diff --git a/finetune/official/dataset.py b/finetune/official/dataset.py
index 5012ec6..048d859 100644
--- a/finetune/official/dataset.py
+++ b/finetune/official/dataset.py
@@ -373,11 +373,13 @@ def preprocess(
     
     images = [transform(i) for i in images]
     
-    if len(images_dict) == 1 and "<image>" in images_dict:       
-        if "<image>" in conversations[0]["content"]:
-            conversations[0]["content"] = conversations[0]["content"].replace(
-                "<image>", image_placeholder
-            )
+    if len(images_dict) == 1 and "<image>" in images_dict:
+        for conversation in conversations:
+            if "<image>" in conversation["content"]:
+                conversation["content"] = conversation["content"].replace(
+                    "<image>", image_placeholder
+                )
+                break
         else:
             conversations[0]["content"] = (
                 image_placeholder + "\n" + conversations[0]["content"]
diff --git a/finetune/official/test_dataset.py b/finetune/official/test_dataset.py
new file mode 100644
index 0000000..c4fdc96
--- /dev/null
+++ b/finetune/official/test_dataset.py
@@ -0,0 +1,96 @@
+import copy
+import importlib.util
+from pathlib import Path
+import unittest
+from unittest.mock import patch
+
+
+DATASET_PATH = Path(__file__).with_name("dataset.py")
+
+
+class Tokenizer:
+    im_start = "<im_start>"
+    im_end = "<im_end>"
+    unk_token = "<unk>"
+
+
+def load_dataset_module():
+    spec = importlib.util.spec_from_file_location("minicpm_dataset", DATASET_PATH)
+    module = importlib.util.module_from_spec(spec)
+    spec.loader.exec_module(module)
+    return module
+
+
+class PreprocessSingleImagePlacementTest(unittest.TestCase):
+    @classmethod
+    def setUpClass(cls):
+        cls.dataset = load_dataset_module()
+
+    def setUp(self):
+        self.tokenizer = Tokenizer()
+        self.image_placeholder = "<im_start><unk><unk><im_end>"
+
+    def preprocess_and_capture(self, conversations):
+        captured = {}
+
+        def capture_conversation_to_ids(updated_conversations, *args):
+            captured["conversations"] = copy.deepcopy(updated_conversations)
+            return {
+                "input_ids": [],
+                "position_ids": [],
+                "target": [],
+                "image_bound": [],
+            }
+
+        with patch.object(
+            self.dataset, "conversation_to_ids", capture_conversation_to_ids
+        ):
+            self.dataset.preprocess(
+                {"<image>": object()},
+                conversations,
+                self.tokenizer,
+                transform=lambda image: image,
+                query_nums=2,
+                max_length=32,
+            )
+
+        return captured["conversations"]
+
+    def test_places_single_image_at_later_placeholder_turn(self):
+        conversations = [
+            {"role": "user", "content": "First question"},
+            {"role": "assistant", "content": "First answer"},
+            {"role": "user", "content": "Please inspect <image> now"},
+            {"role": "assistant", "content": "Second answer"},
+        ]
+
+        updated = self.preprocess_and_capture(conversations)
+
+        self.assertEqual(updated[0]["content"], "First question")
+        self.assertEqual(
+            updated[2]["content"],
+            f"Please inspect {self.image_placeholder} now",
+        )
+        self.assertEqual(
+            "\n".join(message["content"] for message in updated).count(
+                self.image_placeholder
+            ),
+            1,
+        )
+
+    def test_keeps_front_fallback_without_placeholder(self):
+        conversations = [
+            {"role": "user", "content": "First question"},
+            {"role": "assistant", "content": "First answer"},
+        ]
+
+        updated = self.preprocess_and_capture(conversations)
+
+        self.assertEqual(
+            updated[0]["content"],
+            f"{self.image_placeholder}\nFirst question",
+        )
+
+
+if __name__ == "__main__":
+    unittest.main()