model2vec safetensors embeddings static-embeddings sentence-transformers mteb en license:mit model-index region:us
---
base_model: baai/bge-base-en-v1.5
language:
- en
library_name: model2vec
license: mit
tags:
- embeddings
- static-embeddings
- sentence-transformers
- mteb
model-index:
- name: brown-beetle-base-v1.1
  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: 66.8815592203898
    - type: ap
      value: 18.195189738998792
    - type: ap_weighted
      value: 18.195189738998792
    - type: f1
      value: 55.16513139500548
    - type: f1_weighted
      value: 73.16351793408617
    - type: main_score
      value: 66.8815592203898
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonCounterfactualClassification (en)
      type: mteb/amazon_counterfactual
      config: en
      split: test
      revision: e8379541af4e31359cca9fbcf4b00f2671dba205
    metrics:
    - type: accuracy
      value: 70.19402985074626
    - type: ap
      value: 32.56202127210676
    - type: ap_weighted
      value: 32.56202127210676
    - type: f1
      value: 64.10866172582675
    - type: f1_weighted
      value: 73.08892104263525
    - type: main_score
      value: 70.19402985074626
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonPolarityClassification (default)
      type: mteb/amazon_polarity
      config: default
      split: test
      revision: e2d317d38cd51312af73b3d32a06d1a08b442046
    metrics:
    - type: accuracy
      value: 68.72295000000001
    - type: ap
      value: 63.50967718714144
    - type: ap_weighted
      value: 63.50967718714144
    - type: f1
      value: 68.34020808585744
    - type: f1_weighted
      value: 68.34020808585744
    - type: main_score
      value: 68.72295000000001
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonReviewsClassification (en)
      type: mteb/amazon_reviews_multi
      config: en
      split: test
      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
    metrics:
    - type: accuracy
      value: 31.691999999999997
    - type: f1
      value: 31.085241040043943
    - type: f1_weighted
      value: 31.085241040043943
    - type: main_score
      value: 31.691999999999997
  - 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_1
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    - type: map_at_10
      value: 32.775999999999996
    - type: map_at_100
      value: 34.026
    - type: map_at_1000
      value: 34.059
    - type: map_at_20
      value: 33.588
    - type: map_at_3
      value: 28.615000000000002
    - type: map_at_5
      value: 30.824
    - type: mrr_at_1
      value: 20.62588904694168
    - type: mrr_at_10
      value: 32.89335388019595
    - type: mrr_at_100
      value: 34.14268270653552
    - type: mrr_at_1000
      value: 34.175518754164436
    - type: mrr_at_20
      value: 33.7081572497899
    - type: mrr_at_3
      value: 28.73399715504974
    - type: mrr_at_5
      value: 30.938833570412427
    - type: nauc_map_at_1000_diff1
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    - type: ndcg_at_1
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    - type: ndcg_at_10
      value: 40.128
    - type: ndcg_at_100
      value: 46.113
    - type: ndcg_at_1000
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    - type: ndcg_at_20
      value: 43.044
    - type: ndcg_at_3
      value: 31.465
    - type: ndcg_at_5
      value: 35.447
    - type: precision_at_1
      value: 20.341
    - type: precision_at_10
      value: 6.38
    - type: precision_at_100
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    - type: precision_at_1000
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    - type: precision_at_20
      value: 3.762
    - type: precision_at_3
      value: 13.253
    - type: precision_at_5
      value: 9.886000000000001
    - type: recall_at_1
      value: 20.341
    - type: recall_at_10
      value: 63.798
    - type: recall_at_100
      value: 91.607
    - type: recall_at_1000
      value: 98.86200000000001
    - type: recall_at_20
      value: 75.249
    - type: recall_at_3
      value: 39.757999999999996
    - type: recall_at_5
      value: 49.431000000000004
  - task:
      type: Clustering
    dataset:
      name: MTEB ArxivClusteringP2P (default)
      type: mteb/arxiv-clustering-p2p
      config: default
