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1_Pooling/config.json ADDED
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+ {
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+ "word_embedding_dimension": 1024,
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+ "pooling_mode_cls_token": true,
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+ "pooling_mode_mean_tokens": false,
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+ "pooling_mode_max_tokens": false,
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+ "pooling_mode_mean_sqrt_len_tokens": false,
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+ "pooling_mode_weightedmean_tokens": false,
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+ "pooling_mode_lasttoken": false
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+ }
README.md CHANGED
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  ---
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- license: apache-2.0
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
3
  ---
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
  ---
2
+ tags:
3
+ - mteb
4
+ model-index:
5
+ - name: xiaobu-embedding
6
+ results:
7
+ - task:
8
+ type: STS
9
+ dataset:
10
+ type: C-MTEB/AFQMC
11
+ name: MTEB AFQMC
12
+ config: default
13
+ split: validation
14
+ revision: None
15
+ metrics:
16
+ - type: cos_sim_pearson
17
+ value: 49.37874132528482
18
+ - type: cos_sim_spearman
19
+ value: 54.84722470052176
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+ - type: euclidean_pearson
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+ value: 53.0495882931575
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+ - type: euclidean_spearman
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+ value: 54.847727301700665
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+ - type: manhattan_pearson
25
+ value: 53.0632140838278
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+ - type: manhattan_spearman
27
+ value: 54.8744258024692
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+ - task:
29
+ type: STS
30
+ dataset:
31
+ type: C-MTEB/ATEC
32
+ name: MTEB ATEC
33
+ config: default
34
+ split: test
35
+ revision: None
36
+ metrics:
37
+ - type: cos_sim_pearson
38
+ value: 48.15992903013723
39
+ - type: cos_sim_spearman
40
+ value: 55.13198035464577
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+ - type: euclidean_pearson
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+ value: 55.435876753245715
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+ - type: euclidean_spearman
44
+ value: 55.13215936702871
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+ - type: manhattan_pearson
46
+ value: 55.41429518223402
47
+ - type: manhattan_spearman
48
+ value: 55.13363087679285
49
+ - task:
50
+ type: Classification
51
+ dataset:
52
+ type: mteb/amazon_reviews_multi
53
+ name: MTEB AmazonReviewsClassification (zh)
54
+ config: zh
55
+ split: test
56
+ revision: 1399c76144fd37290681b995c656ef9b2e06e26d
57
+ metrics:
58
+ - type: accuracy
59
+ value: 46.722
60
+ - type: f1
61
+ value: 45.039340641893205
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+ - task:
63
+ type: STS
64
+ dataset:
65
+ type: C-MTEB/BQ
66
+ name: MTEB BQ
67
+ config: default
68
+ split: test
69
+ revision: None
70
+ metrics:
71
+ - type: cos_sim_pearson
72
+ value: 63.517830355554224
73
+ - type: cos_sim_spearman
74
+ value: 65.57007801018649
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+ - type: euclidean_pearson
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+ value: 64.05153340906585
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+ - type: euclidean_spearman
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+ value: 65.5696865661119
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+ - type: manhattan_pearson
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+ value: 63.95710619755406
81
+ - type: manhattan_spearman
82
+ value: 65.48565785379489
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+ - task:
84
+ type: Clustering
85
+ dataset:
86
+ type: C-MTEB/CLSClusteringP2P
87
+ name: MTEB CLSClusteringP2P
88
+ config: default
89
+ split: test
90
+ revision: None
91
+ metrics:
92
+ - type: v_measure
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+ value: 43.24046498507819
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+ - task:
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+ type: Clustering
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+ dataset:
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+ type: C-MTEB/CLSClusteringS2S
98
+ name: MTEB CLSClusteringS2S
99
+ config: default
100
+ split: test
101
+ revision: None
102
+ metrics:
103
+ - type: v_measure
104
+ value: 41.22618199372116
105
+ - task:
106
+ type: Reranking
107
+ dataset:
108
+ type: C-MTEB/CMedQAv1-reranking
109
+ name: MTEB CMedQAv1
110
+ config: default
111
+ split: test
112
+ revision: None
113
+ metrics:
114
+ - type: map
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+ value: 87.12213224673621
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+ - type: mrr
