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README.md

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+---
+library_name: peft
+license: mit
+language:
+- en
+pipeline_tag: sentence-similarity
+tags:
+- text-embedding
+- embeddings
+- information-retrieval
+- beir
+- text-classification
+- language-model
+- text-clustering
+- text-semantic-similarity
+- text-evaluation
+- text-reranking
+- feature-extraction
+- sentence-similarity
+- Sentence Similarity
+- natural_questions
+- ms_marco
+- fever
+- hotpot_qa
+- mteb
+model-index:
+- name: LLM2Vec-Meta-Llama-3-supervised
+  results:
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_counterfactual
+      name: MTEB AmazonCounterfactualClassification (en)
+      config: en
+      split: test
+      revision: e8379541af4e31359cca9fbcf4b00f2671dba205
+    metrics:
+    - type: accuracy
+      value: 79.94029850746269
+    - type: ap
+      value: 44.93223506764482
+    - type: f1
+      value: 74.30328994013465
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_polarity
+      name: MTEB AmazonPolarityClassification
+      config: default
+      split: test
+      revision: e2d317d38cd51312af73b3d32a06d1a08b442046
+    metrics:
+    - type: accuracy
+      value: 86.06680000000001
+    - type: ap
+      value: 81.97124658709345
+    - type: f1
+      value: 86.00558036874241
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_reviews_multi
+      name: MTEB AmazonReviewsClassification (en)
+      config: en
+      split: test
+      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
+    metrics:
+    - type: accuracy
+      value: 46.836
+    - type: f1
+      value: 46.05094679201488
+  - task:
+      type: Retrieval
+    dataset:
+      type: arguana
+      name: MTEB ArguAna
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 37.980000000000004
+    - type: map_at_10
+      value: 54.167
+    - type: map_at_100
+      value: 54.735
+    - type: map_at_1000
+      value: 54.738
+    - type: map_at_3
+      value: 49.384
+    - type: map_at_5
+      value: 52.285000000000004
+    - type: mrr_at_1
+      value: 38.549
+    - type: mrr_at_10
+      value: 54.351000000000006
+    - type: mrr_at_100
+      value: 54.932
+    - type: mrr_at_1000
+      value: 54.935
+    - type: mrr_at_3
+      value: 49.585
+    - type: mrr_at_5
+      value: 52.469
+    - type: ndcg_at_1
+      value: 37.980000000000004
+    - type: ndcg_at_10
+      value: 62.778999999999996
+    - type: ndcg_at_100
+      value: 64.986
+    - type: ndcg_at_1000
+      value: 65.036
+    - type: ndcg_at_3
+      value: 53.086999999999996
+    - type: ndcg_at_5
+      value: 58.263
+    - type: precision_at_1
+      value: 37.980000000000004
+    - type: precision_at_10
+      value: 9.011
+    - type: precision_at_100
+      value: 0.993
+    - type: precision_at_1000
+      value: 0.1
+    - type: precision_at_3
+      value: 21.266
+    - type: precision_at_5
+      value: 15.248999999999999
+    - type: recall_at_1
+      value: 37.980000000000004
+    - type: recall_at_10
+      value: 90.114
+    - type: recall_at_100
+      value: 99.289
+    - type: recall_at_1000
+      value: 99.644
+    - type: recall_at_3
+      value: 63.798
+    - type: recall_at_5
+      value: 76.24499999999999
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/arxiv-clustering-p2p
+      name: MTEB ArxivClusteringP2P
+      config: default
+      split: test
+      revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
+    metrics:
+    - type: v_measure
+      value: 44.27081216556421
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/arxiv-clustering-s2s
+      name: MTEB ArxivClusteringS2S
+      config: default
+      split: test
+      revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
+    metrics:
+    - type: v_measure
+      value: 46.8490872532913
+  - task:
+      type: Reranking
+    dataset:
+      type: mteb/askubuntudupquestions-reranking
+      name: MTEB AskUbuntuDupQuestions
+      config: default
+      split: test
+      revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
+    metrics:
+    - type: map
+      value: 65.18525400430678
+    - type: mrr
+      value: 78.80149936244119
+  - task:
+      type: STS
+    dataset:
+      type: mteb/biosses-sts
+      name: MTEB BIOSSES
+      config: default
+      split: test
+      revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
+    metrics:
+    - type: cos_sim_spearman
+      value: 84.92301936595548
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/banking77
+      name: MTEB Banking77Classification
+      config: default
+      split: test
+      revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
+    metrics:
+    - type: accuracy
+      value: 88.0487012987013
+    - type: f1
+      value: 88.00953788281542
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/biorxiv-clustering-p2p
+      name: MTEB BiorxivClusteringP2P
+      config: default
+      split: test
+      revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
+    metrics:
+    - type: v_measure
+      value: 32.34687321141145
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/biorxiv-clustering-s2s
+      name: MTEB BiorxivClusteringS2S
+      config: default
+      split: test
+      revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
+    metrics:
+    - type: v_measure
+      value: 36.69881680534123
+  - task:
+      type: Retrieval
+    dataset:
+      type: cqadupstack/android
+      name: MTEB CQADupstackAndroidRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 37.742
+    - type: map_at_10
+      value: 51.803
+    - type: map_at_100
+      value: 53.556000000000004
+    - type: map_at_1000
+      value: 53.652
+    - type: map_at_3
+      value: 47.286
+    - type: map_at_5
+      value: 50.126000000000005
+    - type: mrr_at_1
+      value: 46.924
+    - type: mrr_at_10
+      value: 57.857
+    - type: mrr_at_100
+      value: 58.592
+    - type: mrr_at_1000
+      value: 58.619
+    - type: mrr_at_3
+      value: 55.340999999999994
+    - type: mrr_at_5
+      value: 57.150999999999996
+    - type: ndcg_at_1
+      value: 46.924
+    - type: ndcg_at_10
+      value: 58.733999999999995
+    - type: ndcg_at_100
+      value: 63.771
+    - type: ndcg_at_1000
+      value: 64.934
+    - type: ndcg_at_3
+      value: 53.189
+    - type: ndcg_at_5
+      value: 56.381
+    - type: precision_at_1
+      value: 46.924
+    - type: precision_at_10
+      value: 11.431
+    - type: precision_at_100
+      value: 1.73
+    - type: precision_at_1000
+      value: 0.213
+    - type: precision_at_3
+      value: 25.942
+    - type: precision_at_5
+      value: 19.113
+    - type: recall_at_1
+      value: 37.742
+    - type: recall_at_10
+      value: 71.34
+    - type: recall_at_100
+      value: 91.523
+    - type: recall_at_1000
+      value: 98.494
+    - type: recall_at_3
+      value: 55.443
+    - type: recall_at_5
+      value: 64.122
+  - task:
+      type: Retrieval
+    dataset:
+      type: cqadupstack/english
+      name: MTEB CQADupstackEnglishRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 34.183
+    - type: map_at_10
+      value: 46.837
+    - type: map_at_100
+      value: 48.126000000000005
+    - type: map_at_1000
+      value: 48.25
+    - type: map_at_3
+      value: 43.171
+    - type: map_at_5
+      value: 45.318999999999996
+    - type: mrr_at_1
+      value: 43.376
+    - type: mrr_at_10
+      value: 52.859
+    - type: mrr_at_100
+      value: 53.422000000000004
+    - type: mrr_at_1000
+      value: 53.456
+    - type: mrr_at_3
+      value: 50.434999999999995
+    - type: mrr_at_5
+      value: 51.861999999999995
+    - type: ndcg_at_1
+      value: 43.376
+    - type: ndcg_at_10
+      value: 53.223
+    - type: ndcg_at_100
+      value: 57.175
+    - type: ndcg_at_1000
+      value: 58.86900000000001
+    - type: ndcg_at_3
+      value: 48.417
+    - type: ndcg_at_5
+      value: 50.77
+    - type: precision_at_1
+      value: 43.376
+    - type: precision_at_10
