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# meat_calssify_fresh_crop_fixed_V_0_2

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: 0.5986
- Accuracy: 0.7885

## 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: 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.0979        | 1.0   | 10   | 1.0867          | 0.3910   |
| 1.0723        | 2.0   | 20   | 1.0606          | 0.4487   |
| 1.0368        | 3.0   | 30   | 1.0202          | 0.4936   |
| 0.968         | 4.0   | 40   | 0.9396          | 0.5449   |
| 0.8927        | 5.0   | 50   | 0.8491          | 0.6410   |
| 0.8256        | 6.0   | 60   | 0.8543          | 0.6282   |
| 0.7477        | 7.0   | 70   | 0.8216          | 0.6410   |
| 0.6567        | 8.0   | 80   | 0.7805          | 0.6282   |
| 0.6121        | 9.0   | 90   | 0.7005          | 0.7308   |
| 0.6303        | 10.0  | 100  | 0.7170          | 0.6923   |
| 0.5335        | 11.0  | 110  | 0.7192          | 0.7051   |
| 0.5375        | 12.0  | 120  | 0.6438          | 0.7436   |
| 0.4651        | 13.0  | 130  | 0.7292          | 0.7115   |
| 0.5207        | 14.0  | 140  | 0.6449          | 0.7244   |
| 0.4692        | 15.0  | 150  | 0.6545          | 0.7244   |
| 0.4146        | 16.0  | 160  | 0.6789          | 0.7372   |
| 0.383         | 17.0  | 170  | 0.6214          | 0.7564   |
| 0.3612        | 18.0  | 180  | 0.6287          | 0.7372   |
| 0.3444        | 19.0  | 190  | 0.7465          | 0.6987   |
| 0.3562        | 20.0  | 200  | 0.6255          | 0.7756   |
| 0.3149        | 21.0  | 210  | 0.5088          | 0.8141   |
| 0.2883        | 22.0  | 220  | 0.6508          | 0.7179   |
| 0.2829        | 23.0  | 230  | 0.7362          | 0.7179   |
| 0.2713        | 24.0  | 240  | 0.5616          | 0.7692   |
| 0.2562        | 25.0  | 250  | 0.7014          | 0.7244   |
| 0.2819        | 26.0  | 260  | 0.6033          | 0.7628   |
| 0.2237        | 27.0  | 270  | 0.5719          | 0.7885   |
| 0.2486        | 28.0  | 280  | 0.7404          | 0.7179   |
| 0.2049        | 29.0  | 290  | 0.6897          | 0.75     |
| 0.2185        | 30.0  | 300  | 0.6415          | 0.7564   |
| 0.239         | 31.0  | 310  | 0.6182          | 0.7821   |
| 0.2315        | 32.0  | 320  | 0.7067          | 0.75     |
| 0.1775        | 33.0  | 330  | 0.6307          | 0.7628   |
| 0.1829        | 34.0  | 340  | 0.5605          | 0.8205   |
| 0.1712        | 35.0  | 350  | 0.6619          | 0.7692   |
| 0.1896        | 36.0  | 360  | 0.5419          | 0.7949   |
| 0.1961        | 37.0  | 370  | 0.6204          | 0.7885   |
| 0.1825        | 38.0  | 380  | 0.5401          | 0.8013   |
| 0.1986        | 39.0  | 390  | 0.5964          | 0.7821   |
| 0.1623        | 40.0  | 400  | 0.5319          | 0.8269   |
| 0.1356        | 41.0  | 410  | 0.6096          | 0.7821   |
| 0.1615        | 42.0  | 420  | 0.6163          | 0.7692   |
| 0.1515        | 43.0  | 430  | 0.5757          | 0.7821   |
| 0.1655        | 44.0  | 440  | 0.6040          | 0.7756   |
| 0.1353        | 45.0  | 450  | 0.6121          | 0.7564   |
| 0.1133        | 46.0  | 460  | 0.4764          | 0.8141   |
| 0.1073        | 47.0  | 470  | 0.6337          | 0.7821   |
| 0.1266        | 48.0  | 480  | 0.5615          | 0.8077   |
| 0.1156        | 49.0  | 490  | 0.5092          | 0.8205   |
| 0.1344        | 50.0  | 500  | 0.5986          | 0.7885   |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.3.1+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1

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