|
--- |
|
model-index: |
|
- name: gte_tiny |
|
results: |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/amazon_counterfactual |
|
name: MTEB AmazonCounterfactualClassification (en) |
|
config: en |
|
split: test |
|
revision: e8379541af4e31359cca9fbcf4b00f2671dba205 |
|
metrics: |
|
- type: accuracy |
|
value: 71.76119402985076 |
|
- type: ap |
|
value: 34.63659287952359 |
|
- type: f1 |
|
value: 65.88939512571113 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/amazon_polarity |
|
name: MTEB AmazonPolarityClassification |
|
config: default |
|
split: test |
|
revision: e2d317d38cd51312af73b3d32a06d1a08b442046 |
|
metrics: |
|
- type: accuracy |
|
value: 86.61324999999998 |
|
- type: ap |
|
value: 81.7476302802319 |
|
- type: f1 |
|
value: 86.5863470912001 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/amazon_reviews_multi |
|
name: MTEB AmazonReviewsClassification (en) |
|
config: en |
|
split: test |
|
revision: 1399c76144fd37290681b995c656ef9b2e06e26d |
|
metrics: |
|
- type: accuracy |
|
value: 42.61000000000001 |
|
- type: f1 |
|
value: 42.2217180000715 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: arguana |
|
name: MTEB ArguAna |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 28.377999999999997 |
|
- type: map_at_10 |
|
value: 44.565 |
|
- type: map_at_100 |
|
value: 45.48 |
|
- type: map_at_1000 |
|
value: 45.487 |
|
- type: map_at_3 |
|
value: 39.841 |
|
- type: map_at_5 |
|
value: 42.284 |
|
- type: mrr_at_1 |
|
value: 29.445 |
|
- type: mrr_at_10 |
|
value: 44.956 |
|
- type: mrr_at_100 |
|
value: 45.877 |
|
- type: mrr_at_1000 |
|
value: 45.884 |
|
- type: mrr_at_3 |
|
value: 40.209 |
|
- type: mrr_at_5 |
|
value: 42.719 |
|
- type: ndcg_at_1 |
|
value: 28.377999999999997 |
|
- type: ndcg_at_10 |
|
value: 53.638 |
|
- type: ndcg_at_100 |
|
value: 57.354000000000006 |
|
- type: ndcg_at_1000 |
|
value: 57.513000000000005 |
|
- type: ndcg_at_3 |
|
value: 43.701 |
|
- type: ndcg_at_5 |
|
value: 48.114000000000004 |
|
- type: precision_at_1 |
|
value: 28.377999999999997 |
|
- type: precision_at_10 |
|
value: 8.272 |
|
- type: precision_at_100 |
|
value: 0.984 |
|
- type: precision_at_1000 |
|
value: 0.1 |
|
- type: precision_at_3 |
|
value: 18.303 |
|
- type: precision_at_5 |
|
value: 13.129 |
|
- type: recall_at_1 |
|
value: 28.377999999999997 |
|
- type: recall_at_10 |
|
value: 82.717 |
|
- type: recall_at_100 |
|
value: 98.43499999999999 |
|
- type: recall_at_1000 |
|
value: 99.644 |
|
- type: recall_at_3 |
|
value: 54.908 |
|
- type: recall_at_5 |
|
value: 65.647 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: mteb/arxiv-clustering-p2p |
|
name: MTEB ArxivClusteringP2P |
|
config: default |
|
split: test |
|
revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d |
|
metrics: |
|
- type: v_measure |
|
value: 46.637318326729876 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: mteb/arxiv-clustering-s2s |
|
name: MTEB ArxivClusteringS2S |
|
config: default |
|
split: test |
|
revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53 |
|
metrics: |
|
- type: v_measure |
|
value: 36.01134479855804 |
|
- task: |
|
type: Reranking |
|
dataset: |
|
type: mteb/askubuntudupquestions-reranking |
|
name: MTEB AskUbuntuDupQuestions |
|
config: default |
|
split: test |
|
revision: 2000358ca161889fa9c082cb41daa8dcfb161a54 |
|
metrics: |
|
- type: map |
|
value: 59.82917555338909 |
|
- type: mrr |
|
value: 74.7888361254012 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: mteb/biosses-sts |
|
name: MTEB BIOSSES |
|
config: default |
|
split: test |
|
revision: d3fb88f8f02e40887cd149695127462bbcf29b4a |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 87.1657730995964 |
|
- type: cos_sim_spearman |
|
value: 86.62787748941281 |
|
- type: euclidean_pearson |
|
value: 85.48127914481798 |
|
- type: euclidean_spearman |
|
value: 86.48148861167424 |
|
- type: manhattan_pearson |
|
value: 85.07496934780823 |
|
- type: manhattan_spearman |
|
value: 86.39473964708843 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/banking77 |
|
name: MTEB Banking77Classification |
|
config: default |
|
split: test |
|
revision: 0fd18e25b25c072e09e0d92ab615fda904d66300 |
|
metrics: |
|
- type: accuracy |
|
value: 81.73051948051948 |
|
- type: f1 |
|
value: 81.66368364988331 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: mteb/biorxiv-clustering-p2p |
|
name: MTEB BiorxivClusteringP2P |
|
config: default |
|
split: test |
|
revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40 |
|
metrics: |
|
- type: v_measure |
|
value: 39.18623707448217 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: mteb/biorxiv-clustering-s2s |
|
name: MTEB BiorxivClusteringS2S |
|
config: default |
|
split: test |
|
revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908 |
|
metrics: |
|
- type: v_measure |
|
value: 32.12697757150375 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: BeIR/cqadupstack |
|
name: MTEB CQADupstackAndroidRetrieval |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 29.160000000000004 |
|
- type: map_at_10 |
|
value: 40.474 |
|
- type: map_at_100 |
|
value: 41.905 |
|
- type: map_at_1000 |
|
value: 42.041000000000004 |
|
- type: map_at_3 |
|
value: 37.147000000000006 |
|
- type: map_at_5 |
|
value: 38.873999999999995 |
|
- type: mrr_at_1 |
|
value: 36.91 |
|
- type: mrr_at_10 |
|
value: 46.495999999999995 |
|
- type: mrr_at_100 |
|
value: 47.288000000000004 |
|
- type: mrr_at_1000 |
|
value: 47.339999999999996 |
|
- type: mrr_at_3 |
|
value: 43.777 |
|
- type: mrr_at_5 |
|
value: 45.257999999999996 |
|
- type: ndcg_at_1 |
|
value: 36.91 |
|
- type: ndcg_at_10 |
|
value: 46.722 |
|
- type: ndcg_at_100 |
|
value: 51.969 |
|
- type: ndcg_at_1000 |
|
value: 54.232 |
|
- type: ndcg_at_3 |
|
value: 41.783 |
|
- type: ndcg_at_5 |
|
value: 43.797000000000004 |
|
- type: precision_at_1 |
|
value: 36.91 |
|
- type: precision_at_10 |
|
value: 9.013 |
|
- type: precision_at_100 |
|
value: 1.455 |
|
- type: precision_at_1000 |
|
value: 0.193 |
|
- type: precision_at_3 |
|
value: 20.124 |
|
- type: precision_at_5 |
|
value: 14.363000000000001 |
|
- type: recall_at_1 |
|
value: 29.160000000000004 |
|
- type: recall_at_10 |
|
value: 58.521 |
|
- type: recall_at_100 |
|
value: 80.323 |
|
- type: recall_at_1000 |
|
value: 95.13000000000001 |
|
- type: recall_at_3 |
|
value: 44.205 |
|
- type: recall_at_5 |
|
value: 49.97 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: BeIR/cqadupstack |
|
name: MTEB CQADupstackEnglishRetrieval |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 27.750000000000004 |
|
- type: map_at_10 |
|
value: 36.39 |
|
- type: map_at_100 |
|
value: 37.5 |
|
- type: map_at_1000 |
|
value: 37.625 |
|
- type: map_at_3 |
|
value: 33.853 |
|
- type: map_at_5 |
|
value: 35.397 |
|
- type: mrr_at_1 |
|
value: 34.14 |
|
- type: mrr_at_10 |
|
value: 41.841 |
|
- type: mrr_at_100 |
|
value: 42.469 |
|
- type: mrr_at_1000 |
|
value: 42.521 |
|
- type: mrr_at_3 |
|
value: 39.724 |
|
- type: mrr_at_5 |
|
value: 40.955999999999996 |
|
- type: ndcg_at_1 |
|
value: 34.14 |
|
- type: ndcg_at_10 |
|
value: 41.409 |
|
- type: ndcg_at_100 |
|
value: 45.668 |
|
- type: ndcg_at_1000 |
|
value: 47.916 |
|
- type: ndcg_at_3 |
|
value: 37.836 |
|
- type: ndcg_at_5 |
|
value: 39.650999999999996 |
|
- type: precision_at_1 |
|
value: 34.14 |
|
- type: precision_at_10 |
|
value: 7.739 |
|
- type: precision_at_100 |
|
value: 1.2630000000000001 |
|
- type: precision_at_1000 |
|
value: 0.173 |
|
- type: precision_at_3 |
|
value: 18.217 |
|
- type: precision_at_5 |
|
value: 12.854 |
|
- type: recall_at_1 |
|
value: 27.750000000000004 |
|
