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Tune Hyperparameters

Use W&B Sweeps to automate hyperparameter search and visualize rich, interactive experiment tracking. Pick from popular search methods such as Bayesian, grid search, and random to search the hyperparameter space. Scale and parallelize sweep across one or more machines.

Draw insights from large hyperparameter tuning experiments with interactive dashboards.

How it worksโ€‹

Create a sweep with two W&B CLI commands:

  1. Initialize a sweep
wandb sweep --project <propject-name> <path-to-config file>
  1. Start the sweep agent
wandb agent <sweep-ID>

The preceding code snippet, and the colab linked on this page, show how to initialize and create a sweep with wht W&B CLI. See the Sweeps Walkthrough for a step-by-step outline of the W&B Python SDK commands to use to define a sweep configuration, initialize a sweep, and start a sweep.

How to get startedโ€‹

Depending on your use case, explore the following resources to get started with W&B Sweeps:

For a step-by-step video, see: Tune Hyperparameters Easily with W&B Sweeps.

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