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End of training

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  1. README.md +45 -45
  2. pytorch_model.bin +1 -1
README.md CHANGED
@@ -22,7 +22,7 @@ model-index:
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  metrics:
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  - name: Accuracy
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  type: accuracy
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- value: 0.8935108153078203
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  ---
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  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -32,8 +32,8 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [microsoft/beit-base-patch16-224](https://huggingface.co/microsoft/beit-base-patch16-224) on the imagefolder dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.8334
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- - Accuracy: 0.8935
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  ## Model description
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@@ -72,49 +72,49 @@ The following hyperparameters were used during training:
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  | 0.0616 | 5.0 | 1875 | 0.3403 | 0.8935 |
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  | 0.036 | 6.0 | 2250 | 0.3534 | 0.9101 |
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  | 0.0382 | 7.0 | 2625 | 0.4309 | 0.8985 |
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- | 0.0686 | 8.0 | 3000 | 0.4835 | 0.8985 |
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  | 0.022 | 9.0 | 3375 | 0.5298 | 0.8935 |
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- | 0.0158 | 10.0 | 3750 | 0.5869 | 0.9002 |
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- | 0.0173 | 11.0 | 4125 | 0.5623 | 0.8952 |
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- | 0.0241 | 12.0 | 4500 | 0.7014 | 0.8869 |
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- | 0.013 | 13.0 | 4875 | 0.6238 | 0.8952 |
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- | 0.004 | 14.0 | 5250 | 0.6124 | 0.9002 |
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- | 0.0249 | 15.0 | 5625 | 0.6495 | 0.8935 |
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- | 0.0004 | 16.0 | 6000 | 0.6999 | 0.8952 |
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- | 0.0493 | 17.0 | 6375 | 0.6887 | 0.8952 |
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- | 0.0087 | 18.0 | 6750 | 0.6681 | 0.9018 |
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- | 0.0007 | 19.0 | 7125 | 0.6956 | 0.8985 |
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- | 0.0126 | 20.0 | 7500 | 0.7749 | 0.8968 |
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- | 0.024 | 21.0 | 7875 | 0.7255 | 0.9002 |
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- | 0.0023 | 22.0 | 8250 | 0.7116 | 0.9052 |
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- | 0.0003 | 23.0 | 8625 | 0.7428 | 0.8985 |
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- | 0.0002 | 24.0 | 9000 | 0.7479 | 0.9002 |
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- | 0.0001 | 25.0 | 9375 | 0.7803 | 0.8952 |
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- | 0.0002 | 26.0 | 9750 | 0.7628 | 0.9002 |
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- | 0.0069 | 27.0 | 10125 | 0.7997 | 0.8985 |
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- | 0.0015 | 28.0 | 10500 | 0.7552 | 0.8985 |
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- | 0.0269 | 29.0 | 10875 | 0.7735 | 0.9002 |
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- | 0.0044 | 30.0 | 11250 | 0.7914 | 0.8985 |
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- | 0.0192 | 31.0 | 11625 | 0.8157 | 0.8918 |
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- | 0.0066 | 32.0 | 12000 | 0.8365 | 0.8952 |
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- | 0.0069 | 33.0 | 12375 | 0.7991 | 0.8952 |
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- | 0.0008 | 34.0 | 12750 | 0.8440 | 0.8968 |
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- | 0.0002 | 35.0 | 13125 | 0.8522 | 0.8985 |
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- | 0.0024 | 36.0 | 13500 | 0.8528 | 0.8968 |
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- | 0.0031 | 37.0 | 13875 | 0.8295 | 0.8968 |
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- | 0.0002 | 38.0 | 14250 | 0.8478 | 0.8952 |
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- | 0.0052 | 39.0 | 14625 | 0.8298 | 0.8918 |
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- | 0.0186 | 40.0 | 15000 | 0.8272 | 0.8935 |
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- | 0.0182 | 41.0 | 15375 | 0.8469 | 0.8935 |
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- | 0.0085 | 42.0 | 15750 | 0.8174 | 0.8968 |
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- | 0.0293 | 43.0 | 16125 | 0.8181 | 0.8935 |
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- | 0.001 | 44.0 | 16500 | 0.8046 | 0.9035 |
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- | 0.0229 | 45.0 | 16875 | 0.8447 | 0.8935 |
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- | 0.0261 | 46.0 | 17250 | 0.8340 | 0.8935 |
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- | 0.0189 | 47.0 | 17625 | 0.8319 | 0.8952 |
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- | 0.0195 | 48.0 | 18000 | 0.8342 | 0.8952 |
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- | 0.0133 | 49.0 | 18375 | 0.8317 | 0.8935 |
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- | 0.0026 | 50.0 | 18750 | 0.8334 | 0.8935 |
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  ### Framework versions
 
