
<!-- 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_base_rms_001_fold1

This model is a fine-tuned version of [facebook/deit-base-patch16-224](https://huggingface.co/facebook/deit-base-patch16-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6839
- Accuracy: 0.7863

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 1.1051        | 1.0   | 376   | 1.0840          | 0.3356   |
| 0.8654        | 2.0   | 752   | 0.8754          | 0.4841   |
| 0.7982        | 3.0   | 1128  | 0.7992          | 0.5843   |
| 0.8215        | 4.0   | 1504  | 0.8640          | 0.5509   |
| 0.8937        | 5.0   | 1880  | 0.7446          | 0.6678   |
| 0.7292        | 6.0   | 2256  | 0.7760          | 0.6361   |
| 0.6914        | 7.0   | 2632  | 0.7052          | 0.6694   |
| 0.6499        | 8.0   | 3008  | 0.7542          | 0.6511   |
| 0.6981        | 9.0   | 3384  | 0.6919          | 0.6912   |
| 0.6852        | 10.0  | 3760  | 0.6488          | 0.6995   |
| 0.5929        | 11.0  | 4136  | 0.6360          | 0.7162   |
| 0.6018        | 12.0  | 4512  | 0.6410          | 0.7212   |
| 0.578         | 13.0  | 4888  | 0.6824          | 0.7078   |
| 0.5646        | 14.0  | 5264  | 0.6123          | 0.7546   |
| 0.5813        | 15.0  | 5640  | 0.6611          | 0.7479   |
| 0.5334        | 16.0  | 6016  | 0.6911          | 0.7012   |
| 0.4401        | 17.0  | 6392  | 0.6234          | 0.7362   |
| 0.5629        | 18.0  | 6768  | 0.5782          | 0.7412   |
| 0.5062        | 19.0  | 7144  | 0.6504          | 0.7329   |
| 0.444         | 20.0  | 7520  | 0.5828          | 0.7696   |
| 0.4995        | 21.0  | 7896  | 0.5919          | 0.7446   |
| 0.4251        | 22.0  | 8272  | 0.6276          | 0.7629   |
| 0.4812        | 23.0  | 8648  | 0.6155          | 0.7462   |
| 0.4775        | 24.0  | 9024  | 0.6984          | 0.7179   |
| 0.4597        | 25.0  | 9400  | 0.6577          | 0.7295   |
| 0.4394        | 26.0  | 9776  | 0.5934          | 0.7429   |
| 0.4129        | 27.0  | 10152 | 0.6066          | 0.7563   |
| 0.4098        | 28.0  | 10528 | 0.5792          | 0.7579   |
| 0.4483        | 29.0  | 10904 | 0.5708          | 0.7613   |
| 0.3862        | 30.0  | 11280 | 0.5970          | 0.7679   |
| 0.4253        | 31.0  | 11656 | 0.6053          | 0.7546   |
| 0.4815        | 32.0  | 12032 | 0.5808          | 0.7479   |
| 0.3892        | 33.0  | 12408 | 0.5698          | 0.7613   |
| 0.35          | 34.0  | 12784 | 0.5670          | 0.7563   |
| 0.3952        | 35.0  | 13160 | 0.5921          | 0.7696   |
| 0.4191        | 36.0  | 13536 | 0.5999          | 0.7863   |
| 0.3174        | 37.0  | 13912 | 0.5845          | 0.7679   |
| 0.3864        | 38.0  | 14288 | 0.6529          | 0.7496   |
| 0.4036        | 39.0  | 14664 | 0.6327          | 0.7679   |
| 0.4274        | 40.0  | 15040 | 0.5923          | 0.7646   |
| 0.357         | 41.0  | 15416 | 0.6017          | 0.7863   |
| 0.348         | 42.0  | 15792 | 0.6309          | 0.7763   |
| 0.2967        | 43.0  | 16168 | 0.6418          | 0.7679   |
| 0.3292        | 44.0  | 16544 | 0.6405          | 0.7780   |
| 0.3428        | 45.0  | 16920 | 0.6600          | 0.7813   |
| 0.3127        | 46.0  | 17296 | 0.6429          | 0.7780   |
| 0.2979        | 47.0  | 17672 | 0.6618          | 0.7813   |
| 0.3209        | 48.0  | 18048 | 0.6803          | 0.7796   |
| 0.2866        | 49.0  | 18424 | 0.6856          | 0.7880   |
| 0.2611        | 50.0  | 18800 | 0.6839          | 0.7863   |


### 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