Update README.md

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: 61.23880597014926
@@ -25,6 +27,8 @@ model-index:
     dataset:
       type: mteb/amazon_counterfactual
       name: MTEB AmazonCounterfactualClassification (de)
+      config: de
+      split: test
     metrics:
     - type: accuracy
       value: 56.88436830835117
@@ -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: 58.27586206896551
@@ -49,6 +55,8 @@ model-index:
     dataset:
       type: mteb/amazon_counterfactual
       name: MTEB AmazonCounterfactualClassification (ja)
+      config: ja
+      split: test
     metrics:
     - type: accuracy
       value: 54.64668094218415
@@ -61,6 +69,8 @@ model-index:
     dataset:
       type: mteb/amazon_polarity
       name: MTEB AmazonPolarityClassification
+      config: default
+      split: test
     metrics:
     - type: accuracy
       value: 65.401225
@@ -73,6 +83,8 @@ model-index:
     dataset:
       type: mteb/amazon_reviews_multi
       name: MTEB AmazonReviewsClassification (en)
+      config: en
+      split: test
     metrics:
     - type: accuracy
       value: 31.165999999999993
@@ -83,6 +95,8 @@ model-index:
     dataset:
       type: mteb/amazon_reviews_multi
       name: MTEB AmazonReviewsClassification (de)
+      config: de
+      split: test
     metrics:
     - type: accuracy
       value: 24.79
@@ -93,6 +107,8 @@ model-index:
     dataset:
       type: mteb/amazon_reviews_multi
       name: MTEB AmazonReviewsClassification (es)
+      config: es
+      split: test
     metrics:
     - type: accuracy
       value: 26.643999999999995
@@ -103,6 +119,8 @@ model-index:
     dataset:
       type: mteb/amazon_reviews_multi
       name: MTEB AmazonReviewsClassification (fr)
+      config: fr
+      split: test
     metrics:
     - type: accuracy
       value: 26.386000000000003
@@ -113,6 +131,8 @@ model-index:
     dataset:
       type: mteb/amazon_reviews_multi
       name: MTEB AmazonReviewsClassification (ja)
+      config: ja
+      split: test
     metrics:
     - type: accuracy
       value: 22.078000000000003
@@ -123,6 +143,8 @@ model-index:
     dataset:
       type: mteb/amazon_reviews_multi
       name: MTEB AmazonReviewsClassification (zh)
+      config: zh
+      split: test
     metrics:
     - type: accuracy
       value: 24.274
@@ -133,6 +155,8 @@ model-index:
     dataset:
       type: arguana
       name: MTEB ArguAna
+      config: default
+      split: test
     metrics:
     - type: map_at_1
       value: 22.404
@@ -199,6 +223,8 @@ model-index:
     dataset:
       type: mteb/arxiv-clustering-p2p
       name: MTEB ArxivClusteringP2P
+      config: default
+      split: test
     metrics:
     - type: v_measure
       value: 39.70858340673288
@@ -207,6 +233,8 @@ model-index:
     dataset:
       type: mteb/arxiv-clustering-s2s
       name: MTEB ArxivClusteringS2S
+      config: default
+      split: test
     metrics:
     - type: v_measure
       value: 28.242847713721048
@@ -215,6 +243,8 @@ model-index:
     dataset:
       type: mteb/askubuntudupquestions-reranking
       name: MTEB AskUbuntuDupQuestions
+      config: default
+      split: test
     metrics:
     - type: map
       value: 55.83700395192393
@@ -225,6 +255,8 @@ model-index:
     dataset:
       type: mteb/biosses-sts
       name: MTEB BIOSSES
+      config: default
+      split: test
     metrics:
     - type: cos_sim_pearson
       value: 79.25366801756223
@@ -243,6 +275,8 @@ model-index:
     dataset:
       type: mteb/banking77
       name: MTEB Banking77Classification
+      config: default
+      split: test
     metrics:
     - type: accuracy
       value: 77.70454545454545
@@ -253,6 +287,8 @@ model-index:
     dataset:
       type: mteb/biorxiv-clustering-p2p
       name: MTEB BiorxivClusteringP2P
+      config: default
+      split: test
     metrics:
     - type: v_measure
       value: 33.63260395543984
@@ -261,6 +297,8 @@ model-index:
     dataset:
       type: mteb/biorxiv-clustering-s2s
       name: MTEB BiorxivClusteringS2S
+      config: default
+      split: test
     metrics:
     - type: v_measure
       value: 27.038042665369925
@@ -269,6 +307,8 @@ model-index:
     dataset:
       type: BeIR/cqadupstack
       name: MTEB CQADupstackAndroidRetrieval
+      config: default
+      split: test
     metrics:
     - type: map_at_1
       value: 22.139
@@ -335,6 +375,8 @@ model-index:
     dataset:
       type: BeIR/cqadupstack
       name: MTEB CQADupstackEnglishRetrieval
+      config: default
+      split: test
     metrics:
     - type: map_at_1
       value: 20.652
@@ -401,6 +443,8 @@ model-index:
     dataset:
       type: BeIR/cqadupstack
       name: MTEB CQADupstackGamingRetrieval
+      config: default
+      split: test
     metrics:
     - type: map_at_1
       value: 25.180000000000003
@@ -467,6 +511,8 @@ model-index:
     dataset:
       type: BeIR/cqadupstack
       name: MTEB CQADupstackGisRetrieval
+      config: default
+      split: test
     metrics:
     - type: map_at_1
       value: 16.303
@@ -533,6 +579,8 @@ model-index:
     dataset:
       type: BeIR/cqadupstack
       name: MTEB CQADupstackMathematicaRetrieval
+      config: default
+      split: test
     metrics:
     - type: map_at_1
       value: 10.133000000000001
@@ -599,6 +647,8 @@ model-index:
     dataset:
       type: BeIR/cqadupstack
       name: MTEB CQADupstackPhysicsRetrieval
+      config: default
+      split: test
     metrics:
     - type: map_at_1
       value: 19.991999999999997
@@ -665,6 +715,8 @@ model-index:
     dataset:
       type: BeIR/cqadupstack
       name: MTEB CQADupstackProgrammersRetrieval
+      config: default
+      split: test
     metrics:
     - type: map_at_1
       value: 17.896
@@ -731,6 +783,8 @@ model-index:
     dataset:
       type: BeIR/cqadupstack
       name: MTEB CQADupstackRetrieval
+      config: default
+      split: test
     metrics:
     - type: map_at_1
       value: 17.195166666666665
@@ -797,6 +851,8 @@ model-index:
     dataset:
       type: BeIR/cqadupstack
       name: MTEB CQADupstackStatsRetrieval
+      config: default
+      split: test
     metrics:
     - type: map_at_1
