|
--- |
|
tags: |
|
- mteb |
|
model-index: |
|
- name: mpnet_main_nobivec |
|
results: |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: None |
|
name: MTEB AmazonCounterfactualClassification (en) |
|
config: en |
|
split: test |
|
revision: e8379541af4e31359cca9fbcf4b00f2671dba205 |
|
metrics: |
|
- type: accuracy |
|
value: 68.14925373134328 |
|
- type: ap |
|
value: 30.344492603232688 |
|
- type: f1 |
|
value: 61.86365588668259 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: None |
|
name: MTEB AmazonPolarityClassification |
|
config: default |
|
split: test |
|
revision: e2d317d38cd51312af73b3d32a06d1a08b442046 |
|
metrics: |
|
- type: accuracy |
|
value: 62.152125000000005 |
|
- type: ap |
|
value: 57.843425428341554 |
|
- type: f1 |
|
value: 62.00827686700807 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: None |
|
name: MTEB AmazonReviewsClassification (en) |
|
config: en |
|
split: test |
|
revision: 1399c76144fd37290681b995c656ef9b2e06e26d |
|
metrics: |
|
- type: accuracy |
|
value: 31.278 |
|
- type: f1 |
|
value: 30.933717306850117 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB ArguAna |
|
config: default |
|
split: test |
|
revision: c22ab2a51041ffd869aaddef7af8d8215647e41a |
|
metrics: |
|
- type: map_at_1 |
|
value: 23.186 |
|
- type: map_at_10 |
|
value: 37.467 |
|
- type: map_at_100 |
|
value: 38.544 |
|
- type: map_at_1000 |
|
value: 38.566 |
|
- type: map_at_3 |
|
value: 32.717 |
|
- type: map_at_5 |
|
value: 35.242000000000004 |
|
- type: mrr_at_1 |
|
value: 23.684 |
|
- type: mrr_at_10 |
|
value: 37.658 |
|
- type: mrr_at_100 |
|
value: 38.735 |
|
- type: mrr_at_1000 |
|
value: 38.756 |
|
- type: mrr_at_3 |
|
value: 32.93 |
|
- type: mrr_at_5 |
|
value: 35.445 |
|
- type: ndcg_at_1 |
|
value: 23.186 |
|
- type: ndcg_at_10 |
|
value: 45.857 |
|
- type: ndcg_at_100 |
|
value: 50.845 |
|
- type: ndcg_at_1000 |
|
value: 51.334999999999994 |
|
- type: ndcg_at_3 |
|
value: 35.992000000000004 |
|
- type: ndcg_at_5 |
|
value: 40.537 |
|
- type: precision_at_1 |
|
value: 23.186 |
|
- type: precision_at_10 |
|
value: 7.283 |
|
- type: precision_at_100 |
|
value: 0.9560000000000001 |
|
- type: precision_at_1000 |
|
value: 0.099 |
|
- type: precision_at_3 |
|
value: 15.173 |
|
- type: precision_at_5 |
|
value: 11.309 |
|
- type: recall_at_1 |
|
value: 23.186 |
|
- type: recall_at_10 |
|
value: 72.831 |
|
- type: recall_at_100 |
|
value: 95.59 |
|
- type: recall_at_1000 |
|
value: 99.289 |
|
- type: recall_at_3 |
|
value: 45.519 |
|
- type: recall_at_5 |
|
value: 56.543 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: None |
|
name: MTEB ArxivClusteringP2P |
|
config: default |
|
split: test |
|
revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d |
|
metrics: |
|
- type: v_measure |
|
value: 36.49112092394214 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: None |
|
name: MTEB ArxivClusteringS2S |
|
config: default |
|
split: test |
|
revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53 |
|
metrics: |
|
- type: v_measure |
|
value: 26.956300550326922 |
|
- task: |
|
type: Reranking |
|
dataset: |
|
type: None |
|
name: MTEB AskUbuntuDupQuestions |
|
config: default |
|
split: test |
|
revision: 2000358ca161889fa9c082cb41daa8dcfb161a54 |
|
metrics: |
|
- type: map |
|
value: 55.21453957338802 |
|
- type: mrr |
|
value: 69.1818361693708 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: None |
|
name: MTEB BIOSSES |
|
config: default |
|
split: test |
|
revision: d3fb88f8f02e40887cd149695127462bbcf29b4a |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 81.00547088743242 |
|
- type: cos_sim_spearman |
|
value: 79.13493567331314 |
|
- type: euclidean_pearson |
|
value: 79.63047595528823 |
|
- type: euclidean_spearman |
|
value: 79.13493567331314 |
|
- type: manhattan_pearson |
|
value: 79.46578839548812 |
|
- type: manhattan_spearman |
|
value: 78.86926696926908 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: None |
|
name: MTEB Banking77Classification |
|
config: default |
|
split: test |
|
revision: 0fd18e25b25c072e09e0d92ab615fda904d66300 |
|
metrics: |
|
- type: accuracy |
|
value: 72.79220779220779 |
|
- type: f1 |
|
value: 72.00183161777994 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: None |
|
name: MTEB BiorxivClusteringP2P |
|
config: default |
|
split: test |
|
revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40 |
|
metrics: |
|
- type: v_measure |
|
value: 33.91469425290078 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: None |
|
name: MTEB BiorxivClusteringS2S |
|
config: default |
|
split: test |
|
revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908 |
|
metrics: |
|
- type: v_measure |
|
value: 25.33265342571266 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB CQADupstackAndroidRetrieval |
|
config: default |
|
split: test |
|
revision: f46a197baaae43b4f621051089b82a364682dfeb |
|
metrics: |
|
- type: map_at_1 |
|
value: 20.383000000000003 |
|
- type: map_at_10 |
|
value: 26.997 |
|
- type: map_at_100 |
|
value: 28.29 |
|
- type: map_at_1000 |
|
value: 28.444000000000003 |
|
- type: map_at_3 |
|
value: 24.765 |
|
- type: map_at_5 |
|
value: 26.072 |
|
- type: mrr_at_1 |
|
value: 25.894000000000002 |
|
- type: mrr_at_10 |
|
value: 32.336 |
|
- type: mrr_at_100 |
|
value: 33.291 |
|
- type: mrr_at_1000 |
|
value: 33.36 |
|
- type: mrr_at_3 |
|
value: 30.353 |
|
- type: mrr_at_5 |
|
value: 31.526 |
|
- type: ndcg_at_1 |
|
value: 25.894000000000002 |
|
- type: ndcg_at_10 |
|
value: 31.497999999999998 |
|
- type: ndcg_at_100 |
|
value: 37.271 |
|
- type: ndcg_at_1000 |
|
value: 40.433 |
|
- type: ndcg_at_3 |
|
value: 28.21 |
|
- type: ndcg_at_5 |
|
value: 29.754 |
|
- type: precision_at_1 |
|
value: 25.894000000000002 |
|
- type: precision_at_10 |
|
value: 6.18 |
|
- type: precision_at_100 |
|
value: 1.139 |
|
- type: precision_at_1000 |
|
value: 0.17600000000000002 |
|
- type: precision_at_3 |
|
value: 13.447999999999999 |
|
- type: precision_at_5 |
|
value: 9.871 |
|
- type: recall_at_1 |
|
value: 20.383000000000003 |
|
- type: recall_at_10 |
|
value: 38.888 |
|
- type: recall_at_100 |
|
value: 64.85300000000001 |
|
- type: recall_at_1000 |
|
value: 86.81400000000001 |
|
- type: recall_at_3 |
|
value: 29.254 |
|
- type: recall_at_5 |
|
value: 33.742 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB CQADupstackEnglishRetrieval |
|
config: default |
|
split: test |
|
revision: ad9991cb51e31e31e430383c75ffb2885547b5f0 |
|
metrics: |
|
- type: map_at_1 |
|
value: 15.414 |
|
- type: map_at_10 |
|
value: 21.178 |
|
- type: map_at_100 |
|
value: 22.112000000000002 |
|
- type: map_at_1000 |
|
value: 22.245 |
|
- type: map_at_3 |
|
value: 19.313 |
|
- type: map_at_5 |
|
value: 20.252 |
|
- type: mrr_at_1 |
|
value: 19.49 |
|
- type: mrr_at_10 |
|
value: 25.066 |
|
- type: mrr_at_100 |
|
value: 25.885 |
|
- type: mrr_at_1000 |
|
value: 25.96 |
|
- type: mrr_at_3 |
|
value: 23.132 |
|
- type: mrr_at_5 |
|
value: 24.09 |
|
- type: ndcg_at_1 |
|
value: 19.49 |
|
- type: ndcg_at_10 |
|
value: 25.009999999999998 |
|
- type: ndcg_at_100 |
|
value: 29.376 |
|
- type: ndcg_at_1000 |
|
value: 32.53 |
|
- type: ndcg_at_3 |
|
value: 21.707 |
|
- type: ndcg_at_5 |
|
value: 22.98 |
|
- type: precision_at_1 |
|
value: 19.49 |
|
- type: precision_at_10 |
|
value: 4.777 |
|
- type: precision_at_100 |
