Update README.md
Browse files
README.md
CHANGED
@@ -1,3 +1,2608 @@
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2 |
license: apache-2.0
|
3 |
---
|
|
|
|
|
|
|
|
|
|
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|
|
|
1 |
---
|
2 |
+
tags:
|
3 |
+
- mteb
|
4 |
+
model-index:
|
5 |
+
- name: gte-base
|
6 |
+
results:
|
7 |
+
- task:
|
8 |
+
type: Classification
|
9 |
+
dataset:
|
10 |
+
type: mteb/amazon_counterfactual
|
11 |
+
name: MTEB AmazonCounterfactualClassification (en)
|
12 |
+
config: en
|
13 |
+
split: test
|
14 |
+
revision: e8379541af4e31359cca9fbcf4b00f2671dba205
|
15 |
+
metrics:
|
16 |
+
- type: accuracy
|
17 |
+
value: 74.17910447761193
|
18 |
+
- type: ap
|
19 |
+
value: 36.827146398068926
|
20 |
+
- type: f1
|
21 |
+
value: 68.11292888046363
|
22 |
+
- task:
|
23 |
+
type: Classification
|
24 |
+
dataset:
|
25 |
+
type: mteb/amazon_polarity
|
26 |
+
name: MTEB AmazonPolarityClassification
|
27 |
+
config: default
|
28 |
+
split: test
|
29 |
+
revision: e2d317d38cd51312af73b3d32a06d1a08b442046
|
30 |
+
metrics:
|
31 |
+
- type: accuracy
|
32 |
+
value: 91.77345000000001
|
33 |
+
- type: ap
|
34 |
+
value: 88.33530426691347
|
35 |
+
- type: f1
|
36 |
+
value: 91.76549906404642
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37 |
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- task:
|
38 |
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type: Classification
|
39 |
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dataset:
|
40 |
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type: mteb/amazon_reviews_multi
|
41 |
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name: MTEB AmazonReviewsClassification (en)
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42 |
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config: en
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43 |
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split: test
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44 |
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revision: 1399c76144fd37290681b995c656ef9b2e06e26d
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metrics:
|
46 |
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- type: accuracy
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47 |
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value: 48.964
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48 |
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- type: f1
|
49 |
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value: 48.22995586184998
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50 |
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- task:
|
51 |
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type: Retrieval
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52 |
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dataset:
|
53 |
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type: arguana
|
54 |
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name: MTEB ArguAna
|
55 |
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config: default
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56 |
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split: test
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57 |
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revision: None
|
58 |
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metrics:
|
59 |
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|
60 |
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value: 32.147999999999996
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61 |
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|
62 |
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63 |
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65 |
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77 |
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88 |
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94 |
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95 |
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98 |
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value: 8.542
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99 |
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value: 0.9900000000000001
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value: 0.1
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value: 19.346
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value: 14.026
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value: 32.147999999999996
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109 |
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value: 85.42
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111 |
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value: 99.004
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113 |
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value: 99.644
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|
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value: 58.037000000000006
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- type: recall_at_5
|
118 |
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value: 70.128
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119 |
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- task:
|
120 |
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type: Clustering
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121 |
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dataset:
|
122 |
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type: mteb/arxiv-clustering-p2p
|
123 |
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name: MTEB ArxivClusteringP2P
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124 |
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config: default
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125 |
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split: test
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126 |
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revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
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127 |
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metrics:
|
128 |
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- type: v_measure
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129 |
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value: 48.59706013699614
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130 |
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- task:
|
131 |
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type: Clustering
|
132 |
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dataset:
|
133 |
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type: mteb/arxiv-clustering-s2s
|
134 |
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name: MTEB ArxivClusteringS2S
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config: default
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136 |
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split: test
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137 |
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revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
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138 |
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metrics:
|
139 |
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- type: v_measure
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140 |
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value: 43.01463593002057
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141 |
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- task:
|
142 |
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type: Reranking
|
143 |
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dataset:
|
144 |
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type: mteb/askubuntudupquestions-reranking
|
145 |
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name: MTEB AskUbuntuDupQuestions
|
146 |
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config: default
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147 |
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split: test
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148 |
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revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
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149 |
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metrics:
|
150 |
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- type: map
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151 |
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value: 61.80250355752458
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152 |
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- type: mrr
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153 |
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value: 74.79455216989844
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- task:
|
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type: STS
|
156 |
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dataset:
|
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type: mteb/biosses-sts
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name: MTEB BIOSSES
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config: default
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160 |
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split: test
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161 |
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revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
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162 |
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|
163 |
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164 |
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value: 89.87448576082345
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165 |
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- type: cos_sim_spearman
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value: 87.64235843637468
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- type: euclidean_pearson
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value: 88.4901825511062
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- type: euclidean_spearman
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value: 87.74537283182033
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- type: manhattan_pearson
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value: 88.39040638362911
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- type: manhattan_spearman
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value: 87.62669542888003
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175 |
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- task:
|
176 |
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type: Classification
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177 |
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dataset:
|
178 |
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type: mteb/banking77
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name: MTEB Banking77Classification
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180 |
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config: default
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181 |
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split: test
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182 |
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revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
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metrics:
|
184 |
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- type: accuracy
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185 |
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value: 85.06818181818183
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186 |
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- type: f1
|
187 |
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value: 85.02524460098233
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188 |
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- task:
|
189 |
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type: Clustering
|
190 |
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dataset:
|
191 |
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type: mteb/biorxiv-clustering-p2p
|
192 |
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name: MTEB BiorxivClusteringP2P
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193 |
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config: default
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194 |
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split: test
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195 |
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revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
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metrics:
|
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- type: v_measure
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198 |
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value: 38.20471092679967
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199 |
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- task:
|
200 |
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type: Clustering
|
201 |
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dataset:
|
202 |
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type: mteb/biorxiv-clustering-s2s
|
203 |
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name: MTEB BiorxivClusteringS2S
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204 |
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config: default
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205 |
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split: test
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206 |
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revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
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metrics:
|
208 |
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209 |
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value: 36.58967592147641
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210 |
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- task:
|
211 |
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type: Retrieval
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212 |
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dataset:
|
213 |
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type: BeIR/cqadupstack
|
214 |
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name: MTEB CQADupstackAndroidRetrieval
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215 |
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config: default
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216 |
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split: test
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217 |
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revision: None
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218 |
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metrics:
|
219 |
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- type: map_at_1
|
220 |
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value: 32.411
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221 |
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- type: map_at_10
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222 |
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value: 45.162
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223 |
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value: 46.836
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value: 41.428
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value: 43.54
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value: 39.914
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value: 51.534
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value: 52.185
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238 |
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value: 52.22
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value: 49.046
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value: 50.548
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value: 39.914
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246 |
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value: 52.235
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248 |
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value: 57.4
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249 |
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value: 58.982
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value: 47.332
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254 |
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value: 49.62
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255 |
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256 |
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value: 39.914
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257 |
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258 |
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value: 10.258000000000001
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259 |
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260 |
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value: 1.6219999999999999
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262 |
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value: 0.20500000000000002
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264 |
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value: 23.462
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265 |
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266 |
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value: 16.71
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267 |
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value: 32.411
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value: 65.408
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value: 87.248
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273 |
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value: 96.951
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275 |
