Model save path: ./New_Models/bn_False_dataset_CIFAR10_epochs_100_lr_0.001_model_type_vgg11_rand_seed_979323_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: 27.691617965698242
Nearest Class Center Accuracy: 0.279125

Layer 1: Conv2d(64, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.025495950132608414
Inter Cos: 0.1090274453163147
Norm Quadratic Average: 29.259801864624023
Nearest Class Center Accuracy: 0.3195

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.02789461612701416
Inter Cos: 0.11211623251438141
Norm Quadratic Average: 22.966930389404297
Nearest Class Center Accuracy: 0.384125

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.036153778433799744
Inter Cos: 0.11530569940805435
Norm Quadratic Average: 27.8220272064209
Nearest Class Center Accuracy: 0.423125

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.05607721954584122
Inter Cos: 0.1458692103624344
Norm Quadratic Average: 17.738679885864258
Nearest Class Center Accuracy: 0.448875

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.06972057372331619
Inter Cos: 0.1535997837781906
Norm Quadratic Average: 16.390241622924805
Nearest Class Center Accuracy: 0.481125

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.09329254925251007
Inter Cos: 0.16250735521316528
Norm Quadratic Average: 9.032470703125
Nearest Class Center Accuracy: 0.537

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.12553343176841736
Inter Cos: 0.1739559769630432
Norm Quadratic Average: 6.6930108070373535
Nearest Class Center Accuracy: 0.7175

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 99.0003662109375
Linear Weight Rank: 4031
Intra Cos: 0.32657214999198914
Inter Cos: 0.264800488948822
Norm Quadratic Average: 27.10186004638672
Nearest Class Center Accuracy: 0.97825

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 40.068904876708984
Linear Weight Rank: 3670
Intra Cos: 0.6043460369110107
Inter Cos: 0.41770508885383606
Norm Quadratic Average: 23.90656089782715
Nearest Class Center Accuracy: 0.99925

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 3.2621004581451416
Linear Weight Rank: 10
Intra Cos: 0.748006284236908
Inter Cos: 0.5258074998855591
Norm Quadratic Average: 28.189481735229492
Nearest Class Center Accuracy: 0.999875

Output Layer:
Intra Cos: 0.801761269569397
Inter Cos: 0.6783312559127808
Norm Quadratic Average: 34.61058044433594
Nearest Class Center Accuracy: 0.996875

Test Set:
Average Loss: 3.0064862213134766
Accuracy: 0.607
NC1 Within Class Collapse: nan
NC2 Equinorm: Features: 0.25504809617996216, Weights: 0.046962328255176544
NC2 Equiangle: Features: 0.4186516231960721, Weights: 0.1610375934176975
NC3 Self-Duality: 0.44612762331962585
NC4 NCC Mismatch: 0.134

Layer 0: Conv2d(3, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.018480457365512848
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: 0.025018801912665367
Inter Cos: 0.09302428364753723
Norm Quadratic Average: 29.08133888244629
Nearest Class Center Accuracy: 0.337

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.028780831024050713
Inter Cos: 0.09829819947481155
Norm Quadratic Average: 22.82682228088379
Nearest Class Center Accuracy: 0.401

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03589317575097084
Inter Cos: 0.10204636305570602
Norm Quadratic Average: 27.70984649658203
Nearest Class Center Accuracy: 0.452

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.052166782319545746
Inter Cos: 0.12889470160007477
Norm Quadratic Average: 17.660245895385742
Nearest Class Center Accuracy: 0.4685

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.06240285560488701
Inter Cos: 0.13420730829238892
Norm Quadratic Average: 16.336877822875977
Nearest Class Center Accuracy: 0.48

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.0760660246014595
Inter Cos: 0.13982002437114716
Norm Quadratic Average: 8.989516258239746
Nearest Class Center Accuracy: 0.496

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.08616666495800018
Inter Cos: 0.14684973657131195
Norm Quadratic Average: 6.631961345672607
Nearest Class Center Accuracy: 0.5425

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 99.0003662109375
Linear Weight Rank: 4031
Intra Cos: 0.14109976589679718
Inter Cos: 0.23971420526504517
Norm Quadratic Average: 26.114788055419922
Nearest Class Center Accuracy: 0.61

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 40.068904876708984
Linear Weight Rank: 3670
Intra Cos: 0.21507564187049866
Inter Cos: 0.36353737115859985
Norm Quadratic Average: 22.39453125
Nearest Class Center Accuracy: 0.603

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 3.2621004581451416
Linear Weight Rank: 10
Intra Cos: 0.24896925687789917
Inter Cos: 0.45104286074638367
Norm Quadratic Average: 26.174203872680664
Nearest Class Center Accuracy: 0.595

Output Layer:
Intra Cos: 0.2878850996494293
Inter Cos: 0.5649813413619995
Norm Quadratic Average: 32.018653869628906
Nearest Class Center Accuracy: 0.577

