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lunwen_ccfc_cifar100_centeral.log
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nohup: ignoring input
cuda:1
Namespace(batch_size=140, data_root='./datasets', exp_dir='./save/CCFC/Cifar100', global_lr=1, image_size=224, k=20, latent_dim=256, lbd=0.1, lr=0.0005, mini_bs=140, n_clients=480, num_proj_layers=2, num_workers=6, p=0.0, pre_hidden_dim=64, proj_hidden_dim=512, resnet='ResNet18', seed=66, test_image_size=256, trial='v0')
Global NMI = 0.1602 ARI = 0.0653 F = 0.1132 ACC = 0.1917
backbone.conv1.weight 9408 torch.Size([64, 3, 7, 7])
backbone.bn1.weight 64 torch.Size([64])
backbone.bn1.bias 64 torch.Size([64])
backbone.layer1.0.conv1.weight 36864 torch.Size([64, 64, 3, 3])
backbone.layer1.0.bn1.weight 64 torch.Size([64])
backbone.layer1.0.bn1.bias 64 torch.Size([64])
backbone.layer1.0.conv2.weight 36864 torch.Size([64, 64, 3, 3])
backbone.layer1.0.bn2.weight 64 torch.Size([64])
backbone.layer1.0.bn2.bias 64 torch.Size([64])
backbone.layer1.1.conv1.weight 36864 torch.Size([64, 64, 3, 3])
backbone.layer1.1.bn1.weight 64 torch.Size([64])
backbone.layer1.1.bn1.bias 64 torch.Size([64])
backbone.layer1.1.conv2.weight 36864 torch.Size([64, 64, 3, 3])
backbone.layer1.1.bn2.weight 64 torch.Size([64])
backbone.layer1.1.bn2.bias 64 torch.Size([64])
backbone.layer2.0.conv1.weight 73728 torch.Size([128, 64, 3, 3])
backbone.layer2.0.bn1.weight 128 torch.Size([128])
backbone.layer2.0.bn1.bias 128 torch.Size([128])
backbone.layer2.0.conv2.weight 147456 torch.Size([128, 128, 3, 3])
backbone.layer2.0.bn2.weight 128 torch.Size([128])
backbone.layer2.0.bn2.bias 128 torch.Size([128])
backbone.layer2.0.downsample.0.weight 8192 torch.Size([128, 64, 1, 1])
backbone.layer2.0.downsample.1.weight 128 torch.Size([128])
backbone.layer2.0.downsample.1.bias 128 torch.Size([128])
backbone.layer2.1.conv1.weight 147456 torch.Size([128, 128, 3, 3])
backbone.layer2.1.bn1.weight 128 torch.Size([128])
backbone.layer2.1.bn1.bias 128 torch.Size([128])
backbone.layer2.1.conv2.weight 147456 torch.Size([128, 128, 3, 3])
backbone.layer2.1.bn2.weight 128 torch.Size([128])
backbone.layer2.1.bn2.bias 128 torch.Size([128])
backbone.layer3.0.conv1.weight 294912 torch.Size([256, 128, 3, 3])
backbone.layer3.0.bn1.weight 256 torch.Size([256])
backbone.layer3.0.bn1.bias 256 torch.Size([256])
backbone.layer3.0.conv2.weight 589824 torch.Size([256, 256, 3, 3])
backbone.layer3.0.bn2.weight 256 torch.Size([256])
