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# smids_1x_deit_small_sgd_001_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: 0.3679
- Accuracy: 0.8617

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.9928        | 1.0   | 75   | 0.9393          | 0.6083   |
| 0.8712        | 2.0   | 150  | 0.8295          | 0.6433   |
| 0.7828        | 3.0   | 225  | 0.7388          | 0.7083   |
| 0.6696        | 4.0   | 300  | 0.6714          | 0.7567   |
| 0.6657        | 5.0   | 375  | 0.6202          | 0.7767   |
| 0.5692        | 6.0   | 450  | 0.5823          | 0.7883   |
| 0.568         | 7.0   | 525  | 0.5504          | 0.795    |
| 0.5196        | 8.0   | 600  | 0.5262          | 0.805    |
| 0.5314        | 9.0   | 675  | 0.5056          | 0.8167   |
| 0.4867        | 10.0  | 750  | 0.4885          | 0.8183   |
| 0.4734        | 11.0  | 825  | 0.4740          | 0.8183   |
| 0.4623        | 12.0  | 900  | 0.4619          | 0.8267   |
| 0.4683        | 13.0  | 975  | 0.4510          | 0.835    |
| 0.4153        | 14.0  | 1050 | 0.4430          | 0.8317   |
| 0.3992        | 15.0  | 1125 | 0.4360          | 0.8333   |
| 0.3763        | 16.0  | 1200 | 0.4269          | 0.845    |
| 0.3576        | 17.0  | 1275 | 0.4206          | 0.85     |
| 0.3638        | 18.0  | 1350 | 0.4146          | 0.845    |
| 0.3788        | 19.0  | 1425 | 0.4098          | 0.8433   |
| 0.333         | 20.0  | 1500 | 0.4060          | 0.85     |
| 0.3671        | 21.0  | 1575 | 0.4016          | 0.85     |
| 0.3178        | 22.0  | 1650 | 0.3983          | 0.8533   |
| 0.3335        | 23.0  | 1725 | 0.3950          | 0.8467   |
| 0.3527        | 24.0  | 1800 | 0.3923          | 0.8533   |
| 0.3211        | 25.0  | 1875 | 0.3897          | 0.8483   |
| 0.3209        | 26.0  | 1950 | 0.3876          | 0.855    |
| 0.2907        | 27.0  | 2025 | 0.3854          | 0.8517   |
| 0.3294        | 28.0  | 2100 | 0.3833          | 0.86     |
| 0.2805        | 29.0  | 2175 | 0.3818          | 0.8533   |
| 0.3183        | 30.0  | 2250 | 0.3799          | 0.855    |
| 0.2622        | 31.0  | 2325 | 0.3784          | 0.86     |
| 0.3165        | 32.0  | 2400 | 0.3771          | 0.86     |
| 0.2898        | 33.0  | 2475 | 0.3761          | 0.8617   |
| 0.2776        | 34.0  | 2550 | 0.3750          | 0.8617   |
| 0.2847        | 35.0  | 2625 | 0.3739          | 0.8633   |
| 0.2631        | 36.0  | 2700 | 0.3731          | 0.86     |
| 0.2584        | 37.0  | 2775 | 0.3723          | 0.8583   |
| 0.2889        | 38.0  | 2850 | 0.3718          | 0.8617   |
| 0.3213        | 39.0  | 2925 | 0.3709          | 0.8617   |
| 0.2873        | 40.0  | 3000 | 0.3704          | 0.865    |
| 0.284         | 41.0  | 3075 | 0.3700          | 0.865    |
| 0.2939        | 42.0  | 3150 | 0.3694          | 0.8633   |
| 0.3121        | 43.0  | 3225 | 0.3692          | 0.8633   |
| 0.2744        | 44.0  | 3300 | 0.3688          | 0.8617   |
| 0.2881        | 45.0  | 3375 | 0.3686          | 0.8617   |
| 0.302         | 46.0  | 3450 | 0.3683          | 0.8617   |
| 0.2645        | 47.0  | 3525 | 0.3682          | 0.8617   |
| 0.307         | 48.0  | 3600 | 0.3681          | 0.8617   |
| 0.2733        | 49.0  | 3675 | 0.3680          | 0.8617   |
| 0.2676        | 50.0  | 3750 | 0.3679          | 0.8617   |


### 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