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| title: README | |
| emoji: 🤗 | |
| colorFrom: green | |
| colorTo: purple | |
| sdk: static | |
| pinned: false | |
| tags: | |
| - evaluate | |
| - measurement | |
| 🤗 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. | |
| - **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. | |
| - **Measurement**: for gaining more insights on datasets and model predictions based on their properties and characteristics. | |
| 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! |