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# smids_3x_deit_base_adamax_001_fold1

This model is a fine-tuned version of [facebook/deit-base-patch16-224](https://huggingface.co/facebook/deit-base-patch16-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8904
- Accuracy: 0.9082

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.4465        | 1.0   | 226   | 0.4094          | 0.8531   |
| 0.3028        | 2.0   | 452   | 0.3873          | 0.8531   |
| 0.2517        | 3.0   | 678   | 0.4048          | 0.8331   |
| 0.2354        | 4.0   | 904   | 0.4907          | 0.8114   |
| 0.1919        | 5.0   | 1130  | 0.3668          | 0.8715   |
| 0.1089        | 6.0   | 1356  | 0.4054          | 0.8631   |
| 0.1437        | 7.0   | 1582  | 0.3749          | 0.8848   |
| 0.1061        | 8.0   | 1808  | 0.4236          | 0.8765   |
| 0.0689        | 9.0   | 2034  | 0.5413          | 0.8481   |
| 0.0296        | 10.0  | 2260  | 0.5357          | 0.8848   |
| 0.0504        | 11.0  | 2486  | 0.4702          | 0.8798   |
| 0.0624        | 12.0  | 2712  | 0.4704          | 0.8815   |
| 0.0348        | 13.0  | 2938  | 0.6106          | 0.8581   |
| 0.0456        | 14.0  | 3164  | 0.5131          | 0.8948   |
| 0.0044        | 15.0  | 3390  | 0.5464          | 0.8731   |
| 0.0468        | 16.0  | 3616  | 0.5959          | 0.8815   |
| 0.0547        | 17.0  | 3842  | 0.5509          | 0.8982   |
| 0.0079        | 18.0  | 4068  | 0.7646          | 0.8765   |
| 0.0305        | 19.0  | 4294  | 0.5293          | 0.8898   |
| 0.0015        | 20.0  | 4520  | 0.6722          | 0.8932   |
| 0.0003        | 21.0  | 4746  | 0.7133          | 0.8915   |
| 0.0053        | 22.0  | 4972  | 0.6759          | 0.8948   |
| 0.0024        | 23.0  | 5198  | 0.6761          | 0.8915   |
| 0.0001        | 24.0  | 5424  | 0.6916          | 0.8948   |
| 0.0           | 25.0  | 5650  | 0.7062          | 0.9015   |
| 0.0           | 26.0  | 5876  | 0.7162          | 0.8948   |
| 0.0           | 27.0  | 6102  | 0.7191          | 0.8965   |
| 0.0           | 28.0  | 6328  | 0.7245          | 0.8982   |
| 0.0           | 29.0  | 6554  | 0.7361          | 0.8982   |
| 0.0           | 30.0  | 6780  | 0.7291          | 0.8982   |
| 0.0           | 31.0  | 7006  | 0.7418          | 0.8998   |
| 0.0           | 32.0  | 7232  | 0.7345          | 0.8965   |
| 0.0031        | 33.0  | 7458  | 0.7834          | 0.9032   |
| 0.0           | 34.0  | 7684  | 0.7928          | 0.9065   |
| 0.0           | 35.0  | 7910  | 0.8008          | 0.9032   |
| 0.0           | 36.0  | 8136  | 0.8059          | 0.9082   |
| 0.0           | 37.0  | 8362  | 0.8162          | 0.9032   |
| 0.0           | 38.0  | 8588  | 0.8201          | 0.9015   |
| 0.0           | 39.0  | 8814  | 0.8345          | 0.9032   |
| 0.0           | 40.0  | 9040  | 0.8336          | 0.9032   |
| 0.003         | 41.0  | 9266  | 0.8468          | 0.9015   |
| 0.003         | 42.0  | 9492  | 0.8578          | 0.9032   |
| 0.0           | 43.0  | 9718  | 0.8626          | 0.9015   |
| 0.0           | 44.0  | 9944  | 0.8520          | 0.9048   |
| 0.0           | 45.0  | 10170 | 0.8711          | 0.9065   |
| 0.0           | 46.0  | 10396 | 0.8787          | 0.9048   |
| 0.0           | 47.0  | 10622 | 0.8816          | 0.9082   |
| 0.0           | 48.0  | 10848 | 0.8859          | 0.9048   |
| 0.0           | 49.0  | 11074 | 0.8890          | 0.9082   |
| 0.0           | 50.0  | 11300 | 0.8904          | 0.9082   |


### 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