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# smids_1x_deit_tiny_adamax_00001_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: 0.9763
- Accuracy: 0.86

## 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: 1e-05
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.7004        | 1.0   | 75   | 0.6502          | 0.7417   |
| 0.5011        | 2.0   | 150  | 0.4927          | 0.795    |
| 0.387         | 3.0   | 225  | 0.4418          | 0.8133   |
| 0.32          | 4.0   | 300  | 0.4153          | 0.835    |
| 0.2817        | 5.0   | 375  | 0.4075          | 0.8333   |
| 0.2233        | 6.0   | 450  | 0.3963          | 0.8433   |
| 0.2099        | 7.0   | 525  | 0.3993          | 0.8517   |
| 0.1587        | 8.0   | 600  | 0.4089          | 0.8517   |
| 0.1492        | 9.0   | 675  | 0.4263          | 0.8533   |
| 0.1374        | 10.0  | 750  | 0.4223          | 0.86     |
| 0.1106        | 11.0  | 825  | 0.4566          | 0.8533   |
| 0.0777        | 12.0  | 900  | 0.4729          | 0.8433   |
| 0.0787        | 13.0  | 975  | 0.4848          | 0.8567   |
| 0.0407        | 14.0  | 1050 | 0.5231          | 0.85     |
| 0.0237        | 15.0  | 1125 | 0.5607          | 0.8533   |
| 0.0206        | 16.0  | 1200 | 0.6045          | 0.8483   |
| 0.0395        | 17.0  | 1275 | 0.6305          | 0.855    |
| 0.0399        | 18.0  | 1350 | 0.6575          | 0.85     |
| 0.0183        | 19.0  | 1425 | 0.7037          | 0.8467   |
| 0.0153        | 20.0  | 1500 | 0.7259          | 0.855    |
| 0.005         | 21.0  | 1575 | 0.7531          | 0.85     |
| 0.0017        | 22.0  | 1650 | 0.7833          | 0.85     |
| 0.0025        | 23.0  | 1725 | 0.8056          | 0.8467   |
| 0.0157        | 24.0  | 1800 | 0.8300          | 0.855    |
| 0.007         | 25.0  | 1875 | 0.8590          | 0.85     |
| 0.0006        | 26.0  | 1950 | 0.8573          | 0.8483   |
| 0.0006        | 27.0  | 2025 | 0.8637          | 0.8483   |
| 0.0055        | 28.0  | 2100 | 0.8671          | 0.8533   |
| 0.0223        | 29.0  | 2175 | 0.8791          | 0.85     |
| 0.0007        | 30.0  | 2250 | 0.8908          | 0.845    |
| 0.0004        | 31.0  | 2325 | 0.8875          | 0.85     |
| 0.0003        | 32.0  | 2400 | 0.8993          | 0.8533   |
| 0.0004        | 33.0  | 2475 | 0.9065          | 0.8517   |
| 0.0002        | 34.0  | 2550 | 0.9107          | 0.855    |
| 0.0003        | 35.0  | 2625 | 0.9197          | 0.855    |
| 0.0002        | 36.0  | 2700 | 0.9278          | 0.8517   |
| 0.02          | 37.0  | 2775 | 0.9327          | 0.8633   |
| 0.0002        | 38.0  | 2850 | 0.9380          | 0.8617   |
| 0.0002        | 39.0  | 2925 | 0.9441          | 0.8567   |
| 0.0003        | 40.0  | 3000 | 0.9479          | 0.86     |
| 0.0203        | 41.0  | 3075 | 0.9563          | 0.8583   |
| 0.0002        | 42.0  | 3150 | 0.9601          | 0.86     |
| 0.0002        | 43.0  | 3225 | 0.9632          | 0.86     |
| 0.0002        | 44.0  | 3300 | 0.9684          | 0.8533   |
| 0.0002        | 45.0  | 3375 | 0.9703          | 0.86     |
| 0.0002        | 46.0  | 3450 | 0.9720          | 0.86     |
| 0.0002        | 47.0  | 3525 | 0.9736          | 0.86     |
| 0.0002        | 48.0  | 3600 | 0.9753          | 0.86     |
| 0.0001        | 49.0  | 3675 | 0.9759          | 0.86     |
| 0.0001        | 50.0  | 3750 | 0.9763          | 0.86     |


### 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