|
--- |
|
tags: |
|
- mteb |
|
model-index: |
|
- name: nomic_classification_307_w30k_b10k |
|
results: |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: None |
|
name: MTEB AmazonCounterfactualClassification (en) |
|
config: en |
|
split: test |
|
revision: e8379541af4e31359cca9fbcf4b00f2671dba205 |
|
metrics: |
|
- type: accuracy |
|
value: 71.955223880597 |
|
- type: ap |
|
value: 34.13197114646943 |
|
- type: f1 |
|
value: 65.68946854348061 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: None |
|
name: MTEB AmazonPolarityClassification |
|
config: default |
|
split: test |
|
revision: e2d317d38cd51312af73b3d32a06d1a08b442046 |
|
metrics: |
|
- type: accuracy |
|
value: 64.32617499999999 |
|
- type: ap |
|
value: 59.490845212236245 |
|
- type: f1 |
|
value: 64.1040492114687 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: None |
|
name: MTEB AmazonReviewsClassification (en) |
|
config: en |
|
split: test |
|
revision: 1399c76144fd37290681b995c656ef9b2e06e26d |
|
metrics: |
|
- type: accuracy |
|
value: 33.838 |
|
- type: f1 |
|
value: 33.407172447103896 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB ArguAna |
|
config: default |
|
split: test |
|
revision: c22ab2a51041ffd869aaddef7af8d8215647e41a |
|
metrics: |
|
- type: map_at_1 |
|
value: 20.128 |
|
- type: map_at_10 |
|
value: 34.056 |
|
- type: map_at_100 |
|
value: 35.238 |
|
- type: map_at_1000 |
|
value: 35.266999999999996 |
|
- type: map_at_3 |
|
value: 29.457 |
|
- type: map_at_5 |
|
value: 32.11 |
|
- type: mrr_at_1 |
|
value: 20.483999999999998 |
|
- type: mrr_at_10 |
|
value: 34.186 |
|
- type: mrr_at_100 |
|
value: 35.388 |
|
- type: mrr_at_1000 |
|
value: 35.416 |
|
- type: mrr_at_3 |
|
value: 29.576 |
|
- type: mrr_at_5 |
|
value: 32.236 |
|
- type: ndcg_at_1 |
|
value: 20.128 |
|
- type: ndcg_at_10 |
|
value: 42.05 |
|
- type: ndcg_at_100 |
|
value: 47.661 |
|
- type: ndcg_at_1000 |
|
value: 48.339999999999996 |
|
- type: ndcg_at_3 |
|
value: 32.555 |
|
- type: ndcg_at_5 |
|
value: 37.348 |
|
- type: precision_at_1 |
|
value: 20.128 |
|
- type: precision_at_10 |
|
value: 6.771000000000001 |
|
- type: precision_at_100 |
|
value: 0.936 |
|
- type: precision_at_1000 |
|
value: 0.099 |
|
- type: precision_at_3 |
|
value: 13.844999999999999 |
|
- type: precision_at_5 |
|
value: 10.639999999999999 |
|
- type: recall_at_1 |
|
value: 20.128 |
|
- type: recall_at_10 |
|
value: 67.71000000000001 |
|
- type: recall_at_100 |
|
value: 93.599 |
|
- type: recall_at_1000 |
|
value: 98.791 |
|
- type: recall_at_3 |
|
value: 41.536 |
|
- type: recall_at_5 |
|
value: 53.201 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: None |
|
name: MTEB ArxivClusteringP2P |
|
config: default |
|
split: test |
|
revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d |
|
metrics: |
|
- type: v_measure |
|
value: 30.332603841310025 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: None |
|
name: MTEB ArxivClusteringS2S |
|
config: default |
|
split: test |
|
revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53 |
|
metrics: |
|
- type: v_measure |
|
value: 20.867624126885154 |
|
- task: |
|
type: Reranking |
|
dataset: |
|
type: None |
|
name: MTEB AskUbuntuDupQuestions |
|
config: default |
|
split: test |
|
revision: 2000358ca161889fa9c082cb41daa8dcfb161a54 |
|
metrics: |
|
- type: map |
|
value: 52.71119008857963 |
|
- type: mrr |
|
value: 66.35789033988479 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: None |
|
name: MTEB BIOSSES |
|
config: default |
|
split: test |
|
revision: d3fb88f8f02e40887cd149695127462bbcf29b4a |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 78.18517708213652 |
|
- type: cos_sim_spearman |
|
value: 77.68068566977038 |
|
- type: euclidean_pearson |
|
value: 77.54287673443481 |
|
- type: euclidean_spearman |
|
value: 77.68068566977038 |
|
- type: manhattan_pearson |
|
value: 77.11580342725216 |
|
- type: manhattan_spearman |
|
value: 76.84632930899711 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: None |
|
name: MTEB Banking77Classification |
|
config: default |
|
split: test |
|
revision: 0fd18e25b25c072e09e0d92ab615fda904d66300 |
|
metrics: |
|
- type: accuracy |
|
value: 71.8603896103896 |
|
- type: f1 |
|
value: 71.02556795780878 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: None |
|
name: MTEB BiorxivClusteringP2P |
|
config: default |
|
split: test |
|
revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40 |
|
metrics: |
|
- type: v_measure |
|
value: 28.30104672592466 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: None |
|
name: MTEB BiorxivClusteringS2S |
|
config: default |
|
split: test |
|
revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908 |
|
metrics: |
|
- type: v_measure |
|
value: 18.177382002944345 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB CQADupstackAndroidRetrieval |
|
config: default |
|
split: test |
|
revision: f46a197baaae43b4f621051089b82a364682dfeb |
|
metrics: |
|
- type: map_at_1 |
|
value: 20.352999999999998 |
|
- type: map_at_10 |
|
value: 27.258 |
|
- type: map_at_100 |
|
value: 28.396 |
|
- type: map_at_1000 |
|
value: 28.554000000000002 |
|
- type: map_at_3 |
|
value: 25.013999999999996 |
|
- type: map_at_5 |
|
value: 26.384999999999998 |
|
- type: mrr_at_1 |
|
value: 25.894000000000002 |
|
- type: mrr_at_10 |
|
value: 32.863 |
|
- type: mrr_at_100 |
|
value: 33.809 |
|
- type: mrr_at_1000 |
|
value: 33.886 |
|
- type: mrr_at_3 |
|
value: 31.020999999999997 |
|
- type: mrr_at_5 |
|
value: 32.129000000000005 |
|
- type: ndcg_at_1 |
|
value: 25.894000000000002 |
|
- type: ndcg_at_10 |
|
value: 31.830000000000002 |
|
- type: ndcg_at_100 |
|
value: 36.895 |
|
- type: ndcg_at_1000 |
|
value: 40.233000000000004 |
|
- type: ndcg_at_3 |
|
value: 28.764 |
|
- type: ndcg_at_5 |
|
value: 30.267 |
|
- type: precision_at_1 |
|
value: 25.894000000000002 |
|
- type: precision_at_10 |
|
value: 6.094 |
|
- type: precision_at_100 |
|
value: 1.072 |
|
- type: precision_at_1000 |
|
value: 0.167 |
|
- type: precision_at_3 |
|
value: 13.828999999999999 |
|
- type: precision_at_5 |
|
value: 10.157 |
|
- type: recall_at_1 |
|
value: 20.352999999999998 |
|
- type: recall_at_10 |
|
value: 39.318999999999996 |
|
- type: recall_at_100 |
|
value: 61.989000000000004 |
|
- type: recall_at_1000 |
|
value: 84.74199999999999 |
|
- type: recall_at_3 |
|
value: 29.673 |
|
- type: recall_at_5 |
|
value: 34.136 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB CQADupstackEnglishRetrieval |
|
config: default |
|
split: test |
|
revision: ad9991cb51e31e31e430383c75ffb2885547b5f0 |
|
metrics: |
|
- type: map_at_1 |
|
value: 16.134 |
|
- type: map_at_10 |
|
value: 21.423000000000002 |
|
- type: map_at_100 |
|
value: 22.326999999999998 |
|
- type: map_at_1000 |
|
value: 22.451999999999998 |
|
- type: map_at_3 |
|
value: 19.602 |
|
- type: map_at_5 |
|
value: 20.77 |
|
- type: mrr_at_1 |
|
value: 20.446 |
|
- type: mrr_at_10 |
|
value: 25.496999999999996 |
|
- type: mrr_at_100 |
|
value: 26.264 |
|
- type: mrr_at_1000 |
|
value: 26.339000000000002 |
|
- type: mrr_at_3 |
|
value: 23.662 |
|
- type: mrr_at_5 |
|
value: 24.752 |
|
- type: ndcg_at_1 |
|
value: 20.446 |
|
- type: ndcg_at_10 |
|
value: 24.933 |
|
- type: ndcg_at_100 |
|
value: 29.268 |
|
- type: ndcg_at_1000 |
|
value: 32.24 |
|
- type: ndcg_at_3 |
