
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# HUSHEM_1x_beit_large_SGD_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: 1.4504
- Accuracy: 0.3333

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.6414        | 1.0   | 11   | 1.5847          | 0.3095   |
| 1.6684        | 2.0   | 22   | 1.5769          | 0.3095   |
| 1.6058        | 3.0   | 33   | 1.5689          | 0.3095   |
| 1.5983        | 4.0   | 44   | 1.5613          | 0.3333   |
| 1.6974        | 5.0   | 55   | 1.5541          | 0.3333   |
| 1.5678        | 6.0   | 66   | 1.5479          | 0.3333   |
| 1.6357        | 7.0   | 77   | 1.5417          | 0.3333   |
| 1.5418        | 8.0   | 88   | 1.5359          | 0.3333   |
| 1.5943        | 9.0   | 99   | 1.5303          | 0.3333   |
| 1.5799        | 10.0  | 110  | 1.5253          | 0.3333   |
| 1.5745        | 11.0  | 121  | 1.5204          | 0.3333   |
| 1.5657        | 12.0  | 132  | 1.5158          | 0.3333   |
| 1.5769        | 13.0  | 143  | 1.5111          | 0.3571   |
| 1.5309        | 14.0  | 154  | 1.5067          | 0.3571   |
| 1.6115        | 15.0  | 165  | 1.5026          | 0.3571   |
| 1.5315        | 16.0  | 176  | 1.4987          | 0.3571   |
| 1.5497        | 17.0  | 187  | 1.4950          | 0.3571   |
| 1.5772        | 18.0  | 198  | 1.4916          | 0.3571   |
| 1.553         | 19.0  | 209  | 1.4884          | 0.3571   |
| 1.5355        | 20.0  | 220  | 1.4853          | 0.3571   |
| 1.5412        | 21.0  | 231  | 1.4823          | 0.3571   |
| 1.5272        | 22.0  | 242  | 1.4795          | 0.3571   |
| 1.5441        | 23.0  | 253  | 1.4768          | 0.3571   |
| 1.5818        | 24.0  | 264  | 1.4744          | 0.3571   |
| 1.5487        | 25.0  | 275  | 1.4718          | 0.3571   |
| 1.5485        | 26.0  | 286  | 1.4697          | 0.3571   |
| 1.4984        | 27.0  | 297  | 1.4676          | 0.3333   |
| 1.5634        | 28.0  | 308  | 1.4656          | 0.3333   |
| 1.476         | 29.0  | 319  | 1.4638          | 0.3333   |
| 1.5111        | 30.0  | 330  | 1.4623          | 0.3333   |
| 1.5183        | 31.0  | 341  | 1.4608          | 0.3333   |
| 1.5105        | 32.0  | 352  | 1.4594          | 0.3333   |
| 1.5315        | 33.0  | 363  | 1.4580          | 0.3333   |
| 1.5179        | 34.0  | 374  | 1.4568          | 0.3333   |
| 1.582         | 35.0  | 385  | 1.4557          | 0.3333   |
| 1.486         | 36.0  | 396  | 1.4547          | 0.3333   |
| 1.512         | 37.0  | 407  | 1.4538          | 0.3333   |
| 1.4904        | 38.0  | 418  | 1.4530          | 0.3333   |
| 1.5636        | 39.0  | 429  | 1.4523          | 0.3333   |
| 1.5095        | 40.0  | 440  | 1.4518          | 0.3333   |
| 1.4972        | 41.0  | 451  | 1.4513          | 0.3333   |
| 1.5075        | 42.0  | 462  | 1.4510          | 0.3333   |
| 1.5           | 43.0  | 473  | 1.4507          | 0.3333   |
| 1.5544        | 44.0  | 484  | 1.4505          | 0.3333   |
| 1.5083        | 45.0  | 495  | 1.4504          | 0.3333   |
| 1.5335        | 46.0  | 506  | 1.4504          | 0.3333   |
| 1.4688        | 47.0  | 517  | 1.4504          | 0.3333   |
| 1.5395        | 48.0  | 528  | 1.4504          | 0.3333   |
| 1.5049        | 49.0  | 539  | 1.4504          | 0.3333   |
| 1.5116        | 50.0  | 550  | 1.4504          | 0.3333   |


### 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_SGD_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": 0.3333333333333333, "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