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# smids_1x_deit_tiny_adamax_001_fold1

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: 1.1082
- Accuracy: 0.8581

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.7889        | 1.0   | 76   | 0.6069          | 0.7679   |
| 0.5102        | 2.0   | 152  | 0.5610          | 0.7997   |
| 0.4217        | 3.0   | 228  | 0.8352          | 0.6995   |
| 0.4159        | 4.0   | 304  | 0.5497          | 0.7813   |
| 0.3589        | 5.0   | 380  | 0.5194          | 0.8114   |
| 0.276         | 6.0   | 456  | 0.5883          | 0.8097   |
| 0.2664        | 7.0   | 532  | 0.6189          | 0.7846   |
| 0.1835        | 8.0   | 608  | 0.6054          | 0.8280   |
| 0.2342        | 9.0   | 684  | 0.5718          | 0.7997   |
| 0.1616        | 10.0  | 760  | 0.4962          | 0.8347   |
| 0.215         | 11.0  | 836  | 0.5625          | 0.8397   |
| 0.0927        | 12.0  | 912  | 0.7589          | 0.8114   |
| 0.1215        | 13.0  | 988  | 0.6624          | 0.8280   |
| 0.1378        | 14.0  | 1064 | 0.6885          | 0.8364   |
| 0.0728        | 15.0  | 1140 | 0.7416          | 0.8297   |
| 0.0869        | 16.0  | 1216 | 0.6972          | 0.8514   |
| 0.036         | 17.0  | 1292 | 0.9407          | 0.8214   |
| 0.0943        | 18.0  | 1368 | 0.8304          | 0.8347   |
| 0.0241        | 19.0  | 1444 | 0.8350          | 0.8347   |
| 0.0865        | 20.0  | 1520 | 0.8686          | 0.8214   |
| 0.0747        | 21.0  | 1596 | 0.9140          | 0.8230   |
| 0.0326        | 22.0  | 1672 | 0.9287          | 0.8464   |
| 0.0264        | 23.0  | 1748 | 1.1143          | 0.8531   |
| 0.0071        | 24.0  | 1824 | 0.9573          | 0.8464   |
| 0.0572        | 25.0  | 1900 | 0.9057          | 0.8347   |
| 0.0013        | 26.0  | 1976 | 0.9807          | 0.8548   |
| 0.0325        | 27.0  | 2052 | 1.0110          | 0.8447   |
| 0.0062        | 28.0  | 2128 | 1.0638          | 0.8247   |
| 0.0158        | 29.0  | 2204 | 0.9283          | 0.8464   |
| 0.018         | 30.0  | 2280 | 0.7858          | 0.8564   |
| 0.0102        | 31.0  | 2356 | 0.9337          | 0.8614   |
| 0.0111        | 32.0  | 2432 | 0.9445          | 0.8581   |
| 0.0002        | 33.0  | 2508 | 0.9913          | 0.8514   |
| 0.0001        | 34.0  | 2584 | 1.0058          | 0.8564   |
| 0.011         | 35.0  | 2660 | 1.0207          | 0.8581   |
| 0.004         | 36.0  | 2736 | 1.0277          | 0.8564   |
| 0.0081        | 37.0  | 2812 | 1.0540          | 0.8548   |
| 0.0           | 38.0  | 2888 | 1.0713          | 0.8497   |
| 0.0038        | 39.0  | 2964 | 1.0596          | 0.8548   |
| 0.0           | 40.0  | 3040 | 1.0612          | 0.8581   |
| 0.0037        | 41.0  | 3116 | 1.0825          | 0.8564   |
| 0.0           | 42.0  | 3192 | 1.0750          | 0.8614   |
| 0.0051        | 43.0  | 3268 | 1.0851          | 0.8581   |
| 0.0           | 44.0  | 3344 | 1.0866          | 0.8564   |
| 0.0           | 45.0  | 3420 | 1.0922          | 0.8614   |
| 0.0           | 46.0  | 3496 | 1.0974          | 0.8598   |
| 0.0           | 47.0  | 3572 | 1.1025          | 0.8598   |
| 0.0028        | 48.0  | 3648 | 1.1080          | 0.8598   |
| 0.0           | 49.0  | 3724 | 1.1080          | 0.8581   |
| 0.0           | 50.0  | 3800 | 1.1082          | 0.8581   |


### 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