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---
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
```python
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"
)
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