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_0.005.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: 0.01937650889158249
Inter Cos: 0.07341426610946655
Norm Quadratic Average: 3.3779797554016113
Nearest Class Center Accuracy: 0.40274

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.020729824900627136
Inter Cos: 0.05632175877690315
Norm Quadratic Average: 1.7117629051208496
Nearest Class Center Accuracy: 0.53958

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.016720617190003395
Inter Cos: 0.04602448269724846
Norm Quadratic Average: 1.301729679107666
Nearest Class Center Accuracy: 0.61468

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.024444090202450752
Inter Cos: 0.04501715302467346
Norm Quadratic Average: 0.8704962134361267
Nearest Class Center Accuracy: 0.76044

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.05809658765792847
Inter Cos: 0.06911884993314743
Norm Quadratic Average: 0.6203394532203674
Nearest Class Center Accuracy: 0.90186

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.3708818554878235
Inter Cos: 0.20524469017982483
Norm Quadratic Average: 0.43661391735076904
Nearest Class Center Accuracy: 0.9984

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.8813946843147278
Inter Cos: 0.08554638922214508
Norm Quadratic Average: 0.7374633550643921
Nearest Class Center Accuracy: 1.0

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 2.208369016647339
Linear Weight Rank: 164
Intra Cos: 0.9852300882339478
Inter Cos: 0.01606673374772072
Norm Quadratic Average: 23.726205825805664
Nearest Class Center Accuracy: 1.0

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 2.221708059310913
Linear Weight Rank: 1107
Intra Cos: 0.9911185503005981
Inter Cos: 0.057376570999622345
Norm Quadratic Average: 16.32295799255371
Nearest Class Center Accuracy: 1.0

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 2.207810878753662
Linear Weight Rank: 9
Intra Cos: 0.9928534626960754
Inter Cos: 0.07892194390296936
Norm Quadratic Average: 11.496365547180176
Nearest Class Center Accuracy: 1.0

Output Layer:
Intra Cos: 0.9938610792160034
Inter Cos: 0.09084925800561905
Norm Quadratic Average: 8.452783584594727
Nearest Class Center Accuracy: 1.0

Test Set:
Average Loss: 0.40873809490203855
Accuracy: 0.8738
NC1 Within Class Collapse: 2.9925613403320312
NC2 Equinorm: Features: 0.11726734787225723, Weights: 0.0035400870256125927
NC2 Equiangle: Features: 0.11971304151746961, Weights: 0.012627053260803222
NC3 Self-Duality: 0.04817349463701248
NC4 NCC Mismatch: 0.016100000000000003

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: 0.018146706745028496
Inter Cos: 0.07542650401592255
Norm Quadratic Average: 3.375511884689331
Nearest Class Center Accuracy: 0.4209

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.01974489539861679
Inter Cos: 0.05743023008108139
Norm Quadratic Average: 1.7126306295394897
Nearest Class Center Accuracy: 0.5421

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.015730557963252068
Inter Cos: 0.04688461124897003
Norm Quadratic Average: 1.3032642602920532
Nearest Class Center Accuracy: 0.6188

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.02119845524430275
Inter Cos: 0.04589264094829559
Norm Quadratic Average: 0.8702937960624695
Nearest Class Center Accuracy: 0.725

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.044553905725479126
Inter Cos: 0.07273154705762863
Norm Quadratic Average: 0.6153751611709595
Nearest Class Center Accuracy: 0.7965

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.2545245289802551
Inter Cos: 0.22729775309562683
Norm Quadratic Average: 0.4218525290489197
Nearest Class Center Accuracy: 0.858

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.5074232220649719
Inter Cos: 0.2618541419506073
Norm Quadratic Average: 0.6730791926383972
Nearest Class Center Accuracy: 0.8742

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 2.208369016647339
Linear Weight Rank: 164
Intra Cos: 0.6068342328071594
Inter Cos: 0.2661186158657074
Norm Quadratic Average: 20.89914321899414
Nearest Class Center Accuracy: 0.8731

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 2.221708059310913
Linear Weight Rank: 1107
Intra Cos: 0.6144101023674011
Inter Cos: 0.2736660838127136
Norm Quadratic Average: 14.357250213623047
Nearest Class Center Accuracy: 0.8732

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 2.207810878753662
Linear Weight Rank: 9
Intra Cos: 0.6177390813827515
Inter Cos: 0.28122755885124207
Norm Quadratic Average: 10.110870361328125
Nearest Class Center Accuracy: 0.8736

Output Layer:
Intra Cos: 0.6213995814323425
Inter Cos: 0.28574225306510925
Norm Quadratic Average: 7.436493873596191
Nearest Class Center Accuracy: 0.8738

