|
|
--- |
|
|
tags: |
|
|
- mteb |
|
|
model-index: |
|
|
- name: nomic_classification_50 |
|
|
results: |
|
|
- task: |
|
|
type: Classification |
|
|
dataset: |
|
|
type: None |
|
|
name: MTEB AmazonCounterfactualClassification (en) |
|
|
config: en |
|
|
split: test |
|
|
revision: e8379541af4e31359cca9fbcf4b00f2671dba205 |
|
|
metrics: |
|
|
- type: accuracy |
|
|
value: 67.26865671641791 |
|
|
- type: ap |
|
|
value: 30.002473367582354 |
|
|
- type: f1 |
|
|
value: 61.1971953752801 |
|
|
- task: |
|
|
type: Classification |
|
|
dataset: |
|
|
type: None |
|
|
name: MTEB AmazonPolarityClassification |
|
|
config: default |
|
|
split: test |
|
|
revision: e2d317d38cd51312af73b3d32a06d1a08b442046 |
|
|
metrics: |
|
|
- type: accuracy |
|
|
value: 64.285825 |
|
|
- type: ap |
|
|
value: 59.48909573055728 |
|
|
- type: f1 |
|
|
value: 63.9870581887586 |
|
|
- task: |
|
|
type: Classification |
|
|
dataset: |
|
|
type: None |
|
|
name: MTEB AmazonReviewsClassification (en) |
|
|
config: en |
|
|
split: test |
|
|
revision: 1399c76144fd37290681b995c656ef9b2e06e26d |
|
|
metrics: |
|
|
- type: accuracy |
|
|
value: 32.094 |
|
|
- type: f1 |
|
|
value: 31.58604218365913 |
|
|
- task: |
|
|
type: Retrieval |
|
|
dataset: |
|
|
type: None |
|
|
name: MTEB ArguAna |
|
|
config: default |
|
|
split: test |
|
|
revision: c22ab2a51041ffd869aaddef7af8d8215647e41a |
|
|
metrics: |
|
|
- type: map_at_1 |
|
|
value: 13.016 |
|
|
- type: map_at_10 |
|
|
value: 22.521 |
|
|
- type: map_at_100 |
|
|
value: 23.799 |
|
|
- type: map_at_1000 |
|
|
value: 23.883 |
|
|
- type: map_at_3 |
|
|
value: 19.381 |
|
|
- type: map_at_5 |
|
|
value: 20.928 |
|
|
- type: mrr_at_1 |
|
|
value: 13.442000000000002 |
|
|
- type: mrr_at_10 |
|
|
value: 22.667 |
|
|
- type: mrr_at_100 |
|
|
value: 23.944 |
|
|
- type: mrr_at_1000 |
|
|
value: 24.029 |
|
|
- type: mrr_at_3 |
|
|
value: 19.523 |
|
|
- type: mrr_at_5 |
|
|
value: 21.102 |
|
|
- type: ndcg_at_1 |
|
|
value: 13.016 |
|
|
- type: ndcg_at_10 |
|
|
value: 28.059 |
|
|
- type: ndcg_at_100 |
|
|
value: 34.812 |
|
|
- type: ndcg_at_1000 |
|
|
value: 37.074 |
|
|
- type: ndcg_at_3 |
|
|
value: 21.438 |
|
|
- type: ndcg_at_5 |
|
|
value: 24.238 |
|
|
- type: precision_at_1 |
|
|
value: 13.016 |
|
|
- type: precision_at_10 |
|
|
value: 4.595 |
|
|
- type: precision_at_100 |
|
|
value: 0.787 |
|
|
- type: precision_at_1000 |
|
|
value: 0.097 |
|
|
- type: precision_at_3 |
|
|
value: 9.128 |
|
|
- type: precision_at_5 |
|
|
value: 6.842 |
|
|
- type: recall_at_1 |
|
|
value: 13.016 |
|
|
- type: recall_at_10 |
|
|
value: 45.946 |
|
|
- type: recall_at_100 |
|
|
value: 78.73400000000001 |
|
|
- type: recall_at_1000 |
|
|
value: 96.515 |
|
|
- type: recall_at_3 |
|
|
value: 27.383000000000003 |
|
|
- type: recall_at_5 |
|
|
value: 34.211000000000006 |
|
|
- task: |
|
|
type: Clustering |
|
|
dataset: |
|
|
type: None |
|
|
name: MTEB ArxivClusteringP2P |
|
|
config: default |
|
|
split: test |
|
|
revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d |
|
|
metrics: |
|
|
- type: v_measure |
|
|
value: 25.72708581045921 |
|
|
- task: |
|
|
type: Clustering |
|
|
dataset: |
|
|
type: None |
|
|
name: MTEB ArxivClusteringS2S |
|
|
config: default |
|
|
split: test |
|
|
revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53 |
|
|
metrics: |
|
|
- type: v_measure |
|
|
value: 17.273102202229808 |
|
|
- task: |
|
|
type: Reranking |
|
|
dataset: |
|
|
type: None |
|
|
name: MTEB AskUbuntuDupQuestions |
|
|
config: default |
|
|
split: test |
|
|
revision: 2000358ca161889fa9c082cb41daa8dcfb161a54 |
|
|
metrics: |
|
|
- type: map |
|
|
value: 48.99875215426555 |
|
|
- type: mrr |
|
|
value: 60.91731521786923 |
|
|
- task: |
|
|
type: STS |
|
|
dataset: |
|
|
type: None |
|
|
name: MTEB BIOSSES |
|
|
config: default |
|
|
split: test |
|
|
revision: d3fb88f8f02e40887cd149695127462bbcf29b4a |
|
|
metrics: |
|
|
- type: cos_sim_pearson |
|
|
value: 67.57739420865997 |
|
|
- type: cos_sim_spearman |
|
|
value: 68.8491591362424 |
|
|
- type: euclidean_pearson |
|
|
value: 67.94540320514962 |
|
|
- type: euclidean_spearman |
|
|
value: 68.8491591362424 |
|
|
- type: manhattan_pearson |
|
|
value: 65.69150432274179 |
|
|
- type: manhattan_spearman |
|
|
value: 66.33223431652344 |
|
|
- task: |
|
|
type: Classification |
|
|
dataset: |
|
|
type: None |
|
|
name: MTEB Banking77Classification |
|
|
config: default |
|
|
split: test |
|
|
revision: 0fd18e25b25c072e09e0d92ab615fda904d66300 |
|
|
metrics: |
|
|
- type: accuracy |
|
|
value: 57.698051948051955 |
|
|
- type: f1 |
|
|
value: 56.00046616188858 |
|
|
- task: |
|
|
type: Clustering |
|
|
dataset: |
|
|
type: None |
|
|
name: MTEB BiorxivClusteringP2P |
|
|
config: default |
|
|
split: test |
|
|
revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40 |
|
|
metrics: |
|
|
- type: v_measure |
|
|
value: 24.472330529075432 |
|
|
- task: |
|
|
type: Clustering |
|
|
dataset: |
|
|
type: None |
|
|
name: MTEB BiorxivClusteringS2S |
|
|
config: default |
|
|
split: test |
|
|
revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908 |
|
|
metrics: |
|
|
- type: v_measure |
|
|
value: 15.20312280133779 |
|
|
- task: |
|
|
type: Retrieval |
|
|
dataset: |
|
|
type: None |
|
|
name: MTEB CQADupstackAndroidRetrieval |
|
|
config: default |
|
|
split: test |
|
|
revision: f46a197baaae43b4f621051089b82a364682dfeb |
|
|
metrics: |
|
|
- type: map_at_1 |
|
|
value: 11.856 |
|
|
- type: map_at_10 |
|
|
value: 15.922 |
|
|
- type: map_at_100 |
|
|
value: 16.692999999999998 |
|
|
- type: map_at_1000 |
|
|
value: 16.844 |
|
|
- type: map_at_3 |
|
|
value: 14.233 |
|
|
- type: map_at_5 |
|
|
value: 15.315999999999999 |
|
|
- type: mrr_at_1 |
|
|
value: 14.449000000000002 |
|
|
- type: mrr_at_10 |
|
|
value: 19.359 |
|
|
- type: mrr_at_100 |
|
|
value: 20.095 |
|
|
- type: mrr_at_1000 |
|
|
value: 20.194000000000003 |
|
|
- type: mrr_at_3 |
|
|
value: 17.501 |
|
|
- type: mrr_at_5 |
|
|
value: 18.66 |
|
|
- type: ndcg_at_1 |
|
|
value: 14.449000000000002 |
|
|
- type: ndcg_at_10 |
|
|
value: 19.192999999999998 |
|
|
- type: ndcg_at_100 |
|
|
value: 23.237 |
|
|
- type: ndcg_at_1000 |
|
|
value: 27.032 |
|
|
- type: ndcg_at_3 |
|
|
value: 16.265 |
|
|
- type: ndcg_at_5 |
|
|
value: 17.863 |
|
|
- type: precision_at_1 |
|
|
value: 14.449000000000002 |
|
|
- type: precision_at_10 |
|
|
value: 3.662 |
|
|
- type: precision_at_100 |
|
|
value: 0.718 |
|
|
- type: precision_at_1000 |
|
|
value: 0.129 |
|
|
- type: precision_at_3 |
|
|
value: 7.630000000000001 |
|
|
- type: precision_at_5 |
|
|
value: 5.866 |
|
|
- type: recall_at_1 |
|
|
value: 11.856 |
|
|
- type: recall_at_10 |
|
|
value: 25.694 |
|
|
- type: recall_at_100 |
|
|
value: 44.003 |
|
|
- type: recall_at_1000 |
|
|
value: 71.039 |
|
|
- type: recall_at_3 |
|
|
value: 17.136000000000003 |
|
|
- type: recall_at_5 |
|
|
value: 21.393 |
|
|
- task: |
|
|
type: Retrieval |
|
|
dataset: |
|
|
type: None |
|
|
name: MTEB CQADupstackEnglishRetrieval |
|
|
config: default |
|
|
split: test |
|
|
revision: ad9991cb51e31e31e430383c75ffb2885547b5f0 |
|
|
metrics: |
|
|
- type: map_at_1 |
|
|
value: 8.758000000000001 |
|
|
- type: map_at_10 |
|
|
value: 12.205 |
|
|
- type: map_at_100 |
|
|
value: 12.859000000000002 |
|
|
- type: map_at_1000 |
|
|
value: 12.967 |
|
|
- type: map_at_3 |
|
|
value: 11.196 |
|
|
- type: map_at_5 |
|
|
value: 11.676 |
|
|
- type: mrr_at_1 |
|
|
value: 11.21 |
|
|
- type: mrr_at_10 |
|
|
value: 15.062000000000001 |
|
|
- type: mrr_at_100 |
|
|
value: 15.720999999999998 |
|
|
- type: mrr_at_1000 |
|
|
value: 15.803 |
|
|
- type: mrr_at_3 |
|
|
value: 13.896 |
|
|
- type: mrr_at_5 |
|
|
value: 14.456 |
|
|
- type: ndcg_at_1 |
|
|
value: 11.21 |
|
|
- type: ndcg_at_10 |
|
|
value: 14.64 |
|
|
- type: ndcg_at_100 |
|
|
value: 18.163 |
|
|
- type: ndcg_at_1000 |
|
|
value: 21.15 |
|
|
- type: ndcg_at_3 |
|
|
value: 12.838 |
|
|
- type: ndcg_at_5 |
|
|
value: 13.475000000000001 |
|
|
- type: precision_at_1 |
|
|
value: 11.21 |
|
|
- type: precision_at_10 |
|
|
value: 2.79 |
|
|
- type: precision_at_100 |
|
|
value: 0.575 |
|
|
- type: precision_at_1000 |
|
|
value: 0.105 |
|
|
