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# smids_1x_deit_small_rms_0001_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: 1.6596
- Accuracy: 0.7733

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.02          | 1.0   | 75   | 0.9685          | 0.5083   |
| 0.9368        | 2.0   | 150  | 0.8387          | 0.5183   |
| 0.8751        | 3.0   | 225  | 0.9305          | 0.5183   |
| 0.8059        | 4.0   | 300  | 0.7779          | 0.5767   |
| 0.821         | 5.0   | 375  | 0.9513          | 0.475    |
| 0.8644        | 6.0   | 450  | 0.7778          | 0.6083   |
| 0.7749        | 7.0   | 525  | 0.7241          | 0.6617   |
| 0.7172        | 8.0   | 600  | 0.9471          | 0.5533   |
| 0.75          | 9.0   | 675  | 0.7669          | 0.6383   |
| 0.7211        | 10.0  | 750  | 0.6657          | 0.6967   |
| 0.6753        | 11.0  | 825  | 0.6888          | 0.695    |
| 0.6887        | 12.0  | 900  | 0.6632          | 0.7017   |
| 0.7301        | 13.0  | 975  | 0.6603          | 0.7117   |
| 0.6939        | 14.0  | 1050 | 0.6241          | 0.7283   |
| 0.7692        | 15.0  | 1125 | 0.6957          | 0.71     |
| 0.6561        | 16.0  | 1200 | 0.6443          | 0.7117   |
| 0.6416        | 17.0  | 1275 | 0.6605          | 0.6983   |
| 0.553         | 18.0  | 1350 | 0.6495          | 0.72     |
| 0.601         | 19.0  | 1425 | 0.6418          | 0.74     |
| 0.577         | 20.0  | 1500 | 0.6362          | 0.7      |
| 0.5839        | 21.0  | 1575 | 0.6592          | 0.7283   |
| 0.4976        | 22.0  | 1650 | 0.6311          | 0.7483   |
| 0.5763        | 23.0  | 1725 | 0.6318          | 0.7533   |
| 0.4997        | 24.0  | 1800 | 0.6050          | 0.7433   |
| 0.5525        | 25.0  | 1875 | 0.5695          | 0.7533   |
| 0.4857        | 26.0  | 1950 | 0.5993          | 0.735    |
| 0.4769        | 27.0  | 2025 | 0.6121          | 0.735    |
| 0.4978        | 28.0  | 2100 | 0.6011          | 0.7567   |
| 0.4365        | 29.0  | 2175 | 0.6331          | 0.76     |
| 0.4881        | 30.0  | 2250 | 0.5762          | 0.775    |
| 0.3678        | 31.0  | 2325 | 0.5874          | 0.765    |
| 0.4583        | 32.0  | 2400 | 0.6049          | 0.7617   |
| 0.3235        | 33.0  | 2475 | 0.6327          | 0.765    |
| 0.3498        | 34.0  | 2550 | 0.6478          | 0.765    |
| 0.3632        | 35.0  | 2625 | 0.6378          | 0.7467   |
| 0.3296        | 36.0  | 2700 | 0.6839          | 0.7683   |
| 0.2708        | 37.0  | 2775 | 0.6765          | 0.7467   |
| 0.2694        | 38.0  | 2850 | 0.6868          | 0.765    |
| 0.2078        | 39.0  | 2925 | 0.7971          | 0.7517   |
| 0.2919        | 40.0  | 3000 | 0.8448          | 0.735    |
| 0.1961        | 41.0  | 3075 | 0.9265          | 0.7367   |
| 0.1701        | 42.0  | 3150 | 0.9269          | 0.74     |
| 0.1813        | 43.0  | 3225 | 1.0013          | 0.755    |
| 0.1056        | 44.0  | 3300 | 1.1339          | 0.7567   |
| 0.0898        | 45.0  | 3375 | 1.2022          | 0.7567   |
| 0.0232        | 46.0  | 3450 | 1.4144          | 0.755    |
| 0.0626        | 47.0  | 3525 | 1.5426          | 0.76     |
| 0.0293        | 48.0  | 3600 | 1.5905          | 0.7517   |
| 0.0028        | 49.0  | 3675 | 1.6357          | 0.7633   |
| 0.0018        | 50.0  | 3750 | 1.6596          | 0.7733   |


### 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