🧠
multilingual-e5-large-instruct model by intfloat
⭐ 18.3
🧠
multilingual-e5-large-instruct
by intfloat Model
ID: hf-model--intfloat--multilingual-e5-large-instruct
FNI 18.3
Top 74%
Audited 18.3 FNI Score
Tiny 0.56B Params
4k Context
Hot 1.3M Downloads
8G GPU ~2GB Est. VRAM
⚡ Quick Commands
🦙 Ollama Run
ollama run multilingual-e5-large-instruct 🤗 HF Download
huggingface-cli download intfloat/multilingual-e5-large-instruct 📦 Install Lib
pip install -U transformers 📊
Engineering Specs
⚡ Hardware
Parameters
0.56B
Architecture
XLMRobertaModel
Context Length
4K
Model Size
8.3GB
🧠 Lifecycle
Library
-
Precision
float16
Tokenizer
-
🌐 Identity
Source
HuggingFace
License
Open Access
💾
Est. VRAM Benchmark
~1.7GB
Analyze Hardware
* Technical estimation for FP16/Q4 weights. Does not include OS overhead or long-context batching. For Technical Reference Only.
🕸️ Neural Mesh Hub
Interconnecting Research, Data & Ecosystem
📈 Interest Trend
--
📡 Knowledge Mesh Synchronizing...
Real-time Trend Indexing In-Progress
Real-time Trend Indexing In-Progress
* Real-time activity index across HuggingFace, GitHub and Research citations.
🔍 Semantic Keywords
🏷️ sentence-transformers 🏷️ onnx 🏷️ safetensors 🏷️ xlm-roberta 🏷️ feature-extraction 🏷️ mteb 🏷️ transformers 🏷️ 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 🏷️ arxiv:2402.05672 🏷️ arxiv:2401.00368 🏷️ arxiv:2104.08663 🏷️ arxiv:2210.07316 🏷️ license:mit 🏷️ model-index 🏷️ text-embeddings-inference 🏷️ endpoints_compatible 🏷️ region:us
No similar models found.
Social Proof
FNI RankTop 74%
HuggingFace Hub
582Likes
1.3MDownloads
🔬Technical Deep Dive
Full Specifications [+]▾
🚀 What's Next?
⚡ Quick Commands
🦙 Ollama Run
ollama run multilingual-e5-large-instruct 🤗 HF Download
huggingface-cli download intfloat/multilingual-e5-large-instruct 📦 Install Lib
pip install -U transformers 🖥️
Hardware Compatibility
Multi-Tier Validation Matrix
Live Sync
🎮 Compatible
RTX 3060 / 4060 Ti
Entry 8GB VRAM
🎮 Compatible
RTX 4070 Super
Mid 12GB VRAM
💻 Compatible
RTX 4080 / Mac M3
High 16GB VRAM
🚀 Compatible
RTX 3090 / 4090
Pro 24GB VRAM
🏗️ Compatible
RTX 6000 Ada
Workstation 48GB VRAM
🏭 Compatible
A100 / H100
Datacenter 80GB VRAM
ℹ️
Pro Tip: Compatibility is estimated for 4-bit quantization (Q4). High-precision (FP16) or ultra-long context windows will significantly increase VRAM requirements.
README
tags:
- mteb
- sentence-transformers
- transformers model-index:
- name: multilingual-e5-large-instruct
results:
- task:
type: Classification
dataset:
type: mteb/amazon_counterfactual
name: MTEB AmazonCounterfactualClassification (en)
config: en
split: test
revision: e8379541af4e31359cca9fbcf4b00f2671dba205
metrics:
- type: accuracy value: 76.23880597014924
- type: ap value: 39.07351965022687
- type: f1 value: 70.04836733862683
- task:
type: Classification
dataset:
type: mteb/amazon_counterfactual
name: MTEB AmazonCounterfactualClassification (de)
config: de
split: test
revision: e8379541af4e31359cca9fbcf4b00f2671dba205
metrics:
- type: accuracy value: 66.71306209850107
- type: ap value: 79.01499914759529
- type: f1 value: 64.81951817560703
- task:
type: Classification
dataset:
type: mteb/amazon_counterfactual
name: MTEB AmazonCounterfactualClassification (en-ext)
config: en-ext
split: test
revision: e8379541af4e31359cca9fbcf4b00f2671dba205
metrics:
- type: accuracy value: 73.85307346326837
- type: ap value: 22.447519885878737
- type: f1 value: 61.0162730745633
- task:
type: Classification
dataset:
type: mteb/amazon_counterfactual
name: MTEB AmazonCounterfactualClassification (ja)
config: ja
split: test
revision: e8379541af4e31359cca9fbcf4b00f2671dba205
metrics:
- type: accuracy value: 76.04925053533191
- type: ap value: 23.44983217128922
- type: f1 value: 62.5723230907759
- task:
type: Classification
dataset:
type: mteb/amazon_polarity
name: MTEB AmazonPolarityClassification
config: default
split: test
revision: e2d317d38cd51312af73b3d32a06d1a08b442046
metrics:
- type: accuracy value: 96.28742500000001
- type: ap value: 94.8449918887462
- type: f1 value: 96.28680923610432
- task:
type: Classification
dataset:
type: mteb/amazon_reviews_multi
name: MTEB AmazonReviewsClassification (en)
config: en
split: test
revision: 1399c76144fd37290681b995c656ef9b2e06e26d
metrics:
- type: accuracy value: 56.716
- type: f1 value: 55.76510398266401
- task:
type: Classification
dataset:
type: mteb/amazon_reviews_multi
name: MTEB AmazonReviewsClassification (de)
config: de
split: test
revision: 1399c76144fd37290681b995c656ef9b2e06e26d
metrics:
- type: accuracy value: 52.99999999999999
- type: f1 value: 52.00829994765178
- task:
type: Classification
dataset:
type: mteb/amazon_reviews_multi
name: MTEB AmazonReviewsClassification (es)
config: es
split: test
revision: 1399c76144fd37290681b995c656ef9b2e06e26d
metrics:
- type: accuracy value: 48.806000000000004
- type: f1 value: 48.082345914983634
- task:
type: Classification
dataset:
type: mteb/amazon_reviews_multi
name: MTEB AmazonReviewsClassification (fr)
config: fr
split: test
revision: 1399c76144fd37290681b995c656ef9b2e06e26d
metrics:
- type: accuracy value: 48.507999999999996
- type: f1 value: 47.68752844642045
- task:
type: Classification
dataset:
type: mteb/amazon_reviews_multi
name: MTEB AmazonReviewsClassification (ja)
config: ja
split: test
revision: 1399c76144fd37290681b995c656ef9b2e06e26d
metrics:
- type: accuracy value: 47.709999999999994
- type: f1 value: 47.05870376637181
- task:
type: Classification
dataset:
type: mteb/amazon_reviews_multi
name: MTEB AmazonReviewsClassification (zh)
config: zh
split: test
revision: 1399c76144fd37290681b995c656ef9b2e06e26d
metrics:
- type: accuracy value: 44.662000000000006
- type: f1 value: 43.42371965372771
- task:
type: Retrieval
dataset:
type: arguana
name: MTEB ArguAna
config: default
split: test
revision: None
metrics:
- type: map_at_1 value: 31.721
- type: map_at_10 value: 49.221
- type: map_at_100 value: 49.884
- type: map_at_1000 value: 49.888
- type: map_at_3 value: 44.31
- type: map_at_5 value: 47.276
- type: mrr_at_1 value: 32.432
- type: mrr_at_10 value: 49.5
- type: mrr_at_100 value: 50.163000000000004
- type: mrr_at_1000 value: 50.166
- type: mrr_at_3 value: 44.618
- type: mrr_at_5 value: 47.541
- type: ndcg_at_1 value: 31.721
- type: ndcg_at_10 value: 58.384
- type: ndcg_at_100 value: 61.111000000000004
- type: ndcg_at_1000 value: 61.187999999999995
- type: ndcg_at_3 value: 48.386
- type: ndcg_at_5 value: 53.708999999999996
- type: precision_at_1 value: 31.721
- type: precision_at_10 value: 8.741
- type: precision_at_100 value: 0.991
- type: precision_at_1000 value: 0.1
- type: precision_at_3 value: 20.057
- type: precision_at_5 value: 14.609
- type: recall_at_1 value: 31.721
- type: recall_at_10 value: 87.411
- type: recall_at_100 value: 99.075
- type: recall_at_1000 value: 99.644
- type: recall_at_3 value: 60.171
- type: recall_at_5 value: 73.044
- task:
type: Clustering
dataset:
type: mteb/arxiv-clustering-p2p
name: MTEB ArxivClusteringP2P
config: default
split: test
revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
metrics:
- type: v_measure value: 46.40419580759799
- task:
type: Clustering
dataset:
type: mteb/arxiv-clustering-s2s
name: MTEB ArxivClusteringS2S
config: default
split: test
revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
metrics:
- type: v_measure value: 40.48593255007969
- task:
type: Reranking
dataset:
type: mteb/askubuntudupquestions-reranking
name: MTEB AskUbuntuDupQuestions
config: default
split: test
revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
metrics:
- type: map value: 63.889179122289995
- type: mrr value: 77.61146286769556
- task:
type: STS
dataset:
type: mteb/biosses-sts
name: MTEB BIOSSES
config: default
split: test
revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
metrics:
- type: cos_sim_pearson value: 88.15075203727929
- type: cos_sim_spearman value: 86.9622224570873
- type: euclidean_pearson value: 86.70473853624121
- type: euclidean_spearman value: 86.9622224570873
- type: manhattan_pearson value: 86.21089380980065
- type: manhattan_spearman value: 86.75318154937008
- task:
type: BitextMining
dataset:
type: mteb/bucc-bitext-mining
name: MTEB BUCC (de-en)
config: de-en
split: test
revision: d51519689f32196a32af33b075a01d0e7c51e252
metrics:
- type: accuracy value: 99.65553235908142
- type: f1 value: 99.60681976339595
- type: precision value: 99.58246346555325
- type: recall value: 99.65553235908142
- task:
type: BitextMining
dataset:
type: mteb/bucc-bitext-mining
name: MTEB BUCC (fr-en)
config: fr-en
split: test
revision: d51519689f32196a32af33b075a01d0e7c51e252
metrics:
- type: accuracy value: 99.26260180497468
- type: f1 value: 99.14520507740848
- type: precision value: 99.08650671362535
- type: recall value: 99.26260180497468
- task:
type: BitextMining
dataset:
type: mteb/bucc-bitext-mining
name: MTEB BUCC (ru-en)
config: ru-en
split: test
revision: d51519689f32196a32af33b075a01d0e7c51e252
metrics:
- type: accuracy value: 98.07412538967787
- type: f1 value: 97.86629719431936
- type: precision value: 97.76238309664012
- type: recall value: 98.07412538967787
- task:
type: BitextMining
dataset:
type: mteb/bucc-bitext-mining
name: MTEB BUCC (zh-en)
config: zh-en
split: test
revision: d51519689f32196a32af33b075a01d0e7c51e252
metrics:
- type: accuracy value: 99.42074776197998
- type: f1 value: 99.38564156573635
- type: precision value: 99.36808846761454
- type: recall value: 99.42074776197998
- task:
type: Classification
dataset:
type: mteb/banking77
name: MTEB Banking77Classification
config: default
split: test
revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
metrics:
- type: accuracy value: 85.73376623376623
- type: f1 value: 85.68480707214599
- task:
type: Clustering
dataset:
type: mteb/biorxiv-clustering-p2p
name: MTEB BiorxivClusteringP2P
config: default
split: test
revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
metrics:
- type: v_measure value: 40.935218072113855
- task:
type: Clustering
dataset:
type: mteb/biorxiv-clustering-s2s
name: MTEB BiorxivClusteringS2S
config: default
split: test
revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
metrics:
- type: v_measure value: 36.276389017675264
- task:
type: Retrieval
dataset:
type: BeIR/cqadupstack
name: MTEB CQADupstackRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1 value: 27.764166666666668
- type: map_at_10 value: 37.298166666666674
- type: map_at_100 value: 38.530166666666666
- type: map_at_1000 value: 38.64416666666667
- type: map_at_3 value: 34.484833333333334
- type: map_at_5 value: 36.0385
- type: mrr_at_1 value: 32.93558333333333
- type: mrr_at_10 value: 41.589749999999995
- type: mrr_at_100 value: 42.425333333333334
- type: mrr_at_1000 value: 42.476333333333336
- type: mrr_at_3 value: 39.26825
- type: mrr_at_5 value: 40.567083333333336
- type: ndcg_at_1 value: 32.93558333333333
- type: ndcg_at_10 value: 42.706583333333334
