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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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- 100K<n<1M |
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task_categories: |
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- summarization |
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- text2text-generation |
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task_ids: [] |
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tags: |
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- conditional-text-generation |
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--- |
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|
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# MediaSum dataset for summarization |
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Summarization dataset copied from [MediaSum: A Large-scale Media Interview Dataset for Dialogue Summarization](https://github.com/zcgzcgzcg1/MediaSum) |
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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/mediasum": ("document", "summary") |
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``` |
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# Configs |
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4 possibles configs: |
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- `roberta` will concatenate documents with "\</s\>" |
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- `newline` will concatenate documents with "\n" |
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- `bert` will concatenate documents with "[SEP]" |
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- `list` will return the list of documents instead of a single string |
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Add `_prepended` to config name to prepend the speaker name before each dialogue: `speaker: text` \ |
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Default is `roberta_prepended` (compatible with BART). |
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### Data Fields |
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- `id`: paper id |
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- `document`: a string/list containing the body of a set of documents |
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- `summary`: a string containing the abstract of the set |
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### Data Splits |
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This dataset has 3 splits: _train_, _validation_, and _test_. \ |
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| Dataset Split | Number of Instances | |
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| ------------- | --------------------| |
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| Train | 443596 | |
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| Validation | 10000 | |
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| Test | 10000 | |
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# Cite original article |
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``` |
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@article{zhu2021mediasum, |
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title={MediaSum: A Large-scale Media Interview Dataset for Dialogue Summarization}, |
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author={Zhu, Chenguang and Liu, Yang and Mei, Jie and Zeng, Michael}, |
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journal={arXiv preprint arXiv:2103.06410}, |
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year={2021} |
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} |
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``` |
