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        <title>TEAM HUB@LT-EDI-EACL2021: Hope Speech Detection Based On Pre-trained Language Model</title>
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        <namePart type="given">Bo</namePart>
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            <title>Proceedings of the First Workshop on Language Technology for Equality, Diversity and Inclusion</title>
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        <name type="personal">
            <namePart type="given">Bharathi</namePart>
            <namePart type="given">Raja</namePart>
            <namePart type="family">Chakravarthi</namePart>
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            <namePart type="given">John</namePart>
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            <namePart type="given">Manel</namePart>
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            <namePart type="given">Kalika</namePart>
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    <abstract>This article introduces the system description of TEAM_HUB team participating in LT-EDI 2021: Hope Speech Detection. This shared task is the first task related to the desired voice detection. The data set in the shared task consists of three different languages (English, Tamil, and Malayalam). The task type is text classification. Based on the analysis and understanding of the task description and data set, we designed a system based on a pre-trained language model to complete this shared task. In this system, we use methods and models that combine the XLM-RoBERTa pre-trained language model and the Tf-Idf algorithm. In the final result ranking announced by the task organizer, our system obtained F1 scores of 0.93, 0.84, 0.59 on the English dataset, Malayalam dataset, and Tamil dataset. Our submission results are ranked 1, 2, and 3 respectively.</abstract>
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%0 Conference Proceedings
%T TEAM HUB@LT-EDI-EACL2021: Hope Speech Detection Based On Pre-trained Language Model
%A Huang, Bo
%A Bai, Yang
%Y Chakravarthi, Bharathi Raja
%Y McCrae, John P.
%Y Zarrouk, Manel
%Y Bali, Kalika
%Y Buitelaar, Paul
%S Proceedings of the First Workshop on Language Technology for Equality, Diversity and Inclusion
%D 2021
%8 April
%I Association for Computational Linguistics
%C Kyiv
%F huang-bai-2021-team
%X This article introduces the system description of TEAM_HUB team participating in LT-EDI 2021: Hope Speech Detection. This shared task is the first task related to the desired voice detection. The data set in the shared task consists of three different languages (English, Tamil, and Malayalam). The task type is text classification. Based on the analysis and understanding of the task description and data set, we designed a system based on a pre-trained language model to complete this shared task. In this system, we use methods and models that combine the XLM-RoBERTa pre-trained language model and the Tf-Idf algorithm. In the final result ranking announced by the task organizer, our system obtained F1 scores of 0.93, 0.84, 0.59 on the English dataset, Malayalam dataset, and Tamil dataset. Our submission results are ranked 1, 2, and 3 respectively.
%U https://aclanthology.org/2021.ltedi-1.17/
%P 122-127

Markdown (Informal)

[TEAM HUB@LT-EDI-EACL2021: Hope Speech Detection Based On Pre-trained Language Model](https://aclanthology.org/2021.ltedi-1.17/) (Huang & Bai, LTEDI 2021)

• TEAM HUB@LT-EDI-EACL2021: Hope Speech Detection Based On Pre-trained Language Model (Huang & Bai, LTEDI 2021)

ACL

• Bo Huang and Yang Bai. 2021. TEAM HUB@LT-EDI-EACL2021: Hope Speech Detection Based On Pre-trained Language Model. In Proceedings of the First Workshop on Language Technology for Equality, Diversity and Inclusion, pages 122–127, Kyiv. Association for Computational Linguistics.