Model Card
conceptA model card is a structured document that describes an AI or machine-learning model’s intended uses, performance, evaluation conditions, limitations, and relevant governance information.
Technical explanation
Model cards commonly record model identity and version, developers, purpose, prohibited or out-of-scope uses, training and evaluation context, metrics across relevant groups or conditions, ethical considerations, limitations, and maintenance information. They support comparison and responsible reuse.
Business relevance
Model cards make important model assumptions visible to product, procurement, risk, audit, and downstream implementation teams. They reduce the chance that a model is deployed outside the conditions in which it was evaluated.
Implementation example
A document-classification model card reports supported languages, evaluation datasets, error rates by document type, data cut-off, known failure modes, licence conditions, and escalation contacts.
Limitations and common misconceptions
A model card is self-reported documentation and may be incomplete or stale. It does not replace independent testing, system-level assessment, security review, or monitoring in the actual deployment context.
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