|
--- |
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tags: |
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- mteb |
|
model-index: |
|
- name: piccolo-large-zh-v2 |
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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: 56.76055988260572 |
|
- type: cos_sim_spearman |
|
value: 61.49271876861677 |
|
- type: euclidean_pearson |
|
value: 59.14524585320711 |
|
- type: euclidean_spearman |
|
value: 60.63579339225774 |
|
- type: manhattan_pearson |
|
value: 59.14662752965445 |
|
- type: manhattan_spearman |
|
value: 60.635190265737904 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: C-MTEB/ATEC |
|
name: MTEB ATEC |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 56.21706298831197 |
|
- type: cos_sim_spearman |
|
value: 59.19831457688953 |
|
- type: euclidean_pearson |
|
value: 62.37752017633299 |
|
- type: euclidean_spearman |
|
value: 58.79400967473204 |
|
- type: manhattan_pearson |
|
value: 62.37015943212308 |
|
- type: manhattan_spearman |
|
value: 58.79232537600814 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: mteb/amazon_reviews_multi |
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name: MTEB AmazonReviewsClassification (zh) |
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config: zh |
|
split: test |
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revision: 1399c76144fd37290681b995c656ef9b2e06e26d |
|
metrics: |
|
- type: accuracy |
|
value: 49.440000000000005 |
|
- type: f1 |
|
value: 46.67381446305019 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: C-MTEB/BQ |
|
name: MTEB BQ |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 70.99026329599994 |
|
- type: cos_sim_spearman |
|
value: 72.87565357908989 |
|
- type: euclidean_pearson |
|
value: 71.17690439270028 |
|
- type: euclidean_spearman |
|
value: 72.50428109969029 |
|
- type: manhattan_pearson |
|
value: 71.17262321033088 |
|
- type: manhattan_spearman |
|
value: 72.49845447987437 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: C-MTEB/CLSClusteringP2P |
|
name: MTEB CLSClusteringP2P |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: v_measure |
|
value: 57.92713421071616 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: C-MTEB/CLSClusteringS2S |
|
name: MTEB CLSClusteringS2S |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: v_measure |
|
value: 48.096546680932235 |
|
- task: |
|
type: Reranking |
|
dataset: |
|
type: C-MTEB/CMedQAv1-reranking |
|
name: MTEB CMedQAv1 |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map |
|
value: 89.31003741715936 |
|
- type: mrr |
|
value: 91.38075396825397 |
|
- task: |
|
type: Reranking |
|
dataset: |
|
type: C-MTEB/CMedQAv2-reranking |
|
name: MTEB CMedQAv2 |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map |
|
value: 90.13769781784876 |
|
- type: mrr |
|
value: 92.14329365079365 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: C-MTEB/CmedqaRetrieval |
|
name: MTEB CmedqaRetrieval |
|
config: default |
|
split: dev |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 26.931 |
|
- type: map_at_10 |
|
value: 40.647 |
|
- type: map_at_100 |
|
value: 42.519 |
|
- type: map_at_1000 |
|
value: 42.616 |
|
- type: map_at_3 |
|
value: 36.144999999999996 |
|
- type: map_at_5 |
|
value: 38.717 |
|
- type: mrr_at_1 |
|
value: 40.935 |
|
- type: mrr_at_10 |
|
value: 49.684 |
|
- type: mrr_at_100 |
|
value: 50.598 |
|
- type: mrr_at_1000 |
