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# hushem_1x_deit_small_adamax_00001_fold5

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: 0.7730
- Accuracy: 0.6585

## 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    | 1.3080          | 0.3171   |
| 1.348         | 2.0   | 12   | 1.2421          | 0.3659   |
| 1.348         | 3.0   | 18   | 1.1840          | 0.4634   |
| 1.1221        | 4.0   | 24   | 1.1443          | 0.4634   |
| 0.9962        | 5.0   | 30   | 1.1209          | 0.4634   |
| 0.9962        | 6.0   | 36   | 1.0884          | 0.5366   |
| 0.8532        | 7.0   | 42   | 1.0512          | 0.5122   |
| 0.8532        | 8.0   | 48   | 1.0147          | 0.5366   |
| 0.73          | 9.0   | 54   | 0.9886          | 0.5366   |
| 0.61          | 10.0  | 60   | 0.9683          | 0.5610   |
| 0.61          | 11.0  | 66   | 0.9452          | 0.5854   |
| 0.5241        | 12.0  | 72   | 0.9201          | 0.6341   |
| 0.5241        | 13.0  | 78   | 0.9013          | 0.6341   |
| 0.4293        | 14.0  | 84   | 0.8851          | 0.6341   |
| 0.3674        | 15.0  | 90   | 0.8707          | 0.6341   |
| 0.3674        | 16.0  | 96   | 0.8542          | 0.6341   |
| 0.304         | 17.0  | 102  | 0.8474          | 0.6341   |
| 0.304         | 18.0  | 108  | 0.8370          | 0.6341   |
| 0.2449        | 19.0  | 114  | 0.8233          | 0.6341   |
| 0.2119        | 20.0  | 120  | 0.8193          | 0.6341   |
| 0.2119        | 21.0  | 126  | 0.8116          | 0.6341   |
| 0.1788        | 22.0  | 132  | 0.8051          | 0.6341   |
| 0.1788        | 23.0  | 138  | 0.7954          | 0.6341   |
| 0.1445        | 24.0  | 144  | 0.7897          | 0.6341   |
| 0.1262        | 25.0  | 150  | 0.7881          | 0.6829   |
| 0.1262        | 26.0  | 156  | 0.7818          | 0.6585   |
| 0.1066        | 27.0  | 162  | 0.7872          | 0.6829   |
| 0.1066        | 28.0  | 168  | 0.7762          | 0.6585   |
| 0.0891        | 29.0  | 174  | 0.7687          | 0.6585   |
| 0.0806        | 30.0  | 180  | 0.7658          | 0.6829   |
| 0.0806        | 31.0  | 186  | 0.7688          | 0.6829   |
| 0.0692        | 32.0  | 192  | 0.7732          | 0.6829   |
| 0.0692        | 33.0  | 198  | 0.7763          | 0.6585   |
| 0.0592        | 34.0  | 204  | 0.7749          | 0.6585   |
| 0.0587        | 35.0  | 210  | 0.7694          | 0.6829   |
| 0.0587        | 36.0  | 216  | 0.7701          | 0.6829   |
| 0.0549        | 37.0  | 222  | 0.7733          | 0.6585   |
| 0.0549        | 38.0  | 228  | 0.7741          | 0.6585   |
| 0.0463        | 39.0  | 234  | 0.7744          | 0.6585   |
| 0.0481        | 40.0  | 240  | 0.7732          | 0.6585   |
| 0.0481        | 41.0  | 246  | 0.7732          | 0.6585   |
| 0.0468        | 42.0  | 252  | 0.7730          | 0.6585   |
| 0.0468        | 43.0  | 258  | 0.7730          | 0.6585   |
| 0.0455        | 44.0  | 264  | 0.7730          | 0.6585   |
| 0.0473        | 45.0  | 270  | 0.7730          | 0.6585   |
| 0.0473        | 46.0  | 276  | 0.7730          | 0.6585   |
| 0.0444        | 47.0  | 282  | 0.7730          | 0.6585   |
| 0.0444        | 48.0  | 288  | 0.7730          | 0.6585   |
| 0.048         | 49.0  | 294  | 0.7730          | 0.6585   |
| 0.0476        | 50.0  | 300  | 0.7730          | 0.6585   |


### 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