backbone.layer3.0.bn2.bias 256 torch.Size([256])
backbone.layer3.0.downsample.0.weight 32768 torch.Size([256, 128, 1, 1])
backbone.layer3.0.downsample.1.weight 256 torch.Size([256])
backbone.layer3.0.downsample.1.bias 256 torch.Size([256])
backbone.layer3.1.conv1.weight 589824 torch.Size([256, 256, 3, 3])
backbone.layer3.1.bn1.weight 256 torch.Size([256])
backbone.layer3.1.bn1.bias 256 torch.Size([256])
backbone.layer3.1.conv2.weight 589824 torch.Size([256, 256, 3, 3])
backbone.layer3.1.bn2.weight 256 torch.Size([256])
backbone.layer3.1.bn2.bias 256 torch.Size([256])
backbone.layer4.0.conv1.weight 1179648 torch.Size([512, 256, 3, 3])
backbone.layer4.0.bn1.weight 512 torch.Size([512])
backbone.layer4.0.bn1.bias 512 torch.Size([512])
backbone.layer4.0.conv2.weight 2359296 torch.Size([512, 512, 3, 3])
backbone.layer4.0.bn2.weight 512 torch.Size([512])
backbone.layer4.0.bn2.bias 512 torch.Size([512])
backbone.layer4.0.downsample.0.weight 131072 torch.Size([512, 256, 1, 1])
backbone.layer4.0.downsample.1.weight 512 torch.Size([512])
backbone.layer4.0.downsample.1.bias 512 torch.Size([512])
backbone.layer4.1.conv1.weight 2359296 torch.Size([512, 512, 3, 3])
backbone.layer4.1.bn1.weight 512 torch.Size([512])
backbone.layer4.1.bn1.bias 512 torch.Size([512])
backbone.layer4.1.conv2.weight 2359296 torch.Size([512, 512, 3, 3])
backbone.layer4.1.bn2.weight 512 torch.Size([512])
backbone.layer4.1.bn2.bias 512 torch.Size([512])
projector.layer1.0.weight 262144 torch.Size([512, 512])
projector.layer1.0.bias 512 torch.Size([512])
projector.layer1.1.weight 512 torch.Size([512])
projector.layer1.1.bias 512 torch.Size([512])
projector.layer2.0.weight 262144 torch.Size([512, 512])
projector.layer2.0.bias 512 torch.Size([512])
projector.layer2.1.weight 512 torch.Size([512])
projector.layer2.1.bias 512 torch.Size([512])
projector.layer3.0.weight 131072 torch.Size([256, 512])
projector.layer3.0.bias 256 torch.Size([256])
predictor.layer1.0.weight 16384 torch.Size([64, 256])
predictor.layer1.0.bias 64 torch.Size([64])
predictor.layer1.1.weight 64 torch.Size([64])
predictor.layer1.1.bias 64 torch.Size([64])
predictor.layer2.weight 16384 torch.Size([256, 64])
predictor.layer2.bias 256 torch.Size([256])
Round: 0 Train Loss: -1.760
Global NMI = 0.1853 ARI = 0.0786 F = 0.1256 ACC = 0.2113
Round: 1 Train Loss: -1.773
Global NMI = 0.1924 ARI = 0.0856 F = 0.1328 ACC = 0.2171
Round: 2 Train Loss: -1.777
Global NMI = 0.1893 ARI = 0.0825 F = 0.1297 ACC = 0.2119
