peft safetensors 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 en license:mit model-index region:us
---
language:
- en
library_name: peft
license: mit
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: BinGSE-Meta-Llama-3-8B-Instruct
  results:
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonCounterfactualClassification (en-ext)
      type: mteb/amazon_counterfactual
      config: en-ext
      split: test
      revision: e8379541af4e31359cca9fbcf4b00f2671dba205
    metrics:
    - type: accuracy
      value: 80.7271364317841
    - type: ap
      value: 29.57781615779065
    - type: ap_weighted
      value: 29.57781615779065
    - type: f1
      value: 67.88722644497633
    - type: f1_weighted
      value: 83.93210384487763
    - type: main_score
      value: 80.7271364317841
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonCounterfactualClassification (en)
      type: mteb/amazon_counterfactual
      config: en
      split: test
      revision: e8379541af4e31359cca9fbcf4b00f2671dba205
    metrics:
    - type: accuracy
      value: 80.41791044776122
    - type: ap
      value: 44.865115567829
    - type: ap_weighted
      value: 44.865115567829
    - type: f1
      value: 74.51584838607613
    - type: f1_weighted
      value: 81.95697646844347
    - type: main_score
      value: 80.41791044776122
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonPolarityClassification (default)
      type: mteb/amazon_polarity
      config: default
      split: test
      revision: e2d317d38cd51312af73b3d32a06d1a08b442046
    metrics:
    - type: accuracy
      value: 91.384925
    - type: ap
      value: 87.67370574947891
    - type: ap_weighted
      value: 87.67370574947891
    - type: f1
      value: 91.37299490898192
    - type: f1_weighted
      value: 91.37299490898194
    - type: main_score
      value: 91.384925
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonReviewsClassification (en)
      type: mteb/amazon_reviews_multi
      config: en
      split: test
      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
    metrics:
    - type: accuracy
      value: 51.532
    - type: f1
      value: 49.493931716627664
    - type: f1_weighted
      value: 49.49393171662767
    - type: main_score
      value: 51.532
  - task:
      type: Retrieval
    dataset:
      name: MTEB ArguAna (default)
      type: mteb/arguana
      config: default
      split: test
      revision: c22ab2a51041ffd869aaddef7af8d8215647e41a
    metrics:
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    - type: map_at_10
      value: 51.995999999999995
    - type: map_at_100
      value: 52.662
    - type: map_at_1000
      value: 52.664
    - type: map_at_20
      value: 52.563
    - type: map_at_3
      value: 47.321000000000005
    - type: map_at_5
      value: 49.864000000000004
    - type: mrr_at_1
      value: 37.12660028449502
    - type: mrr_at_10
      value: 52.21801688906961
    - type: mrr_at_100
      value: 52.896624713480335
    - type: mrr_at_1000
      value: 52.899139810952356
    - type: mrr_at_20
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    - type: mrr_at_3
      value: 47.629208155524005
    - type: mrr_at_5
      value: 50.111427216690494
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    - type: ndcg_at_1
      value: 36.486000000000004
    - type: ndcg_at_10
      value: 60.614000000000004
    - type: ndcg_at_100
      value: 63.243
    - type: ndcg_at_1000
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    - type: ndcg_at_20
      value: 62.598
    - type: ndcg_at_3
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    - type: ndcg_at_5
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    - type: precision_at_1
      value: 36.486000000000004
    - type: precision_at_10
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    - type: precision_at_100
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    - type: precision_at_1000
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    - type: precision_at_3
      value: 20.436
    - type: precision_at_5
      value: 14.466999999999999
    - type: recall_at_1
      value: 36.486000000000004
    - type: recall_at_10
      value: 88.193
    - type: recall_at_100
      value: 99.21799999999999
    - type: recall_at_1000
      value: 99.644
    - type: recall_at_20
      value: 95.875
    - type: recall_at_3
      value: 61.309000000000005
    - type: recall_at_5
      value: 72.333
  - task:
      type: Clustering
    dataset:
      name: MTEB ArxivClusteringP2P (default)
      type: mteb/arxiv-clustering-p2p
      config: default
      split: test
      revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
    metrics:
    - type: main_score
      value: 47.89537370883614
    - type: v_measure
      value: 47.89537370883614
    - type: v_measure_std
      value: 13.564912043981685
  - task:
      type: Clustering
    dataset:
      name: MTEB ArxivClusteringS2S (default)
      type: mteb/arxiv-clustering-s2s
      config: default
      split: test
      revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
    metrics:
    - type: main_score
      value: 46.316519519112575
    - type: v_measure
      value: 46.316519519112575
    - type: v_measure_std
      value: 14.064564320172318
  - task:
      type: Reranking
    dataset:
      name: MTEB AskUbuntuDupQuestions (default)
      type: mteb/askubuntudupquestions-reranking
      config: default
      split: test
      revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
    metrics:
    - type: main_score
      value: 65.09483223839607
    - type: map
      value: 65.09483223839607
    - type: mrr
      value: 77.75601283911533
    - type: nAUC_map_diff1
      value: 12.614852005743735
    - type: nAUC_map_max
      value: 29.257344662071027
    - type: nAUC_map_std
      value: 17.630286672870287
    - type: nAUC_mrr_diff1
      value: 16.314189417460618
    - type: nAUC_mrr_max
      value: 39.68682288371764
    - type: nAUC_mrr_std
      value: 22.85236267444885
  - task:
      type: STS
    dataset:
      name: MTEB BIOSSES (default)
      type: mteb/biosses-sts
      config: default
      split: test
      revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
    metrics:
    - type: cosine_pearson
      value: 87.64275539432272
    - type: cosine_spearman
      value: 86.93752309911496
    - type: euclidean_pearson
      value: 85.76812373084148
    - type: euclidean_spearman
