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# HUSHEM_1x_beit_large_Adamax_lr00001_fold4

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: 0.1434
- Accuracy: 0.9524

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.4188        | 1.0   | 11   | 1.0851          | 0.5952   |
| 0.9517        | 2.0   | 22   | 0.8162          | 0.7143   |
| 0.5963        | 3.0   | 33   | 0.6323          | 0.7381   |
| 0.3273        | 4.0   | 44   | 0.5263          | 0.7143   |
| 0.209         | 5.0   | 55   | 0.4022          | 0.8810   |
| 0.1291        | 6.0   | 66   | 0.3606          | 0.8333   |
| 0.1077        | 7.0   | 77   | 0.3101          | 0.8810   |
| 0.0426        | 8.0   | 88   | 0.2855          | 0.8571   |
| 0.0442        | 9.0   | 99   | 0.2569          | 0.8810   |
| 0.0165        | 10.0  | 110  | 0.2102          | 0.9524   |
| 0.0087        | 11.0  | 121  | 0.1950          | 0.9524   |
| 0.0081        | 12.0  | 132  | 0.2075          | 0.9048   |
| 0.0112        | 13.0  | 143  | 0.2019          | 0.9286   |
| 0.0039        | 14.0  | 154  | 0.1899          | 0.9524   |
| 0.0039        | 15.0  | 165  | 0.1690          | 0.9524   |
| 0.0029        | 16.0  | 176  | 0.1608          | 0.9524   |
| 0.0021        | 17.0  | 187  | 0.1491          | 0.9524   |
| 0.0025        | 18.0  | 198  | 0.1600          | 0.9286   |
| 0.0017        | 19.0  | 209  | 0.1603          | 0.9524   |
| 0.0015        | 20.0  | 220  | 0.1830          | 0.9524   |
| 0.0015        | 21.0  | 231  | 0.1853          | 0.9048   |
| 0.0014        | 22.0  | 242  | 0.1903          | 0.9286   |
| 0.0013        | 23.0  | 253  | 0.2118          | 0.9286   |
| 0.0033        | 24.0  | 264  | 0.2550          | 0.8810   |
| 0.0014        | 25.0  | 275  | 0.2579          | 0.8810   |
| 0.0051        | 26.0  | 286  | 0.2026          | 0.8810   |
| 0.0012        | 27.0  | 297  | 0.1658          | 0.9286   |
| 0.0013        | 28.0  | 308  | 0.1556          | 0.9524   |
| 0.001         | 29.0  | 319  | 0.1494          | 0.9524   |
| 0.0185        | 30.0  | 330  | 0.1550          | 0.9524   |
| 0.0008        | 31.0  | 341  | 0.1641          | 0.9048   |
| 0.0008        | 32.0  | 352  | 0.1569          | 0.9048   |
| 0.001         | 33.0  | 363  | 0.1630          | 0.9286   |
| 0.0006        | 34.0  | 374  | 0.1609          | 0.9048   |
| 0.0012        | 35.0  | 385  | 0.1550          | 0.9048   |
| 0.0011        | 36.0  | 396  | 0.1525          | 0.9286   |
| 0.001         | 37.0  | 407  | 0.1528          | 0.9524   |
| 0.0006        | 38.0  | 418  | 0.1497          | 0.9524   |
| 0.0007        | 39.0  | 429  | 0.1504          | 0.9524   |
| 0.001         | 40.0  | 440  | 0.1479          | 0.9524   |
| 0.001         | 41.0  | 451  | 0.1435          | 0.9524   |
| 0.0007        | 42.0  | 462  | 0.1435          | 0.9524   |
| 0.0007        | 43.0  | 473  | 0.1434          | 0.9524   |
| 0.0007        | 44.0  | 484  | 0.1434          | 0.9524   |
| 0.0006        | 45.0  | 495  | 0.1433          | 0.9524   |
| 0.0008        | 46.0  | 506  | 0.1434          | 0.9524   |
| 0.0009        | 47.0  | 517  | 0.1434          | 0.9524   |
| 0.0006        | 48.0  | 528  | 0.1434          | 0.9524   |
| 0.0009        | 49.0  | 539  | 0.1434          | 0.9524   |
| 0.0005        | 50.0  | 550  | 0.1434          | 0.9524   |


### Framework versions

- Transformers 4.35.0
- Pytorch 2.1.0
- Datasets 2.14.6
- Tokenizers 0.14.1

{"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_Adamax_lr00001_fold4", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imagefolder", "type": "imagefolder", "config": "default", "split": "test", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.9523809523809523, "name": "Accuracy"}]}]}]}
transformers safetensors 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