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--- |
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language: multilingual |
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license: apache-2.0 |
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datasets: |
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- wikipedia |
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--- |
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# DistilBERT base multilingual model (cased) |
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This model is a distilled version of the [BERT base multilingual model](bert-base-multilingual-cased). The code for the distillation process can be found |
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[here](https://github.com/huggingface/transformers/tree/master/examples/distillation). This model is cased: it does make a difference between english and English. |
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The model is trained on the concatenation of Wikipedia in 104 different languages listed [here](https://github.com/google-research/bert/blob/master/multilingual.md#list-of-languages). |
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The model has 6 layers, 768 dimension and 12 heads, totalizing 134M parameters (compared to 177M parameters for mBERT-base). |
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On average DistilmBERT is twice as fast as mBERT-base. |
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We encourage to check [BERT base multilingual model](bert-base-multilingual-cased) to know more about usage, limitations and potential biases. |
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| Model | English | Spanish | Chinese | German | Arabic | Urdu | |
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| :---: | :---: | :---: | :---: | :---: | :---: | :---:| |
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| mBERT base cased (computed) | 82.1 | 74.6 | 69.1 | 72.3 | 66.4 | 58.5 | |
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| mBERT base uncased (reported)| 81.4 | 74.3 | 63.8 | 70.5 | 62.1 | 58.3 | |
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| DistilmBERT | 78.2 | 69.1 | 64.0 | 66.3 | 59.1 | 54.7 | |
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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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