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# hushem_40x_deit_tiny_sgd_0001_fold3

This model is a fine-tuned version of [facebook/deit-tiny-patch16-224](https://huggingface.co/facebook/deit-tiny-patch16-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9959
- Accuracy: 0.6744

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 1.4187        | 1.0   | 217   | 1.4585          | 0.3023   |
| 1.3875        | 2.0   | 434   | 1.4331          | 0.2791   |
| 1.3134        | 3.0   | 651   | 1.4120          | 0.3256   |
| 1.3061        | 4.0   | 868   | 1.3930          | 0.3488   |
| 1.3015        | 5.0   | 1085  | 1.3762          | 0.3721   |
| 1.2507        | 6.0   | 1302  | 1.3597          | 0.3721   |
| 1.2542        | 7.0   | 1519  | 1.3427          | 0.3721   |
| 1.2153        | 8.0   | 1736  | 1.3276          | 0.3721   |
| 1.2187        | 9.0   | 1953  | 1.3127          | 0.4186   |
| 1.1894        | 10.0  | 2170  | 1.2981          | 0.4186   |
| 1.1545        | 11.0  | 2387  | 1.2843          | 0.4186   |
| 1.1296        | 12.0  | 2604  | 1.2697          | 0.4419   |
| 1.1425        | 13.0  | 2821  | 1.2546          | 0.4651   |
| 1.1006        | 14.0  | 3038  | 1.2420          | 0.4884   |
| 1.101         | 15.0  | 3255  | 1.2295          | 0.4884   |
| 1.0751        | 16.0  | 3472  | 1.2159          | 0.4884   |
| 1.0907        | 17.0  | 3689  | 1.2031          | 0.4884   |
| 1.047         | 18.0  | 3906  | 1.1903          | 0.5116   |
| 1.0396        | 19.0  | 4123  | 1.1781          | 0.5581   |
| 1.0151        | 20.0  | 4340  | 1.1663          | 0.5581   |
| 1.0071        | 21.0  | 4557  | 1.1547          | 0.5581   |
| 0.9605        | 22.0  | 4774  | 1.1441          | 0.5814   |
| 0.9825        | 23.0  | 4991  | 1.1328          | 0.6047   |
| 0.9877        | 24.0  | 5208  | 1.1238          | 0.6047   |
| 0.944         | 25.0  | 5425  | 1.1139          | 0.6047   |
| 1.0028        | 26.0  | 5642  | 1.1046          | 0.6047   |
| 0.9583        | 27.0  | 5859  | 1.0948          | 0.6279   |
| 0.9319        | 28.0  | 6076  | 1.0861          | 0.6279   |
| 0.8861        | 29.0  | 6293  | 1.0779          | 0.6279   |
| 0.9631        | 30.0  | 6510  | 1.0704          | 0.6512   |
| 0.8801        | 31.0  | 6727  | 1.0625          | 0.6512   |
| 0.9404        | 32.0  | 6944  | 1.0548          | 0.6512   |
| 0.9252        | 33.0  | 7161  | 1.0485          | 0.6512   |
| 0.8258        | 34.0  | 7378  | 1.0422          | 0.6512   |
| 0.8739        | 35.0  | 7595  | 1.0361          | 0.6744   |
| 0.8975        | 36.0  | 7812  | 1.0306          | 0.6744   |
| 0.8371        | 37.0  | 8029  | 1.0260          | 0.6744   |
| 0.8695        | 38.0  | 8246  | 1.0212          | 0.6744   |
| 0.8346        | 39.0  | 8463  | 1.0171          | 0.6744   |
| 0.8685        | 40.0  | 8680  | 1.0135          | 0.6744   |
| 0.8448        | 41.0  | 8897  | 1.0098          | 0.6744   |
| 0.8514        | 42.0  | 9114  | 1.0067          | 0.6744   |
| 0.8326        | 43.0  | 9331  | 1.0041          | 0.6744   |
| 0.8323        | 44.0  | 9548  | 1.0018          | 0.6744   |
| 0.8178        | 45.0  | 9765  | 0.9998          | 0.6744   |
| 0.8479        | 46.0  | 9982  | 0.9982          | 0.6744   |
| 0.8512        | 47.0  | 10199 | 0.9971          | 0.6744   |
| 0.851         | 48.0  | 10416 | 0.9963          | 0.6744   |
| 0.839         | 49.0  | 10633 | 0.9959          | 0.6744   |
| 0.7968        | 50.0  | 10850 | 0.9959          | 0.6744   |


### Framework versions

- Transformers 4.32.1
- Pytorch 2.1.1+cu121
- Datasets 2.12.0
- Tokenizers 0.13.2

01_normal 02_tapered 03_pyriform 04_amorphous