|
value: 21.919 |
|
- type: ndcg_at_5 |
|
value: 23.54 |
|
- type: precision_at_1 |
|
value: 20.446 |
|
- type: precision_at_10 |
|
value: 4.5920000000000005 |
|
- type: precision_at_100 |
|
value: 0.853 |
|
- type: precision_at_1000 |
|
value: 0.136 |
|
- type: precision_at_3 |
|
value: 10.424999999999999 |
|
- type: precision_at_5 |
|
value: 7.605 |
|
- type: recall_at_1 |
|
value: 16.134 |
|
- type: recall_at_10 |
|
value: 31.369000000000003 |
|
- type: recall_at_100 |
|
value: 50.592999999999996 |
|
- type: recall_at_1000 |
|
value: 71.06 |
|
- type: recall_at_3 |
|
value: 22.888 |
|
- type: recall_at_5 |
|
value: 27.189000000000004 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB CQADupstackGamingRetrieval |
|
config: default |
|
split: test |
|
revision: 4885aa143210c98657558c04aaf3dc47cfb54340 |
|
metrics: |
|
- type: map_at_1 |
|
value: 24.673000000000002 |
|
- type: map_at_10 |
|
value: 32.711 |
|
- type: map_at_100 |
|
value: 33.711 |
|
- type: map_at_1000 |
|
value: 33.802 |
|
- type: map_at_3 |
|
value: 30.301000000000002 |
|
- type: map_at_5 |
|
value: 31.499 |
|
- type: mrr_at_1 |
|
value: 28.589 |
|
- type: mrr_at_10 |
|
value: 35.812 |
|
- type: mrr_at_100 |
|
value: 36.63 |
|
- type: mrr_at_1000 |
|
value: 36.687999999999995 |
|
- type: mrr_at_3 |
|
value: 33.532000000000004 |
|
- type: mrr_at_5 |
|
value: 34.682 |
|
- type: ndcg_at_1 |
|
value: 28.589 |
|
- type: ndcg_at_10 |
|
value: 37.4 |
|
- type: ndcg_at_100 |
|
value: 42.363 |
|
- type: ndcg_at_1000 |
|
value: 44.525999999999996 |
|
- type: ndcg_at_3 |
|
value: 32.768 |
|
- type: ndcg_at_5 |
|
value: 34.683 |
|
- type: precision_at_1 |
|
value: 28.589 |
|
- type: precision_at_10 |
|
value: 6.144 |
|
- type: precision_at_100 |
|
value: 0.9530000000000001 |
|
- type: precision_at_1000 |
|
value: 0.121 |
|
- type: precision_at_3 |
|
value: 14.524999999999999 |
|
- type: precision_at_5 |
|
value: 10.006 |
|
- type: recall_at_1 |
|
value: 24.673000000000002 |
|
- type: recall_at_10 |
|
value: 48.711 |
|
- type: recall_at_100 |
|
value: 71.481 |
|
- type: recall_at_1000 |
|
value: 87.307 |
|
- type: recall_at_3 |
|
value: 36.04 |
|
- type: recall_at_5 |
|
value: 40.851 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB CQADupstackGisRetrieval |
|
config: default |
|
split: test |
|
revision: 5003b3064772da1887988e05400cf3806fe491f2 |
|
metrics: |
|
- type: map_at_1 |
|
value: 10.245 |
|
- type: map_at_10 |
|
value: 14.524000000000001 |
|
- type: map_at_100 |
|
value: 15.315000000000001 |
|
- type: map_at_1000 |
|
value: 15.418999999999999 |
|
- type: map_at_3 |
|
value: 13.255 |
|
- type: map_at_5 |
|
value: 13.898 |
|
- type: mrr_at_1 |
|
value: 11.411999999999999 |
|
- type: mrr_at_10 |
|
value: 15.681999999999999 |
|
- type: mrr_at_100 |
|
value: 16.497999999999998 |
|
- type: mrr_at_1000 |
|
value: 16.597 |
|
- type: mrr_at_3 |
|
value: 14.388000000000002 |
|
- type: mrr_at_5 |
|
value: 15.026 |
|
- type: ndcg_at_1 |
|
value: 11.411999999999999 |
|
- type: ndcg_at_10 |
|
value: 17.11 |
|
- type: ndcg_at_100 |
|
value: 21.426000000000002 |
|
- type: ndcg_at_1000 |
|
value: 24.747 |
|
- type: ndcg_at_3 |
|
value: 14.527999999999999 |
|
- type: ndcg_at_5 |
|
value: 15.626999999999999 |
|
- type: precision_at_1 |
|
value: 11.411999999999999 |
|
- type: precision_at_10 |
|
value: 2.723 |
|
- type: precision_at_100 |
|
value: 0.518 |
|
- type: precision_at_1000 |
|
value: 0.08499999999999999 |
|
- type: precision_at_3 |
|
value: 6.328 |
|
- type: precision_at_5 |
|
value: 4.3839999999999995 |
|
- type: recall_at_1 |
|
value: 10.245 |
|
- type: recall_at_10 |
|
value: 24.065 |
|
- type: recall_at_100 |
|
value: 44.627 |
|
- type: recall_at_1000 |
|
value: 70.844 |
|
- type: recall_at_3 |
|
value: 17.006 |
|
- type: recall_at_5 |
|
value: 19.661 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB CQADupstackMathematicaRetrieval |
|
config: default |
|
split: test |
|
revision: 90fceea13679c63fe563ded68f3b6f06e50061de |
|
metrics: |
|
- type: map_at_1 |
|
value: 6.197 |
|
- type: map_at_10 |
|
value: 9.278 |
|
- type: map_at_100 |
|
value: 9.916 |
|
- type: map_at_1000 |
|
value: 10.038 |
|
- type: map_at_3 |
|
value: 8.218 |
|
- type: map_at_5 |
|
value: 8.752 |
|
- type: mrr_at_1 |
|
value: 8.085 |
|
- type: mrr_at_10 |
|
value: 11.359 |
|
- type: mrr_at_100 |
|
value: 12.071 |
|
- type: mrr_at_1000 |
|
value: 12.174999999999999 |
|
- type: mrr_at_3 |
|
value: 10.158000000000001 |
|
- type: mrr_at_5 |
|
value: 10.73 |
|
- type: ndcg_at_1 |
|
value: 8.085 |
|
- type: ndcg_at_10 |
|
value: 11.545 |
|
- type: ndcg_at_100 |
|
value: 15.126999999999999 |
|
- type: ndcg_at_1000 |
|
value: 18.792 |
|
- type: ndcg_at_3 |
|
value: 9.462 |
|
- type: ndcg_at_5 |
|
value: 10.289 |
|
- type: precision_at_1 |
|
value: 8.085 |
|
- type: precision_at_10 |
|
value: 2.226 |
|
- type: precision_at_100 |
|
value: 0.47400000000000003 |
|
- type: precision_at_1000 |
|
value: 0.092 |
|
- type: precision_at_3 |
|
value: 4.643 |
|
- type: precision_at_5 |
|
value: 3.3329999999999997 |
|
- type: recall_at_1 |
|
value: 6.197 |
|
- type: recall_at_10 |
|
value: 16.597 |
|
- type: recall_at_100 |
|
value: 32.922000000000004 |
|
- type: recall_at_1000 |
|
value: 60.171 |
|
- type: recall_at_3 |
|
value: 10.644 |
|
- type: recall_at_5 |
|
value: 12.867 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB CQADupstackPhysicsRetrieval |
|
config: default |
|
split: test |
|
revision: 79531abbd1fb92d06c6d6315a0cbbbf5bb247ea4 |
|
metrics: |
|
- type: map_at_1 |
|
value: 16.543 |
|
- type: map_at_10 |
|
value: 22.024 |
|
- type: map_at_100 |
|
value: 23.169999999999998 |
|
- type: map_at_1000 |
|
value: 23.304 |
|
- type: map_at_3 |
|
value: 20.215 |
|
- type: map_at_5 |
|
value: 21.208 |
|
- type: mrr_at_1 |
|
value: 20.885 |
|
- type: mrr_at_10 |
|
value: 26.616 |
|
- type: mrr_at_100 |
|
value: 27.508 |
|
- type: mrr_at_1000 |
|
value: 27.589000000000002 |
|
- type: mrr_at_3 |
|
value: 24.607 |
|
- type: mrr_at_5 |
|
value: 25.81 |
|
- type: ndcg_at_1 |
|
value: 20.885 |
|
- type: ndcg_at_10 |
|
value: 25.921 |
|
- type: ndcg_at_100 |
|
value: 31.351000000000003 |
|
- type: ndcg_at_1000 |
|
value: 34.434 |
|
- type: ndcg_at_3 |
|
value: 22.686 |
|
- type: ndcg_at_5 |
|
value: 24.21 |
|
- type: precision_at_1 |
|
value: 20.885 |
|
- type: precision_at_10 |
|
value: 4.735 |
|
- type: precision_at_100 |
|
value: 0.906 |
|
- type: precision_at_1000 |
|
value: 0.136 |
|
- type: precision_at_3 |
|
value: 10.555 |
|
- type: precision_at_5 |
|
value: 7.642 |
|
- type: recall_at_1 |
|
value: 16.543 |
|
- type: recall_at_10 |
|
value: 33.377 |
|
- type: recall_at_100 |
|
value: 57.043 |
|
- type: recall_at_1000 |
|
value: 78.497 |
|
- type: recall_at_3 |
|
value: 24.076 |
|
- type: recall_at_5 |
|
value: 28.101 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB CQADupstackProgrammersRetrieval |
|
config: default |
|
split: test |
|
revision: 6184bc1440d2dbc7612be22b50686b8826d22b32 |
|
metrics: |
|
- type: map_at_1 |
|
value: 10.985 |
|
- type: map_at_10 |
|
value: 16.586000000000002 |
|
- type: map_at_100 |
|
value: 17.616 |
|
- type: map_at_1000 |
|
value: 17.748 |
|
- type: map_at_3 |
|
value: 14.933 |
|
- type: map_at_5 |
|
value: 15.826 |
|
- type: mrr_at_1 |
|
value: 13.699 |
|
- type: mrr_at_10 |
|
value: 19.683999999999997 |
