hxstar
/

bge-large-en-v1.5-Q8_0-GGUF

+---
+tags:
+- sentence-transformers
+- feature-extraction
+- sentence-similarity
+- transformers
+- mteb
+- llama-cpp
+- gguf-my-repo
+license: mit
+language:
+- en
+base_model: BAAI/bge-large-en-v1.5
+model-index:
+- name: bge-large-en-v1.5
+  results:
+  - task:
+      type: Classification
+    dataset:
+      name: MTEB AmazonCounterfactualClassification (en)
+      type: mteb/amazon_counterfactual
+      config: en
+      split: test
+      revision: e8379541af4e31359cca9fbcf4b00f2671dba205
+    metrics:
+    - type: accuracy
+      value: 75.8507462686567
+    - type: ap
+      value: 38.566457320228245
+    - type: f1
+      value: 69.69386648043475
+  - task:
+      type: Classification
+    dataset:
+      name: MTEB AmazonPolarityClassification
+      type: mteb/amazon_polarity
+      config: default
+      split: test
+      revision: e2d317d38cd51312af73b3d32a06d1a08b442046
+    metrics:
+    - type: accuracy
+      value: 92.416675
+    - type: ap
+      value: 89.1928861155922
+    - type: f1
+      value: 92.39477019574215
+  - task:
+      type: Classification
+    dataset:
+      name: MTEB AmazonReviewsClassification (en)
+      type: mteb/amazon_reviews_multi
+      config: en
+      split: test
+      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
+    metrics:
+    - type: accuracy
+      value: 48.175999999999995
+    - type: f1
+      value: 47.80712792870253
+  - task:
+      type: Retrieval
+    dataset:
+      name: MTEB ArguAna
+      type: arguana
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 40.184999999999995
+    - type: map_at_10
+      value: 55.654
+    - type: map_at_100
+      value: 56.25
+    - type: map_at_1000
+      value: 56.255
+    - type: map_at_3
+      value: 51.742999999999995
+    - type: map_at_5
+      value: 54.129000000000005
+    - type: mrr_at_1
+      value: 40.967
+    - type: mrr_at_10
+      value: 55.96
+    - type: mrr_at_100
+      value: 56.54900000000001
+    - type: mrr_at_1000
+      value: 56.554
+    - type: mrr_at_3
+      value: 51.980000000000004
+    - type: mrr_at_5
+      value: 54.44
+    - type: ndcg_at_1
+      value: 40.184999999999995
+    - type: ndcg_at_10
+      value: 63.542
+    - type: ndcg_at_100
+      value: 65.96499999999999
+    - type: ndcg_at_1000
+      value: 66.08699999999999
+    - type: ndcg_at_3
+      value: 55.582
+    - type: ndcg_at_5
+      value: 59.855000000000004
+    - type: precision_at_1
+      value: 40.184999999999995
+    - type: precision_at_10
+      value: 8.841000000000001
+    - type: precision_at_100
+      value: 0.987
+    - type: precision_at_1000
+      value: 0.1
+    - type: precision_at_3
+      value: 22.238
+    - type: precision_at_5
+      value: 15.405
+    - type: recall_at_1
+      value: 40.184999999999995
+    - type: recall_at_10
+      value: 88.407
+    - type: recall_at_100
+      value: 98.72
+    - type: recall_at_1000
+      value: 99.644
+    - type: recall_at_3
+      value: 66.714
+    - type: recall_at_5
+      value: 77.027
+  - task:
+      type: Clustering
+    dataset:
+      name: MTEB ArxivClusteringP2P
+      type: mteb/arxiv-clustering-p2p
+      config: default
+      split: test
+      revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
+    metrics:
+    - type: v_measure
+      value: 48.567077926750066
+  - task:
+      type: Clustering
+    dataset:
+      name: MTEB ArxivClusteringS2S
+      type: mteb/arxiv-clustering-s2s
+      config: default
+      split: test
+      revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
+    metrics:
+    - type: v_measure
+      value: 43.19453389182364
+  - task:
+      type: Reranking
+    dataset:
+      name: MTEB AskUbuntuDupQuestions
+      type: mteb/askubuntudupquestions-reranking
+      config: default
+      split: test
+      revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
+    metrics:
+    - type: map
+      value: 64.46555939623092
+    - type: mrr
+      value: 77.82361605768807
+  - task:
+      type: STS
+    dataset:
+      name: MTEB BIOSSES
+      type: mteb/biosses-sts
+      config: default
+      split: test
+      revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
+    metrics:
+    - type: cos_sim_pearson
+      value: 84.9554128814735
+    - type: cos_sim_spearman
+      value: 84.65373612172036
+    - type: euclidean_pearson
+      value: 83.2905059954138
+    - type: euclidean_spearman
+      value: 84.52240782811128
+    - type: manhattan_pearson
+      value: 82.99533802997436
+    - type: manhattan_spearman
+      value: 84.20673798475734
+  - task:
+      type: Classification
+    dataset:
+      name: MTEB Banking77Classification
+      type: mteb/banking77
+      config: default
+      split: test
+      revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
+    metrics:
+    - type: accuracy
+      value: 87.78896103896103
+    - type: f1
+      value: 87.77189310964883
+  - task:
+      type: Clustering
+    dataset:
+      name: MTEB BiorxivClusteringP2P
+      type: mteb/biorxiv-clustering-p2p
+      config: default
+      split: test
+      revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
+    metrics:
+    - type: v_measure
+      value: 39.714538337650495
+  - task:
+      type: Clustering
+    dataset:
+      name: MTEB BiorxivClusteringS2S
+      type: mteb/biorxiv-clustering-s2s
+      config: default
+      split: test
+      revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
+    metrics:
+    - type: v_measure
+      value: 36.90108349284447
+  - task:
+      type: Retrieval
+    dataset:
+      name: MTEB CQADupstackAndroidRetrieval
+      type: BeIR/cqadupstack
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 32.795
+    - type: map_at_10
+      value: 43.669000000000004
+    - type: map_at_100
+      value: 45.151
+    - type: map_at_1000
+      value: 45.278
+    - type: map_at_3
+      value: 40.006
+    - type: map_at_5
+      value: 42.059999999999995
+    - type: mrr_at_1
+      value: 39.771
+    - type: mrr_at_10
+      value: 49.826
+    - type: mrr_at_100
+      value: 50.504000000000005
+    - type: mrr_at_1000
+      value: 50.549
+    - type: mrr_at_3
+      value: 47.115
+    - type: mrr_at_5
+      value: 48.832
+    - type: ndcg_at_1
+      value: 39.771
+    - type: ndcg_at_10
+      value: 50.217999999999996
+    - type: ndcg_at_100
+      value: 55.454
+    - type: ndcg_at_1000
+      value: 57.37
+    - type: ndcg_at_3
+      value: 44.885000000000005
+    - type: ndcg_at_5
+      value: 47.419
+    - type: precision_at_1
+      value: 39.771
+    - type: precision_at_10
+      value: 9.642000000000001
+    - type: precision_at_100
+      value: 1.538
+    - type: precision_at_1000
+      value: 0.198
+    - type: precision_at_3
+      value: 21.268
+    - type: precision_at_5
+      value: 15.536
+    - type: recall_at_1
+      value: 32.795
+    - type: recall_at_10
+      value: 62.580999999999996
+    - type: recall_at_100
+      value: 84.438
+    - type: recall_at_1000
+      value: 96.492
+    - type: recall_at_3
+      value: 47.071000000000005
+    - type: recall_at_5
+      value: 54.079
+    - type: map_at_1
+      value: 32.671
+    - type: map_at_10
+      value: 43.334
+    - type: map_at_100
+      value: 44.566
+    - type: map_at_1000
+      value: 44.702999999999996
+    - type: map_at_3
+      value: 40.343
+    - type: map_at_5
+      value: 41.983
+    - type: mrr_at_1
+      value: 40.764
+    - type: mrr_at_10
+      value: 49.382
+    - type: mrr_at_100
+      value: 49.988
+    - type: mrr_at_1000
+      value: 50.03300000000001
+    - type: mrr_at_3
+      value: 47.293
+    - type: mrr_at_5
+      value: 48.51
+    - type: ndcg_at_1
+      value: 40.764
+    - type: ndcg_at_10
+      value: 49.039
+    - type: ndcg_at_100
+      value: 53.259
+    - type: ndcg_at_1000
