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--- |
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library_name: transformers |
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tags: |
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- masked-image-modeling |
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- generated_from_trainer |
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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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# smb-vision-base-1029 |
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This model is trained from scratch using [VideoMAE](https://huggingface.co/docs/transformers/en/model_doc/videomae) on over 4.7k CT volumes. |
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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: 3e-04 |
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- train_batch_size: 32 |
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- eval_batch_size: 1 |
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- seed: 42 |
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- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: cosine |
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- num_epochs: 30.0 |
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### Training results |
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{ |
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"_runtime": 54805.860011105, |
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"_step": 4351, |
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"eval/runtime": 17.8428, |
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"eval/samples_per_second": 2.578, |
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"eval/steps_per_second": 2.578, |
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"total_flos": 3.8084565648770335e+21, |
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"train/epoch": 30, |
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"train/global_step": 4350, |
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"train/grad_norm": 0.0735374316573143, |
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"train/learning_rate": 0, |
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"train/loss": 0.5736, |
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"train_loss": 0.5022664608695041, |
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"train_runtime": 54785.1298, |
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"train_samples_per_second": 2.527, |
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"train_steps_per_second": 0.079 |
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} |
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### Framework versions |
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- Transformers 4.46.0 |
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- Pytorch 2.5.0 |
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- Datasets 3.0.2 |
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- Tokenizers 0.20.1 |
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### How to use |
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```python |
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# load data using `dataload.py` |
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model = VideoMAEForPreTraining.from_pretrained( |
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standardmodelbio/smb-vision-base, |
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trust_remote_code=True, |
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) |
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embedding = model.videomae(batch["image"]) |
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``` |
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