|
value: 50.632999999999996 |
|
- type: mrr_at_3 |
|
value: 47.07 |
|
- type: mrr_at_5 |
|
value: 48.49 |
|
- type: ndcg_at_1 |
|
value: 40.935 |
|
- type: ndcg_at_10 |
|
value: 47.583999999999996 |
|
- type: ndcg_at_100 |
|
value: 54.69199999999999 |
|
- type: ndcg_at_1000 |
|
value: 56.314 |
|
- type: ndcg_at_3 |
|
value: 41.973 |
|
- type: ndcg_at_5 |
|
value: 44.334 |
|
- type: precision_at_1 |
|
value: 40.935 |
|
- type: precision_at_10 |
|
value: 10.585 |
|
- type: precision_at_100 |
|
value: 1.637 |
|
- type: precision_at_1000 |
|
value: 0.184 |
|
- type: precision_at_3 |
|
value: 23.881 |
|
- type: precision_at_5 |
|
value: 17.399 |
|
- type: recall_at_1 |
|
value: 26.931 |
|
- type: recall_at_10 |
|
value: 59.006 |
|
- type: recall_at_100 |
|
value: 88.247 |
|
- type: recall_at_1000 |
|
value: 99.045 |
|
- type: recall_at_3 |
|
value: 42.064 |
|
- type: recall_at_5 |
|
value: 49.266 |
|
- task: |
|
type: PairClassification |
|
dataset: |
|
type: C-MTEB/CMNLI |
|
name: MTEB Cmnli |
|
config: default |
|
split: validation |
|
revision: None |
|
metrics: |
|
- type: cos_sim_accuracy |
|
value: 86.08538785327721 |
|
- type: cos_sim_ap |
|
value: 92.64373114205229 |
|
- type: cos_sim_f1 |
|
value: 86.89951395953432 |
|
- type: cos_sim_precision |
|
value: 84.11378555798687 |
|
- type: cos_sim_recall |
|
value: 89.87608136544307 |
|
- type: dot_accuracy |
|
value: 72.66386049308478 |
|
- type: dot_ap |
|
value: 81.053422935767 |
|
- type: dot_f1 |
|
value: 75.19933726830277 |
|
- type: dot_precision |
|
value: 67.4907063197026 |
|
- type: dot_recall |
|
value: 84.89595510872107 |
|
- type: euclidean_accuracy |
|
value: 85.52014431749849 |
|
- type: euclidean_ap |
|
value: 91.90647782899615 |
|
- type: euclidean_f1 |
|
value: 86.26361413647477 |
|
- type: euclidean_precision |
|
value: 82.2071595001059 |
|
- type: euclidean_recall |
|
value: 90.74117371989713 |
|
- type: manhattan_accuracy |
|
value: 85.48406494287433 |
|
- type: manhattan_ap |
|
value: 91.89657919524385 |
|
- type: manhattan_f1 |
|
value: 86.20413761572752 |
|
- type: manhattan_precision |
|
value: 84.324686940966 |
|
- type: manhattan_recall |
|
value: 88.16927753097966 |
|
- type: max_accuracy |
|
value: 86.08538785327721 |
|
- type: max_ap |
|
value: 92.64373114205229 |
|
- type: max_f1 |
|
value: 86.89951395953432 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: C-MTEB/CovidRetrieval |
|
name: MTEB CovidRetrieval |
|
config: default |
|
split: dev |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 75.50099999999999 |
|
- type: map_at_10 |
|
value: 83.43 |
|
- type: map_at_100 |
|
value: 83.577 |
|
- type: map_at_1000 |
|
value: 83.57900000000001 |
|
- type: map_at_3 |
|
value: 82.06400000000001 |
|
- type: map_at_5 |
|
value: 82.88600000000001 |
|
- type: mrr_at_1 |
|
value: 75.869 |
|
- type: mrr_at_10 |
|
value: 83.536 |
|
- type: mrr_at_100 |
|
value: 83.682 |
|
- type: mrr_at_1000 |
|
value: 83.68299999999999 |
|
- type: mrr_at_3 |
|
value: 82.244 |
|
- type: mrr_at_5 |
|
value: 82.998 |
|
- type: ndcg_at_1 |
|
value: 75.764 |
|
- type: ndcg_at_10 |
|
value: 86.777 |
|
- type: ndcg_at_100 |
|
value: 87.36 |
|
- type: ndcg_at_1000 |
|
value: 87.424 |
|
- type: ndcg_at_3 |
|
value: 84.10300000000001 |
|
- type: ndcg_at_5 |
|
value: 85.532 |
|
- type: precision_at_1 |
|
value: 75.764 |
|
- type: precision_at_10 |
|
value: 9.8 |
|
- type: precision_at_100 |
|
value: 1.005 |
|
