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# smids_10x_deit_base_sgd_00001_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: 0.9942
- Accuracy: 0.5776

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 1.1101        | 1.0   | 751   | 1.0912          | 0.3940   |
| 1.1137        | 2.0   | 1502  | 1.0874          | 0.3990   |
| 1.0977        | 3.0   | 2253  | 1.0838          | 0.4057   |
| 1.0963        | 4.0   | 3004  | 1.0803          | 0.4157   |
| 1.0734        | 5.0   | 3755  | 1.0769          | 0.4307   |
| 1.0814        | 6.0   | 4506  | 1.0737          | 0.4424   |
| 1.0905        | 7.0   | 5257  | 1.0705          | 0.4558   |
| 1.0682        | 8.0   | 6008  | 1.0673          | 0.4508   |
| 1.0698        | 9.0   | 6759  | 1.0643          | 0.4524   |
| 1.066         | 10.0  | 7510  | 1.0613          | 0.4608   |
| 1.0809        | 11.0  | 8261  | 1.0584          | 0.4691   |
| 1.0569        | 12.0  | 9012  | 1.0556          | 0.4708   |
| 1.0524        | 13.0  | 9763  | 1.0527          | 0.4908   |
| 1.051         | 14.0  | 10514 | 1.0500          | 0.5042   |
| 1.0693        | 15.0  | 11265 | 1.0473          | 0.5092   |
| 1.0517        | 16.0  | 12016 | 1.0446          | 0.5175   |
| 1.0588        | 17.0  | 12767 | 1.0419          | 0.5159   |
| 1.0399        | 18.0  | 13518 | 1.0394          | 0.5192   |
| 1.0367        | 19.0  | 14269 | 1.0368          | 0.5225   |
| 1.0366        | 20.0  | 15020 | 1.0343          | 0.5259   |
| 1.0281        | 21.0  | 15771 | 1.0318          | 0.5326   |
| 1.036         | 22.0  | 16522 | 1.0294          | 0.5342   |
| 1.0334        | 23.0  | 17273 | 1.0270          | 0.5359   |
| 1.0262        | 24.0  | 18024 | 1.0247          | 0.5376   |
| 1.0153        | 25.0  | 18775 | 1.0224          | 0.5392   |
| 1.0269        | 26.0  | 19526 | 1.0202          | 0.5409   |
| 1.0163        | 27.0  | 20277 | 1.0180          | 0.5459   |
| 1.0112        | 28.0  | 21028 | 1.0159          | 0.5459   |
| 1.0292        | 29.0  | 21779 | 1.0139          | 0.5509   |
| 1.0159        | 30.0  | 22530 | 1.0120          | 0.5526   |
| 1.0063        | 31.0  | 23281 | 1.0102          | 0.5526   |
| 1.0238        | 32.0  | 24032 | 1.0085          | 0.5543   |
| 0.9962        | 33.0  | 24783 | 1.0069          | 0.5543   |
| 1.0016        | 34.0  | 25534 | 1.0053          | 0.5593   |
| 1.0116        | 35.0  | 26285 | 1.0039          | 0.5593   |
| 1.0035        | 36.0  | 27036 | 1.0026          | 0.5626   |
| 1.0094        | 37.0  | 27787 | 1.0013          | 0.5659   |
| 0.9975        | 38.0  | 28538 | 1.0002          | 0.5676   |
| 1.0065        | 39.0  | 29289 | 0.9992          | 0.5743   |
| 0.9968        | 40.0  | 30040 | 0.9982          | 0.5760   |
| 0.9969        | 41.0  | 30791 | 0.9974          | 0.5760   |
| 0.9821        | 42.0  | 31542 | 0.9967          | 0.5776   |
| 0.9849        | 43.0  | 32293 | 0.9961          | 0.5776   |
| 1.002         | 44.0  | 33044 | 0.9955          | 0.5776   |
| 1.0006        | 45.0  | 33795 | 0.9951          | 0.5776   |
| 1.0018        | 46.0  | 34546 | 0.9948          | 0.5776   |
| 0.9926        | 47.0  | 35297 | 0.9945          | 0.5776   |
| 1.0075        | 48.0  | 36048 | 0.9943          | 0.5776   |
| 0.9883        | 49.0  | 36799 | 0.9942          | 0.5776   |
| 0.9793        | 50.0  | 37550 | 0.9942          | 0.5776   |


### Framework versions

- Transformers 4.32.1
- Pytorch 2.1.0+cu121
- Datasets 2.12.0
- Tokenizers 0.13.2

abnormal_sperm non-sperm normal_sperm