Fix the computation of the mean embedding

Signed-off-by: Aivin V. Solatorio <[email protected]>

1_Pooling/config.json

@@ -0,0 +1,11 @@
+{
+  "word_embedding_dimension": 384,
+  "pooling_mode_cls_token": true,
+  "pooling_mode_mean_tokens": false,
+  "pooling_mode_max_tokens": false,
+  "pooling_mode_mean_sqrt_len_tokens": false,
+  "pooling_mode_weightedmean_tokens": false,
+  "pooling_mode_lasttoken": false,
+  "include_prompt": true,
+  "output_key": "sentence_embedding"
+}

2_Pooling/config.json

@@ -0,0 +1,11 @@
+{
+  "word_embedding_dimension": 384,
+  "pooling_mode_cls_token": false,
+  "pooling_mode_mean_tokens": true,
+  "pooling_mode_max_tokens": false,
+  "pooling_mode_mean_sqrt_len_tokens": false,
+  "pooling_mode_weightedmean_tokens": false,
+  "pooling_mode_lasttoken": false,
+  "include_prompt": true,
+  "output_key": "query_embedding"
+}

README.md

@@ -1,3 +1,2676 @@
----
-license: mit
----
+---
+language:
+- en
+library_name: sentence-transformers
+license: mit
+pipeline_tag: sentence-similarity
+tags:
+  - feature-extraction
+  - mteb
+  - sentence-similarity
+  - sentence-transformers
+  - transformers
+model-index:
+- name: NoInstruct-small-Embedding-v0
+  results:
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_counterfactual
+      name: MTEB AmazonCounterfactualClassification (en)
+      config: en
+      split: test
+      revision: e8379541af4e31359cca9fbcf4b00f2671dba205
+    metrics:
+    - type: accuracy
+      value: 75.76119402985074
+    - type: ap
+      value: 39.03628777559392
+    - type: f1
+      value: 69.85860402259618
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_polarity
+      name: MTEB AmazonPolarityClassification
+      config: default
+      split: test
+      revision: e2d317d38cd51312af73b3d32a06d1a08b442046
+    metrics:
+    - type: accuracy
+      value: 93.29920000000001
+    - type: ap
+      value: 90.03479490717608
+    - type: f1
+      value: 93.28554395248467
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_reviews_multi
+      name: MTEB AmazonReviewsClassification (en)
+      config: en
+      split: test
+      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
+    metrics:
+    - type: accuracy
+      value: 49.98799999999999
+    - type: f1
+      value: 49.46151232451642
+  - task:
+      type: Retrieval
+    dataset:
+      type: mteb/arguana
+      name: MTEB ArguAna
+      config: default
+      split: test
+      revision: c22ab2a51041ffd869aaddef7af8d8215647e41a
+    metrics:
+    - type: map_at_1
+      value: 31.935000000000002
+    - type: map_at_10
+      value: 48.791000000000004
+    - type: map_at_100
+      value: 49.619
+    - type: map_at_1000
+      value: 49.623
+    - type: map_at_3
+      value: 44.334
+    - type: map_at_5
+      value: 46.908
+    - type: mrr_at_1
+      value: 32.93
+    - type: mrr_at_10
+      value: 49.158
+    - type: mrr_at_100
+      value: 50.00599999999999
+    - type: mrr_at_1000
+      value: 50.01
+    - type: mrr_at_3
+      value: 44.618
+    - type: mrr_at_5
+      value: 47.325
+    - type: ndcg_at_1
+      value: 31.935000000000002
+    - type: ndcg_at_10
+      value: 57.593
+    - type: ndcg_at_100
+      value: 60.841
+    - type: ndcg_at_1000
+      value: 60.924
+    - type: ndcg_at_3
+      value: 48.416
+    - type: ndcg_at_5
+      value: 53.05
+    - type: precision_at_1
+      value: 31.935000000000002
+    - type: precision_at_10
+      value: 8.549
+    - type: precision_at_100
+      value: 0.9900000000000001
+    - type: precision_at_1000
+      value: 0.1
+    - type: precision_at_3
+      value: 20.081
+    - type: precision_at_5
+      value: 14.296000000000001
+    - type: recall_at_1
+      value: 31.935000000000002
+    - type: recall_at_10
+      value: 85.491
+    - type: recall_at_100
+      value: 99.004
+    - type: recall_at_1000
+      value: 99.644
+    - type: recall_at_3
+      value: 60.242
+    - type: recall_at_5
+      value: 71.479
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/arxiv-clustering-p2p
+      name: MTEB ArxivClusteringP2P
+      config: default
+      split: test
+      revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
+    metrics:
+    - type: v_measure
+      value: 47.78438534940855
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/arxiv-clustering-s2s
+      name: MTEB ArxivClusteringS2S
+      config: default
+      split: test
+      revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
+    metrics:
+    - type: v_measure
+      value: 40.12916178519471
+  - task:
+      type: Reranking
+    dataset:
+      type: mteb/askubuntudupquestions-reranking
+      name: MTEB AskUbuntuDupQuestions
+      config: default
+      split: test
+      revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
+    metrics:
+    - type: map
+      value: 62.125361608299855
+    - type: mrr
+      value: 74.92525172580574
+  - task:
+      type: STS
+    dataset:
+      type: mteb/biosses-sts
+      name: MTEB BIOSSES
+      config: default
+      split: test
+      revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
+    metrics:
+    - type: cos_sim_pearson
+      value: 88.64322910336641
+    - type: cos_sim_spearman
+      value: 87.20138453306345
+    - type: euclidean_pearson
+      value: 87.08547818178234
+    - type: euclidean_spearman
+      value: 87.17066094143931
+    - type: manhattan_pearson
+      value: 87.30053110771618
+    - type: manhattan_spearman
+      value: 86.86824441211934
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/banking77
+      name: MTEB Banking77Classification
+      config: default
+      split: test
+      revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
+    metrics:
+    - type: accuracy
+      value: 86.3961038961039
+    - type: f1
+      value: 86.3669961645295
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/biorxiv-clustering-p2p
+      name: MTEB BiorxivClusteringP2P
+      config: default
+      split: test
+      revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
+    metrics:
+    - type: v_measure
+      value: 39.40291404289857
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/biorxiv-clustering-s2s
+      name: MTEB BiorxivClusteringS2S
+      config: default
+      split: test
+      revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
+    metrics:
+    - type: v_measure
+      value: 35.102356817746816
+  - task:
+      type: Retrieval
+    dataset:
+      type: mteb/cqadupstack-android
+      name: MTEB CQADupstackAndroidRetrieval
+      config: default
+      split: test
+      revision: f46a197baaae43b4f621051089b82a364682dfeb
+    metrics:
+    - type: map_at_1
+      value: 31.013
+    - type: map_at_10
+      value: 42.681999999999995
+    - type: map_at_100
+      value: 44.24
+    - type: map_at_1000
+      value: 44.372
+    - type: map_at_3
+      value: 39.181
+    - type: map_at_5
+      value: 41.071999999999996
+    - type: mrr_at_1
+      value: 38.196999999999996
+    - type: mrr_at_10
+      value: 48.604
+    - type: mrr_at_100
+      value: 49.315
+    - type: mrr_at_1000
+      value: 49.363
+    - type: mrr_at_3
+      value: 45.756
+    - type: mrr_at_5
+      value: 47.43
+    - type: ndcg_at_1
+      value: 38.196999999999996
+    - type: ndcg_at_10
+      value: 49.344
+    - type: ndcg_at_100
+      value: 54.662
+    - type: ndcg_at_1000
+      value: 56.665
+    - type: ndcg_at_3
+      value: 44.146
+    - type: ndcg_at_5
+      value: 46.514
+    - type: precision_at_1
+      value: 38.196999999999996
+    - type: precision_at_10
+      value: 9.571
+    - type: precision_at_100
+      value: 1.542
+    - type: precision_at_1000
+      value: 0.202
+    - type: precision_at_3
+      value: 21.364
+    - type: precision_at_5
+      value: 15.336
+    - type: recall_at_1
+      value: 31.013
+    - type: recall_at_10
+      value: 61.934999999999995
+    - type: recall_at_100
+      value: 83.923
+    - type: recall_at_1000
+      value: 96.601
+    - type: recall_at_3
+      value: 46.86
+    - type: recall_at_5
+      value: 53.620000000000005
+  - task:
+      type: Retrieval
+    dataset:
+      type: mteb/cqadupstack-english
+      name: MTEB CQADupstackEnglishRetrieval
+      config: default
+      split: test
+      revision: ad9991cb51e31e31e430383c75ffb2885547b5f0
+    metrics:
+    - type: map_at_1
+      value: 29.84
+    - type: map_at_10
+      value: 39.335
+    - type: map_at_100
+      value: 40.647
+    - type: map_at_1000
+      value: 40.778
+    - type: map_at_3
+      value: 36.556
+    - type: map_at_5
+      value: 38.048
+    - type: mrr_at_1
+      value: 36.815
+    - type: mrr_at_10
+      value: 45.175
+    - type: mrr_at_100
+      value: 45.907
+    - type: mrr_at_1000
+      value: 45.946999999999996
+    - type: mrr_at_3
+      value: 42.909000000000006
+    - type: mrr_at_5
+      value: 44.227
+    - type: ndcg_at_1
+      value: 36.815
+    - type: ndcg_at_10
+      value: 44.783
+    - type: ndcg_at_100
+      value: 49.551
+    - type: ndcg_at_1000
+      value: 51.612
+    - type: ndcg_at_3
+      value: 40.697
+    - type: ndcg_at_5
+      value: 42.558
+    - type: precision_at_1
+      value: 36.815
+    - type: precision_at_10
+      value: 8.363
+    - type: precision_at_100
+      value: 1.385
+    - type: precision_at_1000
+      value: 0.186
+    - type: precision_at_3
+      value: 19.342000000000002
+    - type: precision_at_5
+      value: 13.706999999999999
+    - type: recall_at_1
+      value: 29.84
+    - type: recall_at_10
+      value: 54.164
+    - type: recall_at_100
+      value: 74.36
+    - type: recall_at_1000
+      value: 87.484
+    - type: recall_at_3
+      value: 42.306
+    - type: recall_at_5
+      value: 47.371
+  - task:
+      type: Retrieval
+    dataset:
+      type: mteb/cqadupstack-gaming
+      name: MTEB CQADupstackGamingRetrieval
+      config: default
+      split: test
+      revision: 4885aa143210c98657558c04aaf3dc47cfb54340
+    metrics:
+    - type: map_at_1
