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# RAFDB-Facial-Expression-Recognition

This model is a fine-tuned version of [motheecreator/vit-Facial-Expression-Recognition](https://huggingface.co/motheecreator/vit-Facial-Expression-Recognition) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5251
- Accuracy: 0.8198

## 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: 3e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 256
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 1000
- num_epochs: 10

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 2.0294        | 2.0833 | 100  | 1.7424          | 0.4547   |
| 0.8701        | 4.1667 | 200  | 0.7676          | 0.7324   |
| 0.6327        | 6.25   | 300  | 0.5953          | 0.7934   |
| 0.5058        | 8.3333 | 400  | 0.5574          | 0.8106   |


### Framework versions

- Transformers 4.46.2
- Pytorch 2.5.1+cu124
- Datasets 3.1.0
- Tokenizers 0.20.3

surprise fear disgust happiness sadness anger neutral