How can teams detect gaps in their training data?
They can analyze evaluation failures by topic, language, format, and user need, then inspect whether the dataset contains representative examples of those cases.
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More FAQs in How does the quality of training data affect an LLM’s performance?
No. Architecture, capacity, optimization, and available computation also constrain performance. Better data improves the learning opportunity but cannot guarantee success on every task.
No. A polished passage can be inaccurate, repetitive, irrelevant, or misleading. Quality must be assessed against the training objective and intended application.
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