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LOG_Train_RecognizeTrafficSign_Resnet_Pytorch.txt
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(alfonso1) c:\RecognizeTrafficSign>python Train_RecognizeTrafficSign_Resnet_Pytorch.py
C:\Users\Alfonso Blanco\.conda\envs\alfonso1\lib\site-packages\numpy\_distributor_init.py:30: UserWarning: loaded more than 1 DLL from .libs:
C:\Users\Alfonso Blanco\.conda\envs\alfonso1\lib\site-packages\numpy\.libs\libopenblas.FB5AE2TYXYH2IJRDKGDGQ3XBKLKTF43H.gfortran-win_amd64.dll
C:\Users\Alfonso Blanco\.conda\envs\alfonso1\lib\site-packages\numpy\.libs\libopenblas64__v0.3.21-gcc_10_3_0.dll
warnings.warn("loaded more than 1 DLL from .libs:"
C:\Users\Alfonso Blanco\AppData\Roaming\Python\Python39\site-packages\torchvision\models\_utils.py:208: UserWarning: The parameter 'pretrained' is deprecated since 0.13 and may be removed in the future, please use 'weights' instead. warnings.warn(
C:\Users\Alfonso Blanco\AppData\Roaming\Python\Python39\site-packages\torchvision\models\_utils.py:223: UserWarning: Arguments other than a weight enum or `None` for 'weights' are deprecated since 0.13 and may be removed in the future. The current behavior is equivalent to passing `weights=ResNet50_Weights.IMAGENET1K_V1`. You can also use `weights=ResNet50_Weights.DEFAULT` to get the most up-to-date weights.
warnings.warn(msg)
No. epochs: 1, Training Loss: 2.493 Valid Loss: 1.919 Valid Accuracy: 0.432
No. epochs: 1, Training Loss: 3.756 Valid Loss: 1.438 Valid Accuracy: 0.576
No. epochs: 1, Training Loss: 4.607 Valid Loss: 0.812 Valid Accuracy: 0.726
No. epochs: 1, Training Loss: 5.244 Valid Loss: 0.794 Valid Accuracy: 0.764
No. epochs: 1, Training Loss: 5.745 Valid Loss: 0.588 Valid Accuracy: 0.813
No. epochs: 2, Training Loss: 0.194 Valid Loss: 0.271 Valid Accuracy: 0.909
No. epochs: 2, Training Loss: 0.45 Valid Loss: 0.235 Valid Accuracy: 0.92
No. epochs: 2, Training Loss: 0.682 Valid Loss: 0.206 Valid Accuracy: 0.929
No. epochs: 2, Training Loss: 0.912 Valid Loss: 0.193 Valid Accuracy: 0.934
No. epochs: 2, Training Loss: 1.127 Valid Loss: 0.187 Valid Accuracy: 0.936
No. epochs: 3, Training Loss: 0.067 Valid Loss: 0.178 Valid Accuracy: 0.939
No. epochs: 3, Training Loss: 0.251 Valid Loss: 0.171 Valid Accuracy: 0.944
No. epochs: 3, Training Loss: 0.433 Valid Loss: 0.175 Valid Accuracy: 0.941
No. epochs: 3, Training Loss: 0.622 Valid Loss: 0.169 Valid Accuracy: 0.943
No. epochs: 3, Training Loss: 0.786 Valid Loss: 0.171 Valid Accuracy: 0.945
No. epochs: 3, Training Loss: 0.965 Valid Loss: 0.164 Valid Accuracy: 0.945
No. epochs: 4, Training Loss: 0.165 Valid Loss: 0.17 Valid Accuracy: 0.942
No. epochs: 4, Training Loss: 0.346 Valid Loss: 0.172 Valid Accuracy: 0.943
No. epochs: 4, Training Loss: 0.532 Valid Loss: 0.164 Valid Accuracy: 0.946
No. epochs: 4, Training Loss: 0.712 Valid Loss: 0.163 Valid Accuracy: 0.945
No. epochs: 4, Training Loss: 0.873 Valid Loss: 0.167 Valid Accuracy: 0.941
No. epochs: 5, Training Loss: 0.106 Valid Loss: 0.168 Valid Accuracy: 0.943
No. epochs: 5, Training Loss: 0.282 Valid Loss: 0.167 Valid Accuracy: 0.942
No. epochs: 5, Training Loss: 0.456 Valid Loss: 0.17 Valid Accuracy: 0.942
