roberta base for Extractive QA This is the roberta base model, fine tuned using the SQuAD2.0 dataset. It's been trained on question answer pairs, including unanswerable questions, for the task of Extractive Question Answering. We have also released a distilled version of this model called deepset/tinyroberta squad2. It has a comparable prediction quality and runs at twice the speed of deepset/roberta base squad2. Overview Language model: roberta base Language: English Downstream task: Extractive QA Training data: SQuAD 2.0 Eval data: SQuAD 2.0 Code: See an example extractive QA pipeline built with Haystack Infrastructure : 4x Tesla v100 Hyperparameters Usage In Haystack Haystack is an AI orchestration framework to build customizable, production ready LLM applications. You can use this model in Haystack to do extractive question answering on documents. To load and run the model with Haystack: For a complete example with an extractive question answering pipeline that scales over many documents, check out the corresponding Haystack tutorial. In Transformers Performance Evaluated on the SQuAD 2.0 dev set with the official eval script. Authors Branden Chan: branden.chan@deepset.ai Timo…
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