A comparative analysis of GPT-3 and BERT models for text-based emotion recognition: performance, efficiency, and robustness

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper presents a comparative analysis between the GPT model and a BERT model for emotion recognition. While GPT has shown remarkable performance across various tasks, the question arises as to whether its results can be compared to models specifically trained for particular tasks. The paper explores the presentations of GPT, including its models (Davinci, Curie, Babbage and Ada) as well as the fine-tuning approach. Similarly, the paper discusses the presentation of BERT, specifically DeBERTa v3, and its fine-tuning methodology. A comparison is then drawn between the two models, considering the general vs. task-specific nature of AI. Furthermore, the paper investigates the reasons behind GPT's exceptional performance and examines why the obtained results for emotion recognition may not be significantly better than those of task-specific models. Ultimately, the conclusion reflects on the better accuracy often exhibited by BERT, but highlights the potential for future advancements, such as the new GPT-4, that may surpass existing models and offer unparalleled versatility in answering various questions.
Original languageEnglish
Title of host publicationAdvances in Computational Intelligence Systems
Subtitle of host publicationContributions Presented at the 22nd UK Workshop on Computational Intelligence (UKCI 2023), September 6–8, 2023, Birmingham, UK
EditorsNitin Naik, Paul Jenkins, Paul Grace, Longzhi Yang, Shaligram Prajapat
PublisherSpringer
Pages567–579
ISBN (Electronic)9783031475085
ISBN (Print)9783031475078
DOIs
Publication statusPublished - 1 Feb 2024
EventUKCI 2023: The 22nd Workshop on Computational Intelligence - Aston University, Birmingham, United Kingdom
Duration: 6 Sept 20238 Sept 2023
https://www.uk-ci.org/home

Publication series

NameAdvances in Intelligent Systems and Computing
PublisherSpringer
Volume1453
ISSN (Print)2194-5357
ISSN (Electronic)2194-5365

Workshop

WorkshopUKCI 2023: The 22nd Workshop on Computational Intelligence
Country/TerritoryUnited Kingdom
CityBirmingham
Period6/09/238/09/23
Internet address

Keywords

  • GPT model
  • BERT model
  • emotion recognition
  • general vs. task specific AI

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