giniUs @LT-EDI-ACL2022: Aasha: Transformers based Hope-EDI

Harshul Surana, Basavraj Chinagundi


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.
Anthology ID:
2022.ltedi-1.43
Volume:
Proceedings of the Second Workshop on Language Technology for Equality, Diversity and Inclusion
Month:
May
Year:
2022
Address:
Dublin, Ireland
Editors:
Bharathi Raja Chakravarthi, B Bharathi, John P McCrae, Manel Zarrouk, Kalika Bali, Paul Buitelaar
Venue:
LTEDI
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
291–295
Language:
URL:
https://aclanthology.org/2022.ltedi-1.43
DOI:
10.18653/v1/2022.ltedi-1.43
Bibkey:
Cite (ACL):
Harshul Surana and Basavraj Chinagundi. 2022. giniUs @LT-EDI-ACL2022: Aasha: Transformers based Hope-EDI. In Proceedings of the Second Workshop on Language Technology for Equality, Diversity and Inclusion, pages 291–295, Dublin, Ireland. Association for Computational Linguistics.
Cite (Informal):
giniUs @LT-EDI-ACL2022: Aasha: Transformers based Hope-EDI (Surana & Chinagundi, LTEDI 2022)
Copy Citation:
PDF:
https://aclanthology.org/2022.ltedi-1.43.pdf
Data
HopeEDI