Fine-Tuned ResNet-50 on FERPlus Dataset

This model is a fine-tuned version of ResNet-50 on the FERPlus dataset, which is more balanced ferplus dataset as owner claimed.

Model Details

  • Base Model: Microsoft ResNet-50
  • Dataset: FERPlus, which contains grayscale images of faces labeled with emotion categories.
  • Task: Emotion Classification
  • Labels:
    • 0: Angry
    • 1: Contempt
    • 2: Disgust
    • 3: Fear
    • 4: Happy
    • 5: Neutral
    • 6: Sad
    • 7: Surprise

Preprocessing Details

This model was fine-tuned on FERPlus dataset images resized to 224x224 pixels. Standard data augmentation techniques were applied, and normalization was performed with the following values:

  • Mean: [0.485, 0.456, 0.406]
  • Standard Deviation: [0.229, 0.224, 0.225]

Training Hyperparameters

  • Batch Size: 16
  • Epochs: 10
  • Learning Rate: 2e-5
  • Weight Decay: 0.01
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