- type: precision_at_1000 |
|
value: 0.101 |
|
- type: precision_at_3 |
|
value: 30.207 |
|
- type: precision_at_5 |
|
value: 18.82 |
|
- type: recall_at_1 |
|
value: 75.50099999999999 |
|
- type: recall_at_10 |
|
value: 96.997 |
|
- type: recall_at_100 |
|
value: 99.473 |
|
- type: recall_at_1000 |
|
value: 100.0 |
|
- type: recall_at_3 |
|
value: 89.831 |
|
- type: recall_at_5 |
|
value: 93.256 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: C-MTEB/DuRetrieval |
|
name: MTEB DuRetrieval |
|
config: default |
|
split: dev |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 27.094 |
|
- type: map_at_10 |
|
value: 82.418 |
|
- type: map_at_100 |
|
value: 85.05 |
|
- type: map_at_1000 |
|
value: 85.083 |
|
- type: map_at_3 |
|
value: 57.68600000000001 |
|
- type: map_at_5 |
|
value: 72.476 |
|
- type: mrr_at_1 |
|
value: 92.25 |
|
- type: mrr_at_10 |
|
value: 94.621 |
|
- type: mrr_at_100 |
|
value: 94.675 |
|
- type: mrr_at_1000 |
|
value: 94.677 |
|
- type: mrr_at_3 |
|
value: 94.375 |
|
- type: mrr_at_5 |
|
value: 94.52199999999999 |
|
- type: ndcg_at_1 |
|
value: 92.25 |
|
- type: ndcg_at_10 |
|
value: 89.13600000000001 |
|
- type: ndcg_at_100 |
|
value: 91.532 |
|
- type: ndcg_at_1000 |
|
value: 91.836 |
|
- type: ndcg_at_3 |
|
value: 88.50099999999999 |
|
- type: ndcg_at_5 |
|
value: 87.251 |
|
- type: precision_at_1 |
|
value: 92.25 |
|
- type: precision_at_10 |
|
value: 42.295 |
|
- type: precision_at_100 |
|
value: 4.812 |
|
- type: precision_at_1000 |
|
value: 0.48900000000000005 |
|
- type: precision_at_3 |
|
value: 79.167 |
|
- type: precision_at_5 |
|
value: 66.56 |
|
- type: recall_at_1 |
|
value: 27.094 |
|
- type: recall_at_10 |
|
value: 89.816 |
|
- type: recall_at_100 |
|
value: 97.855 |
|
- type: recall_at_1000 |
|
value: 99.384 |
|
- type: recall_at_3 |
|
value: 59.557 |
|
- type: recall_at_5 |
|
value: 76.395 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: C-MTEB/EcomRetrieval |
|
name: MTEB EcomRetrieval |
|
config: default |
|
split: dev |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 53.6 |
|
- type: map_at_10 |
|
value: 62.985 |
|
- type: map_at_100 |
|
value: 63.532999999999994 |
|
- type: map_at_1000 |
|
value: 63.546 |
|
- type: map_at_3 |
|
value: 60.617 |
|
- type: map_at_5 |
|
value: 62.017 |
|
- type: mrr_at_1 |
|
value: 53.6 |
|
- type: mrr_at_10 |
|
value: 62.985 |
|
- type: mrr_at_100 |
|
value: 63.532999999999994 |
|
- type: mrr_at_1000 |
|
value: 63.546 |
|
- type: mrr_at_3 |
|
value: 60.617 |
|
- type: mrr_at_5 |
|
value: 62.017 |
|
- type: ndcg_at_1 |
|
value: 53.6 |
|
- type: ndcg_at_10 |
|
value: 67.755 |
|
- type: ndcg_at_100 |
|
value: 70.366 |
|
- type: ndcg_at_1000 |
|
value: 70.696 |
|
- type: ndcg_at_3 |
|
value: 62.89900000000001 |
|
- type: ndcg_at_5 |
|
value: 65.437 |
|
- type: precision_at_1 |
|
value: 53.6 |
|
- type: precision_at_10 |
|
value: 8.28 |
|
- type: precision_at_100 |
|
value: 0.9490000000000001 |
|
- type: precision_at_1000 |
|
value: 0.098 |
|
- type: precision_at_3 |
|
value: 23.166999999999998 |
|
- type: precision_at_5 |
|
value: 15.14 |
|
- type: recall_at_1 |
|
value: 53.6 |
|
- type: recall_at_10 |
|
value: 82.8 |
|
- type: recall_at_100 |
|
value: 94.89999999999999 |
|
- type: recall_at_1000 |
|
value: 97.5 |
|
- type: recall_at_3 |
|
value: 69.5 |
|
- type: recall_at_5 |
|
value: 75.7 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: C-MTEB/IFlyTek-classification |
|
name: MTEB IFlyTek |
