
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# smids_1x_deit_tiny_sgd_001_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: 0.4122
- Accuracy: 0.835

## 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: 0.001
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.0732        | 1.0   | 75   | 1.0625          | 0.4117   |
| 0.95          | 2.0   | 150  | 0.9470          | 0.52     |
| 0.8388        | 3.0   | 225  | 0.8541          | 0.6133   |
| 0.8107        | 4.0   | 300  | 0.7814          | 0.66     |
| 0.7296        | 5.0   | 375  | 0.7116          | 0.6933   |
| 0.6565        | 6.0   | 450  | 0.6560          | 0.7233   |
| 0.6075        | 7.0   | 525  | 0.6119          | 0.7367   |
| 0.5566        | 8.0   | 600  | 0.5801          | 0.76     |
| 0.5592        | 9.0   | 675  | 0.5568          | 0.7717   |
| 0.4945        | 10.0  | 750  | 0.5396          | 0.785    |
| 0.484         | 11.0  | 825  | 0.5228          | 0.79     |
| 0.4564        | 12.0  | 900  | 0.5098          | 0.7917   |
| 0.4689        | 13.0  | 975  | 0.5015          | 0.7917   |
| 0.4232        | 14.0  | 1050 | 0.4882          | 0.7967   |
| 0.4151        | 15.0  | 1125 | 0.4851          | 0.795    |
| 0.3646        | 16.0  | 1200 | 0.4743          | 0.8017   |
| 0.3676        | 17.0  | 1275 | 0.4658          | 0.8083   |
| 0.3612        | 18.0  | 1350 | 0.4603          | 0.8017   |
| 0.4051        | 19.0  | 1425 | 0.4555          | 0.81     |
| 0.3477        | 20.0  | 1500 | 0.4507          | 0.81     |
| 0.375         | 21.0  | 1575 | 0.4488          | 0.8017   |
| 0.3102        | 22.0  | 1650 | 0.4425          | 0.8083   |
| 0.3203        | 23.0  | 1725 | 0.4393          | 0.8117   |
| 0.3847        | 24.0  | 1800 | 0.4374          | 0.8133   |
| 0.3175        | 25.0  | 1875 | 0.4337          | 0.8133   |
| 0.3275        | 26.0  | 1950 | 0.4305          | 0.8183   |
| 0.2952        | 27.0  | 2025 | 0.4280          | 0.8167   |
| 0.3226        | 28.0  | 2100 | 0.4272          | 0.82     |
| 0.2919        | 29.0  | 2175 | 0.4254          | 0.82     |
| 0.3056        | 30.0  | 2250 | 0.4233          | 0.8233   |
| 0.2391        | 31.0  | 2325 | 0.4233          | 0.8233   |
| 0.3148        | 32.0  | 2400 | 0.4205          | 0.8267   |
| 0.2897        | 33.0  | 2475 | 0.4204          | 0.8267   |
| 0.2561        | 34.0  | 2550 | 0.4195          | 0.8267   |
| 0.2841        | 35.0  | 2625 | 0.4186          | 0.8283   |
| 0.2572        | 36.0  | 2700 | 0.4171          | 0.8267   |
| 0.2531        | 37.0  | 2775 | 0.4160          | 0.8267   |
| 0.2737        | 38.0  | 2850 | 0.4152          | 0.8333   |
| 0.276         | 39.0  | 2925 | 0.4146          | 0.8317   |
| 0.3158        | 40.0  | 3000 | 0.4142          | 0.8317   |
| 0.2611        | 41.0  | 3075 | 0.4144          | 0.8367   |
| 0.2512        | 42.0  | 3150 | 0.4134          | 0.835    |
| 0.2782        | 43.0  | 3225 | 0.4133          | 0.835    |
| 0.2613        | 44.0  | 3300 | 0.4133          | 0.8367   |
| 0.2656        | 45.0  | 3375 | 0.4131          | 0.835    |
| 0.2575        | 46.0  | 3450 | 0.4126          | 0.835    |
| 0.2475        | 47.0  | 3525 | 0.4125          | 0.8367   |
| 0.2893        | 48.0  | 3600 | 0.4124          | 0.835    |
| 0.2785        | 49.0  | 3675 | 0.4123          | 0.835    |
| 0.2483        | 50.0  | 3750 | 0.4122          | 0.835    |


### 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