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# hushem_40x_deit_small_adamax_001_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: 2.0018
- Accuracy: 0.8140

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.2113        | 1.0   | 217   | 1.0639          | 0.7209   |
| 0.3075        | 2.0   | 434   | 0.6999          | 0.7442   |
| 0.0797        | 3.0   | 651   | 1.4112          | 0.7209   |
| 0.0613        | 4.0   | 868   | 0.8895          | 0.8605   |
| 0.0448        | 5.0   | 1085  | 0.8165          | 0.8140   |
| 0.0133        | 6.0   | 1302  | 1.2281          | 0.7907   |
| 0.0099        | 7.0   | 1519  | 1.6935          | 0.7907   |
| 0.0195        | 8.0   | 1736  | 0.9261          | 0.8837   |
| 0.0441        | 9.0   | 1953  | 0.6136          | 0.8605   |
| 0.0408        | 10.0  | 2170  | 1.0937          | 0.8605   |
| 0.0001        | 11.0  | 2387  | 1.3536          | 0.8372   |
| 0.0014        | 12.0  | 2604  | 1.5056          | 0.8372   |
| 0.0152        | 13.0  | 2821  | 1.3542          | 0.8140   |
| 0.0011        | 14.0  | 3038  | 1.1435          | 0.8140   |
| 0.0006        | 15.0  | 3255  | 1.7874          | 0.7907   |
| 0.0244        | 16.0  | 3472  | 1.5609          | 0.8140   |
| 0.0           | 17.0  | 3689  | 0.9143          | 0.9070   |
| 0.0           | 18.0  | 3906  | 1.3119          | 0.8140   |
| 0.0           | 19.0  | 4123  | 1.5264          | 0.8372   |
| 0.0024        | 20.0  | 4340  | 1.6055          | 0.8140   |
| 0.0           | 21.0  | 4557  | 1.7071          | 0.8140   |
| 0.0           | 22.0  | 4774  | 1.6943          | 0.8140   |
| 0.0           | 23.0  | 4991  | 1.6871          | 0.8140   |
| 0.0           | 24.0  | 5208  | 1.6854          | 0.8140   |
| 0.0           | 25.0  | 5425  | 1.6881          | 0.8140   |
| 0.0           | 26.0  | 5642  | 1.6930          | 0.8140   |
| 0.0           | 27.0  | 5859  | 1.6999          | 0.8140   |
| 0.0           | 28.0  | 6076  | 1.7095          | 0.8140   |
| 0.0           | 29.0  | 6293  | 1.7201          | 0.8140   |
| 0.0           | 30.0  | 6510  | 1.7321          | 0.8140   |
| 0.0           | 31.0  | 6727  | 1.7453          | 0.8140   |
| 0.0           | 32.0  | 6944  | 1.7591          | 0.8140   |
| 0.0           | 33.0  | 7161  | 1.7739          | 0.8140   |
| 0.0           | 34.0  | 7378  | 1.7893          | 0.8140   |
| 0.0           | 35.0  | 7595  | 1.8052          | 0.8140   |
| 0.0           | 36.0  | 7812  | 1.8215          | 0.8140   |
| 0.0           | 37.0  | 8029  | 1.8380          | 0.8140   |
| 0.0           | 38.0  | 8246  | 1.8542          | 0.8140   |
| 0.0           | 39.0  | 8463  | 1.8709          | 0.8140   |
| 0.0           | 40.0  | 8680  | 1.8874          | 0.8140   |
| 0.0           | 41.0  | 8897  | 1.9038          | 0.8140   |
| 0.0           | 42.0  | 9114  | 1.9194          | 0.8140   |
| 0.0           | 43.0  | 9331  | 1.9350          | 0.8140   |
| 0.0           | 44.0  | 9548  | 1.9494          | 0.8140   |
| 0.0           | 45.0  | 9765  | 1.9631          | 0.8140   |
| 0.0           | 46.0  | 9982  | 1.9753          | 0.8140   |
| 0.0           | 47.0  | 10199 | 1.9864          | 0.8140   |
| 0.0           | 48.0  | 10416 | 1.9949          | 0.8140   |
| 0.0           | 49.0  | 10633 | 2.0003          | 0.8140   |
| 0.0           | 50.0  | 10850 | 2.0018          | 0.8140   |


### 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