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# hushem_40x_deit_tiny_adamax_00001_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: 0.8349
- Accuracy: 0.9070

## 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: 1e-05
- 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.424         | 1.0   | 217   | 0.5360          | 0.8140   |
| 0.1714        | 2.0   | 434   | 0.4093          | 0.8372   |
| 0.024         | 3.0   | 651   | 0.3706          | 0.8372   |
| 0.0076        | 4.0   | 868   | 0.3232          | 0.8605   |
| 0.0117        | 5.0   | 1085  | 0.4002          | 0.8605   |
| 0.0014        | 6.0   | 1302  | 0.3510          | 0.8837   |
| 0.0013        | 7.0   | 1519  | 0.3890          | 0.8837   |
| 0.0003        | 8.0   | 1736  | 0.4966          | 0.8837   |
| 0.0002        | 9.0   | 1953  | 0.4570          | 0.8837   |
| 0.0001        | 10.0  | 2170  | 0.5366          | 0.8837   |
| 0.0001        | 11.0  | 2387  | 0.4687          | 0.8837   |
| 0.0001        | 12.0  | 2604  | 0.5121          | 0.8837   |
| 0.0001        | 13.0  | 2821  | 0.5347          | 0.8837   |
| 0.0001        | 14.0  | 3038  | 0.5583          | 0.8837   |
| 0.0           | 15.0  | 3255  | 0.5404          | 0.8837   |
| 0.0           | 16.0  | 3472  | 0.5914          | 0.8837   |
| 0.0           | 17.0  | 3689  | 0.5903          | 0.8837   |
| 0.0           | 18.0  | 3906  | 0.5962          | 0.8837   |
| 0.0           | 19.0  | 4123  | 0.6082          | 0.8837   |
| 0.0           | 20.0  | 4340  | 0.6491          | 0.9070   |
| 0.0           | 21.0  | 4557  | 0.6647          | 0.8837   |
| 0.0           | 22.0  | 4774  | 0.6416          | 0.8837   |
| 0.0           | 23.0  | 4991  | 0.6353          | 0.9070   |
| 0.0           | 24.0  | 5208  | 0.6866          | 0.9070   |
| 0.0           | 25.0  | 5425  | 0.6552          | 0.9070   |
| 0.0           | 26.0  | 5642  | 0.7023          | 0.9070   |
| 0.0           | 27.0  | 5859  | 0.6738          | 0.9070   |
| 0.0           | 28.0  | 6076  | 0.7119          | 0.9070   |
| 0.0           | 29.0  | 6293  | 0.7453          | 0.9070   |
| 0.0           | 30.0  | 6510  | 0.7641          | 0.9070   |
| 0.0           | 31.0  | 6727  | 0.7753          | 0.9070   |
| 0.0           | 32.0  | 6944  | 0.7598          | 0.9070   |
| 0.0           | 33.0  | 7161  | 0.7952          | 0.9070   |
| 0.0           | 34.0  | 7378  | 0.7621          | 0.9070   |
| 0.0           | 35.0  | 7595  | 0.7849          | 0.9070   |
| 0.0           | 36.0  | 7812  | 0.7647          | 0.9070   |
| 0.0           | 37.0  | 8029  | 0.7761          | 0.9070   |
| 0.0           | 38.0  | 8246  | 0.8153          | 0.9070   |
| 0.0           | 39.0  | 8463  | 0.8099          | 0.9070   |
| 0.0           | 40.0  | 8680  | 0.8036          | 0.9070   |
| 0.0           | 41.0  | 8897  | 0.8358          | 0.9070   |
| 0.0           | 42.0  | 9114  | 0.8036          | 0.9070   |
| 0.0           | 43.0  | 9331  | 0.8414          | 0.9070   |
| 0.0           | 44.0  | 9548  | 0.8111          | 0.9070   |
| 0.0           | 45.0  | 9765  | 0.8271          | 0.9070   |
| 0.0           | 46.0  | 9982  | 0.8237          | 0.9070   |
| 0.0           | 47.0  | 10199 | 0.8249          | 0.9070   |
| 0.0           | 48.0  | 10416 | 0.8315          | 0.9070   |
| 0.0           | 49.0  | 10633 | 0.8343          | 0.9070   |
| 0.0           | 50.0  | 10850 | 0.8349          | 0.9070   |


### 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