Update MTEB meta

README.md

@@ -13,6 +13,8 @@ model-index:
     dataset:
       type: mteb/amazon_counterfactual
       name: MTEB AmazonCounterfactualClassification (en)
+      config: en
+      split: test
     metrics:
     - type: accuracy
       value: 65.88059701492537
@@ -25,6 +27,8 @@ model-index:
     dataset:
       type: mteb/amazon_counterfactual
       name: MTEB AmazonCounterfactualClassification (de)
+      config: de
+      split: test
     metrics:
     - type: accuracy
       value: 59.07922912205568
@@ -37,6 +41,8 @@ model-index:
     dataset:
       type: mteb/amazon_counterfactual
       name: MTEB AmazonCounterfactualClassification (en-ext)
+      config: en-ext
+      split: test
     metrics:
     - type: accuracy
       value: 64.91754122938531
@@ -49,6 +55,8 @@ model-index:
     dataset:
       type: mteb/amazon_counterfactual
       name: MTEB AmazonCounterfactualClassification (ja)
+      config: ja
+      split: test
     metrics:
     - type: accuracy
       value: 56.423982869378996
@@ -61,6 +69,8 @@ model-index:
     dataset:
       type: mteb/amazon_polarity
       name: MTEB AmazonPolarityClassification
+      config: default
+      split: test
     metrics:
     - type: accuracy
       value: 74.938225
@@ -73,6 +83,8 @@ model-index:
     dataset:
       type: mteb/amazon_reviews_multi
       name: MTEB AmazonReviewsClassification (en)
+      config: en
+      split: test
     metrics:
     - type: accuracy
       value: 35.098
@@ -83,6 +95,8 @@ model-index:
     dataset:
       type: mteb/amazon_reviews_multi
       name: MTEB AmazonReviewsClassification (de)
+      config: de
+      split: test
     metrics:
     - type: accuracy
       value: 24.516
@@ -93,6 +107,8 @@ model-index:
     dataset:
       type: mteb/amazon_reviews_multi
       name: MTEB AmazonReviewsClassification (es)
+      config: es
+      split: test
     metrics:
     - type: accuracy
       value: 29.097999999999995
@@ -103,6 +119,8 @@ model-index:
     dataset:
       type: mteb/amazon_reviews_multi
       name: MTEB AmazonReviewsClassification (fr)
+      config: fr
+      split: test
     metrics:
     - type: accuracy
       value: 27.395999999999997
@@ -113,6 +131,8 @@ model-index:
     dataset:
       type: mteb/amazon_reviews_multi
       name: MTEB AmazonReviewsClassification (ja)
+      config: ja
+      split: test
     metrics:
     - type: accuracy
       value: 21.724
@@ -123,6 +143,8 @@ model-index:
     dataset:
       type: mteb/amazon_reviews_multi
       name: MTEB AmazonReviewsClassification (zh)
+      config: zh
+      split: test
     metrics:
     - type: accuracy
       value: 23.976
@@ -133,6 +155,8 @@ model-index:
     dataset:
       type: arguana
       name: MTEB ArguAna
+      config: default
+      split: test
     metrics:
     - type: map_at_1
       value: 13.442000000000002
@@ -187,6 +211,8 @@ model-index:
     dataset:
       type: mteb/arxiv-clustering-p2p
       name: MTEB ArxivClusteringP2P
+      config: default
+      split: test
     metrics:
     - type: v_measure
       value: 34.742482477870766
@@ -195,6 +221,8 @@ model-index:
     dataset:
       type: mteb/arxiv-clustering-s2s
       name: MTEB ArxivClusteringS2S
+      config: default
+      split: test
     metrics:
     - type: v_measure
       value: 24.67870651472156
@@ -203,6 +231,8 @@ model-index:
     dataset:
       type: mteb/askubuntudupquestions-reranking
       name: MTEB AskUbuntuDupQuestions
+      config: default
+      split: test
     metrics:
     - type: map
       value: 52.63439984994702
@@ -213,6 +243,8 @@ model-index:
     dataset:
       type: mteb/biosses-sts
       name: MTEB BIOSSES
+      config: default
+      split: test
     metrics:
     - type: cos_sim_pearson
       value: 72.78000135012542
@@ -231,6 +263,8 @@ model-index:
     dataset:
       type: mteb/bucc-bitext-mining
       name: MTEB BUCC (de-en)
+      config: de-en
+      split: test
     metrics:
     - type: accuracy
       value: 1.0960334029227559
@@ -245,6 +279,8 @@ model-index:
     dataset:
       type: mteb/bucc-bitext-mining
       name: MTEB BUCC (fr-en)
+      config: fr-en
+      split: test
     metrics:
     - type: accuracy
       value: 0.02201188641866608
@@ -259,6 +295,8 @@ model-index:
     dataset:
       type: mteb/bucc-bitext-mining
       name: MTEB BUCC (ru-en)
+      config: ru-en
+      split: test
     metrics:
     - type: accuracy
       value: 0.0
@@ -273,6 +311,8 @@ model-index:
     dataset:
       type: mteb/bucc-bitext-mining
       name: MTEB BUCC (zh-en)
+      config: zh-en
+      split: test
     metrics:
     - type: accuracy
       value: 0.0
@@ -287,6 +327,8 @@ model-index:
     dataset:
       type: mteb/banking77
       name: MTEB Banking77Classification
+      config: default
+      split: test
     metrics:
     - type: accuracy
       value: 74.67857142857142
@@ -297,6 +339,8 @@ model-index:
     dataset:
       type: mteb/biorxiv-clustering-p2p
       name: MTEB BiorxivClusteringP2P
+      config: default
+      split: test
     metrics:
     - type: v_measure
       value: 28.93427045246491
@@ -305,6 +349,8 @@ model-index:
     dataset:
       type: mteb/biorxiv-clustering-s2s
       name: MTEB BiorxivClusteringS2S
+      config: default
+      split: test
     metrics:
     - type: v_measure
       value: 23.080939123955474
@@ -313,6 +359,8 @@ model-index:
     dataset:
       type: BeIR/cqadupstack
       name: MTEB CQADupstackAndroidRetrieval
+      config: default
+      split: test
     metrics:
     - type: map_at_1
       value: 18.221999999999998
@@ -367,6 +415,8 @@ model-index:
     dataset:
       type: BeIR/cqadupstack
       name: MTEB CQADupstackEnglishRetrieval
+      config: default
+      split: test
     metrics:
     - type: map_at_1
       value: 12.058
@@ -421,6 +471,8 @@ model-index:
     dataset:
       type: BeIR/cqadupstack
       name: MTEB CQADupstackGamingRetrieval
+      config: default
+      split: test
     metrics:
     - type: map_at_1
       value: 21.183
@@ -475,6 +527,8 @@ model-index:
     dataset:
       type: BeIR/cqadupstack
       name: MTEB CQADupstackGisRetrieval
+      config: default
+      split: test
     metrics:
     - type: map_at_1
       value: 11.350999999999999
@@ -529,6 +583,8 @@ model-index:
