Epoch: 0001 train_loss= 0.70119 train_acc= 0.48052 val_loss= 0.69777 val_acc= 0.54098 time= 0.76208
Epoch: 0002 train_loss= 0.69811 train_acc= 0.52078 val_loss= 0.69582 val_acc= 0.55738 time= 0.01400
Epoch: 0003 train_loss= 0.69555 train_acc= 0.53766 val_loss= 0.69442 val_acc= 0.55738 time= 0.01200
Epoch: 0004 train_loss= 0.69372 train_acc= 0.54416 val_loss= 0.69346 val_acc= 0.55738 time= 0.01500
Epoch: 0005 train_loss= 0.69258 train_acc= 0.52987 val_loss= 0.69277 val_acc= 0.55738 time= 0.01600
Epoch: 0006 train_loss= 0.69176 train_acc= 0.54545 val_loss= 0.69229 val_acc= 0.55738 time= 0.01400
Epoch: 0007 train_loss= 0.69054 train_acc= 0.54675 val_loss= 0.69200 val_acc= 0.55738 time= 0.01317
Epoch: 0008 train_loss= 0.68962 train_acc= 0.55195 val_loss= 0.69177 val_acc= 0.55738 time= 0.01400
Epoch: 0009 train_loss= 0.68891 train_acc= 0.57922 val_loss= 0.69155 val_acc= 0.55738 time= 0.01300
Epoch: 0010 train_loss= 0.68802 train_acc= 0.59351 val_loss= 0.69128 val_acc= 0.55738 time= 0.01200
Epoch: 0011 train_loss= 0.68908 train_acc= 0.59481 val_loss= 0.69100 val_acc= 0.57377 time= 0.01200
Epoch: 0012 train_loss= 0.68775 train_acc= 0.61169 val_loss= 0.69068 val_acc= 0.60656 time= 0.01000
Epoch: 0013 train_loss= 0.68704 train_acc= 0.63247 val_loss= 0.69030 val_acc= 0.60656 time= 0.00077
Epoch: 0014 train_loss= 0.68656 train_acc= 0.59740 val_loss= 0.68988 val_acc= 0.62295 time= 0.01562
Epoch: 0015 train_loss= 0.68514 train_acc= 0.62597 val_loss= 0.68942 val_acc= 0.65574 time= 0.00000
Epoch: 0016 train_loss= 0.68511 train_acc= 0.59610 val_loss= 0.68892 val_acc= 0.70492 time= 0.01563
Epoch: 0017 train_loss= 0.68326 train_acc= 0.62468 val_loss= 0.68843 val_acc= 0.72131 time= 0.01562
Epoch: 0018 train_loss= 0.68310 train_acc= 0.63117 val_loss= 0.68797 val_acc= 0.73770 time= 0.00000
Epoch: 0019 train_loss= 0.68178 train_acc= 0.66623 val_loss= 0.68754 val_acc= 0.70492 time= 0.01563
Epoch: 0020 train_loss= 0.68133 train_acc= 0.66494 val_loss= 0.68712 val_acc= 0.72131 time= 0.01563
Epoch: 0021 train_loss= 0.68204 train_acc= 0.63117 val_loss= 0.68673 val_acc= 0.72131 time= 0.00000
Epoch: 0022 train_loss= 0.67922 train_acc= 0.62468 val_loss= 0.68633 val_acc= 0.70492 time= 0.02275
Epoch: 0023 train_loss= 0.67816 train_acc= 0.67403 val_loss= 0.68591 val_acc= 0.72131 time= 0.01126
Epoch: 0024 train_loss= 0.67894 train_acc= 0.68052 val_loss= 0.68550 val_acc= 0.75410 time= 0.01106
Epoch: 0025 train_loss= 0.67792 train_acc= 0.63636 val_loss= 0.68511 val_acc= 0.77049 time= 0.01112
Epoch: 0026 train_loss= 0.67689 train_acc= 0.67143 val_loss= 0.68470 val_acc= 0.77049 time= 0.01122
Epoch: 0027 train_loss= 0.67724 train_acc= 0.66753 val_loss= 0.68426 val_acc= 0.75410 time= 0.01100
Epoch: 0028 train_loss= 0.67644 train_acc= 0.67013 val_loss= 0.68383 val_acc= 0.72131 time= 0.01008
Epoch: 0029 train_loss= 0.67560 train_acc= 0.64805 val_loss= 0.68338 val_acc= 0.68852 time= 0.01011
Epoch: 0030 train_loss= 0.67388 train_acc= 0.66364 val_loss= 0.68301 val_acc= 0.72131 time= 0.01010
Epoch: 0031 train_loss= 0.67344 train_acc= 0.63117 val_loss= 0.68289 val_acc= 0.67213 time= 0.01015
