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# meat_calssify_fresh_V_0_5_test

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 imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 2.7620
- Accuracy: 0.3333

## 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: 1
- eval_batch_size: 1
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 30

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.1661        | 1.0   | 44   | 1.1896          | 0.1667   |
| 1.032         | 2.0   | 88   | 1.2389          | 0.25     |
| 1.0784        | 3.0   | 132  | 1.0699          | 0.25     |
| 1.0819        | 4.0   | 176  | 1.2184          | 0.0833   |
| 1.0274        | 5.0   | 220  | 1.4634          | 0.0833   |
| 1.106         | 6.0   | 264  | 1.0843          | 0.4167   |
| 1.1051        | 7.0   | 308  | 1.1752          | 0.25     |
| 1.0964        | 8.0   | 352  | 1.3698          | 0.1667   |
| 1.1467        | 9.0   | 396  | 1.3023          | 0.1667   |
| 0.7936        | 10.0  | 440  | 1.4005          | 0.25     |
| 0.8262        | 11.0  | 484  | 1.2786          | 0.25     |
| 1.1219        | 12.0  | 528  | 1.4314          | 0.25     |
| 0.9306        | 13.0  | 572  | 1.9908          | 0.1667   |
| 1.2061        | 14.0  | 616  | 1.4193          | 0.25     |
| 0.7925        | 15.0  | 660  | 2.1698          | 0.25     |
| 0.104         | 16.0  | 704  | 2.2744          | 0.25     |
| 0.2619        | 17.0  | 748  | 1.7998          | 0.3333   |
| 0.3196        | 18.0  | 792  | 2.0410          | 0.3333   |
| 1.2972        | 19.0  | 836  | 1.4657          | 0.5      |
| 0.7459        | 20.0  | 880  | 2.4774          | 0.3333   |
| 0.4766        | 21.0  | 924  | 2.0181          | 0.3333   |
| 0.1264        | 22.0  | 968  | 2.6095          | 0.25     |
| 0.2541        | 23.0  | 1012 | 2.6884          | 0.1667   |
| 0.179         | 24.0  | 1056 | 2.6612          | 0.25     |
| 0.308         | 25.0  | 1100 | 1.5827          | 0.5      |
| 0.0291        | 26.0  | 1144 | 2.4500          | 0.3333   |
| 0.0773        | 27.0  | 1188 | 2.4238          | 0.4167   |
| 0.0235        | 28.0  | 1232 | 1.8948          | 0.5      |
| 0.1782        | 29.0  | 1276 | 1.7855          | 0.5      |
| 0.0597        | 30.0  | 1320 | 2.7620          | 0.3333   |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1

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