Tinsae/Finetuning
1
0
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity

attcks

Browse Source
This commit is contained in:
Tinsae
2026-07-08 10:07:39 +02:00
parent eb8060fc05
commit a118a975c1
20 changed files with 287 additions and 22 deletions
Download Patch File Download Diff File Expand all files Collapse all files

12
reports/CertifiedUnlearning/RESNET34/forget.csv
View File

@@ -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
1 accuracy macro_precision macro_recall macro_f1 weighted_precision weighted_recall weighted_f1
364 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
365 0.0125 1.0000 0.0125 0.0247 1.0000 0.0125 0.0247
366 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
367 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
368 0.4375 1.0000 0.4375 0.6087 1.0000 0.4375 0.6087
369 0.3875 1.0000 0.3875 0.5586 1.0000 0.3875 0.5586
370 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
371 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
372 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
373 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
374 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
375 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
376 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
377 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
378 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000

12
reports/CertifiedUnlearning/RESNET34/forget_train.csv
View File

@@ -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
1 accuracy macro_precision macro_recall macro_f1 weighted_precision weighted_recall weighted_f1
364 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
365 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
366 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
367 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
368 0.5062 1.0000 0.5062 0.6722 1.0000 0.5062 0.6722
369 0.4750 1.0000 0.4750 0.6441 1.0000 0.4750 0.6441
370 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
371 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
372 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
373 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
374 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
375 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
376 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
377 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
378 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000

12
reports/CertifiedUnlearning/RESNET34/retain.csv
View File

@@ -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
1 accuracy macro_precision macro_recall macro_f1 weighted_precision weighted_recall weighted_f1
364 0.8730 0.9165 0.8730 0.8827 0.9165 0.8730 0.8827
365 0.9454 0.9470 0.9454 0.9454 0.9470 0.9454 0.9454
366 0.5987 0.7725 0.5987 0.5938 0.7725 0.5987 0.5938
367 0.1961 0.3286 0.1961 0.1473 0.3286 0.1961 0.1473
368 0.9474 0.9490 0.9474 0.9475 0.9490 0.9474 0.9475
369 0.9461 0.9485 0.9461 0.9462 0.9485 0.9461 0.9462
370 0.6309 0.8254 0.6309 0.6278 0.8254 0.6309 0.6278
371 0.9079 0.9297 0.9079 0.9121 0.9297 0.9079 0.9121
372 0.0526 0.0028 0.0526 0.0053 0.0028 0.0526 0.0053
373 0.8928 0.9239 0.8928 0.8992 0.9239 0.8928 0.8992
374 0.9316 0.9375 0.9316 0.9323 0.9375 0.9316 0.9323
375 0.8822 0.9078 0.8822 0.8844 0.9078 0.8822 0.8844
376 0.9053 0.9214 0.9053 0.9081 0.9214 0.9053 0.9081
377 0.0533 0.0343 0.0533 0.0077 0.0343 0.0533 0.0077
378 0.7171 0.8599 0.7171 0.7316 0.8599 0.7171 0.7316

29
reports/CertifiedUnlearning/attack_values.csv
View File

@@ -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
1 target_class parameter_mia_accuracy latent_distance_tell lookalike_accuracy
2 0 0.500000 7.219862 0.979167
3 1 0.500000 3.659238 0.958333
4 2 0.500000 6.939345 0.885417
5 3 0.500000 7.800516 0.989583
6 4 0.500000 6.631370 1.000000
7 5 0.500000 7.557893 0.937500
8 6 0.500000 8.085600 0.937500
9 7 0.500000 7.518537 0.947917
10 8 0.500000 9.040818 0.895833
11 9 0.500000 8.269253 0.968750
12 10 0.500000 5.678658 1.000000
13 11 0.450000 6.800340 1.000000
14 12 0.500000 7.708953 0.937500
15 13 0.500000 6.559650 1.000000
16 14 0.500000 8.420962 0.989583
17 15 0.500000 7.526255 1.000000
18 16 0.500000 6.906671 0.968750
19 17 0.500000 5.499599 0.979167
20 18 0.500000 8.465704 0.979167
21 19 0.500000 5.958429 0.979167
22 0 0.500000 5.903083 0.979167
23 1 0.500000 4.479048 0.947917
24 2 0.500000 4.460630 0.979167
25 3 0.500000 9.916990 1.000000
26 4 0.500000 4.245532 0.979167
27 5 0.500000 5.771674 1.000000
28 6 0.500000 6.300947 0.979167
29 7 0.500000 6.803962 0.979167
30 8 0.500000 9.174347 1.000000
31 9 0.500000 7.843153 0.989583
32 10 0.500000 5.029855 1.000000
33 11 0.500000 7.945799 1.000000