Epoch: 0001 train_loss= 1.39714 train_acc= 0.22476 val_loss= 1.39867 val_acc= 0.17857 time= 0.28195
Epoch: 0002 train_loss= 1.39400 train_acc= 0.21173 val_loss= 1.38875 val_acc= 0.37500 time= 0.01101
Epoch: 0003 train_loss= 1.38693 train_acc= 0.30619 val_loss= 1.37984 val_acc= 0.37500 time= 0.00794
Epoch: 0004 train_loss= 1.38228 train_acc= 0.32248 val_loss= 1.37194 val_acc= 0.37500 time= 0.00849
Epoch: 0005 train_loss= 1.37939 train_acc= 0.31596 val_loss= 1.36477 val_acc= 0.37500 time= 0.00796
Epoch: 0006 train_loss= 1.37853 train_acc= 0.31596 val_loss= 1.35819 val_acc= 0.37500 time= 0.00900
Epoch: 0007 train_loss= 1.37562 train_acc= 0.31596 val_loss= 1.35215 val_acc= 0.37500 time= 0.00890
Epoch: 0008 train_loss= 1.37422 train_acc= 0.31596 val_loss= 1.34671 val_acc= 0.37500 time= 0.01000
Epoch: 0009 train_loss= 1.37368 train_acc= 0.31596 val_loss= 1.34188 val_acc= 0.37500 time= 0.00845
Epoch: 0010 train_loss= 1.37074 train_acc= 0.31596 val_loss= 1.33760 val_acc= 0.37500 time= 0.00907
Epoch: 0011 train_loss= 1.37058 train_acc= 0.31596 val_loss= 1.33395 val_acc= 0.37500 time= 0.00887
Epoch: 0012 train_loss= 1.37255 train_acc= 0.31596 val_loss= 1.33094 val_acc= 0.37500 time= 0.01123
Epoch: 0013 train_loss= 1.37198 train_acc= 0.31596 val_loss= 1.32835 val_acc= 0.37500 time= 0.00899
Epoch: 0014 train_loss= 1.36994 train_acc= 0.31596 val_loss= 1.32639 val_acc= 0.37500 time= 0.00806
Epoch: 0015 train_loss= 1.37037 train_acc= 0.31596 val_loss= 1.32499 val_acc= 0.37500 time= 0.00908
Epoch: 0016 train_loss= 1.37059 train_acc= 0.31596 val_loss= 1.32403 val_acc= 0.37500 time= 0.00783
Epoch: 0017 train_loss= 1.37098 train_acc= 0.31596 val_loss= 1.32370 val_acc= 0.37500 time= 0.00908
Epoch: 0018 train_loss= 1.37116 train_acc= 0.31596 val_loss= 1.32381 val_acc= 0.37500 time= 0.00810
Epoch: 0019 train_loss= 1.37097 train_acc= 0.31596 val_loss= 1.32425 val_acc= 0.37500 time= 0.00834
Epoch: 0020 train_loss= 1.37114 train_acc= 0.31596 val_loss= 1.32494 val_acc= 0.37500 time= 0.01009
Epoch: 0021 train_loss= 1.37109 train_acc= 0.31596 val_loss= 1.32584 val_acc= 0.37500 time= 0.00905
Epoch: 0022 train_loss= 1.37105 train_acc= 0.31596 val_loss= 1.32696 val_acc= 0.37500 time= 0.01028
Early stopping...
Optimization Finished!
Test set results: cost= 1.40099 accuracy= 0.28319 time= 0.00400 
