|
--- |
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tags: |
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- mteb |
|
model-index: |
|
- name: alime-embedding-large-zh |
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results: |
|
- task: |
|
type: STS |
|
dataset: |
|
type: C-MTEB/AFQMC |
|
name: MTEB AFQMC |
|
config: default |
|
split: validation |
|
revision: None |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 49.6479989785073 |
|
- type: cos_sim_spearman |
|
value: 54.733173049795425 |
|
- type: euclidean_pearson |
|
value: 53.06330391299694 |
|
- type: euclidean_spearman |
|
value: 54.73321325021156 |
|
- type: manhattan_pearson |
|
value: 53.0477915350307 |
|
- type: manhattan_spearman |
|
value: 54.728508847750845 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: C-MTEB/ATEC |
|
name: MTEB ATEC |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 48.658812679136325 |
|
- type: cos_sim_spearman |
|
value: 55.125070901329146 |
|
- type: euclidean_pearson |
|
value: 55.73373519622172 |
|
- type: euclidean_spearman |
|
value: 55.12506864911728 |
|
- type: manhattan_pearson |
|
value: 55.71155132206361 |
|
- type: manhattan_spearman |
|
value: 55.121598723227905 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/amazon_reviews_multi |
|
name: MTEB AmazonReviewsClassification (zh) |
|
config: zh |
|
split: test |
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revision: 1399c76144fd37290681b995c656ef9b2e06e26d |
|
metrics: |
|
- type: accuracy |
|
value: 46.95 |
|
- type: f1 |
|
value: 45.34383964066362 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: C-MTEB/BQ |
|
name: MTEB BQ |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 62.92731050834033 |
|
- type: cos_sim_spearman |
|
value: 64.8881453551134 |
|
- type: euclidean_pearson |
|
value: 63.31447523186855 |
|
- type: euclidean_spearman |
|
value: 64.88814189042776 |
|
- type: manhattan_pearson |
|
value: 63.222442228527996 |
|
- type: manhattan_spearman |
|
value: 64.79818263591122 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: C-MTEB/CLSClusteringP2P |
|
name: MTEB CLSClusteringP2P |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: v_measure |
|
value: 42.518811360488925 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: C-MTEB/CLSClusteringS2S |
|
name: MTEB CLSClusteringS2S |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: v_measure |
|
value: 39.72890397315954 |
|
- task: |
|
type: Reranking |
|
dataset: |
|
type: C-MTEB/CMedQAv1-reranking |
|
name: MTEB CMedQAv1 |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map |
|
value: 86.51852576014969 |
|
- type: mrr |
|
value: 89.02047619047619 |
|
- task: |
|
type: Reranking |
|
dataset: |
|
type: C-MTEB/CMedQAv2-reranking |
|
name: MTEB CMedQAv2 |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map |
|
value: 87.11415162833914 |
|
- type: mrr |
|
value: 89.6338492063492 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: C-MTEB/CmedqaRetrieval |
|
name: MTEB CmedqaRetrieval |
|
config: default |
|
split: dev |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 24.883 |
|
- type: map_at_10 |
|
value: 37.246 |
|
- type: map_at_100 |
|
value: 39.11 |
|
- type: map_at_1000 |
|
value: 39.222 |
|
- type: map_at_3 |
|
value: 32.956 |
|
- type: map_at_5 |
|
value: 35.411 |
|
- type: mrr_at_1 |
|
value: 37.834 |
|
- type: mrr_at_10 |
|
value: 46.031 |
|
- type: mrr_at_100 |
|
