title: Storing multiple metrics in mlflow from a cross validation
body: <p>I have a logistic regression model for which I'm performing a repeated k-fold cross-validation and I'm wondering on the right way to track the the produced metrics in the mlfflow tracking api.</p>
  <pre><code>exp = mlflow.set_experiment(&quot;all_models_repeated_cross_validation_roc_auc&quot;)
  with mlflow.start_run(experiment_id=exp.experiment_id):
      rkf = RepeatedKFold(n_splits=5, n_repeats=10, random_state=random_state)
      scoring = make_scorer(roc_auc_score, needs_proba=False, multi_class=&quot;ovr&quot;)
      lr_scores = cross_val_score(lr, X_train, y_train, scoring=scoring, cv=rkf)
      # log all the 50 metrics in mlfflow tracking api
  </code></pre>
  <p>What is the proper way to do that with mlflow? Is it storing it as an artifact?</p>