
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# smids_3x_deit_base_sgd_0001_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: 0.6061
- Accuracy: 0.7930

## 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: 0.0001
- 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 1.1207        | 1.0   | 226   | 1.1055          | 0.3255   |
| 1.0758        | 2.0   | 452   | 1.0934          | 0.3472   |
| 1.0718        | 3.0   | 678   | 1.0808          | 0.3773   |
| 1.0624        | 4.0   | 904   | 1.0677          | 0.4090   |
| 1.0382        | 5.0   | 1130  | 1.0537          | 0.4591   |
| 1.0247        | 6.0   | 1356  | 1.0386          | 0.4925   |
| 1.0174        | 7.0   | 1582  | 1.0217          | 0.5209   |
| 0.9921        | 8.0   | 1808  | 1.0035          | 0.5576   |
| 0.9451        | 9.0   | 2034  | 0.9830          | 0.5910   |
| 0.9379        | 10.0  | 2260  | 0.9606          | 0.6260   |
| 0.9321        | 11.0  | 2486  | 0.9380          | 0.6427   |
| 0.8822        | 12.0  | 2712  | 0.9157          | 0.6661   |
| 0.8728        | 13.0  | 2938  | 0.8943          | 0.6778   |
| 0.8476        | 14.0  | 3164  | 0.8736          | 0.6912   |
| 0.8717        | 15.0  | 3390  | 0.8536          | 0.7062   |
| 0.8185        | 16.0  | 3616  | 0.8345          | 0.7229   |
| 0.7787        | 17.0  | 3842  | 0.8163          | 0.7295   |
| 0.8087        | 18.0  | 4068  | 0.7993          | 0.7396   |
| 0.791         | 19.0  | 4294  | 0.7835          | 0.7429   |
| 0.7857        | 20.0  | 4520  | 0.7684          | 0.7462   |
| 0.7846        | 21.0  | 4746  | 0.7543          | 0.7513   |
| 0.7633        | 22.0  | 4972  | 0.7411          | 0.7513   |
| 0.7242        | 23.0  | 5198  | 0.7289          | 0.7546   |
| 0.7569        | 24.0  | 5424  | 0.7173          | 0.7546   |
| 0.7119        | 25.0  | 5650  | 0.7067          | 0.7546   |
| 0.7356        | 26.0  | 5876  | 0.6968          | 0.7629   |
| 0.6807        | 27.0  | 6102  | 0.6877          | 0.7646   |
| 0.7192        | 28.0  | 6328  | 0.6794          | 0.7696   |
| 0.658         | 29.0  | 6554  | 0.6715          | 0.7713   |
| 0.7338        | 30.0  | 6780  | 0.6643          | 0.7713   |
| 0.6572        | 31.0  | 7006  | 0.6576          | 0.7746   |
| 0.6818        | 32.0  | 7232  | 0.6514          | 0.7796   |
| 0.6397        | 33.0  | 7458  | 0.6458          | 0.7780   |
| 0.6265        | 34.0  | 7684  | 0.6406          | 0.7813   |
| 0.6395        | 35.0  | 7910  | 0.6359          | 0.7846   |
| 0.6047        | 36.0  | 8136  | 0.6316          | 0.7863   |
| 0.6592        | 37.0  | 8362  | 0.6277          | 0.7846   |
| 0.6634        | 38.0  | 8588  | 0.6242          | 0.7863   |
| 0.6398        | 39.0  | 8814  | 0.6210          | 0.7863   |
| 0.601         | 40.0  | 9040  | 0.6182          | 0.7863   |
| 0.6061        | 41.0  | 9266  | 0.6157          | 0.7863   |
| 0.6339        | 42.0  | 9492  | 0.6135          | 0.7880   |
| 0.6566        | 43.0  | 9718  | 0.6116          | 0.7896   |
| 0.5859        | 44.0  | 9944  | 0.6100          | 0.7896   |
| 0.6306        | 45.0  | 10170 | 0.6087          | 0.7896   |
| 0.6188        | 46.0  | 10396 | 0.6077          | 0.7896   |
| 0.6096        | 47.0  | 10622 | 0.6069          | 0.7930   |
| 0.6151        | 48.0  | 10848 | 0.6064          | 0.7930   |
| 0.6052        | 49.0  | 11074 | 0.6062          | 0.7930   |
| 0.6333        | 50.0  | 11300 | 0.6061          | 0.7930   |


### 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