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# blurred_faces

This model is a fine-tuned version of [microsoft/resnet-50](https://huggingface.co/microsoft/resnet-50) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0414
- Accuracy: 0.9964

## 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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.514         | 1.0   | 144  | 0.4884          | 0.9358   |
| 0.242         | 2.0   | 288  | 0.1377          | 0.9893   |
| 0.1592        | 2.99  | 432  | 0.0736          | 0.9902   |
| 0.0956        | 4.0   | 577  | 0.0488          | 0.9955   |
| 0.1734        | 4.99  | 720  | 0.0414          | 0.9964   |


### Framework versions

- Transformers 4.30.0.dev0
- Pytorch 1.13.0
- Datasets 2.10.1
- Tokenizers 0.11.0

ffhq_res256 sd_aligned