uploaded readme

README.md

@@ -0,0 +1,2653 @@
+Quantization made by Richard Erkhov.
+
+[Github](https://github.com/RichardErkhov)
+
+[Discord](https://discord.gg/pvy7H8DZMG)
+
+[Request more models](https://github.com/RichardErkhov/quant_request)
+
+
+GritLM-7B - bnb 4bits
+- Model creator: https://huggingface.co/GritLM/
+- Original model: https://huggingface.co/GritLM/GritLM-7B/
+
+
+
+
+Original model description:
+---
+pipeline_tag: text-generation
+inference: true
+license: apache-2.0
+datasets:
+- GritLM/tulu2
+tags:
+- mteb
+model-index:
+- name: GritLM-7B
+  results:
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_counterfactual
+      name: MTEB AmazonCounterfactualClassification (en)
+      config: en
+      split: test
+      revision: e8379541af4e31359cca9fbcf4b00f2671dba205
+    metrics:
+    - type: accuracy
+      value: 81.17910447761194
+    - type: ap
+      value: 46.26260671758199
+    - type: f1
+      value: 75.44565719934167
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_polarity
+      name: MTEB AmazonPolarityClassification
+      config: default
+      split: test
+      revision: e2d317d38cd51312af73b3d32a06d1a08b442046
+    metrics:
+    - type: accuracy
+      value: 96.5161
+    - type: ap
+      value: 94.79131981460425
+    - type: f1
+      value: 96.51506148413065
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_reviews_multi
+      name: MTEB AmazonReviewsClassification (en)
+      config: en
+      split: test
+      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
+    metrics:
+    - type: accuracy
+      value: 57.806000000000004
+    - type: f1
+      value: 56.78350156257903
+  - task:
+      type: Retrieval
+    dataset:
+      type: arguana
+      name: MTEB ArguAna
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 38.478
+    - type: map_at_10
+      value: 54.955
+    - type: map_at_100
+      value: 54.955
+    - type: map_at_1000
+      value: 54.955
+    - type: map_at_3
+      value: 50.888999999999996
+    - type: map_at_5
+      value: 53.349999999999994
+    - type: mrr_at_1
+      value: 39.757999999999996
+    - type: mrr_at_10
+      value: 55.449000000000005
+    - type: mrr_at_100
+      value: 55.449000000000005
+    - type: mrr_at_1000
+      value: 55.449000000000005
+    - type: mrr_at_3
+      value: 51.37500000000001
+    - type: mrr_at_5
+      value: 53.822
+    - type: ndcg_at_1
+      value: 38.478
+    - type: ndcg_at_10
+      value: 63.239999999999995
+    - type: ndcg_at_100
+      value: 63.239999999999995
+    - type: ndcg_at_1000
+      value: 63.239999999999995
+    - type: ndcg_at_3
+      value: 54.935
+    - type: ndcg_at_5
+      value: 59.379000000000005
+    - type: precision_at_1
+      value: 38.478
+    - type: precision_at_10
+      value: 8.933
+    - type: precision_at_100
+      value: 0.893
+    - type: precision_at_1000
+      value: 0.089
+    - type: precision_at_3
+      value: 22.214
+    - type: precision_at_5
+      value: 15.491
+    - type: recall_at_1
+      value: 38.478
+    - type: recall_at_10
+      value: 89.331
+    - type: recall_at_100
+      value: 89.331
+    - type: recall_at_1000
+      value: 89.331
+    - type: recall_at_3
+      value: 66.643
+    - type: recall_at_5
+      value: 77.45400000000001
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/arxiv-clustering-p2p
+      name: MTEB ArxivClusteringP2P
+      config: default
+      split: test
+      revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
+    metrics:
+    - type: v_measure
+      value: 51.67144081472449
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/arxiv-clustering-s2s
+      name: MTEB ArxivClusteringS2S
+      config: default
+      split: test
+      revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
+    metrics:
+    - type: v_measure
+      value: 48.11256154264126
+  - task:
+      type: Reranking
+    dataset:
+      type: mteb/askubuntudupquestions-reranking
+      name: MTEB AskUbuntuDupQuestions
+      config: default
+      split: test
+      revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
+    metrics:
+    - type: map
+      value: 67.33801955487878
+    - type: mrr
+      value: 80.71549487754474
+  - task:
+      type: STS
+    dataset:
+      type: mteb/biosses-sts
+      name: MTEB BIOSSES
+      config: default
+      split: test
+      revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
+    metrics:
+    - type: cos_sim_pearson
+      value: 88.1935203751726
+    - type: cos_sim_spearman
+      value: 86.35497970498659
+    - type: euclidean_pearson
+      value: 85.46910708503744
+    - type: euclidean_spearman
+      value: 85.13928935405485
+    - type: manhattan_pearson
+      value: 85.68373836333303
+    - type: manhattan_spearman
+      value: 85.40013867117746
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/banking77
+      name: MTEB Banking77Classification
+      config: default
+      split: test
+      revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
+    metrics:
+    - type: accuracy
+      value: 88.46753246753248
+    - type: f1
+      value: 88.43006344981134
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/biorxiv-clustering-p2p
+      name: MTEB BiorxivClusteringP2P
+      config: default
+      split: test
+      revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
+    metrics:
+    - type: v_measure
+      value: 40.86793640310432
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/biorxiv-clustering-s2s
+      name: MTEB BiorxivClusteringS2S
+      config: default
+      split: test
+      revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
+    metrics:
+    - type: v_measure
+      value: 39.80291334130727
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackAndroidRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 38.421
+    - type: map_at_10
+      value: 52.349000000000004
+    - type: map_at_100
+      value: 52.349000000000004
+    - type: map_at_1000
+      value: 52.349000000000004
+    - type: map_at_3
+      value: 48.17
+    - type: map_at_5
+      value: 50.432
+    - type: mrr_at_1
+      value: 47.353
+    - type: mrr_at_10
+      value: 58.387
+    - type: mrr_at_100
+      value: 58.387
+    - type: mrr_at_1000
+      value: 58.387
+    - type: mrr_at_3
+      value: 56.199
+    - type: mrr_at_5
+      value: 57.487
+    - type: ndcg_at_1
+      value: 47.353
+    - type: ndcg_at_10
+      value: 59.202
+    - type: ndcg_at_100
+      value: 58.848
+    - type: ndcg_at_1000
+      value: 58.831999999999994
+    - type: ndcg_at_3
+      value: 54.112
+    - type: ndcg_at_5
+      value: 56.312
+    - type: precision_at_1
+      value: 47.353
+    - type: precision_at_10
+      value: 11.459
+    - type: precision_at_100
+      value: 1.146
+    - type: precision_at_1000
+      value: 0.11499999999999999
+    - type: precision_at_3
+      value: 26.133
+    - type: precision_at_5
+      value: 18.627
+    - type: recall_at_1
+      value: 38.421
+    - type: recall_at_10
+      value: 71.89
+    - type: recall_at_100
+      value: 71.89
+    - type: recall_at_1000
+      value: 71.89
+    - type: recall_at_3
+      value: 56.58
+    - type: recall_at_5
+      value: 63.125
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackEnglishRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 38.025999999999996
+    - type: map_at_10
+      value: 50.590999999999994
+    - type: map_at_100
+      value: 51.99700000000001
+    - type: map_at_1000
+      value: 52.11599999999999
+    - type: map_at_3
+      value: 47.435
+    - type: map_at_5
+      value: 49.236000000000004
+    - type: mrr_at_1
+      value: 48.28
+    - type: mrr_at_10
+      value: 56.814
+    - type: mrr_at_100
+      value: 57.446
+    - type: mrr_at_1000
+      value: 57.476000000000006
+    - type: mrr_at_3
+      value: 54.958
+    - type: mrr_at_5
+      value: 56.084999999999994
