---
license: apache-2.0
base_model: microsoft/beit-base-patch16-224-pt22k-ft22k
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: finetuned-FER2013
  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: 0.6788575409265064
---

<!-- 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. -->

# finetuned-FER2013

This model is a fine-tuned version of [microsoft/beit-base-patch16-224-pt22k-ft22k](https://huggingface.co/microsoft/beit-base-patch16-224-pt22k-ft22k) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8812
- Accuracy: 0.6789

## 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-06
- 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: 0.1
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.5466        | 1.0   | 202  | 1.5022          | 0.4500   |
| 1.3372        | 2.0   | 404  | 1.1727          | 0.5632   |
| 1.2372        | 3.0   | 606  | 1.0636          | 0.6075   |
| 1.2096        | 4.0   | 808  | 1.0200          | 0.6116   |
| 1.145         | 5.0   | 1010 | 0.9769          | 0.6325   |
| 1.1589        | 6.0   | 1212 | 0.9515          | 0.6405   |
| 1.0752        | 7.0   | 1414 | 0.9395          | 0.6458   |
| 1.0524        | 8.0   | 1616 | 0.9331          | 0.6458   |
| 1.0829        | 9.0   | 1818 | 0.9173          | 0.6573   |
| 1.0219        | 10.0  | 2020 | 0.9114          | 0.6597   |
| 0.9986        | 11.0  | 2222 | 0.9034          | 0.6580   |
| 1.013         | 12.0  | 2424 | 0.9004          | 0.6656   |
| 1.0133        | 13.0  | 2626 | 0.8940          | 0.6628   |
| 1.0064        | 14.0  | 2828 | 0.8916          | 0.6649   |
| 0.9858        | 15.0  | 3030 | 0.8882          | 0.6733   |
| 0.9863        | 16.0  | 3232 | 0.8850          | 0.6740   |
| 1.0058        | 17.0  | 3434 | 0.8856          | 0.6747   |
| 0.9637        | 18.0  | 3636 | 0.8852          | 0.6722   |
| 0.9803        | 19.0  | 3838 | 0.8829          | 0.6754   |
| 0.9356        | 20.0  | 4040 | 0.8812          | 0.6789   |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0