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# meat_calssify_fresh_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: 1.5238
- Accuracy: 0.7742

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.9291        | 1.0   | 617   | 1.0099          | 0.5613   |
| 1.0473        | 2.0   | 1234  | 1.2180          | 0.4323   |
| 0.7998        | 3.0   | 1851  | 1.0517          | 0.5548   |
| 1.21          | 4.0   | 2468  | 1.3208          | 0.4968   |
| 1.0814        | 5.0   | 3085  | 1.3423          | 0.5290   |
| 1.4674        | 6.0   | 3702  | 1.5941          | 0.5419   |
| 0.0633        | 7.0   | 4319  | 1.6778          | 0.5548   |
| 0.8345        | 8.0   | 4936  | 1.4949          | 0.5419   |
| 1.6888        | 9.0   | 5553  | 1.6784          | 0.4581   |
| 1.0997        | 10.0  | 6170  | 1.9437          | 0.5097   |
| 1.6235        | 11.0  | 6787  | 1.0796          | 0.6194   |
| 1.3159        | 12.0  | 7404  | 1.7363          | 0.5935   |
| 0.5513        | 13.0  | 8021  | 1.6918          | 0.6387   |
| 0.4463        | 14.0  | 8638  | 1.8225          | 0.5742   |
| 0.0455        | 15.0  | 9255  | 1.6463          | 0.6258   |
| 0.5906        | 16.0  | 9872  | 2.0199          | 0.6065   |
| 0.6373        | 17.0  | 10489 | 1.7233          | 0.6516   |
| 1.0226        | 18.0  | 11106 | 1.4137          | 0.6710   |
| 1.0566        | 19.0  | 11723 | 1.3841          | 0.7097   |
| 0.3117        | 20.0  | 12340 | 1.9925          | 0.6258   |
| 0.3041        | 21.0  | 12957 | 1.6802          | 0.6710   |
| 1.0978        | 22.0  | 13574 | 1.8269          | 0.6323   |
| 1.0631        | 23.0  | 14191 | 1.7333          | 0.6645   |
| 0.0039        | 24.0  | 14808 | 1.8621          | 0.6645   |
| 0.0018        | 25.0  | 15425 | 2.1279          | 0.6258   |
| 0.2373        | 26.0  | 16042 | 1.6896          | 0.7032   |
| 0.5993        | 27.0  | 16659 | 1.8411          | 0.6710   |
| 0.0021        | 28.0  | 17276 | 1.9047          | 0.6645   |
| 0.0401        | 29.0  | 17893 | 1.7597          | 0.7226   |
| 0.3687        | 30.0  | 18510 | 2.2599          | 0.6387   |
| 0.2841        | 31.0  | 19127 | 2.0735          | 0.6581   |
| 0.5707        | 32.0  | 19744 | 1.9316          | 0.6581   |
| 0.46          | 33.0  | 20361 | 2.1935          | 0.6452   |
| 0.7589        | 34.0  | 20978 | 1.5770          | 0.7355   |
| 0.0008        | 35.0  | 21595 | 1.7779          | 0.7226   |
| 0.0005        | 36.0  | 22212 | 2.0994          | 0.6774   |
| 0.0114        | 37.0  | 22829 | 1.7210          | 0.7161   |
| 0.4071        | 38.0  | 23446 | 2.2015          | 0.6839   |
| 0.0007        | 39.0  | 24063 | 1.8165          | 0.7161   |
| 0.0005        | 40.0  | 24680 | 1.8461          | 0.7032   |
| 0.0005        | 41.0  | 25297 | 1.9554          | 0.7032   |
| 0.7269        | 42.0  | 25914 | 1.6843          | 0.7355   |
| 0.0008        | 43.0  | 26531 | 1.9346          | 0.7032   |
| 0.5102        | 44.0  | 27148 | 1.7949          | 0.7161   |
| 1.1679        | 45.0  | 27765 | 1.7431          | 0.7484   |
| 0.151         | 46.0  | 28382 | 1.7899          | 0.7355   |
| 0.0004        | 47.0  | 28999 | 1.5098          | 0.7548   |
| 0.0003        | 48.0  | 29616 | 1.7388          | 0.7419   |
| 0.0003        | 49.0  | 30233 | 1.5232          | 0.7677   |
| 0.0003        | 50.0  | 30850 | 1.5238          | 0.7742   |


### Framework versions

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

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