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# meat_calssify_fresh_crop_fixed_V_0_3

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: 1.6191
- Accuracy: 0.75

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 1.0921        | 1.0   | 621   | 1.0844          | 0.3654   |
| 1.0438        | 2.0   | 1242  | 1.1755          | 0.4423   |
| 1.1558        | 3.0   | 1863  | 1.0148          | 0.4487   |
| 1.1274        | 4.0   | 2484  | 1.0371          | 0.5705   |
| 1.1992        | 5.0   | 3105  | 1.0598          | 0.3718   |
| 1.2195        | 6.0   | 3726  | 1.3422          | 0.5256   |
| 1.2366        | 7.0   | 4347  | 1.8744          | 0.4359   |
| 1.1302        | 8.0   | 4968  | 1.4699          | 0.5705   |
| 1.1137        | 9.0   | 5589  | 1.3480          | 0.6154   |
| 0.9534        | 10.0  | 6210  | 1.4723          | 0.5769   |
| 1.0269        | 11.0  | 6831  | 1.0999          | 0.6538   |
| 1.0545        | 12.0  | 7452  | 1.2980          | 0.6090   |
| 0.8669        | 13.0  | 8073  | 1.3408          | 0.6731   |
| 0.9571        | 14.0  | 8694  | 1.4879          | 0.6474   |
| 0.8345        | 15.0  | 9315  | 1.4030          | 0.6603   |
| 0.6623        | 16.0  | 9936  | 1.0840          | 0.7308   |
| 0.6014        | 17.0  | 10557 | 1.5054          | 0.7115   |
| 0.5599        | 18.0  | 11178 | 1.1956          | 0.7628   |
| 0.7209        | 19.0  | 11799 | 1.9734          | 0.5962   |
| 0.6289        | 20.0  | 12420 | 1.6165          | 0.6923   |
| 0.429         | 21.0  | 13041 | 1.5766          | 0.6987   |
| 0.628         | 22.0  | 13662 | 1.3948          | 0.7179   |
| 0.5427        | 23.0  | 14283 | 1.7663          | 0.6795   |
| 0.3806        | 24.0  | 14904 | 1.6219          | 0.6987   |
| 0.4443        | 25.0  | 15525 | 1.5065          | 0.7051   |
| 0.3648        | 26.0  | 16146 | 1.5225          | 0.7308   |
| 0.3812        | 27.0  | 16767 | 1.3488          | 0.75     |
| 0.3106        | 28.0  | 17388 | 1.7758          | 0.6987   |
| 0.3725        | 29.0  | 18009 | 1.4190          | 0.7372   |
| 0.4284        | 30.0  | 18630 | 1.6205          | 0.7115   |
| 0.2257        | 31.0  | 19251 | 1.5535          | 0.7628   |
| 0.2869        | 32.0  | 19872 | 1.2077          | 0.8013   |
| 0.3128        | 33.0  | 20493 | 1.9065          | 0.7051   |
| 0.2802        | 34.0  | 21114 | 1.2794          | 0.7885   |
| 0.2647        | 35.0  | 21735 | 1.5823          | 0.7436   |
| 0.3054        | 36.0  | 22356 | 1.3412          | 0.7756   |
| 0.2619        | 37.0  | 22977 | 1.4471          | 0.7308   |
| 0.2289        | 38.0  | 23598 | 1.8176          | 0.7244   |
| 0.1554        | 39.0  | 24219 | 1.5014          | 0.7628   |
| 0.1794        | 40.0  | 24840 | 1.4112          | 0.7628   |
| 0.1835        | 41.0  | 25461 | 1.8688          | 0.7244   |
| 0.2177        | 42.0  | 26082 | 1.2748          | 0.7821   |
| 0.1063        | 43.0  | 26703 | 1.4471          | 0.7628   |
| 0.1798        | 44.0  | 27324 | 1.1872          | 0.7949   |
| 0.1511        | 45.0  | 27945 | 1.3028          | 0.8077   |
| 0.1659        | 46.0  | 28566 | 1.7257          | 0.7308   |
| 0.0917        | 47.0  | 29187 | 1.2314          | 0.8205   |
| 0.1554        | 48.0  | 29808 | 1.4090          | 0.7821   |
| 0.0927        | 49.0  | 30429 | 1.0295          | 0.8397   |
| 0.1188        | 50.0  | 31050 | 1.6191          | 0.75     |


### Framework versions

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

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