---
library_name: transformers
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
- image-classification
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: finetuned-fake-food
  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. -->

# finetuned-fake-food

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 indian_food_images dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4855
- Accuracy: 0.8548

## 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: 3e-05
- train_batch_size: 4
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- num_epochs: 15
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.6061        | 1.0   | 176  | 0.5937          | 0.6855   |
| 0.481         | 2.0   | 352  | 0.5138          | 0.8226   |
| 0.5522        | 3.0   | 528  | 0.4973          | 0.8065   |
| 0.4092        | 4.0   | 704  | 0.5557          | 0.7903   |
| 0.4882        | 5.0   | 880  | 0.4998          | 0.7984   |
| 0.4442        | 6.0   | 1056 | 0.4647          | 0.8387   |
| 0.5749        | 7.0   | 1232 | 0.4464          | 0.8306   |
| 0.4529        | 8.0   | 1408 | 0.5366          | 0.8065   |
| 0.5287        | 9.0   | 1584 | 0.4633          | 0.8387   |
| 0.3821        | 10.0  | 1760 | 0.4983          | 0.8387   |
| 0.2409        | 11.0  | 1936 | 0.4855          | 0.8548   |
| 0.2025        | 12.0  | 2112 | 0.5102          | 0.8387   |
| 0.2045        | 13.0  | 2288 | 0.4942          | 0.8387   |
| 0.4097        | 14.0  | 2464 | 0.4954          | 0.8387   |
| 0.5798        | 15.0  | 2640 | 0.4941          | 0.8387   |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.19.1