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# hushem_40x_deit_small_sgd_001_fold4

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: 0.2365
- Accuracy: 0.8810

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 1.2757        | 1.0   | 219   | 1.3298          | 0.2619   |
| 1.0766        | 2.0   | 438   | 1.1919          | 0.4048   |
| 0.9095        | 3.0   | 657   | 1.0786          | 0.5476   |
| 0.7507        | 4.0   | 876   | 0.9821          | 0.5476   |
| 0.6994        | 5.0   | 1095  | 0.8850          | 0.5952   |
| 0.5864        | 6.0   | 1314  | 0.8204          | 0.6429   |
| 0.4328        | 7.0   | 1533  | 0.7576          | 0.6905   |
| 0.4293        | 8.0   | 1752  | 0.6999          | 0.7143   |
| 0.3464        | 9.0   | 1971  | 0.6320          | 0.7143   |
| 0.3175        | 10.0  | 2190  | 0.5956          | 0.7381   |
| 0.2382        | 11.0  | 2409  | 0.5588          | 0.7381   |
| 0.2672        | 12.0  | 2628  | 0.5195          | 0.7381   |
| 0.2016        | 13.0  | 2847  | 0.4850          | 0.8095   |
| 0.1832        | 14.0  | 3066  | 0.4528          | 0.8095   |
| 0.1406        | 15.0  | 3285  | 0.4338          | 0.8333   |
| 0.1305        | 16.0  | 3504  | 0.3948          | 0.8571   |
| 0.1504        | 17.0  | 3723  | 0.3785          | 0.8571   |
| 0.1139        | 18.0  | 3942  | 0.3689          | 0.8571   |
| 0.096         | 19.0  | 4161  | 0.3548          | 0.8571   |
| 0.0869        | 20.0  | 4380  | 0.3393          | 0.8571   |
| 0.0874        | 21.0  | 4599  | 0.3057          | 0.8571   |
| 0.0797        | 22.0  | 4818  | 0.2990          | 0.8571   |
| 0.0596        | 23.0  | 5037  | 0.2862          | 0.8571   |
| 0.053         | 24.0  | 5256  | 0.3012          | 0.8810   |
| 0.0562        | 25.0  | 5475  | 0.2885          | 0.8810   |
| 0.0463        | 26.0  | 5694  | 0.2676          | 0.8810   |
| 0.0374        | 27.0  | 5913  | 0.2870          | 0.8810   |
| 0.037         | 28.0  | 6132  | 0.2638          | 0.8810   |
| 0.0341        | 29.0  | 6351  | 0.2690          | 0.8810   |
| 0.0327        | 30.0  | 6570  | 0.2566          | 0.8810   |
| 0.0238        | 31.0  | 6789  | 0.2611          | 0.8810   |
| 0.0256        | 32.0  | 7008  | 0.2643          | 0.8810   |
| 0.0284        | 33.0  | 7227  | 0.2717          | 0.8810   |
| 0.0213        | 34.0  | 7446  | 0.2627          | 0.8810   |
| 0.0191        | 35.0  | 7665  | 0.2395          | 0.8810   |
| 0.0246        | 36.0  | 7884  | 0.2517          | 0.8810   |
| 0.0207        | 37.0  | 8103  | 0.2515          | 0.8810   |
| 0.0134        | 38.0  | 8322  | 0.2484          | 0.8810   |
| 0.0162        | 39.0  | 8541  | 0.2279          | 0.8810   |
| 0.0165        | 40.0  | 8760  | 0.2516          | 0.8810   |
| 0.0146        | 41.0  | 8979  | 0.2253          | 0.8810   |
| 0.0168        | 42.0  | 9198  | 0.2425          | 0.8810   |
| 0.0155        | 43.0  | 9417  | 0.2370          | 0.8810   |
| 0.0145        | 44.0  | 9636  | 0.2352          | 0.8810   |
| 0.0118        | 45.0  | 9855  | 0.2414          | 0.8810   |
| 0.0107        | 46.0  | 10074 | 0.2338          | 0.8810   |
| 0.0124        | 47.0  | 10293 | 0.2350          | 0.8810   |
| 0.0125        | 48.0  | 10512 | 0.2352          | 0.8810   |
| 0.0138        | 49.0  | 10731 | 0.2367          | 0.8810   |
| 0.0183        | 50.0  | 10950 | 0.2365          | 0.8810   |


### 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