+    - type: ndcg_at_1
+      value: 48.28
+    - type: ndcg_at_10
+      value: 56.442
+    - type: ndcg_at_100
+      value: 60.651999999999994
+    - type: ndcg_at_1000
+      value: 62.187000000000005
+    - type: ndcg_at_3
+      value: 52.866
+    - type: ndcg_at_5
+      value: 54.515
+    - type: precision_at_1
+      value: 48.28
+    - type: precision_at_10
+      value: 10.586
+    - type: precision_at_100
+      value: 1.6310000000000002
+    - type: precision_at_1000
+      value: 0.20600000000000002
+    - type: precision_at_3
+      value: 25.945
+    - type: precision_at_5
+      value: 18.076
+    - type: recall_at_1
+      value: 38.025999999999996
+    - type: recall_at_10
+      value: 66.11399999999999
+    - type: recall_at_100
+      value: 83.339
+    - type: recall_at_1000
+      value: 92.413
+    - type: recall_at_3
+      value: 54.493
+    - type: recall_at_5
+      value: 59.64699999999999
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackGamingRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 47.905
+    - type: map_at_10
+      value: 61.58
+    - type: map_at_100
+      value: 62.605
+    - type: map_at_1000
+      value: 62.637
+    - type: map_at_3
+      value: 58.074000000000005
+    - type: map_at_5
+      value: 60.260000000000005
+    - type: mrr_at_1
+      value: 54.42
+    - type: mrr_at_10
+      value: 64.847
+    - type: mrr_at_100
+      value: 65.403
+    - type: mrr_at_1000
+      value: 65.41900000000001
+    - type: mrr_at_3
+      value: 62.675000000000004
+    - type: mrr_at_5
+      value: 64.101
+    - type: ndcg_at_1
+      value: 54.42
+    - type: ndcg_at_10
+      value: 67.394
+    - type: ndcg_at_100
+      value: 70.846
+    - type: ndcg_at_1000
+      value: 71.403
+    - type: ndcg_at_3
+      value: 62.025
+    - type: ndcg_at_5
+      value: 65.032
+    - type: precision_at_1
+      value: 54.42
+    - type: precision_at_10
+      value: 10.646
+    - type: precision_at_100
+      value: 1.325
+    - type: precision_at_1000
+      value: 0.13999999999999999
+    - type: precision_at_3
+      value: 27.398
+    - type: precision_at_5
+      value: 18.796
+    - type: recall_at_1
+      value: 47.905
+    - type: recall_at_10
+      value: 80.84599999999999
+    - type: recall_at_100
+      value: 95.078
+    - type: recall_at_1000
+      value: 98.878
+    - type: recall_at_3
+      value: 67.05600000000001
+    - type: recall_at_5
+      value: 74.261
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackGisRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 30.745
+    - type: map_at_10
+      value: 41.021
+    - type: map_at_100
+      value: 41.021
+    - type: map_at_1000
+      value: 41.021
+    - type: map_at_3
+      value: 37.714999999999996
+    - type: map_at_5
+      value: 39.766
+    - type: mrr_at_1
+      value: 33.559
+    - type: mrr_at_10
+      value: 43.537
+    - type: mrr_at_100
+      value: 43.537
+    - type: mrr_at_1000
+      value: 43.537
+    - type: mrr_at_3
+      value: 40.546
+    - type: mrr_at_5
+      value: 42.439
+    - type: ndcg_at_1
+      value: 33.559
+    - type: ndcg_at_10
+      value: 46.781
+    - type: ndcg_at_100
+      value: 46.781
+    - type: ndcg_at_1000
+      value: 46.781
+    - type: ndcg_at_3
+      value: 40.516000000000005
+    - type: ndcg_at_5
+      value: 43.957
+    - type: precision_at_1
+      value: 33.559
+    - type: precision_at_10
+      value: 7.198
+    - type: precision_at_100
+      value: 0.72
+    - type: precision_at_1000
+      value: 0.07200000000000001
+    - type: precision_at_3
+      value: 17.1
+    - type: precision_at_5
+      value: 12.316
+    - type: recall_at_1
+      value: 30.745
+    - type: recall_at_10
+      value: 62.038000000000004
+    - type: recall_at_100
+      value: 62.038000000000004
+    - type: recall_at_1000
+      value: 62.038000000000004
+    - type: recall_at_3
+      value: 45.378
+    - type: recall_at_5
+      value: 53.580000000000005
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackMathematicaRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 19.637999999999998
+    - type: map_at_10
+      value: 31.05
+    - type: map_at_100
+      value: 31.05
+    - type: map_at_1000
+      value: 31.05
+    - type: map_at_3
+      value: 27.628000000000004
+    - type: map_at_5
+      value: 29.767
+    - type: mrr_at_1
+      value: 25.0
+    - type: mrr_at_10
+      value: 36.131
+    - type: mrr_at_100
+      value: 36.131
+    - type: mrr_at_1000
+      value: 36.131
+    - type: mrr_at_3
+      value: 33.333
+    - type: mrr_at_5
+      value: 35.143
+    - type: ndcg_at_1
+      value: 25.0
+    - type: ndcg_at_10
+      value: 37.478
+    - type: ndcg_at_100
+      value: 37.469
+    - type: ndcg_at_1000
+      value: 37.469
+    - type: ndcg_at_3
+      value: 31.757999999999996
+    - type: ndcg_at_5
+      value: 34.821999999999996
+    - type: precision_at_1
+      value: 25.0
+    - type: precision_at_10
+      value: 7.188999999999999
+    - type: precision_at_100
+      value: 0.719
+    - type: precision_at_1000
+      value: 0.07200000000000001
+    - type: precision_at_3
+      value: 15.837000000000002
+    - type: precision_at_5
+      value: 11.841
+    - type: recall_at_1
+      value: 19.637999999999998
+    - type: recall_at_10
+      value: 51.836000000000006
+    - type: recall_at_100
+      value: 51.836000000000006
+    - type: recall_at_1000
+      value: 51.836000000000006
+    - type: recall_at_3
+      value: 36.384
+    - type: recall_at_5
+      value: 43.964
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackPhysicsRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 34.884
+    - type: map_at_10
+      value: 47.88
+    - type: map_at_100
+      value: 47.88
+    - type: map_at_1000
+      value: 47.88
+    - type: map_at_3
+      value: 43.85
+    - type: map_at_5
+      value: 46.414
+    - type: mrr_at_1
+      value: 43.022
+    - type: mrr_at_10
+      value: 53.569
+    - type: mrr_at_100
+      value: 53.569
+    - type: mrr_at_1000
+      value: 53.569
+    - type: mrr_at_3
+      value: 51.075
+    - type: mrr_at_5
+      value: 52.725
+    - type: ndcg_at_1
+      value: 43.022
+    - type: ndcg_at_10
+      value: 54.461000000000006
+    - type: ndcg_at_100
+      value: 54.388000000000005
+    - type: ndcg_at_1000
+      value: 54.388000000000005
+    - type: ndcg_at_3
+      value: 48.864999999999995
+    - type: ndcg_at_5
+      value: 52.032000000000004
+    - type: precision_at_1
+      value: 43.022
+    - type: precision_at_10
+      value: 9.885
+    - type: precision_at_100
+      value: 0.988
+    - type: precision_at_1000
+      value: 0.099
+    - type: precision_at_3
+      value: 23.612
+    - type: precision_at_5
+      value: 16.997
+    - type: recall_at_1
+      value: 34.884
+    - type: recall_at_10
+      value: 68.12899999999999
+    - type: recall_at_100
+      value: 68.12899999999999
+    - type: recall_at_1000
+      value: 68.12899999999999
+    - type: recall_at_3
+      value: 52.428
+    - type: recall_at_5
+      value: 60.662000000000006
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackProgrammersRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 31.588
+    - type: map_at_10
+      value: 43.85
+    - type: map_at_100
+      value: 45.317
+    - type: map_at_1000
+      value: 45.408
+    - type: map_at_3
+      value: 39.73
+    - type: map_at_5
+      value: 42.122
+    - type: mrr_at_1
+      value: 38.927
+    - type: mrr_at_10
+      value: 49.582
+    - type: mrr_at_100
+      value: 50.39
+    - type: mrr_at_1000
+      value: 50.426
+    - type: mrr_at_3
+      value: 46.518
+    - type: mrr_at_5
+      value: 48.271
+    - type: ndcg_at_1
+      value: 38.927
+    - type: ndcg_at_10
+      value: 50.605999999999995
+    - type: ndcg_at_100
+      value: 56.22200000000001
