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# vit-base-batch-32

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: 0.6201
- Accuracy: 0.8756

## 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: 0.0003
- train_batch_size: 32
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.6735        | 1.0   | 550  | 0.8003          | 0.7583   |
| 0.4048        | 2.0   | 1100 | 0.6471          | 0.8266   |
| 0.2506        | 3.0   | 1650 | 0.6220          | 0.8354   |
| 0.1521        | 4.0   | 2200 | 0.6406          | 0.8493   |
| 0.0812        | 5.0   | 2750 | 0.6855          | 0.8545   |
| 0.0279        | 6.0   | 3300 | 0.6767          | 0.8648   |
| 0.0094        | 7.0   | 3850 | 0.6252          | 0.8744   |
| 0.0074        | 8.0   | 4400 | 0.6064          | 0.8751   |
| 0.0056        | 9.0   | 4950 | 0.5997          | 0.8783   |
| 0.0016        | 10.0  | 5500 | 0.6009          | 0.8767   |


### Framework versions

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

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