|
value: 0.8659999999999999 |
|
- type: precision_at_1000 |
|
value: 0.14100000000000001 |
|
- type: precision_at_3 |
|
value: 10.446 |
|
- type: precision_at_5 |
|
value: 7.452 |
|
- type: recall_at_1 |
|
value: 15.414 |
|
- type: recall_at_10 |
|
value: 32.584 |
|
- type: recall_at_100 |
|
value: 51.912000000000006 |
|
- type: recall_at_1000 |
|
value: 73.636 |
|
- type: recall_at_3 |
|
value: 22.966 |
|
- type: recall_at_5 |
|
value: 26.484 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB CQADupstackGamingRetrieval |
|
config: default |
|
split: test |
|
revision: 4885aa143210c98657558c04aaf3dc47cfb54340 |
|
metrics: |
|
- type: map_at_1 |
|
value: 25.104 |
|
- type: map_at_10 |
|
value: 33.625 |
|
- type: map_at_100 |
|
value: 34.815000000000005 |
|
- type: map_at_1000 |
|
value: 34.910999999999994 |
|
- type: map_at_3 |
|
value: 30.894 |
|
- type: map_at_5 |
|
value: 32.507000000000005 |
|
- type: mrr_at_1 |
|
value: 29.279 |
|
- type: mrr_at_10 |
|
value: 36.942 |
|
- type: mrr_at_100 |
|
value: 37.88 |
|
- type: mrr_at_1000 |
|
value: 37.941 |
|
- type: mrr_at_3 |
|
value: 34.556 |
|
- type: mrr_at_5 |
|
value: 35.916 |
|
- type: ndcg_at_1 |
|
value: 29.279 |
|
- type: ndcg_at_10 |
|
value: 38.485 |
|
- type: ndcg_at_100 |
|
value: 43.974999999999994 |
|
- type: ndcg_at_1000 |
|
value: 46.165 |
|
- type: ndcg_at_3 |
|
value: 33.537 |
|
- type: ndcg_at_5 |
|
value: 36.025 |
|
- type: precision_at_1 |
|
value: 29.279 |
|
- type: precision_at_10 |
|
value: 6.351 |
|
- type: precision_at_100 |
|
value: 1.001 |
|
- type: precision_at_1000 |
|
value: 0.127 |
|
- type: precision_at_3 |
|
value: 14.963000000000001 |
|
- type: precision_at_5 |
|
value: 10.646 |
|
- type: recall_at_1 |
|
value: 25.104 |
|
- type: recall_at_10 |
|
value: 50.047 |
|
- type: recall_at_100 |
|
value: 74.678 |
|
- type: recall_at_1000 |
|
value: 90.471 |
|
- type: recall_at_3 |
|
value: 36.671 |
|
- type: recall_at_5 |
|
value: 42.797000000000004 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB CQADupstackGisRetrieval |
|
config: default |
|
split: test |
|
revision: 5003b3064772da1887988e05400cf3806fe491f2 |
|
metrics: |
|
- type: map_at_1 |
|
value: 12.626999999999999 |
|
- type: map_at_10 |
|
value: 17.686 |
|
- type: map_at_100 |
|
value: 18.568 |
|
- type: map_at_1000 |
|
value: 18.68 |
|
- type: map_at_3 |
|
value: 16.051000000000002 |
|
- type: map_at_5 |
|
value: 16.969 |
|
- type: mrr_at_1 |
|
value: 13.898 |
|
- type: mrr_at_10 |
|
value: 18.987000000000002 |
|
- type: mrr_at_100 |
|
value: 19.853 |
|
- type: mrr_at_1000 |
|
value: 19.955000000000002 |
|
- type: mrr_at_3 |
|
value: 17.307 |
|
- type: mrr_at_5 |
|
value: 18.262 |
|
- type: ndcg_at_1 |
|
value: 13.898 |
|
- type: ndcg_at_10 |
|
value: 20.799 |
|
- type: ndcg_at_100 |
|
value: 25.598 |
|
- type: ndcg_at_1000 |
|
value: 28.945 |
|
- type: ndcg_at_3 |
|
value: 17.482 |
|
- type: ndcg_at_5 |
|
value: 19.073 |
|
- type: precision_at_1 |
|
value: 13.898 |
|
- type: precision_at_10 |
|
value: 3.3329999999999997 |
|
- type: precision_at_100 |
|
value: 0.61 |
|
- type: precision_at_1000 |
|
value: 0.095 |
|
- type: precision_at_3 |
|
value: 7.571 |
|
- type: precision_at_5 |
|
value: 5.492 |
|
- type: recall_at_1 |
|
value: 12.626999999999999 |
|
- type: recall_at_10 |
|
value: 29.261 |
|
- type: recall_at_100 |
|
value: 52.297000000000004 |
|
- type: recall_at_1000 |
|
value: 78.34 |
|
- type: recall_at_3 |
|
value: 20.188 |
|
- type: recall_at_5 |
|
value: 23.971999999999998 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB CQADupstackMathematicaRetrieval |
|
config: default |
|
split: test |
|
revision: 90fceea13679c63fe563ded68f3b6f06e50061de |
|
metrics: |
|
- type: map_at_1 |
|
value: 6.918 |
|
- type: map_at_10 |
|
value: 10.688 |
|
- type: map_at_100 |
|
value: 11.62 |
|
- type: map_at_1000 |
|
value: 11.733 |
|
- type: map_at_3 |
|
value: 9.203 |
|
- type: map_at_5 |
|
value: 10.084999999999999 |
|
- type: mrr_at_1 |
|
value: 9.08 |
|
- type: mrr_at_10 |
|
value: 13.447000000000001 |
|
- type: mrr_at_100 |
|
value: 14.377999999999998 |
|
- type: mrr_at_1000 |
|
value: 14.468 |
|
- type: mrr_at_3 |
|
value: 11.899 |
|
- type: mrr_at_5 |
|
value: 12.788 |
|
- type: ndcg_at_1 |
|
value: 9.08 |
|
- type: ndcg_at_10 |
|
value: 13.608999999999998 |
|
- type: ndcg_at_100 |
|
value: 18.845 |
|
- type: ndcg_at_1000 |
|
value: 22.252 |
|
- type: ndcg_at_3 |
|
value: 10.771 |
|
- type: ndcg_at_5 |
|
value: 12.225 |
|
- type: precision_at_1 |
|
value: 9.08 |
|
- type: precision_at_10 |
|
value: 2.6870000000000003 |
|
- type: precision_at_100 |
|
value: 0.641 |
|
- type: precision_at_1000 |
|
value: 0.107 |
|
- type: precision_at_3 |
|
value: 5.390000000000001 |
|
- type: precision_at_5 |
|
value: 4.204 |
|
- type: recall_at_1 |
|
value: 6.918 |
|
- type: recall_at_10 |
|
value: 20.076 |
|
- type: recall_at_100 |
|
value: 44.185 |
|
- type: recall_at_1000 |
|
value: 69.705 |
|
- type: recall_at_3 |
|
value: 12.147 |
|
- type: recall_at_5 |
|
value: 15.903 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB CQADupstackPhysicsRetrieval |
|
config: default |
|
split: test |
|
revision: 79531abbd1fb92d06c6d6315a0cbbbf5bb247ea4 |
|
metrics: |
|
- type: map_at_1 |
|
value: 18.603 |
|
- type: map_at_10 |
|
value: 24.552 |
|
- type: map_at_100 |
|
value: 25.771 |
|
- type: map_at_1000 |
|
value: 25.917 |
|
- type: map_at_3 |
|
value: 22.286 |
|
- type: map_at_5 |
|
value: 23.398 |
|
- type: mrr_at_1 |
|
value: 22.522000000000002 |
|
- type: mrr_at_10 |
|
value: 28.986 |
|
- type: mrr_at_100 |
|
value: 29.94 |
|
- type: mrr_at_1000 |
|
value: 30.016 |
|
- type: mrr_at_3 |
|
value: 26.612000000000002 |
|
- type: mrr_at_5 |
|
value: 27.907 |
|
- type: ndcg_at_1 |
|
value: 22.522000000000002 |
|
- type: ndcg_at_10 |
|
value: 28.937 |
|
- type: ndcg_at_100 |
|
value: 34.821000000000005 |
|
- type: ndcg_at_1000 |
|
value: 38.086 |
|
- type: ndcg_at_3 |
|
value: 24.879 |
|
- type: ndcg_at_5 |
|
value: 26.576 |
|
- type: precision_at_1 |
|
value: 22.522000000000002 |
|
- type: precision_at_10 |
|
value: 5.371 |
|
- type: precision_at_100 |
|
value: 0.9979999999999999 |
|
- type: precision_at_1000 |
|
value: 0.149 |
|
- type: precision_at_3 |
|
value: 11.517 |
|
- type: precision_at_5 |
|
value: 8.277 |
|
- type: recall_at_1 |
|
value: 18.603 |
|
- type: recall_at_10 |
|
value: 37.669999999999995 |
|
- type: recall_at_100 |
|
value: 63.918 |
|
- type: recall_at_1000 |
|
value: 86.482 |
|
- type: recall_at_3 |
|
value: 26.308 |
|
- type: recall_at_5 |
|
value: 30.830000000000002 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB CQADupstackProgrammersRetrieval |
|
config: default |
|
split: test |
|
revision: 6184bc1440d2dbc7612be22b50686b8826d22b32 |
|
metrics: |
|
- type: map_at_1 |
|
value: 13.38 |
|
- type: map_at_10 |
|
value: 18.875 |
|
- type: map_at_100 |
|
value: 20.008 |
|
- type: map_at_1000 |
|
value: 20.158 |
|
- type: map_at_3 |
|
value: 16.959 |
|
- type: map_at_5 |
|
value: 17.858999999999998 |
|
- type: mrr_at_1 |
|
value: 16.667 |
|
- type: mrr_at_10 |
|
value: 22.409000000000002 |
|
- type: mrr_at_100 |
|
value: 23.391000000000002 |
|
- type: mrr_at_1000 |
|
value: 23.488 |
|
- type: mrr_at_3 |
|
value: 20.491 |
|
- type: mrr_at_5 |
|
value: 21.478 |
|
- type: ndcg_at_1 |
|
value: 16.667 |
|
- type: ndcg_at_10 |
|
value: 22.721 |
