Model save path: ./New_Models/bn_True_dataset_CIFAR10_epochs_100_lr_0.001_model_type_vgg11_rand_seed_314159_weight_decay_0.02.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: 0.022549709305167198
Inter Cos: 0.10230951756238937
Norm Quadratic Average: 33.483028411865234
Nearest Class Center Accuracy: 0.325

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.025633269920945168
Inter Cos: 0.0886327251791954
Norm Quadratic Average: 24.9310302734375
Nearest Class Center Accuracy: 0.359375

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.024059440940618515
Inter Cos: 0.06904111802577972
Norm Quadratic Average: 26.27806854248047
Nearest Class Center Accuracy: 0.40025

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.032801058143377304
Inter Cos: 0.07926179468631744
Norm Quadratic Average: 16.55108642578125
Nearest Class Center Accuracy: 0.431375

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.035749401897192
Inter Cos: 0.07124996930360794
Norm Quadratic Average: 16.91690444946289
Nearest Class Center Accuracy: 0.492625

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.06279411911964417
Inter Cos: 0.08178764581680298
Norm Quadratic Average: 10.355538368225098
Nearest Class Center Accuracy: 0.742625

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.18313011527061462
Inter Cos: 0.11434046924114227
Norm Quadratic Average: 7.048354625701904
Nearest Class Center Accuracy: 1.0

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 38.80506896972656
Linear Weight Rank: 4031
Intra Cos: 0.6479684114456177
Inter Cos: 0.22364839911460876
Norm Quadratic Average: 56.889522552490234
Nearest Class Center Accuracy: 1.0

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 15.735376358032227
Linear Weight Rank: 3669
Intra Cos: 0.9060742855072021
Inter Cos: 0.2896629273891449
Norm Quadratic Average: 29.264558792114258
Nearest Class Center Accuracy: 1.0

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 1.6740225553512573
Linear Weight Rank: 10
Intra Cos: 0.9441139101982117
Inter Cos: 0.3492771089076996
Norm Quadratic Average: 18.94832992553711
Nearest Class Center Accuracy: 1.0

Output Layer:
Intra Cos: 0.9528817534446716
Inter Cos: 0.4762401580810547
Norm Quadratic Average: 12.550704956054688
Nearest Class Center Accuracy: 1.0

Test Set:
Average Loss: 1.4634756698608398
Accuracy: 0.5925
NC1 Within Class Collapse: nan
NC2 Equinorm: Features: 0.19380013644695282, Weights: 0.025549618527293205
NC2 Equiangle: Features: 0.35469915601942276, Weights: 0.16097162034776474
NC3 Self-Duality: 0.3276776373386383
NC4 NCC Mismatch: 0.123

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: 0.021778641268610954
Inter Cos: 0.08911439776420593
Norm Quadratic Average: 33.37282180786133
Nearest Class Center Accuracy: 0.349

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.025913720950484276
Inter Cos: 0.07816948741674423
Norm Quadratic Average: 24.831205368041992
Nearest Class Center Accuracy: 0.379

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.025049053132534027
Inter Cos: 0.06052004545927048
Norm Quadratic Average: 26.217891693115234
Nearest Class Center Accuracy: 0.42

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.029722748324275017
Inter Cos: 0.06920284032821655
Norm Quadratic Average: 16.503318786621094
Nearest Class Center Accuracy: 0.448

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.030933039262890816
Inter Cos: 0.06106473132967949
Norm Quadratic Average: 16.874805450439453
Nearest Class Center Accuracy: 0.485

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03767632320523262
Inter Cos: 0.07433240115642548
Norm Quadratic Average: 10.30815601348877
Nearest Class Center Accuracy: 0.5425

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.054801613092422485
Inter Cos: 0.10807619243860245
Norm Quadratic Average: 6.857751846313477
Nearest Class Center Accuracy: 0.629

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 38.80506896972656
Linear Weight Rank: 4031
Intra Cos: 0.1472877860069275
Inter Cos: 0.23313790559768677
Norm Quadratic Average: 49.71601104736328
Nearest Class Center Accuracy: 0.6045

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 15.735376358032227
Linear Weight Rank: 3669
Intra Cos: 0.2285887598991394
Inter Cos: 0.35342082381248474
Norm Quadratic Average: 23.756826400756836
Nearest Class Center Accuracy: 0.5895

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 1.6740225553512573
Linear Weight Rank: 10
Intra Cos: 0.2387567013502121
Inter Cos: 0.3878573477268219
Norm Quadratic Average: 15.256002426147461
Nearest Class Center Accuracy: 0.584

Output Layer:
Intra Cos: 0.23525552451610565
Inter Cos: 0.41305285692214966
Norm Quadratic Average: 9.974343299865723
Nearest Class Center Accuracy: 0.5655