value: 47.033 |
|
- type: mrr_at_1000 |
|
value: 47.077000000000005 |
|
- type: mrr_at_3 |
|
value: 43.415 |
|
- type: mrr_at_5 |
|
value: 44.938 |
|
- type: ndcg_at_1 |
|
value: 37.834 |
|
- type: ndcg_at_10 |
|
value: 43.928 |
|
- type: ndcg_at_100 |
|
value: 51.312999999999995 |
|
- type: ndcg_at_1000 |
|
value: 53.23 |
|
- type: ndcg_at_3 |
|
value: 38.397 |
|
- type: ndcg_at_5 |
|
value: 40.848 |
|
- type: precision_at_1 |
|
value: 37.834 |
|
- type: precision_at_10 |
|
value: 9.782 |
|
- type: precision_at_100 |
|
value: 1.583 |
|
- type: precision_at_1000 |
|
value: 0.183 |
|
- type: precision_at_3 |
|
value: 21.664 |
|
- type: precision_at_5 |
|
value: 15.934000000000001 |
|
- type: recall_at_1 |
|
value: 24.883 |
|
- type: recall_at_10 |
|
value: 54.911 |
|
- type: recall_at_100 |
|
value: 85.419 |
|
- type: recall_at_1000 |
|
value: 98.16 |
|
- type: recall_at_3 |
|
value: 38.416 |
|
- type: recall_at_5 |
|
value: 45.778 |
|
- task: |
|
type: PairClassification |
|
dataset: |
|
type: C-MTEB/CMNLI |
|
name: MTEB Cmnli |
|
config: default |
|
split: validation |
|
revision: None |
|
metrics: |
|
- type: cos_sim_accuracy |
|
value: 82.5616355983163 |
|
- type: cos_sim_ap |
|
value: 89.3612977679186 |
|
- type: cos_sim_f1 |
|
value: 83.93428161870108 |
|
- type: cos_sim_precision |
|
value: 79.42404006677796 |
|
- type: cos_sim_recall |
|
value: 88.98760813654431 |
|
- type: dot_accuracy |
|
value: 82.5616355983163 |
|
- type: dot_ap |
|
value: 89.38168095374776 |
|
- type: dot_f1 |
|
value: 83.93428161870108 |
|
- type: dot_precision |
|
value: 79.42404006677796 |
|
- type: dot_recall |
|
value: 88.98760813654431 |
|
- type: euclidean_accuracy |
|
value: 82.5616355983163 |
|
- type: euclidean_ap |
|
value: 89.36129603693611 |
|
- type: euclidean_f1 |
|
value: 83.93428161870108 |
|
- type: euclidean_precision |
|
value: 79.42404006677796 |
|
- type: euclidean_recall |
|
value: 88.98760813654431 |
|
- type: manhattan_accuracy |
|
value: 82.42934455802767 |
|
- type: manhattan_ap |
|
value: 89.36577661305246 |
|
- type: manhattan_f1 |
|
value: 83.94765539803707 |
|
- type: manhattan_precision |
|
value: 78.66339668914776 |
|
- type: manhattan_recall |
|
value: 89.99298573766659 |
|
- type: max_accuracy |
|
value: 82.5616355983163 |
|
- type: max_ap |
|
value: 89.38168095374776 |
|
- type: max_f1 |
|
value: 83.94765539803707 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: C-MTEB/CovidRetrieval |
|
name: MTEB CovidRetrieval |
|
config: default |
|
split: dev |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 77.608 |
|
- type: map_at_10 |
|
value: 85.1 |
|
- type: map_at_100 |
|
value: 85.215 |
|
- type: map_at_1000 |
|
value: 85.217 |
|
- type: map_at_3 |
|
value: 83.97 |
|
- type: map_at_5 |
|
value: 84.638 |
|
- type: mrr_at_1 |
|
value: 77.97699999999999 |
|
- type: mrr_at_10 |
|
value: 85.173 |
|
- type: mrr_at_100 |
|
value: 85.28 |
|
- type: mrr_at_1000 |
|
value: 85.282 |
|
- type: mrr_at_3 |
|
value: 84.089 |
|
- type: mrr_at_5 |
|
value: 84.726 |
|
- type: ndcg_at_1 |
|
value: 77.871 |
|
- type: ndcg_at_10 |
|
value: 88.141 |
|
- type: ndcg_at_100 |
|
value: 88.612 |
|
- type: ndcg_at_1000 |
|
value: 88.68 |
|
- type: ndcg_at_3 |
|
value: 85.9 |
|
- type: ndcg_at_5 |
|
value: 87.06 |
|
- type: precision_at_1 |
|
value: 77.871 |
|
- type: precision_at_10 |
|
value: 9.841999999999999 |
|
- type: precision_at_100 |
|
value: 1.005 |
|
