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!