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# smids_1x_deit_tiny_sgd_001_fold5

This model is a fine-tuned version of [facebook/deit-tiny-patch16-224](https://huggingface.co/facebook/deit-tiny-patch16-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3402
- Accuracy: 0.855

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.0561        | 1.0   | 75   | 1.0620          | 0.43     |
| 0.937         | 2.0   | 150  | 0.9594          | 0.51     |
| 0.8543        | 3.0   | 225  | 0.8655          | 0.62     |
| 0.8165        | 4.0   | 300  | 0.7890          | 0.6667   |
| 0.7134        | 5.0   | 375  | 0.7178          | 0.7017   |
| 0.7528        | 6.0   | 450  | 0.6594          | 0.715    |
| 0.6452        | 7.0   | 525  | 0.6058          | 0.75     |
| 0.597         | 8.0   | 600  | 0.5655          | 0.7717   |
| 0.5415        | 9.0   | 675  | 0.5324          | 0.7867   |
| 0.5088        | 10.0  | 750  | 0.5114          | 0.8117   |
| 0.5609        | 11.0  | 825  | 0.4871          | 0.8067   |
| 0.4661        | 12.0  | 900  | 0.4691          | 0.8117   |
| 0.4495        | 13.0  | 975  | 0.4552          | 0.8217   |
| 0.4956        | 14.0  | 1050 | 0.4435          | 0.8217   |
| 0.4383        | 15.0  | 1125 | 0.4330          | 0.83     |
| 0.3764        | 16.0  | 1200 | 0.4243          | 0.8317   |
| 0.4263        | 17.0  | 1275 | 0.4146          | 0.83     |
| 0.39          | 18.0  | 1350 | 0.4087          | 0.83     |
| 0.4056        | 19.0  | 1425 | 0.4021          | 0.8367   |
| 0.4427        | 20.0  | 1500 | 0.3960          | 0.835    |
| 0.3559        | 21.0  | 1575 | 0.3906          | 0.84     |
| 0.3313        | 22.0  | 1650 | 0.3861          | 0.8383   |
| 0.3291        | 23.0  | 1725 | 0.3822          | 0.8383   |
| 0.3377        | 24.0  | 1800 | 0.3784          | 0.8383   |
| 0.3287        | 25.0  | 1875 | 0.3755          | 0.8433   |
| 0.3695        | 26.0  | 1950 | 0.3722          | 0.8467   |
| 0.3651        | 27.0  | 2025 | 0.3680          | 0.845    |
| 0.3421        | 28.0  | 2100 | 0.3650          | 0.845    |
| 0.3095        | 29.0  | 2175 | 0.3617          | 0.85     |
| 0.3232        | 30.0  | 2250 | 0.3592          | 0.8467   |
| 0.2955        | 31.0  | 2325 | 0.3570          | 0.8467   |
| 0.273         | 32.0  | 2400 | 0.3554          | 0.8483   |
| 0.3566        | 33.0  | 2475 | 0.3529          | 0.8467   |
| 0.3239        | 34.0  | 2550 | 0.3508          | 0.85     |
| 0.3231        | 35.0  | 2625 | 0.3501          | 0.8517   |
| 0.2755        | 36.0  | 2700 | 0.3491          | 0.8517   |
| 0.2727        | 37.0  | 2775 | 0.3485          | 0.8433   |
| 0.2931        | 38.0  | 2850 | 0.3470          | 0.845    |
| 0.2624        | 39.0  | 2925 | 0.3453          | 0.85     |
| 0.3211        | 40.0  | 3000 | 0.3440          | 0.855    |
| 0.2988        | 41.0  | 3075 | 0.3437          | 0.855    |
| 0.3248        | 42.0  | 3150 | 0.3424          | 0.855    |
| 0.3151        | 43.0  | 3225 | 0.3419          | 0.855    |
| 0.3064        | 44.0  | 3300 | 0.3415          | 0.8533   |
| 0.2827        | 45.0  | 3375 | 0.3410          | 0.8533   |
| 0.2824        | 46.0  | 3450 | 0.3410          | 0.8517   |
| 0.2636        | 47.0  | 3525 | 0.3406          | 0.8567   |
| 0.275         | 48.0  | 3600 | 0.3403          | 0.8567   |
| 0.2811        | 49.0  | 3675 | 0.3402          | 0.8567   |
| 0.2711        | 50.0  | 3750 | 0.3402          | 0.855    |


### 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