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# HUSHEM_1x_beit_large_Adamax_lr0001_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: 1.6896
- Accuracy: 0.7674

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.7295        | 1.0   | 11   | 1.3664          | 0.3488   |
| 1.116         | 2.0   | 22   | 0.6142          | 0.7674   |
| 0.4105        | 3.0   | 33   | 0.7281          | 0.8140   |
| 0.1348        | 4.0   | 44   | 1.2640          | 0.6977   |
| 0.193         | 5.0   | 55   | 1.2069          | 0.8140   |
| 0.0414        | 6.0   | 66   | 0.9795          | 0.8140   |
| 0.1263        | 7.0   | 77   | 1.3945          | 0.8140   |
| 0.0376        | 8.0   | 88   | 1.5328          | 0.7674   |
| 0.0036        | 9.0   | 99   | 1.8660          | 0.7442   |
| 0.0002        | 10.0  | 110  | 1.8591          | 0.7442   |
| 0.0001        | 11.0  | 121  | 1.9239          | 0.7209   |
| 0.0007        | 12.0  | 132  | 1.9526          | 0.7907   |
| 0.0001        | 13.0  | 143  | 2.0012          | 0.7907   |
| 0.0003        | 14.0  | 154  | 1.8719          | 0.7209   |
| 0.0332        | 15.0  | 165  | 1.6664          | 0.7674   |
| 0.0004        | 16.0  | 176  | 1.6151          | 0.8140   |
| 0.0           | 17.0  | 187  | 1.6196          | 0.8140   |
| 0.0           | 18.0  | 198  | 1.6259          | 0.8140   |
| 0.0           | 19.0  | 209  | 1.6239          | 0.7674   |
| 0.0           | 20.0  | 220  | 1.6401          | 0.7907   |
| 0.0           | 21.0  | 231  | 1.6505          | 0.7907   |
| 0.0           | 22.0  | 242  | 1.6540          | 0.7907   |
| 0.0           | 23.0  | 253  | 1.6595          | 0.7907   |
| 0.0           | 24.0  | 264  | 1.6629          | 0.7907   |
| 0.0           | 25.0  | 275  | 1.6653          | 0.7907   |
| 0.0           | 26.0  | 286  | 1.6712          | 0.7674   |
| 0.0           | 27.0  | 297  | 1.6786          | 0.7674   |
| 0.0           | 28.0  | 308  | 1.6825          | 0.7674   |
| 0.0           | 29.0  | 319  | 1.6853          | 0.7674   |
| 0.0           | 30.0  | 330  | 1.6851          | 0.7674   |
| 0.0           | 31.0  | 341  | 1.6854          | 0.7674   |
| 0.0           | 32.0  | 352  | 1.6860          | 0.7674   |
| 0.0001        | 33.0  | 363  | 1.6849          | 0.7674   |
| 0.0           | 34.0  | 374  | 1.6840          | 0.7674   |
| 0.0           | 35.0  | 385  | 1.6855          | 0.7674   |
| 0.0           | 36.0  | 396  | 1.6869          | 0.7674   |
| 0.0           | 37.0  | 407  | 1.6877          | 0.7674   |
| 0.0           | 38.0  | 418  | 1.6883          | 0.7674   |
| 0.0           | 39.0  | 429  | 1.6888          | 0.7674   |
| 0.0           | 40.0  | 440  | 1.6894          | 0.7674   |
| 0.0           | 41.0  | 451  | 1.6896          | 0.7674   |
| 0.0           | 42.0  | 462  | 1.6896          | 0.7674   |
| 0.0           | 43.0  | 473  | 1.6895          | 0.7674   |
| 0.0           | 44.0  | 484  | 1.6896          | 0.7674   |
| 0.0           | 45.0  | 495  | 1.6896          | 0.7674   |
| 0.0           | 46.0  | 506  | 1.6896          | 0.7674   |
| 0.0           | 47.0  | 517  | 1.6896          | 0.7674   |
| 0.0           | 48.0  | 528  | 1.6896          | 0.7674   |
| 0.0           | 49.0  | 539  | 1.6896          | 0.7674   |
| 0.0           | 50.0  | 550  | 1.6896          | 0.7674   |


### 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_Adamax_lr0001_fold3", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imagefolder", "type": "imagefolder", "config": "default", "split": "test", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.7674418604651163, "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