|
--- |
|
tags: |
|
- mteb |
|
model-index: |
|
- name: nomic_classification_307_w50k_b10k |
|
results: |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: None |
|
name: MTEB AmazonCounterfactualClassification (en) |
|
config: en |
|
split: test |
|
revision: e8379541af4e31359cca9fbcf4b00f2671dba205 |
|
metrics: |
|
- type: accuracy |
|
value: 71.70149253731343 |
|
- type: ap |
|
value: 33.79646861902238 |
|
- type: f1 |
|
value: 65.39377031734182 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: None |
|
name: MTEB AmazonPolarityClassification |
|
config: default |
|
split: test |
|
revision: e2d317d38cd51312af73b3d32a06d1a08b442046 |
|
metrics: |
|
- type: accuracy |
|
value: 64.577125 |
|
- type: ap |
|
value: 59.69737246109206 |
|
- type: f1 |
|
value: 64.3577747072318 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: None |
|
name: MTEB AmazonReviewsClassification (en) |
|
config: en |
|
split: test |
|
revision: 1399c76144fd37290681b995c656ef9b2e06e26d |
|
metrics: |
|
- type: accuracy |
|
value: 33.748 |
|
- type: f1 |
|
value: 33.3254582178127 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB ArguAna |
|
config: default |
|
split: test |
|
revision: c22ab2a51041ffd869aaddef7af8d8215647e41a |
|
metrics: |
|
- type: map_at_1 |
|
value: 20.199 |
|
- type: map_at_10 |
|
value: 34.28 |
|
- type: map_at_100 |
|
value: 35.480000000000004 |
|
- type: map_at_1000 |
|
value: 35.504999999999995 |
|
- type: map_at_3 |
|
value: 29.682 |
|
- type: map_at_5 |
|
value: 32.385000000000005 |
|
- type: mrr_at_1 |
|
value: 20.91 |
|
- type: mrr_at_10 |
|
value: 34.536 |
|
- type: mrr_at_100 |
|
value: 35.743 |
|
- type: mrr_at_1000 |
|
value: 35.768 |
|
- type: mrr_at_3 |
|
value: 29.931 |
|
- type: mrr_at_5 |
|
value: 32.623000000000005 |
|
- type: ndcg_at_1 |
|
value: 20.199 |
|
- type: ndcg_at_10 |
|
value: 42.278 |
|
- type: ndcg_at_100 |
|
value: 47.924 |
|
- type: ndcg_at_1000 |
|
value: 48.537 |
|
- type: ndcg_at_3 |
|
value: 32.815 |
|
- type: ndcg_at_5 |
|
value: 37.681 |
|
- type: precision_at_1 |
|
value: 20.199 |
|
- type: precision_at_10 |
|
value: 6.792 |
|
- type: precision_at_100 |
|
value: 0.9390000000000001 |
|
- type: precision_at_1000 |
|
value: 0.099 |
|
- type: precision_at_3 |
|
value: 13.963999999999999 |
|
- type: precision_at_5 |
|
value: 10.74 |
|
- type: recall_at_1 |
|
value: 20.199 |
|
- type: recall_at_10 |
|
value: 67.923 |
|
- type: recall_at_100 |
|
value: 93.88300000000001 |
|
- type: recall_at_1000 |
|
value: 98.578 |
|
- type: recall_at_3 |
|
value: 41.892 |
|
- type: recall_at_5 |
|
value: 53.698 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: None |
|
name: MTEB ArxivClusteringP2P |
|
config: default |
|
split: test |
|
revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d |
|
metrics: |
|
- type: v_measure |
|
value: 31.715994496712955 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: None |
|
name: MTEB ArxivClusteringS2S |
|
config: default |
|
split: test |
|
revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53 |
|
metrics: |
|
- type: v_measure |
|
value: 22.014928355542406 |
|
- task: |
|
type: Reranking |
|
dataset: |
|
type: None |
|
name: MTEB AskUbuntuDupQuestions |
|
config: default |
|
split: test |
|
revision: 2000358ca161889fa9c082cb41daa8dcfb161a54 |
|
metrics: |
|
- type: map |
|
value: 52.73401198259723 |
|
- type: mrr |
|
value: 66.18574946137272 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: None |
|
name: MTEB BIOSSES |
|
config: default |
|
split: test |
|
revision: d3fb88f8f02e40887cd149695127462bbcf29b4a |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 78.32819163750328 |
|
- type: cos_sim_spearman |
|
value: 76.32884763830812 |
|
- type: euclidean_pearson |
|
value: 77.6247892757331 |
|
- type: euclidean_spearman |
|
value: 76.32884763830812 |
|
- type: manhattan_pearson |
|
value: 77.4560490620549 |
|
- type: manhattan_spearman |
|
value: 76.11679461376502 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: None |
|
name: MTEB Banking77Classification |
|
config: default |
|
split: test |
|
revision: 0fd18e25b25c072e09e0d92ab615fda904d66300 |
|
metrics: |
|
- type: accuracy |
|
value: 72.16883116883118 |
|
- type: f1 |
|
value: 71.34298475263475 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: None |
|
name: MTEB BiorxivClusteringP2P |
|
config: default |
|
split: test |
|
revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40 |
|
metrics: |
|
- type: v_measure |
|
value: 29.528784676707033 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: None |
|
name: MTEB BiorxivClusteringS2S |
|
config: default |
|
split: test |
|
revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908 |
|
metrics: |
|
- type: v_measure |
|
value: 19.565519101446977 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB CQADupstackAndroidRetrieval |
|
config: default |
|
split: test |
|
revision: f46a197baaae43b4f621051089b82a364682dfeb |
|
metrics: |
|
- type: map_at_1 |
|
value: 21.581 |
|
- type: map_at_10 |
|
value: 28.322999999999997 |
|
- type: map_at_100 |
|
value: 29.392000000000003 |
|
- type: map_at_1000 |
|
value: 29.547 |
|
- type: map_at_3 |
|
value: 26.214 |
|
- type: map_at_5 |
|
value: 27.339000000000002 |
|
- type: mrr_at_1 |
|
value: 27.182000000000002 |
|
- type: mrr_at_10 |
|
value: 34.075 |
|
- type: mrr_at_100 |
|
value: 34.92 |
|
- type: mrr_at_1000 |
|
value: 34.997 |
|
- type: mrr_at_3 |
|
value: 32.26 |
|
- type: mrr_at_5 |
|
value: 33.283 |
|
- type: ndcg_at_1 |
|
value: 27.182000000000002 |
|
- type: ndcg_at_10 |
|
value: 32.903999999999996 |
|
- type: ndcg_at_100 |
|
value: 37.852999999999994 |
|
- type: ndcg_at_1000 |
|
value: 41.177 |
|
- type: ndcg_at_3 |
|
value: 29.976999999999997 |
|
- type: ndcg_at_5 |
|
value: 31.039 |
|
- type: precision_at_1 |
|
value: 27.182000000000002 |
|
- type: precision_at_10 |
|
value: 6.194999999999999 |
|
- type: precision_at_100 |
|
value: 1.09 |
|
- type: precision_at_1000 |
|
value: 0.167 |
|
- type: precision_at_3 |
|
value: 14.354 |
|
- type: precision_at_5 |
|
value: 10.157 |
|
- type: recall_at_1 |
|
value: 21.581 |
|
- type: recall_at_10 |
|
value: 40.487 |
|
- type: recall_at_100 |
|
value: 62.832 |
|
- type: recall_at_1000 |
|
value: 85.768 |
|
- type: recall_at_3 |
|
value: 30.842000000000002 |
|
- type: recall_at_5 |
|
value: 34.497 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB CQADupstackEnglishRetrieval |
|
config: default |
|
split: test |
|
revision: ad9991cb51e31e31e430383c75ffb2885547b5f0 |
|
metrics: |
|
- type: map_at_1 |
|
value: 16.495 |
|
- type: map_at_10 |
|
value: 21.625 |
|
- type: map_at_100 |
|
value: 22.506 |
|
- type: map_at_1000 |
|
value: 22.633 |
|
- type: map_at_3 |
|
value: 19.819 |
|
- type: map_at_5 |
|
value: 20.817 |
|
- type: mrr_at_1 |
|
value: 20.892 |
|
- type: mrr_at_10 |
|
value: 25.768 |
|
- type: mrr_at_100 |
|
value: 26.533 |
|
- type: mrr_at_1000 |
|
value: 26.61 |
|
- type: mrr_at_3 |
|
value: 23.96 |
|
- type: mrr_at_5 |
|
value: 24.893 |
|
- type: ndcg_at_1 |
|
value: 20.892 |
|
- type: ndcg_at_10 |
|
value: 25.144 |
|
- type: ndcg_at_100 |
|
value: 29.425 |
|
- type: ndcg_at_1000 |
|
value: 32.436 |
|
- type: ndcg_at_3 |
|
value: 22.105 |
|
- type: ndcg_at_5 |
|
value: 23.416 |
|
- type: precision_at_1 |
|
value: 20.892 |
|
- type: precision_at_10 |
|
value: 4.6240000000000006 |
|