+      value: 10.236
+    - type: precision_at_100
+      value: 1.5730000000000002
+    - type: precision_at_1000
+      value: 0.203
+    - type: precision_at_3
+      value: 23.97
+    - type: precision_at_5
+      value: 17.134
+    - type: recall_at_1
+      value: 34.183
+    - type: recall_at_10
+      value: 64.866
+    - type: recall_at_100
+      value: 81.26100000000001
+    - type: recall_at_1000
+      value: 91.412
+    - type: recall_at_3
+      value: 50.080000000000005
+    - type: recall_at_5
+      value: 56.871
+  - task:
+      type: Retrieval
+    dataset:
+      type: cqadupstack/gaming
+      name: MTEB CQADupstackGamingRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 44.878
+    - type: map_at_10
+      value: 58.656
+    - type: map_at_100
+      value: 59.668
+    - type: map_at_1000
+      value: 59.704
+    - type: map_at_3
+      value: 54.891
+    - type: map_at_5
+      value: 57.050999999999995
+    - type: mrr_at_1
+      value: 51.975
+    - type: mrr_at_10
+      value: 62.357
+    - type: mrr_at_100
+      value: 62.907999999999994
+    - type: mrr_at_1000
+      value: 62.925
+    - type: mrr_at_3
+      value: 59.801
+    - type: mrr_at_5
+      value: 61.278
+    - type: ndcg_at_1
+      value: 51.975
+    - type: ndcg_at_10
+      value: 64.95100000000001
+    - type: ndcg_at_100
+      value: 68.414
+    - type: ndcg_at_1000
+      value: 69.077
+    - type: ndcg_at_3
+      value: 58.897999999999996
+    - type: ndcg_at_5
+      value: 61.866
+    - type: precision_at_1
+      value: 51.975
+    - type: precision_at_10
+      value: 10.502
+    - type: precision_at_100
+      value: 1.31
+    - type: precision_at_1000
+      value: 0.13899999999999998
+    - type: precision_at_3
+      value: 26.290000000000003
+    - type: precision_at_5
+      value: 18.093999999999998
+    - type: recall_at_1
+      value: 44.878
+    - type: recall_at_10
+      value: 79.746
+    - type: recall_at_100
+      value: 94.17
+    - type: recall_at_1000
+      value: 98.80499999999999
+    - type: recall_at_3
+      value: 63.70099999999999
+    - type: recall_at_5
+      value: 70.878
+  - task:
+      type: Retrieval
+    dataset:
+      type: cqadupstack/gis
+      name: MTEB CQADupstackGisRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 28.807
+    - type: map_at_10
+      value: 39.431
+    - type: map_at_100
+      value: 40.56
+    - type: map_at_1000
+      value: 40.617999999999995
+    - type: map_at_3
+      value: 36.436
+    - type: map_at_5
+      value: 37.955
+    - type: mrr_at_1
+      value: 31.186000000000003
+    - type: mrr_at_10
+      value: 41.654
+    - type: mrr_at_100
+      value: 42.58
+    - type: mrr_at_1000
+      value: 42.623
+    - type: mrr_at_3
+      value: 38.983000000000004
+    - type: mrr_at_5
+      value: 40.35
+    - type: ndcg_at_1
+      value: 31.186000000000003
+    - type: ndcg_at_10
+      value: 45.297
+    - type: ndcg_at_100
+      value: 50.515
+    - type: ndcg_at_1000
+      value: 52.005
+    - type: ndcg_at_3
+      value: 39.602
+    - type: ndcg_at_5
+      value: 42.027
+    - type: precision_at_1
+      value: 31.186000000000003
+    - type: precision_at_10
+      value: 7.073
+    - type: precision_at_100
+      value: 1.0210000000000001
+    - type: precision_at_1000
+      value: 0.11900000000000001
+    - type: precision_at_3
+      value: 17.1
+    - type: precision_at_5
+      value: 11.729000000000001
+    - type: recall_at_1
+      value: 28.807
+    - type: recall_at_10
+      value: 61.138999999999996
+    - type: recall_at_100
+      value: 84.491
+    - type: recall_at_1000
+      value: 95.651
+    - type: recall_at_3
+      value: 45.652
+    - type: recall_at_5
+      value: 51.522
+  - task:
+      type: Retrieval
+    dataset:
+      type: cqadupstack/mathematica
+      name: MTEB CQADupstackMathematicaRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 20.607
+    - type: map_at_10
+      value: 31.944
+    - type: map_at_100
+      value: 33.317
+    - type: map_at_1000
+      value: 33.428000000000004
+    - type: map_at_3
+      value: 28.508
+    - type: map_at_5
+      value: 30.348999999999997
+    - type: mrr_at_1
+      value: 25.622
+    - type: mrr_at_10
+      value: 36.726
+    - type: mrr_at_100
+      value: 37.707
+    - type: mrr_at_1000
+      value: 37.761
+    - type: mrr_at_3
+      value: 33.934
+    - type: mrr_at_5
+      value: 35.452
+    - type: ndcg_at_1
+      value: 25.622
+    - type: ndcg_at_10
+      value: 38.462
+    - type: ndcg_at_100
+      value: 44.327
+    - type: ndcg_at_1000
+      value: 46.623
+    - type: ndcg_at_3
+      value: 32.583
+    - type: ndcg_at_5
+      value: 35.175
+    - type: precision_at_1
+      value: 25.622
+    - type: precision_at_10
+      value: 7.425
+    - type: precision_at_100
+      value: 1.173
+    - type: precision_at_1000
+      value: 0.149
+    - type: precision_at_3
+      value: 16.418
+    - type: precision_at_5
+      value: 11.866
+    - type: recall_at_1
+      value: 20.607
+    - type: recall_at_10
+      value: 53.337
+    - type: recall_at_100
+      value: 78.133
+    - type: recall_at_1000
+      value: 94.151
+    - type: recall_at_3
+      value: 37.088
+    - type: recall_at_5
+      value: 43.627
+  - task:
+      type: Retrieval
+    dataset:
+      type: cqadupstack/physics
+      name: MTEB CQADupstackPhysicsRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 33.814
+    - type: map_at_10
+      value: 47.609
+    - type: map_at_100
+      value: 48.972
+    - type: map_at_1000
+      value: 49.061
+    - type: map_at_3
+      value: 43.397999999999996
+    - type: map_at_5
+      value: 45.839
+    - type: mrr_at_1
+      value: 42.059999999999995
+    - type: mrr_at_10
+      value: 53.074
+    - type: mrr_at_100
+      value: 53.76800000000001
+    - type: mrr_at_1000
+      value: 53.794
+    - type: mrr_at_3
+      value: 50.241
+    - type: mrr_at_5
+      value: 51.805
+    - type: ndcg_at_1
+      value: 42.059999999999995
+    - type: ndcg_at_10
+      value: 54.419
+    - type: ndcg_at_100
+      value: 59.508
+    - type: ndcg_at_1000
+      value: 60.858000000000004
+    - type: ndcg_at_3
+      value: 48.296
+    - type: ndcg_at_5
+      value: 51.28
+    - type: precision_at_1
+      value: 42.059999999999995
+    - type: precision_at_10
+      value: 10.231
+    - type: precision_at_100
+      value: 1.4789999999999999
+    - type: precision_at_1000
+      value: 0.17700000000000002
+    - type: precision_at_3
+      value: 23.419999999999998
+    - type: precision_at_5
+      value: 16.843
+    - type: recall_at_1
+      value: 33.814
+    - type: recall_at_10
+      value: 68.88
+    - type: recall_at_100
+      value: 89.794
+    - type: recall_at_1000
+      value: 98.058
+    - type: recall_at_3
+      value: 51.915
+    - type: recall_at_5
+      value: 59.704
+  - task:
+      type: Retrieval
+    dataset:
+      type: cqadupstack/programmers
+      name: MTEB CQADupstackProgrammersRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 29.668
+    - type: map_at_10
+      value: 43.032
+    - type: map_at_100
+      value: 44.48
+    - type: map_at_1000
+      value: 44.574000000000005
+    - type: map_at_3
+      value: 38.609
+    - type: map_at_5
+      value: 41.164
+    - type: mrr_at_1
+      value: 37.785000000000004
+    - type: mrr_at_10
+      value: 48.898
+    - type: mrr_at_100
+      value: 49.728
+    - type: mrr_at_1000
+      value: 49.769000000000005
+    - type: mrr_at_3
+      value: 45.909
+    - type: mrr_at_5
+      value: 47.61
+    - type: ndcg_at_1
+      value: 37.785000000000004
+    - type: ndcg_at_10
+      value: 50.21099999999999
+    - type: ndcg_at_100
+      value: 55.657999999999994
+    - type: ndcg_at_1000
+      value: 57.172
+    - type: ndcg_at_3
+      value: 43.726
+    - type: ndcg_at_5
+      value: 46.758
+    - type: precision_at_1
+      value: 37.785000000000004
+    - type: precision_at_10
+      value: 9.669
