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# smids_3x_deit_tiny_rms_001_fold1

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: 2.0122
- Accuracy: 0.8030

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.8369        | 1.0   | 226   | 0.8757          | 0.5359   |
| 0.8499        | 2.0   | 452   | 0.8448          | 0.5776   |
| 0.7754        | 3.0   | 678   | 0.9313          | 0.5142   |
| 0.8771        | 4.0   | 904   | 0.7652          | 0.6194   |
| 0.7781        | 5.0   | 1130  | 0.7375          | 0.6711   |
| 0.7866        | 6.0   | 1356  | 0.7599          | 0.6394   |
| 0.664         | 7.0   | 1582  | 0.7260          | 0.6711   |
| 0.6855        | 8.0   | 1808  | 0.8844          | 0.5376   |
| 0.6098        | 9.0   | 2034  | 0.7118          | 0.6778   |
| 0.6338        | 10.0  | 2260  | 0.6856          | 0.6962   |
| 0.5812        | 11.0  | 2486  | 0.6665          | 0.6962   |
| 0.5909        | 12.0  | 2712  | 0.8126          | 0.6260   |
| 0.5272        | 13.0  | 2938  | 0.6279          | 0.7329   |
| 0.5688        | 14.0  | 3164  | 0.7483          | 0.6494   |
| 0.5214        | 15.0  | 3390  | 0.6410          | 0.7312   |
| 0.5581        | 16.0  | 3616  | 0.6042          | 0.7412   |
| 0.4723        | 17.0  | 3842  | 0.6758          | 0.7145   |
| 0.5595        | 18.0  | 4068  | 0.6233          | 0.7412   |
| 0.5549        | 19.0  | 4294  | 0.6152          | 0.7329   |
| 0.5078        | 20.0  | 4520  | 0.6278          | 0.7195   |
| 0.5707        | 21.0  | 4746  | 0.5335          | 0.7780   |
| 0.4944        | 22.0  | 4972  | 0.6366          | 0.7396   |
| 0.5416        | 23.0  | 5198  | 0.5752          | 0.7663   |
| 0.5022        | 24.0  | 5424  | 0.5999          | 0.7479   |
| 0.5615        | 25.0  | 5650  | 0.5710          | 0.7596   |
| 0.5132        | 26.0  | 5876  | 0.5875          | 0.7730   |
| 0.3982        | 27.0  | 6102  | 0.5830          | 0.7763   |
| 0.4012        | 28.0  | 6328  | 0.7036          | 0.7563   |
| 0.37          | 29.0  | 6554  | 0.6641          | 0.7429   |
| 0.4588        | 30.0  | 6780  | 0.6124          | 0.7613   |
| 0.3873        | 31.0  | 7006  | 0.6238          | 0.7646   |
| 0.3153        | 32.0  | 7232  | 0.6857          | 0.7613   |
| 0.3038        | 33.0  | 7458  | 0.7385          | 0.7730   |
| 0.2793        | 34.0  | 7684  | 0.6805          | 0.7846   |
| 0.2405        | 35.0  | 7910  | 0.7592          | 0.7846   |
| 0.2843        | 36.0  | 8136  | 0.8044          | 0.7746   |
| 0.2771        | 37.0  | 8362  | 0.7613          | 0.7813   |
| 0.2263        | 38.0  | 8588  | 0.8328          | 0.7679   |
| 0.1499        | 39.0  | 8814  | 0.9707          | 0.7696   |
| 0.1482        | 40.0  | 9040  | 1.0206          | 0.7896   |
| 0.1303        | 41.0  | 9266  | 1.1237          | 0.7947   |
| 0.0595        | 42.0  | 9492  | 1.3060          | 0.7763   |
| 0.0163        | 43.0  | 9718  | 1.4374          | 0.7830   |
| 0.0383        | 44.0  | 9944  | 1.5230          | 0.7863   |
| 0.0303        | 45.0  | 10170 | 1.5896          | 0.7947   |
| 0.0051        | 46.0  | 10396 | 1.8469          | 0.7896   |
| 0.0006        | 47.0  | 10622 | 1.9434          | 0.7880   |
| 0.0004        | 48.0  | 10848 | 2.0244          | 0.7947   |
| 0.0004        | 49.0  | 11074 | 1.9864          | 0.7997   |
| 0.0002        | 50.0  | 11300 | 2.0122          | 0.8030   |


### 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