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276 |
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value: 50.349999999999994
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277 |
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- type: recall_at_5
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278 |
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value: 57.431
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279 |
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- task:
|
280 |
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type: Retrieval
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281 |
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dataset:
|
282 |
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type: BeIR/cqadupstack
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283 |
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name: MTEB CQADupstackEnglishRetrieval
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284 |
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config: default
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285 |
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split: test
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286 |
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revision: None
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287 |
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metrics:
|
288 |
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289 |
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value: 31.911
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290 |
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291 |
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value: 42.608000000000004
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292 |
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value: 44.089
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296 |
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value: 39.652
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298 |
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value: 41.236
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301 |
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value: 40.064
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302 |
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303 |
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304 |
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305 |
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306 |
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307 |
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308 |
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309 |
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310 |
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311 |
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313 |
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314 |
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315 |
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value: 48.442
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316 |
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317 |
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value: 52.798
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318 |
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319 |
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value: 54.871
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320 |
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value: 44.528
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322 |
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323 |
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value: 46.211
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324 |
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325 |
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value: 40.064
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326 |
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327 |
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value: 9.178
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328 |
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329 |
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value: 1.452
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330 |
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value: 0.193
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333 |
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value: 21.614
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334 |
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335 |
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value: 15.185
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336 |
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value: 31.911
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338 |
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339 |
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value: 58.155
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340 |
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value: 76.46300000000001
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342 |
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343 |
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value: 89.622
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344 |
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345 |
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value: 46.195
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346 |
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- type: recall_at_5
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347 |
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value: 51.288999999999994
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348 |
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- task:
|
349 |
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type: Retrieval
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350 |
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dataset:
|
351 |
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type: BeIR/cqadupstack
|
352 |
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name: MTEB CQADupstackGamingRetrieval
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353 |
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config: default
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354 |
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split: test
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355 |
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revision: None
|
356 |
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metrics:
|
357 |
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- type: map_at_1
|
358 |
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value: 40.597
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359 |
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360 |
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379 |
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402 |
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403 |
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404 |
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405 |
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415 |
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value: 66.956
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417 |
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- task:
|
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dataset:
|
420 |
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type: BeIR/cqadupstack
|
421 |
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name: MTEB CQADupstackGisRetrieval
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422 |
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config: default
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revision: None
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metrics:
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427 |
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value: 27.122
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428 |
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|
465 |
+
value: 6.4750000000000005
|
466 |
+
- type: precision_at_100
|
467 |
+
value: 0.951
|
468 |
+
- type: precision_at_1000
|
469 |
+
value: 0.11299999999999999
|
470 |
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- type: precision_at_3
|
471 |
+
value: 15.479999999999999
|
472 |
+
- type: precision_at_5
|
473 |
+
value: 11.028
|
474 |
+
- type: recall_at_1
|
475 |
+
value: 27.122
|
476 |
+
- type: recall_at_10
|
477 |
+
value: 56.279999999999994
|
478 |
+
- type: recall_at_100
|
479 |
+
value: 79.597
|
480 |
+
- type: recall_at_1000
|
481 |
+
value: 92.804
|
482 |
+
- type: recall_at_3
|
483 |
+
value: 41.437000000000005
|
484 |
+
- type: recall_at_5
|
485 |
+
value: 49.019
|
486 |
+
- task:
|
487 |
+
type: Retrieval
|
488 |
+
dataset:
|
489 |
+
type: BeIR/cqadupstack
|
490 |
+
name: MTEB CQADupstackMathematicaRetrieval
|
491 |
+
config: default
|
492 |
+
split: test
|
493 |
+
revision: None
|
494 |
+
metrics:
|
495 |
+
- type: map_at_1
|
496 |
+
value: 17.757
|
497 |
+
- type: map_at_10
|
498 |
+
value: 26.739
|
499 |
+
- type: map_at_100
|
500 |
+
value: 28.015
|
501 |
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- type: map_at_1000
|
502 |
+
value: 28.127999999999997
|
503 |
+
- type: map_at_3
|
504 |
+
value: 23.986
|
505 |
+
- type: map_at_5
|
506 |
+
value: 25.514
|
507 |
+
- type: mrr_at_1
|
508 |
+
value: 22.015
|
509 |
+
- type: mrr_at_10
|
510 |
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value: 31.325999999999997
|
511 |
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- type: mrr_at_100
|
512 |
+
value: 32.368
|
513 |
+
- type: mrr_at_1000
|
514 |
+
value: 32.426
|
515 |
+
- type: mrr_at_3
|
516 |
+
value: 28.897000000000002
|
517 |
+
- type: mrr_at_5
|
518 |
+
value: 30.147000000000002
|
519 |
+
- type: ndcg_at_1
|
520 |
+
value: 22.015
|
521 |
+
- type: ndcg_at_10
|
522 |
+
value: 32.225
|
523 |
+
- type: ndcg_at_100
|
524 |
+
value: 38.405
|
525 |
+
- type: ndcg_at_1000
|
526 |
+
value: 40.932
|
527 |
+
- type: ndcg_at_3
|
528 |
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value: 27.403
|
529 |
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- type: ndcg_at_5
|
530 |
+
value: 29.587000000000003
|
531 |
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- type: precision_at_1
|
532 |
+
value: 22.015
|
533 |
+
- type: precision_at_10
|
534 |
+
value: 5.9830000000000005
|
535 |
+
- type: precision_at_100
|
536 |
+
value: 1.051
|
537 |
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- type: precision_at_1000
|
538 |
+
value: 0.13899999999999998
|
539 |
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- type: precision_at_3
|
540 |
+
value: 13.391
|
541 |
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- type: precision_at_5
|
542 |
+
value: 9.602
|
543 |
+
- type: recall_at_1
|
544 |
+
value: 17.757
|
545 |
+
- type: recall_at_10
|
546 |
+
value: 44.467
|
547 |
+
- type: recall_at_100
|
548 |
+
value: 71.53699999999999
|
549 |
+
- type: recall_at_1000
|
550 |
+
value: 89.281
|
551 |
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- type: recall_at_3
|
552 |
+
value: 31.095
|
553 |
+
- type: recall_at_5
|
554 |
+
value: 36.818
|
555 |
+
- task:
|
556 |
+
type: Retrieval
|
557 |
+
dataset:
|
558 |
+
type: BeIR/cqadupstack
|
559 |
+
name: MTEB CQADupstackPhysicsRetrieval
|
560 |
+
config: default
|
561 |
+
split: test
|
562 |
+
revision: None
|
563 |
+
metrics:
|
564 |
+
- type: map_at_1
|
565 |
+
value: 30.354
|
566 |
+
- type: map_at_10
|
567 |
+
value: 42.134
|
568 |
+
- type: map_at_100
|
569 |
+
value: 43.429
|
570 |
+
- type: map_at_1000
|
571 |
+
value: 43.532
|
572 |
+
- type: map_at_3
|
573 |
+
value: 38.491
|
574 |
+
- type: map_at_5
|
575 |
+
value: 40.736
|
576 |
+
- type: mrr_at_1
|
577 |
+
value: 37.247
|
578 |
+
- type: mrr_at_10
|
579 |
+
value: 47.775
|
580 |
+
- type: mrr_at_100
|
581 |
+
value: 48.522999999999996
|
582 |
+
- type: mrr_at_1000
|
583 |
+
value: 48.567
|
584 |
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- type: mrr_at_3
|
585 |
+
value: 45.059
|
586 |
+
- type: mrr_at_5
|
587 |
+
value: 46.811
|
588 |
+
- type: ndcg_at_1
|
589 |
+
value: 37.247
|
590 |
+
- type: ndcg_at_10
|
591 |
+
value: 48.609
|
592 |
+
- type: ndcg_at_100
|
593 |
+
value: 53.782
|
594 |
+
- type: ndcg_at_1000
|
595 |
+
value: 55.666000000000004
|
596 |
+
- type: ndcg_at_3
|
597 |
+
value: 42.866
|
598 |
+
- type: ndcg_at_5
|
599 |
+
value: 46.001
|
600 |
+
- type: precision_at_1
|
601 |
+
value: 37.247
|
602 |
+
- type: precision_at_10
|
603 |
+
value: 8.892999999999999
|
604 |
+
- type: precision_at_100
|
605 |
+
value: 1.341
|
606 |
+
- type: precision_at_1000
|
607 |
+
value: 0.168
|
608 |
+
- type: precision_at_3
|
609 |
+
value: 20.5
|
610 |
+
- type: precision_at_5
|
611 |
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value: 14.976
|
612 |
+
- type: recall_at_1
|
613 |
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value: 30.354
|
614 |
+
- type: recall_at_10
|
615 |
+
value: 62.273
|
616 |
+
- type: recall_at_100
|
617 |
+
value: 83.65599999999999
|
618 |
+
- type: recall_at_1000
|
619 |
+
value: 95.82000000000001
|
620 |
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- type: recall_at_3
|
621 |
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value: 46.464
|
622 |
+
- type: recall_at_5
|
623 |
+
value: 54.225
|
624 |
+
- task:
|
625 |
+
type: Retrieval
|
626 |
+
dataset:
|
627 |
+
type: BeIR/cqadupstack
|
628 |
+
name: MTEB CQADupstackProgrammersRetrieval
|
629 |
+
config: default
|
630 |
+
split: test
|
631 |
+
revision: None
|
632 |
+
metrics:
|
633 |
+
- type: map_at_1
|
634 |
+
value: 26.949
|
635 |
+
- type: map_at_10
|
636 |
+
value: 37.230000000000004
|
637 |
+
- type: map_at_100
|
638 |
+
value: 38.644
|
639 |
+
- type: map_at_1000
|
640 |
+
value: 38.751999999999995
|
641 |
+
- type: map_at_3
|
642 |
+
value: 33.816
|
643 |
+
- type: map_at_5
|
644 |
+
value: 35.817
|
645 |
+
- type: mrr_at_1
|
646 |
+
value: 33.446999999999996
|
647 |
+
- type: mrr_at_10
|
648 |
+
value: 42.970000000000006
|
649 |
+
- type: mrr_at_100
|
650 |
+
value: 43.873
|
651 |
+
- type: mrr_at_1000
|
652 |
+
value: 43.922
|
653 |
+
- type: mrr_at_3
|
654 |
+
value: 40.467999999999996
|
655 |
+
- type: mrr_at_5
|
656 |
+
value: 41.861
|
657 |
+
- type: ndcg_at_1
|
658 |
+
value: 33.446999999999996
|
659 |
+
- type: ndcg_at_10
|
660 |
+
value: 43.403000000000006
|
661 |
+
- type: ndcg_at_100
|
662 |
+
value: 49.247
|
663 |
+
- type: ndcg_at_1000
|
664 |
+
value: 51.361999999999995
|
665 |
+
- type: ndcg_at_3
|
666 |
+
value: 38.155
|
667 |
+
- type: ndcg_at_5
|
668 |
+
value: 40.643
|
669 |
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- type: precision_at_1
|
670 |
+
value: 33.446999999999996
|
671 |
+
- type: precision_at_10
|
672 |
+
value: 8.128
|
673 |
+
- type: precision_at_100
|
674 |
+
value: 1.274
|
675 |
+
- type: precision_at_1000
|
676 |
+
value: 0.163
|
677 |
+
- type: precision_at_3
|
678 |
+
value: 18.493000000000002
|
679 |
+
- type: precision_at_5
|
680 |
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value: 13.333
|
681 |
+
- type: recall_at_1
|
682 |
+
value: 26.949
|
683 |
+
- type: recall_at_10
|
684 |
+
value: 56.006
|
685 |
+
- type: recall_at_100
|
686 |
+
value: 80.99199999999999
|
687 |
+
- type: recall_at_1000
|
688 |
+
value: 95.074
|
689 |
+
- type: recall_at_3
|
690 |
+
value: 40.809
|
691 |
+
- type: recall_at_5
|
692 |
+
value: 47.57
|
693 |
+
- task:
|
694 |
+
type: Retrieval
|
695 |
+
dataset:
|
696 |
+
type: BeIR/cqadupstack
|
697 |
+
name: MTEB CQADupstackRetrieval
|
698 |
+
config: default
|
699 |
+
split: test
|
700 |
+
revision: None
|
701 |
+
metrics:
|
702 |
+
- type: map_at_1
|
703 |
+
value: 27.243583333333333
|
704 |
+
- type: map_at_10
|
705 |
+
value: 37.193250000000006
|
706 |
+
- type: map_at_100
|
707 |
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value: 38.44833333333334
|
708 |
+
- type: map_at_1000
|
709 |
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value: 38.56083333333333
|
710 |
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- type: map_at_3
|
711 |
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value: 34.06633333333333
|
712 |
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|
713 |
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value: 35.87858333333334
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714 |
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|
715 |
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value: 32.291583333333335
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716 |
+
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|
717 |
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value: 41.482749999999996
|
718 |
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- type: mrr_at_100
|
719 |
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value: 42.33583333333333
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720 |
+
- type: mrr_at_1000
|
721 |
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value: 42.38683333333333
|
722 |
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- type: mrr_at_3
|
723 |
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value: 38.952999999999996
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724 |
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|
725 |
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value: 40.45333333333333
|
726 |
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|
727 |
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value: 32.291583333333335
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728 |
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|
729 |
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value: 42.90533333333334
|
730 |
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|
731 |
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value: 48.138666666666666
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732 |
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- type: ndcg_at_1000
|
733 |
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value: 50.229083333333335
|
734 |
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- type: ndcg_at_3
|
735 |
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value: 37.76133333333334
|
736 |
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|
