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# hushem_40x_deit_base_sgd_0001_fold5

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: 1.1678
- Accuracy: 0.5122

## 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: 0.0001
- 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 1.3902        | 1.0   | 220   | 1.3668          | 0.2683   |
| 1.375         | 2.0   | 440   | 1.3610          | 0.2927   |
| 1.3643        | 3.0   | 660   | 1.3560          | 0.2683   |
| 1.3352        | 4.0   | 880   | 1.3513          | 0.2683   |
| 1.343         | 5.0   | 1100  | 1.3466          | 0.2683   |
| 1.2985        | 6.0   | 1320  | 1.3416          | 0.2683   |
| 1.3152        | 7.0   | 1540  | 1.3365          | 0.2927   |
| 1.2618        | 8.0   | 1760  | 1.3311          | 0.3171   |
| 1.2728        | 9.0   | 1980  | 1.3254          | 0.3415   |
| 1.2604        | 10.0  | 2200  | 1.3195          | 0.3415   |
| 1.2446        | 11.0  | 2420  | 1.3136          | 0.3415   |
| 1.2322        | 12.0  | 2640  | 1.3076          | 0.3902   |
| 1.2519        | 13.0  | 2860  | 1.3017          | 0.4146   |
| 1.2115        | 14.0  | 3080  | 1.2958          | 0.4146   |
| 1.2112        | 15.0  | 3300  | 1.2899          | 0.4390   |
| 1.1892        | 16.0  | 3520  | 1.2841          | 0.4390   |
| 1.1942        | 17.0  | 3740  | 1.2784          | 0.4390   |
| 1.2008        | 18.0  | 3960  | 1.2727          | 0.4390   |
| 1.1853        | 19.0  | 4180  | 1.2671          | 0.4390   |
| 1.1573        | 20.0  | 4400  | 1.2615          | 0.4634   |
| 1.1577        | 21.0  | 4620  | 1.2560          | 0.4634   |
| 1.1317        | 22.0  | 4840  | 1.2506          | 0.4634   |
| 1.1597        | 23.0  | 5060  | 1.2453          | 0.4878   |
| 1.1283        | 24.0  | 5280  | 1.2401          | 0.4878   |
| 1.1168        | 25.0  | 5500  | 1.2349          | 0.4634   |
| 1.142         | 26.0  | 5720  | 1.2300          | 0.4634   |
| 1.1324        | 27.0  | 5940  | 1.2251          | 0.4634   |
| 1.1074        | 28.0  | 6160  | 1.2203          | 0.4634   |
| 1.107         | 29.0  | 6380  | 1.2157          | 0.4634   |
| 1.098         | 30.0  | 6600  | 1.2113          | 0.4634   |
| 1.1034        | 31.0  | 6820  | 1.2071          | 0.4634   |
| 1.0941        | 32.0  | 7040  | 1.2031          | 0.4634   |
| 1.0839        | 33.0  | 7260  | 1.1993          | 0.4634   |
| 1.0528        | 34.0  | 7480  | 1.1956          | 0.4634   |
| 1.0292        | 35.0  | 7700  | 1.1922          | 0.4634   |
| 1.0585        | 36.0  | 7920  | 1.1890          | 0.4634   |
| 1.0434        | 37.0  | 8140  | 1.1859          | 0.4634   |
| 1.0597        | 38.0  | 8360  | 1.1831          | 0.4634   |
| 1.0626        | 39.0  | 8580  | 1.1805          | 0.4634   |
| 1.0375        | 40.0  | 8800  | 1.1782          | 0.4634   |
| 1.0422        | 41.0  | 9020  | 1.1761          | 0.4634   |
| 1.0304        | 42.0  | 9240  | 1.1742          | 0.4634   |
| 1.0373        | 43.0  | 9460  | 1.1726          | 0.4878   |
| 1.0134        | 44.0  | 9680  | 1.1712          | 0.4878   |
| 1.0323        | 45.0  | 9900  | 1.1701          | 0.4878   |
| 1.0327        | 46.0  | 10120 | 1.1692          | 0.5122   |
| 1.0599        | 47.0  | 10340 | 1.1685          | 0.5122   |
| 1.0079        | 48.0  | 10560 | 1.1681          | 0.5122   |
| 1.0145        | 49.0  | 10780 | 1.1679          | 0.5122   |
| 1.0358        | 50.0  | 11000 | 1.1678          | 0.5122   |


### 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