|
--- |
|
pipeline_tag: sentence-similarity |
|
tags: |
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- sentence-transformers |
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- feature-extraction |
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- sentence-similarity |
|
- mteb |
|
model-index: |
|
- name: tao |
|
results: |
|
- task: |
|
type: STS |
|
dataset: |
|
type: C-MTEB/AFQMC |
|
name: MTEB AFQMC |
|
config: default |
|
split: validation |
|
revision: None |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 47.33752515292192 |
|
- type: cos_sim_spearman |
|
value: 49.940772056837176 |
|
- type: euclidean_pearson |
|
value: 48.12147487857213 |
|
- type: euclidean_spearman |
|
value: 49.9407519488174 |
|
- type: manhattan_pearson |
|
value: 48.07550286372865 |
|
- type: manhattan_spearman |
|
value: 49.89535645392862 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: C-MTEB/ATEC |
|
name: MTEB ATEC |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 50.976865711125626 |
|
- type: cos_sim_spearman |
|
value: 53.113084748593465 |
|
- type: euclidean_pearson |
|
value: 55.1209592747571 |
|
- type: euclidean_spearman |
|
value: 53.11308362230699 |
|
- type: manhattan_pearson |
|
value: 55.09799309322416 |
|
- type: manhattan_spearman |
|
value: 53.108059998577076 |
|
- 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: 40.812 |
|
- type: f1 |
|
value: 39.02060856097395 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: C-MTEB/BQ |
|
name: MTEB BQ |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 62.84336868097746 |
|
- type: cos_sim_spearman |
|
value: 65.540605433497 |
|
- type: euclidean_pearson |
|
value: 64.08759819387913 |
|
- type: euclidean_spearman |
|
value: 65.54060543369363 |
|
- type: manhattan_pearson |
|
value: 64.09334283385029 |
|
- type: manhattan_spearman |
|
value: 65.55376209169398 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: C-MTEB/CLSClusteringP2P |
|
name: MTEB CLSClusteringP2P |
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config: default |
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split: test |
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revision: None |
|
metrics: |
|
- type: v_measure |
|
value: 39.964020691388505 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: C-MTEB/CLSClusteringS2S |
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name: MTEB CLSClusteringS2S |
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config: default |
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split: test |
|
revision: None |
|
metrics: |
|
- type: v_measure |
|
value: 38.18628830038994 |
|
- task: |
|
type: Reranking |
|
dataset: |
|
type: C-MTEB/CMedQAv1-reranking |
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name: MTEB CMedQAv1 |
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config: default |
|
split: test |
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revision: None |
|
metrics: |
|
- type: map |
|
value: 85.34294439514511 |
|
- type: mrr |
|
value: 88.03849206349206 |
|
- task: |
|
type: Reranking |
|
dataset: |
|
type: C-MTEB/CMedQAv2-reranking |
|
name: MTEB CMedQAv2 |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map |
|
value: 85.87127698007234 |
|
- type: mrr |
|
value: 88.57980158730159 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: C-MTEB/CmedqaRetrieval |
|
name: MTEB CmedqaRetrieval |
|
config: default |
|
split: dev |
