Add details to config

src/anemoi/training/config/training/default.yaml

@@ -58,19 +58,25 @@ loss_gradient_scaling: False
 
 # Validation metrics calculation,
 # This may be a list, in which case all metrics will be calculated
-# and logged according to their name
+# and logged according to their name.
+# These metrics are calculated in the output model space, and thus
+# have undergone postprocessing.
 validation_metrics:
   # loss class to initialise
   - _target_: anemoi.training.losses.mse.WeightedMSELoss
     # Scalars to include in loss calculation
     # Cannot scale over the variable dimension due to possible remappings.
+    # Available scalars include:
+    # - 'loss_weights_mask': Giving imputed NaNs a zero weight in the loss function
     # Use the `scale_validation_metrics` section to variable scale.
     scalars: []
     # other kwargs
     ignore_nans: True
 
 # List of validation metrics to keep in normalised space, and scalars to be applied
 # Use '*' in reference all metrics, or a list of metric names.
+# Unlike above, variable scaling is possible due to these metrics being
+# calculated in the same way as the training loss, within the internal model space.
 scale_validation_metrics:
   scalars_to_apply: ['variable']
   metrics: