(self):
    '''returns a list of parameters'''
    self.solutions = np.array(self.es.ask())
    return self.solutions

  def tell(self, reward_table_result):
    reward_table = reward_table_result
    self.es.tell(self.solutions, (-reward_table).tolist()) # convert minimizer to maximizer.

  def done(self):
    return self.es.stop()

  def current_param(self):
    return self.es.result()[5] # mean solution, presumably better with noise
  
  def best_param(self):
    return self.es.result()[0] # best evaluated solution

  def result(self): # return best params so far, along with historically best reward, curr reward, sigma
    r = self.es.result()
    return (r[0], -r[1], -r[1], r[6])

class SimpleES:
  '''Simple Evolution Strategies.'''
  def __init__(self, num_params,      # number of model parameters
               sigma_init=0.10,       # initial standard deviation
               sigma_alpha=0.20,      # learning rate for standard deviation
               sigma_decay=0.999,     # anneal standard deviation
               sigma_limit=0.01,      # stop annealing if less than this
               popsize=255,           # population size
               elite_ratio=0.1,       # percentage of the elites
               done_threshold=1e-6,   # threshold when we say we are done
               average_baseline=True, # set baseline to average of batch
               forget_best=True):     # only use the best from latest generation

    self.num_params = num_params
    self.sigma_init = sigma_init
    self.sigma_alpha = sigma_alpha
    self.sigma_decay = sigma_decay
    self.sigma_limit = sigma_limit
    self.popsize = popsize
    self.average_baseline = average_baseline
    if self.average_baseline:
      assert (self.popsize & 2), "Population size must be even"
      self.batch_size = int(self.popsize / 2)
    else:
      assert (self.popsize & 1), "Population size must be odd"
      self.batch_size = int((self.popsize - 1) / 2)
    self.elite_ratio = elite_ratio
    self.elite_popsize = int(self.popsize * self.elite_ratio)
    self.forget_best = forget_best
    self.batch_reward = np.zeros(self.batch_size * 2)
    self.mu = np.zeros(self.num_params)
    self.sigma = np.ones(self.num_params) * self.sigma_init
    self.curr_best_mu = np.zeros(self.num_params)
    self.best_mu = np.zeros(self.num_params)
    self.best_reward = 0
    self.first_interation = True
    self.done_threshold = done_threshold

  def rms_stdev(self):
    sigma = self.sigma
    return np.mean(np.sqrt(sigma*sigma))

  def ask(self):
    '''returns a list of parameters'''
    # antithetic sampling
    self.epsilon = np.random.randn(self.batch_size, self.num_params) * self.sigma.reshape(1, self.num_params)
    self.epsilon_full = np.concatenate([self.epsilon, - self.epsilon])
    if self.average_baseline:
      epsilon = self.epsilon_full
    else:
      # first population is mu, then positive epsilon, then negative epsilon
      epsilon = np.concatenate([np.zeros((1, self.num_params)), self.epsilon_full])
    solutions = self.mu.reshape(1, self.num_params) + epsilon
    return solutions

  def tell(self, reward_table_result):
    # input must be a numpy float array
    assert(len(reward_table_result) == self.popsize), "Inconsistent reward_table size reported."

    reward_table = reward_table_result

    reward_offset = 1
    if self.average_baseline:
      b = np.mean(reward_table)
      reward_offset = 0
    else:
      b = reward_table[0] # baseline
      
    reward = reward_table[reward_offset:]
    idx = np.argsort(reward)[::-1][0:self.elite_popsize]

    best_reward = reward[idx[0]]
    if (best_reward > b or self.average_baseline):
      best_mu = self.mu + self.epsilon_full[idx[0]]
      best_reward = reward[idx[0]]
    else:
      best_mu = self.mu
      best_reward = b

    self.curr_best_reward = best_reward
    self.curr_best_mu = best_mu

    if self.first_interation:
      self.first_interation = False
      self.best_reward = self.curr_best_reward
      self.best_mu = best_mu
    else:
      if self.forget_best or (self.curr_best_reward > self.best_reward):
        self.best_mu = best_mu
        self.best_reward = self.curr_best_reward

    # adaptive sigma
    # normalization
    stdev_reward = reward.std()
    epsilon = self.epsilon
    sigma = self.sigma
    S = ((epsilon * epsilon - (sigma * sigma).reshape(1, self.num_params)) / sigma.reshape(1, self.num_params))
    reward_avg = (reward[:self.batch_size] + reward[self.batch_size:]) / 2.0
    rS = reward_avg - b
    delta_sigma = (np.dot(rS, S)) / (2 * self.batch_size * stdev_reward)

    # move mean to the average of the best idx means
    self.mu += self.epsilon_full[idx].mean(axis=0)

    # adjust sigma according to the adaptive sigma calculation
    change_sigma = self.sigma_alpha * delta_sigma
    change_sigma = np.minimum(change_sigma, self.sigma)
    change_sigma = np.maximum(change_sigma, - 0.5 * self.sigma)
    self.sigma += change_sigma
    self.sigma[self.sigma > self.sigma_limit] *= self.sigma_decay

  def done(self):
    return (self.rms_stdev() < self.done_threshold)

  def current_param(self):
    return self.curr_best_mu
  
  def best_param(self):
    return self.best_mu

  def result(self): # return best params so far, along with historically best reward, curr reward, sigma
    return (self.best_mu, self.best_reward, self.curr_best_reward, self.sigma)

class SimpleGA:
  '''Simple Genetic Algorithm.'''
  def __init__(self, num_params,      # number of model parameters
               sigma_init=0.1,        # initial standard deviation
               sigma_decay=0.999,     # anneal standard deviation
               sigma_limit=0.01,      # stop annealing if less than this
               popsize=255,           # population size
               elite_ratio=0.1,       # percentage of the elites
               forget_best=True,      # forget the historical best elites
               done_threshold=1e-6):  # threshold when we say we are done

    self.num_params = num_params
    self.sigma_init = sigma_init
    self.sigma_decay = sigma_decay
    self.sigma_limit = sigma_limit
    self.popsize = popsize

    self.elite_ratio = elite_ratio
    self.elite_popsize = int(self.popsize * self.elite_ratio)

    self.sigma = self.sigma_init
    self.elite_params = np.zeros((self.elite_popsize, self.num_params))
    self.elite_rewards = np.zeros(self.elite_popsize)
    self.best_param = np.zeros(self.num_params)
    self.best_reward = 0
    self.first_iteration = True
    self.forget_best = forget_best
    self.done_threshold = done_threshold

  def rms_stdev(self):
    return self.sigma # same sigma for all parameters.

  def ask(self):
    '''returns a list of parameters'''
    # antithetic sampling
    self.epsilon = np.random.randn(self.popsize, self.num_params) * self.sigma
    solutions = []
    
    def mate(a, b):
      c = np.copy(a)
      idx = np.where(np.random.rand((c.size)) > 0.5)
      c[idx] = b[idx]
      return c
    
    elite_range = range(self.elite_popsize)
    for i in range(self.popsize):
      idx_a = np.random.choice(elite_range)
      idx_b = np.random.choice(elite_range)
      child_params = mate(self.elite_params[idx_a], self.elite_params[idx_b])
      solutions.append(child_params + self.epsilon[i])

    solutions = np.array(solutions)
    self.solutions = solutions

    return solutions

  def tell(self, reward_table_result):
    # input must be a numpy float array
    assert(len(reward_table_result) == self.popsize), "Inconsistent reward_table size reported."
    
    if (not forget_best or self.first_iteration):
      reward = reward_table_result
      solution = self.solutions
    else:
      reward = np.concatenate([reward_table_result, self.elite_rewards])
      solution = np.concatenate([self.solutions, self.elite_params])

    idx = np.argsort(reward)[::-1][0:self.elite_popsize]

    self.elite_rewards = reward[idx]
    self.elite_params = solution[idx]

    self.curr_best_reward = self.elite_rewards[0]
    
    if self.first_iteration or (self.curr_best_reward > self.best_reward):
      self.first_iteration = False
      self.best_reward = self.elite_rewards[0]
      self.best_param = np.copy(self.elite_params[0])

    if (self.sigma > self.sigma_limit):
      self.sigma *= self.sigma_decay

  def done(self):
    return (self.rms_stdev() < self.done_threshold)

  def current_param(self):
    return self.elite_params[0]

  def best_param(self):
    return self.best_param

  def result(self): # return best params so far, along with historically best reward, curr reward, sigma
    return (self.best_param, self.best_reward, self.curr_best_reward, self.sigma)

class OpenES:
  ''' Basic Version of OpenAI Evolution Strategies.'''
  def __init__(self, num_params,             # number of model parameters
               sigma_init=0.1,               # initial standard deviation
               sigma_decay=0.999,            # anneal standard deviation
               sigma_limit=0.01,             # stop annealing if less than this
               learning_rate=0.001,          # learning rate for standard deviation
               learning_rate_decay = 0.9999, # annealing the learning rate
               learning_rate_limit = 0.001,  # stop annealing learning rate
               popsize=255,                  # population size
               antithetic=False,             # whether to use antithetic sampling
               forget_best=True):           # forget historical best

    self.num_params = num_params
    self.sigma_decay = sigma_decay
    self.sigma = sigma_init
    self.sigma_limit = sigma_limit
    self.learning_rate = learning_rate
    self.learning_rate_decay = learning_rate_decay
    self.learning_rate_limit = learning_rate_limit
    self.popsize = popsize
    self.antithetic = antithetic
    if self.antithetic:
      assert (self.popsize & 2), "Population size must be even"
      self.half_popsize = int(self.popsize / 2)

    self.reward = np.zeros(self.popsize)
    self.mu = np.zeros(self.num_params)
    self.best_mu = np.zeros(self.num_params)
    self.best_reward = 0
    self.first_interation = True
    self.forget_best = forget_best

  def rms_stdev(self):
    sigma = self.sigma
    return np.mean(np.sqrt(sigma*sigma))

  def ask(self):
    '''returns a list of parameters'''
    # antithetic sampling
    if self.antithetic:
      self.epsilon_half = np.random.randn(self.half_popsize, self.num_params)
      self.epsilon = np.concatenate([self.epsilon_half, - self.epsilon_half])
    else:
      self.epsilon = np.random.randn(self.popsize, self.num_params)

    self.solutions = self.mu.reshape(1, self.num_params) + self.epsilon * self.sigma

    return self.solutions

  def tell(self, reward):
    # input must be a numpy float array
    assert(len(reward) == self.popsize), "Inconsistent reward_table size reported."

    idx = np.argsort(reward)[::-1]

    best_reward = reward[idx[0]]
    best_mu = self.solutions[idx[0]]

    self.curr_best_reward = best_reward
    self.curr_best_mu = best_mu

    if self.first_interation:
      self.first_interation = False
      self.best_reward = self.curr_best_reward
      self.best_mu = best_mu
    else:
      if self.forget_best or (self.curr_best_reward > self.best_reward):
        self.best_mu = best_mu
        self.best_reward = self.curr_best_reward

    # main bit:
    # standardize the rewards to have a gaussian distribution
    normalized_reward = (reward - np.mean(reward)) / np.std(reward)
    self.mu += self.learning_rate/(self.popsize*self.sigma)*np.dot(self.epsilon.T, normalized_reward)

    # adjust sigma according to the adaptive sigma calculation
    if (self.sigma > self.sigma_limit):
      self.sigma *= self.sigma_decay

    if (self.learning_rate > self.learning_rate_limit):
      self.learning_rate *= self.learning_rate_decay

  def done(self):
    return False

  def current_param(self):
    return self.curr_best_mu

  def best_param(self):
    return self.best_mu

  def result(self): # return best params so far, along with historically best reward, curr reward, sigma
    return (self.best_mu, self.best_reward, self.curr_best_reward, self.sigma)


    

In [4]:

    

Args = namedtuple('Args', ['batch_size', 'test_batch_size', 'epochs', 'lr', 'cuda', 'seed', 'log_interval'])


    

In [5]:

    

args = Args(batch_size=1000, test_batch_size=1000, epochs=30, lr=0.001, cuda=True, seed=0, log_interval=10)


    

In [6]:

    

torch.manual_seed(args.seed)
if args.cuda:
  torch.cuda.manual_seed(args.seed)


    

In [7]:

    

kwargs = {'num_workers': 1, 'pin_memory': True} if args.cuda else {}

train_loader = torch.utils.data.DataLoader(
  datasets.MNIST('MNIST_data', train=True, download=True, transform=transforms.Compose([transforms.ToTensor(), transforms.Normalize((0.1307,), (0.3081,))])),
  batch_size=args.batch_size, shuffle=True, **kwargs)

valid_loader = train_loader

test_loader = torch.utils.data.DataLoader(
  datasets.MNIST('MNIST_data', train=False, transform=transforms.Compose([transforms.ToTensor(),transforms.Normalize((0.1307,), (0.3081,))])),
  batch_size=args.batch_size, shuffle=True, **kwargs)


    

In [8]:

    

class Net(nn.Module):
  def __init__(self):
    super(Net, self).__init__()
    self.num_filter1 = 8
    self.num_filter2 = 16
    self.num_padding = 2
    # input is 28x28
    # padding=2 for same padding
    self.conv1 = nn.Conv2d(1, self.num_filter1, 5, padding=self.num_padding)
    # feature map size is 14*14 by pooling
    # padding=2 for same padding
    self.conv2 = nn.Conv2d(self.num_filter1, self.num_filter2, 5, padding=self.num_padding)
    # feature map size is 7*7 by pooling
    self.fc = nn.Linear(self.num_filter2*7*7, 10)

  def forward(self, x):
    x = F.max_pool2d(F.relu(self.conv1(x)), 2)
    x = F.max_pool2d(F.relu(self.conv2(x)), 2)
    x = x.view(-1, self.num_filter2*7*7)   # reshape Variable
    x = self.fc(x)
    return F.log_softmax(x)


    

In [9]:

    

NPOPULATION = 101
weight_decay_coef = 0.1


    

In [10]:

    

'''
models = []
for i in range(NPOPULATION):
  model = Net()
  if args.cuda:
    model.cuda()
  model.eval()
  models.append(model)
'''

model = Net()
if args.cuda:
  model.cuda()

orig_model = copy.deepcopy(model)


    

In [11]:

    

# get init params
orig_params = []
model_shapes = []
for param in orig_model.parameters():
  p = param.data.cpu().numpy()
  model_shapes.append(p.shape)
  orig_params.append(p.flatten())
orig_params_flat = np.concatenate(orig_params)
NPARAMS = len(orig_params_flat)
print(NPARAMS)


    

    




11274

In [12]:

    

def update_model(flat_param, model, model_shapes):
  idx = 0
  i = 0
  for param in model.parameters():
    delta = np.product(model_shapes[i])
    block = flat_param[idx:idx+delta]
    block = np.reshape(block, model_shapes[i])
    i += 1
    idx += delta
    block_data = torch.from_numpy(block).float()
    if args.cuda:
      block_data = block_data.cuda()
    param.data = block_data


    

In [13]:

    

def evaluate(model, test_loader, print_mode=True, return_loss=False):
  model.eval()
  test_loss = 0
  correct = 0
  for data, target in test_loader:
    if args.cuda:
      data, target = data.cuda(), target.cuda()
    data, target = Variable(data, volatile=True), Variable(target)
    output = model(data)
    test_loss += F.nll_loss(output, target, size_average=False).data[0] # sum up batch loss
    pred = output.data.max(1, keepdim=True)[1] # get the index of the max log-probability
    correct += pred.eq(target.data.view_as(pred)).cpu().sum()

  test_loss /= len(test_loader.dataset)
  acc = correct / len(test_loader.dataset)
  
  if print_mode:
    print('\nAverage loss: {:.4f}, Accuracy: {}/{} ({:.4f}%)\n'.format(
      test_loss, correct, len(test_loader.dataset),
      100. * acc))
  
  if return_loss:
    return test_loss
  return acc


    

In [17]:

    

"""
es = SimpleES(NPARAMS,
              popsize=NPOPULATION,
              sigma_init=0.01,
              sigma_decay=0.999,
              sigma_alpha=0.2,
              sigma_limit=0.001,
              elite_ratio=0.1,
              average_baseline=False,
              forget_best=True
             )
"""
es = OpenES(NPARAMS,
              popsize=NPOPULATION,
              sigma_init=0.01,
              sigma_decay=0.999,
              sigma_limit=0.01,
              forget_best=False,
              learning_rate=0.001,
              learning_rate_decay = 0.9999,
              learning_rate_limit = 0.0001,
             )


    

In [18]:

    

def worker(procnum, model, solution, data, target, send_end):
  update_model(solution, model, model_shapes)
  output = model(data)
  loss = F.nll_loss(output, target)
  reward = - loss.data[0]
  send_end.send(reward)

def batch_simulation(model_list, solutions, data, target, process_count):
  jobs = []
  pipe_list = []

  for i in range(process_count):
    recv_end, send_end = mp.Pipe(False)
    p = mp.Process(target=worker, args=(i, model_list[i], solutions[i], data, target, send_end))
    jobs.append(p)
    pipe_list.append(recv_end)

  for p in jobs:
    p.start()

  for p in jobs:
    p.join()

  result_list = [x.recv() for x in pipe_list]
  return np.array(result_list)


def batch_simulation_sequential(model_list, solutions, data, target, process_count):
  result_list = []
  for i in range(process_count):
    update_model(solutions[i], model_list[i], model_shapes)
    output = model_list[i](data)
    loss = F.nll_loss(output, target)
    reward = - loss.data[0]
    result_list.append(reward)
  return np.array(result_list)


    

In [19]:

    

#'''
best_valid_acc = 0
training_log = []
for epoch in range(1, 10*args.epochs + 1):

  # train loop
  model.eval()
  for batch_idx, (data, target) in enumerate(train_loader):
    if args.cuda:
      data, target = data.cuda(), target.cuda()
    data, target = Variable(data), Variable(target)
    
    solutions = es.ask()
    reward = np.zeros(es.popsize)
    
    for i in range(es.popsize):
      update_model(solutions[i], model, model_shapes)
      output = model(data)
      loss = F.nll_loss(output, target)
      reward[i] = - loss.data[0]

    best_raw_reward = reward.max()
    #reward = compute_centered_ranks(reward)
    l2_decay = compute_weight_decay(weight_decay_coef, solutions)
    reward += l2_decay

    es.tell(reward)

    result = es.result()
    
    if (batch_idx % 5 == 0):
      print(epoch, batch_idx, best_raw_reward, result[0].mean(), result[3])

  curr_solution = es.current_param()
  update_model(curr_solution, model, model_shapes)

  valid_acc = evaluate(model, valid_loader, print_mode=False)
  training_log.append([epoch, valid_acc])
  print('valid_acc', valid_acc * 100.)
  if valid_acc >= best_valid_acc:
    best_valid_acc = valid_acc
    best_model = copy.deepcopy(model)
    print('best valid_acc', best_valid_acc * 100.)
#'''


    

    




