Epoch: 0001 train_loss= 1.39413 train_acc= 0.24219 val_loss= 1.38929 val_acc= 0.44643 time= 0.25828
Epoch: 0002 train_loss= 1.39088 train_acc= 0.31641 val_loss= 1.38459 val_acc= 0.44643 time= 0.01564
Epoch: 0003 train_loss= 1.38793 train_acc= 0.31641 val_loss= 1.38034 val_acc= 0.44643 time= 0.01562
Epoch: 0004 train_loss= 1.38567 train_acc= 0.31641 val_loss= 1.37663 val_acc= 0.44643 time= 0.01563
Epoch: 0005 train_loss= 1.38385 train_acc= 0.31641 val_loss= 1.37349 val_acc= 0.44643 time= 0.01563
Epoch: 0006 train_loss= 1.38290 train_acc= 0.31641 val_loss= 1.37084 val_acc= 0.44643 time= 0.01562
Epoch: 0007 train_loss= 1.38192 train_acc= 0.31641 val_loss= 1.36869 val_acc= 0.44643 time= 0.01563
Epoch: 0008 train_loss= 1.38104 train_acc= 0.31641 val_loss= 1.36682 val_acc= 0.44643 time= 0.01563
Epoch: 0009 train_loss= 1.38033 train_acc= 0.31641 val_loss= 1.36520 val_acc= 0.44643 time= 0.01563
Epoch: 0010 train_loss= 1.37995 train_acc= 0.31641 val_loss= 1.36383 val_acc= 0.44643 time= 0.03125
Epoch: 0011 train_loss= 1.37933 train_acc= 0.31641 val_loss= 1.36262 val_acc= 0.44643 time= 0.01563
Epoch: 0012 train_loss= 1.37910 train_acc= 0.31641 val_loss= 1.36145 val_acc= 0.44643 time= 0.01563
Epoch: 0013 train_loss= 1.37892 train_acc= 0.31641 val_loss= 1.36050 val_acc= 0.44643 time= 0.01563
Epoch: 0014 train_loss= 1.37917 train_acc= 0.31641 val_loss= 1.35970 val_acc= 0.44643 time= 0.01562
Epoch: 0015 train_loss= 1.37884 train_acc= 0.31641 val_loss= 1.35908 val_acc= 0.44643 time= 0.01563
Epoch: 0016 train_loss= 1.37848 train_acc= 0.31641 val_loss= 1.35846 val_acc= 0.44643 time= 0.01563
Epoch: 0017 train_loss= 1.37769 train_acc= 0.31641 val_loss= 1.35787 val_acc= 0.44643 time= 0.01563
Epoch: 0018 train_loss= 1.37764 train_acc= 0.31641 val_loss= 1.35732 val_acc= 0.44643 time= 0.01563
Epoch: 0019 train_loss= 1.37735 train_acc= 0.31641 val_loss= 1.35698 val_acc= 0.44643 time= 0.03125
Epoch: 0020 train_loss= 1.37764 train_acc= 0.31641 val_loss= 1.35672 val_acc= 0.44643 time= 0.01563
Epoch: 0021 train_loss= 1.37688 train_acc= 0.31641 val_loss= 1.35658 val_acc= 0.44643 time= 0.01563
Epoch: 0022 train_loss= 1.37632 train_acc= 0.31641 val_loss= 1.35652 val_acc= 0.44643 time= 0.01563
Epoch: 0023 train_loss= 1.37626 train_acc= 0.31641 val_loss= 1.35636 val_acc= 0.44643 time= 0.01563
Epoch: 0024 train_loss= 1.37664 train_acc= 0.31641 val_loss= 1.35618 val_acc= 0.44643 time= 0.01562
Epoch: 0025 train_loss= 1.37558 train_acc= 0.31641 val_loss= 1.35594 val_acc= 0.44643 time= 0.01563
Epoch: 0026 train_loss= 1.37529 train_acc= 0.31641 val_loss= 1.35559 val_acc= 0.44643 time= 0.01563
Epoch: 0027 train_loss= 1.37559 train_acc= 0.31641 val_loss= 1.35517 val_acc= 0.44643 time= 0.01563
Epoch: 0028 train_loss= 1.37536 train_acc= 0.31641 val_loss= 1.35470 val_acc= 0.44643 time= 0.01563
Epoch: 0029 train_loss= 1.37550 train_acc= 0.31641 val_loss= 1.35427 val_acc= 0.44643 time= 0.01563