+      value: 55.253
+    - type: ndcg_at_3
+      value: 45.091
+    - type: ndcg_at_5
+      value: 46.839999999999996
+    - type: precision_at_1
+      value: 40.764
+    - type: precision_at_10
+      value: 9.191
+    - type: precision_at_100
+      value: 1.476
+    - type: precision_at_1000
+      value: 0.19499999999999998
+    - type: precision_at_3
+      value: 21.72
+    - type: precision_at_5
+      value: 15.299
+    - type: recall_at_1
+      value: 32.671
+    - type: recall_at_10
+      value: 58.816
+    - type: recall_at_100
+      value: 76.654
+    - type: recall_at_1000
+      value: 89.05999999999999
+    - type: recall_at_3
+      value: 46.743
+    - type: recall_at_5
+      value: 51.783
+    - type: map_at_1
+      value: 40.328
+    - type: map_at_10
+      value: 53.32599999999999
+    - type: map_at_100
+      value: 54.37499999999999
+    - type: map_at_1000
+      value: 54.429
+    - type: map_at_3
+      value: 49.902
+    - type: map_at_5
+      value: 52.002
+    - type: mrr_at_1
+      value: 46.332
+    - type: mrr_at_10
+      value: 56.858
+    - type: mrr_at_100
+      value: 57.522
+    - type: mrr_at_1000
+      value: 57.54899999999999
+    - type: mrr_at_3
+      value: 54.472
+    - type: mrr_at_5
+      value: 55.996
+    - type: ndcg_at_1
+      value: 46.332
+    - type: ndcg_at_10
+      value: 59.313
+    - type: ndcg_at_100
+      value: 63.266999999999996
+    - type: ndcg_at_1000
+      value: 64.36
+    - type: ndcg_at_3
+      value: 53.815000000000005
+    - type: ndcg_at_5
+      value: 56.814
+    - type: precision_at_1
+      value: 46.332
+    - type: precision_at_10
+      value: 9.53
+    - type: precision_at_100
+      value: 1.238
+    - type: precision_at_1000
+      value: 0.13699999999999998
+    - type: precision_at_3
+      value: 24.054000000000002
+    - type: precision_at_5
+      value: 16.589000000000002
+    - type: recall_at_1
+      value: 40.328
+    - type: recall_at_10
+      value: 73.421
+    - type: recall_at_100
+      value: 90.059
+    - type: recall_at_1000
+      value: 97.81
+    - type: recall_at_3
+      value: 59.009
+    - type: recall_at_5
+      value: 66.352
+    - type: map_at_1
+      value: 27.424
+    - type: map_at_10
+      value: 36.332
+    - type: map_at_100
+      value: 37.347
+    - type: map_at_1000
+      value: 37.422
+    - type: map_at_3
+      value: 33.743
+    - type: map_at_5
+      value: 35.176
+    - type: mrr_at_1
+      value: 29.153000000000002
+    - type: mrr_at_10
+      value: 38.233
+    - type: mrr_at_100
+      value: 39.109
+    - type: mrr_at_1000
+      value: 39.164
+    - type: mrr_at_3
+      value: 35.876000000000005
+    - type: mrr_at_5
+      value: 37.169000000000004
+    - type: ndcg_at_1
+      value: 29.153000000000002
+    - type: ndcg_at_10
+      value: 41.439
+    - type: ndcg_at_100
+      value: 46.42
+    - type: ndcg_at_1000
+      value: 48.242000000000004
+    - type: ndcg_at_3
+      value: 36.362
+    - type: ndcg_at_5
+      value: 38.743
+    - type: precision_at_1
+      value: 29.153000000000002
+    - type: precision_at_10
+      value: 6.315999999999999
+    - type: precision_at_100
+      value: 0.927
+    - type: precision_at_1000
+      value: 0.11199999999999999
+    - type: precision_at_3
+      value: 15.443000000000001
+    - type: precision_at_5
+      value: 10.644
+    - type: recall_at_1
+      value: 27.424
+    - type: recall_at_10
+      value: 55.364000000000004
+    - type: recall_at_100
+      value: 78.211
+    - type: recall_at_1000
+      value: 91.74600000000001
+    - type: recall_at_3
+      value: 41.379
+    - type: recall_at_5
+      value: 47.14
+    - type: map_at_1
+      value: 19.601
+    - type: map_at_10
+      value: 27.826
+    - type: map_at_100
+      value: 29.017
+    - type: map_at_1000
+      value: 29.137
+    - type: map_at_3
+      value: 25.125999999999998
+    - type: map_at_5
+      value: 26.765
+    - type: mrr_at_1
+      value: 24.005000000000003
+    - type: mrr_at_10
+      value: 32.716
+    - type: mrr_at_100
+      value: 33.631
+    - type: mrr_at_1000
+      value: 33.694
+    - type: mrr_at_3
+      value: 29.934
+    - type: mrr_at_5
+      value: 31.630999999999997
+    - type: ndcg_at_1
+      value: 24.005000000000003
+    - type: ndcg_at_10
+      value: 33.158
+    - type: ndcg_at_100
+      value: 38.739000000000004
+    - type: ndcg_at_1000
+      value: 41.495
+    - type: ndcg_at_3
+      value: 28.185
+    - type: ndcg_at_5
+      value: 30.796
+    - type: precision_at_1
+      value: 24.005000000000003
+    - type: precision_at_10
+      value: 5.908
+    - type: precision_at_100
+      value: 1.005
+    - type: precision_at_1000
+      value: 0.13899999999999998
+    - type: precision_at_3
+      value: 13.391
+    - type: precision_at_5
+      value: 9.876
+    - type: recall_at_1
+      value: 19.601
+    - type: recall_at_10
+      value: 44.746
+    - type: recall_at_100
+      value: 68.82300000000001
+    - type: recall_at_1000
+      value: 88.215
+    - type: recall_at_3
+      value: 31.239
+    - type: recall_at_5
+      value: 37.695
+    - type: map_at_1
+      value: 30.130000000000003
+    - type: map_at_10
+      value: 40.96
+    - type: map_at_100
+      value: 42.282
+    - type: map_at_1000
+      value: 42.392
+    - type: map_at_3
+      value: 37.889
+    - type: map_at_5
+      value: 39.661
+    - type: mrr_at_1
+      value: 36.958999999999996
+    - type: mrr_at_10
+      value: 46.835
+    - type: mrr_at_100
+      value: 47.644
+    - type: mrr_at_1000
+      value: 47.688
+    - type: mrr_at_3
+      value: 44.562000000000005
+    - type: mrr_at_5
+      value: 45.938
+    - type: ndcg_at_1
+      value: 36.958999999999996
+    - type: ndcg_at_10
+      value: 47.06
+    - type: ndcg_at_100
+      value: 52.345
+    - type: ndcg_at_1000
+      value: 54.35
+    - type: ndcg_at_3
+      value: 42.301
+    - type: ndcg_at_5
+      value: 44.635999999999996
+    - type: precision_at_1
+      value: 36.958999999999996
+    - type: precision_at_10
+      value: 8.479000000000001
+    - type: precision_at_100
+      value: 1.284
+    - type: precision_at_1000
+      value: 0.163
+    - type: precision_at_3
+      value: 20.244
+    - type: precision_at_5
+      value: 14.224999999999998
+    - type: recall_at_1
+      value: 30.130000000000003
+    - type: recall_at_10
+      value: 59.27
+    - type: recall_at_100
+      value: 81.195
+    - type: recall_at_1000
+      value: 94.21199999999999
+    - type: recall_at_3
+      value: 45.885
+    - type: recall_at_5
+      value: 52.016
+    - type: map_at_1
+      value: 26.169999999999998
+    - type: map_at_10
+      value: 36.451
+    - type: map_at_100
+      value: 37.791000000000004
+    - type: map_at_1000
+      value: 37.897
+    - type: map_at_3
+      value: 33.109
+    - type: map_at_5
+      value: 34.937000000000005
+    - type: mrr_at_1
+      value: 32.877
+    - type: mrr_at_10
+      value: 42.368
+    - type: mrr_at_100
+      value: 43.201
+    - type: mrr_at_1000
+      value: 43.259
+    - type: mrr_at_3
+      value: 39.763999999999996
+    - type: mrr_at_5
+      value: 41.260000000000005
+    - type: ndcg_at_1
+      value: 32.877
+    - type: ndcg_at_10
+      value: 42.659000000000006
+    - type: ndcg_at_100
+      value: 48.161
+    - type: ndcg_at_1000
+      value: 50.345
+    - type: ndcg_at_3
+      value: 37.302
+    - type: ndcg_at_5
+      value: 39.722
+    - type: precision_at_1
+      value: 32.877
+    - type: precision_at_10
+      value: 7.9
+    - type: precision_at_100
+      value: 1.236
+    - type: precision_at_1000
+      value: 0.158
+    - type: precision_at_3
+      value: 17.846
+    - type: precision_at_5
+      value: 12.9
+    - type: recall_at_1
+      value: 26.169999999999998
