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# meat_calssify_fresh_crop_fixed_overlap_epoch100_V_0_8

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: 0.2201
- Accuracy: 0.9377

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.0975        | 1.0   | 21   | 1.0890          | 0.4174   |
| 1.0736        | 2.0   | 42   | 1.0605          | 0.4673   |
| 1.0236        | 3.0   | 63   | 1.0034          | 0.5202   |
| 0.9414        | 4.0   | 84   | 0.9182          | 0.6044   |
| 0.8522        | 5.0   | 105  | 0.8534          | 0.6417   |
| 0.7504        | 6.0   | 126  | 0.8599          | 0.6044   |
| 0.7472        | 7.0   | 147  | 0.6873          | 0.7040   |
| 0.6671        | 8.0   | 168  | 0.6945          | 0.7165   |
| 0.5986        | 9.0   | 189  | 0.6044          | 0.7664   |
| 0.5255        | 10.0  | 210  | 0.6201          | 0.7383   |
| 0.4988        | 11.0  | 231  | 0.6229          | 0.7570   |
| 0.5221        | 12.0  | 252  | 0.6687          | 0.7321   |
| 0.4338        | 13.0  | 273  | 0.5720          | 0.7757   |
| 0.4157        | 14.0  | 294  | 0.5662          | 0.7757   |
| 0.5228        | 15.0  | 315  | 0.6383          | 0.7383   |
| 0.3387        | 16.0  | 336  | 0.4655          | 0.8069   |
| 0.2952        | 17.0  | 357  | 0.4642          | 0.8006   |
| 0.3083        | 18.0  | 378  | 0.5752          | 0.7726   |
| 0.2659        | 19.0  | 399  | 0.5155          | 0.7913   |
| 0.2824        | 20.0  | 420  | 0.4943          | 0.8162   |
| 0.3329        | 21.0  | 441  | 0.5901          | 0.7757   |
| 0.3527        | 22.0  | 462  | 0.4185          | 0.8380   |
| 0.2394        | 23.0  | 483  | 0.3630          | 0.8723   |
| 0.2106        | 24.0  | 504  | 0.4305          | 0.8474   |
| 0.1845        | 25.0  | 525  | 0.3412          | 0.8629   |
| 0.1882        | 26.0  | 546  | 0.3621          | 0.8816   |
| 0.2144        | 27.0  | 567  | 0.3275          | 0.8754   |
| 0.1824        | 28.0  | 588  | 0.3481          | 0.8723   |
| 0.163         | 29.0  | 609  | 0.3861          | 0.8598   |
| 0.1467        | 30.0  | 630  | 0.3590          | 0.8692   |
| 0.2073        | 31.0  | 651  | 0.3481          | 0.8879   |
| 0.1669        | 32.0  | 672  | 0.3134          | 0.8847   |
| 0.167         | 33.0  | 693  | 0.3726          | 0.8754   |
| 0.1624        | 34.0  | 714  | 0.5522          | 0.7944   |
| 0.1812        | 35.0  | 735  | 0.4431          | 0.8193   |
| 0.1172        | 36.0  | 756  | 0.3441          | 0.8816   |
| 0.1515        | 37.0  | 777  | 0.4946          | 0.8255   |
| 0.1612        | 38.0  | 798  | 0.3402          | 0.8847   |
| 0.0937        | 39.0  | 819  | 0.4480          | 0.8598   |
| 0.1453        | 40.0  | 840  | 0.4515          | 0.8411   |
| 0.1259        | 41.0  | 861  | 0.3361          | 0.8847   |
| 0.107         | 42.0  | 882  | 0.3544          | 0.8598   |
| 0.1244        | 43.0  | 903  | 0.3990          | 0.8567   |
| 0.0824        | 44.0  | 924  | 0.3566          | 0.9034   |
| 0.1171        | 45.0  | 945  | 0.3223          | 0.9003   |
| 0.1052        | 46.0  | 966  | 0.3364          | 0.8660   |
| 0.1274        | 47.0  | 987  | 0.3034          | 0.8941   |
| 0.0799        | 48.0  | 1008 | 0.3928          | 0.8910   |
| 0.0814        | 49.0  | 1029 | 0.3428          | 0.8847   |
