|
--- |
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tags: |
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- mteb |
|
- llama-cpp |
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- gguf-my-repo |
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license: cc-by-nc-4.0 |
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library_name: sentence-transformers |
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base_model: TencentBAC/Conan-embedding-v1 |
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model-index: |
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- name: conan-embedding |
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results: |
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- task: |
|
type: STS |
|
dataset: |
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name: MTEB AFQMC |
|
type: C-MTEB/AFQMC |
|
config: default |
|
split: validation |
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revision: None |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 56.613572467148856 |
|
- type: cos_sim_spearman |
|
value: 60.66446211824284 |
|
- type: euclidean_pearson |
|
value: 58.42080485872613 |
|
- type: euclidean_spearman |
|
value: 59.82750030458164 |
|
- type: manhattan_pearson |
|
value: 58.39885271199772 |
|
- type: manhattan_spearman |
|
value: 59.817749720366734 |
|
- task: |
|
type: STS |
|
dataset: |
|
name: MTEB ATEC |
|
type: C-MTEB/ATEC |
|
config: default |
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split: test |
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revision: None |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 56.60530380552331 |
|
- type: cos_sim_spearman |
|
value: 58.63822441736707 |
|
- type: euclidean_pearson |
|
value: 62.18551665180664 |
|
- type: euclidean_spearman |
|
value: 58.23168804495912 |
|
- type: manhattan_pearson |
|
value: 62.17191480770053 |
|
- type: manhattan_spearman |
|
value: 58.22556219601401 |
|
- task: |
|
type: Classification |
|
dataset: |
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name: MTEB AmazonReviewsClassification (zh) |
|
type: mteb/amazon_reviews_multi |
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config: zh |
|
split: test |
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revision: 1399c76144fd37290681b995c656ef9b2e06e26d |
|
metrics: |
|
- type: accuracy |
|
value: 50.308 |
|
- type: f1 |
|
value: 46.927458607895126 |
|
- task: |
|
type: STS |
|
dataset: |
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name: MTEB BQ |
|
type: C-MTEB/BQ |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 72.6472074172711 |
|
- type: cos_sim_spearman |
|
value: 74.50748447236577 |
|
- type: euclidean_pearson |
|
value: 72.51833296451854 |
|
- type: euclidean_spearman |
|
value: 73.9898922606105 |
|
- type: manhattan_pearson |
|
value: 72.50184948939338 |
|
- type: manhattan_spearman |
|
value: 73.97797921509638 |
|
- task: |
|
type: Clustering |
|
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 |
|
metrics: |
|
- type: v_measure |
|
value: 60.63545326048343 |
|
- task: |
|
type: Clustering |
|
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 |
|
metrics: |
|
- type: v_measure |
|
value: 52.64834762325994 |
|
- task: |
|
type: Reranking |
|
dataset: |
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name: MTEB CMedQAv1 |
|
type: C-MTEB/CMedQAv1-reranking |
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config: default |
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split: test |
