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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: 0.0622
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- - Mean Iou: 0.3898
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- - Mean Accuracy: 0.7796
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- - Overall Accuracy: 0.7796
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  - Accuracy Unlabeled: nan
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- - Accuracy Tool: nan
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- - Accuracy Wear: 0.7796
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  - Iou Unlabeled: 0.0
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- - Iou Tool: nan
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- - Iou Wear: 0.7796
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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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- | 0.862 | 1.82 | 20 | 0.9317 | 0.4701 | 0.9401 | 0.9401 | nan | nan | 0.9401 | 0.0 | nan | 0.9401 |
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- | 0.6008 | 3.64 | 40 | 0.6036 | 0.4683 | 0.9365 | 0.9365 | nan | nan | 0.9365 | 0.0 | nan | 0.9365 |
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- | 0.5219 | 5.45 | 60 | 0.4657 | 0.4618 | 0.9236 | 0.9236 | nan | nan | 0.9236 | 0.0 | nan | 0.9236 |
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- | 0.3939 | 7.27 | 80 | 0.4035 | 0.4462 | 0.8924 | 0.8924 | nan | nan | 0.8924 | 0.0 | nan | 0.8924 |
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- | 0.3919 | 9.09 | 100 | 0.3229 | 0.3580 | 0.7159 | 0.7159 | nan | nan | 0.7159 | 0.0 | nan | 0.7159 |
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- | 0.3267 | 10.91 | 120 | 0.2979 | 0.4378 | 0.8756 | 0.8756 | nan | nan | 0.8756 | 0.0 | nan | 0.8756 |
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- | 0.2791 | 12.73 | 140 | 0.2356 | 0.3858 | 0.7715 | 0.7715 | nan | nan | 0.7715 | 0.0 | nan | 0.7715 |
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- | 0.2466 | 14.55 | 160 | 0.2299 | 0.4279 | 0.8558 | 0.8558 | nan | nan | 0.8558 | 0.0 | nan | 0.8558 |
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- | 0.1883 | 16.36 | 180 | 0.1804 | 0.4138 | 0.8276 | 0.8276 | nan | nan | 0.8276 | 0.0 | nan | 0.8276 |
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- | 0.1745 | 18.18 | 200 | 0.1772 | 0.4006 | 0.8011 | 0.8011 | nan | nan | 0.8011 | 0.0 | nan | 0.8011 |
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- | 0.144 | 20.0 | 220 | 0.1425 | 0.3985 | 0.7970 | 0.7970 | nan | nan | 0.7970 | 0.0 | nan | 0.7970 |
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- | 0.1901 | 21.82 | 240 | 0.1243 | 0.3619 | 0.7239 | 0.7239 | nan | nan | 0.7239 | 0.0 | nan | 0.7239 |
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- | 0.1248 | 23.64 | 260 | 0.1197 | 0.3573 | 0.7146 | 0.7146 | nan | nan | 0.7146 | 0.0 | nan | 0.7146 |
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- | 0.1245 | 25.45 | 280 | 0.1059 | 0.3985 | 0.7970 | 0.7970 | nan | nan | 0.7970 | 0.0 | nan | 0.7970 |
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- | 0.1189 | 27.27 | 300 | 0.0990 | 0.4031 | 0.8063 | 0.8063 | nan | nan | 0.8063 | 0.0 | nan | 0.8063 |
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- | 0.0985 | 29.09 | 320 | 0.0915 | 0.4186 | 0.8371 | 0.8371 | nan | nan | 0.8371 | 0.0 | nan | 0.8371 |
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- | 0.0884 | 30.91 | 340 | 0.0839 | 0.3677 | 0.7354 | 0.7354 | nan | nan | 0.7354 | 0.0 | nan | 0.7354 |
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- | 0.0797 | 32.73 | 360 | 0.0813 | 0.3796 | 0.7592 | 0.7592 | nan | nan | 0.7592 | 0.0 | nan | 0.7592 |
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- | 0.077 | 34.55 | 380 | 0.0748 | 0.3965 | 0.7931 | 0.7931 | nan | nan | 0.7931 | 0.0 | nan | 0.7931 |
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- | 0.0735 | 36.36 | 400 | 0.0739 | 0.3880 | 0.7760 | 0.7760 | nan | nan | 0.7760 | 0.0 | nan | 0.7760 |
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- | 0.072 | 38.18 | 420 | 0.0725 | 0.3980 | 0.7959 | 0.7959 | nan | nan | 0.7959 | 0.0 | nan | 0.7959 |
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- | 0.0744 | 40.0 | 440 | 0.0672 | 0.3942 | 0.7884 | 0.7884 | nan | nan | 0.7884 | 0.0 | nan | 0.7884 |
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- | 0.0602 | 41.82 | 460 | 0.0652 | 0.4077 | 0.8154 | 0.8154 | nan | nan | 0.8154 | 0.0 | nan | 0.8154 |
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- | 0.0632 | 43.64 | 480 | 0.0660 | 0.3855 | 0.7711 | 0.7711 | nan | nan | 0.7711 | 0.0 | nan | 0.7711 |
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- | 0.0768 | 45.45 | 500 | 0.0629 | 0.3911 | 0.7821 | 0.7821 | nan | nan | 0.7821 | 0.0 | nan | 0.7821 |
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- | 0.0564 | 47.27 | 520 | 0.0619 | 0.3764 | 0.7529 | 0.7529 | nan | nan | 0.7529 | 0.0 | nan | 0.7529 |
