|
--- |
|
tags: |
|
- mteb |
|
model-index: |
|
- name: bge_finetuned |
|
results: |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/amazon_counterfactual |
|
name: MTEB AmazonCounterfactualClassification (en) |
|
config: en |
|
split: test |
|
revision: e8379541af4e31359cca9fbcf4b00f2671dba205 |
|
metrics: |
|
- type: accuracy |
|
value: 61.64179104477612 |
|
- type: ap |
|
value: 25.20497978200253 |
|
- type: f1 |
|
value: 55.51169205110252 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/amazon_polarity |
|
name: MTEB AmazonPolarityClassification |
|
config: default |
|
split: test |
|
revision: e2d317d38cd51312af73b3d32a06d1a08b442046 |
|
metrics: |
|
- type: accuracy |
|
value: 58.6114 |
|
- type: ap |
|
value: 55.013881977883706 |
|
- type: f1 |
|
value: 58.0798269108889 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/amazon_reviews_multi |
|
name: MTEB AmazonReviewsClassification (en) |
|
config: en |
|
split: test |
|
revision: 1399c76144fd37290681b995c656ef9b2e06e26d |
|
metrics: |
|
- type: accuracy |
|
value: 27.009999999999994 |
|
- type: f1 |
|
value: 26.230644551993027 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: arguana |
|
name: MTEB ArguAna |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 14.011000000000001 |
|
- type: map_at_10 |
|
value: 24.082 |
|
- type: map_at_100 |
|
value: 25.273 |
|
- type: map_at_1000 |
|
value: 25.336 |
|
- type: map_at_3 |
|
value: 20.341 |
|
- type: map_at_5 |
|
value: 22.155 |
|
- type: mrr_at_1 |
|
value: 14.651 |
|
- type: mrr_at_10 |
|
value: 24.306 |
|
- type: mrr_at_100 |
|
value: 25.503999999999998 |
|
- type: mrr_at_1000 |
|
value: 25.566 |
|
- type: mrr_at_3 |
|
value: 20.59 |
|
- type: mrr_at_5 |
|
value: 22.400000000000002 |
|
- type: ndcg_at_1 |
|
value: 14.011000000000001 |
|
- type: ndcg_at_10 |
|
value: 30.316 |
|
- type: ndcg_at_100 |
|
value: 36.146 |
|
- type: ndcg_at_1000 |
|
value: 37.972 |
|
- type: ndcg_at_3 |
|
value: 22.422 |
|
- type: ndcg_at_5 |
|
value: 25.727 |
|
- type: precision_at_1 |
|
value: 14.011000000000001 |
|
- type: precision_at_10 |
|
value: 5.0569999999999995 |
|
- type: precision_at_100 |
|
value: 0.7799999999999999 |
|
- type: precision_at_1000 |
|
value: 0.093 |
|
- type: precision_at_3 |
|
value: 9.483 |
|
- type: precision_at_5 |
|
value: 7.312 |
|
- type: recall_at_1 |
|
value: 14.011000000000001 |
|
- type: recall_at_10 |
|
value: 50.568999999999996 |
|
- type: recall_at_100 |
|
value: 77.952 |
|
- type: recall_at_1000 |
|
value: 92.674 |
|
- type: recall_at_3 |
|
value: 28.449999999999996 |
|
- type: recall_at_5 |
|
value: 36.558 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: mteb/arxiv-clustering-p2p |
|
name: MTEB ArxivClusteringP2P |
|
config: default |
|
split: test |
|
revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d |
|
metrics: |
|
- type: v_measure |
|
value: 21.580787107217457 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: mteb/arxiv-clustering-s2s |
|
name: MTEB ArxivClusteringS2S |
|
config: default |
|
split: test |
|
revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53 |
|
metrics: |
|
- type: v_measure |
|
value: 12.755947651867459 |
|
- task: |
|
type: Reranking |
|
dataset: |
|
type: mteb/askubuntudupquestions-reranking |
|
name: MTEB AskUbuntuDupQuestions |
|
config: default |
|
split: test |
|
revision: 2000358ca161889fa9c082cb41daa8dcfb161a54 |
|
metrics: |
|
- type: map |
|
value: 50.36895415359604 |
|
- type: mrr |
|
value: 62.93244075100032 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: mteb/biosses-sts |
|
name: MTEB BIOSSES |
|
config: default |
|
split: test |
|
revision: d3fb88f8f02e40887cd149695127462bbcf29b4a |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 54.84190098866484 |
|
- type: cos_sim_spearman |
|
value: 52.065644182348144 |
|
- type: euclidean_pearson |
|
value: 54.181073661388034 |
|
- type: euclidean_spearman |
|
value: 52.065644182348144 |
|
- type: manhattan_pearson |
|
value: 54.98368207013862 |
|
- type: manhattan_spearman |
|
value: 53.66387337016872 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/banking77 |
|
name: MTEB Banking77Classification |
|
config: default |
|
split: test |
|
revision: 0fd18e25b25c072e09e0d92ab615fda904d66300 |
|
metrics: |
|
- type: accuracy |
|
value: 63.48051948051948 |
|
- type: f1 |
|
value: 61.45740352513437 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: mteb/biorxiv-clustering-p2p |
|
name: MTEB BiorxivClusteringP2P |
|
config: default |
|
split: test |
|
revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40 |
|
metrics: |
|
- type: v_measure |
|
value: 16.23123129183937 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: mteb/biorxiv-clustering-s2s |
|
name: MTEB BiorxivClusteringS2S |
|
config: default |
|
split: test |
|
revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908 |
|
metrics: |
|
- type: v_measure |
|
value: 6.846095550717324 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: BeIR/cqadupstack |
|
name: MTEB CQADupstackAndroidRetrieval |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 14.587 |
|
- type: map_at_10 |
|
value: 20.032 |
|
- type: map_at_100 |
|
value: 21.2 |
|
- type: map_at_1000 |
|
value: 21.351 |
|
- type: map_at_3 |
|
value: 18.224 |
|
- type: map_at_5 |
|
value: 19.028 |
|
- type: mrr_at_1 |
|
value: 18.312 |
|
- type: mrr_at_10 |
|
value: 24.343999999999998 |
|
- type: mrr_at_100 |
|
value: 25.302000000000003 |
|
- type: mrr_at_1000 |
|
value: 25.385 |
|
- type: mrr_at_3 |
|
value: 22.461000000000002 |
|
- type: mrr_at_5 |
|
value: 23.219 |
|
- type: ndcg_at_1 |
|
value: 18.312 |
|
- type: ndcg_at_10 |
|
value: 24.05 |
|
- type: ndcg_at_100 |
|
value: 29.512 |
|
- type: ndcg_at_1000 |
|
value: 33.028999999999996 |
|
- type: ndcg_at_3 |
|
value: 20.947 |
|
- type: ndcg_at_5 |
|
value: 21.807000000000002 |
|
- type: precision_at_1 |
|
value: 18.312 |
|
- type: precision_at_10 |
|
value: 4.664 |
|
- type: precision_at_100 |
|
value: 0.9570000000000001 |
|
- type: precision_at_1000 |
|
value: 0.155 |
|
- type: precision_at_3 |
|
value: 10.11 |
|
- type: precision_at_5 |
|
value: 7.066999999999999 |
|
- type: recall_at_1 |
|
value: 14.587 |
|
- type: recall_at_10 |
|
value: 31.865 |
|
- type: recall_at_100 |
|
value: 55.922000000000004 |
|
- type: recall_at_1000 |
|
value: 80.878 |
|
- type: recall_at_3 |
|
value: 22.229 |
|
- type: recall_at_5 |
|
value: 25.09 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: BeIR/cqadupstack |
|
name: MTEB CQADupstackEnglishRetrieval |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 8.456 |
|
- type: map_at_10 |
|
value: 11.429 |
|
- type: map_at_100 |
|
value: 11.956 |
|
- type: map_at_1000 |
|
value: 12.04 |
|
- type: map_at_3 |
|
value: 10.309 |
|
- type: map_at_5 |
|
value: 11.006 |
|
- type: mrr_at_1 |
|
value: 10.637 |
|
- type: mrr_at_10 |
|
value: 14.047 |
|
- type: mrr_at_100 |
|
value: 14.591999999999999 |
|
- type: mrr_at_1000 |
|
value: 14.66 |
|
- type: mrr_at_3 |
|
value: 12.876999999999999 |
