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# SMIDS_5x_beit_large_SGD_lr001_fold1

This model is a fine-tuned version of [microsoft/beit-large-patch16-224](https://huggingface.co/microsoft/beit-large-patch16-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2965
- Accuracy: 0.8915

## 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: 0.001
- train_batch_size: 16
- eval_batch_size: 16
- 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.5173        | 1.0   | 751   | 0.4799          | 0.8063   |
| 0.3398        | 2.0   | 1502  | 0.3689          | 0.8497   |
| 0.2647        | 3.0   | 2253  | 0.3284          | 0.8664   |
| 0.2959        | 4.0   | 3004  | 0.3110          | 0.8765   |
| 0.3041        | 5.0   | 3755  | 0.2983          | 0.8831   |
| 0.3346        | 6.0   | 4506  | 0.2913          | 0.8932   |
| 0.1946        | 7.0   | 5257  | 0.2879          | 0.8881   |
| 0.1944        | 8.0   | 6008  | 0.2830          | 0.8831   |
| 0.2249        | 9.0   | 6759  | 0.2825          | 0.8848   |
| 0.3122        | 10.0  | 7510  | 0.2836          | 0.8881   |
| 0.2297        | 11.0  | 8261  | 0.2727          | 0.8998   |
| 0.2352        | 12.0  | 9012  | 0.2734          | 0.8915   |
| 0.1383        | 13.0  | 9763  | 0.2693          | 0.9015   |
| 0.1694        | 14.0  | 10514 | 0.2790          | 0.8932   |
| 0.2118        | 15.0  | 11265 | 0.2735          | 0.8915   |
| 0.1728        | 16.0  | 12016 | 0.2726          | 0.8965   |
| 0.2097        | 17.0  | 12767 | 0.2737          | 0.8881   |
| 0.2002        | 18.0  | 13518 | 0.2712          | 0.8915   |
| 0.2198        | 19.0  | 14269 | 0.2717          | 0.8948   |
| 0.1769        | 20.0  | 15020 | 0.2802          | 0.8881   |
| 0.1064        | 21.0  | 15771 | 0.2773          | 0.8965   |
| 0.0668        | 22.0  | 16522 | 0.2831          | 0.8898   |
| 0.2791        | 23.0  | 17273 | 0.2749          | 0.8898   |
| 0.2036        | 24.0  | 18024 | 0.2785          | 0.8932   |
| 0.1633        | 25.0  | 18775 | 0.2797          | 0.8915   |
| 0.2107        | 26.0  | 19526 | 0.2808          | 0.8932   |
| 0.1703        | 27.0  | 20277 | 0.2852          | 0.8932   |
| 0.0866        | 28.0  | 21028 | 0.2898          | 0.8865   |
| 0.1152        | 29.0  | 21779 | 0.2890          | 0.8898   |
| 0.0867        | 30.0  | 22530 | 0.2894          | 0.8898   |
| 0.2133        | 31.0  | 23281 | 0.2897          | 0.8932   |
| 0.1538        | 32.0  | 24032 | 0.2956          | 0.8865   |
| 0.0658        | 33.0  | 24783 | 0.2931          | 0.8898   |
| 0.1112        | 34.0  | 25534 | 0.2931          | 0.8932   |
| 0.1135        | 35.0  | 26285 | 0.2867          | 0.8898   |
| 0.0788        | 36.0  | 27036 | 0.2919          | 0.8915   |
| 0.1088        | 37.0  | 27787 | 0.2995          | 0.8948   |
| 0.1103        | 38.0  | 28538 | 0.2942          | 0.8881   |
| 0.1462        | 39.0  | 29289 | 0.2954          | 0.8865   |
| 0.109         | 40.0  | 30040 | 0.2931          | 0.8915   |
| 0.0926        | 41.0  | 30791 | 0.2933          | 0.8898   |
| 0.1358        | 42.0  | 31542 | 0.2937          | 0.8898   |
| 0.0978        | 43.0  | 32293 | 0.2970          | 0.8881   |
| 0.1247        | 44.0  | 33044 | 0.2974          | 0.8898   |
| 0.0996        | 45.0  | 33795 | 0.2953          | 0.8915   |
| 0.0562        | 46.0  | 34546 | 0.2954          | 0.8898   |
| 0.1049        | 47.0  | 35297 | 0.2966          | 0.8898   |
| 0.0913        | 48.0  | 36048 | 0.2967          | 0.8915   |
| 0.1191        | 49.0  | 36799 | 0.2967          | 0.8915   |
| 0.1467        | 50.0  | 37550 | 0.2965          | 0.8915   |


### Framework versions

- Transformers 4.32.1
- Pytorch 2.0.1
- Datasets 2.12.0
- Tokenizers 0.13.2

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["imagefolder"], "metrics": ["accuracy"], "base_model": "microsoft/beit-large-patch16-224", "model-index": [{"name": "SMIDS_5x_beit_large_SGD_lr001_fold1", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imagefolder", "type": "imagefolder", "config": "default", "split": "test", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.8914858096828047, "name": "Accuracy"}]}]}]}
transformers pytorch beit image-classification generated_from_trainer dataset:imagefolder base_model:microsoft/beit-large-patch16-224 license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us