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# smids_3x_deit_tiny_adamax_001_fold5

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: 0.9334
- Accuracy: 0.89

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.6273        | 1.0   | 225   | 0.4733          | 0.805    |
| 0.2977        | 2.0   | 450   | 0.3448          | 0.8733   |
| 0.3197        | 3.0   | 675   | 0.3620          | 0.88     |
| 0.2909        | 4.0   | 900   | 0.4019          | 0.8367   |
| 0.1808        | 5.0   | 1125  | 0.3972          | 0.8617   |
| 0.2005        | 6.0   | 1350  | 0.4622          | 0.8483   |
| 0.1408        | 7.0   | 1575  | 0.4696          | 0.8717   |
| 0.1502        | 8.0   | 1800  | 0.4332          | 0.8633   |
| 0.2129        | 9.0   | 2025  | 0.3925          | 0.8833   |
| 0.114         | 10.0  | 2250  | 0.4888          | 0.8733   |
| 0.1195        | 11.0  | 2475  | 0.4884          | 0.8717   |
| 0.1124        | 12.0  | 2700  | 0.4439          | 0.8733   |
| 0.0652        | 13.0  | 2925  | 0.6058          | 0.8633   |
| 0.0425        | 14.0  | 3150  | 0.5627          | 0.875    |
| 0.039         | 15.0  | 3375  | 0.5971          | 0.875    |
| 0.0795        | 16.0  | 3600  | 0.6169          | 0.8733   |
| 0.0453        | 17.0  | 3825  | 0.6835          | 0.875    |
| 0.0066        | 18.0  | 4050  | 0.7361          | 0.8783   |
| 0.1031        | 19.0  | 4275  | 0.7941          | 0.8717   |
| 0.0061        | 20.0  | 4500  | 0.7090          | 0.8733   |
| 0.0198        | 21.0  | 4725  | 0.7250          | 0.8783   |
| 0.0155        | 22.0  | 4950  | 0.7045          | 0.8917   |
| 0.023         | 23.0  | 5175  | 0.8046          | 0.8817   |
| 0.057         | 24.0  | 5400  | 0.7359          | 0.8817   |
| 0.0134        | 25.0  | 5625  | 0.7403          | 0.8867   |
| 0.0001        | 26.0  | 5850  | 0.7361          | 0.895    |
| 0.0011        | 27.0  | 6075  | 0.7945          | 0.8733   |
| 0.0014        | 28.0  | 6300  | 0.6928          | 0.8983   |
| 0.0133        | 29.0  | 6525  | 0.6789          | 0.895    |
| 0.0002        | 30.0  | 6750  | 0.7451          | 0.8967   |
| 0.0001        | 31.0  | 6975  | 0.7847          | 0.8867   |
| 0.0           | 32.0  | 7200  | 0.7580          | 0.8917   |
| 0.0043        | 33.0  | 7425  | 0.8908          | 0.8833   |
| 0.0           | 34.0  | 7650  | 0.7939          | 0.89     |
| 0.0034        | 35.0  | 7875  | 0.8753          | 0.8933   |
| 0.0           | 36.0  | 8100  | 0.8470          | 0.8867   |
| 0.0046        | 37.0  | 8325  | 0.9037          | 0.8867   |
| 0.0001        | 38.0  | 8550  | 0.8793          | 0.89     |
| 0.0           | 39.0  | 8775  | 0.8702          | 0.8917   |
| 0.0           | 40.0  | 9000  | 0.8835          | 0.8883   |
| 0.0           | 41.0  | 9225  | 0.9101          | 0.8883   |
| 0.0           | 42.0  | 9450  | 0.9070          | 0.8933   |
| 0.0037        | 43.0  | 9675  | 0.9025          | 0.8933   |
| 0.0           | 44.0  | 9900  | 0.9038          | 0.89     |
| 0.0           | 45.0  | 10125 | 0.9112          | 0.89     |
| 0.0           | 46.0  | 10350 | 0.9228          | 0.89     |
| 0.0           | 47.0  | 10575 | 0.9243          | 0.89     |
| 0.0           | 48.0  | 10800 | 0.9283          | 0.89     |
| 0.0           | 49.0  | 11025 | 0.9314          | 0.89     |
| 0.0           | 50.0  | 11250 | 0.9334          | 0.89     |


### 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