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# SMIDS_10x_beit_base_sgd_lr0001_fold1

This model is a fine-tuned version of [microsoft/beit-base-patch16-224](https://huggingface.co/microsoft/beit-base-patch16-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4077
- Accuracy: 0.8331

## 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: 32
- eval_batch_size: 32
- 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.9365        | 1.0   | 751   | 1.0533          | 0.4274   |
| 0.801         | 2.0   | 1502  | 0.9239          | 0.5275   |
| 0.7365        | 3.0   | 2253  | 0.8262          | 0.6277   |
| 0.6791        | 4.0   | 3004  | 0.7553          | 0.6962   |
| 0.6171        | 5.0   | 3755  | 0.7026          | 0.7279   |
| 0.5731        | 6.0   | 4506  | 0.6630          | 0.7479   |
| 0.553         | 7.0   | 5257  | 0.6307          | 0.7730   |
| 0.5239        | 8.0   | 6008  | 0.6058          | 0.7796   |
| 0.5269        | 9.0   | 6759  | 0.5854          | 0.7896   |
| 0.5199        | 10.0  | 7510  | 0.5652          | 0.7896   |
| 0.557         | 11.0  | 8261  | 0.5496          | 0.7913   |
| 0.4881        | 12.0  | 9012  | 0.5363          | 0.7913   |
| 0.484         | 13.0  | 9763  | 0.5245          | 0.7980   |
| 0.4826        | 14.0  | 10514 | 0.5128          | 0.7997   |
| 0.4428        | 15.0  | 11265 | 0.5034          | 0.8013   |
| 0.5097        | 16.0  | 12016 | 0.4929          | 0.8013   |
| 0.4392        | 17.0  | 12767 | 0.4850          | 0.7997   |
| 0.4678        | 18.0  | 13518 | 0.4784          | 0.8047   |
| 0.4541        | 19.0  | 14269 | 0.4716          | 0.8063   |
| 0.42          | 20.0  | 15020 | 0.4658          | 0.8130   |
| 0.3515        | 21.0  | 15771 | 0.4597          | 0.8180   |
| 0.4252        | 22.0  | 16522 | 0.4538          | 0.8214   |
| 0.3647        | 23.0  | 17273 | 0.4489          | 0.8280   |
| 0.3789        | 24.0  | 18024 | 0.4445          | 0.8280   |
| 0.3924        | 25.0  | 18775 | 0.4409          | 0.8264   |
| 0.3771        | 26.0  | 19526 | 0.4384          | 0.8264   |
| 0.4198        | 27.0  | 20277 | 0.4344          | 0.8297   |
| 0.4311        | 28.0  | 21028 | 0.4318          | 0.8297   |
| 0.4234        | 29.0  | 21779 | 0.4295          | 0.8280   |
| 0.397         | 30.0  | 22530 | 0.4266          | 0.8280   |
| 0.3948        | 31.0  | 23281 | 0.4248          | 0.8280   |
| 0.3687        | 32.0  | 24032 | 0.4230          | 0.8314   |
| 0.3883        | 33.0  | 24783 | 0.4203          | 0.8314   |
| 0.3212        | 34.0  | 25534 | 0.4193          | 0.8297   |
| 0.3218        | 35.0  | 26285 | 0.4181          | 0.8331   |
| 0.3571        | 36.0  | 27036 | 0.4167          | 0.8314   |
| 0.417         | 37.0  | 27787 | 0.4151          | 0.8314   |
| 0.3685        | 38.0  | 28538 | 0.4136          | 0.8314   |
| 0.3339        | 39.0  | 29289 | 0.4133          | 0.8314   |
| 0.3277        | 40.0  | 30040 | 0.4120          | 0.8331   |
| 0.4236        | 41.0  | 30791 | 0.4110          | 0.8314   |
| 0.3466        | 42.0  | 31542 | 0.4101          | 0.8331   |
| 0.3999        | 43.0  | 32293 | 0.4096          | 0.8331   |
| 0.3495        | 44.0  | 33044 | 0.4088          | 0.8331   |
| 0.4002        | 45.0  | 33795 | 0.4085          | 0.8331   |
| 0.357         | 46.0  | 34546 | 0.4082          | 0.8331   |
| 0.3629        | 47.0  | 35297 | 0.4080          | 0.8331   |
| 0.3253        | 48.0  | 36048 | 0.4078          | 0.8331   |
| 0.369         | 49.0  | 36799 | 0.4077          | 0.8331   |
| 0.4327        | 50.0  | 37550 | 0.4077          | 0.8331   |


### 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-base-patch16-224", "model-index": [{"name": "SMIDS_10x_beit_base_sgd_lr0001_fold1", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imagefolder", "type": "imagefolder", "config": "default", "split": "test", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.8330550918196995, "name": "Accuracy"}]}]}]}
transformers safetensors beit image-classification generated_from_trainer dataset:imagefolder base_model:microsoft/beit-base-patch16-224 license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us