
<!-- 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_fold4

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: 1.3428
- Accuracy: 0.875

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.3711        | 1.0   | 225   | 0.3570          | 0.87     |
| 0.1764        | 2.0   | 450   | 0.4501          | 0.86     |
| 0.1125        | 3.0   | 675   | 0.7262          | 0.8017   |
| 0.1192        | 4.0   | 900   | 0.4185          | 0.8867   |
| 0.0724        | 5.0   | 1125  | 0.7207          | 0.8333   |
| 0.0693        | 6.0   | 1350  | 0.5544          | 0.88     |
| 0.012         | 7.0   | 1575  | 0.7617          | 0.865    |
| 0.1104        | 8.0   | 1800  | 0.8266          | 0.8633   |
| 0.0494        | 9.0   | 2025  | 0.7952          | 0.8633   |
| 0.043         | 10.0  | 2250  | 1.1043          | 0.8333   |
| 0.0404        | 11.0  | 2475  | 0.7760          | 0.8583   |
| 0.047         | 12.0  | 2700  | 0.9765          | 0.8483   |
| 0.0545        | 13.0  | 2925  | 0.8078          | 0.885    |
| 0.0635        | 14.0  | 3150  | 0.7741          | 0.8717   |
| 0.0334        | 15.0  | 3375  | 0.9921          | 0.86     |
| 0.0026        | 16.0  | 3600  | 0.9584          | 0.8717   |
| 0.0226        | 17.0  | 3825  | 1.0326          | 0.8633   |
| 0.0021        | 18.0  | 4050  | 1.0274          | 0.8567   |
| 0.0114        | 19.0  | 4275  | 1.0650          | 0.8467   |
| 0.0091        | 20.0  | 4500  | 1.1426          | 0.835    |
| 0.0087        | 21.0  | 4725  | 1.0992          | 0.8533   |
| 0.0141        | 22.0  | 4950  | 1.0907          | 0.8517   |
| 0.0005        | 23.0  | 5175  | 1.0030          | 0.85     |
| 0.0006        | 24.0  | 5400  | 1.1052          | 0.8483   |
| 0.0255        | 25.0  | 5625  | 1.0962          | 0.8633   |
| 0.0002        | 26.0  | 5850  | 1.0258          | 0.8817   |
| 0.0001        | 27.0  | 6075  | 0.8746          | 0.8883   |
| 0.0           | 28.0  | 6300  | 0.9827          | 0.88     |
| 0.0           | 29.0  | 6525  | 0.9372          | 0.8883   |
| 0.0004        | 30.0  | 6750  | 0.9400          | 0.875    |
| 0.0           | 31.0  | 6975  | 0.9451          | 0.8933   |
| 0.0           | 32.0  | 7200  | 1.0223          | 0.88     |
| 0.0007        | 33.0  | 7425  | 1.1451          | 0.88     |
| 0.0           | 34.0  | 7650  | 1.0754          | 0.875    |
| 0.0           | 35.0  | 7875  | 1.1610          | 0.8683   |
| 0.0           | 36.0  | 8100  | 1.1706          | 0.8717   |
| 0.0           | 37.0  | 8325  | 1.0772          | 0.8733   |
| 0.0           | 38.0  | 8550  | 1.1612          | 0.87     |
| 0.0001        | 39.0  | 8775  | 1.1977          | 0.8583   |
| 0.0           | 40.0  | 9000  | 1.2371          | 0.8667   |
| 0.0           | 41.0  | 9225  | 1.2466          | 0.8717   |
| 0.0034        | 42.0  | 9450  | 1.2736          | 0.8733   |
| 0.0           | 43.0  | 9675  | 1.2213          | 0.88     |
| 0.0027        | 44.0  | 9900  | 1.3864          | 0.8617   |
| 0.0           | 45.0  | 10125 | 1.3338          | 0.8717   |
| 0.0           | 46.0  | 10350 | 1.3311          | 0.8683   |
| 0.0           | 47.0  | 10575 | 1.3334          | 0.8717   |
| 0.0           | 48.0  | 10800 | 1.3390          | 0.8733   |
| 0.0           | 49.0  | 11025 | 1.3422          | 0.875    |
| 0.0           | 50.0  | 11250 | 1.3428          | 0.875    |


### 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