Epoch: 0001 train_loss= 1.39406 train_acc= 0.25081 val_loss= 1.38977 val_acc= 0.42857 time= 0.20314
Epoch: 0002 train_loss= 1.39096 train_acc= 0.29967 val_loss= 1.38588 val_acc= 0.42857 time= 0.01563
Epoch: 0003 train_loss= 1.38843 train_acc= 0.32248 val_loss= 1.38233 val_acc= 0.42857 time= 0.01563
Epoch: 0004 train_loss= 1.38634 train_acc= 0.31270 val_loss= 1.37903 val_acc= 0.42857 time= 0.01563
Epoch: 0005 train_loss= 1.38478 train_acc= 0.31922 val_loss= 1.37610 val_acc= 0.42857 time= 0.01563
Epoch: 0006 train_loss= 1.38377 train_acc= 0.31922 val_loss= 1.37351 val_acc= 0.42857 time= 0.01563
Epoch: 0007 train_loss= 1.38285 train_acc= 0.32899 val_loss= 1.37108 val_acc= 0.42857 time= 0.01563
Epoch: 0008 train_loss= 1.38246 train_acc= 0.32248 val_loss= 1.36876 val_acc= 0.42857 time= 0.01563
Epoch: 0009 train_loss= 1.38201 train_acc= 0.32899 val_loss= 1.36657 val_acc= 0.42857 time= 0.01563
Epoch: 0010 train_loss= 1.38201 train_acc= 0.32573 val_loss= 1.36459 val_acc= 0.42857 time= 0.03125
Epoch: 0011 train_loss= 1.38122 train_acc= 0.32573 val_loss= 1.36273 val_acc= 0.42857 time= 0.01562
Epoch: 0012 train_loss= 1.38122 train_acc= 0.32573 val_loss= 1.36111 val_acc= 0.42857 time= 0.03125
Epoch: 0013 train_loss= 1.38146 train_acc= 0.32573 val_loss= 1.35974 val_acc= 0.42857 time= 0.01563
Epoch: 0014 train_loss= 1.38072 train_acc= 0.32573 val_loss= 1.35852 val_acc= 0.42857 time= 0.03125
Epoch: 0015 train_loss= 1.38114 train_acc= 0.32573 val_loss= 1.35750 val_acc= 0.42857 time= 0.01563
Epoch: 0016 train_loss= 1.37984 train_acc= 0.32573 val_loss= 1.35655 val_acc= 0.42857 time= 0.01563
Epoch: 0017 train_loss= 1.37898 train_acc= 0.32573 val_loss= 1.35581 val_acc= 0.42857 time= 0.01563
Epoch: 0018 train_loss= 1.37859 train_acc= 0.32573 val_loss= 1.35508 val_acc= 0.42857 time= 0.01563
Epoch: 0019 train_loss= 1.37812 train_acc= 0.32573 val_loss= 1.35438 val_acc= 0.42857 time= 0.01563
Epoch: 0020 train_loss= 1.37795 train_acc= 0.32573 val_loss= 1.35365 val_acc= 0.42857 time= 0.01563
Epoch: 0021 train_loss= 1.37853 train_acc= 0.32573 val_loss= 1.35305 val_acc= 0.42857 time= 0.01562
Epoch: 0022 train_loss= 1.37770 train_acc= 0.32573 val_loss= 1.35257 val_acc= 0.42857 time= 0.01563
Epoch: 0023 train_loss= 1.37749 train_acc= 0.32573 val_loss= 1.35201 val_acc= 0.42857 time= 0.01563
Epoch: 0024 train_loss= 1.37724 train_acc= 0.32573 val_loss= 1.35145 val_acc= 0.42857 time= 0.02078
Epoch: 0025 train_loss= 1.37729 train_acc= 0.32573 val_loss= 1.35104 val_acc= 0.42857 time= 0.01051
Epoch: 0026 train_loss= 1.37700 train_acc= 0.32573 val_loss= 1.35058 val_acc= 0.42857 time= 0.01563
Epoch: 0027 train_loss= 1.37618 train_acc= 0.32573 val_loss= 1.34994 val_acc= 0.42857 time= 0.00000
Epoch: 0028 train_loss= 1.37705 train_acc= 0.32573 val_loss= 1.34953 val_acc= 0.42857 time= 0.01563
Epoch: 0029 train_loss= 1.37609 train_acc= 0.32573 val_loss= 1.34918 val_acc= 0.42857 time= 0.01562
Epoch: 0030 train_loss= 1.37599 train_acc= 0.32573 val_loss= 1.34894 val_acc= 0.42857 time= 0.01563
Epoch: 0031 train_loss= 1.37682 train_acc= 0.32573 val_loss= 1.34873 val_acc= 0.42857 time= 0.01563
Epoch: 0032 train_loss= 1.37512 train_acc= 0.32573 val_loss= 1.34835 val_acc= 0.42857 time= 0.00000
Epoch: 0033 train_loss= 1.37554 train_acc= 0.32573 val_loss= 1.34788 val_acc= 0.42857 time= 0.01563
Epoch: 0034 train_loss= 1.37565 train_acc= 0.32573 val_loss= 1.34746 val_acc= 0.42857 time= 0.01563
Epoch: 0035 train_loss= 1.37582 train_acc= 0.32573 val_loss= 1.34711 val_acc= 0.42857 time= 0.01563
Epoch: 0036 train_loss= 1.37558 train_acc= 0.32573 val_loss= 1.34673 val_acc= 0.42857 time= 0.01562
Epoch: 0037 train_loss= 1.37575 train_acc= 0.32573 val_loss= 1.34644 val_acc= 0.42857 time= 0.00000
Epoch: 0038 train_loss= 1.37460 train_acc= 0.32573 val_loss= 1.34588 val_acc= 0.42857 time= 0.01563
Epoch: 0039 train_loss= 1.37417 train_acc= 0.32573 val_loss= 1.34504 val_acc= 0.42857 time= 0.01562
Epoch: 0040 train_loss= 1.37448 train_acc= 0.32573 val_loss= 1.34444 val_acc= 0.42857 time= 0.01563
Epoch: 0041 train_loss= 1.37432 train_acc= 0.32573 val_loss= 1.34448 val_acc= 0.42857 time= 0.01563
Epoch: 0042 train_loss= 1.37477 train_acc= 0.32573 val_loss= 1.34483 val_acc= 0.42857 time= 0.00000
Epoch: 0043 train_loss= 1.37441 train_acc= 0.32573 val_loss= 1.34533 val_acc= 0.42857 time= 0.01563
Epoch: 0044 train_loss= 1.37539 train_acc= 0.32573 val_loss= 1.34605 val_acc= 0.42857 time= 0.01562
Early stopping...
Optimization Finished!
Test set results: cost= 1.37474 accuracy= 0.30088 time= 0.00000 