+    - type: recall_at_10
+      value: 55.35
+    - type: recall_at_100
+      value: 78.755
+    - type: recall_at_1000
+      value: 93.518
+    - type: recall_at_3
+      value: 40.176
+    - type: recall_at_5
+      value: 46.589000000000006
+    - type: map_at_1
+      value: 27.15516666666667
+    - type: map_at_10
+      value: 36.65741666666667
+    - type: map_at_100
+      value: 37.84991666666666
+    - type: map_at_1000
+      value: 37.96316666666667
+    - type: map_at_3
+      value: 33.74974999999999
+    - type: map_at_5
+      value: 35.3765
+    - type: mrr_at_1
+      value: 32.08233333333334
+    - type: mrr_at_10
+      value: 41.033833333333334
+    - type: mrr_at_100
+      value: 41.84524999999999
+    - type: mrr_at_1000
+      value: 41.89983333333333
+    - type: mrr_at_3
+      value: 38.62008333333333
+    - type: mrr_at_5
+      value: 40.03441666666666
+    - type: ndcg_at_1
+      value: 32.08233333333334
+    - type: ndcg_at_10
+      value: 42.229
+    - type: ndcg_at_100
+      value: 47.26716666666667
+    - type: ndcg_at_1000
+      value: 49.43466666666667
+    - type: ndcg_at_3
+      value: 37.36408333333333
+    - type: ndcg_at_5
+      value: 39.6715
+    - type: precision_at_1
+      value: 32.08233333333334
+    - type: precision_at_10
+      value: 7.382583333333334
+    - type: precision_at_100
+      value: 1.16625
+    - type: precision_at_1000
+      value: 0.15408333333333332
+    - type: precision_at_3
+      value: 17.218
+    - type: precision_at_5
+      value: 12.21875
+    - type: recall_at_1
+      value: 27.15516666666667
+    - type: recall_at_10
+      value: 54.36683333333333
+    - type: recall_at_100
+      value: 76.37183333333333
+    - type: recall_at_1000
+      value: 91.26183333333333
+    - type: recall_at_3
+      value: 40.769916666666674
+    - type: recall_at_5
+      value: 46.702333333333335
+    - type: map_at_1
+      value: 25.749
+    - type: map_at_10
+      value: 33.001999999999995
+    - type: map_at_100
+      value: 33.891
+    - type: map_at_1000
+      value: 33.993
+    - type: map_at_3
+      value: 30.703999999999997
+    - type: map_at_5
+      value: 31.959
+    - type: mrr_at_1
+      value: 28.834
+    - type: mrr_at_10
+      value: 35.955
+    - type: mrr_at_100
+      value: 36.709
+    - type: mrr_at_1000
+      value: 36.779
+    - type: mrr_at_3
+      value: 33.947
+    - type: mrr_at_5
+      value: 35.089
+    - type: ndcg_at_1
+      value: 28.834
+    - type: ndcg_at_10
+      value: 37.329
+    - type: ndcg_at_100
+      value: 41.79
+    - type: ndcg_at_1000
+      value: 44.169000000000004
+    - type: ndcg_at_3
+      value: 33.184999999999995
+    - type: ndcg_at_5
+      value: 35.107
+    - type: precision_at_1
+      value: 28.834
+    - type: precision_at_10
+      value: 5.7669999999999995
+    - type: precision_at_100
+      value: 0.876
+    - type: precision_at_1000
+      value: 0.11399999999999999
+    - type: precision_at_3
+      value: 14.213000000000001
+    - type: precision_at_5
+      value: 9.754999999999999
+    - type: recall_at_1
+      value: 25.749
+    - type: recall_at_10
+      value: 47.791
+    - type: recall_at_100
+      value: 68.255
+    - type: recall_at_1000
+      value: 85.749
+    - type: recall_at_3
+      value: 36.199
+    - type: recall_at_5
+      value: 41.071999999999996
+    - type: map_at_1
+      value: 17.777
+    - type: map_at_10
+      value: 25.201
+    - type: map_at_100
+      value: 26.423999999999996
+    - type: map_at_1000
+      value: 26.544
+    - type: map_at_3
+      value: 22.869
+    - type: map_at_5
+      value: 24.023
+    - type: mrr_at_1
+      value: 21.473
+    - type: mrr_at_10
+      value: 29.12
+    - type: mrr_at_100
+      value: 30.144
+    - type: mrr_at_1000
+      value: 30.215999999999998
+    - type: mrr_at_3
+      value: 26.933
+    - type: mrr_at_5
+      value: 28.051
+    - type: ndcg_at_1
+      value: 21.473
+    - type: ndcg_at_10
+      value: 30.003
+    - type: ndcg_at_100
+      value: 35.766
+    - type: ndcg_at_1000
+      value: 38.501000000000005
+    - type: ndcg_at_3
+      value: 25.773000000000003
+    - type: ndcg_at_5
+      value: 27.462999999999997
+    - type: precision_at_1
+      value: 21.473
+    - type: precision_at_10
+      value: 5.482
+    - type: precision_at_100
+      value: 0.975
+    - type: precision_at_1000
+      value: 0.13799999999999998
+    - type: precision_at_3
+      value: 12.205
+    - type: precision_at_5
+      value: 8.692
+    - type: recall_at_1
+      value: 17.777
+    - type: recall_at_10
+      value: 40.582
+    - type: recall_at_100
+      value: 66.305
+    - type: recall_at_1000
+      value: 85.636
+    - type: recall_at_3
+      value: 28.687
+    - type: recall_at_5
+      value: 33.089
+    - type: map_at_1
+      value: 26.677
+    - type: map_at_10
+      value: 36.309000000000005
+    - type: map_at_100
+      value: 37.403999999999996
+    - type: map_at_1000
+      value: 37.496
+    - type: map_at_3
+      value: 33.382
+    - type: map_at_5
+      value: 34.98
+    - type: mrr_at_1
+      value: 31.343
+    - type: mrr_at_10
+      value: 40.549
+    - type: mrr_at_100
+      value: 41.342
+    - type: mrr_at_1000
+      value: 41.397
+    - type: mrr_at_3
+      value: 38.029
+    - type: mrr_at_5
+      value: 39.451
+    - type: ndcg_at_1
+      value: 31.343
+    - type: ndcg_at_10
+      value: 42.1
+    - type: ndcg_at_100
+      value: 47.089999999999996
+    - type: ndcg_at_1000
+      value: 49.222
+    - type: ndcg_at_3
+      value: 36.836999999999996
+    - type: ndcg_at_5
+      value: 39.21
+    - type: precision_at_1
+      value: 31.343
+    - type: precision_at_10
+      value: 7.164
+    - type: precision_at_100
+      value: 1.0959999999999999
+    - type: precision_at_1000
+      value: 0.13899999999999998
+    - type: precision_at_3
+      value: 16.915
+    - type: precision_at_5
+      value: 11.940000000000001
+    - type: recall_at_1
+      value: 26.677
+    - type: recall_at_10
+      value: 55.54599999999999
+    - type: recall_at_100
+      value: 77.094
+    - type: recall_at_1000
+      value: 92.01
+    - type: recall_at_3
+      value: 41.191
+    - type: recall_at_5
+      value: 47.006
+    - type: map_at_1
+      value: 24.501
+    - type: map_at_10
+      value: 33.102
+    - type: map_at_100
+      value: 34.676
+    - type: map_at_1000
+      value: 34.888000000000005
+    - type: map_at_3
+      value: 29.944
+    - type: map_at_5
+      value: 31.613999999999997
+    - type: mrr_at_1
+      value: 29.447000000000003
+    - type: mrr_at_10
+      value: 37.996
+    - type: mrr_at_100
+      value: 38.946
+    - type: mrr_at_1000
+      value: 38.995000000000005
+    - type: mrr_at_3
+      value: 35.079
+    - type: mrr_at_5
+      value: 36.69
+    - type: ndcg_at_1
+      value: 29.447000000000003
+    - type: ndcg_at_10
+      value: 39.232
+    - type: ndcg_at_100
+      value: 45.247
+    - type: ndcg_at_1000
+      value: 47.613
+    - type: ndcg_at_3
+      value: 33.922999999999995
+    - type: ndcg_at_5
+      value: 36.284
+    - type: precision_at_1
+      value: 29.447000000000003
+    - type: precision_at_10
+      value: 7.648000000000001
+    - type: precision_at_100
+      value: 1.516
+    - type: precision_at_1000
+      value: 0.23900000000000002
+    - type: precision_at_3
+      value: 16.008
+    - type: precision_at_5
+      value: 11.779
+    - type: recall_at_1
+      value: 24.501
+    - type: recall_at_10
+      value: 51.18899999999999
+    - type: recall_at_100
+      value: 78.437
+    - type: recall_at_1000
+      value: 92.842
+    - type: recall_at_3
+      value: 35.808
+    - type: recall_at_5
+      value: 42.197
+    - type: map_at_1
+      value: 22.039
+    - type: map_at_10
+      value: 30.377
