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# HUSHEM_10x_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: 7.7157
- Accuracy: 0.5111

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.2176        | 1.0   | 107  | 1.6491          | 0.2667   |
| 0.963         | 2.0   | 214  | 1.4710          | 0.4      |
| 0.7117        | 3.0   | 321  | 1.9132          | 0.5333   |
| 0.6943        | 4.0   | 428  | 2.2665          | 0.4889   |
| 0.7762        | 5.0   | 535  | 2.1960          | 0.4444   |
| 0.5908        | 6.0   | 642  | 2.6804          | 0.4889   |
| 0.5946        | 7.0   | 749  | 3.1791          | 0.5333   |
| 0.5552        | 8.0   | 856  | 2.6041          | 0.5111   |
| 0.571         | 9.0   | 963  | 2.5400          | 0.5556   |
| 0.4122        | 10.0  | 1070 | 2.7344          | 0.5778   |
| 0.4723        | 11.0  | 1177 | 2.3569          | 0.5333   |
| 0.411         | 12.0  | 1284 | 2.2110          | 0.5111   |
| 0.3793        | 13.0  | 1391 | 2.5000          | 0.4      |
| 0.3666        | 14.0  | 1498 | 2.5085          | 0.5333   |
| 0.3408        | 15.0  | 1605 | 3.1692          | 0.5556   |
| 0.3208        | 16.0  | 1712 | 2.7896          | 0.5111   |
| 0.3406        | 17.0  | 1819 | 3.3458          | 0.4222   |
| 0.2975        | 18.0  | 1926 | 3.3304          | 0.5333   |
| 0.3398        | 19.0  | 2033 | 3.5372          | 0.5111   |
| 0.2078        | 20.0  | 2140 | 3.5756          | 0.6      |
| 0.1292        | 21.0  | 2247 | 3.3537          | 0.5778   |
| 0.2162        | 22.0  | 2354 | 3.2880          | 0.5333   |
| 0.2256        | 23.0  | 2461 | 4.0207          | 0.5333   |
| 0.1133        | 24.0  | 2568 | 4.2521          | 0.4889   |
| 0.2321        | 25.0  | 2675 | 4.2081          | 0.4889   |
| 0.2146        | 26.0  | 2782 | 4.7757          | 0.5556   |
| 0.1959        | 27.0  | 2889 | 4.2098          | 0.5333   |
| 0.0731        | 28.0  | 2996 | 6.9173          | 0.5333   |
| 0.1238        | 29.0  | 3103 | 7.3091          | 0.5111   |
| 0.1033        | 30.0  | 3210 | 5.5935          | 0.5556   |
| 0.1306        | 31.0  | 3317 | 5.5057          | 0.5556   |
| 0.0379        | 32.0  | 3424 | 4.7954          | 0.6      |
| 0.0944        | 33.0  | 3531 | 6.3010          | 0.5556   |
| 0.1412        | 34.0  | 3638 | 5.7780          | 0.5556   |
| 0.2037        | 35.0  | 3745 | 5.8795          | 0.5111   |
| 0.0176        | 36.0  | 3852 | 7.1343          | 0.5556   |
| 0.0277        | 37.0  | 3959 | 7.2272          | 0.5111   |
| 0.0018        | 38.0  | 4066 | 7.3217          | 0.5333   |
| 0.0446        | 39.0  | 4173 | 7.7775          | 0.5556   |
| 0.1019        | 40.0  | 4280 | 8.0136          | 0.5556   |
| 0.0178        | 41.0  | 4387 | 6.2682          | 0.5556   |
| 0.0775        | 42.0  | 4494 | 6.8370          | 0.5333   |
| 0.006         | 43.0  | 4601 | 6.8949          | 0.5556   |
| 0.0264        | 44.0  | 4708 | 7.1082          | 0.5111   |
| 0.1324        | 45.0  | 4815 | 7.9954          | 0.5111   |
| 0.0007        | 46.0  | 4922 | 7.5464          | 0.5111   |
| 0.0273        | 47.0  | 5029 | 7.3512          | 0.5111   |
| 0.0001        | 48.0  | 5136 | 7.6084          | 0.5111   |
| 0.0183        | 49.0  | 5243 | 7.6246          | 0.5111   |
| 0.0           | 50.0  | 5350 | 7.7157          | 0.5111   |


### 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_10x_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": 0.5111111111111111, "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