1 0 -2.30193543434 -7.93079584148e-05 0.01
1 5 -2.25925588608 0.000434028402925 0.01
1 10 -1.88105452061 0.000863433082393 0.01
1 15 -1.42825007439 0.00091040908483 0.01
1 20 -1.19715201855 0.000916270582721 0.01
1 25 -1.08275806904 0.000974892798043 0.01
1 30 -0.983183026314 0.00104386101784 0.01
1 35 -0.919698655605 0.000678370184286 0.01
1 40 -0.844817101955 0.000926555426733 0.01
1 45 -0.817394971848 0.000922090877786 0.01
1 50 -0.814984381199 0.00116070012036 0.01
1 55 -0.805679738522 0.00116070012036 0.01
valid_acc 74.995
best valid_acc 74.995
2 0 -0.84048551321 0.00116070012036 0.01
2 5 -0.790781915188 0.00128451260662 0.01
2 10 -0.77977091074 0.00128451260662 0.01
2 15 -0.741036474705 0.00128451260662 0.01
2 20 -0.7792776227 0.00123299907838 0.01
2 25 -0.75918161869 0.00123299907838 0.01
2 30 -0.747699975967 0.00123299907838 0.01
2 35 -0.720850110054 0.00123299907838 0.01
2 40 -0.724429726601 0.00123299907838 0.01
2 45 -0.742388427258 0.00123299907838 0.01
2 50 -0.724133014679 7.19565741462e-05 0.01
2 55 -0.652908325195 3.64853758096e-05 0.01
valid_acc 77.13166666666666
best valid_acc 77.13166666666666
3 0 -0.645577549934 1.33878905309e-05 0.01
3 5 -0.682914495468 1.33878905309e-05 0.01
3 10 -0.648366212845 1.33878905309e-05 0.01
3 15 -0.638106167316 0.000125426673433 0.01
3 20 -0.540650069714 -9.21696463994e-05 0.01
3 25 -0.556898653507 -9.21696463994e-05 0.01
3 30 -0.638110458851 -9.21696463994e-05 0.01
3 35 -0.713058412075 -9.21696463994e-05 0.01
3 40 -0.622235655785 -9.21696463994e-05 0.01
3 45 -0.675054490566 -9.21696463994e-05 0.01
3 50 -0.584510922432 -9.21696463994e-05 0.01
3 55 -0.576616287231 -0.000112087453943 0.01
valid_acc 82.30499999999999
best valid_acc 82.30499999999999
4 0 -0.600017428398 -0.000112087453943 0.01
4 5 -0.619903504848 -0.000112087453943 0.01
4 10 -0.605637669563 -0.000112087453943 0.01
4 15 -0.557456731796 -0.000112087453943 0.01
4 20 -0.603248476982 -0.000112087453943 0.01
4 25 -0.516546428204 -0.000130976206558 0.01
4 30 -0.662497699261 -0.000419869767099 0.01
4 35 -0.497017562389 -0.000537615356387 0.01
4 40 -0.48434561491 -0.000537615356387 0.01
4 45 -0.572362482548 -0.000537615356387 0.01
4 50 -0.484995305538 -0.000537615356387 0.01
4 55 -0.402304798365 2.71777749911e-05 0.01
valid_acc 85.425
best valid_acc 85.425
5 0 -0.512217462063 2.71777749911e-05 0.01
5 5 -0.47760027647 0.000290281907917 0.01
5 10 -0.469509631395 0.000290281907917 0.01
5 15 -0.430136412382 0.000290281907917 0.01
5 20 -0.506188929081 -0.000288672359689 0.01
5 25 -0.466771543026 -0.000288672359689 0.01
5 30 -0.468196004629 -0.000288672359689 0.01
5 35 -0.437986165285 -0.000288672359689 0.01
5 40 -0.438537508249 -0.000288672359689 0.01
5 45 -0.387450665236 -0.000288672359689 0.01
5 50 -0.397666871548 -0.000288672359689 0.01
5 55 -0.439944893122 -0.000288672359689 0.01
valid_acc 86.67833333333334
best valid_acc 86.67833333333334
6 0 -0.347905814648 -0.00149817072964 0.01
6 5 -0.447554171085 -0.00149817072964 0.01
6 10 -0.402372598648 -0.00149817072964 0.01
6 15 -0.409267932177 -0.00149817072964 0.01
6 20 -0.4146451056 -0.00149817072964 0.01
6 25 -0.4839220047 -0.00149817072964 0.01
6 30 -0.454222351313 -0.000433241448375 0.01
6 35 -0.387279421091 -0.000433241448375 0.01
6 40 -0.334012746811 -0.000433241448375 0.01
6 45 -0.365834981203 -0.000433241448375 0.01
6 50 -0.404047071934 -0.000433241448375 0.01
6 55 -0.400403231382 -0.000433241448375 0.01
valid_acc 86.65166666666667
7 0 -0.363019198179 -0.000433241448375 0.01
7 5 -0.414384096861 -0.000433241448375 0.01
7 10 -0.379683673382 -0.000433241448375 0.01
7 15 -0.393472790718 -0.000433241448375 0.01
7 20 -0.4494561553 -0.000433241448375 0.01
7 25 -0.392005860806 -0.000433241448375 0.01
7 30 -0.335558623075 -0.000433241448375 0.01
7 35 -0.371694803238 -0.000433241448375 0.01
7 40 -0.416715025902 -0.000433241448375 0.01
7 45 -0.314037531614 -0.00198473241621 0.01
7 50 -0.318436920643 -0.00198473241621 0.01
7 55 -0.394181460142 -0.00198473241621 0.01
valid_acc 89.13333333333333
best valid_acc 89.13333333333333
8 0 -0.331167161465 -0.00198473241621 0.01
8 5 -0.384443312883 -0.00198473241621 0.01
8 10 -0.372689723969 -0.00259837116625 0.01
8 15 -0.373687326908 -0.00259837116625 0.01
8 20 -0.281910330057 -0.00291375822061 0.01
8 25 -0.323569297791 -0.00291375822061 0.01
8 30 -0.368499070406 -0.00291375822061 0.01
8 35 -0.337300509214 -0.00291375822061 0.01
8 40 -0.350602418184 -0.00291375822061 0.01
8 45 -0.389239996672 -0.00297230081081 0.01
8 50 -0.374930620193 -0.00297230081081 0.01
8 55 -0.296674877405 -0.00297230081081 0.01
valid_acc 89.74166666666666
best valid_acc 89.74166666666666
9 0 -0.320743650198 -0.00297230081081 0.01
9 5 -0.323158413172 -0.00297230081081 0.01
9 10 -0.336762040854 -0.00297230081081 0.01
9 15 -0.301319152117 -0.00297230081081 0.01
9 20 -0.282345205545 -0.00297230081081 0.01
9 25 -0.355873435736 -0.00297230081081 0.01
9 30 -0.357389628887 -0.00297230081081 0.01
9 35 -0.339281797409 -0.00297230081081 0.01
9 40 -0.308460146189 -0.00297230081081 0.01
9 45 -0.327920734882 -0.00355290293571 0.01
9 50 -0.308028161526 -0.00359936536822 0.01
9 55 -0.325912952423 -0.00359936536822 0.01
valid_acc 91.23166666666667
best valid_acc 91.23166666666667
10 0 -0.301850050688 -0.00359936536822 0.01
10 5 -0.319415986538 -0.00359936536822 0.01
10 10 -0.268859952688 -0.00359936536822 0.01
10 15 -0.26133787632 -0.00359936536822 0.01
10 20 -0.297950655222 -0.00359936536822 0.01
10 25 -0.307303011417 -0.00359936536822 0.01
10 30 -0.270721167326 -0.00266184739491 0.01
10 35 -0.265403568745 -0.00266184739491 0.01
10 40 -0.234723746777 -0.00266184739491 0.01
10 45 -0.238956734538 -0.00266184739491 0.01
10 50 -0.226362392306 -0.00285833689813 0.01
10 55 -0.216390743852 -0.00282641573113 0.01
valid_acc 92.28333333333333
best valid_acc 92.28333333333333
11 0 -0.313869148493 -0.00282641573113 0.01
11 5 -0.298807680607 -0.0022941715027 0.01
11 10 -0.261306345463 -0.0022941715027 0.01
11 15 -0.266971409321 -0.0022941715027 0.01
11 20 -0.281724721193 -0.0022941715027 0.01
11 25 -0.265448004007 -0.0022941715027 0.01
11 30 -0.235448226333 -0.0022941715027 0.01
11 35 -0.286105573177 -0.0022941715027 0.01
11 40 -0.341850072145 -0.0022941715027 0.01
11 45 -0.290374726057 -0.0022941715027 0.01
11 50 -0.237797632813 -0.0022941715027 0.01
11 55 -0.284512996674 -0.0022941715027 0.01
valid_acc 92.49333333333334
best valid_acc 92.49333333333334
12 0 -0.254266709089 -0.0022941715027 0.01
12 5 -0.284009665251 -0.0022941715027 0.01
12 10 -0.264256238937 -0.0022941715027 0.01
12 15 -0.244095250964 -0.0022941715027 0.01
12 20 -0.241942957044 -0.0022941715027 0.01
12 25 -0.259648025036 -0.0022941715027 0.01
12 30 -0.268098890781 -0.0022941715027 0.01
12 35 -0.271785199642 -0.0022941715027 0.01
12 40 -0.226829901338 -0.0022941715027 0.01
12 45 -0.269428253174 -0.0022941715027 0.01
12 50 -0.283169299364 -0.0022941715027 0.01
12 55 -0.263792365789 -0.0022941715027 0.01
valid_acc 92.30166666666668
13 0 -0.260377705097 -0.0022941715027 0.01
13 5 -0.230912268162 -0.0022941715027 0.01
13 10 -0.277780115604 -0.0022941715027 0.01
13 15 -0.252786666155 -0.0022941715027 0.01
13 20 -0.321997731924 -0.0022941715027 0.01
13 25 -0.224732428789 -0.0022941715027 0.01
13 30 -0.245754793286 -0.0022941715027 0.01
13 35 -0.249502882361 -0.0022941715027 0.01
13 40 -0.287863254547 -0.0022941715027 0.01
13 45 -0.256801664829 -0.0022941715027 0.01
13 50 -0.231633469462 -0.0022941715027 0.01
13 55 -0.281965464354 -0.0022941715027 0.01
valid_acc 92.78166666666667
best valid_acc 92.78166666666667
14 0 -0.28423923254 -0.0022941715027 0.01
14 5 -0.29552334547 -0.0022941715027 0.01
14 10 -0.215178668499 -0.0022941715027 0.01
14 15 -0.22211818397 -0.0022941715027 0.01
14 20 -0.27687934041 -0.0022941715027 0.01
14 25 -0.289502352476 -0.0022941715027 0.01
14 30 -0.224296152592 -0.0022941715027 0.01
14 35 -0.284197866917 -0.0022941715027 0.01
14 40 -0.218760222197 -0.0022941715027 0.01
14 45 -0.23111987114 -0.0022941715027 0.01
14 50 -0.245130345225 -0.0022941715027 0.01
14 55 -0.274078726768 -0.0022941715027 0.01
valid_acc 92.27166666666666
15 0 -0.23385155201 -0.0022941715027 0.01
15 5 -0.311232149601 -0.0022941715027 0.01
15 10 -0.371193230152 -0.0022941715027 0.01
15 15 -0.278257846832 -0.0022941715027 0.01
15 20 -0.199897810817 -0.0022941715027 0.01
15 25 -0.324608832598 -0.0022941715027 0.01
15 30 -0.264069467783 -0.0022941715027 0.01
15 35 -0.313965886831 -0.0022941715027 0.01
15 40 -0.222511783242 -0.0022941715027 0.01
15 45 -0.281480938196 -0.0022941715027 0.01
15 50 -0.315714657307 -0.0022941715027 0.01
15 55 -0.33135831356 -0.0022941715027 0.01
valid_acc 92.34166666666667
16 0 -0.258548766375 -0.0022941715027 0.01
16 5 -0.259231090546 -0.0022941715027 0.01
16 10 -0.268146544695 -0.0022941715027 0.01
16 15 -0.256642192602 -0.0022941715027 0.01
16 20 -0.262843906879 -0.0022941715027 0.01
16 25 -0.364241272211 -0.0022941715027 0.01
16 30 -0.286819070578 -0.0022941715027 0.01
16 35 -0.245955079794 -0.0022941715027 0.01
16 40 -0.269758284092 -0.0022941715027 0.01
16 45 -0.1967754215 -0.0022941715027 0.01
16 50 -0.267617791891 -0.0022941715027 0.01
16 55 -0.26230725646 -0.0022941715027 0.01
valid_acc 92.84
best valid_acc 92.84
17 0 -0.241725966334 -0.0022941715027 0.01
17 5 -0.240905642509 -0.0022941715027 0.01
17 10 -0.249499067664 -0.0022941715027 0.01
17 15 -0.308109819889 -0.0022941715027 0.01
17 20 -0.235664531589 -0.0022941715027 0.01
17 25 -0.207402959466 -0.0022941715027 0.01
17 30 -0.241470128298 -0.0022941715027 0.01
17 35 -0.210576459765 -0.0022941715027 0.01
17 40 -0.222584888339 -0.0022941715027 0.01
17 45 -0.27104011178 -0.0022941715027 0.01
17 50 -0.319921702147 -0.0022941715027 0.01
17 55 -0.269449830055 -0.0022941715027 0.01
valid_acc 92.55
18 0 -0.272245615721 -0.0022941715027 0.01
18 5 -0.281690061092 -0.0022941715027 0.01
18 10 -0.24408185482 -0.0022941715027 0.01
18 15 -0.24980981648 -0.0022941715027 0.01
18 20 -0.377986341715 -0.0022941715027 0.01
18 25 -0.301782935858 -0.0022941715027 0.01
18 30 -0.264545053244 -0.0022941715027 0.01
18 35 -0.194775626063 -0.0022941715027 0.01
18 40 -0.211070939898 -0.0022941715027 0.01
18 45 -0.259994655848 -0.0022941715027 0.01
18 50 -0.338242352009 -0.0022941715027 0.01
18 55 -0.26580363512 -0.0022941715027 0.01
valid_acc 91.99833333333333
19 0 -0.259029626846 -0.0022941715027 0.01
19 5 -0.278894722462 -0.0022941715027 0.01
19 10 -0.290745049715 -0.0022941715027 0.01
19 15 -0.33228456974 -0.0022941715027 0.01
19 20 -0.26794847846 -0.0022941715027 0.01
19 25 -0.238254994154 -0.0022941715027 0.01
19 30 -0.27880820632 -0.0022941715027 0.01
19 35 -0.256795316935 -0.0022941715027 0.01
19 40 -0.243089959025 -0.0022941715027 0.01
19 45 -0.347380131483 -0.0022941715027 0.01
19 50 -0.246182665229 -0.0022941715027 0.01
19 55 -0.231964483857 -0.0022941715027 0.01
valid_acc 92.88499999999999
best valid_acc 92.88499999999999
20 0 -0.243847668171 -0.0022941715027 0.01
20 5 -0.256343364716 -0.0022941715027 0.01
20 10 -0.210675522685 -0.00646955853082 0.01
20 15 -0.220914170146 -0.00646955853082 0.01
20 20 -0.331695795059 -0.00646955853082 0.01
20 25 -0.276671171188 -0.00646955853082 0.01
20 30 -0.272107094526 -0.00646955853082 0.01
20 35 -0.266016274691 -0.00646955853082 0.01
20 40 -0.252979457378 -0.00646955853082 0.01
20 45 -0.272445261478 -0.00646955853082 0.01
20 50 -0.291259855032 -0.00646955853082 0.01
20 55 -0.28097397089 -0.00646955853082 0.01
valid_acc 92.40166666666667
21 0 -0.337855964899 -0.00646955853082 0.01
21 5 -0.259269118309 -0.00646955853082 0.01
21 10 -0.253184318542 -0.00646955853082 0.01
21 15 -0.333418548107 -0.00646955853082 0.01
21 20 -0.352524787188 -0.00646955853082 0.01
21 25 -0.3200301826 -0.00646955853082 0.01
21 30 -0.358736276627 -0.00646955853082 0.01
21 35 -0.306808680296 -0.00646955853082 0.01
21 40 -0.238249644637 -0.00646955853082 0.01
21 45 -0.313325077295 -0.00646955853082 0.01
21 50 -0.277013838291 -0.00646955853082 0.01
21 55 -0.373858720064 -0.00646955853082 0.01
valid_acc 92.50500000000001
22 0 -0.34588894248 -0.00646955853082 0.01
22 5 -0.306712657213 -0.00646955853082 0.01
22 10 -0.374027222395 -0.00646955853082 0.01
22 15 -0.243283852935 -0.00646955853082 0.01
22 20 -0.351316154003 -0.00646955853082 0.01
22 25 -0.312815487385 -0.00646955853082 0.01
22 30 -0.257086277008 -0.00646955853082 0.01
22 35 -0.293620496988 -0.00646955853082 0.01
22 40 -0.266778796911 -0.00646955853082 0.01
22 45 -0.322683721781 -0.00646955853082 0.01
22 50 -0.292902797461 -0.00646955853082 0.01
22 55 -0.29496756196 -0.00646955853082 0.01
valid_acc 91.86166666666666
23 0 -0.313611507416 -0.00646955853082 0.01
23 5 -0.289548426867 -0.00646955853082 0.01
23 10 -0.318103611469 -0.00646955853082 0.01
23 15 -0.358381181955 -0.00646955853082 0.01
23 20 -0.361159414053 -0.00646955853082 0.01
23 25 -0.359393268824 -0.00646955853082 0.01
23 30 -0.325499504805 -0.00646955853082 0.01
23 35 -0.350318998098 -0.00646955853082 0.01
23 40 -0.268177181482 -0.00646955853082 0.01
23 45 -0.223084554076 -0.00646955853082 0.01
23 50 -0.279154896736 -0.00646955853082 0.01
23 55 -0.334509938955 -0.00646955853082 0.01
valid_acc 91.69500000000001
24 0 -0.348437339067 -0.00646955853082 0.01
24 5 -0.281885534525 -0.00646955853082 0.01
24 10 -0.373138129711 -0.00646955853082 0.01
24 15 -0.250396281481 -0.00646955853082 0.01
24 20 -0.32609462738 -0.00646955853082 0.01
24 25 -0.314447432756 -0.00646955853082 0.01
24 30 -0.259373545647 -0.00646955853082 0.01
24 35 -0.354353249073 -0.00646955853082 0.01
24 40 -0.27064883709 -0.00646955853082 0.01
24 45 -0.287314593792 -0.00646955853082 0.01
24 50 -0.310373872519 -0.00646955853082 0.01
24 55 -0.281692802906 -0.00646955853082 0.01
valid_acc 93.01166666666667
best valid_acc 93.01166666666667
25 0 -0.262515187263 -0.00646955853082 0.01
25 5 -0.264885604382 -0.00646955853082 0.01
25 10 -0.240871205926 -0.00646955853082 0.01
25 15 -0.287451207638 -0.00646955853082 0.01
25 20 -0.294904470444 -0.00646955853082 0.01
25 25 -0.336195260286 -0.00646955853082 0.01
25 30 -0.20691549778 -0.00646955853082 0.01
25 35 -0.295392721891 -0.00646955853082 0.01
25 40 -0.34388962388 -0.00897767808967 0.01
25 45 -0.286045074463 -0.00897767808967 0.01
25 50 -0.264104753733 -0.00897767808967 0.01
25 55 -0.216923370957 -0.00897767808967 0.01
valid_acc 92.605
26 0 -0.240363284945 -0.00897767808967 0.01
26 5 -0.237569898367 -0.00897767808967 0.01
26 10 -0.302456855774 -0.00897767808967 0.01
26 15 -0.236826062202 -0.00897767808967 0.01
26 20 -0.359879255295 -0.00897767808967 0.01
26 25 -0.378898859024 -0.00897767808967 0.01
26 30 -0.204447448254 -0.00897767808967 0.01
26 35 -0.277831971645 -0.00897767808967 0.01
26 40 -0.264741748571 -0.00897767808967 0.01
26 45 -0.275427252054 -0.00897767808967 0.01
26 50 -0.241950616241 -0.00897767808967 0.01
26 55 -0.245408460498 -0.00897767808967 0.01
valid_acc 92.78
27 0 -0.278283059597 -0.00897767808967 0.01
27 5 -0.26178047061 -0.00897767808967 0.01
27 10 -0.265624493361 -0.00897767808967 0.01
27 15 -0.273095071316 -0.00897767808967 0.01
27 20 -0.236820444465 -0.00897767808967 0.01
27 25 -0.274168550968 -0.00897767808967 0.01
27 30 -0.240302681923 -0.00897767808967 0.01
27 35 -0.282099038363 -0.00897767808967 0.01
27 40 -0.258236914873 -0.00897767808967 0.01
27 45 -0.237711504102 -0.00897767808967 0.01
27 50 -0.270048737526 -0.00897767808967 0.01
27 55 -0.278987854719 -0.00897767808967 0.01
valid_acc 92.19500000000001
28 0 -0.239867478609 -0.00897767808967 0.01
28 5 -0.332489609718 -0.00897767808967 0.01
28 10 -0.285259604454 -0.00897767808967 0.01
28 15 -0.260457366705 -0.00897767808967 0.01
28 20 -0.253965944052 -0.00897767808967 0.01
28 25 -0.2742369771 -0.00897767808967 0.01
28 30 -0.289694070816 -0.00897767808967 0.01
28 35 -0.218122631311 -0.00897767808967 0.01
28 40 -0.217210680246 -0.00897767808967 0.01
28 45 -0.252503275871 -0.00897767808967 0.01
28 50 -0.260378628969 -0.00897767808967 0.01
28 55 -0.282303988934 -0.00897767808967 0.01
valid_acc 92.40333333333334
29 0 -0.276273220778 -0.00897767808967 0.01
29 5 -0.294383555651 -0.00897767808967 0.01
29 10 -0.279206037521 -0.00897767808967 0.01
29 15 -0.325763523579 -0.00897767808967 0.01
29 20 -0.250636160374 -0.00897767808967 0.01
29 25 -0.257741063833 -0.00897767808967 0.01
29 30 -0.255716532469 -0.00897767808967 0.01
29 35 -0.259692937136 -0.00897767808967 0.01
29 40 -0.324911773205 -0.00897767808967 0.01
29 45 -0.253988355398 -0.00897767808967 0.01
29 50 -0.245892882347 -0.00897767808967 0.01
29 55 -0.307585507631 -0.00897767808967 0.01
valid_acc 92.21000000000001
30 0 -0.328957676888 -0.00897767808967 0.01
30 5 -0.333094775677 -0.00897767808967 0.01
30 10 -0.379304200411 -0.00897767808967 0.01
30 15 -0.317972660065 -0.00897767808967 0.01
30 20 -0.343192368746 -0.00897767808967 0.01
30 25 -0.230095252395 -0.00897767808967 0.01
30 30 -0.309866577387 -0.00897767808967 0.01
30 35 -0.324126899242 -0.00897767808967 0.01
30 40 -0.301585644484 -0.00897767808967 0.01
30 45 -0.270292252302 -0.00897767808967 0.01
30 50 -0.268347501755 -0.00897767808967 0.01
30 55 -0.240454316139 -0.00897767808967 0.01
valid_acc 92.485
31 0 -0.250479251146 -0.00897767808967 0.01
31 5 -0.320560693741 -0.00897767808967 0.01
31 10 -0.244169145823 -0.00897767808967 0.01
31 15 -0.26286098361 -0.00897767808967 0.01
31 20 -0.348679602146 -0.00897767808967 0.01
31 25 -0.265049010515 -0.00897767808967 0.01
31 30 -0.223200544715 -0.00897767808967 0.01
31 35 -0.273916572332 -0.00897767808967 0.01
31 40 -0.260780215263 -0.00897767808967 0.01
31 45 -0.272160857916 -0.00897767808967 0.01
31 50 -0.322493821383 -0.00897767808967 0.01
31 55 -0.340292155743 -0.00897767808967 0.01
valid_acc 92.85166666666666
32 0 -0.215709075332 -0.00897767808967 0.01
32 5 -0.340540319681 -0.00897767808967 0.01
32 10 -0.213605985045 -0.00897767808967 0.01
32 15 -0.234077826142 -0.00897767808967 0.01
32 20 -0.286568254232 -0.00897767808967 0.01
32 25 -0.240438342094 -0.00897767808967 0.01
32 30 -0.290169298649 -0.00897767808967 0.01
32 35 -0.210936486721 -0.00897767808967 0.01
32 40 -0.215850248933 -0.00897767808967 0.01
32 45 -0.304372608662 -0.00897767808967 0.01
32 50 -0.177254930139 -0.00897767808967 0.01
32 55 -0.2741112113 -0.00897767808967 0.01
valid_acc 93.21833333333333
best valid_acc 93.21833333333333
33 0 -0.254667162895 -0.00897767808967 0.01
33 5 -0.247587576509 -0.00897767808967 0.01
33 10 -0.311659038067 -0.00897767808967 0.01
33 15 -0.221598669887 -0.00897767808967 0.01
33 20 -0.196711197495 -0.00897767808967 0.01
33 25 -0.29219853878 -0.00897767808967 0.01
33 30 -0.266324788332 -0.00897767808967 0.01
33 35 -0.251662433147 -0.00897767808967 0.01
33 40 -0.306144028902 -0.0101079540968 0.01
33 45 -0.231359347701 -0.0101079540968 0.01
33 50 -0.241322830319 -0.0101079540968 0.01
33 55 -0.273514539003 -0.0101079540968 0.01
valid_acc 93.435
best valid_acc 93.435
34 0 -0.22014093399 -0.0101079540968 0.01
34 5 -0.20361071825 -0.0101079540968 0.01
34 10 -0.212939798832 -0.0101079540968 0.01
34 15 -0.264475941658 -0.0101079540968 0.01
34 20 -0.265121400356 -0.0101079540968 0.01
34 25 -0.261806815863 -0.0101079540968 0.01
34 30 -0.190179809928 -0.0101079540968 0.01
34 35 -0.258081793785 -0.0101079540968 0.01
34 40 -0.28442838788 -0.0101079540968 0.01
34 45 -0.221319839358 -0.0101079540968 0.01
34 50 -0.274279415607 -0.0101079540968 0.01
34 55 -0.320941179991 -0.0101079540968 0.01
valid_acc 93.80333333333334
best valid_acc 93.80333333333334
35 0 -0.241515278816 -0.0101079540968 0.01
35 5 -0.210339576006 -0.0101079540968 0.01
35 10 -0.281058937311 -0.0101079540968 0.01
35 15 -0.215853765607 -0.0101079540968 0.01
35 20 -0.213444292545 -0.0101079540968 0.01
35 25 -0.189230933785 -0.0101079540968 0.01
35 30 -0.154166251421 -0.0108712821164 0.01
35 35 -0.245077505708 -0.0108712821164 0.01
35 40 -0.217256963253 -0.0108712821164 0.01
35 45 -0.275611847639 -0.0108712821164 0.01
35 50 -0.265886366367 -0.0108712821164 0.01
35 55 -0.278285264969 -0.0108712821164 0.01
valid_acc 93.29499999999999
36 0 -0.26457709074 -0.0108712821164 0.01
36 5 -0.296512573957 -0.0108712821164 0.01
36 10 -0.226633295417 -0.0108712821164 0.01
36 15 -0.243680819869 -0.0108712821164 0.01
36 20 -0.245948329568 -0.0108712821164 0.01
36 25 -0.245825961232 -0.0108712821164 0.01
36 30 -0.26313868165 -0.0108712821164 0.01
36 35 -0.263497620821 -0.0108712821164 0.01
36 40 -0.262411057949 -0.0108712821164 0.01
36 45 -0.198738947511 -0.0108712821164 0.01
36 50 -0.214952602983 -0.0108712821164 0.01
36 55 -0.210648089647 -0.0108712821164 0.01
valid_acc 93.145
37 0 -0.246004521847 -0.0108712821164 0.01
37 5 -0.293535590172 -0.0108712821164 0.01
37 10 -0.209060117602 -0.0108712821164 0.01
37 15 -0.253929674625 -0.0108712821164 0.01
37 20 -0.271325916052 -0.0108712821164 0.01
37 25 -0.239317551255 -0.0108712821164 0.01
37 30 -0.221396028996 -0.0108712821164 0.01
37 35 -0.237317889929 -0.0108712821164 0.01
37 40 -0.295450091362 -0.0108712821164 0.01
37 45 -0.291258215904 -0.0108712821164 0.01
37 50 -0.259179234505 -0.0108712821164 0.01
37 55 -0.320994824171 -0.0108712821164 0.01
valid_acc 93.20333333333333
38 0 -0.247337982059 -0.0108712821164 0.01
38 5 -0.232012540102 -0.0108712821164 0.01
38 10 -0.276096940041 -0.0108712821164 0.01
38 15 -0.276304602623 -0.0108712821164 0.01
38 20 -0.265521287918 -0.0108712821164 0.01
38 25 -0.318916261196 -0.0108712821164 0.01
38 30 -0.261445075274 -0.0108712821164 0.01
38 35 -0.281294792891 -0.0108712821164 0.01
38 40 -0.209817349911 -0.0108712821164 0.01
38 45 -0.230381458998 -0.0108712821164 0.01
38 50 -0.244341954589 -0.0108712821164 0.01
38 55 -0.29643753171 -0.0108712821164 0.01
valid_acc 93.02666666666667
39 0 -0.21520999074 -0.0108712821164 0.01
39 5 -0.297061413527 -0.0108712821164 0.01
39 10 -0.200067937374 -0.0108712821164 0.01
39 15 -0.161522433162 -0.0108712821164 0.01
39 20 -0.25264069438 -0.0108712821164 0.01
39 25 -0.301167935133 -0.0108712821164 0.01
39 30 -0.2318816185 -0.0108712821164 0.01
39 35 -0.243556678295 -0.0108712821164 0.01
39 40 -0.186285093427 -0.0108712821164 0.01
39 45 -0.282643228769 -0.0108712821164 0.01
39 50 -0.242231115699 -0.0108712821164 0.01
39 55 -0.300510287285 -0.0108712821164 0.01
valid_acc 93.08833333333332
40 0 -0.243024587631 -0.0108712821164 0.01
40 5 -0.286292910576 -0.0108712821164 0.01
40 10 -0.268455147743 -0.0108712821164 0.01
40 15 -0.291811138391 -0.0108712821164 0.01
40 20 -0.230621680617 -0.0108712821164 0.01
40 25 -0.223326951265 -0.0108712821164 0.01
40 30 -0.230860725045 -0.0108712821164 0.01
40 35 -0.222735106945 -0.0108712821164 0.01
40 40 -0.283099979162 -0.0108712821164 0.01
40 45 -0.23475907743 -0.0108712821164 0.01
40 50 -0.287657111883 -0.0108712821164 0.01
40 55 -0.228830114007 -0.0108712821164 0.01
valid_acc 92.955
41 0 -0.222592517734 -0.0108712821164 0.01
41 5 -0.275684177876 -0.0108712821164 0.01
41 10 -0.25818502903 -0.0108712821164 0.01
41 15 -0.25929042697 -0.0108712821164 0.01
41 20 -0.221944838762 -0.0108712821164 0.01
41 25 -0.303266763687 -0.0108712821164 0.01
41 30 -0.246411144733 -0.0108712821164 0.01
41 35 -0.276887595654 -0.0108712821164 0.01
41 40 -0.260723799467 -0.0108712821164 0.01
41 45 -0.220482781529 -0.0108712821164 0.01
41 50 -0.233977496624 -0.0108712821164 0.01
41 55 -0.218927368522 -0.0108712821164 0.01
valid_acc 93.02833333333334
42 0 -0.203744381666 -0.0108712821164 0.01
42 5 -0.251389652491 -0.0108712821164 0.01
42 10 -0.242253690958 -0.0108712821164 0.01
42 15 -0.225350990891 -0.0108712821164 0.01
42 20 -0.235027745366 -0.0108712821164 0.01
42 25 -0.247192084789 -0.0108712821164 0.01
42 30 -0.324866682291 -0.0108712821164 0.01
42 35 -0.286709785461 -0.0108712821164 0.01
42 40 -0.190378203988 -0.0108712821164 0.01
42 45 -0.221857964993 -0.0108712821164 0.01
42 50 -0.234659343958 -0.0108712821164 0.01
42 55 -0.282563000917 -0.0108712821164 0.01
valid_acc 92.96166666666666
43 0 -0.171162053943 -0.0108712821164 0.01
43 5 -0.215872317553 -0.0108712821164 0.01
43 10 -0.195874840021 -0.0108712821164 0.01
43 15 -0.253151357174 -0.0108712821164 0.01
43 20 -0.263454049826 -0.0108712821164 0.01
43 25 -0.331230849028 -0.0108712821164 0.01
43 30 -0.265444278717 -0.0108712821164 0.01
43 35 -0.229527890682 -0.0108712821164 0.01
43 40 -0.241208791733 -0.0108712821164 0.01
43 45 -0.305278509855 -0.0108712821164 0.01
43 50 -0.219419077039 -0.0108712821164 0.01
43 55 -0.297164440155 -0.0108712821164 0.01
valid_acc 93.24333333333334
44 0 -0.223572403193 -0.0108712821164 0.01
44 5 -0.342235028744 -0.0108712821164 0.01
44 10 -0.307025462389 -0.0108712821164 0.01
44 15 -0.259135305882 -0.0108712821164 0.01
44 20 -0.246743500233 -0.0108712821164 0.01
44 25 -0.251608341932 -0.0108712821164 0.01
44 30 -0.27457678318 -0.0108712821164 0.01
44 35 -0.24832201004 -0.0108712821164 0.01
44 40 -0.257895290852 -0.0108712821164 0.01
44 45 -0.228023424745 -0.0108712821164 0.01
44 50 -0.313565999269 -0.0108712821164 0.01
44 55 -0.240123018622 -0.0108712821164 0.01
valid_acc 93.30166666666668
45 0 -0.237836867571 -0.0108712821164 0.01
45 5 -0.266578286886 -0.0108712821164 0.01
45 10 -0.215850368142 -0.0108712821164 0.01
45 15 -0.220849618316 -0.0108712821164 0.01
45 20 -0.297386527061 -0.0108712821164 0.01
45 25 -0.2593331635 -0.0108712821164 0.01
45 30 -0.251933515072 -0.0108712821164 0.01
45 35 -0.235688343644 -0.0108712821164 0.01
45 40 -0.260635703802 -0.0108712821164 0.01
45 45 -0.294754296541 -0.0108712821164 0.01
45 50 -0.220173612237 -0.0108712821164 0.01
45 55 -0.284907609224 -0.0108712821164 0.01
valid_acc 93.48333333333333
46 0 -0.209788009524 -0.0108712821164 0.01
46 5 -0.204026699066 -0.0108712821164 0.01
46 10 -0.244791358709 -0.0108712821164 0.01
46 15 -0.218293875456 -0.0108712821164 0.01
46 20 -0.206164821982 -0.0108712821164 0.01
46 25 -0.187757894397 -0.0108712821164 0.01
46 30 -0.231589093804 -0.0108712821164 0.01
46 35 -0.278361439705 -0.0108712821164 0.01
46 40 -0.205553501844 -0.0108712821164 0.01
46 45 -0.231915980577 -0.0108712821164 0.01
46 50 -0.247552677989 -0.0108712821164 0.01
46 55 -0.29002431035 -0.0108712821164 0.01
valid_acc 93.26833333333333
47 0 -0.217791825533 -0.0108712821164 0.01
47 5 -0.23755286634 -0.0108712821164 0.01
47 10 -0.244902014732 -0.0108712821164 0.01
47 15 -0.194895714521 -0.0108712821164 0.01
47 20 -0.201811105013 -0.0108712821164 0.01
47 25 -0.235870599747 -0.0108712821164 0.01
47 30 -0.342636495829 -0.0108712821164 0.01
47 35 -0.208685427904 -0.0108712821164 0.01
47 40 -0.263207405806 -0.0108712821164 0.01
47 45 -0.279778927565 -0.0108712821164 0.01
47 50 -0.256179869175 -0.0108712821164 0.01
47 55 -0.254377096891 -0.0108712821164 0.01
valid_acc 93.48166666666667
48 0 -0.261695057154 -0.0108712821164 0.01
48 5 -0.246737331152 -0.0108712821164 0.01
48 10 -0.256719082594 -0.0108712821164 0.01
48 15 -0.26835334301 -0.0108712821164 0.01
48 20 -0.259616017342 -0.0108712821164 0.01
48 25 -0.251873880625 -0.0108712821164 0.01
48 30 -0.291401565075 -0.0108712821164 0.01
48 35 -0.29457077384 -0.0108712821164 0.01
48 40 -0.226984232664 -0.0108712821164 0.01
48 45 -0.216092139482 -0.0108712821164 0.01
48 50 -0.33145481348 -0.0108712821164 0.01
48 55 -0.235783904791 -0.0108712821164 0.01
valid_acc 93.37666666666667
49 0 -0.228605642915 -0.0108712821164 0.01
49 5 -0.257621020079 -0.0108712821164 0.01
49 10 -0.311709851027 -0.0108712821164 0.01
49 15 -0.254695236683 -0.0108712821164 0.01
49 20 -0.231869205832 -0.0108712821164 0.01
49 25 -0.198228731751 -0.0108712821164 0.01
49 30 -0.289675593376 -0.0108712821164 0.01
49 35 -0.332781612873 -0.0108712821164 0.01
49 40 -0.268916070461 -0.0108712821164 0.01
49 45 -0.209447234869 -0.0108712821164 0.01
49 50 -0.249084174633 -0.0108712821164 0.01
49 55 -0.300188034773 -0.0108712821164 0.01
valid_acc 93.68166666666666
50 0 -0.269237309694 -0.0108712821164 0.01
50 5 -0.241656884551 -0.0108712821164 0.01
50 10 -0.25228664279 -0.0108712821164 0.01
50 15 -0.230397850275 -0.0108712821164 0.01
50 20 -0.258632600307 -0.0108712821164 0.01
50 25 -0.263186126947 -0.0108712821164 0.01
50 30 -0.230748668313 -0.0108712821164 0.01
50 35 -0.222083315253 -0.0108712821164 0.01
50 40 -0.293901145458 -0.0108712821164 0.01
50 45 -0.240151718259 -0.0108712821164 0.01
