Epoch: 0001 train_loss= 2.14994 train_acc= 0.27095 val_loss= 1.35223 val_acc= 0.33929 time= 0.92194
Epoch: 0002 train_loss= 3.04043 train_acc= 0.25559 val_loss= 1.40671 val_acc= 0.23214 time= 0.01563
Epoch: 0003 train_loss= 2.39701 train_acc= 0.26536 val_loss= 1.55422 val_acc= 0.12500 time= 0.03125
Epoch: 0004 train_loss= 2.26037 train_acc= 0.29190 val_loss= 1.50097 val_acc= 0.14286 time= 0.01563
Epoch: 0005 train_loss= 2.00606 train_acc= 0.24302 val_loss= 1.61510 val_acc= 0.16071 time= 0.03125
Epoch: 0006 train_loss= 1.76535 train_acc= 0.31285 val_loss= 1.68063 val_acc= 0.16071 time= 0.03125
Epoch: 0007 train_loss= 2.05749 train_acc= 0.25978 val_loss= 1.76299 val_acc= 0.16071 time= 0.01563
Epoch: 0008 train_loss= 1.62435 train_acc= 0.26397 val_loss= 1.72348 val_acc= 0.12500 time= 0.03125
Epoch: 0009 train_loss= 2.00503 train_acc= 0.29330 val_loss= 1.64530 val_acc= 0.12500 time= 0.01563
Epoch: 0010 train_loss= 2.30606 train_acc= 0.28631 val_loss= 1.51980 val_acc= 0.12500 time= 0.03125
Epoch: 0011 train_loss= 1.49027 train_acc= 0.25559 val_loss= 1.47104 val_acc= 0.12500 time= 0.03125
Epoch: 0012 train_loss= 1.72912 train_acc= 0.24022 val_loss= 1.42260 val_acc= 0.17857 time= 0.01563
Epoch: 0013 train_loss= 1.76539 train_acc= 0.27374 val_loss= 1.42564 val_acc= 0.23214 time= 0.03125
Epoch: 0014 train_loss= 1.41353 train_acc= 0.24302 val_loss= 1.42798 val_acc= 0.23214 time= 0.01563
Epoch: 0015 train_loss= 1.43414 train_acc= 0.24721 val_loss= 1.42736 val_acc= 0.23214 time= 0.03125
Epoch: 0016 train_loss= 1.38557 train_acc= 0.28911 val_loss= 1.42671 val_acc= 0.21429 time= 0.01563
Epoch: 0017 train_loss= 1.39185 train_acc= 0.27514 val_loss= 1.42615 val_acc= 0.21429 time= 0.03125
Epoch: 0018 train_loss= 1.44333 train_acc= 0.26816 val_loss= 1.42560 val_acc= 0.21429 time= 0.03125
Epoch: 0019 train_loss= 1.39005 train_acc= 0.28911 val_loss= 1.42515 val_acc= 0.21429 time= 0.01563
Epoch: 0020 train_loss= 1.52981 train_acc= 0.25559 val_loss= 1.42516 val_acc= 0.23214 time= 0.03125
Epoch: 0021 train_loss= 1.39318 train_acc= 0.27095 val_loss= 1.42487 val_acc= 0.23214 time= 0.03125
Epoch: 0022 train_loss= 1.39940 train_acc= 0.28911 val_loss= 1.42440 val_acc= 0.21429 time= 0.01563
Epoch: 0023 train_loss= 1.38828 train_acc= 0.30168 val_loss= 1.42373 val_acc= 0.19643 time= 0.03125
Epoch: 0024 train_loss= 1.58519 train_acc= 0.27933 val_loss= 1.42331 val_acc= 0.19643 time= 0.03125
Epoch: 0025 train_loss= 1.39375 train_acc= 0.30168 val_loss= 1.42280 val_acc= 0.19643 time= 0.03125
Epoch: 0026 train_loss= 1.39393 train_acc= 0.29330 val_loss= 1.42226 val_acc= 0.21429 time= 0.02062
Epoch: 0027 train_loss= 1.39162 train_acc= 0.26955 val_loss= 1.42148 val_acc= 0.21429 time= 0.02663
Epoch: 0028 train_loss= 1.38175 train_acc= 0.31704 val_loss= 1.42078 val_acc= 0.21429 time= 0.01563
Epoch: 0029 train_loss= 1.40061 train_acc= 0.31006 val_loss= 1.42003 val_acc= 0.21429 time= 0.03125
Epoch: 0030 train_loss= 1.41570 train_acc= 0.26397 val_loss= 1.41946 val_acc= 0.19643 time= 0.01563
Epoch: 0031 train_loss= 1.38726 train_acc= 0.30726 val_loss= 1.41890 val_acc= 0.19643 time= 0.03125
Epoch: 0032 train_loss= 1.39840 train_acc= 0.30866 val_loss= 1.41823 val_acc= 0.19643 time= 0.03125
Epoch: 0033 train_loss= 1.39735 train_acc= 0.31704 val_loss= 1.41767 val_acc= 0.17857 time= 0.01562
Epoch: 0034 train_loss= 1.41750 train_acc= 0.29609 val_loss= 1.41705 val_acc= 0.19643 time= 0.03125
Epoch: 0035 train_loss= 1.38677 train_acc= 0.30028 val_loss= 1.41650 val_acc= 0.17857 time= 0.03125
Epoch: 0036 train_loss= 1.38287 train_acc= 0.29050 val_loss= 1.41587 val_acc= 0.21429 time= 0.01563
Epoch: 0037 train_loss= 1.39577 train_acc= 0.29609 val_loss= 1.41534 val_acc= 0.21429 time= 0.01563
Epoch: 0038 train_loss= 1.43798 train_acc= 0.31425 val_loss= 1.41485 val_acc= 0.19643 time= 0.03125