- type: ndcg_at_100 value: 47.82483333333333
- type: ndcg_at_1000 value: 49.95733333333334
- type: ndcg_at_3 value: 38.064750000000004
- type: ndcg_at_5 value: 40.18158333333333
- type: precision_at_1 value: 32.93558333333333
- type: precision_at_10 value: 7.459833333333334
- type: precision_at_100 value: 1.1830833333333335
- type: precision_at_1000 value: 0.15608333333333332
- type: precision_at_3 value: 17.5235
- type: precision_at_5 value: 12.349833333333333
- type: recall_at_1 value: 27.764166666666668
- type: recall_at_10 value: 54.31775
- type: recall_at_100 value: 76.74350000000001
- type: recall_at_1000 value: 91.45208333333332
- type: recall_at_3 value: 41.23425
- type: recall_at_5 value: 46.73983333333334
- task:
type: Retrieval
dataset:
type: climate-fever
name: MTEB ClimateFEVER
config: default
split: test
revision: None
metrics:
- type: map_at_1 value: 12.969
- type: map_at_10 value: 21.584999999999997
- type: map_at_100 value: 23.3
- type: map_at_1000 value: 23.5
- type: map_at_3 value: 18.218999999999998
- type: map_at_5 value: 19.983
- type: mrr_at_1 value: 29.316
- type: mrr_at_10 value: 40.033
- type: mrr_at_100 value: 40.96
- type: mrr_at_1000 value: 41.001
- type: mrr_at_3 value: 37.123
- type: mrr_at_5 value: 38.757999999999996
- type: ndcg_at_1 value: 29.316
- type: ndcg_at_10 value: 29.858
- type: ndcg_at_100 value: 36.756
- type: ndcg_at_1000 value: 40.245999999999995
- type: ndcg_at_3 value: 24.822
- type: ndcg_at_5 value: 26.565
- type: precision_at_1 value: 29.316
- type: precision_at_10 value: 9.186
- type: precision_at_100 value: 1.6549999999999998
- type: precision_at_1000 value: 0.22999999999999998
- type: precision_at_3 value: 18.436
- type: precision_at_5 value: 13.876
- type: recall_at_1 value: 12.969
- type: recall_at_10 value: 35.142
- type: recall_at_100 value: 59.143
- type: recall_at_1000 value: 78.594
- type: recall_at_3 value: 22.604
- type: recall_at_5 value: 27.883000000000003
- task:
type: Retrieval
dataset:
type: dbpedia-entity
name: MTEB DBPedia
config: default
split: test
revision: None
metrics:
- type: map_at_1 value: 8.527999999999999
- type: map_at_10 value: 17.974999999999998
- type: map_at_100 value: 25.665
- type: map_at_1000 value: 27.406000000000002
- type: map_at_3 value: 13.017999999999999
- type: map_at_5 value: 15.137
- type: mrr_at_1 value: 62.5
- type: mrr_at_10 value: 71.891
- type: mrr_at_100 value: 72.294
- type: mrr_at_1000 value: 72.296
- type: mrr_at_3 value: 69.958
- type: mrr_at_5 value: 71.121
- type: ndcg_at_1 value: 50.875
- type: ndcg_at_10 value: 38.36
- type: ndcg_at_100 value: 44.235
- type: ndcg_at_1000 value: 52.154
- type: ndcg_at_3 value: 43.008
- type: ndcg_at_5 value: 40.083999999999996
- type: precision_at_1 value: 62.5
- type: precision_at_10 value: 30.0
- type: precision_at_100 value: 10.038
- type: precision_at_1000 value: 2.0869999999999997
- type: precision_at_3 value: 46.833000000000006
- type: precision_at_5 value: 38.800000000000004
- type: recall_at_1 value: 8.527999999999999
- type: recall_at_10 value: 23.828
- type: recall_at_100 value: 52.322
- type: recall_at_1000 value: 77.143
- type: recall_at_3 value: 14.136000000000001
- type: recall_at_5 value: 17.761
- task:
type: Classification
dataset:
type: mteb/emotion
name: MTEB EmotionClassification
config: default
split: test
revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
metrics:
- type: accuracy value: 51.51
- type: f1 value: 47.632159862049896
- task:
type: Retrieval
dataset:
type: fever
name: MTEB FEVER
config: default
split: test
revision: None
metrics:
- type: map_at_1 value: 60.734
- type: map_at_10 value: 72.442
- type: map_at_100 value: 72.735
- type: map_at_1000 value: 72.75
- type: map_at_3 value: 70.41199999999999
- type: map_at_5 value: 71.80499999999999
- type: mrr_at_1 value: 65.212
- type: mrr_at_10 value: 76.613
- type: mrr_at_100 value: 76.79899999999999
- type: mrr_at_1000 value: 76.801
- type: mrr_at_3 value: 74.8
- type: mrr_at_5 value: 76.12400000000001
- type: ndcg_at_1 value: 65.212
- type: ndcg_at_10 value: 77.988
- type: ndcg_at_100 value: 79.167
- type: ndcg_at_1000 value: 79.452
- type: ndcg_at_3 value: 74.362
- type: ndcg_at_5 value: 76.666
- type: precision_at_1 value: 65.212
- type: precision_at_10 value: 10.003
- type: precision_at_100 value: 1.077
- type: precision_at_1000 value: 0.11199999999999999
- type: precision_at_3 value: 29.518
- type: precision_at_5 value: 19.016
- type: recall_at_1 value: 60.734
- type: recall_at_10 value: 90.824
- type: recall_at_100 value: 95.71600000000001
- type: recall_at_1000 value: 97.577
- type: recall_at_3 value: 81.243
- type: recall_at_5 value: 86.90299999999999
- task:
type: Retrieval
dataset:
type: fiqa
name: MTEB FiQA2018
config: default
split: test
revision: None
metrics:
- type: map_at_1 value: 23.845
- type: map_at_10 value: 39.281
- type: map_at_100 value: 41.422
- type: map_at_1000 value: 41.593
- type: map_at_3 value: 34.467
- type: map_at_5 value: 37.017
- type: mrr_at_1 value: 47.531
- type: mrr_at_10 value: 56.204
- type: mrr_at_100 value: 56.928999999999995
- type: mrr_at_1000 value: 56.962999999999994
- type: mrr_at_3 value: 54.115
- type: mrr_at_5 value: 55.373000000000005
- type: ndcg_at_1 value: 47.531
- type: ndcg_at_10 value: 47.711999999999996
- type: ndcg_at_100 value: 54.510999999999996
- type: ndcg_at_1000 value: 57.103
- type: ndcg_at_3 value: 44.145
- type: ndcg_at_5 value: 45.032
- type: precision_at_1 value: 47.531
- type: precision_at_10 value: 13.194
- type: precision_at_100 value: 2.045
- type: precision_at_1000 value: 0.249
- type: precision_at_3 value: 29.424
- type: precision_at_5 value: 21.451
- type: recall_at_1 value: 23.845
- type: recall_at_10 value: 54.967
- type: recall_at_100 value: 79.11399999999999
- type: recall_at_1000 value: 94.56700000000001
- type: recall_at_3 value: 40.256
- type: recall_at_5 value: 46.215
- task:
type: Retrieval
dataset:
type: hotpotqa
name: MTEB HotpotQA
config: default
split: test
revision: None
metrics:
- type: map_at_1 value: 37.819
- type: map_at_10 value: 60.889
- type: map_at_100 value: 61.717999999999996
- type: map_at_1000 value: 61.778
- type: map_at_3 value: 57.254000000000005
- type: map_at_5 value: 59.541
- type: mrr_at_1 value: 75.638
- type: mrr_at_10 value: 82.173
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revision: None
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split: test
revision: None
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- type: mrr_at_10 value: 88.301
- type: mrr_at_100 value: 88.383
- type: mrr_at_1000 value: 88.384
- type: mrr_at_3 value: 87.37
- type: mrr_at_5 value: 88.035
- type: ndcg_at_1 value: 82.12
- type: ndcg_at_10 value: 89.149
- type: ndcg_at_100 value: 90.235
- type: ndcg_at_1000 value: 90.307
- type: ndcg_at_3 value: 86.37599999999999
- type: ndcg_at_5 value: 87.964
- type: precision_at_1 value: 82.12
- type: precision_at_10 value: 13.56
- type: precision_at_100 value: 1.539
- type: precision_at_1000 value: 0.157
- type: precision_at_3 value: 37.88
- type: precision_at_5 value: 24.92
- type: recall_at_1 value: 71.241
- type: recall_at_10 value: 96.128
- type: recall_at_100 value: 99.696
- type: recall_at_1000 value: 99.994
- type: recall_at_3 value: 88.181
- type: recall_at_5 value: 92.694
- task:
type: Clustering
dataset:
type: mteb/reddit-clustering
name: MTEB RedditClustering
config: default
split: test
revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
metrics:
- type: v_measure value: 56.59757799655151
- task:
type: Clustering
dataset:
type: mteb/reddit-clustering-p2p
name: MTEB RedditClusteringP2P
config: default
split: test
revision: 282350215ef01743dc01b456c7f5241fa8937f16
metrics:
- type: v_measure value: 64.27391998854624
- task:
type: Retrieval
dataset:
type: scidocs
name: MTEB SCIDOCS
config: default
split: test
revision: None
metrics:
- type: map_at_1 value: 4.243
- type: map_at_10 value: 10.965
- type: map_at_100 value: 12.934999999999999
- type: map_at_1000 value: 13.256
- type: map_at_3 value: 7.907
- type: map_at_5 value: 9.435
- type: mrr_at_1 value: 20.9
- type: mrr_at_10 value: 31.849
- type: mrr_at_100 value: 32.964
- type: mrr_at_1000 value: 33.024
- type: mrr_at_3 value: 28.517
- type: mrr_at_5 value: 30.381999999999998
- type: ndcg_at_1 value: 20.9
- type: ndcg_at_10 value: 18.723
- type: ndcg_at_100 value: 26.384999999999998
- type: ndcg_at_1000 value: 32.114
- type: ndcg_at_3 value: 17.753
- type: ndcg_at_5 value: 15.558
- type: precision_at_1 value: 20.9
- type: precision_at_10 value: 9.8
- type: precision_at_100 value: 2.078
- type: precision_at_1000 value: 0.345
- type: precision_at_3 value: 16.900000000000002
- type: precision_at_5 value: 13.88
- type: recall_at_1 value: 4.243
- type: recall_at_10 value: 19.885
- type: recall_at_100 value: 42.17
- type: recall_at_1000 value: 70.12
- type: recall_at_3 value: 10.288
- type: recall_at_5 value: 14.072000000000001
- task:
type: STS
dataset:
type: mteb/sickr-sts
name: MTEB SICK-R
config: default
split: test
revision: a6ea5a8cab320b040a23452cc28066d9beae2cee
metrics:
- type: cos_sim_pearson value: 85.84209174935282
- type: cos_sim_spearman value: 81.73248048438833
- type: euclidean_pearson value: 83.02810070308149
- type: euclidean_spearman value: 81.73248295679514
- type: manhattan_pearson value: 82.95368060376002
- type: manhattan_spearman value: 81.60277910998718
- task:
type: STS
dataset:
type: mteb/sts12-sts
name: MTEB STS12
config: default
split: test
revision: a0d554a64d88156834ff5ae9920b964011b16384
metrics:
- type: cos_sim_pearson value: 88.52628804556943
- type: cos_sim_spearman value: 82.5713913555672
- type: euclidean_pearson value: 85.8796774746988
- type: euclidean_spearman value: 82.57137506803424
- type: manhattan_pearson value: 85.79671002960058
- type: manhattan_spearman value: 82.49445981618027
- task:
type: STS
dataset:
type: mteb/sts13-sts
name: MTEB STS13
config: default
split: test
revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
metrics:
- type: cos_sim_pearson value: 86.23682503505542
- type: cos_sim_spearman value: 87.15008956711806
- type: euclidean_pearson value: 86.79805401524959
- type: euclidean_spearman value: 87.15008956711806
- type: manhattan_pearson value: 86.65298502699244
- type: manhattan_spearman value: 86.97677821948562
- task:
type: STS
dataset:
type: mteb/sts14-sts
name: MTEB STS14
config: default
split: test
revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
metrics:
- type: cos_sim_pearson value: 85.63370304677802
- type: cos_sim_spearman value: 84.97105553540318
- type: euclidean_pearson value: 85.28896108687721
- type: euclidean_spearman value: 84.97105553540318
- type: manhattan_pearson value: 85.09663190337331
- type: manhattan_spearman value: 84.79126831644619
- task:
type: STS
dataset:
type: mteb/sts15-sts
name: MTEB STS15
config: default
split: test
revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
