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--- |
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tags: |
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- mteb |
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- sentence_embedding |
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- feature_extraction |
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- sentence-transformers |
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- transformers |
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- transformers.js |
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model-index: |
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- name: UAE-Large-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: 75.55223880597015 |
|
- type: ap |
|
value: 38.264070815317794 |
|
- type: f1 |
|
value: 69.40977934769845 |
|
- task: |
|
type: Classification |
|
dataset: |
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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: 92.84267499999999 |
|
- type: ap |
|
value: 89.57568507997713 |
|
- type: f1 |
|
value: 92.82590734337774 |
|
- task: |
|
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: 48.292 |
|
- type: f1 |
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value: 47.90257816032778 |
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- 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: 42.105 |
|
- type: map_at_10 |
|
value: 58.181000000000004 |
|
- type: map_at_100 |
|
value: 58.653999999999996 |
|
- type: map_at_1000 |
|
value: 58.657000000000004 |
|
- type: map_at_3 |
|
value: 54.386 |
|
- type: map_at_5 |
|
value: 56.757999999999996 |
|
- type: mrr_at_1 |
|
value: 42.745 |
|
- type: mrr_at_10 |
|
value: 58.437 |
|
- type: mrr_at_100 |
|
value: 58.894999999999996 |
|
- type: mrr_at_1000 |
|
value: 58.897999999999996 |
|
- type: mrr_at_3 |
|
value: 54.635 |
|
- type: mrr_at_5 |
|
value: 56.99999999999999 |
|
- type: ndcg_at_1 |
|
value: 42.105 |
|
- type: ndcg_at_10 |
|
value: 66.14999999999999 |
|
- type: ndcg_at_100 |
|
value: 68.048 |
|
- type: ndcg_at_1000 |
|
value: 68.11399999999999 |
|
- type: ndcg_at_3 |
|
value: 58.477000000000004 |
|
- type: ndcg_at_5 |
|
value: 62.768 |
|
- type: precision_at_1 |
|
value: 42.105 |
|
- type: precision_at_10 |
|
value: 9.110999999999999 |
|
- type: precision_at_100 |
|
value: 0.991 |
|
- type: precision_at_1000 |
|
value: 0.1 |
|
- type: precision_at_3 |
|
value: 23.447000000000003 |
|
- type: precision_at_5 |
|
value: 16.159000000000002 |
|
- type: recall_at_1 |
|
value: 42.105 |
|
- type: recall_at_10 |
|
value: 91.11 |
|
- type: recall_at_100 |
|
value: 99.14699999999999 |
|
- type: recall_at_1000 |
|
value: 99.644 |
|
- type: recall_at_3 |
|
value: 70.341 |
|
- type: recall_at_5 |
|
value: 80.797 |
|
- task: |
|
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: 49.02580759154173 |
|
- 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: 43.093601280163554 |
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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: 64.19590406875427 |
|
- type: mrr |
|
value: 77.09547992788991 |
|
- task: |
|
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: 87.86678362843676 |
|
- type: cos_sim_spearman |
|
value: 86.1423242570783 |
|
- type: euclidean_pearson |
|
value: 85.98994198511751 |
|
- type: euclidean_spearman |
|
value: 86.48209103503942 |
|
- type: manhattan_pearson |
|
value: 85.6446436316182 |
|
- type: manhattan_spearman |
|
value: 86.21039809734357 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/banking77 |
|
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: 87.69155844155844 |
|
- type: f1 |
|
value: 87.68109381943547 |
|
- task: |
|
type: Clustering |
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dataset: |
|
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: |
|
- type: v_measure |
|
value: 39.37501687500394 |
|
- 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 |
|
metrics: |
|
- type: v_measure |
|
value: 37.23401405155885 |
|
- 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: 30.232 |
|
- type: map_at_10 |
|
value: 41.404999999999994 |
|
- type: map_at_100 |
|
value: 42.896 |
|
- type: map_at_1000 |
|
value: 43.028 |
|
- type: map_at_3 |
|
value: 37.925 |
|
- type: map_at_5 |
|
value: 39.865 |
|
- type: mrr_at_1 |
|
value: 36.338 |
|
- type: mrr_at_10 |
|
value: 46.969 |
|
- type: mrr_at_100 |
|
value: 47.684 |
|
- type: mrr_at_1000 |
|
value: 47.731 |
|
- type: mrr_at_3 |
|
value: 44.063 |
|
- type: mrr_at_5 |
|
value: 45.908 |
|
- type: ndcg_at_1 |
|
value: 36.338 |
|
- type: ndcg_at_10 |
|
value: 47.887 |
|
- type: ndcg_at_100 |
|
value: 53.357 |
|
- type: ndcg_at_1000 |
|
value: 55.376999999999995 |
|
- type: ndcg_at_3 |
|
value: 42.588 |
|
- type: ndcg_at_5 |
|
value: 45.132 |
|
- type: precision_at_1 |
|
value: 36.338 |
|
- type: precision_at_10 |
|
value: 9.17 |
|
- type: precision_at_100 |
|
value: 1.4909999999999999 |
|
- type: precision_at_1000 |
|
value: 0.196 |
|
- type: precision_at_3 |
|
value: 20.315 |
|
- type: precision_at_5 |
|
value: 14.793000000000001 |
|
- type: recall_at_1 |
|
value: 30.232 |
|
- type: recall_at_10 |
|
value: 60.67399999999999 |
|
- type: recall_at_100 |
|
value: 83.628 |
|
- type: recall_at_1000 |
|
value: 96.209 |
|
- type: recall_at_3 |
|
value: 45.48 |
|
- type: recall_at_5 |
|
value: 52.354 |
|
- 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: |
|
- type: map_at_1 |
|
value: 32.237 |
|
- type: map_at_10 |
|
value: 42.829 |
|
- type: map_at_100 |
|
value: 44.065 |
|
- type: map_at_1000 |
|
value: 44.199 |
|
- type: map_at_3 |
|
value: 39.885999999999996 |
|
- type: map_at_5 |
|
value: 41.55 |
|
- type: mrr_at_1 |
|
value: 40.064 |
|
- type: mrr_at_10 |
|
value: 48.611 |
|
- type: mrr_at_100 |
|
value: 49.245 |
|
- type: mrr_at_1000 |
|
value: 49.29 |
|
- type: mrr_at_3 |
|
value: 46.561 |
|
- type: mrr_at_5 |
|
value: 47.771 |
|
- type: ndcg_at_1 |
|
value: 40.064 |
|
- type: ndcg_at_10 |
|
value: 48.388 |
|
- type: ndcg_at_100 |
|
value: 52.666999999999994 |
|
- type: ndcg_at_1000 |
|
value: 54.67100000000001 |
|
- type: ndcg_at_3 |
|
value: 44.504 |
|
- type: ndcg_at_5 |
|
value: 46.303 |
|
- type: precision_at_1 |
|
value: 40.064 |
|
- type: precision_at_10 |
|
value: 9.051 |
|
- type: precision_at_100 |
|
value: 1.4500000000000002 |
|
- type: precision_at_1000 |
|
value: 0.193 |
|
- type: precision_at_3 |
|
value: 21.444 |
|
- type: precision_at_5 |
|
value: 15.045 |
|
- type: recall_at_1 |
|
value: 32.237 |
|
- type: recall_at_10 |
|
value: 57.943999999999996 |
|
- type: recall_at_100 |
|
value: 75.98700000000001 |
|
- type: recall_at_1000 |
|
value: 88.453 |
|
- type: recall_at_3 |
|
value: 46.268 |
|
- type: recall_at_5 |
|
value: 51.459999999999994 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: BeIR/cqadupstack |
|
name: MTEB CQADupstackGamingRetrieval |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 38.797 |
|
- type: map_at_10 |
|
value: 51.263000000000005 |
|
- type: map_at_100 |
|
value: 52.333 |
|
- type: map_at_1000 |
|
value: 52.393 |
|
- type: map_at_3 |
|
value: 47.936 |
|
- type: map_at_5 |
|
value: 49.844 |
|
- type: mrr_at_1 |
|
value: 44.389 |
|
- type: mrr_at_10 |
|
value: 54.601 |
|
- type: mrr_at_100 |
|
value: 55.300000000000004 |
|
- type: mrr_at_1000 |
|
value: 55.333 |
|
- type: mrr_at_3 |
|
value: 52.068999999999996 |
|
- type: mrr_at_5 |
|
value: 53.627 |
|
- type: ndcg_at_1 |
|
value: 44.389 |
|
- type: ndcg_at_10 |
|
value: 57.193000000000005 |
|
- type: ndcg_at_100 |
|
value: 61.307 |
|
- type: ndcg_at_1000 |
|
value: 62.529 |
|
- type: ndcg_at_3 |
|
value: 51.607 |
|
- type: ndcg_at_5 |
|
value: 54.409 |
|
- type: precision_at_1 |
|
value: 44.389 |
|
- type: precision_at_10 |
|
value: 9.26 |
|
- type: precision_at_100 |
|
value: 1.222 |
|
- type: precision_at_1000 |
|
value: 0.13699999999999998 |
|
- type: precision_at_3 |
|
value: 23.03 |
|
- type: precision_at_5 |
|
value: 15.887 |
|
- type: recall_at_1 |
|
value: 38.797 |