|
- type: ndcg_at_100 |
|
value: 28.17 |
|
- type: ndcg_at_1000 |
|
value: 31.886 |
|
- type: ndcg_at_3 |
|
value: 19.261 |
|
- type: ndcg_at_5 |
|
value: 20.575 |
|
- type: precision_at_1 |
|
value: 16.667 |
|
- type: precision_at_10 |
|
value: 4.349 |
|
- type: precision_at_100 |
|
value: 0.839 |
|
- type: precision_at_1000 |
|
value: 0.136 |
|
- type: precision_at_3 |
|
value: 9.399000000000001 |
|
- type: precision_at_5 |
|
value: 6.781 |
|
- type: recall_at_1 |
|
value: 13.38 |
|
- type: recall_at_10 |
|
value: 30.903999999999996 |
|
- type: recall_at_100 |
|
value: 54.75299999999999 |
|
- type: recall_at_1000 |
|
value: 81.188 |
|
- type: recall_at_3 |
|
value: 21.007 |
|
- type: recall_at_5 |
|
value: 24.568 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: mteb/cqadupstack |
|
name: MTEB CQADupstackRetrieval |
|
config: default |
|
split: test |
|
revision: 4885aa143210c98657558c04aaf3dc47cfb54340 |
|
metrics: |
|
- type: map_at_1 |
|
value: 14.091916666666668 |
|
- type: map_at_10 |
|
value: 19.413999999999998 |
|
- type: map_at_100 |
|
value: 20.39841666666667 |
|
- type: map_at_1000 |
|
value: 20.53091666666667 |
|
- type: map_at_3 |
|
value: 17.59308333333333 |
|
- type: map_at_5 |
|
value: 18.568 |
|
- type: mrr_at_1 |
|
value: 17.024666666666665 |
|
- type: mrr_at_10 |
|
value: 22.45566666666667 |
|
- type: mrr_at_100 |
|
value: 23.328166666666668 |
|
- type: mrr_at_1000 |
|
value: 23.417166666666667 |
|
- type: mrr_at_3 |
|
value: 20.65191666666667 |
|
- type: mrr_at_5 |
|
value: 21.653499999999998 |
|
- type: ndcg_at_1 |
|
value: 17.024666666666665 |
|
- type: ndcg_at_10 |
|
value: 23.004916666666666 |
|
- type: ndcg_at_100 |
|
value: 27.916083333333336 |
|
- type: ndcg_at_1000 |
|
value: 31.23883333333334 |
|
- type: ndcg_at_3 |
|
value: 19.685750000000002 |
|
- type: ndcg_at_5 |
|
value: 21.177416666666666 |
|
- type: precision_at_1 |
|
value: 17.024666666666665 |
|
- type: precision_at_10 |
|
value: 4.170999999999999 |
|
- type: precision_at_100 |
|
value: 0.7939999999999999 |
|
- type: precision_at_1000 |
|
value: 0.12708333333333333 |
|
- type: precision_at_3 |
|
value: 9.142083333333332 |
|
- type: precision_at_5 |
|
value: 6.64275 |
|
- type: recall_at_1 |
|
value: 14.091916666666668 |
|
- type: recall_at_10 |
|
value: 30.80275 |
|
- type: recall_at_100 |
|
value: 53.32091666666666 |
|
- type: recall_at_1000 |
|
value: 77.51058333333333 |
|
- type: recall_at_3 |
|
value: 21.45283333333333 |
|
- type: recall_at_5 |
|
value: 25.315333333333335 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB CQADupstackStatsRetrieval |
|
config: default |
|
split: test |
|
revision: 65ac3a16b8e91f9cee4c9828cc7c335575432a2a |
|
metrics: |
|
- type: map_at_1 |
|
value: 10.844 |
|
- type: map_at_10 |
|
value: 15.121 |
|
- type: map_at_100 |
|
value: 15.837000000000002 |
|
- type: map_at_1000 |
|
value: 15.928 |
|
- type: map_at_3 |
|
value: 13.629 |
|
- type: map_at_5 |
|
value: 14.462 |
|
- type: mrr_at_1 |
|
value: 12.577 |
|
- type: mrr_at_10 |
|
value: 16.93 |
|
- type: mrr_at_100 |
|
value: 17.701 |
|
- type: mrr_at_1000 |
|
value: 17.782999999999998 |
|
- type: mrr_at_3 |
|
value: 15.440000000000001 |
|
- type: mrr_at_5 |
|
value: 16.314 |
|
- type: ndcg_at_1 |
|
value: 12.577 |
|
- type: ndcg_at_10 |
|
value: 17.947 |
|
- type: ndcg_at_100 |
|
value: 22.055 |
|
- type: ndcg_at_1000 |
|
value: 24.854000000000003 |
|
- type: ndcg_at_3 |
|
value: 15.003 |
|
- type: ndcg_at_5 |
|
value: 16.433 |
|
- type: precision_at_1 |
|
value: 12.577 |
|
- type: precision_at_10 |
|
value: 3.0669999999999997 |
|
- type: precision_at_100 |
|
value: 0.557 |
|
- type: precision_at_1000 |
|
value: 0.087 |
|
- type: precision_at_3 |
|
value: 6.748 |
|
- type: precision_at_5 |
|
value: 4.968999999999999 |
|
- type: recall_at_1 |
|
value: 10.844 |
|
- type: recall_at_10 |
|
value: 25.014999999999997 |
|
- type: recall_at_100 |
|
value: 44.542 |
|
- type: recall_at_1000 |
|
value: 65.969 |
|
- type: recall_at_3 |
|
value: 16.766000000000002 |
|
- type: recall_at_5 |
|
value: 20.348 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB CQADupstackTexRetrieval |
|
config: default |
|
split: test |
|
revision: 46989137a86843e03a6195de44b09deda022eec7 |
|
metrics: |
|
- type: map_at_1 |
|
value: 7.180000000000001 |
|
- type: map_at_10 |
|
value: 10.648 |
|
- type: map_at_100 |
|
value: 11.34 |
|
- type: map_at_1000 |
|
value: 11.472 |
|
- type: map_at_3 |
|
value: 9.506 |
|
- type: map_at_5 |
|
value: 10.064 |
|
- type: mrr_at_1 |
|
value: 9.222 |
|
- type: mrr_at_10 |
|
value: 13.023000000000001 |
|
- type: mrr_at_100 |
|
value: 13.733 |
|
- type: mrr_at_1000 |
|
value: 13.841999999999999 |
|
- type: mrr_at_3 |
|
value: 11.774 |
|
- type: mrr_at_5 |
|
value: 12.404 |
|
- type: ndcg_at_1 |
|
value: 9.222 |
|
- type: ndcg_at_10 |
|
value: 13.111999999999998 |
|
- type: ndcg_at_100 |
|
value: 16.936999999999998 |
|
- type: ndcg_at_1000 |
|
value: 20.712 |
|
- type: ndcg_at_3 |
|
value: 10.953 |
|
- type: ndcg_at_5 |
|
value: 11.809 |
|
- type: precision_at_1 |
|
value: 9.222 |
|
- type: precision_at_10 |
|
value: 2.5090000000000003 |
|
- type: precision_at_100 |
|
value: 0.536 |
|
- type: precision_at_1000 |
|
value: 0.10200000000000001 |
|
- type: precision_at_3 |
|
value: 5.357 |
|
- type: precision_at_5 |
|
value: 3.909 |
|
- type: recall_at_1 |
|
value: 7.180000000000001 |
|
- type: recall_at_10 |
|
value: 18.318 |
|
- type: recall_at_100 |
|
value: 36.187000000000005 |
|
- type: recall_at_1000 |
|
value: 64.29 |
|
- type: recall_at_3 |
|
value: 12.191 |
|
- type: recall_at_5 |
|
value: 14.421999999999999 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB CQADupstackUnixRetrieval |
|
config: default |
|
split: test |
|
revision: 6c6430d3a6d36f8d2a829195bc5dc94d7e063e53 |
|
metrics: |
|
- type: map_at_1 |
|
value: 12.847 |
|
- type: map_at_10 |
|
value: 17.381 |
|
- type: map_at_100 |
|
value: 18.246000000000002 |
|
- type: map_at_1000 |
|
value: 18.372 |
|
- type: map_at_3 |
|
value: 15.934000000000001 |
|
- type: map_at_5 |
|
value: 16.525000000000002 |
|
- type: mrr_at_1 |
|
value: 15.299 |
|
- type: mrr_at_10 |
|
value: 20.291999999999998 |
|
- type: mrr_at_100 |
|
value: 21.14 |
|
- type: mrr_at_1000 |
|
value: 21.238 |
|
- type: mrr_at_3 |
|
value: 18.688 |
|
- type: mrr_at_5 |
|
value: 19.369 |
|
- type: ndcg_at_1 |
|
value: 15.299 |
|
- type: ndcg_at_10 |
|
value: 20.684 |
|
- type: ndcg_at_100 |
|
value: 25.362000000000002 |
|
- type: ndcg_at_1000 |
|
value: 28.897000000000002 |
|
- type: ndcg_at_3 |
|
value: 17.708 |
|
- type: ndcg_at_5 |
|
value: 18.654 |
|
- type: precision_at_1 |
|
value: 15.299 |
|
- type: precision_at_10 |
|
value: 3.535 |
|
- type: precision_at_100 |
|
value: 0.66 |
|
- type: precision_at_1000 |
|
value: 0.109 |
|
- type: precision_at_3 |
|
value: 8.053 |
|
- type: precision_at_5 |
|
value: 5.485 |
|
- type: recall_at_1 |
|
value: 12.847 |
|
- type: recall_at_10 |
|
value: 28.218 |
|
- type: recall_at_100 |
|
value: 49.816 |
|
- type: recall_at_1000 |
|
value: 75.868 |
|
- type: recall_at_3 |
|
value: 19.636 |
|
- type: recall_at_5 |
|
value: 22.224 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB CQADupstackWebmastersRetrieval |
|
config: default |
|
split: test |
|
revision: 160c094312a0e1facb97e55eeddb698c0abe3571 |
|
metrics: |
|
- type: map_at_1 |
|
value: 14.645 |