No. epochs: 5, Training Loss: 0.638 Valid Loss: 0.169 Valid Accuracy: 0.943
No. epochs: 5, Training Loss: 0.82 Valid Loss: 0.163 Valid Accuracy: 0.946
No. epochs: 6, Training Loss: 0.043 Valid Loss: 0.167 Valid Accuracy: 0.943
No. epochs: 6, Training Loss: 0.216 Valid Loss: 0.168 Valid Accuracy: 0.941
No. epochs: 6, Training Loss: 0.392 Valid Loss: 0.168 Valid Accuracy: 0.946
No. epochs: 6, Training Loss: 0.572 Valid Loss: 0.164 Valid Accuracy: 0.945
No. epochs: 6, Training Loss: 0.754 Valid Loss: 0.17 Valid Accuracy: 0.942
No. epochs: 6, Training Loss: 0.926 Valid Loss: 0.168 Valid Accuracy: 0.945
No. epochs: 7, Training Loss: 0.165 Valid Loss: 0.169 Valid Accuracy: 0.942
No. epochs: 7, Training Loss: 0.344 Valid Loss: 0.165 Valid Accuracy: 0.946
No. epochs: 7, Training Loss: 0.528 Valid Loss: 0.171 Valid Accuracy: 0.942
No. epochs: 7, Training Loss: 0.705 Valid Loss: 0.164 Valid Accuracy: 0.946
No. epochs: 7, Training Loss: 0.887 Valid Loss: 0.163 Valid Accuracy: 0.946
No. epochs: 8, Training Loss: 0.095 Valid Loss: 0.165 Valid Accuracy: 0.945
No. epochs: 8, Training Loss: 0.271 Valid Loss: 0.168 Valid Accuracy: 0.944
No. epochs: 8, Training Loss: 0.448 Valid Loss: 0.167 Valid Accuracy: 0.942
No. epochs: 8, Training Loss: 0.634 Valid Loss: 0.165 Valid Accuracy: 0.944
No. epochs: 8, Training Loss: 0.814 Valid Loss: 0.161 Valid Accuracy: 0.946
No. epochs: 9, Training Loss: 0.039 Valid Loss: 0.168 Valid Accuracy: 0.942
No. epochs: 9, Training Loss: 0.216 Valid Loss: 0.171 Valid Accuracy: 0.941
No. epochs: 9, Training Loss: 0.394 Valid Loss: 0.17 Valid Accuracy: 0.943
No. epochs: 9, Training Loss: 0.579 Valid Loss: 0.167 Valid Accuracy: 0.944
No. epochs: 9, Training Loss: 0.765 Valid Loss: 0.168 Valid Accuracy: 0.944
No. epochs: 9, Training Loss: 0.947 Valid Loss: 0.168 Valid Accuracy: 0.944
No. epochs: 10, Training Loss: 0.152 Valid Loss: 0.163 Valid Accuracy: 0.945
No. epochs: 10, Training Loss: 0.328 Valid Loss: 0.167 Valid Accuracy: 0.941
No. epochs: 10, Training Loss: 0.508 Valid Loss: 0.17 Valid Accuracy: 0.941
No. epochs: 10, Training Loss: 0.684 Valid Loss: 0.162 Valid Accuracy: 0.946
No. epochs: 10, Training Loss: 0.867 Valid Loss: 0.164 Valid Accuracy: 0.944
No. epochs: 11, Training Loss: 0.084 Valid Loss: 0.169 Valid Accuracy: 0.943
No. epochs: 11, Training Loss: 0.27 Valid Loss: 0.167 Valid Accuracy: 0.944
No. epochs: 11, Training Loss: 0.447 Valid Loss: 0.159 Valid Accuracy: 0.946
No. epochs: 11, Training Loss: 0.626 Valid Loss: 0.168 Valid Accuracy: 0.944
No. epochs: 11, Training Loss: 0.797 Valid Loss: 0.169 Valid Accuracy: 0.944
No. epochs: 12, Training Loss: 0.03 Valid Loss: 0.163 Valid Accuracy: 0.946
No. epochs: 12, Training Loss: 0.211 Valid Loss: 0.161 Valid Accuracy: 0.946
No. epochs: 12, Training Loss: 0.4 Valid Loss: 0.168 Valid Accuracy: 0.941
No. epochs: 12, Training Loss: 0.58 Valid Loss: 0.169 Valid Accuracy: 0.944
No. epochs: 12, Training Loss: 0.761 Valid Loss: 0.164 Valid Accuracy: 0.944
No. epochs: 12, Training Loss: 0.931 Valid Loss: 0.17 Valid Accuracy: 0.943
No. epochs: 13, Training Loss: 0.148 Valid Loss: 0.167 Valid Accuracy: 0.945
No. epochs: 13, Training Loss: 0.326 Valid Loss: 0.164 Valid Accuracy: 0.947
