Model save path: ./New_Models/bn_True_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: 0.026563620194792747
Inter Cos: 0.10193126648664474
Norm Quadratic Average: 53.940914154052734
Nearest Class Center Accuracy: 0.33825

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.031002890318632126
Inter Cos: 0.08861655741930008
Norm Quadratic Average: 39.30060958862305
Nearest Class Center Accuracy: 0.377625

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.026805000379681587
Inter Cos: 0.069583460688591
Norm Quadratic Average: 42.62150955200195
Nearest Class Center Accuracy: 0.409875

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.0343768335878849
Inter Cos: 0.0753219947218895
Norm Quadratic Average: 27.097253799438477
Nearest Class Center Accuracy: 0.441

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03321297839283943
Inter Cos: 0.06463459134101868
Norm Quadratic Average: 27.701372146606445
Nearest Class Center Accuracy: 0.4925

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.049682848155498505
Inter Cos: 0.07901731133460999
Norm Quadratic Average: 17.728647232055664
Nearest Class Center Accuracy: 0.641

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.08869563043117523
Inter Cos: 0.08401192724704742
Norm Quadratic Average: 12.305821418762207
Nearest Class Center Accuracy: 0.965625

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 62.74481201171875
Linear Weight Rank: 4031
Intra Cos: 0.32608675956726074
Inter Cos: 0.14418035745620728
Norm Quadratic Average: 74.2567367553711
Nearest Class Center Accuracy: 1.0

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 25.3866024017334
Linear Weight Rank: 3671
Intra Cos: 0.6790191531181335
Inter Cos: 0.2682459354400635
Norm Quadratic Average: 35.88652801513672
Nearest Class Center Accuracy: 1.0

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 1.911630630493164
Linear Weight Rank: 10
Intra Cos: 0.8446880578994751
Inter Cos: 0.353084534406662
Norm Quadratic Average: 23.53351593017578
Nearest Class Center Accuracy: 1.0

Output Layer:
Intra Cos: 0.9160546064376831
Inter Cos: 0.45928728580474854
Norm Quadratic Average: 15.123969078063965
Nearest Class Center Accuracy: 1.0

Test Set:
Average Loss: 1.5998941650390626
Accuracy: 0.591
NC1 Within Class Collapse: nan
NC2 Equinorm: Features: 0.20015737414360046, Weights: 0.02214866317808628
NC2 Equiangle: Features: 0.44036568535698783, Weights: 0.10728997124565973
NC3 Self-Duality: 0.49828463792800903
NC4 NCC Mismatch: 0.14100000000000001

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: 0.024415049701929092
Inter Cos: 0.08956220000982285
Norm Quadratic Average: 53.91962814331055
Nearest Class Center Accuracy: 0.3555

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.02952074445784092
Inter Cos: 0.08776151388883591
Norm Quadratic Average: 39.30101776123047
Nearest Class Center Accuracy: 0.3975

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.026381755247712135
Inter Cos: 0.06528771668672562
Norm Quadratic Average: 42.655914306640625
Nearest Class Center Accuracy: 0.4335

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.032080959528684616
Inter Cos: 0.07565715909004211
Norm Quadratic Average: 27.10000228881836
Nearest Class Center Accuracy: 0.4575

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.02919420413672924
Inter Cos: 0.06243085861206055
Norm Quadratic Average: 27.668127059936523
Nearest Class Center Accuracy: 0.493

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03484818711876869
Inter Cos: 0.07253538072109222
Norm Quadratic Average: 17.672563552856445
Nearest Class Center Accuracy: 0.515

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03987594321370125
Inter Cos: 0.08035881072282791
Norm Quadratic Average: 12.148239135742188
Nearest Class Center Accuracy: 0.608

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 62.74481201171875
Linear Weight Rank: 4031
Intra Cos: 0.08932050317525864
Inter Cos: 0.15018297731876373
Norm Quadratic Average: 69.51116943359375
Nearest Class Center Accuracy: 0.6055

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 25.3866024017334
Linear Weight Rank: 3671
Intra Cos: 0.1837255358695984
Inter Cos: 0.28305190801620483
Norm Quadratic Average: 31.400310516357422
Nearest Class Center Accuracy: 0.588

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 1.911630630493164
Linear Weight Rank: 10
Intra Cos: 0.23923753201961517
Inter Cos: 0.37305471301078796
Norm Quadratic Average: 20.016216278076172
Nearest Class Center Accuracy: 0.5825

Output Layer:
Intra Cos: 0.2731458246707916
Inter Cos: 0.45100292563438416
Norm Quadratic Average: 12.737017631530762
Nearest Class Center Accuracy: 0.579

