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--- |
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tags: |
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- sentence-transformers |
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- feature-extraction |
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- sentence-similarity |
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- mteb |
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- RAG |
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- llama-cpp |
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- gguf-my-repo |
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license: apache-2.0 |
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language: |
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- zh |
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- en |
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pipeline_tag: feature-extraction |
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base_model: DMetaSoul/Dmeta-embedding-zh |
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model-index: |
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- name: Dmeta-embedding |
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results: |
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- task: |
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type: STS |
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dataset: |
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name: MTEB AFQMC |
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type: C-MTEB/AFQMC |
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config: default |
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split: validation |
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revision: None |
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metrics: |
|
- type: cos_sim_pearson |
|
value: 65.60825224706932 |
|
- type: cos_sim_spearman |
|
value: 71.12862586297193 |
|
- type: euclidean_pearson |
|
value: 70.18130275750404 |
|
- type: euclidean_spearman |
|
value: 71.12862586297193 |
|
- type: manhattan_pearson |
|
value: 70.14470398075396 |
|
- type: manhattan_spearman |
|
value: 71.05226975911737 |
|
- task: |
|
type: STS |
|
dataset: |
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name: MTEB ATEC |
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type: C-MTEB/ATEC |
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config: default |
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split: test |
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revision: None |
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metrics: |
|
- type: cos_sim_pearson |
|
value: 65.52386345655479 |
|
- type: cos_sim_spearman |
|
value: 64.64245253181382 |
|
- type: euclidean_pearson |
|
value: 73.20157662981914 |
|
- type: euclidean_spearman |
|
value: 64.64245253178956 |
|
- type: manhattan_pearson |
|
value: 73.22837571756348 |
|
- type: manhattan_spearman |
|
value: 64.62632334391418 |
|
- task: |
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type: Classification |
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dataset: |
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name: MTEB AmazonReviewsClassification (zh) |
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type: mteb/amazon_reviews_multi |
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config: zh |
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split: test |
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revision: 1399c76144fd37290681b995c656ef9b2e06e26d |
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metrics: |
|
- type: accuracy |
|
value: 44.925999999999995 |
|
- type: f1 |
|
value: 42.82555191308971 |
|
- task: |
|
type: STS |
|
dataset: |
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name: MTEB BQ |
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type: C-MTEB/BQ |
