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Parent(s):
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Update README.md
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README.md
CHANGED
@@ -13,6 +13,8 @@ model-index:
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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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metrics:
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- type: accuracy
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value: 67.56716417910448
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@@ -25,6 +27,8 @@ model-index:
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dataset:
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type: mteb/amazon_polarity
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name: MTEB AmazonPolarityClassification
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metrics:
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- type: accuracy
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value: 71.439575
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@@ -37,6 +41,8 @@ model-index:
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dataset:
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type: mteb/amazon_reviews_multi
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name: MTEB AmazonReviewsClassification (en)
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metrics:
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- type: accuracy
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value: 35.748000000000005
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@@ -47,6 +53,8 @@ model-index:
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dataset:
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type: arguana
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name: MTEB ArguAna
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metrics:
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- type: map_at_1
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value: 25.96
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@@ -113,6 +121,8 @@ model-index:
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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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metrics:
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- type: v_measure
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value: 44.72125714642202
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@@ -121,6 +131,8 @@ model-index:
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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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metrics:
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- type: v_measure
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value: 35.081451519142064
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@@ -129,6 +141,8 @@ model-index:
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dataset:
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type: mteb/askubuntudupquestions-reranking
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name: MTEB AskUbuntuDupQuestions
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metrics:
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- type: map
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value: 59.634661990392054
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@@ -139,6 +153,8 @@ model-index:
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dataset:
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type: mteb/biosses-sts
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name: MTEB BIOSSES
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metrics:
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- type: cos_sim_pearson
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value: 87.42754550496836
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@@ -157,6 +173,8 @@ model-index:
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dataset:
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type: mteb/banking77
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name: MTEB Banking77Classification
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metrics:
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- type: accuracy
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value: 83.21753246753246
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@@ -167,6 +185,8 @@ model-index:
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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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metrics:
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- type: v_measure
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value: 34.41414219680629
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@@ -175,6 +195,8 @@ model-index:
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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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metrics:
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- type: v_measure
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value: 30.533275862270028
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@@ -183,6 +205,8 @@ model-index:
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dataset:
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type: BeIR/cqadupstack
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name: MTEB CQADupstackAndroidRetrieval
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metrics:
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- type: map_at_1
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value: 30.808999999999997
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@@ -249,6 +273,8 @@ model-index:
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dataset:
