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EN
Jina Embeddings V3
J
Jina Embeddings V3
Developed by jinaai
Jina Embeddings V3 is a multilingual sentence embedding model supporting over 100 languages, specializing in sentence similarity and feature extraction tasks.
Downloads 3.7M
Release Time : 9/5/2024
Model Overview
This model is a multilingual sentence embedding model capable of converting text into high-dimensional vector representations for computing sentence similarity and feature extraction. It supports a wide range of languages and is suitable for cross-lingual information retrieval and semantic similarity computation tasks.
Model Features
Multilingual Support
Supports over 100 languages, including major languages and various minority languages
Sentence Embeddings
Converts sentences into high-dimensional vector representations for easy computation of semantic similarity
Feature Extraction
Capable of extracting meaningful feature representations from text
Model Capabilities
Sentence similarity computation
Multilingual text embedding
Semantic feature extraction
Cross-lingual information retrieval
Use Cases
Information Retrieval
Cross-lingual Document Retrieval
Find semantically similar content in document collections across different languages
Achieved a primary score of 50.12 on the MTEB ArguAna-PL dataset
Semantic Similarity
Sentence Similarity Computation
Compute semantic similarity between two sentences
Achieved a Spearman correlation coefficient of 43.47 on the MTEB AFQMC dataset
## 🚀 Jina Embeddings V3
*Jina Embeddings V3 is a model designed for feature extraction and sentence similarity tasks. It supports multiple languages and has been evaluated on various MTEB datasets.*
## 📚 Documentation
### Model Information
| Property | Details |
|----------|---------|
| Model Type | jina-embeddings-v3 |
| Training Data | Not specified |
| Library Name | transformers |
| License | cc-by-nc-4.0 |
| Tags | feature-extraction, sentence-similarity, mteb, sentence-transformers |
| Supported Languages | multilingual, af, am, ar, as, az, be, bg, bn, br, bs, ca, cs, cy, da, de, el, en, eo, es, et, eu, fa, fi, fr, fy, ga, gd, gl, gu, ha, he, hi, hr, hu, hy, id, is, it, ja, jv, ka, kk, km, kn, ko, ku, ky, la, lo, lt, lv, mg, mk, ml, mn, mr, ms, my, ne, nl, no, om, or, pa, pl, ps, pt, ro, ru, sa, sd, si, sk, sl, so, sq, sr, su, sv, sw, ta, te, th, tl, tr, ug, uk, ur, uz, vi, xh, yi, zh |
| Inference | false |
### Evaluation Results
#### MTEB AFQMC (default)
- **Task Type**: STS
- **Split**: validation
| Metric | Value |
|--------|-------|
| cosine_pearson | 41.74237700998808 |
| cosine_spearman | 43.4726782647566 |
| euclidean_pearson | 42.244585459479964 |
| euclidean_spearman | 43.525070045169606 |
| main_score | 43.4726782647566 |
| manhattan_pearson | 42.04616728224863 |
| manhattan_spearman | 43.308828270754645 |
| pearson | 41.74237700998808 |
| spearman | 43.4726782647566 |
#### MTEB ArguAna-PL (default)
- **Task Type**: Retrieval
- **Split**: test
| Metric | Value |
|--------|-------|
| main_score | 50.117999999999995 |
| map_at_1 | 24.253 |
| map_at_10 | 40.725 |
| map_at_100 | 41.699999999999996 |
| map_at_1000 | 41.707 |
| map_at_20 | 41.467999999999996 |
| map_at_3 | 35.467 |
| map_at_5 | 38.291 |
| mrr_at_1 | 24.751066856330013 |
| mrr_at_10 | 40.91063808169072 |
| mrr_at_100 | 41.885497923928675 |
| mrr_at_1000 | 41.89301098419842 |
| mrr_at_20 | 41.653552355442514 |
| mrr_at_3 | 35.656709340919775 |
| mrr_at_5 | 38.466097676623946 |
| nauc_map_at_1000_diff1 | 7.503000359807567 |
| nauc_map_at_1000_max | -11.030405164830546 |
| nauc_map_at_1000_std | -8.902792782585117 |
| nauc_map_at_100_diff1 | 7.509899249593199 |
