Deep Learning Brasil - NLP at SemEval-2020 Task 9: Sentiment Analysis of Code-Mixed Tweets Using Ensemble of Language Models
Manoel Veríssimo dos Santos Neto, Ayrton Amaral, Nádia Silva, Anderson da Silva Soares
Abstract
In this paper, we describe a methodology to predict sentiment in code-mixed tweets (hindi-english). Our team called verissimo.manoel in CodaLab developed an approach based on an ensemble of four models (MultiFiT, BERT, ALBERT, and XLNET). The final classification algorithm was an ensemble of some predictions of all softmax values from these four models. This architecture was used and evaluated in the context of the SemEval 2020 challenge (task 9), and our system got 72.7% on the F1 score.- Anthology ID:
- 2020.semeval-1.164
- Volume:
- Proceedings of the Fourteenth Workshop on Semantic Evaluation
- Month:
- December
- Year:
- 2020
- Address:
- Barcelona (online)
- Editors:
- Aurelie Herbelot, Xiaodan Zhu, Alexis Palmer, Nathan Schneider, Jonathan May, Ekaterina Shutova
- Venue:
- SemEval
- SIG:
- SIGLEX
- Publisher:
- International Committee for Computational Linguistics
- Note:
- Pages:
- 1233–1238
- Language:
- URL:
- https://aclanthology.org/2020.semeval-1.164
- DOI:
- 10.18653/v1/2020.semeval-1.164
- Cite (ACL):
- Manoel Veríssimo dos Santos Neto, Ayrton Amaral, Nádia Silva, and Anderson da Silva Soares. 2020. Deep Learning Brasil - NLP at SemEval-2020 Task 9: Sentiment Analysis of Code-Mixed Tweets Using Ensemble of Language Models. In Proceedings of the Fourteenth Workshop on Semantic Evaluation, pages 1233–1238, Barcelona (online). International Committee for Computational Linguistics.
- Cite (Informal):
- Deep Learning Brasil - NLP at SemEval-2020 Task 9: Sentiment Analysis of Code-Mixed Tweets Using Ensemble of Language Models (Veríssimo dos Santos Neto et al., SemEval 2020)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-3/2020.semeval-1.164.pdf