Scalable, customizable ‍hyperparameter search and optimization


We cite all the algorithms that we’re using, and show all the logs of sweep progress. You have complete visibility.


It’s easy to get started. We’ve dealt with edge cases, so you don’t have to worry about concurrent runs and crashing runs.


Our sweeps are infinitely customizable. You can pick your own distribution for inputs, specify logic, and use early stopping.

Parameter importance

Visualize which hyperparameters affect the metrics you care about. W&B comes with default visualizations that make it easy to get started without writing custom code to compare machine learning experiments.

Bayesian optimization

Use our transparent implementations of popular algorithms, or customize your own logic for sweeps.

Early stopping

We implemented the Hyperband algorithm to save GPU hours with customizable early stopping. This feature keeps the most promising, best performing runs running and kills off the bottom runs. Agents are then freed up to try new hyperparameter combinations.

Massive scale

Our sweeps can handle massive scale, and we support early stopping so you can quickly optimize over thousands of hyperparameter combinations without wasting GPU hours.

Collaborate centrally

Visualize all your hyperparameter sweeps in one unified place with our dashboard.