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segformer-b0-finetuned-segments-toolwear

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update model card README.md

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  ---
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  license: other
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  tags:
 
 
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  - generated_from_trainer
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  model-index:
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  - name: segformer-b0-finetuned-segments-toolwear
@@ -12,18 +14,16 @@ should probably proofread and complete it, then remove this comment. -->
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  # segformer-b0-finetuned-segments-toolwear
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- This model is a fine-tuned version of [nvidia/mit-b0](https://huggingface.co/nvidia/mit-b0) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.1141
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- - Mean Iou: 0.4323
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- - Mean Accuracy: 0.8645
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- - Overall Accuracy: 0.8645
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  - Accuracy Unlabeled: nan
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- - Accuracy Tool: nan
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- - Accuracy Wear: 0.8645
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  - Iou Unlabeled: 0.0
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- - Iou Tool: nan
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- - Iou Wear: 0.8645
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  ## Model description
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@@ -52,35 +52,35 @@ 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 Unlabeled | Accuracy Tool | Accuracy Wear | Iou Unlabeled | Iou Tool | Iou Wear |
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- |:-------------:|:-----:|:----:|:---------------:|:--------:|:-------------:|:----------------:|:------------------:|:-------------:|:-------------:|:-------------:|:--------:|:--------:|
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- | 0.7016 | 1.82 | 20 | 0.9090 | 0.4940 | 0.9880 | 0.9880 | nan | nan | 0.9880 | 0.0 | nan | 0.9880 |
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- | 0.5409 | 3.64 | 40 | 0.6405 | 0.4986 | 0.9972 | 0.9972 | nan | nan | 0.9972 | 0.0 | nan | 0.9972 |
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- | 0.4261 | 5.45 | 60 | 0.4407 | 0.4846 | 0.9692 | 0.9692 | nan | nan | 0.9692 | 0.0 | nan | 0.9692 |
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- | 0.3251 | 7.27 | 80 | 0.4075 | 0.4692 | 0.9383 | 0.9383 | nan | nan | 0.9383 | 0.0 | nan | 0.9383 |
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- | 0.2993 | 9.09 | 100 | 0.3055 | 0.4739 | 0.9477 | 0.9477 | nan | nan | 0.9477 | 0.0 | nan | 0.9477 |
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- | 0.2724 | 10.91 | 120 | 0.3326 | 0.4759 | 0.9518 | 0.9518 | nan | nan | 0.9518 | 0.0 | nan | 0.9518 |
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- | 0.2154 | 12.73 | 140 | 0.3281 | 0.4786 | 0.9573 | 0.9573 | nan | nan | 0.9573 | 0.0 | nan | 0.9573 |
