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arXiv · 2305.04673

PreCog: Exploring the Relation between Memorization and Performance in Pre-trained Language Models

Leonardo Ranaldi·Elena Sofia Ruzzetti·Fabio Massimo Zanzotto
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Abstract

Pre-trained Language Models such as BERT are impressive machines with the ability to memorize, possibly generalized learning examples. We present here a small, focused contribution to the analysis of the interplay between memorization and performance of BERT in downstream tasks. We propose PreCog, a measure for evaluating memorization from pre-training, and we analyze its correlation with the BERT's performance. Our experiments show that highly memorized examples are better classified, suggesting memorization is an essential key to success for BERT.

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Leonardo Ranaldi, Elena Sofia Ruzzetti, Fabio Massimo Zanzotto. 2023-05-08. PreCog: Exploring the Relation between Memorization and Performance in Pre-trained Language Models. https://doi.org/10.26615/978-954-452-092-2_103

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