Epoch: 0001 train_loss= 1.39408 train_acc= 0.28013 val_loss= 1.38992 val_acc= 0.33929 time= 0.15626
Epoch: 0002 train_loss= 1.39083 train_acc= 0.29642 val_loss= 1.38590 val_acc= 0.33929 time= 0.01563
Epoch: 0003 train_loss= 1.38815 train_acc= 0.29642 val_loss= 1.38229 val_acc= 0.33929 time= 0.01563
Epoch: 0004 train_loss= 1.38591 train_acc= 0.29642 val_loss= 1.37922 val_acc= 0.33929 time= 0.01563
Epoch: 0005 train_loss= 1.38481 train_acc= 0.29642 val_loss= 1.37672 val_acc= 0.33929 time= 0.01563
Epoch: 0006 train_loss= 1.38348 train_acc= 0.29642 val_loss= 1.37468 val_acc= 0.33929 time= 0.01563
Epoch: 0007 train_loss= 1.38298 train_acc= 0.29642 val_loss= 1.37312 val_acc= 0.33929 time= 0.01563
Epoch: 0008 train_loss= 1.38283 train_acc= 0.29642 val_loss= 1.37197 val_acc= 0.33929 time= 0.01563
Epoch: 0009 train_loss= 1.38227 train_acc= 0.29642 val_loss= 1.37114 val_acc= 0.33929 time= 0.01563
Epoch: 0010 train_loss= 1.38187 train_acc= 0.29642 val_loss= 1.37060 val_acc= 0.33929 time= 0.01563
Epoch: 0011 train_loss= 1.38181 train_acc= 0.29642 val_loss= 1.37019 val_acc= 0.33929 time= 0.01563
Epoch: 0012 train_loss= 1.38202 train_acc= 0.29642 val_loss= 1.36990 val_acc= 0.33929 time= 0.01563
Epoch: 0013 train_loss= 1.38159 train_acc= 0.29642 val_loss= 1.36973 val_acc= 0.33929 time= 0.01563
Epoch: 0014 train_loss= 1.38179 train_acc= 0.29642 val_loss= 1.36968 val_acc= 0.33929 time= 0.01563
Epoch: 0015 train_loss= 1.38182 train_acc= 0.29642 val_loss= 1.36969 val_acc= 0.33929 time= 0.01563
Epoch: 0016 train_loss= 1.38093 train_acc= 0.29642 val_loss= 1.36978 val_acc= 0.33929 time= 0.01563
Epoch: 0017 train_loss= 1.38081 train_acc= 0.29642 val_loss= 1.36981 val_acc= 0.33929 time= 0.01563
Epoch: 0018 train_loss= 1.38105 train_acc= 0.29642 val_loss= 1.36987 val_acc= 0.33929 time= 0.01563
Epoch: 0019 train_loss= 1.38141 train_acc= 0.29642 val_loss= 1.36988 val_acc= 0.33929 time= 0.01563
Epoch: 0020 train_loss= 1.38031 train_acc= 0.29642 val_loss= 1.36980 val_acc= 0.33929 time= 0.01563
Epoch: 0021 train_loss= 1.37997 train_acc= 0.29642 val_loss= 1.36961 val_acc= 0.33929 time= 0.01563
Epoch: 0022 train_loss= 1.38015 train_acc= 0.29642 val_loss= 1.36936 val_acc= 0.33929 time= 0.01563
Epoch: 0023 train_loss= 1.38036 train_acc= 0.29642 val_loss= 1.36909 val_acc= 0.33929 time= 0.01563
Epoch: 0024 train_loss= 1.38010 train_acc= 0.29642 val_loss= 1.36872 val_acc= 0.33929 time= 0.01563
Epoch: 0025 train_loss= 1.37945 train_acc= 0.29642 val_loss= 1.36835 val_acc= 0.33929 time= 0.01563
Epoch: 0026 train_loss= 1.37997 train_acc= 0.29642 val_loss= 1.36800 val_acc= 0.33929 time= 0.01563
Epoch: 0027 train_loss= 1.37921 train_acc= 0.29642 val_loss= 1.36764 val_acc= 0.33929 time= 0.01563
Epoch: 0028 train_loss= 1.37951 train_acc= 0.29642 val_loss= 1.36738 val_acc= 0.33929 time= 0.01563
Epoch: 0029 train_loss= 1.38036 train_acc= 0.29642 val_loss= 1.36724 val_acc= 0.33929 time= 0.01563
Epoch: 0030 train_loss= 1.37923 train_acc= 0.29642 val_loss= 1.36720 val_acc= 0.33929 time= 0.01563
Epoch: 0031 train_loss= 1.37928 train_acc= 0.29642 val_loss= 1.36709 val_acc= 0.33929 time= 0.01563
