### Model Card
- Model Name: Food Type Image Detection Vision Transformer
- Original Model: Vision Transformer (ViT) model pre-trained on ImageNet-21k (14 million images, 21,843 classes) at resolution 224x224. 
    - It was introduced in the paper [An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale](https://arxiv.org/abs/2010.11929) by Dosovitskiy et al. and first released in [this repository](https://github.com/google-research/vision_transformer).
    - Images are presented to the model as a sequence of fixed-size patches (resolution 16x16), which are linearly embedded. 
    - Does not provide any fine-tuned heads, as these were zero'd by Google researchers.
- Model Type: Image Classification
- Model Architecture: Vision Transformer (ViT)
- Fine-tuning: 
    - Fine-tuned on Food Image Classification Dataset by using 12 varieties of these 35 varieties
    - Optimizer: AdamW
    - Epochs: 20
- Model Performance: Achieved an accuracy of 96.23% on all of the kinds of Food Image Classification Dataset
  
crispy chicken burger chole_bhature chai chicken_curry cheesecake baked potato apple_pie dal_makhani butter_naan dhokla chapati