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+ value: 89.57150793650794
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+ - task:
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+ type: Reranking
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+ dataset:
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+ type: C-MTEB/CMedQAv2-reranking
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+ name: MTEB CMedQAv2
123
+ config: default
124
+ split: test
125
+ revision: None
126
+ metrics:
127
+ - type: map
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+ value: 87.57290061886421
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+ - type: mrr
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+ value: 90.19202380952382
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+ - task:
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+ type: Retrieval
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+ dataset:
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+ type: C-MTEB/CmedqaRetrieval
135
+ name: MTEB CmedqaRetrieval
136
+ config: default
137
+ split: dev
138
+ revision: None
139
+ metrics:
140
+ - type: map_at_1
141
+ value: 25.22
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+ - type: map_at_10
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+ value: 37.604
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+ - type: map_at_100
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+ value: 39.501
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+ - type: map_at_1000
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+ - type: map_at_3
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+ value: 33.378
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+ - type: map_at_5
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+ value: 35.774
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+ - type: mrr_at_1
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+ value: 38.385000000000005
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+ - type: mrr_at_10
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+ value: 46.487
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+ - type: mrr_at_100
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+ value: 47.504999999999995
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+ - type: mrr_at_1000
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+ value: 47.548
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+ - type: mrr_at_3
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+ value: 43.885999999999996
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+ - type: mrr_at_5
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+ value: 45.373000000000005
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+ - type: ndcg_at_1
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+ value: 38.385000000000005
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+ - type: ndcg_at_10
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+ value: 44.224999999999994
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+ - type: ndcg_at_100
169
+ value: 51.637
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+ - type: ndcg_at_1000
171
+ value: 53.55799999999999
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+ - type: ndcg_at_3
173
+ value: 38.845
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+ - type: ndcg_at_5
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+ value: 41.163
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+ - type: precision_at_1
177
+ value: 38.385000000000005
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+ - type: precision_at_10
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+ value: 9.812
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+ - type: precision_at_100
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+ value: 1.58
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+ - type: precision_at_1000
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+ value: 0.183
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+ - type: precision_at_3
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+ value: 21.88
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+ - type: precision_at_5
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+ value: 15.974
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+ - type: recall_at_1
189
+ value: 25.22
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+ - type: recall_at_10
191
+ value: 54.897
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+ - type: recall_at_100
193
+ value: 85.469
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+ - type: recall_at_1000
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+ value: 98.18599999999999
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+ - type: recall_at_3
197
+ value: 38.815
198
+ - type: recall_at_5
199
+ value: 45.885
200
+ - task:
201
+ type: PairClassification
202
+ dataset:
203
+ type: C-MTEB/CMNLI
204
+ name: MTEB Cmnli
205
+ config: default
206
+ split: validation
207
+ revision: None
208
+ metrics:
209
+ - type: cos_sim_accuracy
210
+ value: 83.22309079975948