      value: 86.93752309911496
    - type: main_score
      value: 86.93752309911496
    - type: manhattan_pearson
      value: 85.66299640283663
    - type: manhattan_spearman
      value: 86.79053179801122
    - type: pearson
      value: 87.64276222909432
    - type: spearman
      value: 86.93752309911496
  - task:
      type: Classification
    dataset:
      name: MTEB Banking77Classification (default)
      type: mteb/banking77
      config: default
      split: test
      revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
    metrics:
    - type: accuracy
      value: 84.83116883116884
    - type: f1
      value: 84.33922428309117
    - type: f1_weighted
      value: 84.33922428309116
    - type: main_score
      value: 84.83116883116884
  - task:
      type: Clustering
    dataset:
      name: MTEB BiorxivClusteringP2P (default)
      type: mteb/biorxiv-clustering-p2p
      config: default
      split: test
      revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
    metrics:
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      value: 36.931855182990965
    - type: v_measure
      value: 36.931855182990965
    - type: v_measure_std
      value: 1.259241362575525
  - task:
      type: Clustering
    dataset:
      name: MTEB BiorxivClusteringS2S (default)
      type: mteb/biorxiv-clustering-s2s
      config: default
      split: test
      revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
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      value: 38.276834717269345
    - type: v_measure
      value: 38.276834717269345
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      value: 0.8171217218107112
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackAndroidRetrieval (default)
      type: mteb/cqadupstack-android
      config: default
      split: test
      revision: f46a197baaae43b4f621051089b82a364682dfeb
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      value: 53.199
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      value: 32.222
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      value: 45.985
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    - type: map_at_1000
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      type: CQADupstackRetrieval_is_a_combined_dataset
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  - task:
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      type: mteb/imdb
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      revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
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  - task:
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      type: mteb/msmarco
      config: default
      split: dev
      revision: c5a29a104738b98a9e76336939199e264163d4a0
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  - task:
      type: Classification
    dataset:
      name: MTEB MTOPDomainClassification (en)
      type: mteb/mtop_domain
      config: en
      split: test
      revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
    metrics:
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  - task:
      type: Classification
    dataset:
      name: MTEB MTOPIntentClassification (en)
      type: mteb/mtop_intent
      config: en
      split: test
      revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
    metrics:
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    - type: f1
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      value: 80.57433767622484
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      value: 78.61833105335158
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (en)
      type: mteb/amazon_massive_intent
      config: en
      split: test
      revision: 4672e20407010da34463acc759c162ca9734bca6
    metrics:
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  - task:
      type: Classification
    dataset:
      name: MTEB MassiveScenarioClassification (en)
      type: mteb/amazon_massive_scenario
      config: en
      split: test
      revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
    metrics:
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  - task:
      type: Clustering
    dataset:
      name: MTEB MedrxivClusteringP2P (default)
      type: mteb/medrxiv-clustering-p2p
      config: default
      split: test
      revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
    metrics:
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  - task:
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      type: mteb/medrxiv-clustering-s2s
      config: default
      split: test
      revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
    metrics:
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  - task:
      type: Reranking
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      type: mteb/mind_small
      config: default
      split: test
      revision: 59042f120c80e8afa9cdbb224f67076cec0fc9a7
    metrics:
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    - type: map
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  - task:
      type: Retrieval
    dataset:
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  - task:
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      revision: e4e08e0b7dbe3c8700f0daef558ff32256715259
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    - type: recall_at_3
      value: 12.178
    - type: recall_at_5
      value: 16.682
  - task:
      type: STS
    dataset:
      name: MTEB SICK-R (default)
      type: mteb/sickr-sts
      config: default
      split: test
      revision: 20a6d6f312dd54037fe07a32d58e5e168867909d
    metrics:
    - type: cosine_pearson
      value: 86.24041625333884
    - type: cosine_spearman
      value: 83.72893029404888
    - type: euclidean_pearson
      value: 83.33176396347261
    - type: euclidean_spearman
      value: 83.72893162160777
    - type: main_score
      value: 83.72893029404888
    - type: manhattan_pearson
      value: 83.2951639248276
    - type: manhattan_spearman
      value: 83.70786795927772
    - type: pearson
      value: 86.24041617887043
    - type: spearman
      value: 83.72891772746166
  - task:
      type: STS
    dataset:
      name: MTEB STS12 (default)
      type: mteb/sts12-sts
      config: default
      split: test
      revision: a0d554a64d88156834ff5ae9920b964011b16384
    metrics:
    - type: cosine_pearson
      value: 87.17185113605036
    - type: cosine_spearman
      value: 81.39213356797624