+    - type: ndcg_at_1000
+      value: 57.724
+    - type: ndcg_at_3
+      value: 44.232
+    - type: ndcg_at_5
+      value: 47.233999999999995
+    - type: precision_at_1
+      value: 38.927
+    - type: precision_at_10
+      value: 9.429
+    - type: precision_at_100
+      value: 1.435
+    - type: precision_at_1000
+      value: 0.172
+    - type: precision_at_3
+      value: 21.271
+    - type: precision_at_5
+      value: 15.434000000000001
+    - type: recall_at_1
+      value: 31.588
+    - type: recall_at_10
+      value: 64.836
+    - type: recall_at_100
+      value: 88.066
+    - type: recall_at_1000
+      value: 97.748
+    - type: recall_at_3
+      value: 47.128
+    - type: recall_at_5
+      value: 54.954
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 31.956083333333336
+    - type: map_at_10
+      value: 43.33483333333333
+    - type: map_at_100
+      value: 44.64883333333333
+    - type: map_at_1000
+      value: 44.75
+    - type: map_at_3
+      value: 39.87741666666666
+    - type: map_at_5
+      value: 41.86766666666667
+    - type: mrr_at_1
+      value: 38.06341666666667
+    - type: mrr_at_10
+      value: 47.839666666666666
+    - type: mrr_at_100
+      value: 48.644000000000005
+    - type: mrr_at_1000
+      value: 48.68566666666667
+    - type: mrr_at_3
+      value: 45.26358333333334
+    - type: mrr_at_5
+      value: 46.790000000000006
+    - type: ndcg_at_1
+      value: 38.06341666666667
+    - type: ndcg_at_10
+      value: 49.419333333333334
+    - type: ndcg_at_100
+      value: 54.50166666666667
+    - type: ndcg_at_1000
+      value: 56.161166666666674
+    - type: ndcg_at_3
+      value: 43.982416666666666
+    - type: ndcg_at_5
+      value: 46.638083333333334
+    - type: precision_at_1
+      value: 38.06341666666667
+    - type: precision_at_10
+      value: 8.70858333333333
+    - type: precision_at_100
+      value: 1.327
+    - type: precision_at_1000
+      value: 0.165
+    - type: precision_at_3
+      value: 20.37816666666667
+    - type: precision_at_5
+      value: 14.516333333333334
+    - type: recall_at_1
+      value: 31.956083333333336
+    - type: recall_at_10
+      value: 62.69458333333334
+    - type: recall_at_100
+      value: 84.46433333333334
+    - type: recall_at_1000
+      value: 95.58449999999999
+    - type: recall_at_3
+      value: 47.52016666666666
+    - type: recall_at_5
+      value: 54.36066666666666
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackStatsRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 28.912
+    - type: map_at_10
+      value: 38.291
+    - type: map_at_100
+      value: 39.44
+    - type: map_at_1000
+      value: 39.528
+    - type: map_at_3
+      value: 35.638
+    - type: map_at_5
+      value: 37.218
+    - type: mrr_at_1
+      value: 32.822
+    - type: mrr_at_10
+      value: 41.661
+    - type: mrr_at_100
+      value: 42.546
+    - type: mrr_at_1000
+      value: 42.603
+    - type: mrr_at_3
+      value: 39.238
+    - type: mrr_at_5
+      value: 40.726
+    - type: ndcg_at_1
+      value: 32.822
+    - type: ndcg_at_10
+      value: 43.373
+    - type: ndcg_at_100
+      value: 48.638
+    - type: ndcg_at_1000
+      value: 50.654999999999994
+    - type: ndcg_at_3
+      value: 38.643
+    - type: ndcg_at_5
+      value: 41.126000000000005
+    - type: precision_at_1
+      value: 32.822
+    - type: precision_at_10
+      value: 6.8709999999999996
+    - type: precision_at_100
+      value: 1.032
+    - type: precision_at_1000
+      value: 0.128
+    - type: precision_at_3
+      value: 16.82
+    - type: precision_at_5
+      value: 11.718
+    - type: recall_at_1
+      value: 28.912
+    - type: recall_at_10
+      value: 55.376999999999995
+    - type: recall_at_100
+      value: 79.066
+    - type: recall_at_1000
+      value: 93.664
+    - type: recall_at_3
+      value: 42.569
+    - type: recall_at_5
+      value: 48.719
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackTexRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 22.181
+    - type: map_at_10
+      value: 31.462
+    - type: map_at_100
+      value: 32.73
+    - type: map_at_1000
+      value: 32.848
+    - type: map_at_3
+      value: 28.57
+    - type: map_at_5
+      value: 30.182
+    - type: mrr_at_1
+      value: 27.185
+    - type: mrr_at_10
+      value: 35.846000000000004
+    - type: mrr_at_100
+      value: 36.811
+    - type: mrr_at_1000
+      value: 36.873
+    - type: mrr_at_3
+      value: 33.437
+    - type: mrr_at_5
+      value: 34.813
+    - type: ndcg_at_1
+      value: 27.185
+    - type: ndcg_at_10
+      value: 36.858000000000004
+    - type: ndcg_at_100
+      value: 42.501
+    - type: ndcg_at_1000
+      value: 44.945
+    - type: ndcg_at_3
+      value: 32.066
+    - type: ndcg_at_5
+      value: 34.29
+    - type: precision_at_1
+      value: 27.185
+    - type: precision_at_10
+      value: 6.752
+    - type: precision_at_100
+      value: 1.111
+    - type: precision_at_1000
+      value: 0.151
+    - type: precision_at_3
+      value: 15.290000000000001
+    - type: precision_at_5
+      value: 11.004999999999999
+    - type: recall_at_1
+      value: 22.181
+    - type: recall_at_10
+      value: 48.513
+    - type: recall_at_100
+      value: 73.418
+    - type: recall_at_1000
+      value: 90.306
+    - type: recall_at_3
+      value: 35.003
+    - type: recall_at_5
+      value: 40.876000000000005
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackUnixRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 33.934999999999995
+    - type: map_at_10
+      value: 44.727
+    - type: map_at_100
+      value: 44.727
+    - type: map_at_1000
+      value: 44.727
+    - type: map_at_3
+      value: 40.918
+    - type: map_at_5
+      value: 42.961
+    - type: mrr_at_1
+      value: 39.646
+    - type: mrr_at_10
+      value: 48.898
+    - type: mrr_at_100
+      value: 48.898
+    - type: mrr_at_1000
+      value: 48.898
+    - type: mrr_at_3
+      value: 45.896
+    - type: mrr_at_5
+      value: 47.514
+    - type: ndcg_at_1
+      value: 39.646
+    - type: ndcg_at_10
+      value: 50.817
+    - type: ndcg_at_100
+      value: 50.803
+    - type: ndcg_at_1000
+      value: 50.803
+    - type: ndcg_at_3
+      value: 44.507999999999996
+    - type: ndcg_at_5
+      value: 47.259
+    - type: precision_at_1
+      value: 39.646
+    - type: precision_at_10
+      value: 8.759
+    - type: precision_at_100
+      value: 0.876
+    - type: precision_at_1000
+      value: 0.08800000000000001
+    - type: precision_at_3
+      value: 20.274
+    - type: precision_at_5
+      value: 14.366000000000001
+    - type: recall_at_1
+      value: 33.934999999999995
+    - type: recall_at_10
+      value: 65.037
+    - type: recall_at_100
+      value: 65.037
+    - type: recall_at_1000
+      value: 65.037
+    - type: recall_at_3
+      value: 47.439
+    - type: recall_at_5
+      value: 54.567
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackWebmastersRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 32.058
+    - type: map_at_10
+      value: 43.137
+    - type: map_at_100
+      value: 43.137
+    - type: map_at_1000
+      value: 43.137
+    - type: map_at_3
+      value: 39.882
+    - type: map_at_5
+      value: 41.379
+    - type: mrr_at_1
+      value: 38.933
+    - type: mrr_at_10
+      value: 48.344
+    - type: mrr_at_100
+      value: 48.344
+    - type: mrr_at_1000
+      value: 48.344
+    - type: mrr_at_3
+      value: 45.652
+    - type: mrr_at_5
+      value: 46.877
+    - type: ndcg_at_1
+      value: 38.933
+    - type: ndcg_at_10
+      value: 49.964
+    - type: ndcg_at_100
+      value: 49.242000000000004
+    - type: ndcg_at_1000
+      value: 49.222
+    - type: ndcg_at_3
+      value: 44.605
+    - type: ndcg_at_5
+      value: 46.501999999999995
+    - type: precision_at_1
+      value: 38.933