211
+ - type: cos_sim_ap
212
+ value: 89.94833400328307
213
+ - type: cos_sim_f1
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+ value: 84.39319055464031
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+ - type: cos_sim_precision
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+ value: 79.5774647887324
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+ - type: cos_sim_recall
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+ value: 89.82931961655366
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+ - type: dot_accuracy
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+ value: 83.22309079975948
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+ - type: dot_ap
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+ value: 89.95618559578415
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+ - type: dot_f1
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+ value: 84.41173239591345
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+ - type: dot_precision
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+ value: 79.61044343141317
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+ - type: dot_recall
228
+ value: 89.82931961655366
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+ - type: euclidean_accuracy
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+ value: 83.23511725796753
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+ - type: euclidean_ap
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+ value: 89.94836342787318
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+ - type: euclidean_f1
234
+ value: 84.40550133096718
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+ - type: euclidean_precision
236
+ value: 80.29120067524794
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+ - type: euclidean_recall
238
+ value: 88.9642272620996
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+ - type: manhattan_accuracy
240
+ value: 83.23511725796753
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+ - type: manhattan_ap
242
+ value: 89.9450103956978
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+ - type: manhattan_f1
244
+ value: 84.44444444444444
245
+ - type: manhattan_precision
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+ value: 80.09647651006712
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+ - type: manhattan_recall
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+ value: 89.29155950432546
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+ - type: max_accuracy
250
+ value: 83.23511725796753
251
+ - type: max_ap
252
+ value: 89.95618559578415
253
+ - type: max_f1
254
+ value: 84.44444444444444
255
+ - task:
256
+ type: Retrieval
257
+ dataset:
258
+ type: C-MTEB/CovidRetrieval
259
+ name: MTEB CovidRetrieval
260
+ config: default
261
+ split: dev
262
+ revision: None
263
+ metrics:
264
+ - type: map_at_1
265
+ value: 76.87
266
+ - type: map_at_10
267
+ value: 84.502
268
+ - type: map_at_100
269
+ value: 84.615
270
+ - type: map_at_1000
271
+ value: 84.617
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+ - type: map_at_3
273
+ value: 83.127
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+ - type: map_at_5
275
+ value: 83.99600000000001
276
+ - type: mrr_at_1
277
+ value: 77.02799999999999
278
+ - type: mrr_at_10
279
+ value: 84.487
280
+ - type: mrr_at_100
281
+ value: 84.59299999999999
282
+ - type: mrr_at_1000
283
+ value: 84.59400000000001
284
+ - type: mrr_at_3
285
+ value: 83.193
286
+ - type: mrr_at_5
287
+ value: 83.994
288
+ - type: ndcg_at_1
289
+ value: 77.134
290
+ - type: ndcg_at_10
291
+ value: 87.68599999999999
292
+ - type: ndcg_at_100
293
+ value: 88.17099999999999
294
+ - type: ndcg_at_1000
295
+ value: 88.21
296
+ - type: ndcg_at_3
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+ value: 84.993
298
+ - type: ndcg_at_5
299
+ value: 86.519
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+ - type: precision_at_1
301
+ value: 77.134
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+ - type: precision_at_10
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+ value: 9.841999999999999
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+ - type: precision_at_100
305
+ value: 1.006
306
+ - type: precision_at_1000
307
+ value: 0.101
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+ - type: precision_at_3
309
+ value: 30.313000000000002
310
+ - type: precision_at_5
311
+ value: 18.945999999999998
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+ - type: recall_at_1
313
+ value: 76.87
314
+ - type: recall_at_10
315
+ value: 97.418
316
+ - type: recall_at_100
317
+ value: 99.579
318
+ - type: recall_at_1000
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+ value: 99.895
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+ - type: recall_at_3
321
+ value: 90.227
322
+ - type: recall_at_5
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+ value: 93.888
324
+ - task:
325
+ type: Retrieval
326
+ dataset:
327
+ type: C-MTEB/DuRetrieval
328
+ name: MTEB DuRetrieval
329
+ config: default
330
+ split: dev
331
+ revision: None
332
+ metrics:
333
+ - type: map_at_1
334
+ value: 25.941
335