     dataset:
       type: BeIR/cqadupstack
       name: MTEB CQADupstackMathematicaRetrieval
+      config: default
+      split: test
     metrics:
     - type: map_at_1
       value: 8.08
@@ -583,6 +639,8 @@ model-index:
     dataset:
       type: BeIR/cqadupstack
       name: MTEB CQADupstackPhysicsRetrieval
+      config: default
+      split: test
     metrics:
     - type: map_at_1
       value: 13.908999999999999
@@ -637,6 +695,8 @@ model-index:
     dataset:
       type: BeIR/cqadupstack
       name: MTEB CQADupstackProgrammersRetrieval
+      config: default
+      split: test
     metrics:
     - type: map_at_1
       value: 12.598
@@ -691,6 +751,8 @@ model-index:
     dataset:
       type: BeIR/cqadupstack
       name: MTEB CQADupstackRetrieval
+      config: default
+      split: test
     metrics:
     - type: map_at_1
       value: 12.738416666666666
@@ -745,6 +807,8 @@ model-index:
     dataset:
       type: BeIR/cqadupstack
       name: MTEB CQADupstackStatsRetrieval
+      config: default
+      split: test
     metrics:
     - type: map_at_1
       value: 12.307
@@ -799,6 +863,8 @@ model-index:
     dataset:
       type: BeIR/cqadupstack
       name: MTEB CQADupstackTexRetrieval
+      config: default
+      split: test
     metrics:
     - type: map_at_1
       value: 6.496
@@ -853,6 +919,8 @@ model-index:
     dataset:
       type: BeIR/cqadupstack
       name: MTEB CQADupstackUnixRetrieval
+      config: default
+      split: test
     metrics:
     - type: map_at_1
       value: 13.843
@@ -907,6 +975,8 @@ model-index:
     dataset:
       type: BeIR/cqadupstack
       name: MTEB CQADupstackWebmastersRetrieval
+      config: default
+      split: test
     metrics:
     - type: map_at_1
       value: 13.757
@@ -961,6 +1031,8 @@ model-index:
     dataset:
       type: BeIR/cqadupstack
       name: MTEB CQADupstackWordpressRetrieval
+      config: default
+      split: test
     metrics:
     - type: map_at_1
       value: 9.057
@@ -1015,6 +1087,8 @@ model-index:
     dataset:
       type: climate-fever
       name: MTEB ClimateFEVER
+      config: default
+      split: test
     metrics:
     - type: map_at_1
       value: 3.714
@@ -1069,6 +1143,8 @@ model-index:
     dataset:
       type: dbpedia-entity
       name: MTEB DBPedia
+      config: default
+      split: test
     metrics:
     - type: map_at_1
       value: 1.764
@@ -1123,6 +1199,8 @@ model-index:
     dataset:
       type: mteb/emotion
       name: MTEB EmotionClassification
+      config: default
+      split: test
     metrics:
     - type: accuracy
       value: 42.225
@@ -1133,6 +1211,8 @@ model-index:
     dataset:
       type: fever
       name: MTEB FEVER
+      config: default
+      split: test
     metrics:
     - type: map_at_1
       value: 11.497
@@ -1187,6 +1267,8 @@ model-index:
     dataset:
       type: fiqa
       name: MTEB FiQA2018
+      config: default
+      split: test
     metrics:
     - type: map_at_1
       value: 3.637
@@ -1241,6 +1323,8 @@ model-index:
     dataset:
       type: hotpotqa
       name: MTEB HotpotQA
+      config: default
+      split: test
     metrics:
     - type: map_at_1
       value: 9.676
@@ -1295,6 +1379,8 @@ model-index:
     dataset:
       type: mteb/imdb
       name: MTEB ImdbClassification
+      config: default
+      split: test
     metrics:
     - type: accuracy
       value: 62.895999999999994
@@ -1307,6 +1393,8 @@ model-index:
     dataset:
       type: msmarco
       name: MTEB MSMARCO
+      config: default
+      split: validation
     metrics:
     - type: map_at_1
       value: 2.88
@@ -1361,6 +1449,8 @@ model-index:
     dataset:
       type: mteb/mtop_domain
       name: MTEB MTOPDomainClassification (en)
+      config: en
+      split: test
     metrics:
     - type: accuracy
       value: 81.51846785225717
@@ -1371,6 +1461,8 @@ model-index:
     dataset:
       type: mteb/mtop_domain
       name: MTEB MTOPDomainClassification (de)
+      config: de
+      split: test
     metrics:
     - type: accuracy
       value: 60.37475345167653
@@ -1381,6 +1473,8 @@ model-index:
     dataset:
       type: mteb/mtop_domain
       name: MTEB MTOPDomainClassification (es)
+      config: es
+      split: test
     metrics:
     - type: accuracy
       value: 67.36824549699799
@@ -1391,6 +1485,8 @@ model-index:
     dataset:
       type: mteb/mtop_domain
       name: MTEB MTOPDomainClassification (fr)
+      config: fr
+      split: test
     metrics:
     - type: accuracy
       value: 63.12871907297212
@@ -1401,6 +1497,8 @@ model-index:
     dataset:
       type: mteb/mtop_domain
       name: MTEB MTOPDomainClassification (hi)
+      config: hi
+      split: test
     metrics:
     - type: accuracy
       value: 47.04553603442094
@@ -1411,6 +1509,8 @@ model-index:
     dataset:
       type: mteb/mtop_domain
       name: MTEB MTOPDomainClassification (th)
+      config: th
+      split: test
     metrics:
     - type: accuracy
       value: 52.282097649186255
@@ -1421,6 +1521,8 @@ model-index:
     dataset:
       type: mteb/mtop_intent
       name: MTEB MTOPIntentClassification (en)
+      config: en
+      split: test
     metrics:
     - type: accuracy
       value: 58.2421340629275
@@ -1431,6 +1533,8 @@ model-index:
     dataset:
       type: mteb/mtop_intent
       name: MTEB MTOPIntentClassification (de)
+      config: de
+      split: test
     metrics:
     - type: accuracy
       value: 45.069033530571986
@@ -1441,6 +1545,8 @@ model-index:
     dataset:
       type: mteb/mtop_intent
       name: MTEB MTOPIntentClassification (es)
+      config: es
+      split: test
     metrics:
     - type: accuracy
       value: 48.80920613742495
@@ -1451,6 +1557,8 @@ model-index:
     dataset:
       type: mteb/mtop_intent
       name: MTEB MTOPIntentClassification (fr)
+      config: fr
+      split: test
     metrics:
     - type: accuracy
       value: 44.337613529595984
@@ -1461,6 +1569,8 @@ model-index:
     dataset:
       type: mteb/mtop_intent
       name: MTEB MTOPIntentClassification (hi)
+      config: hi
+      split: test
     metrics:
     - type: accuracy
       value: 34.198637504481894
@@ -1471,6 +1581,8 @@ model-index:
     dataset:
       type: mteb/mtop_intent
       name: MTEB MTOPIntentClassification (th)
+      config: th
+      split: test
