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2026-07-08 00:25:07 +02:00
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commit eb8060fc05
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68
reports/Retrain/RESNET34/forget.csv Normal file
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@@ -0,0 +1,68 @@
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
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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
22 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
23 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
24 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
25 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
26 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
27 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
28 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
29 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
30 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
31 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
32 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
33 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
34 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
35 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
36 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
37 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
38 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
39 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
40 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
41 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
42 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
43 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
44 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
45 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
46 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
47 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
48 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
49 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
50 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
51 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
52 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
53 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
54 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
55 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
56 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
57 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
58 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
59 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
60 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
61 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
62 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
63 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
64 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
65 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
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

68
reports/Retrain/RESNET34/forget_train.csv Normal file
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@@ -0,0 +1,68 @@
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
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0.0000,0.0000,0.0000,0.0000,0.0000,0.0000,0.0000
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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
22 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
23 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
24 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
25 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
26 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
27 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
28 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
29 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
30 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
31 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
32 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
33 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
34 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
35 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
36 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
37 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
38 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
39 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
40 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
41 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
42 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
43 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
44 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
45 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
46 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
47 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
48 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
49 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
50 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
51 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
52 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
53 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
54 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
55 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
56 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
57 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
58 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
59 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
60 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
61 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
62 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
63 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
64 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
65 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000
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

