|
--- |
|
tags: |
|
- mteb |
|
model-index: |
|
- name: nomic_classification_307_w50k_b30k |
|
results: |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: None |
|
name: MTEB AmazonCounterfactualClassification (en) |
|
config: en |
|
split: test |
|
revision: e8379541af4e31359cca9fbcf4b00f2671dba205 |
|
metrics: |
|
- type: accuracy |
|
value: 72.04477611940298 |
|
- type: ap |
|
value: 34.133147681736574 |
|
- type: f1 |
|
value: 65.73569090089603 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: None |
|
name: MTEB AmazonPolarityClassification |
|
config: default |
|
split: test |
|
revision: e2d317d38cd51312af73b3d32a06d1a08b442046 |
|
metrics: |
|
- type: accuracy |
|
value: 64.6129 |
|
- type: ap |
|
value: 59.73474867106533 |
|
- type: f1 |
|
value: 64.37745361254407 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: None |
|
name: MTEB AmazonReviewsClassification (en) |
|
config: en |
|
split: test |
|
revision: 1399c76144fd37290681b995c656ef9b2e06e26d |
|
metrics: |
|
- type: accuracy |
|
value: 33.86000000000001 |
|
- type: f1 |
|
value: 33.4167439582646 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB ArguAna |
|
config: default |
|
split: test |
|
revision: c22ab2a51041ffd869aaddef7af8d8215647e41a |
|
metrics: |
|
- type: map_at_1 |
|
value: 20.555 |
|
- type: map_at_10 |
|
value: 34.29 |
|
- type: map_at_100 |
|
value: 35.473 |
|
- type: map_at_1000 |
|
value: 35.498000000000005 |
|
- type: map_at_3 |
|
value: 29.753 |
|
- type: map_at_5 |
|
value: 32.257000000000005 |
|
- type: mrr_at_1 |
|
value: 21.266 |
|
- type: mrr_at_10 |
|
value: 34.571000000000005 |
|
- type: mrr_at_100 |
|
value: 35.732 |
|
- type: mrr_at_1000 |
|
value: 35.758 |
|
- type: mrr_at_3 |
|
value: 30.037999999999997 |
|
- type: mrr_at_5 |
|
value: 32.492 |
|
- type: ndcg_at_1 |
|
value: 20.555 |
|
- type: ndcg_at_10 |
|
value: 42.283 |
|
- type: ndcg_at_100 |
|
value: 47.904 |
|
- type: ndcg_at_1000 |
|
value: 48.518 |
|
- type: ndcg_at_3 |
|
value: 32.845 |
|
- type: ndcg_at_5 |
|
value: 37.372 |
|
- type: precision_at_1 |
|
value: 20.555 |
|
- type: precision_at_10 |
|
value: 6.7989999999999995 |
|
- type: precision_at_100 |
|
value: 0.9400000000000001 |
|
- type: precision_at_1000 |
|
value: 0.099 |
|
- type: precision_at_3 |
|
value: 13.94 |
|
- type: precision_at_5 |
|
value: 10.569 |
|
- type: recall_at_1 |
|
value: 20.555 |
|
- type: recall_at_10 |
|
value: 67.994 |
|
- type: recall_at_100 |
|
value: 93.95400000000001 |
|
- type: recall_at_1000 |
|
value: 98.649 |
|
- type: recall_at_3 |
|
value: 41.821000000000005 |
|
- type: recall_at_5 |
|
value: 52.845 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: None |
|
name: MTEB ArxivClusteringP2P |
|
config: default |
|
split: test |
|
revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d |
|
metrics: |
|
- type: v_measure |
|
value: 31.705177661382283 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: None |
|
name: MTEB ArxivClusteringS2S |
|
config: default |
|
split: test |
|
revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53 |
|
metrics: |
|
- type: v_measure |
|
value: 21.93065120477086 |
|
- task: |
|
type: Reranking |
|
dataset: |
|
type: None |
|
name: MTEB AskUbuntuDupQuestions |
|
config: default |
|
split: test |
|
revision: 2000358ca161889fa9c082cb41daa8dcfb161a54 |
|
metrics: |
|
- type: map |
|
value: 52.52224532394495 |
|
- type: mrr |
|
value: 66.04625599085433 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: None |
|
name: MTEB BIOSSES |
|
config: default |
|
split: test |
|
revision: d3fb88f8f02e40887cd149695127462bbcf29b4a |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 78.75516031950443 |
|
- type: cos_sim_spearman |
|
value: 76.92645161656596 |
|
- type: euclidean_pearson |
|
value: 78.07410163583403 |
|
- type: euclidean_spearman |
|
value: 76.92645161656596 |
|
- type: manhattan_pearson |
|
value: 77.99272531232194 |
|
- type: manhattan_spearman |
|
value: 76.85596808284 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: None |
|
name: MTEB Banking77Classification |
|
config: default |
|
split: test |
|
revision: 0fd18e25b25c072e09e0d92ab615fda904d66300 |
|
metrics: |
|
- type: accuracy |
|
value: 72.29220779220779 |
|
- type: f1 |
|
value: 71.45293655648962 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: None |
|
name: MTEB BiorxivClusteringP2P |
|
config: default |
|
split: test |
|
revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40 |
|
metrics: |
|
- type: v_measure |
|
value: 29.683083608126136 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: None |
|
name: MTEB BiorxivClusteringS2S |
|
config: default |
|
split: test |
|
revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908 |
|
metrics: |
|
- type: v_measure |
|
value: 20.115223677732263 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB CQADupstackAndroidRetrieval |
|
config: default |
|
split: test |
|
revision: f46a197baaae43b4f621051089b82a364682dfeb |
|
metrics: |
|
- type: map_at_1 |
|
value: 21.508 |
|
- type: map_at_10 |
|
value: 28.613 |
|
- type: map_at_100 |
|
value: 29.694 |
|
- type: map_at_1000 |
|
value: 29.848000000000003 |
|
- type: map_at_3 |
|
value: 26.444000000000003 |
|
- type: map_at_5 |
|
value: 27.705000000000002 |
|
- type: mrr_at_1 |
|
value: 27.039 |
|
- type: mrr_at_10 |
|
value: 34.28 |
|
- type: mrr_at_100 |
|
value: 35.156 |
|
- type: mrr_at_1000 |
|
value: 35.229 |
|
- type: mrr_at_3 |
|
value: 32.546 |
|
- type: mrr_at_5 |
|
value: 33.541 |
|
- type: ndcg_at_1 |
|
value: 27.039 |
|
- type: ndcg_at_10 |
|
value: 33.157 |
|
- type: ndcg_at_100 |
|
value: 38.172 |
|
- type: ndcg_at_1000 |
|
value: 41.407 |
|
- type: ndcg_at_3 |
|
value: 30.293999999999997 |
|
- type: ndcg_at_5 |
|
value: 31.540000000000003 |
|
- type: precision_at_1 |
|
value: 27.039 |
|
- type: precision_at_10 |
|
value: 6.223 |
|
- type: precision_at_100 |
|
value: 1.087 |
|
- type: precision_at_1000 |
|
value: 0.166 |
|
- type: precision_at_3 |
|
value: 14.688 |
|
- type: precision_at_5 |
|
value: 10.501000000000001 |
|
- type: recall_at_1 |
|
value: 21.508 |
|
- type: recall_at_10 |
|
value: 40.608 |
|
- type: recall_at_100 |
|
value: 63.131 |
|
- type: recall_at_1000 |
|
value: 85.292 |
|
- type: recall_at_3 |
|
value: 31.283 |
|
- type: recall_at_5 |
|
value: 35.237 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB CQADupstackEnglishRetrieval |
|
config: default |
|
split: test |
|
revision: ad9991cb51e31e31e430383c75ffb2885547b5f0 |
|
metrics: |
|
- type: map_at_1 |
|
value: 16.338 |
|
- type: map_at_10 |
|
value: 21.65 |
|
- type: map_at_100 |
|
value: 22.549 |
|
- type: map_at_1000 |
|
value: 22.675 |
|
- type: map_at_3 |
|
value: 19.888 |
|
- type: map_at_5 |
|
value: 20.848 |
|
- type: mrr_at_1 |
|
value: 20.764 |
|
- type: mrr_at_10 |
|
value: 25.8 |
|
- type: mrr_at_100 |
|
value: 26.590000000000003 |
|
- type: mrr_at_1000 |
|
value: 26.663999999999998 |
|
- type: mrr_at_3 |
|
value: 24.066000000000003 |
|
- type: mrr_at_5 |
|
value: 24.907 |
|
- type: ndcg_at_1 |
|
value: 20.764 |
|
- type: ndcg_at_10 |
|
value: 25.229000000000003 |
|
- type: ndcg_at_100 |
|
value: 29.604000000000003 |
|
- type: ndcg_at_1000 |
|
value: 32.535 |
|
- type: ndcg_at_3 |
|
value: 22.294 |
|
- type: ndcg_at_5 |
|
value: 23.52 |
|
- type: precision_at_1 |
|
value: 20.764 |
|
- type: precision_at_10 |
|
value: 4.675 |
|
