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# emotion_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: 1.2002
- Accuracy: 0.6438

## 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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 12
- num_epochs: 15

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 40   | 1.9756          | 0.2313   |
| No log        | 2.0   | 80   | 1.6788          | 0.3937   |
| No log        | 3.0   | 120  | 1.5219          | 0.5375   |
| No log        | 4.0   | 160  | 1.4542          | 0.45     |
| No log        | 5.0   | 200  | 1.3923          | 0.5      |
| No log        | 6.0   | 240  | 1.3595          | 0.4437   |
| No log        | 7.0   | 280  | 1.3111          | 0.5125   |
| No log        | 8.0   | 320  | 1.2050          | 0.5625   |
| No log        | 9.0   | 360  | 1.2387          | 0.5437   |
| No log        | 10.0  | 400  | 1.2847          | 0.5437   |
| No log        | 11.0  | 440  | 1.2048          | 0.5625   |
| No log        | 12.0  | 480  | 1.2270          | 0.5563   |
| 1.0855        | 13.0  | 520  | 1.2058          | 0.5875   |
| 1.0855        | 14.0  | 560  | 1.1999          | 0.5625   |
| 1.0855        | 15.0  | 600  | 1.2032          | 0.5687   |


### Framework versions

- Transformers 4.41.1
- Pytorch 2.1.2
- Datasets 2.19.1
- Tokenizers 0.19.1
anger contempt disgust fear happy neutral sad surprise