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# vit-base-image-classification-yenthienviet

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 image-classification-yenthienviet dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2380
- Accuracy: 0.9344

## 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: 0.0002
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.6118        | 0.56  | 100  | 0.4854          | 0.8616   |
| 0.329         | 1.11  | 200  | 0.4473          | 0.8616   |
| 0.3002        | 1.67  | 300  | 0.4167          | 0.8637   |
| 0.1549        | 2.22  | 400  | 0.2911          | 0.9178   |
| 0.1993        | 2.78  | 500  | 0.2934          | 0.9168   |
| 0.1071        | 3.33  | 600  | 0.2389          | 0.9324   |
| 0.1027        | 3.89  | 700  | 0.2380          | 0.9344   |


### Framework versions

- Transformers 4.34.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.14.1

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