Epoch: 0001 train_loss= 0.69940 train_acc= 0.48182 val_loss= 0.69872 val_acc= 0.45902 time= 0.10939
Epoch: 0002 train_loss= 0.69872 train_acc= 0.50303 val_loss= 0.69811 val_acc= 0.54098 time= 0.01562
Epoch: 0003 train_loss= 0.69817 train_acc= 0.51818 val_loss= 0.69761 val_acc= 0.54098 time= 0.01563
Epoch: 0004 train_loss= 0.69765 train_acc= 0.51818 val_loss= 0.69713 val_acc= 0.54098 time= 0.01563
Epoch: 0005 train_loss= 0.69712 train_acc= 0.50909 val_loss= 0.69668 val_acc= 0.54098 time= 0.00000
Epoch: 0006 train_loss= 0.69672 train_acc= 0.51515 val_loss= 0.69626 val_acc= 0.54098 time= 0.01562
Epoch: 0007 train_loss= 0.69627 train_acc= 0.51515 val_loss= 0.69586 val_acc= 0.54098 time= 0.01563
Epoch: 0008 train_loss= 0.69586 train_acc= 0.51515 val_loss= 0.69549 val_acc= 0.54098 time= 0.01563
Epoch: 0009 train_loss= 0.69544 train_acc= 0.51515 val_loss= 0.69514 val_acc= 0.54098 time= 0.01563
Epoch: 0010 train_loss= 0.69516 train_acc= 0.51515 val_loss= 0.69482 val_acc= 0.54098 time= 0.00000
Epoch: 0011 train_loss= 0.69472 train_acc= 0.51515 val_loss= 0.69453 val_acc= 0.54098 time= 0.01563
Epoch: 0012 train_loss= 0.69459 train_acc= 0.51515 val_loss= 0.69426 val_acc= 0.54098 time= 0.01563
Epoch: 0013 train_loss= 0.69429 train_acc= 0.51515 val_loss= 0.69401 val_acc= 0.54098 time= 0.01563
Epoch: 0014 train_loss= 0.69401 train_acc= 0.51515 val_loss= 0.69379 val_acc= 0.54098 time= 0.00000
Epoch: 0015 train_loss= 0.69368 train_acc= 0.51515 val_loss= 0.69361 val_acc= 0.54098 time= 0.01563
Epoch: 0016 train_loss= 0.69355 train_acc= 0.51515 val_loss= 0.69345 val_acc= 0.54098 time= 0.01563
Epoch: 0017 train_loss= 0.69356 train_acc= 0.51515 val_loss= 0.69331 val_acc= 0.54098 time= 0.01563
Epoch: 0018 train_loss= 0.69334 train_acc= 0.51515 val_loss= 0.69320 val_acc= 0.54098 time= 0.00000
Epoch: 0019 train_loss= 0.69307 train_acc= 0.51515 val_loss= 0.69310 val_acc= 0.54098 time= 0.01563
Epoch: 0020 train_loss= 0.69349 train_acc= 0.51515 val_loss= 0.69301 val_acc= 0.54098 time= 0.01563
Epoch: 0021 train_loss= 0.69330 train_acc= 0.51515 val_loss= 0.69292 val_acc= 0.54098 time= 0.01562
Epoch: 0022 train_loss= 0.69296 train_acc= 0.51515 val_loss= 0.69284 val_acc= 0.54098 time= 0.00000
Epoch: 0023 train_loss= 0.69322 train_acc= 0.51515 val_loss= 0.69276 val_acc= 0.54098 time= 0.01563
Epoch: 0024 train_loss= 0.69283 train_acc= 0.51515 val_loss= 0.69270 val_acc= 0.54098 time= 0.01563
Epoch: 0025 train_loss= 0.69257 train_acc= 0.51515 val_loss= 0.69265 val_acc= 0.54098 time= 0.01563
Epoch: 0026 train_loss= 0.69305 train_acc= 0.51515 val_loss= 0.69261 val_acc= 0.54098 time= 0.00000
Epoch: 0027 train_loss= 0.69264 train_acc= 0.51515 val_loss= 0.69257 val_acc= 0.54098 time= 0.01563
Epoch: 0028 train_loss= 0.69286 train_acc= 0.51515 val_loss= 0.69255 val_acc= 0.54098 time= 0.01563
