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--- |
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tags: |
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- mteb |
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- sentence-transformers |
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- feature-extraction |
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- sentence-similarity |
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language: en |
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license: mit |
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model-index: |
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- name: ember_v1 |
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results: |
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- task: |
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type: Classification |
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dataset: |
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type: mteb/amazon_counterfactual |
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name: MTEB AmazonCounterfactualClassification (en) |
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config: en |
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split: test |
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revision: e8379541af4e31359cca9fbcf4b00f2671dba205 |
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metrics: |
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- type: accuracy |
|
value: 76.05970149253731 |
|
- type: ap |
|
value: 38.76045348512767 |
|
- type: f1 |
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value: 69.8824007294685 |
|
- task: |
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type: Classification |
|
dataset: |
|
type: mteb/amazon_polarity |
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name: MTEB AmazonPolarityClassification |
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config: default |
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split: test |
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revision: e2d317d38cd51312af73b3d32a06d1a08b442046 |
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metrics: |
|
- type: accuracy |
|
value: 91.977 |
|
- type: ap |
|
value: 88.63507587170176 |
|
- type: f1 |
|
value: 91.9524133311038 |
|
- task: |
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type: Classification |
|
dataset: |
|
type: mteb/amazon_reviews_multi |
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name: MTEB AmazonReviewsClassification (en) |
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config: en |
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split: test |
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revision: 1399c76144fd37290681b995c656ef9b2e06e26d |
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metrics: |
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- type: accuracy |
|
value: 47.938 |
|
- type: f1 |
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value: 47.58273047536129 |
|
- task: |
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type: Retrieval |
|
dataset: |
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type: arguana |
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name: MTEB ArguAna |
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config: default |
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split: test |
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revision: None |
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metrics: |
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- type: map_at_1 |
|
value: 41.252 |
|
- type: map_at_10 |
|
value: 56.567 |
|
- type: map_at_100 |
|
value: 57.07600000000001 |
|
- type: map_at_1000 |
|
value: 57.08 |
|
- type: map_at_3 |
|
value: 52.394 |
|
- type: map_at_5 |
|
value: 55.055 |
|
- type: mrr_at_1 |
|
value: 42.39 |
|
- type: mrr_at_10 |
|
value: 57.001999999999995 |
|
- type: mrr_at_100 |
|
value: 57.531 |
|
- type: mrr_at_1000 |
|
value: 57.535000000000004 |
|
- type: mrr_at_3 |
|
value: 52.845 |
|
- type: mrr_at_5 |
|
value: 55.47299999999999 |
|
- type: ndcg_at_1 |
|
value: 41.252 |
|
- type: ndcg_at_10 |
|
value: 64.563 |
|
- type: ndcg_at_100 |
|
value: 66.667 |
|
- type: ndcg_at_1000 |
|
value: 66.77 |
|
- type: ndcg_at_3 |
|
value: 56.120000000000005 |
|
- type: ndcg_at_5 |
|
value: 60.889 |
|
- type: precision_at_1 |
|
value: 41.252 |
|
- type: precision_at_10 |
|
value: 8.982999999999999 |
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- type: precision_at_100 |
|
value: 0.989 |
|
- type: precision_at_1000 |
|
value: 0.1 |
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- type: precision_at_3 |
|
value: 22.309 |
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- type: precision_at_5 |
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value: 15.690000000000001 |
|
- type: recall_at_1 |
|
value: 41.252 |
|
- type: recall_at_10 |
|
value: 89.82900000000001 |
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- type: recall_at_100 |
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value: 98.86200000000001 |
|
- type: recall_at_1000 |
|
value: 99.644 |
|
- type: recall_at_3 |
|
value: 66.927 |
|
- type: recall_at_5 |
|
value: 78.45 |
|
- task: |
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type: Clustering |
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dataset: |
|
type: mteb/arxiv-clustering-p2p |
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name: MTEB ArxivClusteringP2P |
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config: default |
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split: test |
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revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d |
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metrics: |
|
- type: v_measure |
|
value: 48.5799968717232 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: mteb/arxiv-clustering-s2s |
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name: MTEB ArxivClusteringS2S |
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config: default |
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split: test |
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revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53 |
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metrics: |
|
- type: v_measure |
|
value: 43.142844164856136 |
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- task: |
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type: Reranking |
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dataset: |
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type: mteb/askubuntudupquestions-reranking |
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name: MTEB AskUbuntuDupQuestions |
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config: default |
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split: test |
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revision: 2000358ca161889fa9c082cb41daa8dcfb161a54 |
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metrics: |
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- type: map |
|
value: 64.45997990276463 |
|
- type: mrr |
|
value: 77.85560392208592 |
|
- task: |
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type: STS |
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dataset: |
|
type: mteb/biosses-sts |
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name: MTEB BIOSSES |
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config: default |
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split: test |
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revision: d3fb88f8f02e40887cd149695127462bbcf29b4a |
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metrics: |
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- type: cos_sim_pearson |
|
value: 86.38299310075898 |
|
- type: cos_sim_spearman |
|
value: 85.81038898286454 |
|
- type: euclidean_pearson |
|
value: 84.28002556389774 |
|
- type: euclidean_spearman |
|
value: 85.80315990248238 |
|
- type: manhattan_pearson |
|
value: 83.9755390675032 |
|
- type: manhattan_spearman |
|
value: 85.30435335611396 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/banking77 |
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name: MTEB Banking77Classification |
|
config: default |
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split: test |