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type: BeIR/cqadupstack
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name: MTEB CQADupstackEnglishRetrieval
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metrics:
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- type: map_at_1
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value: 26.962000000000003
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@@ -315,6 +341,8 @@ model-index:
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dataset:
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type: BeIR/cqadupstack
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name: MTEB CQADupstackGamingRetrieval
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metrics:
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- type: map_at_1
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value: 36.318
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@@ -381,6 +409,8 @@ model-index:
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dataset:
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type: BeIR/cqadupstack
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name: MTEB CQADupstackGisRetrieval
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metrics:
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- type: map_at_1
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value: 22.167
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@@ -447,6 +477,8 @@ model-index:
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dataset:
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type: BeIR/cqadupstack
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name: MTEB CQADupstackMathematicaRetrieval
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metrics:
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- type: map_at_1
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value: 12.033000000000001
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@@ -513,6 +545,8 @@ model-index:
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dataset:
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type: BeIR/cqadupstack
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name: MTEB CQADupstackPhysicsRetrieval
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metrics:
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- type: map_at_1
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value: 26.651000000000003
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@@ -579,6 +613,8 @@ model-index:
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dataset:
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type: BeIR/cqadupstack
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name: MTEB CQADupstackProgrammersRetrieval
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metrics:
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- type: map_at_1
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value: 22.589000000000002
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@@ -645,6 +681,8 @@ model-index:
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dataset:
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type: BeIR/cqadupstack
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name: MTEB CQADupstackRetrieval
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metrics:
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- type: map_at_1
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value: 23.190833333333334
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@@ -711,6 +749,8 @@ model-index:
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dataset:
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type: BeIR/cqadupstack
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name: MTEB CQADupstackStatsRetrieval
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metrics:
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- type: map_at_1
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value: 20.409
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@@ -777,6 +817,8 @@ model-index:
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dataset:
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type: BeIR/cqadupstack
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name: MTEB CQADupstackTexRetrieval
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metrics:
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- type: map_at_1
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value: 14.549000000000001
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@@ -843,6 +885,8 @@ model-index:
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dataset:
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type: BeIR/cqadupstack
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name: MTEB CQADupstackUnixRetrieval
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metrics:
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- type: map_at_1
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value: 23.286
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@@ -909,6 +953,8 @@ model-index:
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dataset:
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type: BeIR/cqadupstack
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name: MTEB CQADupstackWebmastersRetrieval
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metrics:
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- type: map_at_1
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value: 23.962
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@@ -975,6 +1021,8 @@ model-index:
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dataset:
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type: BeIR/cqadupstack
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name: MTEB CQADupstackWordpressRetrieval
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metrics:
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- type: map_at_1
