diff --git a/nncf/common/tensor_statistics/aggregator.py b/nncf/common/tensor_statistics/aggregator.py
index 47494145e78..63c03191802 100644
--- a/nncf/common/tensor_statistics/aggregator.py
+++ b/nncf/common/tensor_statistics/aggregator.py
@@ -23,6 +23,7 @@
 from nncf.data.dataset import DataItem
 from nncf.data.dataset import Dataset
 from nncf.data.dataset import ModelInput
+from nncf.common.logging import nncf_logger
 
 TensorType = TypeVar("TensorType")
 TModel = TypeVar("TModel")
@@ -70,7 +71,9 @@ def collect_statistics(self, model: TModel, graph: NNCFGraph) -> None:
         engine = factory.EngineFactory.create(model_with_outputs)
 
         iterations_number = self._get_iterations_number()
-        empty_statistics = True
+        
+        processed_samples = 0
+
         for input_data in track(  # type: ignore
             islice(self.dataset.get_inference_data(), iterations_number),
             total=iterations_number,
@@ -79,9 +82,13 @@ def collect_statistics(self, model: TModel, graph: NNCFGraph) -> None:
             outputs = engine.infer(input_data)
             processed_outputs = self._process_outputs(outputs)
             self._register_statistics(processed_outputs, merged_statistics)
-            empty_statistics = False
-        if empty_statistics:
+            processed_samples += 1
+        
+        if processed_samples == 0:
             raise nncf.ValidationError(EMPTY_DATASET_ERROR)
+        
+        if subset_size > processed_samples:
+            nncf_logger.warning(f"Dataset contains only {processed_samples} samples, smaller than the requested subset size {subset_size}.")  
 
     def register_statistic_points(self, statistic_points: StatisticPointsContainer) -> None:
         """