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--- |
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tags: |
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- mteb |
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- feature-extraction |
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- sentence-similarity |
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model-index: |
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- name: v1 |
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results: |
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- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/amazon_counterfactual |
|
name: MTEB AmazonCounterfactualClassification (en) |
|
config: en |
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split: test |
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revision: e8379541af4e31359cca9fbcf4b00f2671dba205 |
|
metrics: |
|
- type: accuracy |
|
value: 77.07462686567163 |
|
- type: ap |
|
value: 40.56545526400157 |
|
- type: f1 |
|
value: 71.14615231582567 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/amazon_polarity |
|
name: MTEB AmazonPolarityClassification |
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config: default |
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split: test |
|
revision: e2d317d38cd51312af73b3d32a06d1a08b442046 |
|
metrics: |
|
- type: accuracy |
|
value: 93.03617500000001 |
|
- type: ap |
|
value: 89.68075993779713 |
|
- type: f1 |
|
value: 93.01941324029784 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/amazon_reviews_multi |
|
name: MTEB AmazonReviewsClassification (en) |
|
config: en |
|
split: test |
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revision: 1399c76144fd37290681b995c656ef9b2e06e26d |
|
metrics: |
|
- type: accuracy |
|
value: 47.730000000000004 |
|
- type: f1 |
|
value: 47.17780812766083 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: arguana |
|
name: MTEB ArguAna |
|
config: default |
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split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 41.963 |
|
- type: map_at_10 |
|
value: 57.289 |
|
- type: map_at_100 |
|
value: 57.813 |
|
- type: map_at_1000 |
|
value: 57.81699999999999 |
|
- type: map_at_3 |
|
value: 53.425999999999995 |
|
- type: map_at_5 |
|
value: 55.798 |
|
- type: mrr_at_1 |
|
value: 42.603 |
|
- type: mrr_at_10 |
|
value: 57.528999999999996 |
|
- type: mrr_at_100 |
|
value: 58.053999999999995 |
|
- type: mrr_at_1000 |
|
value: 58.058 |
|
- type: mrr_at_3 |
|
value: 53.639 |
|
- type: mrr_at_5 |
|
value: 56.018 |
|
- type: ndcg_at_1 |
|
value: 41.963 |
|
- type: ndcg_at_10 |
|
value: 65.038 |
|
- type: ndcg_at_100 |
|
value: 67.243 |
|
- type: ndcg_at_1000 |
|
value: 67.337 |
|
- type: ndcg_at_3 |
|
value: 57.218 |
|
- type: ndcg_at_5 |
|
value: 61.49400000000001 |
|
- type: precision_at_1 |
|
value: 41.963 |
|
- type: precision_at_10 |
|
value: 8.94 |
|
- type: precision_at_100 |
|
value: 0.989 |
|
- type: precision_at_1000 |
|
value: 0.1 |
|
- type: precision_at_3 |
|
value: 22.736 |
|
- type: precision_at_5 |
|
value: 15.717999999999998 |
|
- type: recall_at_1 |
|
value: 41.963 |
|
- type: recall_at_10 |
|
value: 89.403 |
|
- type: recall_at_100 |
|
value: 98.933 |
|
- type: recall_at_1000 |
|
value: 99.644 |
|
- type: recall_at_3 |
|
value: 68.208 |
|
- type: recall_at_5 |
|
value: 78.592 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: mteb/arxiv-clustering-p2p |
|
name: MTEB ArxivClusteringP2P |
|
config: default |
|
split: test |
|
revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d |
|
metrics: |
|
- type: v_measure |
|
value: 49.7119537244616 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: mteb/arxiv-clustering-s2s |
|
name: MTEB ArxivClusteringS2S |
|
config: default |
|
split: test |
|
revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53 |
|
metrics: |
|
- type: v_measure |
|
value: 43.45461573320737 |
|
- task: |
|
type: Reranking |
|
dataset: |
|
type: mteb/askubuntudupquestions-reranking |
|
name: MTEB AskUbuntuDupQuestions |
|
config: default |
|
split: test |
|
revision: 2000358ca161889fa9c082cb41daa8dcfb161a54 |
|
metrics: |
|
- type: map |
|
value: 63.77183059365367 |
|
- type: mrr |
|
value: 76.47836697005673 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: mteb/biosses-sts |
|
name: MTEB BIOSSES |
|
config: default |
|
split: test |
|
revision: d3fb88f8f02e40887cd149695127462bbcf29b4a |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 84.6676490140397 |
|
- type: cos_sim_spearman |
|
value: 83.62479701399418 |
|
- type: euclidean_pearson |
|
value: 83.77348388669043 |
|
- type: euclidean_spearman |
|
value: 85.15254266808878 |
|
- type: manhattan_pearson |
|
value: 83.82596617753741 |
|
- type: manhattan_spearman |
|
value: 84.92783875287692 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/banking77 |
|
name: MTEB Banking77Classification |
|
config: default |
|
split: test |
|
revision: 0fd18e25b25c072e09e0d92ab615fda904d66300 |
|
metrics: |
|
- type: accuracy |
|
value: 87.85714285714286 |
|
- type: f1 |
|
value: 87.84374773981708 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: mteb/biorxiv-clustering-p2p |
|
name: MTEB BiorxivClusteringP2P |
|
config: default |
|
split: test |
|
revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40 |
|
metrics: |
|
- type: v_measure |
|
value: 42.02700557366043 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: mteb/biorxiv-clustering-s2s |
|
name: MTEB BiorxivClusteringS2S |
|
config: default |
|
split: test |
|
revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908 |
|
metrics: |
|
- type: v_measure |
|
value: 38.19662622375156 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: BeIR/cqadupstack |
|
name: MTEB CQADupstackAndroidRetrieval |
|
config: default |
|
split: test |
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revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 32.83 |
|
- type: map_at_10 |
|
value: 44.035000000000004 |
|
- type: map_at_100 |
|
value: 45.49 |
|
- type: map_at_1000 |
|
value: 45.613 |
|
- type: map_at_3 |
|
value: 40.542 |
|
- type: map_at_5 |
|
value: 42.213 |
|
- type: mrr_at_1 |
|
value: 39.914 |
|
- type: mrr_at_10 |
|
value: 49.742999999999995 |
|
- type: mrr_at_100 |
|
value: 50.473 |
|
- type: mrr_at_1000 |
|
value: 50.514 |
|
- type: mrr_at_3 |
|
value: 47.043 |
|
- type: mrr_at_5 |
|
value: 48.603 |
|
- type: ndcg_at_1 |
|
value: 39.914 |
|
- type: ndcg_at_10 |
|
value: 50.432 |
|
- type: ndcg_at_100 |
|
value: 55.675 |
|
- type: ndcg_at_1000 |
|
value: 57.547000000000004 |
|
- type: ndcg_at_3 |
|
value: 45.33 |
|
- type: ndcg_at_5 |
|
value: 47.326 |
|
- type: precision_at_1 |
|
value: 39.914 |
|
- type: precision_at_10 |
|
value: 9.614 |
|
- type: precision_at_100 |
|
value: 1.522 |
|
- type: precision_at_1000 |
|
value: 0.197 |
|
- type: precision_at_3 |
|
value: 21.602 |
|
- type: precision_at_5 |
|
value: 15.308 |
|
- type: recall_at_1 |
|
value: 32.83 |
|
- type: recall_at_10 |
|
value: 62.824000000000005 |
|
- type: recall_at_100 |
|
value: 84.604 |
|
- type: recall_at_1000 |
|
value: 96.318 |
|
- type: recall_at_3 |
|
value: 47.991 |
|
- type: recall_at_5 |
|
value: 53.74 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: BeIR/cqadupstack |
|
name: MTEB CQADupstackEnglishRetrieval |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 34.666000000000004 |
|
- type: map_at_10 |
|
value: 45.149 |
|
- type: map_at_100 |
|
value: 46.373 |
|
- type: map_at_1000 |
|
value: 46.505 |
|
- type: map_at_3 |
|
value: 41.973 |
|
- type: map_at_5 |
|
value: 43.876 |
|
- type: mrr_at_1 |
|
value: 43.248 |
|
- type: mrr_at_10 |
|
value: 51.346000000000004 |
|
- type: mrr_at_100 |
|
value: 51.903 |
|
- type: mrr_at_1000 |
|
value: 51.94800000000001 |
|
- type: mrr_at_3 |
|
value: 49.289 |
|
- type: mrr_at_5 |
|
value: 50.575 |
|
- type: ndcg_at_1 |
|
value: 43.248 |
|
