transformers gguf language granite embeddings mteb llama-cpp gguf-my-repo sentence-similarity en base_model:ibm-granite/granite-embedding-30m-english base_model:quantized:ibm-granite/granite-embedding-30m-english license:apache-2.0 model-index endpoints_compatible region:us feature-extraction
---
base_model: ibm-granite/granite-embedding-30m-english
language:
- en
library_name: transformers
license: apache-2.0
pipeline_tag: sentence-similarity
tags:
- language
- granite
- embeddings
- mteb
- llama-cpp
- gguf-my-repo
model-index:
- name: ibm-granite/granite-embedding-30m-english
  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: 62.856100000000005
    - type: f1
      value: 51.5046
    - type: f1_weighted
      value: 69.9775
    - type: ap
      value: 15.4995
    - type: ap_weighted
      value: 15.4995
    - type: main_score
      value: 62.856100000000005
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonCounterfactualClassification (en)
      type: mteb/amazon_counterfactual
      config: en
      split: test
      revision: e8379541af4e31359cca9fbcf4b00f2671dba205
    metrics:
    - type: accuracy
      value: 60.925399999999996
    - type: f1
      value: 55.0092
    - type: f1_weighted
      value: 64.8014
    - type: ap
      value: 25.0517
    - type: ap_weighted
      value: 25.0517
    - type: main_score
      value: 60.925399999999996
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonPolarityClassification (default)
      type: mteb/amazon_polarity
      config: default
      split: test
      revision: e2d317d38cd51312af73b3d32a06d1a08b442046
    metrics:
    - type: accuracy
      value: 62.983599999999996
    - type: f1
      value: 62.553599999999996
    - type: f1_weighted
      value: 62.553599999999996
    - type: ap
      value: 58.3423
    - type: ap_weighted
      value: 58.3423
    - type: main_score
      value: 62.983599999999996
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonReviewsClassification (en)
      type: mteb/amazon_reviews_multi
      config: en
      split: test
      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
    metrics:
    - type: accuracy
      value: 32.178000000000004
    - type: f1
      value: 31.5201
    - type: f1_weighted
      value: 31.5201
    - type: main_score
      value: 32.178000000000004
  - task:
      type: Retrieval
    dataset:
      name: MTEB AppsRetrieval (default)
      type: CoIR-Retrieval/apps
      config: default
      split: test
      revision: f22508f96b7a36c2415181ed8bb76f76e04ae2d5
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    - type: ndcg_at_5
      value: 5.314
    - type: ndcg_at_10
      value: 6.203
    - type: ndcg_at_20
      value: 6.801
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      value: 8.588
    - type: ndcg_at_1000
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    - type: map_at_3
      value: 4.471
    - type: map_at_5
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    - type: map_at_100
      value: 5.501
    - type: map_at_1000
      value: 5.611
    - type: recall_at_1
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      value: 5.71
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    - type: recall_at_10
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      value: 12.165
    - type: recall_at_100
      value: 22.205
    - type: recall_at_1000
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    - type: precision_at_5
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    - type: precision_at_100
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    - type: precision_at_1000
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      value: 4.471
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  - task:
      type: Retrieval
    dataset:
      name: MTEB ArguAna (default)
      type: mteb/arguana
      config: default
      split: test
      revision: c22ab2a51041ffd869aaddef7af8d8215647e41a
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      value: 51.623
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    - type: recall_at_1000
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    - type: precision_at_1
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    - type: nauc_mrr_at_100_diff1
      value: 11.325000000000001
    - type: nauc_mrr_at_1000_max
      value: -6.7619
    - type: nauc_mrr_at_1000_std
      value: -8.878400000000001
    - type: nauc_mrr_at_1000_diff1
      value: 11.3251
    - type: main_score
      value: 56.355999999999995
  - task:
      type: Clustering
    dataset:
      name: MTEB ArxivClusteringP2P (default)
      type: mteb/arxiv-clustering-p2p
      config: default
      split: test
      revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
    metrics:
    - type: v_measure
      value: 46.813
    - type: v_measure_std
      value: 13.830899999999998
    - type: main_score
      value: 46.813
  - task:
      type: Clustering
    dataset:
      name: MTEB ArxivClusteringS2S (default)
      type: mteb/arxiv-clustering-s2s
      config: default
      split: test
      revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
    metrics:
    - type: v_measure
      value: 41.9895
    - type: v_measure_std
      value: 14.3004
    - type: main_score
      value: 41.9895
  - task:
      type: Reranking
    dataset:
      name: MTEB AskUbuntuDupQuestions (default)
      type: mteb/askubuntudupquestions-reranking
      config: default
      split: test
      revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
    metrics:
    - type: map
      value: 64.1329
    - type: mrr
      value: 76.8303
    - type: nAUC_map_max
      value: 23.5323
    - type: nAUC_map_std
      value: 14.7567
    - type: nAUC_map_diff1
      value: 11.6783
    - type: nAUC_mrr_max
      value: 32.3309
    - type: nAUC_mrr_std
      value: 19.1617
    - type: nAUC_mrr_diff1
      value: 23.508699999999997
    - type: main_score
      value: 64.1329
  - task:
      type: STS
    dataset:
      name: MTEB BIOSSES (default)
      type: mteb/biosses-sts
      config: default
      split: test
      revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
    metrics:
    - type: pearson
      value: 90.2058
    - type: spearman
      value: 88.1641
    - type: cosine_pearson
      value: 90.2058
    - type: cosine_spearman
      value: 88.1641
    - type: manhattan_pearson
      value: 87.7579
    - type: manhattan_spearman
      value: 87.6249
    - type: euclidean_pearson
      value: 88.3667
    - type: euclidean_spearman
      value: 88.1641
    - type: main_score
      value: 88.1641
  - task:
      type: Classification
    dataset:
      name: MTEB Banking77Classification (default)
      type: mteb/banking77
      config: default
      split: test
      revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
    metrics:
    - type: accuracy
      value: 77.3247
    - type: f1
      value: 76.3532
    - type: f1_weighted
      value: 76.3532
    - type: main_score
      value: 77.3247
  - task:
      type: Clustering
    dataset:
      name: MTEB BiorxivClusteringP2P (default)
      type: mteb/biorxiv-clustering-p2p
      config: default
      split: test
      revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
    metrics:
    - type: v_measure
      value: 39.018
    - type: v_measure_std
      value: 0.7512
    - type: main_score
      value: 39.018
  - task:
      type: Clustering
    dataset:
      name: MTEB BiorxivClusteringS2S (default)
      type: mteb/biorxiv-clustering-s2s
      config: default
      split: test
      revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
    metrics:
    - type: v_measure
      value: 36.8097
    - type: v_measure_std
      value: 0.9368
    - type: main_score
      value: 36.8097
  - task:
      type: Retrieval
    dataset:
      name: MTEB COIRCodeSearchNetRetrieval (python)
      type: CoIR-Retrieval/CodeSearchNet
      config: python
      split: test
      revision: 4adc7bc41202b5c13543c9c886a25f340634dab3
    metrics:
    - type: ndcg_at_1
      value: 85.353
    - type: ndcg_at_3
      value: 89.493
    - type: ndcg_at_5
      value: 90.347
    - type: ndcg_at_10
      value: 90.89699999999999
    - type: ndcg_at_20
      value: 91.20899999999999
    - type: ndcg_at_100
      value: 91.506
    - type: ndcg_at_1000
      value: 91.62400000000001
    - type: map_at_1
      value: 85.353
    - type: map_at_3
      value: 88.532
    - type: map_at_5
      value: 89.008
    - type: map_at_10
      value: 89.238
    - type: map_at_20
      value: 89.323
    - type: map_at_100
      value: 89.366
    - type: map_at_1000
      value: 89.371
    - type: recall_at_1
      value: 85.353
    - type: recall_at_3
      value: 92.251
    - type: recall_at_5
      value: 94.316
    - type: recall_at_10
      value: 95.998
    - type: recall_at_20
      value: 97.238
    - type: recall_at_100
      value: 98.81400000000001
    - type: recall_at_1000
      value: 99.725
    - type: precision_at_1
      value: 85.353
    - type: precision_at_3
      value: 30.75
    - type: precision_at_5
      value: 18.863
    - type: precision_at_10
      value: 9.6
    - type: precision_at_20
      value: 4.862
    - type: precision_at_100
      value: 0.988
    - type: precision_at_1000
      value: 0.1
    - type: mrr_at_1
      value: 85.3533
    - type: mrr_at_3
      value: 88.5318
    - type: mrr_at_5
      value: 89.0077
    - type: mrr_at_10
      value: 89.2381
    - type: mrr_at_20
      value: 89.3231
    - type: mrr_at_100
      value: 89.3659
    - type: mrr_at_1000
      value: 89.3707
    - type: nauc_ndcg_at_1_max
      value: 79.05529999999999
    - type: nauc_ndcg_at_1_std
      value: 6.6982
    - type: nauc_ndcg_at_1_diff1
      value: 89.6212
    - type: nauc_ndcg_at_3_max
      value: 82.5612
    - type: nauc_ndcg_at_3_std
      value: 10.379199999999999
    - type: nauc_ndcg_at_3_diff1
