metadata
language: multilingual
license: apache-2.0
datasets:
- wikipedia
DistilBERT base multilingual model (cased)
This model is a distilled version of the BERT base multilingual model. The code for the distillation process can be found here. This model is cased: it does make a difference between english and English.
The model is trained on the concatenation of Wikipedia in 104 different languages listed here. The model has 6 layers, 768 dimension and 12 heads, totalizing 134M parameters (compared to 177M parameters for mBERT-base). On average DistilmBERT is twice as fast as mBERT-base.
We encourage to check BERT base multilingual model to know more about usage, limitations and potential biases.
Model | English | Spanish | Chinese | German | Arabic | Urdu |
---|---|---|---|---|---|---|
mBERT base cased (computed) | 82.1 | 74.6 | 69.1 | 72.3 | 66.4 | 58.5 |
mBERT base uncased (reported) | 81.4 | 74.3 | 63.8 | 70.5 | 62.1 | 58.3 |
DistilmBERT | 78.2 | 69.1 | 64.0 | 66.3 | 59.1 | 54.7 |
BibTeX entry and citation info
@article{Sanh2019DistilBERTAD,
title={DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighter},
author={Victor Sanh and Lysandre Debut and Julien Chaumond and Thomas Wolf},
journal={ArXiv},
year={2019},
volume={abs/1910.01108}
}