|
--- |
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tags: |
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- mteb |
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model-index: |
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- name: multi-qa-MiniLM-L6-cos-v1 |
|
results: |
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- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/amazon_counterfactual |
|
name: MTEB AmazonCounterfactualClassification (en) |
|
config: en |
|
split: test |
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revision: e8379541af4e31359cca9fbcf4b00f2671dba205 |
|
metrics: |
|
- type: accuracy |
|
value: 61.791044776119406 |
|
- type: ap |
|
value: 25.829130082463124 |
|
- type: f1 |
|
value: 56.00432262887535 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/amazon_polarity |
|
name: MTEB AmazonPolarityClassification |
|
config: default |
|
split: test |
|
revision: e2d317d38cd51312af73b3d32a06d1a08b442046 |
|
metrics: |
|
- type: accuracy |
|
value: 62.36077499999999 |
|
- type: ap |
|
value: 57.68938427410222 |
|
- type: f1 |
|
value: 62.247666843818436 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/amazon_reviews_multi |
|
name: MTEB AmazonReviewsClassification (en) |
|
config: en |
|
split: test |
|
revision: 1399c76144fd37290681b995c656ef9b2e06e26d |
|
metrics: |
|
- type: accuracy |
|
value: 29.59 |
|
- type: f1 |
|
value: 29.241975951560622 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: arguana |
|
name: MTEB ArguAna |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 25.249 |
|
- type: map_at_10 |
|
value: 40.196 |
|
- type: map_at_100 |
|
value: 41.336 |
|
- type: map_at_1000 |
|
value: 41.343 |
|
- type: map_at_3 |
|
value: 34.934 |
|
- type: map_at_5 |
|
value: 37.871 |
|
- type: mrr_at_1 |
|
value: 26.031 |
|
- type: mrr_at_10 |
|
value: 40.488 |
|
- type: mrr_at_100 |
|
value: 41.628 |
|
- type: mrr_at_1000 |
|
value: 41.634 |
|
- type: mrr_at_3 |
|
value: 35.171 |
|
- type: mrr_at_5 |
|
value: 38.126 |
|
- type: ndcg_at_1 |
|
value: 25.249 |
|
- type: ndcg_at_10 |
|
value: 49.11 |
|
- type: ndcg_at_100 |
|
value: 53.827999999999996 |
|
- type: ndcg_at_1000 |
|
value: 53.993 |
|
- type: ndcg_at_3 |
|
value: 38.175 |
|
- type: ndcg_at_5 |
|
value: 43.488 |
|
- type: precision_at_1 |
|
value: 25.249 |
|
- type: precision_at_10 |
|
value: 7.788 |
|
- type: precision_at_100 |
|
value: 0.9820000000000001 |
|
- type: precision_at_1000 |
|
value: 0.1 |
|
- type: precision_at_3 |
|
value: 15.861 |
|
- type: precision_at_5 |
|
value: 12.105 |
|
- type: recall_at_1 |
|
value: 25.249 |
|
- type: recall_at_10 |
|
value: 77.881 |
|
- type: recall_at_100 |
|
value: 98.222 |
|
- type: recall_at_1000 |
|
value: 99.502 |
|
- type: recall_at_3 |
|
value: 47.582 |
|
- type: recall_at_5 |
|
value: 60.526 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: mteb/arxiv-clustering-p2p |
|
name: MTEB ArxivClusteringP2P |
|
config: default |
|
split: test |
|
revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d |
|
metrics: |
|
- type: v_measure |
|
value: 37.75242616816114 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: mteb/arxiv-clustering-s2s |
|
name: MTEB ArxivClusteringS2S |
|
config: default |
|
split: test |
|
revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53 |
|
metrics: |
|
- type: v_measure |
|
value: 27.70031808300247 |
|
- task: |
|
type: Reranking |
|
dataset: |
|
type: mteb/askubuntudupquestions-reranking |
|
name: MTEB AskUbuntuDupQuestions |
|
config: default |
|
split: test |
|
revision: 2000358ca161889fa9c082cb41daa8dcfb161a54 |
|
metrics: |
|
- type: map |
|
value: 63.09199068762668 |
|
- type: mrr |
|
value: 76.08055225783757 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: mteb/biosses-sts |
|
name: MTEB BIOSSES |
|
config: default |
|
split: test |
|
revision: d3fb88f8f02e40887cd149695127462bbcf29b4a |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 80.83007234777145 |
|
- type: cos_sim_spearman |
|
value: 79.76446808992547 |
|
- type: euclidean_pearson |
|
value: 80.24418669808917 |
|
- type: euclidean_spearman |
|
value: 79.76446808992547 |
|
- type: manhattan_pearson |
|
value: 79.58896133042379 |
|
- type: manhattan_spearman |
|
value: 78.9614377441415 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/banking77 |
|
name: MTEB Banking77Classification |
|
config: default |
|
split: test |
|
revision: 0fd18e25b25c072e09e0d92ab615fda904d66300 |
|
metrics: |
|
- type: accuracy |
|
value: 78.6038961038961 |
|
- type: f1 |
|
value: 77.95572823168757 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: mteb/biorxiv-clustering-p2p |
|
name: MTEB BiorxivClusteringP2P |
|
config: default |
|
split: test |
|
revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40 |
|
metrics: |
|
- type: v_measure |
|
value: 30.240388191413935 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: mteb/biorxiv-clustering-s2s |
|
name: MTEB BiorxivClusteringS2S |
|
config: default |
|
split: test |
|
revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908 |
|
metrics: |
|
- type: v_measure |
|
value: 22.670413424756212 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: BeIR/cqadupstack |
|
name: MTEB CQADupstackAndroidRetrieval |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 32.694 |
|
- type: map_at_10 |
|
value: 43.811 |
|
- type: map_at_100 |
|
value: 45.274 |
|
- type: map_at_1000 |
|
value: 45.393 |
|
- type: map_at_3 |
|
value: 40.043 |
|
- type: map_at_5 |
|
value: 41.983 |
|
- type: mrr_at_1 |
|
value: 39.628 |
|
- type: mrr_at_10 |
|
value: 49.748 |
|
- type: mrr_at_100 |
|
value: 50.356 |
|
- type: mrr_at_1000 |
|
value: 50.39900000000001 |
|
- type: mrr_at_3 |
|
value: 46.924 |
|
- type: mrr_at_5 |
|
value: 48.598 |
|
- type: ndcg_at_1 |
|
value: 39.628 |
|
- type: ndcg_at_10 |
|
value: 50.39 |
|
- type: ndcg_at_100 |
|
value: 55.489 |
|
- type: ndcg_at_1000 |
|
value: 57.291000000000004 |
|
- type: ndcg_at_3 |
|
value: 44.849 |
|
- type: ndcg_at_5 |
|
value: 47.195 |
|
- type: precision_at_1 |
|
value: 39.628 |
|
- type: precision_at_10 |
|
value: 9.714 |
|
- type: precision_at_100 |
|
value: 1.591 |
|
- type: precision_at_1000 |
|
value: 0.2 |
|
- type: precision_at_3 |
|
value: 21.507 |
|
- type: precision_at_5 |
|
value: 15.393 |
|
- type: recall_at_1 |
|
value: 32.694 |
|
- type: recall_at_10 |
|
value: 63.031000000000006 |
|
- type: recall_at_100 |
|
value: 84.49 |
|
- type: recall_at_1000 |
|
value: 96.148 |
|
- type: recall_at_3 |
|
value: 46.851 |
|
- type: recall_at_5 |
|
value: 53.64 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: BeIR/cqadupstack |
|
name: MTEB CQADupstackEnglishRetrieval |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 28.183000000000003 |
|
- type: map_at_10 |
|
value: 38.796 |
|
- type: map_at_100 |
|
value: 40.117000000000004 |
|
- type: map_at_1000 |
|
value: 40.251 |
|
- type: map_at_3 |
|
value: 35.713 |
|
- type: map_at_5 |
|
value: 37.446 |
|
- type: mrr_at_1 |
|
value: 35.605 |
|
- type: mrr_at_10 |
|
value: 44.824000000000005 |
|
- type: mrr_at_100 |
|
value: 45.544000000000004 |
|
- type: mrr_at_1000 |
|
value: 45.59 |
|
- type: mrr_at_3 |
|
value: 42.452 |
|
- type: mrr_at_5 |
|
value: 43.891999999999996 |
|
- type: ndcg_at_1 |
|
value: 35.605 |
|
- type: ndcg_at_10 |
|
value: 44.857 |
|
- type: ndcg_at_100 |
|
