Epoch: 0001 train_loss= 2.05395 train_acc= 0.13208 val_loss= 2.09652 val_acc= 0.10345 time= 0.09377
Epoch: 0002 train_loss= 2.04434 train_acc= 0.18239 val_loss= 2.09924 val_acc= 0.13793 time= 0.01562
Epoch: 0003 train_loss= 2.05385 train_acc= 0.19497 val_loss= 2.10278 val_acc= 0.13793 time= 0.01563
Epoch: 0004 train_loss= 2.04558 train_acc= 0.20755 val_loss= 2.10662 val_acc= 0.13793 time= 0.00000
Epoch: 0005 train_loss= 2.02569 train_acc= 0.19497 val_loss= 2.11103 val_acc= 0.10345 time= 0.01563
Epoch: 0006 train_loss= 2.02329 train_acc= 0.21384 val_loss= 2.11641 val_acc= 0.10345 time= 0.00000
Epoch: 0007 train_loss= 2.02251 train_acc= 0.19497 val_loss= 2.12321 val_acc= 0.10345 time= 0.01563
Epoch: 0008 train_loss= 2.03089 train_acc= 0.22642 val_loss= 2.13128 val_acc= 0.10345 time= 0.01563
Epoch: 0009 train_loss= 2.01234 train_acc= 0.20126 val_loss= 2.14026 val_acc= 0.10345 time= 0.00000
Epoch: 0010 train_loss= 2.01561 train_acc= 0.20126 val_loss= 2.14982 val_acc= 0.10345 time= 0.01563
Epoch: 0011 train_loss= 2.00216 train_acc= 0.20126 val_loss= 2.16016 val_acc= 0.10345 time= 0.00000
Epoch: 0012 train_loss= 2.00441 train_acc= 0.20126 val_loss= 2.17105 val_acc= 0.10345 time= 0.01563
Early stopping...
Optimization Finished!
Test set results: cost= 2.14091 accuracy= 0.13559 time= 0.00000 
