Abstract
Task 7, Assessing the Funniness of Edited News Headlines, in the International Workshop SemEval2020 introduces two sub-tasks to predict the funniness values of edited news headlines from the Reddit website. This paper proposes the BFHumor model of the MLEngineer team that participates in both sub-tasks in this competition. The BFHumor’s model is defined as a BERT-Flair based humor detection model that is a combination of different pre-trained models with various Natural Language Processing (NLP) techniques. The Bidirectional Encoder Representations from Transformers (BERT) regressor is considered the primary pre-trained model in our approach, whereas Flair is the main NLP library. It is worth mentioning that the BFHumor model has been ranked 4th in sub-task1 with a root mean square error (RMSE) value of 0.51966, and it is 0.02 away from the first ranked model. Also, the team is ranked 12th in the sub-task2 with an accuracy of 0.62291, which is 0.05 away from the top-ranked model. Our results indicate that the BFHumor model is one of the top models for detecting humor in the text.- Anthology ID:
- 2020.semeval-1.136
- Volume:
- Proceedings of the Fourteenth Workshop on Semantic Evaluation
- Month:
- December
- Year:
- 2020
- Address:
- Barcelona (online)
- Editors:
- Aurelie Herbelot, Xiaodan Zhu, Alexis Palmer, Nathan Schneider, Jonathan May, Ekaterina Shutova
- Venue:
- SemEval
- SIG:
- SIGLEX
- Publisher:
- International Committee for Computational Linguistics
- Note:
- Pages:
- 1041–1048
- Language:
- URL:
- https://aclanthology.org/2020.semeval-1.136
- DOI:
- 10.18653/v1/2020.semeval-1.136
- Cite (ACL):
- Fara Shatnawi, Malak Abdullah, and Mahmoud Hammad. 2020. MLEngineer at SemEval-2020 Task 7: BERT-Flair Based Humor Detection Model (BFHumor). In Proceedings of the Fourteenth Workshop on Semantic Evaluation, pages 1041–1048, Barcelona (online). International Committee for Computational Linguistics.
- Cite (Informal):
- MLEngineer at SemEval-2020 Task 7: BERT-Flair Based Humor Detection Model (BFHumor) (Shatnawi et al., SemEval 2020)
- PDF:
- https://preview.aclanthology.org/landing_page/2020.semeval-1.136.pdf