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value: 18.555
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@@ -1041,6 +1089,8 @@ model-index:
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dataset:
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type: climate-fever
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name: MTEB ClimateFEVER
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metrics:
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- type: map_at_1
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value: 10.366999999999999
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@@ -1107,6 +1157,8 @@ model-index:
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dataset:
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type: dbpedia-entity
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name: MTEB DBPedia
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metrics:
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- type: map_at_1
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value: 8.246
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@@ -1173,6 +1225,8 @@ model-index:
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dataset:
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type: mteb/emotion
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name: MTEB EmotionClassification
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metrics:
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- type: accuracy
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value: 49.214999999999996
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@@ -1183,6 +1237,8 @@ model-index:
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dataset:
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type: fever
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name: MTEB FEVER
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metrics:
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- type: map_at_1
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value: 56.769000000000005
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@@ -1249,6 +1305,8 @@ model-index:
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dataset:
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type: fiqa
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name: MTEB FiQA2018
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metrics:
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- type: map_at_1
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value: 15.753
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@@ -1315,6 +1373,8 @@ model-index:
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dataset:
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type: hotpotqa
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name: MTEB HotpotQA
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metrics:
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- type: map_at_1
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value: 32.153999999999996
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@@ -1381,6 +1441,8 @@ model-index:
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dataset:
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type: mteb/imdb
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name: MTEB ImdbClassification
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metrics:
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- type: accuracy
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value: 63.5316
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@@ -1393,6 +1455,8 @@ model-index:
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dataset:
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type: msmarco
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name: MTEB MSMARCO
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metrics:
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- type: map_at_1
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value: 20.566000000000003
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@@ -1459,6 +1523,8 @@ model-index:
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dataset:
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type: mteb/mtop_domain
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name: MTEB MTOPDomainClassification (en)
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metrics:
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- type: accuracy
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value: 92.56269949840402
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@@ -1469,6 +1535,8 @@ model-index:
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dataset:
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type: mteb/mtop_intent
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name: MTEB MTOPIntentClassification (en)
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metrics:
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- type: accuracy
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value: 71.8467852257182
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@@ -1479,6 +1547,8 @@ model-index:
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dataset:
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type: mteb/amazon_massive_intent
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name: MTEB MassiveIntentClassification (en)
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metrics:
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- type: accuracy
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value: 69.00806993947546
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@@ -1489,6 +1559,8 @@ model-index:
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dataset:
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type: mteb/amazon_massive_scenario
