diff --git a/Tune.py b/Tune.py
index 995742e..8d3af6b 100644
--- a/Tune.py
+++ b/Tune.py
@@ -62,6 +62,7 @@ def prepare_data_and_model_environment():
     # get Cuda or CPU.
     device = get_device()
     dataset_name = Set_Name.CASIAFACES
+    # we are changing this sample size if we use CASIA Set
     if dataset_name == Set_Name.CASIAFACES:
         SAMPLE_SIZE = 400
         TRAINING_SAMPLE = 320
@@ -259,7 +260,7 @@ def run_unlearning_and_strategy_eval(env_dict, forget_class_idx, strategy, evalu
 # entry
 if __name__ == "__main__":
 
-    outer_loop = 20
+    outer_loop = 2
 
     inner_loop = CLASS_SIZE
     
@@ -301,7 +302,7 @@ if __name__ == "__main__":
             # WF-Net
             weight_filtration = WeightFiltration(
                 target_class_index=0,      #arch  ResNet18  GoogLeNet/Inception
-                epochs=6,                       #   
+                epochs=8,                       #   
                 lr=250.0, # ResNet18 = 150      #      150        100
                 gamma=0.001,                    #    0.001      
                 lambda_1=30,                 #       25        100
@@ -319,8 +320,8 @@ if __name__ == "__main__":
 
             strategies = [
                 #retrain,
-                linear_filtration,
-                #weight_filtration,
+                #linear_filtration,
+                weight_filtration,
                 #certified_unlearning,
             ]
             suite_runner = UnlearningAttack(arch=ARCH, class_size=CLASS_SIZE)
@@ -341,7 +342,7 @@ if __name__ == "__main__":
                         # if we are finetuning, no need to evaluate base model. 
                         # or may be never when not either!
                         evaluate = not finetuning,
-                        suite_runner=suite_runner
+                        #suite_runner=suite_runner
                     )
 
 
diff --git a/eval/UnlearningAttack.py b/eval/UnlearningAttack.py
index 265046b..8cf8c51 100644
--- a/eval/UnlearningAttack.py
+++ b/eval/UnlearningAttack.py
@@ -195,6 +195,13 @@ class UnlearningAttack:
                     # out
                     out_filtered = out_filtered[:,mask]
                     out_naive = out_naive[:, mask]
+
+                # testin masked
+                mask = torch.ones(out_filtered.shape[1], dtype = torch.bool, device = device)
+                mask[target_class] = False
+                # out
+                out_filtered = out_filtered[:,mask]
+                out_naive = out_naive[:, mask]
                 
                 filtered_logits.append(out_filtered)
                 naive_logits.append(out_naive)
@@ -225,7 +232,7 @@ class UnlearningAttack:
         # load from disk if saved model available
         target_dir = os.path.join("reports", framework_name)
         os.makedirs(target_dir, exist_ok=True)
-        current_log_file = os.path.join(target_dir, "attack_values.csv")
+        current_log_file = os.path.join(target_dir, "values.csv")
         
