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# smids_5x_deit_tiny_sgd_001_fold1

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: 0.2974
- 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.7214        | 1.0   | 376   | 0.7354          | 0.7112   |
| 0.5305        | 2.0   | 752   | 0.5484          | 0.7780   |
| 0.423         | 3.0   | 1128  | 0.4775          | 0.8063   |
| 0.4098        | 4.0   | 1504  | 0.4302          | 0.8364   |
| 0.4286        | 5.0   | 1880  | 0.4059          | 0.8497   |
| 0.3605        | 6.0   | 2256  | 0.3872          | 0.8548   |
| 0.3093        | 7.0   | 2632  | 0.3738          | 0.8648   |
| 0.3348        | 8.0   | 3008  | 0.3632          | 0.8664   |
| 0.3284        | 9.0   | 3384  | 0.3510          | 0.8765   |
| 0.3008        | 10.0  | 3760  | 0.3447          | 0.8748   |
| 0.289         | 11.0  | 4136  | 0.3398          | 0.8798   |
| 0.2542        | 12.0  | 4512  | 0.3320          | 0.8848   |
| 0.245         | 13.0  | 4888  | 0.3263          | 0.8865   |
| 0.2258        | 14.0  | 5264  | 0.3225          | 0.8865   |
| 0.3082        | 15.0  | 5640  | 0.3188          | 0.8848   |
| 0.2685        | 16.0  | 6016  | 0.3171          | 0.8848   |
| 0.2379        | 17.0  | 6392  | 0.3137          | 0.8865   |
| 0.2778        | 18.0  | 6768  | 0.3111          | 0.8848   |
| 0.2374        | 19.0  | 7144  | 0.3083          | 0.8848   |
| 0.1845        | 20.0  | 7520  | 0.3061          | 0.8848   |
| 0.2126        | 21.0  | 7896  | 0.3049          | 0.8865   |
| 0.2068        | 22.0  | 8272  | 0.3078          | 0.8831   |
| 0.2364        | 23.0  | 8648  | 0.3060          | 0.8798   |
| 0.1851        | 24.0  | 9024  | 0.3035          | 0.8881   |
| 0.2035        | 25.0  | 9400  | 0.3013          | 0.8848   |
| 0.2146        | 26.0  | 9776  | 0.3016          | 0.8881   |
| 0.1495        | 27.0  | 10152 | 0.2986          | 0.8915   |
| 0.1962        | 28.0  | 10528 | 0.2989          | 0.8898   |
| 0.2019        | 29.0  | 10904 | 0.2993          | 0.8881   |
| 0.1531        | 30.0  | 11280 | 0.2975          | 0.8932   |
| 0.1643        | 31.0  | 11656 | 0.2990          | 0.8898   |
| 0.2082        | 32.0  | 12032 | 0.2991          | 0.8881   |
| 0.1845        | 33.0  | 12408 | 0.2980          | 0.8915   |
| 0.1333        | 34.0  | 12784 | 0.2976          | 0.8932   |
| 0.1524        | 35.0  | 13160 | 0.3000          | 0.8865   |
| 0.1908        | 36.0  | 13536 | 0.2977          | 0.8915   |
| 0.1391        | 37.0  | 13912 | 0.2964          | 0.8948   |
| 0.1756        | 38.0  | 14288 | 0.2975          | 0.8915   |
| 0.2131        | 39.0  | 14664 | 0.2969          | 0.8932   |
| 0.1588        | 40.0  | 15040 | 0.2977          | 0.8898   |
| 0.1631        | 41.0  | 15416 | 0.2962          | 0.8932   |
| 0.1431        | 42.0  | 15792 | 0.2974          | 0.8915   |
| 0.1556        | 43.0  | 16168 | 0.2976          | 0.8898   |
| 0.1705        | 44.0  | 16544 | 0.2978          | 0.8915   |
| 0.1792        | 45.0  | 16920 | 0.2986          | 0.8898   |
| 0.1949        | 46.0  | 17296 | 0.2975          | 0.8915   |
| 0.1472        | 47.0  | 17672 | 0.2972          | 0.8915   |
| 0.139         | 48.0  | 18048 | 0.2974          | 0.8915   |
| 0.1452        | 49.0  | 18424 | 0.2974          | 0.8915   |
| 0.1388        | 50.0  | 18800 | 0.2974          | 0.8915   |


### Framework versions

- Transformers 4.32.1
- Pytorch 2.1.1+cu121
- Datasets 2.12.0
- Tokenizers 0.13.2

abnormal_sperm non-sperm normal_sperm