Epoch: 0001 train_loss= 1.39411 train_acc= 0.29883 val_loss= 1.39211 val_acc= 0.23214 time= 0.26564
Epoch: 0002 train_loss= 1.39102 train_acc= 0.30078 val_loss= 1.39069 val_acc= 0.23214 time= 0.01563
Epoch: 0003 train_loss= 1.38874 train_acc= 0.30078 val_loss= 1.39001 val_acc= 0.23214 time= 0.01563
Epoch: 0004 train_loss= 1.38713 train_acc= 0.30078 val_loss= 1.39001 val_acc= 0.23214 time= 0.01563
Epoch: 0005 train_loss= 1.38585 train_acc= 0.30078 val_loss= 1.39060 val_acc= 0.23214 time= 0.01562
Epoch: 0006 train_loss= 1.38505 train_acc= 0.30078 val_loss= 1.39150 val_acc= 0.23214 time= 0.01563
Epoch: 0007 train_loss= 1.38452 train_acc= 0.30078 val_loss= 1.39256 val_acc= 0.23214 time= 0.01563
Epoch: 0008 train_loss= 1.38415 train_acc= 0.30078 val_loss= 1.39376 val_acc= 0.23214 time= 0.01563
Epoch: 0009 train_loss= 1.38408 train_acc= 0.30078 val_loss= 1.39470 val_acc= 0.23214 time= 0.01562
Epoch: 0010 train_loss= 1.38396 train_acc= 0.30078 val_loss= 1.39548 val_acc= 0.23214 time= 0.01563
Epoch: 0011 train_loss= 1.38373 train_acc= 0.30078 val_loss= 1.39614 val_acc= 0.23214 time= 0.01563
Epoch: 0012 train_loss= 1.38362 train_acc= 0.30078 val_loss= 1.39658 val_acc= 0.23214 time= 0.01563
Early stopping...
Optimization Finished!
Test set results: cost= 1.38992 accuracy= 0.28319 time= 0.00000 
