diff --git a/examples/pytorch/text-classification/run_glue.py b/examples/pytorch/text-classification/run_glue.py
index 257a593834..7ecee51c03 100755
--- a/examples/pytorch/text-classification/run_glue.py
+++ b/examples/pytorch/text-classification/run_glue.py
@@ -380,6 +380,9 @@ def main():
     if label_to_id is not None:
         model.config.label2id = label_to_id
         model.config.id2label = {id: label for label, id in config.label2id.items()}
+    elif data_args.task_name is not None and not is_regression:
+        model.config.label2id = {l: i for i, l in enumerate(label_list)}
+        model.config.id2label = {id: label for label, id in config.label2id.items()}
 
     if data_args.max_seq_length > tokenizer.model_max_length:
         logger.warning(
diff --git a/examples/pytorch/text-classification/run_glue_no_trainer.py b/examples/pytorch/text-classification/run_glue_no_trainer.py
index 75f4ad5bbc..4af109a4bb 100644
--- a/examples/pytorch/text-classification/run_glue_no_trainer.py
+++ b/examples/pytorch/text-classification/run_glue_no_trainer.py
@@ -288,6 +288,9 @@ def main():
     if label_to_id is not None:
         model.config.label2id = label_to_id
         model.config.id2label = {id: label for label, id in config.label2id.items()}
+    elif args.task_name is not None and not is_regression:
+        model.config.label2id = {l: i for i, l in enumerate(label_list)}
+        model.config.id2label = {id: label for label, id in config.label2id.items()}
 
     padding = "max_length" if args.pad_to_max_length else False
 
diff --git a/examples/tensorflow/text-classification/run_glue.py b/examples/tensorflow/text-classification/run_glue.py
index ff482e2cf0..0bc2f8d7e1 100644
--- a/examples/tensorflow/text-classification/run_glue.py
+++ b/examples/tensorflow/text-classification/run_glue.py
@@ -355,6 +355,9 @@ def main():
     if label_to_id is not None:
         config.label2id = label_to_id
         config.id2label = {id: label for label, id in config.label2id.items()}
+    elif data_args.task_name is not None and not is_regression:
+        config.label2id = {l: i for i, l in enumerate(label_list)}
+        config.id2label = {id: label for label, id in config.label2id.items()}
 
     if data_args.max_seq_length > tokenizer.model_max_length:
         logger.warning(