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# hushem_40x_beit_large_sgd_lr001_fold4

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: 0.0740
- Accuracy: 0.9524

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 1.0662        | 1.0   | 437   | 1.0521          | 0.5714   |
| 0.7203        | 2.0   | 874   | 0.7246          | 0.7381   |
| 0.5049        | 3.0   | 1311  | 0.5289          | 0.8095   |
| 0.335         | 4.0   | 1748  | 0.4123          | 0.8571   |
| 0.2897        | 5.0   | 2185  | 0.3108          | 0.9524   |
| 0.2138        | 6.0   | 2622  | 0.2584          | 0.9524   |
| 0.1576        | 7.0   | 3059  | 0.2229          | 0.9524   |
| 0.1514        | 8.0   | 3496  | 0.1954          | 0.9524   |
| 0.168         | 9.0   | 3933  | 0.1669          | 0.9524   |
| 0.0911        | 10.0  | 4370  | 0.1589          | 0.9524   |
| 0.0943        | 11.0  | 4807  | 0.1416          | 0.9524   |
| 0.0714        | 12.0  | 5244  | 0.1336          | 0.9524   |
| 0.0531        | 13.0  | 5681  | 0.1238          | 0.9524   |
| 0.0757        | 14.0  | 6118  | 0.1203          | 0.9524   |
| 0.0408        | 15.0  | 6555  | 0.1187          | 0.9524   |
| 0.0419        | 16.0  | 6992  | 0.1120          | 0.9524   |
| 0.0492        | 17.0  | 7429  | 0.1073          | 0.9524   |
| 0.0319        | 18.0  | 7866  | 0.1094          | 0.9524   |
| 0.0267        | 19.0  | 8303  | 0.1084          | 0.9524   |
| 0.0199        | 20.0  | 8740  | 0.0945          | 0.9524   |
| 0.0211        | 21.0  | 9177  | 0.0946          | 0.9524   |
| 0.0171        | 22.0  | 9614  | 0.0863          | 0.9524   |
| 0.0241        | 23.0  | 10051 | 0.0946          | 0.9524   |
| 0.0509        | 24.0  | 10488 | 0.0978          | 0.9524   |
| 0.0252        | 25.0  | 10925 | 0.0880          | 0.9524   |
| 0.0202        | 26.0  | 11362 | 0.0850          | 0.9524   |
| 0.0073        | 27.0  | 11799 | 0.0902          | 0.9524   |
| 0.0135        | 28.0  | 12236 | 0.0803          | 0.9524   |
| 0.0045        | 29.0  | 12673 | 0.0835          | 0.9524   |
| 0.0107        | 30.0  | 13110 | 0.0804          | 0.9524   |
| 0.0142        | 31.0  | 13547 | 0.0861          | 0.9524   |
| 0.0109        | 32.0  | 13984 | 0.0738          | 0.9524   |
| 0.0078        | 33.0  | 14421 | 0.0724          | 0.9524   |
| 0.0045        | 34.0  | 14858 | 0.0788          | 0.9524   |
| 0.0155        | 35.0  | 15295 | 0.0849          | 0.9524   |
| 0.0167        | 36.0  | 15732 | 0.0774          | 0.9524   |
| 0.0055        | 37.0  | 16169 | 0.0785          | 0.9524   |
| 0.0158        | 38.0  | 16606 | 0.0774          | 0.9524   |
| 0.003         | 39.0  | 17043 | 0.0762          | 0.9524   |
| 0.0037        | 40.0  | 17480 | 0.0776          | 0.9524   |
| 0.0124        | 41.0  | 17917 | 0.0776          | 0.9524   |
| 0.0044        | 42.0  | 18354 | 0.0788          | 0.9524   |
| 0.0131        | 43.0  | 18791 | 0.0764          | 0.9524   |
| 0.0079        | 44.0  | 19228 | 0.0761          | 0.9524   |
| 0.0185        | 45.0  | 19665 | 0.0772          | 0.9524   |
| 0.0023        | 46.0  | 20102 | 0.0771          | 0.9524   |
| 0.0031        | 47.0  | 20539 | 0.0752          | 0.9524   |
| 0.0029        | 48.0  | 20976 | 0.0748          | 0.9524   |
| 0.0045        | 49.0  | 21413 | 0.0742          | 0.9524   |
| 0.0112        | 50.0  | 21850 | 0.0740          | 0.9524   |


### 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_fold4", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imagefolder", "type": "imagefolder", "config": "default", "split": "test", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.9523809523809523, "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