+    - type: precision_at_100
+      value: 1.4409999999999998
+    - type: precision_at_1000
+      value: 0.174
+    - type: precision_at_3
+      value: 21.651
+    - type: precision_at_5
+      value: 15.822
+    - type: recall_at_1
+      value: 29.668
+    - type: recall_at_10
+      value: 65.575
+    - type: recall_at_100
+      value: 87.977
+    - type: recall_at_1000
+      value: 97.615
+    - type: recall_at_3
+      value: 47.251
+    - type: recall_at_5
+      value: 55.359
+  - task:
+      type: Retrieval
+    dataset:
+      type: mteb/cqadupstack
+      name: MTEB CQADupstackRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 30.29925
+    - type: map_at_10
+      value: 41.98708333333333
+    - type: map_at_100
+      value: 43.306916666666666
+    - type: map_at_1000
+      value: 43.40716666666667
+    - type: map_at_3
+      value: 38.431666666666665
+    - type: map_at_5
+      value: 40.4195
+    - type: mrr_at_1
+      value: 36.24483333333334
+    - type: mrr_at_10
+      value: 46.32666666666667
+    - type: mrr_at_100
+      value: 47.13983333333333
+    - type: mrr_at_1000
+      value: 47.18058333333334
+    - type: mrr_at_3
+      value: 43.66799999999999
+    - type: mrr_at_5
+      value: 45.163666666666664
+    - type: ndcg_at_1
+      value: 36.24483333333334
+    - type: ndcg_at_10
+      value: 48.251916666666666
+    - type: ndcg_at_100
+      value: 53.3555
+    - type: ndcg_at_1000
+      value: 55.024249999999995
+    - type: ndcg_at_3
+      value: 42.599583333333335
+    - type: ndcg_at_5
+      value: 45.24166666666666
+    - type: precision_at_1
+      value: 36.24483333333334
+    - type: precision_at_10
+      value: 8.666833333333333
+    - type: precision_at_100
+      value: 1.3214166666666665
+    - type: precision_at_1000
+      value: 0.16475
+    - type: precision_at_3
+      value: 19.9955
+    - type: precision_at_5
+      value: 14.271999999999998
+    - type: recall_at_1
+      value: 30.29925
+    - type: recall_at_10
+      value: 62.232333333333344
+    - type: recall_at_100
+      value: 84.151
+    - type: recall_at_1000
+      value: 95.37333333333333
+    - type: recall_at_3
+      value: 46.45541666666667
+    - type: recall_at_5
+      value: 53.264
+  - task:
+      type: Retrieval
+    dataset:
+      type: cqadupstack/stats
+      name: MTEB CQADupstackStatsRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 28.996
+    - type: map_at_10
+      value: 38.047
+    - type: map_at_100
+      value: 39.121
+    - type: map_at_1000
+      value: 39.202999999999996
+    - type: map_at_3
+      value: 35.376000000000005
+    - type: map_at_5
+      value: 36.763
+    - type: mrr_at_1
+      value: 32.362
+    - type: mrr_at_10
+      value: 40.717999999999996
+    - type: mrr_at_100
+      value: 41.586
+    - type: mrr_at_1000
+      value: 41.641
+    - type: mrr_at_3
+      value: 38.292
+    - type: mrr_at_5
+      value: 39.657
+    - type: ndcg_at_1
+      value: 32.362
+    - type: ndcg_at_10
+      value: 43.105
+    - type: ndcg_at_100
+      value: 48.026
+    - type: ndcg_at_1000
+      value: 49.998
+    - type: ndcg_at_3
+      value: 38.147999999999996
+    - type: ndcg_at_5
+      value: 40.385
+    - type: precision_at_1
+      value: 32.362
+    - type: precision_at_10
+      value: 6.7940000000000005
+    - type: precision_at_100
+      value: 1.0170000000000001
+    - type: precision_at_1000
+      value: 0.125
+    - type: precision_at_3
+      value: 16.411
+    - type: precision_at_5
+      value: 11.35
+    - type: recall_at_1
+      value: 28.996
+    - type: recall_at_10
+      value: 55.955
+    - type: recall_at_100
+      value: 77.744
+    - type: recall_at_1000
+      value: 92.196
+    - type: recall_at_3
+      value: 42.254999999999995
+    - type: recall_at_5
+      value: 47.776
+  - task:
+      type: Retrieval
+    dataset:
+      type: cqadupstack/tex
+      name: MTEB CQADupstackTexRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 20.029
+    - type: map_at_10
+      value: 29.188
+    - type: map_at_100
+      value: 30.484
+    - type: map_at_1000
+      value: 30.608
+    - type: map_at_3
+      value: 26.195
+    - type: map_at_5
+      value: 27.866999999999997
+    - type: mrr_at_1
+      value: 24.57
+    - type: mrr_at_10
+      value: 33.461
+    - type: mrr_at_100
+      value: 34.398
+    - type: mrr_at_1000
+      value: 34.464
+    - type: mrr_at_3
+      value: 30.856
+    - type: mrr_at_5
+      value: 32.322
+    - type: ndcg_at_1
+      value: 24.57
+    - type: ndcg_at_10
+      value: 34.846
+    - type: ndcg_at_100
+      value: 40.544000000000004
+    - type: ndcg_at_1000
+      value: 43.019
+    - type: ndcg_at_3
+      value: 29.683999999999997
+    - type: ndcg_at_5
+      value: 32.11
+    - type: precision_at_1
+      value: 24.57
+    - type: precision_at_10
+      value: 6.535
+    - type: precision_at_100
+      value: 1.11
+    - type: precision_at_1000
+      value: 0.149
+    - type: precision_at_3
+      value: 14.338000000000001
+    - type: precision_at_5
+      value: 10.496
+    - type: recall_at_1
+      value: 20.029
+    - type: recall_at_10
+      value: 47.509
+    - type: recall_at_100
+      value: 72.61999999999999
+    - type: recall_at_1000
+      value: 89.778
+    - type: recall_at_3
+      value: 33.031
+    - type: recall_at_5
+      value: 39.306000000000004
+  - task:
+      type: Retrieval
+    dataset:
+      type: cqadupstack/unix
+      name: MTEB CQADupstackUnixRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 31.753999999999998
+    - type: map_at_10
+      value: 43.814
+    - type: map_at_100
+      value: 45.072
+    - type: map_at_1000
+      value: 45.155
+    - type: map_at_3
+      value: 40.316
+    - type: map_at_5
+      value: 42.15
+    - type: mrr_at_1
+      value: 38.06
+    - type: mrr_at_10
+      value: 48.311
+    - type: mrr_at_100
+      value: 49.145
+    - type: mrr_at_1000
+      value: 49.181000000000004
+    - type: mrr_at_3
+      value: 45.678000000000004
+    - type: mrr_at_5
+      value: 47.072
+    - type: ndcg_at_1
+      value: 38.06
+    - type: ndcg_at_10
+      value: 50.083
+    - type: ndcg_at_100
+      value: 55.342
+    - type: ndcg_at_1000
+      value: 56.87
+    - type: ndcg_at_3
+      value: 44.513999999999996
+    - type: ndcg_at_5
+      value: 46.886
+    - type: precision_at_1
+      value: 38.06
+    - type: precision_at_10
+      value: 8.638
+    - type: precision_at_100
+      value: 1.253
+    - type: precision_at_1000
+      value: 0.149
+    - type: precision_at_3
+      value: 20.709
+    - type: precision_at_5
+      value: 14.44
+    - type: recall_at_1
+      value: 31.753999999999998
+    - type: recall_at_10
+      value: 64.473
+    - type: recall_at_100
+      value: 86.832
+    - type: recall_at_1000
+      value: 96.706
+    - type: recall_at_3
+      value: 48.937000000000005
+    - type: recall_at_5
+      value: 55.214
+  - task:
+      type: Retrieval
+    dataset:
+      type: cqadupstack/webmasters
+      name: MTEB CQADupstackWebmastersRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 28.815
+    - type: map_at_10
+      value: 40.595
+    - type: map_at_100
+      value: 42.337
+    - type: map_at_1000
+      value: 42.559000000000005
+    - type: map_at_3
+      value: 37.120999999999995
+    - type: map_at_5
+      value: 38.912
+    - type: mrr_at_1
+      value: 34.585
+    - type: mrr_at_10
+      value: 45.068000000000005
+    - type: mrr_at_100
+      value: 45.93
+    - type: mrr_at_1000
+      value: 45.974
+    - type: mrr_at_3
+      value: 42.26
+    - type: mrr_at_5
+      value: 43.742
+    - type: ndcg_at_1
+      value: 34.585
+    - type: ndcg_at_10
+      value: 47.519
+    - type: ndcg_at_100
+      value: 53.102000000000004
+    - type: ndcg_at_1000
+      value: 54.949999999999996
+    - type: ndcg_at_3
+      value: 41.719
+    - type: ndcg_at_5
+      value: 44.17
+    - type: precision_at_1
+      value: 34.585
