diff --git a/applications/neural_search/recall/in_batch_negative/evaluate.py b/applications/neural_search/recall/in_batch_negative/evaluate.py
index 89da8e5157fe..ea9dde6c6107 100644
--- a/applications/neural_search/recall/in_batch_negative/evaluate.py
+++ b/applications/neural_search/recall/in_batch_negative/evaluate.py
@@ -73,17 +73,15 @@ def recall(rs, N=10):
     with open(args.recall_result_file, "r", encoding="utf-8") as f:
         relevance_labels = []
         for index, line in enumerate(f):
-            if index % args.recall_num == 0 and index != 0:
-                rs.append(relevance_labels)
-                relevance_labels = []
-
             text, recalled_text, cosine_sim = line.rstrip().split("\t")
             if text2similar[text] == recalled_text:
                 relevance_labels.append(1)
             else:
                 relevance_labels.append(0)
 
-        rs.append(relevance_labels)
+            if (index + 1) % args.recall_num == 0:
+                rs.append(relevance_labels)
+                relevance_labels = []
 
     recall_N = []
     recall_num = [1, 5, 10, 20, 50]
diff --git a/applications/neural_search/recall/simcse/evaluate.py b/applications/neural_search/recall/simcse/evaluate.py
index 63d3b2fe1634..bc991250b9df 100644
--- a/applications/neural_search/recall/simcse/evaluate.py
+++ b/applications/neural_search/recall/simcse/evaluate.py
@@ -57,17 +57,16 @@ def recall(rs, N=10):
     with open(args.recall_result_file, "r", encoding="utf-8") as f:
         relevance_labels = []
         for index, line in enumerate(f):
-
-            if index % args.recall_num == 0 and index != 0:
-                rs.append(relevance_labels)
-                relevance_labels = []
-
             text, recalled_text, cosine_sim = line.rstrip().split("\t")
             if text2similar[text] == recalled_text:
                 relevance_labels.append(1)
             else:
                 relevance_labels.append(0)
 
+            if (index + 1) % args.recall_num == 0:
+                rs.append(relevance_labels)
+                relevance_labels = []
+
     recall_N = []
     recall_num = [1, 5, 10, 20, 50]
     result = open("result.tsv", "a")