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revision: 0fd18e25b25c072e09e0d92ab615fda904d66300 |
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metrics: |
|
- type: accuracy |
|
value: 87.89935064935065 |
|
- type: f1 |
|
value: 87.87886687103833 |
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- task: |
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type: Clustering |
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dataset: |
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type: mteb/biorxiv-clustering-p2p |
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name: MTEB BiorxivClusteringP2P |
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config: default |
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split: test |
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revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40 |
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metrics: |
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- type: v_measure |
|
value: 38.84335510371379 |
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- task: |
|
type: Clustering |
|
dataset: |
|
type: mteb/biorxiv-clustering-s2s |
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name: MTEB BiorxivClusteringS2S |
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config: default |
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split: test |
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revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908 |
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metrics: |
|
- type: v_measure |
|
value: 36.377963093857005 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: BeIR/cqadupstack |
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name: MTEB CQADupstackAndroidRetrieval |
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config: default |
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split: test |
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revision: None |
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metrics: |
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- type: map_at_1 |
|
value: 32.557 |
|
- type: map_at_10 |
|
value: 44.501000000000005 |
|
- type: map_at_100 |
|
value: 46.11 |
|
- type: map_at_1000 |
|
value: 46.232 |
|
- type: map_at_3 |
|
value: 40.711000000000006 |
|
- type: map_at_5 |
|
value: 42.937 |
|
- type: mrr_at_1 |
|
value: 40.916000000000004 |
|
- type: mrr_at_10 |
|
value: 51.317 |
|
- type: mrr_at_100 |
|
value: 52.003 |
|
- type: mrr_at_1000 |
|
value: 52.044999999999995 |
|
- type: mrr_at_3 |
|
value: 48.569 |
|
- type: mrr_at_5 |
|
value: 50.322 |
|
- type: ndcg_at_1 |
|
value: 40.916000000000004 |
|
- type: ndcg_at_10 |
|
value: 51.353 |
|
- type: ndcg_at_100 |
|
value: 56.762 |
|
- type: ndcg_at_1000 |
|
value: 58.555 |
|
- type: ndcg_at_3 |
|
value: 46.064 |
|
- type: ndcg_at_5 |
|
value: 48.677 |
|
- type: precision_at_1 |
|
value: 40.916000000000004 |
|
- type: precision_at_10 |
|
value: 9.927999999999999 |
|
- type: precision_at_100 |
|
value: 1.592 |
|
- type: precision_at_1000 |
|
value: 0.20600000000000002 |
|
- type: precision_at_3 |
|
value: 22.078999999999997 |
|
- type: precision_at_5 |
|
value: 16.08 |
|
- type: recall_at_1 |
|
value: 32.557 |
|
- type: recall_at_10 |
|
value: 63.942 |
|
- type: recall_at_100 |
|
value: 86.436 |
|
- type: recall_at_1000 |
|
value: 97.547 |
|
- type: recall_at_3 |
|
value: 48.367 |
|
- type: recall_at_5 |
|
value: 55.818 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: BeIR/cqadupstack |
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name: MTEB CQADupstackEnglishRetrieval |
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config: default |
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split: test |
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revision: None |
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metrics: |
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- type: map_at_1 |
|
value: 32.106 |
|
- type: map_at_10 |
|
value: 42.55 |
|
- type: map_at_100 |
|
value: 43.818 |
|
- type: map_at_1000 |
|
value: 43.952999999999996 |
|
- type: map_at_3 |
|
value: 39.421 |
|
- type: map_at_5 |
|
value: 41.276 |
|
- type: mrr_at_1 |
|
value: 39.936 |
|
- type: mrr_at_10 |
|
value: 48.484 |
|
- type: mrr_at_100 |
|
value: 49.123 |
|
- type: mrr_at_1000 |
|
value: 49.163000000000004 |
|
- type: mrr_at_3 |
|
value: 46.221000000000004 |
|
- type: mrr_at_5 |
|
value: 47.603 |
|
- type: ndcg_at_1 |
|
value: 39.936 |
|
- type: ndcg_at_10 |
|
value: 48.25 |
|
- type: ndcg_at_100 |
|
value: 52.674 |
|
- type: ndcg_at_1000 |
|
value: 54.638 |
|
- type: ndcg_at_3 |
|
value: 44.05 |
|
- type: ndcg_at_5 |
|
value: 46.125 |
|
- type: precision_at_1 |
|
value: 39.936 |
|
- type: precision_at_10 |
|
value: 9.096 |
|
- type: precision_at_100 |
|
value: 1.473 |
|
- type: precision_at_1000 |
|
value: 0.19499999999999998 |
|
- type: precision_at_3 |
|
value: 21.295 |
|
- type: precision_at_5 |
|
value: 15.121 |
|
- type: recall_at_1 |
|
value: 32.106 |
|
- type: recall_at_10 |
|
value: 58.107 |
|
- type: recall_at_100 |
|
value: 76.873 |
|
- type: recall_at_1000 |
|
value: 89.079 |
|
- type: recall_at_3 |
|
value: 45.505 |
|
- type: recall_at_5 |
|
value: 51.479 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: BeIR/cqadupstack |
|
name: MTEB CQADupstackGamingRetrieval |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 41.513 |
|
- type: map_at_10 |
|
value: 54.571999999999996 |
|
- type: map_at_100 |
|
value: 55.579 |
|
- type: map_at_1000 |
|
value: 55.626 |
|
- type: map_at_3 |
|
value: 51.127 |
|
- type: map_at_5 |
|
value: 53.151 |
|
- type: mrr_at_1 |
|
value: 47.398 |
|
- type: mrr_at_10 |
|
value: 57.82000000000001 |
|
- type: mrr_at_100 |
|
value: 58.457 |
|
- type: mrr_at_1000 |
|
value: 58.479000000000006 |
|
- type: mrr_at_3 |
|
value: 55.32899999999999 |
|
- type: mrr_at_5 |
|
value: 56.89999999999999 |
|
- type: ndcg_at_1 |
|
value: 47.398 |
|
- type: ndcg_at_10 |
|
value: 60.599000000000004 |
|
- type: ndcg_at_100 |
|
value: 64.366 |
|
- type: ndcg_at_1000 |
|
value: 65.333 |
|
- type: ndcg_at_3 |
|
value: 54.98 |
|
- type: ndcg_at_5 |
|
value: 57.874 |
|
- type: precision_at_1 |
|
value: 47.398 |
|
- type: precision_at_10 |
|
value: 9.806 |
|
- type: precision_at_100 |
|
value: 1.2590000000000001 |
|
- type: precision_at_1000 |
|
value: 0.13799999999999998 |
|
- type: precision_at_3 |
|
value: 24.619 |
|
- type: precision_at_5 |
|
value: 16.878 |
|
- type: recall_at_1 |
|
value: 41.513 |
|
- type: recall_at_10 |
|
value: 74.91799999999999 |
|
- type: recall_at_100 |
|
value: 90.96 |
|
- type: recall_at_1000 |
|
value: 97.923 |
|
- type: recall_at_3 |
|
value: 60.013000000000005 |
|
- type: recall_at_5 |
|
value: 67.245 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: BeIR/cqadupstack |
|
name: MTEB CQADupstackGisRetrieval |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 26.319 |
|
- type: map_at_10 |
|
value: 35.766999999999996 |
|
- type: map_at_100 |
|
value: 36.765 |
|
- type: map_at_1000 |
|
value: 36.829 |
|
- type: map_at_3 |
|
value: 32.888 |
|
- type: map_at_5 |
|
value: 34.538999999999994 |
|
- type: mrr_at_1 |
|
value: 28.249000000000002 |
|
- type: mrr_at_10 |
|
value: 37.766 |
|
- type: mrr_at_100 |
|
value: 38.62 |
|
- type: mrr_at_1000 |
|
value: 38.667 |
|
- type: mrr_at_3 |
|
value: 35.009 |
|
- type: mrr_at_5 |
|
value: 36.608000000000004 |
|
- type: ndcg_at_1 |
|
value: 28.249000000000002 |
|
- type: ndcg_at_10 |
|
value: 41.215 |
|
- type: ndcg_at_100 |
|
value: 46.274 |
|
- type: ndcg_at_1000 |
|
value: 48.007 |
|
- type: ndcg_at_3 |
|
value: 35.557 |
|
- type: ndcg_at_5 |
|
value: 38.344 |
|
- type: precision_at_1 |
|
value: 28.249000000000002 |
|
- type: precision_at_10 |
|
value: 6.429 |
|
- type: precision_at_100 |
|
value: 0.9480000000000001 |
|
- type: precision_at_1000 |
|
value: 0.11399999999999999 |
|
- type: precision_at_3 |
|
value: 15.179 |
|
- type: precision_at_5 |
|
value: 10.734 |
|
- type: recall_at_1 |
|
value: 26.319 |
|
- type: recall_at_10 |
|
value: 56.157999999999994 |
|
- type: recall_at_100 |
|
value: 79.65 |
|
- type: recall_at_1000 |
|
value: 92.73 |
|
- type: recall_at_3 |
|
value: 40.738 |
|
- type: recall_at_5 |
|
value: 47.418 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: BeIR/cqadupstack |
|
name: MTEB CQADupstackMathematicaRetrieval |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 18.485 |
