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# HUSHEM_1x_beit_large_RMSProp_lr00001_fold1

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: 0.7656
- Accuracy: 0.8222

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.5135        | 1.0   | 11   | 1.1082          | 0.6      |
| 0.7494        | 2.0   | 22   | 0.8165          | 0.6444   |
| 0.2062        | 3.0   | 33   | 0.9435          | 0.7556   |
| 0.096         | 4.0   | 44   | 0.6338          | 0.8444   |
| 0.0381        | 5.0   | 55   | 1.5321          | 0.6667   |
| 0.026         | 6.0   | 66   | 0.8781          | 0.8222   |
| 0.0008        | 7.0   | 77   | 0.8880          | 0.8      |
| 0.001         | 8.0   | 88   | 0.8571          | 0.8222   |
| 0.0005        | 9.0   | 99   | 0.8753          | 0.8222   |
| 0.0002        | 10.0  | 110  | 0.7600          | 0.8      |
| 0.0002        | 11.0  | 121  | 0.7567          | 0.8222   |
| 0.0001        | 12.0  | 132  | 0.7444          | 0.8      |
| 0.0001        | 13.0  | 143  | 0.7700          | 0.8222   |
| 0.0001        | 14.0  | 154  | 0.7651          | 0.8222   |
| 0.0001        | 15.0  | 165  | 0.7669          | 0.8222   |
| 0.0001        | 16.0  | 176  | 0.7625          | 0.8222   |
| 0.0001        | 17.0  | 187  | 0.7953          | 0.8222   |
| 0.0001        | 18.0  | 198  | 0.7937          | 0.8222   |
| 0.0001        | 19.0  | 209  | 0.7988          | 0.8222   |
| 0.0001        | 20.0  | 220  | 0.7800          | 0.8222   |
| 0.0001        | 21.0  | 231  | 0.7851          | 0.8222   |
| 0.0001        | 22.0  | 242  | 0.7944          | 0.8222   |
| 0.0001        | 23.0  | 253  | 0.8228          | 0.8222   |
| 0.0001        | 24.0  | 264  | 0.8055          | 0.8222   |
| 0.0001        | 25.0  | 275  | 0.8096          | 0.8222   |
| 0.0           | 26.0  | 286  | 0.8172          | 0.8222   |
| 0.0001        | 27.0  | 297  | 0.8094          | 0.8222   |
| 0.0           | 28.0  | 308  | 0.8202          | 0.8222   |
| 0.0           | 29.0  | 319  | 0.8221          | 0.8222   |
| 0.0022        | 30.0  | 330  | 0.5867          | 0.8222   |
| 0.0001        | 31.0  | 341  | 0.6917          | 0.8222   |
| 0.0           | 32.0  | 352  | 0.7028          | 0.8222   |
| 0.0           | 33.0  | 363  | 0.7214          | 0.8222   |
| 0.0001        | 34.0  | 374  | 0.7274          | 0.8222   |
| 0.0           | 35.0  | 385  | 0.7373          | 0.8222   |
| 0.0           | 36.0  | 396  | 0.7425          | 0.8222   |
| 0.0           | 37.0  | 407  | 0.7520          | 0.8222   |
| 0.0           | 38.0  | 418  | 0.7543          | 0.8222   |
| 0.0           | 39.0  | 429  | 0.7471          | 0.8222   |
| 0.0           | 40.0  | 440  | 0.7551          | 0.8222   |
| 0.0           | 41.0  | 451  | 0.7600          | 0.8222   |
| 0.0           | 42.0  | 462  | 0.7629          | 0.8222   |
| 0.0           | 43.0  | 473  | 0.7643          | 0.8222   |
| 0.0           | 44.0  | 484  | 0.7646          | 0.8222   |
| 0.0           | 45.0  | 495  | 0.7655          | 0.8222   |
| 0.0           | 46.0  | 506  | 0.7656          | 0.8222   |
| 0.0           | 47.0  | 517  | 0.7656          | 0.8222   |
| 0.0           | 48.0  | 528  | 0.7656          | 0.8222   |
| 0.0           | 49.0  | 539  | 0.7656          | 0.8222   |
| 0.0           | 50.0  | 550  | 0.7656          | 0.8222   |


### 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_lr00001_fold1", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imagefolder", "type": "imagefolder", "config": "default", "split": "test", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.8222222222222222, "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