TensorFlow implementation of "MLP-Mixer: An all-MLP Architecture for Vision"
The MLP-Mixer architecture [1].
| Indicator | Value |
|---|---|
| Accuracy | 0.97860 |
| Precision | 0.97882 |
| Recall | 0.97808 |
| F1-Score | 0.97829 |
Confusion Matrix
[[ 968 0 0 0 2 0 3 0 4 3]
[ 0 1127 0 1 1 0 2 1 3 0]
[ 3 0 1002 6 6 0 1 5 9 0]
[ 1 0 2 993 0 0 0 2 10 2]
[ 0 1 0 0 974 0 3 0 1 3]
[ 3 0 0 17 4 839 9 2 12 6]
[ 4 2 0 0 10 0 940 0 2 0]
[ 0 3 4 4 5 0 0 1005 3 4]
[ 0 0 3 1 5 0 1 3 956 5]
[ 1 3 0 3 14 1 0 4 1 982]]
Class-0 | Precision: 0.98776, Recall: 0.98776, F1-Score: 0.98776
Class-1 | Precision: 0.99208, Recall: 0.99295, F1-Score: 0.99251
Class-2 | Precision: 0.99110, Recall: 0.97093, F1-Score: 0.98091
Class-3 | Precision: 0.96878, Recall: 0.98317, F1-Score: 0.97592
Class-4 | Precision: 0.95397, Recall: 0.99185, F1-Score: 0.97254
Class-5 | Precision: 0.99881, Recall: 0.94058, F1-Score: 0.96882
Class-6 | Precision: 0.98019, Recall: 0.98121, F1-Score: 0.98070
Class-7 | Precision: 0.98337, Recall: 0.97763, F1-Score: 0.98049
Class-8 | Precision: 0.95504, Recall: 0.98152, F1-Score: 0.96810
Class-9 | Precision: 0.97711, Recall: 0.97324, F1-Score: 0.97517
Total | Accuracy: 0.97860, Precision: 0.97882, Recall: 0.97808, F1-Score: 0.97829
- Tensorflow 2.4.0
- whiteboxlayer 0.2.8
[1] Tolstikhin, Ilya O., et al. "Mlp-mixer: An all-mlp architecture for vision." Advances in Neural Information Processing Systems 34 (2021).
React
Typescript
Django
Laravel
Facebook
Microsoft
Google
Alibaba
D3
Tencent