|
- type: mrr_at_100 |
|
value: 20.636 |
|
- type: mrr_at_1000 |
|
value: 20.719 |
|
- type: mrr_at_3 |
|
value: 17.941 |
|
- type: mrr_at_5 |
|
value: 18.866 |
|
- type: ndcg_at_1 |
|
value: 13.699 |
|
- type: ndcg_at_10 |
|
value: 20.057 |
|
- type: ndcg_at_100 |
|
value: 25.215 |
|
- type: ndcg_at_1000 |
|
value: 28.584 |
|
- type: ndcg_at_3 |
|
value: 16.989 |
|
- type: ndcg_at_5 |
|
value: 18.321 |
|
- type: precision_at_1 |
|
value: 13.699 |
|
- type: precision_at_10 |
|
value: 3.8580000000000005 |
|
- type: precision_at_100 |
|
value: 0.76 |
|
- type: precision_at_1000 |
|
value: 0.122 |
|
- type: precision_at_3 |
|
value: 8.219 |
|
- type: precision_at_5 |
|
value: 6.027 |
|
- type: recall_at_1 |
|
value: 10.985 |
|
- type: recall_at_10 |
|
value: 27.351 |
|
- type: recall_at_100 |
|
value: 50.221000000000004 |
|
- type: recall_at_1000 |
|
value: 74.368 |
|
- type: recall_at_3 |
|
value: 19.177 |
|
- type: recall_at_5 |
|
value: 22.42 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: mteb/cqadupstack |
|
name: MTEB CQADupstackRetrieval |
|
config: default |
|
split: test |
|
revision: 4885aa143210c98657558c04aaf3dc47cfb54340 |
|
metrics: |
|
- type: map_at_1 |
|
value: 13.05425 |
|
- type: map_at_10 |
|
value: 18.011166666666668 |
|
- type: map_at_100 |
|
value: 18.863249999999997 |
|
- type: map_at_1000 |
|
value: 18.986499999999996 |
|
- type: map_at_3 |
|
value: 16.473000000000003 |
|
- type: map_at_5 |
|
value: 17.302666666666667 |
|
- type: mrr_at_1 |
|
value: 15.915333333333335 |
|
- type: mrr_at_10 |
|
value: 20.951083333333333 |
|
- type: mrr_at_100 |
|
value: 21.731333333333332 |
|
- type: mrr_at_1000 |
|
value: 21.818749999999998 |
|
- type: mrr_at_3 |
|
value: 19.372833333333332 |
|
- type: mrr_at_5 |
|
value: 20.232750000000003 |
|
- type: ndcg_at_1 |
|
value: 15.915333333333335 |
|
- type: ndcg_at_10 |
|
value: 21.271500000000003 |
|
- type: ndcg_at_100 |
|
value: 25.59883333333333 |
|
- type: ndcg_at_1000 |
|
value: 28.81025 |
|
- type: ndcg_at_3 |
|
value: 18.473500000000005 |
|
- type: ndcg_at_5 |
|
value: 19.711666666666666 |
|
- type: precision_at_1 |
|
value: 15.915333333333335 |
|
- type: precision_at_10 |
|
value: 3.8305 |
|
- type: precision_at_100 |
|
value: 0.7128333333333334 |
|
- type: precision_at_1000 |
|
value: 0.11674999999999999 |
|
- type: precision_at_3 |
|
value: 8.618166666666667 |
|
- type: precision_at_5 |
|
value: 6.160166666666667 |
|
- type: recall_at_1 |
|
value: 13.05425 |
|
- type: recall_at_10 |
|
value: 28.18425 |
|
- type: recall_at_100 |
|
value: 48.085249999999995 |
|
- type: recall_at_1000 |
|
value: 71.58041666666665 |
|
- type: recall_at_3 |
|
value: 20.2705 |
|
- type: recall_at_5 |
|
value: 23.499916666666664 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB CQADupstackStatsRetrieval |
|
config: default |
|
split: test |
|
revision: 65ac3a16b8e91f9cee4c9828cc7c335575432a2a |
|
metrics: |
|
- type: map_at_1 |
|
value: 9.724 |
|
- type: map_at_10 |
|
value: 13.367 |
|
- type: map_at_100 |
|
value: 13.987 |
|
- type: map_at_1000 |
|
value: 14.075 |
|
- type: map_at_3 |
|
value: 12.4 |
|
- type: map_at_5 |
|
value: 12.838 |
|
- type: mrr_at_1 |
|
value: 11.35 |
|
- type: mrr_at_10 |
|
value: 15.268 |
|
- type: mrr_at_100 |
|
value: 15.885 |
|
- type: mrr_at_1000 |
|
value: 15.969 |
|
- type: mrr_at_3 |
|
value: 14.238000000000001 |
|
- type: mrr_at_5 |
|
value: 14.691 |
|
- type: ndcg_at_1 |
|
value: 11.35 |
|
- type: ndcg_at_10 |
|
value: 15.779000000000002 |
|
- type: ndcg_at_100 |
|
value: 19.204 |
|
- type: ndcg_at_1000 |
|
value: 21.964 |
|
- type: ndcg_at_3 |
|
value: 13.896 |
|
- type: ndcg_at_5 |
|
value: 14.538 |
|
- type: precision_at_1 |
|
value: 11.35 |
|
- type: precision_at_10 |
|
value: 2.699 |
|
- type: precision_at_100 |
|
value: 0.486 |
|
- type: precision_at_1000 |
|
value: 0.079 |
|
- type: precision_at_3 |
|
value: 6.442 |
|
- type: precision_at_5 |
|
value: 4.387 |
|
- type: recall_at_1 |
|
value: 9.724 |
|
- type: recall_at_10 |
|
value: 21.393 |
|
- type: recall_at_100 |
|
value: 37.618 |
|
- type: recall_at_1000 |
|
value: 59.035000000000004 |
|
- type: recall_at_3 |
|
value: 15.751000000000001 |
|
- type: recall_at_5 |
|
value: 17.544999999999998 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB CQADupstackTexRetrieval |
|
config: default |
|
split: test |
|
revision: 46989137a86843e03a6195de44b09deda022eec7 |
|
metrics: |
|
- type: map_at_1 |
|
value: 7.026000000000001 |
|
- type: map_at_10 |
|
value: 10.151 |
|
- type: map_at_100 |
|
value: 10.699 |
|
- type: map_at_1000 |
|
value: 10.816 |
|
- type: map_at_3 |
|
value: 9.118 |
|
- type: map_at_5 |
|
value: 9.684 |
|
- type: mrr_at_1 |
|
value: 8.706 |
|
- type: mrr_at_10 |
|
value: 12.289 |
|
- type: mrr_at_100 |
|
value: 12.857 |
|
- type: mrr_at_1000 |
|
value: 12.956999999999999 |
|
- type: mrr_at_3 |
|
value: 11.126 |
|
- type: mrr_at_5 |
|
value: 11.808 |
|
- type: ndcg_at_1 |
|
value: 8.706 |
|
- type: ndcg_at_10 |
|
value: 12.386 |
|
- type: ndcg_at_100 |
|
value: 15.562000000000001 |
|
- type: ndcg_at_1000 |
|
value: 19.038 |
|
- type: ndcg_at_3 |
|
value: 10.392 |
|
- type: ndcg_at_5 |
|
value: 11.33 |
|
- type: precision_at_1 |
|
value: 8.706 |
|
- type: precision_at_10 |
|
value: 2.3539999999999996 |
|
- type: precision_at_100 |
|
value: 0.47400000000000003 |
|
- type: precision_at_1000 |
|
value: 0.093 |
|
- type: precision_at_3 |
|
value: 4.967 |
|
- type: precision_at_5 |
|
value: 3.7159999999999997 |
|
- type: recall_at_1 |
|
value: 7.026000000000001 |
|
- type: recall_at_10 |
|
value: 17.05 |
|
- type: recall_at_100 |
|
value: 32.12 |
|
- type: recall_at_1000 |
|
value: 58.179 |
|
- type: recall_at_3 |
|
value: 11.62 |
|
- type: recall_at_5 |
|
value: 13.91 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB CQADupstackUnixRetrieval |
|
config: default |
|
split: test |
|
revision: 6c6430d3a6d36f8d2a829195bc5dc94d7e063e53 |
|
metrics: |
|
- type: map_at_1 |
|
value: 11.023 |
|
- type: map_at_10 |
|
value: 15.139 |
|
- type: map_at_100 |
|
value: 15.919 |
|
- type: map_at_1000 |
|
value: 16.038 |
|
- type: map_at_3 |
|
value: 13.794 |
|
- type: map_at_5 |
|
value: 14.555000000000001 |
|
- type: mrr_at_1 |
|
value: 13.526 |
|
- type: mrr_at_10 |
|
value: 17.906 |
|
- type: mrr_at_100 |
|
value: 18.731 |
|
- type: mrr_at_1000 |
|
value: 18.831 |
|
- type: mrr_at_3 |
|
value: 16.496 |
|
- type: mrr_at_5 |
|
value: 17.317 |
|
- type: ndcg_at_1 |
|
value: 13.526 |
|
- type: ndcg_at_10 |
|
value: 17.999000000000002 |
|
- type: ndcg_at_100 |
|
value: 22.227 |
|
- type: ndcg_at_1000 |
|
value: 25.708 |
|
- type: ndcg_at_3 |
|
value: 15.421999999999999 |
|
- type: ndcg_at_5 |
|
value: 16.646 |
|
- type: precision_at_1 |
|
value: 13.526 |
|
- type: precision_at_10 |
|
value: 3.106 |
|
- type: precision_at_100 |
|
value: 0.5720000000000001 |
|
- type: precision_at_1000 |
|
value: 0.099 |
|
- type: precision_at_3 |
|
value: 7.1209999999999996 |
|
- type: precision_at_5 |
|
value: 5.075 |
|
- type: recall_at_1 |
|
value: 11.023 |
|
- type: recall_at_10 |
|
value: 24.174 |
|
- type: recall_at_100 |
|
value: 43.861 |
|
- type: recall_at_1000 |
|
value: 69.729 |
|
- type: recall_at_3 |
|
value: 17.019000000000002 |
|
- type: recall_at_5 |
|
value: 20.189 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB CQADupstackWebmastersRetrieval |