      split: test
      revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
    metrics:
    - type: main_score
      value: 32.95868401684924
    - type: v_measure
      value: 32.95868401684924
    - type: v_measure_std
      value: 14.056211834923879
  - task:
      type: Clustering
    dataset:
      name: MTEB ArxivClusteringS2S (default)
      type: mteb/arxiv-clustering-s2s
      config: default
      split: test
      revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
    metrics:
    - type: main_score
      value: 21.233292246705687
    - type: v_measure
      value: 21.233292246705687
    - type: v_measure_std
      value: 15.425917066814412
  - task:
      type: Reranking
    dataset:
      name: MTEB AskUbuntuDupQuestions (default)
      type: mteb/askubuntudupquestions-reranking
      config: default
      split: test
      revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
    metrics:
    - type: main_score
      value: 53.563651922608045
    - type: map
      value: 53.563651922608045
    - type: mrr
      value: 68.38906476718111
    - type: nAUC_map_diff1
      value: 6.0692473614473474
    - type: nAUC_map_max
      value: 14.344767912076911
    - type: nAUC_map_std
      value: 4.756719465003369
    - type: nAUC_mrr_diff1
      value: 7.477185458141965
    - type: nAUC_mrr_max
      value: 18.522973771138822
    - type: nAUC_mrr_std
      value: 6.308062345018368
  - task:
      type: STS
    dataset:
      name: MTEB BIOSSES (default)
      type: mteb/biosses-sts
      config: default
      split: test
      revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
    metrics:
    - type: cosine_pearson
      value: 78.15156521309085
    - type: cosine_spearman
      value: 75.03966163682449
    - type: euclidean_pearson
      value: 51.743736432098494
    - type: euclidean_spearman
      value: 51.92286984480066
    - type: main_score
      value: 75.03966163682449
    - type: manhattan_pearson
      value: 49.81487823004435
    - type: manhattan_spearman
      value: 50.90236466418698
  - task:
      type: Classification
    dataset:
      name: MTEB Banking77Classification (default)
      type: mteb/banking77
      config: default
      split: test
      revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
    metrics:
    - type: accuracy
      value: 75.26948051948052
    - type: f1
      value: 75.30563948359976
    - type: f1_weighted
      value: 75.30563948359976
    - type: main_score
      value: 75.26948051948052
  - 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: 27.964590000454358
    - type: v_measure
      value: 27.964590000454358
    - type: v_measure_std
      value: 0.8174675360012013
  - task:
      type: Clustering
    dataset:
      name: MTEB BiorxivClusteringS2S (default)
      type: mteb/biorxiv-clustering-s2s
      config: default
      split: test
      revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
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      value: 15.33712655362372
    - type: v_measure
      value: 15.33712655362372
    - type: v_measure_std
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  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackAndroidRetrieval (default)
      type: mteb/cqadupstack-android
      config: default
      split: test
      revision: f46a197baaae43b4f621051089b82a364682dfeb
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      value: 30.791
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    - type: map_at_100
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    - type: map_at_1000
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    - type: map_at_3
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      type: CQADupstackRetrieval_is_a_combined_dataset
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  - task:
      type: Classification
    dataset:
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      type: mteb/imdb
      config: default
      split: test
      revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
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    - type: f1
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  - task:
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    dataset:
