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

cleaned up for submission

Browse Source
This commit is contained in:
Tinsae
2026-07-10 20:13:13 +02:00
parent 47fbb19761
commit 7eff030e89
38 changed files with 39 additions and 4175 deletions
Download Patch File Download Diff File Expand all files Collapse all files

29
reports/CertifiedUnlearning/RESNET34/forget.csv
View File

@@ -471,32 +471,3 @@ 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
0.1500,1.0000,0.1500,0.2609,1.0000,0.1500,0.2609
0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
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
0.0250,1.0000,0.0250,0.0488,1.0000,0.0250,0.0488
0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
0.1125,1.0000,0.1125,0.2022,1.0000,0.1125,0.2022
1 accuracy macro_precision macro_recall macro_f1 weighted_precision weighted_recall weighted_f1
471 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
472 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
473 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
0.1500 1.0000 0.1500 0.2609 1.0000 0.1500 0.2609
0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
0.0000 0.0000 0.0000 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
0.0250 1.0000 0.0250 0.0488 1.0000 0.0250 0.0488
0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
0.1125 1.0000 0.1125 0.2022 1.0000 0.1125 0.2022

29
reports/CertifiedUnlearning/RESNET34/forget_train.csv
View File

@@ -471,32 +471,3 @@ 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
0.0250,1.0000,0.0250,0.0488,1.0000,0.0250,0.0488
0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
0.1031,1.0000,0.1031,0.1870,1.0000,0.1031,0.1870
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
0.0656,1.0000,0.0656,0.1232,1.0000,0.0656,0.1232
0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
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
0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
0.0875,1.0000,0.0875,0.1609,1.0000,0.0875,0.1609
1 accuracy macro_precision macro_recall macro_f1 weighted_precision weighted_recall weighted_f1
471 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
472 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
473 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
0.0250 1.0000 0.0250 0.0488 1.0000 0.0250 0.0488
0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
0.1031 1.0000 0.1031 0.1870 1.0000 0.1031 0.1870
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
0.0656 1.0000 0.0656 0.1232 1.0000 0.0656 0.1232
0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
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
0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
0.0875 1.0000 0.0875 0.1609 1.0000 0.0875 0.1609

29
reports/CertifiedUnlearning/RESNET34/retain.csv
View File

@@ -471,32 +471,3 @@ accuracy,macro_precision,macro_recall,macro_f1,weighted_precision,weighted_recal
0.1026,0.1456,0.1026,0.0392,0.1456,0.1026,0.0392
0.6928,0.8887,0.6928,0.7218,0.8887,0.6928,0.7218
0.9191,0.9270,0.9191,0.9197,0.9270,0.9191,0.9197
0.4316,0.8326,0.4316,0.4030,0.8326,0.4316,0.4030
0.9289,0.9391,0.9289,0.9310,0.9391,0.9289,0.9310
0.9454,0.9476,0.9454,0.9456,0.9476,0.9454,0.9456
0.9046,0.9221,0.9046,0.9073,0.9221,0.9046,0.9073
0.9322,0.9393,0.9322,0.9332,0.9393,0.9322,0.9332
0.8842,0.9196,0.8842,0.8916,0.9196,0.8842,0.8916
0.9072,0.9258,0.9072,0.9111,0.9258,0.9072,0.9111
0.1322,0.3672,0.1322,0.0844,0.3672,0.1322,0.0844
0.9447,0.9469,0.9447,0.9451,0.9469,0.9447,0.9451
0.9336,0.9384,0.9336,0.9339,0.9384,0.9336,0.9339
0.7941,0.8921,0.7941,0.8103,0.8921,0.7941,0.8103
0.9447,0.9477,0.9447,0.9449,0.9477,0.9447,0.9449
0.1329,0.2409,0.1329,0.0850,0.2409,0.1329,0.0850
0.9513,0.9546,0.9513,0.9519,0.9546,0.9513,0.9519
0.9408,0.9464,0.9408,0.9416,0.9464,0.9408,0.9416
0.8987,0.9157,0.8987,0.8994,0.9157,0.8987,0.8994
0.8987,0.9205,0.8987,0.9035,0.9205,0.8987,0.9035
0.0750,0.0175,0.0750,0.0233,0.0175,0.0750,0.0233
0.4493,0.7334,0.4493,0.4059,0.7334,0.4493,0.4059
0.9322,0.9380,0.9322,0.9327,0.9380,0.9322,0.9327
0.7204,0.8401,0.7204,0.7178,0.8401,0.7204,0.7178
0.9428,0.9486,0.9428,0.9439,0.9486,0.9428,0.9439
0.9401,0.9450,0.9401,0.9408,0.9450,0.9401,0.9408
0.5875,0.8750,0.5875,0.6154,0.8750,0.5875,0.6154
0.9336,0.9402,0.9336,0.9342,0.9402,0.9336,0.9342
0.8257,0.8913,0.8257,0.8352,0.8913,0.8257,0.8352
0.8987,0.9353,0.8987,0.9086,0.9353,0.8987,0.9086
0.8882,0.9162,0.8882,0.8931,0.9162,0.8882,0.8931
0.9388,0.9419,0.9388,0.9392,0.9419,0.9388,0.9392
1 accuracy macro_precision macro_recall macro_f1 weighted_precision weighted_recall weighted_f1
471 0.1026 0.1456 0.1026 0.0392 0.1456 0.1026 0.0392
472 0.6928 0.8887 0.6928 0.7218 0.8887 0.6928 0.7218
473 0.9191 0.9270 0.9191 0.9197 0.9270 0.9191 0.9197
0.4316 0.8326 0.4316 0.4030 0.8326 0.4316 0.4030
0.9289 0.9391 0.9289 0.9310 0.9391 0.9289 0.9310
0.9454 0.9476 0.9454 0.9456 0.9476 0.9454 0.9456
0.9046 0.9221 0.9046 0.9073 0.9221 0.9046 0.9073
0.9322 0.9393 0.9322 0.9332 0.9393 0.9322 0.9332
0.8842 0.9196 0.8842 0.8916 0.9196 0.8842 0.8916
0.9072 0.9258 0.9072 0.9111 0.9258 0.9072 0.9111
0.1322 0.3672 0.1322 0.0844 0.3672 0.1322 0.0844
0.9447 0.9469 0.9447 0.9451 0.9469 0.9447 0.9451
0.9336 0.9384 0.9336 0.9339 0.9384 0.9336 0.9339
0.7941 0.8921 0.7941 0.8103 0.8921 0.7941 0.8103
0.9447 0.9477 0.9447 0.9449 0.9477 0.9447 0.9449
0.1329 0.2409 0.1329 0.0850 0.2409 0.1329 0.0850
0.9513 0.9546 0.9513 0.9519 0.9546 0.9513 0.9519
0.9408 0.9464 0.9408 0.9416 0.9464 0.9408 0.9416
0.8987 0.9157 0.8987 0.8994 0.9157 0.8987 0.8994
0.8987 0.9205 0.8987 0.9035 0.9205 0.8987 0.9035
0.0750 0.0175 0.0750 0.0233 0.0175 0.0750 0.0233
0.4493 0.7334 0.4493 0.4059 0.7334 0.4493 0.4059
0.9322 0.9380 0.9322 0.9327 0.9380 0.9322 0.9327
0.7204 0.8401 0.7204 0.7178 0.8401 0.7204 0.7178
0.9428 0.9486 0.9428 0.9439 0.9486 0.9428 0.9439
0.9401 0.9450 0.9401 0.9408 0.9450 0.9401 0.9408
0.5875 0.8750 0.5875 0.6154 0.8750 0.5875 0.6154
0.9336 0.9402 0.9336 0.9342 0.9402 0.9336 0.9342
0.8257 0.8913 0.8257 0.8352 0.8913 0.8257 0.8352
0.8987 0.9353 0.8987 0.9086 0.9353 0.8987 0.9086
0.8882 0.9162 0.8882 0.8931 0.9162 0.8882 0.8931
0.9388 0.9419 0.9388 0.9392 0.9419 0.9388 0.9392

