diff --git a/optimum_benchmark/backends/utils.py b/optimum_benchmark/backends/utils.py
index 25bca8ef..fc9348c1 100644
--- a/optimum_benchmark/backends/utils.py
+++ b/optimum_benchmark/backends/utils.py
@@ -59,10 +59,18 @@ def extract_shapes_from_model_artifacts(
 
     # text input
     shapes["vocab_size"] = artifacts_dict.get("vocab_size", 2)
+    if shapes["vocab_size"] == 0:
+        shapes["vocab_size"] = 2
+
     shapes["type_vocab_size"] = artifacts_dict.get("type_vocab_size", 2)
+    if shapes["type_vocab_size"] == 0:
+        shapes["type_vocab_size"] = 2
 
     # image input
     shapes["num_channels"] = artifacts_dict.get("num_channels", None)
+    if shapes["num_channels"] is None:
+        # processors have different names for the number of channels
+        shapes["num_channels"] = artifacts_dict.get("channels", None)
 
     image_size = artifacts_dict.get("image_size", None)
     if image_size is None:
@@ -86,10 +94,15 @@ def extract_shapes_from_model_artifacts(
         shapes["width"] = None
 
     # classification labels (default to 2)
-    shapes["num_labels"] = len(artifacts_dict.get("id2label", {"0": "LABEL_0", "1": "LABEL_1"}))
+    id2label = artifacts_dict.get("id2label", {"0": "LABEL_0", "1": "LABEL_1"})
+    shapes["num_labels"] = len(id2label)
+    if shapes["num_labels"] == 0:
+        shapes["num_labels"] = 2
 
     # object detection labels (default to 2)
     shapes["num_queries"] = artifacts_dict.get("num_queries", 2)
+    if shapes["num_queries"] == 0:
+        shapes["num_queries"] = 2
 
     return shapes