Model save path: /content/drive/MyDrive/Neural Collapse/New_Models/bn_False_dataset_MNIST_epochs_50_lr_0.001_model_type_vgg11_weight_decay_0.001.pth.tar
Training Set:
Layer 0: Conv2d(1, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.08946062624454498
Inter Cos: 0.11311883479356766
Norm Quadratic Average: 23.53293800354004
Nearest Class Center Accuracy: 0.81175

Layer 1: Conv2d(64, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.10870521515607834
Inter Cos: 0.1323118656873703
Norm Quadratic Average: 47.129791259765625
Nearest Class Center Accuracy: 0.8255

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.1516142040491104
Inter Cos: 0.16927459836006165
Norm Quadratic Average: 45.95123291015625
Nearest Class Center Accuracy: 0.805875

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.17018361389636993
Inter Cos: 0.17768335342407227
Norm Quadratic Average: 60.04124069213867
Nearest Class Center Accuracy: 0.818875

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.18929830193519592
Inter Cos: 0.17019657790660858
Norm Quadratic Average: 38.66838455200195
Nearest Class Center Accuracy: 0.857625

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.21572478115558624
Inter Cos: 0.18977856636047363
Norm Quadratic Average: 37.82441711425781
Nearest Class Center Accuracy: 0.895625

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.2737634479999542
Inter Cos: 0.17957694828510284
Norm Quadratic Average: 22.202741622924805
Nearest Class Center Accuracy: 0.939625

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.3916773498058319
Inter Cos: 0.20086801052093506
Norm Quadratic Average: 17.170045852661133
Nearest Class Center Accuracy: 0.979875

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 98.29606628417969
Linear Weight Rank: 4031
Intra Cos: 0.6225204467773438
Inter Cos: 0.25225546956062317
Norm Quadratic Average: 74.38573455810547
Nearest Class Center Accuracy: 0.997125

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 39.73746109008789
Linear Weight Rank: 3670
Intra Cos: 0.7301210165023804
Inter Cos: 0.26141658425331116
Norm Quadratic Average: 46.617286682128906
Nearest Class Center Accuracy: 0.99925

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 2.4433677196502686
Linear Weight Rank: 10
Intra Cos: 0.7795801758766174
Inter Cos: 0.25784555077552795
Norm Quadratic Average: 35.083740234375
Nearest Class Center Accuracy: 0.9995

Output Layer:
Intra Cos: 0.8318659663200378
Inter Cos: 0.32132306694984436
Norm Quadratic Average: 24.384613037109375
Nearest Class Center Accuracy: 0.998875

Test Set:
Average Loss: 0.07980008679628373
Accuracy: 0.982
NC1 Within Class Collapse: 1.761393666267395
NC2 Equinorm: Features: 0.1026608943939209, Weights: 0.013735142536461353
NC2 Equiangle: Features: 0.2385317908393012, Weights: 0.09330967797173394
NC3 Self-Duality: 0.5567522048950195
NC4 NCC Mismatch: 0.012499999999999956

Layer 0: Conv2d(1, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.10133810341358185
Inter Cos: 0.11957789957523346
Norm Quadratic Average: 22.82430076599121
Nearest Class Center Accuracy: 0.809

Layer 1: Conv2d(64, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.1326712816953659
Inter Cos: 0.14430278539657593
Norm Quadratic Average: 46.00617980957031
Nearest Class Center Accuracy: 0.8175

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.17278841137886047
Inter Cos: 0.19754403829574585
Norm Quadratic Average: 44.770572662353516
Nearest Class Center Accuracy: 0.8015

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.18020138144493103
Inter Cos: 0.21700461208820343
Norm Quadratic Average: 58.408565521240234
Nearest Class Center Accuracy: 0.8165

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.1740480214357376
Inter Cos: 0.20559562742710114
Norm Quadratic Average: 37.66655731201172
Nearest Class Center Accuracy: 0.849

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.1953161358833313
Inter Cos: 0.22321905195713043
Norm Quadratic Average: 36.9300537109375
Nearest Class Center Accuracy: 0.886

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.25042057037353516
Inter Cos: 0.21078084409236908
Norm Quadratic Average: 21.698015213012695
Nearest Class Center Accuracy: 0.9345

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.3539440631866455
Inter Cos: 0.23977403342723846
Norm Quadratic Average: 16.66539192199707
Nearest Class Center Accuracy: 0.957

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 98.29606628417969
Linear Weight Rank: 4031
Intra Cos: 0.5623418092727661
Inter Cos: 0.27958083152770996
Norm Quadratic Average: 71.60444641113281
Nearest Class Center Accuracy: 0.975

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 39.73746109008789
Linear Weight Rank: 3670
Intra Cos: 0.6632267832756042
Inter Cos: 0.2761154770851135
Norm Quadratic Average: 44.773067474365234
Nearest Class Center Accuracy: 0.977

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 2.4433677196502686
Linear Weight Rank: 10
Intra Cos: 0.7086519002914429
Inter Cos: 0.2681644856929779
Norm Quadratic Average: 33.71513366699219
Nearest Class Center Accuracy: 0.976

Output Layer:
Intra Cos: 0.7539632320404053
Inter Cos: 0.3354061245918274
Norm Quadratic Average: 23.422225952148438
Nearest Class Center Accuracy: 0.975

