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# smids_1x_deit_tiny_rms_0001_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: 1.0693
- Accuracy: 0.8648

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.7287        | 1.0   | 76   | 0.8533          | 0.6394   |
| 0.5852        | 2.0   | 152  | 0.6881          | 0.7195   |
| 0.3351        | 3.0   | 228  | 0.4986          | 0.7997   |
| 0.2896        | 4.0   | 304  | 0.4784          | 0.8280   |
| 0.1989        | 5.0   | 380  | 0.4421          | 0.8664   |
| 0.1697        | 6.0   | 456  | 0.5180          | 0.8381   |
| 0.1375        | 7.0   | 532  | 0.6205          | 0.8331   |
| 0.099         | 8.0   | 608  | 0.5628          | 0.8631   |
| 0.0915        | 9.0   | 684  | 0.7872          | 0.8464   |
| 0.0302        | 10.0  | 760  | 0.6523          | 0.8748   |
| 0.067         | 11.0  | 836  | 0.7797          | 0.8447   |
| 0.0423        | 12.0  | 912  | 0.7040          | 0.8548   |
| 0.0283        | 13.0  | 988  | 0.7674          | 0.8631   |
| 0.0338        | 14.0  | 1064 | 0.7877          | 0.8564   |
| 0.0931        | 15.0  | 1140 | 0.9177          | 0.8381   |
| 0.0232        | 16.0  | 1216 | 0.9119          | 0.8531   |
| 0.0145        | 17.0  | 1292 | 0.9967          | 0.8514   |
| 0.0553        | 18.0  | 1368 | 0.9035          | 0.8531   |
| 0.0024        | 19.0  | 1444 | 0.9160          | 0.8631   |
| 0.0523        | 20.0  | 1520 | 0.8356          | 0.8648   |
| 0.033         | 21.0  | 1596 | 1.0628          | 0.8531   |
| 0.0448        | 22.0  | 1672 | 0.8647          | 0.8664   |
| 0.0183        | 23.0  | 1748 | 1.0897          | 0.8481   |
| 0.0002        | 24.0  | 1824 | 1.0415          | 0.8431   |
| 0.0163        | 25.0  | 1900 | 0.9932          | 0.8581   |
| 0.0047        | 26.0  | 1976 | 1.1496          | 0.8514   |
| 0.0072        | 27.0  | 2052 | 1.0645          | 0.8531   |
| 0.0133        | 28.0  | 2128 | 1.1427          | 0.8297   |
| 0.0062        | 29.0  | 2204 | 1.0607          | 0.8531   |
| 0.0           | 30.0  | 2280 | 0.9174          | 0.8715   |
| 0.0155        | 31.0  | 2356 | 1.0165          | 0.8598   |
| 0.0239        | 32.0  | 2432 | 1.0075          | 0.8698   |
| 0.0001        | 33.0  | 2508 | 1.0034          | 0.8731   |
| 0.0           | 34.0  | 2584 | 1.0346          | 0.8598   |
| 0.0119        | 35.0  | 2660 | 0.9934          | 0.8631   |
| 0.0037        | 36.0  | 2736 | 1.0215          | 0.8614   |
| 0.0079        | 37.0  | 2812 | 0.9915          | 0.8698   |
| 0.0           | 38.0  | 2888 | 1.0008          | 0.8698   |
| 0.0032        | 39.0  | 2964 | 1.0184          | 0.8731   |
| 0.0           | 40.0  | 3040 | 1.0021          | 0.8664   |
| 0.0033        | 41.0  | 3116 | 1.0395          | 0.8698   |
| 0.0           | 42.0  | 3192 | 1.0443          | 0.8664   |
| 0.0049        | 43.0  | 3268 | 1.0447          | 0.8681   |
| 0.0           | 44.0  | 3344 | 1.0507          | 0.8664   |
| 0.0           | 45.0  | 3420 | 1.0520          | 0.8648   |
| 0.0           | 46.0  | 3496 | 1.0585          | 0.8648   |
| 0.0           | 47.0  | 3572 | 1.0642          | 0.8648   |
| 0.0026        | 48.0  | 3648 | 1.0682          | 0.8648   |
| 0.0           | 49.0  | 3724 | 1.0688          | 0.8648   |
| 0.0           | 50.0  | 3800 | 1.0693          | 0.8648   |


### 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