Model save path: ./New_Models/bn_False_dataset_CIFAR10_epochs_100_lr_0.001_model_type_vgg11_rand_seed_265358_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: 0.021450400352478027
Inter Cos: 0.11371058970689774
Norm Quadratic Average: 27.691621780395508
Nearest Class Center Accuracy: 0.279125

Layer 1: Conv2d(64, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.026203405112028122
Inter Cos: 0.10432646423578262
Norm Quadratic Average: 30.77794647216797
Nearest Class Center Accuracy: 0.311375

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03553472459316254
Inter Cos: 0.11678510159254074
Norm Quadratic Average: 23.603025436401367
Nearest Class Center Accuracy: 0.359125

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03986921161413193
Inter Cos: 0.10964033752679825
Norm Quadratic Average: 27.20699691772461
Nearest Class Center Accuracy: 0.40875

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.05564264953136444
Inter Cos: 0.13202697038650513
Norm Quadratic Average: 17.01872444152832
Nearest Class Center Accuracy: 0.44075

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.06875671446323395
Inter Cos: 0.1374727487564087
Norm Quadratic Average: 15.687963485717773
Nearest Class Center Accuracy: 0.466875

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.09106167405843735
Inter Cos: 0.15031559765338898
Norm Quadratic Average: 8.822400093078613
Nearest Class Center Accuracy: 0.505125

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.12245826423168182
Inter Cos: 0.16125358641147614
Norm Quadratic Average: 6.545487403869629
Nearest Class Center Accuracy: 0.67375

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 96.66246795654297
Linear Weight Rank: 4031
Intra Cos: 0.3227756917476654
Inter Cos: 0.28782546520233154
Norm Quadratic Average: 26.462247848510742
Nearest Class Center Accuracy: 0.959125

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 39.128631591796875
Linear Weight Rank: 3671
Intra Cos: 0.613880455493927
Inter Cos: 0.44249415397644043
Norm Quadratic Average: 23.274810791015625
Nearest Class Center Accuracy: 0.999

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 3.2351982593536377
Linear Weight Rank: 10
Intra Cos: 0.7553520202636719
Inter Cos: 0.5526667833328247
Norm Quadratic Average: 27.674774169921875
Nearest Class Center Accuracy: 0.999625

Output Layer:
Intra Cos: 0.8320227861404419
Inter Cos: 0.7189580202102661
Norm Quadratic Average: 34.50240707397461
Nearest Class Center Accuracy: 0.99825

Test Set:
Average Loss: 2.9352886962890623
Accuracy: 0.596
NC1 Within Class Collapse: nan
NC2 Equinorm: Features: 0.23675130307674408, Weights: 0.040229570120573044
NC2 Equiangle: Features: 0.43213280571831597, Weights: 0.1728412734137641
NC3 Self-Duality: 0.4449530839920044
NC4 NCC Mismatch: 0.14800000000000002

Layer 0: Conv2d(3, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.018480459228157997
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: 0.025151986628770828
Inter Cos: 0.09560898691415787
Norm Quadratic Average: 30.66863441467285
Nearest Class Center Accuracy: 0.332

Layer 2: Conv2d(128, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.03713837265968323
Inter Cos: 0.11293596774339676
Norm Quadratic Average: 23.525009155273438
Nearest Class Center Accuracy: 0.375

Layer 3: Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.04070044681429863
Inter Cos: 0.10370592772960663
Norm Quadratic Average: 27.1385555267334
Nearest Class Center Accuracy: 0.4285

Layer 4: Conv2d(256, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.05412838235497475
Inter Cos: 0.11783832311630249
Norm Quadratic Average: 16.95527458190918
Nearest Class Center Accuracy: 0.458

Layer 5: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.06525104492902756
Inter Cos: 0.12510442733764648
Norm Quadratic Average: 15.64112377166748
Nearest Class Center Accuracy: 0.4705

Layer 6: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.07937857508659363
Inter Cos: 0.13794240355491638
Norm Quadratic Average: 8.786970138549805
Nearest Class Center Accuracy: 0.475

Layer 7: Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
Intra Cos: 0.08964662253856659
Inter Cos: 0.14708805084228516
Norm Quadratic Average: 6.48996114730835
Nearest Class Center Accuracy: 0.5175

Layer 8: Linear(in_features=25088, out_features=4096, bias=True)
Linear Weight Norm: 96.66246795654297
Linear Weight Rank: 4031
Intra Cos: 0.1501723974943161
Inter Cos: 0.2462095022201538
Norm Quadratic Average: 25.513385772705078
Nearest Class Center Accuracy: 0.5875

Layer 9: Linear(in_features=4096, out_features=4096, bias=True)
Linear Weight Norm: 39.128631591796875
Linear Weight Rank: 3671
Intra Cos: 0.2324509620666504
Inter Cos: 0.37238946557044983
Norm Quadratic Average: 21.791196823120117
Nearest Class Center Accuracy: 0.59

Layer 10: Linear(in_features=4096, out_features=10, bias=True)
Linear Weight Norm: 3.2351982593536377
Linear Weight Rank: 10
Intra Cos: 0.2673202157020569
Inter Cos: 0.46179884672164917
Norm Quadratic Average: 25.688875198364258
Nearest Class Center Accuracy: 0.581

Output Layer:
Intra Cos: 0.30058425664901733
Inter Cos: 0.5861826539039612
Norm Quadratic Average: 31.87212371826172
Nearest Class Center Accuracy: 0.562

