|
--- |
|
library_name: sentence-transformers |
|
pipeline_tag: sentence-similarity |
|
tags: |
|
- mteb |
|
model-index: |
|
- name: b1ade_embed_kd |
|
results: |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/amazon_counterfactual |
|
name: MTEB AmazonCounterfactualClassification |
|
config: default |
|
split: test |
|
revision: e8379541af4e31359cca9fbcf4b00f2671dba205 |
|
metrics: |
|
- type: accuracy |
|
value: 75.81709145427287 |
|
- type: ap |
|
value: 23.581082591688467 |
|
- type: f1 |
|
value: 62.54637626017967 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/amazon_polarity |
|
name: MTEB AmazonPolarityClassification |
|
config: default |
|
split: test |
|
revision: e2d317d38cd51312af73b3d32a06d1a08b442046 |
|
metrics: |
|
- type: accuracy |
|
value: 80.300125 |
|
- type: ap |
|
value: 74.26836190039964 |
|
- type: f1 |
|
value: 80.2158066692679 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/amazon_reviews_multi |
|
name: MTEB AmazonReviewsClassification |
|
config: default |
|
split: test |
|
revision: 1399c76144fd37290681b995c656ef9b2e06e26d |
|
metrics: |
|
- type: accuracy |
|
value: 43.084 |
|
- type: f1 |
|
value: 42.66774553366831 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: mteb/arguana |
|
name: MTEB ArguAna |
|
config: default |
|
split: test |
|
revision: c22ab2a51041ffd869aaddef7af8d8215647e41a |
|
metrics: |
|
- type: map_at_1 |
|
value: 29.232000000000003 |
|
- type: map_at_10 |
|
value: 45.777 |
|
- type: map_at_100 |
|
value: 46.634 |
|
- type: map_at_1000 |
|
value: 46.64 |
|
- type: map_at_20 |
|
value: 46.489000000000004 |
|
- type: map_at_3 |
|
value: 40.861 |
|
- type: map_at_5 |
|
value: 43.659 |
|
- type: mrr_at_1 |
|
value: 30.156 |
|
- type: mrr_at_10 |
|
value: 46.141 |
|
- type: mrr_at_100 |
|
value: 46.983999999999995 |
|
- type: mrr_at_1000 |
|
value: 46.989999999999995 |
|
- type: mrr_at_20 |
|
value: 46.839 |
|
- type: mrr_at_3 |
|
value: 41.157 |
|
- type: mrr_at_5 |
|
value: 44.013000000000005 |
|
- type: ndcg_at_1 |
|
value: 29.232000000000003 |
|
- type: ndcg_at_10 |
|
value: 54.832 |
|
- type: ndcg_at_100 |
|
value: 58.303000000000004 |
|
- type: ndcg_at_1000 |
|
value: 58.451 |
|
- type: ndcg_at_20 |
|
value: 57.328 |
|
- type: ndcg_at_3 |
|
value: 44.685 |
|
- type: ndcg_at_5 |
|
value: 49.756 |
|
- type: precision_at_1 |
|
value: 29.232000000000003 |
|
- type: precision_at_10 |
|
value: 8.371 |
|
- type: precision_at_100 |
|
value: 0.985 |
|
- type: precision_at_1000 |
|
value: 0.1 |
|
- type: precision_at_20 |
|
value: 4.6690000000000005 |
|
- type: precision_at_3 |
|
value: 18.587 |
|
- type: precision_at_5 |
|
value: 13.627 |
|
- type: recall_at_1 |
|
value: 29.232000000000003 |
|
- type: recall_at_10 |
|
value: 83.71300000000001 |
|
- type: recall_at_100 |
|
value: 98.506 |
|
- type: recall_at_1000 |
|
value: 99.644 |
|
- type: recall_at_20 |
|
value: 93.38499999999999 |
|
- type: recall_at_3 |
|
value: 55.761 |
|
- type: recall_at_5 |
|
value: 68.137 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: mteb/arxiv-clustering-p2p |
|
name: MTEB ArxivClusteringP2P |
|
config: default |
|
split: test |
|
revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d |
|
metrics: |
|
- type: v_measure |
|
value: 45.801946024895756 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: mteb/arxiv-clustering-s2s |
|
name: MTEB ArxivClusteringS2S |
|
config: default |
|
split: test |
|
revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53 |
|
metrics: |
|
- type: v_measure |
|
value: 37.639210206045206 |
|
- task: |
|
type: Reranking |
|
dataset: |
|
type: mteb/askubuntudupquestions-reranking |
|
name: MTEB AskUbuntuDupQuestions |
|
config: default |
|
split: test |
|
revision: 2000358ca161889fa9c082cb41daa8dcfb161a54 |
|
metrics: |
|
- type: map |
|
value: 57.589359041891576 |
|
- type: mrr |
|
value: 70.88334872268389 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: mteb/biosses-sts |
|
name: MTEB BIOSSES |
|
config: default |
|
split: test |
|
revision: d3fb88f8f02e40887cd149695127462bbcf29b4a |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 86.63594177060354 |
|
- type: cos_sim_spearman |
|
value: 84.75132870687939 |
|
- type: euclidean_pearson |
|
value: 85.05646621990854 |
|
- type: euclidean_spearman |
|
value: 84.68686940680522 |
|
- type: manhattan_pearson |
|
value: 85.08705700579426 |
|
- type: manhattan_spearman |
|
value: 84.83446313127413 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/banking77 |
|
name: MTEB Banking77Classification |
|
config: default |
|
split: test |
|
revision: 0fd18e25b25c072e09e0d92ab615fda904d66300 |
|
metrics: |
|
- type: accuracy |
|
value: 85.1948051948052 |
|
- type: f1 |
|
value: 85.13229898343104 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: mteb/biorxiv-clustering-p2p |
|
name: MTEB BiorxivClusteringP2P |
|
config: default |
|
split: test |
|
revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40 |
|
metrics: |
|
- type: v_measure |
|
value: 38.68616898014911 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: mteb/biorxiv-clustering-s2s |
|
name: MTEB BiorxivClusteringS2S |
|
config: default |
|
split: test |
|
revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908 |
|
metrics: |
|
- type: v_measure |
|
value: 34.45376891835619 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: mteb/cqadupstack-android |
|
name: MTEB CQADupstackAndroidRetrieval |
|
config: default |
|
split: test |
|
revision: f46a197baaae43b4f621051089b82a364682dfeb |
|
metrics: |
|
- type: map_at_1 |
|
value: 26.340000000000003 |
|
- type: map_at_10 |
|
value: 36.513 |
|
- type: map_at_100 |
|
value: 37.968 |
|
- type: map_at_1000 |
|
value: 38.107 |
|
- type: map_at_20 |
|
value: 37.355 |
|
- type: map_at_3 |
|
value: 33.153 |
|
- type: map_at_5 |
|
value: 34.899 |
|
- type: mrr_at_1 |
|
value: 33.763 |
|
- type: mrr_at_10 |
|
value: 42.778 |
|
- type: mrr_at_100 |
|
value: 43.667 |
|
- type: mrr_at_1000 |
|
value: 43.724000000000004 |
|
- type: mrr_at_20 |
|
value: 43.349 |
|
- type: mrr_at_3 |
|
value: 40.32 |
|
- type: mrr_at_5 |
|
value: 41.657 |
|
- type: ndcg_at_1 |
|
value: 33.763 |
|
- type: ndcg_at_10 |
|
value: 42.783 |
|
- type: ndcg_at_100 |
|
value: 48.209999999999994 |
|
- type: ndcg_at_1000 |
|
value: 50.678999999999995 |
|
- type: ndcg_at_20 |
|
value: 45.073 |
|
- type: ndcg_at_3 |
|
value: 37.841 |
|
- type: ndcg_at_5 |
|
value: 39.818999999999996 |
|
- type: precision_at_1 |
|
value: 33.763 |
|
- type: precision_at_10 |
|
value: 8.398 |
|
- type: precision_at_100 |
|
value: 1.396 |
|
- type: precision_at_1000 |
|
value: 0.188 |
|
- type: precision_at_20 |
|
value: 5.0569999999999995 |
|
- type: precision_at_3 |
|
value: 18.503 |
|
- type: precision_at_5 |
|
value: 13.219 |
|
- type: recall_at_1 |
|
value: 26.340000000000003 |
|
- type: recall_at_10 |
|
value: 54.603 |
|
- type: recall_at_100 |
|
value: 77.264 |
|
- type: recall_at_1000 |
|
value: 93.882 |
|
- type: recall_at_20 |
|
value: 63.101 |
|
- type: recall_at_3 |
|
value: 39.6 |
|
- type: recall_at_5 |
|
value: 45.651 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: mteb/cqadupstack-english |
|
name: MTEB CQADupstackEnglishRetrieval |
|
config: default |
|
split: test |
|
revision: ad9991cb51e31e31e430383c75ffb2885547b5f0 |
|
metrics: |
|
- type: map_at_1 |
|
value: 24.313000000000002 |
|
- type: map_at_10 |
|
value: 33.225 |
|
- type: map_at_100 |
|
value: 34.293 |
|
- type: map_at_1000 |
|
value: 34.421 |
|
- type: map_at_20 |
|
value: 33.818 |
|
- type: map_at_3 |
|
value: 30.545 |
|
- type: map_at_5 |
|
value: 32.144 |
|
- type: mrr_at_1 |
|
value: 31.083 |
|
- type: mrr_at_10 |
|
value: 39.199 |
|
- type: mrr_at_100 |
|
value: 39.835 |
|
- type: mrr_at_1000 |
|
value: 39.892 |
|
- type: mrr_at_20 |
|
value: 39.57 |
|
- type: mrr_at_3 |
|
value: 36.879 |
|
- type: mrr_at_5 |
|
value: 38.245000000000005 |
|
- type: ndcg_at_1 |
|
value: 31.083 |
|
- type: ndcg_at_10 |
|
value: 38.553 |
|
- type: ndcg_at_100 |
|
value: 42.685 |
|
- type: ndcg_at_1000 |
|
value: 45.144 |
|
- type: ndcg_at_20 |
|
value: 40.116 |
|
- type: ndcg_at_3 |
|
value: 34.608 |
|
- type: ndcg_at_5 |
|
value: 36.551 |
|
- type: precision_at_1 |
|
value: 31.083 |
|
- type: precision_at_10 |
|
value: 7.28 |
|
- type: precision_at_100 |
|
value: 1.183 |
|
- type: precision_at_1000 |
|
value: 0.168 |
|
- type: precision_at_20 |
|
value: 4.322 |
|
- type: precision_at_3 |
|
value: 16.858 |
|
- type: precision_at_5 |
