Epoch: 0001 train_loss= 1.39400 train_acc= 0.30619 val_loss= 1.39049 val_acc= 0.30357 time= 0.18775
Epoch: 0002 train_loss= 1.39015 train_acc= 0.31270 val_loss= 1.38737 val_acc= 0.30357 time= 0.01563
Epoch: 0003 train_loss= 1.38686 train_acc= 0.31270 val_loss= 1.38489 val_acc= 0.30357 time= 0.01563
Epoch: 0004 train_loss= 1.38431 train_acc= 0.31270 val_loss= 1.38300 val_acc= 0.30357 time= 0.01563
Epoch: 0005 train_loss= 1.38190 train_acc= 0.31270 val_loss= 1.38158 val_acc= 0.30357 time= 0.00000
Epoch: 0006 train_loss= 1.38080 train_acc= 0.31270 val_loss= 1.38065 val_acc= 0.30357 time= 0.01563
Epoch: 0007 train_loss= 1.37990 train_acc= 0.31270 val_loss= 1.38010 val_acc= 0.30357 time= 0.01563
Epoch: 0008 train_loss= 1.37884 train_acc= 0.31270 val_loss= 1.37975 val_acc= 0.30357 time= 0.01562
Epoch: 0009 train_loss= 1.37851 train_acc= 0.31270 val_loss= 1.37949 val_acc= 0.30357 time= 0.00000
Epoch: 0010 train_loss= 1.37845 train_acc= 0.31270 val_loss= 1.37919 val_acc= 0.30357 time= 0.01563
Epoch: 0011 train_loss= 1.37802 train_acc= 0.31270 val_loss= 1.37883 val_acc= 0.30357 time= 0.01563
Epoch: 0012 train_loss= 1.37898 train_acc= 0.31270 val_loss= 1.37843 val_acc= 0.30357 time= 0.01563
Epoch: 0013 train_loss= 1.37828 train_acc= 0.31270 val_loss= 1.37799 val_acc= 0.30357 time= 0.01562
Epoch: 0014 train_loss= 1.37712 train_acc= 0.31270 val_loss= 1.37756 val_acc= 0.30357 time= 0.00000
Epoch: 0015 train_loss= 1.37737 train_acc= 0.31270 val_loss= 1.37721 val_acc= 0.30357 time= 0.01563
Epoch: 0016 train_loss= 1.37582 train_acc= 0.31270 val_loss= 1.37684 val_acc= 0.30357 time= 0.01563
Epoch: 0017 train_loss= 1.37574 train_acc= 0.31270 val_loss= 1.37654 val_acc= 0.30357 time= 0.02659
Epoch: 0018 train_loss= 1.37476 train_acc= 0.31270 val_loss= 1.37626 val_acc= 0.30357 time= 0.01700
Epoch: 0019 train_loss= 1.37505 train_acc= 0.31270 val_loss= 1.37601 val_acc= 0.30357 time= 0.01623
Epoch: 0020 train_loss= 1.37510 train_acc= 0.31270 val_loss= 1.37579 val_acc= 0.30357 time= 0.01500
Epoch: 0021 train_loss= 1.37516 train_acc= 0.31270 val_loss= 1.37563 val_acc= 0.30357 time= 0.01524
Epoch: 0022 train_loss= 1.37489 train_acc= 0.31270 val_loss= 1.37553 val_acc= 0.30357 time= 0.01400
Epoch: 0023 train_loss= 1.37437 train_acc= 0.31270 val_loss= 1.37539 val_acc= 0.30357 time= 0.01523
Epoch: 0024 train_loss= 1.37464 train_acc= 0.31270 val_loss= 1.37515 val_acc= 0.30357 time= 0.01500
Epoch: 0025 train_loss= 1.37310 train_acc= 0.31270 val_loss= 1.37492 val_acc= 0.30357 time= 0.01635
Epoch: 0026 train_loss= 1.37341 train_acc= 0.31270 val_loss= 1.37473 val_acc= 0.30357 time= 0.01600
Epoch: 0027 train_loss= 1.37416 train_acc= 0.31270 val_loss= 1.37452 val_acc= 0.30357 time= 0.01729
Epoch: 0028 train_loss= 1.37302 train_acc= 0.31270 val_loss= 1.37424 val_acc= 0.30357 time= 0.01537
Epoch: 0029 train_loss= 1.37296 train_acc= 0.31270 val_loss= 1.37391 val_acc= 0.30357 time= 0.01400
Epoch: 0030 train_loss= 1.37304 train_acc= 0.31270 val_loss= 1.37358 val_acc= 0.30357 time= 0.01400
Epoch: 0031 train_loss= 1.37312 train_acc= 0.31270 val_loss= 1.37334 val_acc= 0.30357 time= 0.01522
Epoch: 0032 train_loss= 1.37248 train_acc= 0.31270 val_loss= 1.37309 val_acc= 0.30357 time= 0.01663
