Epoch: 0001 train_loss= 1.39201 train_acc= 0.30168 val_loss= 1.39021 val_acc= 0.33929 time= 0.67250
Epoch: 0002 train_loss= 1.39048 train_acc= 0.30168 val_loss= 1.38900 val_acc= 0.33929 time= 0.01562
Epoch: 0003 train_loss= 1.38933 train_acc= 0.30168 val_loss= 1.38789 val_acc= 0.33929 time= 0.00000
Epoch: 0004 train_loss= 1.38832 train_acc= 0.30168 val_loss= 1.38677 val_acc= 0.33929 time= 0.01563
Epoch: 0005 train_loss= 1.38726 train_acc= 0.30168 val_loss= 1.38569 val_acc= 0.33929 time= 0.01563
Epoch: 0006 train_loss= 1.38571 train_acc= 0.30168 val_loss= 1.38466 val_acc= 0.33929 time= 0.02125
Epoch: 0007 train_loss= 1.38506 train_acc= 0.30168 val_loss= 1.38370 val_acc= 0.33929 time= 0.01050
Epoch: 0008 train_loss= 1.38393 train_acc= 0.30168 val_loss= 1.38285 val_acc= 0.33929 time= 0.01563
Epoch: 0009 train_loss= 1.38355 train_acc= 0.30168 val_loss= 1.38214 val_acc= 0.33929 time= 0.01562
Epoch: 0010 train_loss= 1.38301 train_acc= 0.30168 val_loss= 1.38156 val_acc= 0.33929 time= 0.01563
Epoch: 0011 train_loss= 1.38232 train_acc= 0.30168 val_loss= 1.38112 val_acc= 0.33929 time= 0.01563
Epoch: 0012 train_loss= 1.38202 train_acc= 0.30168 val_loss= 1.38079 val_acc= 0.33929 time= 0.01562
Epoch: 0013 train_loss= 1.38238 train_acc= 0.30168 val_loss= 1.38055 val_acc= 0.33929 time= 0.00000
Epoch: 0014 train_loss= 1.38098 train_acc= 0.30168 val_loss= 1.38041 val_acc= 0.33929 time= 0.01563
Epoch: 0015 train_loss= 1.38142 train_acc= 0.30168 val_loss= 1.38034 val_acc= 0.33929 time= 0.01563
Epoch: 0016 train_loss= 1.38085 train_acc= 0.30168 val_loss= 1.38032 val_acc= 0.33929 time= 0.01563
Epoch: 0017 train_loss= 1.38018 train_acc= 0.30168 val_loss= 1.38031 val_acc= 0.33929 time= 0.01563
Epoch: 0018 train_loss= 1.38216 train_acc= 0.30168 val_loss= 1.38030 val_acc= 0.33929 time= 0.03125
Epoch: 0019 train_loss= 1.38186 train_acc= 0.30168 val_loss= 1.38028 val_acc= 0.33929 time= 0.01563
Epoch: 0020 train_loss= 1.38105 train_acc= 0.30168 val_loss= 1.38026 val_acc= 0.33929 time= 0.01563
Epoch: 0021 train_loss= 1.37932 train_acc= 0.30168 val_loss= 1.38023 val_acc= 0.33929 time= 0.00000
Epoch: 0022 train_loss= 1.38080 train_acc= 0.30168 val_loss= 1.38020 val_acc= 0.33929 time= 0.01563
Epoch: 0023 train_loss= 1.37982 train_acc= 0.30168 val_loss= 1.38014 val_acc= 0.33929 time= 0.01563
Epoch: 0024 train_loss= 1.38105 train_acc= 0.30168 val_loss= 1.38008 val_acc= 0.33929 time= 0.01563
Epoch: 0025 train_loss= 1.38034 train_acc= 0.30168 val_loss= 1.37999 val_acc= 0.33929 time= 0.01563
Epoch: 0026 train_loss= 1.37912 train_acc= 0.30168 val_loss= 1.37989 val_acc= 0.33929 time= 0.01562
Epoch: 0027 train_loss= 1.37991 train_acc= 0.30168 val_loss= 1.37979 val_acc= 0.33929 time= 0.01563
Epoch: 0028 train_loss= 1.37995 train_acc= 0.30168 val_loss= 1.37967 val_acc= 0.33929 time= 0.01563
Epoch: 0029 train_loss= 1.38010 train_acc= 0.30168 val_loss= 1.37954 val_acc= 0.33929 time= 0.00000
Epoch: 0030 train_loss= 1.37922 train_acc= 0.30168 val_loss= 1.37942 val_acc= 0.33929 time= 0.01563
Epoch: 0031 train_loss= 1.37915 train_acc= 0.30168 val_loss= 1.37930 val_acc= 0.33929 time= 0.01563
Epoch: 0032 train_loss= 1.38023 train_acc= 0.30168 val_loss= 1.37918 val_acc= 0.33929 time= 0.01563
Epoch: 0033 train_loss= 1.37912 train_acc= 0.30168 val_loss= 1.37902 val_acc= 0.33929 time= 0.01563
Epoch: 0034 train_loss= 1.37946 train_acc= 0.30168 val_loss= 1.37888 val_acc= 0.33929 time= 0.01563
Epoch: 0035 train_loss= 1.37904 train_acc= 0.30168 val_loss= 1.37877 val_acc= 0.33929 time= 0.01562
Epoch: 0036 train_loss= 1.37904 train_acc= 0.30168 val_loss= 1.37865 val_acc= 0.33929 time= 0.01563
Epoch: 0037 train_loss= 1.37964 train_acc= 0.30168 val_loss= 1.37858 val_acc= 0.33929 time= 0.00000
Epoch: 0038 train_loss= 1.37858 train_acc= 0.30168 val_loss= 1.37852 val_acc= 0.33929 time= 0.01563
Epoch: 0039 train_loss= 1.37918 train_acc= 0.30168 val_loss= 1.37848 val_acc= 0.33929 time= 0.01563
Epoch: 0040 train_loss= 1.37947 train_acc= 0.30168 val_loss= 1.37850 val_acc= 0.33929 time= 0.01563
Epoch: 0041 train_loss= 1.37890 train_acc= 0.30168 val_loss= 1.37854 val_acc= 0.33929 time= 0.01562
Epoch: 0042 train_loss= 1.37886 train_acc= 0.30168 val_loss= 1.37861 val_acc= 0.33929 time= 0.01563
Epoch: 0043 train_loss= 1.37885 train_acc= 0.30168 val_loss= 1.37868 val_acc= 0.33929 time= 0.01563
Early stopping...
Optimization Finished!
Test set results: cost= 1.35090 accuracy= 0.36283 time= 0.00000 