|
- type: map_at_10 |
|
value: 20.493 |
|
- type: map_at_100 |
|
value: 21.743000000000002 |
|
- type: map_at_1000 |
|
value: 21.951 |
|
- type: map_at_3 |
|
value: 18.584 |
|
- type: map_at_5 |
|
value: 19.628 |
|
- type: mrr_at_1 |
|
value: 17.984 |
|
- type: mrr_at_10 |
|
value: 23.879 |
|
- type: mrr_at_100 |
|
value: 24.87 |
|
- type: mrr_at_1000 |
|
value: 24.965 |
|
- type: mrr_at_3 |
|
value: 22.167 |
|
- type: mrr_at_5 |
|
value: 23.294 |
|
- type: ndcg_at_1 |
|
value: 17.984 |
|
- type: ndcg_at_10 |
|
value: 24.567 |
|
- type: ndcg_at_100 |
|
value: 29.818 |
|
- type: ndcg_at_1000 |
|
value: 33.667 |
|
- type: ndcg_at_3 |
|
value: 21.453 |
|
- type: ndcg_at_5 |
|
value: 23.018 |
|
- type: precision_at_1 |
|
value: 17.984 |
|
- type: precision_at_10 |
|
value: 4.862 |
|
- type: precision_at_100 |
|
value: 1.1280000000000001 |
|
- type: precision_at_1000 |
|
value: 0.201 |
|
- type: precision_at_3 |
|
value: 10.343 |
|
- type: precision_at_5 |
|
value: 7.747 |
|
- type: recall_at_1 |
|
value: 14.645 |
|
- type: recall_at_10 |
|
value: 32.102000000000004 |
|
- type: recall_at_100 |
|
value: 56.472 |
|
- type: recall_at_1000 |
|
value: 82.901 |
|
- type: recall_at_3 |
|
value: 22.814 |
|
- type: recall_at_5 |
|
value: 26.904 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB CQADupstackWordpressRetrieval |
|
config: default |
|
split: test |
|
revision: 4ffe81d471b1924886b33c7567bfb200e9eec5c4 |
|
metrics: |
|
- type: map_at_1 |
|
value: 11.158 |
|
- type: map_at_10 |
|
value: 15.723999999999998 |
|
- type: map_at_100 |
|
value: 16.431 |
|
- type: map_at_1000 |
|
value: 16.56 |
|
- type: map_at_3 |
|
value: 13.993 |
|
- type: map_at_5 |
|
value: 14.995 |
|
- type: mrr_at_1 |
|
value: 12.384 |
|
- type: mrr_at_10 |
|
value: 17.171 |
|
- type: mrr_at_100 |
|
value: 17.876 |
|
- type: mrr_at_1000 |
|
value: 17.990000000000002 |
|
- type: mrr_at_3 |
|
value: 15.404000000000002 |
|
- type: mrr_at_5 |
|
value: 16.494 |
|
- type: ndcg_at_1 |
|
value: 12.384 |
|
- type: ndcg_at_10 |
|
value: 18.69 |
|
- type: ndcg_at_100 |
|
value: 22.765 |
|
- type: ndcg_at_1000 |
|
value: 26.439 |
|
- type: ndcg_at_3 |
|
value: 15.265 |
|
- type: ndcg_at_5 |
|
value: 17.007 |
|
- type: precision_at_1 |
|
value: 12.384 |
|
- type: precision_at_10 |
|
value: 3.031 |
|
- type: precision_at_100 |
|
value: 0.553 |
|
- type: precision_at_1000 |
|
value: 0.095 |
|
- type: precision_at_3 |
|
value: 6.47 |
|
- type: precision_at_5 |
|
value: 4.88 |
|
- type: recall_at_1 |
|
value: 11.158 |
|
- type: recall_at_10 |
|
value: 26.55 |
|
- type: recall_at_100 |
|
value: 46.238 |
|
- type: recall_at_1000 |
|
value: 74.46300000000001 |
|
- type: recall_at_3 |
|
value: 17.485999999999997 |
|
- type: recall_at_5 |
|
value: 21.59 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB ClimateFEVER |
|
config: default |
|
split: test |
|
revision: 47f2ac6acb640fc46020b02a5b59fdda04d39380 |
|
metrics: |
|
- type: map_at_1 |
|
value: 6.375 |
|
- type: map_at_10 |
|
value: 11.718 |
|
- type: map_at_100 |
|
value: 13.245999999999999 |
|
- type: map_at_1000 |
|
value: 13.459 |
|
- type: map_at_3 |
|
value: 9.607000000000001 |
|
- type: map_at_5 |
|
value: 10.639999999999999 |
|
- type: mrr_at_1 |
|
value: 14.788 |
|
- type: mrr_at_10 |
|
value: 24.168 |
|
- type: mrr_at_100 |
|
value: 25.419999999999998 |
|
- type: mrr_at_1000 |
|
value: 25.480999999999998 |
|
- type: mrr_at_3 |
|
value: 20.955 |
|
- type: mrr_at_5 |
|
value: 22.802 |
|
- type: ndcg_at_1 |
|
value: 14.788 |
|
- type: ndcg_at_10 |
|
value: 17.721 |
|
- type: ndcg_at_100 |
|
value: 24.833 |
|
- type: ndcg_at_1000 |
|
value: 29.01 |
|
- type: ndcg_at_3 |
|
value: 13.714 |
|
- type: ndcg_at_5 |
|
value: 15.160000000000002 |
|
- type: precision_at_1 |
|
value: 14.788 |
|
- type: precision_at_10 |
|
value: 5.876 |
|
- type: precision_at_100 |
|
value: 1.341 |
|
- type: precision_at_1000 |
|
value: 0.211 |
|
- type: precision_at_3 |
|
value: 10.467 |
|
- type: precision_at_5 |
|
value: 8.391 |
|
- type: recall_at_1 |
|
value: 6.375 |
|
- type: recall_at_10 |
|
value: 22.598 |
|
- type: recall_at_100 |
|
value: 47.835 |
|
- type: recall_at_1000 |
|
value: 71.758 |
|
- type: recall_at_3 |
|
value: 13.033 |
|
- type: recall_at_5 |
|
value: 16.858 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB DBPedia |
|
config: default |
|
split: test |
|
revision: c0f706b76e590d620bd6618b3ca8efdd34e2d659 |
|
metrics: |
|
- type: map_at_1 |
|
value: 4.1579999999999995 |
|
- type: map_at_10 |
|
value: 9.283 |
|
- type: map_at_100 |
|
value: 13.092 |
|
- type: map_at_1000 |
|
value: 14.033999999999999 |
|
- type: map_at_3 |
|
value: 6.463000000000001 |
|
- type: map_at_5 |
|
value: 7.701 |
|
- type: mrr_at_1 |
|
value: 41.25 |
|
- type: mrr_at_10 |
|
value: 50.105999999999995 |
|
- type: mrr_at_100 |
|
value: 50.879 |
|
- type: mrr_at_1000 |
|
value: 50.912 |
|
- type: mrr_at_3 |
|
value: 47.292 |
|
- type: mrr_at_5 |
|
value: 48.766999999999996 |
|
- type: ndcg_at_1 |
|
value: 29.625 |
|
- type: ndcg_at_10 |
|
value: 23.26 |
|
- type: ndcg_at_100 |
|
value: 26.556 |
|
- type: ndcg_at_1000 |
|
value: 33.271 |
|
- type: ndcg_at_3 |
|
value: 25.665 |
|
- type: ndcg_at_5 |
|
value: 24.404 |
|
- type: precision_at_1 |
|
value: 41.25 |
|
- type: precision_at_10 |
|
value: 21.075 |
|
- type: precision_at_100 |
|
value: 6.748 |
|
- type: precision_at_1000 |
|
value: 1.444 |
|
- type: precision_at_3 |
|
value: 30.75 |
|
- type: precision_at_5 |
|
value: 26.700000000000003 |
|
- type: recall_at_1 |
|
value: 4.1579999999999995 |
|
- type: recall_at_10 |
|
value: 13.834 |
|
- type: recall_at_100 |
|
value: 33.318999999999996 |
|
- type: recall_at_1000 |
|
value: 56.806999999999995 |
|
- type: recall_at_3 |
|
value: 7.417999999999999 |
|
- type: recall_at_5 |
|
value: 9.872 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: None |
|
name: MTEB EmotionClassification |
|
config: default |
|
split: test |
|
revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37 |
|
metrics: |
|
- type: accuracy |
|
value: 46.825 |
|
- type: f1 |
|
value: 43.13728772840347 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB FEVER |
|
config: default |
|
split: test |
|
revision: bea83ef9e8fb933d90a2f1d5515737465d613e12 |
|
metrics: |
|
- type: map_at_1 |
|
value: 14.036000000000001 |
|
- type: map_at_10 |
|
value: 21.296 |
|
- type: map_at_100 |
|
value: 22.165000000000003 |
|
- type: map_at_1000 |
|
value: 22.24 |
|
- type: map_at_3 |
|
value: 19.186 |
|
- type: map_at_5 |
|
value: 20.366999999999997 |
|
- type: mrr_at_1 |
|
value: 14.865999999999998 |
|
- type: mrr_at_10 |
|
value: 22.503 |
|
- type: mrr_at_100 |
|
value: 23.376 |
|
- type: mrr_at_1000 |
|
value: 23.444000000000003 |
|
- type: mrr_at_3 |
|
value: 20.262 |
|
- type: mrr_at_5 |
|
value: 21.525 |
|
- type: ndcg_at_1 |
|
value: 14.865999999999998 |
|
- type: ndcg_at_10 |
|
value: 25.568 |
|
- type: ndcg_at_100 |
|
value: 30.131999999999998 |
|
- type: ndcg_at_1000 |
|
value: 32.242 |
|
- type: ndcg_at_3 |
|
value: 21.178 |
|
- type: ndcg_at_5 |
|
value: 23.317 |
|
- type: precision_at_1 |
|
value: 14.865999999999998 |
|
- type: precision_at_10 |
|
value: 4.098 |
|
- type: precision_at_100 |
|
value: 0.661 |
|
- type: precision_at_1000 |
|
value: 0.086 |
|
- type: precision_at_3 |
|
value: 9.211 |
|
- type: precision_at_5 |
|
