diff --git a/Tune_new.py b/Tune_new.py
index 98b7c66..14228f3 100644
--- a/Tune_new.py
+++ b/Tune_new.py
@@ -290,15 +290,15 @@ def run_unlearning_and_strategy_eval(env_dict, forget_class_idx, strategy, evalu
             base_shadow_instance=shadow_model,  
             device=device
         )
-    else:
+    
 
-        # Define validation tracking steps dynamically
-        evaluation_domains = [
-            {"loader": retain_test_loader, "mode": "retain", "label": "\n--- Performance on Retained Classes"},
-            {"loader": forget_test_loader, "mode": "forget", "label": "\n--- Performance on Forgotten Class"},
-            {"loader": forget_train_loader, "mode": "forget_train", "label": "\n--- Performance on Forgotten Class (Train Set - Verifying Unlearning)"}
-        ]
-        log_metrics(evaluation_domains, reloaded, strategy_in_use)
+    # Define validation tracking steps dynamically
+    evaluation_domains = [
+        {"loader": retain_test_loader, "mode": "retain", "label": "\n--- Performance on Retained Classes"},
+        {"loader": forget_test_loader, "mode": "forget", "label": "\n--- Performance on Forgotten Class"},
+        {"loader": forget_train_loader, "mode": "forget_train", "label": "\n--- Performance on Forgotten Class (Train Set - Verifying Unlearning)"}
+    ]
+    log_metrics(evaluation_domains, reloaded, strategy_in_use)
 
 
 # entry
@@ -384,7 +384,7 @@ if __name__ == "__main__":
                         strategy=strategy,
                         # if we are finetuning, no need to evaluate base model. 
                         # or may be never when not either!
-                        evaluate = False,
+                        evaluate = not finetuning,
                         suite_runner=suite_runner
                     )
                 # just a single class run before running all remaining classes.
diff --git a/architectures/Model.py b/architectures/Model.py
index 4b5653e..094d76e 100644
--- a/architectures/Model.py
+++ b/architectures/Model.py
@@ -24,18 +24,7 @@ class Model(ABC):
         pass
 
     '''
-    Have to have a new param here as mode, for example it would be base, or retrain
-    param mode = "base" or "retrain"
-    that way I can save time it takes to train and retrain.
-    file would be solved with Util functions
-    log_file = Path(f"reports/{mode}/{self.__class__.__name__}/time_metrics.txt")
-    Util._initialize_log_file(log_file):
-    strt = time.perf_counter()
-    end = time.perf_counter()
-    and then save logs
-    execution_time = end -strt
-    Util.log_metric(log_file, execution_time: float):
-
+   
     '''
     def train(self, epochs, loader, rate, mode = "retrain"):
         criterion = nn.CrossEntropyLoss()
diff --git a/reports/CertifiedUnlearning/RESNET34/forget.csv b/reports/CertifiedUnlearning/RESNET34/forget.csv
index e065a79..74d6ea6 100644
--- a/reports/CertifiedUnlearning/RESNET34/forget.csv
+++ b/reports/CertifiedUnlearning/RESNET34/forget.csv
@@ -364,3 +364,15 @@ accuracy,macro_precision,macro_recall,macro_f1,weighted_precision,weighted_recal
 0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
 0.0125,1.0000,0.0125,0.0247,1.0000,0.0125,0.0247
 0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
+0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
+0.4375,1.0000,0.4375,0.6087,1.0000,0.4375,0.6087
+0.3875,1.0000,0.3875,0.5586,1.0000,0.3875,0.5586
+0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
+0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
+0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
+0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
+0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
+0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
+0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
+0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
+0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
