Model save path: ./New_Models/bn_True_dataset_CIFAR10_epochs_100_lr_0.001_model_type_vgg11_rand_seed_338327_weight_decay_0.01.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: 0.02366214618086815
Inter Cos: 0.10133743286132812
Norm Quadratic Average: 53.52803039550781
Nearest Class Center Accuracy: 0.335625

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.026133686304092407
Inter Cos: 0.09302235394716263
Norm Quadratic Average: 40.149497985839844
Nearest Class Center Accuracy: 0.3725

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.022818338125944138
Inter Cos: 0.07216197997331619
Norm Quadratic Average: 42.80526351928711
Nearest Class Center Accuracy: 0.400375

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03185427933931351
Inter Cos: 0.08183211088180542
Norm Quadratic Average: 27.35370445251465
Nearest Class Center Accuracy: 0.420375

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.030623551458120346
Inter Cos: 0.06885579973459244
Norm Quadratic Average: 27.760404586791992
Nearest Class Center Accuracy: 0.47025

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.04516076296567917
Inter Cos: 0.07481727749109268
Norm Quadratic Average: 17.61166763305664
Nearest Class Center Accuracy: 0.616125

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.08652152866125107
Inter Cos: 0.0839168056845665
Norm Quadratic Average: 12.407916069030762
Nearest Class Center Accuracy: 0.956875

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 62.74253463745117
Linear Weight Rank: 4031
Intra Cos: 0.31473368406295776
Inter Cos: 0.1412830799818039
Norm Quadratic Average: 73.93907165527344
Nearest Class Center Accuracy: 1.0

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 25.377544403076172
Linear Weight Rank: 3670
Intra Cos: 0.6601830720901489
Inter Cos: 0.25355061888694763
Norm Quadratic Average: 35.41197967529297
Nearest Class Center Accuracy: 1.0

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 1.9084961414337158
Linear Weight Rank: 10
Intra Cos: 0.8361881375312805
Inter Cos: 0.351892352104187
Norm Quadratic Average: 23.363712310791016
Nearest Class Center Accuracy: 1.0

Output Layer:
Intra Cos: 0.9053915739059448
Inter Cos: 0.4897657036781311
Norm Quadratic Average: 15.025403022766113
Nearest Class Center Accuracy: 1.0

Test Set:
Average Loss: 1.636246925354004
Accuracy: 0.592
NC1 Within Class Collapse: nan
NC2 Equinorm: Features: 0.2147216498851776, Weights: 0.013019745238125324
NC2 Equiangle: Features: 0.4118909200032552, Weights: 0.1085879537794325
NC3 Self-Duality: 0.4951108992099762
NC4 NCC Mismatch: 0.14449999999999996

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: 0.022790389135479927
Inter Cos: 0.08756508678197861
Norm Quadratic Average: 53.22040557861328
Nearest Class Center Accuracy: 0.353

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.026568511500954628
Inter Cos: 0.08084551990032196
Norm Quadratic Average: 39.93365478515625
Nearest Class Center Accuracy: 0.3965

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.023268256336450577
Inter Cos: 0.06271349638700485
Norm Quadratic Average: 42.65456771850586
Nearest Class Center Accuracy: 0.44

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.02994958497583866
Inter Cos: 0.07250718772411346
Norm Quadratic Average: 27.26088523864746
Nearest Class Center Accuracy: 0.448

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.027807442471385002
Inter Cos: 0.0592360682785511
Norm Quadratic Average: 27.70526885986328
Nearest Class Center Accuracy: 0.483

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03139631450176239
Inter Cos: 0.07238990813493729
Norm Quadratic Average: 17.54501724243164
Nearest Class Center Accuracy: 0.515

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03742191195487976
Inter Cos: 0.07601014524698257
Norm Quadratic Average: 12.260846138000488
Nearest Class Center Accuracy: 0.593

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 62.74253463745117
Linear Weight Rank: 4031
Intra Cos: 0.08101633191108704
Inter Cos: 0.14861883223056793
Norm Quadratic Average: 69.43952178955078
Nearest Class Center Accuracy: 0.6125

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 25.377544403076172
Linear Weight Rank: 3670
Intra Cos: 0.16588550806045532
Inter Cos: 0.2897260785102844
Norm Quadratic Average: 31.112619400024414
Nearest Class Center Accuracy: 0.6005

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 1.9084961414337158
Linear Weight Rank: 10
Intra Cos: 0.217194065451622
Inter Cos: 0.3944530189037323
Norm Quadratic Average: 19.920270919799805
Nearest Class Center Accuracy: 0.593

Output Layer:
Intra Cos: 0.24281400442123413
Inter Cos: 0.48494580388069153
Norm Quadratic Average: 12.636619567871094
Nearest Class Center Accuracy: 0.581

