---
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: vit-Facial-Expression-Recognition
  results: []
pipeline_tag: image-classification
base_model: motheecreator/vit-Facial-Expression-Recognition
library_name: transformers
---

<!-- 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. -->

# vit-Facial-Expression-Recognition

This model is a fine-tuned version of [motheecreator/vit-Facial-Expression-Recognition](https://huggingface.co/motheecreator/vit-Facial-Expression-Recognition) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3708
- Accuracy: 0.8735

## 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: 3e-05
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 512
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 1000
- num_epochs: 3

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 0.5551        | 0.4327 | 100  | 0.3728          | 0.8742   |
| 0.5725        | 0.8653 | 200  | 0.3702          | 0.8749   |
| 0.5513        | 1.2980 | 300  | 0.3683          | 0.8751   |
| 0.5565        | 1.7307 | 400  | 0.3681          | 0.8754   |
| 0.5395        | 2.1633 | 500  | 0.3708          | 0.8735   |
| 0.5306        | 2.5960 | 600  | 0.3696          | 0.8738   |


### Framework versions

- Transformers 4.44.0
- Pytorch 2.4.0
- Datasets 2.21.0
- Tokenizers 0.19.1