- type: precision_at_1000 |
|
value: 0.101 |
|
- type: precision_at_3 |
|
value: 30.698999999999998 |
|
- type: precision_at_5 |
|
value: 19.009 |
|
- type: recall_at_1 |
|
value: 77.608 |
|
- type: recall_at_10 |
|
value: 97.418 |
|
- type: recall_at_100 |
|
value: 99.473 |
|
- type: recall_at_1000 |
|
value: 100.0 |
|
- type: recall_at_3 |
|
value: 91.307 |
|
- type: recall_at_5 |
|
value: 94.125 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: C-MTEB/DuRetrieval |
|
name: MTEB DuRetrieval |
|
config: default |
|
split: dev |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 26.104 |
|
- type: map_at_10 |
|
value: 78.62 |
|
- type: map_at_100 |
|
value: 81.417 |
|
- type: map_at_1000 |
|
value: 81.46600000000001 |
|
- type: map_at_3 |
|
value: 55.077 |
|
- type: map_at_5 |
|
value: 69.18900000000001 |
|
- type: mrr_at_1 |
|
value: 90.55 |
|
- type: mrr_at_10 |
|
value: 93.42200000000001 |
|
- type: mrr_at_100 |
|
value: 93.46900000000001 |
|
- type: mrr_at_1000 |
|
value: 93.472 |
|
- type: mrr_at_3 |
|
value: 93.108 |
|
- type: mrr_at_5 |
|
value: 93.318 |
|
- type: ndcg_at_1 |
|
value: 90.55 |
|
- type: ndcg_at_10 |
|
value: 86.227 |
|
- type: ndcg_at_100 |
|
value: 89.201 |
|
- type: ndcg_at_1000 |
|
value: 89.655 |
|
- type: ndcg_at_3 |
|
value: 85.89099999999999 |
|
- type: ndcg_at_5 |
|
value: 84.443 |
|
- type: precision_at_1 |
|
value: 90.55 |
|
- type: precision_at_10 |
|
value: 40.915 |
|
- type: precision_at_100 |
|
value: 4.749 |
|
- type: precision_at_1000 |
|
value: 0.486 |
|
- type: precision_at_3 |
|
value: 76.9 |
|
- type: precision_at_5 |
|
value: 64.56 |
|
- type: recall_at_1 |
|
value: 26.104 |
|
- type: recall_at_10 |
|
value: 86.924 |
|
- type: recall_at_100 |
|
value: 96.52 |
|
- type: recall_at_1000 |
|
value: 98.83800000000001 |
|
- type: recall_at_3 |
|
value: 57.196999999999996 |
|
- type: recall_at_5 |
|
value: 73.595 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: C-MTEB/EcomRetrieval |
|
name: MTEB EcomRetrieval |
|
config: default |
|
split: dev |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 51.9 |
|
- type: map_at_10 |
|
value: 62.446 |
|
- type: map_at_100 |
|
value: 62.922 |
|
- type: map_at_1000 |
|
value: 62.934999999999995 |
|
- type: map_at_3 |
|
value: 59.933 |
|
- type: map_at_5 |
|
value: 61.548 |
|
- type: mrr_at_1 |
|
value: 51.9 |
|
- type: mrr_at_10 |
|
value: 62.446 |
|
- type: mrr_at_100 |
|
value: 62.922 |
|
- type: mrr_at_1000 |
|
value: 62.934999999999995 |
|
- type: mrr_at_3 |
|
value: 59.933 |
|
- type: mrr_at_5 |
|
value: 61.548 |
|
- type: ndcg_at_1 |
|
value: 51.9 |
|
- type: ndcg_at_10 |
|
value: 67.561 |
|
- type: ndcg_at_100 |
|
value: 69.87400000000001 |
|
- type: ndcg_at_1000 |
|
value: 70.19800000000001 |
|
- type: ndcg_at_3 |
|
value: 62.474 |
|
- type: ndcg_at_5 |
|
value: 65.391 |
|
- type: precision_at_1 |
|
value: 51.9 |
|
- type: precision_at_10 |
|
value: 8.36 |
|
- type: precision_at_100 |
|
value: 0.9440000000000001 |
|
- type: precision_at_1000 |
|
value: 0.097 |
|
- type: precision_at_3 |
|
value: 23.267 |
|
- type: precision_at_5 |
|
value: 15.379999999999999 |
|
- type: recall_at_1 |
|
value: 51.9 |
|
- type: recall_at_10 |
|
value: 83.6 |
|
- type: recall_at_100 |
|
value: 94.39999999999999 |
|
- type: recall_at_1000 |
|
value: 96.89999999999999 |
|
- type: recall_at_3 |
|
value: 69.8 |
|
- type: recall_at_5 |
|
value: 76.9 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: C-MTEB/IFlyTek-classification |
