In [1]:
%load_ext autoreload
%autoreload 2
In [3]:
import sys
sys.path.append('..')
In [9]:
import numpy as np
import matplotlib.pyplot as plt
%matplotlib inline
In [1]:
from sklearn import datasets
from sklearn.metrics import classification_report, roc_curve, auc
from sklearn.model_selection import train_test_split
In [4]:
from vantgrd.logistic import LogisticRegressionFTRL, \
LogisticRegressionWithAdagrad, LogisticRegressionWithAdadelta
from vantgrd.fm import FMWithAdagrad, FMWithSGD
In [5]:
epochs = 1
X, y = datasets.make_classification(n_samples=200000, n_features=25,
n_informative=7, n_redundant=5, n_repeated=3,
random_state=42, weights=[0.92, 0.08])
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.25, random_state=42)
models = [
LogisticRegressionWithAdagrad(eta=.01, epochs=epochs, rate=1000),
LogisticRegressionWithAdadelta(epochs=epochs, rate=1000),
LogisticRegressionFTRL(epochs=epochs, rate=1000),
FMWithAdagrad(eta=0.01, reg0=.01, regw=.01, regv=.01, rate=1000, epochs=epochs, n_factors=5),
FMWithSGD(eta=0.01, reg0=.01, regw=.01, regv=.01, rate=1000, epochs=epochs, n_factors=5)
]
In [6]:
colors = {0: 'blue', 1: 'red', 2: 'black', 3: 'green', 4: 'yellow'}
labels = {0: 'lr-adagrad', 1: 'lr-adadelta', 2: 'lr-ftrl', 3: 'fm-adagrad', 4: 'fm-sgd'}
In [10]:
fig = plt.figure()
ax = fig.add_subplot(1, 2, 1)
ax.grid()
ax.set_ylabel("Logloss")
bx = fig.add_subplot(1, 2, 2)
bx.grid()
bx.set_xlabel("False positive rate")
bx.set_ylabel("True positive rate")
for idx, lr in enumerate(models):
lr.fit(X_train, y_train)
y_pred = lr.predict(X_test)
print(classification_report(y_test, y_pred))
ax.plot(lr.train_tracker_.loss_, color=colors[idx], label=labels[idx])
y_test_prob = lr.raw_predict(X_test)
fpr, tpr, thresholds = roc_curve(y_test, y_test_prob)
roc_auc = auc(fpr, tpr)
print("AUC = %f" % roc_auc)
bx.plot(fpr, tpr, color=colors[idx], label='{0} ROC area = {1:.2f}'.format(labels[idx], roc_auc))
plt.show()
Epoch: 0 | Training Samples: 1000 | Loss: 470.72 | LossAdj: 0.47072 | Time taken: 0 seconds
Epoch: 0 | Training Samples: 2000 | Loss: 887.01 | LossAdj: 0.44350 | Time taken: 0 seconds
Epoch: 0 | Training Samples: 3000 | Loss: 1279.41 | LossAdj: 0.42647 | Time taken: 0 seconds
Epoch: 0 | Training Samples: 4000 | Loss: 1665.92 | LossAdj: 0.41648 | Time taken: 0 seconds
Epoch: 0 | Training Samples: 5000 | Loss: 2025.61 | LossAdj: 0.40512 | Time taken: 1 seconds
Epoch: 0 | Training Samples: 6000 | Loss: 2388.46 | LossAdj: 0.39808 | Time taken: 1 seconds
Epoch: 0 | Training Samples: 7000 | Loss: 2756.16 | LossAdj: 0.39374 | Time taken: 1 seconds
Epoch: 0 | Training Samples: 8000 | Loss: 3101.86 | LossAdj: 0.38773 | Time taken: 1 seconds
Epoch: 0 | Training Samples: 9000 | Loss: 3483.62 | LossAdj: 0.38707 | Time taken: 1 seconds
Epoch: 0 | Training Samples: 10000 | Loss: 3837.15 | LossAdj: 0.38371 | Time taken: 2 seconds
Epoch: 0 | Training Samples: 11000 | Loss: 4189.33 | LossAdj: 0.38085 | Time taken: 2 seconds
Epoch: 0 | Training Samples: 12000 | Loss: 4550.31 | LossAdj: 0.37919 | Time taken: 2 seconds
Epoch: 0 | Training Samples: 13000 | Loss: 4887.99 | LossAdj: 0.37600 | Time taken: 2 seconds
Epoch: 0 | Training Samples: 14000 | Loss: 5238.20 | LossAdj: 0.37416 | Time taken: 3 seconds
Epoch: 0 | Training Samples: 15000 | Loss: 5591.28 | LossAdj: 0.37275 | Time taken: 3 seconds
Epoch: 0 | Training Samples: 16000 | Loss: 5928.90 | LossAdj: 0.37056 | Time taken: 3 seconds
Epoch: 0 | Training Samples: 17000 | Loss: 6261.83 | LossAdj: 0.36834 | Time taken: 3 seconds
Epoch: 0 | Training Samples: 18000 | Loss: 6608.72 | LossAdj: 0.36715 | Time taken: 4 seconds
Epoch: 0 | Training Samples: 19000 | Loss: 6962.23 | LossAdj: 0.36643 | Time taken: 4 seconds
Epoch: 0 | Training Samples: 20000 | Loss: 7309.24 | LossAdj: 0.36546 | Time taken: 4 seconds
Epoch: 0 | Training Samples: 21000 | Loss: 7647.64 | LossAdj: 0.36417 | Time taken: 4 seconds
Epoch: 0 | Training Samples: 22000 | Loss: 7999.27 | LossAdj: 0.36360 | Time taken: 4 seconds
Epoch: 0 | Training Samples: 23000 | Loss: 8348.37 | LossAdj: 0.36297 | Time taken: 5 seconds
Epoch: 0 | Training Samples: 24000 | Loss: 8671.81 | LossAdj: 0.36133 | Time taken: 5 seconds
Epoch: 0 | Training Samples: 25000 | Loss: 9001.01 | LossAdj: 0.36004 | Time taken: 5 seconds
Epoch: 0 | Training Samples: 26000 | Loss: 9365.67 | LossAdj: 0.36022 | Time taken: 5 seconds
Epoch: 0 | Training Samples: 27000 | Loss: 9704.38 | LossAdj: 0.35942 | Time taken: 6 seconds
Epoch: 0 | Training Samples: 28000 | Loss: 10045.72 | LossAdj: 0.35878 | Time taken: 6 seconds
Epoch: 0 | Training Samples: 29000 | Loss: 10388.37 | LossAdj: 0.35822 | Time taken: 6 seconds
Epoch: 0 | Training Samples: 30000 | Loss: 10744.64 | LossAdj: 0.35815 | Time taken: 6 seconds
Epoch: 0 | Training Samples: 31000 | Loss: 11103.24 | LossAdj: 0.35817 | Time taken: 6 seconds
Epoch: 0 | Training Samples: 32000 | Loss: 11434.73 | LossAdj: 0.35734 | Time taken: 7 seconds
Epoch: 0 | Training Samples: 33000 | Loss: 11772.02 | LossAdj: 0.35673 | Time taken: 7 seconds
Epoch: 0 | Training Samples: 34000 | Loss: 12099.72 | LossAdj: 0.35587 | Time taken: 7 seconds
Epoch: 0 | Training Samples: 35000 | Loss: 12421.56 | LossAdj: 0.35490 | Time taken: 7 seconds
Epoch: 0 | Training Samples: 36000 | Loss: 12775.38 | LossAdj: 0.35487 | Time taken: 8 seconds
Epoch: 0 | Training Samples: 37000 | Loss: 13082.44 | LossAdj: 0.35358 | Time taken: 8 seconds
Epoch: 0 | Training Samples: 38000 | Loss: 13395.14 | LossAdj: 0.35250 | Time taken: 8 seconds
Epoch: 0 | Training Samples: 39000 | Loss: 13726.41 | LossAdj: 0.35196 | Time taken: 8 seconds
Epoch: 0 | Training Samples: 40000 | Loss: 14070.23 | LossAdj: 0.35176 | Time taken: 8 seconds
Epoch: 0 | Training Samples: 41000 | Loss: 14405.91 | LossAdj: 0.35136 | Time taken: 9 seconds
Epoch: 0 | Training Samples: 42000 | Loss: 14739.10 | LossAdj: 0.35093 | Time taken: 9 seconds
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Epoch: 0 | Training Samples: 44000 | Loss: 15420.61 | LossAdj: 0.35047 | Time taken: 9 seconds
Epoch: 0 | Training Samples: 45000 | Loss: 15746.40 | LossAdj: 0.34992 | Time taken: 9 seconds
Epoch: 0 | Training Samples: 46000 | Loss: 16077.22 | LossAdj: 0.34950 | Time taken: 10 seconds
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Epoch: 0 | Training Samples: 49000 | Loss: 17084.91 | LossAdj: 0.34867 | Time taken: 10 seconds
Epoch: 0 | Training Samples: 50000 | Loss: 17403.51 | LossAdj: 0.34807 | Time taken: 11 seconds
Epoch: 0 | Training Samples: 51000 | Loss: 17742.75 | LossAdj: 0.34790 | Time taken: 11 seconds
Epoch: 0 | Training Samples: 52000 | Loss: 18083.85 | LossAdj: 0.34777 | Time taken: 11 seconds
Epoch: 0 | Training Samples: 53000 | Loss: 18402.10 | LossAdj: 0.34721 | Time taken: 11 seconds
Epoch: 0 | Training Samples: 54000 | Loss: 18735.51 | LossAdj: 0.34695 | Time taken: 11 seconds
Epoch: 0 | Training Samples: 55000 | Loss: 19067.36 | LossAdj: 0.34668 | Time taken: 12 seconds
Epoch: 0 | Training Samples: 56000 | Loss: 19390.04 | LossAdj: 0.34625 | Time taken: 12 seconds
Epoch: 0 | Training Samples: 57000 | Loss: 19740.23 | LossAdj: 0.34632 | Time taken: 12 seconds
Epoch: 0 | Training Samples: 58000 | Loss: 20087.49 | LossAdj: 0.34634 | Time taken: 12 seconds
Epoch: 0 | Training Samples: 59000 | Loss: 20419.64 | LossAdj: 0.34610 | Time taken: 13 seconds
Epoch: 0 | Training Samples: 60000 | Loss: 20761.32 | LossAdj: 0.34602 | Time taken: 13 seconds
Epoch: 0 | Training Samples: 61000 | Loss: 21085.56 | LossAdj: 0.34566 | Time taken: 13 seconds
Epoch: 0 | Training Samples: 62000 | Loss: 21404.26 | LossAdj: 0.34523 | Time taken: 13 seconds
Epoch: 0 | Training Samples: 63000 | Loss: 21739.67 | LossAdj: 0.34507 | Time taken: 13 seconds
Epoch: 0 | Training Samples: 64000 | Loss: 22046.69 | LossAdj: 0.34448 | Time taken: 14 seconds
Epoch: 0 | Training Samples: 65000 | Loss: 22372.83 | LossAdj: 0.34420 | Time taken: 14 seconds
Epoch: 0 | Training Samples: 66000 | Loss: 22676.00 | LossAdj: 0.34358 | Time taken: 14 seconds
Epoch: 0 | Training Samples: 67000 | Loss: 23010.78 | LossAdj: 0.34344 | Time taken: 14 seconds
Epoch: 0 | Training Samples: 68000 | Loss: 23333.86 | LossAdj: 0.34315 | Time taken: 15 seconds
Epoch: 0 | Training Samples: 69000 | Loss: 23660.18 | LossAdj: 0.34290 | Time taken: 15 seconds
Epoch: 0 | Training Samples: 70000 | Loss: 23966.86 | LossAdj: 0.34238 | Time taken: 15 seconds
Epoch: 0 | Training Samples: 71000 | Loss: 24295.49 | LossAdj: 0.34219 | Time taken: 15 seconds
Epoch: 0 | Training Samples: 72000 | Loss: 24613.06 | LossAdj: 0.34185 | Time taken: 16 seconds
Epoch: 0 | Training Samples: 73000 | Loss: 24919.90 | LossAdj: 0.34137 | Time taken: 16 seconds
Epoch: 0 | Training Samples: 74000 | Loss: 25223.00 | LossAdj: 0.34085 | Time taken: 16 seconds
Epoch: 0 | Training Samples: 75000 | Loss: 25537.77 | LossAdj: 0.34050 | Time taken: 16 seconds
Epoch: 0 | Training Samples: 76000 | Loss: 25880.14 | LossAdj: 0.34053 | Time taken: 16 seconds
Epoch: 0 | Training Samples: 77000 | Loss: 26206.60 | LossAdj: 0.34035 | Time taken: 17 seconds
Epoch: 0 | Training Samples: 78000 | Loss: 26545.99 | LossAdj: 0.34033 | Time taken: 17 seconds
Epoch: 0 | Training Samples: 79000 | Loss: 26862.26 | LossAdj: 0.34003 | Time taken: 17 seconds
Epoch: 0 | Training Samples: 80000 | Loss: 27196.44 | LossAdj: 0.33996 | Time taken: 17 seconds
