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--- |
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base_model: mividia/mit-b2 |
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tags: |
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- retouch |
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- image-segmentation |
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- generated_from_trainer |
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model-index: |
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- name: testing_303 |
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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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# testing_303 |
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This model is a fine-tuned version of [mividia/mit-b2](https://huggingface.co/mividia/mit-b2) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0 |
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- Mean Iou: nan |
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- Mean Accuracy: nan |
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- Overall Accuracy: nan |
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- Accuracy Wht: nan |
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- Iou Wht: nan |
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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: 2 |
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- eval_batch_size: 8 |
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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: 1 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Mean Iou | Mean Accuracy | Overall Accuracy | Accuracy Wht | Iou Wht | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:-------------:|:----------------:|:------------:|:-------:| |
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| 0.0 | 1.0 | 270 | 0.0 | nan | nan | nan | nan | nan | |
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### Framework versions |
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- Transformers 4.33.3 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.14.5 |
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- Tokenizers 0.13.3 |
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