🤗 Evaluate provides access to a wide range of evaluation tools. It covers a range of modalities such as text, computer vision, audio, etc. as well as tools to evaluate models or datasets.

It has three types of evaluations:

• Measurement: for gaining more insights on datasets and model predictions based on their properties and characteristics -- these are covered in this space.
• Metric: measures the performance of a model on a given dataset, usually by comparing the model's predictions to some ground truth labels -- covered in the Evaluate Metric Spaces.
• Comparison: used useful to compare the performance of two or more models on a single test dataset., e.g. by comparing their predictions to ground truth labels and computing their agreement -- covered in the Evaluate Comparison Spaces.

All three types of evaluation supported by the 🤗 Evaluate library are meant to be mutually complementary, and help our community carry out more mindful and responsible evaluation!