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# emotion-classifier-vit

This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 1.2938
- Accuracy: 0.5437

## 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: 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: 13

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.9954        | 1.0   | 40   | 1.9657          | 0.3625   |
| 1.7379        | 2.0   | 80   | 1.7294          | 0.5      |
| 1.521         | 3.0   | 120  | 1.5916          | 0.5312   |
| 1.3358        | 4.0   | 160  | 1.5033          | 0.475    |
| 1.1573        | 5.0   | 200  | 1.4300          | 0.525    |
| 1.0019        | 6.0   | 240  | 1.3785          | 0.5312   |
| 0.8266        | 7.0   | 280  | 1.3402          | 0.5062   |
| 0.6911        | 8.0   | 320  | 1.2938          | 0.5437   |
| 0.5639        | 9.0   | 360  | 1.3023          | 0.5062   |
| 0.4955        | 10.0  | 400  | 1.2990          | 0.5125   |
| 0.4623        | 11.0  | 440  | 1.2864          | 0.5312   |
| 0.4193        | 12.0  | 480  | 1.2813          | 0.5188   |
| 0.4003        | 13.0  | 520  | 1.2815          | 0.5188   |


### Framework versions

- Transformers 4.51.3
- Pytorch 2.7.0+cu128
- Datasets 3.6.0
- Tokenizers 0.21.1

label_0 label_1 label_2 label_3 label_4 label_5 label_6 label_7