50 50 -0.240781262517 -0.0108712821164 0.01
50 55 -0.207753106952 -0.0108712821164 0.01
valid_acc 93.23
51 0 -0.247383400798 -0.0108712821164 0.01
51 5 -0.266742557287 -0.0108712821164 0.01
51 10 -0.305790811777 -0.0108712821164 0.01
51 15 -0.289938867092 -0.0108712821164 0.01
51 20 -0.246877655387 -0.0108712821164 0.01
51 25 -0.294174611568 -0.0108712821164 0.01
51 30 -0.229947715998 -0.0108712821164 0.01
51 35 -0.244348600507 -0.0108712821164 0.01
51 40 -0.244875699282 -0.0108712821164 0.01
51 45 -0.280371427536 -0.0108712821164 0.01
51 50 -0.209285825491 -0.0108712821164 0.01
51 55 -0.231297269464 -0.0108712821164 0.01
valid_acc 92.825
52 0 -0.185628727078 -0.0108712821164 0.01
52 5 -0.200615093112 -0.0108712821164 0.01
52 10 -0.201048329473 -0.0108712821164 0.01
52 15 -0.209661155939 -0.0108712821164 0.01
52 20 -0.258641272783 -0.0108712821164 0.01
52 25 -0.208574622869 -0.0108712821164 0.01
52 30 -0.34569516778 -0.0108712821164 0.01
52 35 -0.319407433271 -0.0108712821164 0.01
52 40 -0.224039778113 -0.0108712821164 0.01
52 45 -0.262784659863 -0.0108712821164 0.01
52 50 -0.193958744407 -0.0108712821164 0.01
52 55 -0.229384541512 -0.0108712821164 0.01
valid_acc 93.23833333333333
53 0 -0.269642204046 -0.0108712821164 0.01
53 5 -0.200149074197 -0.0108712821164 0.01
53 10 -0.337270021439 -0.0108712821164 0.01
53 15 -0.233747184277 -0.0108712821164 0.01
53 20 -0.288092583418 -0.0108712821164 0.01
53 25 -0.293623864651 -0.0108712821164 0.01
53 30 -0.246065914631 -0.0108712821164 0.01
53 35 -0.259731948376 -0.0108712821164 0.01
53 40 -0.222048610449 -0.0108712821164 0.01
53 45 -0.298618972301 -0.0108712821164 0.01
53 50 -0.243907809258 -0.0108712821164 0.01
53 55 -0.295146912336 -0.0108712821164 0.01
valid_acc 93.19333333333333
54 0 -0.219181925058 -0.0108712821164 0.01
54 5 -0.232773825526 -0.0108712821164 0.01
54 10 -0.238168731332 -0.0108712821164 0.01
54 15 -0.223259672523 -0.0108712821164 0.01
54 20 -0.299956023693 -0.0108712821164 0.01
54 25 -0.286667138338 -0.0108712821164 0.01
54 30 -0.221019744873 -0.0108712821164 0.01
54 35 -0.306877553463 -0.0108712821164 0.01
54 40 -0.218521043658 -0.0108712821164 0.01
54 45 -0.197185590863 -0.0108712821164 0.01
54 50 -0.220967158675 -0.0108712821164 0.01
54 55 -0.28874489665 -0.0108712821164 0.01
valid_acc 93.24833333333333
55 0 -0.315719693899 -0.0108712821164 0.01
55 5 -0.354472875595 -0.0108712821164 0.01
55 10 -0.213103041053 -0.0108712821164 0.01
55 15 -0.285176485777 -0.0108712821164 0.01
55 20 -0.237760484219 -0.0108712821164 0.01
55 25 -0.211199894547 -0.0108712821164 0.01
55 30 -0.26150599122 -0.0108712821164 0.01
55 35 -0.201729893684 -0.0108712821164 0.01
55 40 -0.245948255062 -0.0108712821164 0.01
55 45 -0.27153262496 -0.0108712821164 0.01
55 50 -0.177400618792 -0.0108712821164 0.01
55 55 -0.258743792772 -0.0108712821164 0.01
valid_acc 93.745
56 0 -0.262477010489 -0.0108712821164 0.01
56 5 -0.248216450214 -0.0108712821164 0.01
56 10 -0.257536560297 -0.0108712821164 0.01
56 15 -0.285544812679 -0.0108712821164 0.01
56 20 -0.231861934066 -0.0108712821164 0.01
56 25 -0.192188858986 -0.0108712821164 0.01
56 30 -0.253890275955 -0.0108712821164 0.01
56 35 -0.185814648867 -0.0108712821164 0.01
56 40 -0.294590443373 -0.0108712821164 0.01
56 45 -0.248899921775 -0.0108712821164 0.01
56 50 -0.244071707129 -0.0108712821164 0.01
56 55 -0.217879578471 -0.0108712821164 0.01
valid_acc 93.11500000000001
57 0 -0.255091637373 -0.0108712821164 0.01
57 5 -0.219110161066 -0.0108712821164 0.01
57 10 -0.22734156251 -0.0108712821164 0.01
57 15 -0.191066145897 -0.0108712821164 0.01
57 20 -0.301564186811 -0.0108712821164 0.01
57 25 -0.268797963858 -0.0108712821164 0.01
57 30 -0.249213129282 -0.0108712821164 0.01
57 35 -0.253856897354 -0.0108712821164 0.01
57 40 -0.211623802781 -0.0108712821164 0.01
57 45 -0.203581303358 -0.0108712821164 0.01
57 50 -0.234730228782 -0.0108712821164 0.01
57 55 -0.224772691727 -0.0108712821164 0.01
valid_acc 93.22833333333334
58 0 -0.24492841959 -0.0108712821164 0.01
58 5 -0.251979589462 -0.0108712821164 0.01
58 10 -0.227116420865 -0.0108712821164 0.01
58 15 -0.276175558567 -0.0108712821164 0.01
58 20 -0.242517083883 -0.0108712821164 0.01
58 25 -0.21151407063 -0.0108712821164 0.01
58 30 -0.191538929939 -0.0108712821164 0.01
58 35 -0.186708003283 -0.0108712821164 0.01
58 40 -0.226183757186 -0.0108712821164 0.01
58 45 -0.298890262842 -0.0108712821164 0.01
58 50 -0.197493478656 -0.0108712821164 0.01
58 55 -0.241375803947 -0.0108712821164 0.01
valid_acc 93.015
59 0 -0.201030179858 -0.0108712821164 0.01
59 5 -0.171826779842 -0.0108712821164 0.01
59 10 -0.259127855301 -0.0108712821164 0.01
59 15 -0.223295345902 -0.0108712821164 0.01
59 20 -0.198459222913 -0.0108712821164 0.01
59 25 -0.213397368789 -0.0108712821164 0.01
59 30 -0.22652952373 -0.0108712821164 0.01
59 35 -0.286773502827 -0.0108712821164 0.01
59 40 -0.237349167466 -0.0108712821164 0.01
59 45 -0.244044244289 -0.0108712821164 0.01
59 50 -0.301280230284 -0.0108712821164 0.01
59 55 -0.214439332485 -0.0108712821164 0.01
valid_acc 93.21333333333334
60 0 -0.163309052587 -0.0108712821164 0.01
60 5 -0.242734640837 -0.0108712821164 0.01
60 10 -0.220659732819 -0.0108712821164 0.01
60 15 -0.19724200666 -0.0108712821164 0.01
60 20 -0.240264981985 -0.0108712821164 0.01
60 25 -0.136334955692 -0.0191175899505 0.01
60 30 -0.274516046047 -0.0191175899505 0.01
60 35 -0.156088724732 -0.0191175899505 0.01
60 40 -0.261621922255 -0.0191175899505 0.01
60 45 -0.258485227823 -0.0191175899505 0.01
60 50 -0.188260540366 -0.0191175899505 0.01
60 55 -0.226174801588 -0.0191175899505 0.01
valid_acc 93.34
61 0 -0.249201193452 -0.0191175899505 0.01
61 5 -0.267886340618 -0.0191175899505 0.01
61 10 -0.200730159879 -0.0191175899505 0.01
61 15 -0.272738099098 -0.0191175899505 0.01
61 20 -0.203535959125 -0.0191175899505 0.01
61 25 -0.18178679049 -0.0191175899505 0.01
61 30 -0.282279163599 -0.0191175899505 0.01
61 35 -0.16372486949 -0.0191175899505 0.01
61 40 -0.204506516457 -0.0191175899505 0.01
61 45 -0.249247565866 -0.0191175899505 0.01
61 50 -0.235357522964 -0.0191175899505 0.01
61 55 -0.230265915394 -0.0191175899505 0.01
valid_acc 93.22500000000001
62 0 -0.235784977674 -0.0191175899505 0.01
62 5 -0.249364227057 -0.0191175899505 0.01
62 10 -0.175133630633 -0.0191175899505 0.01
62 15 -0.203677728772 -0.0191175899505 0.01
62 20 -0.240101918578 -0.0191175899505 0.01
62 25 -0.203457251191 -0.0191175899505 0.01
62 30 -0.302231639624 -0.0191175899505 0.01
62 35 -0.220971941948 -0.0191175899505 0.01
62 40 -0.191814914346 -0.0191175899505 0.01
62 45 -0.22106705606 -0.0191175899505 0.01
62 50 -0.231721222401 -0.0191175899505 0.01
62 55 -0.21813634038 -0.0191175899505 0.01
valid_acc 94.27
best valid_acc 94.27
63 0 -0.204685941339 -0.0191175899505 0.01
63 5 -0.172175258398 -0.0191175899505 0.01
63 10 -0.206675499678 -0.0191175899505 0.01
63 15 -0.266058504581 -0.0191175899505 0.01
63 20 -0.205075562 -0.0191175899505 0.01
63 25 -0.222835451365 -0.0191175899505 0.01
63 30 -0.260214686394 -0.0191175899505 0.01
63 35 -0.179994672537 -0.0191175899505 0.01
63 40 -0.26378262043 -0.0191175899505 0.01
63 45 -0.238251879811 -0.0191175899505 0.01
63 50 -0.168582320213 -0.0191175899505 0.01
63 55 -0.195011779666 -0.0191175899505 0.01
valid_acc 93.76333333333334
64 0 -0.193926438689 -0.0191175899505 0.01
64 5 -0.235873609781 -0.0191175899505 0.01
64 10 -0.196315526962 -0.0191175899505 0.01
64 15 -0.260353296995 -0.0191175899505 0.01
64 20 -0.243159845471 -0.0191175899505 0.01
64 25 -0.249907568097 -0.0191175899505 0.01
64 30 -0.202096402645 -0.0191175899505 0.01
64 35 -0.231158211827 -0.0191175899505 0.01
64 40 -0.139205023646 -0.0191175899505 0.01
64 45 -0.231636285782 -0.0191175899505 0.01
64 50 -0.26926022768 -0.0191175899505 0.01
64 55 -0.181425526738 -0.0191175899505 0.01
valid_acc 93.57833333333333
65 0 -0.169647663832 -0.0191175899505 0.01
65 5 -0.201169461012 -0.0191175899505 0.01
65 10 -0.150291651487 -0.0191175899505 0.01
65 15 -0.212003260851 -0.0191175899505 0.01
65 20 -0.208115771413 -0.0191175899505 0.01
65 25 -0.227329969406 -0.0191175899505 0.01
65 30 -0.213200986385 -0.0191175899505 0.01
65 35 -0.261828809977 -0.0191175899505 0.01
65 40 -0.168811306357 -0.0191175899505 0.01
65 45 -0.246587887406 -0.0191175899505 0.01
65 50 -0.213523745537 -0.0191175899505 0.01
65 55 -0.247116535902 -0.0191175899505 0.01
valid_acc 93.445
66 0 -0.228771016002 -0.0191175899505 0.01
66 5 -0.201945573092 -0.0191175899505 0.01
66 10 -0.191467955709 -0.0191175899505 0.01
66 15 -0.164990544319 -0.0191175899505 0.01
66 20 -0.241160690784 -0.0191175899505 0.01
66 25 -0.212774023414 -0.0191175899505 0.01
66 30 -0.180508315563 -0.0191175899505 0.01
66 35 -0.240544363856 -0.0191175899505 0.01
66 40 -0.242795705795 -0.0191175899505 0.01
66 45 -0.206930398941 -0.0191175899505 0.01
66 50 -0.227751851082 -0.0191175899505 0.01
66 55 -0.234411135316 -0.0191175899505 0.01
valid_acc 93.96166666666666
67 0 -0.200943782926 -0.0191175899505 0.01
67 5 -0.172681152821 -0.0191175899505 0.01
67 10 -0.197423443198 -0.0191175899505 0.01
67 15 -0.274588674307 -0.0191175899505 0.01
67 20 -0.260636240244 -0.0191175899505 0.01
67 25 -0.208412647247 -0.0191175899505 0.01
67 30 -0.187172457576 -0.0191175899505 0.01
67 35 -0.218402728438 -0.0191175899505 0.01
67 40 -0.24554695189 -0.0191175899505 0.01
67 45 -0.20696093142 -0.0191175899505 0.01
67 50 -0.189990758896 -0.0191175899505 0.01
67 55 -0.179921388626 -0.0191175899505 0.01
valid_acc 93.63666666666667
68 0 -0.238853245974 -0.0191175899505 0.01
68 5 -0.248401120305 -0.0191175899505 0.01
68 10 -0.201305121183 -0.0191175899505 0.01
68 15 -0.25213354826 -0.0191175899505 0.01
68 20 -0.238138869405 -0.0191175899505 0.01
68 25 -0.195007964969 -0.0191175899505 0.01
68 30 -0.23998811841 -0.0191175899505 0.01
68 35 -0.208557978272 -0.0191175899505 0.01
68 40 -0.222667112947 -0.0191175899505 0.01
68 45 -0.195035547018 -0.0191175899505 0.01
68 50 -0.253428071737 -0.0191175899505 0.01
68 55 -0.178720727563 -0.0191175899505 0.01
valid_acc 93.48666666666666
69 0 -0.240671426058 -0.0191175899505 0.01
69 5 -0.247214138508 -0.0191175899505 0.01
69 10 -0.235916689038 -0.0191175899505 0.01
69 15 -0.21636928618 -0.0191175899505 0.01
69 20 -0.17707978189 -0.0191175899505 0.01
69 25 -0.200468212366 -0.0191175899505 0.01
69 30 -0.20374430716 -0.0191175899505 0.01
69 35 -0.242550730705 -0.0191175899505 0.01
69 40 -0.214434474707 -0.0191175899505 0.01
69 45 -0.228832900524 -0.0191175899505 0.01
69 50 -0.193490505219 -0.0191175899505 0.01
69 55 -0.268581420183 -0.0191175899505 0.01
valid_acc 93.935
70 0 -0.196884855628 -0.0191175899505 0.01
70 5 -0.19595618546 -0.0191175899505 0.01
70 10 -0.188909932971 -0.0191175899505 0.01
70 15 -0.221528232098 -0.0191175899505 0.01
70 20 -0.158656969666 -0.0191175899505 0.01
70 25 -0.279067277908 -0.0191175899505 0.01
70 30 -0.260356873274 -0.0191175899505 0.01
70 35 -0.19099059701 -0.0191175899505 0.01
70 40 -0.19161786139 -0.0191175899505 0.01
70 45 -0.188968852162 -0.0191175899505 0.01
70 50 -0.20148076117 -0.0191175899505 0.01
70 55 -0.191748559475 -0.0191175899505 0.01
valid_acc 93.805
71 0 -0.212486892939 -0.0191175899505 0.01
71 5 -0.263003826141 -0.0191175899505 0.01
71 10 -0.20088416338 -0.0191175899505 0.01
71 15 -0.251400858164 -0.0191175899505 0.01
71 20 -0.274516671896 -0.0191175899505 0.01
71 25 -0.245351731777 -0.0191175899505 0.01
71 30 -0.204909101129 -0.0191175899505 0.01
71 35 -0.235844358802 -0.0191175899505 0.01
71 40 -0.23354922235 -0.0191175899505 0.01
71 45 -0.179956942797 -0.0191175899505 0.01
71 50 -0.226221054792 -0.0191175899505 0.01
71 55 -0.217969566584 -0.0191175899505 0.01
valid_acc 93.675
72 0 -0.208299785852 -0.0191175899505 0.01
72 5 -0.178071171045 -0.0191175899505 0.01
72 10 -0.199091598392 -0.0191175899505 0.01
72 15 -0.212448850274 -0.0191175899505 0.01
72 20 -0.23007312417 -0.0191175899505 0.01
72 25 -0.17163592577 -0.0191175899505 0.01
72 30 -0.248388126493 -0.0191175899505 0.01
72 35 -0.230989530683 -0.0191175899505 0.01
72 40 -0.230090230703 -0.0191175899505 0.01
72 45 -0.23970015347 -0.0191175899505 0.01
72 50 -0.264892369509 -0.0191175899505 0.01
72 55 -0.226490169764 -0.0191175899505 0.01
valid_acc 93.71333333333334
73 0 -0.259528338909 -0.0191175899505 0.01
73 5 -0.219932615757 -0.0191175899505 0.01
73 10 -0.223351255059 -0.0191175899505 0.01
73 15 -0.182596251369 -0.0191175899505 0.01
73 20 -0.204853728414 -0.0191175899505 0.01
73 25 -0.240296468139 -0.0191175899505 0.01
73 30 -0.203298687935 -0.0191175899505 0.01
73 35 -0.187667369843 -0.0191175899505 0.01
73 40 -0.192662835121 -0.0191175899505 0.01
73 45 -0.276396602392 -0.0191175899505 0.01
73 50 -0.193713337183 -0.0191175899505 0.01
73 55 -0.197778716683 -0.0191175899505 0.01
valid_acc 92.93666666666667
74 0 -0.240743413568 -0.0191175899505 0.01
74 5 -0.225461125374 -0.0191175899505 0.01
74 10 -0.168684154749 -0.0191175899505 0.01
74 15 -0.220523014665 -0.0191175899505 0.01
74 20 -0.263902336359 -0.0191175899505 0.01
74 25 -0.259078204632 -0.0191175899505 0.01
74 30 -0.228176176548 -0.0191175899505 0.01
74 35 -0.235839188099 -0.0191175899505 0.01
74 40 -0.266179889441 -0.0191175899505 0.01
74 45 -0.190561041236 -0.0191175899505 0.01
74 50 -0.233552828431 -0.0191175899505 0.01
74 55 -0.263083040714 -0.0191175899505 0.01
valid_acc 93.515
75 0 -0.220613434911 -0.0191175899505 0.01
75 5 -0.247496455908 -0.0191175899505 0.01
75 10 -0.256971925497 -0.0191175899505 0.01
75 15 -0.214274391532 -0.0191175899505 0.01
75 20 -0.179808810353 -0.0191175899505 0.01
75 25 -0.175790831447 -0.0191175899505 0.01
75 30 -0.188938781619 -0.0191175899505 0.01
75 35 -0.2292381078 -0.0191175899505 0.01
75 40 -0.20284357667 -0.0191175899505 0.01
75 45 -0.202714696527 -0.0191175899505 0.01
75 50 -0.212022021413 -0.0191175899505 0.01
75 55 -0.222170129418 -0.0191175899505 0.01
valid_acc 93.51
76 0 -0.225315734744 -0.0191175899505 0.01
76 5 -0.287837862968 -0.0191175899505 0.01
76 10 -0.241556614637 -0.0191175899505 0.01
76 15 -0.198347195983 -0.0191175899505 0.01
76 20 -0.247626855969 -0.0191175899505 0.01
76 25 -0.197934940457 -0.0191175899505 0.01
76 30 -0.200395837426 -0.0191175899505 0.01
76 35 -0.243965864182 -0.0191175899505 0.01
76 40 -0.241917103529 -0.0191175899505 0.01
76 45 -0.221733734012 -0.0191175899505 0.01
76 50 -0.168530985713 -0.0191175899505 0.01
76 55 -0.219478115439 -0.0191175899505 0.01
valid_acc 93.4
77 0 -0.261746764183 -0.0191175899505 0.01
77 5 -0.279572635889 -0.0191175899505 0.01
77 10 -0.242623746395 -0.0191175899505 0.01
77 15 -0.286942750216 -0.0191175899505 0.01
77 20 -0.189962208271 -0.0191175899505 0.01
77 25 -0.207267731428 -0.0191175899505 0.01
77 30 -0.200169593096 -0.0191175899505 0.01
77 35 -0.169512242079 -0.0191175899505 0.01
77 40 -0.196963518858 -0.0191175899505 0.01
77 45 -0.210729464889 -0.0191175899505 0.01
77 50 -0.247840508819 -0.0191175899505 0.01
77 55 -0.215661197901 -0.0191175899505 0.01
valid_acc 93.57666666666667
78 0 -0.20090135932 -0.0191175899505 0.01
78 5 -0.249673292041 -0.0191175899505 0.01
78 10 -0.193518355489 -0.0191175899505 0.01
78 15 -0.177512258291 -0.0191175899505 0.01
78 20 -0.213404327631 -0.0191175899505 0.01
78 25 -0.231508791447 -0.0191175899505 0.01
78 30 -0.219040423632 -0.0191175899505 0.01
78 35 -0.182846620679 -0.0191175899505 0.01
78 40 -0.230229154229 -0.0191175899505 0.01
78 45 -0.223652213812 -0.0191175899505 0.01
78 50 -0.246643364429 -0.0191175899505 0.01
78 55 -0.244338348508 -0.0191175899505 0.01
valid_acc 93.20166666666667
79 0 -0.23464538157 -0.0191175899505 0.01
79 5 -0.192574813962 -0.0191175899505 0.01
79 10 -0.159404218197 -0.0191175899505 0.01
79 15 -0.22618021071 -0.02162420887 0.01
79 20 -0.264813482761 -0.02162420887 0.01
79 25 -0.245200112462 -0.02162420887 0.01
79 30 -0.204904660583 -0.02162420887 0.01
79 35 -0.250998973846 -0.02162420887 0.01
79 40 -0.199338942766 -0.02162420887 0.01
79 45 -0.250137001276 -0.02162420887 0.01
79 50 -0.225221425295 -0.02162420887 0.01
79 55 -0.19267347455 -0.02162420887 0.01
valid_acc 94.10666666666667
80 0 -0.190797954798 -0.02162420887 0.01
80 5 -0.240511506796 -0.02162420887 0.01
80 10 -0.226656615734 -0.02162420887 0.01
80 15 -0.240089252591 -0.02162420887 0.01
80 20 -0.201135680079 -0.02162420887 0.01
80 25 -0.170919701457 -0.02162420887 0.01
80 30 -0.221855923533 -0.02162420887 0.01
80 35 -0.201020225883 -0.02162420887 0.01
80 40 -0.202169060707 -0.02162420887 0.01
80 45 -0.263443082571 -0.02162420887 0.01
80 50 -0.226352125406 -0.02162420887 0.01
80 55 -0.226346001029 -0.02162420887 0.01
valid_acc 93.81666666666668
81 0 -0.211189076304 -0.02162420887 0.01
81 5 -0.118264853954 -0.0215318731065 0.01
81 10 -0.264688163996 -0.0215318731065 0.01
81 15 -0.233316063881 -0.0215318731065 0.01
81 20 -0.128518089652 -0.0215318731065 0.01
81 25 -0.176003396511 -0.0215318731065 0.01
81 30 -0.277569174767 -0.0215318731065 0.01
81 35 -0.2178722471 -0.0215318731065 0.01
81 40 -0.199044555426 -0.0215318731065 0.01
81 45 -0.192798525095 -0.0215318731065 0.01
81 50 -0.278001755476 -0.0215318731065 0.01
81 55 -0.227287262678 -0.0215318731065 0.01
valid_acc 93.90833333333333
82 0 -0.160716146231 -0.0215318731065 0.01
82 5 -0.211913228035 -0.0215318731065 0.01
82 10 -0.230614960194 -0.0215318731065 0.01
82 15 -0.244176805019 -0.0215318731065 0.01
82 20 -0.25526279211 -0.0215318731065 0.01
82 25 -0.275315463543 -0.0215318731065 0.01
82 30 -0.224894613028 -0.0215318731065 0.01
82 35 -0.283343315125 -0.0215318731065 0.01
82 40 -0.241914525628 -0.0215318731065 0.01
82 45 -0.242018654943 -0.0215318731065 0.01
82 50 -0.224783018231 -0.0215318731065 0.01
82 55 -0.226550415158 -0.0215318731065 0.01
valid_acc 93.91166666666668
83 0 -0.224347874522 -0.0215318731065 0.01
83 5 -0.201814725995 -0.0215318731065 0.01
83 10 -0.19703873992 -0.0215318731065 0.01
83 15 -0.147442266345 -0.0215318731065 0.01
83 20 -0.223051980138 -0.0215318731065 0.01
83 25 -0.237037077546 -0.0215318731065 0.01
83 30 -0.196401879191 -0.0215318731065 0.01
83 35 -0.253783673048 -0.0215318731065 0.01
83 40 -0.262302815914 -0.0215318731065 0.01
83 45 -0.231366842985 -0.0215318731065 0.01
83 50 -0.208133324981 -0.0215318731065 0.01
83 55 -0.222779721022 -0.0215318731065 0.01
valid_acc 94.02833333333334
84 0 -0.16489867866 -0.0215318731065 0.01
84 5 -0.23164087534 -0.0215318731065 0.01
84 10 -0.227159589529 -0.0215318731065 0.01
84 15 -0.181579500437 -0.0215318731065 0.01
84 20 -0.243737667799 -0.0215318731065 0.01
84 25 -0.15669451654 -0.0215318731065 0.01
84 30 -0.230079457164 -0.0215318731065 0.01
84 35 -0.196878626943 -0.0215318731065 0.01
84 40 -0.287212431431 -0.0215318731065 0.01
84 45 -0.172530025244 -0.0215318731065 0.01
84 50 -0.165016546845 -0.0215318731065 0.01
84 55 -0.259811937809 -0.0215318731065 0.01
valid_acc 94.06166666666667
85 0 -0.243255451322 -0.0215318731065 0.01
85 5 -0.196912527084 -0.0215318731065 0.01
85 10 -0.195767596364 -0.0215318731065 0.01
85 15 -0.193467065692 -0.0215318731065 0.01
85 20 -0.223872929811 -0.0215318731065 0.01
85 25 -0.237086310983 -0.0215318731065 0.01
85 30 -0.262283980846 -0.0215318731065 0.01
85 35 -0.214704155922 -0.0215318731065 0.01
85 40 -0.184465497732 -0.0215318731065 0.01
85 45 -0.232182055712 -0.0215318731065 0.01
85 50 -0.207891076803 -0.0215318731065 0.01
85 55 -0.187142968178 -0.0215318731065 0.01
valid_acc 94.36666666666666
best valid_acc 94.36666666666666
86 0 -0.170450881124 -0.0215318731065 0.01
86 5 -0.227982968092 -0.0215318731065 0.01
86 10 -0.237728729844 -0.0215318731065 0.01
86 15 -0.229282855988 -0.0215318731065 0.01
86 20 -0.201461836696 -0.0215318731065 0.01
86 25 -0.164250671864 -0.0215318731065 0.01
86 30 -0.188461780548 -0.0215318731065 0.01
86 35 -0.209246829152 -0.0215318731065 0.01
86 40 -0.218665078282 -0.0215318731065 0.01
86 45 -0.215851485729 -0.0215318731065 0.01
86 50 -0.216554105282 -0.0215318731065 0.01
86 55 -0.192619472742 -0.0215318731065 0.01
valid_acc 93.92333333333333
87 0 -0.192605614662 -0.0215318731065 0.01
87 5 -0.182633280754 -0.0215318731065 0.01
87 10 -0.228936165571 -0.0215318731065 0.01
87 15 -0.191023573279 -0.0215318731065 0.01
87 20 -0.198103293777 -0.0215318731065 0.01
87 25 -0.236664816737 -0.0215318731065 0.01
87 30 -0.178499206901 -0.0215318731065 0.01
87 35 -0.192637994885 -0.0215318731065 0.01
87 40 -0.259878873825 -0.0215318731065 0.01
87 45 -0.260592311621 -0.0215318731065 0.01
87 50 -0.155196622014 -0.0215318731065 0.01
87 55 -0.159175142646 -0.0215318731065 0.01
valid_acc 94.25
88 0 -0.174258098006 -0.0215318731065 0.01
88 5 -0.204328477383 -0.0215318731065 0.01
88 10 -0.167560368776 -0.0215318731065 0.01
88 15 -0.165464967489 -0.0215318731065 0.01
88 20 -0.251176983118 -0.0215318731065 0.01
88 25 -0.183683931828 -0.0215318731065 0.01
88 30 -0.284718126059 -0.0215318731065 0.01
88 35 -0.254688173532 -0.0215318731065 0.01
88 40 -0.242555558681 -0.0215318731065 0.01
88 45 -0.193336203694 -0.0215318731065 0.01
88 50 -0.180737376213 -0.0215318731065 0.01
88 55 -0.208720341325 -0.0215318731065 0.01
valid_acc 94.1
89 0 -0.213913455606 -0.0215318731065 0.01
89 5 -0.195581912994 -0.0215318731065 0.01
89 10 -0.230656564236 -0.0215318731065 0.01
89 15 -0.179903522134 -0.0215318731065 0.01
89 20 -0.177637889981 -0.0215318731065 0.01
89 25 -0.244201749563 -0.0215318731065 0.01
89 30 -0.19055852294 -0.0215318731065 0.01
89 35 -0.190534293652 -0.0215318731065 0.01
89 40 -0.242186620831 -0.0215318731065 0.01
89 45 -0.189205765724 -0.0215318731065 0.01
89 50 -0.225952684879 -0.0215318731065 0.01
89 55 -0.199784994125 -0.0215318731065 0.01
valid_acc 93.82666666666667
90 0 -0.256474584341 -0.0215318731065 0.01
90 5 -0.213735803962 -0.0215318731065 0.01
90 10 -0.175726428628 -0.0215318731065 0.01
90 15 -0.217112720013 -0.0215318731065 0.01
90 20 -0.213605433702 -0.0215318731065 0.01
90 25 -0.19825387001 -0.0215318731065 0.01
90 30 -0.215885534883 -0.0215318731065 0.01
90 35 -0.214866876602 -0.0215318731065 0.01
90 40 -0.198032304645 -0.0215318731065 0.01
90 45 -0.29971820116 -0.0215318731065 0.01
90 50 -0.202042281628 -0.0215318731065 0.01
90 55 -0.20987123251 -0.0215318731065 0.01
valid_acc 93.895
91 0 -0.195534080267 -0.0215318731065 0.01
91 5 -0.223617047071 -0.0215318731065 0.01
91 10 -0.240793079138 -0.0215318731065 0.01
91 15 -0.253446131945 -0.0215318731065 0.01
91 20 -0.20862364769 -0.0215318731065 0.01
91 25 -0.171319618821 -0.0215318731065 0.01
91 30 -0.196178585291 -0.0215318731065 0.01
91 35 -0.235902160406 -0.0215318731065 0.01
91 40 -0.223032563925 -0.0215318731065 0.01
91 45 -0.19463762641 -0.0215318731065 0.01
91 50 -0.218361347914 -0.0215318731065 0.01
91 55 -0.204463660717 -0.0215318731065 0.01
valid_acc 94.10333333333334
92 0 -0.220431908965 -0.0215318731065 0.01
92 5 -0.204755604267 -0.0215318731065 0.01
92 10 -0.165392145514 -0.0215318731065 0.01
92 15 -0.250057280064 -0.0215318731065 0.01
92 20 -0.303446143866 -0.0215318731065 0.01
92 25 -0.198546543717 -0.0215318731065 0.01
92 30 -0.221463695168 -0.0215318731065 0.01
92 35 -0.227703228593 -0.0215318731065 0.01
92 40 -0.160018622875 -0.0215318731065 0.01
92 45 -0.239077627659 -0.0215318731065 0.01
92 50 -0.202224582434 -0.0215318731065 0.01
92 55 -0.218112871051 -0.0215318731065 0.01
valid_acc 94.29333333333332
93 0 -0.267869085073 -0.0215318731065 0.01
93 5 -0.260796606541 -0.0215318731065 0.01
93 10 -0.261243492365 -0.0215318731065 0.01
93 15 -0.226312175393 -0.0215318731065 0.01
93 20 -0.181648463011 -0.0215318731065 0.01
93 25 -0.19370546937 -0.0215318731065 0.01
93 30 -0.208624184132 -0.0215318731065 0.01
93 35 -0.217496350408 -0.0215318731065 0.01
93 40 -0.28302308917 -0.0215318731065 0.01
93 45 -0.193383485079 -0.0215318731065 0.01
93 50 -0.263111442327 -0.0215318731065 0.01
93 55 -0.241870552301 -0.0215318731065 0.01
valid_acc 94.34333333333333
94 0 -0.147467911243 -0.0215318731065 0.01
94 5 -0.177999004722 -0.0215318731065 0.01
94 10 -0.185550242662 -0.0215318731065 0.01
94 15 -0.247347772121 -0.0215318731065 0.01
94 20 -0.229718104005 -0.0215318731065 0.01
94 25 -0.194028556347 -0.0215318731065 0.01
94 30 -0.239837542176 -0.0215318731065 0.01
94 35 -0.256501197815 -0.0215318731065 0.01
94 40 -0.207276329398 -0.0215318731065 0.01
94 45 -0.146319851279 -0.0215318731065 0.01
94 50 -0.174985811114 -0.0215318731065 0.01
94 55 -0.161881148815 -0.0215318731065 0.01
valid_acc 94.70333333333333
best valid_acc 94.70333333333333
95 0 -0.157962292433 -0.0215318731065 0.01
95 5 -0.236177146435 -0.0215318731065 0.01
95 10 -0.174967452884 -0.0215318731065 0.01
95 15 -0.19929818809 -0.0215318731065 0.01
95 20 -0.327830791473 -0.0215318731065 0.01
95 25 -0.251111030579 -0.0215318731065 0.01
95 30 -0.206430956721 -0.0215318731065 0.01
95 35 -0.282404750586 -0.0215318731065 0.01
95 40 -0.27163118124 -0.0215318731065 0.01
95 45 -0.258383840322 -0.0215318731065 0.01
95 50 -0.233558386564 -0.0215318731065 0.01
95 55 -0.239718958735 -0.0215318731065 0.01
valid_acc 94.175
96 0 -0.152579560876 -0.0215318731065 0.01
96 5 -0.257389992476 -0.0215318731065 0.01
96 10 -0.209611535072 -0.0215318731065 0.01
96 15 -0.20831105113 -0.0215318731065 0.01
96 20 -0.287808477879 -0.0215318731065 0.01
96 25 -0.198635429144 -0.0215318731065 0.01
96 30 -0.258926540613 -0.0215318731065 0.01
96 35 -0.267113745213 -0.0215318731065 0.01
96 40 -0.27352899313 -0.0215318731065 0.01
96 45 -0.275085955858 -0.0215318731065 0.01
96 50 -0.222745239735 -0.0215318731065 0.01
96 55 -0.196141138673 -0.0215318731065 0.01
valid_acc 94.14666666666666
97 0 -0.17057326436 -0.0215318731065 0.01
97 5 -0.223317250609 -0.0215318731065 0.01
97 10 -0.206161633134 -0.0215318731065 0.01
97 15 -0.158079817891 -0.0215318731065 0.01
97 20 -0.201004326344 -0.0215318731065 0.01
97 25 -0.209516257048 -0.0215318731065 0.01
97 30 -0.284664750099 -0.0215318731065 0.01
97 35 -0.244297102094 -0.0215318731065 0.01
97 40 -0.217005640268 -0.0215318731065 0.01
97 45 -0.270807743073 -0.0215318731065 0.01
97 50 -0.159384936094 -0.0215318731065 0.01
97 55 -0.218655914068 -0.0215318731065 0.01
valid_acc 94.28666666666666
98 0 -0.211825817823 -0.0215318731065 0.01
98 5 -0.223182231188 -0.0215318731065 0.01
98 10 -0.211777254939 -0.0215318731065 0.01
98 15 -0.186697602272 -0.0215318731065 0.01
98 20 -0.271771192551 -0.0215318731065 0.01
98 25 -0.191317901015 -0.0215318731065 0.01
98 30 -0.1869276613 -0.0215318731065 0.01
98 35 -0.248043209314 -0.0215318731065 0.01
98 40 -0.184451982379 -0.0215318731065 0.01
98 45 -0.203480169177 -0.0215318731065 0.01
98 50 -0.223931521177 -0.0215318731065 0.01
98 55 -0.229375392199 -0.0215318731065 0.01
valid_acc 93.94166666666666
99 0 -0.187204703689 -0.0215318731065 0.01
99 5 -0.213989958167 -0.0215318731065 0.01
99 10 -0.191436246037 -0.0215318731065 0.01
99 15 -0.238388627768 -0.0215318731065 0.01
99 20 -0.210130318999 -0.0215318731065 0.01
99 25 -0.160368084908 -0.0215318731065 0.01
99 30 -0.220610588789 -0.0215318731065 0.01
99 35 -0.187291949987 -0.0215318731065 0.01
99 40 -0.185248032212 -0.0215318731065 0.01
99 45 -0.177520424128 -0.0215318731065 0.01
99 50 -0.19576318562 -0.0215318731065 0.01
99 55 -0.212697014213 -0.0215318731065 0.01
valid_acc 94.53333333333333
100 0 -0.138347268105 -0.0215318731065 0.01
100 5 -0.174274817109 -0.0215318731065 0.01
100 10 -0.161768764257 -0.0215318731065 0.01
100 15 -0.256225705147 -0.0215318731065 0.01
100 20 -0.212340056896 -0.0215318731065 0.01
100 25 -0.200999364257 -0.0215318731065 0.01
100 30 -0.209875062108 -0.0215318731065 0.01
100 35 -0.205478191376 -0.0215318731065 0.01
100 40 -0.24339620769 -0.0215318731065 0.01
100 45 -0.199207872152 -0.0215318731065 0.01
100 50 -0.241369858384 -0.0215318731065 0.01
100 55 -0.2269577384 -0.0215318731065 0.01
valid_acc 94.36
101 0 -0.216443225741 -0.0215318731065 0.01
101 5 -0.259689122438 -0.0215318731065 0.01
101 10 -0.270999878645 -0.0215318731065 0.01
101 15 -0.168985635042 -0.0215318731065 0.01
101 20 -0.184746652842 -0.0215318731065 0.01
101 25 -0.268391907215 -0.0215318731065 0.01
101 30 -0.196193367243 -0.0215318731065 0.01
101 35 -0.246123090386 -0.0215318731065 0.01
101 40 -0.180350139737 -0.0215318731065 0.01
101 45 -0.195218414068 -0.0215318731065 0.01
101 50 -0.171095401049 -0.0215318731065 0.01