- type: recall_at_10 |
|
value: 49.882 |
|
- type: recall_at_100 |
|
value: 68.556 |
|
- type: recall_at_1000 |
|
value: 83.186 |
|
- type: recall_at_3 |
|
value: 39.047 |
|
- type: recall_at_5 |
|
value: 44.458 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: BeIR/cqadupstack |
|
name: MTEB CQADupstackGamingRetrieval |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 36.879 |
|
- type: map_at_10 |
|
value: 48.878 |
|
- type: map_at_100 |
|
value: 49.918 |
|
- type: map_at_1000 |
|
value: 49.978 |
|
- type: map_at_3 |
|
value: 45.867999999999995 |
|
- type: map_at_5 |
|
value: 47.637 |
|
- type: mrr_at_1 |
|
value: 42.696 |
|
- type: mrr_at_10 |
|
value: 52.342 |
|
- type: mrr_at_100 |
|
value: 53.044000000000004 |
|
- type: mrr_at_1000 |
|
value: 53.077 |
|
- type: mrr_at_3 |
|
value: 50.01 |
|
- type: mrr_at_5 |
|
value: 51.437 |
|
- type: ndcg_at_1 |
|
value: 42.696 |
|
- type: ndcg_at_10 |
|
value: 54.469 |
|
- type: ndcg_at_100 |
|
value: 58.664 |
|
- type: ndcg_at_1000 |
|
value: 59.951 |
|
- type: ndcg_at_3 |
|
value: 49.419999999999995 |
|
- type: ndcg_at_5 |
|
value: 52.007000000000005 |
|
- type: precision_at_1 |
|
value: 42.696 |
|
- type: precision_at_10 |
|
value: 8.734 |
|
- type: precision_at_100 |
|
value: 1.1769999999999998 |
|
- type: precision_at_1000 |
|
value: 0.133 |
|
- type: precision_at_3 |
|
value: 22.027 |
|
- type: precision_at_5 |
|
value: 15.135000000000002 |
|
- type: recall_at_1 |
|
value: 36.879 |
|
- type: recall_at_10 |
|
value: 67.669 |
|
- type: recall_at_100 |
|
value: 85.822 |
|
- type: recall_at_1000 |
|
value: 95.092 |
|
- type: recall_at_3 |
|
value: 54.157999999999994 |
|
- type: recall_at_5 |
|
value: 60.436 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: BeIR/cqadupstack |
|
name: MTEB CQADupstackGisRetrieval |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 22.942 |
|
- type: map_at_10 |
|
value: 31.741999999999997 |
|
- type: map_at_100 |
|
value: 32.721000000000004 |
|
- type: map_at_1000 |
|
value: 32.809 |
|
- type: map_at_3 |
|
value: 29.17 |
|
- type: map_at_5 |
|
value: 30.714000000000002 |
|
- type: mrr_at_1 |
|
value: 24.746000000000002 |
|
- type: mrr_at_10 |
|
value: 33.517 |
|
- type: mrr_at_100 |
|
value: 34.451 |
|
- type: mrr_at_1000 |
|
value: 34.522000000000006 |
|
- type: mrr_at_3 |
|
value: 31.148999999999997 |
|
- type: mrr_at_5 |
|
value: 32.606 |
|
- type: ndcg_at_1 |
|
value: 24.746000000000002 |
|
- type: ndcg_at_10 |
|
value: 36.553000000000004 |
|
- type: ndcg_at_100 |
|
value: 41.53 |
|
- type: ndcg_at_1000 |
|
value: 43.811 |
|
- type: ndcg_at_3 |
|
value: 31.674000000000003 |
|
- type: ndcg_at_5 |
|
value: 34.241 |
|
- type: precision_at_1 |
|
value: 24.746000000000002 |
|
- type: precision_at_10 |
|
value: 5.684 |
|
- type: precision_at_100 |
|
value: 0.859 |
|
- type: precision_at_1000 |
|
value: 0.109 |
|
- type: precision_at_3 |
|
value: 13.597000000000001 |
|
- type: precision_at_5 |
|
value: 9.672 |
|
- type: recall_at_1 |
|
value: 22.942 |
|
- type: recall_at_10 |
|
value: 49.58 |
|
- type: recall_at_100 |
|
value: 72.614 |
|
- type: recall_at_1000 |
|
value: 89.89200000000001 |
|
- type: recall_at_3 |
|
value: 36.552 |
|
- type: recall_at_5 |
|
value: 42.702 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: BeIR/cqadupstack |
|
name: MTEB CQADupstackMathematicaRetrieval |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 15.345 |
|
- type: map_at_10 |
|
value: 22.428 |
|
- type: map_at_100 |
|
value: 23.756 |
|
- type: map_at_1000 |
|
value: 23.872 |
|
- type: map_at_3 |
|
value: 20.212 |
|
- type: map_at_5 |
|
value: 21.291 |
|
- type: mrr_at_1 |
|
value: 19.279 |
|
- type: mrr_at_10 |
|
value: 27.1 |
|
- type: mrr_at_100 |
|
value: 28.211000000000002 |
|
- type: mrr_at_1000 |
|
value: 28.279 |
|
- type: mrr_at_3 |
|
value: 24.813 |
|
- type: mrr_at_5 |
|
value: 25.889 |
|
- type: ndcg_at_1 |
|
value: 19.279 |
|
- type: ndcg_at_10 |
|
value: 27.36 |
|
- type: ndcg_at_100 |
|
value: 33.499 |
|
- type: ndcg_at_1000 |
|
value: 36.452 |
|
- type: ndcg_at_3 |
|
value: 23.233999999999998 |
|
- type: ndcg_at_5 |
|
value: 24.806 |
|
- type: precision_at_1 |
|
value: 19.279 |
|
- type: precision_at_10 |
|
value: 5.149 |
|
- type: precision_at_100 |
|
value: 0.938 |
|
- type: precision_at_1000 |
|
value: 0.133 |
|
- type: precision_at_3 |
|
value: 11.360000000000001 |
|
- type: precision_at_5 |
|
value: 8.035 |
|
- type: recall_at_1 |
|
value: 15.345 |
|
- type: recall_at_10 |
|
value: 37.974999999999994 |
|
- type: recall_at_100 |
|
value: 64.472 |
|
- type: recall_at_1000 |
|
value: 85.97200000000001 |
|
- type: recall_at_3 |
|
value: 26.203 |
|
- type: recall_at_5 |
|
value: 30.485 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: BeIR/cqadupstack |
|
name: MTEB CQADupstackPhysicsRetrieval |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 26.362000000000002 |
|
- type: map_at_10 |
|
value: 36.406 |
|
- type: map_at_100 |
|
value: 37.726 |
|
- type: map_at_1000 |
|
value: 37.84 |
|
- type: map_at_3 |
|
value: 33.425 |
|
- type: map_at_5 |
|
value: 35.043 |
|
- type: mrr_at_1 |
|
value: 32.146 |
|
- type: mrr_at_10 |
|
value: 41.674 |
|
- type: mrr_at_100 |
|
value: 42.478 |
|
- type: mrr_at_1000 |
|
value: 42.524 |
|
- type: mrr_at_3 |
|
value: 38.948 |
|
- type: mrr_at_5 |
|
value: 40.415 |
|
- type: ndcg_at_1 |
|
value: 32.146 |
|
- type: ndcg_at_10 |
|
value: 42.374 |
|
- type: ndcg_at_100 |
|
value: 47.919 |
|
- type: ndcg_at_1000 |
|
value: 50.013 |
|
- type: ndcg_at_3 |
|
value: 37.29 |
|
- type: ndcg_at_5 |
|
value: 39.531 |
|
- type: precision_at_1 |
|
value: 32.146 |
|
- type: precision_at_10 |
|
value: 7.767 |
|
- type: precision_at_100 |
|
value: 1.236 |
|
- type: precision_at_1000 |
|
value: 0.16 |
|
- type: precision_at_3 |
|
value: 17.965999999999998 |
|
- type: precision_at_5 |
|
value: 12.742999999999999 |
|
- type: recall_at_1 |
|
value: 26.362000000000002 |
|
- type: recall_at_10 |
|
value: 54.98800000000001 |
|
- type: recall_at_100 |
|
value: 78.50200000000001 |
|
- type: recall_at_1000 |
|
value: 92.146 |
|
- type: recall_at_3 |
|
value: 40.486 |
|
- type: recall_at_5 |
|
value: 46.236 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: BeIR/cqadupstack |
|
name: MTEB CQADupstackProgrammersRetrieval |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 24.417 |
|
- type: map_at_10 |
|
value: 33.161 |
|
- type: map_at_100 |
|
value: 34.357 |
|
- type: map_at_1000 |
|
value: 34.473 |
|
- type: map_at_3 |
|
value: 30.245 |
|
- type: map_at_5 |
|
value: 31.541999999999998 |
|
- type: mrr_at_1 |
|
value: 29.909000000000002 |
|
- type: mrr_at_10 |
|
value: 38.211 |
|
- type: mrr_at_100 |
|
value: 39.056999999999995 |
|
- type: mrr_at_1000 |
|
value: 39.114 |
|
- type: mrr_at_3 |
|
value: 35.769 |
|
- type: mrr_at_5 |
|
value: 36.922 |
|
- type: ndcg_at_1 |
|
value: 29.909000000000002 |
|
- type: ndcg_at_10 |
|
value: 38.694 |
|
- type: ndcg_at_100 |
|
value: 44.057 |
|
- type: ndcg_at_1000 |
|
value: 46.6 |
|
- type: ndcg_at_3 |
|
value: 33.822 |
|
- type: ndcg_at_5 |
|
value: 35.454 |
|
- type: precision_at_1 |
|
value: 29.909000000000002 |
|
- type: precision_at_10 |
|
value: 7.180000000000001 |
|
- type: precision_at_100 |
|
value: 1.153 |
|
- type: precision_at_1000 |
|
value: 0.155 |
|
- type: precision_at_3 |
|
value: 16.134 |
|
- type: precision_at_5 |
|
value: 11.256 |
|
- type: recall_at_1 |
|
value: 24.417 |
|
- type: recall_at_10 |
|
value: 50.260000000000005 |
|
- type: recall_at_100 |
|
value: 73.55699999999999 |
|
- type: recall_at_1000 |
|
value: 91.216 |
|
- type: recall_at_3 |
|
value: 35.971 |
|
- type: recall_at_5 |
|