      value: 87.809
    - type: nauc_ndcg_at_5_max
      value: 82.4315
    - type: nauc_ndcg_at_5_std
      value: 10.5113
    - type: nauc_ndcg_at_5_diff1
      value: 88.0763
    - type: nauc_ndcg_at_10_max
      value: 82.4135
    - type: nauc_ndcg_at_10_std
      value: 11.046
    - type: nauc_ndcg_at_10_diff1
      value: 88.2008
    - type: nauc_ndcg_at_20_max
      value: 82.3276
    - type: nauc_ndcg_at_20_std
      value: 11.4306
    - type: nauc_ndcg_at_20_diff1
      value: 88.2525
    - type: nauc_ndcg_at_100_max
      value: 82.1023
    - type: nauc_ndcg_at_100_std
      value: 11.2119
    - type: nauc_ndcg_at_100_diff1
      value: 88.3149
    - type: nauc_ndcg_at_1000_max
      value: 81.91720000000001
    - type: nauc_ndcg_at_1000_std
      value: 10.7203
    - type: nauc_ndcg_at_1000_diff1
      value: 88.349
    - type: nauc_map_at_1_max
      value: 79.05529999999999
    - type: nauc_map_at_1_std
      value: 6.6982
    - type: nauc_map_at_1_diff1
      value: 89.6212
    - type: nauc_map_at_3_max
      value: 81.5856
    - type: nauc_map_at_3_std
      value: 9.3626
    - type: nauc_map_at_3_diff1
      value: 88.2364
    - type: nauc_map_at_5_max
      value: 81.4778
    - type: nauc_map_at_5_std
      value: 9.3662
    - type: nauc_map_at_5_diff1
      value: 88.3865
    - type: nauc_map_at_10_max
      value: 81.447
    - type: nauc_map_at_10_std
      value: 9.5111
    - type: nauc_map_at_10_diff1
      value: 88.43469999999999
    - type: nauc_map_at_20_max
      value: 81.4196
    - type: nauc_map_at_20_std
      value: 9.593
    - type: nauc_map_at_20_diff1
      value: 88.4473
    - type: nauc_map_at_100_max
      value: 81.3925
    - type: nauc_map_at_100_std
      value: 9.5683
    - type: nauc_map_at_100_diff1
      value: 88.4559
    - type: nauc_map_at_1000_max
      value: 81.3865
    - type: nauc_map_at_1000_std
      value: 9.554
    - type: nauc_map_at_1000_diff1
      value: 88.457
    - type: nauc_recall_at_1_max
      value: 79.05529999999999
    - type: nauc_recall_at_1_std
      value: 6.6982
    - type: nauc_recall_at_1_diff1
      value: 89.6212
    - type: nauc_recall_at_3_max
      value: 86.56580000000001
    - type: nauc_recall_at_3_std
      value: 14.5464
    - type: nauc_recall_at_3_diff1
      value: 86.1047
    - type: nauc_recall_at_5_max
      value: 87.5044
    - type: nauc_recall_at_5_std
      value: 16.7155
    - type: nauc_recall_at_5_diff1
      value: 86.5603
    - type: nauc_recall_at_10_max
      value: 89.5625
    - type: nauc_recall_at_10_std
      value: 23.230700000000002
    - type: nauc_recall_at_10_diff1
      value: 86.8079
    - type: nauc_recall_at_20_max
      value: 91.7174
    - type: nauc_recall_at_20_std
      value: 33.203700000000005
    - type: nauc_recall_at_20_diff1
      value: 86.8468
    - type: nauc_recall_at_100_max
      value: 95.55160000000001
    - type: nauc_recall_at_100_std
      value: 53.0169
    - type: nauc_recall_at_100_diff1
      value: 87.1867
    - type: nauc_recall_at_1000_max
      value: 97.0907
    - type: nauc_recall_at_1000_std
      value: 75.0177
    - type: nauc_recall_at_1000_diff1
      value: 91.3005
    - type: nauc_precision_at_1_max
      value: 79.05529999999999
    - type: nauc_precision_at_1_std
      value: 6.6982
    - type: nauc_precision_at_1_diff1
      value: 89.6212
    - type: nauc_precision_at_3_max
      value: 86.56580000000001
    - type: nauc_precision_at_3_std
      value: 14.5464
    - type: nauc_precision_at_3_diff1
      value: 86.1047
    - type: nauc_precision_at_5_max
      value: 87.5044
    - type: nauc_precision_at_5_std
      value: 16.7155
    - type: nauc_precision_at_5_diff1
      value: 86.5603
    - type: nauc_precision_at_10_max
      value: 89.5625
    - type: nauc_precision_at_10_std
      value: 23.230700000000002
    - type: nauc_precision_at_10_diff1
      value: 86.8079
    - type: nauc_precision_at_20_max
      value: 91.7174
    - type: nauc_precision_at_20_std
      value: 33.203700000000005
    - type: nauc_precision_at_20_diff1
      value: 86.8468
    - type: nauc_precision_at_100_max
      value: 95.55160000000001
    - type: nauc_precision_at_100_std
      value: 53.0169
    - type: nauc_precision_at_100_diff1
      value: 87.1867
    - type: nauc_precision_at_1000_max
      value: 97.0907
    - type: nauc_precision_at_1000_std
      value: 75.0177
    - type: nauc_precision_at_1000_diff1
      value: 91.3005
    - type: nauc_mrr_at_1_max
      value: 79.05529999999999
    - type: nauc_mrr_at_1_std
      value: 6.6982
    - type: nauc_mrr_at_1_diff1
      value: 89.6212
    - type: nauc_mrr_at_3_max
      value: 81.5856
    - type: nauc_mrr_at_3_std
      value: 9.3626
    - type: nauc_mrr_at_3_diff1
      value: 88.2364
    - type: nauc_mrr_at_5_max
      value: 81.4778
    - type: nauc_mrr_at_5_std
      value: 9.3662
    - type: nauc_mrr_at_5_diff1
      value: 88.3865
    - type: nauc_mrr_at_10_max
      value: 81.447
    - type: nauc_mrr_at_10_std
      value: 9.5111
    - type: nauc_mrr_at_10_diff1
      value: 88.43469999999999
    - type: nauc_mrr_at_20_max
      value: 81.4196
    - type: nauc_mrr_at_20_std
      value: 9.593
    - type: nauc_mrr_at_20_diff1
      value: 88.4473
    - type: nauc_mrr_at_100_max
      value: 81.3925
    - type: nauc_mrr_at_100_std
      value: 9.5683
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      value: 88.4559
    - type: nauc_mrr_at_1000_max
      value: 81.3865
    - type: nauc_mrr_at_1000_std
      value: 9.554
    - type: nauc_mrr_at_1000_diff1
      value: 88.457
    - type: main_score
      value: 90.89699999999999
  - task:
      type: Retrieval
    dataset:
      name: MTEB COIRCodeSearchNetRetrieval (javascript)
      type: CoIR-Retrieval/CodeSearchNet
      config: javascript
      split: test
      revision: 4adc7bc41202b5c13543c9c886a25f340634dab3
    metrics:
    - type: ndcg_at_1
      value: 35.46
    - type: ndcg_at_3
      value: 42.799
    - type: ndcg_at_5
      value: 44.64
    - type: ndcg_at_10
      value: 46.54
    - type: ndcg_at_20
      value: 48.025
    - type: ndcg_at_100
      value: 50.307
    - type: ndcg_at_1000
      value: 51.925
    - type: map_at_1
      value: 35.46
    - type: map_at_3
      value: 41.016000000000005
    - type: map_at_5
      value: 42.038
    - type: map_at_10
      value: 42.825
    - type: map_at_20
      value: 43.233
    - type: map_at_100
      value: 43.541999999999994
    - type: map_at_1000
      value: 43.599
    - type: recall_at_1
      value: 35.46
    - type: recall_at_3
      value: 47.949000000000005
    - type: recall_at_5
      value: 52.416
    - type: recall_at_10
      value: 58.28
    - type: recall_at_20
      value: 64.145
    - type: recall_at_100
      value: 76.542
    - type: recall_at_1000
      value: 89.547
    - type: precision_at_1
      value: 35.46
    - type: precision_at_3
      value: 15.983
    - type: precision_at_5
      value: 10.483
    - type: precision_at_10
      value: 5.827999999999999
    - type: precision_at_20
      value: 3.2070000000000003
    - type: precision_at_100
      value: 0.765
    - type: precision_at_1000
      value: 0.09
    - type: mrr_at_1
      value: 35.460300000000004
    - type: mrr_at_3
      value: 41.0159
    - type: mrr_at_5
      value: 42.038399999999996
    - type: mrr_at_10
      value: 42.8251
    - type: mrr_at_20
      value: 43.2333
    - type: mrr_at_100
      value: 43.542199999999994
    - type: mrr_at_1000
      value: 43.5986
    - type: nauc_ndcg_at_1_max
      value: 48.2915
    - type: nauc_ndcg_at_1_std
      value: 2.4132000000000002
    - type: nauc_ndcg_at_1_diff1
      value: 64.10810000000001
    - type: nauc_ndcg_at_3_max
      value: 51.357
    - type: nauc_ndcg_at_3_std
      value: 4.9681999999999995
    - type: nauc_ndcg_at_3_diff1
      value: 58.012600000000006
    - type: nauc_ndcg_at_5_max
      value: 51.8888
    - type: nauc_ndcg_at_5_std
      value: 6.2654000000000005
    - type: nauc_ndcg_at_5_diff1
      value: 57.103
    - type: nauc_ndcg_at_10_max
      value: 51.9571
    - type: nauc_ndcg_at_10_std
      value: 7.446
    - type: nauc_ndcg_at_10_diff1
      value: 56.505700000000004
    - type: nauc_ndcg_at_20_max
      value: 51.638799999999996
    - type: nauc_ndcg_at_20_std
      value: 7.7742
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      value: 55.9805
    - type: nauc_ndcg_at_100_max
      value: 51.3786
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      value: 8.1191
    - type: nauc_ndcg_at_100_diff1
      value: 56.3265
    - type: nauc_ndcg_at_1000_max
      value: 51.162
    - type: nauc_ndcg_at_1000_std
      value: 7.6863
    - type: nauc_ndcg_at_1000_diff1
      value: 56.6531
    - type: nauc_map_at_1_max
      value: 48.2915
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      value: 2.4132000000000002
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    - type: nauc_map_at_3_max
      value: 50.6599
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      value: 4.3285
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      value: 59.453100000000006
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      value: 50.9502
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      value: 5.0428
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    - type: nauc_map_at_100_max
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      value: 55.125299999999996
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      value: 54.0194
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      value: 16.4329
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      value: 46.1551
    - type: nauc_precision_at_100_max
      value: 52.7898
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      value: 22.375600000000002
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      value: 45.351
    - type: nauc_precision_at_1000_max
