---
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: emotion_recognition_I
  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: 0.60625
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# emotion_recognition_I

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: 1.2755
- Accuracy: 0.6062

## 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: 0.0005
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.3
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.8344        | 1.0   | 5    | 1.1193          | 0.5813   |
| 0.7539        | 2.0   | 10   | 1.2210          | 0.5563   |
| 0.6334        | 3.0   | 15   | 1.2974          | 0.5188   |
| 0.6163        | 4.0   | 20   | 1.1309          | 0.6      |
| 0.4633        | 5.0   | 25   | 1.2804          | 0.5312   |
| 0.4066        | 6.0   | 30   | 1.1664          | 0.6      |
| 0.335         | 7.0   | 35   | 1.1741          | 0.6062   |
| 0.3484        | 8.0   | 40   | 1.1644          | 0.6125   |
| 0.3134        | 9.0   | 45   | 1.2799          | 0.55     |
| 0.2689        | 10.0  | 50   | 1.2276          | 0.6      |


### Framework versions

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