+ - type: map_at_10
336
+ value: 78.793
337
+ - type: map_at_100
338
+ value: 81.57799999999999
339
+ - type: map_at_1000
340
+ value: 81.626
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+ - type: map_at_3
342
+ value: 54.749
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+ - type: map_at_5
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+ value: 69.16
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+ - type: mrr_at_1
346
+ value: 90.45
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+ - type: mrr_at_10
348
+ value: 93.406
349
+ - type: mrr_at_100
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+ value: 93.453
351
+ - type: mrr_at_1000
352
+ value: 93.45700000000001
353
+ - type: mrr_at_3
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+ value: 93.10000000000001
355
+ - type: mrr_at_5
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+ value: 93.27499999999999
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+ - type: ndcg_at_1
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+ value: 90.45
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+ - type: ndcg_at_10
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+ value: 86.44500000000001
361
+ - type: ndcg_at_100
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+ value: 89.28399999999999
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+ - type: ndcg_at_1000
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+ value: 89.739
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+ - type: ndcg_at_3
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+ value: 85.62100000000001
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+ - type: ndcg_at_5
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+ value: 84.441
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+ - type: precision_at_1
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+ value: 90.45
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+ - type: precision_at_10
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+ value: 41.19
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+ - type: precision_at_100
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+ value: 4.761
375
+ - type: precision_at_1000
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+ value: 0.48700000000000004
377
+ - type: precision_at_3
378
+ value: 76.583
379
+ - type: precision_at_5
380
+ value: 64.68
381
+ - type: recall_at_1
382
+ value: 25.941
383
+ - type: recall_at_10
384
+ value: 87.443
385
+ - type: recall_at_100
386
+ value: 96.54
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+ - type: recall_at_1000
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+ value: 98.906
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+ - type: recall_at_3
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+ value: 56.947
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+ - type: recall_at_5
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+ value: 73.714
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+ - task:
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+ type: Retrieval
395
+ dataset:
396
+ type: C-MTEB/EcomRetrieval
397
+ name: MTEB EcomRetrieval
398
+ config: default
399
+ split: dev
400
+ revision: None
401
+ metrics:
402
+ - type: map_at_1
403
+ value: 52.900000000000006
404
+ - type: map_at_10
405
+ value: 63.144
406
+ - type: map_at_100
407
+ value: 63.634
408
+ - type: map_at_1000
409
+ value: 63.644999999999996
410
+ - type: map_at_3
411
+ value: 60.817
412
+ - type: map_at_5
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+ value: 62.202
414
+ - type: mrr_at_1
415
+ value: 52.900000000000006
416
+ - type: mrr_at_10
417
+ value: 63.144
418
+ - type: mrr_at_100
419
+ value: 63.634
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+ - type: mrr_at_1000
421
+ value: 63.644999999999996
422
+ - type: mrr_at_3
423
+ value: 60.817
424
+ - type: mrr_at_5
425
+ value: 62.202
426
+ - type: ndcg_at_1
427
+ value: 52.900000000000006
428
+ - type: ndcg_at_10
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+ value: 68.042
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+ - type: ndcg_at_100
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+ value: 70.417
432
+ - type: ndcg_at_1000
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+ value: 70.722
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+ - type: ndcg_at_3
435
+ value: 63.287000000000006
436
+ - type: ndcg_at_5
437
+ value: 65.77
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+ - type: precision_at_1
439
+ value: 52.900000000000006
440
+ - type: precision_at_10
441
+ value: 8.34
442
+ - type: precision_at_100
443
+ value: 0.9450000000000001
444
+ - type: precision_at_1000
445
+ value: 0.097
446
+ - type: precision_at_3
447
+ value: 23.467
448
+ - type: precision_at_5
449
+ value: 15.28
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+ - type: recall_at_1
451
+ value: 52.900000000000006
452
+ - type: recall_at_10
453
+ value: 83.39999999999999
454
+ - type: recall_at_100
455
+ value: 94.5
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+ - type: recall_at_1000
