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

Source: [Question-Answering System for Bangla: Fine-tuning BERT-Bangla for a Closed Domain](<https://www.sota2.com/research/paper/68fa75141e209131cea65928>)

Collection index: [llms.txt](<https://www.sota2.com/research/llms.txt>)

Data updated: 2025-10-26T03:25:16.855Z

Authors: Subal Chandra Roy, Md Motaleb Hossen Manik

Published: 2024-10-04T20:57:08.000Z

## 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.

## Recorded benchmark results

A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage.

## Original sources and implementation

[Original paper](<https://arxiv.org/abs/2410.03923>)

[PDF](<https://arxiv.org/pdf/2410.03923.pdf>)