Space: iwashuman0405/api-rag
library_name: sentence-transformers
pipeline_tag: sentence-similarity
tags: feature-extraction, sentence-similarity, mteb, transformers, transformers.js
model-index: name: epoch_0_model
results: task: type: Classification
dataset: type: mteb/amazon_counterfactual
name: MTEB AmazonCounterfactualClassification (en)
config: en
split: test
revision: e8379541af4e31359cca9fbcf4b00f2671dba205
metrics: type: accuracy
value: 76.8507462686567, type: ap
value: 40.592189159090495, type: f1
value: 71.01634655512476, task: type: Classification
dataset: type: mteb/amazon_polarity
name: MTEB AmazonPolarityClassification
config: default
split: test
revision: e2d317d38cd51312af73b3d32a06d1a08b442046
metrics: type: accuracy
value: 91.51892500000001, type: ap
value: 88.50346762975335, type: f1
value: 91.50342077459624, task: type: Classification
dataset: type: mteb/amazon_reviews_multi
name: MTEB AmazonReviewsClassification (en)
config: en
split: test
revision: 1399c76144fd37290681b995c656ef9b2e06e26d
metrics: type: accuracy
value: 47.364, type: f1
value: 46.72708080922794, task: type: Retrieval
dataset: type: arguana
name: MTEB ArguAna
config: default
split: test
revision: None
metrics: type: map_at_1
value: 25.178, type: map_at_10
value: 40.244, type: map_at_100
value: 41.321999999999996, type: map_at_1000
value: 41.331, type: map_at_3
value: 35.016999999999996, type: map_at_5
value: 37.99, type: mrr_at_1
value: 25.605, type: mrr_at_10
value: 40.422000000000004, type: mrr_at_100
value: 41.507, type: mrr_at_1000
value: 41.516, type: mrr_at_3
value: 35.23, type: mrr_at_5
value: 38.15, type: ndcg_at_1
value: 25.178, type: ndcg_at_10
value: 49.258, type: ndcg_at_100
value: 53.776, type: ndcg_at_1000
value: 53.995000000000005, type: ndcg_at_3
value: 38.429, type: ndcg_at_5
value: 43.803, type: precision_at_1
value: 25.178, type: precision_at_10
value: 7.831, type: precision_at_100
value: 0.979, type: precision_at_1000
value: 0.1, type: precision_at_3
value: 16.121, type: precision_at_5
value: 12.29, type: recall_at_1
value: 25.178, type: recall_at_10
value: 78.307, type: recall_at_100
value: 97.866, type: recall_at_1000
value: 99.57300000000001, type: recall_at_3
value: 48.364000000000004, type: recall_at_5
value: 61.451, task: type: Clustering
dataset: type: mteb/arxiv-clustering-p2p
name: MTEB ArxivClusteringP2P
config: default
split: test
revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
metrics: type: v_measure
value: 45.93034494751465, task: type: Clustering
dataset: type: mteb/arxiv-clustering-s2s
name: MTEB ArxivClusteringS2S
config: default
split: test
revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
metrics: type: v_measure
value: 36.64579480054327, task: type: Reranking
dataset: type: mteb/askubuntudupquestions-reranking
name: MTEB AskUbuntuDupQuestions
config: default
split: test
revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
metrics: type: map
value: 60.601310529222054, type: mrr
value: 75.04484896451656, task: type: STS
dataset: type: mteb/biosses-sts
name: MTEB BIOSSES
config: default
split: test
revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
metrics: type: cos_sim_pearson
value: 88.57797718095814, type: cos_sim_spearman
value: 86.47064499110101, type: euclidean_pearson
value: 87.4559602783142, type: euclidean_spearman
value: 86.47064499110101, type: manhattan_pearson
value: 87.7232764230245, type: manhattan_spearman
value: 86.91222131777742, task: type: Classification
dataset: type: mteb/banking77
name: MTEB Banking77Classification
config: default
split: test
revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
metrics: type: accuracy
value: 84.5422077922078, type: f1
value: 84.47657456950589, task: type: Clustering
dataset: type: mteb/biorxiv-clustering-p2p
name: MTEB BiorxivClusteringP2P
config: default
split: test
revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
metrics: type: v_measure
value: 38.48953561974464, task: type: Clustering
dataset: type: mteb/biorxiv-clustering-s2s
name: MTEB BiorxivClusteringS2S
config: default
split: test
revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
metrics: type: v_measure
value: 32.75995857510105, task: type: Retrieval
dataset: type: BeIR/cqadupstack
name: MTEB CQADupstackAndroidRetrieval
config: default
split: test
revision: None
metrics: type: map_at_1
value: 30.008000000000003, type: map_at_10
value: 39.51, type: map_at_100
value: 40.841, type: map_at_1000
value: 40.973, type: map_at_3
value: 36.248999999999995, type: map_at_5
value: 38.096999999999994, type: mrr_at_1
value: 36.481, type: mrr_at_10
value: 44.818000000000005, type: mrr_at_100
value: 45.64, type: mrr_at_1000
value: 45.687, type: mrr_at_3
value: 42.036, type: mrr_at_5
value: 43.782, type: ndcg_at_1
value: 36.481, type: ndcg_at_10
value: 45.152, type: ndcg_at_100
value: 50.449, type: ndcg_at_1000
value: 52.76499999999999, type: ndcg_at_3
value: 40.161, type: ndcg_at_5
value: 42.577999999999996, type: precision_at_1
value: 36.481, type: precision_at_10
value: 8.369, type: precision_at_100
value: 1.373, type: precision_at_1000
value: 0.186, type: precision_at_3
value: 18.693, type: precision_at_5
value: 13.533999999999999, type: recall_at_1
value: 30.008000000000003, type: recall_at_10
value: 56.108999999999995, type: recall_at_100
value: 78.55499999999999, type: recall_at_1000
value: 93.659, type: recall_at_3
value: 41.754999999999995, type: recall_at_5
value: 48.296, task: type: Retrieval
dataset: type: BeIR/cqadupstack
name: MTEB CQADupstackEnglishRetrieval
config: default
split: test
revision: None
metrics: type: map_at_1
value: 30.262, type: map_at_10
value: 40.139, type: map_at_100
value: 41.394, type: map_at_1000
value: 41.526, type: map_at_3
value: 37.155, type: map_at_5
value: 38.785, type: mrr_at_1
value: 38.153, type: mrr_at_10
value: 46.369, type: mrr_at_100
value: 47.072, type: mrr_at_1000
value: 47.111999999999995, type: mrr_at_3
value: 44.268, type: mrr_at_5
value: 45.389, type: ndcg_at_1
value: 38.153, type: ndcg_at_10
value: 45.925, type: ndcg_at_100
value: 50.394000000000005, type: ndcg_at_1000
