Epoch: 0001 train_loss= 1.39159 train_acc= 0.28320 val_loss= 1.38879 val_acc= 0.32143 time= 0.23816
Epoch: 0002 train_loss= 1.39015 train_acc= 0.29297 val_loss= 1.38724 val_acc= 0.32143 time= 0.01563
Epoch: 0003 train_loss= 1.38915 train_acc= 0.29297 val_loss= 1.38580 val_acc= 0.32143 time= 0.01563
Epoch: 0004 train_loss= 1.38816 train_acc= 0.29297 val_loss= 1.38438 val_acc= 0.32143 time= 0.01563
Epoch: 0005 train_loss= 1.38733 train_acc= 0.29297 val_loss= 1.38302 val_acc= 0.32143 time= 0.01563
Epoch: 0006 train_loss= 1.38646 train_acc= 0.29297 val_loss= 1.38196 val_acc= 0.32143 time= 0.01563
Epoch: 0007 train_loss= 1.38581 train_acc= 0.29297 val_loss= 1.38094 val_acc= 0.32143 time= 0.01563
Epoch: 0008 train_loss= 1.38474 train_acc= 0.29297 val_loss= 1.37988 val_acc= 0.32143 time= 0.01562
Epoch: 0009 train_loss= 1.38430 train_acc= 0.29297 val_loss= 1.37876 val_acc= 0.32143 time= 0.01563
Epoch: 0010 train_loss= 1.38318 train_acc= 0.29297 val_loss= 1.37768 val_acc= 0.32143 time= 0.01563
Epoch: 0011 train_loss= 1.38268 train_acc= 0.29297 val_loss= 1.37671 val_acc= 0.32143 time= 0.01563
Epoch: 0012 train_loss= 1.38234 train_acc= 0.29297 val_loss= 1.37583 val_acc= 0.32143 time= 0.01562
Epoch: 0013 train_loss= 1.38144 train_acc= 0.29297 val_loss= 1.37504 val_acc= 0.32143 time= 0.01563
Epoch: 0014 train_loss= 1.38095 train_acc= 0.29297 val_loss= 1.37431 val_acc= 0.32143 time= 0.01563
Epoch: 0015 train_loss= 1.38001 train_acc= 0.29297 val_loss= 1.37368 val_acc= 0.32143 time= 0.01562
Epoch: 0016 train_loss= 1.38002 train_acc= 0.29297 val_loss= 1.37314 val_acc= 0.32143 time= 0.01563
Epoch: 0017 train_loss= 1.37997 train_acc= 0.29297 val_loss= 1.37272 val_acc= 0.32143 time= 0.01563
Epoch: 0018 train_loss= 1.37962 train_acc= 0.29297 val_loss= 1.37244 val_acc= 0.32143 time= 0.01563
Epoch: 0019 train_loss= 1.37847 train_acc= 0.29297 val_loss= 1.37228 val_acc= 0.32143 time= 0.03125
Epoch: 0020 train_loss= 1.37933 train_acc= 0.29297 val_loss= 1.37227 val_acc= 0.32143 time= 0.01563
Epoch: 0021 train_loss= 1.37837 train_acc= 0.29297 val_loss= 1.37239 val_acc= 0.32143 time= 0.01563
Epoch: 0022 train_loss= 1.37800 train_acc= 0.29297 val_loss= 1.37260 val_acc= 0.32143 time= 0.01563
Epoch: 0023 train_loss= 1.37797 train_acc= 0.29297 val_loss= 1.37286 val_acc= 0.32143 time= 0.01563
Epoch: 0024 train_loss= 1.37752 train_acc= 0.29297 val_loss= 1.37322 val_acc= 0.32143 time= 0.01563
Early stopping...
Optimization Finished!
Test set results: cost= 1.35029 accuracy= 0.36283 time= 0.00000 
