Model save path: ./New_Models/bn_False_dataset_CIFAR10_epochs_100_lr_0.001_model_type_vgg11_rand_seed_265358_weight_decay_0.02.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: 0.025607619434595108
Inter Cos: 0.10249260812997818
Norm Quadratic Average: 18.896446228027344
Nearest Class Center Accuracy: 0.308625

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03454197198152542
Inter Cos: 0.11685165017843246
Norm Quadratic Average: 10.622695922851562
Nearest Class Center Accuracy: 0.35525

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.048637788742780685
Inter Cos: 0.1490151286125183
Norm Quadratic Average: 9.749479293823242
Nearest Class Center Accuracy: 0.40925

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.08845450729131699
Inter Cos: 0.2171105593442917
Norm Quadratic Average: 6.09929084777832
Nearest Class Center Accuracy: 0.4375

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.15009744465351105
Inter Cos: 0.3062306344509125
Norm Quadratic Average: 5.2442626953125
Nearest Class Center Accuracy: 0.453625

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.17930875718593597
Inter Cos: 0.3887122571468353
Norm Quadratic Average: 3.455437183380127
Nearest Class Center Accuracy: 0.476875

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.21840709447860718
Inter Cos: 0.44975578784942627
Norm Quadratic Average: 2.525066614151001
Nearest Class Center Accuracy: 0.50975

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 38.82085418701172
Linear Weight Rank: 4031
Intra Cos: 0.2825981080532074
Inter Cos: 0.47591254115104675
Norm Quadratic Average: 12.137608528137207
Nearest Class Center Accuracy: 0.537125

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 15.776054382324219
Linear Weight Rank: 3671
Intra Cos: 0.33071690797805786
Inter Cos: 0.5287485718727112
Norm Quadratic Average: 9.174184799194336
Nearest Class Center Accuracy: 0.5425

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 2.002124071121216
Linear Weight Rank: 10
Intra Cos: 0.36954158544540405
Inter Cos: 0.5900716185569763
Norm Quadratic Average: 7.6401543617248535
Nearest Class Center Accuracy: 0.539

Output Layer:
Intra Cos: 0.427739679813385
Inter Cos: 0.676199197769165
Norm Quadratic Average: 7.062668323516846
Nearest Class Center Accuracy: 0.52075

Test Set:
Average Loss: 1.2691098747253418
Accuracy: 0.5365
NC1 Within Class Collapse: nan
NC2 Equinorm: Features: 0.2339932918548584, Weights: 0.11470301449298859
NC2 Equiangle: Features: 0.599527570936415, Weights: 0.23044378492567275
NC3 Self-Duality: 0.34504684805870056
NC4 NCC Mismatch: 0.17600000000000005

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: 0.02460385300219059
Inter Cos: 0.09682783484458923
Norm Quadratic Average: 18.832632064819336
Nearest Class Center Accuracy: 0.3295

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03594828397035599
Inter Cos: 0.10746923834085464
Norm Quadratic Average: 10.578789710998535
Nearest Class Center Accuracy: 0.3715

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.051079049706459045
Inter Cos: 0.13108624517917633
Norm Quadratic Average: 9.707712173461914
Nearest Class Center Accuracy: 0.413

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.08516107499599457
Inter Cos: 0.19261853396892548
Norm Quadratic Average: 6.070981502532959
Nearest Class Center Accuracy: 0.442

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.12964491546154022
Inter Cos: 0.27096304297447205
Norm Quadratic Average: 5.234090805053711
Nearest Class Center Accuracy: 0.4555

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.14539070427417755
Inter Cos: 0.3408913314342499
Norm Quadratic Average: 3.448782444000244
Nearest Class Center Accuracy: 0.4645

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.18035949766635895
Inter Cos: 0.39192983508110046
Norm Quadratic Average: 2.519256830215454
Nearest Class Center Accuracy: 0.4845

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 38.82085418701172
Linear Weight Rank: 4031
Intra Cos: 0.24695423245429993
Inter Cos: 0.47165748476982117
Norm Quadratic Average: 12.127306938171387
Nearest Class Center Accuracy: 0.5135

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 15.776054382324219
Linear Weight Rank: 3671
Intra Cos: 0.30407410860061646
Inter Cos: 0.5462430119514465
Norm Quadratic Average: 9.187027931213379
Nearest Class Center Accuracy: 0.5245

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 2.002124071121216
Linear Weight Rank: 10
Intra Cos: 0.3479882478713989
Inter Cos: 0.6057608723640442
Norm Quadratic Average: 7.664759635925293
Nearest Class Center Accuracy: 0.5165

Output Layer:
Intra Cos: 0.4155539870262146
Inter Cos: 0.6908006072044373
Norm Quadratic Average: 7.105276584625244
Nearest Class Center Accuracy: 0.492