     metrics:
     - type: accuracy
       value: 43.11030741410488
@@ -1481,6 +1593,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_intent
       name: MTEB MassiveIntentClassification (af)
+      config: af
+      split: test
     metrics:
     - type: accuracy
       value: 37.79421654337593
@@ -1491,6 +1605,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_intent
       name: MTEB MassiveIntentClassification (am)
+      config: am
+      split: test
     metrics:
     - type: accuracy
       value: 23.722259583053127
@@ -1501,6 +1617,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_intent
       name: MTEB MassiveIntentClassification (ar)
+      config: ar
+      split: test
     metrics:
     - type: accuracy
       value: 29.64021519838601
@@ -1511,6 +1629,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_intent
       name: MTEB MassiveIntentClassification (az)
+      config: az
+      split: test
     metrics:
     - type: accuracy
       value: 39.4754539340955
@@ -1521,6 +1641,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_intent
       name: MTEB MassiveIntentClassification (bn)
+      config: bn
+      split: test
     metrics:
     - type: accuracy
       value: 26.550100874243444
@@ -1531,6 +1653,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_intent
       name: MTEB MassiveIntentClassification (cy)
+      config: cy
+      split: test
     metrics:
     - type: accuracy
       value: 38.78278412911904
@@ -1541,6 +1665,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_intent
       name: MTEB MassiveIntentClassification (da)
+      config: da
+      split: test
     metrics:
     - type: accuracy
       value: 43.557498318762605
@@ -1551,6 +1677,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_intent
       name: MTEB MassiveIntentClassification (de)
+      config: de
+      split: test
     metrics:
     - type: accuracy
       value: 40.39340954942838
@@ -1561,6 +1689,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_intent
       name: MTEB MassiveIntentClassification (el)
+      config: el
+      split: test
     metrics:
     - type: accuracy
       value: 37.28648285137861
@@ -1571,6 +1701,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_intent
       name: MTEB MassiveIntentClassification (en)
+      config: en
+      split: test
     metrics:
     - type: accuracy
       value: 58.080026899798256
@@ -1581,6 +1713,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_intent
       name: MTEB MassiveIntentClassification (es)
+      config: es
+      split: test
     metrics:
     - type: accuracy
       value: 41.176866173503704
@@ -1591,6 +1725,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_intent
       name: MTEB MassiveIntentClassification (fa)
+      config: fa
+      split: test
     metrics:
     - type: accuracy
       value: 36.422326832548755
@@ -1601,6 +1737,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_intent
       name: MTEB MassiveIntentClassification (fi)
+      config: fi
+      split: test
     metrics:
     - type: accuracy
       value: 38.75588433086752
@@ -1611,6 +1749,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_intent
       name: MTEB MassiveIntentClassification (fr)
+      config: fr
+      split: test
     metrics:
     - type: accuracy
       value: 43.67182246133153
@@ -1621,6 +1761,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_intent
       name: MTEB MassiveIntentClassification (he)
+      config: he
+      split: test
     metrics:
     - type: accuracy
       value: 31.980497646267658
@@ -1631,6 +1773,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_intent
       name: MTEB MassiveIntentClassification (hi)
+      config: hi
+      split: test
     metrics:
     - type: accuracy
       value: 28.039677202420982
@@ -1641,6 +1785,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_intent
       name: MTEB MassiveIntentClassification (hu)
+      config: hu
+      split: test
     metrics:
     - type: accuracy
       value: 38.13718897108272
@@ -1651,6 +1797,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_intent
       name: MTEB MassiveIntentClassification (hy)
+      config: hy
+      split: test
     metrics:
     - type: accuracy
       value: 26.05245460659045
@@ -1661,6 +1809,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_intent
       name: MTEB MassiveIntentClassification (id)
+      config: id
+      split: test
     metrics:
     - type: accuracy
       value: 41.156691324815064
@@ -1671,6 +1821,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_intent
       name: MTEB MassiveIntentClassification (is)
+      config: is
+      split: test
     metrics:
     - type: accuracy
       value: 38.62811028917284
@@ -1681,6 +1833,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_intent
       name: MTEB MassiveIntentClassification (it)
+      config: it
+      split: test
     metrics:
     - type: accuracy
       value: 44.0383322125084
@@ -1691,6 +1845,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_intent
       name: MTEB MassiveIntentClassification (ja)
+      config: ja
+      split: test
     metrics:
     - type: accuracy
       value: 46.20712844653666
@@ -1701,6 +1857,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_intent
       name: MTEB MassiveIntentClassification (jv)
+      config: jv
+      split: test
     metrics:
     - type: accuracy
       value: 37.60591795561533
@@ -1711,6 +1869,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_intent
       name: MTEB MassiveIntentClassification (ka)
+      config: ka
+      split: test
     metrics:
     - type: accuracy
       value: 24.47209145931405
@@ -1721,6 +1881,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_intent
       name: MTEB MassiveIntentClassification (km)
+      config: km
+      split: test
     metrics:
     - type: accuracy
       value: 26.23739071956961
@@ -1731,6 +1893,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_intent
       name: MTEB MassiveIntentClassification (kn)
+      config: kn
+      split: test
     metrics:
     - type: accuracy
       value: 17.831203765971754
@@ -1741,6 +1905,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_intent
       name: MTEB MassiveIntentClassification (ko)
+      config: ko
