Epoch: 0001 train_loss= 1.99410 train_acc= 0.28212 val_loss= 1.85791 val_acc= 0.19643 time= 0.98452
Epoch: 0002 train_loss= 3.41571 train_acc= 0.20810 val_loss= 1.63193 val_acc= 0.21429 time= 0.03125
Epoch: 0003 train_loss= 1.87522 train_acc= 0.26816 val_loss= 1.59724 val_acc= 0.19643 time= 0.01563
Epoch: 0004 train_loss= 2.08786 train_acc= 0.28073 val_loss= 1.54062 val_acc= 0.21429 time= 0.03125
Epoch: 0005 train_loss= 2.28077 train_acc= 0.27654 val_loss= 1.59891 val_acc= 0.19643 time= 0.01563
Epoch: 0006 train_loss= 1.89437 train_acc= 0.26816 val_loss= 1.70524 val_acc= 0.21429 time= 0.03125
Epoch: 0007 train_loss= 1.90783 train_acc= 0.28352 val_loss= 1.69762 val_acc= 0.21429 time= 0.01563
Epoch: 0008 train_loss= 2.31763 train_acc= 0.25000 val_loss= 1.74251 val_acc= 0.21429 time= 0.03125
Epoch: 0009 train_loss= 1.55658 train_acc= 0.28631 val_loss= 1.75953 val_acc= 0.21429 time= 0.01563
Epoch: 0010 train_loss= 1.87948 train_acc= 0.28492 val_loss= 1.73397 val_acc= 0.21429 time= 0.03125
Epoch: 0011 train_loss= 2.98029 train_acc= 0.22626 val_loss= 1.63703 val_acc= 0.21429 time= 0.01563
Epoch: 0012 train_loss= 1.86916 train_acc= 0.25978 val_loss= 1.55949 val_acc= 0.21429 time= 0.03125
Epoch: 0013 train_loss= 2.27127 train_acc= 0.25419 val_loss= 1.48413 val_acc= 0.19643 time= 0.03125
Epoch: 0014 train_loss= 1.99912 train_acc= 0.27514 val_loss= 1.43044 val_acc= 0.19643 time= 0.01563
Epoch: 0015 train_loss= 2.04856 train_acc= 0.26257 val_loss= 1.41427 val_acc= 0.16071 time= 0.03125
Epoch: 0016 train_loss= 1.43527 train_acc= 0.22207 val_loss= 1.40534 val_acc= 0.17857 time= 0.03125
Epoch: 0017 train_loss= 1.51053 train_acc= 0.28352 val_loss= 1.40181 val_acc= 0.19643 time= 0.01563
Epoch: 0018 train_loss= 1.39456 train_acc= 0.24721 val_loss= 1.39852 val_acc= 0.21429 time= 0.03125
Epoch: 0019 train_loss= 1.45246 train_acc= 0.24162 val_loss= 1.39406 val_acc= 0.23214 time= 0.01563
Epoch: 0020 train_loss= 1.41356 train_acc= 0.26257 val_loss= 1.39139 val_acc= 0.25000 time= 0.03125
Epoch: 0021 train_loss= 1.40516 train_acc= 0.24721 val_loss= 1.38930 val_acc= 0.25000 time= 0.01563
Epoch: 0022 train_loss= 1.39823 train_acc= 0.27235 val_loss= 1.38728 val_acc= 0.26786 time= 0.03125
Epoch: 0023 train_loss= 1.38766 train_acc= 0.29330 val_loss= 1.38523 val_acc= 0.23214 time= 0.01563
Epoch: 0024 train_loss= 1.93012 train_acc= 0.27095 val_loss= 1.38258 val_acc= 0.25000 time= 0.03125
Epoch: 0025 train_loss= 1.39985 train_acc= 0.25000 val_loss= 1.38009 val_acc= 0.21429 time= 0.01563
Epoch: 0026 train_loss= 1.39773 train_acc= 0.24860 val_loss= 1.37756 val_acc= 0.28571 time= 0.03125
Epoch: 0027 train_loss= 1.38168 train_acc= 0.33101 val_loss= 1.37509 val_acc= 0.30357 time= 0.01563
Epoch: 0028 train_loss= 1.40495 train_acc= 0.26397 val_loss= 1.37284 val_acc= 0.30357 time= 0.03125
Epoch: 0029 train_loss= 1.38770 train_acc= 0.29609 val_loss= 1.37064 val_acc= 0.32143 time= 0.01563
Epoch: 0030 train_loss= 1.38571 train_acc= 0.30866 val_loss= 1.36882 val_acc= 0.32143 time= 0.03125
Epoch: 0031 train_loss= 1.40698 train_acc= 0.28771 val_loss= 1.36760 val_acc= 0.33929 time= 0.01563
Epoch: 0032 train_loss= 1.39175 train_acc= 0.29330 val_loss= 1.36667 val_acc= 0.33929 time= 0.03125
Epoch: 0033 train_loss= 1.39559 train_acc= 0.25698 val_loss= 1.36558 val_acc= 0.33929 time= 0.01563
Epoch: 0034 train_loss= 1.39701 train_acc= 0.31006 val_loss= 1.36432 val_acc= 0.32143 time= 0.01562
Epoch: 0035 train_loss= 1.40650 train_acc= 0.28771 val_loss= 1.36339 val_acc= 0.32143 time= 0.03125
Epoch: 0036 train_loss= 1.39215 train_acc= 0.29469 val_loss= 1.36233 val_acc= 0.32143 time= 0.01562
Epoch: 0037 train_loss= 1.38283 train_acc= 0.30447 val_loss= 1.36140 val_acc= 0.33929 time= 0.03125
Epoch: 0038 train_loss= 1.39707 train_acc= 0.28911 val_loss= 1.36054 val_acc= 0.35714 time= 0.01563
Epoch: 0039 train_loss= 1.40011 train_acc= 0.29609 val_loss= 1.36012 val_acc= 0.35714 time= 0.03125
Epoch: 0040 train_loss= 1.43407 train_acc= 0.30726 val_loss= 1.36037 val_acc= 0.32143 time= 0.01563
Epoch: 0041 train_loss= 1.38048 train_acc= 0.31006 val_loss= 1.36038 val_acc= 0.32143 time= 0.03125
Epoch: 0042 train_loss= 1.38925 train_acc= 0.31285 val_loss= 1.36044 val_acc= 0.32143 time= 0.01563
Epoch: 0043 train_loss= 1.39331 train_acc= 0.28911 val_loss= 1.36064 val_acc= 0.32143 time= 0.03125
Epoch: 0044 train_loss= 1.38698 train_acc= 0.28492 val_loss= 1.36091 val_acc= 0.32143 time= 0.01563
Epoch: 0045 train_loss= 1.38202 train_acc= 0.31145 val_loss= 1.36107 val_acc= 0.33929 time= 0.03125
Early stopping...
Optimization Finished!
Test set results: cost= 1.39676 accuracy= 0.32743 time= 0.01563 
