---
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: visual_emotion_classification_vit_base_finetunned
  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: 0.525
---

<!-- 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. -->

# visual_emotion_classification_vit_base_finetunned

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: 1.3848
- Accuracy: 0.525

## 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: 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: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.0383        | 0.62  | 50   | 1.9425          | 0.2875   |
| 1.7682        | 1.25  | 100  | 1.6311          | 0.3875   |
| 1.6002        | 1.88  | 150  | 1.5707          | 0.425    |
| 1.413         | 2.5   | 200  | 1.4598          | 0.5      |
| 1.3389        | 3.12  | 250  | 1.3674          | 0.5875   |
| 1.2695        | 3.75  | 300  | 1.3950          | 0.525    |
| 1.1953        | 4.38  | 350  | 1.3466          | 0.5563   |
| 1.1615        | 5.0   | 400  | 1.3819          | 0.5062   |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.17.0
- Tokenizers 0.15.1