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# smids_1x_deit_small_sgd_0001_fold5

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: 0.7968
- Accuracy: 0.6783

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.0626        | 1.0   | 75   | 1.0608          | 0.4483   |
| 1.0568        | 2.0   | 150  | 1.0464          | 0.4867   |
| 1.0365        | 3.0   | 225  | 1.0338          | 0.505    |
| 1.0078        | 4.0   | 300  | 1.0223          | 0.5333   |
| 0.9982        | 5.0   | 375  | 1.0117          | 0.5367   |
| 0.9993        | 6.0   | 450  | 1.0016          | 0.5483   |
| 0.9996        | 7.0   | 525  | 0.9918          | 0.5533   |
| 0.9666        | 8.0   | 600  | 0.9822          | 0.5583   |
| 0.9644        | 9.0   | 675  | 0.9728          | 0.5617   |
| 0.9545        | 10.0  | 750  | 0.9636          | 0.575    |
| 0.9539        | 11.0  | 825  | 0.9547          | 0.5817   |
| 0.9365        | 12.0  | 900  | 0.9461          | 0.5867   |
| 0.9407        | 13.0  | 975  | 0.9377          | 0.5983   |
| 0.9254        | 14.0  | 1050 | 0.9295          | 0.6067   |
| 0.8947        | 15.0  | 1125 | 0.9216          | 0.61     |
| 0.8953        | 16.0  | 1200 | 0.9139          | 0.615    |
| 0.8981        | 17.0  | 1275 | 0.9064          | 0.6217   |
| 0.8879        | 18.0  | 1350 | 0.8991          | 0.625    |
| 0.8717        | 19.0  | 1425 | 0.8924          | 0.625    |
| 0.894         | 20.0  | 1500 | 0.8856          | 0.6233   |
| 0.8798        | 21.0  | 1575 | 0.8793          | 0.6267   |
| 0.8697        | 22.0  | 1650 | 0.8733          | 0.6283   |
| 0.8459        | 23.0  | 1725 | 0.8674          | 0.6283   |
| 0.8379        | 24.0  | 1800 | 0.8619          | 0.6317   |
| 0.8435        | 25.0  | 1875 | 0.8567          | 0.63     |
| 0.8249        | 26.0  | 1950 | 0.8516          | 0.6367   |
| 0.8188        | 27.0  | 2025 | 0.8468          | 0.6433   |
| 0.8401        | 28.0  | 2100 | 0.8423          | 0.645    |
| 0.8328        | 29.0  | 2175 | 0.8381          | 0.6483   |
| 0.8111        | 30.0  | 2250 | 0.8341          | 0.66     |
| 0.8031        | 31.0  | 2325 | 0.8302          | 0.6633   |
| 0.8167        | 32.0  | 2400 | 0.8267          | 0.665    |
| 0.8141        | 33.0  | 2475 | 0.8233          | 0.6667   |
| 0.7864        | 34.0  | 2550 | 0.8201          | 0.6717   |
| 0.7796        | 35.0  | 2625 | 0.8172          | 0.6717   |
| 0.767         | 36.0  | 2700 | 0.8145          | 0.675    |
| 0.759         | 37.0  | 2775 | 0.8119          | 0.675    |
| 0.7758        | 38.0  | 2850 | 0.8096          | 0.675    |
| 0.7909        | 39.0  | 2925 | 0.8075          | 0.675    |
| 0.7767        | 40.0  | 3000 | 0.8055          | 0.6767   |
| 0.7913        | 41.0  | 3075 | 0.8038          | 0.6767   |
| 0.7892        | 42.0  | 3150 | 0.8023          | 0.6783   |
| 0.787         | 43.0  | 3225 | 0.8010          | 0.6783   |
| 0.7743        | 44.0  | 3300 | 0.7998          | 0.6783   |
| 0.7658        | 45.0  | 3375 | 0.7988          | 0.6783   |
| 0.8086        | 46.0  | 3450 | 0.7980          | 0.6817   |
| 0.7797        | 47.0  | 3525 | 0.7974          | 0.68     |
| 0.7878        | 48.0  | 3600 | 0.7970          | 0.6783   |
| 0.77          | 49.0  | 3675 | 0.7968          | 0.6783   |
| 0.742         | 50.0  | 3750 | 0.7968          | 0.6783   |


### 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