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  metrics:
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  - name: Accuracy
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  type: accuracy
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+ value: 0.8985024958402662
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  ---
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  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
 
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  This model is a fine-tuned version of [microsoft/beit-base-patch16-224](https://huggingface.co/microsoft/beit-base-patch16-224) on the imagefolder dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.8394
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+ - Accuracy: 0.8985
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  ## Model description
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  | 0.0616 | 5.0 | 1875 | 0.3403 | 0.8935 |
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  | 0.036 | 6.0 | 2250 | 0.3534 | 0.9101 |
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  | 0.0382 | 7.0 | 2625 | 0.4309 | 0.8985 |
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+ | 0.0686 | 8.0 | 3000 | 0.4834 | 0.8985 |
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  | 0.022 | 9.0 | 3375 | 0.5298 | 0.8935 |
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+ | 0.0159 | 10.0 | 3750 | 0.5866 | 0.8985 |
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+ | 0.0173 | 11.0 | 4125 | 0.5610 | 0.8968 |
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+ | 0.0241 | 12.0 | 4500 | 0.6962 | 0.8869 |
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+ | 0.0123 | 13.0 | 4875 | 0.6252 | 0.8952 |
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+ | 0.0054 | 14.0 | 5250 | 0.6170 | 0.9002 |
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+ | 0.0251 | 15.0 | 5625 | 0.6453 | 0.8952 |
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+ | 0.0003 | 16.0 | 6000 | 0.6804 | 0.8952 |
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+ | 0.0563 | 17.0 | 6375 | 0.6912 | 0.8985 |
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+ | 0.0079 | 18.0 | 6750 | 0.6905 | 0.9018 |
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+ | 0.0009 | 19.0 | 7125 | 0.7171 | 0.8935 |
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+ | 0.0206 | 20.0 | 7500 | 0.7602 | 0.8985 |
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+ | 0.0222 | 21.0 | 7875 | 0.7242 | 0.8952 |
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+ | 0.0005 | 22.0 | 8250 | 0.7227 | 0.9002 |
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+ | 0.0001 | 23.0 | 8625 | 0.7725 | 0.9002 |
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+ | 0.0002 | 24.0 | 9000 | 0.7700 | 0.8935 |
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+ | 0.0001 | 25.0 | 9375 | 0.7746 | 0.8985 |
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+ | 0.0001 | 26.0 | 9750 | 0.7609 | 0.9018 |
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+ | 0.017 | 27.0 | 10125 | 0.8256 | 0.8918 |
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+ | 0.0019 | 28.0 | 10500 | 0.7444 | 0.8952 |
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+ | 0.0254 | 29.0 | 10875 | 0.7839 | 0.9035 |
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+ | 0.0041 | 30.0 | 11250 | 0.7929 | 0.9002 |
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+ | 0.0018 | 31.0 | 11625 | 0.7983 | 0.8968 |
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+ | 0.0163 | 32.0 | 12000 | 0.8337 | 0.8968 |
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+ | 0.0122 | 33.0 | 12375 | 0.8065 | 0.8918 |
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+ | 0.0021 | 34.0 | 12750 | 0.8472 | 0.8968 |
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+ | 0.0003 | 35.0 | 13125 | 0.8572 | 0.8968 |
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+ | 0.0036 | 36.0 | 13500 | 0.8680 | 0.8935 |
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+ | 0.0086 | 37.0 | 13875 | 0.8533 | 0.8935 |
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+ | 0.0002 | 38.0 | 14250 | 0.8606 | 0.8885 |
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+ | 0.0065 | 39.0 | 14625 | 0.8465 | 0.8869 |
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+ | 0.0212 | 40.0 | 15000 | 0.8444 | 0.8952 |
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+ | 0.0163 | 41.0 | 15375 | 0.8576 | 0.8918 |
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+ | 0.0071 | 42.0 | 15750 | 0.8227 | 0.8952 |
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+ | 0.0234 | 43.0 | 16125 | 0.8305 | 0.8935 |
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+ | 0.0019 | 44.0 | 16500 | 0.8174 | 0.9002 |
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+ | 0.0226 | 45.0 | 16875 | 0.8559 | 0.8902 |
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+ | 0.0176 | 46.0 | 17250 | 0.8405 | 0.8918 |
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+ | 0.0236 | 47.0 | 17625 | 0.8413 | 0.8952 |
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+ | 0.0179 | 48.0 | 18000 | 0.8437 | 0.8985 |
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+ | 0.0141 | 49.0 | 18375 | 0.8368 | 0.8968 |
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+ | 0.0007 | 50.0 | 18750 | 0.8394 | 0.8985 |
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  ### Framework versions
pytorch_model.bin CHANGED
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