---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: finetuned-fer2013-balanced
  results: []
---

<!-- 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-balanced

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 None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0183
- Accuracy: 0.6362
- Precision: 0.6312
- Recall: 0.6362
- F1: 0.6310

## 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: 1e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 17
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 1.3969        | 1.0   | 267  | 1.3735          | 0.4996   | 0.4776    | 0.4996 | 0.4436 |
| 1.2341        | 2.0   | 534  | 1.2239          | 0.5442   | 0.5430    | 0.5442 | 0.5108 |
| 1.1363        | 3.0   | 801  | 1.1585          | 0.5758   | 0.5715    | 0.5758 | 0.5638 |
| 1.0894        | 4.0   | 1068 | 1.1087          | 0.5912   | 0.5827    | 0.5912 | 0.5706 |
| 1.0666        | 5.0   | 1335 | 1.0655          | 0.6184   | 0.6111    | 0.6184 | 0.6082 |
| 0.9219        | 6.0   | 1602 | 1.0520          | 0.6233   | 0.6153    | 0.6233 | 0.6136 |
| 0.943         | 7.0   | 1869 | 1.0331          | 0.6299   | 0.6238    | 0.6299 | 0.6231 |
| 0.8906        | 8.0   | 2136 | 1.0238          | 0.6318   | 0.6252    | 0.6318 | 0.6239 |
| 0.8854        | 9.0   | 2403 | 1.0196          | 0.6341   | 0.6313    | 0.6341 | 0.6298 |
| 0.8991        | 10.0  | 2670 | 1.0183          | 0.6362   | 0.6312    | 0.6362 | 0.6310 |


### Framework versions

- Transformers 4.27.0.dev0
- Pytorch 1.13.1+cu116
- Datasets 2.9.0
- Tokenizers 0.13.2