
<!-- 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_1x_deit_base_rms_00001_fold1

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: 1.1852
- Accuracy: 0.6667

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 6    | 1.3238          | 0.3556   |
| 1.1473        | 2.0   | 12   | 1.1817          | 0.5111   |
| 1.1473        | 3.0   | 18   | 1.2929          | 0.4222   |
| 0.433         | 4.0   | 24   | 1.0792          | 0.6      |
| 0.0993        | 5.0   | 30   | 0.8040          | 0.7111   |
| 0.0993        | 6.0   | 36   | 1.0632          | 0.6      |
| 0.0211        | 7.0   | 42   | 1.0076          | 0.6222   |
| 0.0211        | 8.0   | 48   | 1.0203          | 0.6444   |
| 0.0072        | 9.0   | 54   | 1.0447          | 0.6444   |
| 0.0049        | 10.0  | 60   | 1.0417          | 0.6667   |
| 0.0049        | 11.0  | 66   | 1.0618          | 0.6222   |
| 0.0035        | 12.0  | 72   | 1.0538          | 0.6667   |
| 0.0035        | 13.0  | 78   | 1.0657          | 0.6667   |
| 0.0028        | 14.0  | 84   | 1.0857          | 0.6667   |
| 0.0023        | 15.0  | 90   | 1.0998          | 0.6667   |
| 0.0023        | 16.0  | 96   | 1.1075          | 0.6667   |
| 0.002         | 17.0  | 102  | 1.1046          | 0.6667   |
| 0.002         | 18.0  | 108  | 1.1222          | 0.6667   |
| 0.0017        | 19.0  | 114  | 1.1291          | 0.6667   |
| 0.0015        | 20.0  | 120  | 1.1399          | 0.6667   |
| 0.0015        | 21.0  | 126  | 1.1378          | 0.6667   |
| 0.0014        | 22.0  | 132  | 1.1446          | 0.6667   |
| 0.0014        | 23.0  | 138  | 1.1459          | 0.6667   |
| 0.0012        | 24.0  | 144  | 1.1478          | 0.6667   |
| 0.0011        | 25.0  | 150  | 1.1522          | 0.6667   |
| 0.0011        | 26.0  | 156  | 1.1509          | 0.6667   |
| 0.0011        | 27.0  | 162  | 1.1558          | 0.6667   |
| 0.0011        | 28.0  | 168  | 1.1564          | 0.6667   |
| 0.001         | 29.0  | 174  | 1.1604          | 0.6667   |
| 0.001         | 30.0  | 180  | 1.1663          | 0.6667   |
| 0.001         | 31.0  | 186  | 1.1692          | 0.6667   |
| 0.0009        | 32.0  | 192  | 1.1711          | 0.6667   |
| 0.0009        | 33.0  | 198  | 1.1736          | 0.6667   |
| 0.0009        | 34.0  | 204  | 1.1741          | 0.6667   |
| 0.0008        | 35.0  | 210  | 1.1751          | 0.6667   |
| 0.0008        | 36.0  | 216  | 1.1789          | 0.6667   |
| 0.0008        | 37.0  | 222  | 1.1812          | 0.6667   |
| 0.0008        | 38.0  | 228  | 1.1837          | 0.6667   |
| 0.0008        | 39.0  | 234  | 1.1842          | 0.6667   |
| 0.0008        | 40.0  | 240  | 1.1850          | 0.6667   |
| 0.0008        | 41.0  | 246  | 1.1853          | 0.6667   |
| 0.0008        | 42.0  | 252  | 1.1852          | 0.6667   |
| 0.0008        | 43.0  | 258  | 1.1852          | 0.6667   |
| 0.0008        | 44.0  | 264  | 1.1852          | 0.6667   |
| 0.0008        | 45.0  | 270  | 1.1852          | 0.6667   |
| 0.0008        | 46.0  | 276  | 1.1852          | 0.6667   |
| 0.0008        | 47.0  | 282  | 1.1852          | 0.6667   |
| 0.0008        | 48.0  | 288  | 1.1852          | 0.6667   |
| 0.0008        | 49.0  | 294  | 1.1852          | 0.6667   |
| 0.0008        | 50.0  | 300  | 1.1852          | 0.6667   |


### 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