TensorBoard seems to have a feature to display multiple different runs and toggle them.
How can I make multiple runs show up here and how can assign a name to them to differentiate them?
tensorboard --logdir=summaries. --logdir is the directory you will create data to visualize. Files that TensorBoard saves data into are called event files. Type of data saved into the event files is called summary data. Optionally you can use --port=<port_you_like> to change the port TensorBoard runs on.
Tensorboard is helpful in these kinds of scenarios that provide different visualizations for models. You can visualize the model graph, losses, accuracy, etc when your model is under training. It is a very helpful tool that can be used to monitor the model that is getting trained on a large dataset.
In addition to TensorBoard scanning subdirectories (so you can pass a directory containing the directories with your runs), you can also pass multiple directories to TensorBoard explicitly and give custom names (example taken from the --help output):
tensorboard --logdir=name1:/path/to/logs/1,name2:/path/to/logs/2
More information can be found at the TensorBoard documentation.
In recent versions of TensorBoard, aliasing this way requires a different argument, however its use is discouraged (quote from current documentation on github - linked above):
Logdir & Logdir_spec (Legacy Mode)
You may also pass a comma separated list of log directories, and TensorBoard will watch each directory. You can also assign names to individual log directories by putting a colon between the name and the path, as in
tensorboard --logdir_spec name1:/path/to/logs/1,name2:/path/to/logs/2
This flag (--logdir_spec) is discouraged and can usually be avoided. TensorBoard walks log directories recursively; for finer-grained control, prefer using a symlink tree. Some features may not work when using --logdir_spec instead of --logdir.
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