|
config: default |
|
split: validation |
|
revision: None |
|
metrics: |
|
- type: accuracy |
|
value: 52.104655636783384 |
|
- type: f1 |
|
value: 41.025743582860514 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: C-MTEB/JDReview-classification |
|
name: MTEB JDReview |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: accuracy |
|
value: 88.57410881801127 |
|
- type: ap |
|
value: 59.49612312498937 |
|
- type: f1 |
|
value: 83.70595013666741 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: C-MTEB/LCQMC |
|
name: MTEB LCQMC |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 74.00327736048256 |
|
- type: cos_sim_spearman |
|
value: 79.5459672237356 |
|
- type: euclidean_pearson |
|
value: 79.18300205389669 |
|
- type: euclidean_spearman |
|
value: 79.21872988987533 |
|
- type: manhattan_pearson |
|
value: 79.1715470733081 |
|
- type: manhattan_spearman |
|
value: 79.20756273498812 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: C-MTEB/MMarcoRetrieval |
|
name: MTEB MMarcoRetrieval |
|
config: default |
|
split: dev |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 66.94600000000001 |
|
- type: map_at_10 |
|
value: 75.947 |
|
- type: map_at_100 |
|
value: 76.268 |
|
- type: map_at_1000 |
|
value: 76.28 |
|
- type: map_at_3 |
|
value: 74.13300000000001 |
|
- type: map_at_5 |
|
value: 75.28399999999999 |
|
- type: mrr_at_1 |
|
value: 69.241 |
|
- type: mrr_at_10 |
|
value: 76.532 |
|
- type: mrr_at_100 |
|
value: 76.816 |
|
- type: mrr_at_1000 |
|
value: 76.827 |
|
- type: mrr_at_3 |
|
value: 74.95 |
|
- type: mrr_at_5 |
|
value: 75.957 |
|
- type: ndcg_at_1 |
|
value: 69.241 |
|
- type: ndcg_at_10 |
|
value: 79.54299999999999 |
|
- type: ndcg_at_100 |
|
value: 80.95 |
|
- type: ndcg_at_1000 |
|
value: 81.252 |
|
- type: ndcg_at_3 |
|
value: 76.119 |
|
- type: ndcg_at_5 |
|
value: 78.069 |
|
- type: precision_at_1 |
|
value: 69.241 |
|
- type: precision_at_10 |
|
value: 9.576 |
|
- type: precision_at_100 |
|
value: 1.026 |
|
- type: precision_at_1000 |
|
value: 0.105 |
|
- type: precision_at_3 |
|
value: 28.571999999999996 |
|
- type: precision_at_5 |
|
value: 18.181 |
|
- type: recall_at_1 |
|
value: 66.94600000000001 |
|
- type: recall_at_10 |
|
value: 90.024 |
|
- type: recall_at_100 |
|
value: 96.3 |
|
- type: recall_at_1000 |
|
value: 98.656 |
|
- type: recall_at_3 |
|
value: 81.026 |
|
- type: recall_at_5 |
|
value: 85.658 |
|
- 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: 77.71015467383997 |
|
- type: f1 |
|
value: 74.32345894845358 |
|
- 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: 85.63214525891055 |
|
- type: f1 |
|
value: 84.65303466003252 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: C-MTEB/MedicalRetrieval |
|
name: MTEB MedicalRetrieval |
|
config: default |
|
split: dev |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 55.50000000000001 |
|
- type: map_at_10 |
|
value: 61.66199999999999 |
|
- type: map_at_100 |
|
value: 62.13999999999999 |
|
- type: map_at_1000 |
|
value: 62.187000000000005 |
|
- type: map_at_3 |
|
value: 59.967000000000006 |
|
- type: map_at_5 |
|
value: 60.927 |
|
- type: mrr_at_1 |
|
value: 55.7 |
|
- type: mrr_at_10 |
|
value: 61.76199999999999 |
|
- type: mrr_at_100 |
|
value: 62.241 |
|
- type: mrr_at_1000 |
|
value: 62.287000000000006 |
|
- type: mrr_at_3 |
|
value: 60.06700000000001 |
|
- type: mrr_at_5 |
|
value: 61.027 |
|
- type: ndcg_at_1 |
|
value: 55.50000000000001 |
