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# meat_calssify_fresh_crop_fixed_overlap_epoch100_V_0_12

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: 0.1999
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.093         | 1.0   | 21   | 1.0798          | 0.4361   |
| 1.0819        | 2.0   | 42   | 1.0504          | 0.4704   |
| 1.0195        | 3.0   | 63   | 1.0107          | 0.4860   |
| 0.9205        | 4.0   | 84   | 0.9285          | 0.5514   |
| 0.879         | 5.0   | 105  | 0.8812          | 0.6044   |
| 0.757         | 6.0   | 126  | 0.8114          | 0.6324   |
| 0.6884        | 7.0   | 147  | 0.7328          | 0.6885   |
| 0.6399        | 8.0   | 168  | 0.7187          | 0.6978   |
| 0.5531        | 9.0   | 189  | 0.6771          | 0.7196   |
| 0.5187        | 10.0  | 210  | 0.6594          | 0.7134   |
| 0.5125        | 11.0  | 231  | 0.7660          | 0.6729   |
| 0.495         | 12.0  | 252  | 0.7215          | 0.7165   |
| 0.5014        | 13.0  | 273  | 0.5828          | 0.7570   |
| 0.3638        | 14.0  | 294  | 0.7056          | 0.7134   |
| 0.4493        | 15.0  | 315  | 0.7061          | 0.7383   |
| 0.4304        | 16.0  | 336  | 0.5031          | 0.7944   |
| 0.3223        | 17.0  | 357  | 0.5052          | 0.7975   |
| 0.3496        | 18.0  | 378  | 0.5136          | 0.8069   |
| 0.2498        | 19.0  | 399  | 0.5414          | 0.7944   |
| 0.3783        | 20.0  | 420  | 0.4276          | 0.8380   |
| 0.2768        | 21.0  | 441  | 0.4990          | 0.8100   |
| 0.2588        | 22.0  | 462  | 0.5184          | 0.8100   |
| 0.33          | 23.0  | 483  | 0.4037          | 0.8380   |
| 0.2418        | 24.0  | 504  | 0.4764          | 0.8100   |
| 0.2           | 25.0  | 525  | 0.3888          | 0.8505   |
| 0.1859        | 26.0  | 546  | 0.3868          | 0.8660   |
| 0.1804        | 27.0  | 567  | 0.5299          | 0.7944   |
| 0.1891        | 28.0  | 588  | 0.4448          | 0.8411   |
| 0.1837        | 29.0  | 609  | 0.4972          | 0.8349   |
| 0.209         | 30.0  | 630  | 0.4709          | 0.8380   |
| 0.1669        | 31.0  | 651  | 0.4084          | 0.8536   |
| 0.1474        | 32.0  | 672  | 0.4000          | 0.8785   |
| 0.1666        | 33.0  | 693  | 0.4109          | 0.8598   |
| 0.1657        | 34.0  | 714  | 0.3265          | 0.8910   |
| 0.1454        | 35.0  | 735  | 0.5221          | 0.8162   |
| 0.2093        | 36.0  | 756  | 0.6376          | 0.7944   |
| 0.1929        | 37.0  | 777  | 0.4007          | 0.8723   |
| 0.1393        | 38.0  | 798  | 0.3291          | 0.8879   |
| 0.1328        | 39.0  | 819  | 0.3766          | 0.8598   |
| 0.127         | 40.0  | 840  | 0.2965          | 0.9003   |
| 0.1325        | 41.0  | 861  | 0.3481          | 0.8723   |
| 0.118         | 42.0  | 882  | 0.3093          | 0.9065   |
| 0.1001        | 43.0  | 903  | 0.4232          | 0.8692   |
| 0.124         | 44.0  | 924  | 0.3761          | 0.8723   |
| 0.1159        | 45.0  | 945  | 0.3523          | 0.8910   |
| 0.129         | 46.0  | 966  | 0.3309          | 0.8785   |
| 0.1129        | 47.0  | 987  | 0.2915          | 0.9003   |
| 0.1043        | 48.0  | 1008 | 0.3259          | 0.8972   |
| 0.0986        | 49.0  | 1029 | 0.2627          | 0.9097   |