Round: 3 Train Loss: -1.782
Global NMI = 0.1934 ARI = 0.0908 F = 0.1369 ACC = 0.2234
Round: 4 Train Loss: -1.786
Global NMI = 0.1963 ARI = 0.0899 F = 0.1362 ACC = 0.2210
Round: 5 Train Loss: -1.794
Global NMI = 0.1915 ARI = 0.0883 F = 0.1345 ACC = 0.2173
Round: 6 Train Loss: -1.802
Global NMI = 0.2002 ARI = 0.0950 F = 0.1408 ACC = 0.2354
Round: 7 Train Loss: -1.806
Global NMI = 0.2041 ARI = 0.0972 F = 0.1436 ACC = 0.2361
Round: 8 Train Loss: -1.809
Global NMI = 0.2019 ARI = 0.0962 F = 0.1421 ACC = 0.2271
Round: 9 Train Loss: -1.811
Global NMI = 0.2105 ARI = 0.1020 F = 0.1479 ACC = 0.2457
Round: 10 Train Loss: -1.813
Global NMI = 0.2119 ARI = 0.0975 F = 0.1437 ACC = 0.2367
Round: 11 Train Loss: -1.815
Global NMI = 0.2086 ARI = 0.0983 F = 0.1444 ACC = 0.2407
Round: 12 Train Loss: -1.818
Global NMI = 0.2187 ARI = 0.1068 F = 0.1520 ACC = 0.2527
Round: 13 Train Loss: -1.818
Global NMI = 0.2199 ARI = 0.1095 F = 0.1552 ACC = 0.2549
Round: 14 Train Loss: -1.820
Global NMI = 0.2201 ARI = 0.1056 F = 0.1513 ACC = 0.2491
Round: 15 Train Loss: -1.822
Global NMI = 0.2252 ARI = 0.1115 F = 0.1569 ACC = 0.2510
Round: 16 Train Loss: -1.821
Global NMI = 0.2172 ARI = 0.1025 F = 0.1480 ACC = 0.2404
Round: 17 Train Loss: -1.821
Global NMI = 0.2248 ARI = 0.1084 F = 0.1535 ACC = 0.2455
Round: 18 Train Loss: -1.820
Global NMI = 0.2248 ARI = 0.1122 F = 0.1576 ACC = 0.2522
Round: 19 Train Loss: -1.817
Global NMI = 0.2159 ARI = 0.1009 F = 0.1466 ACC = 0.2537
Round: 20 Train Loss: -1.816
Global NMI = 0.2186 ARI = 0.1074 F = 0.1528 ACC = 0.2523
Round: 21 Train Loss: -1.819
Global NMI = 0.2232 ARI = 0.1092 F = 0.1543 ACC = 0.2576
Round: 22 Train Loss: -1.820
Global NMI = 0.2321 ARI = 0.1114 F = 0.1565 ACC = 0.2621
Round: 23 Train Loss: -1.820
Global NMI = 0.2259 ARI = 0.1076 F = 0.1533 ACC = 0.2493
Round: 24 Train Loss: -1.821
Global NMI = 0.2240 ARI = 0.1100 F = 0.1554 ACC = 0.2535
Round: 25 Train Loss: -1.826
Global NMI = 0.2215 ARI = 0.1057 F = 0.1514 ACC = 0.2383
Round: 26 Train Loss: -1.828
Global NMI = 0.2194 ARI = 0.1041 F = 0.1497 ACC = 0.2450
Round: 27 Train Loss: -1.825
Global NMI = 0.2294 ARI = 0.1119 F = 0.1567 ACC = 0.2554
Round: 28 Train Loss: -1.824
Global NMI = 0.2307 ARI = 0.1160 F = 0.1607 ACC = 0.2555
Round: 29 Train Loss: -1.822
Global NMI = 0.2342 ARI = 0.1125 F = 0.1574 ACC = 0.2585
Round: 30 Train Loss: -1.819
Global NMI = 0.2318 ARI = 0.1132 F = 0.1583 ACC = 0.2611
Round: 31 Train Loss: -1.819
