
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# SMIDS_5x_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: 0.5373
- Accuracy: 0.8314

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.9508        | 1.0   | 751   | 0.9623          | 0.5042   |
| 0.9158        | 2.0   | 1502  | 1.2458          | 0.4558   |
| 0.7288        | 3.0   | 2253  | 0.8795          | 0.5192   |
| 0.7665        | 4.0   | 3004  | 0.7490          | 0.6327   |
| 0.7357        | 5.0   | 3755  | 0.7471          | 0.6544   |
| 0.7239        | 6.0   | 4506  | 0.7541          | 0.6377   |
| 0.6766        | 7.0   | 5257  | 0.7003          | 0.6778   |
| 0.6493        | 8.0   | 6008  | 0.6606          | 0.7078   |
| 0.6321        | 9.0   | 6759  | 0.6736          | 0.6945   |
| 0.5374        | 10.0  | 7510  | 0.6601          | 0.7078   |
| 0.5955        | 11.0  | 8261  | 0.7247          | 0.6711   |
| 0.5842        | 12.0  | 9012  | 0.7263          | 0.7012   |
| 0.58          | 13.0  | 9763  | 0.6257          | 0.7412   |
| 0.6657        | 14.0  | 10514 | 0.5798          | 0.7563   |
| 0.6335        | 15.0  | 11265 | 0.6134          | 0.7396   |
| 0.4955        | 16.0  | 12016 | 0.5570          | 0.7780   |
| 0.5728        | 17.0  | 12767 | 0.6069          | 0.7629   |
| 0.4804        | 18.0  | 13518 | 0.5579          | 0.7730   |
| 0.4554        | 19.0  | 14269 | 0.6213          | 0.7563   |
| 0.41          | 20.0  | 15020 | 0.5850          | 0.7780   |
| 0.4487        | 21.0  | 15771 | 0.5539          | 0.7863   |
| 0.3739        | 22.0  | 16522 | 0.5627          | 0.7696   |
| 0.5195        | 23.0  | 17273 | 0.5213          | 0.7830   |
| 0.4251        | 24.0  | 18024 | 0.5584          | 0.7730   |
| 0.4039        | 25.0  | 18775 | 0.5416          | 0.7947   |
| 0.4211        | 26.0  | 19526 | 0.6174          | 0.7529   |
| 0.4196        | 27.0  | 20277 | 0.5472          | 0.7947   |
| 0.3277        | 28.0  | 21028 | 0.5246          | 0.7997   |
| 0.4094        | 29.0  | 21779 | 0.5561          | 0.7896   |
| 0.4819        | 30.0  | 22530 | 0.5868          | 0.7813   |
| 0.5419        | 31.0  | 23281 | 0.5076          | 0.8030   |
| 0.3837        | 32.0  | 24032 | 0.4830          | 0.8130   |
| 0.2546        | 33.0  | 24783 | 0.5543          | 0.8180   |
| 0.2568        | 34.0  | 25534 | 0.5630          | 0.8030   |
| 0.31          | 35.0  | 26285 | 0.5202          | 0.8030   |
| 0.43          | 36.0  | 27036 | 0.5432          | 0.8097   |
| 0.3133        | 37.0  | 27787 | 0.5182          | 0.8080   |
| 0.3267        | 38.0  | 28538 | 0.5481          | 0.8080   |
| 0.2754        | 39.0  | 29289 | 0.5192          | 0.8197   |
| 0.3633        | 40.0  | 30040 | 0.5041          | 0.8331   |
| 0.2904        | 41.0  | 30791 | 0.4819          | 0.8397   |
| 0.3607        | 42.0  | 31542 | 0.5470          | 0.7963   |
| 0.291         | 43.0  | 32293 | 0.5200          | 0.8314   |
| 0.2816        | 44.0  | 33044 | 0.5393          | 0.8297   |
| 0.2919        | 45.0  | 33795 | 0.5389          | 0.8431   |
| 0.1991        | 46.0  | 34546 | 0.5219          | 0.8331   |
| 0.219         | 47.0  | 35297 | 0.5203          | 0.8297   |
| 0.2008        | 48.0  | 36048 | 0.5363          | 0.8331   |
| 0.2199        | 49.0  | 36799 | 0.5364          | 0.8314   |
| 0.2434        | 50.0  | 37550 | 0.5373          | 0.8314   |


### 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_5x_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": 0.8313856427378965, "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