Epoch: 0001 train_loss= 1.39286 train_acc= 0.27036 val_loss= 1.39523 val_acc= 0.19643 time= 0.07809
Epoch: 0002 train_loss= 1.39083 train_acc= 0.28990 val_loss= 1.39638 val_acc= 0.19643 time= 0.01563
Epoch: 0003 train_loss= 1.38922 train_acc= 0.28990 val_loss= 1.39729 val_acc= 0.19643 time= 0.01562
Epoch: 0004 train_loss= 1.38844 train_acc= 0.28990 val_loss= 1.39799 val_acc= 0.19643 time= 0.01563
Epoch: 0005 train_loss= 1.38699 train_acc= 0.28990 val_loss= 1.39875 val_acc= 0.19643 time= 0.00000
Epoch: 0006 train_loss= 1.38601 train_acc= 0.28990 val_loss= 1.39958 val_acc= 0.19643 time= 0.01563
Epoch: 0007 train_loss= 1.38579 train_acc= 0.28990 val_loss= 1.40047 val_acc= 0.19643 time= 0.01563
Epoch: 0008 train_loss= 1.38420 train_acc= 0.28990 val_loss= 1.40146 val_acc= 0.19643 time= 0.01563
Epoch: 0009 train_loss= 1.38311 train_acc= 0.28990 val_loss= 1.40253 val_acc= 0.19643 time= 0.01563
Epoch: 0010 train_loss= 1.38327 train_acc= 0.28990 val_loss= 1.40365 val_acc= 0.19643 time= 0.00000
Epoch: 0011 train_loss= 1.38223 train_acc= 0.28990 val_loss= 1.40483 val_acc= 0.19643 time= 0.01563
Epoch: 0012 train_loss= 1.38095 train_acc= 0.28990 val_loss= 1.40608 val_acc= 0.19643 time= 0.01562
Early stopping...
Optimization Finished!
Test set results: cost= 1.39228 accuracy= 0.24779 time= 0.00000 