value: 49.68 |
|
- type: ndcg_at_1000 |
|
value: 51.841 |
|
- type: ndcg_at_3 |
|
value: 40.445 |
|
- type: ndcg_at_5 |
|
value: 42.535000000000004 |
|
- type: precision_at_1 |
|
value: 35.605 |
|
- type: precision_at_10 |
|
value: 8.624 |
|
- type: precision_at_100 |
|
value: 1.438 |
|
- type: precision_at_1000 |
|
value: 0.193 |
|
- type: precision_at_3 |
|
value: 19.808999999999997 |
|
- type: precision_at_5 |
|
value: 14.191 |
|
- type: recall_at_1 |
|
value: 28.183000000000003 |
|
- type: recall_at_10 |
|
value: 55.742000000000004 |
|
- type: recall_at_100 |
|
value: 76.416 |
|
- type: recall_at_1000 |
|
value: 90.20899999999999 |
|
- type: recall_at_3 |
|
value: 42.488 |
|
- type: recall_at_5 |
|
value: 48.431999999999995 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: BeIR/cqadupstack |
|
name: MTEB CQADupstackGamingRetrieval |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 36.156 |
|
- type: map_at_10 |
|
value: 47.677 |
|
- type: map_at_100 |
|
value: 48.699999999999996 |
|
- type: map_at_1000 |
|
value: 48.756 |
|
- type: map_at_3 |
|
value: 44.467 |
|
- type: map_at_5 |
|
value: 46.132 |
|
- type: mrr_at_1 |
|
value: 41.567 |
|
- type: mrr_at_10 |
|
value: 51.06699999999999 |
|
- type: mrr_at_100 |
|
value: 51.800000000000004 |
|
- type: mrr_at_1000 |
|
value: 51.827999999999996 |
|
- type: mrr_at_3 |
|
value: 48.620999999999995 |
|
- type: mrr_at_5 |
|
value: 50.013 |
|
- type: ndcg_at_1 |
|
value: 41.567 |
|
- type: ndcg_at_10 |
|
value: 53.418 |
|
- type: ndcg_at_100 |
|
value: 57.743 |
|
- type: ndcg_at_1000 |
|
value: 58.940000000000005 |
|
- type: ndcg_at_3 |
|
value: 47.923 |
|
- type: ndcg_at_5 |
|
value: 50.352 |
|
- type: precision_at_1 |
|
value: 41.567 |
|
- type: precision_at_10 |
|
value: 8.74 |
|
- type: precision_at_100 |
|
value: 1.1809999999999998 |
|
- type: precision_at_1000 |
|
value: 0.133 |
|
- type: precision_at_3 |
|
value: 21.337999999999997 |
|
- type: precision_at_5 |
|
value: 14.646 |
|
- type: recall_at_1 |
|
value: 36.156 |
|
- type: recall_at_10 |
|
value: 67.084 |
|
- type: recall_at_100 |
|
value: 86.299 |
|
- type: recall_at_1000 |
|
value: 94.82000000000001 |
|
- type: recall_at_3 |
|
value: 52.209 |
|
- type: recall_at_5 |
|
value: 58.175 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: BeIR/cqadupstack |
|
name: MTEB CQADupstackGisRetrieval |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 23.513 |
|
- type: map_at_10 |
|
value: 32.699 |
|
- type: map_at_100 |
|
value: 33.788000000000004 |
|
- type: map_at_1000 |
|
value: 33.878 |
|
- type: map_at_3 |
|
value: 30.044999999999998 |
|
- type: map_at_5 |
|
value: 31.506 |
|
- type: mrr_at_1 |
|
value: 25.311 |
|
- type: mrr_at_10 |
|
value: 34.457 |
|
- type: mrr_at_100 |
|
value: 35.443999999999996 |
|
- type: mrr_at_1000 |
|
value: 35.504999999999995 |
|
- type: mrr_at_3 |
|
value: 31.902 |
|
- type: mrr_at_5 |
|
value: 33.36 |
|
- type: ndcg_at_1 |
|
value: 25.311 |
|
- type: ndcg_at_10 |
|
value: 37.929 |
|
- type: ndcg_at_100 |
|
value: 43.1 |
|
- type: ndcg_at_1000 |
|
value: 45.275999999999996 |
|
- type: ndcg_at_3 |
|
value: 32.745999999999995 |
|
- type: ndcg_at_5 |
|
value: 35.235 |
|
- type: precision_at_1 |
|
value: 25.311 |
|
- type: precision_at_10 |
|
value: 6.034 |
|
- type: precision_at_100 |
|
value: 0.8959999999999999 |
|
- type: precision_at_1000 |
|
value: 0.11299999999999999 |
|
- type: precision_at_3 |
|
value: 14.237 |
|
- type: precision_at_5 |
|
value: 10.034 |
|
- type: recall_at_1 |
|
value: 23.513 |
|
- type: recall_at_10 |
|
value: 52.312999999999995 |
|
- type: recall_at_100 |
|
value: 75.762 |
|
- type: recall_at_1000 |
|
value: 91.85799999999999 |
|
- type: recall_at_3 |
|
value: 38.222 |
|
- type: recall_at_5 |
|
value: 44.316 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: BeIR/cqadupstack |
|
name: MTEB CQADupstackMathematicaRetrieval |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 16.333000000000002 |
|
- type: map_at_10 |
|
value: 24.605 |
|
- type: map_at_100 |
|
value: 25.924000000000003 |
|
- type: map_at_1000 |
|
value: 26.039 |
|
- type: map_at_3 |
|
value: 21.907 |
|
- type: map_at_5 |
|
value: 23.294999999999998 |
|
- type: mrr_at_1 |
|
value: 20.647 |
|
- type: mrr_at_10 |
|
value: 29.442 |
|
- type: mrr_at_100 |
|
value: 30.54 |
|
- type: mrr_at_1000 |
|
value: 30.601 |
|
- type: mrr_at_3 |
|
value: 26.802999999999997 |
|
- type: mrr_at_5 |
|
value: 28.147 |
|
- type: ndcg_at_1 |
|
value: 20.647 |
|
- type: ndcg_at_10 |
|
value: 30.171999999999997 |
|
- type: ndcg_at_100 |
|
value: 36.466 |
|
- type: ndcg_at_1000 |
|
value: 39.095 |
|
- type: ndcg_at_3 |
|
value: 25.134 |
|
- type: ndcg_at_5 |
|
value: 27.211999999999996 |
|
- type: precision_at_1 |
|
value: 20.647 |
|
- type: precision_at_10 |
|
value: 5.659 |
|
- type: precision_at_100 |
|
value: 1.012 |
|
- type: precision_at_1000 |
|
value: 0.13899999999999998 |
|
- type: precision_at_3 |
|
value: 12.148 |
|
- type: precision_at_5 |
|
value: 8.881 |
|
- type: recall_at_1 |
|
value: 16.333000000000002 |
|
- type: recall_at_10 |
|
value: 42.785000000000004 |
|
- type: recall_at_100 |
|
value: 70.282 |
|
- type: recall_at_1000 |
|
value: 88.539 |
|
- type: recall_at_3 |
|
value: 28.307 |
|
- type: recall_at_5 |
|
value: 33.751 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: BeIR/cqadupstack |
|
name: MTEB CQADupstackPhysicsRetrieval |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 26.821 |
|
- type: map_at_10 |
|
value: 37.188 |
|
- type: map_at_100 |
|
value: 38.516 |
|
- type: map_at_1000 |
|
value: 38.635000000000005 |
|
- type: map_at_3 |
|
value: 33.821 |
|
- type: map_at_5 |
|
value: 35.646 |
|
- type: mrr_at_1 |
|
value: 33.109 |
|
- type: mrr_at_10 |
|
value: 43.003 |
|
- type: mrr_at_100 |
|
value: 43.849 |
|
- type: mrr_at_1000 |
|
value: 43.889 |
|
- type: mrr_at_3 |
|
value: 40.263 |
|
- type: mrr_at_5 |
|
value: 41.957 |
|
- type: ndcg_at_1 |
|
value: 33.109 |
|
- type: ndcg_at_10 |
|
value: 43.556 |
|
- type: ndcg_at_100 |
|
value: 49.197 |
|
- type: ndcg_at_1000 |
|
value: 51.269 |
|
- type: ndcg_at_3 |
|
value: 38.01 |
|
- type: ndcg_at_5 |
|
value: 40.647 |
|
- type: precision_at_1 |
|
value: 33.109 |
|
- type: precision_at_10 |
|
value: 8.085 |
|
- type: precision_at_100 |
|
value: 1.286 |
|
- type: precision_at_1000 |
|
value: 0.166 |
|
- type: precision_at_3 |
|
value: 18.191 |
|
- type: precision_at_5 |
|
value: 13.050999999999998 |
|
- type: recall_at_1 |
|
value: 26.821 |
|
- type: recall_at_10 |
|
value: 56.818000000000005 |
|
- type: recall_at_100 |
|
value: 80.63 |
|
- type: recall_at_1000 |
|
value: 94.042 |
|
- type: recall_at_3 |
|
value: 41.266000000000005 |
|
- type: recall_at_5 |
|
value: 48.087999999999994 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: BeIR/cqadupstack |
|
name: MTEB CQADupstackProgrammersRetrieval |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 22.169 |
|
- type: map_at_10 |
|
value: 31.682 |
|
- type: map_at_100 |
|
value: 32.988 |
|
- type: map_at_1000 |
|
value: 33.097 |
|
- type: map_at_3 |
|
value: 28.708 |
|
- type: map_at_5 |
|
value: 30.319000000000003 |
|
- type: mrr_at_1 |
|
value: 27.854 |
|
- type: mrr_at_10 |
|
value: 36.814 |
|
- type: mrr_at_100 |
|
value: 37.741 |
|
- type: mrr_at_1000 |
|
value: 37.798 |
|
- type: mrr_at_3 |
|
value: 34.418 |
|
- type: mrr_at_5 |
|
value: 35.742000000000004 |
