Interpret dataset-size and quality signals before launching a supervised fine-tuning job.
Use the gauge to judge whether the dataset is ready for a supervised fine-tuning experiment. Fine-tuning dataset readiness Not enough to launch Eight examples cannot meet the minimum training threshold. 8 examples Minimum valid dry run OpenAI SFT training requires at least ten examples. 10 examples First serious experiment Dozens of reviewed examples make behavior change measurable. 50 examples Quality gate Every training row needs a realistic input and ideal output. 100% reviewed Width shows readiness signal strength for a first supervised fine-tuning experiment. The team has eight examples, no validation set, and inconsistent ideal answers. What is the best…
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