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revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 24.484 |
|
- type: map_at_10 |
|
value: 36.3 |
|
- type: map_at_100 |
|
value: 38.181 |
|
- type: map_at_1000 |
|
value: 38.305 |
|
- type: map_at_3 |
|
value: 32.39 |
|
- type: map_at_5 |
|
value: 34.504000000000005 |
|
- type: mrr_at_1 |
|
value: 37.608999999999995 |
|
- type: mrr_at_10 |
|
value: 45.348 |
|
- type: mrr_at_100 |
|
value: 46.375 |
|
- type: mrr_at_1000 |
|
value: 46.425 |
|
- type: mrr_at_3 |
|
value: 42.969 |
|
- type: mrr_at_5 |
|
value: 44.285999999999994 |
|
- type: ndcg_at_1 |
|
value: 37.608999999999995 |
|
- type: ndcg_at_10 |
|
value: 42.675999999999995 |
|
- type: ndcg_at_100 |
|
value: 50.12799999999999 |
|
- type: ndcg_at_1000 |
|
value: 52.321 |
|
- type: ndcg_at_3 |
|
value: 37.864 |
|
- type: ndcg_at_5 |
|
value: 39.701 |
|
- type: precision_at_1 |
|
value: 37.608999999999995 |
|
- type: precision_at_10 |
|
value: 9.527 |
|
- type: precision_at_100 |
|
value: 1.555 |
|
- type: precision_at_1000 |
|
value: 0.183 |
|
- type: precision_at_3 |
|
value: 21.547 |
|
- type: precision_at_5 |
|
value: 15.504000000000001 |
|
- type: recall_at_1 |
|
value: 24.484 |
|
- type: recall_at_10 |
|
value: 52.43299999999999 |
|
- type: recall_at_100 |
|
value: 83.446 |
|
- type: recall_at_1000 |
|
value: 98.24199999999999 |
|
- type: recall_at_3 |
|
value: 37.653 |
|
- type: recall_at_5 |
|
value: 43.643 |
|
- task: |
|
type: PairClassification |
|
dataset: |
|
type: C-MTEB/CMNLI |
|
name: MTEB Cmnli |
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config: default |
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split: validation |
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revision: None |
|
metrics: |
|
- type: cos_sim_accuracy |
|
value: 77.71497294046902 |
|
- type: cos_sim_ap |
|
value: 86.84542027578229 |
|
- type: cos_sim_f1 |
|
value: 79.31987247608926 |
|
- type: cos_sim_precision |
|
value: 72.70601987142022 |
|
- type: cos_sim_recall |
|
value: 87.2574234276362 |
|
- type: dot_accuracy |
|
value: 77.71497294046902 |
|
- type: dot_ap |
|
value: 86.86514752961159 |
|
- type: dot_f1 |
|
value: 79.31987247608926 |
|
- type: dot_precision |
|
value: 72.70601987142022 |
|
- type: dot_recall |
|
value: 87.2574234276362 |
|
- type: euclidean_accuracy |
|
value: 77.71497294046902 |
|
- type: euclidean_ap |
|
value: 86.84541456571337 |
|
- type: euclidean_f1 |
|
value: 79.31987247608926 |
|
- type: euclidean_precision |
|
value: 72.70601987142022 |
|
- type: euclidean_recall |
|
value: 87.2574234276362 |
|
- type: manhattan_accuracy |
|
value: 77.8111846061335 |
|
- type: manhattan_ap |
|
value: 86.81148050422539 |
|
- type: manhattan_f1 |
|
value: 79.41176470588236 |
|
- type: manhattan_precision |
|
value: 72.52173913043478 |
|
- type: manhattan_recall |
|
value: 87.74842179097499 |
|
- type: max_accuracy |
|
value: 77.8111846061335 |
|
- type: max_ap |
|
value: 86.86514752961159 |
|
- type: max_f1 |
|
value: 79.41176470588236 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: C-MTEB/CovidRetrieval |
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name: MTEB CovidRetrieval |
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config: default |
|
split: dev |
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revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 68.862 |
|
- type: map_at_10 |
|
value: 77.079 |
|
- type: map_at_100 |