101 55 -0.23166897893 -0.0215318731065 0.01
valid_acc 93.66
102 0 -0.2106410712 -0.0215318731065 0.01
102 5 -0.191800639033 -0.0215318731065 0.01
102 10 -0.241584986448 -0.0215318731065 0.01
102 15 -0.250091940165 -0.0215318731065 0.01
102 20 -0.212417721748 -0.0215318731065 0.01
102 25 -0.231978937984 -0.0215318731065 0.01
102 30 -0.213805139065 -0.0215318731065 0.01
102 35 -0.165515989065 -0.0215318731065 0.01
102 40 -0.234862759709 -0.0215318731065 0.01
102 45 -0.160677343607 -0.0215318731065 0.01
102 50 -0.182516634464 -0.0215318731065 0.01
102 55 -0.168602868915 -0.0215318731065 0.01
valid_acc 94.06166666666667
103 0 -0.208218932152 -0.0215318731065 0.01
103 5 -0.218223959208 -0.0215318731065 0.01
103 10 -0.177791520953 -0.0215318731065 0.01
103 15 -0.119830146432 -0.0215318731065 0.01
103 20 -0.215905755758 -0.0215318731065 0.01
103 25 -0.222160056233 -0.0215318731065 0.01
103 30 -0.192702919245 -0.0215318731065 0.01
103 35 -0.243080615997 -0.0215318731065 0.01
103 40 -0.209298923612 -0.0215318731065 0.01
103 45 -0.202269122005 -0.0215318731065 0.01
103 50 -0.185232922435 -0.0215318731065 0.01
103 55 -0.162911817431 -0.0215318731065 0.01
valid_acc 93.91333333333334
104 0 -0.19081415236 -0.0215318731065 0.01
104 5 -0.176232904196 -0.0215318731065 0.01
104 10 -0.186407908797 -0.0215318731065 0.01
104 15 -0.146793410182 -0.0215318731065 0.01
104 20 -0.216696515679 -0.0215318731065 0.01
104 25 -0.191189929843 -0.0215318731065 0.01
104 30 -0.211047053337 -0.0215318731065 0.01
104 35 -0.225903883576 -0.0215318731065 0.01
104 40 -0.173151060939 -0.0215318731065 0.01
104 45 -0.19538629055 -0.0215318731065 0.01
104 50 -0.265716224909 -0.0215318731065 0.01
104 55 -0.169058874249 -0.0215318731065 0.01
valid_acc 94.395
105 0 -0.202189221978 -0.0215318731065 0.01
105 5 -0.153549075127 -0.0215318731065 0.01
105 10 -0.225426539779 -0.0215318731065 0.01
105 15 -0.196210041642 -0.0215318731065 0.01
105 20 -0.157882213593 -0.0215318731065 0.01
105 25 -0.24745836854 -0.0215318731065 0.01
105 30 -0.184742003679 -0.0215318731065 0.01
105 35 -0.180968463421 -0.0215318731065 0.01
105 40 -0.206878036261 -0.0215318731065 0.01
105 45 -0.212488904595 -0.0215318731065 0.01
105 50 -0.199648231268 -0.0215318731065 0.01
105 55 -0.196348875761 -0.0215318731065 0.01
valid_acc 93.785
106 0 -0.251279383898 -0.0215318731065 0.01
106 5 -0.163768947124 -0.0215318731065 0.01
106 10 -0.171767100692 -0.0215318731065 0.01
106 15 -0.23985722661 -0.0215318731065 0.01
106 20 -0.176726311445 -0.0215318731065 0.01
106 25 -0.18670502305 -0.0215318731065 0.01
106 30 -0.253426671028 -0.0215318731065 0.01
106 35 -0.220140919089 -0.0215318731065 0.01
106 40 -0.202452644706 -0.0215318731065 0.01
106 45 -0.194585904479 -0.0215318731065 0.01
106 50 -0.243696793914 -0.0215318731065 0.01
106 55 -0.20139105618 -0.0215318731065 0.01
valid_acc 93.99666666666666
107 0 -0.154883369803 -0.0215318731065 0.01
107 5 -0.201387137175 -0.0215318731065 0.01
107 10 -0.207874968648 -0.0215318731065 0.01
107 15 -0.186769217253 -0.0215318731065 0.01
107 20 -0.213660359383 -0.0215318731065 0.01
107 25 -0.258997827768 -0.0215318731065 0.01
107 30 -0.222730562091 -0.0215318731065 0.01
107 35 -0.182027757168 -0.0215318731065 0.01
107 40 -0.197080284357 -0.0215318731065 0.01
107 45 -0.275684207678 -0.0215318731065 0.01
107 50 -0.196856588125 -0.0215318731065 0.01
107 55 -0.200381219387 -0.0215318731065 0.01
valid_acc 94.27
108 0 -0.189819082618 -0.0215318731065 0.01
108 5 -0.182893425226 -0.0215318731065 0.01
108 10 -0.246958449483 -0.0215318731065 0.01
108 15 -0.168254926801 -0.0215318731065 0.01
108 20 -0.209873870015 -0.0215318731065 0.01
108 25 -0.168546020985 -0.0215318731065 0.01
108 30 -0.231325298548 -0.0215318731065 0.01
108 35 -0.182344198227 -0.0215318731065 0.01
108 40 -0.168789356947 -0.0215318731065 0.01
108 45 -0.17998367548 -0.0215318731065 0.01
108 50 -0.204707816243 -0.0215318731065 0.01
108 55 -0.189188405871 -0.0215318731065 0.01
valid_acc 94.36833333333333
109 0 -0.218565404415 -0.0225759469157 0.01
109 5 -0.187388673425 -0.0225759469157 0.01
109 10 -0.200005471706 -0.0225759469157 0.01
109 15 -0.150336146355 -0.0225759469157 0.01
109 20 -0.198246136308 -0.0225759469157 0.01
109 25 -0.215947106481 -0.0225759469157 0.01
109 30 -0.226655736566 -0.0225759469157 0.01
109 35 -0.238967761397 -0.0225759469157 0.01
109 40 -0.202129140496 -0.0225759469157 0.01
109 45 -0.187396585941 -0.0225759469157 0.01
109 50 -0.163278609514 -0.0225759469157 0.01
109 55 -0.135816767812 -0.0225759469157 0.01
valid_acc 93.59333333333333
110 0 -0.154726207256 -0.0225759469157 0.01
110 5 -0.189045861363 -0.0225759469157 0.01
110 10 -0.151815772057 -0.0225759469157 0.01
110 15 -0.13787792623 -0.0225759469157 0.01
110 20 -0.19104847312 -0.0225759469157 0.01
110 25 -0.188683226705 -0.0225759469157 0.01
110 30 -0.230858072639 -0.0225759469157 0.01
110 35 -0.185572177172 -0.0225759469157 0.01
110 40 -0.21528622508 -0.0225759469157 0.01
110 45 -0.194614887238 -0.0225759469157 0.01
110 50 -0.249563828111 -0.0225759469157 0.01
110 55 -0.206811755896 -0.0225759469157 0.01
valid_acc 93.49
111 0 -0.161874771118 -0.0225759469157 0.01
111 5 -0.19925044477 -0.0225759469157 0.01
111 10 -0.179388910532 -0.0225759469157 0.01
111 15 -0.192530378699 -0.0225759469157 0.01
111 20 -0.177974417806 -0.0225759469157 0.01
111 25 -0.201502069831 -0.0225759469157 0.01
111 30 -0.232014551759 -0.0225759469157 0.01
111 35 -0.194384917617 -0.0225759469157 0.01
111 40 -0.190345063806 -0.0225759469157 0.01
111 45 -0.207354709506 -0.0225759469157 0.01
111 50 -0.198423087597 -0.0225759469157 0.01
111 55 -0.191624864936 -0.0225759469157 0.01
valid_acc 94.26666666666667
112 0 -0.228692784905 -0.0225759469157 0.01
112 5 -0.210502505302 -0.0225759469157 0.01
112 10 -0.198906287551 -0.0225759469157 0.01
112 15 -0.179814919829 -0.0225759469157 0.01
112 20 -0.256223529577 -0.0225759469157 0.01
112 25 -0.197138473392 -0.0225759469157 0.01
112 30 -0.108573637903 -0.0225759469157 0.01
112 35 -0.185322701931 -0.0225759469157 0.01
112 40 -0.223925456405 -0.0225759469157 0.01
112 45 -0.225729584694 -0.0225759469157 0.01
112 50 -0.20509685576 -0.0225759469157 0.01
112 55 -0.160237714648 -0.0225759469157 0.01
valid_acc 94.58166666666666
113 0 -0.111448459327 -0.0225759469157 0.01
113 5 -0.192939266562 -0.0225759469157 0.01
113 10 -0.251495689154 -0.0225759469157 0.01
113 15 -0.155432328582 -0.0225759469157 0.01
113 20 -0.171987369657 -0.0225759469157 0.01
113 25 -0.162166580558 -0.0225759469157 0.01
113 30 -0.153507560492 -0.0225759469157 0.01
113 35 -0.218701228499 -0.0225759469157 0.01
113 40 -0.159774824977 -0.0225759469157 0.01
113 45 -0.179782941937 -0.0225759469157 0.01
113 50 -0.169924452901 -0.0225759469157 0.01
113 55 -0.193965539336 -0.0225759469157 0.01
valid_acc 94.58166666666666
114 0 -0.190628603101 -0.0225759469157 0.01
114 5 -0.205185055733 -0.0225759469157 0.01
114 10 -0.214520558715 -0.0225759469157 0.01
114 15 -0.221484333277 -0.0225759469157 0.01
114 20 -0.197158023715 -0.0225759469157 0.01
114 25 -0.241767928004 -0.0225759469157 0.01
114 30 -0.153296768665 -0.0225759469157 0.01
114 35 -0.161594673991 -0.0225759469157 0.01
114 40 -0.237299233675 -0.0225759469157 0.01
114 45 -0.199007093906 -0.0225759469157 0.01
114 50 -0.13636687398 -0.0225759469157 0.01
114 55 -0.181194424629 -0.0225759469157 0.01
valid_acc 94.21166666666667
115 0 -0.19637157023 -0.0225759469157 0.01
115 5 -0.262112826109 -0.0225759469157 0.01
115 10 -0.18664598465 -0.0225759469157 0.01
115 15 -0.163117930293 -0.0225759469157 0.01
115 20 -0.161167219281 -0.0225759469157 0.01
115 25 -0.207086741924 -0.0225759469157 0.01
115 30 -0.179543033242 -0.0225759469157 0.01
115 35 -0.121689625084 -0.0225759469157 0.01
115 40 -0.183370262384 -0.0225759469157 0.01
115 45 -0.287409394979 -0.0225759469157 0.01
115 50 -0.211507558823 -0.0225759469157 0.01
115 55 -0.17316788435 -0.0225759469157 0.01
valid_acc 94.05833333333334
116 0 -0.254360854626 -0.0225759469157 0.01
116 5 -0.214626669884 -0.0225759469157 0.01
116 10 -0.165128171444 -0.0225759469157 0.01
116 15 -0.254624634981 -0.0225759469157 0.01
116 20 -0.177613452077 -0.0225759469157 0.01
116 25 -0.137415617704 -0.0225759469157 0.01
116 30 -0.143834337592 -0.0225759469157 0.01
116 35 -0.160655856133 -0.0225759469157 0.01
116 40 -0.172244742513 -0.0225759469157 0.01
116 45 -0.171542584896 -0.0225759469157 0.01
116 50 -0.179755762219 -0.0225759469157 0.01
116 55 -0.202501490712 -0.0225759469157 0.01
valid_acc 94.38
117 0 -0.18197594583 -0.0225759469157 0.01
117 5 -0.164998665452 -0.0225759469157 0.01
117 10 -0.216620385647 -0.0225759469157 0.01
117 15 -0.271619319916 -0.0225759469157 0.01
117 20 -0.194134771824 -0.0225759469157 0.01
117 25 -0.187608599663 -0.0225759469157 0.01
117 30 -0.206647917628 -0.0225759469157 0.01
117 35 -0.184957027435 -0.0225759469157 0.01
117 40 -0.131004780531 -0.0225759469157 0.01
117 45 -0.17751711607 -0.0225759469157 0.01
117 50 -0.212065413594 -0.0225759469157 0.01
117 55 -0.160433322191 -0.0225759469157 0.01
valid_acc 94.715
best valid_acc 94.715
118 0 -0.267544060946 -0.0225759469157 0.01
118 5 -0.162903994322 -0.0225759469157 0.01
118 10 -0.145889088511 -0.0225759469157 0.01
118 15 -0.149427697062 -0.0225759469157 0.01
118 20 -0.169713631272 -0.0225759469157 0.01
118 25 -0.209406033158 -0.0225759469157 0.01
118 30 -0.259328991175 -0.0225759469157 0.01
118 35 -0.160258516669 -0.0225759469157 0.01
118 40 -0.170490860939 -0.0225759469157 0.01
118 45 -0.164198830724 -0.0225759469157 0.01
118 50 -0.150259807706 -0.0225759469157 0.01
118 55 -0.2226780653 -0.0225759469157 0.01
valid_acc 94.52166666666668
119 0 -0.158425554633 -0.0225759469157 0.01
119 5 -0.164349287748 -0.0225759469157 0.01
119 10 -0.231805607677 -0.0225759469157 0.01
119 15 -0.160710275173 -0.0225759469157 0.01
119 20 -0.229204460979 -0.0225759469157 0.01
119 25 -0.145065844059 -0.0225759469157 0.01
119 30 -0.203490838408 -0.0225759469157 0.01
119 35 -0.172706618905 -0.0225759469157 0.01
119 40 -0.186062529683 -0.0225759469157 0.01
119 45 -0.258815050125 -0.0225759469157 0.01
119 50 -0.158574491739 -0.0225759469157 0.01
119 55 -0.173708096147 -0.0225759469157 0.01
valid_acc 94.38333333333333
120 0 -0.204703211784 -0.0225759469157 0.01
120 5 -0.261439740658 -0.0225759469157 0.01
120 10 -0.173525840044 -0.0225759469157 0.01
120 15 -0.162208214402 -0.0225759469157 0.01
120 20 -0.194895520806 -0.0225759469157 0.01
120 25 -0.181664302945 -0.0225759469157 0.01
120 30 -0.158372193575 -0.0225759469157 0.01
120 35 -0.155544102192 -0.0225759469157 0.01
120 40 -0.177567794919 -0.0225759469157 0.01
120 45 -0.186383292079 -0.0225759469157 0.01
120 50 -0.226799160242 -0.0225759469157 0.01
120 55 -0.159319996834 -0.0225759469157 0.01
valid_acc 94.705
121 0 -0.198401257396 -0.0225759469157 0.01
121 5 -0.196014851332 -0.0225759469157 0.01
121 10 -0.190123215318 -0.0225759469157 0.01
121 15 -0.262699991465 -0.0225759469157 0.01
121 20 -0.199665874243 -0.0225759469157 0.01
121 25 -0.242639660835 -0.0225759469157 0.01
121 30 -0.161144033074 -0.0225759469157 0.01
121 35 -0.20093549788 -0.0225759469157 0.01
121 40 -0.250477880239 -0.0225759469157 0.01
121 45 -0.203871324658 -0.0225759469157 0.01
121 50 -0.168392673135 -0.0225759469157 0.01
121 55 -0.203185424209 -0.0225759469157 0.01
valid_acc 94.43166666666667
122 0 -0.184420481324 -0.0225759469157 0.01
122 5 -0.186467587948 -0.0225759469157 0.01
122 10 -0.169501468539 -0.0225759469157 0.01
122 15 -0.148990914226 -0.0225759469157 0.01
122 20 -0.20618057251 -0.0225759469157 0.01
122 25 -0.182127848268 -0.0225759469157 0.01
122 30 -0.226560220122 -0.0225759469157 0.01
122 35 -0.217454463243 -0.0225759469157 0.01
122 40 -0.250137209892 -0.0225759469157 0.01
122 45 -0.177429065108 -0.0225759469157 0.01
122 50 -0.160456717014 -0.0225759469157 0.01
122 55 -0.166341558099 -0.0225759469157 0.01
valid_acc 94.52000000000001
123 0 -0.201592460275 -0.0225759469157 0.01
123 5 -0.171830832958 -0.0225759469157 0.01
123 10 -0.204314604402 -0.0225759469157 0.01
123 15 -0.148348331451 -0.0225759469157 0.01
123 20 -0.190695568919 -0.0225759469157 0.01
123 25 -0.170541241765 -0.0225759469157 0.01
123 30 -0.164748251438 -0.0225759469157 0.01
123 35 -0.222034394741 -0.0225759469157 0.01
123 40 -0.180989474058 -0.0225759469157 0.01
123 45 -0.211032509804 -0.0225759469157 0.01
123 50 -0.19609542191 -0.0225759469157 0.01
123 55 -0.16144400835 -0.0225759469157 0.01
valid_acc 94.31833333333334
124 0 -0.160121932626 -0.0225759469157 0.01
124 5 -0.269799888134 -0.0225759469157 0.01
124 10 -0.20327784121 -0.0225759469157 0.01
124 15 -0.255646318197 -0.0225759469157 0.01
124 20 -0.225641354918 -0.0225759469157 0.01
124 25 -0.208811193705 -0.0225759469157 0.01
124 30 -0.168588131666 -0.0225759469157 0.01
124 35 -0.143607228994 -0.0225759469157 0.01
124 40 -0.161709427834 -0.0225759469157 0.01
124 45 -0.159242615104 -0.0225759469157 0.01
124 50 -0.196719020605 -0.0225759469157 0.01
124 55 -0.229456081986 -0.0225759469157 0.01
valid_acc 94.43
125 0 -0.215224534273 -0.0225759469157 0.01
125 5 -0.159397512674 -0.0225759469157 0.01
125 10 -0.18062260747 -0.0225759469157 0.01
125 15 -0.151947528124 -0.0225759469157 0.01
125 20 -0.218788444996 -0.0225759469157 0.01
125 25 -0.199363216758 -0.0225759469157 0.01
125 30 -0.200458168983 -0.0225759469157 0.01
125 35 -0.18733727932 -0.0225759469157 0.01
125 40 -0.206478282809 -0.0225759469157 0.01
125 45 -0.168036043644 -0.0225759469157 0.01
125 50 -0.172412231565 -0.0225759469157 0.01
125 55 -0.212371706963 -0.0225759469157 0.01
valid_acc 94.315
126 0 -0.223923966289 -0.0225759469157 0.01
126 5 -0.137261286378 -0.0225759469157 0.01
126 10 -0.21398037672 -0.0225759469157 0.01
126 15 -0.158885210752 -0.0225759469157 0.01
126 20 -0.176455199718 -0.0225759469157 0.01
126 25 -0.239057391882 -0.0225759469157 0.01
126 30 -0.210285708308 -0.0225759469157 0.01
126 35 -0.219668164849 -0.0225759469157 0.01
126 40 -0.188558116555 -0.0225759469157 0.01
126 45 -0.18594917655 -0.0225759469157 0.01
126 50 -0.192381680012 -0.0225759469157 0.01
126 55 -0.154711857438 -0.0225759469157 0.01
valid_acc 94.705
127 0 -0.229205384851 -0.0225759469157 0.01
127 5 -0.225702747703 -0.0225759469157 0.01
127 10 -0.205827727914 -0.0225759469157 0.01
127 15 -0.168649479747 -0.0225759469157 0.01
127 20 -0.19348141551 -0.0225759469157 0.01
127 25 -0.217871323228 -0.0225759469157 0.01
127 30 -0.146676614881 -0.0225759469157 0.01
127 35 -0.185000002384 -0.0225759469157 0.01
127 40 -0.175618156791 -0.0225759469157 0.01
127 45 -0.167501017451 -0.0225759469157 0.01
127 50 -0.243357777596 -0.0225759469157 0.01
127 55 -0.179992735386 -0.0225759469157 0.01
valid_acc 94.375
128 0 -0.190755784512 -0.0225759469157 0.01
128 5 -0.156167760491 -0.0225759469157 0.01
128 10 -0.195908471942 -0.0225759469157 0.01
128 15 -0.193308547139 -0.0225759469157 0.01
128 20 -0.185085371137 -0.0225759469157 0.01
128 25 -0.188468143344 -0.0225759469157 0.01
128 30 -0.151923656464 -0.0225759469157 0.01
128 35 -0.181885182858 -0.0225759469157 0.01
128 40 -0.170112445951 -0.0225759469157 0.01
128 45 -0.1891143471 -0.0225759469157 0.01
128 50 -0.183349475265 -0.0225759469157 0.01
128 55 -0.208928793669 -0.0225759469157 0.01
valid_acc 94.51666666666667
129 0 -0.157780393958 -0.0225759469157 0.01
129 5 -0.203414618969 -0.0225759469157 0.01
129 10 -0.188409760594 -0.0225759469157 0.01
129 15 -0.191214635968 -0.0225759469157 0.01
129 20 -0.197708800435 -0.0225759469157 0.01
129 25 -0.21306759119 -0.0225759469157 0.01
129 30 -0.154051840305 -0.0225759469157 0.01
129 35 -0.177122026682 -0.0225759469157 0.01
129 40 -0.180150046945 -0.0225759469157 0.01
129 45 -0.184027135372 -0.0225759469157 0.01
129 50 -0.190783768892 -0.0225759469157 0.01
129 55 -0.183298021555 -0.0225759469157 0.01
valid_acc 94.73666666666666
best valid_acc 94.73666666666666
130 0 -0.231102615595 -0.0225759469157 0.01
130 5 -0.187976568937 -0.0225759469157 0.01
130 10 -0.190358057618 -0.0225759469157 0.01
130 15 -0.172013327479 -0.0225759469157 0.01
130 20 -0.206343859434 -0.0225759469157 0.01
130 25 -0.179982885718 -0.0225759469157 0.01
130 30 -0.232244387269 -0.0225759469157 0.01
130 35 -0.211442902684 -0.0225759469157 0.01
130 40 -0.170754417777 -0.0225759469157 0.01
130 45 -0.253392785788 -0.0225759469157 0.01
130 50 -0.178806915879 -0.0225759469157 0.01
130 55 -0.154684275389 -0.0225759469157 0.01
valid_acc 94.40166666666666
131 0 -0.207214877009 -0.0225759469157 0.01
131 5 -0.179074466228 -0.0225759469157 0.01
131 10 -0.188856691122 -0.0225759469157 0.01
131 15 -0.207244500518 -0.0225759469157 0.01
131 20 -0.152237907052 -0.0225759469157 0.01
131 25 -0.170619219542 -0.0225759469157 0.01
131 30 -0.16692866385 -0.0225759469157 0.01
131 35 -0.24276919663 -0.0225759469157 0.01
131 40 -0.258093267679 -0.0225759469157 0.01
131 45 -0.224782273173 -0.0225759469157 0.01
131 50 -0.248138859868 -0.0225759469157 0.01
131 55 -0.174214243889 -0.0225759469157 0.01
valid_acc 93.98333333333333
132 0 -0.177441254258 -0.0225759469157 0.01
132 5 -0.211921140552 -0.0225759469157 0.01
132 10 -0.154249683022 -0.0225759469157 0.01
132 15 -0.17189604044 -0.0225759469157 0.01
132 20 -0.166408762336 -0.0225759469157 0.01
132 25 -0.178723201156 -0.0225759469157 0.01
132 30 -0.212646201253 -0.0225759469157 0.01
132 35 -0.142395377159 -0.0225759469157 0.01
132 40 -0.159865945578 -0.0225759469157 0.01
132 45 -0.164192318916 -0.0225759469157 0.01
132 50 -0.282244086266 -0.0225759469157 0.01
132 55 -0.259376019239 -0.0225759469157 0.01
valid_acc 94.35333333333334
133 0 -0.174662873149 -0.0225759469157 0.01
133 5 -0.217292204499 -0.0225759469157 0.01
133 10 -0.202405825257 -0.0225759469157 0.01
133 15 -0.170539617538 -0.0225759469157 0.01
133 20 -0.168009892106 -0.0225759469157 0.01
133 25 -0.181980833411 -0.0225759469157 0.01
133 30 -0.13133828342 -0.0225759469157 0.01
133 35 -0.209300756454 -0.0225759469157 0.01
133 40 -0.192356705666 -0.0225759469157 0.01
133 45 -0.132788211107 -0.0225759469157 0.01
133 50 -0.156998261809 -0.0225759469157 0.01
133 55 -0.195408523083 -0.0225759469157 0.01
valid_acc 94.12
134 0 -0.204708591104 -0.0225759469157 0.01
134 5 -0.174416705966 -0.0225759469157 0.01
134 10 -0.246588528156 -0.0225759469157 0.01
134 15 -0.175597026944 -0.0225759469157 0.01
134 20 -0.19856582582 -0.0225759469157 0.01
134 25 -0.209628343582 -0.0225759469157 0.01
134 30 -0.228818997741 -0.0225759469157 0.01
134 35 -0.20964255929 -0.0225759469157 0.01
134 40 -0.142123937607 -0.0225759469157 0.01
134 45 -0.147014886141 -0.0225759469157 0.01
134 50 -0.188979208469 -0.0225759469157 0.01
134 55 -0.158431574702 -0.0225759469157 0.01
valid_acc 94.52833333333334
135 0 -0.143948197365 -0.0225759469157 0.01
135 5 -0.206586197019 -0.0225759469157 0.01
135 10 -0.189410045743 -0.0225759469157 0.01
135 15 -0.186631366611 -0.0225759469157 0.01
135 20 -0.170910090208 -0.0225759469157 0.01
135 25 -0.19653762877 -0.0225759469157 0.01
135 30 -0.187085881829 -0.0225759469157 0.01
135 35 -0.189868196845 -0.0225759469157 0.01
135 40 -0.189932212234 -0.0225759469157 0.01
135 45 -0.191802218556 -0.0225759469157 0.01
135 50 -0.248981401324 -0.0225759469157 0.01
135 55 -0.222459465265 -0.0225759469157 0.01
valid_acc 94.46833333333333
136 0 -0.206262469292 -0.0225759469157 0.01
136 5 -0.221845388412 -0.0225759469157 0.01
136 10 -0.23697270453 -0.0225759469157 0.01
136 15 -0.250280618668 -0.0225759469157 0.01
136 20 -0.183380484581 -0.0225759469157 0.01
136 25 -0.18700966239 -0.0225759469157 0.01
136 30 -0.174601957202 -0.0225759469157 0.01
136 35 -0.176544010639 -0.0225759469157 0.01
136 40 -0.180302217603 -0.0225759469157 0.01
136 45 -0.188906684518 -0.0225759469157 0.01
136 50 -0.191634431481 -0.0225759469157 0.01
136 55 -0.172768637538 -0.0225759469157 0.01
valid_acc 94.67166666666667
137 0 -0.188518449664 -0.0225759469157 0.01
137 5 -0.181792020798 -0.0225759469157 0.01
137 10 -0.270767003298 -0.0225759469157 0.01
137 15 -0.180549412966 -0.0225759469157 0.01
137 20 -0.158099129796 -0.0225759469157 0.01
137 25 -0.174799010158 -0.0225759469157 0.01
137 30 -0.180354595184 -0.0225759469157 0.01
137 35 -0.138965219259 -0.0225759469157 0.01
137 40 -0.21734842658 -0.0225759469157 0.01
137 45 -0.207819104195 -0.0225759469157 0.01
137 50 -0.153622344136 -0.0225759469157 0.01
137 55 -0.198786050081 -0.0225759469157 0.01
valid_acc 94.32666666666667
138 0 -0.142905667424 -0.0225759469157 0.01
138 5 -0.228920012712 -0.0225759469157 0.01
138 10 -0.184071168303 -0.0225759469157 0.01
138 15 -0.181101307273 -0.0225759469157 0.01
138 20 -0.207516312599 -0.0225759469157 0.01
138 25 -0.195553228259 -0.0225759469157 0.01
138 30 -0.201332911849 -0.0225759469157 0.01
138 35 -0.219482243061 -0.0225759469157 0.01
138 40 -0.133732363582 -0.0225759469157 0.01
138 45 -0.192090064287 -0.0225759469157 0.01
138 50 -0.237618684769 -0.0225759469157 0.01
138 55 -0.149159640074 -0.0225759469157 0.01
valid_acc 94.60666666666665
139 0 -0.143952399492 -0.0225759469157 0.01
139 5 -0.168328076601 -0.0225759469157 0.01
139 10 -0.153139159083 -0.0225759469157 0.01
139 15 -0.13072296977 -0.0225759469157 0.01
139 20 -0.19337053597 -0.0225759469157 0.01
139 25 -0.143985912204 -0.0225759469157 0.01
139 30 -0.161205381155 -0.0225759469157 0.01
139 35 -0.188165545464 -0.0225759469157 0.01
139 40 -0.188344046474 -0.0225759469157 0.01
139 45 -0.173031553626 -0.0225759469157 0.01
139 50 -0.208272337914 -0.0225759469157 0.01
139 55 -0.239138156176 -0.0225759469157 0.01
valid_acc 94.40166666666666
140 0 -0.20164886117 -0.0225759469157 0.01
140 5 -0.17806352675 -0.0225759469157 0.01
140 10 -0.162134230137 -0.0225759469157 0.01
140 15 -0.197404265404 -0.0225759469157 0.01
140 20 -0.188803061843 -0.0225759469157 0.01
140 25 -0.167028665543 -0.0225759469157 0.01
140 30 -0.202046126127 -0.0225759469157 0.01
140 35 -0.164006650448 -0.0225759469157 0.01
140 40 -0.138926357031 -0.0225759469157 0.01
140 45 -0.258219361305 -0.0225759469157 0.01
140 50 -0.159151941538 -0.0225759469157 0.01
140 55 -0.170121043921 -0.0225759469157 0.01
valid_acc 94.54333333333334
141 0 -0.176513820887 -0.0225759469157 0.01
141 5 -0.144518882036 -0.0225759469157 0.01
141 10 -0.186203300953 -0.0225759469157 0.01
141 15 -0.16810375452 -0.0225759469157 0.01
141 20 -0.192268252373 -0.0225759469157 0.01
141 25 -0.143218830228 -0.0225759469157 0.01
141 30 -0.174589142203 -0.0225759469157 0.01
141 35 -0.228543698788 -0.0225759469157 0.01
141 40 -0.147233203053 -0.0225759469157 0.01
141 45 -0.184536278248 -0.0225759469157 0.01
141 50 -0.23546333611 -0.0225759469157 0.01
141 55 -0.142332330346 -0.0225759469157 0.01
valid_acc 94.90333333333332
best valid_acc 94.90333333333332
142 0 -0.131448179483 -0.0225759469157 0.01
142 5 -0.144482687116 -0.0225759469157 0.01
142 10 -0.143941313028 -0.0225759469157 0.01
142 15 -0.196569278836 -0.0225759469157 0.01
142 20 -0.128836467862 -0.0225759469157 0.01
142 25 -0.171658292413 -0.0225759469157 0.01
142 30 -0.151862055063 -0.0225759469157 0.01
142 35 -0.200655996799 -0.0225759469157 0.01
142 40 -0.191664516926 -0.0225759469157 0.01
142 45 -0.163857787848 -0.0225759469157 0.01
142 50 -0.203410968184 -0.0225759469157 0.01
142 55 -0.200022935867 -0.0225759469157 0.01
valid_acc 93.75166666666667
143 0 -0.160986095667 -0.0225759469157 0.01
143 5 -0.132465660572 -0.0225759469157 0.01
143 10 -0.197679340839 -0.0225759469157 0.01
143 15 -0.192908719182 -0.0225759469157 0.01
143 20 -0.160520881414 -0.0225759469157 0.01
143 25 -0.21876001358 -0.0225759469157 0.01
143 30 -0.156589433551 -0.0225759469157 0.01
143 35 -0.166540488601 -0.0225759469157 0.01
143 40 -0.1503431499 -0.0225759469157 0.01
143 45 -0.158779352903 -0.0225759469157 0.01
143 50 -0.152430295944 -0.0225759469157 0.01
143 55 -0.146582409739 -0.0225759469157 0.01
valid_acc 94.61166666666668
144 0 -0.178781569004 -0.0225759469157 0.01
144 5 -0.224188327789 -0.0225759469157 0.01
144 10 -0.156041175127 -0.0225759469157 0.01
144 15 -0.159930437803 -0.0225759469157 0.01
144 20 -0.232752352953 -0.0225759469157 0.01
144 25 -0.210471510887 -0.0225759469157 0.01
144 30 -0.172848030925 -0.0225759469157 0.01
144 35 -0.179369568825 -0.0225759469157 0.01
144 40 -0.190026029944 -0.0234796466309 0.01
144 45 -0.163582712412 -0.0234796466309 0.01
144 50 -0.124182239175 -0.0234796466309 0.01
144 55 -0.211038321257 -0.0234796466309 0.01
valid_acc 94.78833333333333
145 0 -0.169937625527 -0.0234796466309 0.01
145 5 -0.180067539215 -0.0234796466309 0.01
145 10 -0.179353952408 -0.0234796466309 0.01
145 15 -0.215123727918 -0.0234796466309 0.01
145 20 -0.127819254994 -0.0234796466309 0.01
145 25 -0.196751311421 -0.0234796466309 0.01
145 30 -0.133528843522 -0.0234796466309 0.01
145 35 -0.2129997015 -0.0234796466309 0.01
145 40 -0.179653540254 -0.0234796466309 0.01
145 45 -0.126202493906 -0.0234796466309 0.01
145 50 -0.128192946315 -0.0234796466309 0.01
145 55 -0.165745645761 -0.0234796466309 0.01
valid_acc 95.0
best valid_acc 95.0
146 0 -0.16786134243 -0.0234796466309 0.01
146 5 -0.128419816494 -0.0234796466309 0.01
146 10 -0.263108968735 -0.0234796466309 0.01
146 15 -0.188303828239 -0.0234796466309 0.01
146 20 -0.213653430343 -0.0234796466309 0.01
146 25 -0.173540249467 -0.0234796466309 0.01
146 30 -0.173484623432 -0.0234796466309 0.01
146 35 -0.178328543901 -0.0234796466309 0.01
146 40 -0.212755650282 -0.0234796466309 0.01
146 45 -0.213079586625 -0.0234796466309 0.01
146 50 -0.180069372058 -0.0234796466309 0.01
146 55 -0.168479800224 -0.0234796466309 0.01
valid_acc 94.58166666666666
147 0 -0.167419850826 -0.0234796466309 0.01
147 5 -0.187568858266 -0.0234796466309 0.01
147 10 -0.184172689915 -0.0234796466309 0.01
147 15 -0.211850062013 -0.0234796466309 0.01
147 20 -0.162324488163 -0.0234796466309 0.01
147 25 -0.180383473635 -0.0234796466309 0.01
147 30 -0.149541586637 -0.0234796466309 0.01
147 35 -0.176555559039 -0.0234796466309 0.01
147 40 -0.23131814599 -0.0234796466309 0.01
147 45 -0.219373106956 -0.0234796466309 0.01
147 50 -0.15255908668 -0.0234796466309 0.01
147 55 -0.162421822548 -0.0234796466309 0.01
valid_acc 94.16166666666666
148 0 -0.148230046034 -0.0234796466309 0.01
148 5 -0.16827686131 -0.0234796466309 0.01
148 10 -0.132015407085 -0.0234796466309 0.01
148 15 -0.19954675436 -0.0234796466309 0.01
148 20 -0.224714025855 -0.0234796466309 0.01
148 25 -0.211595863104 -0.0234796466309 0.01
148 30 -0.175767824054 -0.0234796466309 0.01
148 35 -0.168140023947 -0.0234796466309 0.01
148 40 -0.255227148533 -0.0234796466309 0.01
148 45 -0.222752228379 -0.0234796466309 0.01
148 50 -0.13370577991 -0.0234796466309 0.01
148 55 -0.236403152347 -0.0234796466309 0.01
valid_acc 94.485
149 0 -0.189185321331 -0.0234796466309 0.01
149 5 -0.148595631123 -0.0234796466309 0.01
149 10 -0.19100612402 -0.0234796466309 0.01
149 15 -0.251616001129 -0.0234796466309 0.01
149 20 -0.179991602898 -0.0234796466309 0.01
149 25 -0.172723844647 -0.0234796466309 0.01
149 30 -0.183736979961 -0.0234796466309 0.01
149 35 -0.18945646286 -0.0234796466309 0.01
149 40 -0.155259564519 -0.0234796466309 0.01
149 45 -0.152549624443 -0.0234796466309 0.01
149 50 -0.178084298968 -0.0234796466309 0.01
149 55 -0.141800075769 -0.0234796466309 0.01
valid_acc 94.58666666666666
150 0 -0.201980024576 -0.0234796466309 0.01
150 5 -0.173543214798 -0.0234796466309 0.01
150 10 -0.159363314509 -0.0234796466309 0.01
150 15 -0.200635716319 -0.0234796466309 0.01
150 20 -0.189240559936 -0.0234796466309 0.01
150 25 -0.147536352277 -0.0234796466309 0.01
150 30 -0.132745400071 -0.0234796466309 0.01
150 35 -0.13796825707 -0.0234796466309 0.01
150 40 -0.169795572758 -0.0234796466309 0.01
150 45 -0.175090864301 -0.0234796466309 0.01
150 50 -0.180858597159 -0.0234796466309 0.01
150 55 -0.172117978334 -0.0234796466309 0.01
valid_acc 94.35666666666667
151 0 -0.176593154669 -0.0234796466309 0.01
151 5 -0.194706723094 -0.0234796466309 0.01
151 10 -0.155712544918 -0.0234796466309 0.01
151 15 -0.183915004134 -0.0234796466309 0.01
151 20 -0.154330149293 -0.0234796466309 0.01
151 25 -0.214924186468 -0.0234796466309 0.01
151 30 -0.193877264857 -0.0234796466309 0.01
151 35 -0.180536165833 -0.0234796466309 0.01
151 40 -0.1756118536 -0.0234796466309 0.01
151 45 -0.154808297753 -0.0234796466309 0.01