value: 6.666999999999999 |
|
- type: recall_at_1 |
|
value: 14.036000000000001 |
|
- type: recall_at_10 |
|
value: 37.775999999999996 |
|
- type: recall_at_100 |
|
value: 59.243 |
|
- type: recall_at_1000 |
|
value: 75.583 |
|
- type: recall_at_3 |
|
value: 25.857000000000003 |
|
- type: recall_at_5 |
|
value: 30.982 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB FiQA2018 |
|
config: default |
|
split: test |
|
revision: 27a168819829fe9bcd655c2df245fb19452e8e06 |
|
metrics: |
|
- type: map_at_1 |
|
value: 6.859999999999999 |
|
- type: map_at_10 |
|
value: 11.631 |
|
- type: map_at_100 |
|
value: 12.795000000000002 |
|
- type: map_at_1000 |
|
value: 12.992999999999999 |
|
- type: map_at_3 |
|
value: 10.08 |
|
- type: map_at_5 |
|
value: 10.772 |
|
- type: mrr_at_1 |
|
value: 13.58 |
|
- type: mrr_at_10 |
|
value: 19.564999999999998 |
|
- type: mrr_at_100 |
|
value: 20.669999999999998 |
|
- type: mrr_at_1000 |
|
value: 20.761 |
|
- type: mrr_at_3 |
|
value: 17.824 |
|
- type: mrr_at_5 |
|
value: 18.619 |
|
- type: ndcg_at_1 |
|
value: 13.58 |
|
- type: ndcg_at_10 |
|
value: 15.78 |
|
- type: ndcg_at_100 |
|
value: 21.707 |
|
- type: ndcg_at_1000 |
|
value: 26.226 |
|
- type: ndcg_at_3 |
|
value: 13.719000000000001 |
|
- type: ndcg_at_5 |
|
value: 14.183000000000002 |
|
- type: precision_at_1 |
|
value: 13.58 |
|
- type: precision_at_10 |
|
value: 4.552 |
|
- type: precision_at_100 |
|
value: 1.028 |
|
- type: precision_at_1000 |
|
value: 0.183 |
|
- type: precision_at_3 |
|
value: 9.311 |
|
- type: precision_at_5 |
|
value: 6.79 |
|
- type: recall_at_1 |
|
value: 6.859999999999999 |
|
- type: recall_at_10 |
|
value: 20.054 |
|
- type: recall_at_100 |
|
value: 43.822 |
|
- type: recall_at_1000 |
|
value: 71.665 |
|
- type: recall_at_3 |
|
value: 13.008000000000001 |
|
- type: recall_at_5 |
|
value: 15.381 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB HotpotQA |
|
config: default |
|
split: test |
|
revision: ab518f4d6fcca38d87c25209f94beba119d02014 |
|
metrics: |
|
- type: map_at_1 |
|
value: 14.045 |
|
- type: map_at_10 |
|
value: 20.054 |
|
- type: map_at_100 |
|
value: 20.89 |
|
- type: map_at_1000 |
|
value: 20.999000000000002 |
|
- type: map_at_3 |
|
value: 18.297 |
|
- type: map_at_5 |
|
value: 19.231 |
|
- type: mrr_at_1 |
|
value: 28.089 |
|
- type: mrr_at_10 |
|
value: 34.583999999999996 |
|
- type: mrr_at_100 |
|
value: 35.337 |
|
- type: mrr_at_1000 |
|
value: 35.400999999999996 |
|
- type: mrr_at_3 |
|
value: 32.66 |
|
- type: mrr_at_5 |
|
value: 33.743 |
|
- type: ndcg_at_1 |
|
value: 28.089 |
|
- type: ndcg_at_10 |
|
value: 25.999 |
|
- type: ndcg_at_100 |
|
value: 30.023 |
|
- type: ndcg_at_1000 |
|
value: 32.742 |
|
- type: ndcg_at_3 |
|
value: 22.519 |
|
- type: ndcg_at_5 |
|
value: 24.15 |
|
- type: precision_at_1 |
|
value: 28.089 |
|
- type: precision_at_10 |
|
value: 5.858 |
|
- type: precision_at_100 |
|
value: 0.909 |
|
- type: precision_at_1000 |
|
value: 0.127 |
|
- type: precision_at_3 |
|
value: 14.265 |
|
- type: precision_at_5 |
|
value: 9.85 |
|
- type: recall_at_1 |
|
value: 14.045 |
|
- type: recall_at_10 |
|
value: 29.291 |
|
- type: recall_at_100 |
|
value: 45.436 |
|
- type: recall_at_1000 |
|
value: 63.666 |
|
- type: recall_at_3 |
|
value: 21.398 |
|
- type: recall_at_5 |
|
value: 24.625 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: None |
|
name: MTEB ImdbClassification |
|
config: default |
|
split: test |
|
revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7 |
|
metrics: |
|
- type: accuracy |
|
value: 61.8104 |
|
- type: ap |
|
value: 57.38352158221927 |
|
- type: f1 |
|
value: 61.535478192568135 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB MSMARCO |
|
config: default |
|
split: dev |
|
revision: c5a29a104738b98a9e76336939199e264163d4a0 |
|
metrics: |
|
- type: map_at_1 |
|
value: 5.821 |
|
- type: map_at_10 |
|
value: 10.403 |
|
- type: map_at_100 |
|
value: 11.271 |
|
- type: map_at_1000 |
|
value: 11.375 |
|
- type: map_at_3 |
|
value: 8.764 |
|
- type: map_at_5 |
|
value: 9.588000000000001 |
|
- type: mrr_at_1 |
|
value: 6.0600000000000005 |
|
- type: mrr_at_10 |
|
value: 10.709 |
|
- type: mrr_at_100 |
|
value: 11.583 |
|
- type: mrr_at_1000 |
|
value: 11.684 |
|
- type: mrr_at_3 |
|
value: 9.046999999999999 |
|
- type: mrr_at_5 |
|
value: 9.894 |
|
- type: ndcg_at_1 |
|
value: 6.032 |
|
- type: ndcg_at_10 |
|
value: 13.264999999999999 |
|
- type: ndcg_at_100 |
|
value: 18.016 |
|
- type: ndcg_at_1000 |
|
value: 21.226 |
|
- type: ndcg_at_3 |
|
value: 9.82 |
|
- type: ndcg_at_5 |
|
value: 11.309 |
|
- type: precision_at_1 |
|
value: 6.032 |
|
- type: precision_at_10 |
|
value: 2.305 |
|
- type: precision_at_100 |
|
value: 0.477 |
|
- type: precision_at_1000 |
|
value: 0.075 |
|
- type: precision_at_3 |
|
value: 4.365 |
|
- type: precision_at_5 |
|
value: 3.367 |
|
- type: recall_at_1 |
|
value: 5.821 |
|
- type: recall_at_10 |
|
value: 22.165000000000003 |
|
- type: recall_at_100 |
|
value: 45.357 |
|
- type: recall_at_1000 |
|
value: 71.28 |
|
- type: recall_at_3 |
|
value: 12.631 |
|
- type: recall_at_5 |
|
value: 16.211000000000002 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: None |
|
name: MTEB MTOPDomainClassification (en) |
|
config: en |
|
split: test |
|
revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf |
|
metrics: |
|
- type: accuracy |
|
value: 88.38349293205654 |
|
- type: f1 |
|
value: 87.54736120600828 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: None |
|
name: MTEB MTOPIntentClassification (en) |
|
config: en |
|
split: test |
|
revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba |
|
metrics: |
|
- type: accuracy |
|
value: 55.23483812129503 |
|
- type: f1 |
|
value: 37.290140441414046 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: None |
|
name: MTEB MassiveIntentClassification (en) |
|
config: en |
|
split: test |
|
revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 |
|
metrics: |
|
- type: accuracy |
|
value: 61.139878950907864 |
|
- type: f1 |
|
value: 59.50881927994892 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: None |
|
name: MTEB MassiveScenarioClassification (en) |
|
config: en |
|
split: test |
|
revision: 7d571f92784cd94a019292a1f45445077d0ef634 |
|
metrics: |
|
- type: accuracy |
|
value: 70.01008742434432 |
|
- type: f1 |
|
value: 68.42281820836324 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: None |
|
name: MTEB MedrxivClusteringP2P |
|
config: default |
|
split: test |
|
revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73 |
|
metrics: |
|
- type: v_measure |
|
value: 30.15718904178607 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: None |
|
name: MTEB MedrxivClusteringS2S |
|
config: default |
|
split: test |
|
revision: 35191c8c0dca72d8ff3efcd72aa802307d469663 |
|
metrics: |
|
- type: v_measure |
|
value: 27.70725540281151 |
|
- task: |
|
type: Reranking |
|
dataset: |
|
type: None |
|
name: MTEB MindSmallReranking |
|
config: default |
|
split: test |
|
revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69 |
|
metrics: |
|
- type: map |
|
value: 30.927012755857614 |
|
- type: mrr |
|
value: 31.985831468302077 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB NFCorpus |
|
config: default |
|
split: test |
|
revision: ec0fa4fe99da2ff19ca1214b7966684033a58814 |
|
metrics: |
|
- type: map_at_1 |
|
