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# smids_1x_deit_tiny_rms_00001_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: 0.8945
- Accuracy: 0.8683

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.4595        | 1.0   | 75   | 0.3430          | 0.875    |
| 0.3075        | 2.0   | 150  | 0.3392          | 0.8667   |
| 0.1885        | 3.0   | 225  | 0.2939          | 0.8833   |
| 0.2401        | 4.0   | 300  | 0.3047          | 0.88     |
| 0.1913        | 5.0   | 375  | 0.2948          | 0.8833   |
| 0.0779        | 6.0   | 450  | 0.3840          | 0.8733   |
| 0.0659        | 7.0   | 525  | 0.3753          | 0.8867   |
| 0.0683        | 8.0   | 600  | 0.4413          | 0.88     |
| 0.0365        | 9.0   | 675  | 0.5012          | 0.875    |
| 0.0284        | 10.0  | 750  | 0.5436          | 0.8783   |
| 0.0339        | 11.0  | 825  | 0.6040          | 0.8883   |
| 0.0022        | 12.0  | 900  | 0.6211          | 0.8767   |
| 0.0421        | 13.0  | 975  | 0.7125          | 0.87     |
| 0.0295        | 14.0  | 1050 | 0.8588          | 0.8567   |
| 0.0522        | 15.0  | 1125 | 0.7259          | 0.875    |
| 0.0002        | 16.0  | 1200 | 0.7288          | 0.87     |
| 0.0239        | 17.0  | 1275 | 0.7745          | 0.865    |
| 0.0349        | 18.0  | 1350 | 0.7880          | 0.8667   |
| 0.0099        | 19.0  | 1425 | 0.7942          | 0.8683   |
| 0.0002        | 20.0  | 1500 | 0.8016          | 0.88     |
| 0.0181        | 21.0  | 1575 | 0.8187          | 0.87     |
| 0.0067        | 22.0  | 1650 | 0.8802          | 0.87     |
| 0.0135        | 23.0  | 1725 | 0.8554          | 0.865    |
| 0.0001        | 24.0  | 1800 | 0.8527          | 0.8733   |
| 0.0254        | 25.0  | 1875 | 0.7951          | 0.87     |
| 0.0001        | 26.0  | 1950 | 0.8033          | 0.87     |
| 0.0127        | 27.0  | 2025 | 0.8239          | 0.8783   |
| 0.0152        | 28.0  | 2100 | 0.9169          | 0.8683   |
| 0.019         | 29.0  | 2175 | 0.8220          | 0.8767   |
| 0.0038        | 30.0  | 2250 | 0.8836          | 0.8683   |
| 0.0001        | 31.0  | 2325 | 0.8686          | 0.875    |
| 0.0           | 32.0  | 2400 | 0.8778          | 0.8717   |
| 0.0121        | 33.0  | 2475 | 1.0279          | 0.8583   |
| 0.0001        | 34.0  | 2550 | 0.9813          | 0.8583   |
| 0.0072        | 35.0  | 2625 | 0.8647          | 0.8767   |
| 0.0           | 36.0  | 2700 | 0.8869          | 0.8683   |
| 0.0027        | 37.0  | 2775 | 0.9010          | 0.865    |
| 0.0           | 38.0  | 2850 | 0.9248          | 0.8633   |
| 0.0           | 39.0  | 2925 | 0.9337          | 0.8617   |
| 0.0           | 40.0  | 3000 | 0.8918          | 0.865    |
| 0.0054        | 41.0  | 3075 | 0.9181          | 0.865    |
| 0.0           | 42.0  | 3150 | 0.8813          | 0.8717   |
| 0.0078        | 43.0  | 3225 | 0.9054          | 0.8633   |
| 0.0           | 44.0  | 3300 | 0.8996          | 0.8667   |
| 0.0016        | 45.0  | 3375 | 0.9082          | 0.8633   |
| 0.0           | 46.0  | 3450 | 0.9083          | 0.865    |
| 0.0068        | 47.0  | 3525 | 0.9001          | 0.8683   |
| 0.0048        | 48.0  | 3600 | 0.8991          | 0.8683   |
| 0.0           | 49.0  | 3675 | 0.8976          | 0.8683   |
| 0.0029        | 50.0  | 3750 | 0.8945          | 0.8683   |


### 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