|
- type: ndcg_at_10 |
|
value: 64.878 |
|
- type: ndcg_at_100 |
|
value: 67.464 |
|
- type: ndcg_at_1000 |
|
value: 68.745 |
|
- type: ndcg_at_3 |
|
value: 61.367000000000004 |
|
- type: ndcg_at_5 |
|
value: 63.117999999999995 |
|
- type: precision_at_1 |
|
value: 55.50000000000001 |
|
- type: precision_at_10 |
|
value: 7.51 |
|
- type: precision_at_100 |
|
value: 0.878 |
|
- type: precision_at_1000 |
|
value: 0.098 |
|
- type: precision_at_3 |
|
value: 21.8 |
|
- type: precision_at_5 |
|
value: 13.94 |
|
- type: recall_at_1 |
|
value: 55.50000000000001 |
|
- type: recall_at_10 |
|
value: 75.1 |
|
- type: recall_at_100 |
|
value: 87.8 |
|
- type: recall_at_1000 |
|
value: 97.89999999999999 |
|
- type: recall_at_3 |
|
value: 65.4 |
|
- type: recall_at_5 |
|
value: 69.69999999999999 |
|
- task: |
|
type: Reranking |
|
dataset: |
|
type: C-MTEB/Mmarco-reranking |
|
name: MTEB MMarcoReranking |
|
config: default |
|
split: dev |
|
revision: None |
|
metrics: |
|
- type: map |
|
value: 33.386980266936106 |
|
- type: mrr |
|
value: 32.11904761904762 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: C-MTEB/MultilingualSentiment-classification |
|
name: MTEB MultilingualSentiment |
|
config: default |
|
split: validation |
|
revision: None |
|
metrics: |
|
- type: accuracy |
|
value: 79.08666666666666 |
|
- type: f1 |
|
value: 78.93142205976953 |
|
- task: |
|
type: PairClassification |
|
dataset: |
|
type: C-MTEB/OCNLI |
|
name: MTEB Ocnli |
|
config: default |
|
split: validation |
|
revision: None |
|
metrics: |
|
- type: cos_sim_accuracy |
|
value: 84.35300487276665 |
|
- type: cos_sim_ap |
|
value: 87.83572265803564 |
|
- type: cos_sim_f1 |
|
value: 85.42713567839195 |
|
- type: cos_sim_precision |
|
value: 81.49568552253116 |
|
- type: cos_sim_recall |
|
value: 89.7571277719113 |
|
- type: dot_accuracy |
|
value: 72.87493232268544 |
|
- type: dot_ap |
|
value: 80.29032993894747 |
|
- type: dot_f1 |
|
value: 76.5938475256353 |
|
- type: dot_precision |
|
value: 66.28086419753086 |
|
- type: dot_recall |
|
value: 90.70749736008447 |
|
- type: euclidean_accuracy |
|
value: 82.34975636166757 |
|
- type: euclidean_ap |
|
value: 85.73873757468064 |
|
- type: euclidean_f1 |
|
value: 83.56713426853707 |
|
- type: euclidean_precision |
|
value: 79.50428979980934 |
|
- type: euclidean_recall |
|
value: 88.0675818373812 |
|
- type: manhattan_accuracy |
|
value: 82.45804006497022 |
|
- type: manhattan_ap |
|
value: 85.7176464290469 |
|
- type: manhattan_f1 |
|
value: 83.65095285857572 |
|
- type: manhattan_precision |
|
value: 79.65616045845272 |
|
- type: manhattan_recall |
|
value: 88.0675818373812 |
|
- type: max_accuracy |
|
value: 84.35300487276665 |
|
- type: max_ap |
|
value: 87.83572265803564 |
|
- type: max_f1 |
|
value: 85.42713567839195 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: C-MTEB/OnlineShopping-classification |
|
name: MTEB OnlineShopping |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: accuracy |
|
value: 94.61999999999999 |
|
- type: ap |
|
value: 92.74140430219491 |
|
- type: f1 |
|
value: 94.60775857122515 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: C-MTEB/PAWSX |
|
name: MTEB PAWSX |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 39.75749234575995 |
|
- type: cos_sim_spearman |
|
value: 46.48035295363829 |
|
- type: euclidean_pearson |
|
value: 45.38711981599582 |
|
- type: euclidean_spearman |
|
value: 46.13915356562481 |