Epoch: 0039 train_loss= 1.38611 train_acc= 0.31844 val_loss= 1.41446 val_acc= 0.19643 time= 0.03125
Epoch: 0040 train_loss= 1.37970 train_acc= 0.31564 val_loss= 1.41410 val_acc= 0.21429 time= 0.01563
Epoch: 0041 train_loss= 1.38323 train_acc= 0.30866 val_loss= 1.41372 val_acc= 0.21429 time= 0.03125
Epoch: 0042 train_loss= 1.38911 train_acc= 0.30028 val_loss= 1.41342 val_acc= 0.21429 time= 0.03125
Epoch: 0043 train_loss= 1.38992 train_acc= 0.27514 val_loss= 1.41313 val_acc= 0.21429 time= 0.01563
Epoch: 0044 train_loss= 1.37995 train_acc= 0.30028 val_loss= 1.41289 val_acc= 0.21429 time= 0.03125
Epoch: 0045 train_loss= 1.39213 train_acc= 0.30726 val_loss= 1.41257 val_acc= 0.19643 time= 0.01563
Epoch: 0046 train_loss= 1.38195 train_acc= 0.30168 val_loss= 1.41229 val_acc= 0.19643 time= 0.03125
Epoch: 0047 train_loss= 1.37738 train_acc= 0.32123 val_loss= 1.41205 val_acc= 0.19643 time= 0.01563
Epoch: 0048 train_loss= 1.38634 train_acc= 0.31285 val_loss= 1.41170 val_acc= 0.19643 time= 0.03125
Epoch: 0049 train_loss= 1.38852 train_acc= 0.30307 val_loss= 1.41136 val_acc= 0.19643 time= 0.03125
Epoch: 0050 train_loss= 1.39161 train_acc= 0.31145 val_loss= 1.41095 val_acc= 0.19643 time= 0.01563
Epoch: 0051 train_loss= 1.37898 train_acc= 0.29749 val_loss= 1.41045 val_acc= 0.19643 time= 0.03125
Epoch: 0052 train_loss= 1.39280 train_acc= 0.28492 val_loss= 1.40992 val_acc= 0.19643 time= 0.03125
Epoch: 0053 train_loss= 1.48448 train_acc= 0.27514 val_loss= 1.40961 val_acc= 0.19643 time= 0.03125
Epoch: 0054 train_loss= 1.38425 train_acc= 0.31006 val_loss= 1.40934 val_acc= 0.19643 time= 0.01563
Epoch: 0055 train_loss= 1.38439 train_acc= 0.30866 val_loss= 1.40897 val_acc= 0.19643 time= 0.03125
Epoch: 0056 train_loss= 1.38874 train_acc= 0.29050 val_loss= 1.40870 val_acc= 0.19643 time= 0.01563
Epoch: 0057 train_loss= 1.38722 train_acc= 0.30028 val_loss= 1.40862 val_acc= 0.19643 time= 0.03125
Epoch: 0058 train_loss= 1.38569 train_acc= 0.30028 val_loss= 1.40852 val_acc= 0.19643 time= 0.01563
Epoch: 0059 train_loss= 1.37724 train_acc= 0.31844 val_loss= 1.40847 val_acc= 0.19643 time= 0.03125
Epoch: 0060 train_loss= 1.38124 train_acc= 0.31145 val_loss= 1.40843 val_acc= 0.19643 time= 0.01563
Epoch: 0061 train_loss= 1.38893 train_acc= 0.30587 val_loss= 1.40834 val_acc= 0.19643 time= 0.03125
Epoch: 0062 train_loss= 1.37921 train_acc= 0.31844 val_loss= 1.40834 val_acc= 0.19643 time= 0.03125
Epoch: 0063 train_loss= 1.38287 train_acc= 0.31983 val_loss= 1.40829 val_acc= 0.19643 time= 0.01563
Epoch: 0064 train_loss= 1.38485 train_acc= 0.31006 val_loss= 1.40824 val_acc= 0.19643 time= 0.03125
Epoch: 0065 train_loss= 1.37953 train_acc= 0.32961 val_loss= 1.40816 val_acc= 0.19643 time= 0.01563
Epoch: 0066 train_loss= 1.37935 train_acc= 0.29888 val_loss= 1.40815 val_acc= 0.19643 time= 0.03125
Epoch: 0067 train_loss= 1.37813 train_acc= 0.30866 val_loss= 1.40812 val_acc= 0.19643 time= 0.01563
Epoch: 0068 train_loss= 1.39111 train_acc= 0.30168 val_loss= 1.40800 val_acc= 0.19643 time= 0.03125
Epoch: 0069 train_loss= 1.38110 train_acc= 0.30726 val_loss= 1.40792 val_acc= 0.19643 time= 0.03125
Epoch: 0070 train_loss= 1.37663 train_acc= 0.30866 val_loss= 1.40793 val_acc= 0.19643 time= 0.01563
Epoch: 0071 train_loss= 1.38058 train_acc= 0.31006 val_loss= 1.40789 val_acc= 0.19643 time= 0.03125
Epoch: 0072 train_loss= 1.37201 train_acc= 0.32402 val_loss= 1.40791 val_acc= 0.19643 time= 0.01563
Epoch: 0073 train_loss= 1.38255 train_acc= 0.30726 val_loss= 1.40799 val_acc= 0.19643 time= 0.03125
Epoch: 0074 train_loss= 1.37987 train_acc= 0.31145 val_loss= 1.40818 val_acc= 0.19643 time= 0.03125
Early stopping...
Optimization Finished!
Test set results: cost= 1.38245 accuracy= 0.30973 time= 0.00000 
