Remove evaluation results

README.md

@@ -24,2505 +24,13 @@ tags:
 - fever
 - hotpot_qa
 - mteb
-language: en
+language:
+- en
+- de
 inference: false
 license: apache-2.0
-model-index:
-- name: final_base_results
-  results:
-  - task:
-      type: Classification
-    dataset:
-      type: mteb/amazon_counterfactual
-      name: MTEB AmazonCounterfactualClassification (en)
-      config: en
-      split: test
-      revision: e8379541af4e31359cca9fbcf4b00f2671dba205
-    metrics:
-    - type: accuracy
-      value: 86.2089552238806
-    - type: ap
-      value: 55.76273850794966
-    - type: f1
-      value: 81.26104211414781
-  - task:
-      type: Classification
-    dataset:
-      type: mteb/amazon_polarity
-      name: MTEB AmazonPolarityClassification
-      config: default
-      split: test
-      revision: e2d317d38cd51312af73b3d32a06d1a08b442046
-    metrics:
-    - type: accuracy
-      value: 88.35995000000001
-    - type: ap
-      value: 84.18839957309655
-    - type: f1
-      value: 88.317619250081
-  - task:
-      type: Classification
-    dataset:
-      type: mteb/amazon_reviews_multi
-      name: MTEB AmazonReviewsClassification (en)
-      config: en
-      split: test
-      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
-    metrics:
-    - type: accuracy
-      value: 44.64
-    - type: f1
-      value: 42.48663956478136
-  - task:
-      type: Retrieval
-    dataset:
-      type: arguana
-      name: MTEB ArguAna
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 27.383000000000003
-    - type: map_at_10
-      value: 43.024
-    - type: map_at_100
-      value: 44.023
-    - type: map_at_1000
-      value: 44.025999999999996
-    - type: map_at_3
-      value: 37.684
-    - type: map_at_5
-      value: 40.884
-    - type: mrr_at_1
-      value: 28.094
-    - type: mrr_at_10
-      value: 43.315
-    - type: mrr_at_100
-      value: 44.313
-    - type: mrr_at_1000
-      value: 44.317
-    - type: mrr_at_3
-      value: 37.862
-    - type: mrr_at_5
-      value: 41.155
-    - type: ndcg_at_1
-      value: 27.383000000000003
-    - type: ndcg_at_10
-      value: 52.032000000000004
-    - type: ndcg_at_100
-      value: 56.19499999999999
-    - type: ndcg_at_1000
-      value: 56.272
-    - type: ndcg_at_3
-      value: 41.166000000000004
-    - type: ndcg_at_5
-      value: 46.92
-    - type: precision_at_1
-      value: 27.383000000000003
-    - type: precision_at_10
-      value: 8.087
-    - type: precision_at_100
-      value: 0.989
-    - type: precision_at_1000
-      value: 0.099
-    - type: precision_at_3
-      value: 17.093
-    - type: precision_at_5
-      value: 13.044
-    - type: recall_at_1
-      value: 27.383000000000003
-    - type: recall_at_10
-      value: 80.868
-    - type: recall_at_100
-      value: 98.86200000000001
-    - type: recall_at_1000
-      value: 99.431
-    - type: recall_at_3
-      value: 51.28
-    - type: recall_at_5
-      value: 65.22
-  - task:
-      type: Clustering
-    dataset:
-      type: mteb/arxiv-clustering-p2p
-      name: MTEB ArxivClusteringP2P
-      config: default
-      split: test
-      revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
-    metrics:
-    - type: v_measure
-      value: 39.68441054431849
-  - task:
-      type: Clustering
-    dataset:
-      type: mteb/arxiv-clustering-s2s
-      name: MTEB ArxivClusteringS2S
-      config: default
-      split: test
-      revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
-    metrics:
-    - type: v_measure
-      value: 29.188539728343844
-  - task:
-      type: Reranking
-    dataset:
-      type: mteb/askubuntudupquestions-reranking
-      name: MTEB AskUbuntuDupQuestions
-      config: default
-      split: test
-      revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
-    metrics:
-    - type: map
-      value: 63.173362687519784
-    - type: mrr
-      value: 76.18860748362133
-  - task:
-      type: STS
-    dataset:
-      type: mteb/biosses-sts
-      name: MTEB BIOSSES
-      config: default
-      split: test
-      revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
-    metrics:
-    - type: cos_sim_spearman
-      value: 82.30789953771232
-  - task:
-      type: Classification
-    dataset:
-      type: mteb/banking77
-      name: MTEB Banking77Classification
-      config: default
-      split: test
-      revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
-    metrics:
-    - type: accuracy
-      value: 77.03571428571428
-    - type: f1
-      value: 75.87384305045917
-  - task:
-      type: Clustering
-    dataset:
-      type: mteb/biorxiv-clustering-p2p
-      name: MTEB BiorxivClusteringP2P
-      config: default
-      split: test
-      revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
-    metrics:
-    - type: v_measure
-      value: 32.98041170516364
-  - task:
-      type: Clustering
-    dataset:
-      type: mteb/biorxiv-clustering-s2s
-      name: MTEB BiorxivClusteringS2S
-      config: default
-      split: test
-      revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
-    metrics:
-    - type: v_measure
-      value: 25.71652988451154
-  - task:
-      type: Retrieval
-    dataset:
-      type: BeIR/cqadupstack
-      name: MTEB CQADupstackAndroidRetrieval
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 33.739999999999995
-    - type: map_at_10
-      value: 46.197
-    - type: map_at_100
-      value: 47.814
-    - type: map_at_1000
-      value: 47.934
-    - type: map_at_3
-      value: 43.091
-    - type: map_at_5
-      value: 44.81
-    - type: mrr_at_1
-      value: 41.059
-    - type: mrr_at_10
-      value: 52.292
-    - type: mrr_at_100
-      value: 52.978
-    - type: mrr_at_1000
-      value: 53.015
-    - type: mrr_at_3
-      value: 49.976
-    - type: mrr_at_5
-      value: 51.449999999999996
-    - type: ndcg_at_1
-      value: 41.059
-    - type: ndcg_at_10
-      value: 52.608
-    - type: ndcg_at_100
-      value: 57.965
-    - type: ndcg_at_1000
-      value: 59.775999999999996
-    - type: ndcg_at_3
-      value: 48.473
-    - type: ndcg_at_5
-      value: 50.407999999999994
-    - type: precision_at_1
-      value: 41.059
-    - type: precision_at_10
-      value: 9.943
-    - type: precision_at_100
-      value: 1.6070000000000002
-    - type: precision_at_1000
-      value: 0.20500000000000002
-    - type: precision_at_3
-      value: 23.413999999999998
-    - type: precision_at_5
-      value: 16.481
-    - type: recall_at_1
-      value: 33.739999999999995
-    - type: recall_at_10
-      value: 63.888999999999996
-    - type: recall_at_100
-      value: 85.832
-    - type: recall_at_1000
-      value: 97.475
-    - type: recall_at_3
-      value: 51.953
-    - type: recall_at_5
-      value: 57.498000000000005
-  - task:
-      type: Retrieval
-    dataset:
-      type: BeIR/cqadupstack
-      name: MTEB CQADupstackEnglishRetrieval
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 31.169999999999998
-    - type: map_at_10
-      value: 41.455
-    - type: map_at_100
-      value: 42.716
-    - type: map_at_1000
-      value: 42.847
-    - type: map_at_3
-      value: 38.568999999999996
-    - type: map_at_5
-      value: 40.099000000000004
-    - type: mrr_at_1
-      value: 39.427
-    - type: mrr_at_10
-      value: 47.818
-    - type: mrr_at_100
-      value: 48.519
-    - type: mrr_at_1000
-      value: 48.558
-    - type: mrr_at_3
-      value: 45.86
-    - type: mrr_at_5
-      value: 46.936
-    - type: ndcg_at_1
-      value: 39.427
-    - type: ndcg_at_10
-      value: 47.181