- type: precision_at_100 |
|
value: 0.8500000000000001 |
|
- type: precision_at_1000 |
|
value: 0.136 |
|
- type: precision_at_3 |
|
value: 10.403 |
|
- type: precision_at_5 |
|
value: 7.4270000000000005 |
|
- type: recall_at_1 |
|
value: 16.495 |
|
- type: recall_at_10 |
|
value: 31.627 |
|
- type: recall_at_100 |
|
value: 50.653999999999996 |
|
- type: recall_at_1000 |
|
value: 71.38 |
|
- type: recall_at_3 |
|
value: 22.987 |
|
- type: recall_at_5 |
|
value: 26.518000000000004 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB CQADupstackGamingRetrieval |
|
config: default |
|
split: test |
|
revision: 4885aa143210c98657558c04aaf3dc47cfb54340 |
|
metrics: |
|
- type: map_at_1 |
|
value: 25.19 |
|
- type: map_at_10 |
|
value: 33.159 |
|
- type: map_at_100 |
|
value: 34.223 |
|
- type: map_at_1000 |
|
value: 34.322 |
|
- type: map_at_3 |
|
value: 30.866 |
|
- type: map_at_5 |
|
value: 32.016 |
|
- type: mrr_at_1 |
|
value: 29.091 |
|
- type: mrr_at_10 |
|
value: 36.208 |
|
- type: mrr_at_100 |
|
value: 37.059999999999995 |
|
- type: mrr_at_1000 |
|
value: 37.124 |
|
- type: mrr_at_3 |
|
value: 34.001999999999995 |
|
- type: mrr_at_5 |
|
value: 35.089999999999996 |
|
- type: ndcg_at_1 |
|
value: 29.091 |
|
- type: ndcg_at_10 |
|
value: 37.696000000000005 |
|
- type: ndcg_at_100 |
|
value: 42.774 |
|
- type: ndcg_at_1000 |
|
value: 45.064 |
|
- type: ndcg_at_3 |
|
value: 33.298 |
|
- type: ndcg_at_5 |
|
value: 35.089 |
|
- type: precision_at_1 |
|
value: 29.091 |
|
- type: precision_at_10 |
|
value: 6.132 |
|
- type: precision_at_100 |
|
value: 0.9530000000000001 |
|
- type: precision_at_1000 |
|
value: 0.123 |
|
- type: precision_at_3 |
|
value: 14.754000000000001 |
|
- type: precision_at_5 |
|
value: 10.082 |
|
- type: recall_at_1 |
|
value: 25.19 |
|
- type: recall_at_10 |
|
value: 48.542 |
|
- type: recall_at_100 |
|
value: 71.475 |
|
- type: recall_at_1000 |
|
value: 88.157 |
|
- type: recall_at_3 |
|
value: 36.512 |
|
- type: recall_at_5 |
|
value: 40.998000000000005 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB CQADupstackGisRetrieval |
|
config: default |
|
split: test |
|
revision: 5003b3064772da1887988e05400cf3806fe491f2 |
|
metrics: |
|
- type: map_at_1 |
|
value: 10.979 |
|
- type: map_at_10 |
|
value: 15.160000000000002 |
|
- type: map_at_100 |
|
value: 15.927 |
|
- type: map_at_1000 |
|
value: 16.039 |
|
- type: map_at_3 |
|
value: 13.905000000000001 |
|
- type: map_at_5 |
|
value: 14.603 |
|
- type: mrr_at_1 |
|
value: 12.09 |
|
- type: mrr_at_10 |
|
value: 16.317999999999998 |
|
- type: mrr_at_100 |
|
value: 17.094 |
|
- type: mrr_at_1000 |
|
value: 17.198 |
|
- type: mrr_at_3 |
|
value: 15.028 |
|
- type: mrr_at_5 |
|
value: 15.712000000000002 |
|
- type: ndcg_at_1 |
|
value: 12.09 |
|
- type: ndcg_at_10 |
|
value: 17.71 |
|
- type: ndcg_at_100 |
|
value: 21.923000000000002 |
|
- type: ndcg_at_1000 |
|
value: 25.407999999999998 |
|
- type: ndcg_at_3 |
|
value: 15.139 |
|
- type: ndcg_at_5 |
|
value: 16.372 |
|
- type: precision_at_1 |
|
value: 12.09 |
|
- type: precision_at_10 |
|
value: 2.768 |
|
- type: precision_at_100 |
|
value: 0.521 |
|
- type: precision_at_1000 |
|
value: 0.087 |
|
- type: precision_at_3 |
|
value: 6.478000000000001 |
|
- type: precision_at_5 |
|
value: 4.542 |
|
- type: recall_at_1 |
|
value: 10.979 |
|
- type: recall_at_10 |
|
value: 24.548000000000002 |
|
- type: recall_at_100 |
|
value: 44.659 |
|
- type: recall_at_1000 |
|
value: 72.15899999999999 |
|
- type: recall_at_3 |
|
value: 17.552 |
|
- type: recall_at_5 |
|
value: 20.584 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB CQADupstackMathematicaRetrieval |
|
config: default |
|
split: test |
|
revision: 90fceea13679c63fe563ded68f3b6f06e50061de |
|
metrics: |
|
- type: map_at_1 |
|
value: 6.703 |
|
- type: map_at_10 |
|
value: 9.588000000000001 |
|
- type: map_at_100 |
|
value: 10.312000000000001 |
|
- type: map_at_1000 |
|
value: 10.428999999999998 |
|
- type: map_at_3 |
|
value: 8.473 |
|
- type: map_at_5 |
|
value: 9.118 |
|
- type: mrr_at_1 |
|
value: 8.706 |
|
- type: mrr_at_10 |
|
value: 11.818 |
|
- type: mrr_at_100 |
|
value: 12.568999999999999 |
|
- type: mrr_at_1000 |
|
value: 12.664 |
|
- type: mrr_at_3 |
|
value: 10.551 |
|
- type: mrr_at_5 |
|
value: 11.235000000000001 |
|
- type: ndcg_at_1 |
|
value: 8.706 |
|
- type: ndcg_at_10 |
|
value: 11.823 |
|
- type: ndcg_at_100 |
|
value: 15.674 |
|
- type: ndcg_at_1000 |
|
value: 19.256 |
|
- type: ndcg_at_3 |
|
value: 9.637 |
|
- type: ndcg_at_5 |
|
value: 10.661 |
|
- type: precision_at_1 |
|
value: 8.706 |
|
- type: precision_at_10 |
|
value: 2.251 |
|
- type: precision_at_100 |
|
value: 0.484 |
|
- type: precision_at_1000 |
|
value: 0.093 |
|
- type: precision_at_3 |
|
value: 4.601999999999999 |
|
- type: precision_at_5 |
|
value: 3.458 |
|
- type: recall_at_1 |
|
value: 6.703 |
|
- type: recall_at_10 |
|
value: 16.579 |
|
- type: recall_at_100 |
|
value: 34.054 |
|
- type: recall_at_1000 |
|
value: 60.769 |
|
- type: recall_at_3 |
|
value: 10.530000000000001 |
|
- type: recall_at_5 |
|
value: 13.126 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB CQADupstackPhysicsRetrieval |
|
config: default |
|
split: test |
|
revision: 79531abbd1fb92d06c6d6315a0cbbbf5bb247ea4 |
|
metrics: |
|
- type: map_at_1 |
|
value: 17.688000000000002 |
|
- type: map_at_10 |
|
value: 23.169 |
|
- type: map_at_100 |
|
value: 24.275 |
|
- type: map_at_1000 |
|
value: 24.409 |
|
- type: map_at_3 |
|
value: 21.284 |
|
- type: map_at_5 |
|
value: 22.171 |
|
- type: mrr_at_1 |
|
value: 22.233 |
|
- type: mrr_at_10 |
|
value: 27.857 |
|
- type: mrr_at_100 |
|
value: 28.76 |
|
- type: mrr_at_1000 |
|
value: 28.841 |
|
- type: mrr_at_3 |
|
value: 25.857999999999997 |
|
- type: mrr_at_5 |
|
value: 26.922 |
|
- type: ndcg_at_1 |
|
value: 22.233 |
|
- type: ndcg_at_10 |
|
value: 27.203 |
|
- type: ndcg_at_100 |
|
value: 32.543 |
|
- type: ndcg_at_1000 |
|
value: 35.654 |
|
- type: ndcg_at_3 |
|
value: 23.863 |
|
- type: ndcg_at_5 |
|
value: 25.117 |
|
- type: precision_at_1 |
|
value: 22.233 |
|
- type: precision_at_10 |
|
value: 4.957000000000001 |
|
- type: precision_at_100 |
|
value: 0.919 |
|
- type: precision_at_1000 |
|
value: 0.13899999999999998 |
|
- type: precision_at_3 |
|
value: 11.036 |
|
- type: precision_at_5 |
|
value: 7.8149999999999995 |
|
- type: recall_at_1 |
|
value: 17.688000000000002 |
|
- type: recall_at_10 |
|
value: 34.969 |
|
- type: recall_at_100 |
|
value: 58.370999999999995 |
|
- type: recall_at_1000 |
|
value: 80.02 |
|
- type: recall_at_3 |
|
value: 25.332 |
|
- type: recall_at_5 |
|
value: 28.703 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB CQADupstackProgrammersRetrieval |
|
config: default |
|
split: test |
|
revision: 6184bc1440d2dbc7612be22b50686b8826d22b32 |
|
metrics: |
|
- type: map_at_1 |
|
value: 11.15 |
|
- type: map_at_10 |
|
value: 16.797 |
|
- type: map_at_100 |
|
value: 17.822 |
|
- type: map_at_1000 |
|
value: 17.956 |
|
- type: map_at_3 |
|
value: 14.985999999999999 |
|
- type: map_at_5 |
|
value: 16.044 |
|
- type: mrr_at_1 |
|
value: 14.155000000000001 |
|
- type: mrr_at_10 |
|
value: 20.01 |
|
- type: mrr_at_100 |
|
value: 20.966 |
|
- type: mrr_at_1000 |
|
value: 21.049 |
|
- type: mrr_at_3 |
|
value: 18.227 |
|
- type: mrr_at_5 |
|
value: 19.231 |
|
- type: ndcg_at_1 |
|
value: 14.155000000000001 |
