
<!-- 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_10x_beit_large_SGD_lr00001_fold2

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: 1.6742
- Accuracy: 0.1556

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.5335        | 1.0   | 107  | 1.7613          | 0.2      |
| 1.5976        | 2.0   | 214  | 1.7568          | 0.2      |
| 1.6768        | 3.0   | 321  | 1.7523          | 0.1778   |
| 1.5442        | 4.0   | 428  | 1.7482          | 0.1778   |
| 1.5756        | 5.0   | 535  | 1.7441          | 0.1778   |
| 1.5092        | 6.0   | 642  | 1.7403          | 0.1778   |
| 1.5878        | 7.0   | 749  | 1.7365          | 0.1778   |
| 1.561         | 8.0   | 856  | 1.7330          | 0.1778   |
| 1.5091        | 9.0   | 963  | 1.7295          | 0.1778   |
| 1.5618        | 10.0  | 1070 | 1.7263          | 0.1778   |
| 1.5675        | 11.0  | 1177 | 1.7231          | 0.1778   |
| 1.5673        | 12.0  | 1284 | 1.7202          | 0.1556   |
| 1.5794        | 13.0  | 1391 | 1.7174          | 0.1556   |
| 1.5625        | 14.0  | 1498 | 1.7147          | 0.1556   |
| 1.5336        | 15.0  | 1605 | 1.7122          | 0.1556   |
| 1.5409        | 16.0  | 1712 | 1.7096          | 0.1556   |
| 1.4991        | 17.0  | 1819 | 1.7072          | 0.1556   |
| 1.4859        | 18.0  | 1926 | 1.7049          | 0.1556   |
| 1.4606        | 19.0  | 2033 | 1.7028          | 0.1556   |
| 1.5867        | 20.0  | 2140 | 1.7007          | 0.1556   |
| 1.5313        | 21.0  | 2247 | 1.6987          | 0.1556   |
| 1.3984        | 22.0  | 2354 | 1.6968          | 0.1556   |
| 1.5433        | 23.0  | 2461 | 1.6950          | 0.1556   |
| 1.5487        | 24.0  | 2568 | 1.6933          | 0.1556   |
| 1.5388        | 25.0  | 2675 | 1.6917          | 0.1556   |
| 1.5276        | 26.0  | 2782 | 1.6902          | 0.1556   |
| 1.5443        | 27.0  | 2889 | 1.6888          | 0.1556   |
| 1.4485        | 28.0  | 2996 | 1.6874          | 0.1556   |
| 1.5601        | 29.0  | 3103 | 1.6861          | 0.1556   |
| 1.5428        | 30.0  | 3210 | 1.6849          | 0.1556   |
| 1.5097        | 31.0  | 3317 | 1.6837          | 0.1556   |
| 1.5075        | 32.0  | 3424 | 1.6826          | 0.1556   |
| 1.5414        | 33.0  | 3531 | 1.6817          | 0.1556   |
| 1.4659        | 34.0  | 3638 | 1.6807          | 0.1556   |
| 1.4984        | 35.0  | 3745 | 1.6799          | 0.1556   |
| 1.5021        | 36.0  | 3852 | 1.6791          | 0.1556   |
| 1.5221        | 37.0  | 3959 | 1.6784          | 0.1556   |
| 1.5362        | 38.0  | 4066 | 1.6777          | 0.1556   |
| 1.4509        | 39.0  | 4173 | 1.6771          | 0.1556   |
| 1.5009        | 40.0  | 4280 | 1.6765          | 0.1556   |
| 1.4718        | 41.0  | 4387 | 1.6760          | 0.1556   |
| 1.4852        | 42.0  | 4494 | 1.6756          | 0.1556   |
| 1.5051        | 43.0  | 4601 | 1.6752          | 0.1556   |
| 1.4079        | 44.0  | 4708 | 1.6749          | 0.1556   |
| 1.5517        | 45.0  | 4815 | 1.6747          | 0.1556   |
| 1.4555        | 46.0  | 4922 | 1.6745          | 0.1556   |
| 1.4979        | 47.0  | 5029 | 1.6743          | 0.1556   |
| 1.504         | 48.0  | 5136 | 1.6742          | 0.1556   |
| 1.4798        | 49.0  | 5243 | 1.6742          | 0.1556   |
| 1.5104        | 50.0  | 5350 | 1.6742          | 0.1556   |


### 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_10x_beit_large_SGD_lr00001_fold2", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imagefolder", "type": "imagefolder", "config": "default", "split": "test", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.15555555555555556, "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