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# hushem_40x_deit_base_rms_001_fold5

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: 3.5781
- Accuracy: 0.7561

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 1.2271        | 1.0   | 220   | 1.5032          | 0.3902   |
| 0.9545        | 2.0   | 440   | 1.5087          | 0.3902   |
| 0.8667        | 3.0   | 660   | 1.0714          | 0.4878   |
| 0.8154        | 4.0   | 880   | 0.7851          | 0.6098   |
| 0.6309        | 5.0   | 1100  | 1.0215          | 0.4878   |
| 0.5655        | 6.0   | 1320  | 0.8556          | 0.6098   |
| 0.4033        | 7.0   | 1540  | 0.7849          | 0.7073   |
| 0.3567        | 8.0   | 1760  | 1.1431          | 0.6585   |
| 0.3869        | 9.0   | 1980  | 0.7273          | 0.7561   |
| 0.2867        | 10.0  | 2200  | 0.9025          | 0.6341   |
| 0.2933        | 11.0  | 2420  | 1.0767          | 0.6829   |
| 0.2822        | 12.0  | 2640  | 0.9054          | 0.7561   |
| 0.2576        | 13.0  | 2860  | 1.1701          | 0.7073   |
| 0.1424        | 14.0  | 3080  | 1.2265          | 0.7317   |
| 0.1597        | 15.0  | 3300  | 1.2021          | 0.7317   |
| 0.0822        | 16.0  | 3520  | 1.5652          | 0.7073   |
| 0.0859        | 17.0  | 3740  | 1.0512          | 0.7561   |
| 0.1048        | 18.0  | 3960  | 1.9377          | 0.6341   |
| 0.0506        | 19.0  | 4180  | 1.4302          | 0.7561   |
| 0.0595        | 20.0  | 4400  | 1.2065          | 0.7073   |
| 0.1492        | 21.0  | 4620  | 1.7891          | 0.7073   |
| 0.0835        | 22.0  | 4840  | 1.5550          | 0.7561   |
| 0.0475        | 23.0  | 5060  | 1.2142          | 0.7317   |
| 0.0941        | 24.0  | 5280  | 1.4080          | 0.7073   |
| 0.0186        | 25.0  | 5500  | 1.5889          | 0.7561   |
| 0.0776        | 26.0  | 5720  | 1.8453          | 0.6829   |
| 0.0752        | 27.0  | 5940  | 1.5817          | 0.7805   |
| 0.0113        | 28.0  | 6160  | 1.6776          | 0.7805   |
| 0.0011        | 29.0  | 6380  | 2.1296          | 0.7317   |
| 0.0107        | 30.0  | 6600  | 1.9807          | 0.7073   |
| 0.0181        | 31.0  | 6820  | 1.9248          | 0.7073   |
| 0.0106        | 32.0  | 7040  | 2.5784          | 0.7317   |
| 0.0002        | 33.0  | 7260  | 1.8180          | 0.8049   |
| 0.0013        | 34.0  | 7480  | 1.5976          | 0.8049   |
| 0.0031        | 35.0  | 7700  | 1.9747          | 0.7317   |
| 0.0094        | 36.0  | 7920  | 2.4830          | 0.7317   |
| 0.0006        | 37.0  | 8140  | 2.9074          | 0.7561   |
| 0.0049        | 38.0  | 8360  | 2.6503          | 0.6829   |
| 0.0002        | 39.0  | 8580  | 2.4189          | 0.7561   |
| 0.0           | 40.0  | 8800  | 2.4124          | 0.7561   |
| 0.0           | 41.0  | 9020  | 2.5470          | 0.7561   |
| 0.0           | 42.0  | 9240  | 2.6196          | 0.7805   |
| 0.0           | 43.0  | 9460  | 2.7251          | 0.7805   |
| 0.0           | 44.0  | 9680  | 2.9457          | 0.7805   |
| 0.0           | 45.0  | 9900  | 3.1311          | 0.7805   |
| 0.0           | 46.0  | 10120 | 3.2547          | 0.7805   |
| 0.0           | 47.0  | 10340 | 3.3567          | 0.7317   |
| 0.0           | 48.0  | 10560 | 3.5689          | 0.7561   |
| 0.0           | 49.0  | 10780 | 3.5825          | 0.7561   |
| 0.0           | 50.0  | 11000 | 3.5781          | 0.7561   |


### 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