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# hushem_40x_deit_base_sgd_0001_fold1

This model is a fine-tuned version of [facebook/deit-base-patch16-224](https://huggingface.co/facebook/deit-base-patch16-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 1.2920
- Accuracy: 0.3778

## 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: 0.0001
- 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 1.3635        | 1.0   | 215   | 1.4586          | 0.2889   |
| 1.3564        | 2.0   | 430   | 1.4485          | 0.2889   |
| 1.3735        | 3.0   | 645   | 1.4395          | 0.2889   |
| 1.3415        | 4.0   | 860   | 1.4312          | 0.2889   |
| 1.3033        | 5.0   | 1075  | 1.4236          | 0.2889   |
| 1.3111        | 6.0   | 1290  | 1.4165          | 0.2667   |
| 1.2796        | 7.0   | 1505  | 1.4098          | 0.2667   |
| 1.265         | 8.0   | 1720  | 1.4035          | 0.2667   |
| 1.2454        | 9.0   | 1935  | 1.3975          | 0.2667   |
| 1.2437        | 10.0  | 2150  | 1.3919          | 0.2667   |
| 1.2689        | 11.0  | 2365  | 1.3867          | 0.2667   |
| 1.212         | 12.0  | 2580  | 1.3818          | 0.2667   |
| 1.2193        | 13.0  | 2795  | 1.3771          | 0.2667   |
| 1.2167        | 14.0  | 3010  | 1.3726          | 0.2667   |
| 1.205         | 15.0  | 3225  | 1.3683          | 0.2667   |
| 1.2084        | 16.0  | 3440  | 1.3641          | 0.2889   |
| 1.1861        | 17.0  | 3655  | 1.3601          | 0.3333   |
| 1.1898        | 18.0  | 3870  | 1.3563          | 0.3556   |
| 1.1745        | 19.0  | 4085  | 1.3526          | 0.3556   |
| 1.1602        | 20.0  | 4300  | 1.3489          | 0.3556   |
| 1.1523        | 21.0  | 4515  | 1.3454          | 0.3556   |
| 1.1329        | 22.0  | 4730  | 1.3420          | 0.3556   |
| 1.1475        | 23.0  | 4945  | 1.3387          | 0.3556   |
| 1.1333        | 24.0  | 5160  | 1.3354          | 0.3556   |
| 1.1285        | 25.0  | 5375  | 1.3322          | 0.3333   |
| 1.0938        | 26.0  | 5590  | 1.3292          | 0.3333   |
| 1.0832        | 27.0  | 5805  | 1.3262          | 0.3333   |
| 1.0889        | 28.0  | 6020  | 1.3234          | 0.3333   |
| 1.0886        | 29.0  | 6235  | 1.3206          | 0.3333   |
| 1.0684        | 30.0  | 6450  | 1.3180          | 0.3333   |
| 1.0707        | 31.0  | 6665  | 1.3154          | 0.3333   |
| 1.068         | 32.0  | 6880  | 1.3130          | 0.3333   |
| 1.0647        | 33.0  | 7095  | 1.3107          | 0.3556   |
| 1.0516        | 34.0  | 7310  | 1.3085          | 0.3556   |
| 1.0515        | 35.0  | 7525  | 1.3064          | 0.3556   |
| 1.0477        | 36.0  | 7740  | 1.3045          | 0.3556   |
| 1.0685        | 37.0  | 7955  | 1.3027          | 0.3556   |
| 1.0459        | 38.0  | 8170  | 1.3010          | 0.3556   |
| 1.0276        | 39.0  | 8385  | 1.2995          | 0.3556   |
| 1.016         | 40.0  | 8600  | 1.2981          | 0.3556   |
| 1.044         | 41.0  | 8815  | 1.2969          | 0.3556   |
| 1.0849        | 42.0  | 9030  | 1.2957          | 0.3556   |
| 1.0504        | 43.0  | 9245  | 1.2948          | 0.3778   |
| 1.0115        | 44.0  | 9460  | 1.2940          | 0.3778   |
| 1.0336        | 45.0  | 9675  | 1.2933          | 0.3778   |
| 1.0415        | 46.0  | 9890  | 1.2928          | 0.3778   |
| 1.013         | 47.0  | 10105 | 1.2924          | 0.3778   |
| 1.0207        | 48.0  | 10320 | 1.2921          | 0.3778   |
| 1.054         | 49.0  | 10535 | 1.2920          | 0.3778   |
| 1.0317        | 50.0  | 10750 | 1.2920          | 0.3778   |


### 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