diff --git a/src/axolotl/core/trainers/grpo/trainer.py b/src/axolotl/core/trainers/grpo/trainer.py
index dccc85d80..c97fccd31 100644
--- a/src/axolotl/core/trainers/grpo/trainer.py
+++ b/src/axolotl/core/trainers/grpo/trainer.py
@@ -3,6 +3,7 @@
 # pylint: disable=too-many-lines,duplicate-code,protected-access,no-member
 
 import warnings
+from functools import partial
 from typing import Any
 
 import datasets
@@ -58,6 +59,42 @@ class AxolotlGRPOTrainer(
 
     _tag_names = ["trl", "grpo", "axolotl"]
 
+    def get_train_dataloader(self):
+        if self.train_dataset is None:
+            raise ValueError("Trainer: training requires a train_dataset.")
+
+        train_dataset = self.train_dataset
+        data_collator = self.data_collator
+        if isinstance(train_dataset, datasets.Dataset):
+            train_dataset = self._remove_unused_columns(
+                train_dataset, description="training"
+            )
+        else:
+            data_collator = self._get_collator_with_removed_columns(
+                data_collator, description="training"
+            )
+
+        dataloader_params = {
+            "batch_size": self._train_batch_size
+            * self.args.steps_per_generation,  # < this is the change
+            "collate_fn": data_collator,
+            "num_workers": self.args.dataloader_num_workers,
+            "pin_memory": self.args.dataloader_pin_memory,
+            "persistent_workers": self.args.dataloader_persistent_workers,
+        }
+
+        if not isinstance(train_dataset, torch.utils.data.IterableDataset):
+            dataloader_params["sampler"] = self._get_train_sampler()
+            dataloader_params["drop_last"] = self.args.dataloader_drop_last
+            dataloader_params["worker_init_fn"] = partial(
+                seed_worker,
+                num_workers=self.args.dataloader_num_workers,
+                rank=self.args.process_index,
+            )
+            dataloader_params["prefetch_factor"] = self.args.dataloader_prefetch_factor
+
+        return self.accelerator.prepare(DataLoader(train_dataset, **dataloader_params))
+
 
 class AxolotlGRPOSequenceParallelTrainer(AxolotlGRPOTrainer):
     """Extend the base GRPOTrainer for sequence parallelism handling"""