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# emotion_image_classification

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: 1.1587
- Accuracy: 0.6

## 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: 7e-05
- train_batch_size: 12
- eval_batch_size: 12
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 54   | 1.6922          | 0.2875   |
| No log        | 2.0   | 108  | 1.4183          | 0.4688   |
| No log        | 3.0   | 162  | 1.3431          | 0.4437   |
| No log        | 4.0   | 216  | 1.1979          | 0.5437   |
| No log        | 5.0   | 270  | 1.1368          | 0.6188   |
| No log        | 6.0   | 324  | 1.1457          | 0.5875   |
| No log        | 7.0   | 378  | 1.1509          | 0.575    |
| No log        | 8.0   | 432  | 1.1037          | 0.5938   |
| No log        | 9.0   | 486  | 1.1060          | 0.575    |
| 1.1174        | 10.0  | 540  | 1.1083          | 0.5938   |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.17.0
- Tokenizers 0.15.2

anger contempt disgust fear happy neutral sad surprise