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# meat_calssify_fresh_crop_fixed_overlap_epoch100_V_0_7

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: 0.1612
- Accuracy: 0.9533

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.1056        | 1.0   | 21   | 1.0902          | 0.4206   |
| 1.0884        | 2.0   | 42   | 1.0625          | 0.4766   |
| 1.0199        | 3.0   | 63   | 1.0114          | 0.5202   |
| 0.9636        | 4.0   | 84   | 0.9735          | 0.5234   |
| 0.8789        | 5.0   | 105  | 0.9093          | 0.5701   |
| 0.8625        | 6.0   | 126  | 0.8850          | 0.6044   |
| 0.7607        | 7.0   | 147  | 0.8773          | 0.6106   |
| 0.7615        | 8.0   | 168  | 0.8370          | 0.5950   |
| 0.7052        | 9.0   | 189  | 0.8290          | 0.6231   |
| 0.6378        | 10.0  | 210  | 0.6312          | 0.7508   |
| 0.5741        | 11.0  | 231  | 0.6255          | 0.7508   |
| 0.5034        | 12.0  | 252  | 0.7393          | 0.6511   |
| 0.5886        | 13.0  | 273  | 0.6083          | 0.7664   |
| 0.4313        | 14.0  | 294  | 0.5113          | 0.7975   |
| 0.4542        | 15.0  | 315  | 0.5826          | 0.7632   |
| 0.3551        | 16.0  | 336  | 0.6452          | 0.7664   |
| 0.3613        | 17.0  | 357  | 0.5993          | 0.7601   |
| 0.3627        | 18.0  | 378  | 0.4192          | 0.8536   |
| 0.2659        | 19.0  | 399  | 0.4967          | 0.8131   |
| 0.2783        | 20.0  | 420  | 0.4777          | 0.8287   |
| 0.2618        | 21.0  | 441  | 0.5573          | 0.7850   |
| 0.2962        | 22.0  | 462  | 0.4956          | 0.7975   |
| 0.3321        | 23.0  | 483  | 0.3398          | 0.8723   |
| 0.3306        | 24.0  | 504  | 0.4910          | 0.8224   |
| 0.2813        | 25.0  | 525  | 0.3536          | 0.8536   |
| 0.189         | 26.0  | 546  | 0.2645          | 0.8910   |
| 0.2114        | 27.0  | 567  | 0.5280          | 0.8224   |
| 0.2027        | 28.0  | 588  | 0.5607          | 0.8100   |
| 0.204         | 29.0  | 609  | 0.3179          | 0.8879   |
| 0.1844        | 30.0  | 630  | 0.2999          | 0.8972   |
| 0.1655        | 31.0  | 651  | 0.3656          | 0.8785   |
| 0.3034        | 32.0  | 672  | 0.2920          | 0.8941   |
| 0.1617        | 33.0  | 693  | 0.3290          | 0.8847   |
| 0.1588        | 34.0  | 714  | 0.2659          | 0.8972   |
| 0.1263        | 35.0  | 735  | 0.4091          | 0.8505   |
| 0.145         | 36.0  | 756  | 0.3294          | 0.8785   |
| 0.1413        | 37.0  | 777  | 0.2408          | 0.9128   |
| 0.1309        | 38.0  | 798  | 0.2980          | 0.8910   |
| 0.1316        | 39.0  | 819  | 0.3839          | 0.8723   |
| 0.1508        | 40.0  | 840  | 0.2546          | 0.9034   |
| 0.1078        | 41.0  | 861  | 0.2317          | 0.9221   |
| 0.1263        | 42.0  | 882  | 0.3212          | 0.8910   |
| 0.142         | 43.0  | 903  | 0.3513          | 0.8660   |
| 0.108         | 44.0  | 924  | 0.2291          | 0.9034   |
| 0.1297        | 45.0  | 945  | 0.3755          | 0.8692   |
| 0.1195        | 46.0  | 966  | 0.2830          | 0.9065   |
| 0.1029        | 47.0  | 987  | 0.3560          | 0.8785   |
| 0.0988        | 48.0  | 1008 | 0.4380          | 0.8536   |
| 0.0931        | 49.0  | 1029 | 0.1965          | 0.9283   |
