Reranker Ms Marco MiniLM L6 V2 Gooaq Bce
這是一個從cross-encoder/ms-marco-MiniLM-L6-v2微調而來的交叉編碼器模型,使用sentence-transformers庫開發。它能夠計算文本對的得分,可用於文本重排序和語義搜索。
下載量 15
發布時間 : 3/30/2025
模型概述
該模型是一個基於MiniLM架構的交叉編碼器,專門用於文本重排序任務。它通過計算查詢和文檔之間的相關性得分,優化搜索結果的排序質量。
模型特點
高效重排序
專門優化用於重排序任務,能夠顯著提升搜索結果的相關性
多數據集驗證
在GooAQ、MSMARCO、NFCorpus和NQ等多個數據集上進行了驗證,表現穩定
長文本處理
支持最大512個標記的序列長度,適合處理較長的查詢和文檔
模型能力
文本相關性評分
搜索結果重排序
語義搜索優化
使用案例
信息檢索
搜索引擎結果優化
對初步檢索結果進行重排序,提高相關文檔的排名
在GooAQ開發集上達到0.6822的NDCG@10分數
問答系統
對候選答案進行相關性排序,選擇最匹配的答案
在NanoNQ數據集上達到0.5091的NDCG@10分數
醫療健康
醫療問答匹配
匹配用戶醫療問題與專業醫學解答
如示例中所示,能準確識別與左臂疼痛相關的醫學解釋
🚀 基於GooAQ訓練的ModernBERT-base模型
這是一個基於Cross Encoder的模型,它使用sentence-transformers庫,從cross-encoder/ms-marco-MiniLM-L6-v2微調而來。該模型可以計算文本對的得分,可用於文本重排序和語義搜索。
🚀 快速開始
此模型可用於計算文本對的得分,適用於文本重排序和語義搜索任務。下面將介紹如何使用此模型。
✨ 主要特性
- 文本重排序:能夠為文本對計算得分,從而實現文本重排序。
- 語義搜索:可用於語義搜索任務,幫助用戶更精準地找到相關文本。
📦 安裝指南
首先,你需要安裝Sentence Transformers庫:
pip install -U sentence-transformers
💻 使用示例
基礎用法
安裝好庫之後,你可以加載此模型並進行推理:
from sentence_transformers import CrossEncoder
# 從🤗 Hub下載模型
model = CrossEncoder("ayushexel/reranker-ms-marco-MiniLM-L6-v2-gooaq-bce")
# 獲取文本對的得分
pairs = [
['what does it mean when you get a sharp pain in your left arm?', 'Pain in the left arm A pain in your left arm could mean you have a bone or joint injury, a pinched nerve, or a problem with your heart. Read on to learn more about the causes of left arm pain and what symptoms could signal a serious problem.'],
['what does it mean when you get a sharp pain in your left arm?', "In this Article Whether it's throbbing, aching, or sharp, everyone has been in pain. The uncomfortable sensation is a red flag. Pain in your armpit could mean that you've simply strained a muscle, which is eased with ice and rest. It could also be a sign of more serious conditions, like an infection or breast cancer."],
['what does it mean when you get a sharp pain in your left arm?', 'Sharp: When you feel a sudden, intense spike of pain, that qualifies as “sharp.” Sharp pain may also fit the descriptors cutting and shooting. Stabbing: Like sharp pain, stabbing pain occurs suddenly and intensely. However, stabbing pain may fade and reoccur many times.'],
['what does it mean when you get a sharp pain in your left arm?', 'Symptoms. A herniated disc in the neck can cause neck pain, radiating arm pain, shoulder pain, and numbness or tingling in the arm or hand. The quality and type of pain can vary from dull, aching, and difficult to localize to sharp, burning, and easy to pinpoint.'],
['what does it mean when you get a sharp pain in your left arm?', 'Injuries or trauma to any part of the arm or shoulder, including bone fractures, joint dislocations, and muscle strains and sprains, are common causes of arm pain. Sometimes diseases that affect other organs in the body, like peripheral vascular disease or arthritis, can be the cause of pain in the arm.'],
]
scores = model.predict(pairs)
print(scores.shape)
# (5,)
# 或者根據與單個文本的相似度對不同文本進行排序
ranks = model.rank(
'what does it mean when you get a sharp pain in your left arm?',
[
