Epoch: 0001 train_loss= 1.39230 train_acc= 0.29297 val_loss= 1.39324 val_acc= 0.19643 time= 0.25002
Epoch: 0002 train_loss= 1.39072 train_acc= 0.29492 val_loss= 1.39333 val_acc= 0.19643 time= 0.01563
Epoch: 0003 train_loss= 1.38986 train_acc= 0.29492 val_loss= 1.39364 val_acc= 0.19643 time= 0.01563
Epoch: 0004 train_loss= 1.38887 train_acc= 0.29492 val_loss= 1.39419 val_acc= 0.19643 time= 0.01563
Epoch: 0005 train_loss= 1.38797 train_acc= 0.29492 val_loss= 1.39488 val_acc= 0.19643 time= 0.01562
Epoch: 0006 train_loss= 1.38743 train_acc= 0.29492 val_loss= 1.39567 val_acc= 0.19643 time= 0.01563
Epoch: 0007 train_loss= 1.38678 train_acc= 0.29492 val_loss= 1.39654 val_acc= 0.19643 time= 0.01562
Epoch: 0008 train_loss= 1.38632 train_acc= 0.29492 val_loss= 1.39745 val_acc= 0.19643 time= 0.01563
Epoch: 0009 train_loss= 1.38579 train_acc= 0.29492 val_loss= 1.39826 val_acc= 0.19643 time= 0.01563
Epoch: 0010 train_loss= 1.38540 train_acc= 0.29492 val_loss= 1.39896 val_acc= 0.19643 time= 0.01563
Epoch: 0011 train_loss= 1.38507 train_acc= 0.29492 val_loss= 1.39950 val_acc= 0.19643 time= 0.01563
Epoch: 0012 train_loss= 1.38436 train_acc= 0.29492 val_loss= 1.39981 val_acc= 0.19643 time= 0.01562
Early stopping...
Optimization Finished!
Test set results: cost= 1.37992 accuracy= 0.29204 time= 0.01563 
