Mmlw Roberta Large

由 sdadas 开发

基于RoBERTa架构的大规模波兰语句子转换模型，专注于句子相似度计算和特征提取任务。

文本嵌入

Transformers

其他

开源协议:Apache-2.0 #波兰语句子相似度 #多任务评估 #高精度语义匹配

下载量 5,007

发布时间 : 11/17/2023

模型介绍

内容详情

替代品

模型简介

该模型是基于RoBERTa架构的波兰语预训练模型，主要用于句子相似度计算、特征提取和相关自然语言处理任务。在MTEB波兰语基准测试中表现出色。

模型特点

波兰语优化

专门针对波兰语进行优化，在波兰语NLP任务中表现优异

多任务能力

支持句子相似度计算、聚类、分类和检索等多种NLP任务

MTEB基准测试验证

在多个MTEB波兰语基准测试中取得良好成绩

模型能力

句子相似度计算

文本特征提取

文本聚类

文本分类

信息检索

使用案例

文本分析

评论分类

对波兰语产品评论进行情感或主题分类

在AllegroReviews数据集上达到47.5%准确率

语义相似度判断

判断两个波兰语句子的语义相似度

在CDSC-R数据集上达到92.5的Spearman相关系数

信息检索

问答系统

构建波兰语问答系统的语义检索组件

在HotpotQA-PL数据集上MAP@10达到62.6

文档检索

基于语义的波兰语文档检索

在DBPedia-PL数据集上MRR@10达到73.6

pipeline_tag: 句子相似度 tags:

