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# HUSHEM_5x_beit_large_Adamax_lr00001_fold2

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: 0.9858
- Accuracy: 0.8444

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.4676        | 1.0   | 54   | 0.9213          | 0.6444   |
| 0.1416        | 2.0   | 108  | 0.6518          | 0.7111   |
| 0.0305        | 3.0   | 162  | 0.7370          | 0.7333   |
| 0.0063        | 4.0   | 216  | 0.6235          | 0.8444   |
| 0.0018        | 5.0   | 270  | 0.7669          | 0.8      |
| 0.0027        | 6.0   | 324  | 0.7445          | 0.8444   |
| 0.0003        | 7.0   | 378  | 0.8505          | 0.8444   |
| 0.0008        | 8.0   | 432  | 0.8897          | 0.8444   |
| 0.0004        | 9.0   | 486  | 0.8717          | 0.8222   |
| 0.0003        | 10.0  | 540  | 0.7948          | 0.8667   |
| 0.0002        | 11.0  | 594  | 0.8291          | 0.8444   |
| 0.0002        | 12.0  | 648  | 0.9924          | 0.8      |
| 0.0005        | 13.0  | 702  | 0.9159          | 0.8222   |
| 0.0001        | 14.0  | 756  | 0.8355          | 0.8222   |
| 0.0001        | 15.0  | 810  | 0.9031          | 0.8222   |
| 0.0002        | 16.0  | 864  | 0.9127          | 0.8444   |
| 0.0001        | 17.0  | 918  | 0.9166          | 0.8222   |
| 0.0004        | 18.0  | 972  | 1.0261          | 0.8      |
| 0.0003        | 19.0  | 1026 | 0.9366          | 0.8444   |
| 0.0001        | 20.0  | 1080 | 0.8647          | 0.8444   |
| 0.0069        | 21.0  | 1134 | 0.8214          | 0.8667   |
| 0.0001        | 22.0  | 1188 | 0.8600          | 0.8667   |
| 0.0001        | 23.0  | 1242 | 0.8954          | 0.8667   |
| 0.0           | 24.0  | 1296 | 0.8770          | 0.8444   |
| 0.0001        | 25.0  | 1350 | 0.8911          | 0.8444   |
| 0.0001        | 26.0  | 1404 | 0.8648          | 0.8667   |
| 0.0           | 27.0  | 1458 | 0.9186          | 0.8444   |
| 0.0001        | 28.0  | 1512 | 0.8423          | 0.8667   |
| 0.0001        | 29.0  | 1566 | 0.8443          | 0.8667   |
| 0.0           | 30.0  | 1620 | 0.9701          | 0.8222   |
| 0.0001        | 31.0  | 1674 | 0.9026          | 0.8667   |
| 0.0           | 32.0  | 1728 | 0.9447          | 0.8444   |
| 0.0001        | 33.0  | 1782 | 0.8571          | 0.8667   |
| 0.0001        | 34.0  | 1836 | 0.9897          | 0.8444   |
| 0.0           | 35.0  | 1890 | 0.8724          | 0.8667   |
| 0.0003        | 36.0  | 1944 | 0.9768          | 0.8222   |
| 0.0           | 37.0  | 1998 | 0.9785          | 0.8222   |
| 0.0           | 38.0  | 2052 | 0.9587          | 0.8444   |
| 0.0           | 39.0  | 2106 | 1.0038          | 0.8444   |
| 0.0           | 40.0  | 2160 | 1.0354          | 0.8222   |
| 0.0001        | 41.0  | 2214 | 0.9948          | 0.8222   |
| 0.0003        | 42.0  | 2268 | 0.9875          | 0.8222   |
| 0.0           | 43.0  | 2322 | 0.9882          | 0.8444   |
| 0.0           | 44.0  | 2376 | 0.9731          | 0.8444   |
| 0.0           | 45.0  | 2430 | 0.9883          | 0.8444   |
| 0.0           | 46.0  | 2484 | 0.9959          | 0.8444   |
| 0.0           | 47.0  | 2538 | 1.0070          | 0.8444   |
| 0.0001        | 48.0  | 2592 | 0.9879          | 0.8444   |
| 0.0           | 49.0  | 2646 | 0.9858          | 0.8444   |
| 0.0           | 50.0  | 2700 | 0.9858          | 0.8444   |


### Framework versions

- Transformers 4.32.1
- Pytorch 2.0.1
- Datasets 2.12.0
- Tokenizers 0.13.2

{"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_lr00001_fold2", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imagefolder", "type": "imagefolder", "config": "default", "split": "test", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.8444444444444444, "name": "Accuracy"}]}]}]}
transformers pytorch 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