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# meat_calssify_fresh_crop_fixed_overlap_epoch100_V_0_1

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: 0.1958
- Accuracy: 0.9470

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.1042        | 1.0   | 21   | 1.0970          | 0.3489   |
| 1.0711        | 2.0   | 42   | 1.0849          | 0.3863   |
| 1.0265        | 3.0   | 63   | 1.0484          | 0.4424   |
| 0.9343        | 4.0   | 84   | 0.9641          | 0.5202   |
| 0.9037        | 5.0   | 105  | 0.8967          | 0.5639   |
| 0.7794        | 6.0   | 126  | 0.8947          | 0.5607   |
| 0.7517        | 7.0   | 147  | 0.7444          | 0.6854   |
| 0.6897        | 8.0   | 168  | 0.7788          | 0.6542   |
| 0.6639        | 9.0   | 189  | 0.9096          | 0.5981   |
| 0.7325        | 10.0  | 210  | 0.7083          | 0.6947   |
| 0.6112        | 11.0  | 231  | 0.6447          | 0.7383   |
| 0.5403        | 12.0  | 252  | 0.7023          | 0.6978   |
| 0.446         | 13.0  | 273  | 0.7003          | 0.7009   |
| 0.481         | 14.0  | 294  | 0.7621          | 0.7103   |
| 0.4406        | 15.0  | 315  | 0.5552          | 0.7882   |
| 0.3905        | 16.0  | 336  | 0.6945          | 0.7445   |
| 0.3573        | 17.0  | 357  | 0.4493          | 0.8318   |
| 0.4212        | 18.0  | 378  | 0.5443          | 0.7975   |
| 0.3467        | 19.0  | 399  | 0.4746          | 0.8006   |
| 0.275         | 20.0  | 420  | 0.4475          | 0.8318   |
| 0.2847        | 21.0  | 441  | 0.5923          | 0.7882   |
| 0.3065        | 22.0  | 462  | 0.4106          | 0.8629   |
| 0.2062        | 23.0  | 483  | 0.7714          | 0.7352   |
| 0.281         | 24.0  | 504  | 0.3681          | 0.8816   |
| 0.2239        | 25.0  | 525  | 0.3852          | 0.8411   |
| 0.2132        | 26.0  | 546  | 0.5309          | 0.8037   |
| 0.2846        | 27.0  | 567  | 0.4192          | 0.8349   |
| 0.1943        | 28.0  | 588  | 0.5426          | 0.7913   |
| 0.1594        | 29.0  | 609  | 0.4108          | 0.8380   |
| 0.2061        | 30.0  | 630  | 0.3541          | 0.8692   |
| 0.1616        | 31.0  | 651  | 0.2926          | 0.9097   |
| 0.1755        | 32.0  | 672  | 0.4088          | 0.8442   |
| 0.156         | 33.0  | 693  | 0.5390          | 0.8131   |
| 0.3471        | 34.0  | 714  | 0.4996          | 0.8255   |
| 0.1627        | 35.0  | 735  | 0.3407          | 0.8847   |
| 0.1332        | 36.0  | 756  | 0.2970          | 0.8972   |
| 0.2394        | 37.0  | 777  | 0.4211          | 0.8411   |
| 0.1086        | 38.0  | 798  | 0.3548          | 0.8847   |
| 0.1369        | 39.0  | 819  | 0.3874          | 0.8754   |
| 0.1235        | 40.0  | 840  | 0.2755          | 0.9065   |
| 0.132         | 41.0  | 861  | 0.3844          | 0.8816   |
| 0.1109        | 42.0  | 882  | 0.4368          | 0.8629   |
| 0.1291        | 43.0  | 903  | 0.3609          | 0.8754   |
| 0.1071        | 44.0  | 924  | 0.2968          | 0.9065   |
| 0.0967        | 45.0  | 945  | 0.3095          | 0.8847   |
| 0.1031        | 46.0  | 966  | 0.2942          | 0.9034   |
| 0.1124        | 47.0  | 987  | 0.2314          | 0.9252   |
| 0.085         | 48.0  | 1008 | 0.3651          | 0.8879   |
| 0.1031        | 49.0  | 1029 | 0.4515          | 0.8598   |
