NITK-IT-NLP@DravidianLangTech-2023: Impact of Focal Loss on Malayalam Fake News Detection using Transformers

dc.contributor.authorLekshmiAmmal, R.L.
dc.contributor.authorAnand Kumar, M.
dc.date.accessioned2026-02-06T06:34:37Z
dc.date.issued2023
dc.description.abstractFake News Detection in Dravidian Languages is a shared task that identifies YouTube comments in the Malayalam language for fake news detection. In this work, we have proposed a transformer-based model with cross-entropy loss and focal loss, which classifies the comments into fake or authentic news. We have used different transformer-based models for the dataset with modifications in the experimental setup, out of which the fine-tuned model, which is based on MuRIL with focal loss, achieved the best overall macro F1-score of 0.87, and we got second position in the final leaderboard. © DravidianLangTech 2023 - 3rd Workshop on Speech and Language Technologies for Dravidian Languages, associated with 14th International Conference on Recent Advances in Natural Language Processing, RANLP 2023 - Proceedings.
dc.identifier.citationDravidianLangTech 2023 - 3rd Workshop on Speech and Language Technologies for Dravidian Languages, associated with 14th International Conference on Recent Advances in Natural Language Processing, RANLP 2023 - Proceedings, 2023, Vol., , p. 207-210
dc.identifier.urihttps://doi.org/10.26615/978-954-452-085-4_029
dc.identifier.urihttps://idr.nitk.ac.in/handle/123456789/29332
dc.publisherIncoma Ltd
dc.titleNITK-IT-NLP@DravidianLangTech-2023: Impact of Focal Loss on Malayalam Fake News Detection using Transformers

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