737 |
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value: 40.31033333333334
|
738 |
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- type: precision_at_1
|
739 |
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value: 32.291583333333335
|
740 |
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- type: precision_at_10
|
741 |
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value: 7.585583333333333
|
742 |
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- type: precision_at_100
|
743 |
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value: 1.2045000000000001
|
744 |
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- type: precision_at_1000
|
745 |
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value: 0.15733333333333335
|
746 |
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- type: precision_at_3
|
747 |
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value: 17.485416666666666
|
748 |
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- type: precision_at_5
|
749 |
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value: 12.5145
|
750 |
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- type: recall_at_1
|
751 |
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value: 27.243583333333333
|
752 |
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- type: recall_at_10
|
753 |
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value: 55.45108333333334
|
754 |
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- type: recall_at_100
|
755 |
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value: 78.25858333333335
|
756 |
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- type: recall_at_1000
|
757 |
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value: 92.61716666666665
|
758 |
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- type: recall_at_3
|
759 |
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value: 41.130583333333334
|
760 |
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- type: recall_at_5
|
761 |
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value: 47.73133333333334
|
762 |
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- task:
|
763 |
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type: Retrieval
|
764 |
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dataset:
|
765 |
+
type: BeIR/cqadupstack
|
766 |
+
name: MTEB CQADupstackStatsRetrieval
|
767 |
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config: default
|
768 |
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split: test
|
769 |
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revision: None
|
770 |
+
metrics:
|
771 |
+
- type: map_at_1
|
772 |
+
value: 26.325
|
773 |
+
- type: map_at_10
|
774 |
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value: 32.795
|
775 |
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- type: map_at_100
|
776 |
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value: 33.96
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777 |
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- type: map_at_1000
|
778 |
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value: 34.054
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779 |
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- type: map_at_3
|
780 |
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value: 30.64
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781 |
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- type: map_at_5
|
782 |
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value: 31.771
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783 |
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|
784 |
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value: 29.908
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785 |
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|
786 |
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value: 35.83
|
787 |
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|
788 |
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value: 36.868
|
789 |
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|
790 |
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value: 36.928
|
791 |
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|
792 |
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value: 33.896
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793 |
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|
794 |
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value: 34.893
|
795 |
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|
796 |
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value: 29.908
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797 |
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|
798 |
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value: 36.746
|
799 |
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|
800 |
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value: 42.225
|
801 |
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|
802 |
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value: 44.523
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803 |
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|
804 |
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value: 32.82
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805 |
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|
806 |
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value: 34.583000000000006
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807 |
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|
808 |
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value: 29.908
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809 |
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|
810 |
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value: 5.6129999999999995
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811 |
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|
812 |
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value: 0.9079999999999999
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813 |
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|
814 |
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value: 0.11800000000000001
|
815 |
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|
816 |
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value: 13.753000000000002
|
817 |
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|
818 |
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value: 9.417
|
819 |
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- type: recall_at_1
|
820 |
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value: 26.325
|
821 |
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- type: recall_at_10
|
822 |
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value: 45.975
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823 |
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|
824 |
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value: 70.393
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825 |
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- type: recall_at_1000
|
826 |
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value: 87.217
|
827 |
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- type: recall_at_3
|
828 |
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value: 35.195
|
829 |
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- type: recall_at_5
|
830 |
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value: 39.69
|
831 |
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- task:
|
832 |
+
type: Retrieval
|
833 |
+
dataset:
|
834 |
+
type: BeIR/cqadupstack
|
835 |
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name: MTEB CQADupstackTexRetrieval
|
836 |
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config: default
|
837 |
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split: test
|
838 |
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revision: None
|
839 |
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metrics:
|
840 |
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|
841 |
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value: 17.828
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842 |
+
- type: map_at_10
|
843 |
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value: 25.759
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844 |
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|
845 |
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value: 26.961000000000002
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846 |
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|
847 |
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value: 27.094
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848 |
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|
849 |
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value: 23.166999999999998
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850 |
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|
851 |
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852 |
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|
853 |
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value: 21.61
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854 |
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855 |
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value: 29.605999999999998
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856 |
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857 |
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value: 30.586000000000002
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858 |
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|
859 |
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value: 30.664
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860 |
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861 |
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value: 27.214
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862 |
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|
863 |
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value: 28.571
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864 |
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|
865 |
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value: 21.61
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866 |
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867 |
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value: 30.740000000000002
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868 |
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|
869 |
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value: 36.332
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870 |
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871 |
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value: 39.296
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872 |
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|
873 |
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value: 26.11
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874 |
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|
875 |
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value: 28.297
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876 |
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|
877 |
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value: 21.61
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878 |
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|
879 |
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value: 5.643
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880 |
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- type: precision_at_100
|
881 |
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value: 1.0
|
882 |
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|
883 |
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value: 0.14400000000000002
|
884 |
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- type: precision_at_3
|
885 |
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value: 12.4
|
886 |
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- type: precision_at_5
|
887 |
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value: 9.119
|
888 |
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- type: recall_at_1
|
889 |
+
value: 17.828
|
890 |
+
- type: recall_at_10
|
891 |
+
value: 41.876000000000005
|
892 |
+
- type: recall_at_100
|
893 |
+
value: 66.648
|
894 |
+
- type: recall_at_1000
|
895 |
+
value: 87.763
|
896 |
+
- type: recall_at_3
|
897 |
+
value: 28.957
|
898 |
+
- type: recall_at_5
|
899 |
+
value: 34.494
|
900 |
+
- task:
|
901 |
+
type: Retrieval
|
902 |
+
dataset:
|
903 |
+
type: BeIR/cqadupstack
|
904 |
+
name: MTEB CQADupstackUnixRetrieval
|
905 |
+
config: default
|
906 |
+
split: test
|
907 |
+
revision: None
|
908 |
+
metrics:
|
909 |
+
- type: map_at_1
|
910 |
+
value: 27.921000000000003
|
911 |
+
- type: map_at_10
|
912 |
+
value: 37.156
|
913 |
+
- type: map_at_100
|
914 |
+
value: 38.399
|
915 |
+
- type: map_at_1000
|
916 |
+
value: 38.498
|
917 |
+
- type: map_at_3
|
918 |
+
value: 34.134
|
919 |
+
- type: map_at_5
|
920 |
+
value: 35.936
|
921 |
+
- type: mrr_at_1
|
922 |
+
value: 32.649
|
923 |
+
- type: mrr_at_10
|
924 |
+
value: 41.19
|
925 |
+
- type: mrr_at_100
|
926 |
+
value: 42.102000000000004
|
927 |
+
- type: mrr_at_1000
|
928 |
+
value: 42.157
|
929 |
+
- type: mrr_at_3
|
930 |
+
value: 38.464
|
931 |
+
- type: mrr_at_5
|
932 |
+
value: 40.148
|
933 |
+
- type: ndcg_at_1
|
934 |
+
value: 32.649
|
935 |
+
- type: ndcg_at_10
|
936 |
+
value: 42.679
|
937 |
+
- type: ndcg_at_100
|
938 |
+
value: 48.27
|
939 |
+
- type: ndcg_at_1000
|
940 |
+
value: 50.312
|
941 |
+
- type: ndcg_at_3
|
942 |
+
value: 37.269000000000005
|
943 |
+
- type: ndcg_at_5
|
944 |
+
value: 40.055
|
945 |
+
- type: precision_at_1
|
946 |
+
value: 32.649
|
947 |
+
- type: precision_at_10
|
948 |
+
value: 7.155
|
949 |
+
- type: precision_at_100
|
950 |
+
value: 1.124
|
951 |
+
- type: precision_at_1000
|
952 |
+
value: 0.14100000000000001
|
953 |
+
- type: precision_at_3
|
954 |
+
value: 16.791
|
955 |
+
- type: precision_at_5
|
956 |
+
value: 12.015
|
957 |
+
- type: recall_at_1
|
958 |
+
value: 27.921000000000003
|
959 |
+
- type: recall_at_10
|
960 |
+
value: 55.357
|
961 |
+
- type: recall_at_100
|
962 |
+
value: 79.476
|
963 |
+
- type: recall_at_1000
|
964 |
+
value: 93.314
|
965 |
+
- type: recall_at_3
|
966 |
+
value: 40.891
|
967 |
+
- type: recall_at_5
|
968 |
+
value: 47.851
|
969 |
+
- task:
|
970 |
+
type: Retrieval
|
971 |
+
dataset:
|
972 |
+
type: BeIR/cqadupstack
|
973 |
+
name: MTEB CQADupstackWebmastersRetrieval
|
974 |
+
config: default
|
975 |
+
split: test
|
976 |
+
revision: None
|
977 |
+
metrics:
|
978 |
+
- type: map_at_1
|
979 |
+
value: 25.524
|
980 |
+
- type: map_at_10
|
981 |
+
value: 35.135
|
982 |
+
- type: map_at_100
|
983 |
+
value: 36.665
|
984 |
+
- type: map_at_1000
|
985 |
+
value: 36.886
|
986 |
+
- type: map_at_3
|
987 |
+
value: 31.367
|
988 |
+
- type: map_at_5
|
989 |
+
value: 33.724
|
990 |
+
- type: mrr_at_1
|
991 |
+
value: 30.631999999999998
|
992 |
+
- type: mrr_at_10
|
993 |
+
value: 39.616
|
994 |
+
- type: mrr_at_100
|
995 |
+
value: 40.54
|
996 |
+
- type: mrr_at_1000
|
997 |
+
value: 40.585
|
998 |
+
- type: mrr_at_3
|
999 |
+
value: 36.462
|
1000 |
+
- type: mrr_at_5
|
1001 |
+
value: 38.507999999999996
|
1002 |
+
- type: ndcg_at_1
|
1003 |
+
value: 30.631999999999998
|
1004 |
+
- type: ndcg_at_10
|
1005 |
+
value: 41.61
|
1006 |
+
- type: ndcg_at_100
|
1007 |
+
value: 47.249
|
1008 |
+
- type: ndcg_at_1000
|
1009 |
+
value: 49.662
|
1010 |
+
- type: ndcg_at_3
|
1011 |
+
value: 35.421
|
1012 |
+
- type: ndcg_at_5
|
1013 |
+
value: 38.811
|
1014 |
+
- type: precision_at_1
|
1015 |
+
value: 30.631999999999998
|
1016 |
+
- type: precision_at_10
|
1017 |
+
value: 8.123
|
1018 |
+
- type: precision_at_100
|
1019 |
+
value: 1.5810000000000002
|
1020 |
+
- type: precision_at_1000
|
1021 |
+
value: 0.245
|
1022 |
+
- type: precision_at_3
|
1023 |
+
value: 16.337
|
1024 |
+
- type: precision_at_5
|
1025 |
+
value: 12.568999999999999
|
1026 |
+
- type: recall_at_1
|
1027 |
+
value: 25.524
|
1028 |
+
- type: recall_at_10
|
1029 |
+
value: 54.994
|
1030 |
+
- type: recall_at_100
|
1031 |
+
value: 80.03099999999999
|
1032 |
+
- type: recall_at_1000
|
1033 |
+
value: 95.25099999999999
|
1034 |
+
- type: recall_at_3
|
1035 |
+
value: 37.563
|
1036 |
+
- type: recall_at_5
|
1037 |
+
value: 46.428999999999995
|
1038 |
+
- task:
|
1039 |
+
type: Retrieval
|
1040 |
+
dataset:
|
1041 |
+
type: BeIR/cqadupstack
|
1042 |
+
name: MTEB CQADupstackWordpressRetrieval
|
1043 |
+
config: default
|
1044 |
+
split: test
|
1045 |
+
revision: None
|
1046 |
+
metrics:
|
1047 |
+
- type: map_at_1
|
1048 |
+
value: 22.224
|
1049 |
+
- type: map_at_10
|
1050 |
+
value: 30.599999999999998
|
1051 |
+
- type: map_at_100
|
1052 |
+
value: 31.526
|
1053 |
+
- type: map_at_1000
|
1054 |
+
value: 31.629
|
1055 |
+
- type: map_at_3
|
1056 |
+
value: 27.491
|
1057 |
+
- type: map_at_5
|
1058 |
+
value: 29.212
|
1059 |
+
- type: mrr_at_1
|
1060 |
+
value: 24.214
|
1061 |
+
- type: mrr_at_10
|
1062 |
+
value: 32.632
|
1063 |
+
- type: mrr_at_100
|
1064 |
+
value: 33.482
|
1065 |
+
- type: mrr_at_1000
|
1066 |
+
value: 33.550000000000004
|
1067 |
+
- type: mrr_at_3
|
1068 |
+
value: 29.852
|
1069 |
+
- type: mrr_at_5
|
1070 |
+
value: 31.451
|
1071 |
+
- type: ndcg_at_1
|
1072 |
+
value: 24.214
|
1073 |
+
- type: ndcg_at_10
|
1074 |
+
value: 35.802
|
1075 |
+
- type: ndcg_at_100
|
1076 |
+
value: 40.502
|
1077 |
+
- type: ndcg_at_1000
|
1078 |
+
value: 43.052
|
1079 |
+
- type: ndcg_at_3
|
1080 |
+
value: 29.847
|
1081 |
+
- type: ndcg_at_5
|
1082 |
+
value: 32.732
|
1083 |
+
- type: precision_at_1
|
1084 |
+
value: 24.214
|
1085 |
+
- type: precision_at_10
|
1086 |
+
value: 5.804
|
1087 |
+
- type: precision_at_100
|
1088 |
+
value: 0.885
|
1089 |
+
- type: precision_at_1000
|
1090 |
+
value: 0.121
|
1091 |
+
- type: precision_at_3
|
1092 |
+
value: 12.692999999999998
|
1093 |
+
- type: precision_at_5
|
1094 |
+
value: 9.242
|
1095 |
+
- type: recall_at_1
|
1096 |
+
value: 22.224
|
1097 |
+
- type: recall_at_10
|
1098 |
+
value: 49.849
|
1099 |
+
- type: recall_at_100
|
1100 |
+
value: 71.45
|
1101 |
+
- type: recall_at_1000
|
1102 |
+
value: 90.583
|
1103 |
+
- type: recall_at_3
|
1104 |
+
value: 34.153
|
1105 |
+
- type: recall_at_5
|
1106 |
+
value: 41.004000000000005
