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# HUSHEM_5x_beit_large_SGD_lr001_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: 0.7587
- Accuracy: 0.6744

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.4732        | 1.0   | 55   | 1.4217          | 0.2558   |
| 1.4262        | 2.0   | 110  | 1.3472          | 0.2791   |
| 1.3498        | 3.0   | 165  | 1.2941          | 0.3488   |
| 1.2033        | 4.0   | 220  | 1.2538          | 0.4186   |
| 1.123         | 5.0   | 275  | 1.2175          | 0.4419   |
| 1.1349        | 6.0   | 330  | 1.1788          | 0.5116   |
| 1.0267        | 7.0   | 385  | 1.1427          | 0.5349   |
| 1.0282        | 8.0   | 440  | 1.1128          | 0.5349   |
| 0.9556        | 9.0   | 495  | 1.0867          | 0.5581   |
| 0.9096        | 10.0  | 550  | 1.0583          | 0.5814   |
| 0.7963        | 11.0  | 605  | 1.0374          | 0.5814   |
| 0.7978        | 12.0  | 660  | 1.0130          | 0.5814   |
| 0.7214        | 13.0  | 715  | 0.9980          | 0.6279   |
| 0.6797        | 14.0  | 770  | 0.9802          | 0.6279   |
| 0.7692        | 15.0  | 825  | 0.9622          | 0.6279   |
| 0.7659        | 16.0  | 880  | 0.9470          | 0.6279   |
| 0.668         | 17.0  | 935  | 0.9285          | 0.6047   |
| 0.5827        | 18.0  | 990  | 0.9128          | 0.6047   |
| 0.5817        | 19.0  | 1045 | 0.9008          | 0.6047   |
| 0.5806        | 20.0  | 1100 | 0.8854          | 0.6279   |
| 0.5777        | 21.0  | 1155 | 0.8782          | 0.6047   |
| 0.5908        | 22.0  | 1210 | 0.8658          | 0.6047   |
| 0.5349        | 23.0  | 1265 | 0.8570          | 0.6279   |
| 0.5493        | 24.0  | 1320 | 0.8480          | 0.6047   |
| 0.5876        | 25.0  | 1375 | 0.8448          | 0.6047   |
| 0.5444        | 26.0  | 1430 | 0.8376          | 0.6047   |
| 0.5224        | 27.0  | 1485 | 0.8279          | 0.6047   |
| 0.4696        | 28.0  | 1540 | 0.8207          | 0.6279   |
| 0.4546        | 29.0  | 1595 | 0.8136          | 0.6512   |
| 0.4291        | 30.0  | 1650 | 0.8047          | 0.6512   |
| 0.4573        | 31.0  | 1705 | 0.8003          | 0.6512   |
| 0.4203        | 32.0  | 1760 | 0.7958          | 0.6512   |
| 0.4814        | 33.0  | 1815 | 0.7930          | 0.6512   |
| 0.4155        | 34.0  | 1870 | 0.7883          | 0.6744   |
| 0.398         | 35.0  | 1925 | 0.7852          | 0.6744   |
| 0.4602        | 36.0  | 1980 | 0.7831          | 0.6744   |
| 0.4268        | 37.0  | 2035 | 0.7814          | 0.6744   |
| 0.4091        | 38.0  | 2090 | 0.7763          | 0.6744   |
| 0.4136        | 39.0  | 2145 | 0.7724          | 0.6744   |
| 0.3751        | 40.0  | 2200 | 0.7686          | 0.6744   |
| 0.3904        | 41.0  | 2255 | 0.7656          | 0.6744   |
| 0.5456        | 42.0  | 2310 | 0.7632          | 0.6744   |
| 0.3593        | 43.0  | 2365 | 0.7602          | 0.6744   |
| 0.472         | 44.0  | 2420 | 0.7593          | 0.6744   |
| 0.3966        | 45.0  | 2475 | 0.7599          | 0.6744   |
| 0.4004        | 46.0  | 2530 | 0.7591          | 0.6744   |
| 0.3313        | 47.0  | 2585 | 0.7587          | 0.6744   |
| 0.3976        | 48.0  | 2640 | 0.7587          | 0.6744   |
| 0.3973        | 49.0  | 2695 | 0.7587          | 0.6744   |
| 0.417         | 50.0  | 2750 | 0.7587          | 0.6744   |


### 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_5x_beit_large_SGD_lr001_fold3", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imagefolder", "type": "imagefolder", "config": "default", "split": "test", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.6744186046511628, "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