
<!-- 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_small_rms_0001_fold2

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: 1.1115
- Accuracy: 0.8802

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.3676        | 1.0   | 225   | 0.3260          | 0.8652   |
| 0.2682        | 2.0   | 450   | 0.4038          | 0.8369   |
| 0.1969        | 3.0   | 675   | 0.3463          | 0.8569   |
| 0.1563        | 4.0   | 900   | 0.3656          | 0.8869   |
| 0.127         | 5.0   | 1125  | 0.4906          | 0.8885   |
| 0.0496        | 6.0   | 1350  | 0.4366          | 0.8852   |
| 0.0874        | 7.0   | 1575  | 0.6811          | 0.8735   |
| 0.0746        | 8.0   | 1800  | 0.4728          | 0.9002   |
| 0.0301        | 9.0   | 2025  | 0.6425          | 0.8802   |
| 0.0064        | 10.0  | 2250  | 0.6457          | 0.8852   |
| 0.021         | 11.0  | 2475  | 0.6671          | 0.8752   |
| 0.0135        | 12.0  | 2700  | 0.6914          | 0.8852   |
| 0.0087        | 13.0  | 2925  | 0.8348          | 0.8686   |
| 0.0257        | 14.0  | 3150  | 0.6378          | 0.8769   |
| 0.0699        | 15.0  | 3375  | 0.7199          | 0.8885   |
| 0.003         | 16.0  | 3600  | 0.7607          | 0.8869   |
| 0.003         | 17.0  | 3825  | 0.7580          | 0.8819   |
| 0.0003        | 18.0  | 4050  | 0.7463          | 0.8835   |
| 0.0005        | 19.0  | 4275  | 0.6721          | 0.8852   |
| 0.0305        | 20.0  | 4500  | 0.7465          | 0.8785   |
| 0.03          | 21.0  | 4725  | 0.8137          | 0.8752   |
| 0.0098        | 22.0  | 4950  | 0.7797          | 0.8802   |
| 0.0223        | 23.0  | 5175  | 0.8830          | 0.8735   |
| 0.0014        | 24.0  | 5400  | 0.9177          | 0.8752   |
| 0.0318        | 25.0  | 5625  | 1.2159          | 0.8519   |
| 0.0263        | 26.0  | 5850  | 0.9640          | 0.8669   |
| 0.0494        | 27.0  | 6075  | 0.9004          | 0.8702   |
| 0.0002        | 28.0  | 6300  | 1.0163          | 0.8752   |
| 0.0354        | 29.0  | 6525  | 1.0067          | 0.8752   |
| 0.0062        | 30.0  | 6750  | 1.0029          | 0.8785   |
| 0.0239        | 31.0  | 6975  | 0.8464          | 0.8835   |
| 0.0305        | 32.0  | 7200  | 0.8764          | 0.8752   |
| 0.0007        | 33.0  | 7425  | 0.8617          | 0.8769   |
| 0.0           | 34.0  | 7650  | 0.9176          | 0.8785   |
| 0.0           | 35.0  | 7875  | 0.9537          | 0.8885   |
| 0.0028        | 36.0  | 8100  | 0.9078          | 0.8802   |
| 0.0           | 37.0  | 8325  | 0.9401          | 0.8902   |
| 0.0066        | 38.0  | 8550  | 0.9351          | 0.8802   |
| 0.0208        | 39.0  | 8775  | 0.9403          | 0.8869   |
| 0.0           | 40.0  | 9000  | 1.0137          | 0.8852   |
| 0.0103        | 41.0  | 9225  | 1.0628          | 0.8769   |
| 0.0           | 42.0  | 9450  | 0.9758          | 0.8802   |
| 0.0           | 43.0  | 9675  | 1.0037          | 0.8802   |
| 0.0           | 44.0  | 9900  | 1.0404          | 0.8769   |
| 0.0           | 45.0  | 10125 | 1.0618          | 0.8819   |
| 0.0           | 46.0  | 10350 | 1.0847          | 0.8802   |
| 0.0           | 47.0  | 10575 | 1.0984          | 0.8819   |
| 0.0           | 48.0  | 10800 | 1.1045          | 0.8819   |
| 0.0023        | 49.0  | 11025 | 1.1110          | 0.8802   |
| 0.0023        | 50.0  | 11250 | 1.1115          | 0.8802   |


### 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