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# vit-emotion-model

This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1329
- Accuracy: 0.575

## 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: 8
- eval_batch_size: 8
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.5767        | 1.0   | 80   | 1.3573          | 0.4875   |
| 0.8289        | 2.0   | 160  | 1.1968          | 0.4938   |
| 0.3138        | 3.0   | 240  | 1.0986          | 0.5687   |
| 0.0858        | 4.0   | 320  | 1.1277          | 0.5687   |
| 0.0471        | 5.0   | 400  | 1.1329          | 0.575    |


### Framework versions

- Transformers 4.48.3
- Pytorch 2.5.1+cu124
- Tokenizers 0.21.0

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