|
--- |
|
tags: |
|
- mteb |
|
model-index: |
|
- name: nomic_classification_nignore30 |
|
results: |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: None |
|
name: MTEB AmazonCounterfactualClassification (en) |
|
config: en |
|
split: test |
|
revision: e8379541af4e31359cca9fbcf4b00f2671dba205 |
|
metrics: |
|
- type: accuracy |
|
value: 74.02985074626865 |
|
- type: ap |
|
value: 36.54755879675939 |
|
- type: f1 |
|
value: 67.84911428462374 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: None |
|
name: MTEB AmazonPolarityClassification |
|
config: default |
|
split: test |
|
revision: e2d317d38cd51312af73b3d32a06d1a08b442046 |
|
metrics: |
|
- type: accuracy |
|
value: 60.98745000000001 |
|
- type: ap |
|
value: 56.79972495487593 |
|
- type: f1 |
|
value: 60.79607311981127 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: None |
|
name: MTEB AmazonReviewsClassification (en) |
|
config: en |
|
split: test |
|
revision: 1399c76144fd37290681b995c656ef9b2e06e26d |
|
metrics: |
|
- type: accuracy |
|
value: 31.606000000000005 |
|
- type: f1 |
|
value: 31.20575804283948 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB ArguAna |
|
config: default |
|
split: test |
|
revision: c22ab2a51041ffd869aaddef7af8d8215647e41a |
|
metrics: |
|
- type: map_at_1 |
|
value: 21.266 |
|
- type: map_at_10 |
|
value: 35.579 |
|
- type: map_at_100 |
|
value: 36.867 |
|
- type: map_at_1000 |
|
value: 36.887 |
|
- type: map_at_3 |
|
value: 31.105 |
|
- type: map_at_5 |
|
value: 33.512 |
|
- type: mrr_at_1 |
|
value: 21.764 |
|
- type: mrr_at_10 |
|
value: 35.768 |
|
- type: mrr_at_100 |
|
value: 37.049 |
|
- type: mrr_at_1000 |
|
value: 37.069 |
|
- type: mrr_at_3 |
|
value: 31.354 |
|
- type: mrr_at_5 |
|
value: 33.694 |
|
- type: ndcg_at_1 |
|
value: 21.266 |
|
- type: ndcg_at_10 |
|
value: 43.697 |
|
- type: ndcg_at_100 |
|
value: 49.444 |
|
- type: ndcg_at_1000 |
|
value: 49.918 |
|
- type: ndcg_at_3 |
|
value: 34.415 |
|
- type: ndcg_at_5 |
|
value: 38.751999999999995 |
|
- type: precision_at_1 |
|
value: 21.266 |
|
- type: precision_at_10 |
|
value: 6.97 |
|
- type: precision_at_100 |
|
value: 0.954 |
|
- type: precision_at_1000 |
|
value: 0.099 |
|
- type: precision_at_3 |
|
value: 14.674999999999999 |
|
- type: precision_at_5 |
|
value: 10.91 |
|
- type: recall_at_1 |
|
value: 21.266 |
|
- type: recall_at_10 |
|
value: 69.70100000000001 |
|
- type: recall_at_100 |
|
value: 95.448 |
|
- type: recall_at_1000 |
|
value: 99.075 |
|
- type: recall_at_3 |
|
value: 44.025999999999996 |
|
- type: recall_at_5 |
|
value: 54.552 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: None |
|
name: MTEB ArxivClusteringP2P |
|
config: default |
|
split: test |
|
revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d |
|
metrics: |
|
- type: v_measure |
|
value: 35.45486521675564 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: None |
|
name: MTEB ArxivClusteringS2S |
|
config: default |
|
split: test |
|
revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53 |
|
metrics: |
|
- type: v_measure |
|
value: 24.270159650279354 |
|
- task: |
|
type: Reranking |
|
dataset: |
|
type: None |
|
name: MTEB AskUbuntuDupQuestions |
|
config: default |
|
split: test |
|
revision: 2000358ca161889fa9c082cb41daa8dcfb161a54 |
|
metrics: |
|
- type: map |
|
value: 53.62399843388994 |
|
- type: mrr |
|
value: 68.1675680429143 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: None |
|
name: MTEB BIOSSES |
|
config: default |
|
split: test |
|
revision: d3fb88f8f02e40887cd149695127462bbcf29b4a |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 83.62266587849676 |
|
- type: cos_sim_spearman |
|
value: 80.48918339823612 |
|
- type: euclidean_pearson |
|
value: 82.46661732971302 |
|
- type: euclidean_spearman |
|
value: 80.48918339823612 |
|
- type: manhattan_pearson |
|
value: 81.55398066885756 |
|
- type: manhattan_spearman |
|
value: 80.27411825686711 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: None |
|
name: MTEB Banking77Classification |
|
config: default |
|
split: test |
|
revision: 0fd18e25b25c072e09e0d92ab615fda904d66300 |
|
metrics: |
|
- type: accuracy |
|
value: 73.07142857142857 |
|
- type: f1 |
|
value: 72.39723822054579 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: None |
|
name: MTEB BiorxivClusteringP2P |
|
config: default |
|
split: test |
|
revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40 |
|
metrics: |
|
- type: v_measure |
|
value: 32.426645848653045 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: None |
|
name: MTEB BiorxivClusteringS2S |
|
config: default |
|
split: test |
|
revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908 |
|
metrics: |
|
- type: v_measure |
|
value: 23.54829160604571 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB CQADupstackAndroidRetrieval |
|
config: default |
|
split: test |
|
revision: f46a197baaae43b4f621051089b82a364682dfeb |
|
metrics: |
|
- type: map_at_1 |
|
value: 24.001 |
|
- type: map_at_10 |
|
value: 31.195 |
|
- type: map_at_100 |
|
value: 32.342999999999996 |
|
- type: map_at_1000 |
|
value: 32.489000000000004 |
|
- type: map_at_3 |
|
value: 28.814 |
|
- type: map_at_5 |
|
value: 30.014000000000003 |
|
- type: mrr_at_1 |
|
value: 30.186 |
|
- type: mrr_at_10 |
|
value: 37.034 |
|
- type: mrr_at_100 |
|
value: 37.881 |
|
- type: mrr_at_1000 |
|
value: 37.946000000000005 |
|
- type: mrr_at_3 |
|
value: 35.241 |
|
- type: mrr_at_5 |
|
value: 36.120999999999995 |
|
- type: ndcg_at_1 |
|
value: 30.186 |
|
- type: ndcg_at_10 |
|
value: 35.972 |
|
- type: ndcg_at_100 |
|
value: 41.25 |
|
- type: ndcg_at_1000 |
|
value: 44.171 |
|
- type: ndcg_at_3 |
|
value: 32.674 |
|
- type: ndcg_at_5 |
|
value: 33.833 |
|
- type: precision_at_1 |
|
value: 30.186 |
|
- type: precision_at_10 |
|
value: 6.723999999999999 |
|
- type: precision_at_100 |
|
value: 1.157 |
|
- type: precision_at_1000 |
|
value: 0.172 |
|
- type: precision_at_3 |
|
value: 15.451 |
|
- type: precision_at_5 |
|
value: 10.815 |
|
- type: recall_at_1 |
|
value: 24.001 |
|
- type: recall_at_10 |
|
value: 44.057 |
|
- type: recall_at_100 |
|
value: 67.72500000000001 |
|
- type: recall_at_1000 |
|
value: 87.464 |
|
- type: recall_at_3 |
|
value: 33.817 |
|
- type: recall_at_5 |
|
value: 37.684 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB CQADupstackEnglishRetrieval |
|
config: default |
|
split: test |
|
revision: ad9991cb51e31e31e430383c75ffb2885547b5f0 |
|
metrics: |
|
- type: map_at_1 |
|
value: 16.766000000000002 |
|
- type: map_at_10 |
|
value: 23.07 |
|
- type: map_at_100 |
|
value: 24.062 |
|
- type: map_at_1000 |
|
value: 24.178 |
|
- type: map_at_3 |
|
value: 21.364 |
|
- type: map_at_5 |
|
value: 22.3 |
|
- type: mrr_at_1 |
|
value: 21.146 |
|
- type: mrr_at_10 |
|
value: 27.24 |
|
- type: mrr_at_100 |
|
value: 28.092 |
|
- type: mrr_at_1000 |
|
value: 28.163 |
|
- type: mrr_at_3 |
|
value: 25.605 |
|
- type: mrr_at_5 |
|
value: 26.567 |
|
- type: ndcg_at_1 |
|
value: 21.146 |
|
- type: ndcg_at_10 |
|
value: 27.031 |
|
- type: ndcg_at_100 |
|
value: 31.430999999999997 |
|
- type: ndcg_at_1000 |
|
value: 34.086 |
|
- type: ndcg_at_3 |
|
value: 24.136 |
|
- type: ndcg_at_5 |
|
value: 25.462 |
|
- type: precision_at_1 |
|
value: 21.146 |
|
- type: precision_at_10 |
|
value: 5.006 |
|
- type: precision_at_100 |
|
value: 0.901 |
|
- type: precision_at_1000 |
