# Question and answer for model evaluation in Amazon Bedrock
Question and answer

Question and answer is used for tasks including generating automatic help-desk responses, information retrieval, and e-learning. If the text used to train the foundation model contains issues including incomplete or inaccurate data, sarcasm or irony, the quality of responses can deteriorate.

**Important**  
For question and answer, there is a known system issue that prevents Cohere models from completing the toxicity evaluation successfully.

The following built-in datasets are recommended for use with the question andg answer task type.

**BoolQ**  
BoolQ is a dataset consisting of yes/no question and answer pairs. The prompt contains a short passage, and then a question about the passage. This dataset is recommended for use with question and answer task type.

**Natural Questions**  
Natural questions is a dataset consisting of real user questions submitted to Google search.

**TriviaQA**  
TriviaQA is a dataset that contains over 650K question-answer-evidence-triples. This dataset is used in question and answer tasks.

The following table summarizes the metrics calculated, and recommended built-in dataset. 


**Available built-in datasets for the question and answer task type in Amazon Bedrock**  
[\[See the AWS documentation website for more details\]](http://docs.aws.amazon.com/sagemaker-unified-studio/latest/userguide/model-evaluation-tasks-question-answer.html)

To learn more about how the computed metric for each built-in dataset is calculated, see [Review a model model evaluation job in Amazon Bedrock](model-evaluation-report.md)