Epoch: 0001 train_loss= 1.41097 train_acc= 0.24414 val_loss= 1.40006 val_acc= 0.26786 time= 0.20314
Epoch: 0002 train_loss= 1.39481 train_acc= 0.23438 val_loss= 1.39510 val_acc= 0.25000 time= 0.01563
Epoch: 0003 train_loss= 1.38404 train_acc= 0.29688 val_loss= 1.39218 val_acc= 0.19643 time= 0.01563
Epoch: 0004 train_loss= 1.38459 train_acc= 0.28711 val_loss= 1.39061 val_acc= 0.26786 time= 0.03125
Epoch: 0005 train_loss= 1.38201 train_acc= 0.28320 val_loss= 1.39042 val_acc= 0.28571 time= 0.01563
Epoch: 0006 train_loss= 1.39093 train_acc= 0.27344 val_loss= 1.39138 val_acc= 0.26786 time= 0.01562
Epoch: 0007 train_loss= 1.38739 train_acc= 0.30078 val_loss= 1.39188 val_acc= 0.26786 time= 0.01563
Epoch: 0008 train_loss= 1.38341 train_acc= 0.29883 val_loss= 1.39225 val_acc= 0.26786 time= 0.01563
Epoch: 0009 train_loss= 1.38392 train_acc= 0.29492 val_loss= 1.39237 val_acc= 0.26786 time= 0.01563
Epoch: 0010 train_loss= 1.38347 train_acc= 0.30273 val_loss= 1.39209 val_acc= 0.26786 time= 0.01563
Epoch: 0011 train_loss= 1.38540 train_acc= 0.30469 val_loss= 1.39144 val_acc= 0.26786 time= 0.03125
Epoch: 0012 train_loss= 1.38077 train_acc= 0.30273 val_loss= 1.39049 val_acc= 0.26786 time= 0.01563
Epoch: 0013 train_loss= 1.38575 train_acc= 0.29688 val_loss= 1.38950 val_acc= 0.26786 time= 0.01563
Epoch: 0014 train_loss= 1.38132 train_acc= 0.29492 val_loss= 1.38879 val_acc= 0.26786 time= 0.01563
Epoch: 0015 train_loss= 1.38078 train_acc= 0.29297 val_loss= 1.38837 val_acc= 0.26786 time= 0.01563
Epoch: 0016 train_loss= 1.38298 train_acc= 0.30078 val_loss= 1.38809 val_acc= 0.26786 time= 0.01563
Epoch: 0017 train_loss= 1.37985 train_acc= 0.29492 val_loss= 1.38799 val_acc= 0.26786 time= 0.01563
Epoch: 0018 train_loss= 1.38114 train_acc= 0.28906 val_loss= 1.38798 val_acc= 0.26786 time= 0.01563
Epoch: 0019 train_loss= 1.37556 train_acc= 0.32227 val_loss= 1.38798 val_acc= 0.26786 time= 0.01563
Epoch: 0020 train_loss= 1.38370 train_acc= 0.26367 val_loss= 1.38807 val_acc= 0.26786 time= 0.03125
Epoch: 0021 train_loss= 1.38113 train_acc= 0.28125 val_loss= 1.38831 val_acc= 0.26786 time= 0.01563
Epoch: 0022 train_loss= 1.37870 train_acc= 0.26367 val_loss= 1.38884 val_acc= 0.26786 time= 0.01563
Early stopping...
Optimization Finished!
Test set results: cost= 1.37574 accuracy= 0.29204 time= 0.00000 