metrics:
- type: cos_sim_pearson value: 90.2614838800733
- type: cos_sim_spearman value: 91.0509162991835
- type: euclidean_pearson value: 90.33098317533373
- type: euclidean_spearman value: 91.05091625871644
- type: manhattan_pearson value: 90.26250435151107
- type: manhattan_spearman value: 90.97999594417519
- task:
type: STS
dataset:
type: mteb/sts16-sts
name: MTEB STS16
config: default
split: test
revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
metrics:
- type: cos_sim_pearson value: 85.80480973335091
- type: cos_sim_spearman value: 87.313695492969
- type: euclidean_pearson value: 86.49267251576939
- type: euclidean_spearman value: 87.313695492969
- type: manhattan_pearson value: 86.44019901831935
- type: manhattan_spearman value: 87.24205395460392
- task:
type: STS
dataset:
type: mteb/sts17-crosslingual-sts
name: MTEB STS17 (en-en)
config: en-en
split: test
revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
metrics:
- type: cos_sim_pearson value: 90.05662789380672
- type: cos_sim_spearman value: 90.02759424426651
- type: euclidean_pearson value: 90.4042483422981
- type: euclidean_spearman value: 90.02759424426651
- type: manhattan_pearson value: 90.51446975000226
- type: manhattan_spearman value: 90.08832889933616
- task:
type: STS
dataset:
type: mteb/sts22-crosslingual-sts
name: MTEB STS22 (en)
config: en
split: test
revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80
metrics:
- type: cos_sim_pearson value: 67.5975528273532
- type: cos_sim_spearman value: 67.62969861411354
- type: euclidean_pearson value: 69.224275734323
- type: euclidean_spearman value: 67.62969861411354
- type: manhattan_pearson value: 69.3761447059927
- type: manhattan_spearman value: 67.90921005611467
- task:
type: STS
dataset:
type: mteb/stsbenchmark-sts
name: MTEB STSBenchmark
config: default
split: test
revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
metrics:
- type: cos_sim_pearson value: 87.11244327231684
- type: cos_sim_spearman value: 88.37902438979035
- type: euclidean_pearson value: 87.86054279847336
- type: euclidean_spearman value: 88.37902438979035
- type: manhattan_pearson value: 87.77257757320378
- type: manhattan_spearman value: 88.25208966098123
- task:
type: Reranking
dataset:
type: mteb/scidocs-reranking
name: MTEB SciDocsRR
config: default
split: test
revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
metrics:
- type: map value: 85.87174608143563
- type: mrr value: 96.12836872640794
- task:
type: Retrieval
dataset:
type: scifact
name: MTEB SciFact
config: default
split: test
revision: None
metrics:
- type: map_at_1 value: 57.760999999999996
- type: map_at_10 value: 67.258
- type: map_at_100 value: 67.757
- type: map_at_1000 value: 67.78800000000001
- type: map_at_3 value: 64.602
- type: map_at_5 value: 65.64
- type: mrr_at_1 value: 60.667
- type: mrr_at_10 value: 68.441
- type: mrr_at_100 value: 68.825
- type: mrr_at_1000 value: 68.853
- type: mrr_at_3 value: 66.444
- type: mrr_at_5 value: 67.26100000000001
- type: ndcg_at_1 value: 60.667
- type: ndcg_at_10 value: 71.852
- type: ndcg_at_100 value: 73.9
- type: ndcg_at_1000 value: 74.628
- type: ndcg_at_3 value: 67.093
- type: ndcg_at_5 value: 68.58
- type: precision_at_1 value: 60.667
- type: precision_at_10 value: 9.6
- type: precision_at_100 value: 1.0670000000000002
- type: precision_at_1000 value: 0.11199999999999999
- type: precision_at_3 value: 26.111
- type: precision_at_5 value: 16.733
- type: recall_at_1 value: 57.760999999999996
- type: recall_at_10 value: 84.967
- type: recall_at_100 value: 93.833
- type: recall_at_1000 value: 99.333
- type: recall_at_3 value: 71.589
- type: recall_at_5 value: 75.483
- task:
type: PairClassification
dataset:
type: mteb/sprintduplicatequestions-pairclassification
name: MTEB SprintDuplicateQuestions
config: default
split: test
revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
metrics:
- type: cos_sim_accuracy value: 99.66633663366336
- type: cos_sim_ap value: 91.17685358899108
- type: cos_sim_f1 value: 82.16818642350559
- type: cos_sim_precision value: 83.26488706365504
- type: cos_sim_recall value: 81.10000000000001
- type: dot_accuracy value: 99.66633663366336
- type: dot_ap value: 91.17663411119032
- type: dot_f1 value: 82.16818642350559
- type: dot_precision value: 83.26488706365504
- type: dot_recall value: 81.10000000000001
- type: euclidean_accuracy value: 99.66633663366336
- type: euclidean_ap value: 91.17685189882275
- type: euclidean_f1 value: 82.16818642350559
- type: euclidean_precision value: 83.26488706365504
- type: euclidean_recall value: 81.10000000000001
- type: manhattan_accuracy value: 99.66633663366336
- type: manhattan_ap value: 91.2241619496737
- type: manhattan_f1 value: 82.20472440944883
- type: manhattan_precision value: 86.51933701657458
- type: manhattan_recall value: 78.3
- type: max_accuracy value: 99.66633663366336
- type: max_ap value: 91.2241619496737
- type: max_f1 value: 82.20472440944883
- task:
type: Clustering
dataset:
type: mteb/stackexchange-clustering
name: MTEB StackExchangeClustering
config: default
split: test
revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
metrics:
- type: v_measure value: 66.85101268897951
- task:
type: Clustering
dataset:
type: mteb/stackexchange-clustering-p2p
name: MTEB StackExchangeClusteringP2P
config: default
split: test
revision: 815ca46b2622cec33ccafc3735d572c266efdb44
metrics:
- type: v_measure value: 42.461184054706905
- task:
type: Reranking
dataset:
type: mteb/stackoverflowdupquestions-reranking
name: MTEB StackOverflowDupQuestions
config: default
split: test
revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
metrics:
- type: map value: 51.44542568873886
- type: mrr value: 52.33656151854681
- task:
type: Summarization
dataset:
type: mteb/summeval
name: MTEB SummEval
config: default
split: test
revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
metrics:
- type: cos_sim_pearson value: 30.75982974997539
- type: cos_sim_spearman value: 30.385405026539914
- type: dot_pearson value: 30.75982433546523
- type: dot_spearman value: 30.385405026539914
- task:
type: Retrieval
dataset:
type: trec-covid
name: MTEB TRECCOVID
config: default
split: test
revision: None
metrics:
- type: map_at_1 value: 0.22799999999999998
- type: map_at_10 value: 2.064
- type: map_at_100 value: 13.056000000000001
- type: map_at_1000 value: 31.747999999999998
- type: map_at_3 value: 0.67
- type: map_at_5 value: 1.097
- type: mrr_at_1 value: 90.0
- type: mrr_at_10 value: 94.667
- type: mrr_at_100 value: 94.667
- type: mrr_at_1000 value: 94.667
- type: mrr_at_3 value: 94.667
- type: mrr_at_5 value: 94.667
- type: ndcg_at_1 value: 86.0
- type: ndcg_at_10 value: 82.0
- type: ndcg_at_100 value: 64.307
- type: ndcg_at_1000 value: 57.023999999999994
- type: ndcg_at_3 value: 85.816
- type: ndcg_at_5 value: 84.904
- type: precision_at_1 value: 90.0
- type: precision_at_10 value: 85.8
- type: precision_at_100 value: 66.46
- type: precision_at_1000 value: 25.202
- type: precision_at_3 value: 90.0
- type: precision_at_5 value: 89.2
- type: recall_at_1 value: 0.22799999999999998
- type: recall_at_10 value: 2.235
- type: recall_at_100 value: 16.185
- type: recall_at_1000 value: 53.620999999999995
- type: recall_at_3 value: 0.7040000000000001
- type: recall_at_5 value: 1.172
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (sqi-eng)
config: sqi-eng
split: test
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
metrics:
- type: accuracy value: 97.39999999999999
- type: f1 value: 96.75
- type: precision value: 96.45
- type: recall value: 97.39999999999999
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (fry-eng)
config: fry-eng
split: test
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
metrics:
- type: accuracy value: 85.54913294797689
- type: f1 value: 82.46628131021194
- type: precision value: 81.1175337186898
- type: recall value: 85.54913294797689
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (kur-eng)
config: kur-eng
split: test
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
metrics:
- type: accuracy value: 81.21951219512195
- type: f1 value: 77.33333333333334
- type: precision value: 75.54878048780488
- type: recall value: 81.21951219512195
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (tur-eng)
config: tur-eng
split: test
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
metrics:
- type: accuracy value: 98.6
- type: f1 value: 98.26666666666665
- type: precision value: 98.1
- type: recall value: 98.6
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (deu-eng)
config: deu-eng
split: test
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
metrics:
- type: accuracy value: 99.5
- type: f1 value: 99.33333333333333
- type: precision value: 99.25
- type: recall value: 99.5
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (nld-eng)
config: nld-eng
split: test
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
metrics:
- type: accuracy value: 97.8
- type: f1 value: 97.2
- type: precision value: 96.89999999999999
- type: recall value: 97.8
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (ron-eng)
config: ron-eng
split: test
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
metrics:
- type: accuracy value: 97.8
- type: f1 value: 97.18333333333334
- type: precision value: 96.88333333333333
- type: recall value: 97.8
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (ang-eng)
config: ang-eng
split: test
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
metrics:
- type: accuracy value: 77.61194029850746
- type: f1 value: 72.81094527363183
- type: precision value: 70.83333333333333
- type: recall value: 77.61194029850746
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (ido-eng)
config: ido-eng
split: test
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
metrics:
- type: accuracy value: 93.7
- type: f1 value: 91.91666666666667
- type: precision value: 91.08333333333334
- type: recall value: 93.7
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (jav-eng)
config: jav-eng
split: test
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
metrics:
- type: accuracy value: 88.29268292682927
- type: f1 value: 85.27642276422765
- type: precision value: 84.01277584204414
- type: recall value: 88.29268292682927
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (isl-eng)
config: isl-eng
split: test
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
metrics:
- type: accuracy value: 96.1
- type: f1 value: 95.0
- type: precision value: 94.46666666666668
- type: recall value: 96.1
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (slv-eng)
config: slv-eng
split: test
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
metrics:
- type: accuracy value: 93.681652490887
- type: f1 value: 91.90765492102065
- type: precision value: 91.05913325232888
- type: recall value: 93.681652490887
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (cym-eng)
