Model save path: ./New_Models/bn_True_dataset_CIFAR10_epochs_100_lr_0.001_model_type_vgg11_rand_seed_979323_weight_decay_0.03.pth.tar
Training Set:
Layer 0: Conv2d(3, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.021450400352478027
Inter Cos: 0.11371058970689774
Norm Quadratic Average: 27.691617965698242
Nearest Class Center Accuracy: 0.279125

Layer 1: Conv2d(64, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.023019911721348763
Inter Cos: 0.10005680471658707
Norm Quadratic Average: 20.96553611755371
Nearest Class Center Accuracy: 0.351375

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.02616232819855213
Inter Cos: 0.09679165482521057
Norm Quadratic Average: 15.474590301513672
Nearest Class Center Accuracy: 0.377875

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.022625673562288284
Inter Cos: 0.06829572468996048
Norm Quadratic Average: 16.338035583496094
Nearest Class Center Accuracy: 0.415

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03164782002568245
Inter Cos: 0.0817936360836029
Norm Quadratic Average: 10.18829345703125
Nearest Class Center Accuracy: 0.460625

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.037000615149736404
Inter Cos: 0.07972633093595505
Norm Quadratic Average: 10.401949882507324
Nearest Class Center Accuracy: 0.557875

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.08591461926698685
Inter Cos: 0.1075286790728569
Norm Quadratic Average: 6.1366167068481445
Nearest Class Center Accuracy: 0.887125

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.371997207403183
Inter Cos: 0.17459949851036072
Norm Quadratic Average: 3.9896771907806396
Nearest Class Center Accuracy: 1.0

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 23.9993839263916
Linear Weight Rank: 4031
Intra Cos: 0.879181981086731
Inter Cos: 0.3129722476005554
Norm Quadratic Average: 45.61843490600586
Nearest Class Center Accuracy: 1.0

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 9.797235488891602
Linear Weight Rank: 3669
Intra Cos: 0.9773370027542114
Inter Cos: 0.31275102496147156
Norm Quadratic Average: 25.07806968688965
Nearest Class Center Accuracy: 1.0

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 1.6056073904037476
Linear Weight Rank: 10
Intra Cos: 0.9835183024406433
Inter Cos: 0.32786527276039124
Norm Quadratic Average: 15.977755546569824
Nearest Class Center Accuracy: 1.0

Output Layer:
Intra Cos: 0.9806642532348633
Inter Cos: 0.3914150893688202
Norm Quadratic Average: 11.017876625061035
Nearest Class Center Accuracy: 1.0

Test Set:
Average Loss: 1.3377757873535157
Accuracy: 0.5885
NC1 Within Class Collapse: nan
NC2 Equinorm: Features: 0.21145449578762054, Weights: 0.026371750980615616
NC2 Equiangle: Features: 0.3601596408420139, Weights: 0.2042462666829427
NC3 Self-Duality: 0.2569498121738434
NC4 NCC Mismatch: 0.09350000000000003

Layer 0: Conv2d(3, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.018480457365512848
Inter Cos: 0.09352368116378784
Norm Quadratic Average: 27.530664443969727
Nearest Class Center Accuracy: 0.2895

Layer 1: Conv2d(64, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.022457370534539223
Inter Cos: 0.08798107504844666
Norm Quadratic Average: 20.86519432067871
Nearest Class Center Accuracy: 0.37

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.026009032502770424
Inter Cos: 0.08540236204862595
Norm Quadratic Average: 15.396374702453613
Nearest Class Center Accuracy: 0.398

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.021632080897688866
Inter Cos: 0.06042436882853508
Norm Quadratic Average: 16.289310455322266
Nearest Class Center Accuracy: 0.4555

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.027719968929886818
Inter Cos: 0.07349832355976105
Norm Quadratic Average: 10.161370277404785
Nearest Class Center Accuracy: 0.4745

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.029750583693385124
Inter Cos: 0.07045494765043259
Norm Quadratic Average: 10.383697509765625
Nearest Class Center Accuracy: 0.525

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.04381825774908066
Inter Cos: 0.09108255058526993
Norm Quadratic Average: 6.1012678146362305
Nearest Class Center Accuracy: 0.58

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.09721052646636963
Inter Cos: 0.17437033355236053
Norm Quadratic Average: 3.7249186038970947
Nearest Class Center Accuracy: 0.6225

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 23.9993839263916
Linear Weight Rank: 4031
Intra Cos: 0.23967482149600983
Inter Cos: 0.3165209889411926
Norm Quadratic Average: 36.42348861694336
Nearest Class Center Accuracy: 0.596

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 9.797235488891602
Linear Weight Rank: 3669
Intra Cos: 0.27348244190216064
Inter Cos: 0.36372488737106323
Norm Quadratic Average: 19.315933227539062
Nearest Class Center Accuracy: 0.588

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 1.6056073904037476
Linear Weight Rank: 10
Intra Cos: 0.2571045458316803
Inter Cos: 0.36792802810668945
Norm Quadratic Average: 12.410022735595703
Nearest Class Center Accuracy: 0.578

Output Layer:
Intra Cos: 0.23387956619262695
Inter Cos: 0.38001549243927
Norm Quadratic Average: 8.486599922180176
Nearest Class Center Accuracy: 0.57

