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# pretrained_result

This model is a fine-tuned version of [motheecreator/vit-Facial-Expression-Recognition](https://huggingface.co/motheecreator/vit-Facial-Expression-Recognition) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6537
- Accuracy: 0.7843

## 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 |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 0.6131        | 0.9904 | 90   | 0.6537          | 0.7843   |
| 0.5963        | 1.9904 | 180  | 0.6502          | 0.7824   |
| 0.5716        | 2.9904 | 270  | 0.6506          | 0.7783   |
| 0.5616        | 3.9904 | 360  | 0.6429          | 0.7821   |
| 0.5272        | 4.9904 | 450  | 0.6516          | 0.7772   |
| 0.5064        | 5.9904 | 540  | 0.6446          | 0.7764   |


### Framework versions

- Transformers 4.48.2
- Pytorch 2.6.0+cu126
- Datasets 3.2.0
- Tokenizers 0.21.0

angry contempt disgust fear happy neutral sad surprise