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# hushem_40x_deit_tiny_adamax_001_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: 1.2217
- Accuracy: 0.8837

## 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: 0.001
- 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.3354        | 1.0   | 217   | 0.9126          | 0.6744   |
| 0.1561        | 2.0   | 434   | 1.0121          | 0.6977   |
| 0.0656        | 3.0   | 651   | 1.0046          | 0.7442   |
| 0.07          | 4.0   | 868   | 0.8401          | 0.7674   |
| 0.0448        | 5.0   | 1085  | 1.1419          | 0.7907   |
| 0.0667        | 6.0   | 1302  | 1.2686          | 0.8372   |
| 0.0198        | 7.0   | 1519  | 1.1351          | 0.8372   |
| 0.009         | 8.0   | 1736  | 1.6617          | 0.8140   |
| 0.0113        | 9.0   | 1953  | 1.1646          | 0.8372   |
| 0.0284        | 10.0  | 2170  | 0.8325          | 0.9302   |
| 0.0093        | 11.0  | 2387  | 1.2543          | 0.8372   |
| 0.0217        | 12.0  | 2604  | 1.5838          | 0.8140   |
| 0.0059        | 13.0  | 2821  | 1.3486          | 0.8605   |
| 0.0271        | 14.0  | 3038  | 0.9639          | 0.8837   |
| 0.0039        | 15.0  | 3255  | 0.9754          | 0.9070   |
| 0.0           | 16.0  | 3472  | 1.4140          | 0.8140   |
| 0.0           | 17.0  | 3689  | 1.2390          | 0.8837   |
| 0.0011        | 18.0  | 3906  | 1.3250          | 0.8605   |
| 0.0004        | 19.0  | 4123  | 1.2826          | 0.8372   |
| 0.0002        | 20.0  | 4340  | 1.1795          | 0.8605   |
| 0.0           | 21.0  | 4557  | 0.9932          | 0.8837   |
| 0.0           | 22.0  | 4774  | 0.9999          | 0.8837   |
| 0.0           | 23.0  | 4991  | 1.0055          | 0.8837   |
| 0.0           | 24.0  | 5208  | 1.0099          | 0.8837   |
| 0.0           | 25.0  | 5425  | 1.0179          | 0.8837   |
| 0.0           | 26.0  | 5642  | 1.0241          | 0.8837   |
| 0.0           | 27.0  | 5859  | 1.0302          | 0.8837   |
| 0.0           | 28.0  | 6076  | 1.0378          | 0.8837   |
| 0.0           | 29.0  | 6293  | 1.0445          | 0.8837   |
| 0.0           | 30.0  | 6510  | 1.0519          | 0.8837   |
| 0.0           | 31.0  | 6727  | 1.0608          | 0.8837   |
| 0.0           | 32.0  | 6944  | 1.0697          | 0.8837   |
| 0.0           | 33.0  | 7161  | 1.0787          | 0.8837   |
| 0.0           | 34.0  | 7378  | 1.0879          | 0.8837   |
| 0.0           | 35.0  | 7595  | 1.0974          | 0.8837   |
| 0.0           | 36.0  | 7812  | 1.1074          | 0.8837   |
| 0.0           | 37.0  | 8029  | 1.1171          | 0.8837   |
| 0.0           | 38.0  | 8246  | 1.1279          | 0.8837   |
| 0.0           | 39.0  | 8463  | 1.1383          | 0.8837   |
| 0.0           | 40.0  | 8680  | 1.1481          | 0.8837   |
| 0.0           | 41.0  | 8897  | 1.1586          | 0.8837   |
| 0.0           | 42.0  | 9114  | 1.1687          | 0.8837   |
| 0.0           | 43.0  | 9331  | 1.1785          | 0.8837   |
| 0.0           | 44.0  | 9548  | 1.1883          | 0.8837   |
| 0.0           | 45.0  | 9765  | 1.1969          | 0.8837   |
| 0.0           | 46.0  | 9982  | 1.2048          | 0.8837   |
| 0.0           | 47.0  | 10199 | 1.2119          | 0.8837   |
| 0.0           | 48.0  | 10416 | 1.2174          | 0.8837   |
| 0.0           | 49.0  | 10633 | 1.2210          | 0.8837   |
| 0.0           | 50.0  | 10850 | 1.2217          | 0.8837   |


### 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