Model Card for Model ID
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This model was pretrained using facebook/hubert-base-ls960 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 14.36 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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How to Get Started with the Model
from transformers import AutoModel
model = AutoModel.from_pretrained("menevsem/hubert-base-ls960-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.