| --- |
| 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 |
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| ## Model Details |
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| ### Model Description |
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| 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. |
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| ### Uses |
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| #### Direct Use |
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| The model can be directly used to detect claps in audio recordings. |
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| ### Bias, Risks, and Limitations |
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| 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. |
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| ## How to Get Started with the Model |
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| [More Information Needed] |
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| ## Training Details |
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| ### Training Data |
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| The model was trained on a dataset consisting of audio recordings containing both clap sounds and background noise. |
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| ### Evaluation |
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| [More Information Needed] |
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| ## Environmental Impact |
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| Carbon emissions and additional considerations have not been evaluated for this model. |
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| ## Technical Specifications |
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| ### Model Architecture and Objective |
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| [More Information Needed] |
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| ### Compute Infrastructure |
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| [More Information Needed] |
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| ## Citation |
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| [More Information Needed] |
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| ## Model Card Authors |
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| [Your Name or Username] |
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| ## Model Card Contact |
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| [Your Contact Information] |
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