    - type: euclidean_pearson
      value: 83.70587654694744
    - type: euclidean_spearman
      value: 81.39213356797624
    - type: main_score
      value: 81.39213356797624
    - type: manhattan_pearson
      value: 83.63386349627461
    - type: manhattan_spearman
      value: 81.35222067791558
    - type: pearson
      value: 87.17185260321112
    - type: spearman
      value: 81.38945351411505
  - task:
      type: STS
    dataset:
      name: MTEB STS13 (default)
      type: mteb/sts13-sts
      config: default
      split: test
      revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
    metrics:
    - type: cosine_pearson
      value: 87.34454475793186
    - type: cosine_spearman
      value: 87.96270687409215
    - type: euclidean_pearson
      value: 87.90388791262633
    - type: euclidean_spearman
      value: 87.96270687409215
    - type: main_score
      value: 87.96270687409215
    - type: manhattan_pearson
      value: 87.83677697801643
    - type: manhattan_spearman
      value: 87.86991808368111
    - type: pearson
      value: 87.34454465314778
    - type: spearman
      value: 87.96270679590305
  - task:
      type: STS
    dataset:
      name: MTEB STS14 (default)
      type: mteb/sts14-sts
      config: default
      split: test
      revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
    metrics:
    - type: cosine_pearson
      value: 86.3049595329839
    - type: cosine_spearman
      value: 85.57773596099139
    - type: euclidean_pearson
      value: 85.61735029771381
    - type: euclidean_spearman
      value: 85.57774644488029
    - type: main_score
      value: 85.57773596099139
    - type: manhattan_pearson
      value: 85.58315505256886
    - type: manhattan_spearman
      value: 85.55100867169023
    - type: pearson
      value: 86.30495993546997
    - type: spearman
      value: 85.57781195336361
  - task:
      type: STS
    dataset:
      name: MTEB STS15 (default)
      type: mteb/sts15-sts
      config: default
      split: test
      revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
    metrics:
    - type: cosine_pearson
      value: 89.43687886823619
    - type: cosine_spearman
      value: 89.77514474209266
    - type: euclidean_pearson
      value: 89.16048792386724
    - type: euclidean_spearman
      value: 89.77514474209266
    - type: main_score
      value: 89.77514474209266
    - type: manhattan_pearson
      value: 89.13664728081469
    - type: manhattan_spearman
      value: 89.75080436431723
    - type: pearson
      value: 89.43687930700762
    - type: spearman
      value: 89.7750799990083
  - task:
      type: STS
    dataset:
      name: MTEB STS16 (default)
      type: mteb/sts16-sts
      config: default
      split: test
      revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
    metrics:
    - type: cosine_pearson
      value: 86.6450386341272
    - type: cosine_spearman
      value: 87.89409021728935
    - type: euclidean_pearson
      value: 87.49933167247268
    - type: euclidean_spearman
      value: 87.89409021728935
    - type: main_score
      value: 87.89409021728935
    - type: manhattan_pearson
      value: 87.50687956428204
    - type: manhattan_spearman
      value: 87.9178498829234
    - type: pearson
      value: 86.64503867578216
    - type: spearman
      value: 87.8940895850418
  - task:
      type: STS
    dataset:
      name: MTEB STS17 (nl-en)
      type: mteb/sts17-crosslingual-sts
      config: nl-en
      split: test
      revision: faeb762787bd10488a50c8b5be4a3b82e411949c
    metrics:
    - type: cosine_pearson
      value: 89.6338656277505
    - type: cosine_spearman
      value: 89.75701751196556
    - type: euclidean_pearson
      value: 90.00670260496013
    - type: euclidean_spearman
      value: 89.75701751196556
    - type: main_score
      value: 89.75701751196556
    - type: manhattan_pearson
      value: 90.02629735900686
    - type: manhattan_spearman
      value: 89.7213070723708
    - type: pearson
      value: 89.63386499936783
    - type: spearman
      value: 89.75701751196556
  - task:
      type: STS
    dataset:
      name: MTEB STS17 (en-tr)
      type: mteb/sts17-crosslingual-sts
      config: en-tr
      split: test
      revision: faeb762787bd10488a50c8b5be4a3b82e411949c
    metrics:
    - type: cosine_pearson
      value: 83.93143564932134
    - type: cosine_spearman
      value: 82.93577775011765
    - type: euclidean_pearson
      value: 84.34621382409651
    - type: euclidean_spearman
      value: 82.93577775011765
    - type: main_score
      value: 82.93577775011765
    - type: manhattan_pearson
      value: 84.31655977000447
    - type: manhattan_spearman
      value: 82.76584164596149
    - type: pearson
      value: 83.9314336093673
    - type: spearman
      value: 82.93577775011765
  - task:
      type: STS
    dataset:
      name: MTEB STS17 (en-en)
      type: mteb/sts17-crosslingual-sts
      config: en-en
      split: test
      revision: faeb762787bd10488a50c8b5be4a3b82e411949c
    metrics:
    - type: cosine_pearson
      value: 91.88424206333126
    - type: cosine_spearman
      value: 92.02107475813581
    - type: euclidean_pearson
      value: 91.9171107672214
    - type: euclidean_spearman
      value: 92.02107475813581
    - type: main_score
      value: 92.02107475813581
    - type: manhattan_pearson
      value: 91.98552208613084
    - type: manhattan_spearman
      value: 92.04844379257229
    - type: pearson
      value: 91.88424111217977
    - type: spearman
      value: 92.02107475813581
  - task:
      type: STS
    dataset:
      name: MTEB STS17 (en-de)
      type: mteb/sts17-crosslingual-sts
      config: en-de
      split: test
      revision: faeb762787bd10488a50c8b5be4a3b82e411949c
    metrics:
    - type: cosine_pearson
      value: 90.04918981538256
    - type: cosine_spearman
      value: 90.03247608046513
    - type: euclidean_pearson
      value: 90.28411220954267
    - type: euclidean_spearman
      value: 90.03247608046513
    - type: main_score
      value: 90.03247608046513
    - type: manhattan_pearson
      value: 90.3114074165839
    - type: manhattan_spearman
      value: 90.09098123553856
    - type: pearson
      value: 90.04919169584696
    - type: spearman
      value: 90.03247608046513
  - task:
      type: STS
    dataset:
      name: MTEB STS17 (fr-en)
      type: mteb/sts17-crosslingual-sts
      config: fr-en
      split: test
      revision: faeb762787bd10488a50c8b5be4a3b82e411949c
