Model save path: ./New_Models/bn_False_dataset_CIFAR10_epochs_200_lr_0.01_model_type_vgg11_rand_seed_314159_test_samples_None_train_samples_None_weight_decay_0.0003.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: 0.10477276146411896
Norm Quadratic Average: 27.59718132019043
Nearest Class Center Accuracy: 0.26968

Layer 1: Conv2d(64, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.02302536368370056
Inter Cos: 0.08132154494524002
Norm Quadratic Average: 28.925647735595703
Nearest Class Center Accuracy: 0.3934

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.026441996917128563
Inter Cos: 0.07408172637224197
Norm Quadratic Average: 25.6029109954834
Nearest Class Center Accuracy: 0.5062

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.026209896430373192
Inter Cos: 0.0577794685959816
Norm Quadratic Average: 27.090534210205078
Nearest Class Center Accuracy: 0.5913

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.02953355945646763
Inter Cos: 0.05054106563329697
Norm Quadratic Average: 12.515798568725586
Nearest Class Center Accuracy: 0.6945

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.04517108201980591
Inter Cos: 0.05270691215991974
Norm Quadratic Average: 7.360998630523682
Nearest Class Center Accuracy: 0.7675

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.13813179731369019
Inter Cos: 0.10601069778203964
Norm Quadratic Average: 2.8335468769073486
Nearest Class Center Accuracy: 0.8899

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.5093836188316345
Inter Cos: 0.21013499796390533
Norm Quadratic Average: 1.8374401330947876
Nearest Class Center Accuracy: 0.99236

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 38.578033447265625
Linear Weight Rank: 4031
Intra Cos: 0.8506017923355103
Inter Cos: 0.20822764933109283
Norm Quadratic Average: 12.367074012756348
Nearest Class Center Accuracy: 0.9985

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 16.037612915039062
Linear Weight Rank: 3668
Intra Cos: 0.9073508381843567
Inter Cos: 0.13924157619476318
Norm Quadratic Average: 13.018472671508789
Nearest Class Center Accuracy: 0.99978

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 3.808570623397827
Linear Weight Rank: 10
Intra Cos: 0.9203958511352539
Inter Cos: 0.1342257261276245
Norm Quadratic Average: 14.732952117919922
Nearest Class Center Accuracy: 0.99998

Output Layer:
Intra Cos: 0.9473466277122498
Inter Cos: 0.3122507929801941
Norm Quadratic Average: 18.402746200561523
Nearest Class Center Accuracy: 1.0

Test Set:
Average Loss: 0.9616829864501953
Accuracy: 0.8179
NC1 Within Class Collapse: 5.722460746765137
NC2 Equinorm: Features: 0.22468487918376923, Weights: 0.023721659556031227
NC2 Equiangle: Features: 0.1945559607611762, Weights: 0.07782403628031413
NC3 Self-Duality: 0.18614843487739563
NC4 NCC Mismatch: 0.057699999999999974

Layer 0: Conv2d(3, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.018526073545217514
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: 0.02137533202767372
Inter Cos: 0.08180856704711914
Norm Quadratic Average: 28.907974243164062
Nearest Class Center Accuracy: 0.4085

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.024924440309405327
Inter Cos: 0.07529569417238235
Norm Quadratic Average: 25.6104736328125
Nearest Class Center Accuracy: 0.5124

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.024069929495453835
Inter Cos: 0.05841909348964691
Norm Quadratic Average: 27.117294311523438
Nearest Class Center Accuracy: 0.5973

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.026031799614429474
Inter Cos: 0.05182215943932533
Norm Quadratic Average: 12.523810386657715
Nearest Class Center Accuracy: 0.6739

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03877023607492447
Inter Cos: 0.054264701902866364
Norm Quadratic Average: 7.34467887878418
Nearest Class Center Accuracy: 0.7133

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.11023199558258057
Inter Cos: 0.11065588891506195
Norm Quadratic Average: 2.809107542037964
Nearest Class Center Accuracy: 0.745

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.31114789843559265
Inter Cos: 0.2527940571308136
Norm Quadratic Average: 1.7798508405685425
Nearest Class Center Accuracy: 0.7975

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 38.578033447265625
Linear Weight Rank: 4031
Intra Cos: 0.503694474697113
Inter Cos: 0.348197340965271
Norm Quadratic Average: 11.679176330566406
Nearest Class Center Accuracy: 0.7985

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 16.037612915039062
Linear Weight Rank: 3668
Intra Cos: 0.5222530961036682
Inter Cos: 0.3293987810611725
Norm Quadratic Average: 12.196111679077148
Nearest Class Center Accuracy: 0.8003

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 3.808570623397827
Linear Weight Rank: 10
Intra Cos: 0.5197626948356628
Inter Cos: 0.3257558345794678
Norm Quadratic Average: 13.803070068359375
Nearest Class Center Accuracy: 0.8046

Output Layer:
Intra Cos: 0.5439230799674988
Inter Cos: 0.37889716029167175
Norm Quadratic Average: 17.18270492553711
Nearest Class Center Accuracy: 0.8129