- type: precision_at_3 |
|
|
value: 6.306000000000001 |
|
|
- type: precision_at_5 |
|
|
value: 4.369 |
|
|
- type: recall_at_1 |
|
|
value: 8.758000000000001 |
|
|
- type: recall_at_10 |
|
|
value: 19.213 |
|
|
- type: recall_at_100 |
|
|
value: 35.434 |
|
|
- type: recall_at_1000 |
|
|
value: 56.720000000000006 |
|
|
- type: recall_at_3 |
|
|
value: 13.758999999999999 |
|
|
- type: recall_at_5 |
|
|
value: 15.618000000000002 |
|
|
- task: |
|
|
type: Retrieval |
|
|
dataset: |
|
|
type: None |
|
|
name: MTEB CQADupstackGamingRetrieval |
|
|
config: default |
|
|
split: test |
|
|
revision: 4885aa143210c98657558c04aaf3dc47cfb54340 |
|
|
metrics: |
|
|
- type: map_at_1 |
|
|
value: 11.655999999999999 |
|
|
- type: map_at_10 |
|
|
value: 15.429 |
|
|
- type: map_at_100 |
|
|
value: 16.223000000000003 |
|
|
- type: map_at_1000 |
|
|
value: 16.334 |
|
|
- type: map_at_3 |
|
|
value: 14.069999999999999 |
|
|
- type: map_at_5 |
|
|
value: 14.815000000000001 |
|
|
- type: mrr_at_1 |
|
|
value: 13.48 |
|
|
- type: mrr_at_10 |
|
|
value: 17.421 |
|
|
- type: mrr_at_100 |
|
|
value: 18.195 |
|
|
- type: mrr_at_1000 |
|
|
value: 18.285 |
|
|
- type: mrr_at_3 |
|
|
value: 15.967 |
|
|
- type: mrr_at_5 |
|
|
value: 16.75 |
|
|
- type: ndcg_at_1 |
|
|
value: 13.48 |
|
|
- type: ndcg_at_10 |
|
|
value: 18.053 |
|
|
- type: ndcg_at_100 |
|
|
value: 22.471 |
|
|
- type: ndcg_at_1000 |
|
|
value: 25.689 |
|
|
- type: ndcg_at_3 |
|
|
value: 15.290000000000001 |
|
|
- type: ndcg_at_5 |
|
|
value: 16.536 |
|
|
- type: precision_at_1 |
|
|
value: 13.48 |
|
|
- type: precision_at_10 |
|
|
value: 2.991 |
|
|
- type: precision_at_100 |
|
|
value: 0.586 |
|
|
- type: precision_at_1000 |
|
|
value: 0.095 |
|
|
- type: precision_at_3 |
|
|
value: 6.729 |
|
|
- type: precision_at_5 |
|
|
value: 4.853 |
|
|
- type: recall_at_1 |
|
|
value: 11.655999999999999 |
|
|
- type: recall_at_10 |
|
|
value: 24.329 |
|
|
- type: recall_at_100 |
|
|
value: 45.178000000000004 |
|
|
- type: recall_at_1000 |
|
|
value: 69.83200000000001 |
|
|
- type: recall_at_3 |
|
|
value: 16.692 |
|
|
- type: recall_at_5 |
|
|
value: 19.767000000000003 |
|
|
- task: |
|
|
type: Retrieval |
|
|
dataset: |
|
|
type: None |
|
|
name: MTEB CQADupstackGisRetrieval |
|
|
config: default |
|
|
split: test |
|
|
revision: 5003b3064772da1887988e05400cf3806fe491f2 |
|
|
metrics: |
|
|
- type: map_at_1 |
|
|
value: 3.672 |
|
|
- type: map_at_10 |
|
|
value: 5.507 |
|
|
- type: map_at_100 |
|
|
value: 5.853 |
|
|
- type: map_at_1000 |
|
|
value: 5.9319999999999995 |
|
|
- type: map_at_3 |
|
|
value: 4.648 |
|
|
- type: map_at_5 |
|
|
value: 5.087 |
|
|
- type: mrr_at_1 |
|
|
value: 4.0680000000000005 |
|
|
- type: mrr_at_10 |
|
|
value: 6.03 |
|
|
- type: mrr_at_100 |
|
|
value: 6.404999999999999 |
|
|
- type: mrr_at_1000 |
|
|
value: 6.485 |
|
|
- type: mrr_at_3 |
|
|
value: 5.16 |
|
|
- type: mrr_at_5 |
|
|
value: 5.595 |
|
|
- type: ndcg_at_1 |
|
|
value: 4.0680000000000005 |
|
|
- type: ndcg_at_10 |
|
|
value: 6.955 |
|
|
- type: ndcg_at_100 |
|
|
value: 9.059000000000001 |
|
|
- type: ndcg_at_1000 |
|
|
value: 11.916 |
|
|
- type: ndcg_at_3 |
|
|
value: 5.137 |
|
|
- type: ndcg_at_5 |
|
|
value: 5.912 |
|
|
- type: precision_at_1 |
|
|
value: 4.0680000000000005 |
|
|
- type: precision_at_10 |
|
|
value: 1.232 |
|
|
- type: precision_at_100 |
|
|
value: 0.246 |
|
|
- type: precision_at_1000 |
|
|
value: 0.053 |
|
|
- type: precision_at_3 |
|
|
value: 2.26 |
|
|
- type: precision_at_5 |
|
|
value: 1.763 |
|
|
- type: recall_at_1 |
|
|
value: 3.672 |
|
|
- type: recall_at_10 |
|
|
value: 11.149000000000001 |
|
|
- type: recall_at_100 |
|
|
value: 21.564 |
|
|
- type: recall_at_1000 |
|
|
value: 44.851 |
|
|
- type: recall_at_3 |
|
|
value: 6.008 |
|
|
- type: recall_at_5 |
|
|
value: 7.91 |
|
|
- task: |
|
|
type: Retrieval |
|
|
dataset: |
|
|
type: None |
|
|
name: MTEB CQADupstackMathematicaRetrieval |
|
|
config: default |
|
|
split: test |
|
|
revision: 90fceea13679c63fe563ded68f3b6f06e50061de |
|
|
metrics: |
|
|
- type: map_at_1 |
|
|
value: 2.308 |
|
|
- type: map_at_10 |
|
|
value: 3.431 |
|
|
- type: map_at_100 |
|
|
value: 3.8890000000000002 |
|
|
- type: map_at_1000 |
|
|
value: 3.988 |
|
|
- type: map_at_3 |
|
|
value: 2.896 |
|
|
- type: map_at_5 |
|
|
value: 3.182 |
|
|
- type: mrr_at_1 |
|
|
value: 2.9850000000000003 |
|
|
- type: mrr_at_10 |
|
|
value: 4.4110000000000005 |
|
|
- type: mrr_at_100 |
|
|
value: 4.925 |
|
|
- type: mrr_at_1000 |
|
|
value: 5.022 |
|
|
- type: mrr_at_3 |
|
|
value: 3.669 |
|
|
- type: mrr_at_5 |
|
|
value: 4.086 |
|
|
- type: ndcg_at_1 |
|
|
value: 2.9850000000000003 |
|
|
- type: ndcg_at_10 |
|
|
value: 4.463 |
|
|
- type: ndcg_at_100 |
|
|
value: 7.03 |
|
|
- type: ndcg_at_1000 |
|
|
value: 10.358 |
|
|
- type: ndcg_at_3 |
|
|
value: 3.3529999999999998 |
|
|
- type: ndcg_at_5 |
|
|
value: 3.866 |
|
|
- type: precision_at_1 |
|
|
value: 2.9850000000000003 |
|
|
- type: precision_at_10 |
|
|
value: 0.9079999999999999 |
|
|
- type: precision_at_100 |
|
|
value: 0.26 |
|
|
- type: precision_at_1000 |
|
|
value: 0.065 |
|
|
- type: precision_at_3 |
|
|
value: 1.575 |
|
|
- type: precision_at_5 |
|
|
value: 1.318 |
|
|
- type: recall_at_1 |
|
|
value: 2.308 |
|
|
- type: recall_at_10 |
|
|
value: 6.776999999999999 |
|
|
- type: recall_at_100 |
|
|
value: 18.618000000000002 |
|
|
- type: recall_at_1000 |
|
|
value: 44.175 |
|
|
- type: recall_at_3 |
|
|
value: 3.687 |
|
|
- type: recall_at_5 |
|
|
value: 4.948 |
|
|
- task: |
|
|
type: Retrieval |
|
|
dataset: |
|
|
type: None |
|
|
name: MTEB CQADupstackPhysicsRetrieval |
|
|
config: default |
|
|
split: test |
|
|
revision: 79531abbd1fb92d06c6d6315a0cbbbf5bb247ea4 |
|
|
metrics: |
|
|
- type: map_at_1 |
|
|
value: 6.862 |
|
|
- type: map_at_10 |
|
|
value: 9.94 |
|
|
- type: map_at_100 |
|
|
value: 10.624 |
|
|
- type: map_at_1000 |
|
|
value: 10.742 |
|
|
- type: map_at_3 |
|
|
value: 8.690000000000001 |
|
|
- type: map_at_5 |
|
|
value: 9.372 |
|
|
- type: mrr_at_1 |
|
|
value: 8.469999999999999 |
|
|
- type: mrr_at_10 |
|
|
value: 12.328999999999999 |
|
|
- type: mrr_at_100 |
|
|
value: 13.035 |
|
|
- type: mrr_at_1000 |
|
|
value: 13.123999999999999 |
|
|
- type: mrr_at_3 |
|
|
value: 10.828 |
|
|
- type: mrr_at_5 |
|
|
value: 11.752 |
|
|
- type: ndcg_at_1 |
|
|
value: 8.469999999999999 |
|
|
- type: ndcg_at_10 |
|
|
value: 12.377 |
|
|
- type: ndcg_at_100 |
|
|
value: 16.151 |
|
|
- type: ndcg_at_1000 |
|
|
value: 19.580000000000002 |
|
|
- type: ndcg_at_3 |
|
|
value: 9.964 |
|
|
- type: ndcg_at_5 |
|
|
value: 11.137 |
|
|
- type: precision_at_1 |
|
|
value: 8.469999999999999 |
|
|
- type: precision_at_10 |
|
|
value: 2.4250000000000003 |
|
|
- type: precision_at_100 |
|
|
value: 0.5479999999999999 |
|
|
- type: precision_at_1000 |
|
|
value: 0.10300000000000001 |
|
|
- type: precision_at_3 |
|
|
value: 4.812 |
|
|
- type: precision_at_5 |
|
|
value: 3.7539999999999996 |
|
|
- type: recall_at_1 |
|
|
value: 6.862 |
|
|
- type: recall_at_10 |
|
|
value: 17.59 |
|
|
- type: recall_at_100 |
|
|
value: 34.557 |
|
|
- type: recall_at_1000 |
|
|
value: 59.78099999999999 |
|
|
- type: recall_at_3 |
|
|
value: 10.838000000000001 |
|
|
- type: recall_at_5 |
|
|
value: 13.8 |
|
|
- task: |
|
|
type: Retrieval |
|
|
dataset: |
|
|
type: None |
|
|
name: MTEB CQADupstackProgrammersRetrieval |
|
|
config: default |
|
|
split: test |
|
|
revision: 6184bc1440d2dbc7612be22b50686b8826d22b32 |
|
|
metrics: |
|
|
- type: map_at_1 |
|
|
value: 4.569 |
|
|
- type: map_at_10 |
|
|
value: 6.9190000000000005 |
|
|
- type: map_at_100 |
|
|
value: 7.435 |
|
|
- type: map_at_1000 |
|
|
value: 7.553999999999999 |
|
|
- type: map_at_3 |
|
|
value: 6.0409999999999995 |
|
|
- type: map_at_5 |
|
|
value: 6.4159999999999995 |
|
|
- type: mrr_at_1 |
|
|
value: 5.822 |
|
|
- type: mrr_at_10 |
|
|
value: 8.639 |
|
|
- type: mrr_at_100 |
|
|
value: 9.195 |
|
|
- type: mrr_at_1000 |
|
|
value: 9.292 |
|
|
- type: mrr_at_3 |
|
|
value: 7.571999999999999 |
|
|
- type: mrr_at_5 |
|
|
value: 8.04 |
|
|
- type: ndcg_at_1 |
|
|
value: 5.822 |
|
|
- type: ndcg_at_10 |
|
|
value: 8.808 |
|
|
- type: ndcg_at_100 |
