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# smids_1x_deit_tiny_sgd_0001_fold4

This model is a fine-tuned version of [facebook/deit-tiny-patch16-224](https://huggingface.co/facebook/deit-tiny-patch16-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8842
- Accuracy: 0.5767

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.2663        | 1.0   | 75   | 1.2852          | 0.3417   |
| 1.1957        | 2.0   | 150  | 1.2221          | 0.36     |
| 1.1637        | 3.0   | 225  | 1.1784          | 0.3767   |
| 1.1755        | 4.0   | 300  | 1.1489          | 0.365    |
| 1.123         | 5.0   | 375  | 1.1280          | 0.3733   |
| 1.103         | 6.0   | 450  | 1.1122          | 0.3833   |
| 1.0888        | 7.0   | 525  | 1.0988          | 0.3917   |
| 1.0793        | 8.0   | 600  | 1.0870          | 0.4      |
| 1.0578        | 9.0   | 675  | 1.0759          | 0.4133   |
| 1.0777        | 10.0  | 750  | 1.0654          | 0.4183   |
| 1.017         | 11.0  | 825  | 1.0553          | 0.4183   |
| 1.0652        | 12.0  | 900  | 1.0460          | 0.43     |
| 1.0325        | 13.0  | 975  | 1.0371          | 0.4417   |
| 1.0323        | 14.0  | 1050 | 1.0281          | 0.45     |
| 1.0256        | 15.0  | 1125 | 1.0196          | 0.4567   |
| 1.0233        | 16.0  | 1200 | 1.0112          | 0.465    |
| 0.9433        | 17.0  | 1275 | 1.0027          | 0.4667   |
| 0.989         | 18.0  | 1350 | 0.9944          | 0.4733   |
| 0.9912        | 19.0  | 1425 | 0.9866          | 0.4783   |
| 0.9822        | 20.0  | 1500 | 0.9787          | 0.4817   |
| 0.9897        | 21.0  | 1575 | 0.9718          | 0.495    |
| 0.9177        | 22.0  | 1650 | 0.9648          | 0.5067   |
| 0.95          | 23.0  | 1725 | 0.9583          | 0.5133   |
| 0.9863        | 24.0  | 1800 | 0.9520          | 0.515    |
| 0.9643        | 25.0  | 1875 | 0.9462          | 0.5217   |
| 0.9026        | 26.0  | 1950 | 0.9408          | 0.5267   |
| 0.9173        | 27.0  | 2025 | 0.9357          | 0.5283   |
| 0.927         | 28.0  | 2100 | 0.9309          | 0.5333   |
| 0.9287        | 29.0  | 2175 | 0.9265          | 0.5417   |
| 0.9309        | 30.0  | 2250 | 0.9222          | 0.5467   |
| 0.9103        | 31.0  | 2325 | 0.9183          | 0.5483   |
| 0.9355        | 32.0  | 2400 | 0.9146          | 0.5583   |
| 0.9176        | 33.0  | 2475 | 0.9110          | 0.56     |
| 0.883         | 34.0  | 2550 | 0.9078          | 0.5617   |
| 0.9163        | 35.0  | 2625 | 0.9049          | 0.5633   |
| 0.8785        | 36.0  | 2700 | 0.9021          | 0.5667   |
| 0.8597        | 37.0  | 2775 | 0.8996          | 0.565    |
| 0.8694        | 38.0  | 2850 | 0.8972          | 0.5717   |
| 0.8945        | 39.0  | 2925 | 0.8952          | 0.5733   |
| 0.8725        | 40.0  | 3000 | 0.8932          | 0.575    |
| 0.875         | 41.0  | 3075 | 0.8915          | 0.575    |
| 0.8552        | 42.0  | 3150 | 0.8899          | 0.575    |
| 0.8903        | 43.0  | 3225 | 0.8886          | 0.575    |
| 0.8534        | 44.0  | 3300 | 0.8873          | 0.575    |
| 0.8746        | 45.0  | 3375 | 0.8863          | 0.5767   |
| 0.8976        | 46.0  | 3450 | 0.8855          | 0.5767   |
| 0.8522        | 47.0  | 3525 | 0.8849          | 0.5767   |
| 0.8759        | 48.0  | 3600 | 0.8845          | 0.5767   |
| 0.9028        | 49.0  | 3675 | 0.8842          | 0.5767   |
| 0.8753        | 50.0  | 3750 | 0.8842          | 0.5767   |


### 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