|
value: 12.127 |
|
- type: recall_at_1 |
|
value: 24.313000000000002 |
|
- type: recall_at_10 |
|
value: 48.117 |
|
- type: recall_at_100 |
|
value: 65.768 |
|
- type: recall_at_1000 |
|
value: 81.935 |
|
- type: recall_at_20 |
|
value: 53.689 |
|
- type: recall_at_3 |
|
value: 36.335 |
|
- type: recall_at_5 |
|
value: 41.803000000000004 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: mteb/cqadupstack-gaming |
|
name: MTEB CQADupstackGamingRetrieval |
|
config: default |
|
split: test |
|
revision: 4885aa143210c98657558c04aaf3dc47cfb54340 |
|
metrics: |
|
- type: map_at_1 |
|
value: 33.013999999999996 |
|
- type: map_at_10 |
|
value: 44.567 |
|
- type: map_at_100 |
|
value: 45.664 |
|
- type: map_at_1000 |
|
value: 45.732 |
|
- type: map_at_20 |
|
value: 45.190000000000005 |
|
- type: map_at_3 |
|
value: 41.393 |
|
- type: map_at_5 |
|
value: 43.147000000000006 |
|
- type: mrr_at_1 |
|
value: 37.806 |
|
- type: mrr_at_10 |
|
value: 47.841 |
|
- type: mrr_at_100 |
|
value: 48.597 |
|
- type: mrr_at_1000 |
|
value: 48.638 |
|
- type: mrr_at_20 |
|
value: 48.262 |
|
- type: mrr_at_3 |
|
value: 45.361000000000004 |
|
- type: mrr_at_5 |
|
value: 46.803 |
|
- type: ndcg_at_1 |
|
value: 37.806 |
|
- type: ndcg_at_10 |
|
value: 50.412 |
|
- type: ndcg_at_100 |
|
value: 55.019 |
|
- type: ndcg_at_1000 |
|
value: 56.52 |
|
- type: ndcg_at_20 |
|
value: 52.23100000000001 |
|
- type: ndcg_at_3 |
|
value: 44.944 |
|
- type: ndcg_at_5 |
|
value: 47.535 |
|
- type: precision_at_1 |
|
value: 37.806 |
|
- type: precision_at_10 |
|
value: 8.351 |
|
- type: precision_at_100 |
|
value: 1.163 |
|
- type: precision_at_1000 |
|
value: 0.134 |
|
- type: precision_at_20 |
|
value: 4.727 |
|
- type: precision_at_3 |
|
value: 20.376 |
|
- type: precision_at_5 |
|
value: 14.056 |
|
- type: recall_at_1 |
|
value: 33.013999999999996 |
|
- type: recall_at_10 |
|
value: 64.35600000000001 |
|
- type: recall_at_100 |
|
value: 84.748 |
|
- type: recall_at_1000 |
|
value: 95.525 |
|
- type: recall_at_20 |
|
value: 71.137 |
|
- type: recall_at_3 |
|
value: 49.726 |
|
- type: recall_at_5 |
|
value: 56.054 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: mteb/cqadupstack-gis |
|
name: MTEB CQADupstackGisRetrieval |
|
config: default |
|
split: test |
|
revision: 5003b3064772da1887988e05400cf3806fe491f2 |
|
metrics: |
|
- type: map_at_1 |
|
value: 18.476 |
|
- type: map_at_10 |
|
value: 24.715999999999998 |
|
- type: map_at_100 |
|
value: 25.72 |
|
- type: map_at_1000 |
|
value: 25.826999999999998 |
|
- type: map_at_20 |
|
value: 25.276 |
|
- type: map_at_3 |
|
value: 22.656000000000002 |
|
- type: map_at_5 |
|
value: 23.737 |
|
- type: mrr_at_1 |
|
value: 20.113 |
|
- type: mrr_at_10 |
|
value: 26.423999999999996 |
|
- type: mrr_at_100 |
|
value: 27.328000000000003 |
|
- type: mrr_at_1000 |
|
value: 27.418 |
|
- type: mrr_at_20 |
|
value: 26.936 |
|
- type: mrr_at_3 |
|
value: 24.275 |
|
- type: mrr_at_5 |
|
value: 25.501 |
|
- type: ndcg_at_1 |
|
value: 20.113 |
|
- type: ndcg_at_10 |
|
value: 28.626 |
|
- type: ndcg_at_100 |
|
value: 33.649 |
|
- type: ndcg_at_1000 |
|
value: 36.472 |
|
- type: ndcg_at_20 |
|
value: 30.581999999999997 |
|
- type: ndcg_at_3 |
|
value: 24.490000000000002 |
|
- type: ndcg_at_5 |
|
value: 26.394000000000002 |
|
- type: precision_at_1 |
|
value: 20.113 |
|
- type: precision_at_10 |
|
value: 4.52 |
|
- type: precision_at_100 |
|
value: 0.739 |
|
- type: precision_at_1000 |
|
value: 0.10200000000000001 |
|
- type: precision_at_20 |
|
value: 2.706 |
|
- type: precision_at_3 |
|
value: 10.433 |
|
- type: precision_at_5 |
|
value: 7.48 |
|
- type: recall_at_1 |
|
value: 18.476 |
|
- type: recall_at_10 |
|
value: 39.129000000000005 |
|
- type: recall_at_100 |
|
value: 62.44 |
|
- type: recall_at_1000 |
|
value: 83.95700000000001 |
|
- type: recall_at_20 |
|
value: 46.611999999999995 |
|
- type: recall_at_3 |
|
value: 27.772000000000002 |
|
- type: recall_at_5 |
|
value: 32.312000000000005 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: mteb/cqadupstack-mathematica |
|
name: MTEB CQADupstackMathematicaRetrieval |
|
config: default |
|
split: test |
|
revision: 90fceea13679c63fe563ded68f3b6f06e50061de |
|
metrics: |
|
- type: map_at_1 |
|
value: 10.126 |
|
- type: map_at_10 |
|
value: 15.916 |
|
- type: map_at_100 |
|
value: 17.049 |
|
- type: map_at_1000 |
|
value: 17.19 |
|
- type: map_at_20 |
|
value: 16.569 |
|
- type: map_at_3 |
|
value: 13.986 |
|
- type: map_at_5 |
|
value: 15.052999999999999 |
|
- type: mrr_at_1 |
|
value: 13.059999999999999 |
|
- type: mrr_at_10 |
|
value: 19.52 |
|
- type: mrr_at_100 |
|
value: 20.599999999999998 |
|
- type: mrr_at_1000 |
|
value: 20.693 |
|
- type: mrr_at_20 |
|
value: 20.177999999999997 |
|
- type: mrr_at_3 |
|
value: 17.496000000000002 |
|
- type: mrr_at_5 |
|
value: 18.541 |
|
- type: ndcg_at_1 |
|
value: 13.059999999999999 |
|
- type: ndcg_at_10 |
|
value: 19.987 |
|
- type: ndcg_at_100 |
|
value: 25.602000000000004 |
|
- type: ndcg_at_1000 |
|
value: 29.171999999999997 |
|
- type: ndcg_at_20 |
|
value: 22.31 |
|
- type: ndcg_at_3 |
|
value: 16.286 |
|
- type: ndcg_at_5 |
|
value: 17.931 |
|
- type: precision_at_1 |
|
value: 13.059999999999999 |
|
- type: precision_at_10 |
|
value: 3.9050000000000002 |
|
- type: precision_at_100 |
|
value: 0.771 |
|
- type: precision_at_1000 |
|
value: 0.123 |
|
- type: precision_at_20 |
|
value: 2.606 |
|
- type: precision_at_3 |
|
value: 8.167 |
|
- type: precision_at_5 |
|
value: 6.045 |
|
- type: recall_at_1 |
|
value: 10.126 |
|
- type: recall_at_10 |
|
value: 29.137 |
|
- type: recall_at_100 |
|
value: 53.824000000000005 |
|
- type: recall_at_1000 |
|
value: 79.373 |
|
- type: recall_at_20 |
|
value: 37.475 |
|
- type: recall_at_3 |
|
value: 18.791 |
|
- type: recall_at_5 |
|
value: 22.993 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: mteb/cqadupstack-physics |
|
name: MTEB CQADupstackPhysicsRetrieval |
|
config: default |
|
split: test |
|
revision: 79531abbd1fb92d06c6d6315a0cbbbf5bb247ea4 |
|
metrics: |
|
- type: map_at_1 |
|
value: 25.281 |
|
- type: map_at_10 |
|
value: 34.875 |
|
- type: map_at_100 |
|
value: 36.268 |
|
- type: map_at_1000 |
|
value: 36.385 |
|
- type: map_at_20 |
|
value: 35.711999999999996 |
|
- type: map_at_3 |
|
value: 31.808999999999997 |
|
- type: map_at_5 |
|
value: 33.550999999999995 |
|
- type: mrr_at_1 |
|
value: 31.28 |
|
- type: mrr_at_10 |
|
value: 40.489000000000004 |
|
- type: mrr_at_100 |
|
value: 41.434 |
|
- type: mrr_at_1000 |
|
value: 41.491 |
|
- type: mrr_at_20 |
|
value: 41.088 |
|
- type: mrr_at_3 |
|
value: 38.033 |
|
- type: mrr_at_5 |
|
value: 39.621 |
|
- type: ndcg_at_1 |
|
value: 31.28 |
|
- type: ndcg_at_10 |
|
value: 40.716 |
|
- type: ndcg_at_100 |
|
value: 46.45 |
|
- type: ndcg_at_1000 |
|
value: 48.851 |
|
- type: ndcg_at_20 |
|
value: 43.216 |
|
- type: ndcg_at_3 |
|
value: 35.845 |
|
- type: ndcg_at_5 |
|
value: 38.251000000000005 |
|
- type: precision_at_1 |
|
value: 31.28 |
|
- type: precision_at_10 |
|
value: 7.623 |
|
- type: precision_at_100 |
|
value: 1.214 |
|
- type: precision_at_1000 |
|
value: 0.159 |
|
- type: precision_at_20 |
|
value: 4.625 |
|
- type: precision_at_3 |
|
value: 17.26 |
|
- type: precision_at_5 |
|
value: 12.435 |
|
- type: recall_at_1 |
|
value: 25.281 |
|
- type: recall_at_10 |
|
value: 52.476 |
|
- type: recall_at_100 |
|
value: 76.535 |
|
- type: recall_at_1000 |
|
value: 92.658 |
|
- type: recall_at_20 |
|
value: 61.211000000000006 |
|
- type: recall_at_3 |
|
value: 38.805 |
|
- type: recall_at_5 |
|
value: 45.053 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: mteb/cqadupstack-programmers |
|
name: MTEB CQADupstackProgrammersRetrieval |
|
config: default |
|
split: test |
|
revision: 6184bc1440d2dbc7612be22b50686b8826d22b32 |
|
metrics: |
|
- type: map_at_1 |
|
value: 20.092 |
|
- type: map_at_10 |
|
value: 27.805999999999997 |
|
- type: map_at_100 |
|
value: 29.137999999999998 |
|
- type: map_at_1000 |
|
value: 29.266 |
|
- type: map_at_20 |
|
value: 28.587 |
|
- type: map_at_3 |
|
value: 25.112000000000002 |
|
- type: map_at_5 |
|
value: 26.551000000000002 |
|
- type: mrr_at_1 |
|
value: 24.315 |
|
- type: mrr_at_10 |
|
value: 32.068000000000005 |
|
- type: mrr_at_100 |
|
value: 33.039 |
|
- type: mrr_at_1000 |
|
value: 33.114 |
|
- type: mrr_at_20 |
|
value: 32.66 |
|
- type: mrr_at_3 |
|
value: 29.49 |
|
- type: mrr_at_5 |
|
value: 30.906 |
|
- type: ndcg_at_1 |
|
value: 24.315 |
|
