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493
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2265
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2272
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2278
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2282
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+ name: MTEB StackOverflowDupQuestions
2291
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2302
+ type: mteb/summeval
2303
+ name: MTEB SummEval
2304
+ config: default
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2306
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2308
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+ type: trec-covid
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+ name: MTEB TRECCOVID
2321
+ config: default
2322
+ split: test
2323
+ revision: None
2324
+ metrics:
2325
+ - type: map_at_1
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+ - type: ndcg_at_5
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+ - type: precision_at_1
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+ - type: precision_at_3
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+ - type: recall_at_1
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+ - type: recall_at_100
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+ - type: recall_at_1000
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+ - type: recall_at_3
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+ - type: recall_at_5
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+ value: 0.983
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+ - task:
2386
+ type: Retrieval
2387
+ dataset:
2388
+ type: webis-touche2020
2389
+ name: MTEB Touche2020
2390
+ config: default
2391
+ split: test
2392
+ revision: None
2393
+ metrics:
2394
+ - type: map_at_1
2395
+ value: 2.29
2396
+ - type: map_at_10
2397
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+ - type: map_at_100
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+ - type: map_at_1000
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+ - type: map_at_5
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+ - type: mrr_at_1
2407
+ value: 28.571
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+ - type: mrr_at_10
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+ value: 45.699
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+ - type: mrr_at_100
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+ value: 46.461000000000006
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+ - type: mrr_at_1000
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+ - type: mrr_at_3
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+ value: 41.837
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+ - type: mrr_at_5
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+ value: 43.163000000000004
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+ - type: ndcg_at_1
2419
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+ - type: ndcg_at_10
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+ value: 23.544999999999998
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2424
+ - type: ndcg_at_1000
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+ - type: precision_at_1
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+ value: 1.484
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+ - type: precision_at_3
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+ value: 29.932
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+ - type: precision_at_5
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+ value: 26.531
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+ - type: recall_at_1
2443
+ value: 2.29
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+ - type: recall_at_10
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+ - type: recall_at_100
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+ - type: recall_at_1000
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+ - type: recall_at_3
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+ value: 6.433
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+ - type: recall_at_5
2453
+ value: 9.484
2454
+ - task:
2455
+ type: Classification
2456
+ dataset:
2457
+ type: mteb/toxic_conversations_50k
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+ name: MTEB ToxicConversationsClassification
2459
+ config: default
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+ split: test
2461
+ revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
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+ metrics:
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+ - type: f1
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+ - task:
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+ type: Classification
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+ dataset:
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+ type: mteb/tweet_sentiment_extraction
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+ name: MTEB TweetSentimentExtractionClassification
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+ config: default
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+ split: test
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+ revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
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+ metrics:
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+ - type: accuracy
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+ - type: f1
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+ - task:
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+ type: Clustering
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+ dataset:
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+ type: mteb/twentynewsgroups-clustering
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+ name: MTEB TwentyNewsgroupsClustering
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+ config: default
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+ revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
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+ metrics:
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+ - type: v_measure
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+ - task:
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+ type: PairClassification
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+ dataset:
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+ type: mteb/twittersemeval2015-pairclassification
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+ name: MTEB TwitterSemEval2015
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+ config: default
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+ split: test
2500
+ revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
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+ metrics:
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+ - type: max_accuracy
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+ - type: max_ap
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2546
+ - type: max_f1
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+ value: 71.98772064466617
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+ - task:
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+ type: PairClassification
2550
+ dataset:
2551
+ type: mteb/twitterurlcorpus-pairclassification
2552
+ name: MTEB TwitterURLCorpus
2553
+ config: default
2554
+ split: test
2555
+ revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
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+ metrics:
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+ - type: cos_sim_accuracy
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+ value: 88.85202002561415
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+ - type: cos_sim_ap
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+ value: 85.9835303311168
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+ - type: cos_sim_f1
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+ value: 78.25741142443962
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+ - type: cos_sim_precision
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+ value: 73.76635768811342
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+ - type: cos_sim_recall
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+ value: 83.3307668617185
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+ - type: dot_accuracy
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+ value: 88.20584468506229
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+ - type: dot_ap
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+ value: 83.591632302697
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+ - type: dot_f1
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+ - type: dot_precision
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+ value: 73.45275728837373
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+ - type: dot_recall
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+ value: 80.50508161379734
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+ - type: euclidean_accuracy
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+ value: 88.64633057787093
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+ - type: euclidean_ap
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+ value: 85.25705123182283
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+ - type: euclidean_f1
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+ value: 77.18535726329199
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+ - type: euclidean_precision
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+ value: 75.17699437997226
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+ - type: euclidean_recall
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+ value: 79.30397289805975
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+ - type: manhattan_accuracy
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+ value: 88.63274731245392
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+ - type: manhattan_ap
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+ value: 85.2376825633018
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+ - type: manhattan_f1
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+ value: 77.15810785937788
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+ - type: manhattan_precision
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+ value: 73.92255061014319
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+ - type: manhattan_recall
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+ value: 80.68986757006468
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+ - type: max_accuracy
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+ value: 88.85202002561415
2599
+ - type: max_ap
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+ value: 85.9835303311168
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+ - type: max_f1
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+ value: 78.25741142443962
2603
  license: mit
2604
+ language:
2605
+ - en
2606
  ---
2607
+
2608
+
2609
+ <h1 align="center">English Large v1</h1>