Epoch: 0030 train_loss= 1.37485 train_acc= 0.31641 val_loss= 1.35377 val_acc= 0.44643 time= 0.01563
Epoch: 0031 train_loss= 1.37478 train_acc= 0.31641 val_loss= 1.35325 val_acc= 0.44643 time= 0.01563
Epoch: 0032 train_loss= 1.37496 train_acc= 0.31641 val_loss= 1.35287 val_acc= 0.44643 time= 0.01563
Epoch: 0033 train_loss= 1.37463 train_acc= 0.31641 val_loss= 1.35245 val_acc= 0.44643 time= 0.01563
Epoch: 0034 train_loss= 1.37426 train_acc= 0.31641 val_loss= 1.35206 val_acc= 0.44643 time= 0.01563
Epoch: 0035 train_loss= 1.37448 train_acc= 0.31641 val_loss= 1.35184 val_acc= 0.44643 time= 0.01563
Epoch: 0036 train_loss= 1.37421 train_acc= 0.31641 val_loss= 1.35149 val_acc= 0.44643 time= 0.01563
Epoch: 0037 train_loss= 1.37447 train_acc= 0.31641 val_loss= 1.35120 val_acc= 0.44643 time= 0.01563
Epoch: 0038 train_loss= 1.37426 train_acc= 0.31641 val_loss= 1.35096 val_acc= 0.44643 time= 0.01563
Epoch: 0039 train_loss= 1.37423 train_acc= 0.31641 val_loss= 1.35078 val_acc= 0.44643 time= 0.01563
Epoch: 0040 train_loss= 1.37350 train_acc= 0.31641 val_loss= 1.35049 val_acc= 0.44643 time= 0.01563
Epoch: 0041 train_loss= 1.37437 train_acc= 0.31641 val_loss= 1.35026 val_acc= 0.44643 time= 0.01563
Epoch: 0042 train_loss= 1.37341 train_acc= 0.31641 val_loss= 1.35004 val_acc= 0.44643 time= 0.01563
Epoch: 0043 train_loss= 1.37346 train_acc= 0.31641 val_loss= 1.35004 val_acc= 0.44643 time= 0.01563
Epoch: 0044 train_loss= 1.37349 train_acc= 0.31641 val_loss= 1.34978 val_acc= 0.44643 time= 0.01563
Epoch: 0045 train_loss= 1.37308 train_acc= 0.31641 val_loss= 1.34939 val_acc= 0.44643 time= 0.01562
Epoch: 0046 train_loss= 1.37327 train_acc= 0.31641 val_loss= 1.34894 val_acc= 0.44643 time= 0.01563
Epoch: 0047 train_loss= 1.37365 train_acc= 0.31641 val_loss= 1.34849 val_acc= 0.44643 time= 0.01563
Epoch: 0048 train_loss= 1.37317 train_acc= 0.31641 val_loss= 1.34815 val_acc= 0.44643 time= 0.01563
Epoch: 0049 train_loss= 1.37286 train_acc= 0.31641 val_loss= 1.34791 val_acc= 0.44643 time= 0.01563
Epoch: 0050 train_loss= 1.37314 train_acc= 0.31641 val_loss= 1.34771 val_acc= 0.44643 time= 0.01563
Epoch: 0051 train_loss= 1.37338 train_acc= 0.31641 val_loss= 1.34778 val_acc= 0.44643 time= 0.01563
Epoch: 0052 train_loss= 1.37310 train_acc= 0.31641 val_loss= 1.34784 val_acc= 0.44643 time= 0.01563
Epoch: 0053 train_loss= 1.37236 train_acc= 0.31641 val_loss= 1.34794 val_acc= 0.44643 time= 0.03112
Epoch: 0054 train_loss= 1.37339 train_acc= 0.31641 val_loss= 1.34818 val_acc= 0.44643 time= 0.01507
Epoch: 0055 train_loss= 1.37250 train_acc= 0.31641 val_loss= 1.34815 val_acc= 0.44643 time= 0.01756
Epoch: 0056 train_loss= 1.37309 train_acc= 0.31641 val_loss= 1.34821 val_acc= 0.44643 time= 0.01569
Early stopping...
Optimization Finished!
Test set results: cost= 1.37198 accuracy= 0.30973 time= 0.00000 
