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# smids_5x_deit_base_sgd_001_fold1

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: 0.2661
- Accuracy: 0.8932

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.7985        | 1.0   | 376   | 0.8182          | 0.6978   |
| 0.594         | 2.0   | 752   | 0.5849          | 0.7746   |
| 0.4653        | 3.0   | 1128  | 0.4811          | 0.8197   |
| 0.4509        | 4.0   | 1504  | 0.4265          | 0.8264   |
| 0.406         | 5.0   | 1880  | 0.3929          | 0.8447   |
| 0.3758        | 6.0   | 2256  | 0.3696          | 0.8581   |
| 0.3147        | 7.0   | 2632  | 0.3531          | 0.8698   |
| 0.3421        | 8.0   | 3008  | 0.3417          | 0.8664   |
| 0.3606        | 9.0   | 3384  | 0.3307          | 0.8798   |
| 0.2866        | 10.0  | 3760  | 0.3222          | 0.8865   |
| 0.2912        | 11.0  | 4136  | 0.3153          | 0.8798   |
| 0.2629        | 12.0  | 4512  | 0.3094          | 0.8865   |
| 0.2464        | 13.0  | 4888  | 0.3048          | 0.8848   |
| 0.2413        | 14.0  | 5264  | 0.3005          | 0.8881   |
| 0.3125        | 15.0  | 5640  | 0.2955          | 0.8932   |
| 0.226         | 16.0  | 6016  | 0.2931          | 0.8865   |
| 0.2346        | 17.0  | 6392  | 0.2899          | 0.8915   |
| 0.2997        | 18.0  | 6768  | 0.2867          | 0.8881   |
| 0.2564        | 19.0  | 7144  | 0.2849          | 0.8898   |
| 0.1951        | 20.0  | 7520  | 0.2838          | 0.8898   |
| 0.2828        | 21.0  | 7896  | 0.2817          | 0.8898   |
| 0.2327        | 22.0  | 8272  | 0.2806          | 0.8898   |
| 0.2604        | 23.0  | 8648  | 0.2786          | 0.8865   |
| 0.2065        | 24.0  | 9024  | 0.2780          | 0.8881   |
| 0.2338        | 25.0  | 9400  | 0.2766          | 0.8881   |
| 0.2197        | 26.0  | 9776  | 0.2745          | 0.8898   |
| 0.1797        | 27.0  | 10152 | 0.2743          | 0.8898   |
| 0.199         | 28.0  | 10528 | 0.2732          | 0.8915   |
| 0.2002        | 29.0  | 10904 | 0.2724          | 0.8898   |
| 0.1586        | 30.0  | 11280 | 0.2714          | 0.8932   |
| 0.1861        | 31.0  | 11656 | 0.2710          | 0.8932   |
| 0.2539        | 32.0  | 12032 | 0.2706          | 0.8948   |
| 0.1906        | 33.0  | 12408 | 0.2700          | 0.8948   |
| 0.1642        | 34.0  | 12784 | 0.2697          | 0.8915   |
| 0.1856        | 35.0  | 13160 | 0.2694          | 0.8915   |
| 0.2084        | 36.0  | 13536 | 0.2691          | 0.8932   |
| 0.1812        | 37.0  | 13912 | 0.2681          | 0.8948   |
| 0.2073        | 38.0  | 14288 | 0.2680          | 0.8948   |
| 0.1854        | 39.0  | 14664 | 0.2677          | 0.8915   |
| 0.1953        | 40.0  | 15040 | 0.2671          | 0.8932   |
| 0.1912        | 41.0  | 15416 | 0.2672          | 0.8948   |
| 0.1646        | 42.0  | 15792 | 0.2669          | 0.8932   |
| 0.1689        | 43.0  | 16168 | 0.2666          | 0.8932   |
| 0.1894        | 44.0  | 16544 | 0.2664          | 0.8932   |
| 0.173         | 45.0  | 16920 | 0.2663          | 0.8932   |
| 0.2186        | 46.0  | 17296 | 0.2661          | 0.8932   |
| 0.1671        | 47.0  | 17672 | 0.2661          | 0.8932   |
| 0.1916        | 48.0  | 18048 | 0.2661          | 0.8932   |
| 0.1583        | 49.0  | 18424 | 0.2661          | 0.8932   |
| 0.137         | 50.0  | 18800 | 0.2661          | 0.8932   |


### 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