|
- type: mrr_at_5 |
|
value: 13.644 |
|
- type: ndcg_at_1 |
|
value: 10.637 |
|
- type: ndcg_at_10 |
|
value: 13.623 |
|
- type: ndcg_at_100 |
|
value: 16.337 |
|
- type: ndcg_at_1000 |
|
value: 18.881 |
|
- type: ndcg_at_3 |
|
value: 11.76 |
|
- type: ndcg_at_5 |
|
value: 12.803 |
|
- type: precision_at_1 |
|
value: 10.637 |
|
- type: precision_at_10 |
|
value: 2.611 |
|
- type: precision_at_100 |
|
value: 0.49899999999999994 |
|
- type: precision_at_1000 |
|
value: 0.08800000000000001 |
|
- type: precision_at_3 |
|
value: 5.7540000000000004 |
|
- type: precision_at_5 |
|
value: 4.306 |
|
- type: recall_at_1 |
|
value: 8.456 |
|
- type: recall_at_10 |
|
value: 17.543 |
|
- type: recall_at_100 |
|
value: 29.696 |
|
- type: recall_at_1000 |
|
value: 48.433 |
|
- type: recall_at_3 |
|
value: 12.299 |
|
- type: recall_at_5 |
|
value: 15.126000000000001 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: BeIR/cqadupstack |
|
name: MTEB CQADupstackGamingRetrieval |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 10.517999999999999 |
|
- type: map_at_10 |
|
value: 14.924999999999999 |
|
- type: map_at_100 |
|
value: 15.716 |
|
- type: map_at_1000 |
|
value: 15.804000000000002 |
|
- type: map_at_3 |
|
value: 13.228000000000002 |
|
- type: map_at_5 |
|
value: 14.155999999999999 |
|
- type: mrr_at_1 |
|
value: 12.790000000000001 |
|
- type: mrr_at_10 |
|
value: 17.122999999999998 |
|
- type: mrr_at_100 |
|
value: 17.874000000000002 |
|
- type: mrr_at_1000 |
|
value: 17.947 |
|
- type: mrr_at_3 |
|
value: 15.528 |
|
- type: mrr_at_5 |
|
value: 16.421 |
|
- type: ndcg_at_1 |
|
value: 12.790000000000001 |
|
- type: ndcg_at_10 |
|
value: 17.967 |
|
- type: ndcg_at_100 |
|
value: 22.016 |
|
- type: ndcg_at_1000 |
|
value: 24.57 |
|
- type: ndcg_at_3 |
|
value: 14.745 |
|
- type: ndcg_at_5 |
|
value: 16.247 |
|
- type: precision_at_1 |
|
value: 12.790000000000001 |
|
- type: precision_at_10 |
|
value: 3.229 |
|
- type: precision_at_100 |
|
value: 0.592 |
|
- type: precision_at_1000 |
|
value: 0.087 |
|
- type: precision_at_3 |
|
value: 6.792 |
|
- type: precision_at_5 |
|
value: 5.066 |
|
- type: recall_at_1 |
|
value: 10.517999999999999 |
|
- type: recall_at_10 |
|
value: 25.194 |
|
- type: recall_at_100 |
|
value: 43.858999999999995 |
|
- type: recall_at_1000 |
|
value: 63.410999999999994 |
|
- type: recall_at_3 |
|
value: 16.384999999999998 |
|
- type: recall_at_5 |
|
value: 20.09 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: BeIR/cqadupstack |
|
name: MTEB CQADupstackGisRetrieval |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 8.325000000000001 |
|
- type: map_at_10 |
|
value: 12.262 |
|
- type: map_at_100 |
|
value: 13.003 |
|
- type: map_at_1000 |
|
value: 13.126999999999999 |
|
- type: map_at_3 |
|
value: 10.946 |
|
- type: map_at_5 |
|
value: 11.581 |
|
- type: mrr_at_1 |
|
value: 9.379 |
|
- type: mrr_at_10 |
|
value: 13.527000000000001 |
|
- type: mrr_at_100 |
|
value: 14.249999999999998 |
|
- type: mrr_at_1000 |
|
value: 14.365 |
|
- type: mrr_at_3 |
|
value: 12.166 |
|
- type: mrr_at_5 |
|
value: 12.798000000000002 |
|
- type: ndcg_at_1 |
|
value: 9.379 |
|
- type: ndcg_at_10 |
|
value: 14.878 |
|
- type: ndcg_at_100 |
|
value: 19.17 |
|
- type: ndcg_at_1000 |
|
value: 22.861 |
|
- type: ndcg_at_3 |
|
value: 12.136 |
|
- type: ndcg_at_5 |
|
value: 13.209000000000001 |
|
- type: precision_at_1 |
|
value: 9.379 |
|
- type: precision_at_10 |
|
value: 2.5309999999999997 |
|
- type: precision_at_100 |
|
value: 0.505 |
|
- type: precision_at_1000 |
|
value: 0.086 |
|
- type: precision_at_3 |
|
value: 5.386 |
|
- type: precision_at_5 |
|
value: 3.887 |
|
- type: recall_at_1 |
|
value: 8.325000000000001 |
|
- type: recall_at_10 |
|
value: 21.886 |
|
- type: recall_at_100 |
|
value: 42.977 |
|
- type: recall_at_1000 |
|
value: 71.946 |
|
- type: recall_at_3 |
|
value: 14.123 |
|
- type: recall_at_5 |
|
value: 16.747 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: BeIR/cqadupstack |
|
name: MTEB CQADupstackMathematicaRetrieval |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 5.982 |
|
- type: map_at_10 |
|
value: 9.249 |
|
- type: map_at_100 |
|
value: 10.0 |
|
- type: map_at_1000 |
|
value: 10.127 |
|
- type: map_at_3 |
|
value: 7.913 |
|
- type: map_at_5 |
|
value: 8.540000000000001 |
|
- type: mrr_at_1 |
|
value: 7.960000000000001 |
|
- type: mrr_at_10 |
|
value: 11.703 |
|
- type: mrr_at_100 |
|
value: 12.43 |
|
- type: mrr_at_1000 |
|
value: 12.534999999999998 |
|
- type: mrr_at_3 |
|
value: 10.344000000000001 |
|
- type: mrr_at_5 |
|
value: 11.022 |
|
- type: ndcg_at_1 |
|
value: 7.960000000000001 |
|
- type: ndcg_at_10 |
|
value: 11.863 |
|
- type: ndcg_at_100 |
|
value: 16.086 |
|
- type: ndcg_at_1000 |
|
value: 19.738 |
|
- type: ndcg_at_3 |
|
value: 9.241000000000001 |
|
- type: ndcg_at_5 |
|
value: 10.228 |
|
- type: precision_at_1 |
|
value: 7.960000000000001 |
|
- type: precision_at_10 |
|
value: 2.4 |
|
- type: precision_at_100 |
|
value: 0.534 |
|
- type: precision_at_1000 |
|
value: 0.097 |
|
- type: precision_at_3 |
|
value: 4.561 |
|
- type: precision_at_5 |
|
value: 3.408 |
|
- type: recall_at_1 |
|
value: 5.982 |
|
- type: recall_at_10 |
|
value: 17.669999999999998 |
|
- type: recall_at_100 |
|
value: 37.261 |
|
- type: recall_at_1000 |
|
value: 64.416 |
|
- type: recall_at_3 |
|
value: 10.376000000000001 |
|
- type: recall_at_5 |
|
value: 12.933 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: BeIR/cqadupstack |
|
name: MTEB CQADupstackPhysicsRetrieval |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 9.068 |
|
- type: map_at_10 |
|
value: 12.101 |
|
- type: map_at_100 |
|
value: 12.828000000000001 |
|
- type: map_at_1000 |
|
value: 12.953000000000001 |
|
- type: map_at_3 |
|
value: 11.047 |
|
- type: map_at_5 |
|
value: 11.542 |
|
- type: mrr_at_1 |
|
value: 10.972 |
|
- type: mrr_at_10 |
|
value: 14.873 |
|
- type: mrr_at_100 |
|
value: 15.584000000000001 |
|
- type: mrr_at_1000 |
|
value: 15.681999999999999 |
|
- type: mrr_at_3 |
|
value: 13.523 |
|
- type: mrr_at_5 |
|
value: 14.254 |
|
- type: ndcg_at_1 |
|
value: 10.972 |
|
- type: ndcg_at_10 |
|
value: 14.557999999999998 |
|
- type: ndcg_at_100 |
|
value: 18.56 |
|
- type: ndcg_at_1000 |
|
value: 21.975 |
|
- type: ndcg_at_3 |
|
value: 12.436 |
|
- type: ndcg_at_5 |
|
value: 13.270999999999999 |
|
- type: precision_at_1 |
|
value: 10.972 |
|
- type: precision_at_10 |
|
value: 2.714 |
|
- type: precision_at_100 |
|
value: 0.5720000000000001 |
|
- type: precision_at_1000 |
|
value: 0.10200000000000001 |
|
- type: precision_at_3 |
|
value: 5.711 |
|
- type: precision_at_5 |
|
value: 4.1579999999999995 |
|
- type: recall_at_1 |
|
value: 9.068 |
|
- type: recall_at_10 |
|
value: 19.381999999999998 |
|
- type: recall_at_100 |
|
value: 37.602999999999994 |
|
- type: recall_at_1000 |
|
value: 62.376 |
|
- type: recall_at_3 |
|
value: 13.48 |
|
- type: recall_at_5 |
|
value: 15.506 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: BeIR/cqadupstack |
|