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revision: None |
|
metrics: |
|
- type: map |
|
value: 91.38528814655234 |
|
- type: mrr |
|
value: 93.35857142857144 |
|
- task: |
|
type: Reranking |
|
dataset: |
|
name: MTEB CMedQAv2 |
|
type: C-MTEB/CMedQAv2-reranking |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: map |
|
value: 89.72084678877096 |
|
- type: mrr |
|
value: 91.74380952380953 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
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 |
|
metrics: |
|
- type: map_at_1 |
|
value: 26.987 |
|
- type: map_at_10 |
|
value: 40.675 |
|
- type: map_at_100 |
|
value: 42.495 |
|
- type: map_at_1000 |
|
value: 42.596000000000004 |
|
- type: map_at_3 |
|
value: 36.195 |
|
- type: map_at_5 |
|
value: 38.704 |
|
- type: mrr_at_1 |
|
value: 41.21 |
|
- type: mrr_at_10 |
|
value: 49.816 |
|
- type: mrr_at_100 |
|
value: 50.743 |
|
- type: mrr_at_1000 |
|
value: 50.77700000000001 |
|
- type: mrr_at_3 |
|
value: 47.312 |
|
- type: mrr_at_5 |
|
value: 48.699999999999996 |
|
- type: ndcg_at_1 |
|
value: 41.21 |
|
- type: ndcg_at_10 |
|
value: 47.606 |
|
- type: ndcg_at_100 |
|
value: 54.457 |
|
- type: ndcg_at_1000 |
|
value: 56.16100000000001 |
|
- type: ndcg_at_3 |
|
value: 42.108000000000004 |
|
- type: ndcg_at_5 |
|
value: 44.393 |
|
- type: precision_at_1 |
|
value: 41.21 |
|
- type: precision_at_10 |
|
value: 10.593 |
|
- type: precision_at_100 |
|
value: 1.609 |
|
- type: precision_at_1000 |
|
value: 0.183 |
|
- type: precision_at_3 |
|
value: 23.881 |
|
- type: precision_at_5 |
|
value: 17.339 |
|
- type: recall_at_1 |
|
value: 26.987 |
|
- type: recall_at_10 |
|
value: 58.875 |
|
- type: recall_at_100 |
|
value: 87.023 |
|
- type: recall_at_1000 |
|
value: 98.328 |
|
- type: recall_at_3 |
|
value: 42.265 |
|
- type: recall_at_5 |
|
value: 49.334 |
|
- task: |
|
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: 85.91701743836441 |
|
- type: cos_sim_ap |
|
value: 92.53650618807644 |
|
- type: cos_sim_f1 |
|
value: 86.80265975431082 |
|
- type: cos_sim_precision |
|
value: 83.79025239338556 |
|
- type: cos_sim_recall |
|
value: 90.039747486556 |
|
- type: dot_accuracy |
|
value: 77.17378232110643 |
|
- type: dot_ap |
|
value: 85.40244368166546 |
|
- type: dot_f1 |
|
value: 79.03038001481951 |
|
- type: dot_precision |
|
value: 72.20502901353966 |
|
- type: dot_recall |
|
value: 87.2808043020809 |
|
- type: euclidean_accuracy |
|
value: 84.65423932651834 |
|
- type: euclidean_ap |
|
value: 91.47775530034588 |
|
- type: euclidean_f1 |
|
value: 85.64471499723298 |
|
- type: euclidean_precision |
|
value: 81.31567885666246 |
|
- type: euclidean_recall |
|
value: 90.46060322656068 |
|
- type: manhattan_accuracy |
|
value: 84.58208057726999 |
|
- type: manhattan_ap |
|
value: 91.46228709402014 |
|
- type: manhattan_f1 |
|
value: 85.6631626034444 |
|
- type: manhattan_precision |
|
value: 82.10075026795283 |
|
- type: manhattan_recall |
|
value: 89.5487491232172 |
|
- type: max_accuracy |
|
value: 85.91701743836441 |
|
- type: max_ap |
|
value: 92.53650618807644 |
|
- type: max_f1 |
|
value: 86.80265975431082 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
name: MTEB CovidRetrieval |
|
type: C-MTEB/CovidRetrieval |
|
config: default |
|
split: dev |
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revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 83.693 |
|
- type: map_at_10 |
|
value: 90.098 |
|
- type: map_at_100 |
|
value: 90.145 |
|
- type: map_at_1000 |
