Epoch: 0001 train_loss= 1.39176 train_acc= 0.27095 val_loss= 1.39062 val_acc= 0.31667 time= 0.68198
Epoch: 0002 train_loss= 1.38868 train_acc= 0.29330 val_loss= 1.39001 val_acc= 0.31667 time= 0.01563
Epoch: 0003 train_loss= 1.38648 train_acc= 0.30587 val_loss= 1.38987 val_acc= 0.31667 time= 0.01563
Epoch: 0004 train_loss= 1.38415 train_acc= 0.30307 val_loss= 1.38993 val_acc= 0.31667 time= 0.01562
Epoch: 0005 train_loss= 1.38222 train_acc= 0.30726 val_loss= 1.39029 val_acc= 0.31667 time= 0.01562
Epoch: 0006 train_loss= 1.38095 train_acc= 0.30587 val_loss= 1.39067 val_acc= 0.31667 time= 0.00000
Epoch: 0007 train_loss= 1.37953 train_acc= 0.30447 val_loss= 1.39118 val_acc= 0.31667 time= 0.01563
Epoch: 0008 train_loss= 1.37910 train_acc= 0.30587 val_loss= 1.39180 val_acc= 0.31667 time= 0.01563
Epoch: 0009 train_loss= 1.37764 train_acc= 0.30587 val_loss= 1.39254 val_acc= 0.31667 time= 0.01562
Epoch: 0010 train_loss= 1.37737 train_acc= 0.30587 val_loss= 1.39336 val_acc= 0.31667 time= 0.00000
Epoch: 0011 train_loss= 1.37677 train_acc= 0.30587 val_loss= 1.39421 val_acc= 0.31667 time= 0.01563
Epoch: 0012 train_loss= 1.37695 train_acc= 0.30587 val_loss= 1.39500 val_acc= 0.31667 time= 0.01563
Early stopping...
Optimization Finished!
Test set results: cost= 1.38529 accuracy= 0.31667 time= 0.01563 
