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