Result table

This table was generated on 2025-12-04 at 08:47. 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 11123.01 556.15 100.0 97.85 99.4 197.25 None BestOf2023-1 profs coktailjet Success 170.88 8.54 68.75 70.14 70.67 140.81 None gradient-hackers Master-IASD upnquick Success 859.65 42.98 92.5 69.95 68.89 138.84 None attaqueoudefense Master-IASD coktailjet Success 11434.84 571.74 57.5 60.73 66.2 126.93 None blast_attack Master-IASD coktailjet Success 7084.13 354.21 57.5 58.06 68.78 126.84 None noeyedeer Master-IASD upnquick Success 2152.27 107.61 75.0 51.58 69.05 120.63 None rattataque Master-IASD coktailjet Success 3370.83 168.54 77.5 48.5 70.83 119.32 None exocet Master-IASD upnquick Success 1796.47 89.82 87.5 51.09 65.94 117.03 None the-taithon-canon Master-IASD upnquick Success 2674.82 133.74 50.0 49.56 65.6 115.16 None BestOf2024-1 profs coktailjet Success 5291.75 264.59 62.5 51.68 63.41 115.09 None BestOfMiles profs coktailjet Success 11113.16 555.66 61.25 51.52 63.57 115.09 None BestOf2024-2 profs upnquick Success 1329.27 66.46 68.75 52.37 59.72 112.09 None best_defense_is_attack Master-IASD upnquick Success 1839.09 91.95 93.75 50.92 59.26 110.18 None counter_attack Master-IASD upnquick Success 1934.46 96.72 61.25 46.28 62.87 109.16 None nyc Master-IASD upnquick Success 2137.95 106.9 62.5 44.21 63.52 107.74 None neural-nightmare Master-IASD coktailjet Success 2898.06 144.9 62.5 42.57 54.11 96.68 None attackonpixels Master-IASD coktailjet Success 4110.81 205.54 75.0 43.87 52.06 95.93 None BestOf2023-2 profs upnquick Success 193.0 9.65 81.25 40.85 53.46 94.31 None invisible_attack Master-IASD upnquick Success 7513.23 375.66 73.75 31.63 51.94 83.57 None the-advengers Master-IASD coktailjet Success 3408.21 170.41 93.75 31.65 49.92 81.57 None jogabonito Master-IASD upnquick Success 2040.02 102.0 75.0 31.31 48.93 80.24 None attaquedestitans Master-IASD coktailjet Success 148.49 7.42 56.25 18.66 38.37 57.03 None attack_mesonet Master-IASD upnquick Success 185.18 9.26 68.75 22.32 33.3 55.62 None attackonnetworks Master-IASD upnquick Success 184.23 9.21 56.25 18.26 32.58 50.84 None base_model profs upnquick Success 189.21 9.46 43.75 6.0 25.11 31.11 None attack-of-babrumen Master-IASD coktailjet Error 0 0 0 0 0 0 AttributeError: 'Net' object has no attribute 'load_for_testing' attackus Master-IASD upnquick 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 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' compo-4-3-3 Master-IASD upnquick 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 coktailjet 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 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/troublemakers/models/ensemble_adp_model_0.pth'

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