name: MTEB CQADupstackProgrammersRetrieval |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 8.206 |
|
- type: map_at_10 |
|
value: 12.032 |
|
- type: map_at_100 |
|
value: 12.992 |
|
- type: map_at_1000 |
|
value: 13.135 |
|
- type: map_at_3 |
|
value: 10.741 |
|
- type: map_at_5 |
|
value: 11.392 |
|
- type: mrr_at_1 |
|
value: 10.502 |
|
- type: mrr_at_10 |
|
value: 14.818999999999999 |
|
- type: mrr_at_100 |
|
value: 15.716 |
|
- type: mrr_at_1000 |
|
value: 15.823 |
|
- type: mrr_at_3 |
|
value: 13.375 |
|
- type: mrr_at_5 |
|
value: 14.169 |
|
- type: ndcg_at_1 |
|
value: 10.502 |
|
- type: ndcg_at_10 |
|
value: 14.790000000000001 |
|
- type: ndcg_at_100 |
|
value: 19.881999999999998 |
|
- type: ndcg_at_1000 |
|
value: 23.703 |
|
- type: ndcg_at_3 |
|
value: 12.281 |
|
- type: ndcg_at_5 |
|
value: 13.33 |
|
- type: precision_at_1 |
|
value: 10.502 |
|
- type: precision_at_10 |
|
value: 2.911 |
|
- type: precision_at_100 |
|
value: 0.668 |
|
- type: precision_at_1000 |
|
value: 0.11499999999999999 |
|
- type: precision_at_3 |
|
value: 6.012 |
|
- type: precision_at_5 |
|
value: 4.475 |
|
- type: recall_at_1 |
|
value: 8.206 |
|
- type: recall_at_10 |
|
value: 20.508000000000003 |
|
- type: recall_at_100 |
|
value: 43.568 |
|
- type: recall_at_1000 |
|
value: 71.56400000000001 |
|
- type: recall_at_3 |
|
value: 13.607 |
|
- type: recall_at_5 |
|
value: 16.211000000000002 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: BeIR/cqadupstack |
|
name: MTEB CQADupstackStatsRetrieval |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 6.4159999999999995 |
|
- type: map_at_10 |
|
value: 9.581000000000001 |
|
- type: map_at_100 |
|
value: 10.123999999999999 |
|
- type: map_at_1000 |
|
value: 10.226 |
|
- type: map_at_3 |
|
value: 8.51 |
|
- type: map_at_5 |
|
value: 9.078999999999999 |
|
- type: mrr_at_1 |
|
value: 7.515 |
|
- type: mrr_at_10 |
|
value: 10.801 |
|
- type: mrr_at_100 |
|
value: 11.373 |
|
- type: mrr_at_1000 |
|
value: 11.466999999999999 |
|
- type: mrr_at_3 |
|
value: 9.637 |
|
- type: mrr_at_5 |
|
value: 10.197000000000001 |
|
- type: ndcg_at_1 |
|
value: 7.515 |
|
- type: ndcg_at_10 |
|
value: 11.776 |
|
- type: ndcg_at_100 |
|
value: 14.776 |
|
- type: ndcg_at_1000 |
|
value: 17.7 |
|
- type: ndcg_at_3 |
|
value: 9.515 |
|
- type: ndcg_at_5 |
|
value: 10.511 |
|
- type: precision_at_1 |
|
value: 7.515 |
|
- type: precision_at_10 |
|
value: 2.086 |
|
- type: precision_at_100 |
|
value: 0.402 |
|
- type: precision_at_1000 |
|
value: 0.07100000000000001 |
|
- type: precision_at_3 |
|
value: 4.397 |
|
- type: precision_at_5 |
|
value: 3.19 |
|
- type: recall_at_1 |
|
value: 6.4159999999999995 |
|
- type: recall_at_10 |
|
value: 17.468 |
|
- type: recall_at_100 |
|
value: 31.398 |
|
- type: recall_at_1000 |
|
value: 53.686 |
|
- type: recall_at_3 |
|
value: 11.379999999999999 |
|
- type: recall_at_5 |
|
value: 13.745 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: BeIR/cqadupstack |
|
name: MTEB CQADupstackTexRetrieval |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 4.646 |
|
- type: map_at_10 |
|
value: 7.047000000000001 |
|
- type: map_at_100 |
|
value: 7.697 |
|
- type: map_at_1000 |
|
value: 7.806 |
|
- type: map_at_3 |
|
value: 6.258 |
|
- type: map_at_5 |
|
value: 6.628 |
|
- type: mrr_at_1 |
|
value: 5.919 |
|
- type: mrr_at_10 |
|
value: 8.767999999999999 |
|
- type: mrr_at_100 |
|
value: 9.434 |
|
- type: mrr_at_1000 |
|
value: 9.524000000000001 |
|
- type: mrr_at_3 |
|
value: 7.8 |
|
- type: mrr_at_5 |
|
value: 8.275 |
|
- type: ndcg_at_1 |
|
value: 5.919 |
|
- type: ndcg_at_10 |
|
value: 8.927999999999999 |
|
- type: ndcg_at_100 |
|
value: 12.467 |
|
- type: ndcg_at_1000 |
|
value: 15.674 |
|
- type: ndcg_at_3 |
|
value: 7.3260000000000005 |
|
- type: ndcg_at_5 |
|
value: 7.931000000000001 |
|
- type: precision_at_1 |
|
value: 5.919 |
|
- type: precision_at_10 |
|
value: 1.7760000000000002 |
|
- type: precision_at_100 |
|
value: 0.438 |
|
- type: precision_at_1000 |
|
value: 0.086 |
|
- type: precision_at_3 |
|
value: 3.6249999999999996 |
|
- type: precision_at_5 |
|
value: 2.657 |
|
- type: recall_at_1 |
|
value: 4.646 |
|
- type: recall_at_10 |
|
value: 12.973 |
|
- type: recall_at_100 |
|
value: 29.444 |
|
- type: recall_at_1000 |
|
value: 53.413999999999994 |
|
- type: recall_at_3 |
|
value: 8.378 |
|
- type: recall_at_5 |
|
value: 9.957 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: BeIR/cqadupstack |
|
name: MTEB CQADupstackUnixRetrieval |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 9.202 |
|
- type: map_at_10 |
|
value: 13.402 |
|
- type: map_at_100 |
|
value: 14.330000000000002 |
|
- type: map_at_1000 |
|
value: 14.455000000000002 |
|
- type: map_at_3 |
|
value: 11.916 |
|
- type: map_at_5 |
|
value: 12.828000000000001 |
|
- type: mrr_at_1 |
|
value: 10.634 |
|
- type: mrr_at_10 |
|
value: 15.528 |
|
- type: mrr_at_100 |
|
value: 16.393 |
|
- type: mrr_at_1000 |
|
value: 16.497999999999998 |
|
- type: mrr_at_3 |
|
value: 13.837 |
|
- type: mrr_at_5 |
|
value: 14.821000000000002 |
|
- type: ndcg_at_1 |
|
value: 10.634 |
|
- type: ndcg_at_10 |
|
value: 16.267 |
|
- type: ndcg_at_100 |
|
value: 21.149 |
|
- type: ndcg_at_1000 |
|
value: 24.509 |
|
- type: ndcg_at_3 |
|
value: 13.320000000000002 |
|
- type: ndcg_at_5 |
|
value: 14.857000000000001 |
|
- type: precision_at_1 |
|
value: 10.634 |
|
- type: precision_at_10 |
|
value: 2.948 |
|
- type: precision_at_100 |
|
value: 0.618 |
|
- type: precision_at_1000 |
|
value: 0.10200000000000001 |
|
- type: precision_at_3 |
|
value: 6.188 |
|
- type: precision_at_5 |
|
value: 4.7010000000000005 |
|
- type: recall_at_1 |
|
value: 9.202 |
|
- type: recall_at_10 |
|
value: 22.921 |
|
- type: recall_at_100 |
|
value: 45.292 |
|
- type: recall_at_1000 |
|
value: 69.853 |
|
- type: recall_at_3 |
|
value: 15.126000000000001 |
|
- type: recall_at_5 |
|
value: 18.863 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: BeIR/cqadupstack |
|
name: MTEB CQADupstackWebmastersRetrieval |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 11.278 |
|
- type: map_at_10 |
|
value: 15.72 |
|
- type: map_at_100 |
|
value: 16.832 |
|
- type: map_at_1000 |
|
value: 17.025000000000002 |
|
- type: map_at_3 |
|
value: 13.852999999999998 |
|
- type: map_at_5 |
|
value: 14.654 |
|
- type: mrr_at_1 |
|
value: 14.822 |
|
- type: mrr_at_10 |
|
value: 19.564 |
|
- type: mrr_at_100 |
|
value: 20.509 |
|
- type: mrr_at_1000 |
|
value: 20.607 |
|
- type: mrr_at_3 |
|
value: 17.721 |
|
- type: mrr_at_5 |
|
value: 18.451999999999998 |
|
- type: ndcg_at_1 |
|
value: 14.822 |
|
- type: ndcg_at_10 |
|
value: 19.548 |
|
- type: ndcg_at_100 |
|
value: 24.734 |
|
- type: ndcg_at_1000 |
|
value: 28.832 |
|
- type: ndcg_at_3 |
|
value: 16.14 |
|
- type: ndcg_at_5 |
|
value: 17.253 |
|
- type: precision_at_1 |
|
value: 14.822 |
|
- type: precision_at_10 |
|
value: 3.972 |
|
- type: precision_at_100 |
|
value: 0.943 |
|
- type: precision_at_1000 |
|
value: 0.183 |
|
- type: precision_at_3 |
|