+    - type: precision_at_10
+      value: 9.427000000000001
+    - type: precision_at_100
+      value: 0.943
+    - type: precision_at_1000
+      value: 0.094
+    - type: precision_at_3
+      value: 20.685000000000002
+    - type: precision_at_5
+      value: 14.585
+    - type: recall_at_1
+      value: 32.058
+    - type: recall_at_10
+      value: 63.074
+    - type: recall_at_100
+      value: 63.074
+    - type: recall_at_1000
+      value: 63.074
+    - type: recall_at_3
+      value: 47.509
+    - type: recall_at_5
+      value: 52.455
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackWordpressRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 26.029000000000003
+    - type: map_at_10
+      value: 34.646
+    - type: map_at_100
+      value: 34.646
+    - type: map_at_1000
+      value: 34.646
+    - type: map_at_3
+      value: 31.456
+    - type: map_at_5
+      value: 33.138
+    - type: mrr_at_1
+      value: 28.281
+    - type: mrr_at_10
+      value: 36.905
+    - type: mrr_at_100
+      value: 36.905
+    - type: mrr_at_1000
+      value: 36.905
+    - type: mrr_at_3
+      value: 34.011
+    - type: mrr_at_5
+      value: 35.638
+    - type: ndcg_at_1
+      value: 28.281
+    - type: ndcg_at_10
+      value: 40.159
+    - type: ndcg_at_100
+      value: 40.159
+    - type: ndcg_at_1000
+      value: 40.159
+    - type: ndcg_at_3
+      value: 33.995
+    - type: ndcg_at_5
+      value: 36.836999999999996
+    - type: precision_at_1
+      value: 28.281
+    - type: precision_at_10
+      value: 6.358999999999999
+    - type: precision_at_100
+      value: 0.636
+    - type: precision_at_1000
+      value: 0.064
+    - type: precision_at_3
+      value: 14.233
+    - type: precision_at_5
+      value: 10.314
+    - type: recall_at_1
+      value: 26.029000000000003
+    - type: recall_at_10
+      value: 55.08
+    - type: recall_at_100
+      value: 55.08
+    - type: recall_at_1000
+      value: 55.08
+    - type: recall_at_3
+      value: 38.487
+    - type: recall_at_5
+      value: 45.308
+  - task:
+      type: Retrieval
+    dataset:
+      type: climate-fever
+      name: MTEB ClimateFEVER
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 12.842999999999998
+    - type: map_at_10
+      value: 22.101000000000003
+    - type: map_at_100
+      value: 24.319
+    - type: map_at_1000
+      value: 24.51
+    - type: map_at_3
+      value: 18.372
+    - type: map_at_5
+      value: 20.323
+    - type: mrr_at_1
+      value: 27.948
+    - type: mrr_at_10
+      value: 40.321
+    - type: mrr_at_100
+      value: 41.262
+    - type: mrr_at_1000
+      value: 41.297
+    - type: mrr_at_3
+      value: 36.558
+    - type: mrr_at_5
+      value: 38.824999999999996
+    - type: ndcg_at_1
+      value: 27.948
+    - type: ndcg_at_10
+      value: 30.906
+    - type: ndcg_at_100
+      value: 38.986
+    - type: ndcg_at_1000
+      value: 42.136
+    - type: ndcg_at_3
+      value: 24.911
+    - type: ndcg_at_5
+      value: 27.168999999999997
+    - type: precision_at_1
+      value: 27.948
+    - type: precision_at_10
+      value: 9.798
+    - type: precision_at_100
+      value: 1.8399999999999999
+    - type: precision_at_1000
+      value: 0.243
+    - type: precision_at_3
+      value: 18.328
+    - type: precision_at_5
+      value: 14.502
+    - type: recall_at_1
+      value: 12.842999999999998
+    - type: recall_at_10
+      value: 37.245
+    - type: recall_at_100
+      value: 64.769
+    - type: recall_at_1000
+      value: 82.055
+    - type: recall_at_3
+      value: 23.159
+    - type: recall_at_5
+      value: 29.113
+  - task:
+      type: Retrieval
+    dataset:
+      type: dbpedia-entity
+      name: MTEB DBPedia
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 8.934000000000001
+    - type: map_at_10
+      value: 21.915000000000003
+    - type: map_at_100
+      value: 21.915000000000003
+    - type: map_at_1000
+      value: 21.915000000000003
+    - type: map_at_3
+      value: 14.623
+    - type: map_at_5
+      value: 17.841
+    - type: mrr_at_1
+      value: 71.25
+    - type: mrr_at_10
+      value: 78.994
+    - type: mrr_at_100
+      value: 78.994
+    - type: mrr_at_1000
+      value: 78.994
+    - type: mrr_at_3
+      value: 77.208
+    - type: mrr_at_5
+      value: 78.55799999999999
+    - type: ndcg_at_1
+      value: 60.62499999999999
+    - type: ndcg_at_10
+      value: 46.604
+    - type: ndcg_at_100
+      value: 35.653
+    - type: ndcg_at_1000
+      value: 35.531
+    - type: ndcg_at_3
+      value: 50.605
+    - type: ndcg_at_5
+      value: 48.730000000000004
+    - type: precision_at_1
+      value: 71.25
+    - type: precision_at_10
+      value: 37.75
+    - type: precision_at_100
+      value: 3.775
+    - type: precision_at_1000
+      value: 0.377
+    - type: precision_at_3
+      value: 54.417
+    - type: precision_at_5
+      value: 48.15
+    - type: recall_at_1
+      value: 8.934000000000001
+    - type: recall_at_10
+      value: 28.471000000000004
+    - type: recall_at_100
+      value: 28.471000000000004
+    - type: recall_at_1000
+      value: 28.471000000000004
+    - type: recall_at_3
+      value: 16.019
+    - type: recall_at_5
+      value: 21.410999999999998
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/emotion
+      name: MTEB EmotionClassification
+      config: default
+      split: test
+      revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
+    metrics:
+    - type: accuracy
+      value: 52.81
+    - type: f1
+      value: 47.987573380720114
+  - task:
+      type: Retrieval
+    dataset:
+      type: fever
+      name: MTEB FEVER
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 66.81899999999999
+    - type: map_at_10
+      value: 78.034
+    - type: map_at_100
+      value: 78.034
+    - type: map_at_1000
+      value: 78.034
+    - type: map_at_3
+      value: 76.43100000000001
+    - type: map_at_5
+      value: 77.515
+    - type: mrr_at_1
+      value: 71.542
+    - type: mrr_at_10
+      value: 81.638
+    - type: mrr_at_100
+      value: 81.638
+    - type: mrr_at_1000
+      value: 81.638
+    - type: mrr_at_3
+      value: 80.403
+    - type: mrr_at_5
+      value: 81.256
+    - type: ndcg_at_1
+      value: 71.542
+    - type: ndcg_at_10
+      value: 82.742
+    - type: ndcg_at_100
+      value: 82.741
+    - type: ndcg_at_1000
+      value: 82.741
+    - type: ndcg_at_3
+      value: 80.039
+    - type: ndcg_at_5
+      value: 81.695
+    - type: precision_at_1
+      value: 71.542
+    - type: precision_at_10
+      value: 10.387
+    - type: precision_at_100
+      value: 1.039
+    - type: precision_at_1000
+      value: 0.104
+    - type: precision_at_3
+      value: 31.447999999999997
+    - type: precision_at_5
+      value: 19.91
+    - type: recall_at_1
+      value: 66.81899999999999
+    - type: recall_at_10
+      value: 93.372
+    - type: recall_at_100
+      value: 93.372
+    - type: recall_at_1000
+      value: 93.372
+    - type: recall_at_3
+      value: 86.33
+    - type: recall_at_5
+      value: 90.347
+  - task:
+      type: Retrieval
+    dataset:
+      type: fiqa
+      name: MTEB FiQA2018
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 31.158
+    - type: map_at_10
+      value: 52.017
+    - type: map_at_100
+      value: 54.259
+    - type: map_at_1000
+      value: 54.367
+    - type: map_at_3
+      value: 45.738
+    - type: map_at_5
+      value: 49.283
+    - type: mrr_at_1
+      value: 57.87
+    - type: mrr_at_10
+      value: 66.215
+    - type: mrr_at_100
+      value: 66.735
+    - type: mrr_at_1000
+      value: 66.75
+    - type: mrr_at_3
+      value: 64.043
+    - type: mrr_at_5
+      value: 65.116
+    - type: ndcg_at_1
+      value: 57.87
+    - type: ndcg_at_10
+      value: 59.946999999999996
+    - type: ndcg_at_100
+      value: 66.31099999999999
+    - type: ndcg_at_1000
