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# HUSHEM_10x_beit_large_SGD_lr001_fold4

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: 0.3395
- Accuracy: 0.9048

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.4558        | 1.0   | 109  | 1.3350          | 0.3571   |
| 1.206         | 2.0   | 218  | 1.2030          | 0.5      |
| 1.1306        | 3.0   | 327  | 1.1075          | 0.5714   |
| 0.9826        | 4.0   | 436  | 1.0201          | 0.6429   |
| 0.8985        | 5.0   | 545  | 0.9449          | 0.6190   |
| 0.7741        | 6.0   | 654  | 0.8771          | 0.5952   |
| 0.769         | 7.0   | 763  | 0.8123          | 0.6667   |
| 0.7254        | 8.0   | 872  | 0.7628          | 0.7143   |
| 0.5774        | 9.0   | 981  | 0.7221          | 0.7143   |
| 0.6138        | 10.0  | 1090 | 0.6896          | 0.7143   |
| 0.6037        | 11.0  | 1199 | 0.6528          | 0.7381   |
| 0.5835        | 12.0  | 1308 | 0.6268          | 0.7381   |
| 0.443         | 13.0  | 1417 | 0.5943          | 0.7619   |
| 0.4416        | 14.0  | 1526 | 0.5749          | 0.8095   |
| 0.4025        | 15.0  | 1635 | 0.5551          | 0.8095   |
| 0.3826        | 16.0  | 1744 | 0.5351          | 0.8095   |
| 0.4338        | 17.0  | 1853 | 0.5218          | 0.8095   |
| 0.4005        | 18.0  | 1962 | 0.5005          | 0.8095   |
| 0.3195        | 19.0  | 2071 | 0.4993          | 0.8095   |
| 0.3182        | 20.0  | 2180 | 0.4804          | 0.8095   |
| 0.3148        | 21.0  | 2289 | 0.4676          | 0.8095   |
| 0.2668        | 22.0  | 2398 | 0.4572          | 0.8095   |
| 0.2863        | 23.0  | 2507 | 0.4388          | 0.8095   |
| 0.3694        | 24.0  | 2616 | 0.4330          | 0.8095   |
| 0.2445        | 25.0  | 2725 | 0.4200          | 0.8571   |
| 0.271         | 26.0  | 2834 | 0.4160          | 0.8571   |
| 0.2662        | 27.0  | 2943 | 0.4128          | 0.8571   |
| 0.3064        | 28.0  | 3052 | 0.4030          | 0.8810   |
| 0.262         | 29.0  | 3161 | 0.3962          | 0.8571   |
| 0.2578        | 30.0  | 3270 | 0.3887          | 0.8571   |
| 0.2253        | 31.0  | 3379 | 0.3836          | 0.8810   |
| 0.2312        | 32.0  | 3488 | 0.3808          | 0.8810   |
| 0.1802        | 33.0  | 3597 | 0.3735          | 0.8810   |
| 0.2202        | 34.0  | 3706 | 0.3632          | 0.8810   |
| 0.2073        | 35.0  | 3815 | 0.3631          | 0.8810   |
| 0.2113        | 36.0  | 3924 | 0.3635          | 0.8810   |
| 0.162         | 37.0  | 4033 | 0.3606          | 0.8810   |
| 0.18          | 38.0  | 4142 | 0.3565          | 0.8810   |
| 0.1669        | 39.0  | 4251 | 0.3546          | 0.8810   |
| 0.1951        | 40.0  | 4360 | 0.3509          | 0.8810   |
| 0.1696        | 41.0  | 4469 | 0.3496          | 0.8810   |
| 0.1633        | 42.0  | 4578 | 0.3467          | 0.8810   |
| 0.2038        | 43.0  | 4687 | 0.3431          | 0.8810   |
| 0.226         | 44.0  | 4796 | 0.3440          | 0.8810   |
| 0.1977        | 45.0  | 4905 | 0.3409          | 0.9048   |
| 0.1976        | 46.0  | 5014 | 0.3419          | 0.8810   |
| 0.1797        | 47.0  | 5123 | 0.3394          | 0.8810   |
| 0.191         | 48.0  | 5232 | 0.3395          | 0.9048   |
| 0.1417        | 49.0  | 5341 | 0.3396          | 0.9048   |
| 0.1916        | 50.0  | 5450 | 0.3395          | 0.9048   |


### 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_fold4", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imagefolder", "type": "imagefolder", "config": "default", "split": "test", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.9047619047619048, "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