# 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.