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# meat_calssify_fresh_crop_fixed_overlap_epoch100_V_0_15

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: 0.1718
- Accuracy: 0.9564

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.1001        | 1.0   | 21   | 1.0997          | 0.3614   |
| 1.0637        | 2.0   | 42   | 1.0850          | 0.3863   |
| 1.0464        | 3.0   | 63   | 1.0524          | 0.4766   |
| 0.9569        | 4.0   | 84   | 0.9464          | 0.5763   |
| 0.8778        | 5.0   | 105  | 0.8916          | 0.6168   |
| 0.8396        | 6.0   | 126  | 0.8181          | 0.6573   |
| 0.7752        | 7.0   | 147  | 0.8517          | 0.6168   |
| 0.7765        | 8.0   | 168  | 1.0433          | 0.5140   |
| 0.7283        | 9.0   | 189  | 0.9781          | 0.5452   |
| 0.6714        | 10.0  | 210  | 0.6957          | 0.7165   |
| 0.5872        | 11.0  | 231  | 0.6338          | 0.7352   |
| 0.4924        | 12.0  | 252  | 0.5824          | 0.7757   |
| 0.4441        | 13.0  | 273  | 0.7042          | 0.7040   |
| 0.4818        | 14.0  | 294  | 0.4985          | 0.8100   |
| 0.4477        | 15.0  | 315  | 0.5176          | 0.8100   |
| 0.387         | 16.0  | 336  | 0.5820          | 0.7757   |
| 0.378         | 17.0  | 357  | 0.4651          | 0.8287   |
| 0.3353        | 18.0  | 378  | 0.5163          | 0.8037   |
| 0.3651        | 19.0  | 399  | 0.3980          | 0.8474   |
| 0.312         | 20.0  | 420  | 0.4217          | 0.8629   |
| 0.2572        | 21.0  | 441  | 0.4610          | 0.8255   |
| 0.25          | 22.0  | 462  | 0.4421          | 0.8349   |
| 0.2325        | 23.0  | 483  | 0.4322          | 0.8193   |
| 0.2384        | 24.0  | 504  | 0.4207          | 0.8380   |
| 0.2295        | 25.0  | 525  | 0.4298          | 0.8411   |
| 0.4004        | 26.0  | 546  | 0.4976          | 0.8224   |
| 0.2136        | 27.0  | 567  | 0.3272          | 0.8723   |
| 0.1851        | 28.0  | 588  | 0.3004          | 0.8941   |
| 0.1513        | 29.0  | 609  | 0.3198          | 0.8785   |
| 0.2132        | 30.0  | 630  | 0.3403          | 0.8879   |
| 0.1704        | 31.0  | 651  | 0.4112          | 0.8692   |
| 0.1639        | 32.0  | 672  | 0.3038          | 0.8941   |
| 0.2028        | 33.0  | 693  | 0.6632          | 0.7601   |
| 0.256         | 34.0  | 714  | 0.3475          | 0.8785   |
| 0.142         | 35.0  | 735  | 0.2709          | 0.9034   |
| 0.1358        | 36.0  | 756  | 0.2745          | 0.9034   |
| 0.1543        | 37.0  | 777  | 0.3139          | 0.8816   |
| 0.1214        | 38.0  | 798  | 0.2518          | 0.9128   |
| 0.1291        | 39.0  | 819  | 0.4121          | 0.8598   |
| 0.1423        | 40.0  | 840  | 0.2469          | 0.9128   |
| 0.1071        | 41.0  | 861  | 0.2351          | 0.9252   |
| 0.1259        | 42.0  | 882  | 0.3639          | 0.8785   |
| 0.1114        | 43.0  | 903  | 0.4624          | 0.8567   |
| 0.123         | 44.0  | 924  | 0.3147          | 0.8941   |
| 0.0914        | 45.0  | 945  | 0.3599          | 0.8879   |
| 0.1154        | 46.0  | 966  | 0.2986          | 0.9003   |
| 0.1001        | 47.0  | 987  | 0.2688          | 0.9034   |
| 0.0959        | 48.0  | 1008 | 0.2358          | 0.9159   |
| 0.0935        | 49.0  | 1029 | 0.2724          | 0.9159   |
