Epoch: 0001 train_loss= 0.70088 train_acc= 0.53030 val_loss= 0.69752 val_acc= 0.55738 time= 0.12545
Epoch: 0002 train_loss= 0.69767 train_acc= 0.54242 val_loss= 0.69507 val_acc= 0.55738 time= 0.01519
Epoch: 0003 train_loss= 0.69540 train_acc= 0.54242 val_loss= 0.69328 val_acc= 0.55738 time= 0.00000
Epoch: 0004 train_loss= 0.69387 train_acc= 0.54242 val_loss= 0.69206 val_acc= 0.55738 time= 0.01563
Epoch: 0005 train_loss= 0.69285 train_acc= 0.54242 val_loss= 0.69129 val_acc= 0.55738 time= 0.01563
Epoch: 0006 train_loss= 0.69192 train_acc= 0.54242 val_loss= 0.69086 val_acc= 0.55738 time= 0.00000
Epoch: 0007 train_loss= 0.69167 train_acc= 0.54242 val_loss= 0.69064 val_acc= 0.55738 time= 0.01562
Epoch: 0008 train_loss= 0.69140 train_acc= 0.54242 val_loss= 0.69056 val_acc= 0.55738 time= 0.01563
Epoch: 0009 train_loss= 0.69173 train_acc= 0.54242 val_loss= 0.69054 val_acc= 0.55738 time= 0.00000
Epoch: 0010 train_loss= 0.69127 train_acc= 0.54242 val_loss= 0.69053 val_acc= 0.55738 time= 0.01563
Epoch: 0011 train_loss= 0.69189 train_acc= 0.54242 val_loss= 0.69050 val_acc= 0.55738 time= 0.01562
Epoch: 0012 train_loss= 0.69154 train_acc= 0.54545 val_loss= 0.69043 val_acc= 0.55738 time= 0.00000
Epoch: 0013 train_loss= 0.69150 train_acc= 0.54242 val_loss= 0.69032 val_acc= 0.55738 time= 0.01563
Epoch: 0014 train_loss= 0.69169 train_acc= 0.54242 val_loss= 0.69019 val_acc= 0.55738 time= 0.01563
Epoch: 0015 train_loss= 0.69041 train_acc= 0.54545 val_loss= 0.69003 val_acc= 0.55738 time= 0.00000
Epoch: 0016 train_loss= 0.69001 train_acc= 0.54242 val_loss= 0.68987 val_acc= 0.55738 time= 0.01562
Epoch: 0017 train_loss= 0.69076 train_acc= 0.54545 val_loss= 0.68971 val_acc= 0.55738 time= 0.01563
Epoch: 0018 train_loss= 0.68997 train_acc= 0.54242 val_loss= 0.68959 val_acc= 0.55738 time= 0.00000
Epoch: 0019 train_loss= 0.69026 train_acc= 0.54545 val_loss= 0.68951 val_acc= 0.55738 time= 0.01562
Epoch: 0020 train_loss= 0.68913 train_acc= 0.54545 val_loss= 0.68944 val_acc= 0.55738 time= 0.01563
Epoch: 0021 train_loss= 0.68894 train_acc= 0.54242 val_loss= 0.68933 val_acc= 0.55738 time= 0.00000
Epoch: 0022 train_loss= 0.68964 train_acc= 0.54545 val_loss= 0.68921 val_acc= 0.55738 time= 0.01563
Epoch: 0023 train_loss= 0.68791 train_acc= 0.54545 val_loss= 0.68912 val_acc= 0.55738 time= 0.01563
Epoch: 0024 train_loss= 0.68831 train_acc= 0.54545 val_loss= 0.68904 val_acc= 0.55738 time= 0.00000
Epoch: 0025 train_loss= 0.68851 train_acc= 0.54242 val_loss= 0.68899 val_acc= 0.55738 time= 0.01563
Epoch: 0026 train_loss= 0.68849 train_acc= 0.54545 val_loss= 0.68898 val_acc= 0.57377 time= 0.01563
Epoch: 0027 train_loss= 0.68798 train_acc= 0.54848 val_loss= 0.68896 val_acc= 0.57377 time= 0.00000
