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# hushem_40x_deit_small_sgd_001_fold3

This model is a fine-tuned version of [facebook/deit-small-patch16-224](https://huggingface.co/facebook/deit-small-patch16-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3304
- Accuracy: 0.8837

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 1.2372        | 1.0   | 217   | 1.2798          | 0.3488   |
| 1.0621        | 2.0   | 434   | 1.1335          | 0.5814   |
| 0.8881        | 3.0   | 651   | 1.0243          | 0.5814   |
| 0.7868        | 4.0   | 868   | 0.9174          | 0.6279   |
| 0.6948        | 5.0   | 1085  | 0.8587          | 0.6279   |
| 0.5714        | 6.0   | 1302  | 0.7810          | 0.7209   |
| 0.4585        | 7.0   | 1519  | 0.7011          | 0.8140   |
| 0.4277        | 8.0   | 1736  | 0.6580          | 0.7907   |
| 0.3688        | 9.0   | 1953  | 0.6164          | 0.8140   |
| 0.2836        | 10.0  | 2170  | 0.5578          | 0.8140   |
| 0.2148        | 11.0  | 2387  | 0.5322          | 0.8140   |
| 0.2211        | 12.0  | 2604  | 0.5199          | 0.8140   |
| 0.2014        | 13.0  | 2821  | 0.4865          | 0.8140   |
| 0.1799        | 14.0  | 3038  | 0.4815          | 0.8140   |
| 0.1565        | 15.0  | 3255  | 0.4749          | 0.7907   |
| 0.1129        | 16.0  | 3472  | 0.4440          | 0.8372   |
| 0.0992        | 17.0  | 3689  | 0.4542          | 0.7907   |
| 0.1           | 18.0  | 3906  | 0.4290          | 0.8140   |
| 0.0944        | 19.0  | 4123  | 0.4149          | 0.8140   |
| 0.0856        | 20.0  | 4340  | 0.4111          | 0.8372   |
| 0.0816        | 21.0  | 4557  | 0.4115          | 0.8140   |
| 0.0563        | 22.0  | 4774  | 0.3956          | 0.7907   |
| 0.0625        | 23.0  | 4991  | 0.3834          | 0.7907   |
| 0.0683        | 24.0  | 5208  | 0.3893          | 0.7907   |
| 0.0454        | 25.0  | 5425  | 0.3773          | 0.8140   |
| 0.0571        | 26.0  | 5642  | 0.3874          | 0.7907   |
| 0.0322        | 27.0  | 5859  | 0.3743          | 0.8140   |
| 0.0339        | 28.0  | 6076  | 0.3713          | 0.8372   |
| 0.0345        | 29.0  | 6293  | 0.3616          | 0.8372   |
| 0.0434        | 30.0  | 6510  | 0.3686          | 0.8372   |
| 0.0377        | 31.0  | 6727  | 0.3495          | 0.8605   |
| 0.0295        | 32.0  | 6944  | 0.3476          | 0.8372   |
| 0.0279        | 33.0  | 7161  | 0.3534          | 0.8605   |
| 0.0232        | 34.0  | 7378  | 0.3489          | 0.8372   |
| 0.0275        | 35.0  | 7595  | 0.3346          | 0.8837   |
| 0.0214        | 36.0  | 7812  | 0.3309          | 0.8605   |
| 0.018         | 37.0  | 8029  | 0.3342          | 0.8605   |
| 0.0167        | 38.0  | 8246  | 0.3289          | 0.8837   |
| 0.0196        | 39.0  | 8463  | 0.3389          | 0.8605   |
| 0.0269        | 40.0  | 8680  | 0.3388          | 0.8605   |
| 0.0126        | 41.0  | 8897  | 0.3309          | 0.8605   |
| 0.0119        | 42.0  | 9114  | 0.3316          | 0.8837   |
| 0.0174        | 43.0  | 9331  | 0.3268          | 0.8837   |
| 0.0199        | 44.0  | 9548  | 0.3304          | 0.8837   |
| 0.0115        | 45.0  | 9765  | 0.3378          | 0.8605   |
| 0.0138        | 46.0  | 9982  | 0.3301          | 0.8837   |
| 0.0107        | 47.0  | 10199 | 0.3312          | 0.8605   |
| 0.0108        | 48.0  | 10416 | 0.3294          | 0.9070   |
| 0.0125        | 49.0  | 10633 | 0.3301          | 0.8837   |
| 0.0148        | 50.0  | 10850 | 0.3304          | 0.8837   |


### 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