+    - type: precision_at_10
+      value: 9.368
+    - type: precision_at_100
+      value: 1.7870000000000001
+    - type: precision_at_1000
+      value: 0.254
+    - type: precision_at_3
+      value: 19.895
+    - type: precision_at_5
+      value: 14.506
+    - type: recall_at_1
+      value: 28.815
+    - type: recall_at_10
+      value: 61.414
+    - type: recall_at_100
+      value: 85.922
+    - type: recall_at_1000
+      value: 97.15
+    - type: recall_at_3
+      value: 45.076
+    - type: recall_at_5
+      value: 51.271
+  - task:
+      type: Retrieval
+    dataset:
+      type: cqadupstack/wordpress
+      name: MTEB CQADupstackWordpressRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 24.298000000000002
+    - type: map_at_10
+      value: 32.889
+    - type: map_at_100
+      value: 33.989999999999995
+    - type: map_at_1000
+      value: 34.074
+    - type: map_at_3
+      value: 29.873
+    - type: map_at_5
+      value: 31.539
+    - type: mrr_at_1
+      value: 26.433
+    - type: mrr_at_10
+      value: 34.937000000000005
+    - type: mrr_at_100
+      value: 35.914
+    - type: mrr_at_1000
+      value: 35.96
+    - type: mrr_at_3
+      value: 32.286
+    - type: mrr_at_5
+      value: 33.663
+    - type: ndcg_at_1
+      value: 26.433
+    - type: ndcg_at_10
+      value: 38.173
+    - type: ndcg_at_100
+      value: 43.884
+    - type: ndcg_at_1000
+      value: 45.916000000000004
+    - type: ndcg_at_3
+      value: 32.419
+    - type: ndcg_at_5
+      value: 35.092
+    - type: precision_at_1
+      value: 26.433
+    - type: precision_at_10
+      value: 6.1
+    - type: precision_at_100
+      value: 0.963
+    - type: precision_at_1000
+      value: 0.126
+    - type: precision_at_3
+      value: 13.802
+    - type: precision_at_5
+      value: 9.871
+    - type: recall_at_1
+      value: 24.298000000000002
+    - type: recall_at_10
+      value: 52.554
+    - type: recall_at_100
+      value: 79.345
+    - type: recall_at_1000
+      value: 94.464
+    - type: recall_at_3
+      value: 37.036
+    - type: recall_at_5
+      value: 43.518
+  - task:
+      type: Retrieval
+    dataset:
+      type: climate-fever
+      name: MTEB ClimateFEVER
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 14.194999999999999
+    - type: map_at_10
+      value: 24.563
+    - type: map_at_100
+      value: 26.775
+    - type: map_at_1000
+      value: 26.965
+    - type: map_at_3
+      value: 19.983999999999998
+    - type: map_at_5
+      value: 22.24
+    - type: mrr_at_1
+      value: 31.661
+    - type: mrr_at_10
+      value: 44.804
+    - type: mrr_at_100
+      value: 45.655
+    - type: mrr_at_1000
+      value: 45.678000000000004
+    - type: mrr_at_3
+      value: 41.292
+    - type: mrr_at_5
+      value: 43.468
+    - type: ndcg_at_1
+      value: 31.661
+    - type: ndcg_at_10
+      value: 34.271
+    - type: ndcg_at_100
+      value: 42.04
+    - type: ndcg_at_1000
+      value: 45.101
+    - type: ndcg_at_3
+      value: 27.529999999999998
+    - type: ndcg_at_5
+      value: 29.862
+    - type: precision_at_1
+      value: 31.661
+    - type: precision_at_10
+      value: 10.925
+    - type: precision_at_100
+      value: 1.92
+    - type: precision_at_1000
+      value: 0.25
+    - type: precision_at_3
+      value: 20.456
+    - type: precision_at_5
+      value: 16.012999999999998
+    - type: recall_at_1
+      value: 14.194999999999999
+    - type: recall_at_10
+      value: 41.388999999999996
+    - type: recall_at_100
+      value: 67.58800000000001
+    - type: recall_at_1000
+      value: 84.283
+    - type: recall_at_3
+      value: 25.089
+    - type: recall_at_5
+      value: 31.642
+  - task:
+      type: Retrieval
+    dataset:
+      type: dbpedia-entity
+      name: MTEB DBPedia
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 9.898
+    - type: map_at_10
+      value: 23.226
+    - type: map_at_100
+      value: 33.372
+    - type: map_at_1000
+      value: 35.407
+    - type: map_at_3
+      value: 15.892999999999999
+    - type: map_at_5
+      value: 18.747
+    - type: mrr_at_1
+      value: 73.5
+    - type: mrr_at_10
+      value: 80.404
+    - type: mrr_at_100
+      value: 80.671
+    - type: mrr_at_1000
+      value: 80.676
+    - type: mrr_at_3
+      value: 78.958
+    - type: mrr_at_5
+      value: 79.683
+    - type: ndcg_at_1
+      value: 62.0
+    - type: ndcg_at_10
+      value: 48.337
+    - type: ndcg_at_100
+      value: 53.474
+    - type: ndcg_at_1000
+      value: 60.999
+    - type: ndcg_at_3
+      value: 52.538
+    - type: ndcg_at_5
+      value: 49.659
+    - type: precision_at_1
+      value: 73.5
+    - type: precision_at_10
+      value: 39.25
+    - type: precision_at_100
+      value: 12.4
+    - type: precision_at_1000
+      value: 2.4459999999999997
+    - type: precision_at_3
+      value: 56.333
+    - type: precision_at_5
+      value: 48.15
+    - type: recall_at_1
+      value: 9.898
+    - type: recall_at_10
+      value: 29.511
+    - type: recall_at_100
+      value: 60.45700000000001
+    - type: recall_at_1000
+      value: 84.47200000000001
+    - type: recall_at_3
+      value: 17.064
+    - type: recall_at_5
+      value: 21.258
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/emotion
+      name: MTEB EmotionClassification
+      config: default
+      split: test
+      revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
+    metrics:
+    - type: accuracy
+      value: 51.19999999999999
+    - type: f1
+      value: 46.23854137552949
+  - task:
+      type: Retrieval
+    dataset:
+      type: fever
+      name: MTEB FEVER
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 80.093
+    - type: map_at_10
+      value: 87.139
+    - type: map_at_100
+      value: 87.333
+    - type: map_at_1000
+      value: 87.344
+    - type: map_at_3
+      value: 86.395
+    - type: map_at_5
+      value: 86.866
+    - type: mrr_at_1
+      value: 86.36399999999999
+    - type: mrr_at_10
+      value: 91.867
+    - type: mrr_at_100
+      value: 91.906
+    - type: mrr_at_1000
+      value: 91.90700000000001
+    - type: mrr_at_3
+      value: 91.484
+    - type: mrr_at_5
+      value: 91.759
+    - type: ndcg_at_1
+      value: 86.36399999999999
+    - type: ndcg_at_10
+      value: 90.197
+    - type: ndcg_at_100
+      value: 90.819
+    - type: ndcg_at_1000
+      value: 91.01599999999999
+    - type: ndcg_at_3
+      value: 89.166
+    - type: ndcg_at_5
+      value: 89.74
+    - type: precision_at_1
+      value: 86.36399999999999
+    - type: precision_at_10
+      value: 10.537
+    - type: precision_at_100
+      value: 1.106
+    - type: precision_at_1000
+      value: 0.11399999999999999
+    - type: precision_at_3
+      value: 33.608
+    - type: precision_at_5
+      value: 20.618
+    - type: recall_at_1
+      value: 80.093
+    - type: recall_at_10
+      value: 95.003
+    - type: recall_at_100
+      value: 97.328
+    - type: recall_at_1000
+      value: 98.485
+    - type: recall_at_3
+      value: 92.072
+    - type: recall_at_5
+      value: 93.661
+  - task:
+      type: Retrieval
+    dataset:
+      type: fiqa
+      name: MTEB FiQA2018
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 29.063
+    - type: map_at_10
+      value: 47.113
+    - type: map_at_100
+      value: 49.294
+    - type: map_at_1000
+      value: 49.422
+    - type: map_at_3
+      value: 40.955000000000005
+    - type: map_at_5
+      value: 44.5
+    - type: mrr_at_1
+      value: 55.401
+    - type: mrr_at_10
+      value: 62.99400000000001
+    - type: mrr_at_100
+      value: 63.63999999999999
+    - type: mrr_at_1000
+      value: 63.661
+    - type: mrr_at_3
+      value: 61.034
+    - type: mrr_at_5
+      value: 62.253
+    - type: ndcg_at_1
+      value: 55.401
+    - type: ndcg_at_10
+      value: 55.332
+    - type: ndcg_at_100
+      value: 61.931000000000004
+    - type: ndcg_at_1000
+      value: 63.841
+    - type: ndcg_at_3
+      value: 50.92
+    - type: ndcg_at_5
