Result table

This table was generated on 2025-11-27 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 BestOf2023-1 profs upnquick Success 191.42 9.57 75.0 70.2 70.81 141.01 None BestOf2024-1 profs upnquick Success 2905.07 145.25 62.5 51.63 63.72 115.35 None the-taithon-canon Master-IASD upnquick Success 1222.61 61.13 68.75 49.17 65.54 114.71 None BestOfMiles profs upnquick Success 5567.04 278.35 73.75 51.51 63.13 114.64 None BestOf2024-2 profs coktailjet Success 1157.59 57.88 81.25 52.12 59.58 111.7 None exocet Master-IASD upnquick Success 819.18 40.96 75.0 40.02 55.24 95.26 None neural-nightmare Master-IASD upnquick Success 833.14 41.66 62.5 41.84 53.08 94.92 None BestOf2023-2 profs coktailjet Success 113.9 5.7 62.5 40.96 53.42 94.38 None noeyedeer Master-IASD coktailjet Success 10458.2 522.91 81.25 39.27 53.17 92.44 None jean-ponce Master-IASD coktailjet Success 7386.85 369.34 68.75 31.28 55.65 86.93 None attack-of-babrumen Master-IASD coktailjet Success 95.42 4.77 55.0 34.94 46.25 81.18 None invisible_attack Master-IASD coktailjet Success 5166.24 258.31 75.0 31.53 47.38 78.91 None best_defense_is_attack Master-IASD coktailjet Success 72.54 3.63 50.0 29.11 38.15 67.26 None ciclose-10 Master-IASD upnquick Success 109.95 5.5 50.0 28.92 35.04 63.96 None attack_mesonet Master-IASD upnquick Success 84.37 4.22 50.0 25.68 32.93 58.61 None attaquedestitans Master-IASD coktailjet Success 73.77 3.69 68.75 18.67 38.4 57.07 None attackonpixels Master-IASD coktailjet Success 78.57 3.93 60.0 11.15 28.03 39.18 None rattataque Master-IASD upnquick Success 132.59 6.63 56.25 6.03 25.15 31.18 None base_model profs coktailjet Success 110.48 5.52 81.25 6.06 25.12 31.18 None attaqueoudefense Master-IASD coktailjet Success 72.22 3.61 43.75 6.04 25.13 31.17 None attackus Master-IASD upnquick Success 83.92 4.2 37.5 6.04 25.12 31.16 None gradient-hackers Master-IASD coktailjet Success 77.07 3.85 43.75 6.05 25.09 31.14 None madraf Master-IASD upnquick Success 151.78 7.59 56.25 5.99 25.14 31.13 None nyc Master-IASD upnquick Success 141.86 7.09 62.5 5.98 25.15 31.13 None the-advengers Master-IASD upnquick Success 132.88 6.64 75.0 6.0 25.13 31.13 None jogabonito Master-IASD coktailjet Success 98.59 4.93 25.0 6.0 25.12 31.12 None attackonnetworks Master-IASD upnquick Success 83.93 4.2 43.75 6.0 25.11 31.11 None blast_attack Master-IASD upnquick Success 109.46 5.47 37.5 5.98 25.11 31.09 None counter_attack Master-IASD upnquick Error 0 0 0 0 0 0 ModuleNotFoundError: No module named 'pandas' harissa 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/harissa/models/default_model.pth' team_joie Master-IASD upnquick Error 0 0 0 0 0 0 AttributeError: module 'model' has no attribute 'Net' troublemakers 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: "backbone.conv1.weight", "backbone.block1.layer.0.bn1.weight", "backbone.block1.layer.0.bn1.bias", "backbone.block1.layer.0.bn1.running_mean", "backbone.block1.layer.0.bn1.running_var", "backbone.block1.layer.0.conv1.weight", "backbone.block1.layer.0.bn2.weight", "backbone.block1.layer.0.bn2.bias", "backbone.block1.layer.0.bn2.running_mean", "backbone.block1.layer.0.bn2.running_var", "backbone.block1.layer.0.conv2.weight", "backbone.block1.layer.0.shortcut.weight", "backbone.block1.layer.1.bn1.weight", "backbone.block1.layer.1.bn1.bias", "backbone.block1.layer.1.bn1.running_mean", "backbone.block1.layer.1.bn1.running_var", "backbone.block1.layer.1.conv1.weight", "backbone.block1.layer.1.bn2.weight", "backbone.block1.layer.1.bn2.bias", "backbone.block1.layer.1.bn2.running_mean", "backbone.block1.layer.1.bn2.running_var", "backbone.block1.layer.1.conv2.weight", "backbone.block1.layer.2.bn1.weight", "backbone.block1.layer.2.bn1.bias", "backbone.block1.layer.2.bn1.running_mean", "backbone.block1.layer.2.bn1.running_var", "backbone.block1.layer.2.conv1.weight", "backbone.block1.layer.2.bn2.weight", "backbone.block1.layer.2.bn2.bias", "backbone.block1.layer.2.bn2.running_mean", "backbone.block1.layer.2.bn2.running_var", "backbone.block1.layer.2.conv2.weight", "backbone.block1.layer.3.bn1.weight", "backbone.block1.layer.3.bn1.bias", "backbone.block1.layer.3.bn1.running_mean", "backbone.block1.layer.3.bn1.running_var", "backbone.block1.layer.3.conv1.weight", "backbone.block1.layer.3.bn2.weight", "backbone.block1.layer.3.bn2.bias", "backbone.block1.layer.3.bn2.running_mean", "backbone.block1.layer.3.bn2.running_var", "backbone.block