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      type: mteb/msmarco
      config: default
      split: test
      revision: c5a29a104738b98a9e76336939199e264163d4a0
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    - type: recall_at_1
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    - type: recall_at_10
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    - type: recall_at_100
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    - type: recall_at_1000
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  - task:
      type: Classification
    dataset:
      name: MTEB MTOPDomainClassification (en)
      type: mteb/mtop_domain
      config: en
      split: test
      revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
    metrics:
    - type: accuracy
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    - type: f1
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    - type: f1_weighted
      value: 86.42253471732333
    - type: main_score
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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
      value: 42.23245201423625
    - type: f1_weighted
      value: 64.52904706608977
    - type: main_score
      value: 60.40355677154583
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (en)
      type: mteb/amazon_massive_intent
      config: en
      split: test
      revision: 4672e20407010da34463acc759c162ca9734bca6
    metrics:
    - type: accuracy
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    - type: f1
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    - type: f1_weighted
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    - type: main_score
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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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      value: 66.39878950907867
    - type: f1
      value: 66.08148670134351
    - type: f1_weighted
      value: 66.75308329528572
    - type: main_score
      value: 66.39878950907867
  - task:
      type: Clustering
    dataset:
      name: MTEB MedrxivClusteringP2P (default)
      type: mteb/medrxiv-clustering-p2p
      config: default
      split: test
      revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
    metrics:
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      value: 25.58908806090526
    - type: v_measure
      value: 25.58908806090526
    - type: v_measure_std
      value: 1.1067644908239649
  - task:
      type: Clustering
    dataset:
      name: MTEB MedrxivClusteringS2S (default)
      type: mteb/medrxiv-clustering-s2s
      config: default
      split: test
      revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
    metrics:
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      value: 20.27612317880978
    - type: v_measure
      value: 20.27612317880978
    - type: v_measure_std
      value: 1.4731971616119242
  - task:
      type: Reranking
    dataset:
      name: MTEB MindSmallReranking (default)
      type: mteb/mind_small
      config: default
      split: test
      revision: 59042f120c80e8afa9cdbb224f67076cec0fc9a7
    metrics:
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      value: 28.939878341266613
    - type: map
      value: 28.939878341266613
    - type: mrr
      value: 29.639163441180692
    - type: nAUC_map_diff1
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      value: -22.869629909935735
    - type: nAUC_map_std
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    - type: nAUC_mrr_max
      value: -17.019803510539926
    - type: nAUC_mrr_std
      value: -6.648705434395337
  - task:
      type: Retrieval
    dataset:
      name: MTEB NFCorpus (default)
      type: mteb/nfcorpus
      config: default
      split: test
      revision: ec0fa4fe99da2ff19ca1214b7966684033a58814
    metrics:
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  - task:
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  - task:
      type: STS
    dataset:
      name: MTEB SICK-R (default)
      type: mteb/sickr-sts
      config: default
      split: test
      revision: 20a6d6f312dd54037fe07a32d58e5e168867909d
    metrics:
    - type: cosine_pearson
      value: 74.47186624461347
    - type: cosine_spearman
      value: 63.91365796295238
    - type: euclidean_pearson
