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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 +14,18 @@ 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: 0.1285
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- - Mean Iou: 0.3499
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- - Mean Accuracy: 0.6998
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- - Overall Accuracy: 0.6998
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  - Accuracy Unlabeled: nan
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- - Accuracy Tool: nan
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- - Accuracy Wear: 0.6998
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  - Iou Unlabeled: 0.0
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- - Iou Tool: nan
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- - Iou Wear: 0.6998
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  ## Model description
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@@ -54,33 +56,33 @@ The following hyperparameters were used during training:
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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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- | 0.8959 | 1.82 | 20 | 0.8677 | 0.4048 | 0.8097 | 0.8097 | nan | nan | 0.8097 | 0.0 | nan | 0.8097 |
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- | 0.6658 | 3.64 | 40 | 0.6010 | 0.3734 | 0.7468 | 0.7468 | nan | nan | 0.7468 | 0.0 | nan | 0.7468 |
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- | 0.4389 | 5.45 | 60 | 0.4941 | 0.3634 | 0.7269 | 0.7269 | nan | nan | 0.7269 | 0.0 | nan | 0.7269 |
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- | 0.3531 | 7.27 | 80 | 0.4390 | 0.3508 | 0.7015 | 0.7015 | nan | nan | 0.7015 | 0.0 | nan | 0.7015 |
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- | 0.3408 | 9.09 | 100 | 0.3753 | 0.3340 | 0.6679 | 0.6679 | nan | nan | 0.6679 | 0.0 | nan | 0.6679 |
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- | 0.3266 | 10.91 | 120 | 0.3769 | 0.3761 | 0.7521 | 0.7521 | nan | nan | 0.7521 | 0.0 | nan | 0.7521 |
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- | 0.2791 | 12.73 | 140 | 0.3491 | 0.3918 | 0.7835 | 0.7835 | nan | nan | 0.7835 | 0.0 | nan | 0.7835 |
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- | 0.2066 | 14.55 | 160 | 0.2705 | 0.3491 | 0.6981 | 0.6981 | nan | nan | 0.6981 | 0.0 | nan | 0.6981 |
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- | 0.161 | 16.36 | 180 | 0.2398 | 0.3283 | 0.6567 | 0.6567 | nan | nan | 0.6567 | 0.0 | nan | 0.6567 |
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- | 0.1558 | 18.18 | 200 | 0.2599 | 0.4021 | 0.8042 | 0.8042 | nan | nan | 0.8042 | 0.0 | nan | 0.8042 |
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- | 0.128 | 20.0 | 220 | 0.2163 | 0.3387 | 0.6775 | 0.6775 | nan | nan | 0.6775 | 0.0 | nan | 0.6775 |
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- | 0.11 | 21.82 | 240 | 0.2019 | 0.3599 | 0.7199 | 0.7199 | nan | nan | 0.7199 | 0.0 | nan | 0.7199 |
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- | 0.1101 | 23.64 | 260 | 0.1905 | 0.3620 | 0.7240 | 0.7240 | nan | nan | 0.7240 | 0.0 | nan | 0.7240 |
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- | 0.0874 | 25.45 | 280 | 0.1708 | 0.3138 | 0.6276 | 0.6276 | nan | nan | 0.6276 | 0.0 | nan | 0.6276 |
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- | 0.0815 | 27.27 | 300 | 0.1505 | 0.3191 | 0.6382 | 0.6382 | nan | nan | 0.6382 | 0.0 | nan | 0.6382 |
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- | 0.082 | 29.09 | 320 | 0.1641 | 0.3520 | 0.7040 | 0.7040 | nan | nan | 0.7040 | 0.0 | nan | 0.7040 |
