Epoch: 0001 train_loss= 1.39395 train_acc= 0.30293 val_loss= 1.38904 val_acc= 0.37500 time= 0.20348
Epoch: 0002 train_loss= 1.39021 train_acc= 0.32248 val_loss= 1.38404 val_acc= 0.37500 time= 0.01563
Epoch: 0003 train_loss= 1.38660 train_acc= 0.32248 val_loss= 1.37915 val_acc= 0.37500 time= 0.01563
Epoch: 0004 train_loss= 1.38380 train_acc= 0.32248 val_loss= 1.37470 val_acc= 0.37500 time= 0.01563
Epoch: 0005 train_loss= 1.38175 train_acc= 0.32248 val_loss= 1.37084 val_acc= 0.37500 time= 0.00000
Epoch: 0006 train_loss= 1.37964 train_acc= 0.32248 val_loss= 1.36752 val_acc= 0.37500 time= 0.01563
Epoch: 0007 train_loss= 1.37833 train_acc= 0.32248 val_loss= 1.36477 val_acc= 0.37500 time= 0.01563
Epoch: 0008 train_loss= 1.37733 train_acc= 0.32248 val_loss= 1.36249 val_acc= 0.37500 time= 0.00000
Epoch: 0009 train_loss= 1.37637 train_acc= 0.32248 val_loss= 1.36063 val_acc= 0.37500 time= 0.01563
Epoch: 0010 train_loss= 1.37699 train_acc= 0.32248 val_loss= 1.35915 val_acc= 0.37500 time= 0.01562
Epoch: 0011 train_loss= 1.37580 train_acc= 0.32248 val_loss= 1.35794 val_acc= 0.37500 time= 0.01563
Epoch: 0012 train_loss= 1.37610 train_acc= 0.32248 val_loss= 1.35694 val_acc= 0.37500 time= 0.00000
Epoch: 0013 train_loss= 1.37544 train_acc= 0.32248 val_loss= 1.35614 val_acc= 0.37500 time= 0.01563
Epoch: 0014 train_loss= 1.37504 train_acc= 0.32248 val_loss= 1.35555 val_acc= 0.37500 time= 0.01563
Epoch: 0015 train_loss= 1.37454 train_acc= 0.32248 val_loss= 1.35521 val_acc= 0.37500 time= 0.00000
Epoch: 0016 train_loss= 1.37379 train_acc= 0.32248 val_loss= 1.35499 val_acc= 0.37500 time= 0.01563
Epoch: 0017 train_loss= 1.37326 train_acc= 0.32248 val_loss= 1.35487 val_acc= 0.37500 time= 0.01563
Epoch: 0018 train_loss= 1.37214 train_acc= 0.32248 val_loss= 1.35485 val_acc= 0.37500 time= 0.01563
Epoch: 0019 train_loss= 1.37272 train_acc= 0.32248 val_loss= 1.35477 val_acc= 0.37500 time= 0.00000
Epoch: 0020 train_loss= 1.37249 train_acc= 0.32248 val_loss= 1.35468 val_acc= 0.37500 time= 0.01563
Epoch: 0021 train_loss= 1.37213 train_acc= 0.32248 val_loss= 1.35449 val_acc= 0.37500 time= 0.01563
Epoch: 0022 train_loss= 1.37253 train_acc= 0.32248 val_loss= 1.35424 val_acc= 0.37500 time= 0.00000
Epoch: 0023 train_loss= 1.37227 train_acc= 0.32248 val_loss= 1.35397 val_acc= 0.37500 time= 0.01563
Epoch: 0024 train_loss= 1.37218 train_acc= 0.32248 val_loss= 1.35367 val_acc= 0.37500 time= 0.01563
Epoch: 0025 train_loss= 1.36944 train_acc= 0.32248 val_loss= 1.35318 val_acc= 0.37500 time= 0.00000
Epoch: 0026 train_loss= 1.37092 train_acc= 0.32248 val_loss= 1.35251 val_acc= 0.37500 time= 0.00000
Epoch: 0027 train_loss= 1.37051 train_acc= 0.32248 val_loss= 1.35186 val_acc= 0.37500 time= 0.01562
Epoch: 0028 train_loss= 1.37169 train_acc= 0.32248 val_loss= 1.35127 val_acc= 0.37500 time= 0.01563
Epoch: 0029 train_loss= 1.37154 train_acc= 0.32248 val_loss= 1.35075 val_acc= 0.37500 time= 0.00000
Epoch: 0030 train_loss= 1.37038 train_acc= 0.32248 val_loss= 1.35031 val_acc= 0.37500 time= 0.01563
Epoch: 0031 train_loss= 1.37029 train_acc= 0.32248 val_loss= 1.34990 val_acc= 0.37500 time= 0.01563
Epoch: 0032 train_loss= 1.36905 train_acc= 0.32248 val_loss= 1.34956 val_acc= 0.37500 time= 0.00000
Epoch: 0033 train_loss= 1.36901 train_acc= 0.32248 val_loss= 1.34944 val_acc= 0.37500 time= 0.02542
