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# HUSHEM_1x_beit_large_RMSProp_lr0001_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: 5.4058
- Accuracy: 0.5556

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 3.8107        | 1.0   | 11   | 3.6022          | 0.2444   |
| 2.3718        | 2.0   | 22   | 1.3999          | 0.2444   |
| 1.4804        | 3.0   | 33   | 1.5241          | 0.2444   |
| 1.465         | 4.0   | 44   | 1.3468          | 0.3556   |
| 1.484         | 5.0   | 55   | 1.4735          | 0.2444   |
| 1.3229        | 6.0   | 66   | 1.1734          | 0.4444   |
| 1.4267        | 7.0   | 77   | 1.7896          | 0.2444   |
| 1.2779        | 8.0   | 88   | 1.2247          | 0.3778   |
| 1.2987        | 9.0   | 99   | 1.2184          | 0.3778   |
| 1.1948        | 10.0  | 110  | 1.4130          | 0.3111   |
| 1.1981        | 11.0  | 121  | 1.2852          | 0.3778   |
| 1.1732        | 12.0  | 132  | 1.1056          | 0.5333   |
| 1.125         | 13.0  | 143  | 1.1349          | 0.3556   |
| 1.2119        | 14.0  | 154  | 1.2211          | 0.4667   |
| 1.0616        | 15.0  | 165  | 1.3610          | 0.4      |
| 0.9835        | 16.0  | 176  | 1.0333          | 0.5556   |
| 1.0119        | 17.0  | 187  | 0.9941          | 0.5333   |
| 0.8418        | 18.0  | 198  | 1.3067          | 0.5333   |
| 0.7708        | 19.0  | 209  | 1.2289          | 0.5111   |
| 0.6407        | 20.0  | 220  | 1.2999          | 0.5778   |
| 0.601         | 21.0  | 231  | 1.2161          | 0.6      |
| 0.5038        | 22.0  | 242  | 1.5685          | 0.5778   |
| 0.5754        | 23.0  | 253  | 2.0250          | 0.5333   |
| 0.4191        | 24.0  | 264  | 1.0475          | 0.6      |
| 0.4447        | 25.0  | 275  | 1.8741          | 0.5778   |
| 0.3373        | 26.0  | 286  | 2.8759          | 0.6      |
| 0.4463        | 27.0  | 297  | 2.4766          | 0.6222   |
| 0.1658        | 28.0  | 308  | 2.4411          | 0.5778   |
| 0.2668        | 29.0  | 319  | 2.2972          | 0.6      |
| 0.2096        | 30.0  | 330  | 2.3595          | 0.5778   |
| 0.1322        | 31.0  | 341  | 4.3494          | 0.6222   |
| 0.1567        | 32.0  | 352  | 3.4902          | 0.6222   |
| 0.1402        | 33.0  | 363  | 4.2926          | 0.6      |
| 0.2325        | 34.0  | 374  | 4.8269          | 0.5778   |
| 0.1268        | 35.0  | 385  | 4.4256          | 0.6222   |
| 0.0627        | 36.0  | 396  | 5.4161          | 0.5556   |
| 0.0476        | 37.0  | 407  | 5.2700          | 0.5778   |
| 0.0487        | 38.0  | 418  | 5.5263          | 0.6      |
| 0.0326        | 39.0  | 429  | 5.4463          | 0.5778   |
| 0.0449        | 40.0  | 440  | 5.6757          | 0.5333   |
| 0.0005        | 41.0  | 451  | 5.2536          | 0.5333   |
| 0.0944        | 42.0  | 462  | 5.3760          | 0.5778   |
| 0.0114        | 43.0  | 473  | 5.6873          | 0.5333   |
| 0.0164        | 44.0  | 484  | 5.4874          | 0.5333   |
| 0.0689        | 45.0  | 495  | 5.4051          | 0.5556   |
| 0.0437        | 46.0  | 506  | 5.4058          | 0.5556   |
| 0.061         | 47.0  | 517  | 5.4058          | 0.5556   |
| 0.0568        | 48.0  | 528  | 5.4058          | 0.5556   |
| 0.0004        | 49.0  | 539  | 5.4058          | 0.5556   |
| 0.0153        | 50.0  | 550  | 5.4058          | 0.5556   |


### 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_fold2", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imagefolder", "type": "imagefolder", "config": "default", "split": "test", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.5555555555555556, "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