Model save path: ./New_Models/bn_False_dataset_CIFAR10_epochs_100_lr_0.001_model_type_vgg11_rand_seed_265358_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: 0.021450400352478027
Inter Cos: 0.11371058970689774
Norm Quadratic Average: 27.691621780395508
Nearest Class Center Accuracy: 0.279125

Layer 1: Conv2d(64, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.02506515011191368
Inter Cos: 0.10364997386932373
Norm Quadratic Average: 29.12415885925293
Nearest Class Center Accuracy: 0.30525

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03474440798163414
Inter Cos: 0.11703310906887054
Norm Quadratic Average: 21.747737884521484
Nearest Class Center Accuracy: 0.359625

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.04155222699046135
Inter Cos: 0.1217276081442833
Norm Quadratic Average: 22.27456283569336
Nearest Class Center Accuracy: 0.415375

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.056448083370923996
Inter Cos: 0.14776702225208282
Norm Quadratic Average: 12.329229354858398
Nearest Class Center Accuracy: 0.444125

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.07670532166957855
Inter Cos: 0.17234155535697937
Norm Quadratic Average: 8.97624683380127
Nearest Class Center Accuracy: 0.477125

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.1067359670996666
Inter Cos: 0.19602535665035248
Norm Quadratic Average: 4.199650764465332
Nearest Class Center Accuracy: 0.531375

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.17608632147312164
Inter Cos: 0.21252237260341644
Norm Quadratic Average: 2.5972824096679688
Nearest Class Center Accuracy: 0.723875

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 62.78165817260742
Linear Weight Rank: 4031
Intra Cos: 0.4486517608165741
Inter Cos: 0.44869086146354675
Norm Quadratic Average: 12.798531532287598
Nearest Class Center Accuracy: 0.9285

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 25.481481552124023
Linear Weight Rank: 3671
Intra Cos: 0.6281450986862183
Inter Cos: 0.6164451241493225
Norm Quadratic Average: 13.517522811889648
Nearest Class Center Accuracy: 0.98425

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 2.9249629974365234
Linear Weight Rank: 10
Intra Cos: 0.6937853097915649
Inter Cos: 0.7147985100746155
Norm Quadratic Average: 16.446420669555664
Nearest Class Center Accuracy: 0.989875

Output Layer:
Intra Cos: 0.7623843550682068
Inter Cos: 0.8507217168807983
Norm Quadratic Average: 21.78844451904297
Nearest Class Center Accuracy: 0.9655

Test Set:
Average Loss: 1.8933373565673828
Accuracy: 0.576
NC1 Within Class Collapse: nan
NC2 Equinorm: Features: 0.26151397824287415, Weights: 0.0720786601305008
NC2 Equiangle: Features: 0.4591974894205729, Weights: 0.23262068430582683
NC3 Self-Duality: 0.3326795995235443
NC4 NCC Mismatch: 0.20199999999999996

Layer 0: Conv2d(3, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.018480459228157997
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: 0.02409781515598297
Inter Cos: 0.09726960211992264
Norm Quadratic Average: 29.018917083740234
Nearest Class Center Accuracy: 0.3265

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.036416418850421906
Inter Cos: 0.11220385879278183
Norm Quadratic Average: 21.668346405029297
Nearest Class Center Accuracy: 0.38

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.04217600077390671
Inter Cos: 0.10992275923490524
Norm Quadratic Average: 22.21767234802246
Nearest Class Center Accuracy: 0.4285

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.055428821593523026
Inter Cos: 0.13149848580360413
Norm Quadratic Average: 12.283366203308105
Nearest Class Center Accuracy: 0.4535

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.07322432845830917
Inter Cos: 0.15159571170806885
Norm Quadratic Average: 8.949990272521973
Nearest Class Center Accuracy: 0.48

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.09046392887830734
Inter Cos: 0.1688801646232605
Norm Quadratic Average: 4.182823657989502
Nearest Class Center Accuracy: 0.4885

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.11517690122127533
Inter Cos: 0.18223990499973297
Norm Quadratic Average: 2.566354274749756
Nearest Class Center Accuracy: 0.53

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 62.78165817260742
Linear Weight Rank: 4031
Intra Cos: 0.21244613826274872
Inter Cos: 0.33743229508399963
Norm Quadratic Average: 12.271663665771484
Nearest Class Center Accuracy: 0.577

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 25.481481552124023
Linear Weight Rank: 3671
Intra Cos: 0.2594917118549347
Inter Cos: 0.45784637331962585
Norm Quadratic Average: 12.724568367004395
Nearest Class Center Accuracy: 0.5825

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 2.9249629974365234
Linear Weight Rank: 10
Intra Cos: 0.26646706461906433
Inter Cos: 0.537712812423706
Norm Quadratic Average: 15.405149459838867
Nearest Class Center Accuracy: 0.569

Output Layer:
Intra Cos: 0.28184887766838074
Inter Cos: 0.6563772559165955
Norm Quadratic Average: 20.222490310668945
Nearest Class Center Accuracy: 0.523