+      value: 39.231
+    - type: map_at_10
+      value: 51.44800000000001
+    - type: map_at_100
+      value: 52.574
+    - type: map_at_1000
+      value: 52.629999999999995
+    - type: map_at_3
+      value: 48.077
+    - type: map_at_5
+      value: 50.019000000000005
+    - type: mrr_at_1
+      value: 44.89
+    - type: mrr_at_10
+      value: 54.803000000000004
+    - type: mrr_at_100
+      value: 55.556000000000004
+    - type: mrr_at_1000
+      value: 55.584
+    - type: mrr_at_3
+      value: 52.32
+    - type: mrr_at_5
+      value: 53.846000000000004
+    - type: ndcg_at_1
+      value: 44.89
+    - type: ndcg_at_10
+      value: 57.228
+    - type: ndcg_at_100
+      value: 61.57
+    - type: ndcg_at_1000
+      value: 62.613
+    - type: ndcg_at_3
+      value: 51.727000000000004
+    - type: ndcg_at_5
+      value: 54.496
+    - type: precision_at_1
+      value: 44.89
+    - type: precision_at_10
+      value: 9.266
+    - type: precision_at_100
+      value: 1.2309999999999999
+    - type: precision_at_1000
+      value: 0.136
+    - type: precision_at_3
+      value: 23.051
+    - type: precision_at_5
+      value: 15.987000000000002
+    - type: recall_at_1
+      value: 39.231
+    - type: recall_at_10
+      value: 70.82000000000001
+    - type: recall_at_100
+      value: 89.446
+    - type: recall_at_1000
+      value: 96.665
+    - type: recall_at_3
+      value: 56.40500000000001
+    - type: recall_at_5
+      value: 62.993
+  - task:
+      type: Retrieval
+    dataset:
+      type: mteb/cqadupstack-gis
+      name: MTEB CQADupstackGisRetrieval
+      config: default
+      split: test
+      revision: 5003b3064772da1887988e05400cf3806fe491f2
+    metrics:
+    - type: map_at_1
+      value: 25.296000000000003
+    - type: map_at_10
+      value: 34.021
+    - type: map_at_100
+      value: 35.158
+    - type: map_at_1000
+      value: 35.233
+    - type: map_at_3
+      value: 31.424999999999997
+    - type: map_at_5
+      value: 33.046
+    - type: mrr_at_1
+      value: 27.232
+    - type: mrr_at_10
+      value: 36.103
+    - type: mrr_at_100
+      value: 37.076
+    - type: mrr_at_1000
+      value: 37.135
+    - type: mrr_at_3
+      value: 33.635
+    - type: mrr_at_5
+      value: 35.211
+    - type: ndcg_at_1
+      value: 27.232
+    - type: ndcg_at_10
+      value: 38.878
+    - type: ndcg_at_100
+      value: 44.284
+    - type: ndcg_at_1000
+      value: 46.268
+    - type: ndcg_at_3
+      value: 33.94
+    - type: ndcg_at_5
+      value: 36.687
+    - type: precision_at_1
+      value: 27.232
+    - type: precision_at_10
+      value: 5.921
+    - type: precision_at_100
+      value: 0.907
+    - type: precision_at_1000
+      value: 0.11199999999999999
+    - type: precision_at_3
+      value: 14.426
+    - type: precision_at_5
+      value: 10.215
+    - type: recall_at_1
+      value: 25.296000000000003
+    - type: recall_at_10
+      value: 51.708
+    - type: recall_at_100
+      value: 76.36699999999999
+    - type: recall_at_1000
+      value: 91.306
+    - type: recall_at_3
+      value: 38.651
+    - type: recall_at_5
+      value: 45.201
+  - task:
+      type: Retrieval
+    dataset:
+      type: mteb/cqadupstack-mathematica
+      name: MTEB CQADupstackMathematicaRetrieval
+      config: default
+      split: test
+      revision: 90fceea13679c63fe563ded68f3b6f06e50061de
+    metrics:
+    - type: map_at_1
+      value: 16.24
+    - type: map_at_10
+      value: 24.696
+    - type: map_at_100
+      value: 25.945
+    - type: map_at_1000
+      value: 26.069
+    - type: map_at_3
+      value: 22.542
+    - type: map_at_5
+      value: 23.526
+    - type: mrr_at_1
+      value: 20.149
+    - type: mrr_at_10
+      value: 29.584
+    - type: mrr_at_100
+      value: 30.548
+    - type: mrr_at_1000
+      value: 30.618000000000002
+    - type: mrr_at_3
+      value: 27.301
+    - type: mrr_at_5
+      value: 28.563
+    - type: ndcg_at_1
+      value: 20.149
+    - type: ndcg_at_10
+      value: 30.029
+    - type: ndcg_at_100
+      value: 35.812
+    - type: ndcg_at_1000
+      value: 38.755
+    - type: ndcg_at_3
+      value: 26.008
+    - type: ndcg_at_5
+      value: 27.517000000000003
+    - type: precision_at_1
+      value: 20.149
+    - type: precision_at_10
+      value: 5.647
+    - type: precision_at_100
+      value: 0.968
+    - type: precision_at_1000
+      value: 0.136
+    - type: precision_at_3
+      value: 12.934999999999999
+    - type: precision_at_5
+      value: 8.955
+    - type: recall_at_1
+      value: 16.24
+    - type: recall_at_10
+      value: 41.464
+    - type: recall_at_100
+      value: 66.781
+    - type: recall_at_1000
+      value: 87.85300000000001
+    - type: recall_at_3
+      value: 29.822
+    - type: recall_at_5
+      value: 34.096
+  - task:
+      type: Retrieval
+    dataset:
+      type: mteb/cqadupstack-physics
+      name: MTEB CQADupstackPhysicsRetrieval
+      config: default
+      split: test
+      revision: 79531abbd1fb92d06c6d6315a0cbbbf5bb247ea4
+    metrics:
+    - type: map_at_1
+      value: 29.044999999999998
+    - type: map_at_10
+      value: 39.568999999999996
+    - type: map_at_100
+      value: 40.831
+    - type: map_at_1000
+      value: 40.948
+    - type: map_at_3
+      value: 36.495
+    - type: map_at_5
+      value: 38.21
+    - type: mrr_at_1
+      value: 35.611
+    - type: mrr_at_10
+      value: 45.175
+    - type: mrr_at_100
+      value: 45.974
+    - type: mrr_at_1000
+      value: 46.025
+    - type: mrr_at_3
+      value: 42.765
+    - type: mrr_at_5
+      value: 44.151
+    - type: ndcg_at_1
+      value: 35.611
+    - type: ndcg_at_10
+      value: 45.556999999999995
+    - type: ndcg_at_100
+      value: 50.86000000000001
+    - type: ndcg_at_1000
+      value: 52.983000000000004
+    - type: ndcg_at_3
+      value: 40.881
+    - type: ndcg_at_5
+      value: 43.035000000000004
+    - type: precision_at_1
+      value: 35.611
+    - type: precision_at_10
+      value: 8.306
+    - type: precision_at_100
+      value: 1.276
+    - type: precision_at_1000
+      value: 0.165
+    - type: precision_at_3
+      value: 19.57
+    - type: precision_at_5
+      value: 13.725000000000001
+    - type: recall_at_1
+      value: 29.044999999999998
+    - type: recall_at_10
+      value: 57.513999999999996
+    - type: recall_at_100
+      value: 80.152
+    - type: recall_at_1000
+      value: 93.982
+    - type: recall_at_3
+      value: 44.121
+    - type: recall_at_5
+      value: 50.007000000000005
+  - task:
+      type: Retrieval
+    dataset:
+      type: mteb/cqadupstack-programmers
+      name: MTEB CQADupstackProgrammersRetrieval
+      config: default
+      split: test
+      revision: 6184bc1440d2dbc7612be22b50686b8826d22b32
+    metrics:
+    - type: map_at_1
+      value: 22.349
+    - type: map_at_10
+      value: 33.434000000000005
+    - type: map_at_100
+      value: 34.8
+    - type: map_at_1000
+      value: 34.919
+    - type: map_at_3
+      value: 30.348000000000003
+    - type: map_at_5
+      value: 31.917
+    - type: mrr_at_1
+      value: 28.195999999999998
+    - type: mrr_at_10
+      value: 38.557
+    - type: mrr_at_100
+      value: 39.550999999999995
+    - type: mrr_at_1000
+      value: 39.607
+    - type: mrr_at_3
+      value: 36.035000000000004
+    - type: mrr_at_5
+      value: 37.364999999999995
+    - type: ndcg_at_1
+      value: 28.195999999999998
+    - type: ndcg_at_10
+      value: 39.656000000000006
+    - type: ndcg_at_100
+      value: 45.507999999999996
+    - type: ndcg_at_1000
+      value: 47.848
+    - type: ndcg_at_3
+      value: 34.609
+    - type: ndcg_at_5
+      value: 36.65
+    - type: precision_at_1
+      value: 28.195999999999998
+    - type: precision_at_10
+      value: 7.534000000000001
+    - type: precision_at_100
+      value: 1.217
+    - type: precision_at_1000
+      value: 0.158
+    - type: precision_at_3
+      value: 17.085
+    - type: precision_at_5
+      value: 12.169
+    - type: recall_at_1
+      value: 22.349
+    - type: recall_at_10
+      value: 53.127
+    - type: recall_at_100
+      value: 77.884
+    - type: recall_at_1000
+      value: 93.705
+    - type: recall_at_3
+      value: 38.611000000000004
+    - type: recall_at_5
+      value: 44.182
+  - task:
+      type: Retrieval
+    dataset:
+      type: mteb/cqadupstack
+      name: MTEB CQADupstackRetrieval
+      config: default
+      split: test
+      revision: 4ffe81d471b1924886b33c7567bfb200e9eec5c4
+    metrics:
+    - type: map_at_1
+      value: 25.215749999999996
+    - type: map_at_10
+      value: 34.332750000000004
+    - type: map_at_100
+      value: 35.58683333333333
+    - type: map_at_1000
+      value: 35.70458333333333
+    - type: map_at_3
+      value: 31.55441666666667
+    - type: map_at_5
+      value: 33.100833333333334
+    - type: mrr_at_1
+      value: 29.697250000000004
+    - type: mrr_at_10
+      value: 38.372249999999994
+    - type: mrr_at_100
+      value: 39.26708333333334
+    - type: mrr_at_1000
+      value: 39.3265
+    - type: mrr_at_3
+      value: 35.946083333333334
+    - type: mrr_at_5
+      value: 37.336999999999996
+    - type: ndcg_at_1
+      value: 29.697250000000004
+    - type: ndcg_at_10
+      value: 39.64575
+    - type: ndcg_at_100
+      value: 44.996833333333335
+    - type: ndcg_at_1000
+      value: 47.314499999999995
+    - type: ndcg_at_3
+      value: 34.93383333333334
+    - type: ndcg_at_5
+      value: 37.15291666666667
+    - type: precision_at_1
+      value: 29.697250000000004
+    - type: precision_at_10
+      value: 6.98825
+    - type: precision_at_100
+      value: 1.138
+    - type: precision_at_1000
+      value: 0.15283333333333332
+    - type: precision_at_3
+      value: 16.115583333333333
+    - type: precision_at_5
+      value: 11.460916666666666
+    - type: recall_at_1
+      value: 25.215749999999996
+    - type: recall_at_10
+      value: 51.261250000000004
+    - type: recall_at_100