    metrics:
    - type: cosine_pearson
      value: 88.9930259888809
    - type: cosine_spearman
      value: 88.83327416007984
    - type: euclidean_pearson
      value: 89.39082582616547
    - type: euclidean_spearman
      value: 88.83327416007984
    - type: main_score
      value: 88.83327416007984
    - type: manhattan_pearson
      value: 89.38701261060531
    - type: manhattan_spearman
      value: 88.92998833233004
    - type: pearson
      value: 88.99302543858553
    - type: spearman
      value: 88.83327416007984
  - task:
      type: STS
    dataset:
      name: MTEB STS17 (es-en)
      type: mteb/sts17-crosslingual-sts
      config: es-en
      split: test
      revision: faeb762787bd10488a50c8b5be4a3b82e411949c
    metrics:
    - type: cosine_pearson
      value: 89.95636875543408
    - type: cosine_spearman
      value: 90.39244260353328
    - type: euclidean_pearson
      value: 90.29925474076606
    - type: euclidean_spearman
      value: 90.39244260353328
    - type: main_score
      value: 90.39244260353328
    - type: manhattan_pearson
      value: 90.37981122989076
    - type: manhattan_spearman
      value: 90.41247149045391
    - type: pearson
      value: 89.95636893306808
    - type: spearman
      value: 90.39244260353328
  - task:
      type: STS
    dataset:
      name: MTEB STS17 (it-en)
      type: mteb/sts17-crosslingual-sts
      config: it-en
      split: test
      revision: faeb762787bd10488a50c8b5be4a3b82e411949c
    metrics:
    - type: cosine_pearson
      value: 89.53145408873213
    - type: cosine_spearman
      value: 89.64992463283636
    - type: euclidean_pearson
      value: 89.92739726473282
    - type: euclidean_spearman
      value: 89.64992463283636
    - type: main_score
      value: 89.64992463283636
    - type: manhattan_pearson
      value: 89.88973812881389
    - type: manhattan_spearman
      value: 89.66533893453442
    - type: pearson
      value: 89.53145070613068
    - type: spearman
      value: 89.64992463283636
  - task:
      type: STS
    dataset:
      name: MTEB STS17 (en-ar)
      type: mteb/sts17-crosslingual-sts
      config: en-ar
      split: test
      revision: faeb762787bd10488a50c8b5be4a3b82e411949c
    metrics:
    - type: cosine_pearson
      value: 83.73753567473895
    - type: cosine_spearman
      value: 83.56786342290584
    - type: euclidean_pearson
      value: 84.2185817227647
    - type: euclidean_spearman
      value: 83.56786342290584
    - type: main_score
      value: 83.56786342290584
    - type: manhattan_pearson
      value: 84.138637673995
    - type: manhattan_spearman
      value: 83.5447994878456
    - type: pearson
      value: 83.73753620404003
    - type: spearman
      value: 83.56786342290584
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (en)
      type: mteb/sts22-crosslingual-sts
      config: en
      split: test
      revision: de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3
    metrics:
    - type: cosine_pearson
      value: 70.0174654163193
    - type: cosine_spearman
      value: 69.00945960078879
    - type: euclidean_pearson
      value: 70.00006875963157
    - type: euclidean_spearman
      value: 69.00945960078879
    - type: main_score
      value: 69.00945960078879
    - type: manhattan_pearson
      value: 70.003828333656
    - type: manhattan_spearman
      value: 69.18289416785358
    - type: pearson
      value: 70.01746869245112
    - type: spearman
      value: 69.00945960078879
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (pl-en)
      type: mteb/sts22-crosslingual-sts
      config: pl-en
      split: test
      revision: de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3
    metrics:
    - type: cosine_pearson
      value: 74.4773241351154
    - type: cosine_spearman
      value: 72.23771584903263
    - type: euclidean_pearson
      value: 74.91922500307354
    - type: euclidean_spearman
      value: 72.23771584903263
    - type: main_score
      value: 72.23771584903263
    - type: manhattan_pearson
      value: 75.40992669459347
    - type: manhattan_spearman
      value: 72.89930017966125
    - type: pearson
      value: 74.47733091997848
    - type: spearman
      value: 72.23771584903263
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (zh-en)
      type: mteb/sts22-crosslingual-sts
      config: zh-en
      split: test
      revision: de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3
    metrics:
    - type: cosine_pearson
      value: 74.66163345044995
    - type: cosine_spearman
      value: 73.412615202234
    - type: euclidean_pearson
      value: 76.51572664173365
    - type: euclidean_spearman
      value: 73.412615202234
    - type: main_score
      value: 73.412615202234
    - type: manhattan_pearson
      value: 76.44349976731687
    - type: manhattan_spearman
      value: 73.40243152214946
    - type: pearson
      value: 74.66163870997642
    - type: spearman
      value: 73.412615202234
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (de-en)
      type: mteb/sts22-crosslingual-sts
      config: de-en
      split: test
      revision: de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3
    metrics:
    - type: cosine_pearson
      value: 65.14758907269797
    - type: cosine_spearman
      value: 58.30708936630836
    - type: euclidean_pearson
      value: 67.98705996212436
    - type: euclidean_spearman
      value: 58.30708936630836
    - type: main_score
      value: 58.30708936630836
    - type: manhattan_pearson
      value: 68.41525035556984
    - type: manhattan_spearman
      value: 58.879912875433405
    - type: pearson
      value: 65.1475973244717
    - type: spearman
      value: 58.30708936630836
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (es-en)
      type: mteb/sts22-crosslingual-sts
      config: es-en
      split: test
      revision: de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3
    metrics:
    - type: cosine_pearson
      value: 74.73278263018503
    - type: cosine_spearman
      value: 77.18831783868316
    - type: euclidean_pearson
      value: 76.28171718825621
    - type: euclidean_spearman
      value: 77.18831783868316
    - type: main_score
      value: 77.18831783868316
    - type: manhattan_pearson
      value: 76.73656610143712
    - type: manhattan_spearman
      value: 77.45086643213952
    - type: pearson
      value: 74.73278783040479
    - type: spearman
      value: 77.18831783868316
  - task:
      type: STS
    dataset:
