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# meat_calssify_fresh_crop_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: 0.6201
- Accuracy: 0.7677

## 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: 100
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.1071        | 1.0   | 7    | 1.1020          | 0.3032   |
| 1.0846        | 2.0   | 14   | 1.0824          | 0.4323   |
| 1.0559        | 3.0   | 21   | 1.0499          | 0.4774   |
| 1.0098        | 4.0   | 28   | 1.0008          | 0.4903   |
| 0.9522        | 5.0   | 35   | 0.9723          | 0.5097   |
| 0.9491        | 6.0   | 42   | 0.9122          | 0.6065   |
| 0.8659        | 7.0   | 49   | 0.9418          | 0.5290   |
| 0.8838        | 8.0   | 56   | 0.8785          | 0.5871   |
| 0.856         | 9.0   | 63   | 0.8893          | 0.5548   |
| 0.7896        | 10.0  | 70   | 0.8382          | 0.6129   |
| 0.7409        | 11.0  | 77   | 0.7915          | 0.6839   |
| 0.6992        | 12.0  | 84   | 0.8152          | 0.6581   |
| 0.6652        | 13.0  | 91   | 0.8571          | 0.6194   |
| 0.6149        | 14.0  | 98   | 0.7757          | 0.6452   |
| 0.6121        | 15.0  | 105  | 0.7275          | 0.7097   |
| 0.5469        | 16.0  | 112  | 0.7461          | 0.6968   |
| 0.4911        | 17.0  | 119  | 0.7415          | 0.7032   |
| 0.4495        | 18.0  | 126  | 0.8020          | 0.6774   |
| 0.4634        | 19.0  | 133  | 0.7726          | 0.6452   |
| 0.4244        | 20.0  | 140  | 0.7531          | 0.6645   |
| 0.4263        | 21.0  | 147  | 0.6650          | 0.7226   |
| 0.3785        | 22.0  | 154  | 0.6666          | 0.7032   |
| 0.3922        | 23.0  | 161  | 0.7982          | 0.6774   |
| 0.3366        | 24.0  | 168  | 0.8043          | 0.6710   |
| 0.3169        | 25.0  | 175  | 0.6897          | 0.7355   |
| 0.3292        | 26.0  | 182  | 0.7959          | 0.6774   |
| 0.2988        | 27.0  | 189  | 0.7386          | 0.7161   |
| 0.2965        | 28.0  | 196  | 0.8410          | 0.6581   |
| 0.3015        | 29.0  | 203  | 0.8074          | 0.6581   |
| 0.2373        | 30.0  | 210  | 0.6866          | 0.7484   |
| 0.2659        | 31.0  | 217  | 0.6660          | 0.7613   |
| 0.2421        | 32.0  | 224  | 0.7252          | 0.6968   |
| 0.2386        | 33.0  | 231  | 0.7942          | 0.6645   |
| 0.2526        | 34.0  | 238  | 0.7830          | 0.6774   |
| 0.2117        | 35.0  | 245  | 0.6239          | 0.7613   |
| 0.2409        | 36.0  | 252  | 0.6610          | 0.7484   |
| 0.2263        | 37.0  | 259  | 0.6636          | 0.7871   |
| 0.2105        | 38.0  | 266  | 0.7461          | 0.7548   |
| 0.1881        | 39.0  | 273  | 0.7684          | 0.6774   |
| 0.194         | 40.0  | 280  | 0.7719          | 0.7032   |
| 0.1734        | 41.0  | 287  | 0.7544          | 0.7226   |
| 0.1913        | 42.0  | 294  | 0.7721          | 0.7032   |
| 0.1863        | 43.0  | 301  | 0.7524          | 0.7097   |
| 0.1747        | 44.0  | 308  | 0.8238          | 0.7032   |
| 0.1871        | 45.0  | 315  | 0.6709          | 0.7613   |
| 0.2191        | 46.0  | 322  | 0.6103          | 0.7484   |
| 0.1634        | 47.0  | 329  | 0.6160          | 0.7806   |
| 0.1717        | 48.0  | 336  | 0.6423          | 0.7419   |
| 0.1868        | 49.0  | 343  | 0.6767          | 0.7484   |
| 0.2183        | 50.0  | 350  | 0.6201          | 0.7677   |


### Framework versions

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

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