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# smids_3x_deit_tiny_sgd_001_fold4

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: 0.3792
- Accuracy: 0.845

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.9374        | 1.0   | 225   | 0.9137          | 0.535    |
| 0.637         | 2.0   | 450   | 0.7038          | 0.6933   |
| 0.528         | 3.0   | 675   | 0.5838          | 0.745    |
| 0.4807        | 4.0   | 900   | 0.5174          | 0.7967   |
| 0.4652        | 5.0   | 1125  | 0.4857          | 0.8033   |
| 0.3253        | 6.0   | 1350  | 0.4581          | 0.8083   |
| 0.3966        | 7.0   | 1575  | 0.4373          | 0.8233   |
| 0.4286        | 8.0   | 1800  | 0.4298          | 0.81     |
| 0.368         | 9.0   | 2025  | 0.4134          | 0.8233   |
| 0.3027        | 10.0  | 2250  | 0.4061          | 0.8417   |
| 0.3611        | 11.0  | 2475  | 0.4002          | 0.8233   |
| 0.3327        | 12.0  | 2700  | 0.3930          | 0.8483   |
| 0.2879        | 13.0  | 2925  | 0.3875          | 0.835    |
| 0.2362        | 14.0  | 3150  | 0.3833          | 0.845    |
| 0.2472        | 15.0  | 3375  | 0.3854          | 0.85     |
| 0.2412        | 16.0  | 3600  | 0.3772          | 0.8483   |
| 0.2474        | 17.0  | 3825  | 0.3765          | 0.8433   |
| 0.2597        | 18.0  | 4050  | 0.3736          | 0.8467   |
| 0.2836        | 19.0  | 4275  | 0.3755          | 0.85     |
| 0.19          | 20.0  | 4500  | 0.3722          | 0.8467   |
| 0.2408        | 21.0  | 4725  | 0.3732          | 0.8483   |
| 0.2395        | 22.0  | 4950  | 0.3728          | 0.8433   |
| 0.2175        | 23.0  | 5175  | 0.3773          | 0.8417   |
| 0.2295        | 24.0  | 5400  | 0.3700          | 0.8517   |
| 0.2109        | 25.0  | 5625  | 0.3716          | 0.8467   |
| 0.1922        | 26.0  | 5850  | 0.3714          | 0.8517   |
| 0.1883        | 27.0  | 6075  | 0.3724          | 0.8517   |
| 0.1939        | 28.0  | 6300  | 0.3739          | 0.85     |
| 0.1633        | 29.0  | 6525  | 0.3736          | 0.8567   |
| 0.1934        | 30.0  | 6750  | 0.3747          | 0.8533   |
| 0.1648        | 31.0  | 6975  | 0.3737          | 0.8467   |
| 0.1378        | 32.0  | 7200  | 0.3775          | 0.845    |
| 0.2214        | 33.0  | 7425  | 0.3749          | 0.85     |
| 0.1912        | 34.0  | 7650  | 0.3749          | 0.845    |
| 0.1512        | 35.0  | 7875  | 0.3732          | 0.8483   |
| 0.2352        | 36.0  | 8100  | 0.3763          | 0.845    |
| 0.2012        | 37.0  | 8325  | 0.3753          | 0.845    |
| 0.1968        | 38.0  | 8550  | 0.3756          | 0.85     |
| 0.1845        | 39.0  | 8775  | 0.3769          | 0.8483   |
| 0.215         | 40.0  | 9000  | 0.3781          | 0.8483   |
| 0.1756        | 41.0  | 9225  | 0.3779          | 0.8483   |
| 0.1667        | 42.0  | 9450  | 0.3792          | 0.8467   |
| 0.1672        | 43.0  | 9675  | 0.3791          | 0.8467   |
| 0.2264        | 44.0  | 9900  | 0.3791          | 0.8467   |
| 0.1992        | 45.0  | 10125 | 0.3783          | 0.8483   |
| 0.1804        | 46.0  | 10350 | 0.3789          | 0.8483   |
| 0.177         | 47.0  | 10575 | 0.3795          | 0.8483   |
| 0.2026        | 48.0  | 10800 | 0.3789          | 0.8467   |
| 0.1973        | 49.0  | 11025 | 0.3793          | 0.8483   |
| 0.1685        | 50.0  | 11250 | 0.3792          | 0.845    |


### Framework versions

- Transformers 4.32.1
- Pytorch 2.1.1+cu121
- Datasets 2.12.0
- Tokenizers 0.13.2

abnormal_sperm non-sperm normal_sperm