keras-io/conv_Mixer
130
Tensorflow Keras implementation of : Image classification with ConvMixer
The full credit goes to: Sayak Paul
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
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:
Training Metrics
After 10 Epocs, the test accuracy of the model is 83.57%
## Model Plot
<details> <summary>View Model Plot</summary>
</details>