      value: 49.0379
    - type: nauc_precision_at_1000_std
      value: 26.0579
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      value: 41.7849
    - type: nauc_mrr_at_1_max
      value: 48.2915
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      value: 2.4132000000000002
    - type: nauc_mrr_at_1_diff1
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      revision: 4adc7bc41202b5c13543c9c886a25f340634dab3
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  - task:
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      type: CoIR-Retrieval/CodeSearchNet
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      revision: 4adc7bc41202b5c13543c9c886a25f340634dab3
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  - task:
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      type: CoIR-Retrieval/CodeSearchNet
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      split: test
      revision: 4adc7bc41202b5c13543c9c886a25f340634dab3
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  - task:
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      type: CoIR-Retrieval/CodeSearchNet-ccr
      config: python
      split: test
      revision: 6e1effa2c03723c5fde48ee912b5ee08d4f211e8
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  - task:
      type: Retrieval
    dataset:
      name: MTEB CodeSearchNetCCRetrieval (javascript)
      type: CoIR-Retrieval/CodeSearchNet-ccr
      config: javascript
      split: test
      revision: 6e1effa2c03723c5fde48ee912b5ee08d4f211e8
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    - type: precision_at_100
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  - task:
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    dataset:
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      type: CoIR-Retrieval/CodeSearchNet-ccr
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      revision: 6e1effa2c03723c5fde48ee912b5ee08d4f211e8
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  - task:
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      revision: fdc6a9e39575768c27eb8a2a5f702bf846eb4759
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  - task:
      type: Retrieval
    dataset:
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      type: code-search-net/code_search_net
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      split: test
      revision: fdc6a9e39575768c27eb8a2a5f702bf846eb4759
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  - task:
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      revision: fdc6a9e39575768c27eb8a2a5f702bf846eb4759
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      type: mteb/hotpotqa
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  - task:
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    dataset:
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      type: mteb/imdb
      config: default
      split: test
      revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
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  - task:
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    dataset:
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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
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  - 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:
    - type: accuracy
      value: 71.3416
    - type: f1
      value: 69.9576
    - type: f1_weighted
      value: 71.19680000000001
    - type: main_score
      value: 71.3416
  - task:
      type: Clustering
    dataset:
      name: MTEB MedrxivClusteringP2P (default)
      type: mteb/medrxiv-clustering-p2p
      config: default
      split: test
      revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
    metrics:
    - type: v_measure
      value: 32.5684
    - type: v_measure_std
      value: 1.6362999999999999
    - type: main_score
      value: 32.5684
  - 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: 31.551299999999998
    - type: v_measure_std
      value: 1.7208999999999999
    - type: main_score
      value: 31.551299999999998
  - task:
      type: Reranking
    dataset:
      name: MTEB MindSmallReranking (default)
      type: mteb/mind_small
      config: default
      split: test
      revision: 59042f120c80e8afa9cdbb224f67076cec0fc9a7
    metrics:
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    - type: mrr
      value: 31.923299999999998
    - type: nAUC_map_max
      value: -20.072000000000003
    - type: nAUC_map_std
      value: -4.8503
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      value: 14.178099999999999
    - type: nAUC_mrr_max
      value: -14.7901
    - type: nAUC_mrr_std
      value: -2.8666
    - type: nAUC_mrr_diff1
      value: 13.2767
    - type: main_score
      value: 30.883
  - task:
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    dataset:
      name: MTEB NFCorpus (default)
      type: mteb/nfcorpus
      config: default
      split: test
      revision: ec0fa4fe99da2ff19ca1214b7966684033a58814
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      value: 41.486000000000004
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      value: 39.324
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      value: 36.949
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      value: 33.737
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    - type: ndcg_at_1000
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      value: 5.452
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      value: 9.45
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      value: 10.92
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      value: 12.758
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    - type: map_at_100
      value: 15.93
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      value: 17.422
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      value: 7.8950000000000005
    - type: precision_at_1000
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      value: 43.3437
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    - type: mrr_at_1000
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    - type: nauc_precision_at_1_max
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      value: 42.796800000000005
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    - type: nauc_precision_at_10_max
      value: 41.562599999999996
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      value: 24.7635
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      value: 10.837900000000001
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      value: 37.2421
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    - type: nauc_mrr_at_1_max
      value: 34.747699999999995
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      value: 36.0582
    - type: nauc_mrr_at_3_max
      value: 40.8392
    - type: nauc_mrr_at_3_std
      value: 24.9403
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      value: 33.9575
    - type: nauc_mrr_at_5_max
      value: 42.2108
    - type: nauc_mrr_at_5_std
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      value: 33.8034
    - type: nauc_mrr_at_10_max
      value: 42.180800000000005
    - type: nauc_mrr_at_10_std
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      value: 33.151
    - type: nauc_mrr_at_20_max
      value: 42.4685
    - type: nauc_mrr_at_20_std
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    - type: nauc_mrr_at_100_max
      value: 42.417
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    - type: nauc_mrr_at_1000_max
      value: 42.3902
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      value: 27.019
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    - type: main_score
      value: 33.737
  - task:
      type: Retrieval
    dataset:
      name: MTEB NQ (default)
      type: mteb/nq
      config: default
      split: test
      revision: b774495ed302d8c44a3a7ea25c90dbce03968f31
    metrics:
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      value: 32.793
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      value: 42.782
    - type: ndcg_at_5
      value: 47.554
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      value: 51.63100000000001
    - type: ndcg_at_20
      value: 54.005
    - type: ndcg_at_100
      value: 56.287
    - type: ndcg_at_1000
      value: 56.949000000000005
    - type: map_at_1
      value: 29.022
    - type: map_at_3
      value: 39.045
    - type: map_at_5
      value: 41.86
    - type: map_at_10
      value: 43.730000000000004
    - type: map_at_20
      value: 44.478
    - type: map_at_100
      value: 44.849
    - type: map_at_1000
      value: 44.877
    - type: recall_at_1
      value: 29.022
    - type: recall_at_3
      value: 50.40599999999999
    - type: recall_at_5
      value: 61.45
    - type: recall_at_10
      value: 73.32499999999999
    - type: recall_at_20
      value: 82.06099999999999
    - type: recall_at_100
      value: 93.455
    - type: recall_at_1000
      value: 98.414
    - type: precision_at_1
      value: 32.793
    - type: precision_at_3
      value: 19.583000000000002
    - type: precision_at_5
      value: 14.484
    - type: precision_at_10
      value: 8.737
    - type: precision_at_20
      value: 4.928
    - type: precision_at_100
      value: 1.134
    - type: precision_at_1000
      value: 0.12
    - type: mrr_at_1
      value: 32.821600000000004
    - type: mrr_at_3
      value: 42.275
    - type: mrr_at_5
      value: 44.7895
    - type: mrr_at_10
      value: 46.2574
    - type: mrr_at_20
      value: 46.8249
    - type: mrr_at_100
      value: 47.0971
    - type: mrr_at_1000
      value: 47.1157
    - type: nauc_ndcg_at_1_max
      value: 23.167299999999997
    - type: nauc_ndcg_at_1_std
      value: -4.5794
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      value: 31.1021