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name: MTEB MassiveScenarioClassification (en)
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metrics:
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- type: accuracy
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value: 75.90114324142569
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@@ -1499,6 +1571,8 @@ model-index:
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dataset:
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type: mteb/medrxiv-clustering-p2p
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name: MTEB MedrxivClusteringP2P
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metrics:
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- type: v_measure
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value: 31.350109978273395
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@@ -1507,6 +1581,8 @@ model-index:
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dataset:
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type: mteb/medrxiv-clustering-s2s
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name: MTEB MedrxivClusteringS2S
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metrics:
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- type: v_measure
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value: 28.768923695767327
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@@ -1515,6 +1591,8 @@ model-index:
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dataset:
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type: mteb/mind_small
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name: MTEB MindSmallReranking
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metrics:
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- type: map
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value: 31.716396735210754
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@@ -1525,6 +1603,8 @@ model-index:
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dataset:
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type: nfcorpus
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name: MTEB NFCorpus
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metrics:
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- type: map_at_1
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value: 5.604
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dataset:
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type: nq
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name: MTEB NQ
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metrics:
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- type: map_at_1
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value: 25.881
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@@ -1657,6 +1739,8 @@ model-index:
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dataset:
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type: quora
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name: MTEB QuoraRetrieval
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metrics:
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- type: map_at_1
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value: 67.553
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@@ -1723,6 +1807,8 @@ model-index:
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dataset:
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type: mteb/reddit-clustering
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name: MTEB RedditClustering
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metrics:
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- type: v_measure
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value: 46.46887711230235
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@@ -1731,6 +1817,8 @@ model-index:
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dataset:
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type: mteb/reddit-clustering-p2p
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name: MTEB RedditClusteringP2P
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metrics:
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- type: v_measure
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value: 54.166876298246926
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@@ -1739,6 +1827,8 @@ model-index:
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dataset:
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type: scidocs
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name: MTEB SCIDOCS
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metrics:
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- type: map_at_1
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value: 4.053
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@@ -1805,6 +1895,8 @@ model-index:
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dataset:
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type: mteb/sickr-sts
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name: MTEB SICK-R
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metrics:
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- type: cos_sim_pearson
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value: 77.7548748519677
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@@ -1823,6 +1915,8 @@ model-index:
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dataset:
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type: mteb/sts12-sts
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name: MTEB STS12
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metrics:
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- type: cos_sim_pearson
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value: 75.91051402657887
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dataset:
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type: mteb/sts13-sts
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name: MTEB STS13
