Model card for “add model name here”

First Author1, Second Author2

1 Planet Earth, Milky Way
2 Planet Earth, Milky Way

Sections and prompts from the model cards paper, v2. (Mitchell et al. (2019)).

Jump to section:

Model details

Basic information about the model.

Review section 4.1 of the model cards paper.

  • Person or organization developing model
  • Model date
  • Model version
  • Model type
  • Information about training algorithms, parameters, fairness 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.

Review section 4.2 of the model cards paper.

Primary intended uses

Primary intended users

Out-of-scope use cases


Factors could include demographic or phenotypic groups, environmental conditions, technical attributes, or others listed in Section 4.3.

Review section 4.3 of the model cards paper.

Relevant factors

Evaluation factors


The appropriate metrics to feature in a model card depend on the type of model that is being tested. For example, classification systems in which the primary output is a class label differ significantly from systems whose primary output is a score. In all cases, the reported metrics should be determined based on the model’s structure and intended use.

Review section 4.4 of the model cards paper.

Model performance measures

Decision thresholds

Approaches to uncertainty and variability

Evaluation data

All referenced datasets would ideally point to any set of documents that provide visibility into the source and composition of the dataset. Evaluation datasets should include datasets that are publicly available for third-party use. These could be existing datasets or new ones provided alongside the model card analyses to enable further benchmarking.

Review section 4.5 of the model cards paper.




Training data

Review section 4.6 of the model cards paper.

Quantitative analyses

Quantitative analyses should be disaggregated, that is, broken down by the chosen factors. Quantitative analyses should provide the results of evaluating the model according to the chosen metrics, providing confidence interval values when possible.

Review section 4.7 of the model cards paper.

Unitary results

Intersectional result

Ethical considerations

This section is intended to demonstrate the ethical considerations that went into model development, surfacing ethical challenges and solutions to stakeholders. Ethical analysis does not always lead to precise solutions, but the process of ethical contemplation is worthwhile to inform on responsible practices and next steps in future work.

Review section 4.8 of the model cards paper.


Human life


Risks and harms

Use cases

Caveats and recommendations

This section should list additional concerns that were not covered in the previous sections.

Review section 4.9 of the model cards paper.


Mitchell, Margaret, Simone Wu, Andrew Zaldivar, Parker Barnes, Lucy Vasserman, Ben Hutchinson, Elena Spitzer, Inioluwa Deborah Raji, and Timnit Gebru. 2019. “Model Cards for Model Reporting.” In Proceedings of the Conference on Fairness, Accountability, and Transparency, 220–29. FAT* ’19. New York, NY, USA: Association for Computing Machinery.