Epoch: 0001 train_loss= 2.08772 train_acc= 0.07008 val_loss= 2.08427 val_acc= 0.13793 time= 0.39066
Epoch: 0002 train_loss= 2.08493 train_acc= 0.14016 val_loss= 2.08116 val_acc= 0.13793 time= 0.00000
Epoch: 0003 train_loss= 2.08271 train_acc= 0.13747 val_loss= 2.07811 val_acc= 0.13793 time= 0.01562
Epoch: 0004 train_loss= 2.08045 train_acc= 0.14016 val_loss= 2.07518 val_acc= 0.13793 time= 0.00000
Epoch: 0005 train_loss= 2.07835 train_acc= 0.14016 val_loss= 2.07237 val_acc= 0.13793 time= 0.01563
Epoch: 0006 train_loss= 2.07688 train_acc= 0.13747 val_loss= 2.06966 val_acc= 0.13793 time= 0.00000
Epoch: 0007 train_loss= 2.07523 train_acc= 0.15094 val_loss= 2.06713 val_acc= 0.13793 time= 0.01563
Epoch: 0008 train_loss= 2.07393 train_acc= 0.17251 val_loss= 2.06473 val_acc= 0.13793 time= 0.01563
Epoch: 0009 train_loss= 2.07256 train_acc= 0.16712 val_loss= 2.06244 val_acc= 0.24138 time= 0.00000
Epoch: 0010 train_loss= 2.07106 train_acc= 0.15094 val_loss= 2.06024 val_acc= 0.24138 time= 0.01563
Epoch: 0011 train_loss= 2.07022 train_acc= 0.16442 val_loss= 2.05817 val_acc= 0.24138 time= 0.00000
Epoch: 0012 train_loss= 2.06877 train_acc= 0.16712 val_loss= 2.05621 val_acc= 0.24138 time= 0.01562
Epoch: 0013 train_loss= 2.06804 train_acc= 0.17520 val_loss= 2.05445 val_acc= 0.24138 time= 0.00000
Epoch: 0014 train_loss= 2.06706 train_acc= 0.17251 val_loss= 2.05284 val_acc= 0.24138 time= 0.01563
Epoch: 0015 train_loss= 2.06538 train_acc= 0.17251 val_loss= 2.05139 val_acc= 0.24138 time= 0.01563
Epoch: 0016 train_loss= 2.06485 train_acc= 0.17251 val_loss= 2.05006 val_acc= 0.24138 time= 0.00000
Epoch: 0017 train_loss= 2.06462 train_acc= 0.17251 val_loss= 2.04888 val_acc= 0.24138 time= 0.01563
Epoch: 0018 train_loss= 2.06397 train_acc= 0.17251 val_loss= 2.04790 val_acc= 0.24138 time= 0.00000
Epoch: 0019 train_loss= 2.06341 train_acc= 0.17251 val_loss= 2.04709 val_acc= 0.24138 time= 0.01563
Epoch: 0020 train_loss= 2.06311 train_acc= 0.16981 val_loss= 2.04642 val_acc= 0.24138 time= 0.01563
Epoch: 0021 train_loss= 2.06312 train_acc= 0.17251 val_loss= 2.04574 val_acc= 0.24138 time= 0.00000
Epoch: 0022 train_loss= 2.06327 train_acc= 0.17520 val_loss= 2.04499 val_acc= 0.24138 time= 0.01563
Epoch: 0023 train_loss= 2.06176 train_acc= 0.17251 val_loss= 2.04431 val_acc= 0.24138 time= 0.00000
Epoch: 0024 train_loss= 2.06190 train_acc= 0.17251 val_loss= 2.04359 val_acc= 0.24138 time= 0.01563
Epoch: 0025 train_loss= 2.06065 train_acc= 0.17251 val_loss= 2.04301 val_acc= 0.24138 time= 0.01563
Epoch: 0026 train_loss= 2.06124 train_acc= 0.17251 val_loss= 2.04241 val_acc= 0.24138 time= 0.00000
Epoch: 0027 train_loss= 2.06020 train_acc= 0.17251 val_loss= 2.04185 val_acc= 0.24138 time= 0.01563
Epoch: 0028 train_loss= 2.06034 train_acc= 0.17251 val_loss= 2.04138 val_acc= 0.24138 time= 0.00000
Epoch: 0029 train_loss= 2.05960 train_acc= 0.17251 val_loss= 2.04099 val_acc= 0.24138 time= 0.01563
Epoch: 0030 train_loss= 2.05871 train_acc= 0.17251 val_loss= 2.04061 val_acc= 0.24138 time= 0.01563
Epoch: 0031 train_loss= 2.05953 train_acc= 0.17251 val_loss= 2.04036 val_acc= 0.24138 time= 0.00000
Epoch: 0032 train_loss= 2.05863 train_acc= 0.17251 val_loss= 2.04012 val_acc= 0.24138 time= 0.01563
Epoch: 0033 train_loss= 2.05796 train_acc= 0.17251 val_loss= 2.03992 val_acc= 0.24138 time= 0.00000
Epoch: 0034 train_loss= 2.05822 train_acc= 0.17251 val_loss= 2.03963 val_acc= 0.24138 time= 0.01563
Epoch: 0035 train_loss= 2.05812 train_acc= 0.17251 val_loss= 2.03922 val_acc= 0.24138 time= 0.01563
Epoch: 0036 train_loss= 2.05806 train_acc= 0.17251 val_loss= 2.03882 val_acc= 0.24138 time= 0.00000
Epoch: 0037 train_loss= 2.05783 train_acc= 0.17251 val_loss= 2.03850 val_acc= 0.24138 time= 0.01563
