Epoch: 0001 train_loss= 0.69852 train_acc= 0.51558 val_loss= 0.70077 val_acc= 0.46774 time= 0.68581
Epoch: 0002 train_loss= 0.69801 train_acc= 0.51558 val_loss= 0.70234 val_acc= 0.46774 time= 0.01400
Epoch: 0003 train_loss= 0.69711 train_acc= 0.51818 val_loss= 0.70331 val_acc= 0.46774 time= 0.01500
Epoch: 0004 train_loss= 0.69754 train_acc= 0.51818 val_loss= 0.70336 val_acc= 0.46774 time= 0.01500
Epoch: 0005 train_loss= 0.69615 train_acc= 0.51948 val_loss= 0.70305 val_acc= 0.46774 time= 0.01800
Epoch: 0006 train_loss= 0.69650 train_acc= 0.51818 val_loss= 0.70237 val_acc= 0.46774 time= 0.01400
Epoch: 0007 train_loss= 0.69571 train_acc= 0.51688 val_loss= 0.70159 val_acc= 0.46774 time= 0.00000
Epoch: 0008 train_loss= 0.69478 train_acc= 0.51948 val_loss= 0.70088 val_acc= 0.46774 time= 0.01566
Epoch: 0009 train_loss= 0.69515 train_acc= 0.51688 val_loss= 0.70021 val_acc= 0.46774 time= 0.01563
Epoch: 0010 train_loss= 0.69475 train_acc= 0.51948 val_loss= 0.69976 val_acc= 0.46774 time= 0.01563
Epoch: 0011 train_loss= 0.69459 train_acc= 0.51558 val_loss= 0.69938 val_acc= 0.46774 time= 0.01563
Epoch: 0012 train_loss= 0.69393 train_acc= 0.51688 val_loss= 0.69909 val_acc= 0.46774 time= 0.01562
Epoch: 0013 train_loss= 0.69424 train_acc= 0.51818 val_loss= 0.69883 val_acc= 0.46774 time= 0.01770
Epoch: 0014 train_loss= 0.69432 train_acc= 0.51688 val_loss= 0.69856 val_acc= 0.46774 time= 0.01400
Epoch: 0015 train_loss= 0.69363 train_acc= 0.51948 val_loss= 0.69836 val_acc= 0.46774 time= 0.01300
Epoch: 0016 train_loss= 0.69343 train_acc= 0.51948 val_loss= 0.69831 val_acc= 0.46774 time= 0.01300
Epoch: 0017 train_loss= 0.69394 train_acc= 0.51429 val_loss= 0.69823 val_acc= 0.46774 time= 0.01605
Epoch: 0018 train_loss= 0.69351 train_acc= 0.52078 val_loss= 0.69807 val_acc= 0.46774 time= 0.01496
Epoch: 0019 train_loss= 0.69295 train_acc= 0.51948 val_loss= 0.69808 val_acc= 0.46774 time= 0.01400
Epoch: 0020 train_loss= 0.69302 train_acc= 0.51948 val_loss= 0.69796 val_acc= 0.46774 time= 0.05001
Epoch: 0021 train_loss= 0.69272 train_acc= 0.51818 val_loss= 0.69798 val_acc= 0.46774 time= 0.01700
Epoch: 0022 train_loss= 0.69289 train_acc= 0.51948 val_loss= 0.69805 val_acc= 0.46774 time= 0.01600
Epoch: 0023 train_loss= 0.69301 train_acc= 0.51688 val_loss= 0.69796 val_acc= 0.46774 time= 0.01500
Epoch: 0024 train_loss= 0.69319 train_acc= 0.51948 val_loss= 0.69761 val_acc= 0.46774 time= 0.01600
Epoch: 0025 train_loss= 0.69265 train_acc= 0.51818 val_loss= 0.69733 val_acc= 0.46774 time= 0.01400
Epoch: 0026 train_loss= 0.69238 train_acc= 0.51948 val_loss= 0.69714 val_acc= 0.46774 time= 0.01400
Epoch: 0027 train_loss= 0.69231 train_acc= 0.51818 val_loss= 0.69714 val_acc= 0.46774 time= 0.01300
Epoch: 0028 train_loss= 0.69271 train_acc= 0.51948 val_loss= 0.69711 val_acc= 0.46774 time= 0.01300
Epoch: 0029 train_loss= 0.69217 train_acc= 0.52078 val_loss= 0.69731 val_acc= 0.46774 time= 0.01513
Epoch: 0030 train_loss= 0.69257 train_acc= 0.51948 val_loss= 0.69744 val_acc= 0.46774 time= 0.01726
Epoch: 0031 train_loss= 0.69263 train_acc= 0.51948 val_loss= 0.69750 val_acc= 0.46774 time= 0.01300
Epoch: 0032 train_loss= 0.69289 train_acc= 0.51818 val_loss= 0.69737 val_acc= 0.46774 time= 0.01309
Epoch: 0033 train_loss= 0.69205 train_acc= 0.51818 val_loss= 0.69733 val_acc= 0.46774 time= 0.00906
Epoch: 0034 train_loss= 0.69261 train_acc= 0.51948 val_loss= 0.69726 val_acc= 0.46774 time= 0.01562
Epoch: 0035 train_loss= 0.69254 train_acc= 0.51948 val_loss= 0.69712 val_acc= 0.46774 time= 0.01468
Epoch: 0036 train_loss= 0.69237 train_acc= 0.51948 val_loss= 0.69709 val_acc= 0.46774 time= 0.01415
Epoch: 0037 train_loss= 0.69240 train_acc= 0.51948 val_loss= 0.69697 val_acc= 0.46774 time= 0.01312
Epoch: 0038 train_loss= 0.69206 train_acc= 0.51948 val_loss= 0.69708 val_acc= 0.46774 time= 0.01310
Epoch: 0039 train_loss= 0.69212 train_acc= 0.51948 val_loss= 0.69724 val_acc= 0.46774 time= 0.01416
Epoch: 0040 train_loss= 0.69251 train_acc= 0.51948 val_loss= 0.69748 val_acc= 0.46774 time= 0.01604
Early stopping...
Optimization Finished!
Test set results: cost= 0.68737 accuracy= 0.55645 time= 0.00700 