+      value: 52.525
+    - type: precision_at_1
+      value: 55.401
+    - type: precision_at_10
+      value: 15.262
+    - type: precision_at_100
+      value: 2.231
+    - type: precision_at_1000
+      value: 0.256
+    - type: precision_at_3
+      value: 33.848
+    - type: precision_at_5
+      value: 25.031
+    - type: recall_at_1
+      value: 29.063
+    - type: recall_at_10
+      value: 62.498
+    - type: recall_at_100
+      value: 85.86
+    - type: recall_at_1000
+      value: 97.409
+    - type: recall_at_3
+      value: 45.472
+    - type: recall_at_5
+      value: 53.344
+  - task:
+      type: Retrieval
+    dataset:
+      type: hotpotqa
+      name: MTEB HotpotQA
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 37.205
+    - type: map_at_10
+      value: 64.19399999999999
+    - type: map_at_100
+      value: 65.183
+    - type: map_at_1000
+      value: 65.23299999999999
+    - type: map_at_3
+      value: 60.239
+    - type: map_at_5
+      value: 62.695
+    - type: mrr_at_1
+      value: 74.409
+    - type: mrr_at_10
+      value: 80.84
+    - type: mrr_at_100
+      value: 81.10199999999999
+    - type: mrr_at_1000
+      value: 81.109
+    - type: mrr_at_3
+      value: 79.739
+    - type: mrr_at_5
+      value: 80.46600000000001
+    - type: ndcg_at_1
+      value: 74.409
+    - type: ndcg_at_10
+      value: 71.757
+    - type: ndcg_at_100
+      value: 75.152
+    - type: ndcg_at_1000
+      value: 76.098
+    - type: ndcg_at_3
+      value: 66.174
+    - type: ndcg_at_5
+      value: 69.283
+    - type: precision_at_1
+      value: 74.409
+    - type: precision_at_10
+      value: 15.503
+    - type: precision_at_100
+      value: 1.8110000000000002
+    - type: precision_at_1000
+      value: 0.194
+    - type: precision_at_3
+      value: 43.457
+    - type: precision_at_5
+      value: 28.532000000000004
+    - type: recall_at_1
+      value: 37.205
+    - type: recall_at_10
+      value: 77.515
+    - type: recall_at_100
+      value: 90.56
+    - type: recall_at_1000
+      value: 96.759
+    - type: recall_at_3
+      value: 65.18599999999999
+    - type: recall_at_5
+      value: 71.33
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/imdb
+      name: MTEB ImdbClassification
+      config: default
+      split: test
+      revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
+    metrics:
+    - type: accuracy
+      value: 82.9448
+    - type: ap
+      value: 78.25923353099166
+    - type: f1
+      value: 82.86422040179993
+  - task:
+      type: Retrieval
+    dataset:
+      type: msmarco
+      name: MTEB MSMARCO
+      config: default
+      split: dev
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 22.834
+    - type: map_at_10
+      value: 35.85
+    - type: map_at_100
+      value: 37.013
+    - type: map_at_1000
+      value: 37.056
+    - type: map_at_3
+      value: 31.613000000000003
+    - type: map_at_5
+      value: 34.113
+    - type: mrr_at_1
+      value: 23.424
+    - type: mrr_at_10
+      value: 36.398
+    - type: mrr_at_100
+      value: 37.498
+    - type: mrr_at_1000
+      value: 37.534
+    - type: mrr_at_3
+      value: 32.275999999999996
+    - type: mrr_at_5
+      value: 34.705000000000005
+    - type: ndcg_at_1
+      value: 23.424
+    - type: ndcg_at_10
+      value: 43.236999999999995
+    - type: ndcg_at_100
+      value: 48.776
+    - type: ndcg_at_1000
+      value: 49.778
+    - type: ndcg_at_3
+      value: 34.692
+    - type: ndcg_at_5
+      value: 39.119
+    - type: precision_at_1
+      value: 23.424
+    - type: precision_at_10
+      value: 6.918
+    - type: precision_at_100
+      value: 0.9690000000000001
+    - type: precision_at_1000
+      value: 0.105
+    - type: precision_at_3
+      value: 14.881
+    - type: precision_at_5
+      value: 11.183
+    - type: recall_at_1
+      value: 22.834
+    - type: recall_at_10
+      value: 66.03999999999999
+    - type: recall_at_100
+      value: 91.532
+    - type: recall_at_1000
+      value: 99.068
+    - type: recall_at_3
+      value: 42.936
+    - type: recall_at_5
+      value: 53.539
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/mtop_domain
+      name: MTEB MTOPDomainClassification (en)
+      config: en
+      split: test
+      revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
+    metrics:
+    - type: accuracy
+      value: 96.1377108983128
+    - type: f1
+      value: 95.87034720246666
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/mtop_intent
+      name: MTEB MTOPIntentClassification (en)
+      config: en
+      split: test
+      revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
+    metrics:
+    - type: accuracy
+      value: 86.10579115367078
+    - type: f1
+      value: 70.20810321445228
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_massive_intent
+      name: MTEB MassiveIntentClassification (en)
+      config: en
+      split: test
+      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
+    metrics:
+    - type: accuracy
+      value: 79.80497646267652
+    - type: f1
+      value: 77.32475274059293
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_massive_scenario
+      name: MTEB MassiveScenarioClassification (en)
+      config: en
+      split: test
+      revision: 7d571f92784cd94a019292a1f45445077d0ef634
+    metrics:
+    - type: accuracy
+      value: 81.52320107599192
+    - type: f1
+      value: 81.22312939311655
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/medrxiv-clustering-p2p
+      name: MTEB MedrxivClusteringP2P
+      config: default
+      split: test
+      revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
+    metrics:
+    - type: v_measure
+      value: 30.709106678767018
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/medrxiv-clustering-s2s
+      name: MTEB MedrxivClusteringS2S
+      config: default
+      split: test
+      revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
+    metrics:
+    - type: v_measure
+      value: 32.95879128399585
+  - task:
+      type: Reranking
+    dataset:
+      type: mteb/mind_small
+      name: MTEB MindSmallReranking
+      config: default
+      split: test
+      revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
+    metrics:
+    - type: map
+      value: 32.67476691128679
+    - type: mrr
+      value: 33.921654478513986
+  - task:
+      type: Retrieval
+    dataset:
+      type: nfcorpus
+      name: MTEB NFCorpus
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 7.223
+    - type: map_at_10
+      value: 15.992999999999999
+    - type: map_at_100
+      value: 21.09
+    - type: map_at_1000
+      value: 22.822
+    - type: map_at_3
+      value: 11.475
+    - type: map_at_5
+      value: 13.501
+    - type: mrr_at_1
+      value: 53.251000000000005
+    - type: mrr_at_10
+      value: 61.878
+    - type: mrr_at_100
+      value: 62.307
+    - type: mrr_at_1000
+      value: 62.342
+    - type: mrr_at_3
+      value: 60.01
+    - type: mrr_at_5
+      value: 61.202
+    - type: ndcg_at_1
+      value: 51.702999999999996
+    - type: ndcg_at_10
+      value: 41.833999999999996
+    - type: ndcg_at_100
+      value: 39.061
+    - type: ndcg_at_1000
+      value: 47.397
+    - type: ndcg_at_3
+      value: 47.083000000000006
+    - type: ndcg_at_5
+      value: 44.722
+    - type: precision_at_1
+      value: 53.251000000000005
+    - type: precision_at_10
+      value: 31.3
+    - type: precision_at_100
+      value: 10.254000000000001
+    - type: precision_at_1000
+      value: 2.338
+    - type: precision_at_3
+      value: 43.756
+    - type: precision_at_5
+      value: 38.824
+    - type: recall_at_1
+      value: 7.223
+    - type: recall_at_10
+      value: 20.529
+    - type: recall_at_100
+      value: 39.818
+    - type: recall_at_1000
+      value: 70.152
+    - type: recall_at_3
+      value: 12.666
+    - type: recall_at_5
+      value: 15.798000000000002
+  - task:
+      type: Retrieval
+    dataset:
+      type: nq
+      name: MTEB NQ
