Epoch: 0001 train_loss= 1.39421 train_acc= 0.26758 val_loss= 1.39157 val_acc= 0.19643 time= 0.25003
Epoch: 0002 train_loss= 1.39123 train_acc= 0.27148 val_loss= 1.38879 val_acc= 0.19643 time= 0.00000
Epoch: 0003 train_loss= 1.38867 train_acc= 0.28320 val_loss= 1.38628 val_acc= 0.32143 time= 0.01562
Epoch: 0004 train_loss= 1.38667 train_acc= 0.27539 val_loss= 1.38423 val_acc= 0.30357 time= 0.01563
Epoch: 0005 train_loss= 1.38488 train_acc= 0.27734 val_loss= 1.38268 val_acc= 0.30357 time= 0.01563
Epoch: 0006 train_loss= 1.38365 train_acc= 0.27539 val_loss= 1.38159 val_acc= 0.30357 time= 0.01563
Epoch: 0007 train_loss= 1.38277 train_acc= 0.26367 val_loss= 1.38083 val_acc= 0.30357 time= 0.01563
Epoch: 0008 train_loss= 1.38214 train_acc= 0.28711 val_loss= 1.38030 val_acc= 0.30357 time= 0.01563
Epoch: 0009 train_loss= 1.38162 train_acc= 0.27734 val_loss= 1.37998 val_acc= 0.30357 time= 0.01563
Epoch: 0010 train_loss= 1.38179 train_acc= 0.28125 val_loss= 1.37975 val_acc= 0.30357 time= 0.01563
Epoch: 0011 train_loss= 1.38142 train_acc= 0.27734 val_loss= 1.37948 val_acc= 0.30357 time= 0.01563
Epoch: 0012 train_loss= 1.38132 train_acc= 0.27539 val_loss= 1.37927 val_acc= 0.30357 time= 0.01562
Epoch: 0013 train_loss= 1.38133 train_acc= 0.28125 val_loss= 1.37913 val_acc= 0.30357 time= 0.01563
Epoch: 0014 train_loss= 1.38082 train_acc= 0.28906 val_loss= 1.37910 val_acc= 0.30357 time= 0.01563
Epoch: 0015 train_loss= 1.38045 train_acc= 0.27930 val_loss= 1.37907 val_acc= 0.30357 time= 0.01563
Epoch: 0016 train_loss= 1.38032 train_acc= 0.28711 val_loss= 1.37889 val_acc= 0.30357 time= 0.01563
Epoch: 0017 train_loss= 1.37986 train_acc= 0.27734 val_loss= 1.37878 val_acc= 0.30357 time= 0.01563
Epoch: 0018 train_loss= 1.37987 train_acc= 0.28125 val_loss= 1.37868 val_acc= 0.30357 time= 0.01563
Epoch: 0019 train_loss= 1.37924 train_acc= 0.28711 val_loss= 1.37859 val_acc= 0.30357 time= 0.01563
Epoch: 0020 train_loss= 1.37893 train_acc= 0.27930 val_loss= 1.37854 val_acc= 0.30357 time= 0.01563
Epoch: 0021 train_loss= 1.37920 train_acc= 0.26953 val_loss= 1.37844 val_acc= 0.30357 time= 0.01562
Epoch: 0022 train_loss= 1.37884 train_acc= 0.28125 val_loss= 1.37833 val_acc= 0.30357 time= 0.02067
Epoch: 0023 train_loss= 1.37796 train_acc= 0.28711 val_loss= 1.37819 val_acc= 0.30357 time= 0.01500
Epoch: 0024 train_loss= 1.37843 train_acc= 0.30273 val_loss= 1.37785 val_acc= 0.30357 time= 0.01856
Epoch: 0025 train_loss= 1.37827 train_acc= 0.28516 val_loss= 1.37765 val_acc= 0.30357 time= 0.01506
Epoch: 0026 train_loss= 1.37799 train_acc= 0.28906 val_loss= 1.37753 val_acc= 0.30357 time= 0.01563
Epoch: 0027 train_loss= 1.37836 train_acc= 0.27539 val_loss= 1.37750 val_acc= 0.30357 time= 0.01563
Epoch: 0028 train_loss= 1.37748 train_acc= 0.29883 val_loss= 1.37750 val_acc= 0.30357 time= 0.01563
Epoch: 0029 train_loss= 1.37723 train_acc= 0.28906 val_loss= 1.37752 val_acc= 0.33929 time= 0.01563
Epoch: 0030 train_loss= 1.37746 train_acc= 0.30273 val_loss= 1.37753 val_acc= 0.37500 time= 0.01563
Epoch: 0031 train_loss= 1.37801 train_acc= 0.30469 val_loss= 1.37735 val_acc= 0.41071 time= 0.01563
Epoch: 0032 train_loss= 1.37726 train_acc= 0.29492 val_loss= 1.37714 val_acc= 0.35714 time= 0.01563
Epoch: 0033 train_loss= 1.37741 train_acc= 0.32031 val_loss= 1.37698 val_acc= 0.33929 time= 0.01563
Epoch: 0034 train_loss= 1.37751 train_acc= 0.31250 val_loss= 1.37695 val_acc= 0.35714 time= 0.01563
Epoch: 0035 train_loss= 1.37699 train_acc= 0.30469 val_loss= 1.37701 val_acc= 0.33929 time= 0.01562
Epoch: 0036 train_loss= 1.37744 train_acc= 0.31055 val_loss= 1.37699 val_acc= 0.33929 time= 0.01563
Epoch: 0037 train_loss= 1.37668 train_acc= 0.31836 val_loss= 1.37693 val_acc= 0.33929 time= 0.01563
Epoch: 0038 train_loss= 1.37728 train_acc= 0.29688 val_loss= 1.37694 val_acc= 0.33929 time= 0.01563
Epoch: 0039 train_loss= 1.37736 train_acc= 0.31445 val_loss= 1.37686 val_acc= 0.32143 time= 0.01563
Epoch: 0040 train_loss= 1.37676 train_acc= 0.32422 val_loss= 1.37664 val_acc= 0.37500 time= 0.01563
Epoch: 0041 train_loss= 1.37622 train_acc= 0.34375 val_loss= 1.37645 val_acc= 0.35714 time= 0.01563
Epoch: 0042 train_loss= 1.37653 train_acc= 0.33203 val_loss= 1.37640 val_acc= 0.35714 time= 0.01563
Epoch: 0043 train_loss= 1.37660 train_acc= 0.30273 val_loss= 1.37641 val_acc= 0.33929 time= 0.01563
Epoch: 0044 train_loss= 1.37668 train_acc= 0.30078 val_loss= 1.37655 val_acc= 0.35714 time= 0.01563
Epoch: 0045 train_loss= 1.37644 train_acc= 0.31836 val_loss= 1.37672 val_acc= 0.33929 time= 0.01563
Epoch: 0046 train_loss= 1.37628 train_acc= 0.35156 val_loss= 1.37676 val_acc= 0.33929 time= 0.01563
Early stopping...
Optimization Finished!
Test set results: cost= 1.37987 accuracy= 0.35398 time= 0.00000 
