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# smids_1x_deit_small_adamax_0001_fold1

This model is a fine-tuned version of [facebook/deit-small-patch16-224](https://huggingface.co/facebook/deit-small-patch16-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6387
- Accuracy: 0.8982

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.4614        | 1.0   | 76   | 0.3156          | 0.8831   |
| 0.2855        | 2.0   | 152  | 0.2885          | 0.8915   |
| 0.1652        | 3.0   | 228  | 0.3412          | 0.8781   |
| 0.0912        | 4.0   | 304  | 0.3542          | 0.8965   |
| 0.1011        | 5.0   | 380  | 0.5346          | 0.8798   |
| 0.038         | 6.0   | 456  | 0.4288          | 0.8982   |
| 0.0075        | 7.0   | 532  | 0.5068          | 0.8998   |
| 0.0075        | 8.0   | 608  | 0.5044          | 0.9098   |
| 0.0143        | 9.0   | 684  | 0.4561          | 0.9032   |
| 0.0021        | 10.0  | 760  | 0.5259          | 0.8982   |
| 0.0314        | 11.0  | 836  | 0.5405          | 0.8932   |
| 0.0002        | 12.0  | 912  | 0.5496          | 0.8965   |
| 0.0052        | 13.0  | 988  | 0.5683          | 0.9098   |
| 0.0001        | 14.0  | 1064 | 0.5233          | 0.9015   |
| 0.0093        | 15.0  | 1140 | 0.5621          | 0.9032   |
| 0.0001        | 16.0  | 1216 | 0.5647          | 0.9048   |
| 0.0001        | 17.0  | 1292 | 0.5914          | 0.8965   |
| 0.0072        | 18.0  | 1368 | 0.5464          | 0.9032   |
| 0.0001        | 19.0  | 1444 | 0.5470          | 0.8982   |
| 0.0035        | 20.0  | 1520 | 0.6054          | 0.8965   |
| 0.004         | 21.0  | 1596 | 0.5757          | 0.9015   |
| 0.0036        | 22.0  | 1672 | 0.5664          | 0.8982   |
| 0.0001        | 23.0  | 1748 | 0.6187          | 0.8948   |
| 0.0           | 24.0  | 1824 | 0.5774          | 0.9048   |
| 0.0072        | 25.0  | 1900 | 0.5831          | 0.8915   |
| 0.0032        | 26.0  | 1976 | 0.5874          | 0.9015   |
| 0.0042        | 27.0  | 2052 | 0.5879          | 0.8998   |
| 0.0028        | 28.0  | 2128 | 0.6082          | 0.8965   |
| 0.0055        | 29.0  | 2204 | 0.6022          | 0.8965   |
| 0.0           | 30.0  | 2280 | 0.5996          | 0.8965   |
| 0.0046        | 31.0  | 2356 | 0.6176          | 0.8948   |
| 0.0082        | 32.0  | 2432 | 0.5942          | 0.8965   |
| 0.0           | 33.0  | 2508 | 0.6226          | 0.8948   |
| 0.0           | 34.0  | 2584 | 0.6117          | 0.8982   |
| 0.0101        | 35.0  | 2660 | 0.6208          | 0.8932   |
| 0.0032        | 36.0  | 2736 | 0.6175          | 0.8948   |
| 0.006         | 37.0  | 2812 | 0.6334          | 0.8932   |
| 0.0           | 38.0  | 2888 | 0.6155          | 0.8982   |
| 0.0031        | 39.0  | 2964 | 0.6236          | 0.8982   |
| 0.0           | 40.0  | 3040 | 0.6141          | 0.8998   |
| 0.0026        | 41.0  | 3116 | 0.6351          | 0.8948   |
| 0.0           | 42.0  | 3192 | 0.6313          | 0.8965   |
| 0.0047        | 43.0  | 3268 | 0.6395          | 0.8932   |
| 0.0           | 44.0  | 3344 | 0.6247          | 0.8998   |
| 0.0           | 45.0  | 3420 | 0.6367          | 0.8982   |
| 0.0           | 46.0  | 3496 | 0.6347          | 0.8982   |
| 0.0           | 47.0  | 3572 | 0.6365          | 0.8982   |
| 0.0024        | 48.0  | 3648 | 0.6411          | 0.8982   |
| 0.0           | 49.0  | 3724 | 0.6383          | 0.8982   |
| 0.0           | 50.0  | 3800 | 0.6387          | 0.8982   |


### 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