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
• Paper: Medical Meadow: A Dataset for Medical Knowledge Question Answering
• 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.