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unlearning LF

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Tinsae
2026-06-07 10:36:03 +02:00
parent e90480adbe
commit 61c3447150
10 changed files with 395 additions and 73 deletions
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35
reports/LinearFiltration_metrics.txt Normal file
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execution_time_sec
0.001269
0.001227
0.001298
0.001281
0.001178
0.001392
0.001391
0.001338
0.001162
0.001355
0.001361
0.001241
0.001210
0.001152
0.001358
0.001250
0.001467
0.001248
0.001411
0.001470
0.001241
0.001366
0.001206
0.001339
0.001268
0.002847
0.001245
0.001299
0.001222
0.001274
0.001351
0.001401
0.001286
0.001214

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reports/resnet50-finetunned.csv Normal file
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accuracy,macro_precision,macro_recall,macro_f1,weighted_precision,weighted_recall,weighted_f1
0.9333,0.9500,0.9333,0.9264,0.9500,0.9333,0.9264
0.9167,0.9425,0.9167,0.9111,0.9425,0.9167,0.9111
0.9333,0.9500,0.9333,0.9264,0.9500,0.9333,0.9264
0.8667,0.9050,0.8667,0.8625,0.9050,0.8667,0.8625
0.9000,0.9208,0.9000,0.8976,0.9208,0.9000,0.8976
0.9000,0.9208,0.9000,0.8926,0.9208,0.9000,0.8926
0.9667,0.9750,0.9667,0.9657,0.9750,0.9667,0.9657
0.9000,0.9308,0.9000,0.9012,0.9308,0.9000,0.9012
0.9833,0.9875,0.9833,0.9829,0.9875,0.9833,0.9829
0.9500,0.9625,0.9500,0.9486,0.9625,0.9500,0.9486
0.8667,0.9008,0.8667,0.8551,0.9008,0.8667,0.8551
0.9167,0.9375,0.9167,0.9093,0.9375,0.9167,0.9093
0.9000,0.9250,0.9000,0.8921,0.9250,0.9000,0.8921
0.9000,0.9333,0.9000,0.9024,0.9333,0.9000,0.9024
0.9500,0.9625,0.9500,0.9486,0.9625,0.9500,0.9486
0.9167,0.9333,0.9167,0.9148,0.9333,0.9167,0.9148
0.9167,0.9375,0.9167,0.9143,0.9375,0.9167,0.9143
0.9667,0.9750,0.9667,0.9657,0.9750,0.9667,0.9657
0.9333,0.9500,0.9333,0.9314,0.9500,0.9333,0.9314
0.9000,0.9350,0.9000,0.8957,0.9350,0.9000,0.8957
1 accuracy macro_precision macro_recall macro_f1 weighted_precision weighted_recall weighted_f1
2 0.9333 0.9500 0.9333 0.9264 0.9500 0.9333 0.9264
3 0.9167 0.9425 0.9167 0.9111 0.9425 0.9167 0.9111
4 0.9333 0.9500 0.9333 0.9264 0.9500 0.9333 0.9264
5 0.8667 0.9050 0.8667 0.8625 0.9050 0.8667 0.8625
6 0.9000 0.9208 0.9000 0.8976 0.9208 0.9000 0.8976
7 0.9000 0.9208 0.9000 0.8926 0.9208 0.9000 0.8926
8 0.9667 0.9750 0.9667 0.9657 0.9750 0.9667 0.9657
9 0.9000 0.9308 0.9000 0.9012 0.9308 0.9000 0.9012
10 0.9833 0.9875 0.9833 0.9829 0.9875 0.9833 0.9829
11 0.9500 0.9625 0.9500 0.9486 0.9625 0.9500 0.9486
12 0.8667 0.9008 0.8667 0.8551 0.9008 0.8667 0.8551
13 0.9167 0.9375 0.9167 0.9093 0.9375 0.9167 0.9093
14 0.9000 0.9250 0.9000 0.8921 0.9250 0.9000 0.8921
15 0.9000 0.9333 0.9000 0.9024 0.9333 0.9000 0.9024
16 0.9500 0.9625 0.9500 0.9486 0.9625 0.9500 0.9486
17 0.9167 0.9333 0.9167 0.9148 0.9333 0.9167 0.9148
18 0.9167 0.9375 0.9167 0.9143 0.9375 0.9167 0.9143
19 0.9667 0.9750 0.9667 0.9657 0.9750 0.9667 0.9657
20 0.9333 0.9500 0.9333 0.9314 0.9500 0.9333 0.9314
21 0.9000 0.9350 0.9000 0.8957 0.9350 0.9000 0.8957

