alon-albalak/xlm-roberta-base-xquad

xlm-roberta-base for multilingual QA

Overview

Language Model: xlm-roberta-base
Downstream task: Extractive QA
Training data: XQuAD
Testing Data: XQuAD

Hyperparameters

batch_size = 40
n_epochs = 10
max_seq_len = 384
doc_stride = 128
learning_rate = 3e-5

Performance

Evaluated on held-out test set from XQuAD

"exact_match": 79.44756554307116,
"f1": 89.79318021513376,
"test_samples": 2307

Usage

In Transformers

from transformers import AutoModelForQuestionAnswering, AutoTokenizer, pipeline

model_name = "alon-albalak/xlm-roberta-base-xquad"

# 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)

In FARM

from farm.modeling.adaptive_model import AdaptiveModel
from farm.modeling.tokenization import Tokenizer
from farm.infer import QAInferencer

model_name = "alon-albalak/xlm-roberta-base-xquad"

# a) Get predictions
nlp = QAInferencer.load(model_name)
QA_input = [{"questions": ["Why is model conversion important?"],
             "text": "The option to convert models between FARM and transformers gives freedom to the user and let people easily switch between frameworks."}]
res = nlp.inference_from_dicts(dicts=QA_input, rest_api_schema=True)

# b) Load model & tokenizer
model = AdaptiveModel.convert_from_transformers(model_name, device="cpu", task_type="question_answering")
tokenizer = Tokenizer.load(model_name)

In Haystack

reader = FARMReader(model_name_or_path="alon-albalak/xlm-roberta-base-xquad")
# or 
reader = TransformersReader(model="alon-albalak/xlm-roberta-base-xquad",tokenizer="alon-albalak/xlm-roberta-base-xquad")

Usage instructions for FARM and Haystack were adopted from https://huggingface.co/deepset/xlm-roberta-large-squad2