|
- type: map_at_10 |
|
value: 27.400999999999996 |
|
- type: map_at_100 |
|
value: 28.665000000000003 |
|
- type: map_at_1000 |
|
value: 28.79 |
|
- type: map_at_3 |
|
value: 24.634 |
|
- type: map_at_5 |
|
value: 26.313 |
|
- type: mrr_at_1 |
|
value: 23.134 |
|
- type: mrr_at_10 |
|
value: 32.332 |
|
- type: mrr_at_100 |
|
value: 33.318 |
|
- type: mrr_at_1000 |
|
value: 33.384 |
|
- type: mrr_at_3 |
|
value: 29.664 |
|
- type: mrr_at_5 |
|
value: 31.262 |
|
- type: ndcg_at_1 |
|
value: 23.134 |
|
- type: ndcg_at_10 |
|
value: 33.016 |
|
- type: ndcg_at_100 |
|
value: 38.763 |
|
- type: ndcg_at_1000 |
|
value: 41.619 |
|
- type: ndcg_at_3 |
|
value: 28.017999999999997 |
|
- type: ndcg_at_5 |
|
value: 30.576999999999998 |
|
- type: precision_at_1 |
|
value: 23.134 |
|
- type: precision_at_10 |
|
value: 6.069999999999999 |
|
- type: precision_at_100 |
|
value: 1.027 |
|
- type: precision_at_1000 |
|
value: 0.14200000000000002 |
|
- type: precision_at_3 |
|
value: 13.599 |
|
- type: precision_at_5 |
|
value: 9.975000000000001 |
|
- type: recall_at_1 |
|
value: 18.485 |
|
- type: recall_at_10 |
|
value: 45.39 |
|
- type: recall_at_100 |
|
value: 69.876 |
|
- type: recall_at_1000 |
|
value: 90.023 |
|
- type: recall_at_3 |
|
value: 31.587 |
|
- type: recall_at_5 |
|
value: 38.164 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: BeIR/cqadupstack |
|
name: MTEB CQADupstackPhysicsRetrieval |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 30.676 |
|
- type: map_at_10 |
|
value: 41.785 |
|
- type: map_at_100 |
|
value: 43.169000000000004 |
|
- type: map_at_1000 |
|
value: 43.272 |
|
- type: map_at_3 |
|
value: 38.462 |
|
- type: map_at_5 |
|
value: 40.32 |
|
- type: mrr_at_1 |
|
value: 37.729 |
|
- type: mrr_at_10 |
|
value: 47.433 |
|
- type: mrr_at_100 |
|
value: 48.303000000000004 |
|
- type: mrr_at_1000 |
|
value: 48.337 |
|
- type: mrr_at_3 |
|
value: 45.011 |
|
- type: mrr_at_5 |
|
value: 46.455 |
|
- type: ndcg_at_1 |
|
value: 37.729 |
|
- type: ndcg_at_10 |
|
value: 47.921 |
|
- type: ndcg_at_100 |
|
value: 53.477 |
|
- type: ndcg_at_1000 |
|
value: 55.300000000000004 |
|
- type: ndcg_at_3 |
|
value: 42.695 |
|
- type: ndcg_at_5 |
|
value: 45.175 |
|
- type: precision_at_1 |
|
value: 37.729 |
|
- type: precision_at_10 |
|
value: 8.652999999999999 |
|
- type: precision_at_100 |
|
value: 1.336 |
|
- type: precision_at_1000 |
|
value: 0.168 |
|
- type: precision_at_3 |
|
value: 20.18 |
|
- type: precision_at_5 |
|
value: 14.302000000000001 |
|
- type: recall_at_1 |
|
value: 30.676 |
|
- type: recall_at_10 |
|
value: 60.441 |
|
- type: recall_at_100 |
|
value: 83.37 |
|
- type: recall_at_1000 |
|
value: 95.092 |
|
- type: recall_at_3 |
|
value: 45.964 |
|
- type: recall_at_5 |
|
value: 52.319 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: BeIR/cqadupstack |
|
name: MTEB CQADupstackProgrammersRetrieval |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 24.978 |
|
- type: map_at_10 |
|
value: 35.926 |
|
- type: map_at_100 |
|
value: 37.341 |
|
- type: map_at_1000 |
|
value: 37.445 |
|
- type: map_at_3 |
|
value: 32.748 |
|
- type: map_at_5 |
|
value: 34.207 |
|
- type: mrr_at_1 |
|
value: 31.163999999999998 |
|
- type: mrr_at_10 |
|
value: 41.394 |
|
- type: mrr_at_100 |
|
value: 42.321 |
|
- type: mrr_at_1000 |
|
value: 42.368 |
|
- type: mrr_at_3 |
|
value: 38.964999999999996 |
|
- type: mrr_at_5 |
|
value: 40.135 |
|
- type: ndcg_at_1 |
|
value: 31.163999999999998 |
|
- type: ndcg_at_10 |
|
value: 42.191 |
|
- type: ndcg_at_100 |
|
value: 48.083999999999996 |
|
- type: ndcg_at_1000 |
|
value: 50.21 |
|
- type: ndcg_at_3 |
|
value: 36.979 |
|
- type: ndcg_at_5 |
|
value: 38.823 |
|
- type: precision_at_1 |
|
value: 31.163999999999998 |
|
- type: precision_at_10 |
|
value: 7.968 |
|
- type: precision_at_100 |
|
value: 1.2550000000000001 |
|
- type: precision_at_1000 |
|
value: 0.16199999999999998 |
|
- type: precision_at_3 |
|
value: 18.075 |
|
- type: precision_at_5 |
|
value: 12.626000000000001 |
|
- type: recall_at_1 |
|
value: 24.978 |
|
- type: recall_at_10 |
|
value: 55.410000000000004 |
|
- type: recall_at_100 |
|
value: 80.562 |
|
- type: recall_at_1000 |
|
value: 94.77600000000001 |
|
- type: recall_at_3 |
|
value: 40.359 |
|
- type: recall_at_5 |
|
value: 45.577 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: BeIR/cqadupstack |
|
name: MTEB CQADupstackRetrieval |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 26.812166666666666 |
|
- type: map_at_10 |
|
value: 36.706916666666665 |
|
- type: map_at_100 |
|
value: 37.94016666666666 |
|
- type: map_at_1000 |
|
value: 38.05358333333333 |
|
- type: map_at_3 |
|
value: 33.72408333333334 |
|
- type: map_at_5 |
|
value: 35.36508333333333 |
|
- type: mrr_at_1 |
|
value: 31.91516666666667 |
|
- type: mrr_at_10 |
|
value: 41.09716666666666 |
|
- type: mrr_at_100 |
|
value: 41.931916666666666 |
|
- type: mrr_at_1000 |
|
value: 41.98458333333333 |
|
- type: mrr_at_3 |
|
value: 38.60183333333333 |
|
- type: mrr_at_5 |
|
value: 40.031916666666675 |
|
- type: ndcg_at_1 |
|
value: 31.91516666666667 |
|
- type: ndcg_at_10 |
|
value: 42.38725 |
|
- type: ndcg_at_100 |
|
value: 47.56291666666667 |
|
- type: ndcg_at_1000 |
|
value: 49.716499999999996 |
|
- type: ndcg_at_3 |
|
value: 37.36491666666667 |
|
- type: ndcg_at_5 |
|
value: 39.692166666666665 |
|
- type: precision_at_1 |
|
value: 31.91516666666667 |
|
- type: precision_at_10 |
|
value: 7.476749999999999 |
|
- type: precision_at_100 |
|
value: 1.1869166666666668 |
|
- type: precision_at_1000 |
|
value: 0.157 |
|
- type: precision_at_3 |
|
value: 17.275249999999996 |
|
- type: precision_at_5 |
|
value: 12.25825 |
|
- type: recall_at_1 |
|
value: 26.812166666666666 |
|
- type: recall_at_10 |
|
value: 54.82933333333333 |
|
- type: recall_at_100 |
|
value: 77.36508333333333 |
|
- type: recall_at_1000 |
|
value: 92.13366666666667 |
|
- type: recall_at_3 |
|
value: 40.83508333333334 |
|
- type: recall_at_5 |
|
value: 46.85083333333334 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: BeIR/cqadupstack |
|
name: MTEB CQADupstackStatsRetrieval |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 25.352999999999998 |
|
- type: map_at_10 |
|
value: 33.025999999999996 |
|
- type: map_at_100 |
|
value: 33.882 |
|
- type: map_at_1000 |
|
value: 33.983999999999995 |
|
- type: map_at_3 |
|
value: 30.995 |
|
- type: map_at_5 |
|
value: 32.113 |
|
- type: mrr_at_1 |
|
value: 28.834 |
|
- type: mrr_at_10 |
|
value: 36.14 |
|
- type: mrr_at_100 |
|
value: 36.815 |
|
- type: mrr_at_1000 |
|
value: 36.893 |
|
- type: mrr_at_3 |
|
value: 34.305 |
|
- type: mrr_at_5 |
|
value: 35.263 |
|
- type: ndcg_at_1 |
|
value: 28.834 |
|
- type: ndcg_at_10 |
|
value: 37.26 |
|
- type: ndcg_at_100 |
|
value: 41.723 |
|
- type: ndcg_at_1000 |
|
value: 44.314 |
|
- type: ndcg_at_3 |
|
value: 33.584 |
|
- type: ndcg_at_5 |
|
value: 35.302 |
|
- type: precision_at_1 |
|
value: 28.834 |
|
- type: precision_at_10 |
|
value: 5.736 |
|
- type: precision_at_100 |
|
value: 0.876 |
|
- type: precision_at_1000 |
|
value: 0.117 |
|
- type: precision_at_3 |
|
value: 14.468 |
|
- type: precision_at_5 |
|
value: 9.847 |
|
- type: recall_at_1 |
|
value: 25.352999999999998 |
|
- type: recall_at_10 |
|
value: 47.155 |
|
- type: recall_at_100 |
|
value: 68.024 |
|
- type: recall_at_1000 |
|
value: 87.26899999999999 |
|
- type: recall_at_3 |
|
value: 37.074 |
|
- type: recall_at_5 |
|
value: 41.352 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: BeIR/cqadupstack |
|
name: MTEB CQADupstackTexRetrieval |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 17.845 |
|
- type: map_at_10 |
|
value: 25.556 |
|
- type: map_at_100 |
|
value: 26.787 |
|
- type: map_at_1000 |
|
value: 26.913999999999998 |
|
- type: map_at_3 |
|
value: 23.075000000000003 |
|
- type: map_at_5 |
|
value: 24.308 |
|
- type: mrr_at_1 |
|
value: 21.714 |
|
- type: mrr_at_10 |
|
value: 29.543999999999997 |
|
- type: mrr_at_100 |
|
value: 30.543 |
|
- type: mrr_at_1000 |
|
value: 30.618000000000002 |
|
- type: mrr_at_3 |
|
value: 27.174 |
|
- type: mrr_at_5 |
|
value: 28.409000000000002 |
|
- type: ndcg_at_1 |
|
value: 21.714 |
|
- type: ndcg_at_10 |
|
value: 30.562 |
|
- type: ndcg_at_100 |
|
value: 36.27 |
|
- type: ndcg_at_1000 |
|
value: 39.033 |
|
- type: ndcg_at_3 |
|
value: 26.006 |
|
- type: ndcg_at_5 |
|
value: 27.843 |
|
- type: precision_at_1 |
|
value: 21.714 |
|
- type: precision_at_10 |
