Epoch: 0001 train_loss= 2.30059 train_acc= 0.48727 val_loss= 0.86186 val_acc= 0.38710 time= 0.41709
Epoch: 0002 train_loss= 0.95797 train_acc= 0.50182 val_loss= 0.91120 val_acc= 0.48387 time= 0.01300
Epoch: 0003 train_loss= 1.15644 train_acc= 0.51636 val_loss= 0.97835 val_acc= 0.51613 time= 0.01200
Epoch: 0004 train_loss= 2.11173 train_acc= 0.51273 val_loss= 0.93894 val_acc= 0.48387 time= 0.01300
Epoch: 0005 train_loss= 1.03059 train_acc= 0.49636 val_loss= 0.87580 val_acc= 0.46774 time= 0.01400
Epoch: 0006 train_loss= 0.98333 train_acc= 0.51091 val_loss= 0.83590 val_acc= 0.46774 time= 0.01100
Epoch: 0007 train_loss= 1.29094 train_acc= 0.52545 val_loss= 0.81769 val_acc= 0.48387 time= 0.01200
Epoch: 0008 train_loss= 1.21782 train_acc= 0.51273 val_loss= 0.82419 val_acc= 0.46774 time= 0.01200
Epoch: 0009 train_loss= 0.93805 train_acc= 0.50182 val_loss= 0.83353 val_acc= 0.46774 time= 0.01300
Epoch: 0010 train_loss= 2.06564 train_acc= 0.48545 val_loss= 0.80396 val_acc= 0.50000 time= 0.01300
Epoch: 0011 train_loss= 1.35507 train_acc= 0.49091 val_loss= 0.77394 val_acc= 0.48387 time= 0.01400
Epoch: 0012 train_loss= 1.17174 train_acc= 0.53091 val_loss= 0.76232 val_acc= 0.50000 time= 0.01300
Epoch: 0013 train_loss= 1.13492 train_acc= 0.51273 val_loss= 0.76809 val_acc= 0.51613 time= 0.01200
Epoch: 0014 train_loss= 1.22860 train_acc= 0.50182 val_loss= 0.76625 val_acc= 0.50000 time= 0.01300
Epoch: 0015 train_loss= 1.44302 train_acc= 0.52182 val_loss= 0.75366 val_acc= 0.50000 time= 0.01300
Epoch: 0016 train_loss= 1.12395 train_acc= 0.51455 val_loss= 0.74319 val_acc= 0.51613 time= 0.01300
Epoch: 0017 train_loss= 1.23470 train_acc= 0.51091 val_loss= 0.74243 val_acc= 0.51613 time= 0.01300
Epoch: 0018 train_loss= 1.01384 train_acc= 0.47636 val_loss= 0.74491 val_acc= 0.53226 time= 0.01400
Epoch: 0019 train_loss= 1.08529 train_acc= 0.49273 val_loss= 0.74583 val_acc= 0.50000 time= 0.01200
Epoch: 0020 train_loss= 0.98970 train_acc= 0.49636 val_loss= 0.74913 val_acc= 0.46774 time= 0.01100
Epoch: 0021 train_loss= 1.04936 train_acc= 0.52000 val_loss= 0.75664 val_acc= 0.45161 time= 0.01300
Early stopping...
Optimization Finished!
Test set results: cost= 0.72915 accuracy= 0.41935 time= 0.00500 
