Modelling Sentiment Analysis: LLMs and data augmentation techniques
Autor: | Prades, Guillem Senabre |
---|---|
Rok vydání: | 2023 |
Předmět: | |
Druh dokumentu: | Working Paper |
Popis: | This paper provides different approaches for a binary sentiment classification on a small training dataset. LLMs that provided state-of-the-art results in sentiment analysis and similar domains are being used, such as BERT, RoBERTa and XLNet. Comment: 4 pages. For more information check the github link in the conclusion. Enjoy! |
Databáze: | arXiv |
Externí odkaz: |