config: cym-eng
split: test
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
metrics:
- type: accuracy value: 92.17391304347827
- type: f1 value: 89.97101449275361
- type: precision value: 88.96811594202899
- type: recall value: 92.17391304347827
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (kaz-eng)
config: kaz-eng
split: test
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
metrics:
- type: accuracy value: 90.43478260869566
- type: f1 value: 87.72173913043478
- type: precision value: 86.42028985507245
- type: recall value: 90.43478260869566
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (est-eng)
config: est-eng
split: test
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
metrics:
- type: accuracy value: 90.4
- type: f1 value: 88.03
- type: precision value: 86.95
- type: recall value: 90.4
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (heb-eng)
config: heb-eng
split: test
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
metrics:
- type: accuracy value: 93.4
- type: f1 value: 91.45666666666666
- type: precision value: 90.525
- type: recall value: 93.4
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (gla-eng)
config: gla-eng
split: test
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
metrics:
- type: accuracy value: 81.9059107358263
- type: f1 value: 78.32557872364869
- type: precision value: 76.78260286824823
- type: recall value: 81.9059107358263
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (mar-eng)
config: mar-eng
split: test
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
metrics:
- type: accuracy value: 94.3
- type: f1 value: 92.58333333333333
- type: precision value: 91.73333333333332
- type: recall value: 94.3
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (lat-eng)
config: lat-eng
split: test
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
metrics:
- type: accuracy value: 79.10000000000001
- type: f1 value: 74.50500000000001
- type: precision value: 72.58928571428571
- type: recall value: 79.10000000000001
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (bel-eng)
config: bel-eng
split: test
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
metrics:
- type: accuracy value: 96.6
- type: f1 value: 95.55
- type: precision value: 95.05
- type: recall value: 96.6
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (pms-eng)
config: pms-eng
split: test
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
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type: BitextMining
dataset:
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revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
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config: pes-eng
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revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
metrics:
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- task:
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dataset:
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config: nob-eng
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revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
metrics:
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type: BitextMining
dataset:
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config: bul-eng
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revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
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revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
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config: hun-eng
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revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
metrics:
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revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
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revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
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config: spa-eng
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revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
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config: tel-eng
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revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
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config: afr-eng
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revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
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config: mon-eng
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revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
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dataset:
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config: arz-eng
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revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
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dataset:
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config: hrv-eng
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revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
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config: nov-eng
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revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
metrics:
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dataset:
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config: gsw-eng
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revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
metrics:
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dataset:
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config: nds-eng
split: test
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
metrics:
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dataset:
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config: ukr-eng
split: test
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
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config: uzb-eng
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config: lit-eng
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revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
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config: ina-eng
split: test
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
metrics:
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config: lfn-eng
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revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
metrics:
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- task:
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dataset:
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name: MTEB Tatoeba (zsm-eng)
config: zsm-eng
split: test
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
metrics:
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- task:
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dataset:
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name: MTEB Tatoeba (ita-eng)
config: ita-eng
split: test
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
metrics:
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- task:
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dataset:
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config: cmn-eng
split: test
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
metrics:
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- type: recall value: 97.2
- task:
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dataset:
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name: MTEB Tatoeba (lvs-eng)
config: lvs-eng
split: test
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
metrics:
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config: glg-eng
split: test
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
metrics:
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- task: type: BitextMining dataset: type: mteb/tatoeba-bitext-mining name: MTEB Tatoeba (ceb-eng)
- task:
type: Classification
dataset:
type: mteb/amazon_counterfactual
name: MTEB AmazonCounterfactualClassification (en)
config: en
split: test
revision: e8379541af4e31359cca9fbcf4b00f2671dba205
metrics:
[Content truncated...]
100,024 chars • Full Disclosure Protocol Active
ZEN MODE • README
tags:
- mteb
- sentence-transformers
- transformers model-index:
- name: multilingual-e5-large-instruct
results:
- task:
type: Classification
dataset:
type: mteb/amazon_counterfactual
name: MTEB AmazonCounterfactualClassification (en)
config: en
split: test
revision: e8379541af4e31359cca9fbcf4b00f2671dba205
metrics:
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- task:
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dataset:
type: mteb/amazon_counterfactual
name: MTEB AmazonCounterfactualClassification (de)
config: de
split: test
revision: e8379541af4e31359cca9fbcf4b00f2671dba205
metrics:
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- task:
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dataset:
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name: MTEB AmazonCounterfactualClassification (en-ext)
config: en-ext
split: test
revision: e8379541af4e31359cca9fbcf4b00f2671dba205
metrics:
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- task:
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dataset:
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name: MTEB AmazonCounterfactualClassification (ja)
config: ja
split: test
revision: e8379541af4e31359cca9fbcf4b00f2671dba205
metrics:
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dataset:
type: mteb/amazon_polarity
name: MTEB AmazonPolarityClassification
config: default
split: test
revision: e2d317d38cd51312af73b3d32a06d1a08b442046
metrics:
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- type: f1 value: 96.28680923610432
- task:
type: Classification
dataset:
type: mteb/amazon_reviews_multi
name: MTEB AmazonReviewsClassification (en)
config: en
split: test
revision: 1399c76144fd37290681b995c656ef9b2e06e26d
metrics:
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- task:
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dataset:
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name: MTEB AmazonReviewsClassification (de)
config: de
split: test
revision: 1399c76144fd37290681b995c656ef9b2e06e26d
metrics:
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dataset:
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name: MTEB AmazonReviewsClassification (es)
config: es
split: test
revision: 1399c76144fd37290681b995c656ef9b2e06e26d
metrics:
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- task:
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dataset:
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name: MTEB AmazonReviewsClassification (fr)
config: fr
split: test
revision: 1399c76144fd37290681b995c656ef9b2e06e26d
