Model save path: ./New_Models/bn_True_dataset_CIFAR10_epochs_100_lr_0.001_model_type_vgg11_rand_seed_314159_weight_decay_0.0007.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: 0.022688664495944977
Inter Cos: 0.10042852908372879
Norm Quadratic Average: 84.71888732910156
Nearest Class Center Accuracy: 0.32475

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.0248660109937191
Inter Cos: 0.0841558426618576
Norm Quadratic Average: 63.29960250854492
Nearest Class Center Accuracy: 0.35325

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.023401517421007156
Inter Cos: 0.06788400560617447
Norm Quadratic Average: 66.64813232421875
Nearest Class Center Accuracy: 0.388125

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03181608393788338
Inter Cos: 0.07379135489463806
Norm Quadratic Average: 42.277530670166016
Nearest Class Center Accuracy: 0.411

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.032713793218135834
Inter Cos: 0.06470286101102829
Norm Quadratic Average: 43.468955993652344
Nearest Class Center Accuracy: 0.450375

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.04468103498220444
Inter Cos: 0.07603952288627625
Norm Quadratic Average: 27.849987030029297
Nearest Class Center Accuracy: 0.537375

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.06366296112537384
Inter Cos: 0.07348711043596268
Norm Quadratic Average: 19.825218200683594
Nearest Class Center Accuracy: 0.816

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 98.03677368164062
Linear Weight Rank: 4031
Intra Cos: 0.18994230031967163
Inter Cos: 0.10755767673254013
Norm Quadratic Average: 105.96923065185547
Nearest Class Center Accuracy: 1.0

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 39.62981033325195
Linear Weight Rank: 3670
Intra Cos: 0.437623530626297
Inter Cos: 0.18763618171215057
Norm Quadratic Average: 54.85502624511719
Nearest Class Center Accuracy: 1.0

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 2.4806017875671387
Linear Weight Rank: 10
Intra Cos: 0.6729915738105774
Inter Cos: 0.2740021347999573
Norm Quadratic Average: 38.235633850097656
Nearest Class Center Accuracy: 1.0

Output Layer:
Intra Cos: 0.884555995464325
Inter Cos: 0.47622594237327576
Norm Quadratic Average: 26.385478973388672
Nearest Class Center Accuracy: 1.0

Test Set:
Average Loss: 2.6734926147460936
Accuracy: 0.583
NC1 Within Class Collapse: nan
NC2 Equinorm: Features: 0.19553421437740326, Weights: 0.0161607526242733
NC2 Equiangle: Features: 0.43969285753038195, Weights: 0.08969448937310112
NC3 Self-Duality: 0.6316626071929932
NC4 NCC Mismatch: 0.132

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: 0.021991828456521034
Inter Cos: 0.08754922449588776
Norm Quadratic Average: 84.45496368408203
Nearest Class Center Accuracy: 0.3495

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.02515394426882267
Inter Cos: 0.08081279695034027
Norm Quadratic Average: 63.08324432373047
Nearest Class Center Accuracy: 0.3755

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.02440834231674671
Inter Cos: 0.060992296785116196
Norm Quadratic Average: 66.52313232421875
Nearest Class Center Accuracy: 0.414

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.028717635199427605
Inter Cos: 0.06879889965057373
Norm Quadratic Average: 42.1772346496582
Nearest Class Center Accuracy: 0.439

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.02841462753713131
Inter Cos: 0.06185087189078331
Norm Quadratic Average: 43.38981628417969
Nearest Class Center Accuracy: 0.4665

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03189481794834137
Inter Cos: 0.07416757196187973
Norm Quadratic Average: 27.750835418701172
Nearest Class Center Accuracy: 0.49

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03390591964125633
Inter Cos: 0.0653122216463089
Norm Quadratic Average: 19.659841537475586
Nearest Class Center Accuracy: 0.5495

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 98.03677368164062
Linear Weight Rank: 4031
Intra Cos: 0.057730335742235184
Inter Cos: 0.10362733155488968
Norm Quadratic Average: 102.15342712402344
Nearest Class Center Accuracy: 0.599

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 39.62981033325195
Linear Weight Rank: 3670
Intra Cos: 0.1177324429154396
Inter Cos: 0.20151107013225555
Norm Quadratic Average: 50.57512664794922
Nearest Class Center Accuracy: 0.587

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 2.4806017875671387
Linear Weight Rank: 10
Intra Cos: 0.18477027118206024
Inter Cos: 0.31454959511756897
Norm Quadratic Average: 33.96247482299805
Nearest Class Center Accuracy: 0.572

Output Layer:
Intra Cos: 0.271419495344162
Inter Cos: 0.4844042658805847
Norm Quadratic Average: 22.79161262512207
Nearest Class Center Accuracy: 0.55

