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_0.001.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: 0.024741586297750473
Inter Cos: 0.09856723994016647
Norm Quadratic Average: 25.93266487121582
Nearest Class Center Accuracy: 0.38652

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.031037788838148117
Inter Cos: 0.0984819307923317
Norm Quadratic Average: 24.603944778442383
Nearest Class Center Accuracy: 0.46706

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03161361441016197
Inter Cos: 0.080577552318573
Norm Quadratic Average: 30.479747772216797
Nearest Class Center Accuracy: 0.54032

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03100583143532276
Inter Cos: 0.06241276115179062
Norm Quadratic Average: 15.096060752868652
Nearest Class Center Accuracy: 0.63628

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.04697118327021599
Inter Cos: 0.06055564433336258
Norm Quadratic Average: 8.317411422729492
Nearest Class Center Accuracy: 0.71178

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.13952471315860748
Inter Cos: 0.17083622515201569
Norm Quadratic Average: 2.9458560943603516
Nearest Class Center Accuracy: 0.84482

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.5731355547904968
Inter Cos: 0.3264007568359375
Norm Quadratic Average: 1.6073920726776123
Nearest Class Center Accuracy: 0.99548

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 5.376183986663818
Linear Weight Rank: 4029
Intra Cos: 0.7677923440933228
Inter Cos: 0.29670265316963196
Norm Quadratic Average: 10.959186553955078
Nearest Class Center Accuracy: 0.9986

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 4.026432991027832
Linear Weight Rank: 3645
Intra Cos: 0.8314656615257263
Inter Cos: 0.22686538100242615
Norm Quadratic Average: 11.80382251739502
Nearest Class Center Accuracy: 0.99982

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 3.5662434101104736
Linear Weight Rank: 9
Intra Cos: 0.842380166053772
Inter Cos: 0.19837136566638947
Norm Quadratic Average: 13.005597114562988
Nearest Class Center Accuracy: 1.0

Output Layer:
Intra Cos: 0.8594565987586975
Inter Cos: 0.2705235481262207
Norm Quadratic Average: 15.99185848236084
Nearest Class Center Accuracy: 1.0

Test Set:
Average Loss: 0.8642660661697388
Accuracy: 0.8087
NC1 Within Class Collapse: 6.294705390930176
NC2 Equinorm: Features: 0.2058819681406021, Weights: 0.04020770266652107
NC2 Equiangle: Features: 0.21696459452311198, Weights: 0.07136747572157118
NC3 Self-Duality: 0.1539859175682068
NC4 NCC Mismatch: 0.04800000000000004

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: 0.02368849143385887
Inter Cos: 0.09928272664546967
Norm Quadratic Average: 25.91847801208496
Nearest Class Center Accuracy: 0.4

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.029454577714204788
Inter Cos: 0.10015058517456055
Norm Quadratic Average: 24.613054275512695
Nearest Class Center Accuracy: 0.4751

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.02938210591673851
Inter Cos: 0.08176054805517197
Norm Quadratic Average: 30.51003646850586
Nearest Class Center Accuracy: 0.5446

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.0277260709553957
Inter Cos: 0.06371986120939255
Norm Quadratic Average: 15.109996795654297
Nearest Class Center Accuracy: 0.6324

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.041118185967206955
Inter Cos: 0.061685945838689804
Norm Quadratic Average: 8.3141508102417
Nearest Class Center Accuracy: 0.682

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.11650700122117996
Inter Cos: 0.17134974896907806
Norm Quadratic Average: 2.9376602172851562
Nearest Class Center Accuracy: 0.7409

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.36671796441078186
Inter Cos: 0.33461010456085205
Norm Quadratic Average: 1.5772998332977295
Nearest Class Center Accuracy: 0.7978

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 5.376183986663818
Linear Weight Rank: 4029
Intra Cos: 0.4666096866130829
Inter Cos: 0.3678058087825775
Norm Quadratic Average: 10.633509635925293
Nearest Class Center Accuracy: 0.7994

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 4.026432991027832
Linear Weight Rank: 3645
Intra Cos: 0.4748987555503845
Inter Cos: 0.345476895570755
Norm Quadratic Average: 11.367701530456543
Nearest Class Center Accuracy: 0.8032

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 3.5662434101104736
Linear Weight Rank: 9
Intra Cos: 0.4561969041824341
Inter Cos: 0.3169635534286499
Norm Quadratic Average: 12.483119010925293
Nearest Class Center Accuracy: 0.8039

Output Layer:
Intra Cos: 0.4554458260536194
Inter Cos: 0.3169754445552826
Norm Quadratic Average: 15.307195663452148
Nearest Class Center Accuracy: 0.8058

