Model save path: ./New_Models/bn_True_dataset_CIFAR10_epochs_100_lr_0.001_model_type_vgg11_rand_seed_979323_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: 0.021450400352478027
Inter Cos: 0.11371058970689774
Norm Quadratic Average: 27.691617965698242
Nearest Class Center Accuracy: 0.279125

Layer 1: Conv2d(64, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.022888313978910446
Inter Cos: 0.0971338152885437
Norm Quadratic Average: 87.5204086303711
Nearest Class Center Accuracy: 0.349375

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.02558187022805214
Inter Cos: 0.09122328460216522
Norm Quadratic Average: 65.49518585205078
Nearest Class Center Accuracy: 0.378625

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.022431379184126854
Inter Cos: 0.0647473856806755
Norm Quadratic Average: 69.05130767822266
Nearest Class Center Accuracy: 0.408625

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.029978973791003227
Inter Cos: 0.07723286747932434
Norm Quadratic Average: 43.654300689697266
Nearest Class Center Accuracy: 0.4325

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.030230578035116196
Inter Cos: 0.06980069726705551
Norm Quadratic Average: 44.516849517822266
Nearest Class Center Accuracy: 0.47675

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.040025368332862854
Inter Cos: 0.07388747483491898
Norm Quadratic Average: 28.482315063476562
Nearest Class Center Accuracy: 0.563625

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.06196436285972595
Inter Cos: 0.07432807981967926
Norm Quadratic Average: 20.295494079589844
Nearest Class Center Accuracy: 0.8325

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 99.93429565429688
Linear Weight Rank: 4031
Intra Cos: 0.1788306087255478
Inter Cos: 0.09194841235876083
Norm Quadratic Average: 108.99853515625
Nearest Class Center Accuracy: 1.0

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 40.4006462097168
Linear Weight Rank: 3670
Intra Cos: 0.41514816880226135
Inter Cos: 0.17657554149627686
Norm Quadratic Average: 56.72290802001953
Nearest Class Center Accuracy: 1.0

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 2.5220487117767334
Linear Weight Rank: 10
Intra Cos: 0.6557937860488892
Inter Cos: 0.27052420377731323
Norm Quadratic Average: 39.471920013427734
Nearest Class Center Accuracy: 1.0

Output Layer:
Intra Cos: 0.8784511089324951
Inter Cos: 0.4299432635307312
Norm Quadratic Average: 27.405750274658203
Nearest Class Center Accuracy: 1.0

Test Set:
Average Loss: 2.686824043273926
Accuracy: 0.5815
NC1 Within Class Collapse: nan
NC2 Equinorm: Features: 0.21469047665596008, Weights: 0.01797262579202652
NC2 Equiangle: Features: 0.4285820855034722, Weights: 0.08913792504204644
NC3 Self-Duality: 0.6334069967269897
NC4 NCC Mismatch: 0.139

Layer 0: Conv2d(3, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.018480457365512848
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: 0.022276395931839943
Inter Cos: 0.0853068083524704
Norm Quadratic Average: 87.11956787109375
Nearest Class Center Accuracy: 0.3675

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.025210639461874962
Inter Cos: 0.080721914768219
Norm Quadratic Average: 65.14524841308594
Nearest Class Center Accuracy: 0.403

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.02121671847999096
Inter Cos: 0.056982602924108505
Norm Quadratic Average: 68.7950439453125
Nearest Class Center Accuracy: 0.4475

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.026017069816589355
Inter Cos: 0.0687175765633583
Norm Quadratic Average: 43.45854949951172
Nearest Class Center Accuracy: 0.453

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.02577512152493
Inter Cos: 0.061672285199165344
Norm Quadratic Average: 44.33864212036133
Nearest Class Center Accuracy: 0.496

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.029158180579543114
Inter Cos: 0.06569918990135193
Norm Quadratic Average: 28.299585342407227
Nearest Class Center Accuracy: 0.5165

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.033036068081855774
Inter Cos: 0.07157855480909348
Norm Quadratic Average: 20.085559844970703
Nearest Class Center Accuracy: 0.567

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 99.93429565429688
Linear Weight Rank: 4031
Intra Cos: 0.05593879148364067
Inter Cos: 0.10403625667095184
Norm Quadratic Average: 104.88355255126953
Nearest Class Center Accuracy: 0.6195

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 40.4006462097168
Linear Weight Rank: 3670
Intra Cos: 0.11196903884410858
Inter Cos: 0.19528910517692566
Norm Quadratic Average: 52.18052291870117
Nearest Class Center Accuracy: 0.589

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 2.5220487117767334
Linear Weight Rank: 10
Intra Cos: 0.1758616864681244
Inter Cos: 0.3063228726387024
Norm Quadratic Average: 34.87211608886719
Nearest Class Center Accuracy: 0.5765

Output Layer:
Intra Cos: 0.2671210765838623
Inter Cos: 0.4867551624774933
Norm Quadratic Average: 23.455883026123047
Nearest Class Center Accuracy: 0.5555

