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# meat_calssify_fresh_crop_fixed_overlap_epoch100_V_0_6

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: 0.2352
- Accuracy: 0.9283

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.1152        | 1.0   | 21   | 1.0916          | 0.3801   |
| 1.0864        | 2.0   | 42   | 1.0644          | 0.4361   |
| 1.0324        | 3.0   | 63   | 1.0130          | 0.4766   |
| 0.9613        | 4.0   | 84   | 0.9579          | 0.5607   |
| 0.9331        | 5.0   | 105  | 0.8873          | 0.6044   |
| 0.8671        | 6.0   | 126  | 0.8661          | 0.5981   |
| 0.7318        | 7.0   | 147  | 0.8945          | 0.5545   |
| 0.7254        | 8.0   | 168  | 0.6857          | 0.7227   |
| 0.7335        | 9.0   | 189  | 0.7473          | 0.6822   |
| 0.5766        | 10.0  | 210  | 0.8212          | 0.6760   |
| 0.6084        | 11.0  | 231  | 0.6611          | 0.7383   |
| 0.4562        | 12.0  | 252  | 0.5661          | 0.7882   |
| 0.4669        | 13.0  | 273  | 0.6090          | 0.7664   |
| 0.4217        | 14.0  | 294  | 0.8163          | 0.6760   |
| 0.4267        | 15.0  | 315  | 0.6919          | 0.7134   |
| 0.3741        | 16.0  | 336  | 0.4754          | 0.8255   |
| 0.3325        | 17.0  | 357  | 0.5114          | 0.8069   |
| 0.298         | 18.0  | 378  | 0.5082          | 0.8069   |
| 0.2493        | 19.0  | 399  | 0.4226          | 0.8255   |
| 0.2422        | 20.0  | 420  | 0.4855          | 0.8255   |
| 0.2086        | 21.0  | 441  | 0.5766          | 0.7913   |
| 0.229         | 22.0  | 462  | 0.5744          | 0.7913   |
| 0.2352        | 23.0  | 483  | 0.4443          | 0.8318   |
| 0.2055        | 24.0  | 504  | 0.4859          | 0.8255   |
| 0.1953        | 25.0  | 525  | 0.4014          | 0.8598   |
| 0.2064        | 26.0  | 546  | 0.4137          | 0.8474   |
| 0.1801        | 27.0  | 567  | 0.4048          | 0.8536   |
| 0.1797        | 28.0  | 588  | 0.3656          | 0.8847   |
| 0.1676        | 29.0  | 609  | 0.4490          | 0.8505   |
| 0.1748        | 30.0  | 630  | 0.4745          | 0.8349   |
| 0.1896        | 31.0  | 651  | 0.4727          | 0.8411   |
| 0.1507        | 32.0  | 672  | 0.3046          | 0.8660   |
| 0.1744        | 33.0  | 693  | 0.4198          | 0.8692   |
| 0.122         | 34.0  | 714  | 0.4129          | 0.8474   |
| 0.1495        | 35.0  | 735  | 0.4908          | 0.8224   |
| 0.164         | 36.0  | 756  | 0.4992          | 0.8411   |
| 0.1876        | 37.0  | 777  | 0.3301          | 0.8816   |
| 0.287         | 38.0  | 798  | 0.4695          | 0.8349   |
| 0.14          | 39.0  | 819  | 0.4662          | 0.8318   |
| 0.1043        | 40.0  | 840  | 0.4756          | 0.8474   |
| 0.1275        | 41.0  | 861  | 0.3540          | 0.8785   |
| 0.1201        | 42.0  | 882  | 0.4236          | 0.8536   |
| 0.131         | 43.0  | 903  | 0.4375          | 0.8598   |
| 0.0773        | 44.0  | 924  | 0.4115          | 0.8723   |
| 0.1095        | 45.0  | 945  | 0.4374          | 0.8598   |
| 0.0934        | 46.0  | 966  | 0.3057          | 0.8972   |
| 0.2323        | 47.0  | 987  | 0.4779          | 0.8536   |
| 0.1005        | 48.0  | 1008 | 0.2861          | 0.9065   |
| 0.1041        | 49.0  | 1029 | 0.3541          | 0.8910   |
