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# vit_cub

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 CUB-200-2011 dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0122
- Accuracy: 0.7447

## 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: 40
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.2462        | 0.33  | 100  | 1.0099          | 0.7573   |
| 0.3515        | 0.67  | 200  | 0.9446          | 0.7740   |
| 0.2781        | 1.0   | 300  | 0.9761          | 0.7473   |
| 0.2071        | 1.33  | 400  | 1.0055          | 0.7431   |
| 0.223         | 1.67  | 500  | 0.9942          | 0.7531   |
| 0.1899        | 2.0   | 600  | 1.0806          | 0.7331   |
| 0.1568        | 2.33  | 700  | 1.1502          | 0.7156   |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2

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