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# HUSHEM_10x_beit_large_RMSProp_lr001_fold3

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: 3.1932
- Accuracy: 0.5349

## 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: 0.001
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.3973        | 1.0   | 109  | 1.6403          | 0.2558   |
| 1.3902        | 2.0   | 218  | 1.3838          | 0.2558   |
| 1.3908        | 3.0   | 327  | 1.2694          | 0.4884   |
| 1.2917        | 4.0   | 436  | 1.0790          | 0.5116   |
| 1.23          | 5.0   | 545  | 2.4533          | 0.4419   |
| 1.268         | 6.0   | 654  | 1.0491          | 0.5349   |
| 1.2087        | 7.0   | 763  | 1.2867          | 0.2791   |
| 1.0852        | 8.0   | 872  | 1.1142          | 0.3721   |
| 0.9988        | 9.0   | 981  | 0.9401          | 0.6047   |
| 0.8497        | 10.0  | 1090 | 1.0888          | 0.5116   |
| 0.9077        | 11.0  | 1199 | 0.8114          | 0.6744   |
| 0.8566        | 12.0  | 1308 | 0.6552          | 0.7674   |
| 0.8077        | 13.0  | 1417 | 0.6949          | 0.7442   |
| 0.8889        | 14.0  | 1526 | 0.7845          | 0.6512   |
| 0.8359        | 15.0  | 1635 | 0.7094          | 0.6977   |
| 0.9499        | 16.0  | 1744 | 0.5989          | 0.7674   |
| 0.7911        | 17.0  | 1853 | 0.6037          | 0.7674   |
| 0.8259        | 18.0  | 1962 | 0.8681          | 0.6744   |
| 0.86          | 19.0  | 2071 | 0.6874          | 0.6279   |
| 0.8252        | 20.0  | 2180 | 0.4812          | 0.7907   |
| 0.7847        | 21.0  | 2289 | 1.6038          | 0.4651   |
| 0.7039        | 22.0  | 2398 | 0.9644          | 0.6047   |
| 0.7461        | 23.0  | 2507 | 0.7259          | 0.7674   |
| 0.7146        | 24.0  | 2616 | 0.7651          | 0.6512   |
| 0.7479        | 25.0  | 2725 | 0.7214          | 0.6977   |
| 0.7816        | 26.0  | 2834 | 0.7340          | 0.7209   |
| 0.6474        | 27.0  | 2943 | 0.6391          | 0.7209   |
| 0.6392        | 28.0  | 3052 | 0.9881          | 0.6977   |
| 0.5164        | 29.0  | 3161 | 1.9224          | 0.5814   |
| 0.6899        | 30.0  | 3270 | 0.7667          | 0.6047   |
| 0.639         | 31.0  | 3379 | 1.1157          | 0.5581   |
| 0.642         | 32.0  | 3488 | 1.0061          | 0.6279   |
| 0.5487        | 33.0  | 3597 | 0.9308          | 0.6512   |
| 0.4763        | 34.0  | 3706 | 1.2588          | 0.6744   |
| 0.5816        | 35.0  | 3815 | 1.7911          | 0.5814   |
| 0.5297        | 36.0  | 3924 | 1.1474          | 0.5814   |
| 0.4493        | 37.0  | 4033 | 1.3151          | 0.5814   |
| 0.4529        | 38.0  | 4142 | 1.4707          | 0.6512   |
| 0.3031        | 39.0  | 4251 | 1.4752          | 0.5349   |
| 0.3389        | 40.0  | 4360 | 1.8395          | 0.6047   |
| 0.3548        | 41.0  | 4469 | 1.4790          | 0.6047   |
| 0.27          | 42.0  | 4578 | 2.3755          | 0.4884   |
| 0.2389        | 43.0  | 4687 | 1.9620          | 0.5116   |
| 0.1666        | 44.0  | 4796 | 2.3401          | 0.6279   |
| 0.3121        | 45.0  | 4905 | 1.8768          | 0.5581   |
| 0.2724        | 46.0  | 5014 | 2.9735          | 0.5349   |
| 0.1134        | 47.0  | 5123 | 3.1799          | 0.4651   |
| 0.17          | 48.0  | 5232 | 3.2744          | 0.5814   |
| 0.1443        | 49.0  | 5341 | 3.2161          | 0.5581   |
| 0.0825        | 50.0  | 5450 | 3.1932          | 0.5349   |


### 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_lr001_fold3", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imagefolder", "type": "imagefolder", "config": "default", "split": "test", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.5348837209302325, "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