+    - type: map_at_100
+      value: 31.275
+    - type: map_at_1000
+      value: 31.379
+    - type: map_at_3
+      value: 27.98
+    - type: map_at_5
+      value: 29.358
+    - type: mrr_at_1
+      value: 24.03
+    - type: mrr_at_10
+      value: 32.568000000000005
+    - type: mrr_at_100
+      value: 33.403
+    - type: mrr_at_1000
+      value: 33.475
+    - type: mrr_at_3
+      value: 30.436999999999998
+    - type: mrr_at_5
+      value: 31.796000000000003
+    - type: ndcg_at_1
+      value: 24.03
+    - type: ndcg_at_10
+      value: 35.198
+    - type: ndcg_at_100
+      value: 39.668
+    - type: ndcg_at_1000
+      value: 42.296
+    - type: ndcg_at_3
+      value: 30.709999999999997
+    - type: ndcg_at_5
+      value: 33.024
+    - type: precision_at_1
+      value: 24.03
+    - type: precision_at_10
+      value: 5.564
+    - type: precision_at_100
+      value: 0.828
+    - type: precision_at_1000
+      value: 0.117
+    - type: precision_at_3
+      value: 13.309000000000001
+    - type: precision_at_5
+      value: 9.39
+    - type: recall_at_1
+      value: 22.039
+    - type: recall_at_10
+      value: 47.746
+    - type: recall_at_100
+      value: 68.23599999999999
+    - type: recall_at_1000
+      value: 87.852
+    - type: recall_at_3
+      value: 35.852000000000004
+    - type: recall_at_5
+      value: 41.410000000000004
+  - task:
+      type: Retrieval
+    dataset:
+      name: MTEB ClimateFEVER
+      type: climate-fever
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 15.692999999999998
+    - type: map_at_10
+      value: 26.903
+    - type: map_at_100
+      value: 28.987000000000002
+    - type: map_at_1000
+      value: 29.176999999999996
+    - type: map_at_3
+      value: 22.137
+    - type: map_at_5
+      value: 24.758
+    - type: mrr_at_1
+      value: 35.57
+    - type: mrr_at_10
+      value: 47.821999999999996
+    - type: mrr_at_100
+      value: 48.608000000000004
+    - type: mrr_at_1000
+      value: 48.638999999999996
+    - type: mrr_at_3
+      value: 44.452000000000005
+    - type: mrr_at_5
+      value: 46.546
+    - type: ndcg_at_1
+      value: 35.57
+    - type: ndcg_at_10
+      value: 36.567
+    - type: ndcg_at_100
+      value: 44.085
+    - type: ndcg_at_1000
+      value: 47.24
+    - type: ndcg_at_3
+      value: 29.964000000000002
+    - type: ndcg_at_5
+      value: 32.511
+    - type: precision_at_1
+      value: 35.57
+    - type: precision_at_10
+      value: 11.485
+    - type: precision_at_100
+      value: 1.9619999999999997
+    - type: precision_at_1000
+      value: 0.256
+    - type: precision_at_3
+      value: 22.237000000000002
+    - type: precision_at_5
+      value: 17.471999999999998
+    - type: recall_at_1
+      value: 15.692999999999998
+    - type: recall_at_10
+      value: 43.056
+    - type: recall_at_100
+      value: 68.628
+    - type: recall_at_1000
+      value: 86.075
+    - type: recall_at_3
+      value: 26.918999999999997
+    - type: recall_at_5
+      value: 34.14
+  - task:
+      type: Retrieval
+    dataset:
+      name: MTEB DBPedia
+      type: dbpedia-entity
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 9.53
+    - type: map_at_10
+      value: 20.951
+    - type: map_at_100
+      value: 30.136000000000003
+    - type: map_at_1000
+      value: 31.801000000000002
+    - type: map_at_3
+      value: 15.021
+    - type: map_at_5
+      value: 17.471999999999998
+    - type: mrr_at_1
+      value: 71.0
+    - type: mrr_at_10
+      value: 79.176
+    - type: mrr_at_100
+      value: 79.418
+    - type: mrr_at_1000
+      value: 79.426
+    - type: mrr_at_3
+      value: 78.125
+    - type: mrr_at_5
+      value: 78.61200000000001
+    - type: ndcg_at_1
+      value: 58.5
+    - type: ndcg_at_10
+      value: 44.106
+    - type: ndcg_at_100
+      value: 49.268
+    - type: ndcg_at_1000
+      value: 56.711999999999996
+    - type: ndcg_at_3
+      value: 48.934
+    - type: ndcg_at_5
+      value: 45.826
+    - type: precision_at_1
+      value: 71.0
+    - type: precision_at_10
+      value: 35.0
+    - type: precision_at_100
+      value: 11.360000000000001
+    - type: precision_at_1000
+      value: 2.046
+    - type: precision_at_3
+      value: 52.833
+    - type: precision_at_5
+      value: 44.15
+    - type: recall_at_1
+      value: 9.53
+    - type: recall_at_10
+      value: 26.811
+    - type: recall_at_100
+      value: 55.916999999999994
+    - type: recall_at_1000
+      value: 79.973
+    - type: recall_at_3
+      value: 16.413
+    - type: recall_at_5
+      value: 19.980999999999998
+  - task:
+      type: Classification
+    dataset:
+      name: MTEB EmotionClassification
+      type: mteb/emotion
+      config: default
+      split: test
+      revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
+    metrics:
+    - type: accuracy
+      value: 51.519999999999996
+    - type: f1
+      value: 46.36601294761231
+  - task:
+      type: Retrieval
+    dataset:
+      name: MTEB FEVER
+      type: fever
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 74.413
+    - type: map_at_10
+      value: 83.414
+    - type: map_at_100
+      value: 83.621
+    - type: map_at_1000
+      value: 83.635
+    - type: map_at_3
+      value: 82.337
+    - type: map_at_5
+      value: 83.039
+    - type: mrr_at_1
+      value: 80.19800000000001
+    - type: mrr_at_10
+      value: 87.715
+    - type: mrr_at_100
+      value: 87.778
+    - type: mrr_at_1000
+      value: 87.779
+    - type: mrr_at_3
+      value: 87.106
+    - type: mrr_at_5
+      value: 87.555
+    - type: ndcg_at_1
+      value: 80.19800000000001
+    - type: ndcg_at_10
+      value: 87.182
+    - type: ndcg_at_100
+      value: 87.90299999999999
+    - type: ndcg_at_1000
+      value: 88.143
+    - type: ndcg_at_3
+      value: 85.60600000000001
+    - type: ndcg_at_5
+      value: 86.541
+    - type: precision_at_1
+      value: 80.19800000000001
+    - type: precision_at_10
+      value: 10.531
+    - type: precision_at_100
+      value: 1.113
+    - type: precision_at_1000
+      value: 0.11499999999999999
+    - type: precision_at_3
+      value: 32.933
+    - type: precision_at_5
+      value: 20.429
+    - type: recall_at_1
+      value: 74.413
+    - type: recall_at_10
+      value: 94.363
+    - type: recall_at_100
+      value: 97.165
+    - type: recall_at_1000
+      value: 98.668
+    - type: recall_at_3
+      value: 90.108
+    - type: recall_at_5
+      value: 92.52
+  - task:
+      type: Retrieval
+    dataset:
+      name: MTEB FiQA2018
+      type: fiqa
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 22.701
+    - type: map_at_10
+      value: 37.122
+    - type: map_at_100
+      value: 39.178000000000004
+    - type: map_at_1000
+      value: 39.326
+    - type: map_at_3
+      value: 32.971000000000004
+    - type: map_at_5
+      value: 35.332
+    - type: mrr_at_1
+      value: 44.753
+    - type: mrr_at_10
+      value: 53.452
+    - type: mrr_at_100
+      value: 54.198
+    - type: mrr_at_1000
+      value: 54.225
+    - type: mrr_at_3
+      value: 50.952
+    - type: mrr_at_5
+      value: 52.464
+    - type: ndcg_at_1
+      value: 44.753
+    - type: ndcg_at_10
+      value: 45.021
+    - type: ndcg_at_100
+      value: 52.028
+    - type: ndcg_at_1000
+      value: 54.596000000000004
+    - type: ndcg_at_3
+      value: 41.622
+    - type: ndcg_at_5
+      value: 42.736000000000004
+    - type: precision_at_1
+      value: 44.753
+    - type: precision_at_10
+      value: 12.284
+    - type: precision_at_100
+      value: 1.955
+    - type: precision_at_1000
+      value: 0.243
+    - type: precision_at_3
+      value: 27.828999999999997
+    - type: precision_at_5
+      value: 20.061999999999998
+    - type: recall_at_1
+      value: 22.701
+    - type: recall_at_10
+      value: 51.432
