diff --git a/src/lighteval/utils/utils.py b/src/lighteval/utils/utils.py
index 3ab5976d8..7f7006b63 100644
--- a/src/lighteval/utils/utils.py
+++ b/src/lighteval/utils/utils.py
@@ -56,7 +56,7 @@ def rec(nest: dict, prefix: str, into: dict):
                         )  # Need this for markdown
                         into[prefix + k + sep + str(i)] = vv.tolist() if isinstance(vv, np.ndarray) else vv
             elif isinstance(v, np.ndarray):
-                into[prefix + k + sep + str(i)] = v.tolist()
+                into[prefix + k] = v.tolist()
             else:
                 v = clean_markdown(v)
                 into[prefix + k] = v
diff --git a/tests/unit/utils/test_utils.py b/tests/unit/utils/test_utils.py
index 68e844712..059e8612a 100644
--- a/tests/unit/utils/test_utils.py
+++ b/tests/unit/utils/test_utils.py
@@ -22,7 +22,9 @@
 
 import unittest
 
-from lighteval.utils.utils import remove_reasoning_tags
+import numpy as np
+
+from lighteval.utils.utils import flatten_dict, remove_reasoning_tags
 
 
 class TestRemoveReasoningTags(unittest.TestCase):
@@ -61,3 +63,24 @@ def test_no_closing_tag(self):
         tag_pairs = [("<think>", "</think>")]
         result = remove_reasoning_tags(text, tag_pairs)
         self.assertEqual(result, "<think> Reasoning section. Answer section")
+
+
+class TestFlattenDict(unittest.TestCase):
+    def test_bare_ndarray_value(self):
+        # A standalone ndarray previously hit the list-loop variable `i`, which
+        # is unbound here -> UnboundLocalError.
+        result = flatten_dict({"a": np.array([1, 2, 3])})
+        self.assertEqual(result, {"a": [1, 2, 3]})
+
+    def test_ndarray_after_list_key(self):
+        # A preceding list key leaks a stale `i`, which produced a bogus indexed
+        # key (e.g. "arr/2") for the ndarray.
+        result = flatten_dict({"lst": [10, 20, 30], "arr": np.array([7, 8, 9])})
+        self.assertEqual(
+            result,
+            {"lst/0": 10, "lst/1": 20, "lst/2": 30, "arr": [7, 8, 9]},
+        )
+
+    def test_list_of_ndarrays_still_indexed(self):
+        result = flatten_dict({"m": [np.array([1, 2]), np.array([3, 4])]})
+        self.assertEqual(result, {"m/0": [1, 2], "m/1": [3, 4]})