+      split: test
     metrics:
     - type: accuracy
       value: 37.266308002689975
@@ -1751,6 +1917,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_intent
       name: MTEB MassiveIntentClassification (lv)
+      config: lv
+      split: test
     metrics:
     - type: accuracy
       value: 40.93140551445864
@@ -1761,6 +1929,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_intent
       name: MTEB MassiveIntentClassification (ml)
+      config: ml
+      split: test
     metrics:
     - type: accuracy
       value: 17.88500336247478
@@ -1771,6 +1941,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_intent
       name: MTEB MassiveIntentClassification (mn)
+      config: mn
+      split: test
     metrics:
     - type: accuracy
       value: 32.975790181573636
@@ -1781,6 +1953,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_intent
       name: MTEB MassiveIntentClassification (ms)
+      config: ms
+      split: test
     metrics:
     - type: accuracy
       value: 40.91123066577001
@@ -1791,6 +1965,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_intent
       name: MTEB MassiveIntentClassification (my)
+      config: my
+      split: test
     metrics:
     - type: accuracy
       value: 17.834566240753194
@@ -1801,6 +1977,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_intent
       name: MTEB MassiveIntentClassification (nb)
+      config: nb
+      split: test
     metrics:
     - type: accuracy
       value: 39.47881640887693
@@ -1811,6 +1989,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_intent
       name: MTEB MassiveIntentClassification (nl)
+      config: nl
+      split: test
     metrics:
     - type: accuracy
       value: 41.76193678547412
@@ -1821,6 +2001,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_intent
       name: MTEB MassiveIntentClassification (pl)
+      config: pl
+      split: test
     metrics:
     - type: accuracy
       value: 42.61936785474109
@@ -1831,6 +2013,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_intent
       name: MTEB MassiveIntentClassification (pt)
+      config: pt
+      split: test
     metrics:
     - type: accuracy
       value: 44.54270342972427
@@ -1841,6 +2025,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_intent
       name: MTEB MassiveIntentClassification (ro)
+      config: ro
+      split: test
     metrics:
     - type: accuracy
       value: 39.96973772696705
@@ -1851,6 +2037,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_intent
       name: MTEB MassiveIntentClassification (ru)
+      config: ru
+      split: test
     metrics:
     - type: accuracy
       value: 37.461331540013454
@@ -1861,6 +2049,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_intent
       name: MTEB MassiveIntentClassification (sl)
+      config: sl
+      split: test
     metrics:
     - type: accuracy
       value: 38.28850033624748
@@ -1871,6 +2061,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_intent
       name: MTEB MassiveIntentClassification (sq)
+      config: sq
+      split: test
     metrics:
     - type: accuracy
       value: 40.95494283792872
@@ -1881,6 +2073,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_intent
       name: MTEB MassiveIntentClassification (sv)
+      config: sv
+      split: test
     metrics:
     - type: accuracy
       value: 41.85272360457296
@@ -1891,6 +2085,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_intent
       name: MTEB MassiveIntentClassification (sw)
+      config: sw
+      split: test
     metrics:
     - type: accuracy
       value: 38.328850033624754
@@ -1901,6 +2097,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_intent
       name: MTEB MassiveIntentClassification (ta)
+      config: ta
+      split: test
     metrics:
     - type: accuracy
       value: 19.031607262945528
@@ -1911,6 +2109,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_intent
       name: MTEB MassiveIntentClassification (te)
+      config: te
+      split: test
     metrics:
     - type: accuracy
       value: 19.38466711499664
@@ -1921,6 +2121,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_intent
       name: MTEB MassiveIntentClassification (th)
+      config: th
+      split: test
     metrics:
     - type: accuracy
       value: 34.088769334229994
@@ -1931,6 +2133,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_intent
       name: MTEB MassiveIntentClassification (tl)
+      config: tl
+      split: test
     metrics:
     - type: accuracy
       value: 40.285810356422324
@@ -1941,6 +2145,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_intent
       name: MTEB MassiveIntentClassification (tr)
+      config: tr
+      split: test
     metrics:
     - type: accuracy
       value: 38.860121049092136
@@ -1951,6 +2157,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_intent
       name: MTEB MassiveIntentClassification (ur)
+      config: ur
+      split: test
     metrics:
     - type: accuracy
       value: 27.834566240753194
@@ -1961,6 +2169,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_intent
       name: MTEB MassiveIntentClassification (vi)
+      config: vi
+      split: test
     metrics:
     - type: accuracy
       value: 38.70544720914593
@@ -1971,6 +2181,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_intent
       name: MTEB MassiveIntentClassification (zh-CN)
+      config: zh-CN
+      split: test
     metrics:
     - type: accuracy
       value: 45.78009414929387
@@ -1981,6 +2193,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_intent
       name: MTEB MassiveIntentClassification (zh-TW)
+      config: zh-TW
+      split: test
     metrics:
     - type: accuracy
       value: 42.32010759919301
@@ -1991,6 +2205,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_scenario
       name: MTEB MassiveScenarioClassification (af)
+      config: af
+      split: test
     metrics:
     - type: accuracy
       value: 40.24546065904506
@@ -2001,6 +2217,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_scenario
       name: MTEB MassiveScenarioClassification (am)
+      config: am
+      split: test
     metrics:
     - type: accuracy
       value: 25.68930733019502
@@ -2011,6 +2229,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_scenario
