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# HUSHEM_1x_beit_large_RMSProp_lr00001_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: 0.6127
- Accuracy: 0.6905

## 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: 1e-05
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.7383        | 1.0   | 11   | 1.4091          | 0.2381   |
| 1.4116        | 2.0   | 22   | 1.3846          | 0.2381   |
| 1.4102        | 3.0   | 33   | 1.2081          | 0.5238   |
| 1.3609        | 4.0   | 44   | 1.3316          | 0.4286   |
| 1.3686        | 5.0   | 55   | 1.2851          | 0.4524   |
| 1.3564        | 6.0   | 66   | 1.1419          | 0.5238   |
| 1.3546        | 7.0   | 77   | 1.2633          | 0.5238   |
| 1.3617        | 8.0   | 88   | 1.1545          | 0.5      |
| 1.324         | 9.0   | 99   | 1.1465          | 0.4762   |
| 1.3102        | 10.0  | 110  | 1.5970          | 0.2619   |
| 1.3512        | 11.0  | 121  | 1.1717          | 0.5      |
| 1.2764        | 12.0  | 132  | 1.1867          | 0.4524   |
| 1.316         | 13.0  | 143  | 1.2553          | 0.4524   |
| 1.3369        | 14.0  | 154  | 1.1525          | 0.5238   |
| 1.2641        | 15.0  | 165  | 1.1300          | 0.5238   |
| 1.3291        | 16.0  | 176  | 1.1789          | 0.5      |
| 1.2815        | 17.0  | 187  | 1.0369          | 0.5238   |
| 1.3064        | 18.0  | 198  | 1.0924          | 0.5238   |
| 1.1685        | 19.0  | 209  | 1.0341          | 0.5238   |
| 0.8424        | 20.0  | 220  | 1.1940          | 0.4286   |
| 0.7261        | 21.0  | 231  | 0.9459          | 0.5238   |
| 0.481         | 22.0  | 242  | 0.9950          | 0.5      |
| 0.5755        | 23.0  | 253  | 0.9994          | 0.5      |
| 0.462         | 24.0  | 264  | 0.9657          | 0.4762   |
| 0.575         | 25.0  | 275  | 0.9198          | 0.6429   |
| 0.3905        | 26.0  | 286  | 0.8985          | 0.6429   |
| 0.5075        | 27.0  | 297  | 0.8166          | 0.6429   |
| 0.4812        | 28.0  | 308  | 0.8200          | 0.6667   |
| 0.4689        | 29.0  | 319  | 0.8387          | 0.5714   |
| 0.4355        | 30.0  | 330  | 0.8353          | 0.6190   |
| 0.3332        | 31.0  | 341  | 0.6817          | 0.6905   |
| 0.3144        | 32.0  | 352  | 0.7345          | 0.6667   |
| 0.3384        | 33.0  | 363  | 0.8072          | 0.6190   |
| 0.3293        | 34.0  | 374  | 0.8046          | 0.6190   |
| 0.4091        | 35.0  | 385  | 0.7940          | 0.6429   |
| 0.3938        | 36.0  | 396  | 0.7652          | 0.6667   |
| 0.2693        | 37.0  | 407  | 0.7576          | 0.6190   |
| 0.3003        | 38.0  | 418  | 0.6501          | 0.6190   |
| 0.2584        | 39.0  | 429  | 0.7222          | 0.6429   |
| 0.2705        | 40.0  | 440  | 0.7091          | 0.6667   |
| 0.2735        | 41.0  | 451  | 0.6626          | 0.6429   |
| 0.2225        | 42.0  | 462  | 0.5892          | 0.6905   |
| 0.1729        | 43.0  | 473  | 0.6641          | 0.6667   |
| 0.1817        | 44.0  | 484  | 0.6556          | 0.6667   |
| 0.1941        | 45.0  | 495  | 0.6141          | 0.6905   |
| 0.2017        | 46.0  | 506  | 0.6127          | 0.6905   |
| 0.2164        | 47.0  | 517  | 0.6127          | 0.6905   |
| 0.2131        | 48.0  | 528  | 0.6127          | 0.6905   |
| 0.2223        | 49.0  | 539  | 0.6127          | 0.6905   |
| 0.2028        | 50.0  | 550  | 0.6127          | 0.6905   |


### 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_1x_beit_large_RMSProp_lr00001_fold4", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imagefolder", "type": "imagefolder", "config": "default", "split": "test", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.6904761904761905, "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