Question-Answering System for Bangla: Fine-tuning BERT-Bangla for a Closed Domain

TL;DR

This paper develops a Bengali question-answering system using a fine-tuned BERT-Bangla model for a specific domain, demonstrating promising results with room for improvement on complex queries.

Contribution

It introduces a domain-specific Bengali QA system based on fine-tuning BERT-Bangla, filling a gap in Bengali NLP applications.

Findings

Achieved 55.26% Exact Match score

Achieved 74.21% F1 score

Demonstrated potential for domain-specific Bengali QA

Abstract

Question-answering systems for Bengali have seen limited development, particularly in domain-specific applications. Leveraging advancements in natural language processing, this paper explores a fine-tuned BERT-Bangla model to address this gap. It presents the development of a question-answering system for Bengali using a fine-tuned BERT-Bangla model in a closed domain. The dataset was sourced from Khulna University of Engineering \& Technology's (KUET) website and other relevant texts. The system was trained and evaluated with 2500 question-answer pairs generated from curated data. Key metrics, including the Exact Match (EM) score and F1 score, were used for evaluation, achieving scores of 55.26\% and 74.21\%, respectively. The results demonstrate promising potential for domain-specific Bengali question-answering systems. Further refinements are needed to improve performance for more complex queries.