---
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: emotion_classification
  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: 0.53125
---

<!-- 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_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: 1.8129
- 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: 5e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine_with_restarts
- lr_scheduler_warmup_steps: 30
- num_epochs: 15

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 40   | 1.4349          | 0.45     |
| No log        | 2.0   | 80   | 1.4560          | 0.5      |
| No log        | 3.0   | 120  | 1.5158          | 0.4813   |
| No log        | 4.0   | 160  | 1.4489          | 0.5125   |
| No log        | 5.0   | 200  | 1.8968          | 0.425    |
| No log        | 6.0   | 240  | 1.6870          | 0.5062   |
| No log        | 7.0   | 280  | 1.6759          | 0.4813   |
| No log        | 8.0   | 320  | 1.6498          | 0.5312   |
| No log        | 9.0   | 360  | 1.7581          | 0.5      |
| No log        | 10.0  | 400  | 1.7798          | 0.5      |
| No log        | 11.0  | 440  | 1.6983          | 0.525    |
| No log        | 12.0  | 480  | 1.7756          | 0.5375   |
| 0.1761        | 13.0  | 520  | 1.7346          | 0.5125   |
| 0.1761        | 14.0  | 560  | 1.8079          | 0.525    |
| 0.1761        | 15.0  | 600  | 1.7950          | 0.5188   |


### Framework versions

- Transformers 4.41.1
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1