Which elements are typically included in a Model Card?

• A. Objectives, training data, capabilities, limitations, and performance
• B. Licensing terms and pricing
• C. Hardware and deployment stack
• D. Marketing summary

Answer: (A)

Model Cards are concise, structured documents that communicate the practical details about a machine learning model to help users understand how and when to use it. The elements listed—objectives, training data, capabilities, limitations, and performance—together cover the essential picture. Objectives describe the intended use and success criteria, guiding users on appropriate applications. Training data details reveal where the model learned from, including data sources and diversity, which helps assess potential biases and generalization. Capabilities and limitations spell out what the model can reliably do and where it may fail or behave unexpectedly. Performance provides evaluation results, showing how the model performs across relevant tasks, datasets, or groups, so users can judge its suitability for their context. Licensing terms and pricing pertain to legal and commercial aspects, not the model’s behavior or evaluation. The hardware and deployment stack relate to the infrastructure required to run the model, rather than the documentation of its use and performance. A marketing summary is oriented toward promotion rather than transparent, technical documentation.