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# smids_1x_deit_small_rms_00001_fold4

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: 1.2283
- Accuracy: 0.86

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.3693        | 1.0   | 75   | 0.4169          | 0.8367   |
| 0.25          | 2.0   | 150  | 0.3480          | 0.86     |
| 0.1826        | 3.0   | 225  | 0.3907          | 0.8517   |
| 0.103         | 4.0   | 300  | 0.4268          | 0.8533   |
| 0.0588        | 5.0   | 375  | 0.4745          | 0.8517   |
| 0.0211        | 6.0   | 450  | 0.5873          | 0.86     |
| 0.0762        | 7.0   | 525  | 0.6785          | 0.8567   |
| 0.0033        | 8.0   | 600  | 0.6768          | 0.8533   |
| 0.0377        | 9.0   | 675  | 0.7784          | 0.855    |
| 0.0107        | 10.0  | 750  | 0.8289          | 0.8467   |
| 0.0009        | 11.0  | 825  | 0.8979          | 0.845    |
| 0.0002        | 12.0  | 900  | 0.8647          | 0.8617   |
| 0.0003        | 13.0  | 975  | 0.8591          | 0.8583   |
| 0.0077        | 14.0  | 1050 | 0.9903          | 0.8483   |
| 0.0002        | 15.0  | 1125 | 0.9262          | 0.86     |
| 0.0075        | 16.0  | 1200 | 1.1297          | 0.8283   |
| 0.0005        | 17.0  | 1275 | 0.9421          | 0.86     |
| 0.0146        | 18.0  | 1350 | 0.8922          | 0.86     |
| 0.0001        | 19.0  | 1425 | 0.9244          | 0.8683   |
| 0.0001        | 20.0  | 1500 | 0.9926          | 0.8683   |
| 0.003         | 21.0  | 1575 | 0.9538          | 0.8633   |
| 0.0001        | 22.0  | 1650 | 0.9796          | 0.8633   |
| 0.0           | 23.0  | 1725 | 0.9957          | 0.865    |
| 0.0079        | 24.0  | 1800 | 0.9969          | 0.8667   |
| 0.0074        | 25.0  | 1875 | 1.0816          | 0.86     |
| 0.0           | 26.0  | 1950 | 1.1025          | 0.8617   |
| 0.0           | 27.0  | 2025 | 1.1525          | 0.8467   |
| 0.0057        | 28.0  | 2100 | 1.1210          | 0.855    |
| 0.0181        | 29.0  | 2175 | 1.1276          | 0.86     |
| 0.0           | 30.0  | 2250 | 1.1208          | 0.8617   |
| 0.0           | 31.0  | 2325 | 1.1193          | 0.865    |
| 0.0           | 32.0  | 2400 | 1.1408          | 0.8617   |
| 0.0           | 33.0  | 2475 | 1.1431          | 0.8633   |
| 0.0           | 34.0  | 2550 | 1.1491          | 0.86     |
| 0.0           | 35.0  | 2625 | 1.1589          | 0.8617   |
| 0.0           | 36.0  | 2700 | 1.1620          | 0.8617   |
| 0.0031        | 37.0  | 2775 | 1.1838          | 0.8633   |
| 0.0           | 38.0  | 2850 | 1.1840          | 0.8633   |
| 0.0           | 39.0  | 2925 | 1.1861          | 0.8617   |
| 0.0           | 40.0  | 3000 | 1.2058          | 0.8633   |
| 0.0028        | 41.0  | 3075 | 1.1981          | 0.865    |
| 0.0           | 42.0  | 3150 | 1.2026          | 0.8617   |
| 0.0           | 43.0  | 3225 | 1.2159          | 0.86     |
| 0.0           | 44.0  | 3300 | 1.2159          | 0.86     |
| 0.0           | 45.0  | 3375 | 1.2189          | 0.86     |
| 0.0           | 46.0  | 3450 | 1.2225          | 0.86     |
| 0.0           | 47.0  | 3525 | 1.2244          | 0.86     |
| 0.0           | 48.0  | 3600 | 1.2263          | 0.86     |
| 0.0           | 49.0  | 3675 | 1.2278          | 0.86     |
| 0.0           | 50.0  | 3750 | 1.2283          | 0.86     |


### 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