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Update README.md
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README.md
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metrics:
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- type: v_measure
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value: 79.58576208710117
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---
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-
tags:
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-
- mteb
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-
- arctic
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- arctic-embed
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-
model-index:
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-
- name: base
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-
results:
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-
- task:
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-
type: Classification
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-
dataset:
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-
type: mteb/amazon_counterfactual
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name: MTEB AmazonCounterfactualClassification (en)
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-
config: en
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-
split: test
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-
revision: e8379541af4e31359cca9fbcf4b00f2671dba205
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-
metrics:
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-
- type: accuracy
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-
value: 76.80597014925374
|
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-
- type: ap
|
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-
value: 39.31198155789558
|
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-
- type: f1
|
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-
value: 70.48198448222148
|
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-
- task:
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-
type: Classification
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-
dataset:
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-
type: mteb/amazon_polarity
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name: MTEB AmazonPolarityClassification
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-
config: default
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-
split: test
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-
revision: e2d317d38cd51312af73b3d32a06d1a08b442046
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-
metrics:
|
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-
- type: accuracy
|
2836 |
-
value: 82.831525
|
2837 |
-
- type: ap
|
2838 |
-
value: 77.4474050181638
|
2839 |
-
- type: f1
|
2840 |
-
value: 82.77204845110204
|
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-
- task:
|
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-
type: Classification
|
2843 |
-
dataset:
|
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-
type: mteb/amazon_reviews_multi
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2845 |
-
name: MTEB AmazonReviewsClassification (en)
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-
config: en
|
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-
split: test
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-
revision: 1399c76144fd37290681b995c656ef9b2e06e26d
|
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-
metrics:
|
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-
- type: accuracy
|
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-
value: 38.93000000000001
|
2852 |
-
- type: f1
|
2853 |
-
value: 37.98013371053459
|
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-
- task:
|
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-
type: Retrieval
|
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-
dataset:
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-
type: mteb/arguana
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-
name: MTEB ArguAna
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-
config: default
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-
split: test
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revision: c22ab2a51041ffd869aaddef7af8d8215647e41a
|
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metrics:
|
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-
- type: map_at_1
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-
value: 31.223
|
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-
- type: map_at_10
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-
value: 47.43
|
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-
- type: map_at_100
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-
value: 48.208
|
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-
- type: map_at_1000
|
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-
value: 48.211
|
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-
- type: map_at_3
|
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-
value: 42.579
|
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-
- type: map_at_5
|
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-
value: 45.263999999999996
|
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-
- type: mrr_at_1
|
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-
value: 31.65
|
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-
- type: mrr_at_10
|
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-
value: 47.573
|
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-
- type: mrr_at_100
|
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-
value: 48.359
|
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-
- type: mrr_at_1000
|
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-
value: 48.362
|
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-
- type: mrr_at_3
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-
value: 42.734
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-
- type: mrr_at_5
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-
value: 45.415
|
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-
- type: ndcg_at_1
|
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-
value: 31.223
|
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-
- type: ndcg_at_10
|
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-
value: 56.436
|
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-
- type: ndcg_at_100
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-
value: 59.657000000000004
|
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-
- type: ndcg_at_1000
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-
value: 59.731
|
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-
- type: ndcg_at_3
|
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-
value: 46.327
|
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-
- type: ndcg_at_5
|
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-
value: 51.178000000000004
|
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-
- type: precision_at_1
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-
value: 31.223
|
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-
- type: precision_at_10
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value: 8.527999999999999
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- type: precision_at_100
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value: 0.991
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-
- type: precision_at_1000
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value: 0.1
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-
- type: precision_at_3
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-
value: 19.061
|
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-
- type: precision_at_5
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-
value: 13.797999999999998
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-
- type: recall_at_1
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-
value: 31.223
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-
- type: recall_at_10
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-
value: 85.277
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-
- type: recall_at_100
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-
value: 99.075
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-
- type: recall_at_1000
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value: 99.644
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-
- type: recall_at_3
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-
value: 57.18299999999999
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- type: recall_at_5
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value: 68.99
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-
- task:
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type: Clustering
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dataset:
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type: mteb/arxiv-clustering-p2p
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name: MTEB ArxivClusteringP2P
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config: default
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split: test
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revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
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metrics:
|
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-
- type: v_measure
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-
value: 47.23625429411296
|
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-
- task:
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-
type: Clustering
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dataset:
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type: mteb/arxiv-clustering-s2s
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name: MTEB ArxivClusteringS2S
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config: default
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split: test
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revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
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-
metrics:
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-
- type: v_measure
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-
value: 37.433880471403654
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-
- task:
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-
type: Reranking
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dataset:
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type: mteb/askubuntudupquestions-reranking
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name: MTEB AskUbuntuDupQuestions
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config: default
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split: test
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revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
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-
metrics:
|
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-
- type: map
|
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-
value: 60.53175025582013
|
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-
- type: mrr
|
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-
value: 74.51160796728664
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-
- task:
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type: STS
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dataset:
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type: mteb/biosses-sts
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name: MTEB BIOSSES
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-
config: default
|
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split: test
|
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-
revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
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-
metrics:
|
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-
- type: cos_sim_pearson
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-
value: 88.93746103286769
|
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-
