Model save path: ./New_Models/bn_True_dataset_CIFAR10_epochs_200_lr_0.01_model_type_vgg11_rand_seed_265358_test_samples_None_train_samples_None_weight_decay_0.001.pth.tar
Training Set:
Layer 0: Conv2d(3, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.01989092119038105
Inter Cos: 0.10477277636528015
Norm Quadratic Average: 27.59717559814453
Nearest Class Center Accuracy: 0.26968

Layer 1: Conv2d(64, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.018837882205843925
Inter Cos: 0.07128091156482697
Norm Quadratic Average: 15.037057876586914
Nearest Class Center Accuracy: 0.40308

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.019390832632780075
Inter Cos: 0.054175954312086105
Norm Quadratic Average: 7.430179595947266
Nearest Class Center Accuracy: 0.52894

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.01404041051864624
Inter Cos: 0.04124952852725983
Norm Quadratic Average: 5.838176727294922
Nearest Class Center Accuracy: 0.61088

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.019656820222735405
Inter Cos: 0.033594902604818344
Norm Quadratic Average: 3.9700663089752197
Nearest Class Center Accuracy: 0.74632

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03369447961449623
Inter Cos: 0.03522803261876106
Norm Quadratic Average: 2.7623183727264404
Nearest Class Center Accuracy: 0.8605

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.13666093349456787
Inter Cos: 0.08465515077114105
Norm Quadratic Average: 2.009492874145508
Nearest Class Center Accuracy: 0.97102

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.6383488178253174
Inter Cos: 0.09349550306797028
Norm Quadratic Average: 1.3285229206085205
Nearest Class Center Accuracy: 1.0

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 4.832339286804199
Linear Weight Rank: 4029
Intra Cos: 0.9204537868499756
Inter Cos: -0.01994357444345951
Norm Quadratic Average: 24.71608543395996
Nearest Class Center Accuracy: 1.0

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 3.299123764038086
Linear Weight Rank: 3637
Intra Cos: 0.9717469215393066
Inter Cos: -0.05708034336566925
Norm Quadratic Average: 18.76730728149414
Nearest Class Center Accuracy: 1.0

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 2.638415813446045
Linear Weight Rank: 9
Intra Cos: 0.9684955477714539
Inter Cos: 0.044684477150440216
Norm Quadratic Average: 14.393394470214844
Nearest Class Center Accuracy: 1.0

Output Layer:
Intra Cos: 0.9859409332275391
Inter Cos: 0.19241942465305328
Norm Quadratic Average: 12.315949440002441
Nearest Class Center Accuracy: 1.0

Test Set:
Average Loss: 0.6223802080154419
Accuracy: 0.8513
NC1 Within Class Collapse: 3.931687593460083
NC2 Equinorm: Features: 0.1422264128923416, Weights: 0.012614453211426735
NC2 Equiangle: Features: 0.11782239278157552, Weights: 0.044135702980889216
NC3 Self-Duality: 0.09414465725421906
NC4 NCC Mismatch: 0.024399999999999977

Layer 0: Conv2d(3, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.018526077270507812
Inter Cos: 0.1042705774307251
Norm Quadratic Average: 27.550134658813477
Nearest Class Center Accuracy: 0.284

Layer 1: Conv2d(64, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.017772499471902847
Inter Cos: 0.07261715084314346
Norm Quadratic Average: 15.023390769958496
Nearest Class Center Accuracy: 0.4191

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.018224211409687996
Inter Cos: 0.05545909330248833
Norm Quadratic Average: 7.431060791015625
Nearest Class Center Accuracy: 0.5416

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.012933621183037758
Inter Cos: 0.04232357442378998
Norm Quadratic Average: 5.8424553871154785
Nearest Class Center Accuracy: 0.6144

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.01633218489587307
Inter Cos: 0.0347258634865284
Norm Quadratic Average: 3.972165822982788
Nearest Class Center Accuracy: 0.7107

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.024912644177675247
Inter Cos: 0.037472933530807495
Norm Quadratic Average: 2.750180721282959
Nearest Class Center Accuracy: 0.7622

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.09712302684783936
Inter Cos: 0.09337899833917618
Norm Quadratic Average: 1.9754306077957153
Nearest Class Center Accuracy: 0.8051

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.32981395721435547
Inter Cos: 0.18374201655387878
Norm Quadratic Average: 1.23830246925354
Nearest Class Center Accuracy: 0.8424

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 4.832339286804199
Linear Weight Rank: 4029
Intra Cos: 0.5319623351097107
Inter Cos: 0.23426786065101624
Norm Quadratic Average: 22.015880584716797
Nearest Class Center Accuracy: 0.8401

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 3.299123764038086
Linear Weight Rank: 3637
Intra Cos: 0.5370185971260071
Inter Cos: 0.22049999237060547
Norm Quadratic Average: 16.520591735839844
Nearest Class Center Accuracy: 0.8448

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 2.638415813446045
Linear Weight Rank: 9
Intra Cos: 0.5367156267166138
Inter Cos: 0.23721888661384583
Norm Quadratic Average: 12.784256935119629
Nearest Class Center Accuracy: 0.8485

Output Layer:
Intra Cos: 0.579532265663147
Inter Cos: 0.3024374842643738
Norm Quadratic Average: 10.922905921936035
Nearest Class Center Accuracy: 0.8488