|
|
value: 11.846 |
|
|
- type: ndcg_at_1000 |
|
|
value: 15.476 |
|
|
- type: ndcg_at_3 |
|
|
value: 6.995 |
|
|
- type: ndcg_at_5 |
|
|
value: 7.5920000000000005 |
|
|
- type: precision_at_1 |
|
|
value: 5.822 |
|
|
- type: precision_at_10 |
|
|
value: 1.7469999999999999 |
|
|
- type: precision_at_100 |
|
|
value: 0.398 |
|
|
- type: precision_at_1000 |
|
|
value: 0.08800000000000001 |
|
|
- type: precision_at_3 |
|
|
value: 3.4250000000000003 |
|
|
- type: precision_at_5 |
|
|
value: 2.489 |
|
|
- type: recall_at_1 |
|
|
value: 4.569 |
|
|
- type: recall_at_10 |
|
|
value: 13.035 |
|
|
- type: recall_at_100 |
|
|
value: 27.102999999999998 |
|
|
- type: recall_at_1000 |
|
|
value: 54.137 |
|
|
- type: recall_at_3 |
|
|
value: 7.839 |
|
|
- type: recall_at_5 |
|
|
value: 9.469 |
|
|
- task: |
|
|
type: Retrieval |
|
|
dataset: |
|
|
type: mteb/cqadupstack |
|
|
name: MTEB CQADupstackRetrieval |
|
|
config: default |
|
|
split: test |
|
|
revision: 4885aa143210c98657558c04aaf3dc47cfb54340 |
|
|
metrics: |
|
|
- type: map_at_1 |
|
|
value: 6.289666666666665 |
|
|
- type: map_at_10 |
|
|
value: 8.76325 |
|
|
- type: map_at_100 |
|
|
value: 9.314083333333333 |
|
|
- type: map_at_1000 |
|
|
value: 9.419 |
|
|
- type: map_at_3 |
|
|
value: 7.856916666666668 |
|
|
- type: map_at_5 |
|
|
value: 8.359333333333334 |
|
|
- type: mrr_at_1 |
|
|
value: 7.752333333333332 |
|
|
- type: mrr_at_10 |
|
|
value: 10.620333333333333 |
|
|
- type: mrr_at_100 |
|
|
value: 11.191083333333333 |
|
|
- type: mrr_at_1000 |
|
|
value: 11.2795 |
|
|
- type: mrr_at_3 |
|
|
value: 9.572916666666668 |
|
|
- type: mrr_at_5 |
|
|
value: 10.152499999999998 |
|
|
- type: ndcg_at_1 |
|
|
value: 7.752333333333332 |
|
|
- type: ndcg_at_10 |
|
|
value: 10.657000000000002 |
|
|
- type: ndcg_at_100 |
|
|
value: 13.755166666666666 |
|
|
- type: ndcg_at_1000 |
|
|
value: 16.9275 |
|
|
- type: ndcg_at_3 |
|
|
value: 8.904916666666665 |
|
|
- type: ndcg_at_5 |
|
|
value: 9.709083333333334 |
|
|
- type: precision_at_1 |
|
|
value: 7.752333333333332 |
|
|
- type: precision_at_10 |
|
|
value: 1.969166666666667 |
|
|
- type: precision_at_100 |
|
|
value: 0.42624999999999996 |
|
|
- type: precision_at_1000 |
|
|
value: 0.08475000000000002 |
|
|
- type: precision_at_3 |
|
|
value: 4.182 |
|
|
- type: precision_at_5 |
|
|
value: 3.0942499999999997 |
|
|
- type: recall_at_1 |
|
|
value: 6.289666666666665 |
|
|
- type: recall_at_10 |
|
|
value: 14.695083333333333 |
|
|
- type: recall_at_100 |
|
|
value: 29.238666666666663 |
|
|
- type: recall_at_1000 |
|
|
value: 53.20016666666667 |
|
|
- type: recall_at_3 |
|
|
value: 9.667 |
|
|
- type: recall_at_5 |
|
|
value: 11.766416666666666 |
|
|
- task: |
|
|
type: Retrieval |
|
|
dataset: |
|
|
type: None |
|
|
name: MTEB CQADupstackStatsRetrieval |
|
|
config: default |
|
|
split: test |
|
|
revision: 65ac3a16b8e91f9cee4c9828cc7c335575432a2a |
|
|
metrics: |
|
|
- type: map_at_1 |
|
|
value: 5.188000000000001 |
|
|
- type: map_at_10 |
|
|
value: 6.97 |
|
|
- type: map_at_100 |
|
|
value: 7.380000000000001 |
|
|
- type: map_at_1000 |
|
|
value: 7.446999999999999 |
|
|
- type: map_at_3 |
|
|
value: 6.357 |
|
|
- type: map_at_5 |
|
|
value: 6.736000000000001 |
|
|
- type: mrr_at_1 |
|
|
value: 6.748 |
|
|
- type: mrr_at_10 |
|
|
value: 8.885 |
|
|
- type: mrr_at_100 |
|
|
value: 9.285 |
|
|
- type: mrr_at_1000 |
|
|
value: 9.353 |
|
|
- type: mrr_at_3 |
|
|
value: 8.206 |
|
|
- type: mrr_at_5 |
|
|
value: 8.689 |
|
|
- type: ndcg_at_1 |
|
|
value: 6.748 |
|
|
- type: ndcg_at_10 |
|
|
value: 8.394 |
|
|
- type: ndcg_at_100 |
|
|
value: 10.554 |
|
|
- type: ndcg_at_1000 |
|
|
value: 12.786 |
|
|
- type: ndcg_at_3 |
|
|
value: 7.227 |
|
|
- type: ndcg_at_5 |
|
|
value: 7.878 |
|
|
- type: precision_at_1 |
|
|
value: 6.748 |
|
|
- type: precision_at_10 |
|
|
value: 1.442 |
|
|
- type: precision_at_100 |
|
|
value: 0.27799999999999997 |
|
|
- type: precision_at_1000 |
|
|
value: 0.052 |
|
|
- type: precision_at_3 |
|
|
value: 3.3230000000000004 |
|
|
- type: precision_at_5 |
|
|
value: 2.4539999999999997 |
|
|
- type: recall_at_1 |
|
|
value: 5.188000000000001 |
|
|
- type: recall_at_10 |
|
|
value: 11.109 |
|
|
- type: recall_at_100 |
|
|
value: 21.134 |
|
|
- type: recall_at_1000 |
|
|
value: 38.686 |
|
|
- type: recall_at_3 |
|
|
value: 7.795000000000001 |
|
|
- type: recall_at_5 |
|
|
value: 9.435 |
|
|
- task: |
|
|
type: Retrieval |
|
|
dataset: |
|
|
type: None |
|
|
name: MTEB CQADupstackTexRetrieval |
|
|
config: default |
|
|
split: test |
|
|
revision: 46989137a86843e03a6195de44b09deda022eec7 |
|
|
metrics: |
|
|
- type: map_at_1 |
|
|
value: 3.4070000000000005 |
|
|
- type: map_at_10 |
|
|
value: 4.735 |
|
|
- type: map_at_100 |
|
|
value: 5.083 |
|
|
- type: map_at_1000 |
|
|
value: 5.162 |
|
|
- type: map_at_3 |
|
|
value: 4.261 |
|
|
- type: map_at_5 |
|
|
value: 4.504 |
|
|
- type: mrr_at_1 |
|
|
value: 4.1290000000000004 |
|
|
- type: mrr_at_10 |
|
|
value: 5.792 |
|
|
- type: mrr_at_100 |
|
|
value: 6.209 |
|
|
- type: mrr_at_1000 |
|
|
value: 6.283999999999999 |
|
|
- type: mrr_at_3 |
|
|
value: 5.173 |
|
|
- type: mrr_at_5 |
|
|
value: 5.505 |
|
|
- type: ndcg_at_1 |
|
|
value: 4.1290000000000004 |
|
|
- type: ndcg_at_10 |
|
|
value: 5.8020000000000005 |
|
|
- type: ndcg_at_100 |
|
|
value: 7.861 |
|
|
- type: ndcg_at_1000 |
|
|
value: 10.495000000000001 |
|
|
- type: ndcg_at_3 |
|
|
value: 4.79 |
|
|
- type: ndcg_at_5 |
|
|
value: 5.2299999999999995 |
|
|
- type: precision_at_1 |
|
|
value: 4.1290000000000004 |
|
|
- type: precision_at_10 |
|
|
value: 1.084 |
|
|
- type: precision_at_100 |
|
|
value: 0.262 |
|
|
- type: precision_at_1000 |
|
|
value: 0.06 |
|
|
- type: precision_at_3 |
|
|
value: 2.237 |
|
|
- type: precision_at_5 |
|
|
value: 1.6789999999999998 |
|
|
- type: recall_at_1 |
|
|
value: 3.4070000000000005 |
|
|
- type: recall_at_10 |
|
|
value: 8.057 |
|
|
- type: recall_at_100 |
|
|
value: 17.662 |
|
|
- type: recall_at_1000 |
|
|
value: 37.738 |
|
|
- type: recall_at_3 |
|
|
value: 5.27 |
|
|
- type: recall_at_5 |
|
|
value: 6.314 |
|
|
- task: |
|
|
type: Retrieval |
|
|
dataset: |
|
|
type: None |
|
|
name: MTEB CQADupstackUnixRetrieval |
|
|
config: default |
|
|
split: test |
|
|
revision: 6c6430d3a6d36f8d2a829195bc5dc94d7e063e53 |
|
|
metrics: |
|
|
- type: map_at_1 |
|
|
value: 5.559 |
|
|
- type: map_at_10 |
|
|
value: 7.374 |
|
|
- type: map_at_100 |
|
|
value: 7.9159999999999995 |
|
|
- type: map_at_1000 |
|
|
value: 8.007 |
|
|
- type: map_at_3 |
|
|
value: 6.882000000000001 |
|
|
- type: map_at_5 |
|
|
value: 7.1209999999999996 |
|
|
- type: mrr_at_1 |
|
|
value: 6.622999999999999 |
|
|
- type: mrr_at_10 |
|
|
value: 8.873000000000001 |
|
|
- type: mrr_at_100 |
|
|
value: 9.478 |
|
|
- type: mrr_at_1000 |
|
|
value: 9.562 |
|
|
- type: mrr_at_3 |
|
|
value: 8.256 |
|
|
- type: mrr_at_5 |
|
|
value: 8.535 |
|
|
- type: ndcg_at_1 |
|
|
value: 6.622999999999999 |
|
|
- type: ndcg_at_10 |
|
|
value: 8.738999999999999 |
|
|
- type: ndcg_at_100 |
|
|
value: 11.931 |
|
|
- type: ndcg_at_1000 |
|
|
value: 14.862 |
|
|
- type: ndcg_at_3 |
|
|
value: 7.713 |
|
|
- type: ndcg_at_5 |
|
|
value: 8.116 |
|
|
- type: precision_at_1 |
|
|
value: 6.622999999999999 |
|
|
- type: precision_at_10 |
|
|
value: 1.493 |
|
|
- type: precision_at_100 |
|
|
value: 0.361 |
|
|
- type: precision_at_1000 |
|
|
value: 0.06899999999999999 |
|
|
- type: precision_at_3 |
|
|
value: 3.6069999999999998 |
|
|
- type: precision_at_5 |
|
|
value: 2.463 |
|
|
- type: recall_at_1 |
|
|
value: 5.559 |
|
|
- type: recall_at_10 |
|
|
value: 11.509 |
|
|
- type: recall_at_100 |
|
|
value: 26.573 |
|
|
- type: recall_at_1000 |
|
|
value: 49.16 |
|
|
- type: recall_at_3 |
|
|
value: 8.468 |
|
|
- type: recall_at_5 |
|
|
value: 9.64 |
|
|
- task: |
|
|
type: Retrieval |
|
|
dataset: |
|
|
type: None |
|
|
name: MTEB CQADupstackWebmastersRetrieval |
|
|
config: default |
|
|
split: test |
|
|
revision: 160c094312a0e1facb97e55eeddb698c0abe3571 |
|
|
metrics: |
|
|
- type: map_at_1 |
|
|
value: 7.291 |
|
|
- type: map_at_10 |
|
|
value: 9.99 |
|
|
- type: map_at_100 |
|
|
value: 10.659 |
|
|