|
value: 77.428 |
|
- type: map_at_1000 |
|
value: 77.432 |
|
- type: map_at_3 |
|
value: 75.40400000000001 |
|
- type: map_at_5 |
|
value: 76.227 |
|
- type: mrr_at_1 |
|
value: 69.02000000000001 |
|
- type: mrr_at_10 |
|
value: 77.04299999999999 |
|
- type: mrr_at_100 |
|
value: 77.391 |
|
- type: mrr_at_1000 |
|
value: 77.395 |
|
- type: mrr_at_3 |
|
value: 75.44800000000001 |
|
- type: mrr_at_5 |
|
value: 76.23299999999999 |
|
- type: ndcg_at_1 |
|
value: 69.02000000000001 |
|
- type: ndcg_at_10 |
|
value: 80.789 |
|
- type: ndcg_at_100 |
|
value: 82.27499999999999 |
|
- type: ndcg_at_1000 |
|
value: 82.381 |
|
- type: ndcg_at_3 |
|
value: 77.40599999999999 |
|
- type: ndcg_at_5 |
|
value: 78.87100000000001 |
|
- type: precision_at_1 |
|
value: 69.02000000000001 |
|
- type: precision_at_10 |
|
value: 9.336 |
|
- type: precision_at_100 |
|
value: 0.9990000000000001 |
|
- type: precision_at_1000 |
|
value: 0.101 |
|
- type: precision_at_3 |
|
value: 27.889000000000003 |
|
- type: precision_at_5 |
|
value: 17.492 |
|
- type: recall_at_1 |
|
value: 68.862 |
|
- type: recall_at_10 |
|
value: 92.308 |
|
- type: recall_at_100 |
|
value: 98.84100000000001 |
|
- type: recall_at_1000 |
|
value: 99.684 |
|
- type: recall_at_3 |
|
value: 83.087 |
|
- type: recall_at_5 |
|
value: 86.617 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: C-MTEB/DuRetrieval |
|
name: MTEB DuRetrieval |
|
config: default |
|
split: dev |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 25.063999999999997 |
|
- type: map_at_10 |
|
value: 78.014 |
|
- type: map_at_100 |
|
value: 81.021 |
|
- type: map_at_1000 |
|
value: 81.059 |
|
- type: map_at_3 |
|
value: 53.616 |
|
- type: map_at_5 |
|
value: 68.00399999999999 |
|
- type: mrr_at_1 |
|
value: 87.8 |
|
- type: mrr_at_10 |
|
value: 91.824 |
|
- type: mrr_at_100 |
|
value: 91.915 |
|
- type: mrr_at_1000 |
|
value: 91.917 |
|
- type: mrr_at_3 |
|
value: 91.525 |
|
- type: mrr_at_5 |
|
value: 91.752 |
|
- type: ndcg_at_1 |
|
value: 87.8 |
|
- type: ndcg_at_10 |
|
value: 85.74199999999999 |
|
- type: ndcg_at_100 |
|
value: 88.82900000000001 |
|
- type: ndcg_at_1000 |
|
value: 89.208 |
|
- type: ndcg_at_3 |
|
value: 84.206 |
|
- type: ndcg_at_5 |
|
value: 83.421 |
|
- type: precision_at_1 |
|
value: 87.8 |
|
- type: precision_at_10 |
|
value: 41.325 |
|
- type: precision_at_100 |
|
value: 4.8 |
|
- type: precision_at_1000 |
|
value: 0.48900000000000005 |
|
- type: precision_at_3 |
|
value: 75.783 |
|
- type: precision_at_5 |
|
value: 64.25999999999999 |
|
- type: recall_at_1 |
|
value: 25.063999999999997 |
|
- type: recall_at_10 |
|
value: 87.324 |
|
- type: recall_at_100 |
|
value: 97.261 |
|
- type: recall_at_1000 |
|
value: 99.309 |
|
- type: recall_at_3 |
|
value: 56.281000000000006 |
|
- type: recall_at_5 |
|
value: 73.467 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: C-MTEB/EcomRetrieval |
|
name: MTEB EcomRetrieval |
|
config: default |
|
split: dev |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 46.800000000000004 |
|
- type: map_at_10 |
|
value: 56.887 |
|
- type: map_at_100 |
|
value: 57.556 |
|
- type: map_at_1000 |
|
value: 57.582 |
|
- type: map_at_3 |
|
value: 54.15 |
|
- type: map_at_5 |
|
value: 55.825 |
|
- type: mrr_at_1 |
|
value: 46.800000000000004 |
|
- type: mrr_at_10 |
|
value: 56.887 |
|
- type: mrr_at_100 |
|
value: 57.556 |
|
- type: mrr_at_1000 |
|
value: 57.582 |
|
- type: mrr_at_3 |
|
value: 54.15 |
|
