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# smids_1x_deit_tiny_sgd_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: 0.8020
- Accuracy: 0.6578

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.277         | 1.0   | 76   | 1.2939          | 0.2771   |
| 1.2116        | 2.0   | 152  | 1.2225          | 0.3172   |
| 1.1682        | 3.0   | 228  | 1.1693          | 0.3740   |
| 1.1189        | 4.0   | 304  | 1.1270          | 0.4073   |
| 1.0545        | 5.0   | 380  | 1.0950          | 0.4240   |
| 1.0649        | 6.0   | 456  | 1.0693          | 0.4574   |
| 1.0629        | 7.0   | 532  | 1.0475          | 0.4858   |
| 1.0345        | 8.0   | 608  | 1.0290          | 0.5142   |
| 1.012         | 9.0   | 684  | 1.0130          | 0.5392   |
| 0.9959        | 10.0  | 760  | 0.9988          | 0.5526   |
| 0.9617        | 11.0  | 836  | 0.9857          | 0.5626   |
| 1.0119        | 12.0  | 912  | 0.9733          | 0.5710   |
| 0.951         | 13.0  | 988  | 0.9618          | 0.5810   |
| 0.8944        | 14.0  | 1064 | 0.9511          | 0.5876   |
| 0.9729        | 15.0  | 1140 | 0.9409          | 0.5910   |
| 0.9626        | 16.0  | 1216 | 0.9311          | 0.5927   |
| 0.9103        | 17.0  | 1292 | 0.9219          | 0.6043   |
| 0.9088        | 18.0  | 1368 | 0.9131          | 0.6144   |
| 0.9045        | 19.0  | 1444 | 0.9046          | 0.6160   |
| 0.9231        | 20.0  | 1520 | 0.8968          | 0.6160   |
| 0.9054        | 21.0  | 1596 | 0.8893          | 0.6177   |
| 0.854         | 22.0  | 1672 | 0.8821          | 0.6227   |
| 0.8305        | 23.0  | 1748 | 0.8753          | 0.6294   |
| 0.8621        | 24.0  | 1824 | 0.8689          | 0.6311   |
| 0.8299        | 25.0  | 1900 | 0.8629          | 0.6327   |
| 0.8471        | 26.0  | 1976 | 0.8573          | 0.6344   |
| 0.817         | 27.0  | 2052 | 0.8521          | 0.6344   |
| 0.792         | 28.0  | 2128 | 0.8472          | 0.6361   |
| 0.8136        | 29.0  | 2204 | 0.8426          | 0.6377   |
| 0.7461        | 30.0  | 2280 | 0.8383          | 0.6411   |
| 0.8135        | 31.0  | 2356 | 0.8343          | 0.6427   |
| 0.7863        | 32.0  | 2432 | 0.8305          | 0.6461   |
| 0.7659        | 33.0  | 2508 | 0.8271          | 0.6494   |
| 0.8238        | 34.0  | 2584 | 0.8240          | 0.6528   |
| 0.8196        | 35.0  | 2660 | 0.8211          | 0.6528   |
| 0.7577        | 36.0  | 2736 | 0.8184          | 0.6528   |
| 0.8136        | 37.0  | 2812 | 0.8159          | 0.6528   |
| 0.7544        | 38.0  | 2888 | 0.8137          | 0.6561   |
| 0.7769        | 39.0  | 2964 | 0.8116          | 0.6561   |
| 0.8539        | 40.0  | 3040 | 0.8098          | 0.6561   |
| 0.7796        | 41.0  | 3116 | 0.8081          | 0.6544   |
| 0.765         | 42.0  | 3192 | 0.8067          | 0.6578   |
| 0.7732        | 43.0  | 3268 | 0.8054          | 0.6578   |
| 0.7585        | 44.0  | 3344 | 0.8044          | 0.6561   |
| 0.7325        | 45.0  | 3420 | 0.8036          | 0.6561   |
| 0.7699        | 46.0  | 3496 | 0.8029          | 0.6578   |
| 0.7818        | 47.0  | 3572 | 0.8024          | 0.6578   |
| 0.7946        | 48.0  | 3648 | 0.8021          | 0.6578   |
| 0.7345        | 49.0  | 3724 | 0.8020          | 0.6578   |
| 0.833         | 50.0  | 3800 | 0.8020          | 0.6578   |


### 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