       value: 16.779
@@ -863,6 +919,8 @@ model-index:
     dataset:
       type: BeIR/cqadupstack
       name: MTEB CQADupstackTexRetrieval
+      config: default
+      split: test
     metrics:
     - type: map_at_1
       value: 9.279
@@ -929,6 +987,8 @@ model-index:
     dataset:
       type: BeIR/cqadupstack
       name: MTEB CQADupstackUnixRetrieval
+      config: default
+      split: test
     metrics:
     - type: map_at_1
       value: 16.36
@@ -995,6 +1055,8 @@ model-index:
     dataset:
       type: BeIR/cqadupstack
       name: MTEB CQADupstackWebmastersRetrieval
+      config: default
+      split: test
     metrics:
     - type: map_at_1
       value: 17.39
@@ -1061,6 +1123,8 @@ model-index:
     dataset:
       type: BeIR/cqadupstack
       name: MTEB CQADupstackWordpressRetrieval
+      config: default
+      split: test
     metrics:
     - type: map_at_1
       value: 14.238999999999999
@@ -1127,6 +1191,8 @@ model-index:
     dataset:
       type: climate-fever
       name: MTEB ClimateFEVER
+      config: default
+      split: test
     metrics:
     - type: map_at_1
       value: 8.828
@@ -1193,6 +1259,8 @@ model-index:
     dataset:
       type: dbpedia-entity
       name: MTEB DBPedia
+      config: default
+      split: test
     metrics:
     - type: map_at_1
       value: 5.586
@@ -1259,6 +1327,8 @@ model-index:
     dataset:
       type: mteb/emotion
       name: MTEB EmotionClassification
+      config: default
+      split: test
     metrics:
     - type: accuracy
       value: 39.075
@@ -1269,6 +1339,8 @@ model-index:
     dataset:
       type: fever
       name: MTEB FEVER
+      config: default
+      split: test
     metrics:
     - type: map_at_1
       value: 43.519999999999996
@@ -1335,6 +1407,8 @@ model-index:
     dataset:
       type: fiqa
       name: MTEB FiQA2018
+      config: default
+      split: test
     metrics:
     - type: map_at_1
       value: 9.549000000000001
@@ -1401,6 +1475,8 @@ model-index:
     dataset:
       type: hotpotqa
       name: MTEB HotpotQA
+      config: default
+      split: test
     metrics:
     - type: map_at_1
       value: 25.544
@@ -1467,6 +1543,8 @@ model-index:
     dataset:
       type: mteb/imdb
       name: MTEB ImdbClassification
+      config: default
+      split: test
     metrics:
     - type: accuracy
       value: 58.6696
@@ -1479,6 +1557,8 @@ model-index:
     dataset:
       type: msmarco
       name: MTEB MSMARCO
+      config: default
+      split: validation
     metrics:
     - type: map_at_1
       value: 14.442
@@ -1545,6 +1625,8 @@ model-index:
     dataset:
       type: mteb/mtop_domain
       name: MTEB MTOPDomainClassification (en)
+      config: en
+      split: test
     metrics:
     - type: accuracy
       value: 86.95622435020519
@@ -1555,6 +1637,8 @@ model-index:
     dataset:
       type: mteb/mtop_domain
       name: MTEB MTOPDomainClassification (de)
+      config: de
+      split: test
     metrics:
     - type: accuracy
       value: 62.73034657650043
@@ -1565,6 +1649,8 @@ model-index:
     dataset:
       type: mteb/mtop_domain
       name: MTEB MTOPDomainClassification (es)
+      config: es
+      split: test
     metrics:
     - type: accuracy
       value: 67.54503002001334
@@ -1575,6 +1661,8 @@ model-index:
     dataset:
       type: mteb/mtop_domain
       name: MTEB MTOPDomainClassification (fr)
+      config: fr
+      split: test
     metrics:
     - type: accuracy
       value: 65.35233322893829
@@ -1585,6 +1673,8 @@ model-index:
     dataset:
       type: mteb/mtop_domain
       name: MTEB MTOPDomainClassification (hi)
+      config: hi
+      split: test
     metrics:
     - type: accuracy
       value: 45.37110075295806
@@ -1595,6 +1685,8 @@ model-index:
     dataset:
       type: mteb/mtop_domain
       name: MTEB MTOPDomainClassification (th)
+      config: th
+      split: test
     metrics:
     - type: accuracy
       value: 55.276672694394215
@@ -1605,6 +1697,8 @@ model-index:
     dataset:
       type: mteb/mtop_intent
       name: MTEB MTOPIntentClassification (en)
+      config: en
+      split: test
     metrics:
     - type: accuracy
       value: 62.25262197902417
@@ -1615,6 +1709,8 @@ model-index:
     dataset:
       type: mteb/mtop_intent
       name: MTEB MTOPIntentClassification (de)
+      config: de
+      split: test
     metrics:
     - type: accuracy
       value: 49.56043956043956
@@ -1625,6 +1721,8 @@ model-index:
     dataset:
       type: mteb/mtop_intent
       name: MTEB MTOPIntentClassification (es)
+      config: es
+      split: test
     metrics:
     - type: accuracy
       value: 49.93995997331555
@@ -1635,6 +1733,8 @@ model-index:
     dataset:
       type: mteb/mtop_intent
       name: MTEB MTOPIntentClassification (fr)
+      config: fr
+      split: test
     metrics:
     - type: accuracy
       value: 46.32947071719386
@@ -1645,6 +1745,8 @@ model-index:
     dataset:
       type: mteb/mtop_intent
       name: MTEB MTOPIntentClassification (hi)
+      config: hi
+      split: test
     metrics:
     - type: accuracy
       value: 32.208676945141626
@@ -1655,6 +1757,8 @@ model-index:
     dataset:
       type: mteb/mtop_intent
       name: MTEB MTOPIntentClassification (th)
+      config: th
+      split: test
     metrics:
     - type: accuracy
       value: 43.627486437613015
@@ -1665,6 +1769,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_intent
       name: MTEB MassiveIntentClassification (af)
+      config: af
+      split: test
     metrics:
     - type: accuracy
       value: 40.548083389374575
@@ -1675,6 +1781,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_intent
       name: MTEB MassiveIntentClassification (am)
+      config: am
+      split: test
     metrics:
     - type: accuracy
       value: 24.18291862811029
@@ -1685,6 +1793,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_intent
       name: MTEB MassiveIntentClassification (ar)
+      config: ar
+      split: test
     metrics:
     - type: accuracy
       value: 30.134498991257562
@@ -1695,6 +1805,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_intent
       name: MTEB MassiveIntentClassification (az)
