
<!-- 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_beit_base_rms_0001_fold1

This model is a fine-tuned version of [microsoft/beit-base-patch16-224](https://huggingface.co/microsoft/beit-base-patch16-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9099
- Accuracy: 0.9032

## 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: 0.0001
- 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.2877        | 1.0   | 376   | 0.3734          | 0.8397   |
| 0.263         | 2.0   | 752   | 0.2897          | 0.8898   |
| 0.214         | 3.0   | 1128  | 0.4392          | 0.8815   |
| 0.1401        | 4.0   | 1504  | 0.3640          | 0.8865   |
| 0.0913        | 5.0   | 1880  | 0.4071          | 0.8982   |
| 0.0792        | 6.0   | 2256  | 0.5796          | 0.8765   |
| 0.0326        | 7.0   | 2632  | 0.5828          | 0.8781   |
| 0.0613        | 8.0   | 3008  | 0.5485          | 0.8965   |
| 0.0614        | 9.0   | 3384  | 0.5394          | 0.8815   |
| 0.0378        | 10.0  | 3760  | 0.5802          | 0.8932   |
| 0.016         | 11.0  | 4136  | 0.5517          | 0.8998   |
| 0.1114        | 12.0  | 4512  | 0.5851          | 0.8798   |
| 0.0304        | 13.0  | 4888  | 0.5301          | 0.8731   |
| 0.0236        | 14.0  | 5264  | 0.6243          | 0.8965   |
| 0.0147        | 15.0  | 5640  | 0.5697          | 0.8998   |
| 0.0009        | 16.0  | 6016  | 0.5289          | 0.9098   |
| 0.003         | 17.0  | 6392  | 0.6450          | 0.8932   |
| 0.045         | 18.0  | 6768  | 0.7662          | 0.8915   |
| 0.0003        | 19.0  | 7144  | 0.6709          | 0.8898   |
| 0.0083        | 20.0  | 7520  | 0.7941          | 0.8865   |
| 0.0011        | 21.0  | 7896  | 0.8204          | 0.8831   |
| 0.0265        | 22.0  | 8272  | 0.7663          | 0.8798   |
| 0.0065        | 23.0  | 8648  | 0.7543          | 0.8865   |
| 0.0005        | 24.0  | 9024  | 0.8605          | 0.8881   |
| 0.0223        | 25.0  | 9400  | 0.7879          | 0.8815   |
| 0.0093        | 26.0  | 9776  | 0.8444          | 0.8748   |
| 0.0004        | 27.0  | 10152 | 0.7708          | 0.8781   |
| 0.0001        | 28.0  | 10528 | 0.7477          | 0.8948   |
| 0.0051        | 29.0  | 10904 | 0.7865          | 0.8831   |
| 0.0131        | 30.0  | 11280 | 0.8049          | 0.9098   |
| 0.0           | 31.0  | 11656 | 0.8832          | 0.8915   |
| 0.0001        | 32.0  | 12032 | 0.8723          | 0.8965   |
| 0.0007        | 33.0  | 12408 | 1.0043          | 0.8865   |
| 0.0001        | 34.0  | 12784 | 0.9137          | 0.8881   |
| 0.0019        | 35.0  | 13160 | 0.7356          | 0.9048   |
| 0.0           | 36.0  | 13536 | 0.7048          | 0.9032   |
| 0.0           | 37.0  | 13912 | 0.8706          | 0.9015   |
| 0.0           | 38.0  | 14288 | 0.7699          | 0.9032   |
| 0.0           | 39.0  | 14664 | 0.8383          | 0.8982   |
| 0.0           | 40.0  | 15040 | 0.8533          | 0.9048   |
| 0.0008        | 41.0  | 15416 | 0.8710          | 0.9015   |
| 0.0001        | 42.0  | 15792 | 0.9271          | 0.8898   |
| 0.0           | 43.0  | 16168 | 0.9308          | 0.8982   |
| 0.0           | 44.0  | 16544 | 0.9577          | 0.8982   |
| 0.0           | 45.0  | 16920 | 0.9412          | 0.8898   |
| 0.0033        | 46.0  | 17296 | 0.9423          | 0.8998   |
| 0.0           | 47.0  | 17672 | 0.9136          | 0.9048   |
| 0.0           | 48.0  | 18048 | 0.9005          | 0.9065   |
| 0.0001        | 49.0  | 18424 | 0.9138          | 0.9048   |
| 0.0023        | 50.0  | 18800 | 0.9099          | 0.9032   |


### 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