Epoch: 0001 train_loss= 0.70048 train_acc= 0.46909 val_loss= 0.69898 val_acc= 0.54098 time= 0.34008
Epoch: 0002 train_loss= 0.69888 train_acc= 0.51818 val_loss= 0.69795 val_acc= 0.54098 time= 0.01200
Epoch: 0003 train_loss= 0.69831 train_acc= 0.51273 val_loss= 0.69716 val_acc= 0.54098 time= 0.01100
Epoch: 0004 train_loss= 0.69772 train_acc= 0.52364 val_loss= 0.69659 val_acc= 0.54098 time= 0.01100
Epoch: 0005 train_loss= 0.69630 train_acc= 0.52182 val_loss= 0.69608 val_acc= 0.54098 time= 0.01200
Epoch: 0006 train_loss= 0.69662 train_acc= 0.52364 val_loss= 0.69564 val_acc= 0.54098 time= 0.01423
Epoch: 0007 train_loss= 0.69562 train_acc= 0.52545 val_loss= 0.69524 val_acc= 0.54098 time= 0.01200
Epoch: 0008 train_loss= 0.69618 train_acc= 0.52182 val_loss= 0.69489 val_acc= 0.54098 time= 0.01100
Epoch: 0009 train_loss= 0.69506 train_acc= 0.52182 val_loss= 0.69457 val_acc= 0.54098 time= 0.01300
Epoch: 0010 train_loss= 0.69466 train_acc= 0.52182 val_loss= 0.69428 val_acc= 0.54098 time= 0.01100
Epoch: 0011 train_loss= 0.69502 train_acc= 0.52182 val_loss= 0.69402 val_acc= 0.54098 time= 0.01000
Epoch: 0012 train_loss= 0.69511 train_acc= 0.52000 val_loss= 0.69377 val_acc= 0.54098 time= 0.01100
Epoch: 0013 train_loss= 0.69515 train_acc= 0.52182 val_loss= 0.69352 val_acc= 0.54098 time= 0.01200
Epoch: 0014 train_loss= 0.69418 train_acc= 0.52000 val_loss= 0.69330 val_acc= 0.54098 time= 0.01300
Epoch: 0015 train_loss= 0.69502 train_acc= 0.52182 val_loss= 0.69310 val_acc= 0.54098 time= 0.01400
Epoch: 0016 train_loss= 0.69383 train_acc= 0.52364 val_loss= 0.69292 val_acc= 0.54098 time= 0.01200
Epoch: 0017 train_loss= 0.69358 train_acc= 0.52182 val_loss= 0.69276 val_acc= 0.54098 time= 0.01300
Epoch: 0018 train_loss= 0.69364 train_acc= 0.52364 val_loss= 0.69263 val_acc= 0.54098 time= 0.01100
Epoch: 0019 train_loss= 0.69376 train_acc= 0.52364 val_loss= 0.69252 val_acc= 0.54098 time= 0.01100
Epoch: 0020 train_loss= 0.69305 train_acc= 0.52000 val_loss= 0.69243 val_acc= 0.54098 time= 0.01300
Epoch: 0021 train_loss= 0.69267 train_acc= 0.52545 val_loss= 0.69235 val_acc= 0.54098 time= 0.01300
Epoch: 0022 train_loss= 0.69310 train_acc= 0.52182 val_loss= 0.69228 val_acc= 0.54098 time= 0.01100
Epoch: 0023 train_loss= 0.69258 train_acc= 0.52182 val_loss= 0.69222 val_acc= 0.54098 time= 0.00725
Epoch: 0024 train_loss= 0.69270 train_acc= 0.52182 val_loss= 0.69216 val_acc= 0.54098 time= 0.01562
Epoch: 0025 train_loss= 0.69277 train_acc= 0.52182 val_loss= 0.69208 val_acc= 0.54098 time= 0.00000
Epoch: 0026 train_loss= 0.69282 train_acc= 0.52182 val_loss= 0.69201 val_acc= 0.54098 time= 0.02059
Epoch: 0027 train_loss= 0.69201 train_acc= 0.52182 val_loss= 0.69194 val_acc= 0.54098 time= 0.01100
Epoch: 0028 train_loss= 0.69227 train_acc= 0.52364 val_loss= 0.69186 val_acc= 0.54098 time= 0.00000
Epoch: 0029 train_loss= 0.69249 train_acc= 0.52182 val_loss= 0.69179 val_acc= 0.54098 time= 0.01563
Epoch: 0030 train_loss= 0.69224 train_acc= 0.52000 val_loss= 0.69172 val_acc= 0.54098 time= 0.01563