+      config: az
+      split: test
     metrics:
     - type: accuracy
       value: 35.88433086751849
@@ -1705,6 +1817,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_intent
       name: MTEB MassiveIntentClassification (bn)
+      config: bn
+      split: test
     metrics:
     - type: accuracy
       value: 29.17283120376597
@@ -1715,6 +1829,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_intent
       name: MTEB MassiveIntentClassification (cy)
+      config: cy
+      split: test
     metrics:
     - type: accuracy
       value: 41.788836583725626
@@ -1725,6 +1841,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_intent
       name: MTEB MassiveIntentClassification (da)
+      config: da
+      split: test
     metrics:
     - type: accuracy
       value: 44.176193678547406
@@ -1735,6 +1853,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_intent
       name: MTEB MassiveIntentClassification (de)
+      config: de
+      split: test
     metrics:
     - type: accuracy
       value: 42.07464694014795
@@ -1745,6 +1865,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_intent
       name: MTEB MassiveIntentClassification (el)
+      config: el
+      split: test
     metrics:
     - type: accuracy
       value: 36.254203093476804
@@ -1755,6 +1877,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_intent
       name: MTEB MassiveIntentClassification (en)
+      config: en
+      split: test
     metrics:
     - type: accuracy
       value: 61.40887693342301
@@ -1765,6 +1889,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_intent
       name: MTEB MassiveIntentClassification (es)
+      config: es
+      split: test
     metrics:
     - type: accuracy
       value: 42.679892400807
@@ -1775,6 +1901,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_intent
       name: MTEB MassiveIntentClassification (fa)
+      config: fa
+      split: test
     metrics:
     - type: accuracy
       value: 35.59179556153329
@@ -1785,6 +1913,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_intent
       name: MTEB MassiveIntentClassification (fi)
+      config: fi
+      split: test
     metrics:
     - type: accuracy
       value: 40.036987222595826
@@ -1795,6 +1925,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_intent
       name: MTEB MassiveIntentClassification (fr)
+      config: fr
+      split: test
     metrics:
     - type: accuracy
       value: 43.43981170141224
@@ -1805,6 +1937,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_intent
       name: MTEB MassiveIntentClassification (he)
+      config: he
+      split: test
     metrics:
     - type: accuracy
       value: 31.593813046402154
@@ -1815,6 +1949,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_intent
       name: MTEB MassiveIntentClassification (hi)
+      config: hi
+      split: test
     metrics:
     - type: accuracy
       value: 27.044384667114997
@@ -1825,6 +1961,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_intent
       name: MTEB MassiveIntentClassification (hu)
+      config: hu
+      split: test
     metrics:
     - type: accuracy
       value: 38.453261600538
@@ -1835,6 +1973,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_intent
       name: MTEB MassiveIntentClassification (hy)
+      config: hy
+      split: test
     metrics:
     - type: accuracy
       value: 27.979152656355076
@@ -1845,6 +1985,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_intent
       name: MTEB MassiveIntentClassification (id)
+      config: id
+      split: test
     metrics:
     - type: accuracy
       value: 43.97108271687963
@@ -1855,6 +1997,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_intent
       name: MTEB MassiveIntentClassification (is)
+      config: is
+      split: test
     metrics:
     - type: accuracy
       value: 40.302622730329524
@@ -1865,6 +2009,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_intent
       name: MTEB MassiveIntentClassification (it)
+      config: it
+      split: test
     metrics:
     - type: accuracy
       value: 45.474108944182916
@@ -1875,6 +2021,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_intent
       name: MTEB MassiveIntentClassification (ja)
+      config: ja
+      split: test
     metrics:
     - type: accuracy
       value: 45.60860793544048
@@ -1885,6 +2033,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_intent
       name: MTEB MassiveIntentClassification (jv)
+      config: jv
+      split: test
     metrics:
     - type: accuracy
       value: 38.668459986550104
@@ -1895,6 +2045,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_intent
       name: MTEB MassiveIntentClassification (ka)
+      config: ka
+      split: test
     metrics:
     - type: accuracy
       value: 25.6523201075992
@@ -1905,6 +2057,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_intent
       name: MTEB MassiveIntentClassification (km)
+      config: km
+      split: test
     metrics:
     - type: accuracy
       value: 28.295225285810353
@@ -1915,6 +2069,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_intent
       name: MTEB MassiveIntentClassification (kn)
+      config: kn
+      split: test
     metrics:
     - type: accuracy
       value: 23.480161398789505
@@ -1925,6 +2081,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_intent
       name: MTEB MassiveIntentClassification (ko)
+      config: ko
+      split: test
     metrics:
     - type: accuracy
       value: 36.55682582380632
@@ -1935,6 +2093,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_intent
       name: MTEB MassiveIntentClassification (lv)
+      config: lv
+      split: test
     metrics:
     - type: accuracy
       value: 41.84936112979153
@@ -1945,6 +2105,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_intent
       name: MTEB MassiveIntentClassification (ml)
+      config: ml
+      split: test
     metrics:
     - type: accuracy
       value: 24.90921318090114
@@ -1955,6 +2117,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_intent
       name: MTEB MassiveIntentClassification (mn)
+      config: mn
+      split: test
     metrics:
     - type: accuracy
