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# HUSHEM_1x_beit_large_SGD_lr00001_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: 1.5756
- Accuracy: 0.3095

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.6437        | 1.0   | 11   | 1.5917          | 0.3333   |
| 1.6776        | 2.0   | 22   | 1.5909          | 0.3333   |
| 1.6201        | 3.0   | 33   | 1.5901          | 0.3333   |
| 1.6202        | 4.0   | 44   | 1.5894          | 0.3333   |
| 1.7279        | 5.0   | 55   | 1.5886          | 0.3333   |
| 1.5998        | 6.0   | 66   | 1.5880          | 0.3333   |
| 1.6782        | 7.0   | 77   | 1.5873          | 0.3333   |
| 1.583         | 8.0   | 88   | 1.5867          | 0.3333   |
| 1.6461        | 9.0   | 99   | 1.5860          | 0.3333   |
| 1.6348        | 10.0  | 110  | 1.5854          | 0.3095   |
| 1.6332        | 11.0  | 121  | 1.5849          | 0.3095   |
| 1.6378        | 12.0  | 132  | 1.5843          | 0.3095   |
| 1.6394        | 13.0  | 143  | 1.5838          | 0.3095   |
| 1.6132        | 14.0  | 154  | 1.5832          | 0.3095   |
| 1.6909        | 15.0  | 165  | 1.5827          | 0.3095   |
| 1.6063        | 16.0  | 176  | 1.5822          | 0.3095   |
| 1.629         | 17.0  | 187  | 1.5818          | 0.3095   |
| 1.6799        | 18.0  | 198  | 1.5813          | 0.3095   |
| 1.6436        | 19.0  | 209  | 1.5809          | 0.3095   |
| 1.6361        | 20.0  | 220  | 1.5805          | 0.3095   |
| 1.6414        | 21.0  | 231  | 1.5801          | 0.3095   |
| 1.6305        | 22.0  | 242  | 1.5797          | 0.3095   |
| 1.6415        | 23.0  | 253  | 1.5794          | 0.3095   |
| 1.7113        | 24.0  | 264  | 1.5790          | 0.3095   |
| 1.6384        | 25.0  | 275  | 1.5787          | 0.3095   |
| 1.6776        | 26.0  | 286  | 1.5784          | 0.3095   |
| 1.5901        | 27.0  | 297  | 1.5781          | 0.3095   |
| 1.6832        | 28.0  | 308  | 1.5778          | 0.3095   |
| 1.5844        | 29.0  | 319  | 1.5775          | 0.3095   |
| 1.6186        | 30.0  | 330  | 1.5773          | 0.3095   |
| 1.6267        | 31.0  | 341  | 1.5771          | 0.3095   |
| 1.642         | 32.0  | 352  | 1.5769          | 0.3095   |
| 1.6512        | 33.0  | 363  | 1.5767          | 0.3095   |
| 1.6503        | 34.0  | 374  | 1.5765          | 0.3095   |
| 1.713         | 35.0  | 385  | 1.5764          | 0.3095   |
| 1.5857        | 36.0  | 396  | 1.5762          | 0.3095   |
| 1.6563        | 37.0  | 407  | 1.5761          | 0.3095   |
| 1.6074        | 38.0  | 418  | 1.5760          | 0.3095   |
| 1.6939        | 39.0  | 429  | 1.5759          | 0.3095   |
| 1.6348        | 40.0  | 440  | 1.5758          | 0.3095   |
| 1.615         | 41.0  | 451  | 1.5757          | 0.3095   |
| 1.6495        | 42.0  | 462  | 1.5757          | 0.3095   |
| 1.609         | 43.0  | 473  | 1.5756          | 0.3095   |
| 1.7116        | 44.0  | 484  | 1.5756          | 0.3095   |
| 1.6353        | 45.0  | 495  | 1.5756          | 0.3095   |
| 1.6642        | 46.0  | 506  | 1.5756          | 0.3095   |
| 1.5818        | 47.0  | 517  | 1.5756          | 0.3095   |
| 1.6851        | 48.0  | 528  | 1.5756          | 0.3095   |
| 1.6399        | 49.0  | 539  | 1.5756          | 0.3095   |
| 1.6546        | 50.0  | 550  | 1.5756          | 0.3095   |


### 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_SGD_lr00001_fold4", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imagefolder", "type": "imagefolder", "config": "default", "split": "test", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.30952380952380953, "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