Epoch: 0 | Training Samples: 81000 | Loss: 27538.10 | LossAdj: 0.33998 | Time taken: 18 seconds
Epoch: 0 | Training Samples: 82000 | Loss: 27872.81 | LossAdj: 0.33991 | Time taken: 18 seconds
Epoch: 0 | Training Samples: 83000 | Loss: 28214.18 | LossAdj: 0.33993 | Time taken: 18 seconds
Epoch: 0 | Training Samples: 84000 | Loss: 28545.62 | LossAdj: 0.33983 | Time taken: 18 seconds
Epoch: 0 | Training Samples: 85000 | Loss: 28855.19 | LossAdj: 0.33947 | Time taken: 18 seconds
Epoch: 0 | Training Samples: 86000 | Loss: 29199.64 | LossAdj: 0.33953 | Time taken: 19 seconds
Epoch: 0 | Training Samples: 87000 | Loss: 29541.74 | LossAdj: 0.33956 | Time taken: 19 seconds
Epoch: 0 | Training Samples: 88000 | Loss: 29873.75 | LossAdj: 0.33947 | Time taken: 19 seconds
Epoch: 0 | Training Samples: 89000 | Loss: 30180.09 | LossAdj: 0.33910 | Time taken: 19 seconds
Epoch: 0 | Training Samples: 90000 | Loss: 30497.45 | LossAdj: 0.33886 | Time taken: 20 seconds
Epoch: 0 | Training Samples: 91000 | Loss: 30842.46 | LossAdj: 0.33893 | Time taken: 20 seconds
Epoch: 0 | Training Samples: 92000 | Loss: 31184.71 | LossAdj: 0.33896 | Time taken: 20 seconds
Epoch: 0 | Training Samples: 93000 | Loss: 31482.70 | LossAdj: 0.33852 | Time taken: 20 seconds
Epoch: 0 | Training Samples: 94000 | Loss: 31823.68 | LossAdj: 0.33855 | Time taken: 20 seconds
Epoch: 0 | Training Samples: 95000 | Loss: 32143.73 | LossAdj: 0.33836 | Time taken: 21 seconds
Epoch: 0 | Training Samples: 96000 | Loss: 32468.74 | LossAdj: 0.33822 | Time taken: 21 seconds
Epoch: 0 | Training Samples: 97000 | Loss: 32785.78 | LossAdj: 0.33800 | Time taken: 21 seconds
Epoch: 0 | Training Samples: 98000 | Loss: 33098.98 | LossAdj: 0.33774 | Time taken: 21 seconds
Epoch: 0 | Training Samples: 99000 | Loss: 33438.79 | LossAdj: 0.33777 | Time taken: 22 seconds
Epoch: 0 | Training Samples: 100000 | Loss: 33771.45 | LossAdj: 0.33771 | Time taken: 22 seconds
Epoch: 0 | Training Samples: 101000 | Loss: 34094.00 | LossAdj: 0.33756 | Time taken: 22 seconds
Epoch: 0 | Training Samples: 102000 | Loss: 34416.90 | LossAdj: 0.33742 | Time taken: 22 seconds
Epoch: 0 | Training Samples: 103000 | Loss: 34754.25 | LossAdj: 0.33742 | Time taken: 22 seconds
Epoch: 0 | Training Samples: 104000 | Loss: 35063.61 | LossAdj: 0.33715 | Time taken: 23 seconds
Epoch: 0 | Training Samples: 105000 | Loss: 35395.20 | LossAdj: 0.33710 | Time taken: 23 seconds
Epoch: 0 | Training Samples: 106000 | Loss: 35735.43 | LossAdj: 0.33713 | Time taken: 23 seconds
Epoch: 0 | Training Samples: 107000 | Loss: 36050.06 | LossAdj: 0.33692 | Time taken: 23 seconds
Epoch: 0 | Training Samples: 108000 | Loss: 36355.68 | LossAdj: 0.33663 | Time taken: 24 seconds
Epoch: 0 | Training Samples: 109000 | Loss: 36682.73 | LossAdj: 0.33654 | Time taken: 24 seconds
Epoch: 0 | Training Samples: 110000 | Loss: 37012.32 | LossAdj: 0.33648 | Time taken: 24 seconds
Epoch: 0 | Training Samples: 111000 | Loss: 37337.16 | LossAdj: 0.33637 | Time taken: 24 seconds
Epoch: 0 | Training Samples: 112000 | Loss: 37654.82 | LossAdj: 0.33620 | Time taken: 24 seconds
Epoch: 0 | Training Samples: 113000 | Loss: 37974.46 | LossAdj: 0.33606 | Time taken: 25 seconds
Epoch: 0 | Training Samples: 114000 | Loss: 38306.67 | LossAdj: 0.33602 | Time taken: 25 seconds
Epoch: 0 | Training Samples: 115000 | Loss: 38627.66 | LossAdj: 0.33589 | Time taken: 25 seconds
Epoch: 0 | Training Samples: 116000 | Loss: 38946.93 | LossAdj: 0.33575 | Time taken: 25 seconds
Epoch: 0 | Training Samples: 117000 | Loss: 39283.28 | LossAdj: 0.33575 | Time taken: 26 seconds
Epoch: 0 | Training Samples: 118000 | Loss: 39603.88 | LossAdj: 0.33563 | Time taken: 26 seconds
Epoch: 0 | Training Samples: 119000 | Loss: 39928.25 | LossAdj: 0.33553 | Time taken: 26 seconds
Epoch: 0 | Training Samples: 120000 | Loss: 40274.44 | LossAdj: 0.33562 | Time taken: 26 seconds
Epoch: 0 | Training Samples: 121000 | Loss: 40609.30 | LossAdj: 0.33561 | Time taken: 27 seconds
Epoch: 0 | Training Samples: 122000 | Loss: 40941.98 | LossAdj: 0.33559 | Time taken: 27 seconds
Epoch: 0 | Training Samples: 123000 | Loss: 41249.06 | LossAdj: 0.33536 | Time taken: 27 seconds
Epoch: 0 | Training Samples: 124000 | Loss: 41601.13 | LossAdj: 0.33549 | Time taken: 27 seconds
Epoch: 0 | Training Samples: 125000 | Loss: 41919.35 | LossAdj: 0.33535 | Time taken: 27 seconds
Epoch: 0 | Training Samples: 126000 | Loss: 42244.57 | LossAdj: 0.33527 | Time taken: 28 seconds
Epoch: 0 | Training Samples: 127000 | Loss: 42572.57 | LossAdj: 0.33522 | Time taken: 28 seconds
Epoch: 0 | Training Samples: 128000 | Loss: 42872.83 | LossAdj: 0.33494 | Time taken: 28 seconds
Epoch: 0 | Training Samples: 129000 | Loss: 43168.19 | LossAdj: 0.33464 | Time taken: 28 seconds
Epoch: 0 | Training Samples: 130000 | Loss: 43475.67 | LossAdj: 0.33443 | Time taken: 29 seconds
Epoch: 0 | Training Samples: 131000 | Loss: 43792.90 | LossAdj: 0.33430 | Time taken: 29 seconds
Epoch: 0 | Training Samples: 132000 | Loss: 44119.77 | LossAdj: 0.33424 | Time taken: 29 seconds
Epoch: 0 | Training Samples: 133000 | Loss: 44440.39 | LossAdj: 0.33414 | Time taken: 29 seconds
Epoch: 0 | Training Samples: 134000 | Loss: 44773.24 | LossAdj: 0.33413 | Time taken: 29 seconds
Epoch: 0 | Training Samples: 135000 | Loss: 45113.47 | LossAdj: 0.33417 | Time taken: 30 seconds
Epoch: 0 | Training Samples: 136000 | Loss: 45432.50 | LossAdj: 0.33406 | Time taken: 30 seconds
Epoch: 0 | Training Samples: 137000 | Loss: 45762.35 | LossAdj: 0.33403 | Time taken: 30 seconds
Epoch: 0 | Training Samples: 138000 | Loss: 46058.09 | LossAdj: 0.33375 | Time taken: 30 seconds
Epoch: 0 | Training Samples: 139000 | Loss: 46355.22 | LossAdj: 0.33349 | Time taken: 31 seconds
Epoch: 0 | Training Samples: 140000 | Loss: 46671.31 | LossAdj: 0.33337 | Time taken: 31 seconds
Epoch: 0 | Training Samples: 141000 | Loss: 46983.53 | LossAdj: 0.33322 | Time taken: 31 seconds
Epoch: 0 | Training Samples: 142000 | Loss: 47303.58 | LossAdj: 0.33312 | Time taken: 31 seconds
Epoch: 0 | Training Samples: 143000 | Loss: 47625.97 | LossAdj: 0.33305 | Time taken: 31 seconds
Epoch: 0 | Training Samples: 144000 | Loss: 47932.16 | LossAdj: 0.33286 | Time taken: 32 seconds
Epoch: 0 | Training Samples: 145000 | Loss: 48235.09 | LossAdj: 0.33266 | Time taken: 32 seconds
Epoch: 0 | Training Samples: 146000 | Loss: 48575.04 | LossAdj: 0.33271 | Time taken: 32 seconds
Epoch: 0 | Training Samples: 147000 | Loss: 48897.69 | LossAdj: 0.33264 | Time taken: 32 seconds
Epoch: 0 | Training Samples: 148000 | Loss: 49233.54 | LossAdj: 0.33266 | Time taken: 33 seconds
Epoch: 0 | Training Samples: 149000 | Loss: 49562.70 | LossAdj: 0.33264 | Time taken: 33 seconds
Epoch: 0 | Training Samples: 150000 | Loss: 49892.19 | LossAdj: 0.33261 | Time taken: 33 seconds
--- TRAINING FINISHED IN 33 SECONDS WITH LOSS 0.33 ---
precision recall f1-score support
0 0.97 0.89 0.93 45786
1 0.38 0.72 0.50 4214
accuracy 0.88 50000
macro avg 0.68 0.81 0.71 50000
weighted avg 0.92 0.88 0.89 50000
AUC = 0.895150
Epoch: 0 | Training Samples: 1000 | Loss: 573.45 | LossAdj: 0.57345 | Time taken: 0 seconds
Epoch: 0 | Training Samples: 2000 | Loss: 1052.40 | LossAdj: 0.52620 | Time taken: 0 seconds
Epoch: 0 | Training Samples: 3000 | Loss: 1480.65 | LossAdj: 0.49355 | Time taken: 0 seconds
Epoch: 0 | Training Samples: 4000 | Loss: 1860.74 | LossAdj: 0.46519 | Time taken: 0 seconds
Epoch: 0 | Training Samples: 5000 | Loss: 2200.74 | LossAdj: 0.44015 | Time taken: 1 seconds
Epoch: 0 | Training Samples: 6000 | Loss: 2508.19 | LossAdj: 0.41803 | Time taken: 1 seconds
Epoch: 0 | Training Samples: 7000 | Loss: 2796.02 | LossAdj: 0.39943 | Time taken: 1 seconds
Epoch: 0 | Training Samples: 8000 | Loss: 3051.23 | LossAdj: 0.38140 | Time taken: 1 seconds
Epoch: 0 | Training Samples: 9000 | Loss: 3332.85 | LossAdj: 0.37032 | Time taken: 2 seconds
Epoch: 0 | Training Samples: 10000 | Loss: 3594.76 | LossAdj: 0.35948 | Time taken: 2 seconds
Epoch: 0 | Training Samples: 11000 | Loss: 3852.40 | LossAdj: 0.35022 | Time taken: 2 seconds
Epoch: 0 | Training Samples: 12000 | Loss: 4104.73 | LossAdj: 0.34206 | Time taken: 2 seconds
Epoch: 0 | Training Samples: 13000 | Loss: 4344.82 | LossAdj: 0.33422 | Time taken: 2 seconds
Epoch: 0 | Training Samples: 14000 | Loss: 4589.11 | LossAdj: 0.32779 | Time taken: 3 seconds
Epoch: 0 | Training Samples: 15000 | Loss: 4821.60 | LossAdj: 0.32144 | Time taken: 3 seconds
Epoch: 0 | Training Samples: 16000 | Loss: 5062.84 | LossAdj: 0.31643 | Time taken: 3 seconds
Epoch: 0 | Training Samples: 17000 | Loss: 5295.81 | LossAdj: 0.31152 | Time taken: 3 seconds
Epoch: 0 | Training Samples: 18000 | Loss: 5536.61 | LossAdj: 0.30759 | Time taken: 4 seconds
Epoch: 0 | Training Samples: 19000 | Loss: 5800.74 | LossAdj: 0.30530 | Time taken: 4 seconds
Epoch: 0 | Training Samples: 20000 | Loss: 6037.36 | LossAdj: 0.30187 | Time taken: 4 seconds
Epoch: 0 | Training Samples: 21000 | Loss: 6295.87 | LossAdj: 0.29980 | Time taken: 4 seconds
Epoch: 0 | Training Samples: 22000 | Loss: 6535.33 | LossAdj: 0.29706 | Time taken: 4 seconds
Epoch: 0 | Training Samples: 23000 | Loss: 6756.56 | LossAdj: 0.29376 | Time taken: 5 seconds
Epoch: 0 | Training Samples: 24000 | Loss: 7006.79 | LossAdj: 0.29195 | Time taken: 5 seconds
