{"query":"Training Datasets and Coverage","corpusVersion":"local","generatedAt":"2026-11-02T06:32:27.903Z","results":[{"blockId":"weights-training.datasets#training-datasets-and-coverage","pageId":"weights-training.datasets","title":"Training Datasets and Coverage","pageTitle":"Training Datasets and Coverage","url":"https://teammately.ai/docs/weights-training/datasets.md","humanUrl":"https://teammately.ai/docs/weights-training/datasets#training-datasets-and-coverage","markdownUrl":"https://teammately.ai/docs/weights-training/datasets.md","sectionId":"training-datasets-and-coverage","kind":"task","productArea":"weights_training","score":2277.5181926263044,"reasons":["search_match","title_match","term_match","prefix_or_fuzzy_match"],"markdown":"# Training Datasets and Coverage\n\nInspect the dataset before exporting or training. Generation completion does not establish realistic examples, balanced coverage or useful learned behavior."},{"blockId":"weights-training.datasets#inspect-coverage","pageId":"weights-training.datasets","title":"Inspect Coverage","pageTitle":"Training Datasets and Coverage","url":"https://teammately.ai/docs/weights-training/datasets.md","humanUrl":"https://teammately.ai/docs/weights-training/datasets#inspect-coverage","markdownUrl":"https://teammately.ai/docs/weights-training/datasets.md","sectionId":"inspect-coverage","kind":"task","productArea":"weights_training","score":1402.3162254439774,"reasons":["search_match","page_title_match","term_match","prefix_or_fuzzy_match"],"markdown":"## Inspect Coverage\n\nCoverage uses the dataset's selected state and split filter. Read classified, no-match and unavailable outcomes distinctly. Unknown or unclassified examples remain in the denominator rather than disappearing from the population.\n\nNew synthesis captures the project Dimension ontology, active Topics, Topic Groups and Scenarios used for classification. Retries reuse that vocabulary. A missing vocabulary is not a successful coverage assessment.\n\nComparing with the captured benchmark can reveal a thin category, but the benchmark distribution is not silently imposed as the training distribution target."},{"blockId":"weights-training.datasets#inspect-dataset","pageId":"weights-training.datasets","title":"Inspect Dataset","pageTitle":"Training Datasets and Coverage","url":"https://teammately.ai/docs/weights-training/datasets.md","humanUrl":"https://teammately.ai/docs/weights-training/datasets#inspect-dataset","markdownUrl":"https://teammately.ai/docs/weights-training/datasets.md","sectionId":"inspect-dataset","kind":"task","productArea":"weights_training","score":1106.1786469569342,"reasons":["search_match","page_title_match","term_match","prefix_or_fuzzy_match"],"markdown":"## Inspect Dataset\n\nOpen Dataset and review the input, response or preference target, captured criteria and observed judgments. Expected labels are not substitutes for the actual outcomes.\n\nKeep related construction-family members in the same split. A small input variation must not leak the same underlying situation across training and held-out testing. Inspect train, validation and test populations before packaging.\n\nExclusion and split changes produce a new dataset state. Existing packages remain bound to their earlier captured content rather than silently acquiring those edits."},{"blockId":"weights-training.datasets#related-reference-pages","pageId":"weights-training.datasets","title":"Related reference pages","pageTitle":"Training Datasets and Coverage","url":"https://teammately.ai/docs/weights-training/datasets.md","humanUrl":"https://teammately.ai/docs/weights-training/datasets#related-reference-pages","markdownUrl":"https://teammately.ai/docs/weights-training/datasets.md","sectionId":"related-reference-pages","kind":"task","productArea":"weights_training","score":1075.9749000385532,"reasons":["search_match","page_title_match","term_match","prefix_or_fuzzy_match"],"markdown":"## Related reference pages\n\n{% related-card-grid title=\"Related reference pages\" %}\n- [Weights Training](/docs/weights-training)\n- [Export, Train, and Evaluate](/docs/weights-training/exports-and-training)\n- [Dataset Representation](/docs/benchmark-datasets/representation)\n{% /related-card-grid %}"},{"blockId":"weights-training.datasets#object-and-state-changes","pageId":"weights-training.datasets","title":"Object and state changes","pageTitle":"Training Datasets and Coverage","url":"https://teammately.ai/docs/weights-training/datasets.md","humanUrl":"https://teammately.ai/docs/weights-training/datasets#object-and-state-changes","markdownUrl":"https://teammately.ai/docs/weights-training/datasets.md","sectionId":"object-and-state-changes","kind":"task","productArea":"weights_training","score":1022.0562224543421,"reasons":["search_match","page_title_match","term_match","prefix_or_fuzzy_match"],"markdown":"## Object and state changes\n\nDataset edits change current membership or split assignment through their owning commands. Representation analysis can publish a new dataset state without regenerating the input or response. It preserves recorded splits and captured vocabulary."},{"blockId":"weights-training.datasets#related-troubleshooting-pages","pageId":"weights-training.datasets","title":"Related troubleshooting pages","pageTitle":"Training Datasets and Coverage","url":"https://teammately.ai/docs/weights-training/datasets.md","humanUrl":"https://teammately.ai/docs/weights-training/datasets#related-troubleshooting-pages","markdownUrl":"https://teammately.ai/docs/weights-training/datasets.md","sectionId":"related-troubleshooting-pages","kind":"task","productArea":"weights_training","score":1012.3762655128814,"reasons":["search_match","page_title_match","term_match","prefix_or_fuzzy_match"],"markdown":"## Related troubleshooting pages\n\n{% related-card-grid title=\"Related troubleshooting pages\" %}\n- [Synthetic Cases That Feel Unrealistic](/docs/troubleshooting/unrealistic-synthetic-cases)\n- [Unbalanced Coverage](/docs/troubleshooting/unbalanced-coverage)\n{% /related-card-grid %}"},{"blockId":"weights-training.datasets#prerequisites","pageId":"weights-training.datasets","title":"Prerequisites","pageTitle":"Training Datasets and Coverage","url":"https://teammately.ai/docs/weights-training/datasets.md","humanUrl":"https://teammately.ai/docs/weights-training/datasets#prerequisites","markdownUrl":"https://teammately.ai/docs/weights-training/datasets.md","sectionId":"prerequisites","kind":"task","productArea":"weights_training","score":984.004469319016,"reasons":["search_match","page_title_match","term_match","prefix_or_fuzzy_match"],"markdown":"## Prerequisites\n\n- A preparation tied to the intended Benchmark Version.\n- Generated examples or a supported existing dataset.\n- Clear training purpose and held-out evaluation intent."},{"blockId":"weights-training.datasets#common-failure-modes","pageId":"weights-training.datasets","title":"Common failure modes","pageTitle":"Training Datasets and Coverage","url":"https://teammately.ai/docs/weights-training/datasets.md","humanUrl":"https://teammately.ai/docs/weights-training/datasets#common-failure-modes","markdownUrl":"https://teammately.ai/docs/weights-training/datasets.md","sectionId":"common-failure-modes","kind":"task","productArea":"weights_training","score":971.8148948943011,"reasons":["search_match","page_title_match","term_match","prefix_or_fuzzy_match"],"markdown":"## Common failure modes\n\n- Treating generation status as a quality score.\n- Substituting expected judgments for observed results.\n- Reading missing classification as proven absence.\n- Training on the held-out test split.\n- Assuming a package changes after the dataset is edited."}]}