Epoch: 0001 train_loss= 2.08513 train_acc= 0.13208 val_loss= 2.07851 val_acc= 0.17241 time= 0.09376
Epoch: 0002 train_loss= 2.08230 train_acc= 0.18239 val_loss= 2.07330 val_acc= 0.17241 time= 0.00000
Epoch: 0003 train_loss= 2.07959 train_acc= 0.18239 val_loss= 2.06775 val_acc= 0.17241 time= 0.01562
Epoch: 0004 train_loss= 2.07697 train_acc= 0.18239 val_loss= 2.06218 val_acc= 0.17241 time= 0.00000
Epoch: 0005 train_loss= 2.07402 train_acc= 0.20126 val_loss= 2.05683 val_acc= 0.17241 time= 0.01562
Epoch: 0006 train_loss= 2.07101 train_acc= 0.16981 val_loss= 2.05150 val_acc= 0.17241 time= 0.00000
Epoch: 0007 train_loss= 2.06937 train_acc= 0.14465 val_loss= 2.04633 val_acc= 0.17241 time= 0.01563
Epoch: 0008 train_loss= 2.06785 train_acc= 0.14465 val_loss= 2.04135 val_acc= 0.17241 time= 0.00000
Epoch: 0009 train_loss= 2.06479 train_acc= 0.16352 val_loss= 2.03646 val_acc= 0.17241 time= 0.01563
Epoch: 0010 train_loss= 2.06349 train_acc= 0.15723 val_loss= 2.03191 val_acc= 0.17241 time= 0.01563
Epoch: 0011 train_loss= 2.06235 train_acc= 0.20126 val_loss= 2.02788 val_acc= 0.17241 time= 0.00000
Epoch: 0012 train_loss= 2.06285 train_acc= 0.16981 val_loss= 2.02477 val_acc= 0.17241 time= 0.02090
Epoch: 0013 train_loss= 2.06305 train_acc= 0.13208 val_loss= 2.02264 val_acc= 0.17241 time= 0.01050
Epoch: 0014 train_loss= 2.06148 train_acc= 0.16981 val_loss= 2.02113 val_acc= 0.17241 time= 0.00000
Epoch: 0015 train_loss= 2.06071 train_acc= 0.15723 val_loss= 2.02033 val_acc= 0.17241 time= 0.01563
Epoch: 0016 train_loss= 2.06186 train_acc= 0.22013 val_loss= 2.01994 val_acc= 0.17241 time= 0.00000
Epoch: 0017 train_loss= 2.06258 train_acc= 0.16981 val_loss= 2.01967 val_acc= 0.17241 time= 0.01563
Epoch: 0018 train_loss= 2.06316 train_acc= 0.16981 val_loss= 2.01985 val_acc= 0.17241 time= 0.00000
Epoch: 0019 train_loss= 2.06184 train_acc= 0.19497 val_loss= 2.02025 val_acc= 0.17241 time= 0.01563
Epoch: 0020 train_loss= 2.06401 train_acc= 0.13208 val_loss= 2.02118 val_acc= 0.17241 time= 0.00000
Epoch: 0021 train_loss= 2.06211 train_acc= 0.17610 val_loss= 2.02207 val_acc= 0.17241 time= 0.01563
Early stopping...
Optimization Finished!
Test set results: cost= 2.04641 accuracy= 0.11864 time= 0.00000 