|
1107 |
+
- task:
|
1108 |
+
type: Retrieval
|
1109 |
+
dataset:
|
1110 |
+
type: climate-fever
|
1111 |
+
name: MTEB ClimateFEVER
|
1112 |
+
config: default
|
1113 |
+
split: test
|
1114 |
+
revision: None
|
1115 |
+
metrics:
|
1116 |
+
- type: map_at_1
|
1117 |
+
value: 12.386999999999999
|
1118 |
+
- type: map_at_10
|
1119 |
+
value: 20.182
|
1120 |
+
- type: map_at_100
|
1121 |
+
value: 21.86
|
1122 |
+
- type: map_at_1000
|
1123 |
+
value: 22.054000000000002
|
1124 |
+
- type: map_at_3
|
1125 |
+
value: 17.165
|
1126 |
+
- type: map_at_5
|
1127 |
+
value: 18.643
|
1128 |
+
- type: mrr_at_1
|
1129 |
+
value: 26.906000000000002
|
1130 |
+
- type: mrr_at_10
|
1131 |
+
value: 37.907999999999994
|
1132 |
+
- type: mrr_at_100
|
1133 |
+
value: 38.868
|
1134 |
+
- type: mrr_at_1000
|
1135 |
+
value: 38.913
|
1136 |
+
- type: mrr_at_3
|
1137 |
+
value: 34.853
|
1138 |
+
- type: mrr_at_5
|
1139 |
+
value: 36.567
|
1140 |
+
- type: ndcg_at_1
|
1141 |
+
value: 26.906000000000002
|
1142 |
+
- type: ndcg_at_10
|
1143 |
+
value: 28.103
|
1144 |
+
- type: ndcg_at_100
|
1145 |
+
value: 35.073
|
1146 |
+
- type: ndcg_at_1000
|
1147 |
+
value: 38.653
|
1148 |
+
- type: ndcg_at_3
|
1149 |
+
value: 23.345
|
1150 |
+
- type: ndcg_at_5
|
1151 |
+
value: 24.828
|
1152 |
+
- type: precision_at_1
|
1153 |
+
value: 26.906000000000002
|
1154 |
+
- type: precision_at_10
|
1155 |
+
value: 8.547
|
1156 |
+
- type: precision_at_100
|
1157 |
+
value: 1.617
|
1158 |
+
- type: precision_at_1000
|
1159 |
+
value: 0.22799999999999998
|
1160 |
+
- type: precision_at_3
|
1161 |
+
value: 17.025000000000002
|
1162 |
+
- type: precision_at_5
|
1163 |
+
value: 12.834000000000001
|
1164 |
+
- type: recall_at_1
|
1165 |
+
value: 12.386999999999999
|
1166 |
+
- type: recall_at_10
|
1167 |
+
value: 33.306999999999995
|
1168 |
+
- type: recall_at_100
|
1169 |
+
value: 57.516
|
1170 |
+
- type: recall_at_1000
|
1171 |
+
value: 77.74799999999999
|
1172 |
+
- type: recall_at_3
|
1173 |
+
value: 21.433
|
1174 |
+
- type: recall_at_5
|
1175 |
+
value: 25.915
|
1176 |
+
- task:
|
1177 |
+
type: Retrieval
|
1178 |
+
dataset:
|
1179 |
+
type: dbpedia-entity
|
1180 |
+
name: MTEB DBPedia
|
1181 |
+
config: default
|
1182 |
+
split: test
|
1183 |
+
revision: None
|
1184 |
+
metrics:
|
1185 |
+
- type: map_at_1
|
1186 |
+
value: 9.322
|
1187 |
+
- type: map_at_10
|
1188 |
+
value: 20.469
|
1189 |
+
- type: map_at_100
|
1190 |
+
value: 28.638
|
1191 |
+
- type: map_at_1000
|
1192 |
+
value: 30.433
|
1193 |
+
- type: map_at_3
|
1194 |
+
value: 14.802000000000001
|
1195 |
+
- type: map_at_5
|
1196 |
+
value: 17.297
|
1197 |
+
- type: mrr_at_1
|
1198 |
+
value: 68.75
|
1199 |
+
- type: mrr_at_10
|
1200 |
+
value: 76.29599999999999
|
1201 |
+
- type: mrr_at_100
|
1202 |
+
value: 76.62400000000001
|
1203 |
+
- type: mrr_at_1000
|
1204 |
+
value: 76.633
|
1205 |
+
- type: mrr_at_3
|
1206 |
+
value: 75.083
|
1207 |
+
- type: mrr_at_5
|
1208 |
+
value: 75.771
|
1209 |
+
- type: ndcg_at_1
|
1210 |
+
value: 54.87499999999999
|
1211 |
+
- type: ndcg_at_10
|
1212 |
+
value: 41.185
|
1213 |
+
- type: ndcg_at_100
|
1214 |
+
value: 46.400000000000006
|
1215 |
+
- type: ndcg_at_1000
|
1216 |
+
value: 54.223
|
1217 |
+
- type: ndcg_at_3
|
1218 |
+
value: 45.489000000000004
|
1219 |
+
- type: ndcg_at_5
|
1220 |
+
value: 43.161
|
1221 |
+
- type: precision_at_1
|
1222 |
+
value: 68.75
|
1223 |
+
- type: precision_at_10
|
1224 |
+
value: 32.300000000000004
|
1225 |
+
- type: precision_at_100
|
1226 |
+
value: 10.607999999999999
|
1227 |
+
- type: precision_at_1000
|
1228 |
+
value: 2.237
|
1229 |
+
- type: precision_at_3
|
1230 |
+
value: 49.083
|
1231 |
+
- type: precision_at_5
|
1232 |
+
value: 41.6
|
1233 |
+
- type: recall_at_1
|
1234 |
+
value: 9.322
|
1235 |
+
- type: recall_at_10
|
1236 |
+
value: 25.696
|
1237 |
+
- type: recall_at_100
|
1238 |
+
value: 52.898
|
1239 |
+
- type: recall_at_1000
|
1240 |
+
value: 77.281
|
1241 |
+
- type: recall_at_3
|
1242 |
+
value: 15.943
|
1243 |
+
- type: recall_at_5
|
1244 |
+
value: 19.836000000000002
|
1245 |
+
- task:
|
1246 |
+
type: Classification
|
1247 |
+
dataset:
|
1248 |
+
type: mteb/emotion
|
1249 |
+
name: MTEB EmotionClassification
|
1250 |
+
config: default
|
1251 |
+
split: test
|
1252 |
+
revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
|
1253 |
+
metrics:
|
1254 |
+
- type: accuracy
|
1255 |
+
value: 48.650000000000006
|
1256 |
+
- type: f1
|
1257 |
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value: 43.528467245539396
|
1258 |
+
- task:
|
1259 |
+
type: Retrieval
|
1260 |
+
dataset:
|
1261 |
+
type: fever
|
1262 |
+
name: MTEB FEVER
|
1263 |
+
config: default
|
1264 |
+
split: test
|
1265 |
+
revision: None
|
1266 |
+
metrics:
|
1267 |
+
- type: map_at_1
|
1268 |
+
value: 66.56
|
1269 |
+
- type: map_at_10
|
1270 |
+
value: 76.767
|
1271 |
+
- type: map_at_100
|
1272 |
+
value: 77.054
|
1273 |
+
- type: map_at_1000
|
1274 |
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value: 77.068
|
1275 |
+
- type: map_at_3
|
1276 |
+
value: 75.29299999999999
|
1277 |
+
- type: map_at_5
|
1278 |
+
value: 76.24
|
1279 |
+
- type: mrr_at_1
|
1280 |
+
value: 71.842
|
1281 |
+
- type: mrr_at_10
|
1282 |
+
value: 81.459
|
1283 |
+
- type: mrr_at_100
|
1284 |
+
value: 81.58800000000001
|
1285 |
+
- type: mrr_at_1000
|
1286 |
+
value: 81.59100000000001
|
1287 |
+
- type: mrr_at_3
|
1288 |
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value: 80.188
|
1289 |
+
- type: mrr_at_5
|
1290 |
+
value: 81.038
|
1291 |
+
- type: ndcg_at_1
|
1292 |
+
value: 71.842
|
1293 |
+
- type: ndcg_at_10
|
1294 |
+
value: 81.51899999999999
|
1295 |
+
- type: ndcg_at_100
|
1296 |
+
value: 82.544
|
1297 |
+
- type: ndcg_at_1000
|
1298 |
+
value: 82.829
|
1299 |
+
- type: ndcg_at_3
|
1300 |
+
value: 78.92
|
1301 |
+
- type: ndcg_at_5
|
1302 |
+
value: 80.406
|
1303 |
+
- type: precision_at_1
|
1304 |
+
value: 71.842
|
1305 |
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- type: precision_at_10
|
1306 |
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value: 10.066
|
1307 |
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- type: precision_at_100
|
1308 |
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value: 1.076
|
1309 |
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- type: precision_at_1000
|
1310 |
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value: 0.11199999999999999
|
1311 |
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|
1312 |
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value: 30.703000000000003
|
1313 |
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- type: precision_at_5
|
1314 |
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value: 19.301
|
1315 |
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- type: recall_at_1
|
1316 |
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value: 66.56
|
1317 |
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- type: recall_at_10
|
1318 |
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value: 91.55
|
1319 |
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- type: recall_at_100
|
1320 |
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value: 95.67099999999999
|
1321 |
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- type: recall_at_1000
|
1322 |
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value: 97.539
|
1323 |
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- type: recall_at_3
|
1324 |
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value: 84.46900000000001
|
1325 |
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- type: recall_at_5
|
1326 |
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value: 88.201
|
1327 |
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- task:
|
1328 |
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type: Retrieval
|
1329 |
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dataset:
|
1330 |
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type: fiqa
|
1331 |
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name: MTEB FiQA2018
|
1332 |
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config: default
|
1333 |
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split: test
|
1334 |
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revision: None
|
1335 |
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metrics:
|
1336 |
+
- type: map_at_1
|
1337 |
+
value: 20.087
|
1338 |
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- type: map_at_10
|
1339 |
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value: 32.830999999999996
|
1340 |
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|
1341 |
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value: 34.814
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1342 |
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1343 |
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value: 34.999
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1344 |
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|
1345 |
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value: 28.198
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1346 |
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|
1347 |
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value: 30.779
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1348 |
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|
1349 |
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value: 38.889
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1350 |
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|
1351 |
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value: 48.415
|
1352 |
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- type: mrr_at_100
|
1353 |
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value: 49.187
|
1354 |
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|
1355 |
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value: 49.226
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1356 |
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|
1357 |
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value: 45.705
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1358 |
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|
1359 |
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value: 47.225
|
1360 |
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|
1361 |
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value: 38.889
|
1362 |
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|
1363 |
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value: 40.758
|
1364 |
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- type: ndcg_at_100
|
1365 |
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value: 47.671
|
1366 |
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|
1367 |
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value: 50.744
|
1368 |
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|
1369 |
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value: 36.296
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1370 |
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|
1371 |
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value: 37.852999999999994
|
1372 |
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|
1373 |
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value: 38.889
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1374 |
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|
1375 |
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value: 11.466
|
1376 |
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- type: precision_at_100
|
1377 |
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value: 1.8499999999999999
|
1378 |
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- type: precision_at_1000
|
1379 |
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value: 0.24
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1380 |
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- type: precision_at_3
|
1381 |
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value: 24.126
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1382 |
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- type: precision_at_5
|
1383 |
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value: 18.21
|
1384 |
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- type: recall_at_1
|
1385 |
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value: 20.087
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1386 |
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- type: recall_at_10
|
1387 |
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value: 48.042
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1388 |
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- type: recall_at_100
|
1389 |
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value: 73.493
|
1390 |
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- type: recall_at_1000
|
1391 |
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value: 91.851
|
1392 |
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- type: recall_at_3
|
1393 |
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value: 32.694
|
1394 |
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- type: recall_at_5
|
1395 |
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value: 39.099000000000004
|
1396 |
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- task:
|
1397 |
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type: Retrieval
|
1398 |
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dataset:
|
1399 |
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type: hotpotqa
|
1400 |
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name: MTEB HotpotQA
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1401 |
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config: default
|
1402 |
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split: test
|
1403 |
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revision: None
|
1404 |
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metrics:
|
1405 |
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- type: map_at_1
|
1406 |
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value: 38.096000000000004
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1407 |
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1408 |
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value: 56.99999999999999
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1409 |
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1410 |
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value: 57.914
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1411 |
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1412 |
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value: 57.984
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1413 |
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1414 |
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value: 53.900999999999996
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1415 |
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1416 |
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value: 55.827000000000005
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1417 |
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1418 |
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1419 |
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|
1420 |
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value: 81.955
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1421 |
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1422 |
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value: 82.164
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1423 |
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1424 |
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value: 82.173
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1425 |
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1426 |
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value: 80.963
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1427 |
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|
1428 |
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value: 81.574
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1429 |
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- type: ndcg_at_1
|
1430 |
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value: 76.19200000000001
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1431 |
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|
1432 |
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value: 65.75
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1433 |
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1434 |
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value: 68.949
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1435 |
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- type: ndcg_at_1000
|
1436 |
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value: 70.342
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1437 |
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- type: ndcg_at_3
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1438 |
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value: 61.29
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1439 |
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1440 |
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value: 63.747
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1441 |
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- type: precision_at_1
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1442 |
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value: 76.19200000000001
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1443 |
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- type: precision_at_10
|
1444 |
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value: 13.571
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1445 |
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- type: precision_at_100
|
1446 |
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value: 1.6070000000000002
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1447 |
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- type: precision_at_1000
|
1448 |
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value: 0.179
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1449 |
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- type: precision_at_3
|
1450 |
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value: 38.663