- type: precision_at_100 |
|
value: 0.859 |
|
- type: precision_at_1000 |
|
value: 0.136 |
|
- type: precision_at_3 |
|
value: 10.616 |
|
- type: precision_at_5 |
|
value: 7.567 |
|
- type: recall_at_1 |
|
value: 16.338 |
|
- type: recall_at_10 |
|
value: 31.825 |
|
- type: recall_at_100 |
|
value: 51.400999999999996 |
|
- type: recall_at_1000 |
|
value: 71.50800000000001 |
|
- type: recall_at_3 |
|
value: 23.372 |
|
- type: recall_at_5 |
|
value: 26.662000000000003 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB CQADupstackGamingRetrieval |
|
config: default |
|
split: test |
|
revision: 4885aa143210c98657558c04aaf3dc47cfb54340 |
|
metrics: |
|
- type: map_at_1 |
|
value: 25.196 |
|
- type: map_at_10 |
|
value: 33.175 |
|
- type: map_at_100 |
|
value: 34.239000000000004 |
|
- type: map_at_1000 |
|
value: 34.339 |
|
- type: map_at_3 |
|
value: 30.887999999999998 |
|
- type: map_at_5 |
|
value: 32.090999999999994 |
|
- type: mrr_at_1 |
|
value: 28.965999999999998 |
|
- type: mrr_at_10 |
|
value: 36.148 |
|
- type: mrr_at_100 |
|
value: 37.015 |
|
- type: mrr_at_1000 |
|
value: 37.078 |
|
- type: mrr_at_3 |
|
value: 33.992 |
|
- type: mrr_at_5 |
|
value: 35.117 |
|
- type: ndcg_at_1 |
|
value: 28.965999999999998 |
|
- type: ndcg_at_10 |
|
value: 37.687 |
|
- type: ndcg_at_100 |
|
value: 42.768 |
|
- type: ndcg_at_1000 |
|
value: 45.07 |
|
- type: ndcg_at_3 |
|
value: 33.341 |
|
- type: ndcg_at_5 |
|
value: 35.237 |
|
- type: precision_at_1 |
|
value: 28.965999999999998 |
|
- type: precision_at_10 |
|
value: 6.138 |
|
- type: precision_at_100 |
|
value: 0.95 |
|
- type: precision_at_1000 |
|
value: 0.123 |
|
- type: precision_at_3 |
|
value: 14.796000000000001 |
|
- type: precision_at_5 |
|
value: 10.194 |
|
- type: recall_at_1 |
|
value: 25.196 |
|
- type: recall_at_10 |
|
value: 48.443000000000005 |
|
- type: recall_at_100 |
|
value: 71.414 |
|
- type: recall_at_1000 |
|
value: 88.108 |
|
- type: recall_at_3 |
|
value: 36.647999999999996 |
|
- type: recall_at_5 |
|
value: 41.384 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB CQADupstackGisRetrieval |
|
config: default |
|
split: test |
|
revision: 5003b3064772da1887988e05400cf3806fe491f2 |
|
metrics: |
|
- type: map_at_1 |
|
value: 11.036 |
|
- type: map_at_10 |
|
value: 15.011 |
|
- type: map_at_100 |
|
value: 15.751999999999999 |
|
- type: map_at_1000 |
|
value: 15.864 |
|
- type: map_at_3 |
|
value: 13.675 |
|
- type: map_at_5 |
|
value: 14.414 |
|
- type: mrr_at_1 |
|
value: 12.203 |
|
- type: mrr_at_10 |
|
value: 16.232 |
|
- type: mrr_at_100 |
|
value: 16.965 |
|
- type: mrr_at_1000 |
|
value: 17.069000000000003 |
|
- type: mrr_at_3 |
|
value: 14.84 |
|
- type: mrr_at_5 |
|
value: 15.591 |
|
- type: ndcg_at_1 |
|
value: 12.203 |
|
- type: ndcg_at_10 |
|
value: 17.59 |
|
- type: ndcg_at_100 |
|
value: 21.718 |
|
- type: ndcg_at_1000 |
|
value: 25.108000000000004 |
|
- type: ndcg_at_3 |
|
value: 14.857999999999999 |
|
- type: ndcg_at_5 |
|
value: 16.161 |
|
- type: precision_at_1 |
|
value: 12.203 |
|
- type: precision_at_10 |
|
value: 2.757 |
|
- type: precision_at_100 |
|
value: 0.518 |
|
- type: precision_at_1000 |
|
value: 0.08499999999999999 |
|
- type: precision_at_3 |
|
value: 6.328 |
|
- type: precision_at_5 |
|
value: 4.497 |
|
- type: recall_at_1 |
|
value: 11.036 |
|
- type: recall_at_10 |
|
value: 24.511 |
|
- type: recall_at_100 |
|
value: 44.396 |
|
- type: recall_at_1000 |
|
value: 70.916 |
|
- type: recall_at_3 |
|
value: 17.1 |
|
- type: recall_at_5 |
|
value: 20.244999999999997 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB CQADupstackMathematicaRetrieval |
|
config: default |
|
split: test |
|
revision: 90fceea13679c63fe563ded68f3b6f06e50061de |
|
metrics: |
|
- type: map_at_1 |
|
value: 6.329999999999999 |
|
- type: map_at_10 |
|
value: 9.338000000000001 |
|
- type: map_at_100 |
|
value: 10.047 |
|
- type: map_at_1000 |
|
value: 10.164 |
|
- type: map_at_3 |
|
value: 8.072 |
|
- type: map_at_5 |
|
value: 8.863 |
|
- type: mrr_at_1 |
|
value: 8.333 |
|
- type: mrr_at_10 |
|
value: 11.55 |
|
- type: mrr_at_100 |
|
value: 12.298 |
|
- type: mrr_at_1000 |
|
value: 12.393 |
|
- type: mrr_at_3 |
|
value: 10.095 |
|
- type: mrr_at_5 |
|
value: 10.947 |
|
- type: ndcg_at_1 |
|
value: 8.333 |
|
- type: ndcg_at_10 |
|
value: 11.676 |
|
- type: ndcg_at_100 |
|
value: 15.468000000000002 |
|
- type: ndcg_at_1000 |
|
value: 19.057 |
|
- type: ndcg_at_3 |
|
value: 9.17 |
|
- type: ndcg_at_5 |
|
value: 10.484 |
|
- type: precision_at_1 |
|
value: 8.333 |
|
- type: precision_at_10 |
|
value: 2.2640000000000002 |
|
- type: precision_at_100 |
|
value: 0.484 |
|
- type: precision_at_1000 |
|
value: 0.093 |
|
- type: precision_at_3 |
|
value: 4.353 |
|
- type: precision_at_5 |
|
value: 3.458 |
|
- type: recall_at_1 |
|
value: 6.329999999999999 |
|
- type: recall_at_10 |
|
value: 16.825000000000003 |
|
- type: recall_at_100 |
|
value: 33.986 |
|
- type: recall_at_1000 |
|
value: 60.80799999999999 |
|
- type: recall_at_3 |
|
value: 9.98 |
|
- type: recall_at_5 |
|
value: 13.251 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB CQADupstackPhysicsRetrieval |
|
config: default |
|
split: test |
|
revision: 79531abbd1fb92d06c6d6315a0cbbbf5bb247ea4 |
|
metrics: |
|
- type: map_at_1 |
|
value: 17.105999999999998 |
|
- type: map_at_10 |
|
value: 22.99 |
|
- type: map_at_100 |
|
value: 24.108999999999998 |
|
- type: map_at_1000 |
|
value: 24.239 |
|
- type: map_at_3 |
|
value: 21.096999999999998 |
|
- type: map_at_5 |
|
value: 22.076 |
|
- type: mrr_at_1 |
|
value: 21.752 |
|
- type: mrr_at_10 |
|
value: 27.793 |
|
- type: mrr_at_100 |
|
value: 28.676000000000002 |
|
- type: mrr_at_1000 |
|
value: 28.754999999999995 |
|
- type: mrr_at_3 |
|
value: 25.874000000000002 |
|
- type: mrr_at_5 |
|
value: 26.88 |
|
- type: ndcg_at_1 |
|
value: 21.752 |
|
- type: ndcg_at_10 |
|
value: 27.151999999999997 |
|
- type: ndcg_at_100 |
|
value: 32.492 |
|
- type: ndcg_at_1000 |
|
value: 35.563 |
|
- type: ndcg_at_3 |
|
value: 23.839 |
|
- type: ndcg_at_5 |
|
value: 25.188 |
|
- type: precision_at_1 |
|
value: 21.752 |
|
- type: precision_at_10 |
|
value: 4.986 |
|
- type: precision_at_100 |
|
value: 0.9249999999999999 |
|
- type: precision_at_1000 |
|
value: 0.13899999999999998 |
|
- type: precision_at_3 |
|
value: 11.197 |
|
- type: precision_at_5 |
|
value: 7.968999999999999 |
|
- type: recall_at_1 |
|
value: 17.105999999999998 |
|
- type: recall_at_10 |
|
value: 35.231 |
|
- type: recall_at_100 |
|
value: 58.634 |
|
- type: recall_at_1000 |
|
value: 80.077 |
|
- type: recall_at_3 |
|
value: 25.534000000000002 |
|
- type: recall_at_5 |
|
value: 29.175 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB CQADupstackProgrammersRetrieval |
|
config: default |
|
split: test |
|
revision: 6184bc1440d2dbc7612be22b50686b8826d22b32 |
|
metrics: |
|
- type: map_at_1 |
|
value: 11.303 |
|
- type: map_at_10 |
|
value: 16.778000000000002 |
|
- type: map_at_100 |
|
value: 17.802 |
|
- type: map_at_1000 |
|
value: 17.944 |
|
- type: map_at_3 |
|
value: 14.906 |
|
- type: map_at_5 |
|
value: 16.038 |
|
- type: mrr_at_1 |
|
value: 14.269000000000002 |
|
- type: mrr_at_10 |
|
value: 19.967 |
|
- type: mrr_at_100 |
|
value: 20.921 |
|
- type: mrr_at_1000 |
|
value: 21.009 |
|
- type: mrr_at_3 |
|
value: 18.075 |
|
- type: mrr_at_5 |
|
value: 19.198999999999998 |
|
- type: ndcg_at_1 |