|
value: 90.146 |
|
- type: map_at_3 |
|
value: 89.445 |
|
- type: map_at_5 |
|
value: 89.935 |
|
- type: mrr_at_1 |
|
value: 83.878 |
|
- type: mrr_at_10 |
|
value: 90.007 |
|
- type: mrr_at_100 |
|
value: 90.045 |
|
- type: mrr_at_1000 |
|
value: 90.046 |
|
- type: mrr_at_3 |
|
value: 89.34 |
|
- type: mrr_at_5 |
|
value: 89.835 |
|
- type: ndcg_at_1 |
|
value: 84.089 |
|
- type: ndcg_at_10 |
|
value: 92.351 |
|
- type: ndcg_at_100 |
|
value: 92.54599999999999 |
|
- type: ndcg_at_1000 |
|
value: 92.561 |
|
- type: ndcg_at_3 |
|
value: 91.15299999999999 |
|
- type: ndcg_at_5 |
|
value: 91.968 |
|
- type: precision_at_1 |
|
value: 84.089 |
|
- type: precision_at_10 |
|
value: 10.011000000000001 |
|
- type: precision_at_100 |
|
value: 1.009 |
|
- type: precision_at_1000 |
|
value: 0.101 |
|
- type: precision_at_3 |
|
value: 32.28 |
|
- type: precision_at_5 |
|
value: 19.789 |
|
- type: recall_at_1 |
|
value: 83.693 |
|
- type: recall_at_10 |
|
value: 99.05199999999999 |
|
- type: recall_at_100 |
|
value: 99.895 |
|
- type: recall_at_1000 |
|
value: 100 |
|
- type: recall_at_3 |
|
value: 95.917 |
|
- type: recall_at_5 |
|
value: 97.893 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
name: MTEB DuRetrieval |
|
type: C-MTEB/DuRetrieval |
|
config: default |
|
split: dev |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 26.924 |
|
- type: map_at_10 |
|
value: 81.392 |
|
- type: map_at_100 |
|
value: 84.209 |
|
- type: map_at_1000 |
|
value: 84.237 |
|
- type: map_at_3 |
|
value: 56.998000000000005 |
|
- type: map_at_5 |
|
value: 71.40100000000001 |
|
- type: mrr_at_1 |
|
value: 91.75 |
|
- type: mrr_at_10 |
|
value: 94.45 |
|
- type: mrr_at_100 |
|
value: 94.503 |
|
- type: mrr_at_1000 |
|
value: 94.505 |
|
- type: mrr_at_3 |
|
value: 94.258 |
|
- type: mrr_at_5 |
|
value: 94.381 |
|
- type: ndcg_at_1 |
|
value: 91.75 |
|
- type: ndcg_at_10 |
|
value: 88.53 |
|
- type: ndcg_at_100 |
|
value: 91.13900000000001 |
|
- type: ndcg_at_1000 |
|
value: 91.387 |
|
- type: ndcg_at_3 |
|
value: 87.925 |
|
- type: ndcg_at_5 |
|
value: 86.461 |
|
- type: precision_at_1 |
|
value: 91.75 |
|
- type: precision_at_10 |
|
value: 42.05 |
|
- type: precision_at_100 |
|
value: 4.827 |
|
- type: precision_at_1000 |
|
value: 0.48900000000000005 |
|
- type: precision_at_3 |
|
value: 78.55 |
|
- type: precision_at_5 |
|
value: 65.82000000000001 |
|
- type: recall_at_1 |
|
value: 26.924 |
|
- type: recall_at_10 |
|
value: 89.338 |
|
- type: recall_at_100 |
|
value: 97.856 |
|
- type: recall_at_1000 |
|
value: 99.11 |
|
- type: recall_at_3 |
|
value: 59.202999999999996 |
|
- type: recall_at_5 |
|
value: 75.642 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
name: MTEB EcomRetrieval |
|
type: C-MTEB/EcomRetrieval |
|
config: default |
|
split: dev |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 54.800000000000004 |
|
- type: map_at_10 |
|
value: 65.613 |
|
- type: map_at_100 |
|
value: 66.185 |
|
- type: map_at_1000 |
|
value: 66.191 |
|
- type: map_at_3 |
|
value: 62.8 |
|
- type: map_at_5 |
|
value: 64.535 |
|
- type: mrr_at_1 |
|
value: 54.800000000000004 |
|
- type: mrr_at_10 |
|
value: 65.613 |
|
- type: mrr_at_100 |
|
value: 66.185 |
|
- type: mrr_at_1000 |
|
value: 66.191 |
|
- type: mrr_at_3 |
|
value: 62.8 |
|
- type: mrr_at_5 |
|
value: 64.535 |
|
- type: ndcg_at_1 |
|
value: 54.800000000000004 |
|
- type: ndcg_at_10 |
|
value: 70.991 |
|
- type: ndcg_at_100 |
|
value: 73.434 |
|
- type: ndcg_at_1000 |
|
value: 73.587 |
|
- type: ndcg_at_3 |
|