         if not os.path.exists(current_log_file):
             with open(current_log_file, "w") as f:
diff --git a/reports/CertifiedUnlearning/ResNet/time_metrics.txt b/reports/CertifiedUnlearning/ResNet/time_metrics.txt
index a1537a4..62345b4 100644
--- a/reports/CertifiedUnlearning/ResNet/time_metrics.txt
+++ b/reports/CertifiedUnlearning/ResNet/time_metrics.txt
@@ -364,3 +364,105 @@ execution_time_sec
 395.553217
 395.613947
 395.703417
+399.307575
+398.598795
+396.550026
+395.576438
+395.851829
+395.795415
+395.707795
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+395.741877
+395.777094
+396.006137
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+396.945919
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+395.940873
+395.802436
+395.810863
+399.934530
+396.091092
+395.880035
+395.704713
+402.741850
diff --git a/reports/CertifiedUnlearning/values.csv b/reports/CertifiedUnlearning/values.csv
new file mode 100644
index 0000000..77d6bd3
--- /dev/null
+++ b/reports/CertifiedUnlearning/values.csv
@@ -0,0 +1,103 @@
+target_class, parameter_mia_accuracy, lookalike_accuracy, A-Dist, JS-Dist
+0,0.500000,0.829167, 0.020833, 0.635532
+1,0.500000,0.197917, 0.104167, 0.451290
+2,0.500000,0.454167, 0.093750, 0.492340
+3,0.500000,0.650000, 0.062500, 0.453693
+4,0.500000,0.258333, 0.343750, 0.575972
+5,0.500000,0.585417, 0.281250, 0.562983
+6,0.500000,0.256250, 0.302083, 0.465092
+7,0.500000,0.550000, 0.177083, 0.511510
+8,0.500000,0.331250, 0.072917, 0.473632
+9,0.500000,0.985417, 0.343750, 0.725261
+10,0.500000,1.000000, 0.031250, 0.633027
+11,0.500000,0.820833, 0.208333, 0.578812
+12,0.500000,0.756250, 0.239583, 0.636515
+13,0.500000,0.987500, 0.052083, 0.668559
+14,0.500000,0.270833, 0.010417, 0.467717
+15,0.500000,0.252083, 0.083333, 0.540191
+16,0.500000,0.385417, 0.114583, 0.470983
+17,0.500000,0.322917, 0.135417, 0.487943
+18,0.500000,0.487500, 0.031250, 0.492180
+19,0.500000,0.547917, 0.041667, 0.575168
+0,0.500000,0.950000, 0.208333, 0.655901
+1,0.500000,0.206250, 0.083333, 0.517121
+2,0.500000,0.387500, 0.125000, 0.505111
+3,0.500000,0.827083, 0.166667, 0.552245
+4,0.500000,0.256250, 0.281250, 0.575184
+5,0.500000,0.562500, 0.270833, 0.548510
+6,0.500000,0.252083, 0.270833, 0.532519
+7,0.500000,0.429167, 0.000000, 0.543832
+8,0.500000,0.204167, 0.145833, 0.511732
+9,0.500000,0.437500, 0.052083, 0.558003
+10,0.500000,1.000000, 0.104167, 0.707821
+11,0.500000,0.743750, 0.114583, 0.602524
+12,0.500000,0.477083, 0.125000, 0.515099
+13,0.500000,0.987500, 0.135417, 0.742003
+14,0.500000,0.322917, 0.104167, 0.490033
+15,0.500000,0.329167, 0.041667, 0.540890
+16,0.500000,0.962500, 0.166667, 0.475392
+17,0.500000,0.372917, 0.083333, 0.455598
+18,0.500000,0.527083, 0.072917, 0.537237
+19,0.500000,0.252083, 0.166667, 0.484630
+0,0.500000,0.979167, 0.125000, 0.703407
+1,0.500000,0.116667, 0.177083, 0.500014
+2,0.500000,0.360417, 0.104167, 0.497060
+3,0.500000,0.947917, 0.250000, 0.599938
+4,0.500000,0.283333, 0.312500, 0.582296
+5,0.500000,0.927083, 0.041667, 0.610601
+6,0.500000,0.277083, 0.343750, 0.515391
+7,0.500000,0.495833, 0.041667, 0.470818
+8,0.500000,0.356250, 0.114583, 0.542806
+9,0.500000,0.993750, 0.229167, 0.732571
+10,0.500000,1.000000, 0.052083, 0.632766
+11,0.500000,0.712500, 0.208333, 0.551207
+12,0.500000,0.193750, 0.239583, 0.412040
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+16,0.500000,0.454167, 0.218750, 0.527519
+17,0.500000,0.285417, 0.104167, 0.480010
+18,0.525000,0.666667, 0.166667, 0.539912
+19,0.500000,0.633333, 0.239583, 0.502165
+0,0.500000,0.637500, 0.010417, 0.580623
+1,0.500000,0.202083, 0.135417, 0.490814
+2,0.500000,0.275000, 0.000000, 0.520270
+3,0.500000,0.500000, 0.166667, 0.401563
+4,0.500000,0.597917, 0.062500, 0.588209
+5,0.500000,0.991667, 0.020833, 0.682998
+6,0.500000,0.222917, 0.302083, 0.515843
+7,0.500000,0.281250, 0.156250, 0.557951
+8,0.500000,0.191667, 0.052083, 0.457328
+9,0.500000,0.987500, 0.208333, 0.676620
+10,0.500000,1.000000, 0.166667, 0.723199
+11,0.500000,0.958333, 0.062500, 0.681015
+12,0.500000,0.495833, 0.208333, 0.518211
+13,0.500000,0.993750, 0.062500, 0.696251
+14,0.500000,0.283333, 0.104167, 0.480926
+15,0.500000,0.287500, 0.114583, 0.535151
+16,0.500000,0.704167, 0.218750, 0.475464
+17,0.500000,0.368750, 0.145833, 0.462922
+18,0.518750,0.489583, 0.166667, 0.549473
+19,0.500000,0.366667, 0.093750, 0.511173
+0,0.500000,0.993750, 0.072917, 0.674594
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+2,0.500000,0.200000, 0.083333, 0.554513
+3,0.500000,0.639583, 0.072917, 0.472225
+4,0.500000,0.272917, 0.250000, 0.572284
+5,0.500000,0.995833, 0.125000, 0.645992