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config: default |
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split: test |
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revision: None |
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metrics: |
|
- type: cos_sim_pearson |
|
value: 71.35236446393156 |
|
- type: cos_sim_spearman |
|
value: 72.29629643702184 |
|
- type: euclidean_pearson |
|
value: 70.94570179874498 |
|
- type: euclidean_spearman |
|
value: 72.29629297226953 |
|
- type: manhattan_pearson |
|
value: 70.84463025501125 |
|
- type: manhattan_spearman |
|
value: 72.24527021975821 |
|
- task: |
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type: Clustering |
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dataset: |
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name: MTEB CLSClusteringP2P |
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type: C-MTEB/CLSClusteringP2P |
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config: default |
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split: test |
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revision: None |
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metrics: |
|
- type: v_measure |
|
value: 40.24232916894152 |
|
- task: |
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type: Clustering |
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dataset: |
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name: MTEB CLSClusteringS2S |
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type: C-MTEB/CLSClusteringS2S |
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config: default |
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split: test |
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revision: None |
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metrics: |
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- type: v_measure |
|
value: 39.167806226929706 |
|
- task: |
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type: Reranking |
|
dataset: |
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name: MTEB CMedQAv1 |
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type: C-MTEB/CMedQAv1-reranking |
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config: default |
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split: test |
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revision: None |
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metrics: |
|
- type: map |
|
value: 88.48837920106357 |
|
- type: mrr |
|
value: 90.36861111111111 |
|
- task: |
|
type: Reranking |
|
dataset: |
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name: MTEB CMedQAv2 |
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type: C-MTEB/CMedQAv2-reranking |
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config: default |
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split: test |
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revision: None |
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metrics: |
|
- type: map |
|
value: 89.17878171657071 |
|
- type: mrr |
|
value: 91.35805555555555 |
|
- task: |
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type: Retrieval |
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dataset: |
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name: MTEB CmedqaRetrieval |
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type: C-MTEB/CmedqaRetrieval |
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config: default |
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split: dev |
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revision: None |
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metrics: |
|
- type: map_at_1 |
|
value: 25.751 |
|
- type: map_at_10 |
|
value: 38.946 |
|
- type: map_at_100 |
|
value: 40.855000000000004 |
|
- type: map_at_1000 |
|
value: 40.953 |