- type: map_at_1000 |
|
|
value: 10.793999999999999 |
|
|
- type: map_at_3 |
|
|
value: 8.968 |
|
|
- type: map_at_5 |
|
|
value: 9.59 |
|
|
- type: mrr_at_1 |
|
|
value: 9.684 |
|
|
- type: mrr_at_10 |
|
|
value: 12.812000000000001 |
|
|
- type: mrr_at_100 |
|
|
value: 13.482 |
|
|
- type: mrr_at_1000 |
|
|
value: 13.575999999999999 |
|
|
- type: mrr_at_3 |
|
|
value: 11.561 |
|
|
- type: mrr_at_5 |
|
|
value: 12.232999999999999 |
|
|
- type: ndcg_at_1 |
|
|
value: 9.684 |
|
|
- type: ndcg_at_10 |
|
|
value: 12.281 |
|
|
- type: ndcg_at_100 |
|
|
value: 15.994 |
|
|
- type: ndcg_at_1000 |
|
|
value: 19.578 |
|
|
- type: ndcg_at_3 |
|
|
value: 10.525 |
|
|
- type: ndcg_at_5 |
|
|
value: 11.349 |
|
|
- type: precision_at_1 |
|
|
value: 9.684 |
|
|
- type: precision_at_10 |
|
|
value: 2.451 |
|
|
- type: precision_at_100 |
|
|
value: 0.5910000000000001 |
|
|
- type: precision_at_1000 |
|
|
value: 0.132 |
|
|
- type: precision_at_3 |
|
|
value: 5.138 |
|
|
- type: precision_at_5 |
|
|
value: 3.794 |
|
|
- type: recall_at_1 |
|
|
value: 7.291 |
|
|
- type: recall_at_10 |
|
|
value: 16.28 |
|
|
- type: recall_at_100 |
|
|
value: 34.432 |
|
|
- type: recall_at_1000 |
|
|
value: 60.155 |
|
|
- type: recall_at_3 |
|
|
value: 10.767 |
|
|
- type: recall_at_5 |
|
|
value: 13.156 |
|
|
- task: |
|
|
type: Retrieval |
|
|
dataset: |
|
|
type: None |
|
|
name: MTEB CQADupstackWordpressRetrieval |
|
|
config: default |
|
|
split: test |
|
|
revision: 4ffe81d471b1924886b33c7567bfb200e9eec5c4 |
|
|
metrics: |
|
|
- type: map_at_1 |
|
|
value: 4.35 |
|
|
- type: map_at_10 |
|
|
value: 6.737 |
|
|
- type: map_at_100 |
|
|
value: 7.155 |
|
|
- type: map_at_1000 |
|
|
value: 7.257 |
|
|
- type: map_at_3 |
|
|
value: 6.0409999999999995 |
|
|
- type: map_at_5 |
|
|
value: 6.497 |
|
|
- type: mrr_at_1 |
|
|
value: 5.36 |
|
|
- type: mrr_at_10 |
|
|
value: 7.831 |
|
|
- type: mrr_at_100 |
|
|
value: 8.268 |
|
|
- type: mrr_at_1000 |
|
|
value: 8.373999999999999 |
|
|
- type: mrr_at_3 |
|
|
value: 7.086 |
|
|
- type: mrr_at_5 |
|
|
value: 7.529 |
|
|
- type: ndcg_at_1 |
|
|
value: 5.36 |
|
|
- type: ndcg_at_10 |
|
|
value: 8.179 |
|
|
- type: ndcg_at_100 |
|
|
value: 10.764999999999999 |
|
|
- type: ndcg_at_1000 |
|
|
value: 14.208000000000002 |
|
|
- type: ndcg_at_3 |
|
|
value: 6.762 |
|
|
- type: ndcg_at_5 |
|
|
value: 7.555000000000001 |
|
|
- type: precision_at_1 |
|
|
value: 5.36 |
|
|
- type: precision_at_10 |
|
|
value: 1.405 |
|
|
- type: precision_at_100 |
|
|
value: 0.292 |
|
|
- type: precision_at_1000 |
|
|
value: 0.066 |
|
|
- type: precision_at_3 |
|
|
value: 3.1419999999999995 |
|
|
- type: precision_at_5 |
|
|
value: 2.329 |
|
|
- type: recall_at_1 |
|
|
value: 4.35 |
|
|
- type: recall_at_10 |
|
|
value: 11.599 |
|
|
- type: recall_at_100 |
|
|
value: 24.606 |
|
|
- type: recall_at_1000 |
|
|
value: 52.128 |
|
|
- type: recall_at_3 |
|
|
value: 7.745 |
|
|
- type: recall_at_5 |
|
|
value: 9.747 |
|
|
- task: |
|
|
type: Retrieval |
|
|
dataset: |
|
|
type: None |
|
|
name: MTEB ClimateFEVER |
|
|
config: default |
|
|
split: test |
|
|
revision: 47f2ac6acb640fc46020b02a5b59fdda04d39380 |
|
|
metrics: |
|
|
- type: map_at_1 |
|
|
value: 1.496 |
|
|
- type: map_at_10 |
|
|
value: 2.412 |
|
|
- type: map_at_100 |
|
|
value: 2.899 |
|
|
- type: map_at_1000 |
|
|
value: 2.996 |
|
|
- type: map_at_3 |
|
|
value: 1.9949999999999999 |
|
|
- type: map_at_5 |
|
|
value: 2.171 |
|
|
- type: mrr_at_1 |
|
|
value: 3.1919999999999997 |
|
|
- type: mrr_at_10 |
|
|
value: 5.2589999999999995 |
|
|
- type: mrr_at_100 |
|
|
value: 6.053 |
|
|
- type: mrr_at_1000 |
|
|
value: 6.142 |
|
|
- type: mrr_at_3 |
|
|
value: 4.376 |
|
|
- type: mrr_at_5 |
|
|
value: 4.793 |
|
|
- type: ndcg_at_1 |
|
|
value: 3.1919999999999997 |
|
|
- type: ndcg_at_10 |
|
|
value: 3.81 |
|
|
- type: ndcg_at_100 |
|
|
value: 6.822 |
|
|
- type: ndcg_at_1000 |
|
|
value: 9.649000000000001 |
|
|
- type: ndcg_at_3 |
|
|
value: 2.817 |
|
|
- type: ndcg_at_5 |
|
|
value: 3.114 |
|
|
- type: precision_at_1 |
|
|
value: 3.1919999999999997 |
|
|
- type: precision_at_10 |
|
|
value: 1.29 |
|
|
- type: precision_at_100 |
|
|
value: 0.45199999999999996 |
|
|
- type: precision_at_1000 |
|
|
value: 0.097 |
|
|
- type: precision_at_3 |
|
|
value: 2.085 |
|
|
- type: precision_at_5 |
|
|
value: 1.6680000000000001 |
|
|
- type: recall_at_1 |
|
|
value: 1.496 |
|
|
- type: recall_at_10 |
|
|
value: 5.053 |
|
|
- type: recall_at_100 |
|
|
value: 16.066 |
|
|
- type: recall_at_1000 |
|
|
value: 32.796 |
|
|
- type: recall_at_3 |
|
|
value: 2.662 |
|
|
- type: recall_at_5 |
|
|
value: 3.434 |
|
|
- task: |
|
|
type: Retrieval |
|
|
dataset: |
|
|
type: None |
|
|
name: MTEB DBPedia |
|
|
config: default |
|
|
split: test |
|
|
revision: c0f706b76e590d620bd6618b3ca8efdd34e2d659 |
|
|
metrics: |
|
|
- type: map_at_1 |
|
|
value: 0.473 |
|
|
- type: map_at_10 |
|
|
value: 1.149 |
|
|
- type: map_at_100 |
|
|
value: 1.614 |
|
|
- type: map_at_1000 |
|
|
value: 1.7760000000000002 |
|
|
- type: map_at_3 |
|
|
value: 0.808 |
|
|
- type: map_at_5 |
|
|
value: 0.9520000000000001 |
|
|
- type: mrr_at_1 |
|
|
value: 9.0 |
|
|
- type: mrr_at_10 |
|
|
value: 13.528 |
|
|
- type: mrr_at_100 |
|
|
value: 14.567 |
|
|
- type: mrr_at_1000 |
|
|
value: 14.648 |
|
|
- type: mrr_at_3 |
|
|
value: 12.417 |
|
|
- type: mrr_at_5 |
|
|
value: 13.129 |
|
|
- type: ndcg_at_1 |
|
|
value: 6.375 |
|
|
- type: ndcg_at_10 |
|
|
value: 4.561 |
|
|
- type: ndcg_at_100 |
|
|
value: 5.412 |
|
|
- type: ndcg_at_1000 |
|
|
value: 8.173 |
|
|
- type: ndcg_at_3 |
|
|
value: 5.882 |
|
|
- type: ndcg_at_5 |
|
|
value: 5.16 |
|
|
- type: precision_at_1 |
|
|
value: 9.0 |
|
|
- type: precision_at_10 |
|
|
value: 4.45 |
|
|
- type: precision_at_100 |
|
|
value: 1.53 |
|
|
- type: precision_at_1000 |
|
|
value: 0.41000000000000003 |
|
|
- type: precision_at_3 |
|
|
value: 7.667 |
|
|
- type: precision_at_5 |
|
|
value: 6.1 |
|
|
- type: recall_at_1 |
|
|
value: 0.473 |
|
|
- type: recall_at_10 |
|
|
value: 2.11 |
|
|
- type: recall_at_100 |
|
|
value: 6.957000000000001 |
|
|
- type: recall_at_1000 |
|
|
value: 16.188 |
|
|
- type: recall_at_3 |
|
|
value: 1.031 |
|
|
- type: recall_at_5 |
|
|
value: 1.447 |
|
|
- task: |
|
|
type: Classification |
|
|
dataset: |
|
|
type: None |
|
|
name: MTEB EmotionClassification |
|
|
config: default |
|
|
split: test |
|
|
revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37 |
|
|
metrics: |
|
|
- type: accuracy |
|
|
value: 36.510000000000005 |
|
|
- type: f1 |
|
|
value: 32.55269059609507 |
|
|
- task: |
|
|
type: Retrieval |
|
|
dataset: |
|
|
type: None |
|
|
name: MTEB FEVER |
|
|
config: default |
|
|
split: test |
|
|
revision: bea83ef9e8fb933d90a2f1d5515737465d613e12 |
|
|
metrics: |
|
|
- type: map_at_1 |
|
|
value: 1.735 |
|
|
- type: map_at_10 |
|
|
value: 2.7969999999999997 |
|
|
- type: map_at_100 |
|
|
value: 3.0300000000000002 |
|
|
- type: map_at_1000 |
|
|
value: 3.078 |
|
|
- type: map_at_3 |
|
|
value: 2.408 |
|
|
- type: map_at_5 |
|
|
value: 2.62 |
|
|
- type: mrr_at_1 |
|
|
value: 1.83 |
|
|
- type: mrr_at_10 |
|
|
value: 2.946 |
|
|
- type: mrr_at_100 |
|
|
value: 3.196 |
|
|
- type: mrr_at_1000 |
|
|
value: 3.2460000000000004 |
|
|
- type: mrr_at_3 |
|
|
value: 2.54 |
|
|
- type: mrr_at_5 |
|
|
value: 2.768 |
|
|
- type: ndcg_at_1 |
|
|
value: 1.83 |
|
|
- type: ndcg_at_10 |
|
|
value: 3.481 |
|
|
- type: ndcg_at_100 |
|
|
value: 4.9110000000000005 |
|
|
- type: ndcg_at_1000 |
|
|
value: 6.553000000000001 |
|
|
- type: ndcg_at_3 |
|
|
value: 2.661 |
|
|
- type: ndcg_at_5 |
|
|
value: 3.052 |
|
|
- type: precision_at_1 |
|
|
value: 1.83 |
|
|
- type: precision_at_10 |
|
|
value: 0.59 |
|
|
- type: precision_at_100 |
|
|
value: 0.13899999999999998 |
|
|
- type: precision_at_1000 |
|
|
value: 0.029 |
|
|
- type: precision_at_3 |
|
|
value: 1.16 |
|
|
- type: precision_at_5 |
|
|
value: 0.897 |
|
|
- type: recall_at_1 |
|
|
value: 1.735 |
|
|
- type: recall_at_10 |
|
|
value: 5.514 |
|
|
- type: recall_at_100 |
|
|
value: 12.671 |
|
|
- type: recall_at_1000 |
|
|
value: 26.081 |
|
|
- type: recall_at_3 |
|
|
value: 3.2649999999999997 |
|
|
