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How do you prepare a dataset to fine-tune an LLM, and why does data quality dominate?

Fine-tuning is mostly a data problem, not a hyperparameter one. The signal is naming what makes a good set (quality, diversity, format, dedup) and arguing why a few thousand clean examples beat a million noisy ones.

Updated Aug 2026 · Grounded in real Applied AI Engineer interview loops and written to a senior-engineer editorial bar.

Fine-tuning is mostly a data problem, not a hyperparameter one. The signal is naming what makes a good set (quality, diversity, format, dedup) and arguing why a few thousand clean examples beat a million noisy ones.

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