diff --git a/examples/flax/question-answering/run_qa.py b/examples/flax/question-answering/run_qa.py
index 7c705090f1181d..16a744ddc32cdb 100644
--- a/examples/flax/question-answering/run_qa.py
+++ b/examples/flax/question-answering/run_qa.py
@@ -426,7 +426,8 @@ def eval_data_collator(dataset: Dataset, batch_size: int):
 
     for idx in batch_idx:
         batch = dataset[idx]
-        batch = {k: np.array(v) for k, v in batch.items()}
+        # Ignore `offset_mapping` to avoid numpy/JAX array conversion issue.
+        batch = {k: np.array(v) for k, v in batch.items() if k != "offset_mapping"}
 
         yield batch
 
@@ -1000,7 +1001,6 @@ def eval_step(state, batch):
                     position=2,
                 ):
                     _ = batch.pop("example_id")
-                    _ = batch.pop("offset_mapping")
                     predictions = pad_shard_unpad(p_eval_step)(
                         state, batch, min_device_batch=per_device_eval_batch_size
                     )
@@ -1055,7 +1055,6 @@ def eval_step(state, batch):
             eval_loader, total=math.ceil(len(eval_dataset) / eval_batch_size), desc="Evaluating ...", position=2
         ):
             _ = batch.pop("example_id")
-            _ = batch.pop("offset_mapping")
             predictions = pad_shard_unpad(p_eval_step)(state, batch, min_device_batch=per_device_eval_batch_size)
             start_logits = np.array(predictions[0])
             end_logits = np.array(predictions[1])