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# HUSHEM_5x_beit_large_SGD_lr001_fold5

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: 0.4737
- Accuracy: 0.9024

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.3901        | 1.0   | 55   | 1.3883          | 0.2683   |
| 1.3884        | 2.0   | 110  | 1.2841          | 0.3902   |
| 1.3634        | 3.0   | 165  | 1.2116          | 0.4146   |
| 1.2504        | 4.0   | 220  | 1.1577          | 0.5122   |
| 1.1529        | 5.0   | 275  | 1.1107          | 0.5122   |
| 1.1138        | 6.0   | 330  | 1.0581          | 0.5610   |
| 1.0255        | 7.0   | 385  | 1.0219          | 0.6098   |
| 0.9487        | 8.0   | 440  | 0.9699          | 0.6098   |
| 0.9747        | 9.0   | 495  | 0.9324          | 0.6341   |
| 0.9476        | 10.0  | 550  | 0.9023          | 0.7317   |
| 0.8672        | 11.0  | 605  | 0.8717          | 0.7317   |
| 0.8908        | 12.0  | 660  | 0.8373          | 0.7561   |
| 0.8486        | 13.0  | 715  | 0.8052          | 0.7805   |
| 0.7269        | 14.0  | 770  | 0.7923          | 0.8049   |
| 0.7006        | 15.0  | 825  | 0.7583          | 0.7805   |
| 0.6755        | 16.0  | 880  | 0.7364          | 0.7805   |
| 0.6968        | 17.0  | 935  | 0.7184          | 0.8049   |
| 0.6567        | 18.0  | 990  | 0.6986          | 0.8049   |
| 0.6297        | 19.0  | 1045 | 0.6853          | 0.8049   |
| 0.6472        | 20.0  | 1100 | 0.6692          | 0.8049   |
| 0.5398        | 21.0  | 1155 | 0.6519          | 0.8049   |
| 0.5955        | 22.0  | 1210 | 0.6302          | 0.8293   |
| 0.5932        | 23.0  | 1265 | 0.6100          | 0.8293   |
| 0.5275        | 24.0  | 1320 | 0.5961          | 0.8293   |
| 0.5136        | 25.0  | 1375 | 0.5843          | 0.8293   |
| 0.5449        | 26.0  | 1430 | 0.5764          | 0.8537   |
| 0.5337        | 27.0  | 1485 | 0.5626          | 0.8293   |
| 0.514         | 28.0  | 1540 | 0.5600          | 0.8537   |
| 0.4772        | 29.0  | 1595 | 0.5420          | 0.8537   |
| 0.4808        | 30.0  | 1650 | 0.5390          | 0.8537   |
| 0.4634        | 31.0  | 1705 | 0.5277          | 0.8780   |
| 0.4411        | 32.0  | 1760 | 0.5210          | 0.9024   |
| 0.477         | 33.0  | 1815 | 0.5132          | 0.9024   |
| 0.398         | 34.0  | 1870 | 0.5086          | 0.9024   |
| 0.457         | 35.0  | 1925 | 0.5077          | 0.9024   |
| 0.4661        | 36.0  | 1980 | 0.5000          | 0.9024   |
| 0.3881        | 37.0  | 2035 | 0.4947          | 0.9024   |
| 0.4311        | 38.0  | 2090 | 0.4920          | 0.9024   |
| 0.4502        | 39.0  | 2145 | 0.4886          | 0.9024   |
| 0.3796        | 40.0  | 2200 | 0.4835          | 0.9024   |
| 0.3919        | 41.0  | 2255 | 0.4843          | 0.9024   |
| 0.4037        | 42.0  | 2310 | 0.4815          | 0.9024   |
| 0.4395        | 43.0  | 2365 | 0.4802          | 0.9024   |
| 0.3966        | 44.0  | 2420 | 0.4777          | 0.9024   |
| 0.4411        | 45.0  | 2475 | 0.4765          | 0.9024   |
| 0.3979        | 46.0  | 2530 | 0.4746          | 0.9024   |
| 0.3931        | 47.0  | 2585 | 0.4744          | 0.9024   |
| 0.3744        | 48.0  | 2640 | 0.4740          | 0.9024   |
| 0.3868        | 49.0  | 2695 | 0.4737          | 0.9024   |
| 0.4004        | 50.0  | 2750 | 0.4737          | 0.9024   |


### 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": "HUSHEM_5x_beit_large_SGD_lr001_fold5", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imagefolder", "type": "imagefolder", "config": "default", "split": "test", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.9024390243902439, "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