Amherst685 at SemEval-2021 Task 7: Joint Modeling of Classification and Regression for Humor and Offense

Brian Zylich, Akshay Gugnani, Gabriel Brookman, Nicholas Samoray


Abstract
This paper describes our submission to theSemEval’21: Task 7- HaHackathon: Detecting and Rating Humor and Offense. In this challenge, we explore intermediate finetuning, backtranslation augmentation, multitask learning, and ensembling of different language models. Curiously, intermediate finetuning and backtranslation do not improve performance, while multitask learning and ensembling do improve performance. We explore why intermediate finetuning and backtranslation do not provide the same benefit as other natural language processing tasks and offer insight into the errors that our model makes. Our best performing system ranks 7th on Task 1bwith an RMSE of 0.5339
Anthology ID:
2021.semeval-1.168
Volume:
Proceedings of the 15th International Workshop on Semantic Evaluation (SemEval-2021)
Month:
August
Year:
2021
Address:
Online
Venues:
ACL | IJCNLP | SemEval
SIG:
SIGLEX
Publisher:
Association for Computational Linguistics
Note:
Pages:
1190–1195
Language:
URL:
https://aclanthology.org/2021.semeval-1.168
DOI:
10.18653/v1/2021.semeval-1.168
Bibkey:
Copy Citation:
PDF:
https://aclanthology.org/2021.semeval-1.168.pdf