Model save path: ./New_Models/bn_True_dataset_CIFAR10_epochs_100_lr_0.001_model_type_vgg11_rand_seed_846264_weight_decay_0.001.pth.tar
Training Set:
Layer 0: Conv2d(3, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.021450398489832878
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: 0.02352805808186531
Inter Cos: 0.07493028044700623
Norm Quadratic Average: 84.48430633544922
Nearest Class Center Accuracy: 0.34375

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.030255034565925598
Inter Cos: 0.08355429023504257
Norm Quadratic Average: 63.24942398071289
Nearest Class Center Accuracy: 0.374875

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.025424879044294357
Inter Cos: 0.06717027723789215
Norm Quadratic Average: 66.13825988769531
Nearest Class Center Accuracy: 0.40375

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03564498946070671
Inter Cos: 0.08164960891008377
Norm Quadratic Average: 42.807159423828125
Nearest Class Center Accuracy: 0.425125

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03386729955673218
Inter Cos: 0.06544079631567001
Norm Quadratic Average: 43.46155548095703
Nearest Class Center Accuracy: 0.462125

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.04677903279662132
Inter Cos: 0.07984960824251175
Norm Quadratic Average: 27.812692642211914
Nearest Class Center Accuracy: 0.548125

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.06363072246313095
Inter Cos: 0.07520337402820587
Norm Quadratic Average: 19.535615921020508
Nearest Class Center Accuracy: 0.832625

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 96.64553833007812
Linear Weight Rank: 4031
Intra Cos: 0.18111316859722137
Inter Cos: 0.09876677393913269
Norm Quadratic Average: 104.79141235351562
Nearest Class Center Accuracy: 0.999875

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 39.069732666015625
Linear Weight Rank: 3671
Intra Cos: 0.40713903307914734
Inter Cos: 0.18935526907444
Norm Quadratic Average: 53.51374816894531
Nearest Class Center Accuracy: 1.0

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 2.443662643432617
Linear Weight Rank: 10
Intra Cos: 0.6351523995399475
Inter Cos: 0.29907864332199097
Norm Quadratic Average: 36.7637825012207
Nearest Class Center Accuracy: 1.0

Output Layer:
Intra Cos: 0.8611259460449219
Inter Cos: 0.5109343528747559
Norm Quadratic Average: 24.732295989990234
Nearest Class Center Accuracy: 1.0

Test Set:
Average Loss: 2.4215707168579104
Accuracy: 0.598
NC1 Within Class Collapse: nan
NC2 Equinorm: Features: 0.21094806492328644, Weights: 0.019464602693915367
NC2 Equiangle: Features: 0.4420401255289714, Weights: 0.08423036999172634
NC3 Self-Duality: 0.6300926804542542
NC4 NCC Mismatch: 0.14600000000000002

Layer 0: Conv2d(3, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.018480457365512848
Inter Cos: 0.09352367371320724
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: 0.0234073456376791
Inter Cos: 0.07035747915506363
Norm Quadratic Average: 84.26748657226562
Nearest Class Center Accuracy: 0.3615

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.029806086793541908
Inter Cos: 0.08061381429433823
Norm Quadratic Average: 63.09437561035156
Nearest Class Center Accuracy: 0.4045

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.024879304692149162
Inter Cos: 0.059696704149246216
Norm Quadratic Average: 66.01466369628906
Nearest Class Center Accuracy: 0.4375

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03287171572446823
Inter Cos: 0.08130062371492386
Norm Quadratic Average: 42.711666107177734
Nearest Class Center Accuracy: 0.4455

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03015206567943096
Inter Cos: 0.06313388049602509
Norm Quadratic Average: 43.35983657836914
Nearest Class Center Accuracy: 0.4715

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03609641641378403
Inter Cos: 0.07822789996862411
Norm Quadratic Average: 27.69644546508789
Nearest Class Center Accuracy: 0.483

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.0378037728369236
Inter Cos: 0.0697920098900795
Norm Quadratic Average: 19.354185104370117
Nearest Class Center Accuracy: 0.563

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 96.64553833007812
Linear Weight Rank: 4031
Intra Cos: 0.06506413221359253
Inter Cos: 0.1044086292386055
Norm Quadratic Average: 101.01110076904297
Nearest Class Center Accuracy: 0.616

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 39.069732666015625
Linear Weight Rank: 3671
Intra Cos: 0.12725310027599335
Inter Cos: 0.20290948450565338
Norm Quadratic Average: 49.456668853759766
Nearest Class Center Accuracy: 0.5915

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 2.443662643432617
Linear Weight Rank: 10
Intra Cos: 0.1934089958667755
Inter Cos: 0.320900559425354
Norm Quadratic Average: 32.77810287475586
Nearest Class Center Accuracy: 0.579

Output Layer:
Intra Cos: 0.2798433005809784
Inter Cos: 0.49893301725387573
Norm Quadratic Average: 21.49384117126465
Nearest Class Center Accuracy: 0.5645

