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wav2vec2-spanish-multilibrispeech

Automatic Speech Recognition PyTorch TensorBoard Transformers

Spanish wav2vec2 audio Eval Results

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	---
	language:
	- es
	tags:
	- audio # Example: audio
	- automatic-speech-recognition # Example:
	datasets:
	- multilingual_librispeech

	metrics:
	- eval_wer: 0.073

	model-index:
	- name: wav2vec2-spanish-multilibrispeech
	results:
	- task:
	type: automatic-speech-recognition # Required. Example: automatic-speech-recognition
	name: Speech Recognition # Optional. Example: Speech Recognition
	dataset:
	type: multilingual_librispeech # Required. Example: common_voice. Use dataset id from https://hf.co/datasets
	name: multilingual_librispeech es # Required. Example: Common Voice zh-CN
	args: es # Optional. Example: zh-CN
	metrics:
	- type: wer
	value: 0.073
	name: eval_wer
	- type: loss
	value: 0.086
	name: eval_loss
	---

	This is a model for automatic speech recognition in spanish, by using the Spanish portion of [multilingual_librispeech](https://huggingface.co/datasets/multilingual_librispeech) and the [pre-trained wav2vec2 multilingual from Facebook](https://huggingface.co/facebook/wav2vec2-large-xlsr-53)


	For training the model, we used the same parameters as they recommend in [the paper](https://arxiv.org/abs/2006.13979). We trained for a total of 15 epochs, obtaining a final wer of 0.073.

	An example of how to use this model:

	```python
	from transformers import Wav2Vec2Tokenizer, AutoModelForCTC

	tokenizer = Wav2Vec2Tokenizer.from_pretrained(
	"IIC/wav2vec2-spanish-multilibrispeech"
	)

	model = AutoModelForCTC.from_pretrained(
	"IIC/wav2vec2-spanish-multilibrispeech"
	)

	```

	### Contributions
	Thanks to [@avacaondata](https://huggingface.co/avacaondata), [@alborotis](https://huggingface.co/alborotis), [@albarji](https://huggingface.co/albarji), [@Dabs](https://huggingface.co/Dabs), [@GuillemGSubies](https://huggingface.co/GuillemGSubies) for adding this model.