|
- type: map_at_3 |
|
value: 34.533 |
|
- type: map_at_5 |
|
value: 36.905 |
|
- type: mrr_at_1 |
|
value: 39.235 |
|
- type: mrr_at_10 |
|
value: 47.713 |
|
- type: mrr_at_100 |
|
value: 48.71 |
|
- type: mrr_at_1000 |
|
value: 48.747 |
|
- type: mrr_at_3 |
|
value: 45.086 |
|
- type: mrr_at_5 |
|
value: 46.498 |
|
- type: ndcg_at_1 |
|
value: 39.235 |
|
- type: ndcg_at_10 |
|
value: 45.831 |
|
- type: ndcg_at_100 |
|
value: 53.162 |
|
- type: ndcg_at_1000 |
|
value: 54.800000000000004 |
|
- type: ndcg_at_3 |
|
value: 40.188 |
|
- type: ndcg_at_5 |
|
value: 42.387 |
|
- type: precision_at_1 |
|
value: 39.235 |
|
- type: precision_at_10 |
|
value: 10.273 |
|
- type: precision_at_100 |
|
value: 1.627 |
|
- type: precision_at_1000 |
|
value: 0.183 |
|
- type: precision_at_3 |
|
value: 22.772000000000002 |
|
- type: precision_at_5 |
|
value: 16.524 |
|
- type: recall_at_1 |
|
value: 25.751 |
|
- type: recall_at_10 |
|
value: 57.411 |
|
- type: recall_at_100 |
|
value: 87.44 |
|
- type: recall_at_1000 |
|
value: 98.386 |
|
- type: recall_at_3 |
|
value: 40.416000000000004 |
|
- type: recall_at_5 |
|
value: 47.238 |
|
- task: |
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type: PairClassification |
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dataset: |
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name: MTEB Cmnli |
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type: C-MTEB/CMNLI |
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config: default |
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split: validation |
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revision: None |
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metrics: |
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- type: cos_sim_accuracy |
|
value: 83.59591100420926 |
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- type: cos_sim_ap |
|
value: 90.65538153970263 |
|
- type: cos_sim_f1 |
|
value: 84.76466651795673 |
|
- type: cos_sim_precision |
|
value: 81.04073363190446 |
|
- type: cos_sim_recall |
|
value: 88.84732288987608 |
|
- type: dot_accuracy |
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value: 83.59591100420926 |
|
- type: dot_ap |
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value: 90.64355541781003 |
|
- type: dot_f1 |
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value: 84.76466651795673 |
|
- type: dot_precision |
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value: 81.04073363190446 |
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- type: dot_recall |
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value: 88.84732288987608 |
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- type: euclidean_accuracy |
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value: 83.59591100420926 |
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- type: euclidean_ap |
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value: 90.6547878194287 |
|
- type: euclidean_f1 |
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value: 84.76466651795673 |
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- type: euclidean_precision |
|
value: 81.04073363190446 |
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- type: euclidean_recall |
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value: 88.84732288987608 |
|
- type: manhattan_accuracy |
|
value: 83.51172579675286 |
|
- type: manhattan_ap |
|
value: 90.59941589844144 |
|
- type: manhattan_f1 |
|
value: 84.51827242524917 |
|
- type: manhattan_precision |
|
value: 80.28613507258574 |
|
- type: manhattan_recall |
|
value: 89.22141688099134 |
|
- type: max_accuracy |
|
value: 83.59591100420926 |
|
- type: max_ap |
|
value: 90.65538153970263 |
|
- type: max_f1 |
|
value: 84.76466651795673 |
|
- task: |
|
type: Retrieval |
|
dataset: |
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name: MTEB CovidRetrieval |
