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--- |
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license: other |
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base_model: nvidia/mit-b0 |
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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: segformerSAADNew |
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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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# segformerSAADNew |
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This model is a fine-tuned version of [nvidia/mit-b0](https://huggingface.co/nvidia/mit-b0) on the saad7489/SixGUNNew dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6994 |
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- Mean Iou: 0.4393 |
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- Mean Accuracy: 0.9081 |
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- Overall Accuracy: 0.9708 |
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- Accuracy Bkg: 0.9732 |
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- Accuracy Gun: nan |
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- Accuracy Knife: 0.8431 |
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- Iou Bkg: 0.9704 |
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- Iou Gun: 0.0 |
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- Iou Knife: 0.3476 |
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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: 5e-05 |
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- train_batch_size: 30 |
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- eval_batch_size: 30 |
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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 Bkg | Accuracy Gun | Accuracy Knife | Iou Bkg | Iou Gun | Iou Knife | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:-------------:|:----------------:|:------------:|:------------:|:--------------:|:-------:|:-------:|:---------:| |
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| 0.8827 | 4.0 | 20 | 0.8654 | 0.4254 | 0.8976 | 0.9662 | 0.9688 | nan | 0.8264 | 0.9657 | 0.0 | 0.3106 | |
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| 0.7151 | 8.0 | 40 | 0.6994 | 0.4393 | 0.9081 | 0.9708 | 0.9732 | nan | 0.8431 | 0.9704 | 0.0 | 0.3476 | |
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### Framework versions |
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- Transformers 4.42.4 |
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- Pytorch 2.4.0+cu121 |
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- Datasets 2.21.0 |
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- Tokenizers 0.19.1 |
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