- type: ndcg_at_10 |
|
value: 50.849999999999994 |
|
- type: ndcg_at_100 |
|
value: 54.836 |
|
- type: ndcg_at_1000 |
|
value: 56.821999999999996 |
|
- type: ndcg_at_3 |
|
value: 46.788000000000004 |
|
- type: ndcg_at_5 |
|
value: 48.901 |
|
- type: precision_at_1 |
|
value: 43.248 |
|
- type: precision_at_10 |
|
value: 9.51 |
|
- type: precision_at_100 |
|
value: 1.5 |
|
- type: precision_at_1000 |
|
value: 0.196 |
|
- type: precision_at_3 |
|
value: 22.548000000000002 |
|
- type: precision_at_5 |
|
value: 15.936 |
|
- type: recall_at_1 |
|
value: 34.666000000000004 |
|
- type: recall_at_10 |
|
value: 60.244 |
|
- type: recall_at_100 |
|
value: 77.03 |
|
- type: recall_at_1000 |
|
value: 89.619 |
|
- type: recall_at_3 |
|
value: 48.147 |
|
- type: recall_at_5 |
|
value: 54.19199999999999 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: BeIR/cqadupstack |
|
name: MTEB CQADupstackGamingRetrieval |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 42.317 |
|
- type: map_at_10 |
|
value: 55.084999999999994 |
|
- type: map_at_100 |
|
value: 56.081 |
|
- type: map_at_1000 |
|
value: 56.131 |
|
- type: map_at_3 |
|
value: 51.87199999999999 |
|
- type: map_at_5 |
|
value: 53.638 |
|
- type: mrr_at_1 |
|
value: 48.464 |
|
- type: mrr_at_10 |
|
value: 58.664 |
|
- type: mrr_at_100 |
|
value: 59.282999999999994 |
|
- type: mrr_at_1000 |
|
value: 59.307 |
|
- type: mrr_at_3 |
|
value: 56.426 |
|
- type: mrr_at_5 |
|
value: 57.799 |
|
- type: ndcg_at_1 |
|
value: 48.464 |
|
- type: ndcg_at_10 |
|
value: 60.939 |
|
- type: ndcg_at_100 |
|
value: 64.77000000000001 |
|
- type: ndcg_at_1000 |
|
value: 65.732 |
|
- type: ndcg_at_3 |
|
value: 55.769000000000005 |
|
- type: ndcg_at_5 |
|
value: 58.282000000000004 |
|
- type: precision_at_1 |
|
value: 48.464 |
|
- type: precision_at_10 |
|
value: 9.693 |
|
- type: precision_at_100 |
|
value: 1.248 |
|
- type: precision_at_1000 |
|
value: 0.13699999999999998 |
|
- type: precision_at_3 |
|
value: 24.89 |
|
- type: precision_at_5 |
|
value: 16.828000000000003 |
|
- type: recall_at_1 |
|
value: 42.317 |
|
- type: recall_at_10 |
|
value: 74.602 |
|
- type: recall_at_100 |
|
value: 90.943 |
|
- type: recall_at_1000 |
|
value: 97.617 |
|
- type: recall_at_3 |
|
value: 60.909 |
|
- type: recall_at_5 |
|
value: 67.172 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: BeIR/cqadupstack |
|
name: MTEB CQADupstackGisRetrieval |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 28.854999999999997 |
|
- type: map_at_10 |
|
value: 37.508 |
|
- type: map_at_100 |
|
value: 38.576 |
|
- type: map_at_1000 |
|
value: 38.646 |
|
- type: map_at_3 |
|
value: 35.066 |
|
- type: map_at_5 |
|
value: 36.291000000000004 |
|
- type: mrr_at_1 |
|
value: 30.959999999999997 |
|
- type: mrr_at_10 |
|
value: 39.559 |
|
- type: mrr_at_100 |
|
value: 40.481 |
|
- type: mrr_at_1000 |
|
value: 40.536 |
|
- type: mrr_at_3 |
|
value: 37.288 |
|
- type: mrr_at_5 |
|
value: 38.463 |
|
- type: ndcg_at_1 |
|
value: 30.959999999999997 |
|
- type: ndcg_at_10 |
|
value: 42.403 |
|
- type: ndcg_at_100 |
|
value: 47.49 |
|
- type: ndcg_at_1000 |
|
value: 49.227 |
|
- type: ndcg_at_3 |
|
value: 37.599 |
|
- type: ndcg_at_5 |
|
value: 39.652 |
|
- type: precision_at_1 |
|
value: 30.959999999999997 |
|
- type: precision_at_10 |
|
value: 6.328 |
|
- type: precision_at_100 |
|
value: 0.9329999999999999 |
|
- type: precision_at_1000 |
|
value: 0.11100000000000002 |
|
- type: precision_at_3 |
|
value: 15.744 |
|
- type: precision_at_5 |
|
value: 10.667 |
|
- type: recall_at_1 |
|
value: 28.854999999999997 |
|
- type: recall_at_10 |
|
value: 55.539 |
|
- type: recall_at_100 |
|
value: 78.481 |
|
- type: recall_at_1000 |
|
value: 91.456 |
|
- type: recall_at_3 |
|
value: 42.302 |
|
- type: recall_at_5 |
|
value: 47.288999999999994 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: BeIR/cqadupstack |
|
name: MTEB CQADupstackMathematicaRetrieval |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 19.17 |
|
- type: map_at_10 |
|
value: 27.737000000000002 |
|
- type: map_at_100 |
|
value: 28.912 |
|
- type: map_at_1000 |
|
value: 29.029 |
|
- type: map_at_3 |
|
value: 25.038 |
|
- type: map_at_5 |
|
value: 26.478 |
|
- type: mrr_at_1 |
|
value: 23.632 |
|
- type: mrr_at_10 |
|
value: 32.614 |
|
- type: mrr_at_100 |
|
value: 33.578 |
|
- type: mrr_at_1000 |
|
value: 33.642 |
|
- type: mrr_at_3 |
|
value: 30.079 |
|
- type: mrr_at_5 |
|
value: 31.490000000000002 |
|
- type: ndcg_at_1 |
|
value: 23.632 |
|
- type: ndcg_at_10 |
|
value: 33.204 |
|
- type: ndcg_at_100 |
|
value: 38.805 |
|
- type: ndcg_at_1000 |
|
value: 41.508 |
|
- type: ndcg_at_3 |
|
value: 28.316999999999997 |
|
- type: ndcg_at_5 |
|
value: 30.459999999999997 |
|
- type: precision_at_1 |
|
value: 23.632 |
|
- type: precision_at_10 |
|
value: 6.007 |
|
- type: precision_at_100 |
|
value: 1.015 |
|
- type: precision_at_1000 |
|
value: 0.13799999999999998 |
|
- type: precision_at_3 |
|
value: 13.639999999999999 |
|
- type: precision_at_5 |
|
value: 9.776 |
|
- type: recall_at_1 |
|
value: 19.17 |
|
- type: recall_at_10 |
|
value: 45.247 |
|
- type: recall_at_100 |
|
value: 69.455 |
|
- type: recall_at_1000 |
|
value: 88.548 |
|
- type: recall_at_3 |
|
value: 31.55 |
|
- type: recall_at_5 |
|
value: 36.97 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: BeIR/cqadupstack |
|
name: MTEB CQADupstackPhysicsRetrieval |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 30.788 |
|
- type: map_at_10 |
|
value: 41.510000000000005 |
|
- type: map_at_100 |
|
value: 42.827 |
|
- type: map_at_1000 |
|
value: 42.936 |
|
- type: map_at_3 |
|
value: 38.454 |
|
- type: map_at_5 |
|
value: 40.116 |
|
- type: mrr_at_1 |
|
value: 37.247 |
|
- type: mrr_at_10 |
|
value: 46.976 |
|
- type: mrr_at_100 |
|
value: 47.797 |
|
- type: mrr_at_1000 |
|
value: 47.838 |
|
- type: mrr_at_3 |
|
value: 44.61 |
|
- type: mrr_at_5 |
|
value: 45.961999999999996 |
|
- type: ndcg_at_1 |
|
value: 37.247 |
|
- type: ndcg_at_10 |
|
value: 47.447 |
|
- type: ndcg_at_100 |
|
value: 52.711 |
|
- type: ndcg_at_1000 |
|
value: 54.663 |
|
- type: ndcg_at_3 |
|
value: 42.576 |
|
- type: ndcg_at_5 |
|
value: 44.832 |
|
- type: precision_at_1 |
|
value: 37.247 |
|
- type: precision_at_10 |
|
value: 8.441 |
|
- type: precision_at_100 |
|
value: 1.277 |
|
- type: precision_at_1000 |
|
value: 0.163 |
|
- type: precision_at_3 |
|
value: 20.019000000000002 |
|
- type: precision_at_5 |
|
value: 14.033000000000001 |
|
- type: recall_at_1 |
|
value: 30.788 |
|
- type: recall_at_10 |
|
value: 59.51499999999999 |
|
- type: recall_at_100 |
|
value: 81.317 |
|
- type: recall_at_1000 |
|
value: 93.88300000000001 |
|
- type: recall_at_3 |
|
value: 46.021 |
|
- type: recall_at_5 |
|
value: 51.791 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: BeIR/cqadupstack |
|
name: MTEB CQADupstackProgrammersRetrieval |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 26.671 |
|
- type: map_at_10 |
|
value: 37.088 |
|
- type: map_at_100 |
|
value: 38.482 |
|
- type: map_at_1000 |
|
value: 38.594 |
|
- type: map_at_3 |
|
value: 33.947 |
|
- type: map_at_5 |
|
value: 35.682 |
|
- type: mrr_at_1 |
|
value: 32.647999999999996 |
|
- type: mrr_at_10 |
|
value: 42.469 |
|
- type: mrr_at_100 |
|
value: 43.332 |
|
- type: mrr_at_1000 |
|
value: 43.387 |
|
- type: mrr_at_3 |
|
value: 39.916000000000004 |
|
- type: mrr_at_5 |
|
value: 41.382999999999996 |
|
- type: ndcg_at_1 |
|
value: 32.647999999999996 |
|
- type: ndcg_at_10 |
|
value: 43.013 |
|
- type: ndcg_at_100 |
|
value: 48.554 |
|
- type: ndcg_at_1000 |
|
value: 50.854 |
|
- type: ndcg_at_3 |
|
value: 37.987 |
|
- type: ndcg_at_5 |
|
value: 40.316 |
|
- type: precision_at_1 |
|
value: 32.647999999999996 |
|
- type: precision_at_10 |
|
value: 7.911 |
|
- type: precision_at_100 |
|
value: 1.2309999999999999 |
|
- type: precision_at_1000 |
|
value: 0.16 |
|
- type: precision_at_3 |
|
value: 18.151 |
|
- type: precision_at_5 |
|
