---
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
```