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# smids_1x_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: 0.3767
- Accuracy: 0.8614

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.9992        | 1.0   | 76   | 0.9734          | 0.5159   |
| 0.868         | 2.0   | 152  | 0.8565          | 0.6578   |
| 0.7395        | 3.0   | 228  | 0.7685          | 0.7112   |
| 0.6957        | 4.0   | 304  | 0.6964          | 0.7329   |
| 0.6074        | 5.0   | 380  | 0.6430          | 0.7546   |
| 0.5254        | 6.0   | 456  | 0.6017          | 0.7763   |
| 0.5109        | 7.0   | 532  | 0.5681          | 0.7930   |
| 0.4805        | 8.0   | 608  | 0.5426          | 0.7963   |
| 0.5102        | 9.0   | 684  | 0.5230          | 0.7980   |
| 0.3976        | 10.0  | 760  | 0.5054          | 0.8047   |
| 0.4427        | 11.0  | 836  | 0.4905          | 0.8130   |
| 0.4239        | 12.0  | 912  | 0.4775          | 0.8230   |
| 0.3866        | 13.0  | 988  | 0.4665          | 0.8247   |
| 0.3955        | 14.0  | 1064 | 0.4585          | 0.8264   |
| 0.3407        | 15.0  | 1140 | 0.4495          | 0.8314   |
| 0.3573        | 16.0  | 1216 | 0.4427          | 0.8347   |
| 0.3641        | 17.0  | 1292 | 0.4365          | 0.8364   |
| 0.3346        | 18.0  | 1368 | 0.4307          | 0.8397   |
| 0.3763        | 19.0  | 1444 | 0.4260          | 0.8414   |
| 0.3869        | 20.0  | 1520 | 0.4209          | 0.8481   |
| 0.3653        | 21.0  | 1596 | 0.4169          | 0.8497   |
| 0.3686        | 22.0  | 1672 | 0.4141          | 0.8548   |
| 0.3341        | 23.0  | 1748 | 0.4097          | 0.8531   |
| 0.3374        | 24.0  | 1824 | 0.4075          | 0.8564   |
| 0.2762        | 25.0  | 1900 | 0.4048          | 0.8548   |
| 0.3405        | 26.0  | 1976 | 0.4003          | 0.8548   |
| 0.2508        | 27.0  | 2052 | 0.3979          | 0.8581   |
| 0.3194        | 28.0  | 2128 | 0.3965          | 0.8531   |
| 0.2863        | 29.0  | 2204 | 0.3942          | 0.8598   |
| 0.2965        | 30.0  | 2280 | 0.3922          | 0.8614   |
| 0.3328        | 31.0  | 2356 | 0.3904          | 0.8614   |
| 0.2682        | 32.0  | 2432 | 0.3879          | 0.8614   |
| 0.27          | 33.0  | 2508 | 0.3869          | 0.8631   |
| 0.3255        | 34.0  | 2584 | 0.3856          | 0.8598   |
| 0.5893        | 35.0  | 2660 | 0.3845          | 0.8614   |
| 0.2978        | 36.0  | 2736 | 0.3831          | 0.8614   |
| 0.3197        | 37.0  | 2812 | 0.3822          | 0.8631   |
| 0.2821        | 38.0  | 2888 | 0.3814          | 0.8631   |
| 0.2797        | 39.0  | 2964 | 0.3806          | 0.8631   |
| 0.3067        | 40.0  | 3040 | 0.3796          | 0.8631   |
| 0.2337        | 41.0  | 3116 | 0.3790          | 0.8648   |
| 0.2989        | 42.0  | 3192 | 0.3784          | 0.8631   |
| 0.2792        | 43.0  | 3268 | 0.3779          | 0.8631   |
| 0.2985        | 44.0  | 3344 | 0.3775          | 0.8631   |
| 0.2895        | 45.0  | 3420 | 0.3772          | 0.8614   |
| 0.2249        | 46.0  | 3496 | 0.3770          | 0.8614   |
| 0.2475        | 47.0  | 3572 | 0.3768          | 0.8631   |
| 0.2872        | 48.0  | 3648 | 0.3767          | 0.8631   |
| 0.2536        | 49.0  | 3724 | 0.3767          | 0.8614   |
| 0.3607        | 50.0  | 3800 | 0.3767          | 0.8614   |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0

abnormal_sperm non-sperm normal_sperm