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segformer-b0-finetuned-segments-toolwear

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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: 0.0517
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- - Mean Iou: 0.3741
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- - Mean Accuracy: 0.7482
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- - Overall Accuracy: 0.7482
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  - Accuracy Unlabeled: nan
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- - Accuracy Tool: nan
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- - Accuracy Wear: 0.7482
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  - Iou Unlabeled: 0.0
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- - Iou Tool: nan
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- - Iou Wear: 0.7482
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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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- | 0.8497 | 1.82 | 20 | 0.8647 | 0.4917 | 0.9834 | 0.9834 | nan | nan | 0.9834 | 0.0 | nan | 0.9834 |
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- | 0.6095 | 3.64 | 40 | 0.5158 | 0.4642 | 0.9283 | 0.9283 | nan | nan | 0.9283 | 0.0 | nan | 0.9283 |
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- | 0.4377 | 5.45 | 60 | 0.4200 | 0.4646 | 0.9291 | 0.9291 | nan | nan | 0.9291 | 0.0 | nan | 0.9291 |
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- | 0.3756 | 7.27 | 80 | 0.3535 | 0.4780 | 0.9560 | 0.9560 | nan | nan | 0.9560 | 0.0 | nan | 0.9560 |
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- | 0.4256 | 9.09 | 100 | 0.2951 | 0.4873 | 0.9746 | 0.9746 | nan | nan | 0.9746 | 0.0 | nan | 0.9746 |
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- | 0.2748 | 10.91 | 120 | 0.2500 | 0.4817 | 0.9634 | 0.9634 | nan | nan | 0.9634 | 0.0 | nan | 0.9634 |
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- | 0.2347 | 12.73 | 140 | 0.2000 | 0.4065 | 0.8129 | 0.8129 | nan | nan | 0.8129 | 0.0 | nan | 0.8129 |
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- | 0.1777 | 14.55 | 160 | 0.1651 | 0.4340 | 0.8680 | 0.8680 | nan | nan | 0.8680 | 0.0 | nan | 0.8680 |
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- | 0.186 | 16.36 | 180 | 0.1530 | 0.4211 | 0.8422 | 0.8422 | nan | nan | 0.8422 | 0.0 | nan | 0.8422 |
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- | 0.1652 | 18.18 | 200 | 0.1143 | 0.4304 | 0.8608 | 0.8608 | nan | nan | 0.8608 | 0.0 | nan | 0.8608 |
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- | 0.1227 | 20.0 | 220 | 0.1436 | 0.4838 | 0.9676 | 0.9676 | nan | nan | 0.9676 | 0.0 | nan | 0.9676 |
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- | 0.1111 | 21.82 | 240 | 0.1014 | 0.3994 | 0.7988 | 0.7988 | nan | nan | 0.7988 | 0.0 | nan | 0.7988 |
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- | 0.0989 | 23.64 | 260 | 0.0914 | 0.3574 | 0.7147 | 0.7147 | nan | nan | 0.7147 | 0.0 | nan | 0.7147 |
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- | 0.1051 | 25.45 | 280 | 0.0871 | 0.2844 | 0.5689 | 0.5689 | nan | nan | 0.5689 | 0.0 | nan | 0.5689 |
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- | 0.0975 | 27.27 | 300 | 0.0679 | 0.3893 | 0.7786 | 0.7786 | nan | nan | 0.7786 | 0.0 | nan | 0.7786 |
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- | 0.0928 | 29.09 | 320 | 0.0723 | 0.4241 | 0.8483 | 0.8483 | nan | nan | 0.8483 | 0.0 | nan | 0.8483 |
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- | 0.0673 | 30.91 | 340 | 0.0653 | 0.3628 | 0.7255 | 0.7255 | nan | nan | 0.7255 | 0.0 | nan | 0.7255 |
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- | 0.0652 | 32.73 | 360 | 0.0641 | 0.4023 | 0.8047 | 0.8047 | nan | nan | 0.8047 | 0.0 | nan | 0.8047 |
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- | 0.0912 | 34.55 | 380 | 0.0734 | 0.4453 | 0.8906 | 0.8906 | nan | nan | 0.8906 | 0.0 | nan | 0.8906 |
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- | 0.0682 | 36.36 | 400 | 0.0609 | 0.3322 | 0.6644 | 0.6644 | nan | nan | 0.6644 | 0.0 | nan | 0.6644 |
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- | 0.0737 | 38.18 | 420 | 0.0619 | 0.4053 | 0.8107 | 0.8107 | nan | nan | 0.8107 | 0.0 | nan | 0.8107 |
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- | 0.06 | 40.0 | 440 | 0.0564 | 0.3593 | 0.7186 | 0.7186 | nan | nan | 0.7186 | 0.0 | nan | 0.7186 |
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- | 0.0555 | 41.82 | 460 | 0.0562 | 0.4025 | 0.8050 | 0.8050 | nan | nan | 0.8050 | 0.0 | nan | 0.8050 |
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- | 0.063 | 43.64 | 480 | 0.0550 | 0.3945 | 0.7891 | 0.7891 | nan | nan | 0.7891 | 0.0 | nan | 0.7891 |
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- | 0.0641 | 45.45 | 500 | 0.0554 | 0.4032 | 0.8065 | 0.8065 | nan | nan | 0.8065 | 0.0 | nan | 0.8065 |
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- | 0.0739 | 47.27 | 520 | 0.0549 | 0.3880 | 0.7760 | 0.7760 | nan | nan | 0.7760 | 0.0 | nan | 0.7760 |
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- | 0.0684 | 49.09 | 540 | 0.0517 | 0.3741 | 0.7482 | 0.7482 | nan | nan | 0.7482 | 0.0 | nan | 0.7482 |
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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: 0.0332
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+ - Mean Iou: 0.4969
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+ - Mean Accuracy: 0.9938
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+ - Overall Accuracy: 0.9938
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  - Accuracy Unlabeled: nan
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+ - Accuracy Tool: 0.9938
 
