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# meat_calssify_fresh_crop_fixed_overlap_V_0_1

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: 0.5094
- Accuracy: 0.9198

## 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: 1
- 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: 50

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 1.0396        | 1.0   | 1293  | 0.9865          | 0.5123   |
| 1.1023        | 2.0   | 2586  | 1.0537          | 0.5525   |
| 1.1657        | 3.0   | 3879  | 1.4125          | 0.6080   |
| 1.1606        | 4.0   | 5172  | 1.0966          | 0.4568   |
| 1.233         | 5.0   | 6465  | 1.0640          | 0.6481   |
| 1.1345        | 6.0   | 7758  | 1.2839          | 0.6451   |
| 1.1208        | 7.0   | 9051  | 1.4499          | 0.6451   |
| 1.0212        | 8.0   | 10344 | 1.1759          | 0.7068   |
| 0.891         | 9.0   | 11637 | 1.0590          | 0.7130   |
| 0.8541        | 10.0  | 12930 | 1.0337          | 0.7253   |
| 0.7985        | 11.0  | 14223 | 0.8852          | 0.7778   |
| 0.7569        | 12.0  | 15516 | 0.9469          | 0.7778   |
| 0.6847        | 13.0  | 16809 | 1.1415          | 0.7407   |
| 0.6794        | 14.0  | 18102 | 0.8935          | 0.8210   |
| 0.6455        | 15.0  | 19395 | 0.9556          | 0.7809   |
| 0.5708        | 16.0  | 20688 | 1.0258          | 0.8056   |
| 0.4988        | 17.0  | 21981 | 1.4170          | 0.7654   |
| 0.477         | 18.0  | 23274 | 0.9100          | 0.8179   |
| 0.4559        | 19.0  | 24567 | 1.0474          | 0.7994   |
| 0.4284        | 20.0  | 25860 | 0.8757          | 0.8488   |
| 0.3892        | 21.0  | 27153 | 0.9961          | 0.8241   |
| 0.419         | 22.0  | 28446 | 0.9303          | 0.8333   |
| 0.3244        | 23.0  | 29739 | 1.0301          | 0.8179   |
| 0.4107        | 24.0  | 31032 | 0.7903          | 0.8488   |
| 0.3853        | 25.0  | 32325 | 0.5818          | 0.9012   |
| 0.294         | 26.0  | 33618 | 0.9773          | 0.8426   |
| 0.2826        | 27.0  | 34911 | 0.7444          | 0.8735   |
| 0.2218        | 28.0  | 36204 | 1.0961          | 0.8426   |
| 0.3422        | 29.0  | 37497 | 0.9692          | 0.8395   |
| 0.2809        | 30.0  | 38790 | 0.8668          | 0.8673   |
| 0.2618        | 31.0  | 40083 | 0.7958          | 0.8704   |
| 0.2702        | 32.0  | 41376 | 0.6700          | 0.8796   |
| 0.253         | 33.0  | 42669 | 1.1036          | 0.8148   |
| 0.2161        | 34.0  | 43962 | 0.5197          | 0.9198   |
| 0.1727        | 35.0  | 45255 | 0.6996          | 0.8981   |
| 0.2117        | 36.0  | 46548 | 1.3509          | 0.8056   |
| 0.1967        | 37.0  | 47841 | 0.5835          | 0.9105   |
| 0.1885        | 38.0  | 49134 | 0.7260          | 0.8673   |
| 0.1445        | 39.0  | 50427 | 0.7016          | 0.8735   |
| 0.1216        | 40.0  | 51720 | 0.7880          | 0.8858   |
| 0.1552        | 41.0  | 53013 | 0.7237          | 0.8765   |
| 0.0992        | 42.0  | 54306 | 0.7155          | 0.9043   |
| 0.1047        | 43.0  | 55599 | 0.5785          | 0.9167   |
| 0.1119        | 44.0  | 56892 | 0.4751          | 0.9228   |
| 0.128         | 45.0  | 58185 | 0.6190          | 0.9043   |
| 0.1066        | 46.0  | 59478 | 0.6420          | 0.9167   |
| 0.1453        | 47.0  | 60771 | 0.5683          | 0.9198   |
| 0.0991        | 48.0  | 62064 | 0.6286          | 0.9074   |
| 0.0688        | 49.0  | 63357 | 0.5495          | 0.9228   |
| 0.0907        | 50.0  | 64650 | 0.5094          | 0.9198   |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.3.0
- Datasets 2.19.2
- Tokenizers 0.19.1

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