# 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}
}