---
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: my_awesome_food_model
  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. -->

# my_awesome_food_model

This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 3.8640
- Accuracy: 0.573

## 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: 5e-05
- train_batch_size: 512
- eval_batch_size: 512
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 2048
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Accuracy | Validation Loss |
|:-------------:|:-----:|:----:|:--------:|:---------------:|
| No log        | 1.0   | 2    | 0.036    | 4.5210          |
| No log        | 2.0   | 4    | 0.278    | 4.4151          |
| No log        | 3.0   | 6    | 0.437    | 4.3629          |
| No log        | 4.0   | 8    | 4.2960   | 0.547           |
| 4.3122        | 5.0   | 10   | 4.1697   | 0.589           |
| 4.3122        | 6.0   | 12   | 4.0601   | 0.568           |
| 4.3122        | 7.0   | 14   | 3.9770   | 0.521           |
| 4.3122        | 8.0   | 16   | 3.9177   | 0.539           |
| 4.3122        | 9.0   | 18   | 3.8843   | 0.545           |
| 3.9792        | 10.0  | 20   | 3.8640   | 0.573           |


### Framework versions

- Transformers 4.37.0
- Pytorch 2.1.2+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1