       value: 29.86213853396099
@@ -1965,6 +2129,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_intent
       name: MTEB MassiveIntentClassification (ms)
+      config: ms
+      split: test
     metrics:
     - type: accuracy
       value: 42.42098184263618
@@ -1975,6 +2141,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_intent
       name: MTEB MassiveIntentClassification (my)
+      config: my
+      split: test
     metrics:
     - type: accuracy
       value: 25.131136516476126
@@ -1985,6 +2153,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_intent
       name: MTEB MassiveIntentClassification (nb)
+      config: nb
+      split: test
     metrics:
     - type: accuracy
       value: 39.81506388702084
@@ -1995,6 +2165,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_intent
       name: MTEB MassiveIntentClassification (nl)
+      config: nl
+      split: test
     metrics:
     - type: accuracy
       value: 43.62138533960995
@@ -2005,6 +2177,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_intent
       name: MTEB MassiveIntentClassification (pl)
+      config: pl
+      split: test
     metrics:
     - type: accuracy
       value: 42.19569603227976
@@ -2015,6 +2189,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_intent
       name: MTEB MassiveIntentClassification (pt)
+      config: pt
+      split: test
     metrics:
     - type: accuracy
       value: 45.20847343644923
@@ -2025,6 +2201,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_intent
       name: MTEB MassiveIntentClassification (ro)
+      config: ro
+      split: test
     metrics:
     - type: accuracy
       value: 41.80901143241426
@@ -2035,6 +2213,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_intent
       name: MTEB MassiveIntentClassification (ru)
+      config: ru
+      split: test
     metrics:
     - type: accuracy
       value: 35.96839273705447
@@ -2045,6 +2225,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_intent
       name: MTEB MassiveIntentClassification (sl)
+      config: sl
+      split: test
     metrics:
     - type: accuracy
       value: 40.60524546065905
@@ -2055,6 +2237,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_intent
       name: MTEB MassiveIntentClassification (sq)
+      config: sq
+      split: test
     metrics:
     - type: accuracy
       value: 42.75722932078009
@@ -2065,6 +2249,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_intent
       name: MTEB MassiveIntentClassification (sv)
+      config: sv
+      split: test
     metrics:
     - type: accuracy
       value: 42.347007397444514
@@ -2075,6 +2261,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_intent
       name: MTEB MassiveIntentClassification (sw)
+      config: sw
+      split: test
     metrics:
     - type: accuracy
       value: 41.12306657700067
@@ -2085,6 +2273,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_intent
       name: MTEB MassiveIntentClassification (ta)
+      config: ta
+      split: test
     metrics:
     - type: accuracy
       value: 24.603227975790183
@@ -2095,6 +2285,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_intent
       name: MTEB MassiveIntentClassification (te)
+      config: te
+      split: test
     metrics:
     - type: accuracy
       value: 25.03698722259583
@@ -2105,6 +2297,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_intent
       name: MTEB MassiveIntentClassification (th)
+      config: th
+      split: test
     metrics:
     - type: accuracy
       value: 35.40013449899126
@@ -2115,6 +2309,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_intent
       name: MTEB MassiveIntentClassification (tl)
+      config: tl
+      split: test
     metrics:
     - type: accuracy
       value: 41.19031607262945
@@ -2125,6 +2321,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_intent
       name: MTEB MassiveIntentClassification (tr)
+      config: tr
+      split: test
     metrics:
     - type: accuracy
       value: 36.405514458641555
@@ -2135,6 +2333,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_intent
       name: MTEB MassiveIntentClassification (ur)
+      config: ur
+      split: test
     metrics:
     - type: accuracy
       value: 25.934767989240076
@@ -2145,6 +2345,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_intent
       name: MTEB MassiveIntentClassification (vi)
+      config: vi
+      split: test
     metrics:
     - type: accuracy
       value: 38.79959650302622
@@ -2155,6 +2357,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_intent
       name: MTEB MassiveIntentClassification (zh-CN)
+      config: zh-CN
+      split: test
     metrics:
     - type: accuracy
       value: 46.244115669132476
@@ -2165,6 +2369,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_intent
       name: MTEB MassiveIntentClassification (zh-TW)
+      config: zh-TW
+      split: test
     metrics:
     - type: accuracy
       value: 42.30665770006724
@@ -2175,6 +2381,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_scenario
       name: MTEB MassiveScenarioClassification (af)
+      config: af
+      split: test
     metrics:
     - type: accuracy
       value: 43.2481506388702
@@ -2185,6 +2393,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_scenario
       name: MTEB MassiveScenarioClassification (am)
+      config: am
+      split: test
     metrics:
     - type: accuracy
       value: 25.30262273032952
@@ -2195,6 +2405,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_scenario
       name: MTEB MassiveScenarioClassification (ar)
+      config: ar
+      split: test
     metrics:
     - type: accuracy
       value: 32.07128446536651
@@ -2205,6 +2417,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_scenario
       name: MTEB MassiveScenarioClassification (az)
+      config: az
+      split: test
     metrics:
     - type: accuracy
       value: 36.681237390719566
@@ -2215,6 +2429,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_scenario
       name: MTEB MassiveScenarioClassification (bn)
+      config: bn
+      split: test
     metrics:
     - type: accuracy
       value: 29.56624075319435