value: 52.37500000000001, type: ndcg_at_3
value: 41.754000000000005, type: ndcg_at_5
value: 43.574, type: precision_at_1
value: 38.153, type: precision_at_10
value: 8.796, type: precision_at_100
value: 1.432, type: precision_at_1000
value: 0.189, type: precision_at_3
value: 20.318, type: precision_at_5
value: 14.395, type: recall_at_1
value: 30.262, type: recall_at_10
value: 55.72200000000001, type: recall_at_100
value: 74.97500000000001, type: recall_at_1000
value: 87.342, type: recall_at_3
value: 43.129, type: recall_at_5
value: 48.336, task: type: Retrieval
dataset: type: BeIR/cqadupstack
name: MTEB CQADupstackGamingRetrieval
config: default
split: test
revision: None
metrics: type: map_at_1
value: 39.951, type: map_at_10
value: 51.248000000000005, type: map_at_100
value: 52.188, type: map_at_1000
value: 52.247, type: map_at_3
value: 48.211, type: map_at_5
value: 49.797000000000004, type: mrr_at_1
value: 45.329, type: mrr_at_10
value: 54.749, type: mrr_at_100
value: 55.367999999999995, type: mrr_at_1000
value: 55.400000000000006, type: mrr_at_3
value: 52.382, type: mrr_at_5
value: 53.649, type: ndcg_at_1
value: 45.329, type: ndcg_at_10
value: 56.847, type: ndcg_at_100
value: 60.738, type: ndcg_at_1000
value: 61.976, type: ndcg_at_3
value: 51.59, type: ndcg_at_5
value: 53.915, type: precision_at_1
value: 45.329, type: precision_at_10
value: 8.959, type: precision_at_100
value: 1.187, type: precision_at_1000
value: 0.134, type: precision_at_3
value: 22.612, type: precision_at_5
value: 15.273, type: recall_at_1
value: 39.951, type: recall_at_10
value: 70.053, type: recall_at_100
value: 86.996, type: recall_at_1000
value: 95.707, type: recall_at_3
value: 56.032000000000004, type: recall_at_5
value: 61.629999999999995, task: type: Retrieval
dataset: type: BeIR/cqadupstack
name: MTEB CQADupstackGisRetrieval
config: default
split: test
revision: None
metrics: type: map_at_1
value: 25.566, type: map_at_10
value: 33.207, type: map_at_100
value: 34.166000000000004, type: map_at_1000
value: 34.245, type: map_at_3
value: 30.94, type: map_at_5
value: 32.01, type: mrr_at_1
value: 27.345000000000002, type: mrr_at_10
value: 35.193000000000005, type: mrr_at_100
value: 35.965, type: mrr_at_1000
value: 36.028999999999996, type: mrr_at_3
value: 32.806000000000004, type: mrr_at_5
value: 34.021, type: ndcg_at_1
value: 27.345000000000002, type: ndcg_at_10
value: 37.891999999999996, type: ndcg_at_100
value: 42.664, type: ndcg_at_1000
value: 44.757000000000005, type: ndcg_at_3
value: 33.123000000000005, type: ndcg_at_5
value: 35.035, type: precision_at_1
value: 27.345000000000002, type: precision_at_10
value: 5.763, type: precision_at_100
value: 0.859, type: precision_at_1000
value: 0.108, type: precision_at_3
value: 13.71, type: precision_at_5
value: 9.401, type: recall_at_1
value: 25.566, type: recall_at_10
value: 50.563, type: recall_at_100
value: 72.86399999999999, type: recall_at_1000
value: 88.68599999999999, type: recall_at_3
value: 37.43, type: recall_at_5
value: 41.894999999999996, task: type: Retrieval
dataset: type: BeIR/cqadupstack
name: MTEB CQADupstackMathematicaRetrieval
config: default
split: test
revision: None
metrics: type: map_at_1
value: 16.663, type: map_at_10
value: 23.552, type: map_at_100
value: 24.538, type: map_at_1000
value: 24.661, type: map_at_3
value: 21.085, type: map_at_5
value: 22.391, type: mrr_at_1
value: 20.025000000000002, type: mrr_at_10
value: 27.643, type: mrr_at_100
value: 28.499999999999996, type: mrr_at_1000
value: 28.582, type: mrr_at_3
value: 25.083, type: mrr_at_5
value: 26.544, type: ndcg_at_1
value: 20.025000000000002, type: ndcg_at_10
value: 28.272000000000002, type: ndcg_at_100
value: 33.353, type: ndcg_at_1000
value: 36.454, type: ndcg_at_3
value: 23.579, type: ndcg_at_5
value: 25.685000000000002, type: precision_at_1
value: 20.025000000000002, type: precision_at_10
value: 5.187, type: precision_at_100
value: 0.897, type: precision_at_1000
value: 0.13, type: precision_at_3
value: 10.987, type: precision_at_5
value: 8.06, type: recall_at_1
value: 16.663, type: recall_at_10
value: 38.808, type: recall_at_100
value: 61.305, type: recall_at_1000
value: 83.571, type: recall_at_3
value: 25.907999999999998, type: recall_at_5
value: 31.214, task: type: Retrieval
dataset: type: BeIR/cqadupstack
name: MTEB CQADupstackPhysicsRetrieval
config: default
split: test
revision: None
metrics: type: map_at_1
value: 27.695999999999998, type: map_at_10
value: 37.018, type: map_at_100
value: 38.263000000000005, type: map_at_1000
value: 38.371, type: map_at_3
value: 34.226, type: map_at_5
value: 35.809999999999995, type: mrr_at_1
value: 32.916000000000004, type: mrr_at_10
value: 42.067, type: mrr_at_100
value: 42.925000000000004, type: mrr_at_1000
value: 42.978, type: mrr_at_3
value: 39.637, type: mrr_at_5
value: 41.134, type: ndcg_at_1
value: 32.916000000000004, type: ndcg_at_10
value: 42.539, type: ndcg_at_100
value: 47.873, type: ndcg_at_1000
value: 50.08200000000001, type: ndcg_at_3
value: 37.852999999999994, type: ndcg_at_5
value: 40.201, type: precision_at_1
value: 32.916000000000004, type: precision_at_10
value: 7.5840000000000005, type: precision_at_100
value: 1.199, type: precision_at_1000
value: 0.155, type: precision_at_3
value: 17.485, type: precision_at_5
value: 12.512, type: recall_at_1
value: 27.695999999999998, type: recall_at_10
value: 53.638, type: recall_at_100
value: 76.116, type: recall_at_1000
value: 91.069, type: recall_at_3
value: 41.13, type: recall_at_5
value: 46.872, task: type: Retrieval
dataset: type: BeIR/cqadupstack
name: MTEB CQADupstackProgrammersRetrieval
config: default
split: test
revision: None
metrics: type: map_at_1
value: 24.108, type: map_at_10
value: 33.372, type: map_at_100
value: 34.656, type: map_at_1000
value: 34.768, type: map_at_3
value: 30.830999999999996, type: map_at_5
value: 32.204, type: mrr_at_1
value: 29.110000000000003, type: mrr_at_10
value: 37.979, type: mrr_at_100
value: 38.933, type: mrr_at_1000
value: 38.988, type: mrr_at_3
value: 35.731, type: mrr_at_5
value: 36.963, type: ndcg_at_1
value: 29.110000000000003, type: ndcg_at_10
