---
license: mit
base_model: google/vit-base-patch16-224-in21k
tags:
- generated_from_trainer
datasets:
- food101
model-index:
- name: Food-Image-Classification-VIT
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# Food-Image-Classification-VIT

This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on the food101 dataset.
It achieves the following results on the evaluation set:
- eval_loss: 1.0611
- eval_accuracy: 0.7274
- eval_runtime: 411.0682
- eval_samples_per_second: 61.425
- eval_steps_per_second: 7.68
- epoch: 0.15
- step: 718

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 0.0002
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4

### Framework versions

- Transformers 4.33.1
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3