Global NMI = 0.2356 ARI = 0.1170 F = 0.1623 ACC = 0.2645
Round: 32 Train Loss: -1.817
Global NMI = 0.2413 ARI = 0.1196 F = 0.1655 ACC = 0.2667
Round: 33 Train Loss: -1.817
Global NMI = 0.2391 ARI = 0.1209 F = 0.1654 ACC = 0.2688
Round: 34 Train Loss: -1.820
Global NMI = 0.2322 ARI = 0.1139 F = 0.1594 ACC = 0.2440
Round: 35 Train Loss: -1.820
Global NMI = 0.2370 ARI = 0.1190 F = 0.1638 ACC = 0.2752
Round: 36 Train Loss: -1.821
Global NMI = 0.2317 ARI = 0.1139 F = 0.1589 ACC = 0.2658
Round: 37 Train Loss: -1.823
Global NMI = 0.2339 ARI = 0.1163 F = 0.1612 ACC = 0.2631
Round: 38 Train Loss: -1.827
Global NMI = 0.2442 ARI = 0.1230 F = 0.1677 ACC = 0.2750
Round: 39 Train Loss: -1.830
Global NMI = 0.2513 ARI = 0.1245 F = 0.1690 ACC = 0.2857
Round: 40 Train Loss: -1.831
Global NMI = 0.2406 ARI = 0.1183 F = 0.1634 ACC = 0.2711
Round: 41 Train Loss: -1.833
Global NMI = 0.2440 ARI = 0.1189 F = 0.1637 ACC = 0.2768
Round: 42 Train Loss: -1.833
Global NMI = 0.2426 ARI = 0.1192 F = 0.1640 ACC = 0.2720
Round: 43 Train Loss: -1.832
Global NMI = 0.2462 ARI = 0.1170 F = 0.1624 ACC = 0.2781
Round: 44 Train Loss: -1.830
Global NMI = 0.2467 ARI = 0.1253 F = 0.1700 ACC = 0.2713
Round: 45 Train Loss: -1.827
Global NMI = 0.2404 ARI = 0.1235 F = 0.1682 ACC = 0.2706
Round: 46 Train Loss: -1.828
Global NMI = 0.2567 ARI = 0.1269 F = 0.1717 ACC = 0.2822
Round: 47 Train Loss: -1.832
Global NMI = 0.2505 ARI = 0.1234 F = 0.1681 ACC = 0.2831
Round: 48 Train Loss: -1.834
Global NMI = 0.2598 ARI = 0.1302 F = 0.1744 ACC = 0.2859
Round: 49 Train Loss: -1.838
Global NMI = 0.2537 ARI = 0.1300 F = 0.1743 ACC = 0.2824
Round: 50 Train Loss: -1.838
Global NMI = 0.2562 ARI = 0.1322 F = 0.1762 ACC = 0.2884
Round: 51 Train Loss: -1.839
Global NMI = 0.2660 ARI = 0.1376 F = 0.1815 ACC = 0.2975
Round: 52 Train Loss: -1.840
Global NMI = 0.2588 ARI = 0.1268 F = 0.1715 ACC = 0.2848
Round: 53 Train Loss: -1.843
Global NMI = 0.2589 ARI = 0.1315 F = 0.1756 ACC = 0.2885
Round: 54 Train Loss: -1.844
Global NMI = 0.2552 ARI = 0.1331 F = 0.1773 ACC = 0.2776
Round: 55 Train Loss: -1.844
Global NMI = 0.2497 ARI = 0.1230 F = 0.1681 ACC = 0.2772
Round: 56 Train Loss: -1.844
Global NMI = 0.2616 ARI = 0.1357 F = 0.1797 ACC = 0.2964
Round: 57 Train Loss: -1.843
Global NMI = 0.2636 ARI = 0.1360 F = 0.1799 ACC = 0.3009
Round: 58 Train Loss: -1.843
Global NMI = 0.2658 ARI = 0.1371 F = 0.1811 ACC = 0.2963
Round: 59 Train Loss: -1.845
Global NMI = 0.2695 ARI = 0.1384 F = 0.1823 ACC = 0.2942
