Epoch: 0001 train_loss= 1.39400 train_acc= 0.28492 val_loss= 1.38994 val_acc= 0.33929 time= 0.76579
Epoch: 0002 train_loss= 1.39074 train_acc= 0.29190 val_loss= 1.38595 val_acc= 0.33929 time= 0.00000
Epoch: 0003 train_loss= 1.38784 train_acc= 0.29190 val_loss= 1.38251 val_acc= 0.33929 time= 0.01563
Epoch: 0004 train_loss= 1.38591 train_acc= 0.29190 val_loss= 1.37984 val_acc= 0.33929 time= 0.01562
Epoch: 0005 train_loss= 1.38462 train_acc= 0.29190 val_loss= 1.37785 val_acc= 0.33929 time= 0.01563
Epoch: 0006 train_loss= 1.38381 train_acc= 0.29190 val_loss= 1.37647 val_acc= 0.33929 time= 0.01563
Epoch: 0007 train_loss= 1.38340 train_acc= 0.29190 val_loss= 1.37559 val_acc= 0.33929 time= 0.01562
Epoch: 0008 train_loss= 1.38337 train_acc= 0.29190 val_loss= 1.37513 val_acc= 0.33929 time= 0.01563
Epoch: 0009 train_loss= 1.38307 train_acc= 0.29190 val_loss= 1.37490 val_acc= 0.33929 time= 0.01563
Epoch: 0010 train_loss= 1.38290 train_acc= 0.29190 val_loss= 1.37485 val_acc= 0.33929 time= 0.00000
Epoch: 0011 train_loss= 1.38300 train_acc= 0.29190 val_loss= 1.37486 val_acc= 0.33929 time= 0.01563
Epoch: 0012 train_loss= 1.38308 train_acc= 0.29190 val_loss= 1.37497 val_acc= 0.33929 time= 0.01562
Epoch: 0013 train_loss= 1.38311 train_acc= 0.29190 val_loss= 1.37510 val_acc= 0.33929 time= 0.01563
Epoch: 0014 train_loss= 1.38275 train_acc= 0.29190 val_loss= 1.37525 val_acc= 0.33929 time= 0.01563
Epoch: 0015 train_loss= 1.38261 train_acc= 0.29190 val_loss= 1.37530 val_acc= 0.33929 time= 0.01562
Epoch: 0016 train_loss= 1.38248 train_acc= 0.29190 val_loss= 1.37523 val_acc= 0.33929 time= 0.00000
Epoch: 0017 train_loss= 1.38178 train_acc= 0.29190 val_loss= 1.37498 val_acc= 0.33929 time= 0.01563
Epoch: 0018 train_loss= 1.38194 train_acc= 0.29190 val_loss= 1.37460 val_acc= 0.33929 time= 0.01563
Epoch: 0019 train_loss= 1.38213 train_acc= 0.29190 val_loss= 1.37423 val_acc= 0.33929 time= 0.01563
Epoch: 0020 train_loss= 1.38175 train_acc= 0.29190 val_loss= 1.37384 val_acc= 0.33929 time= 0.01563
Epoch: 0021 train_loss= 1.38148 train_acc= 0.29190 val_loss= 1.37344 val_acc= 0.33929 time= 0.00000
Epoch: 0022 train_loss= 1.38134 train_acc= 0.29190 val_loss= 1.37319 val_acc= 0.33929 time= 0.00000
Epoch: 0023 train_loss= 1.38142 train_acc= 0.29190 val_loss= 1.37311 val_acc= 0.33929 time= 0.01563
Epoch: 0024 train_loss= 1.38093 train_acc= 0.29190 val_loss= 1.37318 val_acc= 0.33929 time= 0.01563
Epoch: 0025 train_loss= 1.38093 train_acc= 0.29190 val_loss= 1.37327 val_acc= 0.33929 time= 0.01563
Epoch: 0026 train_loss= 1.38080 train_acc= 0.29190 val_loss= 1.37339 val_acc= 0.33929 time= 0.01563
Epoch: 0027 train_loss= 1.38030 train_acc= 0.29190 val_loss= 1.37337 val_acc= 0.33929 time= 0.00000
