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# meat_calssify_fresh_crop_fixed_overlap_epoch100_V_0_16

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: 0.2644
- Accuracy: 0.9159

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.1034        | 1.0   | 21   | 1.0943          | 0.3676   |
| 1.0767        | 2.0   | 42   | 1.0823          | 0.4330   |
| 1.0209        | 3.0   | 63   | 1.0269          | 0.4829   |
| 0.9495        | 4.0   | 84   | 1.0109          | 0.4953   |
| 0.9498        | 5.0   | 105  | 0.8882          | 0.6199   |
| 0.7834        | 6.0   | 126  | 0.8506          | 0.6075   |
| 0.6988        | 7.0   | 147  | 0.7727          | 0.6480   |
| 0.6568        | 8.0   | 168  | 0.8098          | 0.6573   |
| 0.634         | 9.0   | 189  | 0.9338          | 0.5607   |
| 0.7335        | 10.0  | 210  | 0.7394          | 0.6947   |
| 0.5521        | 11.0  | 231  | 0.6369          | 0.7539   |
| 0.5108        | 12.0  | 252  | 0.7480          | 0.7040   |
| 0.4485        | 13.0  | 273  | 0.8050          | 0.6854   |
| 0.4928        | 14.0  | 294  | 0.7566          | 0.7040   |
| 0.5092        | 15.0  | 315  | 0.5191          | 0.7944   |
| 0.4473        | 16.0  | 336  | 0.6516          | 0.7134   |
| 0.3521        | 17.0  | 357  | 0.5184          | 0.8069   |
| 0.2994        | 18.0  | 378  | 0.5233          | 0.8193   |
| 0.2844        | 19.0  | 399  | 0.5587          | 0.7757   |
| 0.301         | 20.0  | 420  | 0.5614          | 0.8131   |
| 0.2898        | 21.0  | 441  | 0.4659          | 0.8287   |
| 0.2513        | 22.0  | 462  | 0.4748          | 0.8287   |
| 0.2121        | 23.0  | 483  | 0.4042          | 0.8505   |
| 0.2302        | 24.0  | 504  | 0.6265          | 0.7757   |
| 0.2201        | 25.0  | 525  | 0.4746          | 0.8349   |
| 0.2193        | 26.0  | 546  | 0.3364          | 0.8816   |
| 0.1852        | 27.0  | 567  | 0.3966          | 0.8567   |
| 0.2117        | 28.0  | 588  | 0.4427          | 0.8349   |
| 0.1705        | 29.0  | 609  | 0.4767          | 0.8255   |
| 0.1756        | 30.0  | 630  | 0.4838          | 0.8380   |
| 0.1744        | 31.0  | 651  | 0.5400          | 0.8131   |
| 0.2296        | 32.0  | 672  | 0.4693          | 0.8255   |
| 0.1517        | 33.0  | 693  | 0.3704          | 0.8660   |
| 0.3201        | 34.0  | 714  | 0.7578          | 0.7539   |
| 0.1561        | 35.0  | 735  | 0.3828          | 0.8660   |
| 0.1458        | 36.0  | 756  | 0.4366          | 0.8692   |
| 0.2448        | 37.0  | 777  | 0.3000          | 0.8972   |
| 0.15          | 38.0  | 798  | 0.4457          | 0.8567   |
| 0.1367        | 39.0  | 819  | 0.2505          | 0.9128   |
| 0.1167        | 40.0  | 840  | 0.2869          | 0.9003   |
| 0.0949        | 41.0  | 861  | 0.3303          | 0.8847   |
| 0.1203        | 42.0  | 882  | 0.3524          | 0.8629   |
| 0.1429        | 43.0  | 903  | 0.4549          | 0.8318   |
| 0.11          | 44.0  | 924  | 0.4028          | 0.8754   |
| 0.1231        | 45.0  | 945  | 0.4290          | 0.8629   |
| 0.1009        | 46.0  | 966  | 0.4046          | 0.8598   |
| 0.1132        | 47.0  | 987  | 0.3221          | 0.8972   |
| 0.1023        | 48.0  | 1008 | 0.2680          | 0.9159   |
| 0.0906        | 49.0  | 1029 | 0.3685          | 0.8754   |
