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# meat_calssify_fresh_crop_fixed_overlap_epoch100_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: 0.2286
- Accuracy: 0.9315

## 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: 64
- 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: 100

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.0983        | 1.0   | 21   | 1.0790          | 0.4517   |
| 1.0782        | 2.0   | 42   | 1.0505          | 0.4891   |
| 1.0069        | 3.0   | 63   | 0.9886          | 0.5639   |
| 0.9347        | 4.0   | 84   | 0.9224          | 0.5794   |
| 0.8519        | 5.0   | 105  | 0.8643          | 0.6324   |
| 0.7989        | 6.0   | 126  | 0.7891          | 0.6667   |
| 0.695         | 7.0   | 147  | 0.8411          | 0.5919   |
| 0.6872        | 8.0   | 168  | 0.7448          | 0.6978   |
| 0.5872        | 9.0   | 189  | 0.7257          | 0.6854   |
| 0.6367        | 10.0  | 210  | 0.6716          | 0.7227   |
| 0.5617        | 11.0  | 231  | 0.6554          | 0.7321   |
| 0.5104        | 12.0  | 252  | 0.6906          | 0.7134   |
| 0.4581        | 13.0  | 273  | 0.6179          | 0.7601   |
| 0.5126        | 14.0  | 294  | 0.6726          | 0.7321   |
| 0.5078        | 15.0  | 315  | 0.5767          | 0.7819   |
| 0.3308        | 16.0  | 336  | 0.5843          | 0.7632   |
| 0.3396        | 17.0  | 357  | 0.5064          | 0.8287   |
| 0.3137        | 18.0  | 378  | 0.7024          | 0.7414   |
| 0.2981        | 19.0  | 399  | 0.4692          | 0.8411   |
| 0.2593        | 20.0  | 420  | 0.7424          | 0.7352   |
| 0.5048        | 21.0  | 441  | 0.4293          | 0.8411   |
| 0.2252        | 22.0  | 462  | 0.5090          | 0.7975   |
| 0.261         | 23.0  | 483  | 0.4810          | 0.8505   |
| 0.2575        | 24.0  | 504  | 0.4389          | 0.8442   |
| 0.176         | 25.0  | 525  | 0.4528          | 0.8287   |
| 0.2075        | 26.0  | 546  | 0.4764          | 0.8349   |
| 0.2069        | 27.0  | 567  | 0.5269          | 0.8162   |
| 0.2306        | 28.0  | 588  | 0.4180          | 0.8536   |
| 0.1564        | 29.0  | 609  | 0.3936          | 0.8505   |
| 0.1632        | 30.0  | 630  | 0.4111          | 0.8474   |
| 0.1923        | 31.0  | 651  | 0.3862          | 0.8629   |
| 0.1708        | 32.0  | 672  | 0.4155          | 0.8474   |
| 0.1744        | 33.0  | 693  | 0.4346          | 0.8505   |
| 0.1381        | 34.0  | 714  | 0.3908          | 0.8660   |
| 0.1668        | 35.0  | 735  | 0.5195          | 0.8255   |
| 0.146         | 36.0  | 756  | 0.4954          | 0.8255   |
| 0.1288        | 37.0  | 777  | 0.4273          | 0.8505   |
| 0.1595        | 38.0  | 798  | 0.3274          | 0.9034   |
| 0.107         | 39.0  | 819  | 0.4688          | 0.8380   |
| 0.1437        | 40.0  | 840  | 0.4269          | 0.8692   |
| 0.1432        | 41.0  | 861  | 0.5034          | 0.8224   |
| 0.1512        | 42.0  | 882  | 0.4046          | 0.8629   |
| 0.1156        | 43.0  | 903  | 0.3166          | 0.8941   |
| 0.1173        | 44.0  | 924  | 0.4023          | 0.8598   |
| 0.1366        | 45.0  | 945  | 0.3869          | 0.8692   |
| 0.1361        | 46.0  | 966  | 0.5182          | 0.8349   |
| 0.2102        | 47.0  | 987  | 0.5841          | 0.8069   |
| 0.1504        | 48.0  | 1008 | 0.4403          | 0.8598   |
