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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: trashbot |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# trashbot |
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This model is a fine-tuned version of [nvidia/mit-b5](https://huggingface.co/nvidia/mit-b5) on the mraottth/all_locations_pooled dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0189 |
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- Mean Iou: 0.4050 |
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- Mean Accuracy: 0.8101 |
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- Overall Accuracy: 0.8101 |
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- Accuracy Unlabeled: nan |
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- Accuracy Trash: 0.8101 |
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- Iou Unlabeled: 0.0 |
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- Iou Trash: 0.8101 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 6e-05 |
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- train_batch_size: 3 |
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- eval_batch_size: 3 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 10 |
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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 Trash | Iou Unlabeled | Iou Trash | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:-------------:|:----------------:|:------------------:|:--------------:|:-------------:|:---------:| |
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| 0.0592 | 1.0 | 90 | 0.0387 | 0.3723 | 0.7446 | 0.7446 | nan | 0.7446 | 0.0 | 0.7446 | |
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| 0.0402 | 2.0 | 180 | 0.0281 | 0.4123 | 0.8247 | 0.8247 | nan | 0.8247 | 0.0 | 0.8247 | |
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| 0.0209 | 3.0 | 270 | 0.0246 | 0.3691 | 0.7382 | 0.7382 | nan | 0.7382 | 0.0 | 0.7382 | |
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| 0.0117 | 4.0 | 360 | 0.0210 | 0.3882 | 0.7763 | 0.7763 | nan | 0.7763 | 0.0 | 0.7763 | |
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| 0.019 | 5.0 | 450 | 0.0198 | 0.3822 | 0.7644 | 0.7644 | nan | 0.7644 | 0.0 | 0.7644 | |
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| 0.0445 | 6.0 | 540 | 0.0199 | 0.3771 | 0.7542 | 0.7542 | nan | 0.7542 | 0.0 | 0.7542 | |
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| 0.0195 | 7.0 | 630 | 0.0191 | 0.4177 | 0.8354 | 0.8354 | nan | 0.8354 | 0.0 | 0.8354 | |
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| 0.008 | 8.0 | 720 | 0.0191 | 0.4060 | 0.8119 | 0.8119 | nan | 0.8119 | 0.0 | 0.8119 | |
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| 0.0268 | 9.0 | 810 | 0.0188 | 0.4083 | 0.8166 | 0.8166 | nan | 0.8166 | 0.0 | 0.8166 | |
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| 0.0061 | 10.0 | 900 | 0.0189 | 0.4050 | 0.8101 | 0.8101 | nan | 0.8101 | 0.0 | 0.8101 | |
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### Framework versions |
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- Transformers 4.26.0 |
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- Pytorch 1.13.1+cu116 |
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- Datasets 2.9.0 |
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- Tokenizers 0.13.2 |
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