Epoch: 0001 train_loss= 2.08759 train_acc= 0.15723 val_loss= 2.08573 val_acc= 0.06897 time= 0.14063
Epoch: 0002 train_loss= 2.08506 train_acc= 0.16981 val_loss= 2.08422 val_acc= 0.10345 time= 0.01563
Epoch: 0003 train_loss= 2.08315 train_acc= 0.17610 val_loss= 2.08305 val_acc= 0.10345 time= 0.00000
Epoch: 0004 train_loss= 2.08121 train_acc= 0.15723 val_loss= 2.08234 val_acc= 0.10345 time= 0.01563
Epoch: 0005 train_loss= 2.07950 train_acc= 0.16352 val_loss= 2.08198 val_acc= 0.10345 time= 0.00000
Epoch: 0006 train_loss= 2.07808 train_acc= 0.15723 val_loss= 2.08198 val_acc= 0.10345 time= 0.01562
Epoch: 0007 train_loss= 2.07684 train_acc= 0.15723 val_loss= 2.08240 val_acc= 0.10345 time= 0.00000
Epoch: 0008 train_loss= 2.07594 train_acc= 0.15723 val_loss= 2.08302 val_acc= 0.10345 time= 0.01563
Epoch: 0009 train_loss= 2.07510 train_acc= 0.15094 val_loss= 2.08395 val_acc= 0.10345 time= 0.00000
Epoch: 0010 train_loss= 2.07417 train_acc= 0.15723 val_loss= 2.08518 val_acc= 0.10345 time= 0.01563
Epoch: 0011 train_loss= 2.07280 train_acc= 0.16352 val_loss= 2.08677 val_acc= 0.10345 time= 0.00000
Epoch: 0012 train_loss= 2.07250 train_acc= 0.16352 val_loss= 2.08862 val_acc= 0.10345 time= 0.01563
Early stopping...
Optimization Finished!
Test set results: cost= 2.08159 accuracy= 0.05085 time= 0.00000 
