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# hushem_40x_deit_tiny_sgd_00001_fold2

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: 1.4218
- Accuracy: 0.2444

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 1.4676        | 1.0   | 215   | 1.4979          | 0.2444   |
| 1.453         | 2.0   | 430   | 1.4941          | 0.2444   |
| 1.4514        | 3.0   | 645   | 1.4903          | 0.2444   |
| 1.4264        | 4.0   | 860   | 1.4866          | 0.2222   |
| 1.4845        | 5.0   | 1075  | 1.4831          | 0.2222   |
| 1.4049        | 6.0   | 1290  | 1.4797          | 0.2444   |
| 1.408         | 7.0   | 1505  | 1.4764          | 0.2444   |
| 1.4075        | 8.0   | 1720  | 1.4733          | 0.2444   |
| 1.4274        | 9.0   | 1935  | 1.4702          | 0.2444   |
| 1.4165        | 10.0  | 2150  | 1.4673          | 0.2444   |
| 1.3408        | 11.0  | 2365  | 1.4645          | 0.2444   |
| 1.387         | 12.0  | 2580  | 1.4617          | 0.2444   |
| 1.3966        | 13.0  | 2795  | 1.4591          | 0.2444   |
| 1.3631        | 14.0  | 3010  | 1.4566          | 0.2444   |
| 1.3966        | 15.0  | 3225  | 1.4542          | 0.2444   |
| 1.4085        | 16.0  | 3440  | 1.4520          | 0.2444   |
| 1.3593        | 17.0  | 3655  | 1.4498          | 0.2444   |
| 1.3872        | 18.0  | 3870  | 1.4477          | 0.2444   |
| 1.3857        | 19.0  | 4085  | 1.4457          | 0.2222   |
| 1.3961        | 20.0  | 4300  | 1.4439          | 0.2222   |
| 1.3725        | 21.0  | 4515  | 1.4421          | 0.2222   |
| 1.3634        | 22.0  | 4730  | 1.4405          | 0.2222   |
| 1.3404        | 23.0  | 4945  | 1.4389          | 0.2222   |
| 1.2947        | 24.0  | 5160  | 1.4374          | 0.2222   |
| 1.3286        | 25.0  | 5375  | 1.4360          | 0.2222   |
| 1.3597        | 26.0  | 5590  | 1.4346          | 0.2222   |
| 1.3935        | 27.0  | 5805  | 1.4334          | 0.2222   |
| 1.3126        | 28.0  | 6020  | 1.4322          | 0.2222   |
| 1.3862        | 29.0  | 6235  | 1.4311          | 0.2222   |
| 1.345         | 30.0  | 6450  | 1.4301          | 0.2222   |
| 1.3332        | 31.0  | 6665  | 1.4291          | 0.2222   |
| 1.3215        | 32.0  | 6880  | 1.4283          | 0.2222   |
| 1.3753        | 33.0  | 7095  | 1.4274          | 0.2222   |
| 1.3397        | 34.0  | 7310  | 1.4267          | 0.2222   |
| 1.3085        | 35.0  | 7525  | 1.4260          | 0.2222   |
| 1.3414        | 36.0  | 7740  | 1.4254          | 0.2222   |
| 1.3773        | 37.0  | 7955  | 1.4248          | 0.2222   |
| 1.2916        | 38.0  | 8170  | 1.4243          | 0.2222   |
| 1.2953        | 39.0  | 8385  | 1.4238          | 0.2222   |
| 1.3053        | 40.0  | 8600  | 1.4234          | 0.2222   |
| 1.3127        | 41.0  | 8815  | 1.4230          | 0.2222   |
| 1.2816        | 42.0  | 9030  | 1.4227          | 0.2222   |
| 1.3493        | 43.0  | 9245  | 1.4225          | 0.2222   |
| 1.3258        | 44.0  | 9460  | 1.4223          | 0.2222   |
| 1.3441        | 45.0  | 9675  | 1.4221          | 0.2444   |
| 1.2959        | 46.0  | 9890  | 1.4220          | 0.2444   |
| 1.3609        | 47.0  | 10105 | 1.4219          | 0.2444   |
| 1.276         | 48.0  | 10320 | 1.4219          | 0.2444   |
| 1.2931        | 49.0  | 10535 | 1.4218          | 0.2444   |
| 1.3383        | 50.0  | 10750 | 1.4218          | 0.2444   |


### 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