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# smids_1x_deit_tiny_sgd_001_fold3

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: 0.3753
- Accuracy: 0.8433

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.1           | 1.0   | 75   | 1.0685          | 0.46     |
| 0.9367        | 2.0   | 150  | 0.9646          | 0.5417   |
| 0.8514        | 3.0   | 225  | 0.8770          | 0.6067   |
| 0.8379        | 4.0   | 300  | 0.8018          | 0.6683   |
| 0.6855        | 5.0   | 375  | 0.7375          | 0.715    |
| 0.6563        | 6.0   | 450  | 0.6796          | 0.7433   |
| 0.6233        | 7.0   | 525  | 0.6334          | 0.7633   |
| 0.5422        | 8.0   | 600  | 0.5966          | 0.7817   |
| 0.5439        | 9.0   | 675  | 0.5698          | 0.795    |
| 0.5302        | 10.0  | 750  | 0.5521          | 0.795    |
| 0.503         | 11.0  | 825  | 0.5277          | 0.8083   |
| 0.4486        | 12.0  | 900  | 0.5133          | 0.8083   |
| 0.4811        | 13.0  | 975  | 0.4988          | 0.8133   |
| 0.4014        | 14.0  | 1050 | 0.4857          | 0.815    |
| 0.3711        | 15.0  | 1125 | 0.4759          | 0.8217   |
| 0.4033        | 16.0  | 1200 | 0.4684          | 0.8167   |
| 0.4414        | 17.0  | 1275 | 0.4593          | 0.8233   |
| 0.3659        | 18.0  | 1350 | 0.4514          | 0.8233   |
| 0.3656        | 19.0  | 1425 | 0.4448          | 0.8233   |
| 0.4021        | 20.0  | 1500 | 0.4388          | 0.825    |
| 0.4189        | 21.0  | 1575 | 0.4325          | 0.8267   |
| 0.3524        | 22.0  | 1650 | 0.4276          | 0.8283   |
| 0.356         | 23.0  | 1725 | 0.4217          | 0.8283   |
| 0.3419        | 24.0  | 1800 | 0.4174          | 0.835    |
| 0.3528        | 25.0  | 1875 | 0.4128          | 0.83     |
| 0.3819        | 26.0  | 1950 | 0.4110          | 0.8233   |
| 0.3203        | 27.0  | 2025 | 0.4057          | 0.835    |
| 0.3243        | 28.0  | 2100 | 0.4027          | 0.8333   |
| 0.3594        | 29.0  | 2175 | 0.3998          | 0.835    |
| 0.3291        | 30.0  | 2250 | 0.3976          | 0.84     |
| 0.3185        | 31.0  | 2325 | 0.3939          | 0.84     |
| 0.3337        | 32.0  | 2400 | 0.3916          | 0.8383   |
| 0.3127        | 33.0  | 2475 | 0.3899          | 0.8367   |
| 0.3111        | 34.0  | 2550 | 0.3887          | 0.835    |
| 0.3206        | 35.0  | 2625 | 0.3862          | 0.8383   |
| 0.3237        | 36.0  | 2700 | 0.3848          | 0.845    |
| 0.2644        | 37.0  | 2775 | 0.3830          | 0.85     |
| 0.3198        | 38.0  | 2850 | 0.3820          | 0.845    |
| 0.3031        | 39.0  | 2925 | 0.3811          | 0.8417   |
| 0.2823        | 40.0  | 3000 | 0.3801          | 0.8433   |
| 0.2812        | 41.0  | 3075 | 0.3793          | 0.8417   |
| 0.3147        | 42.0  | 3150 | 0.3783          | 0.8417   |
| 0.2862        | 43.0  | 3225 | 0.3776          | 0.845    |
| 0.2684        | 44.0  | 3300 | 0.3773          | 0.8433   |
| 0.306         | 45.0  | 3375 | 0.3765          | 0.8467   |
| 0.2738        | 46.0  | 3450 | 0.3761          | 0.845    |
| 0.2493        | 47.0  | 3525 | 0.3758          | 0.8433   |
| 0.2906        | 48.0  | 3600 | 0.3756          | 0.8433   |
| 0.2971        | 49.0  | 3675 | 0.3754          | 0.8433   |
| 0.2597        | 50.0  | 3750 | 0.3753          | 0.8433   |


### 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