| nauc_map_at_100_max | -11.023581259404406 |
| nauc_map_at_100_std | -8.892241185067272 |
| nauc_map_at_10_diff1 | 7.24369711881512 |
| nauc_map_at_10_max | -10.810000200433278 |
| nauc_map_at_10_std | -8.987230542165776 |
| nauc_map_at_1_diff1 | 11.37175831832417 |
| nauc_map_at_1_max | -13.315221903223055 |
| nauc_map_at_1_std | -9.398199605510275 |
| nauc_map_at_20_diff1 | 7.477364530860648 |
| nauc_map_at_20_max | -10.901251218105566 |
| nauc_map_at_20_std | -8.868148116405925 |
| nauc_map_at_3_diff1 | 6.555548802174882 |
| nauc_map_at_3_max | -12.247274800542934 |
| nauc_map_at_3_std | -9.879475250984811 |
| nauc_map_at_5_diff1 | 7.426588563355882 |
| nauc_map_at_5_max | -11.347695686001805 |
| nauc_map_at_5_std | -9.34441892203972 |
| nauc_mrr_at_1000_diff1 | 5.99737552143614 |
| nauc_mrr_at_1000_max | -11.327205136505727 |
| nauc_mrr_at_1000_std | -8.791079115519503 |
| nauc_mrr_at_100_diff1 | 6.004622525255784 |
| nauc_mrr_at_100_max | -11.320336759899723 |
| nauc_mrr_at_100_std | -8.780602249831777 |
| nauc_mrr_at_10_diff1 | 5.783623516930227 |
| nauc_mrr_at_10_max | -11.095971693467078 |
| nauc_mrr_at_10_std | -8.877242032013582 |
| nauc_mrr_at_1_diff1 | 9.694937537703797 |
| nauc_mrr_at_1_max | -12.531905083727912 |
| nauc_mrr_at_1_std | -8.903992940100146 |
| nauc_mrr_at_20_diff1 | 5.984841206233873 |
| nauc_mrr_at_20_max | -11.195236951048969 |
| nauc_mrr_at_20_std | -8.757266039186018 |
| nauc_mrr_at_3_diff1 | 5.114333824261379 |
| nauc_mrr_at_3_max | -12.64809799843464 |
| nauc_mrr_at_3_std | -9.791146138025184 |
| nauc_mrr_at_5_diff1 | 5.88941606224512 |
| nauc_mrr_at_5_max | -11.763903418071918 |
| nauc_mrr_at_5_std | -9.279175712709446 |
| nauc_ndcg_at_1000_diff1 | 7.076950652226086 |
| nauc_ndcg_at_1000_max | -10.386482092087371 |
| nauc_ndcg_at_1000_std | -8.309190917074046 |
| nauc_ndcg_at_100_diff1 | 7.2329220284865245 |
| nauc_ndcg_at_100_max | -10.208048403220337 |
| nauc_ndcg_at_100_std | -7.997975874274613 |
| nauc_ndcg_at_10_diff1 | 6.065391100006953 |
| nauc_ndcg_at_10_max | -9.046164377601153 |
| nauc_ndcg_at_10_std | -8.34724889697153 |
| nauc_ndcg_at_1_diff1 | 11.37175831832417 |
| nauc_ndcg_at_1_max | -13.315221903223055 |
| nauc_ndcg_at_1_std | -9.398199605510275 |
| nauc_ndcg_at_20_diff1 | 6.949389989202601 |
| nauc_ndcg_at_20_max | -9.35740451760307 |
| nauc_ndcg_at_20_std | -7.761295171828212 |
| nauc_ndcg_at_3_diff1 | 5.051471796151364 |
| nauc_ndcg_at_3_max | -12.158763333711653 |
| nauc_ndcg_at_3_std | -10.078902544421926 |
| nauc_ndcg_at_5_diff1 | 6.527454512611454 |
| nauc_ndcg_at_5_max | -10.525118233848586 |
| nauc_ndcg_at_5_std | -9.120055125584031 |
| nauc_precision_at_1000_diff1 | -10.6495668199151 |
| nauc_precision_at_1000_max | 12.070656425217841 |
| nauc_precision_at_1000_std | 55.844551709649004 |
| nauc_precision_at_100_diff1 | 19.206967129266285 |
| nauc_precision_at_100_max | 16.296851020813456 |
| nauc_precision_at_100_std | 45.60378984257811 |
| nauc_precision_at_10_diff1 | 0.6490335354304879 |
| nauc_precision_at_10_max | 0.5757198255366447 |
| nauc_precision_at_10_std | -4.875847131691451 |
| nauc_precision_at_1_diff1 | 11.37175831832417 |
| nauc_precision_at_1_max | -13.315221903223055 |
| nauc_precision_at_1_std | -9.398199605510275 |
| nauc_precision_at_20_diff1 | 4.899369866929203 |
| nauc_precision_at_20_max | 5.988537297189552 |
| nauc_precision_at_20_std | 4.830900387582837 |
| nauc_precision_at_3_diff1 | 0.8791156910997744 |
| nauc_precision_at_3_max | -11.983373635905993 |
| nauc_precision_at_3_std | -10.646185111581257 |
| nauc_precision_at_5_diff1 | 3.9314486166548432 |
| nauc_precision_at_5_max | -7.798591396895839 |
| nauc_precision_at_5_std | -8.293043407234125 |