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+ value: 96.89999999999999
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+ - type: recall_at_3
459
+ value: 70.39999999999999
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+ - type: recall_at_5
461
+ value: 76.4
462
+ - task:
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+ type: Classification
464
+ dataset:
465
+ type: C-MTEB/IFlyTek-classification
466
+ name: MTEB IFlyTek
467
+ config: default
468
+ split: validation
469
+ revision: None
470
+ metrics:
471
+ - type: accuracy
472
+ value: 49.74220854174683
473
+ - type: f1
474
+ value: 38.01399980618159
475
+ - task:
476
+ type: Classification
477
+ dataset:
478
+ type: C-MTEB/JDReview-classification
479
+ name: MTEB JDReview
480
+ config: default
481
+ split: test
482
+ revision: None
483
+ metrics:
484
+ - type: accuracy
485
+ value: 86.73545966228893
486
+ - type: ap
487
+ value: 55.72394235169542
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+ - type: f1
489
+ value: 81.58550390953492
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+ - task:
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+ type: STS
492
+ dataset:
493
+ type: C-MTEB/LCQMC
494
+ name: MTEB LCQMC
495
+ config: default
496
+ split: test
497
+ revision: None
498
+ metrics:
499
+ - type: cos_sim_pearson
500
+ value: 69.96711977441642
501
+ - type: cos_sim_spearman
502
+ value: 75.54747609685569
503
+ - type: euclidean_pearson
504
+ value: 74.62663478056035
505
+ - type: euclidean_spearman
506
+ value: 75.54761576699639
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+ - type: manhattan_pearson
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+ value: 74.60983904582241
509
+ - type: manhattan_spearman
510
+ value: 75.52758938061503
511
+ - task:
512
+ type: Reranking
513
+ dataset:
514
+ type: C-MTEB/Mmarco-reranking
515
+ name: MTEB MMarcoReranking
516
+ config: default
517
+ split: dev
518
+ revision: None
519
+ metrics:
520
+ - type: map
521
+ value: 28.076927649720986
522
+ - type: mrr
523
+ value: 26.98015873015873
524
+ - task:
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+ type: Retrieval
526
+ dataset:
527
+ type: C-MTEB/MMarcoRetrieval
528
+ name: MTEB MMarcoRetrieval
529
+ config: default
530
+ split: dev
531
+ revision: None
532
+ metrics:
533
+ - type: map_at_1
534
+ value: 65.58
535
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+ value: 80.262
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+ value: 75.138
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+ value: 77.094
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571
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573
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+ value: 1.019
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+ - type: precision_at_1000
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+ value: 0.105
577
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579
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+ value: 80.455
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+ - type: recall_at_5
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+ value: 85.063
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+ - task:
594
+ type: Classification
595
+ dataset:
596
+ type: mteb/amazon_massive_intent
597
+ name: MTEB MassiveIntentClassification (zh-CN)
598
+ config: zh-CN
599
+ split: test
600
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+ metrics:
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604
+ - type: f1
605
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+ - task:
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+ dataset:
609
+ type: mteb/amazon_massive_scenario
610
+ name: MTEB MassiveScenarioClassification (zh-CN)
611
+ config: zh-CN
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614
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615
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617
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619
+ - task:
620
+ type: Retrieval
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+ dataset:
622
+ type: C-MTEB/MedicalRetrieval
623
+ name: MTEB MedicalRetrieval
624
+ config: default
625
+ split: dev
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+ revision: None
627
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628
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662
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666
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+ value: 0.877
670
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672
+ - type: precision_at_3
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+ - type: precision_at_5
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+ value: 13.76
676
+ - type: recall_at_1
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+ value: 53.300000000000004
678
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+ value: 73.8
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+ value: 87.7
682
+ - type: recall_at_1000
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+ value: 97.0
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+ - type: recall_at_3
