Metadata Might Make Language Models Better

• URL: http://arxiv.org/abs/2211.10086v1
• Date: Fri, 18 Nov 2022 08:29:00 GMT
• Title: Metadata Might Make Language Models Better
• Authors: Kaspar Beelen and Daniel van Strien
• Abstract summary: Using 19th-century newspapers as a case study, we compare different strategies for inserting temporal, political and geographical information into a Masked Language Model. We find that showing relevant metadata to a language model has a beneficial impact and may even produce more robust and fairer models.
• Score: 1.7100280218774935
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: This paper discusses the benefits of including metadata when training language models on historical collections. Using 19th-century newspapers as a case study, we extend the time-masking approach proposed by Rosin et al., 2022 and compare different strategies for inserting temporal, political and geographical information into a Masked Language Model. After fine-tuning several DistilBERT on enhanced input data, we provide a systematic evaluation of these models on a set of evaluation tasks: pseudo-perplexity, metadata mask-filling and supervised classification. We find that showing relevant metadata to a language model has a beneficial impact and may even produce more robust and fairer models.

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