Model save path: ./New_Models/bn_False_dataset_CIFAR10_epochs_100_lr_0.001_model_type_vgg11_rand_seed_314159_weight_decay_0.0003.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: 0.024980727583169937
Inter Cos: 0.09512826055288315
Norm Quadratic Average: 33.56867980957031
Nearest Class Center Accuracy: 0.302

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.0321035236120224
Inter Cos: 0.10898450016975403
Norm Quadratic Average: 26.55179214477539
Nearest Class Center Accuracy: 0.3565

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03525906056165695
Inter Cos: 0.10042785108089447
Norm Quadratic Average: 30.90268898010254
Nearest Class Center Accuracy: 0.41225

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.05018490552902222
Inter Cos: 0.12606649100780487
Norm Quadratic Average: 19.54121971130371
Nearest Class Center Accuracy: 0.43975

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.06214797496795654
Inter Cos: 0.12895655632019043
Norm Quadratic Average: 18.032337188720703
Nearest Class Center Accuracy: 0.472125

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.0816330686211586
Inter Cos: 0.15140801668167114
Norm Quadratic Average: 9.883553504943848
Nearest Class Center Accuracy: 0.524625

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.11596275866031647
Inter Cos: 0.16678398847579956
Norm Quadratic Average: 7.292051792144775
Nearest Class Center Accuracy: 0.69875

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 99.954833984375
Linear Weight Rank: 4031
Intra Cos: 0.320125937461853
Inter Cos: 0.2780372202396393
Norm Quadratic Average: 29.467458724975586
Nearest Class Center Accuracy: 0.96775

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 40.44986343383789
Linear Weight Rank: 3670
Intra Cos: 0.6043429970741272
Inter Cos: 0.438005656003952
Norm Quadratic Average: 25.643312454223633
Nearest Class Center Accuracy: 0.99875

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 3.2755649089813232
Linear Weight Rank: 10
Intra Cos: 0.738441526889801
Inter Cos: 0.543544590473175
Norm Quadratic Average: 30.050695419311523
Nearest Class Center Accuracy: 0.9995

Output Layer:
Intra Cos: 0.8344860076904297
Inter Cos: 0.7082735300064087
Norm Quadratic Average: 36.983455657958984
Nearest Class Center Accuracy: 0.99925

Test Set:
Average Loss: 3.2504535369873047
Accuracy: 0.5865
NC1 Within Class Collapse: nan
NC2 Equinorm: Features: 0.24839533865451813, Weights: 0.04589752107858658
NC2 Equiangle: Features: 0.4252481248643663, Weights: 0.16189079284667968
NC3 Self-Duality: 0.45503121614456177
NC4 NCC Mismatch: 0.14649999999999996

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: 0.025066755712032318
Inter Cos: 0.08969075977802277
Norm Quadratic Average: 33.40212631225586
Nearest Class Center Accuracy: 0.318

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03424633666872978
Inter Cos: 0.10526334494352341
Norm Quadratic Average: 26.439395904541016
Nearest Class Center Accuracy: 0.3775

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03599545732140541
Inter Cos: 0.09026363492012024
Norm Quadratic Average: 30.778167724609375
Nearest Class Center Accuracy: 0.437

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.04889640212059021
Inter Cos: 0.11423720419406891
Norm Quadratic Average: 19.476619720458984
Nearest Class Center Accuracy: 0.457

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.05875212326645851
Inter Cos: 0.11556204408407211
Norm Quadratic Average: 18.006446838378906
Nearest Class Center Accuracy: 0.4775

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.06825049966573715
Inter Cos: 0.13344217836856842
Norm Quadratic Average: 9.86625862121582
Nearest Class Center Accuracy: 0.491

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.07949548214673996
Inter Cos: 0.14282909035682678
Norm Quadratic Average: 7.2441086769104
Nearest Class Center Accuracy: 0.527

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 99.954833984375
Linear Weight Rank: 4031
Intra Cos: 0.13756996393203735
Inter Cos: 0.23800212144851685
Norm Quadratic Average: 28.39914321899414
Nearest Class Center Accuracy: 0.587

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 40.44986343383789
Linear Weight Rank: 3670
Intra Cos: 0.2223552018404007
Inter Cos: 0.36104458570480347
Norm Quadratic Average: 24.012182235717773
Nearest Class Center Accuracy: 0.579

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 3.2755649089813232
Linear Weight Rank: 10
Intra Cos: 0.25862956047058105
Inter Cos: 0.4447093605995178
Norm Quadratic Average: 27.8966064453125
Nearest Class Center Accuracy: 0.568

Output Layer:
Intra Cos: 0.2878282368183136
Inter Cos: 0.5607706308364868
Norm Quadratic Average: 34.12480545043945
Nearest Class Center Accuracy: 0.5465