Epoch: 0029 train_loss= 0.69233 train_acc= 0.51515 val_loss= 0.69253 val_acc= 0.54098 time= 0.01563
Epoch: 0030 train_loss= 0.69272 train_acc= 0.51515 val_loss= 0.69251 val_acc= 0.54098 time= 0.01563
Epoch: 0031 train_loss= 0.69289 train_acc= 0.51515 val_loss= 0.69250 val_acc= 0.54098 time= 0.00000
Epoch: 0032 train_loss= 0.69281 train_acc= 0.51515 val_loss= 0.69248 val_acc= 0.54098 time= 0.01563
Epoch: 0033 train_loss= 0.69252 train_acc= 0.51515 val_loss= 0.69247 val_acc= 0.54098 time= 0.01563
Epoch: 0034 train_loss= 0.69255 train_acc= 0.51515 val_loss= 0.69246 val_acc= 0.54098 time= 0.01563
Epoch: 0035 train_loss= 0.69282 train_acc= 0.51515 val_loss= 0.69245 val_acc= 0.54098 time= 0.01563
Epoch: 0036 train_loss= 0.69252 train_acc= 0.51515 val_loss= 0.69244 val_acc= 0.54098 time= 0.00000
Epoch: 0037 train_loss= 0.69275 train_acc= 0.51515 val_loss= 0.69244 val_acc= 0.54098 time= 0.01563
Epoch: 0038 train_loss= 0.69276 train_acc= 0.51515 val_loss= 0.69244 val_acc= 0.54098 time= 0.01563
Epoch: 0039 train_loss= 0.69238 train_acc= 0.51515 val_loss= 0.69243 val_acc= 0.54098 time= 0.01562
Epoch: 0040 train_loss= 0.69271 train_acc= 0.51515 val_loss= 0.69243 val_acc= 0.54098 time= 0.00000
Epoch: 0041 train_loss= 0.69287 train_acc= 0.51515 val_loss= 0.69243 val_acc= 0.54098 time= 0.01563
Epoch: 0042 train_loss= 0.69264 train_acc= 0.51515 val_loss= 0.69242 val_acc= 0.54098 time= 0.01563
Epoch: 0043 train_loss= 0.69239 train_acc= 0.51515 val_loss= 0.69242 val_acc= 0.54098 time= 0.01563
Epoch: 0044 train_loss= 0.69251 train_acc= 0.51515 val_loss= 0.69241 val_acc= 0.54098 time= 0.01563
Epoch: 0045 train_loss= 0.69263 train_acc= 0.51515 val_loss= 0.69241 val_acc= 0.54098 time= 0.00000
Epoch: 0046 train_loss= 0.69241 train_acc= 0.51515 val_loss= 0.69240 val_acc= 0.54098 time= 0.01563
Epoch: 0047 train_loss= 0.69256 train_acc= 0.51515 val_loss= 0.69240 val_acc= 0.54098 time= 0.01563
Epoch: 0048 train_loss= 0.69252 train_acc= 0.51515 val_loss= 0.69240 val_acc= 0.54098 time= 0.01563
Epoch: 0049 train_loss= 0.69239 train_acc= 0.51515 val_loss= 0.69240 val_acc= 0.54098 time= 0.00000
Epoch: 0050 train_loss= 0.69247 train_acc= 0.51515 val_loss= 0.69239 val_acc= 0.54098 time= 0.01563
Epoch: 0051 train_loss= 0.69254 train_acc= 0.51515 val_loss= 0.69239 val_acc= 0.54098 time= 0.01563
Epoch: 0052 train_loss= 0.69243 train_acc= 0.51515 val_loss= 0.69240 val_acc= 0.54098 time= 0.01563
Epoch: 0053 train_loss= 0.69251 train_acc= 0.51515 val_loss= 0.69240 val_acc= 0.54098 time= 0.01563
Epoch: 0054 train_loss= 0.69264 train_acc= 0.51515 val_loss= 0.69240 val_acc= 0.54098 time= 0.00000
Early stopping...
Optimization Finished!
Test set results: cost= 0.68996 accuracy= 0.54918 time= 0.01563 