Epoch: 0033 train_loss= 1.37237 train_acc= 0.31270 val_loss= 1.37290 val_acc= 0.30357 time= 0.01400
Epoch: 0034 train_loss= 1.37127 train_acc= 0.31270 val_loss= 1.37274 val_acc= 0.30357 time= 0.01300
Epoch: 0035 train_loss= 1.37164 train_acc= 0.31270 val_loss= 1.37261 val_acc= 0.30357 time= 0.01200
Epoch: 0036 train_loss= 1.37090 train_acc= 0.31270 val_loss= 1.37254 val_acc= 0.30357 time= 0.01300
Epoch: 0037 train_loss= 1.37128 train_acc= 0.31270 val_loss= 1.37255 val_acc= 0.30357 time= 0.01525
Epoch: 0038 train_loss= 1.37108 train_acc= 0.31270 val_loss= 1.37263 val_acc= 0.30357 time= 0.01314
Epoch: 0039 train_loss= 1.37120 train_acc= 0.31270 val_loss= 1.37280 val_acc= 0.30357 time= 0.01294
Epoch: 0040 train_loss= 1.37167 train_acc= 0.31270 val_loss= 1.37278 val_acc= 0.30357 time= 0.01314
Epoch: 0041 train_loss= 1.37106 train_acc= 0.31270 val_loss= 1.37259 val_acc= 0.30357 time= 0.01200
Epoch: 0042 train_loss= 1.37015 train_acc= 0.31270 val_loss= 1.37238 val_acc= 0.30357 time= 0.01527
Epoch: 0043 train_loss= 1.37030 train_acc= 0.31270 val_loss= 1.37217 val_acc= 0.30357 time= 0.01500
Epoch: 0044 train_loss= 1.37028 train_acc= 0.31270 val_loss= 1.37198 val_acc= 0.30357 time= 0.01352
Epoch: 0045 train_loss= 1.37028 train_acc= 0.31270 val_loss= 1.37170 val_acc= 0.30357 time= 0.01415
Epoch: 0046 train_loss= 1.37067 train_acc= 0.31270 val_loss= 1.37153 val_acc= 0.30357 time= 0.01200
Epoch: 0047 train_loss= 1.36964 train_acc= 0.31270 val_loss= 1.37155 val_acc= 0.30357 time= 0.01300
Epoch: 0048 train_loss= 1.36975 train_acc= 0.31270 val_loss= 1.37164 val_acc= 0.30357 time= 0.01300
Epoch: 0049 train_loss= 1.36795 train_acc= 0.31270 val_loss= 1.37165 val_acc= 0.30357 time= 0.01200
Epoch: 0050 train_loss= 1.36909 train_acc= 0.31270 val_loss= 1.37176 val_acc= 0.30357 time= 0.00718
Epoch: 0051 train_loss= 1.37013 train_acc= 0.31270 val_loss= 1.37166 val_acc= 0.30357 time= 0.01563
Epoch: 0052 train_loss= 1.36862 train_acc= 0.31270 val_loss= 1.37133 val_acc= 0.30357 time= 0.00000
Epoch: 0053 train_loss= 1.36911 train_acc= 0.31270 val_loss= 1.37120 val_acc= 0.30357 time= 0.01563
Epoch: 0054 train_loss= 1.36674 train_acc= 0.31270 val_loss= 1.37098 val_acc= 0.30357 time= 0.01563
Epoch: 0055 train_loss= 1.36784 train_acc= 0.31270 val_loss= 1.37085 val_acc= 0.30357 time= 0.00000
Epoch: 0056 train_loss= 1.36630 train_acc= 0.31270 val_loss= 1.37062 val_acc= 0.30357 time= 0.01562
Epoch: 0057 train_loss= 1.36852 train_acc= 0.31270 val_loss= 1.37046 val_acc= 0.30357 time= 0.01563
Epoch: 0058 train_loss= 1.36677 train_acc= 0.31270 val_loss= 1.37045 val_acc= 0.30357 time= 0.00000
Epoch: 0059 train_loss= 1.36602 train_acc= 0.31270 val_loss= 1.37046 val_acc= 0.30357 time= 0.01563
Epoch: 0060 train_loss= 1.36618 train_acc= 0.31270 val_loss= 1.37053 val_acc= 0.30357 time= 0.01563
Epoch: 0061 train_loss= 1.36622 train_acc= 0.31270 val_loss= 1.37057 val_acc= 0.30357 time= 0.01562
Epoch: 0062 train_loss= 1.36384 train_acc= 0.31596 val_loss= 1.37078 val_acc= 0.30357 time= 0.00000
Early stopping...
Optimization Finished!
Test set results: cost= 1.37581 accuracy= 0.29204 time= 0.00000 