      value: 64.47379282614025
    - type: euclidean_spearman
      value: 57.952313105909546
    - type: main_score
      value: 63.91365796295238
    - type: manhattan_pearson
      value: 63.78641984214034
    - type: manhattan_spearman
      value: 58.1628493915856
  - task:
      type: Reranking
    dataset:
      name: MTEB SciDocsRR (default)
      type: mteb/scidocs-reranking
      config: default
      split: test
      revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
    metrics:
    - type: main_score
      value: 70.68076882532134
    - type: map
      value: 70.68076882532134
    - type: mrr
      value: 89.99516188241678
    - type: nAUC_map_diff1
      value: 10.122594085098678
    - type: nAUC_map_max
      value: 54.78827936225146
    - type: nAUC_map_std
      value: 66.34579346833124
    - type: nAUC_mrr_diff1
      value: 49.215609105523825
    - type: nAUC_mrr_max
      value: 76.08848787865979
    - type: nAUC_mrr_std
      value: 72.73263647015558
  - task:
      type: Retrieval
    dataset:
      name: MTEB SciFact (default)
      type: mteb/scifact
      config: default
      split: test
      revision: 0228b52cf27578f30900b9e5271d331663a030d7
    metrics:
    - type: main_score
      value: 48.231
    - type: map_at_1
      value: 34.721999999999994
    - type: map_at_10
      value: 43.265
    - type: map_at_100
      value: 44.289
    - type: map_at_1000
      value: 44.345
    - type: map_at_20
      value: 43.855
    - type: map_at_3
      value: 40.176
    - type: map_at_5
      value: 42.095
    - type: mrr_at_1
      value: 36.666666666666664
    - type: mrr_at_10
      value: 44.615079365079346
    - type: mrr_at_100
      value: 45.52478310480785
    - type: mrr_at_1000
      value: 45.56825745517574
    - type: mrr_at_20
      value: 45.132147618177
    - type: mrr_at_3
      value: 41.833333333333314
    - type: mrr_at_5
      value: 43.583333333333314
    - type: nauc_map_at_1000_diff1
      value: 53.57155702970847
    - type: nauc_map_at_1000_max
      value: 37.553228317905734
    - type: nauc_map_at_1000_std
      value: -6.952334017204984
    - type: nauc_map_at_100_diff1
      value: 53.57075326773955
    - type: nauc_map_at_100_max
      value: 37.55176603615736
    - type: nauc_map_at_100_std
      value: -6.948451471419115
    - type: nauc_map_at_10_diff1
      value: 53.268386251103706
    - type: nauc_map_at_10_max
      value: 37.351400478599736
    - type: nauc_map_at_10_std
      value: -7.379738112714526
    - type: nauc_map_at_1_diff1
      value: 57.56838727422756
    - type: nauc_map_at_1_max
      value: 33.91693407903183
    - type: nauc_map_at_1_std
      value: -12.559053818648572
    - type: nauc_map_at_20_diff1
      value: 53.429671187841
    - type: nauc_map_at_20_max
      value: 37.55936524741779
    - type: nauc_map_at_20_std
      value: -6.880881015953415
    - type: nauc_map_at_3_diff1
      value: 54.458437868703605
    - type: nauc_map_at_3_max
      value: 36.81445939308554
    - type: nauc_map_at_3_std
      value: -8.231513775582439
    - type: nauc_map_at_5_diff1
      value: 53.33057094321079
    - type: nauc_map_at_5_max
      value: 37.195578868838275
    - type: nauc_map_at_5_std
      value: -7.749307309217592
    - type: nauc_mrr_at_1000_diff1
      value: 54.34857273810341
    - type: nauc_mrr_at_1000_max
      value: 38.826755160525714
    - type: nauc_mrr_at_1000_std
      value: -3.129730482959875
    - type: nauc_mrr_at_100_diff1
      value: 54.32917120301528
    - type: nauc_mrr_at_100_max
      value: 38.84753102337434
    - type: nauc_mrr_at_100_std
      value: -3.110529285852822
    - type: nauc_mrr_at_10_diff1
      value: 54.21030071588315
    - type: nauc_mrr_at_10_max
      value: 38.661275938475434
    - type: nauc_mrr_at_10_std
      value: -3.1549502405659173
    - type: nauc_mrr_at_1_diff1
      value: 59.470724157474834
    - type: nauc_mrr_at_1_max
      value: 35.60578977198414
    - type: nauc_mrr_at_1_std
      value: -7.093778610977887
    - type: nauc_mrr_at_20_diff1
      value: 54.2349834325068
    - type: nauc_mrr_at_20_max
      value: 38.85239854501404
    - type: nauc_mrr_at_20_std
      value: -2.997711648490797
    - type: nauc_mrr_at_3_diff1
      value: 55.470098003809824
    - type: nauc_mrr_at_3_max