|
value: 14.269000000000002 |
|
- type: ndcg_at_10 |
|
value: 20.294999999999998 |
|
- type: ndcg_at_100 |
|
value: 25.346999999999998 |
|
- type: ndcg_at_1000 |
|
value: 28.860999999999997 |
|
- type: ndcg_at_3 |
|
value: 16.858 |
|
- type: ndcg_at_5 |
|
value: 18.647 |
|
- type: precision_at_1 |
|
value: 14.269000000000002 |
|
- type: precision_at_10 |
|
value: 3.904 |
|
- type: precision_at_100 |
|
value: 0.757 |
|
- type: precision_at_1000 |
|
value: 0.124 |
|
- type: precision_at_3 |
|
value: 8.029 |
|
- type: precision_at_5 |
|
value: 6.164 |
|
- type: recall_at_1 |
|
value: 11.303 |
|
- type: recall_at_10 |
|
value: 27.661 |
|
- type: recall_at_100 |
|
value: 49.976 |
|
- type: recall_at_1000 |
|
value: 75.01400000000001 |
|
- type: recall_at_3 |
|
value: 18.719 |
|
- type: recall_at_5 |
|
value: 23.061999999999998 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: mteb/cqadupstack |
|
name: MTEB CQADupstackRetrieval |
|
config: default |
|
split: test |
|
revision: 4885aa143210c98657558c04aaf3dc47cfb54340 |
|
metrics: |
|
- type: map_at_1 |
|
value: 13.457416666666669 |
|
- type: map_at_10 |
|
value: 18.469333333333335 |
|
- type: map_at_100 |
|
value: 19.32433333333334 |
|
- type: map_at_1000 |
|
value: 19.44766666666667 |
|
- type: map_at_3 |
|
value: 16.88808333333333 |
|
- type: map_at_5 |
|
value: 17.75958333333333 |
|
- type: mrr_at_1 |
|
value: 16.38458333333333 |
|
- type: mrr_at_10 |
|
value: 21.479583333333334 |
|
- type: mrr_at_100 |
|
value: 22.253666666666664 |
|
- type: mrr_at_1000 |
|
value: 22.340916666666665 |
|
- type: mrr_at_3 |
|
value: 19.879083333333334 |
|
- type: mrr_at_5 |
|
value: 20.749750000000002 |
|
- type: ndcg_at_1 |
|
value: 16.38458333333333 |
|
- type: ndcg_at_10 |
|
value: 21.7645 |
|
- type: ndcg_at_100 |
|
value: 26.100583333333333 |
|
- type: ndcg_at_1000 |
|
value: 29.30358333333334 |
|
- type: ndcg_at_3 |
|
value: 18.90866666666667 |
|
- type: ndcg_at_5 |
|
value: 20.19475 |
|
- type: precision_at_1 |
|
value: 16.38458333333333 |
|
- type: precision_at_10 |
|
value: 3.896916666666667 |
|
- type: precision_at_100 |
|
value: 0.7189999999999999 |
|
- type: precision_at_1000 |
|
value: 0.11716666666666666 |
|
- type: precision_at_3 |
|
value: 8.805583333333333 |
|
- type: precision_at_5 |
|
value: 6.311999999999999 |
|
- type: recall_at_1 |
|
value: 13.457416666666669 |
|
- type: recall_at_10 |
|
value: 28.731250000000003 |
|
- type: recall_at_100 |
|
value: 48.64233333333334 |
|
- type: recall_at_1000 |
|
value: 72.04116666666665 |
|
- type: recall_at_3 |
|
value: 20.665249999999997 |
|
- type: recall_at_5 |
|
value: 23.995583333333332 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB CQADupstackStatsRetrieval |
|
config: default |
|
split: test |
|
revision: 65ac3a16b8e91f9cee4c9828cc7c335575432a2a |
|
metrics: |
|
- type: map_at_1 |
|
value: 10.05 |
|
- type: map_at_10 |
|
value: 14.036999999999999 |
|
- type: map_at_100 |
|
value: 14.64 |
|
- type: map_at_1000 |
|
value: 14.722 |
|
- type: map_at_3 |
|
value: 12.85 |
|
- type: map_at_5 |
|
value: 13.517000000000001 |
|
- type: mrr_at_1 |
|
value: 12.117 |
|
- type: mrr_at_10 |
|
value: 16.145 |
|
- type: mrr_at_100 |
|
value: 16.732 |
|
- type: mrr_at_1000 |
|
value: 16.811 |
|
- type: mrr_at_3 |
|
value: 14.877 |
|
- type: mrr_at_5 |
|
value: 15.583 |
|
- type: ndcg_at_1 |
|
value: 12.117 |
|
- type: ndcg_at_10 |
|
value: 16.668 |
|
- type: ndcg_at_100 |
|
value: 19.971 |
|
- type: ndcg_at_1000 |
|
value: 22.527 |
|
- type: ndcg_at_3 |
|
value: 14.393 |
|
- type: ndcg_at_5 |
|
value: 15.436 |
|
- type: precision_at_1 |
|
value: 12.117 |
|
- type: precision_at_10 |
|
value: 2.822 |
|
- type: precision_at_100 |
|
value: 0.49500000000000005 |
|
- type: precision_at_1000 |
|
value: 0.078 |
|
- type: precision_at_3 |
|
value: 6.646000000000001 |
|
- type: precision_at_5 |
|
value: 4.662999999999999 |
|
- type: recall_at_1 |
|
value: 10.05 |
|
- type: recall_at_10 |
|
value: 22.899 |
|
- type: recall_at_100 |
|
value: 38.489000000000004 |
|
- type: recall_at_1000 |
|
value: 58.275 |
|
- type: recall_at_3 |
|
value: 16.166 |
|
- type: recall_at_5 |
|
value: 18.976000000000003 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB CQADupstackTexRetrieval |
|
config: default |
|
split: test |
|
revision: 46989137a86843e03a6195de44b09deda022eec7 |
|
metrics: |
|
- type: map_at_1 |
|
value: 7.185999999999999 |
|
- type: map_at_10 |
|
value: 10.324 |
|
- type: map_at_100 |
|
value: 10.921 |
|
- type: map_at_1000 |
|
value: 11.038 |
|
- type: map_at_3 |
|
value: 9.35 |
|
- type: map_at_5 |
|
value: 9.918000000000001 |
|
- type: mrr_at_1 |
|
value: 8.878 |
|
- type: mrr_at_10 |
|
value: 12.497 |
|
- type: mrr_at_100 |
|
value: 13.103000000000002 |
|
- type: mrr_at_1000 |
|
value: 13.203000000000001 |
|
- type: mrr_at_3 |
|
value: 11.373 |
|
- type: mrr_at_5 |
|
value: 12.061 |
|
- type: ndcg_at_1 |
|
value: 8.878 |
|
- type: ndcg_at_10 |
|
value: 12.543000000000001 |
|
- type: ndcg_at_100 |
|
value: 15.943999999999999 |
|
- type: ndcg_at_1000 |
|
value: 19.407 |
|
- type: ndcg_at_3 |
|
value: 10.687000000000001 |
|
- type: ndcg_at_5 |
|
value: 11.619 |
|
- type: precision_at_1 |
|
value: 8.878 |
|
- type: precision_at_10 |
|
value: 2.35 |
|
- type: precision_at_100 |
|
value: 0.488 |
|
- type: precision_at_1000 |
|
value: 0.094 |
|
- type: precision_at_3 |
|
value: 5.127000000000001 |
|
- type: precision_at_5 |
|
value: 3.82 |
|
- type: recall_at_1 |
|
value: 7.185999999999999 |
|
- type: recall_at_10 |
|
value: 17.138 |
|
- type: recall_at_100 |
|
value: 33.194 |
|
- type: recall_at_1000 |
|
value: 59.14 |
|
- type: recall_at_3 |
|
value: 12.058 |
|
- type: recall_at_5 |
|
value: 14.329 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB CQADupstackUnixRetrieval |
|
config: default |
|
split: test |
|
revision: 6c6430d3a6d36f8d2a829195bc5dc94d7e063e53 |
|
metrics: |
|
- type: map_at_1 |
|
value: 11.498 |
|
- type: map_at_10 |
|
value: 15.725 |
|
- type: map_at_100 |
|
value: 16.515 |
|
- type: map_at_1000 |
|
value: 16.628 |
|
- type: map_at_3 |
|
value: 14.335999999999999 |
|
- type: map_at_5 |
|
value: 15.027 |
|
- type: mrr_at_1 |
|
value: 14.086000000000002 |
|
- type: mrr_at_10 |
|
value: 18.592 |
|
- type: mrr_at_100 |
|
value: 19.405 |
|
- type: mrr_at_1000 |
|
value: 19.500999999999998 |
|
- type: mrr_at_3 |
|
value: 17.086000000000002 |
|
- type: mrr_at_5 |
|
value: 17.855999999999998 |
|
- type: ndcg_at_1 |
|
value: 14.086000000000002 |
|
- type: ndcg_at_10 |
|
value: 18.686 |
|
- type: ndcg_at_100 |
|
value: 22.925 |
|
- type: ndcg_at_1000 |
|
value: 26.279999999999998 |
|
- type: ndcg_at_3 |
|
value: 15.955 |
|
- type: ndcg_at_5 |
|
value: 17.05 |
|
- type: precision_at_1 |
|
value: 14.086000000000002 |
|
- type: precision_at_10 |
|
value: 3.209 |
|
- type: precision_at_100 |
|
value: 0.587 |
|
- type: precision_at_1000 |
|
value: 0.099 |
|
- type: precision_at_3 |
|
value: 7.338 |
|
- type: precision_at_5 |
|
value: 5.131 |
|
- type: recall_at_1 |
|
value: 11.498 |
|
- type: recall_at_10 |
|
value: 25.135 |
|
- type: recall_at_100 |
|
value: 44.751000000000005 |
|
- type: recall_at_1000 |
|
value: 69.75 |
|
- type: recall_at_3 |
|
value: 17.471999999999998 |
|
- type: recall_at_5 |
|
value: 20.273 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB CQADupstackWebmastersRetrieval |
|
config: default |