- type: mrr_at_5 |
|
value: 55.825 |
|
- type: ndcg_at_1 |
|
value: 46.800000000000004 |
|
- type: ndcg_at_10 |
|
value: 62.061 |
|
- type: ndcg_at_100 |
|
value: 65.042 |
|
- type: ndcg_at_1000 |
|
value: 65.658 |
|
- type: ndcg_at_3 |
|
value: 56.52700000000001 |
|
- type: ndcg_at_5 |
|
value: 59.518 |
|
- type: precision_at_1 |
|
value: 46.800000000000004 |
|
- type: precision_at_10 |
|
value: 7.84 |
|
- type: precision_at_100 |
|
value: 0.9169999999999999 |
|
- type: precision_at_1000 |
|
value: 0.096 |
|
- type: precision_at_3 |
|
value: 21.133 |
|
- type: precision_at_5 |
|
value: 14.12 |
|
- type: recall_at_1 |
|
value: 46.800000000000004 |
|
- type: recall_at_10 |
|
value: 78.4 |
|
- type: recall_at_100 |
|
value: 91.7 |
|
- type: recall_at_1000 |
|
value: 96.39999999999999 |
|
- type: recall_at_3 |
|
value: 63.4 |
|
- type: recall_at_5 |
|
value: 70.6 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: C-MTEB/IFlyTek-classification |
|
name: MTEB IFlyTek |
|
config: default |
|
split: validation |
|
revision: None |
|
metrics: |
|
- type: accuracy |
|
value: 48.010773374374764 |
|
- type: f1 |
|
value: 35.25314495210735 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: C-MTEB/JDReview-classification |
|
name: MTEB JDReview |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: accuracy |
|
value: 87.01688555347093 |
|
- type: ap |
|
value: 56.39167630414159 |
|
- type: f1 |
|
value: 81.91756262306008 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: C-MTEB/LCQMC |
|
name: MTEB LCQMC |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 71.17867432738112 |
|
- type: cos_sim_spearman |
|
value: 77.47954247528372 |
|
- type: euclidean_pearson |
|
value: 76.32408876437825 |
|
- type: euclidean_spearman |
|
value: 77.47954025694959 |
|
- type: manhattan_pearson |
|
value: 76.33345801575938 |
|
- type: manhattan_spearman |
|
value: 77.48901582125997 |
|
- task: |
|
type: Reranking |
|
dataset: |
|
type: C-MTEB/Mmarco-reranking |
|
name: MTEB MMarcoReranking |
|
config: default |
|
split: dev |
|
revision: None |
|
metrics: |
|
- type: map |
|
value: 27.96333052746654 |
|
- type: mrr |
|
value: 26.92023809523809 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: C-MTEB/MMarcoRetrieval |
|
name: MTEB MMarcoRetrieval |
|
config: default |
|
split: dev |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 66.144 |
|
- type: map_at_10 |
|
value: 75.036 |
|
- type: map_at_100 |
|
value: 75.36 |
|
- type: map_at_1000 |
|
value: 75.371 |
|
- type: map_at_3 |
|
value: 73.258 |
|
- type: map_at_5 |
|
value: 74.369 |
|
- type: mrr_at_1 |
|
value: 68.381 |
|
- type: mrr_at_10 |
|
value: 75.633 |
|
- type: mrr_at_100 |
|
value: 75.91799999999999 |
|
- type: mrr_at_1000 |
|
value: 75.928 |
|
- type: mrr_at_3 |
|
value: 74.093 |
|
- type: mrr_at_5 |
|
value: 75.036 |
|
- type: ndcg_at_1 |
|
value: 68.381 |
|
- type: ndcg_at_10 |
|
value: 78.661 |
|
- type: ndcg_at_100 |
|
value: 80.15 |
|
- type: ndcg_at_1000 |
|
value: 80.456 |
|
- type: ndcg_at_3 |
|
value: 75.295 |
|
- type: ndcg_at_5 |
|
value: 77.14999999999999 |
|
- type: precision_at_1 |
|
value: 68.381 |
|
- type: precision_at_10 |
|
value: 9.481 |
|
- type: precision_at_100 |
|
value: 1.023 |
|
- type: precision_at_1000 |
|
value: 0.105 |
|
- type: precision_at_3 |
|
value: 28.309 |
|
- type: precision_at_5 |
|
value: 17.974 |
|
- type: recall_at_1 |
|
value: 66.144 |
|
- type: recall_at_10 |
|
value: 89.24499999999999 |
