I wonder what is best practice for hyperparameter optimization, to do e.g. a parameter sweep, to capture both the models and the metrics. I’d like to try 10 different values for the number of clusters (and also a few other parameters), and then plot figures visualizing each clustering.
Do you just execute
dvc run in a loop from a script? Then that script essentially becomes the “Makefile”?
Also, do you create a new branch for each experiment, or just a new folder with a unique name?