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# HUSHEM_10x_beit_large_SGD_lr001_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: 0.3095
- Accuracy: 0.9268

## 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: 0.001
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.3437        | 1.0   | 110  | 1.2950          | 0.3659   |
| 1.2643        | 2.0   | 220  | 1.1599          | 0.4634   |
| 1.1636        | 3.0   | 330  | 1.0493          | 0.5366   |
| 1.0289        | 4.0   | 440  | 0.9577          | 0.6341   |
| 0.9254        | 5.0   | 550  | 0.8821          | 0.7317   |
| 0.7847        | 6.0   | 660  | 0.8069          | 0.7317   |
| 0.6731        | 7.0   | 770  | 0.7482          | 0.7805   |
| 0.6368        | 8.0   | 880  | 0.6956          | 0.7805   |
| 0.6451        | 9.0   | 990  | 0.6464          | 0.8049   |
| 0.5346        | 10.0  | 1100 | 0.5983          | 0.8293   |
| 0.659         | 11.0  | 1210 | 0.5689          | 0.8780   |
| 0.4631        | 12.0  | 1320 | 0.5301          | 0.8780   |
| 0.5686        | 13.0  | 1430 | 0.5175          | 0.8537   |
| 0.4936        | 14.0  | 1540 | 0.4841          | 0.8780   |
| 0.3392        | 15.0  | 1650 | 0.4583          | 0.8780   |
| 0.3951        | 16.0  | 1760 | 0.4395          | 0.9024   |
| 0.3634        | 17.0  | 1870 | 0.4236          | 0.9268   |
| 0.3271        | 18.0  | 1980 | 0.4170          | 0.9024   |
| 0.311         | 19.0  | 2090 | 0.4094          | 0.8780   |
| 0.2742        | 20.0  | 2200 | 0.3900          | 0.9268   |
| 0.2169        | 21.0  | 2310 | 0.3764          | 0.9268   |
| 0.2822        | 22.0  | 2420 | 0.3700          | 0.9268   |
| 0.2443        | 23.0  | 2530 | 0.3612          | 0.9268   |
| 0.2529        | 24.0  | 2640 | 0.3546          | 0.9268   |
| 0.2665        | 25.0  | 2750 | 0.3438          | 0.9268   |
| 0.1884        | 26.0  | 2860 | 0.3388          | 0.9268   |
| 0.2158        | 27.0  | 2970 | 0.3416          | 0.9268   |
| 0.227         | 28.0  | 3080 | 0.3318          | 0.9268   |
| 0.168         | 29.0  | 3190 | 0.3296          | 0.9268   |
| 0.1805        | 30.0  | 3300 | 0.3236          | 0.9268   |
| 0.2049        | 31.0  | 3410 | 0.3262          | 0.9268   |
| 0.1862        | 32.0  | 3520 | 0.3342          | 0.9268   |
| 0.1738        | 33.0  | 3630 | 0.3156          | 0.9268   |
| 0.1803        | 34.0  | 3740 | 0.3160          | 0.9268   |
| 0.1712        | 35.0  | 3850 | 0.3129          | 0.9268   |
| 0.1733        | 36.0  | 3960 | 0.3190          | 0.9268   |
| 0.1927        | 37.0  | 4070 | 0.3128          | 0.9268   |
| 0.1678        | 38.0  | 4180 | 0.3181          | 0.9268   |
| 0.1559        | 39.0  | 4290 | 0.3114          | 0.9268   |
| 0.1744        | 40.0  | 4400 | 0.3132          | 0.9268   |
| 0.1705        | 41.0  | 4510 | 0.3094          | 0.9268   |
| 0.12          | 42.0  | 4620 | 0.3106          | 0.9268   |
| 0.1288        | 43.0  | 4730 | 0.3097          | 0.9268   |
| 0.1629        | 44.0  | 4840 | 0.3116          | 0.9268   |
| 0.1386        | 45.0  | 4950 | 0.3108          | 0.9268   |
| 0.1139        | 46.0  | 5060 | 0.3073          | 0.9268   |
| 0.13          | 47.0  | 5170 | 0.3057          | 0.9268   |
| 0.1392        | 48.0  | 5280 | 0.3086          | 0.9268   |
| 0.1357        | 49.0  | 5390 | 0.3092          | 0.9268   |
| 0.1628        | 50.0  | 5500 | 0.3095          | 0.9268   |


### 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_lr001_fold5", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imagefolder", "type": "imagefolder", "config": "default", "split": "test", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.926829268292683, "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