|
- type: ndcg_at_1 |
|
value: 27.854 |
|
- type: ndcg_at_10 |
|
value: 37.388 |
|
- type: ndcg_at_100 |
|
value: 43.342999999999996 |
|
- type: ndcg_at_1000 |
|
value: 45.829 |
|
- type: ndcg_at_3 |
|
value: 32.512 |
|
- type: ndcg_at_5 |
|
value: 34.613 |
|
- type: precision_at_1 |
|
value: 27.854 |
|
- type: precision_at_10 |
|
value: 7.031999999999999 |
|
- type: precision_at_100 |
|
value: 1.18 |
|
- type: precision_at_1000 |
|
value: 0.158 |
|
- type: precision_at_3 |
|
value: 15.753 |
|
- type: precision_at_5 |
|
value: 11.301 |
|
- type: recall_at_1 |
|
value: 22.169 |
|
- type: recall_at_10 |
|
value: 49.44 |
|
- type: recall_at_100 |
|
value: 75.644 |
|
- type: recall_at_1000 |
|
value: 92.919 |
|
- type: recall_at_3 |
|
value: 35.528999999999996 |
|
- type: recall_at_5 |
|
value: 41.271 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: BeIR/cqadupstack |
|
name: MTEB CQADupstackRetrieval |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 24.20158333333334 |
|
- type: map_at_10 |
|
value: 33.509 |
|
- type: map_at_100 |
|
value: 34.76525 |
|
- type: map_at_1000 |
|
value: 34.885999999999996 |
|
- type: map_at_3 |
|
value: 30.594333333333335 |
|
- type: map_at_5 |
|
value: 32.160666666666664 |
|
- type: mrr_at_1 |
|
value: 28.803833333333333 |
|
- type: mrr_at_10 |
|
value: 37.61358333333333 |
|
- type: mrr_at_100 |
|
value: 38.5105 |
|
- type: mrr_at_1000 |
|
value: 38.56841666666667 |
|
- type: mrr_at_3 |
|
value: 35.090666666666664 |
|
- type: mrr_at_5 |
|
value: 36.49575 |
|
- type: ndcg_at_1 |
|
value: 28.803833333333333 |
|
- type: ndcg_at_10 |
|
value: 39.038333333333334 |
|
- type: ndcg_at_100 |
|
value: 44.49175 |
|
- type: ndcg_at_1000 |
|
value: 46.835499999999996 |
|
- type: ndcg_at_3 |
|
value: 34.011916666666664 |
|
- type: ndcg_at_5 |
|
value: 36.267 |
|
- type: precision_at_1 |
|
value: 28.803833333333333 |
|
- type: precision_at_10 |
|
value: 6.974583333333334 |
|
- type: precision_at_100 |
|
value: 1.1565 |
|
- type: precision_at_1000 |
|
value: 0.15533333333333332 |
|
- type: precision_at_3 |
|
value: 15.78025 |
|
- type: precision_at_5 |
|
value: 11.279583333333333 |
|
- type: recall_at_1 |
|
value: 24.20158333333334 |
|
- type: recall_at_10 |
|
value: 51.408 |
|
- type: recall_at_100 |
|
value: 75.36958333333334 |
|
- type: recall_at_1000 |
|
value: 91.5765 |
|
- type: recall_at_3 |
|
value: 37.334500000000006 |
|
- type: recall_at_5 |
|
value: 43.14666666666667 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: BeIR/cqadupstack |
|
name: MTEB CQADupstackStatsRetrieval |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 21.394 |
|
- type: map_at_10 |
|
value: 28.807 |
|
- type: map_at_100 |
|
value: 29.851 |
|
- type: map_at_1000 |
|
value: 29.959999999999997 |
|
- type: map_at_3 |
|
value: 26.694000000000003 |
|
- type: map_at_5 |
|
value: 27.805999999999997 |
|
- type: mrr_at_1 |
|
value: 23.773 |
|
- type: mrr_at_10 |
|
value: 30.895 |
|
- type: mrr_at_100 |
|
value: 31.894 |
|
- type: mrr_at_1000 |
|
value: 31.971 |
|
- type: mrr_at_3 |
|
value: 28.988000000000003 |
|
- type: mrr_at_5 |
|
value: 29.908 |
|
- type: ndcg_at_1 |
|
value: 23.773 |
|
- type: ndcg_at_10 |
|
value: 32.976 |
|
- type: ndcg_at_100 |
|
value: 38.109 |
|
- type: ndcg_at_1000 |
|
value: 40.797 |
|
- type: ndcg_at_3 |
|
value: 28.993999999999996 |
|
- type: ndcg_at_5 |
|
value: 30.659999999999997 |
|
- type: precision_at_1 |
|
value: 23.773 |
|
- type: precision_at_10 |
|
value: 5.2299999999999995 |
|
- type: precision_at_100 |
|
value: 0.857 |
|
- type: precision_at_1000 |
|
value: 0.117 |
|
- type: precision_at_3 |
|
value: 12.73 |
|
- type: precision_at_5 |
|
value: 8.741999999999999 |
|
- type: recall_at_1 |
|
value: 21.394 |
|
- type: recall_at_10 |
|
value: 43.75 |
|
- type: recall_at_100 |
|
value: 66.765 |
|
- type: recall_at_1000 |
|
value: 86.483 |
|
- type: recall_at_3 |
|
value: 32.542 |
|
- type: recall_at_5 |
|
value: 36.689 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: BeIR/cqadupstack |
|
name: MTEB CQADupstackTexRetrieval |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 16.266 |
|
- type: map_at_10 |
|
value: 23.639 |
|
- type: map_at_100 |
|
value: 24.814 |
|
- type: map_at_1000 |
|
value: 24.948 |
|
- type: map_at_3 |
|
value: 21.401999999999997 |
|
- type: map_at_5 |
|
value: 22.581 |
|
- type: mrr_at_1 |
|
value: 19.718 |
|
- type: mrr_at_10 |
|
value: 27.276 |
|
- type: mrr_at_100 |
|
value: 28.252 |
|
- type: mrr_at_1000 |
|
value: 28.33 |
|
- type: mrr_at_3 |
|
value: 25.086000000000002 |
|
- type: mrr_at_5 |
|
value: 26.304 |
|
- type: ndcg_at_1 |
|
value: 19.718 |
|
- type: ndcg_at_10 |
|
value: 28.254 |
|
- type: ndcg_at_100 |
|
value: 34.022999999999996 |
|
- type: ndcg_at_1000 |
|
value: 37.031 |
|
- type: ndcg_at_3 |
|
value: 24.206 |
|
- type: ndcg_at_5 |
|
value: 26.009 |
|
- type: precision_at_1 |
|
value: 19.718 |
|
- type: precision_at_10 |
|
value: 5.189 |
|
- type: precision_at_100 |
|
value: 0.9690000000000001 |
|
- type: precision_at_1000 |
|
value: 0.14200000000000002 |
|
- type: precision_at_3 |
|
value: 11.551 |
|
- type: precision_at_5 |
|
value: 8.362 |
|
- type: recall_at_1 |
|
value: 16.266 |
|
- type: recall_at_10 |
|
value: 38.550000000000004 |
|
- type: recall_at_100 |
|
value: 64.63499999999999 |
|
- type: recall_at_1000 |
|
value: 86.059 |
|
- type: recall_at_3 |
|
value: 27.156000000000002 |
|
- type: recall_at_5 |
|
value: 31.829 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: BeIR/cqadupstack |
|
name: MTEB CQADupstackUnixRetrieval |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 26.124000000000002 |
|
- type: map_at_10 |
|
value: 35.099000000000004 |
|
- type: map_at_100 |
|
value: 36.269 |
|
- type: map_at_1000 |
|
value: 36.388999999999996 |
|
- type: map_at_3 |
|
value: 32.017 |
|
- type: map_at_5 |
|
value: 33.614 |
|
- type: mrr_at_1 |
|
value: 31.25 |
|
- type: mrr_at_10 |
|
value: 39.269999999999996 |
|
- type: mrr_at_100 |
|
value: 40.134 |
|
- type: mrr_at_1000 |
|
value: 40.197 |
|
- type: mrr_at_3 |
|
value: 36.536 |
|
- type: mrr_at_5 |
|
value: 37.842 |
|
- type: ndcg_at_1 |
|
value: 31.25 |
|
- type: ndcg_at_10 |
|
value: 40.643 |
|
- type: ndcg_at_100 |
|
value: 45.967999999999996 |
|
- type: ndcg_at_1000 |
|
value: 48.455999999999996 |
|
- type: ndcg_at_3 |
|
value: 34.954 |
|
- type: ndcg_at_5 |
|
value: 37.273 |
|
- type: precision_at_1 |
|
value: 31.25 |
|
- type: precision_at_10 |
|
value: 6.894 |
|
- type: precision_at_100 |
|
value: 1.086 |
|
- type: precision_at_1000 |
|
value: 0.14200000000000002 |
|
- type: precision_at_3 |
|
value: 15.672 |
|
- type: precision_at_5 |
|
value: 11.082 |
|
- type: recall_at_1 |
|
value: 26.124000000000002 |
|
- type: recall_at_10 |
|
value: 53.730999999999995 |
|
- type: recall_at_100 |
|
value: 76.779 |
|
- type: recall_at_1000 |
|
value: 93.908 |
|
- type: recall_at_3 |
|
value: 37.869 |
|
- type: recall_at_5 |
|
value: 43.822 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: BeIR/cqadupstack |
|
name: MTEB CQADupstackWebmastersRetrieval |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 21.776 |
|
- type: map_at_10 |
|
value: 31.384 |
|
- type: map_at_100 |
|
value: 33.108 |
|
- type: map_at_1000 |
|
value: 33.339 |
|
- type: map_at_3 |
|
value: 28.269 |
|
- type: map_at_5 |
|
value: 30.108 |
|
- type: mrr_at_1 |
|
value: 26.482 |