|
config: default |
|
split: test |
|
revision: 160c094312a0e1facb97e55eeddb698c0abe3571 |
|
metrics: |
|
- type: map_at_1 |
|
value: 12.83 |
|
- type: map_at_10 |
|
value: 18.9 |
|
- type: map_at_100 |
|
value: 19.874 |
|
- type: map_at_1000 |
|
value: 20.047 |
|
- type: map_at_3 |
|
value: 17.413 |
|
- type: map_at_5 |
|
value: 18.127 |
|
- type: mrr_at_1 |
|
value: 16.008 |
|
- type: mrr_at_10 |
|
value: 22.157 |
|
- type: mrr_at_100 |
|
value: 22.952 |
|
- type: mrr_at_1000 |
|
value: 23.035 |
|
- type: mrr_at_3 |
|
value: 20.487 |
|
- type: mrr_at_5 |
|
value: 21.397 |
|
- type: ndcg_at_1 |
|
value: 16.008 |
|
- type: ndcg_at_10 |
|
value: 22.898 |
|
- type: ndcg_at_100 |
|
value: 27.345999999999997 |
|
- type: ndcg_at_1000 |
|
value: 30.818 |
|
- type: ndcg_at_3 |
|
value: 20.294 |
|
- type: ndcg_at_5 |
|
value: 21.328 |
|
- type: precision_at_1 |
|
value: 16.008 |
|
- type: precision_at_10 |
|
value: 4.625 |
|
- type: precision_at_100 |
|
value: 0.972 |
|
- type: precision_at_1000 |
|
value: 0.18 |
|
- type: precision_at_3 |
|
value: 10.079 |
|
- type: precision_at_5 |
|
value: 7.154000000000001 |
|
- type: recall_at_1 |
|
value: 12.83 |
|
- type: recall_at_10 |
|
value: 30.509999999999998 |
|
- type: recall_at_100 |
|
value: 51.671 |
|
- type: recall_at_1000 |
|
value: 75.529 |
|
- type: recall_at_3 |
|
value: 22.889 |
|
- type: recall_at_5 |
|
value: 25.740000000000002 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB CQADupstackWordpressRetrieval |
|
config: default |
|
split: test |
|
revision: 4ffe81d471b1924886b33c7567bfb200e9eec5c4 |
|
metrics: |
|
- type: map_at_1 |
|
value: 10.918 |
|
- type: map_at_10 |
|
value: 14.773 |
|
- type: map_at_100 |
|
value: 15.429 |
|
- type: map_at_1000 |
|
value: 15.545 |
|
- type: map_at_3 |
|
value: 13.413 |
|
- type: map_at_5 |
|
value: 14.09 |
|
- type: mrr_at_1 |
|
value: 12.384 |
|
- type: mrr_at_10 |
|
value: 16.28 |
|
- type: mrr_at_100 |
|
value: 16.935 |
|
- type: mrr_at_1000 |
|
value: 17.04 |
|
- type: mrr_at_3 |
|
value: 14.818000000000001 |
|
- type: mrr_at_5 |
|
value: 15.584999999999999 |
|
- type: ndcg_at_1 |
|
value: 12.384 |
|
- type: ndcg_at_10 |
|
value: 17.4 |
|
- type: ndcg_at_100 |
|
value: 21.201999999999998 |
|
- type: ndcg_at_1000 |
|
value: 24.639 |
|
- type: ndcg_at_3 |
|
value: 14.562 |
|
- type: ndcg_at_5 |
|
value: 15.761 |
|
- type: precision_at_1 |
|
value: 12.384 |
|
- type: precision_at_10 |
|
value: 2.81 |
|
- type: precision_at_100 |
|
value: 0.514 |
|
- type: precision_at_1000 |
|
value: 0.091 |
|
- type: precision_at_3 |
|
value: 6.285 |
|
- type: precision_at_5 |
|
value: 4.436 |
|
- type: recall_at_1 |
|
value: 10.918 |
|
- type: recall_at_10 |
|
value: 24.295 |
|
- type: recall_at_100 |
|
value: 42.876999999999995 |
|
- type: recall_at_1000 |
|
value: 69.504 |
|
- type: recall_at_3 |
|
value: 16.463 |
|
- type: recall_at_5 |
|
value: 19.39 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB ClimateFEVER |
|
config: default |
|
split: test |
|
revision: 47f2ac6acb640fc46020b02a5b59fdda04d39380 |
|
metrics: |
|
- type: map_at_1 |
|
value: 5.498 |
|
- type: map_at_10 |
|
value: 9.462 |
|
- type: map_at_100 |
|
value: 10.659 |
|
- type: map_at_1000 |
|
value: 10.837 |
|
- type: map_at_3 |
|
value: 7.701 |
|
- type: map_at_5 |
|
value: 8.524 |
|
- type: mrr_at_1 |
|
value: 12.182 |
|
- type: mrr_at_10 |
|
value: 19.561999999999998 |
|
- type: mrr_at_100 |
|
value: 20.665 |
|
- type: mrr_at_1000 |
|
value: 20.747 |
|
- type: mrr_at_3 |
|
value: 16.84 |
|
- type: mrr_at_5 |
|
value: 18.287 |
|
- type: ndcg_at_1 |
|
value: 12.182 |
|
- type: ndcg_at_10 |
|
value: 14.382 |
|
- type: ndcg_at_100 |
|
value: 20.244 |
|
- type: ndcg_at_1000 |
|
value: 24.247 |
|
- type: ndcg_at_3 |
|
value: 10.876 |
|
- type: ndcg_at_5 |
|
value: 12.064 |
|
- type: precision_at_1 |
|
value: 12.182 |
|
- type: precision_at_10 |
|
value: 4.853 |
|
- type: precision_at_100 |
|
value: 1.115 |
|
- type: precision_at_1000 |
|
value: 0.184 |
|
- type: precision_at_3 |
|
value: 8.208 |
|
- type: precision_at_5 |
|
value: 6.632000000000001 |
|
- type: recall_at_1 |
|
value: 5.498 |
|
- type: recall_at_10 |
|
value: 18.336 |
|
- type: recall_at_100 |
|
value: 39.318999999999996 |
|
- type: recall_at_1000 |
|
value: 62.760000000000005 |
|
- type: recall_at_3 |
|
value: 10.16 |
|
- type: recall_at_5 |
|
value: 13.149 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB DBPedia |
|
config: default |
|
split: test |
|
revision: c0f706b76e590d620bd6618b3ca8efdd34e2d659 |
|
metrics: |
|
- type: map_at_1 |
|
value: 2.928 |
|
- type: map_at_10 |
|
value: 6.816 |
|
- type: map_at_100 |
|
value: 9.347999999999999 |
|
- type: map_at_1000 |
|
value: 10.051 |
|
- type: map_at_3 |
|
value: 4.7669999999999995 |
|
- type: map_at_5 |
|
value: 5.6419999999999995 |
|
- type: mrr_at_1 |
|
value: 33.75 |
|
- type: mrr_at_10 |
|
value: 41.662 |
|
- type: mrr_at_100 |
|
value: 42.483 |
|
- type: mrr_at_1000 |
|
value: 42.536 |
|
- type: mrr_at_3 |
|
value: 39.125 |
|
- type: mrr_at_5 |
|
value: 40.363 |
|
- type: ndcg_at_1 |
|
value: 24.5 |
|
- type: ndcg_at_10 |
|
value: 18.73 |
|
- type: ndcg_at_100 |
|
value: 20.355 |
|
- type: ndcg_at_1000 |
|
value: 26.606 |
|
- type: ndcg_at_3 |
|
value: 21.169 |
|
- type: ndcg_at_5 |
|
value: 19.776 |
|
- type: precision_at_1 |
|
value: 33.75 |
|
- type: precision_at_10 |
|
value: 16.85 |
|
- type: precision_at_100 |
|
value: 5.095000000000001 |
|
- type: precision_at_1000 |
|
value: 1.107 |
|
- type: precision_at_3 |
|
value: 24.667 |
|
- type: precision_at_5 |
|
value: 21.3 |
|
- type: recall_at_1 |
|
value: 2.928 |
|
- type: recall_at_10 |
|
value: 10.637 |
|
- type: recall_at_100 |
|
value: 24.968 |
|
- type: recall_at_1000 |
|
value: 46.566 |
|
- type: recall_at_3 |
|
value: 5.619 |
|
- type: recall_at_5 |
|
value: 7.344 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: None |
|
name: MTEB EmotionClassification |
|
config: default |
|
split: test |
|
revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37 |
|
metrics: |
|
- type: accuracy |
|
value: 43.254999999999995 |
|
- type: f1 |
|
value: 39.47105271415231 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB FEVER |
|
config: default |
|
split: test |
|
revision: bea83ef9e8fb933d90a2f1d5515737465d613e12 |
|
metrics: |
|
- type: map_at_1 |
|
value: 9.212 |
|
- type: map_at_10 |
|
value: 13.952 |
|
- type: map_at_100 |
|
value: 14.680000000000001 |
|
- type: map_at_1000 |
|
value: 14.766000000000002 |
|
- type: map_at_3 |
|
value: 12.292 |
|
- type: map_at_5 |
|
value: 13.192 |
|
- type: mrr_at_1 |
|
value: 9.796000000000001 |
|
- type: mrr_at_10 |
|
value: 14.825 |
|
- type: mrr_at_100 |
|
value: 15.573999999999998 |
|
- type: mrr_at_1000 |
|
value: 15.656 |
|
- type: mrr_at_3 |
|
value: 13.064 |
|
- type: mrr_at_5 |
|
value: 14.025000000000002 |
|
- type: ndcg_at_1 |
|
value: 9.796000000000001 |
|
- type: ndcg_at_10 |
|
value: 16.985 |
|
- type: ndcg_at_100 |
|
value: 21.015 |
|
- type: ndcg_at_1000 |
|
value: 23.507 |
|
- type: ndcg_at_3 |
|
value: 13.505 |
|
- type: ndcg_at_5 |
|
value: 15.132000000000001 |
|
- type: precision_at_1 |
|
value: 9.796000000000001 |
|
- type: precision_at_10 |
|
value: 2.789 |
|
- type: precision_at_100 |
|
value: 0.49899999999999994 |
|
- type: precision_at_1000 |
|
