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# smids_10x_deit_small_sgd_0001_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: 0.4121
- Accuracy: 0.8464

## 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: 0.0001
- 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.9962        | 1.0   | 751   | 1.0240          | 0.4741   |
| 0.8829        | 2.0   | 1502  | 0.9630          | 0.5259   |
| 0.8203        | 3.0   | 2253  | 0.8958          | 0.6027   |
| 0.7637        | 4.0   | 3004  | 0.8327          | 0.6578   |
| 0.7321        | 5.0   | 3755  | 0.7782          | 0.6912   |
| 0.7017        | 6.0   | 4506  | 0.7239          | 0.7078   |
| 0.5812        | 7.0   | 5257  | 0.6809          | 0.7212   |
| 0.581         | 8.0   | 6008  | 0.6410          | 0.7346   |
| 0.5592        | 9.0   | 6759  | 0.6086          | 0.7513   |
| 0.5145        | 10.0  | 7510  | 0.5829          | 0.7679   |
| 0.5332        | 11.0  | 8261  | 0.5629          | 0.7746   |
| 0.4756        | 12.0  | 9012  | 0.5433          | 0.7796   |
| 0.4797        | 13.0  | 9763  | 0.5294          | 0.7846   |
| 0.4315        | 14.0  | 10514 | 0.5168          | 0.7930   |
| 0.4112        | 15.0  | 11265 | 0.5056          | 0.8013   |
| 0.4474        | 16.0  | 12016 | 0.4952          | 0.8030   |
| 0.4529        | 17.0  | 12767 | 0.4868          | 0.8097   |
| 0.421         | 18.0  | 13518 | 0.4802          | 0.8130   |
| 0.4112        | 19.0  | 14269 | 0.4730          | 0.8130   |
| 0.4039        | 20.0  | 15020 | 0.4670          | 0.8180   |
| 0.3219        | 21.0  | 15771 | 0.4615          | 0.8164   |
| 0.411         | 22.0  | 16522 | 0.4563          | 0.8180   |
| 0.3769        | 23.0  | 17273 | 0.4528          | 0.8214   |
| 0.4423        | 24.0  | 18024 | 0.4481          | 0.8214   |
| 0.4214        | 25.0  | 18775 | 0.4442          | 0.8230   |
| 0.4588        | 26.0  | 19526 | 0.4419          | 0.8280   |
| 0.3977        | 27.0  | 20277 | 0.4383          | 0.8314   |
| 0.4288        | 28.0  | 21028 | 0.4359          | 0.8297   |
| 0.3842        | 29.0  | 21779 | 0.4331          | 0.8331   |
| 0.38          | 30.0  | 22530 | 0.4307          | 0.8331   |
| 0.3344        | 31.0  | 23281 | 0.4288          | 0.8347   |
| 0.4273        | 32.0  | 24032 | 0.4264          | 0.8347   |
| 0.3923        | 33.0  | 24783 | 0.4244          | 0.8364   |
| 0.3452        | 34.0  | 25534 | 0.4233          | 0.8364   |
| 0.3666        | 35.0  | 26285 | 0.4214          | 0.8381   |
| 0.3806        | 36.0  | 27036 | 0.4199          | 0.8397   |
| 0.4471        | 37.0  | 27787 | 0.4189          | 0.8397   |
| 0.3236        | 38.0  | 28538 | 0.4183          | 0.8414   |
| 0.2974        | 39.0  | 29289 | 0.4171          | 0.8397   |
| 0.4164        | 40.0  | 30040 | 0.4161          | 0.8397   |
| 0.3819        | 41.0  | 30791 | 0.4153          | 0.8431   |
| 0.3798        | 42.0  | 31542 | 0.4146          | 0.8447   |
| 0.3898        | 43.0  | 32293 | 0.4139          | 0.8447   |
| 0.3508        | 44.0  | 33044 | 0.4133          | 0.8447   |
| 0.3647        | 45.0  | 33795 | 0.4128          | 0.8447   |
| 0.4056        | 46.0  | 34546 | 0.4125          | 0.8447   |
| 0.3591        | 47.0  | 35297 | 0.4123          | 0.8464   |
| 0.4233        | 48.0  | 36048 | 0.4121          | 0.8464   |
| 0.3734        | 49.0  | 36799 | 0.4121          | 0.8464   |
| 0.3779        | 50.0  | 37550 | 0.4121          | 0.8464   |


### 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