diff --git a/applications/ColossalEval/colossal_eval/evaluate/dataset_evaluator/dataset_evaluator.py b/applications/ColossalEval/colossal_eval/evaluate/dataset_evaluator/dataset_evaluator.py
index c70988707a15..22de56b93c81 100644
--- a/applications/ColossalEval/colossal_eval/evaluate/dataset_evaluator/dataset_evaluator.py
+++ b/applications/ColossalEval/colossal_eval/evaluate/dataset_evaluator/dataset_evaluator.py
@@ -60,6 +60,11 @@ def _calculate_label_metrics(self, metric: str, category: str):
                             sample["output"], ref, all_classes=self.data[category]["inference_kwargs"]["all_classes"]
                         ),
                     )
+
+                    score = max(
+                        score,
+                        metric_helper.accuracy_by_options(sample["input"], sample["output"], ref),
+                    )
                 softmaxs.append(references[i] if score == 1 else -1)
             else:
                 softmaxs.append(np.argmax(np.array(list(sample["softmax_over_choices"].values()))))
diff --git a/applications/ColossalEval/colossal_eval/evaluate/dataset_evaluator/metrics.py b/applications/ColossalEval/colossal_eval/evaluate/dataset_evaluator/metrics.py
index 914465478dec..45a12756de69 100644
--- a/applications/ColossalEval/colossal_eval/evaluate/dataset_evaluator/metrics.py
+++ b/applications/ColossalEval/colossal_eval/evaluate/dataset_evaluator/metrics.py
@@ -443,6 +443,20 @@ def multi_choice_accuracy(prediction, reference, **kwargs):
     return score
 
 
+def accuracy_by_options(question, prediction, reference):
+    pattern = r"[A-Z]\. [^\n]+"
+    options = re.findall(pattern, question)
+    answer = prediction.split("\n\n")[0]
+
+    for option in options:
+        choice, content = option.split(". ", 1)
+
+        if choice == reference and content == answer:
+            return 1
+
+    return 0
+
+
 def combined_single_choice_accuracy(prediction, reference, **kwargs):
     return single_choice_accuracy(prediction, reference, **kwargs)
 
diff --git a/applications/ColossalEval/colossal_eval/models/huggingface.py b/applications/ColossalEval/colossal_eval/models/huggingface.py
index 9f785a6aa9d1..47259c1db758 100644
--- a/applications/ColossalEval/colossal_eval/models/huggingface.py
+++ b/applications/ColossalEval/colossal_eval/models/huggingface.py
@@ -96,7 +96,7 @@ def _load_tokenizer(self, path: str, tokenizer_path: Optional[str], tokenizer_kw
             self.logger.warning("pad_token_id is not set for the tokenizer. " "Using eos_token_id as pad_token_id.")
             if self.tokenizer.eos_token:
                 self.tokenizer.pad_token = self.tokenizer.eos_token
-            elif self.tokenizer.eod_id:
+            elif hasattr(self.tokenizer, "eod_id"):
                 # Qwen has an eod token "<|endoftext|>".
                 self.tokenizer.pad_token_id = self.tokenizer.eod_id