Epoch: 0001 train_loss= 1.39230 train_acc= 0.21094 val_loss= 1.39289 val_acc= 0.30357 time= 0.39388
Epoch: 0002 train_loss= 1.39067 train_acc= 0.31641 val_loss= 1.39018 val_acc= 0.30357 time= 0.01700
Epoch: 0003 train_loss= 1.38953 train_acc= 0.30859 val_loss= 1.38943 val_acc= 0.30357 time= 0.01800
Epoch: 0004 train_loss= 1.38854 train_acc= 0.30859 val_loss= 1.38918 val_acc= 0.30357 time= 0.01700
Epoch: 0005 train_loss= 1.38789 train_acc= 0.30859 val_loss= 1.38915 val_acc= 0.30357 time= 0.01700
Epoch: 0006 train_loss= 1.38677 train_acc= 0.30859 val_loss= 1.38926 val_acc= 0.30357 time= 0.01900
Epoch: 0007 train_loss= 1.38578 train_acc= 0.30859 val_loss= 1.38950 val_acc= 0.30357 time= 0.01811
Epoch: 0008 train_loss= 1.38549 train_acc= 0.30859 val_loss= 1.38974 val_acc= 0.30357 time= 0.01628
Epoch: 0009 train_loss= 1.38509 train_acc= 0.30859 val_loss= 1.38992 val_acc= 0.30357 time= 0.01600
Epoch: 0010 train_loss= 1.38392 train_acc= 0.30859 val_loss= 1.39023 val_acc= 0.30357 time= 0.01620
Epoch: 0011 train_loss= 1.38287 train_acc= 0.30859 val_loss= 1.39057 val_acc= 0.30357 time= 0.01827
Epoch: 0012 train_loss= 1.38331 train_acc= 0.30859 val_loss= 1.39083 val_acc= 0.30357 time= 0.01600
Early stopping...
Optimization Finished!
Test set results: cost= 1.38802 accuracy= 0.31858 time= 0.00900 
