
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# hushem_40x_deit_small_sgd_001_fold1

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: 0.6398
- Accuracy: 0.7778

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 1.1952        | 1.0   | 215   | 1.4276          | 0.3778   |
| 1.0042        | 2.0   | 430   | 1.4162          | 0.2889   |
| 0.8488        | 3.0   | 645   | 1.3544          | 0.3778   |
| 0.7465        | 4.0   | 860   | 1.2674          | 0.4889   |
| 0.6036        | 5.0   | 1075  | 1.1735          | 0.5111   |
| 0.5355        | 6.0   | 1290  | 1.0934          | 0.5556   |
| 0.4712        | 7.0   | 1505  | 1.0208          | 0.6      |
| 0.3805        | 8.0   | 1720  | 0.9372          | 0.6222   |
| 0.3422        | 9.0   | 1935  | 0.8901          | 0.6444   |
| 0.2964        | 10.0  | 2150  | 0.8433          | 0.6667   |
| 0.2485        | 11.0  | 2365  | 0.7909          | 0.6889   |
| 0.2255        | 12.0  | 2580  | 0.7693          | 0.7111   |
| 0.1717        | 13.0  | 2795  | 0.7309          | 0.7556   |
| 0.1588        | 14.0  | 3010  | 0.7252          | 0.7556   |
| 0.1672        | 15.0  | 3225  | 0.6986          | 0.7333   |
| 0.1097        | 16.0  | 3440  | 0.6863          | 0.7333   |
| 0.1167        | 17.0  | 3655  | 0.6753          | 0.7556   |
| 0.0952        | 18.0  | 3870  | 0.6754          | 0.7556   |
| 0.0806        | 19.0  | 4085  | 0.6768          | 0.7556   |
| 0.0794        | 20.0  | 4300  | 0.6533          | 0.7556   |
| 0.0649        | 21.0  | 4515  | 0.6553          | 0.7556   |
| 0.0639        | 22.0  | 4730  | 0.6451          | 0.7556   |
| 0.0578        | 23.0  | 4945  | 0.6498          | 0.7556   |
| 0.0439        | 24.0  | 5160  | 0.6457          | 0.7556   |
| 0.0437        | 25.0  | 5375  | 0.6423          | 0.7556   |
| 0.038         | 26.0  | 5590  | 0.6342          | 0.7556   |
| 0.0346        | 27.0  | 5805  | 0.6184          | 0.7556   |
| 0.0278        | 28.0  | 6020  | 0.6299          | 0.7556   |
| 0.035         | 29.0  | 6235  | 0.6381          | 0.7556   |
| 0.0226        | 30.0  | 6450  | 0.6272          | 0.7556   |
| 0.0178        | 31.0  | 6665  | 0.6325          | 0.7556   |
| 0.019         | 32.0  | 6880  | 0.6409          | 0.7556   |
| 0.0184        | 33.0  | 7095  | 0.6323          | 0.7778   |
| 0.0238        | 34.0  | 7310  | 0.6091          | 0.7556   |
| 0.0126        | 35.0  | 7525  | 0.6363          | 0.7778   |
| 0.0156        | 36.0  | 7740  | 0.6253          | 0.7556   |
| 0.0165        | 37.0  | 7955  | 0.6280          | 0.7556   |
| 0.0106        | 38.0  | 8170  | 0.6294          | 0.7778   |
| 0.0189        | 39.0  | 8385  | 0.6262          | 0.7778   |
| 0.0098        | 40.0  | 8600  | 0.6454          | 0.7556   |
| 0.0098        | 41.0  | 8815  | 0.6342          | 0.7778   |
| 0.0112        | 42.0  | 9030  | 0.6356          | 0.7778   |
| 0.0128        | 43.0  | 9245  | 0.6416          | 0.7778   |
| 0.0115        | 44.0  | 9460  | 0.6374          | 0.7778   |
| 0.0087        | 45.0  | 9675  | 0.6423          | 0.7778   |
| 0.0077        | 46.0  | 9890  | 0.6446          | 0.7778   |
| 0.0087        | 47.0  | 10105 | 0.6388          | 0.7778   |
| 0.0071        | 48.0  | 10320 | 0.6394          | 0.7778   |
| 0.0087        | 49.0  | 10535 | 0.6404          | 0.7778   |
| 0.0108        | 50.0  | 10750 | 0.6398          | 0.7778   |


### 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