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 38.847
+    - type: map_at_10
+      value: 56.255
+    - type: map_at_100
+      value: 57.019
+    - type: map_at_1000
+      value: 57.03
+    - type: map_at_3
+      value: 51.665000000000006
+    - type: map_at_5
+      value: 54.543
+    - type: mrr_at_1
+      value: 43.801
+    - type: mrr_at_10
+      value: 58.733999999999995
+    - type: mrr_at_100
+      value: 59.206
+    - type: mrr_at_1000
+      value: 59.21300000000001
+    - type: mrr_at_3
+      value: 55.266999999999996
+    - type: mrr_at_5
+      value: 57.449
+    - type: ndcg_at_1
+      value: 43.772
+    - type: ndcg_at_10
+      value: 64.213
+    - type: ndcg_at_100
+      value: 67.13
+    - type: ndcg_at_1000
+      value: 67.368
+    - type: ndcg_at_3
+      value: 55.977
+    - type: ndcg_at_5
+      value: 60.597
+    - type: precision_at_1
+      value: 43.772
+    - type: precision_at_10
+      value: 10.272
+    - type: precision_at_100
+      value: 1.193
+    - type: precision_at_1000
+      value: 0.121
+    - type: precision_at_3
+      value: 25.261
+    - type: precision_at_5
+      value: 17.885
+    - type: recall_at_1
+      value: 38.847
+    - type: recall_at_10
+      value: 85.76700000000001
+    - type: recall_at_100
+      value: 98.054
+    - type: recall_at_1000
+      value: 99.812
+    - type: recall_at_3
+      value: 64.82
+    - type: recall_at_5
+      value: 75.381
+  - task:
+      type: Retrieval
+    dataset:
+      type: quora
+      name: MTEB QuoraRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 68.77
+    - type: map_at_10
+      value: 83.195
+    - type: map_at_100
+      value: 83.869
+    - type: map_at_1000
+      value: 83.883
+    - type: map_at_3
+      value: 80.04599999999999
+    - type: map_at_5
+      value: 82.011
+    - type: mrr_at_1
+      value: 79.2
+    - type: mrr_at_10
+      value: 85.942
+    - type: mrr_at_100
+      value: 86.063
+    - type: mrr_at_1000
+      value: 86.064
+    - type: mrr_at_3
+      value: 84.82
+    - type: mrr_at_5
+      value: 85.56899999999999
+    - type: ndcg_at_1
+      value: 79.17999999999999
+    - type: ndcg_at_10
+      value: 87.161
+    - type: ndcg_at_100
+      value: 88.465
+    - type: ndcg_at_1000
+      value: 88.553
+    - type: ndcg_at_3
+      value: 83.958
+    - type: ndcg_at_5
+      value: 85.699
+    - type: precision_at_1
+      value: 79.17999999999999
+    - type: precision_at_10
+      value: 13.401
+    - type: precision_at_100
+      value: 1.54
+    - type: precision_at_1000
+      value: 0.157
+    - type: precision_at_3
+      value: 36.903000000000006
+    - type: precision_at_5
+      value: 24.404
+    - type: recall_at_1
+      value: 68.77
+    - type: recall_at_10
+      value: 95.132
+    - type: recall_at_100
+      value: 99.58200000000001
+    - type: recall_at_1000
+      value: 99.997
+    - type: recall_at_3
+      value: 86.119
+    - type: recall_at_5
+      value: 90.932
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/reddit-clustering
+      name: MTEB RedditClustering
+      config: default
+      split: test
+      revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
+    metrics:
+    - type: v_measure
+      value: 61.7204049654583
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/reddit-clustering-p2p
+      name: MTEB RedditClusteringP2P
+      config: default
+      split: test
+      revision: 282350215ef01743dc01b456c7f5241fa8937f16
+    metrics:
+    - type: v_measure
+      value: 63.98164986883849
+  - task:
+      type: Retrieval
+    dataset:
+      type: scidocs
+      name: MTEB SCIDOCS
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 5.443
+    - type: map_at_10
+      value: 13.86
+    - type: map_at_100
+      value: 16.496
+    - type: map_at_1000
+      value: 16.836000000000002
+    - type: map_at_3
+      value: 9.661
+    - type: map_at_5
+      value: 11.745
+    - type: mrr_at_1
+      value: 26.8
+    - type: mrr_at_10
+      value: 37.777
+    - type: mrr_at_100
+      value: 38.928000000000004
+    - type: mrr_at_1000
+      value: 38.967
+    - type: mrr_at_3
+      value: 34.083000000000006
+    - type: mrr_at_5
+      value: 36.308
+    - type: ndcg_at_1
+      value: 26.8
+    - type: ndcg_at_10
+      value: 22.961000000000002
+    - type: ndcg_at_100
+      value: 32.582
+    - type: ndcg_at_1000
+      value: 37.972
+    - type: ndcg_at_3
+      value: 21.292
+    - type: ndcg_at_5
+      value: 18.945999999999998
+    - type: precision_at_1
+      value: 26.8
+    - type: precision_at_10
+      value: 12.06
+    - type: precision_at_100
+      value: 2.593
+    - type: precision_at_1000
+      value: 0.388
+    - type: precision_at_3
+      value: 19.900000000000002
+    - type: precision_at_5
+      value: 16.84
+    - type: recall_at_1
+      value: 5.443
+    - type: recall_at_10
+      value: 24.445
+    - type: recall_at_100
+      value: 52.602000000000004
+    - type: recall_at_1000
+      value: 78.767
+    - type: recall_at_3
+      value: 12.098
+    - type: recall_at_5
+      value: 17.077
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sickr-sts
+      name: MTEB SICK-R
+      config: default
+      split: test
+      revision: a6ea5a8cab320b040a23452cc28066d9beae2cee
+    metrics:
+    - type: cos_sim_spearman
+      value: 83.9379272617096
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts12-sts
+      name: MTEB STS12
+      config: default
+      split: test
+      revision: a0d554a64d88156834ff5ae9920b964011b16384
+    metrics:
+    - type: cos_sim_spearman
+      value: 79.26752176661364
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts13-sts
+      name: MTEB STS13
+      config: default
+      split: test
+      revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
+    metrics:
+    - type: cos_sim_spearman
+      value: 84.8327309083665
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts14-sts
+      name: MTEB STS14
+      config: default
+      split: test
+      revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
+    metrics:
+    - type: cos_sim_spearman
+      value: 82.9394255552954
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts15-sts
+      name: MTEB STS15
+      config: default
+      split: test
+      revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
+    metrics:
+    - type: cos_sim_spearman
+      value: 88.08995363382608
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts16-sts
+      name: MTEB STS16
+      config: default
+      split: test
+      revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
+    metrics:
+    - type: cos_sim_spearman
+      value: 86.53522220099619
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts17-crosslingual-sts
+      name: MTEB STS17 (en-en)
+      config: en-en
+      split: test
+      revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
+    metrics:
+    - type: cos_sim_spearman
+      value: 89.57796559847532
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts22-crosslingual-sts
+      name: MTEB STS22 (en)
+      config: en
+      split: test
+      revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80
+    metrics:
+    - type: cos_sim_spearman
+      value: 67.66598855577894
+  - task:
+      type: STS
+    dataset:
+      type: mteb/stsbenchmark-sts
+      name: MTEB STSBenchmark
+      config: default
+      split: test
+      revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
+    metrics:
+    - type: cos_sim_spearman
+      value: 88.0472708354572
+  - task:
+      type: Reranking
+    dataset:
+      type: mteb/scidocs-reranking
+      name: MTEB SciDocsRR
+      config: default
+      split: test
+      revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
+    metrics:
+    - type: map
+      value: 86.04689157650684
+    - type: mrr
+      value: 96.51889958262507
+  - task:
+      type: Retrieval
+    dataset:
+      type: scifact
+      name: MTEB SciFact
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 62.827999999999996