- type: ndcg_at_10 |
|
value: 32.9 |
|
- type: ndcg_at_100 |
|
value: 38.741 |
|
- type: ndcg_at_1000 |
|
value: 41.657 |
|
- type: ndcg_at_20 |
|
value: 35.338 |
|
- type: ndcg_at_3 |
|
value: 28.069 |
|
- type: ndcg_at_5 |
|
value: 30.169 |
|
- type: precision_at_1 |
|
value: 24.315 |
|
- type: precision_at_10 |
|
value: 6.2330000000000005 |
|
- type: precision_at_100 |
|
value: 1.072 |
|
- type: precision_at_1000 |
|
value: 0.15 |
|
- type: precision_at_20 |
|
value: 3.8580000000000005 |
|
- type: precision_at_3 |
|
value: 13.318 |
|
- type: precision_at_5 |
|
value: 9.748999999999999 |
|
- type: recall_at_1 |
|
value: 20.092 |
|
- type: recall_at_10 |
|
value: 43.832 |
|
- type: recall_at_100 |
|
value: 68.75099999999999 |
|
- type: recall_at_1000 |
|
value: 89.25 |
|
- type: recall_at_20 |
|
value: 52.445 |
|
- type: recall_at_3 |
|
value: 30.666 |
|
- type: recall_at_5 |
|
value: 35.873 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: mteb/cqadupstack |
|
name: MTEB CQADupstackRetrieval |
|
config: default |
|
split: test |
|
revision: 160c094312a0e1facb97e55eeddb698c0abe3571 |
|
metrics: |
|
- type: map_at_1 |
|
value: 19.317 |
|
- type: map_at_10 |
|
value: 26.653 |
|
- type: map_at_100 |
|
value: 28.011999999999997 |
|
- type: map_at_1000 |
|
value: 28.231 |
|
- type: map_at_20 |
|
value: 27.301 |
|
- type: map_at_3 |
|
value: 23.763 |
|
- type: map_at_5 |
|
value: 25.391000000000002 |
|
- type: mrr_at_1 |
|
value: 24.506 |
|
- type: mrr_at_10 |
|
value: 31.991999999999997 |
|
- type: mrr_at_100 |
|
value: 32.924 |
|
- type: mrr_at_1000 |
|
value: 32.993 |
|
- type: mrr_at_20 |
|
value: 32.521 |
|
- type: mrr_at_3 |
|
value: 29.48 |
|
- type: mrr_at_5 |
|
value: 30.982 |
|
- type: ndcg_at_1 |
|
value: 24.506 |
|
- type: ndcg_at_10 |
|
value: 32.202999999999996 |
|
- type: ndcg_at_100 |
|
value: 37.797 |
|
- type: ndcg_at_1000 |
|
value: 40.859 |
|
- type: ndcg_at_20 |
|
value: 34.098 |
|
- type: ndcg_at_3 |
|
value: 27.552 |
|
- type: ndcg_at_5 |
|
value: 29.781000000000002 |
|
- type: precision_at_1 |
|
value: 24.506 |
|
- type: precision_at_10 |
|
value: 6.462 |
|
- type: precision_at_100 |
|
value: 1.35 |
|
- type: precision_at_1000 |
|
value: 0.22499999999999998 |
|
- type: precision_at_20 |
|
value: 4.071000000000001 |
|
- type: precision_at_3 |
|
value: 13.241 |
|
- type: precision_at_5 |
|
value: 9.921000000000001 |
|
- type: recall_at_1 |
|
value: 19.317 |
|
- type: recall_at_10 |
|
value: 42.296 |
|
- type: recall_at_100 |
|
value: 68.2 |
|
- type: recall_at_1000 |
|
value: 88.565 |
|
- type: recall_at_20 |
|
value: 49.883 |
|
- type: recall_at_3 |
|
value: 28.608 |
|
- type: recall_at_5 |
|
value: 34.854 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: mteb/cqadupstack-stats |
|
name: MTEB CQADupstackStatsRetrieval |
|
config: default |
|
split: test |
|
revision: 65ac3a16b8e91f9cee4c9828cc7c335575432a2a |
|
metrics: |
|
- type: map_at_1 |
|
value: 18.0 |
|
- type: map_at_10 |
|
value: 24.444 |
|
- type: map_at_100 |
|
value: 25.205 |
|
- type: map_at_1000 |
|
value: 25.291000000000004 |
|
- type: map_at_20 |
|
value: 24.834 |
|
- type: map_at_3 |
|
value: 22.311 |
|
- type: map_at_5 |
|
value: 23.442 |
|
- type: mrr_at_1 |
|
value: 20.552 |
|
- type: mrr_at_10 |
|
value: 27.028999999999996 |
|
- type: mrr_at_100 |
|
value: 27.706999999999997 |
|
- type: mrr_at_1000 |
|
value: 27.775 |
|
- type: mrr_at_20 |
|
value: 27.366 |
|
- type: mrr_at_3 |
|
value: 25.051000000000002 |
|
- type: mrr_at_5 |
|
value: 26.063 |
|
- type: ndcg_at_1 |
|
value: 20.552 |
|
- type: ndcg_at_10 |
|
value: 28.519 |
|
- type: ndcg_at_100 |
|
value: 32.580999999999996 |
|
- type: ndcg_at_1000 |
|
value: 34.99 |
|
- type: ndcg_at_20 |
|
value: 29.848000000000003 |
|
- type: ndcg_at_3 |
|
value: 24.46 |
|
- type: ndcg_at_5 |
|
value: 26.273000000000003 |
|
- type: precision_at_1 |
|
value: 20.552 |
|
- type: precision_at_10 |
|
value: 4.801 |
|
- type: precision_at_100 |
|
value: 0.729 |
|
- type: precision_at_1000 |
|
value: 0.101 |
|
- type: precision_at_20 |
|
value: 2.715 |
|
- type: precision_at_3 |
|
value: 10.940999999999999 |
|
- type: precision_at_5 |
|
value: 7.761 |
|
- type: recall_at_1 |
|
value: 18.0 |
|
- type: recall_at_10 |
|
value: 38.425 |
|
- type: recall_at_100 |
|
value: 57.885 |
|
- type: recall_at_1000 |
|
value: 75.945 |
|
- type: recall_at_20 |
|
value: 43.472 |
|
- type: recall_at_3 |
|
value: 27.483 |
|
- type: recall_at_5 |
|
value: 31.866 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: mteb/cqadupstack-tex |
|
name: MTEB CQADupstackTexRetrieval |
|
config: default |
|
split: test |
|
revision: 46989137a86843e03a6195de44b09deda022eec7 |
|
metrics: |
|
- type: map_at_1 |
|
value: 10.014000000000001 |
|
- type: map_at_10 |
|
value: 14.462 |
|
- type: map_at_100 |
|
value: 15.364 |
|
- type: map_at_1000 |
|
value: 15.482999999999999 |
|
- type: map_at_20 |
|
value: 14.931 |
|
- type: map_at_3 |
|
value: 12.842 |
|
- type: map_at_5 |
|
value: 13.697999999999999 |
|
- type: mrr_at_1 |
|
value: 12.526000000000002 |
|
- type: mrr_at_10 |
|
value: 17.433 |
|
- type: mrr_at_100 |
|
value: 18.296 |
|
- type: mrr_at_1000 |
|
value: 18.383 |
|
- type: mrr_at_20 |
|
value: 17.897 |
|
- type: mrr_at_3 |
|
value: 15.703 |
|
- type: mrr_at_5 |
|
value: 16.627 |
|
- type: ndcg_at_1 |
|
value: 12.526000000000002 |
|
- type: ndcg_at_10 |
|
value: 17.697 |
|
- type: ndcg_at_100 |
|
value: 22.33 |
|
- type: ndcg_at_1000 |
|
value: 25.587 |
|
- type: ndcg_at_20 |
|
value: 19.302 |
|
- type: ndcg_at_3 |
|
value: 14.606 |
|
- type: ndcg_at_5 |
|
value: 15.946 |
|
- type: precision_at_1 |
|
value: 12.526000000000002 |
|
- type: precision_at_10 |
|
value: 3.383 |
|
- type: precision_at_100 |
|
value: 0.6799999999999999 |
|
- type: precision_at_1000 |
|
value: 0.11199999999999999 |
|
- type: precision_at_20 |
|
value: 2.147 |
|
- type: precision_at_3 |
|
value: 7.02 |
|
- type: precision_at_5 |
|
value: 5.196 |
|
- type: recall_at_1 |
|
value: 10.014000000000001 |
|
- type: recall_at_10 |
|
value: 24.623 |
|
- type: recall_at_100 |
|
value: 45.795 |
|
- type: recall_at_1000 |
|
value: 69.904 |
|
- type: recall_at_20 |
|
value: 30.534 |
|
- type: recall_at_3 |
|
value: 15.955 |
|
- type: recall_at_5 |
|
value: 19.394 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: mteb/cqadupstack-unix |
|
name: MTEB CQADupstackUnixRetrieval |
|
config: default |
|
split: test |
|
revision: 6c6430d3a6d36f8d2a829195bc5dc94d7e063e53 |
|
metrics: |
|
- type: map_at_1 |
|
value: 19.156000000000002 |
|
- type: map_at_10 |
|
value: 26.144000000000002 |
|
- type: map_at_100 |
|
value: 27.157999999999998 |
|
- type: map_at_1000 |
|
value: 27.288 |
|
- type: map_at_20 |
|
value: 26.689 |
|
- type: map_at_3 |
|
value: 24.125 |
|
- type: map_at_5 |
|
value: 25.369000000000003 |
|
- type: mrr_at_1 |
|
value: 22.854 |
|
- type: mrr_at_10 |
|
value: 29.874000000000002 |
|
- type: mrr_at_100 |
|
value: 30.738 |
|
- type: mrr_at_1000 |
|
value: 30.826999999999998 |
|
- type: mrr_at_20 |
|
value: 30.354 |
|
- type: mrr_at_3 |
|
value: 27.689999999999998 |
|
- type: mrr_at_5 |
|
value: 29.131 |
|
- type: ndcg_at_1 |
|
value: 22.854 |
|
- type: ndcg_at_10 |
|
value: 30.469 |
|
- type: ndcg_at_100 |
|
value: 35.475 |
|
- type: ndcg_at_1000 |
|
value: 38.59 |
|
- type: ndcg_at_20 |
|
value: 32.333 |
|
- type: ndcg_at_3 |
|
value: 26.674999999999997 |
|
- type: ndcg_at_5 |
|
value: 28.707 |
|
- type: precision_at_1 |
|
value: 22.854 |
|
- type: precision_at_10 |
|
value: 5.1209999999999996 |
|
- type: precision_at_100 |
|
value: 0.8500000000000001 |
|
- type: precision_at_1000 |
|
value: 0.123 |
|
- type: precision_at_20 |
|
value: 3.0460000000000003 |
|
- type: precision_at_3 |
|
value: 12.127 |
|
- type: precision_at_5 |
|
value: 8.75 |
|
- type: recall_at_1 |
|
value: 19.156000000000002 |
|
- type: recall_at_10 |
|
value: 40.009 |
|
- type: recall_at_100 |
|
value: 62.419999999999995 |
|
- type: recall_at_1000 |
|
value: 84.585 |
|
- type: recall_at_20 |
|
value: 46.912 |
|
- type: recall_at_3 |
|
value: 29.733999999999998 |
|
- type: recall_at_5 |
|
value: 34.741 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: mteb/cqadupstack-webmasters |
|
name: MTEB CQADupstackWebmastersRetrieval |
|
config: default |
|
split: test |
|
revision: 160c094312a0e1facb97e55eeddb698c0abe3571 |
|
metrics: |
|
- type: map_at_1 |
|
value: 19.317 |
|
- type: map_at_10 |
|
value: 26.653 |
|
- type: map_at_100 |
|
value: 28.011999999999997 |