|
- type: mrr_at_10 |
|
value: 35.876000000000005 |
|
- type: mrr_at_100 |
|
value: 36.887 |
|
- type: mrr_at_1000 |
|
value: 36.949 |
|
- type: mrr_at_3 |
|
value: 32.971000000000004 |
|
- type: mrr_at_5 |
|
value: 34.601 |
|
- type: ndcg_at_1 |
|
value: 26.482 |
|
- type: ndcg_at_10 |
|
value: 37.403999999999996 |
|
- type: ndcg_at_100 |
|
value: 43.722 |
|
- type: ndcg_at_1000 |
|
value: 46.417 |
|
- type: ndcg_at_3 |
|
value: 32.149 |
|
- type: ndcg_at_5 |
|
value: 34.818 |
|
- type: precision_at_1 |
|
value: 26.482 |
|
- type: precision_at_10 |
|
value: 7.411 |
|
- type: precision_at_100 |
|
value: 1.532 |
|
- type: precision_at_1000 |
|
value: 0.24 |
|
- type: precision_at_3 |
|
value: 15.152 |
|
- type: precision_at_5 |
|
value: 11.501999999999999 |
|
- type: recall_at_1 |
|
value: 21.776 |
|
- type: recall_at_10 |
|
value: 49.333 |
|
- type: recall_at_100 |
|
value: 76.753 |
|
- type: recall_at_1000 |
|
value: 93.762 |
|
- type: recall_at_3 |
|
value: 35.329 |
|
- type: recall_at_5 |
|
value: 41.82 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: BeIR/cqadupstack |
|
name: MTEB CQADupstackWordpressRetrieval |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 18.990000000000002 |
|
- type: map_at_10 |
|
value: 26.721 |
|
- type: map_at_100 |
|
value: 27.833999999999996 |
|
- type: map_at_1000 |
|
value: 27.947 |
|
- type: map_at_3 |
|
value: 24.046 |
|
- type: map_at_5 |
|
value: 25.491999999999997 |
|
- type: mrr_at_1 |
|
value: 20.702 |
|
- type: mrr_at_10 |
|
value: 28.691 |
|
- type: mrr_at_100 |
|
value: 29.685 |
|
- type: mrr_at_1000 |
|
value: 29.764000000000003 |
|
- type: mrr_at_3 |
|
value: 26.124000000000002 |
|
- type: mrr_at_5 |
|
value: 27.584999999999997 |
|
- type: ndcg_at_1 |
|
value: 20.702 |
|
- type: ndcg_at_10 |
|
value: 31.473000000000003 |
|
- type: ndcg_at_100 |
|
value: 37.061 |
|
- type: ndcg_at_1000 |
|
value: 39.784000000000006 |
|
- type: ndcg_at_3 |
|
value: 26.221 |
|
- type: ndcg_at_5 |
|
value: 28.655 |
|
- type: precision_at_1 |
|
value: 20.702 |
|
- type: precision_at_10 |
|
value: 5.083 |
|
- type: precision_at_100 |
|
value: 0.8500000000000001 |
|
- type: precision_at_1000 |
|
value: 0.121 |
|
- type: precision_at_3 |
|
value: 11.275 |
|
- type: precision_at_5 |
|
value: 8.17 |
|
- type: recall_at_1 |
|
value: 18.990000000000002 |
|
- type: recall_at_10 |
|
value: 44.318999999999996 |
|
- type: recall_at_100 |
|
value: 69.98 |
|
- type: recall_at_1000 |
|
value: 90.171 |
|
- type: recall_at_3 |
|
value: 30.246000000000002 |
|
- type: recall_at_5 |
|
value: 35.927 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: climate-fever |
|
name: MTEB ClimateFEVER |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 9.584 |
|
- type: map_at_10 |
|
value: 16.148 |
|
- type: map_at_100 |
|
value: 17.727 |
|
- type: map_at_1000 |
|
value: 17.913999999999998 |
|
- type: map_at_3 |
|
value: 13.456000000000001 |
|
- type: map_at_5 |
|
value: 14.841999999999999 |
|
- type: mrr_at_1 |
|
value: 21.564 |
|
- type: mrr_at_10 |
|
value: 31.579 |
|
- type: mrr_at_100 |
|
value: 32.586999999999996 |
|
- type: mrr_at_1000 |
|
value: 32.638 |
|
- type: mrr_at_3 |
|
value: 28.294999999999998 |
|
- type: mrr_at_5 |
|
value: 30.064 |
|
- type: ndcg_at_1 |
|
value: 21.564 |
|
- type: ndcg_at_10 |
|
value: 23.294999999999998 |
|
- type: ndcg_at_100 |
|
value: 29.997 |
|
- type: ndcg_at_1000 |
|
value: 33.517 |
|
- type: ndcg_at_3 |
|
value: 18.759 |
|
- type: ndcg_at_5 |
|
value: 20.324 |
|
- type: precision_at_1 |
|
value: 21.564 |
|
- type: precision_at_10 |
|
value: 7.362 |
|
- type: precision_at_100 |
|
value: 1.451 |
|
- type: precision_at_1000 |
|
value: 0.21 |
|
- type: precision_at_3 |
|
value: 13.919999999999998 |
|
- type: precision_at_5 |
|
value: 10.879 |
|
- type: recall_at_1 |
|
value: 9.584 |
|
- type: recall_at_10 |
|
value: 28.508 |
|
- type: recall_at_100 |
|
value: 51.873999999999995 |
|
- type: recall_at_1000 |
|
value: 71.773 |
|
- type: recall_at_3 |
|
value: 17.329 |
|
- type: recall_at_5 |
|
value: 21.823 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: dbpedia-entity |
|
name: MTEB DBPedia |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 7.034 |
|
- type: map_at_10 |
|
value: 14.664 |
|
- type: map_at_100 |
|
value: 19.652 |
|
- type: map_at_1000 |
|
value: 20.701 |
|
- type: map_at_3 |
|
value: 10.626 |
|
- type: map_at_5 |
|
value: 12.334 |
|
- type: mrr_at_1 |
|
value: 54.0 |
|
- type: mrr_at_10 |
|
value: 63.132 |
|
- type: mrr_at_100 |
|
value: 63.639 |
|
- type: mrr_at_1000 |
|
value: 63.663000000000004 |
|
- type: mrr_at_3 |
|
value: 61.083 |
|
- type: mrr_at_5 |
|
value: 62.483 |
|
- type: ndcg_at_1 |
|
value: 42.875 |
|
- type: ndcg_at_10 |
|
value: 32.04 |
|
- type: ndcg_at_100 |
|
value: 35.157 |
|
- type: ndcg_at_1000 |
|
value: 41.4 |
|
- type: ndcg_at_3 |
|
value: 35.652 |
|
- type: ndcg_at_5 |
|
value: 33.617000000000004 |
|
- type: precision_at_1 |
|
value: 54.0 |
|
- type: precision_at_10 |
|
value: 25.55 |
|
- type: precision_at_100 |
|
value: 7.5600000000000005 |
|
- type: precision_at_1000 |
|
value: 1.577 |
|
- type: precision_at_3 |
|
value: 38.833 |
|
- type: precision_at_5 |
|
value: 33.15 |
|
- type: recall_at_1 |
|
value: 7.034 |
|
- type: recall_at_10 |
|
value: 19.627 |
|
- type: recall_at_100 |
|
value: 40.528 |
|
- type: recall_at_1000 |
|
value: 60.789 |
|
- type: recall_at_3 |
|
value: 11.833 |
|
- type: recall_at_5 |
|
value: 14.804 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/emotion |
|
name: MTEB EmotionClassification |
|
config: default |
|
split: test |
|
revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37 |
|
metrics: |
|
- type: accuracy |
|
value: 39.6 |
|
- type: f1 |
|
value: 35.3770765501984 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: fever |
|
name: MTEB FEVER |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 35.098 |
|
- type: map_at_10 |
|
value: 46.437 |
|
- type: map_at_100 |
|
value: 47.156 |
|
- type: map_at_1000 |
|
value: 47.193000000000005 |
|
- type: map_at_3 |
|
value: 43.702000000000005 |
|
- type: map_at_5 |
|
value: 45.326 |
|
- type: mrr_at_1 |
|
value: 37.774 |
|
- type: mrr_at_10 |
|
value: 49.512 |
|
- type: mrr_at_100 |
|
value: 50.196 |
|
- type: mrr_at_1000 |
|
value: 50.224000000000004 |
|
- type: mrr_at_3 |
|
value: 46.747 |
|
- type: mrr_at_5 |
|
value: 48.415 |
|
- type: ndcg_at_1 |
|
value: 37.774 |
|
- type: ndcg_at_10 |
|
value: 52.629000000000005 |
|
- type: ndcg_at_100 |
|
value: 55.995 |
|
- type: ndcg_at_1000 |
|
value: 56.962999999999994 |
|
- type: ndcg_at_3 |
|
value: 47.188 |
|
- type: ndcg_at_5 |
|
value: 50.019000000000005 |
|
- type: precision_at_1 |
|
value: 37.774 |
|
- type: precision_at_10 |
|
value: 7.541 |
|
- type: precision_at_100 |
|
value: 0.931 |
|
- type: precision_at_1000 |
|
value: 0.10300000000000001 |
|
- type: precision_at_3 |
|
value: 19.572 |
|
- type: precision_at_5 |
|
value: 13.288 |
|
- type: recall_at_1 |
|
value: 35.098 |
|
- type: recall_at_10 |
|
value: 68.818 |
|
- type: recall_at_100 |
|
value: 84.004 |
|
- type: recall_at_1000 |
|
value: 91.36800000000001 |
|
- type: recall_at_3 |
|
value: 54.176 |
|
- type: recall_at_5 |
|
value: 60.968999999999994 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: fiqa |
|
name: MTEB FiQA2018 |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 17.982 |
|
