Bge M3 Msmarco V3 Sbert

🚀 基于BAAI/bge-m3的句子转换器

这是一个基于 sentence-transformers 库，从 BAAI/bge-m3 微调而来的模型。它可以将句子和段落映射到一个1024维的密集向量空间，可用于语义文本相似度计算、语义搜索、释义挖掘、文本分类、聚类等任务。

🚀 快速开始

直接使用（Sentence Transformers）

首先，安装 Sentence Transformers 库：

pip install -U sentence-transformers

然后，你可以加载该模型并进行推理：

from sentence_transformers import SentenceTransformer

# 从 🤗 Hub 下载模型
model = SentenceTransformer("BlackBeenie/bge-m3-msmarco-v3-sbert")
# 运行推理
sentences = [
    'who is christopher kyle',
    'Chris Kyle American Sniper. Christopher Scott Kyle was born and raised in Texas and was a United States Navy SEAL from 1999 to 2009. He is currently known as the most successful sniper in American military history. According to his book American Sniper, he had 160 confirmed kills (which was from 255 claimed kills).',
    "'American Sniper' Chris Kyle's wife thanks audiences for 'watching the hard stuff'. Taya Kyle has told of her gratitude to audiences for supporting the film about her dead husband Chris Kyle, a Navy Seal played by Bradley Cooper.",
]
embeddings = model.encode(sentences)
print(embeddings.shape)
# [3, 1024]

# 获取嵌入向量的相似度分数
similarities = model.similarity(embeddings, embeddings)
print(similarities.shape)
# [3, 3]

✨ 主要特性

• 语义映射：能够将句子和段落映射到1024维的密集向量空间，方便进行语义相关任务。
• 多任务支持：可用于语义文本相似度计算、语义搜索、释义挖掘、文本分类、聚类等多种任务。

📦 安装指南

安装 Sentence Transformers 库：

pip install -U sentence-transformers

💻 使用示例

基础用法

from sentence_transformers import SentenceTransformer

# 从 🤗 Hub 下载模型
model = SentenceTransformer("BlackBeenie/bge-m3-msmarco-v3-sbert")
# 运行推理
sentences = [
    'who is christopher kyle',
    'Chris Kyle American Sniper. Christopher Scott Kyle was born and raised in Texas and was a United States Navy SEAL from 1999 to 2009. He is currently known as the most successful sniper in American military history. According to his book American Sniper, he had 160 confirmed kills (which was from 255 claimed kills).',
    "'American Sniper' Chris Kyle's wife thanks audiences for 'watching the hard stuff'. Taya Kyle has told of her gratitude to audiences for supporting the film about her dead husband Chris Kyle, a Navy Seal played by Bradley Cooper.",
]
embeddings = model.encode(sentences)
print(embeddings.shape)
# [3, 1024]

# 获取嵌入向量的相似度分数
similarities = model.similarity(embeddings, embeddings)
print(similarities.shape)
# [3, 3]

📚 详细文档

模型详情

模型描述

模型来源

• 文档：Sentence Transformers 文档
• 仓库：GitHub 上的 Sentence Transformers
• Hugging Face：Hugging Face 上的 Sentence Transformers

完整模型架构

SentenceTransformer(
  (0): Transformer({'max_seq_length': 8192, 'do_lower_case': False}) with Transformer model: XLMRobertaModel 
  (1): Pooling({'word_embedding_dimension': 1024, 'pooling_mode_cls_token': False, 'pooling_mode_mean_tokens': True, 'pooling_mode_max_tokens': False, 'pooling_mode_mean_sqrt_len_tokens': False, 'pooling_mode_weightedmean_tokens': False, 'pooling_mode_lasttoken': False, 'include_prompt': True})
)

训练详情

训练数据集

未命名数据集

• 大小：498,970 个训练样本
• 列：sentence_0、sentence_1 和 sentence_2
• 基于前 1000 个样本的近似统计信息：

  	sentence_0	sentence_1	sentence_2
  类型	字符串	字符串	字符串
  详情	最小：4 个标记 平均：9.93 个标记 最大：37 个标记	最小：17 个标记 平均：90.01 个标记 最大：239 个标记	最小：16 个标记 平均：86.47 个标记 最大：229 个标记