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1451 |
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- type: precision_at_5
|
1452 |
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value: 25.136999999999997
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1453 |
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- type: recall_at_1
|
1454 |
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value: 38.096000000000004
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1455 |
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- type: recall_at_10
|
1456 |
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value: 67.853
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1457 |
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- type: recall_at_100
|
1458 |
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value: 80.365
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1459 |
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- type: recall_at_1000
|
1460 |
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value: 89.629
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1461 |
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- type: recall_at_3
|
1462 |
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value: 57.995
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1463 |
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- type: recall_at_5
|
1464 |
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value: 62.843
|
1465 |
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- task:
|
1466 |
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type: Classification
|
1467 |
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dataset:
|
1468 |
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type: mteb/imdb
|
1469 |
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name: MTEB ImdbClassification
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1470 |
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config: default
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1471 |
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split: test
|
1472 |
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revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
|
1473 |
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metrics:
|
1474 |
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- type: accuracy
|
1475 |
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value: 85.95200000000001
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1476 |
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- type: ap
|
1477 |
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value: 80.73847277002109
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1478 |
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- type: f1
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1479 |
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value: 85.92406135678594
|
1480 |
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- task:
|
1481 |
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1482 |
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dataset:
|
1483 |
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type: msmarco
|
1484 |
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name: MTEB MSMARCO
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1485 |
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config: default
|
1486 |
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split: dev
|
1487 |
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revision: None
|
1488 |
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metrics:
|
1489 |
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|
1490 |
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value: 20.916999999999998
|
1491 |
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- type: map_at_10
|
1492 |
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value: 33.23
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1493 |
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1494 |
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value: 34.427
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1495 |
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- type: map_at_1000
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1496 |
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value: 34.477000000000004
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1497 |
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|
1498 |
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value: 29.292
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1499 |
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- type: map_at_5
|
1500 |
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value: 31.6
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1501 |
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- type: mrr_at_1
|
1502 |
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value: 21.547
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1503 |
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- type: mrr_at_10
|
1504 |
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value: 33.839999999999996
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1505 |
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- type: mrr_at_100
|
1506 |
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value: 34.979
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1507 |
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- type: mrr_at_1000
|
1508 |
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value: 35.022999999999996
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1509 |
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- type: mrr_at_3
|
1510 |
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value: 29.988
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1511 |
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|
1512 |
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value: 32.259
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1513 |
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- type: ndcg_at_1
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1514 |
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value: 21.519
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1515 |
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- type: ndcg_at_10
|
1516 |
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value: 40.209
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1517 |
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- type: ndcg_at_100
|
1518 |
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value: 45.954
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1519 |
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- type: ndcg_at_1000
|
1520 |
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value: 47.187
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1521 |
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- type: ndcg_at_3
|
1522 |
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value: 32.227
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1523 |
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1524 |
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value: 36.347
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1525 |
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|
1526 |
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value: 21.519
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1527 |
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- type: precision_at_10
|
1528 |
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value: 6.447
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1529 |
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- type: precision_at_100
|
1530 |
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value: 0.932
|
1531 |
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- type: precision_at_1000
|
1532 |
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value: 0.104
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1533 |
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|
1534 |
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value: 13.877999999999998
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1535 |
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- type: precision_at_5
|
1536 |
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value: 10.404
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1537 |
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- type: recall_at_1
|
1538 |
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value: 20.916999999999998
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1539 |
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- type: recall_at_10
|
1540 |
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value: 61.7
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1541 |
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- type: recall_at_100
|
1542 |
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value: 88.202
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1543 |
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- type: recall_at_1000
|
1544 |
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value: 97.588
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1545 |
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- type: recall_at_3
|
1546 |
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value: 40.044999999999995
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1547 |
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- type: recall_at_5
|
1548 |
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value: 49.964999999999996
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1549 |
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- task:
|
1550 |
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type: Classification
|
1551 |
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dataset:
|
1552 |
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type: mteb/mtop_domain
|
1553 |
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name: MTEB MTOPDomainClassification (en)
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1554 |
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config: en
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1555 |
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split: test
|
1556 |
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revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
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1557 |
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metrics:
|
1558 |
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- type: accuracy
|
1559 |
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value: 93.02781577747379
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1560 |
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- type: f1
|
1561 |
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value: 92.83653922768306
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1562 |
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- task:
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1563 |
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type: Classification
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1564 |
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dataset:
|
1565 |
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type: mteb/mtop_intent
|
1566 |
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name: MTEB MTOPIntentClassification (en)
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config: en
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1568 |
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split: test
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revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
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1570 |
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metrics:
|
1571 |
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1572 |
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value: 72.04286365709075
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1573 |
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- type: f1
|
1574 |
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value: 53.43867658525793
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1575 |
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- task:
|
1576 |
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|
1577 |
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dataset:
|
1578 |
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type: mteb/amazon_massive_intent
|
1579 |
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name: MTEB MassiveIntentClassification (en)
|
1580 |
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config: en
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1581 |
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split: test
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1582 |
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revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
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1583 |
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metrics:
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1584 |
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1585 |
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value: 71.47276395427035
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1586 |
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- type: f1
|
1587 |
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value: 69.77017399597342
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1588 |
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- task:
|
1589 |
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|
1590 |
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dataset:
|
1591 |
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type: mteb/amazon_massive_scenario
|
1592 |
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name: MTEB MassiveScenarioClassification (en)
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1593 |
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config: en
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1594 |
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1595 |
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metrics:
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1597 |
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1598 |
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value: 76.3819771351715
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1599 |
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- type: f1
|
1600 |
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value: 76.8484533435409
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1601 |
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- task:
|
1602 |
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type: Clustering
|
1603 |
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dataset:
|
1604 |
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type: mteb/medrxiv-clustering-p2p
|
1605 |
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name: MTEB MedrxivClusteringP2P
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1606 |
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config: default
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1607 |
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split: test
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1609 |
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metrics:
|
1610 |
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1611 |
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value: 33.16515993299593
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1612 |
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- task:
|
1613 |
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type: Clustering
|
1614 |
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dataset:
|
1615 |
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type: mteb/medrxiv-clustering-s2s
|
1616 |
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name: MTEB MedrxivClusteringS2S
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1617 |
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config: default
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1618 |
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split: test
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1619 |
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metrics:
|
1621 |
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1622 |
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value: 31.77145323314774
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1623 |
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- task:
|
1624 |
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type: Reranking
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1625 |
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dataset:
|
1626 |
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type: mteb/mind_small
|
1627 |
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name: MTEB MindSmallReranking
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1628 |
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1629 |
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1630 |
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revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
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1633 |
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1635 |
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1636 |
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- task:
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1637 |
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1638 |
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dataset:
|
1639 |
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type: nfcorpus
|
1640 |
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name: MTEB NFCorpus
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1641 |
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config: default
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1642 |
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split: test
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1643 |
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revision: None