+      value: 74.67258333333334
+    - type: recall_at_1000
+      value: 90.72033333333334
+    - type: recall_at_3
+      value: 38.1795
+    - type: recall_at_5
+      value: 43.90658333333334
+  - task:
+      type: Retrieval
+    dataset:
+      type: mteb/cqadupstack-stats
+      name: MTEB CQADupstackStatsRetrieval
+      config: default
+      split: test
+      revision: 65ac3a16b8e91f9cee4c9828cc7c335575432a2a
+    metrics:
+    - type: map_at_1
+      value: 24.352
+    - type: map_at_10
+      value: 30.576999999999998
+    - type: map_at_100
+      value: 31.545
+    - type: map_at_1000
+      value: 31.642
+    - type: map_at_3
+      value: 28.605000000000004
+    - type: map_at_5
+      value: 29.828
+    - type: mrr_at_1
+      value: 26.994
+    - type: mrr_at_10
+      value: 33.151
+    - type: mrr_at_100
+      value: 33.973
+    - type: mrr_at_1000
+      value: 34.044999999999995
+    - type: mrr_at_3
+      value: 31.135
+    - type: mrr_at_5
+      value: 32.262
+    - type: ndcg_at_1
+      value: 26.994
+    - type: ndcg_at_10
+      value: 34.307
+    - type: ndcg_at_100
+      value: 39.079
+    - type: ndcg_at_1000
+      value: 41.548
+    - type: ndcg_at_3
+      value: 30.581000000000003
+    - type: ndcg_at_5
+      value: 32.541
+    - type: precision_at_1
+      value: 26.994
+    - type: precision_at_10
+      value: 5.244999999999999
+    - type: precision_at_100
+      value: 0.831
+    - type: precision_at_1000
+      value: 0.11100000000000002
+    - type: precision_at_3
+      value: 12.781
+    - type: precision_at_5
+      value: 9.017999999999999
+    - type: recall_at_1
+      value: 24.352
+    - type: recall_at_10
+      value: 43.126999999999995
+    - type: recall_at_100
+      value: 64.845
+    - type: recall_at_1000
+      value: 83.244
+    - type: recall_at_3
+      value: 33.308
+    - type: recall_at_5
+      value: 37.984
+  - task:
+      type: Retrieval
+    dataset:
+      type: mteb/cqadupstack-tex
+      name: MTEB CQADupstackTexRetrieval
+      config: default
+      split: test
+      revision: 46989137a86843e03a6195de44b09deda022eec7
+    metrics:
+    - type: map_at_1
+      value: 16.592000000000002
+    - type: map_at_10
+      value: 23.29
+    - type: map_at_100
+      value: 24.423000000000002
+    - type: map_at_1000
+      value: 24.554000000000002
+    - type: map_at_3
+      value: 20.958
+    - type: map_at_5
+      value: 22.267
+    - type: mrr_at_1
+      value: 20.061999999999998
+    - type: mrr_at_10
+      value: 26.973999999999997
+    - type: mrr_at_100
+      value: 27.944999999999997
+    - type: mrr_at_1000
+      value: 28.023999999999997
+    - type: mrr_at_3
+      value: 24.839
+    - type: mrr_at_5
+      value: 26.033
+    - type: ndcg_at_1
+      value: 20.061999999999998
+    - type: ndcg_at_10
+      value: 27.682000000000002
+    - type: ndcg_at_100
+      value: 33.196
+    - type: ndcg_at_1000
+      value: 36.246
+    - type: ndcg_at_3
+      value: 23.559
+    - type: ndcg_at_5
+      value: 25.507
+    - type: precision_at_1
+      value: 20.061999999999998
+    - type: precision_at_10
+      value: 5.086
+    - type: precision_at_100
+      value: 0.9249999999999999
+    - type: precision_at_1000
+      value: 0.136
+    - type: precision_at_3
+      value: 11.046
+    - type: precision_at_5
+      value: 8.149000000000001
+    - type: recall_at_1
+      value: 16.592000000000002
+    - type: recall_at_10
+      value: 37.181999999999995
+    - type: recall_at_100
+      value: 62.224999999999994
+    - type: recall_at_1000
+      value: 84.072
+    - type: recall_at_3
+      value: 25.776
+    - type: recall_at_5
+      value: 30.680000000000003
+  - task:
+      type: Retrieval
+    dataset:
+      type: mteb/cqadupstack-unix
+      name: MTEB CQADupstackUnixRetrieval
+      config: default
+      split: test
+      revision: 6c6430d3a6d36f8d2a829195bc5dc94d7e063e53
+    metrics:
+    - type: map_at_1
+      value: 26.035999999999998
+    - type: map_at_10
+      value: 34.447
+    - type: map_at_100
+      value: 35.697
+    - type: map_at_1000
+      value: 35.802
+    - type: map_at_3
+      value: 31.64
+    - type: map_at_5
+      value: 33.056999999999995
+    - type: mrr_at_1
+      value: 29.851
+    - type: mrr_at_10
+      value: 38.143
+    - type: mrr_at_100
+      value: 39.113
+    - type: mrr_at_1000
+      value: 39.175
+    - type: mrr_at_3
+      value: 35.665
+    - type: mrr_at_5
+      value: 36.901
+    - type: ndcg_at_1
+      value: 29.851
+    - type: ndcg_at_10
+      value: 39.554
+    - type: ndcg_at_100
+      value: 45.091
+    - type: ndcg_at_1000
+      value: 47.504000000000005
+    - type: ndcg_at_3
+      value: 34.414
+    - type: ndcg_at_5
+      value: 36.508
+    - type: precision_at_1
+      value: 29.851
+    - type: precision_at_10
+      value: 6.614000000000001
+    - type: precision_at_100
+      value: 1.051
+    - type: precision_at_1000
+      value: 0.13699999999999998
+    - type: precision_at_3
+      value: 15.329999999999998
+    - type: precision_at_5
+      value: 10.671999999999999
+    - type: recall_at_1
+      value: 26.035999999999998
+    - type: recall_at_10
+      value: 51.396
+    - type: recall_at_100
+      value: 75.09
+    - type: recall_at_1000
+      value: 91.904
+    - type: recall_at_3
+      value: 37.378
+    - type: recall_at_5
+      value: 42.69
+  - task:
+      type: Retrieval
+    dataset:
+      type: mteb/cqadupstack-webmasters
+      name: MTEB CQADupstackWebmastersRetrieval
+      config: default
+      split: test
+      revision: 160c094312a0e1facb97e55eeddb698c0abe3571
+    metrics:
+    - type: map_at_1
+      value: 23.211000000000002
+    - type: map_at_10
+      value: 32.231
+    - type: map_at_100
+      value: 33.772999999999996
+    - type: map_at_1000
+      value: 33.982
+    - type: map_at_3
+      value: 29.128
+    - type: map_at_5
+      value: 31.002999999999997
+    - type: mrr_at_1
+      value: 27.668
+    - type: mrr_at_10
+      value: 36.388
+    - type: mrr_at_100
+      value: 37.384
+    - type: mrr_at_1000
+      value: 37.44
+    - type: mrr_at_3
+      value: 33.762
+    - type: mrr_at_5
+      value: 35.234
+    - type: ndcg_at_1
+      value: 27.668
+    - type: ndcg_at_10
+      value: 38.043
+    - type: ndcg_at_100
+      value: 44.21
+    - type: ndcg_at_1000
+      value: 46.748
+    - type: ndcg_at_3
+      value: 32.981
+    - type: ndcg_at_5
+      value: 35.58
+    - type: precision_at_1
+      value: 27.668
+    - type: precision_at_10
+      value: 7.352
+    - type: precision_at_100
+      value: 1.5
+    - type: precision_at_1000
+      value: 0.23700000000000002
+    - type: precision_at_3
+      value: 15.613
+    - type: precision_at_5
+      value: 11.501999999999999
+    - type: recall_at_1
+      value: 23.211000000000002
+    - type: recall_at_10
+      value: 49.851
+    - type: recall_at_100
+      value: 77.596
+    - type: recall_at_1000
+      value: 93.683
+    - type: recall_at_3
+      value: 35.403
+    - type: recall_at_5
+      value: 42.485
+  - task:
+      type: Retrieval
+    dataset:
+      type: mteb/cqadupstack-wordpress
+      name: MTEB CQADupstackWordpressRetrieval
+      config: default
+      split: test
+      revision: 4ffe81d471b1924886b33c7567bfb200e9eec5c4
+    metrics:
+    - type: map_at_1
+      value: 19.384
+    - type: map_at_10
+      value: 26.262999999999998
+    - type: map_at_100
+      value: 27.409
+    - type: map_at_1000
+      value: 27.526
+    - type: map_at_3
+      value: 23.698
+    - type: map_at_5
+      value: 25.217
+    - type: mrr_at_1
+      value: 20.702
+    - type: mrr_at_10
+      value: 27.810000000000002
+    - type: mrr_at_100
+      value: 28.863
+    - type: mrr_at_1000
+      value: 28.955
+    - type: mrr_at_3
+      value: 25.230999999999998
+    - type: mrr_at_5
+      value: 26.821
+    - type: ndcg_at_1
+      value: 20.702
+    - type: ndcg_at_10
+      value: 30.688
+    - type: ndcg_at_100
+      value: 36.138999999999996
+    - type: ndcg_at_1000
+      value: 38.984
+    - type: ndcg_at_3
+      value: 25.663000000000004
+    - type: ndcg_at_5
+      value: 28.242
+    - type: precision_at_1
+      value: 20.702
+    - type: precision_at_10
+      value: 4.954
+    - type: precision_at_100
+      value: 0.823
+    - type: precision_at_1000
+      value: 0.11800000000000001
+    - type: precision_at_3
+      value: 10.844
+    - type: precision_at_5
+      value: 8.096
+    - type: recall_at_1
+      value: 19.384
+    - type: recall_at_10
+      value: 42.847
+    - type: recall_at_100
+      value: 67.402
+    - type: recall_at_1000
+      value: 88.145
+    - type: recall_at_3
+      value: 29.513
+    - type: recall_at_5
+      value: 35.57
+  - task:
+      type: Retrieval
+    dataset:
+      type: mteb/climate-fever
+      name: MTEB ClimateFEVER
+      config: default
+      split: test
+      revision: 47f2ac6acb640fc46020b02a5b59fdda04d39380
+    metrics:
+    - type: map_at_1
+      value: 14.915000000000001
+    - type: map_at_10
+      value: 25.846999999999998
+    - type: map_at_100
+      value: 27.741
+    - type: map_at_1000
+      value: 27.921000000000003
+    - type: map_at_3
+      value: 21.718
+    - type: map_at_5
+      value: 23.948
+    - type: mrr_at_1
+      value: 33.941
+    - type: mrr_at_10
+      value: 46.897
+    - type: mrr_at_100
+      value: 47.63
+    - type: mrr_at_1000
+      value: 47.658
+    - type: mrr_at_3
+      value: 43.919999999999995
+    - type: mrr_at_5
+      value: 45.783
+    - type: ndcg_at_1
+      value: 33.941
+    - type: ndcg_at_10
+      value: 35.202
+    - type: ndcg_at_100
+      value: 42.132
+    - type: ndcg_at_1000
+      value: 45.190999999999995
+    - type: ndcg_at_3
+      value: 29.68
+    - type: ndcg_at_5
+      value: 31.631999999999998
+    - type: precision_at_1
+      value: 33.941
+    - type: precision_at_10
+      value: 10.906
+    - type: precision_at_100
