Epoch: 0001 train_loss= 1.41049 train_acc= 0.20810 val_loss= 1.42240 val_acc= 0.16071 time= 0.76568
Epoch: 0002 train_loss= 1.40465 train_acc= 0.20670 val_loss= 1.41216 val_acc= 0.17857 time= 0.01563
Epoch: 0003 train_loss= 1.40010 train_acc= 0.21648 val_loss= 1.40201 val_acc= 0.17857 time= 0.00000
Epoch: 0004 train_loss= 1.39551 train_acc= 0.21788 val_loss= 1.39206 val_acc= 0.12500 time= 0.01563
Epoch: 0005 train_loss= 1.39099 train_acc= 0.25559 val_loss= 1.38238 val_acc= 0.44643 time= 0.00000
Epoch: 0006 train_loss= 1.38731 train_acc= 0.26257 val_loss= 1.37311 val_acc= 0.44643 time= 0.01563
Epoch: 0007 train_loss= 1.38412 train_acc= 0.31006 val_loss= 1.36430 val_acc= 0.44643 time= 0.00000
Epoch: 0008 train_loss= 1.38242 train_acc= 0.31285 val_loss= 1.35598 val_acc= 0.42857 time= 0.01563
Epoch: 0009 train_loss= 1.38226 train_acc= 0.30866 val_loss= 1.34832 val_acc= 0.42857 time= 0.00000
Epoch: 0010 train_loss= 1.38084 train_acc= 0.30866 val_loss= 1.34139 val_acc= 0.42857 time= 0.00000
Epoch: 0011 train_loss= 1.37866 train_acc= 0.30726 val_loss= 1.33525 val_acc= 0.42857 time= 0.01562
Epoch: 0012 train_loss= 1.38038 train_acc= 0.30726 val_loss= 1.33004 val_acc= 0.42857 time= 0.00000
Epoch: 0013 train_loss= 1.37788 train_acc= 0.30726 val_loss= 1.32586 val_acc= 0.42857 time= 0.01563
Epoch: 0014 train_loss= 1.37898 train_acc= 0.30726 val_loss= 1.32285 val_acc= 0.42857 time= 0.00000
Epoch: 0015 train_loss= 1.38068 train_acc= 0.30726 val_loss= 1.32103 val_acc= 0.42857 time= 0.01562
Epoch: 0016 train_loss= 1.38042 train_acc= 0.30726 val_loss= 1.32023 val_acc= 0.42857 time= 0.00000
Epoch: 0017 train_loss= 1.38054 train_acc= 0.30726 val_loss= 1.32041 val_acc= 0.42857 time= 0.00000
Epoch: 0018 train_loss= 1.37863 train_acc= 0.30726 val_loss= 1.32113 val_acc= 0.42857 time= 0.01563
Epoch: 0019 train_loss= 1.37909 train_acc= 0.30726 val_loss= 1.32235 val_acc= 0.42857 time= 0.00000
Epoch: 0020 train_loss= 1.38040 train_acc= 0.30726 val_loss= 1.32410 val_acc= 0.42857 time= 0.01563
Epoch: 0021 train_loss= 1.37958 train_acc= 0.30726 val_loss= 1.32630 val_acc= 0.42857 time= 0.01563
Early stopping...
Optimization Finished!
Test set results: cost= 1.38612 accuracy= 0.31858 time= 0.00000 
