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# beans_ViT

This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.2997
- Accuracy: 0.7969
- F1: 0.7991

## 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: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 30

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| No log        | 1.0   | 17   | 0.8693          | 0.6090   | 0.5953 |
| No log        | 2.0   | 34   | 0.9652          | 0.6015   | 0.5977 |
| No log        | 3.0   | 51   | 0.7178          | 0.6992   | 0.6927 |
| No log        | 4.0   | 68   | 0.7488          | 0.6992   | 0.6955 |
| No log        | 5.0   | 85   | 0.6517          | 0.7068   | 0.7070 |
| No log        | 6.0   | 102  | 0.7816          | 0.6842   | 0.6541 |
| No log        | 7.0   | 119  | 0.5014          | 0.7744   | 0.7733 |
| No log        | 8.0   | 136  | 0.5321          | 0.7669   | 0.7680 |
| No log        | 9.0   | 153  | 0.5985          | 0.7444   | 0.7457 |
| No log        | 10.0  | 170  | 0.4675          | 0.8271   | 0.8274 |
| No log        | 11.0  | 187  | 0.5750          | 0.7744   | 0.7576 |
| No log        | 12.0  | 204  | 0.6617          | 0.7293   | 0.7066 |
| No log        | 13.0  | 221  | 0.6396          | 0.7594   | 0.7577 |
| No log        | 14.0  | 238  | 0.4302          | 0.8346   | 0.8352 |
| No log        | 15.0  | 255  | 0.4018          | 0.8421   | 0.8427 |
| No log        | 16.0  | 272  | 0.5673          | 0.7895   | 0.7883 |
| No log        | 17.0  | 289  | 0.5037          | 0.8120   | 0.8097 |
| No log        | 18.0  | 306  | 0.5939          | 0.8496   | 0.8487 |
| No log        | 19.0  | 323  | 0.6590          | 0.8120   | 0.8111 |
| No log        | 20.0  | 340  | 0.6060          | 0.8571   | 0.8559 |
| No log        | 21.0  | 357  | 0.5806          | 0.8421   | 0.8418 |
| No log        | 22.0  | 374  | 0.6180          | 0.8421   | 0.8414 |
| No log        | 23.0  | 391  | 0.7707          | 0.7669   | 0.7633 |
| No log        | 24.0  | 408  | 0.5440          | 0.8421   | 0.8418 |
| No log        | 25.0  | 425  | 0.6596          | 0.8496   | 0.8497 |
| No log        | 26.0  | 442  | 0.5393          | 0.8346   | 0.8342 |
| No log        | 27.0  | 459  | 0.6320          | 0.8797   | 0.8795 |
| No log        | 28.0  | 476  | 0.5903          | 0.8496   | 0.8507 |
| No log        | 29.0  | 493  | 0.6826          | 0.8647   | 0.8644 |
| 0.3346        | 30.0  | 510  | 0.6493          | 0.8571   | 0.8567 |


### Framework versions

- Transformers 4.47.0
- Pytorch 2.5.1+cu121
- Datasets 3.3.1
- Tokenizers 0.21.0

label_0 label_1 label_2