Test sets

A test set is the ground truth for a training run. After fine-tuning, Luna Studio scores the resulting metric against the test set and reports F1, AUC-ROC, and other performance KPIs.

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What makes a good test set

• Human-labelled. Don’t auto-generate test labels — they’re the tape measure for evaluating the run.
• Representative of production data. Sample inputs from the same distribution your application sees in production.
• Size. Use at least 300 rows with min of 100 rows per label. Ideally, a good test set should be 1000-3000 rows.

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Required schema

Check the pre-requisites section for details

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File formats

• CSV — standard comma-separated. Headers required.
• JSONL — one JSON object per line, with input and label keys.

Both formats accept up to a few hundred MB. Larger uploads work but take longer to validate.

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Add a test set

You can add a test set in three places:

• The Datasets page → Add test set primary button.
• The Step 2 of the run creation flow → dropdown’s Add new test set action.
• (Indirectly) by importing from Galileo — see Galileo integration.

All three paths open the same Add test set modal — see Add a dataset for the modal reference.

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Where to go next