Model save path: ./New_Models/bn_False_dataset_CIFAR10_epochs_200_lr_0.01_model_type_vgg11_rand_seed_979323_test_samples_None_train_samples_None_weight_decay_0.0001.pth.tar
Training Set:
Layer 0: Conv2d(3, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.0198909230530262
Inter Cos: 0.10477276891469955
Norm Quadratic Average: 27.59718894958496
Nearest Class Center Accuracy: 0.26968

Layer 1: Conv2d(64, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.021200943738222122
Inter Cos: 0.07790826261043549
Norm Quadratic Average: 30.985469818115234
Nearest Class Center Accuracy: 0.39384

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.02384592965245247
Inter Cos: 0.06376764178276062
Norm Quadratic Average: 28.7390193939209
Nearest Class Center Accuracy: 0.51088

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.022483844310045242
Inter Cos: 0.05279284715652466
Norm Quadratic Average: 33.897884368896484
Nearest Class Center Accuracy: 0.5931

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.02921210788190365
Inter Cos: 0.04420533776283264
Norm Quadratic Average: 18.081148147583008
Nearest Class Center Accuracy: 0.69844

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.042642105370759964
Inter Cos: 0.04736845940351486
Norm Quadratic Average: 12.752473831176758
Nearest Class Center Accuracy: 0.76666

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.1307312250137329
Inter Cos: 0.09885682910680771
Norm Quadratic Average: 5.5077433586120605
Nearest Class Center Accuracy: 0.88246

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.411908358335495
Inter Cos: 0.15844817459583282
Norm Quadratic Average: 3.854053020477295
Nearest Class Center Accuracy: 0.98256

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 73.45758819580078
Linear Weight Rank: 4031
Intra Cos: 0.8292825818061829
Inter Cos: 0.13488784432411194
Norm Quadratic Average: 22.727285385131836
Nearest Class Center Accuracy: 0.99394

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 29.97269058227539
Linear Weight Rank: 3670
Intra Cos: 0.8993626236915588
Inter Cos: 0.08388502150774002
Norm Quadratic Average: 20.544944763183594
Nearest Class Center Accuracy: 0.99866

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 4.015410423278809
Linear Weight Rank: 10
Intra Cos: 0.906898021697998
Inter Cos: 0.06431785970926285
Norm Quadratic Average: 19.848514556884766
Nearest Class Center Accuracy: 1.0

Output Layer:
Intra Cos: 0.9614768028259277
Inter Cos: 0.3800756335258484
Norm Quadratic Average: 22.871122360229492
Nearest Class Center Accuracy: 1.0

Test Set:
Average Loss: 1.174857373714447
Accuracy: 0.8145
NC1 Within Class Collapse: 6.051151752471924
NC2 Equinorm: Features: 0.2409358024597168, Weights: 0.014094006270170212
NC2 Equiangle: Features: 0.14316495259602866, Weights: 0.12411138746473524
NC3 Self-Duality: 0.3887346088886261
NC4 NCC Mismatch: 0.07779999999999998

Layer 0: Conv2d(3, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.018526077270507812
Inter Cos: 0.1042705774307251
Norm Quadratic Average: 27.550140380859375
Nearest Class Center Accuracy: 0.284

Layer 1: Conv2d(64, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.019915064796805382
Inter Cos: 0.07868435233831406
Norm Quadratic Average: 30.963491439819336
Nearest Class Center Accuracy: 0.4073

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.0224108025431633
Inter Cos: 0.06458531320095062
Norm Quadratic Average: 28.757192611694336
Nearest Class Center Accuracy: 0.5159

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.020750373601913452
Inter Cos: 0.053359828889369965
Norm Quadratic Average: 33.942352294921875
Nearest Class Center Accuracy: 0.5934

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.02550371363759041
Inter Cos: 0.04515920206904411
Norm Quadratic Average: 18.103254318237305
Nearest Class Center Accuracy: 0.669

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03596377745270729
Inter Cos: 0.04867742210626602
Norm Quadratic Average: 12.740827560424805
Nearest Class Center Accuracy: 0.7042

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.09933485835790634
Inter Cos: 0.1026391088962555
Norm Quadratic Average: 5.457775115966797
Nearest Class Center Accuracy: 0.7369

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.24546699225902557
Inter Cos: 0.19329839944839478
Norm Quadratic Average: 3.7362849712371826
Nearest Class Center Accuracy: 0.7825

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 73.45758819580078
Linear Weight Rank: 4031
Intra Cos: 0.4609302282333374
Inter Cos: 0.2925071716308594
Norm Quadratic Average: 21.30652618408203
Nearest Class Center Accuracy: 0.7852

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 29.97269058227539
Linear Weight Rank: 3670
Intra Cos: 0.4845227301120758
Inter Cos: 0.2600308358669281
Norm Quadratic Average: 19.089542388916016
Nearest Class Center Accuracy: 0.7899

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 4.015410423278809
Linear Weight Rank: 10
Intra Cos: 0.48944252729415894
Inter Cos: 0.27060529589653015
Norm Quadratic Average: 18.490196228027344
Nearest Class Center Accuracy: 0.7941

Output Layer:
Intra Cos: 0.558048665523529
Inter Cos: 0.4146696925163269
Norm Quadratic Average: 21.115205764770508
Nearest Class Center Accuracy: 0.8059