value: 0.073 |
|
- type: precision_at_3 |
|
value: 5.816000000000001 |
|
- type: precision_at_5 |
|
value: 4.340999999999999 |
|
- type: recall_at_1 |
|
value: 9.212 |
|
- type: recall_at_10 |
|
value: 25.756 |
|
- type: recall_at_100 |
|
value: 45.279 |
|
- type: recall_at_1000 |
|
value: 64.806 |
|
- type: recall_at_3 |
|
value: 16.235 |
|
- type: recall_at_5 |
|
value: 20.125999999999998 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB FiQA2018 |
|
config: default |
|
split: test |
|
revision: 27a168819829fe9bcd655c2df245fb19452e8e06 |
|
metrics: |
|
- type: map_at_1 |
|
value: 5.604 |
|
- type: map_at_10 |
|
value: 9.46 |
|
- type: map_at_100 |
|
value: 10.417 |
|
- type: map_at_1000 |
|
value: 10.604 |
|
- type: map_at_3 |
|
value: 7.776 |
|
- type: map_at_5 |
|
value: 8.601 |
|
- type: mrr_at_1 |
|
value: 11.265 |
|
- type: mrr_at_10 |
|
value: 16.661 |
|
- type: mrr_at_100 |
|
value: 17.575 |
|
- type: mrr_at_1000 |
|
value: 17.684 |
|
- type: mrr_at_3 |
|
value: 14.582999999999998 |
|
- type: mrr_at_5 |
|
value: 15.717999999999998 |
|
- type: ndcg_at_1 |
|
value: 11.265 |
|
- type: ndcg_at_10 |
|
value: 13.36 |
|
- type: ndcg_at_100 |
|
value: 18.199 |
|
- type: ndcg_at_1000 |
|
value: 22.682 |
|
- type: ndcg_at_3 |
|
value: 10.677 |
|
- type: ndcg_at_5 |
|
value: 11.64 |
|
- type: precision_at_1 |
|
value: 11.265 |
|
- type: precision_at_10 |
|
value: 4.043 |
|
- type: precision_at_100 |
|
value: 0.8920000000000001 |
|
- type: precision_at_1000 |
|
value: 0.165 |
|
- type: precision_at_3 |
|
value: 7.305000000000001 |
|
- type: precision_at_5 |
|
value: 5.772 |
|
- type: recall_at_1 |
|
value: 5.604 |
|
- type: recall_at_10 |
|
value: 17.756 |
|
- type: recall_at_100 |
|
value: 36.913000000000004 |
|
- type: recall_at_1000 |
|
value: 65.438 |
|
- type: recall_at_3 |
|
value: 9.626999999999999 |
|
- type: recall_at_5 |
|
value: 12.665000000000001 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB HotpotQA |
|
config: default |
|
split: test |
|
revision: ab518f4d6fcca38d87c25209f94beba119d02014 |
|
metrics: |
|
- type: map_at_1 |
|
value: 12.026 |
|
- type: map_at_10 |
|
value: 16.878999999999998 |
|
- type: map_at_100 |
|
value: 17.607999999999997 |
|
- type: map_at_1000 |
|
value: 17.716 |
|
- type: map_at_3 |
|
value: 15.514 |
|
- type: map_at_5 |
|
value: 16.236 |
|
- type: mrr_at_1 |
|
value: 24.038 |
|
- type: mrr_at_10 |
|
value: 29.831999999999997 |
|
- type: mrr_at_100 |
|
value: 30.578 |
|
- type: mrr_at_1000 |
|
value: 30.656 |
|
- type: mrr_at_3 |
|
value: 28.298000000000002 |
|
- type: mrr_at_5 |
|
value: 29.116999999999997 |
|
- type: ndcg_at_1 |
|
value: 24.051000000000002 |
|
- type: ndcg_at_10 |
|
value: 22.042 |
|
- type: ndcg_at_100 |
|
value: 25.756 |
|
- type: ndcg_at_1000 |
|
value: 28.579 |
|
- type: ndcg_at_3 |
|
value: 19.296 |
|
- type: ndcg_at_5 |
|
value: 20.549999999999997 |
|
- type: precision_at_1 |
|
value: 24.051000000000002 |
|
- type: precision_at_10 |
|
value: 4.920999999999999 |
|
- type: precision_at_100 |
|
value: 0.792 |
|
- type: precision_at_1000 |
|
value: 0.117 |
|
- type: precision_at_3 |
|
value: 12.225999999999999 |
|
- type: precision_at_5 |
|
value: 8.332 |
|
- type: recall_at_1 |
|
value: 12.026 |
|
- type: recall_at_10 |
|
value: 24.605 |
|
- type: recall_at_100 |
|
value: 39.595 |
|
- type: recall_at_1000 |
|
value: 58.494 |
|
- type: recall_at_3 |
|
value: 18.339 |
|
- type: recall_at_5 |
|
value: 20.831 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: None |
|
name: MTEB ImdbClassification |
|
config: default |
|
split: test |
|
revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7 |
|
metrics: |
|
- type: accuracy |
|
value: 63.706399999999995 |
|
- type: ap |
|
value: 58.9524031201249 |
|
- type: f1 |
|
value: 63.556083975109466 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB MSMARCO |
|
config: default |
|
split: dev |
|
revision: c5a29a104738b98a9e76336939199e264163d4a0 |
|
metrics: |
|
- type: map_at_1 |
|
value: 4.845 |
|
- type: map_at_10 |
|
value: 8.402999999999999 |
|
- type: map_at_100 |
|
value: 9.106 |
|
- type: map_at_1000 |
|
value: 9.199 |
|
- type: map_at_3 |
|
value: 7.074999999999999 |
|
- type: map_at_5 |
|
value: 7.757 |
|
- type: mrr_at_1 |
|
value: 5.0 |
|
- type: mrr_at_10 |
|
value: 8.625 |
|
- type: mrr_at_100 |
|
value: 9.337 |
|
- type: mrr_at_1000 |
|
value: 9.428 |
|
- type: mrr_at_3 |
|
value: 7.266 |
|
- type: mrr_at_5 |
|
value: 7.965999999999999 |
|
- type: ndcg_at_1 |
|
value: 4.971 |
|
- type: ndcg_at_10 |
|
value: 10.696 |
|
- type: ndcg_at_100 |
|
value: 14.716000000000001 |
|
- type: ndcg_at_1000 |
|
value: 17.663999999999998 |
|
- type: ndcg_at_3 |
|
value: 7.881 |
|
- type: ndcg_at_5 |
|
value: 9.118 |
|
- type: precision_at_1 |
|
value: 4.971 |
|
- type: precision_at_10 |
|
value: 1.855 |
|
- type: precision_at_100 |
|
value: 0.398 |
|
- type: precision_at_1000 |
|
value: 0.066 |
|
- type: precision_at_3 |
|
value: 3.453 |
|
- type: precision_at_5 |
|
value: 2.693 |
|
- type: recall_at_1 |
|
value: 4.845 |
|
- type: recall_at_10 |
|
value: 17.88 |
|
- type: recall_at_100 |
|
value: 37.816 |
|
- type: recall_at_1000 |
|
value: 61.726000000000006 |
|
- type: recall_at_3 |
|
value: 10.045 |
|
- type: recall_at_5 |
|
value: 13.032 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: None |
|
name: MTEB MTOPDomainClassification (en) |
|
config: en |
|
split: test |
|
revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf |
|
metrics: |
|
- type: accuracy |
|
value: 89.28408572731419 |
|
- type: f1 |
|
value: 88.36057445001192 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: None |
|
name: MTEB MTOPIntentClassification (en) |
|
config: en |
|
split: test |
|
revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba |
|
metrics: |
|
- type: accuracy |
|
value: 59.366165070679436 |
|
- type: f1 |
|
value: 40.06121455563378 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: None |
|
name: MTEB MassiveIntentClassification (en) |
|
config: en |
|
split: test |
|
revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 |
|
metrics: |
|
- type: accuracy |
|
value: 61.80228648285138 |
|
- type: f1 |
|
value: 59.56813863530079 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: None |
|
name: MTEB MassiveScenarioClassification (en) |
|
config: en |
|
split: test |
|
revision: 7d571f92784cd94a019292a1f45445077d0ef634 |
|
metrics: |
|
- type: accuracy |
|
value: 68.55413584398117 |
|
- type: f1 |
|
value: 67.09171141857304 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: None |
|
name: MTEB MedrxivClusteringP2P |
|
config: default |
|
split: test |
|
revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73 |
|
metrics: |
|
- type: v_measure |
|
value: 26.373735594129403 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: None |
|
name: MTEB MedrxivClusteringS2S |
|
config: default |
|
split: test |
|
revision: 35191c8c0dca72d8ff3efcd72aa802307d469663 |
|
metrics: |
|
- type: v_measure |
|
value: 22.97944248268257 |
|
- task: |
|
type: Reranking |
|
dataset: |
|
type: None |
|
name: MTEB MindSmallReranking |
|
config: default |
|
split: test |
|
revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69 |
|
metrics: |
|
- type: map |
|
value: 28.174012229019485 |
|
- type: mrr |
|
value: 28.972842705926528 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB NFCorpus |
