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# smids_5x_beit_base_adamax_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: 1.0655
- Accuracy: 0.8965

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.3493        | 1.0   | 376   | 0.3879          | 0.8581   |
| 0.2155        | 2.0   | 752   | 0.3019          | 0.8915   |
| 0.1776        | 3.0   | 1128  | 0.3875          | 0.8548   |
| 0.1242        | 4.0   | 1504  | 0.3809          | 0.8831   |
| 0.0896        | 5.0   | 1880  | 0.5028          | 0.8798   |
| 0.1253        | 6.0   | 2256  | 0.4979          | 0.8982   |
| 0.1104        | 7.0   | 2632  | 0.5865          | 0.8681   |
| 0.0316        | 8.0   | 3008  | 0.5613          | 0.8831   |
| 0.0721        | 9.0   | 3384  | 0.5293          | 0.8965   |
| 0.0201        | 10.0  | 3760  | 0.6272          | 0.8881   |
| 0.0359        | 11.0  | 4136  | 0.4934          | 0.8998   |
| 0.0744        | 12.0  | 4512  | 0.6114          | 0.8948   |
| 0.0347        | 13.0  | 4888  | 0.5456          | 0.9082   |
| 0.0311        | 14.0  | 5264  | 0.6131          | 0.8881   |
| 0.0168        | 15.0  | 5640  | 0.6543          | 0.8932   |
| 0.0168        | 16.0  | 6016  | 0.7183          | 0.8881   |
| 0.0016        | 17.0  | 6392  | 0.6732          | 0.8982   |
| 0.0267        | 18.0  | 6768  | 0.6217          | 0.9015   |
| 0.0052        | 19.0  | 7144  | 0.8606          | 0.8881   |
| 0.0397        | 20.0  | 7520  | 0.6236          | 0.8965   |
| 0.0267        | 21.0  | 7896  | 0.7627          | 0.8898   |
| 0.0186        | 22.0  | 8272  | 0.6922          | 0.8965   |
| 0.0249        | 23.0  | 8648  | 0.7332          | 0.8865   |
| 0.0032        | 24.0  | 9024  | 0.7665          | 0.8998   |
| 0.0275        | 25.0  | 9400  | 0.6785          | 0.8948   |
| 0.024         | 26.0  | 9776  | 0.7205          | 0.8915   |
| 0.0009        | 27.0  | 10152 | 0.7304          | 0.9015   |
| 0.0003        | 28.0  | 10528 | 0.7307          | 0.9065   |
| 0.0154        | 29.0  | 10904 | 0.7519          | 0.8965   |
| 0.0031        | 30.0  | 11280 | 0.8948          | 0.8932   |
| 0.0002        | 31.0  | 11656 | 0.8220          | 0.8998   |
| 0.0001        | 32.0  | 12032 | 0.7942          | 0.9048   |
| 0.0           | 33.0  | 12408 | 0.8498          | 0.9065   |
| 0.0055        | 34.0  | 12784 | 0.7753          | 0.8798   |
| 0.0001        | 35.0  | 13160 | 0.8717          | 0.8915   |
| 0.0           | 36.0  | 13536 | 0.9811          | 0.8865   |
| 0.0           | 37.0  | 13912 | 0.9556          | 0.8898   |
| 0.0003        | 38.0  | 14288 | 0.9804          | 0.8865   |
| 0.013         | 39.0  | 14664 | 0.9497          | 0.8965   |
| 0.0           | 40.0  | 15040 | 1.0094          | 0.8831   |
| 0.0           | 41.0  | 15416 | 0.9964          | 0.8881   |
| 0.0           | 42.0  | 15792 | 0.9367          | 0.8965   |
| 0.0           | 43.0  | 16168 | 1.0400          | 0.9015   |
| 0.0009        | 44.0  | 16544 | 1.0395          | 0.8948   |
| 0.0           | 45.0  | 16920 | 1.0420          | 0.8932   |
| 0.0031        | 46.0  | 17296 | 1.0873          | 0.8965   |
| 0.0           | 47.0  | 17672 | 1.0455          | 0.9032   |
| 0.0           | 48.0  | 18048 | 1.0612          | 0.8965   |
| 0.0           | 49.0  | 18424 | 1.0632          | 0.8998   |
| 0.0024        | 50.0  | 18800 | 1.0655          | 0.8965   |


### 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