- type: cos_sim_spearman
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-
value: 86.62245567912619
|
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-
- type: euclidean_pearson
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-
value: 87.154173907501
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-
- type: euclidean_spearman
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-
value: 86.62245567912619
|
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-
- type: manhattan_pearson
|
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-
value: 87.17682026633462
|
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-
- type: manhattan_spearman
|
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-
value: 86.74775973908348
|
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-
- task:
|
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-
type: Classification
|
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-
dataset:
|
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type: mteb/banking77
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name: MTEB Banking77Classification
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-
config: default
|
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-
split: test
|
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-
revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
|
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-
metrics:
|
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-
- type: accuracy
|
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-
value: 80.33766233766232
|
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-
- type: f1
|
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-
value: 79.64931422442245
|
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-
- task:
|
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-
type: Clustering
|
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-
dataset:
|
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-
type: jinaai/big-patent-clustering
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name: MTEB BigPatentClustering
|
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-
config: default
|
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-
split: test
|
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-
revision: 62d5330920bca426ce9d3c76ea914f15fc83e891
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-
metrics:
|
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-
- type: v_measure
|
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-
value: 19.116028913890613
|
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-
- task:
|
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-
type: Clustering
|
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-
dataset:
|
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-
type: mteb/biorxiv-clustering-p2p
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-
name: MTEB BiorxivClusteringP2P
|
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-
config: default
|
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-
split: test
|
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-
revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
|
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-
metrics:
|
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-
- type: v_measure
|
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-
value: 36.966921852810174
|
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-
- task:
|
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-
type: Clustering
|
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-
dataset:
|
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-
type: mteb/biorxiv-clustering-s2s
|
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-
name: MTEB BiorxivClusteringS2S
|
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-
config: default
|
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-
split: test
|
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-
revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
|
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-
metrics:
|
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-
- type: v_measure
|
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-
value: 31.98019698537654
|
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-
- task:
|
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-
type: Retrieval
|
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-
dataset:
|
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-
type: mteb/cqadupstack-android
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-
name: MTEB CQADupstackAndroidRetrieval
|
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-
config: default
|
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-
split: test
|
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-
revision: f46a197baaae43b4f621051089b82a364682dfeb
|
3033 |
-
metrics:
|
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-
- type: map_at_1
|
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-
value: 34.079
|
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-
- type: map_at_10
|
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-
value: 46.35
|
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-
- type: map_at_100
|
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-
value: 47.785
|
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-
- type: map_at_1000
|
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-
value: 47.903
|
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-
- type: map_at_3
|
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-
value: 42.620999999999995
|
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-
- type: map_at_5
|
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-
value: 44.765
|
3046 |
-
- type: mrr_at_1
|
3047 |
-
value: 41.345
|
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-
- type: mrr_at_10
|
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-
value: 52.032000000000004
|
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-
- type: mrr_at_100
|
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-
value: 52.690000000000005
|
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-
- type: mrr_at_1000
|
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-
value: 52.727999999999994
|
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-
- type: mrr_at_3
|
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-
value: 49.428
|
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-
- type: mrr_at_5
|
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-
value: 51.093999999999994
|
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-
- type: ndcg_at_1
|
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-
value: 41.345
|
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-
- type: ndcg_at_10
|
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-
value: 53.027
|
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-
- type: ndcg_at_100
|
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-
value: 57.962
|
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-
- type: ndcg_at_1000
|
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-
value: 59.611999999999995
|
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-
- type: ndcg_at_3
|
3067 |
-
value: 47.687000000000005
|
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-
- type: ndcg_at_5
|
3069 |
-
value: 50.367
|
3070 |
-
- type: precision_at_1
|
3071 |
-
value: 41.345
|
3072 |
-
- type: precision_at_10
|
3073 |
-
value: 10.157
|
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-
- type: precision_at_100
|
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-
value: 1.567
|
3076 |
-
- type: precision_at_1000
|
3077 |
-
value: 0.199
|
3078 |
-
- type: precision_at_3
|
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-
value: 23.081
|
3080 |
-
- type: precision_at_5
|
3081 |
-
value: 16.738
|
3082 |
-
- type: recall_at_1
|
3083 |
-
value: 34.079
|
3084 |
-
- type: recall_at_10
|
3085 |
-
value: 65.93900000000001
|
3086 |
-
- type: recall_at_100
|
3087 |
-
value: 86.42699999999999
|
3088 |
-
- type: recall_at_1000
|
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-
value: 96.61
|
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-
- type: recall_at_3
|
3091 |
-
value: 50.56699999999999
|
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-
- type: recall_at_5
|
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-
value: 57.82000000000001
|
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-
- task:
|
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-
type: Retrieval
|
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-
dataset:
|
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-
type: mteb/cqadupstack-english
|
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-
name: MTEB CQADupstackEnglishRetrieval
|
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-
config: default
|
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-
split: test
|
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-
revision: ad9991cb51e31e31e430383c75ffb2885547b5f0
|
3102 |
-
metrics:
|
3103 |
-
- type: map_at_1
|
3104 |
-
value: 33.289
|
3105 |
-
- type: map_at_10
|
3106 |
-
value: 43.681
|
3107 |
-
- type: map_at_100
|
3108 |
-
value: 45.056000000000004
|
3109 |
-
- type: map_at_1000
|
3110 |
-
value: 45.171
|
3111 |
-
- type: map_at_3
|
3112 |
-
value: 40.702
|
3113 |
-
- type: map_at_5
|
3114 |
-
value: 42.292
|
3115 |
-
- type: mrr_at_1
|
3116 |
-
value: 41.146
|
3117 |
-
- type: mrr_at_10
|
3118 |
-
value: 49.604
|
3119 |
-
- type: mrr_at_100
|
3120 |
-
value: 50.28399999999999
|
3121 |
-
- type: mrr_at_1000
|
3122 |
-
value: 50.322
|
3123 |
-
- type: mrr_at_3
|
3124 |
-
value: 47.611
|
3125 |
-
- type: mrr_at_5
|
3126 |
-
value: 48.717
|
3127 |
-
- type: ndcg_at_1
|
3128 |
-
value: 41.146
|
3129 |
-
- type: ndcg_at_10
|
3130 |
-
value: 49.43
|
3131 |
-
- type: ndcg_at_100
|
3132 |
-
value: 54.01899999999999
|
3133 |
-
- type: ndcg_at_1000
|
3134 |
-
value: 55.803000000000004
|
3135 |
-
- type: ndcg_at_3
|
3136 |
-
value: 45.503
|
3137 |
-
- type: ndcg_at_5
|
3138 |
-
value: 47.198
|
3139 |
-
- type: precision_at_1
|
3140 |
-
value: 41.146
|
3141 |
-
- type: precision_at_10
|
3142 |
-
value: 9.268
|
3143 |
-
- type: precision_at_100
|
3144 |
-
value: 1.4749999999999999
|
3145 |
-
- type: precision_at_1000
|
3146 |
-
value: 0.19
|
3147 |
-
- type: precision_at_3
|
3148 |
-
value: 21.932
|
3149 |
-
- type: precision_at_5
|
3150 |
-
value: 15.389
|
3151 |
-
- type: recall_at_1
|
3152 |
-
value: 33.289
|
3153 |
-
- type: recall_at_10
|
3154 |
-
value: 59.209999999999994
|
3155 |
-
- type: recall_at_100
|
3156 |
-
value: 78.676
|
3157 |
-
- type: recall_at_1000
|
3158 |
-
value: 89.84100000000001
|
3159 |
-
- type: recall_at_3
|
3160 |
-
value: 47.351
|
3161 |
-
- type: recall_at_5
|
3162 |
-
value: 52.178999999999995
|
3163 |
-
- task:
|
3164 |
-
type: Retrieval
|
3165 |
-
dataset:
|
3166 |
-
type: mteb/cqadupstack-gaming
|
3167 |
-
name: MTEB CQADupstackGamingRetrieval
|
3168 |
-
config: default
|
3169 |
-
split: test
|
3170 |
-
revision: 4885aa143210c98657558c04aaf3dc47cfb54340
|
3171 |
-
metrics:
|
3172 |
-
- type: map_at_1
|
3173 |
-
value: 44.483
|
3174 |
-
- type: map_at_10
|
3175 |
-
value: 56.862
|
3176 |
-
- type: map_at_100
|
3177 |
-
value: 57.901
|
3178 |
-
- type: map_at_1000
|
3179 |
-
value: 57.948
|
3180 |
-
- type: map_at_3
|
3181 |
-
value: 53.737
|
3182 |
-
- type: map_at_5
|
3183 |
-
value: 55.64
|
3184 |
-
- type: mrr_at_1
|
3185 |
-
value: 50.658
|
3186 |
-
- type: mrr_at_10
|
3187 |
-
value: 60.281
|
3188 |
-
- type: mrr_at_100
|
3189 |
-
value: 60.946
|
3190 |
-
- type: mrr_at_1000
|
3191 |
-
value: 60.967000000000006
|
3192 |
-
- type: mrr_at_3
|
3193 |
-
value: 58.192
|
3194 |
-
- type: mrr_at_5
|
3195 |
-
value: 59.531
|
3196 |
-
- type: ndcg_at_1
|
3197 |
-
value: 50.658
|
3198 |
-
- type: ndcg_at_10
|
3199 |
-
value: 62.339
|
3200 |
-
- type: ndcg_at_100
|
3201 |
-
value: 66.28399999999999
|
3202 |
-
- type: ndcg_at_1000
|
3203 |
-
value: 67.166
|
3204 |
-
- type: ndcg_at_3
|
3205 |
-
value: 57.458
|
3206 |
-
- type: ndcg_at_5
|
3207 |
-
value: 60.112
|
3208 |
-
- type: precision_at_1
