Epoch: 0001 train_loss= 1.67619 train_acc= 0.51429 val_loss= 0.90310 val_acc= 0.34426 time= 0.70552
Epoch: 0002 train_loss= 1.86017 train_acc= 0.48312 val_loss= 0.91760 val_acc= 0.36066 time= 0.01500
Epoch: 0003 train_loss= 1.40658 train_acc= 0.47403 val_loss= 0.89450 val_acc= 0.34426 time= 0.01622
Epoch: 0004 train_loss= 1.68017 train_acc= 0.52468 val_loss= 0.91387 val_acc= 0.34426 time= 0.01400
Epoch: 0005 train_loss= 1.35914 train_acc= 0.50260 val_loss= 0.92652 val_acc= 0.34426 time= 0.01457
Epoch: 0006 train_loss= 1.48166 train_acc= 0.50000 val_loss= 0.95708 val_acc= 0.39344 time= 0.01479
Epoch: 0007 train_loss= 1.38715 train_acc= 0.48701 val_loss= 0.96707 val_acc= 0.40984 time= 0.01619
Epoch: 0008 train_loss= 1.11984 train_acc= 0.53896 val_loss= 1.02563 val_acc= 0.39344 time= 0.01615
Epoch: 0009 train_loss= 1.29738 train_acc= 0.50260 val_loss= 1.07433 val_acc= 0.40984 time= 0.01507
Epoch: 0010 train_loss= 1.33395 train_acc= 0.50390 val_loss= 1.05626 val_acc= 0.42623 time= 0.01500
Epoch: 0011 train_loss= 1.27918 train_acc= 0.50260 val_loss= 1.02824 val_acc= 0.42623 time= 0.01773
Epoch: 0012 train_loss= 0.98284 train_acc= 0.50000 val_loss= 0.99307 val_acc= 0.42623 time= 0.01400
Early stopping...
Optimization Finished!
Test set results: cost= 0.88344 accuracy= 0.54098 time= 0.00700 