      value: 38.84286486592964
    - type: nauc_mrr_at_3_std
      value: -3.830268753542997
    - type: nauc_mrr_at_5_diff1
      value: 54.201419630958156
    - type: nauc_mrr_at_5_max
      value: 38.67554185963586
    - type: nauc_mrr_at_5_std
      value: -3.0596087257425566
    - type: nauc_ndcg_at_1000_diff1
      value: 52.72751108752398
    - type: nauc_ndcg_at_1000_max
      value: 39.941645650054184
    - type: nauc_ndcg_at_1000_std
      value: -3.4493637196751
    - type: nauc_ndcg_at_100_diff1
      value: 52.30910994650125
    - type: nauc_ndcg_at_100_max
      value: 40.33184270901276
    - type: nauc_ndcg_at_100_std
      value: -2.901475443164014
    - type: nauc_ndcg_at_10_diff1
      value: 51.26542850640732
    - type: nauc_ndcg_at_10_max
      value: 39.175805828652656
    - type: nauc_ndcg_at_10_std
      value: -4.381732114321711
    - type: nauc_ndcg_at_1_diff1
      value: 59.470724157474834
    - type: nauc_ndcg_at_1_max
      value: 35.60578977198414
    - type: nauc_ndcg_at_1_std
      value: -7.093778610977887
    - type: nauc_ndcg_at_20_diff1
      value: 51.40324983657063
    - type: nauc_ndcg_at_20_max
      value: 39.97369516223508
    - type: nauc_ndcg_at_20_std
      value: -2.72975335651069
    - type: nauc_ndcg_at_3_diff1
      value: 53.71558494303497
    - type: nauc_ndcg_at_3_max
      value: 38.61655310566153
    - type: nauc_ndcg_at_3_std
      value: -5.262243707278389
    - type: nauc_ndcg_at_5_diff1
      value: 51.55385916859908
    - type: nauc_ndcg_at_5_max
      value: 38.97638742673797
    - type: nauc_ndcg_at_5_std
      value: -4.828131283920876
    - type: nauc_precision_at_1000_diff1
      value: 2.7393612079697673
    - type: nauc_precision_at_1000_max
      value: 29.35941187035881
    - type: nauc_precision_at_1000_std
      value: 45.03378524845005
    - type: nauc_precision_at_100_diff1
      value: 22.31747414714092
    - type: nauc_precision_at_100_max
      value: 42.31726670193232
    - type: nauc_precision_at_100_std
      value: 37.85148997521028
    - type: nauc_precision_at_10_diff1
      value: 34.91968585372156
    - type: nauc_precision_at_10_max
      value: 40.74286545360522
    - type: nauc_precision_at_10_std
      value: 14.679551404285561
    - type: nauc_precision_at_1_diff1
      value: 59.470724157474834
    - type: nauc_precision_at_1_max
      value: 35.60578977198414
    - type: nauc_precision_at_1_std
      value: -7.093778610977887
    - type: nauc_precision_at_20_diff1
      value: 31.7196752846707
    - type: nauc_precision_at_20_max
      value: 41.887774560054275
    - type: nauc_precision_at_20_std
      value: 26.111756052789254
    - type: nauc_precision_at_3_diff1
      value: 47.59338596894126
    - type: nauc_precision_at_3_max
      value: 41.60456773600893
    - type: nauc_precision_at_3_std
      value: 7.290322069735562
    - type: nauc_precision_at_5_diff1
      value: 39.59998573359068
    - type: nauc_precision_at_5_max
      value: 41.716169786122784
    - type: nauc_precision_at_5_std
      value: 10.030870924661512
    - type: nauc_recall_at_1000_diff1
      value: 57.971222677105146
    - type: nauc_recall_at_1000_max
      value: 74.35977239898826
    - type: nauc_recall_at_1000_std
      value: 25.046884850806233
    - type: nauc_recall_at_100_diff1
      value: 44.05189249844107
    - type: nauc_recall_at_100_max
      value: 56.07575711551889
    - type: nauc_recall_at_100_std
      value: 15.984701343858864
    - type: nauc_recall_at_10_diff1
      value: 42.17980666307712
    - type: nauc_recall_at_10_max
      value: 42.410562357398085
    - type: nauc_recall_at_10_std
      value: 0.5085324911166664
    - type: nauc_recall_at_1_diff1
      value: 57.56838727422756
    - type: nauc_recall_at_1_max
      value: 33.91693407903183
    - type: nauc_recall_at_1_std
      value: -12.559053818648572
    - type: nauc_recall_at_20_diff1
      value: 41.4295207526725
    - type: nauc_recall_at_20_max
      value: 47.09186640937312
    - type: nauc_recall_at_20_std
      value: 8.914121841807814
    - type: nauc_recall_at_3_diff1
      value: 49.71735118306758
    - type: nauc_recall_at_3_max
      value: 40.79913675597018
    - type: nauc_recall_at_3_std
      value: -2.6560764286787197