|
value: 5.657 |
|
- type: precision_at_100 |
|
value: 1.0 |
|
- type: precision_at_1000 |
|
value: 0.14100000000000001 |
|
- type: precision_at_3 |
|
value: 12.4 |
|
- type: precision_at_5 |
|
value: 8.863999999999999 |
|
- type: recall_at_1 |
|
value: 17.845 |
|
- type: recall_at_10 |
|
value: 41.72 |
|
- type: recall_at_100 |
|
value: 67.06400000000001 |
|
- type: recall_at_1000 |
|
value: 86.515 |
|
- type: recall_at_3 |
|
value: 28.78 |
|
- type: recall_at_5 |
|
value: 33.629999999999995 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: BeIR/cqadupstack |
|
name: MTEB CQADupstackUnixRetrieval |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 26.695 |
|
- type: map_at_10 |
|
value: 36.205999999999996 |
|
- type: map_at_100 |
|
value: 37.346000000000004 |
|
- type: map_at_1000 |
|
value: 37.447 |
|
- type: map_at_3 |
|
value: 32.84 |
|
- type: map_at_5 |
|
value: 34.733000000000004 |
|
- type: mrr_at_1 |
|
value: 31.343 |
|
- type: mrr_at_10 |
|
value: 40.335 |
|
- type: mrr_at_100 |
|
value: 41.162 |
|
- type: mrr_at_1000 |
|
value: 41.221000000000004 |
|
- type: mrr_at_3 |
|
value: 37.329 |
|
- type: mrr_at_5 |
|
value: 39.068999999999996 |
|
- type: ndcg_at_1 |
|
value: 31.343 |
|
- type: ndcg_at_10 |
|
value: 41.996 |
|
- type: ndcg_at_100 |
|
value: 47.096 |
|
- type: ndcg_at_1000 |
|
value: 49.4 |
|
- type: ndcg_at_3 |
|
value: 35.902 |
|
- type: ndcg_at_5 |
|
value: 38.848 |
|
- type: precision_at_1 |
|
value: 31.343 |
|
- type: precision_at_10 |
|
value: 7.146 |
|
- type: precision_at_100 |
|
value: 1.098 |
|
- type: precision_at_1000 |
|
value: 0.14100000000000001 |
|
- type: precision_at_3 |
|
value: 16.014 |
|
- type: precision_at_5 |
|
value: 11.735 |
|
- type: recall_at_1 |
|
value: 26.695 |
|
- type: recall_at_10 |
|
value: 55.525000000000006 |
|
- type: recall_at_100 |
|
value: 77.376 |
|
- type: recall_at_1000 |
|
value: 93.476 |
|
- type: recall_at_3 |
|
value: 39.439 |
|
- type: recall_at_5 |
|
value: 46.501 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: BeIR/cqadupstack |
|
name: MTEB CQADupstackWebmastersRetrieval |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 24.196 |
|
- type: map_at_10 |
|
value: 33.516 |
|
- type: map_at_100 |
|
value: 35.202 |
|
- type: map_at_1000 |
|
value: 35.426 |
|
- type: map_at_3 |
|
value: 30.561 |
|
- type: map_at_5 |
|
value: 31.961000000000002 |
|
- type: mrr_at_1 |
|
value: 29.644 |
|
- type: mrr_at_10 |
|
value: 38.769 |
|
- type: mrr_at_100 |
|
value: 39.843 |
|
- type: mrr_at_1000 |
|
value: 39.888 |
|
- type: mrr_at_3 |
|
value: 36.132999999999996 |
|
- type: mrr_at_5 |
|
value: 37.467 |
|
- type: ndcg_at_1 |
|
value: 29.644 |
|
- type: ndcg_at_10 |
|
value: 39.584 |
|
- type: ndcg_at_100 |
|
value: 45.964 |
|
- type: ndcg_at_1000 |
|
value: 48.27 |
|
- type: ndcg_at_3 |
|
value: 34.577999999999996 |
|
- type: ndcg_at_5 |
|
value: 36.498000000000005 |
|
- type: precision_at_1 |
|
value: 29.644 |
|
- type: precision_at_10 |
|
value: 7.668 |
|
- type: precision_at_100 |
|
value: 1.545 |
|
- type: precision_at_1000 |
|
value: 0.242 |
|
- type: precision_at_3 |
|
value: 16.271 |
|
- type: precision_at_5 |
|
value: 11.620999999999999 |
|
- type: recall_at_1 |
|
value: 24.196 |
|
- type: recall_at_10 |
|
value: 51.171 |
|
- type: recall_at_100 |
|
value: 79.212 |
|
- type: recall_at_1000 |
|
value: 92.976 |
|
- type: recall_at_3 |
|
value: 36.797999999999995 |
|
- type: recall_at_5 |
|
value: 42.006 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: BeIR/cqadupstack |
|
name: MTEB CQADupstackWordpressRetrieval |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 21.023 |
|
- type: map_at_10 |
|
value: 29.677 |
|
- type: map_at_100 |
|
value: 30.618000000000002 |
|
- type: map_at_1000 |
|
value: 30.725 |
|
- type: map_at_3 |
|
value: 27.227 |
|
- type: map_at_5 |
|
value: 28.523 |
|
- type: mrr_at_1 |
|
value: 22.921 |
|
- type: mrr_at_10 |
|
value: 31.832 |
|
- type: mrr_at_100 |
|
value: 32.675 |
|
- type: mrr_at_1000 |
|
value: 32.751999999999995 |
|
- type: mrr_at_3 |
|
value: 29.513 |
|
- type: mrr_at_5 |
|
value: 30.89 |
|
- type: ndcg_at_1 |
|
value: 22.921 |
|
- type: ndcg_at_10 |
|
value: 34.699999999999996 |
|
- type: ndcg_at_100 |
|
value: 39.302 |
|
- type: ndcg_at_1000 |
|
value: 41.919000000000004 |
|
- type: ndcg_at_3 |
|
value: 29.965999999999998 |
|
- type: ndcg_at_5 |
|
value: 32.22 |
|
- type: precision_at_1 |
|
value: 22.921 |
|
- type: precision_at_10 |
|
value: 5.564 |
|
- type: precision_at_100 |
|
value: 0.8340000000000001 |
|
- type: precision_at_1000 |
|
value: 0.11800000000000001 |
|
- type: precision_at_3 |
|
value: 13.123999999999999 |
|
- type: precision_at_5 |
|
value: 9.316 |
|
- type: recall_at_1 |
|
value: 21.023 |
|
- type: recall_at_10 |
|
value: 48.015 |
|
- type: recall_at_100 |
|
value: 68.978 |
|
- type: recall_at_1000 |
|
value: 88.198 |
|
- type: recall_at_3 |
|
value: 35.397 |
|
- type: recall_at_5 |
|
value: 40.701 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: climate-fever |
|
name: MTEB ClimateFEVER |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 11.198 |
|
- type: map_at_10 |
|
value: 19.336000000000002 |
|
- type: map_at_100 |
|
value: 21.382 |
|
- type: map_at_1000 |
|
value: 21.581 |
|
- type: map_at_3 |
|
value: 15.992 |
|
- type: map_at_5 |
|
value: 17.613 |
|
- type: mrr_at_1 |
|
value: 25.080999999999996 |
|
- type: mrr_at_10 |
|
value: 36.032 |
|
- type: mrr_at_100 |
|
value: 37.1 |
|
- type: mrr_at_1000 |
|
value: 37.145 |
|
- type: mrr_at_3 |
|
value: 32.595 |
|
- type: mrr_at_5 |
|
value: 34.553 |
|
- type: ndcg_at_1 |
|
value: 25.080999999999996 |
|
- type: ndcg_at_10 |
|
value: 27.290999999999997 |
|
- type: ndcg_at_100 |
|
value: 35.31 |
|
- type: ndcg_at_1000 |
|
value: 38.885 |
|
- type: ndcg_at_3 |
|
value: 21.895999999999997 |
|
- type: ndcg_at_5 |
|
value: 23.669999999999998 |
|
- type: precision_at_1 |
|
value: 25.080999999999996 |
|
- type: precision_at_10 |
|
value: 8.645 |
|
- type: precision_at_100 |
|
value: 1.7209999999999999 |
|
- type: precision_at_1000 |
|
value: 0.23900000000000002 |
|
- type: precision_at_3 |
|
value: 16.287 |
|
- type: precision_at_5 |
|
value: 12.625 |
|
- type: recall_at_1 |
|
value: 11.198 |
|
- type: recall_at_10 |
|
value: 33.355000000000004 |
|
- type: recall_at_100 |
|
value: 60.912 |
|
- type: recall_at_1000 |
|
value: 80.89 |
|
- type: recall_at_3 |
|
value: 20.055 |
|
- type: recall_at_5 |
|
value: 25.14 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: dbpedia-entity |
|
name: MTEB DBPedia |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 9.228 |
|
- type: map_at_10 |
|
value: 20.018 |
|
- type: map_at_100 |
|
value: 28.388999999999996 |
|
- type: map_at_1000 |
|
value: 30.073 |
|
- type: map_at_3 |
|
value: 14.366999999999999 |
|
- type: map_at_5 |
|
value: 16.705000000000002 |
|
- type: mrr_at_1 |
|
value: 69.0 |
|
- type: mrr_at_10 |
|
value: 77.058 |
|
- type: mrr_at_100 |
|
value: 77.374 |
|
- type: mrr_at_1000 |
|
value: 77.384 |
|
- type: mrr_at_3 |
|
value: 75.708 |
|
- type: mrr_at_5 |
|
value: 76.608 |
|
- type: ndcg_at_1 |
|
value: 57.49999999999999 |
|
- type: ndcg_at_10 |
|
value: 41.792 |
|
- type: ndcg_at_100 |
|
value: 47.374 |
|
- type: ndcg_at_1000 |
|
value: 55.13 |
|
- type: ndcg_at_3 |
|
value: 46.353 |
|
- type: ndcg_at_5 |
|
value: 43.702000000000005 |
|
- type: precision_at_1 |
|
value: 69.0 |
|
- type: precision_at_10 |
|
value: 32.85 |
|
- type: precision_at_100 |
|
value: 10.708 |
|
- type: precision_at_1000 |
|
value: 2.024 |
|
- type: precision_at_3 |
|
value: 49.5 |
|
- type: precision_at_5 |
|
value: 42.05 |
|
- type: recall_at_1 |
|
value: 9.228 |
|
- type: recall_at_10 |
|
value: 25.635 |
|
- type: recall_at_100 |
|
value: 54.894 |
|
- type: recall_at_1000 |
|
value: 79.38 |
|
- type: recall_at_3 |
|
value: 15.68 |
|
- type: recall_at_5 |
|
value: 19.142 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/emotion |
|
name: MTEB EmotionClassification |
|
config: default |
|
split: test |
|
revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37 |
|
metrics: |
|
- type: accuracy |
|
value: 52.035 |
|
- type: f1 |
|
value: 46.85325505614071 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: fever |
|
name: MTEB FEVER |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 70.132 |
|
- type: map_at_10 |
|
value: 79.527 |
|
- type: map_at_100 |
|
value: 79.81200000000001 |
|
- type: map_at_1000 |
|
value: 79.828 |
|
- type: map_at_3 |
|
value: 78.191 |
|
