Run Page
Each training run of your model gets a dedicated page, organized within the larger project
Use the run page to explore detailed information about a single version of your model.
- Run name, description, and tags
- Run state
- finished: script ended and fully synced data, or called
wandb.finish() - failed: script ended with a non-zero exit status
- crashed: script stopped sending heartbeats in the internal process, which can happen if the machine crashes
- running: script is still running and has recently sent a heartbeat
- Host name, operating system, Python version, and command that launched the run
W&B Dashboard run overview tab
The Python details are private, even if you make the page itself public. Here is an example of my run page in incognito on the left and my account on the right.
- Search, group, and arrange visualizations
- the search bar supports regular expressions
- Click the pencil icon ✏️ on a graph to edit
- change x-axis, metrics, and ranges
- edit legends, titles, and colors of charts
- View examples predictions from your validation set
- Visualize CPU utilization, system memory, disk I/O, network traffic, GPU utilization, GPU temperature, GPU time spent accessing memory, GPU memory allocated, and GPU power usage
- See the layers of your model, the number of parameters, and the output shape of each layer
- Output printed on the command line, the stdout and stderr from the machine training the model
- We show the last 1000 lines. After the run has finished, if you'd like to download the full log file, click the download button in the upper right corner.
- Keep model checkpoints, validation set examples, and more
- Click a row to see information about a particular artifact used or produced by this run
- See the reference for the project-level Artifacts Tab for more on navigating and using the artifacts viewers in the web app View a live example →
Last modified 3mo ago