value: 38.635000000000005, type: ndcg_at_100
value: 44.324999999999996, type: ndcg_at_1000
value: 46.747, type: ndcg_at_3
value: 34.37, type: ndcg_at_5
value: 36.228, type: precision_at_1
value: 29.110000000000003, type: precision_at_10
value: 6.963, type: precision_at_100
value: 1.146, type: precision_at_1000
value: 0.152, type: precision_at_3
value: 16.400000000000002, type: precision_at_5
value: 11.552999999999999, type: recall_at_1
value: 24.108, type: recall_at_10
value: 49.597, type: recall_at_100
value: 73.88900000000001, type: recall_at_1000
value: 90.62400000000001, type: recall_at_3
value: 37.662, type: recall_at_5
value: 42.565, task: type: Retrieval
dataset: type: BeIR/cqadupstack
name: MTEB CQADupstackRetrieval
config: default
split: test
revision: None
metrics: type: map_at_1
value: 25.00791666666667, type: map_at_10
value: 33.287749999999996, type: map_at_100
value: 34.41141666666667, type: map_at_1000
value: 34.52583333333333, type: map_at_3
value: 30.734416666666668, type: map_at_5
value: 32.137166666666666, type: mrr_at_1
value: 29.305666666666664, type: mrr_at_10
value: 37.22966666666666, type: mrr_at_100
value: 38.066583333333334, type: mrr_at_1000
value: 38.12616666666667, type: mrr_at_3
value: 34.92275, type: mrr_at_5
value: 36.23333333333334, type: ndcg_at_1
value: 29.305666666666664, type: ndcg_at_10
value: 38.25533333333333, type: ndcg_at_100
value: 43.25266666666666, type: ndcg_at_1000
value: 45.63583333333334, type: ndcg_at_3
value: 33.777166666666666, type: ndcg_at_5
value: 35.85, type: precision_at_1
value: 29.305666666666664, type: precision_at_10
value: 6.596416666666667, type: precision_at_100
value: 1.0784166666666668, type: precision_at_1000
value: 0.14666666666666664, type: precision_at_3
value: 15.31075, type: precision_at_5
value: 10.830916666666667, type: recall_at_1
value: 25.00791666666667, type: recall_at_10
value: 49.10933333333333, type: recall_at_100
value: 71.09216666666667, type: recall_at_1000
value: 87.77725000000001, type: recall_at_3
value: 36.660916666666665, type: recall_at_5
value: 41.94149999999999, task: type: Retrieval
dataset: type: BeIR/cqadupstack
name: MTEB CQADupstackStatsRetrieval
config: default
split: test
revision: None
metrics: type: map_at_1
value: 23.521, type: map_at_10
value: 30.043, type: map_at_100
value: 30.936000000000003, type: map_at_1000
value: 31.022, type: map_at_3
value: 27.926000000000002, type: map_at_5
value: 29.076999999999998, type: mrr_at_1
value: 26.227, type: mrr_at_10
value: 32.822, type: mrr_at_100
value: 33.61, type: mrr_at_1000
value: 33.672000000000004, type: mrr_at_3
value: 30.776999999999997, type: mrr_at_5
value: 31.866, type: ndcg_at_1
value: 26.227, type: ndcg_at_10
value: 34.041, type: ndcg_at_100
value: 38.394, type: ndcg_at_1000
value: 40.732, type: ndcg_at_3
value: 30.037999999999997, type: ndcg_at_5
value: 31.845000000000002, type: precision_at_1
value: 26.227, type: precision_at_10
value: 5.244999999999999, type: precision_at_100
value: 0.808, type: precision_at_1000
value: 0.107, type: precision_at_3
value: 12.679000000000002, type: precision_at_5
value: 8.773, type: recall_at_1
value: 23.521, type: recall_at_10
value: 43.633, type: recall_at_100
value: 63.126000000000005, type: recall_at_1000
value: 80.765, type: recall_at_3
value: 32.614, type: recall_at_5
value: 37.15, task: type: Retrieval
dataset: type: BeIR/cqadupstack
name: MTEB CQADupstackTexRetrieval
config: default
split: test
revision: None
metrics: type: map_at_1
value: 16.236, type: map_at_10
value: 22.898, type: map_at_100
value: 23.878, type: map_at_1000
value: 24.009, type: map_at_3
value: 20.87, type: map_at_5
value: 22.025, type: mrr_at_1
value: 19.339000000000002, type: mrr_at_10
value: 26.382, type: mrr_at_100
value: 27.245, type: mrr_at_1000
value: 27.33, type: mrr_at_3
value: 24.386, type: mrr_at_5
value: 25.496000000000002, type: ndcg_at_1
value: 19.339000000000002, type: ndcg_at_10
value: 27.139999999999997, type: ndcg_at_100
value: 31.944, type: ndcg_at_1000
value: 35.077999999999996, type: ndcg_at_3
value: 23.424, type: ndcg_at_5
value: 25.188, type: precision_at_1
value: 19.339000000000002, type: precision_at_10
value: 4.8309999999999995, type: precision_at_100
value: 0.845, type: precision_at_1000
value: 0.128, type: precision_at_3
value: 10.874, type: precision_at_5
value: 7.825, type: recall_at_1
value: 16.236, type: recall_at_10
value: 36.513, type: recall_at_100
value: 57.999, type: recall_at_1000
value: 80.512, type: recall_at_3
value: 26.179999999999996, type: recall_at_5
value: 30.712, task: type: Retrieval
dataset: type: BeIR/cqadupstack
name: MTEB CQADupstackUnixRetrieval
config: default
split: test
revision: None
metrics: type: map_at_1
value: 24.11, type: map_at_10
value: 31.566, type: map_at_100
value: 32.647, type: map_at_1000
value: 32.753, type: map_at_3
value: 29.24, type: map_at_5
value: 30.564999999999998, type: mrr_at_1
value: 28.265, type: mrr_at_10
value: 35.504000000000005, type: mrr_at_100
value: 36.436, type: mrr_at_1000
value: 36.503, type: mrr_at_3
value: 33.349000000000004, type: mrr_at_5
value: 34.622, type: ndcg_at_1
value: 28.265, type: ndcg_at_10
value: 36.192, type: ndcg_at_100
value: 41.388000000000005, type: ndcg_at_1000
value: 43.948, type: ndcg_at_3
value: 31.959, type: ndcg_at_5
value: 33.998, type: precision_at_1
value: 28.265, type: precision_at_10
value: 5.989, type: precision_at_100
value: 0.9650000000000001, type: precision_at_1000
value: 0.13, type: precision_at_3
value: 14.335, type: precision_at_5
value: 10.112, type: recall_at_1
value: 24.11, type: recall_at_10
value: 46.418, type: recall_at_100
value: 69.314, type: recall_at_1000
value: 87.397, type: recall_at_3
value: 34.724, type: recall_at_5
value: 39.925, task: type: Retrieval
dataset: type: BeIR/cqadupstack
name: MTEB CQADupstackWebmastersRetrieval
config: default
split: test
revision: None
metrics: type: map_at_1
value: 22.091, type: map_at_10
value: 29.948999999999998, type: map_at_100
value: 31.502000000000002, type: map_at_1000
value: 31.713, type: map_at_3
value: 27.464, type: map_at_5