|
value: 0.13699999999999998 |
|
- type: precision_at_3 |
|
value: 11.762 |
|
- type: precision_at_5 |
|
value: 8.229000000000001 |
|
- type: recall_at_1 |
|
value: 16.766000000000002 |
|
- type: recall_at_10 |
|
value: 34.55 |
|
- type: recall_at_100 |
|
value: 53.542 |
|
- type: recall_at_1000 |
|
value: 71.66900000000001 |
|
- type: recall_at_3 |
|
value: 26.205000000000002 |
|
- type: recall_at_5 |
|
value: 29.854000000000003 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB CQADupstackGamingRetrieval |
|
config: default |
|
split: test |
|
revision: 4885aa143210c98657558c04aaf3dc47cfb54340 |
|
metrics: |
|
- type: map_at_1 |
|
value: 26.579000000000004 |
|
- type: map_at_10 |
|
value: 35.482 |
|
- type: map_at_100 |
|
value: 36.564 |
|
- type: map_at_1000 |
|
value: 36.656 |
|
- type: map_at_3 |
|
value: 32.940999999999995 |
|
- type: map_at_5 |
|
value: 34.331 |
|
- type: mrr_at_1 |
|
value: 30.784 |
|
- type: mrr_at_10 |
|
value: 38.721 |
|
- type: mrr_at_100 |
|
value: 39.592 |
|
- type: mrr_at_1000 |
|
value: 39.653 |
|
- type: mrr_at_3 |
|
value: 36.468 |
|
- type: mrr_at_5 |
|
value: 37.688 |
|
- type: ndcg_at_1 |
|
value: 30.784 |
|
- type: ndcg_at_10 |
|
value: 40.351 |
|
- type: ndcg_at_100 |
|
value: 45.499 |
|
- type: ndcg_at_1000 |
|
value: 47.641 |
|
- type: ndcg_at_3 |
|
value: 35.605 |
|
- type: ndcg_at_5 |
|
value: 37.798 |
|
- type: precision_at_1 |
|
value: 30.784 |
|
- type: precision_at_10 |
|
value: 6.564 |
|
- type: precision_at_100 |
|
value: 1.004 |
|
- type: precision_at_1000 |
|
value: 0.126 |
|
- type: precision_at_3 |
|
value: 15.862000000000002 |
|
- type: precision_at_5 |
|
value: 11.008999999999999 |
|
- type: recall_at_1 |
|
value: 26.579000000000004 |
|
- type: recall_at_10 |
|
value: 51.978 |
|
- type: recall_at_100 |
|
value: 75.331 |
|
- type: recall_at_1000 |
|
value: 90.774 |
|
- type: recall_at_3 |
|
value: 39.149 |
|
- type: recall_at_5 |
|
value: 44.516 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB CQADupstackGisRetrieval |
|
config: default |
|
split: test |
|
revision: 5003b3064772da1887988e05400cf3806fe491f2 |
|
metrics: |
|
- type: map_at_1 |
|
value: 13.013 |
|
- type: map_at_10 |
|
value: 17.393 |
|
- type: map_at_100 |
|
value: 18.256 |
|
- type: map_at_1000 |
|
value: 18.364 |
|
- type: map_at_3 |
|
value: 15.812000000000001 |
|
- type: map_at_5 |
|
value: 16.601 |
|
- type: mrr_at_1 |
|
value: 14.237 |
|
- type: mrr_at_10 |
|
value: 18.706999999999997 |
|
- type: mrr_at_100 |
|
value: 19.553 |
|
- type: mrr_at_1000 |
|
value: 19.651 |
|
- type: mrr_at_3 |
|
value: 17.081 |
|
- type: mrr_at_5 |
|
value: 17.895 |
|
- type: ndcg_at_1 |
|
value: 14.237 |
|
- type: ndcg_at_10 |
|
value: 20.315 |
|
- type: ndcg_at_100 |
|
value: 24.914 |
|
- type: ndcg_at_1000 |
|
value: 28.244999999999997 |
|
- type: ndcg_at_3 |
|
value: 16.994 |
|
- type: ndcg_at_5 |
|
value: 18.396 |
|
- type: precision_at_1 |
|
value: 14.237 |
|
- type: precision_at_10 |
|
value: 3.198 |
|
- type: precision_at_100 |
|
value: 0.583 |
|
- type: precision_at_1000 |
|
value: 0.092 |
|
- type: precision_at_3 |
|
value: 7.0809999999999995 |
|
- type: precision_at_5 |
|
value: 4.994 |
|
- type: recall_at_1 |
|
value: 13.013 |
|
- type: recall_at_10 |
|
value: 28.297 |
|
- type: recall_at_100 |
|
value: 50.113 |
|
- type: recall_at_1000 |
|
value: 76.19500000000001 |
|
- type: recall_at_3 |
|
value: 19.062 |
|
- type: recall_at_5 |
|
value: 22.527 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB CQADupstackMathematicaRetrieval |
|
config: default |
|
split: test |
|
revision: 90fceea13679c63fe563ded68f3b6f06e50061de |
|
metrics: |
|
- type: map_at_1 |
|
value: 6.783 |
|
- type: map_at_10 |
|
value: 10.439 |
|
- type: map_at_100 |
|
value: 11.26 |
|
- type: map_at_1000 |
|
value: 11.394 |
|
- type: map_at_3 |
|
value: 9.314 |
|
- type: map_at_5 |
|
value: 9.832 |
|
- type: mrr_at_1 |
|
value: 8.831 |
|
- type: mrr_at_10 |
|
value: 12.902 |
|
- type: mrr_at_100 |
|
value: 13.799 |
|
- type: mrr_at_1000 |
|
value: 13.901 |
|
- type: mrr_at_3 |
|
value: 11.692 |
|
- type: mrr_at_5 |
|
value: 12.200999999999999 |
|
- type: ndcg_at_1 |
|
value: 8.831 |
|
- type: ndcg_at_10 |
|
value: 12.973 |
|
- type: ndcg_at_100 |
|
value: 17.465 |
|
- type: ndcg_at_1000 |
|
value: 21.203 |
|
- type: ndcg_at_3 |
|
value: 10.778 |
|
- type: ndcg_at_5 |
|
value: 11.601 |
|
- type: precision_at_1 |
|
value: 8.831 |
|
- type: precision_at_10 |
|
value: 2.475 |
|
- type: precision_at_100 |
|
value: 0.553 |
|
- type: precision_at_1000 |
|
value: 0.101 |
|
- type: precision_at_3 |
|
value: 5.265000000000001 |
|
- type: precision_at_5 |
|
value: 3.781 |
|
- type: recall_at_1 |
|
value: 6.783 |
|
- type: recall_at_10 |
|
value: 18.386 |
|
- type: recall_at_100 |
|
value: 38.885999999999996 |
|
- type: recall_at_1000 |
|
value: 66.621 |
|
- type: recall_at_3 |
|
value: 12.235 |
|
- type: recall_at_5 |
|
value: 14.374999999999998 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB CQADupstackPhysicsRetrieval |
|
config: default |
|
split: test |
|
revision: 79531abbd1fb92d06c6d6315a0cbbbf5bb247ea4 |
|
metrics: |
|
- type: map_at_1 |
|
value: 17.946 |
|
- type: map_at_10 |
|
value: 24.188000000000002 |
|
- type: map_at_100 |
|
value: 25.402 |
|
- type: map_at_1000 |
|
value: 25.544 |
|
- type: map_at_3 |
|
value: 22.157 |
|
- type: map_at_5 |
|
value: 23.315 |
|
- type: mrr_at_1 |
|
value: 22.233 |
|
- type: mrr_at_10 |
|
value: 28.703 |
|
- type: mrr_at_100 |
|
value: 29.669 |
|
- type: mrr_at_1000 |
|
value: 29.748 |
|
- type: mrr_at_3 |
|
value: 26.676 |
|
- type: mrr_at_5 |
|
value: 27.894000000000002 |
|
- type: ndcg_at_1 |
|
value: 22.233 |
|
- type: ndcg_at_10 |
|
value: 28.483999999999998 |
|
- type: ndcg_at_100 |
|
value: 34.239999999999995 |
|
- type: ndcg_at_1000 |
|
value: 37.351 |
|
- type: ndcg_at_3 |
|
value: 25.018 |
|
- type: ndcg_at_5 |
|
value: 26.679000000000002 |
|
- type: precision_at_1 |
|
value: 22.233 |
|
- type: precision_at_10 |
|
value: 5.236 |
|
- type: precision_at_100 |
|
value: 0.962 |
|
- type: precision_at_1000 |
|
value: 0.14200000000000002 |
|
- type: precision_at_3 |
|
value: 11.806 |
|
- type: precision_at_5 |
|
value: 8.566 |
|
- type: recall_at_1 |
|
value: 17.946 |
|
- type: recall_at_10 |
|
value: 37.049 |
|
- type: recall_at_100 |
|
value: 62.473 |
|
- type: recall_at_1000 |
|
value: 83.829 |
|
- type: recall_at_3 |
|
value: 27.022000000000002 |
|
- type: recall_at_5 |
|
value: 31.435000000000002 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB CQADupstackProgrammersRetrieval |
|
config: default |
|
split: test |
|
revision: 6184bc1440d2dbc7612be22b50686b8826d22b32 |
|
metrics: |
|
- type: map_at_1 |
|
value: 13.966000000000001 |
|
- type: map_at_10 |
|
value: 19.797 |
|
- type: map_at_100 |
|
value: 20.764 |
|
- type: map_at_1000 |
|
value: 20.913 |
|
- type: map_at_3 |
|
value: 17.688000000000002 |
|
- type: map_at_5 |
|
value: 18.796 |
|
- type: mrr_at_1 |
|
value: 17.122999999999998 |
|
- type: mrr_at_10 |
|
value: 23.277 |
|
- type: mrr_at_100 |
|
value: 24.095 |
|
- type: mrr_at_1000 |
|
value: 24.197 |
|
- type: mrr_at_3 |
|
value: 21.176000000000002 |
|
- type: mrr_at_5 |
|
value: 22.323 |
|
- type: ndcg_at_1 |
|
value: 17.122999999999998 |
|
- type: ndcg_at_10 |
|
value: 23.860999999999997 |
|
- type: ndcg_at_100 |
|
value: 28.669 |
|
- type: ndcg_at_1000 |
|
