51 lines
1.8 KiB
Markdown
51 lines
1.8 KiB
Markdown
---
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language: en
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tags:
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- exbert
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license: apache-2.0
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datasets:
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- openwebtext
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---
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# DistilRoBERTa base model
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This model is a distilled version of the [RoBERTa-base model](https://huggingface.co/roberta-base). It follows the same training procedure as [DistilBERT](https://huggingface.co/distilbert-base-uncased).
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The code for the distillation process can be found [here](https://github.com/huggingface/transformers/tree/master/examples/distillation).
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This model is case-sensitive: it makes a difference between english and English.
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The model has 6 layers, 768 dimension and 12 heads, totalizing 82M parameters (compared to 125M parameters for RoBERTa-base).
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On average DistilRoBERTa is twice as fast as Roberta-base.
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We encourage to check [RoBERTa-base model](https://huggingface.co/roberta-base) to know more about usage, limitations and potential biases.
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## Training data
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DistilRoBERTa was pre-trained on [OpenWebTextCorpus](https://skylion007.github.io/OpenWebTextCorpus/), a reproduction of OpenAI's WebText dataset (it is ~4 times less training data than the teacher RoBERTa).
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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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| | 84.0 | 89.4 | 90.8 | 92.5 | 59.3 | 88.3 | 86.6 | 67.9 |
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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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<a href="https://huggingface.co/exbert/?model=distilroberta-base">
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<img width="300px" src="https://cdn-media.huggingface.co/exbert/button.png">
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</a>
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