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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: 0.5369
- Accuracy: 0.8095

## 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 |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 0.8526        | 0.2077 | 100  | 0.6490          | 0.7761   |
| 0.8116        | 0.4155 | 200  | 0.6106          | 0.7860   |
| 0.7759        | 0.6232 | 300  | 0.5918          | 0.7908   |
| 0.7708        | 0.8310 | 400  | 0.5883          | 0.7904   |
| 0.75          | 1.0374 | 500  | 0.5749          | 0.7971   |
| 0.7496        | 1.2451 | 600  | 0.5737          | 0.7976   |
| 0.7601        | 1.4529 | 700  | 0.5698          | 0.7971   |
| 0.7516        | 1.6606 | 800  | 0.5692          | 0.7991   |
| 0.7359        | 1.8683 | 900  | 0.5740          | 0.7947   |
| 0.6968        | 2.0748 | 1000 | 0.5738          | 0.7953   |
| 0.6854        | 2.2825 | 1100 | 0.5617          | 0.7980   |
| 0.6992        | 2.4903 | 1200 | 0.5566          | 0.8030   |
| 0.6609        | 2.6980 | 1300 | 0.5495          | 0.8035   |
| 0.664         | 2.9057 | 1400 | 0.5370          | 0.8101   |


### Framework versions

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

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