Epoch: 0001 train_loss= 1.13479 train_acc= 0.51169 val_loss= 0.81141 val_acc= 0.37705 time= 0.71705
Epoch: 0002 train_loss= 0.86999 train_acc= 0.51169 val_loss= 0.75069 val_acc= 0.40984 time= 0.01563
Epoch: 0003 train_loss= 0.86613 train_acc= 0.49351 val_loss= 0.73592 val_acc= 0.44262 time= 0.01563
Epoch: 0004 train_loss= 0.90993 train_acc= 0.53247 val_loss= 0.75385 val_acc= 0.40984 time= 0.00000
Epoch: 0005 train_loss= 1.01114 train_acc= 0.53636 val_loss= 0.80173 val_acc= 0.45902 time= 0.01563
Epoch: 0006 train_loss= 1.11019 train_acc= 0.52338 val_loss= 0.80091 val_acc= 0.45902 time= 0.02591
Epoch: 0007 train_loss= 0.75722 train_acc= 0.51818 val_loss= 0.80044 val_acc= 0.45902 time= 0.01260
Epoch: 0008 train_loss= 0.80348 train_acc= 0.51039 val_loss= 0.79932 val_acc= 0.45902 time= 0.01708
Epoch: 0009 train_loss= 0.85352 train_acc= 0.49610 val_loss= 0.80778 val_acc= 0.44262 time= 0.01320
Epoch: 0010 train_loss= 0.91090 train_acc= 0.52727 val_loss= 0.79230 val_acc= 0.45902 time= 0.01318
Epoch: 0011 train_loss= 0.78235 train_acc= 0.49481 val_loss= 0.78035 val_acc= 0.44262 time= 0.01368
Epoch: 0012 train_loss= 0.76661 train_acc= 0.50649 val_loss= 0.77535 val_acc= 0.44262 time= 0.00452
Epoch: 0013 train_loss= 0.83587 train_acc= 0.52338 val_loss= 0.77333 val_acc= 0.44262 time= 0.01562
Epoch: 0014 train_loss= 0.77019 train_acc= 0.52857 val_loss= 0.76802 val_acc= 0.45902 time= 0.01563
Epoch: 0015 train_loss= 0.87653 train_acc= 0.49870 val_loss= 0.76953 val_acc= 0.44262 time= 0.01563
Epoch: 0016 train_loss= 0.77456 train_acc= 0.49610 val_loss= 0.76964 val_acc= 0.39344 time= 0.01563
Epoch: 0017 train_loss= 0.98161 train_acc= 0.52857 val_loss= 0.75755 val_acc= 0.42623 time= 0.00000
Epoch: 0018 train_loss= 0.74659 train_acc= 0.52597 val_loss= 0.74674 val_acc= 0.47541 time= 0.01563
Epoch: 0019 train_loss= 0.85315 train_acc= 0.52338 val_loss= 0.73519 val_acc= 0.49180 time= 0.01562
Epoch: 0020 train_loss= 0.77155 train_acc= 0.52338 val_loss= 0.72681 val_acc= 0.50820 time= 0.01563
Epoch: 0021 train_loss= 0.79285 train_acc= 0.52597 val_loss= 0.71981 val_acc= 0.49180 time= 0.01563
Epoch: 0022 train_loss= 0.83181 train_acc= 0.51039 val_loss= 0.71614 val_acc= 0.47541 time= 0.01563
Epoch: 0023 train_loss= 0.72775 train_acc= 0.54675 val_loss= 0.71439 val_acc= 0.52459 time= 0.01637
Epoch: 0024 train_loss= 0.74591 train_acc= 0.47403 val_loss= 0.71320 val_acc= 0.50820 time= 0.01600
Epoch: 0025 train_loss= 0.72781 train_acc= 0.48831 val_loss= 0.71224 val_acc= 0.50820 time= 0.01600
Epoch: 0026 train_loss= 0.69534 train_acc= 0.54675 val_loss= 0.71163 val_acc= 0.50820 time= 0.01614