|
name: MTEB IFlyTek |
|
config: default |
|
split: validation |
|
revision: None |
|
metrics: |
|
- type: accuracy |
|
value: 49.672951135051946 |
|
- type: f1 |
|
value: 38.246634605142084 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: C-MTEB/JDReview-classification |
|
name: MTEB JDReview |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: accuracy |
|
value: 86.52908067542214 |
|
- type: ap |
|
value: 55.415146961759135 |
|
- type: f1 |
|
value: 81.38343036361825 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: C-MTEB/LCQMC |
|
name: MTEB LCQMC |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 70.15572724302896 |
|
- type: cos_sim_spearman |
|
value: 75.11630463239744 |
|
- type: euclidean_pearson |
|
value: 74.2927184018677 |
|
- type: euclidean_spearman |
|
value: 75.11630463089752 |
|
- type: manhattan_pearson |
|
value: 74.27724224882166 |
|
- type: manhattan_spearman |
|
value: 75.10012699894408 |
|
- task: |
|
type: Reranking |
|
dataset: |
|
type: C-MTEB/Mmarco-reranking |
|
name: MTEB MMarcoReranking |
|
config: default |
|
split: dev |
|
revision: None |
|
metrics: |
|
- type: map |
|
value: 30.62934327678744 |
|
- type: mrr |
|
value: 29.48730158730159 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: C-MTEB/MMarcoRetrieval |
|
name: MTEB MMarcoRetrieval |
|
config: default |
|
split: dev |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 65.33 |
|
- type: map_at_10 |
|
value: 74.524 |
|
- type: map_at_100 |
|
value: 74.851 |
|
- type: map_at_1000 |
|
value: 74.86500000000001 |
|
- type: map_at_3 |
|
value: 72.748 |
|
- type: map_at_5 |
|
value: 73.896 |
|
- type: mrr_at_1 |
|
value: 67.593 |
|
- type: mrr_at_10 |
|
value: 75.19 |
|
- type: mrr_at_100 |
|
value: 75.472 |
|
- type: mrr_at_1000 |
|
value: 75.484 |
|
- type: mrr_at_3 |
|
value: 73.634 |
|
- type: mrr_at_5 |
|
value: 74.638 |
|
- type: ndcg_at_1 |
|
value: 67.593 |
|
- type: ndcg_at_10 |
|
value: 78.254 |
|
- type: ndcg_at_100 |
|
value: 79.727 |
|
- type: ndcg_at_1000 |
|
value: 80.09100000000001 |
|
- type: ndcg_at_3 |
|
value: 74.892 |
|
- type: ndcg_at_5 |
|
value: 76.835 |
|
- type: precision_at_1 |
|
value: 67.593 |
|
- type: precision_at_10 |
|
value: 9.46 |
|
- type: precision_at_100 |
|
value: 1.02 |
|
- type: precision_at_1000 |
|
value: 0.105 |
|
- type: precision_at_3 |
|
value: 28.227999999999998 |
|
- type: precision_at_5 |
|
value: 17.965999999999998 |
|
- type: recall_at_1 |
|
value: 65.33 |
|
- type: recall_at_10 |
|
value: 89.048 |
|
- type: recall_at_100 |
|
value: 95.732 |
|
- type: recall_at_1000 |
|
value: 98.598 |
|
- type: recall_at_3 |
|
value: 80.209 |
|
- type: recall_at_5 |
|
value: 84.824 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/amazon_massive_intent |
|
name: MTEB MassiveIntentClassification (zh-CN) |
|
config: zh-CN |
|
split: test |
|
revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 |
|
metrics: |
|
- type: accuracy |
|
value: 73.38937457969065 |
|
- type: f1 |
|
value: 70.87692475465195 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/amazon_massive_scenario |
|
name: MTEB MassiveScenarioClassification (zh-CN) |
|
config: zh-CN |
|
split: test |
|
revision: 7d571f92784cd94a019292a1f45445077d0ef634 |
|
metrics: |
|
- type: accuracy |
|
value: 76.04236718224612 |
|
- type: f1 |
|
value: 75.52425703483891 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: C-MTEB/MedicalRetrieval |