|
- type: map_at_1000 |
|
value: 28.231 |
|
- type: map_at_20 |
|
value: 27.301 |
|
- type: map_at_3 |
|
value: 23.763 |
|
- type: map_at_5 |
|
value: 25.391000000000002 |
|
- type: mrr_at_1 |
|
value: 24.506 |
|
- type: mrr_at_10 |
|
value: 31.991999999999997 |
|
- type: mrr_at_100 |
|
value: 32.924 |
|
- type: mrr_at_1000 |
|
value: 32.993 |
|
- type: mrr_at_20 |
|
value: 32.521 |
|
- type: mrr_at_3 |
|
value: 29.48 |
|
- type: mrr_at_5 |
|
value: 30.982 |
|
- type: ndcg_at_1 |
|
value: 24.506 |
|
- type: ndcg_at_10 |
|
value: 32.202999999999996 |
|
- type: ndcg_at_100 |
|
value: 37.797 |
|
- type: ndcg_at_1000 |
|
value: 40.859 |
|
- type: ndcg_at_20 |
|
value: 34.098 |
|
- type: ndcg_at_3 |
|
value: 27.552 |
|
- type: ndcg_at_5 |
|
value: 29.781000000000002 |
|
- type: precision_at_1 |
|
value: 24.506 |
|
- type: precision_at_10 |
|
value: 6.462 |
|
- type: precision_at_100 |
|
value: 1.35 |
|
- type: precision_at_1000 |
|
value: 0.22499999999999998 |
|
- type: precision_at_20 |
|
value: 4.071000000000001 |
|
- type: precision_at_3 |
|
value: 13.241 |
|
- type: precision_at_5 |
|
value: 9.921000000000001 |
|
- type: recall_at_1 |
|
value: 19.317 |
|
- type: recall_at_10 |
|
value: 42.296 |
|
- type: recall_at_100 |
|
value: 68.2 |
|
- type: recall_at_1000 |
|
value: 88.565 |
|
- type: recall_at_20 |
|
value: 49.883 |
|
- type: recall_at_3 |
|
value: 28.608 |
|
- type: recall_at_5 |
|
value: 34.854 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: mteb/cqadupstack-wordpress |
|
name: MTEB CQADupstackWordpressRetrieval |
|
config: default |
|
split: test |
|
revision: 4ffe81d471b1924886b33c7567bfb200e9eec5c4 |
|
metrics: |
|
- type: map_at_1 |
|
value: 12.822 |
|
- type: map_at_10 |
|
value: 18.055 |
|
- type: map_at_100 |
|
value: 18.942 |
|
- type: map_at_1000 |
|
value: 19.057 |
|
- type: map_at_20 |
|
value: 18.544 |
|
- type: map_at_3 |
|
value: 15.964 |
|
- type: map_at_5 |
|
value: 16.833000000000002 |
|
- type: mrr_at_1 |
|
value: 14.048 |
|
- type: mrr_at_10 |
|
value: 19.489 |
|
- type: mrr_at_100 |
|
value: 20.392 |
|
- type: mrr_at_1000 |
|
value: 20.49 |
|
- type: mrr_at_20 |
|
value: 19.979 |
|
- type: mrr_at_3 |
|
value: 17.344 |
|
- type: mrr_at_5 |
|
value: 18.287 |
|
- type: ndcg_at_1 |
|
value: 14.048 |
|
- type: ndcg_at_10 |
|
value: 21.737000000000002 |
|
- type: ndcg_at_100 |
|
value: 26.383000000000003 |
|
- type: ndcg_at_1000 |
|
value: 29.555 |
|
- type: ndcg_at_20 |
|
value: 23.463 |
|
- type: ndcg_at_3 |
|
value: 17.29 |
|
- type: ndcg_at_5 |
|
value: 18.829 |
|
- type: precision_at_1 |
|
value: 14.048 |
|
- type: precision_at_10 |
|
value: 3.6229999999999998 |
|
- type: precision_at_100 |
|
value: 0.641 |
|
- type: precision_at_1000 |
|
value: 0.099 |
|
- type: precision_at_20 |
|
value: 2.1999999999999997 |
|
- type: precision_at_3 |
|
value: 7.2090000000000005 |
|
- type: precision_at_5 |
|
value: 5.213 |
|
- type: recall_at_1 |
|
value: 12.822 |
|
- type: recall_at_10 |
|
value: 32.123000000000005 |
|
- type: recall_at_100 |
|
value: 53.657999999999994 |
|
- type: recall_at_1000 |
|
value: 77.72200000000001 |
|
- type: recall_at_20 |
|
value: 38.66 |
|
- type: recall_at_3 |
|
value: 19.814999999999998 |
|
- type: recall_at_5 |
|
value: 23.432 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: mteb/climate-fever |
|
name: MTEB ClimateFEVER |
|
config: default |
|
split: test |
|
revision: 47f2ac6acb640fc46020b02a5b59fdda04d39380 |
|
metrics: |
|
- type: map_at_1 |
|
value: 13.119 |
|
- type: map_at_10 |
|
value: 22.999 |
|
- type: map_at_100 |
|
value: 25.108000000000004 |
|
- type: map_at_1000 |
|
value: 25.306 |
|
- type: map_at_20 |
|
value: 24.141000000000002 |
|
- type: map_at_3 |
|
value: 19.223000000000003 |
|
- type: map_at_5 |
|
value: 21.181 |
|
- type: mrr_at_1 |
|
value: 30.554 |
|
- type: mrr_at_10 |
|
value: 42.553000000000004 |
|
- type: mrr_at_100 |
|
value: 43.498 |
|
- type: mrr_at_1000 |
|
value: 43.527 |
|
- type: mrr_at_20 |
|
value: 43.193 |
|
- type: mrr_at_3 |
|
value: 39.283 |
|
- type: mrr_at_5 |
|
value: 41.143 |
|
- type: ndcg_at_1 |
|
value: 30.554 |
|
- type: ndcg_at_10 |
|
value: 31.946 |
|
- type: ndcg_at_100 |
|
value: 39.934999999999995 |
|
- type: ndcg_at_1000 |
|
value: 43.256 |
|
- type: ndcg_at_20 |
|
value: 35.101 |
|
- type: ndcg_at_3 |
|
value: 26.489 |
|
- type: ndcg_at_5 |
|
value: 28.272000000000002 |
|
- type: precision_at_1 |
|
value: 30.554 |
|
- type: precision_at_10 |
|
value: 10.039 |
|
- type: precision_at_100 |
|
value: 1.864 |
|
- type: precision_at_1000 |
|
value: 0.248 |
|
- type: precision_at_20 |
|
value: 6.371 |
|
- type: precision_at_3 |
|
value: 20.174 |
|
- type: precision_at_5 |
|
value: 15.296000000000001 |
|
- type: recall_at_1 |
|
value: 13.119 |
|
- type: recall_at_10 |
|
value: 37.822 |
|
- type: recall_at_100 |
|
value: 65.312 |
|
- type: recall_at_1000 |
|
value: 83.817 |
|
- type: recall_at_20 |
|
value: 46.760000000000005 |
|
- type: recall_at_3 |
|
value: 23.858999999999998 |
|
- type: recall_at_5 |
|
value: 29.609999999999996 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: mteb/dbpedia |
|
name: MTEB DBPedia |
|
config: default |
|
split: test |
|
revision: c0f706b76e590d620bd6618b3ca8efdd34e2d659 |
|
metrics: |
|
- type: map_at_1 |
|
value: 8.176 |
|
- type: map_at_10 |
|
value: 19.594 |
|
- type: map_at_100 |
|
value: 28.081 |
|
- type: map_at_1000 |
|
value: 29.864 |
|
- type: map_at_20 |
|
value: 22.983999999999998 |
|
- type: map_at_3 |
|
value: 13.923 |
|
- type: map_at_5 |
|
value: 16.597 |
|
- type: mrr_at_1 |
|
value: 66.75 |
|
- type: mrr_at_10 |
|
value: 75.82600000000001 |
|
- type: mrr_at_100 |
|
value: 76.145 |
|
- type: mrr_at_1000 |
|
value: 76.14999999999999 |
|
- type: mrr_at_20 |
|
value: 76.074 |
|
- type: mrr_at_3 |
|
value: 74.333 |
|
- type: mrr_at_5 |
|
value: 75.25800000000001 |
|
- type: ndcg_at_1 |
|
value: 54.50000000000001 |
|
- type: ndcg_at_10 |
|
value: 41.806 |
|
- type: ndcg_at_100 |
|
value: 47.067 |
|
- type: ndcg_at_1000 |
|
value: 54.397 |
|
- type: ndcg_at_20 |
|
value: 41.727 |
|
- type: ndcg_at_3 |
|
value: 46.92 |
|
- type: ndcg_at_5 |
|
value: 44.381 |
|
- type: precision_at_1 |
|
value: 66.75 |
|
- type: precision_at_10 |
|
value: 33.35 |
|
- type: precision_at_100 |
|
value: 10.92 |
|
- type: precision_at_1000 |
|
value: 2.222 |
|
- type: precision_at_20 |
|
value: 25.862000000000002 |
|
- type: precision_at_3 |
|
value: 51.417 |
|
- type: precision_at_5 |
|
value: 43.65 |
|
- type: recall_at_1 |
|
value: 8.176 |
|
- type: recall_at_10 |
|
value: 26.029000000000003 |
|
- type: recall_at_100 |
|
value: 53.872 |
|
- type: recall_at_1000 |
|
value: 76.895 |
|
- type: recall_at_20 |
|
value: 34.192 |
|
- type: recall_at_3 |
|
value: 15.789 |
|
- type: recall_at_5 |
|
value: 20.255000000000003 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/emotion |
|
name: MTEB EmotionClassification |
|
config: default |
|
split: test |
|
revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37 |
|
metrics: |
|
- type: accuracy |
|
value: 48.22 |
|
- type: f1 |
|
value: 43.59074485488622 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: mteb/fever |
|
name: MTEB FEVER |
|
config: default |
|
split: test |
|
revision: bea83ef9e8fb933d90a2f1d5515737465d613e12 |
|
metrics: |
|
- type: map_at_1 |
|
value: 40.872 |
|
- type: map_at_10 |
|
value: 55.178000000000004 |
|
- type: map_at_100 |
|
value: 55.859 |
|
- type: map_at_1000 |
|
value: 55.881 |
|
- type: map_at_20 |
|
value: 55.66 |
|
- type: map_at_3 |
|
value: 51.4 |
|
- type: map_at_5 |
|
value: 53.754000000000005 |
|
- type: mrr_at_1 |
|
value: 43.744 |
|
- type: mrr_at_10 |
|
value: 58.36900000000001 |
|
- type: mrr_at_100 |
|
value: 58.911 |
|
- type: mrr_at_1000 |
|
value: 58.916999999999994 |
|
- type: mrr_at_20 |
|
value: 58.779 |
|
- type: mrr_at_3 |
|
value: 54.653 |
|
- type: mrr_at_5 |
|
value: 56.987 |
|
- type: ndcg_at_1 |
|
value: 43.744 |
|
- type: ndcg_at_10 |
|
value: 62.936 |
|
- type: ndcg_at_100 |
|
value: 65.666 |
|
- type: ndcg_at_1000 |
|
value: 66.08699999999999 |
|
- type: ndcg_at_20 |
|
value: 64.548 |
|
- type: ndcg_at_3 |
|
value: 55.543 |
|
- type: ndcg_at_5 |
|
value: 59.646 |
|
- type: precision_at_1 |
|
value: 43.744 |
|
- type: precision_at_10 |
|
value: 9.191 |
|
- type: precision_at_100 |
|
value: 1.072 |
|
- type: precision_at_1000 |
|
value: 0.11299999999999999 |
|
- type: precision_at_20 |
|
value: 4.967 |
|
- type: precision_at_3 |
|
