Model save path: ./New_Models/bn_False_dataset_CIFAR100_epochs_200_lr_0.01_model_type_vgg11_rand_seed_265358_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: 0.022893192246556282
Inter Cos: 0.07011394202709198
Norm Quadratic Average: 29.326324462890625
Nearest Class Center Accuracy: 0.03258

Layer 1: Conv2d(64, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.034711550921201706
Inter Cos: 0.05962895601987839
Norm Quadratic Average: 34.94755935668945
Nearest Class Center Accuracy: 0.04452

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.042655397206544876
Inter Cos: 0.03807320073246956
Norm Quadratic Average: 43.65485763549805
Nearest Class Center Accuracy: 0.05198

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03633050620555878
Inter Cos: 0.037850625813007355
Norm Quadratic Average: 72.63728332519531
Nearest Class Center Accuracy: 0.06176

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03576118126511574
Inter Cos: 0.03242984414100647
Norm Quadratic Average: 46.18214416503906
Nearest Class Center Accuracy: 0.06992

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03524789959192276
Inter Cos: 0.031050892546772957
Norm Quadratic Average: 26.444913864135742
Nearest Class Center Accuracy: 0.07458

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.08198481053113937
Inter Cos: 0.05772443860769272
Norm Quadratic Average: 8.890833854675293
Nearest Class Center Accuracy: 0.08416

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.3860616087913513
Inter Cos: 0.22233593463897705
Norm Quadratic Average: 4.372030735015869
Nearest Class Center Accuracy: 0.09902

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 7.165520668029785
Linear Weight Rank: 4024
Intra Cos: 0.6759096384048462
Inter Cos: 0.35032424330711365
Norm Quadratic Average: 27.622488021850586
Nearest Class Center Accuracy: 0.1

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 7.139955997467041
Linear Weight Rank: 3591
Intra Cos: 0.694679319858551
Inter Cos: 0.3445185720920563
Norm Quadratic Average: 35.293941497802734
Nearest Class Center Accuracy: 0.1

Layer 10: Linear(in_features=4096, out_features=100, bias=True)
Linear Weight Norm: 7.235040187835693
Linear Weight Rank: 98
Intra Cos: 0.6932909488677979
Inter Cos: 0.3297649919986725
Norm Quadratic Average: 43.509010314941406
Nearest Class Center Accuracy: 0.1

Output Layer:
Intra Cos: 0.7264903783798218
Inter Cos: 0.37219756841659546
Norm Quadratic Average: 64.50859069824219
Nearest Class Center Accuracy: 0.1

Test Set:
Average Loss: 3.551969784927368
Accuracy: 0.4699
NC1 Within Class Collapse: nan
NC2 Equinorm: Features: 0.23761774599552155, Weights: 0.037040241062641144
NC2 Equiangle: Features: 0.23723852292455808, Weights: 0.12588398634785353
NC3 Self-Duality: 0.47092142701148987
NC4 NCC Mismatch: 0.25860000000000005

Layer 0: Conv2d(3, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.006621266715228558
Inter Cos: 0.4067547917366028
Norm Quadratic Average: 29.42218589782715
Nearest Class Center Accuracy: 0.1136

Layer 1: Conv2d(64, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.013803503476083279
Inter Cos: 0.2933667302131653
Norm Quadratic Average: 35.15332794189453
Nearest Class Center Accuracy: 0.2273

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.02144666388630867
Inter Cos: 0.3416285216808319
Norm Quadratic Average: 43.91556167602539
Nearest Class Center Accuracy: 0.2795

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.021615736186504364
Inter Cos: 0.31620827317237854
Norm Quadratic Average: 73.15503692626953
Nearest Class Center Accuracy: 0.3463

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.022497404366731644
Inter Cos: 0.2453424036502838
Norm Quadratic Average: 46.61479187011719
Nearest Class Center Accuracy: 0.4494

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.022968530654907227
Inter Cos: 0.1786879003047943
Norm Quadratic Average: 26.609376907348633
Nearest Class Center Accuracy: 0.5143

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03381825610995293
Inter Cos: 0.27192652225494385
Norm Quadratic Average: 8.862190246582031
Nearest Class Center Accuracy: 0.5078

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.10163235664367676
Inter Cos: 0.534535825252533
Norm Quadratic Average: 4.226064205169678
Nearest Class Center Accuracy: 0.5038

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 7.165520668029785
Linear Weight Rank: 4024
Intra Cos: 0.1359100639820099
Inter Cos: 0.6283641457557678
Norm Quadratic Average: 25.73406982421875
Nearest Class Center Accuracy: 0.4782

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 7.139955997467041
Linear Weight Rank: 3591
Intra Cos: 0.13871444761753082
Inter Cos: 0.6281942129135132
Norm Quadratic Average: 32.83597183227539
Nearest Class Center Accuracy: 0.4703

Layer 10: Linear(in_features=4096, out_features=100, bias=True)
Linear Weight Norm: 7.235040187835693
Linear Weight Rank: 98
Intra Cos: 0.14000824093818665
Inter Cos: 0.6198020577430725
Norm Quadratic Average: 40.75063705444336
Nearest Class Center Accuracy: 0.4656

Output Layer:
Intra Cos: 0.14691342413425446
Inter Cos: 0.6671342849731445
Norm Quadratic Average: 60.523983001708984
Nearest Class Center Accuracy: 0.4544