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      value: -4.8229
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      value: 26.442
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      value: -3.9125
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  - task:
      type: Retrieval
    dataset:
      name: MTEB QuoraRetrieval (default)
      type: mteb/quora
      config: default
      split: test
      revision: e4e08e0b7dbe3c8700f0daef558ff32256715259
    metrics:
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  - task:
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    dataset:
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      type: mteb/reddit-clustering
      config: default
      split: test
      revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
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  - task:
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    dataset:
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      type: mteb/reddit-clustering-p2p
      config: default
      split: test
      revision: 385e3cb46b4cfa89021f56c4380204149d0efe33
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    - type: main_score
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  - task:
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      type: mteb/scidocs
      config: default
      split: test
      revision: f8c2fcf00f625baaa80f62ec5bd9e1fff3b8ae88
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  - task:
      type: STS
    dataset:
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      type: mteb/sickr-sts
      config: default
      split: test
      revision: 20a6d6f312dd54037fe07a32d58e5e168867909d
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    - type: main_score
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  - task:
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    dataset:
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      type: mteb/sts12-sts
      config: default
      split: test
      revision: a0d554a64d88156834ff5ae9920b964011b16384
    metrics:
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    - type: cosine_pearson
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    - type: cosine_spearman
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    - type: manhattan_pearson
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    - type: euclidean_pearson
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    - type: main_score
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  - task:
      type: STS
    dataset:
      name: MTEB STS13 (default)
      type: mteb/sts13-sts
      config: default
      split: test
      revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
    metrics:
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    - type: spearman
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    - type: cosine_pearson
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    - type: cosine_spearman
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    - type: manhattan_pearson
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    - type: manhattan_spearman
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    - type: euclidean_pearson
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    - type: main_score
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  - task:
      type: STS
    dataset:
      name: MTEB STS14 (default)
      type: mteb/sts14-sts
      config: default
      split: test
      revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
    metrics:
    - type: pearson
      value: 75.6791
    - type: spearman
      value: 70.1701
    - type: cosine_pearson
      value: 75.6791
    - type: cosine_spearman
      value: 70.1701
    - type: manhattan_pearson
      value: 73.85239999999999
    - type: manhattan_spearman
      value: 69.9223
    - type: euclidean_pearson
      value: 74.143
    - type: euclidean_spearman
      value: 70.1701
    - type: main_score
      value: 70.1701
  - task:
      type: STS
    dataset:
      name: MTEB STS15 (default)
      type: mteb/sts15-sts
      config: default
      split: test
      revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
    metrics:
    - type: pearson
      value: 80.4413
    - type: spearman
      value: 82.0343
    - type: cosine_pearson
      value: 80.4413
    - type: cosine_spearman
      value: 82.0343
    - type: manhattan_pearson
      value: 81.3627
    - type: manhattan_spearman
      value: 81.8838
    - type: euclidean_pearson
      value: 81.47569999999999
    - type: euclidean_spearman
      value: 82.0343
    - type: main_score
      value: 82.0343
  - task:
      type: STS
    dataset:
      name: MTEB STS16 (default)
      type: mteb/sts16-sts
      config: default
      split: test
      revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
    metrics:
    - type: pearson
      value: 77.172
    - type: spearman
      value: 78.9633
    - type: cosine_pearson
      value: 77.172
    - type: cosine_spearman
      value: 78.9633
    - type: manhattan_pearson
      value: 78.35849999999999
    - type: manhattan_spearman
      value: 78.7975
    - type: euclidean_pearson
      value: 78.5236
    - type: euclidean_spearman
      value: 78.9633
    - type: main_score
      value: 78.9633
  - task:
      type: STS
    dataset:
      name: MTEB STS17 (en-en)
      type: mteb/sts17-crosslingual-sts
      config: en-en
      split: test
      revision: faeb762787bd10488a50c8b5be4a3b82e411949c
    metrics:
    - type: pearson
      value: 83.5117
    - type: spearman
      value: 84.64970000000001
    - type: cosine_pearson
      value: 83.5117
    - type: cosine_spearman
      value: 84.64970000000001
    - type: manhattan_pearson
      value: 84.5137
    - type: manhattan_spearman
      value: 84.7848
    - type: euclidean_pearson
      value: 84.531
    - type: euclidean_spearman
      value: 84.64970000000001
    - type: main_score
      value: 84.64970000000001
  - task:
      type: STS
    dataset:
      name: MTEB STS17 (es-en)
      type: mteb/sts17-crosslingual-sts
      config: es-en
      split: test
      revision: faeb762787bd10488a50c8b5be4a3b82e411949c
    metrics:
    - type: pearson
      value: 29.0052
    - type: spearman
      value: 30.640299999999996
    - type: cosine_pearson
      value: 29.0052
    - type: cosine_spearman
      value: 30.640299999999996
    - type: manhattan_pearson
      value: 25.988099999999996
    - type: manhattan_spearman
      value: 26.935399999999998
    - type: euclidean_pearson
      value: 28.5366
    - type: euclidean_spearman
      value: 30.640299999999996
    - type: main_score
      value: 30.640299999999996
  - task:
      type: STS
    dataset:
      name: MTEB STS17 (nl-en)
      type: mteb/sts17-crosslingual-sts
      config: nl-en
      split: test
      revision: faeb762787bd10488a50c8b5be4a3b82e411949c
    metrics:
    - type: pearson
      value: 42.0755
    - type: spearman
      value: 39.763999999999996
    - type: cosine_pearson
      value: 42.0755
    - type: cosine_spearman
      value: 39.763999999999996
    - type: manhattan_pearson
      value: 40.872
    - type: manhattan_spearman
      value: 38.4749
    - type: euclidean_pearson
      value: 42.051500000000004
    - type: euclidean_spearman
      value: 39.7565
    - type: main_score
      value: 39.763999999999996
  - task:
      type: STS
    dataset:
      name: MTEB STS17 (en-de)
      type: mteb/sts17-crosslingual-sts
      config: en-de
      split: test
      revision: faeb762787bd10488a50c8b5be4a3b82e411949c
    metrics:
    - type: pearson
      value: 44.2318
    - type: spearman
      value: 46.5518
    - type: cosine_pearson
      value: 44.2318
    - type: cosine_spearman
      value: 46.5518
    - type: manhattan_pearson
      value: 43.396699999999996
    - type: manhattan_spearman
      value: 46.1132
    - type: euclidean_pearson
      value: 43.993500000000004
    - type: euclidean_spearman
      value: 46.5518
    - type: main_score
      value: 46.5518
  - task:
      type: STS
    dataset:
      name: MTEB STS17 (fr-en)
      type: mteb/sts17-crosslingual-sts
      config: fr-en
      split: test
      revision: faeb762787bd10488a50c8b5be4a3b82e411949c
    metrics:
    - type: pearson
      value: 36.716100000000004
    - type: spearman
      value: 34.6968
    - type: cosine_pearson
      value: 36.716100000000004
    - type: cosine_spearman
      value: 34.6968
    - type: manhattan_pearson
      value: 35.1918
    - type: manhattan_spearman
      value: 33.3692
    - type: euclidean_pearson
      value: 36.3921
    - type: euclidean_spearman
      value: 34.6968
    - type: main_score
      value: 34.6968
  - task:
      type: STS
    dataset:
      name: MTEB STS17 (en-ar)
      type: mteb/sts17-crosslingual-sts
      config: en-ar
      split: test
      revision: faeb762787bd10488a50c8b5be4a3b82e411949c
    metrics:
    - type: pearson
      value: 21.2825
    - type: spearman
      value: 17.6922
    - type: cosine_pearson
      value: 21.2825
    - type: cosine_spearman
      value: 17.6922
    - type: manhattan_pearson
      value: 19.491
    - type: manhattan_spearman
      value: 15.989700000000001
    - type: euclidean_pearson
      value: 21.583
    - type: euclidean_spearman
      value: 17.6922
    - type: main_score
      value: 17.6922
  - task:
      type: STS
    dataset:
      name: MTEB STS17 (it-en)
      type: mteb/sts17-crosslingual-sts
      config: it-en
      split: test
      revision: faeb762787bd10488a50c8b5be4a3b82e411949c
    metrics:
    - type: pearson
      value: 32.1584
    - type: spearman
      value: 27.9254
    - type: cosine_pearson
      value: 32.1584
    - type: cosine_spearman
      value: 27.9254
    - type: manhattan_pearson
      value: 34.2047
    - type: manhattan_spearman
