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--- |
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language: |
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- en |
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multilinguality: |
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- monolingual |
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size_categories: |
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- 10K<n<100K |
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task_categories: |
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- text-generation |
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task_ids: |
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- summarization |
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tags: |
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- conditional-text-generation |
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--- |
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# GovReport dataset for summarization |
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Dataset for summarization of long documents.\ |
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Adapted from this [repo](https://github.com/luyang-huang96/LongDocSum) and this [paper](https://arxiv.org/pdf/2104.02112.pdf)\ |
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This dataset is compatible with the [`run_summarization.py`](https://github.com/huggingface/transformers/tree/master/examples/pytorch/summarization) script from Transformers if you add this line to the `summarization_name_mapping` variable: |
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```python |
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"ccdv/govreport-summarization": ("report", "summary") |
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``` |
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### Data Fields |
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- `id`: paper id |
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- `report`: a string containing the body of the report |
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- `summary`: a string containing the summary of the report |
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### Data Splits |
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This dataset has 3 splits: _train_, _validation_, and _test_. \ |
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Token counts with a RoBERTa tokenizer. |
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| Dataset Split | Number of Instances | Avg. tokens | |
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| ------------- | --------------------|:----------------------| |
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| Train | 17,517 | < 9,000 / < 500 | |
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| Validation | 973 | < 9,000 / < 500 | |
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| Test | 973 | < 9,000 / < 500 | |
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# Cite original article |
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``` |
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@misc{huang2021efficient, |
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title={Efficient Attentions for Long Document Summarization}, |
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author={Luyang Huang and Shuyang Cao and Nikolaus Parulian and Heng Ji and Lu Wang}, |
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year={2021}, |
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eprint={2104.02112}, |
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archivePrefix={arXiv}, |
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primaryClass={cs.CL} |
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} |
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``` |
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