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# HUSHEM_1x_beit_large_RMSProp_lr00001_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: 0.8929
- Accuracy: 0.8537

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.2277        | 1.0   | 11   | 1.1890          | 0.5122   |
| 1.1626        | 2.0   | 22   | 0.7331          | 0.7317   |
| 0.3926        | 3.0   | 33   | 0.4804          | 0.7805   |
| 0.1604        | 4.0   | 44   | 0.6564          | 0.8293   |
| 0.1132        | 5.0   | 55   | 0.5418          | 0.8049   |
| 0.0429        | 6.0   | 66   | 0.4660          | 0.9024   |
| 0.0167        | 7.0   | 77   | 0.5772          | 0.8780   |
| 0.0008        | 8.0   | 88   | 0.5998          | 0.8537   |
| 0.0005        | 9.0   | 99   | 0.5746          | 0.8780   |
| 0.0003        | 10.0  | 110  | 0.5787          | 0.8780   |
| 0.0002        | 11.0  | 121  | 0.5920          | 0.8780   |
| 0.0002        | 12.0  | 132  | 0.6550          | 0.8780   |
| 0.0011        | 13.0  | 143  | 0.5851          | 0.8537   |
| 0.0002        | 14.0  | 154  | 0.6172          | 0.8780   |
| 0.0002        | 15.0  | 165  | 0.6285          | 0.8780   |
| 0.0001        | 16.0  | 176  | 0.6315          | 0.8780   |
| 0.0001        | 17.0  | 187  | 0.6453          | 0.8780   |
| 0.0001        | 18.0  | 198  | 0.6571          | 0.8780   |
| 0.0001        | 19.0  | 209  | 0.7264          | 0.8780   |
| 0.0001        | 20.0  | 220  | 0.7282          | 0.8780   |
| 0.0001        | 21.0  | 231  | 0.7337          | 0.8780   |
| 0.0001        | 22.0  | 242  | 0.7137          | 0.8780   |
| 0.0001        | 23.0  | 253  | 0.7288          | 0.8780   |
| 0.0001        | 24.0  | 264  | 0.7390          | 0.8780   |
| 0.0001        | 25.0  | 275  | 0.7420          | 0.8780   |
| 0.0           | 26.0  | 286  | 0.7838          | 0.8780   |
| 0.0001        | 27.0  | 297  | 0.7903          | 0.8780   |
| 0.0           | 28.0  | 308  | 0.7897          | 0.8780   |
| 0.0           | 29.0  | 319  | 0.7899          | 0.8780   |
| 0.0001        | 30.0  | 330  | 0.7842          | 0.8780   |
| 0.0001        | 31.0  | 341  | 0.7378          | 0.8780   |
| 0.0           | 32.0  | 352  | 0.7457          | 0.8780   |
| 0.0           | 33.0  | 363  | 0.7489          | 0.8780   |
| 0.0           | 34.0  | 374  | 0.7511          | 0.8780   |
| 0.0002        | 35.0  | 385  | 0.8330          | 0.8537   |
| 0.0           | 36.0  | 396  | 0.8724          | 0.8537   |
| 0.0001        | 37.0  | 407  | 0.8730          | 0.8537   |
| 0.0           | 38.0  | 418  | 0.8725          | 0.8537   |
| 0.0           | 39.0  | 429  | 0.8727          | 0.8537   |
| 0.0           | 40.0  | 440  | 0.8742          | 0.8537   |
| 0.0002        | 41.0  | 451  | 0.8988          | 0.8537   |
| 0.0           | 42.0  | 462  | 0.8976          | 0.8537   |
| 0.0           | 43.0  | 473  | 0.8979          | 0.8537   |
| 0.0           | 44.0  | 484  | 0.8931          | 0.8537   |
| 0.0           | 45.0  | 495  | 0.8929          | 0.8537   |
| 0.0           | 46.0  | 506  | 0.8929          | 0.8537   |
| 0.0           | 47.0  | 517  | 0.8929          | 0.8537   |
| 0.0           | 48.0  | 528  | 0.8929          | 0.8537   |
| 0.0001        | 49.0  | 539  | 0.8929          | 0.8537   |
| 0.0           | 50.0  | 550  | 0.8929          | 0.8537   |


### 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_fold5", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imagefolder", "type": "imagefolder", "config": "default", "split": "test", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.8536585365853658, "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