| 0.104         | 50.0  | 1050 | 0.3857          | 0.8847   |
| 0.1158        | 51.0  | 1071 | 0.3359          | 0.8910   |
| 0.0766        | 52.0  | 1092 | 0.3030          | 0.8941   |
| 0.1048        | 53.0  | 1113 | 0.2648          | 0.9097   |
| 0.1065        | 54.0  | 1134 | 0.2859          | 0.9128   |
| 0.0738        | 55.0  | 1155 | 0.3660          | 0.8910   |
| 0.078         | 56.0  | 1176 | 0.2843          | 0.9221   |
| 0.0755        | 57.0  | 1197 | 0.4503          | 0.8816   |
| 0.1193        | 58.0  | 1218 | 0.5647          | 0.8006   |
| 0.1014        | 59.0  | 1239 | 0.4011          | 0.8660   |
| 0.0557        | 60.0  | 1260 | 0.3376          | 0.8941   |
| 0.054         | 61.0  | 1281 | 0.2309          | 0.9283   |
| 0.0674        | 62.0  | 1302 | 0.3222          | 0.9003   |
| 0.0845        | 63.0  | 1323 | 0.2429          | 0.9221   |
| 0.0721        | 64.0  | 1344 | 0.2247          | 0.9283   |
| 0.0711        | 65.0  | 1365 | 0.3134          | 0.9097   |
| 0.0881        | 66.0  | 1386 | 0.2918          | 0.9159   |
| 0.0753        | 67.0  | 1407 | 0.2734          | 0.9065   |
| 0.059         | 68.0  | 1428 | 0.3353          | 0.8754   |
| 0.0814        | 69.0  | 1449 | 0.3093          | 0.9159   |
| 0.1317        | 70.0  | 1470 | 0.1641          | 0.9439   |
| 0.0539        | 71.0  | 1491 | 0.1988          | 0.9470   |
| 0.0572        | 72.0  | 1512 | 0.2493          | 0.9159   |
| 0.0322        | 73.0  | 1533 | 0.2045          | 0.9315   |
| 0.0473        | 74.0  | 1554 | 0.2380          | 0.9315   |
| 0.0478        | 75.0  | 1575 | 0.1687          | 0.9377   |
| 0.0554        | 76.0  | 1596 | 0.2121          | 0.9315   |
| 0.0444        | 77.0  | 1617 | 0.2172          | 0.9439   |
| 0.0808        | 78.0  | 1638 | 0.3581          | 0.8910   |
| 0.0522        | 79.0  | 1659 | 0.2155          | 0.9408   |
| 0.0402        | 80.0  | 1680 | 0.2204          | 0.9283   |
| 0.0387        | 81.0  | 1701 | 0.1438          | 0.9564   |
| 0.0294        | 82.0  | 1722 | 0.3094          | 0.9221   |
| 0.0449        | 83.0  | 1743 | 0.2850          | 0.9128   |
| 0.029         | 84.0  | 1764 | 0.3040          | 0.9128   |
| 0.0419        | 85.0  | 1785 | 0.1831          | 0.9439   |
| 0.0297        | 86.0  | 1806 | 0.2211          | 0.9221   |
| 0.0382        | 87.0  | 1827 | 0.2203          | 0.9346   |
| 0.0524        | 88.0  | 1848 | 0.2093          | 0.9377   |
| 0.0524        | 89.0  | 1869 | 0.2195          | 0.9252   |
| 0.0446        | 90.0  | 1890 | 0.2358          | 0.9377   |
| 0.0423        | 91.0  | 1911 | 0.2129          | 0.9283   |
| 0.0434        | 92.0  | 1932 | 0.2199          | 0.9315   |
| 0.0429        | 93.0  | 1953 | 0.1954          | 0.9470   |
| 0.0302        | 94.0  | 1974 | 0.1379          | 0.9564   |
| 0.046         | 95.0  | 1995 | 0.1609          | 0.9502   |
| 0.0247        | 96.0  | 2016 | 0.1978          | 0.9315   |
| 0.0289        | 97.0  | 2037 | 0.1872          | 0.9439   |
| 0.0452        | 98.0  | 2058 | 0.2132          | 0.9377   |
| 0.0308        | 99.0  | 2079 | 0.1592          | 0.9377   |
| 0.0274        | 100.0 | 2100 | 0.1718          | 0.9564   |


### Framework versions

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

fresh1 fresh2 fresh3