151 50 -0.216542050242 -0.0234796466309 0.01
151 55 -0.124355360866 -0.0234796466309 0.01
valid_acc 94.71166666666667
152 0 -0.211278274655 -0.0234796466309 0.01
152 5 -0.160899907351 -0.0234796466309 0.01
152 10 -0.166385099292 -0.0234796466309 0.01
152 15 -0.24293397367 -0.0234796466309 0.01
152 20 -0.221559986472 -0.0234796466309 0.01
152 25 -0.203968510032 -0.0234796466309 0.01
152 30 -0.179940745234 -0.0234796466309 0.01
152 35 -0.196825429797 -0.0234796466309 0.01
152 40 -0.185960844159 -0.0234796466309 0.01
152 45 -0.149091497064 -0.0234796466309 0.01
152 50 -0.171173706651 -0.0234796466309 0.01
152 55 -0.173078924417 -0.0234796466309 0.01
valid_acc 94.54166666666667
153 0 -0.221912428737 -0.0234796466309 0.01
153 5 -0.16309671104 -0.0234796466309 0.01
153 10 -0.173858717084 -0.0234796466309 0.01
153 15 -0.136519253254 -0.0234796466309 0.01
153 20 -0.197774767876 -0.0234796466309 0.01
153 25 -0.142001584172 -0.0234796466309 0.01
153 30 -0.147721543908 -0.0234796466309 0.01
153 35 -0.175240278244 -0.0234796466309 0.01
153 40 -0.163756683469 -0.0234796466309 0.01
153 45 -0.212681859732 -0.0234796466309 0.01
153 50 -0.181142032146 -0.0234796466309 0.01
153 55 -0.128692433238 -0.0234796466309 0.01
valid_acc 94.92166666666667
154 0 -0.202488318086 -0.0234796466309 0.01
154 5 -0.180522441864 -0.0234796466309 0.01
154 10 -0.201637297869 -0.0234796466309 0.01
154 15 -0.1802444309 -0.0234796466309 0.01
154 20 -0.228521600366 -0.0234796466309 0.01
154 25 -0.212996244431 -0.0234796466309 0.01
154 30 -0.166349962354 -0.0234796466309 0.01
154 35 -0.195952862501 -0.0234796466309 0.01
154 40 -0.192927718163 -0.0234796466309 0.01
154 45 -0.215912953019 -0.0234796466309 0.01
154 50 -0.183646097779 -0.0234796466309 0.01
154 55 -0.162768125534 -0.0234796466309 0.01
valid_acc 94.78333333333333
155 0 -0.217717975378 -0.0234796466309 0.01
155 5 -0.154578626156 -0.0234796466309 0.01
155 10 -0.168813630939 -0.0234796466309 0.01
155 15 -0.206553578377 -0.0234796466309 0.01
155 20 -0.184295549989 -0.0234796466309 0.01
155 25 -0.172110468149 -0.0234796466309 0.01
155 30 -0.173248648643 -0.0234796466309 0.01
155 35 -0.195999220014 -0.0234796466309 0.01
155 40 -0.165391936898 -0.0234796466309 0.01
155 45 -0.182740136981 -0.0234796466309 0.01
155 50 -0.180191025138 -0.0234796466309 0.01
155 55 -0.18237221241 -0.0234796466309 0.01
valid_acc 94.77499999999999
156 0 -0.168801650405 -0.0234796466309 0.01
156 5 -0.169090226293 -0.0234796466309 0.01
156 10 -0.166259810328 -0.0234796466309 0.01
156 15 -0.198653787374 -0.0234796466309 0.01
156 20 -0.168218672276 -0.0234796466309 0.01
156 25 -0.183265060186 -0.0234796466309 0.01
156 30 -0.17763954401 -0.0234796466309 0.01
156 35 -0.142482370138 -0.0234796466309 0.01
156 40 -0.187691524625 -0.0234796466309 0.01
156 45 -0.160875573754 -0.0234796466309 0.01
156 50 -0.146002337337 -0.0234796466309 0.01
156 55 -0.212488949299 -0.0234796466309 0.01
valid_acc 95.05333333333333
best valid_acc 95.05333333333333
157 0 -0.186921313405 -0.0234796466309 0.01
157 5 -0.153074190021 -0.0234796466309 0.01
157 10 -0.181754291058 -0.0234796466309 0.01
157 15 -0.196647077799 -0.0234796466309 0.01
157 20 -0.124297313392 -0.0234796466309 0.01
157 25 -0.157356053591 -0.0234796466309 0.01
157 30 -0.174787342548 -0.0234796466309 0.01
157 35 -0.17014631629 -0.0234796466309 0.01
157 40 -0.161299362779 -0.0234796466309 0.01
157 45 -0.224540680647 -0.0234796466309 0.01
157 50 -0.138861864805 -0.0234796466309 0.01
157 55 -0.161266967654 -0.0234796466309 0.01
valid_acc 94.94666666666667
158 0 -0.154365494847 -0.0234796466309 0.01
158 5 -0.113458275795 -0.0234796466309 0.01
158 10 -0.170472607017 -0.0234796466309 0.01
158 15 -0.218707382679 -0.0234796466309 0.01
158 20 -0.139014869928 -0.0234796466309 0.01
158 25 -0.170599922538 -0.0234796466309 0.01
158 30 -0.19030199945 -0.0234796466309 0.01
158 35 -0.147064611316 -0.0234796466309 0.01
158 40 -0.203672215343 -0.0234796466309 0.01
158 45 -0.161482721567 -0.0234796466309 0.01
158 50 -0.167442128062 -0.0234796466309 0.01
158 55 -0.1571867764 -0.0234796466309 0.01
valid_acc 95.07166666666666
best valid_acc 95.07166666666666
159 0 -0.126182720065 -0.0234796466309 0.01
159 5 -0.161749973893 -0.0234796466309 0.01
159 10 -0.123376972973 -0.0234796466309 0.01
159 15 -0.196808740497 -0.0234796466309 0.01
159 20 -0.160571321845 -0.0234796466309 0.01
159 25 -0.184516817331 -0.0234796466309 0.01
159 30 -0.160005182028 -0.0234796466309 0.01
159 35 -0.171041458845 -0.0234796466309 0.01
159 40 -0.164963006973 -0.0234796466309 0.01
159 45 -0.222681507468 -0.0234796466309 0.01
159 50 -0.183442637324 -0.0234796466309 0.01
159 55 -0.122710816562 -0.0234796466309 0.01
valid_acc 94.87
160 0 -0.165740266442 -0.0234796466309 0.01
160 5 -0.176374301314 -0.0234796466309 0.01
160 10 -0.141366526484 -0.0234796466309 0.01
160 15 -0.194056153297 -0.0234796466309 0.01
160 20 -0.183043390512 -0.0234796466309 0.01
160 25 -0.198159471154 -0.0234796466309 0.01
160 30 -0.14022949338 -0.0234796466309 0.01
160 35 -0.120392054319 -0.0234796466309 0.01
160 40 -0.114527538419 -0.0234796466309 0.01
160 45 -0.144234105945 -0.0234796466309 0.01
160 50 -0.139109060168 -0.0234796466309 0.01
160 55 -0.166837483644 -0.0234796466309 0.01
valid_acc 95.11
best valid_acc 95.11
161 0 -0.12915353477 -0.0234796466309 0.01
161 5 -0.183421611786 -0.0234796466309 0.01
161 10 -0.131204873323 -0.0234796466309 0.01
161 15 -0.157734706998 -0.0234796466309 0.01
161 20 -0.182372227311 -0.0234796466309 0.01
161 25 -0.171504110098 -0.0234796466309 0.01
161 30 -0.184565991163 -0.0234796466309 0.01
161 35 -0.141305446625 -0.0234796466309 0.01
161 40 -0.167975217104 -0.0234796466309 0.01
161 45 -0.169041648507 -0.0234796466309 0.01
161 50 -0.220979049802 -0.0234796466309 0.01
161 55 -0.184178605676 -0.0234796466309 0.01
valid_acc 94.38
162 0 -0.161689832807 -0.0234796466309 0.01
162 5 -0.14927457273 -0.0234796466309 0.01
162 10 -0.154666736722 -0.0234796466309 0.01
162 15 -0.161314204335 -0.0234796466309 0.01
162 20 -0.192316219211 -0.0234796466309 0.01
162 25 -0.165348127484 -0.0234796466309 0.01
162 30 -0.157969623804 -0.0234796466309 0.01
162 35 -0.151905089617 -0.0234796466309 0.01
162 40 -0.155960544944 -0.0234796466309 0.01
162 45 -0.205649763346 -0.0234796466309 0.01
162 50 -0.200730413198 -0.0234796466309 0.01
162 55 -0.169504448771 -0.0234796466309 0.01
valid_acc 94.845
163 0 -0.218370974064 -0.0234796466309 0.01
163 5 -0.14111559093 -0.0234796466309 0.01
163 10 -0.168515384197 -0.0234796466309 0.01
163 15 -0.184047743678 -0.0234796466309 0.01
163 20 -0.205112442374 -0.0234796466309 0.01
163 25 -0.168580159545 -0.0234796466309 0.01
163 30 -0.166560038924 -0.0234796466309 0.01
163 35 -0.125827923417 -0.0234796466309 0.01
163 40 -0.170971661806 -0.0234796466309 0.01
163 45 -0.160611331463 -0.0234796466309 0.01
163 50 -0.158219814301 -0.0234796466309 0.01
163 55 -0.229155004025 -0.0234796466309 0.01
valid_acc 94.95166666666667
164 0 -0.186562716961 -0.0234796466309 0.01
164 5 -0.172519266605 -0.0234796466309 0.01
164 10 -0.153182864189 -0.0234796466309 0.01
164 15 -0.165679812431 -0.0234796466309 0.01
164 20 -0.158565282822 -0.0234796466309 0.01
164 25 -0.143414989114 -0.0234796466309 0.01
164 30 -0.145477756858 -0.0234796466309 0.01
164 35 -0.229333847761 -0.0234796466309 0.01
164 40 -0.167766585946 -0.0234796466309 0.01
164 45 -0.191423669457 -0.0234796466309 0.01
164 50 -0.150397464633 -0.0234796466309 0.01
164 55 -0.170861840248 -0.0234796466309 0.01
valid_acc 95.03166666666667
165 0 -0.172723427415 -0.0234796466309 0.01
165 5 -0.140438914299 -0.0234796466309 0.01
165 10 -0.163912668824 -0.0234796466309 0.01
165 15 -0.179715886712 -0.0234796466309 0.01
165 20 -0.146998137236 -0.0234796466309 0.01
165 25 -0.16287368536 -0.0234796466309 0.01
165 30 -0.153811603785 -0.0234796466309 0.01
165 35 -0.157534703612 -0.0234796466309 0.01
165 40 -0.159765288234 -0.0234796466309 0.01
165 45 -0.230780273676 -0.0234796466309 0.01
165 50 -0.12267742306 -0.0234796466309 0.01
165 55 -0.160629302263 -0.0234796466309 0.01
valid_acc 95.17166666666667
best valid_acc 95.17166666666667
166 0 -0.170930102468 -0.0234796466309 0.01
166 5 -0.110160417855 -0.0234796466309 0.01
166 10 -0.181509628892 -0.0234796466309 0.01
166 15 -0.153786182404 -0.0234796466309 0.01
166 20 -0.169114500284 -0.0234796466309 0.01
166 25 -0.210642695427 -0.0234796466309 0.01
166 30 -0.171143233776 -0.0234796466309 0.01
166 35 -0.149185121059 -0.0234796466309 0.01
166 40 -0.113603234291 -0.0234796466309 0.01
166 45 -0.140393644571 -0.0234796466309 0.01
166 50 -0.167183622718 -0.0234796466309 0.01
166 55 -0.133756607771 -0.0234796466309 0.01
valid_acc 94.83666666666667
167 0 -0.174850687385 -0.0234796466309 0.01
167 5 -0.179792702198 -0.0234796466309 0.01
167 10 -0.151247859001 -0.0234796466309 0.01
167 15 -0.17756485939 -0.0234796466309 0.01
167 20 -0.147750884295 -0.0234796466309 0.01
167 25 -0.177868187428 -0.0234796466309 0.01
167 30 -0.146681383252 -0.0234796466309 0.01
167 35 -0.174395099282 -0.0234796466309 0.01
167 40 -0.138187870383 -0.0234796466309 0.01
167 45 -0.161239176989 -0.0234796466309 0.01
167 50 -0.143890053034 -0.0234796466309 0.01
167 55 -0.159237906337 -0.0234796466309 0.01
valid_acc 94.94333333333333
168 0 -0.164242237806 -0.0234796466309 0.01
168 5 -0.209232777357 -0.0234796466309 0.01
168 10 -0.109853863716 -0.0234796466309 0.01
168 15 -0.174685567617 -0.0234796466309 0.01
168 20 -0.156632691622 -0.0234796466309 0.01
168 25 -0.196191385388 -0.0234796466309 0.01
168 30 -0.140326648951 -0.0234796466309 0.01
168 35 -0.178463250399 -0.0234796466309 0.01
168 40 -0.0989509746432 -0.0234796466309 0.01
168 45 -0.168328747153 -0.0234796466309 0.01
168 50 -0.159474104643 -0.0234796466309 0.01
168 55 -0.207723557949 -0.0234796466309 0.01
valid_acc 94.85166666666667
169 0 -0.172949761152 -0.0234796466309 0.01
169 5 -0.191368803382 -0.0234796466309 0.01
169 10 -0.149551331997 -0.0234796466309 0.01
169 15 -0.213785916567 -0.0234796466309 0.01
169 20 -0.193080931902 -0.0234796466309 0.01
169 25 -0.150495663285 -0.0234796466309 0.01
169 30 -0.139462649822 -0.0234796466309 0.01
169 35 -0.160988301039 -0.0234796466309 0.01
169 40 -0.165242731571 -0.0234796466309 0.01
169 45 -0.135378047824 -0.0234796466309 0.01
169 50 -0.179071098566 -0.0234796466309 0.01
169 55 -0.102779872715 -0.0234796466309 0.01
valid_acc 95.065
170 0 -0.149333253503 -0.0234796466309 0.01
170 5 -0.187493026257 -0.0234796466309 0.01
170 10 -0.186504140496 -0.0234796466309 0.01
170 15 -0.180115863681 -0.0234796466309 0.01
170 20 -0.170855730772 -0.0234796466309 0.01
170 25 -0.146202087402 -0.0234796466309 0.01
170 30 -0.177524060011 -0.0234796466309 0.01
170 35 -0.141504153609 -0.0234796466309 0.01
170 40 -0.149613127112 -0.0234796466309 0.01
170 45 -0.176535665989 -0.0234796466309 0.01
170 50 -0.147224605083 -0.0234796466309 0.01
170 55 -0.138704940677 -0.0234796466309 0.01
valid_acc 95.17999999999999
best valid_acc 95.17999999999999
171 0 -0.172290086746 -0.0234796466309 0.01
171 5 -0.141457825899 -0.0234796466309 0.01
171 10 -0.187204405665 -0.0234796466309 0.01
171 15 -0.138975277543 -0.0234796466309 0.01
171 20 -0.165136069059 -0.0234796466309 0.01
171 25 -0.16422533989 -0.0234796466309 0.01
171 30 -0.147779166698 -0.0234796466309 0.01
171 35 -0.210170790553 -0.0234796466309 0.01
171 40 -0.114490620792 -0.0234796466309 0.01
171 45 -0.189174234867 -0.0234796466309 0.01
171 50 -0.120984241366 -0.0234796466309 0.01
171 55 -0.149504423141 -0.0234796466309 0.01
valid_acc 95.10499999999999
172 0 -0.185587137938 -0.0234796466309 0.01
172 5 -0.144920513034 -0.0234796466309 0.01
172 10 -0.188914373517 -0.0234796466309 0.01
172 15 -0.170049339533 -0.0234796466309 0.01
172 20 -0.201762348413 -0.0234796466309 0.01
172 25 -0.173324033618 -0.0234796466309 0.01
172 30 -0.149161994457 -0.0234796466309 0.01
172 35 -0.135534793139 -0.0234796466309 0.01
172 40 -0.144252449274 -0.0234796466309 0.01
172 45 -0.184356272221 -0.0234796466309 0.01
172 50 -0.141338020563 -0.0234796466309 0.01
172 55 -0.174240678549 -0.0234796466309 0.01
valid_acc 95.175
173 0 -0.131397992373 -0.0234796466309 0.01
173 5 -0.137181550264 -0.0234796466309 0.01
173 10 -0.177270650864 -0.0234796466309 0.01
173 15 -0.170172661543 -0.0234796466309 0.01
173 20 -0.193031787872 -0.0234796466309 0.01
173 25 -0.160728797317 -0.0234796466309 0.01
173 30 -0.133830666542 -0.0234796466309 0.01
173 35 -0.178264081478 -0.0234796466309 0.01
173 40 -0.109129756689 -0.0234796466309 0.01
173 45 -0.128413543105 -0.0234796466309 0.01
173 50 -0.174625441432 -0.0234796466309 0.01
173 55 -0.178703397512 -0.0234796466309 0.01
valid_acc 94.8
174 0 -0.193395152688 -0.0234796466309 0.01
174 5 -0.125002473593 -0.0234796466309 0.01
174 10 -0.124252669513 -0.0234796466309 0.01
174 15 -0.188521981239 -0.0234796466309 0.01
174 20 -0.167883217335 -0.0234796466309 0.01
174 25 -0.186045125127 -0.0234796466309 0.01
174 30 -0.143696725368 -0.0234796466309 0.01
174 35 -0.131195694208 -0.0234796466309 0.01
174 40 -0.155344754457 -0.0234796466309 0.01
174 45 -0.144891276956 -0.0234796466309 0.01
174 50 -0.200125068426 -0.0234796466309 0.01
174 55 -0.138259604573 -0.0234796466309 0.01
valid_acc 95.04
175 0 -0.170243233442 -0.0234796466309 0.01
175 5 -0.167015701532 -0.0234796466309 0.01
175 10 -0.236837208271 -0.0234796466309 0.01
175 15 -0.175413772464 -0.0234796466309 0.01
175 20 -0.133479088545 -0.0234796466309 0.01
175 25 -0.190456464887 -0.0234796466309 0.01
175 30 -0.120535507798 -0.0234796466309 0.01
175 35 -0.1593529284 -0.0234796466309 0.01
175 40 -0.145481154323 -0.0234796466309 0.01
175 45 -0.168149486184 -0.0234796466309 0.01
175 50 -0.16846549511 -0.0255046946751 0.01
175 55 -0.155435442924 -0.0255046946751 0.01
valid_acc 95.11500000000001
176 0 -0.198949247599 -0.0255046946751 0.01
176 5 -0.176076635718 -0.0255046946751 0.01
176 10 -0.181024983525 -0.0255046946751 0.01
176 15 -0.151682332158 -0.0255046946751 0.01
176 20 -0.161668419838 -0.0255046946751 0.01
176 25 -0.17996019125 -0.0255046946751 0.01
176 30 -0.126373022795 -0.0255046946751 0.01
176 35 -0.134111315012 -0.0255046946751 0.01
176 40 -0.120913118124 -0.0255046946751 0.01
176 45 -0.200207129121 -0.0255046946751 0.01
176 50 -0.161553651094 -0.0255046946751 0.01
176 55 -0.129296720028 -0.0255046946751 0.01
valid_acc 94.77333333333333
177 0 -0.180397331715 -0.0255046946751 0.01
177 5 -0.150705620646 -0.0255046946751 0.01
177 10 -0.15338280797 -0.0255046946751 0.01
177 15 -0.148124963045 -0.0255046946751 0.01
177 20 -0.176832079887 -0.0255046946751 0.01
177 25 -0.254689991474 -0.0255046946751 0.01
177 30 -0.203389823437 -0.0255046946751 0.01
177 35 -0.166807129979 -0.0255046946751 0.01
177 40 -0.16334412992 -0.0255046946751 0.01
177 45 -0.135880485177 -0.0255046946751 0.01
177 50 -0.159860208631 -0.0255046946751 0.01
177 55 -0.121558494866 -0.0255046946751 0.01
valid_acc 95.24000000000001
best valid_acc 95.24000000000001
178 0 -0.158327043056 -0.0255046946751 0.01
178 5 -0.159377977252 -0.0255046946751 0.01
178 10 -0.150695458055 -0.0255046946751 0.01
178 15 -0.208715304732 -0.0255046946751 0.01
178 20 -0.121600233018 -0.0255046946751 0.01
178 25 -0.171353131533 -0.0255046946751 0.01
178 30 -0.158432483673 -0.0255046946751 0.01
178 35 -0.139372646809 -0.0255046946751 0.01
178 40 -0.174942851067 -0.0255046946751 0.01
178 45 -0.133013322949 -0.0255046946751 0.01
178 50 -0.195589736104 -0.0255046946751 0.01
178 55 -0.125329390168 -0.0255046946751 0.01
valid_acc 95.38666666666667
best valid_acc 95.38666666666667
179 0 -0.130092471838 -0.0255046946751 0.01
179 5 -0.242043584585 -0.0255046946751 0.01
179 10 -0.162405073643 -0.0255046946751 0.01
179 15 -0.221665501595 -0.0255046946751 0.01
179 20 -0.12471331656 -0.0255046946751 0.01
179 25 -0.17037679255 -0.0255046946751 0.01
179 30 -0.175672248006 -0.0255046946751 0.01
179 35 -0.177236810327 -0.0255046946751 0.01
179 40 -0.151250705123 -0.0255046946751 0.01
179 45 -0.151815116405 -0.0255046946751 0.01
179 50 -0.186184152961 -0.0255046946751 0.01
179 55 -0.141337603331 -0.0255046946751 0.01
valid_acc 95.24666666666667
180 0 -0.189595609903 -0.0255046946751 0.01
180 5 -0.178843453526 -0.0255046946751 0.01
180 10 -0.217539951205 -0.0255046946751 0.01
180 15 -0.140770897269 -0.0255046946751 0.01
180 20 -0.210136830807 -0.0255046946751 0.01
180 25 -0.147419825196 -0.0255046946751 0.01
180 30 -0.136648774147 -0.0255046946751 0.01
180 35 -0.135064557195 -0.0255046946751 0.01
180 40 -0.247639223933 -0.0255046946751 0.01
180 45 -0.180200725794 -0.0255046946751 0.01
180 50 -0.142220839858 -0.0255046946751 0.01
180 55 -0.15209043026 -0.0255046946751 0.01
valid_acc 95.36
181 0 -0.144280657172 -0.0255046946751 0.01
181 5 -0.166983649135 -0.0255046946751 0.01
181 10 -0.207566171885 -0.0255046946751 0.01
181 15 -0.149750113487 -0.0255046946751 0.01
181 20 -0.212176188827 -0.0255046946751 0.01
181 25 -0.147657766938 -0.0255046946751 0.01
181 30 -0.166867345572 -0.0255046946751 0.01
181 35 -0.17311924696 -0.0255046946751 0.01
181 40 -0.178051486611 -0.0255046946751 0.01
181 45 -0.172588795424 -0.0255046946751 0.01
181 50 -0.139477416873 -0.0255046946751 0.01
181 55 -0.157204180956 -0.0255046946751 0.01
valid_acc 95.27333333333333
182 0 -0.205904126167 -0.0255046946751 0.01
182 5 -0.190776616335 -0.0255046946751 0.01
182 10 -0.172038987279 -0.0255046946751 0.01
182 15 -0.209704264998 -0.0239676150554 0.01
182 20 -0.164635255933 -0.0239676150554 0.01
182 25 -0.161621958017 -0.0239676150554 0.01
182 30 -0.14273737371 -0.0239676150554 0.01
182 35 -0.146237775683 -0.0239676150554 0.01
182 40 -0.132487043738 -0.0239676150554 0.01
182 45 -0.121395282447 -0.0239676150554 0.01
182 50 -0.155121430755 -0.0239676150554 0.01
182 55 -0.219761118293 -0.0239676150554 0.01
valid_acc 95.03666666666668
183 0 -0.127816125751 -0.0239676150554 0.01
183 5 -0.166243374348 -0.0239676150554 0.01
183 10 -0.150893673301 -0.0239676150554 0.01
183 15 -0.155015826225 -0.0239676150554 0.01
183 20 -0.187863454223 -0.0239676150554 0.01
183 25 -0.147670388222 -0.0239676150554 0.01
183 30 -0.171058014035 -0.0239676150554 0.01
183 35 -0.1754950881 -0.0239676150554 0.01
183 40 -0.230867594481 -0.0239676150554 0.01
183 45 -0.123605445027 -0.0239676150554 0.01
183 50 -0.185997933149 -0.0239676150554 0.01
183 55 -0.166093826294 -0.0239676150554 0.01
valid_acc 95.26333333333334
184 0 -0.140696913004 -0.0239676150554 0.01
184 5 -0.163656949997 -0.0239676150554 0.01
184 10 -0.139318078756 -0.0239676150554 0.01
184 15 -0.189434960485 -0.0239676150554 0.01
184 20 -0.134331256151 -0.0239676150554 0.01
184 25 -0.15221272409 -0.0239676150554 0.01
184 30 -0.127339884639 -0.0239676150554 0.01
184 35 -0.139913260937 -0.0239676150554 0.01
184 40 -0.163229122758 -0.0239676150554 0.01
184 45 -0.118083409965 -0.0239676150554 0.01
184 50 -0.129397362471 -0.0239676150554 0.01
184 55 -0.128458604217 -0.0239676150554 0.01
valid_acc 95.07166666666666
185 0 -0.1866453439 -0.0239676150554 0.01
185 5 -0.232474774122 -0.0239676150554 0.01
185 10 -0.228851050138 -0.0239676150554 0.01
185 15 -0.228635326028 -0.0239676150554 0.01
185 20 -0.175142794847 -0.0239676150554 0.01
185 25 -0.163976863027 -0.0239676150554 0.01
185 30 -0.179980412126 -0.0239676150554 0.01
185 35 -0.175288721919 -0.0239676150554 0.01
185 40 -0.147655531764 -0.0239676150554 0.01
185 45 -0.153740406036 -0.0239676150554 0.01
185 50 -0.122549027205 -0.0239676150554 0.01
185 55 -0.158002898097 -0.0239676150554 0.01
valid_acc 95.035
186 0 -0.165772393346 -0.0239676150554 0.01
186 5 -0.17759616673 -0.0239676150554 0.01
186 10 -0.172274276614 -0.0239676150554 0.01
186 15 -0.0983661338687 -0.0239676150554 0.01
186 20 -0.194556102157 -0.0239676150554 0.01
186 25 -0.181467920542 -0.0239676150554 0.01
186 30 -0.143707767129 -0.0239676150554 0.01
186 35 -0.186912566423 -0.0239676150554 0.01
186 40 -0.146136388183 -0.0239676150554 0.01
186 45 -0.15105471015 -0.0239676150554 0.01
186 50 -0.168268978596 -0.0239676150554 0.01
186 55 -0.159911558032 -0.0239676150554 0.01
valid_acc 95.19
187 0 -0.150129944086 -0.0239676150554 0.01
187 5 -0.151745930314 -0.0239676150554 0.01
187 10 -0.157633811235 -0.0239676150554 0.01
187 15 -0.201604634523 -0.0239676150554 0.01
187 20 -0.160894244909 -0.0239676150554 0.01
187 25 -0.123098865151 -0.0239676150554 0.01
187 30 -0.143561214209 -0.0239676150554 0.01
187 35 -0.135856896639 -0.0239676150554 0.01
187 40 -0.245998799801 -0.0239676150554 0.01
187 45 -0.186271458864 -0.0239676150554 0.01
187 50 -0.129833221436 -0.0239676150554 0.01
187 55 -0.106386378407 -0.0239676150554 0.01
valid_acc 95.36166666666666
188 0 -0.168383747339 -0.0239676150554 0.01
188 5 -0.185044556856 -0.0239676150554 0.01
188 10 -0.113095425069 -0.0239676150554 0.01
188 15 -0.137869566679 -0.0239676150554 0.01
188 20 -0.132856160402 -0.0239676150554 0.01
188 25 -0.227620571852 -0.0239676150554 0.01
188 30 -0.170371472836 -0.0239676150554 0.01
188 35 -0.204365536571 -0.0239676150554 0.01
188 40 -0.147730052471 -0.0239676150554 0.01
188 45 -0.190593153238 -0.0239676150554 0.01
188 50 -0.170120924711 -0.0239676150554 0.01
188 55 -0.131215274334 -0.0239676150554 0.01
valid_acc 95.21
189 0 -0.132639601827 -0.0239676150554 0.01
189 5 -0.200348839164 -0.0239676150554 0.01
189 10 -0.18825417757 -0.0239676150554 0.01
189 15 -0.131522119045 -0.0239676150554 0.01
189 20 -0.171320945024 -0.0239676150554 0.01
189 25 -0.167435780168 -0.0239676150554 0.01
189 30 -0.190711483359 -0.0239676150554 0.01
189 35 -0.163420587778 -0.0239676150554 0.01
189 40 -0.170301631093 -0.0239676150554 0.01
189 45 -0.160274982452 -0.0239676150554 0.01
189 50 -0.185533553362 -0.0239676150554 0.01
189 55 -0.136169195175 -0.0239676150554 0.01
valid_acc 95.30333333333333
190 0 -0.166367128491 -0.0239676150554 0.01
190 5 -0.195768326521 -0.0239676150554 0.01
190 10 -0.140797972679 -0.0239676150554 0.01
190 15 -0.126630738378 -0.0239676150554 0.01
190 20 -0.1372410357 -0.0239676150554 0.01
190 25 -0.160632416606 -0.0239676150554 0.01
190 30 -0.203458368778 -0.0239676150554 0.01
190 35 -0.186785086989 -0.0239676150554 0.01
190 40 -0.154414281249 -0.0239676150554 0.01
190 45 -0.17876149714 -0.0239676150554 0.01
190 50 -0.299386709929 -0.0239676150554 0.01
190 55 -0.154163867235 -0.0239676150554 0.01
valid_acc 94.95333333333333
191 0 -0.144308626652 -0.0239676150554 0.01
191 5 -0.178204283118 -0.0239676150554 0.01
191 10 -0.173288136721 -0.0239676150554 0.01
191 15 -0.150782972574 -0.0239676150554 0.01
191 20 -0.127862274647 -0.0239676150554 0.01
191 25 -0.161113142967 -0.0239676150554 0.01
191 30 -0.144841492176 -0.0239676150554 0.01
191 35 -0.177160292864 -0.0239676150554 0.01
191 40 -0.128405898809 -0.0239676150554 0.01
191 45 -0.154437422752 -0.0239676150554 0.01
191 50 -0.125113636255 -0.0239676150554 0.01
191 55 -0.148060277104 -0.0239676150554 0.01
valid_acc 94.94166666666666
192 0 -0.143423721194 -0.0239676150554 0.01
192 5 -0.162306278944 -0.0239676150554 0.01
192 10 -0.185855984688 -0.0239676150554 0.01
192 15 -0.12891818583 -0.0239676150554 0.01
192 20 -0.15031671524 -0.0239676150554 0.01
192 25 -0.188611581922 -0.0239676150554 0.01
192 30 -0.13440836966 -0.0239676150554 0.01
192 35 -0.167601138353 -0.0239676150554 0.01
192 40 -0.182400882244 -0.0239676150554 0.01
192 45 -0.17520429194 -0.0239676150554 0.01
192 50 -0.197066470981 -0.0239676150554 0.01
192 55 -0.175356969237 -0.0239676150554 0.01
valid_acc 95.25166666666667
193 0 -0.134393304586 -0.0239676150554 0.01
193 5 -0.197366684675 -0.0239676150554 0.01
193 10 -0.131065219641 -0.0239676150554 0.01
193 15 -0.125608414412 -0.0239676150554 0.01
193 20 -0.150090157986 -0.0239676150554 0.01
193 25 -0.15163128078 -0.0239676150554 0.01
193 30 -0.148396521807 -0.0239676150554 0.01
193 35 -0.146360650659 -0.0239676150554 0.01
193 40 -0.137050151825 -0.0239676150554 0.01
193 45 -0.197023928165 -0.0239676150554 0.01
193 50 -0.15667450428 -0.0239676150554 0.01
193 55 -0.19219301641 -0.0239676150554 0.01
valid_acc 95.47333333333333
best valid_acc 95.47333333333333
194 0 -0.160808861256 -0.0239676150554 0.01
194 5 -0.164638713002 -0.0239676150554 0.01
194 10 -0.139914497733 -0.0239676150554 0.01
194 15 -0.16273920238 -0.0239676150554 0.01
194 20 -0.17604534328 -0.0239676150554 0.01
194 25 -0.107944756746 -0.0239676150554 0.01
194 30 -0.0903751179576 -0.0239676150554 0.01
194 35 -0.137238055468 -0.0239676150554 0.01
194 40 -0.131187111139 -0.0239676150554 0.01
194 45 -0.143352791667 -0.0239676150554 0.01
194 50 -0.153982982039 -0.0239676150554 0.01
194 55 -0.154196813703 -0.0239676150554 0.01
valid_acc 95.29166666666666
195 0 -0.143903836608 -0.0239676150554 0.01
195 5 -0.155128508806 -0.0239676150554 0.01
195 10 -0.128600075841 -0.0239676150554 0.01
195 15 -0.180333599448 -0.0239676150554 0.01
195 20 -0.176075980067 -0.0239676150554 0.01
195 25 -0.197136193514 -0.0239676150554 0.01
195 30 -0.1329010427 -0.0239676150554 0.01
195 35 -0.192487031221 -0.0239676150554 0.01
195 40 -0.142303094268 -0.0239676150554 0.01
195 45 -0.107255294919 -0.0239676150554 0.01
195 50 -0.189467847347 -0.0239676150554 0.01
195 55 -0.156763702631 -0.0239676150554 0.01
valid_acc 95.05833333333334
196 0 -0.207820549607 -0.0239676150554 0.01
196 5 -0.175095617771 -0.0239676150554 0.01
196 10 -0.160495758057 -0.0239676150554 0.01
196 15 -0.150477468967 -0.0239676150554 0.01
196 20 -0.195050656796 -0.0239676150554 0.01
196 25 -0.182313263416 -0.0239676150554 0.01
196 30 -0.201203674078 -0.0239676150554 0.01
196 35 -0.176768645644 -0.0239676150554 0.01
196 40 -0.167675048113 -0.0239676150554 0.01
196 45 -0.105434887111 -0.0239676150554 0.01
196 50 -0.141198709607 -0.0239676150554 0.01
196 55 -0.154984936118 -0.0239676150554 0.01
valid_acc 95.65333333333334
best valid_acc 95.65333333333334
197 0 -0.138453394175 -0.0239676150554 0.01
197 5 -0.114819131792 -0.0239676150554 0.01
197 10 -0.219600975513 -0.0239676150554 0.01
197 15 -0.148621439934 -0.0239676150554 0.01
197 20 -0.196411475539 -0.0239676150554 0.01
197 25 -0.190305754542 -0.0239676150554 0.01
197 30 -0.112037278712 -0.0239676150554 0.01
197 35 -0.142181053758 -0.0239676150554 0.01
197 40 -0.19714589417 -0.0239676150554 0.01
197 45 -0.1549154073 -0.0239676150554 0.01
197 50 -0.131572172046 -0.0239676150554 0.01
197 55 -0.145214378834 -0.0239676150554 0.01
valid_acc 95.195
198 0 -0.150072962046 -0.0239676150554 0.01
198 5 -0.166116923094 -0.0239676150554 0.01
198 10 -0.123103193939 -0.0239676150554 0.01
198 15 -0.200213760138 -0.0239676150554 0.01
198 20 -0.147432714701 -0.0239676150554 0.01
198 25 -0.108407966793 -0.0239676150554 0.01
198 30 -0.178076177835 -0.0239676150554 0.01
198 35 -0.198897108436 -0.0239676150554 0.01
198 40 -0.141466513276 -0.0239676150554 0.01
198 45 -0.117314524949 -0.0239676150554 0.01
198 50 -0.130285724998 -0.0239676150554 0.01
198 55 -0.165148198605 -0.0239676150554 0.01
valid_acc 95.37666666666667
199 0 -0.1109290272 -0.0239676150554 0.01
199 5 -0.138785794377 -0.0239676150554 0.01
199 10 -0.124226406217 -0.0239676150554 0.01
199 15 -0.214608475566 -0.0239676150554 0.01
199 20 -0.142828673124 -0.0239676150554 0.01
199 25 -0.21571393311 -0.0239676150554 0.01
199 30 -0.148644313216 -0.0239676150554 0.01
199 35 -0.212895601988 -0.0239676150554 0.01
199 40 -0.157059580088 -0.0239676150554 0.01
199 45 -0.136898905039 -0.0239676150554 0.01
199 50 -0.182079046965 -0.0239676150554 0.01
199 55 -0.154872059822 -0.0239676150554 0.01
valid_acc 94.92833333333334
200 0 -0.171515762806 -0.0239676150554 0.01
200 5 -0.14194868505 -0.0239676150554 0.01
200 10 -0.142963424325 -0.0239676150554 0.01
200 15 -0.165827795863 -0.0239676150554 0.01
200 20 -0.153740331531 -0.0239676150554 0.01
200 25 -0.182998865843 -0.0239676150554 0.01
200 30 -0.153435513377 -0.0239676150554 0.01
200 35 -0.173534676433 -0.0239676150554 0.01
200 40 -0.159210190177 -0.0239676150554 0.01
200 45 -0.177729457617 -0.0239676150554 0.01
200 50 -0.168274343014 -0.0239676150554 0.01
200 55 -0.142579138279 -0.0239676150554 0.01
valid_acc 95.25833333333334
201 0 -0.179186075926 -0.0239676150554 0.01
201 5 -0.121770083904 -0.0239676150554 0.01
201 10 -0.151733860373 -0.0239676150554 0.01
201 15 -0.182121858001 -0.0239676150554 0.01
