Model save path: ./New_Models/bn_True_dataset_CIFAR10_epochs_100_lr_0.001_model_type_vgg11_rand_seed_314159_weight_decay_0.001.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: 0.022515753284096718
Inter Cos: 0.09829312562942505
Norm Quadratic Average: 83.67249298095703
Nearest Class Center Accuracy: 0.327

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.025121308863162994
Inter Cos: 0.08438087999820709
Norm Quadratic Average: 62.55525588989258
Nearest Class Center Accuracy: 0.36

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.023799726739525795
Inter Cos: 0.06896105408668518
Norm Quadratic Average: 65.76998138427734
Nearest Class Center Accuracy: 0.3945

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.029613418504595757
Inter Cos: 0.07699120789766312
Norm Quadratic Average: 41.67837905883789
Nearest Class Center Accuracy: 0.420625

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.029753603041172028
Inter Cos: 0.06689170002937317
Norm Quadratic Average: 42.6125602722168
Nearest Class Center Accuracy: 0.463875

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.04235398769378662
Inter Cos: 0.0708698257803917
Norm Quadratic Average: 27.200843811035156
Nearest Class Center Accuracy: 0.551375

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.06291955709457397
Inter Cos: 0.07424609363079071
Norm Quadratic Average: 19.52730369567871
Nearest Class Center Accuracy: 0.8275

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 96.63602447509766
Linear Weight Rank: 4031
Intra Cos: 0.1895524263381958
Inter Cos: 0.10220730304718018
Norm Quadratic Average: 104.06268310546875
Nearest Class Center Accuracy: 1.0

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 39.063785552978516
Linear Weight Rank: 3670
Intra Cos: 0.44180864095687866
Inter Cos: 0.18306295573711395
Norm Quadratic Average: 53.81547546386719
Nearest Class Center Accuracy: 1.0

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 2.449099540710449
Linear Weight Rank: 10
Intra Cos: 0.668610692024231
Inter Cos: 0.292038232088089
Norm Quadratic Average: 37.17653274536133
Nearest Class Center Accuracy: 1.0

Output Layer:
Intra Cos: 0.8715760707855225
Inter Cos: 0.504971981048584
Norm Quadratic Average: 25.405433654785156
Nearest Class Center Accuracy: 1.0

Test Set:
Average Loss: 2.567358818054199
Accuracy: 0.5785
NC1 Within Class Collapse: nan
NC2 Equinorm: Features: 0.20206888020038605, Weights: 0.01891942508518696
NC2 Equiangle: Features: 0.4342480129665799, Weights: 0.08884218004014757
NC3 Self-Duality: 0.6269115805625916
NC4 NCC Mismatch: 0.14449999999999996

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: 0.021827351301908493
Inter Cos: 0.08563046157360077
Norm Quadratic Average: 83.40480041503906
Nearest Class Center Accuracy: 0.35

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.02533419243991375
Inter Cos: 0.07858601212501526
Norm Quadratic Average: 62.333229064941406
Nearest Class Center Accuracy: 0.3835

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.02477264404296875
Inter Cos: 0.06168360635638237
Norm Quadratic Average: 65.63712310791016
Nearest Class Center Accuracy: 0.417

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.02734757401049137
Inter Cos: 0.06801207363605499
Norm Quadratic Average: 41.56010818481445
Nearest Class Center Accuracy: 0.452

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.026432553306221962
Inter Cos: 0.05782400444149971
Norm Quadratic Average: 42.4909782409668
Nearest Class Center Accuracy: 0.471

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.030221344903111458
Inter Cos: 0.06565243005752563
Norm Quadratic Average: 27.06399917602539
Nearest Class Center Accuracy: 0.492

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03330641984939575
Inter Cos: 0.06868894398212433
Norm Quadratic Average: 19.358251571655273
Nearest Class Center Accuracy: 0.5545

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 96.63602447509766
Linear Weight Rank: 4031
Intra Cos: 0.05736556649208069
Inter Cos: 0.10730309784412384
Norm Quadratic Average: 100.44598388671875
Nearest Class Center Accuracy: 0.6045

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 39.063785552978516
Linear Weight Rank: 3670
Intra Cos: 0.11952001601457596
Inter Cos: 0.2116771638393402
Norm Quadratic Average: 49.830413818359375
Nearest Class Center Accuracy: 0.586

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 2.449099540710449
Linear Weight Rank: 10
Intra Cos: 0.18693110346794128
Inter Cos: 0.3316749930381775
Norm Quadratic Average: 33.21269989013672
Nearest Class Center Accuracy: 0.5735

Output Layer:
Intra Cos: 0.2737985849380493
Inter Cos: 0.5070858001708984
Norm Quadratic Average: 22.091064453125
Nearest Class Center Accuracy: 0.559

