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# HUSHEM_1x_beit_large_RMSProp_lr0001_fold5

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: 7.0287
- Accuracy: 0.5366

## 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: 0.0001
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.411         | 1.0   | 11   | 1.4125          | 0.2683   |
| 1.4537        | 2.0   | 22   | 1.3742          | 0.2683   |
| 1.3833        | 3.0   | 33   | 1.6498          | 0.2439   |
| 1.4094        | 4.0   | 44   | 1.3056          | 0.2927   |
| 1.3445        | 5.0   | 55   | 1.4206          | 0.3902   |
| 1.268         | 6.0   | 66   | 1.1642          | 0.4634   |
| 1.224         | 7.0   | 77   | 1.1064          | 0.4390   |
| 1.1851        | 8.0   | 88   | 1.3701          | 0.4634   |
| 1.0882        | 9.0   | 99   | 1.4213          | 0.2195   |
| 1.0002        | 10.0  | 110  | 1.0499          | 0.4878   |
| 0.8912        | 11.0  | 121  | 1.0392          | 0.5122   |
| 0.796         | 12.0  | 132  | 1.3430          | 0.4146   |
| 0.7722        | 13.0  | 143  | 1.1345          | 0.5366   |
| 0.5123        | 14.0  | 154  | 1.4514          | 0.5854   |
| 0.6356        | 15.0  | 165  | 1.2238          | 0.5366   |
| 0.6111        | 16.0  | 176  | 2.1701          | 0.5366   |
| 0.4001        | 17.0  | 187  | 1.6698          | 0.5366   |
| 0.4282        | 18.0  | 198  | 1.6902          | 0.5122   |
| 0.3674        | 19.0  | 209  | 2.2313          | 0.5366   |
| 0.2484        | 20.0  | 220  | 2.4302          | 0.5366   |
| 0.2973        | 21.0  | 231  | 2.8171          | 0.6585   |
| 0.2224        | 22.0  | 242  | 4.4832          | 0.5122   |
| 0.1043        | 23.0  | 253  | 6.0663          | 0.5122   |
| 0.1635        | 24.0  | 264  | 3.5818          | 0.5610   |
| 0.181         | 25.0  | 275  | 3.8199          | 0.5366   |
| 0.0657        | 26.0  | 286  | 7.6741          | 0.4146   |
| 0.0058        | 27.0  | 297  | 5.4097          | 0.5366   |
| 0.0634        | 28.0  | 308  | 4.1952          | 0.6098   |
| 0.0591        | 29.0  | 319  | 5.5582          | 0.5854   |
| 0.0186        | 30.0  | 330  | 6.4272          | 0.5122   |
| 0.1127        | 31.0  | 341  | 6.9246          | 0.4878   |
| 0.0507        | 32.0  | 352  | 6.2447          | 0.5366   |
| 0.1239        | 33.0  | 363  | 5.5756          | 0.6098   |
| 0.0691        | 34.0  | 374  | 6.5472          | 0.6341   |
| 0.0028        | 35.0  | 385  | 7.2873          | 0.5366   |
| 0.0248        | 36.0  | 396  | 6.8124          | 0.5610   |
| 0.0099        | 37.0  | 407  | 6.8225          | 0.5366   |
| 0.1121        | 38.0  | 418  | 7.8090          | 0.4878   |
| 0.0329        | 39.0  | 429  | 7.2140          | 0.4878   |
| 0.0254        | 40.0  | 440  | 7.4569          | 0.4878   |
| 0.0032        | 41.0  | 451  | 7.0338          | 0.5610   |
| 0.0003        | 42.0  | 462  | 6.8283          | 0.5854   |
| 0.0795        | 43.0  | 473  | 7.0519          | 0.5366   |
| 0.0003        | 44.0  | 484  | 7.0553          | 0.5366   |
| 0.0001        | 45.0  | 495  | 7.0561          | 0.5366   |
| 0.0704        | 46.0  | 506  | 7.0287          | 0.5366   |
| 0.0           | 47.0  | 517  | 7.0287          | 0.5366   |
| 0.0903        | 48.0  | 528  | 7.0287          | 0.5366   |
| 0.0228        | 49.0  | 539  | 7.0287          | 0.5366   |
| 0.0009        | 50.0  | 550  | 7.0287          | 0.5366   |


### 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_1x_beit_large_RMSProp_lr0001_fold5", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imagefolder", "type": "imagefolder", "config": "default", "split": "test", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.5365853658536586, "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