value: 32.375 |
|
- type: ndcg_at_3 |
|
value: 19.983999999999998 |
|
- type: ndcg_at_5 |
|
value: 21.647 |
|
- type: precision_at_1 |
|
value: 17.122999999999998 |
|
- type: precision_at_10 |
|
value: 4.623 |
|
- type: precision_at_100 |
|
value: 0.839 |
|
- type: precision_at_1000 |
|
value: 0.133 |
|
- type: precision_at_3 |
|
value: 9.551 |
|
- type: precision_at_5 |
|
value: 7.1 |
|
- type: recall_at_1 |
|
value: 13.966000000000001 |
|
- type: recall_at_10 |
|
value: 32.629999999999995 |
|
- type: recall_at_100 |
|
value: 53.842 |
|
- type: recall_at_1000 |
|
value: 80.583 |
|
- type: recall_at_3 |
|
value: 21.804000000000002 |
|
- type: recall_at_5 |
|
value: 26.101999999999997 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: mteb/cqadupstack |
|
name: MTEB CQADupstackRetrieval |
|
config: default |
|
split: test |
|
revision: 4885aa143210c98657558c04aaf3dc47cfb54340 |
|
metrics: |
|
- type: map_at_1 |
|
value: 14.974750000000004 |
|
- type: map_at_10 |
|
value: 20.34575 |
|
- type: map_at_100 |
|
value: 21.290416666666665 |
|
- type: map_at_1000 |
|
value: 21.41825 |
|
- type: map_at_3 |
|
value: 18.576500000000003 |
|
- type: map_at_5 |
|
value: 19.546166666666668 |
|
- type: mrr_at_1 |
|
value: 18.049249999999997 |
|
- type: mrr_at_10 |
|
value: 23.45216666666667 |
|
- type: mrr_at_100 |
|
value: 24.29241666666667 |
|
- type: mrr_at_1000 |
|
value: 24.37841666666667 |
|
- type: mrr_at_3 |
|
value: 21.728749999999998 |
|
- type: mrr_at_5 |
|
value: 22.680916666666665 |
|
- type: ndcg_at_1 |
|
value: 18.049249999999997 |
|
- type: ndcg_at_10 |
|
value: 23.90125 |
|
- type: ndcg_at_100 |
|
value: 28.57325 |
|
- type: ndcg_at_1000 |
|
value: 31.747583333333335 |
|
- type: ndcg_at_3 |
|
value: 20.71783333333333 |
|
- type: ndcg_at_5 |
|
value: 22.17008333333333 |
|
- type: precision_at_1 |
|
value: 18.049249999999997 |
|
- type: precision_at_10 |
|
value: 4.257666666666667 |
|
- type: precision_at_100 |
|
value: 0.7843333333333332 |
|
- type: precision_at_1000 |
|
value: 0.12375000000000003 |
|
- type: precision_at_3 |
|
value: 9.573750000000002 |
|
- type: precision_at_5 |
|
value: 6.871666666666666 |
|
- type: recall_at_1 |
|
value: 14.974750000000004 |
|
- type: recall_at_10 |
|
value: 31.535416666666666 |
|
- type: recall_at_100 |
|
value: 52.869583333333324 |
|
- type: recall_at_1000 |
|
value: 75.93208333333334 |
|
- type: recall_at_3 |
|
value: 22.561833333333333 |
|
- type: recall_at_5 |
|
value: 26.351583333333334 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB CQADupstackStatsRetrieval |
|
config: default |
|
split: test |
|
revision: 65ac3a16b8e91f9cee4c9828cc7c335575432a2a |
|
metrics: |
|
- type: map_at_1 |
|
value: 11.584 |
|
- type: map_at_10 |
|
value: 15.47 |
|
- type: map_at_100 |
|
value: 16.276 |
|
- type: map_at_1000 |
|
value: 16.361 |
|
- type: map_at_3 |
|
value: 14.022000000000002 |
|
- type: map_at_5 |
|
value: 14.884 |
|
- type: mrr_at_1 |
|
value: 13.65 |
|
- type: mrr_at_10 |
|
value: 17.566000000000003 |
|
- type: mrr_at_100 |
|
value: 18.335 |
|
- type: mrr_at_1000 |
|
value: 18.411 |
|
- type: mrr_at_3 |
|
value: 16.053 |
|
- type: mrr_at_5 |
|
value: 16.843 |
|
- type: ndcg_at_1 |
|
value: 13.65 |
|
- type: ndcg_at_10 |
|
value: 18.208 |
|
- type: ndcg_at_100 |
|
value: 22.352 |
|
- type: ndcg_at_1000 |
|
value: 24.969 |
|
- type: ndcg_at_3 |
|
value: 15.459 |
|
- type: ndcg_at_5 |
|
value: 16.817 |
|
- type: precision_at_1 |
|
value: 13.65 |
|
- type: precision_at_10 |
|
value: 3.083 |
|
- type: precision_at_100 |
|
value: 0.561 |
|
- type: precision_at_1000 |
|
value: 0.086 |
|
- type: precision_at_3 |
|
value: 6.902 |
|
- type: precision_at_5 |
|
value: 4.968999999999999 |
|
- type: recall_at_1 |
|
value: 11.584 |
|
- type: recall_at_10 |
|
value: 24.629 |
|
- type: recall_at_100 |
|
value: 43.963 |
|
- type: recall_at_1000 |
|
value: 63.944 |
|
- type: recall_at_3 |
|
value: 17.155 |
|
- type: recall_at_5 |
|
value: 20.598 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB CQADupstackTexRetrieval |
|
config: default |
|
split: test |
|
revision: 46989137a86843e03a6195de44b09deda022eec7 |
|
metrics: |
|
- type: map_at_1 |
|
value: 7.792000000000001 |
|
- type: map_at_10 |
|
value: 11.246 |
|
- type: map_at_100 |
|
value: 11.955 |
|
- type: map_at_1000 |
|
value: 12.076 |
|
- type: map_at_3 |
|
value: 10.176 |
|
- type: map_at_5 |
|
value: 10.802 |
|
- type: mrr_at_1 |
|
value: 9.67 |
|
- type: mrr_at_10 |
|
value: 13.591000000000001 |
|
- type: mrr_at_100 |
|
value: 14.285999999999998 |
|
- type: mrr_at_1000 |
|
value: 14.385 |
|
- type: mrr_at_3 |
|
value: 12.394 |
|
- type: mrr_at_5 |
|
value: 13.104 |
|
- type: ndcg_at_1 |
|
value: 9.67 |
|
- type: ndcg_at_10 |
|
value: 13.645 |
|
- type: ndcg_at_100 |
|
value: 17.562 |
|
- type: ndcg_at_1000 |
|
value: 21.101 |
|
- type: ndcg_at_3 |
|
value: 11.635 |
|
- type: ndcg_at_5 |
|
value: 12.638 |
|
- type: precision_at_1 |
|
value: 9.67 |
|
- type: precision_at_10 |
|
value: 2.54 |
|
- type: precision_at_100 |
|
value: 0.538 |
|
- type: precision_at_1000 |
|
value: 0.101 |
|
- type: precision_at_3 |
|
value: 5.632000000000001 |
|
- type: precision_at_5 |
|
value: 4.136 |
|
- type: recall_at_1 |
|
value: 7.792000000000001 |
|
- type: recall_at_10 |
|
value: 18.63 |
|
- type: recall_at_100 |
|
value: 37.047999999999995 |
|
- type: recall_at_1000 |
|
value: 63.391 |
|
- type: recall_at_3 |
|
value: 12.956999999999999 |
|
- type: recall_at_5 |
|
value: 15.581 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB CQADupstackUnixRetrieval |
|
config: default |
|
split: test |
|
revision: 6c6430d3a6d36f8d2a829195bc5dc94d7e063e53 |
|
metrics: |
|
- type: map_at_1 |
|
value: 13.358999999999998 |
|
- type: map_at_10 |
|
value: 18.154999999999998 |
|
- type: map_at_100 |
|
value: 19.008 |
|
- type: map_at_1000 |
|
value: 19.125 |
|
- type: map_at_3 |
|
value: 16.645 |
|
- type: map_at_5 |
|
value: 17.544999999999998 |
|
- type: mrr_at_1 |
|
value: 15.672 |
|
- type: mrr_at_10 |
|
value: 20.973 |
|
- type: mrr_at_100 |
|
value: 21.782 |
|
- type: mrr_at_1000 |
|
value: 21.88 |
|
- type: mrr_at_3 |
|
value: 19.356 |
|
- type: mrr_at_5 |
|
value: 20.28 |
|
- type: ndcg_at_1 |
|
value: 15.672 |
|
- type: ndcg_at_10 |
|
value: 21.391 |
|
- type: ndcg_at_100 |
|
value: 25.71 |
|
- type: ndcg_at_1000 |
|
value: 29.016 |
|
- type: ndcg_at_3 |
|
value: 18.489 |
|
- type: ndcg_at_5 |
|
value: 19.916 |
|
- type: precision_at_1 |
|
value: 15.672 |
|
- type: precision_at_10 |
|
value: 3.573 |
|
- type: precision_at_100 |
|
value: 0.636 |
|
- type: precision_at_1000 |
|
value: 0.10300000000000001 |
|
- type: precision_at_3 |
|
value: 8.488999999999999 |
|
- type: precision_at_5 |
|
value: 5.989 |
|
- type: recall_at_1 |
|
value: 13.358999999999998 |
|
- type: recall_at_10 |
|
value: 28.695999999999998 |
|
- type: recall_at_100 |
|
value: 48.165 |
|
- type: recall_at_1000 |
|
value: 72.64500000000001 |
|
- type: recall_at_3 |
|
value: 20.573 |
|
- type: recall_at_5 |
|
value: 24.284 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB CQADupstackWebmastersRetrieval |
|
config: default |
|
split: test |
|
revision: 160c094312a0e1facb97e55eeddb698c0abe3571 |
|
metrics: |
|
- type: map_at_1 |
|
value: 15.881 |
|
- type: map_at_10 |
|
value: 21.754 |
|
- type: map_at_100 |
|
value: 22.88 |
|
- type: map_at_1000 |
|
value: 23.087 |
|
- type: map_at_3 |
