diff --git a/lerobot/scripts/train.py b/lerobot/scripts/train.py
index bd9ddeac..b1d63067 100644
--- a/lerobot/scripts/train.py
+++ b/lerobot/scripts/train.py
@@ -132,10 +132,10 @@ def calculate_online_sample_weight(n_off: int, n_on: int, pc_on: float):
 
 
 def add_episodes_inplace(
-    hf_dataset: datasets.Dataset,
     online_dataset: torch.utils.data.Dataset,
     concat_dataset: torch.utils.data.ConcatDataset,
     sampler: torch.utils.data.WeightedRandomSampler,
+    hf_dataset: datasets.Dataset,
     pc_online_samples: float,
 ):
     """
@@ -145,12 +145,12 @@ def add_episodes_inplace(
     percentage of online samples.
 
     Parameters:
-    - hf_dataset (datasets.Dataset): A Hugging Face dataset containing the new episodes to be added.
     - online_dataset (torch.utils.data.Dataset): The existing online dataset to be updated.
     - concat_dataset (torch.utils.data.ConcatDataset): The concatenated dataset that combines
       offline and online datasets, used for sampling purposes.
     - sampler (torch.utils.data.WeightedRandomSampler): A sampler that will be updated to
       reflect changes in the dataset sizes and specified sampling weights.
+    - hf_dataset (datasets.Dataset): A Hugging Face dataset containing the new episodes to be added.
     - pc_online_samples (float): The target percentage of samples that should come from
       the online dataset during sampling operations.
 
@@ -335,7 +335,7 @@ def train(cfg: dict, out_dir=None, job_name=None):
 
             online_pc_sampling = cfg.get("demo_schedule", 0.5)
             add_episodes_inplace(
-                eval_info["episodes"], online_dataset, concat_dataset, sampler, online_pc_sampling
+                online_dataset, concat_dataset, sampler, eval_info["episodes"], online_pc_sampling
             )
 
         for _ in range(cfg.policy.utd):