Datasets:
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---
language:
- en
multilinguality:
- monolingual
size_categories:
- 10K<n<100K
task_categories:
- summarization
- text-generation
task_ids: []
tags:
- conditional-text-generation
dataset_info:
config_name: document
features:
- name: report
dtype: string
- name: summary
dtype: string
splits:
- name: train
num_bytes: 953321013
num_examples: 17517
- name: validation
num_bytes: 55820431
num_examples: 973
- name: test
num_bytes: 51591123
num_examples: 973
download_size: 506610432
dataset_size: 1060732567
configs:
- config_name: document
data_files:
- split: train
path: document/train-*
- split: validation
path: document/validation-*
- split: test
path: document/test-*
default: true
---
# GovReport dataset for summarization
Dataset for summarization of long documents.\
Adapted from this [repo](https://github.com/luyang-huang96/LongDocSum) and this [paper](https://arxiv.org/pdf/2104.02112.pdf)\
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:
```python
"ccdv/govreport-summarization": ("report", "summary")
```
### Data Fields
- `id`: paper id
- `report`: a string containing the body of the report
- `summary`: a string containing the summary of the report
### Data Splits
This dataset has 3 splits: _train_, _validation_, and _test_. \
Token counts with a RoBERTa tokenizer.
| Dataset Split | Number of Instances | Avg. tokens |
| ------------- | --------------------|:----------------------|
| Train | 17,517 | < 9,000 / < 500 |
| Validation | 973 | < 9,000 / < 500 |
| Test | 973 | < 9,000 / < 500 |
# Cite original article
```
@misc{huang2021efficient,
title={Efficient Attentions for Long Document Summarization},
author={Luyang Huang and Shuyang Cao and Nikolaus Parulian and Heng Ji and Lu Wang},
year={2021},
eprint={2104.02112},
archivePrefix={arXiv},
primaryClass={cs.CL}
}
```
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