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Consequences of Unfiltered Training Data
A development team is building a large language model and has access to a massive corpus of unfiltered text from the internet. Explain two distinct potential negative impacts on the final model's performance and reliability if they use this data directly for training without any processing.
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Ch.2 Generative Models - Foundations of Large Language Models
Foundations of Large Language Models
Foundations of Large Language Models Course
Computing Sciences
Analysis in Bloom's Taxonomy
Cognitive Psychology
Psychology
Social Science
Empirical Science
Science
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A machine learning team is developing a new large-scale text-generating model. They must choose between two potential training datasets. Dataset A contains 5 terabytes of raw, unfiltered text scraped from a wide variety of public websites. Dataset B contains 1 terabyte of text that has been carefully curated, cleaned for errors, and filtered to remove undesirable content. Given that the primary goal is to create a reliable and high-performing model, which of the following is the most justifiable decision?
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Consequences of Unfiltered Training Data