README.md

---
base_model: baai/bge-base-en-v1.5
language:
- en
library_name: model2vec
license: mit
model_name: brown-beetle-tiny-v1
tags:
- embeddings
- static-embeddings
- sentence-transformers
- mteb
model-index:
- name: brown-beetle-tiny-v1
  results:
  - dataset:
      config: en-ext
      name: MTEB AmazonCounterfactualClassification (en-ext)
      revision: e8379541af4e31359cca9fbcf4b00f2671dba205
      split: test
      type: mteb/amazon_counterfactual
    metrics:
    - type: accuracy
      value: 64.09295352323838
    - type: ap
      value: 16.57841154272169
    - type: ap_weighted
      value: 16.57841154272169
    - type: f1
      value: 52.8558683644378
    - type: f1_weighted
      value: 70.99795716291565
    - type: main_score
      value: 64.09295352323838
    task:
      type: Classification
  - dataset:
      config: en
      name: MTEB AmazonCounterfactualClassification (en)
      revision: e8379541af4e31359cca9fbcf4b00f2671dba205
      split: test
      type: mteb/amazon_counterfactual
    metrics:
    - type: accuracy
      value: 66.55223880597015
    - type: ap
      value: 29.489029255823183
    - type: ap_weighted
      value: 29.489029255823183
    - type: f1
      value: 60.63546188197216
    - type: f1_weighted
      value: 69.88550022841326
    - type: main_score
      value: 66.55223880597015
    task:
      type: Classification
  - dataset:
      config: default
      name: MTEB AmazonPolarityClassification (default)
      revision: e2d317d38cd51312af73b3d32a06d1a08b442046
      split: test
      type: mteb/amazon_polarity
    metrics:
    - type: accuracy
      value: 66.96194999999999
    - type: ap
      value: 61.92605604727599
    - type: ap_weighted
      value: 61.92605604727599
    - type: f1
      value: 66.59212154571806
    - type: f1_weighted
      value: 66.59212154571806
    - type: main_score
      value: 66.96194999999999
    task:
      type: Classification
  - dataset:
      config: en
      name: MTEB AmazonReviewsClassification (en)
      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
      split: test
      type: mteb/amazon_reviews_multi
    metrics:
    - type: accuracy
      value: 31.406
    - type: f1
      value: 31.105909676226467
    - type: f1_weighted
      value: 31.105909676226467
    - type: main_score
      value: 31.406
    task:
      type: Classification
  - dataset:
      config: default
      name: MTEB ArguAna (default)
      revision: c22ab2a51041ffd869aaddef7af8d8215647e41a
      split: test
      type: mteb/arguana
    metrics:
    - type: main_score
      value: 28.839
    - type: map_at_1
      value: 14.438
    - type: map_at_10
      value: 23.541
    - type: map_at_100
      value: 24.589
    - type: map_at_1000
      value: 24.672
    - type: map_at_20
      value: 24.093999999999998
    - type: map_at_3
      value: 20.578
    - type: map_at_5
      value: 22.197
    - type: mrr_at_1
      value: 14.864864864864865
    - type: mrr_at_10
      value: 23.69953600216757
    - type: mrr_at_100
      value: 24.754046628510885
    - type: mrr_at_1000
      value: 24.837834580004223
    - type: mrr_at_20
      value: 24.2590837465165
    - type: mrr_at_3
      value: 20.70886676149834
    - type: mrr_at_5
      value: 22.38738738738736
    - type: nauc_map_at_1000_diff1
      value: 11.710523444120719
    - type: nauc_map_at_1000_max
      value: -1.41407564949768
    - type: nauc_map_at_1000_std
      value: 14.46184437776828
    - type: nauc_map_at_100_diff1
      value: 11.695316106812099
    - type: nauc_map_at_100_max
      value: -1.4188305060204984
    - type: nauc_map_at_100_std
      value: 14.490744157955113
    - type: nauc_map_at_10_diff1
      value: 11.567234339158974
    - type: nauc_map_at_10_max
      value: -1.5892321978000112
    - type: nauc_map_at_10_std
      value: 13.73387241027869
    - type: nauc_map_at_1_diff1
      value: 12.88166978338844
    - type: nauc_map_at_1_max
      value: -5.632696878755496
    - type: nauc_map_at_1_std
      value: 11.116501462763512
    - type: nauc_map_at_20_diff1
      value: 11.592369512079118
    - type: nauc_map_at_20_max
      value: -1.3187282261869946
    - type: nauc_map_at_20_std
      value: 14.304147251709228
    - type: nauc_map_at_3_diff1
      value: 11.256151680396243
    - type: nauc_map_at_3_max
      value: -3.1045816700611084
    - type: nauc_map_at_3_std
      value: 11.98559615155674
    - type: nauc_map_at_5_diff1
      value: 11.417135586493323
    - type: nauc_map_at_5_max
      value: -2.827886538484471
    - type: nauc_map_at_5_std
      value: 12.986381975293579
    - type: nauc_mrr_at_1000_diff1
      value: 10.177159281558183
    - type: nauc_mrr_at_1000_max
      value: -1.692409833784558
    - type: nauc_mrr_at_1000_std
      value: 14.152763593329503
    - type: nauc_mrr_at_100_diff1
      value: 10.165711735180038
    - type: nauc_mrr_at_100_max
      value: -1.6964159506726972
    - type: nauc_mrr_at_100_std
      value: 14.182158646102106
    - type: nauc_mrr_at_10_diff1
      value: 10.019035606371064
    - type: nauc_mrr_at_10_max
      value: -1.900984327744186
    - type: nauc_mrr_at_10_std
      value: 13.42201050782521
    - type: nauc_mrr_at_1_diff1
      value: 10.751693263895094
    - type: nauc_mrr_at_1_max
      value: -4.600140598095711
    - type: nauc_mrr_at_1_std
      value: 10.51221661375943
    - type: nauc_mrr_at_20_diff1
      value: 10.076653687342342
    - type: nauc_mrr_at_20_max
      value: -1.5943080739675486
    - type: nauc_mrr_at_20_std
      value: 13.99966842624823
    - type: nauc_mrr_at_3_diff1
      value: 9.452553914393372
    - type: nauc_mrr_at_3_max
      value: -3.7000477765906856
    - type: nauc_mrr_at_3_std
      value: 11.783286035754102
    - type: nauc_mrr_at_5_diff1
      value: 9.948977775457102
    - type: nauc_mrr_at_5_max
      value: -2.9364908406397463
    - type: nauc_mrr_at_5_std
      value: 12.627802226242318
    - type: nauc_ndcg_at_1000_diff1
      value: 12.191441277161175
    - type: nauc_ndcg_at_1000_max
      value: 0.8222149831662116
    - type: nauc_ndcg_at_1000_std
      value: 17.691386726273176
    - type: nauc_ndcg_at_100_diff1
      value: 12.026922096707512
    - type: nauc_ndcg_at_100_max
      value: 0.9649095671797968
    - type: nauc_ndcg_at_100_std
      value: 18.79566154822669
    - type: nauc_ndcg_at_10_diff1
      value: 11.668212582460665
    - type: nauc_ndcg_at_10_max
      value: 0.9423653801824595
    - type: nauc_ndcg_at_10_std
      value: 15.538609047969858
    - type: nauc_ndcg_at_1_diff1
      value: 12.88166978338844
    - type: nauc_ndcg_at_1_max
      value: -5.632696878755496
    - type: nauc_ndcg_at_1_std
      value: 11.116501462763512
    - type: nauc_ndcg_at_20_diff1
      value: 11.692620670468228
    - type: nauc_ndcg_at_20_max
      value: 1.8201755765222798
    - type: nauc_ndcg_at_20_std
      value: 17.560542858395902
    - type: nauc_ndcg_at_3_diff1
      value: 11.023407454967298
    - type: nauc_ndcg_at_3_max