value: 65.324 |
|
- type: ndcg_at_5 |
|
value: 68.431 |
|
- type: precision_at_1 |
|
value: 54.800000000000004 |
|
- type: precision_at_10 |
|
value: 8.790000000000001 |
|
- type: precision_at_100 |
|
value: 0.9860000000000001 |
|
- type: precision_at_1000 |
|
value: 0.1 |
|
- type: precision_at_3 |
|
value: 24.2 |
|
- type: precision_at_5 |
|
value: 16.02 |
|
- type: recall_at_1 |
|
value: 54.800000000000004 |
|
- type: recall_at_10 |
|
value: 87.9 |
|
- type: recall_at_100 |
|
value: 98.6 |
|
- type: recall_at_1000 |
|
value: 99.8 |
|
- type: recall_at_3 |
|
value: 72.6 |
|
- type: recall_at_5 |
|
value: 80.10000000000001 |
|
- task: |
|
type: Classification |
|
dataset: |
|
name: MTEB IFlyTek |
|
type: C-MTEB/IFlyTek-classification |
|
config: default |
|
split: validation |
|
revision: None |
|
metrics: |
|
- type: accuracy |
|
value: 51.94305502116199 |
|
- type: f1 |
|
value: 39.82197338426721 |
|
- task: |
|
type: Classification |
|
dataset: |
|
name: MTEB JDReview |
|
type: C-MTEB/JDReview-classification |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: accuracy |
|
value: 90.31894934333957 |
|
- type: ap |
|
value: 63.89821836499594 |
|
- type: f1 |
|
value: 85.93687177603624 |
|
- task: |
|
type: STS |
|
dataset: |
|
name: MTEB LCQMC |
|
type: C-MTEB/LCQMC |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 73.18906216730208 |
|
- type: cos_sim_spearman |
|
value: 79.44570226735877 |
|
- type: euclidean_pearson |
|
value: 78.8105072242798 |
|
- type: euclidean_spearman |
|
value: 79.15605680863212 |
|
- type: manhattan_pearson |
|
value: 78.80576507484064 |
|
- type: manhattan_spearman |
|
value: 79.14625534068364 |
|
- task: |
|
type: Reranking |
|
dataset: |
|
name: MTEB MMarcoReranking |
|
type: C-MTEB/Mmarco-reranking |
|
config: default |
|
split: dev |
|
revision: None |
|
metrics: |
|
- type: map |
|
value: 41.58107192600853 |
|
- type: mrr |
|
value: 41.37063492063492 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
name: MTEB MMarcoRetrieval |
|
type: C-MTEB/MMarcoRetrieval |
|
config: default |
|
split: dev |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 68.33 |
|
- type: map_at_10 |
|
value: 78.261 |
|
- type: map_at_100 |
|
value: 78.522 |
|
- type: map_at_1000 |
|
value: 78.527 |
|
- type: map_at_3 |
|
value: 76.236 |
|
- type: map_at_5 |
|
value: 77.557 |
|
- type: mrr_at_1 |
|
value: 70.602 |
|
- type: mrr_at_10 |
|
value: 78.779 |
|
- type: mrr_at_100 |
|
value: 79.00500000000001 |
|
- type: mrr_at_1000 |
|
value: 79.01 |
|
- type: mrr_at_3 |
|
value: 77.037 |
|
- type: mrr_at_5 |
|
value: 78.157 |
|
- type: ndcg_at_1 |
|
value: 70.602 |
|
- type: ndcg_at_10 |
|
value: 82.254 |
|
- type: ndcg_at_100 |
|
value: 83.319 |
|
- type: ndcg_at_1000 |
|
value: 83.449 |
|
- type: ndcg_at_3 |
|
value: 78.46 |
|
- type: ndcg_at_5 |
|
value: 80.679 |
|
- type: precision_at_1 |
|
value: 70.602 |
|
- type: precision_at_10 |
|
value: 9.989 |
|
- type: precision_at_100 |
|
value: 1.05 |
|
- type: precision_at_1000 |
|
value: 0.106 |
|
- type: precision_at_3 |
|
value: 29.598999999999997 |
|
- type: precision_at_5 |
|
value: 18.948 |
|
- type: recall_at_1 |
|
value: 68.33 |
|
- type: recall_at_10 |
|
value: 94.00800000000001 |
|
- type: recall_at_100 |
|
value: 98.589 |
|
- type: recall_at_1000 |
|
value: 99.60799999999999 |
|
- type: recall_at_3 |
|
value: 84.057 |
|
- type: recall_at_5 |
|
value: 89.32900000000001 |
|
- 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: 78.13718897108272 |
|
- type: f1 |
|
value: 74.07613180855328 |