|
value: 19.827 |
|
- type: map_at_5 |
|
value: 20.964 |
|
- type: mrr_at_1 |
|
value: 19.564999999999998 |
|
- type: mrr_at_10 |
|
value: 25.246000000000002 |
|
- type: mrr_at_100 |
|
value: 26.163999999999998 |
|
- type: mrr_at_1000 |
|
value: 26.240999999999996 |
|
- type: mrr_at_3 |
|
value: 23.352999999999998 |
|
- type: mrr_at_5 |
|
value: 24.587999999999997 |
|
- type: ndcg_at_1 |
|
value: 19.564999999999998 |
|
- type: ndcg_at_10 |
|
value: 25.740000000000002 |
|
- type: ndcg_at_100 |
|
value: 30.977 |
|
- type: ndcg_at_1000 |
|
value: 34.486 |
|
- type: ndcg_at_3 |
|
value: 22.625 |
|
- type: ndcg_at_5 |
|
value: 24.294 |
|
- type: precision_at_1 |
|
value: 19.564999999999998 |
|
- type: precision_at_10 |
|
value: 5.0200000000000005 |
|
- type: precision_at_100 |
|
value: 1.146 |
|
- type: precision_at_1000 |
|
value: 0.201 |
|
- type: precision_at_3 |
|
value: 10.738 |
|
- type: precision_at_5 |
|
value: 8.103 |
|
- type: recall_at_1 |
|
value: 15.881 |
|
- type: recall_at_10 |
|
value: 32.918 |
|
- type: recall_at_100 |
|
value: 58.184000000000005 |
|
- type: recall_at_1000 |
|
value: 81.76299999999999 |
|
- type: recall_at_3 |
|
value: 23.992 |
|
- type: recall_at_5 |
|
value: 28.265 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB CQADupstackWordpressRetrieval |
|
config: default |
|
split: test |
|
revision: 4ffe81d471b1924886b33c7567bfb200e9eec5c4 |
|
metrics: |
|
- type: map_at_1 |
|
value: 12.027000000000001 |
|
- type: map_at_10 |
|
value: 15.959999999999999 |
|
- type: map_at_100 |
|
value: 16.715 |
|
- type: map_at_1000 |
|
value: 16.832 |
|
- type: map_at_3 |
|
value: 14.158000000000001 |
|
- type: map_at_5 |
|
value: 15.17 |
|
- type: mrr_at_1 |
|
value: 13.494 |
|
- type: mrr_at_10 |
|
value: 17.466 |
|
- type: mrr_at_100 |
|
value: 18.261 |
|
- type: mrr_at_1000 |
|
value: 18.365000000000002 |
|
- type: mrr_at_3 |
|
value: 15.65 |
|
- type: mrr_at_5 |
|
value: 16.667 |
|
- type: ndcg_at_1 |
|
value: 13.494 |
|
- type: ndcg_at_10 |
|
value: 18.844 |
|
- type: ndcg_at_100 |
|
value: 22.81 |
|
- type: ndcg_at_1000 |
|
value: 26.327 |
|
- type: ndcg_at_3 |
|
value: 15.217 |
|
- type: ndcg_at_5 |
|
value: 16.96 |
|
- type: precision_at_1 |
|
value: 13.494 |
|
- type: precision_at_10 |
|
value: 3.05 |
|
- type: precision_at_100 |
|
value: 0.532 |
|
- type: precision_at_1000 |
|
value: 0.091 |
|
- type: precision_at_3 |
|
value: 6.346 |
|
- type: precision_at_5 |
|
value: 4.769 |
|
- type: recall_at_1 |
|
value: 12.027000000000001 |
|
- type: recall_at_10 |
|
value: 26.605 |
|
- type: recall_at_100 |
|
value: 45.163 |
|
- type: recall_at_1000 |
|
value: 72.307 |
|
- type: recall_at_3 |
|
value: 16.771 |
|
- type: recall_at_5 |
|
value: 20.998 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB ClimateFEVER |
|
config: default |
|
split: test |
|
revision: 47f2ac6acb640fc46020b02a5b59fdda04d39380 |
|
metrics: |
|
- type: map_at_1 |
|
value: 6.479 |
|
- type: map_at_10 |
|
value: 11.559 |
|
- type: map_at_100 |
|
value: 12.936 |
|
- type: map_at_1000 |
|
value: 13.120000000000001 |
|
- type: map_at_3 |
|
value: 9.377 |
|
- type: map_at_5 |
|
value: 10.494 |
|
- type: mrr_at_1 |
|
value: 14.396999999999998 |
|
- type: mrr_at_10 |
|
value: 23.039 |
|
- type: mrr_at_100 |
|
value: 24.141000000000002 |
|
- type: mrr_at_1000 |
|
value: 24.215999999999998 |
|
- type: mrr_at_3 |
|
value: 19.814999999999998 |
|
- type: mrr_at_5 |
|
value: 21.656 |
|
- type: ndcg_at_1 |
|
value: 14.396999999999998 |
|
- type: ndcg_at_10 |
|
value: 17.258000000000003 |
|
- type: ndcg_at_100 |
|
value: 23.615 |
|
- type: ndcg_at_1000 |
|
value: 27.605 |
|
- type: ndcg_at_3 |
|
value: 13.114999999999998 |
|
- type: ndcg_at_5 |
|
value: 14.698 |
|
- type: precision_at_1 |
|
value: 14.396999999999998 |
|
- type: precision_at_10 |
|
value: 5.713 |
|
- type: precision_at_100 |
|
value: 1.25 |
|
- type: precision_at_1000 |
|
value: 0.198 |
|
- type: precision_at_3 |
|
value: 9.924 |
|
- type: precision_at_5 |
|
value: 8.104 |
|
- type: recall_at_1 |
|
value: 6.479 |
|
- type: recall_at_10 |
|
value: 22.088 |
|
- type: recall_at_100 |
|
value: 44.681 |
|
- type: recall_at_1000 |
|
value: 67.869 |
|
- type: recall_at_3 |
|
value: 12.203 |
|
- type: recall_at_5 |
|
value: 16.275000000000002 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB DBPedia |
|
config: default |
|
split: test |
|
revision: c0f706b76e590d620bd6618b3ca8efdd34e2d659 |
|
metrics: |
|
- type: map_at_1 |
|
value: 4.618 |
|
- type: map_at_10 |
|
value: 10.217 |
|
- type: map_at_100 |
|
value: 14.038999999999998 |
|
- type: map_at_1000 |
|
value: 15.03 |
|
- type: map_at_3 |
|
value: 7.523000000000001 |
|
- type: map_at_5 |
|
value: 8.688 |
|
- type: mrr_at_1 |
|
value: 41.75 |
|
- type: mrr_at_10 |
|
value: 51.991 |
|
- type: mrr_at_100 |
|
value: 52.711 |
|
- type: mrr_at_1000 |
|
value: 52.746 |
|
- type: mrr_at_3 |
|
value: 49.5 |
|
- type: mrr_at_5 |
|
value: 50.961999999999996 |
|
- type: ndcg_at_1 |
|
value: 30.875000000000004 |
|
- type: ndcg_at_10 |
|
value: 24.709999999999997 |
|
- type: ndcg_at_100 |
|
value: 27.584999999999997 |
|
- type: ndcg_at_1000 |
|
value: 34.508 |
|
- type: ndcg_at_3 |
|
value: 27.88 |
|
- type: ndcg_at_5 |
|
value: 26.168999999999997 |
|
- type: precision_at_1 |
|
value: 41.75 |
|
- type: precision_at_10 |
|
value: 21.45 |
|
- type: precision_at_100 |
|
value: 6.795 |
|
- type: precision_at_1000 |
|
value: 1.43 |
|
- type: precision_at_3 |
|
value: 33.083 |
|
- type: precision_at_5 |
|
value: 27.750000000000004 |
|
- type: recall_at_1 |
|
value: 4.618 |
|
- type: recall_at_10 |
|
value: 14.898 |
|
- type: recall_at_100 |
|
value: 33.027 |
|
- type: recall_at_1000 |
|
value: 57.036 |
|
- type: recall_at_3 |
|
value: 8.995000000000001 |
|
- type: recall_at_5 |
|
value: 11.23 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: None |
|
name: MTEB EmotionClassification |
|
config: default |
|
split: test |
|
revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37 |
|
metrics: |
|
- type: accuracy |
|
value: 43.19499999999999 |
|
- type: f1 |
|
value: 40.60048839070268 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB FEVER |
|
config: default |
|
split: test |
|
revision: bea83ef9e8fb933d90a2f1d5515737465d613e12 |
|
metrics: |
|
- type: map_at_1 |
|
value: 17.11 |
|
- type: map_at_10 |
|
value: 25.478 |
|
- type: map_at_100 |
|
value: 26.436 |
|
- type: map_at_1000 |
|
value: 26.51 |
|
- type: map_at_3 |
|
value: 22.996 |
|
- type: map_at_5 |
|
value: 24.329 |
|
- type: mrr_at_1 |
|
value: 18.317 |
|
- type: mrr_at_10 |
|
value: 27.090999999999998 |
|
- type: mrr_at_100 |
|
value: 28.037 |
|
- type: mrr_at_1000 |
|
value: 28.102 |
|
- type: mrr_at_3 |
|
value: 24.532 |
|
- type: mrr_at_5 |
|
value: 25.918999999999997 |
|
- type: ndcg_at_1 |
|
value: 18.317 |
|
- type: ndcg_at_10 |
|
value: 30.448999999999998 |
|
- type: ndcg_at_100 |
|
value: 35.302 |
|
- type: ndcg_at_1000 |
|
value: 37.325 |
|
- type: ndcg_at_3 |
|
value: 25.326999999999998 |
|
- type: ndcg_at_5 |
|
value: 27.716 |
|
- type: precision_at_1 |
|
value: 18.317 |
|
- type: precision_at_10 |
|
value: 4.8469999999999995 |
|
- type: precision_at_100 |
|
value: 0.747 |
|
- type: precision_at_1000 |
|
value: 0.094 |
|
- type: precision_at_3 |
|
value: 10.975999999999999 |
|
- type: precision_at_5 |
|
value: 7.846 |
|
- type: recall_at_1 |
|
value: 17.11 |