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- | 0.1732 | 14.55 | 160 | 0.2322 | 0.4415 | 0.8831 | 0.8831 | nan | nan | 0.8831 | 0.0 | nan | 0.8831 |
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- | 0.1376 | 16.36 | 180 | 0.2063 | 0.3969 | 0.7937 | 0.7937 | nan | nan | 0.7937 | 0.0 | nan | 0.7937 |
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- | 0.1326 | 18.18 | 200 | 0.2147 | 0.4613 | 0.9226 | 0.9226 | nan | nan | 0.9226 | 0.0 | nan | 0.9226 |
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- | 0.1333 | 20.0 | 220 | 0.1711 | 0.4373 | 0.8747 | 0.8747 | nan | nan | 0.8747 | 0.0 | nan | 0.8747 |
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- | 0.1235 | 21.82 | 240 | 0.1550 | 0.4374 | 0.8748 | 0.8748 | nan | nan | 0.8748 | 0.0 | nan | 0.8748 |
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- | 0.0976 | 23.64 | 260 | 0.1640 | 0.4373 | 0.8745 | 0.8745 | nan | nan | 0.8745 | 0.0 | nan | 0.8745 |
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- | 0.078 | 25.45 | 280 | 0.1463 | 0.4505 | 0.9010 | 0.9010 | nan | nan | 0.9010 | 0.0 | nan | 0.9010 |
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- | 0.0753 | 27.27 | 300 | 0.1395 | 0.4387 | 0.8774 | 0.8774 | nan | nan | 0.8774 | 0.0 | nan | 0.8774 |
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- | 0.0703 | 29.09 | 320 | 0.1529 | 0.4550 | 0.9100 | 0.9100 | nan | nan | 0.9100 | 0.0 | nan | 0.9100 |
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- | 0.0665 | 30.91 | 340 | 0.1336 | 0.4414 | 0.8828 | 0.8828 | nan | nan | 0.8828 | 0.0 | nan | 0.8828 |
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- | 0.0606 | 32.73 | 360 | 0.1320 | 0.4484 | 0.8968 | 0.8968 | nan | nan | 0.8968 | 0.0 | nan | 0.8968 |
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- | 0.0814 | 34.55 | 380 | 0.1215 | 0.4220 | 0.8439 | 0.8439 | nan | nan | 0.8439 | 0.0 | nan | 0.8439 |
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- | 0.0578 | 36.36 | 400 | 0.1194 | 0.4266 | 0.8531 | 0.8531 | nan | nan | 0.8531 | 0.0 | nan | 0.8531 |
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- | 0.0511 | 38.18 | 420 | 0.1232 | 0.4417 | 0.8835 | 0.8835 | nan | nan | 0.8835 | 0.0 | nan | 0.8835 |
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- | 0.0471 | 40.0 | 440 | 0.1182 | 0.4409 | 0.8817 | 0.8817 | nan | nan | 0.8817 | 0.0 | nan | 0.8817 |
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- | 0.0484 | 41.82 | 460 | 0.1084 | 0.4258 | 0.8515 | 0.8515 | nan | nan | 0.8515 | 0.0 | nan | 0.8515 |
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- | 0.0497 | 43.64 | 480 | 0.1212 | 0.4425 | 0.8850 | 0.8850 | nan | nan | 0.8850 | 0.0 | nan | 0.8850 |
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- | 0.0624 | 45.45 | 500 | 0.1071 | 0.4266 | 0.8531 | 0.8531 | nan | nan | 0.8531 | 0.0 | nan | 0.8531 |
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- | 0.0509 | 47.27 | 520 | 0.1157 | 0.4339 | 0.8678 | 0.8678 | nan | nan | 0.8678 | 0.0 | nan | 0.8678 |
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- | 0.0496 | 49.09 | 540 | 0.1141 | 0.4323 | 0.8645 | 0.8645 | nan | nan | 0.8645 | 0.0 | nan | 0.8645 |
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  ### Framework versions
 
