Epoch: 0001 train_loss= 0.70125 train_acc= 0.46753 val_loss= 0.69835 val_acc= 0.50820 time= 0.82562
Epoch: 0002 train_loss= 0.69811 train_acc= 0.55065 val_loss= 0.69659 val_acc= 0.49180 time= 0.00000
Epoch: 0003 train_loss= 0.69555 train_acc= 0.53506 val_loss= 0.69547 val_acc= 0.49180 time= 0.01562
Epoch: 0004 train_loss= 0.69367 train_acc= 0.53377 val_loss= 0.69471 val_acc= 0.49180 time= 0.01563
Epoch: 0005 train_loss= 0.69223 train_acc= 0.53896 val_loss= 0.69421 val_acc= 0.52459 time= 0.00000
Epoch: 0006 train_loss= 0.69152 train_acc= 0.54156 val_loss= 0.69389 val_acc= 0.54098 time= 0.01563
Epoch: 0007 train_loss= 0.69090 train_acc= 0.55974 val_loss= 0.69368 val_acc= 0.54098 time= 0.01563
Epoch: 0008 train_loss= 0.69021 train_acc= 0.55325 val_loss= 0.69355 val_acc= 0.54098 time= 0.00000
Epoch: 0009 train_loss= 0.68992 train_acc= 0.57143 val_loss= 0.69353 val_acc= 0.54098 time= 0.01563
Epoch: 0010 train_loss= 0.68940 train_acc= 0.55844 val_loss= 0.69346 val_acc= 0.54098 time= 0.00000
Epoch: 0011 train_loss= 0.68897 train_acc= 0.58701 val_loss= 0.69333 val_acc= 0.54098 time= 0.01563
Epoch: 0012 train_loss= 0.68787 train_acc= 0.56753 val_loss= 0.69305 val_acc= 0.54098 time= 0.01563
Epoch: 0013 train_loss= 0.68792 train_acc= 0.58571 val_loss= 0.69271 val_acc= 0.54098 time= 0.00000
Epoch: 0014 train_loss= 0.68713 train_acc= 0.60909 val_loss= 0.69229 val_acc= 0.54098 time= 0.01563
Epoch: 0015 train_loss= 0.68607 train_acc= 0.59870 val_loss= 0.69187 val_acc= 0.57377 time= 0.01563
Epoch: 0016 train_loss= 0.68650 train_acc= 0.61169 val_loss= 0.69148 val_acc= 0.57377 time= 0.00000
Epoch: 0017 train_loss= 0.68530 train_acc= 0.58961 val_loss= 0.69091 val_acc= 0.55738 time= 0.02057
Epoch: 0018 train_loss= 0.68473 train_acc= 0.66234 val_loss= 0.69046 val_acc= 0.55738 time= 0.01101
Epoch: 0019 train_loss= 0.68434 train_acc= 0.60260 val_loss= 0.69005 val_acc= 0.55738 time= 0.00000
Epoch: 0020 train_loss= 0.68285 train_acc= 0.60649 val_loss= 0.68961 val_acc= 0.55738 time= 0.01563
Epoch: 0021 train_loss= 0.68163 train_acc= 0.60000 val_loss= 0.68896 val_acc= 0.52459 time= 0.01563
Epoch: 0022 train_loss= 0.68215 train_acc= 0.65844 val_loss= 0.68844 val_acc= 0.59016 time= 0.00000
Epoch: 0023 train_loss= 0.68192 train_acc= 0.65065 val_loss= 0.68808 val_acc= 0.59016 time= 0.01563
Epoch: 0024 train_loss= 0.68177 train_acc= 0.62338 val_loss= 0.68767 val_acc= 0.59016 time= 0.01563
Epoch: 0025 train_loss= 0.67839 train_acc= 0.65325 val_loss= 0.68731 val_acc= 0.59016 time= 0.00000
Epoch: 0026 train_loss= 0.68085 train_acc= 0.67922 val_loss= 0.68713 val_acc= 0.59016 time= 0.02350
Epoch: 0027 train_loss= 0.67744 train_acc= 0.65844 val_loss= 0.68731 val_acc= 0.54098 time= 0.01400
Epoch: 0028 train_loss= 0.67683 train_acc= 0.63766 val_loss= 0.68718 val_acc= 0.52459 time= 0.00707
Epoch: 0029 train_loss= 0.67744 train_acc= 0.65455 val_loss= 0.68696 val_acc= 0.52459 time= 0.01562
Epoch: 0030 train_loss= 0.67437 train_acc= 0.67143 val_loss= 0.68668 val_acc= 0.52459 time= 0.00000
Epoch: 0031 train_loss= 0.67338 train_acc= 0.62338 val_loss= 0.68559 val_acc= 0.55738 time= 0.01563
Epoch: 0032 train_loss= 0.67358 train_acc= 0.66494 val_loss= 0.68456 val_acc= 0.60656 time= 0.01563
Epoch: 0033 train_loss= 0.67784 train_acc= 0.66364 val_loss= 0.68375 val_acc= 0.63934 time= 0.00000
Epoch: 0034 train_loss= 0.67300 train_acc= 0.68961 val_loss= 0.68325 val_acc= 0.67213 time= 0.01563
Epoch: 0035 train_loss= 0.67132 train_acc= 0.65714 val_loss= 0.68271 val_acc= 0.67213 time= 0.00000
Epoch: 0036 train_loss= 0.67235 train_acc= 0.67532 val_loss= 0.68221 val_acc= 0.67213 time= 0.01562
Epoch: 0037 train_loss= 0.67325 train_acc= 0.67792 val_loss= 0.68196 val_acc= 0.65574 time= 0.01563
Epoch: 0038 train_loss= 0.67216 train_acc= 0.68312 val_loss= 0.68207 val_acc= 0.62295 time= 0.01563
Epoch: 0039 train_loss= 0.66755 train_acc= 0.68182 val_loss= 0.68276 val_acc= 0.55738 time= 0.00000
Epoch: 0040 train_loss= 0.66752 train_acc= 0.66234 val_loss= 0.68447 val_acc= 0.54098 time= 0.01563
Early stopping...
Optimization Finished!
Test set results: cost= 0.67494 accuracy= 0.63115 time= 0.00000 