|
split: test |
|
revision: 160c094312a0e1facb97e55eeddb698c0abe3571 |
|
metrics: |
|
- type: map_at_1 |
|
value: 13.111999999999998 |
|
- type: map_at_10 |
|
value: 19.224 |
|
- type: map_at_100 |
|
value: 20.183999999999997 |
|
- type: map_at_1000 |
|
value: 20.354 |
|
- type: map_at_3 |
|
value: 17.738 |
|
- type: map_at_5 |
|
value: 18.518 |
|
- type: mrr_at_1 |
|
value: 16.008 |
|
- type: mrr_at_10 |
|
value: 22.421 |
|
- type: mrr_at_100 |
|
value: 23.174 |
|
- type: mrr_at_1000 |
|
value: 23.261000000000003 |
|
- type: mrr_at_3 |
|
value: 20.784 |
|
- type: mrr_at_5 |
|
value: 21.634 |
|
- type: ndcg_at_1 |
|
value: 16.008 |
|
- type: ndcg_at_10 |
|
value: 23.082 |
|
- type: ndcg_at_100 |
|
value: 27.563 |
|
- type: ndcg_at_1000 |
|
value: 31.135 |
|
- type: ndcg_at_3 |
|
value: 20.517 |
|
- type: ndcg_at_5 |
|
value: 21.595 |
|
- type: precision_at_1 |
|
value: 16.008 |
|
- type: precision_at_10 |
|
value: 4.625 |
|
- type: precision_at_100 |
|
value: 0.966 |
|
- type: precision_at_1000 |
|
value: 0.179 |
|
- type: precision_at_3 |
|
value: 10.079 |
|
- type: precision_at_5 |
|
value: 7.2330000000000005 |
|
- type: recall_at_1 |
|
value: 13.111999999999998 |
|
- type: recall_at_10 |
|
value: 30.297 |
|
- type: recall_at_100 |
|
value: 51.549 |
|
- type: recall_at_1000 |
|
value: 76.255 |
|
- type: recall_at_3 |
|
value: 22.817999999999998 |
|
- type: recall_at_5 |
|
value: 25.741000000000003 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB CQADupstackWordpressRetrieval |
|
config: default |
|
split: test |
|
revision: 4ffe81d471b1924886b33c7567bfb200e9eec5c4 |
|
metrics: |
|
- type: map_at_1 |
|
value: 10.825999999999999 |
|
- type: map_at_10 |
|
value: 14.767 |
|
- type: map_at_100 |
|
value: 15.440000000000001 |
|
- type: map_at_1000 |
|
value: 15.557000000000002 |
|
- type: map_at_3 |
|
value: 13.413 |
|
- type: map_at_5 |
|
value: 14.099999999999998 |
|
- type: mrr_at_1 |
|
value: 12.2 |
|
- type: mrr_at_10 |
|
value: 16.33 |
|
- type: mrr_at_100 |
|
value: 17.009 |
|
- type: mrr_at_1000 |
|
value: 17.118 |
|
- type: mrr_at_3 |
|
value: 14.940999999999999 |
|
- type: mrr_at_5 |
|
value: 15.681000000000001 |
|
- type: ndcg_at_1 |
|
value: 12.2 |
|
- type: ndcg_at_10 |
|
value: 17.409 |
|
- type: ndcg_at_100 |
|
value: 21.235 |
|
- type: ndcg_at_1000 |
|
value: 24.693 |
|
- type: ndcg_at_3 |
|
value: 14.698 |
|
- type: ndcg_at_5 |
|
value: 15.86 |
|
- type: precision_at_1 |
|
value: 12.2 |
|
- type: precision_at_10 |
|
value: 2.81 |
|
- type: precision_at_100 |
|
value: 0.512 |
|
- type: precision_at_1000 |
|
value: 0.09 |
|
- type: precision_at_3 |
|
value: 6.47 |
|
- type: precision_at_5 |
|
value: 4.547 |
|
- type: recall_at_1 |
|
value: 10.825999999999999 |
|
- type: recall_at_10 |
|
value: 24.202 |
|
- type: recall_at_100 |
|
value: 42.787 |
|
- type: recall_at_1000 |
|
value: 69.351 |
|
- type: recall_at_3 |
|
value: 16.833000000000002 |
|
- type: recall_at_5 |
|
value: 19.612 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB ClimateFEVER |
|
config: default |
|
split: test |
|
revision: 47f2ac6acb640fc46020b02a5b59fdda04d39380 |
|
metrics: |
|
- type: map_at_1 |
|
value: 5.436 |
|
- type: map_at_10 |
|
value: 9.59 |
|
- type: map_at_100 |
|
value: 10.847 |
|
- type: map_at_1000 |
|
value: 11.043 |
|
- type: map_at_3 |
|
value: 7.797 |
|
- type: map_at_5 |
|
value: 8.627 |
|
- type: mrr_at_1 |
|
value: 12.182 |
|
- type: mrr_at_10 |
|
value: 19.584 |
|
- type: mrr_at_100 |
|
value: 20.772 |
|
- type: mrr_at_1000 |
|
value: 20.855999999999998 |
|
- type: mrr_at_3 |
|
value: 16.938 |
|
- type: mrr_at_5 |
|
value: 18.358 |
|
- type: ndcg_at_1 |
|
value: 12.182 |
|
- type: ndcg_at_10 |
|
value: 14.514 |
|
- type: ndcg_at_100 |
|
value: 20.495 |
|
- type: ndcg_at_1000 |
|
value: 24.664 |
|
- type: ndcg_at_3 |
|
value: 11.024000000000001 |
|
- type: ndcg_at_5 |
|
value: 12.200999999999999 |
|
- type: precision_at_1 |
|
value: 12.182 |
|
- type: precision_at_10 |
|
value: 4.853 |
|
- type: precision_at_100 |
|
value: 1.124 |
|
- type: precision_at_1000 |
|
value: 0.187 |
|
- type: precision_at_3 |
|
value: 8.317 |
|
- type: precision_at_5 |
|
value: 6.697 |
|
- type: recall_at_1 |
|
value: 5.436 |
|
- type: recall_at_10 |
|
value: 18.615000000000002 |
|
- type: recall_at_100 |
|
value: 39.621 |
|
- type: recall_at_1000 |
|
value: 63.852 |
|
- type: recall_at_3 |
|
value: 10.474 |
|
- type: recall_at_5 |
|
value: 13.370999999999999 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB DBPedia |
|
config: default |
|
split: test |
|
revision: c0f706b76e590d620bd6618b3ca8efdd34e2d659 |
|
metrics: |
|
- type: map_at_1 |
|
value: 3.8309999999999995 |
|
- type: map_at_10 |
|
value: 7.7490000000000006 |
|
- type: map_at_100 |
|
value: 10.421 |
|
- type: map_at_1000 |
|
value: 11.161 |
|
- type: map_at_3 |
|
value: 5.762 |
|
- type: map_at_5 |
|
value: 6.645 |
|
- type: mrr_at_1 |
|
value: 35.25 |
|
- type: mrr_at_10 |
|
value: 43.685 |
|
- type: mrr_at_100 |
|
value: 44.567 |
|
- type: mrr_at_1000 |
|
value: 44.618 |
|
- type: mrr_at_3 |
|
value: 41.375 |
|
- type: mrr_at_5 |
|
value: 42.85 |
|
- type: ndcg_at_1 |
|
value: 25.624999999999996 |
|
- type: ndcg_at_10 |
|
value: 19.837 |
|
- type: ndcg_at_100 |
|
value: 21.92 |
|
- type: ndcg_at_1000 |
|
value: 28.116000000000003 |
|
- type: ndcg_at_3 |
|
value: 22.561 |
|
- type: ndcg_at_5 |
|
value: 21.073 |
|
- type: precision_at_1 |
|
value: 35.25 |
|
- type: precision_at_10 |
|
value: 17.125 |
|
- type: precision_at_100 |
|
value: 5.35 |
|
- type: precision_at_1000 |
|
value: 1.142 |
|
- type: precision_at_3 |
|
value: 25.833000000000002 |
|
- type: precision_at_5 |
|
value: 22.0 |
|
- type: recall_at_1 |
|
value: 3.8309999999999995 |
|
- type: recall_at_10 |
|
value: 11.393 |
|
- type: recall_at_100 |
|
value: 26.519 |
|
- type: recall_at_1000 |
|
value: 47.249 |
|
- type: recall_at_3 |
|
value: 6.708 |
|
- type: recall_at_5 |
|
value: 8.584 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: None |
|
name: MTEB EmotionClassification |
|
config: default |
|
split: test |
|
revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37 |
|
metrics: |
|
- type: accuracy |
|
value: 43.69 |
|
- type: f1 |
|
value: 39.825457200782445 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB FEVER |
|
config: default |
|
split: test |
|
revision: bea83ef9e8fb933d90a2f1d5515737465d613e12 |
|
metrics: |
|
- type: map_at_1 |
|
value: 10.94 |
|
- type: map_at_10 |
|
value: 16.482 |
|
- type: map_at_100 |
|
value: 17.321 |
|
- type: map_at_1000 |
|
value: 17.403 |
|
- type: map_at_3 |
|
value: 14.679 |
|
- type: map_at_5 |
|
value: 15.637 |
|
- type: mrr_at_1 |
|
value: 11.701 |
|
- type: mrr_at_10 |
|
value: 17.583 |
|
- type: mrr_at_100 |
|
value: 18.444 |
|
- type: mrr_at_1000 |
|
value: 18.519 |
|
- type: mrr_at_3 |
|
value: 15.709000000000001 |
|
- type: mrr_at_5 |
|
value: 16.707 |
|
- type: ndcg_at_1 |
|
value: 11.701 |
|
- type: ndcg_at_10 |
|
value: 19.946 |
|
- type: ndcg_at_100 |
|
value: 24.462 |
|
- type: ndcg_at_1000 |
|
value: 26.863 |
|
- type: ndcg_at_3 |
|
value: 16.155 |
|
- type: ndcg_at_5 |
|
value: 17.888 |
|
- type: precision_at_1 |
|
value: 11.701 |
|
- type: precision_at_10 |
|
value: 3.2399999999999998 |
|
- type: precision_at_100 |
|
value: 0.5680000000000001 |
|
- type: precision_at_1000 |
|
value: 0.079 |
|
- type: precision_at_3 |
