Epoch: 0001 train_loss= 2.08706 train_acc= 0.15094 val_loss= 2.08215 val_acc= 0.24138 time= 0.18751
Epoch: 0002 train_loss= 2.08290 train_acc= 0.18868 val_loss= 2.07745 val_acc= 0.24138 time= 0.00000
Epoch: 0003 train_loss= 2.07926 train_acc= 0.21384 val_loss= 2.07170 val_acc= 0.27586 time= 0.01563
Epoch: 0004 train_loss= 2.07491 train_acc= 0.16352 val_loss= 2.06553 val_acc= 0.27586 time= 0.00000
Epoch: 0005 train_loss= 2.07101 train_acc= 0.17610 val_loss= 2.05908 val_acc= 0.27586 time= 0.01563
Epoch: 0006 train_loss= 2.06712 train_acc= 0.18239 val_loss= 2.05261 val_acc= 0.27586 time= 0.00000
Epoch: 0007 train_loss= 2.06372 train_acc= 0.18868 val_loss= 2.04622 val_acc= 0.27586 time= 0.01563
Epoch: 0008 train_loss= 2.05928 train_acc= 0.20126 val_loss= 2.03982 val_acc= 0.27586 time= 0.00000
Epoch: 0009 train_loss= 2.05708 train_acc= 0.19497 val_loss= 2.03355 val_acc= 0.27586 time= 0.01563
Epoch: 0010 train_loss= 2.05452 train_acc= 0.20126 val_loss= 2.02744 val_acc= 0.27586 time= 0.00000
Epoch: 0011 train_loss= 2.05356 train_acc= 0.19497 val_loss= 2.02177 val_acc= 0.27586 time= 0.01563
Epoch: 0012 train_loss= 2.04908 train_acc= 0.19497 val_loss= 2.01658 val_acc= 0.27586 time= 0.00000
Epoch: 0013 train_loss= 2.04789 train_acc= 0.19497 val_loss= 2.01230 val_acc= 0.27586 time= 0.01563
Epoch: 0014 train_loss= 2.04802 train_acc= 0.19497 val_loss= 2.00858 val_acc= 0.27586 time= 0.00000
Epoch: 0015 train_loss= 2.04917 train_acc= 0.19497 val_loss= 2.00545 val_acc= 0.27586 time= 0.00000
Epoch: 0016 train_loss= 2.04709 train_acc= 0.19497 val_loss= 2.00303 val_acc= 0.27586 time= 0.01563
Epoch: 0017 train_loss= 2.04658 train_acc= 0.19497 val_loss= 2.00123 val_acc= 0.27586 time= 0.00000
Epoch: 0018 train_loss= 2.04451 train_acc= 0.19497 val_loss= 1.99991 val_acc= 0.27586 time= 0.01563
Epoch: 0019 train_loss= 2.04613 train_acc= 0.19497 val_loss= 1.99896 val_acc= 0.27586 time= 0.00000
Epoch: 0020 train_loss= 2.04543 train_acc= 0.19497 val_loss= 1.99828 val_acc= 0.27586 time= 0.01563
Epoch: 0021 train_loss= 2.04502 train_acc= 0.19497 val_loss= 1.99788 val_acc= 0.27586 time= 0.00000
Epoch: 0022 train_loss= 2.04565 train_acc= 0.19497 val_loss= 1.99790 val_acc= 0.27586 time= 0.01563
Epoch: 0023 train_loss= 2.04219 train_acc= 0.19497 val_loss= 1.99813 val_acc= 0.27586 time= 0.00000
Epoch: 0024 train_loss= 2.04243 train_acc= 0.19497 val_loss= 1.99858 val_acc= 0.27586 time= 0.01563
Epoch: 0025 train_loss= 2.04000 train_acc= 0.19497 val_loss= 1.99903 val_acc= 0.27586 time= 0.00000
Epoch: 0026 train_loss= 2.04068 train_acc= 0.19497 val_loss= 1.99943 val_acc= 0.27586 time= 0.01563
Early stopping...
Optimization Finished!
Test set results: cost= 2.07762 accuracy= 0.16949 time= 0.00000 
