README.md

metadata

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