value: 12.991 |
|
- type: recall_at_1 |
|
value: 26.671 |
|
- type: recall_at_10 |
|
value: 54.935 |
|
- type: recall_at_100 |
|
value: 78.387 |
|
- type: recall_at_1000 |
|
value: 93.997 |
|
- type: recall_at_3 |
|
value: 41.117 |
|
- type: recall_at_5 |
|
value: 47.211 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: BeIR/cqadupstack |
|
name: MTEB CQADupstackRetrieval |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 28.19883333333333 |
|
- type: map_at_10 |
|
value: 37.64883333333333 |
|
- type: map_at_100 |
|
value: 38.861749999999994 |
|
- type: map_at_1000 |
|
value: 38.97366666666666 |
|
- type: map_at_3 |
|
value: 34.831999999999994 |
|
- type: map_at_5 |
|
value: 36.366083333333336 |
|
- type: mrr_at_1 |
|
value: 33.25125 |
|
- type: mrr_at_10 |
|
value: 41.90383333333333 |
|
- type: mrr_at_100 |
|
value: 42.75125 |
|
- type: mrr_at_1000 |
|
value: 42.80408333333334 |
|
- type: mrr_at_3 |
|
value: 39.58091666666667 |
|
- type: mrr_at_5 |
|
value: 40.919250000000005 |
|
- type: ndcg_at_1 |
|
value: 33.25125 |
|
- type: ndcg_at_10 |
|
value: 43.03475 |
|
- type: ndcg_at_100 |
|
value: 48.11583333333333 |
|
- type: ndcg_at_1000 |
|
value: 50.23949999999999 |
|
- type: ndcg_at_3 |
|
value: 38.373666666666665 |
|
- type: ndcg_at_5 |
|
value: 40.52941666666667 |
|
- type: precision_at_1 |
|
value: 33.25125 |
|
- type: precision_at_10 |
|
value: 7.442750000000001 |
|
- type: precision_at_100 |
|
value: 1.1699166666666667 |
|
- type: precision_at_1000 |
|
value: 0.15416666666666667 |
|
- type: precision_at_3 |
|
value: 17.556416666666667 |
|
- type: precision_at_5 |
|
value: 12.3295 |
|
- type: recall_at_1 |
|
value: 28.19883333333333 |
|
- type: recall_at_10 |
|
value: 54.61899999999999 |
|
- type: recall_at_100 |
|
value: 76.78066666666666 |
|
- type: recall_at_1000 |
|
value: 91.29883333333333 |
|
- type: recall_at_3 |
|
value: 41.69391666666667 |
|
- type: recall_at_5 |
|
value: 47.250083333333336 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: BeIR/cqadupstack |
|
name: MTEB CQADupstackStatsRetrieval |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 26.891 |
|
- type: map_at_10 |
|
value: 33.765 |
|
- type: map_at_100 |
|
value: 34.762 |
|
- type: map_at_1000 |
|
value: 34.855999999999995 |
|
- type: map_at_3 |
|
value: 31.813999999999997 |
|
- type: map_at_5 |
|
value: 32.925 |
|
- type: mrr_at_1 |
|
value: 30.368000000000002 |
|
- type: mrr_at_10 |
|
value: 36.85 |
|
- type: mrr_at_100 |
|
value: 37.681 |
|
- type: mrr_at_1000 |
|
value: 37.747 |
|
- type: mrr_at_3 |
|
value: 35.046 |
|
- type: mrr_at_5 |
|
value: 36.065999999999995 |
|
- type: ndcg_at_1 |
|
value: 30.368000000000002 |
|
- type: ndcg_at_10 |
|
value: 37.716 |
|
- type: ndcg_at_100 |
|
value: 42.529 |
|
- type: ndcg_at_1000 |
|
value: 44.769999999999996 |
|
- type: ndcg_at_3 |
|
value: 34.226 |
|
- type: ndcg_at_5 |
|
value: 35.933 |
|
- type: precision_at_1 |
|
value: 30.368000000000002 |
|
- type: precision_at_10 |
|
value: 5.736 |
|
- type: precision_at_100 |
|
value: 0.8789999999999999 |
|
- type: precision_at_1000 |
|
value: 0.11299999999999999 |
|
- type: precision_at_3 |
|
value: 14.519000000000002 |
|
- type: precision_at_5 |
|
value: 9.969 |
|
- type: recall_at_1 |
|
value: 26.891 |
|
- type: recall_at_10 |
|
value: 46.733999999999995 |
|
- type: recall_at_100 |
|
value: 68.696 |
|
- type: recall_at_1000 |
|
value: 85.085 |
|
- type: recall_at_3 |
|
value: 37.153000000000006 |
|
- type: recall_at_5 |
|
value: 41.396 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: BeIR/cqadupstack |
|
name: MTEB CQADupstackTexRetrieval |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 19.184 |
|
- type: map_at_10 |
|
value: 26.717000000000002 |
|
- type: map_at_100 |
|
value: 27.863 |
|
- type: map_at_1000 |
|
value: 27.98 |
|
- type: map_at_3 |
|
value: 24.248 |
|
- type: map_at_5 |
|
value: 25.619999999999997 |
|
- type: mrr_at_1 |
|
value: 23.021 |
|
- type: mrr_at_10 |
|
value: 30.517 |
|
- type: mrr_at_100 |
|
value: 31.480000000000004 |
|
- type: mrr_at_1000 |
|
value: 31.549 |
|
- type: mrr_at_3 |
|
value: 28.194999999999997 |
|
- type: mrr_at_5 |
|
value: 29.573 |
|
- type: ndcg_at_1 |
|
value: 23.021 |
|
- type: ndcg_at_10 |
|
value: 31.501 |
|
- type: ndcg_at_100 |
|
value: 36.927 |
|
- type: ndcg_at_1000 |
|
value: 39.61 |
|
- type: ndcg_at_3 |
|
value: 27.058 |
|
- type: ndcg_at_5 |
|
value: 29.171999999999997 |
|
- type: precision_at_1 |
|
value: 23.021 |
|
- type: precision_at_10 |
|
value: 5.64 |
|
- type: precision_at_100 |
|
value: 0.97 |
|
- type: precision_at_1000 |
|
value: 0.13799999999999998 |
|
- type: precision_at_3 |
|
value: 12.572 |
|
- type: precision_at_5 |
|
value: 9.147 |
|
- type: recall_at_1 |
|
value: 19.184 |
|
- type: recall_at_10 |
|
value: 42.108000000000004 |
|
- type: recall_at_100 |
|
value: 66.438 |
|
- type: recall_at_1000 |
|
value: 85.309 |
|
- type: recall_at_3 |
|
value: 29.853 |
|
- type: recall_at_5 |
|
value: 35.228 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: BeIR/cqadupstack |
|
name: MTEB CQADupstackUnixRetrieval |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 27.516000000000002 |
|
- type: map_at_10 |
|
value: 37.16 |
|
- type: map_at_100 |
|
value: 38.329 |
|
- type: map_at_1000 |
|
value: 38.424 |
|
- type: map_at_3 |
|
value: 34.365 |
|
- type: map_at_5 |
|
value: 35.905 |
|
- type: mrr_at_1 |
|
value: 32.275999999999996 |
|
- type: mrr_at_10 |
|
value: 41.192 |
|
- type: mrr_at_100 |
|
value: 42.055 |
|
- type: mrr_at_1000 |
|
value: 42.111 |
|
- type: mrr_at_3 |
|
value: 38.682 |
|
- type: mrr_at_5 |
|
value: 40.044000000000004 |
|
- type: ndcg_at_1 |
|
value: 32.275999999999996 |
|
- type: ndcg_at_10 |
|
value: 42.573 |
|
- type: ndcg_at_100 |
|
value: 47.9 |
|
- type: ndcg_at_1000 |
|
value: 50.005 |
|
- type: ndcg_at_3 |
|
value: 37.536 |
|
- type: ndcg_at_5 |
|
value: 39.812 |
|
- type: precision_at_1 |
|
value: 32.275999999999996 |
|
- type: precision_at_10 |
|
value: 7.127 |
|
- type: precision_at_100 |
|
value: 1.107 |
|
- type: precision_at_1000 |
|
value: 0.13899999999999998 |
|
- type: precision_at_3 |
|
value: 16.947000000000003 |
|
- type: precision_at_5 |
|
value: 11.866 |
|
- type: recall_at_1 |
|
value: 27.516000000000002 |
|
- type: recall_at_10 |
|
value: 54.94 |
|
- type: recall_at_100 |
|
value: 78.011 |
|
- type: recall_at_1000 |
|
value: 92.66 |
|
- type: recall_at_3 |
|
value: 41.522 |
|
- type: recall_at_5 |
|
value: 46.989 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: BeIR/cqadupstack |
|
name: MTEB CQADupstackWebmastersRetrieval |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 25.052999999999997 |
|
- type: map_at_10 |
|
value: 33.847 |
|
- type: map_at_100 |
|
value: 35.555 |
|
- type: map_at_1000 |
|
value: 35.772999999999996 |
|
- type: map_at_3 |
|
value: 31.273 |
|
- type: map_at_5 |
|
value: 32.49 |
|
- type: mrr_at_1 |
|
value: 30.435000000000002 |
|
- type: mrr_at_10 |
|
value: 38.41 |
|
- type: mrr_at_100 |
|
value: 39.567 |
|
- type: mrr_at_1000 |
|
value: 39.62 |
|
- type: mrr_at_3 |
|
value: 36.265 |
|
- type: mrr_at_5 |
|
value: 37.342 |
|
- type: ndcg_at_1 |
|
value: 30.435000000000002 |
|
- type: ndcg_at_10 |
|
value: 39.579 |
|
- type: ndcg_at_100 |
|
value: 45.865 |
|
- type: ndcg_at_1000 |
|
value: 48.363 |
|
- type: ndcg_at_3 |
|
value: 35.545 |
|
- type: ndcg_at_5 |
|
value: 37.023 |
|
- type: precision_at_1 |
|
value: 30.435000000000002 |
|
- type: precision_at_10 |
|
value: 7.668 |
|
- type: precision_at_100 |
|
value: 1.518 |
|
- type: precision_at_1000 |
|
value: 0.24 |
|
- type: precision_at_3 |
|
value: 16.798 |
|
- type: precision_at_5 |
|
value: 11.858 |
|
- type: recall_at_1 |
|
value: 25.052999999999997 |
|
- type: recall_at_10 |
|
value: 50.160000000000004 |
|
- type: recall_at_100 |
|
value: 78.313 |
|
- type: recall_at_1000 |
|
value: 93.697 |
|
- type: recall_at_3 |
|
value: 38.368 |
|
- type: recall_at_5 |
|
