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# hushem_40x_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: 4.8840
- Accuracy: 0.6279

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 1.1111        | 1.0   | 434   | 1.3691          | 0.2791   |
| 0.9578        | 2.0   | 868   | 1.1462          | 0.4651   |
| 0.8729        | 3.0   | 1302  | 0.8085          | 0.7209   |
| 0.6503        | 4.0   | 1736  | 1.8174          | 0.3953   |
| 0.618         | 5.0   | 2170  | 0.8093          | 0.6744   |
| 0.5365        | 6.0   | 2604  | 0.8127          | 0.7209   |
| 0.5201        | 7.0   | 3038  | 1.1854          | 0.5814   |
| 0.3099        | 8.0   | 3472  | 1.2455          | 0.6744   |
| 0.348         | 9.0   | 3906  | 1.2285          | 0.6512   |
| 0.2484        | 10.0  | 4340  | 1.5069          | 0.6512   |
| 0.3996        | 11.0  | 4774  | 1.8330          | 0.6047   |
| 0.2246        | 12.0  | 5208  | 1.7345          | 0.6977   |
| 0.1378        | 13.0  | 5642  | 1.4594          | 0.6744   |
| 0.1162        | 14.0  | 6076  | 2.2416          | 0.6744   |
| 0.1271        | 15.0  | 6510  | 1.5886          | 0.6744   |
| 0.0926        | 16.0  | 6944  | 2.6945          | 0.6047   |
| 0.1208        | 17.0  | 7378  | 2.1295          | 0.6512   |
| 0.0088        | 18.0  | 7812  | 2.8145          | 0.5581   |
| 0.0171        | 19.0  | 8246  | 2.8093          | 0.5814   |
| 0.0292        | 20.0  | 8680  | 2.3651          | 0.6279   |
| 0.0619        | 21.0  | 9114  | 2.2113          | 0.7209   |
| 0.0945        | 22.0  | 9548  | 2.1158          | 0.6977   |
| 0.0809        | 23.0  | 9982  | 2.3787          | 0.6744   |
| 0.0334        | 24.0  | 10416 | 2.8543          | 0.6047   |
| 0.01          | 25.0  | 10850 | 2.2286          | 0.6512   |
| 0.0004        | 26.0  | 11284 | 2.9892          | 0.6744   |
| 0.028         | 27.0  | 11718 | 2.6161          | 0.6744   |
| 0.0498        | 28.0  | 12152 | 2.5592          | 0.6512   |
| 0.1281        | 29.0  | 12586 | 2.4255          | 0.6512   |
| 0.0009        | 30.0  | 13020 | 2.6867          | 0.6279   |
| 0.0013        | 31.0  | 13454 | 3.1579          | 0.6279   |
| 0.0           | 32.0  | 13888 | 3.2640          | 0.7209   |
| 0.0001        | 33.0  | 14322 | 3.1087          | 0.6744   |
| 0.0001        | 34.0  | 14756 | 3.7796          | 0.6047   |
| 0.0           | 35.0  | 15190 | 3.9663          | 0.6744   |
| 0.0001        | 36.0  | 15624 | 3.8623          | 0.6977   |
| 0.025         | 37.0  | 16058 | 3.4589          | 0.6512   |
| 0.0           | 38.0  | 16492 | 3.6738          | 0.6744   |
| 0.0           | 39.0  | 16926 | 4.0315          | 0.6279   |
| 0.0           | 40.0  | 17360 | 4.5257          | 0.6279   |
| 0.0           | 41.0  | 17794 | 4.9357          | 0.6279   |
| 0.0002        | 42.0  | 18228 | 4.2860          | 0.6279   |
| 0.0           | 43.0  | 18662 | 4.5524          | 0.6512   |
| 0.0           | 44.0  | 19096 | 4.6872          | 0.6279   |
| 0.0           | 45.0  | 19530 | 4.8559          | 0.6279   |
| 0.0           | 46.0  | 19964 | 5.3520          | 0.6512   |
| 0.0           | 47.0  | 20398 | 5.4098          | 0.6512   |
| 0.0           | 48.0  | 20832 | 4.7361          | 0.6512   |
| 0.0           | 49.0  | 21266 | 4.8609          | 0.6279   |
| 0.0           | 50.0  | 21700 | 4.8840          | 0.6279   |


### 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_fold3", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imagefolder", "type": "imagefolder", "config": "default", "split": "test", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.627906976744186, "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