value: 4.168 |
|
- type: map_at_10 |
|
value: 8.12 |
|
- type: map_at_100 |
|
value: 10.453999999999999 |
|
- type: map_at_1000 |
|
value: 11.937000000000001 |
|
- type: map_at_3 |
|
value: 6.069 |
|
- type: map_at_5 |
|
value: 7.138999999999999 |
|
- type: mrr_at_1 |
|
value: 34.056 |
|
- type: mrr_at_10 |
|
value: 43.980000000000004 |
|
- type: mrr_at_100 |
|
value: 44.638 |
|
- type: mrr_at_1000 |
|
value: 44.699 |
|
- type: mrr_at_3 |
|
value: 41.538000000000004 |
|
- type: mrr_at_5 |
|
value: 43.208999999999996 |
|
- type: ndcg_at_1 |
|
value: 32.507999999999996 |
|
- type: ndcg_at_10 |
|
value: 25.377 |
|
- type: ndcg_at_100 |
|
value: 24.298000000000002 |
|
- type: ndcg_at_1000 |
|
value: 34.327000000000005 |
|
- type: ndcg_at_3 |
|
value: 28.883 |
|
- type: ndcg_at_5 |
|
value: 27.49 |
|
- type: precision_at_1 |
|
value: 34.056 |
|
- type: precision_at_10 |
|
value: 18.978 |
|
- type: precision_at_100 |
|
value: 6.842 |
|
- type: precision_at_1000 |
|
value: 2.073 |
|
- type: precision_at_3 |
|
value: 27.348 |
|
- type: precision_at_5 |
|
value: 23.839 |
|
- type: recall_at_1 |
|
value: 4.168 |
|
- type: recall_at_10 |
|
value: 12.405 |
|
- type: recall_at_100 |
|
value: 26.067 |
|
- type: recall_at_1000 |
|
value: 62.019000000000005 |
|
- type: recall_at_3 |
|
value: 7.381 |
|
- type: recall_at_5 |
|
value: 9.678 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB NQ |
|
config: default |
|
split: test |
|
revision: b774495ed302d8c44a3a7ea25c90dbce03968f31 |
|
metrics: |
|
- type: map_at_1 |
|
value: 7.621 |
|
- type: map_at_10 |
|
value: 13.205 |
|
- type: map_at_100 |
|
value: 14.377999999999998 |
|
- type: map_at_1000 |
|
value: 14.488000000000001 |
|
- type: map_at_3 |
|
value: 10.835 |
|
- type: map_at_5 |
|
value: 12.056000000000001 |
|
- type: mrr_at_1 |
|
value: 8.72 |
|
- type: mrr_at_10 |
|
value: 14.746 |
|
- type: mrr_at_100 |
|
value: 15.814 |
|
- type: mrr_at_1000 |
|
value: 15.903 |
|
- type: mrr_at_3 |
|
value: 12.205 |
|
- type: mrr_at_5 |
|
value: 13.526 |
|
- type: ndcg_at_1 |
|
value: 8.72 |
|
- type: ndcg_at_10 |
|
value: 17.230999999999998 |
|
- type: ndcg_at_100 |
|
value: 23.157 |
|
- type: ndcg_at_1000 |
|
value: 26.11 |
|
- type: ndcg_at_3 |
|
value: 12.215 |
|
- type: ndcg_at_5 |
|
value: 14.448 |
|
- type: precision_at_1 |
|
value: 8.72 |
|
- type: precision_at_10 |
|
value: 3.3489999999999998 |
|
- type: precision_at_100 |
|
value: 0.6689999999999999 |
|
- type: precision_at_1000 |
|
value: 0.095 |
|
- type: precision_at_3 |
|
value: 5.765 |
|
- type: precision_at_5 |
|
value: 4.71 |
|
- type: recall_at_1 |
|
value: 7.621 |
|
- type: recall_at_10 |
|
value: 28.346 |
|
- type: recall_at_100 |
|
value: 55.905 |
|
- type: recall_at_1000 |
|
value: 78.568 |
|
- type: recall_at_3 |
|
value: 14.888000000000002 |
|
- type: recall_at_5 |
|
value: 20.119 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB QuoraRetrieval |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 64.12400000000001 |
|
- type: map_at_10 |
|
value: 77.009 |
|
- type: map_at_100 |
|
value: 77.77 |
|
- type: map_at_1000 |
|
value: 77.803 |
|
- type: map_at_3 |
|
value: 74.05000000000001 |
|
- type: map_at_5 |
|
value: 75.846 |
|
- type: mrr_at_1 |
|
value: 73.78 |
|
- type: mrr_at_10 |
|
value: 80.87100000000001 |
|
- type: mrr_at_100 |
|
value: 81.109 |
|
- type: mrr_at_1000 |
|
value: 81.114 |
|
- type: mrr_at_3 |
|
value: 79.415 |
|
- type: mrr_at_5 |
|
value: 80.345 |
|
- type: ndcg_at_1 |
|
value: 73.81 |
|
- type: ndcg_at_10 |
|
value: 81.50699999999999 |
|
- type: ndcg_at_100 |
|
value: 83.518 |
|
- type: ndcg_at_1000 |
|
value: 83.868 |
|
- type: ndcg_at_3 |
|
value: 77.96600000000001 |
|
- type: ndcg_at_5 |
|
value: 79.794 |
|
- type: precision_at_1 |
|
value: 73.81 |
|
- type: precision_at_10 |
|
value: 12.367 |
|
- type: precision_at_100 |
|
value: 1.469 |
|
- type: precision_at_1000 |
|
value: 0.155 |
|
- type: precision_at_3 |
|
value: 33.94 |
|
- type: precision_at_5 |
|
value: 22.438 |
|
- type: recall_at_1 |
|
value: 64.12400000000001 |
|
- type: recall_at_10 |
|
value: 90.283 |
|
- type: recall_at_100 |
|
value: 97.76 |
|
- type: recall_at_1000 |
|
value: 99.714 |
|
- type: recall_at_3 |
|
value: 80.15299999999999 |
|
- type: recall_at_5 |
|
value: 85.208 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: None |
|
name: MTEB RedditClustering |
|
config: default |
|
split: test |
|
revision: 24640382cdbf8abc73003fb0fa6d111a705499eb |
|
metrics: |
|
- type: v_measure |
|
value: 44.162118605127525 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: None |
|
name: MTEB RedditClusteringP2P |
|
config: default |
|
split: test |
|
revision: 282350215ef01743dc01b456c7f5241fa8937f16 |
|
metrics: |
|
- type: v_measure |
|
value: 46.70881745207942 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB SCIDOCS |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 3.2030000000000003 |
|
- type: map_at_10 |
|
value: 7.474 |
|
- type: map_at_100 |
|
value: 8.898 |
|
- type: map_at_1000 |
|
value: 9.168 |
|
- type: map_at_3 |
|
value: 5.45 |
|
- type: map_at_5 |
|
value: 6.363 |
|
- type: mrr_at_1 |
|
value: 15.7 |
|
- type: mrr_at_10 |
|
value: 23.682 |
|
- type: mrr_at_100 |
|
value: 24.855 |
|
- type: mrr_at_1000 |
|
value: 24.939 |
|
- type: mrr_at_3 |
|
value: 20.782999999999998 |
|
- type: mrr_at_5 |
|
value: 22.208 |
|
- type: ndcg_at_1 |
|
value: 15.7 |
|
- type: ndcg_at_10 |
|
value: 13.235 |
|
- type: ndcg_at_100 |
|
value: 19.679 |
|
- type: ndcg_at_1000 |
|
value: 25.088 |
|
- type: ndcg_at_3 |
|
value: 12.394 |
|
- type: ndcg_at_5 |
|
value: 10.717 |
|
- type: precision_at_1 |
|
value: 15.7 |
|
- type: precision_at_10 |
|
value: 6.909999999999999 |
|
- type: precision_at_100 |
|
value: 1.633 |
|
- type: precision_at_1000 |
|
value: 0.294 |
|
- type: precision_at_3 |
|
value: 11.466999999999999 |
|
- type: precision_at_5 |
|
value: 9.28 |
|
- type: recall_at_1 |
|
value: 3.2030000000000003 |
|
- type: recall_at_10 |
|
value: 14.002999999999998 |
|
- type: recall_at_100 |
|
value: 33.12 |
|
- type: recall_at_1000 |
|
value: 59.675 |
|
- type: recall_at_3 |
|
value: 6.978 |
|
- type: recall_at_5 |
|
value: 9.388 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: None |
|
name: MTEB SICK-R |
|
config: default |
|
split: test |
|
revision: a6ea5a8cab320b040a23452cc28066d9beae2cee |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 76.64379518764505 |
|
- type: cos_sim_spearman |
|
value: 65.03593875325868 |
|
- type: euclidean_pearson |
|
value: 71.30716734159877 |
|
- type: euclidean_spearman |
|
value: 65.0358725107667 |
|
- type: manhattan_pearson |
|
value: 69.64008883410301 |
|
- type: manhattan_spearman |
|
value: 64.1709357952613 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: None |
|
name: MTEB STS12 |
|
config: default |
|
split: test |
|
revision: a0d554a64d88156834ff5ae9920b964011b16384 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 76.10760678507381 |
|
- type: cos_sim_spearman |
|
value: 68.35350054782432 |
|
- type: euclidean_pearson |
|
value: 72.65776988973283 |
|
- type: euclidean_spearman |
|
value: 68.35478315887251 |
|
- type: manhattan_pearson |
|
value: 70.5706666450866 |
|
- type: manhattan_spearman |
|
value: 67.13814826706063 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: None |
|
name: MTEB STS13 |
|
config: default |
|
