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# smids_1x_deit_tiny_adamax_001_fold3

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: 1.4240
- Accuracy: 0.8417

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.7806        | 1.0   | 75   | 0.5704          | 0.7533   |
| 0.5207        | 2.0   | 150  | 0.5966          | 0.73     |
| 0.4092        | 3.0   | 225  | 0.5340          | 0.7933   |
| 0.4512        | 4.0   | 300  | 0.5755          | 0.76     |
| 0.3687        | 5.0   | 375  | 0.4431          | 0.8133   |
| 0.3021        | 6.0   | 450  | 0.4574          | 0.8317   |
| 0.3551        | 7.0   | 525  | 0.5806          | 0.8033   |
| 0.2614        | 8.0   | 600  | 0.5093          | 0.82     |
| 0.2361        | 9.0   | 675  | 0.5262          | 0.8333   |
| 0.1424        | 10.0  | 750  | 0.7202          | 0.83     |
| 0.1293        | 11.0  | 825  | 0.6267          | 0.8333   |
| 0.079         | 12.0  | 900  | 0.7445          | 0.845    |
| 0.1031        | 13.0  | 975  | 0.7831          | 0.8333   |
| 0.0209        | 14.0  | 1050 | 0.7336          | 0.8433   |
| 0.0822        | 15.0  | 1125 | 0.7507          | 0.8217   |
| 0.0881        | 16.0  | 1200 | 0.8785          | 0.8017   |
| 0.0659        | 17.0  | 1275 | 0.8910          | 0.8283   |
| 0.0765        | 18.0  | 1350 | 0.9993          | 0.825    |
| 0.0616        | 19.0  | 1425 | 0.7662          | 0.8417   |
| 0.0408        | 20.0  | 1500 | 0.7907          | 0.8517   |
| 0.0173        | 21.0  | 1575 | 1.0410          | 0.8383   |
| 0.0139        | 22.0  | 1650 | 1.0413          | 0.8333   |
| 0.0185        | 23.0  | 1725 | 1.0477          | 0.84     |
| 0.0006        | 24.0  | 1800 | 1.0787          | 0.8433   |
| 0.0277        | 25.0  | 1875 | 1.0695          | 0.83     |
| 0.0122        | 26.0  | 1950 | 1.1331          | 0.8517   |
| 0.0367        | 27.0  | 2025 | 1.3452          | 0.8283   |
| 0.0236        | 28.0  | 2100 | 1.0892          | 0.83     |
| 0.0104        | 29.0  | 2175 | 1.1352          | 0.8483   |
| 0.0001        | 30.0  | 2250 | 1.2537          | 0.8367   |
| 0.0002        | 31.0  | 2325 | 1.2507          | 0.8317   |
| 0.003         | 32.0  | 2400 | 1.2991          | 0.8333   |
| 0.0046        | 33.0  | 2475 | 1.2933          | 0.8333   |
| 0.0054        | 34.0  | 2550 | 1.3552          | 0.8317   |
| 0.0087        | 35.0  | 2625 | 1.3586          | 0.8333   |
| 0.0052        | 36.0  | 2700 | 1.3844          | 0.8367   |
| 0.0022        | 37.0  | 2775 | 1.3958          | 0.84     |
| 0.0           | 38.0  | 2850 | 1.4041          | 0.8417   |
| 0.0           | 39.0  | 2925 | 1.4038          | 0.84     |
| 0.0           | 40.0  | 3000 | 1.4046          | 0.8433   |
| 0.0           | 41.0  | 3075 | 1.4005          | 0.8433   |
| 0.0031        | 42.0  | 3150 | 1.4048          | 0.8417   |
| 0.0035        | 43.0  | 3225 | 1.4072          | 0.8433   |
| 0.0           | 44.0  | 3300 | 1.4113          | 0.8417   |
| 0.0028        | 45.0  | 3375 | 1.4120          | 0.8417   |
| 0.0026        | 46.0  | 3450 | 1.4166          | 0.84     |
| 0.0061        | 47.0  | 3525 | 1.4166          | 0.8417   |
| 0.0           | 48.0  | 3600 | 1.4221          | 0.84     |
| 0.0           | 49.0  | 3675 | 1.4223          | 0.84     |
| 0.0046        | 50.0  | 3750 | 1.4240          | 0.8417   |


### 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