+      value: 1.8339999999999999
+    - type: precision_at_1000
+      value: 0.241
+    - type: precision_at_3
+      value: 22.606
+    - type: precision_at_5
+      value: 17.081
+    - type: recall_at_1
+      value: 14.915000000000001
+    - type: recall_at_10
+      value: 40.737
+    - type: recall_at_100
+      value: 64.42
+    - type: recall_at_1000
+      value: 81.435
+    - type: recall_at_3
+      value: 26.767000000000003
+    - type: recall_at_5
+      value: 32.895
+  - task:
+      type: Retrieval
+    dataset:
+      type: mteb/dbpedia
+      name: MTEB DBPedia
+      config: default
+      split: test
+      revision: c0f706b76e590d620bd6618b3ca8efdd34e2d659
+    metrics:
+    - type: map_at_1
+      value: 8.665000000000001
+    - type: map_at_10
+      value: 19.087
+    - type: map_at_100
+      value: 26.555
+    - type: map_at_1000
+      value: 28.105999999999998
+    - type: map_at_3
+      value: 13.858999999999998
+    - type: map_at_5
+      value: 16.083
+    - type: mrr_at_1
+      value: 68.5
+    - type: mrr_at_10
+      value: 76.725
+    - type: mrr_at_100
+      value: 76.974
+    - type: mrr_at_1000
+      value: 76.981
+    - type: mrr_at_3
+      value: 75.583
+    - type: mrr_at_5
+      value: 76.208
+    - type: ndcg_at_1
+      value: 55.875
+    - type: ndcg_at_10
+      value: 41.018
+    - type: ndcg_at_100
+      value: 44.982
+    - type: ndcg_at_1000
+      value: 52.43
+    - type: ndcg_at_3
+      value: 46.534
+    - type: ndcg_at_5
+      value: 43.083
+    - type: precision_at_1
+      value: 68.5
+    - type: precision_at_10
+      value: 32.35
+    - type: precision_at_100
+      value: 10.078
+    - type: precision_at_1000
+      value: 1.957
+    - type: precision_at_3
+      value: 50.083
+    - type: precision_at_5
+      value: 41.3
+    - type: recall_at_1
+      value: 8.665000000000001
+    - type: recall_at_10
+      value: 24.596999999999998
+    - type: recall_at_100
+      value: 50.612
+    - type: recall_at_1000
+      value: 74.24
+    - type: recall_at_3
+      value: 15.337
+    - type: recall_at_5
+      value: 18.796
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/emotion
+      name: MTEB EmotionClassification
+      config: default
+      split: test
+      revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
+    metrics:
+    - type: accuracy
+      value: 55.06500000000001
+    - type: f1
+      value: 49.827367590822035
+  - task:
+      type: Retrieval
+    dataset:
+      type: mteb/fever
+      name: MTEB FEVER
+      config: default
+      split: test
+      revision: bea83ef9e8fb933d90a2f1d5515737465d613e12
+    metrics:
+    - type: map_at_1
+      value: 76.059
+    - type: map_at_10
+      value: 83.625
+    - type: map_at_100
+      value: 83.845
+    - type: map_at_1000
+      value: 83.858
+    - type: map_at_3
+      value: 82.67099999999999
+    - type: map_at_5
+      value: 83.223
+    - type: mrr_at_1
+      value: 82.013
+    - type: mrr_at_10
+      value: 88.44800000000001
+    - type: mrr_at_100
+      value: 88.535
+    - type: mrr_at_1000
+      value: 88.537
+    - type: mrr_at_3
+      value: 87.854
+    - type: mrr_at_5
+      value: 88.221
+    - type: ndcg_at_1
+      value: 82.013
+    - type: ndcg_at_10
+      value: 87.128
+    - type: ndcg_at_100
+      value: 87.922
+    - type: ndcg_at_1000
+      value: 88.166
+    - type: ndcg_at_3
+      value: 85.648
+    - type: ndcg_at_5
+      value: 86.366
+    - type: precision_at_1
+      value: 82.013
+    - type: precision_at_10
+      value: 10.32
+    - type: precision_at_100
+      value: 1.093
+    - type: precision_at_1000
+      value: 0.11299999999999999
+    - type: precision_at_3
+      value: 32.408
+    - type: precision_at_5
+      value: 19.973
+    - type: recall_at_1
+      value: 76.059
+    - type: recall_at_10
+      value: 93.229
+    - type: recall_at_100
+      value: 96.387
+    - type: recall_at_1000
+      value: 97.916
+    - type: recall_at_3
+      value: 89.025
+    - type: recall_at_5
+      value: 90.96300000000001
+  - task:
+      type: Retrieval
+    dataset:
+      type: mteb/fiqa
+      name: MTEB FiQA2018
+      config: default
+      split: test
+      revision: 27a168819829fe9bcd655c2df245fb19452e8e06
+    metrics:
+    - type: map_at_1
+      value: 20.479
+    - type: map_at_10
+      value: 33.109
+    - type: map_at_100
+      value: 34.803
+    - type: map_at_1000
+      value: 35.003
+    - type: map_at_3
+      value: 28.967
+    - type: map_at_5
+      value: 31.385
+    - type: mrr_at_1
+      value: 40.278000000000006
+    - type: mrr_at_10
+      value: 48.929
+    - type: mrr_at_100
+      value: 49.655
+    - type: mrr_at_1000
+      value: 49.691
+    - type: mrr_at_3
+      value: 46.605000000000004
+    - type: mrr_at_5
+      value: 48.056
+    - type: ndcg_at_1
+      value: 40.278000000000006
+    - type: ndcg_at_10
+      value: 40.649
+    - type: ndcg_at_100
+      value: 47.027
+    - type: ndcg_at_1000
+      value: 50.249
+    - type: ndcg_at_3
+      value: 37.364000000000004
+    - type: ndcg_at_5
+      value: 38.494
+    - type: precision_at_1
+      value: 40.278000000000006
+    - type: precision_at_10
+      value: 11.327
+    - type: precision_at_100
+      value: 1.802
+    - type: precision_at_1000
+      value: 0.23700000000000002
+    - type: precision_at_3
+      value: 25.102999999999998
+    - type: precision_at_5
+      value: 18.457
+    - type: recall_at_1
+      value: 20.479
+    - type: recall_at_10
+      value: 46.594
+    - type: recall_at_100
+      value: 71.101
+    - type: recall_at_1000
+      value: 90.31099999999999
+    - type: recall_at_3
+      value: 33.378
+    - type: recall_at_5
+      value: 39.587
+  - task:
+      type: Retrieval
+    dataset:
+      type: mteb/hotpotqa
+      name: MTEB HotpotQA
+      config: default
+      split: test
+      revision: ab518f4d6fcca38d87c25209f94beba119d02014
+    metrics:
+    - type: map_at_1
+      value: 36.59
+    - type: map_at_10
+      value: 58.178
+    - type: map_at_100
+      value: 59.095
+    - type: map_at_1000
+      value: 59.16400000000001
+    - type: map_at_3
+      value: 54.907
+    - type: map_at_5
+      value: 56.89999999999999
+    - type: mrr_at_1
+      value: 73.18
+    - type: mrr_at_10
+      value: 79.935
+    - type: mrr_at_100
+      value: 80.16799999999999
+    - type: mrr_at_1000
+      value: 80.17800000000001
+    - type: mrr_at_3
+      value: 78.776
+    - type: mrr_at_5
+      value: 79.522
+    - type: ndcg_at_1
+      value: 73.18
+    - type: ndcg_at_10
+      value: 66.538
+    - type: ndcg_at_100
+      value: 69.78
+    - type: ndcg_at_1000
+      value: 71.102
+    - type: ndcg_at_3
+      value: 61.739
+    - type: ndcg_at_5
+      value: 64.35600000000001
+    - type: precision_at_1
+      value: 73.18
+    - type: precision_at_10
+      value: 14.035
+    - type: precision_at_100
+      value: 1.657
+    - type: precision_at_1000
+      value: 0.183
+    - type: precision_at_3
+      value: 39.684999999999995
+    - type: precision_at_5
+      value: 25.885
+    - type: recall_at_1
+      value: 36.59
+    - type: recall_at_10
+      value: 70.176
+    - type: recall_at_100
+      value: 82.836
+    - type: recall_at_1000
+      value: 91.526
+    - type: recall_at_3
+      value: 59.526999999999994
+    - type: recall_at_5
+      value: 64.713
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/imdb
+      name: MTEB ImdbClassification
+      config: default
+      split: test
+      revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
+    metrics:
+    - type: accuracy
+      value: 90.1472
+    - type: ap
+      value: 85.73994227076815
+    - type: f1
+      value: 90.1271700788608
+  - task:
+      type: Retrieval
+    dataset:
+      type: mteb/msmarco
+      name: MTEB MSMARCO
+      config: default
+      split: dev
+      revision: c5a29a104738b98a9e76336939199e264163d4a0
+    metrics:
+    - type: map_at_1
+      value: 21.689
+    - type: map_at_10
+      value: 33.518
+    - type: map_at_100
+      value: 34.715
+    - type: map_at_1000
+      value: 34.766000000000005
+    - type: map_at_3
+      value: 29.781000000000002
+    - type: map_at_5
+      value: 31.838
+    - type: mrr_at_1
+      value: 22.249
+    - type: mrr_at_10
+      value: 34.085
+    - type: mrr_at_100
+      value: 35.223
+    - type: mrr_at_1000
+      value: 35.266999999999996
+    - type: mrr_at_3
+      value: 30.398999999999997
+    - type: mrr_at_5
+      value: 32.437
+    - type: ndcg_at_1
+      value: 22.249
+    - type: ndcg_at_10
+      value: 40.227000000000004
+    - type: ndcg_at_100
+      value: 45.961999999999996
+    - type: ndcg_at_1000
+      value: 47.248000000000005
+    - type: ndcg_at_3
+      value: 32.566
+    - type: ndcg_at_5
+      value: 36.229
+    - type: precision_at_1
+      value: 22.249
+    - type: precision_at_10
+      value: 6.358
+    - type: precision_at_100
+      value: 0.923
+    - type: precision_at_1000
+      value: 0.10300000000000001
+    - type: precision_at_3
+      value: 13.83
+    - type: precision_at_5
+      value: 10.145999999999999
+    - type: recall_at_1
+      value: 21.689
+    - type: recall_at_10
+      value: 60.92999999999999
+    - type: recall_at_100
+      value: 87.40599999999999
+    - type: recall_at_1000
+      value: 97.283
+    - type: recall_at_3
+      value: 40.01
+    - type: recall_at_5
+      value: 48.776
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/mtop_domain
+      name: MTEB MTOPDomainClassification (en)
+      config: en
+      split: test
+      revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
+    metrics:
+    - type: accuracy
+      value: 95.28727770177838
+    - type: f1
+      value: 95.02577308660041
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/mtop_intent
+      name: MTEB MTOPIntentClassification (en)
+      config: en
+      split: test
+      revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
