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# meat_calssify_fresh_crop_V_0_4

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: 1.3588
- Accuracy: 0.7935

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 1.0748        | 1.0   | 617   | 0.9992          | 0.5290   |
| 1.0075        | 2.0   | 1234  | 1.1657          | 0.4774   |
| 1.1387        | 3.0   | 1851  | 1.7110          | 0.3355   |
| 1.2272        | 4.0   | 2468  | 1.0090          | 0.5032   |
| 1.1872        | 5.0   | 3085  | 1.0040          | 0.5871   |
| 1.1936        | 6.0   | 3702  | 1.4017          | 0.5484   |
| 1.1596        | 7.0   | 4319  | 1.2642          | 0.5935   |
| 1.1932        | 8.0   | 4936  | 1.5967          | 0.5161   |
| 1.1215        | 9.0   | 5553  | 1.4047          | 0.6194   |
| 1.097         | 10.0  | 6170  | 1.2934          | 0.5806   |
| 1.0044        | 11.0  | 6787  | 1.3448          | 0.6323   |
| 0.8965        | 12.0  | 7404  | 1.3799          | 0.6645   |
| 0.9943        | 13.0  | 8021  | 1.3963          | 0.6581   |
| 0.9558        | 14.0  | 8638  | 1.7787          | 0.5742   |
| 0.8692        | 15.0  | 9255  | 1.4618          | 0.6516   |
| 0.8126        | 16.0  | 9872  | 1.2486          | 0.7097   |
| 0.8093        | 17.0  | 10489 | 1.1204          | 0.7226   |
| 0.6681        | 18.0  | 11106 | 1.7933          | 0.6452   |
| 0.5894        | 19.0  | 11723 | 1.2285          | 0.7355   |
| 0.4993        | 20.0  | 12340 | 1.7193          | 0.6516   |
| 0.4736        | 21.0  | 12957 | 1.7766          | 0.6774   |
| 0.4952        | 22.0  | 13574 | 1.8535          | 0.6516   |
| 0.5312        | 23.0  | 14191 | 1.7282          | 0.6774   |
| 0.3942        | 24.0  | 14808 | 1.9881          | 0.6516   |
| 0.4166        | 25.0  | 15425 | 1.6196          | 0.6903   |
| 0.4656        | 26.0  | 16042 | 1.6721          | 0.6774   |
| 0.326         | 27.0  | 16659 | 2.1897          | 0.6387   |
| 0.3692        | 28.0  | 17276 | 1.6734          | 0.6968   |
| 0.3956        | 29.0  | 17893 | 1.6272          | 0.7290   |
| 0.3108        | 30.0  | 18510 | 1.6487          | 0.7548   |
| 0.2318        | 31.0  | 19127 | 1.8501          | 0.6968   |
| 0.3835        | 32.0  | 19744 | 1.7877          | 0.6774   |
| 0.3779        | 33.0  | 20361 | 1.4747          | 0.7355   |
| 0.2913        | 34.0  | 20978 | 1.6122          | 0.7355   |
| 0.275         | 35.0  | 21595 | 1.9130          | 0.6839   |
| 0.2483        | 36.0  | 22212 | 1.9305          | 0.6839   |
| 0.2389        | 37.0  | 22829 | 1.5973          | 0.7419   |
| 0.3375        | 38.0  | 23446 | 1.2684          | 0.7742   |
| 0.1867        | 39.0  | 24063 | 1.7777          | 0.7484   |
| 0.2066        | 40.0  | 24680 | 1.5134          | 0.7613   |
| 0.2555        | 41.0  | 25297 | 1.9315          | 0.6839   |
| 0.1508        | 42.0  | 25914 | 1.6165          | 0.7484   |
| 0.1262        | 43.0  | 26531 | 1.8465          | 0.7290   |
| 0.1113        | 44.0  | 27148 | 2.0645          | 0.7161   |
| 0.1692        | 45.0  | 27765 | 1.7539          | 0.7484   |
| 0.0973        | 46.0  | 28382 | 2.0104          | 0.7161   |
| 0.166         | 47.0  | 28999 | 1.6435          | 0.7742   |
| 0.1476        | 48.0  | 29616 | 1.6865          | 0.7677   |
| 0.1616        | 49.0  | 30233 | 2.1759          | 0.6903   |
| 0.1715        | 50.0  | 30850 | 1.3588          | 0.7935   |


### Framework versions

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

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