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# meat_calssify_fresh_crop_fixed_overlap_epoch100_V_0_9

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: 0.1854
- Accuracy: 0.9439

## 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: 100

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.101         | 1.0   | 21   | 1.0776          | 0.4206   |
| 1.0459        | 2.0   | 42   | 1.0368          | 0.5109   |
| 0.9957        | 3.0   | 63   | 0.9830          | 0.5296   |
| 0.9613        | 4.0   | 84   | 0.8994          | 0.5857   |
| 0.9072        | 5.0   | 105  | 0.8663          | 0.6231   |
| 0.8397        | 6.0   | 126  | 0.7738          | 0.7196   |
| 0.7726        | 7.0   | 147  | 0.7461          | 0.6978   |
| 0.7757        | 8.0   | 168  | 0.7647          | 0.6636   |
| 0.6253        | 9.0   | 189  | 0.6437          | 0.7445   |
| 0.5671        | 10.0  | 210  | 0.6791          | 0.7072   |
| 0.529         | 11.0  | 231  | 0.6623          | 0.7072   |
| 0.4362        | 12.0  | 252  | 0.5876          | 0.7508   |
| 0.552         | 13.0  | 273  | 0.5093          | 0.7913   |
| 0.3779        | 14.0  | 294  | 0.7716          | 0.6573   |
| 0.5052        | 15.0  | 315  | 0.7956          | 0.6791   |
| 0.5263        | 16.0  | 336  | 0.6077          | 0.7445   |
| 0.3712        | 17.0  | 357  | 0.4699          | 0.8474   |
| 0.2958        | 18.0  | 378  | 0.5815          | 0.7819   |
| 0.2775        | 19.0  | 399  | 0.5083          | 0.8100   |
| 0.2467        | 20.0  | 420  | 0.4561          | 0.8162   |
| 0.2541        | 21.0  | 441  | 0.4463          | 0.8380   |
| 0.2689        | 22.0  | 462  | 0.5149          | 0.7944   |
| 0.1893        | 23.0  | 483  | 0.4155          | 0.8567   |
| 0.2263        | 24.0  | 504  | 0.7202          | 0.7601   |
| 0.2646        | 25.0  | 525  | 0.4365          | 0.8162   |
| 0.2416        | 26.0  | 546  | 0.3365          | 0.8816   |
| 0.1788        | 27.0  | 567  | 0.3679          | 0.8723   |
| 0.1947        | 28.0  | 588  | 0.3725          | 0.8660   |
| 0.1802        | 29.0  | 609  | 0.4176          | 0.8567   |
| 0.1695        | 30.0  | 630  | 0.3776          | 0.8692   |
| 0.2089        | 31.0  | 651  | 0.3047          | 0.8785   |
| 0.1727        | 32.0  | 672  | 0.3225          | 0.8754   |
| 0.143         | 33.0  | 693  | 0.2355          | 0.9128   |
| 0.1593        | 34.0  | 714  | 0.3424          | 0.8847   |
| 0.1179        | 35.0  | 735  | 0.2873          | 0.9065   |
| 0.1227        | 36.0  | 756  | 0.3114          | 0.8941   |
| 0.1636        | 37.0  | 777  | 0.4101          | 0.8660   |
| 0.1347        | 38.0  | 798  | 0.2253          | 0.9190   |
| 0.1108        | 39.0  | 819  | 0.3387          | 0.8847   |
| 0.1383        | 40.0  | 840  | 0.4024          | 0.8754   |
| 0.1173        | 41.0  | 861  | 0.2436          | 0.9034   |
| 0.1027        | 42.0  | 882  | 0.2603          | 0.9065   |
| 0.1244        | 43.0  | 903  | 0.2990          | 0.9128   |
| 0.1061        | 44.0  | 924  | 0.3082          | 0.9065   |
| 0.1179        | 45.0  | 945  | 0.2212          | 0.9128   |
| 0.0945        | 46.0  | 966  | 0.3455          | 0.8816   |
| 0.1055        | 47.0  | 987  | 0.2951          | 0.8847   |
| 0.0895        | 48.0  | 1008 | 0.3003          | 0.9065   |
