
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# meat_calssify_fresh_no_crop_V_0_1

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: 1.5082
- Accuracy: 0.7273

## 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: 50

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.1032        | 1.0   | 44   | 1.0785          | 0.3636   |
| 1.0983        | 2.0   | 88   | 1.1069          | 0.2727   |
| 1.1025        | 3.0   | 132  | 1.0854          | 0.4545   |
| 1.1036        | 4.0   | 176  | 1.1205          | 0.3636   |
| 1.16          | 5.0   | 220  | 1.0577          | 0.4545   |
| 1.0902        | 6.0   | 264  | 1.1767          | 0.2727   |
| 1.0789        | 7.0   | 308  | 1.2790          | 0.4545   |
| 1.1269        | 8.0   | 352  | 1.1196          | 0.4545   |
| 1.1132        | 9.0   | 396  | 1.1290          | 0.3636   |
| 1.092         | 10.0  | 440  | 1.2584          | 0.2727   |
| 0.988         | 11.0  | 484  | 0.9824          | 0.4545   |
| 0.9695        | 12.0  | 528  | 1.3389          | 0.2727   |
| 0.9343        | 13.0  | 572  | 1.2876          | 0.3636   |
| 0.8517        | 14.0  | 616  | 1.1018          | 0.4545   |
| 0.7473        | 15.0  | 660  | 1.2833          | 0.4545   |
| 0.7194        | 16.0  | 704  | 1.5489          | 0.4545   |
| 0.5832        | 17.0  | 748  | 1.2821          | 0.5455   |
| 0.4905        | 18.0  | 792  | 0.9996          | 0.7273   |
| 0.3587        | 19.0  | 836  | 1.1785          | 0.6364   |
| 0.178         | 20.0  | 880  | 1.3718          | 0.5455   |
| 0.1253        | 21.0  | 924  | 2.1013          | 0.4545   |
| 0.5536        | 22.0  | 968  | 1.4723          | 0.5455   |
| 0.5241        | 23.0  | 1012 | 1.6866          | 0.6364   |
| 0.2453        | 24.0  | 1056 | 1.6747          | 0.5455   |
| 0.1193        | 25.0  | 1100 | 1.3248          | 0.7273   |
| 0.0892        | 26.0  | 1144 | 2.3257          | 0.4545   |
| 0.3273        | 27.0  | 1188 | 1.8027          | 0.5455   |
| 0.3587        | 28.0  | 1232 | 2.1175          | 0.3636   |
| 0.1693        | 29.0  | 1276 | 0.8854          | 0.7273   |
| 0.2323        | 30.0  | 1320 | 1.5909          | 0.6364   |
| 0.1056        | 31.0  | 1364 | 1.5556          | 0.6364   |
| 0.0158        | 32.0  | 1408 | 1.8192          | 0.6364   |
| 0.2085        | 33.0  | 1452 | 2.1498          | 0.5455   |
| 0.1137        | 34.0  | 1496 | 1.8617          | 0.4545   |
| 0.287         | 35.0  | 1540 | 1.5198          | 0.5455   |
| 0.25          | 36.0  | 1584 | 2.1324          | 0.4545   |
| 0.0135        | 37.0  | 1628 | 2.1540          | 0.4545   |
| 0.1104        | 38.0  | 1672 | 2.2697          | 0.5455   |
| 0.2252        | 39.0  | 1716 | 2.5110          | 0.4545   |
| 0.0584        | 40.0  | 1760 | 2.6245          | 0.3636   |
| 0.2366        | 41.0  | 1804 | 2.2701          | 0.5455   |
| 0.089         | 42.0  | 1848 | 2.3318          | 0.5455   |
| 0.1237        | 43.0  | 1892 | 2.2786          | 0.5455   |
| 0.0121        | 44.0  | 1936 | 1.2596          | 0.6364   |
| 0.1234        | 45.0  | 1980 | 1.2882          | 0.7273   |
| 0.0116        | 46.0  | 2024 | 1.4629          | 0.7273   |
| 0.0508        | 47.0  | 2068 | 1.8392          | 0.6364   |
| 0.0221        | 48.0  | 2112 | 1.7354          | 0.6364   |
| 0.3441        | 49.0  | 2156 | 2.0862          | 0.5455   |
| 0.138         | 50.0  | 2200 | 1.5082          | 0.7273   |


### Framework versions

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

fresh1 fresh2 fresh3