      value: -2.2256962581095268
    - type: nauc_ndcg_at_3_std
      value: 12.147790886487178
    - type: nauc_ndcg_at_5_diff1
      value: 11.23700232185496
    - type: nauc_ndcg_at_5_max
      value: -1.8374455211691147
    - type: nauc_ndcg_at_5_std
      value: 13.822082848830622
    - type: nauc_precision_at_1000_diff1
      value: 19.5190660354492
    - type: nauc_precision_at_1000_max
      value: 18.114410701992146
    - type: nauc_precision_at_1000_std
      value: 49.7944310686017
    - type: nauc_precision_at_100_diff1
      value: 13.493960597733729
    - type: nauc_precision_at_100_max
      value: 8.568691284955749
    - type: nauc_precision_at_100_std
      value: 39.0964671762103
    - type: nauc_precision_at_10_diff1
      value: 12.149349128166126
    - type: nauc_precision_at_10_max
      value: 7.695226757131975
    - type: nauc_precision_at_10_std
      value: 20.424722092975394
    - type: nauc_precision_at_1_diff1
      value: 12.88166978338844
    - type: nauc_precision_at_1_max
      value: -5.632696878755496
    - type: nauc_precision_at_1_std
      value: 11.116501462763512
    - type: nauc_precision_at_20_diff1
      value: 12.152076579176686
    - type: nauc_precision_at_20_max
      value: 10.951422872400038
    - type: nauc_precision_at_20_std
      value: 27.762016972799575
    - type: nauc_precision_at_3_diff1
      value: 10.520705211562325
    - type: nauc_precision_at_3_max
      value: -0.08840953178400665
    - type: nauc_precision_at_3_std
      value: 12.515570437615686
    - type: nauc_precision_at_5_diff1
      value: 10.858147634309764
    - type: nauc_precision_at_5_max
      value: 0.4927084766401162
    - type: nauc_precision_at_5_std
      value: 15.900545493843174
    - type: nauc_recall_at_1000_diff1
      value: 19.51906603544921
    - type: nauc_recall_at_1000_max
      value: 18.114410701992174
    - type: nauc_recall_at_1000_std
      value: 49.79443106860158
    - type: nauc_recall_at_100_diff1
      value: 13.493960597733695
    - type: nauc_recall_at_100_max
      value: 8.568691284955717
    - type: nauc_recall_at_100_std
      value: 39.09646717621017
    - type: nauc_recall_at_10_diff1
      value: 12.14934912816615
    - type: nauc_recall_at_10_max
      value: 7.6952267571319855
    - type: nauc_recall_at_10_std
      value: 20.42472209297543
    - type: nauc_recall_at_1_diff1
      value: 12.88166978338844
    - type: nauc_recall_at_1_max
      value: -5.632696878755496
    - type: nauc_recall_at_1_std
      value: 11.116501462763512
    - type: nauc_recall_at_20_diff1
      value: 12.152076579176654
    - type: nauc_recall_at_20_max
      value: 10.951422872400016
    - type: nauc_recall_at_20_std
      value: 27.76201697279958
    - type: nauc_recall_at_3_diff1
      value: 10.52070521156232
    - type: nauc_recall_at_3_max
      value: -0.08840953178398737
    - type: nauc_recall_at_3_std
      value: 12.515570437615686
    - type: nauc_recall_at_5_diff1
      value: 10.85814763430975
    - type: nauc_recall_at_5_max
      value: 0.49270847664009765
    - type: nauc_recall_at_5_std
      value: 15.900545493843135
    - type: ndcg_at_1
      value: 14.438
    - type: ndcg_at_10
      value: 28.839
    - type: ndcg_at_100
      value: 34.428
    - type: ndcg_at_1000
      value: 36.846000000000004
    - type: ndcg_at_20
      value: 30.842000000000002
    - type: ndcg_at_3
      value: 22.683
    - type: ndcg_at_5
      value: 25.591
    - type: precision_at_1
      value: 14.438
    - type: precision_at_10
      value: 4.587
    - type: precision_at_100
      value: 0.731
    - type: precision_at_1000
      value: 0.093
    - type: precision_at_20
      value: 2.688
    - type: precision_at_3
      value: 9.602
    - type: precision_at_5
      value: 7.1690000000000005
    - type: recall_at_1
      value: 14.438
    - type: recall_at_10
      value: 45.875
    - type: recall_at_100
      value: 73.115
    - type: recall_at_1000
      value: 92.60300000000001
    - type: recall_at_20
      value: 53.769999999999996
    - type: recall_at_3
      value: 28.804999999999996
    - type: recall_at_5
      value: 35.846000000000004
    task:
      type: Retrieval
  - dataset:
      config: default
      name: MTEB ArxivClusteringP2P (default)
      revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
      split: test
      type: mteb/arxiv-clustering-p2p
    metrics:
    - type: main_score
      value: 30.721708670938618
    - type: v_measure
      value: 30.721708670938618
    - type: v_measure_std
      value: 14.59075919640026
    task:
      type: Clustering
  - dataset:
      config: default
      name: MTEB ArxivClusteringP2P (default)
      revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
      split: test
      type: mteb/arxiv-clustering-p2p
    metrics:
    - type: main_score
      value: 30.721628572270227
    - type: v_measure
      value: 30.721628572270227
    - type: v_measure_std
      value: 14.590724884146741
    task:
      type: Clustering
  - dataset:
      config: default
      name: MTEB ArxivClusteringS2S (default)
      revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
      split: test
      type: mteb/arxiv-clustering-s2s
    metrics:
    - type: main_score
      value: 20.81189338758185
    - type: v_measure
      value: 20.81189338758185
    - type: v_measure_std
      value: 15.630749849934816
    task:
      type: Clustering
  - dataset:
      config: default
      name: MTEB ArxivClusteringS2S (default)
      revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
      split: test
      type: mteb/arxiv-clustering-s2s
    metrics:
    - type: main_score
      value: 20.81189338758186
    - type: v_measure
      value: 20.81189338758186
    - type: v_measure_std
      value: 15.630749849934816
    task:
      type: Clustering
  - dataset:
      config: default
      name: MTEB AskUbuntuDupQuestions (default)
      revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
      split: test
      type: mteb/askubuntudupquestions-reranking
    metrics:
    - type: main_score
      value: 51.269563672134986
    - type: map
      value: 51.269563672134986
    - type: mrr
      value: 64.9430594028932
    - type: nAUC_map_diff1
      value: 13.234765254548417
    - type: nAUC_map_max
      value: 14.005654835382275
    - type: nAUC_map_std
      value: 4.940982887482917
    - type: nAUC_mrr_diff1
      value: 20.319406020706065
    - type: nAUC_mrr_max
      value: 20.987604228375332
    - type: nAUC_mrr_std
      value: 9.22453984185132
    task:
      type: Reranking
  - dataset:
      config: default
      name: MTEB AskUbuntuDupQuestions (default)
      revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
      split: test
      type: mteb/askubuntudupquestions-reranking
    metrics:
    - type: main_score
      value: 51.269563672134986
    - type: map
      value: 51.269563672134986
    - type: mrr
      value: 64.9430594028932
    - type: nAUC_map_diff1
      value: 13.234765254548417
