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# hushem_40x_deit_tiny_sgd_00001_fold1

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: 1.3702
- Accuracy: 0.2889

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 1.5833        | 1.0   | 215   | 1.4002          | 0.1778   |
| 1.5381        | 2.0   | 430   | 1.3990          | 0.2      |
| 1.505         | 3.0   | 645   | 1.3978          | 0.2222   |
| 1.446         | 4.0   | 860   | 1.3967          | 0.2444   |
| 1.4742        | 5.0   | 1075  | 1.3956          | 0.2222   |
| 1.3991        | 6.0   | 1290  | 1.3945          | 0.2222   |
| 1.4142        | 7.0   | 1505  | 1.3933          | 0.2222   |
| 1.4895        | 8.0   | 1720  | 1.3923          | 0.2222   |
| 1.4297        | 9.0   | 1935  | 1.3912          | 0.2222   |
| 1.4803        | 10.0  | 2150  | 1.3901          | 0.2222   |
| 1.4253        | 11.0  | 2365  | 1.3890          | 0.2222   |
| 1.4151        | 12.0  | 2580  | 1.3880          | 0.2222   |
| 1.3649        | 13.0  | 2795  | 1.3870          | 0.2222   |
| 1.4058        | 14.0  | 3010  | 1.3860          | 0.2444   |
| 1.3858        | 15.0  | 3225  | 1.3850          | 0.2444   |
| 1.3985        | 16.0  | 3440  | 1.3841          | 0.2444   |
| 1.4078        | 17.0  | 3655  | 1.3832          | 0.2444   |
| 1.3916        | 18.0  | 3870  | 1.3823          | 0.2444   |
| 1.4138        | 19.0  | 4085  | 1.3814          | 0.2444   |
| 1.3697        | 20.0  | 4300  | 1.3807          | 0.2444   |
| 1.3976        | 21.0  | 4515  | 1.3799          | 0.2444   |
| 1.45          | 22.0  | 4730  | 1.3791          | 0.2444   |
| 1.3757        | 23.0  | 4945  | 1.3784          | 0.2444   |
| 1.4088        | 24.0  | 5160  | 1.3777          | 0.2667   |
| 1.3948        | 25.0  | 5375  | 1.3771          | 0.2667   |
| 1.3916        | 26.0  | 5590  | 1.3764          | 0.2667   |
| 1.3383        | 27.0  | 5805  | 1.3759          | 0.2667   |
| 1.3507        | 28.0  | 6020  | 1.3753          | 0.2889   |
| 1.3823        | 29.0  | 6235  | 1.3748          | 0.2889   |
| 1.3489        | 30.0  | 6450  | 1.3743          | 0.2889   |
| 1.3905        | 31.0  | 6665  | 1.3738          | 0.2889   |
| 1.3646        | 32.0  | 6880  | 1.3734          | 0.2889   |
| 1.394         | 33.0  | 7095  | 1.3730          | 0.2889   |
| 1.3256        | 34.0  | 7310  | 1.3726          | 0.2889   |
| 1.342         | 35.0  | 7525  | 1.3723          | 0.2889   |
| 1.3277        | 36.0  | 7740  | 1.3720          | 0.2889   |
| 1.3815        | 37.0  | 7955  | 1.3717          | 0.2889   |
| 1.3516        | 38.0  | 8170  | 1.3714          | 0.2889   |
| 1.3573        | 39.0  | 8385  | 1.3712          | 0.2889   |
| 1.3764        | 40.0  | 8600  | 1.3710          | 0.2889   |
| 1.3508        | 41.0  | 8815  | 1.3708          | 0.2889   |
| 1.4032        | 42.0  | 9030  | 1.3707          | 0.2889   |
| 1.3548        | 43.0  | 9245  | 1.3705          | 0.2889   |
| 1.3623        | 44.0  | 9460  | 1.3704          | 0.2889   |
| 1.3744        | 45.0  | 9675  | 1.3704          | 0.2889   |
| 1.3298        | 46.0  | 9890  | 1.3703          | 0.2889   |
| 1.352         | 47.0  | 10105 | 1.3703          | 0.2889   |
| 1.363         | 48.0  | 10320 | 1.3702          | 0.2889   |
| 1.3844        | 49.0  | 10535 | 1.3702          | 0.2889   |
| 1.3587        | 50.0  | 10750 | 1.3702          | 0.2889   |


### 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