|
- type: recall_at_10 |
|
value: 71.449 |
|
- type: recall_at_100 |
|
value: 88.881 |
|
- type: recall_at_1000 |
|
value: 97.52 |
|
- type: recall_at_3 |
|
value: 56.503 |
|
- type: recall_at_5 |
|
value: 63.392 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: BeIR/cqadupstack |
|
name: MTEB CQADupstackGisRetrieval |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 27.291999999999998 |
|
- type: map_at_10 |
|
value: 35.65 |
|
- type: map_at_100 |
|
value: 36.689 |
|
- type: map_at_1000 |
|
value: 36.753 |
|
- type: map_at_3 |
|
value: 32.995000000000005 |
|
- type: map_at_5 |
|
value: 34.409 |
|
- type: mrr_at_1 |
|
value: 29.04 |
|
- type: mrr_at_10 |
|
value: 37.486000000000004 |
|
- type: mrr_at_100 |
|
value: 38.394 |
|
- type: mrr_at_1000 |
|
value: 38.445 |
|
- type: mrr_at_3 |
|
value: 35.028 |
|
- type: mrr_at_5 |
|
value: 36.305 |
|
- type: ndcg_at_1 |
|
value: 29.04 |
|
- type: ndcg_at_10 |
|
value: 40.613 |
|
- type: ndcg_at_100 |
|
value: 45.733000000000004 |
|
- type: ndcg_at_1000 |
|
value: 47.447 |
|
- type: ndcg_at_3 |
|
value: 35.339999999999996 |
|
- type: ndcg_at_5 |
|
value: 37.706 |
|
- type: precision_at_1 |
|
value: 29.04 |
|
- type: precision_at_10 |
|
value: 6.192 |
|
- type: precision_at_100 |
|
value: 0.9249999999999999 |
|
- type: precision_at_1000 |
|
value: 0.11 |
|
- type: precision_at_3 |
|
value: 14.802000000000001 |
|
- type: precision_at_5 |
|
value: 10.305 |
|
- type: recall_at_1 |
|
value: 27.291999999999998 |
|
- type: recall_at_10 |
|
value: 54.25299999999999 |
|
- type: recall_at_100 |
|
value: 77.773 |
|
- type: recall_at_1000 |
|
value: 90.795 |
|
- type: recall_at_3 |
|
value: 39.731 |
|
- type: recall_at_5 |
|
value: 45.403999999999996 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: BeIR/cqadupstack |
|
name: MTEB CQADupstackMathematicaRetrieval |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 18.326 |
|
- type: map_at_10 |
|
value: 26.290999999999997 |
|
- type: map_at_100 |
|
value: 27.456999999999997 |
|
- type: map_at_1000 |
|
value: 27.583000000000002 |
|
- type: map_at_3 |
|
value: 23.578 |
|
- type: map_at_5 |
|
value: 25.113000000000003 |
|
- type: mrr_at_1 |
|
value: 22.637 |
|
- type: mrr_at_10 |
|
value: 31.139 |
|
- type: mrr_at_100 |
|
value: 32.074999999999996 |
|
- type: mrr_at_1000 |
|
value: 32.147 |
|
- type: mrr_at_3 |
|
value: 28.483000000000004 |
|
- type: mrr_at_5 |
|
value: 29.963 |
|
- type: ndcg_at_1 |
|
value: 22.637 |
|
- type: ndcg_at_10 |
|
value: 31.717000000000002 |
|
- type: ndcg_at_100 |
|
value: 37.201 |
|
- type: ndcg_at_1000 |
|
value: 40.088 |
|
- type: ndcg_at_3 |
|
value: 26.686 |
|
- type: ndcg_at_5 |
|
value: 29.076999999999998 |
|
- type: precision_at_1 |
|
value: 22.637 |
|
- type: precision_at_10 |
|
value: 5.7090000000000005 |
|
- type: precision_at_100 |
|
value: 0.979 |
|
- type: precision_at_1000 |
|
value: 0.13799999999999998 |
|
- type: precision_at_3 |
|
value: 12.894 |
|
- type: precision_at_5 |
|
value: 9.328 |
|
- type: recall_at_1 |
|
value: 18.326 |
|
- type: recall_at_10 |
|
value: 43.824999999999996 |
|
- type: recall_at_100 |
|
value: 67.316 |
|
- type: recall_at_1000 |
|
value: 87.481 |
|
- type: recall_at_3 |
|
value: 29.866999999999997 |
|
- type: recall_at_5 |
|
value: 35.961999999999996 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: BeIR/cqadupstack |
|
name: MTEB CQADupstackPhysicsRetrieval |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 29.875 |
|
- type: map_at_10 |
|
value: 40.458 |
|
- type: map_at_100 |
|
value: 41.772 |
|
- type: map_at_1000 |
|
value: 41.882999999999996 |
|
- type: map_at_3 |
|
value: 37.086999999999996 |
|
- type: map_at_5 |
|
value: 39.153 |
|
- type: mrr_at_1 |
|
value: 36.381 |
|
- type: mrr_at_10 |
|
value: 46.190999999999995 |
|
- type: mrr_at_100 |
|
value: 46.983999999999995 |
|
- type: mrr_at_1000 |
|
value: 47.032000000000004 |
|
- type: mrr_at_3 |
|
value: 43.486999999999995 |
|
- type: mrr_at_5 |
|
value: 45.249 |
|
- type: ndcg_at_1 |
|
value: 36.381 |
|
- type: ndcg_at_10 |
|
value: 46.602 |
|
- type: ndcg_at_100 |
|
value: 51.885999999999996 |
|
- type: ndcg_at_1000 |
|
value: 53.895 |
|
- type: ndcg_at_3 |
|
value: 41.155 |
|
- type: ndcg_at_5 |
|
value: 44.182 |
|
- type: precision_at_1 |
|
value: 36.381 |
|
- type: precision_at_10 |
|
value: 8.402 |
|
- type: precision_at_100 |
|
value: 1.278 |
|
- type: precision_at_1000 |
|
value: 0.16199999999999998 |
|
- type: precision_at_3 |
|
value: 19.346 |
|
- type: precision_at_5 |
|
value: 14.09 |
|
- type: recall_at_1 |
|
value: 29.875 |
|
- type: recall_at_10 |
|
value: 59.065999999999995 |
|
- type: recall_at_100 |
|
value: 80.923 |
|
- type: recall_at_1000 |
|
value: 93.927 |
|
- type: recall_at_3 |
|
value: 44.462 |
|
- type: recall_at_5 |
|
value: 51.89 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: BeIR/cqadupstack |
|
name: MTEB CQADupstackProgrammersRetrieval |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 24.94 |
|
- type: map_at_10 |
|
value: 35.125 |
|
- type: map_at_100 |
|
value: 36.476 |
|
- type: map_at_1000 |
|
value: 36.579 |
|
- type: map_at_3 |
|
value: 31.840000000000003 |
|
- type: map_at_5 |
|
value: 33.647 |
|
- type: mrr_at_1 |
|
value: 30.936000000000003 |
|
- type: mrr_at_10 |
|
value: 40.637 |
|
- type: mrr_at_100 |
|
value: 41.471000000000004 |
|
- type: mrr_at_1000 |
|
value: 41.525 |
|
- type: mrr_at_3 |
|
value: 38.013999999999996 |
|
- type: mrr_at_5 |
|
value: 39.469 |
|
- type: ndcg_at_1 |
|
value: 30.936000000000003 |
|
- type: ndcg_at_10 |
|
value: 41.295 |
|
- type: ndcg_at_100 |
|
value: 46.92 |
|
- type: ndcg_at_1000 |
|
value: 49.183 |
|
- type: ndcg_at_3 |
|
value: 35.811 |
|
- type: ndcg_at_5 |
|
value: 38.306000000000004 |
|
- type: precision_at_1 |
|
value: 30.936000000000003 |
|
- type: precision_at_10 |
|
value: 7.728 |
|
- type: precision_at_100 |
|
value: 1.226 |
|
- type: precision_at_1000 |
|
value: 0.158 |
|
- type: precision_at_3 |
|
value: 17.237 |
|
- type: precision_at_5 |
|
value: 12.42 |
|
- type: recall_at_1 |
|
value: 24.94 |
|
- type: recall_at_10 |
|
value: 54.235 |
|
- type: recall_at_100 |
|
value: 78.314 |
|
- type: recall_at_1000 |
|
value: 93.973 |
|
- type: recall_at_3 |
|
value: 38.925 |
|
- type: recall_at_5 |
|
value: 45.505 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: BeIR/cqadupstack |
|
name: MTEB CQADupstackRetrieval |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 26.250833333333333 |
|
- type: map_at_10 |
|
value: 35.46875 |
|
- type: map_at_100 |
|
value: 36.667 |
|
- type: map_at_1000 |
|
value: 36.78025 |
|
- type: map_at_3 |
|
value: 32.56733333333334 |
|
- type: map_at_5 |
|
value: 34.20333333333333 |
|
- type: mrr_at_1 |
|
value: 30.8945 |
|
- type: mrr_at_10 |
|
value: 39.636833333333335 |
|
- type: mrr_at_100 |
|
value: 40.46508333333333 |
|
- type: mrr_at_1000 |
|
value: 40.521249999999995 |
|
- type: mrr_at_3 |
|
value: 37.140166666666666 |
|
- type: mrr_at_5 |
|
value: 38.60999999999999 |
|
- type: ndcg_at_1 |
|
value: 30.8945 |
|
- type: ndcg_at_10 |
|
value: 40.93441666666667 |
|
- type: ndcg_at_100 |
|
value: 46.062416666666664 |
|
- type: ndcg_at_1000 |
|
value: 48.28341666666667 |
|
- type: ndcg_at_3 |
|
value: 35.97575 |
|
- type: ndcg_at_5 |
|
value: 38.3785 |
|
- type: precision_at_1 |
|
value: 30.8945 |
|
- type: precision_at_10 |
|
value: 7.180250000000001 |
|
- type: precision_at_100 |
|
value: 1.1468333333333334 |
|
- type: precision_at_1000 |
|
value: 0.15283333333333332 |
|
- type: precision_at_3 |
|
value: 16.525583333333334 |
|
- type: precision_at_5 |
|
value: 11.798333333333332 |
|
- type: recall_at_1 |
|
value: 26.250833333333333 |
|
- type: recall_at_10 |
|
value: 52.96108333333333 |
|
- type: recall_at_100 |
|
value: 75.45908333333334 |
|
- type: recall_at_1000 |
|
value: 90.73924999999998 |
|
- type: recall_at_3 |
|
value: 39.25483333333333 |
|
- type: recall_at_5 |
|
value: 45.37950000000001 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: BeIR/cqadupstack |
|