value: 7.642 |
|
- type: precision_at_5 |
|
value: 5.6129999999999995 |
|
- type: recall_at_1 |
|
value: 11.278 |
|
- type: recall_at_10 |
|
value: 27.006999999999998 |
|
- type: recall_at_100 |
|
value: 51.012 |
|
- type: recall_at_1000 |
|
value: 79.833 |
|
- type: recall_at_3 |
|
value: 16.785 |
|
- type: recall_at_5 |
|
value: 19.82 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: BeIR/cqadupstack |
|
name: MTEB CQADupstackWordpressRetrieval |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 5.305 |
|
- type: map_at_10 |
|
value: 9.099 |
|
- type: map_at_100 |
|
value: 9.927999999999999 |
|
- type: map_at_1000 |
|
value: 10.027 |
|
- type: map_at_3 |
|
value: 7.7700000000000005 |
|
- type: map_at_5 |
|
value: 8.333 |
|
- type: mrr_at_1 |
|
value: 6.1 |
|
- type: mrr_at_10 |
|
value: 10.227 |
|
- type: mrr_at_100 |
|
value: 11.057 |
|
- type: mrr_at_1000 |
|
value: 11.151 |
|
- type: mrr_at_3 |
|
value: 8.842 |
|
- type: mrr_at_5 |
|
value: 9.442 |
|
- type: ndcg_at_1 |
|
value: 6.1 |
|
- type: ndcg_at_10 |
|
value: 11.769 |
|
- type: ndcg_at_100 |
|
value: 16.378999999999998 |
|
- type: ndcg_at_1000 |
|
value: 19.517 |
|
- type: ndcg_at_3 |
|
value: 8.936 |
|
- type: ndcg_at_5 |
|
value: 9.907 |
|
- type: precision_at_1 |
|
value: 6.1 |
|
- type: precision_at_10 |
|
value: 2.181 |
|
- type: precision_at_100 |
|
value: 0.481 |
|
- type: precision_at_1000 |
|
value: 0.08099999999999999 |
|
- type: precision_at_3 |
|
value: 4.19 |
|
- type: precision_at_5 |
|
value: 3.031 |
|
- type: recall_at_1 |
|
value: 5.305 |
|
- type: recall_at_10 |
|
value: 19.236 |
|
- type: recall_at_100 |
|
value: 41.333999999999996 |
|
- type: recall_at_1000 |
|
value: 65.96600000000001 |
|
- type: recall_at_3 |
|
value: 11.189 |
|
- type: recall_at_5 |
|
value: 13.592 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: climate-fever |
|
name: MTEB ClimateFEVER |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 0.882 |
|
- type: map_at_10 |
|
value: 1.6 |
|
- type: map_at_100 |
|
value: 1.894 |
|
- type: map_at_1000 |
|
value: 1.9640000000000002 |
|
- type: map_at_3 |
|
value: 1.345 |
|
- type: map_at_5 |
|
value: 1.444 |
|
- type: mrr_at_1 |
|
value: 2.2800000000000002 |
|
- type: mrr_at_10 |
|
value: 3.8510000000000004 |
|
- type: mrr_at_100 |
|
value: 4.401 |
|
- type: mrr_at_1000 |
|
value: 4.472 |
|
- type: mrr_at_3 |
|
value: 3.2359999999999998 |
|
- type: mrr_at_5 |
|
value: 3.519 |
|
- type: ndcg_at_1 |
|
value: 2.2800000000000002 |
|
- type: ndcg_at_10 |
|
value: 2.5829999999999997 |
|
- type: ndcg_at_100 |
|
value: 4.629 |
|
- type: ndcg_at_1000 |
|
value: 6.709 |
|
- type: ndcg_at_3 |
|
value: 1.978 |
|
- type: ndcg_at_5 |
|
value: 2.133 |
|
- type: precision_at_1 |
|
value: 2.2800000000000002 |
|
- type: precision_at_10 |
|
value: 0.86 |
|
- type: precision_at_100 |
|
value: 0.298 |
|
- type: precision_at_1000 |
|
value: 0.065 |
|
- type: precision_at_3 |
|
value: 1.52 |
|
- type: precision_at_5 |
|
value: 1.173 |
|
- type: recall_at_1 |
|
value: 0.882 |
|
- type: recall_at_10 |
|
value: 3.273 |
|
- type: recall_at_100 |
|
value: 11.254 |
|
- type: recall_at_1000 |
|
value: 23.988 |
|
- type: recall_at_3 |
|
value: 1.818 |
|
- type: recall_at_5 |
|
value: 2.236 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: dbpedia-entity |
|
name: MTEB DBPedia |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 1.057 |
|
- type: map_at_10 |
|
value: 2.289 |
|
- type: map_at_100 |
|
value: 2.844 |
|
- type: map_at_1000 |
|
value: 3.026 |
|
- type: map_at_3 |
|
value: 1.661 |
|
- type: map_at_5 |
|
value: 1.931 |
|
- type: mrr_at_1 |
|
value: 12.75 |
|
- type: mrr_at_10 |
|
value: 17.645 |
|
- type: mrr_at_100 |
|
value: 18.312 |
|
- type: mrr_at_1000 |
|
value: 18.385 |
|
- type: mrr_at_3 |
|
value: 15.958 |
|
- type: mrr_at_5 |
|
value: 17.046 |
|
- type: ndcg_at_1 |
|
value: 10.0 |
|
- type: ndcg_at_10 |
|
value: 6.890000000000001 |
|
- type: ndcg_at_100 |
|
value: 7.131 |
|
- type: ndcg_at_1000 |
|
value: 9.725 |
|
- type: ndcg_at_3 |
|
value: 8.222 |
|
- type: ndcg_at_5 |
|
value: 7.536 |
|
- type: precision_at_1 |
|
value: 12.75 |
|
- type: precision_at_10 |
|
value: 5.925 |
|
- type: precision_at_100 |
|
value: 1.6469999999999998 |
|
- type: precision_at_1000 |
|
value: 0.40299999999999997 |
|
- type: precision_at_3 |
|
value: 9.667 |
|
- type: precision_at_5 |
|
value: 8.0 |
|
- type: recall_at_1 |
|
value: 1.057 |
|
- type: recall_at_10 |
|
value: 3.8580000000000005 |
|
- type: recall_at_100 |
|
value: 8.685 |
|
- type: recall_at_1000 |
|
value: 17.605 |
|
- type: recall_at_3 |
|
value: 2.041 |
|
- type: recall_at_5 |
|
value: 2.811 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/emotion |
|
name: MTEB EmotionClassification |
|
config: default |
|
split: test |
|
revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37 |
|
metrics: |
|
- type: accuracy |
|
value: 20.674999999999997 |
|
- type: f1 |
|
value: 17.79184478487413 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: fever |
|
name: MTEB FEVER |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 2.637 |
|
- type: map_at_10 |
|
value: 3.9730000000000003 |
|
- type: map_at_100 |
|
value: 4.228 |
|
- type: map_at_1000 |
|
value: 4.268000000000001 |
|
- type: map_at_3 |
|
value: 3.542 |
|
- type: map_at_5 |
|
value: 3.763 |
|
- type: mrr_at_1 |
|
value: 2.7449999999999997 |
|
- type: mrr_at_10 |
|
value: 4.146 |
|
- type: mrr_at_100 |
|
value: 4.42 |
|
- type: mrr_at_1000 |
|
value: 4.460999999999999 |
|
- type: mrr_at_3 |
|
value: 3.695 |
|
- type: mrr_at_5 |
|
value: 3.925 |
|
- type: ndcg_at_1 |
|
value: 2.7449999999999997 |
|
- type: ndcg_at_10 |
|
value: 4.801 |
|
- type: ndcg_at_100 |
|
value: 6.198 |
|
- type: ndcg_at_1000 |
|
value: 7.468 |
|
- type: ndcg_at_3 |
|
value: 3.882 |
|
- type: ndcg_at_5 |
|
value: 4.283 |
|
- type: precision_at_1 |
|
value: 2.7449999999999997 |
|
- type: precision_at_10 |
|
value: 0.771 |
|
- type: precision_at_100 |
|
value: 0.152 |
|
- type: precision_at_1000 |
|
value: 0.027 |
|
- type: precision_at_3 |
|
value: 1.6549999999999998 |
|
- type: precision_at_5 |
|
value: 1.206 |
|
- type: recall_at_1 |
|
value: 2.637 |
|
- type: recall_at_10 |
|
value: 7.2669999999999995 |
|
- type: recall_at_100 |
|
value: 13.982 |
|
- type: recall_at_1000 |
|
value: 24.192 |
|
- type: recall_at_3 |
|
value: 4.712000000000001 |
|
- type: recall_at_5 |
|
value: 5.6739999999999995 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: fiqa |
|
name: MTEB FiQA2018 |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 2.91 |
|
- type: map_at_10 |
|
value: 5.721 |
|
- type: map_at_100 |
|
value: 6.489000000000001 |
|
- type: map_at_1000 |
|
value: 6.642 |
|
- type: map_at_3 |
|
value: 4.797 |
|
- type: map_at_5 |
|
value: 5.292 |
|
- type: mrr_at_1 |
|
value: 6.481000000000001 |
|
- type: mrr_at_10 |
|
value: 10.624 |
|
- type: mrr_at_100 |
|
value: 11.498999999999999 |
|
- type: mrr_at_1000 |
|
value: 11.599 |
|
- type: mrr_at_3 |
|
value: 9.285 |
|
- type: mrr_at_5 |