- type: map_at_10 |
|
value: 28.994999999999997 |
|
- type: map_at_100 |
|
value: 30.868000000000002 |
|
- type: map_at_1000 |
|
value: 31.045 |
|
- type: map_at_3 |
|
value: 25.081999999999997 |
|
- type: map_at_5 |
|
value: 27.303 |
|
- type: mrr_at_1 |
|
value: 35.031 |
|
- type: mrr_at_10 |
|
value: 43.537 |
|
- type: mrr_at_100 |
|
value: 44.422 |
|
- type: mrr_at_1000 |
|
value: 44.471 |
|
- type: mrr_at_3 |
|
value: 41.024 |
|
- type: mrr_at_5 |
|
value: 42.42 |
|
- type: ndcg_at_1 |
|
value: 35.031 |
|
- type: ndcg_at_10 |
|
value: 36.346000000000004 |
|
- type: ndcg_at_100 |
|
value: 43.275000000000006 |
|
- type: ndcg_at_1000 |
|
value: 46.577 |
|
- type: ndcg_at_3 |
|
value: 32.42 |
|
- type: ndcg_at_5 |
|
value: 33.841 |
|
- type: precision_at_1 |
|
value: 35.031 |
|
- type: precision_at_10 |
|
value: 10.231 |
|
- type: precision_at_100 |
|
value: 1.728 |
|
- type: precision_at_1000 |
|
value: 0.231 |
|
- type: precision_at_3 |
|
value: 21.553 |
|
- type: precision_at_5 |
|
value: 16.204 |
|
- type: recall_at_1 |
|
value: 17.982 |
|
- type: recall_at_10 |
|
value: 43.169000000000004 |
|
- type: recall_at_100 |
|
value: 68.812 |
|
- type: recall_at_1000 |
|
value: 89.008 |
|
- type: recall_at_3 |
|
value: 29.309 |
|
- type: recall_at_5 |
|
value: 35.514 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: hotpotqa |
|
name: MTEB HotpotQA |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 27.387 |
|
- type: map_at_10 |
|
value: 36.931000000000004 |
|
- type: map_at_100 |
|
value: 37.734 |
|
- type: map_at_1000 |
|
value: 37.818000000000005 |
|
- type: map_at_3 |
|
value: 34.691 |
|
- type: map_at_5 |
|
value: 36.016999999999996 |
|
- type: mrr_at_1 |
|
value: 54.774 |
|
- type: mrr_at_10 |
|
value: 62.133 |
|
- type: mrr_at_100 |
|
value: 62.587 |
|
- type: mrr_at_1000 |
|
value: 62.61600000000001 |
|
- type: mrr_at_3 |
|
value: 60.49099999999999 |
|
- type: mrr_at_5 |
|
value: 61.480999999999995 |
|
- type: ndcg_at_1 |
|
value: 54.774 |
|
- type: ndcg_at_10 |
|
value: 45.657 |
|
- type: ndcg_at_100 |
|
value: 48.954 |
|
- type: ndcg_at_1000 |
|
value: 50.78 |
|
- type: ndcg_at_3 |
|
value: 41.808 |
|
- type: ndcg_at_5 |
|
value: 43.816 |
|
- type: precision_at_1 |
|
value: 54.774 |
|
- type: precision_at_10 |
|
value: 9.479 |
|
- type: precision_at_100 |
|
value: 1.208 |
|
- type: precision_at_1000 |
|
value: 0.145 |
|
- type: precision_at_3 |
|
value: 25.856 |
|
- type: precision_at_5 |
|
value: 17.102 |
|
- type: recall_at_1 |
|
value: 27.387 |
|
- type: recall_at_10 |
|
value: 47.394 |
|
- type: recall_at_100 |
|
value: 60.397999999999996 |
|
- type: recall_at_1000 |
|
value: 72.54599999999999 |
|
- type: recall_at_3 |
|
value: 38.785 |
|
- type: recall_at_5 |
|
value: 42.754999999999995 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/imdb |
|
name: MTEB ImdbClassification |
|
config: default |
|
split: test |
|
revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7 |
|
metrics: |
|
- type: accuracy |
|
value: 61.217999999999996 |
|
- type: ap |
|
value: 56.84286974948407 |
|
- type: f1 |
|
value: 60.99211195455131 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: msmarco |
|
name: MTEB MSMARCO |
|
config: default |
|
split: dev |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 19.224 |
|
- type: map_at_10 |
|
value: 30.448999999999998 |
|
- type: map_at_100 |
|
value: 31.663999999999998 |
|
- type: map_at_1000 |
|
value: 31.721 |
|
- type: map_at_3 |
|
value: 26.922 |
|
- type: map_at_5 |
|
value: 28.906 |
|
- type: mrr_at_1 |
|
value: 19.756 |
|
- type: mrr_at_10 |
|
value: 30.994 |
|
- type: mrr_at_100 |
|
value: 32.161 |
|
- type: mrr_at_1000 |
|
value: 32.213 |
|
- type: mrr_at_3 |
|
value: 27.502 |
|
- type: mrr_at_5 |
|
value: 29.48 |
|
- type: ndcg_at_1 |
|
value: 19.742 |
|
- type: ndcg_at_10 |
|
value: 36.833 |
|
- type: ndcg_at_100 |
|
value: 42.785000000000004 |
|
- type: ndcg_at_1000 |
|
value: 44.291000000000004 |
|
- type: ndcg_at_3 |
|
value: 29.580000000000002 |
|
- type: ndcg_at_5 |
|
value: 33.139 |
|
- type: precision_at_1 |
|
value: 19.742 |
|
- type: precision_at_10 |
|
value: 5.894 |
|
- type: precision_at_100 |
|
value: 0.889 |
|
- type: precision_at_1000 |
|
value: 0.10200000000000001 |
|
- type: precision_at_3 |
|
value: 12.665000000000001 |
|
- type: precision_at_5 |
|
value: 9.393 |
|
- type: recall_at_1 |
|
value: 19.224 |
|
- type: recall_at_10 |
|
value: 56.538999999999994 |
|
- type: recall_at_100 |
|
value: 84.237 |
|
- type: recall_at_1000 |
|
value: 95.965 |
|
- type: recall_at_3 |
|
value: 36.71 |
|
- type: recall_at_5 |
|
value: 45.283 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/mtop_domain |
|
name: MTEB MTOPDomainClassification (en) |
|
config: en |
|
split: test |
|
revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf |
|
metrics: |
|
- type: accuracy |
|
value: 89.97264021887824 |
|
- type: f1 |
|
value: 89.53607318488027 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/mtop_intent |
|
name: MTEB MTOPIntentClassification (en) |
|
config: en |
|
split: test |
|
revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba |
|
metrics: |
|
- type: accuracy |
|
value: 59.566803465572285 |
|
- type: f1 |
|
value: 40.94003955225124 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/amazon_massive_intent |
|
name: MTEB MassiveIntentClassification (en) |
|
config: en |
|
split: test |
|
revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 |
|
metrics: |
|
- type: accuracy |
|
value: 66.7787491593813 |
|
- type: f1 |
|
value: 64.51190971513093 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/amazon_massive_scenario |
|
name: MTEB MassiveScenarioClassification (en) |
|
config: en |
|
split: test |
|
revision: 7d571f92784cd94a019292a1f45445077d0ef634 |
|
metrics: |
|
- type: accuracy |
|
value: 73.7794216543376 |
|
- type: f1 |
|
value: 72.71852261076475 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: mteb/medrxiv-clustering-p2p |
|
name: MTEB MedrxivClusteringP2P |
|
config: default |
|
split: test |
|
revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73 |
|
metrics: |
|
- type: v_measure |
|
value: 28.40883054472429 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: mteb/medrxiv-clustering-s2s |
|
name: MTEB MedrxivClusteringS2S |
|
config: default |
|
split: test |
|
revision: 35191c8c0dca72d8ff3efcd72aa802307d469663 |
|
metrics: |
|
- type: v_measure |
|
value: 26.144338339113617 |
|
- task: |
|
type: Reranking |
|
dataset: |
|
type: mteb/mind_small |
|
name: MTEB MindSmallReranking |
|
config: default |
|
split: test |
|
revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69 |
|
metrics: |
|
- type: map |
|
value: 30.894071459751267 |
|
- type: mrr |
|
value: 31.965886150526256 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: nfcorpus |
|
name: MTEB NFCorpus |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 5.024 |
|
- type: map_at_10 |
|
value: 10.533 |
|
- type: map_at_100 |
|
value: 12.97 |
|
- type: map_at_1000 |
|
value: 14.163 |
|
- type: map_at_3 |
|
value: 7.971 |
|
- type: map_at_5 |
|
value: 9.15 |
|
- type: mrr_at_1 |
|
value: 40.867 |
|
- type: mrr_at_10 |
|
value: 48.837 |
|
- type: mrr_at_100 |
|
value: 49.464999999999996 |
|
- type: mrr_at_1000 |
|
value: 49.509 |
|
- type: mrr_at_3 |
|
value: 46.800999999999995 |
|
- type: mrr_at_5 |
|
value: 47.745 |
|
