wav2vec2-base-960h-nmsqa-asr

Model Card for Model ID

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This model was pretrained using Facebook-base-960h model on NMSQA dataset. The task is Automatic Speech Recognition (ASR) in which the questions and context sentences are used.
This is a checkpoint with WER 10.58 on dev set.

Model Details

Model Description

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The input of the models are from NMSQA dataset. The task of the dataset is Spoken QA, but in this model I used the sentences for ASR. The input audios are both from context and questions. This ASR model was trained on using training and dev set of NMSQA.

• Developed by: Merve Menevse
• Model type: Supervised ML
• Language(s) (NLP): English
• Finetuned from model [optional]: facebook/wav2vec2-base-960h

Uses

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The model should be used as fine-tuned model for wav2vec2.

How to Get Started with the Model

 from transformers import AutoModel

 model = AutoModel.from_pretrained("menevsem/wav2vec2-base-960h-nmsqa-asr")

Training Details

Training Data

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The model was trained using voidful/NMSQA train and dev set.

Evaluation

For evalaution WER metric is used on dev set.