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
- Editors:
- Jeremy Barnes, Orphée De Clercq, Valentin Barriere, Shabnam Tafreshi, Sawsan Alqahtani, João Sedoc, Roman Klinger, Alexandra Balahur
- 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
- 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)
- PDF:
- https://preview.aclanthology.org/ingest-2024-clasp/2022.wassa-1.25.pdf
- Data
- GoEmotions