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# smids_3x_deit_small_sgd_001_fold5

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: 0.2955
- Accuracy: 0.875

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.8786        | 1.0   | 225   | 0.8329          | 0.6917   |
| 0.6756        | 2.0   | 450   | 0.6561          | 0.7467   |
| 0.5645        | 3.0   | 675   | 0.5574          | 0.7867   |
| 0.4671        | 4.0   | 900   | 0.4924          | 0.8067   |
| 0.3977        | 5.0   | 1125  | 0.4538          | 0.82     |
| 0.4177        | 6.0   | 1350  | 0.4235          | 0.8367   |
| 0.3878        | 7.0   | 1575  | 0.4039          | 0.8417   |
| 0.4378        | 8.0   | 1800  | 0.3874          | 0.8433   |
| 0.3622        | 9.0   | 2025  | 0.3772          | 0.8483   |
| 0.345         | 10.0  | 2250  | 0.3683          | 0.8517   |
| 0.3638        | 11.0  | 2475  | 0.3631          | 0.8533   |
| 0.3441        | 12.0  | 2700  | 0.3527          | 0.8583   |
| 0.3313        | 13.0  | 2925  | 0.3447          | 0.865    |
| 0.2901        | 14.0  | 3150  | 0.3405          | 0.8633   |
| 0.2288        | 15.0  | 3375  | 0.3333          | 0.865    |
| 0.3024        | 16.0  | 3600  | 0.3306          | 0.865    |
| 0.2544        | 17.0  | 3825  | 0.3278          | 0.8683   |
| 0.299         | 18.0  | 4050  | 0.3253          | 0.8667   |
| 0.2662        | 19.0  | 4275  | 0.3235          | 0.8667   |
| 0.2847        | 20.0  | 4500  | 0.3172          | 0.8683   |
| 0.2132        | 21.0  | 4725  | 0.3164          | 0.8667   |
| 0.2384        | 22.0  | 4950  | 0.3131          | 0.8717   |
| 0.2264        | 23.0  | 5175  | 0.3102          | 0.8733   |
| 0.2574        | 24.0  | 5400  | 0.3121          | 0.8667   |
| 0.2327        | 25.0  | 5625  | 0.3088          | 0.8683   |
| 0.2687        | 26.0  | 5850  | 0.3062          | 0.8667   |
| 0.28          | 27.0  | 6075  | 0.3048          | 0.8667   |
| 0.2544        | 28.0  | 6300  | 0.3033          | 0.8683   |
| 0.2339        | 29.0  | 6525  | 0.3018          | 0.87     |
| 0.2           | 30.0  | 6750  | 0.3023          | 0.8733   |
| 0.1716        | 31.0  | 6975  | 0.3008          | 0.8733   |
| 0.2152        | 32.0  | 7200  | 0.2995          | 0.8717   |
| 0.2129        | 33.0  | 7425  | 0.2994          | 0.8733   |
| 0.1758        | 34.0  | 7650  | 0.2988          | 0.875    |
| 0.1848        | 35.0  | 7875  | 0.3009          | 0.875    |
| 0.2108        | 36.0  | 8100  | 0.2991          | 0.875    |
| 0.2223        | 37.0  | 8325  | 0.2978          | 0.875    |
| 0.1689        | 38.0  | 8550  | 0.2975          | 0.8733   |
| 0.1768        | 39.0  | 8775  | 0.2974          | 0.8767   |
| 0.2093        | 40.0  | 9000  | 0.2965          | 0.8733   |
| 0.1994        | 41.0  | 9225  | 0.2966          | 0.8733   |
| 0.2309        | 42.0  | 9450  | 0.2956          | 0.8733   |
| 0.2412        | 43.0  | 9675  | 0.2974          | 0.8767   |
| 0.2229        | 44.0  | 9900  | 0.2958          | 0.875    |
| 0.2153        | 45.0  | 10125 | 0.2965          | 0.8767   |
| 0.1978        | 46.0  | 10350 | 0.2959          | 0.8767   |
| 0.2092        | 47.0  | 10575 | 0.2956          | 0.875    |
| 0.2126        | 48.0  | 10800 | 0.2958          | 0.875    |
| 0.2109        | 49.0  | 11025 | 0.2956          | 0.875    |
| 0.1728        | 50.0  | 11250 | 0.2955          | 0.875    |


### 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