
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# smids_5x_deit_small_rms_0001_fold3

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: 1.0792
- Accuracy: 0.8933

## 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: 0.0001
- 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.279         | 1.0   | 375   | 0.3229          | 0.88     |
| 0.164         | 2.0   | 750   | 0.3138          | 0.91     |
| 0.1109        | 3.0   | 1125  | 0.3763          | 0.8967   |
| 0.0429        | 4.0   | 1500  | 0.4357          | 0.8933   |
| 0.0647        | 5.0   | 1875  | 0.5383          | 0.9      |
| 0.0292        | 6.0   | 2250  | 0.4950          | 0.8983   |
| 0.0793        | 7.0   | 2625  | 0.5600          | 0.8867   |
| 0.0326        | 8.0   | 3000  | 0.6289          | 0.885    |
| 0.0175        | 9.0   | 3375  | 0.6125          | 0.89     |
| 0.0162        | 10.0  | 3750  | 0.7037          | 0.8983   |
| 0.0357        | 11.0  | 4125  | 0.6928          | 0.8833   |
| 0.0295        | 12.0  | 4500  | 0.7344          | 0.8817   |
| 0.0007        | 13.0  | 4875  | 0.6848          | 0.9033   |
| 0.0001        | 14.0  | 5250  | 0.6912          | 0.89     |
| 0.0101        | 15.0  | 5625  | 0.6507          | 0.9      |
| 0.024         | 16.0  | 6000  | 0.6949          | 0.8933   |
| 0.0004        | 17.0  | 6375  | 0.5735          | 0.9133   |
| 0.0116        | 18.0  | 6750  | 0.6520          | 0.905    |
| 0.0214        | 19.0  | 7125  | 0.8822          | 0.895    |
| 0.0002        | 20.0  | 7500  | 0.7795          | 0.8883   |
| 0.023         | 21.0  | 7875  | 0.7295          | 0.9017   |
| 0.0001        | 22.0  | 8250  | 0.7805          | 0.9      |
| 0.0077        | 23.0  | 8625  | 0.7822          | 0.89     |
| 0.0248        | 24.0  | 9000  | 0.6997          | 0.9017   |
| 0.0192        | 25.0  | 9375  | 0.7612          | 0.8983   |
| 0.0053        | 26.0  | 9750  | 0.6937          | 0.9      |
| 0.0001        | 27.0  | 10125 | 0.8197          | 0.9      |
| 0.0066        | 28.0  | 10500 | 0.7264          | 0.9033   |
| 0.0           | 29.0  | 10875 | 0.9769          | 0.8883   |
| 0.0055        | 30.0  | 11250 | 0.9308          | 0.8817   |
| 0.0083        | 31.0  | 11625 | 0.9275          | 0.88     |
| 0.0           | 32.0  | 12000 | 0.8761          | 0.8917   |
| 0.0001        | 33.0  | 12375 | 0.8754          | 0.8967   |
| 0.0001        | 34.0  | 12750 | 0.9281          | 0.8883   |
| 0.0158        | 35.0  | 13125 | 1.0369          | 0.8767   |
| 0.0043        | 36.0  | 13500 | 1.0161          | 0.88     |
| 0.0023        | 37.0  | 13875 | 0.9274          | 0.8933   |
| 0.0           | 38.0  | 14250 | 0.9705          | 0.8933   |
| 0.0           | 39.0  | 14625 | 1.0691          | 0.8867   |
| 0.0029        | 40.0  | 15000 | 1.0780          | 0.89     |
| 0.0           | 41.0  | 15375 | 1.0592          | 0.885    |
| 0.0           | 42.0  | 15750 | 1.0784          | 0.885    |
| 0.0           | 43.0  | 16125 | 1.0389          | 0.8917   |
| 0.0           | 44.0  | 16500 | 1.0434          | 0.8933   |
| 0.0           | 45.0  | 16875 | 1.0581          | 0.8917   |
| 0.0           | 46.0  | 17250 | 1.0632          | 0.8933   |
| 0.0           | 47.0  | 17625 | 1.0692          | 0.8933   |
| 0.0           | 48.0  | 18000 | 1.0755          | 0.8917   |
| 0.0           | 49.0  | 18375 | 1.0789          | 0.8917   |
| 0.0           | 50.0  | 18750 | 1.0792          | 0.8933   |


### 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