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Upload dataset_infos.json
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dataset_infos.json
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{"emilylearning--cond_ft_none_on_reddit__prcnt_100__test_run_False__roberta-base": {
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"description": "\nThis corpus contains preprocessed posts from the Reddit dataset.\nThe dataset consists of 3,848,330 posts with an average length of 270 words for content,\nand 28 words for the summary.\n\nFeatures includes strings: author, body, normalizedBody, content, summary, subreddit, subreddit_id.\nContent is used as document and summary is used as summary.\n",
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"citation": "\n@inproceedings{volske-etal-2017-tl,\n title = {TL;DR: Mining {R}eddit to Learn Automatic Summarization},\n author = {V{\"o}lske, Michael and Potthast, Martin and Syed, Shahbaz and Stein, Benno},\n booktitle = {Proceedings of the Workshop on New Frontiers in Summarization},\n month = {sep},\n year = {2017},\n address = {Copenhagen, Denmark},\n publisher = {Association for Computational Linguistics},\n url = {https://www.aclweb.org/anthology/W17-4508},\n doi = {10.18653/v1/W17-4508},\n pages = {59--63},\n abstract = {Recent advances in automatic text summarization have used deep neural networks to generate high-quality abstractive summaries, but the performance of these models strongly depends on large amounts of suitable training data. We propose a new method for mining social media for author-provided summaries, taking advantage of the common practice of appending a {``}TL;DR{''} to long posts. A case study using a large Reddit crawl yields the Webis-TLDR-17 dataset, complementing existing corpora primarily from the news genre. Our technique is likely applicable to other social media sites and general web crawls.},\n}\n",
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"homepage": "https://github.com/webis-de/webis-tldr-17-corpus",
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"license": "",
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"features": {
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"input_ids": {
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"feature": {
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"dtype": "int32",
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"id": null,
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"_type": "Value"
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},
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"length": -1,
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"id": null,
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"_type": "Sequence"
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},
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"attention_mask": {
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"feature": {
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"dtype": "int8",
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"id": null,
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"_type": "Value"
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},
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"length": -1,
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"id": null,
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"_type": "Sequence"
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},
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"labels": {
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"feature": {
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"dtype": "int64",
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"id": null,
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"_type": "Value"
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},
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"length": -1,
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"id": null,
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"_type": "Sequence"
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}
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},
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"post_processed": null,
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"supervised_keys": null,
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"task_templates": null,
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"builder_name": "reddit",
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"config_name": "default",
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"version": {
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"version_str": "1.0.0",
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"description": null,
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"major": 1,
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"minor": 0,
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"patch": 0
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},
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"splits": {
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"train": {
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"name": "train",
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"num_bytes": 2933641908,
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"num_examples": 1750383,
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"dataset_name": "cond_ft_none_on_reddit__prcnt_100__test_run_False__roberta-base"
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}
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},
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"download_checksums": null,
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"download_size": 436172602,
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"post_processing_size": null,
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"dataset_size": 2933641908,
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"size_in_bytes": 3369814510
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}}
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