    - type: nAUC_map_max
      value: 14.005654835382275
    - type: nAUC_map_std
      value: 4.940982887482917
    - type: nAUC_mrr_diff1
      value: 20.319406020706065
    - type: nAUC_mrr_max
      value: 20.987604228375332
    - type: nAUC_mrr_std
      value: 9.22453984185132
    task:
      type: Reranking
  - dataset:
      config: default
      name: MTEB BIOSSES (default)
      revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
      split: test
      type: mteb/biosses-sts
    metrics:
    - type: cosine_pearson
      value: 72.65277568567002
    - type: cosine_spearman
      value: 71.5739200169482
    - type: euclidean_pearson
      value: 54.35299652840819
    - type: euclidean_spearman
      value: 55.29644068980453
    - type: main_score
      value: 71.5739200169482
    - type: manhattan_pearson
      value: 52.58607516245499
    - type: manhattan_spearman
      value: 54.298827597067664
    task:
      type: STS
  - dataset:
      config: default
      name: MTEB Banking77Classification (default)
      revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
      split: test
      type: mteb/banking77
    metrics:
    - type: accuracy
      value: 70.06168831168831
    - type: f1
      value: 70.19892920542246
    - type: f1_weighted
      value: 70.19892920542246
    - type: main_score
      value: 70.06168831168831
    task:
      type: Classification
  - dataset:
      config: default
      name: MTEB BiorxivClusteringP2P (default)
      revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
      split: test
      type: mteb/biorxiv-clustering-p2p
    metrics:
    - type: main_score
      value: 24.8818318188809
    - type: v_measure
      value: 24.8818318188809
    - type: v_measure_std
      value: 0.7960068034300037
    task:
      type: Clustering
  - dataset:
      config: default
      name: MTEB BiorxivClusteringP2P (default)
      revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
      split: test
      type: mteb/biorxiv-clustering-p2p
    metrics:
    - type: main_score
      value: 24.880938025057198
    - type: v_measure
      value: 24.880938025057198
    - type: v_measure_std
      value: 0.7956500964619948
    task:
      type: Clustering
  - dataset:
      config: default
      name: MTEB BiorxivClusteringS2S (default)
      revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
      split: test
      type: mteb/biorxiv-clustering-s2s
    metrics:
    - type: main_score
      value: 13.286390001618445
    - type: v_measure
      value: 13.286390001618445
    - type: v_measure_std
      value: 0.9260829767505151
    task:
      type: Clustering
  - dataset:
      config: default
      name: MTEB BiorxivClusteringS2S (default)
      revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
      split: test
      type: mteb/biorxiv-clustering-s2s
    metrics:
    - type: main_score
      value: 13.286390001618448
    - type: v_measure
      value: 13.286390001618448
    - type: v_measure_std
      value: 0.9260829767505148
    task:
      type: Clustering
  - dataset:
      config: default
      name: MTEB CQADupstackAndroidRetrieval (default)
      revision: f46a197baaae43b4f621051089b82a364682dfeb
      split: test
      type: mteb/cqadupstack-android
    metrics:
    - type: main_score
      value: 25.598
    - type: map_at_1
      value: 15.296000000000001
    - type: map_at_10
      value: 21.340999999999998
    - type: map_at_100
      value: 22.299
    - type: map_at_1000
      value: 22.439999999999998
    - type: map_at_20
      value: 21.823
    - type: map_at_3
      value: 19.186
    - type: map_at_5
      value: 20.307
    - type: mrr_at_1
      value: 20.171673819742487
    - type: mrr_at_10
      value: 25.96248609124146
    - type: mrr_at_100
      value: 26.832705786570926
    - type: mrr_at_1000
      value: 26.912543796379445
    - type: mrr_at_20
      value: 26.420649989525486
    - type: mrr_at_3
      value: 23.962804005722468
    - type: mrr_at_5
      value: 25.21459227467812
    - type: nauc_map_at_1000_diff1
      value: 43.81837614044429
    - type: nauc_map_at_1000_max
      value: 29.960220786660646
    - type: nauc_map_at_1000_std
      value: -7.210785807307356
    - type: nauc_map_at_100_diff1
      value: 43.80996491314085
    - type: nauc_map_at_100_max
      value: 29.944713236108733
    - type: nauc_map_at_100_std
      value: -7.255860646858293
    - type: nauc_map_at_10_diff1
      value: 44.01155643098911
    - type: nauc_map_at_10_max
      value: 29.53988039453277
    - type: nauc_map_at_10_std
      value: -7.875507294985671
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    task:
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  - dataset:
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      value: 17.376830266168604
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      value: 16.789615060931666
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      value: 22.79838602202508
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      value: 52.61551537882851
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      value: 16.475684506165464
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      value: 20.875016888477276
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      value: 15.853720513435379
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      value: 21.55356806393905
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      value: 54.03582339434189
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      value: 15.630511672058015
    - type: nauc_mrr_at_1000_std
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      value: 54.02754971342381
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    - type: nauc_mrr_at_10_max
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    - type: nauc_mrr_at_10_std
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    - type: nauc_mrr_at_1_max
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    - type: nauc_mrr_at_1_std
      value: 16.789615060931666
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      value: 54.06024190116767
    - type: nauc_mrr_at_20_max
      value: 15.672485911580274
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      value: 20.207777657353407
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      value: 16.413632034794368
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      value: 19.190556168944575
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      value: 54.54379676882809
    - type: nauc_mrr_at_5_max
      value: 16.026704417546643
    - type: nauc_mrr_at_5_std
      value: 19.622058814048323
    - type: nauc_ndcg_at_1000_diff1
      value: 48.04971818800837
    - type: nauc_ndcg_at_1000_max
      value: 13.872391570548034
    - type: nauc_ndcg_at_1000_std
      value: 28.204630600696422
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      value: 48.20862670553361
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      value: 13.934707982568707
