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# smids_5x_beit_base_sgd_001_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: 0.2771
- Accuracy: 0.8915

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.7737        | 1.0   | 376   | 1.0623          | 0.3957   |
| 0.6499        | 2.0   | 752   | 0.5904          | 0.7679   |
| 0.5039        | 3.0   | 1128  | 0.4948          | 0.8114   |
| 0.4425        | 4.0   | 1504  | 0.4355          | 0.8314   |
| 0.4117        | 5.0   | 1880  | 0.4034          | 0.8381   |
| 0.3506        | 6.0   | 2256  | 0.3735          | 0.8497   |
| 0.3184        | 7.0   | 2632  | 0.3579          | 0.8614   |
| 0.3583        | 8.0   | 3008  | 0.3422          | 0.8664   |
| 0.3344        | 9.0   | 3384  | 0.3340          | 0.8765   |
| 0.3048        | 10.0  | 3760  | 0.3243          | 0.8731   |
| 0.3275        | 11.0  | 4136  | 0.3128          | 0.8815   |
| 0.2663        | 12.0  | 4512  | 0.3111          | 0.8765   |
| 0.2691        | 13.0  | 4888  | 0.3046          | 0.8815   |
| 0.2761        | 14.0  | 5264  | 0.3135          | 0.8715   |
| 0.3203        | 15.0  | 5640  | 0.2998          | 0.8831   |
| 0.2245        | 16.0  | 6016  | 0.2963          | 0.8881   |
| 0.2282        | 17.0  | 6392  | 0.2992          | 0.8881   |
| 0.3086        | 18.0  | 6768  | 0.2841          | 0.8881   |
| 0.2882        | 19.0  | 7144  | 0.2985          | 0.8831   |
| 0.2358        | 20.0  | 7520  | 0.2906          | 0.8898   |
| 0.25          | 21.0  | 7896  | 0.2925          | 0.8848   |
| 0.2381        | 22.0  | 8272  | 0.2832          | 0.8915   |
| 0.2558        | 23.0  | 8648  | 0.2829          | 0.8898   |
| 0.2316        | 24.0  | 9024  | 0.2855          | 0.8865   |
| 0.2594        | 25.0  | 9400  | 0.2808          | 0.8915   |
| 0.2312        | 26.0  | 9776  | 0.2815          | 0.8915   |
| 0.1664        | 27.0  | 10152 | 0.2829          | 0.8865   |
| 0.2051        | 28.0  | 10528 | 0.2875          | 0.8815   |
| 0.229         | 29.0  | 10904 | 0.2816          | 0.8881   |
| 0.1761        | 30.0  | 11280 | 0.2816          | 0.8915   |
| 0.2039        | 31.0  | 11656 | 0.2802          | 0.8965   |
| 0.2453        | 32.0  | 12032 | 0.2762          | 0.8965   |
| 0.186         | 33.0  | 12408 | 0.2762          | 0.8965   |
| 0.1739        | 34.0  | 12784 | 0.2763          | 0.8948   |
| 0.1942        | 35.0  | 13160 | 0.2781          | 0.8898   |
| 0.2172        | 36.0  | 13536 | 0.2768          | 0.8898   |
| 0.1982        | 37.0  | 13912 | 0.2760          | 0.8965   |
| 0.2031        | 38.0  | 14288 | 0.2780          | 0.8881   |
| 0.2045        | 39.0  | 14664 | 0.2746          | 0.8948   |
| 0.1936        | 40.0  | 15040 | 0.2754          | 0.8998   |
| 0.2051        | 41.0  | 15416 | 0.2792          | 0.8948   |
| 0.2059        | 42.0  | 15792 | 0.2787          | 0.8932   |
| 0.2037        | 43.0  | 16168 | 0.2780          | 0.8932   |
| 0.2183        | 44.0  | 16544 | 0.2796          | 0.8898   |
| 0.1934        | 45.0  | 16920 | 0.2779          | 0.8965   |
| 0.2385        | 46.0  | 17296 | 0.2770          | 0.8915   |
| 0.1872        | 47.0  | 17672 | 0.2768          | 0.8948   |
| 0.1967        | 48.0  | 18048 | 0.2773          | 0.8898   |
| 0.1829        | 49.0  | 18424 | 0.2770          | 0.8932   |
| 0.1506        | 50.0  | 18800 | 0.2771          | 0.8915   |


### 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