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Tinsae
2026-07-05 14:22:22 +02:00
parent f81fcab3b9
commit 026ca47800
5 changed files with 90 additions and 37 deletions
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22
reports/CertifiedUnlearning/RESNET34/forget.csv
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@@ -322,3 +322,25 @@ 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
0.0250,1.0000,0.0250,0.0488,1.0000,0.0250,0.0488
0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
0.4750,1.0000,0.4750,0.6441,1.0000,0.4750,0.6441
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
0.0625,1.0000,0.0625,0.1176,1.0000,0.0625,0.1176
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
0.4250,1.0000,0.4250,0.5965,1.0000,0.4250,0.5965
0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
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
322 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
323 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
324 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
325 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
326 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
327 0.0250 1.0000 0.0250 0.0488 1.0000 0.0250 0.0488
328 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
329 0.4750 1.0000 0.4750 0.6441 1.0000 0.4750 0.6441
330 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
331 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
332 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
333 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
334 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
335 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
336 0.0625 1.0000 0.0625 0.1176 1.0000 0.0625 0.1176
337 0.0250 1.0000 0.0250 0.0488 1.0000 0.0250 0.0488
338 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
339 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
340 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
341 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
342 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
343 0.4250 1.0000 0.4250 0.5965 1.0000 0.4250 0.5965
344 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
345 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
346 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000

22
reports/CertifiedUnlearning/RESNET34/forget_train.csv
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@@ -322,3 +322,25 @@ 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
0.0031,1.0000,0.0031,0.0062,1.0000,0.0031,0.0062
0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
0.0281,1.0000,0.0281,0.0547,1.0000,0.0281,0.0547
0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
0.6562,1.0000,0.6562,0.7925,1.0000,0.6562,0.7925
0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
0.0563,1.0000,0.0563,0.1065,1.0000,0.0563,0.1065
0.0406,1.0000,0.0406,0.0781,1.0000,0.0406,0.0781
0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
0.5344,1.0000,0.5344,0.6965,1.0000,0.5344,0.6965
0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
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
322 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
323 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
324 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
325 0.0031 1.0000 0.0031 0.0062 1.0000 0.0031 0.0062
326 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
327 0.0281 1.0000 0.0281 0.0547 1.0000 0.0281 0.0547
328 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
329 0.6562 1.0000 0.6562 0.7925 1.0000 0.6562 0.7925
330 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
331 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
332 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
333 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
334 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
335 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
336 0.0563 1.0000 0.0563 0.1065 1.0000 0.0563 0.1065
337 0.0406 1.0000 0.0406 0.0781 1.0000 0.0406 0.0781
338 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
339 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
340 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
341 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
342 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
343 0.5344 1.0000 0.5344 0.6965 1.0000 0.5344 0.6965
344 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
345 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
346 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000

