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# hushem_5x_beit_base_adamax_0001_fold2

This model is a fine-tuned version of [microsoft/beit-base-patch16-224](https://huggingface.co/microsoft/beit-base-patch16-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1073
- Accuracy: 0.8667

## 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: 32
- eval_batch_size: 32
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.56          | 1.0   | 27   | 0.5803          | 0.8444   |
| 0.1296        | 2.0   | 54   | 0.5439          | 0.8444   |
| 0.0323        | 3.0   | 81   | 1.1689          | 0.7556   |
| 0.051         | 4.0   | 108  | 0.6969          | 0.8444   |
| 0.0058        | 5.0   | 135  | 0.7561          | 0.8444   |
| 0.0281        | 6.0   | 162  | 0.6767          | 0.8444   |
| 0.0031        | 7.0   | 189  | 0.9959          | 0.8      |
| 0.006         | 8.0   | 216  | 1.0852          | 0.8222   |
| 0.0042        | 9.0   | 243  | 0.9557          | 0.8667   |
| 0.0002        | 10.0  | 270  | 0.9792          | 0.8444   |
| 0.0001        | 11.0  | 297  | 1.0071          | 0.8667   |
| 0.0001        | 12.0  | 324  | 1.1614          | 0.8      |
| 0.0001        | 13.0  | 351  | 1.0429          | 0.8667   |
| 0.0001        | 14.0  | 378  | 1.0442          | 0.8667   |
| 0.0001        | 15.0  | 405  | 1.1430          | 0.8222   |
| 0.0001        | 16.0  | 432  | 1.1457          | 0.8222   |
| 0.0027        | 17.0  | 459  | 1.3728          | 0.8222   |
| 0.0001        | 18.0  | 486  | 1.0448          | 0.8667   |
| 0.0001        | 19.0  | 513  | 1.0357          | 0.8667   |
| 0.0           | 20.0  | 540  | 1.2604          | 0.8      |
| 0.0026        | 21.0  | 567  | 1.0654          | 0.8667   |
| 0.0004        | 22.0  | 594  | 1.1414          | 0.8444   |
| 0.0001        | 23.0  | 621  | 1.1523          | 0.8444   |
| 0.0001        | 24.0  | 648  | 1.1307          | 0.8444   |
| 0.0002        | 25.0  | 675  | 1.1816          | 0.8444   |
| 0.0           | 26.0  | 702  | 1.1278          | 0.8444   |
| 0.0           | 27.0  | 729  | 1.0224          | 0.8667   |
| 0.0001        | 28.0  | 756  | 1.4430          | 0.7333   |
| 0.0001        | 29.0  | 783  | 1.3228          | 0.7556   |
| 0.0           | 30.0  | 810  | 1.2875          | 0.8      |
| 0.0001        | 31.0  | 837  | 1.2284          | 0.8222   |
| 0.0003        | 32.0  | 864  | 1.3104          | 0.8444   |
| 0.0001        | 33.0  | 891  | 1.1798          | 0.8667   |
| 0.0001        | 34.0  | 918  | 1.1586          | 0.8667   |
| 0.0001        | 35.0  | 945  | 1.1617          | 0.8667   |
| 0.0           | 36.0  | 972  | 1.1634          | 0.8667   |
| 0.0           | 37.0  | 999  | 1.1712          | 0.8667   |
| 0.0           | 38.0  | 1026 | 1.1767          | 0.8667   |
| 0.0           | 39.0  | 1053 | 1.1666          | 0.8667   |
| 0.0           | 40.0  | 1080 | 1.1693          | 0.8667   |
| 0.0           | 41.0  | 1107 | 1.1706          | 0.8667   |
| 0.0           | 42.0  | 1134 | 1.0988          | 0.8667   |
| 0.001         | 43.0  | 1161 | 1.0945          | 0.8667   |
| 0.0           | 44.0  | 1188 | 1.0895          | 0.8667   |
| 0.0           | 45.0  | 1215 | 1.0977          | 0.8667   |
| 0.0004        | 46.0  | 1242 | 1.0978          | 0.8667   |
| 0.0           | 47.0  | 1269 | 1.1013          | 0.8667   |
| 0.0001        | 48.0  | 1296 | 1.1072          | 0.8667   |
| 0.0001        | 49.0  | 1323 | 1.1073          | 0.8667   |
| 0.0           | 50.0  | 1350 | 1.1073          | 0.8667   |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["imagefolder"], "metrics": ["accuracy"], "base_model": "microsoft/beit-base-patch16-224", "model-index": [{"name": "hushem_5x_beit_base_adamax_0001_fold2", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imagefolder", "type": "imagefolder", "config": "default", "split": "test", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.8666666666666667, "name": "Accuracy"}]}]}]}
transformers tensorboard safetensors beit image-classification generated_from_trainer dataset:imagefolder base_model:microsoft/beit-base-patch16-224 license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us