|
3209 |
-
value: 50.658
|
3210 |
-
- type: precision_at_10
|
3211 |
-
value: 9.762
|
3212 |
-
- type: precision_at_100
|
3213 |
-
value: 1.26
|
3214 |
-
- type: precision_at_1000
|
3215 |
-
value: 0.13799999999999998
|
3216 |
-
- type: precision_at_3
|
3217 |
-
value: 25.329
|
3218 |
-
- type: precision_at_5
|
3219 |
-
value: 17.254
|
3220 |
-
- type: recall_at_1
|
3221 |
-
value: 44.483
|
3222 |
-
- type: recall_at_10
|
3223 |
-
value: 74.819
|
3224 |
-
- type: recall_at_100
|
3225 |
-
value: 91.702
|
3226 |
-
- type: recall_at_1000
|
3227 |
-
value: 97.84
|
3228 |
-
- type: recall_at_3
|
3229 |
-
value: 62.13999999999999
|
3230 |
-
- type: recall_at_5
|
3231 |
-
value: 68.569
|
3232 |
-
- task:
|
3233 |
-
type: Retrieval
|
3234 |
-
dataset:
|
3235 |
-
type: mteb/cqadupstack-gis
|
3236 |
-
name: MTEB CQADupstackGisRetrieval
|
3237 |
-
config: default
|
3238 |
-
split: test
|
3239 |
-
revision: 5003b3064772da1887988e05400cf3806fe491f2
|
3240 |
-
metrics:
|
3241 |
-
- type: map_at_1
|
3242 |
-
value: 26.489
|
3243 |
-
- type: map_at_10
|
3244 |
-
value: 37.004999999999995
|
3245 |
-
- type: map_at_100
|
3246 |
-
value: 38.001000000000005
|
3247 |
-
- type: map_at_1000
|
3248 |
-
value: 38.085
|
3249 |
-
- type: map_at_3
|
3250 |
-
value: 34.239999999999995
|
3251 |
-
- type: map_at_5
|
3252 |
-
value: 35.934
|
3253 |
-
- type: mrr_at_1
|
3254 |
-
value: 28.362
|
3255 |
-
- type: mrr_at_10
|
3256 |
-
value: 38.807
|
3257 |
-
- type: mrr_at_100
|
3258 |
-
value: 39.671
|
3259 |
-
- type: mrr_at_1000
|
3260 |
-
value: 39.736
|
3261 |
-
- type: mrr_at_3
|
3262 |
-
value: 36.29
|
3263 |
-
- type: mrr_at_5
|
3264 |
-
value: 37.906
|
3265 |
-
- type: ndcg_at_1
|
3266 |
-
value: 28.362
|
3267 |
-
- type: ndcg_at_10
|
3268 |
-
value: 42.510999999999996
|
3269 |
-
- type: ndcg_at_100
|
3270 |
-
value: 47.226
|
3271 |
-
- type: ndcg_at_1000
|
3272 |
-
value: 49.226
|
3273 |
-
- type: ndcg_at_3
|
3274 |
-
value: 37.295
|
3275 |
-
- type: ndcg_at_5
|
3276 |
-
value: 40.165
|
3277 |
-
- type: precision_at_1
|
3278 |
-
value: 28.362
|
3279 |
-
- type: precision_at_10
|
3280 |
-
value: 6.633
|
3281 |
-
- type: precision_at_100
|
3282 |
-
value: 0.9490000000000001
|
3283 |
-
- type: precision_at_1000
|
3284 |
-
value: 0.11499999999999999
|
3285 |
-
- type: precision_at_3
|
3286 |
-
value: 16.234
|
3287 |
-
- type: precision_at_5
|
3288 |
-
value: 11.434999999999999
|
3289 |
-
- type: recall_at_1
|
3290 |
-
value: 26.489
|
3291 |
-
- type: recall_at_10
|
3292 |
-
value: 57.457
|
3293 |
-
- type: recall_at_100
|
3294 |
-
value: 78.712
|
3295 |
-
- type: recall_at_1000
|
3296 |
-
value: 93.565
|
3297 |
-
- type: recall_at_3
|
3298 |
-
value: 43.748
|
3299 |
-
- type: recall_at_5
|
3300 |
-
value: 50.589
|
3301 |
-
- task:
|
3302 |
-
type: Retrieval
|
3303 |
-
dataset:
|
3304 |
-
type: mteb/cqadupstack-mathematica
|
3305 |
-
name: MTEB CQADupstackMathematicaRetrieval
|
3306 |
-
config: default
|
3307 |
-
split: test
|
3308 |
-
revision: 90fceea13679c63fe563ded68f3b6f06e50061de
|
3309 |
-
metrics:
|
3310 |
-
- type: map_at_1
|
3311 |
-
value: 12.418999999999999
|
3312 |
-
- type: map_at_10
|
3313 |
-
value: 22.866
|
3314 |
-
- type: map_at_100
|
3315 |
-
value: 24.365000000000002
|
3316 |
-
- type: map_at_1000
|
3317 |
-
value: 24.479
|
3318 |
-
- type: map_at_3
|
3319 |
-
value: 19.965
|
3320 |
-
- type: map_at_5
|
3321 |
-
value: 21.684
|
3322 |
-
- type: mrr_at_1
|
3323 |
-
value: 14.677000000000001
|
3324 |
-
- type: mrr_at_10
|
3325 |
-
value: 26.316
|
3326 |
-
- type: mrr_at_100
|
3327 |
-
value: 27.514
|
3328 |
-
- type: mrr_at_1000
|
3329 |
-
value: 27.57
|
3330 |
-
- type: mrr_at_3
|
3331 |
-
value: 23.3
|
3332 |
-
- type: mrr_at_5
|
3333 |
-
value: 25.191000000000003
|
3334 |
-
- type: ndcg_at_1
|
3335 |
-
value: 14.677000000000001
|
3336 |
-
- type: ndcg_at_10
|
3337 |
-
value: 28.875
|
3338 |
-
- type: ndcg_at_100
|
3339 |
-
value: 35.607
|
3340 |
-
- type: ndcg_at_1000
|
3341 |
-
value: 38.237
|
3342 |
-
- type: ndcg_at_3
|
3343 |
-
value: 23.284
|
3344 |
-
- type: ndcg_at_5
|
3345 |
-
value: 26.226
|
3346 |
-
- type: precision_at_1
|
3347 |
-
value: 14.677000000000001
|
3348 |
-
- type: precision_at_10
|
3349 |
-
value: 5.771
|
3350 |
-
- type: precision_at_100
|
3351 |
-
value: 1.058
|
3352 |
-
- type: precision_at_1000
|
3353 |
-
value: 0.14200000000000002
|
3354 |
-
- type: precision_at_3
|
3355 |
-
value: 11.940000000000001
|
3356 |
-
- type: precision_at_5
|
3357 |
-
value: 9.229
|
3358 |
-
- type: recall_at_1
|
3359 |
-
value: 12.418999999999999
|
3360 |
-
- type: recall_at_10
|
3361 |
-
value: 43.333
|
3362 |
-
- type: recall_at_100
|
3363 |
-
value: 71.942
|
3364 |
-
- type: recall_at_1000
|
3365 |
-
value: 90.67399999999999
|
3366 |
-
- type: recall_at_3
|
3367 |
-
value: 28.787000000000003
|
3368 |
-
- type: recall_at_5
|
3369 |
-
value: 35.638
|
3370 |
-
- task:
|
3371 |
-
type: Retrieval
|
3372 |
-
dataset:
|
3373 |
-
type: mteb/cqadupstack-physics
|
3374 |
-
name: MTEB CQADupstackPhysicsRetrieval
|
3375 |
-
config: default
|
3376 |
-
split: test
|
3377 |
-
revision: 79531abbd1fb92d06c6d6315a0cbbbf5bb247ea4
|
3378 |
-
metrics:
|
3379 |
-
- type: map_at_1
|
3380 |
-
value: 31.686999999999998
|
3381 |
-
- type: map_at_10
|
3382 |
-
value: 42.331
|
3383 |
-
- type: map_at_100
|
3384 |
-
value: 43.655
|
3385 |
-
- type: map_at_1000
|
3386 |
-
value: 43.771
|
3387 |
-
- type: map_at_3
|
3388 |
-
value: 38.944
|
3389 |
-
- type: map_at_5
|
3390 |
-
value: 40.991
|
3391 |
-
- type: mrr_at_1
|
3392 |
-
value: 37.921
|
3393 |
-
- type: mrr_at_10
|
3394 |
-
value: 47.534
|
3395 |
-
- type: mrr_at_100
|
3396 |
-
value: 48.362
|
3397 |
-
- type: mrr_at_1000
|
3398 |
-
value: 48.405
|
3399 |
-
- type: mrr_at_3
|
3400 |
-
value: 44.995000000000005
|
3401 |
-
- type: mrr_at_5
|
3402 |
-
value: 46.617
|
3403 |
-
- type: ndcg_at_1
|
3404 |
-
value: 37.921
|
3405 |
-
- type: ndcg_at_10
|
3406 |
-
value: 48.236000000000004
|
3407 |
-
- type: ndcg_at_100
|
3408 |
-
value: 53.705000000000005
|
3409 |
-
- type: ndcg_at_1000
|
3410 |
-
value: 55.596000000000004
|
3411 |
-
- type: ndcg_at_3
|
3412 |
-
value: 43.11
|
3413 |
-
- type: ndcg_at_5
|
3414 |
-
value: 45.862
|
3415 |
-
- type: precision_at_1
|
3416 |
-
value: 37.921
|
3417 |
-
- type: precision_at_10
|
3418 |
-
value: 8.643
|
3419 |
-
- type: precision_at_100
|
3420 |
-
value: 1.336
|
3421 |
-
- type: precision_at_1000
|
3422 |
-
value: 0.166
|
3423 |
-
- type: precision_at_3
|
3424 |
-
value: 20.308
|
3425 |
-
- type: precision_at_5
|
3426 |
-
value: 14.514
|
3427 |
-
- type: recall_at_1
|
3428 |
-
value: 31.686999999999998
|
3429 |
-
- type: recall_at_10
|
3430 |
-
value: 60.126999999999995
|
3431 |
-
- type: recall_at_100
|
3432 |
-
value: 83.10600000000001
|
3433 |
-
- type: recall_at_1000
|
3434 |
-
value: 95.15
|
3435 |
-
- type: recall_at_3
|
3436 |
-
value: 46.098
|
3437 |
-
- type: recall_at_5
|
3438 |
-
value: 53.179
|
3439 |
-
- task:
|
3440 |
-
type: Retrieval
|
3441 |
-
dataset:
|
3442 |
-
type: mteb/cqadupstack-programmers
|
3443 |
-
name: MTEB CQADupstackProgrammersRetrieval
|
3444 |
-
config: default
|
3445 |
-
split: test
|
3446 |
-
revision: 6184bc1440d2dbc7612be22b50686b8826d22b32
|
3447 |
-
metrics:
|
3448 |
-
- type: map_at_1
|
3449 |
-
value: 28.686
|
3450 |
-
- type: map_at_10
|
3451 |
-
value: 39.146
|
3452 |
-
- type: map_at_100
|
3453 |
-
value: 40.543
|
3454 |
-
- type: map_at_1000
|
3455 |
-
value: 40.644999999999996
|
3456 |
-
- type: map_at_3
|
3457 |
-
value: 36.195
|
3458 |
-
- type: map_at_5
|
3459 |
-
value: 37.919000000000004
|
3460 |
-
- type: mrr_at_1
|
3461 |
-
value: 35.160000000000004
|
3462 |
-
- type: mrr_at_10
|
3463 |
-
value: 44.711
|
3464 |
-
- type: mrr_at_100
|
3465 |
-
value: 45.609
|
3466 |
-
- type: mrr_at_1000
|
3467 |
-
value: 45.655
|
3468 |
-
- type: mrr_at_3
|
3469 |
-
value: 42.409
|
3470 |
-
- type: mrr_at_5
|
3471 |
-
value: 43.779
|
3472 |
-
- type: ndcg_at_1
|
3473 |
-
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|
3474 |
-
- type: ndcg_at_10
|
3475 |
-
value: 44.977000000000004
|
3476 |
-
- type: ndcg_at_100
|
3477 |
-
value: 50.663000000000004
|
3478 |
-
- type: ndcg_at_1000
|
3479 |
-
value: 52.794
|
3480 |
-
- type: ndcg_at_3
|
3481 |
-
value: 40.532000000000004
|
3482 |
-
- type: ndcg_at_5
|
3483 |
-
value: 42.641
|
3484 |
-
- type: precision_at_1
|
3485 |
-
value: 35.160000000000004
|
3486 |
-
- type: precision_at_10
|
3487 |
-
value: 8.014000000000001
|
3488 |
-
- type: precision_at_100
|
3489 |
-
value: 1.269
|
3490 |
-
- type: precision_at_1000
|
3491 |
-
value: 0.163
|
3492 |
-
- type: precision_at_3
|
3493 |
-
value: 19.444
|
3494 |
-
- type: precision_at_5
|
3495 |
-
value: 13.653
|
3496 |
-
- type: recall_at_1
|
3497 |
-
value: 28.686
|
3498 |
-
- type: recall_at_10
|
3499 |
-
value: 56.801
|
3500 |
-
- type: recall_at_100
|
3501 |
-
value: 80.559
|
3502 |
-
- type: recall_at_1000
|
3503 |
-
value: 95.052
|
3504 |
-
- type: recall_at_3
|
3505 |
-
value: 43.675999999999995
|
3506 |
-
- type: recall_at_5
|
3507 |
-
value: 49.703
|
3508 |
-
- task:
|
3509 |
-
type: Retrieval
|
3510 |
-
dataset:
|
3511 |
-
type: mteb/cqadupstack
|
3512 |
-
name: MTEB CQADupstackRetrieval
|
3513 |
-
config: default
|
3514 |
-
split: test
|
3515 |
-
revision: 4ffe81d471b1924886b33c7567bfb200e9eec5c4
|
3516 |
-
metrics:
|
3517 |
-
- type: map_at_1
|
3518 |
-
value: 28.173833333333338
|
3519 |
-
- type: map_at_10
|
3520 |
-
value: 38.202083333333334
|
3521 |
-
- type: map_at_100
|
3522 |
-
value: 39.47475
|
3523 |
-
- type: map_at_1000
|
3524 |
-
value: 39.586499999999994
|
3525 |
-
- type: map_at_3
|
3526 |
-
value: 35.17308333333334
|
3527 |
-
- type: map_at_5
|
3528 |
-
value: 36.914
|
3529 |
-
- type: mrr_at_1
|
3530 |
-
value: 32.92958333333333
|
3531 |
-
- type: mrr_at_10
|
3532 |
-
value: 42.16758333333333
|
3533 |
-
- type: mrr_at_100
|
3534 |
-
value: 43.04108333333333
|
3535 |
-
- type: mrr_at_1000
|
3536 |
-
value: 43.092499999999994
|
3537 |
-
- type: mrr_at_3
|
3538 |
-
value: 39.69166666666666
|
3539 |
-
- type: mrr_at_5
|
3540 |
-
value: 41.19458333333333
|
3541 |
-
- type: ndcg_at_1
|
3542 |
-
value: 32.92958333333333
|
3543 |
-
- type: ndcg_at_10
|
3544 |
-
value: 43.80583333333333
|
3545 |
-
- type: ndcg_at_100
|
3546 |
-
value: 49.060916666666664
|
3547 |
-
- type: ndcg_at_1000
|
3548 |
-
value: 51.127250000000004
|
3549 |
-
- type: ndcg_at_3
|
3550 |
-
value: 38.80383333333333
|
3551 |
-
- type: ndcg_at_5
|
3552 |
-
value: 41.29658333333333
|
3553 |
-
- type: precision_at_1
|
3554 |
-
value: 32.92958333333333
|
3555 |
-
- type: precision_at_10
|
3556 |
-
value: 7.655666666666666
|
3557 |
-
- type: precision_at_100
|
3558 |
-
value: 1.2094166666666668
|
3559 |
-
- type: precision_at_1000
|
3560 |
-
value: 0.15750000000000003
|
3561 |
-
- type: precision_at_3
|
3562 |
-
value: 17.87975
|
3563 |
-
- type: precision_at_5
|
3564 |
-
value: 12.741833333333332
|
3565 |
-
- type: recall_at_1
|
3566 |
-
value: 28.173833333333338
|
3567 |
-
- type: recall_at_10
|
3568 |
-
value: 56.219249999999995
|
3569 |
-
- type: recall_at_100
|
3570 |
-
value: 79.01416666666665
|
3571 |
-
- type: recall_at_1000
|
3572 |
-
value: 93.13425000000001
|
3573 |
-
- type: recall_at_3
|
3574 |
-
value: 42.39241666666667
|
3575 |
-
- type: recall_at_5
|
3576 |
-
value: 48.764833333333335
|
3577 |
-
- task:
|
3578 |
-
type: Retrieval
|
3579 |
-
dataset:
|
3580 |
-
type: mteb/cqadupstack-stats
|
3581 |
-
name: MTEB CQADupstackStatsRetrieval
|
3582 |
-
config: default
|
3583 |
-
split: test
|
3584 |
-
revision: 65ac3a16b8e91f9cee4c9828cc7c335575432a2a
|
3585 |
-
metrics:
|
3586 |
-
- type: map_at_1
|
3587 |
-
value: 25.625999999999998
|
3588 |
-
- type: map_at_10
|
3589 |
-
value: 32.808
|
3590 |
-
- type: map_at_100
|
3591 |
-
value: 33.951
|
3592 |
-
- type: map_at_1000
|
3593 |
-
value: 34.052
|
3594 |
-
- type: map_at_3
|
3595 |
-
value: 30.536
|
3596 |
-
- type: map_at_5
|
3597 |
-
value: 31.77
|
3598 |
-
- type: mrr_at_1
|
3599 |
-
value: 28.374
|
3600 |
-
- type: mrr_at_10
|
3601 |
-
value: 35.527
|
3602 |
-
- type: mrr_at_100
|
3603 |
-
value: 36.451
|
3604 |
-
- type: mrr_at_1000
|
3605 |
-
value: 36.522
|
3606 |
-
- type: mrr_at_3
|
3607 |
-
value: 33.410000000000004
|
3608 |
-
- type: mrr_at_5
|
3609 |
-
value: 34.537
|
3610 |
-
- type: ndcg_at_1
|
3611 |
-
value: 28.374
|
3612 |
-
- type: ndcg_at_10
|
3613 |
-
value: 37.172
|