Epoch: 0032 train_loss= 1.37857 train_acc= 0.29642 val_loss= 1.36694 val_acc= 0.33929 time= 0.01563
Epoch: 0033 train_loss= 1.37901 train_acc= 0.29642 val_loss= 1.36694 val_acc= 0.33929 time= 0.01563
Epoch: 0034 train_loss= 1.37965 train_acc= 0.29642 val_loss= 1.36697 val_acc= 0.33929 time= 0.01563
Epoch: 0035 train_loss= 1.37917 train_acc= 0.29642 val_loss= 1.36703 val_acc= 0.33929 time= 0.01563
Epoch: 0036 train_loss= 1.37912 train_acc= 0.29642 val_loss= 1.36709 val_acc= 0.33929 time= 0.01563
Epoch: 0037 train_loss= 1.37843 train_acc= 0.29642 val_loss= 1.36697 val_acc= 0.33929 time= 0.01563
Epoch: 0038 train_loss= 1.37876 train_acc= 0.29642 val_loss= 1.36688 val_acc= 0.33929 time= 0.01563
Epoch: 0039 train_loss= 1.37852 train_acc= 0.29642 val_loss= 1.36661 val_acc= 0.33929 time= 0.00000
Epoch: 0040 train_loss= 1.37868 train_acc= 0.29642 val_loss= 1.36618 val_acc= 0.33929 time= 0.01563
Epoch: 0041 train_loss= 1.37883 train_acc= 0.29642 val_loss= 1.36586 val_acc= 0.33929 time= 0.01563
Epoch: 0042 train_loss= 1.37859 train_acc= 0.29642 val_loss= 1.36559 val_acc= 0.33929 time= 0.01563
Epoch: 0043 train_loss= 1.37840 train_acc= 0.29642 val_loss= 1.36551 val_acc= 0.33929 time= 0.01563
Epoch: 0044 train_loss= 1.37837 train_acc= 0.29642 val_loss= 1.36562 val_acc= 0.33929 time= 0.01563
Epoch: 0045 train_loss= 1.37900 train_acc= 0.29642 val_loss= 1.36593 val_acc= 0.33929 time= 0.01563
Epoch: 0046 train_loss= 1.37754 train_acc= 0.29642 val_loss= 1.36598 val_acc= 0.33929 time= 0.01563
Epoch: 0047 train_loss= 1.37844 train_acc= 0.29642 val_loss= 1.36583 val_acc= 0.33929 time= 0.01563
Epoch: 0048 train_loss= 1.37808 train_acc= 0.29642 val_loss= 1.36563 val_acc= 0.33929 time= 0.01563
Epoch: 0049 train_loss= 1.37806 train_acc= 0.29642 val_loss= 1.36541 val_acc= 0.33929 time= 0.01563
Epoch: 0050 train_loss= 1.37805 train_acc= 0.29642 val_loss= 1.36536 val_acc= 0.33929 time= 0.01563
Epoch: 0051 train_loss= 1.37860 train_acc= 0.29642 val_loss= 1.36525 val_acc= 0.33929 time= 0.01563
Epoch: 0052 train_loss= 1.37754 train_acc= 0.29642 val_loss= 1.36521 val_acc= 0.33929 time= 0.00000
Epoch: 0053 train_loss= 1.37780 train_acc= 0.29642 val_loss= 1.36507 val_acc= 0.33929 time= 0.00000
Epoch: 0054 train_loss= 1.37825 train_acc= 0.29642 val_loss= 1.36496 val_acc= 0.33929 time= 0.01563
Epoch: 0055 train_loss= 1.37745 train_acc= 0.29642 val_loss= 1.36479 val_acc= 0.33929 time= 0.01563
Epoch: 0056 train_loss= 1.37820 train_acc= 0.29642 val_loss= 1.36464 val_acc= 0.33929 time= 0.01563
Epoch: 0057 train_loss= 1.37698 train_acc= 0.29642 val_loss= 1.36463 val_acc= 0.33929 time= 0.01563
Epoch: 0058 train_loss= 1.37710 train_acc= 0.29642 val_loss= 1.36467 val_acc= 0.33929 time= 0.01563
Epoch: 0059 train_loss= 1.37779 train_acc= 0.29642 val_loss= 1.36478 val_acc= 0.33929 time= 0.01563
Epoch: 0060 train_loss= 1.37757 train_acc= 0.29642 val_loss= 1.36504 val_acc= 0.33929 time= 0.01563
Early stopping...
Optimization Finished!
Test set results: cost= 1.35728 accuracy= 0.36283 time= 0.01563 