value: 23.157 |
|
- type: precision_at_5 |
|
value: 16.115 |
|
- type: recall_at_1 |
|
value: 40.872 |
|
- type: recall_at_10 |
|
value: 83.818 |
|
- type: recall_at_100 |
|
value: 95.14200000000001 |
|
- type: recall_at_1000 |
|
value: 97.897 |
|
- type: recall_at_20 |
|
value: 89.864 |
|
- type: recall_at_3 |
|
value: 64.19200000000001 |
|
- type: recall_at_5 |
|
value: 74.029 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: mteb/fiqa |
|
name: MTEB FiQA2018 |
|
config: default |
|
split: test |
|
revision: 27a168819829fe9bcd655c2df245fb19452e8e06 |
|
metrics: |
|
- type: map_at_1 |
|
value: 14.804999999999998 |
|
- type: map_at_10 |
|
value: 22.86 |
|
- type: map_at_100 |
|
value: 24.823999999999998 |
|
- type: map_at_1000 |
|
value: 25.041000000000004 |
|
- type: map_at_20 |
|
value: 23.881 |
|
- type: map_at_3 |
|
value: 20.09 |
|
- type: map_at_5 |
|
value: 21.39 |
|
- type: mrr_at_1 |
|
value: 29.938 |
|
- type: mrr_at_10 |
|
value: 37.041000000000004 |
|
- type: mrr_at_100 |
|
value: 38.196000000000005 |
|
- type: mrr_at_1000 |
|
value: 38.256 |
|
- type: mrr_at_20 |
|
value: 37.693 |
|
- type: mrr_at_3 |
|
value: 34.721999999999994 |
|
- type: mrr_at_5 |
|
value: 35.787 |
|
- type: ndcg_at_1 |
|
value: 29.938 |
|
- type: ndcg_at_10 |
|
value: 29.358 |
|
- type: ndcg_at_100 |
|
value: 37.544 |
|
- type: ndcg_at_1000 |
|
value: 41.499 |
|
- type: ndcg_at_20 |
|
value: 32.354 |
|
- type: ndcg_at_3 |
|
value: 26.434 |
|
- type: ndcg_at_5 |
|
value: 26.93 |
|
- type: precision_at_1 |
|
value: 29.938 |
|
- type: precision_at_10 |
|
value: 8.117 |
|
- type: precision_at_100 |
|
value: 1.611 |
|
- type: precision_at_1000 |
|
value: 0.232 |
|
- type: precision_at_20 |
|
value: 5.255 |
|
- type: precision_at_3 |
|
value: 17.49 |
|
- type: precision_at_5 |
|
value: 12.747 |
|
- type: recall_at_1 |
|
value: 14.804999999999998 |
|
- type: recall_at_10 |
|
value: 34.776 |
|
- type: recall_at_100 |
|
value: 66.279 |
|
- type: recall_at_1000 |
|
value: 89.96600000000001 |
|
- type: recall_at_20 |
|
value: 44.31 |
|
- type: recall_at_3 |
|
value: 23.623 |
|
- type: recall_at_5 |
|
value: 27.194000000000003 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: mteb/hotpotqa |
|
name: MTEB HotpotQA |
|
config: default |
|
split: test |
|
revision: ab518f4d6fcca38d87c25209f94beba119d02014 |
|
metrics: |
|
- type: map_at_1 |
|
value: 38.555 |
|
- type: map_at_10 |
|
value: 54.20700000000001 |
|
- type: map_at_100 |
|
value: 55.177 |
|
- type: map_at_1000 |
|
value: 55.254999999999995 |
|
- type: map_at_20 |
|
value: 54.788000000000004 |
|
- type: map_at_3 |
|
value: 51.034 |
|
- type: map_at_5 |
|
value: 52.998 |
|
- type: mrr_at_1 |
|
value: 77.11 |
|
- type: mrr_at_10 |
|
value: 82.93199999999999 |
|
- type: mrr_at_100 |
|
value: 83.14200000000001 |
|
- type: mrr_at_1000 |
|
value: 83.15 |
|
- type: mrr_at_20 |
|
value: 83.062 |
|
- type: mrr_at_3 |
|
value: 81.95599999999999 |
|
- type: mrr_at_5 |
|
value: 82.586 |
|
- type: ndcg_at_1 |
|
value: 77.11 |
|
- type: ndcg_at_10 |
|
value: 63.853 |
|
- type: ndcg_at_100 |
|
value: 67.18499999999999 |
|
- type: ndcg_at_1000 |
|
value: 68.676 |
|
- type: ndcg_at_20 |
|
value: 65.279 |
|
- type: ndcg_at_3 |
|
value: 59.301 |
|
- type: ndcg_at_5 |
|
value: 61.822 |
|
- type: precision_at_1 |
|
value: 77.11 |
|
- type: precision_at_10 |
|
value: 13.044 |
|
- type: precision_at_100 |
|
value: 1.5630000000000002 |
|
- type: precision_at_1000 |
|
value: 0.17600000000000002 |
|
- type: precision_at_20 |
|
value: 6.979 |
|
- type: precision_at_3 |
|
value: 36.759 |
|
- type: precision_at_5 |
|
value: 24.054000000000002 |
|
- type: recall_at_1 |
|
value: 38.555 |
|
- type: recall_at_10 |
|
value: 65.21900000000001 |
|
- type: recall_at_100 |
|
value: 78.16300000000001 |
|
- type: recall_at_1000 |
|
value: 88.02799999999999 |
|
- type: recall_at_20 |
|
value: 69.791 |
|
- type: recall_at_3 |
|
value: 55.138 |
|
- type: recall_at_5 |
|
value: 60.135000000000005 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/imdb |
|
name: MTEB ImdbClassification |
|
config: default |
|
split: test |
|
revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7 |
|
metrics: |
|
- type: accuracy |
|
value: 69.8728 |
|
- type: ap |
|
value: 63.98214492125858 |
|
- type: f1 |
|
value: 69.59975497754624 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/mtop_domain |
|
name: MTEB MTOPDomainClassification |
|
config: default |
|
split: test |
|
revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf |
|
metrics: |
|
- type: accuracy |
|
value: 94.76288189694483 |
|
- type: f1 |
|
value: 94.52150972672682 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/mtop_intent |
|
name: MTEB MTOPIntentClassification |
|
config: default |
|
split: test |
|
revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba |
|
metrics: |
|
- type: accuracy |
|
value: 76.83994528043777 |
|
- type: f1 |
|
value: 57.95571154189732 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/amazon_massive_intent |
|
name: MTEB MassiveIntentClassification |
|
config: default |
|
split: test |
|
revision: 4672e20407010da34463acc759c162ca9734bca6 |
|
metrics: |
|
- type: accuracy |
|
value: 46.1163416274378 |
|
- type: f1 |
|
value: 45.425692244093064 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/amazon_massive_scenario |
|
name: MTEB MassiveScenarioClassification |
|
config: default |
|
split: test |
|
revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8 |
|
metrics: |
|
- type: accuracy |
|
value: 45.57834566240753 |
|
- type: f1 |
|
value: 43.84840097785479 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: mteb/medrxiv-clustering-p2p |
|
name: MTEB MedrxivClusteringP2P |
|
config: default |
|
split: test |
|
revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73 |
|
metrics: |
|
- type: v_measure |
|
value: 32.86396397182615 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: mteb/medrxiv-clustering-s2s |
|
name: MTEB MedrxivClusteringS2S |
|
config: default |
|
split: test |
|
revision: 35191c8c0dca72d8ff3efcd72aa802307d469663 |
|
metrics: |
|
- type: v_measure |
|
value: 34.018965727588565 |
|
- task: |
|
type: Reranking |
|
dataset: |
|
type: mteb/mind_small |
|
name: MTEB MindSmallReranking |
|
config: default |
|
split: test |
|
revision: 59042f120c80e8afa9cdbb224f67076cec0fc9a7 |
|
metrics: |
|
- type: map |
|
value: 31.286618059824573 |
|
- type: mrr |
|
value: 32.481830769278965 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: mteb/nfcorpus |
|
name: MTEB NFCorpus |
|
config: default |
|
split: test |
|
revision: ec0fa4fe99da2ff19ca1214b7966684033a58814 |
|
metrics: |
|
- type: map_at_1 |
|
value: 4.236 |
|
- type: map_at_10 |
|
value: 9.352 |
|
- type: map_at_100 |
|
value: 12.382 |
|
- type: map_at_1000 |
|
value: 13.828999999999999 |
|
- type: map_at_20 |
|
value: 10.619 |
|
- type: map_at_3 |
|
value: 6.814000000000001 |
|
- type: map_at_5 |
|
value: 7.887 |
|
- type: mrr_at_1 |
|
value: 37.152 |
|
- type: mrr_at_10 |
|
value: 47.055 |
|
- type: mrr_at_100 |
|
value: 47.82 |
|
- type: mrr_at_1000 |
|
value: 47.86 |
|
- type: mrr_at_20 |
|
value: 47.605 |
|
- type: mrr_at_3 |
|
value: 44.118 |
|
- type: mrr_at_5 |
|
value: 46.115 |
|
- type: ndcg_at_1 |
|
value: 34.365 |
|
- type: ndcg_at_10 |
|
value: 28.473 |
|
- type: ndcg_at_100 |
|
value: 27.311999999999998 |
|
- type: ndcg_at_1000 |
|
value: 36.671 |
|
- type: ndcg_at_20 |
|
value: 27.137 |
|
- type: ndcg_at_3 |
|
value: 31.939 |
|
- type: ndcg_at_5 |
|
value: 30.428 |
|
- type: precision_at_1 |
|
value: 36.223 |
|
- type: precision_at_10 |
|
value: 21.858 |
|
- type: precision_at_100 |
|
value: 7.417999999999999 |
|
- type: precision_at_1000 |
|
value: 2.0709999999999997 |
|
- type: precision_at_20 |
|
value: 16.502 |
|
- type: precision_at_3 |
|
value: 30.857 |
|
- type: precision_at_5 |
|
value: 26.997 |
|
- type: recall_at_1 |
|
value: 4.236 |
|
- type: recall_at_10 |
|
value: 13.489 |
|
- type: recall_at_100 |
|
value: 29.580000000000002 |
|
- type: recall_at_1000 |
|
value: 62.726000000000006 |
|
- type: recall_at_20 |
|
value: 18.346999999999998 |
|
- type: recall_at_3 |
|
value: 7.811 |
|
- type: recall_at_5 |
|
value: 10.086 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: mteb/nq |
|
name: MTEB NQ |
|
config: default |
|
split: test |
|
revision: b774495ed302d8c44a3a7ea25c90dbce03968f31 |
|
metrics: |
|
- type: map_at_1 |
|
value: 21.123 |
|
- type: map_at_10 |
|
value: 34.429 |
|
- type: map_at_100 |
