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# meat_calssify_fresh_crop_fixed_overlap_epoch100_V_0_10

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: 0.2318
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.0968        | 1.0   | 21   | 1.0916          | 0.3551   |
| 1.0709        | 2.0   | 42   | 1.0570          | 0.4704   |
| 1.0215        | 3.0   | 63   | 1.0161          | 0.4891   |
| 0.9489        | 4.0   | 84   | 0.9513          | 0.5670   |
| 0.8937        | 5.0   | 105  | 0.8632          | 0.6106   |
| 0.7992        | 6.0   | 126  | 0.7990          | 0.6449   |
| 0.7194        | 7.0   | 147  | 0.7417          | 0.7227   |
| 0.6455        | 8.0   | 168  | 0.6491          | 0.7321   |
| 0.5874        | 9.0   | 189  | 0.6231          | 0.7072   |
| 0.5869        | 10.0  | 210  | 0.7566          | 0.6978   |
| 0.5565        | 11.0  | 231  | 0.5440          | 0.7913   |
| 0.5238        | 12.0  | 252  | 0.5628          | 0.7726   |
| 0.4397        | 13.0  | 273  | 0.5377          | 0.7882   |
| 0.3858        | 14.0  | 294  | 0.5161          | 0.7850   |
| 0.3587        | 15.0  | 315  | 0.6103          | 0.7726   |
| 0.3383        | 16.0  | 336  | 0.5065          | 0.7850   |
| 0.2967        | 17.0  | 357  | 0.4653          | 0.8224   |
| 0.4375        | 18.0  | 378  | 0.4497          | 0.8255   |
| 0.2805        | 19.0  | 399  | 0.5011          | 0.8287   |
| 0.2937        | 20.0  | 420  | 0.4294          | 0.8318   |
| 0.2917        | 21.0  | 441  | 0.4914          | 0.8224   |
| 0.2387        | 22.0  | 462  | 0.5050          | 0.8255   |
| 0.219         | 23.0  | 483  | 0.4312          | 0.8692   |
| 0.2975        | 24.0  | 504  | 0.4167          | 0.8598   |
| 0.2482        | 25.0  | 525  | 0.4272          | 0.8536   |
| 0.1913        | 26.0  | 546  | 0.3625          | 0.8660   |
| 0.1896        | 27.0  | 567  | 0.5346          | 0.7944   |
| 0.1937        | 28.0  | 588  | 0.3983          | 0.8629   |
| 0.1517        | 29.0  | 609  | 0.3777          | 0.8629   |
| 0.3356        | 30.0  | 630  | 0.3373          | 0.8941   |
| 0.1562        | 31.0  | 651  | 0.3154          | 0.8879   |
| 0.1494        | 32.0  | 672  | 0.3680          | 0.8692   |
| 0.1677        | 33.0  | 693  | 0.3984          | 0.8629   |
| 0.2689        | 34.0  | 714  | 0.2916          | 0.8910   |
| 0.1302        | 35.0  | 735  | 0.3458          | 0.8754   |
| 0.1374        | 36.0  | 756  | 0.2694          | 0.9065   |
| 0.2007        | 37.0  | 777  | 0.3715          | 0.8723   |
| 0.1404        | 38.0  | 798  | 0.4245          | 0.8723   |
| 0.1154        | 39.0  | 819  | 0.4718          | 0.8442   |
| 0.2125        | 40.0  | 840  | 0.3549          | 0.8910   |
| 0.1087        | 41.0  | 861  | 0.4262          | 0.8567   |
| 0.1156        | 42.0  | 882  | 0.3013          | 0.8910   |
| 0.1011        | 43.0  | 903  | 0.3019          | 0.9097   |
| 0.11          | 44.0  | 924  | 0.2630          | 0.9128   |
| 0.1233        | 45.0  | 945  | 0.3000          | 0.8972   |
| 0.1236        | 46.0  | 966  | 0.3547          | 0.8660   |
| 0.1571        | 47.0  | 987  | 0.3384          | 0.8879   |
| 0.0855        | 48.0  | 1008 | 0.3221          | 0.8816   |
| 0.1155        | 49.0  | 1029 | 0.4779          | 0.8536   |
