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# hushem_40x_beit_large_rmsprop_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: 5.1978
- Accuracy: 0.6889

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.7584        | 1.0   | 429   | 1.1132          | 0.5333   |
| 0.5809        | 2.0   | 858   | 1.2163          | 0.4      |
| 0.7377        | 3.0   | 1287  | 2.1595          | 0.4444   |
| 0.4897        | 4.0   | 1716  | 1.2992          | 0.4889   |
| 0.6257        | 5.0   | 2145  | 2.2735          | 0.4444   |
| 0.2903        | 6.0   | 2574  | 2.3656          | 0.5333   |
| 0.2582        | 7.0   | 3003  | 2.0374          | 0.5333   |
| 0.1924        | 8.0   | 3432  | 1.7074          | 0.5556   |
| 0.1661        | 9.0   | 3861  | 1.6205          | 0.6      |
| 0.1314        | 10.0  | 4290  | 1.4356          | 0.6444   |
| 0.0581        | 11.0  | 4719  | 1.5915          | 0.6222   |
| 0.0844        | 12.0  | 5148  | 1.9419          | 0.6667   |
| 0.0497        | 13.0  | 5577  | 2.5857          | 0.5778   |
| 0.0268        | 14.0  | 6006  | 2.5665          | 0.6      |
| 0.0659        | 15.0  | 6435  | 2.2800          | 0.6667   |
| 0.0627        | 16.0  | 6864  | 2.5899          | 0.6444   |
| 0.1291        | 17.0  | 7293  | 2.9142          | 0.6222   |
| 0.0073        | 18.0  | 7722  | 3.3622          | 0.6222   |
| 0.0316        | 19.0  | 8151  | 2.1936          | 0.7111   |
| 0.0715        | 20.0  | 8580  | 2.4865          | 0.6889   |
| 0.0428        | 21.0  | 9009  | 3.5288          | 0.6444   |
| 0.0279        | 22.0  | 9438  | 3.4124          | 0.6      |
| 0.0383        | 23.0  | 9867  | 2.7663          | 0.6222   |
| 0.0013        | 24.0  | 10296 | 2.9801          | 0.6      |
| 0.0039        | 25.0  | 10725 | 3.8223          | 0.6444   |
| 0.0003        | 26.0  | 11154 | 3.6240          | 0.5778   |
| 0.0115        | 27.0  | 11583 | 3.2695          | 0.7111   |
| 0.0652        | 28.0  | 12012 | 3.9061          | 0.6222   |
| 0.0003        | 29.0  | 12441 | 3.3292          | 0.6222   |
| 0.0055        | 30.0  | 12870 | 2.9576          | 0.6444   |
| 0.0001        | 31.0  | 13299 | 3.7674          | 0.6667   |
| 0.0679        | 32.0  | 13728 | 3.8730          | 0.6889   |
| 0.0177        | 33.0  | 14157 | 3.9174          | 0.6      |
| 0.0           | 34.0  | 14586 | 4.6339          | 0.6222   |
| 0.0012        | 35.0  | 15015 | 5.3916          | 0.6222   |
| 0.0           | 36.0  | 15444 | 5.7139          | 0.5778   |
| 0.0           | 37.0  | 15873 | 6.1659          | 0.5778   |
| 0.0001        | 38.0  | 16302 | 3.7207          | 0.7111   |
| 0.0001        | 39.0  | 16731 | 4.4681          | 0.6889   |
| 0.0           | 40.0  | 17160 | 4.8896          | 0.6667   |
| 0.0           | 41.0  | 17589 | 3.6896          | 0.6889   |
| 0.0004        | 42.0  | 18018 | 4.3804          | 0.6889   |
| 0.0           | 43.0  | 18447 | 4.5124          | 0.6889   |
| 0.0           | 44.0  | 18876 | 4.8035          | 0.6889   |
| 0.0           | 45.0  | 19305 | 5.0660          | 0.6667   |
| 0.0           | 46.0  | 19734 | 4.9910          | 0.6667   |
| 0.0           | 47.0  | 20163 | 5.1895          | 0.6667   |
| 0.0           | 48.0  | 20592 | 5.1384          | 0.6889   |
| 0.0           | 49.0  | 21021 | 5.1600          | 0.6889   |
| 0.0           | 50.0  | 21450 | 5.1978          | 0.6889   |


### 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_rmsprop_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": 0.6888888888888889, "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