Epoch: 0001 train_loss= 1.39226 train_acc= 0.27539 val_loss= 1.38864 val_acc= 0.32143 time= 0.18751
Epoch: 0002 train_loss= 1.38713 train_acc= 0.28906 val_loss= 1.38315 val_acc= 0.33929 time= 0.01563
Epoch: 0003 train_loss= 1.38509 train_acc= 0.30078 val_loss= 1.37943 val_acc= 0.33929 time= 0.01563
Epoch: 0004 train_loss= 1.38923 train_acc= 0.30859 val_loss= 1.37821 val_acc= 0.33929 time= 0.01563
Epoch: 0005 train_loss= 1.38069 train_acc= 0.31836 val_loss= 1.37815 val_acc= 0.33929 time= 0.01562
Epoch: 0006 train_loss= 1.38639 train_acc= 0.31055 val_loss= 1.37872 val_acc= 0.33929 time= 0.01563
Epoch: 0007 train_loss= 1.38597 train_acc= 0.30078 val_loss= 1.37980 val_acc= 0.33929 time= 0.01563
Epoch: 0008 train_loss= 1.38594 train_acc= 0.31055 val_loss= 1.38129 val_acc= 0.33929 time= 0.01563
Epoch: 0009 train_loss= 1.39055 train_acc= 0.30859 val_loss= 1.38283 val_acc= 0.32143 time= 0.01563
Epoch: 0010 train_loss= 1.38106 train_acc= 0.31250 val_loss= 1.38450 val_acc= 0.32143 time= 0.01563
Epoch: 0011 train_loss= 1.37818 train_acc= 0.32617 val_loss= 1.38591 val_acc= 0.32143 time= 0.01563
Epoch: 0012 train_loss= 1.38392 train_acc= 0.30273 val_loss= 1.38801 val_acc= 0.33929 time= 0.01563
Early stopping...
Optimization Finished!
Test set results: cost= 1.38350 accuracy= 0.27434 time= 0.01563 