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type: C-MTEB/CovidRetrieval |
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config: default |
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split: dev |
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revision: None |
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metrics: |
|
- type: map_at_1 |
|
value: 63.251000000000005 |
|
- type: map_at_10 |
|
value: 72.442 |
|
- type: map_at_100 |
|
value: 72.79299999999999 |
|
- type: map_at_1000 |
|
value: 72.80499999999999 |
|
- type: map_at_3 |
|
value: 70.293 |
|
- type: map_at_5 |
|
value: 71.571 |
|
- type: mrr_at_1 |
|
value: 63.541000000000004 |
|
- type: mrr_at_10 |
|
value: 72.502 |
|
- type: mrr_at_100 |
|
value: 72.846 |
|
- type: mrr_at_1000 |
|
value: 72.858 |
|
- type: mrr_at_3 |
|
value: 70.39 |
|
- type: mrr_at_5 |
|
value: 71.654 |
|
- type: ndcg_at_1 |
|
value: 63.541000000000004 |
|
- type: ndcg_at_10 |
|
value: 76.774 |
|
- type: ndcg_at_100 |
|
value: 78.389 |
|
- type: ndcg_at_1000 |
|
value: 78.678 |
|
- type: ndcg_at_3 |
|
value: 72.47 |
|
- type: ndcg_at_5 |
|
value: 74.748 |
|
- type: precision_at_1 |
|
value: 63.541000000000004 |
|
- type: precision_at_10 |
|
value: 9.115 |
|
- type: precision_at_100 |
|
value: 0.9860000000000001 |
|
- type: precision_at_1000 |
|
value: 0.101 |
|
- type: precision_at_3 |
|
value: 26.379 |
|
- type: precision_at_5 |
|
value: 16.965 |
|
- type: recall_at_1 |
|
value: 63.251000000000005 |
|
- type: recall_at_10 |
|
value: 90.253 |
|
- type: recall_at_100 |
|
value: 97.576 |
|
- type: recall_at_1000 |
|
value: 99.789 |
|
- type: recall_at_3 |
|
value: 78.635 |
|
- type: recall_at_5 |
|
value: 84.141 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
name: MTEB DuRetrieval |
|
type: C-MTEB/DuRetrieval |
|
config: default |
|
split: dev |
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revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 23.597 |
|
- type: map_at_10 |
|
value: 72.411 |
|
- type: map_at_100 |
|
value: 75.58500000000001 |
|
- type: map_at_1000 |
|
value: 75.64800000000001 |
|
- type: map_at_3 |
|
value: 49.61 |
|
- type: map_at_5 |
|
value: 62.527 |
|
- type: mrr_at_1 |
|
value: 84.65 |
|
- type: mrr_at_10 |
|
value: 89.43900000000001 |
|
- type: mrr_at_100 |
|
value: 89.525 |
|
- type: mrr_at_1000 |
|
value: 89.529 |
|
- type: mrr_at_3 |
|
value: 89 |
|
- type: mrr_at_5 |
|
value: 89.297 |
|
- type: ndcg_at_1 |
|
value: 84.65 |
|
- type: ndcg_at_10 |
|
value: 81.47 |
|
- type: ndcg_at_100 |
|
value: 85.198 |
|
- type: ndcg_at_1000 |
|
value: 85.828 |
|
- type: ndcg_at_3 |
|
value: 79.809 |
|
- type: ndcg_at_5 |
|
value: 78.55 |
|
- type: precision_at_1 |
|
value: 84.65 |
|
- type: precision_at_10 |
|
value: 39.595 |
|
- type: precision_at_100 |
|
value: 4.707 |
|
- type: precision_at_1000 |
|
value: 0.485 |
|
- type: precision_at_3 |
|
value: 71.61699999999999 |
|
- type: precision_at_5 |
|
value: 60.45 |
|
- type: recall_at_1 |
|
value: 23.597 |
|
- type: recall_at_10 |
|
value: 83.34 |
|
- type: recall_at_100 |
|
value: 95.19800000000001 |
|
- type: recall_at_1000 |
|
value: 98.509 |
|
- type: recall_at_3 |
|
value: 52.744 |
|
- type: recall_at_5 |
|
value: 68.411 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
name: MTEB EcomRetrieval |
|
type: C-MTEB/EcomRetrieval |
|
config: default |
|
split: dev |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 53.1 |
|
- type: map_at_10 |
|
value: 63.359 |
|
- type: map_at_100 |
|
value: 63.9 |
|
- type: map_at_1000 |
|
value: 63.909000000000006 |
|
- type: map_at_3 |
|
value: 60.95 |
|
- type: map_at_5 |
|
value: 62.305 |
|
- type: mrr_at_1 |
|
value: 53.1 |
|
- type: mrr_at_10 |
|
value: 63.359 |
|
- type: mrr_at_100 |
|
value: 63.9 |
|
- type: mrr_at_1000 |
|
value: 63.909000000000006 |
|
- type: mrr_at_3 |
|
value: 60.95 |
|
- type: mrr_at_5 |
|
value: 62.305 |
|
- type: ndcg_at_1 |
|
value: 53.1 |
|
- type: ndcg_at_10 |
