Model save path: ./New_Models/bn_False_dataset_CIFAR10_epochs_200_lr_0.01_model_type_vgg11_rand_seed_265358_test_samples_None_train_samples_None_weight_decay_0.0005.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: 0.023938028141856194
Inter Cos: 0.09293234348297119
Norm Quadratic Average: 27.079544067382812
Nearest Class Center Accuracy: 0.3896

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.026899980381131172
Inter Cos: 0.08470144867897034
Norm Quadratic Average: 23.82710838317871
Nearest Class Center Accuracy: 0.49638

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.02666255459189415
Inter Cos: 0.06660681962966919
Norm Quadratic Average: 25.440343856811523
Nearest Class Center Accuracy: 0.5791

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.02980029582977295
Inter Cos: 0.05270291492342949
Norm Quadratic Average: 11.793374061584473
Nearest Class Center Accuracy: 0.67904

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.04642096534371376
Inter Cos: 0.05391969531774521
Norm Quadratic Average: 6.815561771392822
Nearest Class Center Accuracy: 0.75426

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.13857194781303406
Inter Cos: 0.12306869775056839
Norm Quadratic Average: 2.6575028896331787
Nearest Class Center Accuracy: 0.88538

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.5448197722434998
Inter Cos: 0.24395424127578735
Norm Quadratic Average: 1.615161657333374
Nearest Class Center Accuracy: 0.9975

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 20.44198226928711
Linear Weight Rank: 4031
Intra Cos: 0.8246356844902039
Inter Cos: 0.2101057767868042
Norm Quadratic Average: 11.234809875488281
Nearest Class Center Accuracy: 0.99896

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 9.017699241638184
Linear Weight Rank: 3666
Intra Cos: 0.8893299698829651
Inter Cos: 0.13670086860656738
Norm Quadratic Average: 11.984550476074219
Nearest Class Center Accuracy: 0.99982

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 3.723632335662842
Linear Weight Rank: 10
Intra Cos: 0.9042422771453857
Inter Cos: 0.1600789576768875
Norm Quadratic Average: 13.424870491027832
Nearest Class Center Accuracy: 1.0

Output Layer:
Intra Cos: 0.9281641244888306
Inter Cos: 0.3248218595981598
Norm Quadratic Average: 16.556612014770508
Nearest Class Center Accuracy: 1.0

Test Set:
Average Loss: 0.8909905521392822
Accuracy: 0.8136
NC1 Within Class Collapse: 5.623981475830078
NC2 Equinorm: Features: 0.21454079449176788, Weights: 0.036122389137744904
NC2 Equiangle: Features: 0.19396413167317708, Weights: 0.054974635442097984
NC3 Self-Duality: 0.1553768366575241
NC4 NCC Mismatch: 0.05020000000000002

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: 0.02200290560722351
Inter Cos: 0.09367625415325165
Norm Quadratic Average: 27.059703826904297
Nearest Class Center Accuracy: 0.4066

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.025184951722621918
Inter Cos: 0.08588960766792297
Norm Quadratic Average: 23.833860397338867
Nearest Class Center Accuracy: 0.5036

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.02452806942164898
Inter Cos: 0.06753477454185486
Norm Quadratic Average: 25.464818954467773
Nearest Class Center Accuracy: 0.5787

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.026065276935696602
Inter Cos: 0.05384764447808266
Norm Quadratic Average: 11.806670188903809
Nearest Class Center Accuracy: 0.6547

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03967244550585747
Inter Cos: 0.05508699268102646
Norm Quadratic Average: 6.808346748352051
Nearest Class Center Accuracy: 0.6964

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.10672515630722046
Inter Cos: 0.12762553989887238
Norm Quadratic Average: 2.6423656940460205
Nearest Class Center Accuracy: 0.7492

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.33004364371299744
Inter Cos: 0.282060444355011
Norm Quadratic Average: 1.5692447423934937
Nearest Class Center Accuracy: 0.8067

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 20.44198226928711
Linear Weight Rank: 4031
Intra Cos: 0.4872455298900604
Inter Cos: 0.33838337659835815
Norm Quadratic Average: 10.716361045837402
Nearest Class Center Accuracy: 0.8014

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 9.017699241638184
Linear Weight Rank: 3666
Intra Cos: 0.5029101967811584
Inter Cos: 0.313538134098053
Norm Quadratic Average: 11.329785346984863
Nearest Class Center Accuracy: 0.8058

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 3.723632335662842
Linear Weight Rank: 10
Intra Cos: 0.49345219135284424
Inter Cos: 0.2964400053024292
Norm Quadratic Average: 12.660238265991211
Nearest Class Center Accuracy: 0.8096

Output Layer:
Intra Cos: 0.5121981501579285
Inter Cos: 0.35637715458869934
Norm Quadratic Average: 15.571134567260742
Nearest Class Center Accuracy: 0.8115