-    - type: ndcg_at_100
-      value: 51.737
-    - type: ndcg_at_1000
-      value: 53.74
-    - type: ndcg_at_3
-      value: 43.261
-    - type: ndcg_at_5
-      value: 44.891
-    - type: precision_at_1
-      value: 39.427
-    - type: precision_at_10
-      value: 8.847
-    - type: precision_at_100
-      value: 1.425
-    - type: precision_at_1000
-      value: 0.189
-    - type: precision_at_3
-      value: 20.785999999999998
-    - type: precision_at_5
-      value: 14.560999999999998
-    - type: recall_at_1
-      value: 31.169999999999998
-    - type: recall_at_10
-      value: 56.971000000000004
-    - type: recall_at_100
-      value: 76.31400000000001
-    - type: recall_at_1000
-      value: 88.93900000000001
-    - type: recall_at_3
-      value: 45.208
-    - type: recall_at_5
-      value: 49.923
-  - task:
-      type: Retrieval
-    dataset:
-      type: BeIR/cqadupstack
-      name: MTEB CQADupstackGamingRetrieval
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 39.682
-    - type: map_at_10
-      value: 52.766000000000005
-    - type: map_at_100
-      value: 53.84100000000001
-    - type: map_at_1000
-      value: 53.898
-    - type: map_at_3
-      value: 49.291000000000004
-    - type: map_at_5
-      value: 51.365
-    - type: mrr_at_1
-      value: 45.266
-    - type: mrr_at_10
-      value: 56.093
-    - type: mrr_at_100
-      value: 56.763
-    - type: mrr_at_1000
-      value: 56.793000000000006
-    - type: mrr_at_3
-      value: 53.668000000000006
-    - type: mrr_at_5
-      value: 55.1
-    - type: ndcg_at_1
-      value: 45.266
-    - type: ndcg_at_10
-      value: 58.836
-    - type: ndcg_at_100
-      value: 62.863
-    - type: ndcg_at_1000
-      value: 63.912
-    - type: ndcg_at_3
-      value: 53.19199999999999
-    - type: ndcg_at_5
-      value: 56.125
-    - type: precision_at_1
-      value: 45.266
-    - type: precision_at_10
-      value: 9.492
-    - type: precision_at_100
-      value: 1.236
-    - type: precision_at_1000
-      value: 0.13699999999999998
-    - type: precision_at_3
-      value: 23.762
-    - type: precision_at_5
-      value: 16.414
-    - type: recall_at_1
-      value: 39.682
-    - type: recall_at_10
-      value: 73.233
-    - type: recall_at_100
-      value: 90.335
-    - type: recall_at_1000
-      value: 97.452
-    - type: recall_at_3
-      value: 58.562000000000005
-    - type: recall_at_5
-      value: 65.569
-  - task:
-      type: Retrieval
-    dataset:
-      type: BeIR/cqadupstack
-      name: MTEB CQADupstackGisRetrieval
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 26.743
-    - type: map_at_10
-      value: 34.016000000000005
-    - type: map_at_100
-      value: 35.028999999999996
-    - type: map_at_1000
-      value: 35.113
-    - type: map_at_3
-      value: 31.763
-    - type: map_at_5
-      value: 33.013999999999996
-    - type: mrr_at_1
-      value: 28.927000000000003
-    - type: mrr_at_10
-      value: 36.32
-    - type: mrr_at_100
-      value: 37.221
-    - type: mrr_at_1000
-      value: 37.281
-    - type: mrr_at_3
-      value: 34.105000000000004
-    - type: mrr_at_5
-      value: 35.371
-    - type: ndcg_at_1
-      value: 28.927000000000003
-    - type: ndcg_at_10
-      value: 38.474000000000004
-    - type: ndcg_at_100
-      value: 43.580000000000005
-    - type: ndcg_at_1000
-      value: 45.64
-    - type: ndcg_at_3
-      value: 34.035
-    - type: ndcg_at_5
-      value: 36.186
-    - type: precision_at_1
-      value: 28.927000000000003
-    - type: precision_at_10
-      value: 5.74
-    - type: precision_at_100
-      value: 0.8710000000000001
-    - type: precision_at_1000
-      value: 0.108
-    - type: precision_at_3
-      value: 14.124
-    - type: precision_at_5
-      value: 9.74
-    - type: recall_at_1
-      value: 26.743
-    - type: recall_at_10
-      value: 49.955
-    - type: recall_at_100
-      value: 73.904
-    - type: recall_at_1000
-      value: 89.133
-    - type: recall_at_3
-      value: 38.072
-    - type: recall_at_5
-      value: 43.266
-  - task:
-      type: Retrieval
-    dataset:
-      type: BeIR/cqadupstack
-      name: MTEB CQADupstackMathematicaRetrieval
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 16.928
-    - type: map_at_10
-      value: 23.549
-    - type: map_at_100
-      value: 24.887
-    - type: map_at_1000
-      value: 25.018
-    - type: map_at_3
-      value: 21.002000000000002
-    - type: map_at_5
-      value: 22.256
-    - type: mrr_at_1
-      value: 21.02
-    - type: mrr_at_10
-      value: 27.898
-    - type: mrr_at_100
-      value: 29.018
-    - type: mrr_at_1000
-      value: 29.099999999999998
-    - type: mrr_at_3
-      value: 25.456
-    - type: mrr_at_5
-      value: 26.625
-    - type: ndcg_at_1
-      value: 21.02
-    - type: ndcg_at_10
-      value: 28.277
-    - type: ndcg_at_100
-      value: 34.54
-    - type: ndcg_at_1000
-      value: 37.719
-    - type: ndcg_at_3
-      value: 23.707
-    - type: ndcg_at_5
-      value: 25.482
-    - type: precision_at_1
-      value: 21.02
-    - type: precision_at_10
-      value: 5.361
-    - type: precision_at_100
-      value: 0.9809999999999999
-    - type: precision_at_1000
-      value: 0.13899999999999998
-    - type: precision_at_3
-      value: 11.401
-    - type: precision_at_5
-      value: 8.209
-    - type: recall_at_1
-      value: 16.928
-    - type: recall_at_10
-      value: 38.601
-    - type: recall_at_100
-      value: 65.759
-    - type: recall_at_1000
-      value: 88.543
-    - type: recall_at_3
-      value: 25.556
-    - type: recall_at_5
-      value: 30.447000000000003
-  - task:
-      type: Retrieval
-    dataset:
-      type: BeIR/cqadupstack
-      name: MTEB CQADupstackPhysicsRetrieval
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 28.549000000000003
-    - type: map_at_10
-      value: 38.426
-    - type: map_at_100
-      value: 39.845000000000006
-    - type: map_at_1000
-      value: 39.956
-    - type: map_at_3
-      value: 35.372
-    - type: map_at_5
-      value: 37.204
-    - type: mrr_at_1
-      value: 35.034
-    - type: mrr_at_10
-      value: 44.041000000000004
-    - type: mrr_at_100
-      value: 44.95
-    - type: mrr_at_1000
-      value: 44.997
-    - type: mrr_at_3
-      value: 41.498000000000005
-    - type: mrr_at_5
-      value: 43.077
-    - type: ndcg_at_1
-      value: 35.034
-    - type: ndcg_at_10
-      value: 44.218
-    - type: ndcg_at_100
-      value: 49.958000000000006
-    - type: ndcg_at_1000
-      value: 52.019000000000005
-    - type: ndcg_at_3
-      value: 39.34
-    - type: ndcg_at_5
-      value: 41.892
-    - type: precision_at_1
-      value: 35.034
-    - type: precision_at_10
-      value: 7.911
-    - type: precision_at_100
-      value: 1.26
-    - type: precision_at_1000
-      value: 0.16
-    - type: precision_at_3
-      value: 18.511
-    - type: precision_at_5
-      value: 13.205
-    - type: recall_at_1
-      value: 28.549000000000003
-    - type: recall_at_10
-      value: 56.035999999999994
-    - type: recall_at_100
-      value: 79.701
-    - type: recall_at_1000
-      value: 93.149
-    - type: recall_at_3
-      value: 42.275
-    - type: recall_at_5
-      value: 49.097
-  - task:
-      type: Retrieval
-    dataset:
-      type: BeIR/cqadupstack
-      name: MTEB CQADupstackProgrammersRetrieval
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 29.391000000000002
-    - type: map_at_10
-      value: 39.48
-    - type: map_at_100
-      value: 40.727000000000004
-    - type: map_at_1000