value: 40.793 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: BeIR/cqadupstack |
|
name: MTEB CQADupstackRetrieval |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 24.266916666666663 |
|
- type: map_at_10 |
|
value: 32.75025 |
|
- type: map_at_100 |
|
value: 33.91341666666667 |
|
- type: map_at_1000 |
|
value: 34.031749999999995 |
|
- type: map_at_3 |
|
value: 30.166416666666674 |
|
- type: map_at_5 |
|
value: 31.577000000000005 |
|
- type: mrr_at_1 |
|
value: 28.828166666666664 |
|
- type: mrr_at_10 |
|
value: 36.80991666666667 |
|
- type: mrr_at_100 |
|
value: 37.67075 |
|
- type: mrr_at_1000 |
|
value: 37.733 |
|
- type: mrr_at_3 |
|
value: 34.513416666666664 |
|
- type: mrr_at_5 |
|
value: 35.788 |
|
- type: ndcg_at_1 |
|
value: 28.828166666666664 |
|
- type: ndcg_at_10 |
|
value: 37.796 |
|
- type: ndcg_at_100 |
|
value: 42.94783333333333 |
|
- type: ndcg_at_1000 |
|
value: 45.38908333333333 |
|
- type: ndcg_at_3 |
|
value: 33.374750000000006 |
|
- type: ndcg_at_5 |
|
value: 35.379666666666665 |
|
- type: precision_at_1 |
|
value: 28.828166666666664 |
|
- type: precision_at_10 |
|
value: 6.615749999999999 |
|
- type: precision_at_100 |
|
value: 1.0848333333333333 |
|
- type: precision_at_1000 |
|
value: 0.1484166666666667 |
|
- type: precision_at_3 |
|
value: 15.347833333333332 |
|
- type: precision_at_5 |
|
value: 10.848916666666666 |
|
- type: recall_at_1 |
|
value: 24.266916666666663 |
|
- type: recall_at_10 |
|
value: 48.73458333333333 |
|
- type: recall_at_100 |
|
value: 71.56341666666667 |
|
- type: recall_at_1000 |
|
value: 88.63091666666668 |
|
- type: recall_at_3 |
|
value: 36.31208333333333 |
|
- type: recall_at_5 |
|
value: 41.55633333333333 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: BeIR/cqadupstack |
|
name: MTEB CQADupstackStatsRetrieval |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 23.497 |
|
- type: map_at_10 |
|
value: 30.249 |
|
- type: map_at_100 |
|
value: 30.947000000000003 |
|
- type: map_at_1000 |
|
value: 31.049 |
|
- type: map_at_3 |
|
value: 28.188000000000002 |
|
- type: map_at_5 |
|
value: 29.332 |
|
- type: mrr_at_1 |
|
value: 26.687 |
|
- type: mrr_at_10 |
|
value: 33.182 |
|
- type: mrr_at_100 |
|
value: 33.794999999999995 |
|
- type: mrr_at_1000 |
|
value: 33.873 |
|
- type: mrr_at_3 |
|
value: 31.263 |
|
- type: mrr_at_5 |
|
value: 32.428000000000004 |
|
- type: ndcg_at_1 |
|
value: 26.687 |
|
- type: ndcg_at_10 |
|
value: 34.252 |
|
- type: ndcg_at_100 |
|
value: 38.083 |
|
- type: ndcg_at_1000 |
|
value: 40.682 |
|
- type: ndcg_at_3 |
|
value: 30.464999999999996 |
|
- type: ndcg_at_5 |
|
value: 32.282 |
|
- type: precision_at_1 |
|
value: 26.687 |
|
- type: precision_at_10 |
|
value: 5.2909999999999995 |
|
- type: precision_at_100 |
|
value: 0.788 |
|
- type: precision_at_1000 |
|
value: 0.109 |
|
- type: precision_at_3 |
|
value: 13.037 |
|
- type: precision_at_5 |
|
value: 9.049 |
|
- type: recall_at_1 |
|
value: 23.497 |
|
- type: recall_at_10 |
|
value: 43.813 |
|
- type: recall_at_100 |
|
value: 61.88399999999999 |
|
- type: recall_at_1000 |
|
value: 80.926 |
|
- type: recall_at_3 |
|
value: 33.332 |
|
- type: recall_at_5 |
|
value: 37.862 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: BeIR/cqadupstack |
|
name: MTEB CQADupstackTexRetrieval |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 16.073 |
|
- type: map_at_10 |
|
value: 22.705000000000002 |
|
- type: map_at_100 |
|
value: 23.703 |
|
- type: map_at_1000 |
|
value: 23.833 |
|
- type: map_at_3 |
|
value: 20.593 |
|
- type: map_at_5 |
|
value: 21.7 |
|
- type: mrr_at_1 |
|
value: 19.683 |
|
- type: mrr_at_10 |
|
value: 26.39 |
|
- type: mrr_at_100 |
|
value: 27.264 |
|
- type: mrr_at_1000 |
|
value: 27.349 |
|
- type: mrr_at_3 |
|
value: 24.409 |
|
- type: mrr_at_5 |
|
value: 25.474000000000004 |
|
- type: ndcg_at_1 |
|
value: 19.683 |
|
- type: ndcg_at_10 |
|
value: 27.014 |
|
- type: ndcg_at_100 |
|
value: 31.948 |
|
- type: ndcg_at_1000 |
|
value: 35.125 |
|
- type: ndcg_at_3 |
|
value: 23.225 |
|
- type: ndcg_at_5 |
|
value: 24.866 |
|
- type: precision_at_1 |
|
value: 19.683 |
|
- type: precision_at_10 |
|
value: 4.948 |
|
- type: precision_at_100 |
|
value: 0.876 |
|
- type: precision_at_1000 |
|
value: 0.133 |
|
- type: precision_at_3 |
|
value: 10.943 |
|
- type: precision_at_5 |
|
value: 7.86 |
|
- type: recall_at_1 |
|
value: 16.073 |
|
- type: recall_at_10 |
|
value: 36.283 |
|
- type: recall_at_100 |
|
value: 58.745999999999995 |
|
- type: recall_at_1000 |
|
value: 81.711 |
|
- type: recall_at_3 |
|
value: 25.637 |
|
- type: recall_at_5 |
|
value: 29.919 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: BeIR/cqadupstack |
|
name: MTEB CQADupstackUnixRetrieval |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 25.776 |
|
- type: map_at_10 |
|
value: 33.317 |
|
- type: map_at_100 |
|
value: 34.437 |
|
- type: map_at_1000 |
|
value: 34.54 |
|
- type: map_at_3 |
|
value: 30.706 |
|
- type: map_at_5 |
|
value: 32.202999999999996 |
|
- type: mrr_at_1 |
|
value: 30.224 |
|
- type: mrr_at_10 |
|
value: 37.34 |
|
- type: mrr_at_100 |
|
value: 38.268 |
|
- type: mrr_at_1000 |
|
value: 38.335 |
|
- type: mrr_at_3 |
|
value: 35.075 |
|
- type: mrr_at_5 |
|
value: 36.348 |
|
- type: ndcg_at_1 |
|
value: 30.224 |
|
- type: ndcg_at_10 |
|
value: 38.083 |
|
- type: ndcg_at_100 |
|
value: 43.413000000000004 |
|
- type: ndcg_at_1000 |
|
value: 45.856 |
|
- type: ndcg_at_3 |
|
value: 33.437 |
|
- type: ndcg_at_5 |
|
value: 35.661 |
|
- type: precision_at_1 |
|
value: 30.224 |
|
- type: precision_at_10 |
|
value: 6.1850000000000005 |
|
- type: precision_at_100 |
|
value: 1.0030000000000001 |
|
- type: precision_at_1000 |
|
value: 0.132 |
|
- type: precision_at_3 |
|
value: 14.646 |
|
- type: precision_at_5 |
|
value: 10.428999999999998 |
|
- type: recall_at_1 |
|
value: 25.776 |
|
- type: recall_at_10 |
|
value: 48.787000000000006 |
|
- type: recall_at_100 |
|
value: 72.04899999999999 |
|
- type: recall_at_1000 |
|
value: 89.339 |
|
- type: recall_at_3 |
|
value: 36.192 |
|
- type: recall_at_5 |
|
value: 41.665 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: BeIR/cqadupstack |
|
name: MTEB CQADupstackWebmastersRetrieval |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 23.156 |
|
- type: map_at_10 |
|
value: 30.886000000000003 |
|
- type: map_at_100 |
|
value: 32.551 |
|
- type: map_at_1000 |
|
value: 32.769 |
|
- type: map_at_3 |
|
value: 28.584 |
|
- type: map_at_5 |
|
value: 29.959999999999997 |
|
- type: mrr_at_1 |
|
value: 28.260999999999996 |
|
- type: mrr_at_10 |
|
value: 35.555 |
|
- type: mrr_at_100 |
|
value: 36.687 |
|
- type: mrr_at_1000 |
|
value: 36.742999999999995 |
|
- type: mrr_at_3 |
|
value: 33.531 |
|
- type: mrr_at_5 |
|
value: 34.717 |
|
- type: ndcg_at_1 |
|
value: 28.260999999999996 |
|
- type: ndcg_at_10 |
|
value: 36.036 |
|
- type: ndcg_at_100 |
|
value: 42.675000000000004 |
|
- type: ndcg_at_1000 |
|
value: 45.303 |
|
- type: ndcg_at_3 |
|
value: 32.449 |
|
- type: ndcg_at_5 |
|
value: 34.293 |
|
- type: precision_at_1 |
|
value: 28.260999999999996 |
|
- type: precision_at_10 |
|
value: 6.837999999999999 |
|
- type: precision_at_100 |
|
value: 1.4569999999999999 |
|
- type: precision_at_1000 |
|
value: 0.23500000000000001 |
|
- type: precision_at_3 |
|
value: 15.217 |
|
- type: precision_at_5 |
|
value: 11.028 |
|
- type: recall_at_1 |
|
value: 23.156 |
|
- type: recall_at_10 |
|
value: 45.251999999999995 |
|
- type: recall_at_100 |
|
value: 75.339 |
|
- type: recall_at_1000 |
|
value: 91.56 |
|
- type: recall_at_3 |
|
value: 34.701 |
|
- type: recall_at_5 |
|
value: 39.922999999999995 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: BeIR/cqadupstack |