    - type: nauc_recall_at_5_diff1
      value: 44.40157202097473
    - type: nauc_recall_at_5_max
      value: 41.81658165643147
    - type: nauc_recall_at_5_std
      value: -0.9819402152656556
    - type: ndcg_at_1
      value: 36.667
    - type: ndcg_at_10
      value: 48.231
    - type: ndcg_at_100
      value: 53.077
    - type: ndcg_at_1000
      value: 54.529
    - type: ndcg_at_20
      value: 50.202000000000005
    - type: ndcg_at_3
      value: 42.296
    - type: ndcg_at_5
      value: 45.540000000000006
    - type: precision_at_1
      value: 36.667
    - type: precision_at_10
      value: 6.933
    - type: precision_at_100
      value: 0.95
    - type: precision_at_1000
      value: 0.109
    - type: precision_at_20
      value: 3.9170000000000003
    - type: precision_at_3
      value: 16.889000000000003
    - type: precision_at_5
      value: 11.933
    - type: recall_at_1
      value: 34.721999999999994
    - type: recall_at_10
      value: 62.428
    - type: recall_at_100
      value: 84.806
    - type: recall_at_1000
      value: 96.1
    - type: recall_at_20
      value: 69.828
    - type: recall_at_3
      value: 46.417
    - type: recall_at_5
      value: 54.289
  - task:
      type: PairClassification
    dataset:
      name: MTEB SprintDuplicateQuestions (default)
      type: mteb/sprintduplicatequestions-pairclassification
      config: default
      split: test
      revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
    metrics:
    - type: cosine_accuracy
      value: 99.69900990099009
    - type: cosine_accuracy_threshold
      value: 76.38404965400696
    - type: cosine_ap
      value: 89.62871668005243
    - type: cosine_f1
      value: 84.05797101449276
    - type: cosine_f1_threshold
      value: 75.10095834732056
    - type: cosine_precision
      value: 87.1244635193133
    - type: cosine_recall
      value: 81.2
    - type: dot_accuracy
      value: 99.06534653465346
    - type: dot_accuracy_threshold
      value: 67162.48779296875
    - type: dot_ap
      value: 32.76318972787881
    - type: dot_f1
      value: 36.930860033726816
    - type: dot_f1_threshold
      value: 39663.446044921875
    - type: dot_precision
      value: 31.924198250728864
    - type: dot_recall
      value: 43.8
    - type: euclidean_accuracy
      value: 99.44257425742575
    - type: euclidean_accuracy_threshold
      value: 1320.8951950073242
    - type: euclidean_ap
      value: 70.6030643455353
    - type: euclidean_f1
      value: 68.96551724137932
    - type: euclidean_f1_threshold
      value: 1433.2849502563477
    - type: euclidean_precision
      value: 73.44632768361582
    - type: euclidean_recall
      value: 65.0
    - type: main_score
      value: 89.62871668005243
    - type: manhattan_accuracy
      value: 99.43564356435644
    - type: manhattan_accuracy_threshold
      value: 23616.18194580078
    - type: manhattan_ap
      value: 69.53528871039842
    - type: manhattan_f1
      value: 67.80032912781131
    - type: manhattan_f1_threshold
      value: 24650.78887939453
    - type: manhattan_precision
      value: 75.09113001215067
    - type: manhattan_recall
      value: 61.8
    - type: max_accuracy
      value: 99.69900990099009
    - type: max_ap
      value: 89.62871668005243
    - type: max_f1
      value: 84.05797101449276
    - type: max_precision
      value: 87.1244635193133
    - type: max_recall
      value: 81.2
    - type: similarity_accuracy
      value: 99.69900990099009
    - type: similarity_accuracy_threshold
      value: 76.38405561447144
    - type: similarity_ap
      value: 89.62871668005243
    - type: similarity_f1
      value: 84.05797101449276
    - type: similarity_f1_threshold
      value: 75.10097026824951
    - type: similarity_precision
      value: 87.1244635193133
    - type: similarity_recall
      value: 81.2
  - task:
      type: Clustering
    dataset:
      name: MTEB StackExchangeClustering (default)
      type: mteb/stackexchange-clustering
      config: default
      split: test
      revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
    metrics:
    - type: main_score
      value: 39.45192779241171
    - type: v_measure
      value: 39.45192779241171
    - type: v_measure_std
      value: 4.925771037453908
---
# 🪲 brown-beetle-base-v1.1 Model Card

