
<!-- 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_small_adamax_00001_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: 0.7508
- 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    | 1.3350          | 0.3571   |
| 1.346         | 2.0   | 12   | 1.2810          | 0.3810   |
| 1.346         | 3.0   | 18   | 1.2346          | 0.4048   |
| 1.107         | 4.0   | 24   | 1.1917          | 0.4048   |
| 0.9637        | 5.0   | 30   | 1.1623          | 0.3571   |
| 0.9637        | 6.0   | 36   | 1.1357          | 0.4048   |
| 0.8241        | 7.0   | 42   | 1.1137          | 0.4286   |
| 0.8241        | 8.0   | 48   | 1.0906          | 0.4286   |
| 0.6746        | 9.0   | 54   | 1.0721          | 0.4286   |
| 0.594         | 10.0  | 60   | 1.0502          | 0.4286   |
| 0.594         | 11.0  | 66   | 1.0303          | 0.4286   |
| 0.4897        | 12.0  | 72   | 1.0072          | 0.4524   |
| 0.4897        | 13.0  | 78   | 0.9837          | 0.4762   |
| 0.4223        | 14.0  | 84   | 0.9800          | 0.4762   |
| 0.3482        | 15.0  | 90   | 0.9580          | 0.5      |
| 0.3482        | 16.0  | 96   | 0.9315          | 0.5238   |
| 0.2808        | 17.0  | 102  | 0.9182          | 0.5238   |
| 0.2808        | 18.0  | 108  | 0.9032          | 0.5714   |
| 0.2441        | 19.0  | 114  | 0.8918          | 0.6190   |
| 0.2119        | 20.0  | 120  | 0.8729          | 0.6190   |
| 0.2119        | 21.0  | 126  | 0.8574          | 0.6190   |
| 0.1699        | 22.0  | 132  | 0.8454          | 0.6190   |
| 0.1699        | 23.0  | 138  | 0.8308          | 0.6190   |
| 0.1443        | 24.0  | 144  | 0.8166          | 0.6190   |
| 0.1255        | 25.0  | 150  | 0.8066          | 0.6905   |
| 0.1255        | 26.0  | 156  | 0.8088          | 0.6905   |
| 0.1078        | 27.0  | 162  | 0.7901          | 0.6905   |
| 0.1078        | 28.0  | 168  | 0.7892          | 0.6667   |
| 0.094         | 29.0  | 174  | 0.7900          | 0.6667   |
| 0.0785        | 30.0  | 180  | 0.7761          | 0.6667   |
| 0.0785        | 31.0  | 186  | 0.7673          | 0.6667   |
| 0.071         | 32.0  | 192  | 0.7632          | 0.6667   |
| 0.071         | 33.0  | 198  | 0.7572          | 0.6667   |
| 0.066         | 34.0  | 204  | 0.7549          | 0.6667   |
| 0.0595        | 35.0  | 210  | 0.7582          | 0.6667   |
| 0.0595        | 36.0  | 216  | 0.7573          | 0.6667   |
| 0.0553        | 37.0  | 222  | 0.7569          | 0.6667   |
| 0.0553        | 38.0  | 228  | 0.7526          | 0.6667   |
| 0.0524        | 39.0  | 234  | 0.7502          | 0.6667   |
| 0.0501        | 40.0  | 240  | 0.7502          | 0.6667   |
| 0.0501        | 41.0  | 246  | 0.7508          | 0.6667   |
| 0.0507        | 42.0  | 252  | 0.7508          | 0.6667   |
| 0.0507        | 43.0  | 258  | 0.7508          | 0.6667   |
| 0.0466        | 44.0  | 264  | 0.7508          | 0.6667   |
| 0.0501        | 45.0  | 270  | 0.7508          | 0.6667   |
| 0.0501        | 46.0  | 276  | 0.7508          | 0.6667   |
| 0.0512        | 47.0  | 282  | 0.7508          | 0.6667   |
| 0.0512        | 48.0  | 288  | 0.7508          | 0.6667   |
| 0.0478        | 49.0  | 294  | 0.7508          | 0.6667   |
| 0.0501        | 50.0  | 300  | 0.7508          | 0.6667   |


### Framework versions

- Transformers 4.35.0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1

01_normal 02_tapered 03_pyriform 04_amorphous