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# smids_1x_deit_small_rms_00001_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: 0.7203
- Accuracy: 0.8848

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.4024        | 1.0   | 76   | 0.3457          | 0.8598   |
| 0.2939        | 2.0   | 152  | 0.3056          | 0.8765   |
| 0.1494        | 3.0   | 228  | 0.3010          | 0.8815   |
| 0.1219        | 4.0   | 304  | 0.3026          | 0.8848   |
| 0.0709        | 5.0   | 380  | 0.3230          | 0.8881   |
| 0.0265        | 6.0   | 456  | 0.3473          | 0.8915   |
| 0.0053        | 7.0   | 532  | 0.4250          | 0.8815   |
| 0.0086        | 8.0   | 608  | 0.4355          | 0.8848   |
| 0.0119        | 9.0   | 684  | 0.4635          | 0.8865   |
| 0.0011        | 10.0  | 760  | 0.4824          | 0.8932   |
| 0.0255        | 11.0  | 836  | 0.5139          | 0.8831   |
| 0.0006        | 12.0  | 912  | 0.5793          | 0.8815   |
| 0.0183        | 13.0  | 988  | 0.5403          | 0.8848   |
| 0.0037        | 14.0  | 1064 | 0.5951          | 0.8848   |
| 0.024         | 15.0  | 1140 | 0.5951          | 0.8815   |
| 0.0002        | 16.0  | 1216 | 0.6061          | 0.8798   |
| 0.0001        | 17.0  | 1292 | 0.5992          | 0.8948   |
| 0.0157        | 18.0  | 1368 | 0.6206          | 0.8848   |
| 0.0002        | 19.0  | 1444 | 0.6514          | 0.8881   |
| 0.0058        | 20.0  | 1520 | 0.6656          | 0.8798   |
| 0.0096        | 21.0  | 1596 | 0.6589          | 0.8915   |
| 0.0045        | 22.0  | 1672 | 0.6509          | 0.8848   |
| 0.0001        | 23.0  | 1748 | 0.6180          | 0.8881   |
| 0.0001        | 24.0  | 1824 | 0.6676          | 0.8765   |
| 0.0077        | 25.0  | 1900 | 0.6271          | 0.8831   |
| 0.0032        | 26.0  | 1976 | 0.7135          | 0.8848   |
| 0.0043        | 27.0  | 2052 | 0.7062          | 0.8765   |
| 0.0034        | 28.0  | 2128 | 0.7064          | 0.8781   |
| 0.0062        | 29.0  | 2204 | 0.6764          | 0.8781   |
| 0.0001        | 30.0  | 2280 | 0.6847          | 0.8831   |
| 0.006         | 31.0  | 2356 | 0.6868          | 0.8865   |
| 0.009         | 32.0  | 2432 | 0.7122          | 0.8881   |
| 0.0           | 33.0  | 2508 | 0.7011          | 0.8865   |
| 0.0           | 34.0  | 2584 | 0.7102          | 0.8881   |
| 0.0121        | 35.0  | 2660 | 0.7023          | 0.8881   |
| 0.0034        | 36.0  | 2736 | 0.7188          | 0.8765   |
| 0.0064        | 37.0  | 2812 | 0.7029          | 0.8848   |
| 0.0001        | 38.0  | 2888 | 0.7098          | 0.8798   |
| 0.0031        | 39.0  | 2964 | 0.7171          | 0.8815   |
| 0.0           | 40.0  | 3040 | 0.7137          | 0.8815   |
| 0.0029        | 41.0  | 3116 | 0.7143          | 0.8815   |
| 0.0           | 42.0  | 3192 | 0.7224          | 0.8815   |
| 0.0048        | 43.0  | 3268 | 0.7157          | 0.8831   |
| 0.0           | 44.0  | 3344 | 0.7190          | 0.8848   |
| 0.0           | 45.0  | 3420 | 0.7200          | 0.8848   |
| 0.0           | 46.0  | 3496 | 0.7204          | 0.8848   |
| 0.0           | 47.0  | 3572 | 0.7209          | 0.8848   |
| 0.0024        | 48.0  | 3648 | 0.7205          | 0.8848   |
| 0.0           | 49.0  | 3724 | 0.7204          | 0.8848   |
| 0.0           | 50.0  | 3800 | 0.7203          | 0.8848   |


### 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