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--- |
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license: cc |
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task_categories: |
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- summarization |
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- feature-extraction |
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language: |
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- as |
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- bh |
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- bn |
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- en |
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- gu |
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- hi |
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- kn |
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- ml |
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- mr |
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- ne |
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- or |
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- pa |
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- ta |
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- te |
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- ur |
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pretty_name: varta |
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size_categories: |
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- 1B<n<10B |
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--- |
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## Dataset Description |
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- **Repository:** https://github.com/rahular/varta |
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- **Paper:** https://arxiv.org/abs/2305.05858 |
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### Dataset Summary |
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Varta is a diverse, challenging, large-scale, multilingual, and high-quality headline-generation dataset containing 41.8 million news articles in 14 Indic languages and English. |
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The data is crawled from DailyHunt, a popular news aggregator in India that pulls high-quality articles from multiple trusted and reputed news publishers. |
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### Languages |
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Assamese, Bhojpuri, Bengali, English, Gujarati, Hindi, Kannada, Malayalam, Marathi, Nepali, Oriya, Punjabi, Tamil, Telugu, and Urdu. |
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## Dataset Structure |
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### Data Fields |
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- id: unique identifier for the artilce on DailyHunt. This id will be used to recreate the dataset. |
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- langCode: ISO 639-1 language code |
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- source_url: the url that points to the article on the website of the original publisher |
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- dh_url: the url that points to the article on DailyHunt |
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- id: unique identifier for the artilce on DailyHunt. |
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- url: the url that points to the article on DailyHunt |
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- headline: headline of the article |
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- publication_date: date of publication |
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- text: main body of the article |
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- tags: main topics related to the article |
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- reactions: user likes, dislikes, etc. |
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- source_media: original publisher name |
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- source_url: the url that points to the article on the website of the original publisher |
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- word_count: number of words in the article |
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- langCode: language of the article |
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### Data Splits |
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From every language, we randomly sample 10,000 articles each for validation and testing. We also ensure that at least 80% of a language’s data is available for training. |
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Therefore, if a language has less than 100,000 articles, we restrict its validation and test splits to 10% of its size. |
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We also create a `small` training set by limiting the number of articles from each language to 100K. |
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This `small` training set with a size of 1.3M is used in all our fine-tuning experiments. |
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You can find the `small` training set [here](https://huggingface.co/datasets/rahular/varta/blob/main/varta/train/train_100k.json) |
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## Data Recreation |
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To recreate the dataset, follow this [README file](https://github.com/rahular/varta/tree/main/crawler#README.md). |
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## Misc |
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- Original source: https://m.dailyhunt.in/ |
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- License: CC-BY 4.0 |
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## Citation Information |
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``` |
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@misc{aralikatte2023varta, |
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title={V\=arta: A Large-Scale Headline-Generation Dataset for Indic Languages}, |
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author={Rahul Aralikatte and Ziling Cheng and Sumanth Doddapaneni and Jackie Chi Kit Cheung}, |
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year={2023}, |
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eprint={2305.05858}, |
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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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