- type: recall_at_5 |
|
|
value: 4.205 |
|
|
- task: |
|
|
type: Retrieval |
|
|
dataset: |
|
|
type: None |
|
|
name: MTEB FiQA2018 |
|
|
config: default |
|
|
split: test |
|
|
revision: 27a168819829fe9bcd655c2df245fb19452e8e06 |
|
|
metrics: |
|
|
- type: map_at_1 |
|
|
value: 1.8519999999999999 |
|
|
- type: map_at_10 |
|
|
value: 3.3000000000000003 |
|
|
- type: map_at_100 |
|
|
value: 3.7699999999999996 |
|
|
- type: map_at_1000 |
|
|
value: 3.904 |
|
|
- type: map_at_3 |
|
|
value: 2.665 |
|
|
- type: map_at_5 |
|
|
value: 2.991 |
|
|
- type: mrr_at_1 |
|
|
value: 3.8580000000000005 |
|
|
- type: mrr_at_10 |
|
|
value: 6.611000000000001 |
|
|
- type: mrr_at_100 |
|
|
value: 7.244000000000001 |
|
|
- type: mrr_at_1000 |
|
|
value: 7.356999999999999 |
|
|
- type: mrr_at_3 |
|
|
value: 5.607 |
|
|
- type: mrr_at_5 |
|
|
value: 6.101 |
|
|
- type: ndcg_at_1 |
|
|
value: 3.8580000000000005 |
|
|
- type: ndcg_at_10 |
|
|
value: 5.081 |
|
|
- type: ndcg_at_100 |
|
|
value: 8.054 |
|
|
- type: ndcg_at_1000 |
|
|
value: 12.078999999999999 |
|
|
- type: ndcg_at_3 |
|
|
value: 3.934 |
|
|
- type: ndcg_at_5 |
|
|
value: 4.349 |
|
|
- type: precision_at_1 |
|
|
value: 3.8580000000000005 |
|
|
- type: precision_at_10 |
|
|
value: 1.6199999999999999 |
|
|
- type: precision_at_100 |
|
|
value: 0.477 |
|
|
- type: precision_at_1000 |
|
|
value: 0.11399999999999999 |
|
|
- type: precision_at_3 |
|
|
value: 2.881 |
|
|
- type: precision_at_5 |
|
|
value: 2.253 |
|
|
- type: recall_at_1 |
|
|
value: 1.8519999999999999 |
|
|
- type: recall_at_10 |
|
|
value: 7.109999999999999 |
|
|
- type: recall_at_100 |
|
|
value: 19.224 |
|
|
- type: recall_at_1000 |
|
|
value: 45.913 |
|
|
- type: recall_at_3 |
|
|
value: 3.6839999999999997 |
|
|
- type: recall_at_5 |
|
|
value: 4.999 |
|
|
- task: |
|
|
type: Retrieval |
|
|
dataset: |
|
|
type: None |
|
|
name: MTEB HotpotQA |
|
|
config: default |
|
|
split: test |
|
|
revision: ab518f4d6fcca38d87c25209f94beba119d02014 |
|
|
metrics: |
|
|
- type: map_at_1 |
|
|
value: 1.789 |
|
|
- type: map_at_10 |
|
|
value: 2.761 |
|
|
- type: map_at_100 |
|
|
value: 2.997 |
|
|
- type: map_at_1000 |
|
|
value: 3.05 |
|
|
- type: map_at_3 |
|
|
value: 2.4330000000000003 |
|
|
- type: map_at_5 |
|
|
value: 2.612 |
|
|
- type: mrr_at_1 |
|
|
value: 3.579 |
|
|
- type: mrr_at_10 |
|
|
value: 5.311 |
|
|
- type: mrr_at_100 |
|
|
value: 5.692 |
|
|
- type: mrr_at_1000 |
|
|
value: 5.762 |
|
|
- type: mrr_at_3 |
|
|
value: 4.718 |
|
|
- type: mrr_at_5 |
|
|
value: 5.035 |
|
|
- type: ndcg_at_1 |
|
|
value: 3.579 |
|
|
- type: ndcg_at_10 |
|
|
value: 3.988 |
|
|
- type: ndcg_at_100 |
|
|
value: 5.508 |
|
|
- type: ndcg_at_1000 |
|
|
value: 7.3340000000000005 |
|
|
- type: ndcg_at_3 |
|
|
value: 3.183 |
|
|
- type: ndcg_at_5 |
|
|
value: 3.5589999999999997 |
|
|
- type: precision_at_1 |
|
|
value: 3.579 |
|
|
- type: precision_at_10 |
|
|
value: 1.002 |
|
|
- type: precision_at_100 |
|
|
value: 0.22599999999999998 |
|
|
- type: precision_at_1000 |
|
|
value: 0.047 |
|
|
- type: precision_at_3 |
|
|
value: 2.116 |
|
|
- type: precision_at_5 |
|
|
value: 1.569 |
|
|
- type: recall_at_1 |
|
|
value: 1.789 |
|
|
- type: recall_at_10 |
|
|
value: 5.01 |
|
|
- type: recall_at_100 |
|
|
value: 11.296000000000001 |
|
|
- type: recall_at_1000 |
|
|
value: 23.733999999999998 |
|
|
- type: recall_at_3 |
|
|
value: 3.174 |
|
|
- type: recall_at_5 |
|
|
value: 3.923 |
|
|
- task: |
|
|
type: Classification |
|
|
dataset: |
|
|
type: None |
|
|
name: MTEB ImdbClassification |
|
|
config: default |
|
|
split: test |
|
|
revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7 |
|
|
metrics: |
|
|
- type: accuracy |
|
|
value: 64.362 |
|
|
- type: ap |
|
|
value: 59.55580844913024 |
|
|
- type: f1 |
|
|
value: 64.25451691590179 |
|
|
- task: |
|
|
type: Retrieval |
|
|
dataset: |
|
|
type: None |
|
|
name: MTEB MSMARCO |
|
|
config: default |
|
|
split: dev |
|
|
revision: c5a29a104738b98a9e76336939199e264163d4a0 |
|
|
metrics: |
|
|
- type: map_at_1 |
|
|
value: 1.719 |
|
|
- type: map_at_10 |
|
|
value: 2.812 |
|
|
- type: map_at_100 |
|
|
value: 3.124 |
|
|
- type: map_at_1000 |
|
|
value: 3.18 |
|
|
- type: map_at_3 |
|
|
value: 2.4 |
|
|
- type: map_at_5 |
|
|
value: 2.598 |
|
|
- type: mrr_at_1 |
|
|
value: 1.7770000000000001 |
|
|
- type: mrr_at_10 |
|
|
value: 2.889 |
|
|
- type: mrr_at_100 |
|
|
value: 3.211 |
|
|
- type: mrr_at_1000 |
|
|
value: 3.2680000000000002 |
|
|
- type: mrr_at_3 |
|
|
value: 2.467 |
|
|
- type: mrr_at_5 |
|
|
value: 2.67 |
|
|
- type: ndcg_at_1 |
|
|
value: 1.762 |
|
|
- type: ndcg_at_10 |
|
|
value: 3.52 |
|
|
- type: ndcg_at_100 |
|
|
value: 5.343 |
|
|
- type: ndcg_at_1000 |
|
|
value: 7.217999999999999 |
|
|
- type: ndcg_at_3 |
|
|
value: 2.64 |
|
|
- type: ndcg_at_5 |
|
|
value: 2.9979999999999998 |
|
|
- type: precision_at_1 |
|
|
value: 1.762 |
|
|
- type: precision_at_10 |
|
|
value: 0.5950000000000001 |
|
|
- type: precision_at_100 |
|
|
value: 0.155 |
|
|
- type: precision_at_1000 |
|
|
value: 0.032 |
|
|
- type: precision_at_3 |
|
|
value: 1.127 |
|
|
- type: precision_at_5 |
|
|
value: 0.857 |
|
|
- type: recall_at_1 |
|
|
value: 1.719 |
|
|
- type: recall_at_10 |
|
|
value: 5.743 |
|
|
- type: recall_at_100 |
|
|
value: 14.89 |
|
|
- type: recall_at_1000 |
|
|
value: 30.267 |
|
|
- type: recall_at_3 |
|
|
value: 3.2779999999999996 |
|
|
- type: recall_at_5 |
|
|
value: 4.136 |
|
|
- task: |
|
|
type: Classification |
|
|
dataset: |
|
|
type: None |
|
|
name: MTEB MTOPDomainClassification (en) |
|
|
config: en |
|
|
split: test |
|
|
revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf |
|
|
metrics: |
|
|
- type: accuracy |
|
|
value: 80.50615595075239 |
|
|
- type: f1 |
|
|
value: 80.1136210996985 |
|
|
- task: |
|
|
type: Classification |
|
|
dataset: |
|
|
type: None |
|
|
name: MTEB MTOPIntentClassification (en) |
|
|
config: en |
|
|
split: test |
|
|
revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba |
|
|
metrics: |
|
|
- type: accuracy |
|
|
value: 54.031007751937985 |
|
|
- type: f1 |
|
|
value: 34.910049182212575 |
|
|
- task: |
|
|
type: Classification |
|
|
dataset: |
|
|
type: None |
|
|
name: MTEB MassiveIntentClassification (en) |
|
|
config: en |
|
|
split: test |
|
|
revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 |
|
|
metrics: |
|
|
- type: accuracy |
|
|
value: 54.96973772696705 |
|
|
- type: f1 |
|
|
value: 51.482021499786136 |
|
|
- task: |
|
|
type: Classification |
|
|
dataset: |
|
|
type: None |
|
|
name: MTEB MassiveScenarioClassification (en) |
|
|
config: en |
|
|
split: test |
|
|
revision: 7d571f92784cd94a019292a1f45445077d0ef634 |
|
|
metrics: |
|
|
- type: accuracy |
|
|
value: 63.19771351714862 |
|
|
- type: f1 |
|
|
value: 61.16551291933069 |
|
|
- task: |
|
|
type: Clustering |
|
|
dataset: |
|
|
type: None |
|
|
name: MTEB MedrxivClusteringP2P |
|
|
config: default |
|
|
split: test |
|
|
revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73 |
|
|
metrics: |
|
|
- type: v_measure |
|
|
value: 23.502491371355365 |
|
|
- task: |
|
|
type: Clustering |
|
|
dataset: |
|
|
type: None |
|
|
name: MTEB MedrxivClusteringS2S |
|
|
config: default |
|
|
split: test |
|
|
revision: 35191c8c0dca72d8ff3efcd72aa802307d469663 |
|
|
metrics: |
|
|
- type: v_measure |
|
|
value: 20.04508433667435 |
|
|
- task: |
|
|
type: Reranking |
|
|
dataset: |
|
|
type: None |
|
|
name: MTEB MindSmallReranking |
|
|
config: default |
|
|
split: test |
|
|
revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69 |
|
|
metrics: |
|
|
- type: map |
|
|
value: 27.223268042111425 |
|
|
- type: mrr |
|
|
value: 27.804265249287663 |
|
|
- task: |
|
|
type: Retrieval |
|
|
dataset: |
|
|
type: None |
|
|
name: MTEB NFCorpus |
|
|
config: default |
|
|
split: test |
|
|
revision: ec0fa4fe99da2ff19ca1214b7966684033a58814 |
|
|
metrics: |
|
|
- type: map_at_1 |
|
|
value: 0.438 |
|
|
- type: map_at_10 |
|
|
value: 1.414 |
|
|
- type: map_at_100 |
|
|
value: 2.027 |
|
|
- type: map_at_1000 |
|
|
value: 2.866 |
|
|
- type: map_at_3 |
|
|
value: 0.9690000000000001 |
|
|
- type: map_at_5 |
|
|
value: 1.214 |
|
|
- type: mrr_at_1 |
|
|