• 样本：

  sentence_0	sentence_1	sentence_2
  how much does it cost to paint a interior house	Interior House Painting Cost Factors. Generally, it will take a minimum of two gallons of paint to cover a room. At the highest end, paint will cost anywhere between $30 and $60 per gallon and come in three different finishes: flat, semi-gloss or high-gloss.Flat finishes are the least shiny and are best suited for areas requiring frequent cleaning.rovide a few details about your project and receive competitive quotes from local pros. The average national cost to paint a home interior is $1,671, with most homeowners spending between $966 and $2,426.	Question DetailsAsked on 3/12/2014. Guest_... How much does it cost per square foot to paint the interior of a house? We just bought roughly a 1500 sg ft townhouse and want to get the entire house, including ceilings painted (including a roughly 400 sq ft finished basement not included in square footage).
  when is s corp taxes due	If you form a corporate entity for your small business, regardless of whether it's taxed as a C or S corporation, a tax return must be filed with the Internal Revenue Service on its due date each year. Corporate tax returns are always due on the 15th day of the third month following the close of the tax year. The actual day that the tax return filing deadline falls on, however, isn't the same for every corporation.	But if you haven’t, don’t panic: the majority of forms aren’t due quite yet. Most tax forms have an annual January 31 due date. Your tax forms are considered on time if the form is properly addressed and mailed on or before that date. If the regular due date falls on a Saturday, Sunday, or legal holiday – which is the case in 2015 for both January and February due dates – issuers have until the next business day.
  what are disaccharides	Disaccharides are formed when two monosaccharides are joined together and a molecule of water is removed, a process known as dehydration reaction. For example; milk sugar (lactose) is made from glucose and galactose whereas the sugar from sugar cane and sugar beets (sucrose) is made from glucose and fructose.altose, another notable disaccharide, is made up of two glucose molecules. The two monosaccharides are bonded via a dehydration reaction (also called a condensation reaction or dehydration synthesis) that leads to the loss of a molecule of water and formation of a glycosidic bond.	Other disaccharides include (diagrams p. 364): Sucrose, common table sugar, has a glycosidic bond linking the anomeric hydroxyls of glucose and fructose. Because the configuration at the anomeric carbon of glucose is a (O points down from the ring), the linkage is designated a(12).

• 损失：MultipleNegativesRankingLoss，参数如下：

  {
      "scale": 20.0,
      "similarity_fct": "cos_sim"
  }
  

训练超参数

非默认超参数

• eval_strategy：按步骤评估
• per_device_train_batch_size：32
• per_device_eval_batch_size：32
• num_train_epochs：5
• fp16：True
• multi_dataset_batch_sampler：轮询

所有超参数

训练日志

框架版本

• Python：3.11.11
• Sentence Transformers：3.4.1
• Transformers：4.48.3
• PyTorch：2.5.1+cu124
• Accelerate：1.3.0
• Datasets：3.3.2
• Tokenizers：0.21.0

📄 引用

BibTeX

Sentence Transformers

@inproceedings{reimers-2019-sentence-bert,
    title = "Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks",
    author = "Reimers, Nils and Gurevych, Iryna",
    booktitle = "Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing",
    month = "11",
    year = "2019",
    publisher = "Association for Computational Linguistics",
    url = "https://arxiv.org/abs/1908.10084",
}

MultipleNegativesRankingLoss

@misc{henderson2017efficient,
    title={Efficient Natural Language Response Suggestion for Smart Reply},
    author={Matthew Henderson and Rami Al-Rfou and Brian Strope and Yun-hsuan Sung and Laszlo Lukacs and Ruiqi Guo and Sanjiv Kumar and Balint Miklos and Ray Kurzweil},
    year={2017},
    eprint={1705.00652},
    archivePrefix={arXiv},
    primaryClass={cs.CL}
}