-      value: 40.835
-    - type: map_at_3
-      value: 36.234
-    - type: map_at_5
-      value: 37.877
-    - type: mrr_at_1
-      value: 35.959
-    - type: mrr_at_10
-      value: 44.726
-    - type: mrr_at_100
-      value: 45.531
-    - type: mrr_at_1000
-      value: 45.582
-    - type: mrr_at_3
-      value: 42.047000000000004
-    - type: mrr_at_5
-      value: 43.611
-    - type: ndcg_at_1
-      value: 35.959
-    - type: ndcg_at_10
-      value: 45.303
-    - type: ndcg_at_100
-      value: 50.683
-    - type: ndcg_at_1000
-      value: 52.818
-    - type: ndcg_at_3
-      value: 39.987
-    - type: ndcg_at_5
-      value: 42.243
-    - type: precision_at_1
-      value: 35.959
-    - type: precision_at_10
-      value: 8.241999999999999
-    - type: precision_at_100
-      value: 1.274
-    - type: precision_at_1000
-      value: 0.163
-    - type: precision_at_3
-      value: 18.836
-    - type: precision_at_5
-      value: 13.196
-    - type: recall_at_1
-      value: 29.391000000000002
-    - type: recall_at_10
-      value: 57.364000000000004
-    - type: recall_at_100
-      value: 80.683
-    - type: recall_at_1000
-      value: 94.918
-    - type: recall_at_3
-      value: 42.263
-    - type: recall_at_5
-      value: 48.634
-  - task:
-      type: Retrieval
-    dataset:
-      type: BeIR/cqadupstack
-      name: MTEB CQADupstackRetrieval
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 26.791749999999997
-    - type: map_at_10
-      value: 35.75541666666667
-    - type: map_at_100
-      value: 37.00791666666667
-    - type: map_at_1000
-      value: 37.12408333333333
-    - type: map_at_3
-      value: 33.02966666666667
-    - type: map_at_5
-      value: 34.56866666666667
-    - type: mrr_at_1
-      value: 31.744333333333337
-    - type: mrr_at_10
-      value: 39.9925
-    - type: mrr_at_100
-      value: 40.86458333333333
-    - type: mrr_at_1000
-      value: 40.92175000000001
-    - type: mrr_at_3
-      value: 37.68183333333334
-    - type: mrr_at_5
-      value: 39.028499999999994
-    - type: ndcg_at_1
-      value: 31.744333333333337
-    - type: ndcg_at_10
-      value: 40.95008333333334
-    - type: ndcg_at_100
-      value: 46.25966666666667
-    - type: ndcg_at_1000
-      value: 48.535333333333334
-    - type: ndcg_at_3
-      value: 36.43333333333333
-    - type: ndcg_at_5
-      value: 38.602333333333334
-    - type: precision_at_1
-      value: 31.744333333333337
-    - type: precision_at_10
-      value: 7.135166666666666
-    - type: precision_at_100
-      value: 1.1535833333333334
-    - type: precision_at_1000
-      value: 0.15391666666666665
-    - type: precision_at_3
-      value: 16.713
-    - type: precision_at_5
-      value: 11.828416666666666
-    - type: recall_at_1
-      value: 26.791749999999997
-    - type: recall_at_10
-      value: 51.98625
-    - type: recall_at_100
-      value: 75.30358333333334
-    - type: recall_at_1000
-      value: 91.05433333333333
-    - type: recall_at_3
-      value: 39.39583333333333
-    - type: recall_at_5
-      value: 45.05925
-  - task:
-      type: Retrieval
-    dataset:
-      type: BeIR/cqadupstack
-      name: MTEB CQADupstackStatsRetrieval
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 22.219
-    - type: map_at_10
-      value: 29.162
-    - type: map_at_100
-      value: 30.049999999999997
-    - type: map_at_1000
-      value: 30.144
-    - type: map_at_3
-      value: 27.204
-    - type: map_at_5
-      value: 28.351
-    - type: mrr_at_1
-      value: 25.153
-    - type: mrr_at_10
-      value: 31.814999999999998
-    - type: mrr_at_100
-      value: 32.573
-    - type: mrr_at_1000
-      value: 32.645
-    - type: mrr_at_3
-      value: 29.934
-    - type: mrr_at_5
-      value: 30.946
-    - type: ndcg_at_1
-      value: 25.153
-    - type: ndcg_at_10
-      value: 33.099000000000004
-    - type: ndcg_at_100
-      value: 37.768
-    - type: ndcg_at_1000
-      value: 40.331
-    - type: ndcg_at_3
-      value: 29.473
-    - type: ndcg_at_5
-      value: 31.206
-    - type: precision_at_1
-      value: 25.153
-    - type: precision_at_10
-      value: 5.183999999999999
-    - type: precision_at_100
-      value: 0.8170000000000001
-    - type: precision_at_1000
-      value: 0.11100000000000002
-    - type: precision_at_3
-      value: 12.831999999999999
-    - type: precision_at_5
-      value: 8.895999999999999
-    - type: recall_at_1
-      value: 22.219
-    - type: recall_at_10
-      value: 42.637
-    - type: recall_at_100
-      value: 64.704
-    - type: recall_at_1000
-      value: 83.963
-    - type: recall_at_3
-      value: 32.444
-    - type: recall_at_5
-      value: 36.802
-  - task:
-      type: Retrieval
-    dataset:
-      type: BeIR/cqadupstack
-      name: MTEB CQADupstackTexRetrieval
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 17.427999999999997
-    - type: map_at_10
-      value: 24.029
-    - type: map_at_100
-      value: 25.119999999999997
-    - type: map_at_1000
-      value: 25.257
-    - type: map_at_3
-      value: 22.016
-    - type: map_at_5
-      value: 23.143
-    - type: mrr_at_1
-      value: 21.129
-    - type: mrr_at_10
-      value: 27.750000000000004
-    - type: mrr_at_100
-      value: 28.666999999999998
-    - type: mrr_at_1000
-      value: 28.754999999999995
-    - type: mrr_at_3
-      value: 25.849
-    - type: mrr_at_5
-      value: 26.939999999999998
-    - type: ndcg_at_1
-      value: 21.129
-    - type: ndcg_at_10
-      value: 28.203
-    - type: ndcg_at_100
-      value: 33.44
-    - type: ndcg_at_1000
-      value: 36.61
-    - type: ndcg_at_3
-      value: 24.648999999999997
-    - type: ndcg_at_5
-      value: 26.316
-    - type: precision_at_1
-      value: 21.129
-    - type: precision_at_10
-      value: 5.055
-    - type: precision_at_100
-      value: 0.909
-    - type: precision_at_1000
-      value: 0.13699999999999998
-    - type: precision_at_3
-      value: 11.666
-    - type: precision_at_5
-      value: 8.3
-    - type: recall_at_1
-      value: 17.427999999999997
-    - type: recall_at_10
-      value: 36.923
-    - type: recall_at_100
-      value: 60.606
-    - type: recall_at_1000
-      value: 83.19
-    - type: recall_at_3
-      value: 26.845000000000002
-    - type: recall_at_5
-      value: 31.247000000000003
-  - task:
-      type: Retrieval
-    dataset:
-      type: BeIR/cqadupstack
-      name: MTEB CQADupstackUnixRetrieval
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 26.457000000000004
-    - type: map_at_10
-      value: 35.228
-    - type: map_at_100
-      value: 36.475
-    - type: map_at_1000
-      value: 36.585
-    - type: map_at_3
-      value: 32.444
-    - type: map_at_5
-      value: 34.046
-    - type: mrr_at_1
-      value: 30.784
-    - type: mrr_at_10
-      value: 39.133
-    - type: mrr_at_100
-      value: 40.11
-    - type: mrr_at_1000
-      value: 40.169
-    - type: mrr_at_3
-      value: 36.692
-    - type: mrr_at_5
-      value: 38.17
-    - type: ndcg_at_1
-      value: 30.784
-    - type: ndcg_at_10
-      value: 40.358
-    - type: ndcg_at_100
-      value: 46.119
-    - type: ndcg_at_1000
-      value: 48.428
-    - type: ndcg_at_3
-      value: 35.504000000000005
-    - type: ndcg_at_5
-      value: 37.864
-    - type: precision_at_1
-      value: 30.784
-    - type: precision_at_10
-      value: 6.800000000000001
-    - type: precision_at_100
-      value: 1.083
-    - type: precision_at_1000
-      value: 0.13899999999999998
-    - type: precision_at_3
-      value: 15.920000000000002