| 0.1272        | 49.0  | 1029 | 0.3771          | 0.8754   |
| 0.113         | 50.0  | 1050 | 0.3809          | 0.8785   |
| 0.0884        | 51.0  | 1071 | 0.4446          | 0.8629   |
| 0.0951        | 52.0  | 1092 | 0.3689          | 0.8847   |
| 0.0822        | 53.0  | 1113 | 0.4412          | 0.8629   |
| 0.0999        | 54.0  | 1134 | 0.3758          | 0.8785   |
| 0.1321        | 55.0  | 1155 | 0.3982          | 0.8598   |
| 0.0877        | 56.0  | 1176 | 0.3068          | 0.9034   |
| 0.0736        | 57.0  | 1197 | 0.3981          | 0.8910   |
| 0.0903        | 58.0  | 1218 | 0.2888          | 0.8972   |
| 0.0842        | 59.0  | 1239 | 0.3552          | 0.8816   |
| 0.0911        | 60.0  | 1260 | 0.4368          | 0.8536   |
| 0.0847        | 61.0  | 1281 | 0.3188          | 0.9065   |
| 0.066         | 62.0  | 1302 | 0.3727          | 0.8910   |
| 0.059         | 63.0  | 1323 | 0.3373          | 0.8910   |
| 0.0755        | 64.0  | 1344 | 0.3241          | 0.9003   |
| 0.0598        | 65.0  | 1365 | 0.3641          | 0.9003   |
| 0.0561        | 66.0  | 1386 | 0.3889          | 0.8847   |
| 0.0796        | 67.0  | 1407 | 0.3633          | 0.9065   |
| 0.0736        | 68.0  | 1428 | 0.3682          | 0.8816   |
| 0.0723        | 69.0  | 1449 | 0.4165          | 0.8723   |
| 0.0625        | 70.0  | 1470 | 0.2747          | 0.9159   |
| 0.0714        | 71.0  | 1491 | 0.3374          | 0.8972   |
| 0.0723        | 72.0  | 1512 | 0.3534          | 0.9003   |
| 0.0551        | 73.0  | 1533 | 0.3764          | 0.8785   |
| 0.0417        | 74.0  | 1554 | 0.2348          | 0.9252   |
| 0.0513        | 75.0  | 1575 | 0.3214          | 0.9190   |
| 0.0534        | 76.0  | 1596 | 0.2440          | 0.9346   |
| 0.046         | 77.0  | 1617 | 0.3385          | 0.9159   |
| 0.0539        | 78.0  | 1638 | 0.3516          | 0.9003   |
| 0.055         | 79.0  | 1659 | 0.2836          | 0.9221   |
| 0.0686        | 80.0  | 1680 | 0.3542          | 0.8910   |
| 0.0589        | 81.0  | 1701 | 0.2077          | 0.9315   |
| 0.0505        | 82.0  | 1722 | 0.3094          | 0.9034   |
| 0.0332        | 83.0  | 1743 | 0.2678          | 0.9252   |
| 0.0504        | 84.0  | 1764 | 0.3099          | 0.9159   |
| 0.0523        | 85.0  | 1785 | 0.1953          | 0.9315   |
| 0.0291        | 86.0  | 1806 | 0.2377          | 0.9283   |
| 0.0499        | 87.0  | 1827 | 0.2891          | 0.9221   |
| 0.038         | 88.0  | 1848 | 0.2898          | 0.9159   |
| 0.0597        | 89.0  | 1869 | 0.2722          | 0.9190   |
| 0.0367        | 90.0  | 1890 | 0.3110          | 0.9221   |
| 0.0647        | 91.0  | 1911 | 0.2432          | 0.9346   |
| 0.0371        | 92.0  | 1932 | 0.2276          | 0.9377   |
| 0.0286        | 93.0  | 1953 | 0.2281          | 0.9346   |
| 0.0271        | 94.0  | 1974 | 0.2766          | 0.9221   |
| 0.0339        | 95.0  | 1995 | 0.2637          | 0.9283   |
| 0.0211        | 96.0  | 2016 | 0.2434          | 0.9315   |
| 0.0441        | 97.0  | 2037 | 0.3146          | 0.8941   |
| 0.0516        | 98.0  | 2058 | 0.2273          | 0.9439   |
| 0.0311        | 99.0  | 2079 | 0.2151          | 0.9377   |
| 0.0269        | 100.0 | 2100 | 0.2286          | 0.9315   |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.3.1
- Datasets 2.20.0
- Tokenizers 0.19.1

fresh1 fresh2 fresh3