value: 42.568 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: BeIR/cqadupstack |
|
name: MTEB CQADupstackWordpressRetrieval |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 24.445 |
|
- type: map_at_10 |
|
value: 32.185 |
|
- type: map_at_100 |
|
value: 33.091 |
|
- type: map_at_1000 |
|
value: 33.196999999999996 |
|
- type: map_at_3 |
|
value: 29.392000000000003 |
|
- type: map_at_5 |
|
value: 31.159 |
|
- type: mrr_at_1 |
|
value: 26.802 |
|
- type: mrr_at_10 |
|
value: 34.506 |
|
- type: mrr_at_100 |
|
value: 35.385 |
|
- type: mrr_at_1000 |
|
value: 35.449999999999996 |
|
- type: mrr_at_3 |
|
value: 32.132 |
|
- type: mrr_at_5 |
|
value: 33.731 |
|
- type: ndcg_at_1 |
|
value: 26.802 |
|
- type: ndcg_at_10 |
|
value: 36.76 |
|
- type: ndcg_at_100 |
|
value: 41.327999999999996 |
|
- type: ndcg_at_1000 |
|
value: 43.773 |
|
- type: ndcg_at_3 |
|
value: 31.752999999999997 |
|
- type: ndcg_at_5 |
|
value: 34.644000000000005 |
|
- type: precision_at_1 |
|
value: 26.802 |
|
- type: precision_at_10 |
|
value: 5.638 |
|
- type: precision_at_100 |
|
value: 0.839 |
|
- type: precision_at_1000 |
|
value: 0.11800000000000001 |
|
- type: precision_at_3 |
|
value: 13.247 |
|
- type: precision_at_5 |
|
value: 9.575 |
|
- type: recall_at_1 |
|
value: 24.445 |
|
- type: recall_at_10 |
|
value: 48.58 |
|
- type: recall_at_100 |
|
value: 69.69300000000001 |
|
- type: recall_at_1000 |
|
value: 87.397 |
|
- type: recall_at_3 |
|
value: 35.394 |
|
- type: recall_at_5 |
|
value: 42.455 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: climate-fever |
|
name: MTEB ClimateFEVER |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 17.441000000000003 |
|
- type: map_at_10 |
|
value: 29.369 |
|
- type: map_at_100 |
|
value: 31.339 |
|
- type: map_at_1000 |
|
value: 31.537 |
|
- type: map_at_3 |
|
value: 25.09 |
|
- type: map_at_5 |
|
value: 27.388 |
|
- type: mrr_at_1 |
|
value: 39.217999999999996 |
|
- type: mrr_at_10 |
|
value: 51.23799999999999 |
|
- type: mrr_at_100 |
|
value: 51.88 |
|
- type: mrr_at_1000 |
|
value: 51.905 |
|
- type: mrr_at_3 |
|
value: 48.426 |
|
- type: mrr_at_5 |
|
value: 49.986000000000004 |
|
- type: ndcg_at_1 |
|
value: 39.217999999999996 |
|
- type: ndcg_at_10 |
|
value: 38.987 |
|
- type: ndcg_at_100 |
|
value: 46.043 |
|
- type: ndcg_at_1000 |
|
value: 49.19 |
|
- type: ndcg_at_3 |
|
value: 33.426 |
|
- type: ndcg_at_5 |
|
value: 35.182 |
|
- type: precision_at_1 |
|
value: 39.217999999999996 |
|
- type: precision_at_10 |
|
value: 11.909 |
|
- type: precision_at_100 |
|
value: 1.9640000000000002 |
|
- type: precision_at_1000 |
|
value: 0.255 |
|
- type: precision_at_3 |
|
value: 24.973 |
|
- type: precision_at_5 |
|
value: 18.528 |
|
- type: recall_at_1 |
|
value: 17.441000000000003 |
|
- type: recall_at_10 |
|
value: 44.378 |
|
- type: recall_at_100 |
|
value: 68.377 |
|
- type: recall_at_1000 |
|
value: 85.67 |
|
- type: recall_at_3 |
|
value: 30.214999999999996 |
|
- type: recall_at_5 |
|
value: 36.094 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: dbpedia-entity |
|
name: MTEB DBPedia |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 9.922 |
|
- type: map_at_10 |
|
value: 22.095000000000002 |
|
- type: map_at_100 |
|
value: 32.196999999999996 |
|
- type: map_at_1000 |
|
value: 33.949 |
|
- type: map_at_3 |
|
value: 15.695999999999998 |
|
- type: map_at_5 |
|
value: 18.561 |
|
- type: mrr_at_1 |
|
value: 71.75 |
|
- type: mrr_at_10 |
|
value: 79.4 |
|
- type: mrr_at_100 |
|
value: 79.64 |
|
- type: mrr_at_1000 |
|
value: 79.645 |
|
- type: mrr_at_3 |
|
value: 77.792 |
|
- type: mrr_at_5 |
|
value: 79.00399999999999 |
|
- type: ndcg_at_1 |
|
value: 59.25 |
|
- type: ndcg_at_10 |
|
value: 45.493 |
|
- type: ndcg_at_100 |
|
value: 51.461 |
|
- type: ndcg_at_1000 |
|
value: 58.62500000000001 |
|
- type: ndcg_at_3 |
|
value: 50.038000000000004 |
|
- type: ndcg_at_5 |
|
value: 47.796 |
|
- type: precision_at_1 |
|
value: 71.75 |
|
- type: precision_at_10 |
|
value: 36.325 |
|
- type: precision_at_100 |
|
value: 12.068 |
|
- type: precision_at_1000 |
|
value: 2.2089999999999996 |
|
- type: precision_at_3 |
|
value: 53.25 |
|
- type: precision_at_5 |
|
value: 46.650000000000006 |
|
- type: recall_at_1 |
|
value: 9.922 |
|
- type: recall_at_10 |
|
value: 27.371000000000002 |
|
- type: recall_at_100 |
|
value: 58.36900000000001 |
|
- type: recall_at_1000 |
|
value: 81.43 |
|
- type: recall_at_3 |
|
value: 16.817 |
|
- type: recall_at_5 |
|
value: 21.179000000000002 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/emotion |
|
name: MTEB EmotionClassification |
|
config: default |
|
split: test |
|
revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37 |
|
metrics: |
|
- type: accuracy |
|
value: 54.665 |
|
- type: f1 |
|
value: 49.727174733557334 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: fever |
|
name: MTEB FEVER |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 77.523 |
|
- type: map_at_10 |
|
value: 85.917 |
|
- type: map_at_100 |
|
value: 86.102 |
|
- type: map_at_1000 |
|
value: 86.115 |
|
- type: map_at_3 |
|
value: 84.946 |
|
- type: map_at_5 |
|
value: 85.541 |
|
- type: mrr_at_1 |
|
value: 83.678 |
|
- type: mrr_at_10 |
|
value: 90.24600000000001 |
|
- type: mrr_at_100 |
|
value: 90.278 |
|
- type: mrr_at_1000 |
|
value: 90.279 |
|
- type: mrr_at_3 |
|
value: 89.779 |
|
- type: mrr_at_5 |
|
value: 90.09700000000001 |
|
- type: ndcg_at_1 |
|
value: 83.678 |
|
- type: ndcg_at_10 |
|
value: 89.34100000000001 |
|
- type: ndcg_at_100 |
|
value: 89.923 |
|
- type: ndcg_at_1000 |
|
value: 90.14 |
|
- type: ndcg_at_3 |
|
value: 88.01400000000001 |
|
- type: ndcg_at_5 |
|
value: 88.723 |
|
- type: precision_at_1 |
|
value: 83.678 |
|
- type: precision_at_10 |
|
value: 10.687000000000001 |
|
- type: precision_at_100 |
|
value: 1.123 |
|
- type: precision_at_1000 |
|
value: 0.116 |
|
- type: precision_at_3 |
|
value: 33.678000000000004 |
|
- type: precision_at_5 |
|
value: 20.771 |
|
- type: recall_at_1 |
|
value: 77.523 |
|
- type: recall_at_10 |
|
value: 95.48299999999999 |
|
- type: recall_at_100 |
|
value: 97.622 |
|
- type: recall_at_1000 |
|
value: 98.932 |
|
- type: recall_at_3 |
|
value: 91.797 |
|
- type: recall_at_5 |
|
value: 93.702 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: fiqa |
|
name: MTEB FiQA2018 |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 23.335 |
|
- type: map_at_10 |
|
value: 37.689 |
|
- type: map_at_100 |
|
value: 39.638 |
|
- type: map_at_1000 |
|
value: 39.805 |
|
- type: map_at_3 |
|
value: 33.099000000000004 |
|
- type: map_at_5 |
|
value: 35.563 |
|
- type: mrr_at_1 |
|
value: 45.525 |
|
- type: mrr_at_10 |
|
value: 54.07300000000001 |
|
- type: mrr_at_100 |
|
value: 54.736 |
|
- type: mrr_at_1000 |
|
value: 54.772 |
|
- type: mrr_at_3 |
|
value: 51.62 |
|
- type: mrr_at_5 |
|
value: 52.932 |
|
- type: ndcg_at_1 |
|
value: 45.525 |
|
- type: ndcg_at_10 |
|
value: 45.877 |
|
- type: ndcg_at_100 |
|
value: 52.428 |
|
- type: ndcg_at_1000 |
|
value: 55.089 |
|
- type: ndcg_at_3 |
|
value: 42.057 |
|
- type: ndcg_at_5 |
|
value: 43.067 |
|
- type: precision_at_1 |
|
value: 45.525 |
|
- type: precision_at_10 |
|
value: 12.67 |
|
- type: precision_at_100 |
|
value: 1.951 |
|
- type: precision_at_1000 |
|
value: 0.242 |
|
- type: precision_at_3 |
|
value: 28.035 |
|
- type: precision_at_5 |
|
value: 20.525 |
|
- type: recall_at_1 |
|
value: 23.335 |
|
- type: recall_at_10 |
|
value: 53.047 |
|
- type: recall_at_100 |
|
value: 77.061 |
|
- type: recall_at_1000 |
|
value: 92.842 |
|
- type: recall_at_3 |
|
value: 38.182 |
|
- type: recall_at_5 |
|
value: 44.094 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: hotpotqa |
|
name: MTEB HotpotQA |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 41.918 |
|
- type: map_at_10 |
|
value: 69.01 |
|
- type: map_at_100 |
|
value: 69.806 |
|
- type: map_at_1000 |
|
value: 69.853 |
|
- type: map_at_3 |
|
value: 65.594 |
|
- type: map_at_5 |
|
