diff --git a/face_swapper/src/data_loader.py b/face_swapper/src/dataset.py
similarity index 98%
rename from face_swapper/src/data_loader.py
rename to face_swapper/src/dataset.py
index 7410c09..2d42149 100644
--- a/face_swapper/src/data_loader.py
+++ b/face_swapper/src/dataset.py
@@ -9,7 +9,7 @@ from torchvision import transforms
 from .types import Batch
 
 
-class DataLoader(Dataset[Tensor]):
+class DynamicDataset(Dataset[Tensor]):
 	def __init__(self, file_pattern : str, same_person_probability : float) -> None:
 		self.same_person_probability = same_person_probability
 		self.file_paths = glob.glob(file_pattern)
diff --git a/face_swapper/src/training.py b/face_swapper/src/training.py
index ecc70b6..4e2b970 100644
--- a/face_swapper/src/training.py
+++ b/face_swapper/src/training.py
@@ -12,7 +12,7 @@ from torch import Tensor, nn
 from torch.optim import Optimizer
 from torch.utils.data import DataLoader as TorchDataLoader, Dataset, random_split
 
-from .data_loader import DataLoader
+from .dataset import DynamicDataset
 from .helper import calc_id_embedding
 from .models.discriminator import Discriminator
 from .models.generator import Generator
@@ -145,7 +145,7 @@ def train() -> None:
 	same_person_probability = CONFIG.getfloat('training.dataset', 'same_person_probability')
 	output_resume_path = CONFIG.get('training.output', 'resume_path')
 
-	dataset = DataLoader(dataset_file_pattern, same_person_probability)
+	dataset = DynamicDataset(dataset_file_pattern, same_person_probability)
 	training_loader, validation_loader = create_loaders(dataset)
 	face_swapper_trainer = FaceSwapperTrainer()
 	trainer = create_trainer()