---
base_model: motheecreator/vit-Facial-Expression-Recognition
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: vit-Facial-Expression-Recognitio
  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. -->

# vit-Facial-Expression-Recognitio

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: 0.3936
- Accuracy: 0.8675

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.5969        | 0.34  | 100  | 0.3997          | 0.8652   |
| 0.609         | 0.67  | 200  | 0.3994          | 0.8644   |
| 0.6038        | 1.01  | 300  | 0.3969          | 0.8677   |
| 0.5819        | 1.35  | 400  | 0.3947          | 0.8674   |
| 0.5864        | 1.69  | 500  | 0.3936          | 0.8675   |
| 0.5819        | 2.02  | 600  | 0.3925          | 0.8661   |
| 0.5694        | 2.36  | 700  | 0.3961          | 0.8656   |
| 0.5618        | 2.7   | 800  | 0.3994          | 0.8650   |


### Framework versions

- Transformers 4.36.0
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.15.0