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arXiv.org e-Print Archive
Other literature type . Preprint . 2021
https://doi.org/10.48550/arxiv...
Article . 2021
License: CC BY
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Pretrained Transformers for Offensive Language Identification in Tanglish

Authors: Benhur, Sean; Sivanraju, Kanchana;

Pretrained Transformers for Offensive Language Identification in Tanglish

Abstract

This paper describes the system submitted to Dravidian-Codemix-HASOC2021: Hate Speech and Offensive Language Identification in Dravidian Languages (Tamil-English and Malayalam-English). This task aims to identify offensive content in code-mixed comments/posts in Dravidian Languages collected from social media. Our approach utilizes pooling the last layers of pretrained transformer multilingual BERT for this task which helped us achieve rank nine on the leaderboard with a weighted average score of 0.61 for the Tamil-English dataset in subtask B. After the task deadline, we sampled the dataset uniformly and used the MuRIL pretrained model, which helped us achieve a weighted average score of 0.67, the top score in the leaderboard. Furthermore, our approach to utilizing the pretrained models helps reuse our models for the same task with a different dataset. Our code and models are available in https://github.com/seanbenhur/tanglish-offensive-language-identification

Comment: Accepted at FIRE 2021

Related Organizations
Keywords

FOS: Computer and information sciences, Computer Science - Computation and Language, Computation and Language (cs.CL)

[1] S. U. Hegde, A. Hande, R. Priyadharshini, S. Thavareesan, R. Sakuntharaj, S. Thangasamy, B. Bharathi, B. R. Chakravarthi, Do Images really do the Talking? Analysing the significance of Images in Tamil Troll meme classification, arXiv preprint arXiv:2108.03886 (2021).

[2] B. R. Chakravarthi, R. Priyadharshini, R. Ponnusamy, P. K. Kumaresan, K. Sampath, D. Thenmozhi, S. Thangasamy, R. Nallathambi, J. P. McCrae, Dataset for Identification of Homophobia and Transophobia in Multilingual YouTube Comments, arXiv preprint arXiv:2109.00227 (2021).

[3] S. Suryawanshi, B. R. Chakravarthi, M. Arcan, S. Little, P. Buitelaar, TrollsWithOpinion:

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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