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# vit-emotion-output

This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 1.3454
- Accuracy: 0.4875

## 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: 5e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- 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: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.6596        | 1.0   | 40   | 1.6180          | 0.3187   |
| 0.9457        | 2.0   | 80   | 1.5013          | 0.3375   |
| 0.498         | 3.0   | 120  | 1.3814          | 0.4437   |
| 0.2755        | 4.0   | 160  | 1.3854          | 0.4688   |
| 0.1628        | 5.0   | 200  | 1.3454          | 0.4875   |


### Framework versions

- Transformers 4.51.3
- Pytorch 2.6.0+cu124
- Datasets 3.6.0
- Tokenizers 0.21.1

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