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# hushem_40x_deit_base_adamax_001_fold3

This model is a fine-tuned version of [facebook/deit-base-patch16-224](https://huggingface.co/facebook/deit-base-patch16-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 2.0078
- Accuracy: 0.8372

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.1615        | 1.0   | 217   | 0.8891          | 0.7674   |
| 0.0732        | 2.0   | 434   | 0.4751          | 0.8372   |
| 0.0924        | 3.0   | 651   | 1.0550          | 0.8140   |
| 0.0215        | 4.0   | 868   | 0.8222          | 0.8140   |
| 0.0108        | 5.0   | 1085  | 1.0431          | 0.7907   |
| 0.0556        | 6.0   | 1302  | 1.0073          | 0.7907   |
| 0.004         | 7.0   | 1519  | 1.0088          | 0.8372   |
| 0.0126        | 8.0   | 1736  | 0.8896          | 0.8605   |
| 0.0277        | 9.0   | 1953  | 1.5634          | 0.8140   |
| 0.0001        | 10.0  | 2170  | 1.2793          | 0.8605   |
| 0.0292        | 11.0  | 2387  | 1.1442          | 0.7674   |
| 0.0544        | 12.0  | 2604  | 1.8210          | 0.7674   |
| 0.0066        | 13.0  | 2821  | 1.1859          | 0.7907   |
| 0.0012        | 14.0  | 3038  | 1.1578          | 0.7907   |
| 0.0282        | 15.0  | 3255  | 1.6928          | 0.7442   |
| 0.0001        | 16.0  | 3472  | 1.3989          | 0.8372   |
| 0.0           | 17.0  | 3689  | 1.4295          | 0.8372   |
| 0.0           | 18.0  | 3906  | 1.4591          | 0.8372   |
| 0.0           | 19.0  | 4123  | 1.4845          | 0.8372   |
| 0.0           | 20.0  | 4340  | 1.5077          | 0.8372   |
| 0.0           | 21.0  | 4557  | 1.5294          | 0.8372   |
| 0.0           | 22.0  | 4774  | 1.5502          | 0.8372   |
| 0.0           | 23.0  | 4991  | 1.5707          | 0.8372   |
| 0.0           | 24.0  | 5208  | 1.5907          | 0.8372   |
| 0.0           | 25.0  | 5425  | 1.6108          | 0.8372   |
| 0.0           | 26.0  | 5642  | 1.6313          | 0.8372   |
| 0.0           | 27.0  | 5859  | 1.6525          | 0.8372   |
| 0.0           | 28.0  | 6076  | 1.6750          | 0.8372   |
| 0.0           | 29.0  | 6293  | 1.6980          | 0.8372   |
| 0.0           | 30.0  | 6510  | 1.7211          | 0.8372   |
| 0.0           | 31.0  | 6727  | 1.7443          | 0.8372   |
| 0.0           | 32.0  | 6944  | 1.7671          | 0.8372   |
| 0.0           | 33.0  | 7161  | 1.7884          | 0.8372   |
| 0.0           | 34.0  | 7378  | 1.8089          | 0.8372   |
| 0.0           | 35.0  | 7595  | 1.8281          | 0.8372   |
| 0.0           | 36.0  | 7812  | 1.8470          | 0.8372   |
| 0.0           | 37.0  | 8029  | 1.8657          | 0.8372   |
| 0.0           | 38.0  | 8246  | 1.8832          | 0.8372   |
| 0.0           | 39.0  | 8463  | 1.9003          | 0.8372   |
| 0.0           | 40.0  | 8680  | 1.9168          | 0.8372   |
| 0.0           | 41.0  | 8897  | 1.9322          | 0.8372   |
| 0.0           | 42.0  | 9114  | 1.9463          | 0.8372   |
| 0.0           | 43.0  | 9331  | 1.9591          | 0.8372   |
| 0.0           | 44.0  | 9548  | 1.9706          | 0.8372   |
| 0.0           | 45.0  | 9765  | 1.9809          | 0.8372   |
| 0.0           | 46.0  | 9982  | 1.9901          | 0.8372   |
| 0.0           | 47.0  | 10199 | 1.9976          | 0.8372   |
| 0.0           | 48.0  | 10416 | 2.0033          | 0.8372   |
| 0.0           | 49.0  | 10633 | 2.0069          | 0.8372   |
| 0.0           | 50.0  | 10850 | 2.0078          | 0.8372   |


### 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