@inproceedings{surana-chinagundi-2022-ginius,
    title = "gini{U}s @{LT}-{EDI}-{ACL}2022: Aasha: Transformers based Hope-{EDI}",
    author = "Chinagundi, Basavraj  and
      Surana, Harshul",
    editor = "Chakravarthi, Bharathi Raja  and
      Bharathi, B  and
      McCrae, John P  and
      Zarrouk, Manel  and
      Bali, Kalika  and
      Buitelaar, Paul",
    booktitle = "Proceedings of the Second Workshop on Language Technology for Equality, Diversity and Inclusion",
    month = may,
    year = "2022",
    address = "Dublin, Ireland",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/ingest-emnlp/2022.ltedi-1.43/",
    doi = "10.18653/v1/2022.ltedi-1.43",
    pages = "291--295",
    abstract = "This paper describes team giniUs' submission to the Hope Speech Detection for Equality, Diversity and Inclusion Shared Task organised by LT-EDI ACL 2022. We have fine-tuned the Roberta-large pre-trained model and extracted the last four decoder layers to build a classifier. Our best result on the leaderboard achieve a weighted F1 score of 0.86 and a Macro F1 score of 0.51 for English. We have secured a rank of 4 for the English task. We have open-sourced our code implementations on GitHub to facilitate easy reproducibility by the scientific community."
}