|
value: 35.803000000000004 |
|
- type: map_at_1000 |
|
value: 35.853 |
|
- type: map_at_20 |
|
value: 35.308 |
|
- type: map_at_3 |
|
value: 30.095 |
|
- type: map_at_5 |
|
value: 32.435 |
|
- type: mrr_at_1 |
|
value: 23.841 |
|
- type: mrr_at_10 |
|
value: 36.864999999999995 |
|
- type: mrr_at_100 |
|
value: 37.935 |
|
- type: mrr_at_1000 |
|
value: 37.97 |
|
- type: mrr_at_20 |
|
value: 37.566 |
|
- type: mrr_at_3 |
|
value: 32.918 |
|
- type: mrr_at_5 |
|
value: 35.11 |
|
- type: ndcg_at_1 |
|
value: 23.841 |
|
- type: ndcg_at_10 |
|
value: 42.043 |
|
- type: ndcg_at_100 |
|
value: 48.015 |
|
- type: ndcg_at_1000 |
|
value: 49.152 |
|
- type: ndcg_at_20 |
|
value: 44.936 |
|
- type: ndcg_at_3 |
|
value: 33.513999999999996 |
|
- type: ndcg_at_5 |
|
value: 37.541999999999994 |
|
- type: precision_at_1 |
|
value: 23.841 |
|
- type: precision_at_10 |
|
value: 7.454 |
|
- type: precision_at_100 |
|
value: 1.081 |
|
- type: precision_at_1000 |
|
value: 0.11900000000000001 |
|
- type: precision_at_20 |
|
value: 4.413 |
|
- type: precision_at_3 |
|
value: 15.672 |
|
- type: precision_at_5 |
|
value: 11.657 |
|
- type: recall_at_1 |
|
value: 21.123 |
|
- type: recall_at_10 |
|
value: 63.096 |
|
- type: recall_at_100 |
|
value: 89.27199999999999 |
|
- type: recall_at_1000 |
|
value: 97.69 |
|
- type: recall_at_20 |
|
value: 73.873 |
|
- type: recall_at_3 |
|
value: 40.588 |
|
- type: recall_at_5 |
|
value: 49.928 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: mteb/quora |
|
name: MTEB QuoraRetrieval |
|
config: default |
|
split: test |
|
revision: e4e08e0b7dbe3c8700f0daef558ff32256715259 |
|
metrics: |
|
- type: map_at_1 |
|
value: 70.255 |
|
- type: map_at_10 |
|
value: 84.387 |
|
- type: map_at_100 |
|
value: 85.027 |
|
- type: map_at_1000 |
|
value: 85.043 |
|
- type: map_at_20 |
|
value: 84.809 |
|
- type: map_at_3 |
|
value: 81.5 |
|
- type: map_at_5 |
|
value: 83.286 |
|
- type: mrr_at_1 |
|
value: 80.85 |
|
- type: mrr_at_10 |
|
value: 87.25699999999999 |
|
- type: mrr_at_100 |
|
value: 87.363 |
|
- type: mrr_at_1000 |
|
value: 87.363 |
|
- type: mrr_at_20 |
|
value: 87.336 |
|
- type: mrr_at_3 |
|
value: 86.357 |
|
- type: mrr_at_5 |
|
value: 86.939 |
|
- type: ndcg_at_1 |
|
value: 80.86 |
|
- type: ndcg_at_10 |
|
value: 88.151 |
|
- type: ndcg_at_100 |
|
value: 89.381 |
|
- type: ndcg_at_1000 |
|
value: 89.47800000000001 |
|
- type: ndcg_at_20 |
|
value: 88.82100000000001 |
|
- type: ndcg_at_3 |
|
value: 85.394 |
|
- type: ndcg_at_5 |
|
value: 86.855 |
|
- type: precision_at_1 |
|
value: 80.86 |
|
- type: precision_at_10 |
|
value: 13.397 |
|
- type: precision_at_100 |
|
value: 1.5310000000000001 |
|
- type: precision_at_1000 |
|
value: 0.157 |
|
- type: precision_at_20 |
|
value: 7.106999999999999 |
|
- type: precision_at_3 |
|
value: 37.46 |
|
- type: precision_at_5 |
|
value: 24.568 |
|
- type: recall_at_1 |
|
value: 70.255 |
|
- type: recall_at_10 |
|
value: 95.405 |
|
- type: recall_at_100 |
|
value: 99.56 |
|
- type: recall_at_1000 |
|
value: 99.98599999999999 |
|
- type: recall_at_20 |
|
value: 97.544 |
|
- type: recall_at_3 |
|
value: 87.414 |
|
- type: recall_at_5 |
|
value: 91.598 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: mteb/reddit-clustering |
|
name: MTEB RedditClustering |
|
config: default |
|
split: test |
|
revision: 24640382cdbf8abc73003fb0fa6d111a705499eb |
|
metrics: |
|
- type: v_measure |
|
value: 54.7557403999403 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: mteb/reddit-clustering-p2p |
|
name: MTEB RedditClusteringP2P |
|
config: default |
|
split: test |
|
revision: 385e3cb46b4cfa89021f56c4380204149d0efe33 |
|
metrics: |
|
- type: v_measure |
|
value: 56.2773308957202 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: mteb/scidocs |
|
name: MTEB SCIDOCS |
|
config: default |
|
split: test |
|
revision: f8c2fcf00f625baaa80f62ec5bd9e1fff3b8ae88 |
|
metrics: |
|
- type: map_at_1 |
|
value: 4.123 |
|
- type: map_at_10 |
|
value: 9.940999999999999 |
|
- type: map_at_100 |
|
value: 11.928999999999998 |
|
- type: map_at_1000 |
|
value: 12.257 |
|
- type: map_at_20 |
|
value: 10.866000000000001 |
|
- type: map_at_3 |
|
value: 7.091 |
|
- type: map_at_5 |
|
value: 8.393 |
|
- type: mrr_at_1 |
|
value: 20.3 |
|
- type: mrr_at_10 |
|
value: 30.068 |
|
- type: mrr_at_100 |
|
value: 31.296000000000003 |
|
- type: mrr_at_1000 |
|
value: 31.36 |
|
- type: mrr_at_20 |
|
value: 30.756 |
|
- type: mrr_at_3 |
|
value: 26.667 |
|
- type: mrr_at_5 |
|
value: 28.616999999999997 |
|
- type: ndcg_at_1 |
|
value: 20.3 |
|
- type: ndcg_at_10 |
|
value: 17.305 |
|
- type: ndcg_at_100 |
|
value: 25.529000000000003 |
|
- type: ndcg_at_1000 |
|
value: 31.41 |
|
- type: ndcg_at_20 |
|
value: 19.967 |
|
- type: ndcg_at_3 |
|
value: 16.022 |
|
- type: ndcg_at_5 |
|
value: 14.12 |
|
- type: precision_at_1 |
|
value: 20.3 |
|
- type: precision_at_10 |
|
value: 9.06 |
|
- type: precision_at_100 |
|
value: 2.103 |
|
- type: precision_at_1000 |
|
value: 0.35200000000000004 |
|
- type: precision_at_20 |
|
value: 6.075 |
|
- type: precision_at_3 |
|
value: 14.832999999999998 |
|
- type: precision_at_5 |
|
value: 12.36 |
|
- type: recall_at_1 |
|
value: 4.123 |
|
- type: recall_at_10 |
|
value: 18.383 |
|
- type: recall_at_100 |
|
value: 42.67 |
|
- type: recall_at_1000 |
|
value: 71.44800000000001 |
|
- type: recall_at_20 |
|
value: 24.64 |
|
- type: recall_at_3 |
|
value: 9.043 |
|
- type: recall_at_5 |
|
value: 12.543000000000001 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: mteb/sickr-sts |
|
name: MTEB SICK-R |
|
config: default |
|
split: test |
|
revision: 20a6d6f312dd54037fe07a32d58e5e168867909d |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 84.37101718384514 |
|
- type: cos_sim_spearman |
|
value: 80.73657031880697 |
|
- type: euclidean_pearson |
|
value: 81.42351850520845 |
|
- type: euclidean_spearman |
|
value: 80.81452496851979 |
|
- type: manhattan_pearson |
|
value: 81.47676252115669 |
|
- type: manhattan_spearman |
|
value: 80.87566944708885 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: mteb/sts12-sts |
|
name: MTEB STS12 |
|
config: default |
|
split: test |
|
revision: a0d554a64d88156834ff5ae9920b964011b16384 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 84.79559176971591 |
|
- type: cos_sim_spearman |
|
value: 75.41866597445552 |
|
- type: euclidean_pearson |
|
value: 83.20287101163838 |
|
- type: euclidean_spearman |
|
value: 75.54564777571143 |
|
- type: manhattan_pearson |
|
value: 83.24622548900163 |
|
- type: manhattan_spearman |
|
value: 75.63826258190343 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: mteb/sts13-sts |
|
name: MTEB STS13 |
|
config: default |
|
split: test |
|
revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 84.63322096299294 |
|
- type: cos_sim_spearman |
|
value: 85.48272638914783 |
|
- type: euclidean_pearson |
|
value: 85.57327707819331 |
|
- type: euclidean_spearman |
|
value: 85.90735298172922 |
|
- type: manhattan_pearson |
|
value: 85.5744191274933 |
|
- type: manhattan_spearman |
|
value: 85.90828008488766 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: mteb/sts14-sts |
|
name: MTEB STS14 |
|
config: default |
|
split: test |
|
revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 82.05530140566407 |
|
- type: cos_sim_spearman |
|
value: 78.85454907951474 |
|
- type: euclidean_pearson |
|
value: 81.4307311680376 |
|
- type: euclidean_spearman |
|
value: 78.99131623529348 |
|
- type: manhattan_pearson |
|
value: 81.46870892683134 |
|
- type: manhattan_spearman |
|
value: 79.05473823658481 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: mteb/sts15-sts |
|
name: MTEB STS15 |
|
config: default |
|
split: test |
|
revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 83.66620817683379 |
|
- type: cos_sim_spearman |
|
value: 85.23347998035328 |
|
- type: euclidean_pearson |
|
value: 84.59001637865366 |
|
- type: euclidean_spearman |
|
value: 85.0081410316597 |
|
- type: manhattan_pearson |
|
value: 84.59742325369818 |
|
- type: manhattan_spearman |
|
value: 85.01721329704324 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: mteb/sts16-sts |
|
name: MTEB STS16 |
|
config: default |
|
split: test |
|
revision: 4d8694f8f0e0100860b497b999b3dbed754a0513 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 79.86344730144208 |
|
- type: cos_sim_spearman |
|
value: 82.15966778685441 |
|
- type: euclidean_pearson |
|
value: 81.85580574642779 |
|