       name: MTEB MassiveScenarioClassification (ar)
+      config: ar
+      split: test
     metrics:
     - type: accuracy
       value: 32.39744451916611
@@ -2021,6 +2241,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_scenario
       name: MTEB MassiveScenarioClassification (az)
+      config: az
+      split: test
     metrics:
     - type: accuracy
       value: 40.53127101546738
@@ -2031,6 +2253,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_scenario
       name: MTEB MassiveScenarioClassification (bn)
+      config: bn
+      split: test
     metrics:
     - type: accuracy
       value: 27.23268325487559
@@ -2041,6 +2265,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_scenario
       name: MTEB MassiveScenarioClassification (cy)
+      config: cy
+      split: test
     metrics:
     - type: accuracy
       value: 38.69872225958305
@@ -2051,6 +2277,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_scenario
       name: MTEB MassiveScenarioClassification (da)
+      config: da
+      split: test
     metrics:
     - type: accuracy
       value: 44.75453934095494
@@ -2061,6 +2289,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_scenario
       name: MTEB MassiveScenarioClassification (de)
+      config: de
+      split: test
     metrics:
     - type: accuracy
       value: 41.355077336919976
@@ -2071,6 +2301,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_scenario
       name: MTEB MassiveScenarioClassification (el)
+      config: el
+      split: test
     metrics:
     - type: accuracy
       value: 38.43981170141224
@@ -2081,6 +2313,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_scenario
       name: MTEB MassiveScenarioClassification (en)
+      config: en
+      split: test
     metrics:
     - type: accuracy
       value: 66.33826496301278
@@ -2091,6 +2325,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_scenario
       name: MTEB MassiveScenarioClassification (es)
+      config: es
+      split: test
     metrics:
     - type: accuracy
       value: 44.17955615332885
@@ -2101,6 +2337,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_scenario
       name: MTEB MassiveScenarioClassification (fa)
+      config: fa
+      split: test
     metrics:
     - type: accuracy
       value: 34.82851378614661
@@ -2111,6 +2349,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_scenario
       name: MTEB MassiveScenarioClassification (fi)
+      config: fi
+      split: test
     metrics:
     - type: accuracy
       value: 40.561533288500335
@@ -2121,6 +2361,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_scenario
       name: MTEB MassiveScenarioClassification (fr)
+      config: fr
+      split: test
     metrics:
     - type: accuracy
       value: 45.917955615332886
@@ -2131,6 +2373,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_scenario
       name: MTEB MassiveScenarioClassification (he)
+      config: he
+      split: test
     metrics:
     - type: accuracy
       value: 32.08473436449227
@@ -2141,6 +2385,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_scenario
       name: MTEB MassiveScenarioClassification (hi)
+      config: hi
+      split: test
     metrics:
     - type: accuracy
       value: 28.369199731002016
@@ -2151,6 +2397,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_scenario
       name: MTEB MassiveScenarioClassification (hu)
+      config: hu
+      split: test
     metrics:
     - type: accuracy
       value: 39.49226630800269
@@ -2161,6 +2409,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_scenario
       name: MTEB MassiveScenarioClassification (hy)
+      config: hy
+      split: test
     metrics:
     - type: accuracy
       value: 25.904505716207133
@@ -2171,6 +2421,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_scenario
       name: MTEB MassiveScenarioClassification (id)
+      config: id
+      split: test
     metrics:
     - type: accuracy
       value: 40.95830531271016
@@ -2181,6 +2433,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_scenario
       name: MTEB MassiveScenarioClassification (is)
+      config: is
+      split: test
     metrics:
     - type: accuracy
       value: 38.564223268325485
@@ -2191,6 +2445,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_scenario
       name: MTEB MassiveScenarioClassification (it)
+      config: it
+      split: test
     metrics:
     - type: accuracy
       value: 46.58708809683928
@@ -2201,6 +2457,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_scenario
       name: MTEB MassiveScenarioClassification (ja)
+      config: ja
+      split: test
     metrics:
     - type: accuracy
       value: 46.24747814391393
@@ -2211,6 +2469,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_scenario
       name: MTEB MassiveScenarioClassification (jv)
+      config: jv
+      split: test
     metrics:
     - type: accuracy
       value: 39.6570275722932
@@ -2221,6 +2481,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_scenario
       name: MTEB MassiveScenarioClassification (ka)
+      config: ka
+      split: test
     metrics:
     - type: accuracy
       value: 25.279085406859448
@@ -2231,6 +2493,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_scenario
       name: MTEB MassiveScenarioClassification (km)
+      config: km
+      split: test
     metrics:
     - type: accuracy
       value: 28.97108271687962
@@ -2241,6 +2505,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_scenario
       name: MTEB MassiveScenarioClassification (kn)
+      config: kn
+      split: test
     metrics:
     - type: accuracy
       value: 19.27370544720915
@@ -2251,6 +2517,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_scenario
       name: MTEB MassiveScenarioClassification (ko)
+      config: ko
+      split: test
     metrics:
     - type: accuracy
       value: 35.729657027572294
@@ -2261,6 +2529,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_scenario
       name: MTEB MassiveScenarioClassification (lv)
+      config: lv
+      split: test
     metrics:
     - type: accuracy
       value: 39.57296570275723
@@ -2271,6 +2541,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_scenario
       name: MTEB MassiveScenarioClassification (ml)
+      config: ml
+      split: test
     metrics:
     - type: accuracy