value: 67.77300000000001 |
|
- type: mrr_at_1 |
|
value: 83.83500000000001 |
|
- type: mrr_at_10 |
|
value: 88.804 |
|
- type: mrr_at_100 |
|
value: 88.912 |
|
- type: mrr_at_1000 |
|
value: 88.915 |
|
- type: mrr_at_3 |
|
value: 88.091 |
|
- type: mrr_at_5 |
|
value: 88.564 |
|
- type: ndcg_at_1 |
|
value: 83.83500000000001 |
|
- type: ndcg_at_10 |
|
value: 76.627 |
|
- type: ndcg_at_100 |
|
value: 79.269 |
|
- type: ndcg_at_1000 |
|
value: 80.122 |
|
- type: ndcg_at_3 |
|
value: 71.98 |
|
- type: ndcg_at_5 |
|
value: 74.64 |
|
- type: precision_at_1 |
|
value: 83.83500000000001 |
|
- type: precision_at_10 |
|
value: 16.005 |
|
- type: precision_at_100 |
|
value: 1.806 |
|
- type: precision_at_1000 |
|
value: 0.192 |
|
- type: precision_at_3 |
|
value: 46.544999999999995 |
|
- type: precision_at_5 |
|
value: 30.026000000000003 |
|
- type: recall_at_1 |
|
value: 41.918 |
|
- type: recall_at_10 |
|
value: 80.027 |
|
- type: recall_at_100 |
|
value: 90.29700000000001 |
|
- type: recall_at_1000 |
|
value: 95.901 |
|
- type: recall_at_3 |
|
value: 69.818 |
|
- type: recall_at_5 |
|
value: 75.064 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/imdb |
|
name: MTEB ImdbClassification |
|
config: default |
|
split: test |
|
revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7 |
|
metrics: |
|
- type: accuracy |
|
value: 93.70040000000002 |
|
- type: ap |
|
value: 90.58039961008838 |
|
- type: f1 |
|
value: 93.696322976805 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: msmarco |
|
name: MTEB MSMARCO |
|
config: default |
|
split: dev |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 23.388 |
|
- type: map_at_10 |
|
value: 36.164 |
|
- type: map_at_100 |
|
value: 37.289 |
|
- type: map_at_1000 |
|
value: 37.336000000000006 |
|
- type: map_at_3 |
|
value: 32.208 |
|
- type: map_at_5 |
|
value: 34.482 |
|
- type: mrr_at_1 |
|
value: 23.997 |
|
- type: mrr_at_10 |
|
value: 36.779 |
|
- type: mrr_at_100 |
|
value: 37.839 |
|
- type: mrr_at_1000 |
|
value: 37.881 |
|
- type: mrr_at_3 |
|
value: 32.93 |
|
- type: mrr_at_5 |
|
value: 35.158 |
|
- type: ndcg_at_1 |
|
value: 23.997 |
|
- type: ndcg_at_10 |
|
value: 43.282 |
|
- type: ndcg_at_100 |
|
value: 48.637 |
|
- type: ndcg_at_1000 |
|
value: 49.754 |
|
- type: ndcg_at_3 |
|
value: 35.266999999999996 |
|
- type: ndcg_at_5 |
|
value: 39.305 |
|
- type: precision_at_1 |
|
value: 23.997 |
|
- type: precision_at_10 |
|
value: 6.821000000000001 |
|
- type: precision_at_100 |
|
value: 0.9490000000000001 |
|
- type: precision_at_1000 |
|
value: 0.104 |
|
- type: precision_at_3 |
|
value: 15.004999999999999 |
|
- type: precision_at_5 |
|
value: 11.054 |
|
- type: recall_at_1 |
|
value: 23.388 |
|
- type: recall_at_10 |
|
value: 65.127 |
|
- type: recall_at_100 |
|
value: 89.753 |
|
- type: recall_at_1000 |
|
value: 98.173 |
|
- type: recall_at_3 |
|
value: 43.4 |
|
- type: recall_at_5 |
|
value: 53.071999999999996 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/mtop_domain |
|
name: MTEB MTOPDomainClassification (en) |
|
config: en |
|
split: test |
|
revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf |
|
metrics: |
|
- type: accuracy |
|
value: 95.16187870497038 |
|
- type: f1 |
|
value: 94.92465121683176 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/mtop_intent |
|
name: MTEB MTOPIntentClassification (en) |
|
config: en |
|
split: test |
|
revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba |
|
metrics: |
|
- type: accuracy |
|
value: 80.03191974464204 |
|
- type: f1 |
|
value: 61.33007652226683 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/amazon_massive_intent |
|
name: MTEB MassiveIntentClassification (en) |
|
config: en |
|
split: test |
|
revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 |
|
metrics: |
|
- type: accuracy |
|
value: 79.09885675857431 |
|
- type: f1 |
|
value: 76.96223435507879 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/amazon_massive_scenario |
|
name: MTEB MassiveScenarioClassification (en) |
|
config: en |
|
split: test |
|
revision: 7d571f92784cd94a019292a1f45445077d0ef634 |
|
metrics: |
|
- type: accuracy |
|
value: 81.94687289845326 |
|
- type: f1 |
|
value: 81.72213346382495 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: mteb/medrxiv-clustering-p2p |
|
name: MTEB MedrxivClusteringP2P |
|
config: default |
|
split: test |
|
revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73 |
|
metrics: |
|
- type: v_measure |
|
value: 36.23008400582387 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: mteb/medrxiv-clustering-s2s |
|
name: MTEB MedrxivClusteringS2S |
|
config: default |
|
split: test |
|
revision: 35191c8c0dca72d8ff3efcd72aa802307d469663 |
|
metrics: |
|
- type: v_measure |
|
value: 32.38335563600822 |
|
- task: |
|
type: Reranking |
|
dataset: |
|
type: mteb/mind_small |
|
name: MTEB MindSmallReranking |
|
config: default |
|
split: test |
|
revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69 |
|
metrics: |
|
- type: map |
|
value: 31.52782587210441 |
|
- type: mrr |
|
value: 32.7035429328629 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: nfcorpus |
|
name: MTEB NFCorpus |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 6.845999999999999 |
|
- type: map_at_10 |
|
value: 14.63 |
|
- type: map_at_100 |
|
value: 18.345 |
|
- type: map_at_1000 |
|
value: 19.807 |
|
- type: map_at_3 |
|
value: 10.953 |
|
- type: map_at_5 |
|
value: 12.697 |
|
- type: mrr_at_1 |
|
value: 47.368 |
|
- type: mrr_at_10 |
|
value: 56.408 |
|
- type: mrr_at_100 |
|
value: 56.991 |
|
- type: mrr_at_1000 |
|
value: 57.02700000000001 |
|
- type: mrr_at_3 |
|
value: 54.747 |
|
- type: mrr_at_5 |
|
value: 55.846 |
|
- type: ndcg_at_1 |
|
value: 45.82 |
|
- type: ndcg_at_10 |
|
value: 36.732 |
|
- type: ndcg_at_100 |
|
value: 34.036 |
|
- type: ndcg_at_1000 |
|
value: 42.918 |
|
- type: ndcg_at_3 |
|
value: 42.628 |
|
- type: ndcg_at_5 |
|
value: 40.128 |
|
- type: precision_at_1 |
|
value: 47.368 |
|
- type: precision_at_10 |
|
value: 26.904 |
|
- type: precision_at_100 |
|
value: 8.334 |
|
- type: precision_at_1000 |
|
value: 2.111 |
|
- type: precision_at_3 |
|
value: 40.144000000000005 |
|
- type: precision_at_5 |
|
value: 34.489 |
|
- type: recall_at_1 |
|
value: 6.845999999999999 |
|
- type: recall_at_10 |
|
value: 18.232 |
|
- type: recall_at_100 |
|
value: 34.136 |
|
- type: recall_at_1000 |
|
value: 65.57 |
|
- type: recall_at_3 |
|
value: 11.759 |
|
- type: recall_at_5 |
|
value: 14.707999999999998 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: nq |
|
name: MTEB NQ |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 32.607 |
|
- type: map_at_10 |
|
value: 48.68 |
|
- type: map_at_100 |
|
value: 49.631 |
|
- type: map_at_1000 |
|
value: 49.653999999999996 |
|
- type: map_at_3 |
|
value: 44.174 |
|
- type: map_at_5 |
|
value: 46.865 |
|
- type: mrr_at_1 |
|
value: 36.79 |
|
- type: mrr_at_10 |
|
value: 51.156 |
|
- type: mrr_at_100 |
|
value: 51.856 |
|
- type: mrr_at_1000 |
|
value: 51.870000000000005 |
|
- type: mrr_at_3 |
|
value: 47.455999999999996 |
|
- type: mrr_at_5 |
|
value: 49.724000000000004 |
|
- type: ndcg_at_1 |
|
value: 36.79 |
|
- type: ndcg_at_10 |
|
value: 56.541 |
|
- type: ndcg_at_100 |
|
value: 60.465 |
|
- type: ndcg_at_1000 |
|
value: 61.013 |
|
- type: ndcg_at_3 |
|
value: 48.209 |
|
- type: ndcg_at_5 |
|
value: 52.644000000000005 |
|
- type: precision_at_1 |
|
value: 36.79 |
|
- type: precision_at_10 |
|
value: 9.27 |
|
- type: precision_at_100 |
|
value: 1.149 |
|
- type: precision_at_1000 |
|
value: 0.12 |
|
- type: precision_at_3 |
|
value: 21.852 |
|
- type: precision_at_5 |
|
value: 15.672 |
|
- type: recall_at_1 |
|
value: 32.607 |
|
- type: recall_at_10 |
|
value: 77.957 |
|
- type: recall_at_100 |
|
value: 94.757 |
|
- type: recall_at_1000 |
|
value: 98.832 |
|
- type: recall_at_3 |
|
value: 56.61000000000001 |
|
- type: recall_at_5 |
|
value: 66.732 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: quora |