| 0.112         | 50.0  | 1050 | 0.2458          | 0.9190   |
| 0.11          | 51.0  | 1071 | 0.3609          | 0.8972   |
| 0.0742        | 52.0  | 1092 | 0.3382          | 0.9065   |
| 0.0783        | 53.0  | 1113 | 0.3365          | 0.9097   |
| 0.0748        | 54.0  | 1134 | 0.3213          | 0.9065   |
| 0.0983        | 55.0  | 1155 | 0.3021          | 0.9034   |
| 0.0651        | 56.0  | 1176 | 0.2968          | 0.9128   |
| 0.0762        | 57.0  | 1197 | 0.3651          | 0.8660   |
| 0.0831        | 58.0  | 1218 | 0.3192          | 0.9003   |
| 0.0989        | 59.0  | 1239 | 0.3015          | 0.8910   |
| 0.0936        | 60.0  | 1260 | 0.3160          | 0.8879   |
| 0.0725        | 61.0  | 1281 | 0.2810          | 0.8972   |
| 0.0779        | 62.0  | 1302 | 0.2108          | 0.9252   |
| 0.0565        | 63.0  | 1323 | 0.2214          | 0.9315   |
| 0.1442        | 64.0  | 1344 | 0.2242          | 0.9221   |
| 0.051         | 65.0  | 1365 | 0.2143          | 0.9128   |
| 0.0901        | 66.0  | 1386 | 0.3374          | 0.8941   |
| 0.08          | 67.0  | 1407 | 0.2368          | 0.9252   |
| 0.0425        | 68.0  | 1428 | 0.3098          | 0.9003   |
| 0.0603        | 69.0  | 1449 | 0.2638          | 0.9097   |
| 0.0604        | 70.0  | 1470 | 0.2012          | 0.9439   |
| 0.0405        | 71.0  | 1491 | 0.1795          | 0.9439   |
| 0.0526        | 72.0  | 1512 | 0.4807          | 0.8505   |
| 0.0728        | 73.0  | 1533 | 0.2587          | 0.9190   |
| 0.0406        | 74.0  | 1554 | 0.2363          | 0.9408   |
| 0.063         | 75.0  | 1575 | 0.3414          | 0.9034   |
| 0.0498        | 76.0  | 1596 | 0.2719          | 0.9159   |
| 0.0377        | 77.0  | 1617 | 0.2965          | 0.9128   |
| 0.0573        | 78.0  | 1638 | 0.2341          | 0.9377   |
| 0.096         | 79.0  | 1659 | 0.2503          | 0.9252   |
| 0.0373        | 80.0  | 1680 | 0.3416          | 0.9003   |
| 0.0485        | 81.0  | 1701 | 0.3115          | 0.9159   |
| 0.0502        | 82.0  | 1722 | 0.2318          | 0.9346   |
| 0.0559        | 83.0  | 1743 | 0.2506          | 0.9097   |
| 0.0446        | 84.0  | 1764 | 0.2691          | 0.9159   |
| 0.0344        | 85.0  | 1785 | 0.2695          | 0.9221   |
| 0.0306        | 86.0  | 1806 | 0.2747          | 0.9097   |
| 0.0404        | 87.0  | 1827 | 0.1680          | 0.9564   |
| 0.036         | 88.0  | 1848 | 0.2653          | 0.9221   |
| 0.0364        | 89.0  | 1869 | 0.1936          | 0.9408   |
| 0.0418        | 90.0  | 1890 | 0.2321          | 0.9346   |
| 0.0443        | 91.0  | 1911 | 0.2132          | 0.9408   |
| 0.0409        | 92.0  | 1932 | 0.2601          | 0.9190   |
| 0.0431        | 93.0  | 1953 | 0.2282          | 0.9439   |
| 0.0258        | 94.0  | 1974 | 0.2003          | 0.9346   |
| 0.0294        | 95.0  | 1995 | 0.2033          | 0.9439   |
| 0.0336        | 96.0  | 2016 | 0.1445          | 0.9595   |
| 0.0241        | 97.0  | 2037 | 0.2268          | 0.9346   |
| 0.037         | 98.0  | 2058 | 0.1920          | 0.9408   |
| 0.03          | 99.0  | 2079 | 0.1676          | 0.9533   |
| 0.0227        | 100.0 | 2100 | 0.1958          | 0.9470   |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.3.0
- Datasets 2.19.2
- Tokenizers 0.19.1

fresh1 fresh2 fresh3