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# HUSHEM_1x_beit_large_SGD_lr00001_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: 1.5742
- Accuracy: 0.3023

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.6883        | 1.0   | 11   | 1.5890          | 0.3023   |
| 1.628         | 2.0   | 22   | 1.5883          | 0.3023   |
| 1.6463        | 3.0   | 33   | 1.5876          | 0.3023   |
| 1.6639        | 4.0   | 44   | 1.5869          | 0.3023   |
| 1.6934        | 5.0   | 55   | 1.5863          | 0.3023   |
| 1.6098        | 6.0   | 66   | 1.5856          | 0.3023   |
| 1.6904        | 7.0   | 77   | 1.5850          | 0.3023   |
| 1.6111        | 8.0   | 88   | 1.5844          | 0.3023   |
| 1.6445        | 9.0   | 99   | 1.5839          | 0.3023   |
| 1.689         | 10.0  | 110  | 1.5833          | 0.3023   |
| 1.6272        | 11.0  | 121  | 1.5828          | 0.3023   |
| 1.6441        | 12.0  | 132  | 1.5823          | 0.3023   |
| 1.6169        | 13.0  | 143  | 1.5818          | 0.3023   |
| 1.68          | 14.0  | 154  | 1.5813          | 0.3023   |
| 1.6294        | 15.0  | 165  | 1.5809          | 0.3023   |
| 1.5846        | 16.0  | 176  | 1.5804          | 0.3023   |
| 1.6788        | 17.0  | 187  | 1.5800          | 0.3023   |
| 1.6886        | 18.0  | 198  | 1.5795          | 0.3023   |
| 1.6523        | 19.0  | 209  | 1.5791          | 0.3023   |
| 1.6738        | 20.0  | 220  | 1.5787          | 0.3023   |
| 1.647         | 21.0  | 231  | 1.5784          | 0.3023   |
| 1.6215        | 22.0  | 242  | 1.5780          | 0.3023   |
| 1.6566        | 23.0  | 253  | 1.5777          | 0.3023   |
| 1.6129        | 24.0  | 264  | 1.5774          | 0.3023   |
| 1.6384        | 25.0  | 275  | 1.5771          | 0.3023   |
| 1.6385        | 26.0  | 286  | 1.5768          | 0.3023   |
| 1.6962        | 27.0  | 297  | 1.5765          | 0.3023   |
| 1.6346        | 28.0  | 308  | 1.5762          | 0.3023   |
| 1.6725        | 29.0  | 319  | 1.5760          | 0.3023   |
| 1.6792        | 30.0  | 330  | 1.5758          | 0.3023   |
| 1.6063        | 31.0  | 341  | 1.5756          | 0.3023   |
| 1.6312        | 32.0  | 352  | 1.5754          | 0.3023   |
| 1.6773        | 33.0  | 363  | 1.5752          | 0.3023   |
| 1.6081        | 34.0  | 374  | 1.5751          | 0.3023   |
| 1.6664        | 35.0  | 385  | 1.5749          | 0.3023   |
| 1.6255        | 36.0  | 396  | 1.5748          | 0.3023   |
| 1.6332        | 37.0  | 407  | 1.5747          | 0.3023   |
| 1.6239        | 38.0  | 418  | 1.5746          | 0.3023   |
| 1.6672        | 39.0  | 429  | 1.5745          | 0.3023   |
| 1.6435        | 40.0  | 440  | 1.5744          | 0.3023   |
| 1.6443        | 41.0  | 451  | 1.5743          | 0.3023   |
| 1.6136        | 42.0  | 462  | 1.5743          | 0.3023   |
| 1.7411        | 43.0  | 473  | 1.5743          | 0.3023   |
| 1.6364        | 44.0  | 484  | 1.5742          | 0.3023   |
| 1.6292        | 45.0  | 495  | 1.5742          | 0.3023   |
| 1.6549        | 46.0  | 506  | 1.5742          | 0.3023   |
| 1.6324        | 47.0  | 517  | 1.5742          | 0.3023   |
| 1.6327        | 48.0  | 528  | 1.5742          | 0.3023   |
| 1.6072        | 49.0  | 539  | 1.5742          | 0.3023   |
| 1.5906        | 50.0  | 550  | 1.5742          | 0.3023   |


### 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_fold3", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imagefolder", "type": "imagefolder", "config": "default", "split": "test", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.3023255813953488, "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