diff --git a/src/ptbench/engine/trainer.py b/src/ptbench/engine/trainer.py
index b9d89d93dd241447805a885160d46c658f3bc9c7..38147f843c6ee0c4e93b241f813081f7f6c51d64 100644
--- a/src/ptbench/engine/trainer.py
+++ b/src/ptbench/engine/trainer.py
@@ -64,10 +64,12 @@ def check_gpu(device):
             gpu_constants()
         ), f"Device set to '{device}', but nvidia-smi is not installed"
 
+
 def initialize_lowest_validation_loss(logfile_name, arguments):
-    """Initialize the lowest validation loss from the logfile if it exists and if the training
-    does not start from epoch 0, which means that a previous training session is resumed.
-    
+    """Initialize the lowest validation loss from the logfile if it exists and
+    if the training does not start from epoch 0, which means that a previous
+    training session is resumed.
+
     Parameters
     ----------
 
@@ -80,10 +82,10 @@ def initialize_lowest_validation_loss(logfile_name, arguments):
 
     if arguments["epoch"] != 0 and os.path.exists(logfile_name):
         # Open the CSV file
-        with open(logfile_name, 'r') as file:
+        with open(logfile_name) as file:
             reader = csv.DictReader(file)
             column_name = "validation_loss"
-            
+
             if column_name not in reader.fieldnames:
                 return sys.float_info.max
 
@@ -91,11 +93,14 @@ def initialize_lowest_validation_loss(logfile_name, arguments):
             values = [float(row[column_name]) for row in reader]
 
         lowest_value = min(values)
-        logger.info(f"Found lowest validation error from previous session: {lowest_value}")
+        logger.info(
+            f"Found lowest validation error from previous session: {lowest_value}"
+        )
         return lowest_value
 
     return sys.float_info.max
 
+
 def save_model_summary(output_folder, model):
     """Save a little summary of the model in a txt file.