       value: 19.895763281775388
@@ -2281,6 +2553,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_scenario
       name: MTEB MassiveScenarioClassification (mn)
+      config: mn
+      split: test
     metrics:
     - type: accuracy
       value: 32.431069266980494
@@ -2291,6 +2565,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_scenario
       name: MTEB MassiveScenarioClassification (ms)
+      config: ms
+      split: test
     metrics:
     - type: accuracy
       value: 42.32347007397445
@@ -2301,6 +2577,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_scenario
       name: MTEB MassiveScenarioClassification (my)
+      config: my
+      split: test
     metrics:
     - type: accuracy
       value: 20.864156018829856
@@ -2311,6 +2589,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_scenario
       name: MTEB MassiveScenarioClassification (nb)
+      config: nb
+      split: test
     metrics:
     - type: accuracy
       value: 40.47074646940148
@@ -2321,6 +2601,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_scenario
       name: MTEB MassiveScenarioClassification (nl)
+      config: nl
+      split: test
     metrics:
     - type: accuracy
       value: 43.591123066577
@@ -2331,6 +2613,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_scenario
       name: MTEB MassiveScenarioClassification (pl)
+      config: pl
+      split: test
     metrics:
     - type: accuracy
       value: 41.876260928043045
@@ -2341,6 +2625,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_scenario
       name: MTEB MassiveScenarioClassification (pt)
+      config: pt
+      split: test
     metrics:
     - type: accuracy
       value: 46.30800268997983
@@ -2351,6 +2637,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_scenario
       name: MTEB MassiveScenarioClassification (ro)
+      config: ro
+      split: test
     metrics:
     - type: accuracy
       value: 42.525218560860786
@@ -2361,6 +2649,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_scenario
       name: MTEB MassiveScenarioClassification (ru)
+      config: ru
+      split: test
     metrics:
     - type: accuracy
       value: 35.94821788836584
@@ -2371,6 +2661,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_scenario
       name: MTEB MassiveScenarioClassification (sl)
+      config: sl
+      split: test
     metrics:
     - type: accuracy
       value: 38.69199731002017
@@ -2381,6 +2673,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_scenario
       name: MTEB MassiveScenarioClassification (sq)
+      config: sq
+      split: test
     metrics:
     - type: accuracy
       value: 40.474108944182916
@@ -2391,6 +2685,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_scenario
       name: MTEB MassiveScenarioClassification (sv)
+      config: sv
+      split: test
     metrics:
     - type: accuracy
       value: 41.523201075991935
@@ -2401,6 +2697,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_scenario
       name: MTEB MassiveScenarioClassification (sw)
+      config: sw
+      split: test
     metrics:
     - type: accuracy
       value: 39.54942837928716
@@ -2411,6 +2709,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_scenario
       name: MTEB MassiveScenarioClassification (ta)
+      config: ta
+      split: test
     metrics:
     - type: accuracy
       value: 22.8782784129119
@@ -2421,6 +2721,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_scenario
       name: MTEB MassiveScenarioClassification (te)
+      config: te
+      split: test
     metrics:
     - type: accuracy
       value: 20.51445864156019
@@ -2431,6 +2733,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_scenario
       name: MTEB MassiveScenarioClassification (th)
+      config: th
+      split: test
     metrics:
     - type: accuracy
       value: 34.92602555480834
@@ -2441,6 +2745,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_scenario
       name: MTEB MassiveScenarioClassification (tl)
+      config: tl
+      split: test
     metrics:
     - type: accuracy
       value: 40.74983187626093
@@ -2451,6 +2757,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_scenario
       name: MTEB MassiveScenarioClassification (tr)
+      config: tr
+      split: test
     metrics:
     - type: accuracy
       value: 39.06859448554136
@@ -2461,6 +2769,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_scenario
       name: MTEB MassiveScenarioClassification (ur)
+      config: ur
+      split: test
     metrics:
     - type: accuracy
       value: 29.747814391392062
@@ -2471,6 +2781,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_scenario
       name: MTEB MassiveScenarioClassification (vi)
+      config: vi
+      split: test
     metrics:
     - type: accuracy
       value: 38.02286482851379
@@ -2481,6 +2793,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_scenario
       name: MTEB MassiveScenarioClassification (zh-CN)
+      config: zh-CN
+      split: test
     metrics:
     - type: accuracy
       value: 48.550773369199725
@@ -2491,6 +2805,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_scenario
       name: MTEB MassiveScenarioClassification (zh-TW)
+      config: zh-TW
+      split: test
     metrics:
     - type: accuracy
       value: 45.17821116341628
@@ -2501,6 +2817,8 @@ model-index:
     dataset:
       type: mteb/medrxiv-clustering-p2p
       name: MTEB MedrxivClusteringP2P
+      config: default
+      split: test
     metrics:
     - type: v_measure
       value: 28.301902023313875
@@ -2509,6 +2827,8 @@ model-index:
     dataset:
       type: mteb/medrxiv-clustering-s2s
       name: MTEB MedrxivClusteringS2S
+      config: default
+      split: test
     metrics:
     - type: v_measure
       value: 24.932123582259287
@@ -2517,6 +2837,8 @@ model-index:
     dataset:
       type: mteb/mind_small
       name: MTEB MindSmallReranking
+      config: default
+      split: test
     metrics:
     - type: map
       value: 29.269341041468326
@@ -2527,6 +2849,8 @@ model-index:
     dataset:
       type: nfcorpus
       name: MTEB NFCorpus
+      config: default
+      split: test
     metrics:
     - type: map_at_1
       value: 1.2269999999999999
@@ -2581,6 +2905,8 @@ model-index:
     dataset:
       type: nq
       name: MTEB NQ
+      config: default
+      split: test