+      value: 67.75999999999999
+    - type: ndcg_at_3
+      value: 55.483000000000004
+    - type: ndcg_at_5
+      value: 56.891000000000005
+    - type: precision_at_1
+      value: 57.87
+    - type: precision_at_10
+      value: 16.497
+    - type: precision_at_100
+      value: 2.321
+    - type: precision_at_1000
+      value: 0.258
+    - type: precision_at_3
+      value: 37.14
+    - type: precision_at_5
+      value: 27.067999999999998
+    - type: recall_at_1
+      value: 31.158
+    - type: recall_at_10
+      value: 67.381
+    - type: recall_at_100
+      value: 89.464
+    - type: recall_at_1000
+      value: 97.989
+    - type: recall_at_3
+      value: 50.553000000000004
+    - type: recall_at_5
+      value: 57.824
+  - task:
+      type: Retrieval
+    dataset:
+      type: hotpotqa
+      name: MTEB HotpotQA
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 42.073
+    - type: map_at_10
+      value: 72.418
+    - type: map_at_100
+      value: 73.175
+    - type: map_at_1000
+      value: 73.215
+    - type: map_at_3
+      value: 68.791
+    - type: map_at_5
+      value: 71.19
+    - type: mrr_at_1
+      value: 84.146
+    - type: mrr_at_10
+      value: 88.994
+    - type: mrr_at_100
+      value: 89.116
+    - type: mrr_at_1000
+      value: 89.12
+    - type: mrr_at_3
+      value: 88.373
+    - type: mrr_at_5
+      value: 88.82
+    - type: ndcg_at_1
+      value: 84.146
+    - type: ndcg_at_10
+      value: 79.404
+    - type: ndcg_at_100
+      value: 81.83200000000001
+    - type: ndcg_at_1000
+      value: 82.524
+    - type: ndcg_at_3
+      value: 74.595
+    - type: ndcg_at_5
+      value: 77.474
+    - type: precision_at_1
+      value: 84.146
+    - type: precision_at_10
+      value: 16.753999999999998
+    - type: precision_at_100
+      value: 1.8599999999999999
+    - type: precision_at_1000
+      value: 0.19499999999999998
+    - type: precision_at_3
+      value: 48.854
+    - type: precision_at_5
+      value: 31.579
+    - type: recall_at_1
+      value: 42.073
+    - type: recall_at_10
+      value: 83.768
+    - type: recall_at_100
+      value: 93.018
+    - type: recall_at_1000
+      value: 97.481
+    - type: recall_at_3
+      value: 73.282
+    - type: recall_at_5
+      value: 78.947
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/imdb
+      name: MTEB ImdbClassification
+      config: default
+      split: test
+      revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
+    metrics:
+    - type: accuracy
+      value: 94.9968
+    - type: ap
+      value: 92.93892195862824
+    - type: f1
+      value: 94.99327998213761
+  - task:
+      type: Retrieval
+    dataset:
+      type: msmarco
+      name: MTEB MSMARCO
+      config: default
+      split: dev
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 21.698
+    - type: map_at_10
+      value: 34.585
+    - type: map_at_100
+      value: 35.782000000000004
+    - type: map_at_1000
+      value: 35.825
+    - type: map_at_3
+      value: 30.397999999999996
+    - type: map_at_5
+      value: 32.72
+    - type: mrr_at_1
+      value: 22.192
+    - type: mrr_at_10
+      value: 35.085
+    - type: mrr_at_100
+      value: 36.218
+    - type: mrr_at_1000
+      value: 36.256
+    - type: mrr_at_3
+      value: 30.986000000000004
+    - type: mrr_at_5
+      value: 33.268
+    - type: ndcg_at_1
+      value: 22.192
+    - type: ndcg_at_10
+      value: 41.957
+    - type: ndcg_at_100
+      value: 47.658
+    - type: ndcg_at_1000
+      value: 48.697
+    - type: ndcg_at_3
+      value: 33.433
+    - type: ndcg_at_5
+      value: 37.551
+    - type: precision_at_1
+      value: 22.192
+    - type: precision_at_10
+      value: 6.781
+    - type: precision_at_100
+      value: 0.963
+    - type: precision_at_1000
+      value: 0.105
+    - type: precision_at_3
+      value: 14.365
+    - type: precision_at_5
+      value: 10.713000000000001
+    - type: recall_at_1
+      value: 21.698
+    - type: recall_at_10
+      value: 64.79
+    - type: recall_at_100
+      value: 91.071
+    - type: recall_at_1000
+      value: 98.883
+    - type: recall_at_3
+      value: 41.611
+    - type: recall_at_5
+      value: 51.459999999999994
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/mtop_domain
+      name: MTEB MTOPDomainClassification (en)
+      config: en
+      split: test
+      revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
+    metrics:
+    - type: accuracy
+      value: 96.15823073415413
+    - type: f1
+      value: 96.00362034963248
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/mtop_intent
+      name: MTEB MTOPIntentClassification (en)
+      config: en
+      split: test
+      revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
+    metrics:
+    - type: accuracy
+      value: 87.12722298221614
+    - type: f1
+      value: 70.46888967516227
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_massive_intent
+      name: MTEB MassiveIntentClassification (en)
+      config: en
+      split: test
+      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
+    metrics:
+    - type: accuracy
+      value: 80.77673167451245
+    - type: f1
+      value: 77.60202561132175
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_massive_scenario
+      name: MTEB MassiveScenarioClassification (en)
+      config: en
+      split: test
+      revision: 7d571f92784cd94a019292a1f45445077d0ef634
+    metrics:
+    - type: accuracy
+      value: 82.09145931405514
+    - type: f1
+      value: 81.7701921473406
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/medrxiv-clustering-p2p
+      name: MTEB MedrxivClusteringP2P
+      config: default
+      split: test
+      revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
+    metrics:
+    - type: v_measure
+      value: 36.52153488185864
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/medrxiv-clustering-s2s
+      name: MTEB MedrxivClusteringS2S
+      config: default
+      split: test
+      revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
+    metrics:
+    - type: v_measure
+      value: 36.80090398444147
+  - task:
+      type: Reranking
+    dataset:
+      type: mteb/mind_small
+      name: MTEB MindSmallReranking
+      config: default
+      split: test
+      revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
+    metrics:
+    - type: map
+      value: 31.807141746058605
+    - type: mrr
+      value: 32.85025611455029
+  - task:
+      type: Retrieval
+    dataset:
+      type: nfcorpus
+      name: MTEB NFCorpus
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 6.920999999999999
+    - type: map_at_10
+      value: 16.049
+    - type: map_at_100
+      value: 16.049
+    - type: map_at_1000
+      value: 16.049
+    - type: map_at_3
+      value: 11.865
+    - type: map_at_5
+      value: 13.657
+    - type: mrr_at_1
+      value: 53.87
+    - type: mrr_at_10
+      value: 62.291
+    - type: mrr_at_100
+      value: 62.291
+    - type: mrr_at_1000
+      value: 62.291
+    - type: mrr_at_3
+      value: 60.681
+    - type: mrr_at_5
+      value: 61.61
+    - type: ndcg_at_1
+      value: 51.23799999999999
+    - type: ndcg_at_10
+      value: 40.892
+    - type: ndcg_at_100
+      value: 26.951999999999998
+    - type: ndcg_at_1000
+      value: 26.474999999999998
+    - type: ndcg_at_3
+      value: 46.821
+    - type: ndcg_at_5
+      value: 44.333
+    - type: precision_at_1
+      value: 53.251000000000005
+    - type: precision_at_10
+      value: 30.124000000000002
+    - type: precision_at_100
+      value: 3.012
+    - type: precision_at_1000
+      value: 0.301
+    - type: precision_at_3
+      value: 43.55
+    - type: precision_at_5
+      value: 38.266
+    - type: recall_at_1
+      value: 6.920999999999999
+    - type: recall_at_10
+      value: 20.852
+    - type: recall_at_100
+      value: 20.852