|
- type: recall_at_100 |
|
value: 96.032 |
|
- type: recall_at_1000 |
|
value: 98.437 |
|
- type: recall_at_3 |
|
value: 80.327 |
|
- type: recall_at_5 |
|
value: 84.733 |
|
- 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: 68.26832548755884 |
|
- type: f1 |
|
value: 65.97422207086723 |
|
- 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: 73.13046402151984 |
|
- type: f1 |
|
value: 72.69199129694121 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: C-MTEB/MedicalRetrieval |
|
name: MTEB MedicalRetrieval |
|
config: default |
|
split: dev |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 50.4 |
|
- type: map_at_10 |
|
value: 56.645 |
|
- type: map_at_100 |
|
value: 57.160999999999994 |
|
- type: map_at_1000 |
|
value: 57.218 |
|
- type: map_at_3 |
|
value: 55.383 |
|
- type: map_at_5 |
|
value: 56.08800000000001 |
|
- type: mrr_at_1 |
|
value: 50.6 |
|
- type: mrr_at_10 |
|
value: 56.745999999999995 |
|
- type: mrr_at_100 |
|
value: 57.262 |
|
- type: mrr_at_1000 |
|
value: 57.318999999999996 |
|
- type: mrr_at_3 |
|
value: 55.483000000000004 |
|
- type: mrr_at_5 |
|
value: 56.188 |
|
- type: ndcg_at_1 |
|
value: 50.4 |
|
- type: ndcg_at_10 |
|
value: 59.534 |
|
- type: ndcg_at_100 |
|
value: 62.400999999999996 |
|
- type: ndcg_at_1000 |
|
value: 64.01299999999999 |
|
- type: ndcg_at_3 |
|
value: 56.887 |
|
- type: ndcg_at_5 |
|
value: 58.160000000000004 |
|
- type: precision_at_1 |
|
value: 50.4 |
|
- type: precision_at_10 |
|
value: 6.859999999999999 |
|
- type: precision_at_100 |
|
value: 0.828 |
|
- type: precision_at_1000 |
|
value: 0.096 |
|
- type: precision_at_3 |
|
value: 20.4 |
|
- type: precision_at_5 |
|
value: 12.86 |
|
- type: recall_at_1 |
|
value: 50.4 |
|
- type: recall_at_10 |
|
value: 68.60000000000001 |
|
- type: recall_at_100 |
|
value: 82.8 |
|
- type: recall_at_1000 |
|
value: 95.7 |
|
- type: recall_at_3 |
|
value: 61.199999999999996 |
|
- type: recall_at_5 |
|
value: 64.3 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: C-MTEB/MultilingualSentiment-classification |
|
name: MTEB MultilingualSentiment |
|
config: default |
|
split: validation |
|
revision: None |
|
metrics: |
|
- type: accuracy |
|
value: 73.39666666666666 |
|
- type: f1 |
|
value: 72.86349039489504 |
|
- task: |
|
type: PairClassification |
|
dataset: |
|
type: C-MTEB/OCNLI |
|
name: MTEB Ocnli |
|
config: default |
|
split: validation |
|
revision: None |
|
metrics: |
|
- type: cos_sim_accuracy |
|
value: 73.36220898754738 |
|
- type: cos_sim_ap |
|
value: 78.50300066088354 |
|
- type: cos_sim_f1 |
|
value: 75.39370078740157 |
|
- type: cos_sim_precision |
|
value: 70.59907834101382 |
|
- type: cos_sim_recall |
|
value: 80.8870116156283 |
|
- type: dot_accuracy |
|
value: 73.36220898754738 |
|
- type: dot_ap |
|
value: 78.50300066088354 |
|
- type: dot_f1 |
|
value: 75.39370078740157 |
|
- type: dot_precision |
|
value: 70.59907834101382 |
|
- type: dot_recall |
|
value: 80.8870116156283 |
|
- type: euclidean_accuracy |
|
value: 73.36220898754738 |
|
- type: euclidean_ap |
|
value: 78.50300066088354 |
|
- type: euclidean_f1 |
|
value: 75.39370078740157 |
|
- type: euclidean_precision |
|
value: 70.59907834101382 |
|
- type: euclidean_recall |
|
value: 80.8870116156283 |
|
- type: manhattan_accuracy |
|
value: 73.09149972929075 |
|
- type: manhattan_ap |
|
value: 78.41160715817406 |
|
- type: manhattan_f1 |
|
value: 75.3623188405797 |
|
- type: manhattan_precision |
