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# hushem_40x_deit_small_adamax_0001_fold3

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: 0.7579
- Accuracy: 0.9302

## 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: 0.0001
- 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.0315        | 1.0   | 217   | 0.2572          | 0.9070   |
| 0.0049        | 2.0   | 434   | 0.4551          | 0.8837   |
| 0.0004        | 3.0   | 651   | 0.3965          | 0.8837   |
| 0.0001        | 4.0   | 868   | 0.4995          | 0.9070   |
| 0.0           | 5.0   | 1085  | 0.3370          | 0.9535   |
| 0.0           | 6.0   | 1302  | 0.4294          | 0.9302   |
| 0.0           | 7.0   | 1519  | 0.4525          | 0.9302   |
| 0.0           | 8.0   | 1736  | 0.4672          | 0.9302   |
| 0.0           | 9.0   | 1953  | 0.4797          | 0.9302   |
| 0.0           | 10.0  | 2170  | 0.4904          | 0.9302   |
| 0.0           | 11.0  | 2387  | 0.4947          | 0.9302   |
| 0.0           | 12.0  | 2604  | 0.5020          | 0.9302   |
| 0.0           | 13.0  | 2821  | 0.5084          | 0.9302   |
| 0.0           | 14.0  | 3038  | 0.5153          | 0.9302   |
| 0.0           | 15.0  | 3255  | 0.5246          | 0.9302   |
| 0.0           | 16.0  | 3472  | 0.5296          | 0.9302   |
| 0.0           | 17.0  | 3689  | 0.5346          | 0.9302   |
| 0.0           | 18.0  | 3906  | 0.5408          | 0.9302   |
| 0.0           | 19.0  | 4123  | 0.5469          | 0.9302   |
| 0.0           | 20.0  | 4340  | 0.5538          | 0.9302   |
| 0.0           | 21.0  | 4557  | 0.5570          | 0.9302   |
| 0.0           | 22.0  | 4774  | 0.5610          | 0.9302   |
| 0.0           | 23.0  | 4991  | 0.5712          | 0.9302   |
| 0.0           | 24.0  | 5208  | 0.5753          | 0.9302   |
| 0.0           | 25.0  | 5425  | 0.5846          | 0.9302   |
| 0.0           | 26.0  | 5642  | 0.5887          | 0.9302   |
| 0.0           | 27.0  | 5859  | 0.5949          | 0.9302   |
| 0.0           | 28.0  | 6076  | 0.6007          | 0.9302   |
| 0.0           | 29.0  | 6293  | 0.6068          | 0.9302   |
| 0.0           | 30.0  | 6510  | 0.6184          | 0.9302   |
| 0.0           | 31.0  | 6727  | 0.6280          | 0.9302   |
| 0.0           | 32.0  | 6944  | 0.6394          | 0.9302   |
| 0.0           | 33.0  | 7161  | 0.6407          | 0.9302   |
| 0.0           | 34.0  | 7378  | 0.6480          | 0.9302   |
| 0.0           | 35.0  | 7595  | 0.6588          | 0.9302   |
| 0.0           | 36.0  | 7812  | 0.6700          | 0.9302   |
| 0.0           | 37.0  | 8029  | 0.6709          | 0.9302   |
| 0.0           | 38.0  | 8246  | 0.6850          | 0.9302   |
| 0.0           | 39.0  | 8463  | 0.6933          | 0.9302   |
| 0.0           | 40.0  | 8680  | 0.7079          | 0.9302   |
| 0.0           | 41.0  | 8897  | 0.7123          | 0.9302   |
| 0.0           | 42.0  | 9114  | 0.7231          | 0.9302   |
| 0.0           | 43.0  | 9331  | 0.7313          | 0.9302   |
| 0.0           | 44.0  | 9548  | 0.7417          | 0.9302   |
| 0.0           | 45.0  | 9765  | 0.7473          | 0.9302   |
| 0.0           | 46.0  | 9982  | 0.7513          | 0.9302   |
| 0.0           | 47.0  | 10199 | 0.7551          | 0.9302   |
| 0.0           | 48.0  | 10416 | 0.7564          | 0.9302   |
| 0.0           | 49.0  | 10633 | 0.7578          | 0.9302   |
| 0.0           | 50.0  | 10850 | 0.7579          | 0.9302   |


### Framework versions

- Transformers 4.32.1
- Pytorch 2.1.0+cu121
- Datasets 2.12.0
- Tokenizers 0.13.2

01_normal 02_tapered 03_pyriform 04_amorphous