Result table

This table was generated on 2025-12-05 at 06:20. 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 5963.88 298.19 100.0 98.09 99.17 197.26 None BestOf2023-1 profs upnquick Success 174.35 8.72 68.75 70.15 70.86 141.01 None gradient-hackers Master-IASD upnquick Success 785.15 39.26 86.25 70.01 68.72 138.74 None blast_attack Master-IASD coktailjet Success 6996.83 349.84 57.5 58.23 68.95 127.18 None attaqueoudefense Master-IASD upnquick Success 4680.29 234.01 67.5 60.19 66.41 126.59 None noeyedeer Master-IASD upnquick Success 1471.96 73.6 87.5 51.8 68.85 120.65 None rattataque Master-IASD coktailjet Success 2522.24 126.11 77.5 48.63 71.31 119.93 None exocet Master-IASD upnquick Success 1286.15 64.31 80.0 51.06 66.09 117.15 None the-taithon-canon Master-IASD coktailjet Success 3051.91 152.6 68.75 49.8 65.67 115.47 None BestOfMiles profs upnquick Success 5424.5 271.22 85.0 51.77 63.43 115.19 None BestOf2024-1 profs upnquick Success 2762.87 138.14 62.5 51.5 63.36 114.86 None BestOf2024-2 profs coktailjet Success 1197.22 59.86 75.0 52.5 59.4 111.9 None best_defense_is_attack Master-IASD coktailjet Success 3386.19 169.31 75.0 50.93 59.28 110.21 None counter_attack Master-IASD coktailjet Success 3243.82 162.19 76.25 46.5 63.12 109.62 None nyc Master-IASD upnquick Success 1401.77 70.09 75.0 44.05 63.75 107.8 None neural-nightmare Master-IASD coktailjet Success 2869.24 143.46 81.25 42.52 54.14 96.66 None attackonpixels Master-IASD upnquick Success 1784.82 89.24 68.75 43.85 52.46 96.31 None BestOf2023-2 profs coktailjet Success 113.82 5.69 50.0 41.12 53.36 94.48 None invisible_attack Master-IASD upnquick Success 5268.2 263.41 83.75 31.71 51.96 83.67 None the-advengers Master-IASD upnquick Success 916.84 45.84 75.0 31.7 50.53 82.23 None jogabonito Master-IASD coktailjet Success 3701.82 185.09 43.75 31.38 48.72 80.1 None attaquedestitans Master-IASD upnquick Success 155.52 7.78 43.75 18.66 38.36 57.02 None attack_mesonet Master-IASD coktailjet Success 105.81 5.29 68.75 22.39 33.28 55.67 None attackonnetworks Master-IASD coktailjet Success 110.09 5.5 31.25 18.31 32.54 50.85 None base_model profs coktailjet Success 112.98 5.65 68.75 6.01 25.15 31.16 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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