+    metrics:
+    - type: accuracy
+      value: 79.5736434108527
+    - type: f1
+      value: 61.2451202054398
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_massive_intent
+      name: MTEB MassiveIntentClassification (en)
+      config: en
+      split: test
+      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
+    metrics:
+    - type: accuracy
+      value: 76.01210490921318
+    - type: f1
+      value: 73.70188053982473
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_massive_scenario
+      name: MTEB MassiveScenarioClassification (en)
+      config: en
+      split: test
+      revision: 7d571f92784cd94a019292a1f45445077d0ef634
+    metrics:
+    - type: accuracy
+      value: 79.33422999327504
+    - type: f1
+      value: 79.48369022509658
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/medrxiv-clustering-p2p
+      name: MTEB MedrxivClusteringP2P
+      config: default
+      split: test
+      revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
+    metrics:
+    - type: v_measure
+      value: 34.70891567267726
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/medrxiv-clustering-s2s
+      name: MTEB MedrxivClusteringS2S
+      config: default
+      split: test
+      revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
+    metrics:
+    - type: v_measure
+      value: 32.15203494451706
+  - task:
+      type: Reranking
+    dataset:
+      type: mteb/mind_small
+      name: MTEB MindSmallReranking
+      config: default
+      split: test
+      revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
+    metrics:
+    - type: map
+      value: 31.919517862194173
+    - type: mrr
+      value: 33.15466289140483
+  - task:
+      type: Retrieval
+    dataset:
+      type: mteb/nfcorpus
+      name: MTEB NFCorpus
+      config: default
+      split: test
+      revision: ec0fa4fe99da2ff19ca1214b7966684033a58814
+    metrics:
+    - type: map_at_1
+      value: 5.992
+    - type: map_at_10
+      value: 13.197000000000001
+    - type: map_at_100
+      value: 16.907
+    - type: map_at_1000
+      value: 18.44
+    - type: map_at_3
+      value: 9.631
+    - type: map_at_5
+      value: 11.243
+    - type: mrr_at_1
+      value: 44.272
+    - type: mrr_at_10
+      value: 53.321
+    - type: mrr_at_100
+      value: 53.903
+    - type: mrr_at_1000
+      value: 53.952999999999996
+    - type: mrr_at_3
+      value: 51.393
+    - type: mrr_at_5
+      value: 52.708999999999996
+    - type: ndcg_at_1
+      value: 42.415000000000006
+    - type: ndcg_at_10
+      value: 34.921
+    - type: ndcg_at_100
+      value: 32.384
+    - type: ndcg_at_1000
+      value: 41.260000000000005
+    - type: ndcg_at_3
+      value: 40.186
+    - type: ndcg_at_5
+      value: 37.89
+    - type: precision_at_1
+      value: 44.272
+    - type: precision_at_10
+      value: 26.006
+    - type: precision_at_100
+      value: 8.44
+    - type: precision_at_1000
+      value: 2.136
+    - type: precision_at_3
+      value: 37.977
+    - type: precision_at_5
+      value: 32.755
+    - type: recall_at_1
+      value: 5.992
+    - type: recall_at_10
+      value: 17.01
+    - type: recall_at_100
+      value: 33.080999999999996
+    - type: recall_at_1000
+      value: 65.054
+    - type: recall_at_3
+      value: 10.528
+    - type: recall_at_5
+      value: 13.233
+  - task:
+      type: Retrieval
+    dataset:
+      type: mteb/nq
+      name: MTEB NQ
+      config: default
+      split: test
+      revision: b774495ed302d8c44a3a7ea25c90dbce03968f31
+    metrics:
+    - type: map_at_1
+      value: 28.871999999999996
+    - type: map_at_10
+      value: 43.286
+    - type: map_at_100
+      value: 44.432
+    - type: map_at_1000
+      value: 44.464999999999996
+    - type: map_at_3
+      value: 38.856
+    - type: map_at_5
+      value: 41.514
+    - type: mrr_at_1
+      value: 32.619
+    - type: mrr_at_10
+      value: 45.75
+    - type: mrr_at_100
+      value: 46.622
+    - type: mrr_at_1000
+      value: 46.646
+    - type: mrr_at_3
+      value: 41.985
+    - type: mrr_at_5
+      value: 44.277
+    - type: ndcg_at_1
+      value: 32.59
+    - type: ndcg_at_10
+      value: 50.895999999999994
+    - type: ndcg_at_100
+      value: 55.711999999999996
+    - type: ndcg_at_1000
+      value: 56.48800000000001
+    - type: ndcg_at_3
+      value: 42.504999999999995
+    - type: ndcg_at_5
+      value: 46.969
+    - type: precision_at_1
+      value: 32.59
+    - type: precision_at_10
+      value: 8.543000000000001
+    - type: precision_at_100
+      value: 1.123
+    - type: precision_at_1000
+      value: 0.12
+    - type: precision_at_3
+      value: 19.448
+    - type: precision_at_5
+      value: 14.218
+    - type: recall_at_1
+      value: 28.871999999999996
+    - type: recall_at_10
+      value: 71.748
+    - type: recall_at_100
+      value: 92.55499999999999
+    - type: recall_at_1000
+      value: 98.327
+    - type: recall_at_3
+      value: 49.944
+    - type: recall_at_5
+      value: 60.291
+  - task:
+      type: Retrieval
+    dataset:
+      type: mteb/quora
+      name: MTEB QuoraRetrieval
+      config: default
+      split: test
+      revision: e4e08e0b7dbe3c8700f0daef558ff32256715259
+    metrics:
+    - type: map_at_1
+      value: 70.664
+    - type: map_at_10
+      value: 84.681
+    - type: map_at_100
+      value: 85.289
+    - type: map_at_1000
+      value: 85.306
+    - type: map_at_3
+      value: 81.719
+    - type: map_at_5
+      value: 83.601
+    - type: mrr_at_1
+      value: 81.35
+    - type: mrr_at_10
+      value: 87.591
+    - type: mrr_at_100
+      value: 87.691
+    - type: mrr_at_1000
+      value: 87.693
+    - type: mrr_at_3
+      value: 86.675
+    - type: mrr_at_5
+      value: 87.29299999999999
+    - type: ndcg_at_1
+      value: 81.33
+    - type: ndcg_at_10
+      value: 88.411
+    - type: ndcg_at_100
+      value: 89.579
+    - type: ndcg_at_1000
+      value: 89.687
+    - type: ndcg_at_3
+      value: 85.613
+    - type: ndcg_at_5
+      value: 87.17
+    - type: precision_at_1
+      value: 81.33
+    - type: precision_at_10
+      value: 13.422
+    - type: precision_at_100
+      value: 1.5270000000000001
+    - type: precision_at_1000
+      value: 0.157
+    - type: precision_at_3
+      value: 37.463
+    - type: precision_at_5
+      value: 24.646
+    - type: recall_at_1
+      value: 70.664
+    - type: recall_at_10
+      value: 95.54
+    - type: recall_at_100
+      value: 99.496
+    - type: recall_at_1000
+      value: 99.978
+    - type: recall_at_3
+      value: 87.481
+    - type: recall_at_5
+      value: 91.88499999999999
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/reddit-clustering
+      name: MTEB RedditClustering
+      config: default
+      split: test
+      revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
+    metrics:
+    - type: v_measure
+      value: 55.40341814991112
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/reddit-clustering-p2p
+      name: MTEB RedditClusteringP2P
+      config: default
+      split: test
+      revision: 385e3cb46b4cfa89021f56c4380204149d0efe33
+    metrics:
+    - type: v_measure
+      value: 61.231318481346655
+  - task:
+      type: Retrieval
+    dataset:
+      type: mteb/scidocs
+      name: MTEB SCIDOCS
+      config: default
+      split: test
+      revision: f8c2fcf00f625baaa80f62ec5bd9e1fff3b8ae88
+    metrics:
+    - type: map_at_1
+      value: 4.833
+    - type: map_at_10
+      value: 13.149
+    - type: map_at_100
+      value: 15.578
+    - type: map_at_1000
+      value: 15.963
+    - type: map_at_3
+      value: 9.269
+    - type: map_at_5
+      value: 11.182
+    - type: mrr_at_1
+      value: 23.9
+    - type: mrr_at_10
+      value: 35.978
+    - type: mrr_at_100
+      value: 37.076
+    - type: mrr_at_1000
+      value: 37.126
+    - type: mrr_at_3
+      value: 32.333
+    - type: mrr_at_5
+      value: 34.413
+    - type: ndcg_at_1
+      value: 23.9
+    - type: ndcg_at_10
+      value: 21.823
+    - type: ndcg_at_100
+      value: 30.833
+    - type: ndcg_at_1000
+      value: 36.991
+    - type: ndcg_at_3
+      value: 20.465
+    - type: ndcg_at_5
+      value: 17.965999999999998
+    - type: precision_at_1
+      value: 23.9
+    - type: precision_at_10
+      value: 11.49
+    - type: precision_at_100
+      value: 2.444
+    - type: precision_at_1000
+      value: 0.392
+    - type: precision_at_3
+      value: 19.3
+    - type: precision_at_5
+      value: 15.959999999999999
+    - type: recall_at_1
+      value: 4.833
+    - type: recall_at_10
+      value: 23.294999999999998
+    - type: recall_at_100
+      value: 49.63
+    - type: recall_at_1000
+      value: 79.49199999999999
+    - type: recall_at_3
+      value: 11.732
+    - type: recall_at_5
+      value: 16.167
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sickr-sts
+      name: MTEB SICK-R
+      config: default
+      split: test
+      revision: 20a6d6f312dd54037fe07a32d58e5e168867909d
+    metrics:
+    - type: cos_sim_pearson
+      value: 85.62938108735759
+    - type: cos_sim_spearman
+      value: 80.30777094408789
+    - type: euclidean_pearson
+      value: 82.94516686659536
+    - type: euclidean_spearman
+      value: 80.34489663248169
+    - type: manhattan_pearson
+      value: 82.85830094736245
+    - type: manhattan_spearman
+      value: 80.24902623215449
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts12-sts
+      name: MTEB STS12
+      config: default
+      split: test
+      revision: a0d554a64d88156834ff5ae9920b964011b16384
+    metrics:
+    - type: cos_sim_pearson
+      value: 85.23777464247604
+    - type: cos_sim_spearman
+      value: 75.75714864112797
+    - type: euclidean_pearson
+      value: 82.33806918604493
+    - type: euclidean_spearman
+      value: 75.45282124387357
+    - type: manhattan_pearson
+      value: 82.32555620660538
+    - type: manhattan_spearman
+      value: 75.49228731684082