|
name: MTEB MedicalRetrieval |
|
config: default |
|
split: dev |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 53.1 |
|
- type: map_at_10 |
|
value: 60.24 |
|
- type: map_at_100 |
|
value: 60.781 |
|
- type: map_at_1000 |
|
value: 60.81999999999999 |
|
- type: map_at_3 |
|
value: 58.733000000000004 |
|
- type: map_at_5 |
|
value: 59.618 |
|
- type: mrr_at_1 |
|
value: 53.0 |
|
- type: mrr_at_10 |
|
value: 60.195 |
|
- type: mrr_at_100 |
|
value: 60.736000000000004 |
|
- type: mrr_at_1000 |
|
value: 60.775 |
|
- type: mrr_at_3 |
|
value: 58.68299999999999 |
|
- type: mrr_at_5 |
|
value: 59.573 |
|
- type: ndcg_at_1 |
|
value: 53.1 |
|
- type: ndcg_at_10 |
|
value: 63.568999999999996 |
|
- type: ndcg_at_100 |
|
value: 66.401 |
|
- type: ndcg_at_1000 |
|
value: 67.597 |
|
- type: ndcg_at_3 |
|
value: 60.455000000000005 |
|
- type: ndcg_at_5 |
|
value: 62.05500000000001 |
|
- type: precision_at_1 |
|
value: 53.1 |
|
- type: precision_at_10 |
|
value: 7.3999999999999995 |
|
- type: precision_at_100 |
|
value: 0.877 |
|
- type: precision_at_1000 |
|
value: 0.097 |
|
- type: precision_at_3 |
|
value: 21.8 |
|
- type: precision_at_5 |
|
value: 13.86 |
|
- type: recall_at_1 |
|
value: 53.1 |
|
- type: recall_at_10 |
|
value: 74.0 |
|
- type: recall_at_100 |
|
value: 87.7 |
|
- type: recall_at_1000 |
|
value: 97.39999999999999 |
|
- type: recall_at_3 |
|
value: 65.4 |
|
- type: recall_at_5 |
|
value: 69.3 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: C-MTEB/MultilingualSentiment-classification |
|
name: MTEB MultilingualSentiment |
|
config: default |
|
split: validation |
|
revision: None |
|
metrics: |
|
- type: accuracy |
|
value: 76.40333333333332 |
|
- type: f1 |
|
value: 76.40924131087777 |
|
- task: |
|
type: PairClassification |
|
dataset: |
|
type: C-MTEB/OCNLI |
|
name: MTEB Ocnli |
|
config: default |
|
split: validation |
|
revision: None |
|
metrics: |
|
- type: cos_sim_accuracy |
|
value: 77.15213860314023 |
|
- type: cos_sim_ap |
|
value: 79.30594584166899 |
|
- type: cos_sim_f1 |
|
value: 80.25889967637539 |
|
- type: cos_sim_precision |
|
value: 71.38157894736842 |
|
- type: cos_sim_recall |
|
value: 91.65786694825766 |
|
- type: dot_accuracy |
|
value: 77.15213860314023 |
|
- type: dot_ap |
|
value: 79.30594584166899 |
|
- type: dot_f1 |
|
value: 80.25889967637539 |
|
- type: dot_precision |
|
value: 71.38157894736842 |
|
- type: dot_recall |
|
value: 91.65786694825766 |
|
- type: euclidean_accuracy |
|
value: 77.15213860314023 |
|
- type: euclidean_ap |
|
value: 79.30594584166899 |
|
- type: euclidean_f1 |
|
value: 80.25889967637539 |
|
- type: euclidean_precision |
|
value: 71.38157894736842 |
|
- type: euclidean_recall |
|
value: 91.65786694825766 |
|
- type: manhattan_accuracy |
|
value: 77.36870600974554 |
|
- type: manhattan_ap |
|
value: 79.23401219102254 |
|
- type: manhattan_f1 |
|
value: 80.44901777362021 |
|
- type: manhattan_precision |
|
value: 72.20822837951302 |
|
- type: manhattan_recall |
|
value: 90.8130939809926 |
|
- type: max_accuracy |
|
value: 77.36870600974554 |
|
- type: max_ap |
|
value: 79.30594584166899 |
|
- type: max_f1 |
|
value: 80.44901777362021 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: C-MTEB/OnlineShopping-classification |
|
name: MTEB OnlineShopping |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: accuracy |
|
value: 92.6 |
|
- type: ap |
|
value: 90.78779333103819 |
