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JUSTers at SemEval-2020 Task 4: Evaluating Transformer Models Against Commonsense Validation and Explanation

  • Jordan University of Science and Technology
  • Nanyang Technological University

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

10 Scopus citations

Abstract

In this paper, we describe our team's (JUSTers) effort in the Commonsense Validation and Explanation (ComVE) task, which is part of SemEval2020. We evaluate five pre-trained Transformer-based language models with various sizes against the three proposed subtasks. For the first two subtasks, the best accuracy levels achieved by our models are 92.90% and 92.30%, respectively, placing our team in the 12th and 9th places, respectively. As for the last subtask, our models reach 16.10 BLEU score and 1.94 human evaluation score placing our team in the 5th and 3rd places according to these two metrics, respectively. The latter is only 0.16 away from the 1st place human evaluation score.

Original languageEnglish
Title of host publicationCOLING 2020 - The International Workshop on Semantic Evaluation, Proceedings of the 14th Workshop
EditorsAurelie Herbelot, Xiaodan Zhu, Alexis Palmer, Nathan Schneider, Jonathan May, Ekaterina Shutova
PublisherInternational Committee for Computational Linguistics
Pages535-542
Number of pages8
ISBN (Electronic)9781952148316
DOIs
StatePublished - 2020
Externally publishedYes
Event14th International Workshops on Semantic Evaluation, SemEval 2020, co-located with COLING 2020 - Virtual, Online, Spain
Duration: 12 Dec 202013 Dec 2020

Publication series

Name14th International Workshops on Semantic Evaluation, SemEval 2020 - co-located 28th International Conference on Computational Linguistics, COLING 2020, Proceedings

Conference

Conference14th International Workshops on Semantic Evaluation, SemEval 2020, co-located with COLING 2020
Country/TerritorySpain
CityVirtual, Online
Period12/12/2013/12/20

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