22
reports/CertifiedUnlearning/RESNET34/retain.csv
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@@ -322,3 +322,25 @@ accuracy,macro_precision,macro_recall,macro_f1,weighted_precision,weighted_recal
0.4197,0.8763,0.4197,0.4452,0.8763,0.4197,0.4452
0.5237,0.8114,0.5237,0.5252,0.8114,0.5237,0.5252
0.0717,0.3186,0.0717,0.0403,0.3186,0.0717,0.0403
0.9276,0.9394,0.9276,0.9297,0.9394,0.9276,0.9297
0.4822,0.7453,0.4822,0.4555,0.7453,0.4822,0.4555
0.9434,0.9481,0.9434,0.9440,0.9481,0.9434,0.9440
0.8243,0.9041,0.8243,0.8413,0.9041,0.8243,0.8413
0.9572,0.9586,0.9572,0.9571,0.9586,0.9572,0.9571
0.1039,0.3140,0.1039,0.0849,0.3140,0.1039,0.0849
0.4145,0.8569,0.4145,0.4365,0.8569,0.4145,0.4365
0.8270,0.9302,0.8270,0.8580,0.9302,0.8270,0.8580
0.8401,0.8765,0.8401,0.8440,0.8765,0.8401,0.8440
0.9375,0.9423,0.9375,0.9380,0.9423,0.9375,0.9380
0.9382,0.9426,0.9382,0.9384,0.9426,0.9382,0.9384
0.9230,0.9305,0.9230,0.9216,0.9305,0.9230,0.9216
0.9349,0.9383,0.9349,0.9351,0.9383,0.9349,0.9351
0.8283,0.8855,0.8283,0.8375,0.8855,0.8283,0.8375
0.9125,0.9209,0.9125,0.9122,0.9209,0.9125,0.9122
0.8888,0.9106,0.8888,0.8908,0.9106,0.8888,0.8908
0.8776,0.9226,0.8776,0.8875,0.9226,0.8776,0.8875
0.8947,0.9188,0.8947,0.8985,0.9188,0.8947,0.8985
0.9513,0.9526,0.9513,0.9514,0.9526,0.9513,0.9514
0.6434,0.8358,0.6434,0.6622,0.8358,0.6434,0.6622
0.7303,0.8317,0.7303,0.7303,0.8317,0.7303,0.7303
0.2895,0.4174,0.2895,0.2206,0.4174,0.2895,0.2206
1 accuracy macro_precision macro_recall macro_f1 weighted_precision weighted_recall weighted_f1
322 0.4197 0.8763 0.4197 0.4452 0.8763 0.4197 0.4452
323 0.5237 0.8114 0.5237 0.5252 0.8114 0.5237 0.5252
324 0.0717 0.3186 0.0717 0.0403 0.3186 0.0717 0.0403
325 0.9276 0.9394 0.9276 0.9297 0.9394 0.9276 0.9297
326 0.4822 0.7453 0.4822 0.4555 0.7453 0.4822 0.4555
327 0.9434 0.9481 0.9434 0.9440 0.9481 0.9434 0.9440
328 0.8243 0.9041 0.8243 0.8413 0.9041 0.8243 0.8413
329 0.9572 0.9586 0.9572 0.9571 0.9586 0.9572 0.9571
330 0.1039 0.3140 0.1039 0.0849 0.3140 0.1039 0.0849
331 0.4145 0.8569 0.4145 0.4365 0.8569 0.4145 0.4365
332 0.8270 0.9302 0.8270 0.8580 0.9302 0.8270 0.8580
333 0.8401 0.8765 0.8401 0.8440 0.8765 0.8401 0.8440
334 0.9375 0.9423 0.9375 0.9380 0.9423 0.9375 0.9380
335 0.9382 0.9426 0.9382 0.9384 0.9426 0.9382 0.9384
336 0.9230 0.9305 0.9230 0.9216 0.9305 0.9230 0.9216
337 0.9349 0.9383 0.9349 0.9351 0.9383 0.9349 0.9351
338 0.8283 0.8855 0.8283 0.8375 0.8855 0.8283 0.8375
339 0.9125 0.9209 0.9125 0.9122 0.9209 0.9125 0.9122
340 0.8888 0.9106 0.8888 0.8908 0.9106 0.8888 0.8908
341 0.8776 0.9226 0.8776 0.8875 0.9226 0.8776 0.8875
342 0.8947 0.9188 0.8947 0.8985 0.9188 0.8947 0.8985
343 0.9513 0.9526 0.9513 0.9514 0.9526 0.9513 0.9514
344 0.6434 0.8358 0.6434 0.6622 0.8358 0.6434 0.6622
345 0.7303 0.8317 0.7303 0.7303 0.8317 0.7303 0.7303
346 0.2895 0.4174 0.2895 0.2206 0.4174 0.2895 0.2206

59
reports/CertifiedUnlearning/ResNet/time_metrics.txt
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@@ -1,41 +1,4 @@
execution_time_sec
694.885636
694.603929
694.289521
694.251959
694.489893
694.476680
694.684047
694.595256
694.335008
694.979527
694.827956
694.747950
694.377617
694.808482
694.457737
693.867783
694.608748
693.981431
694.415067
694.015972
694.777692
694.465398
694.582325
694.581984
694.759200
694.688170
694.796203
694.642541
694.752118
694.665401
694.588823
694.641001
694.601991
694.684462
694.760856
701.145855
710.367862
395.622126
395.411873
395.804363
@@ -373,3 +336,25 @@ execution_time_sec
401.068551
395.632033
395.682543
395.463989
399.981388
395.567998
395.580986
395.565115
395.543731
395.538798
395.632124
395.480490
395.674171
395.601542
395.663322
395.591307
395.537834
395.541825
395.552843
395.445752
395.488962
395.534835
395.473056
395.455440
395.554517

2
reports/base/RESNET34/Finetuned.csv
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@@ -49,3 +49,5 @@ accuracy,macro_precision,macro_recall,macro_f1,weighted_precision,weighted_recal
0.9500,0.9509,0.9500,0.9501,0.9509,0.9500,0.9501
0.9550,0.9557,0.9550,0.9549,0.9557,0.9550,0.9549
0.9519,0.9533,0.9519,0.9520,0.9533,0.9519,0.9520
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
1 accuracy macro_precision macro_recall macro_f1 weighted_precision weighted_recall weighted_f1
49 0.9500 0.9509 0.9500 0.9501 0.9509 0.9500 0.9501
50 0.9550 0.9557 0.9550 0.9549 0.9557 0.9550 0.9549
51 0.9519 0.9533 0.9519 0.9520 0.9533 0.9519 0.9520
52 0.9581 0.9590 0.9581 0.9581 0.9590 0.9581 0.9581
53 0.9513 0.9525 0.9512 0.9514 0.9525 0.9513 0.9514