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1644 |
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metrics:
|
1645 |
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1646 |
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value: 7.063999999999999
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1647 |
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1655 |
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1672 |
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1674 |
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value: 50.15500000000001
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value: 8.994
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value: 40.041
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1699 |
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- type: recall_at_1000
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1700 |
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value: 67.43
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1701 |
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- type: recall_at_3
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1702 |
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value: 11.562999999999999
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1703 |
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- type: recall_at_5
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1704 |
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value: 14.771
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1705 |
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- task:
|
1706 |
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1707 |
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dataset:
|
1708 |
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type: nq
|
1709 |
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name: MTEB NQ
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1710 |
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config: default
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1711 |
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split: test
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1712 |
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revision: None
|
1713 |
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metrics:
|
1714 |
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- type: map_at_1
|
1715 |
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value: 29.046
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1716 |
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- type: map_at_10
|
1717 |
+
value: 44.808
|
1718 |
+
- type: map_at_100
|
1719 |
+
value: 45.898
|
1720 |
+
- type: map_at_1000
|
1721 |
+
value: 45.927
|
1722 |
+
- type: map_at_3
|
1723 |
+
value: 40.19
|
1724 |
+
- type: map_at_5
|
1725 |
+
value: 42.897
|
1726 |
+
- type: mrr_at_1
|
1727 |
+
value: 32.706
|
1728 |
+
- type: mrr_at_10
|
1729 |
+
value: 47.275
|
1730 |
+
- type: mrr_at_100
|
1731 |
+
value: 48.075
|
1732 |
+
- type: mrr_at_1000
|
1733 |
+
value: 48.095
|
1734 |
+
- type: mrr_at_3
|
1735 |
+
value: 43.463
|
1736 |
+
- type: mrr_at_5
|
1737 |
+
value: 45.741
|
1738 |
+
- type: ndcg_at_1
|
1739 |
+
value: 32.706
|
1740 |
+
- type: ndcg_at_10
|
1741 |
+
value: 52.835
|
1742 |
+
- type: ndcg_at_100
|
1743 |
+
value: 57.345
|
1744 |
+
- type: ndcg_at_1000
|
1745 |
+
value: 57.985
|
1746 |
+
- type: ndcg_at_3
|
1747 |
+
value: 44.171
|
1748 |
+
- type: ndcg_at_5
|
1749 |
+
value: 48.661
|
1750 |
+
- type: precision_at_1
|
1751 |
+
value: 32.706
|
1752 |
+
- type: precision_at_10
|
1753 |
+
value: 8.895999999999999
|
1754 |
+
- type: precision_at_100
|
1755 |
+
value: 1.143
|
1756 |
+
- type: precision_at_1000
|
1757 |
+
value: 0.12
|
1758 |
+
- type: precision_at_3
|
1759 |
+
value: 20.238999999999997
|
1760 |
+
- type: precision_at_5
|
1761 |
+
value: 14.728
|
1762 |
+
- type: recall_at_1
|
1763 |
+
value: 29.046
|
1764 |
+
- type: recall_at_10
|
1765 |
+
value: 74.831
|
1766 |
+
- type: recall_at_100
|
1767 |
+
value: 94.192
|
1768 |
+
- type: recall_at_1000
|
1769 |
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value: 98.897
|
1770 |
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- type: recall_at_3
|
1771 |
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value: 52.37500000000001
|
1772 |
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- type: recall_at_5
|
1773 |
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value: 62.732
|
1774 |
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- task:
|
1775 |
+
type: Retrieval
|
1776 |
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dataset:
|
1777 |
+
type: quora
|
1778 |
+
name: MTEB QuoraRetrieval
|
1779 |
+
config: default
|
1780 |
+
split: test
|
1781 |
+
revision: None
|
1782 |
+
metrics:
|
1783 |
+
- type: map_at_1
|
1784 |
+
value: 70.38799999999999
|
1785 |
+
- type: map_at_10
|
1786 |
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value: 84.315
|
1787 |
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- type: map_at_100
|
1788 |
+
value: 84.955
|
1789 |
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- type: map_at_1000
|
1790 |
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value: 84.971
|
1791 |
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- type: map_at_3
|
1792 |
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value: 81.33399999999999
|
1793 |
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- type: map_at_5
|
1794 |
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value: 83.21300000000001
|
1795 |
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- type: mrr_at_1
|
1796 |
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value: 81.03
|
1797 |
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- type: mrr_at_10
|
1798 |
+
value: 87.395
|
1799 |
+
- type: mrr_at_100
|
1800 |
+
value: 87.488
|
1801 |
+
- type: mrr_at_1000
|
1802 |
+
value: 87.48899999999999
|
1803 |
+
- type: mrr_at_3
|
1804 |
+
value: 86.41499999999999
|
1805 |
+
- type: mrr_at_5
|
1806 |
+
value: 87.074
|
1807 |
+
- type: ndcg_at_1
|
1808 |
+
value: 81.04
|
1809 |
+
- type: ndcg_at_10
|
1810 |
+
value: 88.151
|
1811 |
+
- type: ndcg_at_100
|
1812 |
+
value: 89.38199999999999
|
1813 |
+
- type: ndcg_at_1000
|
1814 |
+
value: 89.479
|
1815 |
+
- type: ndcg_at_3
|
1816 |
+
value: 85.24000000000001
|
1817 |
+
- type: ndcg_at_5
|
1818 |
+
value: 86.856
|
1819 |
+
- type: precision_at_1
|
1820 |
+
value: 81.04
|
1821 |
+
- type: precision_at_10
|
1822 |
+
value: 13.372
|
1823 |
+
- type: precision_at_100
|
1824 |
+
value: 1.526
|
1825 |
+
- type: precision_at_1000
|
1826 |
+
value: 0.157
|
1827 |
+
- type: precision_at_3
|
1828 |
+
value: 37.217
|
1829 |
+
- type: precision_at_5
|
1830 |
+
value: 24.502
|
1831 |
+
- type: recall_at_1
|
1832 |
+
value: 70.38799999999999
|
1833 |
+
- type: recall_at_10
|
1834 |
+
value: 95.452
|
1835 |
+
- type: recall_at_100
|
1836 |
+
value: 99.59700000000001
|
1837 |
+
- type: recall_at_1000
|
1838 |
+
value: 99.988
|
1839 |
+
- type: recall_at_3
|
1840 |
+
value: 87.11
|
1841 |
+
- type: recall_at_5
|
1842 |
+
value: 91.662
|
1843 |
+
- task:
|
1844 |
+
type: Clustering
|
1845 |
+
dataset:
|
1846 |
+
type: mteb/reddit-clustering
|
1847 |
+
name: MTEB RedditClustering
|
1848 |
+
config: default
|
1849 |
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split: test
|
1850 |
+
revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
|
1851 |
+
metrics:
|
1852 |
+
- type: v_measure
|
1853 |
+
value: 59.334991029213235
|
1854 |
+
- task:
|
1855 |
+
type: Clustering
|
1856 |
+
dataset:
|
1857 |
+
type: mteb/reddit-clustering-p2p
|
1858 |
+
name: MTEB RedditClusteringP2P
|
1859 |
+
config: default
|
1860 |
+
split: test
|
1861 |
+
revision: 282350215ef01743dc01b456c7f5241fa8937f16
|
1862 |
+
metrics:
|
1863 |
+
- type: v_measure
|
1864 |
+
value: 62.586500854616666
|
1865 |
+
- task:
|
1866 |
+
type: Retrieval
|
1867 |
+
dataset:
|
1868 |
+
type: scidocs
|
1869 |
+
name: MTEB SCIDOCS
|
1870 |
+
config: default
|
1871 |
+
split: test
|
1872 |
+
revision: None
|
1873 |
+
metrics:
|
1874 |
+
- type: map_at_1
|
1875 |
+
value: 5.153
|
1876 |
+
- type: map_at_10
|
1877 |
+
value: 14.277000000000001
|
1878 |
+
- type: map_at_100
|
1879 |
+
value: 16.922
|
1880 |
+
- type: map_at_1000
|
1881 |
+
value: 17.302999999999997
|
1882 |
+
- type: map_at_3
|
1883 |
+
value: 9.961
|
1884 |
+
- type: map_at_5
|
1885 |
+
value: 12.257
|
1886 |
+
- type: mrr_at_1
|
1887 |
+
value: 25.4
|
1888 |
+
- type: mrr_at_10
|
1889 |
+
value: 37.458000000000006
|
1890 |
+
- type: mrr_at_100
|
1891 |
+
value: 38.681
|
1892 |
+
- type: mrr_at_1000
|
1893 |
+
value: 38.722
|
1894 |
+
- type: mrr_at_3
|
1895 |
+
value: 34.1
|
1896 |
+
- type: mrr_at_5
|
1897 |
+
value: 36.17
|
1898 |
+
- type: ndcg_at_1
|
1899 |
+
value: 25.4
|
1900 |
+
- type: ndcg_at_10
|
1901 |
+
value: 23.132
|
1902 |
+
- type: ndcg_at_100
|
1903 |
+
value: 32.908
|
1904 |
+
- type: ndcg_at_1000
|
1905 |
+
value: 38.754
|
1906 |
+
- type: ndcg_at_3
|
1907 |
+
value: 21.82
|
1908 |
+
- type: ndcg_at_5
|
1909 |
+
value: 19.353
|
1910 |
+
- type: precision_at_1
|
1911 |
+
value: 25.4
|
1912 |
+
- type: precision_at_10
|
1913 |
+
value: 12.1
|
1914 |
+
- type: precision_at_100
|
1915 |
+
value: 2.628
|
1916 |
+
- type: precision_at_1000
|
1917 |
+
value: 0.402
|
1918 |
+
- type: precision_at_3
|
1919 |
+
value: 20.732999999999997
|
1920 |
+
- type: precision_at_5
|
1921 |
+
value: 17.34
|
1922 |
+
- type: recall_at_1
|
1923 |
+
value: 5.153
|
1924 |
+
- type: recall_at_10
|
1925 |
+
value: 24.54
|
1926 |
+
- type: recall_at_100
|
1927 |
+
value: 53.293
|
1928 |
+
- type: recall_at_1000
|
1929 |
+
value: 81.57
|
1930 |
+
- type: recall_at_3
|
1931 |
+
value: 12.613
|
1932 |
+
- type: recall_at_5
|
1933 |
+
value: 17.577
|
1934 |
+
- task:
|
1935 |
+
type: STS
|
1936 |
+
dataset:
|
1937 |
+
type: mteb/sickr-sts
|
1938 |
+
name: MTEB SICK-R
|
1939 |
+
config: default
|
1940 |
+
split: test
|
1941 |
+
revision: a6ea5a8cab320b040a23452cc28066d9beae2cee
|
1942 |
+
metrics:
|
1943 |
+
- type: cos_sim_pearson
|
1944 |
+
value: 84.86284404925333
|
1945 |
+
- type: cos_sim_spearman
|
1946 |
+
value: 78.85870555294795
|
1947 |
+
- type: euclidean_pearson
|
1948 |
+
value: 82.20105295276093
|
1949 |
+
- type: euclidean_spearman
|
1950 |
+
value: 78.92125617009592
|
1951 |
+
- type: manhattan_pearson
|
1952 |
+
value: 82.15840025289069
|
1953 |
+
- type: manhattan_spearman
|
1954 |
+
value: 78.85955732900803
|
1955 |
+
- task:
|
1956 |
+
type: STS
|
1957 |
+
dataset:
|
1958 |
+
type: mteb/sts12-sts
|
1959 |
+
name: MTEB STS12
|
1960 |
+
config: default
|
1961 |
+
split: test
|
1962 |
+
revision: a0d554a64d88156834ff5ae9920b964011b16384
|
1963 |
+
metrics:
|
1964 |
+
- type: cos_sim_pearson
|
1965 |
+
value: 84.98747423389027
|
1966 |
+
- type: cos_sim_spearman
|
1967 |
+
value: 75.71298531799367
|
1968 |
+
- type: euclidean_pearson
|
1969 |
+
value: 81.59709559192291
|
1970 |
+
- type: euclidean_spearman
|
1971 |
+
value: 75.40622749225653
|
1972 |
+
- type: manhattan_pearson
|
1973 |
+
value: 81.55553547608804
|
1974 |
+
- type: manhattan_spearman
|
1975 |
+
value: 75.39380235424899
|
1976 |
+
- task:
|
1977 |
+
type: STS
|
1978 |
+
dataset:
|
1979 |
+
type: mteb/sts13-sts
|
1980 |
+
name: MTEB STS13
|
1981 |
+
config: default
|
1982 |
+
split: test
|
1983 |
+
revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
|
1984 |
+
metrics:
|
1985 |
+
- type: cos_sim_pearson
|
1986 |
+
value: 83.76861330695503
|
1987 |
+
- type: cos_sim_spearman
|
1988 |
+
value: 85.72991921531624
|
1989 |
+
- type: euclidean_pearson
|
1990 |
+
value: 84.84504307397536
|
1991 |
+
- type: euclidean_spearman
|
1992 |
+
value: 86.02679162824732
|
1993 |
+
- type: manhattan_pearson
|
1994 |
+
value: 84.79969439220142
|
1995 |
+
- type: manhattan_spearman
|
1996 |
+
value: 85.99238837291625
|
1997 |
+
- task:
|
1998 |
+
type: STS
|
1999 |
+
dataset:
|
2000 |
+
type: mteb/sts14-sts
|
2001 |
+
name: MTEB STS14
|
2002 |
+
config: default
|
2003 |
+
split: test
|
2004 |
+
revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
|
2005 |
+
metrics:
|
2006 |
+
- type: cos_sim_pearson
|
2007 |
+
value: 83.31929747511796
|
2008 |
+
- type: cos_sim_spearman
|
2009 |
+
value: 81.50806522502528
|
2010 |
+
- type: euclidean_pearson
|
2011 |
+
value: 82.93936686512777
|
2012 |
+
- type: euclidean_spearman
|
2013 |
+
value: 81.54403447993224
|
2014 |
+
- type: manhattan_pearson
|
2015 |
+
value: 82.89696981900828
|
2016 |
+
- type: manhattan_spearman
|
2017 |
+
value: 81.52817825470865
|
2018 |
+
- task:
|
2019 |
+
type: STS
|
2020 |
+
dataset:
|
2021 |
+
type: mteb/sts15-sts
|
2022 |
+
name: MTEB STS15
|
2023 |
+
config: default
|
2024 |
+
split: test
|
2025 |
+
revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
|
2026 |
+
metrics:
|
2027 |
+
- type: cos_sim_pearson
|
2028 |
+
value: 87.14413295332908
|
2029 |
+
- type: cos_sim_spearman
|
2030 |
+
value: 88.81032027008195
|
2031 |
+
- type: euclidean_pearson
|
2032 |
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value: 88.19205563407645
|
2033 |
+
- type: euclidean_spearman
|
2034 |
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value: 88.89738339479216
|
2035 |
+
- type: manhattan_pearson
|
2036 |
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value: 88.11075942004189
|
2037 |
+
- type: manhattan_spearman
|
2038 |
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value: 88.8297061675564
|
2039 |
+
- task:
|
2040 |
+
type: STS
|
2041 |
+
dataset:
|
2042 |
+
type: mteb/sts16-sts
|
2043 |
+
name: MTEB STS16
|
2044 |
+
config: default
|
2045 |
+
split: test
|
2046 |
+
revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
|
2047 |
+
metrics:
|
2048 |
+
- type: cos_sim_pearson
|
2049 |
+
value: 82.15980075557017
|
2050 |
+
- type: cos_sim_spearman
|
2051 |
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value: 83.81896308594801
|
2052 |
+
- type: euclidean_pearson
|
2053 |
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value: 83.11195254311338
|
2054 |
+
- type: euclidean_spearman
|
2055 |
+
value: 84.10479481755407
|
2056 |
+
- type: manhattan_pearson
|
2057 |
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value: 83.13915225100556
|
2058 |
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- type: manhattan_spearman
|
2059 |
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value: 84.09895591027859
|
2060 |
+
- task:
|
2061 |
+
type: STS
|
2062 |
+
dataset:
|
2063 |
+
type: mteb/sts17-crosslingual-sts
|
2064 |
+
name: MTEB STS17 (en-en)
|
2065 |
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config: en-en
|
2066 |
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split: test
|
2067 |
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revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
|
2068 |
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metrics:
|
2069 |
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- type: cos_sim_pearson
|
2070 |
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value: 87.93669480147919
|
2071 |
+
- type: cos_sim_spearman
|
2072 |
+
value: 87.89861394614361
|
2073 |
+
- type: euclidean_pearson
|
2074 |
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value: 88.37316413202339
|
2075 |
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- type: euclidean_spearman
|
2076 |
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value: 88.18033817842569
|
2077 |
+
- type: manhattan_pearson
|
2078 |
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value: 88.39427578879469
|
2079 |
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- type: manhattan_spearman
|
2080 |
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value: 88.09185009236847
|
2081 |
+
- task:
|
2082 |
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type: STS
|
2083 |
+
dataset:
|
2084 |
+
type: mteb/sts22-crosslingual-sts
|
2085 |
+
name: MTEB STS22 (en)
|
2086 |
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config: en
|
2087 |
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split: test
|
2088 |
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revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80
|
2089 |
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metrics:
|
2090 |
+
- type: cos_sim_pearson
|
2091 |
+
value: 66.62215083348255
|
2092 |
+
- type: cos_sim_spearman
|
2093 |
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value: 67.33243665716736
|
2094 |
+
- type: euclidean_pearson
|
2095 |
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value: 67.60871701996284
|
2096 |
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- type: euclidean_spearman
|
2097 |
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value: 66.75929225238659
|
2098 |
+
- type: manhattan_pearson
|
2099 |
+
value: 67.63907838970992
|
2100 |
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- type: manhattan_spearman
|
2101 |
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value: 66.79313656754846
|
2102 |
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- task:
|
2103 |
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type: STS
|
2104 |
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dataset:
|
2105 |
+
type: mteb/stsbenchmark-sts
|
2106 |
+
name: MTEB STSBenchmark
|
2107 |
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config: default
|
2108 |
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split: test
|
2109 |
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revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
|
2110 |
+
metrics:
|
2111 |
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- type: cos_sim_pearson
|
2112 |
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value: 84.65549191934764
|
2113 |
+
- type: cos_sim_spearman
|
2114 |
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value: 85.73266847750143
|
2115 |
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- type: euclidean_pearson
|
2116 |
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value: 85.75609932254318
|
2117 |
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- type: euclidean_spearman
|
2118 |
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value: 85.9452287759371
|
2119 |
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- type: manhattan_pearson
|
2120 |
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value: 85.69717413063573
|
2121 |
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- type: manhattan_spearman
|
2122 |
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value: 85.86546318377046
|
2123 |
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- task:
|
2124 |
