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# HUSHEM_10x_beit_large_RMSProp_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: 2.7596
- Accuracy: 0.7619

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.4042        | 1.0   | 109  | 1.3848          | 0.2381   |
| 1.4118        | 2.0   | 218  | 1.3707          | 0.2619   |
| 1.371         | 3.0   | 327  | 1.3252          | 0.2381   |
| 1.457         | 4.0   | 436  | 1.6554          | 0.2619   |
| 1.3486        | 5.0   | 545  | 1.1992          | 0.4762   |
| 1.2624        | 6.0   | 654  | 1.1614          | 0.5238   |
| 1.261         | 7.0   | 763  | 1.1633          | 0.5      |
| 1.2952        | 8.0   | 872  | 1.0657          | 0.5238   |
| 1.1942        | 9.0   | 981  | 1.0491          | 0.5      |
| 1.199         | 10.0  | 1090 | 1.2301          | 0.3571   |
| 1.0832        | 11.0  | 1199 | 1.1574          | 0.5476   |
| 0.9867        | 12.0  | 1308 | 0.7554          | 0.6429   |
| 0.937         | 13.0  | 1417 | 0.6453          | 0.8095   |
| 0.8484        | 14.0  | 1526 | 0.6454          | 0.7381   |
| 0.8352        | 15.0  | 1635 | 0.6015          | 0.6905   |
| 0.7567        | 16.0  | 1744 | 0.6640          | 0.7143   |
| 0.7857        | 17.0  | 1853 | 0.6827          | 0.7857   |
| 0.7605        | 18.0  | 1962 | 0.4868          | 0.8095   |
| 0.7037        | 19.0  | 2071 | 0.6177          | 0.7381   |
| 0.6067        | 20.0  | 2180 | 0.6134          | 0.7857   |
| 0.7517        | 21.0  | 2289 | 0.9127          | 0.6905   |
| 0.6569        | 22.0  | 2398 | 0.5475          | 0.8333   |
| 0.701         | 23.0  | 2507 | 0.5585          | 0.7619   |
| 0.6677        | 24.0  | 2616 | 0.6431          | 0.7619   |
| 0.6129        | 25.0  | 2725 | 0.8544          | 0.6667   |
| 0.6598        | 26.0  | 2834 | 0.7492          | 0.6905   |
| 0.6615        | 27.0  | 2943 | 0.9682          | 0.6905   |
| 0.5054        | 28.0  | 3052 | 0.9115          | 0.6667   |
| 0.5009        | 29.0  | 3161 | 0.7625          | 0.6905   |
| 0.5254        | 30.0  | 3270 | 1.6477          | 0.6190   |
| 0.4347        | 31.0  | 3379 | 1.0298          | 0.7143   |
| 0.3933        | 32.0  | 3488 | 0.9927          | 0.6667   |
| 0.3087        | 33.0  | 3597 | 0.9865          | 0.6905   |
| 0.3867        | 34.0  | 3706 | 1.3599          | 0.6905   |
| 0.298         | 35.0  | 3815 | 1.4037          | 0.6905   |
| 0.2567        | 36.0  | 3924 | 1.7195          | 0.6905   |
| 0.2544        | 37.0  | 4033 | 1.6400          | 0.7381   |
| 0.1392        | 38.0  | 4142 | 1.3507          | 0.7381   |
| 0.1298        | 39.0  | 4251 | 1.1614          | 0.7143   |
| 0.1497        | 40.0  | 4360 | 1.3832          | 0.6905   |
| 0.0891        | 41.0  | 4469 | 1.5909          | 0.6667   |
| 0.044         | 42.0  | 4578 | 1.8652          | 0.7381   |
| 0.0112        | 43.0  | 4687 | 2.4126          | 0.7143   |
| 0.0515        | 44.0  | 4796 | 3.0261          | 0.7143   |
| 0.0777        | 45.0  | 4905 | 2.2572          | 0.7619   |
| 0.0595        | 46.0  | 5014 | 2.8651          | 0.7619   |
| 0.0034        | 47.0  | 5123 | 2.9631          | 0.7619   |
| 0.0268        | 48.0  | 5232 | 2.6681          | 0.7619   |
| 0.0039        | 49.0  | 5341 | 2.6822          | 0.7619   |
| 0.0073        | 50.0  | 5450 | 2.7596          | 0.7619   |


### 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_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": 0.7619047619047619, "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