name: MTEB CQADupstackStatsRetrieval |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 24.595 |
|
- type: map_at_10 |
|
value: 31.747999999999998 |
|
- type: map_at_100 |
|
value: 32.62 |
|
- type: map_at_1000 |
|
value: 32.713 |
|
- type: map_at_3 |
|
value: 29.48 |
|
- type: map_at_5 |
|
value: 30.635 |
|
- type: mrr_at_1 |
|
value: 27.607 |
|
- type: mrr_at_10 |
|
value: 34.449000000000005 |
|
- type: mrr_at_100 |
|
value: 35.182 |
|
- type: mrr_at_1000 |
|
value: 35.254000000000005 |
|
- type: mrr_at_3 |
|
value: 32.413 |
|
- type: mrr_at_5 |
|
value: 33.372 |
|
- type: ndcg_at_1 |
|
value: 27.607 |
|
- type: ndcg_at_10 |
|
value: 36.041000000000004 |
|
- type: ndcg_at_100 |
|
value: 40.514 |
|
- type: ndcg_at_1000 |
|
value: 42.851 |
|
- type: ndcg_at_3 |
|
value: 31.689 |
|
- type: ndcg_at_5 |
|
value: 33.479 |
|
- type: precision_at_1 |
|
value: 27.607 |
|
- type: precision_at_10 |
|
value: 5.66 |
|
- type: precision_at_100 |
|
value: 0.868 |
|
- type: precision_at_1000 |
|
value: 0.11299999999999999 |
|
- type: precision_at_3 |
|
value: 13.446 |
|
- type: precision_at_5 |
|
value: 9.264 |
|
- type: recall_at_1 |
|
value: 24.595 |
|
- type: recall_at_10 |
|
value: 46.79 |
|
- type: recall_at_100 |
|
value: 67.413 |
|
- type: recall_at_1000 |
|
value: 84.753 |
|
- type: recall_at_3 |
|
value: 34.644999999999996 |
|
- type: recall_at_5 |
|
value: 39.09 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: BeIR/cqadupstack |
|
name: MTEB CQADupstackTexRetrieval |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 17.333000000000002 |
|
- type: map_at_10 |
|
value: 24.427 |
|
- type: map_at_100 |
|
value: 25.576 |
|
- type: map_at_1000 |
|
value: 25.692999999999998 |
|
- type: map_at_3 |
|
value: 22.002 |
|
- type: map_at_5 |
|
value: 23.249 |
|
- type: mrr_at_1 |
|
value: 20.716 |
|
- type: mrr_at_10 |
|
value: 28.072000000000003 |
|
- type: mrr_at_100 |
|
value: 29.067 |
|
- type: mrr_at_1000 |
|
value: 29.137 |
|
- type: mrr_at_3 |
|
value: 25.832 |
|
- type: mrr_at_5 |
|
value: 27.045 |
|
- type: ndcg_at_1 |
|
value: 20.716 |
|
- type: ndcg_at_10 |
|
value: 29.109 |
|
- type: ndcg_at_100 |
|
value: 34.797 |
|
- type: ndcg_at_1000 |
|
value: 37.503 |
|
- type: ndcg_at_3 |
|
value: 24.668 |
|
- type: ndcg_at_5 |
|
value: 26.552999999999997 |
|
- type: precision_at_1 |
|
value: 20.716 |
|
- type: precision_at_10 |
|
value: 5.351 |
|
- type: precision_at_100 |
|
value: 0.955 |
|
- type: precision_at_1000 |
|
value: 0.136 |
|
- type: precision_at_3 |
|
value: 11.584999999999999 |
|
- type: precision_at_5 |
|
value: 8.362 |
|
- type: recall_at_1 |
|
value: 17.333000000000002 |
|
- type: recall_at_10 |
|
value: 39.604 |
|
- type: recall_at_100 |
|
value: 65.525 |
|
- type: recall_at_1000 |
|
value: 84.651 |
|
- type: recall_at_3 |
|
value: 27.199 |
|
- type: recall_at_5 |
|
value: 32.019 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: BeIR/cqadupstack |
|
name: MTEB CQADupstackUnixRetrieval |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 26.342 |
|
- type: map_at_10 |
|
value: 35.349000000000004 |
|
- type: map_at_100 |
|
value: 36.443 |
|
- type: map_at_1000 |
|
value: 36.548 |
|
- type: map_at_3 |
|
value: 32.307 |
|
- type: map_at_5 |
|
value: 34.164 |
|
- type: mrr_at_1 |
|
value: 31.063000000000002 |
|
- type: mrr_at_10 |
|
value: 39.703 |
|
- type: mrr_at_100 |
|
value: 40.555 |
|
- type: mrr_at_1000 |
|
value: 40.614 |
|
- type: mrr_at_3 |
|
value: 37.141999999999996 |
|
- type: mrr_at_5 |
|
value: 38.812000000000005 |
|
- type: ndcg_at_1 |
|
value: 31.063000000000002 |
|
- type: ndcg_at_10 |
|
value: 40.873 |
|
- type: ndcg_at_100 |
|
value: 45.896 |
|
- type: ndcg_at_1000 |
|
value: 48.205999999999996 |
|
- type: ndcg_at_3 |
|
value: 35.522 |
|
- type: ndcg_at_5 |
|
value: 38.419 |
|
- type: precision_at_1 |
|
value: 31.063000000000002 |
|
- type: precision_at_10 |
|
value: 6.866 |
|
- type: precision_at_100 |
|
value: 1.053 |
|
- type: precision_at_1000 |
|
value: 0.13699999999999998 |
|
- type: precision_at_3 |
|
value: 16.014 |
|
- type: precision_at_5 |
|
value: 11.604000000000001 |
|
- type: recall_at_1 |
|
value: 26.342 |
|
- type: recall_at_10 |
|
value: 53.40200000000001 |
|
- type: recall_at_100 |
|
value: 75.251 |
|
- type: recall_at_1000 |
|
value: 91.13799999999999 |
|
- type: recall_at_3 |
|
value: 39.103 |
|
- type: recall_at_5 |
|
value: 46.357 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: BeIR/cqadupstack |
|
name: MTEB CQADupstackWebmastersRetrieval |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 23.71 |
|
- type: map_at_10 |
|
value: 32.153999999999996 |
|
- type: map_at_100 |
|
value: 33.821 |
|
- type: map_at_1000 |
|
value: 34.034 |
|
- type: map_at_3 |
|
value: 29.376 |
|
- type: map_at_5 |
|
value: 30.878 |
|
- type: mrr_at_1 |
|
value: 28.458 |
|
- type: mrr_at_10 |
|
value: 36.775999999999996 |
|
- type: mrr_at_100 |
|
value: 37.804 |
|
- type: mrr_at_1000 |
|
value: 37.858999999999995 |
|
- type: mrr_at_3 |
|
value: 34.123999999999995 |
|
- type: mrr_at_5 |
|
value: 35.596 |
|
- type: ndcg_at_1 |
|
value: 28.458 |
|
- type: ndcg_at_10 |
|
value: 37.858999999999995 |
|
- type: ndcg_at_100 |
|
value: 44.194 |
|
- type: ndcg_at_1000 |
|
value: 46.744 |
|
- type: ndcg_at_3 |
|
value: 33.348 |
|
- type: ndcg_at_5 |
|
value: 35.448 |
|
- type: precision_at_1 |
|
value: 28.458 |
|
- type: precision_at_10 |
|
value: 7.4510000000000005 |
|
- type: precision_at_100 |
|
value: 1.5 |
|
- type: precision_at_1000 |
|
value: 0.23700000000000002 |
|
- type: precision_at_3 |
|
value: 15.809999999999999 |
|
- type: precision_at_5 |
|
value: 11.462 |
|
- type: recall_at_1 |
|
value: 23.71 |
|
- type: recall_at_10 |
|
value: 48.272999999999996 |
|
- type: recall_at_100 |
|
value: 77.134 |
|
- type: recall_at_1000 |
|
value: 93.001 |
|
- type: recall_at_3 |
|
value: 35.480000000000004 |
|
- type: recall_at_5 |
|
value: 41.19 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: BeIR/cqadupstack |
|
name: MTEB CQADupstackWordpressRetrieval |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 21.331 |
|
- type: map_at_10 |
|
value: 28.926000000000002 |
|
- type: map_at_100 |
|
value: 29.855999999999998 |
|
- type: map_at_1000 |
|
value: 29.957 |
|
- type: map_at_3 |
|
value: 26.395999999999997 |
|
- type: map_at_5 |
|
value: 27.933000000000003 |
|
- type: mrr_at_1 |
|
value: 23.105 |
|
- type: mrr_at_10 |
|
value: 31.008000000000003 |
|
- type: mrr_at_100 |
|
value: 31.819999999999997 |
|
- type: mrr_at_1000 |
|
value: 31.887999999999998 |
|
- type: mrr_at_3 |
|
value: 28.466 |
|
- type: mrr_at_5 |
|
value: 30.203000000000003 |
|
- type: ndcg_at_1 |
|
value: 23.105 |
|
- type: ndcg_at_10 |
|
value: 33.635999999999996 |
|
- type: ndcg_at_100 |
|
value: 38.277 |
|
- type: ndcg_at_1000 |
|
value: 40.907 |
|
- type: ndcg_at_3 |
|
value: 28.791 |
|
- type: ndcg_at_5 |
|
value: 31.528 |
|
- type: precision_at_1 |
|
value: 23.105 |
|
- type: precision_at_10 |
|
value: 5.323 |
|
- type: precision_at_100 |
|
value: 0.815 |
|
- type: precision_at_1000 |
|
value: 0.117 |
|
- type: precision_at_3 |
|
value: 12.384 |
|
- type: precision_at_5 |
|
value: 9.02 |
|
- type: recall_at_1 |
|
value: 21.331 |
|
- type: recall_at_10 |
|
value: 46.018 |
|
- type: recall_at_100 |
|
value: 67.364 |
|
- type: recall_at_1000 |
|
value: 86.97 |
|
- type: recall_at_3 |
|
value: 33.395 |
|
- type: recall_at_5 |
|
value: 39.931 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: climate-fever |
|
name: MTEB ClimateFEVER |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 17.011000000000003 |
|
- type: map_at_10 |
|
value: 28.816999999999997 |
|
- type: map_at_100 |
|
value: 30.761 |
|
- type: map_at_1000 |
|
value: 30.958000000000002 |
|
- type: map_at_3 |
|
value: 24.044999999999998 |
|
- type: map_at_5 |
|
value: 26.557 |
|
- type: mrr_at_1 |
|
value: 38.696999999999996 |
|
- type: mrr_at_10 |
|
value: 50.464 |
|
- type: mrr_at_100 |
|
value: 51.193999999999996 |
|
- type: mrr_at_1000 |
|
value: 51.219 |
|
- type: mrr_at_3 |
|
value: 47.339999999999996 |
