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πŸ€— 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:

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

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

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