- type: euclidean_spearman |
|
value: 82.06482873417123 |
|
- type: manhattan_pearson |
|
value: 81.82971046102377 |
|
- type: manhattan_spearman |
|
value: 82.04185436355144 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: mteb/sts17-crosslingual-sts |
|
name: MTEB STS17 |
|
config: default |
|
split: test |
|
revision: faeb762787bd10488a50c8b5be4a3b82e411949c |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 31.440481026661672 |
|
- type: cos_sim_spearman |
|
value: 31.592743544965913 |
|
- type: euclidean_pearson |
|
value: 31.15111049327518 |
|
- type: euclidean_spearman |
|
value: 30.555124184361464 |
|
- type: manhattan_pearson |
|
value: 31.724139249295654 |
|
- type: manhattan_spearman |
|
value: 30.483389245793504 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: mteb/sts22-crosslingual-sts |
|
name: MTEB STS22 |
|
config: default |
|
split: test |
|
revision: de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 34.51489724275415 |
|
- type: cos_sim_spearman |
|
value: 47.06532141601629 |
|
- type: euclidean_pearson |
|
value: 33.28904737503036 |
|
- type: euclidean_spearman |
|
value: 45.111172981641865 |
|
- type: manhattan_pearson |
|
value: 33.36374172942392 |
|
- type: manhattan_spearman |
|
value: 45.100940945158534 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: mteb/stsbenchmark-sts |
|
name: MTEB STSBenchmark |
|
config: default |
|
split: test |
|
revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 82.09996292950329 |
|
- type: cos_sim_spearman |
|
value: 82.69376206796092 |
|
- type: euclidean_pearson |
|
value: 82.83254956369134 |
|
- type: euclidean_spearman |
|
value: 82.34202999843637 |
|
- type: manhattan_pearson |
|
value: 82.8048494319632 |
|
- type: manhattan_spearman |
|
value: 82.34713123336984 |
|
- task: |
|
type: Reranking |
|
dataset: |
|
type: mteb/scidocs-reranking |
|
name: MTEB SciDocsRR |
|
config: default |
|
split: test |
|
revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab |
|
metrics: |
|
- type: map |
|
value: 82.1402269601644 |
|
- type: mrr |
|
value: 94.84447197682492 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: mteb/scifact |
|
name: MTEB SciFact |
|
config: default |
|
split: test |
|
revision: 0228b52cf27578f30900b9e5271d331663a030d7 |
|
metrics: |
|
- type: map_at_1 |
|
value: 49.138999999999996 |
|
- type: map_at_10 |
|
value: 60.288 |
|
- type: map_at_100 |
|
value: 61.082 |
|
- type: map_at_1000 |
|
value: 61.11 |
|
- type: map_at_20 |
|
value: 60.831999999999994 |
|
- type: map_at_3 |
|
value: 57.106 |
|
- type: map_at_5 |
|
value: 58.857000000000006 |
|
- type: mrr_at_1 |
|
value: 51.333 |
|
- type: mrr_at_10 |
|
value: 61.364 |
|
- type: mrr_at_100 |
|
value: 62.029999999999994 |
|
- type: mrr_at_1000 |
|
value: 62.056 |
|
- type: mrr_at_20 |
|
value: 61.85000000000001 |
|
- type: mrr_at_3 |
|
value: 58.721999999999994 |
|
- type: mrr_at_5 |
|
value: 60.221999999999994 |
|
- type: ndcg_at_1 |
|
value: 51.333 |
|
- type: ndcg_at_10 |
|
value: 65.71900000000001 |
|
- type: ndcg_at_100 |
|
value: 69.036 |
|
- type: ndcg_at_1000 |
|
value: 69.626 |
|
- type: ndcg_at_20 |
|
value: 67.571 |
|
- type: ndcg_at_3 |
|
value: 60.019 |
|
- type: ndcg_at_5 |
|
value: 62.733000000000004 |
|
- type: precision_at_1 |
|
value: 51.333 |
|
- type: precision_at_10 |
|
value: 9.067 |
|
- type: precision_at_100 |
|
value: 1.083 |
|
- type: precision_at_1000 |
|
value: 0.11299999999999999 |
|
- type: precision_at_20 |
|
value: 4.95 |
|
- type: precision_at_3 |
|
value: 23.889 |
|
- type: precision_at_5 |
|
value: 16.0 |
|
- type: recall_at_1 |
|
value: 49.138999999999996 |
|
- type: recall_at_10 |
|
value: 81.256 |
|
- type: recall_at_100 |
|
value: 95.6 |
|
- type: recall_at_1000 |
|
value: 100.0 |
|
- type: recall_at_20 |
|
value: 88.289 |
|
- type: recall_at_3 |
|
value: 66.078 |
|
- type: recall_at_5 |
|
value: 72.661 |
|
- task: |
|
type: PairClassification |
|
dataset: |
|
type: mteb/sprintduplicatequestions-pairclassification |
|
name: MTEB SprintDuplicateQuestions |
|
config: default |
|
split: test |
|
revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46 |
|
metrics: |
|
- type: cos_sim_accuracy |
|
value: 99.73762376237623 |
|
- type: cos_sim_ap |
|
value: 93.02149432690442 |
|
- type: cos_sim_f1 |
|
value: 86.59079663532904 |
|
- type: cos_sim_precision |
|
value: 85.70029382957884 |
|
- type: cos_sim_recall |
|
value: 87.5 |
|
- type: dot_accuracy |
|
value: 99.73267326732673 |
|
- type: dot_ap |
|
value: 92.38661051842968 |
|
- type: dot_f1 |
|
value: 85.92283628779978 |
|
- type: dot_precision |
|
value: 89.76034858387798 |
|
- type: dot_recall |
|
value: 82.39999999999999 |
|
- type: euclidean_accuracy |
|
value: 99.73960396039604 |
|
- type: euclidean_ap |
|
value: 92.99557708360517 |
|
- type: euclidean_f1 |
|
value: 86.49183572488866 |
|
- type: euclidean_precision |
|
value: 85.60235063663075 |
|
- type: euclidean_recall |
|
value: 87.4 |
|
- type: manhattan_accuracy |
|
value: 99.74059405940594 |
|
- type: manhattan_ap |
|
value: 93.24237279644005 |
|
- type: manhattan_f1 |
|
value: 86.77727501256913 |
|
- type: manhattan_precision |
|
value: 87.25985844287159 |
|
- type: manhattan_recall |
|
value: 86.3 |
|
- type: max_accuracy |
|
value: 99.74059405940594 |
|
- type: max_ap |
|
value: 93.24237279644005 |
|
- type: max_f1 |
|
value: 86.77727501256913 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: mteb/stackexchange-clustering |
|
name: MTEB StackExchangeClustering |
|
config: default |
|
split: test |
|
revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259 |
|
metrics: |
|
- type: v_measure |
|
value: 63.94924261127149 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: mteb/stackexchange-clustering-p2p |
|
name: MTEB StackExchangeClusteringP2P |
|
config: default |
|
split: test |
|
revision: 815ca46b2622cec33ccafc3735d572c266efdb44 |
|
metrics: |
|
- type: v_measure |
|
value: 32.22297034902405 |
|
- task: |
|
type: Reranking |
|
dataset: |
|
type: mteb/stackoverflowdupquestions-reranking |
|
name: MTEB StackOverflowDupQuestions |
|
config: default |
|
split: test |
|
revision: e185fbe320c72810689fc5848eb6114e1ef5ec69 |
|
metrics: |
|
- type: map |
|
value: 46.12948438780115 |
|
- type: mrr |
|
value: 46.77186783804431 |
|
- task: |
|
type: Summarization |
|
dataset: |
|
type: mteb/summeval |
|
name: MTEB SummEval |
|
config: default |
|
split: test |
|
revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 30.02235612863601 |
|
- type: cos_sim_spearman |
|
value: 30.567504287706598 |
|
- type: dot_pearson |
|
value: 28.943978981614897 |
|
- type: dot_spearman |
|
value: 29.905635915797358 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: mteb/trec-covid |
|
name: MTEB TRECCOVID |
|
config: default |
|
split: test |
|
revision: bb9466bac8153a0349341eb1b22e06409e78ef4e |
|
metrics: |
|
- type: map_at_1 |
|
value: 0.173 |
|
- type: map_at_10 |
|
value: 1.124 |
|
- type: map_at_100 |
|
value: 5.645 |
|
- type: map_at_1000 |
|
value: 14.965 |
|
- type: map_at_20 |
|
value: 1.876 |
|
- type: map_at_3 |
|
value: 0.45599999999999996 |
|
- type: map_at_5 |
|
value: 0.699 |
|
- type: mrr_at_1 |
|
value: 70.0 |
|
- type: mrr_at_10 |
|
value: 81.786 |
|
- type: mrr_at_100 |
|
value: 81.786 |
|
- type: mrr_at_1000 |
|
value: 81.786 |
|
- type: mrr_at_20 |
|
value: 81.786 |
|
- type: mrr_at_3 |
|
value: 80.0 |
|
- type: mrr_at_5 |
|
value: 81.5 |
|
- type: ndcg_at_1 |
|
value: 65.0 |
|
- type: ndcg_at_10 |
|
value: 53.88699999999999 |
|
- type: ndcg_at_100 |
|
value: 38.028 |
|
- type: ndcg_at_1000 |
|
value: 37.183 |
|
- type: ndcg_at_20 |
|
value: 49.286 |
|
- type: ndcg_at_3 |
|
value: 63.05 |
|
- type: ndcg_at_5 |
|
value: 59.49100000000001 |
|
- type: precision_at_1 |
|
value: 70.0 |
|
- type: precision_at_10 |
|
value: 55.400000000000006 |
|
- type: precision_at_100 |
|
value: 38.800000000000004 |
|
- type: precision_at_1000 |
|
value: 17.082 |
|
- type: precision_at_20 |
|
value: 50.7 |
|
- type: precision_at_3 |
|
value: 66.667 |
|
- type: precision_at_5 |
|
value: 62.4 |
|
- type: recall_at_1 |
|
value: 0.173 |
|
- type: recall_at_10 |
|
value: 1.353 |
|
- type: recall_at_100 |
|
value: 8.887 |
|
- type: recall_at_1000 |
|
value: 36.012 |
|
- type: recall_at_20 |
|
value: 2.476 |
|
- type: recall_at_3 |
|
value: 0.508 |
|
- type: recall_at_5 |
|
value: 0.795 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: mteb/touche2020 |
|
name: MTEB Touche2020 |
|
config: default |
