Epoch: 0001 train_loss= 2.12442 train_acc= 0.12938 val_loss= 2.08832 val_acc= 0.10345 time= 0.96882
Epoch: 0002 train_loss= 2.09073 train_acc= 0.13208 val_loss= 2.09020 val_acc= 0.17241 time= 0.01563
Epoch: 0003 train_loss= 2.08904 train_acc= 0.14286 val_loss= 2.09407 val_acc= 0.13793 time= 0.01563
Epoch: 0004 train_loss= 2.07283 train_acc= 0.15903 val_loss= 2.09862 val_acc= 0.10345 time= 0.01563
Epoch: 0005 train_loss= 2.05989 train_acc= 0.15903 val_loss= 2.10590 val_acc= 0.10345 time= 0.01563
Epoch: 0006 train_loss= 2.05248 train_acc= 0.18598 val_loss= 2.11210 val_acc= 0.10345 time= 0.01563
Epoch: 0007 train_loss= 2.05267 train_acc= 0.17251 val_loss= 2.11778 val_acc= 0.10345 time= 0.01563
Epoch: 0008 train_loss= 2.05824 train_acc= 0.15633 val_loss= 2.12237 val_acc= 0.10345 time= 0.01563
Epoch: 0009 train_loss= 2.05348 train_acc= 0.17251 val_loss= 2.12419 val_acc= 0.10345 time= 0.01563
Epoch: 0010 train_loss= 2.03595 train_acc= 0.17790 val_loss= 2.12527 val_acc= 0.10345 time= 0.01563
Epoch: 0011 train_loss= 2.03695 train_acc= 0.20216 val_loss= 2.12245 val_acc= 0.10345 time= 0.01562
Epoch: 0012 train_loss= 2.03684 train_acc= 0.18598 val_loss= 2.11789 val_acc= 0.10345 time= 0.01563
Early stopping...
Optimization Finished!
Test set results: cost= 2.12382 accuracy= 0.11864 time= 0.00000 