句子转换器
特征提取
句子相似度
转换器
MTEB model-index:
name: mmlw-roberta-large results:
- task: type: 聚类 dataset: type: PL-MTEB/8tags-clustering name: MTEB 8TagsClustering config: 默认 split: 测试 revision: 无 metrics:
  - type: v_measure value: 31.16472823814849
- task: type: 分类 dataset: type: PL-MTEB/allegro-reviews name: MTEB AllegroReviews config: 默认 split: 测试 revision: 无 metrics:
  - type: 准确率 value: 47.48508946322067
  - type: f1 value: 42.33327527584009
- task: type: 检索 dataset: type: arguana-pl name: MTEB ArguAna-PL config: 默认 split: 测试 revision: 无 metrics:
  - type: map_at_1 value: 38.834
  - type: map_at_10 value: 55.22899999999999
  - type: map_at_100 value: 55.791999999999994
  - type: map_at_1000 value: 55.794
  - type: map_at_3 value: 51.233
  - type: map_at_5 value: 53.772
  - type: mrr_at_1 value: 39.687
  - type: mrr_at_10 value: 55.596000000000004
  - type: mrr_at_100 value: 56.157000000000004
  - type: mrr_at_1000 value: 56.157999999999994
  - type: mrr_at_3 value: 51.66
  - type: mrr_at_5 value: 54.135
  - type: ndcg_at_1 value: 38.834
  - type: ndcg_at_10 value: 63.402
  - type: ndcg_at_100 value: 65.78
  - type: ndcg_at_1000 value: 65.816
  - type: ndcg_at_3 value: 55.349000000000004
  - type: ndcg_at_5 value: 59.892
  - type: precision_at_1 value: 38.834
  - type: precision_at_10 value: 8.905000000000001
  - type: precision_at_100 value: 0.9939999999999999
  - type: precision_at_1000 value: 0.1
  - type: precision_at_3 value: 22.428
  - type: precision_at_5 value: 15.647
  - type: recall_at_1 value: 38.834
  - type: recall_at_10 value: 89.047
  - type: recall_at_100 value: 99.36
  - type: recall_at_1000 value: 99.644
  - type: recall_at_3 value: 67.283
  - type: recall_at_5 value: 78.236
- task: type: 分类 dataset: type: PL-MTEB/cbd name: MTEB CBD config: 默认 split: 测试 revision: 无 metrics:
  - type: 准确率 value: 69.33
  - type: ap value: 22.972409521444508
  - type: f1 value: 58.91072163784952
- task: type: 对分类 dataset: type: PL-MTEB/cdsce-pairclassification name: MTEB CDSC-E config: 默认 split: 测试 revision: 无 metrics:
  - type: cos_sim_accuracy value: 89.8
  - type: cos_sim_ap value: 79.87039801032493
  - type: cos_sim_f1 value: 68.53932584269663
  - type: cos_sim_precision value: 73.49397590361446
  - type: cos_sim_recall value: 64.21052631578948
  - type: dot_accuracy value: 86.1
  - type: dot_ap value: 63.684975861694035
  - type: dot_f1 value: 63.61746361746362
  - type: dot_precision value: 52.57731958762887
  - type: dot_recall value: 80.52631578947368
  - type: euclidean_accuracy value: 89.8
  - type: euclidean_ap value: 79.7527126811392
  - type: euclidean_f1 value: 68.46361185983827
  - type: euclidean_precision value: 70.1657458563536
  - type: euclidean_recall value: 66.84210526315789
  - type: manhattan_accuracy value: 89.7
  - type: manhattan_ap value: 79.64632771093657
  - type: manhattan_f1 value: 68.4931506849315
  - type: manhattan_precision value: 71.42857142857143
  - type: manhattan_recall value: 65.78947368421053
  - type: max_accuracy value: 89.8
  - type: max_ap value: 79.87039801032493
  - type: max_f1 value: 68.53932584269663
- task: type: STS dataset: type: PL-MTEB/cdscr-sts name: MTEB CDSC-R config: 默认 split: 测试 revision: 无 metrics:
  - type: cos_sim_pearson value: 92.1088892402831
  - type: cos_sim_spearman value: 92.54126377343101
  - type: euclidean_pearson value: 91.99022371986013
  - type: euclidean_spearman value: 92.55235973775511
  - type: manhattan_pearson value: 91.92170171331357
  - type: manhattan_spearman value: 92.47797623672449
- task: type: 检索 dataset: type: dbpedia-pl name: MTEB DBPedia-PL config: 默认 split: 测试 revision: 无 metrics:
  - type: map_at_1 value: 8.683
  - type: map_at_10 value: 18.9
  - type: map_at_100 value: 26.933
  - type: map_at_1000 value: 28.558
  - type: map_at_3 value: 13.638
  - type: map_at_5 value: 15.9
  - type: mrr_at_1 value: 63.74999999999999
  - type: mrr_at_10 value: 73.566
  - type: mrr_at_100 value: 73.817
  - type: mrr_at_1000 value: 73.824
  - type: mrr_at_3 value: 71.875
  - type: mrr_at_5 value: 73.2
  - type: ndcg_at_1 value: 53.125
  - type: ndcg_at_10 value: 40.271
  - type: ndcg_at_100 value: 45.51
  - type: ndcg_at_1000 value: 52.968
  - type: ndcg_at_3 value: 45.122
  - type: ndcg_at_5 value: 42.306
  - type: precision_at_1 value: 63.74999999999999
  - type: precision_at_10 value: 31.55
  - type: precision_at_100 value: 10.440000000000001
  - type: precision_at_1000 value: 2.01
  - type: precision_at_3 value: 48.333
  - type: precision_at_5 value: 40.5
  - type: recall_at_1 value: 8.683
  - type: recall_at_10 value: 24.63
  - type: recall_at_100 value: 51.762
  - type: recall_at_1000 value: 75.64999999999999
  - type: recall_at_3 value: 15.136
  - type: recall_at_5 value: 18.678
- task: type: 检索 dataset: type: fiqa-pl name: MTEB FiQA-PL config: 默认 split: 测试 revision: 无 metrics:
  - type: map_at_1 value: 19.872999999999998
  - type: map_at_10 value: 32.923
  - type: map_at_100 value: 34.819
  - type: map_at_1000 value: 34.99
  - type: map_at_3 value: 28.500999999999998
  - type: map_at_5 value: 31.087999999999997
  - type: mrr_at_1 value: 40.432
  - type: mrr_at_10 value: 49.242999999999995
  - type: mrr_at_100 value: 50.014
  - type: mrr_at_1000 value: 50.05500000000001
  - type: mrr_at_3 value: 47.144999999999996
  - type: mrr_at_5 value: 48.171
  - type: ndcg_at_1 value: 40.586
  - type: ndcg_at_10 value: 40.887
  - type: ndcg_at_100 value: 47.701
  - type: ndcg_at_1000 value: 50.624
  - type: ndcg_at_3 value: 37.143
  - type: ndcg_at_5 value: 38.329
  - type: precision_at_1 value: 40.586
  - type: precision_at_10 value: 11.497
  - type: precision_at_100 value: 1.838
  - type: precision_at_1000 value: 0.23700000000000002
  - type: precision_at_3 value: 25.0
  - type: precision_at_5 value: 18.549
  - type: recall_at_1 value: 19.872999999999998
  - type: recall_at_10 value: 48.073
  - type: recall_at_100 value: 73.473
  - type: recall_at_1000 value: 90.94
  - type: recall_at_3 value: 33.645
  - type: recall_at_5 value: 39.711
- task: type: 检索 dataset: type: hotpotqa-pl name: MTEB HotpotQA-PL config: 默认 split: 测试 revision: 无 metrics:
  - type: map_at_1 value: 39.399
  - type: map_at_10 value: 62.604000000000006
  - type: map_at_100 value: 63.475
  - type: map_at_1000 value: 63.534
  - type: map_at_3