|
- type: mrr_at_5 |
|
value: 49.346000000000004 |
|
- type: ndcg_at_1 |
|
value: 38.696999999999996 |
|
- type: ndcg_at_10 |
|
value: 38.53 |
|
- type: ndcg_at_100 |
|
value: 45.525 |
|
- type: ndcg_at_1000 |
|
value: 48.685 |
|
- type: ndcg_at_3 |
|
value: 32.282 |
|
- type: ndcg_at_5 |
|
value: 34.482 |
|
- type: precision_at_1 |
|
value: 38.696999999999996 |
|
- type: precision_at_10 |
|
value: 11.895999999999999 |
|
- type: precision_at_100 |
|
value: 1.95 |
|
- type: precision_at_1000 |
|
value: 0.254 |
|
- type: precision_at_3 |
|
value: 24.038999999999998 |
|
- type: precision_at_5 |
|
value: 18.332 |
|
- type: recall_at_1 |
|
value: 17.011000000000003 |
|
- type: recall_at_10 |
|
value: 44.452999999999996 |
|
- type: recall_at_100 |
|
value: 68.223 |
|
- type: recall_at_1000 |
|
value: 85.653 |
|
- type: recall_at_3 |
|
value: 28.784 |
|
- type: recall_at_5 |
|
value: 35.66 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: dbpedia-entity |
|
name: MTEB DBPedia |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 9.516 |
|
- type: map_at_10 |
|
value: 21.439 |
|
- type: map_at_100 |
|
value: 31.517 |
|
- type: map_at_1000 |
|
value: 33.267 |
|
- type: map_at_3 |
|
value: 15.004999999999999 |
|
- type: map_at_5 |
|
value: 17.793999999999997 |
|
- type: mrr_at_1 |
|
value: 71.25 |
|
- type: mrr_at_10 |
|
value: 79.071 |
|
- type: mrr_at_100 |
|
value: 79.325 |
|
- type: mrr_at_1000 |
|
value: 79.33 |
|
- type: mrr_at_3 |
|
value: 77.708 |
|
- type: mrr_at_5 |
|
value: 78.546 |
|
- type: ndcg_at_1 |
|
value: 58.62500000000001 |
|
- type: ndcg_at_10 |
|
value: 44.889 |
|
- type: ndcg_at_100 |
|
value: 50.536 |
|
- type: ndcg_at_1000 |
|
value: 57.724 |
|
- type: ndcg_at_3 |
|
value: 49.32 |
|
- type: ndcg_at_5 |
|
value: 46.775 |
|
- type: precision_at_1 |
|
value: 71.25 |
|
- type: precision_at_10 |
|
value: 36.175000000000004 |
|
- type: precision_at_100 |
|
value: 11.940000000000001 |
|
- type: precision_at_1000 |
|
value: 2.178 |
|
- type: precision_at_3 |
|
value: 53.583000000000006 |
|
- type: precision_at_5 |
|
value: 45.550000000000004 |
|
- type: recall_at_1 |
|
value: 9.516 |
|
- type: recall_at_10 |
|
value: 27.028000000000002 |
|
- type: recall_at_100 |
|
value: 57.581 |
|
- type: recall_at_1000 |
|
value: 80.623 |
|
- type: recall_at_3 |
|
value: 16.313 |
|
- type: recall_at_5 |
|
value: 20.674 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/emotion |
|
name: MTEB EmotionClassification |
|
config: default |
|
split: test |
|
revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37 |
|
metrics: |
|
- type: accuracy |
|
value: 51.74999999999999 |
|
- type: f1 |
|
value: 46.46706502669774 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: fever |
|
name: MTEB FEVER |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 77.266 |
|
- type: map_at_10 |
|
value: 84.89999999999999 |
|
- type: map_at_100 |
|
value: 85.109 |
|
- type: map_at_1000 |
|
value: 85.123 |
|
- type: map_at_3 |
|
value: 83.898 |
|
- type: map_at_5 |
|
value: 84.541 |
|
- type: mrr_at_1 |
|
value: 83.138 |
|
- type: mrr_at_10 |
|
value: 89.37 |
|
- type: mrr_at_100 |
|
value: 89.432 |
|
- type: mrr_at_1000 |
|
value: 89.43299999999999 |
|
- type: mrr_at_3 |
|
value: 88.836 |
|
- type: mrr_at_5 |
|
value: 89.21 |
|
- type: ndcg_at_1 |
|
value: 83.138 |
|
- type: ndcg_at_10 |
|
value: 88.244 |
|
- type: ndcg_at_100 |
|
value: 88.98700000000001 |
|
- type: ndcg_at_1000 |
|
value: 89.21900000000001 |
|
- type: ndcg_at_3 |
|
value: 86.825 |
|
- type: ndcg_at_5 |
|
value: 87.636 |
|
- type: precision_at_1 |
|
value: 83.138 |
|
- type: precision_at_10 |
|
value: 10.47 |
|
- type: precision_at_100 |
|
value: 1.1079999999999999 |
|
- type: precision_at_1000 |
|
value: 0.11499999999999999 |
|
- type: precision_at_3 |
|
value: 32.933 |
|
- type: precision_at_5 |
|
value: 20.36 |
|
- type: recall_at_1 |
|
value: 77.266 |
|
- type: recall_at_10 |
|
value: 94.063 |
|
- type: recall_at_100 |
|
value: 96.993 |
|
- type: recall_at_1000 |
|
value: 98.414 |
|
- type: recall_at_3 |
|
value: 90.228 |
|
- type: recall_at_5 |
|
value: 92.328 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: fiqa |
|
name: MTEB FiQA2018 |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 22.319 |
|
- type: map_at_10 |
|
value: 36.943 |
|
- type: map_at_100 |
|
value: 38.951 |
|
- type: map_at_1000 |
|
value: 39.114 |
|
- type: map_at_3 |
|
value: 32.82 |
|
- type: map_at_5 |
|
value: 34.945 |
|
- type: mrr_at_1 |
|
value: 44.135999999999996 |
|
- type: mrr_at_10 |
|
value: 53.071999999999996 |
|
- type: mrr_at_100 |
|
value: 53.87 |
|
- type: mrr_at_1000 |
|
value: 53.90200000000001 |
|
- type: mrr_at_3 |
|
value: 50.77199999999999 |
|
- type: mrr_at_5 |
|
value: 52.129999999999995 |
|
- type: ndcg_at_1 |
|
value: 44.135999999999996 |
|
- type: ndcg_at_10 |
|
value: 44.836 |
|
- type: ndcg_at_100 |
|
value: 51.754 |
|
- type: ndcg_at_1000 |
|
value: 54.36 |
|
- type: ndcg_at_3 |
|
value: 41.658 |
|
- type: ndcg_at_5 |
|
value: 42.354 |
|
- type: precision_at_1 |
|
value: 44.135999999999996 |
|
- type: precision_at_10 |
|
value: 12.284 |
|
- type: precision_at_100 |
|
value: 1.952 |
|
- type: precision_at_1000 |
|
value: 0.242 |
|
- type: precision_at_3 |
|
value: 27.828999999999997 |
|
- type: precision_at_5 |
|
value: 20.093 |
|
- type: recall_at_1 |
|
value: 22.319 |
|
- type: recall_at_10 |
|
value: 51.528 |
|
- type: recall_at_100 |
|
value: 76.70700000000001 |
|
- type: recall_at_1000 |
|
value: 92.143 |
|
- type: recall_at_3 |
|
value: 38.641 |
|
- type: recall_at_5 |
|
value: 43.653999999999996 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: hotpotqa |
|
name: MTEB HotpotQA |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 40.182 |
|
- type: map_at_10 |
|
value: 65.146 |
|
- type: map_at_100 |
|
value: 66.023 |
|
- type: map_at_1000 |
|
value: 66.078 |
|
- type: map_at_3 |
|
value: 61.617999999999995 |
|
- type: map_at_5 |
|
value: 63.82299999999999 |
|
- type: mrr_at_1 |
|
value: 80.365 |
|
- type: mrr_at_10 |
|
value: 85.79 |
|
- type: mrr_at_100 |
|
value: 85.963 |
|
- type: mrr_at_1000 |
|
value: 85.968 |
|
- type: mrr_at_3 |
|
value: 84.952 |
|
- type: mrr_at_5 |
|
value: 85.503 |
|
- type: ndcg_at_1 |
|
value: 80.365 |
|
- type: ndcg_at_10 |
|
value: 73.13499999999999 |
|
- type: ndcg_at_100 |
|
value: 76.133 |
|
- type: ndcg_at_1000 |
|
value: 77.151 |
|
- type: ndcg_at_3 |
|
value: 68.255 |
|
- type: ndcg_at_5 |
|
value: 70.978 |
|
- type: precision_at_1 |
|
value: 80.365 |
|
- type: precision_at_10 |
|
value: 15.359 |
|
- type: precision_at_100 |
|
value: 1.7690000000000001 |
|
- type: precision_at_1000 |
|
value: 0.19 |
|
- type: precision_at_3 |
|
value: 44.024 |
|
- type: precision_at_5 |
|
value: 28.555999999999997 |
|
- type: recall_at_1 |
|
value: 40.182 |
|
- type: recall_at_10 |
|
value: 76.793 |
|
- type: recall_at_100 |
|
value: 88.474 |
|
- type: recall_at_1000 |
|
value: 95.159 |
|
- type: recall_at_3 |
|
value: 66.036 |
|
- type: recall_at_5 |
|
value: 71.391 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/imdb |
|
name: MTEB ImdbClassification |
|
config: default |
|
split: test |
|
revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7 |
|
metrics: |
|
- type: accuracy |
|
value: 92.7796 |
|
- type: ap |
|
value: 89.24883716810874 |
|
- type: f1 |
|
value: 92.7706903433313 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: msmarco |
|
name: MTEB MSMARCO |
|
config: default |
|
split: dev |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 22.016 |
|
- type: map_at_10 |
|
value: 34.408 |
|
- type: map_at_100 |
|
value: 35.592 |
|
- type: map_at_1000 |
|
value: 35.64 |
|
- type: map_at_3 |
|
value: 30.459999999999997 |
|
- type: map_at_5 |
|
value: 32.721000000000004 |
|
- type: mrr_at_1 |
|
value: 22.593 |
|
- type: mrr_at_10 |
|
value: 34.993 |
|
- type: mrr_at_100 |
|
value: 36.113 |
|
- type: mrr_at_1000 |
|
value: 36.156 |
|
- type: mrr_at_3 |
|
value: 31.101 |
|
- type: mrr_at_5 |
|
value: 33.364 |
|
- type: ndcg_at_1 |