      value: 31.1955
    - type: euclidean_pearson
      value: 32.4369
    - type: euclidean_spearman
      value: 27.9254
    - type: main_score
      value: 27.9254
  - task:
      type: STS
    dataset:
      name: MTEB STS17 (en-tr)
      type: mteb/sts17-crosslingual-sts
      config: en-tr
      split: test
      revision: faeb762787bd10488a50c8b5be4a3b82e411949c
    metrics:
    - type: pearson
      value: 21.0842
    - type: spearman
      value: 18.5115
    - type: cosine_pearson
      value: 21.0842
    - type: cosine_spearman
      value: 18.5115
    - type: manhattan_pearson
      value: 23.5904
    - type: manhattan_spearman
      value: 21.032400000000003
    - type: euclidean_pearson
      value: 21.2805
    - type: euclidean_spearman
      value: 18.5115
    - type: main_score
      value: 18.5115
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (en)
      type: mteb/sts22-crosslingual-sts
      config: en
      split: test
      revision: de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3
    metrics:
    - type: pearson
      value: 66.9563
    - type: spearman
      value: 67.4747
    - type: cosine_pearson
      value: 66.9563
    - type: cosine_spearman
      value: 67.4747
    - type: manhattan_pearson
      value: 68.32629999999999
    - type: manhattan_spearman
      value: 66.8163
    - type: euclidean_pearson
      value: 68.731
    - type: euclidean_spearman
      value: 67.4747
    - type: main_score
      value: 67.4747
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (de-en)
      type: mteb/sts22-crosslingual-sts
      config: de-en
      split: test
      revision: de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3
    metrics:
    - type: pearson
      value: 56.3095
    - type: spearman
      value: 54.1005
    - type: cosine_pearson
      value: 56.3095
    - type: cosine_spearman
      value: 54.1005
    - type: manhattan_pearson
      value: 59.4023
    - type: manhattan_spearman
      value: 52.6259
    - type: euclidean_pearson
      value: 58.6527
    - type: euclidean_spearman
      value: 54.1005
    - type: main_score
      value: 54.1005
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (es-en)
      type: mteb/sts22-crosslingual-sts
      config: es-en
      split: test
      revision: de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3
    metrics:
    - type: pearson
      value: 62.0575
    - type: spearman
      value: 66.9527
    - type: cosine_pearson
      value: 62.0575
    - type: cosine_spearman
      value: 66.9527
    - type: manhattan_pearson
      value: 62.648700000000005
    - type: manhattan_spearman
      value: 65.6446
    - type: euclidean_pearson
      value: 63.546800000000005
    - type: euclidean_spearman
      value: 66.9527
    - type: main_score
      value: 66.9527
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (pl-en)
      type: mteb/sts22-crosslingual-sts
      config: pl-en
      split: test
      revision: de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3
    metrics:
    - type: pearson
      value: 68.42439999999999
    - type: spearman
      value: 69.0444
    - type: cosine_pearson
      value: 68.42439999999999
    - type: cosine_spearman
      value: 69.0444
    - type: manhattan_pearson
      value: 65.1492
    - type: manhattan_spearman
      value: 65.2364
    - type: euclidean_pearson
      value: 68.4923
    - type: euclidean_spearman
      value: 69.0444
    - type: main_score
      value: 69.0444
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (zh-en)
      type: mteb/sts22-crosslingual-sts
      config: zh-en
      split: test
      revision: de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3
    metrics:
    - type: pearson
      value: 34.164699999999996
    - type: spearman
      value: 36.1776
    - type: cosine_pearson
      value: 34.164699999999996
    - type: cosine_spearman
      value: 36.1776
    - type: manhattan_pearson
      value: 33.0685
    - type: manhattan_spearman
      value: 34.4054
    - type: euclidean_pearson
      value: 34.1002
    - type: euclidean_spearman
      value: 36.1776
    - type: main_score
      value: 36.1776
  - task:
      type: STS
    dataset:
      name: MTEB STSBenchmark (default)
      type: mteb/stsbenchmark-sts
      config: default
      split: test
      revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
    metrics:
    - type: pearson
      value: 78.0802
    - type: spearman
      value: 78.0444
    - type: cosine_pearson
      value: 78.0802
    - type: cosine_spearman
      value: 78.0444
    - type: manhattan_pearson
      value: 78.0703
    - type: manhattan_spearman
      value: 77.681
    - type: euclidean_pearson
      value: 78.4998
    - type: euclidean_spearman
      value: 78.0444
    - type: main_score
      value: 78.0444
  - task:
      type: Reranking
    dataset:
      name: MTEB SciDocsRR (default)
      type: mteb/scidocs-reranking
      config: default
      split: test
      revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
    metrics:
    - type: map
      value: 86.4489
    - type: mrr
      value: 96.0178
    - type: nAUC_map_max
      value: 49.2333
    - type: nAUC_map_std
      value: 63.6541
    - type: nAUC_map_diff1
      value: 0.40959999999999996
    - type: nAUC_mrr_max
      value: 83.6216
    - type: nAUC_mrr_std
      value: 76.7559
    - type: nAUC_mrr_diff1
      value: 42.9429
    - type: main_score
      value: 86.4489
  - task:
      type: Retrieval
    dataset:
      name: MTEB SciFact (default)
      type: mteb/scifact
      config: default
      split: test
      revision: 0228b52cf27578f30900b9e5271d331663a030d7
    metrics:
    - type: ndcg_at_1
      value: 59.333000000000006
    - type: ndcg_at_3
      value: 65.793
    - type: ndcg_at_5
      value: 69.429
    - type: ndcg_at_10
      value: 71.27
    - type: ndcg_at_20
      value: 72.929
    - type: ndcg_at_100
      value: 73.88900000000001
    - type: ndcg_at_1000
      value: 74.41
    - type: map_at_1
      value: 56.577999999999996
    - type: map_at_3
      value: 63.416
    - type: map_at_5
      value: 65.77
    - type: map_at_10
      value: 66.725
    - type: map_at_20
      value: 67.24799999999999
    - type: map_at_100
      value: 67.379
    - type: map_at_1000
      value: 67.4
    - type: recall_at_1
      value: 56.577999999999996
    - type: recall_at_3
      value: 70.072
    - type: recall_at_5
      value: 79.011
    - type: recall_at_10
      value: 84.2
    - type: recall_at_20
      value: 90.5
    - type: recall_at_100
      value: 95.667
    - type: recall_at_1000
      value: 99.667
    - type: precision_at_1
      value: 59.333000000000006
    - type: precision_at_3
      value: 25.556
    - type: precision_at_5
      value: 17.666999999999998
    - type: precision_at_10
      value: 9.6
    - type: precision_at_20
      value: 5.167
    - type: precision_at_100
      value: 1.087
    - type: precision_at_1000
      value: 0.11299999999999999
    - type: mrr_at_1
      value: 59.3333
    - type: mrr_at_3
      value: 64.9444
    - type: mrr_at_5
      value: 66.9278
    - type: mrr_at_10
      value: 67.5327
    - type: mrr_at_20
      value: 67.9354
    - type: mrr_at_100
      value: 68.0616
    - type: mrr_at_1000
      value: 68.08239999999999
    - type: nauc_ndcg_at_1_max
      value: 62.536199999999994
    - type: nauc_ndcg_at_1_std
      value: 4.3275
    - type: nauc_ndcg_at_1_diff1
      value: 78.2294
    - type: nauc_ndcg_at_3_max
      value: 63.0626
    - type: nauc_ndcg_at_3_std
      value: 6.0584
    - type: nauc_ndcg_at_3_diff1
      value: 74.4931
    - type: nauc_ndcg_at_5_max
      value: 64.73989999999999
    - type: nauc_ndcg_at_5_std
      value: 5.6514
    - type: nauc_ndcg_at_5_diff1
      value: 73.5498
    - type: nauc_ndcg_at_10_max
      value: 65.43090000000001
    - type: nauc_ndcg_at_10_std
      value: 9.1274
    - type: nauc_ndcg_at_10_diff1
      value: 72.4814
    - type: nauc_ndcg_at_20_max
      value: 65.7156
    - type: nauc_ndcg_at_20_std
      value: 9.9385
    - type: nauc_ndcg_at_20_diff1
      value: 73.0996
    - type: nauc_ndcg_at_100_max
      value: 65.5687
    - type: nauc_ndcg_at_100_std
      value: 8.818299999999999
    - type: nauc_ndcg_at_100_diff1
      value: 73.6361
    - type: nauc_ndcg_at_1000_max
      value: 65.1956
    - type: nauc_ndcg_at_1000_std
      value: 8.4772
    - type: nauc_ndcg_at_1000_diff1
      value: 74.0393
    - type: nauc_map_at_1_max
      value: 58.2314
    - type: nauc_map_at_1_std
      value: -2.7946
    - type: nauc_map_at_1_diff1
      value: 78.24940000000001
    - type: nauc_map_at_3_max
      value: 61.364200000000004
    - type: nauc_map_at_3_std
      value: 2.7072
    - type: nauc_map_at_3_diff1
      value: 75.4798
    - type: nauc_map_at_5_max
      value: 63.1297
    - type: nauc_map_at_5_std
      value: 3.9505
    - type: nauc_map_at_5_diff1
      value: 74.9693
    - type: nauc_map_at_10_max
      value: 63.6643
    - type: nauc_map_at_10_std
      value: 5.8328999999999995
    - type: nauc_map_at_10_diff1
      value: 74.5464
    - type: nauc_map_at_20_max
      value: 63.8666
    - type: nauc_map_at_20_std
      value: 6.1967
    - type: nauc_map_at_20_diff1
      value: 74.7224
    - type: nauc_map_at_100_max
      value: 63.8254
    - type: nauc_map_at_100_std
      value: 6.0627
    - type: nauc_map_at_100_diff1
      value: 74.791
    - type: nauc_map_at_1000_max
      value: 63.811499999999995
    - type: nauc_map_at_1000_std
      value: 6.0484
    - type: nauc_map_at_1000_diff1
      value: 74.807
    - type: nauc_recall_at_1_max
      value: 58.2314
    - type: nauc_recall_at_1_std
      value: -2.7946
    - type: nauc_recall_at_1_diff1
      value: 78.24940000000001
    - type: nauc_recall_at_3_max
      value: 61.132299999999994
    - type: nauc_recall_at_3_std
      value: 6.1988
    - type: nauc_recall_at_3_diff1
