princeton-nlp
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README.md
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@@ -22,4 +22,5 @@ Instead, compute the quality ratings for windows of up to 512 token and average
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In the paper, we document various types of bias that are present in the quality ratings from the QuRater model (biases related to domains, topics, social roles, regions and languages - see Section 6 of the paper).
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Hence, be aware that data selection with QuRating could have unintended and harmful effects on the language model that is being trained.
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We strongly recommend a comprehensive evaluation of the language model for these and other types of bias, particularly before real-world deployment.
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We hope that releasing the data/models can facilitate future research aimed at uncovering and mitigating such biases.
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In the paper, we document various types of bias that are present in the quality ratings from the QuRater model (biases related to domains, topics, social roles, regions and languages - see Section 6 of the paper).
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Hence, be aware that data selection with QuRating could have unintended and harmful effects on the language model that is being trained.
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We strongly recommend a comprehensive evaluation of the language model for these and other types of bias, particularly before real-world deployment.
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We hope that releasing the data/models can facilitate future research aimed at uncovering and mitigating such biases.
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Note that the quality ratings do not measure the social or literary value of a text and should *not* be used for textual or demographic studies.
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