|
- 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: 86.20040349697376 |
|
- type: f1 |
|
value: 85.05282136519973 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
name: MTEB MedicalRetrieval |
|
type: C-MTEB/MedicalRetrieval |
|
config: default |
|
split: dev |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 56.8 |
|
- type: map_at_10 |
|
value: 64.199 |
|
- type: map_at_100 |
|
value: 64.89 |
|
- type: map_at_1000 |
|
value: 64.917 |
|
- type: map_at_3 |
|
value: 62.383 |
|
- type: map_at_5 |
|
value: 63.378 |
|
- type: mrr_at_1 |
|
value: 56.8 |
|
- type: mrr_at_10 |
|
value: 64.199 |
|
- type: mrr_at_100 |
|
value: 64.89 |
|
- type: mrr_at_1000 |
|
value: 64.917 |
|
- type: mrr_at_3 |
|
value: 62.383 |
|
- type: mrr_at_5 |
|
value: 63.378 |
|
- type: ndcg_at_1 |
|
value: 56.8 |
|
- type: ndcg_at_10 |
|
value: 67.944 |
|
- type: ndcg_at_100 |
|
value: 71.286 |
|
- type: ndcg_at_1000 |
|
value: 71.879 |
|
- type: ndcg_at_3 |
|
value: 64.163 |
|
- type: ndcg_at_5 |
|
value: 65.96600000000001 |
|
- type: precision_at_1 |
|
value: 56.8 |
|
- type: precision_at_10 |
|
value: 7.9799999999999995 |
|
- type: precision_at_100 |
|
value: 0.954 |
|
- type: precision_at_1000 |
|
value: 0.1 |
|
- type: precision_at_3 |
|
value: 23.1 |
|
- type: precision_at_5 |
|
value: 14.74 |
|
- type: recall_at_1 |
|
value: 56.8 |
|
- type: recall_at_10 |
|
value: 79.80000000000001 |
|
- type: recall_at_100 |
|
value: 95.39999999999999 |
|
- type: recall_at_1000 |
|
value: 99.8 |
|
- type: recall_at_3 |
|
value: 69.3 |
|
- type: recall_at_5 |
|
value: 73.7 |
|
- task: |
|
type: Classification |
|
dataset: |
|
name: MTEB MultilingualSentiment |
|
type: C-MTEB/MultilingualSentiment-classification |
|
config: default |
|
split: validation |
|
revision: None |
|
metrics: |
|
- type: accuracy |
|
value: 78.57666666666667 |
|
- type: f1 |
|
value: 78.23373528202681 |
|
- task: |
|
type: PairClassification |
|
dataset: |
|
name: MTEB Ocnli |
|
type: C-MTEB/OCNLI |
|
config: default |
|
split: validation |
|
revision: None |
|
metrics: |
|
- type: cos_sim_accuracy |
|
value: 85.43584190579317 |
|
- type: cos_sim_ap |
|
value: 90.76665640338129 |
|
- type: cos_sim_f1 |
|
value: 86.5021770682148 |
|
- type: cos_sim_precision |
|
value: 79.82142857142858 |
|
- type: cos_sim_recall |
|
value: 94.40337909186906 |
|
- type: dot_accuracy |
|
value: 78.66811044937737 |
|
- type: dot_ap |
|
value: 85.84084363880804 |
|
- type: dot_f1 |
|
value: 80.10075566750629 |
|
- type: dot_precision |
|
value: 76.58959537572254 |
|
- type: dot_recall |
|
value: 83.9493136219641 |
|
- type: euclidean_accuracy |
|
value: 84.46128857606931 |
|
- type: euclidean_ap |
|
value: 88.62351100230491 |
|
- type: euclidean_f1 |
|
value: 85.7709469509172 |
|
- type: euclidean_precision |
|
value: 80.8411214953271 |
|
- type: euclidean_recall |
|
value: 91.34107708553326 |
|
- type: manhattan_accuracy |
|
value: 84.51543042772063 |
|
- type: manhattan_ap |
|
value: 88.53975607870393 |
|
- type: manhattan_f1 |
|
value: 85.75697211155378 |
|
- type: manhattan_precision |
|
value: 81.14985862393968 |
|
- type: manhattan_recall |
|
value: 90.91869060190075 |
|
- type: max_accuracy |
|
value: 85.43584190579317 |
|
- type: max_ap |
|
value: 90.76665640338129 |
|
- type: max_f1 |
|
value: 86.5021770682148 |
|
- task: |
|
type: Classification |
|
dataset: |
|
name: MTEB OnlineShopping |
|
type: C-MTEB/OnlineShopping-classification |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: accuracy |
|