|
value: 10.003 |
|
- type: ndcg_at_1 |
|
value: 6.481000000000001 |
|
- type: ndcg_at_10 |
|
value: 8.303 |
|
- type: ndcg_at_100 |
|
value: 12.512 |
|
- type: ndcg_at_1000 |
|
value: 16.665 |
|
- type: ndcg_at_3 |
|
value: 6.827 |
|
- type: ndcg_at_5 |
|
value: 7.367 |
|
- type: precision_at_1 |
|
value: 6.481000000000001 |
|
- type: precision_at_10 |
|
value: 2.485 |
|
- type: precision_at_100 |
|
value: 0.668 |
|
- type: precision_at_1000 |
|
value: 0.13899999999999998 |
|
- type: precision_at_3 |
|
value: 4.733 |
|
- type: precision_at_5 |
|
value: 3.642 |
|
- type: recall_at_1 |
|
value: 2.91 |
|
- type: recall_at_10 |
|
value: 11.239 |
|
- type: recall_at_100 |
|
value: 27.877999999999997 |
|
- type: recall_at_1000 |
|
value: 54.507000000000005 |
|
- type: recall_at_3 |
|
value: 6.683 |
|
- type: recall_at_5 |
|
value: 8.591 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: hotpotqa |
|
name: MTEB HotpotQA |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 2.073 |
|
- type: map_at_10 |
|
value: 2.919 |
|
- type: map_at_100 |
|
value: 3.107 |
|
- type: map_at_1000 |
|
value: 3.143 |
|
- type: map_at_3 |
|
value: 2.6100000000000003 |
|
- type: map_at_5 |
|
value: 2.773 |
|
- type: mrr_at_1 |
|
value: 4.146 |
|
- type: mrr_at_10 |
|
value: 5.657 |
|
- type: mrr_at_100 |
|
value: 5.970000000000001 |
|
- type: mrr_at_1000 |
|
value: 6.022 |
|
- type: mrr_at_3 |
|
value: 5.116 |
|
- type: mrr_at_5 |
|
value: 5.411 |
|
- type: ndcg_at_1 |
|
value: 4.146 |
|
- type: ndcg_at_10 |
|
value: 4.115 |
|
- type: ndcg_at_100 |
|
value: 5.319 |
|
- type: ndcg_at_1000 |
|
value: 6.584 |
|
- type: ndcg_at_3 |
|
value: 3.3709999999999996 |
|
- type: ndcg_at_5 |
|
value: 3.7159999999999997 |
|
- type: precision_at_1 |
|
value: 4.146 |
|
- type: precision_at_10 |
|
value: 0.983 |
|
- type: precision_at_100 |
|
value: 0.197 |
|
- type: precision_at_1000 |
|
value: 0.037 |
|
- type: precision_at_3 |
|
value: 2.152 |
|
- type: precision_at_5 |
|
value: 1.564 |
|
- type: recall_at_1 |
|
value: 2.073 |
|
- type: recall_at_10 |
|
value: 4.916 |
|
- type: recall_at_100 |
|
value: 9.844999999999999 |
|
- type: recall_at_1000 |
|
value: 18.454 |
|
- type: recall_at_3 |
|
value: 3.228 |
|
- type: recall_at_5 |
|
value: 3.91 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/imdb |
|
name: MTEB ImdbClassification |
|
config: default |
|
split: test |
|
revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7 |
|
metrics: |
|
- type: accuracy |
|
value: 53.28480000000001 |
|
- type: ap |
|
value: 51.81084207241404 |
|
- type: f1 |
|
value: 52.83683146513476 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: msmarco |
|
name: MTEB MSMARCO |
|
config: default |
|
split: dev |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 2.613 |
|
- type: map_at_10 |
|
value: 4.33 |
|
- type: map_at_100 |
|
value: 4.681 |
|
- type: map_at_1000 |
|
value: 4.731 |
|
- type: map_at_3 |
|
value: 3.7560000000000002 |
|
- type: map_at_5 |
|
value: 4.035 |
|
- type: mrr_at_1 |
|
value: 2.665 |
|
- type: mrr_at_10 |
|
value: 4.436 |
|
- type: mrr_at_100 |
|
value: 4.797 |
|
- type: mrr_at_1000 |
|
value: 4.848 |
|
- type: mrr_at_3 |
|
value: 3.83 |
|
- type: mrr_at_5 |
|
value: 4.123 |
|
- type: ndcg_at_1 |
|
value: 2.665 |
|
- type: ndcg_at_10 |
|
value: 5.399 |
|
- type: ndcg_at_100 |
|
value: 7.402 |
|
- type: ndcg_at_1000 |
|
value: 9.08 |
|
- type: ndcg_at_3 |
|
value: 4.1579999999999995 |
|
- type: ndcg_at_5 |
|
value: 4.664 |
|
- type: precision_at_1 |
|
value: 2.665 |
|
- type: precision_at_10 |
|
value: 0.907 |
|
- type: precision_at_100 |
|
value: 0.19499999999999998 |
|
- type: precision_at_1000 |
|
value: 0.034 |
|
- type: precision_at_3 |
|
value: 1.791 |
|
- type: precision_at_5 |
|
value: 1.3299999999999998 |
|
- type: recall_at_1 |
|
value: 2.613 |
|
- type: recall_at_10 |
|
value: 8.729000000000001 |
|
- type: recall_at_100 |
|
value: 18.668000000000003 |
|
- type: recall_at_1000 |
|
value: 32.387 |
|
- type: recall_at_3 |
|
value: 5.25 |
|
- type: recall_at_5 |
|
value: 6.465 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/mtop_domain |
|
name: MTEB MTOPDomainClassification (en) |
|
config: en |
|
split: test |
|
revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf |
|
metrics: |
|
- type: accuracy |
|
value: 73.57729138166896 |
|
- type: f1 |
|
value: 71.0267308110663 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/mtop_intent |
|
name: MTEB MTOPIntentClassification (en) |
|
config: en |
|
split: test |
|
revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba |
|
metrics: |
|
- type: accuracy |
|
value: 38.76652986776106 |
|
- type: f1 |
|
value: 24.385724192837007 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/amazon_massive_intent |
|
name: MTEB MassiveIntentClassification (en) |
|
config: en |
|
split: test |
|
revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 |
|
metrics: |
|
- type: accuracy |
|
value: 43.43308675184936 |
|
- type: f1 |
|
value: 39.072401899805016 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/amazon_massive_scenario |
|
name: MTEB MassiveScenarioClassification (en) |
|
config: en |
|
split: test |
|
revision: 7d571f92784cd94a019292a1f45445077d0ef634 |
|
metrics: |
|
- type: accuracy |
|
value: 55.225285810356425 |
|
- type: f1 |
|
value: 49.81719052485716 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: mteb/medrxiv-clustering-p2p |
|
name: MTEB MedrxivClusteringP2P |
|
config: default |
|
split: test |
|
revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73 |
|
metrics: |
|
- type: v_measure |
|
value: 20.583405653329283 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: mteb/medrxiv-clustering-s2s |
|
name: MTEB MedrxivClusteringS2S |
|
config: default |
|
split: test |
|
revision: 35191c8c0dca72d8ff3efcd72aa802307d469663 |
|
metrics: |
|
- type: v_measure |
|
value: 17.155646378261917 |
|
- task: |
|
type: Reranking |
|
dataset: |
|
type: mteb/mind_small |
|
name: MTEB MindSmallReranking |
|
config: default |
|
split: test |
|
revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69 |
|
metrics: |
|
- type: map |
|
value: 24.26316550665883 |
|
- type: mrr |
|
value: 23.951621402458755 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: nfcorpus |
|
name: MTEB NFCorpus |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 1.4040000000000001 |
|
- type: map_at_10 |
|
value: 2.199 |
|
- type: map_at_100 |
|
value: 2.597 |
|
- type: map_at_1000 |
|
value: 3.15 |
|
- type: map_at_3 |
|
value: 1.7850000000000001 |
|
- type: map_at_5 |
|
value: 2.005 |
|
- type: mrr_at_1 |
|
value: 13.932 |
|
- type: mrr_at_10 |
|
value: 19.529 |
|
- type: mrr_at_100 |
|
value: 20.53 |
|
- type: mrr_at_1000 |
|
value: 20.635 |
|
- type: mrr_at_3 |
|
value: 17.647 |
|
- type: mrr_at_5 |
|
value: 18.731 |
|
- type: ndcg_at_1 |
|
value: 12.539 |
|
- type: ndcg_at_10 |
|
value: 8.676 |
|
- type: ndcg_at_100 |
|
value: 8.092 |
|
- type: ndcg_at_1000 |
|
value: 16.375999999999998 |
|
- type: ndcg_at_3 |
|