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metrics:
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- type: cos_sim_pearson
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value: 77.23835466417793
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dataset:
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type: mteb/sts14-sts
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name: MTEB STS14
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metrics:
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- type: cos_sim_pearson
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value: 77.91692485139602
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@@ -1877,6 +1975,8 @@ model-index:
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dataset:
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type: mteb/sts15-sts
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name: MTEB STS15
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metrics:
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- type: cos_sim_pearson
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value: 82.13422113617578
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@@ -1895,6 +1995,8 @@ model-index:
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dataset:
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type: mteb/sts16-sts
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name: MTEB STS16
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metrics:
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- type: cos_sim_pearson
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value: 79.07989542843826
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@@ -1913,6 +2015,8 @@ model-index:
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dataset:
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type: mteb/sts17-crosslingual-sts
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name: MTEB STS17 (en-en)
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metrics:
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- type: cos_sim_pearson
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value: 87.0420983224933
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@@ -1931,6 +2035,8 @@ model-index:
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dataset:
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type: mteb/sts22-crosslingual-sts
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name: MTEB STS22 (en)
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metrics:
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- type: cos_sim_pearson
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value: 68.47031320016424
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@@ -1949,6 +2055,8 @@ model-index:
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dataset:
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type: mteb/stsbenchmark-sts
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name: MTEB STSBenchmark
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metrics:
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- type: cos_sim_pearson
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value: 80.79514366062675
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@@ -1967,6 +2075,8 @@ model-index:
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dataset:
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type: mteb/scidocs-reranking
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name: MTEB SciDocsRR
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metrics:
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- type: map
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value: 77.71580844366375
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@@ -1977,6 +2087,8 @@ model-index:
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dataset:
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type: scifact
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name: MTEB SciFact
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metrics:
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- type: map_at_1
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value: 56.39999999999999
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@@ -2043,6 +2155,8 @@ model-index:
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dataset:
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type: mteb/sprintduplicatequestions-pairclassification
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name: MTEB SprintDuplicateQuestions
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|
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metrics:
|
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- type: cos_sim_accuracy
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value: 99.76831683168317
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@@ -2095,6 +2209,8 @@ model-index:
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dataset:
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type: mteb/stackexchange-clustering
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name: MTEB StackExchangeClustering
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|
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metrics:
|
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- type: v_measure
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value: 59.194098673976484
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@@ -2103,6 +2219,8 @@ model-index:
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dataset:
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type: mteb/stackexchange-clustering-p2p
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name: MTEB StackExchangeClusteringP2P
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|
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metrics:
|
