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# smids_10x_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: 0.2634
- Accuracy: 0.8965

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.5921        | 1.0   | 751   | 0.6125          | 0.7713   |
| 0.3591        | 2.0   | 1502  | 0.4405          | 0.8314   |
| 0.3047        | 3.0   | 2253  | 0.3783          | 0.8598   |
| 0.2551        | 4.0   | 3004  | 0.3472          | 0.8781   |
| 0.2903        | 5.0   | 3755  | 0.3280          | 0.8748   |
| 0.2606        | 6.0   | 4506  | 0.3152          | 0.8765   |
| 0.2793        | 7.0   | 5257  | 0.3058          | 0.8881   |
| 0.2466        | 8.0   | 6008  | 0.2984          | 0.8915   |
| 0.2613        | 9.0   | 6759  | 0.2938          | 0.8881   |
| 0.2309        | 10.0  | 7510  | 0.2878          | 0.8948   |
| 0.2362        | 11.0  | 8261  | 0.2856          | 0.8915   |
| 0.2432        | 12.0  | 9012  | 0.2826          | 0.8982   |
| 0.2244        | 13.0  | 9763  | 0.2806          | 0.8898   |
| 0.1581        | 14.0  | 10514 | 0.2786          | 0.8915   |
| 0.1869        | 15.0  | 11265 | 0.2757          | 0.8915   |
| 0.1863        | 16.0  | 12016 | 0.2739          | 0.8915   |
| 0.25          | 17.0  | 12767 | 0.2738          | 0.8898   |
| 0.1609        | 18.0  | 13518 | 0.2717          | 0.8932   |
| 0.1993        | 19.0  | 14269 | 0.2719          | 0.8881   |
| 0.1982        | 20.0  | 15020 | 0.2698          | 0.8915   |
| 0.1558        | 21.0  | 15771 | 0.2692          | 0.8982   |
| 0.1601        | 22.0  | 16522 | 0.2690          | 0.8998   |
| 0.1754        | 23.0  | 17273 | 0.2694          | 0.8898   |
| 0.1664        | 24.0  | 18024 | 0.2677          | 0.8932   |
| 0.1901        | 25.0  | 18775 | 0.2669          | 0.8948   |
| 0.2023        | 26.0  | 19526 | 0.2671          | 0.8965   |
| 0.1982        | 27.0  | 20277 | 0.2651          | 0.8965   |
| 0.2093        | 28.0  | 21028 | 0.2655          | 0.8998   |
| 0.1635        | 29.0  | 21779 | 0.2645          | 0.8982   |
| 0.1441        | 30.0  | 22530 | 0.2639          | 0.8998   |
| 0.1066        | 31.0  | 23281 | 0.2648          | 0.9015   |
| 0.227         | 32.0  | 24032 | 0.2644          | 0.9032   |
| 0.1777        | 33.0  | 24783 | 0.2648          | 0.8965   |
| 0.1846        | 34.0  | 25534 | 0.2641          | 0.8982   |
| 0.1694        | 35.0  | 26285 | 0.2643          | 0.8982   |
| 0.1711        | 36.0  | 27036 | 0.2639          | 0.8965   |
| 0.2649        | 37.0  | 27787 | 0.2640          | 0.9032   |
| 0.1541        | 38.0  | 28538 | 0.2641          | 0.8982   |
| 0.107         | 39.0  | 29289 | 0.2640          | 0.8932   |
| 0.2208        | 40.0  | 30040 | 0.2641          | 0.8998   |
| 0.1601        | 41.0  | 30791 | 0.2638          | 0.8948   |
| 0.1237        | 42.0  | 31542 | 0.2635          | 0.8965   |
| 0.1676        | 43.0  | 32293 | 0.2637          | 0.8932   |
| 0.1349        | 44.0  | 33044 | 0.2638          | 0.8965   |
| 0.1329        | 45.0  | 33795 | 0.2638          | 0.8965   |
| 0.177         | 46.0  | 34546 | 0.2636          | 0.8982   |
| 0.1141        | 47.0  | 35297 | 0.2635          | 0.8965   |
| 0.1694        | 48.0  | 36048 | 0.2636          | 0.8965   |
| 0.1549        | 49.0  | 36799 | 0.2634          | 0.8965   |
| 0.1223        | 50.0  | 37550 | 0.2634          | 0.8965   |


### 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