|
value: 22.579 |
|
- type: ndcg_at_10 |
|
value: 41.404999999999994 |
|
- type: ndcg_at_100 |
|
value: 47.018 |
|
- type: ndcg_at_1000 |
|
value: 48.211999999999996 |
|
- type: ndcg_at_3 |
|
value: 33.389 |
|
- type: ndcg_at_5 |
|
value: 37.425000000000004 |
|
- type: precision_at_1 |
|
value: 22.579 |
|
- type: precision_at_10 |
|
value: 6.59 |
|
- type: precision_at_100 |
|
value: 0.938 |
|
- type: precision_at_1000 |
|
value: 0.104 |
|
- type: precision_at_3 |
|
value: 14.241000000000001 |
|
- type: precision_at_5 |
|
value: 10.59 |
|
- type: recall_at_1 |
|
value: 22.016 |
|
- type: recall_at_10 |
|
value: 62.927 |
|
- type: recall_at_100 |
|
value: 88.72 |
|
- type: recall_at_1000 |
|
value: 97.80799999999999 |
|
- type: recall_at_3 |
|
value: 41.229 |
|
- type: recall_at_5 |
|
value: 50.88 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/mtop_domain |
|
name: MTEB MTOPDomainClassification (en) |
|
config: en |
|
split: test |
|
revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf |
|
metrics: |
|
- type: accuracy |
|
value: 94.01732786137711 |
|
- type: f1 |
|
value: 93.76353126402202 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/mtop_intent |
|
name: MTEB MTOPIntentClassification (en) |
|
config: en |
|
split: test |
|
revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba |
|
metrics: |
|
- type: accuracy |
|
value: 76.91746466028272 |
|
- type: f1 |
|
value: 57.715651682646765 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/amazon_massive_intent |
|
name: MTEB MassiveIntentClassification (en) |
|
config: en |
|
split: test |
|
revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 |
|
metrics: |
|
- type: accuracy |
|
value: 76.5030262273033 |
|
- type: f1 |
|
value: 74.6693629986121 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/amazon_massive_scenario |
|
name: MTEB MassiveScenarioClassification (en) |
|
config: en |
|
split: test |
|
revision: 7d571f92784cd94a019292a1f45445077d0ef634 |
|
metrics: |
|
- type: accuracy |
|
value: 79.74781439139207 |
|
- type: f1 |
|
value: 79.96684171018774 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: mteb/medrxiv-clustering-p2p |
|
name: MTEB MedrxivClusteringP2P |
|
config: default |
|
split: test |
|
revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73 |
|
metrics: |
|
- type: v_measure |
|
value: 33.2156206892017 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: mteb/medrxiv-clustering-s2s |
|
name: MTEB MedrxivClusteringS2S |
|
config: default |
|
split: test |
|
revision: 35191c8c0dca72d8ff3efcd72aa802307d469663 |
|
metrics: |
|
- type: v_measure |
|
value: 31.180539484816137 |
|
- task: |
|
type: Reranking |
|
dataset: |
|
type: mteb/mind_small |
|
name: MTEB MindSmallReranking |
|
config: default |
|
split: test |
|
revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69 |
|
metrics: |
|
- type: map |
|
value: 32.51125957874274 |
|
- type: mrr |
|
value: 33.777037359249995 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: nfcorpus |
|
name: MTEB NFCorpus |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 7.248 |
|
- type: map_at_10 |
|
value: 15.340000000000002 |
|
- type: map_at_100 |
|
value: 19.591 |
|
- type: map_at_1000 |
|
value: 21.187 |
|
- type: map_at_3 |
|
value: 11.329 |
|
- type: map_at_5 |
|
value: 13.209999999999999 |
|
- type: mrr_at_1 |
|
value: 47.678 |
|
- type: mrr_at_10 |
|
value: 57.493 |
|
- type: mrr_at_100 |
|
value: 58.038999999999994 |
|
- type: mrr_at_1000 |
|
value: 58.07 |
|
- type: mrr_at_3 |
|
value: 55.36600000000001 |
|
- type: mrr_at_5 |
|
value: 56.635999999999996 |
|
- type: ndcg_at_1 |
|
value: 46.129999999999995 |
|
- type: ndcg_at_10 |
|
value: 38.653999999999996 |
|
- type: ndcg_at_100 |
|
value: 36.288 |
|
- type: ndcg_at_1000 |
|
value: 44.765 |
|
- type: ndcg_at_3 |
|
value: 43.553 |
|
- type: ndcg_at_5 |
|
value: 41.317 |
|
- type: precision_at_1 |
|
value: 47.368 |
|
- type: precision_at_10 |
|
value: 28.669 |
|
- type: precision_at_100 |
|
value: 9.158 |
|
- type: precision_at_1000 |
|
value: 2.207 |
|
- type: precision_at_3 |
|
value: 40.97 |
|
- type: precision_at_5 |
|
value: 35.604 |
|
- type: recall_at_1 |
|
value: 7.248 |
|
- type: recall_at_10 |
|
value: 19.46 |
|
- type: recall_at_100 |
|
value: 37.214000000000006 |
|
- type: recall_at_1000 |
|
value: 67.64099999999999 |
|
- type: recall_at_3 |
|
value: 12.025 |
|
- type: recall_at_5 |
|
value: 15.443999999999999 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: nq |
|
name: MTEB NQ |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 31.595000000000002 |
|
- type: map_at_10 |
|
value: 47.815999999999995 |
|
- type: map_at_100 |
|
value: 48.811 |
|
- type: map_at_1000 |
|
value: 48.835 |
|
- type: map_at_3 |
|
value: 43.225 |
|
- type: map_at_5 |
|
value: 46.017 |
|
- type: mrr_at_1 |
|
value: 35.689 |
|
- type: mrr_at_10 |
|
value: 50.341 |
|
- type: mrr_at_100 |
|
value: 51.044999999999995 |
|
- type: mrr_at_1000 |
|
value: 51.062 |
|
- type: mrr_at_3 |
|
value: 46.553 |
|
- type: mrr_at_5 |
|
value: 48.918 |
|
- type: ndcg_at_1 |
|
value: 35.66 |
|
- type: ndcg_at_10 |
|
value: 55.859 |
|
- type: ndcg_at_100 |
|
value: 59.864 |
|
- type: ndcg_at_1000 |
|
value: 60.419999999999995 |
|
- type: ndcg_at_3 |
|
value: 47.371 |
|
- type: ndcg_at_5 |
|
value: 51.995000000000005 |
|
- type: precision_at_1 |
|
value: 35.66 |
|
- type: precision_at_10 |
|
value: 9.27 |
|
- type: precision_at_100 |
|
value: 1.1520000000000001 |
|
- type: precision_at_1000 |
|
value: 0.12 |
|
- type: precision_at_3 |
|
value: 21.63 |
|
- type: precision_at_5 |
|
value: 15.655 |
|
- type: recall_at_1 |
|
value: 31.595000000000002 |
|
- type: recall_at_10 |
|
value: 77.704 |
|
- type: recall_at_100 |
|
value: 94.774 |
|
- type: recall_at_1000 |
|
value: 98.919 |
|
- type: recall_at_3 |
|
value: 56.052 |
|
- type: recall_at_5 |
|
value: 66.623 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: quora |
|
name: MTEB QuoraRetrieval |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 71.489 |
|
- type: map_at_10 |
|
value: 85.411 |
|
- type: map_at_100 |
|
value: 86.048 |
|
- type: map_at_1000 |
|
value: 86.064 |
|
- type: map_at_3 |
|
value: 82.587 |
|
- type: map_at_5 |
|
value: 84.339 |
|
- type: mrr_at_1 |
|
value: 82.28 |
|
- type: mrr_at_10 |
|
value: 88.27199999999999 |
|
- type: mrr_at_100 |
|
value: 88.362 |
|
- type: mrr_at_1000 |
|
value: 88.362 |
|
- type: mrr_at_3 |
|
value: 87.372 |
|
- type: mrr_at_5 |
|
value: 87.995 |
|
- type: ndcg_at_1 |
|
value: 82.27 |
|
- type: ndcg_at_10 |
|
value: 89.023 |
|
- type: ndcg_at_100 |
|
value: 90.191 |
|
- type: ndcg_at_1000 |
|
value: 90.266 |
|
- type: ndcg_at_3 |
|
value: 86.37 |
|
- type: ndcg_at_5 |
|
value: 87.804 |
|
- type: precision_at_1 |
|
value: 82.27 |
|
- type: precision_at_10 |
|
value: 13.469000000000001 |
|
- type: precision_at_100 |
|
value: 1.533 |
|
- type: precision_at_1000 |
|
value: 0.157 |
|
- type: precision_at_3 |
|
value: 37.797 |
|
- type: precision_at_5 |
|
value: 24.734 |
|
- type: recall_at_1 |
|
value: 71.489 |
|
- type: recall_at_10 |
|
value: 95.824 |
|
- type: recall_at_100 |
|
value: 99.70599999999999 |
|
- type: recall_at_1000 |
|
value: 99.979 |
|
- type: recall_at_3 |
|
value: 88.099 |
|
- type: recall_at_5 |
|
value: 92.285 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: mteb/reddit-clustering |
|
name: MTEB RedditClustering |
|
config: default |
|
split: test |
|
revision: 24640382cdbf8abc73003fb0fa6d111a705499eb |
|
metrics: |
|
- type: v_measure |
|
value: 60.52398807444541 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: mteb/reddit-clustering-p2p |
|
name: MTEB RedditClusteringP2P |
|
config: default |
|
split: test |
|
revision: 282350215ef01743dc01b456c7f5241fa8937f16 |
|
metrics: |
|
- type: v_measure |
|
value: 65.34855891507871 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: scidocs |
|
name: MTEB SCIDOCS |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 5.188000000000001 |
|
- type: map_at_10 |
|
value: 13.987 |
|
- type: map_at_100 |