metrics:
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config: ja
split: test
revision: 1399c76144fd37290681b995c656ef9b2e06e26d
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dataset:
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config: zh
split: test
revision: 1399c76144fd37290681b995c656ef9b2e06e26d
metrics:
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dataset:
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name: MTEB ArguAna
config: default
split: test
revision: None
metrics:
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- type: map_at_10 value: 49.221
- type: map_at_100 value: 49.884
- type: map_at_1000 value: 49.888
- type: map_at_3 value: 44.31
- type: map_at_5 value: 47.276
- type: mrr_at_1 value: 32.432
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- type: mrr_at_1000 value: 50.166
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- type: ndcg_at_1 value: 31.721
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- type: recall_at_100 value: 99.075
- type: recall_at_1000 value: 99.644
- type: recall_at_3 value: 60.171
- type: recall_at_5 value: 73.044
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type: Clustering
dataset:
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name: MTEB ArxivClusteringP2P
config: default
split: test
revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
metrics:
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config: default
split: test
revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
metrics:
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name: MTEB AskUbuntuDupQuestions
config: default
split: test
revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
metrics:
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- type: mrr value: 77.61146286769556
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dataset:
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name: MTEB BIOSSES
config: default
split: test
revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
metrics:
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- type: euclidean_spearman value: 86.9622224570873
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config: de-en
split: test
revision: d51519689f32196a32af33b075a01d0e7c51e252
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- task:
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dataset:
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config: fr-en
split: test
revision: d51519689f32196a32af33b075a01d0e7c51e252
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- task:
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dataset:
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config: ru-en
split: test
revision: d51519689f32196a32af33b075a01d0e7c51e252
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dataset:
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config: zh-en
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- task:
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dataset:
type: mteb/banking77
name: MTEB Banking77Classification
config: default
split: test
revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
metrics:
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- task:
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name: MTEB BiorxivClusteringP2P
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split: test
revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
metrics:
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- task:
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dataset:
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name: MTEB BiorxivClusteringS2S
config: default
split: test
revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
metrics:
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- task:
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dataset:
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name: MTEB CQADupstackRetrieval
config: default
split: test
revision: None
metrics:
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- type: map_at_10 value: 37.298166666666674
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- type: mrr_at_3 value: 39.26825
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- type: ndcg_at_1 value: 32.93558333333333
- type: ndcg_at_10 value: 42.706583333333334
- type: ndcg_at_100 value: 47.82483333333333
- type: ndcg_at_1000 value: 49.95733333333334
- type: ndcg_at_3 value: 38.064750000000004
- type: ndcg_at_5 value: 40.18158333333333
- type: precision_at_1 value: 32.93558333333333
- type: precision_at_10 value: 7.459833333333334
- type: precision_at_100 value: 1.1830833333333335
- type: precision_at_1000 value: 0.15608333333333332
- type: precision_at_3 value: 17.5235
- type: precision_at_5 value: 12.349833333333333
- type: recall_at_1 value: 27.764166666666668
- type: recall_at_10 value: 54.31775
- type: recall_at_100 value: 76.74350000000001
- type: recall_at_1000 value: 91.45208333333332
- type: recall_at_3 value: 41.23425
- type: recall_at_5 value: 46.73983333333334
- task:
type: Retrieval
dataset:
type: climate-fever
name: MTEB ClimateFEVER
config: default
split: test
revision: None
metrics:
- type: map_at_1 value: 12.969
- type: map_at_10 value: 21.584999999999997
- type: map_at_100 value: 23.3
- type: map_at_1000 value: 23.5
- type: map_at_3 value: 18.218999999999998
- type: map_at_5 value: 19.983
- type: mrr_at_1 value: 29.316
- type: mrr_at_10 value: 40.033
- type: mrr_at_100 value: 40.96
- type: mrr_at_1000 value: 41.001
- type: mrr_at_3 value: 37.123
- type: mrr_at_5 value: 38.757999999999996
- type: ndcg_at_1 value: 29.316
- type: ndcg_at_10 value: 29.858
- type: ndcg_at_100 value: 36.756
- type: ndcg_at_1000 value: 40.245999999999995
- type: ndcg_at_3 value: 24.822
- type: ndcg_at_5 value: 26.565
- type: precision_at_1 value: 29.316
- type: precision_at_10 value: 9.186
- type: precision_at_100 value: 1.6549999999999998
- type: precision_at_1000 value: 0.22999999999999998
- type: precision_at_3 value: 18.436
- type: precision_at_5 value: 13.876
- type: recall_at_1 value: 12.969
- type: recall_at_10 value: 35.142
- type: recall_at_100 value: 59.143
- type: recall_at_1000 value: 78.594
- type: recall_at_3 value: 22.604
- type: recall_at_5 value: 27.883000000000003
- task:
type: Retrieval
dataset:
type: dbpedia-entity
name: MTEB DBPedia
config: default
split: test
revision: None
metrics:
- type: map_at_1 value: 8.527999999999999
- type: map_at_10 value: 17.974999999999998
- type: map_at_100 value: 25.665
- type: map_at_1000 value: 27.406000000000002
- type: map_at_3 value: 13.017999999999999
- type: map_at_5 value: 15.137
- type: mrr_at_1 value: 62.5
- type: mrr_at_10 value: 71.891
- type: mrr_at_100 value: 72.294
- type: mrr_at_1000 value: 72.296
- type: mrr_at_3 value: 69.958
- type: mrr_at_5 value: 71.121
- type: ndcg_at_1 value: 50.875
- type: ndcg_at_10 value: 38.36
- type: ndcg_at_100 value: 44.235
- type: ndcg_at_1000 value: 52.154
- type: ndcg_at_3 value: 43.008
- type: ndcg_at_5 value: 40.083999999999996
- type: precision_at_1 value: 62.5
- type: precision_at_10 value: 30.0
- type: precision_at_100 value: 10.038
- type: precision_at_1000 value: 2.0869999999999997
- type: precision_at_3 value: 46.833000000000006
- type: precision_at_5 value: 38.800000000000004
- type: recall_at_1 value: 8.527999999999999
- type: recall_at_10 value: 23.828
- type: recall_at_100 value: 52.322
- type: recall_at_1000 value: 77.143
- type: recall_at_3 value: 14.136000000000001
- type: recall_at_5 value: 17.761
- task:
type: Classification
dataset:
type: mteb/emotion
name: MTEB EmotionClassification
config: default
split: test
revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
metrics:
- type: accuracy value: 51.51
- type: f1 value: 47.632159862049896
- task:
type: Retrieval
dataset:
type: fever
name: MTEB FEVER
config: default
split: test
revision: None
metrics:
- type: map_at_1 value: 60.734
- type: map_at_10 value: 72.442
- type: map_at_100 value: 72.735
- type: map_at_1000 value: 72.75
- type: map_at_3 value: 70.41199999999999
- type: map_at_5 value: 71.80499999999999
- type: mrr_at_1 value: 65.212
- type: mrr_at_10 value: 76.613
- type: mrr_at_100 value: 76.79899999999999
- type: mrr_at_1000 value: 76.801
- type: mrr_at_3 value: 74.8
- type: mrr_at_5 value: 76.12400000000001
- type: ndcg_at_1 value: 65.212
- type: ndcg_at_10 value: 77.988
- type: ndcg_at_100 value: 79.167
- type: ndcg_at_1000 value: 79.452
- type: ndcg_at_3 value: 74.362
- type: ndcg_at_5 value: 76.666
- type: precision_at_1 value: 65.212
- type: precision_at_10 value: 10.003
- type: precision_at_100 value: 1.077
- type: precision_at_1000 value: 0.11199999999999999
- type: precision_at_3 value: 29.518
- type: precision_at_5 value: 19.016
- type: recall_at_1 value: 60.734
- type: recall_at_10 value: 90.824
- type: recall_at_100 value: 95.71600000000001
- type: recall_at_1000 value: 97.577
- type: recall_at_3 value: 81.243
- type: recall_at_5 value: 86.90299999999999
- task:
type: Retrieval
dataset:
type: fiqa
name: MTEB FiQA2018
config: default
split: test
revision: None
metrics:
- type: map_at_1 value: 23.845
- type: map_at_10 value: 39.281
- type: map_at_100 value: 41.422
- type: map_at_1000 value: 41.593
- type: map_at_3 value: 34.467
- type: map_at_5 value: 37.017
- type: mrr_at_1 value: 47.531
- type: mrr_at_10 value: 56.204
- type: mrr_at_100 value: 56.928999999999995
- type: mrr_at_1000 value: 56.962999999999994
- type: mrr_at_3 value: 54.115
- type: mrr_at_5 value: 55.373000000000005
- type: ndcg_at_1 value: 47.531
- type: ndcg_at_10 value: 47.711999999999996
- type: ndcg_at_100 value: 54.510999999999996
- type: ndcg_at_1000 value: 57.103
- type: ndcg_at_3 value: 44.145
- type: ndcg_at_5 value: 45.032
- type: precision_at_1 value: 47.531
- type: precision_at_10 value: 13.194
- type: precision_at_100 value: 2.045
- type: precision_at_1000 value: 0.249
- type: precision_at_3 value: 29.424
- type: precision_at_5 value: 21.451
- type: recall_at_1 value: 23.845
- type: recall_at_10 value: 54.967
- type: recall_at_100 value: 79.11399999999999
- type: recall_at_1000 value: 94.56700000000001
- type: recall_at_3 value: 40.256
- type: recall_at_5 value: 46.215
- task:
type: Retrieval
dataset:
type: hotpotqa
name: MTEB HotpotQA
config: default
split: test
revision: None
metrics:
- type: map_at_1 value: 37.819
- type: map_at_10 value: 60.889
- type: map_at_100 value: 61.717999999999996
- type: map_at_1000 value: 61.778
- type: map_at_3 value: 57.254000000000005
- type: map_at_5 value: 59.541
- type: mrr_at_1 value: 75.638
- type: mrr_at_10 value: 82.173
- type: mrr_at_100 value: 82.362
- type: mrr_at_1000 value: 82.37
- type: mrr_at_3 value: 81.089
- type: mrr_at_5 value: 81.827
- type: ndcg_at_1 value: 75.638
- type: ndcg_at_10 value: 69.317
- type: ndcg_at_100 value: 72.221
- type: ndcg_at_1000 value: 73.382
