Epoch: 0001 train_loss= 1.38830 train_acc= 0.26397 val_loss= 1.38573 val_acc= 0.33929 time= 0.78130
Epoch: 0002 train_loss= 1.38620 train_acc= 0.30028 val_loss= 1.38319 val_acc= 0.33929 time= 0.01563
Epoch: 0003 train_loss= 1.38397 train_acc= 0.30726 val_loss= 1.38088 val_acc= 0.33929 time= 0.00000
Epoch: 0004 train_loss= 1.38217 train_acc= 0.30726 val_loss= 1.37880 val_acc= 0.33929 time= 0.01563
Epoch: 0005 train_loss= 1.38116 train_acc= 0.30726 val_loss= 1.37693 val_acc= 0.33929 time= 0.00000
Epoch: 0006 train_loss= 1.38059 train_acc= 0.30726 val_loss= 1.37525 val_acc= 0.33929 time= 0.00000
Epoch: 0007 train_loss= 1.38072 train_acc= 0.30726 val_loss= 1.37374 val_acc= 0.33929 time= 0.01563
Epoch: 0008 train_loss= 1.37953 train_acc= 0.30726 val_loss= 1.37239 val_acc= 0.33929 time= 0.00000
Epoch: 0009 train_loss= 1.37697 train_acc= 0.30726 val_loss= 1.37116 val_acc= 0.33929 time= 0.01563
Epoch: 0010 train_loss= 1.37787 train_acc= 0.30726 val_loss= 1.37006 val_acc= 0.33929 time= 0.00000
Epoch: 0011 train_loss= 1.37802 train_acc= 0.30726 val_loss= 1.36909 val_acc= 0.33929 time= 0.01563
Epoch: 0012 train_loss= 1.37864 train_acc= 0.30726 val_loss= 1.36824 val_acc= 0.33929 time= 0.00000
Epoch: 0013 train_loss= 1.37749 train_acc= 0.30726 val_loss= 1.36750 val_acc= 0.33929 time= 0.01563
Epoch: 0014 train_loss= 1.37647 train_acc= 0.30726 val_loss= 1.36691 val_acc= 0.33929 time= 0.00000
Epoch: 0015 train_loss= 1.37689 train_acc= 0.30726 val_loss= 1.36651 val_acc= 0.33929 time= 0.01563
Epoch: 0016 train_loss= 1.37638 train_acc= 0.30726 val_loss= 1.36627 val_acc= 0.33929 time= 0.00000
Epoch: 0017 train_loss= 1.37624 train_acc= 0.30726 val_loss= 1.36608 val_acc= 0.33929 time= 0.01563
Epoch: 0018 train_loss= 1.37719 train_acc= 0.30866 val_loss= 1.36616 val_acc= 0.33929 time= 0.00000
Epoch: 0019 train_loss= 1.37694 train_acc= 0.30726 val_loss= 1.36631 val_acc= 0.33929 time= 0.00000
Epoch: 0020 train_loss= 1.37671 train_acc= 0.30866 val_loss= 1.36656 val_acc= 0.33929 time= 0.01563
Epoch: 0021 train_loss= 1.37541 train_acc= 0.30726 val_loss= 1.36690 val_acc= 0.33929 time= 0.00000
Epoch: 0022 train_loss= 1.37624 train_acc= 0.30866 val_loss= 1.36738 val_acc= 0.33929 time= 0.01563
Early stopping...
Optimization Finished!
Test set results: cost= 1.39237 accuracy= 0.28319 time= 0.00000 