      value: 70.7273
    - type: nauc_recall_at_5_max
      value: 66.542
    - type: nauc_recall_at_5_std
      value: 5.7653
    - type: nauc_recall_at_5_diff1
      value: 66.4586
    - type: nauc_recall_at_10_max
      value: 69.3605
    - type: nauc_recall_at_10_std
      value: 19.6237
    - type: nauc_recall_at_10_diff1
      value: 60.2814
    - type: nauc_recall_at_20_max
      value: 72.6154
    - type: nauc_recall_at_20_std
      value: 31.3504
    - type: nauc_recall_at_20_diff1
      value: 58.8899
    - type: nauc_recall_at_100_max
      value: 78.6002
    - type: nauc_recall_at_100_std
      value: 26.484999999999996
    - type: nauc_recall_at_100_diff1
      value: 56.4605
    - type: nauc_recall_at_1000_max
      value: 55.415499999999994
    - type: nauc_recall_at_1000_std
      value: 72.2222
    - type: nauc_recall_at_1000_diff1
      value: 35.8077
    - type: nauc_precision_at_1_max
      value: 62.536199999999994
    - type: nauc_precision_at_1_std
      value: 4.3275
    - type: nauc_precision_at_1_diff1
      value: 78.2294
    - type: nauc_precision_at_3_max
      value: 53.5524
    - type: nauc_precision_at_3_std
      value: 23.5724
    - type: nauc_precision_at_3_diff1
      value: 47.5389
    - type: nauc_precision_at_5_max
      value: 49.1594
    - type: nauc_precision_at_5_std
      value: 32.3563
    - type: nauc_precision_at_5_diff1
      value: 28.2105
    - type: nauc_precision_at_10_max
      value: 41.955799999999996
    - type: nauc_precision_at_10_std
      value: 44.039699999999996
    - type: nauc_precision_at_10_diff1
      value: 12.0187
    - type: nauc_precision_at_20_max
      value: 34.2442
    - type: nauc_precision_at_20_std
      value: 50.204899999999995
    - type: nauc_precision_at_20_diff1
      value: -0.1954
    - type: nauc_precision_at_100_max
      value: 26.8264
    - type: nauc_precision_at_100_std
      value: 51.4247
    - type: nauc_precision_at_100_diff1
      value: -11.9827
    - type: nauc_precision_at_1000_max
      value: 17.467
    - type: nauc_precision_at_1000_std
      value: 56.435100000000006
    - type: nauc_precision_at_1000_diff1
      value: -24.2103
    - type: nauc_mrr_at_1_max
      value: 62.536199999999994
    - type: nauc_mrr_at_1_std
      value: 4.3275
    - type: nauc_mrr_at_1_diff1
      value: 78.2294
    - type: nauc_mrr_at_3_max
      value: 64.5911
    - type: nauc_mrr_at_3_std
      value: 7.8005
    - type: nauc_mrr_at_3_diff1
      value: 75.82140000000001
    - type: nauc_mrr_at_5_max
      value: 65.1643
    - type: nauc_mrr_at_5_std
      value: 7.258100000000001
    - type: nauc_mrr_at_5_diff1
      value: 75.2062
    - type: nauc_mrr_at_10_max
      value: 65.3198
    - type: nauc_mrr_at_10_std
      value: 8.2173
    - type: nauc_mrr_at_10_diff1
      value: 74.9449
    - type: nauc_mrr_at_20_max
      value: 65.2169
    - type: nauc_mrr_at_20_std
      value: 8.115400000000001
    - type: nauc_mrr_at_20_diff1
      value: 75.1765
    - type: nauc_mrr_at_100_max
      value: 65.1744
    - type: nauc_mrr_at_100_std
      value: 7.994700000000001
    - type: nauc_mrr_at_100_diff1
      value: 75.2388
    - type: nauc_mrr_at_1000_max
      value: 65.1615
    - type: nauc_mrr_at_1000_std
      value: 7.9817
    - type: nauc_mrr_at_1000_diff1
      value: 75.2553
    - type: main_score
      value: 71.27
  - task:
      type: PairClassification
    dataset:
      name: MTEB SprintDuplicateQuestions (default)
      type: mteb/sprintduplicatequestions-pairclassification
      config: default
      split: test
      revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
    metrics:
    - type: similarity_accuracy
      value: 99.7604
    - type: similarity_accuracy_threshold
      value: 84.88210000000001
    - type: similarity_f1
      value: 87.86359999999999
    - type: similarity_f1_threshold
      value: 84.88210000000001
    - type: similarity_precision
      value: 88.1288
    - type: similarity_recall
      value: 87.6
    - type: similarity_ap
      value: 94.07140000000001
    - type: cosine_accuracy
      value: 99.7604
    - type: cosine_accuracy_threshold
      value: 84.88210000000001
    - type: cosine_f1
      value: 87.86359999999999
    - type: cosine_f1_threshold
      value: 84.88210000000001
    - type: cosine_precision
      value: 88.1288
    - type: cosine_recall
      value: 87.6
    - type: cosine_ap
      value: 94.07140000000001
    - type: manhattan_accuracy
      value: 99.7644
    - type: manhattan_accuracy_threshold
      value: 829.5789
    - type: manhattan_f1
      value: 87.92320000000001
    - type: manhattan_f1_threshold
      value: 840.6424
    - type: manhattan_precision
      value: 88.86619999999999
    - type: manhattan_recall
      value: 87.0
    - type: manhattan_ap
      value: 94.17
    - type: euclidean_accuracy
      value: 99.7604
    - type: euclidean_accuracy_threshold
      value: 54.986999999999995
    - type: euclidean_f1
      value: 87.86359999999999
    - type: euclidean_f1_threshold
      value: 54.986999999999995
    - type: euclidean_precision
      value: 88.1288
    - type: euclidean_recall
      value: 87.6
    - type: euclidean_ap
      value: 94.07140000000001
    - type: dot_accuracy
      value: 99.7604
    - type: dot_accuracy_threshold
      value: 84.88210000000001
    - type: dot_f1
      value: 87.86359999999999
    - type: dot_f1_threshold
      value: 84.88210000000001
    - type: dot_precision
      value: 88.1288
    - type: dot_recall
      value: 87.6
    - type: dot_ap
      value: 94.07140000000001
    - type: max_accuracy
      value: 99.7644
    - type: max_f1
      value: 87.92320000000001
    - type: max_precision
      value: 88.86619999999999
    - type: max_recall
      value: 87.6
    - type: max_ap
      value: 94.17
    - type: main_score
      value: 94.17
  - task:
      type: Clustering
    dataset:
      name: MTEB StackExchangeClustering (default)
      type: mteb/stackexchange-clustering
      config: default
      split: test
      revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
    metrics:
    - type: v_measure
      value: 64.6589
    - type: v_measure_std
      value: 4.734
    - type: main_score
      value: 64.6589
  - task:
      type: Clustering
    dataset:
      name: MTEB StackExchangeClusteringP2P (default)
      type: mteb/stackexchange-clustering-p2p
      config: default
      split: test
      revision: 815ca46b2622cec33ccafc3735d572c266efdb44
    metrics:
    - type: v_measure
      value: 32.9388
    - type: v_measure_std
      value: 1.6312
    - type: main_score
      value: 32.9388
  - task:
      type: Reranking
    dataset:
      name: MTEB StackOverflowDupQuestions (default)
      type: mteb/stackoverflowdupquestions-reranking
      config: default
      split: test
      revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
    metrics:
    - type: map
      value: 52.645399999999995
    - type: mrr
      value: 53.5346
    - type: nAUC_map_max
      value: 12.8874
    - type: nAUC_map_std
      value: 9.2781
    - type: nAUC_map_diff1
      value: 39.864
    - type: nAUC_mrr_max
      value: 13.278
    - type: nAUC_mrr_std
      value: 9.501999999999999
    - type: nAUC_mrr_diff1
      value: 39.409499999999994
    - type: main_score
      value: 52.645399999999995
  - task:
      type: Retrieval
    dataset:
      name: MTEB StackOverflowQA (default)
      type: CoIR-Retrieval/stackoverflow-qa
      config: default
      split: test
      revision: db8f169f3894c14a00251061f957b2063eef2bd5
    metrics:
    - type: ndcg_at_1
      value: 74.97500000000001
    - type: ndcg_at_3
      value: 81.247
    - type: ndcg_at_5
      value: 82.921
    - type: ndcg_at_10
      value: 83.92699999999999
    - type: ndcg_at_20
      value: 84.57000000000001
    - type: ndcg_at_100
      value: 85.095
    - type: ndcg_at_1000
      value: 85.33800000000001
    - type: map_at_1
      value: 74.97500000000001
    - type: map_at_3
      value: 79.781
    - type: map_at_5
      value: 80.711
    - type: map_at_10
      value: 81.126
    - type: map_at_20
      value: 81.308
    - type: map_at_100
      value: 81.389
    - type: map_at_1000
      value: 81.39699999999999
    - type: recall_at_1
      value: 74.97500000000001
    - type: recall_at_3
      value: 85.456
    - type: recall_at_5
      value: 89.519
    - type: recall_at_10
      value: 92.628
    - type: recall_at_20
      value: 95.135
    - type: recall_at_100
      value: 97.844
    - type: recall_at_1000
      value: 99.799
    - type: precision_at_1
      value: 74.97500000000001
    - type: precision_at_3
      value: 28.485
    - type: precision_at_5
      value: 17.904
    - type: precision_at_10
      value: 9.263
    - type: precision_at_20
      value: 4.757
    - type: precision_at_100
      value: 0.9780000000000001
    - type: precision_at_1000
      value: 0.1
    - type: mrr_at_1
      value: 74.9749
    - type: mrr_at_3
      value: 79.781
    - type: mrr_at_5
      value: 80.7113
    - type: mrr_at_10
      value: 81.12610000000001
    - type: mrr_at_20
      value: 81.30760000000001
    - type: mrr_at_100
      value: 81.38889999999999
    - type: mrr_at_1000
      value: 81.3974
    - type: nauc_ndcg_at_1_max
      value: 76.1721
    - type: nauc_ndcg_at_1_std
      value: -5.5159
    - type: nauc_ndcg_at_1_diff1
      value: 84.6697
    - type: nauc_ndcg_at_3_max
      value: 78.27629999999999
    - type: nauc_ndcg_at_3_std
      value: -1.2
    - type: nauc_ndcg_at_3_diff1
      value: 81.1214
    - type: nauc_ndcg_at_5_max
      value: 77.7687
    - type: nauc_ndcg_at_5_std
      value: -1.8698
    - type: nauc_ndcg_at_5_diff1
      value: 80.9252
    - type: nauc_ndcg_at_10_max
      value: 77.8029
    - type: nauc_ndcg_at_10_std
      value: -1.5579
    - type: nauc_ndcg_at_10_diff1
      value: 81.1043
    - type: nauc_ndcg_at_20_max
      value: 77.79310000000001
