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autocrop-bilder

Image Segmentation
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Safetensors
segformer
vision
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  1. README.md +42 -38
  2. model.safetensors +1 -1
README.md CHANGED
@@ -3,31 +3,29 @@ library_name: transformers
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  license: other
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  base_model: nvidia/mit-b0
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  tags:
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- - image-segmentation
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- - vision
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  - generated_from_trainer
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  datasets:
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  - generator
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  model-index:
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- - name: autocrop-test
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  results: []
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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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  should probably proofread and complete it, then remove this comment. -->
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- # autocrop-test
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- This model is a fine-tuned version of [nvidia/mit-b0](https://huggingface.co/nvidia/mit-b0) on the /mnt/disk1/autocrop-data/datasets/tekst/ dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.0196
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- - Mean Iou: 0.4964
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- - Mean Accuracy: 0.9928
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- - Overall Accuracy: 0.9928
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  - Accuracy Background: nan
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- - Accuracy Crop: 0.9928
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  - Iou Background: 0.0
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- - Iou Crop: 0.9928
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  ## Model description
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@@ -58,33 +56,39 @@ The following hyperparameters were used during training:
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  ### Training results
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- | Training Loss | Epoch | Step | Validation Loss | Mean Iou | Mean Accuracy | Overall Accuracy | Accuracy Background | Accuracy Crop | Iou Background | Iou Crop |
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- |:-------------:|:-----:|:-----:|:---------------:|:--------:|:-------------:|:----------------:|:-------------------:|:-------------:|:--------------:|:--------:|
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- | 0.4334 | 1.0 | 625 | 0.1014 | 0.4884 | 0.9768 | 0.9768 | nan | 0.9768 | 0.0 | 0.9768 |
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- | 0.1136 | 2.0 | 1250 | 0.0503 | 0.4942 | 0.9883 | 0.9883 | nan | 0.9883 | 0.0 | 0.9883 |
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- | 0.0626 | 3.0 | 1875 | 0.0365 | 0.4952 | 0.9903 | 0.9903 | nan | 0.9903 | 0.0 | 0.9903 |
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- | 0.0376 | 4.0 | 2500 | 0.0304 | 0.4957 | 0.9913 | 0.9913 | nan | 0.9913 | 0.0 | 0.9913 |
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- | 0.0331 | 5.0 | 3125 | 0.0277 | 0.4945 | 0.9890 | 0.9890 | nan | 0.9890 | 0.0 | 0.9890 |
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- | 0.0312 | 6.0 | 3750 | 0.0258 | 0.4961 | 0.9922 | 0.9922 | nan | 0.9922 | 0.0 | 0.9922 |
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- | 0.0290 | 7.0 | 4375 | 0.0252 | 0.4970 | 0.9941 | 0.9941 | nan | 0.9941 | 0.0 | 0.9941 |
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- | 0.0272 | 8.0 | 5000 | 0.0247 | 0.4950 | 0.9900 | 0.9900 | nan | 0.9900 | 0.0 | 0.9900 |
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- | 0.0264 | 9.0 | 5625 | 0.0232 | 0.4963 | 0.9925 | 0.9925 | nan | 0.9925 | 0.0 | 0.9925 |
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- | 0.0260 | 10.0 | 6250 | 0.0230 | 0.4964 | 0.9927 | 0.9927 | nan | 0.9927 | 0.0 | 0.9927 |
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- | 0.0257 | 11.0 | 6875 | 0.0223 | 0.4969 | 0.9937 | 0.9937 | nan | 0.9937 | 0.0 | 0.9937 |
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- | 0.0244 | 12.0 | 7500 | 0.0217 | 0.4966 | 0.9932 | 0.9932 | nan | 0.9932 | 0.0 | 0.9932 |
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- | 0.0240 | 13.0 | 8125 | 0.0223 | 0.4960 | 0.9920 | 0.9920 | nan | 0.9920 | 0.0 | 0.9920 |
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- | 0.0230 | 14.0 | 8750 | 0.0220 | 0.4972 | 0.9943 | 0.9943 | nan | 0.9943 | 0.0 | 0.9943 |
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- | 0.0230 | 15.0 | 9375 | 0.0213 | 0.4963 | 0.9926 | 0.9926 | nan | 0.9926 | 0.0 | 0.9926 |
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- | 0.0228 | 16.0 | 10000 | 0.0208 | 0.4964 | 0.9928 | 0.9928 | nan | 0.9928 | 0.0 | 0.9928 |
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- | 0.0220 | 17.0 | 10625 | 0.0206 | 0.4965 | 0.9930 | 0.9930 | nan | 0.9930 | 0.0 | 0.9930 |
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- | 0.0217 | 18.0 | 11250 | 0.0205 | 0.4960 | 0.9921 | 0.9921 | nan | 0.9921 | 0.0 | 0.9921 |
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- | 0.0212 | 19.0 | 11875 | 0.0207 | 0.4958 | 0.9915 | 0.9915 | nan | 0.9915 | 0.0 | 0.9915 |
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- | 0.0209 | 20.0 | 12500 | 0.0204 | 0.4973 | 0.9946 | 0.9946 | nan | 0.9946 | 0.0 | 0.9946 |
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- | 0.0203 | 21.0 | 13125 | 0.0198 | 0.4969 | 0.9937 | 0.9937 | nan | 0.9937 | 0.0 | 0.9937 |
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- | 0.0202 | 22.0 | 13750 | 0.0196 | 0.4964 | 0.9928 | 0.9928 | nan | 0.9928 | 0.0 | 0.9928 |
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- | 0.0202 | 23.0 | 14375 | 0.0203 | 0.4971 | 0.9942 | 0.9942 | nan | 0.9942 | 0.0 | 0.9942 |
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- | 0.0198 | 24.0 | 15000 | 0.0196 | 0.4966 | 0.9932 | 0.9932 | nan | 0.9932 | 0.0 | 0.9932 |
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- | 0.0194 | 25.0 | 15625 | 0.0197 | 0.4966 | 0.9932 | 0.9932 | nan | 0.9932 | 0.0 | 0.9932 |
 
