
<!-- 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_10x_deit_small_rms_00001_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: 0.8415
- Accuracy: 0.9132

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.2066        | 1.0   | 751   | 0.2884          | 0.8948   |
| 0.1058        | 2.0   | 1502  | 0.3397          | 0.8898   |
| 0.0676        | 3.0   | 2253  | 0.3801          | 0.9098   |
| 0.0667        | 4.0   | 3004  | 0.5510          | 0.8998   |
| 0.0253        | 5.0   | 3755  | 0.5205          | 0.9048   |
| 0.0216        | 6.0   | 4506  | 0.6002          | 0.9082   |
| 0.0362        | 7.0   | 5257  | 0.8486          | 0.8815   |
| 0.0357        | 8.0   | 6008  | 0.6658          | 0.9082   |
| 0.035         | 9.0   | 6759  | 0.5803          | 0.9065   |
| 0.001         | 10.0  | 7510  | 0.6719          | 0.9082   |
| 0.0231        | 11.0  | 8261  | 0.7324          | 0.9098   |
| 0.0001        | 12.0  | 9012  | 0.6703          | 0.9082   |
| 0.0008        | 13.0  | 9763  | 0.8412          | 0.8965   |
| 0.0582        | 14.0  | 10514 | 0.7418          | 0.9115   |
| 0.0077        | 15.0  | 11265 | 0.8736          | 0.8998   |
| 0.0           | 16.0  | 12016 | 0.7725          | 0.9115   |
| 0.0019        | 17.0  | 12767 | 0.7981          | 0.9065   |
| 0.0064        | 18.0  | 13518 | 1.0317          | 0.8848   |
| 0.0           | 19.0  | 14269 | 0.8686          | 0.9048   |
| 0.0           | 20.0  | 15020 | 0.8083          | 0.9082   |
| 0.0           | 21.0  | 15771 | 0.6862          | 0.9115   |
| 0.0           | 22.0  | 16522 | 0.7317          | 0.9132   |
| 0.0           | 23.0  | 17273 | 0.6937          | 0.9182   |
| 0.0           | 24.0  | 18024 | 0.7497          | 0.9199   |
| 0.0           | 25.0  | 18775 | 0.8180          | 0.9098   |
| 0.0001        | 26.0  | 19526 | 0.8680          | 0.9098   |
| 0.0           | 27.0  | 20277 | 0.8268          | 0.9115   |
| 0.0           | 28.0  | 21028 | 0.8126          | 0.9082   |
| 0.0042        | 29.0  | 21779 | 0.8397          | 0.9048   |
| 0.024         | 30.0  | 22530 | 0.8418          | 0.9098   |
| 0.0           | 31.0  | 23281 | 0.8800          | 0.9065   |
| 0.0           | 32.0  | 24032 | 0.8577          | 0.9065   |
| 0.0           | 33.0  | 24783 | 0.7988          | 0.9048   |
| 0.0           | 34.0  | 25534 | 0.8415          | 0.9032   |
| 0.0           | 35.0  | 26285 | 0.8311          | 0.9132   |
| 0.0           | 36.0  | 27036 | 0.8203          | 0.9149   |
| 0.0           | 37.0  | 27787 | 0.8136          | 0.9165   |
| 0.0           | 38.0  | 28538 | 0.8129          | 0.9199   |
| 0.0           | 39.0  | 29289 | 0.8165          | 0.9199   |
| 0.0           | 40.0  | 30040 | 0.8151          | 0.9149   |
| 0.0           | 41.0  | 30791 | 0.8242          | 0.9115   |
| 0.0           | 42.0  | 31542 | 0.8225          | 0.9115   |
| 0.0           | 43.0  | 32293 | 0.8294          | 0.9132   |
| 0.0           | 44.0  | 33044 | 0.8299          | 0.9132   |
| 0.0           | 45.0  | 33795 | 0.8337          | 0.9132   |
| 0.0           | 46.0  | 34546 | 0.8327          | 0.9132   |
| 0.0           | 47.0  | 35297 | 0.8358          | 0.9132   |
| 0.0           | 48.0  | 36048 | 0.8374          | 0.9132   |
| 0.0           | 49.0  | 36799 | 0.8388          | 0.9115   |
| 0.0           | 50.0  | 37550 | 0.8415          | 0.9132   |


### 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