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# HUSHEM_5x_beit_large_Adamax_lr0001_fold2

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: 1.9114
- Accuracy: 0.7778

## 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: 0.0001
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.2859        | 1.0   | 54   | 1.1011          | 0.7556   |
| 0.0933        | 2.0   | 108  | 1.2915          | 0.7111   |
| 0.0575        | 3.0   | 162  | 2.2175          | 0.6444   |
| 0.0179        | 4.0   | 216  | 1.6407          | 0.7333   |
| 0.0002        | 5.0   | 270  | 1.9821          | 0.7111   |
| 0.0002        | 6.0   | 324  | 2.1070          | 0.7111   |
| 0.0           | 7.0   | 378  | 1.9937          | 0.7556   |
| 0.0001        | 8.0   | 432  | 2.0212          | 0.7556   |
| 0.0           | 9.0   | 486  | 2.0131          | 0.7556   |
| 0.0           | 10.0  | 540  | 2.0013          | 0.7333   |
| 0.0           | 11.0  | 594  | 1.9847          | 0.7556   |
| 0.0           | 12.0  | 648  | 1.9848          | 0.7556   |
| 0.0           | 13.0  | 702  | 1.9315          | 0.7556   |
| 0.0           | 14.0  | 756  | 1.9188          | 0.7556   |
| 0.0           | 15.0  | 810  | 1.9205          | 0.7556   |
| 0.0           | 16.0  | 864  | 1.9085          | 0.7778   |
| 0.0           | 17.0  | 918  | 1.8837          | 0.7778   |
| 0.0           | 18.0  | 972  | 1.8491          | 0.7556   |
| 0.0           | 19.0  | 1026 | 1.8681          | 0.7556   |
| 0.0           | 20.0  | 1080 | 1.8724          | 0.7556   |
| 0.0           | 21.0  | 1134 | 1.9298          | 0.7556   |
| 0.0           | 22.0  | 1188 | 1.9126          | 0.7556   |
| 0.0           | 23.0  | 1242 | 1.9030          | 0.7556   |
| 0.0           | 24.0  | 1296 | 1.8936          | 0.7556   |
| 0.0           | 25.0  | 1350 | 1.7808          | 0.8222   |
| 0.0           | 26.0  | 1404 | 1.8639          | 0.7778   |
| 0.0           | 27.0  | 1458 | 1.8994          | 0.7778   |
| 0.0           | 28.0  | 1512 | 1.9092          | 0.7778   |
| 0.0           | 29.0  | 1566 | 1.9081          | 0.7778   |
| 0.0           | 30.0  | 1620 | 1.9048          | 0.7778   |
| 0.0           | 31.0  | 1674 | 1.8968          | 0.7778   |
| 0.0           | 32.0  | 1728 | 1.9004          | 0.7778   |
| 0.0           | 33.0  | 1782 | 1.8961          | 0.7778   |
| 0.0           | 34.0  | 1836 | 1.8893          | 0.7778   |
| 0.0           | 35.0  | 1890 | 1.8865          | 0.7778   |
| 0.0           | 36.0  | 1944 | 1.8971          | 0.7778   |
| 0.0           | 37.0  | 1998 | 1.9118          | 0.7778   |
| 0.0           | 38.0  | 2052 | 1.9192          | 0.7778   |
| 0.0           | 39.0  | 2106 | 1.9177          | 0.7778   |
| 0.0           | 40.0  | 2160 | 1.9143          | 0.7778   |
| 0.0           | 41.0  | 2214 | 1.9152          | 0.7778   |
| 0.0           | 42.0  | 2268 | 1.9165          | 0.7778   |
| 0.0           | 43.0  | 2322 | 1.9175          | 0.7778   |
| 0.0           | 44.0  | 2376 | 1.9181          | 0.7778   |
| 0.0           | 45.0  | 2430 | 1.9154          | 0.7778   |
| 0.0           | 46.0  | 2484 | 1.9117          | 0.7778   |
| 0.0           | 47.0  | 2538 | 1.9118          | 0.7778   |
| 0.0           | 48.0  | 2592 | 1.9116          | 0.7778   |
| 0.0           | 49.0  | 2646 | 1.9114          | 0.7778   |
| 0.0           | 50.0  | 2700 | 1.9114          | 0.7778   |


### 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_lr0001_fold2", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imagefolder", "type": "imagefolder", "config": "default", "split": "test", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.7777777777777778, "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