| 0.0787        | 50.0  | 1050 | 0.3069          | 0.9003   |
| 0.0925        | 51.0  | 1071 | 0.3059          | 0.9065   |
| 0.0999        | 52.0  | 1092 | 0.2761          | 0.9097   |
| 0.1079        | 53.0  | 1113 | 0.4334          | 0.8598   |
| 0.0967        | 54.0  | 1134 | 0.2761          | 0.9097   |
| 0.2187        | 55.0  | 1155 | 0.3166          | 0.8941   |
| 0.2928        | 56.0  | 1176 | 0.1629          | 0.9377   |
| 0.0813        | 57.0  | 1197 | 0.2661          | 0.9159   |
| 0.0898        | 58.0  | 1218 | 0.1690          | 0.9315   |
| 0.0741        | 59.0  | 1239 | 0.2331          | 0.9190   |
| 0.0646        | 60.0  | 1260 | 0.1978          | 0.9221   |
| 0.0576        | 61.0  | 1281 | 0.2079          | 0.9377   |
| 0.0676        | 62.0  | 1302 | 0.2102          | 0.9315   |
| 0.0716        | 63.0  | 1323 | 0.2085          | 0.9315   |
| 0.1935        | 64.0  | 1344 | 0.2461          | 0.9315   |
| 0.0633        | 65.0  | 1365 | 0.1748          | 0.9346   |
| 0.062         | 66.0  | 1386 | 0.2004          | 0.9315   |
| 0.0757        | 67.0  | 1407 | 0.2812          | 0.9034   |
| 0.0548        | 68.0  | 1428 | 0.1503          | 0.9502   |
| 0.0583        | 69.0  | 1449 | 0.3126          | 0.9097   |
| 0.2111        | 70.0  | 1470 | 0.2005          | 0.9470   |
| 0.0648        | 71.0  | 1491 | 0.1651          | 0.9533   |
| 0.0477        | 72.0  | 1512 | 0.2301          | 0.9346   |
| 0.0438        | 73.0  | 1533 | 0.2156          | 0.9252   |
| 0.0631        | 74.0  | 1554 | 0.2343          | 0.9283   |
| 0.0498        | 75.0  | 1575 | 0.2876          | 0.9065   |
| 0.0605        | 76.0  | 1596 | 0.2125          | 0.9283   |
| 0.0604        | 77.0  | 1617 | 0.1966          | 0.9408   |
| 0.0509        | 78.0  | 1638 | 0.2012          | 0.9470   |
| 0.0452        | 79.0  | 1659 | 0.2409          | 0.9315   |
| 0.0419        | 80.0  | 1680 | 0.2316          | 0.9283   |
| 0.0306        | 81.0  | 1701 | 0.2379          | 0.9346   |
| 0.0403        | 82.0  | 1722 | 0.2128          | 0.9346   |
| 0.0484        | 83.0  | 1743 | 0.1239          | 0.9502   |
| 0.0523        | 84.0  | 1764 | 0.2109          | 0.9408   |
| 0.0445        | 85.0  | 1785 | 0.2261          | 0.9283   |
| 0.0442        | 86.0  | 1806 | 0.1753          | 0.9564   |
| 0.0274        | 87.0  | 1827 | 0.1932          | 0.9408   |
| 0.0395        | 88.0  | 1848 | 0.1622          | 0.9439   |
| 0.0587        | 89.0  | 1869 | 0.2000          | 0.9408   |
| 0.0299        | 90.0  | 1890 | 0.2348          | 0.9221   |
| 0.033         | 91.0  | 1911 | 0.1726          | 0.9439   |
| 0.032         | 92.0  | 1932 | 0.1737          | 0.9470   |
| 0.0275        | 93.0  | 1953 | 0.1737          | 0.9470   |
| 0.0324        | 94.0  | 1974 | 0.2660          | 0.9159   |
| 0.0256        | 95.0  | 1995 | 0.1639          | 0.9408   |
| 0.0289        | 96.0  | 2016 | 0.1312          | 0.9502   |
| 0.0304        | 97.0  | 2037 | 0.1784          | 0.9439   |
| 0.0411        | 98.0  | 2058 | 0.1326          | 0.9626   |
| 0.0256        | 99.0  | 2079 | 0.1724          | 0.9470   |
| 0.0382        | 100.0 | 2100 | 0.1612          | 0.9533   |


### Framework versions

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

fresh1 fresh2 fresh3