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- | 0.0694 | 30.91 | 340 | 0.1456 | 0.3322 | 0.6644 | 0.6644 | nan | nan | 0.6644 | 0.0 | nan | 0.6644 |
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- | 0.072 | 32.73 | 360 | 0.1416 | 0.3445 | 0.6889 | 0.6889 | nan | nan | 0.6889 | 0.0 | nan | 0.6889 |
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- | 0.065 | 34.55 | 380 | 0.1348 | 0.3407 | 0.6814 | 0.6814 | nan | nan | 0.6814 | 0.0 | nan | 0.6814 |
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- | 0.0696 | 36.36 | 400 | 0.1372 | 0.3285 | 0.6569 | 0.6569 | nan | nan | 0.6569 | 0.0 | nan | 0.6569 |
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- | 0.0666 | 38.18 | 420 | 0.1430 | 0.3636 | 0.7272 | 0.7272 | nan | nan | 0.7272 | 0.0 | nan | 0.7272 |
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- | 0.0601 | 40.0 | 440 | 0.1222 | 0.3211 | 0.6423 | 0.6423 | nan | nan | 0.6423 | 0.0 | nan | 0.6423 |
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- | 0.0515 | 41.82 | 460 | 0.1225 | 0.3286 | 0.6572 | 0.6572 | nan | nan | 0.6572 | 0.0 | nan | 0.6572 |
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- | 0.0558 | 43.64 | 480 | 0.1229 | 0.3375 | 0.6750 | 0.6750 | nan | nan | 0.6750 | 0.0 | nan | 0.6750 |
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- | 0.07 | 45.45 | 500 | 0.1111 | 0.3057 | 0.6114 | 0.6114 | nan | nan | 0.6114 | 0.0 | nan | 0.6114 |
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- | 0.0606 | 47.27 | 520 | 0.1251 | 0.3391 | 0.6782 | 0.6782 | nan | nan | 0.6782 | 0.0 | nan | 0.6782 |
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- | 0.0561 | 49.09 | 540 | 0.1285 | 0.3499 | 0.6998 | 0.6998 | nan | nan | 0.6998 | 0.0 | nan | 0.6998 |
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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_edges dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.3547
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+ - Mean Iou: 0.3725
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+ - Mean Accuracy: 0.7265
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+ - Overall Accuracy: 0.8226
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  - Accuracy Unlabeled: nan
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+ - Accuracy Tool: 0.6195
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+ - Accuracy Wear: 0.8334
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  - Iou Unlabeled: 0.0
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+ - Iou Tool: 0.2973
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+ - Iou Wear: 0.8202
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  ## Model description
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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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+ | 0.7196 | 1.82 | 20 | 0.9873 | 0.2927 | 0.4996 | 0.6806 | nan | 0.2982 | 0.7009 | 0.0 | 0.2025 | 0.6757 |
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+ | 0.6004 | 3.64 | 40 | 0.7373 | 0.3312 | 0.6517 | 0.7107 | nan | 0.5861 | 0.7173 | 0.0 | 0.2916 | 0.7019 |
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+ | 0.5155 | 5.45 | 60 | 0.6634 | 0.3376 | 0.5621 | 0.6378 | nan | 0.4778 | 0.6463 | 0.0 | 0.3840 | 0.6289 |
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+ | 0.4228 | 7.27 | 80 | 0.5380 | 0.3612 | 0.6707 | 0.7661 | nan | 0.5646 | 0.7768 | 0.0 | 0.3241 | 0.7595 |
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+ | 0.3216 | 9.09 | 100 | 0.5102 | 0.3466 | 0.6845 | 0.7281 | nan | 0.6361 | 0.7330 | 0.0 | 0.3188 | 0.7209 |