diff --git a/reports/CertifiedUnlearning/RESNET34/forget_train.csv b/reports/CertifiedUnlearning/RESNET34/forget_train.csv
index 3d29e2c..0bbc84a 100644
--- a/reports/CertifiedUnlearning/RESNET34/forget_train.csv
+++ b/reports/CertifiedUnlearning/RESNET34/forget_train.csv
@@ -364,3 +364,15 @@ accuracy,macro_precision,macro_recall,macro_f1,weighted_precision,weighted_recal
 0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
 0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
 0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
+0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
+0.5062,1.0000,0.5062,0.6722,1.0000,0.5062,0.6722
+0.4750,1.0000,0.4750,0.6441,1.0000,0.4750,0.6441
+0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
+0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
+0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
+0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
+0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
+0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
+0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
+0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
+0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
diff --git a/reports/CertifiedUnlearning/RESNET34/retain.csv b/reports/CertifiedUnlearning/RESNET34/retain.csv
index eb83522..632b1c2 100644
--- a/reports/CertifiedUnlearning/RESNET34/retain.csv
+++ b/reports/CertifiedUnlearning/RESNET34/retain.csv
@@ -364,3 +364,15 @@ accuracy,macro_precision,macro_recall,macro_f1,weighted_precision,weighted_recal
 0.8730,0.9165,0.8730,0.8827,0.9165,0.8730,0.8827
 0.9454,0.9470,0.9454,0.9454,0.9470,0.9454,0.9454
 0.5987,0.7725,0.5987,0.5938,0.7725,0.5987,0.5938
+0.1961,0.3286,0.1961,0.1473,0.3286,0.1961,0.1473
+0.9474,0.9490,0.9474,0.9475,0.9490,0.9474,0.9475
+0.9461,0.9485,0.9461,0.9462,0.9485,0.9461,0.9462
+0.6309,0.8254,0.6309,0.6278,0.8254,0.6309,0.6278
+0.9079,0.9297,0.9079,0.9121,0.9297,0.9079,0.9121
+0.0526,0.0028,0.0526,0.0053,0.0028,0.0526,0.0053
+0.8928,0.9239,0.8928,0.8992,0.9239,0.8928,0.8992
+0.9316,0.9375,0.9316,0.9323,0.9375,0.9316,0.9323
+0.8822,0.9078,0.8822,0.8844,0.9078,0.8822,0.8844
+0.9053,0.9214,0.9053,0.9081,0.9214,0.9053,0.9081
+0.0533,0.0343,0.0533,0.0077,0.0343,0.0533,0.0077
+0.7171,0.8599,0.7171,0.7316,0.8599,0.7171,0.7316
diff --git a/reports/CertifiedUnlearning/attack_values.csv b/reports/CertifiedUnlearning/attack_values.csv
index 6424bd7..b3c2a69 100644
--- a/reports/CertifiedUnlearning/attack_values.csv
+++ b/reports/CertifiedUnlearning/attack_values.csv
@@ -2,3 +2,32 @@ target_class,parameter_mia_accuracy,latent_distance_tell,lookalike_accuracy
 0,0.500000,7.219862,0.979167
 1,0.500000,3.659238,0.958333
 2,0.500000,6.939345,0.885417
+3,0.500000,7.800516,0.989583
+4,0.500000,6.631370,1.000000
+5,0.500000,7.557893,0.937500
+6,0.500000,8.085600,0.937500
+7,0.500000,7.518537,0.947917
+8,0.500000,9.040818,0.895833
+9,0.500000,8.269253,0.968750
+10,0.500000,5.678658,1.000000
+11,0.450000,6.800340,1.000000
+12,0.500000,7.708953,0.937500
+13,0.500000,6.559650,1.000000
+14,0.500000,8.420962,0.989583
+15,0.500000,7.526255,1.000000
+16,0.500000,6.906671,0.968750
+17,0.500000,5.499599,0.979167
+18,0.500000,8.465704,0.979167
+19,0.500000,5.958429,0.979167
+0,0.500000,5.903083,0.979167
+1,0.500000,4.479048,0.947917
+2,0.500000,4.460630,0.979167
+3,0.500000,9.916990,1.000000
+4,0.500000,4.245532,0.979167
+5,0.500000,5.771674,1.000000
+6,0.500000,6.300947,0.979167
+7,0.500000,6.803962,0.979167
+8,0.500000,9.174347,1.000000
+9,0.500000,7.843153,0.989583
+10,0.500000,5.029855,1.000000
+11,0.500000,7.945799,1.000000
diff --git a/reports/LinearFiltration/RESNET34/forget.csv b/reports/LinearFiltration/RESNET34/forget.csv
index 45c6fca..902dc21 100644
--- a/reports/LinearFiltration/RESNET34/forget.csv
+++ b/reports/LinearFiltration/RESNET34/forget.csv
@@ -436,3 +436,17 @@ accuracy,macro_precision,macro_recall,macro_f1,weighted_precision,weighted_recal
