
<!-- 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_001_fold2

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: 5.1428
- Accuracy: 0.5556

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.3869        | 1.0   | 27   | 1.3961          | 0.2444   |
| 1.1374        | 2.0   | 54   | 1.4468          | 0.4222   |
| 0.928         | 3.0   | 81   | 1.5182          | 0.5111   |
| 1.0235        | 4.0   | 108  | 1.5182          | 0.5333   |
| 0.797         | 5.0   | 135  | 1.2483          | 0.3778   |
| 0.8238        | 6.0   | 162  | 1.2902          | 0.5333   |
| 0.7166        | 7.0   | 189  | 1.5715          | 0.4889   |
| 0.6354        | 8.0   | 216  | 1.5461          | 0.4      |
| 0.5304        | 9.0   | 243  | 2.1851          | 0.5111   |
| 0.5677        | 10.0  | 270  | 2.3132          | 0.4222   |
| 0.4857        | 11.0  | 297  | 2.4291          | 0.5556   |
| 0.3582        | 12.0  | 324  | 2.5091          | 0.4444   |
| 0.3326        | 13.0  | 351  | 2.6635          | 0.5556   |
| 0.3365        | 14.0  | 378  | 2.7106          | 0.6      |
| 0.3145        | 15.0  | 405  | 3.0588          | 0.5556   |
| 0.1837        | 16.0  | 432  | 3.1156          | 0.5778   |
| 0.277         | 17.0  | 459  | 2.8497          | 0.5778   |
| 0.1371        | 18.0  | 486  | 3.1885          | 0.6222   |
| 0.2815        | 19.0  | 513  | 3.0392          | 0.5778   |
| 0.1153        | 20.0  | 540  | 3.8749          | 0.5778   |
| 0.2394        | 21.0  | 567  | 2.9618          | 0.5111   |
| 0.2767        | 22.0  | 594  | 2.7586          | 0.5333   |
| 0.0906        | 23.0  | 621  | 4.0821          | 0.5333   |
| 0.1246        | 24.0  | 648  | 3.7041          | 0.4889   |
| 0.0582        | 25.0  | 675  | 4.8478          | 0.5778   |
| 0.0262        | 26.0  | 702  | 3.9021          | 0.5556   |
| 0.0436        | 27.0  | 729  | 4.3474          | 0.5778   |
| 0.0484        | 28.0  | 756  | 4.4662          | 0.5778   |
| 0.0031        | 29.0  | 783  | 4.8306          | 0.5778   |
| 0.0039        | 30.0  | 810  | 4.6722          | 0.5778   |
| 0.023         | 31.0  | 837  | 4.3620          | 0.5556   |
| 0.0011        | 32.0  | 864  | 4.9095          | 0.5556   |
| 0.0004        | 33.0  | 891  | 4.8409          | 0.5333   |
| 0.0003        | 34.0  | 918  | 5.0267          | 0.5556   |
| 0.0001        | 35.0  | 945  | 5.0410          | 0.5556   |
| 0.0001        | 36.0  | 972  | 5.0651          | 0.5556   |
| 0.0001        | 37.0  | 999  | 5.0839          | 0.5556   |
| 0.0001        | 38.0  | 1026 | 5.0966          | 0.5556   |
| 0.0001        | 39.0  | 1053 | 5.1068          | 0.5556   |
| 0.0           | 40.0  | 1080 | 5.1156          | 0.5556   |
| 0.0001        | 41.0  | 1107 | 5.1226          | 0.5556   |
| 0.0001        | 42.0  | 1134 | 5.1286          | 0.5556   |
| 0.0001        | 43.0  | 1161 | 5.1335          | 0.5556   |
| 0.0           | 44.0  | 1188 | 5.1362          | 0.5556   |
| 0.0           | 45.0  | 1215 | 5.1386          | 0.5556   |
| 0.0001        | 46.0  | 1242 | 5.1410          | 0.5556   |
| 0.0           | 47.0  | 1269 | 5.1424          | 0.5556   |
| 0.0001        | 48.0  | 1296 | 5.1428          | 0.5556   |
| 0.0           | 49.0  | 1323 | 5.1428          | 0.5556   |
| 0.0001        | 50.0  | 1350 | 5.1428          | 0.5556   |


### 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