Epoch: 0001 train_loss= 1.39425 train_acc= 0.25195 val_loss= 1.39204 val_acc= 0.19643 time= 0.52292
Epoch: 0002 train_loss= 1.39105 train_acc= 0.30469 val_loss= 1.39086 val_acc= 0.19643 time= 0.01563
Epoch: 0003 train_loss= 1.38846 train_acc= 0.30859 val_loss= 1.39041 val_acc= 0.19643 time= 0.01563
Epoch: 0004 train_loss= 1.38633 train_acc= 0.30664 val_loss= 1.39071 val_acc= 0.19643 time= 0.01563
Epoch: 0005 train_loss= 1.38477 train_acc= 0.30859 val_loss= 1.39160 val_acc= 0.19643 time= 0.01563
Epoch: 0006 train_loss= 1.38359 train_acc= 0.30859 val_loss= 1.39264 val_acc= 0.19643 time= 0.01563
Epoch: 0007 train_loss= 1.38249 train_acc= 0.30859 val_loss= 1.39396 val_acc= 0.19643 time= 0.01563
Epoch: 0008 train_loss= 1.38239 train_acc= 0.30859 val_loss= 1.39552 val_acc= 0.19643 time= 0.01563
Epoch: 0009 train_loss= 1.38126 train_acc= 0.30859 val_loss= 1.39714 val_acc= 0.19643 time= 0.00000
Epoch: 0010 train_loss= 1.38184 train_acc= 0.30859 val_loss= 1.39890 val_acc= 0.19643 time= 0.01563
Epoch: 0011 train_loss= 1.38142 train_acc= 0.30859 val_loss= 1.40080 val_acc= 0.19643 time= 0.01563
Epoch: 0012 train_loss= 1.38115 train_acc= 0.30859 val_loss= 1.40243 val_acc= 0.19643 time= 0.01562
Early stopping...
Optimization Finished!
Test set results: cost= 1.37933 accuracy= 0.29204 time= 0.01563 