    - type: nauc_ndcg_at_20_std
      value: -1.7669000000000001
    - type: nauc_ndcg_at_20_diff1
      value: 81.4121
    - type: nauc_ndcg_at_100_max
      value: 77.7522
    - type: nauc_ndcg_at_100_std
      value: -1.4502
    - type: nauc_ndcg_at_100_diff1
      value: 81.684
    - type: nauc_ndcg_at_1000_max
      value: 77.6032
    - type: nauc_ndcg_at_1000_std
      value: -2.0256
    - type: nauc_ndcg_at_1000_diff1
      value: 81.7641
    - type: nauc_map_at_1_max
      value: 76.1721
    - type: nauc_map_at_1_std
      value: -5.5159
    - type: nauc_map_at_1_diff1
      value: 84.6697
    - type: nauc_map_at_3_max
      value: 77.6991
    - type: nauc_map_at_3_std
      value: -2.3189
    - type: nauc_map_at_3_diff1
      value: 82.0708
    - type: nauc_map_at_5_max
      value: 77.4286
    - type: nauc_map_at_5_std
      value: -2.721
    - type: nauc_map_at_5_diff1
      value: 82.0265
    - type: nauc_map_at_10_max
      value: 77.4212
    - type: nauc_map_at_10_std
      value: -2.633
    - type: nauc_map_at_10_diff1
      value: 82.109
    - type: nauc_map_at_20_max
      value: 77.4188
    - type: nauc_map_at_20_std
      value: -2.6752000000000002
    - type: nauc_map_at_20_diff1
      value: 82.19340000000001
    - type: nauc_map_at_100_max
      value: 77.4169
    - type: nauc_map_at_100_std
      value: -2.6487
    - type: nauc_map_at_100_diff1
      value: 82.2353
    - type: nauc_map_at_1000_max
      value: 77.413
    - type: nauc_map_at_1000_std
      value: -2.6639
    - type: nauc_map_at_1000_diff1
      value: 82.238
    - type: nauc_recall_at_1_max
      value: 76.1721
    - type: nauc_recall_at_1_std
      value: -5.5159
    - type: nauc_recall_at_1_diff1
      value: 84.6697
    - type: nauc_recall_at_3_max
      value: 80.4678
    - type: nauc_recall_at_3_std
      value: 3.0113000000000003
    - type: nauc_recall_at_3_diff1
      value: 77.5303
    - type: nauc_recall_at_5_max
      value: 79.2732
    - type: nauc_recall_at_5_std
      value: 2.0842
    - type: nauc_recall_at_5_diff1
      value: 75.5155
    - type: nauc_recall_at_10_max
      value: 80.2527
    - type: nauc_recall_at_10_std
      value: 5.7078
    - type: nauc_recall_at_10_diff1
      value: 74.4861
    - type: nauc_recall_at_20_max
      value: 81.29950000000001
    - type: nauc_recall_at_20_std
      value: 6.5553
    - type: nauc_recall_at_20_diff1
      value: 74.5628
    - type: nauc_recall_at_100_max
      value: 83.8742
    - type: nauc_recall_at_100_std
      value: 28.4213
    - type: nauc_recall_at_100_diff1
      value: 74.4027
    - type: nauc_recall_at_1000_max
      value: 60.9178
    - type: nauc_recall_at_1000_std
      value: -2.6599
    - type: nauc_recall_at_1000_diff1
      value: 47.6074
    - type: nauc_precision_at_1_max
      value: 76.1721
    - type: nauc_precision_at_1_std
      value: -5.5159
    - type: nauc_precision_at_1_diff1
      value: 84.6697
    - type: nauc_precision_at_3_max
      value: 80.4678
    - type: nauc_precision_at_3_std
      value: 3.0113000000000003
    - type: nauc_precision_at_3_diff1
      value: 77.5303
    - type: nauc_precision_at_5_max
      value: 79.2732
    - type: nauc_precision_at_5_std
      value: 2.0842
    - type: nauc_precision_at_5_diff1
      value: 75.5155
    - type: nauc_precision_at_10_max
      value: 80.2527
    - type: nauc_precision_at_10_std
      value: 5.7078
    - type: nauc_precision_at_10_diff1
      value: 74.4861
    - type: nauc_precision_at_20_max
      value: 81.29950000000001
    - type: nauc_precision_at_20_std
      value: 6.5553
    - type: nauc_precision_at_20_diff1
      value: 74.5628
    - type: nauc_precision_at_100_max
      value: 83.8742
    - type: nauc_precision_at_100_std
      value: 28.4213
    - type: nauc_precision_at_100_diff1
      value: 74.4027
    - type: nauc_precision_at_1000_max
      value: 60.9178
    - type: nauc_precision_at_1000_std
      value: -2.6599
    - type: nauc_precision_at_1000_diff1
      value: 47.6074
    - type: nauc_mrr_at_1_max
      value: 76.1721
    - type: nauc_mrr_at_1_std
      value: -5.5159
    - type: nauc_mrr_at_1_diff1
      value: 84.6697
    - type: nauc_mrr_at_3_max
      value: 77.6991
    - type: nauc_mrr_at_3_std
      value: -2.3189
    - type: nauc_mrr_at_3_diff1
      value: 82.0708
    - type: nauc_mrr_at_5_max
      value: 77.4286
    - type: nauc_mrr_at_5_std
      value: -2.721
    - type: nauc_mrr_at_5_diff1
      value: 82.0265
    - type: nauc_mrr_at_10_max
      value: 77.4212
    - type: nauc_mrr_at_10_std
      value: -2.633
    - type: nauc_mrr_at_10_diff1
      value: 82.109
    - type: nauc_mrr_at_20_max
      value: 77.4188
    - type: nauc_mrr_at_20_std
      value: -2.6752000000000002
    - type: nauc_mrr_at_20_diff1
      value: 82.19340000000001
    - type: nauc_mrr_at_100_max
      value: 77.4169
    - type: nauc_mrr_at_100_std
      value: -2.6487
    - type: nauc_mrr_at_100_diff1
      value: 82.2353
    - type: nauc_mrr_at_1000_max
      value: 77.413
    - type: nauc_mrr_at_1000_std
      value: -2.6639
    - type: nauc_mrr_at_1000_diff1
      value: 82.238
    - type: main_score
      value: 83.92699999999999
  - task:
      type: Summarization
    dataset:
      name: MTEB SummEval (default)
      type: mteb/summeval
      config: default
      split: test
      revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
    metrics:
    - type: pearson
      value: 29.8395
    - type: spearman
      value: 29.383
    - type: cosine_spearman
      value: 29.383
    - type: cosine_pearson
      value: 29.8395
    - type: dot_spearman
      value: 29.383
    - type: dot_pearson
      value: 29.8395
    - type: main_score
      value: 29.383
  - task:
      type: Retrieval
    dataset:
      name: MTEB SyntheticText2SQL (default)
      type: CoIR-Retrieval/synthetic-text2sql
      config: default
      split: test
      revision: 686b87296c3a0191b5d9415a00526c62db9fce09
    metrics:
    - type: ndcg_at_1
      value: 4.222
    - type: ndcg_at_3
      value: 38.329
    - type: ndcg_at_5
      value: 42.076
    - type: ndcg_at_10
      value: 44.775
    - type: ndcg_at_20
      value: 46.528999999999996
    - type: ndcg_at_100
      value: 48.554
    - type: ndcg_at_1000
      value: 49.143
    - type: map_at_1
      value: 4.222
    - type: map_at_3
      value: 30.676
    - type: map_at_5
      value: 32.76
    - type: map_at_10
      value: 33.898
    - type: map_at_20
      value: 34.386
    - type: map_at_100
      value: 34.677
    - type: map_at_1000
      value: 34.701
    - type: recall_at_1
      value: 4.222
    - type: recall_at_3
      value: 60.178
    - type: recall_at_5
      value: 69.253
    - type: recall_at_10
      value: 77.474
    - type: recall_at_20
      value: 84.36200000000001
    - type: recall_at_100
      value: 95.12899999999999
    - type: recall_at_1000
      value: 99.675
    - type: precision_at_1
      value: 4.222
    - type: precision_at_3
      value: 20.058999999999997
    - type: precision_at_5
      value: 13.850999999999999
    - type: precision_at_10
      value: 7.747
    - type: precision_at_20
      value: 4.218
    - type: precision_at_100
      value: 0.951
    - type: precision_at_1000
      value: 0.1
    - type: mrr_at_1
      value: 27.3287
    - type: mrr_at_3
      value: 43.8956
    - type: mrr_at_5
      value: 45.656
    - type: mrr_at_10
      value: 46.6697
    - type: mrr_at_20
      value: 47.1331
    - type: mrr_at_100
      value: 47.4153
    - type: mrr_at_1000
      value: 47.4391
    - type: nauc_ndcg_at_1_max
      value: 16.045
    - type: nauc_ndcg_at_1_std
      value: -8.7715
    - type: nauc_ndcg_at_1_diff1
      value: 48.4886
    - type: nauc_ndcg_at_3_max
      value: 30.771500000000003
    - type: nauc_ndcg_at_3_std
      value: -16.2537
    - type: nauc_ndcg_at_3_diff1
      value: -59.0158
    - type: nauc_ndcg_at_5_max
      value: 30.354
    - type: nauc_ndcg_at_5_std
      value: -16.576
    - type: nauc_ndcg_at_5_diff1
      value: -55.0555
    - type: nauc_ndcg_at_10_max
      value: 30.0579
    - type: nauc_ndcg_at_10_std
      value: -16.3765
    - type: nauc_ndcg_at_10_diff1
      value: -52.5829
    - type: nauc_ndcg_at_20_max
      value: 29.8131
    - type: nauc_ndcg_at_20_std
      value: -15.7493
    - type: nauc_ndcg_at_20_diff1
      value: -51.1605
    - type: nauc_ndcg_at_100_max
      value: 29.9313
    - type: nauc_ndcg_at_100_std
      value: -14.9786
    - type: nauc_ndcg_at_100_diff1
      value: -49.6997
    - type: nauc_ndcg_at_1000_max
      value: 29.7154
    - type: nauc_ndcg_at_1000_std
      value: -15.2567
    - type: nauc_ndcg_at_1000_diff1
      value: -49.660399999999996
    - type: nauc_map_at_1_max
      value: 16.045
    - type: nauc_map_at_1_std
      value: -8.7715
    - type: nauc_map_at_1_diff1
      value: 48.4886
    - type: nauc_map_at_3_max
      value: 29.6122
    - type: nauc_map_at_3_std
      value: -15.509500000000001
    - type: nauc_map_at_3_diff1
      value: -52.033300000000004
    - type: nauc_map_at_5_max
      value: 29.3076
    - type: nauc_map_at_5_std
      value: -15.7
    - type: nauc_map_at_5_diff1
      value: -49.1839
    - type: nauc_map_at_10_max
      value: 29.1468
    - type: nauc_map_at_10_std
      value: -15.564400000000001
    - type: nauc_map_at_10_diff1
      value: -47.7791
    - type: nauc_map_at_20_max
      value: 29.0578
    - type: nauc_map_at_20_std
      value: -15.3635
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      value: -47.2635
    - type: nauc_map_at_100_max
      value: 29.0523
    - type: nauc_map_at_100_std
      value: -15.2602
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      value: -46.9875
    - type: nauc_map_at_1000_max
      value: 29.048299999999998
    - type: nauc_map_at_1000_std
      value: -15.2626
    - type: nauc_map_at_1000_diff1
      value: -46.98
    - type: nauc_recall_at_1_max