      name: MTEB STSBenchmark (default)
      type: mteb/stsbenchmark-sts
      config: default
      split: test
      revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
    metrics:
    - type: cosine_pearson
      value: 88.25299312156041
    - type: cosine_spearman
      value: 88.82703987306
    - type: euclidean_pearson
      value: 88.42751133294018
    - type: euclidean_spearman
      value: 88.82706405302517
    - type: main_score
      value: 88.82703987306
    - type: manhattan_pearson
      value: 88.41336953833218
    - type: manhattan_spearman
      value: 88.81246784315815
    - type: pearson
      value: 88.25299276543255
    - type: spearman
      value: 88.82706405302517
  - task:
      type: Reranking
    dataset:
      name: MTEB SciDocsRR (default)
      type: mteb/scidocs-reranking
      config: default
      split: test
      revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
    metrics:
    - type: main_score
      value: 86.15363437294592
    - type: map
      value: 86.15363437294592
    - type: mrr
      value: 96.44521056285762
    - type: nAUC_map_diff1
      value: -0.7840810005333841
    - type: nAUC_map_max
      value: 54.6142751932947
    - type: nAUC_map_std
      value: 70.13929703223857
    - type: nAUC_mrr_diff1
      value: 44.20312446414372
    - type: nAUC_mrr_max
      value: 89.20896097421188
    - type: nAUC_mrr_std
      value: 85.57161978228
  - task:
      type: Retrieval
    dataset:
      name: MTEB SciFact (default)
      type: mteb/scifact
      config: default
      split: test
      revision: 0228b52cf27578f30900b9e5271d331663a030d7
    metrics:
    - type: main_score
      value: 77.962
    - type: map_at_1
      value: 60.260999999999996
    - type: map_at_10
      value: 72.719
    - type: map_at_100
      value: 73.071
    - type: map_at_1000
      value: 73.08
    - type: map_at_20
      value: 72.99
    - type: map_at_3
      value: 69.848
    - type: map_at_5
      value: 71.61999999999999
    - type: mrr_at_1
      value: 63.33333333333333
    - type: mrr_at_10
      value: 73.84933862433863
    - type: mrr_at_100
      value: 74.10371086565036
    - type: mrr_at_1000
      value: 74.1131185688027
    - type: mrr_at_20
      value: 74.05291111394054
    - type: mrr_at_3
      value: 71.88888888888891
    - type: mrr_at_5
      value: 73.0388888888889
    - type: nauc_map_at_1000_diff1
      value: 73.28126828990776
    - type: nauc_map_at_1000_max
      value: 56.022306476443916
    - type: nauc_map_at_1000_std
      value: -13.480460345909812
    - type: nauc_map_at_100_diff1
      value: 73.27839985062069
    - type: nauc_map_at_100_max
      value: 56.03493565179317
    - type: nauc_map_at_100_std
      value: -13.454356894686633
    - type: nauc_map_at_10_diff1
      value: 73.12140372590137
    - type: nauc_map_at_10_max
      value: 56.152651928007735
    - type: nauc_map_at_10_std
      value: -13.995855741014923
    - type: nauc_map_at_1_diff1
      value: 77.99227635266456
    - type: nauc_map_at_1_max
      value: 52.094851365294005
    - type: nauc_map_at_1_std
      value: -19.182145033673432
    - type: nauc_map_at_20_diff1
      value: 73.20306405935685
    - type: nauc_map_at_20_max
      value: 56.081550664849445
    - type: nauc_map_at_20_std
      value: -13.584356458468374
    - type: nauc_map_at_3_diff1
      value: 73.19141715738098
    - type: nauc_map_at_3_max
      value: 53.23078378298865
    - type: nauc_map_at_3_std
      value: -16.528167718115526
    - type: nauc_map_at_5_diff1
      value: 73.24024366833353
    - type: nauc_map_at_5_max
      value: 55.180209378383424
    - type: nauc_map_at_5_std
      value: -14.183250373332857
    - type: nauc_mrr_at_1000_diff1
      value: 73.71148233352608
    - type: nauc_mrr_at_1000_max
      value: 56.5362956066201
    - type: nauc_mrr_at_1000_std
      value: -11.469817601047366
    - type: nauc_mrr_at_100_diff1
      value: 73.70835498956635
    - type: nauc_mrr_at_100_max
      value: 56.54902766570207
    - type: nauc_mrr_at_100_std
      value: -11.443909853912619
    - type: nauc_mrr_at_10_diff1
      value: 73.57665142725747
    - type: nauc_mrr_at_10_max
      value: 56.74885354320269
    - type: nauc_mrr_at_10_std
      value: -11.545364799905967
    - type: nauc_mrr_at_1_diff1
      value: 77.9008777001104
    - type: nauc_mrr_at_1_max
      value: 56.02354548799079
    - type: nauc_mrr_at_1_std
      value: -12.985757082041294
    - type: nauc_mrr_at_20_diff1
      value: 73.63832217061234
    - type: nauc_mrr_at_20_max
      value: 56.548555401068235
    - type: nauc_mrr_at_20_std
      value: -11.560701355628849
    - type: nauc_mrr_at_3_diff1
      value: 72.90361783677665
    - type: nauc_mrr_at_3_max
      value: 54.67757749945108
    - type: nauc_mrr_at_3_std
      value: -11.094286378923906
    - type: nauc_mrr_at_5_diff1
      value: 73.54194799038713
    - type: nauc_mrr_at_5_max
      value: 56.396527065053235
    - type: nauc_mrr_at_5_std
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    - type: recall_at_1000
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    - type: recall_at_20
      value: 95.767
    - type: recall_at_3
      value: 80.561
    - type: recall_at_5
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  - task:
      type: PairClassification
    dataset:
      name: MTEB SprintDuplicateQuestions (default)
      type: mteb/sprintduplicatequestions-pairclassification
      config: default
      split: test
      revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
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    - type: cosine_precision
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    - type: cosine_recall
      value: 94.1
    - type: dot_accuracy
      value: 99.83564356435643
    - type: dot_accuracy_threshold
      value: 82.17268586158752
    - type: dot_ap
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    - type: dot_precision
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    - type: dot_recall
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    - type: euclidean_accuracy_threshold
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    - type: euclidean_ap
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    - type: euclidean_precision
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    - type: euclidean_recall
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    - type: manhattan_precision