    - type: nauc_ndcg_at_100_std
      value: 26.816340379977575
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      value: 49.58986553019014
    - type: nauc_ndcg_at_10_max
      value: 14.435063686783565
    - type: nauc_ndcg_at_10_std
      value: 23.268818709527373
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      value: 58.582494559051824
    - type: nauc_ndcg_at_1_max
      value: 17.376830266168604
    - type: nauc_ndcg_at_1_std
      value: 16.789615060931666
    - type: nauc_ndcg_at_20_diff1
      value: 49.07240942409174
    - type: nauc_ndcg_at_20_max
      value: 14.218315852005206
    - type: nauc_ndcg_at_20_std
      value: 24.67103602187103
    - type: nauc_ndcg_at_3_diff1
      value: 52.19624218218015
    - type: nauc_ndcg_at_3_max
      value: 16.143530056387124
    - type: nauc_ndcg_at_3_std
      value: 21.04539485406127
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      value: 51.00405155041411
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      value: 15.262041451084723
    - type: nauc_ndcg_at_5_std
      value: 22.03099708198355
    - type: nauc_precision_at_1000_diff1
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    - type: nauc_precision_at_1000_std
      value: 42.03315489434521
    - type: nauc_precision_at_100_diff1
      value: 30.486222482179166
    - type: nauc_precision_at_100_max
      value: 7.764047081555857
    - type: nauc_precision_at_100_std
      value: 36.7950294397598
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      value: 40.114486285703556
    - type: nauc_precision_at_10_max
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      value: 30.591489232109346
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      value: 44.8979436826324
    - type: nauc_precision_at_5_max
      value: 13.167095157767733
    - type: nauc_precision_at_5_std
      value: 25.063209597419
    - type: nauc_recall_at_1000_diff1
      value: 22.789458502365484
    - type: nauc_recall_at_1000_max
      value: 5.41500915785354
    - type: nauc_recall_at_1000_std
      value: 42.03315489434527
    - type: nauc_recall_at_100_diff1
      value: 30.486222482179144
    - type: nauc_recall_at_100_max
      value: 7.764047081555842
    - type: nauc_recall_at_100_std
      value: 36.795029439759816
    - type: nauc_recall_at_10_diff1
      value: 40.11448628570359
    - type: nauc_recall_at_10_max
      value: 10.703204693529694
    - type: nauc_recall_at_10_std
      value: 27.373045794891134
    - type: nauc_recall_at_1_diff1
      value: 58.582494559051824
    - type: nauc_recall_at_1_max
      value: 17.376830266168604
    - type: nauc_recall_at_1_std
      value: 16.789615060931666
    - type: nauc_recall_at_20_diff1
      value: 36.87434281232932
    - type: nauc_recall_at_20_max
      value: 9.66762724345254
    - type: nauc_recall_at_20_std
      value: 30.591489232109335
    - type: nauc_recall_at_3_diff1
      value: 48.0620077044296
    - type: nauc_recall_at_3_max
      value: 15.263758097688923
    - type: nauc_recall_at_3_std
      value: 23.4198011501745
    - type: nauc_recall_at_5_diff1
      value: 44.897943682632445
    - type: nauc_recall_at_5_max
      value: 13.167095157767752
    - type: nauc_recall_at_5_std
      value: 25.06320959741904
    - type: ndcg_at_1
      value: 29.250999999999998
    - type: ndcg_at_10
      value: 25.745
    - type: ndcg_at_100
      value: 29.215000000000003
    - type: ndcg_at_1000
      value: 31.615
    - type: ndcg_at_20
      value: 27.006999999999998
    - type: ndcg_at_3
      value: 22.642
    - type: ndcg_at_5
      value: 24.221999999999998
    - type: precision_at_1
      value: 29.250999999999998
    - type: precision_at_10
      value: 5.638
    - type: precision_at_100
      value: 0.843
    - type: precision_at_1000
      value: 0.116
    - type: precision_at_20
      value: 3.2259999999999995
    - type: precision_at_3
      value: 14.148
    - type: precision_at_5
      value: 9.742
    - type: recall_at_1
      value: 14.625
    - type: recall_at_10
      value: 28.189999999999998
    - type: recall_at_100
      value: 42.126999999999995
    - type: recall_at_1000
      value: 58.238
    - type: recall_at_20
      value: 32.255
    - type: recall_at_3
      value: 21.221999999999998
    - type: recall_at_5
      value: 24.355
    task:
      type: Retrieval
  - dataset:
      config: default
      name: MTEB ImdbClassification (default)
      revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
      split: test
      type: mteb/imdb
    metrics:
    - type: accuracy
      value: 65.9264
    - type: ap
      value: 60.756531398956945
    - type: ap_weighted
      value: 60.756531398956945
    - type: f1
      value: 65.51017691516725
    - type: f1_weighted
      value: 65.51017691516724
    - type: main_score
      value: 65.9264
    task:
      type: Classification
  - dataset:
      config: en
      name: MTEB MTOPDomainClassification (en)
      revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
      split: test
      type: mteb/mtop_domain
    metrics:
    - type: accuracy
      value: 80.67259461924306
    - type: f1
      value: 79.9597409844225
    - type: f1_weighted
      value: 80.8035256676638
    - type: main_score
      value: 80.67259461924306
    task:
      type: Classification
  - dataset:
      config: en
      name: MTEB MTOPIntentClassification (en)
      revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
      split: test
      type: mteb/mtop_intent
    metrics:
    - type: accuracy
      value: 56.54354765161879
    - type: f1
      value: 40.667405344171634
    - type: f1_weighted
      value: 60.9216341010469
    - type: main_score
      value: 56.54354765161879
    task:
      type: Classification
  - dataset:
      config: en
      name: MTEB MassiveIntentClassification (en)
      revision: 4672e20407010da34463acc759c162ca9734bca6
      split: test
      type: mteb/amazon_massive_intent
    metrics:
    - type: accuracy
      value: 59.0719569603228
    - type: f1
      value: 58.168886864690336
    - type: f1_weighted
      value: 59.57900662649745
    - type: main_score
      value: 59.0719569603228
    task:
      type: Classification
  - dataset:
      config: en
      name: MTEB MassiveScenarioClassification (en)
      revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
      split: test
      type: mteb/amazon_massive_scenario
    metrics:
    - type: accuracy
      value: 62.59246805648958
    - type: f1
      value: 62.08069974222518
    - type: f1_weighted
      value: 62.794653215101604
    - type: main_score
      value: 62.59246805648958
    task:
      type: Classification
  - dataset:
      config: default
      name: MTEB MedrxivClusteringP2P (default)
      revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
      split: test
      type: mteb/medrxiv-clustering-p2p
    metrics:
    - type: main_score
      value: 24.526232087760377
    - type: v_measure
