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--- |
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language: en |
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license: apache-2.0 |
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datasets: |
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- bookcorpus |
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- wikipedia |
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--- |
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# DistilBERT base model (cased) |
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This model is a distilled version of the [BERT base model](https://huggingface.co/bert-base-cased). |
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It was introduced in [this paper](https://arxiv.org/abs/1910.01108). |
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The code for the distillation process can be found |
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[here](https://github.com/huggingface/transformers/tree/master/examples/distillation). |
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This model is cased: it does make a difference between english and English. |
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All the training details on the pre-training, the uses, limitations and potential biases are the same as for [DistilBERT-base-uncased](https://huggingface.co/distilbert-base-uncased). |
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We highly encourage to check it if you want to know more. |
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## Evaluation results |
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When fine-tuned on downstream tasks, this model achieves the following results: |
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Glue test results: |
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| Task | MNLI | QQP | QNLI | SST-2 | CoLA | STS-B | MRPC | RTE | |
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|:----:|:----:|:----:|:----:|:-----:|:----:|:-----:|:----:|:----:| |
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| | 81.5 | 87.8 | 88.2 | 90.4 | 47.2 | 85.5 | 85.6 | 60.6 | |
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### BibTeX entry and citation info |
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```bibtex |
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@article{Sanh2019DistilBERTAD, |
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title={DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighter}, |
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author={Victor Sanh and Lysandre Debut and Julien Chaumond and Thomas Wolf}, |
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journal={ArXiv}, |
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year={2019}, |
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volume={abs/1910.01108} |
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} |
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``` |
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