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# HUSHEM_10x_beit_large_RMSProp_lr0001_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: 2.2920
- Accuracy: 0.8333

## 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: 0.0001
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.3388        | 1.0   | 109  | 1.2863          | 0.2619   |
| 1.0833        | 2.0   | 218  | 0.8220          | 0.6429   |
| 1.0679        | 3.0   | 327  | 0.7227          | 0.7381   |
| 0.8359        | 4.0   | 436  | 0.8348          | 0.6667   |
| 0.8064        | 5.0   | 545  | 0.7231          | 0.7381   |
| 0.5188        | 6.0   | 654  | 1.0551          | 0.6667   |
| 0.4155        | 7.0   | 763  | 1.3638          | 0.6905   |
| 0.3833        | 8.0   | 872  | 0.9005          | 0.7143   |
| 0.2426        | 9.0   | 981  | 1.7145          | 0.5952   |
| 0.2744        | 10.0  | 1090 | 1.1661          | 0.7381   |
| 0.2033        | 11.0  | 1199 | 1.4419          | 0.7857   |
| 0.2153        | 12.0  | 1308 | 0.9525          | 0.7857   |
| 0.0069        | 13.0  | 1417 | 1.2931          | 0.8571   |
| 0.0867        | 14.0  | 1526 | 1.5354          | 0.7857   |
| 0.1158        | 15.0  | 1635 | 1.0696          | 0.7857   |
| 0.1236        | 16.0  | 1744 | 1.7423          | 0.7381   |
| 0.0025        | 17.0  | 1853 | 2.0142          | 0.8095   |
| 0.2334        | 18.0  | 1962 | 1.7761          | 0.7381   |
| 0.1744        | 19.0  | 2071 | 0.9777          | 0.8333   |
| 0.0837        | 20.0  | 2180 | 1.6478          | 0.8095   |
| 0.0211        | 21.0  | 2289 | 1.7295          | 0.7619   |
| 0.0208        | 22.0  | 2398 | 1.3407          | 0.8333   |
| 0.0005        | 23.0  | 2507 | 1.2693          | 0.8333   |
| 0.1748        | 24.0  | 2616 | 1.4965          | 0.8095   |
| 0.0009        | 25.0  | 2725 | 1.7083          | 0.8095   |
| 0.0001        | 26.0  | 2834 | 2.2170          | 0.8095   |
| 0.0           | 27.0  | 2943 | 2.3592          | 0.7381   |
| 0.0442        | 28.0  | 3052 | 1.0155          | 0.8571   |
| 0.0476        | 29.0  | 3161 | 1.3803          | 0.8333   |
| 0.0           | 30.0  | 3270 | 2.1152          | 0.7619   |
| 0.089         | 31.0  | 3379 | 1.6401          | 0.8095   |
| 0.0392        | 32.0  | 3488 | 1.3140          | 0.8333   |
| 0.0001        | 33.0  | 3597 | 1.7063          | 0.7619   |
| 0.0001        | 34.0  | 3706 | 1.3952          | 0.8095   |
| 0.0           | 35.0  | 3815 | 1.8813          | 0.8095   |
| 0.0001        | 36.0  | 3924 | 1.1483          | 0.8571   |
| 0.0           | 37.0  | 4033 | 1.2671          | 0.8333   |
| 0.0002        | 38.0  | 4142 | 2.0348          | 0.7619   |
| 0.0001        | 39.0  | 4251 | 2.2536          | 0.7857   |
| 0.0           | 40.0  | 4360 | 2.2117          | 0.8095   |
| 0.0           | 41.0  | 4469 | 2.2131          | 0.8095   |
| 0.0           | 42.0  | 4578 | 2.4057          | 0.8095   |
| 0.0           | 43.0  | 4687 | 1.5790          | 0.8571   |
| 0.001         | 44.0  | 4796 | 2.4029          | 0.8095   |
| 0.0           | 45.0  | 4905 | 1.5038          | 0.8810   |
| 0.0           | 46.0  | 5014 | 1.5083          | 0.8810   |
| 0.0           | 47.0  | 5123 | 2.2948          | 0.8333   |
| 0.0           | 48.0  | 5232 | 2.2973          | 0.8333   |
| 0.0           | 49.0  | 5341 | 2.2917          | 0.8333   |
| 0.0           | 50.0  | 5450 | 2.2920          | 0.8333   |


### 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_RMSProp_lr0001_fold4", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imagefolder", "type": "imagefolder", "config": "default", "split": "test", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.8333333333333334, "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