diff --git a/src/datasets/arrow_dataset.py b/src/datasets/arrow_dataset.py
index 909f666d4dc..bc7ab6c9492 100644
--- a/src/datasets/arrow_dataset.py
+++ b/src/datasets/arrow_dataset.py
@@ -2929,14 +2929,15 @@ def init_buffer_and_writer():
                 # Loop over single examples or batches and write to buffer/file if examples are to be updated
                 if not batched:
                     pbar_total = len(input_dataset)
-                    pbar_iterable = input_dataset._iter(decoded=False)
+                    pbar_iterable = enumerate(input_dataset._iter(decoded=False))
                 else:
                     num_rows = (
                         len(input_dataset) if not drop_last_batch else len(input_dataset) // batch_size * batch_size
                     )
                     pbar_total = (num_rows // batch_size) + 1 if num_rows % batch_size else num_rows // batch_size
-                    pbar_iterable = input_dataset._iter_batches(
-                        batch_size, decoded=False, drop_last_batch=drop_last_batch
+                    pbar_iterable = zip(
+                        range(0, num_rows, batch_size),
+                        input_dataset._iter_batches(batch_size, decoded=False, drop_last_batch=drop_last_batch),
                     )
                 pbar_unit = "ex" if not batched else "ba"
                 pbar_desc = (desc + " " if desc is not None else "") + "#" + str(rank) if rank is not None else desc
@@ -2949,7 +2950,7 @@ def init_buffer_and_writer():
                     desc=pbar_desc,
                 )
                 if not batched:
-                    for i, example in enumerate(pbar):
+                    for i, example in pbar:
                         example = apply_function_on_filtered_inputs(example, i, offset=offset)
                         if update_data:
                             if i == 0:
@@ -2960,7 +2961,7 @@ def init_buffer_and_writer():
                             else:
                                 writer.write(example)
                 else:
-                    for i, batch in zip(range(0, num_rows, batch_size), pbar):
+                    for i, batch in pbar:
                         indices = list(
                             range(*(slice(i, i + batch_size).indices(input_dataset.num_rows)))
                         )  # Something simpler?