Epoch: 0001 train_loss= 1.39130 train_acc= 0.21094 val_loss= 1.38421 val_acc= 0.21429 time= 0.54691
Epoch: 0002 train_loss= 1.39043 train_acc= 0.20703 val_loss= 1.38380 val_acc= 0.21429 time= 0.00000
Epoch: 0003 train_loss= 1.38972 train_acc= 0.20117 val_loss= 1.38345 val_acc= 0.25000 time= 0.01563
Epoch: 0004 train_loss= 1.38823 train_acc= 0.24609 val_loss= 1.38314 val_acc= 0.37500 time= 0.00000
Epoch: 0005 train_loss= 1.38824 train_acc= 0.25781 val_loss= 1.38288 val_acc= 0.33929 time= 0.00000
Epoch: 0006 train_loss= 1.38672 train_acc= 0.30469 val_loss= 1.38262 val_acc= 0.32143 time= 0.01563
Epoch: 0007 train_loss= 1.38556 train_acc= 0.30469 val_loss= 1.38236 val_acc= 0.32143 time= 0.00000
Epoch: 0008 train_loss= 1.38464 train_acc= 0.30664 val_loss= 1.38210 val_acc= 0.32143 time= 0.01563
Epoch: 0009 train_loss= 1.38496 train_acc= 0.30859 val_loss= 1.38184 val_acc= 0.32143 time= 0.00000
Epoch: 0010 train_loss= 1.38327 train_acc= 0.30859 val_loss= 1.38156 val_acc= 0.32143 time= 0.01563
Epoch: 0011 train_loss= 1.38273 train_acc= 0.30859 val_loss= 1.38127 val_acc= 0.32143 time= 0.00000
Epoch: 0012 train_loss= 1.38255 train_acc= 0.31055 val_loss= 1.38097 val_acc= 0.32143 time= 0.01563
Epoch: 0013 train_loss= 1.38243 train_acc= 0.30859 val_loss= 1.38067 val_acc= 0.32143 time= 0.00000
Epoch: 0014 train_loss= 1.38147 train_acc= 0.30859 val_loss= 1.38036 val_acc= 0.32143 time= 0.00000
Epoch: 0015 train_loss= 1.38092 train_acc= 0.30859 val_loss= 1.38004 val_acc= 0.32143 time= 0.01563
Epoch: 0016 train_loss= 1.38225 train_acc= 0.30859 val_loss= 1.37972 val_acc= 0.32143 time= 0.00000
Epoch: 0017 train_loss= 1.37912 train_acc= 0.31055 val_loss= 1.37941 val_acc= 0.32143 time= 0.01563
Epoch: 0018 train_loss= 1.38069 train_acc= 0.30859 val_loss= 1.37913 val_acc= 0.32143 time= 0.00000
Epoch: 0019 train_loss= 1.38024 train_acc= 0.30859 val_loss= 1.37888 val_acc= 0.32143 time= 0.01563
Epoch: 0020 train_loss= 1.37833 train_acc= 0.30859 val_loss= 1.37866 val_acc= 0.32143 time= 0.00000
Epoch: 0021 train_loss= 1.37864 train_acc= 0.30859 val_loss= 1.37845 val_acc= 0.32143 time= 0.00000
Epoch: 0022 train_loss= 1.37861 train_acc= 0.30859 val_loss= 1.37826 val_acc= 0.32143 time= 0.01563
Epoch: 0023 train_loss= 1.37876 train_acc= 0.30859 val_loss= 1.37804 val_acc= 0.32143 time= 0.00000
Epoch: 0024 train_loss= 1.37873 train_acc= 0.30859 val_loss= 1.37784 val_acc= 0.32143 time= 0.01563
Epoch: 0025 train_loss= 1.37893 train_acc= 0.30859 val_loss= 1.37766 val_acc= 0.32143 time= 0.00000
Epoch: 0026 train_loss= 1.37762 train_acc= 0.30859 val_loss= 1.37750 val_acc= 0.32143 time= 0.01563
Epoch: 0027 train_loss= 1.37919 train_acc= 0.30859 val_loss= 1.37738 val_acc= 0.32143 time= 0.00000
Epoch: 0028 train_loss= 1.37869 train_acc= 0.30859 val_loss= 1.37730 val_acc= 0.32143 time= 0.01563
Epoch: 0029 train_loss= 1.37943 train_acc= 0.30859 val_loss= 1.37724 val_acc= 0.32143 time= 0.00000
Epoch: 0030 train_loss= 1.37865 train_acc= 0.30859 val_loss= 1.37722 val_acc= 0.32143 time= 0.00000
Epoch: 0031 train_loss= 1.37770 train_acc= 0.30859 val_loss= 1.37721 val_acc= 0.32143 time= 0.01563
Epoch: 0032 train_loss= 1.37699 train_acc= 0.30859 val_loss= 1.37724 val_acc= 0.32143 time= 0.00000
Epoch: 0033 train_loss= 1.37856 train_acc= 0.30859 val_loss= 1.37724 val_acc= 0.32143 time= 0.01562
Epoch: 0034 train_loss= 1.37667 train_acc= 0.30859 val_loss= 1.37727 val_acc= 0.32143 time= 0.00000
Epoch: 0035 train_loss= 1.37741 train_acc= 0.30859 val_loss= 1.37735 val_acc= 0.32143 time= 0.01563
Early stopping...
Optimization Finished!
Test set results: cost= 1.38159 accuracy= 0.29204 time= 0.00000 