      value: 16.045
    - type: nauc_recall_at_1_std
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    - type: nauc_recall_at_1_diff1
      value: 48.4886
    - type: nauc_recall_at_3_max
      value: 32.8552
    - type: nauc_recall_at_3_std
      value: -17.6374
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      value: -71.1273
    - type: nauc_recall_at_5_max
      value: 32.378299999999996
    - type: nauc_recall_at_5_std
      value: -18.411
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      value: -65.7517
    - type: nauc_recall_at_10_max
      value: 32.041799999999995
    - type: nauc_recall_at_10_std
      value: -18.4057
    - type: nauc_recall_at_10_diff1
      value: -62.019999999999996
    - type: nauc_recall_at_20_max
      value: 31.663999999999998
    - type: nauc_recall_at_20_std
      value: -16.352800000000002
    - type: nauc_recall_at_20_diff1
      value: -59.1186
    - type: nauc_recall_at_100_max
      value: 37.872499999999995
    - type: nauc_recall_at_100_std
      value: -4.3914
    - type: nauc_recall_at_100_diff1
      value: -51.8363
    - type: nauc_recall_at_1000_max
      value: 59.5105
    - type: nauc_recall_at_1000_std
      value: 23.3375
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      value: -37.7379
    - type: nauc_mrr_at_10_std
      value: -6.2844
    - type: nauc_mrr_at_10_diff1
      value: -0.6525000000000001
    - type: nauc_mrr_at_20_max
      value: -38.4522
    - type: nauc_mrr_at_20_std
      value: -5.0927
    - type: nauc_mrr_at_20_diff1
      value: -0.2814
    - type: nauc_mrr_at_100_max
      value: -38.1599
    - type: nauc_mrr_at_100_std
      value: -5.2147
    - type: nauc_mrr_at_100_diff1
      value: -0.7001000000000001
    - type: nauc_mrr_at_1000_max
      value: -38.1599
    - type: nauc_mrr_at_1000_std
      value: -5.2147
    - type: nauc_mrr_at_1000_diff1
      value: -0.7001000000000001
    - type: main_score
      value: 24.029
  - task:
      type: Classification
    dataset:
      name: MTEB ToxicConversationsClassification (default)
      type: mteb/toxic_conversations_50k
      config: default
      split: test
      revision: edfaf9da55d3dd50d43143d90c1ac476895ae6de
    metrics:
    - type: accuracy
      value: 62.9395
    - type: f1
      value: 47.7133
    - type: f1_weighted
      value: 71.0525
    - type: ap
      value: 10.306600000000001
    - type: ap_weighted
      value: 10.306600000000001
    - type: main_score
      value: 62.9395
  - task:
      type: Classification
    dataset:
      name: MTEB TweetSentimentExtractionClassification (default)
      type: mteb/tweet_sentiment_extraction
      config: default
      split: test
      revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
    metrics:
    - type: accuracy
      value: 52.8721
    - type: f1
      value: 53.034800000000004
    - type: f1_weighted
      value: 52.4319
    - type: main_score
      value: 52.8721
  - task:
      type: Clustering
    dataset:
      name: MTEB TwentyNewsgroupsClustering (default)
      type: mteb/twentynewsgroups-clustering
      config: default
      split: test
      revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
    metrics:
    - type: v_measure
      value: 44.9227
    - type: v_measure_std
      value: 1.1638000000000002
    - type: main_score
      value: 44.9227
  - task:
      type: PairClassification
    dataset:
      name: MTEB TwitterSemEval2015 (default)
      type: mteb/twittersemeval2015-pairclassification
      config: default
      split: test
      revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
    metrics:
    - type: similarity_accuracy
      value: 82.04090000000001
    - type: similarity_accuracy_threshold
      value: 86.6147
    - type: similarity_f1
      value: 57.258399999999995
    - type: similarity_f1_threshold
      value: 82.9233
    - type: similarity_precision
      value: 52.1456
    - type: similarity_recall
      value: 63.4828
    - type: similarity_ap
      value: 60.0317
    - type: cosine_accuracy
      value: 82.04090000000001
    - type: cosine_accuracy_threshold
      value: 86.6147
    - type: cosine_f1
      value: 57.258399999999995
    - type: cosine_f1_threshold
      value: 82.9233
    - type: cosine_precision
      value: 52.1456
    - type: cosine_recall
      value: 63.4828
    - type: cosine_ap
      value: 60.0317
    - type: manhattan_accuracy
      value: 81.9574
    - type: manhattan_accuracy_threshold
      value: 794.4433
    - type: manhattan_f1
      value: 57.1936
    - type: manhattan_f1_threshold
      value: 898.9445
    - type: manhattan_precision
      value: 51.91480000000001
    - type: manhattan_recall
      value: 63.6675
    - type: manhattan_ap
      value: 59.9255
    - type: euclidean_accuracy
      value: 82.04090000000001
    - type: euclidean_accuracy_threshold
      value: 51.7403
    - type: euclidean_f1
      value: 57.258399999999995
    - type: euclidean_f1_threshold
      value: 58.440999999999995
    - type: euclidean_precision
      value: 52.1456
    - type: euclidean_recall
      value: 63.4828
    - type: euclidean_ap
      value: 60.0317
    - type: dot_accuracy
      value: 82.04090000000001
    - type: dot_accuracy_threshold
      value: 86.6147
    - type: dot_f1
      value: 57.258399999999995
    - type: dot_f1_threshold
      value: 82.9233
    - type: dot_precision
      value: 52.1456
    - type: dot_recall
      value: 63.4828
    - type: dot_ap
      value: 60.0317
    - type: max_accuracy
      value: 82.04090000000001
    - type: max_f1
      value: 57.258399999999995
    - type: max_precision
      value: 52.1456
    - type: max_recall
      value: 63.6675
    - type: max_ap
      value: 60.0317
    - type: main_score
      value: 60.0317
  - task:
      type: PairClassification
    dataset:
      name: MTEB TwitterURLCorpus (default)
      type: mteb/twitterurlcorpus-pairclassification
      config: default
      split: test
      revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
    metrics:
    - type: similarity_accuracy
      value: 87.3035
    - type: similarity_accuracy_threshold
      value: 85.4123
    - type: similarity_f1
      value: 74.5555
    - type: similarity_f1_threshold
      value: 83.7581
    - type: similarity_precision
      value: 72.55369999999999
    - type: similarity_recall
      value: 76.6708
    - type: similarity_ap
      value: 82.42930000000001
    - type: cosine_accuracy
      value: 87.3035
    - type: cosine_accuracy_threshold
      value: 85.4123
    - type: cosine_f1
      value: 74.5555
    - type: cosine_f1_threshold
      value: 83.7581
    - type: cosine_precision
      value: 72.55369999999999
    - type: cosine_recall
      value: 76.6708
    - type: cosine_ap
      value: 82.42930000000001
    - type: manhattan_accuracy
      value: 87.3249
    - type: manhattan_accuracy_threshold
      value: 831.9304999999999
    - type: manhattan_f1
      value: 74.8665
    - type: manhattan_f1_threshold
      value: 893.9980999999999
    - type: manhattan_precision
      value: 70.8502
    - type: manhattan_recall
      value: 79.3656
    - type: manhattan_ap
      value: 82.5792
    - type: euclidean_accuracy
      value: 87.3035
    - type: euclidean_accuracy_threshold
      value: 54.014300000000006
    - type: euclidean_f1
      value: 74.5555
    - type: euclidean_f1_threshold
      value: 56.9946
    - type: euclidean_precision
      value: 72.55369999999999
    - type: euclidean_recall
      value: 76.6708
    - type: euclidean_ap
      value: 82.42920000000001
    - type: dot_accuracy
      value: 87.3035
    - type: dot_accuracy_threshold
      value: 85.4123
    - type: dot_f1
      value: 74.5555
    - type: dot_f1_threshold
      value: 83.7581
    - type: dot_precision
      value: 72.55369999999999
    - type: dot_recall
      value: 76.6708
    - type: dot_ap
      value: 82.42920000000001
    - type: max_accuracy
      value: 87.3249
    - type: max_f1
      value: 74.8665
    - type: max_precision
      value: 72.55369999999999
    - type: max_recall
      value: 79.3656
    - type: max_ap
      value: 82.5792
    - type: main_score
      value: 82.5792
---

# danbev/granite-embedding-30m-english-Q8_0-GGUF
This model was converted to GGUF format from [`ibm-granite/granite-embedding-30m-english`](https://huggingface.co/ibm-granite/granite-embedding-30m-english) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space.
Refer to the [original model card](https://huggingface.co/ibm-granite/granite-embedding-30m-english) for more details on the model.

## Use with llama.cpp
Install llama.cpp through brew (works on Mac and Linux)

```bash
brew install llama.cpp

```
Invoke the llama.cpp server or the CLI.

### CLI:
```bash
llama-cli --hf-repo danbev/granite-embedding-30m-english-Q8_0-GGUF --hf-file granite-embedding-30m-english-q8_0.gguf -p "The meaning to life and the universe is"
```

### Server:
```bash
llama-server --hf-repo danbev/granite-embedding-30m-english-Q8_0-GGUF --hf-file granite-embedding-30m-english-q8_0.gguf -c 2048
```

Note: You can also use this checkpoint directly through the [usage steps](https://github.com/ggerganov/llama.cpp?tab=readme-ov-file#usage) listed in the Llama.cpp repo as well.

Step 1: Clone llama.cpp from GitHub.
```
git clone https://github.com/ggerganov/llama.cpp
```

Step 2: Move into the llama.cpp folder and build it with `LLAMA_CURL=1` flag along with other hardware-specific flags (for ex: LLAMA_CUDA=1 for Nvidia GPUs on Linux).
```
cd llama.cpp && LLAMA_CURL=1 make
```

Step 3: Run inference through the main binary.
```
./llama-cli --hf-repo danbev/granite-embedding-30m-english-Q8_0-GGUF --hf-file granite-embedding-30m-english-q8_0.gguf -p "The meaning to life and the universe is"
```
or 
```
./llama-server --hf-repo danbev/granite-embedding-30m-english-Q8_0-GGUF --hf-file granite-embedding-30m-english-q8_0.gguf -c 2048
```