- type: ndcg_at_3 value: 64.14
- type: ndcg_at_5 value: 67.07600000000001
- type: precision_at_1 value: 75.638
- type: precision_at_10 value: 14.704999999999998
- type: precision_at_100 value: 1.698
- type: precision_at_1000 value: 0.185
- type: precision_at_3 value: 41.394999999999996
- type: precision_at_5 value: 27.162999999999997
- type: recall_at_1 value: 37.819
- type: recall_at_10 value: 73.52499999999999
- type: recall_at_100 value: 84.875
- type: recall_at_1000 value: 92.559
- type: recall_at_3 value: 62.092999999999996
- type: recall_at_5 value: 67.907
- task:
type: Classification
dataset:
type: mteb/imdb
name: MTEB ImdbClassification
config: default
split: test
revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
metrics:
- type: accuracy value: 94.60079999999999
- type: ap value: 92.67396345347356
- type: f1 value: 94.5988098167121
- task:
type: Retrieval
dataset:
type: msmarco
name: MTEB MSMARCO
config: default
split: dev
revision: None
metrics:
- type: map_at_1 value: 21.285
- type: map_at_10 value: 33.436
- type: map_at_100 value: 34.63
- type: map_at_1000 value: 34.681
- type: map_at_3 value: 29.412
- type: map_at_5 value: 31.715
- type: mrr_at_1 value: 21.848
- type: mrr_at_10 value: 33.979
- type: mrr_at_100 value: 35.118
- type: mrr_at_1000 value: 35.162
- type: mrr_at_3 value: 30.036
- type: mrr_at_5 value: 32.298
- type: ndcg_at_1 value: 21.862000000000002
- type: ndcg_at_10 value: 40.43
- type: ndcg_at_100 value: 46.17
- type: ndcg_at_1000 value: 47.412
- type: ndcg_at_3 value: 32.221
- type: ndcg_at_5 value: 36.332
- type: precision_at_1 value: 21.862000000000002
- type: precision_at_10 value: 6.491
- type: precision_at_100 value: 0.935
- type: precision_at_1000 value: 0.104
- type: precision_at_3 value: 13.744
- type: precision_at_5 value: 10.331999999999999
- type: recall_at_1 value: 21.285
- type: recall_at_10 value: 62.083
- type: recall_at_100 value: 88.576
- type: recall_at_1000 value: 98.006
- type: recall_at_3 value: 39.729
- type: recall_at_5 value: 49.608000000000004
- task:
type: Classification
dataset:
type: mteb/mtop_domain
name: MTEB MTOPDomainClassification (en)
config: en
split: test
revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
metrics:
- type: accuracy value: 93.92612859097127
- type: f1 value: 93.82370333372853
- task:
type: Classification
dataset:
type: mteb/mtop_domain
name: MTEB MTOPDomainClassification (de)
config: de
split: test
revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
metrics:
- type: accuracy value: 92.67681036911807
- type: f1 value: 92.14191382411472
- task:
type: Classification
dataset:
type: mteb/mtop_domain
name: MTEB MTOPDomainClassification (es)
config: es
split: test
revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
metrics:
- type: accuracy value: 92.26817878585723
- type: f1 value: 91.92824250337878
- task:
type: Classification
dataset:
type: mteb/mtop_domain
name: MTEB MTOPDomainClassification (fr)
config: fr
split: test
revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
metrics:
- type: accuracy value: 89.96554963983714
- type: f1 value: 90.02859329630792
- task:
type: Classification
dataset:
type: mteb/mtop_domain
name: MTEB MTOPDomainClassification (hi)
config: hi
split: test
revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
metrics:
- type: accuracy value: 90.02509860164935
- type: f1 value: 89.30665159182062
- task:
type: Classification
dataset:
type: mteb/mtop_domain
name: MTEB MTOPDomainClassification (th)
config: th
split: test
revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
metrics:
- type: accuracy value: 87.55515370705244
- type: f1 value: 87.94449232331907
- task:
type: Classification
dataset:
type: mteb/mtop_intent
name: MTEB MTOPIntentClassification (en)
config: en
split: test
revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
metrics:
- type: accuracy value: 82.4623803009576
- type: f1 value: 66.06738378772725
- task:
type: Classification
dataset:
type: mteb/mtop_intent
name: MTEB MTOPIntentClassification (de)
config: de
split: test
revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
metrics:
- type: accuracy value: 79.3716539870386
- type: f1 value: 60.37614033396853
- task:
type: Classification
dataset:
type: mteb/mtop_intent
name: MTEB MTOPIntentClassification (es)
config: es
split: test
revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
metrics:
- type: accuracy value: 80.34022681787857
- type: f1 value: 58.302008026952
- task:
type: Classification
dataset:
type: mteb/mtop_intent
name: MTEB MTOPIntentClassification (fr)
config: fr
split: test
revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
metrics:
- type: accuracy value: 76.72095208268087
- type: f1 value: 59.64524724009049
- task:
type: Classification
dataset:
type: mteb/mtop_intent
name: MTEB MTOPIntentClassification (hi)
config: hi
split: test
revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
metrics:
- type: accuracy value: 77.87020437432773
- type: f1 value: 57.80202694670567
- task:
type: Classification
dataset:
type: mteb/mtop_intent
name: MTEB MTOPIntentClassification (th)
config: th
split: test
revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
metrics:
- type: accuracy value: 77.73598553345387
- type: f1 value: 58.19628250675031
- task:
type: Classification
dataset:
type: mteb/amazon_massive_intent
name: MTEB MassiveIntentClassification (af)
config: af
split: test
revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
metrics:
- type: accuracy value: 67.6630800268998
- type: f1 value: 65.00996668051691
- task:
type: Classification
dataset:
type: mteb/amazon_massive_intent
name: MTEB MassiveIntentClassification (am)
config: am
split: test
revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
metrics:
- type: accuracy value: 60.7128446536651
- type: f1 value: 57.95860594874963
- task:
type: Classification
dataset:
type: mteb/amazon_massive_intent
name: MTEB MassiveIntentClassification (ar)
config: ar
split: test
revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
metrics:
- type: accuracy value: 63.61129791526563
- type: f1 value: 59.75328290206483
- task:
type: Classification
dataset:
type: mteb/amazon_massive_intent
name: MTEB MassiveIntentClassification (az)
config: az
split: test
revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
metrics:
- type: accuracy value: 69.00134498991257
- type: f1 value: 67.0230483991802
- task:
type: Classification
dataset:
type: mteb/amazon_massive_intent
name: MTEB MassiveIntentClassification (bn)
config: bn
split: test
revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
metrics:
- type: accuracy value: 68.54068594485541
- type: f1 value: 65.54604628946976
- task:
type: Classification
dataset:
type: mteb/amazon_massive_intent
name: MTEB MassiveIntentClassification (cy)
config: cy
split: test
revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
metrics:
- type: accuracy value: 63.032952252858095
- type: f1 value: 58.715741857057104
- task:
type: Classification
dataset:
type: mteb/amazon_massive_intent
name: MTEB MassiveIntentClassification (da)
config: da
split: test
revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
metrics:
- type: accuracy value: 71.80901143241427
- type: f1 value: 68.33963989243877
- task:
type: Classification
dataset:
type: mteb/amazon_massive_intent
name: MTEB MassiveIntentClassification (de)
config: de
split: test
revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
metrics:
- type: accuracy value: 72.47141896435777
- type: f1 value: 69.56765020308262
- task:
type: Classification
dataset:
type: mteb/amazon_massive_intent
name: MTEB MassiveIntentClassification (el)
config: el
split: test
revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
metrics:
- type: accuracy value: 71.2373907195696
- type: f1 value: 69.04529836036467
- task:
type: Classification
dataset:
type: mteb/amazon_massive_intent
name: MTEB MassiveIntentClassification (en)
config: en
split: test
revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
metrics:
- type: accuracy value: 77.05783456624076
- type: f1 value: 74.69430584708174
- task:
type: Classification
dataset:
type: mteb/amazon_massive_intent
name: MTEB MassiveIntentClassification (es)
config: es
split: test
revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
metrics:
- type: accuracy value: 72.82111634162744
- type: f1 value: 70.77228952803762
- task:
type: Classification
dataset:
type: mteb/amazon_massive_intent
name: MTEB MassiveIntentClassification (fa)
config: fa
split: test
revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
metrics:
- type: accuracy value: 74.25353059852051
- type: f1 value: 71.05310103416411
- task:
type: Classification
dataset:
type: mteb/amazon_massive_intent
name: MTEB MassiveIntentClassification (fi)
config: fi
split: test
revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
metrics:
- type: accuracy value: 72.28648285137861
- type: f1 value: 69.08020473732226
- task:
type: Classification
dataset:
type: mteb/amazon_massive_intent
name: MTEB MassiveIntentClassification (fr)
config: fr
split: test
revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
metrics:
- type: accuracy value: 73.31540013449899
- type: f1 value: 70.9426355465791
- task:
type: Classification
dataset:
type: mteb/amazon_massive_intent
name: MTEB MassiveIntentClassification (he)
config: he
split: test
revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
metrics:
- type: accuracy value: 70.2151983860121
- type: f1 value: 67.52541755908858
- task:
type: Classification
dataset:
type: mteb/amazon_massive_intent
name: MTEB MassiveIntentClassification (hi)
config: hi
split: test
revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
metrics:
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- type: f1 value: 69.49769064229827
- task:
type: Classification
dataset:
type: mteb/amazon_massive_intent
name: MTEB MassiveIntentClassification (hu)
config: hu
split: test
revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
metrics:
- type: accuracy value: 71.9233355749832
- type: f1 value: 69.36311548259593
- task:
type: Classification
dataset:
type: mteb/amazon_massive_intent
name: MTEB MassiveIntentClassification (hy)
config: hy
split: test
revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
metrics:
- type: accuracy value: 68.07330195023538
- type: f1 value: 64.99882022345572
- task:
type: Classification
dataset:
type: mteb/amazon_massive_intent
name: MTEB MassiveIntentClassification (id)
config: id
split: test
revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
metrics:
- type: accuracy value: 72.62273032952253
- type: f1 value: 70.6394885471001
- task:
type: Classification
dataset:
type: mteb/amazon_massive_intent
name: MTEB MassiveIntentClassification (is)
config: is
split: test
revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
metrics:
- type: accuracy value: 65.77000672494957
- type: f1 value: 62.9368944815065