|
value: 68.418 |
|
- type: ndcg_at_100 |
|
value: 70.88499999999999 |
|
- type: ndcg_at_1000 |
|
value: 71.135 |
|
- type: ndcg_at_3 |
|
value: 63.50599999999999 |
|
- type: ndcg_at_5 |
|
value: 65.92 |
|
- type: precision_at_1 |
|
value: 53.1 |
|
- type: precision_at_10 |
|
value: 8.43 |
|
- type: precision_at_100 |
|
value: 0.955 |
|
- type: precision_at_1000 |
|
value: 0.098 |
|
- type: precision_at_3 |
|
value: 23.633000000000003 |
|
- type: precision_at_5 |
|
value: 15.340000000000002 |
|
- type: recall_at_1 |
|
value: 53.1 |
|
- type: recall_at_10 |
|
value: 84.3 |
|
- type: recall_at_100 |
|
value: 95.5 |
|
- type: recall_at_1000 |
|
value: 97.5 |
|
- type: recall_at_3 |
|
value: 70.89999999999999 |
|
- type: recall_at_5 |
|
value: 76.7 |
|
- task: |
|
type: Classification |
|
dataset: |
|
name: MTEB IFlyTek |
|
type: C-MTEB/IFlyTek-classification |
|
config: default |
|
split: validation |
|
revision: None |
|
metrics: |
|
- type: accuracy |
|
value: 48.303193535975375 |
|
- type: f1 |
|
value: 35.96559358693866 |
|
- task: |
|
type: Classification |
|
dataset: |
|
name: MTEB JDReview |
|
type: C-MTEB/JDReview-classification |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: accuracy |
|
value: 85.06566604127579 |
|
- type: ap |
|
value: 52.0596483757231 |
|
- type: f1 |
|
value: 79.5196835127668 |
|
- task: |
|
type: STS |
|
dataset: |
|
name: MTEB LCQMC |
|
type: C-MTEB/LCQMC |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 74.48499423626059 |
|
- type: cos_sim_spearman |
|
value: 78.75806756061169 |
|
- type: euclidean_pearson |
|
value: 78.47917601852879 |
|
- type: euclidean_spearman |
|
value: 78.75807199272622 |
|
- type: manhattan_pearson |
|
value: 78.40207586289772 |
|
- type: manhattan_spearman |
|
value: 78.6911776964119 |
|
- task: |
|
type: Reranking |
|
dataset: |
|
name: MTEB MMarcoReranking |
|
type: C-MTEB/Mmarco-reranking |
|
config: default |
|
split: dev |
|
revision: None |
|
metrics: |
|
- type: map |
|
value: 24.75987466552363 |
|
- type: mrr |
|
value: 23.40515873015873 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
name: MTEB MMarcoRetrieval |
|
type: C-MTEB/MMarcoRetrieval |
|
config: default |
|
split: dev |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 58.026999999999994 |
|
- type: map_at_10 |
|
value: 67.50699999999999 |
|
- type: map_at_100 |
|
value: 67.946 |
|
- type: map_at_1000 |
|
value: 67.96600000000001 |
|
- type: map_at_3 |
|
value: 65.503 |
|
- type: map_at_5 |
|
value: 66.649 |
|
- type: mrr_at_1 |
|
value: 60.20100000000001 |
|
- type: mrr_at_10 |
|
value: 68.271 |
|
- type: mrr_at_100 |
|
value: 68.664 |
|
- type: mrr_at_1000 |
|
value: 68.682 |
|
- type: mrr_at_3 |
|
value: 66.47800000000001 |
|
- type: mrr_at_5 |
|
value: 67.499 |
|
- type: ndcg_at_1 |
|
value: 60.20100000000001 |
|
- type: ndcg_at_10 |
|
value: 71.697 |
|
- type: ndcg_at_100 |
|
value: 73.736 |
|
- type: ndcg_at_1000 |
|
value: 74.259 |
|
- type: ndcg_at_3 |
|
value: 67.768 |
|
- type: ndcg_at_5 |
|
value: 69.72 |
|
- type: precision_at_1 |
|
value: 60.20100000000001 |
|
- type: precision_at_10 |
|
value: 8.927999999999999 |
|
- type: precision_at_100 |
|
value: 0.9950000000000001 |
|
- type: precision_at_1000 |
|
value: 0.104 |
|
- type: precision_at_3 |
|
value: 25.883 |
|
- type: precision_at_5 |
|
value: 16.55 |
|
- type: recall_at_1 |
|
value: 58.026999999999994 |
|
- type: recall_at_10 |
|
value: 83.966 |
|
- type: recall_at_100 |
|
value: 93.313 |
|
- type: recall_at_1000 |
|
value: 97.426 |
|
- type: recall_at_3 |
|
value: 73.342 |
|
- type: recall_at_5 |
|
value: 77.997 |
|
- task: |
|
type: Classification |
|
dataset: |
|
name: MTEB MassiveIntentClassification (zh-CN) |
|
type: mteb/amazon_massive_intent |
|
config: zh-CN |
|
split: test |
|
revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 |
|
metrics: |
|
- type: accuracy |
|
value: 71.1600537995965 |
|
- type: f1 |
|
value: 68.8126216609964 |