Epoch: 0 | Training Samples: 25000 | Loss: 7226.08 | LossAdj: 0.28904 | Time taken: 5 seconds
Epoch: 0 | Training Samples: 26000 | Loss: 7466.81 | LossAdj: 0.28718 | Time taken: 5 seconds
Epoch: 0 | Training Samples: 27000 | Loss: 7709.35 | LossAdj: 0.28553 | Time taken: 6 seconds
Epoch: 0 | Training Samples: 28000 | Loss: 7938.90 | LossAdj: 0.28353 | Time taken: 6 seconds
Epoch: 0 | Training Samples: 29000 | Loss: 8164.53 | LossAdj: 0.28154 | Time taken: 6 seconds
Epoch: 0 | Training Samples: 30000 | Loss: 8421.96 | LossAdj: 0.28073 | Time taken: 6 seconds
Epoch: 0 | Training Samples: 31000 | Loss: 8671.44 | LossAdj: 0.27972 | Time taken: 6 seconds
Epoch: 0 | Training Samples: 32000 | Loss: 8912.28 | LossAdj: 0.27851 | Time taken: 7 seconds
Epoch: 0 | Training Samples: 33000 | Loss: 9128.50 | LossAdj: 0.27662 | Time taken: 7 seconds
Epoch: 0 | Training Samples: 34000 | Loss: 9365.36 | LossAdj: 0.27545 | Time taken: 7 seconds
Epoch: 0 | Training Samples: 35000 | Loss: 9575.84 | LossAdj: 0.27360 | Time taken: 7 seconds
Epoch: 0 | Training Samples: 36000 | Loss: 9829.03 | LossAdj: 0.27303 | Time taken: 8 seconds
Epoch: 0 | Training Samples: 37000 | Loss: 10030.71 | LossAdj: 0.27110 | Time taken: 8 seconds
Epoch: 0 | Training Samples: 38000 | Loss: 10258.56 | LossAdj: 0.26996 | Time taken: 8 seconds
Epoch: 0 | Training Samples: 39000 | Loss: 10489.83 | LossAdj: 0.26897 | Time taken: 8 seconds
Epoch: 0 | Training Samples: 40000 | Loss: 10716.04 | LossAdj: 0.26790 | Time taken: 8 seconds
Epoch: 0 | Training Samples: 41000 | Loss: 10933.79 | LossAdj: 0.26668 | Time taken: 9 seconds
Epoch: 0 | Training Samples: 42000 | Loss: 11136.03 | LossAdj: 0.26514 | Time taken: 9 seconds
Epoch: 0 | Training Samples: 43000 | Loss: 11360.49 | LossAdj: 0.26420 | Time taken: 9 seconds
Epoch: 0 | Training Samples: 44000 | Loss: 11582.47 | LossAdj: 0.26324 | Time taken: 9 seconds
Epoch: 0 | Training Samples: 45000 | Loss: 11795.96 | LossAdj: 0.26213 | Time taken: 10 seconds
Epoch: 0 | Training Samples: 46000 | Loss: 12039.98 | LossAdj: 0.26174 | Time taken: 10 seconds
Epoch: 0 | Training Samples: 47000 | Loss: 12249.80 | LossAdj: 0.26063 | Time taken: 10 seconds
Epoch: 0 | Training Samples: 48000 | Loss: 12495.84 | LossAdj: 0.26033 | Time taken: 10 seconds
Epoch: 0 | Training Samples: 49000 | Loss: 12711.04 | LossAdj: 0.25941 | Time taken: 10 seconds
Epoch: 0 | Training Samples: 50000 | Loss: 12910.48 | LossAdj: 0.25821 | Time taken: 11 seconds
Epoch: 0 | Training Samples: 51000 | Loss: 13110.62 | LossAdj: 0.25707 | Time taken: 11 seconds
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Epoch: 0 | Training Samples: 56000 | Loss: 14177.63 | LossAdj: 0.25317 | Time taken: 12 seconds
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Epoch: 0 | Training Samples: 59000 | Loss: 14831.95 | LossAdj: 0.25139 | Time taken: 13 seconds
Epoch: 0 | Training Samples: 60000 | Loss: 15019.63 | LossAdj: 0.25033 | Time taken: 13 seconds
Epoch: 0 | Training Samples: 61000 | Loss: 15210.39 | LossAdj: 0.24935 | Time taken: 13 seconds
Epoch: 0 | Training Samples: 62000 | Loss: 15417.17 | LossAdj: 0.24866 | Time taken: 13 seconds
Epoch: 0 | Training Samples: 63000 | Loss: 15639.59 | LossAdj: 0.24825 | Time taken: 14 seconds
Epoch: 0 | Training Samples: 64000 | Loss: 15844.09 | LossAdj: 0.24756 | Time taken: 14 seconds
Epoch: 0 | Training Samples: 65000 | Loss: 16041.35 | LossAdj: 0.24679 | Time taken: 14 seconds
Epoch: 0 | Training Samples: 66000 | Loss: 16223.59 | LossAdj: 0.24581 | Time taken: 14 seconds
Epoch: 0 | Training Samples: 67000 | Loss: 16429.62 | LossAdj: 0.24522 | Time taken: 14 seconds
Epoch: 0 | Training Samples: 68000 | Loss: 16640.48 | LossAdj: 0.24471 | Time taken: 15 seconds
Epoch: 0 | Training Samples: 69000 | Loss: 16853.01 | LossAdj: 0.24425 | Time taken: 15 seconds
Epoch: 0 | Training Samples: 70000 | Loss: 17075.29 | LossAdj: 0.24393 | Time taken: 15 seconds
Epoch: 0 | Training Samples: 71000 | Loss: 17294.03 | LossAdj: 0.24358 | Time taken: 15 seconds
Epoch: 0 | Training Samples: 72000 | Loss: 17507.40 | LossAdj: 0.24316 | Time taken: 16 seconds
Epoch: 0 | Training Samples: 73000 | Loss: 17720.44 | LossAdj: 0.24275 | Time taken: 16 seconds
Epoch: 0 | Training Samples: 74000 | Loss: 17939.96 | LossAdj: 0.24243 | Time taken: 16 seconds
Epoch: 0 | Training Samples: 75000 | Loss: 18189.16 | LossAdj: 0.24252 | Time taken: 16 seconds
Epoch: 0 | Training Samples: 76000 | Loss: 18392.08 | LossAdj: 0.24200 | Time taken: 16 seconds
Epoch: 0 | Training Samples: 77000 | Loss: 18607.25 | LossAdj: 0.24165 | Time taken: 17 seconds
Epoch: 0 | Training Samples: 78000 | Loss: 18806.09 | LossAdj: 0.24110 | Time taken: 17 seconds
Epoch: 0 | Training Samples: 79000 | Loss: 19016.91 | LossAdj: 0.24072 | Time taken: 17 seconds
Epoch: 0 | Training Samples: 80000 | Loss: 19242.32 | LossAdj: 0.24053 | Time taken: 17 seconds
Epoch: 0 | Training Samples: 81000 | Loss: 19460.39 | LossAdj: 0.24025 | Time taken: 18 seconds
Epoch: 0 | Training Samples: 82000 | Loss: 19696.29 | LossAdj: 0.24020 | Time taken: 18 seconds
Epoch: 0 | Training Samples: 83000 | Loss: 19916.44 | LossAdj: 0.23996 | Time taken: 18 seconds
Epoch: 0 | Training Samples: 84000 | Loss: 20155.78 | LossAdj: 0.23995 | Time taken: 18 seconds
Epoch: 0 | Training Samples: 85000 | Loss: 20386.03 | LossAdj: 0.23984 | Time taken: 18 seconds
Epoch: 0 | Training Samples: 86000 | Loss: 20616.06 | LossAdj: 0.23972 | Time taken: 19 seconds
Epoch: 0 | Training Samples: 87000 | Loss: 20834.22 | LossAdj: 0.23947 | Time taken: 19 seconds
Epoch: 0 | Training Samples: 88000 | Loss: 21050.58 | LossAdj: 0.23921 | Time taken: 19 seconds
Epoch: 0 | Training Samples: 89000 | Loss: 21217.89 | LossAdj: 0.23840 | Time taken: 19 seconds
Epoch: 0 | Training Samples: 90000 | Loss: 21405.14 | LossAdj: 0.23783 | Time taken: 20 seconds
Epoch: 0 | Training Samples: 91000 | Loss: 21626.20 | LossAdj: 0.23765 | Time taken: 20 seconds
Epoch: 0 | Training Samples: 92000 | Loss: 21858.53 | LossAdj: 0.23759 | Time taken: 20 seconds
Epoch: 0 | Training Samples: 93000 | Loss: 22069.67 | LossAdj: 0.23731 | Time taken: 20 seconds
Epoch: 0 | Training Samples: 94000 | Loss: 22279.68 | LossAdj: 0.23702 | Time taken: 21 seconds
Epoch: 0 | Training Samples: 95000 | Loss: 22501.58 | LossAdj: 0.23686 | Time taken: 21 seconds
Epoch: 0 | Training Samples: 96000 | Loss: 22743.99 | LossAdj: 0.23692 | Time taken: 21 seconds
Epoch: 0 | Training Samples: 97000 | Loss: 22936.44 | LossAdj: 0.23646 | Time taken: 21 seconds
Epoch: 0 | Training Samples: 98000 | Loss: 23175.67 | LossAdj: 0.23649 | Time taken: 21 seconds
Epoch: 0 | Training Samples: 99000 | Loss: 23375.34 | LossAdj: 0.23611 | Time taken: 22 seconds
Epoch: 0 | Training Samples: 100000 | Loss: 23601.83 | LossAdj: 0.23602 | Time taken: 22 seconds
Epoch: 0 | Training Samples: 101000 | Loss: 23809.16 | LossAdj: 0.23573 | Time taken: 22 seconds
Epoch: 0 | Training Samples: 102000 | Loss: 23982.66 | LossAdj: 0.23512 | Time taken: 22 seconds
Epoch: 0 | Training Samples: 103000 | Loss: 24204.59 | LossAdj: 0.23500 | Time taken: 23 seconds
Epoch: 0 | Training Samples: 104000 | Loss: 24402.49 | LossAdj: 0.23464 | Time taken: 23 seconds
Epoch: 0 | Training Samples: 105000 | Loss: 24630.39 | LossAdj: 0.23458 | Time taken: 23 seconds
Epoch: 0 | Training Samples: 106000 | Loss: 24795.04 | LossAdj: 0.23392 | Time taken: 23 seconds
Epoch: 0 | Training Samples: 107000 | Loss: 25011.06 | LossAdj: 0.23375 | Time taken: 23 seconds
Epoch: 0 | Training Samples: 108000 | Loss: 25235.32 | LossAdj: 0.23366 | Time taken: 24 seconds
Epoch: 0 | Training Samples: 109000 | Loss: 25449.76 | LossAdj: 0.23348 | Time taken: 24 seconds
Epoch: 0 | Training Samples: 110000 | Loss: 25627.35 | LossAdj: 0.23298 | Time taken: 24 seconds
Epoch: 0 | Training Samples: 111000 | Loss: 25850.50 | LossAdj: 0.23289 | Time taken: 24 seconds
Epoch: 0 | Training Samples: 112000 | Loss: 26057.97 | LossAdj: 0.23266 | Time taken: 25 seconds
Epoch: 0 | Training Samples: 113000 | Loss: 26260.82 | LossAdj: 0.23240 | Time taken: 25 seconds
Epoch: 0 | Training Samples: 114000 | Loss: 26485.64 | LossAdj: 0.23233 | Time taken: 25 seconds
Epoch: 0 | Training Samples: 115000 | Loss: 26676.44 | LossAdj: 0.23197 | Time taken: 25 seconds
Epoch: 0 | Training Samples: 116000 | Loss: 26887.05 | LossAdj: 0.23178 | Time taken: 25 seconds
Epoch: 0 | Training Samples: 117000 | Loss: 27073.44 | LossAdj: 0.23140 | Time taken: 26 seconds
Epoch: 0 | Training Samples: 118000 | Loss: 27308.63 | LossAdj: 0.23143 | Time taken: 26 seconds
Epoch: 0 | Training Samples: 119000 | Loss: 27538.91 | LossAdj: 0.23142 | Time taken: 26 seconds
Epoch: 0 | Training Samples: 120000 | Loss: 27760.00 | LossAdj: 0.23133 | Time taken: 26 seconds
Epoch: 0 | Training Samples: 121000 | Loss: 27967.90 | LossAdj: 0.23114 | Time taken: 27 seconds
Epoch: 0 | Training Samples: 122000 | Loss: 28166.33 | LossAdj: 0.23087 | Time taken: 27 seconds
Epoch: 0 | Training Samples: 123000 | Loss: 28359.42 | LossAdj: 0.23056 | Time taken: 27 seconds
Epoch: 0 | Training Samples: 124000 | Loss: 28574.40 | LossAdj: 0.23044 | Time taken: 27 seconds
Epoch: 0 | Training Samples: 125000 | Loss: 28788.24 | LossAdj: 0.23031 | Time taken: 27 seconds
Epoch: 0 | Training Samples: 126000 | Loss: 28976.51 | LossAdj: 0.22997 | Time taken: 28 seconds