 0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
 0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
 0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
+0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
+0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
+0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
+0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
+0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
+0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
+0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
+0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
+0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
+0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
+0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
+0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
+0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
+0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
diff --git a/reports/LinearFiltration/RESNET34/forget_train.csv b/reports/LinearFiltration/RESNET34/forget_train.csv
index 45c6fca..902dc21 100644
--- a/reports/LinearFiltration/RESNET34/forget_train.csv
+++ b/reports/LinearFiltration/RESNET34/forget_train.csv
@@ -436,3 +436,17 @@ accuracy,macro_precision,macro_recall,macro_f1,weighted_precision,weighted_recal
 0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
 0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
 0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
+0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
+0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
+0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
+0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
+0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
+0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
+0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
+0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
+0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
+0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
+0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
+0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
+0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
+0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
diff --git a/reports/LinearFiltration/RESNET34/retain.csv b/reports/LinearFiltration/RESNET34/retain.csv
index ee8e76b..8f966b4 100644
--- a/reports/LinearFiltration/RESNET34/retain.csv
+++ b/reports/LinearFiltration/RESNET34/retain.csv
@@ -436,3 +436,17 @@ accuracy,macro_precision,macro_recall,macro_f1,weighted_precision,weighted_recal
 0.9546,0.9556,0.9546,0.9547,0.9556,0.9546,0.9547
 0.9533,0.9543,0.9533,0.9534,0.9543,0.9533,0.9534
 0.9533,0.9543,0.9533,0.9534,0.9543,0.9533,0.9534
+0.9526,0.9541,0.9526,0.9529,0.9541,0.9526,0.9529
+0.9526,0.9541,0.9526,0.9529,0.9541,0.9526,0.9529
+0.9533,0.9551,0.9533,0.9536,0.9551,0.9533,0.9536
+0.9533,0.9545,0.9533,0.9535,0.9545,0.9533,0.9535
+0.9546,0.9562,0.9546,0.9548,0.9562,0.9546,0.9548
+0.9553,0.9570,0.9553,0.9555,0.9570,0.9553,0.9555
+0.9566,0.9581,0.9566,0.9568,0.9581,0.9566,0.9568
+0.9553,0.9568,0.9553,0.9555,0.9568,0.9553,0.9555
+0.9513,0.9532,0.9513,0.9516,0.9532,0.9513,0.9516
+0.9539,0.9556,0.9539,0.9542,0.9556,0.9539,0.9542
+0.9520,0.9539,0.9520,0.9523,0.9539,0.9520,0.9523
+0.9533,0.9547,0.9533,0.9535,0.9547,0.9533,0.9535
+0.9546,0.9561,0.9546,0.9549,0.9561,0.9546,0.9549
+0.9513,0.9531,0.9513,0.9516,0.9531,0.9513,0.9516
diff --git a/reports/LinearFiltration/attack_values.csv b/reports/LinearFiltration/attack_values.csv
index 550e4c3..3f03843 100644
--- a/reports/LinearFiltration/attack_values.csv
+++ b/reports/LinearFiltration/attack_values.csv
@@ -3,3 +3,33 @@ target_class,parameter_mia_accuracy,latent_distance_tell,lookalike_accuracy
 1,0.500000,3.573733,1.000000
 2,0.500000,3.924550,1.000000
 3,0.500000,3.515182,1.000000