|
- type: f1 |
|
value: 92.59253441654515 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: C-MTEB/PAWSX |
|
name: MTEB PAWSX |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 34.4442917065113 |
|
- type: cos_sim_spearman |
|
value: 37.93070836936766 |
|
- type: euclidean_pearson |
|
value: 38.35141108502335 |
|
- type: euclidean_spearman |
|
value: 37.936378767247106 |
|
- type: manhattan_pearson |
|
value: 38.357078125497566 |
|
- type: manhattan_spearman |
|
value: 37.94413026678537 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: C-MTEB/QBQTC |
|
name: MTEB QBQTC |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 32.84777948741198 |
|
- type: cos_sim_spearman |
|
value: 34.212129449696285 |
|
- type: euclidean_pearson |
|
value: 32.69161407750465 |
|
- type: euclidean_spearman |
|
value: 34.21178008084197 |
|
- type: manhattan_pearson |
|
value: 32.675418316752506 |
|
- type: manhattan_spearman |
|
value: 34.178590557249 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: mteb/sts22-crosslingual-sts |
|
name: MTEB STS22 (zh) |
|
config: zh |
|
split: test |
|
revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 64.65903821549742 |
|
- type: cos_sim_spearman |
|
value: 64.54376284777354 |
|
- type: euclidean_pearson |
|
value: 63.70022677799055 |
|
- type: euclidean_spearman |
|
value: 64.54376284777354 |
|
- type: manhattan_pearson |
|
value: 64.46392290759724 |
|
- type: manhattan_spearman |
|
value: 65.2496975447815 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: C-MTEB/STSB |
|
name: MTEB STSB |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 80.05773088991484 |
|
- type: cos_sim_spearman |
|
value: 80.71550237522008 |
|
- type: euclidean_pearson |
|
value: 80.31115977415573 |
|
- type: euclidean_spearman |
|
value: 80.71510951779365 |
|
- type: manhattan_pearson |
|
value: 80.25235514937249 |
|
- type: manhattan_spearman |
|
value: 80.65958309383224 |
|
- task: |
|
type: Reranking |
|
dataset: |
|
type: C-MTEB/T2Reranking |
|
name: MTEB T2Reranking |
|
config: default |
|
split: dev |
|
revision: None |
|
metrics: |
|
- type: map |
|
value: 66.18255262304848 |
|
- type: mrr |
|
value: 75.95393252087565 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: C-MTEB/T2Retrieval |
|
name: MTEB T2Retrieval |
|
config: default |
|
split: dev |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 28.651 |
|
- type: map_at_10 |
|
value: 76.281 |
|
- type: map_at_100 |
|
value: 80.018 |
|
- type: map_at_1000 |
|
value: 80.098 |
|
- type: map_at_3 |
|
value: 54.783 |
|
- type: map_at_5 |
|
value: 66.508 |
|
- type: mrr_at_1 |
|
value: 90.99199999999999 |
|
- type: mrr_at_10 |
|
value: 93.812 |
|
- type: mrr_at_100 |
|
value: 93.87100000000001 |
|
- type: mrr_at_1000 |
|
value: 93.87299999999999 |
|
- type: mrr_at_3 |
|
value: 93.415 |
|
- type: mrr_at_5 |
|
value: 93.685 |
|
- type: ndcg_at_1 |
|
value: 90.99199999999999 |
|
- type: ndcg_at_10 |
|
value: 84.57900000000001 |
|
- type: ndcg_at_100 |
|
value: 88.474 |
|
- type: ndcg_at_1000 |
|
value: 89.172 |
|
- type: ndcg_at_3 |
|
value: 86.56099999999999 |
|
- type: ndcg_at_5 |
|
value: 84.811 |
|
- type: precision_at_1 |
|
value: 90.99199999999999 |
|
- type: precision_at_10 |
|
value: 40.969 |
|
- type: precision_at_100 |
|
value: 4.97 |
|
- type: precision_at_1000 |
|
value: 0.515 |
|
- type: precision_at_3 |
|
value: 74.734 |
|
- type: precision_at_5 |
|
value: 61.980999999999995 |