'Pain in the left arm A pain in your left arm could mean you have a bone or joint injury, a pinched nerve, or a problem with your heart. Read on to learn more about the causes of left arm pain and what symptoms could signal a serious problem.',
"In this Article Whether it's throbbing, aching, or sharp, everyone has been in pain. The uncomfortable sensation is a red flag. Pain in your armpit could mean that you've simply strained a muscle, which is eased with ice and rest. It could also be a sign of more serious conditions, like an infection or breast cancer.",
'Sharp: When you feel a sudden, intense spike of pain, that qualifies as “sharp.” Sharp pain may also fit the descriptors cutting and shooting. Stabbing: Like sharp pain, stabbing pain occurs suddenly and intensely. However, stabbing pain may fade and reoccur many times.',
'Symptoms. A herniated disc in the neck can cause neck pain, radiating arm pain, shoulder pain, and numbness or tingling in the arm or hand. The quality and type of pain can vary from dull, aching, and difficult to localize to sharp, burning, and easy to pinpoint.',
'Injuries or trauma to any part of the arm or shoulder, including bone fractures, joint dislocations, and muscle strains and sprains, are common causes of arm pain. Sometimes diseases that affect other organs in the body, like peripheral vascular disease or arthritis, can be the cause of pain in the arm.',
]
)
# [{'corpus_id': ..., 'score': ...}, {'corpus_id': ..., 'score': ...}, ...]
📚 詳細文檔
模型詳情
模型描述
屬性 | 詳情 |
---|---|
模型類型 | 交叉編碼器(Cross Encoder) |
基礎模型 | cross-encoder/ms-marco-MiniLM-L6-v2 |
最大序列長度 | 512個詞元 |
輸出標籤數量 | 1個標籤 |
語言 | 英語 |
許可證 | apache-2.0 |
模型來源
- 文檔:Sentence Transformers文檔
- 文檔:Cross Encoder文檔
- 代碼倉庫:GitHub上的Sentence Transformers
- Hugging Face:Hugging Face上的Cross Encoders
評估
指標
交叉編碼器重排序(數據集:gooaq-dev
)
使用CrossEncoderRerankingEvaluator
進行評估,參數如下:
{
"at_k": 10,
"always_rerank_positives": false
}
指標 | 值 |
---|---|
map | 0.6380 (+0.2121) |
mrr@10 | 0.6361 (+0.2199) |
ndcg@10 | 0.6822 (+0.2001) |
交叉編碼器重排序(數據集:NanoMSMARCO_R100
、NanoNFCorpus_R100
和NanoNQ_R100
)
使用CrossEncoderRerankingEvaluator
進行評估,參數如下:
{
"at_k": 10,
"always_rerank_positives": true
}
指標 | NanoMSMARCO_R100 | NanoNFCorpus_R100 | NanoNQ_R100 |
---|---|---|---|
map | 0.5437 (+0.0541) | 0.3885 (+0.1275) | 0.4626 (+0.0430) |
mrr@10 | 0.5348 (+0.0573) | 0.5630 (+0.0632) | 0.4628 (+0.0361) |
ndcg@10 | 0.6060 (+0.0655) | 0.4077 (+0.0827) | 0.5091 (+0.0084) |
交叉編碼器Nano BEIR(數據集:NanoBEIR_R100_mean
)
使用CrossEncoderNanoBEIREvaluator
進行評估,參數如下:
{
"dataset_names": [
"msmarco",
"nfcorpus",
"nq"
],
"rerank_k": 100,
"at_k": 10,
"always_rerank_positives": true
}
指標 | 值 |
---|---|
map | 0.4649 (+0.0749) |
mrr@10 | 0.5202 (+0.0522) |
ndcg@10 | 0.5076 (+0.0522) |
訓練詳情
訓練數據集
未命名數據集
- 規模:2,223,773個訓練樣本
- 列名:
question
、answer
和label
- 基於前1000個樣本的近似統計信息:
| | 問題 | 答案 | 標籤 |
|------|------|------|------|
| 類型 | 字符串 | 字符串 | 整數 |
| 詳情 |
- 最小:19個字符
- 平均:45.87個字符
- 最大:88個字符
- 最小:61個字符
- 平均:253.13個字符
- 最大:374個字符
- 0:約86.70%
- 1:約13.30%
- 樣本示例:
| 問題 | 答案 | 標籤 |
|------|------|------|
|
what does it mean when you get a sharp pain in your left arm?