- type: ndcg_at_1 |
|
value: 38.854 |
|
- type: ndcg_at_10 |
|
value: 29.674 |
|
- type: ndcg_at_100 |
|
value: 26.66 |
|
- type: ndcg_at_1000 |
|
value: 35.088 |
|
- type: ndcg_at_3 |
|
value: 34.838 |
|
- type: ndcg_at_5 |
|
value: 32.423 |
|
- type: precision_at_1 |
|
value: 40.248 |
|
- type: precision_at_10 |
|
value: 21.826999999999998 |
|
- type: precision_at_100 |
|
value: 6.78 |
|
- type: precision_at_1000 |
|
value: 1.889 |
|
- type: precision_at_3 |
|
value: 32.405 |
|
- type: precision_at_5 |
|
value: 27.74 |
|
- type: recall_at_1 |
|
value: 5.024 |
|
- type: recall_at_10 |
|
value: 13.996 |
|
- type: recall_at_100 |
|
value: 26.636 |
|
- type: recall_at_1000 |
|
value: 57.816 |
|
- type: recall_at_3 |
|
value: 9.063 |
|
- type: recall_at_5 |
|
value: 10.883 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: nq |
|
name: MTEB NQ |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 23.088 |
|
- type: map_at_10 |
|
value: 36.915 |
|
- type: map_at_100 |
|
value: 38.141999999999996 |
|
- type: map_at_1000 |
|
value: 38.191 |
|
- type: map_at_3 |
|
value: 32.458999999999996 |
|
- type: map_at_5 |
|
value: 35.004999999999995 |
|
- type: mrr_at_1 |
|
value: 26.101000000000003 |
|
- type: mrr_at_10 |
|
value: 39.1 |
|
- type: mrr_at_100 |
|
value: 40.071 |
|
- type: mrr_at_1000 |
|
value: 40.106 |
|
- type: mrr_at_3 |
|
value: 35.236000000000004 |
|
- type: mrr_at_5 |
|
value: 37.43 |
|
- type: ndcg_at_1 |
|
value: 26.072 |
|
- type: ndcg_at_10 |
|
value: 44.482 |
|
- type: ndcg_at_100 |
|
value: 49.771 |
|
- type: ndcg_at_1000 |
|
value: 50.903 |
|
- type: ndcg_at_3 |
|
value: 35.922 |
|
- type: ndcg_at_5 |
|
value: 40.178000000000004 |
|
- type: precision_at_1 |
|
value: 26.072 |
|
- type: precision_at_10 |
|
value: 7.795000000000001 |
|
- type: precision_at_100 |
|
value: 1.072 |
|
- type: precision_at_1000 |
|
value: 0.11800000000000001 |
|
- type: precision_at_3 |
|
value: 16.725 |
|
- type: precision_at_5 |
|
value: 12.468 |
|
- type: recall_at_1 |
|
value: 23.088 |
|
- type: recall_at_10 |
|
value: 65.534 |
|
- type: recall_at_100 |
|
value: 88.68 |
|
- type: recall_at_1000 |
|
value: 97.101 |
|
- type: recall_at_3 |
|
value: 43.161 |
|
- type: recall_at_5 |
|
value: 52.959999999999994 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: quora |
|
name: MTEB QuoraRetrieval |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 69.612 |
|
- type: map_at_10 |
|
value: 83.292 |
|
- type: map_at_100 |
|
value: 83.96000000000001 |
|
- type: map_at_1000 |
|
value: 83.978 |
|
- type: map_at_3 |
|
value: 80.26299999999999 |
|
- type: map_at_5 |
|
value: 82.11500000000001 |
|
- type: mrr_at_1 |
|
value: 80.21000000000001 |
|
- type: mrr_at_10 |
|
value: 86.457 |
|
- type: mrr_at_100 |
|
value: 86.58500000000001 |
|
- type: mrr_at_1000 |
|
value: 86.587 |
|
- type: mrr_at_3 |
|
value: 85.452 |
|
- type: mrr_at_5 |
|
value: 86.101 |
|
- type: ndcg_at_1 |
|
value: 80.21000000000001 |
|
- type: ndcg_at_10 |
|
value: 87.208 |
|
- type: ndcg_at_100 |
|
value: 88.549 |
|
- type: ndcg_at_1000 |
|
value: 88.683 |
|
- type: ndcg_at_3 |
|
value: 84.20400000000001 |
|
- type: ndcg_at_5 |
|
value: 85.768 |
|
- type: precision_at_1 |
|
value: 80.21000000000001 |
|
- type: precision_at_10 |
|
value: 13.29 |
|
- type: precision_at_100 |
|
value: 1.5230000000000001 |
|
- type: precision_at_1000 |
|
value: 0.156 |
|
- type: precision_at_3 |
|
value: 36.767 |
|
- type: precision_at_5 |
|
value: 24.2 |
|
- type: recall_at_1 |
|
value: 69.612 |
|
- type: recall_at_10 |
|
value: 94.651 |
|
- type: recall_at_100 |
|
value: 99.297 |
|
- type: recall_at_1000 |
|
value: 99.95100000000001 |
|
- type: recall_at_3 |
|
value: 86.003 |
|
- type: recall_at_5 |
|
value: 90.45100000000001 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: mteb/reddit-clustering |
|
name: MTEB RedditClustering |
|
config: default |
|
split: test |
|
revision: 24640382cdbf8abc73003fb0fa6d111a705499eb |
|
metrics: |
|
- type: v_measure |
|
value: 46.28945925252077 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: mteb/reddit-clustering-p2p |
|
name: MTEB RedditClusteringP2P |
|
config: default |
|
split: test |
|
revision: 282350215ef01743dc01b456c7f5241fa8937f16 |
|
metrics: |
|
- type: v_measure |
|
value: 50.954446620859684 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: scidocs |
|
name: MTEB SCIDOCS |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 3.888 |
|
- type: map_at_10 |
|
value: 9.21 |
|
- type: map_at_100 |
|
value: 10.629 |
|
- type: map_at_1000 |
|
value: 10.859 |
|
- type: map_at_3 |
|
value: 6.743 |
|
- type: map_at_5 |
|
value: 7.982 |
|
- type: mrr_at_1 |
|
value: 19.1 |
|
- type: mrr_at_10 |
|
value: 28.294000000000004 |
|
- type: mrr_at_100 |
|
value: 29.326999999999998 |
|
- type: mrr_at_1000 |
|
value: 29.414 |
|
- type: mrr_at_3 |
|
value: 25.367 |
|
- type: mrr_at_5 |
|
value: 27.002 |
|
- type: ndcg_at_1 |
|
value: 19.1 |
|
- type: ndcg_at_10 |
|
value: 15.78 |
|
- type: ndcg_at_100 |
|
value: 21.807000000000002 |
|
- type: ndcg_at_1000 |
|
value: 26.593 |
|
- type: ndcg_at_3 |
|
value: 15.204999999999998 |
|
- type: ndcg_at_5 |
|
value: 13.217 |
|
- type: precision_at_1 |
|
value: 19.1 |
|
- type: precision_at_10 |
|
value: 7.9799999999999995 |
|
- type: precision_at_100 |
|
value: 1.667 |
|
- type: precision_at_1000 |
|
value: 0.28300000000000003 |
|
- type: precision_at_3 |
|
value: 13.933000000000002 |
|
- type: precision_at_5 |
|
value: 11.379999999999999 |
|
- type: recall_at_1 |
|
value: 3.888 |
|
- type: recall_at_10 |
|
value: 16.17 |
|
- type: recall_at_100 |
|
value: 33.848 |
|
- type: recall_at_1000 |
|
value: 57.345 |
|
- type: recall_at_3 |
|
value: 8.468 |
|
- type: recall_at_5 |
|
value: 11.540000000000001 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: mteb/sickr-sts |
|
name: MTEB SICK-R |
|
config: default |
|
split: test |
|
revision: a6ea5a8cab320b040a23452cc28066d9beae2cee |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 79.05803116288386 |
|
- type: cos_sim_spearman |
|
value: 70.0403855402571 |
|
- type: euclidean_pearson |
|
value: 75.59006280166072 |
|
- type: euclidean_spearman |
|
value: 70.04038926247613 |
|
- type: manhattan_pearson |
|
value: 75.48136278078455 |
|
- type: manhattan_spearman |
|
value: 69.9608897701754 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: mteb/sts12-sts |
|
name: MTEB STS12 |
|
config: default |
|
split: test |
|
revision: a0d554a64d88156834ff5ae9920b964011b16384 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 68.56836430603597 |
|
- type: cos_sim_spearman |
|
value: 64.38407759822387 |
|
- type: euclidean_pearson |
|
value: 65.93619045541732 |
|
- type: euclidean_spearman |
|
value: 64.38184049884836 |
|
- type: manhattan_pearson |
|
value: 65.97148637646873 |
|
- type: manhattan_spearman |
|
value: 64.48011982438929 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: mteb/sts13-sts |
|
name: MTEB STS13 |
|
config: default |
|
split: test |
|
revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 75.990362280318 |
|
- type: cos_sim_spearman |
|
value: 76.40621890996734 |
|
- type: euclidean_pearson |
|
value: 76.01739766577184 |
|
- type: euclidean_spearman |
|
value: 76.4062736496846 |
|
- type: manhattan_pearson |
|
value: 76.04738378838042 |
|
- type: manhattan_spearman |
|