201 20 -0.17249417305 -0.0239676150554 0.01
201 25 -0.202595546842 -0.0239676150554 0.01
201 30 -0.16742439568 -0.0239676150554 0.01
201 35 -0.158464848995 -0.0239676150554 0.01
201 40 -0.14944665134 -0.0239676150554 0.01
201 45 -0.174994811416 -0.0239676150554 0.01
201 50 -0.126104101539 -0.0239676150554 0.01
201 55 -0.151530772448 -0.0239676150554 0.01
valid_acc 95.49166666666666
202 0 -0.137238651514 -0.0239676150554 0.01
202 5 -0.148907363415 -0.0239676150554 0.01
202 10 -0.175424233079 -0.0239676150554 0.01
202 15 -0.134956985712 -0.0239676150554 0.01
202 20 -0.155078783631 -0.0239676150554 0.01
202 25 -0.146477684379 -0.0239676150554 0.01
202 30 -0.117679536343 -0.0239676150554 0.01
202 35 -0.190343663096 -0.0239676150554 0.01
202 40 -0.140858367085 -0.0239676150554 0.01
202 45 -0.170128628612 -0.0239676150554 0.01
202 50 -0.158469244838 -0.0239676150554 0.01
202 55 -0.162683993578 -0.0239676150554 0.01
valid_acc 95.33166666666666
203 0 -0.171389475465 -0.0239676150554 0.01
203 5 -0.165755584836 -0.0239676150554 0.01
203 10 -0.1805703789 -0.0239676150554 0.01
203 15 -0.133179277182 -0.0239676150554 0.01
203 20 -0.131549820304 -0.0239676150554 0.01
203 25 -0.135783448815 -0.0239676150554 0.01
203 30 -0.172489792109 -0.0239676150554 0.01
203 35 -0.141439571977 -0.0239676150554 0.01
203 40 -0.226321771741 -0.0239676150554 0.01
203 45 -0.123511448503 -0.0239676150554 0.01
203 50 -0.154647856951 -0.0239676150554 0.01
203 55 -0.133654236794 -0.0239676150554 0.01
valid_acc 95.64833333333334
204 0 -0.154562368989 -0.0239676150554 0.01
204 5 -0.194786906242 -0.0239676150554 0.01
204 10 -0.167515680194 -0.0239676150554 0.01
204 15 -0.163131028414 -0.0239676150554 0.01
204 20 -0.170390367508 -0.0239676150554 0.01
204 25 -0.177394658327 -0.0239676150554 0.01
204 30 -0.153341799974 -0.0239676150554 0.01
204 35 -0.128967031837 -0.0239676150554 0.01
204 40 -0.134800121188 -0.0239676150554 0.01
204 45 -0.116349704564 -0.0239676150554 0.01
204 50 -0.155106469989 -0.0239676150554 0.01
204 55 -0.167814269662 -0.0239676150554 0.01
valid_acc 95.34333333333333
205 0 -0.168392375112 -0.0239676150554 0.01
205 5 -0.115702852607 -0.0239676150554 0.01
205 10 -0.130864396691 -0.0239676150554 0.01
205 15 -0.156137466431 -0.0239676150554 0.01
205 20 -0.176535114646 -0.0239676150554 0.01
205 25 -0.135346159339 -0.0239676150554 0.01
205 30 -0.196038722992 -0.0239676150554 0.01
205 35 -0.11547292769 -0.0239676150554 0.01
205 40 -0.145567581058 -0.0239676150554 0.01
205 45 -0.193931594491 -0.0239676150554 0.01
205 50 -0.178313270211 -0.0239676150554 0.01
205 55 -0.165195405483 -0.0239676150554 0.01
valid_acc 95.28
206 0 -0.167412832379 -0.0239676150554 0.01
206 5 -0.178414806724 -0.0239676150554 0.01
206 10 -0.105171330273 -0.0239676150554 0.01
206 15 -0.178330749273 -0.0239676150554 0.01
206 20 -0.150951102376 -0.0239676150554 0.01
206 25 -0.137670218945 -0.0239676150554 0.01
206 30 -0.174897164106 -0.0239676150554 0.01
206 35 -0.146595731378 -0.0239676150554 0.01
206 40 -0.184889897704 -0.0239676150554 0.01
206 45 -0.13753503561 -0.0239676150554 0.01
206 50 -0.188366010785 -0.0239676150554 0.01
206 55 -0.167907714844 -0.0239676150554 0.01
valid_acc 95.33
207 0 -0.13097769022 -0.0249063676327 0.01
207 5 -0.140952304006 -0.0249063676327 0.01
207 10 -0.140880212188 -0.0249063676327 0.01
207 15 -0.160347446799 -0.0249063676327 0.01
207 20 -0.180471986532 -0.0249063676327 0.01
207 25 -0.158102974296 -0.0249063676327 0.01
207 30 -0.161048710346 -0.0249063676327 0.01
207 35 -0.170021936297 -0.0249063676327 0.01
207 40 -0.14539141953 -0.0249063676327 0.01
207 45 -0.149126842618 -0.0249063676327 0.01
207 50 -0.188016965985 -0.0249063676327 0.01
207 55 -0.157183974981 -0.0249063676327 0.01
valid_acc 95.75166666666667
best valid_acc 95.75166666666667
208 0 -0.151951029897 -0.0249063676327 0.01
208 5 -0.111423350871 -0.0249063676327 0.01
208 10 -0.151017010212 -0.0249063676327 0.01
208 15 -0.169681474566 -0.0249063676327 0.01
208 20 -0.129479110241 -0.0249063676327 0.01
208 25 -0.127691954374 -0.0249063676327 0.01
208 30 -0.165085822344 -0.0249063676327 0.01
208 35 -0.144198998809 -0.0249063676327 0.01
208 40 -0.162755221128 -0.0249063676327 0.01
208 45 -0.147846907377 -0.0249063676327 0.01
208 50 -0.160010129213 -0.0249063676327 0.01
208 55 -0.147129520774 -0.0249063676327 0.01
valid_acc 95.46333333333334
209 0 -0.124723777175 -0.0249063676327 0.01
209 5 -0.140708178282 -0.0249063676327 0.01
209 10 -0.159584417939 -0.0249063676327 0.01
209 15 -0.242639362812 -0.0249063676327 0.01
209 20 -0.110460184515 -0.0249063676327 0.01
209 25 -0.14190363884 -0.0249063676327 0.01
209 30 -0.13938190043 -0.0249063676327 0.01
209 35 -0.163050800562 -0.0249063676327 0.01
209 40 -0.176484003663 -0.0249063676327 0.01
209 45 -0.131974816322 -0.0249063676327 0.01
209 50 -0.192848831415 -0.0249063676327 0.01
209 55 -0.148071587086 -0.0249063676327 0.01
valid_acc 95.70166666666667
210 0 -0.144862368703 -0.0249063676327 0.01
210 5 -0.134855419397 -0.0249063676327 0.01
210 10 -0.159256190062 -0.0249063676327 0.01
210 15 -0.168529242277 -0.0249063676327 0.01
210 20 -0.178047552705 -0.0249063676327 0.01
210 25 -0.166920855641 -0.0249063676327 0.01
210 30 -0.225031480193 -0.0249063676327 0.01
210 35 -0.142535164952 -0.0249063676327 0.01
210 40 -0.170997977257 -0.0249063676327 0.01
210 45 -0.138080120087 -0.0249063676327 0.01
210 50 -0.160550639033 -0.0249063676327 0.01
210 55 -0.129111230373 -0.0249063676327 0.01
valid_acc 95.485
211 0 -0.107523582876 -0.0249063676327 0.01
211 5 -0.101449683309 -0.0249063676327 0.01
211 10 -0.164349347353 -0.0249063676327 0.01
211 15 -0.165777415037 -0.0249063676327 0.01
211 20 -0.179585725069 -0.0249063676327 0.01
211 25 -0.130032986403 -0.0249063676327 0.01
211 30 -0.119398832321 -0.0249063676327 0.01
211 35 -0.117123439908 -0.0249063676327 0.01
211 40 -0.151881530881 -0.0249063676327 0.01
211 45 -0.133411154151 -0.0249063676327 0.01
211 50 -0.161885589361 -0.0249063676327 0.01
211 55 -0.157410383224 -0.0249063676327 0.01
valid_acc 95.63833333333334
212 0 -0.179363131523 -0.0249063676327 0.01
212 5 -0.145456925035 -0.0249063676327 0.01
212 10 -0.139745876193 -0.0249063676327 0.01
212 15 -0.139635175467 -0.0249063676327 0.01
212 20 -0.163333132863 -0.0249063676327 0.01
212 25 -0.1071049124 -0.0249063676327 0.01
212 30 -0.155314326286 -0.0249063676327 0.01
212 35 -0.124421589077 -0.0249063676327 0.01
212 40 -0.149630710483 -0.0249063676327 0.01
212 45 -0.146513685584 -0.0249063676327 0.01
212 50 -0.146314159036 -0.0249063676327 0.01
212 55 -0.153867602348 -0.0249063676327 0.01
valid_acc 95.585
213 0 -0.156186908484 -0.0249063676327 0.01
213 5 -0.15058209002 -0.0249063676327 0.01
213 10 -0.138068780303 -0.0249063676327 0.01
213 15 -0.162946358323 -0.0249063676327 0.01
213 20 -0.20383810997 -0.0249063676327 0.01
213 25 -0.138408601284 -0.0249063676327 0.01
213 30 -0.149851709604 -0.0249063676327 0.01
213 35 -0.183325946331 -0.0249063676327 0.01
213 40 -0.128831237555 -0.0249063676327 0.01
213 45 -0.148484945297 -0.0249063676327 0.01
213 50 -0.159422531724 -0.0249063676327 0.01
213 55 -0.212505593896 -0.0249063676327 0.01
valid_acc 95.265
214 0 -0.149836242199 -0.0249063676327 0.01
214 5 -0.152427971363 -0.0249063676327 0.01
214 10 -0.180972501636 -0.0249063676327 0.01
214 15 -0.185222119093 -0.0249063676327 0.01
214 20 -0.125150755048 -0.0249063676327 0.01
214 25 -0.116713471711 -0.0249063676327 0.01
214 30 -0.125818297267 -0.0249063676327 0.01
214 35 -0.141444772482 -0.0249063676327 0.01
214 40 -0.134083986282 -0.0249063676327 0.01
214 45 -0.148367956281 -0.0249063676327 0.01
214 50 -0.177345275879 -0.0249063676327 0.01
214 55 -0.112563878298 -0.0249063676327 0.01
valid_acc 95.34833333333333
215 0 -0.147287741303 -0.0249063676327 0.01
215 5 -0.135857969522 -0.0249063676327 0.01
215 10 -0.149052664638 -0.0249063676327 0.01
215 15 -0.137375682592 -0.0249063676327 0.01
215 20 -0.178577274084 -0.0249063676327 0.01
215 25 -0.15851277113 -0.0249063676327 0.01
215 30 -0.180344834924 -0.0249063676327 0.01
215 35 -0.137992590666 -0.0249063676327 0.01
215 40 -0.168380588293 -0.0249063676327 0.01
215 45 -0.168174594641 -0.0249063676327 0.01
215 50 -0.175294712186 -0.0249063676327 0.01
215 55 -0.166787996888 -0.0249063676327 0.01
valid_acc 95.34833333333333
216 0 -0.169222414494 -0.0249063676327 0.01
216 5 -0.163856118917 -0.0249063676327 0.01
216 10 -0.179338738322 -0.0249063676327 0.01
216 15 -0.0895545780659 -0.0249063676327 0.01
216 20 -0.166554436088 -0.0249063676327 0.01
216 25 -0.180583626032 -0.0249063676327 0.01
216 30 -0.145747005939 -0.0249063676327 0.01
216 35 -0.167208448052 -0.0249063676327 0.01
216 40 -0.118387542665 -0.0249063676327 0.01
216 45 -0.122755654156 -0.0249063676327 0.01
216 50 -0.210434243083 -0.0249063676327 0.01
216 55 -0.164686098695 -0.0249063676327 0.01
valid_acc 95.36833333333334
217 0 -0.125990867615 -0.0249063676327 0.01
217 5 -0.12678694725 -0.0249063676327 0.01
217 10 -0.108587868512 -0.0249063676327 0.01
217 15 -0.103897742927 -0.0249063676327 0.01
217 20 -0.177203550935 -0.0249063676327 0.01
217 25 -0.155643358827 -0.0249063676327 0.01
217 30 -0.126983910799 -0.0249063676327 0.01
217 35 -0.115810282528 -0.0249063676327 0.01
217 40 -0.132787153125 -0.0249063676327 0.01
217 45 -0.159961819649 -0.0249063676327 0.01
217 50 -0.125632986426 -0.0249063676327 0.01
217 55 -0.170932248235 -0.0249063676327 0.01
valid_acc 95.51666666666667
218 0 -0.166674852371 -0.0249063676327 0.01
218 5 -0.143853083253 -0.0249063676327 0.01
218 10 -0.198807090521 -0.0249063676327 0.01
218 15 -0.14661309123 -0.0249063676327 0.01
218 20 -0.13117288053 -0.0249063676327 0.01
218 25 -0.127237871289 -0.0249063676327 0.01
218 30 -0.143353804946 -0.0249063676327 0.01
218 35 -0.115259483457 -0.0249063676327 0.01
218 40 -0.129624947906 -0.0249063676327 0.01
218 45 -0.127055749297 -0.0249063676327 0.01
218 50 -0.18468940258 -0.0249063676327 0.01
218 55 -0.190232992172 -0.0249063676327 0.01
valid_acc 95.39333333333333
219 0 -0.120084971189 -0.0249063676327 0.01
219 5 -0.166757002473 -0.0249063676327 0.01
219 10 -0.122796632349 -0.0249063676327 0.01
219 15 -0.136421129107 -0.0249063676327 0.01
219 20 -0.129893392324 -0.0249063676327 0.01
219 25 -0.169218957424 -0.0249063676327 0.01
219 30 -0.132562860847 -0.0249063676327 0.01
219 35 -0.10259090364 -0.0249063676327 0.01
219 40 -0.116802699864 -0.0249063676327 0.01
219 45 -0.142587333918 -0.0249063676327 0.01
219 50 -0.192940235138 -0.0249063676327 0.01
219 55 -0.168069839478 -0.0249063676327 0.01
valid_acc 95.03666666666668
220 0 -0.156961739063 -0.0249063676327 0.01
220 5 -0.127801015973 -0.0249063676327 0.01
220 10 -0.134435534477 -0.0249063676327 0.01
220 15 -0.206985503435 -0.0249063676327 0.01
220 20 -0.114409424365 -0.0249063676327 0.01
220 25 -0.139603406191 -0.0249063676327 0.01
220 30 -0.101717576385 -0.0249063676327 0.01
220 35 -0.195905715227 -0.0249063676327 0.01
220 40 -0.16389349103 -0.0249063676327 0.01
220 45 -0.142488747835 -0.0249063676327 0.01
220 50 -0.159179285169 -0.0249063676327 0.01
220 55 -0.148891851306 -0.0249063676327 0.01
valid_acc 95.62666666666667
221 0 -0.138237148523 -0.0249063676327 0.01
221 5 -0.129331991076 -0.0249063676327 0.01
221 10 -0.156728819013 -0.0249063676327 0.01
221 15 -0.163242965937 -0.0249063676327 0.01
221 20 -0.143952772021 -0.0249063676327 0.01
221 25 -0.129672497511 -0.0249063676327 0.01
221 30 -0.135797783732 -0.0249063676327 0.01
221 35 -0.197747901082 -0.0249063676327 0.01
221 40 -0.150996655226 -0.0249063676327 0.01
221 45 -0.165629014373 -0.0249063676327 0.01
221 50 -0.164652958512 -0.0249063676327 0.01
221 55 -0.156802237034 -0.0249063676327 0.01
valid_acc 95.02833333333334
222 0 -0.124108538032 -0.0249063676327 0.01
222 5 -0.118837624788 -0.0249063676327 0.01
222 10 -0.149185866117 -0.0249063676327 0.01
222 15 -0.154628962278 -0.0249063676327 0.01
222 20 -0.102988764644 -0.0249063676327 0.01
222 25 -0.154579609632 -0.0249063676327 0.01
222 30 -0.14694391191 -0.0249063676327 0.01
222 35 -0.231830984354 -0.0249063676327 0.01
222 40 -0.166015028954 -0.0249063676327 0.01
222 45 -0.149168103933 -0.0249063676327 0.01
222 50 -0.157304286957 -0.0249063676327 0.01
222 55 -0.130500942469 -0.0249063676327 0.01
valid_acc 95.49499999999999
223 0 -0.145091831684 -0.0249063676327 0.01
223 5 -0.173756107688 -0.0249063676327 0.01
223 10 -0.134096428752 -0.0249063676327 0.01
223 15 -0.164189055562 -0.0249063676327 0.01
223 20 -0.146208465099 -0.0249063676327 0.01
223 25 -0.205492690206 -0.0249063676327 0.01
223 30 -0.125153973699 -0.0249063676327 0.01
223 35 -0.146769568324 -0.0249063676327 0.01
223 40 -0.133936032653 -0.0249063676327 0.01
223 45 -0.15556576848 -0.0249063676327 0.01
223 50 -0.145575493574 -0.0249063676327 0.01
223 55 -0.162379980087 -0.0249063676327 0.01
valid_acc 95.63333333333334
224 0 -0.192192718387 -0.0249063676327 0.01
224 5 -0.170116230845 -0.0249063676327 0.01
224 10 -0.151507869363 -0.0249063676327 0.01
224 15 -0.141245529056 -0.0249063676327 0.01
224 20 -0.1697165519 -0.0249063676327 0.01
224 25 -0.169948831201 -0.0249063676327 0.01
224 30 -0.161652013659 -0.0249063676327 0.01
224 35 -0.149236679077 -0.0249063676327 0.01
224 40 -0.157482206821 -0.0249063676327 0.01
224 45 -0.17355145514 -0.0249063676327 0.01
224 50 -0.125100567937 -0.0249063676327 0.01
224 55 -0.162726849318 -0.0249063676327 0.01
valid_acc 95.41333333333334
225 0 -0.176717340946 -0.0249063676327 0.01
225 5 -0.143181204796 -0.0249063676327 0.01
225 10 -0.145752713084 -0.0249063676327 0.01
225 15 -0.114218771458 -0.0249063676327 0.01
225 20 -0.133176654577 -0.0249063676327 0.01
225 25 -0.142490923405 -0.0249063676327 0.01
225 30 -0.122161887586 -0.0249063676327 0.01
225 35 -0.161278560758 -0.0249063676327 0.01
225 40 -0.186606168747 -0.0249063676327 0.01
225 45 -0.147575467825 -0.0249063676327 0.01
225 50 -0.180580809712 -0.0249063676327 0.01
225 55 -0.136460602283 -0.0249063676327 0.01
valid_acc 95.47166666666666
226 0 -0.152569070458 -0.0249063676327 0.01
226 5 -0.137706726789 -0.0249063676327 0.01
226 10 -0.191804468632 -0.0249063676327 0.01
226 15 -0.153051316738 -0.0249063676327 0.01
226 20 -0.183347299695 -0.0249063676327 0.01
226 25 -0.141962125897 -0.0249063676327 0.01
226 30 -0.132059663534 -0.0249063676327 0.01
226 35 -0.127126604319 -0.0249063676327 0.01
226 40 -0.184958949685 -0.0249063676327 0.01
226 45 -0.134828805923 -0.0249063676327 0.01
226 50 -0.133970424533 -0.0249063676327 0.01
226 55 -0.126120537519 -0.0249063676327 0.01
valid_acc 95.54666666666667
227 0 -0.139581099153 -0.0249063676327 0.01
227 5 -0.143792212009 -0.0249063676327 0.01
227 10 -0.127423703671 -0.0249063676327 0.01
227 15 -0.132261365652 -0.0249063676327 0.01
227 20 -0.109772890806 -0.0249063676327 0.01
227 25 -0.233357667923 -0.0249063676327 0.01
227 30 -0.142570793629 -0.0249063676327 0.01
227 35 -0.182569116354 -0.0249063676327 0.01
227 40 -0.185261383653 -0.0249063676327 0.01
227 45 -0.126731202006 -0.0249063676327 0.01
227 50 -0.138006180525 -0.0249063676327 0.01
227 55 -0.154125899076 -0.0249063676327 0.01
valid_acc 95.63833333333334
228 0 -0.116849824786 -0.0249063676327 0.01
228 5 -0.125144377351 -0.0249063676327 0.01
228 10 -0.118303589523 -0.0249063676327 0.01
228 15 -0.197075679898 -0.0249063676327 0.01
228 20 -0.162308186293 -0.0249063676327 0.01
228 25 -0.166483670473 -0.0249063676327 0.01
228 30 -0.14068993926 -0.0249063676327 0.01
228 35 -0.151827037334 -0.0249063676327 0.01
228 40 -0.12206531316 -0.0249063676327 0.01
228 45 -0.14625069499 -0.0249063676327 0.01
228 50 -0.124108783901 -0.0249063676327 0.01
228 55 -0.157484546304 -0.0249063676327 0.01
valid_acc 95.66
229 0 -0.139182373881 -0.0249063676327 0.01
229 5 -0.165242120624 -0.0249063676327 0.01
229 10 -0.15961587429 -0.0249063676327 0.01
229 15 -0.130741655827 -0.0249063676327 0.01
229 20 -0.166071489453 -0.0249063676327 0.01
229 25 -0.157416671515 -0.0249063676327 0.01
229 30 -0.136253193021 -0.0249063676327 0.01
229 35 -0.136990711093 -0.0249063676327 0.01
229 40 -0.118360348046 -0.0249063676327 0.01
229 45 -0.137091144919 -0.0249063676327 0.01
229 50 -0.160705819726 -0.0249063676327 0.01
229 55 -0.201918110251 -0.0249063676327 0.01
valid_acc 95.585
230 0 -0.162618339062 -0.0249063676327 0.01
230 5 -0.0908185988665 -0.0249063676327 0.01
230 10 -0.132212325931 -0.0249063676327 0.01
230 15 -0.167791172862 -0.0249063676327 0.01
230 20 -0.130171954632 -0.0249063676327 0.01
230 25 -0.140550494194 -0.0249063676327 0.01
230 30 -0.159831568599 -0.0249063676327 0.01
230 35 -0.170714870095 -0.0249063676327 0.01
230 40 -0.185442045331 -0.0249063676327 0.01
230 45 -0.144236713648 -0.0249063676327 0.01
230 50 -0.151260882616 -0.0249063676327 0.01
230 55 -0.145575881004 -0.0249063676327 0.01
valid_acc 95.38499999999999
231 0 -0.11921621114 -0.0249063676327 0.01
231 5 -0.172054633498 -0.0249063676327 0.01
231 10 -0.112196780741 -0.0249063676327 0.01
231 15 -0.0868139714003 -0.0249063676327 0.01
231 20 -0.145243763924 -0.0249063676327 0.01
231 25 -0.172235459089 -0.0249063676327 0.01
231 30 -0.178120464087 -0.0249063676327 0.01
231 35 -0.151039540768 -0.0249063676327 0.01
231 40 -0.129163578153 -0.0249063676327 0.01
231 45 -0.173255264759 -0.0249063676327 0.01
231 50 -0.172057315707 -0.0249063676327 0.01
231 55 -0.16585560143 -0.0249063676327 0.01
valid_acc 95.10666666666665
232 0 -0.109347544611 -0.0249063676327 0.01
232 5 -0.144823372364 -0.0249063676327 0.01
232 10 -0.153752535582 -0.0249063676327 0.01
232 15 -0.153958633542 -0.0249063676327 0.01
232 20 -0.128522932529 -0.0249063676327 0.01
232 25 -0.122865542769 -0.0249063676327 0.01
232 30 -0.160912439227 -0.0249063676327 0.01
232 35 -0.193103373051 -0.0249063676327 0.01
232 40 -0.152952209115 -0.0249063676327 0.01
232 45 -0.202124372125 -0.0249063676327 0.01
232 50 -0.131352648139 -0.0249063676327 0.01
232 55 -0.132446408272 -0.0249063676327 0.01
valid_acc 95.64166666666667
233 0 -0.172177568078 -0.0249063676327 0.01
233 5 -0.174802869558 -0.0249063676327 0.01
233 10 -0.132611900568 -0.0249063676327 0.01
233 15 -0.122739695013 -0.0249063676327 0.01
233 20 -0.124237902462 -0.0249063676327 0.01
233 25 -0.145001605153 -0.0249063676327 0.01
233 30 -0.147847950459 -0.0249063676327 0.01
233 35 -0.117641158402 -0.0249063676327 0.01
233 40 -0.132246807218 -0.0249063676327 0.01
233 45 -0.101330459118 -0.0249063676327 0.01
233 50 -0.199576050043 -0.0249063676327 0.01
233 55 -0.0884717926383 -0.0249063676327 0.01
valid_acc 95.62166666666667
234 0 -0.127964347601 -0.0249063676327 0.01
234 5 -0.171504899859 -0.0249063676327 0.01
234 10 -0.125430360436 -0.0249063676327 0.01
234 15 -0.14708198607 -0.0249063676327 0.01
234 20 -0.138728484511 -0.0249063676327 0.01
234 25 -0.140346869826 -0.0249063676327 0.01
234 30 -0.168493211269 -0.0249063676327 0.01
234 35 -0.174837917089 -0.0249063676327 0.01
234 40 -0.133071616292 -0.0249063676327 0.01
234 45 -0.11893710494 -0.0249063676327 0.01
234 50 -0.133888885379 -0.0249063676327 0.01
234 55 -0.14752420783 -0.0249063676327 0.01
valid_acc 95.45166666666667
235 0 -0.138855785131 -0.0249063676327 0.01
235 5 -0.181627035141 -0.0249063676327 0.01
235 10 -0.110576525331 -0.0249063676327 0.01
235 15 -0.100181497633 -0.0249063676327 0.01
235 20 -0.126646742225 -0.0249063676327 0.01
235 25 -0.11535679549 -0.0249063676327 0.01
235 30 -0.202055260539 -0.0249063676327 0.01
235 35 -0.127652511001 -0.0249063676327 0.01
235 40 -0.12426353991 -0.0249063676327 0.01
235 45 -0.131065040827 -0.0249063676327 0.01
235 50 -0.105633825064 -0.0249063676327 0.01
235 55 -0.120351530612 -0.0249063676327 0.01
valid_acc 95.48666666666666
236 0 -0.11313855648 -0.0249063676327 0.01
236 5 -0.103776231408 -0.0249063676327 0.01
236 10 -0.157857507467 -0.0249063676327 0.01
236 15 -0.161920636892 -0.0249063676327 0.01
236 20 -0.166388466954 -0.0249063676327 0.01
236 25 -0.117285624146 -0.0249063676327 0.01
236 30 -0.179581522942 -0.0249063676327 0.01
236 35 -0.164721265435 -0.0249063676327 0.01
236 40 -0.138758182526 -0.0249063676327 0.01
236 45 -0.168466478586 -0.0249063676327 0.01
236 50 -0.107165835798 -0.0249063676327 0.01
236 55 -0.175663039088 -0.0249063676327 0.01
valid_acc 95.26666666666667
237 0 -0.12298180908 -0.0249063676327 0.01
237 5 -0.145505875349 -0.0249063676327 0.01
237 10 -0.105146057904 -0.0249063676327 0.01
237 15 -0.183352231979 -0.0249063676327 0.01
237 20 -0.100338205695 -0.0249063676327 0.01
237 25 -0.143976598978 -0.0249063676327 0.01
237 30 -0.12498883158 -0.0249063676327 0.01
237 35 -0.177747637033 -0.0249063676327 0.01
237 40 -0.160671696067 -0.0249063676327 0.01
237 45 -0.190907806158 -0.0249063676327 0.01
237 50 -0.146953955293 -0.0249063676327 0.01
237 55 -0.151172220707 -0.0249063676327 0.01
valid_acc 95.58833333333332
238 0 -0.144954547286 -0.0249063676327 0.01
238 5 -0.123192578554 -0.0249063676327 0.01
238 10 -0.191331937909 -0.0249063676327 0.01
238 15 -0.135722190142 -0.0249063676327 0.01
238 20 -0.122519090772 -0.0249063676327 0.01
238 25 -0.0994058847427 -0.0249063676327 0.01
238 30 -0.102013088763 -0.0249063676327 0.01
238 35 -0.208237051964 -0.0249063676327 0.01
238 40 -0.180569186807 -0.0249063676327 0.01
238 45 -0.158602356911 -0.0249063676327 0.01
238 50 -0.119658723474 -0.0249063676327 0.01
238 55 -0.157417908311 -0.0249063676327 0.01
valid_acc 95.69166666666666
239 0 -0.146181762218 -0.0249063676327 0.01
239 5 -0.148423150182 -0.0249063676327 0.01
239 10 -0.184275835752 -0.0249063676327 0.01
239 15 -0.156605124474 -0.0249063676327 0.01
239 20 -0.173796027899 -0.0249063676327 0.01
239 25 -0.148644506931 -0.0249063676327 0.01
239 30 -0.105855695903 -0.0249063676327 0.01
239 35 -0.132431551814 -0.0249063676327 0.01
239 40 -0.144950017333 -0.0249063676327 0.01
239 45 -0.124718010426 -0.0249063676327 0.01
239 50 -0.13243535161 -0.0249063676327 0.01
239 55 -0.128093227744 -0.0249063676327 0.01
valid_acc 95.645
240 0 -0.0958046093583 -0.0249063676327 0.01
240 5 -0.150288373232 -0.0249063676327 0.01
240 10 -0.17119461298 -0.0249063676327 0.01
240 15 -0.122961550951 -0.0249063676327 0.01
240 20 -0.143783643842 -0.0249063676327 0.01
240 25 -0.152379304171 -0.0249063676327 0.01
240 30 -0.162263274193 -0.0249063676327 0.01
240 35 -0.12885633111 -0.0249063676327 0.01
240 40 -0.150937482715 -0.0249063676327 0.01
240 45 -0.15143661201 -0.0249063676327 0.01
240 50 -0.134500980377 -0.0249063676327 0.01
240 55 -0.127085015178 -0.0249063676327 0.01
valid_acc 95.785
best valid_acc 95.785
241 0 -0.154059395194 -0.0249063676327 0.01
241 5 -0.187355518341 -0.0249063676327 0.01
241 10 -0.139495968819 -0.0249063676327 0.01
241 15 -0.146195158362 -0.0249063676327 0.01
241 20 -0.100735284388 -0.0249063676327 0.01
241 25 -0.167145580053 -0.0249063676327 0.01
241 30 -0.154127106071 -0.0249063676327 0.01
241 35 -0.174986302853 -0.0249063676327 0.01
241 40 -0.139655634761 -0.0249063676327 0.01
241 45 -0.114498406649 -0.0249063676327 0.01
241 50 -0.141329228878 -0.0249063676327 0.01
241 55 -0.124798230827 -0.0249063676327 0.01
valid_acc 95.41666666666667
242 0 -0.143197253346 -0.0249063676327 0.01
242 5 -0.108378261328 -0.0249063676327 0.01
242 10 -0.150008708239 -0.0249063676327 0.01
242 15 -0.13928309083 -0.0249063676327 0.01
242 20 -0.160347133875 -0.0249063676327 0.01
242 25 -0.194064572453 -0.0249063676327 0.01
242 30 -0.126461967826 -0.0249063676327 0.01
242 35 -0.179603070021 -0.0249063676327 0.01
242 40 -0.130557954311 -0.0249063676327 0.01
242 45 -0.133246734738 -0.0249063676327 0.01
242 50 -0.112746454775 -0.0249063676327 0.01
242 55 -0.152605608106 -0.0249063676327 0.01
valid_acc 95.67166666666667
243 0 -0.139280378819 -0.0249063676327 0.01
243 5 -0.126523867249 -0.0249063676327 0.01
243 10 -0.132871180773 -0.0249063676327 0.01
243 15 -0.131170019507 -0.0249063676327 0.01
243 20 -0.165936365724 -0.0249063676327 0.01
243 25 -0.138203307986 -0.0249063676327 0.01
243 30 -0.168278351426 -0.0249063676327 0.01
243 35 -0.157861381769 -0.0249063676327 0.01
243 40 -0.129139229655 -0.0249063676327 0.01
243 45 -0.117641046643 -0.0249063676327 0.01
243 50 -0.120670311153 -0.0249063676327 0.01
243 55 -0.120341017842 -0.0249063676327 0.01
valid_acc 95.595
244 0 -0.171602934599 -0.0249063676327 0.01
244 5 -0.135251417756 -0.0249063676327 0.01
244 10 -0.0976615101099 -0.0249063676327 0.01
244 15 -0.127023756504 -0.0249063676327 0.01
244 20 -0.1716927737 -0.0249063676327 0.01
244 25 -0.153261333704 -0.0249063676327 0.01
244 30 -0.124888420105 -0.0249063676327 0.01
244 35 -0.147068485618 -0.0249063676327 0.01
244 40 -0.198561355472 -0.0249063676327 0.01
244 45 -0.171361982822 -0.0249063676327 0.01
244 50 -0.183333158493 -0.0249063676327 0.01
244 55 -0.132490649819 -0.0249063676327 0.01
valid_acc 94.91833333333334
245 0 -0.163006842136 -0.0249063676327 0.01
245 5 -0.162776678801 -0.0249063676327 0.01
245 10 -0.171258971095 -0.0249063676327 0.01
245 15 -0.0921995639801 -0.0249063676327 0.01
245 20 -0.158812090755 -0.0249063676327 0.01
245 25 -0.153114810586 -0.0249063676327 0.01
245 30 -0.145182341337 -0.0249063676327 0.01
245 35 -0.110424146056 -0.0249063676327 0.01
245 40 -0.12960152328 -0.0249063676327 0.01
245 45 -0.174730420113 -0.0249063676327 0.01
245 50 -0.0905750244856 -0.0249063676327 0.01
245 55 -0.131664127111 -0.0249063676327 0.01
valid_acc 95.625
246 0 -0.16066044569 -0.0249063676327 0.01
246 5 -0.113449312747 -0.0249063676327 0.01
246 10 -0.187009185553 -0.0249063676327 0.01
246 15 -0.132556781173 -0.0249063676327 0.01
246 20 -0.125973671675 -0.0249063676327 0.01
246 25 -0.185639590025 -0.0249063676327 0.01
246 30 -0.153395071626 -0.0249063676327 0.01
246 35 -0.179293915629 -0.0249063676327 0.01
246 40 -0.140447080135 -0.0249063676327 0.01
246 45 -0.166577085853 -0.0249063676327 0.01
246 50 -0.150403603911 -0.0249063676327 0.01
246 55 -0.189142718911 -0.0249063676327 0.01
valid_acc 95.5
247 0 -0.185874283314 -0.0249063676327 0.01
247 5 -0.138273224235 -0.0249063676327 0.01
247 10 -0.160038262606 -0.0249063676327 0.01
247 15 -0.14090976119 -0.0249063676327 0.01
247 20 -0.142946720123 -0.0249063676327 0.01
247 25 -0.153229281306 -0.0249063676327 0.01
247 30 -0.121096856892 -0.0249063676327 0.01
247 35 -0.16253760457 -0.0249063676327 0.01
247 40 -0.172178074718 -0.0249063676327 0.01
247 45 -0.129829600453 -0.0249063676327 0.01
247 50 -0.14321282506 -0.0249063676327 0.01
247 55 -0.12218926847 -0.0249063676327 0.01
valid_acc 95.78666666666666
best valid_acc 95.78666666666666
248 0 -0.133231669664 -0.0249063676327 0.01
248 5 -0.163449749351 -0.0249063676327 0.01
248 10 -0.154052764177 -0.0249063676327 0.01
248 15 -0.149747565389 -0.0249063676327 0.01
248 20 -0.131529122591 -0.0249063676327 0.01
248 25 -0.186157882214 -0.0249063676327 0.01
248 30 -0.140811786056 -0.0249063676327 0.01
248 35 -0.103044323623 -0.0249063676327 0.01
248 40 -0.155555143952 -0.0249063676327 0.01
248 45 -0.154628783464 -0.0249063676327 0.01
248 50 -0.146906524897 -0.0249063676327 0.01
248 55 -0.147831141949 -0.0249063676327 0.01
valid_acc 95.23166666666667
249 0 -0.183214336634 -0.0249063676327 0.01
249 5 -0.118878573179 -0.0249063676327 0.01
249 10 -0.12408836931 -0.0249063676327 0.01
249 15 -0.101995110512 -0.0249063676327 0.01
249 20 -0.11836347729 -0.0249063676327 0.01
249 25 -0.127511546016 -0.0249063676327 0.01
249 30 -0.0945787876844 -0.0249063676327 0.01
249 35 -0.151189953089 -0.0249063676327 0.01
249 40 -0.141809910536 -0.0249063676327 0.01
249 45 -0.127720713615 -0.0249063676327 0.01
249 50 -0.125276342034 -0.0249063676327 0.01
249 55 -0.198367357254 -0.0249063676327 0.01
valid_acc 95.70666666666666
250 0 -0.144662976265 -0.0249063676327 0.01
250 5 -0.142772629857 -0.0249063676327 0.01
250 10 -0.109702937305 -0.0249063676327 0.01
250 15 -0.183019280434 -0.0249063676327 0.01
250 20 -0.137247920036 -0.0249063676327 0.01
250 25 -0.162184923887 -0.0249063676327 0.01
250 30 -0.12722826004 -0.0249063676327 0.01
250 35 -0.141092538834 -0.0249063676327 0.01
250 40 -0.166620984674 -0.0249063676327 0.01
250 45 -0.098625279963 -0.0249063676327 0.01
250 50 -0.163390368223 -0.0249063676327 0.01
250 55 -0.120421022177 -0.0249063676327 0.01
valid_acc 95.79833333333333
best valid_acc 95.79833333333333
251 0 -0.156445711851 -0.0249063676327 0.01