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    - type: manhattan_recall
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    - type: max_ap
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      value: 94.5
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    - type: similarity_accuracy_threshold
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    - type: similarity_ap
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      value: 1805.6900024414062
    - type: similarity_precision
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    - type: similarity_recall
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  - task:
      type: Clustering
    dataset:
      name: MTEB StackExchangeClustering (default)
      type: mteb/stackexchange-clustering
      config: default
      split: test
      revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
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    - type: v_measure
      value: 70.93157767772517
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      value: 4.307686954444112
  - task:
      type: Clustering
    dataset:
      name: MTEB StackExchangeClusteringP2P (default)
      type: mteb/stackexchange-clustering-p2p
      config: default
      split: test
      revision: 815ca46b2622cec33ccafc3735d572c266efdb44
    metrics:
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    - type: v_measure
      value: 33.95011259900505
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  - task:
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    dataset:
      name: MTEB StackOverflowDupQuestions (default)
      type: mteb/stackoverflowdupquestions-reranking
      config: default
      split: test
      revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
    metrics:
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  - task:
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      name: MTEB SummEval (default)
      type: mteb/summeval
      config: default
      split: test
      revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
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    - type: pearson
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    - type: spearman
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  - task:
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      type: mteb/trec-covid
      config: default
      split: test
      revision: bb9466bac8153a0349341eb1b22e06409e78ef4e
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    - type: precision_at_5
      value: 88.4
    - type: recall_at_1
      value: 0.244
    - type: recall_at_10
      value: 2.22
    - type: recall_at_100
      value: 16.697
    - type: recall_at_1000
      value: 57.033
    - type: recall_at_20
      value: 4.301
    - type: recall_at_3
      value: 0.685
    - type: recall_at_5
      value: 1.159
  - task:
      type: Retrieval
    dataset:
      name: MTEB Touche2020 (default)
      type: mteb/touche2020
      config: default
      split: test
      revision: a34f9a33db75fa0cbb21bb5cfc3dae8dc8bec93f
    metrics:
    - type: main_score
      value: 24.7
    - type: map_at_1
      value: 1.8350000000000002
    - type: map_at_10
      value: 9.385
    - type: map_at_100
      value: 15.751999999999999
    - type: map_at_1000
      value: 17.357
    - type: map_at_20
      value: 11.93
    - type: map_at_3
      value: 4.455
    - type: map_at_5
      value: 6.188
    - type: mrr_at_1
      value: 28.57142857142857
    - type: mrr_at_10
      value: 43.27340459993521
    - type: mrr_at_100
      value: 44.588722072878205
    - type: mrr_at_1000
      value: 44.588722072878205
    - type: mrr_at_20
      value: 44.17137463324359
    - type: mrr_at_3
      value: 39.455782312925166
    - type: mrr_at_5
      value: 41.70068027210883
    - type: nauc_map_at_1000_diff1
      value: 3.8298195437770537
    - type: nauc_map_at_1000_max
      value: 13.771844732194829
    - type: nauc_map_at_1000_std
      value: 19.29786404290547
    - type: nauc_map_at_100_diff1
      value: 3.8927604843499735
    - type: nauc_map_at_100_max
      value: 12.769257441869922
    - type: nauc_map_at_100_std
      value: 15.788237027355665
    - type: nauc_map_at_10_diff1
      value: 5.931490598251997
    - type: nauc_map_at_10_max
      value: 13.680069332373563
    - type: nauc_map_at_10_std
      value: 1.1621360655557855
    - type: nauc_map_at_1_diff1
      value: 2.5191045547339246
    - type: nauc_map_at_1_max
      value: 26.262684180827723
    - type: nauc_map_at_1_std
      value: 11.673938727339559
    - type: nauc_map_at_20_diff1
      value: 3.006592455468332
    - type: nauc_map_at_20_max
      value: 11.717797097718446
    - type: nauc_map_at_20_std
      value: 2.2724143319154315
    - type: nauc_map_at_3_diff1
      value: 12.831129328925664
    - type: nauc_map_at_3_max
      value: 12.405779573598991
    - type: nauc_map_at_3_std
      value: -2.8124187492891264
    - type: nauc_map_at_5_diff1
      value: 15.98021350983196
    - type: nauc_map_at_5_max
      value: 9.056183547839753
    - type: nauc_map_at_5_std
      value: -3.2826962878341788
    - type: nauc_mrr_at_1000_diff1
      value: -5.794890738524456
    - type: nauc_mrr_at_1000_max
      value: 13.697185831632897
    - type: nauc_mrr_at_1000_std
      value: 24.631969103480568
    - type: nauc_mrr_at_100_diff1
      value: -5.794890738524456
    - type: nauc_mrr_at_100_max
      value: 13.697185831632897
    - type: nauc_mrr_at_100_std
      value: 24.631969103480568
    - type: nauc_mrr_at_10_diff1
      value: -6.386203318843087
    - type: nauc_mrr_at_10_max
      value: 13.244363733609843
    - type: nauc_mrr_at_10_std
      value: 23.85218563666624
    - type: nauc_mrr_at_1_diff1
      value: -10.071571494502948
    - type: nauc_mrr_at_1_max
      value: 17.28112978017911
    - type: nauc_mrr_at_1_std
      value: 21.458308992920365
    - type: nauc_mrr_at_20_diff1
      value: -6.003367578570198
    - type: nauc_mrr_at_20_max
      value: 13.911873192715065
    - type: nauc_mrr_at_20_std
      value: 25.477100749222902
    - type: nauc_mrr_at_3_diff1
      value: -6.867484873134922
    - type: nauc_mrr_at_3_max
      value: 15.64058174587745
    - type: nauc_mrr_at_3_std
      value: 22.712306358508364
    - type: nauc_mrr_at_5_diff1
      value: -4.809966508264632
    - type: nauc_mrr_at_5_max
      value: 12.095003702970027
    - type: nauc_mrr_at_5_std
      value: 24.442255620074484
    - type: nauc_ndcg_at_1000_diff1