value: 28.968, type: mrr_at_1
value: 26.482, type: mrr_at_10
value: 34.009, type: mrr_at_100
value: 35.081, type: mrr_at_1000
value: 35.138000000000005, type: mrr_at_3
value: 31.785000000000004, type: mrr_at_5
value: 33.178999999999995, type: ndcg_at_1
value: 26.482, type: ndcg_at_10
value: 35.008, type: ndcg_at_100
value: 41.272999999999996, type: ndcg_at_1000
value: 43.972, type: ndcg_at_3
value: 30.804, type: ndcg_at_5
value: 33.046, type: precision_at_1
value: 26.482, type: precision_at_10
value: 6.462, type: precision_at_100
value: 1.431, type: precision_at_1000
value: 0.22899999999999998, type: precision_at_3
value: 14.360999999999999, type: precision_at_5
value: 10.474, type: recall_at_1
value: 22.091, type: recall_at_10
value: 45.125, type: recall_at_100
value: 72.313, type: recall_at_1000
value: 89.503, type: recall_at_3
value: 33.158, type: recall_at_5
value: 39.086999999999996, task: type: Retrieval
dataset: type: BeIR/cqadupstack
name: MTEB CQADupstackWordpressRetrieval
config: default
split: test
revision: None
metrics: type: map_at_1
value: 19.883, type: map_at_10
value: 26.951000000000004, type: map_at_100
value: 27.927999999999997, type: map_at_1000
value: 28.022000000000002, type: map_at_3
value: 24.616, type: map_at_5
value: 25.917, type: mrr_at_1
value: 21.996, type: mrr_at_10
value: 29.221000000000004, type: mrr_at_100
value: 30.024, type: mrr_at_1000
value: 30.095, type: mrr_at_3
value: 26.833000000000002, type: mrr_at_5
value: 28.155, type: ndcg_at_1
value: 21.996, type: ndcg_at_10
value: 31.421, type: ndcg_at_100
value: 36.237, type: ndcg_at_1000
value: 38.744, type: ndcg_at_3
value: 26.671, type: ndcg_at_5
value: 28.907, type: precision_at_1
value: 21.996, type: precision_at_10
value: 5.009, type: precision_at_100
value: 0.799, type: precision_at_1000
value: 0.11199999999999999, type: precision_at_3
value: 11.275, type: precision_at_5
value: 8.059, type: recall_at_1
value: 19.883, type: recall_at_10
value: 43.132999999999996, type: recall_at_100
value: 65.654, type: recall_at_1000
value: 84.492, type: recall_at_3
value: 30.209000000000003, type: recall_at_5
value: 35.616, task: type: Retrieval
dataset: type: climate-fever
name: MTEB ClimateFEVER
config: default
split: test
revision: None
metrics: type: map_at_1
value: 17.756, type: map_at_10
value: 30.378, type: map_at_100
value: 32.537, type: map_at_1000
value: 32.717, type: map_at_3
value: 25.599, type: map_at_5
value: 28.372999999999998, type: mrr_at_1
value: 41.303, type: mrr_at_10
value: 53.483999999999995, type: mrr_at_100
value: 54.106, type: mrr_at_1000
value: 54.127, type: mrr_at_3
value: 50.315, type: mrr_at_5
value: 52.396, type: ndcg_at_1
value: 41.303, type: ndcg_at_10
value: 40.503, type: ndcg_at_100
value: 47.821000000000005, type: ndcg_at_1000
value: 50.788, type: ndcg_at_3
value: 34.364, type: ndcg_at_5
value: 36.818, type: precision_at_1
value: 41.303, type: precision_at_10
value: 12.463000000000001, type: precision_at_100
value: 2.037, type: precision_at_1000
value: 0.26, type: precision_at_3
value: 25.798, type: precision_at_5
value: 19.896, type: recall_at_1
value: 17.756, type: recall_at_10
value: 46.102, type: recall_at_100
value: 70.819, type: recall_at_1000
value: 87.21799999999999, type: recall_at_3
value: 30.646, type: recall_at_5
value: 38.022, task: type: Retrieval
dataset: type: dbpedia-entity
name: MTEB DBPedia
config: default
split: test
revision: None
metrics: type: map_at_1
value: 9.033, type: map_at_10
value: 20.584, type: map_at_100
value: 29.518, type: map_at_1000
value: 31.186000000000003, type: map_at_3
value: 14.468, type: map_at_5
value: 17.177, type: mrr_at_1
value: 69.75, type: mrr_at_10
value: 77.025, type: mrr_at_100
value: 77.36699999999999, type: mrr_at_1000
value: 77.373, type: mrr_at_3
value: 75.583, type: mrr_at_5
value: 76.396, type: ndcg_at_1
value: 58.5, type: ndcg_at_10
value: 45.033, type: ndcg_at_100
value: 49.071, type: ndcg_at_1000
value: 56.056, type: ndcg_at_3
value: 49.936, type: ndcg_at_5
value: 47.471999999999994, type: precision_at_1
value: 69.75, type: precision_at_10
value: 35.775, type: precision_at_100
value: 11.594999999999999, type: precision_at_1000
value: 2.062, type: precision_at_3
value: 52.5, type: precision_at_5
value: 45.300000000000004, type: recall_at_1
value: 9.033, type: recall_at_10
value: 26.596999999999998, type: recall_at_100
value: 54.607000000000006, type: recall_at_1000
value: 76.961, type: recall_at_3
value: 15.754999999999999, type: recall_at_5
value: 20.033, task: type: Classification
dataset: type: mteb/emotion
name: MTEB EmotionClassification
config: default
split: test
revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
metrics: type: accuracy
value: 48.345000000000006, type: f1
value: 43.4514918068706, task: type: Retrieval
dataset: type: fever
name: MTEB FEVER
config: default
split: test
revision: None
metrics: type: map_at_1
value: 71.29100000000001, type: map_at_10
value: 81.059, type: map_at_100
value: 81.341, type: map_at_1000
value: 81.355, type: map_at_3
value: 79.74799999999999, type: map_at_5
value: 80.612, type: mrr_at_1
value: 76.40299999999999, type: mrr_at_10
value: 84.615, type: mrr_at_100
value: 84.745, type: mrr_at_1000
value: 84.748, type: mrr_at_3
value: 83.776, type: mrr_at_5
value: 84.343, type: ndcg_at_1
value: 76.40299999999999, type: ndcg_at_10
value: 84.981, type: ndcg_at_100
value: 86.00999999999999, type: ndcg_at_1000
value: 86.252, type: ndcg_at_3
value: 82.97, type: ndcg_at_5
value: 84.152, type: precision_at_1
value: 76.40299999999999, type: precision_at_10
value: 10.446, type: precision_at_100
value: 1.1199999999999999, type: precision_at_1000
value: 0.116, type: precision_at_3
value: 32.147999999999996, type: precision_at_5
value: 20.135, type: recall_at_1
value: 71.29100000000001, type: recall_at_10
value: 93.232, type: recall_at_100
value: 97.363, type: recall_at_1000
value: 98.905, type: recall_at_3
value: 87.893, type: recall_at_5
value: 90.804, task: type: Retrieval
dataset: type: fiqa
name: MTEB FiQA2018
config: default
split: test
revision: None
metrics: type: map_at_1
value: 18.667, type: map_at_10
