---
license: apache-2.0
base_model: dima806/facial_emotions_image_detection
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: vit-emotional-classifier
  results:
  - task:
      name: Image Classification
      type: image-classification
    dataset:
      name: imagefolder
      type: imagefolder
      config: default
      split: train
      args: default
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.6125
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# vit-emotional-classifier

This model is a fine-tuned version of [dima806/facial_emotions_image_detection](https://huggingface.co/dima806/facial_emotions_image_detection) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 1.2566
- Accuracy: 0.6125

## 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: 8
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.8894        | 1.0   | 20   | 1.8158          | 0.3875   |
| 1.5847        | 2.0   | 40   | 1.5658          | 0.475    |
| 1.3711        | 3.0   | 60   | 1.4249          | 0.5125   |
| 1.205         | 4.0   | 80   | 1.3139          | 0.5875   |
| 1.1244        | 5.0   | 100  | 1.2566          | 0.6125   |
| 0.9923        | 6.0   | 120  | 1.2256          | 0.6062   |
| 0.8801        | 7.0   | 140  | 1.1949          | 0.5875   |
| 0.8631        | 8.0   | 160  | 1.1929          | 0.575    |
| 0.8277        | 9.0   | 180  | 1.1734          | 0.6      |
| 0.786         | 10.0  | 200  | 1.1779          | 0.6      |


### Framework versions

- Transformers 4.41.1
- Pytorch 2.3.0+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1