Model save path: ./New_Models/bn_True_dataset_CIFAR10_epochs_100_lr_0.001_model_type_vgg11_rand_seed_265358_weight_decay_0.0001.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: 0.026964904740452766
Inter Cos: 0.10300234705209732
Norm Quadratic Average: 86.79888153076172
Nearest Class Center Accuracy: 0.339125

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03164766728878021
Inter Cos: 0.09374174475669861
Norm Quadratic Average: 63.406620025634766
Nearest Class Center Accuracy: 0.373125

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.027435986325144768
Inter Cos: 0.07492567598819733
Norm Quadratic Average: 68.80072784423828
Nearest Class Center Accuracy: 0.401875

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.034782715141773224
Inter Cos: 0.07902097702026367
Norm Quadratic Average: 44.03758239746094
Nearest Class Center Accuracy: 0.431

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03291066735982895
Inter Cos: 0.06964218616485596
Norm Quadratic Average: 45.11842727661133
Nearest Class Center Accuracy: 0.46675

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.04462965950369835
Inter Cos: 0.07793170213699341
Norm Quadratic Average: 29.105072021484375
Nearest Class Center Accuracy: 0.557

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.06135743856430054
Inter Cos: 0.0775456428527832
Norm Quadratic Average: 20.481470108032227
Nearest Class Center Accuracy: 0.839125

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 100.90557861328125
Linear Weight Rank: 4031
Intra Cos: 0.18178962171077728
Inter Cos: 0.10880342125892639
Norm Quadratic Average: 108.64508819580078
Nearest Class Center Accuracy: 0.999625

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 40.79640579223633
Linear Weight Rank: 3671
Intra Cos: 0.41955310106277466
Inter Cos: 0.19013261795043945
Norm Quadratic Average: 57.17538833618164
Nearest Class Center Accuracy: 1.0

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 2.5555529594421387
Linear Weight Rank: 10
Intra Cos: 0.6551331281661987
Inter Cos: 0.29146096110343933
Norm Quadratic Average: 40.39793395996094
Nearest Class Center Accuracy: 1.0

Output Layer:
Intra Cos: 0.8768159747123718
Inter Cos: 0.49979132413864136
Norm Quadratic Average: 28.77443504333496
Nearest Class Center Accuracy: 1.0

Test Set:
Average Loss: 2.776933029174805
Accuracy: 0.577
NC1 Within Class Collapse: nan
NC2 Equinorm: Features: 0.20797714591026306, Weights: 0.019085075706243515
NC2 Equiangle: Features: 0.45840106540256076, Weights: 0.08868349393208821
NC3 Self-Duality: 0.6396447420120239
NC4 NCC Mismatch: 0.15500000000000003

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: 0.024678723886609077
Inter Cos: 0.09058903902769089
Norm Quadratic Average: 86.79002380371094
Nearest Class Center Accuracy: 0.355

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03009810857474804
Inter Cos: 0.08909173309803009
Norm Quadratic Average: 63.402732849121094
Nearest Class Center Accuracy: 0.393

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.02699895016849041
Inter Cos: 0.06904467940330505
Norm Quadratic Average: 68.87003326416016
Nearest Class Center Accuracy: 0.4185

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03292660042643547
Inter Cos: 0.08029817789793015
Norm Quadratic Average: 44.05234909057617
Nearest Class Center Accuracy: 0.448

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.030156666412949562
Inter Cos: 0.0672396793961525
Norm Quadratic Average: 45.096553802490234
Nearest Class Center Accuracy: 0.4755

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03498547524213791
Inter Cos: 0.07820701599121094
Norm Quadratic Average: 29.023591995239258
Nearest Class Center Accuracy: 0.491

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03504562005400658
Inter Cos: 0.07203293591737747
Norm Quadratic Average: 20.323909759521484
Nearest Class Center Accuracy: 0.568

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 100.90557861328125
Linear Weight Rank: 4031
Intra Cos: 0.06213787570595741
Inter Cos: 0.11086273193359375
Norm Quadratic Average: 104.46231079101562
Nearest Class Center Accuracy: 0.605

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 40.79640579223633
Linear Weight Rank: 3671
Intra Cos: 0.1254042237997055
Inter Cos: 0.19971515238285065
Norm Quadratic Average: 52.46488952636719
Nearest Class Center Accuracy: 0.589

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 2.5555529594421387
Linear Weight Rank: 10
Intra Cos: 0.1945156753063202
Inter Cos: 0.3115188181400299
Norm Quadratic Average: 35.61543655395508
Nearest Class Center Accuracy: 0.58

Output Layer:
Intra Cos: 0.28740328550338745
Inter Cos: 0.49342259764671326
Norm Quadratic Average: 24.585556030273438
Nearest Class Center Accuracy: 0.5595

