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# HUSHEM_5x_beit_large_Adamax_lr001_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: 2.4703
- Accuracy: 0.7619

## 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: 0.001
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.4396        | 1.0   | 55   | 1.3695          | 0.2619   |
| 1.084         | 2.0   | 110  | 0.8152          | 0.7143   |
| 1.0818        | 3.0   | 165  | 1.5515          | 0.3095   |
| 1.0309        | 4.0   | 220  | 0.9313          | 0.6429   |
| 0.9364        | 5.0   | 275  | 0.7436          | 0.7143   |
| 0.8951        | 6.0   | 330  | 0.6686          | 0.7857   |
| 1.0556        | 7.0   | 385  | 0.6091          | 0.7143   |
| 1.0385        | 8.0   | 440  | 0.6649          | 0.7857   |
| 0.87          | 9.0   | 495  | 0.8470          | 0.6190   |
| 0.8442        | 10.0  | 550  | 0.7710          | 0.7143   |
| 0.8243        | 11.0  | 605  | 0.6806          | 0.7381   |
| 0.8587        | 12.0  | 660  | 0.6603          | 0.7381   |
| 0.8369        | 13.0  | 715  | 0.6348          | 0.7381   |
| 0.75          | 14.0  | 770  | 0.8870          | 0.6429   |
| 0.9176        | 15.0  | 825  | 0.6132          | 0.8571   |
| 0.6421        | 16.0  | 880  | 0.6076          | 0.7857   |
| 0.6832        | 17.0  | 935  | 0.7085          | 0.8333   |
| 0.7576        | 18.0  | 990  | 0.7510          | 0.6905   |
| 0.5995        | 19.0  | 1045 | 0.9108          | 0.7381   |
| 0.6614        | 20.0  | 1100 | 0.8983          | 0.7857   |
| 0.6985        | 21.0  | 1155 | 0.5893          | 0.7857   |
| 0.4548        | 22.0  | 1210 | 0.8180          | 0.8333   |
| 0.4722        | 23.0  | 1265 | 0.6611          | 0.8095   |
| 0.6732        | 24.0  | 1320 | 0.7466          | 0.7857   |
| 0.3762        | 25.0  | 1375 | 0.5836          | 0.8571   |
| 0.5084        | 26.0  | 1430 | 0.8482          | 0.7381   |
| 0.3601        | 27.0  | 1485 | 0.7275          | 0.8333   |
| 0.3739        | 28.0  | 1540 | 1.0988          | 0.7381   |
| 0.3804        | 29.0  | 1595 | 0.6636          | 0.8333   |
| 0.3551        | 30.0  | 1650 | 0.8843          | 0.8095   |
| 0.2619        | 31.0  | 1705 | 1.0733          | 0.7857   |
| 0.2314        | 32.0  | 1760 | 0.7232          | 0.8571   |
| 0.2171        | 33.0  | 1815 | 1.3551          | 0.7857   |
| 0.2193        | 34.0  | 1870 | 1.1362          | 0.7619   |
| 0.2263        | 35.0  | 1925 | 1.0323          | 0.8095   |
| 0.1921        | 36.0  | 1980 | 1.0481          | 0.7619   |
| 0.1144        | 37.0  | 2035 | 1.3816          | 0.7857   |
| 0.0924        | 38.0  | 2090 | 1.8367          | 0.8333   |
| 0.1142        | 39.0  | 2145 | 1.8424          | 0.7857   |
| 0.071         | 40.0  | 2200 | 2.1412          | 0.8333   |
| 0.1405        | 41.0  | 2255 | 2.3873          | 0.7619   |
| 0.0545        | 42.0  | 2310 | 2.6161          | 0.7381   |
| 0.1051        | 43.0  | 2365 | 2.8398          | 0.7619   |
| 0.0626        | 44.0  | 2420 | 2.3418          | 0.7381   |
| 0.0125        | 45.0  | 2475 | 2.4318          | 0.7381   |
| 0.0038        | 46.0  | 2530 | 2.5424          | 0.7857   |
| 0.0784        | 47.0  | 2585 | 2.4497          | 0.7619   |
| 0.0448        | 48.0  | 2640 | 2.5619          | 0.7381   |
| 0.1012        | 49.0  | 2695 | 2.4719          | 0.7619   |
| 0.0002        | 50.0  | 2750 | 2.4703          | 0.7619   |


### 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_5x_beit_large_Adamax_lr001_fold4", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imagefolder", "type": "imagefolder", "config": "default", "split": "test", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.7619047619047619, "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