# Fine-Tuned GPT-2 Model for Medical Question Answering

## Model Description
This model is a fine-tuned version of GPT-2 on the MedQuAD dataset. The primary objective of this model is to generate accurate and informative responses to medical queries based on the training data.

## Training Data
The model was trained on the MedQuAD dataset, which consists of medical questions and answers. The dataset covers a wide range of medical topics and is intended to provide reliable and evidence-based information.

## Training Procedure
- **Base Model:** GPT-2
- **Dataset:** MedQuAD
- **Training Framework:** Hugging Face Transformers
- **Training Arguments:**
  - `output_dir="./results"`
  - `num_train_epochs=1`
  - `per_device_train_batch_size=4`
  - `save_steps=10,000`
  - `save_total_limit=2`
  - `logging_dir="./logs"`

## Intended Use
This model is intended for generating responses to medical questions. It can be used in applications such as telemedicine, healthcare chatbots, and medical information retrieval systems.

## Limitations
- The model's responses are based on the training data and may not always reflect the most up-to-date medical knowledge.
- Users should always consult a medical professional for accurate and personalized medical advice.

## Evaluation
The model's performance was evaluated based on the coherence, accuracy, and relevance of the generated responses. Additional metrics and evaluations can be added as needed.

## Licensing
The model is released under the Apache 2.0 license.

## Contact Information
For questions or comments about the model, please contact the developer.