-    - type: precision_at_5
-      value: 11.437
-    - type: recall_at_1
-      value: 26.457000000000004
-    - type: recall_at_10
-      value: 51.845
-    - type: recall_at_100
-      value: 77.046
-    - type: recall_at_1000
-      value: 92.892
-    - type: recall_at_3
-      value: 38.89
-    - type: recall_at_5
-      value: 44.688
-  - task:
-      type: Retrieval
-    dataset:
-      type: BeIR/cqadupstack
-      name: MTEB CQADupstackWebmastersRetrieval
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 29.378999999999998
-    - type: map_at_10
-      value: 37.373
-    - type: map_at_100
-      value: 39.107
-    - type: map_at_1000
-      value: 39.317
-    - type: map_at_3
-      value: 34.563
-    - type: map_at_5
-      value: 36.173
-    - type: mrr_at_1
-      value: 35.178
-    - type: mrr_at_10
-      value: 42.44
-    - type: mrr_at_100
-      value: 43.434
-    - type: mrr_at_1000
-      value: 43.482
-    - type: mrr_at_3
-      value: 39.987
-    - type: mrr_at_5
-      value: 41.370000000000005
-    - type: ndcg_at_1
-      value: 35.178
-    - type: ndcg_at_10
-      value: 42.82
-    - type: ndcg_at_100
-      value: 48.935
-    - type: ndcg_at_1000
-      value: 51.28
-    - type: ndcg_at_3
-      value: 38.562999999999995
-    - type: ndcg_at_5
-      value: 40.687
-    - type: precision_at_1
-      value: 35.178
-    - type: precision_at_10
-      value: 7.945
-    - type: precision_at_100
-      value: 1.524
-    - type: precision_at_1000
-      value: 0.242
-    - type: precision_at_3
-      value: 17.721
-    - type: precision_at_5
-      value: 12.925
-    - type: recall_at_1
-      value: 29.378999999999998
-    - type: recall_at_10
-      value: 52.141999999999996
-    - type: recall_at_100
-      value: 79.49000000000001
-    - type: recall_at_1000
-      value: 93.782
-    - type: recall_at_3
-      value: 39.579
-    - type: recall_at_5
-      value: 45.462
-  - task:
-      type: Retrieval
-    dataset:
-      type: BeIR/cqadupstack
-      name: MTEB CQADupstackWordpressRetrieval
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 19.814999999999998
-    - type: map_at_10
-      value: 27.383999999999997
-    - type: map_at_100
-      value: 28.483999999999998
-    - type: map_at_1000
-      value: 28.585
-    - type: map_at_3
-      value: 24.807000000000002
-    - type: map_at_5
-      value: 26.485999999999997
-    - type: mrr_at_1
-      value: 21.996
-    - type: mrr_at_10
-      value: 29.584
-    - type: mrr_at_100
-      value: 30.611
-    - type: mrr_at_1000
-      value: 30.684
-    - type: mrr_at_3
-      value: 27.11
-    - type: mrr_at_5
-      value: 28.746
-    - type: ndcg_at_1
-      value: 21.996
-    - type: ndcg_at_10
-      value: 32.024
-    - type: ndcg_at_100
-      value: 37.528
-    - type: ndcg_at_1000
-      value: 40.150999999999996
-    - type: ndcg_at_3
-      value: 27.016000000000002
-    - type: ndcg_at_5
-      value: 29.927999999999997
-    - type: precision_at_1
-      value: 21.996
-    - type: precision_at_10
-      value: 5.102
-    - type: precision_at_100
-      value: 0.856
-    - type: precision_at_1000
-      value: 0.117
-    - type: precision_at_3
-      value: 11.583
-    - type: precision_at_5
-      value: 8.577
-    - type: recall_at_1
-      value: 19.814999999999998
-    - type: recall_at_10
-      value: 44.239
-    - type: recall_at_100
-      value: 69.269
-    - type: recall_at_1000
-      value: 89.216
-    - type: recall_at_3
-      value: 31.102999999999998
-    - type: recall_at_5
-      value: 38.078
-  - task:
-      type: Retrieval
-    dataset:
-      type: climate-fever
-      name: MTEB ClimateFEVER
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 11.349
-    - type: map_at_10
-      value: 19.436
-    - type: map_at_100
-      value: 21.282999999999998
-    - type: map_at_1000
-      value: 21.479
-    - type: map_at_3
-      value: 15.841
-    - type: map_at_5
-      value: 17.558
-    - type: mrr_at_1
-      value: 25.863000000000003
-    - type: mrr_at_10
-      value: 37.218
-    - type: mrr_at_100
-      value: 38.198
-    - type: mrr_at_1000
-      value: 38.236
-    - type: mrr_at_3
-      value: 33.409
-    - type: mrr_at_5
-      value: 35.602000000000004
-    - type: ndcg_at_1
-      value: 25.863000000000003
-    - type: ndcg_at_10
-      value: 27.953
-    - type: ndcg_at_100
-      value: 35.327
-    - type: ndcg_at_1000
-      value: 38.708999999999996
-    - type: ndcg_at_3
-      value: 21.985
-    - type: ndcg_at_5
-      value: 23.957
-    - type: precision_at_1
-      value: 25.863000000000003
-    - type: precision_at_10
-      value: 8.99
-    - type: precision_at_100
-      value: 1.6889999999999998
-    - type: precision_at_1000
-      value: 0.232
-    - type: precision_at_3
-      value: 16.308
-    - type: precision_at_5
-      value: 12.912
-    - type: recall_at_1
-      value: 11.349
-    - type: recall_at_10
-      value: 34.581
-    - type: recall_at_100
-      value: 60.178
-    - type: recall_at_1000
-      value: 78.88199999999999
-    - type: recall_at_3
-      value: 20.041999999999998
-    - type: recall_at_5
-      value: 25.458
-  - task:
-      type: Retrieval
-    dataset:
-      type: dbpedia-entity
-      name: MTEB DBPedia
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 7.893
-    - type: map_at_10
-      value: 15.457
-    - type: map_at_100
-      value: 20.905
-    - type: map_at_1000
-      value: 22.116
-    - type: map_at_3
-      value: 11.593
-    - type: map_at_5
-      value: 13.134
-    - type: mrr_at_1
-      value: 57.49999999999999
-    - type: mrr_at_10
-      value: 65.467
-    - type: mrr_at_100
-      value: 66.022
-    - type: mrr_at_1000
-      value: 66.039
-    - type: mrr_at_3
-      value: 63.458000000000006
-    - type: mrr_at_5
-      value: 64.546
-    - type: ndcg_at_1
-      value: 45.875
-    - type: ndcg_at_10
-      value: 33.344
-    - type: ndcg_at_100
-      value: 36.849
-    - type: ndcg_at_1000
-      value: 44.03
-    - type: ndcg_at_3
-      value: 37.504
-    - type: ndcg_at_5
-      value: 34.892
-    - type: precision_at_1
-      value: 57.49999999999999
-    - type: precision_at_10
-      value: 25.95
-    - type: precision_at_100
-      value: 7.89
-    - type: precision_at_1000
-      value: 1.669
-    - type: precision_at_3
-      value: 40.333000000000006
-    - type: precision_at_5
-      value: 33.050000000000004
-    - type: recall_at_1
-      value: 7.893
-    - type: recall_at_10
-      value: 20.724999999999998
-    - type: recall_at_100
-      value: 42.516
-    - type: recall_at_1000
-      value: 65.822
-    - type: recall_at_3
-      value: 12.615000000000002
-    - type: recall_at_5
-      value: 15.482000000000001
-  - task:
-      type: Classification
-    dataset:
-      type: mteb/emotion
-      name: MTEB EmotionClassification
-      config: default
-      split: test
-      revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
-    metrics:
-    - type: accuracy
-      value: 51.760000000000005
-    - type: f1
-      value: 45.51690565701713
-  - task:
-      type: Retrieval
-    dataset:
-      type: fever
-      name: MTEB FEVER
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 53.882
-    - type: map_at_10
-      value: 65.902
-    - type: map_at_100
-      value: 66.33
-    - type: map_at_1000
-      value: 66.348
-    - type: map_at_3
-      value: 63.75999999999999
-    - type: map_at_5
-      value: 65.181
-    - type: mrr_at_1
-      value: 58.041
-    - type: mrr_at_10
-      value: 70.133
-    - type: mrr_at_100
