
<!-- 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_small_rms_00001_fold3

This model is a fine-tuned version of [facebook/deit-small-patch16-224](https://huggingface.co/facebook/deit-small-patch16-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0303
- Accuracy: 0.8967

## 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: 1e-05
- 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.2375        | 1.0   | 375   | 0.2542          | 0.9083   |
| 0.1409        | 2.0   | 750   | 0.2770          | 0.91     |
| 0.0609        | 3.0   | 1125  | 0.3094          | 0.8983   |
| 0.0237        | 4.0   | 1500  | 0.3996          | 0.8983   |
| 0.0338        | 5.0   | 1875  | 0.5715          | 0.8883   |
| 0.0534        | 6.0   | 2250  | 0.6112          | 0.8933   |
| 0.0052        | 7.0   | 2625  | 0.6878          | 0.8933   |
| 0.0006        | 8.0   | 3000  | 0.6908          | 0.9      |
| 0.0283        | 9.0   | 3375  | 0.6671          | 0.8983   |
| 0.0065        | 10.0  | 3750  | 0.7326          | 0.9067   |
| 0.0065        | 11.0  | 4125  | 0.6436          | 0.915    |
| 0.0           | 12.0  | 4500  | 0.7498          | 0.9      |
| 0.0016        | 13.0  | 4875  | 0.8235          | 0.8933   |
| 0.0003        | 14.0  | 5250  | 0.8655          | 0.895    |
| 0.0082        | 15.0  | 5625  | 0.7486          | 0.9067   |
| 0.0001        | 16.0  | 6000  | 0.8142          | 0.9017   |
| 0.0001        | 17.0  | 6375  | 0.7387          | 0.8917   |
| 0.0001        | 18.0  | 6750  | 0.8424          | 0.9067   |
| 0.0           | 19.0  | 7125  | 0.7973          | 0.9017   |
| 0.0378        | 20.0  | 7500  | 0.7948          | 0.8967   |
| 0.0           | 21.0  | 7875  | 0.8629          | 0.8917   |
| 0.0           | 22.0  | 8250  | 0.7939          | 0.9017   |
| 0.0063        | 23.0  | 8625  | 0.8369          | 0.89     |
| 0.0           | 24.0  | 9000  | 0.8848          | 0.9      |
| 0.0           | 25.0  | 9375  | 0.8284          | 0.91     |
| 0.0           | 26.0  | 9750  | 0.9412          | 0.9      |
| 0.0           | 27.0  | 10125 | 0.8363          | 0.905    |
| 0.0           | 28.0  | 10500 | 0.9351          | 0.8917   |
| 0.0           | 29.0  | 10875 | 0.8734          | 0.9033   |
| 0.0037        | 30.0  | 11250 | 0.9770          | 0.9067   |
| 0.0           | 31.0  | 11625 | 0.8887          | 0.905    |
| 0.0           | 32.0  | 12000 | 0.9455          | 0.9      |
| 0.0           | 33.0  | 12375 | 0.9432          | 0.9033   |
| 0.0           | 34.0  | 12750 | 0.9703          | 0.8983   |
| 0.0           | 35.0  | 13125 | 0.9495          | 0.9067   |
| 0.0           | 36.0  | 13500 | 0.9886          | 0.8983   |
| 0.0           | 37.0  | 13875 | 0.9999          | 0.9      |
| 0.0           | 38.0  | 14250 | 1.0388          | 0.8983   |
| 0.0           | 39.0  | 14625 | 1.0645          | 0.8917   |
| 0.0038        | 40.0  | 15000 | 0.9923          | 0.9017   |
| 0.0           | 41.0  | 15375 | 1.0132          | 0.8983   |
| 0.0           | 42.0  | 15750 | 1.0058          | 0.9017   |
| 0.0           | 43.0  | 16125 | 1.0185          | 0.8983   |
| 0.0           | 44.0  | 16500 | 1.0211          | 0.8967   |
| 0.0           | 45.0  | 16875 | 1.0174          | 0.8967   |
| 0.0           | 46.0  | 17250 | 1.0256          | 0.8967   |
| 0.0           | 47.0  | 17625 | 1.0251          | 0.8967   |
| 0.0           | 48.0  | 18000 | 1.0297          | 0.8967   |
| 0.0           | 49.0  | 18375 | 1.0318          | 0.8967   |
| 0.0           | 50.0  | 18750 | 1.0303          | 0.8967   |


### 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