Epoch: 0001 train_loss= 1.39415 train_acc= 0.23464 val_loss= 1.39034 val_acc= 0.35714 time= 0.37503
Epoch: 0002 train_loss= 1.39099 train_acc= 0.29190 val_loss= 1.38664 val_acc= 0.35714 time= 0.01563
Epoch: 0003 train_loss= 1.38841 train_acc= 0.29190 val_loss= 1.38322 val_acc= 0.35714 time= 0.01563
Epoch: 0004 train_loss= 1.38637 train_acc= 0.29190 val_loss= 1.38014 val_acc= 0.35714 time= 0.01563
Epoch: 0005 train_loss= 1.38486 train_acc= 0.29190 val_loss= 1.37746 val_acc= 0.35714 time= 0.01563
Epoch: 0006 train_loss= 1.38400 train_acc= 0.29190 val_loss= 1.37522 val_acc= 0.35714 time= 0.01563
Epoch: 0007 train_loss= 1.38341 train_acc= 0.29190 val_loss= 1.37335 val_acc= 0.35714 time= 0.01563
Epoch: 0008 train_loss= 1.38309 train_acc= 0.29190 val_loss= 1.37180 val_acc= 0.35714 time= 0.01563
Epoch: 0009 train_loss= 1.38295 train_acc= 0.29190 val_loss= 1.37054 val_acc= 0.35714 time= 0.01563
Epoch: 0010 train_loss= 1.38286 train_acc= 0.29190 val_loss= 1.36949 val_acc= 0.35714 time= 0.01563
Epoch: 0011 train_loss= 1.38274 train_acc= 0.29190 val_loss= 1.36862 val_acc= 0.35714 time= 0.03125
Epoch: 0012 train_loss= 1.38250 train_acc= 0.29190 val_loss= 1.36791 val_acc= 0.35714 time= 0.01563
Epoch: 0013 train_loss= 1.38259 train_acc= 0.29190 val_loss= 1.36737 val_acc= 0.35714 time= 0.01563
Epoch: 0014 train_loss= 1.38215 train_acc= 0.29190 val_loss= 1.36699 val_acc= 0.35714 time= 0.01563
Epoch: 0015 train_loss= 1.38204 train_acc= 0.29190 val_loss= 1.36674 val_acc= 0.35714 time= 0.01563
Epoch: 0016 train_loss= 1.38169 train_acc= 0.29190 val_loss= 1.36655 val_acc= 0.35714 time= 0.01563
Epoch: 0017 train_loss= 1.38150 train_acc= 0.29190 val_loss= 1.36637 val_acc= 0.35714 time= 0.01563
Epoch: 0018 train_loss= 1.38149 train_acc= 0.29190 val_loss= 1.36628 val_acc= 0.35714 time= 0.01563
Epoch: 0019 train_loss= 1.38118 train_acc= 0.29190 val_loss= 1.36614 val_acc= 0.35714 time= 0.01563
Epoch: 0020 train_loss= 1.38076 train_acc= 0.29190 val_loss= 1.36597 val_acc= 0.35714 time= 0.01563
Epoch: 0021 train_loss= 1.38077 train_acc= 0.29190 val_loss= 1.36576 val_acc= 0.35714 time= 0.01563
Epoch: 0022 train_loss= 1.38070 train_acc= 0.29190 val_loss= 1.36551 val_acc= 0.35714 time= 0.01563
Epoch: 0023 train_loss= 1.38032 train_acc= 0.29190 val_loss= 1.36519 val_acc= 0.35714 time= 0.01563
Epoch: 0024 train_loss= 1.38053 train_acc= 0.29190 val_loss= 1.36481 val_acc= 0.35714 time= 0.01563
Epoch: 0025 train_loss= 1.38041 train_acc= 0.29190 val_loss= 1.36439 val_acc= 0.35714 time= 0.01563
Epoch: 0026 train_loss= 1.38027 train_acc= 0.29190 val_loss= 1.36399 val_acc= 0.35714 time= 0.01563
Epoch: 0027 train_loss= 1.38064 train_acc= 0.29190 val_loss= 1.36374 val_acc= 0.35714 time= 0.01563
Epoch: 0028 train_loss= 1.38013 train_acc= 0.29190 val_loss= 1.36345 val_acc= 0.35714 time= 0.01563
Epoch: 0029 train_loss= 1.37963 train_acc= 0.29190 val_loss= 1.36312 val_acc= 0.35714 time= 0.01563
Epoch: 0030 train_loss= 1.37970 train_acc= 0.29190 val_loss= 1.36292 val_acc= 0.35714 time= 0.03125
Epoch: 0031 train_loss= 1.37961 train_acc= 0.29190 val_loss= 1.36279 val_acc= 0.35714 time= 0.01563
Epoch: 0032 train_loss= 1.37943 train_acc= 0.29190 val_loss= 1.36260 val_acc= 0.35714 time= 0.01563
Epoch: 0033 train_loss= 1.37944 train_acc= 0.29190 val_loss= 1.36243 val_acc= 0.35714 time= 0.01563
Epoch: 0034 train_loss= 1.37976 train_acc= 0.29190 val_loss= 1.36228 val_acc= 0.35714 time= 0.01563
Epoch: 0035 train_loss= 1.37984 train_acc= 0.29190 val_loss= 1.36215 val_acc= 0.35714 time= 0.01563
Epoch: 0036 train_loss= 1.37969 train_acc= 0.29190 val_loss= 1.36197 val_acc= 0.35714 time= 0.01563
Epoch: 0037 train_loss= 1.37932 train_acc= 0.29190 val_loss= 1.36166 val_acc= 0.35714 time= 0.01563
Epoch: 0038 train_loss= 1.37949 train_acc= 0.29190 val_loss= 1.36137 val_acc= 0.35714 time= 0.01563
Epoch: 0039 train_loss= 1.37908 train_acc= 0.29190 val_loss= 1.36115 val_acc= 0.35714 time= 0.01563
Epoch: 0040 train_loss= 1.37915 train_acc= 0.29190 val_loss= 1.36112 val_acc= 0.35714 time= 0.01563
Epoch: 0041 train_loss= 1.37892 train_acc= 0.29190 val_loss= 1.36126 val_acc= 0.35714 time= 0.01563
Epoch: 0042 train_loss= 1.37937 train_acc= 0.29190 val_loss= 1.36153 val_acc= 0.35714 time= 0.01563
Epoch: 0043 train_loss= 1.37929 train_acc= 0.29190 val_loss= 1.36186 val_acc= 0.35714 time= 0.01563
Early stopping...
Optimization Finished!
Test set results: cost= 1.37749 accuracy= 0.29204 time= 0.01563 