|Pain in the left arm A pain in your left arm could mean you have a bone or joint injury, a pinched nerve, or a problem with your heart. Read on to learn more about the causes of left arm pain and what symptoms could signal a serious problem.
|1
| |what does it mean when you get a sharp pain in your left arm?
|In this Article Whether it's throbbing, aching, or sharp, everyone has been in pain. The uncomfortable sensation is a red flag. Pain in your armpit could mean that you've simply strained a muscle, which is eased with ice and rest. It could also be a sign of more serious conditions, like an infection or breast cancer.
|0
| |what does it mean when you get a sharp pain in your left arm?
|Sharp: When you feel a sudden, intense spike of pain, that qualifies as “sharp.” Sharp pain may also fit the descriptors cutting and shooting. Stabbing: Like sharp pain, stabbing pain occurs suddenly and intensely. However, stabbing pain may fade and reoccur many times.
|0
| - 損失函數:
BinaryCrossEntropyLoss
,參數如下:
{
"activation_fn": "torch.nn.modules.linear.Identity",
"pos_weight": 7
}
訓練超參數
非默認超參數
eval_strategy
:按步驟評估per_device_train_batch_size
:2048per_device_eval_batch_size
:2048learning_rate
:2e-05warmup_ratio
:0.1seed
:12bf16
:Truedataloader_num_workers
:12load_best_model_at_end
:True
所有超參數
點擊展開
overwrite_output_dir
: Falsedo_predict
: Falseeval_strategy
: stepsprediction_loss_only
: Trueper_device_train_batch_size
: 2048per_device_eval_batch_size
: 2048per_gpu_train_batch_size
: Noneper_gpu_eval_batch_size
: Nonegradient_accumulation_steps
: 1eval_accumulation_steps
: Nonetorch_empty_cache_steps
: Nonelearning_rate
: 2e-05weight_decay
: 0.0adam_beta1
: 0.9adam_beta2
: 0.999adam_epsilon
: 1e-08max_grad_norm
: 1.0num_train_epochs
: 3max_steps
: -1lr_scheduler_type
: linearlr_scheduler_kwargs
: {}warmup_ratio
: 0.1warmup_steps
: 0log_level
: passivelog_level_replica
: warninglog_on_each_node
: Truelogging_nan_inf_filter
: Truesave_safetensors
: Truesave_on_each_node
: Falsesave_only_model
: Falserestore_callback_states_from_checkpoint
: Falseno_cuda
: Falseuse_cpu
: Falseuse_mps_device
: Falseseed
: 12data_seed
: Nonejit_mode_eval
: Falseuse_ipex
: Falsebf16
: Truefp16
: Falsefp16_opt_level
: O1half_precision_backend
: autobf16_full_eval
: Falsefp16_full_eval
: Falsetf32
: Nonelocal_rank
: 0ddp_backend
: Nonetpu_num_cores
: Nonetpu_metrics_debug
: Falsedebug
: []dataloader_drop_last
: Falsedataloader_num_workers
: 12dataloader_prefetch_factor
: Nonepast_index
: -1disable_tqdm
: Falseremove_unused_columns
: Truelabel_names
: Noneload_best_model_at_end
: Trueignore_data_skip
: Falsefsdp
: []fsdp_min_num_params
: 0fsdp_config
: {'min_num_params': 0, 'xla': False, 'xla_fsdp_v2': False, 'xla_fsdp_grad_ckpt': False}tp_size
: 0fsdp_transformer_layer_cls_to_wrap
: Noneaccelerator_config
: {'split_batches': False, 'dispatch_batches': None, 'even_batches': True, 'use_seedable_sampler': True, 'non_blocking': False, 'gradient_accumulation_kwargs': None}deepspeed
