---
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: 0.56875
---

<!-- 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: 1.1901
- Accuracy: 0.5687

## 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: linear
- num_epochs: 15

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 20   | 1.9937          | 0.225    |
| No log        | 2.0   | 40   | 1.7466          | 0.4188   |
| No log        | 3.0   | 60   | 1.5370          | 0.5375   |
| No log        | 4.0   | 80   | 1.4797          | 0.5125   |
| No log        | 5.0   | 100  | 1.3531          | 0.55     |
| No log        | 6.0   | 120  | 1.3115          | 0.5687   |
| No log        | 7.0   | 140  | 1.2982          | 0.5375   |
| No log        | 8.0   | 160  | 1.2543          | 0.5437   |
| No log        | 9.0   | 180  | 1.2666          | 0.525    |
| No log        | 10.0  | 200  | 1.2427          | 0.5312   |
| No log        | 11.0  | 220  | 1.2100          | 0.5687   |
| No log        | 12.0  | 240  | 1.2494          | 0.5375   |
| No log        | 13.0  | 260  | 1.2266          | 0.5625   |
| No log        | 14.0  | 280  | 1.2360          | 0.5437   |
| No log        | 15.0  | 300  | 1.1901          | 0.5687   |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.17.0
- Tokenizers 0.15.2