@@ -2225,6 +2441,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_scenario
       name: MTEB MassiveScenarioClassification (cy)
+      config: cy
+      split: test
     metrics:
     - type: accuracy
       value: 42.1049092131809
@@ -2235,6 +2453,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_scenario
       name: MTEB MassiveScenarioClassification (da)
+      config: da
+      split: test
     metrics:
     - type: accuracy
       value: 45.44384667114997
@@ -2245,6 +2465,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_scenario
       name: MTEB MassiveScenarioClassification (de)
+      config: de
+      split: test
     metrics:
     - type: accuracy
       value: 43.211163416274374
@@ -2255,6 +2477,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_scenario
       name: MTEB MassiveScenarioClassification (el)
+      config: el
+      split: test
     metrics:
     - type: accuracy
       value: 36.503026227303295
@@ -2265,6 +2489,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_scenario
       name: MTEB MassiveScenarioClassification (en)
+      config: en
+      split: test
     metrics:
     - type: accuracy
       value: 69.73772696704773
@@ -2275,6 +2501,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_scenario
       name: MTEB MassiveScenarioClassification (es)
+      config: es
+      split: test
     metrics:
     - type: accuracy
       value: 44.078681909885674
@@ -2285,6 +2513,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_scenario
       name: MTEB MassiveScenarioClassification (fa)
+      config: fa
+      split: test
     metrics:
     - type: accuracy
       value: 32.61264290517821
@@ -2295,6 +2525,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_scenario
       name: MTEB MassiveScenarioClassification (fi)
+      config: fi
+      split: test
     metrics:
     - type: accuracy
       value: 40.35642232683255
@@ -2305,6 +2537,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_scenario
       name: MTEB MassiveScenarioClassification (fr)
+      config: fr
+      split: test
     metrics:
     - type: accuracy
       value: 45.06724949562878
@@ -2315,6 +2549,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_scenario
       name: MTEB MassiveScenarioClassification (he)
+      config: he
+      split: test
     metrics:
     - type: accuracy
       value: 32.178883658372555
@@ -2325,6 +2561,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_scenario
       name: MTEB MassiveScenarioClassification (hi)
+      config: hi
+      split: test
     metrics:
     - type: accuracy
       value: 26.903160726294555
@@ -2335,6 +2573,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_scenario
       name: MTEB MassiveScenarioClassification (hu)
+      config: hu
+      split: test
     metrics:
     - type: accuracy
       value: 40.379959650302624
@@ -2345,6 +2585,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_scenario
       name: MTEB MassiveScenarioClassification (hy)
+      config: hy
+      split: test
     metrics:
     - type: accuracy
       value: 28.375924680564896
@@ -2355,6 +2597,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_scenario
       name: MTEB MassiveScenarioClassification (id)
+      config: id
+      split: test
     metrics:
     - type: accuracy
       value: 44.361129791526565
@@ -2365,6 +2609,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_scenario
       name: MTEB MassiveScenarioClassification (is)
+      config: is
+      split: test
     metrics:
     - type: accuracy
       value: 39.290517821116346
@@ -2375,6 +2621,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_scenario
       name: MTEB MassiveScenarioClassification (it)
+      config: it
+      split: test
     metrics:
     - type: accuracy
       value: 46.4694014794889
@@ -2385,6 +2633,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_scenario
       name: MTEB MassiveScenarioClassification (ja)
+      config: ja
+      split: test
     metrics:
     - type: accuracy
       value: 46.25756556825824
@@ -2395,6 +2645,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_scenario
       name: MTEB MassiveScenarioClassification (jv)
+      config: jv
+      split: test
     metrics:
     - type: accuracy
       value: 41.12642905178212
@@ -2405,6 +2657,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_scenario
       name: MTEB MassiveScenarioClassification (ka)
+      config: ka
+      split: test
     metrics:
     - type: accuracy
       value: 24.72763954270343
@@ -2415,6 +2669,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_scenario
       name: MTEB MassiveScenarioClassification (km)
+      config: km
+      split: test
     metrics:
     - type: accuracy
       value: 29.741089441829182
@@ -2425,6 +2681,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_scenario
       name: MTEB MassiveScenarioClassification (kn)
+      config: kn
+      split: test
     metrics:
     - type: accuracy
       value: 23.850033624747816
@@ -2435,6 +2693,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_scenario
       name: MTEB MassiveScenarioClassification (ko)
+      config: ko
+      split: test
     metrics:
     - type: accuracy
       value: 36.56691324815064
@@ -2445,6 +2705,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_scenario
       name: MTEB MassiveScenarioClassification (lv)
+      config: lv
+      split: test
     metrics:
     - type: accuracy
       value: 40.928043039677206
@@ -2455,6 +2717,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_scenario
       name: MTEB MassiveScenarioClassification (ml)
+      config: ml
+      split: test
     metrics:
     - type: accuracy
       value: 25.527908540685946
@@ -2465,6 +2729,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_scenario
       name: MTEB MassiveScenarioClassification (mn)
+      config: mn
+      split: test
     metrics:
     - type: accuracy
       value: 29.105581708137183
@@ -2475,6 +2741,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_scenario
       name: MTEB MassiveScenarioClassification (ms)
+      config: ms
+      split: test
     metrics:
     - type: accuracy