- type: map_at_5 |
|
value: 79.092 |
|
- type: mrr_at_1 |
|
value: 75.563 |
|
- type: mrr_at_10 |
|
value: 83.80199999999999 |
|
- type: mrr_at_100 |
|
value: 83.93 |
|
- type: mrr_at_1000 |
|
value: 83.933 |
|
- type: mrr_at_3 |
|
value: 82.818 |
|
- type: mrr_at_5 |
|
value: 83.505 |
|
- type: ndcg_at_1 |
|
value: 75.563 |
|
- type: ndcg_at_10 |
|
value: 83.692 |
|
- type: ndcg_at_100 |
|
value: 84.706 |
|
- type: ndcg_at_1000 |
|
value: 85.001 |
|
- type: ndcg_at_3 |
|
value: 81.51 |
|
- type: ndcg_at_5 |
|
value: 82.832 |
|
- type: precision_at_1 |
|
value: 75.563 |
|
- type: precision_at_10 |
|
value: 10.245 |
|
- type: precision_at_100 |
|
value: 1.0959999999999999 |
|
- type: precision_at_1000 |
|
value: 0.11399999999999999 |
|
- type: precision_at_3 |
|
value: 31.518 |
|
- type: precision_at_5 |
|
value: 19.772000000000002 |
|
- type: recall_at_1 |
|
value: 70.132 |
|
- type: recall_at_10 |
|
value: 92.204 |
|
- type: recall_at_100 |
|
value: 96.261 |
|
- type: recall_at_1000 |
|
value: 98.17399999999999 |
|
- type: recall_at_3 |
|
value: 86.288 |
|
- type: recall_at_5 |
|
value: 89.63799999999999 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: fiqa |
|
name: MTEB FiQA2018 |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 22.269 |
|
- type: map_at_10 |
|
value: 36.042 |
|
- type: map_at_100 |
|
value: 37.988 |
|
- type: map_at_1000 |
|
value: 38.162 |
|
- type: map_at_3 |
|
value: 31.691000000000003 |
|
- type: map_at_5 |
|
value: 33.988 |
|
- type: mrr_at_1 |
|
value: 44.907000000000004 |
|
- type: mrr_at_10 |
|
value: 53.348 |
|
- type: mrr_at_100 |
|
value: 54.033 |
|
- type: mrr_at_1000 |
|
value: 54.064 |
|
- type: mrr_at_3 |
|
value: 50.977 |
|
- type: mrr_at_5 |
|
value: 52.112 |
|
- type: ndcg_at_1 |
|
value: 44.907000000000004 |
|
- type: ndcg_at_10 |
|
value: 44.302 |
|
- type: ndcg_at_100 |
|
value: 51.054 |
|
- type: ndcg_at_1000 |
|
value: 53.822 |
|
- type: ndcg_at_3 |
|
value: 40.615 |
|
- type: ndcg_at_5 |
|
value: 41.455999999999996 |
|
- type: precision_at_1 |
|
value: 44.907000000000004 |
|
- type: precision_at_10 |
|
value: 12.176 |
|
- type: precision_at_100 |
|
value: 1.931 |
|
- type: precision_at_1000 |
|
value: 0.243 |
|
- type: precision_at_3 |
|
value: 27.16 |
|
- type: precision_at_5 |
|
value: 19.567999999999998 |
|
- type: recall_at_1 |
|
value: 22.269 |
|
- type: recall_at_10 |
|
value: 51.188 |
|
- type: recall_at_100 |
|
value: 75.924 |
|
- type: recall_at_1000 |
|
value: 92.525 |
|
- type: recall_at_3 |
|
value: 36.643 |
|
- type: recall_at_5 |
|
value: 42.27 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: hotpotqa |
|
name: MTEB HotpotQA |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 40.412 |
|
- type: map_at_10 |
|
value: 66.376 |
|
- type: map_at_100 |
|
value: 67.217 |
|
- type: map_at_1000 |
|
value: 67.271 |
|
- type: map_at_3 |
|
value: 62.741 |
|
- type: map_at_5 |
|
value: 65.069 |
|
- type: mrr_at_1 |
|
value: 80.824 |
|
- type: mrr_at_10 |
|
value: 86.53 |
|
- type: mrr_at_100 |
|
value: 86.67399999999999 |
|
- type: mrr_at_1000 |
|
value: 86.678 |
|
- type: mrr_at_3 |
|
value: 85.676 |
|
- type: mrr_at_5 |
|
value: 86.256 |
|
- type: ndcg_at_1 |
|
value: 80.824 |
|
- type: ndcg_at_10 |
|
value: 74.332 |
|
- type: ndcg_at_100 |
|
value: 77.154 |
|
- type: ndcg_at_1000 |
|
value: 78.12400000000001 |
|
- type: ndcg_at_3 |
|
value: 69.353 |
|
- type: ndcg_at_5 |
|
value: 72.234 |
|
- type: precision_at_1 |
|
value: 80.824 |
|
- type: precision_at_10 |
|
value: 15.652 |
|
- type: precision_at_100 |
|
value: 1.7840000000000003 |
|
- type: precision_at_1000 |
|
value: 0.191 |
|
- type: precision_at_3 |
|
value: 44.911 |
|
- type: precision_at_5 |
|
value: 29.221000000000004 |
|
- type: recall_at_1 |
|
value: 40.412 |
|
- type: recall_at_10 |
|
value: 78.25800000000001 |
|
- type: recall_at_100 |
|
value: 89.196 |
|
- type: recall_at_1000 |
|
value: 95.544 |
|
- type: recall_at_3 |
|
value: 67.367 |
|
- type: recall_at_5 |
|
value: 73.05199999999999 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/imdb |
|
name: MTEB ImdbClassification |
|
config: default |
|
split: test |
|
revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7 |
|
metrics: |
|
- type: accuracy |
|
value: 92.78880000000001 |
|
- type: ap |
|
value: 89.39251741048801 |
|
- type: f1 |
|
value: 92.78019950076781 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: msmarco |
|
name: MTEB MSMARCO |
|
config: default |
|
split: dev |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 22.888 |
|
- type: map_at_10 |
|
value: 35.146 |
|
- type: map_at_100 |
|
value: 36.325 |
|
- type: map_at_1000 |
|
value: 36.372 |
|
- type: map_at_3 |
|
value: 31.3 |
|
- type: map_at_5 |
|
value: 33.533 |
|
- type: mrr_at_1 |
|
value: 23.480999999999998 |
|
- type: mrr_at_10 |
|
value: 35.777 |
|
- type: mrr_at_100 |
|
value: 36.887 |
|
- type: mrr_at_1000 |
|
value: 36.928 |
|
- type: mrr_at_3 |
|
value: 31.989 |
|
- type: mrr_at_5 |
|
value: 34.202 |
|
- type: ndcg_at_1 |
|
value: 23.496 |
|
- type: ndcg_at_10 |
|
value: 42.028999999999996 |
|
- type: ndcg_at_100 |
|
value: 47.629 |
|
- type: ndcg_at_1000 |
|
value: 48.785000000000004 |
|
- type: ndcg_at_3 |
|
value: 34.227000000000004 |
|
- type: ndcg_at_5 |
|
value: 38.207 |
|
- type: precision_at_1 |
|
value: 23.496 |
|
- type: precision_at_10 |
|
value: 6.596 |
|
- type: precision_at_100 |
|
value: 0.9400000000000001 |
|
- type: precision_at_1000 |
|
value: 0.104 |
|
- type: precision_at_3 |
|
value: 14.513000000000002 |
|
- type: precision_at_5 |
|
value: 10.711 |
|
- type: recall_at_1 |
|
value: 22.888 |
|
- type: recall_at_10 |
|
value: 63.129999999999995 |
|
- type: recall_at_100 |
|
value: 88.90299999999999 |
|
- type: recall_at_1000 |
|
value: 97.69 |
|
- type: recall_at_3 |
|
value: 42.014 |
|
- type: recall_at_5 |
|
value: 51.554 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/mtop_domain |
|
name: MTEB MTOPDomainClassification (en) |
|
config: en |
|
split: test |
|
revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf |
|
metrics: |
|
- type: accuracy |
|
value: 94.59188326493388 |
|
- type: f1 |
|
value: 94.36568950290486 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/mtop_intent |
|
name: MTEB MTOPIntentClassification (en) |
|
config: en |
|
split: test |
|
revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba |
|
metrics: |
|
- type: accuracy |
|
value: 79.25672594619242 |
|
- type: f1 |
|
value: 59.52405059722216 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/amazon_massive_intent |
|
name: MTEB MassiveIntentClassification (en) |
|
config: en |
|
split: test |
|
revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 |
|
metrics: |
|
- type: accuracy |
|
value: 77.4142568930733 |
|
- type: f1 |
|
value: 75.23044196543388 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/amazon_massive_scenario |
|
name: MTEB MassiveScenarioClassification (en) |
|
config: en |
|
split: test |
|
revision: 7d571f92784cd94a019292a1f45445077d0ef634 |
|
metrics: |
|
- type: accuracy |
|
value: 80.44720914593141 |
|
- type: f1 |
|
value: 80.41049641537015 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: mteb/medrxiv-clustering-p2p |
|
name: MTEB MedrxivClusteringP2P |
|
config: default |
|
split: test |
|
revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73 |
|
metrics: |
|
- type: v_measure |
|
value: 31.960921474993775 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: mteb/medrxiv-clustering-s2s |
|
name: MTEB MedrxivClusteringS2S |
|
config: default |
|
split: test |
|
revision: 35191c8c0dca72d8ff3efcd72aa802307d469663 |
|
metrics: |
|
- type: v_measure |
|
value: 30.88042240204361 |
|
- task: |
|
type: Reranking |
|
dataset: |
|
type: mteb/mind_small |
|
name: MTEB MindSmallReranking |
|
config: default |
|
split: test |
|
revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69 |
|
metrics: |
|
- type: map |
|
value: 32.27071371606404 |
|
- type: mrr |
|
value: 33.541450459533856 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: nfcorpus |
|
name: MTEB NFCorpus |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 6.551 |
|
- type: map_at_10 |
|
value: 14.359 |
|
- type: map_at_100 |
|
value: 18.157 |
|
- type: map_at_1000 |
|
value: 19.659 |
|
- type: map_at_3 |
|
value: 10.613999999999999 |
|
- type: map_at_5 |
|
value: 12.296 |
|
- type: mrr_at_1 |
|
value: 47.368 |
|
- type: mrr_at_10 |
|
value: 56.689 |
|
- type: mrr_at_100 |
|
value: 57.24399999999999 |
|
