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# vit-emotion

This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.6412
- Accuracy: 0.45

## 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: 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: 10
- label_smoothing_factor: 0.1

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 80   | 2.0356          | 0.2      |
| 2.0342        | 2.0   | 160  | 1.8868          | 0.3312   |
| 1.7429        | 3.0   | 240  | 1.7304          | 0.4188   |
| 1.4173        | 4.0   | 320  | 1.6726          | 0.4125   |
| 1.1255        | 5.0   | 400  | 1.6412          | 0.45     |
| 1.1255        | 6.0   | 480  | 1.6340          | 0.4375   |
| 0.8705        | 7.0   | 560  | 1.6473          | 0.4188   |
| 0.7143        | 8.0   | 640  | 1.6618          | 0.425    |
| 0.6206        | 9.0   | 720  | 1.6705          | 0.4313   |
| 0.5788        | 10.0  | 800  | 1.6769          | 0.4313   |


### Framework versions

- Transformers 4.48.3
- Pytorch 2.5.1+cu124
- Tokenizers 0.21.0

label_0 label_1 label_2 label_3 label_4 label_5 label_6 label_7