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# hushem_40x_deit_small_rms_0001_fold5

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: 1.9788
- Accuracy: 0.8049

## 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: 0.0001
- 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.1371        | 1.0   | 220   | 0.3701          | 0.8293   |
| 0.0445        | 2.0   | 440   | 1.9924          | 0.7073   |
| 0.0133        | 3.0   | 660   | 1.1496          | 0.8049   |
| 0.0131        | 4.0   | 880   | 0.3434          | 0.9024   |
| 0.0354        | 5.0   | 1100  | 0.4117          | 0.8537   |
| 0.0497        | 6.0   | 1320  | 0.2267          | 0.9268   |
| 0.0845        | 7.0   | 1540  | 1.0625          | 0.8293   |
| 0.0001        | 8.0   | 1760  | 1.4387          | 0.7317   |
| 0.0648        | 9.0   | 1980  | 0.2862          | 0.9756   |
| 0.0159        | 10.0  | 2200  | 0.5399          | 0.8780   |
| 0.0001        | 11.0  | 2420  | 0.6240          | 0.8293   |
| 0.0069        | 12.0  | 2640  | 0.9226          | 0.8049   |
| 0.071         | 13.0  | 2860  | 1.0657          | 0.8293   |
| 0.0001        | 14.0  | 3080  | 1.2561          | 0.7805   |
| 0.0           | 15.0  | 3300  | 1.2385          | 0.7805   |
| 0.0           | 16.0  | 3520  | 1.2648          | 0.7805   |
| 0.0           | 17.0  | 3740  | 1.3089          | 0.7805   |
| 0.0           | 18.0  | 3960  | 1.3750          | 0.7805   |
| 0.0           | 19.0  | 4180  | 1.4566          | 0.7805   |
| 0.0           | 20.0  | 4400  | 1.5453          | 0.8049   |
| 0.0           | 21.0  | 4620  | 1.6338          | 0.8049   |
| 0.0           | 22.0  | 4840  | 1.6896          | 0.8049   |
| 0.0           | 23.0  | 5060  | 1.7347          | 0.8049   |
| 0.0           | 24.0  | 5280  | 1.7835          | 0.8049   |
| 0.0           | 25.0  | 5500  | 1.8255          | 0.8049   |
| 0.0           | 26.0  | 5720  | 1.8621          | 0.8049   |
| 0.0           | 27.0  | 5940  | 1.8887          | 0.8049   |
| 0.0           | 28.0  | 6160  | 1.9074          | 0.8049   |
| 0.0           | 29.0  | 6380  | 1.9212          | 0.8049   |
| 0.0           | 30.0  | 6600  | 1.9317          | 0.8049   |
| 0.0           | 31.0  | 6820  | 1.9398          | 0.8049   |
| 0.0           | 32.0  | 7040  | 1.9465          | 0.8049   |
| 0.0           | 33.0  | 7260  | 1.9519          | 0.8049   |
| 0.0           | 34.0  | 7480  | 1.9563          | 0.8049   |
| 0.0           | 35.0  | 7700  | 1.9601          | 0.8049   |
| 0.0           | 36.0  | 7920  | 1.9632          | 0.8049   |
| 0.0           | 37.0  | 8140  | 1.9659          | 0.8049   |
| 0.0           | 38.0  | 8360  | 1.9682          | 0.8049   |
| 0.0           | 39.0  | 8580  | 1.9702          | 0.8049   |
| 0.0           | 40.0  | 8800  | 1.9718          | 0.8049   |
| 0.0           | 41.0  | 9020  | 1.9733          | 0.8049   |
| 0.0           | 42.0  | 9240  | 1.9745          | 0.8049   |
| 0.0           | 43.0  | 9460  | 1.9756          | 0.8049   |
| 0.0           | 44.0  | 9680  | 1.9764          | 0.8049   |
| 0.0           | 45.0  | 9900  | 1.9772          | 0.8049   |
| 0.0           | 46.0  | 10120 | 1.9777          | 0.8049   |
| 0.0           | 47.0  | 10340 | 1.9782          | 0.8049   |
| 0.0           | 48.0  | 10560 | 1.9785          | 0.8049   |
| 0.0           | 49.0  | 10780 | 1.9787          | 0.8049   |
| 0.0           | 50.0  | 11000 | 1.9788          | 0.8049   |


### 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