9th International Conference on ICT for Sustainable Development

Authors - Sanjana Kumari, Nandini Verma, Shailesh Kamble, Praful V. Barekar
Abstract - This paper presents a systematic evaluation and comparison of various pre-trained Natural Language Processing (NLP) models across diverse NLP tasks, encompassing question-answering (QA) and text summarization. Our objective is to discern the most efficient and effective models tailored for specific applications. Through meticulous analysis, we delve into the nuanced strengths and weaknesses of each model, shedding light on their performance metrics. By contributing empirical insights, this research aims to propel the advancement of NLP technology. Our findings serve as a valuable resource for decision-makers, offering guidance in the selection of appropriate models for real-world use cases. Overall, this study bridges the gap between theory and practice, paving the way for enhanced NLP applications across various domains.