# MedicalMeadow ⚕️💬🩺

## Overview

MedicalMeadow is a project focused on training a chatbot using the LLaMA model, fine-tuned with the Medical Meadow dataset. The aim is to develop a robust NLP system capable of answering medical questions effectively.

## Scope

The primary goal is to fine-tune a pre-trained NLP model on a specialized medical dataset to enable accurate and context-aware medical question answering.

## Dataset: Medical Meadow Medical Flashcards

- **Website:** [Medical Meadow on Hugging Face](https://huggingface.co/datasets/medalpaca/medical_meadow_medical_flashcards)

- **Paper:** [Medical Meadow: A Dataset for Medical Knowledge Question Answering](https://arxiv.org/pdf/2304.08247.pdf)

- **Description:** This dataset consists of question-answer pairs generated by GPT-3.5 based on medical curriculum flashcards. It provides a comprehensive resource for training models in medical knowledge retrieval and question answering.

- **Task:** Develop and fine-tune an NLP model to handle medical question answering tasks efficiently.

## Project Objectives

- **Model Selection:** Utilize the LLaMA model as the base for chatbot development.

- **Fine-Tuning:** Apply transfer learning techniques to fine-tune the model with the Medical Meadow dataset.

- **Performance Evaluation:** Assess the chatbot's performance on various medical question-answering benchmarks to ensure reliability and accuracy.

## License

This project is licensed under the MIT License. See the `LICENSE` file for more details.