diff --git a/scripts/question_answering/run_squad.py b/scripts/question_answering/run_squad.py
index 521ee15a47..01e1ae1f65 100644
--- a/scripts/question_answering/run_squad.py
+++ b/scripts/question_answering/run_squad.py
@@ -126,6 +126,8 @@ def parse_args():
                              'may increase for mixed precision training on GPUs with TensorCores.')
     parser.add_argument('--overwrite_cache', action='store_true',
                         help='Whether to overwrite the feature cache.')
+    parser.add_argument('--sort_input_data', action='store_true',
+                        help='Whether to sort input data before evaluation.')
     # Evaluation hyperparameters
     parser.add_argument('--start_top_n', type=int, default=5,
                         help='Number of start-position candidates')
@@ -837,6 +839,8 @@ def evaluate(args, last=True):
 
     logging.info('Prepare dev data')
     dev_features = get_squad_features(args, tokenizer, segment='dev')
+    if args.sort_input_data:
+        dev_features.sort(key=lambda x: x.qas_id)
     dev_data_path = os.path.join(args.data_dir, 'dev-v{}.json'.format(args.version))
     dataset_processor = SquadDatasetProcessor(tokenizer=tokenizer,
                                               doc_stride=args.doc_stride,
@@ -848,6 +852,8 @@ def evaluate(args, last=True):
         chunk_features = dataset_processor.process_sample(feature)
         dev_all_chunk_features.extend(chunk_features)
         dev_chunk_feature_ptr.append(dev_chunk_feature_ptr[-1] + len(chunk_features))
+    if args.sort_input_data:
+        dev_all_chunk_features.sort(key=lambda x: x.valid_length, reverse=True)
 
     def eval_validation(ckpt_name, best_eval):
         """
@@ -912,6 +918,9 @@ def eval_validation(ckpt_name, best_eval):
         all_predictions = collections.OrderedDict()
         all_nbest_json = collections.OrderedDict()
         no_answer_score_json = collections.OrderedDict()
+        if args.sort_input_data:
+            all_results.sort(key=lambda x: x.qas_id)
+            dev_all_chunk_features.sort(key=lambda x: x.qas_id)
         for index, (left_index, right_index) in enumerate(zip(dev_chunk_feature_ptr[:-1],
                                                               dev_chunk_feature_ptr[1:])):
             chunked_features = dev_all_chunk_features[left_index:right_index]