      value: 11.434789444093685
    - type: nauc_ndcg_at_1000_max
      value: 19.86851237564927
    - type: nauc_ndcg_at_1000_std
      value: 40.75483058183507
    - type: nauc_ndcg_at_100_diff1
      value: 8.47533044191214
    - type: nauc_ndcg_at_100_max
      value: 13.575094411118432
    - type: nauc_ndcg_at_100_std
      value: 35.56446142831008
    - type: nauc_ndcg_at_10_diff1
      value: 3.8335346471495133
    - type: nauc_ndcg_at_10_max
      value: 13.604843458587629
    - type: nauc_ndcg_at_10_std
      value: 14.026218004849186
    - type: nauc_ndcg_at_1_diff1
      value: -7.753442025343042
    - type: nauc_ndcg_at_1_max
      value: 16.06299655203062
    - type: nauc_ndcg_at_1_std
      value: 21.58079636889492
    - type: nauc_ndcg_at_20_diff1
      value: 7.440981403494449
    - type: nauc_ndcg_at_20_max
      value: 10.960931136182648
    - type: nauc_ndcg_at_20_std
      value: 14.132481758302665
    - type: nauc_ndcg_at_3_diff1
      value: 8.097829929493612
    - type: nauc_ndcg_at_3_max
      value: 13.50824542271782
    - type: nauc_ndcg_at_3_std
      value: 13.275247050693869
    - type: nauc_ndcg_at_5_diff1
      value: 11.971002032611313
    - type: nauc_ndcg_at_5_max
      value: 7.246169276334145
    - type: nauc_ndcg_at_5_std
      value: 13.975255468959613
    - type: nauc_precision_at_1000_diff1
      value: 5.616105475807897
    - type: nauc_precision_at_1000_max
      value: 25.581074402479505
    - type: nauc_precision_at_1000_std
      value: 28.030885522347404
    - type: nauc_precision_at_100_diff1
      value: 5.563452871367157
    - type: nauc_precision_at_100_max
      value: 20.2742392314572
    - type: nauc_precision_at_100_std
      value: 69.72201297915448
    - type: nauc_precision_at_10_diff1
      value: 1.3379158842989611
    - type: nauc_precision_at_10_max
      value: 12.076929332870746
    - type: nauc_precision_at_10_std
      value: 19.420680340269207
    - type: nauc_precision_at_1_diff1
      value: -10.071571494502948
    - type: nauc_precision_at_1_max
      value: 17.28112978017911
    - type: nauc_precision_at_1_std
      value: 21.458308992920365
    - type: nauc_precision_at_20_diff1
      value: 4.240200829917038
    - type: nauc_precision_at_20_max
      value: 8.993878588160804
    - type: nauc_precision_at_20_std
      value: 30.80491219798138
    - type: nauc_precision_at_3_diff1
      value: 12.886975175455992
    - type: nauc_precision_at_3_max
      value: 11.298461410464169
    - type: nauc_precision_at_3_std
      value: 10.518238245615933
    - type: nauc_precision_at_5_diff1
      value: 17.435560313660595
    - type: nauc_precision_at_5_max
      value: 2.2155983021008256
    - type: nauc_precision_at_5_std
      value: 11.998919133184952
    - type: nauc_recall_at_1000_diff1
      value: 20.776784820989995
    - type: nauc_recall_at_1000_max
      value: 7.82142405608866
    - type: nauc_recall_at_1000_std
      value: 61.814763636984914
    - type: nauc_recall_at_100_diff1
      value: 3.8928372388427777
    - type: nauc_recall_at_100_max
      value: 0.9218533326334627
    - type: nauc_recall_at_100_std
      value: 37.90057790091917
    - type: nauc_recall_at_10_diff1
      value: 1.620404946253575
    - type: nauc_recall_at_10_max
      value: 7.657179453157968
    - type: nauc_recall_at_10_std
      value: 1.4727974035045146
    - type: nauc_recall_at_1_diff1
      value: 2.5191045547339246
    - type: nauc_recall_at_1_max
      value: 26.262684180827723
    - type: nauc_recall_at_1_std
      value: 11.673938727339559
    - type: nauc_recall_at_20_diff1
      value: 1.7449368151648579
    - type: nauc_recall_at_20_max
      value: 1.7480936001393137
    - type: nauc_recall_at_20_std
      value: 4.712827220834413
    - type: nauc_recall_at_3_diff1
      value: 11.857687870032672
    - type: nauc_recall_at_3_max
      value: 7.014395082015944
    - type: nauc_recall_at_3_std
      value: -2.9526240248867732
    - type: nauc_recall_at_5_diff1
      value: 15.486663741149448
    - type: nauc_recall_at_5_max
      value: 2.6981538842605866
    - type: nauc_recall_at_5_std
      value: -2.279294596760028
    - type: ndcg_at_1
      value: 26.531
    - type: ndcg_at_10
      value: 24.7
    - type: ndcg_at_100
      value: 37.21
    - type: ndcg_at_1000
      value: 48.687999999999995
    - type: ndcg_at_20
      value: 25.365
    - type: ndcg_at_3
      value: 26.8
    - type: ndcg_at_5
      value: 24.618000000000002
    - type: precision_at_1
      value: 28.571
    - type: precision_at_10
      value: 22.041
    - type: precision_at_100
      value: 8.122
    - type: precision_at_1000
      value: 1.5879999999999999
    - type: precision_at_20
      value: 16.735
    - type: precision_at_3
      value: 27.211000000000002
    - type: precision_at_5
      value: 24.082
    - type: recall_at_1
      value: 1.8350000000000002
    - type: recall_at_10
      value: 16.039
    - type: recall_at_100
      value: 49.82
    - type: recall_at_1000
      value: 85.979
    - type: recall_at_20
      value: 24.169999999999998
    - type: recall_at_3
      value: 5.789
    - type: recall_at_5
      value: 8.725
  - task:
      type: Classification
    dataset:
      name: MTEB ToxicConversationsClassification (default)
      type: mteb/toxic_conversations_50k
      config: default
      split: test
      revision: edfaf9da55d3dd50d43143d90c1ac476895ae6de
    metrics:
    - type: accuracy
      value: 67.314453125
    - type: ap
      value: 13.15420979399679
    - type: ap_weighted
      value: 13.15420979399679
    - type: f1
      value: 52.03706668900905
    - type: f1_weighted
      value: 74.55554872499289
    - type: main_score
      value: 67.314453125
  - task:
      type: Classification
    dataset:
      name: MTEB TweetSentimentExtractionClassification (default)
      type: mteb/tweet_sentiment_extraction
      config: default
      split: test
      revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
    metrics:
    - type: accuracy
      value: 64.03225806451613
    - type: f1
      value: 64.06843534121843
    - type: f1_weighted
      value: 62.74796899202356
    - type: main_score
      value: 64.03225806451613
  - task:
      type: Clustering
    dataset:
      name: MTEB TwentyNewsgroupsClustering (default)
      type: mteb/twentynewsgroups-clustering
      config: default
      split: test
      revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
