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# hushem_40x_deit_small_rms_001_fold1

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: 7.2597
- Accuracy: 0.4222

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 1.3825        | 1.0   | 215   | 1.4688          | 0.2667   |
| 1.3534        | 2.0   | 430   | 1.4553          | 0.3778   |
| 0.9498        | 3.0   | 645   | 1.8460          | 0.3333   |
| 0.7874        | 4.0   | 860   | 1.0992          | 0.4444   |
| 0.6519        | 5.0   | 1075  | 1.5864          | 0.4222   |
| 0.6238        | 6.0   | 1290  | 1.5678          | 0.4444   |
| 0.6712        | 7.0   | 1505  | 1.5837          | 0.3778   |
| 0.6234        | 8.0   | 1720  | 1.4844          | 0.3778   |
| 0.6842        | 9.0   | 1935  | 1.4360          | 0.4      |
| 0.5244        | 10.0  | 2150  | 1.9225          | 0.3778   |
| 0.5422        | 11.0  | 2365  | 1.4512          | 0.4667   |
| 0.4482        | 12.0  | 2580  | 2.2789          | 0.3556   |
| 0.5899        | 13.0  | 2795  | 1.6124          | 0.4222   |
| 0.4227        | 14.0  | 3010  | 1.8210          | 0.4444   |
| 0.4862        | 15.0  | 3225  | 1.4215          | 0.4667   |
| 0.4615        | 16.0  | 3440  | 2.1496          | 0.3778   |
| 0.6895        | 17.0  | 3655  | 1.7698          | 0.4667   |
| 0.3741        | 18.0  | 3870  | 2.6905          | 0.3556   |
| 0.3762        | 19.0  | 4085  | 2.4546          | 0.4222   |
| 0.3383        | 20.0  | 4300  | 2.0176          | 0.3778   |
| 0.3622        | 21.0  | 4515  | 2.9706          | 0.4      |
| 0.3284        | 22.0  | 4730  | 2.9396          | 0.4      |
| 0.2403        | 23.0  | 4945  | 2.3459          | 0.4889   |
| 0.345         | 24.0  | 5160  | 3.1195          | 0.4222   |
| 0.3045        | 25.0  | 5375  | 2.4187          | 0.4667   |
| 0.2936        | 26.0  | 5590  | 2.9167          | 0.3556   |
| 0.249         | 27.0  | 5805  | 2.5521          | 0.4667   |
| 0.2161        | 28.0  | 6020  | 3.7842          | 0.3778   |
| 0.2382        | 29.0  | 6235  | 3.0584          | 0.4      |
| 0.1225        | 30.0  | 6450  | 4.4557          | 0.4      |
| 0.2075        | 31.0  | 6665  | 4.7131          | 0.3111   |
| 0.1575        | 32.0  | 6880  | 3.8714          | 0.3556   |
| 0.1516        | 33.0  | 7095  | 4.5510          | 0.4      |
| 0.1231        | 34.0  | 7310  | 5.0636          | 0.3778   |
| 0.0943        | 35.0  | 7525  | 4.2212          | 0.4      |
| 0.0741        | 36.0  | 7740  | 4.4947          | 0.4      |
| 0.0582        | 37.0  | 7955  | 4.8808          | 0.4222   |
| 0.0412        | 38.0  | 8170  | 5.2254          | 0.3778   |
| 0.0508        | 39.0  | 8385  | 5.2558          | 0.3556   |
| 0.0566        | 40.0  | 8600  | 5.9529          | 0.3556   |
| 0.0397        | 41.0  | 8815  | 5.9087          | 0.3333   |
| 0.0462        | 42.0  | 9030  | 6.2634          | 0.4444   |
| 0.0245        | 43.0  | 9245  | 6.0294          | 0.4222   |
| 0.0398        | 44.0  | 9460  | 6.9015          | 0.4222   |
| 0.0182        | 45.0  | 9675  | 5.5112          | 0.4667   |
| 0.0162        | 46.0  | 9890  | 6.0476          | 0.4889   |
| 0.0028        | 47.0  | 10105 | 6.5416          | 0.4667   |
| 0.0087        | 48.0  | 10320 | 6.8964          | 0.4444   |
| 0.0011        | 49.0  | 10535 | 7.0908          | 0.4222   |
| 0.0007        | 50.0  | 10750 | 7.2597          | 0.4222   |


### 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