Epoch: 0001 train_loss= 0.70094 train_acc= 0.54545 val_loss= 0.69844 val_acc= 0.50000 time= 0.15626
Epoch: 0002 train_loss= 0.69783 train_acc= 0.53939 val_loss= 0.69673 val_acc= 0.50000 time= 0.01562
Epoch: 0003 train_loss= 0.69548 train_acc= 0.54242 val_loss= 0.69580 val_acc= 0.50000 time= 0.01563
Epoch: 0004 train_loss= 0.69381 train_acc= 0.54242 val_loss= 0.69547 val_acc= 0.50000 time= 0.00000
Epoch: 0005 train_loss= 0.69266 train_acc= 0.54242 val_loss= 0.69565 val_acc= 0.50000 time= 0.01563
Epoch: 0006 train_loss= 0.69185 train_acc= 0.54242 val_loss= 0.69618 val_acc= 0.50000 time= 0.01563
Epoch: 0007 train_loss= 0.69144 train_acc= 0.54242 val_loss= 0.69687 val_acc= 0.50000 time= 0.00000
Epoch: 0008 train_loss= 0.69156 train_acc= 0.54242 val_loss= 0.69760 val_acc= 0.50000 time= 0.01563
Epoch: 0009 train_loss= 0.69122 train_acc= 0.54242 val_loss= 0.69833 val_acc= 0.50000 time= 0.01563
Epoch: 0010 train_loss= 0.69104 train_acc= 0.54242 val_loss= 0.69899 val_acc= 0.50000 time= 0.00000
Epoch: 0011 train_loss= 0.69145 train_acc= 0.54242 val_loss= 0.69947 val_acc= 0.50000 time= 0.01563
Epoch: 0012 train_loss= 0.69145 train_acc= 0.54242 val_loss= 0.69963 val_acc= 0.50000 time= 0.01563
Early stopping...
Optimization Finished!
Test set results: cost= 0.68854 accuracy= 0.55645 time= 0.00000 
