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# smids_10x_deit_small_adamax_001_fold1

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: 0.9202
- Accuracy: 0.9098

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.3418        | 1.0   | 751   | 0.3645          | 0.8681   |
| 0.228         | 2.0   | 1502  | 0.3383          | 0.8815   |
| 0.2191        | 3.0   | 2253  | 0.3232          | 0.8915   |
| 0.2142        | 4.0   | 3004  | 0.3382          | 0.9015   |
| 0.1533        | 5.0   | 3755  | 0.4440          | 0.8681   |
| 0.1001        | 6.0   | 4506  | 0.4207          | 0.8698   |
| 0.085         | 7.0   | 5257  | 0.5360          | 0.8748   |
| 0.0859        | 8.0   | 6008  | 0.4176          | 0.9032   |
| 0.0802        | 9.0   | 6759  | 0.5292          | 0.8781   |
| 0.0332        | 10.0  | 7510  | 0.5218          | 0.9015   |
| 0.0553        | 11.0  | 8261  | 0.4537          | 0.9015   |
| 0.039         | 12.0  | 9012  | 0.7412          | 0.8848   |
| 0.0239        | 13.0  | 9763  | 0.6194          | 0.8915   |
| 0.0108        | 14.0  | 10514 | 0.7066          | 0.8848   |
| 0.0526        | 15.0  | 11265 | 0.6131          | 0.9032   |
| 0.0063        | 16.0  | 12016 | 0.8576          | 0.8681   |
| 0.0154        | 17.0  | 12767 | 0.6269          | 0.8948   |
| 0.0175        | 18.0  | 13518 | 0.6667          | 0.9048   |
| 0.0017        | 19.0  | 14269 | 0.6041          | 0.9048   |
| 0.0002        | 20.0  | 15020 | 0.7017          | 0.8798   |
| 0.0104        | 21.0  | 15771 | 0.6523          | 0.8965   |
| 0.0004        | 22.0  | 16522 | 0.5978          | 0.9065   |
| 0.0007        | 23.0  | 17273 | 0.7511          | 0.8982   |
| 0.0003        | 24.0  | 18024 | 0.8000          | 0.8948   |
| 0.0003        | 25.0  | 18775 | 0.7612          | 0.8932   |
| 0.0002        | 26.0  | 19526 | 0.7543          | 0.9032   |
| 0.0           | 27.0  | 20277 | 0.7144          | 0.9032   |
| 0.0           | 28.0  | 21028 | 0.8366          | 0.8831   |
| 0.0053        | 29.0  | 21779 | 0.9486          | 0.8815   |
| 0.0           | 30.0  | 22530 | 0.9579          | 0.8932   |
| 0.0           | 31.0  | 23281 | 0.8276          | 0.9015   |
| 0.0           | 32.0  | 24032 | 0.8430          | 0.9065   |
| 0.0           | 33.0  | 24783 | 0.7752          | 0.9098   |
| 0.0           | 34.0  | 25534 | 0.7966          | 0.9098   |
| 0.0           | 35.0  | 26285 | 0.8408          | 0.9048   |
| 0.0           | 36.0  | 27036 | 0.8314          | 0.9065   |
| 0.0           | 37.0  | 27787 | 0.8780          | 0.9015   |
| 0.0           | 38.0  | 28538 | 0.8886          | 0.8998   |
| 0.0           | 39.0  | 29289 | 0.8653          | 0.9048   |
| 0.0           | 40.0  | 30040 | 0.8404          | 0.9082   |
| 0.0           | 41.0  | 30791 | 0.8630          | 0.8998   |
| 0.0           | 42.0  | 31542 | 0.8333          | 0.9098   |
| 0.0           | 43.0  | 32293 | 0.9256          | 0.9048   |
| 0.0           | 44.0  | 33044 | 0.8529          | 0.9082   |
| 0.0           | 45.0  | 33795 | 0.8963          | 0.9082   |
| 0.0           | 46.0  | 34546 | 0.8944          | 0.9098   |
| 0.0           | 47.0  | 35297 | 0.9059          | 0.9098   |
| 0.0           | 48.0  | 36048 | 0.9120          | 0.9098   |
| 0.0           | 49.0  | 36799 | 0.9160          | 0.9098   |
| 0.0           | 50.0  | 37550 | 0.9202          | 0.9098   |


### Framework versions

- Transformers 4.32.1
- Pytorch 2.1.0+cu121
- Datasets 2.12.0
- Tokenizers 0.13.2

abnormal_sperm non-sperm normal_sperm