|
- type: manhattan_pearson |
|
value: 45.420770530489065 |
|
- type: manhattan_spearman |
|
value: 46.179913441143775 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: C-MTEB/QBQTC |
|
name: MTEB QBQTC |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 44.02008249965321 |
|
- type: cos_sim_spearman |
|
value: 45.906917552219156 |
|
- type: euclidean_pearson |
|
value: 36.600317631983316 |
|
- type: euclidean_spearman |
|
value: 41.97740958824762 |
|
- type: manhattan_pearson |
|
value: 36.54329048509785 |
|
- type: manhattan_spearman |
|
value: 41.91222171040451 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: mteb/sts22-crosslingual-sts |
|
name: MTEB STS22 (zh) |
|
config: zh |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 60.97044608578288 |
|
- type: cos_sim_spearman |
|
value: 63.76187490245927 |
|
- type: euclidean_pearson |
|
value: 60.74245987426317 |
|
- type: euclidean_spearman |
|
value: 63.32990713078846 |
|
- type: manhattan_pearson |
|
value: 60.62422616577702 |
|
- type: manhattan_spearman |
|
value: 63.256612476686826 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: C-MTEB/STSB |
|
name: MTEB STSB |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 76.28185867362305 |
|
- type: cos_sim_spearman |
|
value: 78.71478656159289 |
|
- type: euclidean_pearson |
|
value: 79.80734359535234 |
|
- type: euclidean_spearman |
|
value: 79.85403491297063 |
|
- type: manhattan_pearson |
|
value: 79.79454037962215 |
|
- type: manhattan_spearman |
|
value: 79.82796402623201 |
|
- task: |
|
type: Reranking |
|
dataset: |
|
type: C-MTEB/T2Reranking |
|
name: MTEB T2Reranking |
|
config: default |
|
split: dev |
|
revision: None |
|
metrics: |
|
- type: map |
|
value: 67.14759526113295 |
|
- type: mrr |
|
value: 77.36422096484723 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: C-MTEB/T2Retrieval |
|
name: MTEB T2Retrieval |
|
config: default |
|
split: dev |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 28.177999999999997 |
|
- type: map_at_10 |
|
value: 78.77199999999999 |
|
- type: map_at_100 |
|
value: 82.365 |
|
- type: map_at_1000 |
|
value: 82.422 |
|
- type: map_at_3 |
|
value: 55.452999999999996 |
|
- type: map_at_5 |
|
value: 68.12700000000001 |
|
- type: mrr_at_1 |
|
value: 91.097 |
|
- type: mrr_at_10 |
|
value: 93.52000000000001 |
|
- type: mrr_at_100 |
|
value: 93.587 |
|
- type: mrr_at_1000 |
|
value: 93.589 |
|
- type: mrr_at_3 |
|
value: 93.136 |
|
- type: mrr_at_5 |
|
value: 93.381 |
|
- type: ndcg_at_1 |
|
value: 91.097 |
|
- type: ndcg_at_10 |
|
value: 86.136 |
|
- type: ndcg_at_100 |
|
value: 89.515 |
|
- type: ndcg_at_1000 |
|
value: 90.049 |
|
- type: ndcg_at_3 |
|
value: 87.41600000000001 |
|
- type: ndcg_at_5 |
|
value: 86.115 |
|
- type: precision_at_1 |
|
value: 91.097 |
|
- type: precision_at_10 |
|
value: 42.597 |
|
- type: precision_at_100 |
|
value: 5.043 |
|
- type: precision_at_1000 |
|
value: 0.517 |
|
- type: precision_at_3 |
|
value: 76.239 |
|
- type: precision_at_5 |
|
value: 63.93 |
|
- type: recall_at_1 |
|
value: 28.177999999999997 |
|
- type: recall_at_10 |
|
value: 85.182 |
|
- type: recall_at_100 |
|
value: 96.174 |
|
- type: recall_at_1000 |
|
value: 98.848 |
|
- type: recall_at_3 |
|
value: 57.150999999999996 |
|
- type: recall_at_5 |
|
value: 71.50999999999999 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: C-MTEB/TNews-classification |
|
name: MTEB TNews |
|
config: default |
