Sentiment Analysis using DistilBERT


Ng, Song Yi and Lim, Kian Ming and Lee, Chin Poo and Lim, Jit Yan (2023) Sentiment Analysis using DistilBERT. In: 2023 IEEE 11th Conference on Systems, Process & Control (ICSPC), 16-16 December 2023, Malacca, Malaysia.

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Transformers is an architecture that performs well in NLP task. To understand and improve its performance on sentiment analysis, DistilBERT is employed as the base model. Sentiment analysis is a process that extracts subjective information from textual data and categorizes them into different classes. The classification classes may include polarity (positive, neutral, negative) or emotions (happy, sad, angry). In addition, multiple techniques such as fine tuning, regularization and hyperparameter tuning are applied to improve the performance of the model. The proposed solution acquired an accuracy score of 85.41% on Internet Movie Database (IMDB) dataset and 86.59% on Customer Reviews (CR) dataset.

Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: Sentiment Analysis, DistilBERT, Deep Learning, Transformers
Subjects: Q Science > QA Mathematics > QA71-90 Instruments and machines > QA75.5-76.95 Electronic computers. Computer science
Divisions: Faculty of Information Science and Technology (FIST)
Depositing User: Ms Nurul Iqtiani Ahmad
Date Deposited: 27 Mar 2024 03:11
Last Modified: 27 Mar 2024 03:11


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