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# smids_1x_beit_base_rms_00001_fold2

This model is a fine-tuned version of [microsoft/beit-base-patch16-224](https://huggingface.co/microsoft/beit-base-patch16-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7810
- Accuracy: 0.8885

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.3067        | 1.0   | 75   | 0.2670          | 0.9018   |
| 0.1737        | 2.0   | 150  | 0.2937          | 0.8918   |
| 0.1236        | 3.0   | 225  | 0.2592          | 0.8968   |
| 0.093         | 4.0   | 300  | 0.2806          | 0.9085   |
| 0.0342        | 5.0   | 375  | 0.3377          | 0.9035   |
| 0.0514        | 6.0   | 450  | 0.4662          | 0.8769   |
| 0.0285        | 7.0   | 525  | 0.4751          | 0.8902   |
| 0.0245        | 8.0   | 600  | 0.4931          | 0.8968   |
| 0.0336        | 9.0   | 675  | 0.4686          | 0.9035   |
| 0.0057        | 10.0  | 750  | 0.6619          | 0.8852   |
| 0.0005        | 11.0  | 825  | 0.5601          | 0.9018   |
| 0.045         | 12.0  | 900  | 0.6300          | 0.8869   |
| 0.0006        | 13.0  | 975  | 0.6005          | 0.8968   |
| 0.0104        | 14.0  | 1050 | 0.6903          | 0.8769   |
| 0.0013        | 15.0  | 1125 | 0.6574          | 0.8968   |
| 0.0022        | 16.0  | 1200 | 0.6330          | 0.8952   |
| 0.0138        | 17.0  | 1275 | 0.6340          | 0.9018   |
| 0.0109        | 18.0  | 1350 | 0.7199          | 0.8902   |
| 0.007         | 19.0  | 1425 | 0.7166          | 0.8968   |
| 0.009         | 20.0  | 1500 | 0.8141          | 0.8802   |
| 0.0077        | 21.0  | 1575 | 0.8216          | 0.8935   |
| 0.0199        | 22.0  | 1650 | 0.8347          | 0.8802   |
| 0.0056        | 23.0  | 1725 | 0.7454          | 0.8869   |
| 0.0076        | 24.0  | 1800 | 0.6539          | 0.8968   |
| 0.0001        | 25.0  | 1875 | 0.7625          | 0.8819   |
| 0.0105        | 26.0  | 1950 | 0.7771          | 0.8918   |
| 0.0191        | 27.0  | 2025 | 0.7871          | 0.8902   |
| 0.0146        | 28.0  | 2100 | 0.7395          | 0.8968   |
| 0.0063        | 29.0  | 2175 | 0.7297          | 0.8968   |
| 0.0064        | 30.0  | 2250 | 0.6880          | 0.8952   |
| 0.0044        | 31.0  | 2325 | 0.7924          | 0.8918   |
| 0.0115        | 32.0  | 2400 | 0.7709          | 0.8918   |
| 0.0213        | 33.0  | 2475 | 0.6964          | 0.8918   |
| 0.0034        | 34.0  | 2550 | 0.7612          | 0.8918   |
| 0.0052        | 35.0  | 2625 | 0.7685          | 0.8968   |
| 0.0043        | 36.0  | 2700 | 0.8478          | 0.8869   |
| 0.0001        | 37.0  | 2775 | 0.7661          | 0.8902   |
| 0.0031        | 38.0  | 2850 | 0.7393          | 0.8968   |
| 0.0464        | 39.0  | 2925 | 0.7536          | 0.8918   |
| 0.0026        | 40.0  | 3000 | 0.7768          | 0.8852   |
| 0.0001        | 41.0  | 3075 | 0.8423          | 0.8835   |
| 0.0041        | 42.0  | 3150 | 0.7762          | 0.8918   |
| 0.0072        | 43.0  | 3225 | 0.7847          | 0.8902   |
| 0.0           | 44.0  | 3300 | 0.7699          | 0.8835   |
| 0.0049        | 45.0  | 3375 | 0.7675          | 0.8852   |
| 0.0001        | 46.0  | 3450 | 0.7767          | 0.8885   |
| 0.0029        | 47.0  | 3525 | 0.7697          | 0.8885   |
| 0.0           | 48.0  | 3600 | 0.7734          | 0.8885   |
| 0.0           | 49.0  | 3675 | 0.7813          | 0.8885   |
| 0.0231        | 50.0  | 3750 | 0.7810          | 0.8885   |


### 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