|
value: 16.438 |
|
- type: map_at_1000 |
|
value: 16.829 |
|
- type: map_at_3 |
|
value: 9.767000000000001 |
|
- type: map_at_5 |
|
value: 11.912 |
|
- type: mrr_at_1 |
|
value: 25.6 |
|
- type: mrr_at_10 |
|
value: 37.744 |
|
- type: mrr_at_100 |
|
value: 38.847 |
|
- type: mrr_at_1000 |
|
value: 38.894 |
|
- type: mrr_at_3 |
|
value: 34.166999999999994 |
|
- type: mrr_at_5 |
|
value: 36.207 |
|
- type: ndcg_at_1 |
|
value: 25.6 |
|
- type: ndcg_at_10 |
|
value: 22.980999999999998 |
|
- type: ndcg_at_100 |
|
value: 32.039 |
|
- type: ndcg_at_1000 |
|
value: 38.157000000000004 |
|
- type: ndcg_at_3 |
|
value: 21.567 |
|
- type: ndcg_at_5 |
|
value: 19.070999999999998 |
|
- type: precision_at_1 |
|
value: 25.6 |
|
- type: precision_at_10 |
|
value: 12.02 |
|
- type: precision_at_100 |
|
value: 2.5100000000000002 |
|
- type: precision_at_1000 |
|
value: 0.396 |
|
- type: precision_at_3 |
|
value: 20.333000000000002 |
|
- type: precision_at_5 |
|
value: 16.98 |
|
- type: recall_at_1 |
|
value: 5.188000000000001 |
|
- type: recall_at_10 |
|
value: 24.372 |
|
- type: recall_at_100 |
|
value: 50.934999999999995 |
|
- type: recall_at_1000 |
|
value: 80.477 |
|
- type: recall_at_3 |
|
value: 12.363 |
|
- type: recall_at_5 |
|
value: 17.203 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: mteb/sickr-sts |
|
name: MTEB SICK-R |
|
config: default |
|
split: test |
|
revision: a6ea5a8cab320b040a23452cc28066d9beae2cee |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 87.24286275535398 |
|
- type: cos_sim_spearman |
|
value: 82.62333770991818 |
|
- type: euclidean_pearson |
|
value: 84.60353717637284 |
|
- type: euclidean_spearman |
|
value: 82.32990108810047 |
|
- type: manhattan_pearson |
|
value: 84.6089049738196 |
|
- type: manhattan_spearman |
|
value: 82.33361785438936 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: mteb/sts12-sts |
|
name: MTEB STS12 |
|
config: default |
|
split: test |
|
revision: a0d554a64d88156834ff5ae9920b964011b16384 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 87.87428858503165 |
|
- type: cos_sim_spearman |
|
value: 79.09145886519929 |
|
- type: euclidean_pearson |
|
value: 86.42669231664036 |
|
- type: euclidean_spearman |
|
value: 80.03127375435449 |
|
- type: manhattan_pearson |
|
value: 86.41330338305022 |
|
- type: manhattan_spearman |
|
value: 80.02492538673368 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: mteb/sts13-sts |
|
name: MTEB STS13 |
|
config: default |
|
split: test |
|
revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 88.67912277322645 |
|
- type: cos_sim_spearman |
|
value: 89.6171319711762 |
|
- type: euclidean_pearson |
|
value: 86.56571917398725 |
|
- type: euclidean_spearman |
|
value: 87.71216907898948 |
|
- type: manhattan_pearson |
|
value: 86.57459050182473 |
|
- type: manhattan_spearman |
|
value: 87.71916648349993 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: mteb/sts14-sts |
|
name: MTEB STS14 |
|
config: default |
|
split: test |
|
revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 86.71957379085862 |
|
- type: cos_sim_spearman |
|
value: 85.01784075851465 |
|
- type: euclidean_pearson |
|
value: 84.7407848472801 |
|
- type: euclidean_spearman |
|
value: 84.61063091345538 |
|
- type: manhattan_pearson |
|
value: 84.71494352494403 |
|
- type: manhattan_spearman |
|
value: 84.58772077604254 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: mteb/sts15-sts |
|
name: MTEB STS15 |
|
config: default |
|
split: test |
|
revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 88.40508326325175 |
|
- type: cos_sim_spearman |
|
value: 89.50912897763186 |
|
- type: euclidean_pearson |
|
value: 87.82349070086627 |
|
- type: euclidean_spearman |
|
value: 88.44179162727521 |
|
- type: manhattan_pearson |
|
value: 87.80181927025595 |
|
- type: manhattan_spearman |
|
value: 88.43205129636243 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: mteb/sts16-sts |
|
name: MTEB STS16 |
|
config: default |
|
split: test |
|
revision: 4d8694f8f0e0100860b497b999b3dbed754a0513 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 85.35846741715478 |
|
- type: cos_sim_spearman |
|
value: 86.61172476741842 |
|
- type: euclidean_pearson |
|
value: 84.60123125491637 |
|
- type: euclidean_spearman |
|
value: 85.3001948141827 |
|
- type: manhattan_pearson |
|
value: 84.56231142658329 |
|
- type: manhattan_spearman |
|
value: 85.23579900798813 |
|
- 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: 88.94539129818824 |
|
- type: cos_sim_spearman |
|
value: 88.99349064256742 |
|
- type: euclidean_pearson |
|
value: 88.7142444640351 |
|
- type: euclidean_spearman |
|
value: 88.34120813505011 |
|
- type: manhattan_pearson |
|
value: 88.70363008238084 |
|
- type: manhattan_spearman |
|
value: 88.31952816956954 |
|
- 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: 68.29910260369893 |
|
- type: cos_sim_spearman |
|
value: 68.79263346213466 |
|
- type: euclidean_pearson |
|
value: 68.41627521422252 |
|
- type: euclidean_spearman |
|
value: 66.61602587398579 |
|
- type: manhattan_pearson |
|
value: 68.49402183447361 |
|
- type: manhattan_spearman |
|
value: 66.80157792354453 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: mteb/stsbenchmark-sts |
|
name: MTEB STSBenchmark |
|
config: default |
|
split: test |
|
revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 87.43703906343708 |
|
- type: cos_sim_spearman |
|
value: 89.06081805093662 |
|
- type: euclidean_pearson |
|
value: 87.48311456299662 |
|
- type: euclidean_spearman |
|
value: 88.07417597580013 |
|
- type: manhattan_pearson |
|
value: 87.48202249768894 |
|
- type: manhattan_spearman |
|
value: 88.04758031111642 |
|
- task: |
|
type: Reranking |
|
dataset: |
|
type: mteb/scidocs-reranking |
|
name: MTEB SciDocsRR |
|
config: default |
|
split: test |
|
revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab |
|
metrics: |
|
- type: map |
|
value: 87.49080620485203 |
|
- type: mrr |
|
value: 96.19145378949301 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: scifact |
|
name: MTEB SciFact |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 59.317 |
|
- type: map_at_10 |
|
value: 69.296 |
|
- type: map_at_100 |
|
value: 69.738 |
|
- type: map_at_1000 |
|
value: 69.759 |
|
- type: map_at_3 |
|
value: 66.12599999999999 |
|
- type: map_at_5 |
|
value: 67.532 |
|
- type: mrr_at_1 |
|
value: 62 |
|
- type: mrr_at_10 |
|
value: 70.176 |
|
- type: mrr_at_100 |
|
value: 70.565 |
|
- type: mrr_at_1000 |
|
value: 70.583 |
|
- type: mrr_at_3 |
|
value: 67.833 |
|
- type: mrr_at_5 |
|
value: 68.93299999999999 |
|
- type: ndcg_at_1 |
|
value: 62 |
|
- type: ndcg_at_10 |
|
value: 74.069 |
|
- type: ndcg_at_100 |
|
value: 76.037 |
|
- type: ndcg_at_1000 |
|
value: 76.467 |
|
- type: ndcg_at_3 |
|
value: 68.628 |
|
- type: ndcg_at_5 |
|
value: 70.57600000000001 |
|
- type: precision_at_1 |
|
value: 62 |
|
- type: precision_at_10 |
|
value: 10 |
|
- type: precision_at_100 |
|
value: 1.097 |
|
- type: precision_at_1000 |
|
value: 0.11299999999999999 |
|
- type: precision_at_3 |
|
value: 26.667 |
|
- type: precision_at_5 |
|
value: 17.4 |
|
- type: recall_at_1 |
|
value: 59.317 |
|
- type: recall_at_10 |
|
value: 87.822 |
|
- type: recall_at_100 |
|
value: 96.833 |
|
- type: recall_at_1000 |
|
value: 100 |
|
- type: recall_at_3 |
|
value: 73.06099999999999 |
|
- type: recall_at_5 |
|
value: 77.928 |
|
- task: |
|
type: PairClassification |
|
dataset: |
|
type: mteb/sprintduplicatequestions-pairclassification |
|
name: MTEB SprintDuplicateQuestions |
|
config: default |
|
split: test |
|
revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46 |
|
metrics: |
|
- type: cos_sim_accuracy |
|
value: 99.88910891089108 |
|
- type: cos_sim_ap |
|
value: 97.236958456951 |
|
- type: cos_sim_f1 |
|
value: 94.39999999999999 |
|
- type: cos_sim_precision |
|
value: 94.39999999999999 |
|
- type: cos_sim_recall |
|
value: 94.39999999999999 |
|
- type: dot_accuracy |
|
value: 99.82574257425742 |
|
- type: dot_ap |
|
