Epoch 2 / 200 lr=0.0002
New best accuracy found: 0.21% at epoch 2. Model saved.

New lowest loss found: 1.9924 at epoch 2.

train_acc: 21.50% 	 train_loss: 2.0850
val_acc: 20.90% 	 val_loss: 1.9924
Train time elapsed 7m 27s


Epoch 3 / 200 lr=0.0002
New best accuracy found: 0.27% at epoch 3. Model saved.

New lowest loss found: 1.8661 at epoch 3.

train_acc: 25.78% 	 train_loss: 1.9540
val_acc: 27.43% 	 val_loss: 1.8661
Train time elapsed 11m 10s


Epoch 4 / 200 lr=0.0002
New lowest loss found: 1.8364 at epoch 4.

train_acc: 27.30% 	 train_loss: 1.8868
val_acc: 26.45% 	 val_loss: 1.8364
Train time elapsed 14m 53s


Epoch 5 / 200 lr=0.0002
New best accuracy found: 0.32% at epoch 5. Model saved.

New lowest loss found: 1.8072 at epoch 5.

train_acc: 30.04% 	 train_loss: 1.8233
val_acc: 31.85% 	 val_loss: 1.8072
Train time elapsed 18m 37s


Epoch 6 / 200 lr=0.0002
New best accuracy found: 0.40% at epoch 6. Model saved.

New lowest loss found: 1.6653 at epoch 6.

train_acc: 36.12% 	 train_loss: 1.7262
val_acc: 40.40% 	 val_loss: 1.6653
Train time elapsed 22m 20s


Epoch 7 / 200 lr=0.0002
New best accuracy found: 0.44% at epoch 7. Model saved.

New lowest loss found: 1.5459 at epoch 7.

train_acc: 41.50% 	 train_loss: 1.5791
val_acc: 43.70% 	 val_loss: 1.5459
Train time elapsed 26m 4s


Epoch 8 / 200 lr=0.0002
New best accuracy found: 0.46% at epoch 8. Model saved.

New lowest loss found: 1.4906 at epoch 8.

train_acc: 42.32% 	 train_loss: 1.5110
val_acc: 45.95% 	 val_loss: 1.4906
Train time elapsed 29m 47s


Epoch 9 / 200 lr=0.0002
train_acc: 45.44% 	 train_loss: 1.4281
val_acc: 41.20% 	 val_loss: 1.5503
Train time elapsed 33m 31s


Epoch 10 / 200 lr=0.0002
New best accuracy found: 0.47% at epoch 10. Model saved.

New lowest loss found: 1.4653 at epoch 10.

train_acc: 46.22% 	 train_loss: 1.4069
val_acc: 47.10% 	 val_loss: 1.4653
Train time elapsed 37m 15s


Epoch 11 / 200 lr=0.0002
New best accuracy found: 0.52% at epoch 11. Model saved.

New lowest loss found: 1.3368 at epoch 11.

train_acc: 49.22% 	 train_loss: 1.3491
val_acc: 52.15% 	 val_loss: 1.3368
Train time elapsed 40m 58s


Epoch 12 / 200 lr=0.0002
train_acc: 50.36% 	 train_loss: 1.3269
val_acc: 50.50% 	 val_loss: 1.3854
Train time elapsed 44m 42s


Epoch 13 / 200 lr=0.0002
train_acc: 48.56% 	 train_loss: 1.3468
val_acc: 47.62% 	 val_loss: 1.4404
Train time elapsed 48m 26s


Epoch 14 / 200 lr=0.0002
train_acc: 52.82% 	 train_loss: 1.2504
val_acc: 51.38% 	 val_loss: 1.3581
Train time elapsed 52m 10s


Epoch 15 / 200 lr=0.0002
New best accuracy found: 0.53% at epoch 15. Model saved.

New lowest loss found: 1.3260 at epoch 15.

train_acc: 52.62% 	 train_loss: 1.2406
val_acc: 52.55% 	 val_loss: 1.3260
Train time elapsed 55m 55s


Epoch 16 / 200 lr=0.0002
train_acc: 54.28% 	 train_loss: 1.2198
val_acc: 44.75% 	 val_loss: 1.4967
Train time elapsed 59m 39s


Epoch 17 / 200 lr=0.0002
train_acc: 54.56% 	 train_loss: 1.1890
val_acc: 52.30% 	 val_loss: 1.3394
Train time elapsed 63m 23s


Epoch 18 / 200 lr=0.0002
train_acc: 55.52% 	 train_loss: 1.1782
val_acc: 51.10% 	 val_loss: 1.3920
Train time elapsed 67m 7s


Epoch 19 / 200 lr=0.0002
train_acc: 55.80% 	 train_loss: 1.1686
val_acc: 50.42% 	 val_loss: 1.3559
Train time elapsed 70m 51s


Epoch 20 / 200 lr=0.0002
train_acc: 57.28% 	 train_loss: 1.1143
val_acc: 50.85% 	 val_loss: 1.3965
Train time elapsed 74m 35s


Epoch 21 / 200 lr=0.0002
train_acc: 56.56% 	 train_loss: 1.1221
val_acc: 51.60% 	 val_loss: 1.3815
Train time elapsed 78m 19s


Epoch 22 / 200 lr=0.0002
New best accuracy found: 0.53% at epoch 22. Model saved.

train_acc: 57.90% 	 train_loss: 1.1178
val_acc: 52.58% 	 val_loss: 1.3699
Train time elapsed 82m 3s


Epoch 23 / 200 lr=0.0002
train_acc: 59.68% 	 train_loss: 1.0642
val_acc: 52.52% 	 val_loss: 1.3631
Train time elapsed 85m 47s


Epoch 24 / 200 lr=0.0002
train_acc: 61.18% 	 train_loss: 1.0275
val_acc: 52.20% 	 val_loss: 1.3807
Train time elapsed 89m 31s


Epoch 25 / 200 lr=0.0002
train_acc: 60.10% 	 train_loss: 1.0782
val_acc: 50.60% 	 val_loss: 1.3958
Train time elapsed 93m 15s


Epoch 26 / 200 lr=0.0002
New best accuracy found: 0.55% at epoch 26. Model saved.

New lowest loss found: 1.3259 at epoch 26.

train_acc: 62.10% 	 train_loss: 1.0199
val_acc: 54.50% 	 val_loss: 1.3259
Train time elapsed 96m 59s


Epoch 27 / 200 lr=0.0002
train_acc: 62.48% 	 train_loss: 0.9936
val_acc: 52.12% 	 val_loss: 1.4585
Train time elapsed 100m 43s


Epoch 28 / 200 lr=0.0002
train_acc: 63.20% 	 train_loss: 0.9808
val_acc: 53.15% 	 val_loss: 1.4278
Train time elapsed 104m 28s


Epoch 29 / 200 lr=0.0002
train_acc: 65.24% 	 train_loss: 0.9314
val_acc: 50.78% 	 val_loss: 1.4748
Train time elapsed 108m 12s


Epoch 30 / 200 lr=0.0002
train_acc: 66.12% 	 train_loss: 0.9047
val_acc: 51.88% 	 val_loss: 1.5025
Train time elapsed 111m 56s