| 0.1067        | 50.0  | 1050 | 0.3192          | 0.8941   |
| 0.1206        | 51.0  | 1071 | 0.3898          | 0.8816   |
| 0.0798        | 52.0  | 1092 | 0.4014          | 0.8723   |
| 0.088         | 53.0  | 1113 | 0.3105          | 0.9097   |
| 0.1013        | 54.0  | 1134 | 0.3736          | 0.8785   |
| 0.0896        | 55.0  | 1155 | 0.2967          | 0.8972   |
| 0.0862        | 56.0  | 1176 | 0.3588          | 0.8879   |
| 0.0686        | 57.0  | 1197 | 0.2938          | 0.8941   |
| 0.0847        | 58.0  | 1218 | 0.4074          | 0.8910   |
| 0.0953        | 59.0  | 1239 | 0.3553          | 0.8910   |
| 0.0854        | 60.0  | 1260 | 0.2624          | 0.9097   |
| 0.0712        | 61.0  | 1281 | 0.3190          | 0.9065   |
| 0.0699        | 62.0  | 1302 | 0.2595          | 0.9190   |
| 0.0644        | 63.0  | 1323 | 0.2592          | 0.9190   |
| 0.0754        | 64.0  | 1344 | 0.2786          | 0.9003   |
| 0.0548        | 65.0  | 1365 | 0.2758          | 0.9159   |
| 0.0715        | 66.0  | 1386 | 0.2817          | 0.9003   |
| 0.0806        | 67.0  | 1407 | 0.2805          | 0.9065   |
| 0.0485        | 68.0  | 1428 | 0.2198          | 0.9159   |
| 0.0688        | 69.0  | 1449 | 0.3272          | 0.8941   |
| 0.0713        | 70.0  | 1470 | 0.4739          | 0.8754   |
| 0.0746        | 71.0  | 1491 | 0.2930          | 0.9065   |
| 0.0753        | 72.0  | 1512 | 0.3323          | 0.8972   |
| 0.0565        | 73.0  | 1533 | 0.2289          | 0.9190   |
| 0.0509        | 74.0  | 1554 | 0.5005          | 0.8536   |
| 0.0787        | 75.0  | 1575 | 0.2635          | 0.9128   |
| 0.0541        | 76.0  | 1596 | 0.3005          | 0.9128   |
| 0.0415        | 77.0  | 1617 | 0.2386          | 0.9315   |
| 0.0538        | 78.0  | 1638 | 0.3808          | 0.8972   |
| 0.064         | 79.0  | 1659 | 0.1887          | 0.9252   |
| 0.0549        | 80.0  | 1680 | 0.3037          | 0.9034   |
| 0.0547        | 81.0  | 1701 | 0.2018          | 0.9283   |
| 0.0404        | 82.0  | 1722 | 0.2307          | 0.9315   |
| 0.0438        | 83.0  | 1743 | 0.2480          | 0.9159   |
| 0.0298        | 84.0  | 1764 | 0.2932          | 0.9221   |
| 0.0409        | 85.0  | 1785 | 0.2534          | 0.9252   |
| 0.028         | 86.0  | 1806 | 0.3352          | 0.9065   |
| 0.0421        | 87.0  | 1827 | 0.3456          | 0.8972   |
| 0.0376        | 88.0  | 1848 | 0.2733          | 0.9221   |
| 0.0413        | 89.0  | 1869 | 0.3693          | 0.8941   |
| 0.035         | 90.0  | 1890 | 0.2873          | 0.9159   |
| 0.0688        | 91.0  | 1911 | 0.1962          | 0.9439   |
| 0.0438        | 92.0  | 1932 | 0.2506          | 0.9252   |
| 0.046         | 93.0  | 1953 | 0.2469          | 0.9252   |
| 0.0325        | 94.0  | 1974 | 0.2693          | 0.9190   |
| 0.0315        | 95.0  | 1995 | 0.1809          | 0.9533   |
| 0.0417        | 96.0  | 2016 | 0.2053          | 0.9315   |
| 0.0511        | 97.0  | 2037 | 0.2489          | 0.9346   |
| 0.0305        | 98.0  | 2058 | 0.2066          | 0.9315   |
| 0.0301        | 99.0  | 2079 | 0.2825          | 0.9159   |
| 0.0371        | 100.0 | 2100 | 0.2352          | 0.9283   |


### Framework versions

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

fresh1 fresh2 fresh3