Epoch: 0001 train_loss= 1.39074 train_acc= 0.26384 val_loss= 1.38599 val_acc= 0.44643 time= 0.10937
Epoch: 0002 train_loss= 1.38873 train_acc= 0.32248 val_loss= 1.38138 val_acc= 0.44643 time= 0.01563
Epoch: 0003 train_loss= 1.38700 train_acc= 0.32573 val_loss= 1.37719 val_acc= 0.44643 time= 0.01563
Epoch: 0004 train_loss= 1.38531 train_acc= 0.32573 val_loss= 1.37334 val_acc= 0.44643 time= 0.01563
Epoch: 0005 train_loss= 1.38365 train_acc= 0.32573 val_loss= 1.36934 val_acc= 0.44643 time= 0.01563
Epoch: 0006 train_loss= 1.38202 train_acc= 0.32573 val_loss= 1.36522 val_acc= 0.44643 time= 0.01563
Epoch: 0007 train_loss= 1.38060 train_acc= 0.32573 val_loss= 1.36105 val_acc= 0.44643 time= 0.01563
Epoch: 0008 train_loss= 1.37821 train_acc= 0.32573 val_loss= 1.35691 val_acc= 0.44643 time= 0.01563
Epoch: 0009 train_loss= 1.37621 train_acc= 0.32573 val_loss= 1.35277 val_acc= 0.44643 time= 0.01563
Epoch: 0010 train_loss= 1.37552 train_acc= 0.32573 val_loss= 1.34875 val_acc= 0.44643 time= 0.01563
Epoch: 0011 train_loss= 1.37440 train_acc= 0.32573 val_loss= 1.34499 val_acc= 0.44643 time= 0.01563
Epoch: 0012 train_loss= 1.37355 train_acc= 0.32573 val_loss= 1.34154 val_acc= 0.44643 time= 0.01563
Epoch: 0013 train_loss= 1.37182 train_acc= 0.32573 val_loss= 1.33852 val_acc= 0.44643 time= 0.01563
Epoch: 0014 train_loss= 1.37170 train_acc= 0.32573 val_loss= 1.33599 val_acc= 0.44643 time= 0.01563
Epoch: 0015 train_loss= 1.37073 train_acc= 0.32573 val_loss= 1.33399 val_acc= 0.44643 time= 0.01563
Epoch: 0016 train_loss= 1.37224 train_acc= 0.32573 val_loss= 1.33256 val_acc= 0.44643 time= 0.01563
Epoch: 0017 train_loss= 1.37262 train_acc= 0.32573 val_loss= 1.33169 val_acc= 0.44643 time= 0.01563
Epoch: 0018 train_loss= 1.37144 train_acc= 0.32573 val_loss= 1.33120 val_acc= 0.44643 time= 0.01563
Epoch: 0019 train_loss= 1.37169 train_acc= 0.32573 val_loss= 1.33108 val_acc= 0.44643 time= 0.01563
Epoch: 0020 train_loss= 1.37133 train_acc= 0.32573 val_loss= 1.33119 val_acc= 0.44643 time= 0.01563
Epoch: 0021 train_loss= 1.37078 train_acc= 0.32573 val_loss= 1.33151 val_acc= 0.44643 time= 0.01563
Epoch: 0022 train_loss= 1.37127 train_acc= 0.32573 val_loss= 1.33209 val_acc= 0.44643 time= 0.01563
Epoch: 0023 train_loss= 1.37010 train_acc= 0.32573 val_loss= 1.33278 val_acc= 0.44643 time= 0.01563
Epoch: 0024 train_loss= 1.36995 train_acc= 0.32573 val_loss= 1.33362 val_acc= 0.44643 time= 0.01563
Early stopping...
Optimization Finished!
Test set results: cost= 1.38487 accuracy= 0.29204 time= 0.00000 
