metadata
language: en
license: apache-2.0
datasets:
- bookcorpus
- wikipedia
DistilBERT base model (cased)
This model is a distilled version of the BERT base model. It was introduced in this paper. The code for the distillation process can be found here. This model is cased: it does make a difference between english and English.
All the training details on the pre-training, the uses, limitations and potential biases are the same as for DistilBERT-base-uncased. We highly encourage to check it if you want to know more.
Evaluation results
When fine-tuned on downstream tasks, this model achieves the following results:
Glue test results:
| Task | MNLI | QQP | QNLI | SST-2 | CoLA | STS-B | MRPC | RTE |
|---|---|---|---|---|---|---|---|---|
| 81.5 | 87.8 | 88.2 | 90.4 | 47.2 | 85.5 | 85.6 | 60.6 |
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}
}