685
+ value: 65.0
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+ - type: recall_at_5
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+ value: 68.8
688
+ - task:
689
+ type: Classification
690
+ dataset:
691
+ type: C-MTEB/MultilingualSentiment-classification
692
+ name: MTEB MultilingualSentiment
693
+ config: default
694
+ split: validation
695
+ revision: None
696
+ metrics:
697
+ - type: accuracy
698
+ value: 76.27666666666667
699
+ - type: f1
700
+ value: 76.31280038435165
701
+ - task:
702
+ type: PairClassification
703
+ dataset:
704
+ type: C-MTEB/OCNLI
705
+ name: MTEB Ocnli
706
+ config: default
707
+ split: validation
708
+ revision: None
709
+ metrics:
710
+ - type: cos_sim_accuracy
711
+ value: 78.72225230102869
712
+ - type: cos_sim_ap
713
+ value: 80.63941899467723
714
+ - type: cos_sim_f1
715
+ value: 80.52190121155638
716
+ - type: cos_sim_precision
717
+ value: 72.06005004170142
718
+ - type: cos_sim_recall
719
+ value: 91.23548046462513
720
+ - type: dot_accuracy
721
+ value: 78.72225230102869
722
+ - type: dot_ap
723
+ value: 80.63913939812744
724
+ - type: dot_f1
725
+ value: 80.51948051948052
726
+ - type: dot_precision
727
+ value: 71.7948717948718
728
+ - type: dot_recall
729
+ value: 91.65786694825766
730
+ - type: euclidean_accuracy
731
+ value: 78.72225230102869
732
+ - type: euclidean_ap
733
+ value: 80.64403797436798
734
+ - type: euclidean_f1
735
+ value: 80.52190121155638
736
+ - type: euclidean_precision
737
+ value: 72.06005004170142
738
+ - type: euclidean_recall
739
+ value: 91.23548046462513
740
+ - type: manhattan_accuracy
741
+ value: 78.18083378451544
742
+ - type: manhattan_ap
743
+ value: 80.5241189302444
744
+ - type: manhattan_f1
745
+ value: 80.43478260869566
746
+ - type: manhattan_precision
747
+ value: 72.7972626176219
748
+ - type: manhattan_recall
749
+ value: 89.86272439281943
750
+ - type: max_accuracy
751
+ value: 78.72225230102869
752
+ - type: max_ap
753
+ value: 80.64403797436798
754
+ - type: max_f1
755
+ value: 80.52190121155638
756
+ - task:
757
+ type: Classification
758
+ dataset:
759
+ type: C-MTEB/OnlineShopping-classification
760
+ name: MTEB OnlineShopping
761
+ config: default
762
+ split: test
763
+ revision: None
764
+ metrics:
765
+ - type: accuracy
766
+ value: 92.49000000000001
767
+ - type: ap
768
+ value: 90.66330807324402
769
+ - type: f1
770
+ value: 92.48245049107115
771
+ - task:
772
+ type: STS
773
+ dataset:
774
+ type: C-MTEB/PAWSX
775
+ name: MTEB PAWSX
776
+ config: default
777
+ split: test
778
+ revision: None
779
+ metrics:
780
+ - type: cos_sim_pearson
781
+ value: 33.6275431596535
782
+ - type: cos_sim_spearman
783
+ value: 37.865700050451494
784
+ - type: euclidean_pearson
785
+ value: 38.1050665279388
786
+ - type: euclidean_spearman
787
+ value: 37.864125056066364
788
+ - type: manhattan_pearson
789
+ value: 38.11206873232881
790
+ - type: manhattan_spearman
791
+ value: 37.852977098473936
792
+ - task:
793
+ type: STS
794
+ dataset:
795
+ type: C-MTEB/QBQTC
796
+ name: MTEB QBQTC
797
+ config: default
798
+ split: test
799
+ revision: None
800
+ metrics:
801
+ - type: cos_sim_pearson
802
+ value: 32.137955501231104
803
+ - type: cos_sim_spearman
804
+ value: 33.68610910423116
805
+ - type: euclidean_pearson
806
+ value: 32.155444753547926
807
+ - type: euclidean_spearman
808
+ value: 33.685799252964124
809
+ - type: manhattan_pearson
810
+ value: 32.14490855334317
811
+ - type: manhattan_spearman
812
+ value: 33.656549820048554
813
+ - task:
814
+ type: STS
815
+ dataset:
816
+ type: mteb/sts22-crosslingual-sts
817
+ name: MTEB STS22 (zh)
818
+ config: zh
819
+ split: test
820
+ revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80
821
+ metrics:
822
+ - type: cos_sim_pearson
823
+ value: 63.63884916818661
824
+ - type: cos_sim_spearman
825
+ value: 64.3217581571435
826
+ - type: euclidean_pearson
827
+ value: 63.475760085926055
828
+ - type: euclidean_spearman
829
+ value: 64.31638169371887
830
+ - type: manhattan_pearson
831
+ value: 64.39677572604752
832
+ - type: manhattan_spearman
833
+ value: 64.85585019406021
834
+ - task:
835
+ type: STS
836
+ dataset:
837
+ type: C-MTEB/STSB
838
+ name: MTEB STSB
839
+ config: default
840
+ split: test
841
+ revision: None
842
+ metrics:
843
+ - type: cos_sim_pearson
844
+ value: 79.74698333415277
845
+ - type: cos_sim_spearman
846
+ value: 81.1850043859317
847
+ - type: euclidean_pearson
848
+ value: 80.94512578669881
849
+ - type: euclidean_spearman
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+ value: 81.18825478390181
851
+ - type: manhattan_pearson
852
+ value: 80.88114336824758
853
+ - type: manhattan_spearman
854
+ value: 81.12266715583868
855
+ - task:
856
+ type: Reranking
857
+ dataset:
858
+ type: C-MTEB/T2Reranking
859
+ name: MTEB T2Reranking
860
+ config: default
861
+ split: dev
862
+ revision: None
863
+ metrics:
864
+ - type: map
865
+ value: 66.59971552953814
866
+ - type: mrr
867
+ value: 76.42177408088038
868
+ - task:
869
+ type: Retrieval
870
+ dataset:
871
+ type: C-MTEB/T2Retrieval
872
+ name: MTEB T2Retrieval
873
+ config: default
874
+ split: dev
