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# emotion_recognition

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: 1.7451
- Accuracy: 0.4125

## 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: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 5    | 2.0629          | 0.1625   |
| 2.0494        | 2.0   | 10   | 2.0216          | 0.2375   |
| 2.0494        | 3.0   | 15   | 1.9567          | 0.3438   |
| 1.8758        | 4.0   | 20   | 1.8914          | 0.3937   |
| 1.8758        | 5.0   | 25   | 1.8314          | 0.3937   |
| 1.6857        | 6.0   | 30   | 1.7821          | 0.3812   |
| 1.6857        | 7.0   | 35   | 1.7451          | 0.4125   |
| 1.5477        | 8.0   | 40   | 1.7205          | 0.4125   |
| 1.5477        | 9.0   | 45   | 1.7058          | 0.4125   |
| 1.4739        | 10.0  | 50   | 1.7010          | 0.4125   |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1

anger contempt disgust fear happy neutral sad surprise