Epoch: 0001 train_loss= 2.08752 train_acc= 0.09434 val_loss= 2.08646 val_acc= 0.13793 time= 0.45445
Epoch: 0002 train_loss= 2.08448 train_acc= 0.13585 val_loss= 2.08610 val_acc= 0.10345 time= 0.00900
Epoch: 0003 train_loss= 2.08189 train_acc= 0.13208 val_loss= 2.08638 val_acc= 0.10345 time= 0.00700
Epoch: 0004 train_loss= 2.07909 train_acc= 0.12830 val_loss= 2.08720 val_acc= 0.10345 time= 0.00800
Epoch: 0005 train_loss= 2.07676 train_acc= 0.14717 val_loss= 2.08855 val_acc= 0.10345 time= 0.00700
Epoch: 0006 train_loss= 2.07477 train_acc= 0.14717 val_loss= 2.09036 val_acc= 0.10345 time= 0.00800
Epoch: 0007 train_loss= 2.07227 train_acc= 0.15472 val_loss= 2.09264 val_acc= 0.10345 time= 0.00800
Epoch: 0008 train_loss= 2.07057 train_acc= 0.13962 val_loss= 2.09540 val_acc= 0.10345 time= 0.00800
Epoch: 0009 train_loss= 2.06889 train_acc= 0.15094 val_loss= 2.09855 val_acc= 0.10345 time= 0.00900
Epoch: 0010 train_loss= 2.06839 train_acc= 0.13208 val_loss= 2.10197 val_acc= 0.10345 time= 0.00900
Epoch: 0011 train_loss= 2.06567 train_acc= 0.14717 val_loss= 2.10570 val_acc= 0.10345 time= 0.00800
Epoch: 0012 train_loss= 2.06436 train_acc= 0.13962 val_loss= 2.10970 val_acc= 0.10345 time= 0.00800
Early stopping...
Optimization Finished!
Test set results: cost= 2.05715 accuracy= 0.20339 time= 0.00300 
