Result table

This table was generated on 2025-11-28 at 06:34. See more results here. See last results here.

results

project_name group_name hostname status time time_per_image_ms acc_nat acc_pgdlinf acc_pgdl2 agg error_msg jean-ponce Master-IASD upnquick Success 5633.35 281.67 100.0 60.53 89.59 150.12 None BestOf2023-1 profs upnquick Success 183.02 9.15 62.5 70.18 70.79 140.97 None BestOf2024-1 profs upnquick Success 2744.41 137.22 63.75 51.36 63.88 115.24 None the-taithon-canon Master-IASD coktailjet Success 5071.28 253.56 75.0 49.2 65.53 114.73 None BestOfMiles profs upnquick Success 5339.93 267.0 77.5 51.5 63.15 114.66 None BestOf2024-2 profs coktailjet Success 1155.76 57.79 87.5 52.48 59.87 112.35 None neural-nightmare Master-IASD coktailjet Success 1777.43 88.87 68.75 41.86 53.09 94.95 None BestOf2023-2 profs coktailjet Success 112.59 5.63 81.25 41.01 53.51 94.52 None noeyedeer Master-IASD upnquick Success 5413.63 270.68 75.0 38.87 52.58 91.45 None exocet Master-IASD coktailjet Success 1226.12 61.31 37.5 37.1 45.44 82.54 None invisible_attack Master-IASD upnquick Success 2531.71 126.59 57.5 26.22 50.21 76.43 None best_defense_is_attack Master-IASD coktailjet Success 72.26 3.61 62.5 29.13 38.14 67.27 None gradient-hackers Master-IASD coktailjet Success 94.83 4.74 68.75 29.18 34.9 64.08 None the-advengers Master-IASD coktailjet Success 122.56 6.13 31.25 28.66 34.59 63.25 None jogabonito Master-IASD coktailjet Success 124.1 6.21 75.0 27.32 34.57 61.89 None counter_attack Master-IASD upnquick Success 98.15 4.91 31.25 26.91 30.19 57.1 None attaquedestitans Master-IASD coktailjet Success 75.96 3.8 68.75 18.54 38.4 56.94 None attack_mesonet Master-IASD upnquick Success 78.29 3.91 56.25 22.35 33.31 55.66 None attaqueoudefense Master-IASD coktailjet Success 73.11 3.66 37.5 6.02 25.14 31.16 None rattataque Master-IASD coktailjet Success 131.19 6.56 50.0 6.03 25.13 31.16 None base_model profs coktailjet Success 110.72 5.54 62.5 6.0 25.15 31.15 None attackonnetworks Master-IASD upnquick Success 77.56 3.88 75.0 5.99 25.12 31.11 None attackus Master-IASD upnquick Success 77.59 3.88 50.0 6.01 25.1 31.11 None nyc Master-IASD coktailjet Success 131.61 6.58 50.0 6.02 25.09 31.11 None blast_attack Master-IASD coktailjet Success 98.61 4.93 37.5 5.99 25.1 31.09 None troublemakers Master-IASD coktailjet Success 9727.77 486.39 87.5 6.78 7.15 13.94 None attack-of-babrumen Master-IASD coktailjet Error 0 0 0 0 0 0 FileNotFoundError: [Errno 2] No such file or directory: '/home/lamsade/testplatform/test-platform-a3/repos/Master-IASD/attack-of-babrumen/models/model_spectral_norm[adv_CW].pth' attackonpixels Master-IASD coktailjet Error 0 0 0 0 0 0 RuntimeError: Error(s) in loading state_dict for Net: Missing key(s) in state_dict: "resnet.conv1.weight", "resnet.bn1.weight", "resnet.bn1.bias", "resnet.bn1.running_mean", "resnet.bn1.running_var", "resnet.layer1.0.conv1.weight", "resnet.layer1.0.bn1.weight", "resnet.layer1.0.bn1.bias", "resnet.layer1.0.bn1.running_mean", "resnet.layer1.0.bn1.running_var", "resnet.layer1.0.conv2.weight", "resnet.layer1.0.bn2.weight", "resnet.layer1.0.bn2.bias", "resnet.layer1.0.bn2.running_mean", "resnet.layer1.0.bn2.running_var", "resnet.layer1.1.conv1.weight", "resnet.layer1.1.bn1.weight", "resnet.layer1.1.bn1.bias", "resnet.layer1.1.bn1.running_mean", "resnet.layer1.1.bn1.running_var", "resnet.layer1.1.conv2.weight", "resnet.layer1.1.bn2.weight", "resnet.layer1.1.bn2.bias", "resnet.layer1.1.bn