diff --git a/applications/ColossalChat/coati/distributed/reward/reward_fn.py b/applications/ColossalChat/coati/distributed/reward/reward_fn.py
index 9e6d1066e..da19c7d22 100644
--- a/applications/ColossalChat/coati/distributed/reward/reward_fn.py
+++ b/applications/ColossalChat/coati/distributed/reward/reward_fn.py
@@ -5,7 +5,9 @@ from .reward_utils import extract_solution, validate_response_structure
 
 def math_reward_fn(input_ids, gt_answer, response_idx, **kwargs):
     tokenizer = kwargs["tokenizer"]
-    reward = torch.tensor(0.0).to(input_ids.device)
+    reward = torch.tensor(0.0)
+    format_reward = torch.tensor(0.0)
+    acc_reward = torch.tensor(0.0)
     s, e = response_idx[0], response_idx[1]
     if gt_answer is None:
         return reward
@@ -15,13 +17,21 @@ def math_reward_fn(input_ids, gt_answer, response_idx, **kwargs):
     final_answer, processed_str = extract_solution(decoded_final_answer)
 
     format_valid = validate_response_structure(processed_str, kwargs["tags"])
-    if not format_valid:
-        return reward
-    else:
+
+    # Check format accuracy
+    if format_valid:
+        format_reward += 1.0
         reward += 1.0
-        if gt_answer.strip().replace(" ", "").lower() == final_answer.strip().replace(" ", "").lower():
-            reward = reward + 2.0
-        return reward
+
+    # Check answer accuracy
+    if (
+        final_answer is not None
+        and gt_answer.strip().replace(" ", "").lower() == final_answer.strip().replace(" ", "").lower()
+    ):
+        acc_reward += 5.0
+        reward += 5.0
+
+    return torch.tensor([reward, format_reward, acc_reward]).to(input_ids.device)
 
 
 def gsm8k_reward_fn(input_ids, **kwargs):