| nauc_recall_at_1000_diff1 | -10.649566819918673 |
| nauc_recall_at_1000_max | 12.070656425214647 |
| nauc_recall_at_1000_std | 55.84455170965023 |
| nauc_recall_at_100_diff1 | 19.206967129265127 |
| nauc_recall_at_100_max | 16.296851020813722 |
| nauc_recall_at_100_std | 45.60378984257728 |
| nauc_recall_at_10_diff1 | 0.6490335354304176 |
| nauc_recall_at_10_max | 0.5757198255366095 |
| nauc_recall_at_10_std | -4.875847131691468 |
| nauc_recall_at_1_diff1 | 11.37175831832417 |
| nauc_recall_at_1_max | -13.315221903223055 |
| nauc_recall_at_1_std | -9.398199605510275 |
| nauc_recall_at_20_diff1 | 4.899369866929402 |
| nauc_recall_at_20_max | 5.98853729718968 |
| nauc_recall_at_20_std | 4.830900387582967 |
| nauc_recall_at_3_diff1 | 0.8791156910997652 |
| nauc_recall_at_3_max | -11.983373635905997 |
| nauc_recall_at_3_std | -10.64618511158124 |
| nauc_recall_at_5_diff1 | 3.9314486166548472 |
| nauc_recall_at_5_max | -7.7985913968958585 |
| nauc_recall_at_5_std | -8.293043407234132 |
| ndcg_at_1 | 24.253 |
| ndcg_at_10 | 50.117999999999995 |
| ndcg_at_100 | 54.291999999999994 |
| ndcg_at_1000 | 54.44799999999999 |
| ndcg_at_20 | 52.771 |
| ndcg_at_3 | 39.296 |
| ndcg_at_5 | 44.373000000000005 |
| precision_at_1 | 24.253 |
| precision_at_10 | 8.016 |
| precision_at_100 | 0.984 |
| precision_at_1000 | 0.1 |
| precision_at_20 | 4.527 |
| precision_at_3 | 16.808999999999997 |
| precision_at_5 | 12.546 |
| recall_at_1 | 24.253 |
| recall_at_10 | 80.156 |
| recall_at_100 | 98.43499999999999 |
| recall_at_1000 | 99.57300000000001 |
| recall_at_20 | 90.54100000000001 |
| recall_at_3 | 50.427 |
| recall_at_5 | 62.731 |
#### MTEB DBPedia-PL (default)
- **Task Type**: Retrieval
- **Split**: test
| Metric | Value |
|--------|-------|
| main_score | 34.827000000000005 |
| map_at_1 | 7.049999999999999 |
| map_at_10 | 14.982999999999999 |
| map_at_100 | 20.816000000000003 |
| map_at_1000 | 22.33 |
| map_at_20 | 17.272000000000002 |
| map_at_3 | 10.661 |
| map_at_5 | 12.498 |
| mrr_at_1 | 57.25 |
| mrr_at_10 | 65.81934523809524 |
| mrr_at_100 | 66.2564203928212 |
| mrr_at_1000 | 66.27993662923856 |
| mrr_at_20 | 66.0732139130649 |
| mrr_at_3 | 64.08333333333333 |
| mrr_at_5 | 65.27083333333333 |
| nauc_map_at_1000_diff1 | 16.41780871174038 |
| nauc_map_at_1000_max | 30.193946325654654 |
| nauc_map_at_1000_std | 31.46095497039037 |
| nauc_map_at_100_diff1 | 18.57903165498531 |
| nauc_map_at_100_max | 29.541476938623262 |
| nauc_map_at_100_std | 28.228604103301052 |
| nauc_map_at_10_diff1 | 24.109434489748946 |
| nauc_map_at_10_max | 21.475954208048968 |
| nauc_map_at_10_std | 9.964464537806988 |
| nauc_map_at_1_diff1 | 38.67437644802124 |
| nauc_map_at_1_max | 14.52136658726491 |
| nauc_map_at_1_std | -2.8981666782088755 |
| nauc_map_at_20_diff1 | 21.42547228801935 |
| nauc_map_at_20_max | 25.04510402960458 |
| nauc_map_at_20_std | 16.533079346431155 |
| nauc_map_at_3_diff1 | 26.63648858245477 |
| nauc_map_at_3_max | 13.632235789780415 |
| nauc_map_at_3_std | -0.40129174577700716 |
| nauc_map_at_5_diff1 | 24.513861031197933 |
| nauc_map_at_5_max | 16.599888813946688 |
| nauc_map_at_5_std | 3.4448514739556346 |
| nauc_mrr_at_1000_diff1 | 36.57353464537154 |
| nauc_mrr_at_1000_max | 55.34763483979515 |
| nauc_mrr_at_1000_std | 40.3722796438533 |
| ... | ... |
## 📄 License
This project is licensed under the CC BY-NC 4.0 license.
This README has been translated into English and structured for better readability. It includes key information about the model, its evaluation results on different datasets, and the license details. The evaluation results are presented in tabular form for easy comparison.
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