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts13-sts
+      name: MTEB STS13
+      config: default
+      split: test
+      revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
+    metrics:
+    - type: cos_sim_pearson
+      value: 84.88151620954451
+    - type: cos_sim_spearman
+      value: 86.08377598473446
+    - type: euclidean_pearson
+      value: 85.36958329369413
+    - type: euclidean_spearman
+      value: 86.10274219670679
+    - type: manhattan_pearson
+      value: 85.25873897594711
+    - type: manhattan_spearman
+      value: 85.98096461661584
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts14-sts
+      name: MTEB STS14
+      config: default
+      split: test
+      revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
+    metrics:
+    - type: cos_sim_pearson
+      value: 84.29360558735978
+    - type: cos_sim_spearman
+      value: 82.28284203795577
+    - type: euclidean_pearson
+      value: 83.81636655536633
+    - type: euclidean_spearman
+      value: 82.24340438530236
+    - type: manhattan_pearson
+      value: 83.83914453428608
+    - type: manhattan_spearman
+      value: 82.28391354080694
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts15-sts
+      name: MTEB STS15
+      config: default
+      split: test
+      revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
+    metrics:
+    - type: cos_sim_pearson
+      value: 87.47344180426744
+    - type: cos_sim_spearman
+      value: 88.90045649789438
+    - type: euclidean_pearson
+      value: 88.43020815961273
+    - type: euclidean_spearman
+      value: 89.0087449011776
+    - type: manhattan_pearson
+      value: 88.37601826505525
+    - type: manhattan_spearman
+      value: 88.96756360690617
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts16-sts
+      name: MTEB STS16
+      config: default
+      split: test
+      revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
+    metrics:
+    - type: cos_sim_pearson
+      value: 83.35997025304613
+    - type: cos_sim_spearman
+      value: 85.18237675717147
+    - type: euclidean_pearson
+      value: 84.46478196990202
+    - type: euclidean_spearman
+      value: 85.27748677712205
+    - type: manhattan_pearson
+      value: 84.29342543953123
+    - type: manhattan_spearman
+      value: 85.10579612516567
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts17-crosslingual-sts
+      name: MTEB STS17 (en-en)
+      config: en-en
+      split: test
+      revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
+    metrics:
+    - type: cos_sim_pearson
+      value: 88.56668329596836
+    - type: cos_sim_spearman
+      value: 88.72837234129177
+    - type: euclidean_pearson
+      value: 89.39395650897828
+    - type: euclidean_spearman
+      value: 88.82001247906778
+    - type: manhattan_pearson
+      value: 89.41735354368878
+    - type: manhattan_spearman
+      value: 88.95159141850039
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts22-crosslingual-sts
+      name: MTEB STS22 (en)
+      config: en
+      split: test
+      revision: eea2b4fe26a775864c896887d910b76a8098ad3f
+    metrics:
+    - type: cos_sim_pearson
+      value: 67.466167902991
+    - type: cos_sim_spearman
+      value: 68.54466147197274
+    - type: euclidean_pearson
+      value: 69.35551179564695
+    - type: euclidean_spearman
+      value: 68.75455717749132
+    - type: manhattan_pearson
+      value: 69.42432368208264
+    - type: manhattan_spearman
+      value: 68.83203709670562
+  - task:
+      type: STS
+    dataset:
+      type: mteb/stsbenchmark-sts
+      name: MTEB STSBenchmark
+      config: default
+      split: test
+      revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
+    metrics:
+    - type: cos_sim_pearson
+      value: 85.33241300373689
+    - type: cos_sim_spearman
+      value: 86.97909372129874
+    - type: euclidean_pearson
+      value: 86.99526113559924
+    - type: euclidean_spearman
+      value: 87.02644372623219
+    - type: manhattan_pearson
+      value: 86.78744182759846
+    - type: manhattan_spearman
+      value: 86.8886180198196
+  - task:
+      type: Reranking
+    dataset:
+      type: mteb/scidocs-reranking
+      name: MTEB SciDocsRR
+      config: default
+      split: test
+      revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
+    metrics:
+    - type: map
+      value: 86.18374413668717
+    - type: mrr
+      value: 95.93213068703264
+  - task:
+      type: Retrieval
+    dataset:
+      type: mteb/scifact
+      name: MTEB SciFact
+      config: default
+      split: test
+      revision: 0228b52cf27578f30900b9e5271d331663a030d7
+    metrics:
+    - type: map_at_1
+      value: 58.31699999999999
+    - type: map_at_10
+      value: 67.691
+    - type: map_at_100
+      value: 68.201
+    - type: map_at_1000
+      value: 68.232
+    - type: map_at_3
+      value: 64.47800000000001
+    - type: map_at_5
+      value: 66.51
+    - type: mrr_at_1
+      value: 61.0
+    - type: mrr_at_10
+      value: 68.621
+    - type: mrr_at_100
+      value: 68.973
+    - type: mrr_at_1000
+      value: 69.002
+    - type: mrr_at_3
+      value: 66.111
+    - type: mrr_at_5
+      value: 67.578
+    - type: ndcg_at_1
+      value: 61.0
+    - type: ndcg_at_10
+      value: 72.219
+    - type: ndcg_at_100
+      value: 74.397
+    - type: ndcg_at_1000
+      value: 75.021
+    - type: ndcg_at_3
+      value: 66.747
+    - type: ndcg_at_5
+      value: 69.609
+    - type: precision_at_1
+      value: 61.0
+    - type: precision_at_10
+      value: 9.6
+    - type: precision_at_100
+      value: 1.08
+    - type: precision_at_1000
+      value: 0.11299999999999999
+    - type: precision_at_3
+      value: 25.667
+    - type: precision_at_5
+      value: 17.267
+    - type: recall_at_1
+      value: 58.31699999999999
+    - type: recall_at_10
+      value: 85.233
+    - type: recall_at_100
+      value: 95.167
+    - type: recall_at_1000
+      value: 99.667
+    - type: recall_at_3
+      value: 70.589
+    - type: recall_at_5
+      value: 77.628
+  - task:
+      type: PairClassification
+    dataset:
+      type: mteb/sprintduplicatequestions-pairclassification
+      name: MTEB SprintDuplicateQuestions
+      config: default
+      split: test
+      revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
+    metrics:
+    - type: cos_sim_accuracy
+      value: 99.83267326732673
+    - type: cos_sim_ap
+      value: 96.13707107038228
+    - type: cos_sim_f1
+      value: 91.48830263812842
+    - type: cos_sim_precision
+      value: 91.0802775024777
+    - type: cos_sim_recall
+      value: 91.9
+    - type: dot_accuracy
+      value: 99.83069306930693
+    - type: dot_ap
+      value: 96.21199069147254
+    - type: dot_f1
+      value: 91.36295556665004
+    - type: dot_precision
+      value: 91.22632103688933
+    - type: dot_recall
+      value: 91.5
+    - type: euclidean_accuracy
+      value: 99.83267326732673
+    - type: euclidean_ap
+      value: 96.08957801367436
+    - type: euclidean_f1
+      value: 91.33004926108374
+    - type: euclidean_precision
+      value: 90.0
+    - type: euclidean_recall
+      value: 92.7
+    - type: manhattan_accuracy
+      value: 99.83564356435643
+    - type: manhattan_ap
+      value: 96.10534946461945
+    - type: manhattan_f1
+      value: 91.74950298210736
+    - type: manhattan_precision
+      value: 91.20553359683794
+    - type: manhattan_recall
+      value: 92.30000000000001
+    - type: max_accuracy
+      value: 99.83564356435643
+    - type: max_ap
+      value: 96.21199069147254
+    - type: max_f1
+      value: 91.74950298210736
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/stackexchange-clustering
+      name: MTEB StackExchangeClustering
+      config: default
+      split: test
+      revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
+    metrics:
+    - type: v_measure
+      value: 62.045718843534736
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/stackexchange-clustering-p2p
+      name: MTEB StackExchangeClusteringP2P
+      config: default
+      split: test
+      revision: 815ca46b2622cec33ccafc3735d572c266efdb44
+    metrics:
+    - type: v_measure
+      value: 36.6501777041092
+  - task:
+      type: Reranking
+    dataset:
+      type: mteb/stackoverflowdupquestions-reranking
+      name: MTEB StackOverflowDupQuestions
+      config: default
+      split: test
+      revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
+    metrics:
+    - type: map
+      value: 52.963913408053955
+    - type: mrr
+      value: 53.87972423818012
+  - task:
+      type: Summarization
+    dataset:
+      type: mteb/summeval
+      name: MTEB SummEval
+      config: default
+      split: test
+      revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
+    metrics:
+    - type: cos_sim_pearson
+      value: 30.44195730764998
+    - type: cos_sim_spearman
+      value: 30.59626288679397
+    - type: dot_pearson
+      value: 30.22974492404086
+    - type: dot_spearman
+      value: 29.345245972906497
+  - task:
+      type: Retrieval
+    dataset:
+      type: mteb/trec-covid
+      name: MTEB TRECCOVID
+      config: default
+      split: test
+      revision: bb9466bac8153a0349341eb1b22e06409e78ef4e
+    metrics:
+    - type: map_at_1
+      value: 0.24
+    - type: map_at_10
+      value: 2.01
+    - type: map_at_100
+      value: 11.928999999999998
+    - type: map_at_1000
+      value: 29.034
+    - type: map_at_3
+      value: 0.679
+    - type: map_at_5
+      value: 1.064
+    - type: mrr_at_1
+      value: 92.0
+    - type: mrr_at_10
+      value: 96.0
+    - type: mrr_at_100
+      value: 96.0
+    - type: mrr_at_1000
+      value: 96.0
+    - type: mrr_at_3
+      value: 96.0
+    - type: mrr_at_5
+      value: 96.0
+    - type: ndcg_at_1
+      value: 87.0
+    - type: ndcg_at_10
+      value: 80.118
+    - type: ndcg_at_100
+      value: 60.753
+    - type: ndcg_at_1000
+      value: 54.632999999999996
+    - type: ndcg_at_3