value: 94.94344759441888 |
|
- type: dot_f1 |
|
value: 91.17352056168507 |
|
- type: dot_precision |
|
value: 91.44869215291752 |
|
- type: dot_recall |
|
value: 90.9 |
|
- type: euclidean_accuracy |
|
value: 99.88415841584158 |
|
- type: euclidean_ap |
|
value: 97.2044250782305 |
|
- type: euclidean_f1 |
|
value: 94.210786739238 |
|
- type: euclidean_precision |
|
value: 93.24191968658178 |
|
- type: euclidean_recall |
|
value: 95.19999999999999 |
|
- type: manhattan_accuracy |
|
value: 99.88613861386139 |
|
- type: manhattan_ap |
|
value: 97.20683205497689 |
|
- type: manhattan_f1 |
|
value: 94.2643391521197 |
|
- type: manhattan_precision |
|
value: 94.02985074626866 |
|
- type: manhattan_recall |
|
value: 94.5 |
|
- type: max_accuracy |
|
value: 99.88910891089108 |
|
- type: max_ap |
|
value: 97.236958456951 |
|
- type: max_f1 |
|
value: 94.39999999999999 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: mteb/stackexchange-clustering |
|
name: MTEB StackExchangeClustering |
|
config: default |
|
split: test |
|
revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259 |
|
metrics: |
|
- type: v_measure |
|
value: 66.53940781726187 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: mteb/stackexchange-clustering-p2p |
|
name: MTEB StackExchangeClusteringP2P |
|
config: default |
|
split: test |
|
revision: 815ca46b2622cec33ccafc3735d572c266efdb44 |
|
metrics: |
|
- type: v_measure |
|
value: 36.71865011295108 |
|
- task: |
|
type: Reranking |
|
dataset: |
|
type: mteb/stackoverflowdupquestions-reranking |
|
name: MTEB StackOverflowDupQuestions |
|
config: default |
|
split: test |
|
revision: e185fbe320c72810689fc5848eb6114e1ef5ec69 |
|
metrics: |
|
- type: map |
|
value: 55.3218674533331 |
|
- type: mrr |
|
value: 56.28279910449028 |
|
- task: |
|
type: Summarization |
|
dataset: |
|
type: mteb/summeval |
|
name: MTEB SummEval |
|
config: default |
|
split: test |
|
revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 30.723915667479673 |
|
- type: cos_sim_spearman |
|
value: 32.029070449745234 |
|
- type: dot_pearson |
|
value: 28.864944212481454 |
|
- type: dot_spearman |
|
value: 27.939266999596725 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: trec-covid |
|
name: MTEB TRECCOVID |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 0.231 |
|
- type: map_at_10 |
|
value: 1.949 |
|
- type: map_at_100 |
|
value: 10.023 |
|
- type: map_at_1000 |
|
value: 23.485 |
|
- type: map_at_3 |
|
value: 0.652 |
|
- type: map_at_5 |
|
value: 1.054 |
|
- type: mrr_at_1 |
|
value: 86 |
|
- type: mrr_at_10 |
|
value: 92.067 |
|
- type: mrr_at_100 |
|
value: 92.067 |
|
- type: mrr_at_1000 |
|
value: 92.067 |
|
- type: mrr_at_3 |
|
value: 91.667 |
|
- type: mrr_at_5 |
|
value: 92.067 |
|
- type: ndcg_at_1 |
|
value: 83 |
|
- type: ndcg_at_10 |
|
value: 76.32900000000001 |
|
- type: ndcg_at_100 |
|
value: 54.662 |
|
- type: ndcg_at_1000 |
|
value: 48.062 |
|
- type: ndcg_at_3 |
|
value: 81.827 |
|
- type: ndcg_at_5 |
|
value: 80.664 |
|
- type: precision_at_1 |
|
value: 86 |
|
- type: precision_at_10 |
|
value: 80 |
|
- type: precision_at_100 |
|
value: 55.48 |
|
- type: precision_at_1000 |
|
value: 20.938000000000002 |
|
- type: precision_at_3 |
|
value: 85.333 |
|
- type: precision_at_5 |
|
value: 84.39999999999999 |
|
- type: recall_at_1 |
|
value: 0.231 |
|
- type: recall_at_10 |
|
value: 2.158 |
|
- type: recall_at_100 |
|
value: 13.344000000000001 |
|
- type: recall_at_1000 |
|
value: 44.31 |
|
- type: recall_at_3 |
|
value: 0.6779999999999999 |
|
- type: recall_at_5 |
|
value: 1.13 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: webis-touche2020 |
|
name: MTEB Touche2020 |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 2.524 |
|
- type: map_at_10 |
|
value: 10.183 |
|
- type: map_at_100 |
|
value: 16.625 |
|
- type: map_at_1000 |
|
value: 18.017 |
|
- type: map_at_3 |
|
value: 5.169 |
|
- type: map_at_5 |
|
value: 6.772 |
|
- type: mrr_at_1 |
|
value: 32.653 |
|
- type: mrr_at_10 |
|
value: 47.128 |
|
- type: mrr_at_100 |
|
value: 48.458 |
|
- type: mrr_at_1000 |
|
value: 48.473 |
|
- type: mrr_at_3 |
|
value: 44.897999999999996 |
|
- type: mrr_at_5 |
|
value: 45.306000000000004 |
|
- type: ndcg_at_1 |
|
value: 30.612000000000002 |
|
- type: ndcg_at_10 |
|
value: 24.928 |
|
- type: ndcg_at_100 |
|
value: 37.613 |
|
- type: ndcg_at_1000 |
|
value: 48.528 |
|
- type: ndcg_at_3 |
|
value: 28.829 |
|
- type: ndcg_at_5 |
|
value: 25.237 |
|
- type: precision_at_1 |
|
value: 32.653 |
|
- type: precision_at_10 |
|
value: 22.448999999999998 |
|
- type: precision_at_100 |
|
value: 8.02 |
|
- type: precision_at_1000 |
|
value: 1.537 |
|
- type: precision_at_3 |
|
value: 30.612000000000002 |
|
- type: precision_at_5 |
|
value: 24.490000000000002 |
|
- type: recall_at_1 |
|
value: 2.524 |
|
- type: recall_at_10 |
|
value: 16.38 |
|
- type: recall_at_100 |
|
value: 49.529 |
|
- type: recall_at_1000 |
|
value: 83.598 |
|
- type: recall_at_3 |
|
value: 6.411 |
|
- type: recall_at_5 |
|
value: 8.932 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/toxic_conversations_50k |
|
name: MTEB ToxicConversationsClassification |
|
config: default |
|
split: test |
|
revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c |
|
metrics: |
|
- type: accuracy |
|
value: 71.09020000000001 |
|
- type: ap |
|
value: 14.451710060978993 |
|
- type: f1 |
|
value: 54.7874410609049 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/tweet_sentiment_extraction |
|
name: MTEB TweetSentimentExtractionClassification |
|
config: default |
|
split: test |
|
revision: d604517c81ca91fe16a244d1248fc021f9ecee7a |
|
metrics: |
|
- type: accuracy |
|
value: 59.745331069609506 |
|
- type: f1 |
|
value: 60.08387848592697 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: mteb/twentynewsgroups-clustering |
|
name: MTEB TwentyNewsgroupsClustering |
|
config: default |
|
split: test |
|
revision: 6125ec4e24fa026cec8a478383ee943acfbd5449 |
|
metrics: |
|
- type: v_measure |
|
value: 51.71549485462037 |
|
- task: |
|
type: PairClassification |
|
dataset: |
|
type: mteb/twittersemeval2015-pairclassification |
|
name: MTEB TwitterSemEval2015 |
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config: default |
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split: test |
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revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1 |
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metrics: |
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- type: cos_sim_accuracy |
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value: 87.39345532574357 |
|
- type: cos_sim_ap |
|
value: 78.16796549696478 |
|
- type: cos_sim_f1 |
|
value: 71.27713276123171 |
|
- type: cos_sim_precision |
|
value: 68.3115626511853 |
|
- type: cos_sim_recall |
|
value: 74.51187335092348 |
|
- type: dot_accuracy |
|
value: 85.12248912201228 |
|
- type: dot_ap |
|
value: 69.26039256107077 |
|
- type: dot_f1 |
|
value: 65.04294321240867 |
|
- type: dot_precision |
|
value: 63.251059586138126 |
|
- type: dot_recall |
|
value: 66.93931398416886 |
|
- type: euclidean_accuracy |
|
value: 87.07754664123503 |
|
- type: euclidean_ap |
|
value: 77.7872176038945 |
|
- type: euclidean_f1 |
|
value: 70.85587801278899 |
|
- type: euclidean_precision |
|
value: 66.3519115614924 |
|
- type: euclidean_recall |
|
value: 76.01583113456465 |
|
- type: manhattan_accuracy |
|
value: 87.07754664123503 |
|
- type: manhattan_ap |
|
value: 77.7341400185556 |
|
- type: manhattan_f1 |
|
value: 70.80310880829015 |
|
- type: manhattan_precision |
|
value: 69.54198473282443 |
|
- type: manhattan_recall |
|
value: 72.1108179419525 |
|
- type: max_accuracy |
|
value: 87.39345532574357 |
|
- type: max_ap |
|
value: 78.16796549696478 |
|
- type: max_f1 |
|
value: 71.27713276123171 |
|
- task: |
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type: PairClassification |
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dataset: |