|
- task: |
|
type: Classification |
|
dataset: |
|
name: MTEB MassiveScenarioClassification (zh-CN) |
|
type: mteb/amazon_massive_scenario |
|
config: zh-CN |
|
split: test |
|
revision: 7d571f92784cd94a019292a1f45445077d0ef634 |
|
metrics: |
|
- type: accuracy |
|
value: 73.54068594485541 |
|
- type: f1 |
|
value: 73.46845879869848 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
name: MTEB MedicalRetrieval |
|
type: C-MTEB/MedicalRetrieval |
|
config: default |
|
split: dev |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 54.900000000000006 |
|
- type: map_at_10 |
|
value: 61.363 |
|
- type: map_at_100 |
|
value: 61.924 |
|
- type: map_at_1000 |
|
value: 61.967000000000006 |
|
- type: map_at_3 |
|
value: 59.767 |
|
- type: map_at_5 |
|
value: 60.802 |
|
- type: mrr_at_1 |
|
value: 55.1 |
|
- type: mrr_at_10 |
|
value: 61.454 |
|
- type: mrr_at_100 |
|
value: 62.016000000000005 |
|
- type: mrr_at_1000 |
|
value: 62.059 |
|
- type: mrr_at_3 |
|
value: 59.882999999999996 |
|
- type: mrr_at_5 |
|
value: 60.893 |
|
- type: ndcg_at_1 |
|
value: 54.900000000000006 |
|
- type: ndcg_at_10 |
|
value: 64.423 |
|
- type: ndcg_at_100 |
|
value: 67.35900000000001 |
|
- type: ndcg_at_1000 |
|
value: 68.512 |
|
- type: ndcg_at_3 |
|
value: 61.224000000000004 |
|
- type: ndcg_at_5 |
|
value: 63.083 |
|
- type: precision_at_1 |
|
value: 54.900000000000006 |
|
- type: precision_at_10 |
|
value: 7.3999999999999995 |
|
- type: precision_at_100 |
|
value: 0.882 |
|
- type: precision_at_1000 |
|
value: 0.097 |
|
- type: precision_at_3 |
|
value: 21.8 |
|
- type: precision_at_5 |
|
value: 13.98 |
|
- type: recall_at_1 |
|
value: 54.900000000000006 |
|
- type: recall_at_10 |
|
value: 74 |
|
- type: recall_at_100 |
|
value: 88.2 |
|
- type: recall_at_1000 |
|
value: 97.3 |
|
- type: recall_at_3 |
|
value: 65.4 |
|
- type: recall_at_5 |
|
value: 69.89999999999999 |
|
- task: |
|
type: Classification |
|
dataset: |
|
name: MTEB MultilingualSentiment |
|
type: C-MTEB/MultilingualSentiment-classification |
|
config: default |
|
split: validation |
|
revision: None |
|
metrics: |
|
- type: accuracy |
|
value: 75.15666666666667 |
|
- type: f1 |
|
value: 74.8306375354435 |
|
- task: |
|
type: PairClassification |
|
dataset: |
|
name: MTEB Ocnli |
|
type: C-MTEB/OCNLI |
|
config: default |
|
split: validation |
|
revision: None |
|
metrics: |
|
- type: cos_sim_accuracy |
|
value: 83.10774228478614 |
|
- type: cos_sim_ap |
|
value: 87.17679348388666 |
|
- type: cos_sim_f1 |
|
value: 84.59302325581395 |
|
- type: cos_sim_precision |
|
value: 78.15577439570276 |
|
- type: cos_sim_recall |
|
value: 92.18585005279832 |
|
- type: dot_accuracy |
|
value: 83.10774228478614 |
|
- type: dot_ap |
|
value: 87.17679348388666 |
|
- type: dot_f1 |
|
value: 84.59302325581395 |
|
- type: dot_precision |
|
value: 78.15577439570276 |
|
- type: dot_recall |
|
value: 92.18585005279832 |
|
- type: euclidean_accuracy |
|
value: 83.10774228478614 |
|
- type: euclidean_ap |
|
value: 87.17679348388666 |
|
- type: euclidean_f1 |
|
value: 84.59302325581395 |
|
- type: euclidean_precision |
|
value: 78.15577439570276 |
|
- type: euclidean_recall |
|
value: 92.18585005279832 |
|
- type: manhattan_accuracy |
|
value: 82.67460747157553 |
|
- type: manhattan_ap |
|
value: 86.94296334435238 |
|
- type: manhattan_f1 |
|
value: 84.32327166504382 |
|
- type: manhattan_precision |
|
value: 78.22944896115628 |
|
- type: manhattan_recall |
|
value: 91.4466737064414 |
|
- type: max_accuracy |
|
value: 83.10774228478614 |
|
- type: max_ap |
|
value: 87.17679348388666 |
|
- type: max_f1 |
|
value: 84.59302325581395 |
|
- task: |
|
type: Classification |
|
dataset: |
|
name: MTEB OnlineShopping |
|
type: C-MTEB/OnlineShopping-classification |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: accuracy |
|
value: 93.24999999999999 |
|
- type: ap |
|
value: 90.98617641063584 |
|
- type: f1 |
|
value: 93.23447883650289 |
