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---
title: Submission Template
emoji: 🔥
colorFrom: yellow
colorTo: green
sdk: docker
pinned: false
---
# Conformer model
## Model Description
This is a CNN followed by Conformer encoder
### Intended Use
- baseline for audio predictions
## Training Data
The model uses the rfcx audio dataset:
- Size: ~35000 examples
- Split: 80% train, 20% validation
- Binary classification
### Labels
0. Chain Saw in audio
1. no Chain Saw in audio
## Performance
90% accuracy on validation
### Metrics
- **Accuracy**: 90% on validation
- **Environmental Impact**:
- Emissions tracked in gCO2eq
- Energy consumption tracked in Wh
### Model Architecture
CNN and Conformer. Conformer is a mixture between
transformer (MHSA with RoPE
positional encoding), and CNN blocks.
## Environmental Impact
Environmental impact is tracked using CodeCarbon, measuring:
- Carbon emissions during inference
- Energy consumption during inference
This tracking helps establish a baseline for the environmental impact of model deployment and inference.
## Limitations
- simple
## Ethical Considerations
- Environmental impact is tracked to promote awareness of AI's carbon footprint
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