|
- type: ndcg_at_10 |
|
value: 20.327 |
|
- type: ndcg_at_100 |
|
value: 25.490000000000002 |
|
- type: ndcg_at_1000 |
|
value: 28.854000000000003 |
|
- type: ndcg_at_3 |
|
value: 17.046 |
|
- type: ndcg_at_5 |
|
value: 18.647 |
|
- type: precision_at_1 |
|
value: 14.155000000000001 |
|
- type: precision_at_10 |
|
value: 3.893 |
|
- type: precision_at_100 |
|
value: 0.771 |
|
- type: precision_at_1000 |
|
value: 0.124 |
|
- type: precision_at_3 |
|
value: 8.219 |
|
- type: precision_at_5 |
|
value: 6.164 |
|
- type: recall_at_1 |
|
value: 11.15 |
|
- type: recall_at_10 |
|
value: 27.750999999999998 |
|
- type: recall_at_100 |
|
value: 50.612 |
|
- type: recall_at_1000 |
|
value: 74.617 |
|
- type: recall_at_3 |
|
value: 19.101000000000003 |
|
- type: recall_at_5 |
|
value: 22.999 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: mteb/cqadupstack |
|
name: MTEB CQADupstackRetrieval |
|
config: default |
|
split: test |
|
revision: 4885aa143210c98657558c04aaf3dc47cfb54340 |
|
metrics: |
|
- type: map_at_1 |
|
value: 13.562333333333335 |
|
- type: map_at_10 |
|
value: 18.514583333333334 |
|
- type: map_at_100 |
|
value: 19.362916666666667 |
|
- type: map_at_1000 |
|
value: 19.48625 |
|
- type: map_at_3 |
|
value: 16.955583333333337 |
|
- type: map_at_5 |
|
value: 17.788 |
|
- type: mrr_at_1 |
|
value: 16.54575 |
|
- type: mrr_at_10 |
|
value: 21.549249999999997 |
|
- type: mrr_at_100 |
|
value: 22.318500000000004 |
|
- type: mrr_at_1000 |
|
value: 22.405583333333333 |
|
- type: mrr_at_3 |
|
value: 19.9585 |
|
- type: mrr_at_5 |
|
value: 20.82183333333333 |
|
- type: ndcg_at_1 |
|
value: 16.54575 |
|
- type: ndcg_at_10 |
|
value: 21.80341666666667 |
|
- type: ndcg_at_100 |
|
value: 26.133833333333328 |
|
- type: ndcg_at_1000 |
|
value: 29.348666666666666 |
|
- type: ndcg_at_3 |
|
value: 18.973499999999998 |
|
- type: ndcg_at_5 |
|
value: 20.200833333333332 |
|
- type: precision_at_1 |
|
value: 16.54575 |
|
- type: precision_at_10 |
|
value: 3.895333333333334 |
|
- type: precision_at_100 |
|
value: 0.7226666666666668 |
|
- type: precision_at_1000 |
|
value: 0.11775 |
|
- type: precision_at_3 |
|
value: 8.796666666666667 |
|
- type: precision_at_5 |
|
value: 6.278083333333333 |
|
- type: recall_at_1 |
|
value: 13.562333333333335 |
|
- type: recall_at_10 |
|
value: 28.738833333333336 |
|
- type: recall_at_100 |
|
value: 48.66516666666668 |
|
- type: recall_at_1000 |
|
value: 72.21291666666666 |
|
- type: recall_at_3 |
|
value: 20.722166666666663 |
|
- type: recall_at_5 |
|
value: 23.920416666666668 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB CQADupstackStatsRetrieval |
|
config: default |
|
split: test |
|
revision: 65ac3a16b8e91f9cee4c9828cc7c335575432a2a |
|
metrics: |
|
- type: map_at_1 |
|
value: 10.612 |
|
- type: map_at_10 |
|
value: 14.233 |
|
- type: map_at_100 |
|
value: 14.804999999999998 |
|
- type: map_at_1000 |
|
value: 14.887 |
|
- type: map_at_3 |
|
value: 13.050999999999998 |
|
- type: map_at_5 |
|
value: 13.642999999999999 |
|
- type: mrr_at_1 |
|
value: 12.577 |
|
- type: mrr_at_10 |
|
value: 16.256999999999998 |
|
- type: mrr_at_100 |
|
value: 16.830000000000002 |
|
- type: mrr_at_1000 |
|
value: 16.909 |
|
- type: mrr_at_3 |
|
value: 15.031 |
|
- type: mrr_at_5 |
|
value: 15.613 |
|
- type: ndcg_at_1 |
|
value: 12.577 |
|
- type: ndcg_at_10 |
|
value: 16.81 |
|
- type: ndcg_at_100 |
|
value: 20.085 |
|
- type: ndcg_at_1000 |
|
value: 22.684 |
|
- type: ndcg_at_3 |
|
value: 14.471 |
|
- type: ndcg_at_5 |
|
value: 15.384 |
|
- type: precision_at_1 |
|
value: 12.577 |
|
- type: precision_at_10 |
|
value: 2.8529999999999998 |
|
- type: precision_at_100 |
|
value: 0.49699999999999994 |
|
- type: precision_at_1000 |
|
value: 0.079 |
|
- type: precision_at_3 |
|
value: 6.544 |
|
- type: precision_at_5 |
|
value: 4.601 |
|
- type: recall_at_1 |
|
value: 10.612 |
|
- type: recall_at_10 |
|
value: 22.983999999999998 |
|
- type: recall_at_100 |
|
value: 38.745000000000005 |
|
- type: recall_at_1000 |
|
value: 58.886 |
|
- type: recall_at_3 |
|
value: 15.982 |
|
- type: recall_at_5 |
|
value: 18.433 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB CQADupstackTexRetrieval |
|
config: default |
|
split: test |
|
revision: 46989137a86843e03a6195de44b09deda022eec7 |
|
metrics: |
|
- type: map_at_1 |
|
value: 7.04 |
|
- type: map_at_10 |
|
value: 10.277 |
|
- type: map_at_100 |
|
value: 10.873 |
|
- type: map_at_1000 |
|
value: 10.989 |
|
- type: map_at_3 |
|
value: 9.243 |
|
- type: map_at_5 |
|
value: 9.843 |
|
- type: mrr_at_1 |
|
value: 8.774999999999999 |
|
- type: mrr_at_10 |
|
value: 12.468 |
|
- type: mrr_at_100 |
|
value: 13.084999999999999 |
|
- type: mrr_at_1000 |
|
value: 13.184000000000001 |
|
- type: mrr_at_3 |
|
value: 11.293000000000001 |
|
- type: mrr_at_5 |
|
value: 12.034 |
|
- type: ndcg_at_1 |
|
value: 8.774999999999999 |
|
- type: ndcg_at_10 |
|
value: 12.527 |
|
- type: ndcg_at_100 |
|
value: 15.939 |
|
- type: ndcg_at_1000 |
|
value: 19.383 |
|
- type: ndcg_at_3 |
|
value: 10.565 |
|
- type: ndcg_at_5 |
|
value: 11.555 |
|
- type: precision_at_1 |
|
value: 8.774999999999999 |
|
- type: precision_at_10 |
|
value: 2.3640000000000003 |
|
- type: precision_at_100 |
|
value: 0.49 |
|
- type: precision_at_1000 |
|
value: 0.094 |
|
- type: precision_at_3 |
|
value: 5.047 |
|
- type: precision_at_5 |
|
value: 3.8129999999999997 |
|
- type: recall_at_1 |
|
value: 7.04 |
|
- type: recall_at_10 |
|
value: 17.193 |
|
- type: recall_at_100 |
|
value: 33.33 |
|
- type: recall_at_1000 |
|
value: 59.134 |
|
- type: recall_at_3 |
|
value: 11.859 |
|
- type: recall_at_5 |
|
value: 14.243 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB CQADupstackUnixRetrieval |
|
config: default |
|
split: test |
|
revision: 6c6430d3a6d36f8d2a829195bc5dc94d7e063e53 |
|
metrics: |
|
- type: map_at_1 |
|
value: 11.381 |
|
- type: map_at_10 |
|
value: 15.676000000000002 |
|
- type: map_at_100 |
|
value: 16.448999999999998 |
|
- type: map_at_1000 |
|
value: 16.563 |
|
- type: map_at_3 |
|
value: 14.313 |
|
- type: map_at_5 |
|
value: 15.010000000000002 |
|
- type: mrr_at_1 |
|
value: 14.086000000000002 |
|
- type: mrr_at_10 |
|
value: 18.621 |
|
- type: mrr_at_100 |
|
value: 19.41 |
|
- type: mrr_at_1000 |
|
value: 19.506999999999998 |
|
- type: mrr_at_3 |
|
value: 17.149 |
|
- type: mrr_at_5 |
|
value: 17.918 |
|
- type: ndcg_at_1 |
|
value: 14.086000000000002 |
|
- type: ndcg_at_10 |
|
value: 18.647 |
|
- type: ndcg_at_100 |
|
value: 22.823 |
|
- type: ndcg_at_1000 |
|
value: 26.207 |
|
- type: ndcg_at_3 |
|
value: 15.986 |
|
- type: ndcg_at_5 |
|
value: 17.108 |
|
- type: precision_at_1 |
|
value: 14.086000000000002 |
|
- type: precision_at_10 |
|
value: 3.218 |
|
- type: precision_at_100 |
|
value: 0.585 |
|
- type: precision_at_1000 |
|
value: 0.099 |
|
- type: precision_at_3 |
|
value: 7.369000000000001 |
|
- type: precision_at_5 |
|
value: 5.187 |
|
- type: recall_at_1 |
|
value: 11.381 |
|
- type: recall_at_10 |
|
value: 25.008999999999997 |
|
- type: recall_at_100 |
|
value: 44.368 |
|
- type: recall_at_1000 |
|
value: 69.587 |
|
- type: recall_at_3 |
|
value: 17.612 |
|
- type: recall_at_5 |
|
value: 20.506 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB CQADupstackWebmastersRetrieval |
|
config: default |
|
split: test |
|
revision: 160c094312a0e1facb97e55eeddb698c0abe3571 |