+4,0.500000,3.369485,1.000000
+5,0.500000,4.697085,1.000000
+6,0.500000,4.185269,1.000000
+7,0.500000,3.473583,1.000000
+8,0.500000,4.518519,1.000000
+9,0.500000,4.484542,1.000000
+10,0.500000,3.353875,1.000000
+11,0.500000,3.815037,0.989583
+12,0.500000,3.493994,1.000000
+13,0.500000,4.018041,1.000000
+14,0.500000,4.059689,1.000000
+15,0.500000,4.097189,1.000000
+16,0.500000,3.287521,1.000000
+17,0.500000,3.872488,1.000000
+18,0.500000,3.698952,0.989583
+19,0.500000,3.844830,0.989583
+0,0.500000,3.413494,1.000000
+0,0.500000,3.416399,1.000000
+1,0.500000,3.396268,1.000000
+2,0.500000,3.648122,1.000000
+3,0.500000,3.889339,0.989583
+4,0.500000,3.408539,1.000000
+5,0.500000,4.625342,1.000000
+6,0.500000,3.925502,0.989583
+7,0.500000,3.033561,0.989583
+8,0.500000,3.819170,0.989583
+9,0.500000,4.497495,1.000000
+10,0.500000,3.701839,1.000000
+11,0.500000,4.369391,0.989583
+12,0.500000,3.945474,1.000000
diff --git a/reports/Retrain/RESNET34/forget.csv b/reports/Retrain/RESNET34/forget.csv
index cbf5469..7b97a60 100644
--- a/reports/Retrain/RESNET34/forget.csv
+++ b/reports/Retrain/RESNET34/forget.csv
@@ -66,3 +66,17 @@ accuracy,macro_precision,macro_recall,macro_f1,weighted_precision,weighted_recal
 0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
 0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
 0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
+0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
+0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
+0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
+0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
+0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
+0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
+0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
+0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
+0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
+0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
+0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
+0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
+0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
+0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
diff --git a/reports/Retrain/RESNET34/forget_train.csv b/reports/Retrain/RESNET34/forget_train.csv
index cbf5469..7b97a60 100644
--- a/reports/Retrain/RESNET34/forget_train.csv
+++ b/reports/Retrain/RESNET34/forget_train.csv
@@ -66,3 +66,17 @@ accuracy,macro_precision,macro_recall,macro_f1,weighted_precision,weighted_recal
 0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
 0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
 0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
+0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
+0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
+0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
+0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
+0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
+0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
+0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
+0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
+0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
+0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
+0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
+0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
+0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
+0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
diff --git a/reports/Retrain/RESNET34/retain.csv b/reports/Retrain/RESNET34/retain.csv
index 40b40fc..4ef5e70 100644
--- a/reports/Retrain/RESNET34/retain.csv
+++ b/reports/Retrain/RESNET34/retain.csv
@@ -66,3 +66,17 @@ accuracy,macro_precision,macro_recall,macro_f1,weighted_precision,weighted_recal
 0.9533,0.9543,0.9533,0.9534,0.9543,0.9533,0.9534
 0.9586,0.9599,0.9586,0.9588,0.9599,0.9586,0.9588
 0.9612,0.9620,0.9612,0.9613,0.9620,0.9612,0.9613