|
config: default |
|
split: test |
|
revision: ec0fa4fe99da2ff19ca1214b7966684033a58814 |
|
metrics: |
|
- type: map_at_1 |
|
value: 2.814 |
|
- type: map_at_10 |
|
value: 5.412999999999999 |
|
- type: map_at_100 |
|
value: 7.0120000000000005 |
|
- type: map_at_1000 |
|
value: 8.187 |
|
- type: map_at_3 |
|
value: 4.289 |
|
- type: map_at_5 |
|
value: 4.825 |
|
- type: mrr_at_1 |
|
value: 29.102 |
|
- type: mrr_at_10 |
|
value: 36.876999999999995 |
|
- type: mrr_at_100 |
|
value: 37.506 |
|
- type: mrr_at_1000 |
|
value: 37.592 |
|
- type: mrr_at_3 |
|
value: 34.262 |
|
- type: mrr_at_5 |
|
value: 35.888 |
|
- type: ndcg_at_1 |
|
value: 27.089999999999996 |
|
- type: ndcg_at_10 |
|
value: 19.134999999999998 |
|
- type: ndcg_at_100 |
|
value: 18.29 |
|
- type: ndcg_at_1000 |
|
value: 27.842 |
|
- type: ndcg_at_3 |
|
value: 22.417 |
|
- type: ndcg_at_5 |
|
value: 21.081 |
|
- type: precision_at_1 |
|
value: 29.102 |
|
- type: precision_at_10 |
|
value: 14.302999999999999 |
|
- type: precision_at_100 |
|
value: 5.632000000000001 |
|
- type: precision_at_1000 |
|
value: 1.856 |
|
- type: precision_at_3 |
|
value: 21.156 |
|
- type: precision_at_5 |
|
value: 18.39 |
|
- type: recall_at_1 |
|
value: 2.814 |
|
- type: recall_at_10 |
|
value: 8.431 |
|
- type: recall_at_100 |
|
value: 19.332 |
|
- type: recall_at_1000 |
|
value: 53.879999999999995 |
|
- type: recall_at_3 |
|
value: 5.212 |
|
- type: recall_at_5 |
|
value: 6.364 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB NQ |
|
config: default |
|
split: test |
|
revision: b774495ed302d8c44a3a7ea25c90dbce03968f31 |
|
metrics: |
|
- type: map_at_1 |
|
value: 7.423 |
|
- type: map_at_10 |
|
value: 12.638 |
|
- type: map_at_100 |
|
value: 13.672 |
|
- type: map_at_1000 |
|
value: 13.776 |
|
- type: map_at_3 |
|
value: 10.727 |
|
- type: map_at_5 |
|
value: 11.745 |
|
- type: mrr_at_1 |
|
value: 8.459 |
|
- type: mrr_at_10 |
|
value: 14.068 |
|
- type: mrr_at_100 |
|
value: 15.067 |
|
- type: mrr_at_1000 |
|
value: 15.155 |
|
- type: mrr_at_3 |
|
value: 12.065 |
|
- type: mrr_at_5 |
|
value: 13.142999999999999 |
|
- type: ndcg_at_1 |
|
value: 8.459 |
|
- type: ndcg_at_10 |
|
value: 16.152 |
|
- type: ndcg_at_100 |
|
value: 21.636 |
|
- type: ndcg_at_1000 |
|
value: 24.593 |
|
- type: ndcg_at_3 |
|
value: 12.16 |
|
- type: ndcg_at_5 |
|
value: 14.011000000000001 |
|
- type: precision_at_1 |
|
value: 8.459 |
|
- type: precision_at_10 |
|
value: 3.004 |
|
- type: precision_at_100 |
|
value: 0.615 |
|
- type: precision_at_1000 |
|
value: 0.09 |
|
- type: precision_at_3 |
|
value: 5.755 |
|
- type: precision_at_5 |
|
value: 4.460999999999999 |
|
- type: recall_at_1 |
|
value: 7.423 |
|
- type: recall_at_10 |
|
value: 25.698 |
|
- type: recall_at_100 |
|
value: 51.556999999999995 |
|
- type: recall_at_1000 |
|
value: 74.435 |
|
- type: recall_at_3 |
|
value: 15.015 |
|
- type: recall_at_5 |
|
value: 19.397000000000002 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB QuoraRetrieval |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 60.516999999999996 |
|
- type: map_at_10 |
|
value: 72.943 |
|
- type: map_at_100 |
|
value: 73.741 |
|
- type: map_at_1000 |
|
value: 73.78 |
|
- type: map_at_3 |
|
value: 70.025 |
|
- type: map_at_5 |
|
value: 71.786 |
|
- type: mrr_at_1 |
|
value: 69.82000000000001 |
|
- type: mrr_at_10 |
|
value: 77.402 |
|
- type: mrr_at_100 |
|
value: 77.694 |
|
- type: mrr_at_1000 |
|
value: 77.702 |
|
- type: mrr_at_3 |
|
value: 75.852 |
|
- type: mrr_at_5 |
|
value: 76.839 |
|
- type: ndcg_at_1 |
|
value: 69.78 |
|
- type: ndcg_at_10 |
|
value: 77.777 |
|
- type: ndcg_at_100 |
|
value: 80.148 |
|
- type: ndcg_at_1000 |
|
value: 80.64 |
|
- type: ndcg_at_3 |
|
value: 74.071 |
|
- type: ndcg_at_5 |
|
value: 75.974 |
|
- type: precision_at_1 |
|
value: 69.78 |
|
- type: precision_at_10 |
|
value: 11.776 |
|
- type: precision_at_100 |
|
value: 1.431 |
|
- type: precision_at_1000 |
|
value: 0.153 |
|
- type: precision_at_3 |
|
value: 32.11 |
|
- type: precision_at_5 |
|
value: 21.284 |
|
- type: recall_at_1 |
|
value: 60.516999999999996 |
|
- type: recall_at_10 |
|
value: 87.149 |
|
- type: recall_at_100 |
|
value: 96.33 |
|
- type: recall_at_1000 |
|
value: 99.236 |
|
- type: recall_at_3 |
|
value: 76.592 |
|
- type: recall_at_5 |
|
value: 81.828 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: None |
|
name: MTEB RedditClustering |
|
config: default |
|
split: test |
|
revision: 24640382cdbf8abc73003fb0fa6d111a705499eb |
|
metrics: |
|
- type: v_measure |
|
value: 24.96238867406633 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: None |
|
name: MTEB RedditClusteringP2P |
|
config: default |
|
split: test |
|
revision: 282350215ef01743dc01b456c7f5241fa8937f16 |
|
metrics: |
|
- type: v_measure |
|
value: 42.15456565539958 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB SCIDOCS |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 2.545 |
|
- type: map_at_10 |
|
value: 5.84 |
|
- type: map_at_100 |
|
value: 6.984999999999999 |
|
- type: map_at_1000 |
|
value: 7.216 |
|
- type: map_at_3 |
|
value: 4.348 |
|
- type: map_at_5 |
|
value: 5.064 |
|
- type: mrr_at_1 |
|
value: 12.6 |
|
- type: mrr_at_10 |
|
value: 19.799 |
|
- type: mrr_at_100 |
|
value: 20.964 |
|
- type: mrr_at_1000 |
|
value: 21.067 |
|
- type: mrr_at_3 |
|
value: 17.349999999999998 |
|
- type: mrr_at_5 |
|
value: 18.77 |
|
- type: ndcg_at_1 |
|
value: 12.6 |
|
- type: ndcg_at_10 |
|
value: 10.683 |
|
- type: ndcg_at_100 |
|
value: 16.256 |
|
- type: ndcg_at_1000 |
|
value: 21.304000000000002 |
|
- type: ndcg_at_3 |
|
value: 10.167 |
|
- type: ndcg_at_5 |
|
value: 8.853 |
|
- type: precision_at_1 |
|
value: 12.6 |
|
- type: precision_at_10 |
|
value: 5.54 |
|
- type: precision_at_100 |
|
value: 1.3679999999999999 |
|
- type: precision_at_1000 |
|
value: 0.259 |
|
- type: precision_at_3 |
|
value: 9.467 |
|
- type: precision_at_5 |
|
value: 7.739999999999999 |
|
- type: recall_at_1 |
|
value: 2.545 |
|
- type: recall_at_10 |
|
value: 11.212 |
|
- type: recall_at_100 |
|
value: 27.785 |
|
- type: recall_at_1000 |
|
value: 52.588 |
|
- type: recall_at_3 |
|
value: 5.768 |
|
- type: recall_at_5 |
|
value: 7.843 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: None |
|
name: MTEB SICK-R |
|
config: default |
|
split: test |
|
revision: a6ea5a8cab320b040a23452cc28066d9beae2cee |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 76.14154775161344 |
|
- type: cos_sim_spearman |
|
value: 67.34346119954171 |
|
- type: euclidean_pearson |
|
value: 72.35899953785258 |
|
- type: euclidean_spearman |
|
value: 67.3437533363199 |
|
- type: manhattan_pearson |
|
value: 70.9274622484765 |
|
- type: manhattan_spearman |
|
value: 66.00500346801255 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: None |
|
name: MTEB STS12 |
|
config: default |
|
split: test |
|
revision: a0d554a64d88156834ff5ae9920b964011b16384 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 73.45319575935073 |
|
- type: cos_sim_spearman |
|
value: 66.85451568709998 |
|
- type: euclidean_pearson |
|
value: 69.91095676583507 |
|
- type: euclidean_spearman |
|
value: 66.8557417173495 |
|
- type: manhattan_pearson |
|
value: 70.79095833168148 |
|
- type: manhattan_spearman |
|
value: 68.07407266249538 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: None |
