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# hushem_40x_deit_tiny_adamax_00001_fold5

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: 0.8352
- Accuracy: 0.8537

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.3813        | 1.0   | 220   | 0.6093          | 0.7561   |
| 0.131         | 2.0   | 440   | 0.4372          | 0.8293   |
| 0.0714        | 3.0   | 660   | 0.6223          | 0.7805   |
| 0.0083        | 4.0   | 880   | 0.5773          | 0.8537   |
| 0.0038        | 5.0   | 1100  | 0.5967          | 0.8537   |
| 0.0013        | 6.0   | 1320  | 0.7213          | 0.8537   |
| 0.0005        | 7.0   | 1540  | 0.6555          | 0.8537   |
| 0.0003        | 8.0   | 1760  | 0.7129          | 0.8537   |
| 0.0002        | 9.0   | 1980  | 0.6903          | 0.8537   |
| 0.0001        | 10.0  | 2200  | 0.7139          | 0.8537   |
| 0.0001        | 11.0  | 2420  | 0.7461          | 0.8537   |
| 0.0001        | 12.0  | 2640  | 0.7296          | 0.8537   |
| 0.0001        | 13.0  | 2860  | 0.7461          | 0.8537   |
| 0.0001        | 14.0  | 3080  | 0.7537          | 0.8537   |
| 0.0           | 15.0  | 3300  | 0.7347          | 0.8537   |
| 0.0           | 16.0  | 3520  | 0.7586          | 0.8537   |
| 0.0           | 17.0  | 3740  | 0.7585          | 0.8537   |
| 0.0           | 18.0  | 3960  | 0.7603          | 0.8537   |
| 0.0           | 19.0  | 4180  | 0.7375          | 0.8537   |
| 0.0           | 20.0  | 4400  | 0.7584          | 0.8537   |
| 0.0           | 21.0  | 4620  | 0.7582          | 0.8537   |
| 0.0           | 22.0  | 4840  | 0.7660          | 0.8537   |
| 0.0           | 23.0  | 5060  | 0.7826          | 0.8537   |
| 0.0           | 24.0  | 5280  | 0.7552          | 0.8537   |
| 0.0           | 25.0  | 5500  | 0.7401          | 0.8537   |
| 0.0           | 26.0  | 5720  | 0.7783          | 0.8537   |
| 0.0           | 27.0  | 5940  | 0.7654          | 0.8537   |
| 0.0           | 28.0  | 6160  | 0.7518          | 0.8537   |
| 0.0           | 29.0  | 6380  | 0.7644          | 0.8537   |
| 0.0           | 30.0  | 6600  | 0.7962          | 0.8537   |
| 0.0           | 31.0  | 6820  | 0.8050          | 0.8537   |
| 0.0           | 32.0  | 7040  | 0.7846          | 0.8537   |
| 0.0           | 33.0  | 7260  | 0.7663          | 0.8537   |
| 0.0           | 34.0  | 7480  | 0.7669          | 0.8780   |
| 0.0           | 35.0  | 7700  | 0.7816          | 0.8780   |
| 0.0           | 36.0  | 7920  | 0.7902          | 0.8537   |
| 0.0           | 37.0  | 8140  | 0.7775          | 0.8537   |
| 0.0           | 38.0  | 8360  | 0.8004          | 0.8537   |
| 0.0           | 39.0  | 8580  | 0.7724          | 0.8537   |
| 0.0           | 40.0  | 8800  | 0.7795          | 0.8780   |
| 0.0           | 41.0  | 9020  | 0.8084          | 0.8537   |
| 0.0           | 42.0  | 9240  | 0.8224          | 0.8537   |
| 0.0           | 43.0  | 9460  | 0.8366          | 0.8293   |
| 0.0           | 44.0  | 9680  | 0.8236          | 0.8780   |
| 0.0           | 45.0  | 9900  | 0.8365          | 0.8293   |
| 0.0           | 46.0  | 10120 | 0.8207          | 0.8537   |
| 0.0           | 47.0  | 10340 | 0.8439          | 0.8293   |
| 0.0           | 48.0  | 10560 | 0.8465          | 0.8537   |
| 0.0           | 49.0  | 10780 | 0.8311          | 0.8537   |
| 0.0           | 50.0  | 11000 | 0.8352          | 0.8537   |


### 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