Round: 60 Train Loss: -1.842
Global NMI = 0.2692 ARI = 0.1394 F = 0.1838 ACC = 0.2997
Round: 61 Train Loss: -1.841
Global NMI = 0.2669 ARI = 0.1382 F = 0.1820 ACC = 0.2958
Round: 62 Train Loss: -1.844
Global NMI = 0.2704 ARI = 0.1391 F = 0.1832 ACC = 0.2971
Round: 63 Train Loss: -1.845
Global NMI = 0.2721 ARI = 0.1450 F = 0.1884 ACC = 0.3045
Round: 64 Train Loss: -1.841
Global NMI = 0.2691 ARI = 0.1377 F = 0.1815 ACC = 0.2884
Round: 65 Train Loss: -1.841
Global NMI = 0.2652 ARI = 0.1363 F = 0.1803 ACC = 0.2916
Round: 66 Train Loss: -1.839
Global NMI = 0.2719 ARI = 0.1399 F = 0.1836 ACC = 0.3026
Round: 67 Train Loss: -1.843
Global NMI = 0.2606 ARI = 0.1299 F = 0.1742 ACC = 0.2829
Round: 68 Train Loss: -1.842
Global NMI = 0.2666 ARI = 0.1381 F = 0.1818 ACC = 0.2957
Round: 69 Train Loss: -1.843
Global NMI = 0.2680 ARI = 0.1395 F = 0.1834 ACC = 0.2912
Round: 70 Train Loss: -1.846
Global NMI = 0.2709 ARI = 0.1419 F = 0.1857 ACC = 0.2957
Round: 71 Train Loss: -1.845
Global NMI = 0.2740 ARI = 0.1425 F = 0.1865 ACC = 0.2948
Round: 72 Train Loss: -1.845
Global NMI = 0.2774 ARI = 0.1464 F = 0.1898 ACC = 0.2966
Round: 73 Train Loss: -1.845
Global NMI = 0.2805 ARI = 0.1528 F = 0.1962 ACC = 0.3065
Round: 74 Train Loss: -1.849
Global NMI = 0.2725 ARI = 0.1447 F = 0.1884 ACC = 0.3042
Round: 75 Train Loss: -1.849
Global NMI = 0.2730 ARI = 0.1389 F = 0.1829 ACC = 0.2947
Round: 76 Train Loss: -1.850
Global NMI = 0.2758 ARI = 0.1401 F = 0.1842 ACC = 0.2952
Round: 77 Train Loss: -1.853
Global NMI = 0.2752 ARI = 0.1372 F = 0.1814 ACC = 0.2957
Round: 78 Train Loss: -1.853
Global NMI = 0.2787 ARI = 0.1398 F = 0.1840 ACC = 0.3009
Round: 79 Train Loss: -1.851
Global NMI = 0.2793 ARI = 0.1422 F = 0.1860 ACC = 0.3015
Round: 80 Train Loss: -1.850
Global NMI = 0.2756 ARI = 0.1445 F = 0.1888 ACC = 0.2910
Round: 81 Train Loss: -1.849
Global NMI = 0.2722 ARI = 0.1341 F = 0.1788 ACC = 0.2888
Round: 82 Train Loss: -1.849
Global NMI = 0.2881 ARI = 0.1448 F = 0.1887 ACC = 0.3099
Round: 83 Train Loss: -1.847
Global NMI = 0.2813 ARI = 0.1350 F = 0.1803 ACC = 0.2942
Round: 84 Train Loss: -1.850
Global NMI = 0.2826 ARI = 0.1394 F = 0.1838 ACC = 0.2959
Round: 85 Train Loss: -1.852
Global NMI = 0.2842 ARI = 0.1434 F = 0.1873 ACC = 0.3008
Round: 86 Train Loss: -1.851
Global NMI = 0.2810 ARI = 0.1409 F = 0.1854 ACC = 0.3062
Round: 87 Train Loss: -1.852
Global NMI = 0.2761 ARI = 0.1343 F = 0.1790 ACC = 0.2891
Round: 88 Train Loss: -1.852