       value: 43.78614660390047
@@ -2485,6 +2753,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_scenario
       name: MTEB MassiveScenarioClassification (my)
+      config: my
+      split: test
     metrics:
     - type: accuracy
       value: 27.269670477471415
@@ -2495,6 +2765,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_scenario
       name: MTEB MassiveScenarioClassification (nb)
+      config: nb
+      split: test
     metrics:
     - type: accuracy
       value: 39.018157363819775
@@ -2505,6 +2777,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_scenario
       name: MTEB MassiveScenarioClassification (nl)
+      config: nl
+      split: test
     metrics:
     - type: accuracy
       value: 45.35978480161399
@@ -2515,6 +2789,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_scenario
       name: MTEB MassiveScenarioClassification (pl)
+      config: pl
+      split: test
     metrics:
     - type: accuracy
       value: 41.89307330195023
@@ -2525,6 +2801,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_scenario
       name: MTEB MassiveScenarioClassification (pt)
+      config: pt
+      split: test
     metrics:
     - type: accuracy
       value: 45.901143241425686
@@ -2535,6 +2813,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_scenario
       name: MTEB MassiveScenarioClassification (ro)
+      config: ro
+      split: test
     metrics:
     - type: accuracy
       value: 44.11566913248151
@@ -2545,6 +2825,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_scenario
       name: MTEB MassiveScenarioClassification (ru)
+      config: ru
+      split: test
     metrics:
     - type: accuracy
       value: 32.76395427034297
@@ -2555,6 +2837,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_scenario
       name: MTEB MassiveScenarioClassification (sl)
+      config: sl
+      split: test
     metrics:
     - type: accuracy
       value: 40.504371217215876
@@ -2565,6 +2849,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_scenario
       name: MTEB MassiveScenarioClassification (sq)
+      config: sq
+      split: test
     metrics:
     - type: accuracy
       value: 42.51849361129792
@@ -2575,6 +2861,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_scenario
       name: MTEB MassiveScenarioClassification (sv)
+      config: sv
+      split: test
     metrics:
     - type: accuracy
       value: 42.293207800941495
@@ -2585,6 +2873,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_scenario
       name: MTEB MassiveScenarioClassification (sw)
+      config: sw
+      split: test
     metrics:
     - type: accuracy
       value: 42.9993275050437
@@ -2595,6 +2885,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_scenario
       name: MTEB MassiveScenarioClassification (ta)
+      config: ta
+      split: test
     metrics:
     - type: accuracy
       value: 28.32548755884331
@@ -2605,6 +2897,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_scenario
       name: MTEB MassiveScenarioClassification (te)
+      config: te
+      split: test
     metrics:
     - type: accuracy
       value: 26.593813046402154
@@ -2615,6 +2909,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_scenario
       name: MTEB MassiveScenarioClassification (th)
+      config: th
+      split: test
     metrics:
     - type: accuracy
       value: 36.788836583725626
@@ -2625,6 +2921,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_scenario
       name: MTEB MassiveScenarioClassification (tl)
+      config: tl
+      split: test
     metrics:
     - type: accuracy
       value: 42.5689307330195
@@ -2635,6 +2933,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_scenario
       name: MTEB MassiveScenarioClassification (tr)
+      config: tr
+      split: test
     metrics:
     - type: accuracy
       value: 37.09482178883658
@@ -2645,6 +2945,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_scenario
       name: MTEB MassiveScenarioClassification (ur)
+      config: ur
+      split: test
     metrics:
     - type: accuracy
       value: 28.836583725622063
@@ -2655,6 +2957,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_scenario
       name: MTEB MassiveScenarioClassification (vi)
+      config: vi
+      split: test
     metrics:
     - type: accuracy
       value: 37.357094821788834
@@ -2665,6 +2969,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_scenario
       name: MTEB MassiveScenarioClassification (zh-CN)
+      config: zh-CN
+      split: test
     metrics:
     - type: accuracy
       value: 49.37794216543375
@@ -2675,6 +2981,8 @@ model-index:
     dataset:
       type: mteb/amazon_massive_scenario
       name: MTEB MassiveScenarioClassification (zh-TW)
+      config: zh-TW
+      split: test
     metrics:
     - type: accuracy
       value: 44.42165433759248
@@ -2685,6 +2993,8 @@ model-index:
     dataset:
       type: mteb/medrxiv-clustering-p2p
       name: MTEB MedrxivClusteringP2P
+      config: default
+      split: test
     metrics:
     - type: v_measure
       value: 31.374938993074252
@@ -2693,6 +3003,8 @@ model-index:
     dataset:
       type: mteb/medrxiv-clustering-s2s
       name: MTEB MedrxivClusteringS2S
+      config: default
+      split: test
     metrics:
     - type: v_measure
       value: 26.871455379644093
@@ -2701,6 +3013,8 @@ model-index:
     dataset:
       type: mteb/mind_small
       name: MTEB MindSmallReranking
+      config: default
+      split: test
     metrics:
     - type: map
       value: 30.402396942935333
@@ -2711,6 +3025,8 @@ model-index:
     dataset:
       type: nfcorpus
       name: MTEB NFCorpus
+      config: default
+      split: test
     metrics:
     - type: map_at_1
       value: 3.7740000000000005
@@ -2777,6 +3093,8 @@ model-index:
     dataset:
       type: nq
       name: MTEB NQ
+      config: default
+      split: test
     metrics:
     - type: map_at_1
       value: 15.620999999999999
@@ -2843,6 +3161,8 @@ model-index:
     dataset:
       type: quora
       name: MTEB QuoraRetrieval
+      config: default
+      split: test
     metrics:
     - type: map_at_1
       value: 54.717000000000006
@@ -2909,6 +3229,8 @@ model-index:
