diff --git a/face_swapper/src/models/loss.py b/face_swapper/src/models/loss.py
index 517b88b..01a9d12 100644
--- a/face_swapper/src/models/loss.py
+++ b/face_swapper/src/models/loss.py
@@ -37,7 +37,7 @@ class FaceSwapperLoss:
 		generator_loss_set =\
 		{
 			'loss_adversarial': self.calc_adversarial_loss(discriminator_outputs),
-			'loss_id': self.calc_id_loss(source_tensor, swap_tensor),
+			'loss_identity': self.calc_identity_loss(source_tensor, swap_tensor),
 			'loss_attribute': self.calc_attribute_loss(target_attributes, swap_attributes),
 			'loss_reconstruction': self.calc_reconstruction_loss(swap_tensor, target_tensor, is_same_person)
 		}
@@ -101,11 +101,11 @@ class FaceSwapperLoss:
 		loss_reconstruction = (loss_reconstruction + loss_ssim) * 0.5
 		return loss_reconstruction
 
-	def calc_id_loss(self, source_tensor : VisionTensor, swap_tensor : VisionTensor) -> LossTensor:
+	def calc_identity_loss(self, source_tensor : VisionTensor, swap_tensor : VisionTensor) -> LossTensor:
 		swap_embedding = calc_id_embedding(self.id_embedder, swap_tensor, (30, 0, 10, 10))
 		source_embedding = calc_id_embedding(self.id_embedder, source_tensor, (30, 0, 10, 10))
-		loss_id = (1 - torch.cosine_similarity(source_embedding, swap_embedding)).mean()
-		return loss_id
+		loss_identity = (1 - torch.cosine_similarity(source_embedding, swap_embedding)).mean()
+		return loss_identity
 
 	def calc_pose_loss(self, swap_tensor : VisionTensor, target_tensor : VisionTensor) -> LossTensor:
 		swap_motion_features = self.get_pose_features(swap_tensor)
diff --git a/face_swapper/src/training.py b/face_swapper/src/training.py
index b267d93..fc20ead 100644
--- a/face_swapper/src/training.py
+++ b/face_swapper/src/training.py
@@ -63,10 +63,10 @@ class FaceSwapperTrain(pytorch_lightning.LightningModule, FaceSwapperLoss):
 
 		self.log('loss_generator', generator_losses.get('loss_generator'), prog_bar = True)
 		self.log('loss_discriminator', discriminator_losses.get('loss_discriminator'), prog_bar = True)
-		self.log('loss_adversarial', generator_losses.get('loss_adversarial'), prog_bar = True)
-		self.log('loss_attribute', generator_losses.get('loss_attribute'), prog_bar = True)
-		self.log('loss_id', generator_losses.get('loss_id'), prog_bar = True)
-		self.log('loss_reconstruction', generator_losses.get('loss_reconstruction'), prog_bar = True)
+		self.log('loss_adversarial', generator_losses.get('loss_adversarial'))
+		self.log('loss_attribute', generator_losses.get('loss_attribute'))
+		self.log('loss_identity', generator_losses.get('loss_identity'))
+		self.log('loss_reconstruction', generator_losses.get('loss_reconstruction'))
 		return generator_losses.get('loss_generator')
 
 	def generate_preview(self, source_tensor : VisionTensor, target_tensor : VisionTensor, swap_tensor : VisionTensor) -> None: