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# smids_3x_deit_small_adamax_001_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: 0.9284
- Accuracy: 0.8831

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.5541        | 1.0   | 226   | 0.6212          | 0.7379   |
| 0.2991        | 2.0   | 452   | 0.3577          | 0.8748   |
| 0.3025        | 3.0   | 678   | 0.3328          | 0.8765   |
| 0.2535        | 4.0   | 904   | 0.3762          | 0.8631   |
| 0.2002        | 5.0   | 1130  | 0.3237          | 0.8581   |
| 0.2266        | 6.0   | 1356  | 0.2994          | 0.8898   |
| 0.1986        | 7.0   | 1582  | 0.4068          | 0.8831   |
| 0.102         | 8.0   | 1808  | 0.5862          | 0.8564   |
| 0.1677        | 9.0   | 2034  | 0.4842          | 0.8431   |
| 0.0849        | 10.0  | 2260  | 0.4657          | 0.8848   |
| 0.0597        | 11.0  | 2486  | 0.4867          | 0.8698   |
| 0.0739        | 12.0  | 2712  | 0.4601          | 0.8881   |
| 0.057         | 13.0  | 2938  | 0.5719          | 0.8614   |
| 0.0476        | 14.0  | 3164  | 0.5741          | 0.8898   |
| 0.0028        | 15.0  | 3390  | 0.5632          | 0.8932   |
| 0.0442        | 16.0  | 3616  | 0.6974          | 0.8748   |
| 0.0232        | 17.0  | 3842  | 0.7080          | 0.8731   |
| 0.0139        | 18.0  | 4068  | 0.6478          | 0.8848   |
| 0.0142        | 19.0  | 4294  | 0.6320          | 0.8881   |
| 0.0278        | 20.0  | 4520  | 0.7359          | 0.8698   |
| 0.0017        | 21.0  | 4746  | 0.5842          | 0.8948   |
| 0.0064        | 22.0  | 4972  | 0.8360          | 0.8681   |
| 0.0257        | 23.0  | 5198  | 0.6566          | 0.8865   |
| 0.0027        | 24.0  | 5424  | 0.6515          | 0.8948   |
| 0.0001        | 25.0  | 5650  | 0.6767          | 0.8998   |
| 0.0009        | 26.0  | 5876  | 0.7783          | 0.8865   |
| 0.0001        | 27.0  | 6102  | 0.7799          | 0.8815   |
| 0.0004        | 28.0  | 6328  | 0.8472          | 0.8831   |
| 0.0002        | 29.0  | 6554  | 0.6998          | 0.8848   |
| 0.0           | 30.0  | 6780  | 0.8253          | 0.8815   |
| 0.0           | 31.0  | 7006  | 0.7884          | 0.8898   |
| 0.0001        | 32.0  | 7232  | 0.8156          | 0.8798   |
| 0.0032        | 33.0  | 7458  | 0.8222          | 0.8881   |
| 0.0           | 34.0  | 7684  | 0.8187          | 0.8848   |
| 0.0           | 35.0  | 7910  | 0.8080          | 0.8848   |
| 0.0           | 36.0  | 8136  | 0.8285          | 0.8798   |
| 0.0           | 37.0  | 8362  | 0.8277          | 0.8848   |
| 0.0           | 38.0  | 8588  | 0.8358          | 0.8831   |
| 0.0           | 39.0  | 8814  | 0.8499          | 0.8831   |
| 0.0           | 40.0  | 9040  | 0.8554          | 0.8798   |
| 0.0034        | 41.0  | 9266  | 0.8762          | 0.8798   |
| 0.0035        | 42.0  | 9492  | 0.8827          | 0.8798   |
| 0.0           | 43.0  | 9718  | 0.8772          | 0.8798   |
| 0.0           | 44.0  | 9944  | 0.8964          | 0.8831   |
| 0.0           | 45.0  | 10170 | 0.9072          | 0.8831   |
| 0.0           | 46.0  | 10396 | 0.9164          | 0.8815   |
| 0.0           | 47.0  | 10622 | 0.9219          | 0.8815   |
| 0.0           | 48.0  | 10848 | 0.9247          | 0.8831   |
| 0.0           | 49.0  | 11074 | 0.9274          | 0.8831   |
| 0.0           | 50.0  | 11300 | 0.9284          | 0.8831   |


### 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