|
name: MTEB QuoraRetrieval |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 71.949 |
|
- type: map_at_10 |
|
value: 85.863 |
|
- type: map_at_100 |
|
value: 86.491 |
|
- type: map_at_1000 |
|
value: 86.505 |
|
- type: map_at_3 |
|
value: 83.043 |
|
- type: map_at_5 |
|
value: 84.8 |
|
- type: mrr_at_1 |
|
value: 82.93 |
|
- type: mrr_at_10 |
|
value: 88.716 |
|
- type: mrr_at_100 |
|
value: 88.805 |
|
- type: mrr_at_1000 |
|
value: 88.805 |
|
- type: mrr_at_3 |
|
value: 87.848 |
|
- type: mrr_at_5 |
|
value: 88.452 |
|
- type: ndcg_at_1 |
|
value: 82.94 |
|
- type: ndcg_at_10 |
|
value: 89.396 |
|
- type: ndcg_at_100 |
|
value: 90.523 |
|
- type: ndcg_at_1000 |
|
value: 90.596 |
|
- type: ndcg_at_3 |
|
value: 86.833 |
|
- type: ndcg_at_5 |
|
value: 88.225 |
|
- type: precision_at_1 |
|
value: 82.94 |
|
- type: precision_at_10 |
|
value: 13.522 |
|
- type: precision_at_100 |
|
value: 1.5350000000000001 |
|
- type: precision_at_1000 |
|
value: 0.157 |
|
- type: precision_at_3 |
|
value: 38.019999999999996 |
|
- type: precision_at_5 |
|
value: 24.874 |
|
- type: recall_at_1 |
|
value: 71.949 |
|
- type: recall_at_10 |
|
value: 95.985 |
|
- type: recall_at_100 |
|
value: 99.705 |
|
- type: recall_at_1000 |
|
value: 99.982 |
|
- type: recall_at_3 |
|
value: 88.413 |
|
- type: recall_at_5 |
|
value: 92.532 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: mteb/reddit-clustering |
|
name: MTEB RedditClustering |
|
config: default |
|
split: test |
|
revision: 24640382cdbf8abc73003fb0fa6d111a705499eb |
|
metrics: |
|
- type: v_measure |
|
value: 58.50397537756067 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: mteb/reddit-clustering-p2p |
|
name: MTEB RedditClusteringP2P |
|
config: default |
|
split: test |
|
revision: 282350215ef01743dc01b456c7f5241fa8937f16 |
|
metrics: |
|
- type: v_measure |
|
value: 65.09111585312182 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: scidocs |
|
name: MTEB SCIDOCS |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 5.328 |
|
- type: map_at_10 |
|
value: 14.025000000000002 |
|
- type: map_at_100 |
|
value: 16.403000000000002 |
|
- type: map_at_1000 |
|
value: 16.755 |
|
- type: map_at_3 |
|
value: 10.128 |
|
- type: map_at_5 |
|
value: 12.042 |
|
- type: mrr_at_1 |
|
value: 26.3 |
|
- type: mrr_at_10 |
|
value: 38.027 |
|
- type: mrr_at_100 |
|
value: 39.112 |
|
- type: mrr_at_1000 |
|
value: 39.15 |
|
- type: mrr_at_3 |
|
value: 34.433 |
|
- type: mrr_at_5 |
|
value: 36.437999999999995 |
|
- type: ndcg_at_1 |
|
value: 26.3 |
|
- type: ndcg_at_10 |
|
value: 22.904 |
|
- type: ndcg_at_100 |
|
value: 31.808999999999997 |
|
- type: ndcg_at_1000 |
|
value: 37.408 |
|
- type: ndcg_at_3 |
|
value: 22.017999999999997 |
|
- type: ndcg_at_5 |
|
value: 19.122 |
|
- type: precision_at_1 |
|
value: 26.3 |
|
- type: precision_at_10 |
|
value: 11.84 |
|
- type: precision_at_100 |
|
value: 2.471 |
|
- type: precision_at_1000 |
|
value: 0.38 |
|
- type: precision_at_3 |
|
value: 20.767 |
|
- type: precision_at_5 |
|
value: 16.84 |
|
- type: recall_at_1 |
|
value: 5.328 |
|
- type: recall_at_10 |
|
value: 24 |
|
- type: recall_at_100 |
|
value: 50.173 |
|
- type: recall_at_1000 |
|
value: 77.22200000000001 |
|
- type: recall_at_3 |
|
value: 12.652 |
|
- type: recall_at_5 |
|
value: 17.092 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: mteb/sickr-sts |
|
name: MTEB SICK-R |
|
config: default |
|
split: test |
|
revision: a6ea5a8cab320b040a23452cc28066d9beae2cee |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 84.24083803725871 |
|
- type: cos_sim_spearman |
|
value: 81.00003675131066 |
|
- type: euclidean_pearson |
|
value: 81.66288190755017 |
|
- type: euclidean_spearman |
|
value: 80.8591677979369 |
|
- type: manhattan_pearson |
|
value: 81.65188499932559 |
|
- type: manhattan_spearman |
|
value: 80.84969273926379 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: mteb/sts12-sts |
|
name: MTEB STS12 |
|
config: default |
|
split: test |
|
revision: a0d554a64d88156834ff5ae9920b964011b16384 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 86.86245596720207 |
|
- type: cos_sim_spearman |
|
value: 79.76982315849432 |
|
- type: euclidean_pearson |
|
value: 84.08674590166918 |
|
- type: euclidean_spearman |
|
value: 79.82960710579087 |
|
- type: manhattan_pearson |
|
value: 84.05370633411236 |
|
- type: manhattan_spearman |
|
value: 79.78889972125556 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: mteb/sts13-sts |
|
name: MTEB STS13 |
|
config: default |
|
split: test |
|
revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 84.3103299403235 |
|
- type: cos_sim_spearman |
|
value: 85.4504570470498 |
|
- type: euclidean_pearson |
|
value: 84.78582379605986 |
|
- type: euclidean_spearman |
|
value: 85.42627922874793 |
|
- type: manhattan_pearson |
|
value: 84.72093039095986 |
|
- type: manhattan_spearman |
|
value: 85.37545973987105 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: mteb/sts14-sts |
|
name: MTEB STS14 |
|
config: default |
|
split: test |
|
revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 81.7811125755656 |
|
- type: cos_sim_spearman |
|
value: 82.1418064552016 |
|
- type: euclidean_pearson |
|
value: 81.76768854155489 |
|
- type: euclidean_spearman |
|
value: 81.87925885994605 |
|
- type: manhattan_pearson |
|
value: 81.73823381133532 |
|
- type: manhattan_spearman |
|
value: 81.83848324852914 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: mteb/sts15-sts |
|
name: MTEB STS15 |
|
config: default |
|
split: test |
|
revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 84.77170385298344 |
|
- type: cos_sim_spearman |
|
value: 86.6995105881395 |
|
- type: euclidean_pearson |
|
value: 86.09997193597131 |
|
- type: euclidean_spearman |
|
value: 86.6691809576152 |
|
- type: manhattan_pearson |
|
value: 86.05819223132623 |
|
- type: manhattan_spearman |
|
value: 86.63909618446979 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: mteb/sts16-sts |
|
name: MTEB STS16 |
|
config: default |
|
split: test |
|
revision: 4d8694f8f0e0100860b497b999b3dbed754a0513 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 84.42286993921634 |
|
- type: cos_sim_spearman |
|
value: 86.35209040752669 |
|
- type: euclidean_pearson |
|
value: 85.42582334105671 |
|
- type: euclidean_spearman |
|
value: 86.28412244758633 |
|
- type: manhattan_pearson |
|
value: 85.43059107029272 |
|
- type: manhattan_spearman |
|
value: 86.27090062806225 |
|
- 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: 85.27814644680406 |
|
- type: cos_sim_spearman |
|
value: 86.13269619051003 |
|
- type: euclidean_pearson |
|
value: 86.43759619681596 |
|
- type: euclidean_spearman |
|
value: 85.35609983837541 |
|
- type: manhattan_pearson |
|
value: 86.56900966648851 |
|
- type: manhattan_spearman |
|
value: 85.53334508807559 |
|
- 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: 66.53522441640088 |
|
- type: cos_sim_spearman |
|
value: 66.98460545542223 |
|
- type: euclidean_pearson |
|
value: 68.14585405221024 |
|
- type: euclidean_spearman |
|
value: 66.50486820484109 |
|
- type: manhattan_pearson |
|
value: 68.07695653374543 |
|
- type: manhattan_spearman |
|
value: 66.60229880909495 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: mteb/stsbenchmark-sts |
|
name: MTEB STSBenchmark |
|
config: default |
|
split: test |
|
revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 83.36210258340701 |
|
- type: cos_sim_spearman |
|
value: 86.27961596583953 |
|
- type: euclidean_pearson |
|
value: 85.05824596275431 |
|
- type: euclidean_spearman |
|
value: 85.95626794662996 |
|
- type: manhattan_pearson |
|
value: 85.08493690885169 |
|
- type: manhattan_spearman |
|
value: 85.97991960000013 |
|
- task: |
|
type: Reranking |
|
dataset: |
|
type: mteb/scidocs-reranking |
|
name: MTEB SciDocsRR |
|
config: default |
|
split: test |
|
revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab |
|
metrics: |
|
- type: map |
|
value: 88.05926431433953 |
|
- type: mrr |
|
value: 96.53995786348727 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: scifact |
|
name: MTEB SciFact |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 59.660999999999994 |
|
- type: map_at_10 |
|
value: 69.39999999999999 |
|
- type: map_at_100 |
|
value: 69.787 |
|
- type: map_at_1000 |
|
value: 69.82000000000001 |
|
- type: map_at_3 |
|
value: 66.43 |
|
- type: map_at_5 |
|
value: 67.989 |
|
- type: mrr_at_1 |
|
value: 63 |
|
- type: mrr_at_10 |
|
value: 70.509 |
|
- type: mrr_at_100 |
|
value: 70.792 |
|
- type: mrr_at_1000 |
|
value: 70.824 |
|
- type: mrr_at_3 |
|
value: 68.167 |
|
- type: mrr_at_5 |
|
value: 69.5 |
|
- type: ndcg_at_1 |
|
value: 63 |
|
- type: ndcg_at_10 |
|
value: 74.209 |
|
- type: ndcg_at_100 |
|
value: 75.74300000000001 |
|
- type: ndcg_at_1000 |
|
value: 76.423 |
|
- type: ndcg_at_3 |
|
value: 69.087 |
|
- type: ndcg_at_5 |
|
value: 71.42399999999999 |
|
- type: precision_at_1 |
|
value: 63 |
|
- type: precision_at_10 |
|
value: 9.966999999999999 |
|
- type: precision_at_100 |
|
value: 1.077 |
|
- type: precision_at_1000 |
|
value: 0.11299999999999999 |
|
- type: precision_at_3 |
|
value: 27.111 |
|
- type: precision_at_5 |
|
value: 17.8 |
|
- type: recall_at_1 |
|
value: 59.660999999999994 |
|
- type: recall_at_10 |
|
value: 87.922 |
|
- type: recall_at_100 |
|
value: 94.667 |
|
- type: recall_at_1000 |
|
value: 99.667 |
|
- type: recall_at_3 |
|
value: 73.906 |
|
- type: recall_at_5 |
|
value: 80.094 |
|
- task: |
|
type: PairClassification |
|
dataset: |
|
type: mteb/sprintduplicatequestions-pairclassification |
|
name: MTEB SprintDuplicateQuestions |
|
config: default |
|
split: test |
|
revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46 |
|
metrics: |
|
- type: cos_sim_accuracy |
|
value: 99.87029702970297 |
|
- type: cos_sim_ap |
|
value: 96.78080271162648 |
|
- type: cos_sim_f1 |
|
value: 93.33333333333333 |
|
- type: cos_sim_precision |
|
value: 95.02590673575129 |
|
- type: cos_sim_recall |
|
value: 91.7 |
|
- type: dot_accuracy |
|
value: 99.6960396039604 |
|
- type: dot_ap |
|
value: 91.07533824017564 |
|
- type: dot_f1 |
|
value: 84.41432720232332 |
|
- type: dot_precision |
|
value: 81.80112570356472 |
|
- type: dot_recall |
|
value: 87.2 |
|
- type: euclidean_accuracy |
|
value: 99.87425742574257 |
|
- type: euclidean_ap |
|
value: 96.82184426825803 |
|
- type: euclidean_f1 |
|
value: 93.52371239163692 |
|
- type: euclidean_precision |
|
value: 95.42143600416233 |
|
- type: euclidean_recall |
|
value: 91.7 |
|
- type: manhattan_accuracy |
|
value: 99.87425742574257 |
|
- type: manhattan_ap |
|
value: 96.84824127992334 |
|
- type: manhattan_f1 |
|
value: 93.5500253936008 |
|
- type: manhattan_precision |
|
value: 95.04643962848297 |
|
- type: manhattan_recall |
|
value: 92.10000000000001 |
|
- type: max_accuracy |
|
value: 99.87425742574257 |
|
- type: max_ap |
|
value: 96.84824127992334 |
|
- type: max_f1 |
|
value: 93.5500253936008 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: mteb/stackexchange-clustering |
|
name: MTEB StackExchangeClustering |
|
config: default |
|
split: test |
|
revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259 |
|
metrics: |
|
- type: v_measure |
|
value: 66.80646711150717 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: mteb/stackexchange-clustering-p2p |
|
name: MTEB StackExchangeClusteringP2P |
|
config: default |
|
split: test |
|
revision: 815ca46b2622cec33ccafc3735d572c266efdb44 |
|
metrics: |
|
- type: v_measure |
|
value: 35.28773452906587 |
|
- task: |
|
type: Reranking |
|
dataset: |
|
type: mteb/stackoverflowdupquestions-reranking |
|
name: MTEB StackOverflowDupQuestions |
|
config: default |
|
split: test |
|
revision: e185fbe320c72810689fc5848eb6114e1ef5ec69 |
|
metrics: |
|
- type: map |
|
value: 55.28585488417727 |
|
- type: mrr |
|
value: 56.23835519056107 |
|
- task: |
|
type: Summarization |
|
dataset: |
|
type: mteb/summeval |
|
name: MTEB SummEval |
|
config: default |
|
split: test |
|
revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 31.303110609843536 |
|
- type: cos_sim_spearman |
|
value: 32.121313527446944 |
|
- type: dot_pearson |
|
value: 28.14303657628762 |
|
- type: dot_spearman |
|
value: 27.80000491563264 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: trec-covid |
|
name: MTEB TRECCOVID |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 0.243 |
|
- type: map_at_10 |
|
value: 2.099 |
|
- type: map_at_100 |
|
value: 10.894 |
|
- type: map_at_1000 |
|
value: 24.587999999999997 |
|
- type: map_at_3 |
|
value: 0.6910000000000001 |
|
- type: map_at_5 |
|
value: 1.1039999999999999 |
|
- type: mrr_at_1 |
|
value: 90 |
|
- type: mrr_at_10 |
|
value: 94.5 |
|
- type: mrr_at_100 |
|
value: 94.5 |
|
- type: mrr_at_1000 |
|
value: 94.5 |
|
- type: mrr_at_3 |
|
value: 94 |
|
- type: mrr_at_5 |
|
value: 94.5 |
|
- type: ndcg_at_1 |
|
value: 87 |
|
- type: ndcg_at_10 |
|
value: 80.265 |
|
- type: ndcg_at_100 |
|
value: 57.371 |
|
- type: ndcg_at_1000 |
|
value: 49.147999999999996 |
|
- type: ndcg_at_3 |
|
value: 83.296 |
|
- type: ndcg_at_5 |
|
value: 82.003 |
|
- type: precision_at_1 |
|
value: 90 |
|
- type: precision_at_10 |
|
value: 85 |
|
- type: precision_at_100 |
|
value: 58.36 |
|
- type: precision_at_1000 |
|
value: 21.352 |
|
- type: precision_at_3 |
|
value: 87.333 |
|
- type: precision_at_5 |
|
value: 86.8 |
|
- type: recall_at_1 |
|
value: 0.243 |
|
- type: recall_at_10 |
|
value: 2.262 |
|
- type: recall_at_100 |
|
value: 13.919 |
|
- type: recall_at_1000 |
|
value: 45.251999999999995 |
|
- type: recall_at_3 |
|
value: 0.711 |
|
- type: recall_at_5 |
|
value: 1.162 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: webis-touche2020 |
|
name: MTEB Touche2020 |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 3.334 |
|
- type: map_at_10 |
|
value: 11.221 |
|
- type: map_at_100 |
|
value: 18.207 |
|
- type: map_at_1000 |
|
value: 19.588 |
|
- type: map_at_3 |
|
value: 6.085 |
|
- type: map_at_5 |
|
value: 8.773 |
|
- type: mrr_at_1 |
|
value: 42.857 |
|
- type: mrr_at_10 |
|
value: 55.175 |
|
- type: mrr_at_100 |
|
value: 56.133 |
|
- type: mrr_at_1000 |
|
value: 56.133 |
|
- type: mrr_at_3 |
|
value: 51.019999999999996 |
|
- type: mrr_at_5 |
|
value: 53.878 |
|
- type: ndcg_at_1 |
|
value: 39.796 |
|
- type: ndcg_at_10 |
|
value: 27.533 |
|
- type: ndcg_at_100 |
|
value: 39.823 |
|
- type: ndcg_at_1000 |
|
value: 50.412 |
|
- type: ndcg_at_3 |
|
value: 32.558 |
|
- type: ndcg_at_5 |
|
value: 31.863000000000003 |
|
- type: precision_at_1 |
|
value: 42.857 |
|
- type: precision_at_10 |
|
value: 23.673 |
|
- type: precision_at_100 |
|
value: 8.184 |
|
- type: precision_at_1000 |
|
value: 1.522 |
|
- type: precision_at_3 |
|
value: 32.653 |
|
- type: precision_at_5 |
|
value: 31.429000000000002 |
|
- type: recall_at_1 |
|
value: 3.334 |
|
- type: recall_at_10 |
|
value: 16.645 |
|
- type: recall_at_100 |
|
value: 49.876 |
|
- type: recall_at_1000 |
|
value: 82.512 |
|
- type: recall_at_3 |
|
value: 6.763 |
|
- type: recall_at_5 |
|
value: 11.461 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/toxic_conversations_50k |
|
name: MTEB ToxicConversationsClassification |
|
config: default |
|
split: test |
|
revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c |
|
metrics: |
|
- type: accuracy |
|
value: 72.1264 |
|
- type: ap |
|
value: 14.7287447276112 |
|
- type: f1 |
|
value: 55.46235112706406 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/tweet_sentiment_extraction |
|
name: MTEB TweetSentimentExtractionClassification |
|
config: default |
|
split: test |
|
revision: d604517c81ca91fe16a244d1248fc021f9ecee7a |
|
metrics: |
|
- type: accuracy |
|
value: 61.07809847198642 |
|
- type: f1 |
|
value: 61.377630233653036 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: mteb/twentynewsgroups-clustering |
|
