diff --git a/src/transformers/modeling_rope_utils.py b/src/transformers/modeling_rope_utils.py
index c09664d688c3b1..5788238b58b3db 100644
--- a/src/transformers/modeling_rope_utils.py
+++ b/src/transformers/modeling_rope_utils.py
@@ -487,10 +487,11 @@ def _validate_longrope_parameters(config: PretrainedConfig):
             logger.warning(f"`rope_scaling`'s factor field must be a float >= 1, got {factor}")
 
         attention_factor = rope_scaling.get("attention_factor")
-        if attention_factor is not None and not isinstance(attention_factor, float) or attention_factor < 0:
-            logger.warning(
-                f"`rope_scaling`'s attention_factor field must be a float greater than 0, got {attention_factor}"
-            )
+        if attention_factor is not None:
+            if not isinstance(attention_factor, float) or attention_factor < 0.0:
+                logger.warning(
+                    f"`rope_scaling`'s attention_factor field must be a float greater than 0, got {attention_factor}"
+                )
 
 
 def _validate_llama3_parameters(config: PretrainedConfig):
diff --git a/tests/utils/test_modeling_rope_utils.py b/tests/utils/test_modeling_rope_utils.py
index cfc648a71d2ecb..a1d1fd6b922ab3 100644
--- a/tests/utils/test_modeling_rope_utils.py
+++ b/tests/utils/test_modeling_rope_utils.py
@@ -330,6 +330,16 @@ def test_longrope_rope_numerically(self):
             _, attention_scale = rope_fn(config=config, device=torch_device, seq_len=1)
             self.assertEqual(attention_scale, 0.5)
 
+            config.rope_scaling = {
+                "rope_type": "longrope",
+                "factor": factor,
+                "short_factor": short_factor,
+                "long_factor": long_factor,
+            }
+            self.assertEqual(config.rope_scaling.get("attention_factor"), None)
+            # Verify that "TypeError: '<' not supported between instances of 'NoneType' and 'int'" is not raised.
+            rope_config_validation(config)
+
         # Check 2: Factor == 1.0 -> short factor is applied to the default frequencies
         factor = 1.0
         config.rope_scaling = {