|
metrics: |
|
- type: map_at_1 |
|
value: 12.641 |
|
- type: map_at_10 |
|
value: 19.067 |
|
- type: map_at_100 |
|
value: 20.046 |
|
- type: map_at_1000 |
|
value: 20.221 |
|
- type: map_at_3 |
|
value: 17.699 |
|
- type: map_at_5 |
|
value: 18.458 |
|
- type: mrr_at_1 |
|
value: 16.008 |
|
- type: mrr_at_10 |
|
value: 22.526 |
|
- type: mrr_at_100 |
|
value: 23.307 |
|
- type: mrr_at_1000 |
|
value: 23.391000000000002 |
|
- type: mrr_at_3 |
|
value: 21.047 |
|
- type: mrr_at_5 |
|
value: 21.956999999999997 |
|
- type: ndcg_at_1 |
|
value: 16.008 |
|
- type: ndcg_at_10 |
|
value: 23.029 |
|
- type: ndcg_at_100 |
|
value: 27.533 |
|
- type: ndcg_at_1000 |
|
value: 31.096 |
|
- type: ndcg_at_3 |
|
value: 20.806 |
|
- type: ndcg_at_5 |
|
value: 21.859 |
|
- type: precision_at_1 |
|
value: 16.008 |
|
- type: precision_at_10 |
|
value: 4.605 |
|
- type: precision_at_100 |
|
value: 0.9939999999999999 |
|
- type: precision_at_1000 |
|
value: 0.182 |
|
- type: precision_at_3 |
|
value: 10.408000000000001 |
|
- type: precision_at_5 |
|
value: 7.470000000000001 |
|
- type: recall_at_1 |
|
value: 12.641 |
|
- type: recall_at_10 |
|
value: 30.236 |
|
- type: recall_at_100 |
|
value: 51.543000000000006 |
|
- type: recall_at_1000 |
|
value: 76.265 |
|
- type: recall_at_3 |
|
value: 23.677999999999997 |
|
- type: recall_at_5 |
|
value: 26.456000000000003 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB CQADupstackWordpressRetrieval |
|
config: default |
|
split: test |
|
revision: 4ffe81d471b1924886b33c7567bfb200e9eec5c4 |
|
metrics: |
|
- type: map_at_1 |
|
value: 11.288 |
|
- type: map_at_10 |
|
value: 15.101 |
|
- type: map_at_100 |
|
value: 15.725 |
|
- type: map_at_1000 |
|
value: 15.840000000000002 |
|
- type: map_at_3 |
|
value: 13.614 |
|
- type: map_at_5 |
|
value: 14.394000000000002 |
|
- type: mrr_at_1 |
|
value: 12.753999999999998 |
|
- type: mrr_at_10 |
|
value: 16.665 |
|
- type: mrr_at_100 |
|
value: 17.288 |
|
- type: mrr_at_1000 |
|
value: 17.393 |
|
- type: mrr_at_3 |
|
value: 15.096000000000002 |
|
- type: mrr_at_5 |
|
value: 15.974 |
|
- type: ndcg_at_1 |
|
value: 12.753999999999998 |
|
- type: ndcg_at_10 |
|
value: 17.821 |
|
- type: ndcg_at_100 |
|
value: 21.544 |
|
- type: ndcg_at_1000 |
|
value: 24.965 |
|
- type: ndcg_at_3 |
|
value: 14.789 |
|
- type: ndcg_at_5 |
|
value: 16.163 |
|
- type: precision_at_1 |
|
value: 12.753999999999998 |
|
- type: precision_at_10 |
|
value: 2.884 |
|
- type: precision_at_100 |
|
value: 0.518 |
|
- type: precision_at_1000 |
|
value: 0.09 |
|
- type: precision_at_3 |
|
value: 6.346 |
|
- type: precision_at_5 |
|
value: 4.621 |
|
- type: recall_at_1 |
|
value: 11.288 |
|
- type: recall_at_10 |
|
value: 24.941 |
|
- type: recall_at_100 |
|
value: 43.339 |
|
- type: recall_at_1000 |
|
value: 69.813 |
|
- type: recall_at_3 |
|
value: 16.679 |
|
- type: recall_at_5 |
|
value: 19.982 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB ClimateFEVER |
|
config: default |
|
split: test |
|
revision: 47f2ac6acb640fc46020b02a5b59fdda04d39380 |
|
metrics: |
|
- type: map_at_1 |
|
value: 5.319 |
|
- type: map_at_10 |
|
value: 9.538 |
|
- type: map_at_100 |
|
value: 10.786 |
|
- type: map_at_1000 |
|
value: 10.979 |
|
- type: map_at_3 |
|
value: 7.693999999999999 |
|
- type: map_at_5 |
|
value: 8.623 |
|
- type: mrr_at_1 |
|
value: 11.922 |
|
- type: mrr_at_10 |
|
value: 19.683 |
|
- type: mrr_at_100 |
|
value: 20.881 |
|
- type: mrr_at_1000 |
|
value: 20.961 |
|
- type: mrr_at_3 |
|
value: 17.014000000000003 |
|
- type: mrr_at_5 |
|
value: 18.47 |
|
- type: ndcg_at_1 |
|
value: 11.922 |
|
- type: ndcg_at_10 |
|
value: 14.517 |
|
- type: ndcg_at_100 |
|
value: 20.541999999999998 |
|
- type: ndcg_at_1000 |
|
value: 24.648999999999997 |
|
- type: ndcg_at_3 |
|
value: 10.975 |
|
- type: ndcg_at_5 |
|
value: 12.276 |
|
- type: precision_at_1 |
|
value: 11.922 |
|
- type: precision_at_10 |
|
value: 4.893 |
|
- type: precision_at_100 |
|
value: 1.129 |
|
- type: precision_at_1000 |
|
value: 0.187 |
|
- type: precision_at_3 |
|
value: 8.382000000000001 |
|
- type: precision_at_5 |
|
value: 6.801 |
|
- type: recall_at_1 |
|
value: 5.319 |
|
- type: recall_at_10 |
|
value: 18.593 |
|
- type: recall_at_100 |
|
value: 39.957 |
|
- type: recall_at_1000 |
|
value: 63.748000000000005 |
|
- type: recall_at_3 |
|
value: 10.314 |
|
- type: recall_at_5 |
|
value: 13.564000000000002 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB DBPedia |
|
config: default |
|
split: test |
|
revision: c0f706b76e590d620bd6618b3ca8efdd34e2d659 |
|
metrics: |
|
- type: map_at_1 |
|
value: 3.819 |
|
- type: map_at_10 |
|
value: 7.771999999999999 |
|
- type: map_at_100 |
|
value: 10.424999999999999 |
|
- type: map_at_1000 |
|
value: 11.165 |
|
- type: map_at_3 |
|
value: 5.586 |
|
- type: map_at_5 |
|
value: 6.524000000000001 |
|
- type: mrr_at_1 |
|
value: 34.75 |
|
- type: mrr_at_10 |
|
value: 43.289 |
|
- type: mrr_at_100 |
|
value: 44.184 |
|
- type: mrr_at_1000 |
|
value: 44.239 |
|
- type: mrr_at_3 |
|
value: 40.75 |
|
- type: mrr_at_5 |
|
value: 42.175000000000004 |
|
- type: ndcg_at_1 |
|
value: 25.5 |
|
- type: ndcg_at_10 |
|
value: 19.994 |
|
- type: ndcg_at_100 |
|
value: 21.802 |
|
- type: ndcg_at_1000 |
|
value: 28.086 |
|
- type: ndcg_at_3 |
|
value: 22.279 |
|
- type: ndcg_at_5 |
|
value: 20.986 |
|
- type: precision_at_1 |
|
value: 34.75 |
|
- type: precision_at_10 |
|
value: 17.65 |
|
- type: precision_at_100 |
|
value: 5.317 |
|
- type: precision_at_1000 |
|
value: 1.146 |
|
- type: precision_at_3 |
|
value: 25.75 |
|
- type: precision_at_5 |
|
value: 22.400000000000002 |
|
- type: recall_at_1 |
|
value: 3.819 |
|
- type: recall_at_10 |
|
value: 11.533 |
|
- type: recall_at_100 |
|
value: 26.484999999999996 |
|
- type: recall_at_1000 |
|
value: 47.63 |
|
- type: recall_at_3 |
|
value: 6.268999999999999 |
|
- type: recall_at_5 |
|
value: 8.218 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: None |
|
name: MTEB EmotionClassification |
|
config: default |
|
split: test |
|
revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37 |
|
metrics: |
|
- type: accuracy |
|
value: 43.69500000000001 |
|
- type: f1 |
|
value: 39.81935458907266 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB FEVER |
|
config: default |
|
split: test |
|
revision: bea83ef9e8fb933d90a2f1d5515737465d613e12 |
|
metrics: |
|
- type: map_at_1 |
|
value: 10.544 |
|
- type: map_at_10 |
|
value: 16.105 |
|
- type: map_at_100 |
|
value: 16.91 |
|
- type: map_at_1000 |
|
value: 16.993 |
|
- type: map_at_3 |
|
value: 14.273 |
|
- type: map_at_5 |
|
value: 15.259 |
|
- type: mrr_at_1 |
|
value: 11.206000000000001 |
|
- type: mrr_at_10 |
|
value: 17.129 |
|
- type: mrr_at_100 |
|
value: 17.955 |
|
- type: mrr_at_1000 |
|
value: 18.032999999999998 |
|
- type: mrr_at_3 |
|
value: 15.214 |
|
- type: mrr_at_5 |
|
value: 16.249 |
|
- type: ndcg_at_1 |
|
value: 11.206000000000001 |
|
- type: ndcg_at_10 |
|
value: 19.546 |
|
- type: ndcg_at_100 |
|
value: 23.934 |
|
- type: ndcg_at_1000 |
|
value: 26.356 |
|
- type: ndcg_at_3 |
|
value: 15.706999999999999 |
|
- type: ndcg_at_5 |
|
value: 17.488999999999997 |
|
- type: precision_at_1 |
|
value: 11.206000000000001 |
|
- type: precision_at_10 |
|
value: 3.195 |
|
- type: precision_at_100 |
|
value: 0.557 |
|
- type: precision_at_1000 |
|
value: 0.078 |
|