+      value: 83.073
+    - type: ndcg_at_5
+      value: 80.733
+    - type: precision_at_1
+      value: 92.0
+    - type: precision_at_10
+      value: 84.8
+    - type: precision_at_100
+      value: 62.019999999999996
+    - type: precision_at_1000
+      value: 24.028
+    - type: precision_at_3
+      value: 87.333
+    - type: precision_at_5
+      value: 85.2
+    - type: recall_at_1
+      value: 0.24
+    - type: recall_at_10
+      value: 2.205
+    - type: recall_at_100
+      value: 15.068000000000001
+    - type: recall_at_1000
+      value: 51.796
+    - type: recall_at_3
+      value: 0.698
+    - type: recall_at_5
+      value: 1.1199999999999999
+  - task:
+      type: Retrieval
+    dataset:
+      type: mteb/touche2020
+      name: MTEB Touche2020
+      config: default
+      split: test
+      revision: a34f9a33db75fa0cbb21bb5cfc3dae8dc8bec93f
+    metrics:
+    - type: map_at_1
+      value: 3.066
+    - type: map_at_10
+      value: 9.219
+    - type: map_at_100
+      value: 15.387
+    - type: map_at_1000
+      value: 16.957
+    - type: map_at_3
+      value: 5.146
+    - type: map_at_5
+      value: 6.6739999999999995
+    - type: mrr_at_1
+      value: 40.816
+    - type: mrr_at_10
+      value: 50.844
+    - type: mrr_at_100
+      value: 51.664
+    - type: mrr_at_1000
+      value: 51.664
+    - type: mrr_at_3
+      value: 46.259
+    - type: mrr_at_5
+      value: 49.116
+    - type: ndcg_at_1
+      value: 37.755
+    - type: ndcg_at_10
+      value: 23.477
+    - type: ndcg_at_100
+      value: 36.268
+    - type: ndcg_at_1000
+      value: 47.946
+    - type: ndcg_at_3
+      value: 25.832
+    - type: ndcg_at_5
+      value: 24.235
+    - type: precision_at_1
+      value: 40.816
+    - type: precision_at_10
+      value: 20.204
+    - type: precision_at_100
+      value: 7.611999999999999
+    - type: precision_at_1000
+      value: 1.543
+    - type: precision_at_3
+      value: 25.169999999999998
+    - type: precision_at_5
+      value: 23.265
+    - type: recall_at_1
+      value: 3.066
+    - type: recall_at_10
+      value: 14.985999999999999
+    - type: recall_at_100
+      value: 47.902
+    - type: recall_at_1000
+      value: 83.56400000000001
+    - type: recall_at_3
+      value: 5.755
+    - type: recall_at_5
+      value: 8.741999999999999
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/toxic_conversations_50k
+      name: MTEB ToxicConversationsClassification
+      config: default
+      split: test
+      revision: edfaf9da55d3dd50d43143d90c1ac476895ae6de
+    metrics:
+    - type: accuracy
+      value: 69.437
+    - type: ap
+      value: 12.844066827082706
+    - type: f1
+      value: 52.74974809872495
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/tweet_sentiment_extraction
+      name: MTEB TweetSentimentExtractionClassification
+      config: default
+      split: test
+      revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
+    metrics:
+    - type: accuracy
+      value: 61.26768534238823
+    - type: f1
+      value: 61.65100187399282
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/twentynewsgroups-clustering
+      name: MTEB TwentyNewsgroupsClustering
+      config: default
+      split: test
+      revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
+    metrics:
+    - type: v_measure
+      value: 49.860968711078804
+  - task:
+      type: PairClassification
+    dataset:
+      type: mteb/twittersemeval2015-pairclassification
+      name: MTEB TwitterSemEval2015
+      config: default
+      split: test
+      revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
+    metrics:
+    - type: cos_sim_accuracy
+      value: 85.7423854085951
+    - type: cos_sim_ap
+      value: 73.47560303339571
+    - type: cos_sim_f1
+      value: 67.372778183589
+    - type: cos_sim_precision
+      value: 62.54520795660036
+    - type: cos_sim_recall
+      value: 73.00791556728232
+    - type: dot_accuracy
+      value: 85.36091077069798
+    - type: dot_ap
+      value: 72.42521572307255
+    - type: dot_f1
+      value: 66.90576304724215
+    - type: dot_precision
+      value: 62.96554934823091
+    - type: dot_recall
+      value: 71.37203166226914
+    - type: euclidean_accuracy
+      value: 85.76026703224653
+    - type: euclidean_ap
+      value: 73.44852563860128
+    - type: euclidean_f1
+      value: 67.3
+    - type: euclidean_precision
+      value: 63.94299287410926
+    - type: euclidean_recall
+      value: 71.02902374670185
+    - type: manhattan_accuracy
+      value: 85.7423854085951
+    - type: manhattan_ap
+      value: 73.2635034755551
+    - type: manhattan_f1
+      value: 67.3180263800684
+    - type: manhattan_precision
+      value: 62.66484765802638
+    - type: manhattan_recall
+      value: 72.71767810026385
+    - type: max_accuracy
+      value: 85.76026703224653
+    - type: max_ap
+      value: 73.47560303339571
+    - type: max_f1
+      value: 67.372778183589
+  - task:
+      type: PairClassification
+    dataset:
+      type: mteb/twitterurlcorpus-pairclassification
+      name: MTEB TwitterURLCorpus
+      config: default
+      split: test
+      revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
+    metrics:
+    - type: cos_sim_accuracy
+      value: 88.67543757519307
+    - type: cos_sim_ap
+      value: 85.35516518531304
+    - type: cos_sim_f1
+      value: 77.58197635511934
+    - type: cos_sim_precision
+      value: 75.01078360891445
+    - type: cos_sim_recall
+      value: 80.33569448721897
+    - type: dot_accuracy
+      value: 87.61400240617844
+    - type: dot_ap
+      value: 83.0774968268665
+    - type: dot_f1
+      value: 75.68229012162561
+    - type: dot_precision
+      value: 72.99713876967095
+    - type: dot_recall
+      value: 78.57252848783493
+    - type: euclidean_accuracy
+      value: 88.73753250281368
+    - type: euclidean_ap
+      value: 85.48043564821317
+    - type: euclidean_f1
+      value: 77.75975862719216
+    - type: euclidean_precision
+      value: 76.21054187920456
+    - type: euclidean_recall
+      value: 79.37326763166
+    - type: manhattan_accuracy
+      value: 88.75111576823068
+    - type: manhattan_ap
+      value: 85.44993439423668
+    - type: manhattan_f1
+      value: 77.6861329994845
+    - type: manhattan_precision
+      value: 74.44601270289344
+    - type: manhattan_recall
+      value: 81.22112719433323
+    - type: max_accuracy
+      value: 88.75111576823068
+    - type: max_ap
+      value: 85.48043564821317
+    - type: max_f1
+      value: 77.75975862719216
+---
+<h1 align="center">NoInstruct small Embedding v0</h1>
+
+*NoInstruct Embedding: Asymmetric Pooling is All You Need*
+
+This model has improved retrieval performance compared to the [avsolatorio/GIST-small-Embedding-v0](https://huggingface.co/avsolatorio/GIST-small-Embedding-v0) model.
+
+One of the things that the `GIST` family of models fell short on is the performance on retrieval tasks. We propose a method that produces improved retrieval performance while maintaining independence on crafting arbitrary instructions, a trending paradigm in embedding models for retrieval tasks, when encoding a query.
+
+Technical details of the model will be published shortly.
+
+# Usage
+
+```Python
+from typing import Union
+import torch
+import torch.nn.functional as F
+from transformers import AutoModel, AutoTokenizer
+
+model = AutoModel.from_pretrained("avsolatorio/NoInstruct-small-Embedding-v0")
+tokenizer = AutoTokenizer.from_pretrained("avsolatorio/NoInstruct-small-Embedding-v0")
+
+
+def get_embedding(text: Union[str, list[str]], mode: str = "sentence"):
+    model.eval()
+
+    assert mode in ("query", "sentence"), f"mode={mode} was passed but only `query` and `sentence` are the supported modes."
+
+    if isinstance(text, str):
+        text = [text]
+
+    inp = tokenizer(text, return_tensors="pt", padding=True, truncation=True)
+
+    with torch.no_grad():
+        output = model(**inp)
+
+    # The model is optimized to use the mean pooling for queries,
+    # while the sentence / document embedding uses the [CLS] representation.
+
+    if mode == "query":
+        vectors = output.last_hidden_state * inp["attention_mask"].unsqueeze(2)
+        vectors = vectors.sum(dim=1) / inp["attention_mask"].sum(dim=-1).view(-1, 1)
+    else:
+        vectors = output.last_hidden_state[:, 0, :]
+
+    return vectors
+
+
+texts = [
+    "Illustration of the REaLTabFormer model. The left block shows the non-relational tabular data model using GPT-2 with a causal LM head. In contrast, the right block shows how a relational dataset's child table is modeled using a sequence-to-sequence (Seq2Seq) model. The Seq2Seq model uses the observations in the parent table to condition the generation of the observations in the child table. The trained GPT-2 model on the parent table, with weights frozen, is also used as the encoder in the Seq2Seq model.",
+    "Predicting human mobility holds significant practical value, with applications ranging from enhancing disaster risk planning to simulating epidemic spread. In this paper, we present the GeoFormer, a decoder-only transformer model adapted from the GPT architecture to forecast human mobility.",
+    "As the economies of Southeast Asia continue adopting digital technologies, policy makers increasingly ask how to prepare the workforce for emerging labor demands. However, little is known about the skills that workers need to adapt to these changes"
+]
+
+# Compute embeddings
+embeddings = get_embedding(texts, mode="sentence")
+
+# Compute cosine-similarity for each pair of sentences
+scores = F.cosine_similarity(embeddings.unsqueeze(1), embeddings.unsqueeze(0), dim=-1)
+print(scores.cpu().numpy())
+
+# Test the retrieval performance.
+query = get_embedding("Which sentence talks about concept on jobs?", mode="query")
+
+scores = F.cosine_similarity(query, embeddings, dim=-1)
+print(scores.cpu().numpy())
+```
+
+Support for the Sentence Transformers library will follow soon.

