readme: ---
  library_name: keras
  tags:
  - image-classification
  - Architecture
  ---
  
  # Tensorflow Keras implementation of : [Image classification with ConvMixer](https://keras.io/examples/vision/convmixer/)
  
  The full credit goes to: [Sayak Paul](https://twitter.com/RisingSayak)
  
  ## Short description:
  
  ConvMixer is a simple model based on the ideas of representing an image as patches( used in ViT) and separating the mixing of Spatial and channel dimensions (used in MLP-Mixer). Unlike ViT and MLP-Mixer, they use only standard Convolution operations. The full paper is a submission to ICLR 22 and can be found [here](https://openreview.net/pdf?id=TVHS5Y4dNvM)
  
  ## Model and Dataset used
  
  The Dataset used here is CIFAR-10. The model is called ConvMixer-256/8 where 256 is the hidden dimension (the dimension of patches) and 8 is the depth(number of repetitions of ConvMix layers)
  
  ## Training procedure
  
  ### Training hyperparameters
  
  The following hyperparameters were used during training:
  
  | Hyperparameters | Value |
  | :-- | :-- |
  | name | AdamW |
  | learning_rate | 0.0010000000474974513 |
  | decay | 0.0 |
  | beta_1 | 0.8999999761581421 |
  | beta_2 | 0.9990000128746033 |
  | epsilon | 1e-07 |
  | amsgrad | False |
  | weight_decay | 9.999999747378752e-05 |
  | exclude_from_weight_decay | None |
  | training_precision | float32 |
  
  ## Training Metrics
  After 10 Epocs, the test accuracy of the model is 83.57%
  
   ## Model Plot
  
  <details>
  <summary>View Model Plot</summary>
  
  ![Model Image](./model.png)
  
  </details>