 
 
 
 
 
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  ### Framework versions
 
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  license: other
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  base_model: nvidia/mit-b0
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  tags:
 
 
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  - generated_from_trainer
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  datasets:
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  - generator
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  model-index:
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+ - name: autocrop-bilder
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  results: []
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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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  should probably proofread and complete it, then remove this comment. -->
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+ # autocrop-bilder
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+ This model is a fine-tuned version of [nvidia/mit-b0](https://huggingface.co/nvidia/mit-b0) on the generator dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.1091
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+ - Mean Iou: 0.4907
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+ - Mean Accuracy: 0.9814
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+ - Overall Accuracy: 0.9814
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  - Accuracy Background: nan
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+ - Accuracy Crop: 0.9814
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  - Iou Background: 0.0
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+ - Iou Crop: 0.9814
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  ## Model description
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  ### Training results
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+ | Training Loss | Epoch | Step | Validation Loss | Mean Iou | Mean Accuracy | Overall Accuracy | Accuracy Background | Accuracy Crop | Iou Background | Iou Crop |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|:-------------:|:----------------:|:-------------------:|:-------------:|:--------------:|:--------:|
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+ | No log | 1.0 | 7 | 0.6694 | 0.3399 | 0.6798 | 0.6798 | nan | 0.6798 | 0.0 | 0.6798 |
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+ | No log | 2.0 | 14 | 0.5930 | 0.4623 | 0.9246 | 0.9246 | nan | 0.9246 | 0.0 | 0.9246 |
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+ | No log | 3.0 | 21 | 0.4610 | 0.4706 | 0.9412 | 0.9412 | nan | 0.9412 | 0.0 | 0.9412 |
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+ | No log | 4.0 | 28 | 0.3075 | 0.4705 | 0.9411 | 0.9411 | nan | 0.9411 | 0.0 | 0.9411 |
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+ | No log | 5.0 | 35 | 0.2037 | 0.4709 | 0.9417 | 0.9417 | nan | 0.9417 | 0.0 | 0.9417 |
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+ | No log | 6.0 | 42 | 0.1668 | 0.4662 | 0.9324 | 0.9324 | nan | 0.9324 | 0.0 | 0.9324 |
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+ | No log | 7.0 | 49 | 0.1421 | 0.4752 | 0.9503 | 0.9503 | nan | 0.9503 | 0.0 | 0.9503 |
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+ | No log | 8.0 | 56 | 0.1382 | 0.4773 | 0.9547 | 0.9547 | nan | 0.9547 | 0.0 | 0.9547 |
