语言模型: electra-base 语言: 英语 下游任务: 提取型问答 训练数据: SQuAD 2.0 评估数据: SQuAD 2.0 代码: 参见 example 和 FARM 基础设施: 1x Tesla v100
seed=42 batch_size = 32 n_epochs = 5 base_LM_model = "google/electra-base-discriminator" max_seq_len = 384 learning_rate = 1e-4 lr_schedule = LinearWarmup warmup_proportion = 0.1 doc_stride=128 max_query_length=64
在SQuAD 2.0开发集上进行评估,性能为 official eval script 。
"exact": 77.30144024256717, "f1": 81.35438272008543, "total": 11873, "HasAns_exact": 74.34210526315789, "HasAns_f1": 82.45961302894314, "HasAns_total": 5928, "NoAns_exact": 80.25231286795626, "NoAns_f1": 80.25231286795626, "NoAns_total": 5945
from transformers import AutoModelForQuestionAnswering, AutoTokenizer, pipeline model_name = "deepset/electra-base-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 lets 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)
from farm.modeling.adaptive_model import AdaptiveModel from farm.modeling.tokenization import Tokenizer from farm.infer import Inferencer model_name = "deepset/electra-base-squad2" # a) Get predictions nlp = Inferencer.load(model_name, task_type="question_answering") QA_input = [{"questions": ["Why is model conversion important?"], "text": "The option to convert models between FARM and transformers gives freedom to the user and lets people easily switch between frameworks."}] res = nlp.inference_from_dicts(dicts=QA_input) # b) Load model & tokenizer model = AdaptiveModel.convert_from_transformers(model_name, device="cpu", task_type="question_answering") tokenizer = Tokenizer.load(model_name)
如果要对大规模的文档进行问答(而不是单个段落),可以在 haystack 中加载模型:
reader = FARMReader(model_name_or_path="deepset/electra-base-squad2") # or reader = TransformersReader(model="deepset/electra-base-squad2",tokenizer="deepset/electra-base-squad2")
Vaishali Pal vaishali.pal [at] deepset.ai Branden Chan: branden.chan [at] deepset.ai Timo Möller: timo.moeller [at] deepset.ai Malte Pietsch: malte.pietsch [at] deepset.ai Tanay Soni: tanay.soni [at] deepset.ai
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