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- type: v_measure
|
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value: 32.5744032578115
|
@@ -2111,6 +2229,8 @@ model-index:
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dataset:
|
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type: mteb/stackoverflowdupquestions-reranking
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name: MTEB StackOverflowDupQuestions
|
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|
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metrics:
|
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- type: map
|
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value: 49.61186384154483
|
@@ -2121,6 +2241,8 @@ model-index:
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dataset:
|
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type: mteb/summeval
|
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name: MTEB SummEval
|
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|
2124 |
metrics:
|
2125 |
- type: cos_sim_pearson
|
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value: 26.047224542079068
|
@@ -2135,6 +2257,8 @@ model-index:
|
|
2135 |
dataset:
|
2136 |
type: trec-covid
|
2137 |
name: MTEB TRECCOVID
|
|
|
|
|
2138 |
metrics:
|
2139 |
- type: map_at_1
|
2140 |
value: 0.22300000000000003
|
@@ -2201,6 +2325,8 @@ model-index:
|
|
2201 |
dataset:
|
2202 |
type: webis-touche2020
|
2203 |
name: MTEB Touche2020
|
|
|
|
|
2204 |
metrics:
|
2205 |
- type: map_at_1
|
2206 |
value: 3.047
|
@@ -2267,6 +2393,8 @@ model-index:
|
|
2267 |
dataset:
|
2268 |
type: mteb/toxic_conversations_50k
|
2269 |
name: MTEB ToxicConversationsClassification
|
|
|
|
|
2270 |
metrics:
|
2271 |
- type: accuracy
|
2272 |
value: 68.84080000000002
|
@@ -2279,6 +2407,8 @@ model-index:
|
|
2279 |
dataset:
|
2280 |
type: mteb/tweet_sentiment_extraction
|
2281 |
name: MTEB TweetSentimentExtractionClassification
|
|
|
|
|
2282 |
metrics:
|
2283 |
- type: accuracy
|
2284 |
value: 56.68647425014149
|
@@ -2289,6 +2419,8 @@ model-index:
|
|
2289 |
dataset:
|
2290 |
type: mteb/twentynewsgroups-clustering
|
2291 |
name: MTEB TwentyNewsgroupsClustering
|
|
|
|
|
2292 |
metrics:
|
2293 |
- type: v_measure
|
2294 |
value: 40.8911707239219
|
@@ -2297,6 +2429,8 @@ model-index:
|
|
2297 |
dataset:
|
2298 |
type: mteb/twittersemeval2015-pairclassification
|
2299 |
name: MTEB TwitterSemEval2015
|
|
|
|
|
2300 |
metrics:
|
2301 |
- type: cos_sim_accuracy
|
2302 |
value: 83.04226023722954
|
@@ -2349,6 +2483,8 @@ model-index:
|
|
2349 |
dataset:
|
2350 |
type: mteb/twitterurlcorpus-pairclassification
|
2351 |
name: MTEB TwitterURLCorpus
|
|
|
|
|
2352 |
metrics:
|
2353 |
- type: cos_sim_accuracy
|
2354 |
value: 88.56871191834517
|
@@ -2461,4 +2597,4 @@ SentenceTransformer(
|
|
2461 |
journal={arXiv preprint arXiv:2202.08904},
|
2462 |
year={2022}
|
2463 |
}
|
2464 |
-
```
|
|
|
13 |
dataset:
|
14 |
type: mteb/amazon_counterfactual
|
15 |
name: MTEB AmazonCounterfactualClassification (en)
|
16 |
+
config: en
|
17 |
+
split: test
|
18 |
metrics:
|
19 |
- type: accuracy
|
20 |
value: 67.56716417910448
|
|
|
27 |
dataset:
|
28 |
type: mteb/amazon_polarity
|
29 |
name: MTEB AmazonPolarityClassification
|
30 |
+
config: default
|
31 |
+
split: test
|
32 |
metrics:
|
33 |
- type: accuracy
|
34 |
value: 71.439575
|
|
|
41 |
dataset:
|
42 |
type: mteb/amazon_reviews_multi
|
43 |
name: MTEB AmazonReviewsClassification (en)
|
44 |
+
config: en
|
45 |
+
split: test
|
46 |
metrics:
|
47 |
- type: accuracy
|
48 |
value: 35.748000000000005
|
|
|
53 |
dataset:
|
54 |
type: arguana
|
55 |
name: MTEB ArguAna
|
56 |
+
config: default
|
57 |
+
split: test
|
58 |
metrics:
|
59 |
- type: map_at_1
|
60 |
value: 25.96
|
|
|
121 |
dataset:
|
122 |
type: mteb/arxiv-clustering-p2p
|
123 |
name: MTEB ArxivClusteringP2P
|
124 |
+
config: default
|
125 |
+
split: test
|
126 |
metrics:
|
127 |
- type: v_measure
|
128 |
value: 44.72125714642202
|
|
|
131 |
dataset:
|
132 |
type: mteb/arxiv-clustering-s2s
|
133 |
name: MTEB ArxivClusteringS2S
|
134 |
+
config: default
|
135 |
+
split: test
|
136 |
metrics:
|
137 |
- type: v_measure
|
138 |
value: 35.081451519142064
|
|
|
141 |
dataset:
|
142 |
type: mteb/askubuntudupquestions-reranking
|
143 |
name: MTEB AskUbuntuDupQuestions
|
144 |
+
config: default
|
145 |
+
split: test
|
146 |
metrics:
|
147 |
- type: map
|
148 |
value: 59.634661990392054
|
|
|
153 |
dataset:
|
154 |
type: mteb/biosses-sts
|
155 |
name: MTEB BIOSSES
|
156 |
+
config: default
|
157 |
+
split: test
|
158 |
metrics:
|
159 |
- type: cos_sim_pearson
|
160 |
value: 87.42754550496836
|
|
|
173 |
dataset:
|
174 |
type: mteb/banking77
|
175 |
name: MTEB Banking77Classification
|
176 |
+
config: default
|
177 |
+
split: test
|
178 |
metrics:
|
179 |
- type: accuracy
|
180 |
value: 83.21753246753246
|
|
|
185 |
dataset:
|
186 |
type: mteb/biorxiv-clustering-p2p
|
187 |
name: MTEB BiorxivClusteringP2P
|
188 |
+
config: default
|
189 |
+
split: test
|
190 |
metrics:
|
191 |
- type: v_measure
|
192 |
value: 34.41414219680629
|
|
|
195 |
dataset:
|
196 |
type: mteb/biorxiv-clustering-s2s
|
197 |
name: MTEB BiorxivClusteringS2S
|
198 |
+
config: default
|
199 |
+
split: test
|
200 |
metrics:
|
201 |
- type: v_measure
|
202 |
value: 30.533275862270028
|
|
|
205 |
dataset:
|
206 |
type: BeIR/cqadupstack
|
207 |
name: MTEB CQADupstackAndroidRetrieval
|
208 |
+
config: default
|
209 |
+
split: test
|
210 |
metrics:
|
211 |
- type: map_at_1
|
212 |
value: 30.808999999999997
|
|
|
273 |
dataset:
|
274 |
type: BeIR/cqadupstack
|
275 |
name: MTEB CQADupstackEnglishRetrieval
|
276 |
+
config: default
|
277 |
+
split: test
|
278 |
metrics:
|
279 |
- type: map_at_1
|
280 |
value: 26.962000000000003
|
|
|
341 |
dataset:
|
342 |
type: BeIR/cqadupstack
|
343 |
name: MTEB CQADupstackGamingRetrieval
|
344 |
+
config: default
|
345 |
+
split: test
|
346 |
metrics:
|
347 |
- type: map_at_1
|
348 |
value: 36.318
|
|
|
409 |
dataset:
|
410 |
type: BeIR/cqadupstack