251 5 -0.120685838163 -0.0249063676327 0.01
251 10 -0.114889807999 -0.0249063676327 0.01
251 15 -0.136225283146 -0.0249063676327 0.01
251 20 -0.14524333179 -0.0249063676327 0.01
251 25 -0.174331396818 -0.0249063676327 0.01
251 30 -0.141880303621 -0.0249063676327 0.01
251 35 -0.135092437267 -0.0249063676327 0.01
251 40 -0.116668239236 -0.0249063676327 0.01
251 45 -0.159716442227 -0.0249063676327 0.01
251 50 -0.120125323534 -0.0249063676327 0.01
251 55 -0.112637251616 -0.0249063676327 0.01
valid_acc 95.645
252 0 -0.160156011581 -0.0249063676327 0.01
252 5 -0.141303285956 -0.0249063676327 0.01
252 10 -0.193120315671 -0.0249063676327 0.01
252 15 -0.149512737989 -0.0249063676327 0.01
252 20 -0.130226612091 -0.0249063676327 0.01
252 25 -0.152881920338 -0.0249063676327 0.01
252 30 -0.160630941391 -0.0249063676327 0.01
252 35 -0.145570501685 -0.0249063676327 0.01
252 40 -0.123486876488 -0.0249063676327 0.01
252 45 -0.145552828908 -0.0249063676327 0.01
252 50 -0.146421566606 -0.0249063676327 0.01
252 55 -0.155083030462 -0.0249063676327 0.01
valid_acc 95.44
253 0 -0.12971766293 -0.0249063676327 0.01
253 5 -0.176793053746 -0.0249063676327 0.01
253 10 -0.147717192769 -0.0249063676327 0.01
253 15 -0.149839356542 -0.0249063676327 0.01
253 20 -0.176794961095 -0.0249063676327 0.01
253 25 -0.144095376134 -0.0249063676327 0.01
253 30 -0.171440526843 -0.0249063676327 0.01
253 35 -0.123028665781 -0.0249063676327 0.01
253 40 -0.159250199795 -0.0249063676327 0.01
253 45 -0.122091256082 -0.0249063676327 0.01
253 50 -0.106323994696 -0.0249063676327 0.01
253 55 -0.170014560223 -0.0249063676327 0.01
valid_acc 95.94666666666667
best valid_acc 95.94666666666667
254 0 -0.204507276416 -0.0249063676327 0.01
254 5 -0.167104259133 -0.0249063676327 0.01
254 10 -0.166949629784 -0.0249063676327 0.01
254 15 -0.140329629183 -0.0249063676327 0.01
254 20 -0.134263664484 -0.0249063676327 0.01
254 25 -0.155596628785 -0.0249063676327 0.01
254 30 -0.12972445786 -0.0249063676327 0.01
254 35 -0.148729205132 -0.0249063676327 0.01
254 40 -0.157836690545 -0.0249063676327 0.01
254 45 -0.144139304757 -0.0249063676327 0.01
254 50 -0.142340764403 -0.0249063676327 0.01
254 55 -0.134711042047 -0.0249063676327 0.01
valid_acc 95.47166666666666
255 0 -0.152231037617 -0.0249063676327 0.01
255 5 -0.146937966347 -0.0249063676327 0.01
255 10 -0.11543020606 -0.0249063676327 0.01
255 15 -0.133307337761 -0.0249063676327 0.01
255 20 -0.19844828546 -0.0249063676327 0.01
255 25 -0.158650949597 -0.0249063676327 0.01
255 30 -0.182816788554 -0.0249063676327 0.01
255 35 -0.105610817671 -0.0249063676327 0.01
255 40 -0.141765892506 -0.0249063676327 0.01
255 45 -0.123672805727 -0.0249063676327 0.01
255 50 -0.101140633225 -0.0249063676327 0.01
255 55 -0.121046587825 -0.0249063676327 0.01
valid_acc 95.57666666666667
256 0 -0.121576309204 -0.0249063676327 0.01
256 5 -0.132027551532 -0.0249063676327 0.01
256 10 -0.098344437778 -0.0249063676327 0.01
256 15 -0.0999481081963 -0.0249063676327 0.01
256 20 -0.132001578808 -0.0249063676327 0.01
256 25 -0.191410958767 -0.0249063676327 0.01
256 30 -0.125089347363 -0.0249063676327 0.01
256 35 -0.152269855142 -0.0249063676327 0.01
256 40 -0.13949264586 -0.0249063676327 0.01
256 45 -0.128143131733 -0.0249063676327 0.01
256 50 -0.196494281292 -0.0249063676327 0.01
256 55 -0.126070201397 -0.0249063676327 0.01
valid_acc 95.61666666666667
257 0 -0.121837280691 -0.0249063676327 0.01
257 5 -0.107366070151 -0.0249063676327 0.01
257 10 -0.114380270243 -0.0249063676327 0.01
257 15 -0.128634318709 -0.0249063676327 0.01
257 20 -0.145710468292 -0.0249063676327 0.01
257 25 -0.115988910198 -0.0249063676327 0.01
257 30 -0.127383947372 -0.0249063676327 0.01
257 35 -0.142277851701 -0.0249063676327 0.01
257 40 -0.17124338448 -0.0249063676327 0.01
257 45 -0.161544859409 -0.0249063676327 0.01
257 50 -0.104648888111 -0.0249063676327 0.01
257 55 -0.178166344762 -0.0249063676327 0.01
valid_acc 95.41166666666666
258 0 -0.153392642736 -0.0249063676327 0.01
258 5 -0.112044669688 -0.0249063676327 0.01
258 10 -0.0893082022667 -0.0249063676327 0.01
258 15 -0.129510238767 -0.0249063676327 0.01
258 20 -0.177300289273 -0.0249063676327 0.01
258 25 -0.150151103735 -0.0249063676327 0.01
258 30 -0.167328163981 -0.0249063676327 0.01
258 35 -0.136588051915 -0.0249063676327 0.01
258 40 -0.158075481653 -0.0249063676327 0.01
258 45 -0.144526228309 -0.0249063676327 0.01
258 50 -0.145049825311 -0.0249063676327 0.01
258 55 -0.138540118933 -0.0249063676327 0.01
valid_acc 95.81
259 0 -0.127617716789 -0.0249063676327 0.01
259 5 -0.113691993058 -0.0249063676327 0.01
259 10 -0.124442346394 -0.0249063676327 0.01
259 15 -0.139847517014 -0.0249063676327 0.01
259 20 -0.151488780975 -0.0249063676327 0.01
259 25 -0.12062612921 -0.0249063676327 0.01
259 30 -0.146065250039 -0.0249063676327 0.01
259 35 -0.156167596579 -0.0249063676327 0.01
259 40 -0.109667517245 -0.0249063676327 0.01
259 45 -0.1514659971 -0.0249063676327 0.01
259 50 -0.162556484342 -0.0249063676327 0.01
259 55 -0.112340018153 -0.0249063676327 0.01
valid_acc 95.62166666666667
260 0 -0.118690989912 -0.0249063676327 0.01
260 5 -0.117800779641 -0.0249063676327 0.01
260 10 -0.157915636897 -0.0249063676327 0.01
260 15 -0.186009675264 -0.0249063676327 0.01
260 20 -0.154405921698 -0.0249063676327 0.01
260 25 -0.105637572706 -0.0249063676327 0.01
260 30 -0.179929986596 -0.0249063676327 0.01
260 35 -0.144883170724 -0.0249063676327 0.01
260 40 -0.135191291571 -0.0249063676327 0.01
260 45 -0.131964504719 -0.0249063676327 0.01
260 50 -0.106863796711 -0.0249063676327 0.01
260 55 -0.148425966501 -0.0249063676327 0.01
valid_acc 95.58166666666666
261 0 -0.136373355985 -0.0249063676327 0.01
261 5 -0.146447405219 -0.0249063676327 0.01
261 10 -0.109886661172 -0.0249063676327 0.01
261 15 -0.164772480726 -0.0249063676327 0.01
261 20 -0.121552370489 -0.0249063676327 0.01
261 25 -0.135236784816 -0.0249063676327 0.01
261 30 -0.115994565189 -0.0249063676327 0.01
261 35 -0.112690120935 -0.0249063676327 0.01
261 40 -0.186522960663 -0.0249063676327 0.01
261 45 -0.189444854856 -0.0249063676327 0.01
261 50 -0.149529784918 -0.0249063676327 0.01
261 55 -0.171115681529 -0.0249063676327 0.01
valid_acc 95.59
262 0 -0.130152761936 -0.0249063676327 0.01
262 5 -0.1390799582 -0.0249063676327 0.01
262 10 -0.152548894286 -0.0249063676327 0.01
262 15 -0.148340046406 -0.0249063676327 0.01
262 20 -0.123026154935 -0.0249063676327 0.01
262 25 -0.145503386855 -0.0249063676327 0.01
262 30 -0.177201747894 -0.0249063676327 0.01
262 35 -0.176690518856 -0.0249063676327 0.01
262 40 -0.144704267383 -0.0249063676327 0.01
262 45 -0.1349747926 -0.0249063676327 0.01
262 50 -0.092645406723 -0.0249063676327 0.01
262 55 -0.130228817463 -0.0249063676327 0.01
valid_acc 95.95166666666667
best valid_acc 95.95166666666667
263 0 -0.157326877117 -0.0249063676327 0.01
263 5 -0.121519185603 -0.0249063676327 0.01
263 10 -0.14275303483 -0.0249063676327 0.01
263 15 -0.198865219951 -0.0249063676327 0.01
263 20 -0.111918628216 -0.0249063676327 0.01
263 25 -0.16772814095 -0.0249063676327 0.01
263 30 -0.142384678125 -0.0249063676327 0.01
263 35 -0.114322446287 -0.0249063676327 0.01
263 40 -0.139199182391 -0.0249063676327 0.01
263 45 -0.126422807574 -0.0249063676327 0.01
263 50 -0.163576349616 -0.0249063676327 0.01
263 55 -0.162611022592 -0.0249063676327 0.01
valid_acc 95.81333333333333
264 0 -0.111535906792 -0.0249063676327 0.01
264 5 -0.15713609755 -0.0249063676327 0.01
264 10 -0.140892252326 -0.0249063676327 0.01
264 15 -0.147079616785 -0.0249063676327 0.01
264 20 -0.117124319077 -0.0249063676327 0.01
264 25 -0.099180214107 -0.0249063676327 0.01
264 30 -0.100307010114 -0.0249063676327 0.01
264 35 -0.132666125894 -0.0249063676327 0.01
264 40 -0.11050054431 -0.0249063676327 0.01
264 45 -0.120886556804 -0.0249063676327 0.01
264 50 -0.167192861438 -0.0249063676327 0.01
264 55 -0.145652189851 -0.0249063676327 0.01
valid_acc 95.72833333333334
265 0 -0.158030420542 -0.0249063676327 0.01
265 5 -0.144122630358 -0.0249063676327 0.01
265 10 -0.123322874308 -0.0249063676327 0.01
265 15 -0.165191620588 -0.0249063676327 0.01
265 20 -0.109535142779 -0.0249063676327 0.01
265 25 -0.117244146764 -0.0249063676327 0.01
265 30 -0.109866060317 -0.0249063676327 0.01
265 35 -0.160352557898 -0.0249063676327 0.01
265 40 -0.124380886555 -0.0249063676327 0.01
265 45 -0.127737149596 -0.0249063676327 0.01
265 50 -0.0965594872832 -0.0249063676327 0.01
265 55 -0.123030029237 -0.0249063676327 0.01
valid_acc 95.56166666666667
266 0 -0.169042691588 -0.0249063676327 0.01
266 5 -0.153693899512 -0.0249063676327 0.01
266 10 -0.143428266048 -0.0249063676327 0.01
266 15 -0.101406119764 -0.0249063676327 0.01
266 20 -0.182555049658 -0.0249063676327 0.01
266 25 -0.145375400782 -0.0249063676327 0.01
266 30 -0.107022210956 -0.0249063676327 0.01
266 35 -0.125631213188 -0.0249063676327 0.01
266 40 -0.156111776829 -0.0249063676327 0.01
266 45 -0.151356071234 -0.0249063676327 0.01
266 50 -0.147419303656 -0.0249063676327 0.01
266 55 -0.0901898890734 -0.0249063676327 0.01
valid_acc 95.83666666666667
267 0 -0.122464373708 -0.0249063676327 0.01
267 5 -0.162448048592 -0.0249063676327 0.01
267 10 -0.152868002653 -0.0249063676327 0.01
267 15 -0.118800267577 -0.0249063676327 0.01
267 20 -0.137733817101 -0.0249063676327 0.01
267 25 -0.153750896454 -0.0249063676327 0.01
267 30 -0.158875092864 -0.0249063676327 0.01
267 35 -0.166832432151 -0.0249063676327 0.01
267 40 -0.102796860039 -0.0249063676327 0.01
267 45 -0.124610073864 -0.0249063676327 0.01
267 50 -0.128225281835 -0.0249063676327 0.01
267 55 -0.145849406719 -0.0249063676327 0.01
valid_acc 95.73666666666666
268 0 -0.129175335169 -0.0249063676327 0.01
268 5 -0.115802012384 -0.0249063676327 0.01
268 10 -0.0876716077328 -0.0249063676327 0.01
268 15 -0.135636925697 -0.0249063676327 0.01
268 20 -0.166251525283 -0.0249063676327 0.01
268 25 -0.155501231551 -0.0249063676327 0.01
268 30 -0.128021270037 -0.0249063676327 0.01
268 35 -0.157430499792 -0.0249063676327 0.01
268 40 -0.121413223445 -0.0249063676327 0.01
268 45 -0.128130480647 -0.0249063676327 0.01
268 50 -0.168211191893 -0.0249063676327 0.01
268 55 -0.119839735329 -0.0249063676327 0.01
valid_acc 95.545
269 0 -0.139934182167 -0.0249063676327 0.01
269 5 -0.178531557322 -0.0249063676327 0.01
269 10 -0.12844312191 -0.0249063676327 0.01
269 15 -0.107244282961 -0.0249063676327 0.01
269 20 -0.164496451616 -0.0249063676327 0.01
269 25 -0.146000489593 -0.0249063676327 0.01
269 30 -0.164770677686 -0.0249063676327 0.01
269 35 -0.141993165016 -0.0249063676327 0.01
269 40 -0.154559895396 -0.0249063676327 0.01
269 45 -0.156955331564 -0.0249063676327 0.01
269 50 -0.143436685205 -0.0249063676327 0.01
269 55 -0.135815829039 -0.0249063676327 0.01
valid_acc 95.44166666666666
270 0 -0.186489477754 -0.0249063676327 0.01
270 5 -0.146410748363 -0.0249063676327 0.01
270 10 -0.132082760334 -0.0249063676327 0.01
270 15 -0.129864946008 -0.0249063676327 0.01
270 20 -0.17671866715 -0.0249063676327 0.01
270 25 -0.139074921608 -0.0249063676327 0.01
270 30 -0.153316169977 -0.0249063676327 0.01
270 35 -0.137099042535 -0.0249063676327 0.01
270 40 -0.147089168429 -0.0249063676327 0.01
270 45 -0.122034832835 -0.0249063676327 0.01
270 50 -0.147190362215 -0.0249063676327 0.01
270 55 -0.101940385997 -0.0249063676327 0.01
valid_acc 95.80333333333333
271 0 -0.12462965399 -0.0249063676327 0.01
271 5 -0.148579448462 -0.0249063676327 0.01
271 10 -0.110915064812 -0.0249063676327 0.01
271 15 -0.171615675092 -0.0249063676327 0.01
271 20 -0.129587695003 -0.0249063676327 0.01
271 25 -0.150741383433 -0.0249063676327 0.01
271 30 -0.107318602502 -0.0249063676327 0.01
271 35 -0.127856552601 -0.0249063676327 0.01
271 40 -0.140371739864 -0.0249063676327 0.01
271 45 -0.180672302842 -0.0249063676327 0.01
271 50 -0.187552586198 -0.0249063676327 0.01
271 55 -0.165786266327 -0.0249063676327 0.01
valid_acc 95.68166666666667
272 0 -0.105702355504 -0.0249063676327 0.01
272 5 -0.180472493172 -0.0249063676327 0.01
272 10 -0.128743469715 -0.0249063676327 0.01
272 15 -0.113908648491 -0.0249063676327 0.01
272 20 -0.164923489094 -0.0249063676327 0.01
272 25 -0.178181260824 -0.0249063676327 0.01
272 30 -0.136813923717 -0.0249063676327 0.01
272 35 -0.152875542641 -0.0249063676327 0.01
272 40 -0.118243560195 -0.0249063676327 0.01
272 45 -0.120387412608 -0.0249063676327 0.01
272 50 -0.137691959739 -0.0249063676327 0.01
272 55 -0.15524558723 -0.0249063676327 0.01
valid_acc 95.57
273 0 -0.138341352344 -0.0249063676327 0.01
273 5 -0.105380445719 -0.0249063676327 0.01
273 10 -0.133769124746 -0.0249063676327 0.01
273 15 -0.176697060466 -0.0249063676327 0.01
273 20 -0.130617082119 -0.0249063676327 0.01
273 25 -0.132180258632 -0.0249063676327 0.01
273 30 -0.128838807344 -0.0249063676327 0.01
273 35 -0.165081948042 -0.0249063676327 0.01
273 40 -0.131298452616 -0.0249063676327 0.01
273 45 -0.143459871411 -0.0249063676327 0.01
273 50 -0.121893003583 -0.0249063676327 0.01
273 55 -0.150759160519 -0.0249063676327 0.01
valid_acc 95.67666666666666
274 0 -0.156912639737 -0.0249063676327 0.01
274 5 -0.120998524129 -0.0249063676327 0.01
274 10 -0.165130585432 -0.0249063676327 0.01
274 15 -0.160952284932 -0.0249063676327 0.01
274 20 -0.12740688026 -0.0249063676327 0.01
274 25 -0.153554081917 -0.0249063676327 0.01
274 30 -0.114130184054 -0.0249063676327 0.01
274 35 -0.153545275331 -0.0249063676327 0.01
274 40 -0.102965638041 -0.0249063676327 0.01
274 45 -0.184312328696 -0.0249063676327 0.01
274 50 -0.15037946403 -0.0249063676327 0.01
274 55 -0.175300732255 -0.0249063676327 0.01
valid_acc 95.66833333333334
275 0 -0.16160801053 -0.0249063676327 0.01
275 5 -0.12462502718 -0.0249063676327 0.01
275 10 -0.149503648281 -0.0249063676327 0.01
275 15 -0.12461809814 -0.0249063676327 0.01
275 20 -0.142317399383 -0.0249063676327 0.01
275 25 -0.106218598783 -0.0249063676327 0.01
275 30 -0.107095845044 -0.0249063676327 0.01
275 35 -0.13802395761 -0.0249063676327 0.01
275 40 -0.141579523683 -0.0249063676327 0.01
275 45 -0.125989794731 -0.0249063676327 0.01
275 50 -0.086842186749 -0.0249063676327 0.01
275 55 -0.158349424601 -0.0249063676327 0.01
valid_acc 95.68333333333334
276 0 -0.115748152137 -0.0249063676327 0.01
276 5 -0.157358467579 -0.0249063676327 0.01
276 10 -0.159655302763 -0.0249063676327 0.01
276 15 -0.139173299074 -0.0249063676327 0.01
276 20 -0.142434045672 -0.0249063676327 0.01
276 25 -0.120120100677 -0.0249063676327 0.01
276 30 -0.140326067805 -0.0249063676327 0.01
276 35 -0.131976678967 -0.0249063676327 0.01
276 40 -0.147913604975 -0.0249063676327 0.01
276 45 -0.0999696180224 -0.0249063676327 0.01
276 50 -0.0907898843288 -0.0249063676327 0.01
276 55 -0.128593161702 -0.0249063676327 0.01
valid_acc 95.89666666666666
277 0 -0.153926074505 -0.0249063676327 0.01
277 5 -0.117655605078 -0.0249063676327 0.01
277 10 -0.16889975965 -0.0249063676327 0.01
277 15 -0.118168018758 -0.0249063676327 0.01
277 20 -0.130238175392 -0.0249063676327 0.01
277 25 -0.170780569315 -0.0249063676327 0.01
277 30 -0.141634806991 -0.0249063676327 0.01
277 35 -0.148396894336 -0.0249063676327 0.01
277 40 -0.155357763171 -0.0249063676327 0.01
277 45 -0.104117944837 -0.0249063676327 0.01
277 50 -0.154187723994 -0.0249063676327 0.01
277 55 -0.114585191011 -0.0249063676327 0.01
valid_acc 95.73666666666666
278 0 -0.139173537493 -0.0249063676327 0.01
278 5 -0.110388852656 -0.0249063676327 0.01
278 10 -0.14557518065 -0.0249063676327 0.01
278 15 -0.134438663721 -0.0249063676327 0.01
278 20 -0.146103203297 -0.0249063676327 0.01
278 25 -0.164970830083 -0.0249063676327 0.01
278 30 -0.163028940558 -0.0249063676327 0.01
278 35 -0.105988331139 -0.0249063676327 0.01
278 40 -0.119548670948 -0.0249063676327 0.01
278 45 -0.124517157674 -0.0249063676327 0.01
278 50 -0.120659269392 -0.0249063676327 0.01
278 55 -0.118288077414 -0.0249063676327 0.01
valid_acc 95.755
279 0 -0.0916623771191 -0.0249063676327 0.01
279 5 -0.133765488863 -0.0249063676327 0.01
279 10 -0.146170154214 -0.0249063676327 0.01
279 15 -0.151219144464 -0.0249063676327 0.01
279 20 -0.112214706838 -0.0249063676327 0.01
279 25 -0.13818924129 -0.0249063676327 0.01
279 30 -0.164551153779 -0.0249063676327 0.01
279 35 -0.137941285968 -0.0249063676327 0.01
279 40 -0.133789926767 -0.0249063676327 0.01
279 45 -0.149082988501 -0.0249063676327 0.01
279 50 -0.121044188738 -0.0249063676327 0.01
279 55 -0.153039008379 -0.0249063676327 0.01
valid_acc 95.67999999999999
280 0 -0.147434949875 -0.0249063676327 0.01
280 5 -0.163510158658 -0.0249063676327 0.01
280 10 -0.111529782414 -0.0249063676327 0.01
280 15 -0.114677354693 -0.0249063676327 0.01
280 20 -0.153850287199 -0.0249063676327 0.01
280 25 -0.136095836759 -0.0249063676327 0.01
280 30 -0.127375856042 -0.0249063676327 0.01
280 35 -0.0910692512989 -0.0249063676327 0.01
280 40 -0.126319184899 -0.0249063676327 0.01
280 45 -0.142186641693 -0.0249063676327 0.01
280 50 -0.123217009008 -0.0249063676327 0.01
280 55 -0.125323578715 -0.0249063676327 0.01
valid_acc 95.45333333333333
281 0 -0.147039458156 -0.0249063676327 0.01
281 5 -0.149697571993 -0.0249063676327 0.01
281 10 -0.127284839749 -0.0249063676327 0.01
281 15 -0.13870754838 -0.0249063676327 0.01
281 20 -0.146521195769 -0.0249063676327 0.01
281 25 -0.209236741066 -0.0249063676327 0.01
281 30 -0.15363804996 -0.0249063676327 0.01
281 35 -0.151799753308 -0.0249063676327 0.01
281 40 -0.140838697553 -0.0249063676327 0.01
281 45 -0.118173867464 -0.0249063676327 0.01
281 50 -0.123155288398 -0.0249063676327 0.01
281 55 -0.134182527661 -0.0249063676327 0.01
valid_acc 95.54666666666667
282 0 -0.145228296518 -0.0249063676327 0.01
282 5 -0.166910156608 -0.0249063676327 0.01
282 10 -0.171341210604 -0.0249063676327 0.01
282 15 -0.121327474713 -0.0249063676327 0.01
282 20 -0.14399176836 -0.0249063676327 0.01
282 25 -0.138863265514 -0.0249063676327 0.01
282 30 -0.122375458479 -0.0249063676327 0.01
282 35 -0.149145692587 -0.0249063676327 0.01
282 40 -0.120390221477 -0.0249063676327 0.01
282 45 -0.131851837039 -0.0249063676327 0.01
282 50 -0.132853284478 -0.0249063676327 0.01
282 55 -0.152847722173 -0.0249063676327 0.01
valid_acc 95.43666666666667
283 0 -0.136375427246 -0.0249063676327 0.01
283 5 -0.112297713757 -0.0249063676327 0.01
283 10 -0.184276744723 -0.0249063676327 0.01
283 15 -0.1441154778 -0.0249063676327 0.01
283 20 -0.102986097336 -0.0249063676327 0.01
283 25 -0.148481577635 -0.0249063676327 0.01
283 30 -0.177429586649 -0.0249063676327 0.01
283 35 -0.107493266463 -0.0249063676327 0.01
283 40 -0.143910035491 -0.0249063676327 0.01
283 45 -0.164101719856 -0.0249063676327 0.01
283 50 -0.117785729468 -0.0249063676327 0.01
283 55 -0.175818324089 -0.0249063676327 0.01
valid_acc 95.645
284 0 -0.136630937457 -0.0249063676327 0.01
284 5 -0.0929939225316 -0.0249063676327 0.01
284 10 -0.157077237964 -0.0249063676327 0.01
284 15 -0.13628539443 -0.0249063676327 0.01
284 20 -0.146986499429 -0.0249063676327 0.01
284 25 -0.167211309075 -0.0249063676327 0.01
284 30 -0.114103257656 -0.0249063676327 0.01
284 35 -0.164668396115 -0.0249063676327 0.01
284 40 -0.14595733583 -0.0249063676327 0.01
284 45 -0.134827956557 -0.0249063676327 0.01
284 50 -0.130179136992 -0.0249063676327 0.01
284 55 -0.127465650439 -0.0249063676327 0.01
valid_acc 95.51833333333335
285 0 -0.116848051548 -0.0249063676327 0.01
285 5 -0.135513305664 -0.0249063676327 0.01
285 10 -0.138330236077 -0.0249063676327 0.01
285 15 -0.162980660796 -0.0249063676327 0.01
285 20 -0.118898563087 -0.0249063676327 0.01
285 25 -0.144920110703 -0.0249063676327 0.01
285 30 -0.155367672443 -0.0249063676327 0.01
285 35 -0.091622710228 -0.0249063676327 0.01
285 40 -0.169370949268 -0.0249063676327 0.01
285 45 -0.0986340194941 -0.0249063676327 0.01
285 50 -0.177769944072 -0.0249063676327 0.01
285 55 -0.12915147841 -0.0249063676327 0.01
valid_acc 95.77833333333334
286 0 -0.149790450931 -0.0249063676327 0.01
286 5 -0.146741852164 -0.0249063676327 0.01
286 10 -0.1415835917 -0.0249063676327 0.01
286 15 -0.110200293362 -0.0249063676327 0.01
286 20 -0.145730793476 -0.0249063676327 0.01
286 25 -0.124764882028 -0.0249063676327 0.01
286 30 -0.136523380876 -0.0249063676327 0.01
286 35 -0.149413838983 -0.0249063676327 0.01
286 40 -0.164723679423 -0.0249063676327 0.01
286 45 -0.120505236089 -0.0249063676327 0.01
286 50 -0.112272173166 -0.0249063676327 0.01
286 55 -0.124107047915 -0.0249063676327 0.01
valid_acc 95.34666666666666
287 0 -0.0890993922949 -0.0249063676327 0.01
287 5 -0.130455568433 -0.0249063676327 0.01
287 10 -0.146975129843 -0.0249063676327 0.01
287 15 -0.097332328558 -0.0249063676327 0.01
287 20 -0.158209398389 -0.0249063676327 0.01
287 25 -0.162010520697 -0.0249063676327 0.01
287 30 -0.129163175821 -0.0249063676327 0.01
287 35 -0.141543507576 -0.0249063676327 0.01
287 40 -0.13870382309 -0.0249063676327 0.01
287 45 -0.120847456157 -0.0249063676327 0.01
287 50 -0.140630230308 -0.0249063676327 0.01
287 55 -0.112006574869 -0.0249063676327 0.01
valid_acc 95.905
288 0 -0.138475880027 -0.0249063676327 0.01
288 5 -0.119940049946 -0.0249063676327 0.01
288 10 -0.126955643296 -0.0249063676327 0.01
288 15 -0.119448937476 -0.0249063676327 0.01
288 20 -0.128466829658 -0.0249063676327 0.01
288 25 -0.110205560923 -0.0249063676327 0.01
288 30 -0.0963671207428 -0.0249063676327 0.01
288 35 -0.119956590235 -0.0249063676327 0.01
288 40 -0.143803283572 -0.0249063676327 0.01
288 45 -0.114505261183 -0.0249063676327 0.01
288 50 -0.172807022929 -0.0249063676327 0.01
288 55 -0.137309759855 -0.0249063676327 0.01
valid_acc 95.85166666666667
289 0 -0.107139892876 -0.0249063676327 0.01
289 5 -0.14392067492 -0.0249063676327 0.01
289 10 -0.148021042347 -0.0249063676327 0.01
289 15 -0.151187554002 -0.0249063676327 0.01
289 20 -0.171447455883 -0.0249063676327 0.01
289 25 -0.104497790337 -0.0249063676327 0.01
289 30 -0.105764321983 -0.0249063676327 0.01
289 35 -0.0853819772601 -0.0249063676327 0.01
289 40 -0.141768366098 -0.0249063676327 0.01
289 45 -0.111159235239 -0.0249063676327 0.01
289 50 -0.148600757122 -0.0249063676327 0.01
289 55 -0.130206048489 -0.0249063676327 0.01
valid_acc 95.64
290 0 -0.136348247528 -0.0249063676327 0.01
290 5 -0.102578409016 -0.0249063676327 0.01
290 10 -0.116462484002 -0.0249063676327 0.01
290 15 -0.148477673531 -0.0249063676327 0.01
290 20 -0.105541698635 -0.0249063676327 0.01
290 25 -0.116524606943 -0.0249063676327 0.01
290 30 -0.184659913182 -0.0249063676327 0.01
290 35 -0.125862821937 -0.0249063676327 0.01
290 40 -0.0854595452547 -0.0249063676327 0.01
290 45 -0.0959890186787 -0.0249063676327 0.01
290 50 -0.166446805 -0.0249063676327 0.01
290 55 -0.144700303674 -0.0249063676327 0.01
valid_acc 95.77
291 0 -0.156893968582 -0.0249063676327 0.01
291 5 -0.125991791487 -0.0249063676327 0.01
291 10 -0.161239892244 -0.0249063676327 0.01
291 15 -0.128546014428 -0.0249063676327 0.01
291 20 -0.116793431342 -0.0249063676327 0.01
291 25 -0.110167741776 -0.0249063676327 0.01
291 30 -0.110384844244 -0.0249063676327 0.01
291 35 -0.105532579124 -0.0249063676327 0.01
291 40 -0.135504350066 -0.0249063676327 0.01
291 45 -0.139508023858 -0.0249063676327 0.01
291 50 -0.133893892169 -0.0249063676327 0.01
291 55 -0.113674141467 -0.0249063676327 0.01
valid_acc 95.33
292 0 -0.131528422236 -0.0249063676327 0.01
292 5 -0.111332222819 -0.0249063676327 0.01
292 10 -0.134474799037 -0.0249063676327 0.01
292 15 -0.129885435104 -0.0249063676327 0.01
292 20 -0.132591098547 -0.0249063676327 0.01
292 25 -0.162392109632 -0.0249063676327 0.01
292 30 -0.101946875453 -0.0249063676327 0.01
292 35 -0.0975028946996 -0.0249063676327 0.01
292 40 -0.121408499777 -0.0249063676327 0.01
292 45 -0.1005275473 -0.0249063676327 0.01
292 50 -0.163310095668 -0.0249063676327 0.01
292 55 -0.0868398696184 -0.0249063676327 0.01
valid_acc 95.74666666666667
293 0 -0.168142348528 -0.0249063676327 0.01
293 5 -0.142961487174 -0.0249063676327 0.01
293 10 -0.145347058773 -0.0249063676327 0.01
293 15 -0.12118049711 -0.0249063676327 0.01
293 20 -0.134934917092 -0.0249063676327 0.01
293 25 -0.131124719977 -0.0249063676327 0.01
293 30 -0.139846920967 -0.0249063676327 0.01
293 35 -0.15787473321 -0.0249063676327 0.01
293 40 -0.119491904974 -0.0249063676327 0.01
293 45 -0.127970591187 -0.0249063676327 0.01
293 50 -0.157705098391 -0.0249063676327 0.01
293 55 -0.104803062975 -0.0249063676327 0.01
valid_acc 95.73166666666667
294 0 -0.164887830615 -0.0249063676327 0.01
294 5 -0.108257979155 -0.0249063676327 0.01
294 10 -0.130477935076 -0.0249063676327 0.01
294 15 -0.121569700539 -0.0249063676327 0.01
294 20 -0.135665476322 -0.0249063676327 0.01
294 25 -0.107686392963 -0.0249063676327 0.01
294 30 -0.112809613347 -0.0249063676327 0.01
294 35 -0.108562335372 -0.0249063676327 0.01
294 40 -0.213281571865 -0.0249063676327 0.01
294 45 -0.0881291031837 -0.0249063676327 0.01
294 50 -0.137437671423 -0.0249063676327 0.01
294 55 -0.128516480327 -0.0249063676327 0.01
valid_acc 95.86166666666666
295 0 -0.130128920078 -0.0249063676327 0.01
295 5 -0.112321741879 -0.0249063676327 0.01
295 10 -0.17364422977 -0.0249063676327 0.01
295 15 -0.164612397552 -0.0249063676327 0.01
295 20 -0.0972039625049 -0.0249063676327 0.01
295 25 -0.147577911615 -0.0249063676327 0.01
295 30 -0.131539642811 -0.0249063676327 0.01
295 35 -0.134079962969 -0.0249063676327 0.01
295 40 -0.136595457792 -0.0249063676327 0.01
295 45 -0.179489314556 -0.0249063676327 0.01
295 50 -0.106558889151 -0.0249063676327 0.01
295 55 -0.115529619157 -0.0249063676327 0.01
valid_acc 95.795
296 0 -0.143267393112 -0.0249063676327 0.01
296 5 -0.117168232799 -0.0249063676327 0.01
296 10 -0.121377840638 -0.0249063676327 0.01
296 15 -0.11649980396 -0.0249063676327 0.01
296 20 -0.118499755859 -0.0249063676327 0.01
296 25 -0.150268226862 -0.0249063676327 0.01
296 30 -0.111232824624 -0.0249063676327 0.01
296 35 -0.143500596285 -0.0249063676327 0.01
296 40 -0.0961132347584 -0.0249063676327 0.01
296 45 -0.125697687268 -0.0249063676327 0.01
296 50 -0.133831098676 -0.0249063676327 0.01
296 55 -0.141444832087 -0.0249063676327 0.01
valid_acc 95.30999999999999
297 0 -0.163662388921 -0.0249063676327 0.01
297 5 -0.143377527595 -0.0249063676327 0.01
297 10 -0.162172079086 -0.0249063676327 0.01
297 15 -0.164224818349 -0.0249063676327 0.01
297 20 -0.0968138128519 -0.0249063676327 0.01
297 25 -0.151337325573 -0.0249063676327 0.01
297 30 -0.126516416669 -0.0249063676327 0.01
297 35 -0.160577088594 -0.0249063676327 0.01
297 40 -0.132771447301 -0.0249063676327 0.01
297 45 -0.0999313667417 -0.0249063676327 0.01
297 50 -0.123763807118 -0.0249063676327 0.01
297 55 -0.118508927524 -0.0249063676327 0.01
valid_acc 95.67
298 0 -0.14034537971 -0.0249063676327 0.01
298 5 -0.149334549904 -0.0249063676327 0.01
298 10 -0.115720264614 -0.0249063676327 0.01
298 15 -0.106145054102 -0.0249063676327 0.01
298 20 -0.14876075089 -0.0249063676327 0.01
298 25 -0.121020168066 -0.0249063676327 0.01
298 30 -0.102354474366 -0.0249063676327 0.01
298 35 -0.161934942007 -0.0249063676327 0.01
298 40 -0.136257514358 -0.0249063676327 0.01
298 45 -0.177727356553 -0.0249063676327 0.01
298 50 -0.162447378039 -0.0249063676327 0.01
298 55 -0.166371643543 -0.0249063676327 0.01
valid_acc 95.73166666666667
299 0 -0.133649632335 -0.0249063676327 0.01
299 5 -0.145225822926 -0.0249063676327 0.01
299 10 -0.146333858371 -0.0249063676327 0.01
299 15 -0.1170739308 -0.0249063676327 0.01
299 20 -0.154226928949 -0.0249063676327 0.01
299 25 -0.101971112192 -0.0249063676327 0.01
299 30 -0.0993184670806 -0.0249063676327 0.01
299 35 -0.125582993031 -0.0249063676327 0.01
299 40 -0.128264456987 -0.0249063676327 0.01
299 45 -0.135524645448 -0.0249063676327 0.01
299 50 -0.10744933784 -0.0249063676327 0.01
299 55 -0.139569625258 -0.0249063676327 0.01
valid_acc 95.78833333333333
300 0 -0.13381101191 -0.0249063676327 0.01
300 5 -0.188772559166 -0.0249063676327 0.01
300 10 -0.155195862055 -0.0249063676327 0.01
300 15 -0.116457529366 -0.0249063676327 0.01
300 20 -0.118354745209 -0.0249063676327 0.01
300 25 -0.105151519179 -0.0249063676327 0.01
300 30 -0.123921409249 -0.0249063676327 0.01
300 35 -0.11506909132 -0.0249063676327 0.01
300 40 -0.143985807896 -0.0249063676327 0.01
300 45 -0.108036637306 -0.0249063676327 0.01
300 50 -0.143300130963 -0.0249063676327 0.01
300 55 -0.143106624484 -0.0249063676327 0.01
valid_acc 95.535

