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# smids_5x_deit_base_sgd_001_fold3

This model is a fine-tuned version of [facebook/deit-base-patch16-224](https://huggingface.co/facebook/deit-base-patch16-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2756
- Accuracy: 0.9017

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.8095        | 1.0   | 375   | 0.8274          | 0.695    |
| 0.5875        | 2.0   | 750   | 0.5872          | 0.8033   |
| 0.4116        | 3.0   | 1125  | 0.4743          | 0.83     |
| 0.3737        | 4.0   | 1500  | 0.4186          | 0.855    |
| 0.4258        | 5.0   | 1875  | 0.3874          | 0.86     |
| 0.3489        | 6.0   | 2250  | 0.3641          | 0.8633   |
| 0.3464        | 7.0   | 2625  | 0.3477          | 0.8667   |
| 0.3297        | 8.0   | 3000  | 0.3357          | 0.8667   |
| 0.277         | 9.0   | 3375  | 0.3288          | 0.8683   |
| 0.2815        | 10.0  | 3750  | 0.3210          | 0.8733   |
| 0.2355        | 11.0  | 4125  | 0.3122          | 0.8767   |
| 0.2863        | 12.0  | 4500  | 0.3078          | 0.8833   |
| 0.2701        | 13.0  | 4875  | 0.3051          | 0.8833   |
| 0.2736        | 14.0  | 5250  | 0.3025          | 0.8833   |
| 0.2395        | 15.0  | 5625  | 0.2961          | 0.885    |
| 0.2031        | 16.0  | 6000  | 0.2952          | 0.885    |
| 0.2473        | 17.0  | 6375  | 0.2943          | 0.885    |
| 0.2814        | 18.0  | 6750  | 0.2910          | 0.8883   |
| 0.2316        | 19.0  | 7125  | 0.2893          | 0.89     |
| 0.2303        | 20.0  | 7500  | 0.2871          | 0.8883   |
| 0.1561        | 21.0  | 7875  | 0.2852          | 0.8883   |
| 0.1795        | 22.0  | 8250  | 0.2878          | 0.8933   |
| 0.2424        | 23.0  | 8625  | 0.2847          | 0.8933   |
| 0.234         | 24.0  | 9000  | 0.2843          | 0.89     |
| 0.2148        | 25.0  | 9375  | 0.2840          | 0.8883   |
| 0.2353        | 26.0  | 9750  | 0.2810          | 0.8967   |
| 0.2055        | 27.0  | 10125 | 0.2823          | 0.895    |
| 0.2361        | 28.0  | 10500 | 0.2802          | 0.8967   |
| 0.1834        | 29.0  | 10875 | 0.2796          | 0.895    |
| 0.2029        | 30.0  | 11250 | 0.2813          | 0.8967   |
| 0.2296        | 31.0  | 11625 | 0.2806          | 0.8983   |
| 0.2077        | 32.0  | 12000 | 0.2800          | 0.8983   |
| 0.2574        | 33.0  | 12375 | 0.2785          | 0.8983   |
| 0.1786        | 34.0  | 12750 | 0.2764          | 0.8967   |
| 0.1549        | 35.0  | 13125 | 0.2758          | 0.9      |
| 0.1665        | 36.0  | 13500 | 0.2763          | 0.8983   |
| 0.187         | 37.0  | 13875 | 0.2766          | 0.9      |
| 0.1745        | 38.0  | 14250 | 0.2765          | 0.9      |
| 0.1886        | 39.0  | 14625 | 0.2765          | 0.9      |
| 0.1628        | 40.0  | 15000 | 0.2755          | 0.9017   |
| 0.1471        | 41.0  | 15375 | 0.2749          | 0.9017   |
| 0.1795        | 42.0  | 15750 | 0.2759          | 0.9017   |
| 0.2305        | 43.0  | 16125 | 0.2754          | 0.9017   |
| 0.168         | 44.0  | 16500 | 0.2757          | 0.9017   |
| 0.1598        | 45.0  | 16875 | 0.2757          | 0.9033   |
| 0.1914        | 46.0  | 17250 | 0.2755          | 0.9017   |
| 0.2052        | 47.0  | 17625 | 0.2754          | 0.9017   |
| 0.1945        | 48.0  | 18000 | 0.2755          | 0.9017   |
| 0.1764        | 49.0  | 18375 | 0.2755          | 0.9017   |
| 0.1798        | 50.0  | 18750 | 0.2756          | 0.9017   |


### Framework versions

- Transformers 4.32.1
- Pytorch 2.1.0+cu121
- Datasets 2.12.0
- Tokenizers 0.13.2

abnormal_sperm non-sperm normal_sperm