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+ | No log | 9.0 | 63 | 0.1588 | 0.4737 | 0.9473 | 0.9473 | nan | 0.9473 | 0.0 | 0.9473 |
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+ | No log | 10.0 | 70 | 0.1317 | 0.4845 | 0.9690 | 0.9690 | nan | 0.9690 | 0.0 | 0.9690 |
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+ | No log | 11.0 | 77 | 0.1307 | 0.4836 | 0.9671 | 0.9671 | nan | 0.9671 | 0.0 | 0.9671 |
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+ | No log | 12.0 | 84 | 0.1328 | 0.4899 | 0.9798 | 0.9798 | nan | 0.9798 | 0.0 | 0.9798 |
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+ | No log | 13.0 | 91 | 0.1265 | 0.4863 | 0.9725 | 0.9725 | nan | 0.9725 | 0.0 | 0.9725 |
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+ | No log | 14.0 | 98 | 0.1283 | 0.4886 | 0.9772 | 0.9772 | nan | 0.9772 | 0.0 | 0.9772 |
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+ | No log | 15.0 | 105 | 0.1286 | 0.4887 | 0.9775 | 0.9775 | nan | 0.9775 | 0.0 | 0.9775 |
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+ | No log | 16.0 | 112 | 0.1235 | 0.4894 | 0.9788 | 0.9788 | nan | 0.9788 | 0.0 | 0.9788 |
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+ | No log | 17.0 | 119 | 0.1213 | 0.4898 | 0.9795 | 0.9795 | nan | 0.9795 | 0.0 | 0.9795 |
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+ | No log | 18.0 | 126 | 0.1223 | 0.4910 | 0.9821 | 0.9821 | nan | 0.9821 | 0.0 | 0.9821 |
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+ | No log | 19.0 | 133 | 0.1179 | 0.4882 | 0.9763 | 0.9763 | nan | 0.9763 | 0.0 | 0.9763 |
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+ | No log | 20.0 | 140 | 0.1169 | 0.4914 | 0.9829 | 0.9829 | nan | 0.9829 | 0.0 | 0.9829 |
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+ | No log | 21.0 | 147 | 0.1153 | 0.4908 | 0.9816 | 0.9816 | nan | 0.9816 | 0.0 | 0.9816 |
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+ | No log | 22.0 | 154 | 0.1155 | 0.4902 | 0.9804 | 0.9804 | nan | 0.9804 | 0.0 | 0.9804 |
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+ | No log | 23.0 | 161 | 0.1143 | 0.4919 | 0.9839 | 0.9839 | nan | 0.9839 | 0.0 | 0.9839 |
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+ | No log | 24.0 | 168 | 0.1115 | 0.4913 | 0.9825 | 0.9825 | nan | 0.9825 | 0.0 | 0.9825 |
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+ | No log | 25.0 | 175 | 0.1113 | 0.4920 | 0.9841 | 0.9841 | nan | 0.9841 | 0.0 | 0.9841 |
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+ | No log | 26.0 | 182 | 0.1106 | 0.4923 | 0.9846 | 0.9846 | nan | 0.9846 | 0.0 | 0.9846 |
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+ | No log | 27.0 | 189 | 0.1097 | 0.4907 | 0.9814 | 0.9814 | nan | 0.9814 | 0.0 | 0.9814 |
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+ | No log | 28.0 | 196 | 0.1087 | 0.4908 | 0.9816 | 0.9816 | nan | 0.9816 | 0.0 | 0.9816 |
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+ | No log | 29.0 | 203 | 0.1094 | 0.4920 | 0.9840 | 0.9840 | nan | 0.9840 | 0.0 | 0.9840 |
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+ | No log | 30.0 | 210 | 0.1093 | 0.4911 | 0.9821 | 0.9821 | nan | 0.9821 | 0.0 | 0.9821 |
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+ | No log | 31.0 | 217 | 0.1091 | 0.4907 | 0.9814 | 0.9814 | nan | 0.9814 | 0.0 | 0.9814 |
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  ### Framework versions
model.safetensors CHANGED
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  size 14884776
 
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