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# HUSHEM_5x_beit_large_Adamax_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: 0.6585
- Accuracy: 0.8837

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.512         | 1.0   | 55   | 0.7505          | 0.6744   |
| 0.0935        | 2.0   | 110  | 0.4273          | 0.8140   |
| 0.0332        | 3.0   | 165  | 0.4993          | 0.8140   |
| 0.006         | 4.0   | 220  | 0.2833          | 0.9070   |
| 0.0015        | 5.0   | 275  | 0.5179          | 0.8837   |
| 0.0015        | 6.0   | 330  | 0.5658          | 0.8605   |
| 0.0007        | 7.0   | 385  | 0.5994          | 0.8605   |
| 0.0005        | 8.0   | 440  | 0.7158          | 0.8605   |
| 0.0002        | 9.0   | 495  | 0.5120          | 0.8837   |
| 0.0003        | 10.0  | 550  | 0.4911          | 0.8837   |
| 0.0017        | 11.0  | 605  | 0.6487          | 0.8837   |
| 0.0002        | 12.0  | 660  | 0.5351          | 0.9070   |
| 0.0001        | 13.0  | 715  | 0.5349          | 0.8837   |
| 0.0003        | 14.0  | 770  | 0.5366          | 0.8837   |
| 0.0006        | 15.0  | 825  | 0.4881          | 0.9070   |
| 0.0001        | 16.0  | 880  | 0.5075          | 0.8837   |
| 0.0001        | 17.0  | 935  | 0.4129          | 0.9070   |
| 0.0002        | 18.0  | 990  | 0.4194          | 0.9070   |
| 0.0006        | 19.0  | 1045 | 0.5565          | 0.8837   |
| 0.0001        | 20.0  | 1100 | 0.5743          | 0.8605   |
| 0.0002        | 21.0  | 1155 | 0.6587          | 0.8605   |
| 0.0001        | 22.0  | 1210 | 0.6834          | 0.8605   |
| 0.0002        | 23.0  | 1265 | 0.6015          | 0.9070   |
| 0.0002        | 24.0  | 1320 | 0.5414          | 0.8837   |
| 0.0005        | 25.0  | 1375 | 0.7558          | 0.8605   |
| 0.0001        | 26.0  | 1430 | 0.8458          | 0.8605   |
| 0.0001        | 27.0  | 1485 | 0.7319          | 0.8605   |
| 0.0001        | 28.0  | 1540 | 0.7142          | 0.8837   |
| 0.0001        | 29.0  | 1595 | 0.6416          | 0.8837   |
| 0.0001        | 30.0  | 1650 | 0.6503          | 0.8837   |
| 0.0001        | 31.0  | 1705 | 0.6757          | 0.8837   |
| 0.0001        | 32.0  | 1760 | 0.8746          | 0.8372   |
| 0.0024        | 33.0  | 1815 | 0.7659          | 0.8837   |
| 0.0001        | 34.0  | 1870 | 0.7762          | 0.8837   |
| 0.0           | 35.0  | 1925 | 0.7304          | 0.8837   |
| 0.0           | 36.0  | 1980 | 0.7767          | 0.8837   |
| 0.0001        | 37.0  | 2035 | 0.6925          | 0.8837   |
| 0.0           | 38.0  | 2090 | 0.6925          | 0.8837   |
| 0.0           | 39.0  | 2145 | 0.7037          | 0.8837   |
| 0.0002        | 40.0  | 2200 | 0.7063          | 0.8837   |
| 0.0           | 41.0  | 2255 | 0.7326          | 0.8837   |
| 0.0001        | 42.0  | 2310 | 0.7463          | 0.8837   |
| 0.0001        | 43.0  | 2365 | 0.7406          | 0.8837   |
| 0.0           | 44.0  | 2420 | 0.7108          | 0.8837   |
| 0.0           | 45.0  | 2475 | 0.7039          | 0.8837   |
| 0.0           | 46.0  | 2530 | 0.6625          | 0.8837   |
| 0.0           | 47.0  | 2585 | 0.6652          | 0.8837   |
| 0.0           | 48.0  | 2640 | 0.6582          | 0.8837   |
| 0.0           | 49.0  | 2695 | 0.6585          | 0.8837   |
| 0.0001        | 50.0  | 2750 | 0.6585          | 0.8837   |


### 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_Adamax_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": 0.8837209302325582, "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