Epoch: 0001 train_loss= 1.42205 train_acc= 0.22266 val_loss= 1.38657 val_acc= 0.23214 time= 0.20314
Epoch: 0002 train_loss= 1.41660 train_acc= 0.22266 val_loss= 1.37831 val_acc= 0.32143 time= 0.01563
Epoch: 0003 train_loss= 1.39762 train_acc= 0.23047 val_loss= 1.37283 val_acc= 0.35714 time= 0.01563
Epoch: 0004 train_loss= 1.39635 train_acc= 0.22461 val_loss= 1.36896 val_acc= 0.37500 time= 0.01563
Epoch: 0005 train_loss= 1.38852 train_acc= 0.28711 val_loss= 1.36678 val_acc= 0.37500 time= 0.01563
Epoch: 0006 train_loss= 1.39759 train_acc= 0.25391 val_loss= 1.36574 val_acc= 0.37500 time= 0.01563
Epoch: 0007 train_loss= 1.39053 train_acc= 0.28125 val_loss= 1.36513 val_acc= 0.37500 time= 0.01563
Epoch: 0008 train_loss= 1.38892 train_acc= 0.29492 val_loss= 1.36535 val_acc= 0.37500 time= 0.01563
Epoch: 0009 train_loss= 1.38741 train_acc= 0.29102 val_loss= 1.36622 val_acc= 0.37500 time= 0.01562
Epoch: 0010 train_loss= 1.39175 train_acc= 0.29297 val_loss= 1.36753 val_acc= 0.37500 time= 0.01563
Epoch: 0011 train_loss= 1.38395 train_acc= 0.29297 val_loss= 1.36905 val_acc= 0.37500 time= 0.01563
Epoch: 0012 train_loss= 1.39540 train_acc= 0.28906 val_loss= 1.37118 val_acc= 0.37500 time= 0.01563
Early stopping...
Optimization Finished!
Test set results: cost= 1.35734 accuracy= 0.36283 time= 0.01563 
