Epoch: 0001 train_loss= 1.39406 train_acc= 0.26397 val_loss= 1.39109 val_acc= 0.33929 time= 0.79812
Epoch: 0002 train_loss= 1.39067 train_acc= 0.31145 val_loss= 1.38887 val_acc= 0.32143 time= 0.01561
Epoch: 0003 train_loss= 1.38783 train_acc= 0.29749 val_loss= 1.38737 val_acc= 0.32143 time= 0.01563
Epoch: 0004 train_loss= 1.38531 train_acc= 0.30028 val_loss= 1.38661 val_acc= 0.32143 time= 0.01562
Epoch: 0005 train_loss= 1.38348 train_acc= 0.30028 val_loss= 1.38638 val_acc= 0.32143 time= 0.01563
Epoch: 0006 train_loss= 1.38274 train_acc= 0.30028 val_loss= 1.38657 val_acc= 0.32143 time= 0.00000
Epoch: 0007 train_loss= 1.38205 train_acc= 0.30028 val_loss= 1.38711 val_acc= 0.32143 time= 0.01562
Epoch: 0008 train_loss= 1.38142 train_acc= 0.30168 val_loss= 1.38787 val_acc= 0.32143 time= 0.01563
Epoch: 0009 train_loss= 1.38134 train_acc= 0.30028 val_loss= 1.38857 val_acc= 0.32143 time= 0.01563
Epoch: 0010 train_loss= 1.38163 train_acc= 0.30028 val_loss= 1.38915 val_acc= 0.32143 time= 0.01563
Epoch: 0011 train_loss= 1.38094 train_acc= 0.30028 val_loss= 1.38954 val_acc= 0.32143 time= 0.01563
Epoch: 0012 train_loss= 1.38067 train_acc= 0.30028 val_loss= 1.38976 val_acc= 0.32143 time= 0.00000
Early stopping...
Optimization Finished!
Test set results: cost= 1.39041 accuracy= 0.31858 time= 0.01563 