6
reports/CertifiedUnlearning/attack_values.csv
View File

@@ -19,10 +19,6 @@ target_class, parameter_mia_accuracy, lookalike_accuracy, A-Dist, JS-Dist
17,0.500000,0.989583, 0.062500, 0.503747
18,0.550000,1.000000, 0.166667, 0.495459
19,0.500000,0.916667, 0.052083, 0.551996
0,0.500000,0.937500, 0.020833, 0.532267
1,0.500000,0.937500, 0.093750, 0.503973
2,0.500000,0.989583, 0.104167, 0.570063
0,0.500000,0.402083, 0.031250, 0.511158
1,0.500000,0.154167, 0.312500, 0.496193
2,0.500000,0.602083, 0.145833, 0.530453
@@ -103,5 +99,3 @@ target_class, parameter_mia_accuracy, lookalike_accuracy, A-Dist, JS-Dist
17,0.500000,0.377083, 0.166667, 0.459667
18,0.600000,0.881250, 0.083333, 0.488006
19,0.500000,0.568750, 0.187500, 0.546058
0,0.500000,0.635417, 0.156250, 0.527750
1,0.500000,0.193750, 0.333333, 0.447474
1 target_class parameter_mia_accuracy lookalike_accuracy A-Dist JS-Dist
19 17 0.500000 0.989583 0.062500 0.503747
20 18 0.550000 1.000000 0.166667 0.495459
21 19 0.500000 0.916667 0.052083 0.551996
0 0.500000 0.937500 0.020833 0.532267
1 0.500000 0.937500 0.093750 0.503973
2 0.500000 0.989583 0.104167 0.570063
0 0.500000 0.402083 0.031250 0.511158
22 1 0 0.500000 0.154167 0.402083 0.312500 0.031250 0.496193 0.511158
23 2 1 0.500000 0.602083 0.154167 0.145833 0.312500 0.530453 0.496193
24 3 2 0.500000 0.852083 0.602083 0.135417 0.145833 0.491837 0.530453
99 18 17 0.600000 0.500000 0.881250 0.377083 0.083333 0.166667 0.488006 0.459667
100 19 18 0.500000 0.600000 0.568750 0.881250 0.187500 0.083333 0.546058 0.488006
101 0 19 0.500000 0.635417 0.568750 0.156250 0.187500 0.527750 0.546058
1 0.500000 0.193750 0.333333 0.447474