Epoch: 0028 train_loss= 1.38109 train_acc= 0.29190 val_loss= 1.37335 val_acc= 0.33929 time= 0.01563
Epoch: 0029 train_loss= 1.38065 train_acc= 0.29190 val_loss= 1.37322 val_acc= 0.33929 time= 0.01563
Epoch: 0030 train_loss= 1.38070 train_acc= 0.29190 val_loss= 1.37304 val_acc= 0.33929 time= 0.01563
Epoch: 0031 train_loss= 1.38038 train_acc= 0.29190 val_loss= 1.37288 val_acc= 0.33929 time= 0.01563
Epoch: 0032 train_loss= 1.38009 train_acc= 0.29190 val_loss= 1.37267 val_acc= 0.33929 time= 0.01562
Epoch: 0033 train_loss= 1.38032 train_acc= 0.29190 val_loss= 1.37247 val_acc= 0.33929 time= 0.01563
Epoch: 0034 train_loss= 1.37987 train_acc= 0.29190 val_loss= 1.37219 val_acc= 0.33929 time= 0.01563
Epoch: 0035 train_loss= 1.38037 train_acc= 0.29190 val_loss= 1.37200 val_acc= 0.33929 time= 0.01563
Epoch: 0036 train_loss= 1.37990 train_acc= 0.29190 val_loss= 1.37196 val_acc= 0.33929 time= 0.01563
Epoch: 0037 train_loss= 1.38041 train_acc= 0.29190 val_loss= 1.37190 val_acc= 0.33929 time= 0.01563
Epoch: 0038 train_loss= 1.38037 train_acc= 0.29190 val_loss= 1.37189 val_acc= 0.33929 time= 0.00000
Epoch: 0039 train_loss= 1.37999 train_acc= 0.29190 val_loss= 1.37191 val_acc= 0.33929 time= 0.01563
Epoch: 0040 train_loss= 1.37964 train_acc= 0.29190 val_loss= 1.37191 val_acc= 0.33929 time= 0.01563
Epoch: 0041 train_loss= 1.37953 train_acc= 0.29190 val_loss= 1.37178 val_acc= 0.33929 time= 0.01563
Epoch: 0042 train_loss= 1.37985 train_acc= 0.29190 val_loss= 1.37155 val_acc= 0.33929 time= 0.01563
Epoch: 0043 train_loss= 1.37974 train_acc= 0.29190 val_loss= 1.37139 val_acc= 0.33929 time= 0.00000
Epoch: 0044 train_loss= 1.37972 train_acc= 0.29190 val_loss= 1.37132 val_acc= 0.33929 time= 0.01563
Epoch: 0045 train_loss= 1.37969 train_acc= 0.29190 val_loss= 1.37149 val_acc= 0.33929 time= 0.01563
Epoch: 0046 train_loss= 1.37891 train_acc= 0.29190 val_loss= 1.37147 val_acc= 0.33929 time= 0.01562
Epoch: 0047 train_loss= 1.37917 train_acc= 0.29190 val_loss= 1.37129 val_acc= 0.33929 time= 0.01563
Epoch: 0048 train_loss= 1.37913 train_acc= 0.29190 val_loss= 1.37107 val_acc= 0.33929 time= 0.01563
Epoch: 0049 train_loss= 1.37826 train_acc= 0.29190 val_loss= 1.37083 val_acc= 0.33929 time= 0.00000
Epoch: 0050 train_loss= 1.37904 train_acc= 0.29190 val_loss= 1.37086 val_acc= 0.33929 time= 0.01563
Epoch: 0051 train_loss= 1.37844 train_acc= 0.29190 val_loss= 1.37091 val_acc= 0.33929 time= 0.01563
Epoch: 0052 train_loss= 1.37877 train_acc= 0.29190 val_loss= 1.37120 val_acc= 0.33929 time= 0.01563
Epoch: 0053 train_loss= 1.37871 train_acc= 0.29190 val_loss= 1.37150 val_acc= 0.33929 time= 0.00000
Early stopping...
Optimization Finished!
Test set results: cost= 1.37712 accuracy= 0.29204 time= 0.01563 