value: 8.978 |
|
|
- type: mrr_at_10 |
|
|
value: 16.274 |
|
|
- type: mrr_at_100 |
|
|
value: 17.544999999999998 |
|
|
- type: mrr_at_1000 |
|
|
value: 17.649 |
|
|
- type: mrr_at_3 |
|
|
value: 13.674 |
|
|
- type: mrr_at_5 |
|
|
value: 15.021 |
|
|
- type: ndcg_at_1 |
|
|
value: 8.514 |
|
|
- type: ndcg_at_10 |
|
|
value: 7.301 |
|
|
- type: ndcg_at_100 |
|
|
value: 8.613999999999999 |
|
|
- type: ndcg_at_1000 |
|
|
value: 18.851000000000003 |
|
|
- type: ndcg_at_3 |
|
|
value: 8.193 |
|
|
- type: ndcg_at_5 |
|
|
value: 7.747999999999999 |
|
|
- type: precision_at_1 |
|
|
value: 8.978 |
|
|
- type: precision_at_10 |
|
|
value: 5.913 |
|
|
- type: precision_at_100 |
|
|
value: 3.198 |
|
|
- type: precision_at_1000 |
|
|
value: 1.6 |
|
|
- type: precision_at_3 |
|
|
value: 8.256 |
|
|
- type: precision_at_5 |
|
|
value: 7.1209999999999996 |
|
|
- type: recall_at_1 |
|
|
value: 0.438 |
|
|
- type: recall_at_10 |
|
|
value: 3.5360000000000005 |
|
|
- type: recall_at_100 |
|
|
value: 12.414 |
|
|
- type: recall_at_1000 |
|
|
value: 47.949000000000005 |
|
|
- type: recall_at_3 |
|
|
value: 1.462 |
|
|
- type: recall_at_5 |
|
|
value: 2.4299999999999997 |
|
|
- task: |
|
|
type: Retrieval |
|
|
dataset: |
|
|
type: None |
|
|
name: MTEB NQ |
|
|
config: default |
|
|
split: test |
|
|
revision: b774495ed302d8c44a3a7ea25c90dbce03968f31 |
|
|
metrics: |
|
|
- type: map_at_1 |
|
|
value: 2.2640000000000002 |
|
|
- type: map_at_10 |
|
|
value: 3.6859999999999995 |
|
|
- type: map_at_100 |
|
|
value: 4.071000000000001 |
|
|
- type: map_at_1000 |
|
|
value: 4.141 |
|
|
- type: map_at_3 |
|
|
value: 3.136 |
|
|
- type: map_at_5 |
|
|
value: 3.4130000000000003 |
|
|
- type: mrr_at_1 |
|
|
value: 2.52 |
|
|
- type: mrr_at_10 |
|
|
value: 4.093 |
|
|
- type: mrr_at_100 |
|
|
value: 4.51 |
|
|
- type: mrr_at_1000 |
|
|
value: 4.583 |
|
|
- type: mrr_at_3 |
|
|
value: 3.4909999999999997 |
|
|
- type: mrr_at_5 |
|
|
value: 3.791 |
|
|
- type: ndcg_at_1 |
|
|
value: 2.52 |
|
|
- type: ndcg_at_10 |
|
|
value: 4.696 |
|
|
- type: ndcg_at_100 |
|
|
value: 6.914 |
|
|
- type: ndcg_at_1000 |
|
|
value: 9.264999999999999 |
|
|
- type: ndcg_at_3 |
|
|
value: 3.5159999999999996 |
|
|
- type: ndcg_at_5 |
|
|
value: 4.026 |
|
|
- type: precision_at_1 |
|
|
value: 2.52 |
|
|
- type: precision_at_10 |
|
|
value: 0.855 |
|
|
- type: precision_at_100 |
|
|
value: 0.211 |
|
|
- type: precision_at_1000 |
|
|
value: 0.044000000000000004 |
|
|
- type: precision_at_3 |
|
|
value: 1.6420000000000001 |
|
|
- type: precision_at_5 |
|
|
value: 1.257 |
|
|
- type: recall_at_1 |
|
|
value: 2.2640000000000002 |
|
|
- type: recall_at_10 |
|
|
value: 7.478999999999999 |
|
|
- type: recall_at_100 |
|
|
value: 18.163 |
|
|
- type: recall_at_1000 |
|
|
value: 36.846000000000004 |
|
|
- type: recall_at_3 |
|
|
value: 4.268000000000001 |
|
|
- type: recall_at_5 |
|
|
value: 5.485 |
|
|
- task: |
|
|
type: Retrieval |
|
|
dataset: |
|
|
type: None |
|
|
name: MTEB QuoraRetrieval |
|
|
config: default |
|
|
split: test |
|
|
revision: None |
|
|
metrics: |
|
|
- type: map_at_1 |
|
|
value: 44.559 |
|
|
- type: map_at_10 |
|
|
value: 53.623 |
|
|
- type: map_at_100 |
|
|
value: 54.513999999999996 |
|
|
- type: map_at_1000 |
|
|
value: 54.584999999999994 |
|
|
- type: map_at_3 |
|
|
value: 51.229 |
|
|
- type: map_at_5 |
|
|
value: 52.635 |
|
|
- type: mrr_at_1 |
|
|
value: 51.23 |
|
|
- type: mrr_at_10 |
|
|
value: 58.431999999999995 |
|
|
- type: mrr_at_100 |
|
|
value: 59.00300000000001 |
|
|
- type: mrr_at_1000 |
|
|
value: 59.036 |
|
|
- type: mrr_at_3 |
|
|
value: 56.61000000000001 |
|
|
- type: mrr_at_5 |
|
|
value: 57.730000000000004 |
|
|
- type: ndcg_at_1 |
|
|
value: 51.28 |
|
|
- type: ndcg_at_10 |
|
|
value: 58.306000000000004 |
|
|
- type: ndcg_at_100 |
|
|
value: 61.915 |
|
|
- type: ndcg_at_1000 |
|
|
value: 63.343 |
|
|
- type: ndcg_at_3 |
|
|
value: 54.608000000000004 |
|
|
- type: ndcg_at_5 |
|
|
value: 56.431 |
|
|
- type: precision_at_1 |
|
|
value: 51.28 |
|
|
- type: precision_at_10 |
|
|
value: 8.755 |
|
|
- type: precision_at_100 |
|
|
value: 1.17 |
|
|
- type: precision_at_1000 |
|
|
value: 0.13899999999999998 |
|
|
- type: precision_at_3 |
|
|
value: 23.297 |
|
|
- type: precision_at_5 |
|
|
value: 15.598 |
|
|
- type: recall_at_1 |
|
|
value: 44.559 |
|
|
- type: recall_at_10 |
|
|
value: 67.491 |
|
|
- type: recall_at_100 |
|
|
value: 82.938 |
|
|
- type: recall_at_1000 |
|
|
value: 92.72200000000001 |
|
|
- type: recall_at_3 |
|
|
value: 56.952999999999996 |
|
|
- type: recall_at_5 |
|
|
value: 61.83 |
|
|
- task: |
|
|
type: Clustering |
|
|
dataset: |
|
|
type: None |
|
|
name: MTEB RedditClustering |
|
|
config: default |
|
|
split: test |
|
|
revision: 24640382cdbf8abc73003fb0fa6d111a705499eb |
|
|
metrics: |
|
|
- type: v_measure |
|
|
value: 22.705180109905008 |
|
|
- task: |
|
|
type: Clustering |
|
|
dataset: |
|
|
type: None |
|
|
name: MTEB RedditClusteringP2P |
|
|
config: default |
|
|
split: test |
|
|
revision: 282350215ef01743dc01b456c7f5241fa8937f16 |
|
|
metrics: |
|
|
- type: v_measure |
|
|
value: 34.83434688813055 |
|
|
- task: |
|
|
type: Retrieval |
|
|
dataset: |
|
|
type: None |
|
|
name: MTEB SCIDOCS |
|
|
config: default |
|
|
split: test |
|
|
revision: None |
|
|
metrics: |
|
|
- type: map_at_1 |
|
|
value: 1.13 |
|
|
- type: map_at_10 |
|
|
value: 2.4570000000000003 |
|
|
- type: map_at_100 |
|
|
value: 3.048 |
|
|
- type: map_at_1000 |
|
|
value: 3.234 |
|
|
- type: map_at_3 |
|
|
value: 1.802 |
|
|
- type: map_at_5 |
|
|
value: 2.078 |
|
|
- type: mrr_at_1 |
|
|
value: 5.6000000000000005 |
|
|
- type: mrr_at_10 |
|
|
value: 9.468 |
|
|
- type: mrr_at_100 |
|
|
value: 10.472 |
|
|
- type: mrr_at_1000 |
|
|
value: 10.605 |
|
|
- type: mrr_at_3 |
|
|
value: 7.7829999999999995 |
|
|
- type: mrr_at_5 |
|
|
value: 8.468 |
|
|
- type: ndcg_at_1 |
|
|
value: 5.6000000000000005 |
|
|
- type: ndcg_at_10 |
|
|
value: 4.936999999999999 |
|
|
- type: ndcg_at_100 |
|
|
value: 8.597000000000001 |
|
|
- type: ndcg_at_1000 |
|
|
value: 13.508999999999999 |
|
|
- type: ndcg_at_3 |
|
|
value: 4.345000000000001 |
|
|
- type: ndcg_at_5 |
|
|
value: 3.782 |
|
|
- type: precision_at_1 |
|
|
value: 5.6000000000000005 |
|
|
- type: precision_at_10 |
|
|
value: 2.68 |
|
|
- type: precision_at_100 |
|
|
value: 0.814 |
|
|
- type: precision_at_1000 |
|
|
value: 0.201 |
|
|
- type: precision_at_3 |
|
|
value: 4.0 |
|
|
- type: precision_at_5 |
|
|
value: 3.2800000000000002 |
|
|
- type: recall_at_1 |
|
|
value: 1.13 |
|
|
- type: recall_at_10 |
|
|
value: 5.457999999999999 |
|
|
- type: recall_at_100 |
|
|
value: 16.533 |
|
|
- type: recall_at_1000 |
|
|
value: 40.983000000000004 |
|
|
- type: recall_at_3 |
|
|
value: 2.44 |
|
|
- type: recall_at_5 |
|
|
value: 3.343 |
|
|
- task: |
|
|
type: STS |
|
|
dataset: |
|
|
type: None |
|
|
name: MTEB SICK-R |
|
|
config: default |
|
|
split: test |
|
|
revision: a6ea5a8cab320b040a23452cc28066d9beae2cee |
|
|
metrics: |
|
|
- type: cos_sim_pearson |
|
|
value: 73.60605619256489 |
|
|
- type: cos_sim_spearman |
|
|
value: 67.90225840700592 |
|
|
- type: euclidean_pearson |
|
|
value: 72.33353541178548 |
|
|
- type: euclidean_spearman |
|
|
value: 67.9022659941869 |
|
|
- type: manhattan_pearson |
|
|
value: 72.05976338595539 |
|
|
- type: manhattan_spearman |
|
|
value: 67.56691734710643 |
|
|
- task: |
|
|
type: STS |
|
|
dataset: |
|
|
type: None |
|
|
name: MTEB STS12 |
|
|
config: default |
|
|
split: test |
|
|
revision: a0d554a64d88156834ff5ae9920b964011b16384 |
|
|
metrics: |
|
|
- type: cos_sim_pearson |
|
|
value: 64.53970557195757 |
|
|
- type: cos_sim_spearman |
|
|
value: 57.30488503100292 |
|
|
- type: euclidean_pearson |
|
|
value: 61.892226450716926 |
|
|
- type: euclidean_spearman |
|
|
value: 57.30614347479237 |
|
|
- type: manhattan_pearson |
|
|
value: 62.211926976767394 |
|
|
- type: manhattan_spearman |
|
|
value: 57.68789726090663 |
|
|
- task: |
|
|
type: STS |
|
|
dataset: |
|
|
type: None |
|
|
name: MTEB STS13 |
|
|
config: default |
|
|
split: test |
|
|
revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca |
|
|
metrics: |
|
|
- type: cos_sim_pearson |
