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# hushem_40x_deit_tiny_rms_001_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: 4.1758
- Accuracy: 0.7317

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 1.1377        | 1.0   | 220   | 1.4706          | 0.3171   |
| 0.8838        | 2.0   | 440   | 1.1169          | 0.4634   |
| 0.7297        | 3.0   | 660   | 0.9759          | 0.6098   |
| 0.6075        | 4.0   | 880   | 0.6205          | 0.7317   |
| 0.4922        | 5.0   | 1100  | 1.0787          | 0.6098   |
| 0.4263        | 6.0   | 1320  | 0.7206          | 0.7561   |
| 0.1851        | 7.0   | 1540  | 0.8644          | 0.7317   |
| 0.1792        | 8.0   | 1760  | 0.9149          | 0.7073   |
| 0.1954        | 9.0   | 1980  | 0.9202          | 0.7561   |
| 0.1313        | 10.0  | 2200  | 0.8113          | 0.8049   |
| 0.0886        | 11.0  | 2420  | 1.2174          | 0.7073   |
| 0.0848        | 12.0  | 2640  | 1.1156          | 0.7805   |
| 0.1044        | 13.0  | 2860  | 1.2101          | 0.7073   |
| 0.1348        | 14.0  | 3080  | 1.1458          | 0.7317   |
| 0.0626        | 15.0  | 3300  | 1.0690          | 0.7317   |
| 0.0309        | 16.0  | 3520  | 1.3430          | 0.7073   |
| 0.0473        | 17.0  | 3740  | 1.3747          | 0.7317   |
| 0.1091        | 18.0  | 3960  | 1.0321          | 0.7805   |
| 0.1069        | 19.0  | 4180  | 1.7755          | 0.7073   |
| 0.0244        | 20.0  | 4400  | 1.5213          | 0.7317   |
| 0.0331        | 21.0  | 4620  | 1.3935          | 0.7805   |
| 0.1167        | 22.0  | 4840  | 1.2913          | 0.7561   |
| 0.0052        | 23.0  | 5060  | 0.9792          | 0.8049   |
| 0.0198        | 24.0  | 5280  | 0.8211          | 0.8780   |
| 0.0358        | 25.0  | 5500  | 1.1277          | 0.8049   |
| 0.0008        | 26.0  | 5720  | 1.4574          | 0.7073   |
| 0.0001        | 27.0  | 5940  | 1.0665          | 0.7561   |
| 0.0001        | 28.0  | 6160  | 1.1272          | 0.7805   |
| 0.0006        | 29.0  | 6380  | 1.2564          | 0.7073   |
| 0.0011        | 30.0  | 6600  | 1.4453          | 0.7073   |
| 0.0002        | 31.0  | 6820  | 1.9210          | 0.7805   |
| 0.0108        | 32.0  | 7040  | 2.0987          | 0.7317   |
| 0.0           | 33.0  | 7260  | 2.5706          | 0.7317   |
| 0.0           | 34.0  | 7480  | 2.5154          | 0.7317   |
| 0.0           | 35.0  | 7700  | 2.7600          | 0.7317   |
| 0.0           | 36.0  | 7920  | 2.9535          | 0.7317   |
| 0.0           | 37.0  | 8140  | 3.1263          | 0.7317   |
| 0.0           | 38.0  | 8360  | 3.3175          | 0.7317   |
| 0.0           | 39.0  | 8580  | 3.4937          | 0.7317   |
| 0.0           | 40.0  | 8800  | 3.6752          | 0.7317   |
| 0.0           | 41.0  | 9020  | 3.8325          | 0.7317   |
| 0.0           | 42.0  | 9240  | 3.9616          | 0.7317   |
| 0.0           | 43.0  | 9460  | 4.0429          | 0.7317   |
| 0.0           | 44.0  | 9680  | 4.1055          | 0.7317   |
| 0.0           | 45.0  | 9900  | 4.1340          | 0.7317   |
| 0.0           | 46.0  | 10120 | 4.1489          | 0.7317   |
| 0.0           | 47.0  | 10340 | 4.1566          | 0.7317   |
| 0.0           | 48.0  | 10560 | 4.1688          | 0.7317   |
| 0.0           | 49.0  | 10780 | 4.1743          | 0.7317   |
| 0.0           | 50.0  | 11000 | 4.1758          | 0.7317   |


### 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