split: test |
|
revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 75.32161265212544 |
|
- type: cos_sim_spearman |
|
value: 76.93198204035276 |
|
- type: euclidean_pearson |
|
value: 76.60126151642021 |
|
- type: euclidean_spearman |
|
value: 76.93199423707081 |
|
- type: manhattan_pearson |
|
value: 76.5056121876099 |
|
- type: manhattan_spearman |
|
value: 76.86184669371214 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: None |
|
name: MTEB STS14 |
|
config: default |
|
split: test |
|
revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 77.10524062982039 |
|
- type: cos_sim_spearman |
|
value: 72.59969217378233 |
|
- type: euclidean_pearson |
|
value: 76.10064294747684 |
|
- type: euclidean_spearman |
|
value: 72.59968248507782 |
|
- type: manhattan_pearson |
|
value: 75.2538128834374 |
|
- type: manhattan_spearman |
|
value: 72.14612849441266 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: None |
|
name: MTEB STS15 |
|
config: default |
|
split: test |
|
revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 79.92563014030377 |
|
- type: cos_sim_spearman |
|
value: 80.98166673776733 |
|
- type: euclidean_pearson |
|
value: 80.9596078291122 |
|
- type: euclidean_spearman |
|
value: 80.9816574633563 |
|
- type: manhattan_pearson |
|
value: 79.89230536933664 |
|
- type: manhattan_spearman |
|
value: 80.00574493608646 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: None |
|
name: MTEB STS16 |
|
config: default |
|
split: test |
|
revision: 4d8694f8f0e0100860b497b999b3dbed754a0513 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 74.19795257280954 |
|
- type: cos_sim_spearman |
|
value: 75.43790136296928 |
|
- type: euclidean_pearson |
|
value: 75.57117891505544 |
|
- type: euclidean_spearman |
|
value: 75.43845178483879 |
|
- type: manhattan_pearson |
|
value: 75.41513445680592 |
|
- type: manhattan_spearman |
|
value: 75.38085076755232 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: None |
|
name: MTEB STS17 (en-en) |
|
config: en-en |
|
split: test |
|
revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 82.61027585526848 |
|
- type: cos_sim_spearman |
|
value: 83.72082588978941 |
|
- type: euclidean_pearson |
|
value: 83.72701589311066 |
|
- type: euclidean_spearman |
|
value: 83.7217002176894 |
|
- type: manhattan_pearson |
|
value: 83.24293225606534 |
|
- type: manhattan_spearman |
|
value: 83.4135678831862 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: None |
|
name: MTEB STS22 (en) |
|
config: en |
|
split: test |
|
revision: eea2b4fe26a775864c896887d910b76a8098ad3f |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 64.42651773313223 |
|
- type: cos_sim_spearman |
|
value: 61.7038845289896 |
|
- type: euclidean_pearson |
|
value: 64.54756406367291 |
|
- type: euclidean_spearman |
|
value: 61.7038845289896 |
|
- type: manhattan_pearson |
|
value: 63.51018692682091 |
|
- type: manhattan_spearman |
|
value: 60.45964817925399 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: None |
|
name: MTEB STSBenchmark |
|
config: default |
|
split: test |
|
revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 75.55989105968095 |
|
- type: cos_sim_spearman |
|
value: 73.7042941496097 |
|
- type: euclidean_pearson |
|
value: 75.91151565422992 |
|
- type: euclidean_spearman |
|
value: 73.70428269603238 |
|
- type: manhattan_pearson |
|
value: 75.4126729336794 |
|
- type: manhattan_spearman |
|
value: 73.5240782951808 |
|
- task: |
|
type: Reranking |
|
dataset: |
|
type: None |
|
name: MTEB SciDocsRR |
|
config: default |
|
split: test |
|
revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab |
|
metrics: |
|
- type: map |
|
value: 74.49865014688187 |
|
- type: mrr |
|
value: 91.71895823856607 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB SciFact |
|
config: default |
|
split: test |
|
revision: 0228b52cf27578f30900b9e5271d331663a030d7 |
|
metrics: |
|
- type: map_at_1 |
|
value: 33.306000000000004 |
|
- type: map_at_10 |
|
value: 41.848 |
|
- type: map_at_100 |
|
value: 42.909000000000006 |
|
- type: map_at_1000 |
|
value: 42.981 |
|
- type: map_at_3 |
|
value: 39.389 |
|
- type: map_at_5 |
|
value: 41.031 |
|
- type: mrr_at_1 |
|
value: 35.333 |
|
- type: mrr_at_10 |
|
value: 43.641000000000005 |
|
- type: mrr_at_100 |
|
value: 44.539 |
|
- type: mrr_at_1000 |
|
value: 44.603 |
|
- type: mrr_at_3 |
|
value: 41.611 |
|
- type: mrr_at_5 |
|
value: 42.943999999999996 |
|
- type: ndcg_at_1 |
|
value: 35.333 |
|
- type: ndcg_at_10 |
|
value: 46.452 |
|
- type: ndcg_at_100 |
|
value: 51.7 |
|
- type: ndcg_at_1000 |
|
value: 53.622 |
|
- type: ndcg_at_3 |
|
value: 41.833 |
|
- type: ndcg_at_5 |
|
value: 44.553 |
|
- type: precision_at_1 |
|
value: 35.333 |
|
- type: precision_at_10 |
|
value: 6.4670000000000005 |
|
- type: precision_at_100 |
|
value: 0.947 |
|
- type: precision_at_1000 |
|
value: 0.11100000000000002 |
|
- type: precision_at_3 |
|
value: 16.667 |
|
- type: precision_at_5 |
|
value: 11.533 |
|
- type: recall_at_1 |
|
value: 33.306000000000004 |
|
- type: recall_at_10 |
|
value: 59.0 |
|
- type: recall_at_100 |
|
value: 83.556 |
|
- type: recall_at_1000 |
|
value: 98.6 |
|
- type: recall_at_3 |
|
value: 46.639 |
|
- type: recall_at_5 |
|
value: 53.306 |
|
- task: |
|
type: PairClassification |
|
dataset: |
|
type: None |
|
name: MTEB SprintDuplicateQuestions |
|
config: default |
|
split: test |
|
revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46 |
|
metrics: |
|
- type: cos_sim_accuracy |
|
value: 99.69108910891089 |
|
- type: cos_sim_ap |
|
value: 90.4977489865437 |
|
- type: cos_sim_f1 |
|
value: 83.7493632195619 |
|
- type: cos_sim_precision |
|
value: 85.35825545171339 |
|
- type: cos_sim_recall |
|
value: 82.19999999999999 |
|
- type: dot_accuracy |
|
value: 99.69108910891089 |
|
- type: dot_ap |
|
value: 90.4977489865437 |
|
- type: dot_f1 |
|
value: 83.7493632195619 |
|
- type: dot_precision |
|
value: 85.35825545171339 |
|
- type: dot_recall |
|
value: 82.19999999999999 |
|
- type: euclidean_accuracy |
|
value: 99.69108910891089 |
|
- type: euclidean_ap |
|
value: 90.4977489865437 |
|
- type: euclidean_f1 |
|
value: 83.7493632195619 |
|
- type: euclidean_precision |
|
value: 85.35825545171339 |
|
- type: euclidean_recall |
|
value: 82.19999999999999 |
|
- type: manhattan_accuracy |
|
value: 99.70792079207921 |
|
- type: manhattan_ap |
|
value: 91.16860160199867 |
|
- type: manhattan_f1 |
|
value: 84.73874806001035 |
|
- type: manhattan_precision |
|
value: 87.78135048231512 |
|
- type: manhattan_recall |
|
value: 81.89999999999999 |
|
- type: max_accuracy |
|
value: 99.70792079207921 |
|
- type: max_ap |
|
value: 91.16860160199867 |
|
- type: max_f1 |
|
value: 84.73874806001035 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: None |
|
name: MTEB StackExchangeClustering |
|
config: default |
|
split: test |
|
revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259 |
|
metrics: |
|
- type: v_measure |
|
value: 43.35434708006249 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: None |
|
name: MTEB StackExchangeClusteringP2P |
|
config: default |
|
split: test |
|
revision: 815ca46b2622cec33ccafc3735d572c266efdb44 |
|
metrics: |
|
- type: v_measure |
|
value: 31.335469165398756 |
|
- task: |
|
type: Reranking |
|
dataset: |
|
type: None |
|
name: MTEB StackOverflowDupQuestions |
|