- task:
type: Classification
dataset:
type: mteb/amazon_massive_intent
name: MTEB MassiveIntentClassification (it)
config: it
split: test
revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
metrics:
- type: accuracy value: 73.453261600538
- type: f1 value: 70.85069934666681
- task:
type: Classification
dataset:
type: mteb/amazon_massive_intent
name: MTEB MassiveIntentClassification (ja)
config: ja
split: test
revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
metrics:
- type: accuracy value: 74.6906523201076
- type: f1 value: 72.03249740074217
- task:
type: Classification
dataset:
type: mteb/amazon_massive_intent
name: MTEB MassiveIntentClassification (jv)
config: jv
split: test
revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
metrics:
- type: accuracy value: 63.03631472763953
- type: f1 value: 59.3165215571852
- task:
type: Classification
dataset:
type: mteb/amazon_massive_intent
name: MTEB MassiveIntentClassification (ka)
config: ka
split: test
revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
metrics:
- type: accuracy value: 58.913920645595155
- type: f1 value: 57.367337711611285
- task:
type: Classification
dataset:
type: mteb/amazon_massive_intent
name: MTEB MassiveIntentClassification (km)
config: km
split: test
revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
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- type: accuracy value: 67.91862811028918
- type: f1 value: 66.50386121217983
- task:
type: Classification
dataset:
type: mteb/amazon_massive_scenario
name: MTEB MassiveScenarioClassification (ta)
config: ta
split: test
revision: 7d571f92784cd94a019292a1f45445077d0ef634
metrics:
- type: accuracy value: 70.93140551445865
- type: f1 value: 70.755435928495
- task:
type: Classification
dataset:
type: mteb/amazon_massive_scenario
name: MTEB MassiveScenarioClassification (te)
config: te
split: test
revision: 7d571f92784cd94a019292a1f45445077d0ef634
metrics:
- type: accuracy value: 72.40753194351042
- type: f1 value: 71.61816115782923
- task:
type: Classification
dataset:
type: mteb/amazon_massive_scenario
name: MTEB MassiveScenarioClassification (th)
config: th
split: test
revision: 7d571f92784cd94a019292a1f45445077d0ef634
metrics:
- type: accuracy value: 75.1815736381977
- type: f1 value: 75.08016717887205
- task:
type: Classification
dataset:
type: mteb/amazon_massive_scenario
name: MTEB MassiveScenarioClassification (tl)
config: tl
split: test
revision: 7d571f92784cd94a019292a1f45445077d0ef634
metrics:
- type: accuracy value: 72.86482851378614
- type: f1 value: 72.39521180006291
- task:
type: Classification
dataset:
type: mteb/amazon_massive_scenario
name: MTEB MassiveScenarioClassification (tr)
config: tr
split: test
revision: 7d571f92784cd94a019292a1f45445077d0ef634
metrics:
- type: accuracy value: 76.46940147948891
- type: f1 value: 76.70044085362349
- task:
type: Classification
dataset:
type: mteb/amazon_massive_scenario
name: MTEB MassiveScenarioClassification (ur)
config: ur
split: test
revision: 7d571f92784cd94a019292a1f45445077d0ef634
metrics:
- type: accuracy value: 71.89307330195024
- type: f1 value: 71.5721825332298
- task:
type: Classification
dataset:
type: mteb/amazon_massive_scenario
name: MTEB MassiveScenarioClassification (vi)
config: vi
split: test
revision: 7d571f92784cd94a019292a1f45445077d0ef634
metrics:
- type: accuracy value: 74.7511768661735
- type: f1 value: 75.17918654541515
- task:
type: Classification
dataset:
type: mteb/amazon_massive_scenario
name: MTEB MassiveScenarioClassification (zh-CN)
config: zh-CN
split: test
revision: 7d571f92784cd94a019292a1f45445077d0ef634
metrics:
- type: accuracy value: 78.69535978480162
- type: f1 value: 78.90019070153316
- task:
type: Classification
dataset:
type: mteb/amazon_massive_scenario
name: MTEB MassiveScenarioClassification (zh-TW)
config: zh-TW
split: test
revision: 7d571f92784cd94a019292a1f45445077d0ef634
metrics:
- type: accuracy value: 75.45729657027572
- type: f1 value: 76.19578371794672
- task:
type: Clustering
dataset:
type: mteb/medrxiv-clustering-p2p
name: MTEB MedrxivClusteringP2P
config: default
split: test
revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
metrics:
- type: v_measure value: 36.92715354123554
- task:
type: Clustering
dataset:
type: mteb/medrxiv-clustering-s2s
name: MTEB MedrxivClusteringS2S
config: default
split: test
revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
metrics:
- type: v_measure value: 35.53536244162518
- task:
type: Reranking
dataset:
type: mteb/mind_small
name: MTEB MindSmallReranking
config: default
split: test
revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
metrics:
- type: map value: 33.08507884504006
- type: mrr value: 34.32436977159129
- task:
type: Retrieval
dataset:
type: nfcorpus
name: MTEB NFCorpus
config: default
split: test
revision: None
metrics:
- type: map_at_1 value: 5.935
- type: map_at_10 value: 13.297
- type: map_at_100 value: 16.907
- type: map_at_1000 value: 18.391
- type: map_at_3 value: 9.626999999999999
- type: map_at_5 value: 11.190999999999999
- type: mrr_at_1 value: 46.129999999999995
- type: mrr_at_10 value: 54.346000000000004
- type: mrr_at_100 value: 55.067
- type: mrr_at_1000 value: 55.1
- type: mrr_at_3 value: 51.961
- type: mrr_at_5 value: 53.246
- type: ndcg_at_1 value: 44.118
- type: ndcg_at_10 value: 35.534
- type: ndcg_at_100 value: 32.946999999999996
- type: ndcg_at_1000 value: 41.599000000000004
- type: ndcg_at_3 value: 40.25
- type: ndcg_at_5 value: 37.978
- type: precision_at_1 value: 46.129999999999995
- type: precision_at_10 value: 26.842
- type: precision_at_100 value: 8.427
- type: precision_at_1000 value: 2.128
- type: precision_at_3 value: 37.977
- type: precision_at_5 value: 32.879000000000005
- type: recall_at_1 value: 5.935
- type: recall_at_10 value: 17.211000000000002
- type: recall_at_100 value: 34.33
- type: recall_at_1000 value: 65.551
- type: recall_at_3 value: 10.483
- type: recall_at_5 value: 13.078999999999999
- task:
type: Retrieval
dataset:
type: nq
name: MTEB NQ
config: default
split: test
revision: None
metrics:
- type: map_at_1 value: 35.231
- type: map_at_10 value: 50.202000000000005
- type: map_at_100 value: 51.154999999999994
- type: map_at_1000 value: 51.181
- type: map_at_3 value: 45.774
- type: map_at_5 value: 48.522
- type: mrr_at_1 value: 39.687
- type: mrr_at_10 value: 52.88
- type: mrr_at_100 value: 53.569
- type: mrr_at_1000 value: 53.58500000000001
- type: mrr_at_3 value: 49.228
- type: mrr_at_5 value: 51.525
- type: ndcg_at_1 value: 39.687
- type: ndcg_at_10 value: 57.754000000000005
- type: ndcg_at_100 value: 61.597
- type: ndcg_at_1000 value: 62.18900000000001
- type: ndcg_at_3 value: 49.55
- type: ndcg_at_5 value: 54.11899999999999
- type: precision_at_1 value: 39.687
- type: precision_at_10 value: 9.313
- type: precision_at_100 value: 1.146
- type: precision_at_1000 value: 0.12
- type: precision_at_3 value: 22.229
- type: precision_at_5 value: 15.939
- type: recall_at_1 value: 35.231
- type: recall_at_10 value: 78.083
- type: recall_at_100 value: 94.42099999999999
- type: recall_at_1000 value: 98.81
- type: recall_at_3 value: 57.047000000000004
- type: recall_at_5 value: 67.637
- task:
type: Retrieval
dataset:
type: quora
name: MTEB QuoraRetrieval
config: default
split: test
revision: None
metrics:
- type: map_at_1 value: 71.241
- type: map_at_10 value: 85.462
- type: map_at_100 value: 86.083
- type: map_at_1000 value: 86.09700000000001
- type: map_at_3 value: 82.49499999999999
- type: map_at_5 value: 84.392
- type: mrr_at_1 value: 82.09
- type: mrr_at_10 value: 88.301
- type: mrr_at_100 value: 88.383
- type: mrr_at_1000 value: 88.384
- type: mrr_at_3 value: 87.37
- type: mrr_at_5 value: 88.035
- type: ndcg_at_1 value: 82.12
- type: ndcg_at_10 value: 89.149
- type: ndcg_at_100 value: 90.235
- type: ndcg_at_1000 value: 90.307
- type: ndcg_at_3 value: 86.37599999999999
- type: ndcg_at_5 value: 87.964
- type: precision_at_1 value: 82.12
- type: precision_at_10 value: 13.56
- type: precision_at_100 value: 1.539
- type: precision_at_1000 value: 0.157
- type: precision_at_3 value: 37.88
- type: precision_at_5 value: 24.92
- type: recall_at_1 value: 71.241
- type: recall_at_10 value: 96.128
- type: recall_at_100 value: 99.696
- type: recall_at_1000 value: 99.994
- type: recall_at_3 value: 88.181
- type: recall_at_5 value: 92.694
- task:
type: Clustering
dataset:
type: mteb/reddit-clustering
name: MTEB RedditClustering
config: default
split: test
revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
metrics:
- type: v_measure value: 56.59757799655151
- task:
type: Clustering
dataset:
type: mteb/reddit-clustering-p2p
name: MTEB RedditClusteringP2P
config: default
split: test
revision: 282350215ef01743dc01b456c7f5241fa8937f16
metrics:
- type: v_measure value: 64.27391998854624
- task:
type: Retrieval
dataset:
type: scidocs
name: MTEB SCIDOCS
config: default
split: test
revision: None
metrics:
- type: map_at_1 value: 4.243
- type: map_at_10 value: 10.965
- type: map_at_100 value: 12.934999999999999
- type: map_at_1000 value: 13.256
- type: map_at_3 value: 7.907
- type: map_at_5 value: 9.435
- type: mrr_at_1 value: 20.9
- type: mrr_at_10 value: 31.849
- type: mrr_at_100 value: 32.964
- type: mrr_at_1000 value: 33.024
- type: mrr_at_3 value: 28.517
- type: mrr_at_5 value: 30.381999999999998
- type: ndcg_at_1 value: 20.9
- type: ndcg_at_10 value: 18.723
- type: ndcg_at_100 value: 26.384999999999998
- type: ndcg_at_1000 value: 32.114
- type: ndcg_at_3 value: 17.753
- type: ndcg_at_5 value: 15.558
- type: precision_at_1 value: 20.9
- type: precision_at_10 value: 9.8
- type: precision_at_100 value: 2.078
- type: precision_at_1000 value: 0.345
- type: precision_at_3 value: 16.900000000000002
- type: precision_at_5 value: 13.88
- type: recall_at_1 value: 4.243
- type: recall_at_10 value: 19.885
- type: recall_at_100 value: 42.17
- type: recall_at_1000 value: 70.12
- type: recall_at_3 value: 10.288
- type: recall_at_5 value: 14.072000000000001
- task:
type: STS
dataset:
type: mteb/sickr-sts
name: MTEB SICK-R
config: default
split: test
revision: a6ea5a8cab320b040a23452cc28066d9beae2cee
metrics:
- type: cos_sim_pearson value: 85.84209174935282
- type: cos_sim_spearman value: 81.73248048438833
- type: euclidean_pearson value: 83.02810070308149
- type: euclidean_spearman value: 81.73248295679514
- type: manhattan_pearson value: 82.95368060376002
- type: manhattan_spearman value: 81.60277910998718
- task:
type: STS
dataset:
type: mteb/sts12-sts
name: MTEB STS12
config: default
split: test
revision: a0d554a64d88156834ff5ae9920b964011b16384
metrics:
- type: cos_sim_pearson value: 88.52628804556943
- type: cos_sim_spearman value: 82.5713913555672
- type: euclidean_pearson value: 85.8796774746988
- type: euclidean_spearman value: 82.57137506803424
- type: manhattan_pearson value: 85.79671002960058
- type: manhattan_spearman value: 82.49445981618027