| 0.1089        | 50.0  | 1050 | 0.3355          | 0.9034   |
| 0.0939        | 51.0  | 1071 | 0.2130          | 0.9221   |
| 0.0826        | 52.0  | 1092 | 0.3103          | 0.9097   |
| 0.0943        | 53.0  | 1113 | 0.3179          | 0.9034   |
| 0.0574        | 54.0  | 1134 | 0.3351          | 0.8972   |
| 0.0818        | 55.0  | 1155 | 0.2165          | 0.9315   |
| 0.0863        | 56.0  | 1176 | 0.3347          | 0.8879   |
| 0.0963        | 57.0  | 1197 | 0.3789          | 0.8972   |
| 0.0762        | 58.0  | 1218 | 0.3579          | 0.8972   |
| 0.0898        | 59.0  | 1239 | 0.2550          | 0.9159   |
| 0.0802        | 60.0  | 1260 | 0.2112          | 0.9221   |
| 0.0698        | 61.0  | 1281 | 0.3252          | 0.9097   |
| 0.0764        | 62.0  | 1302 | 0.4277          | 0.8754   |
| 0.0781        | 63.0  | 1323 | 0.3593          | 0.8879   |
| 0.0939        | 64.0  | 1344 | 0.3397          | 0.8941   |
| 0.0669        | 65.0  | 1365 | 0.3701          | 0.8847   |
| 0.0632        | 66.0  | 1386 | 0.2624          | 0.9097   |
| 0.0569        | 67.0  | 1407 | 0.2987          | 0.9221   |
| 0.0655        | 68.0  | 1428 | 0.3286          | 0.9003   |
| 0.0581        | 69.0  | 1449 | 0.2540          | 0.9283   |
| 0.0668        | 70.0  | 1470 | 0.2397          | 0.9346   |
| 0.0639        | 71.0  | 1491 | 0.2721          | 0.9190   |
| 0.0617        | 72.0  | 1512 | 0.2059          | 0.9377   |
| 0.0555        | 73.0  | 1533 | 0.4196          | 0.8879   |
| 0.0515        | 74.0  | 1554 | 0.2260          | 0.9346   |
| 0.0494        | 75.0  | 1575 | 0.3137          | 0.9097   |
| 0.0425        | 76.0  | 1596 | 0.3027          | 0.9128   |
| 0.0529        | 77.0  | 1617 | 0.2964          | 0.9221   |
| 0.0473        | 78.0  | 1638 | 0.2776          | 0.9190   |
| 0.0629        | 79.0  | 1659 | 0.2397          | 0.9346   |
| 0.0417        | 80.0  | 1680 | 0.2041          | 0.9408   |
| 0.0437        | 81.0  | 1701 | 0.2451          | 0.9408   |
| 0.0444        | 82.0  | 1722 | 0.2813          | 0.9315   |
| 0.0561        | 83.0  | 1743 | 0.2596          | 0.9159   |
| 0.0458        | 84.0  | 1764 | 0.2085          | 0.9346   |
| 0.0653        | 85.0  | 1785 | 0.3033          | 0.9221   |
| 0.0301        | 86.0  | 1806 | 0.1604          | 0.9470   |
| 0.0441        | 87.0  | 1827 | 0.3603          | 0.8941   |
| 0.0297        | 88.0  | 1848 | 0.2406          | 0.9377   |
| 0.0472        | 89.0  | 1869 | 0.3045          | 0.9190   |
| 0.0421        | 90.0  | 1890 | 0.2231          | 0.9377   |
| 0.0391        | 91.0  | 1911 | 0.2259          | 0.9439   |
| 0.0418        | 92.0  | 1932 | 0.2433          | 0.9377   |
| 0.0405        | 93.0  | 1953 | 0.2753          | 0.9221   |
| 0.0338        | 94.0  | 1974 | 0.1519          | 0.9533   |
| 0.0355        | 95.0  | 1995 | 0.2370          | 0.9408   |
| 0.028         | 96.0  | 2016 | 0.2116          | 0.9346   |
| 0.0248        | 97.0  | 2037 | 0.2833          | 0.9283   |
| 0.033         | 98.0  | 2058 | 0.2603          | 0.9221   |
| 0.0304        | 99.0  | 2079 | 0.2598          | 0.9252   |
| 0.0148        | 100.0 | 2100 | 0.2318          | 0.9439   |


### Framework versions

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

fresh1 fresh2 fresh3