68
reports/Retrain/RESNET34/retain.csv Normal file
View File

@@ -0,0 +1,68 @@
accuracy,macro_precision,macro_recall,macro_f1,weighted_precision,weighted_recall,weighted_f1
0.9618,0.9624,0.9618,0.9619,0.9624,0.9618,0.9619
0.9625,0.9632,0.9625,0.9626,0.9632,0.9625,0.9626
0.9572,0.9584,0.9572,0.9575,0.9584,0.9572,0.9575
0.9566,0.9579,0.9566,0.9568,0.9579,0.9566,0.9568
0.9658,0.9660,0.9658,0.9658,0.9660,0.9658,0.9658
0.9651,0.9655,0.9651,0.9651,0.9655,0.9651,0.9651
0.9539,0.9551,0.9539,0.9540,0.9551,0.9539,0.9540
0.9632,0.9640,0.9632,0.9632,0.9640,0.9632,0.9632
0.9618,0.9624,0.9618,0.9620,0.9624,0.9618,0.9620
0.9612,0.9622,0.9612,0.9613,0.9622,0.9612,0.9613
0.9592,0.9602,0.9592,0.9593,0.9602,0.9592,0.9593
0.9566,0.9578,0.9566,0.9567,0.9578,0.9566,0.9567
0.9605,0.9615,0.9605,0.9605,0.9615,0.9605,0.9605
0.9539,0.9560,0.9539,0.9542,0.9560,0.9539,0.9542
0.9632,0.9639,0.9632,0.9632,0.9639,0.9632,0.9632
0.9625,0.9633,0.9625,0.9625,0.9633,0.9625,0.9625
0.9625,0.9632,0.9625,0.9626,0.9632,0.9625,0.9626
0.9625,0.9631,0.9625,0.9626,0.9631,0.9625,0.9626
0.9592,0.9598,0.9592,0.9591,0.9598,0.9592,0.9591
0.9586,0.9600,0.9586,0.9588,0.9600,0.9586,0.9588
0.9566,0.9577,0.9566,0.9567,0.9577,0.9566,0.9567
0.9605,0.9611,0.9605,0.9605,0.9611,0.9605,0.9605
0.9612,0.9621,0.9612,0.9613,0.9621,0.9612,0.9613
0.9625,0.9636,0.9625,0.9626,0.9636,0.9625,0.9626
0.9625,0.9631,0.9625,0.9624,0.9631,0.9625,0.9624
0.9553,0.9563,0.9553,0.9554,0.9563,0.9553,0.9554
0.9566,0.9578,0.9566,0.9567,0.9578,0.9566,0.9567
0.9632,0.9639,0.9632,0.9632,0.9639,0.9632,0.9632
0.9592,0.9600,0.9592,0.9593,0.9600,0.9592,0.9593
0.9553,0.9568,0.9553,0.9554,0.9568,0.9553,0.9554
0.9612,0.9614,0.9612,0.9611,0.9614,0.9612,0.9611
0.9625,0.9633,0.9625,0.9626,0.9633,0.9625,0.9626
0.9618,0.9629,0.9618,0.9620,0.9629,0.9618,0.9620
0.9553,0.9569,0.9553,0.9554,0.9569,0.9553,0.9554
0.9513,0.9526,0.9513,0.9515,0.9526,0.9513,0.9515
0.9612,0.9614,0.9612,0.9612,0.9614,0.9612,0.9612
0.9572,0.9585,0.9572,0.9573,0.9585,0.9572,0.9573
0.9599,0.9604,0.9599,0.9598,0.9604,0.9599,0.9598
0.9592,0.9603,0.9592,0.9594,0.9603,0.9592,0.9594
0.9599,0.9611,0.9599,0.9600,0.9611,0.9599,0.9600
0.9632,0.9638,0.9632,0.9632,0.9638,0.9632,0.9632
0.9599,0.9602,0.9599,0.9599,0.9602,0.9599,0.9599
0.9526,0.9536,0.9526,0.9527,0.9536,0.9526,0.9527
0.9579,0.9586,0.9579,0.9579,0.9586,0.9579,0.9579
0.9579,0.9593,0.9579,0.9580,0.9593,0.9579,0.9580
0.9599,0.9607,0.9599,0.9600,0.9607,0.9599,0.9600
0.9632,0.9641,0.9632,0.9633,0.9641,0.9632,0.9633
0.9599,0.9607,0.9599,0.9601,0.9607,0.9599,0.9601
0.9664,0.9669,0.9664,0.9665,0.9669,0.9664,0.9665
0.9592,0.9604,0.9592,0.9594,0.9604,0.9592,0.9594
0.9625,0.9630,0.9625,0.9625,0.9630,0.9625,0.9625
0.9579,0.9590,0.9579,0.9581,0.9590,0.9579,0.9581
0.9572,0.9579,0.9572,0.9573,0.9579,0.9572,0.9573
0.9632,0.9638,0.9632,0.9632,0.9638,0.9632,0.9632
0.9566,0.9576,0.9566,0.9566,0.9576,0.9566,0.9566
0.9651,0.9662,0.9651,0.9653,0.9662,0.9651,0.9653
0.9579,0.9593,0.9579,0.9581,0.9593,0.9579,0.9581
0.9592,0.9603,0.9592,0.9593,0.9603,0.9592,0.9593
0.9671,0.9677,0.9671,0.9672,0.9677,0.9671,0.9672
0.9638,0.9644,0.9638,0.9639,0.9644,0.9638,0.9639
0.9645,0.9653,0.9645,0.9646,0.9653,0.9645,0.9646
0.9618,0.9631,0.9618,0.9620,0.9631,0.9618,0.9620
0.9599,0.9606,0.9599,0.9599,0.9606,0.9599,0.9599
0.9553,0.9565,0.9553,0.9553,0.9565,0.9553,0.9553
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
1 accuracy macro_precision macro_recall macro_f1 weighted_precision weighted_recall weighted_f1
2 0.9618 0.9624 0.9618 0.9619 0.9624 0.9618 0.9619
3 0.9625 0.9632 0.9625 0.9626 0.9632 0.9625 0.9626
4 0.9572 0.9584 0.9572 0.9575 0.9584 0.9572 0.9575
5 0.9566 0.9579 0.9566 0.9568 0.9579 0.9566 0.9568
6 0.9658 0.9660 0.9658 0.9658 0.9660 0.9658 0.9658
7 0.9651 0.9655 0.9651 0.9651 0.9655 0.9651 0.9651
8 0.9539 0.9551 0.9539 0.9540 0.9551 0.9539 0.9540
9 0.9632 0.9640 0.9632 0.9632 0.9640 0.9632 0.9632
10 0.9618 0.9624 0.9618 0.9620 0.9624 0.9618 0.9620
11 0.9612 0.9622 0.9612 0.9613 0.9622 0.9612 0.9613
