Epoch: 0001 train_loss= 2.06558 train_acc= 0.23779 val_loss= 1.76357 val_acc= 0.37500 time= 0.33368
Epoch: 0002 train_loss= 2.56961 train_acc= 0.19544 val_loss= 1.48906 val_acc= 0.41071 time= 0.02400
Epoch: 0003 train_loss= 1.91687 train_acc= 0.26384 val_loss= 1.37122 val_acc= 0.41071 time= 0.02201
Epoch: 0004 train_loss= 2.27621 train_acc= 0.25081 val_loss= 1.36543 val_acc= 0.35714 time= 0.02501
Epoch: 0005 train_loss= 2.08840 train_acc= 0.28664 val_loss= 1.35736 val_acc= 0.35714 time= 0.02200
Epoch: 0006 train_loss= 1.67745 train_acc= 0.28339 val_loss= 1.35349 val_acc= 0.30357 time= 0.02200
Epoch: 0007 train_loss= 1.41279 train_acc= 0.26059 val_loss= 1.35824 val_acc= 0.32143 time= 0.02201
Epoch: 0008 train_loss= 1.40062 train_acc= 0.29316 val_loss= 1.37122 val_acc= 0.30357 time= 0.02301
Epoch: 0009 train_loss= 1.57209 train_acc= 0.27036 val_loss= 1.38673 val_acc= 0.32143 time= 0.02301
Epoch: 0010 train_loss= 1.42161 train_acc= 0.25407 val_loss= 1.38778 val_acc= 0.30357 time= 0.02300
Epoch: 0011 train_loss= 1.52608 train_acc= 0.23127 val_loss= 1.38888 val_acc= 0.28571 time= 0.02697
Epoch: 0012 train_loss= 1.39378 train_acc= 0.30293 val_loss= 1.39002 val_acc= 0.23214 time= 0.02301
Early stopping...
Optimization Finished!
Test set results: cost= 1.38726 accuracy= 0.30088 time= 0.01000 
