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# smids_3x_deit_tiny_sgd_001_fold5

This model is a fine-tuned version of [facebook/deit-tiny-patch16-224](https://huggingface.co/facebook/deit-tiny-patch16-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2846
- Accuracy: 0.8767

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.8735        | 1.0   | 225   | 0.9170          | 0.545    |
| 0.6877        | 2.0   | 450   | 0.6945          | 0.7167   |
| 0.5875        | 3.0   | 675   | 0.5531          | 0.79     |
| 0.4761        | 4.0   | 900   | 0.4755          | 0.82     |
| 0.4339        | 5.0   | 1125  | 0.4319          | 0.83     |
| 0.3839        | 6.0   | 1350  | 0.4018          | 0.8483   |
| 0.4408        | 7.0   | 1575  | 0.3811          | 0.85     |
| 0.4281        | 8.0   | 1800  | 0.3653          | 0.8583   |
| 0.3652        | 9.0   | 2025  | 0.3551          | 0.8533   |
| 0.324         | 10.0  | 2250  | 0.3480          | 0.8567   |
| 0.3571        | 11.0  | 2475  | 0.3391          | 0.86     |
| 0.3339        | 12.0  | 2700  | 0.3292          | 0.86     |
| 0.343         | 13.0  | 2925  | 0.3232          | 0.865    |
| 0.3099        | 14.0  | 3150  | 0.3188          | 0.8633   |
| 0.2636        | 15.0  | 3375  | 0.3160          | 0.87     |
| 0.2725        | 16.0  | 3600  | 0.3109          | 0.8633   |
| 0.2598        | 17.0  | 3825  | 0.3041          | 0.8717   |
| 0.2377        | 18.0  | 4050  | 0.3051          | 0.8683   |
| 0.2636        | 19.0  | 4275  | 0.2990          | 0.8683   |
| 0.2944        | 20.0  | 4500  | 0.2992          | 0.8733   |
| 0.2247        | 21.0  | 4725  | 0.2983          | 0.8733   |
| 0.2126        | 22.0  | 4950  | 0.2963          | 0.8733   |
| 0.2221        | 23.0  | 5175  | 0.2922          | 0.8783   |
| 0.2198        | 24.0  | 5400  | 0.2918          | 0.8717   |
| 0.2574        | 25.0  | 5625  | 0.2955          | 0.88     |
| 0.2932        | 26.0  | 5850  | 0.2903          | 0.88     |
| 0.2755        | 27.0  | 6075  | 0.2866          | 0.8767   |
| 0.2735        | 28.0  | 6300  | 0.2890          | 0.8783   |
| 0.2207        | 29.0  | 6525  | 0.2874          | 0.88     |
| 0.1879        | 30.0  | 6750  | 0.2869          | 0.875    |
| 0.1763        | 31.0  | 6975  | 0.2867          | 0.88     |
| 0.2308        | 32.0  | 7200  | 0.2871          | 0.8733   |
| 0.1914        | 33.0  | 7425  | 0.2850          | 0.8767   |
| 0.1699        | 34.0  | 7650  | 0.2866          | 0.875    |
| 0.1804        | 35.0  | 7875  | 0.2842          | 0.88     |
| 0.182         | 36.0  | 8100  | 0.2861          | 0.8783   |
| 0.2385        | 37.0  | 8325  | 0.2854          | 0.8783   |
| 0.1637        | 38.0  | 8550  | 0.2879          | 0.8783   |
| 0.1554        | 39.0  | 8775  | 0.2876          | 0.8767   |
| 0.2151        | 40.0  | 9000  | 0.2856          | 0.8783   |
| 0.1931        | 41.0  | 9225  | 0.2849          | 0.8783   |
| 0.1711        | 42.0  | 9450  | 0.2846          | 0.8783   |
| 0.2357        | 43.0  | 9675  | 0.2864          | 0.8783   |
| 0.202         | 44.0  | 9900  | 0.2845          | 0.88     |
| 0.1905        | 45.0  | 10125 | 0.2855          | 0.88     |
| 0.1822        | 46.0  | 10350 | 0.2847          | 0.8767   |
| 0.2034        | 47.0  | 10575 | 0.2849          | 0.8767   |
| 0.1793        | 48.0  | 10800 | 0.2851          | 0.8767   |
| 0.2049        | 49.0  | 11025 | 0.2846          | 0.8767   |
| 0.168         | 50.0  | 11250 | 0.2846          | 0.8767   |


### Framework versions

- Transformers 4.32.1
- Pytorch 2.1.1+cu121
- Datasets 2.12.0
- Tokenizers 0.13.2

abnormal_sperm non-sperm normal_sperm