      value: 24.526232087760377
    - type: v_measure_std
      value: 1.3231622419863613
    task:
      type: Clustering
  - dataset:
      config: default
      name: MTEB MedrxivClusteringS2S (default)
      revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
      split: test
      type: mteb/medrxiv-clustering-s2s
    metrics:
    - type: main_score
      value: 20.194412620609075
    - type: v_measure
      value: 20.194412620609075
    - type: v_measure_std
      value: 1.636243479295598
    task:
      type: Clustering
  - dataset:
      config: default
      name: MTEB MindSmallReranking (default)
      revision: 59042f120c80e8afa9cdbb224f67076cec0fc9a7
      split: test
      type: mteb/mind_small
    metrics:
    - type: main_score
      value: 26.59574079364091
    - type: map
      value: 26.59574079364091
    - type: mrr
      value: 26.734835405117906
    - type: nAUC_map_diff1
      value: 17.816336924527814
    - type: nAUC_map_max
      value: -32.28299945433697
    - type: nAUC_map_std
      value: -18.970361215864656
    - type: nAUC_mrr_diff1
      value: 16.909657362222404
    - type: nAUC_mrr_max
      value: -26.468833047236117
    - type: nAUC_mrr_std
      value: -16.206930004122203
    task:
      type: Reranking
  - dataset:
      config: default
      name: MTEB RedditClustering (default)
      revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
      split: test
      type: mteb/reddit-clustering
    metrics:
    - type: main_score
      value: 25.20525559369379
    - type: v_measure
      value: 25.20525559369379
    - type: v_measure_std
      value: 3.716703201672722
    task:
      type: Clustering
  - dataset:
      config: default
      name: MTEB RedditClusteringP2P (default)
      revision: 385e3cb46b4cfa89021f56c4380204149d0efe33
      split: test
      type: mteb/reddit-clustering-p2p
    metrics:
    - type: main_score
      value: 36.610660271894346
    - type: v_measure
      value: 36.610660271894346
    - type: v_measure_std
      value: 10.534090572143375
    task:
      type: Clustering
  - dataset:
      config: default
      name: MTEB SICK-R (default)
      revision: 20a6d6f312dd54037fe07a32d58e5e168867909d
      split: test
      type: mteb/sickr-sts
    metrics:
    - type: cosine_pearson
      value: 73.88162235809878
    - type: cosine_spearman
      value: 64.19649802838084
    - type: euclidean_pearson
      value: 66.51859611378926
    - type: euclidean_spearman
      value: 59.6266264848432
    - type: main_score
      value: 64.19649802838084
    - type: manhattan_pearson
      value: 66.67285438914075
    - type: manhattan_spearman
      value: 59.87530286451058
    task:
      type: STS
  - dataset:
      config: default
      name: MTEB STS12 (default)
      revision: a0d554a64d88156834ff5ae9920b964011b16384
      split: test
      type: mteb/sts12-sts
    metrics:
    - type: cosine_pearson
      value: 67.73929220446036
    - type: cosine_spearman
      value: 60.75363314544754
    - type: euclidean_pearson
      value: 56.81702291127883
    - type: euclidean_spearman
      value: 51.923738495157814
    - type: main_score
      value: 60.75363314544754
    - type: manhattan_pearson
      value: 56.86705283582077
    - type: manhattan_spearman
      value: 51.93399158324235
    task:
      type: STS
  - dataset:
      config: default
      name: MTEB STS13 (default)
      revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
      split: test
      type: mteb/sts13-sts
    metrics:
    - type: cosine_pearson
      value: 72.42112734144125
    - type: cosine_spearman
      value: 73.59653137440841
    - type: euclidean_pearson
      value: 57.561401730473264
    - type: euclidean_spearman
      value: 58.581546191861
    - type: main_score
      value: 73.59653137440841
    - type: manhattan_pearson
      value: 57.70055341285516
    - type: manhattan_spearman
      value: 58.42777714658004
    task:
      type: STS
  - dataset:
      config: default
      name: MTEB STS14 (default)
      revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
      split: test
      type: mteb/sts14-sts
    metrics:
    - type: cosine_pearson
      value: 69.6802098874101
    - type: cosine_spearman
      value: 67.31752503036513
    - type: euclidean_pearson
      value: 57.77439148526571
    - type: euclidean_spearman
      value: 57.54518624632547
    - type: main_score
      value: 67.31752503036513
    - type: manhattan_pearson
      value: 57.826113726980225
    - type: manhattan_spearman
      value: 57.62333865582037
    task:
      type: STS
  - dataset:
      config: default
      name: MTEB STS15 (default)
      revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
      split: test
      type: mteb/sts15-sts
    metrics:
    - type: cosine_pearson
      value: 72.70416316480933
    - type: cosine_spearman
      value: 74.27113308901295
    - type: euclidean_pearson
      value: 56.71321653105237
    - type: euclidean_spearman
      value: 59.50982015715706
    - type: main_score
      value: 74.27113308901295
    - type: manhattan_pearson
      value: 56.89847334180773
    - type: manhattan_spearman
      value: 59.46793125210128
    task:
      type: STS
  - dataset:
      config: default
      name: MTEB STS16 (default)
      revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
      split: test
      type: mteb/sts16-sts
    metrics:
    - type: cosine_pearson
      value: 63.90089258497955
    - type: cosine_spearman
      value: 66.87333410406687
    - type: euclidean_pearson
      value: 51.17410118962291
    - type: euclidean_spearman
      value: 54.00446857938969
    - type: main_score
      value: 66.87333410406687
    - type: manhattan_pearson
      value: 50.957252868925785
    - type: manhattan_spearman
      value: 53.90823679117365
    task:
      type: STS
  - dataset:
      config: en-en
      name: MTEB STS17 (en-en)
      revision: faeb762787bd10488a50c8b5be4a3b82e411949c
      split: test
      type: mteb/sts17-crosslingual-sts
    metrics:
    - type: cosine_pearson
      value: 78.3081155365183
    - type: cosine_spearman
      value: 79.95190716648233
    - type: euclidean_pearson
      value: 65.61131056255932
    - type: euclidean_spearman
      value: 66.47265770652439
    - type: main_score
      value: 79.95190716648233
    - type: manhattan_pearson
      value: 66.45361314456927
    - type: manhattan_spearman
      value: 67.37156904121075
    task:
      type: STS
  - dataset:
      config: fr-en
      name: MTEB STS17 (fr-en)
      revision: faeb762787bd10488a50c8b5be4a3b82e411949c
      split: test
      type: mteb/sts17-crosslingual-sts
    metrics:
    - type: cosine_pearson
      value: 21.052932104990603
    - type: cosine_spearman
      value: 18.11753200383624
    - type: euclidean_pearson
      value: -13.223141516540442
    - type: euclidean_spearman
      value: -13.840197821416345
    - type: main_score
      value: 18.11753200383624
    - type: manhattan_pearson
      value: -15.780391442498672