- type: precision_at_3 |
|
value: 6.7860000000000005 |
|
- type: precision_at_5 |
|
value: 4.997999999999999 |
|
- type: recall_at_1 |
|
value: 10.544 |
|
- type: recall_at_10 |
|
value: 29.421999999999997 |
|
- type: recall_at_100 |
|
value: 50.54 |
|
- type: recall_at_1000 |
|
value: 69.53200000000001 |
|
- type: recall_at_3 |
|
value: 18.901 |
|
- type: recall_at_5 |
|
value: 23.183999999999997 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB FiQA2018 |
|
config: default |
|
split: test |
|
revision: 27a168819829fe9bcd655c2df245fb19452e8e06 |
|
metrics: |
|
- type: map_at_1 |
|
value: 5.688 |
|
- type: map_at_10 |
|
value: 9.454 |
|
- type: map_at_100 |
|
value: 10.459 |
|
- type: map_at_1000 |
|
value: 10.645 |
|
- type: map_at_3 |
|
value: 7.914000000000001 |
|
- type: map_at_5 |
|
value: 8.622 |
|
- type: mrr_at_1 |
|
value: 11.42 |
|
- type: mrr_at_10 |
|
value: 16.608 |
|
- type: mrr_at_100 |
|
value: 17.566000000000003 |
|
- type: mrr_at_1000 |
|
value: 17.675 |
|
- type: mrr_at_3 |
|
value: 14.712 |
|
- type: mrr_at_5 |
|
value: 15.638 |
|
- type: ndcg_at_1 |
|
value: 11.42 |
|
- type: ndcg_at_10 |
|
value: 13.293 |
|
- type: ndcg_at_100 |
|
value: 18.289 |
|
- type: ndcg_at_1000 |
|
value: 22.781000000000002 |
|
- type: ndcg_at_3 |
|
value: 10.835 |
|
- type: ndcg_at_5 |
|
value: 11.576 |
|
- type: precision_at_1 |
|
value: 11.42 |
|
- type: precision_at_10 |
|
value: 3.997 |
|
- type: precision_at_100 |
|
value: 0.897 |
|
- type: precision_at_1000 |
|
value: 0.167 |
|
- type: precision_at_3 |
|
value: 7.356 |
|
- type: precision_at_5 |
|
value: 5.772 |
|
- type: recall_at_1 |
|
value: 5.688 |
|
- type: recall_at_10 |
|
value: 17.544 |
|
- type: recall_at_100 |
|
value: 37.358999999999995 |
|
- type: recall_at_1000 |
|
value: 65.735 |
|
- type: recall_at_3 |
|
value: 9.987 |
|
- type: recall_at_5 |
|
value: 12.337 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB HotpotQA |
|
config: default |
|
split: test |
|
revision: ab518f4d6fcca38d87c25209f94beba119d02014 |
|
metrics: |
|
- type: map_at_1 |
|
value: 13.248 |
|
- type: map_at_10 |
|
value: 18.584 |
|
- type: map_at_100 |
|
value: 19.348000000000003 |
|
- type: map_at_1000 |
|
value: 19.457 |
|
- type: map_at_3 |
|
value: 16.962 |
|
- type: map_at_5 |
|
value: 17.862000000000002 |
|
- type: mrr_at_1 |
|
value: 26.496 |
|
- type: mrr_at_10 |
|
value: 32.580999999999996 |
|
- type: mrr_at_100 |
|
value: 33.314 |
|
- type: mrr_at_1000 |
|
value: 33.387 |
|
- type: mrr_at_3 |
|
value: 30.808000000000003 |
|
- type: mrr_at_5 |
|
value: 31.805 |
|
- type: ndcg_at_1 |
|
value: 26.496 |
|
- type: ndcg_at_10 |
|
value: 24.198 |
|
- type: ndcg_at_100 |
|
value: 28.017999999999997 |
|
- type: ndcg_at_1000 |
|
value: 30.839 |
|
- type: ndcg_at_3 |
|
value: 21.002000000000002 |
|
- type: ndcg_at_5 |
|
value: 22.547 |
|
- type: precision_at_1 |
|
value: 26.496 |
|
- type: precision_at_10 |
|
value: 5.415 |
|
- type: precision_at_100 |
|
value: 0.8500000000000001 |
|
- type: precision_at_1000 |
|
value: 0.123 |
|
- type: precision_at_3 |
|
value: 13.234000000000002 |
|
- type: precision_at_5 |
|
value: 9.164 |
|
- type: recall_at_1 |
|
value: 13.248 |
|
- type: recall_at_10 |
|
value: 27.076 |
|
- type: recall_at_100 |
|
value: 42.512 |
|
- type: recall_at_1000 |
|
value: 61.41799999999999 |
|
- type: recall_at_3 |
|
value: 19.851 |
|
- type: recall_at_5 |
|
value: 22.91 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: None |
|
name: MTEB ImdbClassification |
|
config: default |
|
split: test |
|
revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7 |
|
metrics: |
|
- type: accuracy |
|
value: 63.98560000000001 |
|
- type: ap |
|
value: 59.217561950701445 |
|
- type: f1 |
|
value: 63.818409911217046 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB MSMARCO |
|
config: default |
|
split: dev |
|
revision: c5a29a104738b98a9e76336939199e264163d4a0 |
|
metrics: |
|
- type: map_at_1 |
|
value: 5.179 |
|
- type: map_at_10 |
|
value: 9.055 |
|
- type: map_at_100 |
|
value: 9.814 |
|
- type: map_at_1000 |
|
value: 9.911 |
|
- type: map_at_3 |
|
value: 7.631 |
|
- type: map_at_5 |
|
value: 8.415000000000001 |
|
- type: mrr_at_1 |
|
value: 5.3580000000000005 |
|
- type: mrr_at_10 |
|
value: 9.302000000000001 |
|
- type: mrr_at_100 |
|
value: 10.075000000000001 |
|
- type: mrr_at_1000 |
|
value: 10.169 |
|
- type: mrr_at_3 |
|
value: 7.856000000000001 |
|
- type: mrr_at_5 |
|
value: 8.654 |
|
- type: ndcg_at_1 |
|
value: 5.33 |
|
- type: ndcg_at_10 |
|
value: 11.491 |
|
- type: ndcg_at_100 |
|
value: 15.735 |
|
- type: ndcg_at_1000 |
|
value: 18.721 |
|
- type: ndcg_at_3 |
|
value: 8.522 |
|
- type: ndcg_at_5 |
|
value: 9.943 |
|
- type: precision_at_1 |
|
value: 5.33 |
|
- type: precision_at_10 |
|
value: 1.983 |
|
- type: precision_at_100 |
|
value: 0.42 |
|
- type: precision_at_1000 |
|
value: 0.068 |
|
- type: precision_at_3 |
|
value: 3.763 |
|
- type: precision_at_5 |
|
value: 2.9770000000000003 |
|
- type: recall_at_1 |
|
value: 5.179 |
|
- type: recall_at_10 |
|
value: 19.069 |
|
- type: recall_at_100 |
|
value: 39.946 |
|
- type: recall_at_1000 |
|
value: 64.031 |
|
- type: recall_at_3 |
|
value: 10.91 |
|
- type: recall_at_5 |
|
value: 14.334 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: None |
|
name: MTEB MTOPDomainClassification (en) |
|
config: en |
|
split: test |
|
revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf |
|
metrics: |
|
- type: accuracy |
|
value: 89.25444596443229 |
|
- type: f1 |
|
value: 88.34114464691379 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: None |
|
name: MTEB MTOPIntentClassification (en) |
|
config: en |
|
split: test |
|
revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba |
|
metrics: |
|
- type: accuracy |
|
value: 59.3251253989968 |
|
- type: f1 |
|
value: 39.879870396124964 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: None |
|
name: MTEB MassiveIntentClassification (en) |
|
config: en |
|
split: test |
|
revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 |
|
metrics: |
|
- type: accuracy |
|
value: 61.90316072629455 |
|
- type: f1 |
|
value: 59.6419867903448 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: None |
|
name: MTEB MassiveScenarioClassification (en) |
|
config: en |
|
split: test |
|
revision: 7d571f92784cd94a019292a1f45445077d0ef634 |
|
metrics: |
|
- type: accuracy |
|
value: 68.5474108944183 |
|
- type: f1 |
|
value: 67.13260105586494 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: None |
|
name: MTEB MedrxivClusteringP2P |
|
config: default |
|
split: test |
|
revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73 |
|
metrics: |
|
- type: v_measure |
|
value: 27.08360278577924 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: None |
|
name: MTEB MedrxivClusteringS2S |
|
config: default |
|
split: test |
|
revision: 35191c8c0dca72d8ff3efcd72aa802307d469663 |
|
metrics: |
|
- type: v_measure |
|
value: 23.539985814012603 |
|
- task: |
|
type: Reranking |
|
dataset: |
|
type: None |
|
name: MTEB MindSmallReranking |
|
config: default |
|
split: test |
|
revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69 |
|
metrics: |
|
- type: map |
|
value: 28.52217790319968 |
|
- type: mrr |
|
value: 29.375037759331086 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB NFCorpus |
|
config: default |
|
split: test |
|