value: 95.06999999999998 |
|
- type: ap |
|
value: 93.45104559324996 |
|
- type: f1 |
|
value: 95.06036329426092 |
|
- task: |
|
type: STS |
|
dataset: |
|
name: MTEB PAWSX |
|
type: C-MTEB/PAWSX |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 40.01998290519605 |
|
- type: cos_sim_spearman |
|
value: 46.5989769986853 |
|
- type: euclidean_pearson |
|
value: 45.37905883182924 |
|
- type: euclidean_spearman |
|
value: 46.22213849806378 |
|
- type: manhattan_pearson |
|
value: 45.40925124776211 |
|
- type: manhattan_spearman |
|
value: 46.250705124226386 |
|
- task: |
|
type: STS |
|
dataset: |
|
name: MTEB QBQTC |
|
type: C-MTEB/QBQTC |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 42.719516197112526 |
|
- type: cos_sim_spearman |
|
value: 44.57507789581106 |
|
- type: euclidean_pearson |
|
value: 35.73062264160721 |
|
- type: euclidean_spearman |
|
value: 40.473523909913695 |
|
- type: manhattan_pearson |
|
value: 35.69868964086357 |
|
- type: manhattan_spearman |
|
value: 40.46349925372903 |
|
- 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: 62.340118285801104 |
|
- type: cos_sim_spearman |
|
value: 67.72781908620632 |
|
- type: euclidean_pearson |
|
value: 63.161965746091596 |
|
- type: euclidean_spearman |
|
value: 67.36825684340769 |
|
- type: manhattan_pearson |
|
value: 63.089863788261425 |
|
- type: manhattan_spearman |
|
value: 67.40868898995384 |
|
- task: |
|
type: STS |
|
dataset: |
|
name: MTEB STSB |
|
type: C-MTEB/STSB |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: cos_sim_pearson |
|
value: 79.1646360962365 |
|
- type: cos_sim_spearman |
|
value: 81.24426700767087 |
|
- type: euclidean_pearson |
|
value: 79.43826409936123 |
|
- type: euclidean_spearman |
|
value: 79.71787965300125 |
|
- type: manhattan_pearson |
|
value: 79.43377784961737 |
|
- type: manhattan_spearman |
|
value: 79.69348376886967 |
|
- task: |
|
type: Reranking |
|
dataset: |
|
name: MTEB T2Reranking |
|
type: C-MTEB/T2Reranking |
|
config: default |
|
split: dev |
|
revision: None |
|
metrics: |
|
- type: map |
|
value: 68.35595092507496 |
|
- type: mrr |
|
value: 79.00244892585788 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
name: MTEB T2Retrieval |
|
type: C-MTEB/T2Retrieval |
|
config: default |
|
split: dev |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 26.588 |
|
- type: map_at_10 |
|
value: 75.327 |
|
- type: map_at_100 |
|
value: 79.095 |
|
- type: map_at_1000 |
|
value: 79.163 |
|
- type: map_at_3 |
|
value: 52.637 |
|
- type: map_at_5 |
|
value: 64.802 |
|
- type: mrr_at_1 |
|
value: 88.103 |
|
- type: mrr_at_10 |
|
value: 91.29899999999999 |
|
- type: mrr_at_100 |
|
value: 91.408 |
|
- type: mrr_at_1000 |
|
value: 91.411 |
|
- type: mrr_at_3 |
|
value: 90.801 |
|
- type: mrr_at_5 |
|
value: 91.12700000000001 |
|
- type: ndcg_at_1 |
|
value: 88.103 |
|
- type: ndcg_at_10 |
|
value: 83.314 |
|
- type: ndcg_at_100 |
|
value: 87.201 |
|
- type: ndcg_at_1000 |
|
value: 87.83999999999999 |
|
- type: ndcg_at_3 |
|
value: 84.408 |
|
- type: ndcg_at_5 |
|
value: 83.078 |
|
- type: precision_at_1 |
|
value: 88.103 |
|
- type: precision_at_10 |
|
value: 41.638999999999996 |
|
- type: precision_at_100 |
|
value: 5.006 |
|
- type: precision_at_1000 |
|
value: 0.516 |
|
- type: precision_at_3 |
|
value: 73.942 |
|
- type: precision_at_5 |
|
value: 62.056 |
|
- type: recall_at_1 |
|
value: 26.588 |
|
- type: recall_at_10 |
|
value: 82.819 |
|
- type: recall_at_100 |
|
value: 95.334 |
|
- type: recall_at_1000 |
|
value: 98.51299999999999 |