value: 10.615 |
|
- type: ndcg_at_5 |
|
value: 9.690999999999999 |
|
- type: precision_at_1 |
|
value: 13.622 |
|
- type: precision_at_10 |
|
value: 6.315999999999999 |
|
- type: precision_at_100 |
|
value: 2.486 |
|
- type: precision_at_1000 |
|
value: 1.317 |
|
- type: precision_at_3 |
|
value: 10.113999999999999 |
|
- type: precision_at_5 |
|
value: 8.235000000000001 |
|
- type: recall_at_1 |
|
value: 1.4040000000000001 |
|
- type: recall_at_10 |
|
value: 3.794 |
|
- type: recall_at_100 |
|
value: 9.71 |
|
- type: recall_at_1000 |
|
value: 37.476 |
|
- type: recall_at_3 |
|
value: 2.197 |
|
- type: recall_at_5 |
|
value: 2.929 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: nq |
|
name: MTEB NQ |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 1.299 |
|
- type: map_at_10 |
|
value: 2.7279999999999998 |
|
- type: map_at_100 |
|
value: 3.065 |
|
- type: map_at_1000 |
|
value: 3.118 |
|
- type: map_at_3 |
|
value: 2.182 |
|
- type: map_at_5 |
|
value: 2.48 |
|
- type: mrr_at_1 |
|
value: 1.6219999999999999 |
|
- type: mrr_at_10 |
|
value: 3.237 |
|
- type: mrr_at_100 |
|
value: 3.5749999999999997 |
|
- type: mrr_at_1000 |
|
value: 3.626 |
|
- type: mrr_at_3 |
|
value: 2.6550000000000002 |
|
- type: mrr_at_5 |
|
value: 2.9770000000000003 |
|
- type: ndcg_at_1 |
|
value: 1.6219999999999999 |
|
- type: ndcg_at_10 |
|
value: 3.768 |
|
- type: ndcg_at_100 |
|
value: 5.721 |
|
- type: ndcg_at_1000 |
|
value: 7.346 |
|
- type: ndcg_at_3 |
|
value: 2.604 |
|
- type: ndcg_at_5 |
|
value: 3.1530000000000005 |
|
- type: precision_at_1 |
|
value: 1.6219999999999999 |
|
- type: precision_at_10 |
|
value: 0.776 |
|
- type: precision_at_100 |
|
value: 0.194 |
|
- type: precision_at_1000 |
|
value: 0.034999999999999996 |
|
- type: precision_at_3 |
|
value: 1.371 |
|
- type: precision_at_5 |
|
value: 1.1119999999999999 |
|
- type: recall_at_1 |
|
value: 1.299 |
|
- type: recall_at_10 |
|
value: 6.54 |
|
- type: recall_at_100 |
|
value: 16.014999999999997 |
|
- type: recall_at_1000 |
|
value: 28.776000000000003 |
|
- type: recall_at_3 |
|
value: 3.37 |
|
- type: recall_at_5 |
|
value: 4.676 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: quora |
|
name: MTEB QuoraRetrieval |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 50.827 |
|
- type: map_at_10 |
|
value: 60.903 |
|
- type: map_at_100 |
|
value: 61.67700000000001 |
|
- type: map_at_1000 |
|
value: 61.729 |
|
- type: map_at_3 |
|
value: 58.411 |
|
- type: map_at_5 |
|
value: 59.854 |
|
- type: mrr_at_1 |
|
value: 58.52 |
|
- type: mrr_at_10 |
|
value: 65.53999999999999 |
|
- type: mrr_at_100 |
|
value: 65.94 |
|
- type: mrr_at_1000 |
|
value: 65.962 |
|
- type: mrr_at_3 |
|
value: 63.905 |
|
- type: mrr_at_5 |
|
value: 64.883 |
|
- type: ndcg_at_1 |
|
value: 58.51 |
|
- type: ndcg_at_10 |
|
value: 65.458 |
|
- type: ndcg_at_100 |
|
value: 68.245 |
|
- type: ndcg_at_1000 |
|
value: 69.244 |
|
- type: ndcg_at_3 |
|
value: 61.970000000000006 |
|
- type: ndcg_at_5 |
|
value: 63.664 |
|
- type: precision_at_1 |
|
value: 58.51 |
|
- type: precision_at_10 |
|
value: 9.873999999999999 |
|
- type: precision_at_100 |
|
value: 1.24 |
|
- type: precision_at_1000 |
|
value: 0.13899999999999998 |
|
- type: precision_at_3 |
|
value: 26.650000000000002 |
|
- type: precision_at_5 |
|
value: 17.666 |
|
- type: recall_at_1 |
|
value: 50.827 |
|
- type: recall_at_10 |
|
value: 74.13300000000001 |
|
- type: recall_at_100 |
|
value: 85.724 |
|
- type: recall_at_1000 |
|
value: 92.551 |
|
- type: recall_at_3 |
|
value: 64.122 |
|
- type: recall_at_5 |
|
value: 68.757 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: mteb/reddit-clustering |
|
name: MTEB RedditClustering |
|
config: default |
|
split: test |
|
revision: 24640382cdbf8abc73003fb0fa6d111a705499eb |
|
metrics: |
|
- type: v_measure |
|
value: 15.106948858308094 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: mteb/reddit-clustering-p2p |
|
name: MTEB RedditClusteringP2P |
|
config: default |
|
split: test |
|
revision: 282350215ef01743dc01b456c7f5241fa8937f16 |
|
metrics: |
|
- type: v_measure |
|
value: 30.968103547012337 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: scidocs |
|
name: MTEB SCIDOCS |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 1.4749999999999999 |
|
- type: map_at_10 |
|
value: 3.434 |
|
- type: map_at_100 |
|
value: 4.139 |
|
- type: map_at_1000 |
|
value: 4.312 |
|
- type: map_at_3 |
|
value: 2.554 |
|
- type: map_at_5 |
|
value: 2.999 |
|
- type: mrr_at_1 |
|
value: 7.3 |
|
- type: mrr_at_10 |
|
value: 12.031 |
|
- type: mrr_at_100 |
|
value: 12.97 |
|
- type: mrr_at_1000 |
|
value: 13.092 |
|
- type: mrr_at_3 |
|
value: 10.217 |
|
- type: mrr_at_5 |
|
value: 11.172 |
|
- type: ndcg_at_1 |
|
value: 7.3 |
|
- type: ndcg_at_10 |
|
value: 6.406000000000001 |
|
- type: ndcg_at_100 |
|
value: 10.302999999999999 |
|
- type: ndcg_at_1000 |
|
value: 14.791000000000002 |
|
- type: ndcg_at_3 |
|
value: 5.982 |
|
- type: ndcg_at_5 |
|
value: 5.274 |
|
- type: precision_at_1 |
|
value: 7.3 |
|
- type: precision_at_10 |
|
value: 3.37 |
|
- type: precision_at_100 |
|
value: 0.914 |
|
- type: precision_at_1000 |
|
value: 0.201 |
|
- type: precision_at_3 |
|
value: 5.567 |
|
- type: precision_at_5 |
|
value: 4.68 |
|
- type: recall_at_1 |
|
value: 1.4749999999999999 |
|
- type: recall_at_10 |
|
value: 6.79 |
|
- type: recall_at_100 |
|
value: 18.55 |
|
- type: recall_at_1000 |
|
value: 40.842 |
|
- type: recall_at_3 |
|
value: 3.36 |
|
- type: recall_at_5 |
|
value: 4.72 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: mteb/sickr-sts |
|
name: MTEB SICK-R |
|
config: default |
|
split: test |
|
revision: a6ea5a8cab320b040a23452cc28066d9beae2cee |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 59.464420082440526 |
|
- type: cos_sim_spearman |
|
value: 54.319988337451704 |
|
- type: euclidean_pearson |
|
value: 57.042312873314295 |
|
- type: euclidean_spearman |
|
value: 54.31996388571784 |
|
- type: manhattan_pearson |
|
value: 57.078786802338435 |
|
- type: manhattan_spearman |
|
value: 54.323312153757456 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: mteb/sts12-sts |
|
name: MTEB STS12 |
|
config: default |
|
split: test |
|
revision: a0d554a64d88156834ff5ae9920b964011b16384 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 60.08105871689929 |
|
- type: cos_sim_spearman |
|
value: 57.53293836132526 |
|
- type: euclidean_pearson |
|
value: 57.69984777047449 |
|
- type: euclidean_spearman |
|
value: 57.534154476967345 |
|
- type: manhattan_pearson |
|
value: 57.661519973840946 |
|
- type: manhattan_spearman |
|
value: 57.447636234309854 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: mteb/sts13-sts |
|
name: MTEB STS13 |
|
config: default |
|
split: test |
|
revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 57.12692049687197 |
|
- type: cos_sim_spearman |
|
value: 57.4759438730368 |
|
- type: euclidean_pearson |
|
value: 58.41782334532981 |
|
- type: euclidean_spearman |
|
value: 57.47613008122331 |