revision: ec0fa4fe99da2ff19ca1214b7966684033a58814 |
|
metrics: |
|
- type: map_at_1 |
|
value: 3.202 |
|
- type: map_at_10 |
|
value: 6.216 |
|
- type: map_at_100 |
|
value: 7.902000000000001 |
|
- type: map_at_1000 |
|
value: 9.114 |
|
- type: map_at_3 |
|
value: 4.752 |
|
- type: map_at_5 |
|
value: 5.414 |
|
- type: mrr_at_1 |
|
value: 31.269000000000002 |
|
- type: mrr_at_10 |
|
value: 39.649 |
|
- type: mrr_at_100 |
|
value: 40.261 |
|
- type: mrr_at_1000 |
|
value: 40.338 |
|
- type: mrr_at_3 |
|
value: 37.049 |
|
- type: mrr_at_5 |
|
value: 38.643 |
|
- type: ndcg_at_1 |
|
value: 29.412 |
|
- type: ndcg_at_10 |
|
value: 21.224 |
|
- type: ndcg_at_100 |
|
value: 19.897000000000002 |
|
- type: ndcg_at_1000 |
|
value: 29.53 |
|
- type: ndcg_at_3 |
|
value: 24.635 |
|
- type: ndcg_at_5 |
|
value: 23.114 |
|
- type: precision_at_1 |
|
value: 31.269000000000002 |
|
- type: precision_at_10 |
|
value: 15.697 |
|
- type: precision_at_100 |
|
value: 5.842 |
|
- type: precision_at_1000 |
|
value: 1.8880000000000001 |
|
- type: precision_at_3 |
|
value: 23.013 |
|
- type: precision_at_5 |
|
value: 19.628 |
|
- type: recall_at_1 |
|
value: 3.202 |
|
- type: recall_at_10 |
|
value: 9.889000000000001 |
|
- type: recall_at_100 |
|
value: 21.366 |
|
- type: recall_at_1000 |
|
value: 56.267999999999994 |
|
- type: recall_at_3 |
|
value: 5.7459999999999996 |
|
- type: recall_at_5 |
|
value: 7.473000000000001 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB NQ |
|
config: default |
|
split: test |
|
revision: b774495ed302d8c44a3a7ea25c90dbce03968f31 |
|
metrics: |
|
- type: map_at_1 |
|
value: 7.892 |
|
- type: map_at_10 |
|
value: 13.358999999999998 |
|
- type: map_at_100 |
|
value: 14.396 |
|
- type: map_at_1000 |
|
value: 14.499 |
|
- type: map_at_3 |
|
value: 11.335 |
|
- type: map_at_5 |
|
value: 12.375 |
|
- type: mrr_at_1 |
|
value: 8.98 |
|
- type: mrr_at_10 |
|
value: 14.762 |
|
- type: mrr_at_100 |
|
value: 15.787 |
|
- type: mrr_at_1000 |
|
value: 15.873000000000001 |
|
- type: mrr_at_3 |
|
value: 12.65 |
|
- type: mrr_at_5 |
|
value: 13.761000000000001 |
|
- type: ndcg_at_1 |
|
value: 8.98 |
|
- type: ndcg_at_10 |
|
value: 17.013 |
|
- type: ndcg_at_100 |
|
value: 22.582 |
|
- type: ndcg_at_1000 |
|
value: 25.546000000000003 |
|
- type: ndcg_at_3 |
|
value: 12.765 |
|
- type: ndcg_at_5 |
|
value: 14.662 |
|
- type: precision_at_1 |
|
value: 8.98 |
|
- type: precision_at_10 |
|
value: 3.152 |
|
- type: precision_at_100 |
|
value: 0.636 |
|
- type: precision_at_1000 |
|
value: 0.092 |
|
- type: precision_at_3 |
|
value: 5.997 |
|
- type: precision_at_5 |
|
value: 4.652 |
|
- type: recall_at_1 |
|
value: 7.892 |
|
- type: recall_at_10 |
|
value: 27.081 |
|
- type: recall_at_100 |
|
value: 53.36300000000001 |
|
- type: recall_at_1000 |
|
value: 76.419 |
|
- type: recall_at_3 |
|
value: 15.623999999999999 |
|
- type: recall_at_5 |
|
value: 20.104 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB QuoraRetrieval |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 61.224999999999994 |
|
- type: map_at_10 |
|
value: 73.768 |
|
- type: map_at_100 |
|
value: 74.54899999999999 |
|
- type: map_at_1000 |
|
value: 74.588 |
|
- type: map_at_3 |
|
value: 70.845 |
|
- type: map_at_5 |
|
value: 72.61 |
|
- type: mrr_at_1 |
|
value: 70.63000000000001 |
|
- type: mrr_at_10 |
|
value: 78.204 |
|
- type: mrr_at_100 |
|
value: 78.469 |
|
- type: mrr_at_1000 |
|
value: 78.477 |
|
- type: mrr_at_3 |
|
value: 76.67500000000001 |
|
- type: mrr_at_5 |
|
value: 77.644 |
|
- type: ndcg_at_1 |
|
value: 70.61 |
|
- type: ndcg_at_10 |
|
value: 78.586 |
|
- type: ndcg_at_100 |
|
value: 80.852 |
|
- type: ndcg_at_1000 |
|
value: 81.32000000000001 |
|
- type: ndcg_at_3 |
|
value: 74.902 |
|
- type: ndcg_at_5 |
|
value: 76.787 |
|
- type: precision_at_1 |
|
value: 70.61 |
|
- type: precision_at_10 |
|
value: 11.904 |
|
- type: precision_at_100 |
|
value: 1.438 |
|
- type: precision_at_1000 |
|
value: 0.154 |
|
- type: precision_at_3 |
|
value: 32.503 |
|
- type: precision_at_5 |
|
value: 21.526 |
|
- type: recall_at_1 |
|
value: 61.224999999999994 |
|
- type: recall_at_10 |
|
value: 87.908 |
|
- type: recall_at_100 |
|
value: 96.63000000000001 |
|
- type: recall_at_1000 |
|
value: 99.367 |
|
- type: recall_at_3 |
|
value: 77.358 |
|
- type: recall_at_5 |
|
value: 82.584 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: None |
|
name: MTEB RedditClustering |
|
config: default |
|
split: test |
|
revision: 24640382cdbf8abc73003fb0fa6d111a705499eb |
|
metrics: |
|
- type: v_measure |
|
value: 33.05951893381823 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: None |
|
name: MTEB RedditClusteringP2P |
|
config: default |
|
split: test |
|
revision: 282350215ef01743dc01b456c7f5241fa8937f16 |
|
metrics: |
|
- type: v_measure |
|
value: 42.691497046210955 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB SCIDOCS |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 2.585 |
|
- type: map_at_10 |
|
value: 5.988 |
|
- type: map_at_100 |
|
value: 7.21 |
|
- type: map_at_1000 |
|
value: 7.449999999999999 |
|
- type: map_at_3 |
|
value: 4.372 |
|
- type: map_at_5 |
|
value: 5.194 |
|
- type: mrr_at_1 |
|
value: 12.8 |
|
- type: mrr_at_10 |
|
value: 19.963 |
|
- type: mrr_at_100 |
|
value: 21.195 |
|
- type: mrr_at_1000 |
|
value: 21.29 |
|
- type: mrr_at_3 |
|
value: 17.533 |
|
- type: mrr_at_5 |
|
value: 18.853 |
|
- type: ndcg_at_1 |
|
value: 12.8 |
|
- type: ndcg_at_10 |
|
value: 10.874 |
|
- type: ndcg_at_100 |
|
value: 16.695 |
|
- type: ndcg_at_1000 |
|
value: 21.762999999999998 |
|
- type: ndcg_at_3 |
|
value: 10.209 |
|
- type: ndcg_at_5 |
|
value: 8.999 |
|
- type: precision_at_1 |
|
value: 12.8 |
|
- type: precision_at_10 |
|
value: 5.65 |
|
- type: precision_at_100 |
|
value: 1.411 |
|
- type: precision_at_1000 |
|
value: 0.264 |
|
- type: precision_at_3 |
|
value: 9.433 |
|
- type: precision_at_5 |
|
value: 7.88 |
|
- type: recall_at_1 |
|
value: 2.585 |
|
- type: recall_at_10 |
|
value: 11.455 |
|
- type: recall_at_100 |
|
value: 28.665000000000003 |
|
- type: recall_at_1000 |
|
value: 53.547999999999995 |
|
- type: recall_at_3 |
|
value: 5.748 |
|
- type: recall_at_5 |
|
value: 7.983 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: None |
|
name: MTEB SICK-R |
|
config: default |
|
split: test |
|
revision: a6ea5a8cab320b040a23452cc28066d9beae2cee |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 76.47089854443493 |
|
- type: cos_sim_spearman |
|
value: 67.65881641628117 |
|
- type: euclidean_pearson |
|
value: 72.75220596907191 |
|
- type: euclidean_spearman |
|
value: 67.65881507675402 |
|
- type: manhattan_pearson |
|
value: 71.2932268352905 |
|
- type: manhattan_spearman |
|
value: 66.28937203768146 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: None |
|
name: MTEB STS12 |
|
config: default |
|
split: test |
|
revision: a0d554a64d88156834ff5ae9920b964011b16384 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 73.59904123111602 |
|
- type: cos_sim_spearman |
|
value: 66.64191118455778 |
|
- type: euclidean_pearson |
|
value: 70.031991407929 |
|
- type: euclidean_spearman |
|
value: 66.64312867708462 |
|
- type: manhattan_pearson |
|
value: 70.87113974670322 |
|
- type: manhattan_spearman |
|
value: 67.87998624470126 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: None |
|
name: MTEB STS13 |
