Result table

This table was generated on 2025-12-11 at 08:23. 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 5963.13 298.16 100.0 97.89 99.32 197.21 None BestOf2023-1 profs coktailjet Success 187.96 9.4 50.0 70.2 70.72 140.92 None gradient-hackers Master-IASD upnquick Success 783.51 39.18 77.5 69.76 69.04 138.81 None blast_attack Master-IASD coktailjet Success 7216.8 360.84 57.5 58.68 69.28 127.97 None attaqueoudefense Master-IASD upnquick Success 4678.11 233.91 72.5 60.11 66.16 126.27 None noeyedeer Master-IASD upnquick Success 1456.77 72.84 50.0 51.17 68.72 119.88 None rattataque Master-IASD coktailjet Success 2621.14 131.06 53.75 48.56 70.99 119.55 None exocet Master-IASD upnquick Success 1285.16 64.26 72.5 51.63 65.94 117.57 None BestOf2024-1 profs coktailjet Success 5750.97 287.55 51.25 51.93 63.37 115.3 None BestOfMiles profs coktailjet Success 12304.06 615.2 75.0 51.5 63.37 114.86 None the-taithon-canon Master-IASD coktailjet Success 3289.66 164.48 68.75 49.1 65.26 114.36 None BestOf2024-2 profs upnquick Success 638.18 31.91 62.5 51.79 59.74 111.53 None best_defense_is_attack Master-IASD coktailjet Success 3500.73 175.04 93.75 50.92 59.24 110.16 None counter_attack Master-IASD coktailjet Success 3365.03 168.25 85.0 46.06 63.49 109.55 None nyc Master-IASD upnquick Success 1392.39 69.62 56.25 44.37 63.71 108.08 None attackonpixels Master-IASD upnquick Success 1788.76 89.44 62.5 44.22 52.45 96.67 None neural-nightmare Master-IASD coktailjet Success 2982.64 149.13 68.75 42.53 54.09 96.62 None BestOf2023-2 profs upnquick Success 121.01 6.05 62.5 40.8 53.49 94.29 None invisible_attack Master-IASD upnquick Success 5273.39 263.67 92.5 31.85 51.93 83.78 None the-advengers Master-IASD upnquick Success 895.82 44.79 81.25 31.3 49.97 81.27 None jogabonito Master-IASD coktailjet Success 3832.4 191.62 81.25 31.8 48.45 80.25 None attaquedestitans Master-IASD upnquick Success 154.27 7.71 68.75 18.59 38.4 56.99 None attack_mesonet Master-IASD coktailjet Success 114.37 5.72 43.75 22.33 33.3 55.63 None attackonnetworks Master-IASD coktailjet Success 120.18 6.01 31.25 18.35 32.58 50.93 None base_model profs upnquick Success 118.63 5.93 56.25 6.04 25.14 31.18 None attack-of-babrumen Master-IASD upnquick Error 0 0 0 0 0 0 AttributeError: 'Net' object has no attribute 'load_for_testing' attackus Master-IASD coktailjet Error 0 0 0 0 0 0 FileNotFoundError: Model file not found: /home/lamsade/testplatform/test-platform-a3/repos/Master-IASD/attackus/models/robust_model.pth ciclose-10 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/ciclose-10/models/default_model.pth' compo-4-3-3 Master-IASD coktailjet Error 0 0 0 0 0 0 FileNotFoundError: [Errno 2] No such file or directory: 'models/resnet_adv_finetune_8_pgd_3.pth' harissa Master-IASD upnquick Error 0 0 0 0 0 0 FileNotFoundError: The config file does not exist. Model could not be loaded properly. madraf 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/madraf/models/default_model.pth' team_joie Master-IASD upnquick Error 0 0 0 0 0 0 RuntimeError: Error(s) in loading state_dict for Net: Missing key(s) in state_dict: "conv1.weight", "conv1.bias", "conv2.weight", "conv2.bias", "conv3.weight", "conv3.bias", "conv4.weight", "conv4.bias", "fc1.weight", "fc1.bias", "fc2.weight", "fc2.bias", "fc3.weight", "fc3.bias". Unexpected key(s) in state_dict: "model.conv1.weight", "model.bn1.weight", "model.bn1.bias", "model.bn1.running_mean", "model.bn1.running_var", "model.bn1.num_batches_tracked", "model.layer1.0.conv1.weight", "model.layer1.0.bn1.weight", "model.layer1.0.bn1.bias", "model.layer1.0.bn1.running_mean", "model.layer1.0.bn1.running_var", "model.layer1.0.bn1.num_batches_tracked", "model.layer1.0.conv2.weight", "model.layer1.0.bn2.weight", "model.layer1.0.bn2.bias", "model.layer1.0.bn2.running_mean", "model.layer1.0.bn2.running_var", "model.layer1.0.bn2.num_batches_tracked", "model.layer1.1.conv1.weight", "model.layer1.1.bn1.weight", "model.layer1.1.bn1.bias", "model.layer1.1.bn1.running_mean", "model.layer1.1.bn1.running_var", "model.layer1.1.bn1.num_batches_tracked", "model.layer1.1.conv2.weight", "model.layer1.1.bn2.weight", "model.layer1.1.bn2.bias", "model.layer1.1.bn2.running_mean", "model.layer1.1.bn2.running_var", "model.layer1.1.bn2.num_batches_tracked", "model.layer2.0.conv1.weight", "model.layer2.0.bn1.weight", "model.layer2.0.bn1.bias", "model.layer2.0.bn1.running_mean", "model.layer2.0.bn1.running_var", "model.layer2.0.bn1.num_batches_tracked", "model.layer2.0.conv2.weight", "model.layer2.0.bn2.weight", "model.layer2.0.bn2.bias", "model.layer2.0.bn2.running_mean", "model.layer2.0.bn2.running_var", "model.layer2.0.bn2.num_batches_tracked", "model.layer2.0.downsample.0.weight", "model.layer2.0.downsample.1.weight", "model.layer2.0.downsample.1.bias", "model.layer2.0.downsample.1.running_mean", "model.layer2.0.downsample.1.running_var", "model.layer2.0.downsample.1.num_batches_tracked", "model.layer2.1.conv1.weight", "model.layer2.1.bn1.weight", "model.layer2.1.bn1.bias", "model.layer2.1.bn1.running_mean", "model.layer2.1.bn1.running_var", "model.layer2.1.bn1.num_batches_tracked", "model.layer2.1.conv2.weight", "model.layer2.1.bn2.weight", "model.layer2.1.bn2.bias", "model.layer2.1.bn2.running_mean", "model.layer2.1.bn2.running_var", "model.layer2.1.bn2.num_batches_tracked", "model.layer3.0.conv1.weight", "model.layer3.0.bn1.weight", "model.layer3.0.bn1.bias", "model.layer3.0.bn1.running_mean", "model.layer3.0.bn1.running_var", "model.layer3.0.bn1.num_batches_tracked", "model.layer3.0.conv2.weight", "model.layer3.0.bn2.weight", "model.layer3.0.bn2.bias", "model.layer3.0.bn2.running_mean", "model.layer3.0.bn2.running_var", "model.layer3.0.bn2.num_batches_tracked", "model.layer3.0.downsample.0.weight", "model.layer3.0.downsample.1.weight", "model.layer3.0.downsample.1.bias", "model.layer3.0.downsample.1.running_mean", "model.layer3.0.downsample.1.running_var", "model.layer3.0.downsample.1.num_batches_tracked", "model.layer3.1.conv1.weight", "model.layer3.1.bn1.weight", "model.layer3.1.bn1.bias", "model.layer3.1.bn1.running_mean", "model.layer3.1.bn1.running_var", "model.layer3.1.bn1.num_batches_tracked", "model.layer3.1.conv2.weight", "model.layer3.1.bn2.weight", "model.layer3.1.bn2.bias", "model.layer3.1.bn2.running_mean", "model.layer3.1.bn2.running_var", "model.layer3.1.bn2.num_batches_tracked", "model.layer4.0.conv1.weight", "model.layer4.0.bn1.weight", "model.layer4.0.bn1.bias", "model.layer4.0.bn1.running_mean", "model.layer4.0.bn1.running_var", "model.layer4.0.bn1.num_batches_tracked", "model.layer4.0.conv2.weight", "model.layer4.0.bn2.weight", "model.layer4.0.bn2.bias", "model.layer4.0.bn2.running_mean", "model.layer4.0.bn2.running_var", "model.layer4.0.bn2.num_batches_tracked", "model.layer4.0.downsample.0.weight", "model.layer4.0.downsample.1.weight", "model.layer4.0.downsample.1.bias", "model.layer4.0.downsample.1.running_mean", "model.layer4.0.downsample.1.running_var", "model.layer4.0.downsample.1.num_batches_tracked", "model.layer4.1.conv1.weight", "model.layer4.1.bn1.weight", "model.layer4.1.bn1.bias", "model.layer4.1.bn1.running_mean", "model.layer4.1.bn1.running_var", "model.layer4.1.bn1.num_batches_tracked", "model.layer4.1.conv2.weight", "model.layer4.1.bn2.weight", "model.layer4.1.bn2.bias", "model.layer4.1.bn2.running_mean", "model.layer4.1.bn2.running_var", "model.layer4.1.bn2.num_batches_tracked", "model.fc.weight", "model.fc.bias". troublemakers 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/troublemakers/models/ensemble_adp_model_0.pth'

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