Epoch: 0001 train_loss= 1.38654 train_acc= 0.30469 val_loss= 1.39216 val_acc= 0.19643 time= 0.53157
Epoch: 0002 train_loss= 1.38543 train_acc= 0.31641 val_loss= 1.39261 val_acc= 0.19643 time= 0.00000
Epoch: 0003 train_loss= 1.38516 train_acc= 0.30664 val_loss= 1.39317 val_acc= 0.19643 time= 0.01562
Epoch: 0004 train_loss= 1.38371 train_acc= 0.31055 val_loss= 1.39378 val_acc= 0.19643 time= 0.00000
Epoch: 0005 train_loss= 1.38239 train_acc= 0.31836 val_loss= 1.39451 val_acc= 0.19643 time= 0.01563
Epoch: 0006 train_loss= 1.38114 train_acc= 0.31836 val_loss= 1.39532 val_acc= 0.19643 time= 0.00000
Epoch: 0007 train_loss= 1.38148 train_acc= 0.32031 val_loss= 1.39607 val_acc= 0.19643 time= 0.00000
Epoch: 0008 train_loss= 1.38159 train_acc= 0.31836 val_loss= 1.39681 val_acc= 0.19643 time= 0.01563
Epoch: 0009 train_loss= 1.37848 train_acc= 0.31641 val_loss= 1.39760 val_acc= 0.19643 time= 0.00000
Epoch: 0010 train_loss= 1.37848 train_acc= 0.31836 val_loss= 1.39842 val_acc= 0.19643 time= 0.01563
Epoch: 0011 train_loss= 1.37625 train_acc= 0.31836 val_loss= 1.39920 val_acc= 0.19643 time= 0.00000
Epoch: 0012 train_loss= 1.37674 train_acc= 0.31836 val_loss= 1.39999 val_acc= 0.19643 time= 0.01563
Early stopping...
Optimization Finished!
Test set results: cost= 1.38145 accuracy= 0.29204 time= 0.00000 
