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        <title>MSR India at SemEval-2020 Task 9: Multilingual Models Can Do Code-Mixing Too</title>
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    <abstract>In this paper, we present our system for the SemEval 2020 task on code-mixed sentiment analysis. Our system makes use of large transformer based multilingual embeddings like mBERT. Recent work has shown that these models posses the ability to solve code-mixed tasks in addition to their originally demonstrated cross-lingual abilities. We evaluate the stock versions of these models for the sentiment analysis task and also show that their performance can be improved by using unlabelled code-mixed data. Our submission (username Genius1237) achieved the second rank on the English-Hindi subtask with an F1 score of 0.726.</abstract>
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%0 Conference Proceedings
%T MSR India at SemEval-2020 Task 9: Multilingual Models Can Do Code-Mixing Too
%A Srinivasan, Anirudh
%Y Herbelot, Aurelie
%Y Zhu, Xiaodan
%Y Palmer, Alexis
%Y Schneider, Nathan
%Y May, Jonathan
%Y Shutova, Ekaterina
%S Proceedings of the Fourteenth Workshop on Semantic Evaluation
%D 2020
%8 December
%I International Committee for Computational Linguistics
%C Barcelona (online)
%F srinivasan-2020-msr
%X In this paper, we present our system for the SemEval 2020 task on code-mixed sentiment analysis. Our system makes use of large transformer based multilingual embeddings like mBERT. Recent work has shown that these models posses the ability to solve code-mixed tasks in addition to their originally demonstrated cross-lingual abilities. We evaluate the stock versions of these models for the sentiment analysis task and also show that their performance can be improved by using unlabelled code-mixed data. Our submission (username Genius1237) achieved the second rank on the English-Hindi subtask with an F1 score of 0.726.
%R 10.18653/v1/2020.semeval-1.122
%U https://aclanthology.org/2020.semeval-1.122
%U https://doi.org/10.18653/v1/2020.semeval-1.122
%P 951-956

Markdown (Informal)

[MSR India at SemEval-2020 Task 9: Multilingual Models Can Do Code-Mixing Too](https://aclanthology.org/2020.semeval-1.122) (Srinivasan, SemEval 2020)

• MSR India at SemEval-2020 Task 9: Multilingual Models Can Do Code-Mixing Too (Srinivasan, SemEval 2020)

ACL

• Anirudh Srinivasan. 2020. MSR India at SemEval-2020 Task 9: Multilingual Models Can Do Code-Mixing Too. In Proceedings of the Fourteenth Workshop on Semantic Evaluation, pages 951–956, Barcelona (online). International Committee for Computational Linguistics.