|
split: test |
|
revision: a34f9a33db75fa0cbb21bb5cfc3dae8dc8bec93f |
|
metrics: |
|
- type: map_at_1 |
|
value: 2.614 |
|
- type: map_at_10 |
|
value: 6.651999999999999 |
|
- type: map_at_100 |
|
value: 11.59 |
|
- type: map_at_1000 |
|
value: 13.044 |
|
- type: map_at_20 |
|
value: 8.702 |
|
- type: map_at_3 |
|
value: 4.159 |
|
- type: map_at_5 |
|
value: 5.327 |
|
- type: mrr_at_1 |
|
value: 30.612000000000002 |
|
- type: mrr_at_10 |
|
value: 42.664 |
|
- type: mrr_at_100 |
|
value: 43.957 |
|
- type: mrr_at_1000 |
|
value: 43.957 |
|
- type: mrr_at_20 |
|
value: 43.193 |
|
- type: mrr_at_3 |
|
value: 40.476 |
|
- type: mrr_at_5 |
|
value: 42.007 |
|
- type: ndcg_at_1 |
|
value: 27.551 |
|
- type: ndcg_at_10 |
|
value: 18.098 |
|
- type: ndcg_at_100 |
|
value: 30.019000000000002 |
|
- type: ndcg_at_1000 |
|
value: 42.179 |
|
- type: ndcg_at_20 |
|
value: 19.552 |
|
- type: ndcg_at_3 |
|
value: 21.22 |
|
- type: ndcg_at_5 |
|
value: 19.774 |
|
- type: precision_at_1 |
|
value: 30.612000000000002 |
|
- type: precision_at_10 |
|
value: 15.101999999999999 |
|
- type: precision_at_100 |
|
value: 6.510000000000001 |
|
- type: precision_at_1000 |
|
value: 1.4569999999999999 |
|
- type: precision_at_20 |
|
value: 12.449 |
|
- type: precision_at_3 |
|
value: 22.448999999999998 |
|
- type: precision_at_5 |
|
value: 19.592000000000002 |
|
- type: recall_at_1 |
|
value: 2.614 |
|
- type: recall_at_10 |
|
value: 11.068 |
|
- type: recall_at_100 |
|
value: 42.317 |
|
- type: recall_at_1000 |
|
value: 79.063 |
|
- type: recall_at_20 |
|
value: 18.589 |
|
- type: recall_at_3 |
|
value: 5.06 |
|
- type: recall_at_5 |
|
value: 7.356 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/toxic_conversations_50k |
|
name: MTEB ToxicConversationsClassification |
|
config: default |
|
split: test |
|
revision: edfaf9da55d3dd50d43143d90c1ac476895ae6de |
|
metrics: |
|
- type: accuracy |
|
value: 75.0146484375 |
|
- type: ap |
|
value: 16.80191476928431 |
|
- type: f1 |
|
value: 58.08037205204817 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/tweet_sentiment_extraction |
|
name: MTEB TweetSentimentExtractionClassification |
|
config: default |
|
split: test |
|
revision: d604517c81ca91fe16a244d1248fc021f9ecee7a |
|
metrics: |
|
- type: accuracy |
|
value: 61.80249009620826 |
|
- type: f1 |
|
value: 62.24155926661914 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: mteb/twentynewsgroups-clustering |
|
name: MTEB TwentyNewsgroupsClustering |
|
config: default |
|
split: test |
|
revision: 6125ec4e24fa026cec8a478383ee943acfbd5449 |
|
metrics: |
|
- type: v_measure |
|
value: 47.074846780747094 |
|
- task: |
|
type: PairClassification |
|
dataset: |
|
type: mteb/twittersemeval2015-pairclassification |
|
name: MTEB TwitterSemEval2015 |
|
config: default |
|
split: test |
|
revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1 |
|
metrics: |
|
- type: cos_sim_accuracy |
|
value: 85.21785778148656 |
|
- type: cos_sim_ap |
|
value: 71.06584074764645 |
|
- type: cos_sim_f1 |
|
value: 65.81720166625826 |
|
- type: cos_sim_precision |
|
value: 61.43641354071363 |
|
- type: cos_sim_recall |
|
value: 70.87071240105541 |
|
- type: dot_accuracy |
|
value: 84.30589497526375 |
|
- type: dot_ap |
|
value: 68.85872202019365 |
|
- type: dot_f1 |
|
value: 64.20295157946092 |
|
- type: dot_precision |
|
value: 59.69607620775687 |
|
- type: dot_recall |
|
value: 69.44591029023746 |
|
- type: euclidean_accuracy |
|
value: 85.21189724026942 |
|
- type: euclidean_ap |
|
value: 71.18847194129523 |
|
- type: euclidean_f1 |
|
value: 66.00049962528105 |
|
- type: euclidean_precision |
|
value: 62.66603415559773 |
|
- type: euclidean_recall |
|
value: 69.70976253298153 |
|
- type: manhattan_accuracy |
|
value: 85.25958157000656 |
|
- type: manhattan_ap |
|
value: 71.12967638566641 |
|
- type: manhattan_f1 |
|
value: 65.77477594492791 |
|
- type: manhattan_precision |
|
value: 64.77359938603223 |
|
- type: manhattan_recall |
|
value: 66.80738786279683 |
|
- type: max_accuracy |
|
value: 85.25958157000656 |
|
- type: max_ap |
|
value: 71.18847194129523 |
|
- type: max_f1 |
|
value: 66.00049962528105 |
|
- task: |
|
type: PairClassification |
|
dataset: |
|
type: mteb/twitterurlcorpus-pairclassification |
|
name: MTEB TwitterURLCorpus |
|
config: default |
|
split: test |
|
revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf |
|
metrics: |
|
- type: cos_sim_accuracy |
|
value: 88.22330888345559 |
|
- type: cos_sim_ap |
|
value: 84.40304506741951 |
|
- type: cos_sim_f1 |
|
value: 76.46823520855303 |
|
- type: cos_sim_precision |
|
value: 72.45537867824409 |
|
- type: cos_sim_recall |
|
value: 80.95164767477672 |
|
- type: dot_accuracy |
|
value: 87.9400007761866 |
|
- type: dot_ap |
|
value: 83.63499141834609 |
|
- type: dot_f1 |
|
value: 75.98620939938304 |
|
- type: dot_precision |
|
value: 71.86792064254823 |
|
- type: dot_recall |
|
value: 80.60517400677548 |
|
- type: euclidean_accuracy |
|
value: 88.21166608452671 |
|
- type: euclidean_ap |
|
value: 84.40463988450605 |
|
- type: euclidean_f1 |
|
value: 76.52312831312177 |
|
- type: euclidean_precision |
|
value: 72.40621135083138 |
|
- type: euclidean_recall |
|
value: 81.13643363104404 |
|
- type: manhattan_accuracy |
|
value: 88.24659448131331 |
|
- type: manhattan_ap |
|
value: 84.42287495905447 |
|
- type: manhattan_f1 |
|
value: 76.54849595413475 |
|
- type: manhattan_precision |
|
value: 72.39036442248302 |
|
- type: manhattan_recall |
|
value: 81.21342777948875 |
|
- type: max_accuracy |
|
value: 88.24659448131331 |
|
- type: max_ap |
|
value: 84.42287495905447 |
|
- type: max_f1 |
|
value: 76.54849595413475 |
|
--- |
|
|
|
# b1ade-embed-kd |
|
|
|
This is a [sentence-transformers](https://www.SBERT.net) model: It maps sentences & paragraphs to a 1024 dimensional dense vector space and can be used for tasks like clustering or semantic search. |
|
|
|
<!--- 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}) |
|
|
|
|
|
## Training |
|
The model was distilled with teacher model as |
|
|
|
|
|
and student model as b1ade-embed |
|
|
|
**DataLoader**: |
|
|
|
`torch.utils.data.dataloader.DataLoader` of length 275105 with parameters: |
|
``` |
|
{'batch_size': 32, 'sampler': 'torch.utils.data.sampler.RandomSampler', 'batch_sampler': 'torch.utils.data.sampler.BatchSampler'} |
|
``` |
|
|
|
**Loss**: |
|
|
|
`sentence_transformers.losses.MSELoss.MSELoss` |
|
|
|
Parameters of the fit()-Method: |
|
``` |
|
{ |
|
"epochs": 3, |
|
"evaluation_steps": 5000, |
|
"evaluator": "sentence_transformers.evaluation.SequentialEvaluator.SequentialEvaluator", |
|
"max_grad_norm": 1, |
|
"optimizer_class": "<class 'torch.optim.adamw.AdamW'>", |
|
"optimizer_params": { |
|
"eps": 1e-06, |
|
"lr": 5e-05 |
|
}, |
|
"scheduler": "WarmupLinear", |
|
"steps_per_epoch": null, |
|
"warmup_steps": 1000, |
|
"weight_decay": 0.01 |
|
} |
|
``` |
|
|
|
|
|
## Full Model Architecture |
|
``` |
|
SentenceTransformer( |
|
(0): Transformer({'max_seq_length': 512, 'do_lower_case': False}) with Transformer model: BertModel |
|
(1): Pooling({'word_embedding_dimension': 1024, 'pooling_mode_cls_token': False, 'pooling_mode_mean_tokens': True, 'pooling_mode_max_tokens': False, 'pooling_mode_mean_sqrt_len_tokens': False, 'pooling_mode_weightedmean_tokens': False, 'pooling_mode_lasttoken': False, 'include_prompt': True}) |
|
) |
|
``` |
|
|
|
## Results: |
|
|
|
Good agreement with teacher model, at least on STS: |
|
|
|
Teacher: |
|
``` |
|
2024-05-20 16:29:07 - Teacher Performance: |
|
2024-05-20 16:29:07 - EmbeddingSimilarityEvaluator: Evaluating the model on the sts-dev dataset: |
|
2024-05-20 16:29:12 - Cosine-Similarity : Pearson: 0.8561 Spearman: 0.8597 |
|
2024-05-20 16:29:12 - Manhattan-Distance: Pearson: 0.8569 Spearman: 0.8567 |
|
2024-05-20 16:29:12 - Euclidean-Distance: Pearson: 0.8575 Spearman: 0.8571 |
|
2024-05-20 16:29:12 - Dot-Product-Similarity: Pearson: 0.8624 Spearman: 0.8662 |
|
``` |
|
|
|
Student: |
|
``` |
|
2024-05-20 16:29:12 - Student Performance: |
|
2024-05-20 16:29:12 - EmbeddingSimilarityEvaluator: Evaluating the model on the sts-dev dataset: |
|
2024-05-20 16:29:17 - Cosine-Similarity : Pearson: 0.8561 Spearman: 0.8597 |
|
2024-05-20 16:29:17 - Manhattan-Distance: Pearson: 0.8569 Spearman: 0.8567 |
|
2024-05-20 16:29:17 - Euclidean-Distance: Pearson: 0.8575 Spearman: 0.8571 |
|
2024-05-20 16:29:17 - Dot-Product-Similarity: Pearson: 0.8624 Spearman: 0.8662 |
|
``` |
