MIPT-NSU-UTMN at SemEval-2021 Task 5: Ensembling Learning with Pre-trained Language Models for Toxic Spans Detection

Mikhail Kotyushev; Anna Glazkova; Dmitry Morozov

doi:10.18653/v1/2021.semeval-1.124

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arXiv · 2104.04739

MIPT-NSU-UTMN at SemEval-2021 Task 5: Ensembling Learning with Pre-trained Language Models for Toxic Spans Detection

Mikhail Kotyushev·Anna Glazkova·Dmitry Morozov

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Abstract

This paper describes our system for SemEval-2021 Task 5 on Toxic Spans Detection. We developed ensemble models using BERT-based neural architectures and post-processing to combine tokens into spans. We evaluated several pre-trained language models using various ensemble techniques for toxic span identification and achieved sizable improvements over our baseline fine-tuned BERT models. Finally, our system obtained a F1-score of 67.55% on test data.

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Mikhail Kotyushev, Anna Glazkova, Dmitry Morozov. 2021-04-10. MIPT-NSU-UTMN at SemEval-2021 Task 5: Ensembling Learning with Pre-trained Language Models for Toxic Spans Detection. https://doi.org/10.18653/v1/2021.semeval-1.124

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