Epoch: 0001 train_loss= 0.69905 train_acc= 0.52468 val_loss= 0.69909 val_acc= 0.47541 time= 0.65115
Epoch: 0002 train_loss= 0.69753 train_acc= 0.52727 val_loss= 0.69938 val_acc= 0.47541 time= 0.01400
Epoch: 0003 train_loss= 0.69715 train_acc= 0.52338 val_loss= 0.69982 val_acc= 0.47541 time= 0.01300
Epoch: 0004 train_loss= 0.69731 train_acc= 0.52338 val_loss= 0.70002 val_acc= 0.47541 time= 0.01200
Epoch: 0005 train_loss= 0.69601 train_acc= 0.52468 val_loss= 0.69995 val_acc= 0.47541 time= 0.01200
Epoch: 0006 train_loss= 0.69613 train_acc= 0.52468 val_loss= 0.69960 val_acc= 0.47541 time= 0.01100
Epoch: 0007 train_loss= 0.69572 train_acc= 0.52468 val_loss= 0.69906 val_acc= 0.47541 time= 0.01400
Epoch: 0008 train_loss= 0.69489 train_acc= 0.52468 val_loss= 0.69845 val_acc= 0.47541 time= 0.01300
Epoch: 0009 train_loss= 0.69469 train_acc= 0.52597 val_loss= 0.69785 val_acc= 0.47541 time= 0.01300
Epoch: 0010 train_loss= 0.69462 train_acc= 0.52468 val_loss= 0.69728 val_acc= 0.47541 time= 0.01300
Epoch: 0011 train_loss= 0.69520 train_acc= 0.52338 val_loss= 0.69679 val_acc= 0.47541 time= 0.01400
Epoch: 0012 train_loss= 0.69392 train_acc= 0.52338 val_loss= 0.69640 val_acc= 0.47541 time= 0.01200
Epoch: 0013 train_loss= 0.69388 train_acc= 0.52468 val_loss= 0.69608 val_acc= 0.47541 time= 0.01200
Epoch: 0014 train_loss= 0.69412 train_acc= 0.52597 val_loss= 0.69579 val_acc= 0.47541 time= 0.01200
Epoch: 0015 train_loss= 0.69361 train_acc= 0.52468 val_loss= 0.69556 val_acc= 0.47541 time= 0.01400
Epoch: 0016 train_loss= 0.69350 train_acc= 0.52468 val_loss= 0.69537 val_acc= 0.47541 time= 0.01400
Epoch: 0017 train_loss= 0.69326 train_acc= 0.52468 val_loss= 0.69524 val_acc= 0.47541 time= 0.01500
Epoch: 0018 train_loss= 0.69293 train_acc= 0.52468 val_loss= 0.69514 val_acc= 0.47541 time= 0.01300
Epoch: 0019 train_loss= 0.69304 train_acc= 0.52468 val_loss= 0.69507 val_acc= 0.47541 time= 0.01400
Epoch: 0020 train_loss= 0.69299 train_acc= 0.52468 val_loss= 0.69501 val_acc= 0.47541 time= 0.01500
Epoch: 0021 train_loss= 0.69258 train_acc= 0.52338 val_loss= 0.69497 val_acc= 0.47541 time= 0.01500
Epoch: 0022 train_loss= 0.69240 train_acc= 0.52468 val_loss= 0.69494 val_acc= 0.47541 time= 0.01500
Epoch: 0023 train_loss= 0.69234 train_acc= 0.52468 val_loss= 0.69494 val_acc= 0.47541 time= 0.01400
Epoch: 0024 train_loss= 0.69228 train_acc= 0.52468 val_loss= 0.69493 val_acc= 0.47541 time= 0.01600
Epoch: 0025 train_loss= 0.69229 train_acc= 0.52468 val_loss= 0.69495 val_acc= 0.47541 time= 0.01597
Epoch: 0026 train_loss= 0.69178 train_acc= 0.52468 val_loss= 0.69501 val_acc= 0.47541 time= 0.01300
Epoch: 0027 train_loss= 0.69205 train_acc= 0.52468 val_loss= 0.69502 val_acc= 0.47541 time= 0.01300
Epoch: 0028 train_loss= 0.69211 train_acc= 0.52468 val_loss= 0.69496 val_acc= 0.47541 time= 0.01300
Epoch: 0029 train_loss= 0.69212 train_acc= 0.52468 val_loss= 0.69481 val_acc= 0.47541 time= 0.01200
Epoch: 0030 train_loss= 0.69173 train_acc= 0.52468 val_loss= 0.69466 val_acc= 0.47541 time= 0.01400
Epoch: 0031 train_loss= 0.69175 train_acc= 0.52468 val_loss= 0.69452 val_acc= 0.47541 time= 0.01300
Epoch: 0032 train_loss= 0.69137 train_acc= 0.52468 val_loss= 0.69441 val_acc= 0.47541 time= 0.01200
Epoch: 0033 train_loss= 0.69160 train_acc= 0.52468 val_loss= 0.69431 val_acc= 0.47541 time= 0.01200
Epoch: 0034 train_loss= 0.69148 train_acc= 0.52468 val_loss= 0.69425 val_acc= 0.47541 time= 0.01300
Epoch: 0035 train_loss= 0.69169 train_acc= 0.52468 val_loss= 0.69419 val_acc= 0.47541 time= 0.01500
Epoch: 0036 train_loss= 0.69189 train_acc= 0.52468 val_loss= 0.69413 val_acc= 0.47541 time= 0.01300
Epoch: 0037 train_loss= 0.69166 train_acc= 0.52468 val_loss= 0.69410 val_acc= 0.47541 time= 0.01700
Epoch: 0038 train_loss= 0.69177 train_acc= 0.52468 val_loss= 0.69409 val_acc= 0.47541 time= 0.01400
Epoch: 0039 train_loss= 0.69152 train_acc= 0.52468 val_loss= 0.69411 val_acc= 0.47541 time= 0.01400
Epoch: 0040 train_loss= 0.69157 train_acc= 0.52468 val_loss= 0.69414 val_acc= 0.47541 time= 0.01600
Epoch: 0041 train_loss= 0.69158 train_acc= 0.52468 val_loss= 0.69418 val_acc= 0.47541 time= 0.01400
Epoch: 0042 train_loss= 0.69170 train_acc= 0.52468 val_loss= 0.69420 val_acc= 0.47541 time= 0.01500
Early stopping...
Optimization Finished!
Test set results: cost= 0.69169 accuracy= 0.52459 time= 0.00700 