|
|
value: 71.42835803449617 |
|
|
- type: cos_sim_spearman |
|
|
value: 73.427655387467 |
|
|
- type: euclidean_pearson |
|
|
value: 72.95603876012058 |
|
|
- type: euclidean_spearman |
|
|
value: 73.42766761221965 |
|
|
- type: manhattan_pearson |
|
|
value: 72.95156508487149 |
|
|
- type: manhattan_spearman |
|
|
value: 73.50217040506452 |
|
|
- task: |
|
|
type: STS |
|
|
dataset: |
|
|
type: None |
|
|
name: MTEB STS14 |
|
|
config: default |
|
|
split: test |
|
|
revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375 |
|
|
metrics: |
|
|
- type: cos_sim_pearson |
|
|
value: 68.76336169760297 |
|
|
- type: cos_sim_spearman |
|
|
value: 65.84204583356208 |
|
|
- type: euclidean_pearson |
|
|
value: 68.43410821913582 |
|
|
- type: euclidean_spearman |
|
|
value: 65.84203615293073 |
|
|
- type: manhattan_pearson |
|
|
value: 68.31068072556376 |
|
|
- type: manhattan_spearman |
|
|
value: 65.83052670300172 |
|
|
- task: |
|
|
type: STS |
|
|
dataset: |
|
|
type: None |
|
|
name: MTEB STS15 |
|
|
config: default |
|
|
split: test |
|
|
revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3 |
|
|
metrics: |
|
|
- type: cos_sim_pearson |
|
|
value: 70.72278060206496 |
|
|
- type: cos_sim_spearman |
|
|
value: 72.94488223638993 |
|
|
- type: euclidean_pearson |
|
|
value: 72.87272723558824 |
|
|
- type: euclidean_spearman |
|
|
value: 72.9448808909619 |
|
|
- type: manhattan_pearson |
|
|
value: 73.14312374863987 |
|
|
- type: manhattan_spearman |
|
|
value: 73.17094226040652 |
|
|
- task: |
|
|
type: STS |
|
|
dataset: |
|
|
type: None |
|
|
name: MTEB STS16 |
|
|
config: default |
|
|
split: test |
|
|
revision: 4d8694f8f0e0100860b497b999b3dbed754a0513 |
|
|
metrics: |
|
|
- type: cos_sim_pearson |
|
|
value: 67.38872313741369 |
|
|
- type: cos_sim_spearman |
|
|
value: 69.39591053377866 |
|
|
- type: euclidean_pearson |
|
|
value: 69.51934754021094 |
|
|
- type: euclidean_spearman |
|
|
value: 69.39674025878926 |
|
|
- type: manhattan_pearson |
|
|
value: 69.45552921345616 |
|
|
- type: manhattan_spearman |
|
|
value: 69.43073792027799 |
|
|
- task: |
|
|
type: STS |
|
|
dataset: |
|
|
type: None |
|
|
name: MTEB STS17 (en-en) |
|
|
config: en-en |
|
|
split: test |
|
|
revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d |
|
|
metrics: |
|
|
- type: cos_sim_pearson |
|
|
value: 74.8928962240664 |
|
|
- type: cos_sim_spearman |
|
|
value: 78.20100249603948 |
|
|
- type: euclidean_pearson |
|
|
value: 78.32388609298962 |
|
|
- type: euclidean_spearman |
|
|
value: 78.20188000341075 |
|
|
- type: manhattan_pearson |
|
|
value: 78.4500539248116 |
|
|
- type: manhattan_spearman |
|
|
value: 78.19642157133745 |
|
|
- task: |
|
|
type: STS |
|
|
dataset: |
|
|
type: None |
|
|
name: MTEB STS22 (en) |
|
|
config: en |
|
|
split: test |
|
|
revision: eea2b4fe26a775864c896887d910b76a8098ad3f |
|
|
metrics: |
|
|
- type: cos_sim_pearson |
|
|
value: 58.85262050940674 |
|
|
- type: cos_sim_spearman |
|
|
value: 58.37965417152291 |
|
|
- type: euclidean_pearson |
|
|
value: 59.76016227940433 |
|
|
- type: euclidean_spearman |
|
|
value: 58.37965417152291 |
|
|
- type: manhattan_pearson |
|
|
value: 60.2166257965911 |
|
|
- type: manhattan_spearman |
|
|
value: 58.747276855442045 |
|
|
- task: |
|
|
type: STS |
|
|
dataset: |
|
|
type: None |
|
|
name: MTEB STSBenchmark |
|
|
config: default |
|
|
split: test |
|
|
revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831 |
|
|
metrics: |
|
|
- type: cos_sim_pearson |
|
|
value: 65.88908703880968 |
|
|
- type: cos_sim_spearman |
|
|
value: 64.7638356299519 |
|
|
- type: euclidean_pearson |
|
|
value: 66.43284083997051 |
|
|
- type: euclidean_spearman |
|
|
value: 64.76388404493919 |
|
|
- type: manhattan_pearson |
|
|
value: 66.54689278447367 |
|
|
- type: manhattan_spearman |
|
|
value: 64.76609191059656 |
|
|
- task: |
|
|
type: Reranking |
|
|
dataset: |
|
|
type: None |
|
|
name: MTEB SciDocsRR |
|
|
config: default |
|
|
split: test |
|
|
revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab |
|
|
metrics: |
|
|
- type: map |
|
|
value: 62.39526919052546 |
|
|
- type: mrr |
|
|
value: 83.57624673801143 |
|
|
- task: |
|
|
type: Retrieval |
|
|
dataset: |
|
|
type: None |
|
|
name: MTEB SciFact |
|
|
config: default |
|
|
split: test |
|
|
revision: 0228b52cf27578f30900b9e5271d331663a030d7 |
|
|
metrics: |
|
|
- type: map_at_1 |
|
|
value: 11.472 |
|
|
- type: map_at_10 |
|
|
value: 15.892000000000001 |
|
|
- type: map_at_100 |
|
|
value: 16.75 |
|
|
- type: map_at_1000 |
|
|
value: 16.898 |
|
|
- type: map_at_3 |
|
|
value: 14.167 |
|
|
- type: map_at_5 |
|
|
value: 15.0 |
|
|
- type: mrr_at_1 |
|
|
value: 12.667 |
|
|
- type: mrr_at_10 |
|
|
value: 17.065 |
|
|
- type: mrr_at_100 |
|
|
value: 17.899 |
|
|
- type: mrr_at_1000 |
|
|
value: 18.035999999999998 |
|
|
- type: mrr_at_3 |
|
|
value: 15.443999999999999 |
|
|
- type: mrr_at_5 |
|
|
value: 16.228 |
|
|
- type: ndcg_at_1 |
|
|
value: 12.667 |
|
|
- type: ndcg_at_10 |
|
|
value: 18.856 |
|
|
- type: ndcg_at_100 |
|
|
value: 23.555999999999997 |
|
|
- type: ndcg_at_1000 |
|
|
value: 28.138 |
|
|
- type: ndcg_at_3 |
|
|
value: 15.360999999999999 |
|
|
- type: ndcg_at_5 |
|
|
value: 16.712 |
|
|
- type: precision_at_1 |
|
|
value: 12.667 |
|
|
- type: precision_at_10 |
|
|
value: 3.033 |
|
|
- type: precision_at_100 |
|
|
value: 0.563 |
|
|
- type: precision_at_1000 |
|
|
value: 0.098 |
|
|
- type: precision_at_3 |
|
|
value: 6.444 |
|
|
- type: precision_at_5 |
|
|
value: 4.6 |
|
|
- type: recall_at_1 |
|
|
value: 11.472 |
|
|
- type: recall_at_10 |
|
|
value: 27.278000000000002 |
|
|
- type: recall_at_100 |
|
|
value: 49.917 |
|
|
- type: recall_at_1000 |
|
|
value: 86.75 |
|
|
- type: recall_at_3 |
|
|
value: 17.416999999999998 |
|
|
- type: recall_at_5 |
|
|
value: 20.75 |
|
|
- task: |
|
|
type: PairClassification |
|
|
dataset: |
|
|
type: None |
|
|
name: MTEB SprintDuplicateQuestions |
|
|
config: default |
|
|
split: test |
|
|
revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46 |
|
|
metrics: |
|
|
- type: cos_sim_accuracy |
|
|
value: 99.31683168316832 |
|
|
- type: cos_sim_ap |
|
|
value: 61.13034379900418 |
|
|
- type: cos_sim_f1 |
|
|
value: 58.92957746478873 |
|
|
- type: cos_sim_precision |
|
|
value: 67.48387096774194 |
|
|
- type: cos_sim_recall |
|
|
value: 52.300000000000004 |
|
|
- type: dot_accuracy |
|
|
value: 99.31683168316832 |
|
|
- type: dot_ap |
|
|
value: 61.13034379900418 |
|
|
- type: dot_f1 |
|
|
value: 58.92957746478873 |
|
|
- type: dot_precision |
|
|
value: 67.48387096774194 |
|
|
- type: dot_recall |
|
|
value: 52.300000000000004 |
|
|
- type: euclidean_accuracy |
|
|
value: 99.31683168316832 |
|
|
- type: euclidean_ap |
|
|
value: 61.13034379900418 |
|
|
- type: euclidean_f1 |
|
|
value: 58.92957746478873 |
|
|
- type: euclidean_precision |
|
|
value: 67.48387096774194 |
|
|
- type: euclidean_recall |
|
|
value: 52.300000000000004 |
|
|
- type: manhattan_accuracy |
|
|
value: 99.34554455445544 |
|
|
- type: manhattan_ap |
|
|
value: 63.09142729872116 |
|
|
- type: manhattan_f1 |
|
|
value: 61.02425876010782 |
|
|
- type: manhattan_precision |
|
|
value: 66.19883040935673 |
|
|
- type: manhattan_recall |
|
|
value: 56.599999999999994 |
|
|
- type: max_accuracy |
|
|
value: 99.34554455445544 |
|
|
- type: max_ap |
|
|
value: 63.09142729872116 |
|
|
- type: max_f1 |
|
|
value: 61.02425876010782 |
|
|
- task: |
|
|
type: Clustering |
|
|
dataset: |
|
|
type: None |
|
|
name: MTEB StackExchangeClustering |
|
|
config: default |
|
|
split: test |
|
|
revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259 |
|
|
metrics: |
|
|
- type: v_measure |
|
|
value: 31.859456190950397 |
|
|
- task: |
|
|
type: Clustering |
|
|
dataset: |
|
|
type: None |
|
|
name: MTEB StackExchangeClusteringP2P |
|
|
config: default |
|
|
split: test |
|
|
revision: 815ca46b2622cec33ccafc3735d572c266efdb44 |
|
|
metrics: |
|
|
- type: v_measure |
|
|
value: 29.22083488612398 |
|
|
- task: |
|
|
type: Reranking |
|
|
dataset: |
|
|
type: None |
|
|
name: MTEB StackOverflowDupQuestions |
|
|
config: default |
|
|
split: test |
|
|