|
value: 69.45681211041853 |
|
- type: manhattan_recall |
|
value: 82.36536430834214 |
|
- type: max_accuracy |
|
value: 73.36220898754738 |
|
- type: max_ap |
|
value: 78.50300066088354 |
|
- type: max_f1 |
|
value: 75.39370078740157 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: C-MTEB/OnlineShopping-classification |
|
name: MTEB OnlineShopping |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: accuracy |
|
value: 91.82000000000001 |
|
- type: ap |
|
value: 89.3671278896903 |
|
- type: f1 |
|
value: 91.8021970144045 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: C-MTEB/PAWSX |
|
name: MTEB PAWSX |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 30.07022294131062 |
|
- type: cos_sim_spearman |
|
value: 36.21542804954441 |
|
- type: euclidean_pearson |
|
value: 36.37841945307606 |
|
- type: euclidean_spearman |
|
value: 36.215513214835546 |
|
- type: manhattan_pearson |
|
value: 36.31755715017088 |
|
- type: manhattan_spearman |
|
value: 36.16848256918425 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: C-MTEB/QBQTC |
|
name: MTEB QBQTC |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 36.779755871073505 |
|
- type: cos_sim_spearman |
|
value: 38.736220679196606 |
|
- type: euclidean_pearson |
|
value: 37.13356686891227 |
|
- type: euclidean_spearman |
|
value: 38.73619198602118 |
|
- type: manhattan_pearson |
|
value: 37.175466658530816 |
|
- type: manhattan_spearman |
|
value: 38.74523158724344 |
|
- 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: 65.9737863254904 |
|
- type: cos_sim_spearman |
|
value: 68.88293545840186 |
|
- type: euclidean_pearson |
|
value: 67.23730973929247 |
|
- type: euclidean_spearman |
|
value: 68.88293545840186 |
|
- type: manhattan_pearson |
|
value: 67.30647960940956 |
|
- type: manhattan_spearman |
|
value: 68.90553460682702 |
|
- task: |
|
type: STS |
|
dataset: |
|
type: C-MTEB/STSB |
|
name: MTEB STSB |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 78.99371432933002 |
|
- type: cos_sim_spearman |
|
value: 79.36496709214312 |
|
- type: euclidean_pearson |
|
value: 78.77721120706431 |
|
- type: euclidean_spearman |
|
value: 79.36500761622595 |
|
- type: manhattan_pearson |
|
value: 78.82503201285202 |
|
- type: manhattan_spearman |
|
value: 79.43915548337401 |
|
- task: |
|
type: Reranking |
|
dataset: |
|
type: C-MTEB/T2Reranking |
|
name: MTEB T2Reranking |
|
config: default |
|
split: dev |
|
revision: None |
|
metrics: |
|
- type: map |
|
value: 66.38418982516941 |
|
- type: mrr |
|
value: 76.09996131153883 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: C-MTEB/T2Retrieval |
|
name: MTEB T2Retrieval |
|
config: default |
|
split: dev |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 27.426000000000002 |
|
- type: map_at_10 |
|
value: 77.209 |
|
- type: map_at_100 |
|
value: 80.838 |
|
- type: map_at_1000 |
|
value: 80.903 |
|
- type: map_at_3 |
|
value: 54.196 |
|
- type: map_at_5 |
|
value: 66.664 |
|
- type: mrr_at_1 |
|
value: 90.049 |
|
- type: mrr_at_10 |
|
value: 92.482 |
|
- type: mrr_at_100 |
|
value: 92.568 |
|
- type: mrr_at_1000 |
|
value: 92.572 |
|
- type: mrr_at_3 |
|
value: 92.072 |
|
- type: mrr_at_5 |
|
value: 92.33 |
|
- type: ndcg_at_1 |
|
value: 90.049 |
|
- type: ndcg_at_10 |
|
value: 84.69200000000001 |
|
- type: ndcg_at_100 |
|
value: 88.25699999999999 |
|
- type: ndcg_at_1000 |
|
value: 88.896 |
|
- type: ndcg_at_3 |
|
value: 86.09700000000001 |
|
