diff --git a/openfl/component/collaborator/collaborator.py b/openfl/component/collaborator/collaborator.py
index d4fd380998..c90be90f22 100644
--- a/openfl/component/collaborator/collaborator.py
+++ b/openfl/component/collaborator/collaborator.py
@@ -382,15 +382,17 @@ def get_data_for_tensorkey(self, tensor_key):
                         return nparray
                     prior_round -= 1
                 logger.info(f"Cannot find any prior version of tensor {tensor_name} locally...")
-            logger.debug(
-                "Unable to get tensor from local store..." "attempting to retrieve from client"
-            )
             # Determine whether there are additional compression related
             # dependencies.
             # Typically, dependencies are only relevant to model layers
             tensor_dependencies = self.tensor_codec.find_dependencies(
                 tensor_key, self.delta_updates
             )
+            logger.debug(
+                "Unable to get tensor from local store..."
+                "attempting to retrieve from client len tensor_dependencies"
+                f" tensor_key {tensor_key}"
+            )
             if len(tensor_dependencies) > 0:
                 # Resolve dependencies
                 # tensor_dependencies[0] corresponds to the prior version
@@ -411,10 +413,10 @@ def get_data_for_tensorkey(self, tensor_key):
                     self.tensor_db.cache_tensor({new_model_tk: nparray})
                 else:
                     logger.info(
-                        "Count not find previous model layer."
+                        "Could not find previous model layer."
                         "Fetching latest layer from aggregator"
                     )
-                    # The original model tensor should be fetched from client
+                    # The original model tensor should be fetched from aggregator
                     nparray = self.get_aggregated_tensor_from_aggregator(
                         tensor_key, require_lossless=True
                     )
@@ -423,6 +425,18 @@ def get_data_for_tensorkey(self, tensor_key):
                 nparray = self.get_aggregated_tensor_from_aggregator(
                     tensor_key, require_lossless=True
                 )
+            else:
+                # we should try fetching the tensor from aggregator
+                tensor_name, origin, round_number, report, tags = tensor_key
+                tags = (self.collaborator_name,) + tags
+                tensor_key = (tensor_name, origin, round_number, report, tags)
+                logger.info(
+                    "Could not find previous model layer."
+                    f"Fetching latest layer from aggregator {tensor_key}"
+                )
+                nparray = self.get_aggregated_tensor_from_aggregator(
+                    tensor_key, require_lossless=True
+                )
         else:
             logger.debug("Found tensor %s in local TensorDB", tensor_key)
 
diff --git a/openfl/federated/task/runner_keras.py b/openfl/federated/task/runner_keras.py
index e2dd069f72..c7803cb0eb 100644
--- a/openfl/federated/task/runner_keras.py
+++ b/openfl/federated/task/runner_keras.py
@@ -182,7 +182,16 @@ def train_(self, batch_generator, metrics: list = None, **kwargs):
         #  initialization (build_model).
         #  If metrics are added (i.e. not a subset of what was originally
         #  defined) then the model must be recompiled.
-        results = self.model.get_metrics_result()
+        try:
+            results = self.model.get_metrics_result()
+        except ValueError:
+            if "batch_size" in kwargs:
+                batch_size = kwargs["batch_size"]
+            else:
+                batch_size = 1
+            # evaluation needed before metrics can be resolved
+            self.model.evaluate(self.data_loader.get_valid_loader(batch_size), verbose=1)
+            results = self.model.get_metrics_result()
 
         # TODO if there are new metrics in the flplan that were not included
         #  in the originally