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# vit-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: 0.5465
- Accuracy: 0.8040

## 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 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: 3

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 0.8497        | 0.2077 | 100  | 0.6552          | 0.7754   |
| 0.7899        | 0.4155 | 200  | 0.6210          | 0.7806   |
| 0.7952        | 0.6232 | 300  | 0.6013          | 0.7876   |
| 0.7838        | 0.8310 | 400  | 0.5912          | 0.7891   |
| 0.7701        | 1.0374 | 500  | 0.5825          | 0.7920   |
| 0.75          | 1.2451 | 600  | 0.5841          | 0.7927   |
| 0.743         | 1.4529 | 700  | 0.5807          | 0.7916   |
| 0.7443        | 1.6606 | 800  | 0.5793          | 0.7939   |
| 0.7298        | 1.8683 | 900  | 0.5776          | 0.7938   |
| 0.7024        | 2.0748 | 1000 | 0.5859          | 0.7903   |
| 0.6962        | 2.2825 | 1100 | 0.5854          | 0.7910   |
| 0.6824        | 2.4903 | 1200 | 0.5603          | 0.8014   |
| 0.6653        | 2.6980 | 1300 | 0.5544          | 0.8016   |
| 0.6614        | 2.9057 | 1400 | 0.5468          | 0.8041   |


### Framework versions

- Transformers 4.47.0
- Pytorch 2.5.1+cu121
- Datasets 3.3.1
- Tokenizers 0.21.0

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