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# HUSHEM_1x_beit_large_RMSProp_lr0001_fold4

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: 4.1752
- Accuracy: 0.5952

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 3.4609        | 1.0   | 11   | 2.3102          | 0.2619   |
| 1.803         | 2.0   | 22   | 1.4780          | 0.2381   |
| 1.4521        | 3.0   | 33   | 1.4252          | 0.2619   |
| 1.3971        | 4.0   | 44   | 1.3192          | 0.5238   |
| 1.4084        | 5.0   | 55   | 1.2608          | 0.6905   |
| 1.3423        | 6.0   | 66   | 1.0942          | 0.5476   |
| 1.3352        | 7.0   | 77   | 1.1367          | 0.4762   |
| 1.2625        | 8.0   | 88   | 0.9477          | 0.5952   |
| 1.0642        | 9.0   | 99   | 0.8864          | 0.6667   |
| 0.9987        | 10.0  | 110  | 0.8179          | 0.6905   |
| 0.9326        | 11.0  | 121  | 0.8351          | 0.6667   |
| 0.9356        | 12.0  | 132  | 0.7174          | 0.7381   |
| 0.9512        | 13.0  | 143  | 0.7916          | 0.7143   |
| 0.8293        | 14.0  | 154  | 0.8575          | 0.5952   |
| 0.7825        | 15.0  | 165  | 0.7921          | 0.7619   |
| 0.776         | 16.0  | 176  | 1.0116          | 0.6667   |
| 0.7171        | 17.0  | 187  | 0.9161          | 0.6429   |
| 0.6522        | 18.0  | 198  | 1.2832          | 0.4048   |
| 0.7577        | 19.0  | 209  | 0.9092          | 0.7143   |
| 0.6166        | 20.0  | 220  | 1.2325          | 0.5714   |
| 0.4914        | 21.0  | 231  | 1.9848          | 0.5      |
| 0.4458        | 22.0  | 242  | 1.5565          | 0.6190   |
| 0.4219        | 23.0  | 253  | 1.2716          | 0.6429   |
| 0.4401        | 24.0  | 264  | 1.9499          | 0.5952   |
| 0.4017        | 25.0  | 275  | 1.9150          | 0.6190   |
| 0.3112        | 26.0  | 286  | 1.8155          | 0.7143   |
| 0.3008        | 27.0  | 297  | 1.9089          | 0.6905   |
| 0.2877        | 28.0  | 308  | 2.8986          | 0.6429   |
| 0.2083        | 29.0  | 319  | 2.4784          | 0.6905   |
| 0.2888        | 30.0  | 330  | 3.3901          | 0.5476   |
| 0.3113        | 31.0  | 341  | 4.0123          | 0.6667   |
| 0.1503        | 32.0  | 352  | 3.3514          | 0.6190   |
| 0.0556        | 33.0  | 363  | 3.9057          | 0.6429   |
| 0.1249        | 34.0  | 374  | 3.3066          | 0.5952   |
| 0.0977        | 35.0  | 385  | 5.0505          | 0.5952   |
| 0.0308        | 36.0  | 396  | 4.1795          | 0.6190   |
| 0.0764        | 37.0  | 407  | 4.2703          | 0.6429   |
| 0.1657        | 38.0  | 418  | 3.1543          | 0.6190   |
| 0.1858        | 39.0  | 429  | 4.1003          | 0.6190   |
| 0.0207        | 40.0  | 440  | 4.2887          | 0.6190   |
| 0.0208        | 41.0  | 451  | 4.5150          | 0.6190   |
| 0.0006        | 42.0  | 462  | 4.5100          | 0.5952   |
| 0.0269        | 43.0  | 473  | 4.2925          | 0.5952   |
| 0.0634        | 44.0  | 484  | 4.1527          | 0.5952   |
| 0.0496        | 45.0  | 495  | 4.1725          | 0.5952   |
| 0.0354        | 46.0  | 506  | 4.1752          | 0.5952   |
| 0.0049        | 47.0  | 517  | 4.1752          | 0.5952   |
| 0.0014        | 48.0  | 528  | 4.1752          | 0.5952   |
| 0.0571        | 49.0  | 539  | 4.1752          | 0.5952   |
| 0.1079        | 50.0  | 550  | 4.1752          | 0.5952   |


### 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_fold4", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imagefolder", "type": "imagefolder", "config": "default", "split": "test", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.5952380952380952, "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