Epoch: 0 | Training Samples: 127000 | Loss: 29204.45 | LossAdj: 0.22996 | Time taken: 28 seconds
Epoch: 0 | Training Samples: 128000 | Loss: 29413.85 | LossAdj: 0.22980 | Time taken: 28 seconds
Epoch: 0 | Training Samples: 129000 | Loss: 29624.33 | LossAdj: 0.22965 | Time taken: 28 seconds
Epoch: 0 | Training Samples: 130000 | Loss: 29825.74 | LossAdj: 0.22943 | Time taken: 29 seconds
Epoch: 0 | Training Samples: 131000 | Loss: 29995.28 | LossAdj: 0.22897 | Time taken: 29 seconds
Epoch: 0 | Training Samples: 132000 | Loss: 30179.85 | LossAdj: 0.22864 | Time taken: 29 seconds
Epoch: 0 | Training Samples: 133000 | Loss: 30418.59 | LossAdj: 0.22871 | Time taken: 29 seconds
Epoch: 0 | Training Samples: 134000 | Loss: 30629.00 | LossAdj: 0.22857 | Time taken: 30 seconds
Epoch: 0 | Training Samples: 135000 | Loss: 30831.80 | LossAdj: 0.22838 | Time taken: 30 seconds
Epoch: 0 | Training Samples: 136000 | Loss: 31027.20 | LossAdj: 0.22814 | Time taken: 30 seconds
Epoch: 0 | Training Samples: 137000 | Loss: 31248.52 | LossAdj: 0.22809 | Time taken: 30 seconds
Epoch: 0 | Training Samples: 138000 | Loss: 31443.67 | LossAdj: 0.22785 | Time taken: 30 seconds
Epoch: 0 | Training Samples: 139000 | Loss: 31679.40 | LossAdj: 0.22791 | Time taken: 31 seconds
Epoch: 0 | Training Samples: 140000 | Loss: 31873.79 | LossAdj: 0.22767 | Time taken: 31 seconds
Epoch: 0 | Training Samples: 141000 | Loss: 32109.59 | LossAdj: 0.22773 | Time taken: 31 seconds
Epoch: 0 | Training Samples: 142000 | Loss: 32296.49 | LossAdj: 0.22744 | Time taken: 31 seconds
Epoch: 0 | Training Samples: 143000 | Loss: 32513.48 | LossAdj: 0.22737 | Time taken: 32 seconds
Epoch: 0 | Training Samples: 144000 | Loss: 32734.63 | LossAdj: 0.22732 | Time taken: 32 seconds
Epoch: 0 | Training Samples: 145000 | Loss: 32925.14 | LossAdj: 0.22707 | Time taken: 32 seconds
Epoch: 0 | Training Samples: 146000 | Loss: 33115.58 | LossAdj: 0.22682 | Time taken: 32 seconds
Epoch: 0 | Training Samples: 147000 | Loss: 33338.74 | LossAdj: 0.22679 | Time taken: 33 seconds
Epoch: 0 | Training Samples: 148000 | Loss: 33549.00 | LossAdj: 0.22668 | Time taken: 33 seconds
Epoch: 0 | Training Samples: 149000 | Loss: 33746.69 | LossAdj: 0.22649 | Time taken: 33 seconds
Epoch: 0 | Training Samples: 150000 | Loss: 33978.04 | LossAdj: 0.22652 | Time taken: 33 seconds
--- TRAINING FINISHED IN 33 SECONDS WITH LOSS 0.23 ---
precision recall f1-score support
0 0.97 0.95 0.96 45786
1 0.55 0.63 0.59 4214
accuracy 0.93 50000
macro avg 0.76 0.79 0.77 50000
weighted avg 0.93 0.93 0.93 50000
AUC = 0.902750
Epoch: 0 | Training Samples: 1000 | Loss: 429.08 | LossAdj: 0.42908 | Time taken: 0 seconds
Epoch: 0 | Training Samples: 2000 | Loss: 788.95 | LossAdj: 0.39448 | Time taken: 0 seconds
Epoch: 0 | Training Samples: 3000 | Loss: 1157.35 | LossAdj: 0.38578 | Time taken: 0 seconds
Epoch: 0 | Training Samples: 4000 | Loss: 1479.28 | LossAdj: 0.36982 | Time taken: 0 seconds
Epoch: 0 | Training Samples: 5000 | Loss: 1805.41 | LossAdj: 0.36108 | Time taken: 1 seconds
Epoch: 0 | Training Samples: 6000 | Loss: 2135.81 | LossAdj: 0.35597 | Time taken: 1 seconds
Epoch: 0 | Training Samples: 7000 | Loss: 2488.75 | LossAdj: 0.35554 | Time taken: 1 seconds
Epoch: 0 | Training Samples: 8000 | Loss: 2812.27 | LossAdj: 0.35153 | Time taken: 1 seconds
Epoch: 0 | Training Samples: 9000 | Loss: 3134.12 | LossAdj: 0.34824 | Time taken: 1 seconds
Epoch: 0 | Training Samples: 10000 | Loss: 3467.09 | LossAdj: 0.34671 | Time taken: 2 seconds
Epoch: 0 | Training Samples: 11000 | Loss: 3786.86 | LossAdj: 0.34426 | Time taken: 2 seconds
Epoch: 0 | Training Samples: 12000 | Loss: 4078.00 | LossAdj: 0.33983 | Time taken: 2 seconds
Epoch: 0 | Training Samples: 13000 | Loss: 4413.44 | LossAdj: 0.33950 | Time taken: 2 seconds
Epoch: 0 | Training Samples: 14000 | Loss: 4751.29 | LossAdj: 0.33938 | Time taken: 2 seconds
Epoch: 0 | Training Samples: 15000 | Loss: 5111.37 | LossAdj: 0.34076 | Time taken: 3 seconds
Epoch: 0 | Training Samples: 16000 | Loss: 5435.62 | LossAdj: 0.33973 | Time taken: 3 seconds
Epoch: 0 | Training Samples: 17000 | Loss: 5756.48 | LossAdj: 0.33862 | Time taken: 3 seconds
Epoch: 0 | Training Samples: 18000 | Loss: 6079.64 | LossAdj: 0.33776 | Time taken: 3 seconds
Epoch: 0 | Training Samples: 19000 | Loss: 6398.83 | LossAdj: 0.33678 | Time taken: 4 seconds
Epoch: 0 | Training Samples: 20000 | Loss: 6729.96 | LossAdj: 0.33650 | Time taken: 4 seconds
Epoch: 0 | Training Samples: 21000 | Loss: 7067.80 | LossAdj: 0.33656 | Time taken: 4 seconds
Epoch: 0 | Training Samples: 22000 | Loss: 7378.98 | LossAdj: 0.33541 | Time taken: 4 seconds
Epoch: 0 | Training Samples: 23000 | Loss: 7674.94 | LossAdj: 0.33369 | Time taken: 4 seconds
Epoch: 0 | Training Samples: 24000 | Loss: 7962.76 | LossAdj: 0.33178 | Time taken: 5 seconds
Epoch: 0 | Training Samples: 25000 | Loss: 8281.98 | LossAdj: 0.33128 | Time taken: 5 seconds
Epoch: 0 | Training Samples: 26000 | Loss: 8581.04 | LossAdj: 0.33004 | Time taken: 5 seconds
Epoch: 0 | Training Samples: 27000 | Loss: 8898.03 | LossAdj: 0.32956 | Time taken: 5 seconds
Epoch: 0 | Training Samples: 28000 | Loss: 9240.10 | LossAdj: 0.33000 | Time taken: 5 seconds
Epoch: 0 | Training Samples: 29000 | Loss: 9568.43 | LossAdj: 0.32995 | Time taken: 6 seconds
Epoch: 0 | Training Samples: 30000 | Loss: 9877.80 | LossAdj: 0.32926 | Time taken: 6 seconds
Epoch: 0 | Training Samples: 31000 | Loss: 10166.29 | LossAdj: 0.32794 | Time taken: 6 seconds
Epoch: 0 | Training Samples: 32000 | Loss: 10511.15 | LossAdj: 0.32847 | Time taken: 6 seconds
Epoch: 0 | Training Samples: 33000 | Loss: 10823.15 | LossAdj: 0.32797 | Time taken: 7 seconds
Epoch: 0 | Training Samples: 34000 | Loss: 11143.79 | LossAdj: 0.32776 | Time taken: 7 seconds
Epoch: 0 | Training Samples: 35000 | Loss: 11452.11 | LossAdj: 0.32720 | Time taken: 7 seconds
Epoch: 0 | Training Samples: 36000 | Loss: 11768.27 | LossAdj: 0.32690 | Time taken: 7 seconds
Epoch: 0 | Training Samples: 37000 | Loss: 12077.75 | LossAdj: 0.32643 | Time taken: 7 seconds
Epoch: 0 | Training Samples: 38000 | Loss: 12398.41 | LossAdj: 0.32627 | Time taken: 8 seconds
Epoch: 0 | Training Samples: 39000 | Loss: 12691.67 | LossAdj: 0.32543 | Time taken: 8 seconds
Epoch: 0 | Training Samples: 40000 | Loss: 12975.49 | LossAdj: 0.32439 | Time taken: 8 seconds
Epoch: 0 | Training Samples: 41000 | Loss: 13277.92 | LossAdj: 0.32385 | Time taken: 8 seconds
Epoch: 0 | Training Samples: 42000 | Loss: 13605.36 | LossAdj: 0.32394 | Time taken: 9 seconds
Epoch: 0 | Training Samples: 43000 | Loss: 13926.96 | LossAdj: 0.32388 | Time taken: 9 seconds
Epoch: 0 | Training Samples: 44000 | Loss: 14240.99 | LossAdj: 0.32366 | Time taken: 9 seconds
Epoch: 0 | Training Samples: 45000 | Loss: 14558.51 | LossAdj: 0.32352 | Time taken: 9 seconds
Epoch: 0 | Training Samples: 46000 | Loss: 14889.84 | LossAdj: 0.32369 | Time taken: 9 seconds
Epoch: 0 | Training Samples: 47000 | Loss: 15181.13 | LossAdj: 0.32300 | Time taken: 10 seconds
Epoch: 0 | Training Samples: 48000 | Loss: 15504.28 | LossAdj: 0.32301 | Time taken: 10 seconds
Epoch: 0 | Training Samples: 49000 | Loss: 15796.08 | LossAdj: 0.32237 | Time taken: 10 seconds
Epoch: 0 | Training Samples: 50000 | Loss: 16095.93 | LossAdj: 0.32192 | Time taken: 10 seconds
Epoch: 0 | Training Samples: 51000 | Loss: 16355.95 | LossAdj: 0.32070 | Time taken: 10 seconds
Epoch: 0 | Training Samples: 52000 | Loss: 16652.06 | LossAdj: 0.32023 | Time taken: 11 seconds
Epoch: 0 | Training Samples: 53000 | Loss: 16943.38 | LossAdj: 0.31969 | Time taken: 11 seconds
Epoch: 0 | Training Samples: 54000 | Loss: 17243.89 | LossAdj: 0.31933 | Time taken: 11 seconds
Epoch: 0 | Training Samples: 55000 | Loss: 17532.29 | LossAdj: 0.31877 | Time taken: 11 seconds
Epoch: 0 | Training Samples: 56000 | Loss: 17845.78 | LossAdj: 0.31867 | Time taken: 12 seconds
Epoch: 0 | Training Samples: 57000 | Loss: 18178.84 | LossAdj: 0.31893 | Time taken: 12 seconds
Epoch: 0 | Training Samples: 58000 | Loss: 18477.71 | LossAdj: 0.31858 | Time taken: 12 seconds
Epoch: 0 | Training Samples: 59000 | Loss: 18800.70 | LossAdj: 0.31866 | Time taken: 12 seconds
Epoch: 0 | Training Samples: 60000 | Loss: 19124.40 | LossAdj: 0.31874 | Time taken: 12 seconds
Epoch: 0 | Training Samples: 61000 | Loss: 19422.69 | LossAdj: 0.31840 | Time taken: 13 seconds
Epoch: 0 | Training Samples: 62000 | Loss: 19736.06 | LossAdj: 0.31832 | Time taken: 13 seconds
Epoch: 0 | Training Samples: 63000 | Loss: 20063.13 | LossAdj: 0.31846 | Time taken: 13 seconds
Epoch: 0 | Training Samples: 64000 | Loss: 20373.58 | LossAdj: 0.31834 | Time taken: 13 seconds
Epoch: 0 | Training Samples: 65000 | Loss: 20679.33 | LossAdj: 0.31814 | Time taken: 13 seconds
Epoch: 0 | Training Samples: 66000 | Loss: 20988.07 | LossAdj: 0.31800 | Time taken: 14 seconds
Epoch: 0 | Training Samples: 67000 | Loss: 21318.62 | LossAdj: 0.31819 | Time taken: 14 seconds
Epoch: 0 | Training Samples: 68000 | Loss: 21616.23 | LossAdj: 0.31789 | Time taken: 14 seconds
Epoch: 0 | Training Samples: 69000 | Loss: 21934.97 | LossAdj: 0.31790 | Time taken: 14 seconds
Epoch: 0 | Training Samples: 70000 | Loss: 22262.20 | LossAdj: 0.31803 | Time taken: 15 seconds
Epoch: 0 | Training Samples: 71000 | Loss: 22577.80 | LossAdj: 0.31800 | Time taken: 15 seconds
Epoch: 0 | Training Samples: 72000 | Loss: 22889.76 | LossAdj: 0.31791 | Time taken: 15 seconds
