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# hushem_40x_deit_small_rms_001_fold4

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: 2.0611
- Accuracy: 0.8571

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 1.2113        | 1.0   | 219   | 1.1711          | 0.4286   |
| 1.0563        | 2.0   | 438   | 1.0188          | 0.5476   |
| 1.1492        | 3.0   | 657   | 1.0982          | 0.5      |
| 0.8355        | 4.0   | 876   | 0.9249          | 0.4524   |
| 0.9277        | 5.0   | 1095  | 0.9715          | 0.4762   |
| 0.9059        | 6.0   | 1314  | 0.8917          | 0.5476   |
| 0.697         | 7.0   | 1533  | 1.5323          | 0.5      |
| 0.7359        | 8.0   | 1752  | 0.7730          | 0.6190   |
| 0.6186        | 9.0   | 1971  | 0.7734          | 0.6190   |
| 0.5814        | 10.0  | 2190  | 0.7874          | 0.7143   |
| 0.5808        | 11.0  | 2409  | 0.5974          | 0.7619   |
| 0.5808        | 12.0  | 2628  | 0.7519          | 0.7381   |
| 0.5465        | 13.0  | 2847  | 0.4863          | 0.8095   |
| 0.4671        | 14.0  | 3066  | 0.6575          | 0.6905   |
| 0.5228        | 15.0  | 3285  | 0.6495          | 0.7143   |
| 0.4327        | 16.0  | 3504  | 0.7075          | 0.7619   |
| 0.3283        | 17.0  | 3723  | 0.6356          | 0.7381   |
| 0.3853        | 18.0  | 3942  | 0.5432          | 0.7857   |
| 0.3803        | 19.0  | 4161  | 0.9396          | 0.7857   |
| 0.3493        | 20.0  | 4380  | 0.8015          | 0.7143   |
| 0.3953        | 21.0  | 4599  | 0.7074          | 0.7619   |
| 0.3223        | 22.0  | 4818  | 1.0523          | 0.6667   |
| 0.2414        | 23.0  | 5037  | 1.0911          | 0.6667   |
| 0.2219        | 24.0  | 5256  | 1.1394          | 0.6905   |
| 0.2892        | 25.0  | 5475  | 0.7116          | 0.7619   |
| 0.2739        | 26.0  | 5694  | 1.1234          | 0.7143   |
| 0.2207        | 27.0  | 5913  | 0.8565          | 0.7857   |
| 0.1354        | 28.0  | 6132  | 1.1975          | 0.7381   |
| 0.2042        | 29.0  | 6351  | 0.8634          | 0.7619   |
| 0.152         | 30.0  | 6570  | 0.8119          | 0.7857   |
| 0.1453        | 31.0  | 6789  | 0.8364          | 0.7381   |
| 0.1714        | 32.0  | 7008  | 1.2193          | 0.8095   |
| 0.1106        | 33.0  | 7227  | 1.0792          | 0.7619   |
| 0.1157        | 34.0  | 7446  | 0.9831          | 0.7619   |
| 0.096         | 35.0  | 7665  | 1.1093          | 0.8095   |
| 0.0452        | 36.0  | 7884  | 0.9133          | 0.8095   |
| 0.0552        | 37.0  | 8103  | 1.3044          | 0.8095   |
| 0.0539        | 38.0  | 8322  | 0.9892          | 0.8095   |
| 0.041         | 39.0  | 8541  | 1.1780          | 0.8571   |
| 0.0165        | 40.0  | 8760  | 1.3517          | 0.8333   |
| 0.0361        | 41.0  | 8979  | 1.5071          | 0.8333   |
| 0.046         | 42.0  | 9198  | 1.2679          | 0.8571   |
| 0.0477        | 43.0  | 9417  | 1.7256          | 0.8333   |
| 0.0088        | 44.0  | 9636  | 1.2515          | 0.8333   |
| 0.0208        | 45.0  | 9855  | 1.8769          | 0.8571   |
| 0.0012        | 46.0  | 10074 | 1.9828          | 0.8333   |
| 0.0014        | 47.0  | 10293 | 1.9685          | 0.8571   |
| 0.0001        | 48.0  | 10512 | 1.7583          | 0.8571   |
| 0.0001        | 49.0  | 10731 | 2.0944          | 0.8571   |
| 0.0001        | 50.0  | 10950 | 2.0611          | 0.8571   |


### 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