Result table

This table was generated on 2025-12-10 at 06:27. 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 5960.14 298.01 100.0 98.0 99.35 197.35 None BestOf2023-1 profs upnquick Success 174.62 8.73 43.75 70.37 70.81 141.18 None gradient-hackers Master-IASD upnquick Success 784.59 39.23 87.5 70.05 68.38 138.43 None blast_attack Master-IASD coktailjet Success 7219.82 360.99 57.5 58.02 69.24 127.27 None attaqueoudefense Master-IASD upnquick Success 4703.44 235.17 80.0 60.33 65.76 126.09 None noeyedeer Master-IASD upnquick Success 1456.99 72.85 65.0 51.42 68.89 120.32 None rattataque Master-IASD coktailjet Success 2618.03 130.9 75.0 48.7 71.32 120.02 None exocet Master-IASD upnquick Success 1287.41 64.37 75.0 50.92 65.94 116.86 None the-taithon-canon Master-IASD coktailjet Success 3241.95 162.1 81.25 49.52 65.92 115.44 None BestOfMiles profs upnquick Success 5393.67 269.68 57.5 51.49 63.52 115.0 None BestOf2024-1 profs upnquick Success 2800.64 140.03 55.0 51.36 63.45 114.81 None BestOf2024-2 profs coktailjet Success 1367.97 68.4 56.25 52.15 59.44 111.59 None best_defense_is_attack Master-IASD coktailjet Success 3484.82 174.24 75.0 50.95 59.3 110.25 None counter_attack Master-IASD coktailjet Success 3355.43 167.77 78.75 46.06 63.19 109.25 None nyc Master-IASD upnquick Success 1395.93 69.8 82.5 43.64 63.21 106.85 None attackonpixels Master-IASD upnquick Success 1793.15 89.66 68.75 44.28 52.67 96.95 None neural-nightmare Master-IASD coktailjet Success 2966.26 148.31 75.0 42.49 54.1 96.59 None BestOf2023-2 profs coktailjet Success 124.55 6.23 68.75 40.88 53.45 94.33 None invisible_attack Master-IASD upnquick Success 5247.24 262.36 80.0 32.29 52.0 84.29 None the-advengers Master-IASD upnquick Success 917.45 45.87 75.0 31.28 50.22 81.5 None jogabonito Master-IASD coktailjet Success 3816.2 190.81 68.75 31.04 48.76 79.8 None attaquedestitans Master-IASD upnquick Success 150.75 7.54 56.25 18.62 38.43 57.05 None attack_mesonet Master-IASD coktailjet Success 115.84 5.79 18.75 22.42 33.3 55.72 None attackonnetworks Master-IASD coktailjet Success 121.51 6.08 37.5 18.24 32.58 50.82 None base_model profs coktailjet Success 123.74 6.19 37.5 5.98 25.11 31.09 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'

Plots