config: default |
|
split: test |
|
revision: e185fbe320c72810689fc5848eb6114e1ef5ec69 |
|
metrics: |
|
- type: map |
|
value: 41.97374025833599 |
|
- type: mrr |
|
value: 42.262077179356595 |
|
- task: |
|
type: Summarization |
|
dataset: |
|
type: None |
|
name: MTEB SummEval |
|
config: default |
|
split: test |
|
revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 30.976845934718288 |
|
- type: cos_sim_spearman |
|
value: 31.683535959644406 |
|
- type: dot_pearson |
|
value: 30.97684544705739 |
|
- type: dot_spearman |
|
value: 31.732556691703294 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB TRECCOVID |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 0.109 |
|
- type: map_at_10 |
|
value: 0.893 |
|
- type: map_at_100 |
|
value: 5.261 |
|
- type: map_at_1000 |
|
value: 13.122 |
|
- type: map_at_3 |
|
value: 0.317 |
|
- type: map_at_5 |
|
value: 0.488 |
|
- type: mrr_at_1 |
|
value: 46.0 |
|
- type: mrr_at_10 |
|
value: 62.352 |
|
- type: mrr_at_100 |
|
value: 62.941 |
|
- type: mrr_at_1000 |
|
value: 62.941 |
|
- type: mrr_at_3 |
|
value: 60.0 |
|
- type: mrr_at_5 |
|
value: 61.4 |
|
- type: ndcg_at_1 |
|
value: 38.0 |
|
- type: ndcg_at_10 |
|
value: 42.480000000000004 |
|
- type: ndcg_at_100 |
|
value: 34.835 |
|
- type: ndcg_at_1000 |
|
value: 32.592 |
|
- type: ndcg_at_3 |
|
value: 44.665 |
|
- type: ndcg_at_5 |
|
value: 43.911 |
|
- type: precision_at_1 |
|
value: 44.0 |
|
- type: precision_at_10 |
|
value: 46.800000000000004 |
|
- type: precision_at_100 |
|
value: 37.4 |
|
- type: precision_at_1000 |
|
value: 15.918 |
|
- type: precision_at_3 |
|
value: 51.333 |
|
- type: precision_at_5 |
|
value: 49.2 |
|
- type: recall_at_1 |
|
value: 0.109 |
|
- type: recall_at_10 |
|
value: 1.154 |
|
- type: recall_at_100 |
|
value: 8.389000000000001 |
|
- type: recall_at_1000 |
|
value: 32.096000000000004 |
|
- type: recall_at_3 |
|
value: 0.387 |
|
- type: recall_at_5 |
|
value: 0.612 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: None |
|
name: MTEB Touche2020 |
|
config: default |
|
split: test |
|
revision: a34f9a33db75fa0cbb21bb5cfc3dae8dc8bec93f |
|
metrics: |
|
- type: map_at_1 |
|
value: 1.7489999999999999 |
|
- type: map_at_10 |
|
value: 7.498 |
|
- type: map_at_100 |
|
value: 13.675 |
|
- type: map_at_1000 |
|
value: 15.379999999999999 |
|
- type: map_at_3 |
|
value: 4.073 |
|
- type: map_at_5 |
|
value: 5.575 |
|
- type: mrr_at_1 |
|
value: 24.490000000000002 |
|
- type: mrr_at_10 |
|
value: 39.521 |
|
- type: mrr_at_100 |
|
value: 40.63 |
|
- type: mrr_at_1000 |
|
value: 40.63 |
|
- type: mrr_at_3 |
|
value: 35.034 |
|
- type: mrr_at_5 |
|
value: 36.870999999999995 |
|
- type: ndcg_at_1 |
|
value: 23.469 |
|
- type: ndcg_at_10 |
|
value: 20.269000000000002 |
|
- type: ndcg_at_100 |
|
value: 34.174 |
|
- type: ndcg_at_1000 |
|
value: 46.137 |
|
- type: ndcg_at_3 |
|
value: 22.977 |
|
- type: ndcg_at_5 |
|
value: 21.604 |
|
- type: precision_at_1 |
|
value: 24.490000000000002 |
|
- type: precision_at_10 |
|
value: 18.776 |
|
- type: precision_at_100 |
|
value: 7.939 |
|
- type: precision_at_1000 |
|
value: 1.555 |
|
- type: precision_at_3 |
|
value: 25.169999999999998 |
|
- type: precision_at_5 |
|
value: 22.857 |
|
- type: recall_at_1 |
|
value: 1.7489999999999999 |
|
- type: recall_at_10 |
|
value: 13.354 |
|
- type: recall_at_100 |
|
value: 48.303000000000004 |
|
- type: recall_at_1000 |
|
value: 84.65 |
|
- type: recall_at_3 |
|
value: 5.293 |
|
- type: recall_at_5 |
|
value: 7.994 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: None |
|
name: MTEB ToxicConversationsClassification |
|
config: default |
|
split: test |
|
revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c |
|
metrics: |
|
- type: accuracy |
|
value: 71.8018 |
|
- type: ap |
|
value: 14.536819438052662 |
|
- type: f1 |
|
value: 55.19152517845791 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: None |
|
name: MTEB TweetSentimentExtractionClassification |
|
config: default |
|
split: test |
|
revision: d604517c81ca91fe16a244d1248fc021f9ecee7a |
|
metrics: |
|
- type: accuracy |
|
value: 53.52574985851726 |
|
- type: f1 |
|
value: 53.69703116168891 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: None |
|
name: MTEB TwentyNewsgroupsClustering |
|
config: default |
|
split: test |
|
revision: 6125ec4e24fa026cec8a478383ee943acfbd5449 |
|
metrics: |
|
- type: v_measure |
|
value: 38.1774041110333 |
|
- task: |
|
type: PairClassification |
|
dataset: |
|
type: None |
|
name: MTEB TwitterSemEval2015 |
|
config: default |
|
split: test |
|
revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1 |
|
metrics: |
|
- type: cos_sim_accuracy |
|
value: 81.9991655242296 |
|
- type: cos_sim_ap |
|
value: 58.53652893055794 |
|
- type: cos_sim_f1 |
|
value: 56.55495317890586 |
|
- type: cos_sim_precision |
|
value: 53.051317614424406 |
|
- type: cos_sim_recall |
|
value: 60.554089709762536 |
|
- type: dot_accuracy |
|
value: 81.9991655242296 |
|
- type: dot_ap |
|
value: 58.53652893055794 |
|
- type: dot_f1 |
|
value: 56.55495317890586 |
|
- type: dot_precision |
|
value: 53.051317614424406 |
|
- type: dot_recall |
|
value: 60.554089709762536 |
|
- type: euclidean_accuracy |
|
value: 81.9991655242296 |
|
- type: euclidean_ap |
|
value: 58.53652809144572 |
|
- type: euclidean_f1 |
|
value: 56.55495317890586 |
|
- type: euclidean_precision |
|
value: 53.051317614424406 |
|
- type: euclidean_recall |
|
value: 60.554089709762536 |
|
- type: manhattan_accuracy |
|
value: 81.55808547416106 |
|
- type: manhattan_ap |
|
value: 56.9619587668482 |
|
- type: manhattan_f1 |
|
value: 55.47429078014184 |
|
- type: manhattan_precision |
|
value: 47.82193351165457 |
|
- type: manhattan_recall |
|
value: 66.04221635883904 |
|
- type: max_accuracy |
|
value: 81.9991655242296 |
|
- type: max_ap |
|
value: 58.53652893055794 |
|
- type: max_f1 |
|
value: 56.55495317890586 |
|
- task: |
|
type: PairClassification |
|
dataset: |
|
type: None |
|
name: MTEB TwitterURLCorpus |
|
config: default |
|
split: test |
|
revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf |
|
metrics: |
|
- type: cos_sim_accuracy |
|
value: 86.946481934257 |
|
- type: cos_sim_ap |
|
value: 81.66664549248112 |
|
- type: cos_sim_f1 |
|
value: 74.09368335907051 |
|
- type: cos_sim_precision |
|
value: 70.90781140042223 |
|
- type: cos_sim_recall |
|
value: 77.57930397289806 |
|
- type: dot_accuracy |
|
value: 86.946481934257 |
|
- type: dot_ap |
|
value: 81.66664549326697 |
|
- type: dot_f1 |
|
value: 74.09368335907051 |
|
- type: dot_precision |
|
value: 70.90781140042223 |
|
- type: dot_recall |
|
value: 77.57930397289806 |
|
- type: euclidean_accuracy |
|
value: 86.946481934257 |
|
- type: euclidean_ap |
|
value: 81.66664561833119 |
|
- type: euclidean_f1 |
|
value: 74.09368335907051 |
|
- type: euclidean_precision |
|
value: 70.90781140042223 |
|
- type: euclidean_recall |
|
value: 77.57930397289806 |
|
- type: manhattan_accuracy |
|
value: 86.89602980556526 |
|
- type: manhattan_ap |
|
value: 81.68402162687751 |
|
- type: manhattan_f1 |
|
value: 73.93715341959334 |
|
- type: manhattan_precision |
|
value: 71.11363959607453 |
|
- type: manhattan_recall |
|
value: 76.9941484447182 |
|
- type: max_accuracy |
|
value: 86.946481934257 |
|
- type: max_ap |
|
value: 81.68402162687751 |
|
- type: max_f1 |
|
value: 74.09368335907051 |
|
--- |