     dataset:
       type: mteb/reddit-clustering
       name: MTEB RedditClustering
+      config: default
+      split: test
     metrics:
     - type: v_measure
       value: 40.23390747226228
@@ -2917,6 +3239,8 @@ model-index:
     dataset:
       type: mteb/reddit-clustering-p2p
       name: MTEB RedditClusteringP2P
+      config: default
+      split: test
     metrics:
     - type: v_measure
       value: 49.090518272935626
@@ -2925,6 +3249,8 @@ model-index:
     dataset:
       type: scidocs
       name: MTEB SCIDOCS
+      config: default
+      split: test
     metrics:
     - type: map_at_1
       value: 3.028
@@ -2991,6 +3317,8 @@ model-index:
     dataset:
       type: mteb/sickr-sts
       name: MTEB SICK-R
+      config: default
+      split: test
     metrics:
     - type: cos_sim_pearson
       value: 76.62983928119752
@@ -3009,6 +3337,8 @@ model-index:
     dataset:
       type: mteb/sts12-sts
       name: MTEB STS12
+      config: default
+      split: test
     metrics:
     - type: cos_sim_pearson
       value: 74.42679147085553
@@ -3027,6 +3357,8 @@ model-index:
     dataset:
       type: mteb/sts13-sts
       name: MTEB STS13
+      config: default
+      split: test
     metrics:
     - type: cos_sim_pearson
       value: 75.62472426599543
@@ -3045,6 +3377,8 @@ model-index:
     dataset:
       type: mteb/sts14-sts
       name: MTEB STS14
+      config: default
+      split: test
     metrics:
     - type: cos_sim_pearson
       value: 74.48227705407035
@@ -3063,6 +3397,8 @@ model-index:
     dataset:
       type: mteb/sts15-sts
       name: MTEB STS15
+      config: default
+      split: test
     metrics:
     - type: cos_sim_pearson
       value: 78.1566527175902
@@ -3081,6 +3417,8 @@ model-index:
     dataset:
       type: mteb/sts16-sts
       name: MTEB STS16
+      config: default
+      split: test
     metrics:
     - type: cos_sim_pearson
       value: 75.068454465977
@@ -3099,6 +3437,8 @@ model-index:
     dataset:
       type: mteb/sts17-crosslingual-sts
       name: MTEB STS17 (ko-ko)
+      config: ko-ko
+      split: test
     metrics:
     - type: cos_sim_pearson
       value: 39.43327289939437
@@ -3117,6 +3457,8 @@ model-index:
     dataset:
       type: mteb/sts17-crosslingual-sts
       name: MTEB STS17 (ar-ar)
+      config: ar-ar
+      split: test
     metrics:
     - type: cos_sim_pearson
       value: 55.54431928210687
@@ -3135,6 +3477,8 @@ model-index:
     dataset:
       type: mteb/sts17-crosslingual-sts
       name: MTEB STS17 (en-ar)
+      config: en-ar
+      split: test
     metrics:
     - type: cos_sim_pearson
       value: 11.378463868809098
@@ -3153,6 +3497,8 @@ model-index:
     dataset:
       type: mteb/sts17-crosslingual-sts
       name: MTEB STS17 (en-de)
+      config: en-de
+      split: test
     metrics:
     - type: cos_sim_pearson
       value: 32.71403560929013
@@ -3171,6 +3517,8 @@ model-index:
     dataset:
       type: mteb/sts17-crosslingual-sts
       name: MTEB STS17 (en-en)
+      config: en-en
+      split: test
     metrics:
     - type: cos_sim_pearson
       value: 83.36340470799158
@@ -3189,6 +3537,8 @@ model-index:
     dataset:
       type: mteb/sts17-crosslingual-sts
       name: MTEB STS17 (en-tr)
+      config: en-tr
+      split: test
     metrics:
     - type: cos_sim_pearson
       value: 1.9200044163754912
@@ -3207,6 +3557,8 @@ model-index:
     dataset:
       type: mteb/sts17-crosslingual-sts
       name: MTEB STS17 (es-en)
+      config: es-en
+      split: test
     metrics:
     - type: cos_sim_pearson
       value: 26.561262451099577
@@ -3225,6 +3577,8 @@ model-index:
     dataset:
       type: mteb/sts17-crosslingual-sts
       name: MTEB STS17 (es-es)
+      config: es-es
+      split: test
     metrics:
     - type: cos_sim_pearson
       value: 69.7544202001433
@@ -3243,6 +3597,8 @@ model-index:
     dataset:
       type: mteb/sts17-crosslingual-sts
       name: MTEB STS17 (fr-en)
+      config: fr-en
+      split: test
     metrics:
     - type: cos_sim_pearson
       value: 27.70511842301491
@@ -3261,6 +3617,8 @@ model-index:
     dataset:
       type: mteb/sts17-crosslingual-sts
       name: MTEB STS17 (it-en)
+      config: it-en
+      split: test
     metrics:
     - type: cos_sim_pearson
       value: 24.226521799447692
@@ -3279,6 +3637,8 @@ model-index:
     dataset:
       type: mteb/sts17-crosslingual-sts
       name: MTEB STS17 (nl-en)
+      config: nl-en
+      split: test
     metrics:
     - type: cos_sim_pearson
       value: 29.131412364061234
@@ -3297,6 +3657,8 @@ model-index:
     dataset:
       type: mteb/sts22-crosslingual-sts
       name: MTEB STS22 (en)
+      config: en
+      split: test
     metrics:
     - type: cos_sim_pearson
       value: 64.04750650962879
@@ -3315,6 +3677,8 @@ model-index:
     dataset:
       type: mteb/sts22-crosslingual-sts
       name: MTEB STS22 (de)
+      config: de
+      split: test
     metrics:
     - type: cos_sim_pearson
       value: 19.26519187000913
@@ -3333,6 +3697,8 @@ model-index:
     dataset:
       type: mteb/sts22-crosslingual-sts
       name: MTEB STS22 (es)
+      config: es
+      split: test
     metrics:
     - type: cos_sim_pearson
       value: 34.221261828226936
@@ -3351,6 +3717,8 @@ model-index:
     dataset:
       type: mteb/sts22-crosslingual-sts
       name: MTEB STS22 (pl)
+      config: pl
+      split: test
     metrics:
     - type: cos_sim_pearson
       value: 3.620381732096531
@@ -3369,6 +3737,8 @@ model-index:
     dataset:
       type: mteb/sts22-crosslingual-sts
       name: MTEB STS22 (tr)
+      config: tr
+      split: test
     metrics:
     - type: cos_sim_pearson
       value: 16.69489628726267
@@ -3387,6 +3757,8 @@ model-index:
     dataset:
       type: mteb/sts22-crosslingual-sts
       name: MTEB STS22 (ar)
+      config: ar
+      split: test
     metrics:
     - type: cos_sim_pearson
       value: 9.134927430889528
@@ -3405,6 +3777,8 @@ model-index:
     dataset:
       type: mteb/sts22-crosslingual-sts
       name: MTEB STS22 (ru)
+      config: ru
+      split: test
     metrics:
     - type: cos_sim_pearson
