ixambert-base-cased针对问答 (QA) 进行微调

这是一个基本实现的多语言模型 "ixambert-base-cased" ，针对SQuAD v1.1进行了微调，能够用英语、西班牙语和巴斯克语回答基本的事实性问题。

概述

• 语言模型：ixambert-base-cased
• 语言：英语、西班牙语和巴斯克语
• 下游任务：提取型问答（Extractive QA）
• 训练数据：SQuAD v1.1
• 评估数据：SQuAD v1.1
• 基础设施：1x GeForce RTX 2080

输出

该模型输出问题的答案、答案在原始上下文中的起始和结束位置，以及表示该文本片段是正确答案的概率分数。例如：

{'score': 0.9667195081710815, 'start': 101, 'end': 105, 'answer': '1820'}

如何使用

from transformers import AutoModelForQuestionAnswering, AutoTokenizer, pipeline

model_name = "MarcBrun/ixambert-finetuned-squad"

# To get predictions
context = "Florence Nightingale, known for being the founder of modern nursing, was born in Florence, Italy, in 1820"
question = "When was Florence Nightingale born?"
qa = pipeline("question-answering", model=model_name, tokenizer=model_name)
pred = qa(question=question,context=context)

# To load the model and tokenizer
model = AutoModelForQuestionAnswering.from_pretrained(model_name)
tokenizer = AutoTokenizer.from_pretrained(model_name)

超参数

batch_size = 8
n_epochs = 3
learning_rate = 2e-5
optimizer = AdamW
lr_schedule = linear
max_seq_len = 384
doc_stride = 128