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type: mteb/twitterurlcorpus-pairclassification |
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name: MTEB TwitterURLCorpus |
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config: default |
|
split: test |
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revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf |
|
metrics: |
|
- type: cos_sim_accuracy |
|
value: 89.09457833663213 |
|
- type: cos_sim_ap |
|
value: 86.33024314706873 |
|
- type: cos_sim_f1 |
|
value: 78.59623733719248 |
|
- type: cos_sim_precision |
|
value: 74.13322413322413 |
|
- type: cos_sim_recall |
|
value: 83.63104404065291 |
|
- type: dot_accuracy |
|
value: 88.3086894089339 |
|
- type: dot_ap |
|
value: 83.92225241805097 |
|
- type: dot_f1 |
|
value: 76.8721826377781 |
|
- type: dot_precision |
|
value: 72.8168044077135 |
|
- type: dot_recall |
|
value: 81.40591315060055 |
|
- type: euclidean_accuracy |
|
value: 88.77052043311213 |
|
- type: euclidean_ap |
|
value: 85.7410710218755 |
|
- type: euclidean_f1 |
|
value: 77.97705489398781 |
|
- type: euclidean_precision |
|
value: 73.77713657598241 |
|
- type: euclidean_recall |
|
value: 82.68401601478288 |
|
- type: manhattan_accuracy |
|
value: 88.73753250281368 |
|
- type: manhattan_ap |
|
value: 85.72867199072802 |
|
- type: manhattan_f1 |
|
value: 77.89774182922812 |
|
- type: manhattan_precision |
|
value: 74.23787931635857 |
|
- type: manhattan_recall |
|
value: 81.93717277486911 |
|
- type: max_accuracy |
|
value: 89.09457833663213 |
|
- type: max_ap |
|
value: 86.33024314706873 |
|
- type: max_f1 |
|
value: 78.59623733719248 |
|
license: mit |
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language: |
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- en |
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--- |
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# [Universal AnglE Embedding](https://github.com/SeanLee97/AnglE) |
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📢 `WhereIsAI/UAE-Large-V1` **is licensed under MIT. Feel free to use it in any scenario.** |
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If you use it for academic papers, we would greatly appreciate it if you could cite us. 👉 [citation info](#citation). |
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**🤝 Follow us on:** |
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- GitHub: https://github.com/SeanLee97/AnglE. |
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- Arxiv: https://arxiv.org/abs/2309.12871 |
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🔥 Our universal English sentence embedding `WhereIsAI/UAE-Large-V1` achieves **SOTA** on the [MTEB Leaderboard](https://huggingface.co/spaces/mteb/leaderboard) with an average score of 64.64! |
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 |
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**🧑🤝🧑 Siblings:** |
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- [WhereIsAI/UAE-Code-Large-V1](https://huggingface.co/WhereIsAI/UAE-Code-Large-V1): This model can be used for code or GitHub issue similarity measurement. |
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# Usage |
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## 1. angle_emb |
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```bash |
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python -m pip install -U angle-emb |
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``` |
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1) Non-Retrieval Tasks |
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There is no need to specify any prompts. |
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```python |
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from angle_emb import AnglE |
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from scipy import spatial |
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angle = AnglE.from_pretrained('WhereIsAI/UAE-Large-V1', pooling_strategy='cls').cuda() |
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doc_vecs = angle.encode([ |
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'The weather is great!', |
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'The weather is very good!', |
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'i am going to bed' |
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]) |
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for i, dv1 in enumerate(doc_vecs): |
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for dv2 in doc_vecs[i+1:]: |
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print(1 - spatial.distance.cosine(dv1, dv2)) |
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``` |
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2) Retrieval Tasks |
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For retrieval purposes, please use the prompt `Prompts.C` for query (not for document). |
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```python |
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from angle_emb import AnglE, Prompts |
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from scipy import spatial |
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angle = AnglE.from_pretrained('WhereIsAI/UAE-Large-V1', pooling_strategy='cls').cuda() |
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qv = angle.encode(Prompts.C.format(text='what is the weather?')) |
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doc_vecs = angle.encode([ |
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'The weather is great!', |
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'it is rainy today.', |
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'i am going to bed' |
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]) |
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for dv in doc_vecs: |
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print(1 - spatial.distance.cosine(qv[0], dv)) |
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``` |
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## 2. sentence transformer |
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```python |
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from angle_emb import Prompts |
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from sentence_transformers import SentenceTransformer |
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model = SentenceTransformer("WhereIsAI/UAE-Large-V1").cuda() |
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qv = model.encode(Prompts.C.format(text='what is the weather?')) |
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doc_vecs = model.encode([ |
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'The weather is great!', |
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'it is rainy today.', |
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'i am going to bed' |
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]) |
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for dv in doc_vecs: |
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print(1 - spatial.distance.cosine(qv, dv)) |
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``` |
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# Citation |
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If you use our pre-trained models, welcome to support us by citing our work: |
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``` |
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@article{li2023angle, |
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title={AnglE-optimized Text Embeddings}, |
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author={Li, Xianming and Li, Jing}, |
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journal={arXiv preprint arXiv:2309.12871}, |
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year={2023} |
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} |
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``` |