1.layer.3.conv2.weight", "backbone.block2.layer.0.bn1.weight", "backbone.block2.layer.0.bn1.bias", "backbone.block2.layer.0.bn1.running_mean", "backbone.block2.layer.0.bn1.running_var", "backbone.block2.layer.0.conv1.weight", "backbone.block2.layer.0.bn2.weight", "backbone.block2.layer.0.bn2.bias", "backbone.block2.layer.0.bn2.running_mean", "backbone.block2.layer.0.bn2.running_var", "backbone.block2.layer.0.conv2.weight", "backbone.block2.layer.0.shortcut.weight", "backbone.block2.layer.1.bn1.weight", "backbone.block2.layer.1.bn1.bias", "backbone.block2.layer.1.bn1.running_mean", "backbone.block2.layer.1.bn1.running_var", "backbone.block2.layer.1.conv1.weight", "backbone.block2.layer.1.bn2.weight", "backbone.block2.layer.1.bn2.bias", "backbone.block2.layer.1.bn2.running_mean", "backbone.block2.layer.1.bn2.running_var", "backbone.block2.layer.1.conv2.weight", "backbone.block2.layer.2.bn1.weight", "backbone.block2.layer.2.bn1.bias", "backbone.block2.layer.2.bn1.running_mean", "backbone.block2.layer.2.bn1.running_var", "backbone.block2.layer.2.conv1.weight", "backbone.block2.layer.2.bn2.weight", "backbone.block2.layer.2.bn2.bias", "backbone.block2.layer.2.bn2.running_mean", "backbone.block2.layer.2.bn2.running_var", "backbone.block2.layer.2.conv2.weight", "backbone.block2.layer.3.bn1.weight", "backbone.block2.layer.3.bn1.bias", "backbone.block2.layer.3.bn1.running_mean", "backbone.block2.layer.3.bn1.running_var", "backbone.block2.layer.3.conv1.weight", "backbone.block2.layer.3.bn2.weight", "backbone.block2.layer.3.bn2.bias", "backbone.block2.layer.3.bn2.running_mean", "backbone.block2.layer.3.bn2.running_var", "backbone.block2.layer.3.conv2.weight", "backbone.block3.layer.0.bn1.weight", "backbone.block3.layer.0.bn1.bias", "backbone.block3.layer.0.bn1.running_mean", "backbone.block3.layer.0.bn1.running_var", "backbone.block3.layer.0.conv1.weight", "backbone.block3.layer.0.bn2.weight", "backbone.block3.layer.0.bn2.bias", "backbone.block3.layer.0.bn2.running_mean", "backbone.block3.layer.0.bn2.running_var", "backbone.block3.layer.0.conv2.weight", "backbone.block3.layer.0.shortcut.weight", "backbone.block3.layer.1.bn1.weight", "backbone.block3.layer.1.bn1.bias", "backbone.block3.layer.1.bn1.running_mean", "backbone.block3.layer.1.bn1.running_var", "backbone.block3.layer.1.conv1.weight", "backbone.block3.layer.1.bn2.weight", "backbone.block3.layer.1.bn2.bias", "backbone.block3.layer.1.bn2.running_mean", "backbone.block3.layer.1.bn2.running_var", "backbone.block3.layer.1.conv2.weight", "backbone.block3.layer.2.bn1.weight", "backbone.block3.layer.2.bn1.bias", "backbone.block3.layer.2.bn1.running_mean", "backbone.block3.layer.2.bn1.running_var", "backbone.block3.layer.2.conv1.weight", "backbone.block3.layer.2.bn2.weight", "backbone.block3.layer.2.bn2.bias", "backbone.block3.layer.2.bn2.running_mean", "backbone.block3.layer.2.bn2.running_var", "backbone.block3.layer.2.conv2.weight", "backbone.block3.layer.3.bn1.weight", "backbone.block3.layer.3.bn1.bias", "backbone.block3.layer.3.bn1.running_mean", "backbone.block3.layer.3.bn1.running_var", "backbone.block3.layer.3.conv1.weight", "backbone.block3.layer.3.bn2.weight", "backbone.block3.layer.3.bn2.bias", "backbone.block3.layer.3.bn2.running_mean", "backbone.block3.layer.3.bn2.running_var", "backbone.block3.layer.3.conv2.weight", "backbone.bn1.weight", "backbone.bn1.bias", "backbone.bn1.running_mean", "backbone.bn1.running_var", "backbone.fc.weight", "backbone.fc.bias". Unexpected key(s) in state_dict: "conv1_1.weight", "conv1_1.bias", "bn1_1.weight", "bn1_1.bias", "bn1_1.running_mean", "bn1_1.running_var", "bn1_1.num_batches_tracked", "conv1_2.weight", "conv1_2.bias", "bn1_2.weight", "bn1_2.bias", "bn1_2.running_mean", "bn1_2.running_var", "bn1_2.num_batches_tracked", "conv2_1.weight", "conv2_1.bias", "bn2_1.weight", "bn2_1.bias", "bn2_1.running_mean", "bn2_1.running_var", "bn2_1.num_batches_tracked", "conv2_2.weight", "conv2_2.bias", "bn2_2.weight", "bn2_2.bias", "bn2_2.running_mean", "bn2_2.running_var", "bn2_2.num_batches_tracked", "conv3_1.weight", "conv3_1.bias", "bn3_1.weight", "bn3_1.bias", "bn3_1.running_mean", "bn3_1.running_var", "bn3_1.num_batches_tracked", "conv3_2.weight", "conv3_2.bias", "bn3_2.weight", "bn3_2.bias", "bn3_2.running_mean", "bn3_2.running_var", "bn3_2.num_batches_tracked", "fc1.weight", "fc1.bias", "fc2.weight", "fc2.bias".

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