sftsalman / askme-----nlp_model_for_qa Goto Github PK

Fine-tuning a pre-trained transformer model for specific NLP tasks can significantly improve its performance on specialized datasets. In this project, we focus on fine-tuning a DistilBERT model for question answering using the TyDi QA dataset.

Utilize Hugging Face's Datasets library to access the TyDi QA dataset. We'll use a filtered version containing only English examples.

Preprocess the text using the tokenizer provided by Hugging Face. This step ensures that the text is properly formatted for input into the transformer model.

Fine-tune the pre-trained DistilBERT model on the TyDi QA dataset using Hugging Face's Trainer object. This involves training the model on the dataset and adjusting its parameters to improve performance on question answering tasks.