Epoch: 0001 train_loss= 1.39349 train_acc= 0.23779 val_loss= 1.39946 val_acc= 0.10714 time= 0.10938
Epoch: 0002 train_loss= 1.39189 train_acc= 0.23779 val_loss= 1.39534 val_acc= 0.35714 time= 0.01563
Epoch: 0003 train_loss= 1.39053 train_acc= 0.28339 val_loss= 1.39162 val_acc= 0.35714 time= 0.01563
Epoch: 0004 train_loss= 1.38977 train_acc= 0.28664 val_loss= 1.38889 val_acc= 0.35714 time= 0.01562
Epoch: 0005 train_loss= 1.38889 train_acc= 0.28664 val_loss= 1.38687 val_acc= 0.35714 time= 0.01563
Epoch: 0006 train_loss= 1.38842 train_acc= 0.28664 val_loss= 1.38514 val_acc= 0.35714 time= 0.01563
Epoch: 0007 train_loss= 1.38752 train_acc= 0.28664 val_loss= 1.38394 val_acc= 0.35714 time= 0.01563
Epoch: 0008 train_loss= 1.38742 train_acc= 0.28664 val_loss= 1.38342 val_acc= 0.35714 time= 0.01563
Epoch: 0009 train_loss= 1.38689 train_acc= 0.28664 val_loss= 1.38306 val_acc= 0.35714 time= 0.01563
Epoch: 0010 train_loss= 1.38638 train_acc= 0.28664 val_loss= 1.38299 val_acc= 0.35714 time= 0.01563
Epoch: 0011 train_loss= 1.38671 train_acc= 0.28664 val_loss= 1.38286 val_acc= 0.35714 time= 0.01563
Epoch: 0012 train_loss= 1.38639 train_acc= 0.28664 val_loss= 1.38284 val_acc= 0.35714 time= 0.01563
Epoch: 0013 train_loss= 1.38641 train_acc= 0.28664 val_loss= 1.38278 val_acc= 0.35714 time= 0.01563
Epoch: 0014 train_loss= 1.38564 train_acc= 0.28664 val_loss= 1.38268 val_acc= 0.35714 time= 0.01563
Epoch: 0015 train_loss= 1.38543 train_acc= 0.28664 val_loss= 1.38254 val_acc= 0.35714 time= 0.01563
Epoch: 0016 train_loss= 1.38505 train_acc= 0.28664 val_loss= 1.38234 val_acc= 0.35714 time= 0.01563
Epoch: 0017 train_loss= 1.38467 train_acc= 0.28664 val_loss= 1.38217 val_acc= 0.35714 time= 0.01563
Epoch: 0018 train_loss= 1.38476 train_acc= 0.28664 val_loss= 1.38208 val_acc= 0.35714 time= 0.01563
Epoch: 0019 train_loss= 1.38402 train_acc= 0.28664 val_loss= 1.38198 val_acc= 0.35714 time= 0.01563
Epoch: 0020 train_loss= 1.38430 train_acc= 0.28664 val_loss= 1.38198 val_acc= 0.35714 time= 0.01563
Epoch: 0021 train_loss= 1.38403 train_acc= 0.28664 val_loss= 1.38191 val_acc= 0.35714 time= 0.01563
Epoch: 0022 train_loss= 1.38390 train_acc= 0.28664 val_loss= 1.38184 val_acc= 0.35714 time= 0.01563
Epoch: 0023 train_loss= 1.38381 train_acc= 0.28664 val_loss= 1.38178 val_acc= 0.35714 time= 0.01563
Epoch: 0024 train_loss= 1.38381 train_acc= 0.28664 val_loss= 1.38174 val_acc= 0.35714 time= 0.01563
Epoch: 0025 train_loss= 1.38341 train_acc= 0.28664 val_loss= 1.38164 val_acc= 0.35714 time= 0.01563
Epoch: 0026 train_loss= 1.38381 train_acc= 0.28664 val_loss= 1.38153 val_acc= 0.35714 time= 0.01563
Epoch: 0027 train_loss= 1.38335 train_acc= 0.28664 val_loss= 1.38143 val_acc= 0.35714 time= 0.01562
Epoch: 0028 train_loss= 1.38313 train_acc= 0.28664 val_loss= 1.38128 val_acc= 0.35714 time= 0.01563
Epoch: 0029 train_loss= 1.38356 train_acc= 0.28664 val_loss= 1.38109 val_acc= 0.35714 time= 0.01563
Epoch: 0030 train_loss= 1.38346 train_acc= 0.28664 val_loss= 1.38093 val_acc= 0.35714 time= 0.01563
Epoch: 0031 train_loss= 1.38279 train_acc= 0.28664 val_loss= 1.38083 val_acc= 0.35714 time= 0.01563
Epoch: 0032 train_loss= 1.38351 train_acc= 0.28664 val_loss= 1.38076 val_acc= 0.35714 time= 0.00000
Epoch: 0033 train_loss= 1.38307 train_acc= 0.28664 val_loss= 1.38077 val_acc= 0.35714 time= 0.00000
Epoch: 0034 train_loss= 1.38316 train_acc= 0.28664 val_loss= 1.38088 val_acc= 0.35714 time= 0.01563
Epoch: 0035 train_loss= 1.38307 train_acc= 0.28664 val_loss= 1.38086 val_acc= 0.35714 time= 0.01563
Epoch: 0036 train_loss= 1.38272 train_acc= 0.28664 val_loss= 1.38085 val_acc= 0.35714 time= 0.01563
Epoch: 0037 train_loss= 1.38249 train_acc= 0.28664 val_loss= 1.38080 val_acc= 0.35714 time= 0.01563
Epoch: 0038 train_loss= 1.38321 train_acc= 0.28664 val_loss= 1.38080 val_acc= 0.35714 time= 0.01563
Epoch: 0039 train_loss= 1.38330 train_acc= 0.28664 val_loss= 1.38097 val_acc= 0.35714 time= 0.01563
Early stopping...
Optimization Finished!
Test set results: cost= 1.37987 accuracy= 0.31858 time= 0.01563 
