Model save path: ./New_Models/bn_True_dataset_CIFAR10_epochs_100_lr_0.001_model_type_vgg11_rand_seed_846264_weight_decay_0.01.pth.tar
Training Set:
Layer 0: Conv2d(3, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.021450398489832878
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: 0.02354164980351925
Inter Cos: 0.07642778754234314
Norm Quadratic Average: 54.94095230102539
Nearest Class Center Accuracy: 0.34525

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03007642552256584
Inter Cos: 0.08315861970186234
Norm Quadratic Average: 41.05253982543945
Nearest Class Center Accuracy: 0.376375

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.02497245743870735
Inter Cos: 0.06344316899776459
Norm Quadratic Average: 42.92143249511719
Nearest Class Center Accuracy: 0.40925

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03568467125296593
Inter Cos: 0.08057650923728943
Norm Quadratic Average: 27.581619262695312
Nearest Class Center Accuracy: 0.432

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03371455892920494
Inter Cos: 0.06716881692409515
Norm Quadratic Average: 27.943588256835938
Nearest Class Center Accuracy: 0.48125

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.04883318394422531
Inter Cos: 0.07709886878728867
Norm Quadratic Average: 17.68074607849121
Nearest Class Center Accuracy: 0.632125

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.08991539478302002
Inter Cos: 0.08751468360424042
Norm Quadratic Average: 12.295028686523438
Nearest Class Center Accuracy: 0.96575

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 62.746864318847656
Linear Weight Rank: 4031
Intra Cos: 0.31587886810302734
Inter Cos: 0.14086677134037018
Norm Quadratic Average: 74.32701873779297
Nearest Class Center Accuracy: 1.0

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 25.384096145629883
Linear Weight Rank: 3671
Intra Cos: 0.6494104862213135
Inter Cos: 0.241914302110672
Norm Quadratic Average: 35.38522720336914
Nearest Class Center Accuracy: 1.0

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 1.9015302658081055
Linear Weight Rank: 10
Intra Cos: 0.8290950059890747
Inter Cos: 0.3274213373661041
Norm Quadratic Average: 23.006778717041016
Nearest Class Center Accuracy: 1.0

Output Layer:
Intra Cos: 0.9127930402755737
Inter Cos: 0.463814914226532
Norm Quadratic Average: 14.472899436950684
Nearest Class Center Accuracy: 1.0

Test Set:
Average Loss: 1.5400188102722168
Accuracy: 0.608
NC1 Within Class Collapse: nan
NC2 Equinorm: Features: 0.20525754988193512, Weights: 0.015705879777669907
NC2 Equiangle: Features: 0.4098597632514106, Weights: 0.10069833331637912
NC3 Self-Duality: 0.4848044216632843
NC4 NCC Mismatch: 0.14100000000000001

Layer 0: Conv2d(3, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.018480457365512848
Inter Cos: 0.09352367371320724
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: 0.023309413343667984
Inter Cos: 0.07130749523639679
Norm Quadratic Average: 54.806663513183594
Nearest Class Center Accuracy: 0.36

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.029918288812041283
Inter Cos: 0.07876023650169373
Norm Quadratic Average: 40.937522888183594
Nearest Class Center Accuracy: 0.403

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.02464853599667549
Inter Cos: 0.05970832705497742
Norm Quadratic Average: 42.847633361816406
Nearest Class Center Accuracy: 0.439

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03261125832796097
Inter Cos: 0.08065620809793472
Norm Quadratic Average: 27.524972915649414
Nearest Class Center Accuracy: 0.455

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.029479244723916054
Inter Cos: 0.06240246817469597
Norm Quadratic Average: 27.871604919433594
Nearest Class Center Accuracy: 0.4885

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03446312993764877
Inter Cos: 0.07159590721130371
Norm Quadratic Average: 17.609699249267578
Nearest Class Center Accuracy: 0.5315

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.04045029729604721
Inter Cos: 0.07471787929534912
Norm Quadratic Average: 12.140454292297363
Nearest Class Center Accuracy: 0.6105

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 62.746864318847656
Linear Weight Rank: 4031
Intra Cos: 0.09166019409894943
Inter Cos: 0.14658436179161072
Norm Quadratic Average: 69.99336242675781
Nearest Class Center Accuracy: 0.625

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 25.384096145629883
Linear Weight Rank: 3671
Intra Cos: 0.18198180198669434
Inter Cos: 0.2803395092487335
Norm Quadratic Average: 31.33188819885254
Nearest Class Center Accuracy: 0.5965

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 1.9015302658081055
Linear Weight Rank: 10
Intra Cos: 0.23646880686283112
Inter Cos: 0.37331753969192505
Norm Quadratic Average: 19.841516494750977
Nearest Class Center Accuracy: 0.592

Output Layer:
Intra Cos: 0.268449604511261
Inter Cos: 0.45388540625572205
Norm Quadratic Average: 12.36998176574707
Nearest Class Center Accuracy: 0.578

