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# meat_calssify_fresh_crop_fixed_overlap_epoch100_V_0_14

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: 0.1627
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.0987        | 1.0   | 21   | 1.0847          | 0.4361   |
| 1.0683        | 2.0   | 42   | 1.0508          | 0.5171   |
| 1.0224        | 3.0   | 63   | 1.0214          | 0.4704   |
| 0.9556        | 4.0   | 84   | 0.9954          | 0.4891   |
| 0.9266        | 5.0   | 105  | 0.9473          | 0.5389   |
| 0.9168        | 6.0   | 126  | 0.8557          | 0.5919   |
| 0.7754        | 7.0   | 147  | 0.8971          | 0.5763   |
| 0.7383        | 8.0   | 168  | 0.6777          | 0.7695   |
| 0.6482        | 9.0   | 189  | 0.7117          | 0.7009   |
| 0.5976        | 10.0  | 210  | 0.5923          | 0.7757   |
| 0.6336        | 11.0  | 231  | 0.5497          | 0.7975   |
| 0.5193        | 12.0  | 252  | 0.6389          | 0.7383   |
| 0.4496        | 13.0  | 273  | 0.5799          | 0.7632   |
| 0.4089        | 14.0  | 294  | 0.5227          | 0.8006   |
| 0.3668        | 15.0  | 315  | 0.5907          | 0.7539   |
| 0.3644        | 16.0  | 336  | 0.7197          | 0.7414   |
| 0.3398        | 17.0  | 357  | 0.4430          | 0.8255   |
| 0.2927        | 18.0  | 378  | 0.5855          | 0.7819   |
| 0.3007        | 19.0  | 399  | 0.4378          | 0.8287   |
| 0.252         | 20.0  | 420  | 0.3540          | 0.8816   |
| 0.3041        | 21.0  | 441  | 0.5140          | 0.8162   |
| 0.2773        | 22.0  | 462  | 0.4456          | 0.8287   |
| 0.2474        | 23.0  | 483  | 0.4632          | 0.8100   |
| 0.2469        | 24.0  | 504  | 0.5080          | 0.8131   |
| 0.2201        | 25.0  | 525  | 0.3787          | 0.8660   |
| 0.167         | 26.0  | 546  | 0.3245          | 0.8723   |
| 0.1614        | 27.0  | 567  | 0.5479          | 0.8287   |
| 0.1585        | 28.0  | 588  | 0.3292          | 0.8598   |
| 0.1686        | 29.0  | 609  | 0.5806          | 0.7944   |
| 0.2157        | 30.0  | 630  | 0.4449          | 0.8193   |
| 0.1846        | 31.0  | 651  | 0.6371          | 0.7850   |
| 0.1614        | 32.0  | 672  | 0.3739          | 0.8754   |
| 0.1214        | 33.0  | 693  | 0.3230          | 0.8879   |
| 0.1294        | 34.0  | 714  | 0.4792          | 0.8442   |
| 0.112         | 35.0  | 735  | 0.3600          | 0.8847   |
| 0.1436        | 36.0  | 756  | 0.4445          | 0.8567   |
| 0.121         | 37.0  | 777  | 0.3601          | 0.8785   |
| 0.1524        | 38.0  | 798  | 0.4202          | 0.8567   |
| 0.1221        | 39.0  | 819  | 0.3454          | 0.8754   |
| 0.1397        | 40.0  | 840  | 0.4782          | 0.8536   |
| 0.1608        | 41.0  | 861  | 0.5481          | 0.8224   |
| 0.1207        | 42.0  | 882  | 0.3432          | 0.8660   |
| 0.1176        | 43.0  | 903  | 0.3480          | 0.8816   |
| 0.1072        | 44.0  | 924  | 0.3242          | 0.8785   |
| 0.0989        | 45.0  | 945  | 0.3556          | 0.8847   |
| 0.0946        | 46.0  | 966  | 0.3630          | 0.8723   |
| 0.1087        | 47.0  | 987  | 0.2972          | 0.8910   |
| 0.2532        | 48.0  | 1008 | 0.2845          | 0.9097   |
| 0.0912        | 49.0  | 1029 | 0.3424          | 0.8816   |