|
name: MTEB CQADupstackWordpressRetrieval |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 19.846 |
|
- type: map_at_10 |
|
value: 26.367 |
|
- type: map_at_100 |
|
value: 27.439999999999998 |
|
- type: map_at_1000 |
|
value: 27.552 |
|
- type: map_at_3 |
|
value: 24.006 |
|
- type: map_at_5 |
|
value: 25.230999999999998 |
|
- type: mrr_at_1 |
|
value: 21.257 |
|
- type: mrr_at_10 |
|
value: 28.071 |
|
- type: mrr_at_100 |
|
value: 29.037000000000003 |
|
- type: mrr_at_1000 |
|
value: 29.119 |
|
- type: mrr_at_3 |
|
value: 25.692999999999998 |
|
- type: mrr_at_5 |
|
value: 27.006000000000004 |
|
- type: ndcg_at_1 |
|
value: 21.257 |
|
- type: ndcg_at_10 |
|
value: 30.586000000000002 |
|
- type: ndcg_at_100 |
|
value: 35.949 |
|
- type: ndcg_at_1000 |
|
value: 38.728 |
|
- type: ndcg_at_3 |
|
value: 25.862000000000002 |
|
- type: ndcg_at_5 |
|
value: 27.967 |
|
- type: precision_at_1 |
|
value: 21.257 |
|
- type: precision_at_10 |
|
value: 4.861 |
|
- type: precision_at_100 |
|
value: 0.8130000000000001 |
|
- type: precision_at_1000 |
|
value: 0.116 |
|
- type: precision_at_3 |
|
value: 10.906 |
|
- type: precision_at_5 |
|
value: 7.763000000000001 |
|
- type: recall_at_1 |
|
value: 19.846 |
|
- type: recall_at_10 |
|
value: 41.805 |
|
- type: recall_at_100 |
|
value: 66.89699999999999 |
|
- type: recall_at_1000 |
|
value: 87.401 |
|
- type: recall_at_3 |
|
value: 29.261 |
|
- type: recall_at_5 |
|
value: 34.227000000000004 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: climate-fever |
|
name: MTEB ClimateFEVER |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 10.333 |
|
- type: map_at_10 |
|
value: 17.14 |
|
- type: map_at_100 |
|
value: 18.878 |
|
- type: map_at_1000 |
|
value: 19.067 |
|
- type: map_at_3 |
|
value: 14.123 |
|
- type: map_at_5 |
|
value: 15.699 |
|
- type: mrr_at_1 |
|
value: 23.192 |
|
- type: mrr_at_10 |
|
value: 33.553 |
|
- type: mrr_at_100 |
|
value: 34.553 |
|
- type: mrr_at_1000 |
|
value: 34.603 |
|
- type: mrr_at_3 |
|
value: 29.848000000000003 |
|
- type: mrr_at_5 |
|
value: 32.18 |
|
- type: ndcg_at_1 |
|
value: 23.192 |
|
- type: ndcg_at_10 |
|
value: 24.707 |
|
- type: ndcg_at_100 |
|
value: 31.701 |
|
- type: ndcg_at_1000 |
|
value: 35.260999999999996 |
|
- type: ndcg_at_3 |
|
value: 19.492 |
|
- type: ndcg_at_5 |
|
value: 21.543 |
|
- type: precision_at_1 |
|
value: 23.192 |
|
- type: precision_at_10 |
|
value: 7.824000000000001 |
|
- type: precision_at_100 |
|
value: 1.52 |
|
- type: precision_at_1000 |
|
value: 0.218 |
|
- type: precision_at_3 |
|
value: 14.180000000000001 |
|
- type: precision_at_5 |
|
value: 11.530999999999999 |
|
- type: recall_at_1 |
|
value: 10.333 |
|
- type: recall_at_10 |
|
value: 30.142999999999997 |
|
- type: recall_at_100 |
|
value: 54.298 |
|
- type: recall_at_1000 |
|
value: 74.337 |
|
- type: recall_at_3 |
|
value: 17.602999999999998 |
|
- type: recall_at_5 |
|
value: 22.938 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: dbpedia-entity |
|
name: MTEB DBPedia |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 8.03 |
|
- type: map_at_10 |
|
value: 17.345 |
|
- type: map_at_100 |
|
value: 23.462 |
|
- type: map_at_1000 |
|
value: 24.77 |
|
- type: map_at_3 |
|
value: 12.714 |
|
- type: map_at_5 |
|
value: 14.722 |
|
- type: mrr_at_1 |
|
value: 61.0 |
|
- type: mrr_at_10 |
|
value: 69.245 |
|
- type: mrr_at_100 |
|
value: 69.715 |
|
- type: mrr_at_1000 |
|
value: 69.719 |
|
- type: mrr_at_3 |
|
value: 67.583 |
|
- type: mrr_at_5 |
|
value: 68.521 |
|
- type: ndcg_at_1 |
|
value: 47.625 |
|
- type: ndcg_at_10 |
|
value: 35.973 |
|
- type: ndcg_at_100 |
|
value: 39.875 |
|
- type: ndcg_at_1000 |
|
value: 46.922000000000004 |
|
- type: ndcg_at_3 |
|
value: 40.574 |
|
- type: ndcg_at_5 |
|
value: 38.18 |
|
- type: precision_at_1 |
|
value: 61.0 |
|
- type: precision_at_10 |
|
value: 29.049999999999997 |
|
- type: precision_at_100 |
|
value: 8.828 |
|
- type: precision_at_1000 |
|
value: 1.8290000000000002 |
|
- type: precision_at_3 |
|
value: 45.333 |
|
- type: precision_at_5 |
|
value: 37.9 |
|
- type: recall_at_1 |
|
value: 8.03 |
|
- type: recall_at_10 |
|
value: 22.334 |
|
- type: recall_at_100 |
|
value: 45.919 |
|
- type: recall_at_1000 |
|
value: 68.822 |
|
- type: recall_at_3 |
|
value: 14.038999999999998 |
|
- type: recall_at_5 |
|
value: 17.118 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/emotion |
|
name: MTEB EmotionClassification |
|
config: default |
|
split: test |
|
revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37 |
|
metrics: |
|
- type: accuracy |
|
value: 44.714999999999996 |
|
- type: f1 |
|
value: 39.83929362259356 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: fever |
|
name: MTEB FEVER |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 52.242999999999995 |
|
- type: map_at_10 |
|
value: 64.087 |
|
- type: map_at_100 |
|
value: 64.549 |
|
- type: map_at_1000 |
|
value: 64.567 |
|
- type: map_at_3 |
|
value: 61.667 |
|
- type: map_at_5 |
|
value: 63.266 |
|
- type: mrr_at_1 |
|
value: 56.271 |
|
- type: mrr_at_10 |
|
value: 68.146 |
|
- type: mrr_at_100 |
|
value: 68.524 |
|
- type: mrr_at_1000 |
|
value: 68.53200000000001 |
|
- type: mrr_at_3 |
|
value: 65.869 |
|
- type: mrr_at_5 |
|
value: 67.37100000000001 |
|
- type: ndcg_at_1 |
|
value: 56.271 |
|
- type: ndcg_at_10 |
|
value: 70.109 |
|
- type: ndcg_at_100 |
|
value: 72.09 |
|
- type: ndcg_at_1000 |
|
value: 72.479 |
|
- type: ndcg_at_3 |
|
value: 65.559 |
|
- type: ndcg_at_5 |
|
value: 68.242 |
|
- type: precision_at_1 |
|
value: 56.271 |
|
- type: precision_at_10 |
|
value: 9.286999999999999 |
|
- type: precision_at_100 |
|
value: 1.039 |
|
- type: precision_at_1000 |
|
value: 0.109 |
|
- type: precision_at_3 |
|
value: 26.308 |
|
- type: precision_at_5 |
|
value: 17.291 |
|
- type: recall_at_1 |
|
value: 52.242999999999995 |
|
- type: recall_at_10 |
|
value: 84.71 |
|
- type: recall_at_100 |
|
value: 93.309 |
|
- type: recall_at_1000 |
|
value: 96.013 |
|
- type: recall_at_3 |
|
value: 72.554 |
|
- type: recall_at_5 |
|
value: 79.069 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: fiqa |
|
name: MTEB FiQA2018 |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 14.346 |
|
- type: map_at_10 |
|
value: 24.552 |
|
- type: map_at_100 |
|
value: 26.161 |
|
- type: map_at_1000 |
|
value: 26.345000000000002 |
|
- type: map_at_3 |
|
value: 21.208 |
|
- type: map_at_5 |
|
value: 22.959 |
|
- type: mrr_at_1 |
|
value: 29.166999999999998 |
|
- type: mrr_at_10 |
|
value: 38.182 |
|
- type: mrr_at_100 |
|
value: 39.22 |
|
- type: mrr_at_1000 |
|
value: 39.263 |
|
- type: mrr_at_3 |
|
value: 35.983 |
|
- type: mrr_at_5 |
|
value: 37.14 |
|
- type: ndcg_at_1 |
|
value: 29.166999999999998 |
|
- type: ndcg_at_10 |
|
value: 31.421 |
|
- type: ndcg_at_100 |
|
value: 38.129999999999995 |
|
- type: ndcg_at_1000 |
|
value: 41.569 |
|
- type: ndcg_at_3 |
|
value: 28.172000000000004 |
|
- type: ndcg_at_5 |
|
value: 29.029 |
|
- type: precision_at_1 |
|
value: 29.166999999999998 |
|
- type: precision_at_10 |
|
value: 8.997 |
|
- type: precision_at_100 |
|
value: 1.5709999999999997 |
|
- type: precision_at_1000 |
|
value: 0.22 |
|
- type: precision_at_3 |
|
value: 19.187 |
|
- type: precision_at_5 |
|
value: 13.980999999999998 |
|
- type: recall_at_1 |
|
value: 14.346 |
|
- type: recall_at_10 |
|
value: 37.963 |
|
- type: recall_at_100 |
|
value: 63.43299999999999 |
|
- type: recall_at_1000 |
|
value: 84.057 |
|
- type: recall_at_3 |
|
value: 26.119999999999997 |
|
- type: recall_at_5 |
|
value: 30.988 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: hotpotqa |
