ViSoBERT: A Pre-Trained Language Model for Vietnamese Social Media Text Processing

• URL: http://arxiv.org/abs/2310.11166v2
• Date: Sat, 28 Oct 2023 16:22:19 GMT
• Title: ViSoBERT: A Pre-Trained Language Model for Vietnamese Social Media Text Processing
• Authors: Quoc-Nam Nguyen, Thang Chau Phan, Duc-Vu Nguyen, Kiet Van Nguyen
• Abstract summary: We present the first monolingual pre-trained language model for Vietnamese social media texts, ViSoBERT. Our experiments demonstrate that ViSoBERT, with far fewer parameters, surpasses the previous state-of-the-art models on multiple Vietnamese social media tasks.
• Score: 1.1765925931670576
• License: http://creativecommons.org/licenses/by-nc-sa/4.0/
• Abstract: English and Chinese, known as resource-rich languages, have witnessed the strong development of transformer-based language models for natural language processing tasks. Although Vietnam has approximately 100M people speaking Vietnamese, several pre-trained models, e.g., PhoBERT, ViBERT, and vELECTRA, performed well on general Vietnamese NLP tasks, including POS tagging and named entity recognition. These pre-trained language models are still limited to Vietnamese social media tasks. In this paper, we present the first monolingual pre-trained language model for Vietnamese social media texts, ViSoBERT, which is pre-trained on a large-scale corpus of high-quality and diverse Vietnamese social media texts using XLM-R architecture. Moreover, we explored our pre-trained model on five important natural language downstream tasks on Vietnamese social media texts: emotion recognition, hate speech detection, sentiment analysis, spam reviews detection, and hate speech spans detection. Our experiments demonstrate that ViSoBERT, with far fewer parameters, surpasses the previous state-of-the-art models on multiple Vietnamese social media tasks. Our ViSoBERT model is available only for research purposes.

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