| 0.1298        | 49.0  | 1029 | 0.3123          | 0.9097   |
| 0.1379        | 50.0  | 1050 | 0.2787          | 0.9128   |
| 0.0879        | 51.0  | 1071 | 0.2920          | 0.9128   |
| 0.1011        | 52.0  | 1092 | 0.3667          | 0.8816   |
| 0.1038        | 53.0  | 1113 | 0.2967          | 0.9034   |
| 0.0834        | 54.0  | 1134 | 0.2281          | 0.9346   |
| 0.0998        | 55.0  | 1155 | 0.2835          | 0.8941   |
| 0.0794        | 56.0  | 1176 | 0.2260          | 0.9221   |
| 0.0732        | 57.0  | 1197 | 0.3309          | 0.9003   |
| 0.0612        | 58.0  | 1218 | 0.3392          | 0.9065   |
| 0.0679        | 59.0  | 1239 | 0.2728          | 0.9252   |
| 0.0986        | 60.0  | 1260 | 0.2380          | 0.9221   |
| 0.0639        | 61.0  | 1281 | 0.2672          | 0.9221   |
| 0.061         | 62.0  | 1302 | 0.2898          | 0.9221   |
| 0.0741        | 63.0  | 1323 | 0.3098          | 0.9097   |
| 0.0532        | 64.0  | 1344 | 0.2621          | 0.9252   |
| 0.0642        | 65.0  | 1365 | 0.1643          | 0.9377   |
| 0.0762        | 66.0  | 1386 | 0.2332          | 0.9346   |
| 0.0562        | 67.0  | 1407 | 0.2603          | 0.9252   |
| 0.0481        | 68.0  | 1428 | 0.2363          | 0.9097   |
| 0.0576        | 69.0  | 1449 | 0.2421          | 0.9377   |
| 0.0355        | 70.0  | 1470 | 0.2040          | 0.9346   |
| 0.07          | 71.0  | 1491 | 0.2900          | 0.9283   |
| 0.0631        | 72.0  | 1512 | 0.2531          | 0.9221   |
| 0.046         | 73.0  | 1533 | 0.2054          | 0.9346   |
| 0.0767        | 74.0  | 1554 | 0.1651          | 0.9408   |
| 0.0569        | 75.0  | 1575 | 0.2251          | 0.9377   |
| 0.0454        | 76.0  | 1596 | 0.2003          | 0.9408   |
| 0.0596        | 77.0  | 1617 | 0.1607          | 0.9564   |
| 0.0602        | 78.0  | 1638 | 0.1789          | 0.9408   |
| 0.0512        | 79.0  | 1659 | 0.2390          | 0.9221   |
| 0.0402        | 80.0  | 1680 | 0.1433          | 0.9564   |
| 0.0425        | 81.0  | 1701 | 0.1379          | 0.9502   |
| 0.0428        | 82.0  | 1722 | 0.1422          | 0.9564   |
| 0.0353        | 83.0  | 1743 | 0.1433          | 0.9502   |
| 0.0449        | 84.0  | 1764 | 0.2206          | 0.9190   |
| 0.0402        | 85.0  | 1785 | 0.2194          | 0.9470   |
| 0.041         | 86.0  | 1806 | 0.1564          | 0.9502   |
| 0.057         | 87.0  | 1827 | 0.2352          | 0.9346   |
| 0.0475        | 88.0  | 1848 | 0.1618          | 0.9502   |
| 0.0399        | 89.0  | 1869 | 0.1322          | 0.9564   |
| 0.0324        | 90.0  | 1890 | 0.1803          | 0.9502   |
| 0.0796        | 91.0  | 1911 | 0.1577          | 0.9408   |
| 0.0283        | 92.0  | 1932 | 0.1599          | 0.9626   |
| 0.0325        | 93.0  | 1953 | 0.1741          | 0.9626   |
| 0.0345        | 94.0  | 1974 | 0.1089          | 0.9533   |
| 0.0361        | 95.0  | 1995 | 0.1044          | 0.9595   |
| 0.0346        | 96.0  | 2016 | 0.1416          | 0.9533   |
| 0.0339        | 97.0  | 2037 | 0.2032          | 0.9346   |
| 0.0309        | 98.0  | 2058 | 0.1348          | 0.9595   |
| 0.046         | 99.0  | 2079 | 0.1345          | 0.9533   |
| 0.0285        | 100.0 | 2100 | 0.1854          | 0.9439   |


### Framework versions

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

fresh1 fresh2 fresh3