value: 30.853, type: map_at_100
value: 32.494, type: map_at_1000
value: 32.677, type: map_at_3
value: 26.91, type: map_at_5
value: 29.099000000000004, type: mrr_at_1
value: 37.191, type: mrr_at_10
value: 46.171, type: mrr_at_100
value: 47.056, type: mrr_at_1000
value: 47.099000000000004, type: mrr_at_3
value: 44.059, type: mrr_at_5
value: 45.147, type: ndcg_at_1
value: 37.191, type: ndcg_at_10
value: 38.437, type: ndcg_at_100
value: 44.62, type: ndcg_at_1000
value: 47.795, type: ndcg_at_3
value: 35.003, type: ndcg_at_5
value: 36.006, type: precision_at_1
value: 37.191, type: precision_at_10
value: 10.586, type: precision_at_100
value: 1.688, type: precision_at_1000
value: 0.22699999999999998, type: precision_at_3
value: 23.302, type: precision_at_5
value: 17.006, type: recall_at_1
value: 18.667, type: recall_at_10
value: 45.367000000000004, type: recall_at_100
value: 68.207, type: recall_at_1000
value: 87.072, type: recall_at_3
value: 32.129000000000005, type: recall_at_5
value: 37.719, task: type: Retrieval
dataset: type: hotpotqa
name: MTEB HotpotQA
config: default
split: test
revision: None
metrics: type: map_at_1
value: 39.494, type: map_at_10
value: 66.223, type: map_at_100
value: 67.062, type: map_at_1000
value: 67.11500000000001, type: map_at_3
value: 62.867, type: map_at_5
value: 64.994, type: mrr_at_1
value: 78.987, type: mrr_at_10
value: 84.585, type: mrr_at_100
value: 84.773, type: mrr_at_1000
value: 84.77900000000001, type: mrr_at_3
value: 83.592, type: mrr_at_5
value: 84.235, type: ndcg_at_1
value: 78.987, type: ndcg_at_10
value: 73.64, type: ndcg_at_100
value: 76.519, type: ndcg_at_1000
value: 77.51, type: ndcg_at_3
value: 68.893, type: ndcg_at_5
value: 71.585, type: precision_at_1
value: 78.987, type: precision_at_10
value: 15.529000000000002, type: precision_at_100
value: 1.7770000000000001, type: precision_at_1000
value: 0.191, type: precision_at_3
value: 44.808, type: precision_at_5
value: 29.006999999999998, type: recall_at_1
value: 39.494, type: recall_at_10
value: 77.643, type: recall_at_100
value: 88.825, type: recall_at_1000
value: 95.321, type: recall_at_3
value: 67.211, type: recall_at_5
value: 72.519, task: type: Classification
dataset: type: mteb/imdb
name: MTEB ImdbClassification
config: default
split: test
revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
metrics: type: accuracy
value: 85.55959999999999, type: ap
value: 80.7246500384617, type: f1
value: 85.52336485065454, task: type: Retrieval
dataset: type: msmarco
name: MTEB MSMARCO
config: default
split: dev
revision: None
metrics: type: map_at_1
value: 23.631, type: map_at_10
value: 36.264, type: map_at_100
value: 37.428, type: map_at_1000
value: 37.472, type: map_at_3
value: 32.537, type: map_at_5
value: 34.746, type: mrr_at_1
value: 24.312, type: mrr_at_10
value: 36.858000000000004, type: mrr_at_100
value: 37.966, type: mrr_at_1000
value: 38.004, type: mrr_at_3
value: 33.188, type: mrr_at_5
value: 35.367, type: ndcg_at_1
value: 24.312, type: ndcg_at_10
value: 43.126999999999995, type: ndcg_at_100
value: 48.642, type: ndcg_at_1000
value: 49.741, type: ndcg_at_3
value: 35.589, type: ndcg_at_5
value: 39.515, type: precision_at_1
value: 24.312, type: precision_at_10
value: 6.699, type: precision_at_100
value: 0.9450000000000001, type: precision_at_1000
value: 0.104, type: precision_at_3
value: 15.153, type: precision_at_5
value: 11.065999999999999, type: recall_at_1
value: 23.631, type: recall_at_10
value: 64.145, type: recall_at_100
value: 89.41, type: recall_at_1000
value: 97.83500000000001, type: recall_at_3
value: 43.769000000000005, type: recall_at_5
value: 53.169, task: type: Classification
dataset: type: mteb/mtop_domain
name: MTEB MTOPDomainClassification (en)
config: en
split: test
revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
metrics: type: accuracy
value: 93.4108527131783, type: f1
value: 93.1415880261038, task: type: Classification
dataset: type: mteb/mtop_intent
name: MTEB MTOPIntentClassification (en)
config: en
split: test
revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
metrics: type: accuracy
value: 77.24806201550388, type: f1
value: 60.531916308197175, task: type: Classification
dataset: type: mteb/amazon_massive_intent
name: MTEB MassiveIntentClassification (en)
config: en
split: test
revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
metrics: type: accuracy
value: 73.71553463349024, type: f1
value: 71.70753174900791, task: type: Classification
dataset: type: mteb/amazon_massive_scenario
name: MTEB MassiveScenarioClassification (en)
config: en
split: test
revision: 7d571f92784cd94a019292a1f45445077d0ef634
metrics: type: accuracy
value: 77.79757901815736, type: f1
value: 77.83719850433258, task: type: Clustering
dataset: type: mteb/medrxiv-clustering-p2p
name: MTEB MedrxivClusteringP2P
config: default
split: test
revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
metrics: type: v_measure
value: 33.74193296622113, task: type: Clustering
dataset: type: mteb/medrxiv-clustering-s2s
name: MTEB MedrxivClusteringS2S
config: default
split: test
revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
metrics: type: v_measure
value: 30.64257594108566, task: type: Reranking
dataset: type: mteb/mind_small
name: MTEB MindSmallReranking
config: default
split: test
revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
metrics: type: map
value: 30.811018518883625, type: mrr
value: 31.910376577445003, task: type: Retrieval
dataset: type: nfcorpus
name: MTEB NFCorpus
config: default
split: test
revision: None
metrics: type: map_at_1
value: 5.409, type: map_at_10
value: 13.093, type: map_at_100
value: 16.256999999999998, type: map_at_1000
value: 17.617, type: map_at_3
value: 9.555, type: map_at_5
value: 11.428, type: mrr_at_1
value: 45.201, type: mrr_at_10
value: 54.179, type: mrr_at_100
value: 54.812000000000005, type: mrr_at_1000
value: 54.840999999999994, type: mrr_at_3
value: 51.909000000000006, type: mrr_at_5
value: 53.519000000000005, type: ndcg_at_1
value: 43.189, type: ndcg_at_10
value: 35.028, type: ndcg_at_100
value: 31.226, type: ndcg_at_1000
