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--- |
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license: apache-2.0 |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: clinical-t5 |
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results: [] |
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datasets: |
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- AGBonnet/augmented-clinical-notes |
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language: |
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- en |
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metrics: |
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- rouge |
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pipeline_tag: summarization |
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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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# clinical-t5 |
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This is a finetuned T5-small model from Google, a checkpoint with 60 million parameters, for clinical note summarization. |
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It was finetuned with the [augmented-clinical-notes](https://huggingface.co/datasets/AGBonnet/augmented-clinical-notes) dataset, available in the Hugging Face. |
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## Intended uses & limitations |
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The model was created for learning purposes. Hence, although being briefly evaluated in [this](https://github.com/hossboll/clinical_nlp/blob/main/clinical_t5_finetuned.ipynb |
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) notebook, it should be further refined. |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 2e-05 |
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- train_batch_size: 16 |
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- eval_batch_size: 16 |
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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: 4 |
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### Framework versions |
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- Transformers 4.30.0 |
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- Pytorch 2.2.1+cu121 |
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- Datasets 2.19.1 |
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- Tokenizers 0.13.3 |