Epoch: 0032 train_loss= 0.67046 train_acc= 0.66234 val_loss= 0.68272 val_acc= 0.62295 time= 0.01100
Epoch: 0033 train_loss= 0.67298 train_acc= 0.67662 val_loss= 0.68227 val_acc= 0.62295 time= 0.01100
Epoch: 0034 train_loss= 0.67339 train_acc= 0.67662 val_loss= 0.68168 val_acc= 0.65574 time= 0.00840
Epoch: 0035 train_loss= 0.66813 train_acc= 0.67922 val_loss= 0.68095 val_acc= 0.72131 time= 0.01347
Epoch: 0036 train_loss= 0.66827 train_acc= 0.68701 val_loss= 0.68045 val_acc= 0.78689 time= 0.01069
Epoch: 0037 train_loss= 0.66806 train_acc= 0.64545 val_loss= 0.68004 val_acc= 0.78689 time= 0.00000
Epoch: 0038 train_loss= 0.66668 train_acc= 0.65844 val_loss= 0.67959 val_acc= 0.78689 time= 0.01563
Epoch: 0039 train_loss= 0.66500 train_acc= 0.67532 val_loss= 0.67916 val_acc= 0.72131 time= 0.01563
Epoch: 0040 train_loss= 0.66599 train_acc= 0.66234 val_loss= 0.67896 val_acc= 0.68852 time= 0.00000
Epoch: 0041 train_loss= 0.66778 train_acc= 0.68961 val_loss= 0.67892 val_acc= 0.62295 time= 0.01563
Epoch: 0042 train_loss= 0.66480 train_acc= 0.67013 val_loss= 0.67822 val_acc= 0.65574 time= 0.01563
Epoch: 0043 train_loss= 0.66439 train_acc= 0.67792 val_loss= 0.67754 val_acc= 0.68852 time= 0.00000
Epoch: 0044 train_loss= 0.66147 train_acc= 0.66364 val_loss= 0.67690 val_acc= 0.77049 time= 0.01563
Epoch: 0045 train_loss= 0.66278 train_acc= 0.66883 val_loss= 0.67660 val_acc= 0.80328 time= 0.01563
Epoch: 0046 train_loss= 0.66135 train_acc= 0.67013 val_loss= 0.67619 val_acc= 0.80328 time= 0.00000
Epoch: 0047 train_loss= 0.66147 train_acc= 0.62857 val_loss= 0.67573 val_acc= 0.75410 time= 0.01563
Epoch: 0048 train_loss= 0.66187 train_acc= 0.67922 val_loss= 0.67579 val_acc= 0.65574 time= 0.01562
Epoch: 0049 train_loss= 0.66013 train_acc= 0.70390 val_loss= 0.67615 val_acc= 0.60656 time= 0.00000
Epoch: 0050 train_loss= 0.65645 train_acc= 0.68182 val_loss= 0.67617 val_acc= 0.62295 time= 0.01563
Epoch: 0051 train_loss= 0.65768 train_acc= 0.68182 val_loss= 0.67548 val_acc= 0.60656 time= 0.01563
Epoch: 0052 train_loss= 0.65910 train_acc= 0.70260 val_loss= 0.67446 val_acc= 0.65574 time= 0.00000
Epoch: 0053 train_loss= 0.65772 train_acc= 0.68182 val_loss= 0.67407 val_acc= 0.68852 time= 0.01563
Epoch: 0054 train_loss= 0.65927 train_acc= 0.67013 val_loss= 0.67350 val_acc= 0.68852 time= 0.01563
Epoch: 0055 train_loss= 0.65243 train_acc= 0.67792 val_loss= 0.67303 val_acc= 0.75410 time= 0.00701
Epoch: 0056 train_loss= 0.65661 train_acc= 0.68182 val_loss= 0.67276 val_acc= 0.78689 time= 0.01832
Epoch: 0057 train_loss= 0.65956 train_acc= 0.67273 val_loss= 0.67258 val_acc= 0.80328 time= 0.00544
Epoch: 0058 train_loss= 0.65577 train_acc= 0.66104 val_loss= 0.67229 val_acc= 0.72131 time= 0.01563
Epoch: 0059 train_loss= 0.65785 train_acc= 0.64026 val_loss= 0.67397 val_acc= 0.62295 time= 0.01442
Epoch: 0060 train_loss= 0.65046 train_acc= 0.69351 val_loss= 0.67539 val_acc= 0.62295 time= 0.01200
Early stopping...
Optimization Finished!
Test set results: cost= 0.68012 accuracy= 0.59016 time= 0.00500 
