---
license: mit
language:
- en
library_name: adapter-transformers
pipeline_tag: audio-classification
tags:
- code
- audio
- clap detection
- machine learning
---

# Model Card for Clap Detection Model

## Model Details

### Model Description

This model is a deep learning-based audio classifier trained to detect claps in audio recordings. It has been developed using the PyTorch framework and utilizes the adapter-transformers library. The model can differentiate between clap sounds and background noise.

### Uses

#### Direct Use

The model can be directly used to detect claps in audio recordings.

### Bias, Risks, and Limitations

The model may have limitations in accurately detecting claps in noisy environments or when there are overlapping sounds. It is recommended to evaluate the model's performance in various real-world scenarios.

## How to Get Started with the Model

[More Information Needed]

## Training Details

### Training Data

The model was trained on a dataset consisting of audio recordings containing both clap sounds and background noise.

### Evaluation

[More Information Needed]

## Environmental Impact

Carbon emissions and additional considerations have not been evaluated for this model.

## Technical Specifications

### Model Architecture and Objective

[More Information Needed]

### Compute Infrastructure

[More Information Needed]

## Citation

[More Information Needed]

## Model Card Authors

[Your Name or Username]

## Model Card Contact

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