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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: 0.3652
- Accuracy: 0.8771

## 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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 1000
- num_epochs: 3

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 0.5697        | 0.2164 | 100  | 0.3684          | 0.8756   |
| 0.5697        | 0.4328 | 200  | 0.3664          | 0.8763   |
| 0.5708        | 0.6492 | 300  | 0.3643          | 0.8763   |
| 0.5829        | 0.8656 | 400  | 0.3661          | 0.8754   |
| 0.5458        | 1.0820 | 500  | 0.3652          | 0.8771   |
| 0.5635        | 1.2984 | 600  | 0.3702          | 0.8748   |
| 0.5495        | 1.5147 | 700  | 0.3767          | 0.8694   |
| 0.5633        | 1.7311 | 800  | 0.3848          | 0.8659   |
| 0.5666        | 1.9475 | 900  | 0.3882          | 0.8655   |
| 0.5284        | 2.1639 | 1000 | 0.3914          | 0.8640   |
| 0.5135        | 2.3803 | 1100 | 0.3824          | 0.8679   |
| 0.5036        | 2.5967 | 1200 | 0.3726          | 0.8722   |
| 0.4927        | 2.8131 | 1300 | 0.3664          | 0.8739   |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.2.0
- Tokenizers 0.19.1

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