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# HUSHEM_5x_beit_large_SGD_lr001_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: 0.8970
- Accuracy: 0.6

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.5342        | 1.0   | 54   | 1.5979          | 0.1778   |
| 1.314         | 2.0   | 108  | 1.5159          | 0.2      |
| 1.2514        | 3.0   | 162  | 1.4623          | 0.2444   |
| 1.1904        | 4.0   | 216  | 1.4105          | 0.2889   |
| 1.0541        | 5.0   | 270  | 1.3630          | 0.3333   |
| 1.0131        | 6.0   | 324  | 1.3253          | 0.3556   |
| 0.9769        | 7.0   | 378  | 1.2881          | 0.4      |
| 0.9492        | 8.0   | 432  | 1.2530          | 0.4667   |
| 0.8247        | 9.0   | 486  | 1.2242          | 0.4889   |
| 0.7827        | 10.0  | 540  | 1.1958          | 0.5111   |
| 0.7699        | 11.0  | 594  | 1.1711          | 0.5556   |
| 0.7392        | 12.0  | 648  | 1.1426          | 0.5556   |
| 0.6925        | 13.0  | 702  | 1.1224          | 0.6      |
| 0.6619        | 14.0  | 756  | 1.0987          | 0.6222   |
| 0.6147        | 15.0  | 810  | 1.0801          | 0.6222   |
| 0.6121        | 16.0  | 864  | 1.0592          | 0.6222   |
| 0.6227        | 17.0  | 918  | 1.0464          | 0.6222   |
| 0.5807        | 18.0  | 972  | 1.0281          | 0.6222   |
| 0.5992        | 19.0  | 1026 | 1.0150          | 0.6222   |
| 0.5798        | 20.0  | 1080 | 1.0051          | 0.6222   |
| 0.5423        | 21.0  | 1134 | 0.9959          | 0.6444   |
| 0.5106        | 22.0  | 1188 | 0.9897          | 0.6444   |
| 0.4892        | 23.0  | 1242 | 0.9795          | 0.6222   |
| 0.4483        | 24.0  | 1296 | 0.9703          | 0.6222   |
| 0.4736        | 25.0  | 1350 | 0.9611          | 0.6222   |
| 0.4227        | 26.0  | 1404 | 0.9520          | 0.6222   |
| 0.4302        | 27.0  | 1458 | 0.9440          | 0.6222   |
| 0.4126        | 28.0  | 1512 | 0.9427          | 0.6      |
| 0.4069        | 29.0  | 1566 | 0.9390          | 0.6222   |
| 0.3885        | 30.0  | 1620 | 0.9331          | 0.6222   |
| 0.3939        | 31.0  | 1674 | 0.9262          | 0.6222   |
| 0.4293        | 32.0  | 1728 | 0.9199          | 0.6      |
| 0.3557        | 33.0  | 1782 | 0.9148          | 0.6      |
| 0.321         | 34.0  | 1836 | 0.9127          | 0.6      |
| 0.3874        | 35.0  | 1890 | 0.9095          | 0.6      |
| 0.3474        | 36.0  | 1944 | 0.9080          | 0.6      |
| 0.359         | 37.0  | 1998 | 0.9077          | 0.6      |
| 0.354         | 38.0  | 2052 | 0.9053          | 0.6      |
| 0.3279        | 39.0  | 2106 | 0.9029          | 0.6      |
| 0.3224        | 40.0  | 2160 | 0.9031          | 0.6      |
| 0.3381        | 41.0  | 2214 | 0.9020          | 0.6      |
| 0.3078        | 42.0  | 2268 | 0.9023          | 0.6      |
| 0.3967        | 43.0  | 2322 | 0.9005          | 0.6      |
| 0.3475        | 44.0  | 2376 | 0.8993          | 0.6      |
| 0.3398        | 45.0  | 2430 | 0.8986          | 0.6      |
| 0.3474        | 46.0  | 2484 | 0.8979          | 0.6      |
| 0.3756        | 47.0  | 2538 | 0.8974          | 0.6      |
| 0.2921        | 48.0  | 2592 | 0.8973          | 0.6      |
| 0.4069        | 49.0  | 2646 | 0.8970          | 0.6      |
| 0.3442        | 50.0  | 2700 | 0.8970          | 0.6      |


### 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_SGD_lr001_fold2", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imagefolder", "type": "imagefolder", "config": "default", "split": "test", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.6, "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