+    - type: recall_at_1000
+      value: 20.852
+    - type: recall_at_3
+      value: 13.628000000000002
+    - type: recall_at_5
+      value: 16.273
+  - task:
+      type: Retrieval
+    dataset:
+      type: nq
+      name: MTEB NQ
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 46.827999999999996
+    - type: map_at_10
+      value: 63.434000000000005
+    - type: map_at_100
+      value: 63.434000000000005
+    - type: map_at_1000
+      value: 63.434000000000005
+    - type: map_at_3
+      value: 59.794000000000004
+    - type: map_at_5
+      value: 62.08
+    - type: mrr_at_1
+      value: 52.288999999999994
+    - type: mrr_at_10
+      value: 65.95
+    - type: mrr_at_100
+      value: 65.95
+    - type: mrr_at_1000
+      value: 65.95
+    - type: mrr_at_3
+      value: 63.413
+    - type: mrr_at_5
+      value: 65.08
+    - type: ndcg_at_1
+      value: 52.288999999999994
+    - type: ndcg_at_10
+      value: 70.301
+    - type: ndcg_at_100
+      value: 70.301
+    - type: ndcg_at_1000
+      value: 70.301
+    - type: ndcg_at_3
+      value: 63.979
+    - type: ndcg_at_5
+      value: 67.582
+    - type: precision_at_1
+      value: 52.288999999999994
+    - type: precision_at_10
+      value: 10.576
+    - type: precision_at_100
+      value: 1.058
+    - type: precision_at_1000
+      value: 0.106
+    - type: precision_at_3
+      value: 28.177000000000003
+    - type: precision_at_5
+      value: 19.073
+    - type: recall_at_1
+      value: 46.827999999999996
+    - type: recall_at_10
+      value: 88.236
+    - type: recall_at_100
+      value: 88.236
+    - type: recall_at_1000
+      value: 88.236
+    - type: recall_at_3
+      value: 72.371
+    - type: recall_at_5
+      value: 80.56
+  - task:
+      type: Retrieval
+    dataset:
+      type: quora
+      name: MTEB QuoraRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 71.652
+    - type: map_at_10
+      value: 85.953
+    - type: map_at_100
+      value: 85.953
+    - type: map_at_1000
+      value: 85.953
+    - type: map_at_3
+      value: 83.05399999999999
+    - type: map_at_5
+      value: 84.89
+    - type: mrr_at_1
+      value: 82.42
+    - type: mrr_at_10
+      value: 88.473
+    - type: mrr_at_100
+      value: 88.473
+    - type: mrr_at_1000
+      value: 88.473
+    - type: mrr_at_3
+      value: 87.592
+    - type: mrr_at_5
+      value: 88.211
+    - type: ndcg_at_1
+      value: 82.44
+    - type: ndcg_at_10
+      value: 89.467
+    - type: ndcg_at_100
+      value: 89.33
+    - type: ndcg_at_1000
+      value: 89.33
+    - type: ndcg_at_3
+      value: 86.822
+    - type: ndcg_at_5
+      value: 88.307
+    - type: precision_at_1
+      value: 82.44
+    - type: precision_at_10
+      value: 13.616
+    - type: precision_at_100
+      value: 1.362
+    - type: precision_at_1000
+      value: 0.136
+    - type: precision_at_3
+      value: 38.117000000000004
+    - type: precision_at_5
+      value: 25.05
+    - type: recall_at_1
+      value: 71.652
+    - type: recall_at_10
+      value: 96.224
+    - type: recall_at_100
+      value: 96.224
+    - type: recall_at_1000
+      value: 96.224
+    - type: recall_at_3
+      value: 88.571
+    - type: recall_at_5
+      value: 92.812
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/reddit-clustering
+      name: MTEB RedditClustering
+      config: default
+      split: test
+      revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
+    metrics:
+    - type: v_measure
+      value: 61.295010338050474
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/reddit-clustering-p2p
+      name: MTEB RedditClusteringP2P
+      config: default
+      split: test
+      revision: 282350215ef01743dc01b456c7f5241fa8937f16
+    metrics:
+    - type: v_measure
+      value: 67.26380819328142
+  - task:
+      type: Retrieval
+    dataset:
+      type: scidocs
+      name: MTEB SCIDOCS
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 5.683
+    - type: map_at_10
+      value: 14.924999999999999
+    - type: map_at_100
+      value: 17.532
+    - type: map_at_1000
+      value: 17.875
+    - type: map_at_3
+      value: 10.392
+    - type: map_at_5
+      value: 12.592
+    - type: mrr_at_1
+      value: 28.000000000000004
+    - type: mrr_at_10
+      value: 39.951
+    - type: mrr_at_100
+      value: 41.025
+    - type: mrr_at_1000
+      value: 41.056
+    - type: mrr_at_3
+      value: 36.317
+    - type: mrr_at_5
+      value: 38.412
+    - type: ndcg_at_1
+      value: 28.000000000000004
+    - type: ndcg_at_10
+      value: 24.410999999999998
+    - type: ndcg_at_100
+      value: 33.79
+    - type: ndcg_at_1000
+      value: 39.035
+    - type: ndcg_at_3
+      value: 22.845
+    - type: ndcg_at_5
+      value: 20.080000000000002
+    - type: precision_at_1
+      value: 28.000000000000004
+    - type: precision_at_10
+      value: 12.790000000000001
+    - type: precision_at_100
+      value: 2.633
+    - type: precision_at_1000
+      value: 0.388
+    - type: precision_at_3
+      value: 21.367
+    - type: precision_at_5
+      value: 17.7
+    - type: recall_at_1
+      value: 5.683
+    - type: recall_at_10
+      value: 25.91
+    - type: recall_at_100
+      value: 53.443
+    - type: recall_at_1000
+      value: 78.73
+    - type: recall_at_3
+      value: 13.003
+    - type: recall_at_5
+      value: 17.932000000000002
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sickr-sts
+      name: MTEB SICK-R
+      config: default
+      split: test
+      revision: a6ea5a8cab320b040a23452cc28066d9beae2cee
+    metrics:
+    - type: cos_sim_pearson
+      value: 84.677978681023
+    - type: cos_sim_spearman
+      value: 83.13093441058189
+    - type: euclidean_pearson
+      value: 83.35535759341572
+    - type: euclidean_spearman
+      value: 83.42583744219611
+    - type: manhattan_pearson
+      value: 83.2243124045889
+    - type: manhattan_spearman
+      value: 83.39801618652632
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts12-sts
+      name: MTEB STS12
+      config: default
+      split: test
+      revision: a0d554a64d88156834ff5ae9920b964011b16384
+    metrics:
+    - type: cos_sim_pearson
+      value: 81.68960206569666
+    - type: cos_sim_spearman
+      value: 77.3368966488535
+    - type: euclidean_pearson
+      value: 77.62828980560303
+    - type: euclidean_spearman
+      value: 76.77951481444651
+    - type: manhattan_pearson
+      value: 77.88637240839041
+    - type: manhattan_spearman
+      value: 77.22157841466188
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts13-sts
+      name: MTEB STS13
+      config: default
+      split: test
+      revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
+    metrics:
+    - type: cos_sim_pearson
+      value: 84.18745821650724
+    - type: cos_sim_spearman
+      value: 85.04423285574542
+    - type: euclidean_pearson
+      value: 85.46604816931023
+    - type: euclidean_spearman
+      value: 85.5230593932974
+    - type: manhattan_pearson
+      value: 85.57912805986261
+    - type: manhattan_spearman
+      value: 85.65955905111873
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts14-sts
+      name: MTEB STS14
+      config: default
+      split: test
+      revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
+    metrics:
+    - type: cos_sim_pearson
+      value: 83.6715333300355
+    - type: cos_sim_spearman
+      value: 82.9058522514908
+    - type: euclidean_pearson
+      value: 83.9640357424214
+    - type: euclidean_spearman
+      value: 83.60415457472637
+    - type: manhattan_pearson
+      value: 84.05621005853469
+    - type: manhattan_spearman
+      value: 83.87077724707746
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts15-sts
+      name: MTEB STS15
+      config: default
+      split: test
+      revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
+    metrics:
+    - type: cos_sim_pearson
