diff --git a/use-cases/eurac/trainer.py b/use-cases/eurac/trainer.py
index abe85471..88ac42f5 100644
--- a/use-cases/eurac/trainer.py
+++ b/use-cases/eurac/trainer.py
@@ -29,6 +29,7 @@
 from itwinai.torch.type import Metric
 from itwinai.torch.profiling.profiler import profile_torch_trainer
 
+
 class RNNDistributedTrainer(TorchTrainer):
     """Trainer class for RNN model using pytorch.
 
@@ -90,13 +91,12 @@ def __init__(
         )
         self.save_parameters(**self.locals2params(locals()))
 
-
     @suppress_workers_print
     @profile_torch_trainer
     def execute(
-        self, 
-        train_dataset: Dataset, 
-        validation_dataset: Optional[Dataset] = None, 
+        self,
+        train_dataset: Dataset,
+        validation_dataset: Optional[Dataset] = None,
         test_dataset: Optional[Dataset] = None
     ) -> Tuple[Dataset, Dataset, Dataset, Any]:
         return super().execute(train_dataset, validation_dataset, test_dataset)
@@ -138,8 +138,8 @@ def create_model_loss_optimizer(self) -> None:
             **distribute_kwargs,
         )
 
-    def set_epoch(self, epoch: int): 
-        if self.profiler is not None: 
+    def set_epoch(self, epoch: int):
+        if self.profiler is not None:
             self.profiler.step()
 
         if self.strategy.is_distributed:
@@ -180,7 +180,6 @@ def train(self):
         for epoch in tqdm(range(self.epochs)):
             epoch_start_time = timer()
             self.set_epoch(epoch)
-
             self.model.train()
 
             # set time indices for training
@@ -386,7 +385,6 @@ def create_model_loss_optimizer(self) -> None:
             patience=self.config.lr_reduction_patience
         )
 
-
         target_weights = {
             t: 1 / len(self.config.target_names) for t in self.config.target_names
         }
@@ -507,7 +505,7 @@ def create_dataloaders(self, train_dataset, validation_dataset, test_dataset):
             processing=(
                 "multi-gpu" if self.config.distributed else "single-gpu"
             ),
-        )  
+        )
 
         val_sampler_builder = SamplerBuilder(
             validation_dataset,
diff --git a/use-cases/virgo/trainer.py b/use-cases/virgo/trainer.py
index 8226e070..5fd2a3f9 100644
--- a/use-cases/virgo/trainer.py
+++ b/use-cases/virgo/trainer.py
@@ -43,7 +43,7 @@ def __init__(
     ) -> None:
         super().__init__(
             epochs=num_epochs,
-            config={},
+            config=config,
             strategy=strategy,
             logger=logger,
             random_seed=random_seed,