Epoch: 0001 train_loss= 2.08880 train_acc= 0.06918 val_loss= 2.07713 val_acc= 0.24138 time= 0.21904
Epoch: 0002 train_loss= 2.08791 train_acc= 0.05031 val_loss= 2.07762 val_acc= 0.24138 time= 0.00000
Epoch: 0003 train_loss= 2.08445 train_acc= 0.07547 val_loss= 2.07731 val_acc= 0.10345 time= 0.00000
Epoch: 0004 train_loss= 2.08271 train_acc= 0.13208 val_loss= 2.07656 val_acc= 0.06897 time= 0.01562
Epoch: 0005 train_loss= 2.08209 train_acc= 0.15723 val_loss= 2.07545 val_acc= 0.06897 time= 0.00000
Epoch: 0006 train_loss= 2.08040 train_acc= 0.15094 val_loss= 2.07422 val_acc= 0.06897 time= 0.00000
Epoch: 0007 train_loss= 2.07722 train_acc= 0.16352 val_loss= 2.07289 val_acc= 0.06897 time= 0.00000
Epoch: 0008 train_loss= 2.07505 train_acc= 0.23270 val_loss= 2.07151 val_acc= 0.13793 time= 0.01563
Epoch: 0009 train_loss= 2.07338 train_acc= 0.14465 val_loss= 2.07012 val_acc= 0.20690 time= 0.00000
Epoch: 0010 train_loss= 2.07222 train_acc= 0.19497 val_loss= 2.06867 val_acc= 0.20690 time= 0.00000
Epoch: 0011 train_loss= 2.06891 train_acc= 0.18868 val_loss= 2.06723 val_acc= 0.20690 time= 0.01563
Epoch: 0012 train_loss= 2.06587 train_acc= 0.18868 val_loss= 2.06589 val_acc= 0.20690 time= 0.00000
Epoch: 0013 train_loss= 2.06431 train_acc= 0.21384 val_loss= 2.06468 val_acc= 0.20690 time= 0.00000
Epoch: 0014 train_loss= 2.05997 train_acc= 0.18239 val_loss= 2.06361 val_acc= 0.20690 time= 0.01563
Epoch: 0015 train_loss= 2.05926 train_acc= 0.20755 val_loss= 2.06264 val_acc= 0.20690 time= 0.00000
Epoch: 0016 train_loss= 2.05681 train_acc= 0.20126 val_loss= 2.06187 val_acc= 0.20690 time= 0.00000
Epoch: 0017 train_loss= 2.05043 train_acc= 0.19497 val_loss= 2.06125 val_acc= 0.20690 time= 0.01563
Epoch: 0018 train_loss= 2.04836 train_acc= 0.20126 val_loss= 2.06102 val_acc= 0.20690 time= 0.00000
Epoch: 0019 train_loss= 2.04700 train_acc= 0.18868 val_loss= 2.06127 val_acc= 0.20690 time= 0.00000
Epoch: 0020 train_loss= 2.04209 train_acc= 0.19497 val_loss= 2.06206 val_acc= 0.20690 time= 0.01563
Epoch: 0021 train_loss= 2.03867 train_acc= 0.20755 val_loss= 2.06357 val_acc= 0.20690 time= 0.00000
Early stopping...
Optimization Finished!
Test set results: cost= 2.11204 accuracy= 0.16949 time= 0.00000 