875
+ revision: None
876
+ metrics:
877
+ - type: map_at_1
878
+ value: 28.825
879
+ - type: map_at_10
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+ value: 77.48899999999999
881
+ - type: map_at_100
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+ value: 81.144
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+ value: 81.216
885
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+ value: 55.435
887
+ - type: map_at_5
888
+ value: 67.496
889
+ - type: mrr_at_1
890
+ value: 91.377
891
+ - type: mrr_at_10
892
+ value: 94.062
893
+ - type: mrr_at_100
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+ value: 94.122
895
+ - type: mrr_at_1000
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+ value: 94.123
897
+ - type: mrr_at_3
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+ value: 93.709
899
+ - type: mrr_at_5
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+ value: 93.932
901
+ - type: ndcg_at_1
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+ value: 91.377
903
+ - type: ndcg_at_10
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+ value: 85.44800000000001
905
+ - type: ndcg_at_100
906
+ value: 89.11099999999999
907
+ - type: ndcg_at_1000
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+ value: 89.752
909
+ - type: ndcg_at_3
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+ value: 87.262
911
+ - type: ndcg_at_5
912
+ value: 85.668
913
+ - type: precision_at_1
914
+ value: 91.377
915
+ - type: precision_at_10
916
+ value: 41.525
917
+ - type: precision_at_100
918
+ value: 4.989
919
+ - type: precision_at_1000
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+ value: 0.516
921
+ - type: precision_at_3
922
+ value: 75.452
923
+ - type: precision_at_5
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+ value: 62.785000000000004
925
+ - type: recall_at_1
926
+ value: 28.825
927
+ - type: recall_at_10
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+ value: 84.202
929
+ - type: recall_at_100
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+ value: 95.768
931
+ - type: recall_at_1000
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+ value: 98.791
933
+ - type: recall_at_3
934
+ value: 57.284
935
+ - type: recall_at_5
936
+ value: 71.071
937
+ - task:
938
+ type: Classification
939
+ dataset:
940
+ type: C-MTEB/TNews-classification
941
+ name: MTEB TNews
942
+ config: default
943
+ split: validation
944
+ revision: None
945
+ metrics:
946
+ - type: accuracy
947
+ value: 52.160000000000004
948
+ - type: f1
949
+ value: 50.49492950548829
950
+ - task:
951
+ type: Clustering
952
+ dataset:
953
+ type: C-MTEB/ThuNewsClusteringP2P
954
+ name: MTEB ThuNewsClusteringP2P
955
+ config: default
956
+ split: test
957
+ revision: None
958
+ metrics:
959
+ - type: v_measure
960
+ value: 70.06019845009966
961
+ - task:
962
+ type: Clustering
963
+ dataset:
964
+ type: C-MTEB/ThuNewsClusteringS2S
965
+ name: MTEB ThuNewsClusteringS2S
966
+ config: default
967
+ split: test
968
+ revision: None
969
+ metrics:
970
+ - type: v_measure
971
+ value: 63.9370959228245
972
+ - task:
973
+ type: Retrieval
974
+ dataset:
975
+ type: C-MTEB/VideoRetrieval
976
+ name: MTEB VideoRetrieval
977
+ config: default
978
+ split: dev
979
+ revision: None
980
+ metrics:
981
+ - type: map_at_1
982
+ value: 60.0
983
+ - type: map_at_10
984
+ value: 69.362
985
+ - type: map_at_100
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+ value: 69.819
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+ - type: map_at_1000
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+ value: 69.833
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+ - type: map_at_3
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+ value: 67.783
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+ - type: map_at_5
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+ value: 68.71300000000001
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+ - type: mrr_at_1
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+ value: 60.0
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+ - type: mrr_at_10
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+ value: 69.362
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+ - type: mrr_at_100
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+ value: 69.819
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+ - type: mrr_at_1000
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+ value: 69.833
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+ - type: mrr_at_3
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+ value: 67.783
1003
+ - type: mrr_at_5
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+ value: 68.71300000000001
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+ - type: ndcg_at_1
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+ value: 60.0
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+ - type: ndcg_at_10
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+ value: 73.59400000000001
1009
+ - type: ndcg_at_100
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+ value: 75.734
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+ - type: ndcg_at_1000
