Epoch: 0001 train_loss= 1.25777 train_acc= 0.51429 val_loss= 1.31726 val_acc= 0.44262 time= 0.94896
Epoch: 0002 train_loss= 1.00124 train_acc= 0.51558 val_loss= 1.83136 val_acc= 0.42623 time= 0.01563
Epoch: 0003 train_loss= 1.30362 train_acc= 0.51558 val_loss= 1.72372 val_acc= 0.40984 time= 0.01563
Epoch: 0004 train_loss= 1.13791 train_acc= 0.51429 val_loss= 1.44673 val_acc= 0.40984 time= 0.01563
Epoch: 0005 train_loss= 0.95199 train_acc= 0.51429 val_loss= 1.10697 val_acc= 0.42623 time= 0.03125
Epoch: 0006 train_loss= 1.01871 train_acc= 0.52078 val_loss= 0.78684 val_acc= 0.42623 time= 0.01563
Epoch: 0007 train_loss= 0.84001 train_acc= 0.53117 val_loss= 0.70340 val_acc= 0.52459 time= 0.03125
Epoch: 0008 train_loss= 1.16727 train_acc= 0.51299 val_loss= 0.85196 val_acc= 0.52459 time= 0.03125
Epoch: 0009 train_loss= 0.80138 train_acc= 0.51948 val_loss= 1.07114 val_acc= 0.52459 time= 0.01563
Epoch: 0010 train_loss= 0.78730 train_acc= 0.53247 val_loss= 1.24215 val_acc= 0.52459 time= 0.01563
Epoch: 0011 train_loss= 1.11743 train_acc= 0.51818 val_loss= 1.25983 val_acc= 0.52459 time= 0.03125
Epoch: 0012 train_loss= 0.80136 train_acc= 0.51948 val_loss= 1.29926 val_acc= 0.54098 time= 0.01563
Early stopping...
Optimization Finished!
Test set results: cost= 1.24464 accuracy= 0.43443 time= 0.01563 
