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# SMIDS_1x_beit_large_RMSProp_lr0001_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: 1.4643
- Accuracy: 0.83

## 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: 0.0001
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.8266        | 1.0   | 150  | 0.8112          | 0.56     |
| 0.8444        | 2.0   | 300  | 0.7996          | 0.605    |
| 0.6941        | 3.0   | 450  | 0.6035          | 0.725    |
| 0.6737        | 4.0   | 600  | 0.6341          | 0.7383   |
| 0.4878        | 5.0   | 750  | 0.5894          | 0.76     |
| 0.5403        | 6.0   | 900  | 0.6041          | 0.7317   |
| 0.4943        | 7.0   | 1050 | 0.6457          | 0.7417   |
| 0.4218        | 8.0   | 1200 | 0.5819          | 0.7783   |
| 0.467         | 9.0   | 1350 | 0.6056          | 0.7333   |
| 0.4329        | 10.0  | 1500 | 0.5028          | 0.8133   |
| 0.4591        | 11.0  | 1650 | 0.4947          | 0.82     |
| 0.365         | 12.0  | 1800 | 0.4430          | 0.8317   |
| 0.2817        | 13.0  | 1950 | 0.6377          | 0.7867   |
| 0.2019        | 14.0  | 2100 | 0.7043          | 0.8283   |
| 0.1119        | 15.0  | 2250 | 0.7357          | 0.8183   |
| 0.2291        | 16.0  | 2400 | 0.8531          | 0.7867   |
| 0.1881        | 17.0  | 2550 | 0.9245          | 0.805    |
| 0.1977        | 18.0  | 2700 | 0.8381          | 0.8233   |
| 0.0808        | 19.0  | 2850 | 1.0013          | 0.8133   |
| 0.1163        | 20.0  | 3000 | 1.1394          | 0.8283   |
| 0.0356        | 21.0  | 3150 | 1.0908          | 0.83     |
| 0.1479        | 22.0  | 3300 | 1.1198          | 0.7983   |
| 0.0677        | 23.0  | 3450 | 1.1073          | 0.8083   |
| 0.0915        | 24.0  | 3600 | 1.1142          | 0.8167   |
| 0.0776        | 25.0  | 3750 | 1.2448          | 0.805    |
| 0.0573        | 26.0  | 3900 | 1.1691          | 0.8233   |
| 0.0885        | 27.0  | 4050 | 1.1900          | 0.805    |
| 0.1276        | 28.0  | 4200 | 1.0890          | 0.8283   |
| 0.0282        | 29.0  | 4350 | 1.3288          | 0.8183   |
| 0.1332        | 30.0  | 4500 | 0.9922          | 0.8233   |
| 0.033         | 31.0  | 4650 | 1.4762          | 0.805    |
| 0.0512        | 32.0  | 4800 | 1.3289          | 0.8167   |
| 0.0057        | 33.0  | 4950 | 1.3948          | 0.82     |
| 0.0117        | 34.0  | 5100 | 1.4781          | 0.8117   |
| 0.0005        | 35.0  | 5250 | 1.4098          | 0.8117   |
| 0.0037        | 36.0  | 5400 | 1.5700          | 0.81     |
| 0.0004        | 37.0  | 5550 | 1.5218          | 0.825    |
| 0.0383        | 38.0  | 5700 | 1.2339          | 0.8283   |
| 0.0213        | 39.0  | 5850 | 1.4567          | 0.8267   |
| 0.0554        | 40.0  | 6000 | 1.3905          | 0.8267   |
| 0.0007        | 41.0  | 6150 | 1.5787          | 0.8267   |
| 0.0019        | 42.0  | 6300 | 1.5439          | 0.8267   |
| 0.0158        | 43.0  | 6450 | 1.5566          | 0.8133   |
| 0.0002        | 44.0  | 6600 | 1.5614          | 0.835    |
| 0.0693        | 45.0  | 6750 | 1.5616          | 0.8317   |
| 0.0381        | 46.0  | 6900 | 1.4872          | 0.84     |
| 0.0134        | 47.0  | 7050 | 1.4782          | 0.835    |
| 0.0008        | 48.0  | 7200 | 1.5174          | 0.8283   |
| 0.0001        | 49.0  | 7350 | 1.4686          | 0.8317   |
| 0.0001        | 50.0  | 7500 | 1.4643          | 0.83     |


### Framework versions

- Transformers 4.32.1
- Pytorch 2.0.1
- Datasets 2.12.0
- Tokenizers 0.13.2

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["imagefolder"], "metrics": ["accuracy"], "base_model": "microsoft/beit-large-patch16-224", "model-index": [{"name": "SMIDS_1x_beit_large_RMSProp_lr0001_fold3", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imagefolder", "type": "imagefolder", "config": "default", "split": "test", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.83, "name": "Accuracy"}]}]}]}
transformers pytorch 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