3614 |
-
- type: ndcg_at_100
|
3615 |
-
value: 42.474000000000004
|
3616 |
-
- type: ndcg_at_1000
|
3617 |
-
value: 44.853
|
3618 |
-
- type: ndcg_at_3
|
3619 |
-
value: 32.931
|
3620 |
-
- type: ndcg_at_5
|
3621 |
-
value: 34.882999999999996
|
3622 |
-
- type: precision_at_1
|
3623 |
-
value: 28.374
|
3624 |
-
- type: precision_at_10
|
3625 |
-
value: 5.813
|
3626 |
-
- type: precision_at_100
|
3627 |
-
value: 0.928
|
3628 |
-
- type: precision_at_1000
|
3629 |
-
value: 0.121
|
3630 |
-
- type: precision_at_3
|
3631 |
-
value: 14.008000000000001
|
3632 |
-
- type: precision_at_5
|
3633 |
-
value: 9.754999999999999
|
3634 |
-
- type: recall_at_1
|
3635 |
-
value: 25.625999999999998
|
3636 |
-
- type: recall_at_10
|
3637 |
-
value: 47.812
|
3638 |
-
- type: recall_at_100
|
3639 |
-
value: 71.61800000000001
|
3640 |
-
- type: recall_at_1000
|
3641 |
-
value: 88.881
|
3642 |
-
- type: recall_at_3
|
3643 |
-
value: 35.876999999999995
|
3644 |
-
- type: recall_at_5
|
3645 |
-
value: 40.839
|
3646 |
-
- task:
|
3647 |
-
type: Retrieval
|
3648 |
-
dataset:
|
3649 |
-
type: mteb/cqadupstack-tex
|
3650 |
-
name: MTEB CQADupstackTexRetrieval
|
3651 |
-
config: default
|
3652 |
-
split: test
|
3653 |
-
revision: 46989137a86843e03a6195de44b09deda022eec7
|
3654 |
-
metrics:
|
3655 |
-
- type: map_at_1
|
3656 |
-
value: 18.233
|
3657 |
-
- type: map_at_10
|
3658 |
-
value: 26.375999999999998
|
3659 |
-
- type: map_at_100
|
3660 |
-
value: 27.575
|
3661 |
-
- type: map_at_1000
|
3662 |
-
value: 27.706999999999997
|
3663 |
-
- type: map_at_3
|
3664 |
-
value: 23.619
|
3665 |
-
- type: map_at_5
|
3666 |
-
value: 25.217
|
3667 |
-
- type: mrr_at_1
|
3668 |
-
value: 22.023
|
3669 |
-
- type: mrr_at_10
|
3670 |
-
value: 30.122
|
3671 |
-
- type: mrr_at_100
|
3672 |
-
value: 31.083
|
3673 |
-
- type: mrr_at_1000
|
3674 |
-
value: 31.163999999999998
|
3675 |
-
- type: mrr_at_3
|
3676 |
-
value: 27.541
|
3677 |
-
- type: mrr_at_5
|
3678 |
-
value: 29.061999999999998
|
3679 |
-
- type: ndcg_at_1
|
3680 |
-
value: 22.023
|
3681 |
-
- type: ndcg_at_10
|
3682 |
-
value: 31.476
|
3683 |
-
- type: ndcg_at_100
|
3684 |
-
value: 37.114000000000004
|
3685 |
-
- type: ndcg_at_1000
|
3686 |
-
value: 39.981
|
3687 |
-
- type: ndcg_at_3
|
3688 |
-
value: 26.538
|
3689 |
-
- type: ndcg_at_5
|
3690 |
-
value: 29.016
|
3691 |
-
- type: precision_at_1
|
3692 |
-
value: 22.023
|
3693 |
-
- type: precision_at_10
|
3694 |
-
value: 5.819
|
3695 |
-
- type: precision_at_100
|
3696 |
-
value: 1.018
|
3697 |
-
- type: precision_at_1000
|
3698 |
-
value: 0.14300000000000002
|
3699 |
-
- type: precision_at_3
|
3700 |
-
value: 12.583
|
3701 |
-
- type: precision_at_5
|
3702 |
-
value: 9.36
|
3703 |
-
- type: recall_at_1
|
3704 |
-
value: 18.233
|
3705 |
-
- type: recall_at_10
|
3706 |
-
value: 43.029
|
3707 |
-
- type: recall_at_100
|
3708 |
-
value: 68.253
|
3709 |
-
- type: recall_at_1000
|
3710 |
-
value: 88.319
|
3711 |
-
- type: recall_at_3
|
3712 |
-
value: 29.541
|
3713 |
-
- type: recall_at_5
|
3714 |
-
value: 35.783
|
3715 |
-
- task:
|
3716 |
-
type: Retrieval
|
3717 |
-
dataset:
|
3718 |
-
type: mteb/cqadupstack-unix
|
3719 |
-
name: MTEB CQADupstackUnixRetrieval
|
3720 |
-
config: default
|
3721 |
-
split: test
|
3722 |
-
revision: 6c6430d3a6d36f8d2a829195bc5dc94d7e063e53
|
3723 |
-
metrics:
|
3724 |
-
- type: map_at_1
|
3725 |
-
value: 28.923
|
3726 |
-
- type: map_at_10
|
3727 |
-
value: 39.231
|
3728 |
-
- type: map_at_100
|
3729 |
-
value: 40.483000000000004
|
3730 |
-
- type: map_at_1000
|
3731 |
-
value: 40.575
|
3732 |
-
- type: map_at_3
|
3733 |
-
value: 35.94
|
3734 |
-
- type: map_at_5
|
3735 |
-
value: 37.683
|
3736 |
-
- type: mrr_at_1
|
3737 |
-
value: 33.955
|
3738 |
-
- type: mrr_at_10
|
3739 |
-
value: 43.163000000000004
|
3740 |
-
- type: mrr_at_100
|
3741 |
-
value: 44.054
|
3742 |
-
- type: mrr_at_1000
|
3743 |
-
value: 44.099
|
3744 |
-
- type: mrr_at_3
|
3745 |
-
value: 40.361000000000004
|
3746 |
-
- type: mrr_at_5
|
3747 |
-
value: 41.905
|
3748 |
-
- type: ndcg_at_1
|
3749 |
-
value: 33.955
|
3750 |
-
- type: ndcg_at_10
|
3751 |
-
value: 45.068000000000005
|
3752 |
-
- type: ndcg_at_100
|
3753 |
-
value: 50.470000000000006
|
3754 |
-
- type: ndcg_at_1000
|
3755 |
-
value: 52.349000000000004
|
3756 |
-
- type: ndcg_at_3
|
3757 |
-
value: 39.298
|
3758 |
-
- type: ndcg_at_5
|
3759 |
-
value: 41.821999999999996
|
3760 |
-
- type: precision_at_1
|
3761 |
-
value: 33.955
|
3762 |
-
- type: precision_at_10
|
3763 |
-
value: 7.649
|
3764 |
-
- type: precision_at_100
|
3765 |
-
value: 1.173
|
3766 |
-
- type: precision_at_1000
|
3767 |
-
value: 0.14200000000000002
|
3768 |
-
- type: precision_at_3
|
3769 |
-
value: 17.817
|
3770 |
-
- type: precision_at_5
|
3771 |
-
value: 12.537
|
3772 |
-
- type: recall_at_1
|
3773 |
-
value: 28.923
|
3774 |
-
- type: recall_at_10
|
3775 |
-
value: 58.934
|
3776 |
-
- type: recall_at_100
|
3777 |
-
value: 81.809
|
3778 |
-
- type: recall_at_1000
|
3779 |
-
value: 94.71300000000001
|
3780 |
-
- type: recall_at_3
|
3781 |
-
value: 42.975
|
3782 |
-
- type: recall_at_5
|
3783 |
-
value: 49.501
|
3784 |
-
- task:
|
3785 |
-
type: Retrieval
|
3786 |
-
dataset:
|
3787 |
-
type: mteb/cqadupstack-webmasters
|
3788 |
-
name: MTEB CQADupstackWebmastersRetrieval
|
3789 |
-
config: default
|
3790 |
-
split: test
|
3791 |
-
revision: 160c094312a0e1facb97e55eeddb698c0abe3571
|
3792 |
-
metrics:
|
3793 |
-
- type: map_at_1
|
3794 |
-
value: 28.596
|
3795 |
-
- type: map_at_10
|
3796 |
-
value: 38.735
|
3797 |
-
- type: map_at_100
|
3798 |
-
value: 40.264
|
3799 |
-
- type: map_at_1000
|
3800 |
-
value: 40.48
|
3801 |
-
- type: map_at_3
|
3802 |
-
value: 35.394999999999996
|
3803 |
-
- type: map_at_5
|
3804 |
-
value: 37.099
|
3805 |
-
- type: mrr_at_1
|
3806 |
-
value: 33.992
|
3807 |
-
- type: mrr_at_10
|
3808 |
-
value: 43.076
|
3809 |
-
- type: mrr_at_100
|
3810 |
-
value: 44.005
|
3811 |
-
- type: mrr_at_1000
|
3812 |
-
value: 44.043
|
3813 |
-
- type: mrr_at_3
|
3814 |
-
value: 40.415
|
3815 |
-
- type: mrr_at_5
|
3816 |
-
value: 41.957
|
3817 |
-
- type: ndcg_at_1
|
3818 |
-
value: 33.992
|
3819 |
-
- type: ndcg_at_10
|
3820 |
-
value: 44.896
|
3821 |
-
- type: ndcg_at_100
|
3822 |
-
value: 50.44499999999999
|
3823 |
-
- type: ndcg_at_1000
|
3824 |
-
value: 52.675000000000004
|
3825 |
-
- type: ndcg_at_3
|
3826 |
-
value: 39.783
|
3827 |
-
- type: ndcg_at_5
|
3828 |
-
value: 41.997
|
3829 |
-
- type: precision_at_1
|
3830 |
-
value: 33.992
|
3831 |
-
- type: precision_at_10
|
3832 |
-
value: 8.498
|
3833 |
-
- type: precision_at_100
|
3834 |
-
value: 1.585
|
3835 |
-
- type: precision_at_1000
|
3836 |
-
value: 0.248
|
3837 |
-
- type: precision_at_3
|
3838 |
-
value: 18.511
|
3839 |
-
- type: precision_at_5
|
3840 |
-
value: 13.241
|
3841 |
-
- type: recall_at_1
|
3842 |
-
value: 28.596
|
3843 |
-
- type: recall_at_10
|
3844 |
-
value: 56.885
|
3845 |
-
- type: recall_at_100
|
3846 |
-
value: 82.306
|
3847 |
-
- type: recall_at_1000
|
3848 |
-
value: 95.813
|
3849 |
-
- type: recall_at_3
|
3850 |
-
value: 42.168
|
3851 |
-
- type: recall_at_5
|
3852 |
-
value: 48.32
|
3853 |
-
- task:
|
3854 |
-
type: Retrieval
|
3855 |
-
dataset:
|
3856 |
-
type: mteb/cqadupstack-wordpress
|
3857 |
-
name: MTEB CQADupstackWordpressRetrieval
|
3858 |
-
config: default
|
3859 |
-
split: test
|
3860 |
-
revision: 4ffe81d471b1924886b33c7567bfb200e9eec5c4
|
3861 |
-
metrics:
|
3862 |
-
- type: map_at_1
|
3863 |
-
value: 25.576
|
3864 |
-
- type: map_at_10
|
3865 |
-
value: 33.034
|
3866 |
-
- type: map_at_100
|
3867 |
-
value: 34.117999999999995
|
3868 |
-
- type: map_at_1000
|
3869 |
-
value: 34.222
|
3870 |
-
- type: map_at_3
|
3871 |
-
value: 30.183
|
3872 |
-
- type: map_at_5
|
3873 |
-
value: 31.974000000000004
|
3874 |
-
- type: mrr_at_1
|
3875 |
-
value: 27.542
|
3876 |
-
- type: mrr_at_10
|
3877 |
-
value: 34.838
|
3878 |
-
- type: mrr_at_100
|
3879 |
-
value: 35.824
|
3880 |
-
- type: mrr_at_1000
|
3881 |
-
value: 35.899
|
3882 |
-
- type: mrr_at_3
|
3883 |
-
value: 32.348
|
3884 |
-
- type: mrr_at_5
|
3885 |
-
value: 34.039
|
3886 |
-
- type: ndcg_at_1
|
3887 |
-
value: 27.542
|
3888 |
-
- type: ndcg_at_10
|
3889 |
-
value: 37.663000000000004
|
3890 |
-
- type: ndcg_at_100
|
3891 |
-
value: 42.762
|
3892 |
-
- type: ndcg_at_1000
|
3893 |
-
value: 45.235
|
3894 |
-
- type: ndcg_at_3
|
3895 |
-
value: 32.227
|
3896 |
-
- type: ndcg_at_5
|
3897 |
-
value: 35.27
|
3898 |
-
- type: precision_at_1
|
3899 |
-
value: 27.542
|
3900 |
-
- type: precision_at_10
|
3901 |
-
value: 5.840999999999999
|
3902 |
-
- type: precision_at_100
|
3903 |
-
value: 0.895
|
3904 |
-
- type: precision_at_1000
|
3905 |
-
value: 0.123
|
3906 |
-
- type: precision_at_3
|
3907 |
-
value: 13.370000000000001
|
3908 |
-
- type: precision_at_5
|
3909 |
-
value: 9.797
|
3910 |
-
- type: recall_at_1
|
3911 |
-
value: 25.576
|
3912 |
-
- type: recall_at_10
|
3913 |
-
value: 50.285000000000004
|
3914 |
-
- type: recall_at_100
|
3915 |
-
value: 73.06
|
3916 |
-
- type: recall_at_1000
|
3917 |
-
value: 91.15299999999999
|
3918 |
-
- type: recall_at_3
|
3919 |
-
value: 35.781
|
3920 |
-
- type: recall_at_5
|
3921 |
-
value: 43.058
|
3922 |
-
- task:
|
3923 |
-
type: Retrieval
|
3924 |
-
dataset:
|
3925 |
-
type: mteb/climate-fever
|
3926 |
-
name: MTEB ClimateFEVER
|
3927 |
-
config: default
|
3928 |
-
split: test
|
3929 |
-
revision: 47f2ac6acb640fc46020b02a5b59fdda04d39380
|
3930 |
-
metrics:
|
3931 |
-
- type: map_at_1
|
3932 |
-
value: 17.061
|
3933 |
-
- type: map_at_10
|
3934 |
-
value: 29.464000000000002
|
3935 |
-
- type: map_at_100
|
3936 |
-
value: 31.552999999999997
|
3937 |
-
- type: map_at_1000
|
3938 |
-
value: 31.707
|
3939 |
-
- type: map_at_3
|
3940 |
-
value: 24.834999999999997
|
3941 |
-
- type: map_at_5
|
3942 |
-
value: 27.355
|
3943 |
-
- type: mrr_at_1
|
3944 |
-
value: 38.958
|
3945 |
-
- type: mrr_at_10
|
3946 |
-
value: 51.578
|
3947 |
-
- type: mrr_at_100
|
3948 |
-
value: 52.262
|
3949 |
-
- type: mrr_at_1000
|
3950 |
-
value: 52.283
|
3951 |
-
- type: mrr_at_3
|
3952 |
-
value: 48.599
|
3953 |
-
- type: mrr_at_5
|
3954 |
-
value: 50.404
|
3955 |
-
- type: ndcg_at_1
|
3956 |
-
value: 38.958
|
3957 |
-
- type: ndcg_at_10
|
3958 |
-
value: 39.367999999999995
|
3959 |
-
- type: ndcg_at_100
|
3960 |
-
value: 46.521
|
3961 |
-
- type: ndcg_at_1000
|
3962 |
-
value: 49.086999999999996
|
3963 |
-
- type: ndcg_at_3
|
3964 |
-
value: 33.442
|
3965 |
-
- type: ndcg_at_5
|
3966 |
-
value: 35.515
|
3967 |
-
- type: precision_at_1
|
3968 |
-
value: 38.958
|
3969 |
-
- type: precision_at_10
|
3970 |
-
value: 12.110999999999999
|
3971 |
-
- type: precision_at_100
|
3972 |
-
value: 1.982
|
3973 |
-
- type: precision_at_1000
|
3974 |
-
value: 0.247
|
3975 |
-
- type: precision_at_3
|
3976 |
-
value: 25.102999999999998
|
3977 |
-
- type: precision_at_5
|
3978 |
-
value: 18.971
|
3979 |
-
- type: recall_at_1
|
3980 |
-
value: 17.061
|
3981 |
-
- type: recall_at_10
|
3982 |
-
value: 45.198
|
3983 |
-
- type: recall_at_100
|
3984 |
-
value: 69.18900000000001
|
3985 |
-
- type: recall_at_1000
|
3986 |
-
value: 83.38499999999999
|
3987 |
-
- type: recall_at_3
|
3988 |
-
value: 30.241
|
3989 |
-
- type: recall_at_5
|
3990 |
-
value: 36.851
|
3991 |
-
- task:
|
3992 |
-
type: Retrieval
|
3993 |
-
dataset:
|
3994 |
-
type: mteb/dbpedia
|
3995 |
-
name: MTEB DBPedia
|
3996 |
-
config: default
|
3997 |
-
split: test
|
3998 |
-
revision: c0f706b76e590d620bd6618b3ca8efdd34e2d659
|
3999 |
-
metrics:
|
4000 |
-
- type: map_at_1
|
4001 |
-
value: 9.398
|
4002 |
-
- type: map_at_10
|
4003 |
-
value: 21.421
|
4004 |
-
- type: map_at_100
|
4005 |
-
value: 31.649
|
4006 |
-
- type: map_at_1000
|
4007 |
-
value: 33.469
|
4008 |
-
- type: map_at_3
|
4009 |
-
value: 15.310000000000002
|
4010 |
-
- type: map_at_5
|
4011 |
-
value: 17.946
|
4012 |
-
- type: mrr_at_1
|
4013 |
-
value: 71
|
4014 |
-
- type: mrr_at_10
|
4015 |
-
value: 78.92099999999999
|
4016 |
-
- type: mrr_at_100
|
4017 |
-
value: 79.225
|
4018 |
-
- type: mrr_at_1000
|
4019 |
-
value: 79.23
|
4020 |
-
- type: mrr_at_3
|
4021 |
-
value: 77.792
|
4022 |
-
- type: mrr_at_5
|
4023 |
-
value: 78.467
|
4024 |
-
- type: ndcg_at_1
|
4025 |
-
value: 57.99999999999999
|
4026 |
-
- type: ndcg_at_10
|
4027 |
-
value: 44.733000000000004
|
4028 |
-
- type: ndcg_at_100
|
4029 |
-
value: 50.646
|
4030 |
-
- type: ndcg_at_1000
|
4031 |
-
