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# smids_1x_deit_small_rms_00001_fold5

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: 0.9281
- Accuracy: 0.88

## 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: 1e-05
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.3852        | 1.0   | 75   | 0.3081          | 0.87     |
| 0.2965        | 2.0   | 150  | 0.3016          | 0.8733   |
| 0.1467        | 3.0   | 225  | 0.3200          | 0.8783   |
| 0.1384        | 4.0   | 300  | 0.3262          | 0.8833   |
| 0.0702        | 5.0   | 375  | 0.3415          | 0.8817   |
| 0.0486        | 6.0   | 450  | 0.4818          | 0.8817   |
| 0.0342        | 7.0   | 525  | 0.4838          | 0.8817   |
| 0.0455        | 8.0   | 600  | 0.6047          | 0.8717   |
| 0.0096        | 9.0   | 675  | 0.5775          | 0.8817   |
| 0.028         | 10.0  | 750  | 0.6719          | 0.875    |
| 0.0419        | 11.0  | 825  | 0.6284          | 0.8833   |
| 0.0004        | 12.0  | 900  | 0.6384          | 0.8817   |
| 0.0259        | 13.0  | 975  | 0.6301          | 0.875    |
| 0.03          | 14.0  | 1050 | 0.6619          | 0.8733   |
| 0.0082        | 15.0  | 1125 | 0.8292          | 0.8667   |
| 0.0001        | 16.0  | 1200 | 0.7120          | 0.88     |
| 0.005         | 17.0  | 1275 | 0.7140          | 0.8867   |
| 0.028         | 18.0  | 1350 | 0.8747          | 0.865    |
| 0.0095        | 19.0  | 1425 | 0.8049          | 0.8767   |
| 0.0001        | 20.0  | 1500 | 0.7748          | 0.8767   |
| 0.0085        | 21.0  | 1575 | 0.7202          | 0.885    |
| 0.0152        | 22.0  | 1650 | 0.8388          | 0.875    |
| 0.0057        | 23.0  | 1725 | 0.8400          | 0.8733   |
| 0.0001        | 24.0  | 1800 | 0.8934          | 0.8717   |
| 0.0082        | 25.0  | 1875 | 0.8430          | 0.8783   |
| 0.0001        | 26.0  | 1950 | 0.8852          | 0.8783   |
| 0.008         | 27.0  | 2025 | 0.8664          | 0.8767   |
| 0.0113        | 28.0  | 2100 | 0.8872          | 0.88     |
| 0.0078        | 29.0  | 2175 | 0.8576          | 0.8817   |
| 0.0049        | 30.0  | 2250 | 0.8872          | 0.88     |
| 0.0           | 31.0  | 2325 | 0.9217          | 0.8733   |
| 0.0           | 32.0  | 2400 | 0.8681          | 0.8833   |
| 0.0081        | 33.0  | 2475 | 0.9201          | 0.8783   |
| 0.0           | 34.0  | 2550 | 0.9023          | 0.8767   |
| 0.0058        | 35.0  | 2625 | 0.9043          | 0.8767   |
| 0.0           | 36.0  | 2700 | 0.9027          | 0.88     |
| 0.0029        | 37.0  | 2775 | 0.9082          | 0.88     |
| 0.0           | 38.0  | 2850 | 0.9260          | 0.8767   |
| 0.0           | 39.0  | 2925 | 0.9311          | 0.8783   |
| 0.0           | 40.0  | 3000 | 0.9195          | 0.8767   |
| 0.0028        | 41.0  | 3075 | 0.9229          | 0.8767   |
| 0.0           | 42.0  | 3150 | 0.9218          | 0.8783   |
| 0.0075        | 43.0  | 3225 | 0.9281          | 0.8767   |
| 0.0           | 44.0  | 3300 | 0.9291          | 0.8767   |
| 0.0025        | 45.0  | 3375 | 0.9268          | 0.8783   |
| 0.0           | 46.0  | 3450 | 0.9285          | 0.88     |
| 0.0049        | 47.0  | 3525 | 0.9282          | 0.88     |
| 0.0048        | 48.0  | 3600 | 0.9283          | 0.88     |
| 0.0           | 49.0  | 3675 | 0.9284          | 0.88     |
| 0.0043        | 50.0  | 3750 | 0.9281          | 0.88     |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0

abnormal_sperm non-sperm normal_sperm