diff --git a/src/accelerate/accelerator.py b/src/accelerate/accelerator.py
index a9e976d4a71..cd00cf91b79 100755
--- a/src/accelerate/accelerator.py
+++ b/src/accelerate/accelerator.py
@@ -2795,7 +2795,7 @@ def _inner(folder):
                 schedulers.append(scheduler)
         elif self.distributed_type not in [DistributedType.MEGATRON_LM]:
             schedulers = self._schedulers
-            
+
         # Save the samplers of the dataloaders
         dataloaders = self._dataloaders
 
@@ -2938,7 +2938,7 @@ def _inner(folder):
                 schedulers.append(scheduler)
         elif self.distributed_type not in [DistributedType.MEGATRON_LM]:
             schedulers = self._schedulers
-            
+
         dataloaders = self._dataloaders
 
         # Call model loading hooks that might have been registered with
diff --git a/src/accelerate/checkpointing.py b/src/accelerate/checkpointing.py
index d50aff4c5c5..862182a71d5 100644
--- a/src/accelerate/checkpointing.py
+++ b/src/accelerate/checkpointing.py
@@ -188,12 +188,12 @@ def load_accelerator_state(
         input_scheduler_file = os.path.join(input_dir, scheduler_name)
         scheduler.load_state_dict(torch.load(input_scheduler_file))
     logger.info("All scheduler states loaded successfully")
-    
+
     for i, dataloader in enumerate(dataloaders):
         sampler_name = f"{SAMPLER_NAME}.bin" if i == 0 else f"{SAMPLER_NAME}_{i}.bin"
         input_sampler_file = os.path.join(input_dir, sampler_name)
         dataloader.sampler = torch.load(input_sampler_file)
-    logger.info(f"All dataloader sampler states loaded successfully")
+    logger.info("All dataloader sampler states loaded successfully")
 
     # GradScaler state
     if scaler is not None: