
<!-- 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_3x_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: 0.3433
- Accuracy: 0.8681

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.8537        | 1.0   | 226   | 0.8519          | 0.6194   |
| 0.627         | 2.0   | 452   | 0.6595          | 0.7162   |
| 0.5599        | 3.0   | 678   | 0.5836          | 0.7563   |
| 0.5294        | 4.0   | 904   | 0.5378          | 0.7830   |
| 0.541         | 5.0   | 1130  | 0.5094          | 0.7930   |
| 0.4706        | 6.0   | 1356  | 0.4828          | 0.8030   |
| 0.4252        | 7.0   | 1582  | 0.4633          | 0.8264   |
| 0.4132        | 8.0   | 1808  | 0.4456          | 0.8214   |
| 0.3872        | 9.0   | 2034  | 0.4395          | 0.8197   |
| 0.4235        | 10.0  | 2260  | 0.4220          | 0.8347   |
| 0.363         | 11.0  | 2486  | 0.4107          | 0.8414   |
| 0.3912        | 12.0  | 2712  | 0.4033          | 0.8381   |
| 0.304         | 13.0  | 2938  | 0.4009          | 0.8381   |
| 0.3002        | 14.0  | 3164  | 0.4007          | 0.8414   |
| 0.3207        | 15.0  | 3390  | 0.3907          | 0.8431   |
| 0.3295        | 16.0  | 3616  | 0.3840          | 0.8481   |
| 0.2579        | 17.0  | 3842  | 0.3879          | 0.8447   |
| 0.2728        | 18.0  | 4068  | 0.3774          | 0.8514   |
| 0.2754        | 19.0  | 4294  | 0.3738          | 0.8514   |
| 0.2647        | 20.0  | 4520  | 0.3691          | 0.8531   |
| 0.2981        | 21.0  | 4746  | 0.3671          | 0.8548   |
| 0.2768        | 22.0  | 4972  | 0.3598          | 0.8614   |
| 0.3183        | 23.0  | 5198  | 0.3674          | 0.8548   |
| 0.2945        | 24.0  | 5424  | 0.3555          | 0.8598   |
| 0.2478        | 25.0  | 5650  | 0.3546          | 0.8648   |
| 0.325         | 26.0  | 5876  | 0.3592          | 0.8564   |
| 0.2291        | 27.0  | 6102  | 0.3605          | 0.8548   |
| 0.2815        | 28.0  | 6328  | 0.3547          | 0.8564   |
| 0.2072        | 29.0  | 6554  | 0.3519          | 0.8614   |
| 0.3343        | 30.0  | 6780  | 0.3526          | 0.8631   |
| 0.2535        | 31.0  | 7006  | 0.3589          | 0.8614   |
| 0.25          | 32.0  | 7232  | 0.3529          | 0.8648   |
| 0.21          | 33.0  | 7458  | 0.3549          | 0.8581   |
| 0.2119        | 34.0  | 7684  | 0.3504          | 0.8598   |
| 0.2671        | 35.0  | 7910  | 0.3485          | 0.8648   |
| 0.2299        | 36.0  | 8136  | 0.3541          | 0.8614   |
| 0.2465        | 37.0  | 8362  | 0.3470          | 0.8631   |
| 0.2631        | 38.0  | 8588  | 0.3446          | 0.8648   |
| 0.239         | 39.0  | 8814  | 0.3471          | 0.8598   |
| 0.1883        | 40.0  | 9040  | 0.3479          | 0.8648   |
| 0.226         | 41.0  | 9266  | 0.3450          | 0.8681   |
| 0.258         | 42.0  | 9492  | 0.3451          | 0.8698   |
| 0.2562        | 43.0  | 9718  | 0.3456          | 0.8681   |
| 0.1938        | 44.0  | 9944  | 0.3435          | 0.8681   |
| 0.2807        | 45.0  | 10170 | 0.3449          | 0.8664   |
| 0.253         | 46.0  | 10396 | 0.3419          | 0.8698   |
| 0.2465        | 47.0  | 10622 | 0.3435          | 0.8664   |
| 0.2602        | 48.0  | 10848 | 0.3432          | 0.8664   |
| 0.2179        | 49.0  | 11074 | 0.3434          | 0.8681   |
| 0.2786        | 50.0  | 11300 | 0.3433          | 0.8681   |


### 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