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+ value: 76.049
1013
+ - type: ndcg_at_3
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+ value: 70.33
1015
+ - type: ndcg_at_5
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+ value: 72.033
1017
+ - type: precision_at_1
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+ value: 60.0
1019
+ - type: precision_at_10
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+ value: 8.67
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+ - type: precision_at_100
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+ value: 0.9650000000000001
1023
+ - type: precision_at_1000
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+ value: 0.099
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+ - type: precision_at_3
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+ value: 25.900000000000002
1027
+ - type: precision_at_5
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+ value: 16.38
1029
+ - type: recall_at_1
1030
+ value: 60.0
1031
+ - type: recall_at_10
1032
+ value: 86.7
1033
+ - type: recall_at_100
1034
+ value: 96.5
1035
+ - type: recall_at_1000
1036
+ value: 98.9
1037
+ - type: recall_at_3
1038
+ value: 77.7
1039
+ - type: recall_at_5
1040
+ value: 81.89999999999999
1041
+ - task:
1042
+ type: Classification
1043
+ dataset:
1044
+ type: C-MTEB/waimai-classification
1045
+ name: MTEB Waimai
1046
+ config: default
1047
+ split: test
1048
+ revision: None
1049
+ metrics:
1050
+ - type: accuracy
1051
+ value: 88.36
1052
+ - type: ap
1053
+ value: 73.25144216855439
1054
+ - type: f1
1055
+ value: 86.75076261442027
1056
  ---
1057
+ # xiaobu-embedding
1058
+
1059
+ 模型:基于GTE模型[1]多任务微调。
1060
+ 数据:闲聊类Query-Query、知识类Query-Doc、BGE开源Query-Doc[2];清洗正例,挖掘中等难度负例;累计6M(质量更重要)。
1061
+
1062
+ ## Usage (Sentence-Transformers)
1063
+
1064
+ ```
1065
+ pip install -U sentence-transformers
1066
+ ```
1067
+ 相似度计算:
1068
+ ```python
1069
+ from sentence_transformers import SentenceTransformer
1070
+ sentences_1 = ["样例数据-1", "样例数据-2"]
1071
+ sentences_2 = ["样例数据-3", "样例数据-4"]
1072
+ model = SentenceTransformer('lier007/xiaobu-embedding')
1073
+ embeddings_1 = model.encode(sentences_1, normalize_embeddings=True)
1074
+ embeddings_2 = model.encode(sentences_2, normalize_embeddings=True)
1075
+ similarity = embeddings_1 @ embeddings_2.T
1076
+ print(similarity)
1077
+ ```
1078
+
1079
+ ## Evaluation
1080
+ 参考BGE中文CMTEB评估[2]
1081
+
1082
+ ## Finetune
1083
+ 参考BGE微调模块[2]
1084
+
1085
+ ## Reference
1086
+ 1. https://huggingface.co/thenlper/gte-large-zh
1087
+ 2. https://github.com/FlagOpen/FlagEmbedding
added_tokens.json ADDED
@@ -0,0 +1,7 @@
 
 
 
 
 
 
 
 
1
+ {
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+ "[CLS]": 101,
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+ "[MASK]": 103,
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+ "[PAD]": 0,
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+ "[SEP]": 102,
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+ "[UNK]": 100
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+ }
config.json ADDED
@@ -0,0 +1,31 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "architectures": [
3
+ "BertModel"
4
+ ],
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+ "attention_probs_dropout_prob": 0.1,
6
+ "classifier_dropout": null,
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+ "directionality": "bidi",
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+ "gradient_checkpointing": false,
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+ "hidden_act": "gelu",
10
+ "hidden_dropout_prob": 0.1,
11
+ "hidden_size": 1024,
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+ "initializer_range": 0.02,
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+ "intermediate_size": 4096,
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+ "layer_norm_eps": 1e-12,
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+ "max_position_embeddings": 512,
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+ "model_type": "bert",
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+ "num_attention_heads": 16,
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+ "num_hidden_layers": 24,
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+ "pad_token_id": 0,
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+ "pooler_fc_size": 768,
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+ "pooler_num_attention_heads": 12,
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+ "pooler_num_fc_layers": 3,
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+ "pooler_size_per_head": 128,
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+ "pooler_type": "first_token_transform",
25
+ "position_embedding_type": "absolute",
26
+ "torch_dtype": "float32",
27
+ "transformers_version": "4.34.0",
28
+ "type_vocab_size": 2,
29
+ "use_cache": true,
30
+ "vocab_size": 21128
31
+ }
config_sentence_transformers.json ADDED
@@ -0,0 +1,7 @@
 
 
 
 
 
 
 
 
1
+ {
2
+ "__version__": {
3
+ "sentence_transformers": "2.2.2",
4
+ "transformers": "4.34.0",
5
+ "pytorch": "2.0.1+cu118"
6
+ }
7
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