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Tinsae
2026-07-08 10:07:39 +02:00
parent eb8060fc05
commit a118a975c1
20 changed files with 287 additions and 22 deletions
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14
reports/Retrain/RESNET34/forget.csv
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@@ -66,3 +66,17 @@ 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
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
66 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
67 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
68 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
69 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
70 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
71 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
72 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
73 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
74 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
75 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
76 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
77 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
78 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
79 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
80 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
81 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
82 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000

14
reports/Retrain/RESNET34/forget_train.csv
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@@ -66,3 +66,17 @@ 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
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
66 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
67 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
68 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
69 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
70 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
71 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
72 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
73 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
74 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
75 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
76 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
77 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
78 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
79 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
80 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
81 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
82 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000

14
reports/Retrain/RESNET34/retain.csv
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@@ -66,3 +66,17 @@ accuracy,macro_precision,macro_recall,macro_f1,weighted_precision,weighted_recal
0.9533,0.9543,0.9533,0.9534,0.9543,0.9533,0.9534
0.9586,0.9599,0.9586,0.9588,0.9599,0.9586,0.9588
0.9612,0.9620,0.9612,0.9613,0.9620,0.9612,0.9613
0.9559,0.9571,0.9559,0.9560,0.9571,0.9559,0.9560
0.9559,0.9571,0.9559,0.9560,0.9571,0.9559,0.9560
0.9507,0.9518,0.9507,0.9507,0.9518,0.9507,0.9507
0.9612,0.9622,0.9612,0.9612,0.9622,0.9612,0.9612
0.9553,0.9561,0.9553,0.9552,0.9561,0.9553,0.9552
0.9618,0.9626,0.9618,0.9618,0.9626,0.9618,0.9618
0.9566,0.9586,0.9566,0.9569,0.9586,0.9566,0.9569
0.9533,0.9548,0.9533,0.9535,0.9548,0.9533,0.9535
0.9539,0.9548,0.9539,0.9541,0.9548,0.9539,0.9541
0.9500,0.9511,0.9500,0.9500,0.9511,0.9500,0.9500
0.9566,0.9572,0.9566,0.9565,0.9572,0.9566,0.9565
0.9546,0.9554,0.9546,0.9546,0.9554,0.9546,0.9546
0.9612,0.9620,0.9612,0.9613,0.9620,0.9612,0.9613
0.9539,0.9551,0.9539,0.9540,0.9551,0.9539,0.9540
1 accuracy macro_precision macro_recall macro_f1 weighted_precision weighted_recall weighted_f1
66 0.9533 0.9543 0.9533 0.9534 0.9543 0.9533 0.9534
67 0.9586 0.9599 0.9586 0.9588 0.9599 0.9586 0.9588
68 0.9612 0.9620 0.9612 0.9613 0.9620 0.9612 0.9613
69 0.9559 0.9571 0.9559 0.9560 0.9571 0.9559 0.9560
70 0.9559 0.9571 0.9559 0.9560 0.9571 0.9559 0.9560
71 0.9507 0.9518 0.9507 0.9507 0.9518 0.9507 0.9507
72 0.9612 0.9622 0.9612 0.9612 0.9622 0.9612 0.9612
73 0.9553 0.9561 0.9553 0.9552 0.9561 0.9553 0.9552
74 0.9618 0.9626 0.9618 0.9618 0.9626 0.9618 0.9618
75 0.9566 0.9586 0.9566 0.9569 0.9586 0.9566 0.9569
76 0.9533 0.9548 0.9533 0.9535 0.9548 0.9533 0.9535
77 0.9539 0.9548 0.9539 0.9541 0.9548 0.9539 0.9541
78 0.9500 0.9511 0.9500 0.9500 0.9511 0.9500 0.9500
79 0.9566 0.9572 0.9566 0.9565 0.9572 0.9566 0.9565
80 0.9546 0.9554 0.9546 0.9546 0.9554 0.9546 0.9546
81 0.9612 0.9620 0.9612 0.9613 0.9620 0.9612 0.9613
82 0.9539 0.9551 0.9539 0.9540 0.9551 0.9539 0.9540