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# smids_1x_deit_tiny_rms_00001_fold3

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: 0.7866
- Accuracy: 0.8917

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.4569        | 1.0   | 75   | 0.3524          | 0.8733   |
| 0.257         | 2.0   | 150  | 0.3177          | 0.8783   |
| 0.228         | 3.0   | 225  | 0.2830          | 0.895    |
| 0.1874        | 4.0   | 300  | 0.2625          | 0.9133   |
| 0.0988        | 5.0   | 375  | 0.3112          | 0.8867   |
| 0.0547        | 6.0   | 450  | 0.3480          | 0.895    |
| 0.0671        | 7.0   | 525  | 0.4401          | 0.8783   |
| 0.0314        | 8.0   | 600  | 0.4835          | 0.8917   |
| 0.0373        | 9.0   | 675  | 0.4879          | 0.8983   |
| 0.007         | 10.0  | 750  | 0.5903          | 0.895    |
| 0.0283        | 11.0  | 825  | 0.5783          | 0.8867   |
| 0.0151        | 12.0  | 900  | 0.7372          | 0.8833   |
| 0.0012        | 13.0  | 975  | 0.6965          | 0.8783   |
| 0.0175        | 14.0  | 1050 | 0.6546          | 0.89     |
| 0.0013        | 15.0  | 1125 | 0.7058          | 0.8783   |
| 0.0001        | 16.0  | 1200 | 0.6811          | 0.8917   |
| 0.0007        | 17.0  | 1275 | 0.7469          | 0.8967   |
| 0.0153        | 18.0  | 1350 | 0.6408          | 0.8917   |
| 0.0082        | 19.0  | 1425 | 0.8396          | 0.8783   |
| 0.0026        | 20.0  | 1500 | 0.8283          | 0.8883   |
| 0.0001        | 21.0  | 1575 | 0.7596          | 0.89     |
| 0.0037        | 22.0  | 1650 | 0.8137          | 0.875    |
| 0.007         | 23.0  | 1725 | 0.7276          | 0.8833   |
| 0.0           | 24.0  | 1800 | 0.6779          | 0.9      |
| 0.0001        | 25.0  | 1875 | 0.7204          | 0.895    |
| 0.0081        | 26.0  | 1950 | 0.7595          | 0.8883   |
| 0.0           | 27.0  | 2025 | 0.7620          | 0.895    |
| 0.0           | 28.0  | 2100 | 0.7575          | 0.8867   |
| 0.0001        | 29.0  | 2175 | 0.7827          | 0.89     |
| 0.0           | 30.0  | 2250 | 0.7351          | 0.8917   |
| 0.0           | 31.0  | 2325 | 0.7715          | 0.89     |
| 0.0           | 32.0  | 2400 | 0.7652          | 0.8917   |
| 0.0           | 33.0  | 2475 | 0.7881          | 0.89     |
| 0.0066        | 34.0  | 2550 | 0.7810          | 0.89     |
| 0.0102        | 35.0  | 2625 | 0.8490          | 0.89     |
| 0.0026        | 36.0  | 2700 | 0.7973          | 0.885    |
| 0.0016        | 37.0  | 2775 | 0.7751          | 0.8983   |
| 0.0           | 38.0  | 2850 | 0.7861          | 0.8933   |
| 0.0           | 39.0  | 2925 | 0.7652          | 0.8917   |
| 0.0           | 40.0  | 3000 | 0.7874          | 0.8917   |
| 0.0           | 41.0  | 3075 | 0.7876          | 0.8883   |
| 0.0033        | 42.0  | 3150 | 0.7858          | 0.8917   |
| 0.0029        | 43.0  | 3225 | 0.7835          | 0.8917   |
| 0.0           | 44.0  | 3300 | 0.7876          | 0.8917   |
| 0.0023        | 45.0  | 3375 | 0.7887          | 0.8917   |
| 0.0023        | 46.0  | 3450 | 0.7887          | 0.8917   |
| 0.0053        | 47.0  | 3525 | 0.7882          | 0.8917   |
| 0.0           | 48.0  | 3600 | 0.7869          | 0.8917   |
| 0.0           | 49.0  | 3675 | 0.7873          | 0.8917   |
| 0.0047        | 50.0  | 3750 | 0.7866          | 0.8917   |


### 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