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- | 0.06 | 49.09 | 540 | 0.0622 | 0.3898 | 0.7796 | 0.7796 | nan | nan | 0.7796 | 0.0 | nan | 0.7796 |
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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: 0.0480
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+ - Mean Iou: 0.4892
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+ - Mean Accuracy: 0.9785
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+ - Overall Accuracy: 0.9785
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  - Accuracy Unlabeled: nan
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+ - Accuracy Tool: 0.9785
 
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  - Iou Unlabeled: 0.0
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+ - Iou Tool: 0.9785
 
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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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+ | 0.257 | 1.82 | 20 | 0.4274 | 0.4894 | 0.9788 | 0.9788 | nan | 0.9788 | 0.0 | 0.9788 |
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+ | 0.14 | 3.64 | 40 | 0.1857 | 0.4878 | 0.9756 | 0.9756 | nan | 0.9756 | 0.0 | 0.9756 |
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+ | 0.0945 | 5.45 | 60 | 0.1383 | 0.4877 | 0.9754 | 0.9754 | nan | 0.9754 | 0.0 | 0.9754 |
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+ | 0.0766 | 7.27 | 80 | 0.1041 | 0.4907 | 0.9813 | 0.9813 | nan | 0.9813 | 0.0 | 0.9813 |
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+ | 0.0752 | 9.09 | 100 | 0.1055 | 0.4836 | 0.9672 | 0.9672 | nan | 0.9672 | 0.0 | 0.9672 |
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+ | 0.0433 | 10.91 | 120 | 0.1180 | 0.4659 | 0.9318 | 0.9318 | nan | 0.9318 | 0.0 | 0.9318 |
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+ | 0.0358 | 12.73 | 140 | 0.0857 | 0.4831 | 0.9662 | 0.9662 | nan | 0.9662 | 0.0 | 0.9662 |
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+ | 0.0357 | 14.55 | 160 | 0.0765 | 0.4865 | 0.9730 | 0.9730 | nan | 0.9730 | 0.0 | 0.9730 |
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+ | 0.0401 | 16.36 | 180 | 0.0898 | 0.4793 | 0.9587 | 0.9587 | nan | 0.9587 | 0.0 | 0.9587 |
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+ | 0.042 | 18.18 | 200 | 0.0755 | 0.4828 | 0.9655 | 0.9655 | nan | 0.9655 | 0.0 | 0.9655 |
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+ | 0.0366 | 20.0 | 220 | 0.0744 | 0.4818 | 0.9635 | 0.9635 | nan | 0.9635 | 0.0 | 0.9635 |
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+ | 0.0213 | 21.82 | 240 | 0.0708 | 0.4828 | 0.9656 | 0.9656 | nan | 0.9656 | 0.0 | 0.9656 |
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+ | 0.0284 | 23.64 | 260 | 0.0684 | 0.4851 | 0.9701 | 0.9701 | nan | 0.9701 | 0.0 | 0.9701 |
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+ | 0.0237 | 25.45 | 280 | 0.0625 | 0.4879 | 0.9757 | 0.9757 | nan | 0.9757 | 0.0 | 0.9757 |
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+ | 0.0189 | 27.27 | 300 | 0.0603 | 0.4858 | 0.9716 | 0.9716 | nan | 0.9716 | 0.0 | 0.9716 |
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+ | 0.026 | 29.09 | 320 | 0.0632 | 0.4860 | 0.9719 | 0.9719 | nan | 0.9719 | 0.0 | 0.9719 |
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+ | 0.0231 | 30.91 | 340 | 0.0662 | 0.4840 | 0.9680 | 0.9680 | nan | 0.9680 | 0.0 | 0.9680 |
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+ | 0.0218 | 32.73 | 360 | 0.0563 | 0.4855 | 0.9710 | 0.9710 | nan | 0.9710 | 0.0 | 0.9710 |
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+ | 0.0253 | 34.55 | 380 | 0.0627 | 0.4848 | 0.9697 | 0.9697 | nan | 0.9697 | 0.0 | 0.9697 |
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+ | 0.0142 | 36.36 | 400 | 0.0621 | 0.4844 | 0.9689 | 0.9689 | nan | 0.9689 | 0.0 | 0.9689 |
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+ | 0.0214 | 38.18 | 420 | 0.0668 | 0.4820 | 0.9639 | 0.9639 | nan | 0.9639 | 0.0 | 0.9639 |
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+ | 0.0166 | 40.0 | 440 | 0.0555 | 0.4858 | 0.9716 | 0.9716 | nan | 0.9716 | 0.0 | 0.9716 |
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+ | 0.0185 | 41.82 | 460 | 0.0545 | 0.4859 | 0.9718 | 0.9718 | nan | 0.9718 | 0.0 | 0.9718 |
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+ | 0.0218 | 43.64 | 480 | 0.0500 | 0.4876 | 0.9753 | 0.9753 | nan | 0.9753 | 0.0 | 0.9753 |
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+ | 0.0184 | 45.45 | 500 | 0.0481 | 0.4892 | 0.9784 | 0.9784 | nan | 0.9784 | 0.0 | 0.9784 |
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+ | 0.018 | 47.27 | 520 | 0.0487 | 0.4893 | 0.9786 | 0.9786 | nan | 0.9786 | 0.0 | 0.9786 |
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+ | 0.0254 | 49.09 | 540 | 0.0480 | 0.4892 | 0.9785 | 0.9785 | nan | 0.9785 | 0.0 | 0.9785 |
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  ### Framework versions