-      value: 70.463
-    - type: mrr_at_1000
-      value: 70.47
-    - type: mrr_at_3
-      value: 68.164
-    - type: mrr_at_5
-      value: 69.465
-    - type: ndcg_at_1
-      value: 58.041
-    - type: ndcg_at_10
-      value: 71.84700000000001
-    - type: ndcg_at_100
-      value: 73.699
-    - type: ndcg_at_1000
-      value: 74.06700000000001
-    - type: ndcg_at_3
-      value: 67.855
-    - type: ndcg_at_5
-      value: 70.203
-    - type: precision_at_1
-      value: 58.041
-    - type: precision_at_10
-      value: 9.427000000000001
-    - type: precision_at_100
-      value: 1.049
-    - type: precision_at_1000
-      value: 0.11
-    - type: precision_at_3
-      value: 27.278000000000002
-    - type: precision_at_5
-      value: 17.693
-    - type: recall_at_1
-      value: 53.882
-    - type: recall_at_10
-      value: 85.99
-    - type: recall_at_100
-      value: 94.09100000000001
-    - type: recall_at_1000
-      value: 96.612
-    - type: recall_at_3
-      value: 75.25
-    - type: recall_at_5
-      value: 80.997
-  - task:
-      type: Retrieval
-    dataset:
-      type: fiqa
-      name: MTEB FiQA2018
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 19.165
-    - type: map_at_10
-      value: 31.845000000000002
-    - type: map_at_100
-      value: 33.678999999999995
-    - type: map_at_1000
-      value: 33.878
-    - type: map_at_3
-      value: 27.881
-    - type: map_at_5
-      value: 30.049999999999997
-    - type: mrr_at_1
-      value: 38.272
-    - type: mrr_at_10
-      value: 47.04
-    - type: mrr_at_100
-      value: 47.923
-    - type: mrr_at_1000
-      value: 47.973
-    - type: mrr_at_3
-      value: 44.985
-    - type: mrr_at_5
-      value: 46.150000000000006
-    - type: ndcg_at_1
-      value: 38.272
-    - type: ndcg_at_10
-      value: 39.177
-    - type: ndcg_at_100
-      value: 45.995000000000005
-    - type: ndcg_at_1000
-      value: 49.312
-    - type: ndcg_at_3
-      value: 36.135
-    - type: ndcg_at_5
-      value: 36.936
-    - type: precision_at_1
-      value: 38.272
-    - type: precision_at_10
-      value: 10.926
-    - type: precision_at_100
-      value: 1.809
-    - type: precision_at_1000
-      value: 0.23700000000000002
-    - type: precision_at_3
-      value: 24.331
-    - type: precision_at_5
-      value: 17.747
-    - type: recall_at_1
-      value: 19.165
-    - type: recall_at_10
-      value: 45.103
-    - type: recall_at_100
-      value: 70.295
-    - type: recall_at_1000
-      value: 90.592
-    - type: recall_at_3
-      value: 32.832
-    - type: recall_at_5
-      value: 37.905
-  - task:
-      type: Retrieval
-    dataset:
-      type: hotpotqa
-      name: MTEB HotpotQA
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 32.397
-    - type: map_at_10
-      value: 44.83
-    - type: map_at_100
-      value: 45.716
-    - type: map_at_1000
-      value: 45.797
-    - type: map_at_3
-      value: 41.955999999999996
-    - type: map_at_5
-      value: 43.736999999999995
-    - type: mrr_at_1
-      value: 64.794
-    - type: mrr_at_10
-      value: 71.866
-    - type: mrr_at_100
-      value: 72.22
-    - type: mrr_at_1000
-      value: 72.238
-    - type: mrr_at_3
-      value: 70.416
-    - type: mrr_at_5
-      value: 71.304
-    - type: ndcg_at_1
-      value: 64.794
-    - type: ndcg_at_10
-      value: 54.186
-    - type: ndcg_at_100
-      value: 57.623000000000005
-    - type: ndcg_at_1000
-      value: 59.302
-    - type: ndcg_at_3
-      value: 49.703
-    - type: ndcg_at_5
-      value: 52.154999999999994
-    - type: precision_at_1
-      value: 64.794
-    - type: precision_at_10
-      value: 11.219
-    - type: precision_at_100
-      value: 1.394
-    - type: precision_at_1000
-      value: 0.16199999999999998
-    - type: precision_at_3
-      value: 30.767
-    - type: precision_at_5
-      value: 20.397000000000002
-    - type: recall_at_1
-      value: 32.397
-    - type: recall_at_10
-      value: 56.096999999999994
-    - type: recall_at_100
-      value: 69.696
-    - type: recall_at_1000
-      value: 80.88499999999999
-    - type: recall_at_3
-      value: 46.150999999999996
-    - type: recall_at_5
-      value: 50.993
-  - task:
-      type: Classification
-    dataset:
-      type: mteb/imdb
-      name: MTEB ImdbClassification
-      config: default
-      split: test
-      revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
-    metrics:
-    - type: accuracy
-      value: 81.1744
-    - type: ap
-      value: 75.44973697032414
-    - type: f1
-      value: 81.09901117955782
-  - task:
-      type: Retrieval
-    dataset:
-      type: msmarco
-      name: MTEB MSMARCO
-      config: default
-      split: dev
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 19.519000000000002
-    - type: map_at_10
-      value: 31.025000000000002
-    - type: map_at_100
-      value: 32.275999999999996
-    - type: map_at_1000
-      value: 32.329
-    - type: map_at_3
-      value: 27.132
-    - type: map_at_5
-      value: 29.415999999999997
-    - type: mrr_at_1
-      value: 20.115
-    - type: mrr_at_10
-      value: 31.569000000000003
-    - type: mrr_at_100
-      value: 32.768
-    - type: mrr_at_1000
-      value: 32.816
-    - type: mrr_at_3
-      value: 27.748
-    - type: mrr_at_5
-      value: 29.956
-    - type: ndcg_at_1
-      value: 20.115
-    - type: ndcg_at_10
-      value: 37.756
-    - type: ndcg_at_100
-      value: 43.858000000000004
-    - type: ndcg_at_1000
-      value: 45.199
-    - type: ndcg_at_3
-      value: 29.818
-    - type: ndcg_at_5
-      value: 33.875
-    - type: precision_at_1
-      value: 20.115
-    - type: precision_at_10
-      value: 6.122
-    - type: precision_at_100
-      value: 0.919
-    - type: precision_at_1000
-      value: 0.10300000000000001
-    - type: precision_at_3
-      value: 12.794
-    - type: precision_at_5
-      value: 9.731
-    - type: recall_at_1
-      value: 19.519000000000002
-    - type: recall_at_10
-      value: 58.62500000000001
-    - type: recall_at_100
-      value: 86.99
-    - type: recall_at_1000
-      value: 97.268
-    - type: recall_at_3
-      value: 37.002
-    - type: recall_at_5
-      value: 46.778
-  - task:
-      type: Classification
-    dataset:
-      type: mteb/mtop_domain
-      name: MTEB MTOPDomainClassification (en)
-      config: en
-      split: test
-      revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
-    metrics:
-    - type: accuracy
-      value: 93.71865025079799
-    - type: f1
-      value: 93.38906173610519
-  - task:
-      type: Classification
-    dataset:
-      type: mteb/mtop_intent
-      name: MTEB MTOPIntentClassification (en)
-      config: en
-      split: test
-      revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
-    metrics:
-    - type: accuracy
-      value: 70.2576379388965
-    - type: f1
-      value: 49.20405830249464
-  - task:
-      type: Classification
-    dataset:
-      type: mteb/amazon_massive_intent
-      name: MTEB MassiveIntentClassification (en)
-      config: en
-      split: test
-      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
-    metrics:
-    - type: accuracy
-      value: 67.48486886348351
-    - type: f1
-      value: 64.92199176095157
-  - task:
-      type: Classification
-    dataset:
-      type: mteb/amazon_massive_scenario
-      name: MTEB MassiveScenarioClassification (en)
-      config: en
-      split: test
-      revision: 7d571f92784cd94a019292a1f45445077d0ef634
-    metrics:
-    - type: accuracy
-      value: 72.59246805648958
