Model save path: ./New_Models/bn_True_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: 0.02262684516608715
Inter Cos: 0.10058093070983887
Norm Quadratic Average: 86.55146789550781
Nearest Class Center Accuracy: 0.327

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.02466505393385887
Inter Cos: 0.08287842571735382
Norm Quadratic Average: 64.56163024902344
Nearest Class Center Accuracy: 0.361375

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.023393724113702774
Inter Cos: 0.06746680289506912
Norm Quadratic Average: 68.148193359375
Nearest Class Center Accuracy: 0.394

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03213699162006378
Inter Cos: 0.07520722597837448
Norm Quadratic Average: 43.29309844970703
Nearest Class Center Accuracy: 0.416875

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03274829313158989
Inter Cos: 0.06413714587688446
Norm Quadratic Average: 44.42958068847656
Nearest Class Center Accuracy: 0.45475

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.04491402953863144
Inter Cos: 0.07673550397157669
Norm Quadratic Average: 28.58161735534668
Nearest Class Center Accuracy: 0.526875

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.06247260421514511
Inter Cos: 0.07149821519851685
Norm Quadratic Average: 20.30390739440918
Nearest Class Center Accuracy: 0.8085

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 99.9354248046875
Linear Weight Rank: 4031
Intra Cos: 0.185614213347435
Inter Cos: 0.09827933460474014
Norm Quadratic Average: 107.51299285888672
Nearest Class Center Accuracy: 1.0

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 40.39695358276367
Linear Weight Rank: 3670
Intra Cos: 0.4426371455192566
Inter Cos: 0.17909321188926697
Norm Quadratic Average: 56.007606506347656
Nearest Class Center Accuracy: 1.0

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 2.5238990783691406
Linear Weight Rank: 10
Intra Cos: 0.6831661462783813
Inter Cos: 0.2862655222415924
Norm Quadratic Average: 39.32421112060547
Nearest Class Center Accuracy: 1.0

Output Layer:
Intra Cos: 0.8849425315856934
Inter Cos: 0.4904737174510956
Norm Quadratic Average: 27.55211067199707
Nearest Class Center Accuracy: 1.0

Test Set:
Average Loss: 2.711951858520508
Accuracy: 0.5795
NC1 Within Class Collapse: nan
NC2 Equinorm: Features: 0.20314650237560272, Weights: 0.017229242250323296
NC2 Equiangle: Features: 0.42128982543945315, Weights: 0.09103727340698242
NC3 Self-Duality: 0.6220411062240601
NC4 NCC Mismatch: 0.13049999999999995

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: 0.021835681051015854
Inter Cos: 0.08761976659297943
Norm Quadratic Average: 86.29215240478516
Nearest Class Center Accuracy: 0.352

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.02511911280453205
Inter Cos: 0.076260507106781
Norm Quadratic Average: 64.33397674560547
Nearest Class Center Accuracy: 0.3835

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.02454187721014023
Inter Cos: 0.058930035680532455
Norm Quadratic Average: 68.02433013916016
Nearest Class Center Accuracy: 0.421

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.029418105259537697
Inter Cos: 0.06825868040323257
Norm Quadratic Average: 43.19198989868164
Nearest Class Center Accuracy: 0.4445

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.029233889654278755
Inter Cos: 0.06032354012131691
Norm Quadratic Average: 44.34059524536133
Nearest Class Center Accuracy: 0.4675

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.031687431037425995
Inter Cos: 0.0733051672577858
Norm Quadratic Average: 28.468290328979492
Nearest Class Center Accuracy: 0.4735

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.032807786017656326
Inter Cos: 0.06572282314300537
Norm Quadratic Average: 20.125402450561523
Nearest Class Center Accuracy: 0.5485

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 99.9354248046875
Linear Weight Rank: 4031
Intra Cos: 0.05291253328323364
Inter Cos: 0.09973467141389847
Norm Quadratic Average: 103.74169921875
Nearest Class Center Accuracy: 0.6065

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 40.39695358276367
Linear Weight Rank: 3670
Intra Cos: 0.11198578774929047
Inter Cos: 0.19685611128807068
Norm Quadratic Average: 51.69243240356445
Nearest Class Center Accuracy: 0.59

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 2.5238990783691406
Linear Weight Rank: 10
Intra Cos: 0.17744635045528412
Inter Cos: 0.3132723867893219
Norm Quadratic Average: 34.919227600097656
Nearest Class Center Accuracy: 0.579

Output Layer:
Intra Cos: 0.26003506779670715
Inter Cos: 0.48702889680862427
Norm Quadratic Average: 23.71769905090332
Nearest Class Center Accuracy: 0.563

