annotations_creators:
- machine-generated
language:
- en
language_creators:
- found
license:
- mit
multilinguality:
- monolingual
pretty_name: pile-detoxify
size_categories:
- 1M<n<10M
source_datasets:
- extended|the_pile
tags:
- toxicity
- pretraining-with-human-feedback
task_categories:
- text-classification
- other
task_ids:
- acceptability-classification
- hate-speech-detection
- text-scoring
Dataset Card for pile-pii-scrubadub
Dataset Description
- Repository: https://github.com/tomekkorbak/aligned-pretraining-objectives
- Paper: Arxiv link to be added
Dataset Summary
This dataset contains text from The Pile, annotated based on the toxicity of each sentence. Each document (row in the dataset) is segmented into sentences, and each sentence is given a score: the toxicity predicted by the Detoxify.
Supported Tasks and Leaderboards
[More Information Needed]
Languages
This dataset is taken from The Pile, which is English text.
Dataset Structure
Data Instances
1949977
Data Fields
- texts (sequence): a list of the sentences in the document, segmented using SpaCy
- meta (dict): the section of The Pile from which it originated
- scores (sequence): a score for each sentence in the
textscolumn indicating the toxicity predicted by Detoxify - avg_score (float64): the average of the scores listed in the
scorescolumn - num_sents (int64): the number of sentences (and scores) in that document
Data Splits
Training set only
Dataset Creation
Curation Rationale
This is labeled text from The Pile, a large dataset of text in English. The text is scored for toxicity so that generative language models can be trained to avoid generating toxic text.
Source Data
Initial Data Collection and Normalization
This is labeled text from The Pile.
Who are the source language producers?
Please see The Pile for the source of the dataset.
Annotations
Annotation process
Each sentence was scored using Detoxify, which is a toxic comment classifier.
We used the unbiased model which is based on the 124M parameter RoBERTa and trained on the Jigsaw Unintended Bias in Toxicity Classification dataset.
Who are the annotators?
Personal and Sensitive Information
This dataset contains all personal identifable information and toxic text that was originally contained in The Pile.
Considerations for Using the Data
Social Impact of Dataset
This dataset contains examples of toxic text and personal identifiable information. (A version of this datatset with personal identifiable information annotated is available here.) Please take care to avoid misusing the toxic text or putting anybody in danger by publicizing their information. This dataset is intended for research purposes only. We cannot guarantee that all toxic text has been detected, and we cannot guarantee that models trained using it will avoid generating toxic text. We do not recommend deploying models trained on this data.
Discussion of Biases
This dataset contains all biases from The Pile discussed in their paper: https://arxiv.org/abs/2101.00027
Other Known Limitations
The toxic text in this dataset was detected using imperfect automated detection methods. We cannot guarantee that the labels are 100% accurate.
Additional Information
Dataset Curators
Licensing Information
From The Pile: PubMed Central: MIT License
Citation Information
Paper information to be added