Epoch: 0038 train_loss= 2.05733 train_acc= 0.17251 val_loss= 2.03809 val_acc= 0.24138 time= 0.00000
Epoch: 0039 train_loss= 2.05605 train_acc= 0.17251 val_loss= 2.03775 val_acc= 0.24138 time= 0.01563
Epoch: 0040 train_loss= 2.05765 train_acc= 0.17251 val_loss= 2.03752 val_acc= 0.24138 time= 0.00000
Epoch: 0041 train_loss= 2.05700 train_acc= 0.17251 val_loss= 2.03730 val_acc= 0.24138 time= 0.01563
Epoch: 0042 train_loss= 2.05593 train_acc= 0.17251 val_loss= 2.03711 val_acc= 0.24138 time= 0.01563
Epoch: 0043 train_loss= 2.05626 train_acc= 0.17251 val_loss= 2.03700 val_acc= 0.24138 time= 0.00000
Epoch: 0044 train_loss= 2.05599 train_acc= 0.17251 val_loss= 2.03695 val_acc= 0.24138 time= 0.01563
Epoch: 0045 train_loss= 2.05665 train_acc= 0.17251 val_loss= 2.03696 val_acc= 0.24138 time= 0.00000
Epoch: 0046 train_loss= 2.05626 train_acc= 0.17251 val_loss= 2.03694 val_acc= 0.24138 time= 0.01563
Epoch: 0047 train_loss= 2.05579 train_acc= 0.17251 val_loss= 2.03701 val_acc= 0.24138 time= 0.01563
Epoch: 0048 train_loss= 2.05579 train_acc= 0.17251 val_loss= 2.03700 val_acc= 0.24138 time= 0.00000
Epoch: 0049 train_loss= 2.05557 train_acc= 0.17251 val_loss= 2.03692 val_acc= 0.24138 time= 0.01563
Epoch: 0050 train_loss= 2.05576 train_acc= 0.17251 val_loss= 2.03686 val_acc= 0.24138 time= 0.00000
Epoch: 0051 train_loss= 2.05502 train_acc= 0.17251 val_loss= 2.03662 val_acc= 0.24138 time= 0.01563
Epoch: 0052 train_loss= 2.05549 train_acc= 0.17251 val_loss= 2.03637 val_acc= 0.24138 time= 0.01563
Epoch: 0053 train_loss= 2.05497 train_acc= 0.17251 val_loss= 2.03620 val_acc= 0.24138 time= 0.00000
Epoch: 0054 train_loss= 2.05543 train_acc= 0.17251 val_loss= 2.03609 val_acc= 0.24138 time= 0.01563
Epoch: 0055 train_loss= 2.05525 train_acc= 0.17251 val_loss= 2.03597 val_acc= 0.24138 time= 0.00000
Epoch: 0056 train_loss= 2.05543 train_acc= 0.17251 val_loss= 2.03596 val_acc= 0.24138 time= 0.01563
Epoch: 0057 train_loss= 2.05445 train_acc= 0.17251 val_loss= 2.03583 val_acc= 0.24138 time= 0.01563
Epoch: 0058 train_loss= 2.05550 train_acc= 0.17251 val_loss= 2.03590 val_acc= 0.24138 time= 0.00000
Epoch: 0059 train_loss= 2.05509 train_acc= 0.17251 val_loss= 2.03583 val_acc= 0.24138 time= 0.01562
Epoch: 0060 train_loss= 2.05401 train_acc= 0.17251 val_loss= 2.03572 val_acc= 0.24138 time= 0.00000
Epoch: 0061 train_loss= 2.05505 train_acc= 0.17251 val_loss= 2.03552 val_acc= 0.24138 time= 0.01563
Epoch: 0062 train_loss= 2.05458 train_acc= 0.17251 val_loss= 2.03533 val_acc= 0.24138 time= 0.01563
Epoch: 0063 train_loss= 2.05428 train_acc= 0.17251 val_loss= 2.03533 val_acc= 0.24138 time= 0.00000
Epoch: 0064 train_loss= 2.05473 train_acc= 0.17251 val_loss= 2.03543 val_acc= 0.24138 time= 0.01563
Epoch: 0065 train_loss= 2.05412 train_acc= 0.17251 val_loss= 2.03547 val_acc= 0.24138 time= 0.00000
Epoch: 0066 train_loss= 2.05339 train_acc= 0.17251 val_loss= 2.03548 val_acc= 0.24138 time= 0.01563
Epoch: 0067 train_loss= 2.05424 train_acc= 0.17251 val_loss= 2.03533 val_acc= 0.24138 time= 0.01562
Epoch: 0068 train_loss= 2.05411 train_acc= 0.17251 val_loss= 2.03531 val_acc= 0.24138 time= 0.00000
Epoch: 0069 train_loss= 2.05395 train_acc= 0.17251 val_loss= 2.03538 val_acc= 0.24138 time= 0.01563
Epoch: 0070 train_loss= 2.05424 train_acc= 0.17251 val_loss= 2.03540 val_acc= 0.24138 time= 0.00000
Epoch: 0071 train_loss= 2.05358 train_acc= 0.17251 val_loss= 2.03532 val_acc= 0.24138 time= 0.01563
Epoch: 0072 train_loss= 2.05359 train_acc= 0.17251 val_loss= 2.03538 val_acc= 0.24138 time= 0.01563
Early stopping...
Optimization Finished!
Test set results: cost= 2.09912 accuracy= 0.16949 time= 0.00000 