Epoch: 0027 train_loss= 0.70822 train_acc= 0.53247 val_loss= 0.71111 val_acc= 0.50820 time= 0.01511
Epoch: 0028 train_loss= 0.75187 train_acc= 0.50649 val_loss= 0.71013 val_acc= 0.52459 time= 0.01700
Epoch: 0029 train_loss= 0.72124 train_acc= 0.53247 val_loss= 0.70947 val_acc= 0.52459 time= 0.01718
Epoch: 0030 train_loss= 0.74832 train_acc= 0.47662 val_loss= 0.70868 val_acc= 0.52459 time= 0.01700
Epoch: 0031 train_loss= 0.70972 train_acc= 0.51818 val_loss= 0.70794 val_acc= 0.52459 time= 0.01700
Epoch: 0032 train_loss= 0.72216 train_acc= 0.53896 val_loss= 0.70736 val_acc= 0.52459 time= 0.01600
Epoch: 0033 train_loss= 0.74450 train_acc= 0.50779 val_loss= 0.70696 val_acc= 0.52459 time= 0.01400
Epoch: 0034 train_loss= 0.71036 train_acc= 0.54416 val_loss= 0.70651 val_acc= 0.49180 time= 0.01600
Epoch: 0035 train_loss= 0.69747 train_acc= 0.50130 val_loss= 0.70615 val_acc= 0.49180 time= 0.01617
Epoch: 0036 train_loss= 0.73641 train_acc= 0.51948 val_loss= 0.70587 val_acc= 0.49180 time= 0.01613
Epoch: 0037 train_loss= 0.71368 train_acc= 0.52727 val_loss= 0.70567 val_acc= 0.49180 time= 0.00500
Epoch: 0038 train_loss= 0.70935 train_acc= 0.52468 val_loss= 0.70531 val_acc= 0.50820 time= 0.01567
Epoch: 0039 train_loss= 0.71302 train_acc= 0.48442 val_loss= 0.70509 val_acc= 0.50820 time= 0.01563
Epoch: 0040 train_loss= 0.72024 train_acc= 0.52597 val_loss= 0.70489 val_acc= 0.50820 time= 0.01563
Epoch: 0041 train_loss= 0.70984 train_acc= 0.51818 val_loss= 0.70469 val_acc= 0.49180 time= 0.01989
Epoch: 0042 train_loss= 0.71469 train_acc= 0.54935 val_loss= 0.70454 val_acc= 0.49180 time= 0.01611
Epoch: 0043 train_loss= 0.71784 train_acc= 0.49351 val_loss= 0.70444 val_acc= 0.47541 time= 0.01607
Epoch: 0044 train_loss= 0.70064 train_acc= 0.53377 val_loss= 0.70426 val_acc= 0.47541 time= 0.01467
Epoch: 0045 train_loss= 0.74400 train_acc= 0.50390 val_loss= 0.70401 val_acc= 0.49180 time= 0.01375
Epoch: 0046 train_loss= 0.71818 train_acc= 0.48571 val_loss= 0.70380 val_acc= 0.49180 time= 0.01615
Epoch: 0047 train_loss= 0.74481 train_acc= 0.51818 val_loss= 0.70359 val_acc= 0.47541 time= 0.01711
Epoch: 0048 train_loss= 0.70651 train_acc= 0.49091 val_loss= 0.70332 val_acc= 0.47541 time= 0.01517
Epoch: 0049 train_loss= 0.70289 train_acc= 0.55455 val_loss= 0.70303 val_acc= 0.47541 time= 0.01512
Epoch: 0050 train_loss= 0.74253 train_acc= 0.50779 val_loss= 0.70259 val_acc= 0.49180 time= 0.01522
Epoch: 0051 train_loss= 0.70089 train_acc= 0.53377 val_loss= 0.70218 val_acc= 0.47541 time= 0.01609
Epoch: 0052 train_loss= 0.71071 train_acc= 0.51948 val_loss= 0.70175 val_acc= 0.50820 time= 0.01600
Epoch: 0053 train_loss= 0.69715 train_acc= 0.48961 val_loss= 0.70137 val_acc= 0.52459 time= 0.01600
