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# smids_3x_deit_small_sgd_001_fold1

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: 0.3034
- Accuracy: 0.8765

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.874         | 1.0   | 226   | 0.8422          | 0.6477   |
| 0.6808        | 2.0   | 452   | 0.6564          | 0.7362   |
| 0.5184        | 3.0   | 678   | 0.5592          | 0.7780   |
| 0.5173        | 4.0   | 904   | 0.5087          | 0.7813   |
| 0.5113        | 5.0   | 1130  | 0.4746          | 0.8047   |
| 0.4469        | 6.0   | 1356  | 0.4445          | 0.8214   |
| 0.3731        | 7.0   | 1582  | 0.4247          | 0.8364   |
| 0.413         | 8.0   | 1808  | 0.4105          | 0.8397   |
| 0.369         | 9.0   | 2034  | 0.3943          | 0.8464   |
| 0.3882        | 10.0  | 2260  | 0.3826          | 0.8548   |
| 0.3525        | 11.0  | 2486  | 0.3772          | 0.8648   |
| 0.3235        | 12.0  | 2712  | 0.3644          | 0.8598   |
| 0.2669        | 13.0  | 2938  | 0.3578          | 0.8715   |
| 0.2463        | 14.0  | 3164  | 0.3531          | 0.8681   |
| 0.3167        | 15.0  | 3390  | 0.3484          | 0.8698   |
| 0.3258        | 16.0  | 3616  | 0.3417          | 0.8715   |
| 0.2311        | 17.0  | 3842  | 0.3383          | 0.8748   |
| 0.2669        | 18.0  | 4068  | 0.3359          | 0.8748   |
| 0.2828        | 19.0  | 4294  | 0.3332          | 0.8731   |
| 0.2409        | 20.0  | 4520  | 0.3289          | 0.8731   |
| 0.3064        | 21.0  | 4746  | 0.3277          | 0.8715   |
| 0.2918        | 22.0  | 4972  | 0.3274          | 0.8731   |
| 0.3068        | 23.0  | 5198  | 0.3218          | 0.8748   |
| 0.2544        | 24.0  | 5424  | 0.3201          | 0.8715   |
| 0.2207        | 25.0  | 5650  | 0.3191          | 0.8781   |
| 0.2923        | 26.0  | 5876  | 0.3153          | 0.8748   |
| 0.2033        | 27.0  | 6102  | 0.3156          | 0.8765   |
| 0.2492        | 28.0  | 6328  | 0.3128          | 0.8731   |
| 0.2136        | 29.0  | 6554  | 0.3157          | 0.8715   |
| 0.2344        | 30.0  | 6780  | 0.3143          | 0.8765   |
| 0.2394        | 31.0  | 7006  | 0.3111          | 0.8781   |
| 0.2259        | 32.0  | 7232  | 0.3105          | 0.8781   |
| 0.2144        | 33.0  | 7458  | 0.3085          | 0.8781   |
| 0.1831        | 34.0  | 7684  | 0.3101          | 0.8748   |
| 0.2542        | 35.0  | 7910  | 0.3071          | 0.8781   |
| 0.211         | 36.0  | 8136  | 0.3058          | 0.8781   |
| 0.2498        | 37.0  | 8362  | 0.3047          | 0.8815   |
| 0.2414        | 38.0  | 8588  | 0.3058          | 0.8765   |
| 0.1832        | 39.0  | 8814  | 0.3053          | 0.8765   |
| 0.1872        | 40.0  | 9040  | 0.3039          | 0.8781   |
| 0.1641        | 41.0  | 9266  | 0.3048          | 0.8765   |
| 0.244         | 42.0  | 9492  | 0.3047          | 0.8748   |
| 0.1877        | 43.0  | 9718  | 0.3040          | 0.8765   |
| 0.1335        | 44.0  | 9944  | 0.3029          | 0.8781   |
| 0.2501        | 45.0  | 10170 | 0.3036          | 0.8781   |
| 0.2161        | 46.0  | 10396 | 0.3032          | 0.8765   |
| 0.222         | 47.0  | 10622 | 0.3033          | 0.8781   |
| 0.2279        | 48.0  | 10848 | 0.3033          | 0.8765   |
| 0.1815        | 49.0  | 11074 | 0.3033          | 0.8765   |
| 0.1776        | 50.0  | 11300 | 0.3034          | 0.8765   |


### 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