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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: 1.2445
- Accuracy: 0.5312

## 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: 0.0001
- train_batch_size: 64
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 15

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 10   | 1.9385          | 0.325    |
| No log        | 2.0   | 20   | 1.7153          | 0.4188   |
| No log        | 3.0   | 30   | 1.5905          | 0.3937   |
| No log        | 4.0   | 40   | 1.4706          | 0.4625   |
| No log        | 5.0   | 50   | 1.4078          | 0.5062   |
| No log        | 6.0   | 60   | 1.3739          | 0.4813   |
| No log        | 7.0   | 70   | 1.3108          | 0.5125   |
| No log        | 8.0   | 80   | 1.2874          | 0.5312   |
| No log        | 9.0   | 90   | 1.2810          | 0.5312   |
| No log        | 10.0  | 100  | 1.2754          | 0.5437   |
| No log        | 11.0  | 110  | 1.2380          | 0.5563   |
| No log        | 12.0  | 120  | 1.1721          | 0.6125   |
| No log        | 13.0  | 130  | 1.2242          | 0.5875   |
| No log        | 14.0  | 140  | 1.2530          | 0.525    |
| No log        | 15.0  | 150  | 1.2610          | 0.575    |


### Framework versions

- Transformers 4.33.2
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3

calling clapping running sitting sleeping texting using_laptop cycling dancing drinking eating fighting hugging laughing listening_to_music