-    - type: f1
-      value: 72.1222026389164
-  - task:
-      type: Clustering
-    dataset:
-      type: mteb/medrxiv-clustering-p2p
-      name: MTEB MedrxivClusteringP2P
-      config: default
-      split: test
-      revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
-    metrics:
-    - type: v_measure
-      value: 30.887642595096825
-  - task:
-      type: Clustering
-    dataset:
-      type: mteb/medrxiv-clustering-s2s
-      name: MTEB MedrxivClusteringS2S
-      config: default
-      split: test
-      revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
-    metrics:
-    - type: v_measure
-      value: 28.3764418784054
-  - task:
-      type: Reranking
-    dataset:
-      type: mteb/mind_small
-      name: MTEB MindSmallReranking
-      config: default
-      split: test
-      revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
-    metrics:
-    - type: map
-      value: 31.81544126336991
-    - type: mrr
-      value: 32.82666576268031
-  - task:
-      type: Retrieval
-    dataset:
-      type: nfcorpus
-      name: MTEB NFCorpus
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 5.185
-    - type: map_at_10
-      value: 11.158
-    - type: map_at_100
-      value: 14.041
-    - type: map_at_1000
-      value: 15.360999999999999
-    - type: map_at_3
-      value: 8.417
-    - type: map_at_5
-      value: 9.378
-    - type: mrr_at_1
-      value: 44.582
-    - type: mrr_at_10
-      value: 53.083999999999996
-    - type: mrr_at_100
-      value: 53.787
-    - type: mrr_at_1000
-      value: 53.824000000000005
-    - type: mrr_at_3
-      value: 51.187000000000005
-    - type: mrr_at_5
-      value: 52.379
-    - type: ndcg_at_1
-      value: 42.57
-    - type: ndcg_at_10
-      value: 31.593
-    - type: ndcg_at_100
-      value: 29.093999999999998
-    - type: ndcg_at_1000
-      value: 37.909
-    - type: ndcg_at_3
-      value: 37.083
-    - type: ndcg_at_5
-      value: 34.397
-    - type: precision_at_1
-      value: 43.963
-    - type: precision_at_10
-      value: 23.498
-    - type: precision_at_100
-      value: 7.6160000000000005
-    - type: precision_at_1000
-      value: 2.032
-    - type: precision_at_3
-      value: 34.572
-    - type: precision_at_5
-      value: 29.412
-    - type: recall_at_1
-      value: 5.185
-    - type: recall_at_10
-      value: 15.234
-    - type: recall_at_100
-      value: 29.49
-    - type: recall_at_1000
-      value: 62.273999999999994
-    - type: recall_at_3
-      value: 9.55
-    - type: recall_at_5
-      value: 11.103
-  - task:
-      type: Retrieval
-    dataset:
-      type: nq
-      name: MTEB NQ
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 23.803
-    - type: map_at_10
-      value: 38.183
-    - type: map_at_100
-      value: 39.421
-    - type: map_at_1000
-      value: 39.464
-    - type: map_at_3
-      value: 33.835
-    - type: map_at_5
-      value: 36.327
-    - type: mrr_at_1
-      value: 26.68
-    - type: mrr_at_10
-      value: 40.439
-    - type: mrr_at_100
-      value: 41.415
-    - type: mrr_at_1000
-      value: 41.443999999999996
-    - type: mrr_at_3
-      value: 36.612
-    - type: mrr_at_5
-      value: 38.877
-    - type: ndcg_at_1
-      value: 26.68
-    - type: ndcg_at_10
-      value: 45.882
-    - type: ndcg_at_100
-      value: 51.227999999999994
-    - type: ndcg_at_1000
-      value: 52.207
-    - type: ndcg_at_3
-      value: 37.511
-    - type: ndcg_at_5
-      value: 41.749
-    - type: precision_at_1
-      value: 26.68
-    - type: precision_at_10
-      value: 7.9750000000000005
-    - type: precision_at_100
-      value: 1.0959999999999999
-    - type: precision_at_1000
-      value: 0.11900000000000001
-    - type: precision_at_3
-      value: 17.449
-    - type: precision_at_5
-      value: 12.897
-    - type: recall_at_1
-      value: 23.803
-    - type: recall_at_10
-      value: 67.152
-    - type: recall_at_100
-      value: 90.522
-    - type: recall_at_1000
-      value: 97.743
-    - type: recall_at_3
-      value: 45.338
-    - type: recall_at_5
-      value: 55.106
-  - task:
-      type: Retrieval
-    dataset:
-      type: quora
-      name: MTEB QuoraRetrieval
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 70.473
-    - type: map_at_10
-      value: 84.452
-    - type: map_at_100
-      value: 85.101
-    - type: map_at_1000
-      value: 85.115
-    - type: map_at_3
-      value: 81.435
-    - type: map_at_5
-      value: 83.338
-    - type: mrr_at_1
-      value: 81.19
-    - type: mrr_at_10
-      value: 87.324
-    - type: mrr_at_100
-      value: 87.434
-    - type: mrr_at_1000
-      value: 87.435
-    - type: mrr_at_3
-      value: 86.31
-    - type: mrr_at_5
-      value: 87.002
-    - type: ndcg_at_1
-      value: 81.21000000000001
-    - type: ndcg_at_10
-      value: 88.19
-    - type: ndcg_at_100
-      value: 89.44
-    - type: ndcg_at_1000
-      value: 89.526
-    - type: ndcg_at_3
-      value: 85.237
-    - type: ndcg_at_5
-      value: 86.892
-    - type: precision_at_1
-      value: 81.21000000000001
-    - type: precision_at_10
-      value: 13.417000000000002
-    - type: precision_at_100
-      value: 1.537
-    - type: precision_at_1000
-      value: 0.157
-    - type: precision_at_3
-      value: 37.31
-    - type: precision_at_5
-      value: 24.59
-    - type: recall_at_1
-      value: 70.473
-    - type: recall_at_10
-      value: 95.367
-    - type: recall_at_100
-      value: 99.616
-    - type: recall_at_1000
-      value: 99.996
-    - type: recall_at_3
-      value: 86.936
-    - type: recall_at_5
-      value: 91.557
-  - task:
-      type: Clustering
-    dataset:
-      type: mteb/reddit-clustering
-      name: MTEB RedditClustering
-      config: default
-      split: test
-      revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
-    metrics:
-    - type: v_measure
-      value: 59.25776525253911
-  - task:
-      type: Clustering
-    dataset:
-      type: mteb/reddit-clustering-p2p
-      name: MTEB RedditClusteringP2P
-      config: default
-      split: test
-      revision: 282350215ef01743dc01b456c7f5241fa8937f16
-    metrics:
-    - type: v_measure
-      value: 63.22135271663078
-  - task:
-      type: Retrieval
-    dataset:
-      type: scidocs
-      name: MTEB SCIDOCS
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 4.003
-    - type: map_at_10
-      value: 10.062999999999999
-    - type: map_at_100
-      value: 11.854000000000001
-    - type: map_at_1000
-      value: 12.145999999999999
-    - type: map_at_3
-      value: 7.242
-    - type: map_at_5
-      value: 8.652999999999999
-    - type: mrr_at_1
-      value: 19.7
-    - type: mrr_at_10
-      value: 29.721999999999998
-    - type: mrr_at_100
-      value: 30.867
-    - type: mrr_at_1000
-      value: 30.944
-    - type: mrr_at_3
-      value: 26.683
-    - type: mrr_at_5
-      value: 28.498
-    - type: ndcg_at_1
-      value: 19.7
-    - type: ndcg_at_10
-      value: 17.095
-    - type: ndcg_at_100
-      value: 24.375
-    - type: ndcg_at_1000
-      value: 29.831000000000003
-    - type: ndcg_at_3
-      value: 16.305
-    - type: ndcg_at_5
-      value: 14.291
-    - type: precision_at_1
-      value: 19.7
-    - type: precision_at_10
-      value: 8.799999999999999
-    - type: precision_at_100
-      value: 1.9349999999999998
-    - type: precision_at_1000
-      value: 0.32399999999999995
-    - type: precision_at_3
-      value: 15.2
-    - type: precision_at_5
-      value: 12.540000000000001
-    - type: recall_at_1
-      value: 4.003
-    - type: recall_at_10
