omi-health
/

sum-small

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-library_name: transformers
-tags: []
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+title: "Summ Small: Medical Dialogue to SOAP Summarizer"
+emoji: "📄"
+colorFrom: "green"
+colorTo: "pink"
+sdk: "static"
+pinned: false
 ---
+# Model Card for Summ (3B) Small
+## Model Description
+Summ Small is a powerful language model specifically designed to generate SOAP summaries from medical dialogues. It is a fine-tuned version of the Microsoft/Phi-3-mini-4k-instruct model using the Omi Health/medical-dialogue-to-soap-summary dataset. Despite its 'small' label, which anticipates future larger versions, this model delivers superior performance compared to larger models like GPT-4.
+## Intended Use
+This model is intended for research and development in AI-powered medical documentation. It is not ready for direct clinical use without further validation and should be integrated with additional safety guardrails before deployment in a medical setting.
+## Training Data
+The model was trained on the Omi Health's synthetic medical-dialogue-to-soap-summary dataset, which consists of 10,000 synthetically generated dialogues and corresponding SOAP summaries.
+## Training Procedure
+Training was conducted on NVIDIA A100 GPUs, ensuring efficient processing and model optimization.
 ## Evaluation
+Preliminary evaluation using Rouge-1 metrics shows Summ Small achieving a score of 70, outperforming other models like GPT4Turbo (69), LLama3 8B Instruct (59), and GPT3.5 (54).
+## Limitations
+While Summ Small demonstrates promising results, the training data is completely synthetic and not derived from actual clinical interactions. Care must be taken when considering this model for practical applications, as it requires significant testing and adaptation to meet clinical safety standards.
+## Licensing
+The Summ Small model is released under the MIT License, which permits broad use with fewer restrictions, making it accessible for both commercial and non-commercial use.
+## How to Use
+For those interested in experimenting with or further developing Summ Small, access can be granted upon request, with terms aligning with usage rights and ethical considerations.
+## Ethical Considerations
+Users are urged to consider the ethical implications of AI in healthcare and ensure that any deployment of such models prioritizes patient safety and data privacy.
+## Contact
+For more information or to request access to Summ Small, please contact [[email protected]](mailto:[email protected]).