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PhoBERT: Pre-trained language models for Vietnamese

About

We present PhoBERT with two versions, PhoBERT-base and PhoBERT-large, the first public large-scale monolingual language models pre-trained for Vietnamese. Experimental results show that PhoBERT consistently outperforms the recent best pre-trained multilingual model XLM-R (Conneau et al., 2020) and improves the state-of-the-art in multiple Vietnamese-specific NLP tasks including Part-of-speech tagging, Dependency parsing, Named-entity recognition and Natural language inference. We release PhoBERT to facilitate future research and downstream applications for Vietnamese NLP. Our PhoBERT models are available at https://github.com/VinAIResearch/PhoBERT

Dat Quoc Nguyen, Anh Tuan Nguyen• 2020

Related benchmarks

TaskDatasetResultRank
Multiple-choice reading comprehensionViMMRC 2.0
Accuracy54.73
29
Natural Language InferenceViNLI
Accuracy80.67
17
Information RetrievalViWikiFC
Top-1 Accuracy76.69
12
Named Entity RecognitionPhoNER_COVID19 (test)
Micro-F194.5
11
Topic ClassificationUIT-VSFC (test)
Accuracy89.24
9
Toxic Speech DetectionViCTSD
Acc90.78
9
Hate Speech DetectionViHSD
Acc87.42
9
Sentiment ClassificationUIT-VSFC (test)
Accuracy94.1
9
Machine Reading ComprehensionUIT-ViQuAD 2.0
EM57.27
9
Hate Spans DetectionViHOS
Accuracy84.92
9
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