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  ---
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  license: other
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  tags:
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+ - vision
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+ - image-segmentation
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  - generated_from_trainer
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  model-index:
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  - name: segformer-b0-finetuned-segments-toolwear
 
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  # segformer-b0-finetuned-segments-toolwear
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+ This model is a fine-tuned version of [nvidia/mit-b0](https://huggingface.co/nvidia/mit-b0) on the HorcruxNo13/toolwear_segmentsai_tools dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.0341
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+ - Mean Iou: 0.4939
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+ - Mean Accuracy: 0.9878
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+ - Overall Accuracy: 0.9878
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  - Accuracy Unlabeled: nan
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+ - Accuracy Tool: 0.9878
 
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  - Iou Unlabeled: 0.0
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+ - Iou Tool: 0.9878
 
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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 Unlabeled | Accuracy Tool | Iou Unlabeled | Iou Tool |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|:-------------:|:----------------:|:------------------:|:-------------:|:-------------:|:--------:|
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+ | 0.2127 | 1.82 | 20 | 0.3537 | 0.4996 | 0.9991 | 0.9991 | nan | 0.9991 | 0.0 | 0.9991 |
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+ | 0.2095 | 3.64 | 40 | 0.1407 | 0.4987 | 0.9974 | 0.9974 | nan | 0.9974 | 0.0 | 0.9974 |
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+ | 0.1253 | 5.45 | 60 | 0.1011 | 0.4970 | 0.9940 | 0.9940 | nan | 0.9940 | 0.0 | 0.9940 |
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+ | 0.0812 | 7.27 | 80 | 0.0821 | 0.4957 | 0.9914 | 0.9914 | nan | 0.9914 | 0.0 | 0.9914 |
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+ | 0.0841 | 9.09 | 100 | 0.0652 | 0.4926 | 0.9851 | 0.9851 | nan | 0.9851 | 0.0 | 0.9851 |
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+ | 0.0574 | 10.91 | 120 | 0.0612 | 0.4930 | 0.9861 | 0.9861 | nan | 0.9861 | 0.0 | 0.9861 |
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+ | 0.047 | 12.73 | 140 | 0.0562 | 0.4940 | 0.9880 | 0.9880 | nan | 0.9880 | 0.0 | 0.9880 |
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+ | 0.0542 | 14.55 | 160 | 0.0488 | 0.4937 | 0.9874 | 0.9874 | nan | 0.9874 | 0.0 | 0.9874 |
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+ | 0.0405 | 16.36 | 180 | 0.0487 | 0.4958 | 0.9916 | 0.9916 | nan | 0.9916 | 0.0 | 0.9916 |
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+ | 0.045 | 18.18 | 200 | 0.0484 | 0.4964 | 0.9929 | 0.9929 | nan | 0.9929 | 0.0 | 0.9929 |
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+ | 0.0487 | 20.0 | 220 | 0.0412 | 0.4936 | 0.9873 | 0.9873 | nan | 0.9873 | 0.0 | 0.9873 |
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+ | 0.0417 | 21.82 | 240 | 0.0397 | 0.4936 | 0.9872 | 0.9872 | nan | 0.9872 | 0.0 | 0.9872 |
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+ | 0.0525 | 23.64 | 260 | 0.0393 | 0.4934 | 0.9868 | 0.9868 | nan | 0.9868 | 0.0 | 0.9868 |
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+ | 0.0425 | 25.45 | 280 | 0.0381 | 0.4930 | 0.9861 | 0.9861 | nan | 0.9861 | 0.0 | 0.9861 |
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+ | 0.0386 | 27.27 | 300 | 0.0393 | 0.4927 | 0.9855 | 0.9855 | nan | 0.9855 | 0.0 | 0.9855 |
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+ | 0.0239 | 29.09 | 320 | 0.0387 | 0.4933 | 0.9866 | 0.9866 | nan | 0.9866 | 0.0 | 0.9866 |
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+ | 0.0279 | 30.91 | 340 | 0.0369 | 0.4941 | 0.9882 | 0.9882 | nan | 0.9882 | 0.0 | 0.9882 |
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+ | 0.0194 | 32.73 | 360 | 0.0368 | 0.4916 | 0.9832 | 0.9832 | nan | 0.9832 | 0.0 | 0.9832 |
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+ | 0.0238 | 34.55 | 380 | 0.0370 | 0.4937 | 0.9874 | 0.9874 | nan | 0.9874 | 0.0 | 0.9874 |
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+ | 0.0281 | 36.36 | 400 | 0.0347 | 0.4930 | 0.9859 | 0.9859 | nan | 0.9859 | 0.0 | 0.9859 |
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+ | 0.0218 | 38.18 | 420 | 0.0351 | 0.4924 | 0.9848 | 0.9848 | nan | 0.9848 | 0.0 | 0.9848 |
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+ | 0.0197 | 40.0 | 440 | 0.0354 | 0.4932 | 0.9864 | 0.9864 | nan | 0.9864 | 0.0 | 0.9864 |
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+ | 0.0197 | 41.82 | 460 | 0.0343 | 0.4933 | 0.9865 | 0.9865 | nan | 0.9865 | 0.0 | 0.9865 |
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+ | 0.0231 | 43.64 | 480 | 0.0345 | 0.4931 | 0.9862 | 0.9862 | nan | 0.9862 | 0.0 | 0.9862 |
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+ | 0.0223 | 45.45 | 500 | 0.0346 | 0.4938 | 0.9875 | 0.9875 | nan | 0.9875 | 0.0 | 0.9875 |
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+ | 0.0184 | 47.27 | 520 | 0.0340 | 0.4927 | 0.9854 | 0.9854 | nan | 0.9854 | 0.0 | 0.9854 |
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+ | 0.0202 | 49.09 | 540 | 0.0341 | 0.4939 | 0.9878 | 0.9878 | nan | 0.9878 | 0.0 | 0.9878 |
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  ### Framework versions