|
- type: recall_at_3 |
|
value: 54.74 |
|
- type: recall_at_5 |
|
value: 68.864 |
|
- task: |
|
type: Classification |
|
dataset: |
|
name: MTEB TNews |
|
type: C-MTEB/TNews-classification |
|
config: default |
|
split: validation |
|
revision: None |
|
metrics: |
|
- type: accuracy |
|
value: 55.029 |
|
- type: f1 |
|
value: 53.043617905026764 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
name: MTEB ThuNewsClusteringP2P |
|
type: C-MTEB/ThuNewsClusteringP2P |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: v_measure |
|
value: 77.83675116835911 |
|
- task: |
|
type: Clustering |
|
dataset: |
|
name: MTEB ThuNewsClusteringS2S |
|
type: C-MTEB/ThuNewsClusteringS2S |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: v_measure |
|
value: 74.19701455865277 |
|
- task: |
|
type: Retrieval |
|
dataset: |
|
name: MTEB VideoRetrieval |
|
type: C-MTEB/VideoRetrieval |
|
config: default |
|
split: dev |
|
revision: None |
|
metrics: |
|
- type: map_at_1 |
|
value: 64.7 |
|
- type: map_at_10 |
|
value: 75.593 |
|
- type: map_at_100 |
|
value: 75.863 |
|
- type: map_at_1000 |
|
value: 75.863 |
|
- type: map_at_3 |
|
value: 73.63300000000001 |
|
- type: map_at_5 |
|
value: 74.923 |
|
- type: mrr_at_1 |
|
value: 64.7 |
|
- type: mrr_at_10 |
|
value: 75.593 |
|
- type: mrr_at_100 |
|
value: 75.863 |
|
- type: mrr_at_1000 |
|
value: 75.863 |
|
- type: mrr_at_3 |
|
value: 73.63300000000001 |
|
- type: mrr_at_5 |
|
value: 74.923 |
|
- type: ndcg_at_1 |
|
value: 64.7 |
|
- type: ndcg_at_10 |
|
value: 80.399 |
|
- type: ndcg_at_100 |
|
value: 81.517 |
|
- type: ndcg_at_1000 |
|
value: 81.517 |
|
- type: ndcg_at_3 |
|
value: 76.504 |
|
- type: ndcg_at_5 |
|
value: 78.79899999999999 |
|
- type: precision_at_1 |
|
value: 64.7 |
|
- type: precision_at_10 |
|
value: 9.520000000000001 |
|
- type: precision_at_100 |
|
value: 1 |
|
- type: precision_at_1000 |
|
value: 0.1 |
|
- type: precision_at_3 |
|
value: 28.266999999999996 |
|
- type: precision_at_5 |
|
value: 18.060000000000002 |
|
- type: recall_at_1 |
|
value: 64.7 |
|
- type: recall_at_10 |
|
value: 95.19999999999999 |
|
- type: recall_at_100 |
|
value: 100 |
|
- type: recall_at_1000 |
|
value: 100 |
|
- type: recall_at_3 |
|
value: 84.8 |
|
- type: recall_at_5 |
|
value: 90.3 |
|
- task: |
|
type: Classification |
|
dataset: |
|
name: MTEB Waimai |
|
type: C-MTEB/waimai-classification |
|
config: default |
|
split: test |
|
revision: None |
|
metrics: |
|
- type: accuracy |
|
value: 89.69999999999999 |
|
- type: ap |
|
value: 75.91371640164184 |
|
- type: f1 |
|
value: 88.34067777698694 |
|
--- |
|
|
|
# Saco93/Conan-embedding-v1-Q4_K_S-GGUF |
|
This model was converted to GGUF format from [`TencentBAC/Conan-embedding-v1`](https://huggingface.co/TencentBAC/Conan-embedding-v1) 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/TencentBAC/Conan-embedding-v1) 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 Saco93/Conan-embedding-v1-Q4_K_S-GGUF --hf-file conan-embedding-v1-q4_k_s.gguf -p "The meaning to life and the universe is" |
|
``` |
|
|
|
### Server: |
|
```bash |
|
llama-server --hf-repo Saco93/Conan-embedding-v1-Q4_K_S-GGUF --hf-file conan-embedding-v1-q4_k_s.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 Saco93/Conan-embedding-v1-Q4_K_S-GGUF --hf-file conan-embedding-v1-q4_k_s.gguf -p "The meaning to life and the universe is" |
|
``` |
|
or |
|
``` |
|
./llama-server --hf-repo Saco93/Conan-embedding-v1-Q4_K_S-GGUF --hf-file conan-embedding-v1-q4_k_s.gguf -c 2048 |
|
``` |
|
|