12 0.9592 0.9602 0.9592 0.9593 0.9602 0.9592 0.9593
13 0.9566 0.9578 0.9566 0.9567 0.9578 0.9566 0.9567
14 0.9605 0.9615 0.9605 0.9605 0.9615 0.9605 0.9605
15 0.9539 0.9560 0.9539 0.9542 0.9560 0.9539 0.9542
16 0.9632 0.9639 0.9632 0.9632 0.9639 0.9632 0.9632
17 0.9625 0.9633 0.9625 0.9625 0.9633 0.9625 0.9625
18 0.9625 0.9632 0.9625 0.9626 0.9632 0.9625 0.9626
19 0.9625 0.9631 0.9625 0.9626 0.9631 0.9625 0.9626
20 0.9592 0.9598 0.9592 0.9591 0.9598 0.9592 0.9591
21 0.9586 0.9600 0.9586 0.9588 0.9600 0.9586 0.9588
22 0.9566 0.9577 0.9566 0.9567 0.9577 0.9566 0.9567
23 0.9605 0.9611 0.9605 0.9605 0.9611 0.9605 0.9605
24 0.9612 0.9621 0.9612 0.9613 0.9621 0.9612 0.9613
25 0.9625 0.9636 0.9625 0.9626 0.9636 0.9625 0.9626
26 0.9625 0.9631 0.9625 0.9624 0.9631 0.9625 0.9624
27 0.9553 0.9563 0.9553 0.9554 0.9563 0.9553 0.9554
28 0.9566 0.9578 0.9566 0.9567 0.9578 0.9566 0.9567
29 0.9632 0.9639 0.9632 0.9632 0.9639 0.9632 0.9632
30 0.9592 0.9600 0.9592 0.9593 0.9600 0.9592 0.9593
31 0.9553 0.9568 0.9553 0.9554 0.9568 0.9553 0.9554
32 0.9612 0.9614 0.9612 0.9611 0.9614 0.9612 0.9611
33 0.9625 0.9633 0.9625 0.9626 0.9633 0.9625 0.9626
34 0.9618 0.9629 0.9618 0.9620 0.9629 0.9618 0.9620
35 0.9553 0.9569 0.9553 0.9554 0.9569 0.9553 0.9554
36 0.9513 0.9526 0.9513 0.9515 0.9526 0.9513 0.9515
37 0.9612 0.9614 0.9612 0.9612 0.9614 0.9612 0.9612
38 0.9572 0.9585 0.9572 0.9573 0.9585 0.9572 0.9573
39 0.9599 0.9604 0.9599 0.9598 0.9604 0.9599 0.9598
40 0.9592 0.9603 0.9592 0.9594 0.9603 0.9592 0.9594
41 0.9599 0.9611 0.9599 0.9600 0.9611 0.9599 0.9600
42 0.9632 0.9638 0.9632 0.9632 0.9638 0.9632 0.9632
43 0.9599 0.9602 0.9599 0.9599 0.9602 0.9599 0.9599
44 0.9526 0.9536 0.9526 0.9527 0.9536 0.9526 0.9527
45 0.9579 0.9586 0.9579 0.9579 0.9586 0.9579 0.9579
46 0.9579 0.9593 0.9579 0.9580 0.9593 0.9579 0.9580
47 0.9599 0.9607 0.9599 0.9600 0.9607 0.9599 0.9600
48 0.9632 0.9641 0.9632 0.9633 0.9641 0.9632 0.9633
49 0.9599 0.9607 0.9599 0.9601 0.9607 0.9599 0.9601
50 0.9664 0.9669 0.9664 0.9665 0.9669 0.9664 0.9665
51 0.9592 0.9604 0.9592 0.9594 0.9604 0.9592 0.9594
52 0.9625 0.9630 0.9625 0.9625 0.9630 0.9625 0.9625
53 0.9579 0.9590 0.9579 0.9581 0.9590 0.9579 0.9581
54 0.9572 0.9579 0.9572 0.9573 0.9579 0.9572 0.9573
55 0.9632 0.9638 0.9632 0.9632 0.9638 0.9632 0.9632
56 0.9566 0.9576 0.9566 0.9566 0.9576 0.9566 0.9566
57 0.9651 0.9662 0.9651 0.9653 0.9662 0.9651 0.9653
58 0.9579 0.9593 0.9579 0.9581 0.9593 0.9579 0.9581
59 0.9592 0.9603 0.9592 0.9593 0.9603 0.9592 0.9593
60 0.9671 0.9677 0.9671 0.9672 0.9677 0.9671 0.9672
61 0.9638 0.9644 0.9638 0.9639 0.9644 0.9638 0.9639
62 0.9645 0.9653 0.9645 0.9646 0.9653 0.9645 0.9646
63 0.9618 0.9631 0.9618 0.9620 0.9631 0.9618 0.9620
64 0.9599 0.9606 0.9599 0.9599 0.9606 0.9599 0.9599
65 0.9553 0.9565 0.9553 0.9553 0.9565 0.9553 0.9553
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

44
reports/Retrain/ResNet/time_metrics.txt Normal file
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execution_time_sec
848.855054
851.395526
857.667636
864.373247
921.414065
1006.761514
851.995606
850.456523
851.156817
855.827699
852.529868
855.051966
851.841468
852.182889
859.966127
870.718984
859.687153
849.761404
892.106300
880.976200
894.792684
918.782255
862.899020
848.422644
848.069965
849.830024
850.185797
850.567450
850.479165
849.162948
850.724711
848.658417
850.287266
848.900766
849.176482
849.449771
850.224029
848.678724
851.971777
850.963888
848.760931
848.571131
856.289965

5
reports/Retrain/attack_values.csv Normal file
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target_class,parameter_mia_accuracy,latent_distance_tell,lookalike_accuracy
0,0.500000,11.573492,0.000000
1,0.500000,12.793120,0.000000
2,0.500000,12.951434,0.000000
3,0.500000,10.942259,0.000000
1 target_class parameter_mia_accuracy latent_distance_tell lookalike_accuracy
2 0 0.500000 11.573492 0.000000
3 1 0.500000 12.793120 0.000000
4 2 0.500000 12.951434 0.000000
5 3 0.500000 10.942259 0.000000