-      value: 17.877000000000002
-    - type: recall_at_100
-      value: 39.217
-    - type: recall_at_1000
-      value: 65.862
-    - type: recall_at_3
-      value: 9.242
-    - type: recall_at_5
-      value: 12.715000000000002
-  - task:
-      type: STS
-    dataset:
-      type: mteb/sickr-sts
-      name: MTEB SICK-R
-      config: default
-      split: test
-      revision: a6ea5a8cab320b040a23452cc28066d9beae2cee
-    metrics:
-    - type: cos_sim_spearman
-      value: 80.25888668589654
-  - task:
-      type: STS
-    dataset:
-      type: mteb/sts12-sts
-      name: MTEB STS12
-      config: default
-      split: test
-      revision: a0d554a64d88156834ff5ae9920b964011b16384
-    metrics:
-    - type: cos_sim_spearman
-      value: 77.02037527837669
-  - task:
-      type: STS
-    dataset:
-      type: mteb/sts13-sts
-      name: MTEB STS13
-      config: default
-      split: test
-      revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
-    metrics:
-    - type: cos_sim_spearman
-      value: 86.58432681008449
-  - task:
-      type: STS
-    dataset:
-      type: mteb/sts14-sts
-      name: MTEB STS14
-      config: default
-      split: test
-      revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
-    metrics:
-    - type: cos_sim_spearman
-      value: 81.31697756099051
-  - task:
-      type: STS
-    dataset:
-      type: mteb/sts15-sts
-      name: MTEB STS15
-      config: default
-      split: test
-      revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
-    metrics:
-    - type: cos_sim_spearman
-      value: 88.18867599667057
-  - task:
-      type: STS
-    dataset:
-      type: mteb/sts16-sts
-      name: MTEB STS16
-      config: default
-      split: test
-      revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
-    metrics:
-    - type: cos_sim_spearman
-      value: 84.87853941747623
-  - 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_spearman
-      value: 89.46479925383916
-  - task:
-      type: STS
-    dataset:
-      type: mteb/sts22-crosslingual-sts
-      name: MTEB STS22 (en)
-      config: en
-      split: test
-      revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80
-    metrics:
-    - type: cos_sim_spearman
-      value: 66.45272113649146
-  - task:
-      type: STS
-    dataset:
-      type: mteb/stsbenchmark-sts
-      name: MTEB STSBenchmark
-      config: default
-      split: test
-      revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
-    metrics:
-    - type: cos_sim_spearman
-      value: 86.43357313527851
-  - task:
-      type: Reranking
-    dataset:
-      type: mteb/scidocs-reranking
-      name: MTEB SciDocsRR
-      config: default
-      split: test
-      revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
-    metrics:
-    - type: map
-      value: 78.82761687254882
-    - type: mrr
-      value: 93.46223674655047
-  - task:
-      type: Retrieval
-    dataset:
-      type: scifact
-      name: MTEB SciFact
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 44.583
-    - type: map_at_10
-      value: 52.978
-    - type: map_at_100
-      value: 53.803
-    - type: map_at_1000
-      value: 53.839999999999996
-    - type: map_at_3
-      value: 50.03300000000001
-    - type: map_at_5
-      value: 51.939
-    - type: mrr_at_1
-      value: 47.0
-    - type: mrr_at_10
-      value: 54.730000000000004
-    - type: mrr_at_100
-      value: 55.31399999999999
-    - type: mrr_at_1000
-      value: 55.346
-    - type: mrr_at_3
-      value: 52.0
-    - type: mrr_at_5
-      value: 53.783
-    - type: ndcg_at_1
-      value: 47.0
-    - type: ndcg_at_10
-      value: 57.82899999999999
-    - type: ndcg_at_100
-      value: 61.49400000000001
-    - type: ndcg_at_1000
-      value: 62.676
-    - type: ndcg_at_3
-      value: 52.373000000000005
-    - type: ndcg_at_5
-      value: 55.481
-    - type: precision_at_1
-      value: 47.0
-    - type: precision_at_10
-      value: 7.867
-    - type: precision_at_100
-      value: 0.997
-    - type: precision_at_1000
-      value: 0.11
-    - type: precision_at_3
-      value: 20.556
-    - type: precision_at_5
-      value: 14.066999999999998
-    - type: recall_at_1
-      value: 44.583
-    - type: recall_at_10
-      value: 71.172
-    - type: recall_at_100
-      value: 87.7
-    - type: recall_at_1000
-      value: 97.333
-    - type: recall_at_3
-      value: 56.511
-    - type: recall_at_5
-      value: 64.206
-  - task:
-      type: PairClassification
-    dataset:
-      type: mteb/sprintduplicatequestions-pairclassification
-      name: MTEB SprintDuplicateQuestions
-      config: default
-      split: test
-      revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
-    metrics:
-    - type: cos_sim_accuracy
-      value: 99.66237623762376
-    - type: cos_sim_ap
-      value: 90.35465126226322
-    - type: cos_sim_f1
-      value: 82.44575936883628
-    - type: cos_sim_precision
-      value: 81.32295719844358
-    - type: cos_sim_recall
-      value: 83.6
-    - type: dot_accuracy
-      value: 99.66237623762376
-    - type: dot_ap
-      value: 90.35464287920453
-    - type: dot_f1
-      value: 82.44575936883628
-    - type: dot_precision
-      value: 81.32295719844358
-    - type: dot_recall
-      value: 83.6
-    - type: euclidean_accuracy
-      value: 99.66237623762376
-    - type: euclidean_ap
-      value: 90.3546512622632
-    - type: euclidean_f1
-      value: 82.44575936883628
-    - type: euclidean_precision
-      value: 81.32295719844358
-    - type: euclidean_recall
-      value: 83.6
-    - type: manhattan_accuracy
-      value: 99.65940594059406
-    - type: manhattan_ap
-      value: 90.29220174849843
-    - type: manhattan_f1
-      value: 82.4987605354487
-    - type: manhattan_precision
-      value: 81.80924287118977
-    - type: manhattan_recall
-      value: 83.2
-    - type: max_accuracy
-      value: 99.66237623762376
-    - type: max_ap
-      value: 90.35465126226322
-    - type: max_f1
-      value: 82.4987605354487
-  - task:
-      type: Clustering
-    dataset:
-      type: mteb/stackexchange-clustering
-      name: MTEB StackExchangeClustering
-      config: default
-      split: test
-      revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
-    metrics:
-    - type: v_measure
-      value: 65.0394225901397
-  - task:
-      type: Clustering
-    dataset:
-      type: mteb/stackexchange-clustering-p2p
-      name: MTEB StackExchangeClusteringP2P
-      config: default
-      split: test
-      revision: 815ca46b2622cec33ccafc3735d572c266efdb44
-    metrics:
-    - type: v_measure
-      value: 35.27954189859326
-  - task:
-      type: Reranking
-    dataset:
-      type: mteb/stackoverflowdupquestions-reranking
-      name: MTEB StackOverflowDupQuestions
-      config: default
-      split: test
-      revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
-    metrics:
-    - type: map
-      value: 50.99055979974896
-    - type: mrr
-      value: 51.82745257193787
-  - task:
-      type: Summarization
-    dataset:
-      type: mteb/summeval
-      name: MTEB SummEval
-      config: default
-      split: test
-      revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
-    metrics:
-    - type: cos_sim_pearson
-      value: 30.21655465344237
-    - type: cos_sim_spearman
-      value: 29.853205339630172
-    - type: dot_pearson
-      value: 30.216540628083564
-    - type: dot_spearman
-      value: 29.868978894753027
-  - task:
-      type: Retrieval
-    dataset:
-      type: trec-covid
-      name: MTEB TRECCOVID