|
name: MTEB HotpotQA |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 33.059 |
|
- type: map_at_10 |
|
value: 46.421 |
|
- type: map_at_100 |
|
value: 47.323 |
|
- type: map_at_1000 |
|
value: 47.403 |
|
- type: map_at_3 |
|
value: 43.553999999999995 |
|
- type: map_at_5 |
|
value: 45.283 |
|
- type: mrr_at_1 |
|
value: 66.117 |
|
- type: mrr_at_10 |
|
value: 73.10900000000001 |
|
- type: mrr_at_100 |
|
value: 73.444 |
|
- type: mrr_at_1000 |
|
value: 73.46000000000001 |
|
- type: mrr_at_3 |
|
value: 71.70400000000001 |
|
- type: mrr_at_5 |
|
value: 72.58099999999999 |
|
- type: ndcg_at_1 |
|
value: 66.117 |
|
- type: ndcg_at_10 |
|
value: 55.696999999999996 |
|
- type: ndcg_at_100 |
|
value: 59.167 |
|
- type: ndcg_at_1000 |
|
value: 60.809000000000005 |
|
- type: ndcg_at_3 |
|
value: 51.243 |
|
- type: ndcg_at_5 |
|
value: 53.627 |
|
- type: precision_at_1 |
|
value: 66.117 |
|
- type: precision_at_10 |
|
value: 11.538 |
|
- type: precision_at_100 |
|
value: 1.429 |
|
- type: precision_at_1000 |
|
value: 0.165 |
|
- type: precision_at_3 |
|
value: 31.861 |
|
- type: precision_at_5 |
|
value: 20.997 |
|
- type: recall_at_1 |
|
value: 33.059 |
|
- type: recall_at_10 |
|
value: 57.691 |
|
- type: recall_at_100 |
|
value: 71.458 |
|
- type: recall_at_1000 |
|
value: 82.35 |
|
- type: recall_at_3 |
|
value: 47.792 |
|
- type: recall_at_5 |
|
value: 52.492000000000004 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/imdb |
|
name: MTEB ImdbClassification |
|
config: default |
|
split: test |
|
revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7 |
|
metrics: |
|
- type: accuracy |
|
value: 80.544 |
|
- type: ap |
|
value: 74.69592367984956 |
|
- type: f1 |
|
value: 80.51138138449883 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: msmarco |
|
name: MTEB MSMARCO |
|
config: default |
|
split: dev |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 17.095 |
|
- type: map_at_10 |
|
value: 28.038999999999998 |
|
- type: map_at_100 |
|
value: 29.246 |
|
- type: map_at_1000 |
|
value: 29.311 |
|
- type: map_at_3 |
|
value: 24.253 |
|
- type: map_at_5 |
|
value: 26.442 |
|
- type: mrr_at_1 |
|
value: 17.535999999999998 |
|
- type: mrr_at_10 |
|
value: 28.53 |
|
- type: mrr_at_100 |
|
value: 29.697000000000003 |
|
- type: mrr_at_1000 |
|
value: 29.755 |
|
- type: mrr_at_3 |
|
value: 24.779999999999998 |
|
- type: mrr_at_5 |
|
value: 26.942 |
|
- type: ndcg_at_1 |
|
value: 17.549999999999997 |
|
- type: ndcg_at_10 |
|
value: 34.514 |
|
- type: ndcg_at_100 |
|
value: 40.497 |
|
- type: ndcg_at_1000 |
|
value: 42.17 |
|
- type: ndcg_at_3 |
|
value: 26.764 |
|
- type: ndcg_at_5 |
|
value: 30.678 |
|
- type: precision_at_1 |
|
value: 17.549999999999997 |
|
- type: precision_at_10 |
|
value: 5.692 |
|
- type: precision_at_100 |
|
value: 0.8699999999999999 |
|
- type: precision_at_1000 |
|
value: 0.101 |
|
- type: precision_at_3 |
|
value: 11.562 |
|
- type: precision_at_5 |
|
value: 8.917 |
|
- type: recall_at_1 |
|
value: 17.095 |
|
- type: recall_at_10 |
|
value: 54.642 |
|
- type: recall_at_100 |
|
value: 82.652 |
|
- type: recall_at_1000 |
|
value: 95.555 |
|
- type: recall_at_3 |
|
value: 33.504 |
|
- type: recall_at_5 |
|
value: 42.925000000000004 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/mtop_domain |
|
name: MTEB MTOPDomainClassification (en) |
|
config: en |
|
split: test |
|
revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf |
|
metrics: |
|
- type: accuracy |
|
value: 91.75558595531236 |
|
- type: f1 |
|
value: 91.25979279648296 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/mtop_intent |
|
name: MTEB MTOPIntentClassification (en) |
|
config: en |
|
split: test |
|
revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba |
|
metrics: |
|
- type: accuracy |
|
value: 69.90424076607387 |
|
- type: f1 |
|
value: 52.067408707562244 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/amazon_massive_intent |
|
name: MTEB MassiveIntentClassification (en) |
|
config: en |
|
split: test |
|
revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 |
|
metrics: |
|
- type: accuracy |
|
value: 70.13449899125757 |
|
- type: f1 |
|
value: 67.62456762910598 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/amazon_massive_scenario |
|
name: MTEB MassiveScenarioClassification (en) |
|
config: en |
|
split: test |
|
revision: 7d571f92784cd94a019292a1f45445077d0ef634 |
|
metrics: |
|
- type: accuracy |
|
value: 74.862138533961 |
|
- type: f1 |
|
value: 74.66457222091381 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: mteb/medrxiv-clustering-p2p |
|
name: MTEB MedrxivClusteringP2P |
|
config: default |
|
split: test |
|
revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73 |
|
metrics: |
|
- type: v_measure |
|
value: 34.10761942610792 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: mteb/medrxiv-clustering-s2s |
|
name: MTEB MedrxivClusteringS2S |
|
config: default |
|
split: test |
|
revision: 35191c8c0dca72d8ff3efcd72aa802307d469663 |
|
metrics: |
|
- type: v_measure |
|
value: 31.673172170578408 |
|
- task: |
|
type: Reranking |
|
dataset: |
|
type: mteb/mind_small |
|
name: MTEB MindSmallReranking |
|
config: default |
|
split: test |
|
revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69 |
|
metrics: |
|
- type: map |
|
value: 32.058704977250315 |
|
- type: mrr |
|
value: 33.24327760839221 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: nfcorpus |
|
name: MTEB NFCorpus |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 5.163 |
|
- type: map_at_10 |
|
value: 11.652999999999999 |
|
- type: map_at_100 |
|
value: 14.849 |
|
- type: map_at_1000 |
|
value: 16.253999999999998 |
|
- type: map_at_3 |
|
value: 8.616999999999999 |
|
- type: map_at_5 |
|
value: 10.100000000000001 |
|
- type: mrr_at_1 |
|
value: 44.272 |
|
- type: mrr_at_10 |
|
value: 52.25 |
|
- type: mrr_at_100 |
|
value: 52.761 |
|
- type: mrr_at_1000 |
|
value: 52.811 |
|
- type: mrr_at_3 |
|
value: 50.31 |
|
- type: mrr_at_5 |
|
value: 51.347 |
|
- type: ndcg_at_1 |
|
value: 42.105 |
|
- type: ndcg_at_10 |
|
value: 32.044 |
|
- type: ndcg_at_100 |
|
value: 29.763 |
|
- type: ndcg_at_1000 |
|
value: 38.585 |
|
- type: ndcg_at_3 |
|
value: 36.868 |
|
- type: ndcg_at_5 |
|
value: 35.154999999999994 |
|
- type: precision_at_1 |
|
value: 43.653 |
|
- type: precision_at_10 |
|
value: 23.622 |
|
- type: precision_at_100 |
|
value: 7.7490000000000006 |
|
- type: precision_at_1000 |
|
value: 2.054 |
|
- type: precision_at_3 |
|
value: 34.262 |
|
- type: precision_at_5 |
|
value: 30.154999999999998 |
|
- type: recall_at_1 |
|
value: 5.163 |
|
- type: recall_at_10 |
|
value: 15.478 |
|
- type: recall_at_100 |
|
value: 30.424 |
|
- type: recall_at_1000 |
|
value: 62.67 |
|
- type: recall_at_3 |
|
value: 9.615 |
|
- type: recall_at_5 |
|
value: 12.369 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: nq |
|
name: MTEB NQ |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 21.618000000000002 |
|
- type: map_at_10 |
|
value: 35.465 |
|
- type: map_at_100 |
|
value: 36.712 |
|
- type: map_at_1000 |
|
value: 36.757 |
|
- type: map_at_3 |
|
value: 31.189 |
|
- type: map_at_5 |
|
value: 33.537 |
|
- type: mrr_at_1 |
|
value: 24.305 |
|
- type: mrr_at_10 |
|
value: 37.653 |
|
- type: mrr_at_100 |
|
value: 38.662 |
|
- type: mrr_at_1000 |
|
value: 38.694 |
|
- type: mrr_at_3 |
|
value: 33.889 |
|
- type: mrr_at_5 |
|
value: 35.979 |
|
- type: ndcg_at_1 |
|
value: 24.305 |
|
- type: ndcg_at_10 |
|
value: 43.028 |
|
- type: ndcg_at_100 |
|
value: 48.653999999999996 |
|
- type: ndcg_at_1000 |
|
value: 49.733 |
|
- type: ndcg_at_3 |
|
value: 34.768 |
|