|
- type: recall_at_10 |
|
value: 44.466 |
|
- type: recall_at_100 |
|
value: 67.06299999999999 |
|
- type: recall_at_1000 |
|
value: 82.64200000000001 |
|
- type: recall_at_3 |
|
value: 30.509999999999998 |
|
- type: recall_at_5 |
|
value: 36.27 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB FiQA2018 |
|
config: default |
|
split: test |
|
revision: 27a168819829fe9bcd655c2df245fb19452e8e06 |
|
metrics: |
|
- type: map_at_1 |
|
value: 7.446999999999999 |
|
- type: map_at_10 |
|
value: 12.188 |
|
- type: map_at_100 |
|
value: 13.241 |
|
- type: map_at_1000 |
|
value: 13.450000000000001 |
|
- type: map_at_3 |
|
value: 10.184999999999999 |
|
- type: map_at_5 |
|
value: 11.266 |
|
- type: mrr_at_1 |
|
value: 15.123000000000001 |
|
- type: mrr_at_10 |
|
value: 21.397 |
|
- type: mrr_at_100 |
|
value: 22.303 |
|
- type: mrr_at_1000 |
|
value: 22.398 |
|
- type: mrr_at_3 |
|
value: 19.187 |
|
- type: mrr_at_5 |
|
value: 20.383000000000003 |
|
- type: ndcg_at_1 |
|
value: 15.123000000000001 |
|
- type: ndcg_at_10 |
|
value: 16.957 |
|
- type: ndcg_at_100 |
|
value: 22.147 |
|
- type: ndcg_at_1000 |
|
value: 26.759 |
|
- type: ndcg_at_3 |
|
value: 14.091000000000001 |
|
- type: ndcg_at_5 |
|
value: 15.135000000000002 |
|
- type: precision_at_1 |
|
value: 15.123000000000001 |
|
- type: precision_at_10 |
|
value: 4.938 |
|
- type: precision_at_100 |
|
value: 1.019 |
|
- type: precision_at_1000 |
|
value: 0.18 |
|
- type: precision_at_3 |
|
value: 9.568 |
|
- type: precision_at_5 |
|
value: 7.438000000000001 |
|
- type: recall_at_1 |
|
value: 7.446999999999999 |
|
- type: recall_at_10 |
|
value: 22.094 |
|
- type: recall_at_100 |
|
value: 42.397 |
|
- type: recall_at_1000 |
|
value: 71.15700000000001 |
|
- type: recall_at_3 |
|
value: 12.879 |
|
- type: recall_at_5 |
|
value: 16.49 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB HotpotQA |
|
config: default |
|
split: test |
|
revision: ab518f4d6fcca38d87c25209f94beba119d02014 |
|
metrics: |
|
- type: map_at_1 |
|
value: 18.285 |
|
- type: map_at_10 |
|
value: 25.703 |
|
- type: map_at_100 |
|
value: 26.634 |
|
- type: map_at_1000 |
|
value: 26.741999999999997 |
|
- type: map_at_3 |
|
value: 23.642 |
|
- type: map_at_5 |
|
value: 24.826 |
|
- type: mrr_at_1 |
|
value: 36.57 |
|
- type: mrr_at_10 |
|
value: 43.772 |
|
- type: mrr_at_100 |
|
value: 44.51 |
|
- type: mrr_at_1000 |
|
value: 44.561 |
|
- type: mrr_at_3 |
|
value: 41.787 |
|
- type: mrr_at_5 |
|
value: 42.964 |
|
- type: ndcg_at_1 |
|
value: 36.57 |
|
- type: ndcg_at_10 |
|
value: 32.763999999999996 |
|
- type: ndcg_at_100 |
|
value: 37.077 |
|
- type: ndcg_at_1000 |
|
value: 39.666000000000004 |
|
- type: ndcg_at_3 |
|
value: 28.906 |
|
- type: ndcg_at_5 |
|
value: 30.86 |
|
- type: precision_at_1 |
|
value: 36.57 |
|
- type: precision_at_10 |
|
value: 7.202 |
|
- type: precision_at_100 |
|
value: 1.065 |
|
- type: precision_at_1000 |
|
value: 0.14100000000000001 |
|
- type: precision_at_3 |
|
value: 18.231 |
|
- type: precision_at_5 |
|
value: 12.483 |
|
- type: recall_at_1 |
|
value: 18.285 |
|
- type: recall_at_10 |
|
value: 36.009 |
|
- type: recall_at_100 |
|
value: 53.27499999999999 |
|
- type: recall_at_1000 |
|
value: 70.635 |
|
- type: recall_at_3 |
|
value: 27.345999999999997 |
|
- type: recall_at_5 |
|
value: 31.208999999999996 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: None |
|
name: MTEB ImdbClassification |
|
config: default |
|
split: test |
|
revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7 |
|
metrics: |
|
- type: accuracy |
|
value: 61.361999999999995 |
|
- type: ap |
|
value: 57.09674595597791 |
|
- type: f1 |
|
value: 60.94720401382382 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB MSMARCO |
|
config: default |
|
split: dev |
|
revision: c5a29a104738b98a9e76336939199e264163d4a0 |
|
metrics: |
|
- type: map_at_1 |
|
value: 6.686 |
|
- type: map_at_10 |
|
value: 11.454 |
|
- type: map_at_100 |
|
value: 12.342 |
|
- type: map_at_1000 |
|
value: 12.447 |
|
- type: map_at_3 |
|
value: 9.722 |
|
- type: map_at_5 |
|
value: 10.632 |
|
- type: mrr_at_1 |
|
value: 6.891 |
|
- type: mrr_at_10 |
|
value: 11.768 |
|
- type: mrr_at_100 |
|
value: 12.651000000000002 |
|
- type: mrr_at_1000 |
|
value: 12.753 |
|
- type: mrr_at_3 |
|
value: 10.001999999999999 |
|
- type: mrr_at_5 |
|
value: 10.918999999999999 |
|
- type: ndcg_at_1 |
|
value: 6.848 |
|
- type: ndcg_at_10 |
|
value: 14.466000000000001 |
|
- type: ndcg_at_100 |
|
value: 19.301 |
|
- type: ndcg_at_1000 |
|
value: 22.458 |
|
- type: ndcg_at_3 |
|
value: 10.836 |
|
- type: ndcg_at_5 |
|
value: 12.475 |
|
- type: precision_at_1 |
|
value: 6.848 |
|
- type: precision_at_10 |
|
value: 2.48 |
|
- type: precision_at_100 |
|
value: 0.49899999999999994 |
|
- type: precision_at_1000 |
|
value: 0.077 |
|
- type: precision_at_3 |
|
value: 4.766 |
|
- type: precision_at_5 |
|
value: 3.682 |
|
- type: recall_at_1 |
|
value: 6.686 |
|
- type: recall_at_10 |
|
value: 23.82 |
|
- type: recall_at_100 |
|
value: 47.349999999999994 |
|
- type: recall_at_1000 |
|
value: 72.66 |
|
- type: recall_at_3 |
|
value: 13.811000000000002 |
|
- type: recall_at_5 |
|
value: 17.76 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: None |
|
name: MTEB MTOPDomainClassification (en) |
|
config: en |
|
split: test |
|
revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf |
|
metrics: |
|
- type: accuracy |
|
value: 87.67213862289103 |
|
- type: f1 |
|
value: 86.45841301738238 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: None |
|
name: MTEB MTOPIntentClassification (en) |
|
config: en |
|
split: test |
|
revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba |
|
metrics: |
|
- type: accuracy |
|
value: 56.82170542635659 |
|
- type: f1 |
|
value: 39.12615117855274 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: None |
|
name: MTEB MassiveIntentClassification (en) |
|
config: en |
|
split: test |
|
revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 |
|
metrics: |
|
- type: accuracy |
|
value: 60.18829858776058 |
|
- type: f1 |
|
value: 58.617914607265064 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: None |
|
name: MTEB MassiveScenarioClassification (en) |
|
config: en |
|
split: test |
|
revision: 7d571f92784cd94a019292a1f45445077d0ef634 |
|
metrics: |
|
- type: accuracy |
|
value: 66.45595158036315 |
|
- type: f1 |
|
value: 64.9778374481982 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: None |
|
name: MTEB MedrxivClusteringP2P |
|
config: default |
|
split: test |
|
revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73 |
|
metrics: |
|
- type: v_measure |
|
value: 29.531989286141012 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: None |
|
name: MTEB MedrxivClusteringS2S |
|
config: default |
|
split: test |
|
revision: 35191c8c0dca72d8ff3efcd72aa802307d469663 |
|
metrics: |
|
- type: v_measure |
|
value: 26.070324322784792 |
|
- task: |
|
type: Reranking |
|
dataset: |
|
type: None |
|
name: MTEB MindSmallReranking |
|
config: default |
|
split: test |
|
revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69 |
|
metrics: |
|
- type: map |
|
value: 29.516858081965257 |
|
- type: mrr |
|
value: 30.51047930520146 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB NFCorpus |
|
config: default |
|
split: test |
|
revision: ec0fa4fe99da2ff19ca1214b7966684033a58814 |
|
metrics: |
|
