Model Card

Model Details. Basic information about the model.

Person or organization developing model
Model date
Model version
Model type
Information about training algorithms, parameters, fair- ness constraints or other applied approaches, and features
Paper or other resource for more information
Citation details
License
Where to send questions or comments about the model

Intended Use. Use cases that were envisioned during development.

Primary intended uses
Primary intended users
Out-of-scope use cases

Factors. Factors could include demographic or phenotypic

groups, environmental conditions, technical attributes, or others listed in Section 4.3.

Relevant factors
Evaluation factors

Metrics. Metrics should be chosen to reflect potential real- world impacts of the model.

Model performance measures
Decision thresholds
Variation approaches

Evaluation Data. Details on the dataset(s) used for the

quantitative analyses in the card.

Datasets
Motivation
Preprocessing

Training Data. May not be possible to provide in practice. When possible, this section should mirror Evaluation Data. If such detail is not possible, minimal allowable information should be provided here, such as details of the distribution over various factors in the training datasets.

Quantitative Analyses * Unitary results

Intersectional results

Ethical Considerations

Caveats and Recommendations