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# hushem_40x_deit_base_sgd_001_fold3

This model is a fine-tuned version of [facebook/deit-base-patch16-224](https://huggingface.co/facebook/deit-base-patch16-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4834
- Accuracy: 0.7674

## 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: 0.001
- train_batch_size: 32
- eval_batch_size: 32
- 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 1.2567        | 1.0   | 217   | 1.3908          | 0.3023   |
| 1.1156        | 2.0   | 434   | 1.3183          | 0.4186   |
| 0.9891        | 3.0   | 651   | 1.2352          | 0.5116   |
| 0.902         | 4.0   | 868   | 1.1401          | 0.5814   |
| 0.7383        | 5.0   | 1085  | 1.0533          | 0.6047   |
| 0.6659        | 6.0   | 1302  | 0.9783          | 0.6279   |
| 0.577         | 7.0   | 1519  | 0.9088          | 0.6047   |
| 0.5084        | 8.0   | 1736  | 0.8504          | 0.6512   |
| 0.4618        | 9.0   | 1953  | 0.8112          | 0.6512   |
| 0.3986        | 10.0  | 2170  | 0.7644          | 0.6744   |
| 0.3262        | 11.0  | 2387  | 0.7405          | 0.6744   |
| 0.3187        | 12.0  | 2604  | 0.7073          | 0.7442   |
| 0.287         | 13.0  | 2821  | 0.6756          | 0.7442   |
| 0.2667        | 14.0  | 3038  | 0.6524          | 0.7674   |
| 0.2566        | 15.0  | 3255  | 0.6373          | 0.7674   |
| 0.2206        | 16.0  | 3472  | 0.6121          | 0.7674   |
| 0.1851        | 17.0  | 3689  | 0.6018          | 0.7674   |
| 0.1802        | 18.0  | 3906  | 0.5901          | 0.7674   |
| 0.1691        | 19.0  | 4123  | 0.5735          | 0.7674   |
| 0.1555        | 20.0  | 4340  | 0.5642          | 0.7674   |
| 0.1532        | 21.0  | 4557  | 0.5647          | 0.7907   |
| 0.1287        | 22.0  | 4774  | 0.5473          | 0.7907   |
| 0.1172        | 23.0  | 4991  | 0.5337          | 0.7907   |
| 0.1215        | 24.0  | 5208  | 0.5344          | 0.7907   |
| 0.1           | 25.0  | 5425  | 0.5177          | 0.7907   |
| 0.1218        | 26.0  | 5642  | 0.5181          | 0.7907   |
| 0.0935        | 27.0  | 5859  | 0.5065          | 0.7907   |
| 0.0833        | 28.0  | 6076  | 0.4985          | 0.7907   |
| 0.0714        | 29.0  | 6293  | 0.4998          | 0.7907   |
| 0.0825        | 30.0  | 6510  | 0.4944          | 0.7907   |
| 0.0754        | 31.0  | 6727  | 0.4956          | 0.7674   |
| 0.0765        | 32.0  | 6944  | 0.4881          | 0.7674   |
| 0.0774        | 33.0  | 7161  | 0.4958          | 0.7674   |
| 0.057         | 34.0  | 7378  | 0.4894          | 0.7674   |
| 0.0663        | 35.0  | 7595  | 0.4882          | 0.7674   |
| 0.059         | 36.0  | 7812  | 0.4848          | 0.7674   |
| 0.0537        | 37.0  | 8029  | 0.4865          | 0.7674   |
| 0.0454        | 38.0  | 8246  | 0.4882          | 0.7674   |
| 0.0514        | 39.0  | 8463  | 0.4854          | 0.7674   |
| 0.0629        | 40.0  | 8680  | 0.4861          | 0.7674   |
| 0.0453        | 41.0  | 8897  | 0.4865          | 0.7674   |
| 0.0447        | 42.0  | 9114  | 0.4837          | 0.7674   |
| 0.0452        | 43.0  | 9331  | 0.4805          | 0.7907   |
| 0.0545        | 44.0  | 9548  | 0.4818          | 0.7907   |
| 0.0444        | 45.0  | 9765  | 0.4816          | 0.7907   |
| 0.0454        | 46.0  | 9982  | 0.4835          | 0.7674   |
| 0.0369        | 47.0  | 10199 | 0.4841          | 0.7674   |
| 0.0401        | 48.0  | 10416 | 0.4827          | 0.7907   |
| 0.0524        | 49.0  | 10633 | 0.4835          | 0.7674   |
| 0.0394        | 50.0  | 10850 | 0.4834          | 0.7674   |


### Framework versions

- Transformers 4.32.1
- Pytorch 2.1.0+cu121
- Datasets 2.12.0
- Tokenizers 0.13.2

01_normal 02_tapered 03_pyriform 04_amorphous