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# hushem_40x_beit_large_sgd_lr001_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: 0.5109
- Accuracy: 0.8444

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.8994        | 1.0   | 429   | 1.3432          | 0.3111   |
| 0.7531        | 2.0   | 858   | 1.1818          | 0.3778   |
| 0.5263        | 3.0   | 1287  | 1.0006          | 0.4889   |
| 0.3368        | 4.0   | 1716  | 0.8416          | 0.6444   |
| 0.2929        | 5.0   | 2145  | 0.7330          | 0.7556   |
| 0.2265        | 6.0   | 2574  | 0.6919          | 0.7778   |
| 0.1571        | 7.0   | 3003  | 0.6041          | 0.8667   |
| 0.1129        | 8.0   | 3432  | 0.5638          | 0.8667   |
| 0.1148        | 9.0   | 3861  | 0.5630          | 0.8444   |
| 0.0769        | 10.0  | 4290  | 0.5237          | 0.8667   |
| 0.0881        | 11.0  | 4719  | 0.4878          | 0.8444   |
| 0.0653        | 12.0  | 5148  | 0.4839          | 0.8444   |
| 0.0462        | 13.0  | 5577  | 0.4855          | 0.8444   |
| 0.0372        | 14.0  | 6006  | 0.5072          | 0.8222   |
| 0.0549        | 15.0  | 6435  | 0.4617          | 0.8444   |
| 0.0434        | 16.0  | 6864  | 0.4728          | 0.8444   |
| 0.0603        | 17.0  | 7293  | 0.4238          | 0.8444   |
| 0.0152        | 18.0  | 7722  | 0.4615          | 0.8444   |
| 0.0361        | 19.0  | 8151  | 0.4850          | 0.8222   |
| 0.0339        | 20.0  | 8580  | 0.4558          | 0.8444   |
| 0.0361        | 21.0  | 9009  | 0.4432          | 0.8444   |
| 0.0188        | 22.0  | 9438  | 0.4559          | 0.8444   |
| 0.0111        | 23.0  | 9867  | 0.4531          | 0.8444   |
| 0.018         | 24.0  | 10296 | 0.4481          | 0.8444   |
| 0.0089        | 25.0  | 10725 | 0.4882          | 0.8222   |
| 0.007         | 26.0  | 11154 | 0.4621          | 0.8222   |
| 0.005         | 27.0  | 11583 | 0.4548          | 0.8222   |
| 0.0118        | 28.0  | 12012 | 0.4703          | 0.8222   |
| 0.0166        | 29.0  | 12441 | 0.4907          | 0.8222   |
| 0.0067        | 30.0  | 12870 | 0.4835          | 0.8222   |
| 0.0031        | 31.0  | 13299 | 0.4928          | 0.8222   |
| 0.0067        | 32.0  | 13728 | 0.4925          | 0.8222   |
| 0.0069        | 33.0  | 14157 | 0.4945          | 0.8444   |
| 0.0076        | 34.0  | 14586 | 0.4959          | 0.8444   |
| 0.0052        | 35.0  | 15015 | 0.4972          | 0.8444   |
| 0.0025        | 36.0  | 15444 | 0.4893          | 0.8222   |
| 0.0065        | 37.0  | 15873 | 0.4702          | 0.8444   |
| 0.0099        | 38.0  | 16302 | 0.5146          | 0.8222   |
| 0.0052        | 39.0  | 16731 | 0.5006          | 0.8444   |
| 0.0021        | 40.0  | 17160 | 0.5245          | 0.8444   |
| 0.006         | 41.0  | 17589 | 0.5002          | 0.8444   |
| 0.0055        | 42.0  | 18018 | 0.4995          | 0.8444   |
| 0.0034        | 43.0  | 18447 | 0.4846          | 0.8444   |
| 0.0023        | 44.0  | 18876 | 0.4911          | 0.8444   |
| 0.0033        | 45.0  | 19305 | 0.5106          | 0.8444   |
| 0.0034        | 46.0  | 19734 | 0.5087          | 0.8444   |
| 0.0024        | 47.0  | 20163 | 0.5234          | 0.8444   |
| 0.0029        | 48.0  | 20592 | 0.5071          | 0.8444   |
| 0.0032        | 49.0  | 21021 | 0.5115          | 0.8444   |
| 0.0014        | 50.0  | 21450 | 0.5109          | 0.8444   |


### Framework versions

- Transformers 4.35.0
- Pytorch 2.1.0
- Datasets 2.14.6
- Tokenizers 0.14.1

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["imagefolder"], "metrics": ["accuracy"], "base_model": "microsoft/beit-large-patch16-224", "model-index": [{"name": "hushem_40x_beit_large_sgd_lr001_fold1", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imagefolder", "type": "imagefolder", "config": "default", "split": "test", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.8444444444444444, "name": "Accuracy"}]}]}]}
transformers safetensors 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