value: 39.678000000000004, type: ndcg_at_3
value: 40.596, type: ndcg_at_5
value: 38.75, type: precision_at_1
value: 44.582, type: precision_at_10
value: 25.974999999999998, type: precision_at_100
value: 7.793, type: precision_at_1000
value: 2.036, type: precision_at_3
value: 38.493, type: precision_at_5
value: 33.994, type: recall_at_1
value: 5.409, type: recall_at_10
value: 16.875999999999998, type: recall_at_100
value: 30.316, type: recall_at_1000
value: 60.891, type: recall_at_3
value: 10.688, type: recall_at_5
value: 13.832, task: type: Retrieval
dataset: type: nq
name: MTEB NQ
config: default
split: test
revision: None
metrics: type: map_at_1
value: 36.375, type: map_at_10
value: 51.991, type: map_at_100
value: 52.91400000000001, type: map_at_1000
value: 52.93600000000001, type: map_at_3
value: 48.014, type: map_at_5
value: 50.381, type: mrr_at_1
value: 40.759, type: mrr_at_10
value: 54.617000000000004, type: mrr_at_100
value: 55.301, type: mrr_at_1000
value: 55.315000000000005, type: mrr_at_3
value: 51.516, type: mrr_at_5
value: 53.435, type: ndcg_at_1
value: 40.759, type: ndcg_at_10
value: 59.384, type: ndcg_at_100
value: 63.157, type: ndcg_at_1000
value: 63.654999999999994, type: ndcg_at_3
value: 52.114000000000004, type: ndcg_at_5
value: 55.986000000000004, type: precision_at_1
value: 40.759, type: precision_at_10
value: 9.411999999999999, type: precision_at_100
value: 1.153, type: precision_at_1000
value: 0.12, type: precision_at_3
value: 23.329, type: precision_at_5
value: 16.256999999999998, type: recall_at_1
value: 36.375, type: recall_at_10
value: 79.053, type: recall_at_100
value: 95.167, type: recall_at_1000
value: 98.82, type: recall_at_3
value: 60.475, type: recall_at_5
value: 69.327, task: type: Retrieval
dataset: type: quora
name: MTEB QuoraRetrieval
config: default
split: test
revision: None
metrics: type: map_at_1
value: 70.256, type: map_at_10
value: 83.8, type: map_at_100
value: 84.425, type: map_at_1000
value: 84.444, type: map_at_3
value: 80.906, type: map_at_5
value: 82.717, type: mrr_at_1
value: 80.97999999999999, type: mrr_at_10
value: 87.161, type: mrr_at_100
value: 87.262, type: mrr_at_1000
value: 87.263, type: mrr_at_3
value: 86.175, type: mrr_at_5
value: 86.848, type: ndcg_at_1
value: 80.97999999999999, type: ndcg_at_10
value: 87.697, type: ndcg_at_100
value: 88.959, type: ndcg_at_1000
value: 89.09899999999999, type: ndcg_at_3
value: 84.83800000000001, type: ndcg_at_5
value: 86.401, type: precision_at_1
value: 80.97999999999999, type: precision_at_10
value: 13.261000000000001, type: precision_at_100
value: 1.5150000000000001, type: precision_at_1000
value: 0.156, type: precision_at_3
value: 37.01, type: precision_at_5
value: 24.298000000000002, type: recall_at_1
value: 70.256, type: recall_at_10
value: 94.935, type: recall_at_100
value: 99.274, type: recall_at_1000
value: 99.928, type: recall_at_3
value: 86.602, type: recall_at_5
value: 91.133, task: type: Clustering
dataset: type: mteb/reddit-clustering
name: MTEB RedditClustering
config: default
split: test
revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
metrics: type: v_measure
value: 56.322692497613104, task: type: Clustering
dataset: type: mteb/reddit-clustering-p2p
name: MTEB RedditClusteringP2P
config: default
split: test
revision: 282350215ef01743dc01b456c7f5241fa8937f16
metrics: type: v_measure
value: 61.895813503775074, task: type: Retrieval
dataset: type: scidocs
name: MTEB SCIDOCS
config: default
split: test
revision: None
metrics: type: map_at_1
value: 4.338, type: map_at_10
value: 10.767, type: map_at_100
value: 12.537999999999998, type: map_at_1000
value: 12.803999999999998, type: map_at_3
value: 7.788, type: map_at_5
value: 9.302000000000001, type: mrr_at_1
value: 21.4, type: mrr_at_10
value: 31.637999999999998, type: mrr_at_100
value: 32.688, type: mrr_at_1000
value: 32.756, type: mrr_at_3
value: 28.433000000000003, type: mrr_at_5
value: 30.178, type: ndcg_at_1
value: 21.4, type: ndcg_at_10
value: 18.293, type: ndcg_at_100
value: 25.274, type: ndcg_at_1000
value: 30.284, type: ndcg_at_3
value: 17.391000000000002, type: ndcg_at_5
value: 15.146999999999998, type: precision_at_1
value: 21.4, type: precision_at_10
value: 9.48, type: precision_at_100
value: 1.949, type: precision_at_1000
value: 0.316, type: precision_at_3
value: 16.167, type: precision_at_5
value: 13.22, type: recall_at_1
value: 4.338, type: recall_at_10
value: 19.213, type: recall_at_100
value: 39.562999999999995, type: recall_at_1000
value: 64.08, type: recall_at_3
value: 9.828000000000001, type: recall_at_5
value: 13.383000000000001, task: type: STS
dataset: type: mteb/sickr-sts
name: MTEB SICK-R
config: default
split: test
revision: a6ea5a8cab320b040a23452cc28066d9beae2cee
metrics: type: cos_sim_pearson
value: 82.42568163642142, type: cos_sim_spearman
value: 78.5797159641342, type: euclidean_pearson
value: 80.22151260811604, type: euclidean_spearman
value: 78.5797151953878, type: manhattan_pearson
value: 80.21224215864788, type: manhattan_spearman
value: 78.55641478381344, task: type: STS
dataset: type: mteb/sts12-sts
name: MTEB STS12
config: default
split: test
revision: a0d554a64d88156834ff5ae9920b964011b16384
metrics: type: cos_sim_pearson
value: 85.44020710812569, type: cos_sim_spearman
value: 78.91631735081286, type: euclidean_pearson
value: 81.64188964182102, type: euclidean_spearman
value: 78.91633286881678, type: manhattan_pearson
value: 81.69294748512496, type: manhattan_spearman
value: 78.93438558002656, task: type: STS
dataset: type: mteb/sts13-sts
name: MTEB STS13
config: default
split: test
revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
metrics: type: cos_sim_pearson
value: 84.27165426412311, type: cos_sim_spearman
value: 85.40429140249618, type: euclidean_pearson
value: 84.7509580724893, type: euclidean_spearman
value: 85.40429140249618, type: manhattan_pearson
value: 84.76488289321308, type: manhattan_spearman
value: 85.4256793698708, task: type: STS
dataset: type: mteb/sts14-sts
name: MTEB STS14
config: default
split: test
revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