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type: Reranking
|
2125 |
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dataset:
|
2126 |
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type: mteb/scidocs-reranking
|
2127 |
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name: MTEB SciDocsRR
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2128 |
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config: default
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2129 |
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split: test
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2130 |
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revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
|
2131 |
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metrics:
|
2132 |
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- type: map
|
2133 |
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value: 87.08164129085783
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2134 |
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- type: mrr
|
2135 |
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2136 |
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- task:
|
2137 |
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type: Retrieval
|
2138 |
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dataset:
|
2139 |
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type: scifact
|
2140 |
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name: MTEB SciFact
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2141 |
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config: default
|
2142 |
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split: test
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2143 |
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revision: None
|
2144 |
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metrics:
|
2145 |
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- type: map_at_1
|
2146 |
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value: 62.09400000000001
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2147 |
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2148 |
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value: 71.712
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2149 |
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2150 |
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2151 |
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2152 |
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2154 |
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2155 |
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2156 |
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2157 |
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2158 |
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value: 65.0
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2159 |
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2160 |
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value: 72.572
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2161 |
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2162 |
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2163 |
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2164 |
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value: 72.856
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2165 |
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2166 |
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2167 |
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2168 |
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2169 |
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2170 |
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value: 65.0
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2171 |
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2172 |
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2173 |
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2174 |
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value: 77.887
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2175 |
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2176 |
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2177 |
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2178 |
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2179 |
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2180 |
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2181 |
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2182 |
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value: 65.0
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2183 |
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2184 |
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value: 10.033
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2185 |
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- type: precision_at_100
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value: 1.097
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2187 |
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- type: precision_at_1000
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value: 0.11199999999999999
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2189 |
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- type: precision_at_3
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2190 |
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value: 27.667
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2191 |
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2192 |
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value: 18.4
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2193 |
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- type: recall_at_1
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2194 |
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value: 62.09400000000001
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2195 |
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2196 |
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2198 |
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value: 96.833
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2199 |
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- type: recall_at_1000
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2200 |
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2201 |
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2202 |
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value: 75.922
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2203 |
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- type: recall_at_5
|
2204 |
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value: 82.428
|
2205 |
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- task:
|
2206 |
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type: PairClassification
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2207 |
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dataset:
|
2208 |
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type: mteb/sprintduplicatequestions-pairclassification
|
2209 |
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name: MTEB SprintDuplicateQuestions
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2210 |
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config: default
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2211 |
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split: test
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2212 |
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revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
|
2213 |
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metrics:
|
2214 |
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- type: cos_sim_accuracy
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2215 |
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value: 99.82178217821782
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2216 |
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- type: cos_sim_ap
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2217 |
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2222 |
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- type: cos_sim_recall
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2223 |
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value: 88.1
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2224 |
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- type: dot_accuracy
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2225 |
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- type: dot_precision
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2232 |
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- type: dot_recall
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2233 |
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2234 |
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- type: euclidean_accuracy
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2235 |
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2236 |
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- type: euclidean_ap
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2238 |
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- type: euclidean_f1
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2240 |
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- type: euclidean_precision
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2241 |
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2242 |
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- type: euclidean_recall
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2243 |
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value: 88.4
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2244 |
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- type: manhattan_accuracy
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2245 |
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value: 99.82574257425742
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2246 |
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- type: manhattan_ap
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2247 |
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2248 |
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- type: manhattan_f1
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2250 |
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- type: manhattan_precision
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2251 |
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value: 92.55429162357808
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2252 |
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- type: manhattan_recall
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2253 |
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value: 89.5
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2254 |
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- type: max_accuracy
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2255 |
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value: 99.82574257425742
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2256 |
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- type: max_ap
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2257 |
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2258 |
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- type: max_f1
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2259 |
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2260 |
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- task:
|
2261 |
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type: Clustering
|
2262 |
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dataset:
|
2263 |
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type: mteb/stackexchange-clustering
|
2264 |
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name: MTEB StackExchangeClustering
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2265 |
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config: default
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2266 |
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split: test
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2267 |
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revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
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2268 |
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metrics:
|
2269 |
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- type: v_measure
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2270 |
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value: 66.63957663468679
|
2271 |
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- task:
|
2272 |
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type: Clustering
|
2273 |
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dataset:
|
2274 |
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type: mteb/stackexchange-clustering-p2p
|
2275 |
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name: MTEB StackExchangeClusteringP2P
|
2276 |
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config: default
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2277 |
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split: test
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2278 |
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revision: 815ca46b2622cec33ccafc3735d572c266efdb44
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2279 |
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metrics:
|
2280 |
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- type: v_measure
|
2281 |
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value: 36.003307257923964
|
2282 |
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- task:
|
2283 |
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type: Reranking
|
2284 |
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dataset:
|
2285 |
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type: mteb/stackoverflowdupquestions-reranking
|
2286 |
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name: MTEB StackOverflowDupQuestions
|
2287 |
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config: default
|
2288 |
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split: test
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2289 |
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revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
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2290 |
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metrics:
|
2291 |
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- type: map
|
2292 |
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value: 53.005825525863905
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2293 |
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- type: mrr
|
2294 |
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|
2295 |
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- task:
|
2296 |
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type: Summarization
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2297 |
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dataset:
|
2298 |
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type: mteb/summeval
|
2299 |
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name: MTEB SummEval
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2300 |
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2301 |
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split: test
|
2302 |
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revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
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2303 |
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metrics:
|
2304 |
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- type: cos_sim_pearson
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2305 |
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value: 30.503611569974098
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2306 |
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- type: cos_sim_spearman
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2307 |
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value: 31.17155564248449
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2308 |
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- type: dot_pearson
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2309 |
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value: 26.740428413981306
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2310 |
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- type: dot_spearman
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2311 |
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value: 26.55727635469746
|
2312 |
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- task:
|
2313 |
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type: Retrieval
|
2314 |
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dataset:
|
2315 |
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type: trec-covid
|
2316 |
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name: MTEB TRECCOVID
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2317 |
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config: default
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2318 |
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split: test
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2319 |
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revision: None
|
2320 |
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metrics:
|
2321 |
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- type: map_at_1
|
2322 |
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value: 0.23600000000000002
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2323 |
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- type: map_at_10
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2324 |
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value: 1.7670000000000001
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2325 |
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2326 |
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2327 |
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2328 |
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value: 25.997999999999998