| 0.091         | 50.0  | 1050 | 0.3141          | 0.9065   |
| 0.0777        | 51.0  | 1071 | 0.4016          | 0.8785   |
| 0.0644        | 52.0  | 1092 | 0.3398          | 0.8972   |
| 0.1019        | 53.0  | 1113 | 0.3559          | 0.8847   |
| 0.076         | 54.0  | 1134 | 0.3503          | 0.8910   |
| 0.067         | 55.0  | 1155 | 0.3245          | 0.8910   |
| 0.0679        | 56.0  | 1176 | 0.3099          | 0.9034   |
| 0.0661        | 57.0  | 1197 | 0.3249          | 0.8723   |
| 0.0716        | 58.0  | 1218 | 0.3016          | 0.9034   |
| 0.075         | 59.0  | 1239 | 0.4144          | 0.8692   |
| 0.0874        | 60.0  | 1260 | 0.3850          | 0.8723   |
| 0.0821        | 61.0  | 1281 | 0.2938          | 0.9065   |
| 0.0735        | 62.0  | 1302 | 0.2518          | 0.9190   |
| 0.0755        | 63.0  | 1323 | 0.4015          | 0.8972   |
| 0.2235        | 64.0  | 1344 | 0.3127          | 0.8972   |
| 0.0631        | 65.0  | 1365 | 0.2518          | 0.9128   |
| 0.0711        | 66.0  | 1386 | 0.3544          | 0.8941   |
| 0.0671        | 67.0  | 1407 | 0.3616          | 0.8816   |
| 0.059         | 68.0  | 1428 | 0.2567          | 0.9097   |
| 0.0558        | 69.0  | 1449 | 0.3696          | 0.8692   |
| 0.0755        | 70.0  | 1470 | 0.3032          | 0.9065   |
| 0.0666        | 71.0  | 1491 | 0.2819          | 0.9128   |
| 0.0519        | 72.0  | 1512 | 0.2179          | 0.9252   |
| 0.0443        | 73.0  | 1533 | 0.2722          | 0.9159   |
| 0.0415        | 74.0  | 1554 | 0.2167          | 0.9346   |
| 0.0632        | 75.0  | 1575 | 0.2115          | 0.9377   |
| 0.067         | 76.0  | 1596 | 0.4024          | 0.8785   |
| 0.0592        | 77.0  | 1617 | 0.2328          | 0.9283   |
| 0.0528        | 78.0  | 1638 | 0.2425          | 0.9065   |
| 0.0462        | 79.0  | 1659 | 0.2385          | 0.9252   |
| 0.0248        | 80.0  | 1680 | 0.2694          | 0.9159   |
| 0.04          | 81.0  | 1701 | 0.2192          | 0.9283   |
| 0.0436        | 82.0  | 1722 | 0.2697          | 0.9221   |
| 0.0415        | 83.0  | 1743 | 0.2855          | 0.9128   |
| 0.0431        | 84.0  | 1764 | 0.1680          | 0.9502   |
| 0.0438        | 85.0  | 1785 | 0.2513          | 0.9221   |
| 0.0385        | 86.0  | 1806 | 0.2609          | 0.9190   |
| 0.0291        | 87.0  | 1827 | 0.2136          | 0.9439   |
| 0.0326        | 88.0  | 1848 | 0.2069          | 0.9439   |
| 0.0347        | 89.0  | 1869 | 0.2450          | 0.9315   |
| 0.0393        | 90.0  | 1890 | 0.2609          | 0.9377   |
| 0.0355        | 91.0  | 1911 | 0.1932          | 0.9408   |
| 0.0423        | 92.0  | 1932 | 0.2481          | 0.9315   |
| 0.0386        | 93.0  | 1953 | 0.1963          | 0.9377   |
| 0.029         | 94.0  | 1974 | 0.2220          | 0.9377   |
| 0.0383        | 95.0  | 1995 | 0.2626          | 0.9252   |
| 0.0205        | 96.0  | 2016 | 0.1894          | 0.9470   |
| 0.0392        | 97.0  | 2037 | 0.1744          | 0.9502   |
| 0.0282        | 98.0  | 2058 | 0.2907          | 0.9190   |
| 0.0416        | 99.0  | 2079 | 0.1868          | 0.9533   |
| 0.0223        | 100.0 | 2100 | 0.2201          | 0.9377   |


### Framework versions

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

fresh1 fresh2 fresh3