|
name: MTEB STS13 |
|
config: default |
|
split: test |
|
revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 76.69086874055675 |
|
- type: cos_sim_spearman |
|
value: 78.04733839857 |
|
- type: euclidean_pearson |
|
value: 77.63075897573337 |
|
- type: euclidean_spearman |
|
value: 78.04737621071355 |
|
- type: manhattan_pearson |
|
value: 77.94694857794688 |
|
- type: manhattan_spearman |
|
value: 78.45352622493287 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: None |
|
name: MTEB STS14 |
|
config: default |
|
split: test |
|
revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 76.79462726940899 |
|
- type: cos_sim_spearman |
|
value: 73.75004555900799 |
|
- type: euclidean_pearson |
|
value: 75.98934348748296 |
|
- type: euclidean_spearman |
|
value: 73.7500358689292 |
|
- type: manhattan_pearson |
|
value: 76.00086800123202 |
|
- type: manhattan_spearman |
|
value: 74.06711780537452 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: None |
|
name: MTEB STS15 |
|
config: default |
|
split: test |
|
revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 79.78001899088082 |
|
- type: cos_sim_spearman |
|
value: 80.8098659330615 |
|
- type: euclidean_pearson |
|
value: 80.81455975868363 |
|
- type: euclidean_spearman |
|
value: 80.80987420717732 |
|
- type: manhattan_pearson |
|
value: 81.43248963554757 |
|
- type: manhattan_spearman |
|
value: 81.56756512374152 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: None |
|
name: MTEB STS16 |
|
config: default |
|
split: test |
|
revision: 4d8694f8f0e0100860b497b999b3dbed754a0513 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 75.09273075600336 |
|
- type: cos_sim_spearman |
|
value: 76.44072137673248 |
|
- type: euclidean_pearson |
|
value: 76.07667290013225 |
|
- type: euclidean_spearman |
|
value: 76.44127170482552 |
|
- type: manhattan_pearson |
|
value: 76.6332220160955 |
|
- type: manhattan_spearman |
|
value: 77.11730946641201 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: None |
|
name: MTEB STS17 (en-en) |
|
config: en-en |
|
split: test |
|
revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 82.86191718272701 |
|
- type: cos_sim_spearman |
|
value: 84.05759596682893 |
|
- type: euclidean_pearson |
|
value: 84.05247433515731 |
|
- type: euclidean_spearman |
|
value: 84.05847010074612 |
|
- type: manhattan_pearson |
|
value: 84.20796352611727 |
|
- type: manhattan_spearman |
|
value: 84.20823102579908 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: None |
|
name: MTEB STS22 (en) |
|
config: en |
|
split: test |
|
revision: eea2b4fe26a775864c896887d910b76a8098ad3f |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 63.405232991348434 |
|
- type: cos_sim_spearman |
|
value: 61.017715202418366 |
|
- type: euclidean_pearson |
|
value: 63.436431062341434 |
|
- type: euclidean_spearman |
|
value: 61.017715202418366 |
|
- type: manhattan_pearson |
|
value: 63.6521277557926 |
|
- type: manhattan_spearman |
|
value: 61.73049790460205 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: None |
|
name: MTEB STSBenchmark |
|
config: default |
|
split: test |
|
revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 76.80795371667985 |
|
- type: cos_sim_spearman |
|
value: 75.43643133516306 |
|
- type: euclidean_pearson |
|
value: 76.87791904895818 |
|
- type: euclidean_spearman |
|
value: 75.4364797257313 |
|
- type: manhattan_pearson |
|
value: 76.89603534893224 |
|
- type: manhattan_spearman |
|
value: 75.44538808910046 |
|
- task: |
|
type: Reranking |
|
dataset: |
|
type: None |
|
name: MTEB SciDocsRR |
|
config: default |
|
split: test |
|
revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab |
|
metrics: |
|
- type: map |
|
value: 69.67746354273282 |
|
- type: mrr |
|
value: 89.80577701165936 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB SciFact |
|
config: default |
|
split: test |
|
revision: 0228b52cf27578f30900b9e5271d331663a030d7 |
|
metrics: |
|
- type: map_at_1 |
|
value: 31.333 |
|
- type: map_at_10 |
|
value: 37.378 |
|
- type: map_at_100 |
|
value: 38.641999999999996 |
|
- type: map_at_1000 |
|
value: 38.719 |
|
- type: map_at_3 |
|
value: 35.06 |
|
- type: map_at_5 |
|
value: 36.64 |
|
- type: mrr_at_1 |
|
value: 33.667 |
|
- type: mrr_at_10 |
|
value: 39.324 |
|
- type: mrr_at_100 |
|
value: 40.449 |
|
- type: mrr_at_1000 |
|
value: 40.512 |
|
- type: mrr_at_3 |
|
value: 37.278 |
|
- type: mrr_at_5 |
|
value: 38.744 |
|
- type: ndcg_at_1 |
|
value: 33.667 |
|
- type: ndcg_at_10 |
|
value: 40.92 |
|
- type: ndcg_at_100 |
|
value: 46.938 |
|
- type: ndcg_at_1000 |
|
value: 48.811 |
|
- type: ndcg_at_3 |
|
value: 36.675999999999995 |
|
- type: ndcg_at_5 |
|
value: 39.31 |
|
- type: precision_at_1 |
|
value: 33.667 |
|
- type: precision_at_10 |
|
value: 5.633 |
|
- type: precision_at_100 |
|
value: 0.88 |
|
- type: precision_at_1000 |
|
value: 0.104 |
|
- type: precision_at_3 |
|
value: 14.222000000000001 |
|
- type: precision_at_5 |
|
value: 10.0 |
|
- type: recall_at_1 |
|
value: 31.333 |
|
- type: recall_at_10 |
|
value: 49.956 |
|
- type: recall_at_100 |
|
value: 77.683 |
|
- type: recall_at_1000 |
|
value: 92.133 |
|
- type: recall_at_3 |
|
value: 39.0 |
|
- type: recall_at_5 |
|
value: 45.317 |
|
- task: |
|
type: PairClassification |
|
dataset: |
|
type: None |
|
name: MTEB SprintDuplicateQuestions |
|
config: default |
|
split: test |
|
revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46 |
|
metrics: |
|
- type: cos_sim_accuracy |
|
value: 99.63663366336634 |
|
- type: cos_sim_ap |
|
value: 87.01958641278611 |
|
- type: cos_sim_f1 |
|
value: 80.12684989429175 |
|
- type: cos_sim_precision |
|
value: 84.97757847533633 |
|
- type: cos_sim_recall |
|
value: 75.8 |
|
- type: dot_accuracy |
|
value: 99.63663366336634 |
|
- type: dot_ap |
|
value: 87.01958641278611 |
|
- type: dot_f1 |
|
value: 80.12684989429175 |
|
- type: dot_precision |
|
value: 84.97757847533633 |
|
- type: dot_recall |
|
value: 75.8 |
|
- type: euclidean_accuracy |
|
value: 99.63663366336634 |
|
- type: euclidean_ap |
|
value: 87.01958641278611 |
|
- type: euclidean_f1 |
|
value: 80.12684989429175 |
|
- type: euclidean_precision |
|
value: 84.97757847533633 |
|
- type: euclidean_recall |
|
value: 75.8 |
|
- type: manhattan_accuracy |
|
value: 99.68613861386139 |
|
- type: manhattan_ap |
|
value: 90.11510992894823 |
|
- type: manhattan_f1 |
|
value: 83.73035985808414 |
|
- type: manhattan_precision |
|
value: 84.89208633093526 |
|
- type: manhattan_recall |
|
value: 82.6 |
|
- type: max_accuracy |
|
value: 99.68613861386139 |
|
- type: max_ap |
|
value: 90.11510992894823 |
|
- type: max_f1 |
|
value: 83.73035985808414 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: None |
|
name: MTEB StackExchangeClustering |
|
config: default |
|
split: test |
|
revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259 |
|
metrics: |
|
- type: v_measure |
|
value: 31.564966710258002 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: None |
|
name: MTEB StackExchangeClusteringP2P |
|
config: default |
|
split: test |
|
revision: 815ca46b2622cec33ccafc3735d572c266efdb44 |
|
metrics: |
|
- type: v_measure |
|
value: 28.902331000032934 |
|
- task: |
|
type: Reranking |
|
dataset: |
|
type: None |
|
name: MTEB StackOverflowDupQuestions |