+0.9559,0.9571,0.9559,0.9560,0.9571,0.9559,0.9560
+0.9559,0.9571,0.9559,0.9560,0.9571,0.9559,0.9560
+0.9507,0.9518,0.9507,0.9507,0.9518,0.9507,0.9507
+0.9612,0.9622,0.9612,0.9612,0.9622,0.9612,0.9612
+0.9553,0.9561,0.9553,0.9552,0.9561,0.9553,0.9552
+0.9618,0.9626,0.9618,0.9618,0.9626,0.9618,0.9618
+0.9566,0.9586,0.9566,0.9569,0.9586,0.9566,0.9569
+0.9533,0.9548,0.9533,0.9535,0.9548,0.9533,0.9535
+0.9539,0.9548,0.9539,0.9541,0.9548,0.9539,0.9541
+0.9500,0.9511,0.9500,0.9500,0.9511,0.9500,0.9500
+0.9566,0.9572,0.9566,0.9565,0.9572,0.9566,0.9565
+0.9546,0.9554,0.9546,0.9546,0.9554,0.9546,0.9546
+0.9612,0.9620,0.9612,0.9613,0.9620,0.9612,0.9613
+0.9539,0.9551,0.9539,0.9540,0.9551,0.9539,0.9540
diff --git a/reports/Retrain/attack_values.csv b/reports/Retrain/attack_values.csv
index b0518af..382b135 100644
--- a/reports/Retrain/attack_values.csv
+++ b/reports/Retrain/attack_values.csv
@@ -3,3 +3,33 @@ target_class,parameter_mia_accuracy,latent_distance_tell,lookalike_accuracy
 1,0.500000,12.793120,0.000000
 2,0.500000,12.951434,0.000000
 3,0.500000,10.942259,0.000000
+4,0.500000,10.675704,0.000000
+5,0.500000,13.046491,0.000000
+6,0.500000,11.343709,0.000000
+7,0.500000,10.020437,0.000000
+8,0.500000,12.896643,0.000000
+9,0.500000,12.220088,0.000000
+10,0.500000,11.315407,0.000000
+11,0.450000,10.556920,0.000000
+12,0.500000,10.925443,0.000000
+13,0.500000,12.007375,0.000000
+14,0.500000,11.471087,0.000000
+15,0.500000,12.301955,0.000000
+16,0.500000,10.831913,0.000000
+17,0.500000,10.942777,0.000000
+18,0.500000,11.699934,0.000000
+19,0.500000,12.526654,0.000000
+0,0.500000,11.601441,0.000000
+0,0.500000,11.639872,0.000000
+1,0.500000,12.723348,0.000000
+2,0.500000,13.151769,0.000000
+3,0.500000,10.969514,0.000000
+4,0.500000,10.674448,0.000000
+5,0.500000,13.068334,0.000000
+6,0.500000,11.328772,0.000000
+7,0.500000,9.926997,0.000000
+8,0.500000,12.859781,0.000000
+9,0.500000,12.061253,0.000000
+10,0.500000,11.358070,0.000000
+11,0.500000,10.484346,0.000000
+12,0.500000,10.926878,0.000000
diff --git a/reports/WeightFiltration/RESNET34/forget.csv b/reports/WeightFiltration/RESNET34/forget.csv
index 8804daa..0eae8ef 100644
--- a/reports/WeightFiltration/RESNET34/forget.csv
+++ b/reports/WeightFiltration/RESNET34/forget.csv
@@ -527,3 +527,15 @@ accuracy,macro_precision,macro_recall,macro_f1,weighted_precision,weighted_recal
 0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
 0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
 0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
+0.0375,1.0000,0.0375,0.0723,1.0000,0.0375,0.0723
+0.1750,1.0000,0.1750,0.2979,1.0000,0.1750,0.2979
+0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
+0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
+0.0375,1.0000,0.0375,0.0723,1.0000,0.0375,0.0723
+0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
+0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
+0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
+0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
+0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
+0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
+0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
diff --git a/reports/WeightFiltration/RESNET34/forget_train.csv b/reports/WeightFiltration/RESNET34/forget_train.csv
index d15d79a..b5f4f81 100644
--- a/reports/WeightFiltration/RESNET34/forget_train.csv
+++ b/reports/WeightFiltration/RESNET34/forget_train.csv
@@ -527,3 +527,15 @@ accuracy,macro_precision,macro_recall,macro_f1,weighted_precision,weighted_recal
 0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
 0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
 0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
+0.0375,1.0000,0.0375,0.0723,1.0000,0.0375,0.0723
+0.2281,1.0000,0.2281,0.3715,1.0000,0.2281,0.3715
+0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
+0.0094,1.0000,0.0094,0.0186,1.0000,0.0094,0.0186