- task:
type: STS
dataset:
type: mteb/sts13-sts
name: MTEB STS13
config: default
split: test
revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
metrics:
- type: cos_sim_pearson value: 86.23682503505542
- type: cos_sim_spearman value: 87.15008956711806
- type: euclidean_pearson value: 86.79805401524959
- type: euclidean_spearman value: 87.15008956711806
- type: manhattan_pearson value: 86.65298502699244
- type: manhattan_spearman value: 86.97677821948562
- task:
type: STS
dataset:
type: mteb/sts14-sts
name: MTEB STS14
config: default
split: test
revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
metrics:
- type: cos_sim_pearson value: 85.63370304677802
- type: cos_sim_spearman value: 84.97105553540318
- type: euclidean_pearson value: 85.28896108687721
- type: euclidean_spearman value: 84.97105553540318
- type: manhattan_pearson value: 85.09663190337331
- type: manhattan_spearman value: 84.79126831644619
- task:
type: STS
dataset:
type: mteb/sts15-sts
name: MTEB STS15
config: default
split: test
revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
metrics:
- type: cos_sim_pearson value: 90.2614838800733
- type: cos_sim_spearman value: 91.0509162991835
- type: euclidean_pearson value: 90.33098317533373
- type: euclidean_spearman value: 91.05091625871644
- type: manhattan_pearson value: 90.26250435151107
- type: manhattan_spearman value: 90.97999594417519
- task:
type: STS
dataset:
type: mteb/sts16-sts
name: MTEB STS16
config: default
split: test
revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
metrics:
- type: cos_sim_pearson value: 85.80480973335091
- type: cos_sim_spearman value: 87.313695492969
- type: euclidean_pearson value: 86.49267251576939
- type: euclidean_spearman value: 87.313695492969
- type: manhattan_pearson value: 86.44019901831935
- type: manhattan_spearman value: 87.24205395460392
- task:
type: STS
dataset:
type: mteb/sts17-crosslingual-sts
name: MTEB STS17 (en-en)
config: en-en
split: test
revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
metrics:
- type: cos_sim_pearson value: 90.05662789380672
- type: cos_sim_spearman value: 90.02759424426651
- type: euclidean_pearson value: 90.4042483422981
- type: euclidean_spearman value: 90.02759424426651
- type: manhattan_pearson value: 90.51446975000226
- type: manhattan_spearman value: 90.08832889933616
- task:
type: STS
dataset:
type: mteb/sts22-crosslingual-sts
name: MTEB STS22 (en)
config: en
split: test
revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80
metrics:
- type: cos_sim_pearson value: 67.5975528273532
- type: cos_sim_spearman value: 67.62969861411354
- type: euclidean_pearson value: 69.224275734323
- type: euclidean_spearman value: 67.62969861411354
- type: manhattan_pearson value: 69.3761447059927
- type: manhattan_spearman value: 67.90921005611467
- task:
type: STS
dataset:
type: mteb/stsbenchmark-sts
name: MTEB STSBenchmark
config: default
split: test
revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
metrics:
- type: cos_sim_pearson value: 87.11244327231684
- type: cos_sim_spearman value: 88.37902438979035
- type: euclidean_pearson value: 87.86054279847336
- type: euclidean_spearman value: 88.37902438979035
- type: manhattan_pearson value: 87.77257757320378
- type: manhattan_spearman value: 88.25208966098123
- task:
type: Reranking
dataset:
type: mteb/scidocs-reranking
name: MTEB SciDocsRR
config: default
split: test
revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
metrics:
- type: map value: 85.87174608143563
- type: mrr value: 96.12836872640794
- task:
type: Retrieval
dataset:
type: scifact
name: MTEB SciFact
config: default
split: test
revision: None
metrics:
- type: map_at_1 value: 57.760999999999996
- type: map_at_10 value: 67.258
- type: map_at_100 value: 67.757
- type: map_at_1000 value: 67.78800000000001
- type: map_at_3 value: 64.602
- type: map_at_5 value: 65.64
- type: mrr_at_1 value: 60.667
- type: mrr_at_10 value: 68.441
- type: mrr_at_100 value: 68.825
- type: mrr_at_1000 value: 68.853
- type: mrr_at_3 value: 66.444
- type: mrr_at_5 value: 67.26100000000001
- type: ndcg_at_1 value: 60.667
- type: ndcg_at_10 value: 71.852
- type: ndcg_at_100 value: 73.9
- type: ndcg_at_1000 value: 74.628
- type: ndcg_at_3 value: 67.093
- type: ndcg_at_5 value: 68.58
- type: precision_at_1 value: 60.667
- type: precision_at_10 value: 9.6
- type: precision_at_100 value: 1.0670000000000002
- type: precision_at_1000 value: 0.11199999999999999
- type: precision_at_3 value: 26.111
- type: precision_at_5 value: 16.733
- type: recall_at_1 value: 57.760999999999996
- type: recall_at_10 value: 84.967
- type: recall_at_100 value: 93.833
- type: recall_at_1000 value: 99.333
- type: recall_at_3 value: 71.589
- type: recall_at_5 value: 75.483
- task:
type: PairClassification
dataset:
type: mteb/sprintduplicatequestions-pairclassification
name: MTEB SprintDuplicateQuestions
config: default
split: test
revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
metrics:
- type: cos_sim_accuracy value: 99.66633663366336
- type: cos_sim_ap value: 91.17685358899108
- type: cos_sim_f1 value: 82.16818642350559
- type: cos_sim_precision value: 83.26488706365504
- type: cos_sim_recall value: 81.10000000000001
- type: dot_accuracy value: 99.66633663366336
- type: dot_ap value: 91.17663411119032
- type: dot_f1 value: 82.16818642350559
- type: dot_precision value: 83.26488706365504
- type: dot_recall value: 81.10000000000001
- type: euclidean_accuracy value: 99.66633663366336
- type: euclidean_ap value: 91.17685189882275
- type: euclidean_f1 value: 82.16818642350559
- type: euclidean_precision value: 83.26488706365504
- type: euclidean_recall value: 81.10000000000001
- type: manhattan_accuracy value: 99.66633663366336
- type: manhattan_ap value: 91.2241619496737
- type: manhattan_f1 value: 82.20472440944883
- type: manhattan_precision value: 86.51933701657458
- type: manhattan_recall value: 78.3
- type: max_accuracy value: 99.66633663366336
- type: max_ap value: 91.2241619496737
- type: max_f1 value: 82.20472440944883
- task:
type: Clustering
dataset:
type: mteb/stackexchange-clustering
name: MTEB StackExchangeClustering
config: default
split: test
revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
metrics:
- type: v_measure value: 66.85101268897951
- task:
type: Clustering
dataset:
type: mteb/stackexchange-clustering-p2p
name: MTEB StackExchangeClusteringP2P
config: default
split: test
revision: 815ca46b2622cec33ccafc3735d572c266efdb44
metrics:
- type: v_measure value: 42.461184054706905
- task:
type: Reranking
dataset:
type: mteb/stackoverflowdupquestions-reranking
name: MTEB StackOverflowDupQuestions
config: default
split: test
revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
metrics:
- type: map value: 51.44542568873886
- type: mrr value: 52.33656151854681
- task:
type: Summarization
dataset:
type: mteb/summeval
name: MTEB SummEval
config: default
split: test
revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
metrics:
- type: cos_sim_pearson value: 30.75982974997539
- type: cos_sim_spearman value: 30.385405026539914
- type: dot_pearson value: 30.75982433546523
- type: dot_spearman value: 30.385405026539914
- task:
type: Retrieval
dataset:
type: trec-covid
name: MTEB TRECCOVID
config: default
split: test
revision: None
metrics:
- type: map_at_1 value: 0.22799999999999998
- type: map_at_10 value: 2.064
- type: map_at_100 value: 13.056000000000001
- type: map_at_1000 value: 31.747999999999998
- type: map_at_3 value: 0.67
- type: map_at_5 value: 1.097
- type: mrr_at_1 value: 90.0
- type: mrr_at_10 value: 94.667
- type: mrr_at_100 value: 94.667
- type: mrr_at_1000 value: 94.667
- type: mrr_at_3 value: 94.667
- type: mrr_at_5 value: 94.667
- type: ndcg_at_1 value: 86.0
- type: ndcg_at_10 value: 82.0
- type: ndcg_at_100 value: 64.307
- type: ndcg_at_1000 value: 57.023999999999994
- type: ndcg_at_3 value: 85.816
- type: ndcg_at_5 value: 84.904
- type: precision_at_1 value: 90.0
- type: precision_at_10 value: 85.8
- type: precision_at_100 value: 66.46
- type: precision_at_1000 value: 25.202
- type: precision_at_3 value: 90.0
- type: precision_at_5 value: 89.2
- type: recall_at_1 value: 0.22799999999999998
- type: recall_at_10 value: 2.235
- type: recall_at_100 value: 16.185
- type: recall_at_1000 value: 53.620999999999995
- type: recall_at_3 value: 0.7040000000000001
- type: recall_at_5 value: 1.172
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (sqi-eng)
config: sqi-eng
split: test
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
metrics:
- type: accuracy value: 97.39999999999999
- type: f1 value: 96.75
- type: precision value: 96.45
- type: recall value: 97.39999999999999
- task:
type: BitextMining
dataset:
type: mteb/tatoeba-bitext-mining
name: MTEB Tatoeba (fry-eng)
config: fry-eng
split: test
revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553
metrics:
- type: accuracy value: 85.54913294797689
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[Content truncated...]
📝 Limitations & Considerations
- • Benchmark scores may vary based on evaluation methodology and hardware configuration.
- • VRAM requirements are estimates; actual usage depends on quantization and batch size.
- • FNI scores are relative rankings and may change as new models are added.
- ⚠ License Unknown: Verify licensing terms before commercial use.
- • Source: Unknown
📜
Cite this model
Academic & Research Attribution
BibTeX
@misc{hf_model__intfloat__multilingual_e5_large_instruct,
author = {intfloat},
title = {undefined Model},
year = {2026},
howpublished = {\url{https://huggingface.co/intfloat/multilingual-e5-large-instruct}},
note = {Accessed via Free2AITools Knowledge Fortress}
} APA Style
intfloat. (2026). undefined [Model]. Free2AITools. https://huggingface.co/intfloat/multilingual-e5-large-instruct
🔄 Daily sync (03:00 UTC)
AI Summary: Based on Hugging Face metadata. Not a recommendation.
🛡️ Model Transparency Report
Verified data manifest for traceability and transparency.
100% Data Disclosure Active
🆔 Identity & Source
- id
- hf-model--intfloat--multilingual-e5-large-instruct
- author
- intfloat
- tags
- sentence-transformersonnxsafetensorsxlm-robertafeature-extractionmtebtransformersmultilingualafamarasazbebgbnbrbscacscydadeeleneoeseteufafifrfygagdglguhahehihrhuhyidisitjajvkakkkmknkokukylaloltlvmgmkmlmnmrmsmynenlnoomorpaplpsptrorusasdsiskslsosqsrsusvswtatethtltrugukuruzvixhyizharxiv:2402.05672arxiv:2401.00368arxiv:2104.08663arxiv:2210.07316license:mitmodel-indextext-embeddings-inferenceendpoints_compatibleregion:us
⚙️ Technical Specs
- architecture
- XLMRobertaModel
- params billions
- 0.56
- context length
- 4,096
- vram gb
- 1.7
- vram is estimated
- true
- vram formula
- VRAM ≈ (params * 0.75) + 0.8GB (KV) + 0.5GB (OS)
📊 Engagement & Metrics
- likes
- 582
- downloads
- 1,284,364
Free2AITools Constitutional Data Pipeline: Curated disclosure mode active. (V15.x Standard)