    - type: manhattan_spearman
      value: -15.964949757477415
    task:
      type: STS
  - dataset:
      config: en-de
      name: MTEB STS17 (en-de)
      revision: faeb762787bd10488a50c8b5be4a3b82e411949c
      split: test
      type: mteb/sts17-crosslingual-sts
    metrics:
    - type: cosine_pearson
      value: 19.391740742905483
    - type: cosine_spearman
      value: 16.72340259240136
    - type: euclidean_pearson
      value: -11.027102023055617
    - type: euclidean_spearman
      value: -14.089671183063315
    - type: main_score
      value: 16.72340259240136
    - type: manhattan_pearson
      value: -9.630121740021742
    - type: manhattan_spearman
      value: -12.712224581945044
    task:
      type: STS
  - dataset:
      config: it-en
      name: MTEB STS17 (it-en)
      revision: faeb762787bd10488a50c8b5be4a3b82e411949c
      split: test
      type: mteb/sts17-crosslingual-sts
    metrics:
    - type: cosine_pearson
      value: 16.543270296306552
    - type: cosine_spearman
      value: 13.326682468836701
    - type: euclidean_pearson
      value: -16.68928390130844
    - type: euclidean_spearman
      value: -16.549540032350627
    - type: main_score
      value: 13.326682468836701
    - type: manhattan_pearson
      value: -19.00891735419843
    - type: manhattan_spearman
      value: -17.698001607994165
    task:
      type: STS
  - dataset:
      config: en-ar
      name: MTEB STS17 (en-ar)
      revision: faeb762787bd10488a50c8b5be4a3b82e411949c
      split: test
      type: mteb/sts17-crosslingual-sts
    metrics:
    - type: cosine_pearson
      value: -2.9439800614294684
    - type: cosine_spearman
      value: -5.3077802551968265
    - type: euclidean_pearson
      value: -11.370503095296403
    - type: euclidean_spearman
      value: -11.559874891543458
    - type: main_score
      value: -5.3077802551968265
    - type: manhattan_pearson
      value: -11.568850533311064
    - type: manhattan_spearman
      value: -11.33350236892719
    task:
      type: STS
  - dataset:
      config: nl-en
      name: MTEB STS17 (nl-en)
      revision: faeb762787bd10488a50c8b5be4a3b82e411949c
      split: test
      type: mteb/sts17-crosslingual-sts
    metrics:
    - type: cosine_pearson
      value: 18.65393295613954
    - type: cosine_spearman
      value: 15.24163076732163
    - type: euclidean_pearson
      value: -17.67941685499847
    - type: euclidean_spearman
      value: -18.798375175098357
    - type: main_score
      value: 15.24163076732163
    - type: manhattan_pearson
      value: -18.12153260050368
    - type: manhattan_spearman
      value: -20.005495664435774
    task:
      type: STS
  - dataset:
      config: es-en
      name: MTEB STS17 (es-en)
      revision: faeb762787bd10488a50c8b5be4a3b82e411949c
      split: test
      type: mteb/sts17-crosslingual-sts
    metrics:
    - type: cosine_pearson
      value: 9.521577216425623
    - type: cosine_spearman
      value: 6.843613091602483
    - type: euclidean_pearson
      value: -4.097799713874057
    - type: euclidean_spearman
      value: -11.156128457955933
    - type: main_score
      value: 6.843613091602483
    - type: manhattan_pearson
      value: -4.05688864628645
    - type: manhattan_spearman
      value: -11.89166145882455
    task:
      type: STS
  - dataset:
      config: en-tr
      name: MTEB STS17 (en-tr)
      revision: faeb762787bd10488a50c8b5be4a3b82e411949c
      split: test
      type: mteb/sts17-crosslingual-sts
    metrics:
    - type: cosine_pearson
      value: -1.4988979360452002
    - type: cosine_spearman
      value: -3.2874562266915137
    - type: euclidean_pearson
      value: -20.943851828369116
    - type: euclidean_spearman
      value: -23.783711189126038
    - type: main_score
      value: -3.2874562266915137
    - type: manhattan_pearson
      value: -21.108855435186715
    - type: manhattan_spearman
      value: -23.244298623218594
    task:
      type: STS
  - dataset:
      config: de-en
      name: MTEB STS22 (de-en)
      revision: de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3
      split: test
      type: mteb/sts22-crosslingual-sts
    metrics:
    - type: cosine_pearson
      value: 15.136123348625533
    - type: cosine_spearman
      value: 20.810954246441803
    - type: euclidean_pearson
      value: 19.516242119260312
    - type: euclidean_spearman
      value: 24.474690200239962
    - type: main_score
      value: 20.810954246441803
    - type: manhattan_pearson
      value: 20.44847818877696
    - type: manhattan_spearman
      value: 27.624281563749992
    task:
      type: STS
  - dataset:
      config: zh-en
      name: MTEB STS22 (zh-en)
      revision: de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3
      split: test
      type: mteb/sts22-crosslingual-sts
    metrics:
    - type: cosine_pearson
      value: 3.14950505909999
    - type: cosine_spearman
      value: 8.436389259170458
    - type: euclidean_pearson
      value: 7.7506147255123725
    - type: euclidean_spearman
      value: 7.037062440876494
    - type: main_score
      value: 8.436389259170458
    - type: manhattan_pearson
      value: 9.706026714640052
    - type: manhattan_spearman
      value: 8.00200100450235
    task:
      type: STS
  - dataset:
      config: pl-en
      name: MTEB STS22 (pl-en)
      revision: de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3
      split: test
      type: mteb/sts22-crosslingual-sts
    metrics:
    - type: cosine_pearson
      value: 8.59590335620229
    - type: cosine_spearman
      value: 10.778094331264766
    - type: euclidean_pearson
      value: 28.70358543656486
    - type: euclidean_spearman
      value: 20.863348379272782
    - type: main_score
      value: 10.778094331264766
    - type: manhattan_pearson
      value: 32.10263640633953
    - type: manhattan_spearman
      value: 16.555236242029686
    task:
      type: STS
  - dataset:
      config: es-en
      name: MTEB STS22 (es-en)
      revision: de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3
      split: test
      type: mteb/sts22-crosslingual-sts
    metrics:
    - type: cosine_pearson
      value: 8.00733458463991
    - type: cosine_spearman
      value: 9.118706078872984
    - type: euclidean_pearson
      value: 9.07149432617858
    - type: euclidean_spearman
      value: 11.219345362943432
    - type: main_score
      value: 9.118706078872984
    - type: manhattan_pearson
      value: 8.832718333342706
    - type: manhattan_spearman
      value: 10.263754583872384
    task:
      type: STS
  - dataset:
      config: en
      name: MTEB STS22 (en)
      revision: de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3
      split: test
      type: mteb/sts22-crosslingual-sts
    metrics:
    - type: cosine_pearson
      value: 43.55249623133272
    - type: cosine_spearman
      value: 53.697978884880406
    - type: euclidean_pearson
      value: 43.8389320084649
    - type: euclidean_spearman
      value: 52.42704777306256