value: 57.903999999999996
|
4032 |
-
- type: ndcg_at_3
|
4033 |
-
value: 49.175999999999995
|
4034 |
-
- type: ndcg_at_5
|
4035 |
-
value: 46.800999999999995
|
4036 |
-
- type: precision_at_1
|
4037 |
-
value: 71
|
4038 |
-
- type: precision_at_10
|
4039 |
-
value: 36.25
|
4040 |
-
- type: precision_at_100
|
4041 |
-
value: 12.135
|
4042 |
-
- type: precision_at_1000
|
4043 |
-
value: 2.26
|
4044 |
-
- type: precision_at_3
|
4045 |
-
value: 52.75
|
4046 |
-
- type: precision_at_5
|
4047 |
-
value: 45.65
|
4048 |
-
- type: recall_at_1
|
4049 |
-
value: 9.398
|
4050 |
-
- type: recall_at_10
|
4051 |
-
value: 26.596999999999998
|
4052 |
-
- type: recall_at_100
|
4053 |
-
value: 57.943
|
4054 |
-
- type: recall_at_1000
|
4055 |
-
value: 81.147
|
4056 |
-
- type: recall_at_3
|
4057 |
-
value: 16.634
|
4058 |
-
- type: recall_at_5
|
4059 |
-
value: 20.7
|
4060 |
-
- task:
|
4061 |
-
type: Classification
|
4062 |
-
dataset:
|
4063 |
-
type: mteb/emotion
|
4064 |
-
name: MTEB EmotionClassification
|
4065 |
-
config: default
|
4066 |
-
split: test
|
4067 |
-
revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
|
4068 |
-
metrics:
|
4069 |
-
- type: accuracy
|
4070 |
-
value: 46.535000000000004
|
4071 |
-
- type: f1
|
4072 |
-
value: 42.53702746452163
|
4073 |
-
- task:
|
4074 |
-
type: Retrieval
|
4075 |
-
dataset:
|
4076 |
-
type: mteb/fever
|
4077 |
-
name: MTEB FEVER
|
4078 |
-
config: default
|
4079 |
-
split: test
|
4080 |
-
revision: bea83ef9e8fb933d90a2f1d5515737465d613e12
|
4081 |
-
metrics:
|
4082 |
-
- type: map_at_1
|
4083 |
-
value: 77.235
|
4084 |
-
- type: map_at_10
|
4085 |
-
value: 85.504
|
4086 |
-
- type: map_at_100
|
4087 |
-
value: 85.707
|
4088 |
-
- type: map_at_1000
|
4089 |
-
value: 85.718
|
4090 |
-
- type: map_at_3
|
4091 |
-
value: 84.425
|
4092 |
-
- type: map_at_5
|
4093 |
-
value: 85.13
|
4094 |
-
- type: mrr_at_1
|
4095 |
-
value: 83.363
|
4096 |
-
- type: mrr_at_10
|
4097 |
-
value: 89.916
|
4098 |
-
- type: mrr_at_100
|
4099 |
-
value: 89.955
|
4100 |
-
- type: mrr_at_1000
|
4101 |
-
value: 89.956
|
4102 |
-
- type: mrr_at_3
|
4103 |
-
value: 89.32600000000001
|
4104 |
-
- type: mrr_at_5
|
4105 |
-
value: 89.79
|
4106 |
-
- type: ndcg_at_1
|
4107 |
-
value: 83.363
|
4108 |
-
- type: ndcg_at_10
|
4109 |
-
value: 89.015
|
4110 |
-
- type: ndcg_at_100
|
4111 |
-
value: 89.649
|
4112 |
-
- type: ndcg_at_1000
|
4113 |
-
value: 89.825
|
4114 |
-
- type: ndcg_at_3
|
4115 |
-
value: 87.45100000000001
|
4116 |
-
- type: ndcg_at_5
|
4117 |
-
value: 88.39399999999999
|
4118 |
-
- type: precision_at_1
|
4119 |
-
value: 83.363
|
4120 |
-
- type: precision_at_10
|
4121 |
-
value: 10.659
|
4122 |
-
- type: precision_at_100
|
4123 |
-
value: 1.122
|
4124 |
-
- type: precision_at_1000
|
4125 |
-
value: 0.11499999999999999
|
4126 |
-
- type: precision_at_3
|
4127 |
-
value: 33.338
|
4128 |
-
- type: precision_at_5
|
4129 |
-
value: 20.671999999999997
|
4130 |
-
- type: recall_at_1
|
4131 |
-
value: 77.235
|
4132 |
-
- type: recall_at_10
|
4133 |
-
value: 95.389
|
4134 |
-
- type: recall_at_100
|
4135 |
-
value: 97.722
|
4136 |
-
- type: recall_at_1000
|
4137 |
-
value: 98.744
|
4138 |
-
- type: recall_at_3
|
4139 |
-
value: 91.19800000000001
|
4140 |
-
- type: recall_at_5
|
4141 |
-
value: 93.635
|
4142 |
-
- task:
|
4143 |
-
type: Retrieval
|
4144 |
-
dataset:
|
4145 |
-
type: mteb/fiqa
|
4146 |
-
name: MTEB FiQA2018
|
4147 |
-
config: default
|
4148 |
-
split: test
|
4149 |
-
revision: 27a168819829fe9bcd655c2df245fb19452e8e06
|
4150 |
-
metrics:
|
4151 |
-
- type: map_at_1
|
4152 |
-
value: 20.835
|
4153 |
-
- type: map_at_10
|
4154 |
-
value: 34.459
|
4155 |
-
- type: map_at_100
|
4156 |
-
value: 36.335
|
4157 |
-
- type: map_at_1000
|
4158 |
-
value: 36.518
|
4159 |
-
- type: map_at_3
|
4160 |
-
value: 30.581000000000003
|
4161 |
-
- type: map_at_5
|
4162 |
-
value: 32.859
|
4163 |
-
- type: mrr_at_1
|
4164 |
-
value: 40.894999999999996
|
4165 |
-
- type: mrr_at_10
|
4166 |
-
value: 50.491
|
4167 |
-
- type: mrr_at_100
|
4168 |
-
value: 51.243
|
4169 |
-
- type: mrr_at_1000
|
4170 |
-
value: 51.286
|
4171 |
-
- type: mrr_at_3
|
4172 |
-
value: 47.994
|
4173 |
-
- type: mrr_at_5
|
4174 |
-
value: 49.429
|
4175 |
-
- type: ndcg_at_1
|
4176 |
-
value: 40.894999999999996
|
4177 |
-
- type: ndcg_at_10
|
4178 |
-
value: 42.403
|
4179 |
-
- type: ndcg_at_100
|
4180 |
-
value: 48.954
|
4181 |
-
- type: ndcg_at_1000
|
4182 |
-
value: 51.961
|
4183 |
-
- type: ndcg_at_3
|
4184 |
-
value: 39.11
|
4185 |
-
- type: ndcg_at_5
|
4186 |
-
value: 40.152
|
4187 |
-
- type: precision_at_1
|
4188 |
-
value: 40.894999999999996
|
4189 |
-
- type: precision_at_10
|
4190 |
-
value: 11.466
|
4191 |
-
- type: precision_at_100
|
4192 |
-
value: 1.833
|
4193 |
-
- type: precision_at_1000
|
4194 |
-
value: 0.23700000000000002
|
4195 |
-
- type: precision_at_3
|
4196 |
-
value: 25.874000000000002
|
4197 |
-
- type: precision_at_5
|
4198 |
-
value: 19.012
|
4199 |
-
- type: recall_at_1
|
4200 |
-
value: 20.835
|
4201 |
-
- type: recall_at_10
|
4202 |
-
value: 49.535000000000004
|
4203 |
-
- type: recall_at_100
|
4204 |
-
value: 73.39099999999999
|
4205 |
-
- type: recall_at_1000
|
4206 |
-
value: 91.01599999999999
|
4207 |
-
- type: recall_at_3
|
4208 |
-
value: 36.379
|
4209 |
-
- type: recall_at_5
|
4210 |
-
value: 42.059999999999995
|
4211 |
-
- task:
|
4212 |
-
type: Retrieval
|
4213 |
-
dataset:
|
4214 |
-
type: mteb/hotpotqa
|
4215 |
-
name: MTEB HotpotQA
|
4216 |
-
config: default
|
4217 |
-
split: test
|
4218 |
-
revision: ab518f4d6fcca38d87c25209f94beba119d02014
|
4219 |
-
metrics:
|
4220 |
-
- type: map_at_1
|
4221 |
-
value: 40.945
|
4222 |
-
- type: map_at_10
|
4223 |
-
value: 65.376
|
4224 |
-
- type: map_at_100
|
4225 |
-
value: 66.278
|
4226 |
-
- type: map_at_1000
|
4227 |
-
value: 66.33
|
4228 |
-
- type: map_at_3
|
4229 |
-
value: 61.753
|
4230 |
-
- type: map_at_5
|
4231 |
-
value: 64.077
|
4232 |
-
- type: mrr_at_1
|
4233 |
-
value: 81.891
|
4234 |
-
- type: mrr_at_10
|
4235 |
-
value: 87.256
|
4236 |
-
- type: mrr_at_100
|
4237 |
-
value: 87.392
|
4238 |
-
- type: mrr_at_1000
|
4239 |
-
value: 87.395
|
4240 |
-
- type: mrr_at_3
|
4241 |
-
value: 86.442
|
4242 |
-
- type: mrr_at_5
|
4243 |
-
value: 86.991
|
4244 |
-
- type: ndcg_at_1
|
4245 |
-
value: 81.891
|
4246 |
-
- type: ndcg_at_10
|
4247 |
-
value: 73.654
|
4248 |
-
- type: ndcg_at_100
|
4249 |
-
value: 76.62299999999999
|
4250 |
-
- type: ndcg_at_1000
|
4251 |
-
value: 77.60000000000001
|
4252 |
-
- type: ndcg_at_3
|
4253 |
-
value: 68.71199999999999
|
4254 |
-
- type: ndcg_at_5
|
4255 |
-
value: 71.563
|
4256 |
-
- type: precision_at_1
|
4257 |
-
value: 81.891
|
4258 |
-
- type: precision_at_10
|
4259 |
-
value: 15.409
|
4260 |
-
- type: precision_at_100
|
4261 |
-
value: 1.77
|
4262 |
-
- type: precision_at_1000
|
4263 |
-
value: 0.19
|
4264 |
-
- type: precision_at_3
|
4265 |
-
value: 44.15
|
4266 |
-
- type: precision_at_5
|
4267 |
-
value: 28.732000000000003
|
4268 |
-
- type: recall_at_1
|
4269 |
-
value: 40.945
|
4270 |
-
- type: recall_at_10
|
4271 |
-
value: 77.04299999999999
|
4272 |
-
- type: recall_at_100
|
4273 |
-
value: 88.508
|
4274 |
-
- type: recall_at_1000
|
4275 |
-
value: 94.943
|
4276 |
-
- type: recall_at_3
|
4277 |
-
value: 66.226
|
4278 |
-
- type: recall_at_5
|
4279 |
-
value: 71.83
|
4280 |
-
- task:
|
4281 |
-
type: Classification
|
4282 |
-
dataset:
|
4283 |
-
type: mteb/imdb
|
4284 |
-
name: MTEB ImdbClassification
|
4285 |
-
config: default
|
4286 |
-
split: test
|
4287 |
-
revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
|
4288 |
-
metrics:
|
4289 |
-
- type: accuracy
|
4290 |
-
value: 74.08200000000001
|
4291 |
-
- type: ap
|
4292 |
-
value: 68.10929101713998
|
4293 |
-
- type: f1
|
4294 |
-
value: 73.98447117652009
|
4295 |
-
- task:
|
4296 |
-
type: Retrieval
|
4297 |
-
dataset:
|
4298 |
-
type: mteb/msmarco
|
4299 |
-
name: MTEB MSMARCO
|
4300 |
-
config: default
|
4301 |
-
split: dev
|
4302 |
-
revision: c5a29a104738b98a9e76336939199e264163d4a0
|
4303 |
-
metrics:
|
4304 |
-
- type: map_at_1
|
4305 |
-
value: 21.729000000000003
|
4306 |
-
- type: map_at_10
|
4307 |
-
value: 34.602
|
4308 |
-
- type: map_at_100
|
4309 |
-
value: 35.756
|
4310 |
-
- type: map_at_1000
|
4311 |
-
value: 35.803000000000004
|
4312 |
-
- type: map_at_3
|
4313 |
-
value: 30.619000000000003
|
4314 |
-
- type: map_at_5
|
4315 |
-
value: 32.914
|
4316 |
-
- type: mrr_at_1
|
4317 |
-
value: 22.364
|
4318 |
-
- type: mrr_at_10
|
4319 |
-
value: 35.183
|
4320 |
-
- type: mrr_at_100
|
4321 |
-
value: 36.287000000000006
|
4322 |
-
- type: mrr_at_1000
|
4323 |
-
value: 36.327999999999996
|
4324 |
-
- type: mrr_at_3
|
4325 |
-
value: 31.258000000000003
|
4326 |
-
- type: mrr_at_5
|
4327 |
-
value: 33.542
|
4328 |
-
- type: ndcg_at_1
|
4329 |
-
value: 22.364
|
4330 |
-
- type: ndcg_at_10
|
4331 |
-
value: 41.765
|
4332 |
-
- type: ndcg_at_100
|
4333 |
-
value: 47.293
|
4334 |
-
- type: ndcg_at_1000
|
4335 |
-
value: 48.457
|
4336 |
-
- type: ndcg_at_3
|
4337 |
-
value: 33.676
|
4338 |
-
- type: ndcg_at_5
|
4339 |
-
value: 37.783
|
4340 |
-
- type: precision_at_1
|
4341 |
-
value: 22.364
|
4342 |
-
- type: precision_at_10
|
4343 |
-
value: 6.662
|
4344 |
-
- type: precision_at_100
|
4345 |
-
value: 0.943
|
4346 |
-
- type: precision_at_1000
|
4347 |
-
value: 0.104
|
4348 |
-
- type: precision_at_3
|
4349 |
-
value: 14.435999999999998
|
4350 |
-
- type: precision_at_5
|
4351 |
-
value: 10.764999999999999
|
4352 |
-
- type: recall_at_1
|
4353 |
-
value: 21.729000000000003
|
4354 |
-
- type: recall_at_10
|
4355 |
-
value: 63.815999999999995
|
4356 |
-
- type: recall_at_100
|
4357 |
-
value: 89.265
|
4358 |
-
- type: recall_at_1000
|
4359 |
-
value: 98.149
|
4360 |
-
- type: recall_at_3
|
4361 |
-
value: 41.898
|
4362 |
-
- type: recall_at_5
|
4363 |
-
value: 51.76500000000001
|
4364 |
-
- task:
|
4365 |
-
type: Classification
|
4366 |
-
dataset:
|
4367 |
-
type: mteb/mtop_domain
|
4368 |
-
name: MTEB MTOPDomainClassification (en)
|
4369 |
-
config: en
|
4370 |
-
split: test
|
4371 |
-
revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
|
4372 |
-
metrics:
|
4373 |
-
- type: accuracy
|
4374 |
-
value: 92.73141814865483
|
4375 |
-
- type: f1
|
4376 |
-
value: 92.17518476408004
|
4377 |
-
- task:
|
4378 |
-
type: Classification
|
4379 |
-
dataset:
|
4380 |
-
type: mteb/mtop_intent
|
4381 |
-
name: MTEB MTOPIntentClassification (en)
|
4382 |
-
config: en
|
4383 |
-
split: test
|
4384 |
-
revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
|
4385 |
-
metrics:
|
4386 |
-
- type: accuracy
|
4387 |
-
value: 65.18011855905152
|
4388 |
-
- type: f1
|
4389 |
-
value: 46.70999638311856
|
4390 |
-
- task:
|
4391 |
-
type: Classification
|
4392 |
-
dataset:
|
4393 |
-
type: masakhane/masakhanews
|
4394 |
-
name: MTEB MasakhaNEWSClassification (eng)
|
4395 |
-
config: eng
|
4396 |
-
split: test
|
4397 |
-
revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60
|
4398 |
-
metrics:
|
4399 |
-
- type: accuracy
|
4400 |
-
value: 75.24261603375525
|
4401 |
-
- type: f1
|
4402 |
-
value: 74.07895183913367
|
4403 |
-
- task:
|
4404 |
-
type: Clustering
|
4405 |
-
dataset:
|
4406 |
-
type: masakhane/masakhanews
|
4407 |
-
name: MTEB MasakhaNEWSClusteringP2P (eng)
|
4408 |
-
config: eng
|
4409 |
-
split: test
|
4410 |
-
revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60
|
4411 |
-
metrics:
|
4412 |
-
- type: v_measure
|
4413 |
-
value: 28.43855875387446
|
4414 |
-
- task:
|
4415 |
-
type: Clustering
|
4416 |
-
dataset:
|
4417 |
-
type: masakhane/masakhanews
|
4418 |
-
name: MTEB MasakhaNEWSClusteringS2S (eng)
|
4419 |
-
config: eng
|
4420 |
-
split: test
|
4421 |
-
revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60
|
4422 |
-
metrics:
|
4423 |
-
- type: v_measure
|
4424 |
-
value: 29.05331990256969
|
4425 |
-
- task:
|
4426 |
-
type: Classification
|
4427 |
-
dataset:
|
4428 |
-
type: mteb/amazon_massive_intent
|
4429 |
-
name: MTEB MassiveIntentClassification (en)
|
4430 |
-
config: en
|
4431 |
-
split: test
|
4432 |
-
revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
|
4433 |
-
metrics:
|
4434 |
-
- type: accuracy
|
4435 |
-
value: 66.92333557498318
|
4436 |
-
- type: f1
|
4437 |
-
value: 64.29789389602692
|
4438 |
-
- task:
|
4439 |
-
type: Classification
|
4440 |
-
dataset:
|
4441 |
-
type: mteb/amazon_massive_scenario
|
4442 |
-