metrics: type: cos_sim_pearson
value: 83.138851760732, type: cos_sim_spearman
value: 81.64101363896586, type: euclidean_pearson
value: 82.55165038934942, type: euclidean_spearman
value: 81.64105257080502, type: manhattan_pearson
value: 82.52802949883335, type: manhattan_spearman
value: 81.61255430718158, task: type: STS
dataset: type: mteb/sts15-sts
name: MTEB STS15
config: default
split: test
revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
metrics: type: cos_sim_pearson
value: 86.0654695484029, type: cos_sim_spearman
value: 87.20408521902229, type: euclidean_pearson
value: 86.8110651362115, type: euclidean_spearman
value: 87.20408521902229, type: manhattan_pearson
value: 86.77984656478691, type: manhattan_spearman
value: 87.1719947099227, task: type: STS
dataset: type: mteb/sts16-sts
name: MTEB STS16
config: default
split: test
revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
metrics: type: cos_sim_pearson
value: 83.77823915496512, type: cos_sim_spearman
value: 85.43566325729779, type: euclidean_pearson
value: 84.5396956658821, type: euclidean_spearman
value: 85.43566325729779, type: manhattan_pearson
value: 84.5665398848169, type: manhattan_spearman
value: 85.44375870303232, task: type: STS
dataset: type: mteb/sts17-crosslingual-sts
name: MTEB STS17 (en-en)
config: en-en
split: test
revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
metrics: type: cos_sim_pearson
value: 87.20030208471798, type: cos_sim_spearman
value: 87.20485505076539, type: euclidean_pearson
value: 88.10588324368722, type: euclidean_spearman
value: 87.20485505076539, type: manhattan_pearson
value: 87.92324770415183, type: manhattan_spearman
value: 87.0571314561877, task: type: STS
dataset: type: mteb/sts22-crosslingual-sts
name: MTEB STS22 (en)
config: en
split: test
revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80
metrics: type: cos_sim_pearson
value: 63.06093161604453, type: cos_sim_spearman
value: 64.2163140357722, type: euclidean_pearson
value: 65.27589680994006, type: euclidean_spearman
value: 64.2163140357722, type: manhattan_pearson
value: 65.45904383711101, type: manhattan_spearman
value: 64.55404716679305, task: type: STS
dataset: type: mteb/stsbenchmark-sts
name: MTEB STSBenchmark
config: default
split: test
revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
metrics: type: cos_sim_pearson
value: 84.32976164578706, type: cos_sim_spearman
value: 85.54302197678368, type: euclidean_pearson
value: 85.26307149193056, type: euclidean_spearman
value: 85.54302197678368, type: manhattan_pearson
value: 85.26647282029371, type: manhattan_spearman
value: 85.5316135265568, task: type: Reranking
dataset: type: mteb/scidocs-reranking
name: MTEB SciDocsRR
config: default
split: test
revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
metrics: type: map
value: 81.44675968318754, type: mrr
value: 94.92741826075158, task: type: Retrieval
dataset: type: scifact
name: MTEB SciFact
config: default
split: test
revision: None
metrics: type: map_at_1
value: 56.34400000000001, type: map_at_10
value: 65.927, type: map_at_100
value: 66.431, type: map_at_1000
value: 66.461, type: map_at_3
value: 63.529, type: map_at_5
value: 64.818, type: mrr_at_1
value: 59.333000000000006, type: mrr_at_10
value: 67.54599999999999, type: mrr_at_100
value: 67.892, type: mrr_at_1000
value: 67.917, type: mrr_at_3
value: 65.778, type: mrr_at_5
value: 66.794, type: ndcg_at_1
value: 59.333000000000006, type: ndcg_at_10
value: 70.5, type: ndcg_at_100
value: 72.688, type: ndcg_at_1000
value: 73.483, type: ndcg_at_3
value: 66.338, type: ndcg_at_5
value: 68.265, type: precision_at_1
value: 59.333000000000006, type: precision_at_10
value: 9.3, type: precision_at_100
value: 1.053, type: precision_at_1000
value: 0.11199999999999999, type: precision_at_3
value: 25.889, type: precision_at_5
value: 16.866999999999997, type: recall_at_1
value: 56.34400000000001, type: recall_at_10
value: 82.789, type: recall_at_100
value: 92.767, type: recall_at_1000
value: 99, type: recall_at_3
value: 71.64399999999999, type: recall_at_5
value: 76.322, task: type: PairClassification
dataset: type: mteb/sprintduplicatequestions-pairclassification
name: MTEB SprintDuplicateQuestions
config: default
split: test
revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
metrics: type: cos_sim_accuracy
value: 99.75742574257426, type: cos_sim_ap
value: 93.52081548447406, type: cos_sim_f1
value: 87.33850129198966, type: cos_sim_precision
value: 90.37433155080214, type: cos_sim_recall
value: 84.5, type: dot_accuracy
value: 99.75742574257426, type: dot_ap
value: 93.52081548447406, type: dot_f1
value: 87.33850129198966, type: dot_precision
value: 90.37433155080214, type: dot_recall
value: 84.5, type: euclidean_accuracy
value: 99.75742574257426, type: euclidean_ap
value: 93.52081548447406, type: euclidean_f1
value: 87.33850129198966, type: euclidean_precision
value: 90.37433155080214, type: euclidean_recall
value: 84.5, type: manhattan_accuracy
value: 99.75841584158415, type: manhattan_ap
value: 93.4975678585854, type: manhattan_f1
value: 87.26708074534162, type: manhattan_precision
value: 90.45064377682404, type: manhattan_recall
value: 84.3, type: max_accuracy
value: 99.75841584158415, type: max_ap
value: 93.52081548447406, type: max_f1
value: 87.33850129198966, task: type: Clustering
dataset: type: mteb/stackexchange-clustering
name: MTEB StackExchangeClustering
config: default
split: test
revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
metrics: type: v_measure
value: 64.31437036686651, task: type: Clustering
dataset: type: mteb/stackexchange-clustering-p2p
name: MTEB StackExchangeClusteringP2P
config: default
split: test
revision: 815ca46b2622cec33ccafc3735d572c266efdb44
metrics: type: v_measure
value: 33.25569319007206, task: type: Reranking
dataset: type: mteb/stackoverflowdupquestions-reranking
name: MTEB StackOverflowDupQuestions
config: default
split: test
revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
metrics: type: map
value: 49.90474939720706, type: mrr
value: 50.568115503777264, task: type: Summarization
dataset: type: mteb/summeval