    - type: main_score
      value: 53.697978884880406
    - type: manhattan_pearson
      value: 43.86629307814909
    - type: manhattan_spearman
      value: 52.0381832205353
    task:
      type: STS
  - dataset:
      config: default
      name: MTEB STSBenchmark (default)
      revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
      split: test
      type: mteb/stsbenchmark-sts
    metrics:
    - type: cosine_pearson
      value: 67.31658836868895
    - type: cosine_spearman
      value: 66.82184731765354
    - type: euclidean_pearson
      value: 57.80273593674898
    - type: euclidean_spearman
      value: 57.772446648657706
    - type: main_score
      value: 66.82184731765354
    - type: manhattan_pearson
      value: 58.234209002194795
    - type: manhattan_spearman
      value: 58.12293550703129
    task:
      type: STS
  - dataset:
      config: default
      name: MTEB SciDocsRR (default)
      revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
      split: test
      type: mteb/scidocs-reranking
    metrics:
    - type: main_score
      value: 66.86139617126783
    - type: map
      value: 66.86139617126783
    - type: mrr
      value: 87.3149943738179
    - type: nAUC_map_diff1
      value: 10.92124948908669
    - type: nAUC_map_max
      value: 55.79229386744934
    - type: nAUC_map_std
      value: 65.42609776668083
    - type: nAUC_mrr_diff1
      value: 42.06337561377432
    - type: nAUC_mrr_max
      value: 72.26477089952296
    - type: nAUC_mrr_std
      value: 68.47174098478668
    task:
      type: Reranking
  - dataset:
      config: default
      name: MTEB SprintDuplicateQuestions (default)
      revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
      split: test
      type: mteb/sprintduplicatequestions-pairclassification
    metrics:
    - type: cosine_accuracy
      value: 99.6009900990099
    - type: cosine_accuracy_threshold
      value: 78.9186954498291
    - type: cosine_ap
      value: 84.68208216332572
    - type: cosine_f1
      value: 78.88487351574601
    - type: cosine_f1_threshold
      value: 76.20431184768677
    - type: cosine_precision
      value: 81.53681963713981
    - type: cosine_recall
      value: 76.4
    - type: dot_accuracy
      value: 99.05346534653465
    - type: dot_accuracy_threshold
      value: 62070.60546875
    - type: dot_ap
      value: 30.67111560824568
    - type: dot_f1
      value: 36.43184660275114
    - type: dot_f1_threshold
      value: 38959.15222167969
    - type: dot_precision
      value: 31.236597569692638
    - type: dot_recall
      value: 43.7
    - type: euclidean_accuracy
      value: 99.42871287128713
    - type: euclidean_accuracy_threshold
      value: 1293.6470031738281
    - type: euclidean_ap
      value: 68.4948217545871
    - type: euclidean_f1
      value: 66.38161411010155
    - type: euclidean_f1_threshold
      value: 1388.7130737304688
    - type: euclidean_precision
      value: 71.29735935706086
    - type: euclidean_recall
      value: 62.1
    - type: main_score
      value: 84.68208216332572
    - type: manhattan_accuracy
      value: 99.41584158415841
    - type: manhattan_accuracy_threshold
      value: 11503.255462646484
    - type: manhattan_ap
      value: 68.54990551262247
    - type: manhattan_f1
      value: 66.26173384870238
    - type: manhattan_f1_threshold
      value: 12185.600280761719
    - type: manhattan_precision
      value: 73.98273736128237
    - type: manhattan_recall
      value: 60.0
    - type: max_accuracy
      value: 99.6009900990099
    - type: max_ap
      value: 84.68208216332572
    - type: max_f1
      value: 78.88487351574601
    - type: max_precision
      value: 81.53681963713981
    - type: max_recall
      value: 76.4
    - type: similarity_accuracy
      value: 99.6009900990099
    - type: similarity_accuracy_threshold
      value: 78.9186954498291
    - type: similarity_ap
      value: 84.68208080875644
    - type: similarity_f1
      value: 78.88487351574601
    - type: similarity_f1_threshold
      value: 76.20431184768677
    - type: similarity_precision
      value: 81.53681963713981
    - type: similarity_recall
      value: 76.4
    task:
      type: PairClassification
  - dataset:
      config: default
      name: MTEB StackExchangeClustering (default)
      revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
      split: test
      type: mteb/stackexchange-clustering
    metrics:
    - type: main_score
      value: 35.27926530004693
    - type: v_measure
      value: 35.27926530004693
    - type: v_measure_std
      value: 4.213594415514492
    task:
      type: Clustering
  - dataset:
      config: default
      name: MTEB StackExchangeClusteringP2P (default)
      revision: 815ca46b2622cec33ccafc3735d572c266efdb44
      split: test
      type: mteb/stackexchange-clustering-p2p
    metrics:
    - type: main_score
      value: 29.27592909966068
    - type: v_measure
      value: 29.27592909966068
    - type: v_measure_std
      value: 1.4306687739012842
    task:
      type: Clustering
  - dataset:
      config: default
      name: MTEB StackOverflowDupQuestions (default)
      revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
      split: test
      type: mteb/stackoverflowdupquestions-reranking
    metrics:
    - type: main_score
      value: 42.46430536151378
    - type: map
      value: 42.46430536151378
    - type: mrr
      value: 42.978697160682444
    - type: nAUC_map_diff1
      value: 34.16488374642183
    - type: nAUC_map_max
      value: 15.990699582552214
    - type: nAUC_map_std
      value: 7.0505058354865024
    - type: nAUC_mrr_diff1
      value: 33.67219566480288
    - type: nAUC_mrr_max
      value: 16.990618160743995
    - type: nAUC_mrr_std
      value: 7.524962858906838
    task:
      type: Reranking
  - dataset:
      config: default
      name: MTEB SummEval (default)
      revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
      split: test
      type: mteb/summeval
    metrics:
    - type: cosine_pearson
      value: 30.183315092157393
    - type: cosine_spearman
      value: 30.164573201350965
    - type: dot_pearson
      value: 15.532441039164112
    - type: dot_spearman
      value: 17.744350263113876
    - type: main_score
      value: 30.164573201350965
    - type: pearson
      value: 30.183314669218987
    - type: spearman
      value: 30.161615957372895
    task:
      type: Summarization
  - dataset:
      config: default
      name: MTEB ToxicConversationsClassification (default)
      revision: edfaf9da55d3dd50d43143d90c1ac476895ae6de
      split: test
      type: mteb/toxic_conversations_50k
    metrics:
    - type: accuracy
      value: 62.1435546875
    - type: ap
      value: 10.253828258206063
    - type: ap_weighted
      value: 10.253828258206063
    - type: f1
      value: 47.395641667877385
    - type: f1_weighted
      value: 70.68010031561886
    - type: main_score
      value: 62.1435546875
    task:
      type: Classification
  - dataset:
      config: default
