diff --git a/embedding_converter/src/training.py b/embedding_converter/src/training.py
index a492df9..91aea51 100644
--- a/embedding_converter/src/training.py
+++ b/embedding_converter/src/training.py
@@ -121,7 +121,7 @@ def create_trainer() -> Trainer:
 
 
 def train() -> None:
-	config : ConfigSet =\
+	config_set : ConfigSet =\
 	{
 		'dataset':
 		{
@@ -133,7 +133,7 @@ def train() -> None:
 			'target_path': CONFIG.get('training.model', 'target_path'),
 			'learning_rate': CONFIG.getfloat('training.trainer', 'learning_rate')
 		},
-		'common':
+		'output':
 		{
 			'resume_path': CONFIG.get('training.output', 'resume_path')
 		}
@@ -142,12 +142,12 @@ def train() -> None:
 	if torch.cuda.is_available():
 		torch.set_float32_matmul_precision('high')
 
-	dataset = StaticDataset(config.get('dataset'))
+	dataset = StaticDataset(config_set.get('dataset'))
 	training_loader, validation_loader = create_loaders(dataset)
-	embedding_converter_trainer = EmbeddingConverterTrainer(config.get('trainer'))
+	embedding_converter_trainer = EmbeddingConverterTrainer(config_set.get('trainer'))
 	trainer = create_trainer()
 
-	if os.path.exists(config.get('common').get('resume_path')):
-		trainer.fit(embedding_converter_trainer, training_loader, validation_loader, ckpt_path = config.get('common').get('resume_path'))
+	if os.path.exists(config_set.get('output').get('resume_path')):
+		trainer.fit(embedding_converter_trainer, training_loader, validation_loader, ckpt_path = config_set.get('output').get('resume_path'))
 	else:
 		trainer.fit(embedding_converter_trainer, training_loader, validation_loader)