# Text classification for model evaluation in Amazon Bedrock
Text classification

Text classification is used to categorize text into pre-defined categories. Applications that use text classification include content recommendation, spam detection, language identification and trend analysis on social media. Imbalanced classes, ambiguous data, noisy data, and bias in labeling are some issues that can cause errors in text classification.

**Important**  
For text classification, 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 text classification task type.

**Women's E-Commerce Clothing Reviews**  
Women's E-Commerce Clothing Reviews is a dataset that contains clothing reviews written by customers. This dataset is used in text classification tasks. 

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




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