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# smids_3x_deit_tiny_sgd_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: 1.0996
- Accuracy: 0.4057

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 1.3881        | 1.0   | 226   | 1.3111          | 0.3489   |
| 1.3128        | 2.0   | 452   | 1.2903          | 0.3523   |
| 1.3013        | 3.0   | 678   | 1.2711          | 0.3589   |
| 1.3217        | 4.0   | 904   | 1.2541          | 0.3656   |
| 1.2917        | 5.0   | 1130  | 1.2386          | 0.3639   |
| 1.3196        | 6.0   | 1356  | 1.2247          | 0.3656   |
| 1.2618        | 7.0   | 1582  | 1.2122          | 0.3673   |
| 1.2868        | 8.0   | 1808  | 1.2013          | 0.3689   |
| 1.2007        | 9.0   | 2034  | 1.1914          | 0.3790   |
| 1.1905        | 10.0  | 2260  | 1.1825          | 0.3856   |
| 1.2678        | 11.0  | 2486  | 1.1746          | 0.3823   |
| 1.1575        | 12.0  | 2712  | 1.1675          | 0.3856   |
| 1.1907        | 13.0  | 2938  | 1.1613          | 0.3840   |
| 1.2093        | 14.0  | 3164  | 1.1556          | 0.3840   |
| 1.2019        | 15.0  | 3390  | 1.1505          | 0.3756   |
| 1.1269        | 16.0  | 3616  | 1.1458          | 0.3756   |
| 1.2046        | 17.0  | 3842  | 1.1416          | 0.3790   |
| 1.1582        | 18.0  | 4068  | 1.1378          | 0.3740   |
| 1.1486        | 19.0  | 4294  | 1.1344          | 0.3806   |
| 1.1865        | 20.0  | 4520  | 1.1312          | 0.3773   |
| 1.1413        | 21.0  | 4746  | 1.1283          | 0.3773   |
| 1.1132        | 22.0  | 4972  | 1.1257          | 0.3856   |
| 1.1589        | 23.0  | 5198  | 1.1233          | 0.3873   |
| 1.1721        | 24.0  | 5424  | 1.1210          | 0.3856   |
| 1.1316        | 25.0  | 5650  | 1.1189          | 0.3856   |
| 1.1482        | 26.0  | 5876  | 1.1170          | 0.3957   |
| 1.126         | 27.0  | 6102  | 1.1153          | 0.4007   |
| 1.0926        | 28.0  | 6328  | 1.1137          | 0.4040   |
| 1.1041        | 29.0  | 6554  | 1.1121          | 0.4023   |
| 1.206         | 30.0  | 6780  | 1.1107          | 0.3973   |
| 1.1379        | 31.0  | 7006  | 1.1094          | 0.3940   |
| 1.1454        | 32.0  | 7232  | 1.1082          | 0.3990   |
| 1.1347        | 33.0  | 7458  | 1.1071          | 0.4040   |
| 1.0924        | 34.0  | 7684  | 1.1061          | 0.4057   |
| 1.0887        | 35.0  | 7910  | 1.1052          | 0.4057   |
| 1.1281        | 36.0  | 8136  | 1.1043          | 0.4057   |
| 1.1197        | 37.0  | 8362  | 1.1035          | 0.4057   |
| 1.0883        | 38.0  | 8588  | 1.1028          | 0.4090   |
| 1.1185        | 39.0  | 8814  | 1.1022          | 0.4090   |
| 1.1206        | 40.0  | 9040  | 1.1017          | 0.4090   |
| 1.1449        | 41.0  | 9266  | 1.1012          | 0.4073   |
| 1.0923        | 42.0  | 9492  | 1.1008          | 0.4057   |
| 1.1262        | 43.0  | 9718  | 1.1004          | 0.4073   |
| 1.1447        | 44.0  | 9944  | 1.1002          | 0.4040   |
| 1.11          | 45.0  | 10170 | 1.0999          | 0.4040   |
| 1.1348        | 46.0  | 10396 | 1.0998          | 0.4057   |
| 1.1134        | 47.0  | 10622 | 1.0997          | 0.4057   |
| 1.119         | 48.0  | 10848 | 1.0996          | 0.4057   |
| 1.1325        | 49.0  | 11074 | 1.0996          | 0.4057   |
| 1.1613        | 50.0  | 11300 | 1.0996          | 0.4057   |


### 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