       value: 3.6386482942352085
@@ -3423,6 +3797,8 @@ model-index:
     dataset:
       type: mteb/sts22-crosslingual-sts
       name: MTEB STS22 (zh)
+      config: zh
+      split: test
     metrics:
     - type: cos_sim_pearson
       value: 2.972091574908432
@@ -3441,6 +3817,8 @@ model-index:
     dataset:
       type: mteb/sts22-crosslingual-sts
       name: MTEB STS22 (fr)
+      config: fr
+      split: test
     metrics:
     - type: cos_sim_pearson
       value: 54.4745185734135
@@ -3459,6 +3837,8 @@ model-index:
     dataset:
       type: mteb/sts22-crosslingual-sts
       name: MTEB STS22 (de-en)
+      config: de-en
+      split: test
     metrics:
     - type: cos_sim_pearson
       value: 49.37865412588201
@@ -3477,6 +3857,8 @@ model-index:
     dataset:
       type: mteb/sts22-crosslingual-sts
       name: MTEB STS22 (es-en)
+      config: es-en
+      split: test
     metrics:
     - type: cos_sim_pearson
       value: 44.925652392562135
@@ -3495,6 +3877,8 @@ model-index:
     dataset:
       type: mteb/sts22-crosslingual-sts
       name: MTEB STS22 (it)
+      config: it
+      split: test
     metrics:
     - type: cos_sim_pearson
       value: 45.241690321111875
@@ -3513,6 +3897,8 @@ model-index:
     dataset:
       type: mteb/sts22-crosslingual-sts
       name: MTEB STS22 (pl-en)
+      config: pl-en
+      split: test
     metrics:
     - type: cos_sim_pearson
       value: 36.42138324083909
@@ -3531,6 +3917,8 @@ model-index:
     dataset:
       type: mteb/sts22-crosslingual-sts
       name: MTEB STS22 (zh-en)
+      config: zh-en
+      split: test
     metrics:
     - type: cos_sim_pearson
       value: 26.55350664089358
@@ -3549,6 +3937,8 @@ model-index:
     dataset:
       type: mteb/sts22-crosslingual-sts
       name: MTEB STS22 (es-it)
+      config: es-it
+      split: test
     metrics:
     - type: cos_sim_pearson
       value: 38.54682179114309
@@ -3567,6 +3957,8 @@ model-index:
     dataset:
       type: mteb/sts22-crosslingual-sts
       name: MTEB STS22 (de-fr)
+      config: de-fr
+      split: test
     metrics:
     - type: cos_sim_pearson
       value: 35.12956772546032
@@ -3585,6 +3977,8 @@ model-index:
     dataset:
       type: mteb/sts22-crosslingual-sts
       name: MTEB STS22 (de-pl)
+      config: de-pl
+      split: test
     metrics:
     - type: cos_sim_pearson
       value: 30.507667380509634
@@ -3603,6 +3997,8 @@ model-index:
     dataset:
       type: mteb/sts22-crosslingual-sts
       name: MTEB STS22 (fr-pl)
+      config: fr-pl
+      split: test
     metrics:
     - type: cos_sim_pearson
       value: 71.10820459712156
@@ -3621,6 +4017,8 @@ model-index:
     dataset:
       type: mteb/stsbenchmark-sts
       name: MTEB STSBenchmark
+      config: default
+      split: test
     metrics:
     - type: cos_sim_pearson
       value: 76.53032504460737
@@ -3639,6 +4037,8 @@ model-index:
     dataset:
       type: mteb/scidocs-reranking
       name: MTEB SciDocsRR
+      config: default
+      split: test
     metrics:
     - type: map
       value: 71.33941904192648
@@ -3649,6 +4049,8 @@ model-index:
     dataset:
       type: scifact
       name: MTEB SciFact
+      config: default
+      split: test
     metrics:
     - type: map_at_1
       value: 43.333
@@ -3715,6 +4117,8 @@ model-index:
     dataset:
       type: mteb/sprintduplicatequestions-pairclassification
       name: MTEB SprintDuplicateQuestions
+      config: default
+      split: test
     metrics:
     - type: cos_sim_accuracy
       value: 99.7
@@ -3767,6 +4171,8 @@ model-index:
     dataset:
       type: mteb/stackexchange-clustering
       name: MTEB StackExchangeClustering
+      config: default
+      split: test
     metrics:
     - type: v_measure
       value: 52.74481093815175
@@ -3775,6 +4181,8 @@ model-index:
     dataset:
       type: mteb/stackexchange-clustering-p2p
       name: MTEB StackExchangeClusteringP2P
+      config: default
+      split: test
     metrics:
     - type: v_measure
       value: 32.65999453562101
@@ -3783,6 +4191,8 @@ model-index:
     dataset:
       type: mteb/stackoverflowdupquestions-reranking
       name: MTEB StackOverflowDupQuestions
+      config: default
+      split: test
     metrics:
     - type: map
       value: 44.74498464555465
@@ -3793,6 +4203,8 @@ model-index:
     dataset:
       type: mteb/summeval
       name: MTEB SummEval
+      config: default
+      split: test
     metrics:
     - type: cos_sim_pearson
       value: 29.5961822471627
@@ -3807,6 +4219,8 @@ model-index:
     dataset:
       type: trec-covid
       name: MTEB TRECCOVID
+      config: default
+      split: test
     metrics:
     - type: map_at_1
       value: 0.241
@@ -3873,6 +4287,8 @@ model-index:
     dataset:
       type: webis-touche2020
       name: MTEB Touche2020
+      config: default
+      split: test
     metrics:
     - type: map_at_1
       value: 2.782
@@ -3939,6 +4355,8 @@ model-index:
     dataset:
       type: mteb/toxic_conversations_50k
       name: MTEB ToxicConversationsClassification
+      config: default
+      split: test
     metrics:
     - type: accuracy
       value: 62.657999999999994
@@ -3951,6 +4369,8 @@ model-index:
     dataset:
       type: mteb/tweet_sentiment_extraction
       name: MTEB TweetSentimentExtractionClassification
+      config: default
+      split: test
     metrics:
     - type: accuracy
       value: 52.40803621958121
@@ -3961,6 +4381,8 @@ model-index:
     dataset:
       type: mteb/twentynewsgroups-clustering
       name: MTEB TwentyNewsgroupsClustering
+      config: default
+      split: test
     metrics:
     - type: v_measure
       value: 32.12697126747911
@@ -3969,6 +4391,8 @@ model-index:
     dataset:
       type: mteb/twittersemeval2015-pairclassification
       name: MTEB TwitterSemEval2015
+      config: default
+      split: test
     metrics:
     - type: cos_sim_accuracy
       value: 80.69976753889253
@@ -4021,6 +4445,8 @@ model-index:
     dataset:
       type: mteb/twitterurlcorpus-pairclassification
       name: MTEB TwitterURLCorpus
+      config: default
+      split: test
     metrics:
     - type: cos_sim_accuracy
       value: 86.90573213800597