- type: mrr_at_1000 |
|
value: 57.284 |
|
- type: mrr_at_3 |
|
value: 54.489 |
|
- type: mrr_at_5 |
|
value: 55.928999999999995 |
|
- type: ndcg_at_1 |
|
value: 45.511 |
|
- type: ndcg_at_10 |
|
value: 36.911 |
|
- type: ndcg_at_100 |
|
value: 34.241 |
|
- type: ndcg_at_1000 |
|
value: 43.064 |
|
- type: ndcg_at_3 |
|
value: 42.348 |
|
- type: ndcg_at_5 |
|
value: 39.884 |
|
- type: precision_at_1 |
|
value: 46.749 |
|
- type: precision_at_10 |
|
value: 27.028000000000002 |
|
- type: precision_at_100 |
|
value: 8.52 |
|
- type: precision_at_1000 |
|
value: 2.154 |
|
- type: precision_at_3 |
|
value: 39.525 |
|
- type: precision_at_5 |
|
value: 34.18 |
|
- type: recall_at_1 |
|
value: 6.551 |
|
- type: recall_at_10 |
|
value: 18.602 |
|
- type: recall_at_100 |
|
value: 34.882999999999996 |
|
- type: recall_at_1000 |
|
value: 66.049 |
|
- type: recall_at_3 |
|
value: 11.872 |
|
- type: recall_at_5 |
|
value: 14.74 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: nq |
|
name: MTEB NQ |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 27.828999999999997 |
|
- type: map_at_10 |
|
value: 43.606 |
|
- type: map_at_100 |
|
value: 44.656 |
|
- type: map_at_1000 |
|
value: 44.690000000000005 |
|
- type: map_at_3 |
|
value: 39.015 |
|
- type: map_at_5 |
|
value: 41.625 |
|
- type: mrr_at_1 |
|
value: 31.518 |
|
- type: mrr_at_10 |
|
value: 46.047 |
|
- type: mrr_at_100 |
|
value: 46.846 |
|
- type: mrr_at_1000 |
|
value: 46.867999999999995 |
|
- type: mrr_at_3 |
|
value: 42.154 |
|
- type: mrr_at_5 |
|
value: 44.468999999999994 |
|
- type: ndcg_at_1 |
|
value: 31.518 |
|
- type: ndcg_at_10 |
|
value: 51.768 |
|
- type: ndcg_at_100 |
|
value: 56.184999999999995 |
|
- type: ndcg_at_1000 |
|
value: 56.92 |
|
- type: ndcg_at_3 |
|
value: 43.059999999999995 |
|
- type: ndcg_at_5 |
|
value: 47.481 |
|
- type: precision_at_1 |
|
value: 31.518 |
|
- type: precision_at_10 |
|
value: 8.824 |
|
- type: precision_at_100 |
|
value: 1.131 |
|
- type: precision_at_1000 |
|
value: 0.12 |
|
- type: precision_at_3 |
|
value: 19.969 |
|
- type: precision_at_5 |
|
value: 14.502 |
|
- type: recall_at_1 |
|
value: 27.828999999999997 |
|
- type: recall_at_10 |
|
value: 74.244 |
|
- type: recall_at_100 |
|
value: 93.325 |
|
- type: recall_at_1000 |
|
value: 98.71799999999999 |
|
- type: recall_at_3 |
|
value: 51.601 |
|
- type: recall_at_5 |
|
value: 61.841 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: quora |
|
name: MTEB QuoraRetrieval |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 71.54 |
|
- type: map_at_10 |
|
value: 85.509 |
|
- type: map_at_100 |
|
value: 86.137 |
|
- type: map_at_1000 |
|
value: 86.151 |
|
- type: map_at_3 |
|
value: 82.624 |
|
- type: map_at_5 |
|
value: 84.425 |
|
- type: mrr_at_1 |
|
value: 82.45 |
|
- type: mrr_at_10 |
|
value: 88.344 |
|
- type: mrr_at_100 |
|
value: 88.437 |
|
- type: mrr_at_1000 |
|
value: 88.437 |
|
- type: mrr_at_3 |
|
value: 87.417 |
|
- type: mrr_at_5 |
|
value: 88.066 |
|
- type: ndcg_at_1 |
|
value: 82.45 |
|
- type: ndcg_at_10 |
|
value: 89.092 |
|
- type: ndcg_at_100 |
|
value: 90.252 |
|
- type: ndcg_at_1000 |
|
value: 90.321 |
|
- type: ndcg_at_3 |
|
value: 86.404 |
|
- type: ndcg_at_5 |
|
value: 87.883 |
|
- type: precision_at_1 |
|
value: 82.45 |
|
- type: precision_at_10 |
|
value: 13.496 |
|
- type: precision_at_100 |
|
value: 1.536 |
|
- type: precision_at_1000 |
|
value: 0.157 |
|
- type: precision_at_3 |
|
value: 37.833 |
|
- type: precision_at_5 |
|
value: 24.79 |
|
- type: recall_at_1 |
|
value: 71.54 |
|
- type: recall_at_10 |
|
value: 95.846 |
|
- type: recall_at_100 |
|
value: 99.715 |
|
- type: recall_at_1000 |
|
value: 99.979 |
|
- type: recall_at_3 |
|
value: 88.01299999999999 |
|
- type: recall_at_5 |
|
value: 92.32000000000001 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: mteb/reddit-clustering |
|
name: MTEB RedditClustering |
|
config: default |
|
split: test |
|
revision: 24640382cdbf8abc73003fb0fa6d111a705499eb |
|
metrics: |
|
- type: v_measure |
|
value: 57.60557586253866 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: mteb/reddit-clustering-p2p |
|
name: MTEB RedditClusteringP2P |
|
config: default |
|
split: test |
|
revision: 282350215ef01743dc01b456c7f5241fa8937f16 |
|
metrics: |
|
- type: v_measure |
|
value: 64.0287172242051 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: scidocs |
|
name: MTEB SCIDOCS |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 3.9849999999999994 |
|
- type: map_at_10 |
|
value: 11.397 |
|
- type: map_at_100 |
|
value: 13.985 |
|
- type: map_at_1000 |
|
value: 14.391000000000002 |
|
- type: map_at_3 |
|
value: 7.66 |
|
- type: map_at_5 |
|
value: 9.46 |
|
- type: mrr_at_1 |
|
value: 19.8 |
|
- type: mrr_at_10 |
|
value: 31.958 |
|
- type: mrr_at_100 |
|
value: 33.373999999999995 |
|
- type: mrr_at_1000 |
|
value: 33.411 |
|
- type: mrr_at_3 |
|
value: 28.316999999999997 |
|
- type: mrr_at_5 |
|
value: 30.297 |
|
- type: ndcg_at_1 |
|
value: 19.8 |
|
- type: ndcg_at_10 |
|
value: 19.580000000000002 |
|
- type: ndcg_at_100 |
|
value: 29.555999999999997 |
|
- type: ndcg_at_1000 |
|
value: 35.882 |
|
- type: ndcg_at_3 |
|
value: 17.544 |
|
- type: ndcg_at_5 |
|
value: 15.815999999999999 |
|
- type: precision_at_1 |
|
value: 19.8 |
|
- type: precision_at_10 |
|
value: 10.61 |
|
- type: precision_at_100 |
|
value: 2.501 |
|
- type: precision_at_1000 |
|
value: 0.40099999999999997 |
|
- type: precision_at_3 |
|
value: 16.900000000000002 |
|
- type: precision_at_5 |
|
value: 14.44 |
|
- type: recall_at_1 |
|
value: 3.9849999999999994 |
|
- type: recall_at_10 |
|
value: 21.497 |
|
- type: recall_at_100 |
|
value: 50.727999999999994 |
|
- type: recall_at_1000 |
|
value: 81.27499999999999 |
|
- type: recall_at_3 |
|
value: 10.263 |
|
- type: recall_at_5 |
|
value: 14.643 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: mteb/sickr-sts |
|
name: MTEB SICK-R |
|
config: default |
|
split: test |
|
revision: a6ea5a8cab320b040a23452cc28066d9beae2cee |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 85.0087509585503 |
|
- type: cos_sim_spearman |
|
value: 81.74697270664319 |
|
- type: euclidean_pearson |
|
value: 81.80424382731947 |
|
- type: euclidean_spearman |
|
value: 81.29794251968431 |
|
- type: manhattan_pearson |
|
value: 81.81524666226125 |
|
- type: manhattan_spearman |
|
value: 81.29475370198963 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: mteb/sts12-sts |
|
name: MTEB STS12 |
|
config: default |
|
split: test |
|
revision: a0d554a64d88156834ff5ae9920b964011b16384 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 86.44442736429552 |
|
- type: cos_sim_spearman |
|
value: 78.51011398910948 |
|
- type: euclidean_pearson |
|
value: 83.36181801196723 |
|
- type: euclidean_spearman |
|
value: 79.47272621331535 |
|
- type: manhattan_pearson |
|
value: 83.3660113483837 |
|
- type: manhattan_spearman |
|
value: 79.47695922566032 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: mteb/sts13-sts |
|
name: MTEB STS13 |
|
config: default |
|
split: test |
|
revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 85.82923943323635 |
|
- type: cos_sim_spearman |
|
value: 86.62037823380983 |
|
- type: euclidean_pearson |
|
value: 83.56369548403958 |
|
- type: euclidean_spearman |
|
value: 84.2176755481191 |
|
- type: manhattan_pearson |
|
value: 83.55460702084464 |
|
- type: manhattan_spearman |
|
value: 84.18617930921467 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: mteb/sts14-sts |
|
name: MTEB STS14 |
|
config: default |
|
split: test |
|
revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 84.09071068110103 |
|
- type: cos_sim_spearman |
|
value: 83.05697553913335 |
|
- type: euclidean_pearson |
|
value: 81.1377457216497 |
|
- type: euclidean_spearman |
|
value: 81.74714169016676 |
|
- type: manhattan_pearson |
|
value: 81.0893424142723 |
|
- type: manhattan_spearman |
|
value: 81.7058918219677 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: mteb/sts15-sts |
|
name: MTEB STS15 |
|
config: default |
|
split: test |
|
revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 87.61132157220429 |
|
- type: cos_sim_spearman |
|
value: 88.38581627185445 |
|
- type: euclidean_pearson |
|
value: 86.14904510913374 |
|
- type: euclidean_spearman |
|
value: 86.5452758925542 |
|
- type: manhattan_pearson |
|
value: 86.1484025377679 |
|
- type: manhattan_spearman |
|
value: 86.55483841566252 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: mteb/sts16-sts |
