Epoch: 0001 train_loss= 1.42963 train_acc= 0.21927 val_loss= 1.34881 val_acc= 0.42857 time= 0.70328
Epoch: 0002 train_loss= 1.41126 train_acc= 0.24302 val_loss= 1.34490 val_acc= 0.44643 time= 0.01563
Epoch: 0003 train_loss= 1.40498 train_acc= 0.27095 val_loss= 1.34481 val_acc= 0.46429 time= 0.01562
Epoch: 0004 train_loss= 1.40300 train_acc= 0.28771 val_loss= 1.34698 val_acc= 0.48214 time= 0.01563
Epoch: 0005 train_loss= 1.39479 train_acc= 0.27654 val_loss= 1.35061 val_acc= 0.48214 time= 0.01563
Epoch: 0006 train_loss= 1.39380 train_acc= 0.27933 val_loss= 1.35426 val_acc= 0.48214 time= 0.03125
Epoch: 0007 train_loss= 1.39542 train_acc= 0.29050 val_loss= 1.35728 val_acc= 0.48214 time= 0.00000
Epoch: 0008 train_loss= 1.39737 train_acc= 0.27235 val_loss= 1.35985 val_acc= 0.48214 time= 0.01563
Epoch: 0009 train_loss= 1.38710 train_acc= 0.28212 val_loss= 1.36243 val_acc= 0.48214 time= 0.01563
Epoch: 0010 train_loss= 1.39222 train_acc= 0.28352 val_loss= 1.36545 val_acc= 0.44643 time= 0.01563
Epoch: 0011 train_loss= 1.38707 train_acc= 0.27793 val_loss= 1.36805 val_acc= 0.46429 time= 0.01563
Epoch: 0012 train_loss= 1.38539 train_acc= 0.27933 val_loss= 1.37020 val_acc= 0.46429 time= 0.01563
Early stopping...
Optimization Finished!
Test set results: cost= 1.38756 accuracy= 0.26549 time= 0.01563 
