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# smids_1x_deit_tiny_rms_0001_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: 1.0984
- Accuracy: 0.8817

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.7593        | 1.0   | 75   | 0.5650          | 0.795    |
| 0.4619        | 2.0   | 150  | 0.5773          | 0.74     |
| 0.3635        | 3.0   | 225  | 0.4403          | 0.85     |
| 0.3309        | 4.0   | 300  | 0.3368          | 0.865    |
| 0.2141        | 5.0   | 375  | 0.4183          | 0.86     |
| 0.1728        | 6.0   | 450  | 0.5130          | 0.8617   |
| 0.154         | 7.0   | 525  | 0.4040          | 0.8683   |
| 0.1331        | 8.0   | 600  | 0.5264          | 0.855    |
| 0.0922        | 9.0   | 675  | 0.7609          | 0.8467   |
| 0.0818        | 10.0  | 750  | 0.6611          | 0.8733   |
| 0.1085        | 11.0  | 825  | 0.6834          | 0.8783   |
| 0.0246        | 12.0  | 900  | 0.6979          | 0.8783   |
| 0.0878        | 13.0  | 975  | 0.9032          | 0.8433   |
| 0.1089        | 14.0  | 1050 | 0.7716          | 0.86     |
| 0.0143        | 15.0  | 1125 | 0.8328          | 0.8633   |
| 0.0139        | 16.0  | 1200 | 0.8299          | 0.86     |
| 0.0102        | 17.0  | 1275 | 0.9296          | 0.865    |
| 0.1127        | 18.0  | 1350 | 0.8373          | 0.8517   |
| 0.0195        | 19.0  | 1425 | 0.9545          | 0.87     |
| 0.0133        | 20.0  | 1500 | 1.0697          | 0.8617   |
| 0.0108        | 21.0  | 1575 | 1.2111          | 0.8333   |
| 0.0129        | 22.0  | 1650 | 1.0019          | 0.8667   |
| 0.0225        | 23.0  | 1725 | 1.0409          | 0.8567   |
| 0.0251        | 24.0  | 1800 | 1.1816          | 0.8467   |
| 0.0012        | 25.0  | 1875 | 1.1276          | 0.8633   |
| 0.003         | 26.0  | 1950 | 1.2613          | 0.8517   |
| 0.0173        | 27.0  | 2025 | 1.2463          | 0.8667   |
| 0.0413        | 28.0  | 2100 | 1.0810          | 0.8667   |
| 0.0002        | 29.0  | 2175 | 1.0875          | 0.8683   |
| 0.0257        | 30.0  | 2250 | 1.0511          | 0.86     |
| 0.0           | 31.0  | 2325 | 0.9064          | 0.895    |
| 0.0           | 32.0  | 2400 | 0.9226          | 0.8933   |
| 0.0           | 33.0  | 2475 | 0.9451          | 0.8933   |
| 0.0062        | 34.0  | 2550 | 0.9369          | 0.8917   |
| 0.0083        | 35.0  | 2625 | 0.9494          | 0.885    |
| 0.0047        | 36.0  | 2700 | 0.9547          | 0.885    |
| 0.0019        | 37.0  | 2775 | 0.9760          | 0.885    |
| 0.0           | 38.0  | 2850 | 1.0147          | 0.8883   |
| 0.0           | 39.0  | 2925 | 0.9604          | 0.885    |
| 0.0           | 40.0  | 3000 | 0.9768          | 0.8883   |
| 0.0           | 41.0  | 3075 | 0.9916          | 0.8817   |
| 0.003         | 42.0  | 3150 | 1.0329          | 0.8867   |
| 0.0028        | 43.0  | 3225 | 1.1065          | 0.8733   |
| 0.0           | 44.0  | 3300 | 1.0908          | 0.8817   |
| 0.0025        | 45.0  | 3375 | 1.0917          | 0.8817   |
| 0.0025        | 46.0  | 3450 | 1.0917          | 0.8817   |
| 0.0051        | 47.0  | 3525 | 1.0933          | 0.8817   |
| 0.0           | 48.0  | 3600 | 1.0955          | 0.8817   |
| 0.0           | 49.0  | 3675 | 1.0973          | 0.8817   |
| 0.0044        | 50.0  | 3750 | 1.0984          | 0.8817   |


### 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