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# HUSHEM_10x_beit_large_SGD_lr001_fold3

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: 0.6324
- Accuracy: 0.6977

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.364         | 1.0   | 109  | 1.3530          | 0.2791   |
| 1.1919        | 2.0   | 218  | 1.2681          | 0.3488   |
| 1.0901        | 3.0   | 327  | 1.1877          | 0.4186   |
| 0.9288        | 4.0   | 436  | 1.1197          | 0.5116   |
| 0.8753        | 5.0   | 545  | 1.0533          | 0.5581   |
| 0.7443        | 6.0   | 654  | 1.0015          | 0.6512   |
| 0.6921        | 7.0   | 763  | 0.9563          | 0.6512   |
| 0.6658        | 8.0   | 872  | 0.9269          | 0.6512   |
| 0.5754        | 9.0   | 981  | 0.8894          | 0.6512   |
| 0.5207        | 10.0  | 1090 | 0.8638          | 0.6279   |
| 0.564         | 11.0  | 1199 | 0.8416          | 0.6512   |
| 0.4201        | 12.0  | 1308 | 0.8166          | 0.6512   |
| 0.4439        | 13.0  | 1417 | 0.7970          | 0.6512   |
| 0.3685        | 14.0  | 1526 | 0.7876          | 0.6744   |
| 0.3555        | 15.0  | 1635 | 0.7655          | 0.6744   |
| 0.3245        | 16.0  | 1744 | 0.7574          | 0.6744   |
| 0.3553        | 17.0  | 1853 | 0.7509          | 0.6744   |
| 0.3126        | 18.0  | 1962 | 0.7246          | 0.6744   |
| 0.3063        | 19.0  | 2071 | 0.7149          | 0.6744   |
| 0.3258        | 20.0  | 2180 | 0.7125          | 0.6744   |
| 0.3275        | 21.0  | 2289 | 0.6916          | 0.6977   |
| 0.2814        | 22.0  | 2398 | 0.6942          | 0.6977   |
| 0.2506        | 23.0  | 2507 | 0.6881          | 0.6977   |
| 0.2579        | 24.0  | 2616 | 0.6865          | 0.6977   |
| 0.2196        | 25.0  | 2725 | 0.6736          | 0.6744   |
| 0.1966        | 26.0  | 2834 | 0.6706          | 0.6977   |
| 0.2302        | 27.0  | 2943 | 0.6664          | 0.6977   |
| 0.1664        | 28.0  | 3052 | 0.6669          | 0.6744   |
| 0.1956        | 29.0  | 3161 | 0.6672          | 0.6977   |
| 0.187         | 30.0  | 3270 | 0.6571          | 0.6744   |
| 0.217         | 31.0  | 3379 | 0.6457          | 0.6744   |
| 0.1944        | 32.0  | 3488 | 0.6553          | 0.7209   |
| 0.1681        | 33.0  | 3597 | 0.6423          | 0.7209   |
| 0.1818        | 34.0  | 3706 | 0.6447          | 0.6977   |
| 0.1922        | 35.0  | 3815 | 0.6394          | 0.7209   |
| 0.1705        | 36.0  | 3924 | 0.6420          | 0.7209   |
| 0.1498        | 37.0  | 4033 | 0.6336          | 0.7209   |
| 0.1419        | 38.0  | 4142 | 0.6374          | 0.7209   |
| 0.1735        | 39.0  | 4251 | 0.6415          | 0.6977   |
| 0.1578        | 40.0  | 4360 | 0.6344          | 0.7209   |
| 0.1449        | 41.0  | 4469 | 0.6377          | 0.6977   |
| 0.1436        | 42.0  | 4578 | 0.6388          | 0.6977   |
| 0.1412        | 43.0  | 4687 | 0.6300          | 0.6977   |
| 0.1248        | 44.0  | 4796 | 0.6328          | 0.6977   |
| 0.1378        | 45.0  | 4905 | 0.6328          | 0.6977   |
| 0.1715        | 46.0  | 5014 | 0.6340          | 0.7209   |
| 0.1499        | 47.0  | 5123 | 0.6304          | 0.6977   |
| 0.1329        | 48.0  | 5232 | 0.6324          | 0.7209   |
| 0.1614        | 49.0  | 5341 | 0.6324          | 0.6977   |
| 0.1315        | 50.0  | 5450 | 0.6324          | 0.6977   |


### 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_10x_beit_large_SGD_lr001_fold3", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imagefolder", "type": "imagefolder", "config": "default", "split": "test", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.6976744186046512, "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