|
config: default |
|
split: test |
|
revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 77.1868454480634 |
|
- type: cos_sim_spearman |
|
value: 78.5663631376088 |
|
- type: euclidean_pearson |
|
value: 78.1441330499307 |
|
- type: euclidean_spearman |
|
value: 78.5663753212518 |
|
- type: manhattan_pearson |
|
value: 78.7258747377543 |
|
- type: manhattan_spearman |
|
value: 79.24251325682667 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: None |
|
name: MTEB STS14 |
|
config: default |
|
split: test |
|
revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 77.39709143417873 |
|
- type: cos_sim_spearman |
|
value: 74.33024682805708 |
|
- type: euclidean_pearson |
|
value: 76.65457389990631 |
|
- type: euclidean_spearman |
|
value: 74.33023713728515 |
|
- type: manhattan_pearson |
|
value: 76.73342787471654 |
|
- type: manhattan_spearman |
|
value: 74.74461118652161 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: None |
|
name: MTEB STS15 |
|
config: default |
|
split: test |
|
revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 79.9395037638594 |
|
- type: cos_sim_spearman |
|
value: 81.01819776486752 |
|
- type: euclidean_pearson |
|
value: 81.03043241994847 |
|
- type: euclidean_spearman |
|
value: 81.01819627953365 |
|
- type: manhattan_pearson |
|
value: 81.68968136619384 |
|
- type: manhattan_spearman |
|
value: 81.82363999592259 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: None |
|
name: MTEB STS16 |
|
config: default |
|
split: test |
|
revision: 4d8694f8f0e0100860b497b999b3dbed754a0513 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 75.243504336461 |
|
- type: cos_sim_spearman |
|
value: 76.61917655422197 |
|
- type: euclidean_pearson |
|
value: 76.26910712210864 |
|
- type: euclidean_spearman |
|
value: 76.62000560376505 |
|
- type: manhattan_pearson |
|
value: 76.91613259757325 |
|
- type: manhattan_spearman |
|
value: 77.4215820608173 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: None |
|
name: MTEB STS17 (en-en) |
|
config: en-en |
|
split: test |
|
revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 82.99178286054092 |
|
- type: cos_sim_spearman |
|
value: 84.2361483019332 |
|
- type: euclidean_pearson |
|
value: 84.30885968598922 |
|
- type: euclidean_spearman |
|
value: 84.23702233300253 |
|
- type: manhattan_pearson |
|
value: 84.64734537899606 |
|
- type: manhattan_spearman |
|
value: 84.71355882886535 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: None |
|
name: MTEB STS22 (en) |
|
config: en |
|
split: test |
|
revision: eea2b4fe26a775864c896887d910b76a8098ad3f |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 63.18741235485141 |
|
- type: cos_sim_spearman |
|
value: 60.873579764468225 |
|
- type: euclidean_pearson |
|
value: 63.18427359110471 |
|
- type: euclidean_spearman |
|
value: 60.873579764468225 |
|
- type: manhattan_pearson |
|
value: 63.443408253414354 |
|
- type: manhattan_spearman |
|
value: 61.5997912341628 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: None |
|
name: MTEB STSBenchmark |
|
config: default |
|
split: test |
|
revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 77.15144919426055 |
|
- type: cos_sim_spearman |
|
value: 75.76050778643061 |
|
- type: euclidean_pearson |
|
value: 77.30073366013343 |
|
- type: euclidean_spearman |
|
value: 75.76052625455534 |
|
- type: manhattan_pearson |
|
value: 77.41746598074477 |
|
- type: manhattan_spearman |
|
value: 75.98770131791319 |
|
- task: |
|
type: Reranking |
|
dataset: |
|
type: None |
|
name: MTEB SciDocsRR |
|
config: default |
|
split: test |
|
revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab |
|
metrics: |
|
- type: map |
|
value: 70.66070662385174 |
|
- type: mrr |
|
value: 90.05894523051387 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB SciFact |
|
config: default |
|
split: test |
|
revision: 0228b52cf27578f30900b9e5271d331663a030d7 |
|
metrics: |
|
- type: map_at_1 |
|
value: 31.139 |
|
- type: map_at_10 |
|
value: 38.127 |
|
- type: map_at_100 |
|
value: 39.216 |
|
- type: map_at_1000 |
|
value: 39.290000000000006 |
|
- type: map_at_3 |
|
value: 35.667 |
|
- type: map_at_5 |
|
value: 37.317 |
|
- type: mrr_at_1 |
|
value: 33.333 |
|
- type: mrr_at_10 |
|
value: 39.972 |
|
- type: mrr_at_100 |
|
value: 40.892 |
|
- type: mrr_at_1000 |
|
value: 40.955000000000005 |
|
- type: mrr_at_3 |
|
value: 37.889 |
|
- type: mrr_at_5 |
|
value: 39.222 |
|
- type: ndcg_at_1 |
|
value: 33.333 |
|
- type: ndcg_at_10 |
|
value: 42.177 |
|
- type: ndcg_at_100 |
|
value: 47.772999999999996 |
|
- type: ndcg_at_1000 |
|
value: 49.738 |
|
- type: ndcg_at_3 |
|
value: 37.568 |
|
- type: ndcg_at_5 |
|
value: 40.294999999999995 |
|
- type: precision_at_1 |
|
value: 33.333 |
|
- type: precision_at_10 |
|
value: 5.867 |
|
- type: precision_at_100 |
|
value: 0.903 |
|
- type: precision_at_1000 |
|
value: 0.107 |
|
- type: precision_at_3 |
|
value: 14.777999999999999 |
|
- type: precision_at_5 |
|
value: 10.4 |
|
- type: recall_at_1 |
|
value: 31.139 |
|
- type: recall_at_10 |
|
value: 53.056000000000004 |
|
- type: recall_at_100 |
|
value: 79.60000000000001 |
|
- type: recall_at_1000 |
|
value: 95.133 |
|
- type: recall_at_3 |
|
value: 40.75 |
|
- type: recall_at_5 |
|
value: 47.417 |
|
- task: |
|
type: PairClassification |
|
dataset: |
|
type: None |
|
name: MTEB SprintDuplicateQuestions |
|
config: default |
|
split: test |
|
revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46 |
|
metrics: |
|
- type: cos_sim_accuracy |
|
value: 99.63663366336634 |
|
- type: cos_sim_ap |
|
value: 87.41569381811651 |
|
- type: cos_sim_f1 |
|
value: 80.8154730789336 |
|
- type: cos_sim_precision |
|
value: 84.66593647316539 |
|
- type: cos_sim_recall |
|
value: 77.3 |
|
- type: dot_accuracy |
|
value: 99.63663366336634 |
|
- type: dot_ap |
|
value: 87.41569381811651 |
|
- type: dot_f1 |
|
value: 80.8154730789336 |
|
- type: dot_precision |
|
value: 84.66593647316539 |
|
- type: dot_recall |
|
value: 77.3 |
|
- type: euclidean_accuracy |
|
value: 99.63663366336634 |
|
- type: euclidean_ap |
|
value: 87.41569381811651 |
|
- type: euclidean_f1 |
|
value: 80.8154730789336 |
|
- type: euclidean_precision |
|
value: 84.66593647316539 |
|
- type: euclidean_recall |
|
value: 77.3 |
|
- type: manhattan_accuracy |
|
value: 99.6930693069307 |
|
- type: manhattan_ap |
|
value: 90.67306262109962 |
|
- type: manhattan_f1 |
|
value: 84.03707518022657 |
|
- type: manhattan_precision |
|
value: 86.62420382165605 |
|
- type: manhattan_recall |
|
value: 81.6 |
|
- type: max_accuracy |
|
value: 99.6930693069307 |
|
- type: max_ap |
|
value: 90.67306262109962 |
|
- type: max_f1 |
|
value: 84.03707518022657 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: None |
|
name: MTEB StackExchangeClustering |
|
config: default |
|
split: test |
|
revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259 |
|
metrics: |
|
- type: v_measure |
|
value: 36.46819467809413 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: None |
|
name: MTEB StackExchangeClusteringP2P |
|
config: default |
|
split: test |
|
revision: 815ca46b2622cec33ccafc3735d572c266efdb44 |
|
metrics: |
|
- type: v_measure |
|
value: 29.142679626551587 |
|
- task: |
|
type: Reranking |
|
dataset: |
|
type: None |
|
name: MTEB StackOverflowDupQuestions |
|
config: default |
|
split: test |
