diff --git a/_paramters.py b/_paramters.py
index d81b4ab..7a5258e 100644
--- a/_paramters.py
+++ b/_paramters.py
@@ -35,8 +35,20 @@ main_arg_parser.add_argument("--data_loudness_ratio", type=float, default=0, hel
 main_arg_parser.add_argument("--data_shift_ratio", type=float, default=0, help="")  # 0.3
 main_arg_parser.add_argument("--data_noise_ratio", type=float, default=0, help="")  # 0.4
 main_arg_parser.add_argument("--data_mask_ratio", type=float, default=0, help="")  # 0.2
-main_arg_parser.add_argument("--data_speed_ratio", type=float, default=0, help="")  # 0.3
-main_arg_parser.add_argument("--data_speed_factor", type=float, default=0, help="")  # 0.7
+main_arg_parser.add_argument("--data_speed_ratio", type=float, default=0.3, help="")  # 0.3
+main_arg_parser.add_argument("--data_speed_factor", type=float, default=0.7, help="")  # 0.7
+
+# Model Parameters
+main_arg_parser.add_argument("--model_type", type=str, default="RCC", help="")
+main_arg_parser.add_argument("--model_secondary_type", type=str, default="RCC", help="")
+main_arg_parser.add_argument("--model_weight_init", type=str, default="xavier_normal_", help="")
+main_arg_parser.add_argument("--model_activation", type=str, default="leaky_relu", help="")
+main_arg_parser.add_argument("--model_filters", type=str, default="[32, 64, 128, 64]", help="")
+main_arg_parser.add_argument("--model_classes", type=int, default=2, help="")
+main_arg_parser.add_argument("--model_lat_dim", type=int, default=128, help="")
+main_arg_parser.add_argument("--model_bias", type=strtobool, default=True, help="")
+main_arg_parser.add_argument("--model_norm", type=strtobool, default=True, help="")
+main_arg_parser.add_argument("--model_dropout", type=float, default=0.2, help="")
 
 # Training Parameters
 main_arg_parser.add_argument("--train_outpath", type=str, default="output", help="")
@@ -49,18 +61,6 @@ main_arg_parser.add_argument("--train_batch_size", type=int, default=300, help="
 main_arg_parser.add_argument("--train_lr", type=float, default=1e-4, help="")
 main_arg_parser.add_argument("--train_num_sanity_val_steps", type=int, default=0, help="")
 
-# Model Parameters
-main_arg_parser.add_argument("--model_type", type=str, default="CC", help="")
-main_arg_parser.add_argument("--model_secondary_type", type=str, default="CC", help="")
-main_arg_parser.add_argument("--model_weight_init", type=str, default="xavier_normal_", help="")
-main_arg_parser.add_argument("--model_activation", type=str, default="leaky_relu", help="")
-main_arg_parser.add_argument("--model_filters", type=str, default="[32, 64, 128, 64]", help="")
-main_arg_parser.add_argument("--model_classes", type=int, default=2, help="")
-main_arg_parser.add_argument("--model_lat_dim", type=int, default=128, help="")
-main_arg_parser.add_argument("--model_bias", type=strtobool, default=True, help="")
-main_arg_parser.add_argument("--model_norm", type=strtobool, default=True, help="")
-main_arg_parser.add_argument("--model_dropout", type=float, default=0.2, help="")
-
 # Project Parameters
 main_arg_parser.add_argument("--project_name", type=str, default=_ROOT.name, help="")
 main_arg_parser.add_argument("--project_owner", type=str, default='si11ium', help="")
diff --git a/main_inference.py b/main_inference.py
index f10f4bf..9a034c3 100644
--- a/main_inference.py
+++ b/main_inference.py
@@ -34,10 +34,9 @@ def prepare_dataloader(config_obj):
     transforms = Compose([NormalizeLocal(), ToTensor()])
     aug_transforms = Compose([
             NoiseInjection(0.4),
-            LoudnessManipulator(0),
-            ShiftTime(0),
-            MaskAug(0),
-        # Utility
+            LoudnessManipulator(0.4),
+            ShiftTime(0.3),
+            MaskAug(0.2),
         NormalizeLocal(), ToTensor()
     ])
 
@@ -73,8 +72,9 @@ if __name__ == '__main__':
     p = Plotter(outpath)
     from matplotlib import pyplot as plt
 
-    d = test_dataloader.dataset[0][0].squeeze()
+    d = test_dataloader.dataset[100][0].squeeze()
     plt.imshow(d)
+    p.save_current_figure('100')
 
     loaded_model = restore_logger_and_model(config)
     loaded_model.eval()