Model save path: ./New_Models/bn_False_dataset_CIFAR10_epochs_100_lr_0.001_model_type_vgg11_rand_seed_338327_weight_decay_0.007.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: 0.11371058225631714
Norm Quadratic Average: 27.691619873046875
Nearest Class Center Accuracy: 0.279125

Layer 1: Conv2d(64, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.023914171382784843
Inter Cos: 0.09616141766309738
Norm Quadratic Average: 34.499168395996094
Nearest Class Center Accuracy: 0.298625

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.02913215383887291
Inter Cos: 0.10567408800125122
Norm Quadratic Average: 28.00455093383789
Nearest Class Center Accuracy: 0.35825

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03567638248205185
Inter Cos: 0.1120314747095108
Norm Quadratic Average: 31.260805130004883
Nearest Class Center Accuracy: 0.407125

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.05269305035471916
Inter Cos: 0.14143820106983185
Norm Quadratic Average: 18.288192749023438
Nearest Class Center Accuracy: 0.436

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.06290069967508316
Inter Cos: 0.15124493837356567
Norm Quadratic Average: 13.838508605957031
Nearest Class Center Accuracy: 0.46525

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.08241362124681473
Inter Cos: 0.1604314148426056
Norm Quadratic Average: 6.208826065063477
Nearest Class Center Accuracy: 0.5245

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.12894275784492493
Inter Cos: 0.1895444393157959
Norm Quadratic Average: 3.906066417694092
Nearest Class Center Accuracy: 0.7185

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 72.4969253540039
Linear Weight Rank: 4031
Intra Cos: 0.4083201289176941
Inter Cos: 0.35479456186294556
Norm Quadratic Average: 16.445362091064453
Nearest Class Center Accuracy: 0.967625

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 29.38610076904297
Linear Weight Rank: 3670
Intra Cos: 0.6722321510314941
Inter Cos: 0.5009472370147705
Norm Quadratic Average: 16.248886108398438
Nearest Class Center Accuracy: 0.997625

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 3.0529427528381348
Linear Weight Rank: 10
Intra Cos: 0.755895733833313
Inter Cos: 0.5893577933311462
Norm Quadratic Average: 19.653705596923828
Nearest Class Center Accuracy: 0.999

Output Layer:
Intra Cos: 0.8336591124534607
Inter Cos: 0.7284629940986633
Norm Quadratic Average: 24.975866317749023
Nearest Class Center Accuracy: 0.998625

Test Set:
Average Loss: 2.2045830307006837
Accuracy: 0.5945
NC1 Within Class Collapse: nan
NC2 Equinorm: Features: 0.23169657588005066, Weights: 0.05543288588523865
NC2 Equiangle: Features: 0.43811687893337675, Weights: 0.20127218034532335
NC3 Self-Duality: 0.36923083662986755
NC4 NCC Mismatch: 0.16200000000000003

Layer 0: Conv2d(3, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.018480459228157997
Inter Cos: 0.09352367371320724
Norm Quadratic Average: 27.53066635131836
Nearest Class Center Accuracy: 0.2895

Layer 1: Conv2d(64, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.025027258321642876
Inter Cos: 0.07918435335159302
Norm Quadratic Average: 34.24382781982422
Nearest Class Center Accuracy: 0.3085

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03224307671189308
Inter Cos: 0.09089997410774231
Norm Quadratic Average: 27.834463119506836
Nearest Class Center Accuracy: 0.37

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.037380658090114594
Inter Cos: 0.0994332954287529
Norm Quadratic Average: 31.138254165649414
Nearest Class Center Accuracy: 0.431

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.052111394703388214
Inter Cos: 0.12538382411003113
Norm Quadratic Average: 18.239070892333984
Nearest Class Center Accuracy: 0.452

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.06027786806225777
Inter Cos: 0.13367877900600433
Norm Quadratic Average: 13.832671165466309
Nearest Class Center Accuracy: 0.469

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.07026071101427078
Inter Cos: 0.1377670019865036
Norm Quadratic Average: 6.201359748840332
Nearest Class Center Accuracy: 0.4925

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.09003790467977524
Inter Cos: 0.1635434329509735
Norm Quadratic Average: 3.8756046295166016
Nearest Class Center Accuracy: 0.519

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 72.4969253540039
Linear Weight Rank: 4031
Intra Cos: 0.19337350130081177
Inter Cos: 0.30779948830604553
Norm Quadratic Average: 15.760695457458496
Nearest Class Center Accuracy: 0.577

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 29.38610076904297
Linear Weight Rank: 3670
Intra Cos: 0.27110016345977783
Inter Cos: 0.41610851883888245
Norm Quadratic Average: 15.197745323181152
Nearest Class Center Accuracy: 0.586

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 3.0529427528381348
Linear Weight Rank: 10
Intra Cos: 0.2843293249607086
Inter Cos: 0.4770452082157135
Norm Quadratic Average: 18.30743980407715
Nearest Class Center Accuracy: 0.5775

Output Layer:
Intra Cos: 0.3065548241138458
Inter Cos: 0.5700904130935669
Norm Quadratic Average: 23.134605407714844
Nearest Class Center Accuracy: 0.56

