Epoch: 0001 train_loss= 1.43036 train_acc= 0.19553 val_loss= 1.39571 val_acc= 0.21429 time= 0.29690
Epoch: 0002 train_loss= 1.44021 train_acc= 0.19553 val_loss= 1.39354 val_acc= 0.21429 time= 0.01563
Epoch: 0003 train_loss= 1.41792 train_acc= 0.19972 val_loss= 1.39274 val_acc= 0.21429 time= 0.01563
Epoch: 0004 train_loss= 1.40610 train_acc= 0.21508 val_loss= 1.39241 val_acc= 0.21429 time= 0.01563
Epoch: 0005 train_loss= 1.40078 train_acc= 0.20391 val_loss= 1.39314 val_acc= 0.25000 time= 0.01563
Epoch: 0006 train_loss= 1.40010 train_acc= 0.22067 val_loss= 1.39449 val_acc= 0.26786 time= 0.01563
Epoch: 0007 train_loss= 1.39831 train_acc= 0.24022 val_loss= 1.39572 val_acc= 0.30357 time= 0.03125
Epoch: 0008 train_loss= 1.38761 train_acc= 0.29469 val_loss= 1.39723 val_acc= 0.32143 time= 0.01563
Epoch: 0009 train_loss= 1.38985 train_acc= 0.30168 val_loss= 1.39888 val_acc= 0.33929 time= 0.01563
Epoch: 0010 train_loss= 1.38745 train_acc= 0.29190 val_loss= 1.40066 val_acc= 0.33929 time= 0.01563
Epoch: 0011 train_loss= 1.38364 train_acc= 0.29609 val_loss= 1.40235 val_acc= 0.33929 time= 0.01563
Epoch: 0012 train_loss= 1.38134 train_acc= 0.30866 val_loss= 1.40394 val_acc= 0.33929 time= 0.01563
Early stopping...
Optimization Finished!
Test set results: cost= 1.38399 accuracy= 0.29204 time= 0.00000 