commit-info.json

@@ -0,0 +1 @@
+{"repo_id": "avsolatorio/01-600-11-1-3-2-0-0-cls-qli_0-normed-384-512_ASYM_BAAI_bge-small-en-v1.5-20240424083154-latest", "commit_message": "{\"loss\": 0.4601, \"grad_norm\": 5.519935131072998, \"learning_rate\": 2.6289851550653513e-06, \"epoch\": 2.97, \"step\": 169000}"}

config.json

@@ -0,0 +1,32 @@
+{
+  "_name_or_path": "avsolatorio/NoInstruct-small-Embedding-v0",
+  "architectures": [
+    "BertModel"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "classifier_dropout": null,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 384,
+  "id2label": {
+    "0": "LABEL_0"
+  },
+  "initializer_range": 0.02,
+  "intermediate_size": 1536,
+  "label2id": {
+    "LABEL_0": 0
+  },
+  "layer_norm_eps": 1e-12,
+  "max_position_embeddings": 512,
+  "model_type": "bert",
+  "num_attention_heads": 12,
+  "num_hidden_layers": 12,
+  "output_hidden_states": true,
+  "pad_token_id": 0,
+  "position_embedding_type": "absolute",
+  "torch_dtype": "float32",
+  "transformers_version": "4.39.3",
+  "type_vocab_size": 2,
+  "use_cache": true,
+  "vocab_size": 30522
+}

config_sentence_transformers.json

@@ -0,0 +1,9 @@
+{
+  "__version__": {
+    "sentence_transformers": "2.2.2",
+    "transformers": "4.28.1",
+    "pytorch": "1.13.0+cu117"
+  },
+  "prompts": {},
+  "default_prompt_name": null
+}

model.safetensors

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+version https://git-lfs.github.com/spec/v1
+oid sha256:831a0c15cd73d37ef70185fd446b873d8018ed6b6a108cbedb8efb8f42d6997e
+size 133462128

modules.json

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+[
+  {
+    "idx": 0,
+    "name": "0",
+    "path": "",
+    "type": "sentence_transformers.models.Transformer"
+  },
+  {
+    "idx": 1,
+    "name": "1",
+    "path": "1_Pooling",
+    "type": "sentence_transformers.models.Pooling"
+  },
+  {
+    "idx": 2,
+    "name": "2",
+    "path": "2_Pooling",
+    "type": "sentence_transformers.models.Pooling"
+  },
+  {
+    "idx": 3,
+    "name": "3",
+    "path": "3_Normalize",
+    "type": "sentence_transformers.models.Normalize"
+  }
+]

sentence_bert_config.json

@@ -0,0 +1,4 @@
+{
+  "max_seq_length": 512,
+  "do_lower_case": true
+}

special_tokens_map.json

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+{
+  "cls_token": {
+    "content": "[CLS]",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "mask_token": {
+    "content": "[MASK]",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "pad_token": {
+    "content": "[PAD]",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "sep_token": {
+    "content": "[SEP]",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "unk_token": {
+    "content": "[UNK]",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  }
+}

tokenizer_config.json

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+{
+  "added_tokens_decoder": {
+    "0": {
+      "content": "[PAD]",
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+  "do_lower_case": true,
+  "mask_token": "[MASK]",
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+  "never_split": null,
+  "pad_token": "[PAD]",
+  "sep_token": "[SEP]",
+  "strip_accents": null,
+  "tokenize_chinese_chars": true,
+  "tokenizer_class": "BertTokenizer",
+  "unk_token": "[UNK]"
+}