name: MTEB MassiveScenarioClassification (en)
|
4443 |
-
config: en
|
4444 |
-
split: test
|
4445 |
-
revision: 7d571f92784cd94a019292a1f45445077d0ef634
|
4446 |
-
metrics:
|
4447 |
-
- type: accuracy
|
4448 |
-
value: 72.74714189643578
|
4449 |
-
- type: f1
|
4450 |
-
value: 71.672585608315
|
4451 |
-
- task:
|
4452 |
-
type: Clustering
|
4453 |
-
dataset:
|
4454 |
-
type: mteb/medrxiv-clustering-p2p
|
4455 |
-
name: MTEB MedrxivClusteringP2P
|
4456 |
-
config: default
|
4457 |
-
split: test
|
4458 |
-
revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
|
4459 |
-
metrics:
|
4460 |
-
- type: v_measure
|
4461 |
-
value: 31.503564225501613
|
4462 |
-
- task:
|
4463 |
-
type: Clustering
|
4464 |
-
dataset:
|
4465 |
-
type: mteb/medrxiv-clustering-s2s
|
4466 |
-
name: MTEB MedrxivClusteringS2S
|
4467 |
-
config: default
|
4468 |
-
split: test
|
4469 |
-
revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
|
4470 |
-
metrics:
|
4471 |
-
- type: v_measure
|
4472 |
-
value: 28.410225127136457
|
4473 |
-
- task:
|
4474 |
-
type: Reranking
|
4475 |
-
dataset:
|
4476 |
-
type: mteb/mind_small
|
4477 |
-
name: MTEB MindSmallReranking
|
4478 |
-
config: default
|
4479 |
-
split: test
|
4480 |
-
revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
|
4481 |
-
metrics:
|
4482 |
-
- type: map
|
4483 |
-
value: 29.170019896091908
|
4484 |
-
- type: mrr
|
4485 |
-
value: 29.881276831500976
|
4486 |
-
- task:
|
4487 |
-
type: Retrieval
|
4488 |
-
dataset:
|
4489 |
-
type: mteb/nfcorpus
|
4490 |
-
name: MTEB NFCorpus
|
4491 |
-
config: default
|
4492 |
-
split: test
|
4493 |
-
revision: ec0fa4fe99da2ff19ca1214b7966684033a58814
|
4494 |
-
metrics:
|
4495 |
-
- type: map_at_1
|
4496 |
-
value: 6.544
|
4497 |
-
- type: map_at_10
|
4498 |
-
value: 14.116999999999999
|
4499 |
-
- type: map_at_100
|
4500 |
-
value: 17.522
|
4501 |
-
- type: map_at_1000
|
4502 |
-
value: 19
|
4503 |
-
- type: map_at_3
|
4504 |
-
value: 10.369
|
4505 |
-
- type: map_at_5
|
4506 |
-
value: 12.189
|
4507 |
-
- type: mrr_at_1
|
4508 |
-
value: 47.988
|
4509 |
-
- type: mrr_at_10
|
4510 |
-
value: 56.84
|
4511 |
-
- type: mrr_at_100
|
4512 |
-
value: 57.367000000000004
|
4513 |
-
- type: mrr_at_1000
|
4514 |
-
value: 57.403000000000006
|
4515 |
-
- type: mrr_at_3
|
4516 |
-
value: 54.592
|
4517 |
-
- type: mrr_at_5
|
4518 |
-
value: 56.233
|
4519 |
-
- type: ndcg_at_1
|
4520 |
-
value: 45.82
|
4521 |
-
- type: ndcg_at_10
|
4522 |
-
value: 36.767
|
4523 |
-
- type: ndcg_at_100
|
4524 |
-
value: 33.356
|
4525 |
-
- type: ndcg_at_1000
|
4526 |
-
value: 42.062
|
4527 |
-
- type: ndcg_at_3
|
4528 |
-
value: 42.15
|
4529 |
-
- type: ndcg_at_5
|
4530 |
-
value: 40.355000000000004
|
4531 |
-
- type: precision_at_1
|
4532 |
-
value: 47.988
|
4533 |
-
- type: precision_at_10
|
4534 |
-
value: 27.121000000000002
|
4535 |
-
- type: precision_at_100
|
4536 |
-
value: 8.455
|
4537 |
-
- type: precision_at_1000
|
4538 |
-
value: 2.103
|
4539 |
-
- type: precision_at_3
|
4540 |
-
value: 39.628
|
4541 |
-
- type: precision_at_5
|
4542 |
-
value: 35.356
|
4543 |
-
- type: recall_at_1
|
4544 |
-
value: 6.544
|
4545 |
-
- type: recall_at_10
|
4546 |
-
value: 17.928
|
4547 |
-
- type: recall_at_100
|
4548 |
-
value: 32.843
|
4549 |
-
- type: recall_at_1000
|
4550 |
-
value: 65.752
|
4551 |
-
- type: recall_at_3
|
4552 |
-
value: 11.297
|
4553 |
-
- type: recall_at_5
|
4554 |
-
value: 14.357000000000001
|
4555 |
-
- task:
|
4556 |
-
type: Retrieval
|
4557 |
-
dataset:
|
4558 |
-
type: mteb/nq
|
4559 |
-
name: MTEB NQ
|
4560 |
-
config: default
|
4561 |
-
split: test
|
4562 |
-
revision: b774495ed302d8c44a3a7ea25c90dbce03968f31
|
4563 |
-
metrics:
|
4564 |
-
- type: map_at_1
|
4565 |
-
value: 39.262
|
4566 |
-
- type: map_at_10
|
4567 |
-
value: 55.095000000000006
|
4568 |
-
- type: map_at_100
|
4569 |
-
value: 55.93900000000001
|
4570 |
-
- type: map_at_1000
|
4571 |
-
value: 55.955999999999996
|
4572 |
-
- type: map_at_3
|
4573 |
-
value: 50.93
|
4574 |
-
- type: map_at_5
|
4575 |
-
value: 53.491
|
4576 |
-
- type: mrr_at_1
|
4577 |
-
value: 43.598
|
4578 |
-
- type: mrr_at_10
|
4579 |
-
value: 57.379999999999995
|
4580 |
-
- type: mrr_at_100
|
4581 |
-
value: 57.940999999999995
|
4582 |
-
- type: mrr_at_1000
|
4583 |
-
value: 57.952000000000005
|
4584 |
-
- type: mrr_at_3
|
4585 |
-
value: 53.998000000000005
|
4586 |
-
- type: mrr_at_5
|
4587 |
-
value: 56.128
|
4588 |
-
- type: ndcg_at_1
|
4589 |
-
value: 43.598
|
4590 |
-
- type: ndcg_at_10
|
4591 |
-
value: 62.427
|
4592 |
-
- type: ndcg_at_100
|
4593 |
-
value: 65.759
|
4594 |
-
- type: ndcg_at_1000
|
4595 |
-
value: 66.133
|
4596 |
-
- type: ndcg_at_3
|
4597 |
-
value: 54.745999999999995
|
4598 |
-
- type: ndcg_at_5
|
4599 |
-
value: 58.975
|
4600 |
-
- type: precision_at_1
|
4601 |
-
value: 43.598
|
4602 |
-
- type: precision_at_10
|
4603 |
-
value: 9.789
|
4604 |
-
- type: precision_at_100
|
4605 |
-
value: 1.171
|
4606 |
-
- type: precision_at_1000
|
4607 |
-
value: 0.121
|
4608 |
-
- type: precision_at_3
|
4609 |
-
value: 24.295
|
4610 |
-
- type: precision_at_5
|
4611 |
-
value: 17.028
|
4612 |
-
- type: recall_at_1
|
4613 |
-
value: 39.262
|
4614 |
-
- type: recall_at_10
|
4615 |
-
value: 82.317
|
4616 |
-
- type: recall_at_100
|
4617 |
-
value: 96.391
|
4618 |
-
- type: recall_at_1000
|
4619 |
-
value: 99.116
|
4620 |
-
- type: recall_at_3
|
4621 |
-
value: 62.621
|
4622 |
-
- type: recall_at_5
|
4623 |
-
value: 72.357
|
4624 |
-
- task:
|
4625 |
-
type: Classification
|
4626 |
-
dataset:
|
4627 |
-
type: ag_news
|
4628 |
-
name: MTEB NewsClassification
|
4629 |
-
config: default
|
4630 |
-
split: test
|
4631 |
-
revision: eb185aade064a813bc0b7f42de02595523103ca4
|
4632 |
-
metrics:
|
4633 |
-
- type: accuracy
|
4634 |
-
value: 78.17500000000001
|
4635 |
-
- type: f1
|
4636 |
-
value: 78.01940892857273
|
4637 |
-
- task:
|
4638 |
-
type: PairClassification
|
4639 |
-
dataset:
|
4640 |
-
type: GEM/opusparcus
|
4641 |
-
name: MTEB OpusparcusPC (en)
|
4642 |
-
config: en
|
4643 |
-
split: test
|
4644 |
-
revision: 9e9b1f8ef51616073f47f306f7f47dd91663f86a
|
4645 |
-
metrics:
|
4646 |
-
- type: cos_sim_accuracy
|
4647 |
-
value: 99.89816700610999
|
4648 |
-
- type: cos_sim_ap
|
4649 |
-
value: 100
|
4650 |
-
- type: cos_sim_f1
|
4651 |
-
value: 99.9490575649516
|
4652 |
-
- type: cos_sim_precision
|
4653 |
-
value: 100
|
4654 |
-
- type: cos_sim_recall
|
4655 |
-
value: 99.89816700610999
|
4656 |
-
- type: dot_accuracy
|
4657 |
-
value: 99.89816700610999
|
4658 |
-
- type: dot_ap
|
4659 |
-
value: 100
|
4660 |
-
- type: dot_f1
|
4661 |
-
value: 99.9490575649516
|
4662 |
-
- type: dot_precision
|
4663 |
-
value: 100
|
4664 |
-
- type: dot_recall
|
4665 |
-
value: 99.89816700610999
|
4666 |
-
- type: euclidean_accuracy
|
4667 |
-
value: 99.89816700610999
|
4668 |
-
- type: euclidean_ap
|
4669 |
-
value: 100
|
4670 |
-
- type: euclidean_f1
|
4671 |
-
value: 99.9490575649516
|
4672 |
-
- type: euclidean_precision
|
4673 |
-
value: 100
|
4674 |
-
- type: euclidean_recall
|
4675 |
-
value: 99.89816700610999
|
4676 |
-
- type: manhattan_accuracy
|
4677 |
-
value: 99.89816700610999
|
4678 |
-
- type: manhattan_ap
|
4679 |
-
value: 100
|
4680 |
-
- type: manhattan_f1
|
4681 |
-
value: 99.9490575649516
|
4682 |
-
- type: manhattan_precision
|
4683 |
-
value: 100
|
4684 |
-
- type: manhattan_recall
|
4685 |
-
value: 99.89816700610999
|
4686 |
-
- type: max_accuracy
|
4687 |
-
value: 99.89816700610999
|
4688 |
-
- type: max_ap
|
4689 |
-
value: 100
|
4690 |
-
- type: max_f1
|
4691 |
-
value: 99.9490575649516
|
4692 |
-
- task:
|
4693 |
-
type: PairClassification
|
4694 |
-
dataset:
|
4695 |
-
type: paws-x
|
4696 |
-
name: MTEB PawsX (en)
|
4697 |
-
config: en
|
4698 |
-
split: test
|
4699 |
-
revision: 8a04d940a42cd40658986fdd8e3da561533a3646
|
4700 |
-
metrics:
|
4701 |
-
- type: cos_sim_accuracy
|
4702 |
-
value: 61
|
4703 |
-
- type: cos_sim_ap
|
4704 |
-
value: 59.630757252602464
|
4705 |
-
- type: cos_sim_f1
|
4706 |
-
value: 62.37521514629949
|
4707 |
-
- type: cos_sim_precision
|
4708 |
-
value: 45.34534534534534
|
4709 |
-
- type: cos_sim_recall
|
4710 |
-
value: 99.88974641675854
|
4711 |
-
- type: dot_accuracy
|
4712 |
-
value: 61
|
4713 |
-
- type: dot_ap
|
4714 |
-
value: 59.631527308059006
|
4715 |
-
- type: dot_f1
|
4716 |
-
value: 62.37521514629949
|
4717 |
-
- type: dot_precision
|
4718 |
-
value: 45.34534534534534
|
4719 |
-
- type: dot_recall
|
4720 |
-
value: 99.88974641675854
|
4721 |
-
- type: euclidean_accuracy
|
4722 |
-
value: 61
|
4723 |
-
- type: euclidean_ap
|
4724 |
-
value: 59.630757252602464
|
4725 |
-
- type: euclidean_f1
|
4726 |
-
value: 62.37521514629949
|
4727 |
-
- type: euclidean_precision
|
4728 |
-
value: 45.34534534534534
|
4729 |
-
- type: euclidean_recall
|
4730 |
-
value: 99.88974641675854
|
4731 |
-
- type: manhattan_accuracy
|
4732 |
-
value: 60.9
|
4733 |
-
- type: manhattan_ap
|
4734 |
-
value: 59.613947780462254
|
4735 |
-
- type: manhattan_f1
|
4736 |
-
value: 62.37521514629949
|
4737 |
-
- type: manhattan_precision
|
4738 |
-
value: 45.34534534534534
|
4739 |
-
- type: manhattan_recall
|
4740 |
-
value: 99.88974641675854
|
4741 |
-
- type: max_accuracy
|
4742 |
-
value: 61
|
4743 |
-
- type: max_ap
|
4744 |
-
value: 59.631527308059006
|
4745 |
-
- type: max_f1
|
4746 |
-
value: 62.37521514629949
|
4747 |
-
- task:
|
4748 |
-
type: Retrieval
|
4749 |
-
dataset:
|
4750 |
-
type: mteb/quora
|
4751 |
-
name: MTEB QuoraRetrieval
|
4752 |
-
config: default
|
4753 |
-
split: test
|
4754 |
-
revision: e4e08e0b7dbe3c8700f0daef558ff32256715259
|
4755 |
-
metrics:
|
4756 |
-
- type: map_at_1
|
4757 |
-
value: 69.963
|
4758 |
-
- type: map_at_10
|
4759 |
-
value: 83.59400000000001
|
4760 |
-
- type: map_at_100
|
4761 |
-
value: 84.236
|
4762 |
-
- type: map_at_1000
|
4763 |
-
value: 84.255
|
4764 |
-
- type: map_at_3
|
4765 |
-
value: 80.69800000000001
|
4766 |
-
- type: map_at_5
|
4767 |
-
value: 82.568
|
4768 |
-
- type: mrr_at_1
|
4769 |
-
value: 80.58999999999999
|
4770 |
-
- type: mrr_at_10
|
4771 |
-
value: 86.78200000000001
|
4772 |
-
- type: mrr_at_100
|
4773 |
-
value: 86.89099999999999
|
4774 |
-
- type: mrr_at_1000
|
4775 |
-
value: 86.893
|
4776 |
-
- type: mrr_at_3
|
4777 |
-
value: 85.757
|
4778 |
-
- type: mrr_at_5
|
4779 |
-
value: 86.507
|
4780 |
-
- type: ndcg_at_1
|
4781 |
-
value: 80.60000000000001
|
4782 |
-
- type: ndcg_at_10
|
4783 |
-
value: 87.41799999999999
|
4784 |
-
- type: ndcg_at_100
|
4785 |
-
value: 88.723
|
4786 |
-
- type: ndcg_at_1000
|
4787 |
-
value: 88.875
|
4788 |
-
- type: ndcg_at_3
|
4789 |
-
value: 84.565
|
4790 |
-
- type: ndcg_at_5
|
4791 |
-
value: 86.236
|
4792 |
-
- type: precision_at_1
|
4793 |
-
value: 80.60000000000001
|
4794 |
-
- type: precision_at_10
|
4795 |
-
value: 13.239
|
4796 |
-
- type: precision_at_100
|
4797 |
-
value: 1.5150000000000001
|
4798 |
-
- type: precision_at_1000
|
4799 |
-
value: 0.156
|
4800 |
-
- type: precision_at_3
|
4801 |
-
value: 36.947
|
4802 |
-
- type: precision_at_5
|
4803 |
-
value: 24.354
|
4804 |
-
- type: recall_at_1
|
4805 |
-
value: 69.963
|
4806 |
-
- type: recall_at_10
|
4807 |
-
value: 94.553
|
4808 |
-
- type: recall_at_100
|
4809 |
-
value: 99.104
|
4810 |
-
- type: recall_at_1000
|
4811 |
-
value: 99.872
|
4812 |
-
- type: recall_at_3
|
4813 |
-
value: 86.317
|
4814 |
-
- type: recall_at_5
|
4815 |
-
value: 91.023
|
4816 |
-
- task:
|
4817 |
-
type: Clustering
|
4818 |
-
dataset:
|
4819 |
-
type: mteb/reddit-clustering
|
4820 |
-
name: MTEB RedditClustering
|
4821 |
-
config: default
|
4822 |
-
split: test
|
4823 |
-
revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
|
4824 |
-
metrics:
|
4825 |
-
- type: v_measure
|
4826 |
-
value: 47.52890410998761
|
4827 |
-
- task:
|
4828 |
-
type: Clustering
|
4829 |
-
dataset:
|
4830 |
-
type: mteb/reddit-clustering-p2p
|
4831 |
-
name: MTEB RedditClusteringP2P
|
4832 |
-
config: default
|
4833 |
-
split: test
|
4834 |
-
revision: 385e3cb46b4cfa89021f56c4380204149d0efe33
|
4835 |
-
metrics:
|
4836 |
-
- type: v_measure
|
4837 |
-
value: 62.760692287940486
|
4838 |
-
- task:
|
4839 |
-
type: Retrieval
|
4840 |
-
dataset:
|
4841 |
-
type: mteb/scidocs
|
4842 |
-
name: MTEB SCIDOCS
|
4843 |
-
config: default
|
4844 |
-
split: test
|
4845 |
-
revision: f8c2fcf00f625baaa80f62ec5bd9e1fff3b8ae88
|
4846 |
-
metrics:
|
4847 |
-
- type: map_at_1
|
4848 |
-
value: 5.093
|
4849 |
-