name: MTEB SummEval
config: default
split: test
revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
metrics: type: cos_sim_pearson
value: 29.866828641244712, type: cos_sim_spearman
value: 30.077555055873866, type: dot_pearson
value: 29.866832988572266, type: dot_spearman
value: 30.077555055873866, task: type: Retrieval
dataset: type: trec-covid
name: MTEB TRECCOVID
config: default
split: test
revision: None
metrics: type: map_at_1
value: 0.232, type: map_at_10
value: 2.094, type: map_at_100
value: 11.971, type: map_at_1000
value: 28.158, type: map_at_3
value: 0.688, type: map_at_5
value: 1.114, type: mrr_at_1
value: 88, type: mrr_at_10
value: 93.4, type: mrr_at_100
value: 93.4, type: mrr_at_1000
value: 93.4, type: mrr_at_3
value: 93, type: mrr_at_5
value: 93.4, type: ndcg_at_1
value: 84, type: ndcg_at_10
value: 79.923, type: ndcg_at_100
value: 61.17, type: ndcg_at_1000
value: 53.03, type: ndcg_at_3
value: 84.592, type: ndcg_at_5
value: 82.821, type: precision_at_1
value: 88, type: precision_at_10
value: 85, type: precision_at_100
value: 63.019999999999996, type: precision_at_1000
value: 23.554, type: precision_at_3
value: 89.333, type: precision_at_5
value: 87.2, type: recall_at_1
value: 0.232, type: recall_at_10
value: 2.255, type: recall_at_100
value: 14.823, type: recall_at_1000
value: 49.456, type: recall_at_3
value: 0.718, type: recall_at_5
value: 1.175, task: type: Retrieval
dataset: type: webis-touche2020
name: MTEB Touche2020
config: default
split: test
revision: None
metrics: type: map_at_1
value: 2.547, type: map_at_10
value: 11.375, type: map_at_100
value: 18.194, type: map_at_1000
value: 19.749, type: map_at_3
value: 5.825, type: map_at_5
value: 8.581, type: mrr_at_1
value: 32.653, type: mrr_at_10
value: 51.32, type: mrr_at_100
value: 51.747, type: mrr_at_1000
value: 51.747, type: mrr_at_3
value: 47.278999999999996, type: mrr_at_5
value: 48.605, type: ndcg_at_1
value: 29.592000000000002, type: ndcg_at_10
value: 28.151, type: ndcg_at_100
value: 39.438, type: ndcg_at_1000
value: 50.769, type: ndcg_at_3
value: 30.758999999999997, type: ndcg_at_5
value: 30.366, type: precision_at_1
value: 32.653, type: precision_at_10
value: 25.714, type: precision_at_100
value: 8.041, type: precision_at_1000
value: 1.555, type: precision_at_3
value: 33.333, type: precision_at_5
value: 31.837, type: recall_at_1
value: 2.547, type: recall_at_10
value: 18.19, type: recall_at_100
value: 49.538, type: recall_at_1000
value: 83.86, type: recall_at_3
value: 7.329, type: recall_at_5
value: 11.532, task: type: Classification
dataset: type: mteb/toxic_conversations_50k
name: MTEB ToxicConversationsClassification
config: default
split: test
revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
metrics: type: accuracy
value: 71.4952, type: ap
value: 14.793362635531409, type: f1
value: 55.204635551516915, task: type: Classification
dataset: type: mteb/tweet_sentiment_extraction
name: MTEB TweetSentimentExtractionClassification
config: default
split: test
revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
metrics: type: accuracy
value: 61.5365025466893, type: f1
value: 61.81742556334845, task: type: Clustering
dataset: type: mteb/twentynewsgroups-clustering
name: MTEB TwentyNewsgroupsClustering
config: default
split: test
revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
metrics: type: v_measure
value: 49.05531070301185, task: type: PairClassification
dataset: type: mteb/twittersemeval2015-pairclassification
name: MTEB TwitterSemEval2015
config: default
split: test
revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
metrics: type: cos_sim_accuracy
value: 86.51725576682364, type: cos_sim_ap
value: 75.2292304265163, type: cos_sim_f1
value: 69.54022988505749, type: cos_sim_precision
value: 63.65629110039457, type: cos_sim_recall
value: 76.62269129287598, type: dot_accuracy
value: 86.51725576682364, type: dot_ap
value: 75.22922386081054, type: dot_f1
value: 69.54022988505749, type: dot_precision
value: 63.65629110039457, type: dot_recall
value: 76.62269129287598, type: euclidean_accuracy
value: 86.51725576682364, type: euclidean_ap
value: 75.22925730473472, type: euclidean_f1
value: 69.54022988505749, type: euclidean_precision
value: 63.65629110039457, type: euclidean_recall
value: 76.62269129287598, type: manhattan_accuracy
value: 86.52321630804077, type: manhattan_ap
value: 75.20608115037336, type: manhattan_f1
value: 69.60000000000001, type: manhattan_precision
value: 64.37219730941705, type: manhattan_recall
value: 75.75197889182058, type: max_accuracy
value: 86.52321630804077, type: max_ap
value: 75.22925730473472, type: max_f1
value: 69.60000000000001, task: type: PairClassification
dataset: type: mteb/twitterurlcorpus-pairclassification
name: MTEB TwitterURLCorpus
config: default
split: test
revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
metrics: type: cos_sim_accuracy
value: 89.34877944657896, type: cos_sim_ap
value: 86.71257569277373, type: cos_sim_f1
value: 79.10386355986088, type: cos_sim_precision
value: 76.91468470434214, type: cos_sim_recall
value: 81.4213119802895, type: dot_accuracy
value: 89.34877944657896, type: dot_ap
value: 86.71257133133368, type: dot_f1
value: 79.10386355986088, type: dot_precision
value: 76.91468470434214, type: dot_recall
value: 81.4213119802895, type: euclidean_accuracy
value: 89.34877944657896, type: euclidean_ap
value: 86.71257651501476, type: euclidean_f1
value: 79.10386355986088, type: euclidean_precision
value: 76.91468470434214, type: euclidean_recall
value: 81.4213119802895, type: manhattan_accuracy
value: 89.35848177901967, type: manhattan_ap
value: 86.69330615469126, type: manhattan_f1
value: 79.13867741453949, type: manhattan_precision
value: 76.78881807647741, type: manhattan_recall
value: 81.63689559593472, type: max_accuracy
value: 89.35848177901967, type: max_ap
value: 86.71257651501476, type: max_f1
value: 79.13867741453949
license: apache-2.0
language: en
new_version: nomic-ai/nomic-embed-text-v1.5
title: API endpoint 
sdk: docker
Tags: docker, feature-extraction, sentence-similarity, mteb, transformers, transformers.js, region:us