- type: ndcg_at_5 |
|
value: 38.753 |
|
- type: precision_at_1 |
|
value: 24.305 |
|
- type: precision_at_10 |
|
value: 7.59 |
|
- type: precision_at_100 |
|
value: 1.076 |
|
- type: precision_at_1000 |
|
value: 0.11800000000000001 |
|
- type: precision_at_3 |
|
value: 16.271 |
|
- type: precision_at_5 |
|
value: 12.068 |
|
- type: recall_at_1 |
|
value: 21.618000000000002 |
|
- type: recall_at_10 |
|
value: 63.977 |
|
- type: recall_at_100 |
|
value: 89.03999999999999 |
|
- type: recall_at_1000 |
|
value: 97.10600000000001 |
|
- type: recall_at_3 |
|
value: 42.422 |
|
- type: recall_at_5 |
|
value: 51.629000000000005 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: quora |
|
name: MTEB QuoraRetrieval |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 69.405 |
|
- type: map_at_10 |
|
value: 83.05 |
|
- type: map_at_100 |
|
value: 83.684 |
|
- type: map_at_1000 |
|
value: 83.70400000000001 |
|
- type: map_at_3 |
|
value: 80.08800000000001 |
|
- type: map_at_5 |
|
value: 81.937 |
|
- type: mrr_at_1 |
|
value: 79.85 |
|
- type: mrr_at_10 |
|
value: 86.369 |
|
- type: mrr_at_100 |
|
value: 86.48599999999999 |
|
- type: mrr_at_1000 |
|
value: 86.48700000000001 |
|
- type: mrr_at_3 |
|
value: 85.315 |
|
- type: mrr_at_5 |
|
value: 86.044 |
|
- type: ndcg_at_1 |
|
value: 79.86999999999999 |
|
- type: ndcg_at_10 |
|
value: 87.04499999999999 |
|
- type: ndcg_at_100 |
|
value: 88.373 |
|
- type: ndcg_at_1000 |
|
value: 88.531 |
|
- type: ndcg_at_3 |
|
value: 84.04 |
|
- type: ndcg_at_5 |
|
value: 85.684 |
|
- type: precision_at_1 |
|
value: 79.86999999999999 |
|
- type: precision_at_10 |
|
value: 13.183 |
|
- type: precision_at_100 |
|
value: 1.51 |
|
- type: precision_at_1000 |
|
value: 0.156 |
|
- type: precision_at_3 |
|
value: 36.67 |
|
- type: precision_at_5 |
|
value: 24.12 |
|
- type: recall_at_1 |
|
value: 69.405 |
|
- type: recall_at_10 |
|
value: 94.634 |
|
- type: recall_at_100 |
|
value: 99.214 |
|
- type: recall_at_1000 |
|
value: 99.958 |
|
- type: recall_at_3 |
|
value: 85.992 |
|
- type: recall_at_5 |
|
value: 90.656 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: mteb/reddit-clustering |
|
name: MTEB RedditClustering |
|
config: default |
|
split: test |
|
revision: 24640382cdbf8abc73003fb0fa6d111a705499eb |
|
metrics: |
|
- type: v_measure |
|
value: 50.191676323145465 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: mteb/reddit-clustering-p2p |
|
name: MTEB RedditClusteringP2P |
|
config: default |
|
split: test |
|
revision: 282350215ef01743dc01b456c7f5241fa8937f16 |
|
metrics: |
|
- type: v_measure |
|
value: 56.4874020363744 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: scidocs |
|
name: MTEB SCIDOCS |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 4.228 |
|
- type: map_at_10 |
|
value: 11.245 |
|
- type: map_at_100 |
|
value: 13.353000000000002 |
|
- type: map_at_1000 |
|
value: 13.665 |
|
- type: map_at_3 |
|
value: 7.779999999999999 |
|
- type: map_at_5 |
|
value: 9.405 |
|
- type: mrr_at_1 |
|
value: 20.9 |
|
- type: mrr_at_10 |
|
value: 31.657999999999998 |
|
- type: mrr_at_100 |
|
value: 32.769999999999996 |
|
- type: mrr_at_1000 |
|
value: 32.833 |
|
- type: mrr_at_3 |
|
value: 28.333000000000002 |
|
- type: mrr_at_5 |
|
value: 30.043 |
|
- type: ndcg_at_1 |
|
value: 20.9 |
|
- type: ndcg_at_10 |
|
value: 19.073 |
|
- type: ndcg_at_100 |
|
value: 27.055 |
|
- type: ndcg_at_1000 |
|
value: 32.641 |
|
- type: ndcg_at_3 |
|
value: 17.483999999999998 |
|
- type: ndcg_at_5 |
|
value: 15.42 |
|
- type: precision_at_1 |
|
value: 20.9 |
|
- type: precision_at_10 |
|
value: 10.17 |
|
- type: precision_at_100 |
|
value: 2.162 |
|
- type: precision_at_1000 |
|
value: 0.35100000000000003 |
|
- type: precision_at_3 |
|
value: 16.467000000000002 |
|
- type: precision_at_5 |
|
value: 13.68 |
|
- type: recall_at_1 |
|
value: 4.228 |
|
- type: recall_at_10 |
|
value: 20.573 |
|
- type: recall_at_100 |
|
value: 43.887 |
|
- type: recall_at_1000 |
|
value: 71.22 |
|
- type: recall_at_3 |
|
value: 10.023 |
|
- type: recall_at_5 |
|
value: 13.873 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: mteb/sickr-sts |
|
name: MTEB SICK-R |
|
config: default |
|
split: test |
|
revision: a6ea5a8cab320b040a23452cc28066d9beae2cee |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 82.77965135067481 |
|
- type: cos_sim_spearman |
|
value: 75.85121335808076 |
|
- type: euclidean_pearson |
|
value: 80.09115175262697 |
|
- type: euclidean_spearman |
|
value: 75.72249155647123 |
|
- type: manhattan_pearson |
|
value: 79.89723577351782 |
|
- type: manhattan_spearman |
|
value: 75.49855259442387 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: mteb/sts12-sts |
|
name: MTEB STS12 |
|
config: default |
|
split: test |
|
revision: a0d554a64d88156834ff5ae9920b964011b16384 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 80.46084116030949 |
|
- type: cos_sim_spearman |
|
value: 72.57579204392951 |
|
- type: euclidean_pearson |
|
value: 76.39020830763684 |
|
- type: euclidean_spearman |
|
value: 72.3718627025895 |
|
- type: manhattan_pearson |
|
value: 76.6148833027359 |
|
- type: manhattan_spearman |
|
value: 72.57570008442319 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: mteb/sts13-sts |
|
name: MTEB STS13 |
|
config: default |
|
split: test |
|
revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 80.43678068337017 |
|
- type: cos_sim_spearman |
|
value: 82.38941154076062 |
|
- type: euclidean_pearson |
|
value: 81.59260573633661 |
|
- type: euclidean_spearman |
|
value: 82.31144262574114 |
|
- type: manhattan_pearson |
|
value: 81.43266909137056 |
|
- type: manhattan_spearman |
|
value: 82.14704293004861 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: mteb/sts14-sts |
|
name: MTEB STS14 |
|
config: default |
|
split: test |
|
revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 80.73713431763163 |
|
- type: cos_sim_spearman |
|
value: 77.97860512809388 |
|
- type: euclidean_pearson |
|
value: 80.35755041527027 |
|
- type: euclidean_spearman |
|
value: 78.021703511412 |
|
- type: manhattan_pearson |
|
value: 80.24440317109162 |
|
- type: manhattan_spearman |
|
value: 77.93165415697575 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: mteb/sts15-sts |
|
name: MTEB STS15 |
|
config: default |
|
split: test |
|
revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 85.15111852351204 |
|
- type: cos_sim_spearman |
|
value: 86.54032447238258 |
|
- type: euclidean_pearson |
|
value: 86.14157021537433 |
|
- type: euclidean_spearman |
|
value: 86.67537291929713 |
|
- type: manhattan_pearson |
|
value: 86.081041854808 |
|
- type: manhattan_spearman |
|
value: 86.61561701560558 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: mteb/sts16-sts |
|
name: MTEB STS16 |
|
config: default |
|
split: test |
|
revision: 4d8694f8f0e0100860b497b999b3dbed754a0513 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 81.34532445104026 |
|
- type: cos_sim_spearman |
|
value: 83.31325001474116 |
|
- type: euclidean_pearson |
|
value: 82.81892375201032 |
|
- type: euclidean_spearman |
|
value: 83.4521695148055 |
|
- type: manhattan_pearson |
|
value: 82.72503790526163 |
|
- type: manhattan_spearman |
|
value: 83.37833652941349 |
|
- 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: 87.25463453839801 |
|
- type: cos_sim_spearman |
|
value: 88.27655263515948 |
|
- type: euclidean_pearson |
|
value: 88.0248334411439 |
|
- type: euclidean_spearman |
|
value: 88.18141448876868 |
|
- type: manhattan_pearson |
|
value: 87.8080451127279 |
|
- type: manhattan_spearman |
|
value: 88.01028114423058 |
|
- 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: 63.57551045355218 |
