Epoch: 0001 train_loss= 1.39581 train_acc= 0.29642 val_loss= 1.39219 val_acc= 0.30357 time= 0.07813
Epoch: 0002 train_loss= 1.39898 train_acc= 0.31596 val_loss= 1.38859 val_acc= 0.30357 time= 0.01563
Epoch: 0003 train_loss= 1.37545 train_acc= 0.32573 val_loss= 1.38892 val_acc= 0.30357 time= 0.01563
Epoch: 0004 train_loss= 1.36925 train_acc= 0.34853 val_loss= 1.39239 val_acc= 0.32143 time= 0.01563
Epoch: 0005 train_loss= 1.37175 train_acc= 0.34528 val_loss= 1.39719 val_acc= 0.33929 time= 0.01563
Epoch: 0006 train_loss= 1.38375 train_acc= 0.32899 val_loss= 1.40100 val_acc= 0.32143 time= 0.01563
Epoch: 0007 train_loss= 1.35956 train_acc= 0.34528 val_loss= 1.40450 val_acc= 0.32143 time= 0.01563
Epoch: 0008 train_loss= 1.37166 train_acc= 0.34853 val_loss= 1.40620 val_acc= 0.32143 time= 0.01563
Epoch: 0009 train_loss= 1.36771 train_acc= 0.35179 val_loss= 1.40763 val_acc= 0.32143 time= 0.01563
Epoch: 0010 train_loss= 1.37419 train_acc= 0.34202 val_loss= 1.40825 val_acc= 0.32143 time= 0.01563
Epoch: 0011 train_loss= 1.37807 train_acc= 0.34528 val_loss= 1.40760 val_acc= 0.33929 time= 0.01563
Epoch: 0012 train_loss= 1.36748 train_acc= 0.34528 val_loss= 1.40640 val_acc= 0.32143 time= 0.01563
Early stopping...
Optimization Finished!
Test set results: cost= 1.39017 accuracy= 0.29204 time= 0.00000 