|
value: 6.991 |
|
- type: precision_at_5 |
|
value: 5.101 |
|
- type: recall_at_1 |
|
value: 10.94 |
|
- type: recall_at_10 |
|
value: 29.848000000000003 |
|
- type: recall_at_100 |
|
value: 51.451 |
|
- type: recall_at_1000 |
|
value: 70.316 |
|
- type: recall_at_3 |
|
value: 19.39 |
|
- type: recall_at_5 |
|
value: 23.583000000000002 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB FiQA2018 |
|
config: default |
|
split: test |
|
revision: 27a168819829fe9bcd655c2df245fb19452e8e06 |
|
metrics: |
|
- type: map_at_1 |
|
value: 5.825 |
|
- type: map_at_10 |
|
value: 9.669 |
|
- type: map_at_100 |
|
value: 10.657 |
|
- type: map_at_1000 |
|
value: 10.850999999999999 |
|
- type: map_at_3 |
|
value: 8.174 |
|
- type: map_at_5 |
|
value: 8.931000000000001 |
|
- type: mrr_at_1 |
|
value: 11.574 |
|
- type: mrr_at_10 |
|
value: 17.153 |
|
- type: mrr_at_100 |
|
value: 18.027 |
|
- type: mrr_at_1000 |
|
value: 18.138 |
|
- type: mrr_at_3 |
|
value: 15.201 |
|
- type: mrr_at_5 |
|
value: 16.119 |
|
- type: ndcg_at_1 |
|
value: 11.574 |
|
- type: ndcg_at_10 |
|
value: 13.599 |
|
- type: ndcg_at_100 |
|
value: 18.422 |
|
- type: ndcg_at_1000 |
|
value: 23.124 |
|
- type: ndcg_at_3 |
|
value: 11.219999999999999 |
|
- type: ndcg_at_5 |
|
value: 11.984 |
|
- type: precision_at_1 |
|
value: 11.574 |
|
- type: precision_at_10 |
|
value: 4.043 |
|
- type: precision_at_100 |
|
value: 0.8869999999999999 |
|
- type: precision_at_1000 |
|
value: 0.168 |
|
- type: precision_at_3 |
|
value: 7.716000000000001 |
|
- type: precision_at_5 |
|
value: 5.926 |
|
- type: recall_at_1 |
|
value: 5.825 |
|
- type: recall_at_10 |
|
value: 17.837 |
|
- type: recall_at_100 |
|
value: 36.771 |
|
- type: recall_at_1000 |
|
value: 66.81 |
|
- type: recall_at_3 |
|
value: 10.181999999999999 |
|
- type: recall_at_5 |
|
value: 12.909 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB HotpotQA |
|
config: default |
|
split: test |
|
revision: ab518f4d6fcca38d87c25209f94beba119d02014 |
|
metrics: |
|
- type: map_at_1 |
|
value: 13.558 |
|
- type: map_at_10 |
|
value: 18.987000000000002 |
|
- type: map_at_100 |
|
value: 19.768 |
|
- type: map_at_1000 |
|
value: 19.878999999999998 |
|
- type: map_at_3 |
|
value: 17.399 |
|
- type: map_at_5 |
|
value: 18.231 |
|
- type: mrr_at_1 |
|
value: 27.117 |
|
- type: mrr_at_10 |
|
value: 33.32 |
|
- type: mrr_at_100 |
|
value: 34.050000000000004 |
|
- type: mrr_at_1000 |
|
value: 34.122 |
|
- type: mrr_at_3 |
|
value: 31.570999999999998 |
|
- type: mrr_at_5 |
|
value: 32.519999999999996 |
|
- type: ndcg_at_1 |
|
value: 27.117 |
|
- type: ndcg_at_10 |
|
value: 24.708 |
|
- type: ndcg_at_100 |
|
value: 28.566000000000003 |
|
- type: ndcg_at_1000 |
|
value: 31.418000000000003 |
|
- type: ndcg_at_3 |
|
value: 21.549 |
|
- type: ndcg_at_5 |
|
value: 22.997 |
|
- type: precision_at_1 |
|
value: 27.117 |
|
- type: precision_at_10 |
|
value: 5.5169999999999995 |
|
- type: precision_at_100 |
|
value: 0.8630000000000001 |
|
- type: precision_at_1000 |
|
value: 0.125 |
|
- type: precision_at_3 |
|
value: 13.603000000000002 |
|
- type: precision_at_5 |
|
value: 9.313 |
|
- type: recall_at_1 |
|
value: 13.558 |
|
- type: recall_at_10 |
|
value: 27.583000000000002 |
|
- type: recall_at_100 |
|
value: 43.153000000000006 |
|
- type: recall_at_1000 |
|
value: 62.255 |
|
- type: recall_at_3 |
|
value: 20.405 |
|
- type: recall_at_5 |
|
value: 23.282 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: None |
|
name: MTEB ImdbClassification |
|
config: default |
|
split: test |
|
revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7 |
|
metrics: |
|
- type: accuracy |
|
value: 64.06880000000001 |
|
- type: ap |
|
value: 59.27294551535466 |
|
- type: f1 |
|
value: 63.91536827569369 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB MSMARCO |
|
config: default |
|
split: dev |
|
revision: c5a29a104738b98a9e76336939199e264163d4a0 |
|
metrics: |
|
- type: map_at_1 |
|
value: 5.241 |
|
- type: map_at_10 |
|
value: 9.158 |
|
- type: map_at_100 |
|
value: 9.907 |
|
- type: map_at_1000 |
|
value: 10.001 |
|
- type: map_at_3 |
|
value: 7.7 |
|
- type: map_at_5 |
|
value: 8.466999999999999 |
|
- type: mrr_at_1 |
|
value: 5.43 |
|
- type: mrr_at_10 |
|
value: 9.42 |
|
- type: mrr_at_100 |
|
value: 10.174999999999999 |
|
- type: mrr_at_1000 |
|
value: 10.267999999999999 |
|
- type: mrr_at_3 |
|
value: 7.932 |
|
- type: mrr_at_5 |
|
value: 8.718 |
|
- type: ndcg_at_1 |
|
value: 5.415 |
|
- type: ndcg_at_10 |
|
value: 11.655 |
|
- type: ndcg_at_100 |
|
value: 15.894 |
|
- type: ndcg_at_1000 |
|
value: 18.837 |
|
- type: ndcg_at_3 |
|
value: 8.59 |
|
- type: ndcg_at_5 |
|
value: 9.982000000000001 |
|
- type: precision_at_1 |
|
value: 5.415 |
|
- type: precision_at_10 |
|
value: 2.023 |
|
- type: precision_at_100 |
|
value: 0.42500000000000004 |
|
- type: precision_at_1000 |
|
value: 0.068 |
|
- type: precision_at_3 |
|
value: 3.7920000000000003 |
|
- type: precision_at_5 |
|
value: 2.971 |
|
- type: recall_at_1 |
|
value: 5.241 |
|
- type: recall_at_10 |
|
value: 19.429 |
|
- type: recall_at_100 |
|
value: 40.422999999999995 |
|
- type: recall_at_1000 |
|
value: 64.191 |
|
- type: recall_at_3 |
|
value: 10.95 |
|
- type: recall_at_5 |
|
value: 14.319 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: None |
|
name: MTEB MTOPDomainClassification (en) |
|
config: en |
|
split: test |
|
revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf |
|
metrics: |
|
- type: accuracy |
|
value: 89.40264477884178 |
|
- type: f1 |
|
value: 88.48890314653876 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: None |
|
name: MTEB MTOPIntentClassification (en) |
|
config: en |
|
split: test |
|
revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba |
|
metrics: |
|
- type: accuracy |
|
value: 59.86320109439125 |
|
- type: f1 |
|
value: 40.351741507970175 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: None |
|
name: MTEB MassiveIntentClassification (en) |
|
config: en |
|
split: test |
|
revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 |
|
metrics: |
|
- type: accuracy |
|
value: 62.17552118359112 |
|
- type: f1 |
|
value: 59.92291942649051 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: None |
|
name: MTEB MassiveScenarioClassification (en) |
|
config: en |
|
split: test |
|
revision: 7d571f92784cd94a019292a1f45445077d0ef634 |
|
metrics: |
|
- type: accuracy |
|
value: 68.89710827168797 |
|
- type: f1 |
|
value: 67.48141199477321 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: None |
|
name: MTEB MedrxivClusteringP2P |
|
config: default |
|
split: test |
|
revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73 |
|
metrics: |
|
- type: v_measure |
|
value: 27.003683715948068 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: None |
|
name: MTEB MedrxivClusteringS2S |
|
config: default |
|
split: test |
|
revision: 35191c8c0dca72d8ff3efcd72aa802307d469663 |
|
metrics: |
|
- type: v_measure |
|
value: 23.655067999182727 |
|
- task: |
|
type: Reranking |
|
dataset: |
|
type: None |
|
name: MTEB MindSmallReranking |
|
config: default |
|
split: test |
|
revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69 |
|
metrics: |
|
- type: map |
|
value: 28.614207594880682 |
|
- type: mrr |
|
value: 29.46624248673221 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB NFCorpus |
|
config: default |
|
