title: Fietje: An open, efficient LLM for Dutch
summary: This paper introduces Fietje, a family of small language models (SLMs)
  specifically designed for the Dutch language. The model is based on Phi 2, an
  English-centric model of 2.7 billion parameters. Fietje demonstrated
  competitive results with larger language models upon its release. A core
  emphasis of this work is transparency and reproducibility: Fietje is fully
  open-source, with model weights, datasets, training, and evaluation code all
  publicly accessible.
    The paper discusses the performance of Fietje and many other models on an
  extensive evaluation suite of benchmarks on reasoning, sentiment analysis,
  world knowledge, linguistic acceptability and word sense disambiguation.
  Evaluation results illustrate the rapid progress in the field of LLMs, where
  recent small models outperform older, larger models that were fine-tuned for
  Dutch. This trend signals an exciting future for Dutch language processing,
  suggesting that even compact LLMs are becoming increasingly capable.
  Furthermore, ongoing and future efforts to adapt LLMs to Dutch are poised to
  enhance these models even further, broadening their applicability and
  accessibility. Fietje is only an intermediate step in improving accessibility
  to language technology for users of the Dutch language.
paper_authors._id: 676911953727573d69c04ad6
paper_authors.name: Bram Vanroy
paper_authors.status: extracted_confirmed
paper_authors.statusLastChangedAt: 2024-12-23T09:14:08.298Z
paper_authors._id: 5e1e17b6fcf41d740b6996a8
paper_authors.avatarUrl: https://cdn-avatars.huggingface.co/v1/production/uploads/1594192845975-5e1e17b6fcf41d740b6996a8.jpeg
paper_authors.fullname: Bram Vanroy
paper_authors.type: user
paper_authors.user: BramVanroy
paper_title: Fietje: An open, efficient LLM for Dutch
paper_summary: This paper introduces Fietje, a family of small language models (SLMs)
  specifically designed for the Dutch language. The model is based on Phi 2, an
  English-centric model of 2.7 billion parameters. Fietje demonstrated
  competitive results with larger language models upon its release. A core
  emphasis of this work is transparency and reproducibility: Fietje is fully
  open-source, with model weights, datasets, training, and evaluation code all
  publicly accessible.
    The paper discusses the performance of Fietje and many other models on an
  extensive evaluation suite of benchmarks on reasoning, sentiment analysis,
  world knowledge, linguistic acceptability and word sense disambiguation.
  Evaluation results illustrate the rapid progress in the field of LLMs, where
  recent small models outperform older, larger models that were fine-tuned for
  Dutch. This trend signals an exciting future for Dutch language processing,
  suggesting that even compact LLMs are becoming increasingly capable.
  Furthermore, ongoing and future efforts to adapt LLMs to Dutch are poised to
  enhance these models even further, broadening their applicability and
  accessibility. Fietje is only an intermediate step in improving accessibility
  to language technology for users of the Dutch language.
paper_ai_summary: Fietje, a family of small language models for Dutch based on Phi 2, demonstrates competitive performance on various benchmark tasks, showcasing the potential of compact models in Dutch language processing.
paper_ai_keywords: language models small language models PhI 2 reasoning sentiment analysis world knowledge linguistic acceptability word sense disambiguation LLMs fine-tuning