Epoch: 0001 train_loss= 2.09280 train_acc= 0.07817 val_loss= 2.09819 val_acc= 0.06897 time= 0.78130
Epoch: 0002 train_loss= 2.08951 train_acc= 0.06739 val_loss= 2.09664 val_acc= 0.06897 time= 0.01563
Epoch: 0003 train_loss= 2.08794 train_acc= 0.07817 val_loss= 2.09500 val_acc= 0.10345 time= 0.00000
Epoch: 0004 train_loss= 2.08574 train_acc= 0.14825 val_loss= 2.09330 val_acc= 0.10345 time= 0.01563
Epoch: 0005 train_loss= 2.08271 train_acc= 0.15364 val_loss= 2.09161 val_acc= 0.10345 time= 0.00000
Epoch: 0006 train_loss= 2.08083 train_acc= 0.16173 val_loss= 2.08982 val_acc= 0.10345 time= 0.00000
Epoch: 0007 train_loss= 2.07845 train_acc= 0.15903 val_loss= 2.08814 val_acc= 0.10345 time= 0.01563
Epoch: 0008 train_loss= 2.07571 train_acc= 0.15633 val_loss= 2.08651 val_acc= 0.10345 time= 0.00000
Epoch: 0009 train_loss= 2.07593 train_acc= 0.16173 val_loss= 2.08496 val_acc= 0.10345 time= 0.00000
Epoch: 0010 train_loss= 2.07362 train_acc= 0.15903 val_loss= 2.08352 val_acc= 0.10345 time= 0.00000
Epoch: 0011 train_loss= 2.07044 train_acc= 0.15633 val_loss= 2.08217 val_acc= 0.10345 time= 0.01563
Epoch: 0012 train_loss= 2.06953 train_acc= 0.15903 val_loss= 2.08095 val_acc= 0.10345 time= 0.00000
Epoch: 0013 train_loss= 2.06735 train_acc= 0.15903 val_loss= 2.07977 val_acc= 0.10345 time= 0.01563
Epoch: 0014 train_loss= 2.06489 train_acc= 0.16981 val_loss= 2.07877 val_acc= 0.10345 time= 0.00000
Epoch: 0015 train_loss= 2.06417 train_acc= 0.15903 val_loss= 2.07784 val_acc= 0.10345 time= 0.00000
Epoch: 0016 train_loss= 2.06295 train_acc= 0.15903 val_loss= 2.07670 val_acc= 0.10345 time= 0.01563
Epoch: 0017 train_loss= 2.06051 train_acc= 0.16442 val_loss= 2.07569 val_acc= 0.10345 time= 0.00000
Epoch: 0018 train_loss= 2.05998 train_acc= 0.16173 val_loss= 2.07455 val_acc= 0.10345 time= 0.00000
Epoch: 0019 train_loss= 2.05739 train_acc= 0.15633 val_loss= 2.07317 val_acc= 0.10345 time= 0.01563
Epoch: 0020 train_loss= 2.05605 train_acc= 0.14825 val_loss= 2.07154 val_acc= 0.10345 time= 0.00000
Epoch: 0021 train_loss= 2.05746 train_acc= 0.16981 val_loss= 2.06961 val_acc= 0.10345 time= 0.01563
Epoch: 0022 train_loss= 2.05865 train_acc= 0.15903 val_loss= 2.06752 val_acc= 0.10345 time= 0.00000
Epoch: 0023 train_loss= 2.05398 train_acc= 0.15364 val_loss= 2.06524 val_acc= 0.17241 time= 0.01563
Epoch: 0024 train_loss= 2.05531 train_acc= 0.15094 val_loss= 2.06285 val_acc= 0.13793 time= 0.00000
Epoch: 0025 train_loss= 2.05481 train_acc= 0.17520 val_loss= 2.06083 val_acc= 0.13793 time= 0.00000
Epoch: 0026 train_loss= 2.05660 train_acc= 0.15903 val_loss= 2.05874 val_acc= 0.13793 time= 0.01563
Epoch: 0027 train_loss= 2.05501 train_acc= 0.18329 val_loss= 2.05696 val_acc= 0.13793 time= 0.00000
Epoch: 0028 train_loss= 2.05247 train_acc= 0.17790 val_loss= 2.05561 val_acc= 0.13793 time= 0.01563
Epoch: 0029 train_loss= 2.05320 train_acc= 0.15903 val_loss= 2.05448 val_acc= 0.13793 time= 0.00000
Epoch: 0030 train_loss= 2.05366 train_acc= 0.16173 val_loss= 2.05349 val_acc= 0.13793 time= 0.00000
Epoch: 0031 train_loss= 2.05477 train_acc= 0.16173 val_loss= 2.05287 val_acc= 0.13793 time= 0.01563
Epoch: 0032 train_loss= 2.05500 train_acc= 0.17251 val_loss= 2.05234 val_acc= 0.13793 time= 0.00000
Epoch: 0033 train_loss= 2.05344 train_acc= 0.16981 val_loss= 2.05212 val_acc= 0.13793 time= 0.00000
Epoch: 0034 train_loss= 2.05345 train_acc= 0.16981 val_loss= 2.05200 val_acc= 0.13793 time= 0.01563
Epoch: 0035 train_loss= 2.05546 train_acc= 0.16981 val_loss= 2.05180 val_acc= 0.13793 time= 0.00000
Epoch: 0036 train_loss= 2.05272 train_acc= 0.16712 val_loss= 2.05156 val_acc= 0.13793 time= 0.00000
Epoch: 0037 train_loss= 2.06005 train_acc= 0.16981 val_loss= 2.05139 val_acc= 0.13793 time= 0.01563
Epoch: 0038 train_loss= 2.05446 train_acc= 0.17251 val_loss= 2.05159 val_acc= 0.13793 time= 0.00000
Epoch: 0039 train_loss= 2.05440 train_acc= 0.16712 val_loss= 2.05208 val_acc= 0.13793 time= 0.00000
Epoch: 0040 train_loss= 2.05642 train_acc= 0.15903 val_loss= 2.05246 val_acc= 0.13793 time= 0.01563
Early stopping...
Optimization Finished!
Test set results: cost= 2.08393 accuracy= 0.10169 time= 0.00000 