value: 76.44991409719592 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: mteb/sts14-sts |
|
name: MTEB STS14 |
|
config: default |
|
split: test |
|
revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 74.8516957692617 |
|
- type: cos_sim_spearman |
|
value: 69.325199098278 |
|
- type: euclidean_pearson |
|
value: 73.37922793254768 |
|
- type: euclidean_spearman |
|
value: 69.32520119670215 |
|
- type: manhattan_pearson |
|
value: 73.3795212376615 |
|
- type: manhattan_spearman |
|
value: 69.35306787926315 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: mteb/sts15-sts |
|
name: MTEB STS15 |
|
config: default |
|
split: test |
|
revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 78.644002190612 |
|
- type: cos_sim_spearman |
|
value: 80.18337978181648 |
|
- type: euclidean_pearson |
|
value: 79.7628642371887 |
|
- type: euclidean_spearman |
|
value: 80.18337906907526 |
|
- type: manhattan_pearson |
|
value: 79.68810722704522 |
|
- type: manhattan_spearman |
|
value: 80.10664518173466 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: mteb/sts16-sts |
|
name: MTEB STS16 |
|
config: default |
|
split: test |
|
revision: 4d8694f8f0e0100860b497b999b3dbed754a0513 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 77.8303940874723 |
|
- type: cos_sim_spearman |
|
value: 79.56812599677549 |
|
- type: euclidean_pearson |
|
value: 79.38928950396344 |
|
- type: euclidean_spearman |
|
value: 79.56812556750812 |
|
- type: manhattan_pearson |
|
value: 79.41057583507681 |
|
- type: manhattan_spearman |
|
value: 79.57604428731142 |
|
- 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: 78.90792116013353 |
|
- type: cos_sim_spearman |
|
value: 81.18059230233499 |
|
- type: euclidean_pearson |
|
value: 80.2622631297375 |
|
- type: euclidean_spearman |
|
value: 81.18059230233499 |
|
- type: manhattan_pearson |
|
value: 80.23946026135997 |
|
- type: manhattan_spearman |
|
value: 81.11947325071426 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: mteb/sts22-crosslingual-sts |
|
name: MTEB STS22 (en) |
|
config: en |
|
split: test |
|
revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 64.46850619973324 |
|
- type: cos_sim_spearman |
|
value: 65.50839374141563 |
|
- type: euclidean_pearson |
|
value: 66.60130812260707 |
|
- type: euclidean_spearman |
|
value: 65.50839374141563 |
|
- type: manhattan_pearson |
|
value: 66.58871918195092 |
|
- type: manhattan_spearman |
|
value: 65.7347325297592 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: mteb/stsbenchmark-sts |
|
name: MTEB STSBenchmark |
|
config: default |
|
split: test |
|
revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 75.71536124107834 |
|
- type: cos_sim_spearman |
|
value: 75.98365906208434 |
|
- type: euclidean_pearson |
|
value: 76.64573753881218 |
|
- type: euclidean_spearman |
|
value: 75.98365906208434 |
|
- type: manhattan_pearson |
|
value: 76.63637189172626 |
|
- type: manhattan_spearman |
|
value: 75.9660207821009 |
|
- task: |
|
type: Reranking |
|
dataset: |
|
type: mteb/scidocs-reranking |
|
name: MTEB SciDocsRR |
|
config: default |
|
split: test |
|
revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab |
|
metrics: |
|
- type: map |
|
value: 74.27669440147513 |
|
- type: mrr |
|
value: 91.7729356699945 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: scifact |
|
name: MTEB SciFact |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 41.028 |
|
- type: map_at_10 |
|
value: 49.919000000000004 |
|
- type: map_at_100 |
|
value: 50.91 |
|
- type: map_at_1000 |
|
value: 50.955 |
|
- type: map_at_3 |
|
value: 47.785 |
|
- type: map_at_5 |
|
value: 49.084 |
|
- type: mrr_at_1 |
|
value: 43.667 |
|
- type: mrr_at_10 |
|
value: 51.342 |
|
- type: mrr_at_100 |
|
value: 52.197 |
|
- type: mrr_at_1000 |
|
value: 52.236000000000004 |
|
- type: mrr_at_3 |
|
value: 49.667 |
|
- type: mrr_at_5 |
|
value: 50.766999999999996 |
|
- type: ndcg_at_1 |
|
value: 43.667 |
|
- type: ndcg_at_10 |
|
value: 54.029 |
|
- type: ndcg_at_100 |
|
value: 58.909 |
|
- type: ndcg_at_1000 |
|
value: 60.131 |
|
- type: ndcg_at_3 |
|
value: 50.444 |
|
- type: ndcg_at_5 |
|
value: 52.354 |
|
- type: precision_at_1 |
|
value: 43.667 |
|
- type: precision_at_10 |
|
value: 7.432999999999999 |
|
- type: precision_at_100 |
|
value: 1.0 |
|
- type: precision_at_1000 |
|
value: 0.11100000000000002 |
|
- type: precision_at_3 |
|
value: 20.444000000000003 |
|
- type: precision_at_5 |
|
value: 13.533000000000001 |
|
- type: recall_at_1 |
|
value: 41.028 |
|
- type: recall_at_10 |
|
value: 65.011 |
|
- type: recall_at_100 |
|
value: 88.033 |
|
- type: recall_at_1000 |
|
value: 97.667 |
|
- type: recall_at_3 |
|
value: 55.394 |
|
- type: recall_at_5 |
|
value: 60.183 |
|
- task: |
|
type: PairClassification |
|
dataset: |
|
type: mteb/sprintduplicatequestions-pairclassification |
|
name: MTEB SprintDuplicateQuestions |
|
config: default |
|
split: test |
|
revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46 |
|
metrics: |
|
- type: cos_sim_accuracy |
|
value: 99.76534653465346 |
|
- type: cos_sim_ap |
|
value: 93.83756773536699 |
|
- type: cos_sim_f1 |
|
value: 87.91097622660598 |
|
- type: cos_sim_precision |
|
value: 88.94575230296827 |
|
- type: cos_sim_recall |
|
value: 86.9 |
|
- type: dot_accuracy |
|
value: 99.76534653465346 |
|
- type: dot_ap |
|
value: 93.83756773536699 |
|
- type: dot_f1 |
|
value: 87.91097622660598 |
|
- type: dot_precision |
|
value: 88.94575230296827 |
|
- type: dot_recall |
|
value: 86.9 |
|
- type: euclidean_accuracy |
|
value: 99.76534653465346 |
|
- type: euclidean_ap |
|
value: 93.837567735367 |
|
- type: euclidean_f1 |
|
value: 87.91097622660598 |
|
- type: euclidean_precision |
|
value: 88.94575230296827 |
|
- type: euclidean_recall |
|
value: 86.9 |
|
- type: manhattan_accuracy |
|
value: 99.76633663366337 |
|
- type: manhattan_ap |
|
value: 93.84480825492724 |
|
- type: manhattan_f1 |
|
value: 87.97145769622833 |
|
- type: manhattan_precision |
|
value: 89.70893970893971 |
|
- type: manhattan_recall |
|
value: 86.3 |
|
- type: max_accuracy |
|
value: 99.76633663366337 |
|
- type: max_ap |
|
value: 93.84480825492724 |
|
- type: max_f1 |
|
value: 87.97145769622833 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: mteb/stackexchange-clustering |
|
name: MTEB StackExchangeClustering |
|
config: default |
|
split: test |
|
revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259 |
|
metrics: |
|
- type: v_measure |
|
value: 48.078155553339585 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: mteb/stackexchange-clustering-p2p |
|
name: MTEB StackExchangeClusteringP2P |
|
config: default |
|
split: test |
|
revision: 815ca46b2622cec33ccafc3735d572c266efdb44 |
|
metrics: |
|
- type: v_measure |
|
value: 33.34857297824906 |
|
- task: |
|
type: Reranking |
|
dataset: |
|
type: mteb/stackoverflowdupquestions-reranking |
|
name: MTEB StackOverflowDupQuestions |
|
config: default |
|
split: test |
|
revision: e185fbe320c72810689fc5848eb6114e1ef5ec69 |
|
metrics: |
|
- type: map |
|
value: 50.06219491505384 |
|
- type: mrr |
|
value: 50.77479097699686 |
|
- task: |
|
type: Summarization |
|
dataset: |
|
type: mteb/summeval |
|
name: MTEB SummEval |
|
config: default |
|
split: test |
|
revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 30.48401937651373 |
|
- type: cos_sim_spearman |
|
value: 31.048654273022606 |
|