    metrics:
    - type: main_score
      value: 53.5182998227727
    - type: v_measure
      value: 53.5182998227727
    - type: v_measure_std
      value: 1.8758215247032688
  - task:
      type: PairClassification
    dataset:
      name: MTEB TwitterSemEval2015 (default)
      type: mteb/twittersemeval2015-pairclassification
      config: default
      split: test
      revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
    metrics:
    - type: cosine_accuracy
      value: 88.77630088812064
    - type: cosine_accuracy_threshold
      value: 78.23218107223511
    - type: cosine_ap
      value: 82.3910336126561
    - type: cosine_f1
      value: 74.85029940119759
    - type: cosine_f1_threshold
      value: 74.12334680557251
    - type: cosine_precision
      value: 70.9891150023663
    - type: cosine_recall
      value: 79.15567282321899
    - type: dot_accuracy
      value: 88.77630088812064
    - type: dot_accuracy_threshold
      value: 78.23217511177063
    - type: dot_ap
      value: 82.39102411942014
    - type: dot_f1
      value: 74.85029940119759
    - type: dot_f1_threshold
      value: 74.12335872650146
    - type: dot_precision
      value: 70.9891150023663
    - type: dot_recall
      value: 79.15567282321899
    - type: euclidean_accuracy
      value: 88.77630088812064
    - type: euclidean_accuracy_threshold
      value: 65.98154306411743
    - type: euclidean_ap
      value: 82.39103194961726
    - type: euclidean_f1
      value: 74.85029940119759
    - type: euclidean_f1_threshold
      value: 71.93976640701294
    - type: euclidean_precision
      value: 70.9891150023663
    - type: euclidean_recall
      value: 79.15567282321899
    - type: main_score
      value: 82.39103516928604
    - type: manhattan_accuracy
      value: 88.72265601716636
    - type: manhattan_accuracy_threshold
      value: 3392.3141479492188
    - type: manhattan_ap
      value: 82.37303670339044
    - type: manhattan_f1
      value: 74.91452450297581
    - type: manhattan_f1_threshold
      value: 3631.7977905273438
    - type: manhattan_precision
      value: 72.02337472607742
    - type: manhattan_recall
      value: 78.04749340369393
    - type: max_accuracy
      value: 88.77630088812064
    - type: max_ap
      value: 82.39103516928604
    - type: max_f1
      value: 74.91452450297581
    - type: max_precision
      value: 72.02337472607742
    - type: max_recall
      value: 79.15567282321899
    - type: similarity_accuracy
      value: 88.77630088812064
    - type: similarity_accuracy_threshold
      value: 1776.1724472045898
    - type: similarity_ap
      value: 82.39103516928604
    - type: similarity_f1
      value: 74.85029940119759
    - type: similarity_f1_threshold
      value: 1682.8865051269531
    - type: similarity_precision
      value: 70.9891150023663
    - type: similarity_recall
      value: 79.15567282321899
  - task:
      type: PairClassification
    dataset:
      name: MTEB TwitterURLCorpus (default)
      type: mteb/twitterurlcorpus-pairclassification
      config: default
      split: test
      revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
    metrics:
    - type: cosine_accuracy
      value: 89.86688399891334
    - type: cosine_accuracy_threshold
      value: 72.39344120025635
    - type: cosine_ap
      value: 87.60291936910795
    - type: cosine_f1
      value: 80.1902671057446
    - type: cosine_f1_threshold
      value: 69.8064923286438
    - type: cosine_precision
      value: 76.40496444010599
    - type: cosine_recall
      value: 84.3701878657222
    - type: dot_accuracy
      value: 89.86688399891334
    - type: dot_accuracy_threshold
      value: 72.39343523979187
    - type: dot_ap
      value: 87.60292256175723
    - type: dot_f1
      value: 80.1902671057446
    - type: dot_f1_threshold
      value: 69.80648040771484
    - type: dot_precision
      value: 76.40496444010599
    - type: dot_recall
      value: 84.3701878657222
    - type: euclidean_accuracy
      value: 89.86688399891334
    - type: euclidean_accuracy_threshold
      value: 74.30553436279297
    - type: euclidean_ap
      value: 87.60291559616975
    - type: euclidean_f1
      value: 80.1902671057446
    - type: euclidean_f1_threshold
      value: 77.70909070968628
    - type: euclidean_precision
      value: 76.40496444010599
    - type: euclidean_recall
      value: 84.3701878657222
    - type: main_score
      value: 87.60538403560003
    - type: manhattan_accuracy
      value: 89.88822913028291
    - type: manhattan_accuracy_threshold
      value: 3783.2366943359375
    - type: manhattan_ap
      value: 87.60538403560003
    - type: manhattan_f1
      value: 80.16710642040458
    - type: manhattan_f1_threshold
      value: 3948.430633544922
    - type: manhattan_precision
      value: 76.4895104895105
    - type: manhattan_recall
      value: 84.21619956883278
    - type: max_accuracy
      value: 89.88822913028291
    - type: max_ap
      value: 87.60538403560003
    - type: max_f1
      value: 80.1902671057446
    - type: max_precision
      value: 76.4895104895105
    - type: max_recall
      value: 84.3701878657222
    - type: similarity_accuracy
      value: 89.86688399891334
    - type: similarity_accuracy_threshold
      value: 1643.6103820800781
    - type: similarity_ap
      value: 87.6029128769812
    - type: similarity_f1
      value: 80.1902671057446
    - type: similarity_f1_threshold
      value: 1584.8767280578613
    - type: similarity_precision
      value: 76.40496444010599
    - type: similarity_recall
      value: 84.3701878657222
---




# BinGE: TODO

TODO: 2 line summary  and link to paper

## Usage
```python
import torch
from transformers import AutoTokenizer, AutoModel, AutoConfig
from peft import PeftModel


if __name__ == "__main__":
    # Loading base Meta-Llama-3 model, along with custom code that enables bidirectional connections in decoder-only LLMs.
    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",
    )

    # Loading MNTP (Masked Next Token Prediction) model.
    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 BinGSE model. This loads the trained LoRA weights on top of MNTP model. Hence the final weights are -- Base model + MNTP (LoRA) + BinGSE (LoRA).
    model = PeftModel.from_pretrained(
        model, model_path 
    )

```

TODO: initialize wrapper, provide example to check loading happened properly - see https://huggingface.co/McGill-NLP/LLM2Vec-Meta-Llama-3-8B-Instruct-mntp-unsup-simcse