
<!-- 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_lr00001_fold5

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: 1.5551
- Accuracy: 0.2439

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.7127        | 1.0   | 11   | 1.5714          | 0.2439   |
| 1.6322        | 2.0   | 22   | 1.5706          | 0.2439   |
| 1.6452        | 3.0   | 33   | 1.5698          | 0.2439   |
| 1.6617        | 4.0   | 44   | 1.5691          | 0.2439   |
| 1.6609        | 5.0   | 55   | 1.5684          | 0.2439   |
| 1.6344        | 6.0   | 66   | 1.5677          | 0.2439   |
| 1.6139        | 7.0   | 77   | 1.5671          | 0.2439   |
| 1.6692        | 8.0   | 88   | 1.5664          | 0.2439   |
| 1.6783        | 9.0   | 99   | 1.5658          | 0.2439   |
| 1.6508        | 10.0  | 110  | 1.5652          | 0.2439   |
| 1.6741        | 11.0  | 121  | 1.5646          | 0.2439   |
| 1.7016        | 12.0  | 132  | 1.5640          | 0.2439   |
| 1.5991        | 13.0  | 143  | 1.5635          | 0.2439   |
| 1.7082        | 14.0  | 154  | 1.5629          | 0.2439   |
| 1.5776        | 15.0  | 165  | 1.5624          | 0.2439   |
| 1.7384        | 16.0  | 176  | 1.5619          | 0.2439   |
| 1.5435        | 17.0  | 187  | 1.5615          | 0.2439   |
| 1.6689        | 18.0  | 198  | 1.5610          | 0.2439   |
| 1.6596        | 19.0  | 209  | 1.5606          | 0.2439   |
| 1.6819        | 20.0  | 220  | 1.5601          | 0.2439   |
| 1.6484        | 21.0  | 231  | 1.5597          | 0.2439   |
| 1.6503        | 22.0  | 242  | 1.5593          | 0.2439   |
| 1.6087        | 23.0  | 253  | 1.5590          | 0.2439   |
| 1.6626        | 24.0  | 264  | 1.5586          | 0.2439   |
| 1.6794        | 25.0  | 275  | 1.5583          | 0.2439   |
| 1.5213        | 26.0  | 286  | 1.5579          | 0.2439   |
| 1.6061        | 27.0  | 297  | 1.5576          | 0.2439   |
| 1.619         | 28.0  | 308  | 1.5573          | 0.2439   |
| 1.6938        | 29.0  | 319  | 1.5571          | 0.2439   |
| 1.6219        | 30.0  | 330  | 1.5569          | 0.2439   |
| 1.6491        | 31.0  | 341  | 1.5566          | 0.2439   |
| 1.6425        | 32.0  | 352  | 1.5564          | 0.2439   |
| 1.6915        | 33.0  | 363  | 1.5562          | 0.2439   |
| 1.6345        | 34.0  | 374  | 1.5561          | 0.2439   |
| 1.6462        | 35.0  | 385  | 1.5559          | 0.2439   |
| 1.6513        | 36.0  | 396  | 1.5558          | 0.2439   |
| 1.6228        | 37.0  | 407  | 1.5556          | 0.2439   |
| 1.6323        | 38.0  | 418  | 1.5555          | 0.2439   |
| 1.6619        | 39.0  | 429  | 1.5554          | 0.2439   |
| 1.6667        | 40.0  | 440  | 1.5553          | 0.2439   |
| 1.6175        | 41.0  | 451  | 1.5553          | 0.2439   |
| 1.5913        | 42.0  | 462  | 1.5552          | 0.2439   |
| 1.7152        | 43.0  | 473  | 1.5552          | 0.2439   |
| 1.5788        | 44.0  | 484  | 1.5551          | 0.2439   |
| 1.6511        | 45.0  | 495  | 1.5551          | 0.2439   |
| 1.5972        | 46.0  | 506  | 1.5551          | 0.2439   |
| 1.7235        | 47.0  | 517  | 1.5551          | 0.2439   |
| 1.6694        | 48.0  | 528  | 1.5551          | 0.2439   |
| 1.6588        | 49.0  | 539  | 1.5551          | 0.2439   |
| 1.6231        | 50.0  | 550  | 1.5551          | 0.2439   |


### 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_lr00001_fold5", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imagefolder", "type": "imagefolder", "config": "default", "split": "test", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.24390243902439024, "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