|
name: MTEB STS16 |
|
config: default |
|
split: test |
|
revision: 4d8694f8f0e0100860b497b999b3dbed754a0513 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 85.46195145161064 |
|
- type: cos_sim_spearman |
|
value: 86.82409112251158 |
|
- type: euclidean_pearson |
|
value: 84.75479672288957 |
|
- type: euclidean_spearman |
|
value: 85.41144307151548 |
|
- type: manhattan_pearson |
|
value: 84.70914329694165 |
|
- type: manhattan_spearman |
|
value: 85.38477943384089 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: mteb/sts17-crosslingual-sts |
|
name: MTEB STS17 (en-en) |
|
config: en-en |
|
split: test |
|
revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 88.06351289930238 |
|
- type: cos_sim_spearman |
|
value: 87.90311138579116 |
|
- type: euclidean_pearson |
|
value: 86.17651467063077 |
|
- type: euclidean_spearman |
|
value: 84.89447802019073 |
|
- type: manhattan_pearson |
|
value: 86.3267677479595 |
|
- type: manhattan_spearman |
|
value: 85.00472295103874 |
|
- 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: 67.78311975978767 |
|
- type: cos_sim_spearman |
|
value: 66.76465685245887 |
|
- type: euclidean_pearson |
|
value: 67.21687806595443 |
|
- type: euclidean_spearman |
|
value: 65.05776733534435 |
|
- type: manhattan_pearson |
|
value: 67.14008143635883 |
|
- type: manhattan_spearman |
|
value: 65.25247076149701 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: mteb/stsbenchmark-sts |
|
name: MTEB STSBenchmark |
|
config: default |
|
split: test |
|
revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 86.7403488889418 |
|
- type: cos_sim_spearman |
|
value: 87.76870289783061 |
|
- type: euclidean_pearson |
|
value: 84.83171077794671 |
|
- type: euclidean_spearman |
|
value: 85.50579695091902 |
|
- type: manhattan_pearson |
|
value: 84.83074260180555 |
|
- type: manhattan_spearman |
|
value: 85.47589026938667 |
|
- task: |
|
type: Reranking |
|
dataset: |
|
type: mteb/scidocs-reranking |
|
name: MTEB SciDocsRR |
|
config: default |
|
split: test |
|
revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab |
|
metrics: |
|
- type: map |
|
value: 87.56234016237356 |
|
- type: mrr |
|
value: 96.26124238869338 |
|
- 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: 69.105 |
|
- type: map_at_100 |
|
value: 69.78 |
|
- type: map_at_1000 |
|
value: 69.80199999999999 |
|
- type: map_at_3 |
|
value: 65.991 |
|
- type: map_at_5 |
|
value: 68.02 |
|
- type: mrr_at_1 |
|
value: 62.666999999999994 |
|
- type: mrr_at_10 |
|
value: 70.259 |
|
- type: mrr_at_100 |
|
value: 70.776 |
|
- type: mrr_at_1000 |
|
value: 70.796 |
|
- type: mrr_at_3 |
|
value: 67.889 |
|
- type: mrr_at_5 |
|
value: 69.52199999999999 |
|
- type: ndcg_at_1 |
|
value: 62.666999999999994 |
|
- type: ndcg_at_10 |
|
value: 73.425 |
|
- type: ndcg_at_100 |
|
value: 75.955 |
|
- type: ndcg_at_1000 |
|
value: 76.459 |
|
- type: ndcg_at_3 |
|
value: 68.345 |
|
- type: ndcg_at_5 |
|
value: 71.319 |
|
- type: precision_at_1 |
|
value: 62.666999999999994 |
|
- type: precision_at_10 |
|
value: 9.667 |
|
- type: precision_at_100 |
|
value: 1.09 |
|
- type: precision_at_1000 |
|
value: 0.11299999999999999 |
|
- type: precision_at_3 |
|
value: 26.333000000000002 |
|
- type: precision_at_5 |
|
value: 17.732999999999997 |
|
- type: recall_at_1 |
|
value: 59.660999999999994 |
|
- type: recall_at_10 |
|
value: 85.422 |
|
- type: recall_at_100 |
|
value: 96.167 |
|
- type: recall_at_1000 |
|
value: 100.0 |
|
- type: recall_at_3 |
|
value: 72.044 |
|
- type: recall_at_5 |
|
value: 79.428 |
|
- task: |
|
type: PairClassification |
|
dataset: |
|
type: mteb/sprintduplicatequestions-pairclassification |
|
name: MTEB SprintDuplicateQuestions |
|
config: default |
|
split: test |
|
revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46 |
|
metrics: |
|
- type: cos_sim_accuracy |
|
value: 99.86435643564356 |
|
- type: cos_sim_ap |
|
value: 96.83057412333741 |
|
- type: cos_sim_f1 |
|
value: 93.04215337734891 |
|
- type: cos_sim_precision |
|
value: 94.53044375644994 |
|
- type: cos_sim_recall |
|
value: 91.60000000000001 |
|
- type: dot_accuracy |
|
value: 99.7910891089109 |
|
- type: dot_ap |
|
value: 94.10681982106397 |
|
- type: dot_f1 |
|
value: 89.34881373043918 |
|
- type: dot_precision |
|
value: 90.21406727828746 |
|
- type: dot_recall |
|
value: 88.5 |
|
- type: euclidean_accuracy |
|
value: 99.85544554455446 |
|
- type: euclidean_ap |
|
value: 96.78545104478602 |
|
- type: euclidean_f1 |
|
value: 92.65143992055613 |
|
- type: euclidean_precision |
|
value: 92.01183431952663 |
|
- type: euclidean_recall |
|
value: 93.30000000000001 |
|
- type: manhattan_accuracy |
|
value: 99.85841584158416 |
|
- type: manhattan_ap |
|
value: 96.80748903307823 |
|
- type: manhattan_f1 |
|
value: 92.78247884519662 |
|
- type: manhattan_precision |
|
value: 92.36868186323092 |
|
- type: manhattan_recall |
|
value: 93.2 |
|
- type: max_accuracy |
|
value: 99.86435643564356 |
|
- type: max_ap |
|
value: 96.83057412333741 |
|
- type: max_f1 |
|
value: 93.04215337734891 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: mteb/stackexchange-clustering |
|
name: MTEB StackExchangeClustering |
|
config: default |
|
split: test |
|
revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259 |
|
metrics: |
|
- type: v_measure |
|
value: 65.53971025855282 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: mteb/stackexchange-clustering-p2p |
|
name: MTEB StackExchangeClusteringP2P |
|
config: default |
|
split: test |
|
revision: 815ca46b2622cec33ccafc3735d572c266efdb44 |
|
metrics: |
|
- type: v_measure |
|
value: 33.97791591490788 |
|
- task: |
|
type: Reranking |
|
dataset: |
|
type: mteb/stackoverflowdupquestions-reranking |
|
name: MTEB StackOverflowDupQuestions |
|
config: default |
|
split: test |
|
revision: e185fbe320c72810689fc5848eb6114e1ef5ec69 |
|
metrics: |
|
- type: map |
|
value: 55.852215301355066 |
|
- type: mrr |
|
value: 56.85527809608691 |
|
- task: |
|
type: Summarization |
|
dataset: |
|
type: mteb/summeval |
|
name: MTEB SummEval |
|
config: default |
|
split: test |
|
revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 31.21442519856758 |
|
- type: cos_sim_spearman |
|
value: 30.822536216936825 |
|
- type: dot_pearson |
|
value: 28.661325528121807 |
|
- type: dot_spearman |
|
value: 28.1435226478879 |
|
- 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: 1.526 |
|
- type: map_at_100 |
|
value: 7.915 |
|
- type: map_at_1000 |
|
value: 19.009 |
|
- type: map_at_3 |
|
value: 0.541 |
|
- type: map_at_5 |
|
value: 0.8659999999999999 |
|
- type: mrr_at_1 |
|
value: 68.0 |
|
- type: mrr_at_10 |
|
value: 81.186 |
|
- type: mrr_at_100 |
|
value: 81.186 |
|
- type: mrr_at_1000 |
|
value: 81.186 |
|
- type: mrr_at_3 |
|
value: 80.0 |
|
- type: mrr_at_5 |
|
value: 80.9 |
|
- type: ndcg_at_1 |
|
value: 64.0 |
|
- type: ndcg_at_10 |
|
value: 64.13799999999999 |
|
- type: ndcg_at_100 |
|
value: 47.632000000000005 |
|
- type: ndcg_at_1000 |
|
value: 43.037 |
|
- type: ndcg_at_3 |
|
value: 67.542 |
|
- type: ndcg_at_5 |
|
value: 67.496 |
|
- type: precision_at_1 |
|
value: 68.0 |
|
- type: precision_at_10 |
|
value: 67.80000000000001 |
|
- type: precision_at_100 |
|
value: 48.980000000000004 |
|
- type: precision_at_1000 |
|
value: 19.036 |
|
- type: precision_at_3 |
|
value: 72.0 |
|
- type: precision_at_5 |
|
value: 71.2 |
|
- type: recall_at_1 |
|
value: 0.183 |
|
- type: recall_at_10 |
|
value: 1.799 |
|
- type: recall_at_100 |
|
value: 11.652999999999999 |
|
- type: recall_at_1000 |
|
value: 40.086 |
|
- type: recall_at_3 |
|
value: 0.5930000000000001 |
|
- type: recall_at_5 |
|
value: 0.983 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: webis-touche2020 |
|
name: MTEB Touche2020 |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 2.29 |
|
- type: map_at_10 |
|
value: 9.489 |
|
- type: map_at_100 |
|
value: 15.051 |
|
- type: map_at_1000 |
|
value: 16.561999999999998 |
|
- type: map_at_3 |
|
value: 5.137 |
|
- type: map_at_5 |
|
value: 6.7989999999999995 |
|
- type: mrr_at_1 |
|
value: 28.571 |
|
- type: mrr_at_10 |
|
value: 45.699 |
|
- type: mrr_at_100 |
|
value: 46.461000000000006 |
|
- type: mrr_at_1000 |
|
value: 46.461000000000006 |
|
- type: mrr_at_3 |
|
value: 41.837 |
|
- type: mrr_at_5 |
|
value: 43.163000000000004 |
|
- type: ndcg_at_1 |
|
value: 23.469 |
|
- type: ndcg_at_10 |
|
value: 23.544999999999998 |
|
- type: ndcg_at_100 |
|
value: 34.572 |
|
- type: ndcg_at_1000 |
|
value: 46.035 |