     metrics:
     - type: map_at_1
       value: 3.515
@@ -2635,6 +2961,8 @@ model-index:
     dataset:
       type: quora
       name: MTEB QuoraRetrieval
+      config: default
+      split: test
     metrics:
     - type: map_at_1
       value: 61.697
@@ -2689,6 +3017,8 @@ model-index:
     dataset:
       type: mteb/reddit-clustering
       name: MTEB RedditClustering
+      config: default
+      split: test
     metrics:
     - type: v_measure
       value: 33.75741018380938
@@ -2697,6 +3027,8 @@ model-index:
     dataset:
       type: mteb/reddit-clustering-p2p
       name: MTEB RedditClusteringP2P
+      config: default
+      split: test
     metrics:
     - type: v_measure
       value: 41.00799910099266
@@ -2705,6 +3037,8 @@ model-index:
     dataset:
       type: scidocs
       name: MTEB SCIDOCS
+      config: default
+      split: test
     metrics:
     - type: map_at_1
       value: 1.72
@@ -2759,6 +3093,8 @@ model-index:
     dataset:
       type: mteb/sickr-sts
       name: MTEB SICK-R
+      config: default
+      split: test
     metrics:
     - type: cos_sim_pearson
       value: 80.96286245858941
@@ -2777,6 +3113,8 @@ model-index:
     dataset:
       type: mteb/sts12-sts
       name: MTEB STS12
+      config: default
+      split: test
     metrics:
     - type: cos_sim_pearson
       value: 80.20938796088339
@@ -2795,6 +3133,8 @@ model-index:
     dataset:
       type: mteb/sts13-sts
       name: MTEB STS13
+      config: default
+      split: test
     metrics:
     - type: cos_sim_pearson
       value: 76.401935081936
@@ -2813,6 +3153,8 @@ model-index:
     dataset:
       type: mteb/sts14-sts
       name: MTEB STS14
+      config: default
+      split: test
     metrics:
     - type: cos_sim_pearson
       value: 75.35551963935667
@@ -2831,6 +3173,8 @@ model-index:
     dataset:
       type: mteb/sts15-sts
       name: MTEB STS15
+      config: default
+      split: test
     metrics:
     - type: cos_sim_pearson
       value: 79.05293131911803
@@ -2849,6 +3193,8 @@ model-index:
     dataset:
       type: mteb/sts16-sts
       name: MTEB STS16
+      config: default
+      split: test
     metrics:
     - type: cos_sim_pearson
       value: 76.04750373932828
@@ -2867,6 +3213,8 @@ model-index:
     dataset:
       type: mteb/sts17-crosslingual-sts
       name: MTEB STS17 (ko-ko)
+      config: ko-ko
+      split: test
     metrics:
     - type: cos_sim_pearson
       value: 43.0464619152799
@@ -2885,6 +3233,8 @@ model-index:
     dataset:
       type: mteb/sts17-crosslingual-sts
       name: MTEB STS17 (ar-ar)
+      config: ar-ar
+      split: test
     metrics:
     - type: cos_sim_pearson
       value: 53.27469278912148
@@ -2903,6 +3253,8 @@ model-index:
     dataset:
       type: mteb/sts17-crosslingual-sts
       name: MTEB STS17 (en-ar)
+      config: en-ar
+      split: test
     metrics:
     - type: cos_sim_pearson
       value: 1.5482997790039945
@@ -2921,6 +3273,8 @@ model-index:
     dataset:
       type: mteb/sts17-crosslingual-sts
       name: MTEB STS17 (en-de)
+      config: en-de
+      split: test
     metrics:
     - type: cos_sim_pearson
       value: 27.5420218362265
@@ -2939,6 +3293,8 @@ model-index:
     dataset:
       type: mteb/sts17-crosslingual-sts
       name: MTEB STS17 (en-en)
+      config: en-en
+      split: test
     metrics:
     - type: cos_sim_pearson
       value: 85.32029757646663
@@ -2957,6 +3313,8 @@ model-index:
     dataset:
       type: mteb/sts17-crosslingual-sts
       name: MTEB STS17 (en-tr)
+      config: en-tr
+      split: test
     metrics:
     - type: cos_sim_pearson
       value: 4.37162299241808
@@ -2975,6 +3333,8 @@ model-index:
     dataset:
       type: mteb/sts17-crosslingual-sts
       name: MTEB STS17 (es-en)
+      config: es-en
+      split: test
     metrics:
     - type: cos_sim_pearson
       value: 20.306030448858603
@@ -2993,6 +3353,8 @@ model-index:
     dataset:
       type: mteb/sts17-crosslingual-sts
       name: MTEB STS17 (es-es)
+      config: es-es
+      split: test
     metrics:
     - type: cos_sim_pearson
       value: 66.81873207478459
@@ -3011,6 +3373,8 @@ model-index:
     dataset:
       type: mteb/sts17-crosslingual-sts
       name: MTEB STS17 (fr-en)
+      config: fr-en
+      split: test
     metrics:
     - type: cos_sim_pearson
       value: 21.366487281202602
@@ -3029,6 +3393,8 @@ model-index:
     dataset:
       type: mteb/sts17-crosslingual-sts
       name: MTEB STS17 (it-en)
+      config: it-en
+      split: test
     metrics:
     - type: cos_sim_pearson
       value: 20.73153177251085
@@ -3047,6 +3413,8 @@ model-index:
     dataset:
       type: mteb/sts17-crosslingual-sts
       name: MTEB STS17 (nl-en)
+      config: nl-en
+      split: test
     metrics:
     - type: cos_sim_pearson
       value: 26.618435024084253
@@ -3065,6 +3433,8 @@ model-index:
     dataset:
       type: mteb/sts22-crosslingual-sts
       name: MTEB STS22 (en)
+      config: en
+      split: test
     metrics:
     - type: cos_sim_pearson
       value: 59.17638344661753
@@ -3083,6 +3453,8 @@ model-index:
     dataset:
       type: mteb/sts22-crosslingual-sts
       name: MTEB STS22 (de)
+      config: de
+      split: test
     metrics:
     - type: cos_sim_pearson
       value: 10.322254716987457
@@ -3101,6 +3473,8 @@ model-index:
     dataset:
       type: mteb/sts22-crosslingual-sts
       name: MTEB STS22 (es)
+      config: es
+      split: test
     metrics:
     - type: cos_sim_pearson
       value: 43.38031880545056
@@ -3119,6 +3493,8 @@ model-index:
     dataset:
       type: mteb/sts22-crosslingual-sts
       name: MTEB STS22 (pl)
+      config: pl
+      split: test
     metrics:
     - type: cos_sim_pearson
       value: 4.291290504363136
@@ -3137,6 +3513,8 @@ model-index:
     dataset:
       type: mteb/sts22-crosslingual-sts
       name: MTEB STS22 (tr)
+      config: tr
+      split: test
     metrics:
     - type: cos_sim_pearson
       value: 4.102739498555817
@@ -3155,6 +3533,8 @@ model-index:
     dataset:
       type: mteb/sts22-crosslingual-sts
       name: MTEB STS22 (ar)
+      config: ar
+      split: test
     metrics:
     - type: cos_sim_pearson
       value: 2.38765395226737
@@ -3173,6 +3553,8 @@ model-index:
     dataset:
       type: mteb/sts22-crosslingual-sts
