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# smids_10x_deit_tiny_adamax_00001_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: 0.8545
- Accuracy: 0.9115

## 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: 1e-05
- 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.2768        | 1.0   | 751   | 0.3271          | 0.8681   |
| 0.2559        | 2.0   | 1502  | 0.2686          | 0.8932   |
| 0.1723        | 3.0   | 2253  | 0.2752          | 0.8932   |
| 0.1343        | 4.0   | 3004  | 0.2784          | 0.8898   |
| 0.1389        | 5.0   | 3755  | 0.2896          | 0.8965   |
| 0.1143        | 6.0   | 4506  | 0.3456          | 0.8881   |
| 0.0797        | 7.0   | 5257  | 0.3441          | 0.8865   |
| 0.0583        | 8.0   | 6008  | 0.3964          | 0.8998   |
| 0.0472        | 9.0   | 6759  | 0.4458          | 0.8915   |
| 0.0757        | 10.0  | 7510  | 0.4767          | 0.8982   |
| 0.0191        | 11.0  | 8261  | 0.5147          | 0.8915   |
| 0.031         | 12.0  | 9012  | 0.5873          | 0.8898   |
| 0.0022        | 13.0  | 9763  | 0.6291          | 0.8982   |
| 0.0003        | 14.0  | 10514 | 0.6449          | 0.9048   |
| 0.0014        | 15.0  | 11265 | 0.6651          | 0.8982   |
| 0.0237        | 16.0  | 12016 | 0.7228          | 0.9015   |
| 0.0016        | 17.0  | 12767 | 0.7272          | 0.8948   |
| 0.0001        | 18.0  | 13518 | 0.7560          | 0.9032   |
| 0.0001        | 19.0  | 14269 | 0.7571          | 0.8982   |
| 0.0           | 20.0  | 15020 | 0.7689          | 0.9048   |
| 0.0           | 21.0  | 15771 | 0.7584          | 0.9048   |
| 0.0           | 22.0  | 16522 | 0.7967          | 0.9032   |
| 0.0           | 23.0  | 17273 | 0.7987          | 0.9065   |
| 0.0001        | 24.0  | 18024 | 0.8298          | 0.9065   |
| 0.0           | 25.0  | 18775 | 0.8022          | 0.9098   |
| 0.0           | 26.0  | 19526 | 0.8054          | 0.9098   |
| 0.0           | 27.0  | 20277 | 0.8124          | 0.9065   |
| 0.0           | 28.0  | 21028 | 0.8128          | 0.9082   |
| 0.0194        | 29.0  | 21779 | 0.8361          | 0.9015   |
| 0.0           | 30.0  | 22530 | 0.8316          | 0.9065   |
| 0.0           | 31.0  | 23281 | 0.8255          | 0.9132   |
| 0.0           | 32.0  | 24032 | 0.8225          | 0.9115   |
| 0.0           | 33.0  | 24783 | 0.8294          | 0.9098   |
| 0.0           | 34.0  | 25534 | 0.8377          | 0.9082   |
| 0.0           | 35.0  | 26285 | 0.8477          | 0.9032   |
| 0.0           | 36.0  | 27036 | 0.8439          | 0.9115   |
| 0.0           | 37.0  | 27787 | 0.8492          | 0.9065   |
| 0.0           | 38.0  | 28538 | 0.8435          | 0.9098   |
| 0.0           | 39.0  | 29289 | 0.8490          | 0.9098   |
| 0.0           | 40.0  | 30040 | 0.8482          | 0.9115   |
| 0.0           | 41.0  | 30791 | 0.8506          | 0.9065   |
| 0.0           | 42.0  | 31542 | 0.8515          | 0.9082   |
| 0.0           | 43.0  | 32293 | 0.8517          | 0.9115   |
| 0.0           | 44.0  | 33044 | 0.8525          | 0.9115   |
| 0.0           | 45.0  | 33795 | 0.8550          | 0.9048   |
| 0.0           | 46.0  | 34546 | 0.8557          | 0.9082   |
| 0.0           | 47.0  | 35297 | 0.8547          | 0.9115   |
| 0.0           | 48.0  | 36048 | 0.8545          | 0.9115   |
| 0.0           | 49.0  | 36799 | 0.8544          | 0.9115   |
| 0.0           | 50.0  | 37550 | 0.8545          | 0.9115   |


### Framework versions

- Transformers 4.32.1
- Pytorch 2.1.1+cu121
- Datasets 2.12.0
- Tokenizers 0.13.2

abnormal_sperm non-sperm normal_sperm