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# smids_1x_deit_small_adamax_00001_fold4

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: 0.9148
- Accuracy: 0.86

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.5803        | 1.0   | 75   | 0.4968          | 0.8167   |
| 0.4066        | 2.0   | 150  | 0.3965          | 0.8517   |
| 0.3494        | 3.0   | 225  | 0.3679          | 0.8583   |
| 0.257         | 4.0   | 300  | 0.3627          | 0.8583   |
| 0.1968        | 5.0   | 375  | 0.3612          | 0.8567   |
| 0.1309        | 6.0   | 450  | 0.3609          | 0.865    |
| 0.1744        | 7.0   | 525  | 0.3526          | 0.8667   |
| 0.1066        | 8.0   | 600  | 0.3650          | 0.8733   |
| 0.0701        | 9.0   | 675  | 0.3803          | 0.87     |
| 0.058         | 10.0  | 750  | 0.3887          | 0.8683   |
| 0.0585        | 11.0  | 825  | 0.4227          | 0.8667   |
| 0.0507        | 12.0  | 900  | 0.4565          | 0.8667   |
| 0.0443        | 13.0  | 975  | 0.4751          | 0.8667   |
| 0.023         | 14.0  | 1050 | 0.5029          | 0.875    |
| 0.0067        | 15.0  | 1125 | 0.5522          | 0.8667   |
| 0.0046        | 16.0  | 1200 | 0.5758          | 0.8683   |
| 0.0072        | 17.0  | 1275 | 0.6012          | 0.8667   |
| 0.0186        | 18.0  | 1350 | 0.6185          | 0.8667   |
| 0.0049        | 19.0  | 1425 | 0.6452          | 0.8633   |
| 0.0012        | 20.0  | 1500 | 0.6704          | 0.8633   |
| 0.0009        | 21.0  | 1575 | 0.6922          | 0.8633   |
| 0.0009        | 22.0  | 1650 | 0.7205          | 0.8617   |
| 0.0007        | 23.0  | 1725 | 0.7357          | 0.8617   |
| 0.0194        | 24.0  | 1800 | 0.7622          | 0.86     |
| 0.0038        | 25.0  | 1875 | 0.7720          | 0.8583   |
| 0.0005        | 26.0  | 1950 | 0.7827          | 0.86     |
| 0.0003        | 27.0  | 2025 | 0.7974          | 0.8583   |
| 0.0054        | 28.0  | 2100 | 0.8004          | 0.8583   |
| 0.019         | 29.0  | 2175 | 0.8026          | 0.8633   |
| 0.0003        | 30.0  | 2250 | 0.8285          | 0.86     |
| 0.0002        | 31.0  | 2325 | 0.8245          | 0.8617   |
| 0.0002        | 32.0  | 2400 | 0.8349          | 0.86     |
| 0.0002        | 33.0  | 2475 | 0.8577          | 0.8617   |
| 0.0002        | 34.0  | 2550 | 0.8568          | 0.86     |
| 0.0002        | 35.0  | 2625 | 0.8651          | 0.8583   |
| 0.0002        | 36.0  | 2700 | 0.8693          | 0.86     |
| 0.0161        | 37.0  | 2775 | 0.8692          | 0.8633   |
| 0.0002        | 38.0  | 2850 | 0.8782          | 0.8583   |
| 0.0002        | 39.0  | 2925 | 0.8858          | 0.86     |
| 0.0001        | 40.0  | 3000 | 0.8886          | 0.8583   |
| 0.0154        | 41.0  | 3075 | 0.8970          | 0.86     |
| 0.0001        | 42.0  | 3150 | 0.8973          | 0.86     |
| 0.0001        | 43.0  | 3225 | 0.9034          | 0.86     |
| 0.0001        | 44.0  | 3300 | 0.9094          | 0.8617   |
| 0.0001        | 45.0  | 3375 | 0.9094          | 0.86     |
| 0.0001        | 46.0  | 3450 | 0.9101          | 0.86     |
| 0.0001        | 47.0  | 3525 | 0.9123          | 0.86     |
| 0.0001        | 48.0  | 3600 | 0.9135          | 0.86     |
| 0.0001        | 49.0  | 3675 | 0.9142          | 0.86     |
| 0.0001        | 50.0  | 3750 | 0.9148          | 0.86     |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0

abnormal_sperm non-sperm normal_sperm