- type: dot_pearson |
|
value: 30.484020082707847 |
|
- type: dot_spearman |
|
value: 31.048654273022606 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: trec-covid |
|
name: MTEB TRECCOVID |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 0.183 |
|
- type: map_at_10 |
|
value: 1.32 |
|
- type: map_at_100 |
|
value: 7.01 |
|
- type: map_at_1000 |
|
value: 16.957 |
|
- type: map_at_3 |
|
value: 0.481 |
|
- type: map_at_5 |
|
value: 0.737 |
|
- type: mrr_at_1 |
|
value: 66.0 |
|
- type: mrr_at_10 |
|
value: 78.7 |
|
- type: mrr_at_100 |
|
value: 78.7 |
|
- type: mrr_at_1000 |
|
value: 78.7 |
|
- type: mrr_at_3 |
|
value: 76.0 |
|
- type: mrr_at_5 |
|
value: 78.7 |
|
- type: ndcg_at_1 |
|
value: 56.99999999999999 |
|
- type: ndcg_at_10 |
|
value: 55.846 |
|
- type: ndcg_at_100 |
|
value: 43.138 |
|
- type: ndcg_at_1000 |
|
value: 39.4 |
|
- type: ndcg_at_3 |
|
value: 57.306999999999995 |
|
- type: ndcg_at_5 |
|
value: 57.294 |
|
- type: precision_at_1 |
|
value: 66.0 |
|
- type: precision_at_10 |
|
value: 60.0 |
|
- type: precision_at_100 |
|
value: 44.6 |
|
- type: precision_at_1000 |
|
value: 17.8 |
|
- type: precision_at_3 |
|
value: 62.0 |
|
- type: precision_at_5 |
|
value: 62.0 |
|
- type: recall_at_1 |
|
value: 0.183 |
|
- type: recall_at_10 |
|
value: 1.583 |
|
- type: recall_at_100 |
|
value: 10.412 |
|
- type: recall_at_1000 |
|
value: 37.358999999999995 |
|
- type: recall_at_3 |
|
value: 0.516 |
|
- type: recall_at_5 |
|
value: 0.845 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: webis-touche2020 |
|
name: MTEB Touche2020 |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 1.7420000000000002 |
|
- type: map_at_10 |
|
value: 6.4879999999999995 |
|
- type: map_at_100 |
|
value: 11.654 |
|
- type: map_at_1000 |
|
value: 13.23 |
|
- type: map_at_3 |
|
value: 3.148 |
|
- type: map_at_5 |
|
value: 4.825 |
|
- type: mrr_at_1 |
|
value: 18.367 |
|
- type: mrr_at_10 |
|
value: 30.258000000000003 |
|
- type: mrr_at_100 |
|
value: 31.570999999999998 |
|
- type: mrr_at_1000 |
|
value: 31.594 |
|
- type: mrr_at_3 |
|
value: 26.19 |
|
- type: mrr_at_5 |
|
value: 28.027 |
|
- type: ndcg_at_1 |
|
value: 15.306000000000001 |
|
- type: ndcg_at_10 |
|
value: 15.608 |
|
- type: ndcg_at_100 |
|
value: 28.808 |
|
- type: ndcg_at_1000 |
|
value: 41.603 |
|
- type: ndcg_at_3 |
|
value: 13.357 |
|
- type: ndcg_at_5 |
|
value: 15.306000000000001 |
|
- type: precision_at_1 |
|
value: 18.367 |
|
- type: precision_at_10 |
|
value: 15.101999999999999 |
|
- type: precision_at_100 |
|
value: 6.49 |
|
- type: precision_at_1000 |
|
value: 1.488 |
|
- type: precision_at_3 |
|
value: 14.966 |
|
- type: precision_at_5 |
|
value: 17.143 |
|
- type: recall_at_1 |
|
value: 1.7420000000000002 |
|
- type: recall_at_10 |
|
value: 12.267 |
|
- type: recall_at_100 |
|
value: 41.105999999999995 |
|
- type: recall_at_1000 |
|
value: 80.569 |
|
- type: recall_at_3 |
|
value: 4.009 |
|
- type: recall_at_5 |
|
value: 7.417999999999999 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/toxic_conversations_50k |
|
name: MTEB ToxicConversationsClassification |
|
config: default |
|
split: test |
|
revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c |
|
metrics: |
|
- type: accuracy |
|
value: 65.1178 |
|
- type: ap |
|
value: 11.974961582206614 |
|
- type: f1 |
|
value: 50.24491996814835 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/tweet_sentiment_extraction |
|
name: MTEB TweetSentimentExtractionClassification |
|
config: default |
|
split: test |
|
revision: d604517c81ca91fe16a244d1248fc021f9ecee7a |
|
metrics: |
|
- type: accuracy |
|
value: 51.63271080928127 |
|
- type: f1 |
|
value: 51.81589904316042 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: mteb/twentynewsgroups-clustering |
|
name: MTEB TwentyNewsgroupsClustering |
|
config: default |
|
split: test |
|
revision: 6125ec4e24fa026cec8a478383ee943acfbd5449 |
|
metrics: |
|
- type: v_measure |
|
value: 40.791709673552276 |
|
- task: |
|
type: PairClassification |
|
dataset: |
|
type: mteb/twittersemeval2015-pairclassification |
|
name: MTEB TwitterSemEval2015 |
|
config: default |
|
split: test |
|
revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1 |
|
metrics: |
|
- type: cos_sim_accuracy |
|
value: 83.05418131966383 |
|
- type: cos_sim_ap |
|
value: 64.72353098186304 |
|
- type: cos_sim_f1 |
|
value: 61.313330054107226 |
|
- type: cos_sim_precision |
|
value: 57.415937356057114 |
|
- type: cos_sim_recall |
|
value: 65.77836411609499 |
|
- type: dot_accuracy |
|
value: 83.05418131966383 |
|
- type: dot_ap |
|
value: 64.72352701424393 |
|
- type: dot_f1 |
|
value: 61.313330054107226 |
|
- type: dot_precision |
|
value: 57.415937356057114 |
|
- type: dot_recall |
|
value: 65.77836411609499 |
|
- type: euclidean_accuracy |
|
value: 83.05418131966383 |
|
- type: euclidean_ap |
|
value: 64.72353124585976 |
|
- type: euclidean_f1 |
|
value: 61.313330054107226 |
|
- type: euclidean_precision |
|
value: 57.415937356057114 |
|
- type: euclidean_recall |
|
value: 65.77836411609499 |
|
- type: manhattan_accuracy |
|
value: 82.98861536627525 |
|
- type: manhattan_ap |
|
value: 64.53981837182303 |
|
- type: manhattan_f1 |
|
value: 60.94911377930246 |
|
- type: manhattan_precision |
|
value: 53.784056508577194 |
|
- type: manhattan_recall |
|
value: 70.31662269129288 |
|
- type: max_accuracy |
|
value: 83.05418131966383 |
|
- type: max_ap |
|
value: 64.72353124585976 |
|
- type: max_f1 |
|
value: 61.313330054107226 |
|
- task: |
|
type: PairClassification |
|
dataset: |
|
type: mteb/twitterurlcorpus-pairclassification |
|
name: MTEB TwitterURLCorpus |
|
config: default |
|
split: test |
|
revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf |
|
metrics: |
|
- type: cos_sim_accuracy |
|
value: 88.06225016493966 |
|
- type: cos_sim_ap |
|
value: 84.00829172423475 |
|
- type: cos_sim_f1 |
|
value: 76.1288446157202 |
|
- type: cos_sim_precision |
|
value: 72.11737153877945 |
|
- type: cos_sim_recall |
|
value: 80.61287342161995 |
|
- type: dot_accuracy |
|
value: 88.06225016493966 |
|
- type: dot_ap |
|
value: 84.00827913374181 |
|
- type: dot_f1 |
|
value: 76.1288446157202 |
|
- type: dot_precision |
|
value: 72.11737153877945 |
|
- type: dot_recall |
|
value: 80.61287342161995 |
|
- type: euclidean_accuracy |
|
value: 88.06225016493966 |
|
- type: euclidean_ap |
|
value: 84.00827099295034 |
|
- type: euclidean_f1 |
|
value: 76.1288446157202 |
|
- type: euclidean_precision |
|
value: 72.11737153877945 |
|
- type: euclidean_recall |
|
value: 80.61287342161995 |
|
- type: manhattan_accuracy |
|
value: 88.05642876547523 |
|
- type: manhattan_ap |
|
value: 83.9157542691417 |
|
- type: manhattan_f1 |
|
value: 76.09045667447307 |
|
- type: manhattan_precision |
|
value: 72.50348675034869 |
|
- type: manhattan_recall |
|
value: 80.05081613797351 |
|
- type: max_accuracy |
|
value: 88.06225016493966 |
|
- type: max_ap |
|
value: 84.00829172423475 |
|
- type: max_f1 |
|
value: 76.1288446157202 |
|
--- |
|
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MTEB evaluation results on English language for 'multi-qa-MiniLM-L6-cos-v1' sbert model |
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Model and licence can be found [here](https://huggingface.co/sentence-transformers/multi-qa-MiniLM-L6-cos-v1) |
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