---
license: cc-by-2.0
datasets:
- openslr/librispeech_asr
language:
- en
metrics:
- wer
base_model:
- facebook/wav2vec2-base-960h
pipeline_tag: automatic-speech-recognition
library_name: transformers
---

<img src="./EE.gif" align="center" width="70%">

# Model Card for Model ID

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This modelcard aims to be a base template for new models. It has been generated using [this raw template](https://github.com/huggingface/huggingface_hub/blob/main/src/huggingface_hub/templates/modelcard_template.md?plain=1).

## Model Details

### Model Description

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## How to Get Started with the Model

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## Training Details

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#### Summary



## Citation [optional]

## Citation

```
@inproceedings{wright2024training,
  title={Training early-exit architectures for automatic speech recognition: Fine-tuning pre-trained models or training from scratch},
  author={Wright, George August and Cappellazzo, Umberto and Zaiem, Salah and Raj, Desh and Yang, Lucas Ondel and Falavigna, Daniele and Ali, Mohamed Nabih and Brutti, Alessio},
  booktitle={2024 IEEE International Conference on Acoustics, Speech, and Signal Processing Workshops (ICASSPW)},
  pages={685--689},
  year={2024},
  organization={IEEE}
}

```