| 0.1039        | 50.0  | 1050 | 0.3564          | 0.8785   |
| 0.0948        | 51.0  | 1071 | 0.4784          | 0.8380   |
| 0.0881        | 52.0  | 1092 | 0.3369          | 0.8816   |
| 0.0918        | 53.0  | 1113 | 0.2608          | 0.9159   |
| 0.0828        | 54.0  | 1134 | 0.2678          | 0.9003   |
| 0.0819        | 55.0  | 1155 | 0.2618          | 0.9034   |
| 0.1696        | 56.0  | 1176 | 0.3057          | 0.9034   |
| 0.0943        | 57.0  | 1197 | 0.3915          | 0.8847   |
| 0.0718        | 58.0  | 1218 | 0.3162          | 0.9065   |
| 0.0775        | 59.0  | 1239 | 0.3678          | 0.8847   |
| 0.0674        | 60.0  | 1260 | 0.3083          | 0.8972   |
| 0.0666        | 61.0  | 1281 | 0.3120          | 0.9128   |
| 0.0631        | 62.0  | 1302 | 0.3648          | 0.9003   |
| 0.0726        | 63.0  | 1323 | 0.3771          | 0.8910   |
| 0.0619        | 64.0  | 1344 | 0.3278          | 0.8910   |
| 0.0823        | 65.0  | 1365 | 0.4250          | 0.8692   |
| 0.0628        | 66.0  | 1386 | 0.3618          | 0.9003   |
| 0.0714        | 67.0  | 1407 | 0.4590          | 0.8629   |
| 0.056         | 68.0  | 1428 | 0.4471          | 0.8910   |
| 0.0613        | 69.0  | 1449 | 0.2702          | 0.9097   |
| 0.0642        | 70.0  | 1470 | 0.2646          | 0.9190   |
| 0.0549        | 71.0  | 1491 | 0.3084          | 0.8972   |
| 0.0534        | 72.0  | 1512 | 0.3388          | 0.9128   |
| 0.0414        | 73.0  | 1533 | 0.2962          | 0.9190   |
| 0.0552        | 74.0  | 1554 | 0.3004          | 0.9221   |
| 0.0502        | 75.0  | 1575 | 0.4007          | 0.8879   |
| 0.0403        | 76.0  | 1596 | 0.2649          | 0.9065   |
| 0.0341        | 77.0  | 1617 | 0.1945          | 0.9408   |
| 0.061         | 78.0  | 1638 | 0.2936          | 0.9221   |
| 0.059         | 79.0  | 1659 | 0.2938          | 0.9128   |
| 0.0393        | 80.0  | 1680 | 0.3278          | 0.8941   |
| 0.0475        | 81.0  | 1701 | 0.2856          | 0.9190   |
| 0.0404        | 82.0  | 1722 | 0.2679          | 0.9252   |
| 0.0528        | 83.0  | 1743 | 0.2544          | 0.9283   |
| 0.05          | 84.0  | 1764 | 0.2992          | 0.9097   |
| 0.0449        | 85.0  | 1785 | 0.3004          | 0.9128   |
| 0.0337        | 86.0  | 1806 | 0.2744          | 0.9190   |
| 0.0406        | 87.0  | 1827 | 0.3380          | 0.9003   |
| 0.0314        | 88.0  | 1848 | 0.2801          | 0.9221   |
| 0.0355        | 89.0  | 1869 | 0.2609          | 0.9190   |
| 0.0313        | 90.0  | 1890 | 0.2507          | 0.9315   |
| 0.0478        | 91.0  | 1911 | 0.2934          | 0.9128   |
| 0.0365        | 92.0  | 1932 | 0.2642          | 0.9283   |
| 0.0486        | 93.0  | 1953 | 0.1662          | 0.9626   |
| 0.0271        | 94.0  | 1974 | 0.2194          | 0.9377   |
| 0.0215        | 95.0  | 1995 | 0.2492          | 0.9252   |
| 0.0365        | 96.0  | 2016 | 0.2006          | 0.9502   |
| 0.0275        | 97.0  | 2037 | 0.2267          | 0.9159   |
| 0.0647        | 98.0  | 2058 | 0.3226          | 0.9159   |
| 0.0222        | 99.0  | 2079 | 0.2469          | 0.9346   |
| 0.0426        | 100.0 | 2100 | 0.2644          | 0.9159   |


### Framework versions

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

fresh1 fresh2 fresh3