Global NMI = 0.2857 ARI = 0.1435 F = 0.1876 ACC = 0.3129
Round: 89 Train Loss: -1.855
Global NMI = 0.2809 ARI = 0.1430 F = 0.1870 ACC = 0.3042
Round: 90 Train Loss: -1.853
Global NMI = 0.2814 ARI = 0.1401 F = 0.1839 ACC = 0.2972
Round: 91 Train Loss: -1.853
Global NMI = 0.2890 ARI = 0.1475 F = 0.1914 ACC = 0.3134
Round: 92 Train Loss: -1.850
Global NMI = 0.2826 ARI = 0.1452 F = 0.1888 ACC = 0.3000
Round: 93 Train Loss: -1.852
Global NMI = 0.2834 ARI = 0.1427 F = 0.1868 ACC = 0.2974
Round: 94 Train Loss: -1.849
Global NMI = 0.2890 ARI = 0.1484 F = 0.1922 ACC = 0.3127
Round: 95 Train Loss: -1.852
Global NMI = 0.2832 ARI = 0.1463 F = 0.1897 ACC = 0.2968
Round: 96 Train Loss: -1.851
Global NMI = 0.2851 ARI = 0.1438 F = 0.1875 ACC = 0.3028
Round: 97 Train Loss: -1.852
Global NMI = 0.2965 ARI = 0.1574 F = 0.2006 ACC = 0.3224
Round: 98 Train Loss: -1.853
Global NMI = 0.2937 ARI = 0.1523 F = 0.1952 ACC = 0.3068
Round: 99 Train Loss: -1.854
Global NMI = 0.2885 ARI = 0.1431 F = 0.1874 ACC = 0.3059
Round: 100 Train Loss: -1.856
Global NMI = 0.2922 ARI = 0.1523 F = 0.1957 ACC = 0.3074
Round: 101 Train Loss: -1.858
Global NMI = 0.2927 ARI = 0.1474 F = 0.1912 ACC = 0.3099
Round: 102 Train Loss: -1.860
Global NMI = 0.2927 ARI = 0.1474 F = 0.1913 ACC = 0.3124
Round: 103 Train Loss: -1.859
Global NMI = 0.2949 ARI = 0.1544 F = 0.1975 ACC = 0.3248
Round: 104 Train Loss: -1.856
Global NMI = 0.2968 ARI = 0.1522 F = 0.1957 ACC = 0.3090
Round: 105 Train Loss: -1.853
Global NMI = 0.2954 ARI = 0.1548 F = 0.1980 ACC = 0.3129
Round: 106 Train Loss: -1.852
Global NMI = 0.2877 ARI = 0.1433 F = 0.1880 ACC = 0.3096
Round: 107 Train Loss: -1.855
Global NMI = 0.2923 ARI = 0.1472 F = 0.1913 ACC = 0.3135
Round: 108 Train Loss: -1.855
Global NMI = 0.2891 ARI = 0.1503 F = 0.1940 ACC = 0.3060
Round: 109 Train Loss: -1.855
Global NMI = 0.2933 ARI = 0.1479 F = 0.1916 ACC = 0.3070
Round: 110 Train Loss: -1.857
Global NMI = 0.3039 ARI = 0.1603 F = 0.2033 ACC = 0.3262
Round: 111 Train Loss: -1.856
Global NMI = 0.3041 ARI = 0.1615 F = 0.2040 ACC = 0.3280
Round: 112 Train Loss: -1.860
Global NMI = 0.2967 ARI = 0.1540 F = 0.1970 ACC = 0.3168
Round: 113 Train Loss: -1.862
Global NMI = 0.2926 ARI = 0.1443 F = 0.1883 ACC = 0.3030
Round: 114 Train Loss: -1.865
Global NMI = 0.2968 ARI = 0.1502 F = 0.1938 ACC = 0.3085
Round: 115 Train Loss: -1.865
Global NMI = 0.3039 ARI = 0.1585 F = 0.2024 ACC = 0.3177
Round: 116 Train Loss: -1.865
Global NMI = 0.2903 ARI = 0.1421 F = 0.1864 ACC = 0.3009
