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# smids_3x_deit_base_sgd_001_fold5

This model is a fine-tuned version of [facebook/deit-base-patch16-224](https://huggingface.co/facebook/deit-base-patch16-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2858
- Accuracy: 0.8733

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.9502        | 1.0   | 225   | 0.9617          | 0.575    |
| 0.7701        | 2.0   | 450   | 0.7420          | 0.7533   |
| 0.6098        | 3.0   | 675   | 0.5976          | 0.7833   |
| 0.477         | 4.0   | 900   | 0.5110          | 0.805    |
| 0.4263        | 5.0   | 1125  | 0.4583          | 0.82     |
| 0.414         | 6.0   | 1350  | 0.4227          | 0.8233   |
| 0.4045        | 7.0   | 1575  | 0.3990          | 0.8233   |
| 0.4145        | 8.0   | 1800  | 0.3808          | 0.8267   |
| 0.3701        | 9.0   | 2025  | 0.3676          | 0.8383   |
| 0.3094        | 10.0  | 2250  | 0.3582          | 0.845    |
| 0.3923        | 11.0  | 2475  | 0.3474          | 0.845    |
| 0.3461        | 12.0  | 2700  | 0.3427          | 0.8467   |
| 0.3684        | 13.0  | 2925  | 0.3332          | 0.8483   |
| 0.3232        | 14.0  | 3150  | 0.3290          | 0.8517   |
| 0.2418        | 15.0  | 3375  | 0.3249          | 0.855    |
| 0.2931        | 16.0  | 3600  | 0.3205          | 0.8517   |
| 0.2688        | 17.0  | 3825  | 0.3173          | 0.8533   |
| 0.3031        | 18.0  | 4050  | 0.3158          | 0.8567   |
| 0.2623        | 19.0  | 4275  | 0.3109          | 0.8517   |
| 0.298         | 20.0  | 4500  | 0.3083          | 0.8533   |
| 0.2399        | 21.0  | 4725  | 0.3072          | 0.8583   |
| 0.2519        | 22.0  | 4950  | 0.3035          | 0.8633   |
| 0.2394        | 23.0  | 5175  | 0.3028          | 0.86     |
| 0.254         | 24.0  | 5400  | 0.3011          | 0.8633   |
| 0.232         | 25.0  | 5625  | 0.3006          | 0.865    |
| 0.2794        | 26.0  | 5850  | 0.2984          | 0.865    |
| 0.2948        | 27.0  | 6075  | 0.2979          | 0.8633   |
| 0.2603        | 28.0  | 6300  | 0.2957          | 0.87     |
| 0.2519        | 29.0  | 6525  | 0.2949          | 0.8617   |
| 0.2151        | 30.0  | 6750  | 0.2933          | 0.8667   |
| 0.1937        | 31.0  | 6975  | 0.2918          | 0.8683   |
| 0.2408        | 32.0  | 7200  | 0.2919          | 0.87     |
| 0.2318        | 33.0  | 7425  | 0.2909          | 0.87     |
| 0.1908        | 34.0  | 7650  | 0.2902          | 0.8717   |
| 0.2103        | 35.0  | 7875  | 0.2898          | 0.87     |
| 0.2236        | 36.0  | 8100  | 0.2888          | 0.8717   |
| 0.2275        | 37.0  | 8325  | 0.2884          | 0.87     |
| 0.2349        | 38.0  | 8550  | 0.2885          | 0.87     |
| 0.1941        | 39.0  | 8775  | 0.2873          | 0.8683   |
| 0.2123        | 40.0  | 9000  | 0.2867          | 0.8667   |
| 0.2183        | 41.0  | 9225  | 0.2867          | 0.8683   |
| 0.2291        | 42.0  | 9450  | 0.2862          | 0.8667   |
| 0.2371        | 43.0  | 9675  | 0.2863          | 0.8717   |
| 0.2487        | 44.0  | 9900  | 0.2863          | 0.8717   |
| 0.2098        | 45.0  | 10125 | 0.2862          | 0.8717   |
| 0.2225        | 46.0  | 10350 | 0.2861          | 0.8733   |
| 0.2189        | 47.0  | 10575 | 0.2859          | 0.8733   |
| 0.2461        | 48.0  | 10800 | 0.2858          | 0.8733   |
| 0.2284        | 49.0  | 11025 | 0.2858          | 0.8733   |
| 0.236         | 50.0  | 11250 | 0.2858          | 0.8733   |


### 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