+    - type: recall_at_100
+      value: 77.009
+    - type: recall_at_1000
+      value: 92.511
+    - type: recall_at_3
+      value: 37.919000000000004
+    - type: recall_at_5
+      value: 44.131
+  - task:
+      type: Retrieval
+    dataset:
+      name: MTEB HotpotQA
+      type: hotpotqa
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 40.189
+    - type: map_at_10
+      value: 66.24600000000001
+    - type: map_at_100
+      value: 67.098
+    - type: map_at_1000
+      value: 67.149
+    - type: map_at_3
+      value: 62.684
+    - type: map_at_5
+      value: 64.974
+    - type: mrr_at_1
+      value: 80.378
+    - type: mrr_at_10
+      value: 86.127
+    - type: mrr_at_100
+      value: 86.29299999999999
+    - type: mrr_at_1000
+      value: 86.297
+    - type: mrr_at_3
+      value: 85.31400000000001
+    - type: mrr_at_5
+      value: 85.858
+    - type: ndcg_at_1
+      value: 80.378
+    - type: ndcg_at_10
+      value: 74.101
+    - type: ndcg_at_100
+      value: 76.993
+    - type: ndcg_at_1000
+      value: 77.948
+    - type: ndcg_at_3
+      value: 69.232
+    - type: ndcg_at_5
+      value: 72.04599999999999
+    - type: precision_at_1
+      value: 80.378
+    - type: precision_at_10
+      value: 15.595999999999998
+    - type: precision_at_100
+      value: 1.7840000000000003
+    - type: precision_at_1000
+      value: 0.191
+    - type: precision_at_3
+      value: 44.884
+    - type: precision_at_5
+      value: 29.145
+    - type: recall_at_1
+      value: 40.189
+    - type: recall_at_10
+      value: 77.981
+    - type: recall_at_100
+      value: 89.21
+    - type: recall_at_1000
+      value: 95.48299999999999
+    - type: recall_at_3
+      value: 67.326
+    - type: recall_at_5
+      value: 72.863
+  - task:
+      type: Classification
+    dataset:
+      name: MTEB ImdbClassification
+      type: mteb/imdb
+      config: default
+      split: test
+      revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
+    metrics:
+    - type: accuracy
+      value: 92.84599999999999
+    - type: ap
+      value: 89.4710787567357
+    - type: f1
+      value: 92.83752676932258
+  - task:
+      type: Retrieval
+    dataset:
+      name: MTEB MSMARCO
+      type: msmarco
+      config: default
+      split: dev
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 23.132
+    - type: map_at_10
+      value: 35.543
+    - type: map_at_100
+      value: 36.702
+    - type: map_at_1000
+      value: 36.748999999999995
+    - type: map_at_3
+      value: 31.737
+    - type: map_at_5
+      value: 33.927
+    - type: mrr_at_1
+      value: 23.782
+    - type: mrr_at_10
+      value: 36.204
+    - type: mrr_at_100
+      value: 37.29
+    - type: mrr_at_1000
+      value: 37.330999999999996
+    - type: mrr_at_3
+      value: 32.458999999999996
+    - type: mrr_at_5
+      value: 34.631
+    - type: ndcg_at_1
+      value: 23.782
+    - type: ndcg_at_10
+      value: 42.492999999999995
+    - type: ndcg_at_100
+      value: 47.985
+    - type: ndcg_at_1000
+      value: 49.141
+    - type: ndcg_at_3
+      value: 34.748000000000005
+    - type: ndcg_at_5
+      value: 38.651
+    - type: precision_at_1
+      value: 23.782
+    - type: precision_at_10
+      value: 6.665
+    - type: precision_at_100
+      value: 0.941
+    - type: precision_at_1000
+      value: 0.104
+    - type: precision_at_3
+      value: 14.776
+    - type: precision_at_5
+      value: 10.84
+    - type: recall_at_1
+      value: 23.132
+    - type: recall_at_10
+      value: 63.794
+    - type: recall_at_100
+      value: 89.027
+    - type: recall_at_1000
+      value: 97.807
+    - type: recall_at_3
+      value: 42.765
+    - type: recall_at_5
+      value: 52.11
+  - task:
+      type: Classification
+    dataset:
+      name: MTEB MTOPDomainClassification (en)
+      type: mteb/mtop_domain
+      config: en
+      split: test
+      revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
+    metrics:
+    - type: accuracy
+      value: 94.59188326493388
+    - type: f1
+      value: 94.3842594786827
+  - task:
+      type: Classification
+    dataset:
+      name: MTEB MTOPIntentClassification (en)
+      type: mteb/mtop_intent
+      config: en
+      split: test
+      revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
+    metrics:
+    - type: accuracy
+      value: 79.49384404924761
+    - type: f1
+      value: 59.7580539534629
+  - task:
+      type: Classification
+    dataset:
+      name: MTEB MassiveIntentClassification (en)
+      type: mteb/amazon_massive_intent
+      config: en
+      split: test
+      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
+    metrics:
+    - type: accuracy
+      value: 77.56220578345663
+    - type: f1
+      value: 75.27228165561478
+  - task:
+      type: Classification
+    dataset:
+      name: MTEB MassiveScenarioClassification (en)
+      type: mteb/amazon_massive_scenario
+      config: en
+      split: test
+      revision: 7d571f92784cd94a019292a1f45445077d0ef634
+    metrics:
+    - type: accuracy
+      value: 80.53463349024884
+    - type: f1
+      value: 80.4893958236536
+  - task:
+      type: Clustering
+    dataset:
+      name: MTEB MedrxivClusteringP2P
+      type: mteb/medrxiv-clustering-p2p
+      config: default
+      split: test
+      revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
+    metrics:
+    - type: v_measure
+      value: 32.56100273484962
+  - task:
+      type: Clustering
+    dataset:
+      name: MTEB MedrxivClusteringS2S
+      type: mteb/medrxiv-clustering-s2s
+      config: default
+      split: test
+      revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
+    metrics:
+    - type: v_measure
+      value: 31.470380028839607
+  - task:
+      type: Reranking
+    dataset:
+      name: MTEB MindSmallReranking
+      type: mteb/mind_small
+      config: default
+      split: test
+      revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
+    metrics:
+    - type: map
+      value: 32.06102792457849
+    - type: mrr
+      value: 33.30709199672238
+  - task:
+      type: Retrieval
+    dataset:
+      name: MTEB NFCorpus
+      type: nfcorpus
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 6.776999999999999
+    - type: map_at_10
+      value: 14.924000000000001
+    - type: map_at_100
+      value: 18.955
+    - type: map_at_1000
+      value: 20.538999999999998
+    - type: map_at_3
+      value: 10.982
+    - type: map_at_5
+      value: 12.679000000000002
+    - type: mrr_at_1
+      value: 47.988
+    - type: mrr_at_10
+      value: 57.232000000000006
+    - type: mrr_at_100
+      value: 57.818999999999996
+    - type: mrr_at_1000
+      value: 57.847
+    - type: mrr_at_3
+      value: 54.901999999999994
+    - type: mrr_at_5
+      value: 56.481
+    - type: ndcg_at_1
+      value: 46.594
+    - type: ndcg_at_10
+      value: 38.129000000000005
+    - type: ndcg_at_100
+      value: 35.54
+    - type: ndcg_at_1000
+      value: 44.172
+    - type: ndcg_at_3
+      value: 43.025999999999996
+    - type: ndcg_at_5
+      value: 41.052
+    - type: precision_at_1
+      value: 47.988
+    - type: precision_at_10
+      value: 28.111000000000004
+    - type: precision_at_100
+      value: 8.929
+    - type: precision_at_1000
+      value: 2.185
+    - type: precision_at_3
+      value: 40.144000000000005
+    - type: precision_at_5
+      value: 35.232
+    - type: recall_at_1
+      value: 6.776999999999999
+    - type: recall_at_10
+      value: 19.289
+    - type: recall_at_100
+      value: 36.359
+    - type: recall_at_1000
+      value: 67.54
+    - type: recall_at_3
+      value: 11.869
+    - type: recall_at_5
+      value: 14.999
+  - task:
+      type: Retrieval
+    dataset:
+      name: MTEB NQ
+      type: nq
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 31.108000000000004
+    - type: map_at_10