+      value: 87.82422928098886
+    - type: cos_sim_spearman
+      value: 88.12660311894628
+    - type: euclidean_pearson
+      value: 87.50974805056555
+    - type: euclidean_spearman
+      value: 87.91957275596677
+    - type: manhattan_pearson
+      value: 87.74119404878883
+    - type: manhattan_spearman
+      value: 88.2808922165719
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts16-sts
+      name: MTEB STS16
+      config: default
+      split: test
+      revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
+    metrics:
+    - type: cos_sim_pearson
+      value: 84.80605838552093
+    - type: cos_sim_spearman
+      value: 86.24123388765678
+    - type: euclidean_pearson
+      value: 85.32648347339814
+    - type: euclidean_spearman
+      value: 85.60046671950158
+    - type: manhattan_pearson
+      value: 85.53800168487811
+    - type: manhattan_spearman
+      value: 85.89542420480763
+  - 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: 89.87540978988132
+    - type: cos_sim_spearman
+      value: 90.12715295099461
+    - type: euclidean_pearson
+      value: 91.61085993525275
+    - type: euclidean_spearman
+      value: 91.31835942311758
+    - type: manhattan_pearson
+      value: 91.57500202032934
+    - type: manhattan_spearman
+      value: 91.1790925526635
+  - 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: 69.87136205329556
+    - type: cos_sim_spearman
+      value: 68.6253154635078
+    - type: euclidean_pearson
+      value: 68.91536015034222
+    - type: euclidean_spearman
+      value: 67.63744649352542
+    - type: manhattan_pearson
+      value: 69.2000713045275
+    - type: manhattan_spearman
+      value: 68.16002901587316
+  - task:
+      type: STS
+    dataset:
+      type: mteb/stsbenchmark-sts
+      name: MTEB STSBenchmark
+      config: default
+      split: test
+      revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
+    metrics:
+    - type: cos_sim_pearson
+      value: 85.21849551039082
+    - type: cos_sim_spearman
+      value: 85.6392959372461
+    - type: euclidean_pearson
+      value: 85.92050852609488
+    - type: euclidean_spearman
+      value: 85.97205649009734
+    - type: manhattan_pearson
+      value: 86.1031154802254
+    - type: manhattan_spearman
+      value: 86.26791155517466
+  - task:
+      type: Reranking
+    dataset:
+      type: mteb/scidocs-reranking
+      name: MTEB SciDocsRR
+      config: default
+      split: test
+      revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
+    metrics:
+    - type: map
+      value: 86.83953958636627
+    - type: mrr
+      value: 96.71167612344082
+  - task:
+      type: Retrieval
+    dataset:
+      type: scifact
+      name: MTEB SciFact
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 64.994
+    - type: map_at_10
+      value: 74.763
+    - type: map_at_100
+      value: 75.127
+    - type: map_at_1000
+      value: 75.143
+    - type: map_at_3
+      value: 71.824
+    - type: map_at_5
+      value: 73.71
+    - type: mrr_at_1
+      value: 68.333
+    - type: mrr_at_10
+      value: 75.749
+    - type: mrr_at_100
+      value: 75.922
+    - type: mrr_at_1000
+      value: 75.938
+    - type: mrr_at_3
+      value: 73.556
+    - type: mrr_at_5
+      value: 74.739
+    - type: ndcg_at_1
+      value: 68.333
+    - type: ndcg_at_10
+      value: 79.174
+    - type: ndcg_at_100
+      value: 80.41
+    - type: ndcg_at_1000
+      value: 80.804
+    - type: ndcg_at_3
+      value: 74.361
+    - type: ndcg_at_5
+      value: 76.861
+    - type: precision_at_1
+      value: 68.333
+    - type: precision_at_10
+      value: 10.333
+    - type: precision_at_100
+      value: 1.0999999999999999
+    - type: precision_at_1000
+      value: 0.11299999999999999
+    - type: precision_at_3
+      value: 28.778
+    - type: precision_at_5
+      value: 19.067
+    - type: recall_at_1
+      value: 64.994
+    - type: recall_at_10
+      value: 91.822
+    - type: recall_at_100
+      value: 97.0
+    - type: recall_at_1000
+      value: 100.0
+    - type: recall_at_3
+      value: 78.878
+    - type: recall_at_5
+      value: 85.172
+  - task:
+      type: PairClassification
+    dataset:
+      type: mteb/sprintduplicatequestions-pairclassification
+      name: MTEB SprintDuplicateQuestions
+      config: default
+      split: test
+      revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
+    metrics:
+    - type: cos_sim_accuracy
+      value: 99.72079207920792
+    - type: cos_sim_ap
+      value: 93.00265215525152
+    - type: cos_sim_f1
+      value: 85.06596306068602
+    - type: cos_sim_precision
+      value: 90.05586592178771
+    - type: cos_sim_recall
+      value: 80.60000000000001
+    - type: dot_accuracy
+      value: 99.66039603960397
+    - type: dot_ap
+      value: 91.22371407479089
+    - type: dot_f1
+      value: 82.34693877551021
+    - type: dot_precision
+      value: 84.0625
+    - type: dot_recall
+      value: 80.7
+    - type: euclidean_accuracy
+      value: 99.71881188118812
+    - type: euclidean_ap
+      value: 92.88449963304728
+    - type: euclidean_f1
+      value: 85.19480519480518
+    - type: euclidean_precision
+      value: 88.64864864864866
+    - type: euclidean_recall
+      value: 82.0
+    - type: manhattan_accuracy
+      value: 99.73267326732673
+    - type: manhattan_ap
+      value: 93.23055393056883
+    - type: manhattan_f1
+      value: 85.88957055214725
+    - type: manhattan_precision
+      value: 87.86610878661088
+    - type: manhattan_recall
+      value: 84.0
+    - type: max_accuracy
+      value: 99.73267326732673
+    - type: max_ap
+      value: 93.23055393056883
+    - type: max_f1
+      value: 85.88957055214725
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/stackexchange-clustering
+      name: MTEB StackExchangeClustering
+      config: default
+      split: test
+      revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
+    metrics:
+    - type: v_measure
+      value: 77.3305735900358
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/stackexchange-clustering-p2p
+      name: MTEB StackExchangeClusteringP2P
+      config: default
+      split: test
+      revision: 815ca46b2622cec33ccafc3735d572c266efdb44
+    metrics:
+    - type: v_measure
+      value: 41.32967136540674
+  - task:
+      type: Reranking
+    dataset:
+      type: mteb/stackoverflowdupquestions-reranking
+      name: MTEB StackOverflowDupQuestions
+      config: default
+      split: test
+      revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
+    metrics:
+    - type: map
+      value: 55.95514866379359
+    - type: mrr
+      value: 56.95423245055598
+  - task:
+      type: Summarization
+    dataset:
+      type: mteb/summeval
+      name: MTEB SummEval
+      config: default
+      split: test
+      revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
+    metrics:
+    - type: cos_sim_pearson
+      value: 30.783007208997144
+    - type: cos_sim_spearman
+      value: 30.373444721540533
+    - type: dot_pearson
+      value: 29.210604111143905
+    - type: dot_spearman
+      value: 29.98809758085659
+  - task:
+      type: Retrieval
+    dataset:
+      type: trec-covid
+      name: MTEB TRECCOVID
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 0.234
+    - type: map_at_10
+      value: 1.894
+    - type: map_at_100
+      value: 1.894
+    - type: map_at_1000
+      value: 1.894
+    - type: map_at_3
+      value: 0.636
+    - type: map_at_5
+      value: 1.0
+    - type: mrr_at_1
+      value: 88.0
+    - type: mrr_at_10
+      value: 93.667
+    - type: mrr_at_100
+      value: 93.667
+    - type: mrr_at_1000
+      value: 93.667
+    - type: mrr_at_3
+      value: 93.667
+    - type: mrr_at_5
+      value: 93.667
+    - type: ndcg_at_1
+      value: 85.0
+    - type: ndcg_at_10
+      value: 74.798
+    - type: ndcg_at_100
