Model save path: ./New_Models/bn_True_dataset_CIFAR10_epochs_100_lr_0.001_model_type_vgg11_rand_seed_338327_weight_decay_0.0003.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: 0.11371058225631714
Norm Quadratic Average: 27.691619873046875
Nearest Class Center Accuracy: 0.279125

Layer 1: Conv2d(64, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.023899726569652557
Inter Cos: 0.10039417445659637
Norm Quadratic Average: 85.15560913085938
Nearest Class Center Accuracy: 0.33475

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.02595895528793335
Inter Cos: 0.09003692865371704
Norm Quadratic Average: 64.03068542480469
Nearest Class Center Accuracy: 0.37275

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.023151589557528496
Inter Cos: 0.07035209983587265
Norm Quadratic Average: 68.39730834960938
Nearest Class Center Accuracy: 0.404

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.031145524233579636
Inter Cos: 0.07658792287111282
Norm Quadratic Average: 43.731895446777344
Nearest Class Center Accuracy: 0.418625

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.030036237090826035
Inter Cos: 0.06490226835012436
Norm Quadratic Average: 44.54019546508789
Nearest Class Center Accuracy: 0.46225

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03962930291891098
Inter Cos: 0.07617563009262085
Norm Quadratic Average: 28.587133407592773
Nearest Class Center Accuracy: 0.55475

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.062106743454933167
Inter Cos: 0.07411016523838043
Norm Quadratic Average: 20.20772361755371
Nearest Class Center Accuracy: 0.834875

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 99.9376220703125
Linear Weight Rank: 4031
Intra Cos: 0.18216478824615479
Inter Cos: 0.10288766771554947
Norm Quadratic Average: 107.2754898071289
Nearest Class Center Accuracy: 1.0

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 40.39133834838867
Linear Weight Rank: 3670
Intra Cos: 0.42194315791130066
Inter Cos: 0.19153699278831482
Norm Quadratic Average: 56.22886276245117
Nearest Class Center Accuracy: 1.0

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 2.5121352672576904
Linear Weight Rank: 10
Intra Cos: 0.6489238142967224
Inter Cos: 0.3051939308643341
Norm Quadratic Average: 39.56465148925781
Nearest Class Center Accuracy: 1.0

Output Layer:
Intra Cos: 0.868713915348053
Inter Cos: 0.5162359476089478
Norm Quadratic Average: 27.40814781188965
Nearest Class Center Accuracy: 1.0

Test Set:
Average Loss: 2.7948969268798827
Accuracy: 0.5805
NC1 Within Class Collapse: nan
NC2 Equinorm: Features: 0.21576069295406342, Weights: 0.012913502752780914
NC2 Equiangle: Features: 0.44681260850694443, Weights: 0.08800654941134983
NC3 Self-Duality: 0.6465402245521545
NC4 NCC Mismatch: 0.16000000000000003

Layer 0: Conv2d(3, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.018480459228157997
Inter Cos: 0.09352367371320724
Norm Quadratic Average: 27.53066635131836
Nearest Class Center Accuracy: 0.2895

Layer 1: Conv2d(64, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.02317359857261181
Inter Cos: 0.08668085932731628
Norm Quadratic Average: 84.66458892822266
Nearest Class Center Accuracy: 0.352

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.02613217756152153
Inter Cos: 0.07855422049760818
Norm Quadratic Average: 63.69026565551758
Nearest Class Center Accuracy: 0.402

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.02341436967253685
Inter Cos: 0.06142350658774376
Norm Quadratic Average: 68.1539077758789
Nearest Class Center Accuracy: 0.439

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.029165467247366905
Inter Cos: 0.06814175844192505
Norm Quadratic Average: 43.555885314941406
Nearest Class Center Accuracy: 0.4525

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.027518967166543007
Inter Cos: 0.0583634227514267
Norm Quadratic Average: 44.396209716796875
Nearest Class Center Accuracy: 0.4785

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.02929745800793171
Inter Cos: 0.07381003350019455
Norm Quadratic Average: 28.456493377685547
Nearest Class Center Accuracy: 0.4935

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.032085321843624115
Inter Cos: 0.0669078603386879
Norm Quadratic Average: 20.04603385925293
Nearest Class Center Accuracy: 0.5575

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 99.9376220703125
Linear Weight Rank: 4031
Intra Cos: 0.053468987345695496
Inter Cos: 0.10213596373796463
Norm Quadratic Average: 103.4488525390625
Nearest Class Center Accuracy: 0.599

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 40.39133834838867
Linear Weight Rank: 3670
Intra Cos: 0.1108635812997818
Inter Cos: 0.1993408352136612
Norm Quadratic Average: 51.9616584777832
Nearest Class Center Accuracy: 0.5825

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 2.5121352672576904
Linear Weight Rank: 10
Intra Cos: 0.1740078181028366
Inter Cos: 0.3176957368850708
Norm Quadratic Average: 35.25249099731445
Nearest Class Center Accuracy: 0.5725

Output Layer:
Intra Cos: 0.25536903738975525
Inter Cos: 0.5008487105369568
Norm Quadratic Average: 23.67525863647461
Nearest Class Center Accuracy: 0.549

