
<!-- 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_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: 1.4656
- Accuracy: 0.2558

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.6863        | 1.0   | 11   | 1.5829          | 0.3023   |
| 1.6191        | 2.0   | 22   | 1.5759          | 0.3023   |
| 1.6316        | 3.0   | 33   | 1.5687          | 0.3023   |
| 1.6421        | 4.0   | 44   | 1.5621          | 0.2791   |
| 1.6592        | 5.0   | 55   | 1.5558          | 0.2791   |
| 1.5762        | 6.0   | 66   | 1.5499          | 0.2791   |
| 1.6467        | 7.0   | 77   | 1.5440          | 0.2791   |
| 1.5722        | 8.0   | 88   | 1.5391          | 0.2791   |
| 1.5895        | 9.0   | 99   | 1.5344          | 0.2558   |
| 1.6239        | 10.0  | 110  | 1.5297          | 0.2558   |
| 1.5604        | 11.0  | 121  | 1.5257          | 0.2558   |
| 1.5738        | 12.0  | 132  | 1.5218          | 0.2558   |
| 1.5483        | 13.0  | 143  | 1.5178          | 0.2558   |
| 1.5985        | 14.0  | 154  | 1.5142          | 0.2558   |
| 1.548         | 15.0  | 165  | 1.5107          | 0.2326   |
| 1.5074        | 16.0  | 176  | 1.5071          | 0.2326   |
| 1.5842        | 17.0  | 187  | 1.5041          | 0.2326   |
| 1.5858        | 18.0  | 198  | 1.5009          | 0.2326   |
| 1.5614        | 19.0  | 209  | 1.4981          | 0.2558   |
| 1.5688        | 20.0  | 220  | 1.4952          | 0.2558   |
| 1.5443        | 21.0  | 231  | 1.4925          | 0.2558   |
| 1.5147        | 22.0  | 242  | 1.4902          | 0.2558   |
| 1.5553        | 23.0  | 253  | 1.4880          | 0.2558   |
| 1.4997        | 24.0  | 264  | 1.4860          | 0.2558   |
| 1.5291        | 25.0  | 275  | 1.4839          | 0.2558   |
| 1.513         | 26.0  | 286  | 1.4822          | 0.2558   |
| 1.5818        | 27.0  | 297  | 1.4802          | 0.2558   |
| 1.5041        | 28.0  | 308  | 1.4786          | 0.2558   |
| 1.5684        | 29.0  | 319  | 1.4771          | 0.2558   |
| 1.5537        | 30.0  | 330  | 1.4757          | 0.2558   |
| 1.4895        | 31.0  | 341  | 1.4744          | 0.2558   |
| 1.5012        | 32.0  | 352  | 1.4731          | 0.2558   |
| 1.5433        | 33.0  | 363  | 1.4720          | 0.2558   |
| 1.4855        | 34.0  | 374  | 1.4709          | 0.2558   |
| 1.5292        | 35.0  | 385  | 1.4700          | 0.2558   |
| 1.4888        | 36.0  | 396  | 1.4692          | 0.2558   |
| 1.5036        | 37.0  | 407  | 1.4684          | 0.2558   |
| 1.5015        | 38.0  | 418  | 1.4678          | 0.2558   |
| 1.5265        | 39.0  | 429  | 1.4672          | 0.2558   |
| 1.5072        | 40.0  | 440  | 1.4667          | 0.2558   |
| 1.512         | 41.0  | 451  | 1.4664          | 0.2558   |
| 1.4889        | 42.0  | 462  | 1.4660          | 0.2558   |
| 1.59          | 43.0  | 473  | 1.4658          | 0.2558   |
| 1.4951        | 44.0  | 484  | 1.4657          | 0.2558   |
| 1.485         | 45.0  | 495  | 1.4656          | 0.2558   |
| 1.535         | 46.0  | 506  | 1.4656          | 0.2558   |
| 1.4909        | 47.0  | 517  | 1.4656          | 0.2558   |
| 1.4993        | 48.0  | 528  | 1.4656          | 0.2558   |
| 1.4774        | 49.0  | 539  | 1.4656          | 0.2558   |
| 1.4609        | 50.0  | 550  | 1.4656          | 0.2558   |


### 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_fold3", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imagefolder", "type": "imagefolder", "config": "default", "split": "test", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.2558139534883721, "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