|
- task: |
|
type: STS |
|
dataset: |
|
name: MTEB PAWSX |
|
type: C-MTEB/PAWSX |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 41.071417937737856 |
|
- type: cos_sim_spearman |
|
value: 45.049199344455424 |
|
- type: euclidean_pearson |
|
value: 44.913450096830786 |
|
- type: euclidean_spearman |
|
value: 45.05733424275291 |
|
- type: manhattan_pearson |
|
value: 44.881623825912065 |
|
- type: manhattan_spearman |
|
value: 44.989923561416596 |
|
- task: |
|
type: STS |
|
dataset: |
|
name: MTEB QBQTC |
|
type: C-MTEB/QBQTC |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 41.38238052689359 |
|
- type: cos_sim_spearman |
|
value: 42.61949690594399 |
|
- type: euclidean_pearson |
|
value: 40.61261500356766 |
|
- type: euclidean_spearman |
|
value: 42.619626605620724 |
|
- type: manhattan_pearson |
|
value: 40.8886109204474 |
|
- type: manhattan_spearman |
|
value: 42.75791523010463 |
|
- task: |
|
type: STS |
|
dataset: |
|
name: MTEB STS22 (zh) |
|
type: mteb/sts22-crosslingual-sts |
|
config: zh |
|
split: test |
|
revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 62.10977863727196 |
|
- type: cos_sim_spearman |
|
value: 63.843727112473225 |
|
- type: euclidean_pearson |
|
value: 63.25133487817196 |
|
- type: euclidean_spearman |
|
value: 63.843727112473225 |
|
- type: manhattan_pearson |
|
value: 63.58749018644103 |
|
- type: manhattan_spearman |
|
value: 63.83820575456674 |
|
- task: |
|
type: STS |
|
dataset: |
|
name: MTEB STSB |
|
type: C-MTEB/STSB |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 79.30616496720054 |
|
- type: cos_sim_spearman |
|
value: 80.767935782436 |
|
- type: euclidean_pearson |
|
value: 80.4160642670106 |
|
- type: euclidean_spearman |
|
value: 80.76820284024356 |
|
- type: manhattan_pearson |
|
value: 80.27318714580251 |
|
- type: manhattan_spearman |
|
value: 80.61030164164964 |
|
- task: |
|
type: Reranking |
|
dataset: |
|
name: MTEB T2Reranking |
|
type: C-MTEB/T2Reranking |
|
config: default |
|
split: dev |
|
revision: None |
|
metrics: |
|
- type: map |
|
value: 66.26242871142425 |
|
- type: mrr |
|
value: 76.20689863623174 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
name: MTEB T2Retrieval |
|
type: C-MTEB/T2Retrieval |
|
config: default |
|
split: dev |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 26.240999999999996 |
|
- type: map_at_10 |
|
value: 73.009 |
|
- type: map_at_100 |
|
value: 76.893 |
|
- type: map_at_1000 |
|
value: 76.973 |
|
- type: map_at_3 |
|
value: 51.339 |
|
- type: map_at_5 |
|
value: 63.003 |
|
- type: mrr_at_1 |
|
value: 87.458 |
|
- type: mrr_at_10 |
|
value: 90.44 |
|
- type: mrr_at_100 |
|
value: 90.558 |
|
- type: mrr_at_1000 |
|
value: 90.562 |
|
- type: mrr_at_3 |
|
value: 89.89 |
|
- type: mrr_at_5 |
|
value: 90.231 |
|
- type: ndcg_at_1 |
|
value: 87.458 |
|
- type: ndcg_at_10 |
|
value: 81.325 |
|
- type: ndcg_at_100 |
|
value: 85.61999999999999 |
|
- type: ndcg_at_1000 |
|
value: 86.394 |
|
- type: ndcg_at_3 |
|
value: 82.796 |
|
- type: ndcg_at_5 |
|
value: 81.219 |
|
- type: precision_at_1 |
|
value: 87.458 |
|
- type: precision_at_10 |
|
value: 40.534 |
|
- type: precision_at_100 |
|
value: 4.96 |
|
- type: precision_at_1000 |
|
value: 0.514 |
|
- type: precision_at_3 |
|
value: 72.444 |
|
- type: precision_at_5 |
|
value: 60.601000000000006 |
|
- type: recall_at_1 |
|
value: 26.240999999999996 |
|
- type: recall_at_10 |
|
value: 80.42 |
|
- type: recall_at_100 |
|
value: 94.118 |
|
- type: recall_at_1000 |
|
value: 98.02199999999999 |
|
- type: recall_at_3 |
|
value: 53.174 |
|
- type: recall_at_5 |
|
value: 66.739 |
|
- task: |
|
type: Classification |
|
dataset: |
|
name: MTEB TNews |
|
type: C-MTEB/TNews-classification |
|
config: default |
|
split: validation |
|
revision: None |
|
metrics: |
|
- type: accuracy |
|
value: 52.40899999999999 |
|
- type: f1 |
|
value: 50.68532128056062 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
