CroissantLLM: A Truly Bilingual French-English Language Model - Machine Learning and Information Access
Preprints, Working Papers, ... Year : 2024

CroissantLLM: A Truly Bilingual French-English Language Model

Antonio Loison
  • Function : Author
Caio Corro
François Yvon

Abstract

We introduce CroissantLLM, a 1.3B language model pretrained on a set of 3T English and French tokens, to bring to the research and industrial community a high-performance, fully open-sourced bilingual model that runs swiftly on consumer-grade local hardware. To that end, we pioneer the approach of training an intrinsically bilingual model with a 1:1 English-to-French pretraining data ratio, a custom tokenizer, and bilingual finetuning datasets. We release the training dataset, notably containing a French split with manually curated, high-quality, and varied data sources. To assess performance outside of English, we craft a novel benchmark, FrenchBench, consisting of an array of classification and generation tasks, covering various orthogonal aspects of model performance in the French Language. Additionally, rooted in transparency and to foster further Large Language Model research, we release codebases, and dozens of checkpoints across various model sizes, training data distributions, and training steps, as well as fine-tuned Chat models, and strong translation models. We evaluate our model through the FMTI framework, and validate 81 % of the transparency criteria, far beyond the scores of even most open initiatives. This work enriches the NLP landscape, breaking away from previous English-centric work in order to strengthen our understanding of multilinguality in language models.
Fichier principal
Vignette du fichier
2402.00786v4.pdf (1.78 Mo) Télécharger le fichier
Origin Files produced by the author(s)

Dates and versions

hal-04574908 , version 1 (14-05-2024)

Identifiers

Cite

Manuel Faysse, Patrick Fernandes, Nuno Guerreiro, Antonio Loison, Duarte Alves, et al.. CroissantLLM: A Truly Bilingual French-English Language Model. 2024. ⟨hal-04574908⟩
48 View
91 Download

Altmetric

Share

More