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# HUSHEM_1x_beit_large_SGD_lr00001_fold1

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: 1.7491
- Accuracy: 0.2889

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.8651        | 1.0   | 11   | 1.7709          | 0.2889   |
| 1.8997        | 2.0   | 22   | 1.7699          | 0.2889   |
| 1.9212        | 3.0   | 33   | 1.7689          | 0.2889   |
| 1.8552        | 4.0   | 44   | 1.7679          | 0.2889   |
| 1.8974        | 5.0   | 55   | 1.7669          | 0.2889   |
| 1.8808        | 6.0   | 66   | 1.7660          | 0.2889   |
| 1.8455        | 7.0   | 77   | 1.7651          | 0.2889   |
| 1.7855        | 8.0   | 88   | 1.7643          | 0.2889   |
| 1.9075        | 9.0   | 99   | 1.7634          | 0.2889   |
| 1.846         | 10.0  | 110  | 1.7626          | 0.2889   |
| 1.8487        | 11.0  | 121  | 1.7618          | 0.2889   |
| 1.9176        | 12.0  | 132  | 1.7611          | 0.2889   |
| 1.8518        | 13.0  | 143  | 1.7603          | 0.2889   |
| 1.8971        | 14.0  | 154  | 1.7596          | 0.2889   |
| 1.8597        | 15.0  | 165  | 1.7589          | 0.2889   |
| 1.8735        | 16.0  | 176  | 1.7582          | 0.2889   |
| 1.7682        | 17.0  | 187  | 1.7576          | 0.2889   |
| 1.9422        | 18.0  | 198  | 1.7569          | 0.2889   |
| 1.8314        | 19.0  | 209  | 1.7564          | 0.2889   |
| 1.8044        | 20.0  | 220  | 1.7558          | 0.2889   |
| 1.861         | 21.0  | 231  | 1.7553          | 0.2889   |
| 1.8777        | 22.0  | 242  | 1.7548          | 0.2889   |
| 1.8717        | 23.0  | 253  | 1.7543          | 0.2889   |
| 1.871         | 24.0  | 264  | 1.7538          | 0.2889   |
| 1.7137        | 25.0  | 275  | 1.7534          | 0.2889   |
| 2.0687        | 26.0  | 286  | 1.7530          | 0.2889   |
| 1.8393        | 27.0  | 297  | 1.7526          | 0.2889   |
| 1.7891        | 28.0  | 308  | 1.7522          | 0.2889   |
| 1.8258        | 29.0  | 319  | 1.7518          | 0.2889   |
| 1.8714        | 30.0  | 330  | 1.7515          | 0.2889   |
| 1.8476        | 31.0  | 341  | 1.7512          | 0.2889   |
| 1.8466        | 32.0  | 352  | 1.7509          | 0.2889   |
| 1.8617        | 33.0  | 363  | 1.7506          | 0.2889   |
| 1.824         | 34.0  | 374  | 1.7504          | 0.2889   |
| 1.8914        | 35.0  | 385  | 1.7502          | 0.2889   |
| 1.8172        | 36.0  | 396  | 1.7500          | 0.2889   |
| 1.8154        | 37.0  | 407  | 1.7498          | 0.2889   |
| 1.8624        | 38.0  | 418  | 1.7497          | 0.2889   |
| 1.8263        | 39.0  | 429  | 1.7495          | 0.2889   |
| 1.8623        | 40.0  | 440  | 1.7494          | 0.2889   |
| 1.8293        | 41.0  | 451  | 1.7493          | 0.2889   |
| 1.8217        | 42.0  | 462  | 1.7492          | 0.2889   |
| 1.8829        | 43.0  | 473  | 1.7492          | 0.2889   |
| 1.8525        | 44.0  | 484  | 1.7492          | 0.2889   |
| 1.8361        | 45.0  | 495  | 1.7491          | 0.2889   |
| 1.8854        | 46.0  | 506  | 1.7491          | 0.2889   |
| 1.8961        | 47.0  | 517  | 1.7491          | 0.2889   |
| 1.7676        | 48.0  | 528  | 1.7491          | 0.2889   |
| 1.9067        | 49.0  | 539  | 1.7491          | 0.2889   |
| 1.8785        | 50.0  | 550  | 1.7491          | 0.2889   |


### 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_fold1", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imagefolder", "type": "imagefolder", "config": "default", "split": "test", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.28888888888888886, "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