Amobee at SemEval-2020 Task 7: Regularization of Language Model Based Classifiers

Alon Rozental, Dadi Biton, Ido Blank


Abstract
This paper describes Amobee’s participation in SemEval-2020 task 7: “Assessing Humor in Edited News Headlines”, sub-tasks 1 and 2. The goal of this task was to estimate the funniness of human modified news headlines. in this paper we present methods to fine-tune and ensemble various language models (LM) based classifiers to for this task. This technique used for both sub-tasks and reached the second place (out of 49) in sub-tasks 1 with RMSE score of 0.5, and the second (out of 32) place in sub-task 2 with accuracy of 66% without using any additional data except the official training set.
Anthology ID:
2020.semeval-1.127
Volume:
Proceedings of the Fourteenth Workshop on Semantic Evaluation
Month:
December
Year:
2020
Address:
Barcelona (online)
Venue:
SemEval
SIG:
SIGLEX
Publisher:
International Committee for Computational Linguistics
Note:
Pages:
981–985
Language:
URL:
https://aclanthology.org/2020.semeval-1.127
DOI:
10.18653/v1/2020.semeval-1.127
Bibkey:
Cite (ACL):
Alon Rozental, Dadi Biton, and Ido Blank. 2020. Amobee at SemEval-2020 Task 7: Regularization of Language Model Based Classifiers. In Proceedings of the Fourteenth Workshop on Semantic Evaluation, pages 981–985, Barcelona (online). International Committee for Computational Linguistics.
Cite (Informal):
Amobee at SemEval-2020 Task 7: Regularization of Language Model Based Classifiers (Rozental et al., SemEval 2020)
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PDF:
https://preview.aclanthology.org/emnlp-22-attachments/2020.semeval-1.127.pdf