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# hushem_40x_beit_large_sgd_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: 0.4863
- Accuracy: 0.8372

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 1.042         | 1.0   | 434   | 1.0626          | 0.6279   |
| 0.6858        | 2.0   | 868   | 0.7065          | 0.7674   |
| 0.4118        | 3.0   | 1302  | 0.5370          | 0.7907   |
| 0.2724        | 4.0   | 1736  | 0.4399          | 0.8372   |
| 0.2346        | 5.0   | 2170  | 0.3933          | 0.8372   |
| 0.1735        | 6.0   | 2604  | 0.3712          | 0.8605   |
| 0.1557        | 7.0   | 3038  | 0.3679          | 0.8605   |
| 0.1125        | 8.0   | 3472  | 0.3456          | 0.8837   |
| 0.0946        | 9.0   | 3906  | 0.3427          | 0.8837   |
| 0.0707        | 10.0  | 4340  | 0.3487          | 0.8605   |
| 0.0654        | 11.0  | 4774  | 0.3536          | 0.8605   |
| 0.0387        | 12.0  | 5208  | 0.3814          | 0.8605   |
| 0.0242        | 13.0  | 5642  | 0.3547          | 0.8605   |
| 0.0194        | 14.0  | 6076  | 0.3531          | 0.8605   |
| 0.02          | 15.0  | 6510  | 0.3812          | 0.8372   |
| 0.026         | 16.0  | 6944  | 0.4118          | 0.8372   |
| 0.0232        | 17.0  | 7378  | 0.3963          | 0.8372   |
| 0.0087        | 18.0  | 7812  | 0.4087          | 0.8372   |
| 0.0126        | 19.0  | 8246  | 0.4558          | 0.8372   |
| 0.0098        | 20.0  | 8680  | 0.4308          | 0.8372   |
| 0.0184        | 21.0  | 9114  | 0.4212          | 0.8372   |
| 0.0065        | 22.0  | 9548  | 0.4332          | 0.8372   |
| 0.0177        | 23.0  | 9982  | 0.4547          | 0.8372   |
| 0.0045        | 24.0  | 10416 | 0.4348          | 0.8372   |
| 0.0077        | 25.0  | 10850 | 0.4558          | 0.8372   |
| 0.0084        | 26.0  | 11284 | 0.4243          | 0.8372   |
| 0.0085        | 27.0  | 11718 | 0.4734          | 0.8372   |
| 0.0041        | 28.0  | 12152 | 0.4614          | 0.8372   |
| 0.0042        | 29.0  | 12586 | 0.4664          | 0.8372   |
| 0.0132        | 30.0  | 13020 | 0.4304          | 0.8372   |
| 0.0051        | 31.0  | 13454 | 0.4562          | 0.8372   |
| 0.0027        | 32.0  | 13888 | 0.4517          | 0.8372   |
| 0.0053        | 33.0  | 14322 | 0.4373          | 0.8372   |
| 0.0081        | 34.0  | 14756 | 0.4381          | 0.8372   |
| 0.002         | 35.0  | 15190 | 0.4734          | 0.8372   |
| 0.0074        | 36.0  | 15624 | 0.4464          | 0.8372   |
| 0.0141        | 37.0  | 16058 | 0.4757          | 0.8372   |
| 0.0037        | 38.0  | 16492 | 0.4834          | 0.8372   |
| 0.0024        | 39.0  | 16926 | 0.4681          | 0.8372   |
| 0.0054        | 40.0  | 17360 | 0.4669          | 0.8372   |
| 0.0022        | 41.0  | 17794 | 0.4624          | 0.8372   |
| 0.0015        | 42.0  | 18228 | 0.4733          | 0.8372   |
| 0.0028        | 43.0  | 18662 | 0.4797          | 0.8372   |
| 0.0049        | 44.0  | 19096 | 0.4749          | 0.8372   |
| 0.0021        | 45.0  | 19530 | 0.4669          | 0.8372   |
| 0.0041        | 46.0  | 19964 | 0.4747          | 0.8372   |
| 0.0037        | 47.0  | 20398 | 0.4820          | 0.8372   |
| 0.0084        | 48.0  | 20832 | 0.4852          | 0.8372   |
| 0.0026        | 49.0  | 21266 | 0.4886          | 0.8372   |
| 0.0023        | 50.0  | 21700 | 0.4863          | 0.8372   |


### 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_fold3", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imagefolder", "type": "imagefolder", "config": "default", "split": "test", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.8372093023255814, "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