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Tinsae
2026-07-05 09:21:40 +02:00
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10
reports/CertifiedUnlearning/RESNET34/forget.csv
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@@ -297,3 +297,13 @@ 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
0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
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
297 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
298 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
299 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
300 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
301 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
302 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
303 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
304 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
305 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
306 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
307 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
308 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
309 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000

10
reports/CertifiedUnlearning/RESNET34/forget_train.csv
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@@ -297,3 +297,13 @@ 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 0.0031,1.0000,0.0031,0.0062,1.0000,0.0031,0.0062
0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000 0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
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
297 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
298 0.0031 1.0000 0.0031 0.0062 1.0000 0.0031 0.0062
299 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
300 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
301 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
302 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
303 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
304 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
305 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
306 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
307 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
308 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
309 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000

10
reports/CertifiedUnlearning/RESNET34/retain.csv
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@@ -297,3 +297,13 @@ accuracy,macro_precision,macro_recall,macro_f1,weighted_precision,weighted_recal
0.5658,0.8289,0.5658,0.5697,0.8289,0.5658,0.5697 0.5658,0.8289,0.5658,0.5697,0.8289,0.5658,0.5697
0.9099,0.9273,0.9099,0.9123,0.9273,0.9099,0.9123 0.9099,0.9273,0.9099,0.9123,0.9273,0.9099,0.9123
0.4000,0.8547,0.4000,0.4331,0.8547,0.4000,0.4331 0.4000,0.8547,0.4000,0.4331,0.8547,0.4000,0.4331
0.9118,0.9278,0.9118,0.9143,0.9278,0.9118,0.9143
0.8855,0.9100,0.8855,0.8881,0.9100,0.8855,0.8881
0.0526,0.0028,0.0526,0.0053,0.0028,0.0526,0.0053
0.8776,0.9068,0.8776,0.8818,0.9068,0.8776,0.8818
0.8967,0.9304,0.8967,0.9056,0.9304,0.8967,0.9056
0.7980,0.8756,0.7980,0.8078,0.8756,0.7980,0.8078
0.8789,0.9042,0.8789,0.8822,0.9042,0.8789,0.8822
0.4447,0.7262,0.4447,0.3814,0.7262,0.4447,0.3814
0.8980,0.9171,0.8980,0.8995,0.9171,0.8980,0.8995
0.6217,0.8081,0.6217,0.6290,0.8081,0.6217,0.6290
1 accuracy macro_precision macro_recall macro_f1 weighted_precision weighted_recall weighted_f1
297 0.5658 0.8289 0.5658 0.5697 0.8289 0.5658 0.5697
298 0.9099 0.9273 0.9099 0.9123 0.9273 0.9099 0.9123
299 0.4000 0.8547 0.4000 0.4331 0.8547 0.4000 0.4331
300 0.9118 0.9278 0.9118 0.9143 0.9278 0.9118 0.9143
301 0.8855 0.9100 0.8855 0.8881 0.9100 0.8855 0.8881
302 0.0526 0.0028 0.0526 0.0053 0.0028 0.0526 0.0053
303 0.8776 0.9068 0.8776 0.8818 0.9068 0.8776 0.8818
304 0.8967 0.9304 0.8967 0.9056 0.9304 0.8967 0.9056
305 0.7980 0.8756 0.7980 0.8078 0.8756 0.7980 0.8078
306 0.8789 0.9042 0.8789 0.8822 0.9042 0.8789 0.8822
307 0.4447 0.7262 0.4447 0.3814 0.7262 0.4447 0.3814
308 0.8980 0.9171 0.8980 0.8995 0.9171 0.8980 0.8995
309 0.6217 0.8081 0.6217 0.6290 0.8081 0.6217 0.6290

10
reports/CertifiedUnlearning/ResNet/time_metrics.txt
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@@ -348,3 +348,13 @@ execution_time_sec
395.694666 395.694666
395.510094 395.510094
395.383846 395.383846
409.957779
406.676189
395.744297
396.049791
395.549960
395.804624
395.546120
395.674757
395.578882
395.659949

1
reports/base/RESNET34/Finetuned.csv
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@@ -48,3 +48,4 @@ accuracy,macro_precision,macro_recall,macro_f1,weighted_precision,weighted_recal
0.9575,0.9583,0.9575,0.9575,0.9583,0.9575,0.9575 0.9575,0.9583,0.9575,0.9575,0.9583,0.9575,0.9575
0.9500,0.9509,0.9500,0.9501,0.9509,0.9500,0.9501 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 0.9550,0.9557,0.9550,0.9549,0.9557,0.9550,0.9549
0.9519,0.9533,0.9519,0.9520,0.9533,0.9519,0.9520
1 accuracy macro_precision macro_recall macro_f1 weighted_precision weighted_recall weighted_f1
48 0.9575 0.9583 0.9575 0.9575 0.9583 0.9575 0.9575
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