- type: map_at_10
|
4850 |
-
value: 12.695
|
4851 |
-
- type: map_at_100
|
4852 |
-
value: 14.824000000000002
|
4853 |
-
- type: map_at_1000
|
4854 |
-
value: 15.123000000000001
|
4855 |
-
- type: map_at_3
|
4856 |
-
value: 8.968
|
4857 |
-
- type: map_at_5
|
4858 |
-
value: 10.828
|
4859 |
-
- type: mrr_at_1
|
4860 |
-
value: 25.1
|
4861 |
-
- type: mrr_at_10
|
4862 |
-
value: 35.894999999999996
|
4863 |
-
- type: mrr_at_100
|
4864 |
-
value: 36.966
|
4865 |
-
- type: mrr_at_1000
|
4866 |
-
value: 37.019999999999996
|
4867 |
-
- type: mrr_at_3
|
4868 |
-
value: 32.467
|
4869 |
-
- type: mrr_at_5
|
4870 |
-
value: 34.416999999999994
|
4871 |
-
- type: ndcg_at_1
|
4872 |
-
value: 25.1
|
4873 |
-
- type: ndcg_at_10
|
4874 |
-
value: 21.096999999999998
|
4875 |
-
- type: ndcg_at_100
|
4876 |
-
value: 29.202
|
4877 |
-
- type: ndcg_at_1000
|
4878 |
-
value: 34.541
|
4879 |
-
- type: ndcg_at_3
|
4880 |
-
value: 19.875
|
4881 |
-
- type: ndcg_at_5
|
4882 |
-
value: 17.497
|
4883 |
-
- type: precision_at_1
|
4884 |
-
value: 25.1
|
4885 |
-
- type: precision_at_10
|
4886 |
-
value: 10.9
|
4887 |
-
- type: precision_at_100
|
4888 |
-
value: 2.255
|
4889 |
-
- type: precision_at_1000
|
4890 |
-
value: 0.35400000000000004
|
4891 |
-
- type: precision_at_3
|
4892 |
-
value: 18.367
|
4893 |
-
- type: precision_at_5
|
4894 |
-
value: 15.299999999999999
|
4895 |
-
- type: recall_at_1
|
4896 |
-
value: 5.093
|
4897 |
-
- type: recall_at_10
|
4898 |
-
value: 22.092
|
4899 |
-
- type: recall_at_100
|
4900 |
-
value: 45.778
|
4901 |
-
- type: recall_at_1000
|
4902 |
-
value: 71.985
|
4903 |
-
- type: recall_at_3
|
4904 |
-
value: 11.167
|
4905 |
-
- type: recall_at_5
|
4906 |
-
value: 15.501999999999999
|
4907 |
-
- task:
|
4908 |
-
type: STS
|
4909 |
-
dataset:
|
4910 |
-
type: mteb/sickr-sts
|
4911 |
-
name: MTEB SICK-R
|
4912 |
-
config: default
|
4913 |
-
split: test
|
4914 |
-
revision: 20a6d6f312dd54037fe07a32d58e5e168867909d
|
4915 |
-
metrics:
|
4916 |
-
- type: cos_sim_pearson
|
4917 |
-
value: 74.04386981759481
|
4918 |
-
- type: cos_sim_spearman
|
4919 |
-
value: 69.12484963763646
|
4920 |
-
- type: euclidean_pearson
|
4921 |
-
value: 71.49384353291062
|
4922 |
-
- type: euclidean_spearman
|
4923 |
-
value: 69.12484548317074
|
4924 |
-
- type: manhattan_pearson
|
4925 |
-
value: 71.49828173987272
|
4926 |
-
- type: manhattan_spearman
|
4927 |
-
value: 69.08350274367014
|
4928 |
-
- task:
|
4929 |
-
type: STS
|
4930 |
-
dataset:
|
4931 |
-
type: mteb/sts12-sts
|
4932 |
-
name: MTEB STS12
|
4933 |
-
config: default
|
4934 |
-
split: test
|
4935 |
-
revision: a0d554a64d88156834ff5ae9920b964011b16384
|
4936 |
-
metrics:
|
4937 |
-
- type: cos_sim_pearson
|
4938 |
-
value: 66.95372527615659
|
4939 |
-
- type: cos_sim_spearman
|
4940 |
-
value: 66.96821894433991
|
4941 |
-
- type: euclidean_pearson
|
4942 |
-
value: 64.675348002074
|
4943 |
-
- type: euclidean_spearman
|
4944 |
-
value: 66.96821894433991
|
4945 |
-
- type: manhattan_pearson
|
4946 |
-
value: 64.5965887073831
|
4947 |
-
- type: manhattan_spearman
|
4948 |
-
value: 66.88569076794741
|
4949 |
-
- task:
|
4950 |
-
type: STS
|
4951 |
-
dataset:
|
4952 |
-
type: mteb/sts13-sts
|
4953 |
-
name: MTEB STS13
|
4954 |
-
config: default
|
4955 |
-
split: test
|
4956 |
-
revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
|
4957 |
-
metrics:
|
4958 |
-
- type: cos_sim_pearson
|
4959 |
-
value: 77.34698437961983
|
4960 |
-
- type: cos_sim_spearman
|
4961 |
-
value: 79.1153001117325
|
4962 |
-
- type: euclidean_pearson
|
4963 |
-
value: 78.53562874696966
|
4964 |
-
- type: euclidean_spearman
|
4965 |
-
value: 79.11530018205724
|
4966 |
-
- type: manhattan_pearson
|
4967 |
-
value: 78.46484988944093
|
4968 |
-
- type: manhattan_spearman
|
4969 |
-
value: 79.01416027493104
|
4970 |
-
- task:
|
4971 |
-
type: STS
|
4972 |
-
dataset:
|
4973 |
-
type: mteb/sts14-sts
|
4974 |
-
name: MTEB STS14
|
4975 |
-
config: default
|
4976 |
-
split: test
|
4977 |
-
revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
|
4978 |
-
metrics:
|
4979 |
-
- type: cos_sim_pearson
|
4980 |
-
value: 68.81220371935373
|
4981 |
-
- type: cos_sim_spearman
|
4982 |
-
value: 68.50538405089604
|
4983 |
-
- type: euclidean_pearson
|
4984 |
-
value: 68.69204272683749
|
4985 |
-
- type: euclidean_spearman
|
4986 |
-
value: 68.50534223912419
|
4987 |
-
- type: manhattan_pearson
|
4988 |
-
value: 68.67300120149523
|
4989 |
-
- type: manhattan_spearman
|
4990 |
-
value: 68.45404301623115
|
4991 |
-
- task:
|
4992 |
-
type: STS
|
4993 |
-
dataset:
|
4994 |
-
type: mteb/sts15-sts
|
4995 |
-
name: MTEB STS15
|
4996 |
-
config: default
|
4997 |
-
split: test
|
4998 |
-
revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
|
4999 |
-
metrics:
|
5000 |
-
- type: cos_sim_pearson
|
5001 |
-
value: 78.2464678879813
|
5002 |
-
- type: cos_sim_spearman
|
5003 |
-
value: 79.92003940566667
|
5004 |
-
- type: euclidean_pearson
|
5005 |
-
value: 79.8080778793964
|
5006 |
-
- type: euclidean_spearman
|
5007 |
-
value: 79.92003940566667
|
5008 |
-
- type: manhattan_pearson
|
5009 |
-
value: 79.80153621444681
|
5010 |
-
- type: manhattan_spearman
|
5011 |
-
value: 79.91293261418134
|
5012 |
-
- task:
|
5013 |
-
type: STS
|
5014 |
-
dataset:
|
5015 |
-
type: mteb/sts16-sts
|
5016 |
-
name: MTEB STS16
|
5017 |
-
config: default
|
5018 |
-
split: test
|
5019 |
-
revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
|
5020 |
-
metrics:
|
5021 |
-
- type: cos_sim_pearson
|
5022 |
-
value: 76.31179207708662
|
5023 |
-
- type: cos_sim_spearman
|
5024 |
-
value: 78.65597349856115
|
5025 |
-
- type: euclidean_pearson
|
5026 |
-
value: 78.76937027472678
|
5027 |
-
- type: euclidean_spearman
|
5028 |
-
value: 78.65597349856115
|
5029 |
-
- type: manhattan_pearson
|
5030 |
-
value: 78.77129513300605
|
5031 |
-
- type: manhattan_spearman
|
5032 |
-
value: 78.62640467680775
|
5033 |
-
- task:
|
5034 |
-
type: STS
|
5035 |
-
dataset:
|
5036 |
-
type: mteb/sts17-crosslingual-sts
|
5037 |
-
name: MTEB STS17 (en-en)
|
5038 |
-
config: en-en
|
5039 |
-
split: test
|
5040 |
-
revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
|
5041 |
-
metrics:
|
5042 |
-
- type: cos_sim_pearson
|
5043 |
-
value: 79.43158429552561
|
5044 |
-
- type: cos_sim_spearman
|
5045 |
-
value: 81.46108646565362
|
5046 |
-
- type: euclidean_pearson
|
5047 |
-
value: 81.47071791452292
|
5048 |
-
- type: euclidean_spearman
|
5049 |
-
value: 81.46108646565362
|
5050 |
-
- type: manhattan_pearson
|
5051 |
-
value: 81.56920643846031
|
5052 |
-
- type: manhattan_spearman
|
5053 |
-
value: 81.42226241399516
|
5054 |
-
- task:
|
5055 |
-
type: STS
|
5056 |
-
dataset:
|
5057 |
-
type: mteb/sts22-crosslingual-sts
|
5058 |
-
name: MTEB STS22 (en)
|
5059 |
-
config: en
|
5060 |
-
split: test
|
5061 |
-
revision: eea2b4fe26a775864c896887d910b76a8098ad3f
|
5062 |
-
metrics:
|
5063 |
-
- type: cos_sim_pearson
|
5064 |
-
value: 66.89546474141514
|
5065 |
-
- type: cos_sim_spearman
|
5066 |
-
value: 65.8393752170531
|
5067 |
-
- type: euclidean_pearson
|
5068 |
-
value: 67.2580522762307
|
5069 |
-
- type: euclidean_spearman
|
5070 |
-
value: 65.8393752170531
|
5071 |
-
- type: manhattan_pearson
|
5072 |
-
value: 67.45157729300522
|
5073 |
-
- type: manhattan_spearman
|
5074 |
-
value: 66.19470854403802
|
5075 |
-
- task:
|
5076 |
-
type: STS
|
5077 |
-
dataset:
|
5078 |
-
type: mteb/stsbenchmark-sts
|
5079 |
-
name: MTEB STSBenchmark
|
5080 |
-
config: default
|
5081 |
-
split: test
|
5082 |
-
revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
|
5083 |
-
metrics:
|
5084 |
-
- type: cos_sim_pearson
|
5085 |
-
value: 71.39566306334434
|
5086 |
-
- type: cos_sim_spearman
|
5087 |
-
value: 74.0981396086974
|
5088 |
-
- type: euclidean_pearson
|
5089 |
-
value: 73.7834496259745
|
5090 |
-
- type: euclidean_spearman
|
5091 |
-
value: 74.09803741302046
|
5092 |
-
- type: manhattan_pearson
|
5093 |
-
value: 73.79958138780945
|
5094 |
-
- type: manhattan_spearman
|
5095 |
-
value: 74.09894837555905
|
5096 |
-
- task:
|
5097 |
-
type: STS
|
5098 |
-
dataset:
|
5099 |
-
type: PhilipMay/stsb_multi_mt
|
5100 |
-
name: MTEB STSBenchmarkMultilingualSTS (en)
|
5101 |
-
config: en
|
5102 |
-
split: test
|
5103 |
-
revision: 93d57ef91790589e3ce9c365164337a8a78b7632
|
5104 |
-
metrics:
|
5105 |
-
- type: cos_sim_pearson
|
5106 |
-
value: 71.39566311006806
|
5107 |
-
- type: cos_sim_spearman
|
5108 |
-
value: 74.0981396086974
|
5109 |
-
- type: euclidean_pearson
|
5110 |
-
value: 73.78344970897099
|
5111 |
-
- type: euclidean_spearman
|
5112 |
-
value: 74.09803741302046
|
5113 |
-
- type: manhattan_pearson
|
5114 |
-
value: 73.79958147136705
|
5115 |
-
- type: manhattan_spearman
|
5116 |
-
value: 74.09894837555905
|
5117 |
-
- task:
|
5118 |
-
type: Reranking
|
5119 |
-
dataset:
|
5120 |
-
type: mteb/scidocs-reranking
|
5121 |
-
name: MTEB SciDocsRR
|
5122 |
-
config: default
|
5123 |
-
split: test
|
5124 |
-
revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
|
5125 |
-
metrics:
|
5126 |
-
- type: map
|
5127 |
-
value: 80.81059564334683
|
5128 |
-
- type: mrr
|
5129 |
-
value: 94.62696617108381
|
5130 |
-
- task:
|
5131 |
-
type: Retrieval
|
5132 |
-
dataset:
|
5133 |
-
type: mteb/scifact
|
5134 |
-
name: MTEB SciFact
|
5135 |
-
config: default
|
5136 |
-
split: test
|
5137 |
-
revision: 0228b52cf27578f30900b9e5271d331663a030d7
|
5138 |
-
metrics:
|
5139 |
-
- type: map_at_1
|
5140 |
-
value: 57.760999999999996
|
5141 |
-
- type: map_at_10
|
5142 |
-
value: 68.614
|
5143 |
-
- type: map_at_100
|
5144 |
-
value: 69.109
|
5145 |
-
- type: map_at_1000
|
5146 |
-
value: 69.134
|
5147 |
-
- type: map_at_3
|
5148 |
-
value: 65.735
|
5149 |
-
- type: map_at_5
|
5150 |
-
value: 67.42099999999999
|
5151 |
-
- type: mrr_at_1
|
5152 |
-
value: 60.667
|
5153 |
-
- type: mrr_at_10
|
5154 |
-
value: 69.94200000000001
|
5155 |
-
- type: mrr_at_100
|
5156 |
-
value: 70.254
|
5157 |
-
- type: mrr_at_1000
|
5158 |
-
value: 70.28
|
5159 |
-
- type: mrr_at_3
|
5160 |
-
value: 67.72200000000001
|
5161 |
-
- type: mrr_at_5
|
5162 |
-
value: 69.18900000000001
|
5163 |
-
- type: ndcg_at_1
|
5164 |
-
value: 60.667
|
5165 |
-
- type: ndcg_at_10
|
5166 |
-
value: 73.548
|
5167 |
-
- type: ndcg_at_100
|
5168 |
-
value: 75.381
|
5169 |
-
- type: ndcg_at_1000
|
5170 |
-
value: 75.991
|
5171 |
-
- type: ndcg_at_3
|
5172 |
-
value: 68.685
|
5173 |
-
- type: ndcg_at_5
|
5174 |
-
value: 71.26
|
5175 |
-
- type: precision_at_1
|
5176 |
-
value: 60.667
|
5177 |
-
- type: precision_at_10
|
5178 |
-
value: 9.833
|
5179 |
-
- type: precision_at_100
|
5180 |
-
value: 1.08
|
5181 |
-
- type: precision_at_1000
|
5182 |
-
value: 0.11299999999999999
|
5183 |
-
- type: precision_at_3
|
5184 |
-
value: 26.889000000000003
|
5185 |
-
- type: precision_at_5
|
5186 |
-
value: 17.8
|
5187 |
-
- type: recall_at_1
|
5188 |
-
value: 57.760999999999996
|
5189 |
-
- type: recall_at_10
|
5190 |
-
value: 87.13300000000001
|
5191 |
-
- type: recall_at_100
|
5192 |
-
value: 95
|
5193 |
-
- type: recall_at_1000
|
5194 |
-
value: 99.667
|
5195 |
-
- type: recall_at_3
|
5196 |
-
value: 74.211
|
5197 |
-
- type: recall_at_5
|
5198 |
-
value: 80.63900000000001
|
5199 |
-
- task:
|
5200 |
-
type: PairClassification
|
5201 |
-
dataset:
|
5202 |
-
type: mteb/sprintduplicatequestions-pairclassification
|
5203 |
-
name: MTEB SprintDuplicateQuestions
|
5204 |
-
config: default
|
5205 |
-
split: test
|
5206 |
-
revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
|
5207 |
-
metrics:
|
5208 |
-
- type: cos_sim_accuracy
|
5209 |
-
value: 99.81881188118813
|
5210 |
-
- type: cos_sim_ap
|
5211 |
-
value: 95.21196473745837
|
5212 |
-
- type: cos_sim_f1
|
5213 |
-
value: 90.69767441860465
|
5214 |
-
- type: cos_sim_precision
|
5215 |
-
value: 91.71779141104295
|
5216 |
-
- type: cos_sim_recall
|
5217 |
-
value: 89.7
|
5218 |
-
- type: dot_accuracy
|
5219 |
-
value: 99.81881188118813
|
5220 |
-
- type: dot_ap
|
5221 |
-
value: 95.21196473745837
|
5222 |
-
- type: dot_f1
|
5223 |
-
value: 90.69767441860465
|
5224 |
-
- type: dot_precision
|
5225 |
-
value: 91.71779141104295
|
5226 |
-
- type: dot_recall
|
5227 |
-
value: 89.7
|
5228 |
-
- type: euclidean_accuracy
|
5229 |
-
value: 99.81881188118813
|
5230 |
-
- type: euclidean_ap
|
5231 |
-
value: 95.21196473745839
|
5232 |
-
- type: euclidean_f1
|
5233 |
-
value: 90.69767441860465
|
5234 |
-
- type: euclidean_precision