|
revision: e185fbe320c72810689fc5848eb6114e1ef5ec69 |
|
metrics: |
|
- type: map |
|
value: 43.08118718504021 |
|
- type: mrr |
|
value: 43.547356442577026 |
|
- task: |
|
type: Summarization |
|
dataset: |
|
type: None |
|
name: MTEB SummEval |
|
config: default |
|
split: test |
|
revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 30.26989671913281 |
|
- type: cos_sim_spearman |
|
value: 30.01993799277349 |
|
- type: dot_pearson |
|
value: 30.26989672303903 |
|
- type: dot_spearman |
|
value: 30.03106981258351 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB TRECCOVID |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 0.133 |
|
- type: map_at_10 |
|
value: 0.707 |
|
- type: map_at_100 |
|
value: 3.759 |
|
- type: map_at_1000 |
|
value: 9.02 |
|
- type: map_at_3 |
|
value: 0.27399999999999997 |
|
- type: map_at_5 |
|
value: 0.4 |
|
- type: mrr_at_1 |
|
value: 54.0 |
|
- type: mrr_at_10 |
|
value: 61.147 |
|
- type: mrr_at_100 |
|
value: 62.076 |
|
- type: mrr_at_1000 |
|
value: 62.076 |
|
- type: mrr_at_3 |
|
value: 57.99999999999999 |
|
- type: mrr_at_5 |
|
value: 59.3 |
|
- type: ndcg_at_1 |
|
value: 44.0 |
|
- type: ndcg_at_10 |
|
value: 36.039 |
|
- type: ndcg_at_100 |
|
value: 28.122999999999998 |
|
- type: ndcg_at_1000 |
|
value: 25.650000000000002 |
|
- type: ndcg_at_3 |
|
value: 38.173 |
|
- type: ndcg_at_5 |
|
value: 37.35 |
|
- type: precision_at_1 |
|
value: 52.0 |
|
- type: precision_at_10 |
|
value: 39.4 |
|
- type: precision_at_100 |
|
value: 29.82 |
|
- type: precision_at_1000 |
|
value: 12.690000000000001 |
|
- type: precision_at_3 |
|
value: 42.0 |
|
- type: precision_at_5 |
|
value: 40.400000000000006 |
|
- type: recall_at_1 |
|
value: 0.133 |
|
- type: recall_at_10 |
|
value: 0.897 |
|
- type: recall_at_100 |
|
value: 6.336 |
|
- type: recall_at_1000 |
|
value: 24.990000000000002 |
|
- type: recall_at_3 |
|
value: 0.301 |
|
- type: recall_at_5 |
|
value: 0.462 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB Touche2020 |
|
config: default |
|
split: test |
|
revision: a34f9a33db75fa0cbb21bb5cfc3dae8dc8bec93f |
|
metrics: |
|
- type: map_at_1 |
|
value: 2.664 |
|
- type: map_at_10 |
|
value: 8.95 |
|
- type: map_at_100 |
|
value: 14.699000000000002 |
|
- type: map_at_1000 |
|
value: 16.275000000000002 |
|
- type: map_at_3 |
|
value: 4.963 |
|
- type: map_at_5 |
|
value: 6.707000000000001 |
|
- type: mrr_at_1 |
|
value: 36.735 |
|
- type: mrr_at_10 |
|
value: 48.016 |
|
- type: mrr_at_100 |
|
value: 48.826 |
|
- type: mrr_at_1000 |
|
value: 48.826 |
|
- type: mrr_at_3 |
|
value: 44.558 |
|
- type: mrr_at_5 |
|
value: 46.394999999999996 |
|
- type: ndcg_at_1 |
|
value: 33.672999999999995 |
|
- type: ndcg_at_10 |
|
value: 21.981 |
|
- type: ndcg_at_100 |
|
value: 35.227000000000004 |
|
- type: ndcg_at_1000 |
|
value: 46.428999999999995 |
|
- type: ndcg_at_3 |
|
value: 27.496 |
|
- type: ndcg_at_5 |
|
value: 24.886 |
|
- type: precision_at_1 |
|
value: 36.735 |
|
- type: precision_at_10 |
|
value: 19.184 |
|
- type: precision_at_100 |
|
value: 7.754999999999999 |
|
- type: precision_at_1000 |
|
value: 1.486 |
|
- type: precision_at_3 |
|
value: 27.891 |
|
- type: precision_at_5 |
|
value: 24.898 |
|
- type: recall_at_1 |
|
value: 2.664 |
|
- type: recall_at_10 |
|
value: 13.309999999999999 |
|
- type: recall_at_100 |
|
value: 46.727000000000004 |
|
- type: recall_at_1000 |
|
value: 81.158 |
|
- type: recall_at_3 |
|
value: 5.872 |
|
- type: recall_at_5 |
|
value: 8.694 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: None |
|
name: MTEB ToxicConversationsClassification |
|
config: default |
|
split: test |
|
revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c |
|
metrics: |
|
- type: accuracy |
|
value: 69.86019999999999 |
|
- type: ap |
|
value: 13.439585186117995 |
|
- type: f1 |
|
value: 53.53111224664294 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: None |
|
name: MTEB TweetSentimentExtractionClassification |
|
config: default |
|
split: test |
|
revision: d604517c81ca91fe16a244d1248fc021f9ecee7a |
|
metrics: |
|
- type: accuracy |
|
value: 53.539898132427844 |
|
- type: f1 |
|
value: 53.736121370681076 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: None |
|
name: MTEB TwentyNewsgroupsClustering |
|
config: default |
|
split: test |
|
revision: 6125ec4e24fa026cec8a478383ee943acfbd5449 |
|
metrics: |
|
- type: v_measure |
|
value: 33.790329189415395 |
|
- task: |
|
type: PairClassification |
|
dataset: |
|
type: None |
|
name: MTEB TwitterSemEval2015 |
|
config: default |
|
split: test |
|
revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1 |
|
metrics: |
|
- type: cos_sim_accuracy |
|
value: 83.59063002920665 |
|
- type: cos_sim_ap |
|
value: 65.1646758019036 |
|
- type: cos_sim_f1 |
|
value: 61.95799041886746 |
|
- type: cos_sim_precision |
|
value: 57.96368650884855 |
|
- type: cos_sim_recall |
|
value: 66.54353562005278 |
|
- type: dot_accuracy |
|
value: 83.59063002920665 |
|
- type: dot_ap |
|
value: 65.1646758019036 |
|
- type: dot_f1 |
|
value: 61.95799041886746 |
|
- type: dot_precision |
|
value: 57.96368650884855 |
|
- type: dot_recall |
|
value: 66.54353562005278 |
|
- type: euclidean_accuracy |
|
value: 83.59063002920665 |
|
- type: euclidean_ap |
|
value: 65.1646758019036 |
|
- type: euclidean_f1 |
|
value: 61.95799041886746 |
|
- type: euclidean_precision |
|
value: 57.96368650884855 |
|
- type: euclidean_recall |
|
value: 66.54353562005278 |
|
- type: manhattan_accuracy |
|
value: 83.29856350956668 |
|
- type: manhattan_ap |
|
value: 63.803561536283404 |
|
- type: manhattan_f1 |
|
value: 60.45279383429673 |
|
- type: manhattan_precision |
|
value: 55.60478511298184 |
|
- type: manhattan_recall |
|
value: 66.2269129287599 |
|
- type: max_accuracy |
|
value: 83.59063002920665 |
|
- type: max_ap |
|
value: 65.1646758019036 |
|
- type: max_f1 |
|
value: 61.95799041886746 |
|
- task: |
|
type: PairClassification |
|
dataset: |
|
type: None |
|
name: MTEB TwitterURLCorpus |
|
config: default |
|
split: test |
|
revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf |
|
metrics: |
|
- type: cos_sim_accuracy |
|
value: 87.46264602010324 |
|
- type: cos_sim_ap |
|
value: 82.64331601180713 |
|
- type: cos_sim_f1 |
|
value: 74.66489420627008 |
|
- type: cos_sim_precision |
|
value: 71.73774214148868 |
|
- type: cos_sim_recall |
|
value: 77.8410840776101 |
|
- type: dot_accuracy |
|
value: 87.46264602010324 |
|
- type: dot_ap |
|
value: 82.64331811121104 |
|
- type: dot_f1 |
|
value: 74.66489420627008 |
|
- type: dot_precision |
|
value: 71.73774214148868 |
|
- type: dot_recall |
|
value: 77.8410840776101 |
|
- type: euclidean_accuracy |
|
value: 87.46264602010324 |
|
- type: euclidean_ap |
|
value: 82.64331792274162 |
|
- type: euclidean_f1 |
|
value: 74.66489420627008 |
|
- type: euclidean_precision |
|
value: 71.73774214148868 |
|
- type: euclidean_recall |
|
value: 77.8410840776101 |
|
- type: manhattan_accuracy |
|
value: 87.35203943027904 |
|
- type: manhattan_ap |
|
value: 82.69548093072707 |
|
- type: manhattan_f1 |
|
value: 74.90158915293776 |
|
- type: manhattan_precision |
|
value: 71.1171096345515 |
|
- type: manhattan_recall |
|
value: 79.11148752694795 |
|
- type: max_accuracy |
|
value: 87.46264602010324 |
|
- type: max_ap |
|
value: 82.69548093072707 |
|
- type: max_f1 |
|
value: 74.90158915293776 |
|
--- |