|
- type: ndcg_at_3 |
|
value: 27.200000000000003 |
|
- type: ndcg_at_5 |
|
value: 25.266 |
|
- type: precision_at_1 |
|
value: 28.571 |
|
- type: precision_at_10 |
|
value: 22.041 |
|
- type: precision_at_100 |
|
value: 7.3469999999999995 |
|
- type: precision_at_1000 |
|
value: 1.484 |
|
- type: precision_at_3 |
|
value: 29.932 |
|
- type: precision_at_5 |
|
value: 26.531 |
|
- type: recall_at_1 |
|
value: 2.29 |
|
- type: recall_at_10 |
|
value: 15.895999999999999 |
|
- type: recall_at_100 |
|
value: 45.518 |
|
- type: recall_at_1000 |
|
value: 80.731 |
|
- type: recall_at_3 |
|
value: 6.433 |
|
- type: recall_at_5 |
|
value: 9.484 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/toxic_conversations_50k |
|
name: MTEB ToxicConversationsClassification |
|
config: default |
|
split: test |
|
revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c |
|
metrics: |
|
- type: accuracy |
|
value: 71.4178 |
|
- type: ap |
|
value: 14.575240629602373 |
|
- type: f1 |
|
value: 55.02449563229096 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/tweet_sentiment_extraction |
|
name: MTEB TweetSentimentExtractionClassification |
|
config: default |
|
split: test |
|
revision: d604517c81ca91fe16a244d1248fc021f9ecee7a |
|
metrics: |
|
- type: accuracy |
|
value: 60.00282965478212 |
|
- type: f1 |
|
value: 60.34413028768773 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: mteb/twentynewsgroups-clustering |
|
name: MTEB TwentyNewsgroupsClustering |
|
config: default |
|
split: test |
|
revision: 6125ec4e24fa026cec8a478383ee943acfbd5449 |
|
metrics: |
|
- type: v_measure |
|
value: 50.409448342549936 |
|
- task: |
|
type: PairClassification |
|
dataset: |
|
type: mteb/twittersemeval2015-pairclassification |
|
name: MTEB TwitterSemEval2015 |
|
config: default |
|
split: test |
|
revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1 |
|
metrics: |
|
- type: cos_sim_accuracy |
|
value: 87.62591643321214 |
|
- type: cos_sim_ap |
|
value: 79.28766491329633 |
|
- type: cos_sim_f1 |
|
value: 71.98772064466617 |
|
- type: cos_sim_precision |
|
value: 69.8609731876862 |
|
- type: cos_sim_recall |
|
value: 74.24802110817942 |
|
- type: dot_accuracy |
|
value: 84.75293556654945 |
|
- type: dot_ap |
|
value: 69.72705761174353 |
|
- type: dot_f1 |
|
value: 65.08692852543464 |
|
- type: dot_precision |
|
value: 63.57232704402516 |
|
- type: dot_recall |
|
value: 66.6754617414248 |
|
- type: euclidean_accuracy |
|
value: 87.44710019669786 |
|
- type: euclidean_ap |
|
value: 79.11021477292638 |
|
- type: euclidean_f1 |
|
value: 71.5052389470994 |
|
- type: euclidean_precision |
|
value: 69.32606541129832 |
|
- type: euclidean_recall |
|
value: 73.82585751978891 |
|
- type: manhattan_accuracy |
|
value: 87.42325803182929 |
|
- type: manhattan_ap |
|
value: 79.05094494327616 |
|
- type: manhattan_f1 |
|
value: 71.36333985649055 |
|
- type: manhattan_precision |
|
value: 70.58064516129032 |
|
- type: manhattan_recall |
|
value: 72.16358839050132 |
|
- type: max_accuracy |
|
value: 87.62591643321214 |
|
- type: max_ap |
|
value: 79.28766491329633 |
|
- type: max_f1 |
|
value: 71.98772064466617 |
|
- task: |
|
type: PairClassification |
|
dataset: |
|
type: mteb/twitterurlcorpus-pairclassification |
|
name: MTEB TwitterURLCorpus |
|
config: default |
|
split: test |
|
revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf |
|
metrics: |
|
- type: cos_sim_accuracy |
|
value: 88.85202002561415 |
|
- type: cos_sim_ap |
|
value: 85.9835303311168 |
|
- type: cos_sim_f1 |
|
value: 78.25741142443962 |
|
- type: cos_sim_precision |
|
value: 73.76635768811342 |
|
- type: cos_sim_recall |
|
value: 83.3307668617185 |
|
- type: dot_accuracy |
|
value: 88.20584468506229 |
|
- type: dot_ap |
|
value: 83.591632302697 |
|
- type: dot_f1 |
|
value: 76.81739705396173 |
|
- type: dot_precision |
|
value: 73.45275728837373 |
|
- type: dot_recall |
|
value: 80.50508161379734 |
|
- type: euclidean_accuracy |
|
value: 88.64633057787093 |
|
- type: euclidean_ap |
|
value: 85.25705123182283 |
|
- type: euclidean_f1 |
|
value: 77.18535726329199 |
|
- type: euclidean_precision |
|
value: 75.17699437997226 |
|
- type: euclidean_recall |
|
value: 79.30397289805975 |
|
- type: manhattan_accuracy |
|
value: 88.63274731245392 |
|
- type: manhattan_ap |
|
value: 85.2376825633018 |
|
- type: manhattan_f1 |
|
value: 77.15810785937788 |
|
- type: manhattan_precision |
|
value: 73.92255061014319 |
|
- type: manhattan_recall |
|
value: 80.68986757006468 |
|
- type: max_accuracy |
|
value: 88.85202002561415 |
|
- type: max_ap |
|
value: 85.9835303311168 |
|
- type: max_f1 |
|
value: 78.25741142443962 |
|
--- |
|
|
|
# ember-v1 |
|
|
|
<p align="center"> |
|
<img src="https://console.llmrails.com/assets/img/logo-black.svg" width="150px"> |
|
</p> |
|
|
|
This model has been trained on an extensive corpus of text pairs that encompass a broad spectrum of domains, including finance, science, medicine, law, and various others. During the training process, we incorporated techniques derived from the [RetroMAE](https://arxiv.org/abs/2205.12035) and [SetFit](https://arxiv.org/abs/2209.11055) research papers. |
|
|
|
We are pleased to offer this model as an API service through our platform, [LLMRails](https://llmrails.com/?ref=ember-v1). If you are interested, please don't hesitate to sign up. |
|
|
|
### Plans |
|
- The research paper will be published soon. |
|
- The v2 of the model is currently in development and will feature an extended maximum sequence length of 4,000 tokens. |
|
|
|
## Usage |
|
Use with API request: |
|
```bash |
|
curl --location 'https://api.llmrails.com/v1/embeddings' \ |
|
--header 'X-API-KEY: {token}' \ |
|
--header 'Content-Type: application/json' \ |
|
--data '{ |
|
"input": ["This is an example sentence"], |
|
"model":"embedding-english-v1" # equals to ember-v1 |
|
}' |
|
``` |
|
API docs: https://docs.llmrails.com/embedding/embed-text<br> |
|
Langchain plugin: https://python.langchain.com/docs/integrations/text_embedding/llm_rails |
|
|
|
Use with transformers: |
|
```python |
|
import torch.nn.functional as F |
|
from torch import Tensor |
|
from transformers import AutoTokenizer, AutoModel |
|
|
|
def average_pool(last_hidden_states: Tensor, |
|
attention_mask: Tensor) -> Tensor: |
|
last_hidden = last_hidden_states.masked_fill(~attention_mask[..., None].bool(), 0.0) |
|
return last_hidden.sum(dim=1) / attention_mask.sum(dim=1)[..., None] |
|
|
|
input_texts = [ |
|
"This is an example sentence", |
|
"Each sentence is converted" |
|
] |
|
|
|
tokenizer = AutoTokenizer.from_pretrained("llmrails/ember-v1") |
|
model = AutoModel.from_pretrained("llmrails/ember-v1") |
|
|
|
# Tokenize the input texts |
|
batch_dict = tokenizer(input_texts, max_length=512, padding=True, truncation=True, return_tensors='pt') |
|
|
|
outputs = model(**batch_dict) |
|
embeddings = average_pool(outputs.last_hidden_state, batch_dict['attention_mask']) |
|
|
|
# (Optionally) normalize embeddings |
|
embeddings = F.normalize(embeddings, p=2, dim=1) |
|
scores = (embeddings[:1] @ embeddings[1:].T) * 100 |
|
print(scores.tolist()) |
|
``` |
|
|
|
Use with sentence-transformers: |
|
```python |
|
from sentence_transformers import SentenceTransformer |
|
from sentence_transformers.util import cos_sim |
|
|
|
sentences = [ |
|
"This is an example sentence", |
|
"Each sentence is converted" |
|
] |
|
|
|
model = SentenceTransformer('llmrails/ember-v1') |
|
embeddings = model.encode(sentences) |
|
print(cos_sim(embeddings[0], embeddings[1])) |
|
``` |
|
|
|
## Massive Text Embedding Benchmark (MTEB) Evaluation |
|
Our model achieve state-of-the-art performance on [MTEB leaderboard](https://huggingface.co/spaces/mteb/leaderboard) |
|
|
|
| Model Name | Dimension | Sequence Length | Average (56) | |
|
|:-----------------------------------------------------------------------:|:---------:|:---:|:------------:| |
|
| [bge-large-en-v1.5](https://huggingface.co/BAAI/bge-large-en-v1.5) | 1024 | 512 | 64.23 | |
|
| [bge-base-en-v1.5](https://huggingface.co/BAAI/bge-base-en-v1.5) | 768 | 512 | 63.55 | |
|
| [ember-v1](https://huggingface.co/llmrails/emmbedding-en-v1) | 1024 | 512 | **63.54** | |
|
| [text-embedding-ada-002](https://platform.openai.com/docs/guides/embeddings/types-of-embedding-models) | 1536 | 8191 | 60.99 | |
|
|
|
### Limitation |
|
|
|
This model exclusively caters to English texts, and any lengthy texts will be truncated to a maximum of 512 tokens. |