- type: map_at_1 |
|
value: 4.131 |
|
- type: map_at_10 |
|
value: 8.826 |
|
- type: map_at_100 |
|
value: 11.094999999999999 |
|
- type: map_at_1000 |
|
value: 12.484 |
|
- type: map_at_3 |
|
value: 6.723 |
|
- type: map_at_5 |
|
value: 7.683 |
|
- type: mrr_at_1 |
|
value: 34.985 |
|
- type: mrr_at_10 |
|
value: 44.921 |
|
- type: mrr_at_100 |
|
value: 45.62 |
|
- type: mrr_at_1000 |
|
value: 45.676 |
|
- type: mrr_at_3 |
|
value: 42.931000000000004 |
|
- type: mrr_at_5 |
|
value: 44.385999999999996 |
|
- type: ndcg_at_1 |
|
value: 32.507999999999996 |
|
- type: ndcg_at_10 |
|
value: 26.773000000000003 |
|
- type: ndcg_at_100 |
|
value: 24.751 |
|
- type: ndcg_at_1000 |
|
value: 34.19 |
|
- type: ndcg_at_3 |
|
value: 31.213 |
|
- type: ndcg_at_5 |
|
value: 29.249000000000002 |
|
- type: precision_at_1 |
|
value: 34.985 |
|
- type: precision_at_10 |
|
value: 20.247999999999998 |
|
- type: precision_at_100 |
|
value: 6.907000000000001 |
|
- type: precision_at_1000 |
|
value: 2.031 |
|
- type: precision_at_3 |
|
value: 30.341 |
|
- type: precision_at_5 |
|
value: 25.759 |
|
- type: recall_at_1 |
|
value: 4.131 |
|
- type: recall_at_10 |
|
value: 12.465 |
|
- type: recall_at_100 |
|
value: 25.776 |
|
- type: recall_at_1000 |
|
value: 59.876 |
|
- type: recall_at_3 |
|
value: 7.968 |
|
- type: recall_at_5 |
|
value: 9.968 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB NQ |
|
config: default |
|
split: test |
|
revision: b774495ed302d8c44a3a7ea25c90dbce03968f31 |
|
metrics: |
|
- type: map_at_1 |
|
value: 9.277000000000001 |
|
- type: map_at_10 |
|
value: 15.709999999999999 |
|
- type: map_at_100 |
|
value: 16.980999999999998 |
|
- type: map_at_1000 |
|
value: 17.074 |
|
- type: map_at_3 |
|
value: 13.157 |
|
- type: map_at_5 |
|
value: 14.571000000000002 |
|
- type: mrr_at_1 |
|
value: 10.574 |
|
- type: mrr_at_10 |
|
value: 17.344 |
|
- type: mrr_at_100 |
|
value: 18.506 |
|
- type: mrr_at_1000 |
|
value: 18.584999999999997 |
|
- type: mrr_at_3 |
|
value: 14.677000000000001 |
|
- type: mrr_at_5 |
|
value: 16.213 |
|
- type: ndcg_at_1 |
|
value: 10.574 |
|
- type: ndcg_at_10 |
|
value: 20.044 |
|
- type: ndcg_at_100 |
|
value: 26.447 |
|
- type: ndcg_at_1000 |
|
value: 29.084 |
|
- type: ndcg_at_3 |
|
value: 14.787 |
|
- type: ndcg_at_5 |
|
value: 17.362 |
|
- type: precision_at_1 |
|
value: 10.574 |
|
- type: precision_at_10 |
|
value: 3.7600000000000002 |
|
- type: precision_at_100 |
|
value: 0.738 |
|
- type: precision_at_1000 |
|
value: 0.099 |
|
- type: precision_at_3 |
|
value: 6.933 |
|
- type: precision_at_5 |
|
value: 5.608 |
|
- type: recall_at_1 |
|
value: 9.277000000000001 |
|
- type: recall_at_10 |
|
value: 31.948 |
|
- type: recall_at_100 |
|
value: 61.708 |
|
- type: recall_at_1000 |
|
value: 82.07799999999999 |
|
- type: recall_at_3 |
|
value: 18.045 |
|
- type: recall_at_5 |
|
value: 24.038999999999998 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB QuoraRetrieval |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 64.268 |
|
- type: map_at_10 |
|
value: 77.19500000000001 |
|
- type: map_at_100 |
|
value: 77.95299999999999 |
|
- type: map_at_1000 |
|
value: 77.986 |
|
- type: map_at_3 |
|
value: 74.30499999999999 |
|
- type: map_at_5 |
|
value: 76.054 |
|
- type: mrr_at_1 |
|
value: 74.09 |
|
- type: mrr_at_10 |
|
value: 81.384 |
|
- type: mrr_at_100 |
|
value: 81.592 |
|
- type: mrr_at_1000 |
|
value: 81.597 |
|
- type: mrr_at_3 |
|
value: 80.00500000000001 |
|
- type: mrr_at_5 |
|
value: 80.876 |
|
- type: ndcg_at_1 |
|
value: 74.16 |
|
- type: ndcg_at_10 |
|
value: 81.813 |
|
- type: ndcg_at_100 |
|
value: 83.787 |
|
- type: ndcg_at_1000 |
|
value: 84.11800000000001 |
|
- type: ndcg_at_3 |
|
value: 78.389 |
|
- type: ndcg_at_5 |
|
value: 80.123 |
|
- type: precision_at_1 |
|
value: 74.16 |
|
- type: precision_at_10 |
|
value: 12.35 |
|
- type: precision_at_100 |
|
value: 1.466 |
|
- type: precision_at_1000 |
|
value: 0.155 |
|
- type: precision_at_3 |
|
value: 34.067 |
|
- type: precision_at_5 |
|
value: 22.442 |
|
- type: recall_at_1 |
|
value: 64.268 |
|
- type: recall_at_10 |
|
value: 90.67 |
|
- type: recall_at_100 |
|
value: 97.935 |
|
- type: recall_at_1000 |
|
value: 99.703 |
|
- type: recall_at_3 |
|
value: 80.752 |
|
- type: recall_at_5 |
|
value: 85.63300000000001 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: None |
|
name: MTEB RedditClustering |
|
config: default |
|
split: test |
|
revision: 24640382cdbf8abc73003fb0fa6d111a705499eb |
|
metrics: |
|
- type: v_measure |
|
value: 39.191626251430044 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: None |
|
name: MTEB RedditClusteringP2P |
|
config: default |
|
split: test |
|
revision: 282350215ef01743dc01b456c7f5241fa8937f16 |
|
metrics: |
|
- type: v_measure |
|
value: 47.00784930616429 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB SCIDOCS |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 2.948 |
|
- type: map_at_10 |
|
value: 7.126 |
|
- type: map_at_100 |
|
value: 8.462 |
|
- type: map_at_1000 |
|
value: 8.713 |
|
- type: map_at_3 |
|
value: 5.143 |
|
- type: map_at_5 |
|
value: 6.117 |
|
- type: mrr_at_1 |
|
value: 14.499999999999998 |
|
- type: mrr_at_10 |
|
value: 22.455 |
|
- type: mrr_at_100 |
|
value: 23.666 |
|
- type: mrr_at_1000 |
|
value: 23.745 |
|
- type: mrr_at_3 |
|
value: 19.417 |
|
- type: mrr_at_5 |
|
value: 21.117 |
|
- type: ndcg_at_1 |
|
value: 14.499999999999998 |
|
- type: ndcg_at_10 |
|
value: 12.666 |
|
- type: ndcg_at_100 |
|
value: 18.993 |
|
- type: ndcg_at_1000 |
|
value: 24.09 |
|
- type: ndcg_at_3 |
|
value: 11.655999999999999 |
|
- type: ndcg_at_5 |
|
value: 10.342 |
|
- type: precision_at_1 |
|
value: 14.499999999999998 |
|
- type: precision_at_10 |
|
value: 6.65 |
|
- type: precision_at_100 |
|
value: 1.598 |
|
- type: precision_at_1000 |
|
value: 0.28300000000000003 |
|
- type: precision_at_3 |
|
value: 10.8 |
|
- type: precision_at_5 |
|
value: 9.1 |
|
- type: recall_at_1 |
|
value: 2.948 |
|
- type: recall_at_10 |
|
value: 13.492 |
|
- type: recall_at_100 |
|
value: 32.448 |
|
- type: recall_at_1000 |
|
value: 57.553 |
|
- type: recall_at_3 |
|
value: 6.578 |
|
- type: recall_at_5 |
|
value: 9.242 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: None |
|
name: MTEB SICK-R |
|
config: default |
|
split: test |
|
revision: a6ea5a8cab320b040a23452cc28066d9beae2cee |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 75.38146213095916 |
|
- type: cos_sim_spearman |
|
value: 65.36914729991646 |
|
- type: euclidean_pearson |
|
value: 70.34893420889419 |
|
- type: euclidean_spearman |
|
value: 65.36925972117625 |
|
- type: manhattan_pearson |
|
value: 68.16816720045782 |
|
- type: manhattan_spearman |
|
value: 64.0884396246228 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: None |
|
name: MTEB STS12 |
|
config: default |
|
split: test |
|
revision: a0d554a64d88156834ff5ae9920b964011b16384 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 74.45813185900207 |
|
- type: cos_sim_spearman |
|
value: 68.03206487736479 |
|
- type: euclidean_pearson |
|
value: 70.55331228911669 |
|
- type: euclidean_spearman |
|
value: 68.03330456319067 |
|
- type: manhattan_pearson |
|
value: 68.32513309931606 |
|
- type: manhattan_spearman |
|
value: 66.90519361570585 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: None |
|
name: MTEB STS13 |
|
config: default |
|
