---
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: 0.7133402995471961
---

<!-- 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: 0.8079
- Accuracy: 0.7133

## 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: 60

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 1.7999        | 1.0   | 202   | 1.7896          | 0.2713   |
| 1.5165        | 2.0   | 404   | 1.4311          | 0.4758   |
| 1.3381        | 3.0   | 606   | 1.2065          | 0.5468   |
| 1.2629        | 4.0   | 808   | 1.1050          | 0.5886   |
| 1.248         | 5.0   | 1010  | 1.0425          | 0.6054   |
| 1.2007        | 6.0   | 1212  | 0.9874          | 0.6339   |
| 1.083         | 7.0   | 1414  | 0.9610          | 0.6447   |
| 1.1061        | 8.0   | 1616  | 0.9385          | 0.6524   |
| 1.0597        | 9.0   | 1818  | 0.9155          | 0.6517   |
| 1.0511        | 10.0  | 2020  | 0.9128          | 0.6580   |
| 1.012         | 11.0  | 2222  | 0.9048          | 0.6660   |
| 1.0479        | 12.0  | 2424  | 0.8821          | 0.6729   |
| 0.9993        | 13.0  | 2626  | 0.8770          | 0.6747   |
| 0.9784        | 14.0  | 2828  | 0.8672          | 0.6757   |
| 1.0439        | 15.0  | 3030  | 0.8766          | 0.6750   |
| 0.9782        | 16.0  | 3232  | 0.8658          | 0.6747   |
| 0.9664        | 17.0  | 3434  | 0.8596          | 0.6764   |
| 1.0132        | 18.0  | 3636  | 0.8491          | 0.6806   |
| 0.9703        | 19.0  | 3838  | 0.8538          | 0.6827   |
| 0.9399        | 20.0  | 4040  | 0.8452          | 0.6876   |
| 0.9299        | 21.0  | 4242  | 0.8420          | 0.6904   |
| 0.9815        | 22.0  | 4444  | 0.8417          | 0.6872   |
| 0.9029        | 23.0  | 4646  | 0.8379          | 0.6900   |
| 0.9142        | 24.0  | 4848  | 0.8336          | 0.6897   |
| 0.8695        | 25.0  | 5050  | 0.8312          | 0.6938   |
| 0.8791        | 26.0  | 5252  | 0.8323          | 0.6942   |
| 0.923         | 27.0  | 5454  | 0.8244          | 0.6956   |
| 0.8866        | 28.0  | 5656  | 0.8261          | 0.6970   |
| 0.9319        | 29.0  | 5858  | 0.8255          | 0.6991   |
| 0.9019        | 30.0  | 6060  | 0.8160          | 0.7050   |
| 0.8785        | 31.0  | 6262  | 0.8169          | 0.7071   |
| 0.8859        | 32.0  | 6464  | 0.8178          | 0.7039   |
| 0.8464        | 33.0  | 6666  | 0.8147          | 0.7092   |
| 0.9143        | 34.0  | 6868  | 0.8232          | 0.7029   |
| 0.8506        | 35.0  | 7070  | 0.8158          | 0.7032   |
| 0.9084        | 36.0  | 7272  | 0.8166          | 0.7057   |
| 0.8616        | 37.0  | 7474  | 0.8132          | 0.7088   |
| 0.8656        | 38.0  | 7676  | 0.8155          | 0.7046   |
| 0.8238        | 39.0  | 7878  | 0.8170          | 0.7064   |
| 0.8673        | 40.0  | 8080  | 0.8190          | 0.7092   |
| 0.8624        | 41.0  | 8282  | 0.8127          | 0.7095   |
| 0.8261        | 42.0  | 8484  | 0.8113          | 0.7113   |
| 0.8218        | 43.0  | 8686  | 0.8150          | 0.7095   |
| 0.8584        | 44.0  | 8888  | 0.8170          | 0.7071   |
| 0.8156        | 45.0  | 9090  | 0.8117          | 0.7119   |
| 0.8075        | 46.0  | 9292  | 0.8133          | 0.7116   |
| 0.8382        | 47.0  | 9494  | 0.8146          | 0.7088   |
| 0.7501        | 48.0  | 9696  | 0.8096          | 0.7113   |
| 0.7859        | 49.0  | 9898  | 0.8102          | 0.7081   |
| 0.8195        | 50.0  | 10100 | 0.8121          | 0.7085   |
| 0.8397        | 51.0  | 10302 | 0.8120          | 0.7099   |
| 0.8561        | 52.0  | 10504 | 0.8089          | 0.7126   |
| 0.8082        | 53.0  | 10706 | 0.8090          | 0.7133   |
| 0.8574        | 54.0  | 10908 | 0.8087          | 0.7106   |
| 0.8611        | 55.0  | 11110 | 0.8093          | 0.7092   |
| 0.8886        | 56.0  | 11312 | 0.8100          | 0.7092   |
| 0.7857        | 57.0  | 11514 | 0.8086          | 0.7133   |
| 0.8467        | 58.0  | 11716 | 0.8083          | 0.7119   |
| 0.795         | 59.0  | 11918 | 0.8083          | 0.7119   |
| 0.7975        | 60.0  | 12120 | 0.8079          | 0.7133   |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.0
- Tokenizers 0.15.0