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# HUSHEM_10x_beit_large_Adamax_lr00001_fold3

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: 0.9641
- Accuracy: 0.8837

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.178         | 1.0   | 109  | 0.4882          | 0.8372   |
| 0.0198        | 2.0   | 218  | 0.5119          | 0.8140   |
| 0.0058        | 3.0   | 327  | 0.5904          | 0.8372   |
| 0.0011        | 4.0   | 436  | 0.6292          | 0.8605   |
| 0.0006        | 5.0   | 545  | 0.4058          | 0.8605   |
| 0.0002        | 6.0   | 654  | 0.5785          | 0.8605   |
| 0.0003        | 7.0   | 763  | 0.8079          | 0.8372   |
| 0.0002        | 8.0   | 872  | 0.6589          | 0.8837   |
| 0.0001        | 9.0   | 981  | 0.7672          | 0.8605   |
| 0.0001        | 10.0  | 1090 | 0.7710          | 0.8605   |
| 0.0001        | 11.0  | 1199 | 0.9076          | 0.8372   |
| 0.0001        | 12.0  | 1308 | 0.7994          | 0.8605   |
| 0.0004        | 13.0  | 1417 | 0.4839          | 0.8837   |
| 0.0001        | 14.0  | 1526 | 0.6157          | 0.8837   |
| 0.0001        | 15.0  | 1635 | 0.6784          | 0.8837   |
| 0.0001        | 16.0  | 1744 | 0.6735          | 0.8837   |
| 0.0           | 17.0  | 1853 | 0.9170          | 0.8605   |
| 0.0001        | 18.0  | 1962 | 0.8533          | 0.8605   |
| 0.0003        | 19.0  | 2071 | 0.8366          | 0.8837   |
| 0.0           | 20.0  | 2180 | 0.6623          | 0.9070   |
| 0.0           | 21.0  | 2289 | 0.7393          | 0.8837   |
| 0.0           | 22.0  | 2398 | 0.6734          | 0.9070   |
| 0.0005        | 23.0  | 2507 | 0.7931          | 0.8837   |
| 0.0001        | 24.0  | 2616 | 0.9133          | 0.8605   |
| 0.0           | 25.0  | 2725 | 0.7918          | 0.8605   |
| 0.0001        | 26.0  | 2834 | 0.8042          | 0.8837   |
| 0.0           | 27.0  | 2943 | 0.7976          | 0.8837   |
| 0.0           | 28.0  | 3052 | 0.7474          | 0.8837   |
| 0.0           | 29.0  | 3161 | 0.8237          | 0.8837   |
| 0.0           | 30.0  | 3270 | 0.8779          | 0.8605   |
| 0.0           | 31.0  | 3379 | 0.8970          | 0.8605   |
| 0.0001        | 32.0  | 3488 | 0.8570          | 0.8837   |
| 0.0           | 33.0  | 3597 | 0.8984          | 0.8837   |
| 0.0           | 34.0  | 3706 | 0.8784          | 0.8837   |
| 0.0           | 35.0  | 3815 | 0.9371          | 0.8605   |
| 0.0           | 36.0  | 3924 | 0.9083          | 0.8605   |
| 0.0004        | 37.0  | 4033 | 0.9021          | 0.8605   |
| 0.0           | 38.0  | 4142 | 0.9636          | 0.8605   |
| 0.0001        | 39.0  | 4251 | 0.9805          | 0.8372   |
| 0.0           | 40.0  | 4360 | 0.9995          | 0.8605   |
| 0.0           | 41.0  | 4469 | 0.9224          | 0.8837   |
| 0.0           | 42.0  | 4578 | 0.9213          | 0.8837   |
| 0.0001        | 43.0  | 4687 | 0.9892          | 0.8605   |
| 0.0           | 44.0  | 4796 | 1.0581          | 0.8372   |
| 0.0           | 45.0  | 4905 | 1.0307          | 0.8372   |
| 0.0           | 46.0  | 5014 | 1.0200          | 0.8605   |
| 0.0004        | 47.0  | 5123 | 0.9796          | 0.8837   |
| 0.0           | 48.0  | 5232 | 0.9605          | 0.8837   |
| 0.0001        | 49.0  | 5341 | 0.9652          | 0.8837   |
| 0.0           | 50.0  | 5450 | 0.9641          | 0.8837   |


### 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_10x_beit_large_Adamax_lr00001_fold3", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imagefolder", "type": "imagefolder", "config": "default", "split": "test", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.8837209302325582, "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