|
- type: cos_sim_spearman |
|
value: 66.67614095126629 |
|
- type: euclidean_pearson |
|
value: 66.0787243112528 |
|
- type: euclidean_spearman |
|
value: 66.83660560636939 |
|
- type: manhattan_pearson |
|
value: 66.74684019662031 |
|
- type: manhattan_spearman |
|
value: 67.11761598074368 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: mteb/stsbenchmark-sts |
|
name: MTEB STSBenchmark |
|
config: default |
|
split: test |
|
revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 83.70881496766829 |
|
- type: cos_sim_spearman |
|
value: 84.37803542941634 |
|
- type: euclidean_pearson |
|
value: 84.84501245857096 |
|
- type: euclidean_spearman |
|
value: 84.47088079741476 |
|
- type: manhattan_pearson |
|
value: 84.77244090794765 |
|
- type: manhattan_spearman |
|
value: 84.43307343706205 |
|
- task: |
|
type: Reranking |
|
dataset: |
|
type: mteb/scidocs-reranking |
|
name: MTEB SciDocsRR |
|
config: default |
|
split: test |
|
revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab |
|
metrics: |
|
- type: map |
|
value: 81.53946254759089 |
|
- type: mrr |
|
value: 94.68259953554072 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: scifact |
|
name: MTEB SciFact |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 51.817 |
|
- type: map_at_10 |
|
value: 62.339999999999996 |
|
- type: map_at_100 |
|
value: 62.88 |
|
- type: map_at_1000 |
|
value: 62.909000000000006 |
|
- type: map_at_3 |
|
value: 59.004 |
|
- type: map_at_5 |
|
value: 60.906000000000006 |
|
- type: mrr_at_1 |
|
value: 54.333 |
|
- type: mrr_at_10 |
|
value: 63.649 |
|
- type: mrr_at_100 |
|
value: 64.01 |
|
- type: mrr_at_1000 |
|
value: 64.039 |
|
- type: mrr_at_3 |
|
value: 61.056 |
|
- type: mrr_at_5 |
|
value: 62.639 |
|
- type: ndcg_at_1 |
|
value: 54.333 |
|
- type: ndcg_at_10 |
|
value: 67.509 |
|
- type: ndcg_at_100 |
|
value: 69.69999999999999 |
|
- type: ndcg_at_1000 |
|
value: 70.613 |
|
- type: ndcg_at_3 |
|
value: 61.729 |
|
- type: ndcg_at_5 |
|
value: 64.696 |
|
- type: precision_at_1 |
|
value: 54.333 |
|
- type: precision_at_10 |
|
value: 9.2 |
|
- type: precision_at_100 |
|
value: 1.043 |
|
- type: precision_at_1000 |
|
value: 0.11199999999999999 |
|
- type: precision_at_3 |
|
value: 24.0 |
|
- type: precision_at_5 |
|
value: 16.2 |
|
- type: recall_at_1 |
|
value: 51.817 |
|
- type: recall_at_10 |
|
value: 82.056 |
|
- type: recall_at_100 |
|
value: 91.667 |
|
- type: recall_at_1000 |
|
value: 99.0 |
|
- type: recall_at_3 |
|
value: 66.717 |
|
- type: recall_at_5 |
|
value: 74.17200000000001 |
|
- task: |
|
type: PairClassification |
|
dataset: |
|
type: mteb/sprintduplicatequestions-pairclassification |
|
name: MTEB SprintDuplicateQuestions |
|
config: default |
|
split: test |
|
revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46 |
|
metrics: |
|
- type: cos_sim_accuracy |
|
value: 99.82475247524752 |
|
- type: cos_sim_ap |
|
value: 95.4781199603258 |
|
- type: cos_sim_f1 |
|
value: 91.16186693147964 |
|
- type: cos_sim_precision |
|
value: 90.53254437869822 |
|
- type: cos_sim_recall |
|
value: 91.8 |
|
- type: dot_accuracy |
|
value: 99.75049504950495 |
|
- type: dot_ap |
|
value: 93.05183539809457 |
|
- type: dot_f1 |
|
value: 87.31117824773412 |
|
- type: dot_precision |
|
value: 87.93103448275862 |
|
- type: dot_recall |
|
value: 86.7 |
|
- type: euclidean_accuracy |
|
value: 99.82475247524752 |
|
- type: euclidean_ap |
|
value: 95.38547978154382 |
|
- type: euclidean_f1 |
|
value: 91.16325511732403 |
|
- type: euclidean_precision |
|
value: 91.02691924227318 |
|
- type: euclidean_recall |
|
value: 91.3 |
|
- type: manhattan_accuracy |
|
value: 99.82574257425742 |
|
- type: manhattan_ap |
|
value: 95.47237521890308 |
|
- type: manhattan_f1 |
|
value: 91.27849355797821 |
|
- type: manhattan_precision |
|
value: 90.47151277013754 |
|
- type: manhattan_recall |
|
value: 92.10000000000001 |
|
- type: max_accuracy |
|
value: 99.82574257425742 |
|
- type: max_ap |
|
value: 95.4781199603258 |
|
- type: max_f1 |
|
value: 91.27849355797821 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: mteb/stackexchange-clustering |
|
name: MTEB StackExchangeClustering |
|
config: default |
|
split: test |
|
revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259 |
|
metrics: |
|
- type: v_measure |
|
value: 57.542169376331245 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: mteb/stackexchange-clustering-p2p |
|
name: MTEB StackExchangeClusteringP2P |
|
config: default |
|
split: test |
|
revision: 815ca46b2622cec33ccafc3735d572c266efdb44 |
|
metrics: |
|
- type: v_measure |
|
value: 35.74399302634387 |
|
- task: |
|
type: Reranking |
|
dataset: |
|
type: mteb/stackoverflowdupquestions-reranking |
|
name: MTEB StackOverflowDupQuestions |
|
config: default |
|
split: test |
|
revision: e185fbe320c72810689fc5848eb6114e1ef5ec69 |
|
metrics: |
|
- type: map |
|
value: 49.65076347632749 |
|
- type: mrr |
|
value: 50.418099057804945 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: trec-covid |
|
name: MTEB TRECCOVID |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 0.208 |
|
- type: map_at_10 |
|
value: 1.434 |
|
- type: map_at_100 |
|
value: 7.829 |
|
- type: map_at_1000 |
|
value: 19.807 |
|
- type: map_at_3 |
|
value: 0.549 |
|
- type: map_at_5 |
|
value: 0.8330000000000001 |
|
- type: mrr_at_1 |
|
value: 78.0 |
|
- type: mrr_at_10 |
|
value: 85.35199999999999 |
|
- type: mrr_at_100 |
|
value: 85.673 |
|
- type: mrr_at_1000 |
|
value: 85.673 |
|
- type: mrr_at_3 |
|
value: 84.667 |
|
- type: mrr_at_5 |
|
value: 85.06700000000001 |
|
- type: ndcg_at_1 |
|
value: 72.0 |
|
- type: ndcg_at_10 |
|
value: 59.214999999999996 |
|
- type: ndcg_at_100 |
|
value: 44.681 |
|
- type: ndcg_at_1000 |
|
value: 43.035000000000004 |
|
- type: ndcg_at_3 |
|
value: 66.53099999999999 |
|
- type: ndcg_at_5 |
|
value: 63.23 |
|
- type: precision_at_1 |
|
value: 78.0 |
|
- type: precision_at_10 |
|
value: 62.4 |
|
- type: precision_at_100 |
|
value: 45.76 |
|
- type: precision_at_1000 |
|
value: 19.05 |
|
- type: precision_at_3 |
|
value: 71.333 |
|
- type: precision_at_5 |
|
value: 67.2 |
|
- type: recall_at_1 |
|
value: 0.208 |
|
- type: recall_at_10 |
|
value: 1.6580000000000001 |
|
- type: recall_at_100 |
|
value: 11.324 |
|
- type: recall_at_1000 |
|
value: 41.537 |
|
- type: recall_at_3 |
|
value: 0.579 |
|
- type: recall_at_5 |
|
value: 0.8959999999999999 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: webis-touche2020 |
|
name: MTEB Touche2020 |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 2.442 |
|
- type: map_at_10 |
|
value: 8.863 |
|
- type: map_at_100 |
|
value: 14.606 |
|
- type: map_at_1000 |
|
value: 16.258 |
|
- type: map_at_3 |
|
value: 4.396 |
|
- type: map_at_5 |
|
value: 6.199000000000001 |
|
- type: mrr_at_1 |
|
value: 30.612000000000002 |
|
- type: mrr_at_10 |
|
value: 43.492 |
|
- type: mrr_at_100 |
|
value: 44.557 |
|
- type: mrr_at_1000 |
|
value: 44.557 |
|
- type: mrr_at_3 |
|
value: 40.816 |
|
- type: mrr_at_5 |
|
value: 42.143 |
|
- type: ndcg_at_1 |
|
value: 25.509999999999998 |
|
- type: ndcg_at_10 |
|
value: 22.076 |
|
- type: ndcg_at_100 |
|
value: 34.098 |
|
- type: ndcg_at_1000 |
|
value: 46.265 |
|
- type: ndcg_at_3 |
|
value: 24.19 |
|
- type: ndcg_at_5 |
|
value: 23.474 |
|
- type: precision_at_1 |
|
value: 30.612000000000002 |
|
- type: precision_at_10 |
|
value: 19.796 |
|
- type: precision_at_100 |
|
value: 7.286 |
|
- type: precision_at_1000 |
|
value: 1.5310000000000001 |
|
- type: precision_at_3 |
|
value: 25.85 |
|
- type: precision_at_5 |
|
value: 24.490000000000002 |
|
- type: recall_at_1 |
|
