Epoch: 0001 train_loss= 2.08744 train_acc= 0.11590 val_loss= 2.08401 val_acc= 0.20690 time= 0.78193
Epoch: 0002 train_loss= 2.08495 train_acc= 0.14555 val_loss= 2.07999 val_acc= 0.20690 time= 0.01562
Epoch: 0003 train_loss= 2.08258 train_acc= 0.14555 val_loss= 2.07585 val_acc= 0.20690 time= 0.00000
Epoch: 0004 train_loss= 2.08088 train_acc= 0.11860 val_loss= 2.07181 val_acc= 0.20690 time= 0.01563
Epoch: 0005 train_loss= 2.07880 train_acc= 0.14555 val_loss= 2.06783 val_acc= 0.13793 time= 0.00000
Epoch: 0006 train_loss= 2.07713 train_acc= 0.15094 val_loss= 2.06403 val_acc= 0.27586 time= 0.01563
Epoch: 0007 train_loss= 2.07565 train_acc= 0.14016 val_loss= 2.06058 val_acc= 0.24138 time= 0.00000
Epoch: 0008 train_loss= 2.07453 train_acc= 0.11860 val_loss= 2.05733 val_acc= 0.27586 time= 0.01563
Epoch: 0009 train_loss= 2.07350 train_acc= 0.14286 val_loss= 2.05412 val_acc= 0.17241 time= 0.01563
Epoch: 0010 train_loss= 2.07285 train_acc= 0.12399 val_loss= 2.05115 val_acc= 0.17241 time= 0.00000
Epoch: 0011 train_loss= 2.07203 train_acc= 0.14825 val_loss= 2.04844 val_acc= 0.31034 time= 0.00000
Epoch: 0012 train_loss= 2.07033 train_acc= 0.15903 val_loss= 2.04618 val_acc= 0.31034 time= 0.01563
Epoch: 0013 train_loss= 2.07017 train_acc= 0.16173 val_loss= 2.04426 val_acc= 0.24138 time= 0.01563
Epoch: 0014 train_loss= 2.06900 train_acc= 0.14286 val_loss= 2.04260 val_acc= 0.10345 time= 0.00000
Epoch: 0015 train_loss= 2.06874 train_acc= 0.15633 val_loss= 2.04143 val_acc= 0.10345 time= 0.01563
Epoch: 0016 train_loss= 2.06816 train_acc= 0.17251 val_loss= 2.04085 val_acc= 0.10345 time= 0.00000
Epoch: 0017 train_loss= 2.06842 train_acc= 0.14286 val_loss= 2.04071 val_acc= 0.10345 time= 0.01563
Epoch: 0018 train_loss= 2.06534 train_acc= 0.17520 val_loss= 2.04102 val_acc= 0.10345 time= 0.00000
Epoch: 0019 train_loss= 2.06652 train_acc= 0.15633 val_loss= 2.04165 val_acc= 0.10345 time= 0.01563
Epoch: 0020 train_loss= 2.06508 train_acc= 0.19407 val_loss= 2.04242 val_acc= 0.10345 time= 0.00000
Epoch: 0021 train_loss= 2.06495 train_acc= 0.16442 val_loss= 2.04335 val_acc= 0.10345 time= 0.01562
Early stopping...
Optimization Finished!
Test set results: cost= 2.07082 accuracy= 0.22034 time= 0.00000 
