Model save path: ./New_Models/bn_True_dataset_CIFAR10_epochs_100_lr_0.001_model_type_vgg11_rand_seed_979323_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: 0.021450400352478027
Inter Cos: 0.11371058970689774
Norm Quadratic Average: 27.691617965698242
Nearest Class Center Accuracy: 0.279125

Layer 1: Conv2d(64, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.0232891533523798
Inter Cos: 0.10069918632507324
Norm Quadratic Average: 88.43093872070312
Nearest Class Center Accuracy: 0.35175

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.02659151516854763
Inter Cos: 0.09513799846172333
Norm Quadratic Average: 66.05416870117188
Nearest Class Center Accuracy: 0.378375

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.02263811230659485
Inter Cos: 0.07080235332250595
Norm Quadratic Average: 69.80581665039062
Nearest Class Center Accuracy: 0.4085

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.030657000839710236
Inter Cos: 0.08201895654201508
Norm Quadratic Average: 44.15180206298828
Nearest Class Center Accuracy: 0.4325

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03046787902712822
Inter Cos: 0.07236432284116745
Norm Quadratic Average: 44.88063430786133
Nearest Class Center Accuracy: 0.47425

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.04125944897532463
Inter Cos: 0.07705943286418915
Norm Quadratic Average: 28.626220703125
Nearest Class Center Accuracy: 0.56475

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.06158367544412613
Inter Cos: 0.0748685747385025
Norm Quadratic Average: 20.488502502441406
Nearest Class Center Accuracy: 0.8385

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 100.89766693115234
Linear Weight Rank: 4031
Intra Cos: 0.17600393295288086
Inter Cos: 0.09922877699136734
Norm Quadratic Average: 110.52507781982422
Nearest Class Center Accuracy: 1.0

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 40.78962326049805
Linear Weight Rank: 3670
Intra Cos: 0.4047349989414215
Inter Cos: 0.17302584648132324
Norm Quadratic Average: 57.762672424316406
Nearest Class Center Accuracy: 1.0

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 2.5362350940704346
Linear Weight Rank: 10
Intra Cos: 0.6456462740898132
Inter Cos: 0.2621789872646332
Norm Quadratic Average: 40.44533920288086
Nearest Class Center Accuracy: 1.0

Output Layer:
Intra Cos: 0.8723046183586121
Inter Cos: 0.4532095789909363
Norm Quadratic Average: 28.2385311126709
Nearest Class Center Accuracy: 1.0

Test Set:
Average Loss: 2.7707844848632814
Accuracy: 0.578
NC1 Within Class Collapse: nan
NC2 Equinorm: Features: 0.209971085190773, Weights: 0.018525298684835434
NC2 Equiangle: Features: 0.43405270046657984, Weights: 0.09020732243855795
NC3 Self-Duality: 0.6349238157272339
NC4 NCC Mismatch: 0.132

Layer 0: Conv2d(3, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.018480457365512848
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: 0.02295003831386566
Inter Cos: 0.08879739046096802
Norm Quadratic Average: 88.04218292236328
Nearest Class Center Accuracy: 0.3725

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.02614431269466877
Inter Cos: 0.08411761373281479
Norm Quadratic Average: 65.72947692871094
Nearest Class Center Accuracy: 0.404

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.021600743755698204
Inter Cos: 0.06290051341056824
Norm Quadratic Average: 69.53899383544922
Nearest Class Center Accuracy: 0.439

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.02670408971607685
Inter Cos: 0.07315533608198166
Norm Quadratic Average: 43.94874954223633
Nearest Class Center Accuracy: 0.453

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.02585851401090622
Inter Cos: 0.06411340832710266
Norm Quadratic Average: 44.695552825927734
Nearest Class Center Accuracy: 0.4845

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03021666221320629
Inter Cos: 0.06723862886428833
Norm Quadratic Average: 28.44155502319336
Nearest Class Center Accuracy: 0.5065

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.034038007259368896
Inter Cos: 0.07259546220302582
Norm Quadratic Average: 20.29081153869629
Nearest Class Center Accuracy: 0.577

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 100.89766693115234
Linear Weight Rank: 4031
Intra Cos: 0.05980618670582771
Inter Cos: 0.1090632975101471
Norm Quadratic Average: 106.4825668334961
Nearest Class Center Accuracy: 0.61

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 40.78962326049805
Linear Weight Rank: 3670
Intra Cos: 0.12092592567205429
Inter Cos: 0.20037460327148438
Norm Quadratic Average: 53.264617919921875
Nearest Class Center Accuracy: 0.5845

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 2.5362350940704346
Linear Weight Rank: 10
Intra Cos: 0.1939951777458191
Inter Cos: 0.3139379918575287
Norm Quadratic Average: 35.857337951660156
Nearest Class Center Accuracy: 0.5755

Output Layer:
Intra Cos: 0.2908785343170166
Inter Cos: 0.494176983833313
Norm Quadratic Average: 24.2634334564209
Nearest Class Center Accuracy: 0.5625

