@inproceedings{raaj-p-etal-2023-harmony,
    title = "{HARMONY}@{D}ravidian{L}ang{T}ech: Transformer-based Ensemble Learning for Abusive Comment Detection",
    author = "Raaj P, Amrish  and
      Murugappan, Abirami  and
      Packiam R S, Lysa  and
      M, Deivamani",
    editor = "Chakravarthi, Bharathi R.  and
      Priyadharshini, Ruba  and
      M, Anand Kumar  and
      Thavareesan, Sajeetha  and
      Sherly, Elizabeth",
    booktitle = "Proceedings of the Third Workshop on Speech and Language Technologies for Dravidian Languages",
    month = sep,
    year = "2023",
    address = "Varna, Bulgaria",
    publisher = "INCOMA Ltd., Shoumen, Bulgaria",
    url = "https://preview.aclanthology.org/ingest_wac_2008/2023.dravidianlangtech-1.21/",
    pages = "160--165",
    abstract = "Millions of posts and comments are created every minute as a result of the widespread use of social media and easy access to the internet.It is essential to create an inclusive environment and forbid the use of abusive language against any individual or group of individuals.This paper describes the approach of team HARMONY for the {\textquotedblleft}Abusive Comment Detection{\textquotedblright} shared task at the Third Workshop on Speech and Language Technologies for Dravidian Languages.A Transformer-based ensemble learning approach is proposed for detecting abusive comments in code-mixed (Tamil-English) language and Tamil language. The proposed architecture achieved rank 2 in Tamil text classification sub task and rank 3 in code mixed text classification sub task with macro-F1 score of 0.41 for Tamil and 0.50 for code-mixed data."
}