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Machine learning experiment tracking and visualizations |
Use the Weights & Biases Dashboard as a central place to organize and visualize results from your machine learning models.
Anywhere you train your models, whether on your local machine, your lab cluster, or spot instances in the cloud, we give you the same centralized dashboard. You don't need to spend your time copying outputs from your terminal into a spreadsheet or organizing TensorBoard files from different machines.
If you hand off a project to a collaborator or take a vacation, W&B makes it easy to see all the models your team has already tried so you're not wasting hours re-running old experiments.
Compare each training run and see what hyperparameters changed. Search, filter, sort, and group results from different models. It's easy to look over thousands of model versions and find the best performing models for different tasks.
Weights & Biases is good for experimentation, exploration, and reproducing models later. We capture not just the metrics, but also the hyperparameters and version of the code, and we can save your model checkpoints for you so your project is reproducible.
Add W&B to your project in 5 minutes. Install our free open-source Python package and add a couple of lines to your code, and every time you run your model you'll have nice logged metrics and records.
Use W&B to organize complex machine learning projects. It's easy to share a link to W&B, and you can use private teams to have everyone sending results to a shared project. We also support collaboration via reports— add interactive visualizations and describe your work in markdown. This is a great way to keep a work log, share findings with your supervisor, or present findings to your lab.