Epoch: 0 | Training Samples: 73000 | Loss: 23204.05 | LossAdj: 0.31786 | Time taken: 15 seconds
Epoch: 0 | Training Samples: 74000 | Loss: 23525.44 | LossAdj: 0.31791 | Time taken: 15 seconds
Epoch: 0 | Training Samples: 75000 | Loss: 23834.34 | LossAdj: 0.31779 | Time taken: 16 seconds
Epoch: 0 | Training Samples: 76000 | Loss: 24148.53 | LossAdj: 0.31774 | Time taken: 16 seconds
Epoch: 0 | Training Samples: 77000 | Loss: 24482.28 | LossAdj: 0.31795 | Time taken: 16 seconds
Epoch: 0 | Training Samples: 78000 | Loss: 24776.62 | LossAdj: 0.31765 | Time taken: 16 seconds
Epoch: 0 | Training Samples: 79000 | Loss: 25074.03 | LossAdj: 0.31739 | Time taken: 16 seconds
Epoch: 0 | Training Samples: 80000 | Loss: 25387.24 | LossAdj: 0.31734 | Time taken: 17 seconds
Epoch: 0 | Training Samples: 81000 | Loss: 25684.22 | LossAdj: 0.31709 | Time taken: 17 seconds
Epoch: 0 | Training Samples: 82000 | Loss: 25979.97 | LossAdj: 0.31683 | Time taken: 17 seconds
Epoch: 0 | Training Samples: 83000 | Loss: 26286.78 | LossAdj: 0.31671 | Time taken: 17 seconds
Epoch: 0 | Training Samples: 84000 | Loss: 26609.69 | LossAdj: 0.31678 | Time taken: 18 seconds
Epoch: 0 | Training Samples: 85000 | Loss: 26927.31 | LossAdj: 0.31679 | Time taken: 18 seconds
Epoch: 0 | Training Samples: 86000 | Loss: 27233.99 | LossAdj: 0.31667 | Time taken: 18 seconds
Epoch: 0 | Training Samples: 87000 | Loss: 27546.79 | LossAdj: 0.31663 | Time taken: 18 seconds
Epoch: 0 | Training Samples: 88000 | Loss: 27868.15 | LossAdj: 0.31668 | Time taken: 18 seconds
Epoch: 0 | Training Samples: 89000 | Loss: 28174.47 | LossAdj: 0.31657 | Time taken: 19 seconds
Epoch: 0 | Training Samples: 90000 | Loss: 28490.26 | LossAdj: 0.31656 | Time taken: 19 seconds
Epoch: 0 | Training Samples: 91000 | Loss: 28807.77 | LossAdj: 0.31657 | Time taken: 19 seconds
Epoch: 0 | Training Samples: 92000 | Loss: 29132.45 | LossAdj: 0.31666 | Time taken: 19 seconds
Epoch: 0 | Training Samples: 93000 | Loss: 29461.66 | LossAdj: 0.31679 | Time taken: 20 seconds
Epoch: 0 | Training Samples: 94000 | Loss: 29770.68 | LossAdj: 0.31671 | Time taken: 20 seconds
Epoch: 0 | Training Samples: 95000 | Loss: 30087.02 | LossAdj: 0.31671 | Time taken: 20 seconds
Epoch: 0 | Training Samples: 96000 | Loss: 30402.71 | LossAdj: 0.31669 | Time taken: 20 seconds
Epoch: 0 | Training Samples: 97000 | Loss: 30704.91 | LossAdj: 0.31655 | Time taken: 20 seconds
Epoch: 0 | Training Samples: 98000 | Loss: 31015.24 | LossAdj: 0.31648 | Time taken: 21 seconds
Epoch: 0 | Training Samples: 99000 | Loss: 31319.42 | LossAdj: 0.31636 | Time taken: 21 seconds
Epoch: 0 | Training Samples: 100000 | Loss: 31641.37 | LossAdj: 0.31641 | Time taken: 21 seconds
Epoch: 0 | Training Samples: 101000 | Loss: 31956.02 | LossAdj: 0.31640 | Time taken: 21 seconds
Epoch: 0 | Training Samples: 102000 | Loss: 32263.43 | LossAdj: 0.31631 | Time taken: 22 seconds
Epoch: 0 | Training Samples: 103000 | Loss: 32573.02 | LossAdj: 0.31624 | Time taken: 22 seconds
Epoch: 0 | Training Samples: 104000 | Loss: 32883.38 | LossAdj: 0.31619 | Time taken: 22 seconds
Epoch: 0 | Training Samples: 105000 | Loss: 33174.57 | LossAdj: 0.31595 | Time taken: 22 seconds
Epoch: 0 | Training Samples: 106000 | Loss: 33476.43 | LossAdj: 0.31582 | Time taken: 22 seconds
Epoch: 0 | Training Samples: 107000 | Loss: 33779.68 | LossAdj: 0.31570 | Time taken: 23 seconds
Epoch: 0 | Training Samples: 108000 | Loss: 34078.84 | LossAdj: 0.31554 | Time taken: 23 seconds
Epoch: 0 | Training Samples: 109000 | Loss: 34390.37 | LossAdj: 0.31551 | Time taken: 23 seconds
Epoch: 0 | Training Samples: 110000 | Loss: 34695.78 | LossAdj: 0.31542 | Time taken: 23 seconds
Epoch: 0 | Training Samples: 111000 | Loss: 34952.37 | LossAdj: 0.31489 | Time taken: 23 seconds
Epoch: 0 | Training Samples: 112000 | Loss: 35258.84 | LossAdj: 0.31481 | Time taken: 24 seconds
Epoch: 0 | Training Samples: 113000 | Loss: 35562.57 | LossAdj: 0.31471 | Time taken: 24 seconds
Epoch: 0 | Training Samples: 114000 | Loss: 35861.13 | LossAdj: 0.31457 | Time taken: 24 seconds
Epoch: 0 | Training Samples: 115000 | Loss: 36165.19 | LossAdj: 0.31448 | Time taken: 24 seconds
Epoch: 0 | Training Samples: 116000 | Loss: 36487.19 | LossAdj: 0.31454 | Time taken: 25 seconds
Epoch: 0 | Training Samples: 117000 | Loss: 36786.02 | LossAdj: 0.31441 | Time taken: 25 seconds
Epoch: 0 | Training Samples: 118000 | Loss: 37107.41 | LossAdj: 0.31447 | Time taken: 25 seconds
Epoch: 0 | Training Samples: 119000 | Loss: 37415.51 | LossAdj: 0.31442 | Time taken: 25 seconds
Epoch: 0 | Training Samples: 120000 | Loss: 37727.66 | LossAdj: 0.31440 | Time taken: 25 seconds
Epoch: 0 | Training Samples: 121000 | Loss: 38070.43 | LossAdj: 0.31463 | Time taken: 26 seconds
Epoch: 0 | Training Samples: 122000 | Loss: 38374.85 | LossAdj: 0.31455 | Time taken: 26 seconds
Epoch: 0 | Training Samples: 123000 | Loss: 38681.90 | LossAdj: 0.31449 | Time taken: 26 seconds
Epoch: 0 | Training Samples: 124000 | Loss: 38974.23 | LossAdj: 0.31431 | Time taken: 26 seconds
Epoch: 0 | Training Samples: 125000 | Loss: 39277.32 | LossAdj: 0.31422 | Time taken: 27 seconds
Epoch: 0 | Training Samples: 126000 | Loss: 39562.93 | LossAdj: 0.31399 | Time taken: 27 seconds
Epoch: 0 | Training Samples: 127000 | Loss: 39889.18 | LossAdj: 0.31409 | Time taken: 27 seconds
Epoch: 0 | Training Samples: 128000 | Loss: 40179.66 | LossAdj: 0.31390 | Time taken: 27 seconds
Epoch: 0 | Training Samples: 129000 | Loss: 40512.26 | LossAdj: 0.31405 | Time taken: 27 seconds
Epoch: 0 | Training Samples: 130000 | Loss: 40818.22 | LossAdj: 0.31399 | Time taken: 28 seconds
Epoch: 0 | Training Samples: 131000 | Loss: 41110.86 | LossAdj: 0.31382 | Time taken: 28 seconds
Epoch: 0 | Training Samples: 132000 | Loss: 41420.47 | LossAdj: 0.31379 | Time taken: 28 seconds
Epoch: 0 | Training Samples: 133000 | Loss: 41740.01 | LossAdj: 0.31383 | Time taken: 28 seconds
Epoch: 0 | Training Samples: 134000 | Loss: 42038.69 | LossAdj: 0.31372 | Time taken: 28 seconds
Epoch: 0 | Training Samples: 135000 | Loss: 42348.12 | LossAdj: 0.31369 | Time taken: 29 seconds
Epoch: 0 | Training Samples: 136000 | Loss: 42648.81 | LossAdj: 0.31359 | Time taken: 29 seconds
Epoch: 0 | Training Samples: 137000 | Loss: 42933.91 | LossAdj: 0.31339 | Time taken: 29 seconds
Epoch: 0 | Training Samples: 138000 | Loss: 43236.28 | LossAdj: 0.31331 | Time taken: 29 seconds
Epoch: 0 | Training Samples: 139000 | Loss: 43523.81 | LossAdj: 0.31312 | Time taken: 30 seconds
Epoch: 0 | Training Samples: 140000 | Loss: 43813.86 | LossAdj: 0.31296 | Time taken: 30 seconds
Epoch: 0 | Training Samples: 141000 | Loss: 44109.54 | LossAdj: 0.31283 | Time taken: 30 seconds
Epoch: 0 | Training Samples: 142000 | Loss: 44400.47 | LossAdj: 0.31268 | Time taken: 30 seconds
Epoch: 0 | Training Samples: 143000 | Loss: 44712.03 | LossAdj: 0.31267 | Time taken: 30 seconds
Epoch: 0 | Training Samples: 144000 | Loss: 45030.82 | LossAdj: 0.31271 | Time taken: 31 seconds
Epoch: 0 | Training Samples: 145000 | Loss: 45318.77 | LossAdj: 0.31254 | Time taken: 31 seconds
Epoch: 0 | Training Samples: 146000 | Loss: 45651.16 | LossAdj: 0.31268 | Time taken: 31 seconds
Epoch: 0 | Training Samples: 147000 | Loss: 45978.55 | LossAdj: 0.31278 | Time taken: 31 seconds
Epoch: 0 | Training Samples: 148000 | Loss: 46277.01 | LossAdj: 0.31268 | Time taken: 31 seconds
Epoch: 0 | Training Samples: 149000 | Loss: 46577.75 | LossAdj: 0.31260 | Time taken: 32 seconds
Epoch: 0 | Training Samples: 150000 | Loss: 46878.62 | LossAdj: 0.31252 | Time taken: 32 seconds
--- TRAINING FINISHED IN 32 SECONDS WITH LOSS 0.31 ---
precision recall f1-score support
0 0.97 0.90 0.93 45786
1 0.39 0.72 0.51 4214
accuracy 0.88 50000
macro avg 0.68 0.81 0.72 50000
weighted avg 0.92 0.88 0.90 50000
AUC = 0.896821
Epoch: 0 | Training Samples: 1000 | Loss: 1163.22 | LossAdj: 1.16322 | Time taken: 0 seconds
Epoch: 0 | Training Samples: 2000 | Loss: 2053.44 | LossAdj: 1.02672 | Time taken: 1 seconds
Epoch: 0 | Training Samples: 3000 | Loss: 2663.24 | LossAdj: 0.88775 | Time taken: 1 seconds
Epoch: 0 | Training Samples: 4000 | Loss: 3286.72 | LossAdj: 0.82168 | Time taken: 2 seconds
Epoch: 0 | Training Samples: 5000 | Loss: 3864.88 | LossAdj: 0.77298 | Time taken: 2 seconds
Epoch: 0 | Training Samples: 6000 | Loss: 4526.01 | LossAdj: 0.75434 | Time taken: 3 seconds
Epoch: 0 | Training Samples: 7000 | Loss: 5291.94 | LossAdj: 0.75599 | Time taken: 3 seconds
Epoch: 0 | Training Samples: 8000 | Loss: 5929.73 | LossAdj: 0.74122 | Time taken: 4 seconds
Epoch: 0 | Training Samples: 9000 | Loss: 6483.85 | LossAdj: 0.72043 | Time taken: 5 seconds
Epoch: 0 | Training Samples: 10000 | Loss: 6974.19 | LossAdj: 0.69742 | Time taken: 5 seconds
Epoch: 0 | Training Samples: 11000 | Loss: 7289.89 | LossAdj: 0.66272 | Time taken: 6 seconds
Epoch: 0 | Training Samples: 12000 | Loss: 7636.15 | LossAdj: 0.63635 | Time taken: 6 seconds
Epoch: 0 | Training Samples: 13000 | Loss: 8277.91 | LossAdj: 0.63676 | Time taken: 7 seconds
Epoch: 0 | Training Samples: 14000 | Loss: 8882.99 | LossAdj: 0.63450 | Time taken: 7 seconds
Epoch: 0 | Training Samples: 15000 | Loss: 9368.03 | LossAdj: 0.62454 | Time taken: 8 seconds
Epoch: 0 | Training Samples: 16000 | Loss: 9776.12 | LossAdj: 0.61101 | Time taken: 9 seconds