No. epochs: 13, Training Loss: 0.502 Valid Loss: 0.166 Valid Accuracy: 0.946
No. epochs: 13, Training Loss: 0.677 Valid Loss: 0.17 Valid Accuracy: 0.943
No. epochs: 13, Training Loss: 0.856 Valid Loss: 0.168 Valid Accuracy: 0.946
No. epochs: 14, Training Loss: 0.083 Valid Loss: 0.162 Valid Accuracy: 0.947
No. epochs: 14, Training Loss: 0.25 Valid Loss: 0.169 Valid Accuracy: 0.944
No. epochs: 14, Training Loss: 0.428 Valid Loss: 0.169 Valid Accuracy: 0.943
No. epochs: 14, Training Loss: 0.616 Valid Loss: 0.169 Valid Accuracy: 0.943
No. epochs: 14, Training Loss: 0.798 Valid Loss: 0.166 Valid Accuracy: 0.944
No. epochs: 15, Training Loss: 0.016 Valid Loss: 0.164 Valid Accuracy: 0.946
No. epochs: 15, Training Loss: 0.197 Valid Loss: 0.167 Valid Accuracy: 0.944
No. epochs: 15, Training Loss: 0.368 Valid Loss: 0.165 Valid Accuracy: 0.946
No. epochs: 15, Training Loss: 0.546 Valid Loss: 0.168 Valid Accuracy: 0.943
No. epochs: 15, Training Loss: 0.739 Valid Loss: 0.169 Valid Accuracy: 0.943
No. epochs: 15, Training Loss: 0.91 Valid Loss: 0.167 Valid Accuracy: 0.944
No. epochs: 16, Training Loss: 0.124 Valid Loss: 0.164 Valid Accuracy: 0.945
No. epochs: 16, Training Loss: 0.316 Valid Loss: 0.166 Valid Accuracy: 0.945
No. epochs: 16, Training Loss: 0.495 Valid Loss: 0.167 Valid Accuracy: 0.944
No. epochs: 16, Training Loss: 0.675 Valid Loss: 0.166 Valid Accuracy: 0.942
No. epochs: 16, Training Loss: 0.849 Valid Loss: 0.168 Valid Accuracy: 0.943
No. epochs: 17, Training Loss: 0.07 Valid Loss: 0.165 Valid Accuracy: 0.944
No. epochs: 17, Training Loss: 0.25 Valid Loss: 0.174 Valid Accuracy: 0.941
No. epochs: 17, Training Loss: 0.424 Valid Loss: 0.164 Valid Accuracy: 0.945
No. epochs: 17, Training Loss: 0.594 Valid Loss: 0.166 Valid Accuracy: 0.946
No. epochs: 17, Training Loss: 0.766 Valid Loss: 0.17 Valid Accuracy: 0.944
No. epochs: 18, Training Loss: 0.01 Valid Loss: 0.163 Valid Accuracy: 0.945
No. epochs: 18, Training Loss: 0.186 Valid Loss: 0.166 Valid Accuracy: 0.945
No. epochs: 18, Training Loss: 0.37 Valid Loss: 0.164 Valid Accuracy: 0.945
No. epochs: 18, Training Loss: 0.543 Valid Loss: 0.163 Valid Accuracy: 0.943
No. epochs: 18, Training Loss: 0.713 Valid Loss: 0.17 Valid Accuracy: 0.943
No. epochs: 18, Training Loss: 0.899 Valid Loss: 0.16 Valid Accuracy: 0.948
No. epochs: 19, Training Loss: 0.119 Valid Loss: 0.165 Valid Accuracy: 0.946
No. epochs: 19, Training Loss: 0.293 Valid Loss: 0.171 Valid Accuracy: 0.943
No. epochs: 19, Training Loss: 0.48 Valid Loss: 0.166 Valid Accuracy: 0.946
No. epochs: 19, Training Loss: 0.658 Valid Loss: 0.162 Valid Accuracy: 0.946
No. epochs: 19, Training Loss: 0.848 Valid Loss: 0.165 Valid Accuracy: 0.945
No. epochs: 20, Training Loss: 0.064 Valid Loss: 0.166 Valid Accuracy: 0.944
No. epochs: 20, Training Loss: 0.255 Valid Loss: 0.17 Valid Accuracy: 0.942
No. epochs: 20, Training Loss: 0.431 Valid Loss: 0.159 Valid Accuracy: 0.945
No. epochs: 20, Training Loss: 0.604 Valid Loss: 0.167 Valid Accuracy: 0.945
No. epochs: 20, Training Loss: 0.789 Valid Loss: 0.173 Valid Accuracy: 0.942
No. epochs: 20, Training Loss: 0.962 Valid Loss: 0.171 Valid Accuracy: 0.943
Test accuracy of model: 94.35%
(alfonso1) c:\RecognizeTrafficSign>