Model save path: ./New_Models/bn_True_dataset_CIFAR10_epochs_100_lr_0.001_model_type_vgg11_rand_seed_265358_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: 0.02666507661342621
Inter Cos: 0.10330871492624283
Norm Quadratic Average: 83.07220458984375
Nearest Class Center Accuracy: 0.338

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03143182024359703
Inter Cos: 0.09237846732139587
Norm Quadratic Average: 60.61371612548828
Nearest Class Center Accuracy: 0.377625

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.02710481360554695
Inter Cos: 0.07353410124778748
Norm Quadratic Average: 65.75459289550781
Nearest Class Center Accuracy: 0.405375

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.0359097383916378
Inter Cos: 0.07787887006998062
Norm Quadratic Average: 41.8486213684082
Nearest Class Center Accuracy: 0.428375

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03383881598711014
Inter Cos: 0.06621867418289185
Norm Quadratic Average: 42.90675735473633
Nearest Class Center Accuracy: 0.46925

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.04789207503199577
Inter Cos: 0.08090225607156754
Norm Quadratic Average: 27.844846725463867
Nearest Class Center Accuracy: 0.555375

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.06371231377124786
Inter Cos: 0.07793857902288437
Norm Quadratic Average: 19.48346519470215
Nearest Class Center Accuracy: 0.849625

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 96.6422119140625
Linear Weight Rank: 4031
Intra Cos: 0.18544727563858032
Inter Cos: 0.10176438093185425
Norm Quadratic Average: 103.99974822998047
Nearest Class Center Accuracy: 1.0

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 39.07320022583008
Linear Weight Rank: 3671
Intra Cos: 0.43970224261283875
Inter Cos: 0.18573704361915588
Norm Quadratic Average: 53.688629150390625
Nearest Class Center Accuracy: 1.0

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 2.456655979156494
Linear Weight Rank: 10
Intra Cos: 0.677627444267273
Inter Cos: 0.27910372614860535
Norm Quadratic Average: 37.09247589111328
Nearest Class Center Accuracy: 1.0

Output Layer:
Intra Cos: 0.8887049555778503
Inter Cos: 0.4683682322502136
Norm Quadratic Average: 25.55512046813965
Nearest Class Center Accuracy: 1.0

Test Set:
Average Loss: 2.5496602325439452
Accuracy: 0.597
NC1 Within Class Collapse: nan
NC2 Equinorm: Features: 0.20614106953144073, Weights: 0.020154964178800583
NC2 Equiangle: Features: 0.44907006157769097, Weights: 0.08935402764214409
NC3 Self-Duality: 0.6307296752929688
NC4 NCC Mismatch: 0.13449999999999995

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: 0.02448350004851818
Inter Cos: 0.09075843542814255
Norm Quadratic Average: 83.04508209228516
Nearest Class Center Accuracy: 0.355

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.030046267434954643
Inter Cos: 0.0867028683423996
Norm Quadratic Average: 60.609920501708984
Nearest Class Center Accuracy: 0.399

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.02673186920583248
Inter Cos: 0.0666125938296318
Norm Quadratic Average: 65.7910385131836
Nearest Class Center Accuracy: 0.425

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03438955545425415
Inter Cos: 0.07840649783611298
Norm Quadratic Average: 41.851524353027344
Nearest Class Center Accuracy: 0.4515

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03113452158868313
Inter Cos: 0.06455933302640915
Norm Quadratic Average: 42.88791275024414
Nearest Class Center Accuracy: 0.48

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.037263136357069016
Inter Cos: 0.07883284986019135
Norm Quadratic Average: 27.78607940673828
Nearest Class Center Accuracy: 0.488

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03730819746851921
Inter Cos: 0.07323644310235977
Norm Quadratic Average: 19.34588050842285
Nearest Class Center Accuracy: 0.5635

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 96.6422119140625
Linear Weight Rank: 4031
Intra Cos: 0.0628342553973198
Inter Cos: 0.10884994268417358
Norm Quadratic Average: 100.09917449951172
Nearest Class Center Accuracy: 0.6165

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 39.07320022583008
Linear Weight Rank: 3671
Intra Cos: 0.1327027529478073
Inter Cos: 0.20516616106033325
Norm Quadratic Average: 49.31220245361328
Nearest Class Center Accuracy: 0.6045

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 2.456655979156494
Linear Weight Rank: 10
Intra Cos: 0.20670142769813538
Inter Cos: 0.3194328546524048
Norm Quadratic Average: 32.75629806518555
Nearest Class Center Accuracy: 0.5935

Output Layer:
Intra Cos: 0.30127426981925964
Inter Cos: 0.4947539269924164
Norm Quadratic Average: 21.916807174682617
Nearest Class Center Accuracy: 0.572