2.running_mean", "resnet.layer1.1.bn2.running_var", "resnet.layer2.0.conv1.weight", "resnet.layer2.0.bn1.weight", "resnet.layer2.0.bn1.bias", "resnet.layer2.0.bn1.running_mean", "resnet.layer2.0.bn1.running_var", "resnet.layer2.0.conv2.weight", "resnet.layer2.0.bn2.weight", "resnet.layer2.0.bn2.bias", "resnet.layer2.0.bn2.running_mean", "resnet.layer2.0.bn2.running_var", "resnet.layer2.0.shortcut.0.weight", "resnet.layer2.0.shortcut.1.weight", "resnet.layer2.0.shortcut.1.bias", "resnet.layer2.0.shortcut.1.running_mean", "resnet.layer2.0.shortcut.1.running_var", "resnet.layer2.1.conv1.weight", "resnet.layer2.1.bn1.weight", "resnet.layer2.1.bn1.bias", "resnet.layer2.1.bn1.running_mean", "resnet.layer2.1.bn1.running_var", "resnet.layer2.1.conv2.weight", "resnet.layer2.1.bn2.weight", "resnet.layer2.1.bn2.bias", "resnet.layer2.1.bn2.running_mean", "resnet.layer2.1.bn2.running_var", "resnet.layer3.0.conv1.weight", "resnet.layer3.0.bn1.weight", "resnet.layer3.0.bn1.bias", "resnet.layer3.0.bn1.running_mean", "resnet.layer3.0.bn1.running_var", "resnet.layer3.0.conv2.weight", "resnet.layer3.0.bn2.weight", "resnet.layer3.0.bn2.bias", "resnet.layer3.0.bn2.running_mean", "resnet.layer3.0.bn2.running_var", "resnet.layer3.0.shortcut.0.weight", "resnet.layer3.0.shortcut.1.weight", "resnet.layer3.0.shortcut.1.bias", "resnet.layer3.0.shortcut.1.running_mean", "resnet.layer3.0.shortcut.1.running_var", "resnet.layer3.1.conv1.weight", "resnet.layer3.1.bn1.weight", "resnet.layer3.1.bn1.bias", "resnet.layer3.1.bn1.running_mean", "resnet.layer3.1.bn1.running_var", "resnet.layer3.1.conv2.weight", "resnet.layer3.1.bn2.weight", "resnet.layer3.1.bn2.bias", "resnet.layer3.1.bn2.running_mean", "resnet.layer3.1.bn2.running_var", "resnet.layer4.0.conv1.weight", "resnet.layer4.0.bn1.weight", "resnet.layer4.0.bn1.bias", "resnet.layer4.0.bn1.running_mean", "resnet.layer4.0.bn1.running_var", "resnet.layer4.0.conv2.weight", "resnet.layer4.0.bn2.weight", "resnet.layer4.0.bn2.bias", "resnet.layer4.0.bn2.running_mean", "resnet.layer4.0.bn2.running_var", "resnet.layer4.0.shortcut.0.weight", "resnet.layer4.0.shortcut.1.weight", "resnet.layer4.0.shortcut.1.bias", "resnet.layer4.0.shortcut.1.running_mean", "resnet.layer4.0.shortcut.1.running_var", "resnet.layer4.1.conv1.weight", "resnet.layer4.1.bn1.weight", "resnet.layer4.1.bn1.bias", "resnet.layer4.1.bn1.running_mean", "resnet.layer4.1.bn1.running_var", "resnet.layer4.1.conv2.weight", "resnet.layer4.1.bn2.weight", "resnet.layer4.1.bn2.bias", "resnet.layer4.1.bn2.running_mean", "resnet.layer4.1.bn2.running_var", "resnet.linear.weight", "resnet.linear.bias". Unexpected key(s) in state_dict: "conv1.weight", "conv1.bias", "conv2.weight", "conv2.bias", "fc1.weight", "fc1.bias", "fc2.weight", "fc2.bias", "fc3.weight", "fc3.bias". ciclose-10 Master-IASD upnquick Error 0 0 0 0 0 0 FileNotFoundError: [Errno 2] No such file or directory: '/home/lamsade/testplatform/test-platform-a3/repos/Master-IASD/ciclose-10/models/default_model.pth' harissa Master-IASD upnquick Error 0 0 0 0 0 0 FileNotFoundError: [Errno 2] No such file or directory: '/home/lamsade/testplatform/test-platform-a3/repos/Master-IASD/harissa/models/default_model.pth' madraf Master-IASD upnquick Error 0 0 0 0 0 0 TypeError: Net.load() missing 1 required positional argument: 'device' team_joie Master-IASD coktailjet Error 0 0 0 0 0 0 AttributeError: module 'model' has no attribute 'Net'

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