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# smids_10x_deit_small_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: 0.2862
- Accuracy: 0.9015

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.5539        | 1.0   | 751   | 0.5690          | 0.7763   |
| 0.3867        | 2.0   | 1502  | 0.4456          | 0.8314   |
| 0.3236        | 3.0   | 2253  | 0.3927          | 0.8497   |
| 0.259         | 4.0   | 3004  | 0.3726          | 0.8514   |
| 0.3099        | 5.0   | 3755  | 0.3487          | 0.8598   |
| 0.2986        | 6.0   | 4506  | 0.3416          | 0.8715   |
| 0.2728        | 7.0   | 5257  | 0.3260          | 0.8731   |
| 0.2249        | 8.0   | 6008  | 0.3188          | 0.8781   |
| 0.2673        | 9.0   | 6759  | 0.3155          | 0.8848   |
| 0.2491        | 10.0  | 7510  | 0.3089          | 0.8848   |
| 0.2349        | 11.0  | 8261  | 0.3099          | 0.8881   |
| 0.2513        | 12.0  | 9012  | 0.3016          | 0.8898   |
| 0.2098        | 13.0  | 9763  | 0.3061          | 0.8898   |
| 0.1606        | 14.0  | 10514 | 0.3022          | 0.8881   |
| 0.1914        | 15.0  | 11265 | 0.2955          | 0.8881   |
| 0.2039        | 16.0  | 12016 | 0.2953          | 0.8898   |
| 0.2821        | 17.0  | 12767 | 0.2940          | 0.8965   |
| 0.1703        | 18.0  | 13518 | 0.2962          | 0.8915   |
| 0.2178        | 19.0  | 14269 | 0.2905          | 0.8965   |
| 0.1883        | 20.0  | 15020 | 0.2902          | 0.8998   |
| 0.13          | 21.0  | 15771 | 0.2893          | 0.8948   |
| 0.1613        | 22.0  | 16522 | 0.2875          | 0.8982   |
| 0.1627        | 23.0  | 17273 | 0.2879          | 0.8948   |
| 0.2201        | 24.0  | 18024 | 0.2853          | 0.8998   |
| 0.2067        | 25.0  | 18775 | 0.2893          | 0.8965   |
| 0.1982        | 26.0  | 19526 | 0.2860          | 0.8982   |
| 0.1922        | 27.0  | 20277 | 0.2854          | 0.8998   |
| 0.2065        | 28.0  | 21028 | 0.2873          | 0.8948   |
| 0.1663        | 29.0  | 21779 | 0.2836          | 0.9032   |
| 0.1637        | 30.0  | 22530 | 0.2824          | 0.9032   |
| 0.1216        | 31.0  | 23281 | 0.2840          | 0.8998   |
| 0.2073        | 32.0  | 24032 | 0.2863          | 0.9065   |
| 0.1694        | 33.0  | 24783 | 0.2888          | 0.8965   |
| 0.1525        | 34.0  | 25534 | 0.2882          | 0.8982   |
| 0.1562        | 35.0  | 26285 | 0.2864          | 0.9032   |
| 0.1612        | 36.0  | 27036 | 0.2821          | 0.9032   |
| 0.2418        | 37.0  | 27787 | 0.2832          | 0.9015   |
| 0.138         | 38.0  | 28538 | 0.2859          | 0.9032   |
| 0.0832        | 39.0  | 29289 | 0.2853          | 0.8998   |
| 0.1792        | 40.0  | 30040 | 0.2866          | 0.9015   |
| 0.1296        | 41.0  | 30791 | 0.2848          | 0.9032   |
| 0.1436        | 42.0  | 31542 | 0.2863          | 0.9032   |
| 0.1676        | 43.0  | 32293 | 0.2864          | 0.9015   |
| 0.129         | 44.0  | 33044 | 0.2863          | 0.9015   |
| 0.1268        | 45.0  | 33795 | 0.2864          | 0.9015   |
| 0.182         | 46.0  | 34546 | 0.2870          | 0.8998   |
| 0.0802        | 47.0  | 35297 | 0.2872          | 0.9015   |
| 0.1369        | 48.0  | 36048 | 0.2866          | 0.9015   |
| 0.1294        | 49.0  | 36799 | 0.2861          | 0.9015   |
| 0.1488        | 50.0  | 37550 | 0.2862          | 0.9015   |


### 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