Model save path: ./New_Models/bn_False_dataset_CIFAR10_epochs_100_lr_0.001_model_type_vgg11_rand_seed_979323_weight_decay_0.005.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: 0.025370735675096512
Inter Cos: 0.10881674289703369
Norm Quadratic Average: 29.246566772460938
Nearest Class Center Accuracy: 0.313875

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.02823314629495144
Inter Cos: 0.11137424409389496
Norm Quadratic Average: 23.321151733398438
Nearest Class Center Accuracy: 0.374625

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.036288656294345856
Inter Cos: 0.11767999082803726
Norm Quadratic Average: 26.48919105529785
Nearest Class Center Accuracy: 0.417625

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.056822020560503006
Inter Cos: 0.151973694562912
Norm Quadratic Average: 15.8677396774292
Nearest Class Center Accuracy: 0.44575

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.07300037145614624
Inter Cos: 0.16484707593917847
Norm Quadratic Average: 12.921453475952148
Nearest Class Center Accuracy: 0.473875

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.09604918956756592
Inter Cos: 0.1754305213689804
Norm Quadratic Average: 6.333334445953369
Nearest Class Center Accuracy: 0.522375

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.14119043946266174
Inter Cos: 0.1941695362329483
Norm Quadratic Average: 4.213858127593994
Nearest Class Center Accuracy: 0.706375

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 79.79069519042969
Linear Weight Rank: 4031
Intra Cos: 0.40181154012680054
Inter Cos: 0.3217296898365021
Norm Quadratic Average: 17.316991806030273
Nearest Class Center Accuracy: 0.96475

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 32.32957077026367
Linear Weight Rank: 3670
Intra Cos: 0.6742978096008301
Inter Cos: 0.47330042719841003
Norm Quadratic Average: 16.638652801513672
Nearest Class Center Accuracy: 0.9985

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 3.108750581741333
Linear Weight Rank: 10
Intra Cos: 0.7442367076873779
Inter Cos: 0.5572384595870972
Norm Quadratic Average: 20.335765838623047
Nearest Class Center Accuracy: 0.998875

Output Layer:
Intra Cos: 0.7919473052024841
Inter Cos: 0.6768806576728821
Norm Quadratic Average: 26.017444610595703
Nearest Class Center Accuracy: 0.995375

Test Set:
Average Loss: 2.255607498168945
Accuracy: 0.5985
NC1 Within Class Collapse: nan
NC2 Equinorm: Features: 0.25561222434043884, Weights: 0.049398329108953476
NC2 Equiangle: Features: 0.42650358412000866, Weights: 0.19898079766167534
NC3 Self-Duality: 0.3843685984611511
NC4 NCC Mismatch: 0.14500000000000002

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: 0.025324203073978424
Inter Cos: 0.09212593734264374
Norm Quadratic Average: 29.05044937133789
Nearest Class Center Accuracy: 0.3315

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.029785146936774254
Inter Cos: 0.09695441275835037
Norm Quadratic Average: 23.17386817932129
Nearest Class Center Accuracy: 0.3905

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.036355093121528625
Inter Cos: 0.10422064363956451
Norm Quadratic Average: 26.373510360717773
Nearest Class Center Accuracy: 0.445

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.05317392200231552
Inter Cos: 0.13451772928237915
Norm Quadratic Average: 15.801875114440918
Nearest Class Center Accuracy: 0.4645

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.06524469703435898
Inter Cos: 0.1445668488740921
Norm Quadratic Average: 12.88491439819336
Nearest Class Center Accuracy: 0.4795

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.07783806324005127
Inter Cos: 0.15120303630828857
Norm Quadratic Average: 6.302907466888428
Nearest Class Center Accuracy: 0.4865

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.09432036429643631
Inter Cos: 0.16375625133514404
Norm Quadratic Average: 4.172881126403809
Nearest Class Center Accuracy: 0.534

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 79.79069519042969
Linear Weight Rank: 4031
Intra Cos: 0.16889852285385132
Inter Cos: 0.2871105372905731
Norm Quadratic Average: 16.627971649169922
Nearest Class Center Accuracy: 0.6035

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 32.32957077026367
Linear Weight Rank: 3670
Intra Cos: 0.23710469901561737
Inter Cos: 0.4112013280391693
Norm Quadratic Average: 15.572010040283203
Nearest Class Center Accuracy: 0.5965

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 3.108750581741333
Linear Weight Rank: 10
Intra Cos: 0.24897193908691406
Inter Cos: 0.48342984914779663
Norm Quadratic Average: 18.915010452270508
Nearest Class Center Accuracy: 0.591

Output Layer:
Intra Cos: 0.26899415254592896
Inter Cos: 0.580803632736206
Norm Quadratic Average: 24.081899642944336
Nearest Class Center Accuracy: 0.5635

