Model save path: ./New_Models/bn_False_dataset_CIFAR10_epochs_100_lr_0.001_model_type_vgg11_rand_seed_979323_weight_decay_0.03.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: 0.02577107958495617
Inter Cos: 0.11669053137302399
Norm Quadratic Average: 13.264433860778809
Nearest Class Center Accuracy: 0.32825

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.029075641185045242
Inter Cos: 0.14121918380260468
Norm Quadratic Average: 5.884910583496094
Nearest Class Center Accuracy: 0.388875

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.06127060949802399
Inter Cos: 0.21539947390556335
Norm Quadratic Average: 6.112661361694336
Nearest Class Center Accuracy: 0.39675

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.10109225660562515
Inter Cos: 0.2892366349697113
Norm Quadratic Average: 5.513246059417725
Nearest Class Center Accuracy: 0.380875

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.15323905646800995
Inter Cos: 0.3776369094848633
Norm Quadratic Average: 6.482503890991211
Nearest Class Center Accuracy: 0.374

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.21490900218486786
Inter Cos: 0.4621932804584503
Norm Quadratic Average: 5.405825138092041
Nearest Class Center Accuracy: 0.38125

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.25806793570518494
Inter Cos: 0.5156237483024597
Norm Quadratic Average: 4.147649765014648
Nearest Class Center Accuracy: 0.405625

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 23.994722366333008
Linear Weight Rank: 4031
Intra Cos: 0.2684222459793091
Inter Cos: 0.5574430227279663
Norm Quadratic Average: 17.93816566467285
Nearest Class Center Accuracy: 0.42775

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 9.790544509887695
Linear Weight Rank: 3670
Intra Cos: 0.28125494718551636
Inter Cos: 0.5958327054977417
Norm Quadratic Average: 11.557083129882812
Nearest Class Center Accuracy: 0.43625

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 1.5794804096221924
Linear Weight Rank: 10
Intra Cos: 0.3069736659526825
Inter Cos: 0.6343593597412109
Norm Quadratic Average: 7.789731979370117
Nearest Class Center Accuracy: 0.433125

Output Layer:
Intra Cos: 0.3468528687953949
Inter Cos: 0.7089486718177795
Norm Quadratic Average: 6.154027462005615
Nearest Class Center Accuracy: 0.411

Test Set:
Average Loss: 1.466523765563965
Accuracy: 0.435
NC1 Within Class Collapse: nan
NC2 Equinorm: Features: 0.254238486289978, Weights: 0.09936133027076721
NC2 Equiangle: Features: 0.7381089952256944, Weights: 0.276123407151964
NC3 Self-Duality: 0.42438381910324097
NC4 NCC Mismatch: 0.261

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: 0.028174972161650658
Inter Cos: 0.10014934837818146
Norm Quadratic Average: 13.159579277038574
Nearest Class Center Accuracy: 0.3465

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.030487025156617165
Inter Cos: 0.12428893893957138
Norm Quadratic Average: 5.815860748291016
Nearest Class Center Accuracy: 0.404

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.05721209943294525
Inter Cos: 0.19817112386226654
Norm Quadratic Average: 6.045958518981934
Nearest Class Center Accuracy: 0.4125

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.08739800751209259
Inter Cos: 0.2789212763309479
Norm Quadratic Average: 5.463327884674072
Nearest Class Center Accuracy: 0.3865

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.13267244398593903
Inter Cos: 0.37266266345977783
Norm Quadratic Average: 6.437503814697266
Nearest Class Center Accuracy: 0.378

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.18342530727386475
Inter Cos: 0.46348243951797485
Norm Quadratic Average: 5.376642227172852
Nearest Class Center Accuracy: 0.376

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.2298518270254135
Inter Cos: 0.5207662582397461
Norm Quadratic Average: 4.128329753875732
Nearest Class Center Accuracy: 0.397

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 23.994722366333008
Linear Weight Rank: 4031
Intra Cos: 0.2679143249988556
Inter Cos: 0.5671024322509766
Norm Quadratic Average: 17.897863388061523
Nearest Class Center Accuracy: 0.4145

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 9.790544509887695
Linear Weight Rank: 3670
Intra Cos: 0.2960997521877289
Inter Cos: 0.608815610408783
Norm Quadratic Average: 11.563556671142578
Nearest Class Center Accuracy: 0.423

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 1.5794804096221924
Linear Weight Rank: 10
Intra Cos: 0.3298637866973877
Inter Cos: 0.6523921489715576
Norm Quadratic Average: 7.8141679763793945
Nearest Class Center Accuracy: 0.415

Output Layer:
Intra Cos: 0.3943212330341339
Inter Cos: 0.736937940120697
Norm Quadratic Average: 6.192973613739014
Nearest Class Center Accuracy: 0.4015