| 0.083         | 50.0  | 1050 | 0.3035          | 0.9034   |
| 0.0874        | 51.0  | 1071 | 0.3994          | 0.8629   |
| 0.0959        | 52.0  | 1092 | 0.2904          | 0.9065   |
| 0.0883        | 53.0  | 1113 | 0.2771          | 0.9128   |
| 0.0766        | 54.0  | 1134 | 0.2984          | 0.9128   |
| 0.0865        | 55.0  | 1155 | 0.3534          | 0.8941   |
| 0.0907        | 56.0  | 1176 | 0.3874          | 0.8723   |
| 0.0596        | 57.0  | 1197 | 0.2080          | 0.9283   |
| 0.0658        | 58.0  | 1218 | 0.3571          | 0.8879   |
| 0.0806        | 59.0  | 1239 | 0.3444          | 0.9003   |
| 0.0709        | 60.0  | 1260 | 0.3292          | 0.8972   |
| 0.0864        | 61.0  | 1281 | 0.3551          | 0.8816   |
| 0.0773        | 62.0  | 1302 | 0.2930          | 0.9159   |
| 0.0758        | 63.0  | 1323 | 0.2828          | 0.9221   |
| 0.0767        | 64.0  | 1344 | 0.2919          | 0.9065   |
| 0.0686        | 65.0  | 1365 | 0.2971          | 0.9065   |
| 0.0818        | 66.0  | 1386 | 0.3057          | 0.8972   |
| 0.0659        | 67.0  | 1407 | 0.2323          | 0.9221   |
| 0.0627        | 68.0  | 1428 | 0.3991          | 0.8754   |
| 0.0536        | 69.0  | 1449 | 0.2314          | 0.9221   |
| 0.2167        | 70.0  | 1470 | 0.2586          | 0.9346   |
| 0.0706        | 71.0  | 1491 | 0.2813          | 0.9315   |
| 0.0631        | 72.0  | 1512 | 0.2981          | 0.9034   |
| 0.0586        | 73.0  | 1533 | 0.2586          | 0.9283   |
| 0.0597        | 74.0  | 1554 | 0.3115          | 0.9097   |
| 0.0412        | 75.0  | 1575 | 0.2327          | 0.9315   |
| 0.0504        | 76.0  | 1596 | 0.2493          | 0.9408   |
| 0.0515        | 77.0  | 1617 | 0.2861          | 0.9283   |
| 0.0394        | 78.0  | 1638 | 0.2715          | 0.9128   |
| 0.0526        | 79.0  | 1659 | 0.2521          | 0.9190   |
| 0.043         | 80.0  | 1680 | 0.2421          | 0.9283   |
| 0.0466        | 81.0  | 1701 | 0.2918          | 0.9034   |
| 0.0418        | 82.0  | 1722 | 0.2956          | 0.9065   |
| 0.048         | 83.0  | 1743 | 0.2199          | 0.9283   |
| 0.0311        | 84.0  | 1764 | 0.2732          | 0.9128   |
| 0.0681        | 85.0  | 1785 | 0.2148          | 0.9346   |
| 0.0392        | 86.0  | 1806 | 0.2609          | 0.9252   |
| 0.0447        | 87.0  | 1827 | 0.2791          | 0.9346   |
| 0.0244        | 88.0  | 1848 | 0.2863          | 0.9221   |
| 0.0382        | 89.0  | 1869 | 0.2894          | 0.9190   |
| 0.0524        | 90.0  | 1890 | 0.1708          | 0.9408   |
| 0.0356        | 91.0  | 1911 | 0.2084          | 0.9221   |
| 0.0387        | 92.0  | 1932 | 0.2262          | 0.9377   |
| 0.0345        | 93.0  | 1953 | 0.2441          | 0.9377   |
| 0.0298        | 94.0  | 1974 | 0.2042          | 0.9408   |
| 0.0427        | 95.0  | 1995 | 0.1611          | 0.9533   |
| 0.043         | 96.0  | 2016 | 0.2175          | 0.9533   |
| 0.0241        | 97.0  | 2037 | 0.2445          | 0.9283   |
| 0.0416        | 98.0  | 2058 | 0.2236          | 0.9283   |
| 0.0311        | 99.0  | 2079 | 0.1943          | 0.9502   |
| 0.0352        | 100.0 | 2100 | 0.1999          | 0.9439   |


### Framework versions

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

fresh1 fresh2 fresh3