diff --git a/examples/pytorch/question-answering/run_qa.py b/examples/pytorch/question-answering/run_qa.py
index 57b0cb04e949..391e5b7a3998 100755
--- a/examples/pytorch/question-answering/run_qa.py
+++ b/examples/pytorch/question-answering/run_qa.py
@@ -283,6 +283,7 @@ def main():
         cache_dir=model_args.cache_dir,
         revision=model_args.model_revision,
         use_auth_token=True if model_args.use_auth_token else None,
+        ort = training_args.ort,
     )
     tokenizer = AutoTokenizer.from_pretrained(
         model_args.tokenizer_name if model_args.tokenizer_name else model_args.model_name_or_path,
diff --git a/src/transformers/models/roberta/modeling_roberta.py b/src/transformers/models/roberta/modeling_roberta.py
index cf535a719c8b..c078b14b4c5d 100644
--- a/src/transformers/models/roberta/modeling_roberta.py
+++ b/src/transformers/models/roberta/modeling_roberta.py
@@ -1414,6 +1414,7 @@ class RobertaForQuestionAnswering(RobertaPreTrainedModel):
     def __init__(self, config):
         super().__init__(config)
         self.num_labels = config.num_labels
+        self.ort = config.ort
 
         self.roberta = RobertaModel(config, add_pooling_layer=False)
         self.qa_outputs = nn.Linear(config.hidden_size, config.num_labels)
@@ -1480,7 +1481,7 @@ def forward(
             if len(end_positions.size()) > 1:
                 end_positions = end_positions.squeeze(-1)
             # sometimes the start/end positions are outside our model inputs, we ignore these terms
-            ignored_index = start_logits.size(1)
+            ignored_index = start_logits.size(1) if not self.ort else 344
             start_positions.clamp_(0, ignored_index)
             end_positions.clamp_(0, ignored_index)