Epoch: 0028 train_loss= 0.68810 train_acc= 0.55455 val_loss= 0.68894 val_acc= 0.57377 time= 0.01563
Epoch: 0029 train_loss= 0.68720 train_acc= 0.54848 val_loss= 0.68888 val_acc= 0.57377 time= 0.01594
Epoch: 0030 train_loss= 0.68756 train_acc= 0.55152 val_loss= 0.68885 val_acc= 0.57377 time= 0.00805
Epoch: 0031 train_loss= 0.68825 train_acc= 0.55455 val_loss= 0.68880 val_acc= 0.57377 time= 0.01380
Epoch: 0032 train_loss= 0.68665 train_acc= 0.55455 val_loss= 0.68879 val_acc= 0.57377 time= 0.01100
Epoch: 0033 train_loss= 0.68654 train_acc= 0.55758 val_loss= 0.68880 val_acc= 0.57377 time= 0.01105
Epoch: 0034 train_loss= 0.68562 train_acc= 0.55152 val_loss= 0.68882 val_acc= 0.57377 time= 0.00000
Epoch: 0035 train_loss= 0.68695 train_acc= 0.56667 val_loss= 0.68861 val_acc= 0.57377 time= 0.01563
Epoch: 0036 train_loss= 0.68563 train_acc= 0.55152 val_loss= 0.68843 val_acc= 0.57377 time= 0.01563
Epoch: 0037 train_loss= 0.68619 train_acc= 0.56970 val_loss= 0.68831 val_acc= 0.57377 time= 0.00000
Epoch: 0038 train_loss= 0.68575 train_acc= 0.54848 val_loss= 0.68825 val_acc= 0.57377 time= 0.01563
Epoch: 0039 train_loss= 0.68455 train_acc= 0.56970 val_loss= 0.68825 val_acc= 0.57377 time= 0.01563
Epoch: 0040 train_loss= 0.68439 train_acc= 0.55758 val_loss= 0.68842 val_acc= 0.57377 time= 0.00000
Epoch: 0041 train_loss= 0.68433 train_acc= 0.57273 val_loss= 0.68852 val_acc= 0.57377 time= 0.01563
Epoch: 0042 train_loss= 0.68413 train_acc= 0.60303 val_loss= 0.68824 val_acc= 0.57377 time= 0.01563
Epoch: 0043 train_loss= 0.68451 train_acc= 0.55455 val_loss= 0.68819 val_acc= 0.57377 time= 0.00000
Epoch: 0044 train_loss= 0.68443 train_acc= 0.56667 val_loss= 0.68817 val_acc= 0.57377 time= 0.01563
Epoch: 0045 train_loss= 0.68495 train_acc= 0.56970 val_loss= 0.68814 val_acc= 0.57377 time= 0.01563
Epoch: 0046 train_loss= 0.68288 train_acc= 0.57576 val_loss= 0.68812 val_acc= 0.57377 time= 0.00000
Epoch: 0047 train_loss= 0.68373 train_acc= 0.57273 val_loss= 0.68816 val_acc= 0.59016 time= 0.01563
Epoch: 0048 train_loss= 0.68489 train_acc= 0.62424 val_loss= 0.68807 val_acc= 0.57377 time= 0.01563
Epoch: 0049 train_loss= 0.68128 train_acc= 0.59394 val_loss= 0.68808 val_acc= 0.57377 time= 0.00000
Epoch: 0050 train_loss= 0.68113 train_acc= 0.56970 val_loss= 0.68806 val_acc= 0.57377 time= 0.01563
Epoch: 0051 train_loss= 0.67964 train_acc= 0.62424 val_loss= 0.68814 val_acc= 0.57377 time= 0.01563
Epoch: 0052 train_loss= 0.68168 train_acc= 0.56364 val_loss= 0.68801 val_acc= 0.57377 time= 0.00000
Epoch: 0053 train_loss= 0.68435 train_acc= 0.56061 val_loss= 0.68825 val_acc= 0.59016 time= 0.01563
Early stopping...
Optimization Finished!
Test set results: cost= 0.69156 accuracy= 0.60656 time= 0.00000 