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  - Iou Unlabeled: 0.0
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+ - Iou Tool: 0.9938
 
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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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+ | 0.1957 | 1.82 | 20 | 0.3708 | 0.4995 | 0.9991 | 0.9991 | nan | 0.9991 | 0.0 | 0.9991 |
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+ | 0.1896 | 3.64 | 40 | 0.1768 | 0.4985 | 0.9970 | 0.9970 | nan | 0.9970 | 0.0 | 0.9970 |
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+ | 0.1022 | 5.45 | 60 | 0.0996 | 0.4966 | 0.9933 | 0.9933 | nan | 0.9933 | 0.0 | 0.9933 |
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+ | 0.0855 | 7.27 | 80 | 0.0863 | 0.4767 | 0.9535 | 0.9535 | nan | 0.9535 | 0.0 | 0.9535 |
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+ | 0.1223 | 9.09 | 100 | 0.0677 | 0.4964 | 0.9927 | 0.9927 | nan | 0.9927 | 0.0 | 0.9927 |
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+ | 0.0791 | 10.91 | 120 | 0.0583 | 0.4948 | 0.9896 | 0.9896 | nan | 0.9896 | 0.0 | 0.9896 |
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+ | 0.0521 | 12.73 | 140 | 0.0500 | 0.4938 | 0.9876 | 0.9876 | nan | 0.9876 | 0.0 | 0.9876 |
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+ | 0.0397 | 14.55 | 160 | 0.0443 | 0.4958 | 0.9916 | 0.9916 | nan | 0.9916 | 0.0 | 0.9916 |
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+ | 0.0283 | 16.36 | 180 | 0.0594 | 0.4972 | 0.9943 | 0.9943 | nan | 0.9943 | 0.0 | 0.9943 |
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+ | 0.0378 | 18.18 | 200 | 0.0485 | 0.4987 | 0.9974 | 0.9974 | nan | 0.9974 | 0.0 | 0.9974 |
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+ | 0.0347 | 20.0 | 220 | 0.0382 | 0.4971 | 0.9941 | 0.9941 | nan | 0.9941 | 0.0 | 0.9941 |
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+ | 0.0245 | 21.82 | 240 | 0.0346 | 0.4966 | 0.9932 | 0.9932 | nan | 0.9932 | 0.0 | 0.9932 |
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+ | 0.0425 | 23.64 | 260 | 0.0393 | 0.4961 | 0.9921 | 0.9921 | nan | 0.9921 | 0.0 | 0.9921 |
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+ | 0.0293 | 25.45 | 280 | 0.0336 | 0.4973 | 0.9946 | 0.9946 | nan | 0.9946 | 0.0 | 0.9946 |
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+ | 0.0247 | 27.27 | 300 | 0.0368 | 0.4972 | 0.9944 | 0.9944 | nan | 0.9944 | 0.0 | 0.9944 |
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+ | 0.0287 | 29.09 | 320 | 0.0317 | 0.4958 | 0.9915 | 0.9915 | nan | 0.9915 | 0.0 | 0.9915 |
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+ | 0.0254 | 30.91 | 340 | 0.0408 | 0.4966 | 0.9932 | 0.9932 | nan | 0.9932 | 0.0 | 0.9932 |
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+ | 0.0347 | 32.73 | 360 | 0.0291 | 0.4965 | 0.9930 | 0.9930 | nan | 0.9930 | 0.0 | 0.9930 |
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+ | 0.0174 | 34.55 | 380 | 0.0361 | 0.4978 | 0.9955 | 0.9955 | nan | 0.9955 | 0.0 | 0.9955 |
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+ | 0.0191 | 36.36 | 400 | 0.0417 | 0.4972 | 0.9944 | 0.9944 | nan | 0.9944 | 0.0 | 0.9944 |
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+ | 0.0234 | 38.18 | 420 | 0.0373 | 0.4974 | 0.9947 | 0.9947 | nan | 0.9947 | 0.0 | 0.9947 |
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+ | 0.0306 | 40.0 | 440 | 0.0370 | 0.4969 | 0.9938 | 0.9938 | nan | 0.9938 | 0.0 | 0.9938 |
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+ | 0.0178 | 41.82 | 460 | 0.0407 | 0.4973 | 0.9946 | 0.9946 | nan | 0.9946 | 0.0 | 0.9946 |
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+ | 0.0152 | 43.64 | 480 | 0.0323 | 0.4968 | 0.9935 | 0.9935 | nan | 0.9935 | 0.0 | 0.9935 |
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+ | 0.0181 | 45.45 | 500 | 0.0346 | 0.4974 | 0.9947 | 0.9947 | nan | 0.9947 | 0.0 | 0.9947 |
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+ | 0.0155 | 47.27 | 520 | 0.0338 | 0.4971 | 0.9942 | 0.9942 | nan | 0.9942 | 0.0 | 0.9942 |
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+ | 0.0223 | 49.09 | 540 | 0.0332 | 0.4969 | 0.9938 | 0.9938 | nan | 0.9938 | 0.0 | 0.9938 |
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  ### Framework versions