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# hushem_5x_beit_base_adamax_00001_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: 1.0731
- 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: 1e-05
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.133         | 1.0   | 27   | 1.1782          | 0.4444   |
| 0.7374        | 2.0   | 54   | 0.9657          | 0.6889   |
| 0.4404        | 3.0   | 81   | 0.7664          | 0.7556   |
| 0.2921        | 4.0   | 108  | 0.7034          | 0.7778   |
| 0.1574        | 5.0   | 135  | 0.7044          | 0.7778   |
| 0.0983        | 6.0   | 162  | 0.6550          | 0.8222   |
| 0.0636        | 7.0   | 189  | 0.6911          | 0.7778   |
| 0.0455        | 8.0   | 216  | 0.6445          | 0.8      |
| 0.0369        | 9.0   | 243  | 0.7441          | 0.8      |
| 0.0208        | 10.0  | 270  | 0.7266          | 0.8222   |
| 0.0164        | 11.0  | 297  | 0.7445          | 0.8      |
| 0.0128        | 12.0  | 324  | 0.7928          | 0.7556   |
| 0.0152        | 13.0  | 351  | 0.8051          | 0.8      |
| 0.0093        | 14.0  | 378  | 0.8366          | 0.8      |
| 0.005         | 15.0  | 405  | 0.8967          | 0.7778   |
| 0.0081        | 16.0  | 432  | 0.8765          | 0.7556   |
| 0.0143        | 17.0  | 459  | 0.8233          | 0.8      |
| 0.0086        | 18.0  | 486  | 0.8818          | 0.7778   |
| 0.0082        | 19.0  | 513  | 0.9209          | 0.7778   |
| 0.0106        | 20.0  | 540  | 0.9710          | 0.7778   |
| 0.0048        | 21.0  | 567  | 0.8635          | 0.8      |
| 0.0078        | 22.0  | 594  | 1.0340          | 0.7778   |
| 0.0037        | 23.0  | 621  | 1.0458          | 0.7778   |
| 0.0038        | 24.0  | 648  | 1.0554          | 0.7778   |
| 0.0027        | 25.0  | 675  | 0.9290          | 0.8      |
| 0.0037        | 26.0  | 702  | 0.9379          | 0.7778   |
| 0.006         | 27.0  | 729  | 0.9412          | 0.8      |
| 0.001         | 28.0  | 756  | 0.9493          | 0.8      |
| 0.0018        | 29.0  | 783  | 1.0041          | 0.8      |
| 0.0014        | 30.0  | 810  | 1.0318          | 0.8      |
| 0.0008        | 31.0  | 837  | 1.0197          | 0.8      |
| 0.0016        | 32.0  | 864  | 1.0685          | 0.7556   |
| 0.005         | 33.0  | 891  | 1.0574          | 0.7556   |
| 0.0013        | 34.0  | 918  | 1.0948          | 0.7556   |
| 0.0027        | 35.0  | 945  | 1.0699          | 0.7556   |
| 0.0008        | 36.0  | 972  | 1.0485          | 0.8      |
| 0.0014        | 37.0  | 999  | 1.0539          | 0.7778   |
| 0.0009        | 38.0  | 1026 | 1.0508          | 0.7778   |
| 0.0013        | 39.0  | 1053 | 1.0236          | 0.7778   |
| 0.0008        | 40.0  | 1080 | 1.0556          | 0.8      |
| 0.0014        | 41.0  | 1107 | 1.0682          | 0.8      |
| 0.0011        | 42.0  | 1134 | 1.0760          | 0.8      |
| 0.0041        | 43.0  | 1161 | 1.0831          | 0.8      |
| 0.0007        | 44.0  | 1188 | 1.0675          | 0.7778   |
| 0.0039        | 45.0  | 1215 | 1.0667          | 0.7778   |
| 0.0013        | 46.0  | 1242 | 1.0695          | 0.7778   |
| 0.0014        | 47.0  | 1269 | 1.0717          | 0.7778   |
| 0.0015        | 48.0  | 1296 | 1.0731          | 0.7778   |
| 0.002         | 49.0  | 1323 | 1.0731          | 0.7778   |
| 0.0013        | 50.0  | 1350 | 1.0731          | 0.7778   |


### 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_00001_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 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