+      value: 47.126000000000005
+    - type: map_at_100
+      value: 48.171
+    - type: map_at_1000
+      value: 48.199
+    - type: map_at_3
+      value: 42.734
+    - type: map_at_5
+      value: 45.362
+    - type: mrr_at_1
+      value: 34.936
+    - type: mrr_at_10
+      value: 49.571
+    - type: mrr_at_100
+      value: 50.345
+    - type: mrr_at_1000
+      value: 50.363
+    - type: mrr_at_3
+      value: 45.959
+    - type: mrr_at_5
+      value: 48.165
+    - type: ndcg_at_1
+      value: 34.936
+    - type: ndcg_at_10
+      value: 55.028999999999996
+    - type: ndcg_at_100
+      value: 59.244
+    - type: ndcg_at_1000
+      value: 59.861
+    - type: ndcg_at_3
+      value: 46.872
+    - type: ndcg_at_5
+      value: 51.217999999999996
+    - type: precision_at_1
+      value: 34.936
+    - type: precision_at_10
+      value: 9.099
+    - type: precision_at_100
+      value: 1.145
+    - type: precision_at_1000
+      value: 0.12
+    - type: precision_at_3
+      value: 21.456
+    - type: precision_at_5
+      value: 15.411
+    - type: recall_at_1
+      value: 31.108000000000004
+    - type: recall_at_10
+      value: 76.53999999999999
+    - type: recall_at_100
+      value: 94.39
+    - type: recall_at_1000
+      value: 98.947
+    - type: recall_at_3
+      value: 55.572
+    - type: recall_at_5
+      value: 65.525
+  - task:
+      type: Retrieval
+    dataset:
+      name: MTEB QuoraRetrieval
+      type: quora
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 71.56400000000001
+    - type: map_at_10
+      value: 85.482
+    - type: map_at_100
+      value: 86.114
+    - type: map_at_1000
+      value: 86.13
+    - type: map_at_3
+      value: 82.607
+    - type: map_at_5
+      value: 84.405
+    - type: mrr_at_1
+      value: 82.42
+    - type: mrr_at_10
+      value: 88.304
+    - type: mrr_at_100
+      value: 88.399
+    - type: mrr_at_1000
+      value: 88.399
+    - type: mrr_at_3
+      value: 87.37
+    - type: mrr_at_5
+      value: 88.024
+    - type: ndcg_at_1
+      value: 82.45
+    - type: ndcg_at_10
+      value: 89.06500000000001
+    - type: ndcg_at_100
+      value: 90.232
+    - type: ndcg_at_1000
+      value: 90.305
+    - type: ndcg_at_3
+      value: 86.375
+    - type: ndcg_at_5
+      value: 87.85300000000001
+    - type: precision_at_1
+      value: 82.45
+    - type: precision_at_10
+      value: 13.486999999999998
+    - type: precision_at_100
+      value: 1.534
+    - type: precision_at_1000
+      value: 0.157
+    - type: precision_at_3
+      value: 37.813
+    - type: precision_at_5
+      value: 24.773999999999997
+    - type: recall_at_1
+      value: 71.56400000000001
+    - type: recall_at_10
+      value: 95.812
+    - type: recall_at_100
+      value: 99.7
+    - type: recall_at_1000
+      value: 99.979
+    - type: recall_at_3
+      value: 87.966
+    - type: recall_at_5
+      value: 92.268
+  - task:
+      type: Clustering
+    dataset:
+      name: MTEB RedditClustering
+      type: mteb/reddit-clustering
+      config: default
+      split: test
+      revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
+    metrics:
+    - type: v_measure
+      value: 57.241876648614145
+  - task:
+      type: Clustering
+    dataset:
+      name: MTEB RedditClusteringP2P
+      type: mteb/reddit-clustering-p2p
+      config: default
+      split: test
+      revision: 282350215ef01743dc01b456c7f5241fa8937f16
+    metrics:
+    - type: v_measure
+      value: 64.66212576446223
+  - task:
+      type: Retrieval
+    dataset:
+      name: MTEB SCIDOCS
+      type: scidocs
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 5.308
+    - type: map_at_10
+      value: 13.803
+    - type: map_at_100
+      value: 16.176
+    - type: map_at_1000
+      value: 16.561
+    - type: map_at_3
+      value: 9.761000000000001
+    - type: map_at_5
+      value: 11.802
+    - type: mrr_at_1
+      value: 26.200000000000003
+    - type: mrr_at_10
+      value: 37.621
+    - type: mrr_at_100
+      value: 38.767
+    - type: mrr_at_1000
+      value: 38.815
+    - type: mrr_at_3
+      value: 34.117
+    - type: mrr_at_5
+      value: 36.107
+    - type: ndcg_at_1
+      value: 26.200000000000003
+    - type: ndcg_at_10
+      value: 22.64
+    - type: ndcg_at_100
+      value: 31.567
+    - type: ndcg_at_1000
+      value: 37.623
+    - type: ndcg_at_3
+      value: 21.435000000000002
+    - type: ndcg_at_5
+      value: 18.87
+    - type: precision_at_1
+      value: 26.200000000000003
+    - type: precision_at_10
+      value: 11.74
+    - type: precision_at_100
+      value: 2.465
+    - type: precision_at_1000
+      value: 0.391
+    - type: precision_at_3
+      value: 20.033
+    - type: precision_at_5
+      value: 16.64
+    - type: recall_at_1
+      value: 5.308
+    - type: recall_at_10
+      value: 23.794999999999998
+    - type: recall_at_100
+      value: 50.015
+    - type: recall_at_1000
+      value: 79.283
+    - type: recall_at_3
+      value: 12.178
+    - type: recall_at_5
+      value: 16.882
+  - task:
+      type: STS
+    dataset:
+      name: MTEB SICK-R
+      type: mteb/sickr-sts
+      config: default
+      split: test
+      revision: a6ea5a8cab320b040a23452cc28066d9beae2cee
+    metrics:
+    - type: cos_sim_pearson
+      value: 84.93231134675553
+    - type: cos_sim_spearman
+      value: 81.68319292603205
+    - type: euclidean_pearson
+      value: 81.8396814380367
+    - type: euclidean_spearman
+      value: 81.24641903349945
+    - type: manhattan_pearson
+      value: 81.84698799204274
+    - type: manhattan_spearman
+      value: 81.24269997904105
+  - task:
+      type: STS
+    dataset:
+      name: MTEB STS12
+      type: mteb/sts12-sts
+      config: default
+      split: test
+      revision: a0d554a64d88156834ff5ae9920b964011b16384
+    metrics:
+    - type: cos_sim_pearson
+      value: 86.73241671587446
+    - type: cos_sim_spearman
+      value: 79.05091082971826
+    - type: euclidean_pearson
+      value: 83.91146869578044
+    - type: euclidean_spearman
+      value: 79.87978465370936
+    - type: manhattan_pearson
+      value: 83.90888338917678
+    - type: manhattan_spearman
+      value: 79.87482848584241
+  - task:
+      type: STS
+    dataset:
+      name: MTEB STS13
+      type: mteb/sts13-sts
+      config: default
+      split: test
+      revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
+    metrics:
+    - type: cos_sim_pearson
+      value: 85.14970731146177
+    - type: cos_sim_spearman
+      value: 86.37363490084627
+    - type: euclidean_pearson
+      value: 83.02154218530433
+    - type: euclidean_spearman
+      value: 83.80258761957367
+    - type: manhattan_pearson
+      value: 83.01664495119347
+    - type: manhattan_spearman
+      value: 83.77567458007952
+  - task:
+      type: STS
+    dataset:
+      name: MTEB STS14
+      type: mteb/sts14-sts
+      config: default
+      split: test
+      revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
+    metrics:
+    - type: cos_sim_pearson
+      value: 83.40474139886784
+    - type: cos_sim_spearman
+      value: 82.77768789165984
+    - type: euclidean_pearson
+      value: 80.7065877443695
+    - type: euclidean_spearman
+      value: 81.375940662505
+    - type: manhattan_pearson
+      value: 80.6507552270278
+    - type: manhattan_spearman
+      value: 81.32782179098741
+  - task:
+      type: STS
+    dataset:
+      name: MTEB STS15
+      type: mteb/sts15-sts
+      config: default
+      split: test
+      revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
+    metrics:
+    - type: cos_sim_pearson
+      value: 87.08585968722274
+    - type: cos_sim_spearman
+      value: 88.03110031451399
+    - type: euclidean_pearson
+      value: 85.74012019602384
+    - type: euclidean_spearman
+      value: 86.13592849438209