|
- type: manhattan_pearson |
|
value: 58.41335837274888 |
|
- type: manhattan_spearman |
|
value: 57.465936751045746 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: mteb/sts14-sts |
|
name: MTEB STS14 |
|
config: default |
|
split: test |
|
revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 53.84165004759765 |
|
- type: cos_sim_spearman |
|
value: 52.32112048731462 |
|
- type: euclidean_pearson |
|
value: 52.790405817119094 |
|
- type: euclidean_spearman |
|
value: 52.32112268628659 |
|
- type: manhattan_pearson |
|
value: 52.804939090733804 |
|
- type: manhattan_spearman |
|
value: 52.31750678935915 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: mteb/sts15-sts |
|
name: MTEB STS15 |
|
config: default |
|
split: test |
|
revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 63.555819199866036 |
|
- type: cos_sim_spearman |
|
value: 64.05841117331784 |
|
- type: euclidean_pearson |
|
value: 63.659991414541786 |
|
- type: euclidean_spearman |
|
value: 64.05841071779129 |
|
- type: manhattan_pearson |
|
value: 63.6915442281397 |
|
- type: manhattan_spearman |
|
value: 64.07728265258595 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: mteb/sts16-sts |
|
name: MTEB STS16 |
|
config: default |
|
split: test |
|
revision: 4d8694f8f0e0100860b497b999b3dbed754a0513 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 63.03024268207247 |
|
- type: cos_sim_spearman |
|
value: 63.53003651570799 |
|
- type: euclidean_pearson |
|
value: 64.09620752390686 |
|
- type: euclidean_spearman |
|
value: 63.530036058718096 |
|
- type: manhattan_pearson |
|
value: 64.07468313413827 |
|
- type: manhattan_spearman |
|
value: 63.526415746516285 |
|
- 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: 70.18862439704168 |
|
- type: cos_sim_spearman |
|
value: 70.97966882821095 |
|
- type: euclidean_pearson |
|
value: 71.04858522892525 |
|
- type: euclidean_spearman |
|
value: 70.97966882821095 |
|
- type: manhattan_pearson |
|
value: 71.0777838495318 |
|
- type: manhattan_spearman |
|
value: 71.08141859528023 |
|
- 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: 49.680993011354964 |
|
- type: cos_sim_spearman |
|
value: 55.990646519065734 |
|
- type: euclidean_pearson |
|
value: 52.53309325175639 |
|
- type: euclidean_spearman |
|
value: 55.990646519065734 |
|
- type: manhattan_pearson |
|
value: 52.55809108662631 |
|
- type: manhattan_spearman |
|
value: 55.65236114980215 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: mteb/stsbenchmark-sts |
|
name: MTEB STSBenchmark |
|
config: default |
|
split: test |
|
revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 61.18394695826386 |
|
- type: cos_sim_spearman |
|
value: 60.77402126712771 |
|
- type: euclidean_pearson |
|
value: 61.202070794992736 |
|
- type: euclidean_spearman |
|
value: 60.77402126712771 |
|
- type: manhattan_pearson |
|
value: 61.2505175850885 |
|
- type: manhattan_spearman |
|
value: 60.77213463387346 |
|
- task: |
|
type: Reranking |
|
dataset: |
|
type: mteb/scidocs-reranking |
|
name: MTEB SciDocsRR |
|
config: default |
|
split: test |
|
revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab |
|
metrics: |
|
- type: map |
|
value: 58.251838750265804 |
|
- type: mrr |
|
value: 81.27406090641384 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: scifact |
|
name: MTEB SciFact |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 8.833 |
|
- type: map_at_10 |
|
value: 11.219999999999999 |
|
- type: map_at_100 |
|
value: 12.086 |
|
- type: map_at_1000 |
|
value: 12.200999999999999 |
|
- type: map_at_3 |
|
value: 10.056 |
|
- type: map_at_5 |
|
value: 10.664 |
|
- type: mrr_at_1 |
|
value: 9.0 |
|
- type: mrr_at_10 |
|
value: 11.875 |
|
- type: mrr_at_100 |
|
value: 12.757 |
|
- type: mrr_at_1000 |
|
value: 12.864 |
|
- type: mrr_at_3 |
|
value: 10.722 |
|
- type: mrr_at_5 |
|
value: 11.322000000000001 |
|
- type: ndcg_at_1 |
|
value: 9.0 |
|
- type: ndcg_at_10 |
|
value: 13.001 |
|
- type: ndcg_at_100 |
|
value: 17.784 |
|
- type: ndcg_at_1000 |
|
value: 21.695 |
|
- type: ndcg_at_3 |
|
value: 10.63 |
|
- type: ndcg_at_5 |
|
value: 11.693000000000001 |
|
- type: precision_at_1 |
|
value: 9.0 |
|
- type: precision_at_10 |
|
value: 2.0 |
|
- type: precision_at_100 |
|
value: 0.46299999999999997 |
|
- type: precision_at_1000 |
|
value: 0.083 |
|
- type: precision_at_3 |
|
value: 4.222 |
|
- type: precision_at_5 |
|
value: 3.1329999999999996 |
|
- type: recall_at_1 |
|
value: 8.833 |
|
- type: recall_at_10 |
|
value: 18.0 |
|
- type: recall_at_100 |
|
value: 41.211 |
|
- type: recall_at_1000 |
|
value: 73.14399999999999 |
|
- type: recall_at_3 |
|
value: 11.5 |
|
- type: recall_at_5 |
|
value: 14.083000000000002 |
|
- task: |
|
type: PairClassification |
|
dataset: |
|
type: mteb/sprintduplicatequestions-pairclassification |
|
name: MTEB SprintDuplicateQuestions |
|
config: default |
|
split: test |
|
revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46 |
|
metrics: |
|
- type: cos_sim_accuracy |
|
value: 99.44455445544554 |
|
- type: cos_sim_ap |
|
value: 68.76115592640271 |
|
- type: cos_sim_f1 |
|
value: 67.29805013927577 |
|
- type: cos_sim_precision |
|
value: 75.9748427672956 |
|
- type: cos_sim_recall |
|
value: 60.4 |
|
- type: dot_accuracy |
|
value: 99.44455445544554 |
|
- type: dot_ap |
|
value: 68.76115778951738 |
|
- type: dot_f1 |
|
value: 67.29805013927577 |
|
- type: dot_precision |
|
value: 75.9748427672956 |
|
- type: dot_recall |
|
value: 60.4 |
|
- type: euclidean_accuracy |
|
value: 99.44455445544554 |
|
- type: euclidean_ap |
|
value: 68.76115530286063 |
|
- type: euclidean_f1 |
|
value: 67.29805013927577 |
|
- type: euclidean_precision |
|
value: 75.9748427672956 |
|
- type: euclidean_recall |
|
value: 60.4 |
|
- type: manhattan_accuracy |
|
value: 99.44653465346535 |
|
- type: manhattan_ap |
|
value: 68.76446446842253 |
|
- type: manhattan_f1 |
|
value: 67.34926052332196 |
|
- type: manhattan_precision |
|
value: 78.10026385224275 |
|
- type: manhattan_recall |
|
value: 59.199999999999996 |
|
- type: max_accuracy |
|
value: 99.44653465346535 |
|
- type: max_ap |
|
value: 68.76446446842253 |
|
- type: max_f1 |
|
value: 67.34926052332196 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: mteb/stackexchange-clustering |
|
name: MTEB StackExchangeClustering |
|
config: default |
|
split: test |
|
revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259 |
|
metrics: |
|
- type: v_measure |
|
value: 28.486032726226675 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: mteb/stackexchange-clustering-p2p |
|
name: MTEB StackExchangeClusteringP2P |
|
config: default |
|
split: test |
|
revision: 815ca46b2622cec33ccafc3735d572c266efdb44 |
|
metrics: |
|
- type: v_measure |
|
value: 29.654061810103283 |
|
- task: |
|
type: Reranking |
|
dataset: |
|
type: mteb/stackoverflowdupquestions-reranking |
|
name: MTEB StackOverflowDupQuestions |
|
config: default |
|
split: test |
|
revision: e185fbe320c72810689fc5848eb6114e1ef5ec69 |
|
metrics: |