Epoch: 0031 train_loss= 0.69280 train_acc= 0.52182 val_loss= 0.69166 val_acc= 0.54098 time= 0.01563
Epoch: 0032 train_loss= 0.69209 train_acc= 0.52182 val_loss= 0.69161 val_acc= 0.54098 time= 0.00000
Epoch: 0033 train_loss= 0.69198 train_acc= 0.52182 val_loss= 0.69156 val_acc= 0.54098 time= 0.01562
Epoch: 0034 train_loss= 0.69235 train_acc= 0.52182 val_loss= 0.69152 val_acc= 0.54098 time= 0.01563
Epoch: 0035 train_loss= 0.69239 train_acc= 0.52364 val_loss= 0.69149 val_acc= 0.54098 time= 0.01563
Epoch: 0036 train_loss= 0.69164 train_acc= 0.52182 val_loss= 0.69145 val_acc= 0.54098 time= 0.00000
Epoch: 0037 train_loss= 0.69171 train_acc= 0.52364 val_loss= 0.69142 val_acc= 0.54098 time= 0.01563
Epoch: 0038 train_loss= 0.69302 train_acc= 0.52182 val_loss= 0.69140 val_acc= 0.54098 time= 0.01563
Epoch: 0039 train_loss= 0.69260 train_acc= 0.52182 val_loss= 0.69139 val_acc= 0.54098 time= 0.01562
Epoch: 0040 train_loss= 0.69229 train_acc= 0.52182 val_loss= 0.69138 val_acc= 0.54098 time= 0.00000
Epoch: 0041 train_loss= 0.69179 train_acc= 0.52364 val_loss= 0.69137 val_acc= 0.54098 time= 0.01563
Epoch: 0042 train_loss= 0.69171 train_acc= 0.52000 val_loss= 0.69136 val_acc= 0.54098 time= 0.01563
Epoch: 0043 train_loss= 0.69215 train_acc= 0.52182 val_loss= 0.69136 val_acc= 0.54098 time= 0.00000
Epoch: 0044 train_loss= 0.69162 train_acc= 0.52182 val_loss= 0.69135 val_acc= 0.54098 time= 0.01563
Epoch: 0045 train_loss= 0.69200 train_acc= 0.52364 val_loss= 0.69135 val_acc= 0.54098 time= 0.01563
Epoch: 0046 train_loss= 0.69294 train_acc= 0.52000 val_loss= 0.69136 val_acc= 0.54098 time= 0.01563
Epoch: 0047 train_loss= 0.69210 train_acc= 0.52182 val_loss= 0.69137 val_acc= 0.54098 time= 0.01563
Epoch: 0048 train_loss= 0.69143 train_acc= 0.52364 val_loss= 0.69136 val_acc= 0.54098 time= 0.01563
Epoch: 0049 train_loss= 0.69165 train_acc= 0.52182 val_loss= 0.69134 val_acc= 0.54098 time= 0.00000
Epoch: 0050 train_loss= 0.69210 train_acc= 0.52364 val_loss= 0.69133 val_acc= 0.54098 time= 0.01563
Epoch: 0051 train_loss= 0.69179 train_acc= 0.52182 val_loss= 0.69133 val_acc= 0.54098 time= 0.01563
Epoch: 0052 train_loss= 0.69140 train_acc= 0.52182 val_loss= 0.69131 val_acc= 0.54098 time= 0.01563
Epoch: 0053 train_loss= 0.69196 train_acc= 0.52182 val_loss= 0.69130 val_acc= 0.54098 time= 0.00000
Epoch: 0054 train_loss= 0.69217 train_acc= 0.52182 val_loss= 0.69130 val_acc= 0.54098 time= 0.01563
Epoch: 0055 train_loss= 0.69239 train_acc= 0.52182 val_loss= 0.69129 val_acc= 0.54098 time= 0.02384
Epoch: 0056 train_loss= 0.69183 train_acc= 0.52182 val_loss= 0.69129 val_acc= 0.54098 time= 0.01206
Epoch: 0057 train_loss= 0.69206 train_acc= 0.52182 val_loss= 0.69129 val_acc= 0.54098 time= 0.02173
Epoch: 0058 train_loss= 0.69256 train_acc= 0.52182 val_loss= 0.69131 val_acc= 0.54098 time= 0.01000
Epoch: 0059 train_loss= 0.69227 train_acc= 0.52182 val_loss= 0.69133 val_acc= 0.54098 time= 0.00000
Early stopping...
Optimization Finished!
Test set results: cost= 0.68877 accuracy= 0.54918 time= 0.01563 