- type: ndcg_at_5 |
|
value: 84.68599999999999 |
|
- type: precision_at_1 |
|
value: 90.049 |
|
- type: precision_at_10 |
|
value: 42.142 |
|
- type: precision_at_100 |
|
value: 5.017 |
|
- type: precision_at_1000 |
|
value: 0.516 |
|
- type: precision_at_3 |
|
value: 75.358 |
|
- type: precision_at_5 |
|
value: 63.173 |
|
- type: recall_at_1 |
|
value: 27.426000000000002 |
|
- type: recall_at_10 |
|
value: 83.59400000000001 |
|
- type: recall_at_100 |
|
value: 95.21 |
|
- type: recall_at_1000 |
|
value: 98.503 |
|
- type: recall_at_3 |
|
value: 55.849000000000004 |
|
- type: recall_at_5 |
|
value: 69.986 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: C-MTEB/TNews-classification |
|
name: MTEB TNews |
|
config: default |
|
split: validation |
|
revision: None |
|
metrics: |
|
- type: accuracy |
|
value: 51.925999999999995 |
|
- type: f1 |
|
value: 50.16867723626971 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: C-MTEB/ThuNewsClusteringP2P |
|
name: MTEB ThuNewsClusteringP2P |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: v_measure |
|
value: 60.738901671970005 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
type: C-MTEB/ThuNewsClusteringS2S |
|
name: MTEB ThuNewsClusteringS2S |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: v_measure |
|
value: 57.08563183138733 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
type: C-MTEB/VideoRetrieval |
|
name: MTEB VideoRetrieval |
|
config: default |
|
split: dev |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 52 |
|
- type: map_at_10 |
|
value: 62.956 |
|
- type: map_at_100 |
|
value: 63.491 |
|
- type: map_at_1000 |
|
value: 63.50599999999999 |
|
- type: map_at_3 |
|
value: 60.733000000000004 |
|
- type: map_at_5 |
|
value: 62.217999999999996 |
|
- type: mrr_at_1 |
|
value: 52 |
|
- type: mrr_at_10 |
|
value: 62.956 |
|
- type: mrr_at_100 |
|
value: 63.491 |
|
- type: mrr_at_1000 |
|
value: 63.50599999999999 |
|
- type: mrr_at_3 |
|
value: 60.733000000000004 |
|
- type: mrr_at_5 |
|
value: 62.217999999999996 |
|
- type: ndcg_at_1 |
|
value: 52 |
|
- type: ndcg_at_10 |
|
value: 67.956 |
|
- type: ndcg_at_100 |
|
value: 70.536 |
|
- type: ndcg_at_1000 |
|
value: 70.908 |
|
- type: ndcg_at_3 |
|
value: 63.456999999999994 |
|
- type: ndcg_at_5 |
|
value: 66.155 |
|
- type: precision_at_1 |
|
value: 52 |
|
- type: precision_at_10 |
|
value: 8.35 |
|
- type: precision_at_100 |
|
value: 0.955 |
|
- type: precision_at_1000 |
|
value: 0.098 |
|
- type: precision_at_3 |
|
value: 23.767 |
|
- type: precision_at_5 |
|
value: 15.58 |
|
- type: recall_at_1 |
|
value: 52 |
|
- type: recall_at_10 |
|
value: 83.5 |
|
- type: recall_at_100 |
|
value: 95.5 |
|
- type: recall_at_1000 |
|
value: 98.4 |
|
- type: recall_at_3 |
|
value: 71.3 |
|
- type: recall_at_5 |
|
value: 77.9 |
|
- task: |
|
type: Classification |
|
dataset: |
|
type: C-MTEB/waimai-classification |
|
name: MTEB Waimai |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: accuracy |
|
value: 87.10000000000001 |
|
- type: ap |
|
value: 70.81766065881429 |
|
- type: f1 |
|
value: 85.5323306120456 |
|
license: apache-2.0 |
|
language: |
|
- zh |
|
--- |
|
|
|
A try for emebdding model: |
|
|
|
The method is the same as the stella-v2, I just fine-tuned it in a small dataset for test. |
|
|
|
Now I'm working on the tao-v2, It will have a different sturcture. |
|
|
|
I will release tao-v2 as fast as I can. |
|
|
|
Thank you to the open source community. |
