Transformer based ensemble for emotion detection

Aditya Kane, Shantanu Patankar, Sahil Khose, Neeraja Kirtane


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 (https://bit.ly/WASSA_shared_task) and our WandB project (https://wandb.ai/acl_wassa_pictxmanipal/acl_wassa) is publicly available.
Anthology ID:
2022.wassa-1.25
Volume:
Proceedings of the 12th Workshop on Computational Approaches to Subjectivity, Sentiment & Social Media Analysis
Month:
May
Year:
2022
Address:
Dublin, Ireland
Venue:
WASSA
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
250–254
Language:
URL:
https://aclanthology.org/2022.wassa-1.25
DOI:
10.18653/v1/2022.wassa-1.25
Bibkey:
Cite (ACL):
Aditya Kane, Shantanu Patankar, Sahil Khose, and Neeraja Kirtane. 2022. Transformer based ensemble for emotion detection. In Proceedings of the 12th Workshop on Computational Approaches to Subjectivity, Sentiment & Social Media Analysis, pages 250–254, Dublin, Ireland. Association for Computational Linguistics.
Cite (Informal):
Transformer based ensemble for emotion detection (Kane et al., WASSA 2022)
Copy Citation:
PDF:
https://aclanthology.org/2022.wassa-1.25.pdf
Video:
 https://aclanthology.org/2022.wassa-1.25.mp4
Data
GoEmotions