
<!-- 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_5x_deit_tiny_adamax_001_fold3

This model is a fine-tuned version of [facebook/deit-small-patch16-224](https://huggingface.co/facebook/deit-small-patch16-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0439
- Accuracy: 0.905

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.3308        | 1.0   | 375   | 0.3353          | 0.875    |
| 0.2337        | 2.0   | 750   | 0.3320          | 0.8817   |
| 0.1696        | 3.0   | 1125  | 0.3479          | 0.8783   |
| 0.1669        | 4.0   | 1500  | 0.3755          | 0.8767   |
| 0.1864        | 5.0   | 1875  | 0.3099          | 0.8983   |
| 0.1212        | 6.0   | 2250  | 0.3912          | 0.91     |
| 0.1119        | 7.0   | 2625  | 0.4167          | 0.8817   |
| 0.1024        | 8.0   | 3000  | 0.4153          | 0.8733   |
| 0.0484        | 9.0   | 3375  | 0.5188          | 0.8733   |
| 0.0551        | 10.0  | 3750  | 0.6042          | 0.885    |
| 0.0468        | 11.0  | 4125  | 0.6570          | 0.8767   |
| 0.0137        | 12.0  | 4500  | 0.6069          | 0.8733   |
| 0.0177        | 13.0  | 4875  | 0.7091          | 0.8817   |
| 0.0201        | 14.0  | 5250  | 0.7010          | 0.89     |
| 0.0183        | 15.0  | 5625  | 0.6654          | 0.8867   |
| 0.0149        | 16.0  | 6000  | 0.7079          | 0.8883   |
| 0.0065        | 17.0  | 6375  | 0.6100          | 0.8933   |
| 0.001         | 18.0  | 6750  | 0.9491          | 0.8817   |
| 0.0034        | 19.0  | 7125  | 0.8269          | 0.8833   |
| 0.0213        | 20.0  | 7500  | 0.8028          | 0.8833   |
| 0.0137        | 21.0  | 7875  | 0.7227          | 0.8933   |
| 0.0           | 22.0  | 8250  | 0.8796          | 0.8917   |
| 0.0014        | 23.0  | 8625  | 0.8924          | 0.8733   |
| 0.0002        | 24.0  | 9000  | 0.6942          | 0.8917   |
| 0.0           | 25.0  | 9375  | 0.7445          | 0.89     |
| 0.0           | 26.0  | 9750  | 0.7840          | 0.885    |
| 0.0103        | 27.0  | 10125 | 0.7469          | 0.9033   |
| 0.0           | 28.0  | 10500 | 0.8867          | 0.8783   |
| 0.0           | 29.0  | 10875 | 0.8617          | 0.8867   |
| 0.003         | 30.0  | 11250 | 0.8295          | 0.8983   |
| 0.0008        | 31.0  | 11625 | 0.9061          | 0.895    |
| 0.0           | 32.0  | 12000 | 0.8630          | 0.8967   |
| 0.0           | 33.0  | 12375 | 0.8010          | 0.9017   |
| 0.0           | 34.0  | 12750 | 0.8248          | 0.8983   |
| 0.0           | 35.0  | 13125 | 0.8438          | 0.91     |
| 0.0           | 36.0  | 13500 | 0.9235          | 0.9      |
| 0.0           | 37.0  | 13875 | 0.8167          | 0.9083   |
| 0.0           | 38.0  | 14250 | 0.8531          | 0.9033   |
| 0.0           | 39.0  | 14625 | 0.9035          | 0.9067   |
| 0.0027        | 40.0  | 15000 | 0.9614          | 0.9017   |
| 0.0           | 41.0  | 15375 | 0.9740          | 0.9017   |
| 0.0           | 42.0  | 15750 | 0.9907          | 0.9      |
| 0.0           | 43.0  | 16125 | 0.9964          | 0.9033   |
| 0.0           | 44.0  | 16500 | 1.0084          | 0.9033   |
| 0.0           | 45.0  | 16875 | 1.0215          | 0.905    |
| 0.0           | 46.0  | 17250 | 1.0234          | 0.9017   |
| 0.0           | 47.0  | 17625 | 1.0315          | 0.905    |
| 0.0           | 48.0  | 18000 | 1.0372          | 0.905    |
| 0.0           | 49.0  | 18375 | 1.0413          | 0.905    |
| 0.0           | 50.0  | 18750 | 1.0439          | 0.905    |


### Framework versions

- Transformers 4.32.1
- Pytorch 2.1.1+cu121
- Datasets 2.12.0
- Tokenizers 0.13.2

abnormal_sperm non-sperm normal_sperm