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# meat_calssify_fresh_crop_fixed_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: 1.8065
- Accuracy: 0.7405

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 1.0665        | 1.0   | 630   | 1.0532          | 0.4051   |
| 1.0373        | 2.0   | 1260  | 1.0018          | 0.5063   |
| 1.1547        | 3.0   | 1890  | 1.0149          | 0.4557   |
| 1.2332        | 4.0   | 2520  | 1.0203          | 0.4937   |
| 1.2068        | 5.0   | 3150  | 1.8757          | 0.4114   |
| 1.2576        | 6.0   | 3780  | 1.1679          | 0.5570   |
| 1.2601        | 7.0   | 4410  | 1.0406          | 0.5886   |
| 1.0981        | 8.0   | 5040  | 1.1907          | 0.5949   |
| 1.0283        | 9.0   | 5670  | 1.1140          | 0.6962   |
| 1.0173        | 10.0  | 6300  | 1.3832          | 0.6582   |
| 1.0185        | 11.0  | 6930  | 1.0796          | 0.6646   |
| 0.8782        | 12.0  | 7560  | 1.4764          | 0.6582   |
| 0.8761        | 13.0  | 8190  | 1.5654          | 0.6076   |
| 0.8258        | 14.0  | 8820  | 1.4798          | 0.6456   |
| 0.8745        | 15.0  | 9450  | 2.2686          | 0.5380   |
| 0.6339        | 16.0  | 10080 | 1.5005          | 0.6835   |
| 0.6122        | 17.0  | 10710 | 1.7847          | 0.6709   |
| 0.5812        | 18.0  | 11340 | 1.6494          | 0.6962   |
| 0.54          | 19.0  | 11970 | 1.6806          | 0.6899   |
| 0.4075        | 20.0  | 12600 | 2.0121          | 0.6709   |
| 0.4847        | 21.0  | 13230 | 1.5560          | 0.7089   |
| 0.4862        | 22.0  | 13860 | 1.5739          | 0.7215   |
| 0.5239        | 23.0  | 14490 | 1.5406          | 0.6835   |
| 0.4293        | 24.0  | 15120 | 1.7675          | 0.6962   |
| 0.4592        | 25.0  | 15750 | 1.7242          | 0.7215   |
| 0.366         | 26.0  | 16380 | 1.4541          | 0.7468   |
| 0.3754        | 27.0  | 17010 | 1.8378          | 0.7089   |
| 0.356         | 28.0  | 17640 | 1.6920          | 0.7152   |
| 0.3689        | 29.0  | 18270 | 1.7062          | 0.7152   |
| 0.3305        | 30.0  | 18900 | 1.6425          | 0.7025   |
| 0.2995        | 31.0  | 19530 | 1.9092          | 0.6835   |
| 0.3692        | 32.0  | 20160 | 1.5893          | 0.7405   |
| 0.2386        | 33.0  | 20790 | 1.5449          | 0.7532   |
| 0.2427        | 34.0  | 21420 | 1.7221          | 0.7532   |
| 0.2645        | 35.0  | 22050 | 1.3437          | 0.7975   |
| 0.2673        | 36.0  | 22680 | 1.7081          | 0.7025   |
| 0.1925        | 37.0  | 23310 | 1.4535          | 0.7911   |
| 0.1304        | 38.0  | 23940 | 1.9245          | 0.7152   |
| 0.1797        | 39.0  | 24570 | 1.6966          | 0.7468   |
| 0.2092        | 40.0  | 25200 | 1.3813          | 0.7911   |
| 0.161         | 41.0  | 25830 | 1.4498          | 0.7975   |
| 0.1872        | 42.0  | 26460 | 1.6249          | 0.7595   |
| 0.1308        | 43.0  | 27090 | 1.4823          | 0.7785   |
| 0.1939        | 44.0  | 27720 | 1.4895          | 0.7848   |
| 0.1561        | 45.0  | 28350 | 1.6162          | 0.7532   |
| 0.0929        | 46.0  | 28980 | 1.4918          | 0.7911   |
| 0.0911        | 47.0  | 29610 | 1.5509          | 0.7722   |
| 0.0945        | 48.0  | 30240 | 1.4868          | 0.7848   |
| 0.0985        | 49.0  | 30870 | 1.6767          | 0.7595   |
| 0.1023        | 50.0  | 31500 | 1.8065          | 0.7405   |


### Framework versions

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

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