Epoch: 0001 train_loss= 1.38623 train_acc= 0.24430 val_loss= 1.38271 val_acc= 0.23214 time= 0.25001
Epoch: 0002 train_loss= 1.38462 train_acc= 0.25407 val_loss= 1.38241 val_acc= 0.21429 time= 0.01562
Epoch: 0003 train_loss= 1.38540 train_acc= 0.25081 val_loss= 1.38203 val_acc= 0.21429 time= 0.00000
Epoch: 0004 train_loss= 1.38374 train_acc= 0.28339 val_loss= 1.38162 val_acc= 0.23214 time= 0.01563
Epoch: 0005 train_loss= 1.38344 train_acc= 0.27687 val_loss= 1.38121 val_acc= 0.23214 time= 0.00000
Epoch: 0006 train_loss= 1.38368 train_acc= 0.26059 val_loss= 1.38080 val_acc= 0.23214 time= 0.01563
Epoch: 0007 train_loss= 1.38203 train_acc= 0.28339 val_loss= 1.38041 val_acc= 0.23214 time= 0.00000
Epoch: 0008 train_loss= 1.38073 train_acc= 0.25081 val_loss= 1.38005 val_acc= 0.23214 time= 0.00000
Epoch: 0009 train_loss= 1.38185 train_acc= 0.26384 val_loss= 1.37964 val_acc= 0.23214 time= 0.01563
Epoch: 0010 train_loss= 1.37991 train_acc= 0.28339 val_loss= 1.37923 val_acc= 0.23214 time= 0.00000
Epoch: 0011 train_loss= 1.38163 train_acc= 0.28339 val_loss= 1.37878 val_acc= 0.23214 time= 0.01563
Epoch: 0012 train_loss= 1.38144 train_acc= 0.27687 val_loss= 1.37834 val_acc= 0.23214 time= 0.00000
Epoch: 0013 train_loss= 1.37922 train_acc= 0.26384 val_loss= 1.37787 val_acc= 0.23214 time= 0.01563
Epoch: 0014 train_loss= 1.38033 train_acc= 0.28013 val_loss= 1.37737 val_acc= 0.23214 time= 0.00000
Epoch: 0015 train_loss= 1.37842 train_acc= 0.27362 val_loss= 1.37689 val_acc= 0.23214 time= 0.00000
Epoch: 0016 train_loss= 1.37919 train_acc= 0.27036 val_loss= 1.37641 val_acc= 0.23214 time= 0.01563
Epoch: 0017 train_loss= 1.37795 train_acc= 0.28013 val_loss= 1.37595 val_acc= 0.23214 time= 0.00000
Epoch: 0018 train_loss= 1.37788 train_acc= 0.27687 val_loss= 1.37549 val_acc= 0.23214 time= 0.01563
Epoch: 0019 train_loss= 1.37813 train_acc= 0.27036 val_loss= 1.37503 val_acc= 0.23214 time= 0.00000
Epoch: 0020 train_loss= 1.37768 train_acc= 0.27687 val_loss= 1.37457 val_acc= 0.23214 time= 0.01563
Epoch: 0021 train_loss= 1.37874 train_acc= 0.27362 val_loss= 1.37408 val_acc= 0.23214 time= 0.00000
Epoch: 0022 train_loss= 1.37718 train_acc= 0.28013 val_loss= 1.37358 val_acc= 0.23214 time= 0.01563
Epoch: 0023 train_loss= 1.37846 train_acc= 0.26059 val_loss= 1.37303 val_acc= 0.23214 time= 0.00000
Epoch: 0024 train_loss= 1.37728 train_acc= 0.26710 val_loss= 1.37249 val_acc= 0.26786 time= 0.00000
Epoch: 0025 train_loss= 1.37635 train_acc= 0.29967 val_loss= 1.37198 val_acc= 0.30357 time= 0.01563
Epoch: 0026 train_loss= 1.37721 train_acc= 0.25407 val_loss= 1.37149 val_acc= 0.25000 time= 0.00000
Epoch: 0027 train_loss= 1.37684 train_acc= 0.24430 val_loss= 1.37100 val_acc= 0.25000 time= 0.01563
Epoch: 0028 train_loss= 1.37865 train_acc= 0.30293 val_loss= 1.37054 val_acc= 0.26786 time= 0.00000
Epoch: 0029 train_loss= 1.37794 train_acc= 0.26384 val_loss= 1.37016 val_acc= 0.28571 time= 0.01563
Epoch: 0030 train_loss= 1.37871 train_acc= 0.25081 val_loss= 1.36974 val_acc= 0.28571 time= 0.00000
Epoch: 0031 train_loss= 1.37726 train_acc= 0.27036 val_loss= 1.36940 val_acc= 0.28571 time= 0.00000
Epoch: 0032 train_loss= 1.37665 train_acc= 0.27687 val_loss= 1.36906 val_acc= 0.28571 time= 0.00000
Epoch: 0033 train_loss= 1.37797 train_acc= 0.27036 val_loss= 1.36874 val_acc= 0.28571 time= 0.00000
Epoch: 0034 train_loss= 1.37583 train_acc= 0.28990 val_loss= 1.36849 val_acc= 0.28571 time= 0.01563
Epoch: 0035 train_loss= 1.37685 train_acc= 0.25407 val_loss= 1.36830 val_acc= 0.28571 time= 0.00000
Epoch: 0036 train_loss= 1.37765 train_acc= 0.26710 val_loss= 1.36817 val_acc= 0.23214 time= 0.00000
Epoch: 0037 train_loss= 1.37769 train_acc= 0.27036 val_loss= 1.36809 val_acc= 0.21429 time= 0.01562
Epoch: 0038 train_loss= 1.37707 train_acc= 0.26710 val_loss= 1.36804 val_acc= 0.26786 time= 0.00000
Epoch: 0039 train_loss= 1.37705 train_acc= 0.27362 val_loss= 1.36799 val_acc= 0.28571 time= 0.01563
Epoch: 0040 train_loss= 1.37770 train_acc= 0.26710 val_loss= 1.36801 val_acc= 0.25000 time= 0.00000
Epoch: 0041 train_loss= 1.37619 train_acc= 0.26384 val_loss= 1.36806 val_acc= 0.25000 time= 0.00000
Epoch: 0042 train_loss= 1.37845 train_acc= 0.27362 val_loss= 1.36811 val_acc= 0.25000 time= 0.01563
Epoch: 0043 train_loss= 1.37704 train_acc= 0.30293 val_loss= 1.36820 val_acc= 0.25000 time= 0.00000
Early stopping...
Optimization Finished!
Test set results: cost= 1.37893 accuracy= 0.24779 time= 0.00000 
