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segformer-b0-finetuned-segments-sidewalk-2
erikhenriksson1/segformer-b0-finetuned-segments-sidewalk-2
segformer-b0-finetuned-segments-sidewalk-2 is a image segmentation model from erikhenriksson1. Use it for the image segmentation task on the model card, and read the license before you ship it in a product. It is set up for transformers. The card lists the license as other.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Image Segmentation
- Library
- transformers
- License
- other
- Model type
- segformer
- Access
- Public
- Created
- Mar 26, 2024
- Updated
- Mar 26, 2024
- SHA
- 82d689c9
Base models
Model card
From the Hugging Face model README
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
segformer-b0-finetuned-segments-sidewalk-2
This model is a fine-tuned version of nvidia/mit-b0 on the erikhenriksson1/test_skin_segmentation dataset. It achieves the following results on the evaluation set:
- Loss: 0.1985
- Mean Iou: 0.6571
- Mean Accuracy: 0.6626
- Overall Accuracy: 0.9937
- Accuracy Unlabeled: nan
- Accuracy Skin: 0.9939
- Accuracy Mark of interest: 0.0
- Accuracy Non-skin: 0.9939
- Iou Unlabeled: nan
- Iou Skin: 0.9801
- Iou Mark of interest: 0.0
- Iou Non-skin: 0.9911
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 6e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 50
Training results
| Training Loss | Epoch | Step | Validation Loss | Mean Iou | Mean Accuracy | Overall Accuracy | Accuracy Unlabeled | Accuracy Skin | Accuracy Mark of interest | Accuracy Non-skin | Iou Unlabeled | Iou Skin | Iou Mark of interest | Iou Non-skin |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0.6293 | 5.0 | 20 | 0.9612 | 0.5999 | 0.6435 | 0.9522 | nan | 1.0 | 0.0 | 0.9306 | nan | 0.8691 | 0.0 | 0.9306 |
| 0.4646 | 10.0 | 40 | 0.4611 | 0.6321 | 0.6552 | 0.9765 | nan | 0.9990 | 0.0 | 0.9665 | nan | 0.9304 | 0.0 | 0.9660 |
| 0.3595 | 15.0 | 60 | 0.3382 | 0.6423 | 0.6578 | 0.9837 | nan | 0.9944 | 0.0 | 0.9791 | nan | 0.9505 | 0.0 | 0.9766 |
| 0.3065 | 20.0 | 80 | 0.3041 | 0.6461 | 0.6592 | 0.9863 | nan | 0.9951 | 0.0 | 0.9826 | nan | 0.9581 | 0.0 | 0.9804 |
| 0.2874 | 25.0 | 100 | 0.2659 | 0.6506 | 0.6604 | 0.9893 | nan | 0.9934 | 0.0 | 0.9877 | nan | 0.9669 | 0.0 | 0.9848 |
| 0.2319 | 30.0 | 120 | 0.2461 | 0.6522 | 0.6614 | 0.9904 | nan | 0.9961 | 0.0 | 0.9881 | nan | 0.9703 | 0.0 | 0.9864 |
| 0.2396 | 35.0 | 140 | 0.2279 | 0.6565 | 0.6626 | 0.9933 | nan | 0.9952 | 0.0 | 0.9927 | nan | 0.9790 | 0.0 | 0.9906 |
| 0.2215 | 40.0 | 160 | 0.2099 | 0.6564 | 0.6624 | 0.9932 | nan | 0.9939 | 0.0 | 0.9932 | nan | 0.9788 | 0.0 | 0.9904 |
| 0.2128 | 45.0 | 180 | 0.2021 | 0.6565 | 0.6626 | 0.9933 | nan | 0.9948 | 0.0 | 0.9929 | nan | 0.9789 | 0.0 | 0.9905 |
| 0.1855 | 50.0 | 200 | 0.1985 | 0.6571 | 0.6626 | 0.9937 | nan | 0.9939 | 0.0 | 0.9939 | nan | 0.9801 | 0.0 | 0.9911 |
Framework versions
- Transformers 4.39.1
- Pytorch 2.2.1
- Datasets 2.18.0
- Tokenizers 0.15.2
- Task
- Image Segmentation
- Library
- transformers
- Type
- segformer
- License
- other
- Created
- Mar 26, 2024
- Updated
- Mar 26, 2024