Epoch: 0 | Training Samples: 17000 | Loss: 10064.15 | LossAdj: 0.59201 | Time taken: 9 seconds
Epoch: 0 | Training Samples: 18000 | Loss: 10708.52 | LossAdj: 0.59492 | Time taken: 10 seconds
Epoch: 0 | Training Samples: 19000 | Loss: 11127.11 | LossAdj: 0.58564 | Time taken: 10 seconds
Epoch: 0 | Training Samples: 20000 | Loss: 11731.54 | LossAdj: 0.58658 | Time taken: 11 seconds
Epoch: 0 | Training Samples: 21000 | Loss: 12354.85 | LossAdj: 0.58833 | Time taken: 11 seconds
Epoch: 0 | Training Samples: 22000 | Loss: 12870.19 | LossAdj: 0.58501 | Time taken: 12 seconds
Epoch: 0 | Training Samples: 23000 | Loss: 13204.10 | LossAdj: 0.57409 | Time taken: 13 seconds
Epoch: 0 | Training Samples: 24000 | Loss: 13665.48 | LossAdj: 0.56939 | Time taken: 13 seconds
Epoch: 0 | Training Samples: 25000 | Loss: 14295.83 | LossAdj: 0.57183 | Time taken: 14 seconds
Epoch: 0 | Training Samples: 26000 | Loss: 14782.59 | LossAdj: 0.56856 | Time taken: 14 seconds
Epoch: 0 | Training Samples: 27000 | Loss: 15339.88 | LossAdj: 0.56814 | Time taken: 15 seconds
Epoch: 0 | Training Samples: 28000 | Loss: 15649.23 | LossAdj: 0.55890 | Time taken: 15 seconds
Epoch: 0 | Training Samples: 29000 | Loss: 16180.84 | LossAdj: 0.55796 | Time taken: 16 seconds
Epoch: 0 | Training Samples: 30000 | Loss: 16665.69 | LossAdj: 0.55552 | Time taken: 16 seconds
Epoch: 0 | Training Samples: 31000 | Loss: 17067.87 | LossAdj: 0.55058 | Time taken: 17 seconds
Epoch: 0 | Training Samples: 32000 | Loss: 17657.53 | LossAdj: 0.55180 | Time taken: 18 seconds
Epoch: 0 | Training Samples: 33000 | Loss: 18317.52 | LossAdj: 0.55508 | Time taken: 18 seconds
Epoch: 0 | Training Samples: 34000 | Loss: 18759.91 | LossAdj: 0.55176 | Time taken: 19 seconds
Epoch: 0 | Training Samples: 35000 | Loss: 19290.19 | LossAdj: 0.55115 | Time taken: 19 seconds
Epoch: 0 | Training Samples: 36000 | Loss: 19606.48 | LossAdj: 0.54462 | Time taken: 20 seconds
Epoch: 0 | Training Samples: 37000 | Loss: 20272.33 | LossAdj: 0.54790 | Time taken: 20 seconds
Epoch: 0 | Training Samples: 38000 | Loss: 20671.80 | LossAdj: 0.54399 | Time taken: 21 seconds
Epoch: 0 | Training Samples: 39000 | Loss: 20881.02 | LossAdj: 0.53541 | Time taken: 22 seconds
Epoch: 0 | Training Samples: 40000 | Loss: 21285.34 | LossAdj: 0.53213 | Time taken: 22 seconds
Epoch: 0 | Training Samples: 41000 | Loss: 21719.18 | LossAdj: 0.52974 | Time taken: 23 seconds
Epoch: 0 | Training Samples: 42000 | Loss: 21954.45 | LossAdj: 0.52272 | Time taken: 23 seconds
Epoch: 0 | Training Samples: 43000 | Loss: 22386.33 | LossAdj: 0.52061 | Time taken: 24 seconds
Epoch: 0 | Training Samples: 44000 | Loss: 22803.83 | LossAdj: 0.51827 | Time taken: 24 seconds
Epoch: 0 | Training Samples: 45000 | Loss: 23373.19 | LossAdj: 0.51940 | Time taken: 25 seconds
Epoch: 0 | Training Samples: 46000 | Loss: 23746.28 | LossAdj: 0.51622 | Time taken: 25 seconds
Epoch: 0 | Training Samples: 47000 | Loss: 24077.82 | LossAdj: 0.51229 | Time taken: 26 seconds
Epoch: 0 | Training Samples: 48000 | Loss: 24711.91 | LossAdj: 0.51483 | Time taken: 27 seconds
Epoch: 0 | Training Samples: 49000 | Loss: 25141.45 | LossAdj: 0.51309 | Time taken: 27 seconds
Epoch: 0 | Training Samples: 50000 | Loss: 25519.79 | LossAdj: 0.51040 | Time taken: 28 seconds
Epoch: 0 | Training Samples: 51000 | Loss: 26020.04 | LossAdj: 0.51020 | Time taken: 28 seconds
Epoch: 0 | Training Samples: 52000 | Loss: 26598.91 | LossAdj: 0.51152 | Time taken: 29 seconds
Epoch: 0 | Training Samples: 53000 | Loss: 26978.16 | LossAdj: 0.50902 | Time taken: 29 seconds
Epoch: 0 | Training Samples: 54000 | Loss: 27277.00 | LossAdj: 0.50513 | Time taken: 30 seconds
Epoch: 0 | Training Samples: 55000 | Loss: 27643.82 | LossAdj: 0.50261 | Time taken: 31 seconds
Epoch: 0 | Training Samples: 56000 | Loss: 27997.18 | LossAdj: 0.49995 | Time taken: 31 seconds
Epoch: 0 | Training Samples: 57000 | Loss: 28688.33 | LossAdj: 0.50330 | Time taken: 32 seconds
Epoch: 0 | Training Samples: 58000 | Loss: 29351.87 | LossAdj: 0.50607 | Time taken: 32 seconds
Epoch: 0 | Training Samples: 59000 | Loss: 29902.63 | LossAdj: 0.50682 | Time taken: 33 seconds
Epoch: 0 | Training Samples: 60000 | Loss: 30281.31 | LossAdj: 0.50469 | Time taken: 33 seconds
Epoch: 0 | Training Samples: 61000 | Loss: 30690.72 | LossAdj: 0.50313 | Time taken: 34 seconds
Epoch: 0 | Training Samples: 62000 | Loss: 31035.57 | LossAdj: 0.50057 | Time taken: 35 seconds
Epoch: 0 | Training Samples: 63000 | Loss: 31442.41 | LossAdj: 0.49909 | Time taken: 35 seconds
Epoch: 0 | Training Samples: 64000 | Loss: 32065.53 | LossAdj: 0.50102 | Time taken: 36 seconds
Epoch: 0 | Training Samples: 65000 | Loss: 32396.35 | LossAdj: 0.49841 | Time taken: 36 seconds
Epoch: 0 | Training Samples: 66000 | Loss: 32811.30 | LossAdj: 0.49714 | Time taken: 37 seconds
Epoch: 0 | Training Samples: 67000 | Loss: 33237.75 | LossAdj: 0.49609 | Time taken: 38 seconds
Epoch: 0 | Training Samples: 68000 | Loss: 33690.42 | LossAdj: 0.49545 | Time taken: 38 seconds
Epoch: 0 | Training Samples: 69000 | Loss: 34015.70 | LossAdj: 0.49298 | Time taken: 39 seconds
Epoch: 0 | Training Samples: 70000 | Loss: 34604.21 | LossAdj: 0.49435 | Time taken: 39 seconds
Epoch: 0 | Training Samples: 71000 | Loss: 34910.12 | LossAdj: 0.49169 | Time taken: 40 seconds
Epoch: 0 | Training Samples: 72000 | Loss: 35370.63 | LossAdj: 0.49126 | Time taken: 41 seconds
Epoch: 0 | Training Samples: 73000 | Loss: 35911.17 | LossAdj: 0.49193 | Time taken: 41 seconds
Epoch: 0 | Training Samples: 74000 | Loss: 36315.88 | LossAdj: 0.49076 | Time taken: 42 seconds
Epoch: 0 | Training Samples: 75000 | Loss: 36748.56 | LossAdj: 0.48998 | Time taken: 42 seconds
Epoch: 0 | Training Samples: 76000 | Loss: 37202.95 | LossAdj: 0.48951 | Time taken: 43 seconds
Epoch: 0 | Training Samples: 77000 | Loss: 37780.98 | LossAdj: 0.49066 | Time taken: 44 seconds
Epoch: 0 | Training Samples: 78000 | Loss: 38210.73 | LossAdj: 0.48988 | Time taken: 44 seconds
Epoch: 0 | Training Samples: 79000 | Loss: 38659.35 | LossAdj: 0.48936 | Time taken: 45 seconds
Epoch: 0 | Training Samples: 80000 | Loss: 39088.99 | LossAdj: 0.48861 | Time taken: 45 seconds
Epoch: 0 | Training Samples: 81000 | Loss: 39425.74 | LossAdj: 0.48674 | Time taken: 46 seconds
Epoch: 0 | Training Samples: 82000 | Loss: 39677.90 | LossAdj: 0.48388 | Time taken: 47 seconds
Epoch: 0 | Training Samples: 83000 | Loss: 40042.14 | LossAdj: 0.48244 | Time taken: 47 seconds
Epoch: 0 | Training Samples: 84000 | Loss: 40479.19 | LossAdj: 0.48190 | Time taken: 48 seconds
Epoch: 0 | Training Samples: 85000 | Loss: 41037.21 | LossAdj: 0.48279 | Time taken: 48 seconds
Epoch: 0 | Training Samples: 86000 | Loss: 41496.24 | LossAdj: 0.48251 | Time taken: 49 seconds
Epoch: 0 | Training Samples: 87000 | Loss: 42045.46 | LossAdj: 0.48328 | Time taken: 49 seconds
Epoch: 0 | Training Samples: 88000 | Loss: 42622.88 | LossAdj: 0.48435 | Time taken: 50 seconds
Epoch: 0 | Training Samples: 89000 | Loss: 43226.97 | LossAdj: 0.48570 | Time taken: 51 seconds
Epoch: 0 | Training Samples: 90000 | Loss: 43817.15 | LossAdj: 0.48686 | Time taken: 51 seconds
Epoch: 0 | Training Samples: 91000 | Loss: 44218.01 | LossAdj: 0.48591 | Time taken: 52 seconds
Epoch: 0 | Training Samples: 92000 | Loss: 44694.71 | LossAdj: 0.48581 | Time taken: 52 seconds
Epoch: 0 | Training Samples: 93000 | Loss: 44980.07 | LossAdj: 0.48366 | Time taken: 53 seconds
Epoch: 0 | Training Samples: 94000 | Loss: 45257.12 | LossAdj: 0.48146 | Time taken: 53 seconds
Epoch: 0 | Training Samples: 95000 | Loss: 45659.86 | LossAdj: 0.48063 | Time taken: 54 seconds
Epoch: 0 | Training Samples: 96000 | Loss: 46299.64 | LossAdj: 0.48229 | Time taken: 55 seconds
Epoch: 0 | Training Samples: 97000 | Loss: 46739.96 | LossAdj: 0.48186 | Time taken: 55 seconds
Epoch: 0 | Training Samples: 98000 | Loss: 47165.04 | LossAdj: 0.48128 | Time taken: 56 seconds
Epoch: 0 | Training Samples: 99000 | Loss: 47482.38 | LossAdj: 0.47962 | Time taken: 56 seconds
Epoch: 0 | Training Samples: 100000 | Loss: 47680.76 | LossAdj: 0.47681 | Time taken: 57 seconds
Epoch: 0 | Training Samples: 101000 | Loss: 48234.33 | LossAdj: 0.47757 | Time taken: 57 seconds
Epoch: 0 | Training Samples: 102000 | Loss: 48709.22 | LossAdj: 0.47754 | Time taken: 58 seconds
Epoch: 0 | Training Samples: 103000 | Loss: 49037.14 | LossAdj: 0.47609 | Time taken: 59 seconds
Epoch: 0 | Training Samples: 104000 | Loss: 49449.75 | LossAdj: 0.47548 | Time taken: 59 seconds
Epoch: 0 | Training Samples: 105000 | Loss: 49803.88 | LossAdj: 0.47432 | Time taken: 60 seconds
Epoch: 0 | Training Samples: 106000 | Loss: 50112.19 | LossAdj: 0.47276 | Time taken: 60 seconds
Epoch: 0 | Training Samples: 107000 | Loss: 50649.39 | LossAdj: 0.47336 | Time taken: 61 seconds
Epoch: 0 | Training Samples: 108000 | Loss: 51156.93 | LossAdj: 0.47368 | Time taken: 61 seconds
Epoch: 0 | Training Samples: 109000 | Loss: 51592.43 | LossAdj: 0.47333 | Time taken: 62 seconds
Epoch: 0 | Training Samples: 110000 | Loss: 51954.63 | LossAdj: 0.47231 | Time taken: 63 seconds
Epoch: 0 | Training Samples: 111000 | Loss: 52335.31 | LossAdj: 0.47149 | Time taken: 63 seconds
Epoch: 0 | Training Samples: 112000 | Loss: 52767.08 | LossAdj: 0.47113 | Time taken: 64 seconds
Epoch: 0 | Training Samples: 113000 | Loss: 53203.69 | LossAdj: 0.47083 | Time taken: 64 seconds
