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RAFDB-Facial-Expression-Recognition

Image Classification
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Safetensors
vit
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RAFDB-Facial-Expression-Recognition / README.md
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metadata
library_name: transformers
base_model: carlosleao/vit-Facial-Expression-Recognition
tags:
  - generated_from_trainer
metrics:
  - accuracy
model-index:
  - name: RAFDB-Facial-Expression-Recognition
    results: []

RAFDB-Facial-Expression-Recognition

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

  • Loss: 1.5906
  • Accuracy: 0.4159

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: 30

Training results

Training Loss Epoch Step Validation Loss Accuracy
1.7235 2.0833 100 1.6571 0.3875
1.5738 4.1667 200 1.5756 0.3967
1.4811 6.25 300 1.5389 0.4166
1.3178 8.3333 400 1.5501 0.4003
1.095 10.4167 500 1.5906 0.4159
0.8081 12.5 600 1.7889 0.3641
0.594 14.5833 700 1.9123 0.3833
0.434 16.6667 800 2.1054 0.3638
0.3201 18.75 900 2.3273 0.3455
0.2472 20.8333 1000 2.3722 0.3510
0.1879 22.9167 1100 2.4218 0.3611
0.1255 25.0 1200 2.4329 0.3817
0.0749 27.0833 1300 2.5189 0.3585
0.0538 29.1667 1400 2.5638 0.3686

Framework versions

  • Transformers 4.45.1
  • Pytorch 2.4.1+cu121
  • Datasets 3.0.1
  • Tokenizers 0.20.0