Epoch: 0001 train_loss= 1.39550 train_acc= 0.20508 val_loss= 1.39287 val_acc= 0.17857 time= 0.35568
Epoch: 0002 train_loss= 1.39254 train_acc= 0.20508 val_loss= 1.39021 val_acc= 0.32143 time= 0.01800
Epoch: 0003 train_loss= 1.38956 train_acc= 0.33008 val_loss= 1.38873 val_acc= 0.32143 time= 0.01800
Epoch: 0004 train_loss= 1.38761 train_acc= 0.33789 val_loss= 1.38801 val_acc= 0.32143 time= 0.02000
Epoch: 0005 train_loss= 1.38664 train_acc= 0.33789 val_loss= 1.38733 val_acc= 0.32143 time= 0.01700
Epoch: 0006 train_loss= 1.38545 train_acc= 0.33789 val_loss= 1.38669 val_acc= 0.32143 time= 0.01855
Epoch: 0007 train_loss= 1.38419 train_acc= 0.33789 val_loss= 1.38609 val_acc= 0.32143 time= 0.01621
Epoch: 0008 train_loss= 1.38341 train_acc= 0.33789 val_loss= 1.38552 val_acc= 0.32143 time= 0.01700
Epoch: 0009 train_loss= 1.38219 train_acc= 0.33789 val_loss= 1.38500 val_acc= 0.32143 time= 0.01700
Epoch: 0010 train_loss= 1.38173 train_acc= 0.33789 val_loss= 1.38452 val_acc= 0.32143 time= 0.01700
Epoch: 0011 train_loss= 1.37972 train_acc= 0.33789 val_loss= 1.38411 val_acc= 0.32143 time= 0.01565
Epoch: 0012 train_loss= 1.37926 train_acc= 0.33789 val_loss= 1.38374 val_acc= 0.32143 time= 0.01500
Epoch: 0013 train_loss= 1.37782 train_acc= 0.33789 val_loss= 1.38344 val_acc= 0.32143 time= 0.01500
Epoch: 0014 train_loss= 1.37740 train_acc= 0.33789 val_loss= 1.38318 val_acc= 0.32143 time= 0.01701
Epoch: 0015 train_loss= 1.37696 train_acc= 0.33789 val_loss= 1.38296 val_acc= 0.32143 time= 0.01300
Epoch: 0016 train_loss= 1.37514 train_acc= 0.33789 val_loss= 1.38279 val_acc= 0.32143 time= 0.01600
Epoch: 0017 train_loss= 1.37485 train_acc= 0.33789 val_loss= 1.38260 val_acc= 0.32143 time= 0.01700
Epoch: 0018 train_loss= 1.37425 train_acc= 0.33789 val_loss= 1.38240 val_acc= 0.32143 time= 0.01616
Epoch: 0019 train_loss= 1.37295 train_acc= 0.33789 val_loss= 1.38217 val_acc= 0.32143 time= 0.01713
Epoch: 0020 train_loss= 1.37424 train_acc= 0.33789 val_loss= 1.38183 val_acc= 0.32143 time= 0.01425
Epoch: 0021 train_loss= 1.37361 train_acc= 0.33789 val_loss= 1.38141 val_acc= 0.32143 time= 0.01300
Epoch: 0022 train_loss= 1.37279 train_acc= 0.33789 val_loss= 1.38089 val_acc= 0.32143 time= 0.01443
Epoch: 0023 train_loss= 1.37283 train_acc= 0.33789 val_loss= 1.38029 val_acc= 0.32143 time= 0.01501
Epoch: 0024 train_loss= 1.37155 train_acc= 0.33789 val_loss= 1.37965 val_acc= 0.32143 time= 0.01518
Epoch: 0025 train_loss= 1.37148 train_acc= 0.33789 val_loss= 1.37894 val_acc= 0.32143 time= 0.01097
Epoch: 0026 train_loss= 1.36946 train_acc= 0.33789 val_loss= 1.37822 val_acc= 0.32143 time= 0.01534
Epoch: 0027 train_loss= 1.37133 train_acc= 0.33789 val_loss= 1.37746 val_acc= 0.32143 time= 0.01500
Epoch: 0028 train_loss= 1.36953 train_acc= 0.33789 val_loss= 1.37667 val_acc= 0.32143 time= 0.01310
Epoch: 0029 train_loss= 1.37021 train_acc= 0.33789 val_loss= 1.37583 val_acc= 0.32143 time= 0.01309
