Epoch: 0001 train_loss= 0.70096 train_acc= 0.49636 val_loss= 0.69750 val_acc= 0.54098 time= 0.26564
Epoch: 0002 train_loss= 0.69792 train_acc= 0.52000 val_loss= 0.69504 val_acc= 0.54098 time= 0.00000
Epoch: 0003 train_loss= 0.69568 train_acc= 0.52182 val_loss= 0.69331 val_acc= 0.54098 time= 0.01562
Epoch: 0004 train_loss= 0.69435 train_acc= 0.52182 val_loss= 0.69225 val_acc= 0.54098 time= 0.01563
Epoch: 0005 train_loss= 0.69347 train_acc= 0.52364 val_loss= 0.69168 val_acc= 0.54098 time= 0.00000
Epoch: 0006 train_loss= 0.69290 train_acc= 0.52182 val_loss= 0.69142 val_acc= 0.54098 time= 0.01563
Epoch: 0007 train_loss= 0.69250 train_acc= 0.52364 val_loss= 0.69139 val_acc= 0.54098 time= 0.01563
Epoch: 0008 train_loss= 0.69244 train_acc= 0.52545 val_loss= 0.69143 val_acc= 0.54098 time= 0.00000
Epoch: 0009 train_loss= 0.69212 train_acc= 0.52545 val_loss= 0.69144 val_acc= 0.54098 time= 0.01563
Epoch: 0010 train_loss= 0.69251 train_acc= 0.52727 val_loss= 0.69137 val_acc= 0.55738 time= 0.01563
Epoch: 0011 train_loss= 0.69256 train_acc= 0.52909 val_loss= 0.69126 val_acc= 0.57377 time= 0.00000
Epoch: 0012 train_loss= 0.69249 train_acc= 0.52909 val_loss= 0.69120 val_acc= 0.57377 time= 0.01563
Epoch: 0013 train_loss= 0.69201 train_acc= 0.53818 val_loss= 0.69100 val_acc= 0.57377 time= 0.01563
Epoch: 0014 train_loss= 0.69183 train_acc= 0.52727 val_loss= 0.69087 val_acc= 0.57377 time= 0.01563
Epoch: 0015 train_loss= 0.69140 train_acc= 0.55273 val_loss= 0.69058 val_acc= 0.57377 time= 0.00000
Epoch: 0016 train_loss= 0.69108 train_acc= 0.53636 val_loss= 0.69033 val_acc= 0.57377 time= 0.01563
Epoch: 0017 train_loss= 0.69115 train_acc= 0.54545 val_loss= 0.69002 val_acc= 0.57377 time= 0.01562
Epoch: 0018 train_loss= 0.69092 train_acc= 0.55273 val_loss= 0.68965 val_acc= 0.57377 time= 0.00000
Epoch: 0019 train_loss= 0.69082 train_acc= 0.53636 val_loss= 0.68930 val_acc= 0.57377 time= 0.01563
Epoch: 0020 train_loss= 0.69052 train_acc= 0.59636 val_loss= 0.68883 val_acc= 0.57377 time= 0.01563
Epoch: 0021 train_loss= 0.69029 train_acc= 0.55455 val_loss= 0.68836 val_acc= 0.57377 time= 0.00000
Epoch: 0022 train_loss= 0.68963 train_acc= 0.54909 val_loss= 0.68823 val_acc= 0.57377 time= 0.01563
Epoch: 0023 train_loss= 0.68984 train_acc= 0.56364 val_loss= 0.68824 val_acc= 0.57377 time= 0.01563
Epoch: 0024 train_loss= 0.68934 train_acc= 0.55091 val_loss= 0.68850 val_acc= 0.57377 time= 0.00000
Epoch: 0025 train_loss= 0.68943 train_acc= 0.58364 val_loss= 0.68874 val_acc= 0.62295 time= 0.01563
Epoch: 0026 train_loss= 0.68970 train_acc= 0.56909 val_loss= 0.68906 val_acc= 0.62295 time= 0.01563
Early stopping...
Optimization Finished!
Test set results: cost= 0.69461 accuracy= 0.51639 time= 0.00000 