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reports/resnet50-forget.csv Normal file
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accuracy,macro_precision,macro_recall,macro_f1,weighted_precision,weighted_recall,weighted_f1
0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
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
2 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
3 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
4 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
5 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
6 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
7 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
8 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
9 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
10 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
11 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
12 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
13 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
14 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
15 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
16 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
17 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
18 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
19 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
20 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
21 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000

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reports/resnet50-retain.csv Normal file
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accuracy,macro_precision,macro_recall,macro_f1,weighted_precision,weighted_recall,weighted_f1,
0.9474,0.9605,0.9474,0.9459,0.9605,0.9474,0.9459
0.9123,0.9395,0.9123,0.9064,0.9395,0.9123,0.9064
0.9298,0.9526,0.9298,0.9244,0.9526,0.9298,0.9244
0.8596,0.9000,0.8596,0.8553,0.9000,0.8596,0.8553
0.9123,0.9298,0.9123,0.9103,0.9298,0.9123,0.9103
0.9123,0.9342,0.9123,0.9045,0.9342,0.9123,0.9045
0.9649,0.9737,0.9649,0.9639,0.9737,0.9649,0.9639
0.8947,0.9272,0.8947,0.8960,0.9272,0.8947,0.8960
1.0000,1.0000,1.0000,1.0000,1.0000,1.0000,1.0000
0.9649,0.9737,0.9649,0.9639,0.9737,0.9649,0.9639
0.8772,0.9132,0.8772,0.8650,0.9132,0.8772,0.8650
0.9123,0.9342,0.9123,0.9045,0.9342,0.9123,0.9045
0.9123,0.9342,0.9123,0.9045,0.9342,0.9123,0.9045
0.9298,0.9605,0.9298,0.9328,0.9605,0.9298,0.9328
0.9649,0.9737,0.9649,0.9639,0.9737,0.9649,0.9639
0.9298,0.9430,0.9298,0.9283,0.9430,0.9298,0.9283
0.9298,0.9474,0.9298,0.9278,0.9474,0.9298,0.9278
0.9649,0.9737,0.9649,0.9639,0.9737,0.9649,0.9639
0.9298,0.9474,0.9298,0.9278,0.9474,0.9298,0.9278
0.8947,0.9316,0.8947,0.8902,0.9316,0.8947,0.8902
1 accuracy,macro_precision,macro_recall,macro_f1,weighted_precision,weighted_recall,weighted_f1,
2 0.9474,0.9605,0.9474,0.9459,0.9605,0.9474,0.9459
3 0.9123,0.9395,0.9123,0.9064,0.9395,0.9123,0.9064
4 0.9298,0.9526,0.9298,0.9244,0.9526,0.9298,0.9244
5 0.8596,0.9000,0.8596,0.8553,0.9000,0.8596,0.8553
6 0.9123,0.9298,0.9123,0.9103,0.9298,0.9123,0.9103
7 0.9123,0.9342,0.9123,0.9045,0.9342,0.9123,0.9045
8 0.9649,0.9737,0.9649,0.9639,0.9737,0.9649,0.9639
9 0.8947,0.9272,0.8947,0.8960,0.9272,0.8947,0.8960
10 1.0000,1.0000,1.0000,1.0000,1.0000,1.0000,1.0000
11 0.9649,0.9737,0.9649,0.9639,0.9737,0.9649,0.9639
12 0.8772,0.9132,0.8772,0.8650,0.9132,0.8772,0.8650
13 0.9123,0.9342,0.9123,0.9045,0.9342,0.9123,0.9045
14 0.9123,0.9342,0.9123,0.9045,0.9342,0.9123,0.9045
15 0.9298,0.9605,0.9298,0.9328,0.9605,0.9298,0.9328
16 0.9649,0.9737,0.9649,0.9639,0.9737,0.9649,0.9639
17 0.9298,0.9430,0.9298,0.9283,0.9430,0.9298,0.9283
18 0.9298,0.9474,0.9298,0.9278,0.9474,0.9298,0.9278
19 0.9649,0.9737,0.9649,0.9639,0.9737,0.9649,0.9639
20 0.9298,0.9474,0.9298,0.9278,0.9474,0.9298,0.9278
21 0.8947,0.9316,0.8947,0.8902,0.9316,0.8947,0.8902