|
5235 |
-
value: 91.71779141104295
|
5236 |
-
- type: euclidean_recall
|
5237 |
-
value: 89.7
|
5238 |
-
- type: manhattan_accuracy
|
5239 |
-
value: 99.81287128712871
|
5240 |
-
- type: manhattan_ap
|
5241 |
-
value: 95.16667174835017
|
5242 |
-
- type: manhattan_f1
|
5243 |
-
value: 90.41095890410959
|
5244 |
-
- type: manhattan_precision
|
5245 |
-
value: 91.7610710607621
|
5246 |
-
- type: manhattan_recall
|
5247 |
-
value: 89.1
|
5248 |
-
- type: max_accuracy
|
5249 |
-
value: 99.81881188118813
|
5250 |
-
- type: max_ap
|
5251 |
-
value: 95.21196473745839
|
5252 |
-
- type: max_f1
|
5253 |
-
value: 90.69767441860465
|
5254 |
-
- task:
|
5255 |
-
type: Clustering
|
5256 |
-
dataset:
|
5257 |
-
type: mteb/stackexchange-clustering
|
5258 |
-
name: MTEB StackExchangeClustering
|
5259 |
-
config: default
|
5260 |
-
split: test
|
5261 |
-
revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
|
5262 |
-
metrics:
|
5263 |
-
- type: v_measure
|
5264 |
-
value: 59.54942204515638
|
5265 |
-
- task:
|
5266 |
-
type: Clustering
|
5267 |
-
dataset:
|
5268 |
-
type: mteb/stackexchange-clustering-p2p
|
5269 |
-
name: MTEB StackExchangeClusteringP2P
|
5270 |
-
config: default
|
5271 |
-
split: test
|
5272 |
-
revision: 815ca46b2622cec33ccafc3735d572c266efdb44
|
5273 |
-
metrics:
|
5274 |
-
- type: v_measure
|
5275 |
-
value: 39.42892282672948
|
5276 |
-
- task:
|
5277 |
-
type: Reranking
|
5278 |
-
dataset:
|
5279 |
-
type: mteb/stackoverflowdupquestions-reranking
|
5280 |
-
name: MTEB StackOverflowDupQuestions
|
5281 |
-
config: default
|
5282 |
-
split: test
|
5283 |
-
revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
|
5284 |
-
metrics:
|
5285 |
-
- type: map
|
5286 |
-
value: 51.189033075914324
|
5287 |
-
- type: mrr
|
5288 |
-
value: 51.97014790764791
|
5289 |
-
- task:
|
5290 |
-
type: Summarization
|
5291 |
-
dataset:
|
5292 |
-
type: mteb/summeval
|
5293 |
-
name: MTEB SummEval
|
5294 |
-
config: default
|
5295 |
-
split: test
|
5296 |
-
revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
|
5297 |
-
metrics:
|
5298 |
-
- type: cos_sim_pearson
|
5299 |
-
value: 30.09466569775977
|
5300 |
-
- type: cos_sim_spearman
|
5301 |
-
value: 30.31058660775912
|
5302 |
-
- type: dot_pearson
|
5303 |
-
value: 30.09466438861689
|
5304 |
-
- type: dot_spearman
|
5305 |
-
value: 30.31058660775912
|
5306 |
-
- task:
|
5307 |
-
type: Retrieval
|
5308 |
-
dataset:
|
5309 |
-
type: mteb/trec-covid
|
5310 |
-
name: MTEB TRECCOVID
|
5311 |
-
config: default
|
5312 |
-
split: test
|
5313 |
-
revision: bb9466bac8153a0349341eb1b22e06409e78ef4e
|
5314 |
-
metrics:
|
5315 |
-
- type: map_at_1
|
5316 |
-
value: 0.253
|
5317 |
-
- type: map_at_10
|
5318 |
-
value: 2.07
|
5319 |
-
- type: map_at_100
|
5320 |
-
value: 12.679000000000002
|
5321 |
-
- type: map_at_1000
|
5322 |
-
value: 30.412
|
5323 |
-
- type: map_at_3
|
5324 |
-
value: 0.688
|
5325 |
-
- type: map_at_5
|
5326 |
-
value: 1.079
|
5327 |
-
- type: mrr_at_1
|
5328 |
-
value: 96
|
5329 |
-
- type: mrr_at_10
|
5330 |
-
value: 98
|
5331 |
-
- type: mrr_at_100
|
5332 |
-
value: 98
|
5333 |
-
- type: mrr_at_1000
|
5334 |
-
value: 98
|
5335 |
-
- type: mrr_at_3
|
5336 |
-
value: 98
|
5337 |
-
- type: mrr_at_5
|
5338 |
-
value: 98
|
5339 |
-
- type: ndcg_at_1
|
5340 |
-
value: 89
|
5341 |
-
- type: ndcg_at_10
|
5342 |
-
value: 79.646
|
5343 |
-
- type: ndcg_at_100
|
5344 |
-
value: 62.217999999999996
|
5345 |
-
- type: ndcg_at_1000
|
5346 |
-
value: 55.13400000000001
|
5347 |
-
- type: ndcg_at_3
|
5348 |
-
value: 83.458
|
5349 |
-
- type: ndcg_at_5
|
5350 |
-
value: 80.982
|
5351 |
-
- type: precision_at_1
|
5352 |
-
value: 96
|
5353 |
-
- type: precision_at_10
|
5354 |
-
value: 84.6
|
5355 |
-
- type: precision_at_100
|
5356 |
-
value: 64.34
|
5357 |
-
- type: precision_at_1000
|
5358 |
-
value: 24.534
|
5359 |
-
- type: precision_at_3
|
5360 |
-
value: 88.667
|
5361 |
-
- type: precision_at_5
|
5362 |
-
value: 85.6
|
5363 |
-
- type: recall_at_1
|
5364 |
-
value: 0.253
|
5365 |
-
- type: recall_at_10
|
5366 |
-
value: 2.253
|
5367 |
-
- type: recall_at_100
|
5368 |
-
value: 15.606
|
5369 |
-
- type: recall_at_1000
|
5370 |
-
value: 51.595
|
5371 |
-
- type: recall_at_3
|
5372 |
-
value: 0.7100000000000001
|
5373 |
-
- type: recall_at_5
|
5374 |
-
value: 1.139
|
5375 |
-
- task:
|
5376 |
-
type: Retrieval
|
5377 |
-
dataset:
|
5378 |
-
type: mteb/touche2020
|
5379 |
-
name: MTEB Touche2020
|
5380 |
-
config: default
|
5381 |
-
split: test
|
5382 |
-
revision: a34f9a33db75fa0cbb21bb5cfc3dae8dc8bec93f
|
5383 |
-
metrics:
|
5384 |
-
- type: map_at_1
|
5385 |
-
value: 3.0540000000000003
|
5386 |
-
- type: map_at_10
|
5387 |
-
value: 13.078999999999999
|
5388 |
-
- type: map_at_100
|
5389 |
-
value: 19.468
|
5390 |
-
- type: map_at_1000
|
5391 |
-
value: 21.006
|
5392 |
-
- type: map_at_3
|
5393 |
-
value: 6.8629999999999995
|
5394 |
-
- type: map_at_5
|
5395 |
-
value: 9.187
|
5396 |
-
- type: mrr_at_1
|
5397 |
-
value: 42.857
|
5398 |
-
- type: mrr_at_10
|
5399 |
-
value: 56.735
|
5400 |
-
- type: mrr_at_100
|
5401 |
-
value: 57.352000000000004
|
5402 |
-
- type: mrr_at_1000
|
5403 |
-
value: 57.352000000000004
|
5404 |
-
- type: mrr_at_3
|
5405 |
-
value: 52.721
|
5406 |
-
- type: mrr_at_5
|
5407 |
-
value: 54.66
|
5408 |
-
- type: ndcg_at_1
|
5409 |
-
value: 38.775999999999996
|
5410 |
-
- type: ndcg_at_10
|
5411 |
-
value: 31.469
|
5412 |
-
- type: ndcg_at_100
|
5413 |
-
value: 42.016999999999996
|
5414 |
-
- type: ndcg_at_1000
|
5415 |
-
value: 52.60399999999999
|
5416 |
-
- type: ndcg_at_3
|
5417 |
-
value: 35.894
|
5418 |
-
- type: ndcg_at_5
|
5419 |
-
value: 33.873
|
5420 |
-
- type: precision_at_1
|
5421 |
-
value: 42.857
|
5422 |
-
- type: precision_at_10
|
5423 |
-
value: 27.346999999999998
|
5424 |
-
- type: precision_at_100
|
5425 |
-
value: 8.327
|
5426 |
-
- type: precision_at_1000
|
5427 |
-
value: 1.551
|
5428 |
-
- type: precision_at_3
|
5429 |
-
value: 36.735
|
5430 |
-
- type: precision_at_5
|
5431 |
-
value: 33.469
|
5432 |
-
- type: recall_at_1
|
5433 |
-
value: 3.0540000000000003
|
5434 |
-
- type: recall_at_10
|
5435 |
-
value: 19.185
|
5436 |
-
- type: recall_at_100
|
5437 |
-
value: 51.056000000000004
|
5438 |
-
- type: recall_at_1000
|
5439 |
-
value: 82.814
|
5440 |
-
- type: recall_at_3
|
5441 |
-
value: 7.961
|
5442 |
-
- type: recall_at_5
|
5443 |
-
value: 11.829
|
5444 |
-
- task:
|
5445 |
-
type: Classification
|
5446 |
-
dataset:
|
5447 |
-
type: mteb/toxic_conversations_50k
|
5448 |
-
name: MTEB ToxicConversationsClassification
|
5449 |
-
config: default
|
5450 |
-
split: test
|
5451 |
-
revision: edfaf9da55d3dd50d43143d90c1ac476895ae6de
|
5452 |
-
metrics:
|
5453 |
-
- type: accuracy
|
5454 |
-
value: 64.9346
|
5455 |
-
- type: ap
|
5456 |
-
value: 12.121605736777527
|
5457 |
-
- type: f1
|
5458 |
-
value: 50.169902005887955
|
5459 |
-
- task:
|
5460 |
-
type: Classification
|
5461 |
-
dataset:
|
5462 |
-
type: mteb/tweet_sentiment_extraction
|
5463 |
-
name: MTEB TweetSentimentExtractionClassification
|
5464 |
-
config: default
|
5465 |
-
split: test
|
5466 |
-
revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
|
5467 |
-
metrics:
|
5468 |
-
- type: accuracy
|
5469 |
-
value: 56.72608941709111
|
5470 |
-
- type: f1
|
5471 |
-
value: 57.0702928875253
|
5472 |
-
- task:
|
5473 |
-
type: Clustering
|
5474 |
-
dataset:
|
5475 |
-
type: mteb/twentynewsgroups-clustering
|
5476 |
-
name: MTEB TwentyNewsgroupsClustering
|
5477 |
-
config: default
|
5478 |
-
split: test
|
5479 |
-
revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
|
5480 |
-
metrics:
|
5481 |
-
- type: v_measure
|
5482 |
-
value: 37.72671554400943
|
5483 |
-
- task:
|
5484 |
-
type: PairClassification
|
5485 |
-
dataset:
|
5486 |
-
type: mteb/twittersemeval2015-pairclassification
|
5487 |
-
name: MTEB TwitterSemEval2015
|
5488 |
-
config: default
|
5489 |
-
split: test
|
5490 |
-
revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
|
5491 |
-
metrics:
|
5492 |
-
- type: cos_sim_accuracy
|
5493 |
-
value: 82.84556237706384
|
5494 |
-
- type: cos_sim_ap
|
5495 |
-
value: 63.28364215788651
|
5496 |
-
- type: cos_sim_f1
|
5497 |
-
value: 60.00000000000001
|
5498 |
-
- type: cos_sim_precision
|
5499 |
-
value: 54.45161290322581
|
5500 |
-
- type: cos_sim_recall
|
5501 |
-
value: 66.80738786279683
|
5502 |
-
- type: dot_accuracy
|
5503 |
-
value: 82.84556237706384
|
5504 |
-
- type: dot_ap
|
5505 |
-
value: 63.28364302860433
|
5506 |
-
- type: dot_f1
|
5507 |
-
value: 60.00000000000001
|
5508 |
-
- type: dot_precision
|
5509 |
-
value: 54.45161290322581
|
5510 |
-
- type: dot_recall
|
5511 |
-
value: 66.80738786279683
|
5512 |
-
- type: euclidean_accuracy
|
5513 |
-
value: 82.84556237706384
|
5514 |
-
- type: euclidean_ap
|
5515 |
-
value: 63.28363625097978
|
5516 |
-
- type: euclidean_f1
|
5517 |
-
value: 60.00000000000001
|
5518 |
-
- type: euclidean_precision
|
5519 |
-
value: 54.45161290322581
|
5520 |
-
- type: euclidean_recall
|
5521 |
-
value: 66.80738786279683
|
5522 |
-
- type: manhattan_accuracy
|
5523 |
-
value: 82.86940454193241
|
5524 |
-
- type: manhattan_ap
|
5525 |
-
value: 63.244773709836764
|
5526 |
-
- type: manhattan_f1
|
5527 |
-
value: 60.12680942696495
|
5528 |
-
- type: manhattan_precision
|
5529 |
-
value: 55.00109433136353
|
5530 |
-
- type: manhattan_recall
|
5531 |
-
value: 66.3060686015831
|
5532 |
-
- type: max_accuracy
|
5533 |
-
value: 82.86940454193241
|
5534 |
-
- type: max_ap
|
5535 |
-
value: 63.28364302860433
|
5536 |
-
- type: max_f1
|
5537 |
-
value: 60.12680942696495
|
5538 |
-
- task:
|
5539 |
-
type: PairClassification
|
5540 |
-
dataset:
|
5541 |
-
type: mteb/twitterurlcorpus-pairclassification
|
5542 |
-
name: MTEB TwitterURLCorpus
|
5543 |
-
config: default
|
5544 |
-
split: test
|
5545 |
-
revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
|
5546 |
-
metrics:
|
5547 |
-
- type: cos_sim_accuracy
|
5548 |
-
value: 88.32033220786278
|
5549 |
-
- type: cos_sim_ap
|
5550 |
-
value: 84.71928176006863
|
5551 |
-
- type: cos_sim_f1
|
5552 |
-
value: 76.51483333969684
|
5553 |
-
- type: cos_sim_precision
|
5554 |
-
value: 75.89184276300841
|
5555 |
-
- type: cos_sim_recall
|
5556 |
-
value: 77.14813674160764
|
5557 |
-
- type: dot_accuracy
|
5558 |
-
value: 88.32033220786278
|
5559 |
-
- type: dot_ap
|
5560 |
-
value: 84.71928330149228
|
5561 |
-
- type: dot_f1
|
5562 |
-
value: 76.51483333969684
|
5563 |
-
- type: dot_precision
|
5564 |
-
value: 75.89184276300841
|
5565 |
-
- type: dot_recall
|
5566 |
-
value: 77.14813674160764
|
5567 |
-
- type: euclidean_accuracy
|
5568 |
-
value: 88.32033220786278
|
5569 |
-
- type: euclidean_ap
|
5570 |
-
value: 84.71928045384345
|
5571 |
-
- type: euclidean_f1
|
5572 |
-
value: 76.51483333969684
|
5573 |
-
- type: euclidean_precision
|
5574 |
-
value: 75.89184276300841
|
5575 |
-
- type: euclidean_recall
|
5576 |
-
value: 77.14813674160764
|
5577 |
-
- type: manhattan_accuracy
|
5578 |
-
value: 88.27570147863545
|
5579 |
-
- type: manhattan_ap
|
5580 |
-
value: 84.68523541579755
|
5581 |
-
- type: manhattan_f1
|
5582 |
-
value: 76.51512269355146
|
5583 |
-
- type: manhattan_precision
|
5584 |
-
value: 75.62608107091825
|
5585 |
-
- type: manhattan_recall
|
5586 |
-
value: 77.42531567600862
|
5587 |
-
- type: max_accuracy
|
5588 |
-
value: 88.32033220786278
|
5589 |
-
- type: max_ap
|
5590 |
-
value: 84.71928330149228
|
5591 |
-
- type: max_f1
|
5592 |
-
value: 76.51512269355146
|
5593 |
-
- task:
|
5594 |
-
type: Clustering
|
5595 |
-
dataset:
|
5596 |
-
type: jinaai/cities_wiki_clustering
|
5597 |
-
name: MTEB WikiCitiesClustering
|
5598 |
-
config: default
|
5599 |
-
split: test
|
5600 |
-
revision: ddc9ee9242fa65332597f70e967ecc38b9d734fa
|
5601 |
-
metrics:
|
5602 |
-
- type: v_measure
|
5603 |
-
value: 85.30624598674467
|
5604 |
license: apache-2.0
|
5605 |
---
|
5606 |
-
<h1 align="center">Snowflake's Artic-embed
|
5607 |
<h4 align="center">
|
5608 |
<p>
|
5609 |
<a href=#news>News</a> |
|
|
|
2799 |
metrics:
|
2800 |
- type: v_measure
|
2801 |
value: 79.58576208710117
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2802 |
license: apache-2.0
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2803 |
---
|
2804 |
+
<h1 align="center">Snowflake's Artic-embed-s</h1>
|
2805 |
<h4 align="center">
|
2806 |
<p>
|
2807 |
<a href=#news>News</a> |
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