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# vit-base-1e-4-20ep

This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) on the vuongnhathien/30VNFoods dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4034
- Accuracy: 0.8873

## 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: 0.0001
- train_batch_size: 64
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.5376        | 1.0   | 275  | 0.4677          | 0.8640   |
| 0.2085        | 2.0   | 550  | 0.4375          | 0.8811   |
| 0.0755        | 3.0   | 825  | 0.4605          | 0.8899   |
| 0.0429        | 4.0   | 1100 | 0.4784          | 0.8879   |
| 0.0146        | 5.0   | 1375 | 0.5386          | 0.8799   |
| 0.0176        | 6.0   | 1650 | 0.5524          | 0.8803   |
| 0.0137        | 7.0   | 1925 | 0.5249          | 0.8887   |
| 0.0076        | 8.0   | 2200 | 0.5401          | 0.8942   |
| 0.0026        | 9.0   | 2475 | 0.5477          | 0.8934   |
| 0.0054        | 10.0  | 2750 | 0.5417          | 0.8946   |
| 0.0034        | 11.0  | 3025 | 0.5430          | 0.8974   |
| 0.0033        | 12.0  | 3300 | 0.5443          | 0.8954   |
| 0.0027        | 13.0  | 3575 | 0.5423          | 0.8986   |
| 0.0024        | 14.0  | 3850 | 0.5434          | 0.8990   |
| 0.0027        | 15.0  | 4125 | 0.5483          | 0.8962   |
| 0.0027        | 16.0  | 4400 | 0.5485          | 0.8998   |
| 0.0019        | 17.0  | 4675 | 0.5502          | 0.8998   |
| 0.0022        | 18.0  | 4950 | 0.5508          | 0.8998   |
| 0.0015        | 19.0  | 5225 | 0.5509          | 0.9002   |
| 0.002         | 20.0  | 5500 | 0.5510          | 0.9010   |


### Framework versions

- Transformers 4.39.3
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.15.2

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