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# smids_1x_deit_small_rms_00001_fold3

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: 0.7182
- Accuracy: 0.905

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.3259        | 1.0   | 75   | 0.3001          | 0.89     |
| 0.2426        | 2.0   | 150  | 0.3217          | 0.8717   |
| 0.1676        | 3.0   | 225  | 0.2596          | 0.9083   |
| 0.1287        | 4.0   | 300  | 0.2827          | 0.895    |
| 0.0316        | 5.0   | 375  | 0.3452          | 0.885    |
| 0.0237        | 6.0   | 450  | 0.3793          | 0.9017   |
| 0.0244        | 7.0   | 525  | 0.4128          | 0.8967   |
| 0.0233        | 8.0   | 600  | 0.4590          | 0.8883   |
| 0.0286        | 9.0   | 675  | 0.4790          | 0.8983   |
| 0.0295        | 10.0  | 750  | 0.4835          | 0.8917   |
| 0.0562        | 11.0  | 825  | 0.4705          | 0.9067   |
| 0.0087        | 12.0  | 900  | 0.5035          | 0.9033   |
| 0.0083        | 13.0  | 975  | 0.5418          | 0.9017   |
| 0.0001        | 14.0  | 1050 | 0.5563          | 0.9      |
| 0.0012        | 15.0  | 1125 | 0.5874          | 0.8983   |
| 0.0001        | 16.0  | 1200 | 0.5698          | 0.8967   |
| 0.0001        | 17.0  | 1275 | 0.5930          | 0.9033   |
| 0.0062        | 18.0  | 1350 | 0.5972          | 0.9017   |
| 0.0048        | 19.0  | 1425 | 0.5918          | 0.9033   |
| 0.0089        | 20.0  | 1500 | 0.6518          | 0.9017   |
| 0.0001        | 21.0  | 1575 | 0.7835          | 0.885    |
| 0.0001        | 22.0  | 1650 | 0.6700          | 0.9      |
| 0.0031        | 23.0  | 1725 | 0.6679          | 0.8983   |
| 0.0           | 24.0  | 1800 | 0.6364          | 0.9033   |
| 0.0001        | 25.0  | 1875 | 0.6464          | 0.8983   |
| 0.003         | 26.0  | 1950 | 0.6535          | 0.8967   |
| 0.0           | 27.0  | 2025 | 0.6525          | 0.8983   |
| 0.0           | 28.0  | 2100 | 0.6526          | 0.8983   |
| 0.0           | 29.0  | 2175 | 0.6663          | 0.895    |
| 0.0           | 30.0  | 2250 | 0.6645          | 0.8983   |
| 0.0           | 31.0  | 2325 | 0.6717          | 0.9      |
| 0.0           | 32.0  | 2400 | 0.6659          | 0.8983   |
| 0.0           | 33.0  | 2475 | 0.6774          | 0.9017   |
| 0.0051        | 34.0  | 2550 | 0.6726          | 0.905    |
| 0.0059        | 35.0  | 2625 | 0.7209          | 0.8933   |
| 0.0031        | 36.0  | 2700 | 0.6818          | 0.9067   |
| 0.0022        | 37.0  | 2775 | 0.6938          | 0.8967   |
| 0.0           | 38.0  | 2850 | 0.6968          | 0.8967   |
| 0.0           | 39.0  | 2925 | 0.7122          | 0.8983   |
| 0.0           | 40.0  | 3000 | 0.7008          | 0.8983   |
| 0.0           | 41.0  | 3075 | 0.7070          | 0.8983   |
| 0.0026        | 42.0  | 3150 | 0.7002          | 0.9      |
| 0.0025        | 43.0  | 3225 | 0.7107          | 0.9      |
| 0.0           | 44.0  | 3300 | 0.7106          | 0.9033   |
| 0.0025        | 45.0  | 3375 | 0.7116          | 0.905    |
| 0.0025        | 46.0  | 3450 | 0.7142          | 0.905    |
| 0.0047        | 47.0  | 3525 | 0.7163          | 0.9033   |
| 0.0           | 48.0  | 3600 | 0.7169          | 0.9033   |
| 0.0           | 49.0  | 3675 | 0.7178          | 0.9033   |
| 0.0045        | 50.0  | 3750 | 0.7182          | 0.905    |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0

abnormal_sperm non-sperm normal_sperm