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# smids_1x_deit_tiny_adamax_0001_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: 0.7938
- Accuracy: 0.8883

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.3497        | 1.0   | 75   | 0.3438          | 0.8583   |
| 0.2686        | 2.0   | 150  | 0.4010          | 0.835    |
| 0.2132        | 3.0   | 225  | 0.3099          | 0.895    |
| 0.1475        | 4.0   | 300  | 0.4693          | 0.8433   |
| 0.07          | 5.0   | 375  | 0.3951          | 0.8967   |
| 0.0348        | 6.0   | 450  | 0.4706          | 0.8833   |
| 0.1076        | 7.0   | 525  | 0.4897          | 0.8817   |
| 0.0371        | 8.0   | 600  | 0.5659          | 0.8817   |
| 0.0539        | 9.0   | 675  | 0.5525          | 0.8917   |
| 0.0289        | 10.0  | 750  | 0.6768          | 0.8783   |
| 0.053         | 11.0  | 825  | 0.5526          | 0.9017   |
| 0.0394        | 12.0  | 900  | 0.6804          | 0.8867   |
| 0.0028        | 13.0  | 975  | 0.6916          | 0.8717   |
| 0.0003        | 14.0  | 1050 | 0.6282          | 0.8983   |
| 0.0001        | 15.0  | 1125 | 0.6544          | 0.8883   |
| 0.0001        | 16.0  | 1200 | 0.6284          | 0.9      |
| 0.0001        | 17.0  | 1275 | 0.6590          | 0.89     |
| 0.0087        | 18.0  | 1350 | 0.7168          | 0.885    |
| 0.0041        | 19.0  | 1425 | 0.6749          | 0.8933   |
| 0.0108        | 20.0  | 1500 | 0.7413          | 0.885    |
| 0.0001        | 21.0  | 1575 | 0.6857          | 0.8867   |
| 0.0           | 22.0  | 1650 | 0.7103          | 0.8833   |
| 0.0055        | 23.0  | 1725 | 0.7459          | 0.8883   |
| 0.0           | 24.0  | 1800 | 0.7428          | 0.8833   |
| 0.0           | 25.0  | 1875 | 0.7179          | 0.885    |
| 0.0041        | 26.0  | 1950 | 0.7150          | 0.8883   |
| 0.0           | 27.0  | 2025 | 0.7370          | 0.8833   |
| 0.0           | 28.0  | 2100 | 0.7342          | 0.885    |
| 0.0           | 29.0  | 2175 | 0.7378          | 0.8833   |
| 0.0           | 30.0  | 2250 | 0.7711          | 0.8883   |
| 0.0           | 31.0  | 2325 | 0.7434          | 0.8883   |
| 0.0           | 32.0  | 2400 | 0.7467          | 0.8883   |
| 0.0           | 33.0  | 2475 | 0.7543          | 0.885    |
| 0.0049        | 34.0  | 2550 | 0.7604          | 0.885    |
| 0.0078        | 35.0  | 2625 | 0.7800          | 0.8833   |
| 0.0032        | 36.0  | 2700 | 0.7784          | 0.885    |
| 0.0024        | 37.0  | 2775 | 0.7619          | 0.89     |
| 0.0           | 38.0  | 2850 | 0.7714          | 0.89     |
| 0.0           | 39.0  | 2925 | 0.7703          | 0.8883   |
| 0.0           | 40.0  | 3000 | 0.7842          | 0.885    |
| 0.0           | 41.0  | 3075 | 0.7774          | 0.8867   |
| 0.0028        | 42.0  | 3150 | 0.7773          | 0.8883   |
| 0.003         | 43.0  | 3225 | 0.7810          | 0.8867   |
| 0.0           | 44.0  | 3300 | 0.7850          | 0.8867   |
| 0.0027        | 45.0  | 3375 | 0.7856          | 0.8867   |
| 0.0025        | 46.0  | 3450 | 0.7889          | 0.8883   |
| 0.0052        | 47.0  | 3525 | 0.7872          | 0.8883   |
| 0.0           | 48.0  | 3600 | 0.7928          | 0.8883   |
| 0.0           | 49.0  | 3675 | 0.7922          | 0.8867   |
| 0.0045        | 50.0  | 3750 | 0.7938          | 0.8883   |


### 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