+    - type: map_at_10
+      value: 73.54899999999999
+    - type: map_at_100
+      value: 73.892
+    - type: map_at_1000
+      value: 73.901
+    - type: map_at_3
+      value: 70.663
+    - type: map_at_5
+      value: 72.449
+    - type: mrr_at_1
+      value: 66.0
+    - type: mrr_at_10
+      value: 74.554
+    - type: mrr_at_100
+      value: 74.81700000000001
+    - type: mrr_at_1000
+      value: 74.82600000000001
+    - type: mrr_at_3
+      value: 72.667
+    - type: mrr_at_5
+      value: 73.717
+    - type: ndcg_at_1
+      value: 66.0
+    - type: ndcg_at_10
+      value: 78.218
+    - type: ndcg_at_100
+      value: 79.706
+    - type: ndcg_at_1000
+      value: 79.925
+    - type: ndcg_at_3
+      value: 73.629
+    - type: ndcg_at_5
+      value: 75.89
+    - type: precision_at_1
+      value: 66.0
+    - type: precision_at_10
+      value: 10.333
+    - type: precision_at_100
+      value: 1.113
+    - type: precision_at_1000
+      value: 0.11299999999999999
+    - type: precision_at_3
+      value: 28.889
+    - type: precision_at_5
+      value: 19.067
+    - type: recall_at_1
+      value: 62.827999999999996
+    - type: recall_at_10
+      value: 91.533
+    - type: recall_at_100
+      value: 98.333
+    - type: recall_at_1000
+      value: 100.0
+    - type: recall_at_3
+      value: 79.0
+    - type: recall_at_5
+      value: 84.68900000000001
+  - task:
+      type: PairClassification
+    dataset:
+      type: mteb/sprintduplicatequestions-pairclassification
+      name: MTEB SprintDuplicateQuestions
+      config: default
+      split: test
+      revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
+    metrics:
+    - type: cos_sim_accuracy
+      value: 99.8019801980198
+    - type: cos_sim_ap
+      value: 95.09301057928796
+    - type: cos_sim_f1
+      value: 89.71193415637859
+    - type: cos_sim_precision
+      value: 92.37288135593221
+    - type: cos_sim_recall
+      value: 87.2
+    - type: dot_accuracy
+      value: 99.72079207920792
+    - type: dot_ap
+      value: 92.77707970155015
+    - type: dot_f1
+      value: 85.88588588588588
+    - type: dot_precision
+      value: 85.97194388777555
+    - type: dot_recall
+      value: 85.8
+    - type: euclidean_accuracy
+      value: 99.7980198019802
+    - type: euclidean_ap
+      value: 95.04124481520121
+    - type: euclidean_f1
+      value: 89.61693548387096
+    - type: euclidean_precision
+      value: 90.34552845528455
+    - type: euclidean_recall
+      value: 88.9
+    - type: manhattan_accuracy
+      value: 99.7960396039604
+    - type: manhattan_ap
+      value: 95.02691504694813
+    - type: manhattan_f1
+      value: 89.60321446509292
+    - type: manhattan_precision
+      value: 90.0100908173562
+    - type: manhattan_recall
+      value: 89.2
+    - type: max_accuracy
+      value: 99.8019801980198
+    - type: max_ap
+      value: 95.09301057928796
+    - type: max_f1
+      value: 89.71193415637859
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/stackexchange-clustering
+      name: MTEB StackExchangeClustering
+      config: default
+      split: test
+      revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
+    metrics:
+    - type: v_measure
+      value: 72.74124969197169
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/stackexchange-clustering-p2p
+      name: MTEB StackExchangeClusteringP2P
+      config: default
+      split: test
+      revision: 815ca46b2622cec33ccafc3735d572c266efdb44
+    metrics:
+    - type: v_measure
+      value: 32.262798307863996
+  - task:
+      type: Reranking
+    dataset:
+      type: mteb/stackoverflowdupquestions-reranking
+      name: MTEB StackOverflowDupQuestions
+      config: default
+      split: test
+      revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
+    metrics:
+    - type: map
+      value: 54.823414217790464
+    - type: mrr
+      value: 55.557133838383834
+  - task:
+      type: Summarization
+    dataset:
+      type: mteb/summeval
+      name: MTEB SummEval
+      config: default
+      split: test
+      revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
+    metrics:
+    - type: cos_sim_pearson
+      value: 31.01226930465494
+    - type: cos_sim_spearman
+      value: 30.9368445798007
+    - type: dot_pearson
+      value: 30.204833368654533
+    - type: dot_spearman
+      value: 30.438900411966618
+  - task:
+      type: Retrieval
+    dataset:
+      type: trec-covid
+      name: MTEB TRECCOVID
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 0.22699999999999998
+    - type: map_at_10
+      value: 2.0420000000000003
+    - type: map_at_100
+      value: 13.33
+    - type: map_at_1000
+      value: 33.627
+    - type: map_at_3
+      value: 0.639
+    - type: map_at_5
+      value: 1.056
+    - type: mrr_at_1
+      value: 84.0
+    - type: mrr_at_10
+      value: 91.167
+    - type: mrr_at_100
+      value: 91.167
+    - type: mrr_at_1000
+      value: 91.167
+    - type: mrr_at_3
+      value: 90.667
+    - type: mrr_at_5
+      value: 91.167
+    - type: ndcg_at_1
+      value: 82.0
+    - type: ndcg_at_10
+      value: 80.337
+    - type: ndcg_at_100
+      value: 65.852
+    - type: ndcg_at_1000
+      value: 59.821000000000005
+    - type: ndcg_at_3
+      value: 81.061
+    - type: ndcg_at_5
+      value: 81.396
+    - type: precision_at_1
+      value: 84.0
+    - type: precision_at_10
+      value: 85.0
+    - type: precision_at_100
+      value: 67.75999999999999
+    - type: precision_at_1000
+      value: 26.272000000000002
+    - type: precision_at_3
+      value: 85.333
+    - type: precision_at_5
+      value: 86.4
+    - type: recall_at_1
+      value: 0.22699999999999998
+    - type: recall_at_10
+      value: 2.241
+    - type: recall_at_100
+      value: 16.478
+    - type: recall_at_1000
+      value: 56.442
+    - type: recall_at_3
+      value: 0.672
+    - type: recall_at_5
+      value: 1.143
+  - task:
+      type: Retrieval
+    dataset:
+      type: webis-touche2020
+      name: MTEB Touche2020
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 1.836
+    - type: map_at_10
+      value: 8.536000000000001
+    - type: map_at_100
+      value: 14.184
+    - type: map_at_1000
+      value: 15.885
+    - type: map_at_3
+      value: 3.7359999999999998
+    - type: map_at_5
+      value: 5.253
+    - type: mrr_at_1
+      value: 22.448999999999998
+    - type: mrr_at_10
+      value: 34.77
+    - type: mrr_at_100
+      value: 36.18
+    - type: mrr_at_1000
+      value: 36.18
+    - type: mrr_at_3
+      value: 30.612000000000002
+    - type: mrr_at_5
+      value: 32.449
+    - type: ndcg_at_1
+      value: 20.408
+    - type: ndcg_at_10
+      value: 20.498
+    - type: ndcg_at_100
+      value: 33.354
+    - type: ndcg_at_1000
+      value: 45.699
+    - type: ndcg_at_3
+      value: 19.292
+    - type: ndcg_at_5
+      value: 19.541
+    - type: precision_at_1
+      value: 22.448999999999998
+    - type: precision_at_10
+      value: 19.387999999999998
+    - type: precision_at_100
+      value: 7.163
+    - type: precision_at_1000
+      value: 1.541
+    - type: precision_at_3
+      value: 19.728
+    - type: precision_at_5
+      value: 20.0
+    - type: recall_at_1
+      value: 1.836
+    - type: recall_at_10
+      value: 15.212
+    - type: recall_at_100
+      value: 45.364
+    - type: recall_at_1000
+      value: 83.64
+    - type: recall_at_3
+      value: 4.651000000000001
+    - type: recall_at_5
+      value: 7.736
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/toxic_conversations_50k
+      name: MTEB ToxicConversationsClassification
+      config: default
+      split: test
+      revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
+    metrics:
+    - type: accuracy
+      value: 70.5856
+    - type: ap
+      value: 14.297836125608864
+    - type: f1
+      value: 54.45458507465688
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/tweet_sentiment_extraction
+      name: MTEB TweetSentimentExtractionClassification