: Nonelabel_smoothing_factor
: 0.0optim
: adamw_torchoptim_args
: Noneadafactor
: Falsegroup_by_length
: Falselength_column_name
: lengthddp_find_unused_parameters
: Noneddp_bucket_cap_mb
: Noneddp_broadcast_buffers
: Falsedataloader_pin_memory
: Truedataloader_persistent_workers
: Falseskip_memory_metrics
: Trueuse_legacy_prediction_loop
: Falsepush_to_hub
: Falseresume_from_checkpoint
: Nonehub_model_id
: Nonehub_strategy
: every_savehub_private_repo
: Nonehub_always_push
: Falsegradient_checkpointing
: Falsegradient_checkpointing_kwargs
: Noneinclude_inputs_for_metrics
: Falseinclude_for_metrics
: []eval_do_concat_batches
: Truefp16_backend
: autopush_to_hub_model_id
: Nonepush_to_hub_organization
: Nonemp_parameters
:auto_find_batch_size
: Falsefull_determinism
: Falsetorchdynamo
: Noneray_scope
: lastddp_timeout
: 1800torch_compile
: Falsetorch_compile_backend
: Nonetorch_compile_mode
: Nonedispatch_batches
: Nonesplit_batches
: Noneinclude_tokens_per_second
: Falseinclude_num_input_tokens_seen
: Falseneftune_noise_alpha
: Noneoptim_target_modules
: Nonebatch_eval_metrics
: Falseeval_on_start
: Falseuse_liger_kernel
: Falseeval_use_gather_object
: Falseaverage_tokens_across_devices
: Falseprompts
: Nonebatch_sampler
: batch_samplermulti_dataset_batch_sampler
: proportional
訓練日誌
輪數 | 步驟 | 訓練損失 | gooaq-dev_ndcg@10 | NanoMSMARCO_R100_ndcg@10 | NanoNFCorpus_R100_ndcg@10 | NanoNQ_R100_ndcg@10 | NanoBEIR_R100_mean_ndcg@10 |
---|---|---|---|---|---|---|---|
-1 | -1 | - | 0.6371 (+0.1550) | 0.6686 (+0.1282) | 0.3930 (+0.0680) | 0.7599 (+0.2592) | 0.6072 (+0.1518) |
0.0009 | 1 | 2.1175 | - | - | - | - | - |
0.1842 | 200 | 1.1892 | - | - | - | - | - |
0.3683 | 400 | 0.676 | - | - | - | - | - |
0.5525 | 600 | 0.6268 | - | - | - | - | - |
0.7366 | 800 | 0.606 | - | - | - | - | - |
0.9208 | 1000 | 0.5933 | 0.6731 (+0.1910) | 0.6038 (+0.0634) | 0.4572 (+0.1321) | 0.5220 (+0.0213) | 0.5277 (+0.0723) |
1.1050 | 1200 | 0.5756 | - | - | - | - | - |
1.2891 | 1400 | 0.5625 | - | - | - | - | - |
1.4733 | 1600 | 0.5575 | - | - | - | - | - |
1.6575 | 1800 | 0.549 | - | - | - | - | - |
1.8416 | 2000 | 0.5475 | 0.6799 (+0.1977) | 0.6072 (+0.0667) | 0.4278 (+0.1028) | 0.5031 (+0.0024) | 0.5127 (+0.0573) |
2.0258 | 2200 | 0.5391 | - | - | - | - | - |
2.2099 | 2400 | 0.5276 | - | - | - | - | - |
2.3941 | 2600 | 0.5271 | - | - | - | - | - |
2.5783 | 2800 | 0.5264 | - | - | - | - | - |
2.7624 | 3000 | 0.5244 | 0.6822 (+0.2001) | 0.6060 (+0.0655) | 0.4077 (+0.0827) | 0.5091 (+0.0084) | 0.5076 (+0.0522) |
2.9466 | 3200 | 0.5235 | - | - | - | - | - |
-1 | -1 | - | 0.6822 (+0.2001) | 0.6060 (+0.0655) | 0.4077 (+0.0827) | 0.5091 (+0.0084) | 0.5076 (+0.0522) |
注:加粗行表示保存的檢查點。
框架版本
- Python:3.11.0
- Sentence Transformers:4.0.1
- Transformers:4.50.3
- PyTorch:2.6.0+cu124
- Accelerate:1.5.2
- Datasets:3.5.0
- Tokenizers:0.21.1
📄 許可證
本模型使用apache-2.0許可證。
🔖 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",
}
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