name: MTEB TwentyNewsgroupsClustering |
|
config: default |
|
split: test |
|
revision: 6125ec4e24fa026cec8a478383ee943acfbd5449 |
|
metrics: |
|
- type: v_measure |
|
value: 54.10055371858293 |
|
- task: |
|
type: PairClassification |
|
dataset: |
|
type: mteb/twittersemeval2015-pairclassification |
|
name: MTEB TwitterSemEval2015 |
|
config: default |
|
split: test |
|
revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1 |
|
metrics: |
|
- type: cos_sim_accuracy |
|
value: 87.35769207844072 |
|
- type: cos_sim_ap |
|
value: 78.4339038750439 |
|
- type: cos_sim_f1 |
|
value: 71.50245668476856 |
|
- type: cos_sim_precision |
|
value: 70.10649087221095 |
|
- type: cos_sim_recall |
|
value: 72.95514511873351 |
|
- type: dot_accuracy |
|
value: 82.8396018358467 |
|
- type: dot_ap |
|
value: 62.120847549876125 |
|
- type: dot_f1 |
|
value: 58.371350364963504 |
|
- type: dot_precision |
|
value: 51.40618722378465 |
|
- type: dot_recall |
|
value: 67.5197889182058 |
|
- type: euclidean_accuracy |
|
value: 87.52458723252072 |
|
- type: euclidean_ap |
|
value: 78.77453300254041 |
|
- type: euclidean_f1 |
|
value: 71.625 |
|
- type: euclidean_precision |
|
value: 68.05225653206651 |
|
- type: euclidean_recall |
|
value: 75.59366754617413 |
|
- type: manhattan_accuracy |
|
value: 87.536508314955 |
|
- type: manhattan_ap |
|
value: 78.75992501489914 |
|
- type: manhattan_f1 |
|
value: 71.6182364729459 |
|
- type: manhattan_precision |
|
value: 68.16881258941345 |
|
- type: manhattan_recall |
|
value: 75.4353562005277 |
|
- type: max_accuracy |
|
value: 87.536508314955 |
|
- type: max_ap |
|
value: 78.77453300254041 |
|
- type: max_f1 |
|
value: 71.625 |
|
- task: |
|
type: PairClassification |
|
dataset: |
|
type: mteb/twitterurlcorpus-pairclassification |
|
name: MTEB TwitterURLCorpus |
|
config: default |
|
split: test |
|
revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf |
|
metrics: |
|
- type: cos_sim_accuracy |
|
value: 88.48721232584313 |
|
- type: cos_sim_ap |
|
value: 84.74350149247529 |
|
- type: cos_sim_f1 |
|
value: 76.55672345052554 |
|
- type: cos_sim_precision |
|
value: 72.32570880701273 |
|
- type: cos_sim_recall |
|
value: 81.3135201724669 |
|
- type: dot_accuracy |
|
value: 84.74599293670198 |
|
- type: dot_ap |
|
value: 75.44592372136103 |
|
- type: dot_f1 |
|
value: 69.34277843368751 |
|
- type: dot_precision |
|
value: 64.76642384548553 |
|
- type: dot_recall |
|
value: 74.61502925777641 |
|
- type: euclidean_accuracy |
|
value: 88.52020025614158 |
|
- type: euclidean_ap |
|
value: 85.01860042460612 |
|
- type: euclidean_f1 |
|
value: 76.97924816512052 |
|
- type: euclidean_precision |
|
value: 74.57590413628817 |
|
- type: euclidean_recall |
|
value: 79.54265475823837 |
|
- type: manhattan_accuracy |
|
value: 88.51049792370085 |
|
- type: manhattan_ap |
|
value: 85.03208810011937 |
|
- type: manhattan_f1 |
|
value: 77.0230840258541 |
|
- type: manhattan_precision |
|
value: 74.01859870802868 |
|
- type: manhattan_recall |
|
value: 80.28179858330768 |
|
- type: max_accuracy |
|
value: 88.52020025614158 |
|
- type: max_ap |
|
value: 85.03208810011937 |
|
- type: max_f1 |
|
value: 77.0230840258541 |
|
language: |
|
- en |
|
library_name: transformers |
|
--- |
|
|
|
# Sionic AI Embedding API v1 |
|
|
|
## About Sionic AI |
|
|
|
Sionic AI delivers more accessible and cost-effective AI technology addressing the various needs to boost productivity and drive innovation. |
|
|
|
The Large Language Model (LLM) is not for research and experimentation. |
|
We offer solutions that leverage LLM to add value to your business. |
|
Anyone can easily train and control AI. |
|
|
|
## How to get embeddings |
|
|
|
Currently, we open the beta version of embedding APIs. |
|
To get embeddings, you should call API endpoint to send your text. |
|
You can send either a single sentence or multiple sentences. |
|
The embeddings that correspond to the inputs will be returned. |
|
|
|
API Endpoint : https://api.sionic.ai/v1/embedding |
|
|
|
### Command line Example |
|
Request: |
|
```shell |
|
curl https://api.sionic.ai/v1/embedding \ |
|
-H "Content-Type: application/json" \ |
|
-d '{ |
|
"inputs": ["first query", "second query", "third query"] |
|
}' |
|
``` |
|
|
|
Response: |
|
```shell |
|
{ |
|
"embedding": [ |
|
[ |
|
0.1380517, |
|
0.0749767, |
|
-0.0600897, |
|
0.6106221, |
|
-0.3284067, |
|
... |
|
], |
|
[ |
|
-0.0237823, |
|
-0.103611, |
|
-0.0491666, |
|
0.671397, |
|
-0.8827474, |
|
... |
|
], |
|
[ |
|
0.0137392, |
|
-0.1101281, |
|
-0.2256125, |
|
0.7899137, |
|
-0.8847492, |
|
... |
|
] |
|
] |
|
} |
|
``` |
|
|
|
### Python code Example |
|
Get embeddings by directly calling Sionic's embedding API. |
|
|
|
```python |
|
from typing import List |
|
import numpy as np |
|
import requests |
|
|
|
def get_embedding(queries: List[str], url): |
|
response = requests.post(url=url, json={'inputs': queries}) |
|
return np.asarray(response.json()['embedding'], dtype=np.float32) |
|
|
|
url = "https://api.sionic.ai/v1/embedding" |
|
inputs1 = ["first query", "second query"] |
|
inputs2 = ["third query", "fourth query"] |
|
embedding1 = get_embedding(inputs1, url=url) |
|
embedding2 = get_embedding(inputs2, url=url) |
|
cos_similarity = (embedding1 / np.linalg.norm(embedding1)) @ (embedding2 / np.linalg.norm(embedding1)).T |
|
print(cos_similarity) |
|
``` |
|
|
|
Using pre-defined [SionicEmbeddingModel](https://huggingface.co/sionic-ai/sionic-ai-v1/blob/main/model_api.py) to obtain embeddings. |
|
|
|
```python |
|
from model_api import SionicEmbeddingModel |
|
import numpy as np |
|
|
|
inputs1 = ["first query", "second query"] |
|
inputs2 = ["third query", "fourth query"] |
|
model = SionicEmbeddingModel(url="https://api.sionic.ai/v1/embedding", |
|
dimension=2048) |
|
embedding1 = model.encode(inputs1) |
|
embedding2 = model.encode(inputs2) |
|
cos_similarity = (embedding1 / np.linalg.norm(embedding1)) @ (embedding2 / np.linalg.norm(embedding1)).T |
|
print(cos_similarity) |
|
``` |
|
We apply the instruction to encode short queries for retrieval tasks. |
|
By using `encode_queries()`, you can use the instruction to encode queries which is prefixed to each query as the following example. |
|
The recommended instruction for both v1 and v2 models is `"query: "`. |
|
|
|
```python |
|
from model_api import SionicEmbeddingModel |
|
import numpy as np |
|
|
|
query = ["first query", "second query"] |
|
passage = ["This is a passage related to the first query", "This is a passage related to the second query"] |
|
model = SionicEmbeddingModel(url="https://api.sionic.ai/v1/embedding", |
|
instruction="query: ", |
|
dimension=2048) |
|
query_embedding = model.encode_queries(query) |
|
passage_embedding = model.encode_corpus(passage) |
|
cos_similarity = (query_embedding / np.linalg.norm(query_embedding)) @ (passage_embedding / np.linalg.norm(passage_embedding)).T |
|
print(cos_similarity) |
|
``` |
|
|
|
## Massive Text Embedding Benchmark (MTEB) Evaluation |
|
|
|
Both versions of Sionic AI's embedding show the state-of-the-art performances on the MTEB! |
|
You can find a code to evaluate MTEB datasets [here](https://huggingface.co/sionic-ai/sionic-ai-v1/blob/main/mteb_evaluate.py). |
|
|
|
| Model Name | Dimension | Sequence Length | Average (56) | |
|
|:-----------------------------------------------------------------------:|:---------:|:---:|:------------:| |
|
| [sionic-ai/sionic-ai-v2](https://huggingface.co/sionic-ai/sionic-ai-v2) | 3072 | 512 | 65.23 | |
|
| [sionic-ai/sionic-ai-v1](https://huggingface.co/sionic-ai/sionic-ai-v1) | 2048 | 512 | **64.92** | |
|
| [bge-large-en-v1.5](https://huggingface.co/BAAI/bge-large-en-v1.5) | 1024 | 512 | 64.23 | |
|
| [gte-large-en](https://huggingface.co/barisaydin/gte-large) | 1024 | 512 | 63.13 | |
|
| [text-embedding-ada-002](https://platform.openai.com/docs/guides/embeddings/types-of-embedding-models) | 1536 | 8191 | 60.99 | |
|
|
|
|
