Thanks AgitatedDove14 . I am not using ClearML for scheduling/execution at this stage. I am evaluating ClearML for adding reporting to our current workflow. We have existing (parallelised) code for cross-validating models and I am playing with how best to log training/testing to ClearML. One thought is to initialise a new clearML task in each fold to capture the iteration-level metrics, and then create another task/experiment at the end to capture the aggregated metrics across folds. Alternatively, I could simply dump all fold and aggregated metrics into a single experiment. I don't have a good feel yet as to the pros and cons and was wondering if anyone had any advice.