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# smids_1x_deit_tiny_adamax_0001_fold4

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: 1.0781
- Accuracy: 0.8733

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.437         | 1.0   | 75   | 0.3878          | 0.8467   |
| 0.3579        | 2.0   | 150  | 0.3600          | 0.8533   |
| 0.205         | 3.0   | 225  | 0.4349          | 0.8517   |
| 0.1111        | 4.0   | 300  | 0.4456          | 0.8633   |
| 0.0776        | 5.0   | 375  | 0.5350          | 0.8483   |
| 0.0492        | 6.0   | 450  | 0.6337          | 0.845    |
| 0.046         | 7.0   | 525  | 0.6226          | 0.8567   |
| 0.0111        | 8.0   | 600  | 0.7050          | 0.8617   |
| 0.0753        | 9.0   | 675  | 0.7254          | 0.8767   |
| 0.0006        | 10.0  | 750  | 0.8282          | 0.8717   |
| 0.0291        | 11.0  | 825  | 0.8528          | 0.87     |
| 0.0019        | 12.0  | 900  | 0.8610          | 0.875    |
| 0.0132        | 13.0  | 975  | 0.9173          | 0.87     |
| 0.0003        | 14.0  | 1050 | 0.9559          | 0.8717   |
| 0.0002        | 15.0  | 1125 | 0.9248          | 0.875    |
| 0.0004        | 16.0  | 1200 | 1.0147          | 0.8717   |
| 0.0016        | 17.0  | 1275 | 0.9350          | 0.8733   |
| 0.0151        | 18.0  | 1350 | 1.0934          | 0.8667   |
| 0.0007        | 19.0  | 1425 | 0.9772          | 0.8733   |
| 0.0001        | 20.0  | 1500 | 0.9904          | 0.8683   |
| 0.0007        | 21.0  | 1575 | 1.0162          | 0.8783   |
| 0.0           | 22.0  | 1650 | 1.0249          | 0.8767   |
| 0.0           | 23.0  | 1725 | 1.0244          | 0.8767   |
| 0.0092        | 24.0  | 1800 | 1.0296          | 0.88     |
| 0.0033        | 25.0  | 1875 | 1.0414          | 0.8767   |
| 0.0           | 26.0  | 1950 | 1.0492          | 0.8783   |
| 0.0           | 27.0  | 2025 | 1.0373          | 0.8733   |
| 0.0041        | 28.0  | 2100 | 1.0586          | 0.8767   |
| 0.0098        | 29.0  | 2175 | 1.0478          | 0.8783   |
| 0.0           | 30.0  | 2250 | 1.0448          | 0.8767   |
| 0.0           | 31.0  | 2325 | 1.0423          | 0.8733   |
| 0.0           | 32.0  | 2400 | 1.0519          | 0.875    |
| 0.0           | 33.0  | 2475 | 1.0303          | 0.875    |
| 0.0           | 34.0  | 2550 | 1.0338          | 0.875    |
| 0.0           | 35.0  | 2625 | 1.0649          | 0.8767   |
| 0.0           | 36.0  | 2700 | 1.0482          | 0.8767   |
| 0.0047        | 37.0  | 2775 | 1.0661          | 0.875    |
| 0.0           | 38.0  | 2850 | 1.0529          | 0.875    |
| 0.0           | 39.0  | 2925 | 1.0563          | 0.875    |
| 0.0           | 40.0  | 3000 | 1.0657          | 0.875    |
| 0.0035        | 41.0  | 3075 | 1.0671          | 0.875    |
| 0.0           | 42.0  | 3150 | 1.0658          | 0.875    |
| 0.0           | 43.0  | 3225 | 1.0667          | 0.8733   |
| 0.0           | 44.0  | 3300 | 1.0735          | 0.875    |
| 0.0           | 45.0  | 3375 | 1.0750          | 0.875    |
| 0.0           | 46.0  | 3450 | 1.0752          | 0.8733   |
| 0.0           | 47.0  | 3525 | 1.0774          | 0.8733   |
| 0.0           | 48.0  | 3600 | 1.0784          | 0.8733   |
| 0.0           | 49.0  | 3675 | 1.0781          | 0.8733   |
| 0.0           | 50.0  | 3750 | 1.0781          | 0.8733   |


### 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