I highly recommend ClearML for effortless experiment that just works. It does a lot more of MLOps besides experiment tracking but I haven’t used those functionalities
I had researched and spent time with several other tools including DVC, GuildAI and MLFlow but finally settled on ClearML. WandB pricing is too aggressive for my liking (they force an annual subscription of $600 last I checked)
There are a lot of tools in this space. Shameless plug to follow.
I helped build and use Disdat, which is a simple data versioning tool. It notably doesn't have the metadata capture libraries MLFlow has for different model libs, but it's meant to a lower-layer on which that can be built. Thus you won't see particulars about tracking "models" or "experiments", because models/experiments/features/intermediates are all just data thingies (or bundles in Disdat parlance). For the last 2+ years we've used Disdat to track runs and outputs of a custom distributed planning tool, and used Disdat-Luigi (an integration of Disdat with Luigi to automatically consume/produce versioned data) to manage model training and prediction pipelines (some with 10ks of artifacts). https://disdat.gitbook.io/disdat-documentation