split: test |
|
revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 77.32203252223916 |
|
- type: cos_sim_spearman |
|
value: 78.44952447167366 |
|
- type: euclidean_pearson |
|
value: 78.18870184193474 |
|
- type: euclidean_spearman |
|
value: 78.44956228059971 |
|
- type: manhattan_pearson |
|
value: 77.82417744157945 |
|
- type: manhattan_spearman |
|
value: 78.17317129725184 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: None |
|
name: MTEB STS14 |
|
config: default |
|
split: test |
|
revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 77.98515479114604 |
|
- type: cos_sim_spearman |
|
value: 74.70914230860409 |
|
- type: euclidean_pearson |
|
value: 76.81874418213698 |
|
- type: euclidean_spearman |
|
value: 74.70913261737951 |
|
- type: manhattan_pearson |
|
value: 75.54410520012546 |
|
- type: manhattan_spearman |
|
value: 73.74596322038998 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: None |
|
name: MTEB STS15 |
|
config: default |
|
split: test |
|
revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 81.34912352314105 |
|
- type: cos_sim_spearman |
|
value: 82.13479378308254 |
|
- type: euclidean_pearson |
|
value: 82.07291865315551 |
|
- type: euclidean_spearman |
|
value: 82.13479226815167 |
|
- type: manhattan_pearson |
|
value: 81.51909627091456 |
|
- type: manhattan_spearman |
|
value: 81.70075499671213 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: None |
|
name: MTEB STS16 |
|
config: default |
|
split: test |
|
revision: 4d8694f8f0e0100860b497b999b3dbed754a0513 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 76.1116492955691 |
|
- type: cos_sim_spearman |
|
value: 77.19800116078945 |
|
- type: euclidean_pearson |
|
value: 76.8231316467101 |
|
- type: euclidean_spearman |
|
value: 77.19883015620502 |
|
- type: manhattan_pearson |
|
value: 77.10588536013977 |
|
- type: manhattan_spearman |
|
value: 77.50215416532438 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: None |
|
name: MTEB STS17 (en-en) |
|
config: en-en |
|
split: test |
|
revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 84.10770264372314 |
|
- type: cos_sim_spearman |
|
value: 84.97403648808209 |
|
- type: euclidean_pearson |
|
value: 84.41825024902698 |
|
- type: euclidean_spearman |
|
value: 84.97491009412074 |
|
- type: manhattan_pearson |
|
value: 84.16827578787243 |
|
- type: manhattan_spearman |
|
value: 84.92739867128569 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: None |
|
name: MTEB STS22 (en) |
|
config: en |
|
split: test |
|
revision: eea2b4fe26a775864c896887d910b76a8098ad3f |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 62.91807215204278 |
|
- type: cos_sim_spearman |
|
value: 59.61282196137074 |
|
- type: euclidean_pearson |
|
value: 62.702286829442436 |
|
- type: euclidean_spearman |
|
value: 59.61282196137074 |
|
- type: manhattan_pearson |
|
value: 62.26491120673072 |
|
- type: manhattan_spearman |
|
value: 59.7161013914999 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: None |
|
name: MTEB STSBenchmark |
|
config: default |
|
split: test |
|
revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 78.43114398442724 |
|
- type: cos_sim_spearman |
|
value: 77.35423527756463 |
|
- type: euclidean_pearson |
|
value: 78.2269102978861 |
|
- type: euclidean_spearman |
|
value: 77.35428366374488 |
|
- type: manhattan_pearson |
|
value: 77.26973789544932 |
|
- type: manhattan_spearman |
|
value: 76.58307796792111 |
|
- task: |
|
type: Reranking |
|
dataset: |
|
type: None |
|
name: MTEB SciDocsRR |
|
config: default |
|
split: test |
|
revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab |
|
metrics: |
|
- type: map |
|
value: 72.61932743075317 |
|
- type: mrr |
|
value: 91.38920810489437 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB SciFact |
|
config: default |
|
split: test |
|
revision: 0228b52cf27578f30900b9e5271d331663a030d7 |
|
metrics: |
|
- type: map_at_1 |
|
value: 36.861 |
|
- type: map_at_10 |
|
value: 45.93 |
|
- type: map_at_100 |
|
value: 46.861000000000004 |
|
- type: map_at_1000 |
|
value: 46.924 |
|
- type: map_at_3 |
|
value: 43.283 |
|
- type: map_at_5 |
|
value: 44.675 |
|
- type: mrr_at_1 |
|
value: 39.333 |
|
- type: mrr_at_10 |
|
value: 47.906 |
|
- type: mrr_at_100 |
|
value: 48.665000000000006 |
|
- type: mrr_at_1000 |
|
value: 48.722 |
|
- type: mrr_at_3 |
|
value: 45.611000000000004 |
|
- type: mrr_at_5 |
|
value: 46.778 |
|
- type: ndcg_at_1 |
|
value: 39.333 |
|
- type: ndcg_at_10 |
|
value: 50.970000000000006 |
|
- type: ndcg_at_100 |
|
value: 55.491 |
|
- type: ndcg_at_1000 |
|
value: 57.099 |
|
- type: ndcg_at_3 |
|
value: 45.837 |
|
- type: ndcg_at_5 |
|
value: 48.081 |
|
- type: precision_at_1 |
|
value: 39.333 |
|
- type: precision_at_10 |
|
value: 7.199999999999999 |
|
- type: precision_at_100 |
|
value: 0.9730000000000001 |
|
- type: precision_at_1000 |
|
value: 0.11100000000000002 |
|
- type: precision_at_3 |
|
value: 18.333 |
|
- type: precision_at_5 |
|
value: 12.4 |
|
- type: recall_at_1 |
|
value: 36.861 |
|
- type: recall_at_10 |
|
value: 64.839 |
|
- type: recall_at_100 |
|
value: 85.983 |
|
- type: recall_at_1000 |
|
value: 98.467 |
|
- type: recall_at_3 |
|
value: 50.678 |
|
- type: recall_at_5 |
|
value: 56.24400000000001 |
|
- task: |
|
type: PairClassification |
|
dataset: |
|
type: None |
|
name: MTEB SprintDuplicateQuestions |
|
config: default |
|
split: test |
|
revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46 |
|
metrics: |
|
- type: cos_sim_accuracy |
|
value: 99.75742574257426 |
|
- type: cos_sim_ap |
|
value: 93.4938177052363 |
|
- type: cos_sim_f1 |
|
value: 87.45019920318725 |
|
- type: cos_sim_precision |
|
value: 87.10317460317461 |
|
- type: cos_sim_recall |
|
value: 87.8 |
|
- type: dot_accuracy |
|
value: 99.75742574257426 |
|
- type: dot_ap |
|
value: 93.4938177052363 |
|
- type: dot_f1 |
|
value: 87.45019920318725 |
|
- type: dot_precision |
|
value: 87.10317460317461 |
|
- type: dot_recall |
|
value: 87.8 |
|
- type: euclidean_accuracy |
|
value: 99.75742574257426 |
|
- type: euclidean_ap |
|
value: 93.4938177052363 |
|
- type: euclidean_f1 |
|
value: 87.45019920318725 |
|
- type: euclidean_precision |
|
value: 87.10317460317461 |
|
- type: euclidean_recall |
|
value: 87.8 |
|
- type: manhattan_accuracy |
|
value: 99.77425742574258 |
|
- type: manhattan_ap |
|
value: 94.11582049960462 |
|
- type: manhattan_f1 |
|
value: 88.3367139959432 |
|
- type: manhattan_precision |
|
value: 89.60905349794238 |
|
- type: manhattan_recall |
|
value: 87.1 |
|
- type: max_accuracy |
|
value: 99.77425742574258 |
|
- type: max_ap |
|
value: 94.11582049960462 |
|
- type: max_f1 |
|
value: 88.3367139959432 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: None |
|
name: MTEB StackExchangeClustering |
|
config: default |
|
split: test |
|
revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259 |
|
metrics: |
|
- type: v_measure |
|
value: 40.69098529569445 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: None |
|
name: MTEB StackExchangeClusteringP2P |
|
config: default |
|
split: test |
|
revision: 815ca46b2622cec33ccafc3735d572c266efdb44 |
|
metrics: |
|
- type: v_measure |
|
value: 29.68544212745689 |
|
- task: |
|
type: Reranking |
|
dataset: |
|
type: None |
|
name: MTEB StackOverflowDupQuestions |
|
config: default |
|
split: test |
|
revision: e185fbe320c72810689fc5848eb6114e1ef5ec69 |