|
- type: recall_at_1 |
|
value: 28.651 |
|
- type: recall_at_10 |
|
value: 83.321 |
|
- type: recall_at_100 |
|
value: 95.498 |
|
- type: recall_at_1000 |
|
value: 98.759 |
|
- type: recall_at_3 |
|
value: 56.708000000000006 |
|
- type: recall_at_5 |
|
value: 70.25200000000001 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: C-MTEB/TNews-classification |
|
name: MTEB TNews |
|
config: default |
|
split: validation |
|
revision: None |
|
metrics: |
|
- type: accuracy |
|
value: 52.037 |
|
- type: f1 |
|
value: 50.3832093595745 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: C-MTEB/ThuNewsClusteringP2P |
|
name: MTEB ThuNewsClusteringP2P |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: v_measure |
|
value: 70.09793315196697 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: C-MTEB/ThuNewsClusteringS2S |
|
name: MTEB ThuNewsClusteringS2S |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: v_measure |
|
value: 63.66930246094367 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: C-MTEB/VideoRetrieval |
|
name: MTEB VideoRetrieval |
|
config: default |
|
split: dev |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 60.4 |
|
- type: map_at_10 |
|
value: 69.878 |
|
- type: map_at_100 |
|
value: 70.285 |
|
- type: map_at_1000 |
|
value: 70.295 |
|
- type: map_at_3 |
|
value: 68.033 |
|
- type: map_at_5 |
|
value: 69.233 |
|
- type: mrr_at_1 |
|
value: 60.3 |
|
- type: mrr_at_10 |
|
value: 69.828 |
|
- type: mrr_at_100 |
|
value: 70.235 |
|
- type: mrr_at_1000 |
|
value: 70.245 |
|
- type: mrr_at_3 |
|
value: 67.983 |
|
- type: mrr_at_5 |
|
value: 69.18299999999999 |
|
- type: ndcg_at_1 |
|
value: 60.4 |
|
- type: ndcg_at_10 |
|
value: 74.155 |
|
- type: ndcg_at_100 |
|
value: 76.173 |
|
- type: ndcg_at_1000 |
|
value: 76.44800000000001 |
|
- type: ndcg_at_3 |
|
value: 70.44500000000001 |
|
- type: ndcg_at_5 |
|
value: 72.61800000000001 |
|
- type: precision_at_1 |
|
value: 60.4 |
|
- type: precision_at_10 |
|
value: 8.74 |
|
- type: precision_at_100 |
|
value: 0.9690000000000001 |
|
- type: precision_at_1000 |
|
value: 0.099 |
|
- type: precision_at_3 |
|
value: 25.8 |
|
- type: precision_at_5 |
|
value: 16.54 |
|
- type: recall_at_1 |
|
value: 60.4 |
|
- type: recall_at_10 |
|
value: 87.4 |
|
- type: recall_at_100 |
|
value: 96.89999999999999 |
|
- type: recall_at_1000 |
|
value: 99.1 |
|
- type: recall_at_3 |
|
value: 77.4 |
|
- type: recall_at_5 |
|
value: 82.69999999999999 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: C-MTEB/waimai-classification |
|
name: MTEB Waimai |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: accuracy |
|
value: 88.49000000000001 |
|
- type: ap |
|
value: 73.5441395538586 |
|
- type: f1 |
|
value: 86.88114969870975 |
|
--- |
|
|
|
|
|
# alime-embedding-large-zh |
|
|
|
The alime embedding model. |
|
|
|
<!--- Describe your model here --> |
|
|
|
## Usage (Sentence-Transformers) |
|
|
|
Using this model becomes easy when you have [sentence-transformers](https://www.SBERT.net) installed: |
|
|
|
``` |
|
pip install -U sentence-transformers |
|
``` |
|
|
|
Then you can use the model like this: |
|
|
|
```python |
|
from sentence_transformers import SentenceTransformer |
|
sentences = ["西湖在哪？", "西湖风景名胜区位于浙江省杭州市"] |
|
|
|
model = SentenceTransformer('Pristinenlp/alime-embedding-large-zh') |
|
embeddings = model.encode(sentences, normalize_embeddings=True) |
|
print(embeddings) |
|
``` |
