metadata

library_name: transformers
base_model: motheecreator/vit-Facial-Expression-Recognition
tags:
  - generated_from_trainer
datasets:
  - imagefolder
metrics:
  - accuracy
model-index:
  - name: vit-Facial-Expression-Recognition
    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: 0.9320388349514563

vit-Facial-Expression-Recognition

This model is a fine-tuned version of motheecreator/vit-Facial-Expression-Recognition on the imagefolder dataset. It achieves the following results on the evaluation set:

Loss: 0.1672
Accuracy: 0.9320

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: 32
eval_batch_size: 32
seed: 42
gradient_accumulation_steps: 8
total_train_batch_size: 256
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: cosine
lr_scheduler_warmup_steps: 1000
num_epochs: 50

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.7209	21.6216	100	0.5301	0.8155
0.0966	43.2432	200	0.1672	0.9320

Framework versions

Transformers 4.45.1
Pytorch 2.4.0+cu118
Datasets 2.21.0
Tokenizers 0.20.0