|
- type: map |
|
value: 39.81455140801657 |
|
- type: mrr |
|
value: 40.09712407690349 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: trec-covid |
|
name: MTEB TRECCOVID |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 0.05 |
|
- type: map_at_10 |
|
value: 0.191 |
|
- type: map_at_100 |
|
value: 0.346 |
|
- type: map_at_1000 |
|
value: 0.553 |
|
- type: map_at_3 |
|
value: 0.11299999999999999 |
|
- type: map_at_5 |
|
value: 0.148 |
|
- type: mrr_at_1 |
|
value: 22.0 |
|
- type: mrr_at_10 |
|
value: 30.091 |
|
- type: mrr_at_100 |
|
value: 31.241999999999997 |
|
- type: mrr_at_1000 |
|
value: 31.298 |
|
- type: mrr_at_3 |
|
value: 28.000000000000004 |
|
- type: mrr_at_5 |
|
value: 28.999999999999996 |
|
- type: ndcg_at_1 |
|
value: 18.0 |
|
- type: ndcg_at_10 |
|
value: 12.501000000000001 |
|
- type: ndcg_at_100 |
|
value: 5.605 |
|
- type: ndcg_at_1000 |
|
value: 4.543 |
|
- type: ndcg_at_3 |
|
value: 17.531 |
|
- type: ndcg_at_5 |
|
value: 15.254999999999999 |
|
- type: precision_at_1 |
|
value: 22.0 |
|
- type: precision_at_10 |
|
value: 12.6 |
|
- type: precision_at_100 |
|
value: 5.06 |
|
- type: precision_at_1000 |
|
value: 2.028 |
|
- type: precision_at_3 |
|
value: 20.666999999999998 |
|
- type: precision_at_5 |
|
value: 16.8 |
|
- type: recall_at_1 |
|
value: 0.05 |
|
- type: recall_at_10 |
|
value: 0.267 |
|
- type: recall_at_100 |
|
value: 1.102 |
|
- type: recall_at_1000 |
|
value: 4.205 |
|
- type: recall_at_3 |
|
value: 0.134 |
|
- type: recall_at_5 |
|
value: 0.182 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: webis-touche2020 |
|
name: MTEB Touche2020 |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 0.45199999999999996 |
|
- type: map_at_10 |
|
value: 1.986 |
|
- type: map_at_100 |
|
value: 3.887 |
|
- type: map_at_1000 |
|
value: 4.5809999999999995 |
|
- type: map_at_3 |
|
value: 0.9299999999999999 |
|
- type: map_at_5 |
|
value: 1.287 |
|
- type: mrr_at_1 |
|
value: 8.163 |
|
- type: mrr_at_10 |
|
value: 16.152 |
|
- type: mrr_at_100 |
|
value: 17.187 |
|
- type: mrr_at_1000 |
|
value: 17.301 |
|
- type: mrr_at_3 |
|
value: 11.224 |
|
- type: mrr_at_5 |
|
value: 12.653 |
|
- type: ndcg_at_1 |
|
value: 4.082 |
|
- type: ndcg_at_10 |
|
value: 6.687 |
|
- type: ndcg_at_100 |
|
value: 13.158 |
|
- type: ndcg_at_1000 |
|
value: 22.259 |
|
- type: ndcg_at_3 |
|
value: 5.039 |
|
- type: ndcg_at_5 |
|
value: 5.519 |
|
- type: precision_at_1 |
|
value: 8.163 |
|
- type: precision_at_10 |
|
value: 8.163 |
|
- type: precision_at_100 |
|
value: 3.51 |
|
- type: precision_at_1000 |
|
value: 0.9159999999999999 |
|
- type: precision_at_3 |
|
value: 7.483 |
|
- type: precision_at_5 |
|
value: 7.3469999999999995 |
|
- type: recall_at_1 |
|
value: 0.45199999999999996 |
|
- type: recall_at_10 |
|
value: 5.27 |
|
- type: recall_at_100 |
|
value: 20.75 |
|
- type: recall_at_1000 |
|
value: 49.236999999999995 |
|
- type: recall_at_3 |
|
value: 1.28 |
|
- type: recall_at_5 |
|
value: 2.045 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/toxic_conversations_50k |
|
name: MTEB ToxicConversationsClassification |
|
config: default |
|
split: test |
|
revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c |
|
metrics: |
|
- type: accuracy |
|
value: 57.08740000000001 |
|
- type: ap |
|
value: 9.092681400063896 |
|
- type: f1 |
|
value: 43.966684273361125 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/tweet_sentiment_extraction |
|
name: MTEB TweetSentimentExtractionClassification |
|
config: default |
|
split: test |
|
revision: d604517c81ca91fe16a244d1248fc021f9ecee7a |
|
metrics: |
|
- type: accuracy |
|
value: 42.314657611771366 |
|
- type: f1 |
|
value: 42.2349043058169 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: mteb/twentynewsgroups-clustering |
|
name: MTEB TwentyNewsgroupsClustering |
|
config: default |
|
split: test |
|
revision: 6125ec4e24fa026cec8a478383ee943acfbd5449 |
|
metrics: |
|
- type: v_measure |
|
value: 15.71319288909283 |
|
- task: |
|
type: PairClassification |
|
dataset: |
|
type: mteb/twittersemeval2015-pairclassification |
|
name: MTEB TwitterSemEval2015 |
|
config: default |
|
split: test |
|
revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1 |
|
metrics: |
|
- type: cos_sim_accuracy |
|
value: 78.84007867914407 |
|
- type: cos_sim_ap |
|
value: 42.2183603452187 |
|
- type: cos_sim_f1 |
|
value: 43.1781412906705 |
|
- type: cos_sim_precision |
|
value: 32.74263904034896 |
|
- type: cos_sim_recall |
|
value: 63.377308707124016 |
|
- type: dot_accuracy |
|
value: 78.84007867914407 |
|
- type: dot_ap |
|
value: 42.21836359699547 |
|
- type: dot_f1 |
|
value: 43.1781412906705 |
|
- type: dot_precision |
|
value: 32.74263904034896 |
|
- type: dot_recall |
|
value: 63.377308707124016 |
|
- type: euclidean_accuracy |
|
value: 78.84007867914407 |
|
- type: euclidean_ap |
|
value: 42.218363575958854 |
|
- type: euclidean_f1 |
|
value: 43.1781412906705 |
|
- type: euclidean_precision |
|
value: 32.74263904034896 |
|
- type: euclidean_recall |
|
value: 63.377308707124016 |
|
- type: manhattan_accuracy |
|
value: 78.79239434940692 |
|
- type: manhattan_ap |
|
value: 42.178124350579 |
|
- type: manhattan_f1 |
|
value: 43.16231513602337 |
|
- type: manhattan_precision |
|
value: 32.99832495812395 |
|
- type: manhattan_recall |
|
value: 62.37467018469657 |
|
- type: max_accuracy |
|
value: 78.84007867914407 |
|
- type: max_ap |
|
value: 42.21836359699547 |
|
- type: max_f1 |
|
value: 43.1781412906705 |
|
- task: |
|
type: PairClassification |
|
dataset: |
|
type: mteb/twitterurlcorpus-pairclassification |
|
name: MTEB TwitterURLCorpus |
|
config: default |
|
split: test |
|
revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf |
|
metrics: |
|
- type: cos_sim_accuracy |
|
value: 82.51445647533667 |
|
- type: cos_sim_ap |
|
value: 69.65701766911302 |
|
- type: cos_sim_f1 |
|
value: 62.92060699362217 |
|
- type: cos_sim_precision |
|
value: 60.046173219532676 |
|
- type: cos_sim_recall |
|
value: 66.08407761010163 |
|
- type: dot_accuracy |
|
value: 82.51445647533667 |
|
- type: dot_ap |
|
value: 69.6569952654014 |
|
- type: dot_f1 |
|
value: 62.92060699362217 |
|
- type: dot_precision |
|
value: 60.046173219532676 |
|
- type: dot_recall |
|
value: 66.08407761010163 |
|
- type: euclidean_accuracy |
|
value: 82.51445647533667 |
|
- type: euclidean_ap |
|
value: 69.65697749857492 |
|
- type: euclidean_f1 |
|
value: 62.92060699362217 |
|
- type: euclidean_precision |
|
value: 60.046173219532676 |
|
- type: euclidean_recall |
|
value: 66.08407761010163 |
|
- type: manhattan_accuracy |
|
value: 82.52221834128925 |
|
- type: manhattan_ap |
|
value: 69.65965534790995 |
|
- type: manhattan_f1 |
|
value: 62.865817064991006 |
|
- type: manhattan_precision |
|
value: 58.04811265401917 |
|
- type: manhattan_recall |
|
value: 68.55558977517708 |
|
- type: max_accuracy |
|
value: 82.52221834128925 |
|
- type: max_ap |
|
value: 69.65965534790995 |
|
- type: max_f1 |
|
value: 62.92060699362217 |
|
--- |
|
|