In [20]:

    

evaluate(best_model, valid_loader, print_mode=True)


    

    




Average loss: 0.1493, Accuracy: 57571/60000 (95.9517%)







    
Out[20]:





0.9595166666666667

In [21]:

    

evaluate(best_model, test_loader, print_mode=True)


    

    




Average loss: 0.1398, Accuracy: 9623/10000 (96.2300%)







    
Out[21]:





0.9623

In [22]:

    

evaluate(best_model, train_loader, print_mode=True)


    

    




Average loss: 0.1493, Accuracy: 57571/60000 (95.9517%)







    
Out[22]:





0.9595166666666667

In [23]:

    

update_model(es.best_param(), model, model_shapes)


    

In [24]:

    

evaluate(model, valid_loader, print_mode=True)


    

    




Average loss: 0.1689, Accuracy: 57364/60000 (95.6067%)







    
Out[24]:





0.9560666666666666

In [25]:

    

evaluate(model, test_loader, print_mode=True)


    

    




Average loss: 0.1591, Accuracy: 9558/10000 (95.5800%)







    
Out[25]:





0.9558

In [26]:

    

evaluate(model, train_loader, print_mode=True)


    

    




Average loss: 0.1689, Accuracy: 57364/60000 (95.6067%)







    
Out[26]:





0.9560666666666666

In [27]:

    

update_model(es.current_param(), model, model_shapes)


    

In [28]:

    

evaluate(model, valid_loader, print_mode=True)


    

    




Average loss: 0.1554, Accuracy: 57321/60000 (95.5350%)







    
Out[28]:





0.95535

In [29]:

    

evaluate(model, test_loader, print_mode=True)


    

    




Average loss: 0.1479, Accuracy: 9569/10000 (95.6900%)







    
Out[29]:





0.9569

In [30]:

    

evaluate(model, train_loader, print_mode=True)


    

    




Average loss: 0.1554, Accuracy: 57321/60000 (95.5350%)







    
Out[30]:





0.95535

In [31]:

    

eval_acc = evaluate(best_model, test_loader)
print('final test acc', eval_acc * 100.)


    

    




Average loss: 0.1398, Accuracy: 9623/10000 (96.2300%)

final test acc 96.23

In [32]:

    

param_count = 0
for param in model.parameters():
  print(param.data.shape)
  param_count += np.product(param.data.shape)
print(param_count)


    

    




torch.Size([8, 1, 5, 5])
torch.Size([8])
torch.Size([16, 8, 5, 5])
torch.Size([16])
torch.Size([10, 784])
torch.Size([10])
11274

In [33]:

    

orig_params = []
for param in orig_model.parameters():
  orig_params.append(param.data.cpu().numpy().flatten())


    

In [34]:

    

orig_params_flat = np.concatenate(orig_params)


    

In [35]:

    

import matplotlib.pyplot as plt


    

In [36]:

    

_ = plt.hist(orig_params_flat, bins=200)
plt.show()


    

In [37]:

    

final_params = []
for param in best_model.parameters():
  final_params.append(param.data.cpu().numpy().flatten())
final_params_flat = np.concatenate(final_params)


    

In [38]:

    

_ = plt.hist(final_params_flat, bins=200)
plt.show()


    

In [ ]:

    




    

In [ ]: