nishiwen1214/GLUE-bert4keras
基于bert4keras的GLUE基准代码
This project offers clear and easy-to-understand baseline code for evaluating English language understanding models. It helps researchers and natural language processing practitioners test their models on standard datasets like CoLA, SST-2, and QQP. You provide your language model and the GLUE benchmark datasets, and it outputs performance metrics, enabling you to compare your model's effectiveness against established benchmarks.
No commits in the last 6 months.
Use this if you are a researcher or NLP engineer who needs to benchmark your English language understanding models using the GLUE datasets and want a straightforward, high-performing reference implementation.
Not ideal if you are looking for a pre-trained model for immediate application rather than a framework for evaluating your own models.
Stars
65
Forks
6
Language
Python
License
MIT
Category
Last pushed
Jan 30, 2022
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/nlp/nishiwen1214/GLUE-bert4keras"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
codertimo/BERT-pytorch
Google AI 2018 BERT pytorch implementation
JayYip/m3tl
BERT for Multitask Learning
920232796/bert_seq2seq
pytorch实现 Bert 做seq2seq任务，使用unilm方案,现在也可以做自动摘要，文本分类，情感分析，NER，词性标注等任务,支持t5模型，支持GPT2进行文章续写。
sileod/tasknet
Easy modernBERT fine-tuning and multi-task learning
graykode/toeicbert
TOEIC(Test of English for International Communication) solving using pytorch-pretrained-BERT model.