---
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
- image-classification
- vision
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: food101-vit-base-patch16-224-in21k
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# food101-vit-base-patch16-224-in21k

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:
- Loss: 0.3853
- Accuracy: 0.908

## 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: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 1337
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10.0

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.8312        | 1.0   | 9469  | 0.6893          | 0.8576   |
| 0.6401        | 2.0   | 18938 | 0.4571          | 0.8784   |
| 0.7021        | 3.0   | 28407 | 0.4081          | 0.8905   |
| 0.8365        | 4.0   | 37876 | 0.3962          | 0.8946   |
| 0.3562        | 5.0   | 47345 | 0.3932          | 0.8954   |
| 0.3552        | 6.0   | 56814 | 0.3876          | 0.9004   |
| 0.3962        | 7.0   | 66283 | 0.3854          | 0.9049   |
| 0.4242        | 8.0   | 75752 | 0.3865          | 0.9066   |
| 0.2785        | 9.0   | 85221 | 0.3867          | 0.9070   |
| 0.3446        | 10.0  | 94690 | 0.3853          | 0.908    |


### Framework versions

- Transformers 4.38.0
- Pytorch 2.1.2+cu118
- Datasets 2.19.1
- Tokenizers 0.15.2