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# smids_3x_deit_small_adamax_00001_fold1

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: 0.8130
- Accuracy: 0.8815

## 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: 1e-05
- 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.424         | 1.0   | 226   | 0.3513          | 0.8731   |
| 0.2946        | 2.0   | 452   | 0.3000          | 0.8798   |
| 0.1827        | 3.0   | 678   | 0.2979          | 0.8865   |
| 0.2004        | 4.0   | 904   | 0.3148          | 0.8932   |
| 0.1798        | 5.0   | 1130  | 0.3139          | 0.8998   |
| 0.0853        | 6.0   | 1356  | 0.3299          | 0.8965   |
| 0.0515        | 7.0   | 1582  | 0.3457          | 0.8865   |
| 0.0826        | 8.0   | 1808  | 0.3663          | 0.8932   |
| 0.0216        | 9.0   | 2034  | 0.3989          | 0.8948   |
| 0.0193        | 10.0  | 2260  | 0.4487          | 0.8948   |
| 0.0094        | 11.0  | 2486  | 0.5419          | 0.8815   |
| 0.0096        | 12.0  | 2712  | 0.5555          | 0.8898   |
| 0.0006        | 13.0  | 2938  | 0.5917          | 0.8881   |
| 0.0105        | 14.0  | 3164  | 0.6078          | 0.8982   |
| 0.0003        | 15.0  | 3390  | 0.6602          | 0.8815   |
| 0.0002        | 16.0  | 3616  | 0.6567          | 0.8815   |
| 0.0159        | 17.0  | 3842  | 0.6787          | 0.8881   |
| 0.0001        | 18.0  | 4068  | 0.7011          | 0.8865   |
| 0.0111        | 19.0  | 4294  | 0.7444          | 0.8815   |
| 0.0001        | 20.0  | 4520  | 0.7129          | 0.8865   |
| 0.0001        | 21.0  | 4746  | 0.7374          | 0.8898   |
| 0.0255        | 22.0  | 4972  | 0.7516          | 0.8748   |
| 0.0198        | 23.0  | 5198  | 0.7561          | 0.8898   |
| 0.0001        | 24.0  | 5424  | 0.7448          | 0.8865   |
| 0.0           | 25.0  | 5650  | 0.7702          | 0.8831   |
| 0.0001        | 26.0  | 5876  | 0.7830          | 0.8798   |
| 0.0           | 27.0  | 6102  | 0.7463          | 0.8898   |
| 0.0001        | 28.0  | 6328  | 0.7479          | 0.8815   |
| 0.0           | 29.0  | 6554  | 0.7622          | 0.8898   |
| 0.0           | 30.0  | 6780  | 0.7645          | 0.8898   |
| 0.0           | 31.0  | 7006  | 0.7711          | 0.8898   |
| 0.0           | 32.0  | 7232  | 0.7799          | 0.8865   |
| 0.012         | 33.0  | 7458  | 0.7796          | 0.8898   |
| 0.0           | 34.0  | 7684  | 0.8089          | 0.8848   |
| 0.0           | 35.0  | 7910  | 0.7888          | 0.8831   |
| 0.0           | 36.0  | 8136  | 0.8152          | 0.8815   |
| 0.0           | 37.0  | 8362  | 0.7978          | 0.8831   |
| 0.0           | 38.0  | 8588  | 0.7987          | 0.8781   |
| 0.0           | 39.0  | 8814  | 0.7888          | 0.8915   |
| 0.0           | 40.0  | 9040  | 0.7970          | 0.8831   |
| 0.0095        | 41.0  | 9266  | 0.8023          | 0.8815   |
| 0.0008        | 42.0  | 9492  | 0.8065          | 0.8798   |
| 0.0           | 43.0  | 9718  | 0.7964          | 0.8881   |
| 0.0           | 44.0  | 9944  | 0.8002          | 0.8865   |
| 0.0           | 45.0  | 10170 | 0.8035          | 0.8831   |
| 0.0           | 46.0  | 10396 | 0.8056          | 0.8815   |
| 0.0           | 47.0  | 10622 | 0.8110          | 0.8815   |
| 0.0           | 48.0  | 10848 | 0.8125          | 0.8831   |
| 0.0           | 49.0  | 11074 | 0.8131          | 0.8815   |
| 0.0           | 50.0  | 11300 | 0.8130          | 0.8815   |


### 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