
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# hushem_5x_deit_small_adamax_00001_fold1

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: 1.0089
- Accuracy: 0.6889

## 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: 1e-05
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.2704        | 1.0   | 27   | 1.2632          | 0.3333   |
| 0.9284        | 2.0   | 54   | 1.1387          | 0.4      |
| 0.673         | 3.0   | 81   | 0.9948          | 0.5111   |
| 0.5262        | 4.0   | 108  | 0.8999          | 0.6222   |
| 0.3091        | 5.0   | 135  | 0.8487          | 0.5778   |
| 0.2356        | 6.0   | 162  | 0.7708          | 0.7333   |
| 0.1849        | 7.0   | 189  | 0.7590          | 0.7111   |
| 0.1256        | 8.0   | 216  | 0.7636          | 0.6889   |
| 0.0704        | 9.0   | 243  | 0.7602          | 0.6444   |
| 0.0451        | 10.0  | 270  | 0.7394          | 0.6667   |
| 0.0288        | 11.0  | 297  | 0.7424          | 0.7111   |
| 0.0167        | 12.0  | 324  | 0.7807          | 0.6667   |
| 0.0111        | 13.0  | 351  | 0.8113          | 0.6667   |
| 0.0073        | 14.0  | 378  | 0.8256          | 0.7111   |
| 0.006         | 15.0  | 405  | 0.8473          | 0.6889   |
| 0.0044        | 16.0  | 432  | 0.8545          | 0.6889   |
| 0.0038        | 17.0  | 459  | 0.8649          | 0.7111   |
| 0.0035        | 18.0  | 486  | 0.8829          | 0.6889   |
| 0.0029        | 19.0  | 513  | 0.8931          | 0.6889   |
| 0.0027        | 20.0  | 540  | 0.8979          | 0.6889   |
| 0.0022        | 21.0  | 567  | 0.9159          | 0.6889   |
| 0.0022        | 22.0  | 594  | 0.9078          | 0.6889   |
| 0.002         | 23.0  | 621  | 0.9310          | 0.6889   |
| 0.0018        | 24.0  | 648  | 0.9346          | 0.6889   |
| 0.0018        | 25.0  | 675  | 0.9373          | 0.6889   |
| 0.0017        | 26.0  | 702  | 0.9476          | 0.6889   |
| 0.0016        | 27.0  | 729  | 0.9510          | 0.6889   |
| 0.0014        | 28.0  | 756  | 0.9558          | 0.6889   |
| 0.0015        | 29.0  | 783  | 0.9590          | 0.6889   |
| 0.0013        | 30.0  | 810  | 0.9714          | 0.6889   |
| 0.0012        | 31.0  | 837  | 0.9702          | 0.6889   |
| 0.0012        | 32.0  | 864  | 0.9742          | 0.6889   |
| 0.0011        | 33.0  | 891  | 0.9800          | 0.6889   |
| 0.0011        | 34.0  | 918  | 0.9820          | 0.6889   |
| 0.0011        | 35.0  | 945  | 0.9877          | 0.6889   |
| 0.0011        | 36.0  | 972  | 0.9898          | 0.6889   |
| 0.001         | 37.0  | 999  | 0.9922          | 0.6889   |
| 0.001         | 38.0  | 1026 | 0.9935          | 0.6889   |
| 0.0009        | 39.0  | 1053 | 0.9969          | 0.6889   |
| 0.0009        | 40.0  | 1080 | 0.9993          | 0.6889   |
| 0.0009        | 41.0  | 1107 | 1.0018          | 0.6889   |
| 0.0009        | 42.0  | 1134 | 1.0033          | 0.6889   |
| 0.0009        | 43.0  | 1161 | 1.0054          | 0.6889   |
| 0.0009        | 44.0  | 1188 | 1.0069          | 0.6889   |
| 0.0009        | 45.0  | 1215 | 1.0080          | 0.6889   |
| 0.0009        | 46.0  | 1242 | 1.0085          | 0.6889   |
| 0.0009        | 47.0  | 1269 | 1.0088          | 0.6889   |
| 0.0009        | 48.0  | 1296 | 1.0089          | 0.6889   |
| 0.0009        | 49.0  | 1323 | 1.0089          | 0.6889   |
| 0.0009        | 50.0  | 1350 | 1.0089          | 0.6889   |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0

01_normal 02_tapered 03_pyriform 04_amorphous