|
411 |
name: MTEB CQADupstackGisRetrieval
|
412 |
+
config: default
|
413 |
+
split: test
|
414 |
metrics:
|
415 |
- type: map_at_1
|
416 |
value: 22.167
|
|
|
477 |
dataset:
|
478 |
type: BeIR/cqadupstack
|
479 |
name: MTEB CQADupstackMathematicaRetrieval
|
480 |
+
config: default
|
481 |
+
split: test
|
482 |
metrics:
|
483 |
- type: map_at_1
|
484 |
value: 12.033000000000001
|
|
|
545 |
dataset:
|
546 |
type: BeIR/cqadupstack
|
547 |
name: MTEB CQADupstackPhysicsRetrieval
|
548 |
+
config: default
|
549 |
+
split: test
|
550 |
metrics:
|
551 |
- type: map_at_1
|
552 |
value: 26.651000000000003
|
|
|
613 |
dataset:
|
614 |
type: BeIR/cqadupstack
|
615 |
name: MTEB CQADupstackProgrammersRetrieval
|
616 |
+
config: default
|
617 |
+
split: test
|
618 |
metrics:
|
619 |
- type: map_at_1
|
620 |
value: 22.589000000000002
|
|
|
681 |
dataset:
|
682 |
type: BeIR/cqadupstack
|
683 |
name: MTEB CQADupstackRetrieval
|
684 |
+
config: default
|
685 |
+
split: test
|
686 |
metrics:
|
687 |
- type: map_at_1
|
688 |
value: 23.190833333333334
|
|
|
749 |
dataset:
|
750 |
type: BeIR/cqadupstack
|
751 |
name: MTEB CQADupstackStatsRetrieval
|
752 |
+
config: default
|
753 |
+
split: test
|
754 |
metrics:
|
755 |
- type: map_at_1
|
756 |
value: 20.409
|
|
|
817 |
dataset:
|
818 |
type: BeIR/cqadupstack
|
819 |
name: MTEB CQADupstackTexRetrieval
|
820 |
+
config: default
|
821 |
+
split: test
|
822 |
metrics:
|
823 |
- type: map_at_1
|
824 |
value: 14.549000000000001
|
|
|
885 |
dataset:
|
886 |
type: BeIR/cqadupstack
|
887 |
name: MTEB CQADupstackUnixRetrieval
|
888 |
+
config: default
|
889 |
+
split: test
|
890 |
metrics:
|
891 |
- type: map_at_1
|
892 |
value: 23.286
|
|
|
953 |
dataset:
|
954 |
type: BeIR/cqadupstack
|
955 |
name: MTEB CQADupstackWebmastersRetrieval
|
956 |
+
config: default
|
957 |
+
split: test
|
958 |
metrics:
|
959 |
- type: map_at_1
|
960 |
value: 23.962
|
|
|
1021 |
dataset:
|
1022 |
type: BeIR/cqadupstack
|
1023 |
name: MTEB CQADupstackWordpressRetrieval
|
1024 |
+
config: default
|
1025 |
+
split: test
|
1026 |
metrics:
|
1027 |
- type: map_at_1
|
1028 |
value: 18.555
|
|
|
1089 |
dataset:
|
1090 |
type: climate-fever
|
1091 |
name: MTEB ClimateFEVER
|
1092 |
+
config: default
|
1093 |
+
split: test
|
1094 |
metrics:
|
1095 |
- type: map_at_1
|
1096 |
value: 10.366999999999999
|
|
|
1157 |
dataset:
|
1158 |
type: dbpedia-entity
|
1159 |
name: MTEB DBPedia
|
1160 |
+
config: default
|
1161 |
+
split: test
|
1162 |
metrics:
|
1163 |
- type: map_at_1
|
1164 |
value: 8.246
|
|
|
1225 |
dataset:
|
1226 |
type: mteb/emotion
|
1227 |
name: MTEB EmotionClassification
|
1228 |
+
config: default
|
1229 |
+
split: test
|
1230 |
metrics:
|
1231 |
- type: accuracy
|
1232 |
value: 49.214999999999996
|
|
|
1237 |
dataset:
|
1238 |
type: fever
|
1239 |
name: MTEB FEVER
|
1240 |
+
config: default
|
1241 |
+
split: test
|
1242 |
metrics:
|
1243 |
- type: map_at_1
|
1244 |
value: 56.769000000000005
|
|
|
1305 |
dataset:
|
1306 |
type: fiqa
|
1307 |
name: MTEB FiQA2018
|
1308 |
+
config: default
|
1309 |
+
split: test
|
1310 |
metrics:
|
1311 |
- type: map_at_1
|
1312 |
value: 15.753
|
|
|
1373 |
dataset:
|
1374 |
type: hotpotqa
|
1375 |
name: MTEB HotpotQA
|
1376 |
+
config: default
|
1377 |
+
split: test
|
1378 |
metrics:
|
1379 |
- type: map_at_1
|
1380 |
value: 32.153999999999996
|
|
|
1441 |
dataset:
|
1442 |
type: mteb/imdb
|
1443 |
name: MTEB ImdbClassification
|
1444 |
+
config: default
|
1445 |
+
split: test
|
1446 |
metrics:
|
1447 |
- type: accuracy
|
1448 |
value: 63.5316
|
|
|
1455 |
dataset:
|
1456 |
type: msmarco
|
1457 |
name: MTEB MSMARCO
|
1458 |
+
config: default
|
1459 |
+
split: validation
|
1460 |
metrics:
|
1461 |
- type: map_at_1
|
1462 |
value: 20.566000000000003
|
|
|
1523 |
dataset:
|
1524 |
type: mteb/mtop_domain
|
1525 |
name: MTEB MTOPDomainClassification (en)
|
1526 |
+
config: en
|
1527 |
+
split: test
|
1528 |
metrics:
|
1529 |
- type: accuracy
|
1530 |
value: 92.56269949840402
|
|
|
1535 |
dataset:
|
1536 |
type: mteb/mtop_intent
|
1537 |
name: MTEB MTOPIntentClassification (en)
|
1538 |
+
config: en
|
1539 |
+
split: test
|
1540 |
metrics:
|
1541 |
- type: accuracy
|
1542 |
value: 71.8467852257182
|
|
|
1547 |
dataset:
|
1548 |
type: mteb/amazon_massive_intent
|
1549 |
name: MTEB MassiveIntentClassification (en)
|
1550 |
+
config: en
|
1551 |
+
split: test
|
1552 |
metrics:
|
1553 |
- type: accuracy
|
1554 |
value: 69.00806993947546
|
|
|
1559 |
dataset:
|
1560 |
type: mteb/amazon_massive_scenario
|
1561 |
name: MTEB MassiveScenarioClassification (en)
|
1562 |
+
config: en
|
1563 |
+
split: test
|
1564 |
metrics:
|
1565 |
- type: accuracy
|
1566 |
value: 75.90114324142569
|
|
|
1571 |
dataset:
|
1572 |
type: mteb/medrxiv-clustering-p2p
|
1573 |
name: MTEB MedrxivClusteringP2P
|
1574 |
+
config: default
|
1575 |
+
split: test
|
1576 |
metrics:
|
1577 |
- type: v_measure
|
1578 |
value: 31.350109978273395
|
|
|
1581 |
dataset:
|
1582 |
type: mteb/medrxiv-clustering-s2s
|
1583 |
name: MTEB MedrxivClusteringS2S
|
1584 |
+
config: default
|
1585 |
+
split: test
|
1586 |
metrics:
|
1587 |
- type: v_measure
|
1588 |
value: 28.768923695767327
|
|
|
1591 |
dataset:
|
1592 |
type: mteb/mind_small
|
1593 |
name: MTEB MindSmallReranking
|
1594 |
+
config: default
|
1595 |
+
split: test
|
1596 |
metrics:
|
1597 |
- type: map
|
1598 |
value: 31.716396735210754
|
|
|
1603 |
dataset:
|
1604 |
type: nfcorpus
|
1605 |
name: MTEB NFCorpus
|
1606 |
+
config: default
|
1607 |
+
split: test
|
1608 |
metrics:
|
1609 |
- type: map_at_1
|
1610 |
value: 5.604
|
|
|
1671 |
dataset:
|
1672 |
type: nq
|
1673 |
name: MTEB NQ
|
1674 |
+
config: default
|
1675 |
+
split: test
|
1676 |
metrics:
|
1677 |
- type: map_at_1
|
1678 |
value: 25.881
|
|
|
1739 |
dataset:
|
1740 |
type: quora
|
1741 |
name: MTEB QuoraRetrieval
|
1742 |
+
config: default
|
1743 |
+
split: test
|
1744 |
metrics:
|
1745 |
- type: map_at_1
|
1746 |
value: 67.553
|
|
|
1807 |
dataset:
|
1808 |