+      value: 16.462
+    - type: ndcg_at_1000
+      value: 7.0889999999999995
+    - type: ndcg_at_3
+      value: 80.754
+    - type: ndcg_at_5
+      value: 77.319
+    - type: precision_at_1
+      value: 88.0
+    - type: precision_at_10
+      value: 78.0
+    - type: precision_at_100
+      value: 7.8
+    - type: precision_at_1000
+      value: 0.7799999999999999
+    - type: precision_at_3
+      value: 83.333
+    - type: precision_at_5
+      value: 80.80000000000001
+    - type: recall_at_1
+      value: 0.234
+    - type: recall_at_10
+      value: 2.093
+    - type: recall_at_100
+      value: 2.093
+    - type: recall_at_1000
+      value: 2.093
+    - type: recall_at_3
+      value: 0.662
+    - type: recall_at_5
+      value: 1.0739999999999998
+  - task:
+      type: Retrieval
+    dataset:
+      type: webis-touche2020
+      name: MTEB Touche2020
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 2.703
+    - type: map_at_10
+      value: 10.866000000000001
+    - type: map_at_100
+      value: 10.866000000000001
+    - type: map_at_1000
+      value: 10.866000000000001
+    - type: map_at_3
+      value: 5.909
+    - type: map_at_5
+      value: 7.35
+    - type: mrr_at_1
+      value: 36.735
+    - type: mrr_at_10
+      value: 53.583000000000006
+    - type: mrr_at_100
+      value: 53.583000000000006
+    - type: mrr_at_1000
+      value: 53.583000000000006
+    - type: mrr_at_3
+      value: 49.32
+    - type: mrr_at_5
+      value: 51.769
+    - type: ndcg_at_1
+      value: 34.694
+    - type: ndcg_at_10
+      value: 27.926000000000002
+    - type: ndcg_at_100
+      value: 22.701
+    - type: ndcg_at_1000
+      value: 22.701
+    - type: ndcg_at_3
+      value: 32.073
+    - type: ndcg_at_5
+      value: 28.327999999999996
+    - type: precision_at_1
+      value: 36.735
+    - type: precision_at_10
+      value: 24.694
+    - type: precision_at_100
+      value: 2.469
+    - type: precision_at_1000
+      value: 0.247
+    - type: precision_at_3
+      value: 31.973000000000003
+    - type: precision_at_5
+      value: 26.939
+    - type: recall_at_1
+      value: 2.703
+    - type: recall_at_10
+      value: 17.702
+    - type: recall_at_100
+      value: 17.702
+    - type: recall_at_1000
+      value: 17.702
+    - type: recall_at_3
+      value: 7.208
+    - type: recall_at_5
+      value: 9.748999999999999
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/toxic_conversations_50k
+      name: MTEB ToxicConversationsClassification
+      config: default
+      split: test
+      revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
+    metrics:
+    - type: accuracy
+      value: 70.79960000000001
+    - type: ap
+      value: 15.467565415565815
+    - type: f1
+      value: 55.28639823443618
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/tweet_sentiment_extraction
+      name: MTEB TweetSentimentExtractionClassification
+      config: default
+      split: test
+      revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
+    metrics:
+    - type: accuracy
+      value: 64.7792869269949
+    - type: f1
+      value: 65.08597154774318
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/twentynewsgroups-clustering
+      name: MTEB TwentyNewsgroupsClustering
+      config: default
+      split: test
+      revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
+    metrics:
+    - type: v_measure
+      value: 55.70352297774293
+  - task:
+      type: PairClassification
+    dataset:
+      type: mteb/twittersemeval2015-pairclassification
+      name: MTEB TwitterSemEval2015
+      config: default
+      split: test
+      revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
+    metrics:
+    - type: cos_sim_accuracy
+      value: 88.27561542588067
+    - type: cos_sim_ap
+      value: 81.08262141256193
+    - type: cos_sim_f1
+      value: 73.82341501361338
+    - type: cos_sim_precision
+      value: 72.5720112159062
+    - type: cos_sim_recall
+      value: 75.11873350923483
+    - type: dot_accuracy
+      value: 86.66030875603504
+    - type: dot_ap
+      value: 76.6052349228621
+    - type: dot_f1
+      value: 70.13897280966768
+    - type: dot_precision
+      value: 64.70457079152732
+    - type: dot_recall
+      value: 76.56992084432717
+    - type: euclidean_accuracy
+      value: 88.37098408535495
+    - type: euclidean_ap
+      value: 81.12515230092113
+    - type: euclidean_f1
+      value: 74.10338225909379
+    - type: euclidean_precision
+      value: 71.76761433868974
+    - type: euclidean_recall
+      value: 76.59630606860158
+    - type: manhattan_accuracy
+      value: 88.34118137926924
+    - type: manhattan_ap
+      value: 80.95751834536561
+    - type: manhattan_f1
+      value: 73.9119496855346
+    - type: manhattan_precision
+      value: 70.625
+    - type: manhattan_recall
+      value: 77.5197889182058
+    - type: max_accuracy
+      value: 88.37098408535495
+    - type: max_ap
+      value: 81.12515230092113
+    - type: max_f1
+      value: 74.10338225909379
+  - task:
+      type: PairClassification
+    dataset:
+      type: mteb/twitterurlcorpus-pairclassification
+      name: MTEB TwitterURLCorpus
+      config: default
+      split: test
+      revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
+    metrics:
+    - type: cos_sim_accuracy
+      value: 89.79896767182831
+    - type: cos_sim_ap
+      value: 87.40071784061065
+    - type: cos_sim_f1
+      value: 79.87753144712087
+    - type: cos_sim_precision
+      value: 76.67304015296367
+    - type: cos_sim_recall
+      value: 83.3615645210964
+    - type: dot_accuracy
+      value: 88.95486474948578
+    - type: dot_ap
+      value: 86.00227979119943
+    - type: dot_f1
+      value: 78.54601474525914
+    - type: dot_precision
+      value: 75.00525394045535
+    - type: dot_recall
+      value: 82.43763473975977
+    - type: euclidean_accuracy
+      value: 89.7892653393876
+    - type: euclidean_ap
+      value: 87.42174706480819
+    - type: euclidean_f1
+      value: 80.07283321194465
+    - type: euclidean_precision
+      value: 75.96738529574351
+    - type: euclidean_recall
+      value: 84.6473668001232
+    - type: manhattan_accuracy
+      value: 89.8474793340319
+    - type: manhattan_ap
+      value: 87.47814292587448
+    - type: manhattan_f1
+      value: 80.15461150280949
+    - type: manhattan_precision
+      value: 74.88798234468
+    - type: manhattan_recall
+      value: 86.21804742839544
+    - type: max_accuracy
+      value: 89.8474793340319
+    - type: max_ap
+      value: 87.47814292587448
+    - type: max_f1
+      value: 80.15461150280949
+---
+
+# Model Summary
+
+> GritLM is a generative representational instruction tuned language model. It unifies text representation (embedding) and text generation into a single model achieving state-of-the-art performance on both types of tasks.
+
+- **Repository:** [ContextualAI/gritlm](https://github.com/ContextualAI/gritlm)
+- **Paper:** https://arxiv.org/abs/2402.09906
+- **Logs:** https://wandb.ai/muennighoff/gritlm/runs/0uui712t/overview
+- **Script:** https://github.com/ContextualAI/gritlm/blob/main/scripts/training/train_gritlm_7b.sh
+
+| Model | Description |
+|-------|-------------|
+| [GritLM 7B](https://hf.co/GritLM/GritLM-7B) | Mistral 7B finetuned using GRIT |
+| [GritLM 8x7B](https://hf.co/GritLM/GritLM-8x7B) | Mixtral 8x7B finetuned using GRIT |
+
+# Use
+
+The model usage is documented [here](https://github.com/ContextualAI/gritlm?tab=readme-ov-file#inference).
+
+# Citation
+
+```bibtex
+@misc{muennighoff2024generative,
+      title={Generative Representational Instruction Tuning}, 
+      author={Niklas Muennighoff and Hongjin Su and Liang Wang and Nan Yang and Furu Wei and Tao Yu and Amanpreet Singh and Douwe Kiela},
+      year={2024},
+      eprint={2402.09906},
+      archivePrefix={arXiv},
+      primaryClass={cs.CL}
+}
+```
+