name: MTEB ThuNewsClusteringP2P |
|
type: C-MTEB/ThuNewsClusteringP2P |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: v_measure |
|
value: 65.57616085176686 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
name: MTEB ThuNewsClusteringS2S |
|
type: C-MTEB/ThuNewsClusteringS2S |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: v_measure |
|
value: 58.844999922904925 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
name: MTEB VideoRetrieval |
|
type: C-MTEB/VideoRetrieval |
|
config: default |
|
split: dev |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 58.4 |
|
- type: map_at_10 |
|
value: 68.64 |
|
- type: map_at_100 |
|
value: 69.062 |
|
- type: map_at_1000 |
|
value: 69.073 |
|
- type: map_at_3 |
|
value: 66.567 |
|
- type: map_at_5 |
|
value: 67.89699999999999 |
|
- type: mrr_at_1 |
|
value: 58.4 |
|
- type: mrr_at_10 |
|
value: 68.64 |
|
- type: mrr_at_100 |
|
value: 69.062 |
|
- type: mrr_at_1000 |
|
value: 69.073 |
|
- type: mrr_at_3 |
|
value: 66.567 |
|
- type: mrr_at_5 |
|
value: 67.89699999999999 |
|
- type: ndcg_at_1 |
|
value: 58.4 |
|
- type: ndcg_at_10 |
|
value: 73.30600000000001 |
|
- type: ndcg_at_100 |
|
value: 75.276 |
|
- type: ndcg_at_1000 |
|
value: 75.553 |
|
- type: ndcg_at_3 |
|
value: 69.126 |
|
- type: ndcg_at_5 |
|
value: 71.519 |
|
- type: precision_at_1 |
|
value: 58.4 |
|
- type: precision_at_10 |
|
value: 8.780000000000001 |
|
- type: precision_at_100 |
|
value: 0.968 |
|
- type: precision_at_1000 |
|
value: 0.099 |
|
- type: precision_at_3 |
|
value: 25.5 |
|
- type: precision_at_5 |
|
value: 16.46 |
|
- type: recall_at_1 |
|
value: 58.4 |
|
- type: recall_at_10 |
|
value: 87.8 |
|
- type: recall_at_100 |
|
value: 96.8 |
|
- type: recall_at_1000 |
|
value: 99 |
|
- type: recall_at_3 |
|
value: 76.5 |
|
- type: recall_at_5 |
|
value: 82.3 |
|
- task: |
|
type: Classification |
|
dataset: |
|
name: MTEB Waimai |
|
type: C-MTEB/waimai-classification |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: accuracy |
|
value: 86.21000000000001 |
|
- type: ap |
|
value: 69.17460264576461 |
|
- type: f1 |
|
value: 84.68032984659226 |
|
--- |
|
|
|
# annofung/Dmeta-embedding-zh-Q5_K_M-GGUF |
|
This model was converted to GGUF format from [`DMetaSoul/Dmeta-embedding-zh`](https://huggingface.co/DMetaSoul/Dmeta-embedding-zh) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space. |
|
Refer to the [original model card](https://huggingface.co/DMetaSoul/Dmeta-embedding-zh) for more details on the model. |
|
|
|
## Use with llama.cpp |
|
Install llama.cpp through brew (works on Mac and Linux) |
|
|
|
```bash |
|
brew install llama.cpp |
|
|
|
``` |
|
Invoke the llama.cpp server or the CLI. |
|
|
|
### CLI: |
|
```bash |
|
llama-cli --hf-repo annofung/Dmeta-embedding-zh-Q5_K_M-GGUF --hf-file dmeta-embedding-zh-q5_k_m.gguf -p "The meaning to life and the universe is" |
|
``` |
|
|
|
### Server: |
|
```bash |
|
llama-server --hf-repo annofung/Dmeta-embedding-zh-Q5_K_M-GGUF --hf-file dmeta-embedding-zh-q5_k_m.gguf -c 2048 |
|
``` |
|
|
|
Note: You can also use this checkpoint directly through the [usage steps](https://github.com/ggerganov/llama.cpp?tab=readme-ov-file#usage) listed in the Llama.cpp repo as well. |
|
|
|
Step 1: Clone llama.cpp from GitHub. |
|
``` |
|
git clone https://github.com/ggerganov/llama.cpp |
|
``` |
|
|
|
Step 2: Move into the llama.cpp folder and build it with `LLAMA_CURL=1` flag along with other hardware-specific flags (for ex: LLAMA_CUDA=1 for Nvidia GPUs on Linux). |
|
``` |
|
cd llama.cpp && LLAMA_CURL=1 make |
|
``` |
|
|
|
Step 3: Run inference through the main binary. |
|
``` |
|
./llama-cli --hf-repo annofung/Dmeta-embedding-zh-Q5_K_M-GGUF --hf-file dmeta-embedding-zh-q5_k_m.gguf -p "The meaning to life and the universe is" |
|
``` |
|
or |
|
``` |
|
./llama-server --hf-repo annofung/Dmeta-embedding-zh-Q5_K_M-GGUF --hf-file dmeta-embedding-zh-q5_k_m.gguf -c 2048 |
|
``` |
|
|