+0.0094,1.0000,0.0094,0.0186,1.0000,0.0094,0.0186
+0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
+0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
+0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
+0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
+0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
+0.0063,1.0000,0.0063,0.0124,1.0000,0.0063,0.0124
+0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
diff --git a/reports/WeightFiltration/RESNET34/retain.csv b/reports/WeightFiltration/RESNET34/retain.csv
index 00bdf44..f30418e 100644
--- a/reports/WeightFiltration/RESNET34/retain.csv
+++ b/reports/WeightFiltration/RESNET34/retain.csv
@@ -527,3 +527,15 @@ accuracy,macro_precision,macro_recall,macro_f1,weighted_precision,weighted_recal
 0.9546,0.9558,0.9546,0.9547,0.9558,0.9546,0.9547
 0.9526,0.9540,0.9526,0.9528,0.9540,0.9526,0.9528
 0.9526,0.9540,0.9526,0.9528,0.9540,0.9526,0.9528
+0.9520,0.9541,0.9520,0.9524,0.9541,0.9520,0.9524
+0.9520,0.9542,0.9520,0.9524,0.9542,0.9520,0.9524
+0.9507,0.9515,0.9507,0.9507,0.9515,0.9507,0.9507
+0.9533,0.9548,0.9533,0.9535,0.9548,0.9533,0.9535
+0.9566,0.9583,0.9566,0.9569,0.9583,0.9566,0.9569
+0.9572,0.9588,0.9572,0.9574,0.9588,0.9572,0.9574
+0.9533,0.9551,0.9533,0.9536,0.9551,0.9533,0.9536
+0.9487,0.9518,0.9487,0.9493,0.9518,0.9487,0.9493
+0.9546,0.9559,0.9546,0.9547,0.9559,0.9546,0.9547
+0.9520,0.9534,0.9520,0.9522,0.9534,0.9520,0.9522
+0.9539,0.9554,0.9539,0.9542,0.9554,0.9539,0.9542
+0.9539,0.9559,0.9539,0.9543,0.9559,0.9539,0.9543
diff --git a/reports/WeightFiltration/attack_values.csv b/reports/WeightFiltration/attack_values.csv
index bc7b05e..0d2b8d7 100644
--- a/reports/WeightFiltration/attack_values.csv
+++ b/reports/WeightFiltration/attack_values.csv
@@ -3,3 +3,33 @@ target_class,parameter_mia_accuracy,latent_distance_tell,lookalike_accuracy
 1,0.500000,1.279257,0.968750
 2,0.500000,1.717911,0.937500
 3,0.500000,1.354225,0.989583
+4,0.500000,1.308562,0.968750
+5,0.500000,2.087495,0.947917
+6,0.500000,1.793863,0.927083
+7,0.500000,1.213634,0.937500
+8,0.500000,1.705230,0.979167
+9,0.500000,1.713113,0.979167
+10,0.500000,1.358761,0.968750
+11,0.500000,1.485312,1.000000
+12,0.500000,1.393625,0.947917
+13,0.500000,1.677361,0.947917
+14,0.500000,1.734759,0.906250
+15,0.500000,1.715959,0.968750
+16,0.500000,1.180073,0.947917
+17,0.500000,1.597037,0.947917
+18,0.500000,1.491600,0.947917
+19,0.500000,1.622301,0.968750
+0,0.500000,1.562955,0.968750
+0,0.500000,1.526132,0.979167
+1,0.500000,1.323757,0.968750
+2,0.500000,1.493928,0.958333
+3,0.500000,1.643880,0.989583
+4,0.500000,1.479018,0.989583
+5,0.500000,2.176565,0.958333
+6,0.500000,1.620670,0.958333
+7,0.500000,0.977823,0.937500
+8,0.500000,1.455012,0.968750
+9,0.500000,2.145126,0.989583
+10,0.500000,1.905214,0.895833
+11,0.500000,2.171935,0.958333
+12,0.500000,1.761187,0.937500
diff --git a/reports/base/RESNET34/Finetuned.csv b/reports/base/RESNET34/Finetuned.csv
index 14ac68b..34f3e61 100644
--- a/reports/base/RESNET34/Finetuned.csv
+++ b/reports/base/RESNET34/Finetuned.csv
@@ -52,3 +52,4 @@ accuracy,macro_precision,macro_recall,macro_f1,weighted_precision,weighted_recal
 0.9581,0.9590,0.9581,0.9581,0.9590,0.9581,0.9581
 0.9513,0.9525,0.9512,0.9514,0.9525,0.9513,0.9514
 0.9531,0.9541,0.9531,0.9532,0.9541,0.9531,0.9532
+0.9525,0.9542,0.9525,0.9528,0.9542,0.9525,0.9528
diff --git a/unlearning/WeightFiltration.py b/unlearning/WeightFiltration.py
index f557179..a352487 100644
--- a/unlearning/WeightFiltration.py
+++ b/unlearning/WeightFiltration.py
@@ -126,7 +126,7 @@ class WeightFiltration(Strategy):
             print(f"Gating matrix loaded. Switching layout to target class index: {self.target_class_index}")
             self.wf_model.target_class_index = self.target_class_index
             
-        return self.wf_model.get()
+        return self.wf_model
     
     def _split_data(self, dataset):
         return vertical_split(