+6,0.500000,0.289583, 0.156250, 0.505494
+7,0.500000,0.329167, 0.125000, 0.562745
+8,0.500000,0.506250, 0.072917, 0.586938
+9,0.500000,0.647917, 0.093750, 0.621831
+10,0.500000,1.000000, 0.260417, 0.760782
+11,0.500000,0.708333, 0.104167, 0.595735
+12,0.500000,0.447917, 0.239583, 0.414643
+13,0.500000,0.954167, 0.104167, 0.513961
+14,0.500000,0.318750, 0.208333, 0.476281
+15,0.500000,0.320833, 0.062500, 0.540674
+16,0.500000,0.589583, 0.156250, 0.525595
+17,0.500000,0.295833, 0.052083, 0.456003
+18,0.500000,0.612500, 0.104167, 0.526532
+19,0.500000,0.362500, 0.041667, 0.469123
+0,0.500000,0.852083, 0.145833, 0.652528
+1,0.500000,0.185417, 0.052083, 0.504167
diff --git a/reports/LinearFiltration/RESNET34/forget.csv b/reports/LinearFiltration/RESNET34/forget.csv
index b800a70..a38b4a4 100644
--- a/reports/LinearFiltration/RESNET34/forget.csv
+++ b/reports/LinearFiltration/RESNET34/forget.csv
@@ -471,3 +471,5 @@ 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
diff --git a/reports/LinearFiltration/RESNET34/forget_train.csv b/reports/LinearFiltration/RESNET34/forget_train.csv
index b800a70..a38b4a4 100644
--- a/reports/LinearFiltration/RESNET34/forget_train.csv
+++ b/reports/LinearFiltration/RESNET34/forget_train.csv
@@ -471,3 +471,5 @@ 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
diff --git a/reports/LinearFiltration/RESNET34/retain.csv b/reports/LinearFiltration/RESNET34/retain.csv
index 0776e6f..6ec9300 100644
--- a/reports/LinearFiltration/RESNET34/retain.csv
+++ b/reports/LinearFiltration/RESNET34/retain.csv
@@ -471,3 +471,5 @@ accuracy,macro_precision,macro_recall,macro_f1,weighted_precision,weighted_recal
 0.9520,0.9538,0.9520,0.9523,0.9538,0.9520,0.9523
 0.9539,0.9554,0.9539,0.9542,0.9554,0.9539,0.9542
 0.9526,0.9544,0.9526,0.9529,0.9544,0.9526,0.9529
+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
diff --git a/reports/LinearFiltration/ResNet/time_metrics.txt b/reports/LinearFiltration/ResNet/time_metrics.txt
index 7030728..4a5331a 100644
--- a/reports/LinearFiltration/ResNet/time_metrics.txt
+++ b/reports/LinearFiltration/ResNet/time_metrics.txt
@@ -439,3 +439,5 @@ execution_time_sec
 0.001898
 0.001888
 0.001884
+1.632938
+0.001915
diff --git a/reports/WeightFiltration/RESNET34/forget.csv b/reports/WeightFiltration/RESNET34/forget.csv
index 756987f..15f1c01 100644
--- a/reports/WeightFiltration/RESNET34/forget.csv
+++ b/reports/WeightFiltration/RESNET34/forget.csv
@@ -471,3 +471,45 @@ 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
+0.0125,1.0000,0.0125,0.0247,1.0000,0.0125,0.0247
+0.1375,1.0000,0.1375,0.2418,1.0000,0.1375,0.2418
+0.0125,1.0000,0.0125,0.0247,1.0000,0.0125,0.0247
+0.2125,1.0000,0.2125,0.3505,1.0000,0.2125,0.3505
+0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
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+0.0625,1.0000,0.0625,0.1176,1.0000,0.0625,0.1176
+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 a2e80cd..89555a5 100644
--- a/reports/WeightFiltration/RESNET34/forget_train.csv
+++ b/reports/WeightFiltration/RESNET34/forget_train.csv
@@ -471,3 +471,45 @@ 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
 0.0031,1.0000,0.0031,0.0062,1.0000,0.0031,0.0062
+0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
+0.1219,1.0000,0.1219,0.2173,1.0000,0.1219,0.2173
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+0.0063,1.0000,0.0063,0.0124,1.0000,0.0063,0.0124
+0.0031,1.0000,0.0031,0.0062,1.0000,0.0031,0.0062
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diff --git a/reports/WeightFiltration/RESNET34/retain.csv b/reports/WeightFiltration/RESNET34/retain.csv
index a0fe3fa..555cb93 100644
--- a/reports/WeightFiltration/RESNET34/retain.csv
+++ b/reports/WeightFiltration/RESNET34/retain.csv
@@ -471,3 +471,45 @@ accuracy,macro_precision,macro_recall,macro_f1,weighted_precision,weighted_recal
 0.9559,0.9566,0.9559,0.9560,0.9566,0.9559,0.9560
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diff --git a/reports/WeightFiltration/ResNet/time_metrics.txt b/reports/WeightFiltration/ResNet/time_metrics.txt
index 095c43f..c427901 100644
--- a/reports/WeightFiltration/ResNet/time_metrics.txt
+++ b/reports/WeightFiltration/ResNet/time_metrics.txt
@@ -439,3 +439,148 @@ execution_time_sec
 0.000431
 0.000414
 0.000410
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diff --git a/reports/WeightFiltration/values.csv b/reports/WeightFiltration/values.csv
new file mode 100644
index 0000000..aee9eff
--- /dev/null
+++ b/reports/WeightFiltration/values.csv
@@ -0,0 +1,104 @@
+target_class, parameter_mia_accuracy, lookalike_accuracy, A-Dist, JS-Dist
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