|
split: validation |
|
revision: None |
|
metrics: |
|
- type: accuracy |
|
value: 54.521 |
|
- type: f1 |
|
value: 52.53528052282081 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: C-MTEB/ThuNewsClusteringP2P |
|
name: MTEB ThuNewsClusteringP2P |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: v_measure |
|
value: 74.2003249023509 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: C-MTEB/ThuNewsClusteringS2S |
|
name: MTEB ThuNewsClusteringS2S |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: v_measure |
|
value: 68.4277378629746 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: C-MTEB/VideoRetrieval |
|
name: MTEB VideoRetrieval |
|
config: default |
|
split: dev |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 58.599999999999994 |
|
- type: map_at_10 |
|
value: 68.671 |
|
- type: map_at_100 |
|
value: 69.148 |
|
- type: map_at_1000 |
|
value: 69.157 |
|
- type: map_at_3 |
|
value: 66.9 |
|
- type: map_at_5 |
|
value: 68.045 |
|
- type: mrr_at_1 |
|
value: 58.599999999999994 |
|
- type: mrr_at_10 |
|
value: 68.671 |
|
- type: mrr_at_100 |
|
value: 69.148 |
|
- type: mrr_at_1000 |
|
value: 69.157 |
|
- type: mrr_at_3 |
|
value: 66.9 |
|
- type: mrr_at_5 |
|
value: 68.045 |
|
- type: ndcg_at_1 |
|
value: 58.599999999999994 |
|
- type: ndcg_at_10 |
|
value: 73.099 |
|
- type: ndcg_at_100 |
|
value: 75.33 |
|
- type: ndcg_at_1000 |
|
value: 75.58500000000001 |
|
- type: ndcg_at_3 |
|
value: 69.502 |
|
- type: ndcg_at_5 |
|
value: 71.542 |
|
- type: precision_at_1 |
|
value: 58.599999999999994 |
|
- type: precision_at_10 |
|
value: 8.68 |
|
- type: precision_at_100 |
|
value: 0.97 |
|
- type: precision_at_1000 |
|
value: 0.099 |
|
- type: precision_at_3 |
|
value: 25.667 |
|
- type: precision_at_5 |
|
value: 16.38 |
|
- type: recall_at_1 |
|
value: 58.599999999999994 |
|
- type: recall_at_10 |
|
value: 86.8 |
|
- type: recall_at_100 |
|
value: 97.0 |
|
- type: recall_at_1000 |
|
value: 99.1 |
|
- type: recall_at_3 |
|
value: 77.0 |
|
- type: recall_at_5 |
|
value: 81.89999999999999 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: C-MTEB/waimai-classification |
|
name: MTEB Waimai |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: accuracy |
|
value: 89.58999999999999 |
|
- type: ap |
|
value: 75.69899834265364 |
|
- type: f1 |
|
value: 88.2026184757175 |
|
--- |
|
|
|
**新闻 | News** |
|
|
|
**[2024-04-22]** |
|
|
|
piccolo-large-zh-v2 目前在C-MTEB榜单取得第一名，领先上一名BERT模型约1.9个点。 |
|
|
|
piccolo-large-zh-v2 currently ranks first on the C-MTEB list, leading the previous BERT model by about 1.9 points. |
|
|
|
## piccolo-large-zh-v2 |
|
|
|
piccolo-large-zh-v2 是一个通用embedding模型(中文), 由来自商汤科技的通用模型组完成训练，此次piccolo升级旨在更多地关注通用的下游finetune方式。我们将在近期更新我们的技术报告，同时详细技术细节也将在商汤4.23技术交流日披露: https://www.sensetime.com/cn |
|
|
|
piccolo-large-zh-v2 is a Chinese embedding model developed by the general model group at SenseTime Research. This upgraded version of Piccolo aims to prioritize general downstream fine-tuning methods. We plan to release an updated technical report in the near future, and further technical details will be disclosed during the SenseTime Tech Day on April 23rd: https://www.sensetime.com/cn |
|
|
|
## Usage |
|
目前该模型暂时需要通过API来进行访问: https://platform.sensenova.cn/doc?path=/chat/Embeddings/Embeddings.md |
|
|
|
Currently, the model needs to be accessed through API: https://platform.sensenova.cn/doc?path=/chat/Embeddings/Embeddings.md |
|
|