+    - type: manhattan_pearson
+      value: 85.74404842369206
+    - type: manhattan_spearman
+      value: 86.14492318960154
+  - task:
+      type: STS
+    dataset:
+      name: MTEB STS16
+      type: mteb/sts16-sts
+      config: default
+      split: test
+      revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
+    metrics:
+    - type: cos_sim_pearson
+      value: 84.95069052788875
+    - type: cos_sim_spearman
+      value: 86.4867991595147
+    - type: euclidean_pearson
+      value: 84.31013325754635
+    - type: euclidean_spearman
+      value: 85.01529258006482
+    - type: manhattan_pearson
+      value: 84.26995570085374
+    - type: manhattan_spearman
+      value: 84.96982104986162
+  - task:
+      type: STS
+    dataset:
+      name: MTEB STS17 (en-en)
+      type: mteb/sts17-crosslingual-sts
+      config: en-en
+      split: test
+      revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
+    metrics:
+    - type: cos_sim_pearson
+      value: 87.54617647971897
+    - type: cos_sim_spearman
+      value: 87.49834181751034
+    - type: euclidean_pearson
+      value: 86.01015322577122
+    - type: euclidean_spearman
+      value: 84.63362652063199
+    - type: manhattan_pearson
+      value: 86.13807574475706
+    - type: manhattan_spearman
+      value: 84.7772370721132
+  - task:
+      type: STS
+    dataset:
+      name: MTEB STS22 (en)
+      type: mteb/sts22-crosslingual-sts
+      config: en
+      split: test
+      revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80
+    metrics:
+    - type: cos_sim_pearson
+      value: 67.20047755786615
+    - type: cos_sim_spearman
+      value: 67.05324077987636
+    - type: euclidean_pearson
+      value: 66.91930642976601
+    - type: euclidean_spearman
+      value: 65.21491856099105
+    - type: manhattan_pearson
+      value: 66.78756851976624
+    - type: manhattan_spearman
+      value: 65.12356257740728
+  - task:
+      type: STS
+    dataset:
+      name: MTEB STSBenchmark
+      type: mteb/stsbenchmark-sts
+      config: default
+      split: test
+      revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
+    metrics:
+    - type: cos_sim_pearson
+      value: 86.19852871539686
+    - type: cos_sim_spearman
+      value: 87.5161895296395
+    - type: euclidean_pearson
+      value: 84.59848645207485
+    - type: euclidean_spearman
+      value: 85.26427328757919
+    - type: manhattan_pearson
+      value: 84.59747366996524
+    - type: manhattan_spearman
+      value: 85.24045855146915
+  - task:
+      type: Reranking
+    dataset:
+      name: MTEB SciDocsRR
+      type: mteb/scidocs-reranking
+      config: default
+      split: test
+      revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
+    metrics:
+    - type: map
+      value: 87.63320317811032
+    - type: mrr
+      value: 96.26242947321379
+  - task:
+      type: Retrieval
+    dataset:
+      name: MTEB SciFact
+      type: scifact
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 60.928000000000004
+    - type: map_at_10
+      value: 70.112
+    - type: map_at_100
+      value: 70.59299999999999
+    - type: map_at_1000
+      value: 70.623
+    - type: map_at_3
+      value: 66.846
+    - type: map_at_5
+      value: 68.447
+    - type: mrr_at_1
+      value: 64.0
+    - type: mrr_at_10
+      value: 71.212
+    - type: mrr_at_100
+      value: 71.616
+    - type: mrr_at_1000
+      value: 71.64500000000001
+    - type: mrr_at_3
+      value: 68.77799999999999
+    - type: mrr_at_5
+      value: 70.094
+    - type: ndcg_at_1
+      value: 64.0
+    - type: ndcg_at_10
+      value: 74.607
+    - type: ndcg_at_100
+      value: 76.416
+    - type: ndcg_at_1000
+      value: 77.102
+    - type: ndcg_at_3
+      value: 69.126
+    - type: ndcg_at_5
+      value: 71.41300000000001
+    - type: precision_at_1
+      value: 64.0
+    - type: precision_at_10
+      value: 9.933
+    - type: precision_at_100
+      value: 1.077
+    - type: precision_at_1000
+      value: 0.11299999999999999
+    - type: precision_at_3
+      value: 26.556
+    - type: precision_at_5
+      value: 17.467
+    - type: recall_at_1
+      value: 60.928000000000004
+    - type: recall_at_10
+      value: 87.322
+    - type: recall_at_100
+      value: 94.833
+    - type: recall_at_1000
+      value: 100.0
+    - type: recall_at_3
+      value: 72.628
+    - type: recall_at_5
+      value: 78.428
+  - task:
+      type: PairClassification
+    dataset:
+      name: MTEB SprintDuplicateQuestions
+      type: mteb/sprintduplicatequestions-pairclassification
+      config: default
+      split: test
+      revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
+    metrics:
+    - type: cos_sim_accuracy
+      value: 99.86237623762376
+    - type: cos_sim_ap
+      value: 96.72586477206649
+    - type: cos_sim_f1
+      value: 93.01858362631845
+    - type: cos_sim_precision
+      value: 93.4409687184662
+    - type: cos_sim_recall
+      value: 92.60000000000001
+    - type: dot_accuracy
+      value: 99.78019801980199
+    - type: dot_ap
+      value: 93.72748205246228
+    - type: dot_f1
+      value: 89.04109589041096
+    - type: dot_precision
+      value: 87.16475095785441
+    - type: dot_recall
+      value: 91.0
+    - type: euclidean_accuracy
+      value: 99.85445544554456
+    - type: euclidean_ap
+      value: 96.6661459876145
+    - type: euclidean_f1
+      value: 92.58337481333997
+    - type: euclidean_precision
+      value: 92.17046580773042
+    - type: euclidean_recall
+      value: 93.0
+    - type: manhattan_accuracy
+      value: 99.85445544554456
+    - type: manhattan_ap
+      value: 96.6883549244056
+    - type: manhattan_f1
+      value: 92.57598405580468
+    - type: manhattan_precision
+      value: 92.25422045680239
+    - type: manhattan_recall
+      value: 92.9
+    - type: max_accuracy
+      value: 99.86237623762376
+    - type: max_ap
+      value: 96.72586477206649
+    - type: max_f1
+      value: 93.01858362631845
+  - task:
+      type: Clustering
+    dataset:
+      name: MTEB StackExchangeClustering
+      type: mteb/stackexchange-clustering
+      config: default
+      split: test
+      revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
+    metrics:
+    - type: v_measure
+      value: 66.39930057069995
+  - task:
+      type: Clustering
+    dataset:
+      name: MTEB StackExchangeClusteringP2P
+      type: mteb/stackexchange-clustering-p2p
+      config: default
+      split: test
+      revision: 815ca46b2622cec33ccafc3735d572c266efdb44
+    metrics:
+    - type: v_measure
+      value: 34.96398659903402
+  - task:
+      type: Reranking
+    dataset:
+      name: MTEB StackOverflowDupQuestions
+      type: mteb/stackoverflowdupquestions-reranking
+      config: default
+      split: test
+      revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
+    metrics:
+    - type: map
+      value: 55.946944700355395
+    - type: mrr
+      value: 56.97151398438164
+  - task:
+      type: Summarization
+    dataset:
+      name: MTEB SummEval
+      type: mteb/summeval
+      config: default
+      split: test
+      revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
+    metrics:
+    - type: cos_sim_pearson
+      value: 31.541657650692905
+    - type: cos_sim_spearman
+      value: 31.605804192286303
+    - type: dot_pearson
+      value: 28.26905996736398
+    - type: dot_spearman
+      value: 27.864801765851187
+  - task:
+      type: Retrieval
+    dataset:
+      name: MTEB TRECCOVID
+      type: trec-covid
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 0.22599999999999998
+    - type: map_at_10
+      value: 1.8870000000000002
+    - type: map_at_100
+      value: 9.78
+    - type: map_at_1000
+      value: 22.514
+    - type: map_at_3
+      value: 0.6669999999999999
+    - type: map_at_5
+      value: 1.077
