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# hushem_40x_deit_tiny_sgd_00001_fold4

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: 1.5700
- Accuracy: 0.1429

## 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: 1e-05
- 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 1.5195        | 1.0   | 219   | 1.6573          | 0.1429   |
| 1.4299        | 2.0   | 438   | 1.6538          | 0.1429   |
| 1.5002        | 3.0   | 657   | 1.6502          | 0.1429   |
| 1.4923        | 4.0   | 876   | 1.6467          | 0.1429   |
| 1.4507        | 5.0   | 1095  | 1.6433          | 0.1667   |
| 1.4843        | 6.0   | 1314  | 1.6398          | 0.1667   |
| 1.4439        | 7.0   | 1533  | 1.6365          | 0.1667   |
| 1.461         | 8.0   | 1752  | 1.6332          | 0.1667   |
| 1.4438        | 9.0   | 1971  | 1.6299          | 0.1667   |
| 1.421         | 10.0  | 2190  | 1.6268          | 0.1667   |
| 1.3797        | 11.0  | 2409  | 1.6238          | 0.1667   |
| 1.4481        | 12.0  | 2628  | 1.6208          | 0.1429   |
| 1.37          | 13.0  | 2847  | 1.6179          | 0.1429   |
| 1.4257        | 14.0  | 3066  | 1.6150          | 0.1429   |
| 1.3565        | 15.0  | 3285  | 1.6123          | 0.1429   |
| 1.3893        | 16.0  | 3504  | 1.6097          | 0.1429   |
| 1.4087        | 17.0  | 3723  | 1.6071          | 0.1429   |
| 1.3822        | 18.0  | 3942  | 1.6047          | 0.1429   |
| 1.3943        | 19.0  | 4161  | 1.6023          | 0.1429   |
| 1.4156        | 20.0  | 4380  | 1.6000          | 0.1429   |
| 1.397         | 21.0  | 4599  | 1.5977          | 0.1429   |
| 1.3921        | 22.0  | 4818  | 1.5956          | 0.1429   |
| 1.345         | 23.0  | 5037  | 1.5936          | 0.1429   |
| 1.3941        | 24.0  | 5256  | 1.5916          | 0.1429   |
| 1.3428        | 25.0  | 5475  | 1.5898          | 0.1429   |
| 1.3959        | 26.0  | 5694  | 1.5880          | 0.1429   |
| 1.3527        | 27.0  | 5913  | 1.5863          | 0.1429   |
| 1.3622        | 28.0  | 6132  | 1.5847          | 0.1429   |
| 1.3233        | 29.0  | 6351  | 1.5833          | 0.1429   |
| 1.3602        | 30.0  | 6570  | 1.5819          | 0.1429   |
| 1.3369        | 31.0  | 6789  | 1.5805          | 0.1429   |
| 1.3891        | 32.0  | 7008  | 1.5793          | 0.1429   |
| 1.3567        | 33.0  | 7227  | 1.5782          | 0.1429   |
| 1.3341        | 34.0  | 7446  | 1.5771          | 0.1429   |
| 1.3827        | 35.0  | 7665  | 1.5761          | 0.1429   |
| 1.3365        | 36.0  | 7884  | 1.5752          | 0.1429   |
| 1.3545        | 37.0  | 8103  | 1.5744          | 0.1429   |
| 1.3874        | 38.0  | 8322  | 1.5736          | 0.1429   |
| 1.3749        | 39.0  | 8541  | 1.5729          | 0.1429   |
| 1.3026        | 40.0  | 8760  | 1.5724          | 0.1429   |
| 1.3806        | 41.0  | 8979  | 1.5718          | 0.1429   |
| 1.3467        | 42.0  | 9198  | 1.5714          | 0.1429   |
| 1.3584        | 43.0  | 9417  | 1.5710          | 0.1429   |
| 1.3511        | 44.0  | 9636  | 1.5707          | 0.1429   |
| 1.3397        | 45.0  | 9855  | 1.5704          | 0.1429   |
| 1.35          | 46.0  | 10074 | 1.5703          | 0.1429   |
| 1.328         | 47.0  | 10293 | 1.5701          | 0.1429   |
| 1.3922        | 48.0  | 10512 | 1.5700          | 0.1429   |
| 1.3345        | 49.0  | 10731 | 1.5700          | 0.1429   |
| 1.3302        | 50.0  | 10950 | 1.5700          | 0.1429   |


### 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