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+ | 0.3752 | 10.91 | 120 | 0.4615 | 0.3902 | 0.7013 | 0.8268 | nan | 0.5616 | 0.8409 | 0.0 | 0.3476 | 0.8229 |
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+ | 0.3014 | 12.73 | 140 | 0.4504 | 0.4075 | 0.7007 | 0.8311 | nan | 0.5558 | 0.8457 | 0.0 | 0.3949 | 0.8275 |
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+ | 0.2183 | 14.55 | 160 | 0.4241 | 0.3708 | 0.7363 | 0.8002 | nan | 0.6653 | 0.8073 | 0.0 | 0.3165 | 0.7959 |
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+ | 0.1674 | 16.36 | 180 | 0.4173 | 0.4020 | 0.7433 | 0.8684 | nan | 0.6041 | 0.8824 | 0.0 | 0.3397 | 0.8664 |
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+ | 0.2385 | 18.18 | 200 | 0.4716 | 0.3450 | 0.6543 | 0.7462 | nan | 0.5520 | 0.7566 | 0.0 | 0.2941 | 0.7410 |
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+ | 0.1588 | 20.0 | 220 | 0.3742 | 0.3820 | 0.7108 | 0.8179 | nan | 0.5917 | 0.8299 | 0.0 | 0.3311 | 0.8149 |
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+ | 0.1553 | 21.82 | 240 | 0.3677 | 0.3811 | 0.7312 | 0.8313 | nan | 0.6199 | 0.8426 | 0.0 | 0.3144 | 0.8291 |
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+ | 0.1765 | 23.64 | 260 | 0.4131 | 0.3689 | 0.7032 | 0.8024 | nan | 0.5929 | 0.8135 | 0.0 | 0.3082 | 0.7985 |
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+ | 0.2516 | 25.45 | 280 | 0.3632 | 0.4142 | 0.7158 | 0.8856 | nan | 0.5270 | 0.9047 | 0.0 | 0.3585 | 0.8841 |
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+ | 0.1534 | 27.27 | 300 | 0.3979 | 0.3813 | 0.7191 | 0.8236 | nan | 0.6029 | 0.8354 | 0.0 | 0.3231 | 0.8209 |
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+ | 0.1104 | 29.09 | 320 | 0.3787 | 0.3640 | 0.7439 | 0.8044 | nan | 0.6765 | 0.8112 | 0.0 | 0.2911 | 0.8007 |
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+ | 0.1799 | 30.91 | 340 | 0.3654 | 0.3868 | 0.7217 | 0.8257 | nan | 0.6060 | 0.8374 | 0.0 | 0.3378 | 0.8227 |
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+ | 0.1069 | 32.73 | 360 | 0.3928 | 0.3524 | 0.7171 | 0.7606 | nan | 0.6687 | 0.7655 | 0.0 | 0.3018 | 0.7554 |
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+ | 0.1178 | 34.55 | 380 | 0.3703 | 0.3622 | 0.7259 | 0.8079 | nan | 0.6345 | 0.8172 | 0.0 | 0.2814 | 0.8052 |
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+ | 0.1191 | 36.36 | 400 | 0.3636 | 0.3766 | 0.7396 | 0.8264 | nan | 0.6431 | 0.8361 | 0.0 | 0.3069 | 0.8230 |
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+ | 0.2008 | 38.18 | 420 | 0.3836 | 0.3685 | 0.7249 | 0.7907 | nan | 0.6516 | 0.7981 | 0.0 | 0.3194 | 0.7860 |
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+ | 0.0846 | 40.0 | 440 | 0.3602 | 0.3738 | 0.7285 | 0.8244 | nan | 0.6218 | 0.8352 | 0.0 | 0.2994 | 0.8219 |
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+ | 0.1178 | 41.82 | 460 | 0.3631 | 0.3751 | 0.7224 | 0.8311 | nan | 0.6015 | 0.8433 | 0.0 | 0.2964 | 0.8288 |
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+ | 0.0806 | 43.64 | 480 | 0.3631 | 0.3678 | 0.7233 | 0.8074 | nan | 0.6297 | 0.8169 | 0.0 | 0.2988 | 0.8045 |
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+ | 0.1102 | 45.45 | 500 | 0.3731 | 0.3686 | 0.7113 | 0.8067 | nan | 0.6053 | 0.8174 | 0.0 | 0.3025 | 0.8032 |
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+ | 0.0751 | 47.27 | 520 | 0.3671 | 0.3682 | 0.7249 | 0.8117 | nan | 0.6283 | 0.8215 | 0.0 | 0.2959 | 0.8085 |
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+ | 0.1272 | 49.09 | 540 | 0.3547 | 0.3725 | 0.7265 | 0.8226 | nan | 0.6195 | 0.8334 | 0.0 | 0.2973 | 0.8202 |
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  ### Framework versions