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 0.2
-    - type: map_at_10
-      value: 1.398
-    - type: map_at_100
-      value: 7.406
-    - type: map_at_1000
-      value: 18.401
-    - type: map_at_3
-      value: 0.479
-    - type: map_at_5
-      value: 0.772
-    - type: mrr_at_1
-      value: 70.0
-    - type: mrr_at_10
-      value: 79.25999999999999
-    - type: mrr_at_100
-      value: 79.25999999999999
-    - type: mrr_at_1000
-      value: 79.25999999999999
-    - type: mrr_at_3
-      value: 77.333
-    - type: mrr_at_5
-      value: 78.133
-    - type: ndcg_at_1
-      value: 63.0
-    - type: ndcg_at_10
-      value: 58.548
-    - type: ndcg_at_100
-      value: 45.216
-    - type: ndcg_at_1000
-      value: 41.149
-    - type: ndcg_at_3
-      value: 60.641999999999996
-    - type: ndcg_at_5
-      value: 61.135
-    - type: precision_at_1
-      value: 70.0
-    - type: precision_at_10
-      value: 64.0
-    - type: precision_at_100
-      value: 46.92
-    - type: precision_at_1000
-      value: 18.642
-    - type: precision_at_3
-      value: 64.667
-    - type: precision_at_5
-      value: 66.4
-    - type: recall_at_1
-      value: 0.2
-    - type: recall_at_10
-      value: 1.6729999999999998
-    - type: recall_at_100
-      value: 10.856
-    - type: recall_at_1000
-      value: 38.964999999999996
-    - type: recall_at_3
-      value: 0.504
-    - type: recall_at_5
-      value: 0.852
-  - task:
-      type: Retrieval
-    dataset:
-      type: webis-touche2020
-      name: MTEB Touche2020
-      config: default
-      split: test
-      revision: None
-    metrics:
-    - type: map_at_1
-      value: 1.6629999999999998
-    - type: map_at_10
-      value: 8.601
-    - type: map_at_100
-      value: 14.354
-    - type: map_at_1000
-      value: 15.927
-    - type: map_at_3
-      value: 4.1930000000000005
-    - type: map_at_5
-      value: 5.655
-    - type: mrr_at_1
-      value: 18.367
-    - type: mrr_at_10
-      value: 34.466
-    - type: mrr_at_100
-      value: 35.235
-    - type: mrr_at_1000
-      value: 35.27
-    - type: mrr_at_3
-      value: 28.571
-    - type: mrr_at_5
-      value: 31.531
-    - type: ndcg_at_1
-      value: 14.285999999999998
-    - type: ndcg_at_10
-      value: 20.374
-    - type: ndcg_at_100
-      value: 33.532000000000004
-    - type: ndcg_at_1000
-      value: 45.561
-    - type: ndcg_at_3
-      value: 18.442
-    - type: ndcg_at_5
-      value: 18.076
-    - type: precision_at_1
-      value: 18.367
-    - type: precision_at_10
-      value: 20.204
-    - type: precision_at_100
-      value: 7.489999999999999
-    - type: precision_at_1000
-      value: 1.5630000000000002
-    - type: precision_at_3
-      value: 21.769
-    - type: precision_at_5
-      value: 20.408
-    - type: recall_at_1
-      value: 1.6629999999999998
-    - type: recall_at_10
-      value: 15.549
-    - type: recall_at_100
-      value: 47.497
-    - type: recall_at_1000
-      value: 84.524
-    - type: recall_at_3
-      value: 5.289
-    - type: recall_at_5
-      value: 8.035
-  - task:
-      type: Classification
-    dataset:
-      type: mteb/toxic_conversations_50k
-      name: MTEB ToxicConversationsClassification
-      config: default
-      split: test
-      revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
-    metrics:
-    - type: accuracy
-      value: 71.8194
-    - type: ap
-      value: 14.447702451658554
-    - type: f1
-      value: 55.13659412856185
-  - task:
-      type: Classification
-    dataset:
-      type: mteb/tweet_sentiment_extraction
-      name: MTEB TweetSentimentExtractionClassification
-      config: default
-      split: test
-      revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
-    metrics:
-    - type: accuracy
-      value: 63.310696095076416
-    - type: f1
-      value: 63.360434851097814
-  - task:
-      type: Clustering
-    dataset:
-      type: mteb/twentynewsgroups-clustering
-      name: MTEB TwentyNewsgroupsClustering
-      config: default
-      split: test
-      revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
-    metrics:
-    - type: v_measure
-      value: 51.30677907335145
-  - task:
-      type: PairClassification
-    dataset:
-      type: mteb/twittersemeval2015-pairclassification
-      name: MTEB TwitterSemEval2015
-      config: default
-      split: test
-      revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
-    metrics:
-    - type: cos_sim_accuracy
-      value: 86.12386004649221
-    - type: cos_sim_ap
-      value: 73.99096426215495
-    - type: cos_sim_f1
-      value: 68.18416968442834
-    - type: cos_sim_precision
-      value: 66.86960933536275
-    - type: cos_sim_recall
-      value: 69.55145118733509
-    - type: dot_accuracy
-      value: 86.12386004649221
-    - type: dot_ap
-      value: 73.99096813038672
-    - type: dot_f1
-      value: 68.18416968442834
-    - type: dot_precision
-      value: 66.86960933536275
-    - type: dot_recall
-      value: 69.55145118733509
-    - type: euclidean_accuracy
-      value: 86.12386004649221
-    - type: euclidean_ap
-      value: 73.99095984980165
-    - type: euclidean_f1
-      value: 68.18416968442834
-    - type: euclidean_precision
-      value: 66.86960933536275
-    - type: euclidean_recall
-      value: 69.55145118733509
-    - type: manhattan_accuracy
-      value: 86.09405734040651
-    - type: manhattan_ap
-      value: 73.96825745608601
-    - type: manhattan_f1
-      value: 68.13888179729383
-    - type: manhattan_precision
-      value: 65.99901088031652
-    - type: manhattan_recall
-      value: 70.42216358839049
-    - type: max_accuracy
-      value: 86.12386004649221
-    - type: max_ap
-      value: 73.99096813038672
-    - type: max_f1
-      value: 68.18416968442834
-  - task:
-      type: PairClassification
-    dataset:
-      type: mteb/twitterurlcorpus-pairclassification
-      name: MTEB TwitterURLCorpus
-      config: default
-      split: test
-      revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
-    metrics:
-    - type: cos_sim_accuracy
-      value: 88.99367407924865
-    - type: cos_sim_ap
-      value: 86.19720829843081
-    - type: cos_sim_f1
-      value: 78.39889075384951
-    - type: cos_sim_precision
-      value: 74.5110278818144
-    - type: cos_sim_recall
-      value: 82.71481367416075
-    - type: dot_accuracy
-      value: 88.99367407924865
-    - type: dot_ap
-      value: 86.19718471454047
-    - type: dot_f1
-      value: 78.39889075384951
-    - type: dot_precision
-      value: 74.5110278818144
-    - type: dot_recall
-      value: 82.71481367416075
-    - type: euclidean_accuracy
-      value: 88.99367407924865
-    - type: euclidean_ap
-      value: 86.1972021422436
-    - type: euclidean_f1
-      value: 78.39889075384951
-    - type: euclidean_precision
-      value: 74.5110278818144
-    - type: euclidean_recall
-      value: 82.71481367416075
-    - type: manhattan_accuracy
-      value: 88.95680521597392
-    - type: manhattan_ap
-      value: 86.16659921351506
-    - type: manhattan_f1
-      value: 78.39125971550081
-    - type: manhattan_precision
-      value: 74.82502799552073
-    - type: manhattan_recall
-      value: 82.31444410224823
-    - type: max_accuracy
-      value: 88.99367407924865
-    - type: max_ap
-      value: 86.19720829843081
-    - type: max_f1
-      value: 78.39889075384951
 ---
+
 # pascalhuerten/instructor-skillfit
 A finetuning of hkunlp/instructor-base specialized on performing retrival of relevant skills based on a given learning outcome.