
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# smids_3x_deit_tiny_sgd_0001_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: 0.5739
- Accuracy: 0.775

## 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: 0.0001
- 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 1.1702        | 1.0   | 225   | 1.1979          | 0.3733   |
| 1.1054        | 2.0   | 450   | 1.1279          | 0.4033   |
| 1.0995        | 3.0   | 675   | 1.0911          | 0.4167   |
| 1.0744        | 4.0   | 900   | 1.0627          | 0.4367   |
| 1.0062        | 5.0   | 1125  | 1.0378          | 0.45     |
| 1.0305        | 6.0   | 1350  | 1.0143          | 0.4633   |
| 1.0048        | 7.0   | 1575  | 0.9914          | 0.4917   |
| 0.9977        | 8.0   | 1800  | 0.9686          | 0.515    |
| 0.8819        | 9.0   | 2025  | 0.9464          | 0.5283   |
| 0.899         | 10.0  | 2250  | 0.9249          | 0.5517   |
| 0.8919        | 11.0  | 2475  | 0.9036          | 0.5633   |
| 0.887         | 12.0  | 2700  | 0.8832          | 0.5833   |
| 0.8706        | 13.0  | 2925  | 0.8626          | 0.5983   |
| 0.8705        | 14.0  | 3150  | 0.8429          | 0.6117   |
| 0.7649        | 15.0  | 3375  | 0.8245          | 0.6267   |
| 0.8058        | 16.0  | 3600  | 0.8064          | 0.6383   |
| 0.7948        | 17.0  | 3825  | 0.7895          | 0.6517   |
| 0.7127        | 18.0  | 4050  | 0.7738          | 0.66     |
| 0.7637        | 19.0  | 4275  | 0.7581          | 0.665    |
| 0.7239        | 20.0  | 4500  | 0.7434          | 0.6717   |
| 0.7375        | 21.0  | 4725  | 0.7293          | 0.685    |
| 0.7685        | 22.0  | 4950  | 0.7159          | 0.6917   |
| 0.7357        | 23.0  | 5175  | 0.7032          | 0.7      |
| 0.7155        | 24.0  | 5400  | 0.6916          | 0.7067   |
| 0.6674        | 25.0  | 5625  | 0.6809          | 0.7133   |
| 0.6906        | 26.0  | 5850  | 0.6707          | 0.7183   |
| 0.7171        | 27.0  | 6075  | 0.6612          | 0.725    |
| 0.6365        | 28.0  | 6300  | 0.6523          | 0.725    |
| 0.6614        | 29.0  | 6525  | 0.6441          | 0.73     |
| 0.6178        | 30.0  | 6750  | 0.6364          | 0.7367   |
| 0.6066        | 31.0  | 6975  | 0.6295          | 0.7417   |
| 0.6191        | 32.0  | 7200  | 0.6230          | 0.7467   |
| 0.6396        | 33.0  | 7425  | 0.6169          | 0.7533   |
| 0.5735        | 34.0  | 7650  | 0.6116          | 0.76     |
| 0.6004        | 35.0  | 7875  | 0.6067          | 0.76     |
| 0.61          | 36.0  | 8100  | 0.6022          | 0.7633   |
| 0.6           | 37.0  | 8325  | 0.5980          | 0.765    |
| 0.6039        | 38.0  | 8550  | 0.5941          | 0.7683   |
| 0.5538        | 39.0  | 8775  | 0.5906          | 0.7667   |
| 0.5453        | 40.0  | 9000  | 0.5875          | 0.77     |
| 0.603         | 41.0  | 9225  | 0.5848          | 0.77     |
| 0.606         | 42.0  | 9450  | 0.5825          | 0.7733   |
| 0.5852        | 43.0  | 9675  | 0.5804          | 0.7733   |
| 0.6705        | 44.0  | 9900  | 0.5786          | 0.7733   |
| 0.6134        | 45.0  | 10125 | 0.5771          | 0.7733   |
| 0.5569        | 46.0  | 10350 | 0.5759          | 0.7733   |
| 0.6464        | 47.0  | 10575 | 0.5750          | 0.7733   |
| 0.605         | 48.0  | 10800 | 0.5744          | 0.775    |
| 0.5703        | 49.0  | 11025 | 0.5740          | 0.775    |
| 0.5837        | 50.0  | 11250 | 0.5739          | 0.775    |


### 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