# BioBERT Fine-Tuned

## Model Description
This model is a fine-tuned version of **BioBERT**, a pre-trained biomedical language model, adapted for **medical text classification**. It classifies medical abstracts into predefined categories based on their content.

## Training Data
- **Dataset**: Contains **2286 medical abstracts** across five categories:
  - Neoplasms
  - Digestive System Diseases
  - Nervous System Diseases
  - Cardiovascular Diseases
  - General Pathological Conditions
- **Preprocessing**: Includes normalization, lemmatization, tokenization, stopword removal, and medical term standardization.

## Intended Use
- **Medical Text Classification**: This model can be used for categorizing medical abstracts and research papers into relevant medical departments.

## Limitations
- **Not suitable for general-purpose NLP tasks**.
- **Domain-specific**: The model may not perform well outside the medical field or with non-English text.