license: mit
language: fr
library_name: transformers
pipeline_tag: feature-extraction
datasets:
- uonlp/CulturaX
- oscar
- almanach/HALvest
- wikimedia/wikipedia
tags:
- deberta-v2
- deberta-v3
- debertav2
- debertav3
- camembert
CamemBERT(a)-v2: A Smarter French Language Model Aged to Perfection
CamemBERTav2 is a French language model pretrained on a large corpus of 275B tokens of French text. It is the second version of the CamemBERTa model, which is based on the DebertaV2 architecture. CamemBERTav2 is trained using the Replaced Token Detection (RTD) objective with 20% mask rate on 275B tokens on 32 H100 GPUs. The dataset used for training is a combination of French OSCAR dumps from the CulturaX Project, French scientific documents from HALvest, and the French Wikipedia.
The model is a drop-in replacement for the original CamemBERTa model. Note that the new tokenizer is different from the original CamemBERTa tokenizer, so you will need to use Fast Tokenizers to use the model. It will work with DebertaV2TokenizerFast from transformers library even if the original DebertaV2TokenizerFast was sentencepiece-based.
Model Checkpoints
This repository contains all intermediate model checkpoints with corresponding checkpoints in TF and PT structured as follows:
├── checkpoints/
│ ├── iter_ckpt_rank_XX/ # Contains all iterator checkpoints from a specific rank
│ ├── summaries/ # Tensorboard logs
│ ├── ckpt-YYYYY.data-00000-of-00001
│ ├── ckpt-YYYYY.index
├── post/
│ ├── ckpt-YYYYY/
│ │ ├── pt/
│ │ │ ├── discriminator/
│ │ │ │ ├── config.json
│ │ │ │ ├── pytorch_model.bin
│ │ │ │ ├── special_tokens_map.json
│ │ │ │ ├── tokenizer.json
│ │ │ │ ├── tokenizer_config.json
│ │ │ ├── generator/
│ │ │ │ ├── ...
│ │ ├── tf/
│ │ │ ├── ...
Citation
@misc{antoun2024camembert20smarterfrench,
title={CamemBERT 2.0: A Smarter French Language Model Aged to Perfection},
author={Wissam Antoun and Francis Kulumba and Rian Touchent and Éric de la Clergerie and Benoît Sagot and Djamé Seddah},
year={2024},
eprint={2411.08868},
archivePrefix={arXiv},
primaryClass={cs.CL},
url={https://arxiv.org/abs/2411.08868},
}