---
license: apache-2.0
base_model: google/vit-base-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: emotion_recognition
  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: 0.475
---

<!-- 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. -->

# emotion_recognition

This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 1.4479
- Accuracy: 0.475

## 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: 3e-05
- train_batch_size: 8
- 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
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 80   | 1.7877          | 0.3      |
| No log        | 2.0   | 160  | 1.5989          | 0.4062   |
| No log        | 3.0   | 240  | 1.4993          | 0.4313   |
| No log        | 4.0   | 320  | 1.4446          | 0.4437   |
| No log        | 5.0   | 400  | 1.4479          | 0.475    |
| No log        | 6.0   | 480  | 1.4549          | 0.4437   |
| 0.6433        | 7.0   | 560  | 1.4635          | 0.45     |
| 0.6433        | 8.0   | 640  | 1.4767          | 0.4562   |
| 0.6433        | 9.0   | 720  | 1.4850          | 0.4437   |
| 0.6433        | 10.0  | 800  | 1.4864          | 0.4437   |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1