|
config: default |
|
split: test |
|
revision: e185fbe320c72810689fc5848eb6114e1ef5ec69 |
|
metrics: |
|
- type: map |
|
value: 42.84399261061117 |
|
- type: mrr |
|
value: 43.29435372633902 |
|
- task: |
|
type: Summarization |
|
dataset: |
|
type: None |
|
name: MTEB SummEval |
|
config: default |
|
split: test |
|
revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 29.95259336062129 |
|
- type: cos_sim_spearman |
|
value: 29.305731756791836 |
|
- type: dot_pearson |
|
value: 29.95259337454406 |
|
- type: dot_spearman |
|
value: 29.33902263846769 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB TRECCOVID |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 0.13 |
|
- type: map_at_10 |
|
value: 0.653 |
|
- type: map_at_100 |
|
value: 3.5479999999999996 |
|
- type: map_at_1000 |
|
value: 8.239 |
|
- type: map_at_3 |
|
value: 0.27 |
|
- type: map_at_5 |
|
value: 0.387 |
|
- type: mrr_at_1 |
|
value: 46.0 |
|
- type: mrr_at_10 |
|
value: 58.477999999999994 |
|
- type: mrr_at_100 |
|
value: 59.079 |
|
- type: mrr_at_1000 |
|
value: 59.099000000000004 |
|
- type: mrr_at_3 |
|
value: 56.00000000000001 |
|
- type: mrr_at_5 |
|
value: 57.3 |
|
- type: ndcg_at_1 |
|
value: 42.0 |
|
- type: ndcg_at_10 |
|
value: 34.636 |
|
- type: ndcg_at_100 |
|
value: 26.856 |
|
- type: ndcg_at_1000 |
|
value: 24.409 |
|
- type: ndcg_at_3 |
|
value: 39.050000000000004 |
|
- type: ndcg_at_5 |
|
value: 36.541000000000004 |
|
- type: precision_at_1 |
|
value: 50.0 |
|
- type: precision_at_10 |
|
value: 37.2 |
|
- type: precision_at_100 |
|
value: 28.28 |
|
- type: precision_at_1000 |
|
value: 11.996 |
|
- type: precision_at_3 |
|
value: 44.0 |
|
- type: precision_at_5 |
|
value: 40.0 |
|
- type: recall_at_1 |
|
value: 0.13 |
|
- type: recall_at_10 |
|
value: 0.822 |
|
- type: recall_at_100 |
|
value: 6.015000000000001 |
|
- type: recall_at_1000 |
|
value: 23.772 |
|
- type: recall_at_3 |
|
value: 0.307 |
|
- type: recall_at_5 |
|
value: 0.453 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB Touche2020 |
|
config: default |
|
split: test |
|
revision: a34f9a33db75fa0cbb21bb5cfc3dae8dc8bec93f |
|
metrics: |
|
- type: map_at_1 |
|
value: 2.537 |
|
- type: map_at_10 |
|
value: 8.591 |
|
- type: map_at_100 |
|
value: 14.328 |
|
- type: map_at_1000 |
|
value: 15.919 |
|
- type: map_at_3 |
|
value: 4.8500000000000005 |
|
- type: map_at_5 |
|
value: 6.389 |
|
- type: mrr_at_1 |
|
value: 34.694 |
|
- type: mrr_at_10 |
|
value: 46.553 |
|
- type: mrr_at_100 |
|
value: 47.515 |
|
- type: mrr_at_1000 |
|
value: 47.515 |
|
- type: mrr_at_3 |
|
value: 42.857 |
|
- type: mrr_at_5 |
|
value: 44.796 |
|
- type: ndcg_at_1 |
|
value: 33.672999999999995 |
|
- type: ndcg_at_10 |
|
value: 21.73 |
|
- type: ndcg_at_100 |
|
value: 34.699000000000005 |
|
- type: ndcg_at_1000 |
|
value: 46.143 |
|
- type: ndcg_at_3 |
|
value: 27.343 |
|
- type: ndcg_at_5 |
|
value: 24.11 |
|
- type: precision_at_1 |
|
value: 34.694 |
|
- type: precision_at_10 |
|
value: 18.776 |
|
- type: precision_at_100 |
|
value: 7.571 |
|
- type: precision_at_1000 |
|
value: 1.478 |
|
- type: precision_at_3 |
|
value: 27.211000000000002 |
|
- type: precision_at_5 |
|
value: 23.673 |
|
- type: recall_at_1 |
|
value: 2.537 |
|
- type: recall_at_10 |
|
value: 13.012 |
|
- type: recall_at_100 |
|
value: 45.891 |
|
- type: recall_at_1000 |
|
value: 80.739 |
|
- type: recall_at_3 |
|
value: 5.744 |
|
- type: recall_at_5 |
|
value: 8.278 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: None |
|
name: MTEB ToxicConversationsClassification |
|
config: default |
|
split: test |
|
revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c |
|
metrics: |
|
- type: accuracy |
|
value: 69.004 |
|
- type: ap |
|
value: 13.022449069209996 |
|
- type: f1 |
|
value: 52.831422157603235 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: None |
|
name: MTEB TweetSentimentExtractionClassification |
|
config: default |
|
split: test |
|
revision: d604517c81ca91fe16a244d1248fc021f9ecee7a |
|
metrics: |
|
- type: accuracy |
|
value: 53.55687606112054 |
|
- type: f1 |
|
value: 53.742471169925146 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: None |
|
name: MTEB TwentyNewsgroupsClustering |
|
config: default |
|
split: test |
|
revision: 6125ec4e24fa026cec8a478383ee943acfbd5449 |
|
metrics: |
|
- type: v_measure |
|
value: 30.854612368831237 |
|
- task: |
|
type: PairClassification |
|
dataset: |
|
type: None |
|
name: MTEB TwitterSemEval2015 |
|
config: default |
|
split: test |
|
revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1 |
|
metrics: |
|
- type: cos_sim_accuracy |
|
value: 83.20915539130954 |
|
- type: cos_sim_ap |
|
value: 64.64935846149021 |
|
- type: cos_sim_f1 |
|
value: 61.74544588641505 |
|
- type: cos_sim_precision |
|
value: 56.25949229767846 |
|
- type: cos_sim_recall |
|
value: 68.41688654353561 |
|
- type: dot_accuracy |
|
value: 83.20915539130954 |
|
- type: dot_ap |
|
value: 64.64935846149021 |
|
- type: dot_f1 |
|
value: 61.74544588641505 |
|
- type: dot_precision |
|
value: 56.25949229767846 |
|
- type: dot_recall |
|
value: 68.41688654353561 |
|
- type: euclidean_accuracy |
|
value: 83.20915539130954 |
|
- type: euclidean_ap |
|
value: 64.64935846149021 |
|
- type: euclidean_f1 |
|
value: 61.74544588641505 |
|
- type: euclidean_precision |
|
value: 56.25949229767846 |
|
- type: euclidean_recall |
|
value: 68.41688654353561 |
|
- type: manhattan_accuracy |
|
value: 83.00649698992669 |
|
- type: manhattan_ap |
|
value: 63.241363240922475 |
|
- type: manhattan_f1 |
|
value: 60.10508778674869 |
|
- type: manhattan_precision |
|
value: 58.435085970595566 |
|
- type: manhattan_recall |
|
value: 61.87335092348285 |
|
- type: max_accuracy |
|
value: 83.20915539130954 |
|
- type: max_ap |
|
value: 64.64935846149021 |
|
- type: max_f1 |
|
value: 61.74544588641505 |
|
- task: |
|
type: PairClassification |
|
dataset: |
|
type: None |
|
name: MTEB TwitterURLCorpus |
|
config: default |
|
split: test |
|
revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf |
|
metrics: |
|
- type: cos_sim_accuracy |
|
value: 87.33457523188575 |
|
- type: cos_sim_ap |
|
value: 82.48667288124405 |
|
- type: cos_sim_f1 |
|
value: 74.60564319040213 |
|
- type: cos_sim_precision |
|
value: 71.86474532743615 |
|
- type: cos_sim_recall |
|
value: 77.56390514320911 |
|
- type: dot_accuracy |
|
value: 87.33457523188575 |
|
- type: dot_ap |
|
value: 82.48667984460607 |
|
- type: dot_f1 |
|
value: 74.60564319040213 |
|
- type: dot_precision |
|
value: 71.86474532743615 |
|
- type: dot_recall |
|
value: 77.56390514320911 |
|
- type: euclidean_accuracy |
|
value: 87.33457523188575 |
|
- type: euclidean_ap |
|
value: 82.48667328332766 |
|
- type: euclidean_f1 |
|
value: 74.60564319040213 |
|
- type: euclidean_precision |
|
value: 71.86474532743615 |
|
- type: euclidean_recall |
|
value: 77.56390514320911 |
|
- type: manhattan_accuracy |
|
value: 87.28994450265843 |
|
- type: manhattan_ap |
|
value: 82.53662260997004 |
|
- type: manhattan_f1 |
|
value: 74.64819224940463 |
|
- type: manhattan_precision |
|
value: 70.24310742903708 |
|
- type: manhattan_recall |
|
value: 79.64274715121651 |
|
- type: max_accuracy |
|
value: 87.33457523188575 |
|
- type: max_ap |
|
value: 82.53662260997004 |
|
- type: max_f1 |
|
value: 74.64819224940463 |
|
--- |