type: mteb/reddit-clustering
|
1809 |
name: MTEB RedditClustering
|
1810 |
+
config: default
|
1811 |
+
split: test
|
1812 |
metrics:
|
1813 |
- type: v_measure
|
1814 |
value: 46.46887711230235
|
|
|
1817 |
dataset:
|
1818 |
type: mteb/reddit-clustering-p2p
|
1819 |
name: MTEB RedditClusteringP2P
|
1820 |
+
config: default
|
1821 |
+
split: test
|
1822 |
metrics:
|
1823 |
- type: v_measure
|
1824 |
value: 54.166876298246926
|
|
|
1827 |
dataset:
|
1828 |
type: scidocs
|
1829 |
name: MTEB SCIDOCS
|
1830 |
+
config: default
|
1831 |
+
split: test
|
1832 |
metrics:
|
1833 |
- type: map_at_1
|
1834 |
value: 4.053
|
|
|
1895 |
dataset:
|
1896 |
type: mteb/sickr-sts
|
1897 |
name: MTEB SICK-R
|
1898 |
+
config: default
|
1899 |
+
split: test
|
1900 |
metrics:
|
1901 |
- type: cos_sim_pearson
|
1902 |
value: 77.7548748519677
|
|
|
1915 |
dataset:
|
1916 |
type: mteb/sts12-sts
|
1917 |
name: MTEB STS12
|
1918 |
+
config: default
|
1919 |
+
split: test
|
1920 |
metrics:
|
1921 |
- type: cos_sim_pearson
|
1922 |
value: 75.91051402657887
|
|
|
1935 |
dataset:
|
1936 |
type: mteb/sts13-sts
|
1937 |
name: MTEB STS13
|
1938 |
+
config: default
|
1939 |
+
split: test
|
1940 |
metrics:
|
1941 |
- type: cos_sim_pearson
|
1942 |
value: 77.23835466417793
|
|
|
1955 |
dataset:
|
1956 |
type: mteb/sts14-sts
|
1957 |
name: MTEB STS14
|
1958 |
+
config: default
|
1959 |
+
split: test
|
1960 |
metrics:
|
1961 |
- type: cos_sim_pearson
|
1962 |
value: 77.91692485139602
|
|
|
1975 |
dataset:
|
1976 |
type: mteb/sts15-sts
|
1977 |
name: MTEB STS15
|
1978 |
+
config: default
|
1979 |
+
split: test
|
1980 |
metrics:
|
1981 |
- type: cos_sim_pearson
|
1982 |
value: 82.13422113617578
|
|
|
1995 |
dataset:
|
1996 |
type: mteb/sts16-sts
|
1997 |
name: MTEB STS16
|
1998 |
+
config: default
|
1999 |
+
split: test
|
2000 |
metrics:
|
2001 |
- type: cos_sim_pearson
|
2002 |
value: 79.07989542843826
|
|
|
2015 |
dataset:
|
2016 |
type: mteb/sts17-crosslingual-sts
|
2017 |
name: MTEB STS17 (en-en)
|
2018 |
+
config: en-en
|
2019 |
+
split: test
|
2020 |
metrics:
|
2021 |
- type: cos_sim_pearson
|
2022 |
value: 87.0420983224933
|
|
|
2035 |
dataset:
|
2036 |
type: mteb/sts22-crosslingual-sts
|
2037 |
name: MTEB STS22 (en)
|
2038 |
+
config: en
|
2039 |
+
split: test
|
2040 |
metrics:
|
2041 |
- type: cos_sim_pearson
|
2042 |
value: 68.47031320016424
|
|
|
2055 |
dataset:
|
2056 |
type: mteb/stsbenchmark-sts
|
2057 |
name: MTEB STSBenchmark
|
2058 |
+
config: default
|
2059 |
+
split: test
|
2060 |
metrics:
|
2061 |
- type: cos_sim_pearson
|
2062 |
value: 80.79514366062675
|
|
|
2075 |
dataset:
|
2076 |
type: mteb/scidocs-reranking
|
2077 |
name: MTEB SciDocsRR
|
2078 |
+
config: default
|
2079 |
+
split: test
|
2080 |
metrics:
|
2081 |
- type: map
|
2082 |
value: 77.71580844366375
|
|
|
2087 |
dataset:
|
2088 |
type: scifact
|
2089 |
name: MTEB SciFact
|
2090 |
+
config: default
|
2091 |
+
split: test
|
2092 |
metrics:
|
2093 |
- type: map_at_1
|
2094 |
value: 56.39999999999999
|
|
|
2155 |
dataset:
|
2156 |
type: mteb/sprintduplicatequestions-pairclassification
|
2157 |
name: MTEB SprintDuplicateQuestions
|
2158 |
+
config: default
|
2159 |
+
split: test
|
2160 |
metrics:
|
2161 |
- type: cos_sim_accuracy
|
2162 |
value: 99.76831683168317
|
|
|
2209 |
dataset:
|
2210 |
type: mteb/stackexchange-clustering
|
2211 |
name: MTEB StackExchangeClustering
|
2212 |
+
config: default
|
2213 |
+
split: test
|
2214 |
metrics:
|
2215 |
- type: v_measure
|
2216 |
value: 59.194098673976484
|
|
|
2219 |
dataset:
|
2220 |
type: mteb/stackexchange-clustering-p2p
|
2221 |
name: MTEB StackExchangeClusteringP2P
|
2222 |
+
config: default
|
2223 |
+
split: test
|
2224 |
metrics:
|
2225 |
- type: v_measure
|
2226 |
value: 32.5744032578115
|
|
|
2229 |
dataset:
|
2230 |
type: mteb/stackoverflowdupquestions-reranking
|
2231 |
name: MTEB StackOverflowDupQuestions
|
2232 |
+
config: default
|
2233 |
+
split: test
|
2234 |
metrics:
|
2235 |
- type: map
|
2236 |
value: 49.61186384154483
|
|
|
2241 |
dataset:
|
2242 |
type: mteb/summeval
|
2243 |
name: MTEB SummEval
|
2244 |
+
config: default
|
2245 |
+
split: test
|
2246 |
metrics:
|
2247 |
- type: cos_sim_pearson
|
2248 |
value: 26.047224542079068
|
|
|
2257 |
dataset:
|
2258 |
type: trec-covid
|
2259 |
name: MTEB TRECCOVID
|
2260 |
+
config: default
|
2261 |
+
split: test
|
2262 |
metrics:
|
2263 |
- type: map_at_1
|
2264 |
value: 0.22300000000000003
|
|
|
2325 |
dataset:
|
2326 |
type: webis-touche2020
|
2327 |
name: MTEB Touche2020
|
2328 |
+
config: default
|
2329 |
+
split: test
|
2330 |
metrics:
|
2331 |
- type: map_at_1
|
2332 |
value: 3.047
|
|
|
2393 |
dataset:
|
2394 |
type: mteb/toxic_conversations_50k
|
2395 |
name: MTEB ToxicConversationsClassification
|
2396 |
+
config: default
|
2397 |
+
split: test
|
2398 |
metrics:
|
2399 |
- type: accuracy
|
2400 |
value: 68.84080000000002
|
|
|
2407 |
dataset:
|
2408 |
type: mteb/tweet_sentiment_extraction
|
2409 |
name: MTEB TweetSentimentExtractionClassification
|
2410 |
+
config: default
|
2411 |
+
split: test
|
2412 |
metrics:
|
2413 |
- type: accuracy
|
2414 |
value: 56.68647425014149
|
|
|
2419 |
dataset:
|
2420 |
type: mteb/twentynewsgroups-clustering
|
2421 |
name: MTEB TwentyNewsgroupsClustering
|
2422 |
+
config: default
|
2423 |
+
split: test
|
2424 |
metrics:
|
2425 |
- type: v_measure
|
2426 |
value: 40.8911707239219
|
|
|
2429 |
dataset:
|
2430 |
type: mteb/twittersemeval2015-pairclassification
|
2431 |
name: MTEB TwitterSemEval2015
|
2432 |
+
config: default
|
2433 |
+
split: test
|
2434 |
metrics:
|
2435 |
- type: cos_sim_accuracy
|
2436 |
value: 83.04226023722954
|
|
|
2483 |
dataset:
|
2484 |
type: mteb/twitterurlcorpus-pairclassification
|
2485 |
name: MTEB TwitterURLCorpus
|
2486 |
+
config: default
|
2487 |
+
split: test
|
2488 |
metrics:
|
2489 |
- type: cos_sim_accuracy
|
2490 |
value: 88.56871191834517
|
|
|
2597 |
journal={arXiv preprint arXiv:2202.08904},
|
2598 |
year={2022}
|
2599 |
}
|
2600 |
+
```
|