value: 2.442 |
|
- type: recall_at_10 |
|
value: 15.012 |
|
- type: recall_at_100 |
|
value: 45.865 |
|
- type: recall_at_1000 |
|
value: 82.958 |
|
- type: recall_at_3 |
|
value: 5.731 |
|
- type: recall_at_5 |
|
value: 9.301 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/toxic_conversations_50k |
|
name: MTEB ToxicConversationsClassification |
|
config: default |
|
split: test |
|
revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c |
|
metrics: |
|
- type: accuracy |
|
value: 70.974 |
|
- type: ap |
|
value: 14.534996211286682 |
|
- type: f1 |
|
value: 54.785946183399005 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/tweet_sentiment_extraction |
|
name: MTEB TweetSentimentExtractionClassification |
|
config: default |
|
split: test |
|
revision: d604517c81ca91fe16a244d1248fc021f9ecee7a |
|
metrics: |
|
- type: accuracy |
|
value: 58.56819468024901 |
|
- type: f1 |
|
value: 58.92391487111204 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: mteb/twentynewsgroups-clustering |
|
name: MTEB TwentyNewsgroupsClustering |
|
config: default |
|
split: test |
|
revision: 6125ec4e24fa026cec8a478383ee943acfbd5449 |
|
metrics: |
|
- type: v_measure |
|
value: 43.273202335218194 |
|
- task: |
|
type: PairClassification |
|
dataset: |
|
type: mteb/twittersemeval2015-pairclassification |
|
name: MTEB TwitterSemEval2015 |
|
config: default |
|
split: test |
|
revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1 |
|
metrics: |
|
- type: cos_sim_accuracy |
|
value: 84.37742146986946 |
|
- type: cos_sim_ap |
|
value: 68.1684129575579 |
|
- type: cos_sim_f1 |
|
value: 64.93475108748189 |
|
- type: cos_sim_precision |
|
value: 59.89745876058849 |
|
- type: cos_sim_recall |
|
value: 70.89709762532982 |
|
- type: dot_accuracy |
|
value: 80.49710913750968 |
|
- type: dot_ap |
|
value: 54.699790073944186 |
|
- type: dot_f1 |
|
value: 54.45130013221684 |
|
- type: dot_precision |
|
value: 46.74612183125236 |
|
- type: dot_recall |
|
value: 65.19788918205805 |
|
- type: euclidean_accuracy |
|
value: 84.5085533766466 |
|
- type: euclidean_ap |
|
value: 68.38835695236224 |
|
- type: euclidean_f1 |
|
value: 65.3391121002694 |
|
- type: euclidean_precision |
|
value: 58.75289656625237 |
|
- type: euclidean_recall |
|
value: 73.58839050131925 |
|
- type: manhattan_accuracy |
|
value: 84.40126363473803 |
|
- type: manhattan_ap |
|
value: 68.09539181555348 |
|
- type: manhattan_f1 |
|
value: 64.99028182701653 |
|
- type: manhattan_precision |
|
value: 60.22062134173795 |
|
- type: manhattan_recall |
|
value: 70.58047493403694 |
|
- type: max_accuracy |
|
value: 84.5085533766466 |
|
- type: max_ap |
|
value: 68.38835695236224 |
|
- type: max_f1 |
|
value: 65.3391121002694 |
|
- task: |
|
type: PairClassification |
|
dataset: |
|
type: mteb/twitterurlcorpus-pairclassification |
|
name: MTEB TwitterURLCorpus |
|
config: default |
|
split: test |
|
revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf |
|
metrics: |
|
- type: cos_sim_accuracy |
|
value: 88.34167733923235 |
|
- type: cos_sim_ap |
|
value: 84.84136381147736 |
|
- type: cos_sim_f1 |
|
value: 77.01434980904001 |
|
- type: cos_sim_precision |
|
value: 74.27937915742794 |
|
- type: cos_sim_recall |
|
value: 79.95842315983985 |
|
- type: dot_accuracy |
|
value: 85.06422944075756 |
|
- type: dot_ap |
|
value: 76.49446747522325 |
|
- type: dot_f1 |
|
value: 71.11606520830432 |
|
- type: dot_precision |
|
value: 64.93638676844785 |
|
- type: dot_recall |
|
value: 78.59562673236834 |
|
- type: euclidean_accuracy |
|
value: 88.45810532852097 |
|
- type: euclidean_ap |
|
value: 84.91526721863501 |
|
- type: euclidean_f1 |
|
value: 77.04399001750662 |
|
- type: euclidean_precision |
|
value: 74.62298867162133 |
|
- type: euclidean_recall |
|
value: 79.62734832152756 |
|
- type: manhattan_accuracy |
|
value: 88.46004579500912 |
|
- type: manhattan_ap |
|
value: 84.81590026238194 |
|
- type: manhattan_f1 |
|
value: 76.97804626491822 |
|
- type: manhattan_precision |
|
value: 73.79237288135593 |
|
- type: manhattan_recall |
|
value: 80.45118570988605 |
|
- type: max_accuracy |
|
value: 88.46004579500912 |
|
- type: max_ap |
|
value: 84.91526721863501 |
|
- type: max_f1 |
|
value: 77.04399001750662 |
|
|
|
pipeline_tag: sentence-similarity |
|
tags: |
|
- sentence-transformers |
|
- feature-extraction |
|
- sentence-similarity |
|
- transformers |
|
- mteb |
|
|
|
--- |
|
|
|
# {gte-tiny} |
|
|
|
This is a [sentence-transformers](https://www.SBERT.net) model: It maps sentences & paragraphs to a 384 dimensional dense vector space and can be used for tasks like clustering or semantic search. |
|
It is distilled from `thenlper/gte-small`, with comparable (slightly worse) performance at around half the size. |
|
|
|
<!--- Describe your model here --> |
|
|
|
## Usage (Sentence-Transformers) |
|
|
|
Using this model becomes easy when you have [sentence-transformers](https://www.SBERT.net) installed: |
|
|
|
``` |
|
pip install -U sentence-transformers |
|
``` |
|
|
|
Then you can use the model like this: |
|
|
|
```python |
|
from sentence_transformers import SentenceTransformer |
|
sentences = ["This is an example sentence", "Each sentence is converted"] |
|
|
|
model = SentenceTransformer('{MODEL_NAME}') |
|
embeddings = model.encode(sentences) |
|
print(embeddings) |
|
``` |
|
|
|
|
|
|
|
## Usage (HuggingFace Transformers) |
|
Without [sentence-transformers](https://www.SBERT.net), you can use the model like this: First, you pass your input through the transformer model, then you have to apply the right pooling-operation on-top of the contextualized word embeddings. |
|
|
|
```python |
|
from transformers import AutoTokenizer, AutoModel |
|
import torch |
|
|
|
|
|
#Mean Pooling - Take attention mask into account for correct averaging |
|
def mean_pooling(model_output, attention_mask): |
|
token_embeddings = model_output[0] #First element of model_output contains all token embeddings |
|
input_mask_expanded = attention_mask.unsqueeze(-1).expand(token_embeddings.size()).float() |
|
return torch.sum(token_embeddings * input_mask_expanded, 1) / torch.clamp(input_mask_expanded.sum(1), min=1e-9) |
|
|
|
|
|
# Sentences we want sentence embeddings for |
|
sentences = ['This is an example sentence', 'Each sentence is converted'] |
|
|
|
# Load model from HuggingFace Hub |
|
tokenizer = AutoTokenizer.from_pretrained('{MODEL_NAME}') |
|
model = AutoModel.from_pretrained('{MODEL_NAME}') |
|
|
|
# Tokenize sentences |
|
encoded_input = tokenizer(sentences, padding=True, truncation=True, return_tensors='pt') |
|
|
|
# Compute token embeddings |
|
with torch.no_grad(): |
|
model_output = model(**encoded_input) |
|
|
|
# Perform pooling. In this case, mean pooling. |
|
sentence_embeddings = mean_pooling(model_output, encoded_input['attention_mask']) |
|
|
|
print("Sentence embeddings:") |
|
print(sentence_embeddings) |
|
``` |
|
|
|
|
|
|
|
## Evaluation Results |
|
|
|
<!--- Describe how your model was evaluated --> |
|
|
|
For an automated evaluation of this model, see the *Sentence Embeddings Benchmark*: [https://seb.sbert.net](https://seb.sbert.net?model_name={MODEL_NAME}) |
|
|
|
|
|
|
|
## Full Model Architecture |
|
``` |
|
SentenceTransformer( |
|
(0): Transformer({'max_seq_length': 512, 'do_lower_case': False}) with Transformer model: BertModel |
|
(1): Pooling({'word_embedding_dimension': 384, 'pooling_mode_cls_token': False, 'pooling_mode_mean_tokens': True, 'pooling_mode_max_tokens': False, 'pooling_mode_mean_sqrt_len_tokens': False}) |
|
) |
|
``` |
|
|
|
## Citing & Authors |
|
|
|
<!--- Describe where people can find more information --> |
