@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://aclanthology.org/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.",
}
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<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.</abstract>
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%0 Conference Proceedings
%T giniUs @LT-EDI-ACL2022: Aasha: Transformers based Hope-EDI
%A Chinagundi, Basavraj
%A Surana, Harshul
%Y Chakravarthi, Bharathi Raja
%Y Bharathi, B.
%Y McCrae, John P.
%Y Zarrouk, Manel
%Y Bali, Kalika
%Y Buitelaar, Paul
%S Proceedings of the Second Workshop on Language Technology for Equality, Diversity and Inclusion
%D 2022
%8 May
%I Association for Computational Linguistics
%C Dublin, Ireland
%F surana-chinagundi-2022-ginius
%X 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.
%R 10.18653/v1/2022.ltedi-1.43
%U https://aclanthology.org/2022.ltedi-1.43
%U https://doi.org/10.18653/v1/2022.ltedi-1.43
%P 291-295
Markdown (Informal)
[giniUs @LT-EDI-ACL2022: Aasha: Transformers based Hope-EDI](https://aclanthology.org/2022.ltedi-1.43) (Chinagundi & Surana, LTEDI 2022)
ACL