split: test |
|
revision: ec0fa4fe99da2ff19ca1214b7966684033a58814 |
|
metrics: |
|
- type: map_at_1 |
|
value: 3.047 |
|
- type: map_at_10 |
|
value: 6.144 |
|
- type: map_at_100 |
|
value: 7.806 |
|
- type: map_at_1000 |
|
value: 8.998000000000001 |
|
- type: map_at_3 |
|
value: 4.566 |
|
- type: map_at_5 |
|
value: 5.321 |
|
- type: mrr_at_1 |
|
value: 30.65 |
|
- type: mrr_at_10 |
|
value: 39.213 |
|
- type: mrr_at_100 |
|
value: 39.973 |
|
- type: mrr_at_1000 |
|
value: 40.048 |
|
- type: mrr_at_3 |
|
value: 36.687 |
|
- type: mrr_at_5 |
|
value: 38.421 |
|
- type: ndcg_at_1 |
|
value: 28.638 |
|
- type: ndcg_at_10 |
|
value: 21.032 |
|
- type: ndcg_at_100 |
|
value: 19.85 |
|
- type: ndcg_at_1000 |
|
value: 29.416999999999998 |
|
- type: ndcg_at_3 |
|
value: 24.403 |
|
- type: ndcg_at_5 |
|
value: 22.956 |
|
- type: precision_at_1 |
|
value: 30.65 |
|
- type: precision_at_10 |
|
value: 15.479999999999999 |
|
- type: precision_at_100 |
|
value: 5.83 |
|
- type: precision_at_1000 |
|
value: 1.8800000000000001 |
|
- type: precision_at_3 |
|
value: 23.22 |
|
- type: precision_at_5 |
|
value: 19.628 |
|
- type: recall_at_1 |
|
value: 3.047 |
|
- type: recall_at_10 |
|
value: 9.871 |
|
- type: recall_at_100 |
|
value: 21.556 |
|
- type: recall_at_1000 |
|
value: 56.15 |
|
- type: recall_at_3 |
|
value: 5.476 |
|
- type: recall_at_5 |
|
value: 7.359 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB NQ |
|
config: default |
|
split: test |
|
revision: b774495ed302d8c44a3a7ea25c90dbce03968f31 |
|
metrics: |
|
- type: map_at_1 |
|
value: 7.79 |
|
- type: map_at_10 |
|
value: 13.5 |
|
- type: map_at_100 |
|
value: 14.541 |
|
- type: map_at_1000 |
|
value: 14.643 |
|
- type: map_at_3 |
|
value: 11.446000000000002 |
|
- type: map_at_5 |
|
value: 12.437 |
|
- type: mrr_at_1 |
|
value: 8.863999999999999 |
|
- type: mrr_at_10 |
|
value: 14.985000000000001 |
|
- type: mrr_at_100 |
|
value: 15.989999999999998 |
|
- type: mrr_at_1000 |
|
value: 16.073 |
|
- type: mrr_at_3 |
|
value: 12.799 |
|
- type: mrr_at_5 |
|
value: 13.902999999999999 |
|
- type: ndcg_at_1 |
|
value: 8.863999999999999 |
|
- type: ndcg_at_10 |
|
value: 17.335 |
|
- type: ndcg_at_100 |
|
value: 22.884 |
|
- type: ndcg_at_1000 |
|
value: 25.747999999999998 |
|
- type: ndcg_at_3 |
|
value: 12.97 |
|
- type: ndcg_at_5 |
|
value: 14.799000000000001 |
|
- type: precision_at_1 |
|
value: 8.863999999999999 |
|
- type: precision_at_10 |
|
value: 3.2620000000000005 |
|
- type: precision_at_100 |
|
value: 0.6459999999999999 |
|
- type: precision_at_1000 |
|
value: 0.092 |
|
- type: precision_at_3 |
|
value: 6.161 |
|
- type: precision_at_5 |
|
value: 4.733 |
|
- type: recall_at_1 |
|
value: 7.79 |
|
- type: recall_at_10 |
|
value: 27.868 |
|
- type: recall_at_100 |
|
value: 54.096999999999994 |
|
- type: recall_at_1000 |
|
value: 76.27199999999999 |
|
- type: recall_at_3 |
|
value: 16.063 |
|
- type: recall_at_5 |
|
value: 20.355 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB QuoraRetrieval |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 60.968 |
|
- type: map_at_10 |
|
value: 73.346 |
|
- type: map_at_100 |
|
value: 74.144 |
|
- type: map_at_1000 |
|
value: 74.181 |
|
- type: map_at_3 |
|
value: 70.462 |
|
- type: map_at_5 |
|
value: 72.167 |
|
- type: mrr_at_1 |
|
value: 70.24000000000001 |
|
- type: mrr_at_10 |
|
value: 77.794 |
|
- type: mrr_at_100 |
|
value: 78.079 |
|
- type: mrr_at_1000 |
|
value: 78.086 |
|
- type: mrr_at_3 |
|
value: 76.265 |
|
- type: mrr_at_5 |
|
value: 77.242 |
|
- type: ndcg_at_1 |
|
value: 70.28999999999999 |
|
- type: ndcg_at_10 |
|
value: 78.16199999999999 |
|
- type: ndcg_at_100 |
|
value: 80.515 |
|
- type: ndcg_at_1000 |
|
value: 80.987 |
|
- type: ndcg_at_3 |
|
value: 74.49 |
|
- type: ndcg_at_5 |
|
value: 76.334 |
|
- type: precision_at_1 |
|
value: 70.28999999999999 |
|
- type: precision_at_10 |
|
value: 11.827 |
|
- type: precision_at_100 |
|
value: 1.435 |
|
- type: precision_at_1000 |
|
value: 0.154 |
|
- type: precision_at_3 |
|
value: 32.25 |
|
- type: precision_at_5 |
|
value: 21.342 |
|
- type: recall_at_1 |
|
value: 60.968 |
|
- type: recall_at_10 |
|
value: 87.449 |
|
- type: recall_at_100 |
|
value: 96.557 |
|
- type: recall_at_1000 |
|
value: 99.328 |
|
- type: recall_at_3 |
|
value: 76.91799999999999 |
|
- type: recall_at_5 |
|
value: 82.048 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: None |
|
name: MTEB RedditClustering |
|
config: default |
|
split: test |
|
revision: 24640382cdbf8abc73003fb0fa6d111a705499eb |
|
metrics: |
|
- type: v_measure |
|
value: 28.013469586101447 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: None |
|
name: MTEB RedditClusteringP2P |
|
config: default |
|
split: test |
|
revision: 282350215ef01743dc01b456c7f5241fa8937f16 |
|
metrics: |
|
- type: v_measure |
|
value: 43.29182795065702 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB SCIDOCS |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 2.635 |
|
- type: map_at_10 |
|
value: 6.061 |
|
- type: map_at_100 |
|
value: 7.287000000000001 |
|
- type: map_at_1000 |
|
value: 7.528 |
|
- type: map_at_3 |
|
value: 4.424 |
|
- type: map_at_5 |
|
value: 5.226 |
|
- type: mrr_at_1 |
|
value: 13.0 |
|
- type: mrr_at_10 |
|
value: 20.066 |
|
- type: mrr_at_100 |
|
value: 21.352 |
|
- type: mrr_at_1000 |
|
value: 21.447 |
|
- type: mrr_at_3 |
|
value: 17.666999999999998 |
|
- type: mrr_at_5 |
|
value: 19.002 |
|
- type: ndcg_at_1 |
|
value: 13.0 |
|
- type: ndcg_at_10 |
|
value: 10.943 |
|
- type: ndcg_at_100 |
|
value: 16.822 |
|
- type: ndcg_at_1000 |
|
value: 21.905 |
|
- type: ndcg_at_3 |
|
value: 10.291 |
|
- type: ndcg_at_5 |
|
value: 9.028 |
|
- type: precision_at_1 |
|
value: 13.0 |
|
- type: precision_at_10 |
|
value: 5.680000000000001 |
|
- type: precision_at_100 |
|
value: 1.4200000000000002 |
|
- type: precision_at_1000 |
|
value: 0.265 |
|
- type: precision_at_3 |
|
value: 9.5 |
|
- type: precision_at_5 |
|
value: 7.86 |
|
- type: recall_at_1 |
|
value: 2.635 |
|
- type: recall_at_10 |
|
value: 11.501999999999999 |
|
- type: recall_at_100 |
|
value: 28.854999999999997 |
|
- type: recall_at_1000 |
|
value: 53.818 |
|
- type: recall_at_3 |
|
value: 5.798 |
|
- type: recall_at_5 |
|
value: 7.963000000000001 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: None |
|
name: MTEB SICK-R |
|
config: default |
|
split: test |
|
revision: a6ea5a8cab320b040a23452cc28066d9beae2cee |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 76.50555278582816 |
|
- type: cos_sim_spearman |
|
value: 67.67214548084267 |
|
- type: euclidean_pearson |
|
value: 72.80672647042718 |
|
- type: euclidean_spearman |
|
value: 67.67205019006775 |
|
- type: manhattan_pearson |
|
value: 71.39917324420631 |
|
- type: manhattan_spearman |
|
value: 66.3359934752193 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: None |
|
name: MTEB STS12 |
|
config: default |
|
split: test |
|
revision: a0d554a64d88156834ff5ae9920b964011b16384 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 73.46335143910176 |
|
- type: cos_sim_spearman |
|
value: 66.48232205374549 |
|
- type: euclidean_pearson |
|
value: 69.85631416436473 |
|
- type: euclidean_spearman |
|
value: 66.48363705410418 |
|
- type: manhattan_pearson |
|
value: 70.72055367256513 |
|
- type: manhattan_spearman |
|
value: 67.85751320875836 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: None |