       name: MTEB STS22 (ru)
+      config: ru
+      split: test
     metrics:
     - type: cos_sim_pearson
       value: 7.6735490672676345
@@ -3191,6 +3573,8 @@ model-index:
     dataset:
       type: mteb/sts22-crosslingual-sts
       name: MTEB STS22 (zh)
+      config: zh
+      split: test
     metrics:
     - type: cos_sim_pearson
       value: 0.06167614416104335
@@ -3209,6 +3593,8 @@ model-index:
     dataset:
       type: mteb/sts22-crosslingual-sts
       name: MTEB STS22 (fr)
+      config: fr
+      split: test
     metrics:
     - type: cos_sim_pearson
       value: 53.19490347682836
@@ -3227,6 +3613,8 @@ model-index:
     dataset:
       type: mteb/sts22-crosslingual-sts
       name: MTEB STS22 (de-en)
+      config: de-en
+      split: test
     metrics:
     - type: cos_sim_pearson
       value: 51.151158530122146
@@ -3245,6 +3633,8 @@ model-index:
     dataset:
       type: mteb/sts22-crosslingual-sts
       name: MTEB STS22 (es-en)
+      config: es-en
+      split: test
     metrics:
     - type: cos_sim_pearson
       value: 30.36194885126792
@@ -3263,6 +3653,8 @@ model-index:
     dataset:
       type: mteb/sts22-crosslingual-sts
       name: MTEB STS22 (it)
+      config: it
+      split: test
     metrics:
     - type: cos_sim_pearson
       value: 35.23883630335275
@@ -3281,6 +3673,8 @@ model-index:
     dataset:
       type: mteb/sts22-crosslingual-sts
       name: MTEB STS22 (pl-en)
+      config: pl-en
+      split: test
     metrics:
     - type: cos_sim_pearson
       value: 19.809302548119547
@@ -3299,6 +3693,8 @@ model-index:
     dataset:
       type: mteb/sts22-crosslingual-sts
       name: MTEB STS22 (zh-en)
+      config: zh-en
+      split: test
     metrics:
     - type: cos_sim_pearson
       value: 20.393500955410488
@@ -3317,6 +3713,8 @@ model-index:
     dataset:
       type: mteb/sts22-crosslingual-sts
       name: MTEB STS22 (es-it)
+      config: es-it
+      split: test
     metrics:
     - type: cos_sim_pearson
       value: 36.58919983075148
@@ -3335,6 +3733,8 @@ model-index:
     dataset:
       type: mteb/sts22-crosslingual-sts
       name: MTEB STS22 (de-fr)
+      config: de-fr
+      split: test
     metrics:
     - type: cos_sim_pearson
       value: 26.350936227950083
@@ -3353,6 +3753,8 @@ model-index:
     dataset:
       type: mteb/sts22-crosslingual-sts
       name: MTEB STS22 (de-pl)
+      config: de-pl
+      split: test
     metrics:
     - type: cos_sim_pearson
       value: 20.056269198600322
@@ -3371,6 +3773,8 @@ model-index:
     dataset:
       type: mteb/sts22-crosslingual-sts
       name: MTEB STS22 (fr-pl)
+      config: fr-pl
+      split: test
     metrics:
     - type: cos_sim_pearson
       value: 19.563740271419395
@@ -3389,6 +3793,8 @@ model-index:
     dataset:
       type: mteb/stsbenchmark-sts
       name: MTEB STSBenchmark
+      config: default
+      split: test
     metrics:
     - type: cos_sim_pearson
       value: 80.00905671833966
@@ -3407,6 +3813,8 @@ model-index:
     dataset:
       type: mteb/scidocs-reranking
       name: MTEB SciDocsRR
+      config: default
+      split: test
     metrics:
     - type: map
       value: 68.35710819755543
@@ -3417,6 +3825,8 @@ model-index:
     dataset:
       type: scifact
       name: MTEB SciFact
+      config: default
+      split: test
     metrics:
     - type: map_at_1
       value: 21.556
@@ -3471,6 +3881,8 @@ model-index:
     dataset:
       type: mteb/sprintduplicatequestions-pairclassification
       name: MTEB SprintDuplicateQuestions
+      config: default
+      split: test
     metrics:
     - type: cos_sim_accuracy
       value: 99.49306930693069
@@ -3523,6 +3935,8 @@ model-index:
     dataset:
       type: mteb/stackexchange-clustering
       name: MTEB StackExchangeClustering
+      config: default
+      split: test
     metrics:
     - type: v_measure
       value: 44.59127540530939
@@ -3531,6 +3945,8 @@ model-index:
     dataset:
       type: mteb/stackexchange-clustering-p2p
       name: MTEB StackExchangeClusteringP2P
+      config: default
+      split: test
     metrics:
     - type: v_measure
       value: 28.230204578753636
@@ -3539,6 +3955,8 @@ model-index:
     dataset:
       type: mteb/stackoverflowdupquestions-reranking
       name: MTEB StackOverflowDupQuestions
+      config: default
+      split: test
     metrics:
     - type: map
       value: 39.96520488022785
@@ -3549,6 +3967,8 @@ model-index:
     dataset:
       type: mteb/summeval
       name: MTEB SummEval
+      config: default
+      split: test
     metrics:
     - type: cos_sim_pearson
       value: 30.56303767714449
@@ -3563,6 +3983,8 @@ model-index:
     dataset:
       type: trec-covid
       name: MTEB TRECCOVID
+      config: default
+      split: test
     metrics:
     - type: map_at_1
       value: 0.11299999999999999
@@ -3617,6 +4039,8 @@ model-index:
     dataset:
       type: webis-touche2020
       name: MTEB Touche2020
+      config: default
+      split: test
     metrics:
     - type: map_at_1
       value: 0.645
@@ -3671,6 +4095,8 @@ model-index:
     dataset:
       type: mteb/toxic_conversations_50k
       name: MTEB ToxicConversationsClassification
+      config: default
+      split: test
     metrics:
     - type: accuracy
       value: 62.7862
@@ -3683,6 +4109,8 @@ model-index:
     dataset:
       type: mteb/tweet_sentiment_extraction
       name: MTEB TweetSentimentExtractionClassification
+      config: default
+      split: test
     metrics:
     - type: accuracy
       value: 54.821731748726656
@@ -3693,6 +4121,8 @@ model-index:
     dataset:
       type: mteb/twentynewsgroups-clustering
       name: MTEB TwentyNewsgroupsClustering
+      config: default
+      split: test
     metrics:
     - type: v_measure
       value: 28.24295128553035
@@ -3701,6 +4131,8 @@ model-index:
     dataset:
       type: mteb/twittersemeval2015-pairclassification
       name: MTEB TwitterSemEval2015
+      config: default
+      split: test
     metrics:
     - type: cos_sim_accuracy
       value: 81.5640460153782
@@ -3753,6 +4185,8 @@ model-index:
     dataset:
       type: mteb/twitterurlcorpus-pairclassification
       name: MTEB TwitterURLCorpus
+      config: default
+      split: test
     metrics:
     - type: cos_sim_accuracy
       value: 86.63018589668955