BERTje: A Dutch BERT Model
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Abstract (arXiv)
The transformer-based pre-trained language model BERT has helped to improve state-of-the-art performance on many natural language processing (NLP) tasks. Using the same architecture and parameters, we developed and evaluated a monolingual Dutch BERT model called BERTje. Compared to the multilingual BERT model, which includes Dutch but is only based on Wikipedia text, BERTje is based on a large and diverse dataset of 2.4 billion tokens. BERTje consistently outperforms the equally-sized multilingual BERT model on downstream NLP tasks (part-of-speech tagging, named-entity recognition, semantic role labeling, and sentiment analysis). Our pre-trained Dutch BERT model is made available at https://github.com/wietsedv/bertje.
Key facts. Cited by 109 papers in the map (data through 7 Oct 2026). First posted on arXiv 19 Dec 2019.
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Citing papers per year: 2021: 36; 2022: 22; 2023: 19; 2024: 16; 2025: 10; 2026: 6.
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- 2026From Values to Benchmarks: Evaluating Large Language Models for Governmental Use in Dutch10 Aug 2026
- 2026The Word and the Way: Strategies for Domain-Specific BERT Pre-Training in German Medical NLP2 Jun 2026
- 2026Finding Meaning in Embeddings: Concept Separation Curves23 Apr 2026
- 2026Differentially Private De-identification of Dutch Clinical Notes: A Comparative Evaluation23 Apr 2026
- 2025Multilingual BERT language model for medical tasks: Evaluation on domain-specific adaptation and cross-linguality31 Oct 2025
- 2025Automated HIV Screening on Dutch Electronic Health Records with Large Language Models22 Oct 2025
- 2025MTEB-NL and E5-NL: Embedding Benchmark and Models for Dutch15 Sep 2025
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