Epoch: 0034 train_loss= 1.36931 train_acc= 0.32573 val_loss= 1.34945 val_acc= 0.37500 time= 0.00411
Epoch: 0035 train_loss= 1.37055 train_acc= 0.32248 val_loss= 1.34942 val_acc= 0.37500 time= 0.01562
Epoch: 0036 train_loss= 1.36820 train_acc= 0.32573 val_loss= 1.34927 val_acc= 0.37500 time= 0.00000
Epoch: 0037 train_loss= 1.36783 train_acc= 0.32248 val_loss= 1.34919 val_acc= 0.37500 time= 0.01563
Epoch: 0038 train_loss= 1.36733 train_acc= 0.32248 val_loss= 1.34898 val_acc= 0.37500 time= 0.01563
Epoch: 0039 train_loss= 1.36810 train_acc= 0.32573 val_loss= 1.34857 val_acc= 0.37500 time= 0.01562
Epoch: 0040 train_loss= 1.36801 train_acc= 0.32248 val_loss= 1.34815 val_acc= 0.37500 time= 0.00000
Epoch: 0041 train_loss= 1.36753 train_acc= 0.32248 val_loss= 1.34778 val_acc= 0.37500 time= 0.01563
Epoch: 0042 train_loss= 1.36845 train_acc= 0.32248 val_loss= 1.34722 val_acc= 0.37500 time= 0.01563
Epoch: 0043 train_loss= 1.36853 train_acc= 0.32248 val_loss= 1.34691 val_acc= 0.37500 time= 0.00000
Epoch: 0044 train_loss= 1.36848 train_acc= 0.32248 val_loss= 1.34692 val_acc= 0.37500 time= 0.01563
Epoch: 0045 train_loss= 1.36805 train_acc= 0.32248 val_loss= 1.34692 val_acc= 0.37500 time= 0.01562
Epoch: 0046 train_loss= 1.36781 train_acc= 0.32248 val_loss= 1.34689 val_acc= 0.37500 time= 0.01563
Epoch: 0047 train_loss= 1.36642 train_acc= 0.32248 val_loss= 1.34660 val_acc= 0.37500 time= 0.00000
Epoch: 0048 train_loss= 1.36761 train_acc= 0.32248 val_loss= 1.34631 val_acc= 0.37500 time= 0.01563
Epoch: 0049 train_loss= 1.36772 train_acc= 0.32248 val_loss= 1.34593 val_acc= 0.37500 time= 0.01563
Epoch: 0050 train_loss= 1.36839 train_acc= 0.32248 val_loss= 1.34565 val_acc= 0.37500 time= 0.00000
Epoch: 0051 train_loss= 1.36624 train_acc= 0.32248 val_loss= 1.34538 val_acc= 0.37500 time= 0.01563
Epoch: 0052 train_loss= 1.36665 train_acc= 0.32248 val_loss= 1.34548 val_acc= 0.37500 time= 0.01563
Epoch: 0053 train_loss= 1.36702 train_acc= 0.32248 val_loss= 1.34534 val_acc= 0.37500 time= 0.00000
Epoch: 0054 train_loss= 1.36829 train_acc= 0.32573 val_loss= 1.34525 val_acc= 0.37500 time= 0.01563
Epoch: 0055 train_loss= 1.36537 train_acc= 0.32899 val_loss= 1.34515 val_acc= 0.37500 time= 0.01563
Epoch: 0056 train_loss= 1.36507 train_acc= 0.32248 val_loss= 1.34498 val_acc= 0.37500 time= 0.00000
Epoch: 0057 train_loss= 1.36562 train_acc= 0.32899 val_loss= 1.34468 val_acc= 0.37500 time= 0.01563
Epoch: 0058 train_loss= 1.36656 train_acc= 0.32248 val_loss= 1.34395 val_acc= 0.37500 time= 0.01563
Epoch: 0059 train_loss= 1.36649 train_acc= 0.32248 val_loss= 1.34330 val_acc= 0.37500 time= 0.00000
Epoch: 0060 train_loss= 1.36532 train_acc= 0.32573 val_loss= 1.34266 val_acc= 0.37500 time= 0.01563
Epoch: 0061 train_loss= 1.36463 train_acc= 0.32899 val_loss= 1.34215 val_acc= 0.37500 time= 0.01563
Epoch: 0062 train_loss= 1.36323 train_acc= 0.32899 val_loss= 1.34192 val_acc= 0.37500 time= 0.01563
Epoch: 0063 train_loss= 1.36517 train_acc= 0.32899 val_loss= 1.34226 val_acc= 0.37500 time= 0.00000
Epoch: 0064 train_loss= 1.36456 train_acc= 0.32899 val_loss= 1.34312 val_acc= 0.37500 time= 0.01563
Epoch: 0065 train_loss= 1.36436 train_acc= 0.32899 val_loss= 1.34364 val_acc= 0.37500 time= 0.01563
Early stopping...
Optimization Finished!
Test set results: cost= 1.34117 accuracy= 0.36283 time= 0.00000 
