Model save path: ./New_Models/bn_False_dataset_CIFAR10_epochs_200_lr_0.01_model_type_vgg11_rand_seed_265358_test_samples_None_train_samples_None_weight_decay_0.0001.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: 0.10477277636528015
Norm Quadratic Average: 27.59717559814453
Nearest Class Center Accuracy: 0.26968

Layer 1: Conv2d(64, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.022000771015882492
Inter Cos: 0.07869302481412888
Norm Quadratic Average: 32.39595413208008
Nearest Class Center Accuracy: 0.39568

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.02311161532998085
Inter Cos: 0.06753650307655334
Norm Quadratic Average: 29.854127883911133
Nearest Class Center Accuracy: 0.51852

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.021962737664580345
Inter Cos: 0.05426393821835518
Norm Quadratic Average: 35.51178741455078
Nearest Class Center Accuracy: 0.59956

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.027600979432463646
Inter Cos: 0.04629762843251228
Norm Quadratic Average: 19.10418701171875
Nearest Class Center Accuracy: 0.7013

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.0414934903383255
Inter Cos: 0.041065458208322525
Norm Quadratic Average: 13.573997497558594
Nearest Class Center Accuracy: 0.7734

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.12620285153388977
Inter Cos: 0.0809427797794342
Norm Quadratic Average: 5.916080474853516
Nearest Class Center Accuracy: 0.88026

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.40974414348602295
Inter Cos: 0.15032485127449036
Norm Quadratic Average: 3.9981603622436523
Nearest Class Center Accuracy: 0.97962

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 73.47350311279297
Linear Weight Rank: 4031
Intra Cos: 0.8399762511253357
Inter Cos: 0.14817188680171967
Norm Quadratic Average: 23.371623992919922
Nearest Class Center Accuracy: 0.99198

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 30.004737854003906
Linear Weight Rank: 3670
Intra Cos: 0.9057819843292236
Inter Cos: 0.06981872767210007
Norm Quadratic Average: 21.264266967773438
Nearest Class Center Accuracy: 0.99706

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 4.12932014465332
Linear Weight Rank: 10
Intra Cos: 0.9074280261993408
Inter Cos: 0.07049400359392166
Norm Quadratic Average: 20.8381404876709
Nearest Class Center Accuracy: 0.99946

Output Layer:
Intra Cos: 0.968032717704773
Inter Cos: 0.3429732918739319
Norm Quadratic Average: 24.179428100585938
Nearest Class Center Accuracy: 1.0

Test Set:
Average Loss: 1.2800604220718146
Accuracy: 0.8042
NC1 Within Class Collapse: 6.589637279510498
NC2 Equinorm: Features: 0.24749451875686646, Weights: 0.01455007866024971
NC2 Equiangle: Features: 0.13362295362684462, Weights: 0.1133111106024848
NC3 Self-Duality: 0.40450218319892883
NC4 NCC Mismatch: 0.10189999999999999

Layer 0: Conv2d(3, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.018526077270507812
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: 0.02038365602493286
Inter Cos: 0.07957623898983002
Norm Quadratic Average: 32.362369537353516
Nearest Class Center Accuracy: 0.4136

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.021676190197467804
Inter Cos: 0.06860624253749847
Norm Quadratic Average: 29.8615665435791
Nearest Class Center Accuracy: 0.5263

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.020289892330765724
Inter Cos: 0.05496791750192642
Norm Quadratic Average: 35.54656982421875
Nearest Class Center Accuracy: 0.599

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.024059996008872986
Inter Cos: 0.04756111279129982
Norm Quadratic Average: 19.107141494750977
Nearest Class Center Accuracy: 0.6681

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.034913793206214905
Inter Cos: 0.0431041456758976
Norm Quadratic Average: 13.525026321411133
Nearest Class Center Accuracy: 0.7037

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.09498289972543716
Inter Cos: 0.07846181094646454
Norm Quadratic Average: 5.838187217712402
Nearest Class Center Accuracy: 0.7305

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.23792842030525208
Inter Cos: 0.18432506918907166
Norm Quadratic Average: 3.8542351722717285
Nearest Class Center Accuracy: 0.7713

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 73.47350311279297
Linear Weight Rank: 4031
Intra Cos: 0.4735591411590576
Inter Cos: 0.289861261844635
Norm Quadratic Average: 21.799036026000977
Nearest Class Center Accuracy: 0.7712

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 30.004737854003906
Linear Weight Rank: 3670
Intra Cos: 0.5011582970619202
Inter Cos: 0.255491703748703
Norm Quadratic Average: 19.663612365722656
Nearest Class Center Accuracy: 0.772

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 4.12932014465332
Linear Weight Rank: 10
Intra Cos: 0.5008744597434998
Inter Cos: 0.2619696259498596
Norm Quadratic Average: 19.32514762878418
Nearest Class Center Accuracy: 0.7769

Output Layer:
Intra Cos: 0.5460594892501831
Inter Cos: 0.37270474433898926
Norm Quadratic Average: 22.076038360595703
Nearest Class Center Accuracy: 0.7935

