Epoch: 0001 train_loss= 1.39426 train_acc= 0.22626 val_loss= 1.39164 val_acc= 0.21429 time= 0.75063
Epoch: 0002 train_loss= 1.39147 train_acc= 0.26676 val_loss= 1.38992 val_acc= 0.19643 time= 0.01563
Epoch: 0003 train_loss= 1.38939 train_acc= 0.26257 val_loss= 1.38885 val_acc= 0.19643 time= 0.01563
Epoch: 0004 train_loss= 1.38787 train_acc= 0.26257 val_loss= 1.38825 val_acc= 0.19643 time= 0.01562
Epoch: 0005 train_loss= 1.38677 train_acc= 0.26117 val_loss= 1.38809 val_acc= 0.19643 time= 0.00000
Epoch: 0006 train_loss= 1.38609 train_acc= 0.26536 val_loss= 1.38849 val_acc= 0.19643 time= 0.01563
Epoch: 0007 train_loss= 1.38581 train_acc= 0.26117 val_loss= 1.38886 val_acc= 0.19643 time= 0.01562
Epoch: 0008 train_loss= 1.38531 train_acc= 0.25838 val_loss= 1.38907 val_acc= 0.19643 time= 0.01563
Epoch: 0009 train_loss= 1.38504 train_acc= 0.27654 val_loss= 1.38945 val_acc= 0.19643 time= 0.01563
Epoch: 0010 train_loss= 1.38490 train_acc= 0.29330 val_loss= 1.38994 val_acc= 0.17857 time= 0.00000
Epoch: 0011 train_loss= 1.38496 train_acc= 0.29888 val_loss= 1.39042 val_acc= 0.25000 time= 0.01563
Epoch: 0012 train_loss= 1.38452 train_acc= 0.30168 val_loss= 1.39078 val_acc= 0.35714 time= 0.01563
Early stopping...
Optimization Finished!
Test set results: cost= 1.38329 accuracy= 0.31858 time= 0.00000 
