metadata
license: mit
tags:
- computer-vision
- emotion-detection
- facial-recognition
- efficientnet
- pytorch
datasets:
- custom
language:
- en
model-index:
- name: emotion-detection-efficientnet-b2-v1
results:
- task:
type: image-classification
name: Emotion Detection
dataset:
name: Facial Emotion Dataset (Kaggle)
type: image
metrics:
- type: accuracy
value: 0.8025
EfficientNet-B2 Emotion Detection (v1)
This model classifies facial emotions into 7 categories:
angry, disgust, fear, happy, neutral, sad, surprise.
Architecture: EfficientNet-B2
Training Platform: Kaggle GPU
Accuracy: ~80.25%
Framework: PyTorch
Developer: Varad V. Choudhari (Atman AI)
License: MIT
Example Usage
from huggingface_hub import hf_hub_download
path = hf_hub_download(
repo_id="AtmanAI/emotion-detection-efficientnet-b2-v1",
filename="efficientnet_b2_emotion_final.pth"
)