Round: 117 Train Loss: -1.864
Global NMI = 0.3062 ARI = 0.1605 F = 0.2039 ACC = 0.3257
Round: 118 Train Loss: -1.864
Global NMI = 0.3095 ARI = 0.1631 F = 0.2062 ACC = 0.3337
Round: 119 Train Loss: -1.864
Global NMI = 0.3033 ARI = 0.1548 F = 0.1989 ACC = 0.3280
Round: 120 Train Loss: -1.866
Global NMI = 0.3153 ARI = 0.1725 F = 0.2151 ACC = 0.3377
Round: 121 Train Loss: -1.866
Global NMI = 0.3136 ARI = 0.1697 F = 0.2127 ACC = 0.3382
Round: 122 Train Loss: -1.863
Global NMI = 0.3107 ARI = 0.1659 F = 0.2086 ACC = 0.3329
Round: 123 Train Loss: -1.864
Global NMI = 0.3149 ARI = 0.1625 F = 0.2061 ACC = 0.3286
Round: 124 Train Loss: -1.866
Global NMI = 0.3113 ARI = 0.1640 F = 0.2071 ACC = 0.3342
Round: 125 Train Loss: -1.864
Global NMI = 0.3085 ARI = 0.1659 F = 0.2088 ACC = 0.3335
Round: 126 Train Loss: -1.865
Global NMI = 0.3142 ARI = 0.1704 F = 0.2132 ACC = 0.3247
Round: 127 Train Loss: -1.865
Global NMI = 0.3269 ARI = 0.1810 F = 0.2232 ACC = 0.3466
Round: 128 Train Loss: -1.863
Global NMI = 0.3127 ARI = 0.1689 F = 0.2116 ACC = 0.3334
Round: 129 Train Loss: -1.865
Global NMI = 0.3147 ARI = 0.1694 F = 0.2124 ACC = 0.3412
Round: 130 Train Loss: -1.863
Global NMI = 0.3004 ARI = 0.1535 F = 0.1970 ACC = 0.3201
Round: 131 Train Loss: -1.864
Global NMI = 0.3065 ARI = 0.1605 F = 0.2041 ACC = 0.3302
Round: 132 Train Loss: -1.864
Global NMI = 0.3153 ARI = 0.1691 F = 0.2115 ACC = 0.3311
Round: 133 Train Loss: -1.864
Global NMI = 0.3161 ARI = 0.1648 F = 0.2081 ACC = 0.3311
Round: 134 Train Loss: -1.863
Global NMI = 0.3151 ARI = 0.1685 F = 0.2114 ACC = 0.3435
Round: 135 Train Loss: -1.865
Global NMI = 0.3179 ARI = 0.1705 F = 0.2130 ACC = 0.3412
Round: 136 Train Loss: -1.866
Global NMI = 0.3205 ARI = 0.1697 F = 0.2124 ACC = 0.3458
Round: 137 Train Loss: -1.868
Global NMI = 0.3242 ARI = 0.1748 F = 0.2173 ACC = 0.3417
Round: 138 Train Loss: -1.869
Global NMI = 0.3225 ARI = 0.1714 F = 0.2150 ACC = 0.3405
Round: 139 Train Loss: -1.869
Global NMI = 0.3242 ARI = 0.1781 F = 0.2201 ACC = 0.3559
Round: 140 Train Loss: -1.868
Global NMI = 0.3122 ARI = 0.1644 F = 0.2079 ACC = 0.3364
Round: 141 Train Loss: -1.870
Global NMI = 0.3186 ARI = 0.1691 F = 0.2120 ACC = 0.3397
Round: 142 Train Loss: -1.870
Global NMI = 0.3161 ARI = 0.1700 F = 0.2124 ACC = 0.3455
Round: 143 Train Loss: -1.871
Global NMI = 0.3170 ARI = 0.1659 F = 0.2096 ACC = 0.3388
Round: 144 Train Loss: -1.869
Global NMI = 0.3250 ARI = 0.1777 F = 0.2205 ACC = 0.3472