Epoch: 0054 train_loss= 0.70890 train_acc= 0.49870 val_loss= 0.70103 val_acc= 0.52459 time= 0.01600
Epoch: 0055 train_loss= 0.72732 train_acc= 0.51169 val_loss= 0.70080 val_acc= 0.50820 time= 0.01700
Epoch: 0056 train_loss= 0.70484 train_acc= 0.50390 val_loss= 0.70061 val_acc= 0.50820 time= 0.01500
Epoch: 0057 train_loss= 0.71013 train_acc= 0.51818 val_loss= 0.70045 val_acc= 0.49180 time= 0.01700
Epoch: 0058 train_loss= 0.70078 train_acc= 0.52857 val_loss= 0.70039 val_acc= 0.50820 time= 0.01525
Epoch: 0059 train_loss= 0.69629 train_acc= 0.54416 val_loss= 0.70025 val_acc= 0.47541 time= 0.02018
Epoch: 0060 train_loss= 0.70419 train_acc= 0.51429 val_loss= 0.70015 val_acc= 0.49180 time= 0.01800
Epoch: 0061 train_loss= 0.70217 train_acc= 0.51429 val_loss= 0.70004 val_acc= 0.50820 time= 0.01800
Epoch: 0062 train_loss= 0.70721 train_acc= 0.50390 val_loss= 0.69999 val_acc= 0.50820 time= 0.01600
Epoch: 0063 train_loss= 0.69673 train_acc= 0.51299 val_loss= 0.69996 val_acc= 0.50820 time= 0.01700
Epoch: 0064 train_loss= 0.69496 train_acc= 0.53636 val_loss= 0.69987 val_acc= 0.50820 time= 0.01500
Epoch: 0065 train_loss= 0.70007 train_acc= 0.53506 val_loss= 0.69969 val_acc= 0.52459 time= 0.01500
Epoch: 0066 train_loss= 0.70427 train_acc= 0.50000 val_loss= 0.69954 val_acc= 0.50820 time= 0.00600
Epoch: 0067 train_loss= 0.70841 train_acc= 0.51299 val_loss= 0.69932 val_acc= 0.50820 time= 0.01567
Epoch: 0068 train_loss= 0.70668 train_acc= 0.51558 val_loss= 0.69926 val_acc= 0.49180 time= 0.01563
Epoch: 0069 train_loss= 0.69502 train_acc= 0.52208 val_loss= 0.69925 val_acc= 0.49180 time= 0.00000
Epoch: 0070 train_loss= 0.69966 train_acc= 0.54545 val_loss= 0.69920 val_acc= 0.47541 time= 0.01563
Epoch: 0071 train_loss= 0.71049 train_acc= 0.53896 val_loss= 0.69915 val_acc= 0.47541 time= 0.01562
Epoch: 0072 train_loss= 0.71540 train_acc= 0.49610 val_loss= 0.69913 val_acc= 0.45902 time= 0.01563
Epoch: 0073 train_loss= 0.69760 train_acc= 0.52597 val_loss= 0.69908 val_acc= 0.45902 time= 0.01563
Epoch: 0074 train_loss= 0.69940 train_acc= 0.52727 val_loss= 0.69900 val_acc= 0.45902 time= 0.01563
Epoch: 0075 train_loss= 0.69871 train_acc= 0.53377 val_loss= 0.69905 val_acc= 0.45902 time= 0.00000
Epoch: 0076 train_loss= 0.69347 train_acc= 0.51429 val_loss= 0.69908 val_acc= 0.45902 time= 0.02043
Epoch: 0077 train_loss= 0.70909 train_acc= 0.53247 val_loss= 0.69912 val_acc= 0.49180 time= 0.01100
Epoch: 0078 train_loss= 0.72749 train_acc= 0.52987 val_loss= 0.69925 val_acc= 0.49180 time= 0.01563
Early stopping...
Optimization Finished!
Test set results: cost= 0.69588 accuracy= 0.50000 time= 0.00000 