Epoch: 0 | Training Samples: 114000 | Loss: 53480.39 | LossAdj: 0.46913 | Time taken: 65 seconds
Epoch: 0 | Training Samples: 115000 | Loss: 53911.85 | LossAdj: 0.46880 | Time taken: 65 seconds
Epoch: 0 | Training Samples: 116000 | Loss: 54481.56 | LossAdj: 0.46967 | Time taken: 66 seconds
Epoch: 0 | Training Samples: 117000 | Loss: 54888.32 | LossAdj: 0.46913 | Time taken: 67 seconds
Epoch: 0 | Training Samples: 118000 | Loss: 55293.53 | LossAdj: 0.46859 | Time taken: 67 seconds
Epoch: 0 | Training Samples: 119000 | Loss: 55767.51 | LossAdj: 0.46863 | Time taken: 68 seconds
Epoch: 0 | Training Samples: 120000 | Loss: 56412.18 | LossAdj: 0.47010 | Time taken: 68 seconds
Epoch: 0 | Training Samples: 121000 | Loss: 56783.45 | LossAdj: 0.46928 | Time taken: 69 seconds
Epoch: 0 | Training Samples: 122000 | Loss: 57315.33 | LossAdj: 0.46980 | Time taken: 70 seconds
Epoch: 0 | Training Samples: 123000 | Loss: 57801.33 | LossAdj: 0.46993 | Time taken: 70 seconds
Epoch: 0 | Training Samples: 124000 | Loss: 58230.60 | LossAdj: 0.46960 | Time taken: 71 seconds
Epoch: 0 | Training Samples: 125000 | Loss: 58561.44 | LossAdj: 0.46849 | Time taken: 71 seconds
Epoch: 0 | Training Samples: 126000 | Loss: 59023.23 | LossAdj: 0.46844 | Time taken: 72 seconds
Epoch: 0 | Training Samples: 127000 | Loss: 59465.08 | LossAdj: 0.46823 | Time taken: 73 seconds
Epoch: 0 | Training Samples: 128000 | Loss: 60033.85 | LossAdj: 0.46901 | Time taken: 73 seconds
Epoch: 0 | Training Samples: 129000 | Loss: 60341.89 | LossAdj: 0.46777 | Time taken: 74 seconds
Epoch: 0 | Training Samples: 130000 | Loss: 60526.91 | LossAdj: 0.46559 | Time taken: 74 seconds
Epoch: 0 | Training Samples: 131000 | Loss: 60888.07 | LossAdj: 0.46479 | Time taken: 75 seconds
Epoch: 0 | Training Samples: 132000 | Loss: 61388.89 | LossAdj: 0.46507 | Time taken: 75 seconds
Epoch: 0 | Training Samples: 133000 | Loss: 61743.22 | LossAdj: 0.46423 | Time taken: 76 seconds
Epoch: 0 | Training Samples: 134000 | Loss: 62132.27 | LossAdj: 0.46367 | Time taken: 77 seconds
Epoch: 0 | Training Samples: 135000 | Loss: 62711.31 | LossAdj: 0.46453 | Time taken: 77 seconds
Epoch: 0 | Training Samples: 136000 | Loss: 63204.01 | LossAdj: 0.46474 | Time taken: 78 seconds
Epoch: 0 | Training Samples: 137000 | Loss: 63495.84 | LossAdj: 0.46347 | Time taken: 78 seconds
Epoch: 0 | Training Samples: 138000 | Loss: 63965.98 | LossAdj: 0.46352 | Time taken: 79 seconds
Epoch: 0 | Training Samples: 139000 | Loss: 64398.76 | LossAdj: 0.46330 | Time taken: 79 seconds
Epoch: 0 | Training Samples: 140000 | Loss: 64865.07 | LossAdj: 0.46332 | Time taken: 80 seconds
Epoch: 0 | Training Samples: 141000 | Loss: 65246.32 | LossAdj: 0.46274 | Time taken: 80 seconds
Epoch: 0 | Training Samples: 142000 | Loss: 65598.68 | LossAdj: 0.46196 | Time taken: 81 seconds
Epoch: 0 | Training Samples: 143000 | Loss: 65900.02 | LossAdj: 0.46084 | Time taken: 82 seconds
Epoch: 0 | Training Samples: 144000 | Loss: 66483.19 | LossAdj: 0.46169 | Time taken: 82 seconds
Epoch: 0 | Training Samples: 145000 | Loss: 67193.78 | LossAdj: 0.46341 | Time taken: 83 seconds
Epoch: 0 | Training Samples: 146000 | Loss: 67543.41 | LossAdj: 0.46263 | Time taken: 83 seconds
Epoch: 0 | Training Samples: 147000 | Loss: 67869.03 | LossAdj: 0.46169 | Time taken: 84 seconds
Epoch: 0 | Training Samples: 148000 | Loss: 68402.78 | LossAdj: 0.46218 | Time taken: 84 seconds
Epoch: 0 | Training Samples: 149000 | Loss: 68961.32 | LossAdj: 0.46283 | Time taken: 85 seconds
Epoch: 0 | Training Samples: 150000 | Loss: 69501.21 | LossAdj: 0.46334 | Time taken: 85 seconds
--- TRAINING FINISHED IN 85 SECONDS WITH LOSS 0.46 ---
precision recall f1-score support
0 0.99 0.96 0.97 45786
1 0.68 0.88 0.77 4214
accuracy 0.95 50000
macro avg 0.83 0.92 0.87 50000
weighted avg 0.96 0.95 0.96 50000
AUC = 0.963656
Epoch: 0 | Training Samples: 1000 | Loss: 1257.57 | LossAdj: 1.25757 | Time taken: 0 seconds
Epoch: 0 | Training Samples: 2000 | Loss: 2112.75 | LossAdj: 1.05637 | Time taken: 0 seconds
Epoch: 0 | Training Samples: 3000 | Loss: 2993.43 | LossAdj: 0.99781 | Time taken: 1 seconds
Epoch: 0 | Training Samples: 4000 | Loss: 3922.74 | LossAdj: 0.98068 | Time taken: 1 seconds
Epoch: 0 | Training Samples: 5000 | Loss: 5088.32 | LossAdj: 1.01766 | Time taken: 2 seconds
Epoch: 0 | Training Samples: 6000 | Loss: 5995.98 | LossAdj: 0.99933 | Time taken: 2 seconds
Epoch: 0 | Training Samples: 7000 | Loss: 7110.94 | LossAdj: 1.01585 | Time taken: 3 seconds
Epoch: 0 | Training Samples: 8000 | Loss: 8156.98 | LossAdj: 1.01962 | Time taken: 3 seconds
Epoch: 0 | Training Samples: 9000 | Loss: 9001.04 | LossAdj: 1.00012 | Time taken: 3 seconds
Epoch: 0 | Training Samples: 10000 | Loss: 10078.24 | LossAdj: 1.00782 | Time taken: 4 seconds
Epoch: 0 | Training Samples: 11000 | Loss: 11177.21 | LossAdj: 1.01611 | Time taken: 4 seconds
Epoch: 0 | Training Samples: 12000 | Loss: 12171.60 | LossAdj: 1.01430 | Time taken: 5 seconds
Epoch: 0 | Training Samples: 13000 | Loss: 13394.17 | LossAdj: 1.03032 | Time taken: 5 seconds
Epoch: 0 | Training Samples: 14000 | Loss: 14323.12 | LossAdj: 1.02308 | Time taken: 6 seconds
Epoch: 0 | Training Samples: 15000 | Loss: 14942.94 | LossAdj: 0.99620 | Time taken: 6 seconds
Epoch: 0 | Training Samples: 16000 | Loss: 16090.88 | LossAdj: 1.00568 | Time taken: 7 seconds
Epoch: 0 | Training Samples: 17000 | Loss: 16988.05 | LossAdj: 0.99930 | Time taken: 7 seconds
Epoch: 0 | Training Samples: 18000 | Loss: 18004.15 | LossAdj: 1.00023 | Time taken: 8 seconds
Epoch: 0 | Training Samples: 19000 | Loss: 18904.84 | LossAdj: 0.99499 | Time taken: 8 seconds
Epoch: 0 | Training Samples: 20000 | Loss: 19981.50 | LossAdj: 0.99908 | Time taken: 9 seconds
Epoch: 0 | Training Samples: 21000 | Loss: 21207.77 | LossAdj: 1.00989 | Time taken: 9 seconds
Epoch: 0 | Training Samples: 22000 | Loss: 22482.16 | LossAdj: 1.02192 | Time taken: 9 seconds
Epoch: 0 | Training Samples: 23000 | Loss: 23362.86 | LossAdj: 1.01578 | Time taken: 10 seconds
Epoch: 0 | Training Samples: 24000 | Loss: 24191.96 | LossAdj: 1.00800 | Time taken: 10 seconds
Epoch: 0 | Training Samples: 25000 | Loss: 24924.61 | LossAdj: 0.99698 | Time taken: 11 seconds
Epoch: 0 | Training Samples: 26000 | Loss: 26015.79 | LossAdj: 1.00061 | Time taken: 11 seconds
Epoch: 0 | Training Samples: 27000 | Loss: 26783.98 | LossAdj: 0.99200 | Time taken: 12 seconds
Epoch: 0 | Training Samples: 28000 | Loss: 27646.95 | LossAdj: 0.98739 | Time taken: 12 seconds
Epoch: 0 | Training Samples: 29000 | Loss: 28376.89 | LossAdj: 0.97851 | Time taken: 13 seconds
Epoch: 0 | Training Samples: 30000 | Loss: 29228.78 | LossAdj: 0.97429 | Time taken: 13 seconds
Epoch: 0 | Training Samples: 31000 | Loss: 30210.54 | LossAdj: 0.97453 | Time taken: 13 seconds
Epoch: 0 | Training Samples: 32000 | Loss: 30822.37 | LossAdj: 0.96320 | Time taken: 14 seconds
Epoch: 0 | Training Samples: 33000 | Loss: 32029.66 | LossAdj: 0.97060 | Time taken: 14 seconds
Epoch: 0 | Training Samples: 34000 | Loss: 33289.04 | LossAdj: 0.97909 | Time taken: 15 seconds
Epoch: 0 | Training Samples: 35000 | Loss: 34255.27 | LossAdj: 0.97872 | Time taken: 15 seconds
Epoch: 0 | Training Samples: 36000 | Loss: 35003.99 | LossAdj: 0.97233 | Time taken: 16 seconds
Epoch: 0 | Training Samples: 37000 | Loss: 35706.04 | LossAdj: 0.96503 | Time taken: 16 seconds
Epoch: 0 | Training Samples: 38000 | Loss: 36680.91 | LossAdj: 0.96529 | Time taken: 17 seconds
Epoch: 0 | Training Samples: 39000 | Loss: 37258.07 | LossAdj: 0.95534 | Time taken: 17 seconds
Epoch: 0 | Training Samples: 40000 | Loss: 37940.05 | LossAdj: 0.94850 | Time taken: 17 seconds
Epoch: 0 | Training Samples: 41000 | Loss: 38860.91 | LossAdj: 0.94783 | Time taken: 18 seconds
Epoch: 0 | Training Samples: 42000 | Loss: 39667.87 | LossAdj: 0.94447 | Time taken: 18 seconds
Epoch: 0 | Training Samples: 43000 | Loss: 40426.38 | LossAdj: 0.94015 | Time taken: 19 seconds
Epoch: 0 | Training Samples: 44000 | Loss: 41325.41 | LossAdj: 0.93921 | Time taken: 19 seconds
Epoch: 0 | Training Samples: 45000 | Loss: 42282.13 | LossAdj: 0.93960 | Time taken: 20 seconds
Epoch: 0 | Training Samples: 46000 | Loss: 43045.49 | LossAdj: 0.93577 | Time taken: 20 seconds
Epoch: 0 | Training Samples: 47000 | Loss: 44070.65 | LossAdj: 0.93767 | Time taken: 21 seconds
Epoch: 0 | Training Samples: 48000 | Loss: 45305.59 | LossAdj: 0.94387 | Time taken: 21 seconds
Epoch: 0 | Training Samples: 49000 | Loss: 46459.40 | LossAdj: 0.94815 | Time taken: 21 seconds
Epoch: 0 | Training Samples: 50000 | Loss: 47507.75 | LossAdj: 0.95015 | Time taken: 22 seconds
Epoch: 0 | Training Samples: 51000 | Loss: 48207.39 | LossAdj: 0.94524 | Time taken: 22 seconds
Epoch: 0 | Training Samples: 52000 | Loss: 48813.61 | LossAdj: 0.93872 | Time taken: 23 seconds
Epoch: 0 | Training Samples: 53000 | Loss: 49551.49 | LossAdj: 0.93493 | Time taken: 23 seconds
Epoch: 0 | Training Samples: 54000 | Loss: 50318.73 | LossAdj: 0.93183 | Time taken: 24 seconds
Epoch: 0 | Training Samples: 55000 | Loss: 51146.89 | LossAdj: 0.92994 | Time taken: 24 seconds
Epoch: 0 | Training Samples: 56000 | Loss: 52061.12 | LossAdj: 0.92966 | Time taken: 24 seconds
Epoch: 0 | Training Samples: 57000 | Loss: 52705.46 | LossAdj: 0.92466 | Time taken: 25 seconds
Epoch: 0 | Training Samples: 58000 | Loss: 53390.88 | LossAdj: 0.92053 | Time taken: 25 seconds