| 0.1181        | 50.0  | 1050 | 0.2204          | 0.9159   |
| 0.0925        | 51.0  | 1071 | 0.3311          | 0.8785   |
| 0.1092        | 52.0  | 1092 | 0.2445          | 0.9221   |
| 0.0924        | 53.0  | 1113 | 0.3297          | 0.8879   |
| 0.0871        | 54.0  | 1134 | 0.1846          | 0.9315   |
| 0.0799        | 55.0  | 1155 | 0.3486          | 0.9034   |
| 0.1778        | 56.0  | 1176 | 0.3292          | 0.8941   |
| 0.1039        | 57.0  | 1197 | 0.4066          | 0.8567   |
| 0.0732        | 58.0  | 1218 | 0.3245          | 0.9097   |
| 0.0642        | 59.0  | 1239 | 0.2939          | 0.9190   |
| 0.0811        | 60.0  | 1260 | 0.4293          | 0.8847   |
| 0.0679        | 61.0  | 1281 | 0.3204          | 0.8941   |
| 0.0563        | 62.0  | 1302 | 0.3244          | 0.9190   |
| 0.0868        | 63.0  | 1323 | 0.2359          | 0.9315   |
| 0.1067        | 64.0  | 1344 | 0.2720          | 0.9159   |
| 0.0696        | 65.0  | 1365 | 0.3054          | 0.9003   |
| 0.0586        | 66.0  | 1386 | 0.3045          | 0.9003   |
| 0.0612        | 67.0  | 1407 | 0.3321          | 0.8972   |
| 0.059         | 68.0  | 1428 | 0.3224          | 0.9003   |
| 0.0669        | 69.0  | 1449 | 0.3123          | 0.9003   |
| 0.056         | 70.0  | 1470 | 0.2288          | 0.9252   |
| 0.0517        | 71.0  | 1491 | 0.2590          | 0.9221   |
| 0.0496        | 72.0  | 1512 | 0.2533          | 0.9252   |
| 0.0462        | 73.0  | 1533 | 0.2943          | 0.9065   |
| 0.0457        | 74.0  | 1554 | 0.2280          | 0.9377   |
| 0.051         | 75.0  | 1575 | 0.3099          | 0.9128   |
| 0.0395        | 76.0  | 1596 | 0.2711          | 0.9221   |
| 0.0338        | 77.0  | 1617 | 0.1932          | 0.9408   |
| 0.0483        | 78.0  | 1638 | 0.1974          | 0.9533   |
| 0.0506        | 79.0  | 1659 | 0.2310          | 0.9283   |
| 0.0362        | 80.0  | 1680 | 0.2853          | 0.9252   |
| 0.0485        | 81.0  | 1701 | 0.1954          | 0.9408   |
| 0.0448        | 82.0  | 1722 | 0.2609          | 0.9252   |
| 0.0313        | 83.0  | 1743 | 0.2825          | 0.9190   |
| 0.0506        | 84.0  | 1764 | 0.3219          | 0.9065   |
| 0.0379        | 85.0  | 1785 | 0.2786          | 0.9221   |
| 0.0345        | 86.0  | 1806 | 0.3341          | 0.9065   |
| 0.019         | 87.0  | 1827 | 0.2731          | 0.9346   |
| 0.0438        | 88.0  | 1848 | 0.2449          | 0.9252   |
| 0.0321        | 89.0  | 1869 | 0.2719          | 0.9252   |
| 0.0478        | 90.0  | 1890 | 0.2214          | 0.9408   |
| 0.0598        | 91.0  | 1911 | 0.2174          | 0.9315   |
| 0.0372        | 92.0  | 1932 | 0.2075          | 0.9315   |
| 0.0422        | 93.0  | 1953 | 0.1781          | 0.9439   |
| 0.0324        | 94.0  | 1974 | 0.1692          | 0.9470   |
| 0.0325        | 95.0  | 1995 | 0.1999          | 0.9408   |
| 0.0369        | 96.0  | 2016 | 0.1929          | 0.9346   |
| 0.0309        | 97.0  | 2037 | 0.2310          | 0.9315   |
| 0.0347        | 98.0  | 2058 | 0.1347          | 0.9626   |
| 0.0445        | 99.0  | 2079 | 0.1967          | 0.9470   |
| 0.0337        | 100.0 | 2100 | 0.1627          | 0.9470   |


### Framework versions

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

fresh1 fresh2 fresh3