Abstract
Detecting emotions in languages is important to accomplish a complete interaction between humans and machines. This paper describes our contribution to the WASSA 2022 shared task which handles this crucial task of emotion detection. We have to identify the following emotions: sadness, surprise, neutral, anger, fear, disgust, joy based on a given essay text. We are using an ensemble of ELECTRA and BERT models to tackle this problem achieving an F1 score of 62.76%. Our codebase 1 and our WandB project2 is publicly available.
Cite
CITATION STYLE
Kane, A., Patankar, S., Khose, S., & Kirtane, N. (2022). Transformer based ensemble for emotion detection. In WASSA 2022 - 12th Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis, Proceedings of the Workshop (pp. 250–254). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/2022.wassa-1.25
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