|
name: MTEB STS13 |
|
config: default |
|
split: test |
|
revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 77.64955371743831 |
|
- type: cos_sim_spearman |
|
value: 78.9381622922565 |
|
- type: euclidean_pearson |
|
value: 78.55659975799884 |
|
- type: euclidean_spearman |
|
value: 78.93820009727344 |
|
- type: manhattan_pearson |
|
value: 79.0225046950142 |
|
- type: manhattan_spearman |
|
value: 79.48472901118284 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: None |
|
name: MTEB STS14 |
|
config: default |
|
split: test |
|
revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 77.25183335845733 |
|
- type: cos_sim_spearman |
|
value: 74.24842723953067 |
|
- type: euclidean_pearson |
|
value: 76.4686232324461 |
|
- type: euclidean_spearman |
|
value: 74.24841754885648 |
|
- type: manhattan_pearson |
|
value: 76.58863832312952 |
|
- type: manhattan_spearman |
|
value: 74.65445574230469 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: None |
|
name: MTEB STS15 |
|
config: default |
|
split: test |
|
revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 79.89380076521006 |
|
- type: cos_sim_spearman |
|
value: 80.97474081393298 |
|
- type: euclidean_pearson |
|
value: 80.98258525159558 |
|
- type: euclidean_spearman |
|
value: 80.97473932039865 |
|
- type: manhattan_pearson |
|
value: 81.6739145030644 |
|
- type: manhattan_spearman |
|
value: 81.84024193133868 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: None |
|
name: MTEB STS16 |
|
config: default |
|
split: test |
|
revision: 4d8694f8f0e0100860b497b999b3dbed754a0513 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 75.47297982552274 |
|
- type: cos_sim_spearman |
|
value: 76.78688389457616 |
|
- type: euclidean_pearson |
|
value: 76.42350164312737 |
|
- type: euclidean_spearman |
|
value: 76.78743419029857 |
|
- type: manhattan_pearson |
|
value: 77.05352545216272 |
|
- type: manhattan_spearman |
|
value: 77.51886896774369 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: None |
|
name: MTEB STS17 (en-en) |
|
config: en-en |
|
split: test |
|
revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 82.91509212460161 |
|
- type: cos_sim_spearman |
|
value: 84.0998411802368 |
|
- type: euclidean_pearson |
|
value: 84.18246980817624 |
|
- type: euclidean_spearman |
|
value: 84.10071528982036 |
|
- type: manhattan_pearson |
|
value: 84.4128363010489 |
|
- type: manhattan_spearman |
|
value: 84.43725453490214 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: None |
|
name: MTEB STS22 (en) |
|
config: en |
|
split: test |
|
revision: eea2b4fe26a775864c896887d910b76a8098ad3f |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 62.86109059526856 |
|
- type: cos_sim_spearman |
|
value: 60.51897891571115 |
|
- type: euclidean_pearson |
|
value: 62.803664785666925 |
|
- type: euclidean_spearman |
|
value: 60.51897891571115 |
|
- type: manhattan_pearson |
|
value: 63.29647652965783 |
|
- type: manhattan_spearman |
|
value: 61.57692163615942 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: None |
|
name: MTEB STSBenchmark |
|
config: default |
|
split: test |
|
revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 77.23785194416263 |
|
- type: cos_sim_spearman |
|
value: 75.86058891622369 |
|
- type: euclidean_pearson |
|
value: 77.38393317729829 |
|
- type: euclidean_spearman |
|
value: 75.86063730582144 |
|
- type: manhattan_pearson |
|
value: 77.4860432550345 |
|
- type: manhattan_spearman |
|
value: 76.0756045460265 |
|
- task: |
|
type: Reranking |
|
dataset: |
|
type: None |
|
name: MTEB SciDocsRR |
|
config: default |
|
split: test |
|
revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab |
|
metrics: |
|
- type: map |
|
value: 70.65732608186795 |
|
- type: mrr |
|
value: 90.0984182846928 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB SciFact |
|
config: default |
|
split: test |
|
revision: 0228b52cf27578f30900b9e5271d331663a030d7 |
|
metrics: |
|
- type: map_at_1 |
|
value: 30.721999999999998 |
|
- type: map_at_10 |
|
value: 37.522 |
|
- type: map_at_100 |
|
value: 38.699 |
|
- type: map_at_1000 |
|
value: 38.769 |
|
- type: map_at_3 |
|
value: 34.995 |
|
- type: map_at_5 |
|
value: 36.701 |
|
- type: mrr_at_1 |
|
value: 32.667 |
|
- type: mrr_at_10 |
|
value: 39.298 |
|
- type: mrr_at_100 |
|
value: 40.297 |
|
- type: mrr_at_1000 |
|
value: 40.354 |
|
- type: mrr_at_3 |
|
value: 37.167 |
|
- type: mrr_at_5 |
|
value: 38.533 |
|
- type: ndcg_at_1 |
|
value: 32.667 |
|
- type: ndcg_at_10 |
|
value: 41.634 |
|
- type: ndcg_at_100 |
|
value: 47.49 |
|
- type: ndcg_at_1000 |
|
value: 49.419000000000004 |
|
- type: ndcg_at_3 |
|
value: 36.925000000000004 |
|
- type: ndcg_at_5 |
|
value: 39.739000000000004 |
|
- type: precision_at_1 |
|
value: 32.667 |
|
- type: precision_at_10 |
|
value: 5.833 |
|
- type: precision_at_100 |
|
value: 0.91 |
|
- type: precision_at_1000 |
|
value: 0.108 |
|
- type: precision_at_3 |
|
value: 14.556 |
|
- type: precision_at_5 |
|
value: 10.333 |
|
- type: recall_at_1 |
|
value: 30.721999999999998 |
|
- type: recall_at_10 |
|
value: 52.722 |
|
- type: recall_at_100 |
|
value: 80.417 |
|
- type: recall_at_1000 |
|
value: 95.8 |
|
- type: recall_at_3 |
|
value: 40.306 |
|
- type: recall_at_5 |
|
value: 47.083000000000006 |
|
- task: |
|
type: PairClassification |
|
dataset: |
|
type: None |
|
name: MTEB SprintDuplicateQuestions |
|
config: default |
|
split: test |
|
revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46 |
|
metrics: |
|
- type: cos_sim_accuracy |
|
value: 99.63564356435643 |
|
- type: cos_sim_ap |
|
value: 87.3180475245355 |
|
- type: cos_sim_f1 |
|
value: 80.3125 |
|
- type: cos_sim_precision |
|
value: 83.80434782608695 |
|
- type: cos_sim_recall |
|
value: 77.10000000000001 |
|
- type: dot_accuracy |
|
value: 99.63564356435643 |
|
- type: dot_ap |
|
value: 87.3180475245355 |
|
- type: dot_f1 |
|
value: 80.3125 |
|
- type: dot_precision |
|
value: 83.80434782608695 |
|
- type: dot_recall |
|
value: 77.10000000000001 |
|
- type: euclidean_accuracy |
|
value: 99.63564356435643 |
|
- type: euclidean_ap |
|
value: 87.3180475245355 |
|
- type: euclidean_f1 |
|
value: 80.3125 |
|
- type: euclidean_precision |
|
value: 83.80434782608695 |
|
- type: euclidean_recall |
|
value: 77.10000000000001 |
|
- type: manhattan_accuracy |
|
value: 99.69504950495049 |
|
- type: manhattan_ap |
|
value: 90.59998550104231 |
|
- type: manhattan_f1 |
|
value: 83.91462779802187 |
|
- type: manhattan_precision |
|
value: 87.51357220412595 |
|
- type: manhattan_recall |
|
value: 80.60000000000001 |
|
- type: max_accuracy |
|
value: 99.69504950495049 |
|
- type: max_ap |
|
value: 90.59998550104231 |
|
- type: max_f1 |
|
value: 83.91462779802187 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: None |
|
name: MTEB StackExchangeClustering |
|
config: default |
|
split: test |
|
revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259 |
|
metrics: |
|
- type: v_measure |
|
value: 32.31610507058257 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: None |
|
name: MTEB StackExchangeClusteringP2P |
|
config: default |
|
split: test |
|
revision: 815ca46b2622cec33ccafc3735d572c266efdb44 |
|
metrics: |
|
- type: v_measure |
|
value: 29.125242344875502 |
|
- task: |
|
type: Reranking |
|
dataset: |
|
type: None |
|
name: MTEB StackOverflowDupQuestions |