revision: e185fbe320c72810689fc5848eb6114e1ef5ec69 |
|
|
metrics: |
|
|
- type: map |
|
|
value: 38.763497690161216 |
|
|
- type: mrr |
|
|
value: 38.9332134368899 |
|
|
- task: |
|
|
type: Summarization |
|
|
dataset: |
|
|
type: None |
|
|
name: MTEB SummEval |
|
|
config: default |
|
|
split: test |
|
|
revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c |
|
|
metrics: |
|
|
- type: cos_sim_pearson |
|
|
value: 31.037408929578664 |
|
|
- type: cos_sim_spearman |
|
|
value: 29.62877340560356 |
|
|
- type: dot_pearson |
|
|
value: 31.037408876961713 |
|
|
- type: dot_spearman |
|
|
value: 29.578544636218147 |
|
|
- task: |
|
|
type: Retrieval |
|
|
dataset: |
|
|
type: None |
|
|
name: MTEB TRECCOVID |
|
|
config: default |
|
|
split: test |
|
|
revision: None |
|
|
metrics: |
|
|
- type: map_at_1 |
|
|
value: 0.055999999999999994 |
|
|
- type: map_at_10 |
|
|
value: 0.292 |
|
|
- type: map_at_100 |
|
|
value: 1.335 |
|
|
- type: map_at_1000 |
|
|
value: 3.074 |
|
|
- type: map_at_3 |
|
|
value: 0.123 |
|
|
- type: map_at_5 |
|
|
value: 0.191 |
|
|
- type: mrr_at_1 |
|
|
value: 28.000000000000004 |
|
|
- type: mrr_at_10 |
|
|
value: 38.879999999999995 |
|
|
- type: mrr_at_100 |
|
|
value: 39.953 |
|
|
- type: mrr_at_1000 |
|
|
value: 39.978 |
|
|
- type: mrr_at_3 |
|
|
value: 33.333 |
|
|
- type: mrr_at_5 |
|
|
value: 37.233 |
|
|
- type: ndcg_at_1 |
|
|
value: 22.0 |
|
|
- type: ndcg_at_10 |
|
|
value: 19.601 |
|
|
- type: ndcg_at_100 |
|
|
value: 14.735000000000001 |
|
|
- type: ndcg_at_1000 |
|
|
value: 14.915000000000001 |
|
|
- type: ndcg_at_3 |
|
|
value: 20.358 |
|
|
- type: ndcg_at_5 |
|
|
value: 21.543 |
|
|
- type: precision_at_1 |
|
|
value: 28.000000000000004 |
|
|
- type: precision_at_10 |
|
|
value: 21.2 |
|
|
- type: precision_at_100 |
|
|
value: 15.5 |
|
|
- type: precision_at_1000 |
|
|
value: 7.417999999999999 |
|
|
- type: precision_at_3 |
|
|
value: 22.667 |
|
|
- type: precision_at_5 |
|
|
value: 24.4 |
|
|
- type: recall_at_1 |
|
|
value: 0.055999999999999994 |
|
|
- type: recall_at_10 |
|
|
value: 0.44799999999999995 |
|
|
- type: recall_at_100 |
|
|
value: 3.3070000000000004 |
|
|
- type: recall_at_1000 |
|
|
value: 15.334 |
|
|
- type: recall_at_3 |
|
|
value: 0.13699999999999998 |
|
|
- type: recall_at_5 |
|
|
value: 0.27499999999999997 |
|
|
- task: |
|
|
type: Retrieval |
|
|
dataset: |
|
|
type: None |
|
|
name: MTEB Touche2020 |
|
|
config: default |
|
|
split: test |
|
|
revision: a34f9a33db75fa0cbb21bb5cfc3dae8dc8bec93f |
|
|
metrics: |
|
|
- type: map_at_1 |
|
|
value: 1.66 |
|
|
- type: map_at_10 |
|
|
value: 4.183 |
|
|
- type: map_at_100 |
|
|
value: 5.748 |
|
|
- type: map_at_1000 |
|
|
value: 6.645 |
|
|
- type: map_at_3 |
|
|
value: 3.024 |
|
|
- type: map_at_5 |
|
|
value: 3.711 |
|
|
- type: mrr_at_1 |
|
|
value: 24.490000000000002 |
|
|
- type: mrr_at_10 |
|
|
value: 30.226 |
|
|
- type: mrr_at_100 |
|
|
value: 31.849 |
|
|
- type: mrr_at_1000 |
|
|
value: 31.915 |
|
|
- type: mrr_at_3 |
|
|
value: 27.211000000000002 |
|
|
- type: mrr_at_5 |
|
|
value: 29.048000000000002 |
|
|
- type: ndcg_at_1 |
|
|
value: 23.469 |
|
|
- type: ndcg_at_10 |
|
|
value: 12.527 |
|
|
- type: ndcg_at_100 |
|
|
value: 17.624000000000002 |
|
|
- type: ndcg_at_1000 |
|
|
value: 28.534 |
|
|
- type: ndcg_at_3 |
|
|
value: 18.118000000000002 |
|
|
- type: ndcg_at_5 |
|
|
value: 15.520999999999999 |
|
|
- type: precision_at_1 |
|
|
value: 24.490000000000002 |
|
|
- type: precision_at_10 |
|
|
value: 9.592 |
|
|
- type: precision_at_100 |
|
|
value: 3.653 |
|
|
- type: precision_at_1000 |
|
|
value: 1.006 |
|
|
- type: precision_at_3 |
|
|
value: 17.687 |
|
|
- type: precision_at_5 |
|
|
value: 14.285999999999998 |
|
|
- type: recall_at_1 |
|
|
value: 1.66 |
|
|
- type: recall_at_10 |
|
|
value: 6.419 |
|
|
- type: recall_at_100 |
|
|
value: 20.97 |
|
|
- type: recall_at_1000 |
|
|
value: 55.001 |
|
|
- type: recall_at_3 |
|
|
value: 3.37 |
|
|
- type: recall_at_5 |
|
|
value: 4.855 |
|
|
- task: |
|
|
type: Classification |
|
|
dataset: |
|
|
type: None |
|
|
name: MTEB ToxicConversationsClassification |
|
|
config: default |
|
|
split: test |
|
|
revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c |
|
|
metrics: |
|
|
- type: accuracy |
|
|
value: 64.55300000000001 |
|
|
- type: ap |
|
|
value: 11.51171190900715 |
|
|
- type: f1 |
|
|
value: 49.64107076870409 |
|
|
- task: |
|
|
type: Classification |
|
|
dataset: |
|
|
type: None |
|
|
name: MTEB TweetSentimentExtractionClassification |
|
|
config: default |
|
|
split: test |
|
|
revision: d604517c81ca91fe16a244d1248fc021f9ecee7a |
|
|
metrics: |
|
|
- type: accuracy |
|
|
value: 52.857951329937755 |
|
|
- type: f1 |
|
|
value: 52.984245378050296 |
|
|
- task: |
|
|
type: Clustering |
|
|
dataset: |
|
|
type: None |
|
|
name: MTEB TwentyNewsgroupsClustering |
|
|
config: default |
|
|
split: test |
|
|
revision: 6125ec4e24fa026cec8a478383ee943acfbd5449 |
|
|
metrics: |
|
|
- type: v_measure |
|
|
value: 25.391338056888934 |
|
|
- task: |
|
|
type: PairClassification |
|
|
dataset: |
|
|
type: None |
|
|
name: MTEB TwitterSemEval2015 |
|
|
config: default |
|
|
split: test |
|
|
revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1 |
|
|
metrics: |
|
|
- type: cos_sim_accuracy |
|
|
value: 83.24491863861239 |
|
|
- type: cos_sim_ap |
|
|
value: 63.21977665263634 |
|
|
- type: cos_sim_f1 |
|
|
value: 60.90813587019961 |
|
|
- type: cos_sim_precision |
|
|
value: 54.61586769939293 |
|
|
- type: cos_sim_recall |
|
|
value: 68.83905013192611 |
|
|
- type: dot_accuracy |
|
|
value: 83.24491863861239 |
|
|
- type: dot_ap |
|
|
value: 63.21977665263634 |
|
|
- type: dot_f1 |
|
|
value: 60.90813587019961 |
|
|
- type: dot_precision |
|
|
value: 54.61586769939293 |
|
|
- type: dot_recall |
|
|
value: 68.83905013192611 |
|
|
- type: euclidean_accuracy |
|
|
value: 83.24491863861239 |
|
|
- type: euclidean_ap |
|
|
value: 63.21977665263634 |
|
|
- type: euclidean_f1 |
|
|
value: 60.90813587019961 |
|
|
- type: euclidean_precision |
|
|
value: 54.61586769939293 |
|
|
- type: euclidean_recall |
|
|
value: 68.83905013192611 |
|
|
- type: manhattan_accuracy |
|
|
value: 83.05418131966383 |
|
|
- type: manhattan_ap |
|
|
value: 62.73044800285885 |
|
|
- type: manhattan_f1 |
|
|
value: 60.47024246877296 |
|
|
- type: manhattan_precision |
|
|
value: 56.42138939670932 |
|
|
- type: manhattan_recall |
|
|
value: 65.14511873350924 |
|
|
- type: max_accuracy |
|
|
value: 83.24491863861239 |
|
|
- type: max_ap |
|
|
value: 63.21977665263634 |
|
|
- type: max_f1 |
|
|
value: 60.90813587019961 |
|
|
- task: |
|
|
type: PairClassification |
|
|
dataset: |
|
|
type: None |
|
|
name: MTEB TwitterURLCorpus |
|
|
config: default |
|
|
split: test |
|
|
revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf |
|
|
metrics: |
|
|
- type: cos_sim_accuracy |
|
|
value: 85.89086816470679 |
|
|
- type: cos_sim_ap |
|
|
value: 78.81106183704443 |
|
|
- type: cos_sim_f1 |
|
|
value: 71.13646466143133 |
|
|
- type: cos_sim_precision |
|
|
value: 68.54654483152484 |
|
|
- type: cos_sim_recall |
|
|
value: 73.92978133661842 |
|
|
- type: dot_accuracy |
|
|
value: 85.89086816470679 |
|
|
- type: dot_ap |
|
|
value: 78.81106438949705 |
|
|
- type: dot_f1 |
|
|
value: 71.13646466143133 |
|
|
- type: dot_precision |
|
|
value: 68.54654483152484 |
|
|
- type: dot_recall |
|
|
value: 73.92978133661842 |
|
|
- type: euclidean_accuracy |
|
|
value: 85.89086816470679 |
|
|
- type: euclidean_ap |
|
|
value: 78.81106117828325 |
|
|
- type: euclidean_f1 |
|
|
value: 71.13646466143133 |
|
|
- type: euclidean_precision |
|
|
value: 68.54654483152484 |
|
|
- type: euclidean_recall |
|
|
value: 73.92978133661842 |
|
|
- type: manhattan_accuracy |
|
|
value: 85.89474909768309 |
|
|
- type: manhattan_ap |
|
|
value: 78.67476153897563 |
|
|
- type: manhattan_f1 |
|
|
value: 70.78659868900219 |
|
|
- type: manhattan_precision |
|
|
value: 67.15726920950802 |
|
|
- type: manhattan_recall |
|
|
value: 74.83061287342161 |
|
|
- type: max_accuracy |
|
|
value: 85.89474909768309 |
|
|
- type: max_ap |
|
|
value: 78.81106438949705 |
|
|
- type: max_f1 |
|
|
value: 71.13646466143133 |
|
|
--- |