<div align="center">
  <img width="75%" alt="Beetle logo" src="./assets/beetle_logo.png">
</div>

> [!TIP]
> Beetles are some of the most diverse and interesting creatures on Earth. They are found in every environment, from the deepest oceans to the highest mountains. They are also known for their ability to adapt to a wide range of habitats and lifestyles. They are small, fast and powerful!

The beetle series of models are made as good starting points for Static Embedding training (via TokenLearn or Fine-tuning), as well as decent Static Embedding models. Each beetle model is made to be an improvement over the original **M2V_base_output** model in some way, and that's the threshold we set for each model (except the brown beetle series, which is the original model).

This model has been distilled from `baai/bge-base-en-v1.5`, with PCA with 768 dimensions, applying Zipf and applying SIF re-weighting, learnt from a subset of the C4 corpus. This model is significantly better than the M2V_base_output model.

> [!NOTE]
> The brown beetle series is made for convinience in loading and using the model instead of having to run it, though it is pretty fast to reproduce anyways. If you want to use the original model by the folks from the Minish Lab, you can use the **M2V_base_output** model.

## Version Information

- **brown-beetle-base-v0**: The original model, without using PCA or Zipf. The lack of PCA and Zipf also makes this a decent model for further training.
- **brown-beetle-base-v0.1**: The original model, with PCA but of the same size as the original model. This model is great if you want to experiment with Zipf or other weighting methods.
- **brown-beetle-base-v1**: The original model, with PCA and Zipf.
- **brown-beetle-small-v1**: A smaller version of the original model, with PCA and Zipf. Equivalent to **M2V_base_output**.
- **brown-beetle-tiny-v1**: A tiny version of the original model, with PCA and Zipf.
- **brown-beetle-base-v1.1**: The original model, with PCA with 768 dimensions, applying Zipf and applying SIF re-weighting, learnt from a subset of the C4 corpus. This model is significantly better than the M2V_base_output model.
- **brown-beetle-small-v1.1**: A smaller version of the original model, with PCA with 256 dimensions, applying Zipf and applying SIF re-weighting, learnt from a subset of the C4 corpus. This model is significantly better than the M2V_base_output model but slightly worse than the brown-beetle-base-v1.1 model.
- **brown-beetle-tiny-v1.1**: A tiny version of the original model, with PCA with 128 dimensions, applying Zipf and applying SIF re-weighting, learnt from a subset of the C4 corpus. This model is significantly better than the M2V_base_output model but slightly worse than the brown-beetle-small-v1.1 model.

## Installation

Install model2vec using pip:

```bash
pip install model2vec
```

## Usage

Load this model using the `from_pretrained` method:

```python
from model2vec import StaticModel

# Load a pretrained Model2Vec model
model = StaticModel.from_pretrained("bhavnicksm/brown-beetle-base-v1.1")

# Compute text embeddings
embeddings = model.encode(["Example sentence"])
```

Read more about the Model2Vec library [here](https://github.com/MinishLab/model2vec).

## Comparison with other models

Coming soon...

## Acknowledgements

This model is made using the [Model2Vec](https://github.com/MinishLab/model2vec) library. Credit goes to the [Minish Lab](https://github.com/MinishLab) team for developing this library.

## Citation

Please cite the [Model2Vec repository](https://github.com/MinishLab/model2vec) if you use this model in your work.

```bibtex
@software{minishlab2024model2vec,
  authors = {Stephan Tulkens, Thomas van Dongen},
  title = {Model2Vec: Turn any Sentence Transformer into a Small Fast Model},
  year = {2024},
  url = {https://github.com/MinishLab/model2vec},
}
```