|
config: default |
|
split: test |
|
revision: e185fbe320c72810689fc5848eb6114e1ef5ec69 |
|
metrics: |
|
- type: map |
|
value: 43.09273403724595 |
|
- type: mrr |
|
value: 43.54354999575587 |
|
- task: |
|
type: Summarization |
|
dataset: |
|
type: None |
|
name: MTEB SummEval |
|
config: default |
|
split: test |
|
revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 30.14375732010076 |
|
- type: cos_sim_spearman |
|
value: 29.565975101655656 |
|
- type: dot_pearson |
|
value: 30.14375735419279 |
|
- type: dot_spearman |
|
value: 29.497714274949065 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB TRECCOVID |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 0.11299999999999999 |
|
- type: map_at_10 |
|
value: 0.652 |
|
- type: map_at_100 |
|
value: 3.51 |
|
- type: map_at_1000 |
|
value: 8.445 |
|
- type: map_at_3 |
|
value: 0.259 |
|
- type: map_at_5 |
|
value: 0.392 |
|
- type: mrr_at_1 |
|
value: 46.0 |
|
- type: mrr_at_10 |
|
value: 58.263 |
|
- type: mrr_at_100 |
|
value: 58.935 |
|
- type: mrr_at_1000 |
|
value: 58.935 |
|
- type: mrr_at_3 |
|
value: 55.00000000000001 |
|
- type: mrr_at_5 |
|
value: 56.39999999999999 |
|
- type: ndcg_at_1 |
|
value: 41.0 |
|
- type: ndcg_at_10 |
|
value: 34.724 |
|
- type: ndcg_at_100 |
|
value: 27.108999999999998 |
|
- type: ndcg_at_1000 |
|
value: 24.773999999999997 |
|
- type: ndcg_at_3 |
|
value: 38.48 |
|
- type: ndcg_at_5 |
|
value: 37.399 |
|
- type: precision_at_1 |
|
value: 48.0 |
|
- type: precision_at_10 |
|
value: 37.2 |
|
- type: precision_at_100 |
|
value: 28.4 |
|
- type: precision_at_1000 |
|
value: 12.21 |
|
- type: precision_at_3 |
|
value: 42.667 |
|
- type: precision_at_5 |
|
value: 40.8 |
|
- type: recall_at_1 |
|
value: 0.11299999999999999 |
|
- type: recall_at_10 |
|
value: 0.8370000000000001 |
|
- type: recall_at_100 |
|
value: 5.992 |
|
- type: recall_at_1000 |
|
value: 24.051000000000002 |
|
- type: recall_at_3 |
|
value: 0.28800000000000003 |
|
- type: recall_at_5 |
|
value: 0.469 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB Touche2020 |
|
config: default |
|
split: test |
|
revision: a34f9a33db75fa0cbb21bb5cfc3dae8dc8bec93f |
|
metrics: |
|
- type: map_at_1 |
|
value: 2.173 |
|
- type: map_at_10 |
|
value: 8.079 |
|
- type: map_at_100 |
|
value: 13.44 |
|
- type: map_at_1000 |
|
value: 14.985000000000001 |
|
- type: map_at_3 |
|
value: 4.756 |
|
- type: map_at_5 |
|
value: 5.995 |
|
- type: mrr_at_1 |
|
value: 30.612000000000002 |
|
- type: mrr_at_10 |
|
value: 43.341 |
|
- type: mrr_at_100 |
|
value: 44.192 |
|
- type: mrr_at_1000 |
|
value: 44.192 |
|
- type: mrr_at_3 |
|
value: 40.136 |
|
- type: mrr_at_5 |
|
value: 41.463 |
|
- type: ndcg_at_1 |
|
value: 27.551 |
|
- type: ndcg_at_10 |
|
value: 20.093 |
|
- type: ndcg_at_100 |
|
value: 33.133 |
|
- type: ndcg_at_1000 |
|
value: 44.344 |
|
- type: ndcg_at_3 |
|
value: 25.82 |
|
- type: ndcg_at_5 |
|
value: 22.216 |
|
- type: precision_at_1 |
|
value: 30.612000000000002 |
|
- type: precision_at_10 |
|
value: 17.755000000000003 |
|
- type: precision_at_100 |
|
value: 7.469 |
|
- type: precision_at_1000 |
|
value: 1.465 |
|
- type: precision_at_3 |
|
value: 27.891 |
|
- type: precision_at_5 |
|
value: 22.448999999999998 |
|
- type: recall_at_1 |
|
value: 2.173 |
|
- type: recall_at_10 |
|
value: 12.662999999999998 |
|
- type: recall_at_100 |
|
value: 44.589 |
|
- type: recall_at_1000 |
|
value: 78.997 |
|
- type: recall_at_3 |
|
value: 5.955 |
|
- type: recall_at_5 |
|
value: 7.89 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: None |
|
name: MTEB ToxicConversationsClassification |
|
config: default |
|
split: test |
|
revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c |
|
metrics: |
|
- type: accuracy |
|
value: 69.899 |
|
- type: ap |
|
value: 13.50183607213333 |
|
- type: f1 |
|
value: 53.589735425592465 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: None |
|
name: MTEB TweetSentimentExtractionClassification |
|
config: default |
|
split: test |
|
revision: d604517c81ca91fe16a244d1248fc021f9ecee7a |
|
metrics: |
|
- type: accuracy |
|
value: 53.74080362195812 |
|
- type: f1 |
|
value: 53.940488490088434 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: None |
|
name: MTEB TwentyNewsgroupsClustering |
|
config: default |
|
split: test |
|
revision: 6125ec4e24fa026cec8a478383ee943acfbd5449 |
|
metrics: |
|
- type: v_measure |
|
value: 33.38930659623301 |
|
- task: |
|
type: PairClassification |
|
dataset: |
|
type: None |
|
name: MTEB TwitterSemEval2015 |
|
config: default |
|
split: test |
|
revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1 |
|
metrics: |
|
- type: cos_sim_accuracy |
|
value: 83.71580139476664 |
|
- type: cos_sim_ap |
|
value: 65.75325189939345 |
|
- type: cos_sim_f1 |
|
value: 62.39284383153186 |
|
- type: cos_sim_precision |
|
value: 58.95750176097676 |
|
- type: cos_sim_recall |
|
value: 66.25329815303431 |
|
- type: dot_accuracy |
|
value: 83.71580139476664 |
|
- type: dot_ap |
|
value: 65.75325189939345 |
|
- type: dot_f1 |
|
value: 62.39284383153186 |
|
- type: dot_precision |
|
value: 58.95750176097676 |
|
- type: dot_recall |
|
value: 66.25329815303431 |
|
- type: euclidean_accuracy |
|
value: 83.71580139476664 |
|
- type: euclidean_ap |
|
value: 65.75325189939345 |
|
- type: euclidean_f1 |
|
value: 62.39284383153186 |
|
- type: euclidean_precision |
|
value: 58.95750176097676 |
|
- type: euclidean_recall |
|
value: 66.25329815303431 |
|
- type: manhattan_accuracy |
|
value: 83.4714192048638 |
|
- type: manhattan_ap |
|
value: 64.42014741278865 |
|
- type: manhattan_f1 |
|
value: 60.886814469078175 |
|
- type: manhattan_precision |
|
value: 54.58158995815899 |
|
- type: manhattan_recall |
|
value: 68.83905013192611 |
|
- type: max_accuracy |
|
value: 83.71580139476664 |
|
- type: max_ap |
|
value: 65.75325189939345 |
|
- type: max_f1 |
|
value: 62.39284383153186 |
|
- task: |
|
type: PairClassification |
|
dataset: |
|
type: None |
|
name: MTEB TwitterURLCorpus |
|
config: default |
|
split: test |
|
revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf |
|
metrics: |
|
- type: cos_sim_accuracy |
|
value: 87.46846741956766 |
|
- type: cos_sim_ap |
|
value: 82.74561195728911 |
|
- type: cos_sim_f1 |
|
value: 74.91745501762196 |
|
- type: cos_sim_precision |
|
value: 72.29183074389633 |
|
- type: cos_sim_recall |
|
value: 77.74099168463196 |
|
- type: dot_accuracy |
|
value: 87.46846741956766 |
|
- type: dot_ap |
|
value: 82.74561216064899 |
|
- type: dot_f1 |
|
value: 74.91745501762196 |
|
- type: dot_precision |
|
value: 72.29183074389633 |
|
- type: dot_recall |
|
value: 77.74099168463196 |
|
- type: euclidean_accuracy |
|
value: 87.46846741956766 |
|
- type: euclidean_ap |
|
value: 82.74561227188258 |
|
- type: euclidean_f1 |
|
value: 74.91745501762196 |
|
- type: euclidean_precision |
|
value: 72.29183074389633 |
|
- type: euclidean_recall |
|
value: 77.74099168463196 |
|
- type: manhattan_accuracy |
|
value: 87.4607055536151 |
|
- type: manhattan_ap |
|
value: 82.82100726504085 |
|
- type: manhattan_f1 |
|
value: 74.95324413753418 |
|
- type: manhattan_precision |
|
value: 70.329373650108 |
|
- type: manhattan_recall |
|
value: 80.22790267939637 |
|
- type: max_accuracy |
|
value: 87.46846741956766 |
|
- type: max_ap |
|
value: 82.82100726504085 |
|
- type: max_f1 |
|
value: 74.95324413753418 |
|
--- |