Epoch: 0 | Training Samples: 59000 | Loss: 54059.54 | LossAdj: 0.91626 | Time taken: 26 seconds
Epoch: 0 | Training Samples: 60000 | Loss: 55178.80 | LossAdj: 0.91965 | Time taken: 26 seconds
Epoch: 0 | Training Samples: 61000 | Loss: 55870.49 | LossAdj: 0.91591 | Time taken: 27 seconds
Epoch: 0 | Training Samples: 62000 | Loss: 56644.42 | LossAdj: 0.91362 | Time taken: 27 seconds
Epoch: 0 | Training Samples: 63000 | Loss: 57705.42 | LossAdj: 0.91596 | Time taken: 28 seconds
Epoch: 0 | Training Samples: 64000 | Loss: 58970.33 | LossAdj: 0.92141 | Time taken: 28 seconds
Epoch: 0 | Training Samples: 65000 | Loss: 60195.57 | LossAdj: 0.92609 | Time taken: 28 seconds
Epoch: 0 | Training Samples: 66000 | Loss: 61377.78 | LossAdj: 0.92997 | Time taken: 29 seconds
Epoch: 0 | Training Samples: 67000 | Loss: 62111.35 | LossAdj: 0.92704 | Time taken: 29 seconds
Epoch: 0 | Training Samples: 68000 | Loss: 63504.42 | LossAdj: 0.93389 | Time taken: 30 seconds
Epoch: 0 | Training Samples: 69000 | Loss: 64852.09 | LossAdj: 0.93989 | Time taken: 30 seconds
Epoch: 0 | Training Samples: 70000 | Loss: 65601.76 | LossAdj: 0.93717 | Time taken: 31 seconds
Epoch: 0 | Training Samples: 71000 | Loss: 66242.42 | LossAdj: 0.93299 | Time taken: 31 seconds
Epoch: 0 | Training Samples: 72000 | Loss: 66937.99 | LossAdj: 0.92969 | Time taken: 31 seconds
Epoch: 0 | Training Samples: 73000 | Loss: 68138.61 | LossAdj: 0.93341 | Time taken: 32 seconds
Epoch: 0 | Training Samples: 74000 | Loss: 68886.27 | LossAdj: 0.93090 | Time taken: 32 seconds
Epoch: 0 | Training Samples: 75000 | Loss: 69900.55 | LossAdj: 0.93201 | Time taken: 33 seconds
Epoch: 0 | Training Samples: 76000 | Loss: 70842.98 | LossAdj: 0.93214 | Time taken: 33 seconds
Epoch: 0 | Training Samples: 77000 | Loss: 71483.82 | LossAdj: 0.92836 | Time taken: 34 seconds
Epoch: 0 | Training Samples: 78000 | Loss: 72154.74 | LossAdj: 0.92506 | Time taken: 34 seconds
Epoch: 0 | Training Samples: 79000 | Loss: 73012.41 | LossAdj: 0.92421 | Time taken: 34 seconds
Epoch: 0 | Training Samples: 80000 | Loss: 74440.91 | LossAdj: 0.93051 | Time taken: 35 seconds
Epoch: 0 | Training Samples: 81000 | Loss: 75418.48 | LossAdj: 0.93109 | Time taken: 35 seconds
Epoch: 0 | Training Samples: 82000 | Loss: 76294.89 | LossAdj: 0.93043 | Time taken: 36 seconds
Epoch: 0 | Training Samples: 83000 | Loss: 77157.43 | LossAdj: 0.92961 | Time taken: 36 seconds
Epoch: 0 | Training Samples: 84000 | Loss: 77970.58 | LossAdj: 0.92822 | Time taken: 37 seconds
Epoch: 0 | Training Samples: 85000 | Loss: 78426.28 | LossAdj: 0.92266 | Time taken: 37 seconds
Epoch: 0 | Training Samples: 86000 | Loss: 79520.20 | LossAdj: 0.92465 | Time taken: 37 seconds
Epoch: 0 | Training Samples: 87000 | Loss: 80307.06 | LossAdj: 0.92307 | Time taken: 38 seconds
Epoch: 0 | Training Samples: 88000 | Loss: 80786.82 | LossAdj: 0.91803 | Time taken: 38 seconds
Epoch: 0 | Training Samples: 89000 | Loss: 81672.57 | LossAdj: 0.91767 | Time taken: 39 seconds
Epoch: 0 | Training Samples: 90000 | Loss: 83088.54 | LossAdj: 0.92321 | Time taken: 39 seconds
Epoch: 0 | Training Samples: 91000 | Loss: 84763.46 | LossAdj: 0.93147 | Time taken: 40 seconds
Epoch: 0 | Training Samples: 92000 | Loss: 85629.42 | LossAdj: 0.93075 | Time taken: 40 seconds
Epoch: 0 | Training Samples: 93000 | Loss: 86275.04 | LossAdj: 0.92769 | Time taken: 40 seconds
Epoch: 0 | Training Samples: 94000 | Loss: 86918.13 | LossAdj: 0.92466 | Time taken: 41 seconds
Epoch: 0 | Training Samples: 95000 | Loss: 87656.31 | LossAdj: 0.92270 | Time taken: 41 seconds
Epoch: 0 | Training Samples: 96000 | Loss: 88541.03 | LossAdj: 0.92230 | Time taken: 42 seconds
Epoch: 0 | Training Samples: 97000 | Loss: 89605.20 | LossAdj: 0.92376 | Time taken: 42 seconds
Epoch: 0 | Training Samples: 98000 | Loss: 90917.31 | LossAdj: 0.92773 | Time taken: 42 seconds
Epoch: 0 | Training Samples: 99000 | Loss: 91771.78 | LossAdj: 0.92699 | Time taken: 43 seconds
Epoch: 0 | Training Samples: 100000 | Loss: 92744.42 | LossAdj: 0.92744 | Time taken: 43 seconds
Epoch: 0 | Training Samples: 101000 | Loss: 93969.04 | LossAdj: 0.93039 | Time taken: 44 seconds
Epoch: 0 | Training Samples: 102000 | Loss: 94463.27 | LossAdj: 0.92611 | Time taken: 44 seconds
Epoch: 0 | Training Samples: 103000 | Loss: 95752.45 | LossAdj: 0.92964 | Time taken: 45 seconds
Epoch: 0 | Training Samples: 104000 | Loss: 96390.35 | LossAdj: 0.92683 | Time taken: 45 seconds
Epoch: 0 | Training Samples: 105000 | Loss: 97190.71 | LossAdj: 0.92563 | Time taken: 45 seconds
Epoch: 0 | Training Samples: 106000 | Loss: 98215.18 | LossAdj: 0.92656 | Time taken: 46 seconds
Epoch: 0 | Training Samples: 107000 | Loss: 98900.67 | LossAdj: 0.92431 | Time taken: 46 seconds
Epoch: 0 | Training Samples: 108000 | Loss: 99735.78 | LossAdj: 0.92348 | Time taken: 47 seconds
Epoch: 0 | Training Samples: 109000 | Loss: 101027.22 | LossAdj: 0.92686 | Time taken: 47 seconds
Epoch: 0 | Training Samples: 110000 | Loss: 101753.20 | LossAdj: 0.92503 | Time taken: 48 seconds
Epoch: 0 | Training Samples: 111000 | Loss: 102688.48 | LossAdj: 0.92512 | Time taken: 48 seconds
Epoch: 0 | Training Samples: 112000 | Loss: 103524.09 | LossAdj: 0.92432 | Time taken: 49 seconds
Epoch: 0 | Training Samples: 113000 | Loss: 104823.08 | LossAdj: 0.92764 | Time taken: 49 seconds
Epoch: 0 | Training Samples: 114000 | Loss: 105424.51 | LossAdj: 0.92478 | Time taken: 49 seconds
Epoch: 0 | Training Samples: 115000 | Loss: 106426.80 | LossAdj: 0.92545 | Time taken: 50 seconds
Epoch: 0 | Training Samples: 116000 | Loss: 107188.28 | LossAdj: 0.92404 | Time taken: 50 seconds
Epoch: 0 | Training Samples: 117000 | Loss: 108603.67 | LossAdj: 0.92824 | Time taken: 51 seconds
Epoch: 0 | Training Samples: 118000 | Loss: 109673.32 | LossAdj: 0.92943 | Time taken: 51 seconds
Epoch: 0 | Training Samples: 119000 | Loss: 110869.72 | LossAdj: 0.93168 | Time taken: 52 seconds
Epoch: 0 | Training Samples: 120000 | Loss: 111506.35 | LossAdj: 0.92922 | Time taken: 52 seconds
Epoch: 0 | Training Samples: 121000 | Loss: 112116.66 | LossAdj: 0.92658 | Time taken: 53 seconds
Epoch: 0 | Training Samples: 122000 | Loss: 112906.72 | LossAdj: 0.92546 | Time taken: 53 seconds
Epoch: 0 | Training Samples: 123000 | Loss: 114101.98 | LossAdj: 0.92766 | Time taken: 54 seconds
Epoch: 0 | Training Samples: 124000 | Loss: 115055.00 | LossAdj: 0.92786 | Time taken: 54 seconds
Epoch: 0 | Training Samples: 125000 | Loss: 116074.96 | LossAdj: 0.92860 | Time taken: 54 seconds
Epoch: 0 | Training Samples: 126000 | Loss: 116790.69 | LossAdj: 0.92691 | Time taken: 55 seconds
Epoch: 0 | Training Samples: 127000 | Loss: 117436.62 | LossAdj: 0.92470 | Time taken: 55 seconds
Epoch: 0 | Training Samples: 128000 | Loss: 118342.75 | LossAdj: 0.92455 | Time taken: 56 seconds
Epoch: 0 | Training Samples: 129000 | Loss: 119441.61 | LossAdj: 0.92590 | Time taken: 56 seconds
Epoch: 0 | Training Samples: 130000 | Loss: 120179.34 | LossAdj: 0.92446 | Time taken: 57 seconds
Epoch: 0 | Training Samples: 131000 | Loss: 120722.99 | LossAdj: 0.92155 | Time taken: 57 seconds
Epoch: 0 | Training Samples: 132000 | Loss: 121762.82 | LossAdj: 0.92245 | Time taken: 57 seconds
Epoch: 0 | Training Samples: 133000 | Loss: 123170.46 | LossAdj: 0.92609 | Time taken: 58 seconds
Epoch: 0 | Training Samples: 134000 | Loss: 123758.02 | LossAdj: 0.92357 | Time taken: 58 seconds
Epoch: 0 | Training Samples: 135000 | Loss: 125366.03 | LossAdj: 0.92864 | Time taken: 59 seconds
Epoch: 0 | Training Samples: 136000 | Loss: 125886.07 | LossAdj: 0.92563 | Time taken: 59 seconds
Epoch: 0 | Training Samples: 137000 | Loss: 127142.53 | LossAdj: 0.92805 | Time taken: 60 seconds
Epoch: 0 | Training Samples: 138000 | Loss: 127784.96 | LossAdj: 0.92598 | Time taken: 60 seconds
Epoch: 0 | Training Samples: 139000 | Loss: 128407.45 | LossAdj: 0.92379 | Time taken: 60 seconds
Epoch: 0 | Training Samples: 140000 | Loss: 129070.45 | LossAdj: 0.92193 | Time taken: 61 seconds
Epoch: 0 | Training Samples: 141000 | Loss: 129857.51 | LossAdj: 0.92098 | Time taken: 61 seconds
Epoch: 0 | Training Samples: 142000 | Loss: 131083.36 | LossAdj: 0.92312 | Time taken: 62 seconds
Epoch: 0 | Training Samples: 143000 | Loss: 131600.55 | LossAdj: 0.92028 | Time taken: 62 seconds
Epoch: 0 | Training Samples: 144000 | Loss: 132075.63 | LossAdj: 0.91719 | Time taken: 63 seconds
Epoch: 0 | Training Samples: 145000 | Loss: 133875.26 | LossAdj: 0.92328 | Time taken: 63 seconds
Epoch: 0 | Training Samples: 146000 | Loss: 135101.30 | LossAdj: 0.92535 | Time taken: 63 seconds
Epoch: 0 | Training Samples: 147000 | Loss: 136453.21 | LossAdj: 0.92825 | Time taken: 64 seconds
Epoch: 0 | Training Samples: 148000 | Loss: 137657.81 | LossAdj: 0.93012 | Time taken: 64 seconds
Epoch: 0 | Training Samples: 149000 | Loss: 138492.22 | LossAdj: 0.92948 | Time taken: 65 seconds
Epoch: 0 | Training Samples: 150000 | Loss: 139432.42 | LossAdj: 0.92955 | Time taken: 65 seconds
--- TRAINING FINISHED IN 65 SECONDS WITH LOSS 0.93 ---
precision recall f1-score support
0 0.99 0.97 0.98 45786
1 0.72 0.84 0.78 4214
accuracy 0.96 50000
macro avg 0.85 0.91 0.88 50000
weighted avg 0.96 0.96 0.96 50000
AUC = 0.955793
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Content source: davideanastasia/vantgrd-py
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