Epoch: 0030 train_loss= 1.37069 train_acc= 0.33789 val_loss= 1.37500 val_acc= 0.32143 time= 0.01159
Epoch: 0031 train_loss= 1.37132 train_acc= 0.33789 val_loss= 1.37416 val_acc= 0.32143 time= 0.01200
Epoch: 0032 train_loss= 1.37093 train_acc= 0.33789 val_loss= 1.37330 val_acc= 0.32143 time= 0.01400
Epoch: 0033 train_loss= 1.36986 train_acc= 0.33789 val_loss= 1.37245 val_acc= 0.32143 time= 0.01192
Epoch: 0034 train_loss= 1.37006 train_acc= 0.33789 val_loss= 1.37164 val_acc= 0.32143 time= 0.01421
Epoch: 0035 train_loss= 1.36926 train_acc= 0.33789 val_loss= 1.37084 val_acc= 0.32143 time= 0.01006
Epoch: 0036 train_loss= 1.37095 train_acc= 0.33789 val_loss= 1.37013 val_acc= 0.32143 time= 0.01719
Epoch: 0037 train_loss= 1.36913 train_acc= 0.33789 val_loss= 1.36950 val_acc= 0.32143 time= 0.01316
Epoch: 0038 train_loss= 1.36922 train_acc= 0.33789 val_loss= 1.36901 val_acc= 0.32143 time= 0.01313
Epoch: 0039 train_loss= 1.36862 train_acc= 0.33789 val_loss= 1.36862 val_acc= 0.32143 time= 0.01100
Epoch: 0040 train_loss= 1.36895 train_acc= 0.33789 val_loss= 1.36831 val_acc= 0.32143 time= 0.01622
Epoch: 0041 train_loss= 1.36814 train_acc= 0.33789 val_loss= 1.36809 val_acc= 0.32143 time= 0.01511
Epoch: 0042 train_loss= 1.36877 train_acc= 0.33789 val_loss= 1.36782 val_acc= 0.32143 time= 0.01300
Epoch: 0043 train_loss= 1.36834 train_acc= 0.33789 val_loss= 1.36759 val_acc= 0.32143 time= 0.01400
Epoch: 0044 train_loss= 1.36821 train_acc= 0.33789 val_loss= 1.36736 val_acc= 0.32143 time= 0.00848
Epoch: 0045 train_loss= 1.36910 train_acc= 0.33789 val_loss= 1.36712 val_acc= 0.32143 time= 0.01849
Epoch: 0046 train_loss= 1.36932 train_acc= 0.33789 val_loss= 1.36691 val_acc= 0.32143 time= 0.00573
Epoch: 0047 train_loss= 1.37022 train_acc= 0.33789 val_loss= 1.36674 val_acc= 0.32143 time= 0.01563
Epoch: 0048 train_loss= 1.36689 train_acc= 0.33789 val_loss= 1.36663 val_acc= 0.32143 time= 0.01768
Epoch: 0049 train_loss= 1.36708 train_acc= 0.33789 val_loss= 1.36656 val_acc= 0.32143 time= 0.01213
Epoch: 0050 train_loss= 1.36867 train_acc= 0.33789 val_loss= 1.36651 val_acc= 0.32143 time= 0.00821
Epoch: 0051 train_loss= 1.36838 train_acc= 0.33789 val_loss= 1.36648 val_acc= 0.32143 time= 0.01764
Epoch: 0052 train_loss= 1.36677 train_acc= 0.33789 val_loss= 1.36644 val_acc= 0.32143 time= 0.01300
Epoch: 0053 train_loss= 1.36780 train_acc= 0.33789 val_loss= 1.36644 val_acc= 0.32143 time= 0.01500
Epoch: 0054 train_loss= 1.36924 train_acc= 0.33789 val_loss= 1.36645 val_acc= 0.32143 time= 0.01300
Epoch: 0055 train_loss= 1.36843 train_acc= 0.33789 val_loss= 1.36650 val_acc= 0.32143 time= 0.01403
Epoch: 0056 train_loss= 1.36851 train_acc= 0.33789 val_loss= 1.36656 val_acc= 0.32143 time= 0.01400
Epoch: 0057 train_loss= 1.36806 train_acc= 0.33789 val_loss= 1.36662 val_acc= 0.32143 time= 0.01500
Early stopping...
Optimization Finished!
Test set results: cost= 1.37991 accuracy= 0.29204 time= 0.00700 
