Model save path: ./New_Models/bn_True_dataset_CIFAR10_epochs_100_lr_0.001_model_type_vgg11_rand_seed_265358_weight_decay_0.0005.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: 0.026817627251148224
Inter Cos: 0.1022864505648613
Norm Quadratic Average: 84.96142578125
Nearest Class Center Accuracy: 0.3395

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03129061684012413
Inter Cos: 0.08889652043581009
Norm Quadratic Average: 62.199039459228516
Nearest Class Center Accuracy: 0.376375

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.027490846812725067
Inter Cos: 0.06990236043930054
Norm Quadratic Average: 67.57371520996094
Nearest Class Center Accuracy: 0.408125

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03586273640394211
Inter Cos: 0.07960420846939087
Norm Quadratic Average: 42.98841094970703
Nearest Class Center Accuracy: 0.431375

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03433309867978096
Inter Cos: 0.06464499980211258
Norm Quadratic Average: 43.919944763183594
Nearest Class Center Accuracy: 0.469375

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.04731335863471031
Inter Cos: 0.08078137785196304
Norm Quadratic Average: 28.545991897583008
Nearest Class Center Accuracy: 0.551125

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.060648735612630844
Inter Cos: 0.07962450385093689
Norm Quadratic Average: 20.097869873046875
Nearest Class Center Accuracy: 0.838625

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 98.9881820678711
Linear Weight Rank: 4031
Intra Cos: 0.17381541430950165
Inter Cos: 0.10743092745542526
Norm Quadratic Average: 106.53886413574219
Nearest Class Center Accuracy: 1.0

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 40.021663665771484
Linear Weight Rank: 3671
Intra Cos: 0.4164488613605499
Inter Cos: 0.20196887850761414
Norm Quadratic Average: 55.64906311035156
Nearest Class Center Accuracy: 1.0

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 2.515803098678589
Linear Weight Rank: 10
Intra Cos: 0.6569830179214478
Inter Cos: 0.2874951660633087
Norm Quadratic Average: 38.82098388671875
Nearest Class Center Accuracy: 1.0

Output Layer:
Intra Cos: 0.8792413473129272
Inter Cos: 0.46991124749183655
Norm Quadratic Average: 27.16173553466797
Nearest Class Center Accuracy: 1.0

Test Set:
Average Loss: 2.6676661987304686
Accuracy: 0.588
NC1 Within Class Collapse: nan
NC2 Equinorm: Features: 0.20508916676044464, Weights: 0.01827346906065941
NC2 Equiangle: Features: 0.4513819376627604, Weights: 0.08886694378323025
NC3 Self-Duality: 0.6306951642036438
NC4 NCC Mismatch: 0.13849999999999996

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: 0.024784477427601814
Inter Cos: 0.08993121236562729
Norm Quadratic Average: 84.93408203125
Nearest Class Center Accuracy: 0.3535

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.030001914128661156
Inter Cos: 0.08755114674568176
Norm Quadratic Average: 62.200164794921875
Nearest Class Center Accuracy: 0.394

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.02723522298038006
Inter Cos: 0.06770061701536179
Norm Quadratic Average: 67.62896728515625
Nearest Class Center Accuracy: 0.4305

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03367261216044426
Inter Cos: 0.08032169938087463
Norm Quadratic Average: 42.98688507080078
Nearest Class Center Accuracy: 0.452

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.030983252450823784
Inter Cos: 0.06606079638004303
Norm Quadratic Average: 43.90503692626953
Nearest Class Center Accuracy: 0.477

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03545130044221878
Inter Cos: 0.0784737840294838
Norm Quadratic Average: 28.470563888549805
Nearest Class Center Accuracy: 0.4915

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.033853963017463684
Inter Cos: 0.07298584282398224
Norm Quadratic Average: 19.939029693603516
Nearest Class Center Accuracy: 0.5715

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 98.9881820678711
Linear Weight Rank: 4031
Intra Cos: 0.05555371195077896
Inter Cos: 0.10559569299221039
Norm Quadratic Average: 102.64570617675781
Nearest Class Center Accuracy: 0.6225

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 40.021663665771484
Linear Weight Rank: 3671
Intra Cos: 0.11776704341173172
Inter Cos: 0.19223973155021667
Norm Quadratic Average: 51.26182174682617
Nearest Class Center Accuracy: 0.6065

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 2.515803098678589
Linear Weight Rank: 10
Intra Cos: 0.18630677461624146
Inter Cos: 0.3005102276802063
Norm Quadratic Average: 34.40521240234375
Nearest Class Center Accuracy: 0.5915

Output Layer:
Intra Cos: 0.2776834964752197
Inter Cos: 0.47814127802848816
Norm Quadratic Average: 23.390056610107422
Nearest Class Center Accuracy: 0.5775

