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# Swin_transformer_dent_detection

This model is a fine-tuned version of [microsoft/swin-base-patch4-window7-224-in22k](https://huggingface.co/microsoft/swin-base-patch4-window7-224-in22k) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6854
- Accuracy: 0.55
- F1: 0.55
- Recall: 0.55
- Precision: 0.55

## 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: 5e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1   | Recall | Precision |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:----:|:------:|:---------:|
| No log        | 0.8   | 1    | 0.6854          | 0.55     | 0.55 | 0.55   | 0.55      |
| No log        | 1.8   | 2    | 0.9226          | 0.55     | 0.55 | 0.55   | 0.55      |
| No log        | 2.8   | 3    | 0.8610          | 0.55     | 0.55 | 0.55   | 0.55      |


### Framework versions

- Transformers 4.23.1
- Pytorch 1.13.0
- Datasets 2.6.1
- Tokenizers 0.13.1

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["imagefolder"], "metrics": ["accuracy", "f1", "recall", "precision"], "model-index": [{"name": "Swin_transformer_dent_detection", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imagefolder", "type": "imagefolder", "config": "default", "split": "train", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.55, "name": "Accuracy"}, {"type": "f1", "value": 0.55, "name": "F1"}, {"type": "recall", "value": 0.55, "name": "Recall"}, {"type": "precision", "value": 0.55, "name": "Precision"}]}]}]}
transformers pytorch tensorboard swin image-classification generated_from_trainer dataset:imagefolder license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us