Hello @User, can you give a reproducible example (e.g. a repo I can clone) so I can try to reproduce the bug? I guess that what you mean by "running a pipeline with several model" is to use modular pipelines to duplicate a "base" pipeline, and you use a namespace which changes the names of its datasets (in particular, the metrics and models you persist in your ``catalog.yml`` which should be persisted). In this case, it seems that Kedro does not namespace parameters according to this pinned issue, so mlflow has no way to distinguish them: https://github.com/quantumblacklabs/kedro/issues/929, but this will be fixed in 0.18.0. Since this is more a Kedro bug than a kedro-mlflow bug, I won't support any specific trick to fix it and we will have to wait 0.18.0 unfortunately ☹️ Would you mind trying using the develop branch and tell me if it fixes the issue? If i misunderstood what you said, feel free to ask again!