metadata

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

vit-Facial-Expression-Recognition

This model is a fine-tuned version of motheecreator/vit-Facial-Expression-Recognition on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.3629
Accuracy: 0.8758

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: 256
eval_batch_size: 256
seed: 42
gradient_accumulation_steps: 8
total_train_batch_size: 2048
optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: cosine
lr_scheduler_warmup_steps: 1000
num_epochs: 3

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.5354	2.1633	500	0.3629	0.8758

Framework versions

Transformers 4.46.2
Pytorch 2.5.1+cu121
Datasets 3.1.0
Tokenizers 0.20.3