---
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: 0.54375
---

<!-- 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: 1.3248
- Accuracy: 0.5437

## 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: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine_with_restarts
- lr_scheduler_warmup_steps: 18
- num_epochs: 18

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 20   | 1.4238          | 0.4625   |
| No log        | 2.0   | 40   | 1.4238          | 0.4188   |
| No log        | 3.0   | 60   | 1.4457          | 0.4625   |
| No log        | 4.0   | 80   | 1.5008          | 0.45     |
| No log        | 5.0   | 100  | 1.4511          | 0.5062   |
| No log        | 6.0   | 120  | 1.6197          | 0.4375   |
| No log        | 7.0   | 140  | 1.6023          | 0.45     |
| No log        | 8.0   | 160  | 1.6301          | 0.4562   |
| No log        | 9.0   | 180  | 1.7171          | 0.4688   |
| No log        | 10.0  | 200  | 1.9459          | 0.3688   |
| No log        | 11.0  | 220  | 1.8110          | 0.4062   |
| No log        | 12.0  | 240  | 1.7246          | 0.425    |
| No log        | 13.0  | 260  | 1.7258          | 0.475    |
| No log        | 14.0  | 280  | 1.7419          | 0.475    |
| No log        | 15.0  | 300  | 1.6547          | 0.4625   |
| No log        | 16.0  | 320  | 1.7231          | 0.4625   |
| No log        | 17.0  | 340  | 1.8635          | 0.4125   |
| No log        | 18.0  | 360  | 1.6725          | 0.4562   |


### Framework versions

- Transformers 4.41.1
- Pytorch 2.1.2
- Datasets 2.19.1
- Tokenizers 0.19.1