|
metrics: |
|
- type: map |
|
value: 43.065922067847836 |
|
- type: mrr |
|
value: 43.64432136490961 |
|
- task: |
|
type: Summarization |
|
dataset: |
|
type: None |
|
name: MTEB SummEval |
|
config: default |
|
split: test |
|
revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 29.750957237960492 |
|
- type: cos_sim_spearman |
|
value: 30.099771071145582 |
|
- type: dot_pearson |
|
value: 29.75095720371408 |
|
- type: dot_spearman |
|
value: 30.128683537072114 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB TRECCOVID |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 0.129 |
|
- type: map_at_10 |
|
value: 0.6890000000000001 |
|
- type: map_at_100 |
|
value: 3.511 |
|
- type: map_at_1000 |
|
value: 8.943 |
|
- type: map_at_3 |
|
value: 0.304 |
|
- type: map_at_5 |
|
value: 0.42700000000000005 |
|
- type: mrr_at_1 |
|
value: 56.00000000000001 |
|
- type: mrr_at_10 |
|
value: 65.908 |
|
- type: mrr_at_100 |
|
value: 66.60199999999999 |
|
- type: mrr_at_1000 |
|
value: 66.60199999999999 |
|
- type: mrr_at_3 |
|
value: 63.333 |
|
- type: mrr_at_5 |
|
value: 64.23299999999999 |
|
- type: ndcg_at_1 |
|
value: 51.0 |
|
- type: ndcg_at_10 |
|
value: 39.304 |
|
- type: ndcg_at_100 |
|
value: 29.392000000000003 |
|
- type: ndcg_at_1000 |
|
value: 26.044 |
|
- type: ndcg_at_3 |
|
value: 45.408 |
|
- type: ndcg_at_5 |
|
value: 41.997 |
|
- type: precision_at_1 |
|
value: 56.00000000000001 |
|
- type: precision_at_10 |
|
value: 40.8 |
|
- type: precision_at_100 |
|
value: 30.48 |
|
- type: precision_at_1000 |
|
value: 12.692 |
|
- type: precision_at_3 |
|
value: 48.0 |
|
- type: precision_at_5 |
|
value: 43.6 |
|
- type: recall_at_1 |
|
value: 0.129 |
|
- type: recall_at_10 |
|
value: 0.893 |
|
- type: recall_at_100 |
|
value: 6.324000000000001 |
|
- type: recall_at_1000 |
|
value: 24.964 |
|
- type: recall_at_3 |
|
value: 0.33999999999999997 |
|
- type: recall_at_5 |
|
value: 0.505 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB Touche2020 |
|
config: default |
|
split: test |
|
revision: a34f9a33db75fa0cbb21bb5cfc3dae8dc8bec93f |
|
metrics: |
|
- type: map_at_1 |
|
value: 1.6179999999999999 |
|
- type: map_at_10 |
|
value: 8.232000000000001 |
|
- type: map_at_100 |
|
value: 14.643999999999998 |
|
- type: map_at_1000 |
|
value: 16.259 |
|
- type: map_at_3 |
|
value: 4.2090000000000005 |
|
- type: map_at_5 |
|
value: 5.401 |
|
- type: mrr_at_1 |
|
value: 24.490000000000002 |
|
- type: mrr_at_10 |
|
value: 43.963 |
|
- type: mrr_at_100 |
|
value: 45.022 |
|
- type: mrr_at_1000 |
|
value: 45.039 |
|
- type: mrr_at_3 |
|
value: 42.177 |
|
- type: mrr_at_5 |
|
value: 42.687000000000005 |
|
- type: ndcg_at_1 |
|
value: 23.469 |
|
- type: ndcg_at_10 |
|
value: 22.526 |
|
- type: ndcg_at_100 |
|
value: 36.411 |
|
- type: ndcg_at_1000 |
|
value: 47.461 |
|
- type: ndcg_at_3 |
|
value: 27.176000000000002 |
|
- type: ndcg_at_5 |
|
value: 23.787 |
|
- type: precision_at_1 |
|
value: 24.490000000000002 |
|
- type: precision_at_10 |
|
value: 20.0 |
|
- type: precision_at_100 |
|
value: 8.286 |
|
- type: precision_at_1000 |
|
value: 1.543 |
|
- type: precision_at_3 |
|
value: 29.252 |
|
- type: precision_at_5 |
|
value: 23.265 |
|
- type: recall_at_1 |
|
value: 1.6179999999999999 |
|
- type: recall_at_10 |
|
value: 14.443 |
|
- type: recall_at_100 |
|
value: 50.073 |
|
- type: recall_at_1000 |
|
value: 83.56700000000001 |
|
- type: recall_at_3 |
|
value: 5.831 |
|
- type: recall_at_5 |
|
value: 7.797 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: None |
|
name: MTEB ToxicConversationsClassification |
|
config: default |
|
split: test |
|
revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c |
|
metrics: |
|
- type: accuracy |
|
value: 69.5932 |
|
- type: ap |
|
value: 13.748287764670659 |
|
- type: f1 |
|
value: 53.6121537777008 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: None |
|
name: MTEB TweetSentimentExtractionClassification |
|
config: default |
|
split: test |
|
revision: d604517c81ca91fe16a244d1248fc021f9ecee7a |
|
metrics: |
|
- type: accuracy |
|
value: 48.60498019241653 |
|
- type: f1 |
|
value: 48.8190614849162 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: None |
|
name: MTEB TwentyNewsgroupsClustering |
|
config: default |
|
split: test |
|
revision: 6125ec4e24fa026cec8a478383ee943acfbd5449 |
|
metrics: |
|
- type: v_measure |
|
value: 37.40279692338929 |
|
- task: |
|
type: PairClassification |
|
dataset: |
|
type: None |
|
name: MTEB TwitterSemEval2015 |
|
config: default |
|
split: test |
|
revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1 |
|
metrics: |
|
- type: cos_sim_accuracy |
|
value: 83.11378673183525 |
|
- type: cos_sim_ap |
|
value: 63.412004464549696 |
|
- type: cos_sim_f1 |
|
value: 60.880921286952386 |
|
- type: cos_sim_precision |
|
value: 55.34211094323332 |
|
- type: cos_sim_recall |
|
value: 67.65171503957784 |
|
- type: dot_accuracy |
|
value: 83.11378673183525 |
|
- type: dot_ap |
|
value: 63.412004464549696 |
|
- type: dot_f1 |
|
value: 60.880921286952386 |
|
- type: dot_precision |
|
value: 55.34211094323332 |
|
- type: dot_recall |
|
value: 67.65171503957784 |
|
- type: euclidean_accuracy |
|
value: 83.11378673183525 |
|
- type: euclidean_ap |
|
value: 63.412004464549696 |
|
- type: euclidean_f1 |
|
value: 60.880921286952386 |
|
- type: euclidean_precision |
|
value: 55.34211094323332 |
|
- type: euclidean_recall |
|
value: 67.65171503957784 |
|
- type: manhattan_accuracy |
|
value: 82.13625797222389 |
|
- type: manhattan_ap |
|
value: 60.704142220415335 |
|
- type: manhattan_f1 |
|
value: 58.10686319668357 |
|
- type: manhattan_precision |
|
value: 51.55292194523907 |
|
- type: manhattan_recall |
|
value: 66.56992084432719 |
|
- type: max_accuracy |
|
value: 83.11378673183525 |
|
- type: max_ap |
|
value: 63.412004464549696 |
|
- type: max_f1 |
|
value: 60.880921286952386 |
|
- task: |
|
type: PairClassification |
|
dataset: |
|
type: None |
|
name: MTEB TwitterURLCorpus |
|
config: default |
|
split: test |
|
revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf |
|
metrics: |
|
- type: cos_sim_accuracy |
|
value: 87.48593161796096 |
|
- type: cos_sim_ap |
|
value: 83.09276630048417 |
|
- type: cos_sim_f1 |
|
value: 75.22376690154258 |
|
- type: cos_sim_precision |
|
value: 74.4328031958996 |
|
- type: cos_sim_recall |
|
value: 76.03172158915923 |
|
- type: dot_accuracy |
|
value: 87.48593161796096 |
|
- type: dot_ap |
|
value: 83.09276630048417 |
|
- type: dot_f1 |
|
value: 75.22376690154258 |
|
- type: dot_precision |
|
value: 74.4328031958996 |
|
- type: dot_recall |
|
value: 76.03172158915923 |
|
- type: euclidean_accuracy |
|
value: 87.48593161796096 |
|
- type: euclidean_ap |
|
value: 83.09276683624702 |
|
- type: euclidean_f1 |
|
value: 75.22376690154258 |
|
- type: euclidean_precision |
|
value: 74.4328031958996 |
|
- type: euclidean_recall |
|
value: 76.03172158915923 |
|
- type: manhattan_accuracy |
|
value: 87.49369348391353 |
|
- type: manhattan_ap |
|
value: 82.94869347657408 |
|
- type: manhattan_f1 |
|
value: 74.95875695376942 |
|
- type: manhattan_precision |
|
value: 74.70367821365757 |
|
- type: manhattan_recall |
|
value: 75.21558361564522 |
|
- type: max_accuracy |
|
value: 87.49369348391353 |
|
- type: max_ap |
|
value: 83.09276683624702 |
|
- type: max_f1 |
|
value: 75.22376690154258 |
|
--- |
