deepset / roberta-large-squad2

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question-answering

Introduction of roberta-large-squad2

Model Details of roberta-large-squad2

roberta-large for QA

This is the roberta-large model, fine-tuned using the SQuAD2.0 dataset. It's been trained on question-answer pairs, including unanswerable questions, for the task of Question Answering.

Overview

Language model: roberta-large
Language: English
Downstream-task: Extractive QA
Training data: SQuAD 2.0
Eval data: SQuAD 2.0
Code: See an example QA pipeline on Haystack
Infrastructure : 4x Tesla v100

Hyperparameters
base_LM_model = "roberta-large"
Using a distilled model instead

Please note that we have also released a distilled version of this model called deepset/roberta-base-squad2-distilled . The distilled model has a comparable prediction quality and runs at twice the speed of the large model.

Usage
In Haystack

Haystack is an NLP framework by deepset. You can use this model in a Haystack pipeline to do question answering at scale (over many documents). To load the model in Haystack :

reader = FARMReader(model_name_or_path="deepset/roberta-large-squad2")
# or 
reader = TransformersReader(model_name_or_path="deepset/roberta-large-squad2",tokenizer="deepset/roberta-large-squad2")

For a complete example of roberta-large-squad2 being used for Question Answering, check out the Tutorials in Haystack Documentation

In Transformers
from transformers import AutoModelForQuestionAnswering, AutoTokenizer, pipeline

model_name = "deepset/roberta-large-squad2"

# a) Get predictions
nlp = pipeline('question-answering', model=model_name, tokenizer=model_name)
QA_input = {
    'question': 'Why is model conversion important?',
    'context': 'The option to convert models between FARM and transformers gives freedom to the user and let people easily switch between frameworks.'
}
res = nlp(QA_input)

# b) Load model & tokenizer
model = AutoModelForQuestionAnswering.from_pretrained(model_name)
tokenizer = AutoTokenizer.from_pretrained(model_name)
Authors

Branden Chan: [email protected]
Timo Möller: [email protected]
Malte Pietsch: [email protected]
Tanay Soni: [email protected]

About us

deepset is the company behind the open-source NLP framework Haystack which is designed to help you build production ready NLP systems that use: Question answering, summarization, ranking etc.

Some of our other work:

Get in touch and join the Haystack community

For more info on Haystack, visit our GitHub repo and Documentation .

We also have a Discord community open to everyone!

Twitter | LinkedIn | Discord | GitHub Discussions | Website

By the way: we're hiring!

Runs of deepset roberta-large-squad2 on huggingface.co

16.8K
Total runs
2.5K
24-hour runs
2.5K
3-day runs
1.8K
7-day runs
-796
30-day runs

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