---
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: 0.55625
---

<!-- 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: 1.3006
- Accuracy: 0.5563

## 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: 30
- eval_batch_size: 30
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 22   | 1.8368          | 0.425    |
| No log        | 2.0   | 44   | 1.6260          | 0.375    |
| No log        | 3.0   | 66   | 1.4368          | 0.5      |
| No log        | 4.0   | 88   | 1.3790          | 0.5062   |
| No log        | 5.0   | 110  | 1.3382          | 0.5125   |
| No log        | 6.0   | 132  | 1.3136          | 0.4938   |
| No log        | 7.0   | 154  | 1.2557          | 0.4938   |
| No log        | 8.0   | 176  | 1.2959          | 0.5      |
| No log        | 9.0   | 198  | 1.2810          | 0.5125   |
| No log        | 10.0  | 220  | 1.2689          | 0.5563   |
| No log        | 11.0  | 242  | 1.3548          | 0.4875   |
| No log        | 12.0  | 264  | 1.2026          | 0.5563   |
| No log        | 13.0  | 286  | 1.2096          | 0.575    |
| No log        | 14.0  | 308  | 1.3175          | 0.525    |
| No log        | 15.0  | 330  | 1.3121          | 0.5312   |
| No log        | 16.0  | 352  | 1.4260          | 0.5312   |
| No log        | 17.0  | 374  | 1.4547          | 0.5062   |
| No log        | 18.0  | 396  | 1.3529          | 0.525    |
| No log        | 19.0  | 418  | 1.2386          | 0.5938   |
| No log        | 20.0  | 440  | 1.3504          | 0.5375   |


### Framework versions

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