+      config: default
+      split: test
+      revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
+    metrics:
+    - type: accuracy
+      value: 61.89869835880024
+    - type: f1
+      value: 62.15163526419782
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/twentynewsgroups-clustering
+      name: MTEB TwentyNewsgroupsClustering
+      config: default
+      split: test
+      revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
+    metrics:
+    - type: v_measure
+      value: 56.408998393035446
+  - task:
+      type: PairClassification
+    dataset:
+      type: mteb/twittersemeval2015-pairclassification
+      name: MTEB TwitterSemEval2015
+      config: default
+      split: test
+      revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
+    metrics:
+    - type: cos_sim_accuracy
+      value: 88.78822197055493
+    - type: cos_sim_ap
+      value: 81.73234934293887
+    - type: cos_sim_f1
+      value: 74.16373812312898
+    - type: cos_sim_precision
+      value: 73.18263549961469
+    - type: cos_sim_recall
+      value: 75.17150395778364
+    - type: dot_accuracy
+      value: 87.85837754068069
+    - type: dot_ap
+      value: 79.69812660365871
+    - type: dot_f1
+      value: 72.52999744702579
+    - type: dot_precision
+      value: 70.25222551928783
+    - type: dot_recall
+      value: 74.96042216358839
+    - type: euclidean_accuracy
+      value: 88.74649818203493
+    - type: euclidean_ap
+      value: 81.47777928110055
+    - type: euclidean_f1
+      value: 74.1248097412481
+    - type: euclidean_precision
+      value: 71.37274059599413
+    - type: euclidean_recall
+      value: 77.0976253298153
+    - type: manhattan_accuracy
+      value: 88.7286165583835
+    - type: manhattan_ap
+      value: 81.47766386927232
+    - type: manhattan_f1
+      value: 74.16730231375541
+    - type: manhattan_precision
+      value: 71.56526005888125
+    - type: manhattan_recall
+      value: 76.96569920844327
+    - type: max_accuracy
+      value: 88.78822197055493
+    - type: max_ap
+      value: 81.73234934293887
+    - type: max_f1
+      value: 74.16730231375541
+  - task:
+      type: PairClassification
+    dataset:
+      type: mteb/twitterurlcorpus-pairclassification
+      name: MTEB TwitterURLCorpus
+      config: default
+      split: test
+      revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
+    metrics:
+    - type: cos_sim_accuracy
+      value: 89.30026778437536
+    - type: cos_sim_ap
+      value: 86.56353001037664
+    - type: cos_sim_f1
+      value: 79.359197907585
+    - type: cos_sim_precision
+      value: 75.12379642365887
+    - type: cos_sim_recall
+      value: 84.10070834616569
+    - type: dot_accuracy
+      value: 88.8539604921023
+    - type: dot_ap
+      value: 85.44601003294055
+    - type: dot_f1
+      value: 78.20008094484713
+    - type: dot_precision
+      value: 74.88549080403072
+    - type: dot_recall
+      value: 81.82168155220204
+    - type: euclidean_accuracy
+      value: 89.25369658865992
+    - type: euclidean_ap
+      value: 86.46965679550075
+    - type: euclidean_f1
+      value: 79.16785612332285
+    - type: euclidean_precision
+      value: 73.77627028465017
+    - type: euclidean_recall
+      value: 85.4096088697259
+    - type: manhattan_accuracy
+      value: 89.26727985407692
+    - type: manhattan_ap
+      value: 86.46460344566123
+    - type: manhattan_f1
+      value: 79.1723543358
+    - type: manhattan_precision
+      value: 74.20875420875421
+    - type: manhattan_recall
+      value: 84.84755158607946
+    - type: max_accuracy
+      value: 89.30026778437536
+    - type: max_ap
+      value: 86.56353001037664
+    - type: max_f1
+      value: 79.359197907585
+---
+
+# LLM2Vec: Large Language Models Are Secretly Powerful Text Encoders
+
+> LLM2Vec is a simple recipe to convert decoder-only LLMs into text encoders. It consists of 3 simple steps: 1) enabling bidirectional attention, 2) masked next token prediction, and 3) unsupervised contrastive learning. The model can be further fine-tuned to achieve state-of-the-art performance.
+- **Repository:** https://github.com/McGill-NLP/llm2vec
+- **Paper:** https://arxiv.org/abs/2404.05961
+
+
+## Installation
+```bash
+pip install llm2vec
+```
+
+## Usage
+```python
+from llm2vec import LLM2Vec
+
+import torch
+from transformers import AutoTokenizer, AutoModel, AutoConfig
+from peft import PeftModel
+
+# Loading base Mistral model, along with custom code that enables bidirectional connections in decoder-only LLMs. MNTP LoRA weights are merged into the base model.
+tokenizer = AutoTokenizer.from_pretrained(
+    "McGill-NLP/LLM2Vec-Meta-Llama-3-8B-Instruct-mntp"
+)
+config = AutoConfig.from_pretrained(
+    "McGill-NLP/LLM2Vec-Meta-Llama-3-8B-Instruct-mntp", trust_remote_code=True
+)
+model = AutoModel.from_pretrained(
+    "McGill-NLP/LLM2Vec-Meta-Llama-3-8B-Instruct-mntp",
+    trust_remote_code=True,
+    config=config,
+    torch_dtype=torch.bfloat16,
+    device_map="cuda" if torch.cuda.is_available() else "cpu",
+)
+model = PeftModel.from_pretrained(
+    model,
+    "McGill-NLP/LLM2Vec-Meta-Llama-3-8B-Instruct-mntp",
+)
+model = model.merge_and_unload()  # This can take several minutes on cpu
+
+# Loading supervised model. This loads the trained LoRA weights on top of MNTP model. Hence the final weights are -- Base model + MNTP (LoRA) + supervised (LoRA).
+model = PeftModel.from_pretrained(
+    model, "McGill-NLP/LLM2Vec-Meta-Llama-3-8B-Instruct-mntp-supervised"
+)
+
+# Wrapper for encoding and pooling operations
+l2v = LLM2Vec(model, tokenizer, pooling_mode="mean", max_length=512)
+
+# Encoding queries using instructions
+instruction = (
+    "Given a web search query, retrieve relevant passages that answer the query:"
+)
+queries = [
+    [instruction, "how much protein should a female eat"],
+    [instruction, "summit define"],
+]
+q_reps = l2v.encode(queries)
+
+# Encoding documents. Instruction are not required for documents
+documents = [
+    "As a general guideline, the CDC's average requirement of protein for women ages 19 to 70 is 46 grams per day. But, as you can see from this chart, you'll need to increase that if you're expecting or training for a marathon. Check out the chart below to see how much protein you should be eating each day.",
+    "Definition of summit for English Language Learners. : 1  the highest point of a mountain : the top of a mountain. : 2  the highest level. : 3  a meeting or series of meetings between the leaders of two or more governments.",
+]
+d_reps = l2v.encode(documents)
+
+# Compute cosine similarity
+q_reps_norm = torch.nn.functional.normalize(q_reps, p=2, dim=1)
+d_reps_norm = torch.nn.functional.normalize(d_reps, p=2, dim=1)
+cos_sim = torch.mm(q_reps_norm, d_reps_norm.transpose(0, 1))
+
+print(cos_sim)
+"""
+tensor([[0.6470, 0.1619],
+        [0.0786, 0.5844]])
+"""
+```
+
+## Questions
+If you have any question about the code, feel free to email Parishad (`parishad.behnamghader@mila.quebec`) and Vaibhav (`vaibhav.adlakha@mila.quebec`).

adapter_config.json

@@ -0,0 +1,35 @@
+{
+  "alpha_pattern": {},
+  "auto_mapping": {
+    "base_model_class": "LlamaEncoderModel",
+    "parent_library": "llama_encoder_model.modeling_llama_encoder"
+  },
+  "base_model_name_or_path": "6Morpheus6/LLM2Vec-Meta-Llama-3-8B-Instruct-mntp",
+  "bias": "none",
+  "fan_in_fan_out": false,
+  "inference_mode": true,
+  "init_lora_weights": true,
+  "layers_pattern": null,
+  "layers_to_transform": null,
+  "loftq_config": {},
+  "lora_alpha": 32,
+  "lora_dropout": 0.05,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "r": 16,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "k_proj",
+    "gate_proj",
+    "down_proj",
+    "up_proj",
+    "q_proj",
+    "o_proj",
+    "v_proj"
+  ],
+  "task_type": null,
+  "use_rslora": false
+}

adapter_model.safetensors

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+oid sha256:53f8f94ebdf396667ba99dd96e78203edae27bbcdbd1cf5f12b611e1d916b225
+size 167829552