Epoch: 0001 train_loss= 2.11399 train_acc= 0.09704 val_loss= 2.11939 val_acc= 0.03448 time= 0.81464
Epoch: 0002 train_loss= 2.11250 train_acc= 0.09704 val_loss= 2.11405 val_acc= 0.03448 time= 0.00000
Epoch: 0003 train_loss= 2.10335 train_acc= 0.09704 val_loss= 2.10924 val_acc= 0.03448 time= 0.01563
Epoch: 0004 train_loss= 2.09823 train_acc= 0.09973 val_loss= 2.10513 val_acc= 0.03448 time= 0.00000
Epoch: 0005 train_loss= 2.09351 train_acc= 0.09704 val_loss= 2.10165 val_acc= 0.03448 time= 0.00000
Epoch: 0006 train_loss= 2.09025 train_acc= 0.09973 val_loss= 2.09858 val_acc= 0.03448 time= 0.01563
Epoch: 0007 train_loss= 2.08633 train_acc= 0.09704 val_loss= 2.09587 val_acc= 0.03448 time= 0.00000
Epoch: 0008 train_loss= 2.08313 train_acc= 0.11590 val_loss= 2.09352 val_acc= 0.03448 time= 0.00000
Epoch: 0009 train_loss= 2.08069 train_acc= 0.16173 val_loss= 2.09148 val_acc= 0.03448 time= 0.01563
Epoch: 0010 train_loss= 2.07807 train_acc= 0.16442 val_loss= 2.08970 val_acc= 0.03448 time= 0.00000
Epoch: 0011 train_loss= 2.07520 train_acc= 0.16173 val_loss= 2.08799 val_acc= 0.03448 time= 0.00000
Epoch: 0012 train_loss= 2.07261 train_acc= 0.16173 val_loss= 2.08618 val_acc= 0.03448 time= 0.01563
Epoch: 0013 train_loss= 2.06947 train_acc= 0.16712 val_loss= 2.08433 val_acc= 0.03448 time= 0.00000
Epoch: 0014 train_loss= 2.06828 train_acc= 0.16442 val_loss= 2.08251 val_acc= 0.03448 time= 0.01563
Epoch: 0015 train_loss= 2.06553 train_acc= 0.16442 val_loss= 2.08167 val_acc= 0.03448 time= 0.00000
Epoch: 0016 train_loss= 2.06291 train_acc= 0.16442 val_loss= 2.08134 val_acc= 0.03448 time= 0.00000
Epoch: 0017 train_loss= 2.06238 train_acc= 0.16442 val_loss= 2.08124 val_acc= 0.03448 time= 0.01563
Epoch: 0018 train_loss= 2.05906 train_acc= 0.16173 val_loss= 2.08151 val_acc= 0.03448 time= 0.00000
Epoch: 0019 train_loss= 2.05486 train_acc= 0.16442 val_loss= 2.08216 val_acc= 0.03448 time= 0.00000
Epoch: 0020 train_loss= 2.05572 train_acc= 0.16712 val_loss= 2.08315 val_acc= 0.03448 time= 0.01563
Epoch: 0021 train_loss= 2.05337 train_acc= 0.16442 val_loss= 2.08424 val_acc= 0.03448 time= 0.00000
Early stopping...
Optimization Finished!
Test set results: cost= 2.10999 accuracy= 0.06780 time= 0.00000 