+    - type: mrr_at_1
+      value: 82.0
+    - type: mrr_at_10
+      value: 89.86699999999999
+    - type: mrr_at_100
+      value: 89.86699999999999
+    - type: mrr_at_1000
+      value: 89.86699999999999
+    - type: mrr_at_3
+      value: 89.667
+    - type: mrr_at_5
+      value: 89.667
+    - type: ndcg_at_1
+      value: 79.0
+    - type: ndcg_at_10
+      value: 74.818
+    - type: ndcg_at_100
+      value: 53.715999999999994
+    - type: ndcg_at_1000
+      value: 47.082
+    - type: ndcg_at_3
+      value: 82.134
+    - type: ndcg_at_5
+      value: 79.81899999999999
+    - type: precision_at_1
+      value: 82.0
+    - type: precision_at_10
+      value: 78.0
+    - type: precision_at_100
+      value: 54.48
+    - type: precision_at_1000
+      value: 20.518
+    - type: precision_at_3
+      value: 87.333
+    - type: precision_at_5
+      value: 85.2
+    - type: recall_at_1
+      value: 0.22599999999999998
+    - type: recall_at_10
+      value: 2.072
+    - type: recall_at_100
+      value: 13.013
+    - type: recall_at_1000
+      value: 43.462
+    - type: recall_at_3
+      value: 0.695
+    - type: recall_at_5
+      value: 1.139
+  - task:
+      type: Retrieval
+    dataset:
+      name: MTEB Touche2020
+      type: webis-touche2020
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 2.328
+    - type: map_at_10
+      value: 9.795
+    - type: map_at_100
+      value: 15.801000000000002
+    - type: map_at_1000
+      value: 17.23
+    - type: map_at_3
+      value: 4.734
+    - type: map_at_5
+      value: 6.644
+    - type: mrr_at_1
+      value: 30.612000000000002
+    - type: mrr_at_10
+      value: 46.902
+    - type: mrr_at_100
+      value: 47.495
+    - type: mrr_at_1000
+      value: 47.495
+    - type: mrr_at_3
+      value: 41.156
+    - type: mrr_at_5
+      value: 44.218
+    - type: ndcg_at_1
+      value: 28.571
+    - type: ndcg_at_10
+      value: 24.806
+    - type: ndcg_at_100
+      value: 36.419000000000004
+    - type: ndcg_at_1000
+      value: 47.272999999999996
+    - type: ndcg_at_3
+      value: 25.666
+    - type: ndcg_at_5
+      value: 25.448999999999998
+    - type: precision_at_1
+      value: 30.612000000000002
+    - type: precision_at_10
+      value: 23.061
+    - type: precision_at_100
+      value: 7.714
+    - type: precision_at_1000
+      value: 1.484
+    - type: precision_at_3
+      value: 26.531
+    - type: precision_at_5
+      value: 26.122
+    - type: recall_at_1
+      value: 2.328
+    - type: recall_at_10
+      value: 16.524
+    - type: recall_at_100
+      value: 47.179
+    - type: recall_at_1000
+      value: 81.22200000000001
+    - type: recall_at_3
+      value: 5.745
+    - type: recall_at_5
+      value: 9.339
+  - task:
+      type: Classification
+    dataset:
+      name: MTEB ToxicConversationsClassification
+      type: mteb/toxic_conversations_50k
+      config: default
+      split: test
+      revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
+    metrics:
+    - type: accuracy
+      value: 70.9142
+    - type: ap
+      value: 14.335574772555415
+    - type: f1
+      value: 54.62839595194111
+  - task:
+      type: Classification
+    dataset:
+      name: MTEB TweetSentimentExtractionClassification
+      type: mteb/tweet_sentiment_extraction
+      config: default
+      split: test
+      revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
+    metrics:
+    - type: accuracy
+      value: 59.94340690435768
+    - type: f1
+      value: 60.286487936731916
+  - task:
+      type: Clustering
+    dataset:
+      name: MTEB TwentyNewsgroupsClustering
+      type: mteb/twentynewsgroups-clustering
+      config: default
+      split: test
+      revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
+    metrics:
+    - type: v_measure
+      value: 51.26597708987974
+  - task:
+      type: PairClassification
+    dataset:
+      name: MTEB TwitterSemEval2015
+      type: mteb/twittersemeval2015-pairclassification
+      config: default
+      split: test
+      revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
+    metrics:
+    - type: cos_sim_accuracy
+      value: 87.48882398521786
+    - type: cos_sim_ap
+      value: 79.04326607602204
+    - type: cos_sim_f1
+      value: 71.64566826860633
+    - type: cos_sim_precision
+      value: 70.55512918905092
+    - type: cos_sim_recall
+      value: 72.77044854881267
+    - type: dot_accuracy
+      value: 84.19264469213805
+    - type: dot_ap
+      value: 67.96360043562528
+    - type: dot_f1
+      value: 64.06418393006827
+    - type: dot_precision
+      value: 58.64941898706424
+    - type: dot_recall
+      value: 70.58047493403694
+    - type: euclidean_accuracy
+      value: 87.45902127913214
+    - type: euclidean_ap
+      value: 78.9742237648272
+    - type: euclidean_f1
+      value: 71.5553235908142
+    - type: euclidean_precision
+      value: 70.77955601445535
+    - type: euclidean_recall
+      value: 72.34828496042216
+    - type: manhattan_accuracy
+      value: 87.41729749061214
+    - type: manhattan_ap
+      value: 78.90073137580596
+    - type: manhattan_f1
+      value: 71.3942611553533
+    - type: manhattan_precision
+      value: 68.52705653967483
+    - type: manhattan_recall
+      value: 74.51187335092348
+    - type: max_accuracy
+      value: 87.48882398521786
+    - type: max_ap
+      value: 79.04326607602204
+    - type: max_f1
+      value: 71.64566826860633
+  - task:
+      type: PairClassification
+    dataset:
+      name: MTEB TwitterURLCorpus
+      type: mteb/twitterurlcorpus-pairclassification
+      config: default
+      split: test
+      revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
+    metrics:
+    - type: cos_sim_accuracy
+      value: 88.68125897465751
+    - type: cos_sim_ap
+      value: 85.6003454431979
+    - type: cos_sim_f1
+      value: 77.6957163958641
+    - type: cos_sim_precision
+      value: 73.0110366307807
+    - type: cos_sim_recall
+      value: 83.02279026793964
+    - type: dot_accuracy
+      value: 87.7672992587418
+    - type: dot_ap
+      value: 82.4971301112899
+    - type: dot_f1
+      value: 75.90528233151184
+    - type: dot_precision
+      value: 72.0370626469368
+    - type: dot_recall
+      value: 80.21250384970742
+    - type: euclidean_accuracy
+      value: 88.4503434625684
+    - type: euclidean_ap
+      value: 84.91949884748384
+    - type: euclidean_f1
+      value: 76.92365018444684
+    - type: euclidean_precision
+      value: 74.53245721712759
+    - type: euclidean_recall
+      value: 79.47336002463813
+    - type: manhattan_accuracy
+      value: 88.47556952691427
+    - type: manhattan_ap
+      value: 84.8963689101517
+    - type: manhattan_f1
+      value: 76.85901249256395
+    - type: manhattan_precision
+      value: 74.31693989071039
+    - type: manhattan_recall
+      value: 79.58115183246073
+    - type: max_accuracy
+      value: 88.68125897465751
+    - type: max_ap
+      value: 85.6003454431979
+    - type: max_f1
+      value: 77.6957163958641
+---
+# hxstar/bge-large-en-v1.5-Q8_0-GGUF
+This model was converted to GGUF format from [`BAAI/bge-large-en-v1.5`](https://huggingface.co/BAAI/bge-large-en-v1.5) 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/BAAI/bge-large-en-v1.5) 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 hxstar/bge-large-en-v1.5-Q8_0-GGUF --hf-file bge-large-en-v1.5-q8_0.gguf -p "The meaning to life and the universe is"
+```
+### Server:
+```bash
+llama-server --hf-repo hxstar/bge-large-en-v1.5-Q8_0-GGUF --hf-file bge-large-en-v1.5-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 hxstar/bge-large-en-v1.5-Q8_0-GGUF --hf-file bge-large-en-v1.5-q8_0.gguf -p "The meaning to life and the universe is"
+```
+or
+```
+./llama-server --hf-repo hxstar/bge-large-en-v1.5-Q8_0-GGUF --hf-file bge-large-en-v1.5-q8_0.gguf -c 2048
+```