      name: MTEB TweetSentimentExtractionClassification (default)
      revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
      split: test
      type: mteb/tweet_sentiment_extraction
    metrics:
    - type: accuracy
      value: 48.39841539332202
    - type: f1
      value: 48.58310905274024
    - type: f1_weighted
      value: 48.03031996995187
    - type: main_score
      value: 48.39841539332202
    task:
      type: Classification
  - dataset:
      config: default
      name: MTEB TwentyNewsgroupsClustering (default)
      revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
      split: test
      type: mteb/twentynewsgroups-clustering
    metrics:
    - type: main_score
      value: 21.965681413174785
    - type: v_measure
      value: 21.965681413174785
    - type: v_measure_std
      value: 2.2097945438628344
    task:
      type: Clustering
  - dataset:
      config: default
      name: MTEB TwitterSemEval2015 (default)
      revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
      split: test
      type: mteb/twittersemeval2015-pairclassification
    metrics:
    - type: cosine_accuracy
      value: 81.76670441676104
    - type: cosine_accuracy_threshold
      value: 77.6945948600769
    - type: cosine_ap
      value: 57.43644750160504
    - type: cosine_f1
      value: 54.339194554736245
    - type: cosine_f1_threshold
      value: 66.83574914932251
    - type: cosine_precision
      value: 47.66169154228856
    - type: cosine_recall
      value: 63.19261213720316
    - type: dot_accuracy
      value: 78.04136615604696
    - type: dot_accuracy_threshold
      value: 69279.91943359375
    - type: dot_ap
      value: 41.27462915286439
    - type: dot_f1
      value: 45.9406677206361
    - type: dot_f1_threshold
      value: 38870.428466796875
    - type: dot_precision
      value: 35.473215568002296
    - type: dot_recall
      value: 65.17150395778364
    - type: euclidean_accuracy
      value: 80.03218692257256
    - type: euclidean_accuracy_threshold
      value: 1667.4659729003906
    - type: euclidean_ap
      value: 51.44165670701795
    - type: euclidean_f1
      value: 50.63679245283019
    - type: euclidean_f1_threshold
      value: 2015.814208984375
    - type: euclidean_precision
      value: 45.778251599147126
    - type: euclidean_recall
      value: 56.6490765171504
    - type: main_score
      value: 57.43645711181132
    - type: manhattan_accuracy
      value: 80.07987125230972
    - type: manhattan_accuracy_threshold
      value: 14477.607727050781
    - type: manhattan_ap
      value: 51.609695680028544
    - type: manhattan_f1
      value: 50.732328592655485
    - type: manhattan_f1_threshold
      value: 18645.140075683594
    - type: manhattan_precision
      value: 42.43607954545455
    - type: manhattan_recall
      value: 63.06068601583114
    - type: max_accuracy
      value: 81.76670441676104
    - type: max_ap
      value: 57.43645711181132
    - type: max_f1
      value: 54.339194554736245
    - type: max_precision
      value: 47.66169154228856
    - type: max_recall
      value: 65.17150395778364
    - type: similarity_accuracy
      value: 81.76670441676104
    - type: similarity_accuracy_threshold
      value: 77.6945948600769
    - type: similarity_ap
      value: 57.43645711181132
    - type: similarity_f1
      value: 54.339194554736245
    - type: similarity_f1_threshold
      value: 66.83574914932251
    - type: similarity_precision
      value: 47.66169154228856
    - type: similarity_recall
      value: 63.19261213720316
    task:
      type: PairClassification
  - dataset:
      config: default
      name: MTEB TwitterURLCorpus (default)
      revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
      split: test
      type: mteb/twitterurlcorpus-pairclassification
    metrics:
    - type: cosine_accuracy
      value: 85.71040478130942
    - type: cosine_accuracy_threshold
      value: 69.46260929107666
    - type: cosine_ap
      value: 78.33655877180354
    - type: cosine_f1
      value: 70.4509162801308
    - type: cosine_f1_threshold
      value: 66.09716415405273
    - type: cosine_precision
      value: 69.5884031846177
    - type: cosine_recall
      value: 71.33507853403141
    - type: dot_accuracy
      value: 82.07008964955175
    - type: dot_accuracy_threshold
      value: 27785.427856445312
    - type: dot_ap
      value: 67.05507223333423
    - type: dot_f1
      value: 63.016089065717374
    - type: dot_f1_threshold
      value: 23387.98828125
    - type: dot_precision
      value: 57.63166294286626
    - type: dot_recall
      value: 69.51031721589159
    - type: euclidean_accuracy
      value: 83.10435828773237
    - type: euclidean_accuracy_threshold
      value: 1362.842082977295
    - type: euclidean_ap
      value: 70.21973250044095
    - type: euclidean_f1
      value: 62.38352870453863
    - type: euclidean_f1_threshold
      value: 1582.8761100769043
    - type: euclidean_precision
      value: 60.91869680070443
    - type: euclidean_recall
      value: 63.92054203880505
    - type: main_score
      value: 78.33656919387448
    - type: manhattan_accuracy
      value: 83.06942989094578
    - type: manhattan_accuracy_threshold
      value: 12189.000701904297
    - type: manhattan_ap
      value: 70.16377530413878
    - type: manhattan_f1
      value: 62.365993052183335
    - type: manhattan_f1_threshold
      value: 14111.676025390625
    - type: manhattan_precision
      value: 60.56736559529856
    - type: manhattan_recall
      value: 64.27471512165074
    - type: max_accuracy
      value: 85.71040478130942
    - type: max_ap
      value: 78.33656919387448
    - type: max_f1
      value: 70.4509162801308
    - type: max_precision
      value: 69.5884031846177
    - type: max_recall
      value: 71.33507853403141
    - type: similarity_accuracy
      value: 85.71040478130942
    - type: similarity_accuracy_threshold
      value: 69.46260929107666
    - type: similarity_ap
      value: 78.33656919387448
    - type: similarity_f1
      value: 70.4509162801308
    - type: similarity_f1_threshold
      value: 66.09715819358826
    - type: similarity_precision
      value: 69.5884031846177
    - type: similarity_recall
      value: 71.33507853403141
    task:
      type: PairClassification

---
# 🪲 brown-beetle-tiny-v1 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 128 dimensions and applying Zipf.

> [!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-tiny-v1")

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

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

## Reproduce this model

To reproduce this model, you must install the `model2vec[distill]` package and use the following code:

```python
from model2vec.distill import distill

# Distill the model
m2v_model = distill(
    model_name="bge-base-en-v1.5",
    pca_dims=128,
    apply_zipf=True,
)

# Save the model
m2v_model.save_pretrained("brown-beetle-tiny-v1")
```

## 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},
}
```