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2329 |
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- type: map_at_3
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2330 |
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value: 0.605
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2331 |
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2332 |
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value: 0.9560000000000001
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2333 |
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2334 |
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value: 84.0
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2335 |
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2336 |
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value: 90.167
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2337 |
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2338 |
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value: 90.167
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2339 |
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- type: mrr_at_1000
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2340 |
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value: 90.167
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2341 |
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2342 |
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value: 89.667
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2343 |
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2344 |
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value: 90.167
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2345 |
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- type: ndcg_at_1
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2346 |
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value: 77.0
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2347 |
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2348 |
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value: 68.783
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2349 |
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- type: ndcg_at_100
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2350 |
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value: 54.196
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2351 |
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- type: ndcg_at_1000
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2352 |
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value: 52.077
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2353 |
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- type: ndcg_at_3
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2354 |
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value: 71.642
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2355 |
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- type: ndcg_at_5
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2356 |
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value: 70.45700000000001
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2357 |
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- type: precision_at_1
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2358 |
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value: 84.0
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2359 |
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2360 |
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value: 73.0
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2361 |
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2362 |
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value: 55.48
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2363 |
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- type: precision_at_1000
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2364 |
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value: 23.102
|
2365 |
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- type: precision_at_3
|
2366 |
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value: 76.0
|
2367 |
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- type: precision_at_5
|
2368 |
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value: 74.8
|
2369 |
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- type: recall_at_1
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2370 |
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value: 0.23600000000000002
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2371 |
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- type: recall_at_10
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2372 |
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value: 1.9869999999999999
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2373 |
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2374 |
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value: 13.749
|
2375 |
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- type: recall_at_1000
|
2376 |
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value: 50.157
|
2377 |
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- type: recall_at_3
|
2378 |
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value: 0.633
|
2379 |
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- type: recall_at_5
|
2380 |
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value: 1.0290000000000001
|
2381 |
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- task:
|
2382 |
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type: Retrieval
|
2383 |
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dataset:
|
2384 |
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type: webis-touche2020
|
2385 |
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name: MTEB Touche2020
|
2386 |
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config: default
|
2387 |
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split: test
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2388 |
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revision: None
|
2389 |
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metrics:
|
2390 |
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- type: map_at_1
|
2391 |
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value: 1.437
|
2392 |
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- type: map_at_10
|
2393 |
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value: 8.791
|
2394 |
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- type: map_at_100
|
2395 |
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value: 15.001999999999999
|
2396 |
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- type: map_at_1000
|
2397 |
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value: 16.549
|
2398 |
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|
2399 |
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value: 3.8080000000000003
|
2400 |
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- type: map_at_5
|
2401 |
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value: 5.632000000000001
|
2402 |
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- type: mrr_at_1
|
2403 |
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value: 20.408
|
2404 |
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- type: mrr_at_10
|
2405 |
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value: 36.96
|
2406 |
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- type: mrr_at_100
|
2407 |
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value: 37.912
|
2408 |
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- type: mrr_at_1000
|
2409 |
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value: 37.912
|
2410 |
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- type: mrr_at_3
|
2411 |
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value: 29.592000000000002
|
2412 |
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- type: mrr_at_5
|
2413 |
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value: 34.489999999999995
|
2414 |
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- type: ndcg_at_1
|
2415 |
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value: 19.387999999999998
|
2416 |
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- type: ndcg_at_10
|
2417 |
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value: 22.554
|
2418 |
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- type: ndcg_at_100
|
2419 |
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value: 35.197
|
2420 |
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- type: ndcg_at_1000
|
2421 |
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value: 46.58
|
2422 |
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- type: ndcg_at_3
|
2423 |
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value: 20.285
|
2424 |
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|
2425 |
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value: 21.924
|
2426 |
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- type: precision_at_1
|
2427 |
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value: 20.408
|
2428 |
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- type: precision_at_10
|
2429 |
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value: 21.837
|
2430 |
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- type: precision_at_100
|
2431 |
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value: 7.754999999999999
|
2432 |
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- type: precision_at_1000
|
2433 |
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value: 1.537
|
2434 |
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- type: precision_at_3
|
2435 |
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value: 21.769
|
2436 |
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- type: precision_at_5
|
2437 |
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value: 23.673
|
2438 |
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- type: recall_at_1
|
2439 |
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value: 1.437
|
2440 |
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- type: recall_at_10
|
2441 |
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value: 16.314999999999998
|
2442 |
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- type: recall_at_100
|
2443 |
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value: 47.635
|
2444 |
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- type: recall_at_1000
|
2445 |
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value: 82.963
|
2446 |
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- type: recall_at_3
|
2447 |
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value: 4.955
|
2448 |
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- type: recall_at_5
|
2449 |
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value: 8.805
|
2450 |
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- task:
|
2451 |
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type: Classification
|
2452 |
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dataset:
|
2453 |
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type: mteb/toxic_conversations_50k
|
2454 |
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name: MTEB ToxicConversationsClassification
|
2455 |
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config: default
|
2456 |
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split: test
|
2457 |
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|
2458 |
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metrics:
|
2459 |
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- type: accuracy
|
2460 |
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value: 71.6128
|
2461 |
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- type: ap
|
2462 |
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value: 14.279639861175664
|
2463 |
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- type: f1
|
2464 |
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value: 54.922292491204274
|
2465 |
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- task:
|
2466 |
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type: Classification
|
2467 |
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dataset:
|
2468 |
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type: mteb/tweet_sentiment_extraction
|
2469 |
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name: MTEB TweetSentimentExtractionClassification
|
2470 |
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config: default
|
2471 |
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split: test
|
2472 |
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|
2473 |
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metrics:
|
2474 |
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- type: accuracy
|
2475 |
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value: 57.01188455008489
|
2476 |
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- type: f1
|
2477 |
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value: 57.377953019225515
|
2478 |
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- task:
|
2479 |
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type: Clustering
|
2480 |
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dataset:
|
2481 |
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type: mteb/twentynewsgroups-clustering
|
2482 |
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name: MTEB TwentyNewsgroupsClustering
|
2483 |
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config: default
|
2484 |
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split: test
|
2485 |
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2486 |
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metrics:
|
2487 |
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- type: v_measure
|
2488 |
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value: 52.306769136544254
|
2489 |
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- task:
|
2490 |
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type: PairClassification
|
2491 |
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dataset:
|
2492 |
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type: mteb/twittersemeval2015-pairclassification
|
2493 |
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name: MTEB TwitterSemEval2015
|
2494 |
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config: default
|
2495 |
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split: test
|
2496 |
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|
2497 |
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metrics:
|
2498 |
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|
2499 |
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value: 85.64701674912082
|
2500 |
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- type: cos_sim_ap
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2501 |
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value: 72.46600945328552
|
2502 |
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2503 |
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value: 67.96572367648784
|
2504 |
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- type: cos_sim_precision
|
2505 |
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value: 61.21801649397336
|
2506 |
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- type: cos_sim_recall
|
2507 |
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value: 76.38522427440633
|
2508 |
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- type: dot_accuracy
|
2509 |
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|
2510 |
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- type: dot_ap
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2511 |
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2512 |
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2513 |
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2514 |
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- type: dot_precision
|
2515 |
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|
2516 |
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- type: dot_recall
|
2517 |
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|
2518 |
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- type: euclidean_accuracy
|
2519 |
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|
2520 |
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- type: euclidean_ap
|
2521 |
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value: 72.76873850945174
|
2522 |
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- type: euclidean_f1
|
2523 |
+
value: 68.23556960543262
|
2524 |
+
- type: euclidean_precision
|
2525 |
+
value: 61.3344559040202
|
2526 |
+
- type: euclidean_recall
|
2527 |
+
value: 76.88654353562005
|
2528 |
+
- type: manhattan_accuracy
|
2529 |
+
value: 85.74834594981225
|
2530 |
+
- type: manhattan_ap
|
2531 |
+
value: 72.66825372446462
|
2532 |
+
- type: manhattan_f1
|
2533 |
+
value: 68.21539194662853
|
2534 |
+
- type: manhattan_precision
|
2535 |
+
value: 62.185056472632496
|
2536 |
+
- type: manhattan_recall
|
2537 |
+
value: 75.54089709762533
|
2538 |
+
- type: max_accuracy
|
2539 |
+
value: 85.74834594981225
|
2540 |
+
- type: max_ap
|
2541 |
+
value: 72.76873850945174
|
2542 |
+
- type: max_f1
|
2543 |
+
value: 68.23556960543262
|
2544 |
+
- task:
|
2545 |
+
type: PairClassification
|
2546 |
+
dataset:
|
2547 |
+
type: mteb/twitterurlcorpus-pairclassification
|
2548 |
+
name: MTEB TwitterURLCorpus
|
2549 |
+
config: default
|
2550 |
+
split: test
|
2551 |
+
revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
|
2552 |
+
metrics:
|
2553 |
+
- type: cos_sim_accuracy
|
2554 |
+
value: 88.73171110334924
|
2555 |
+
- type: cos_sim_ap
|
2556 |
+
value: 85.51855542063649
|
2557 |
+
- type: cos_sim_f1
|
2558 |
+
value: 77.95706775700934
|
2559 |
+
- type: cos_sim_precision
|
2560 |
+
value: 74.12524298805887
|
2561 |
+
- type: cos_sim_recall
|
2562 |
+
value: 82.20665229442562
|
2563 |
+
- type: dot_accuracy
|
2564 |
+
value: 86.94842240074514
|
2565 |
+
- type: dot_ap
|
2566 |
+
value: 80.90995345771762
|
2567 |
+
- type: dot_f1
|
2568 |
+
value: 74.20765027322403
|
2569 |
+
- type: dot_precision
|
2570 |
+
value: 70.42594385285575
|
2571 |
+
- type: dot_recall
|
2572 |
+
value: 78.41854019094548
|
2573 |
+
- type: euclidean_accuracy
|
2574 |
+
value: 88.73753250281368
|
2575 |
+
- type: euclidean_ap
|
2576 |
+
value: 85.54712254033734
|
2577 |
+
- type: euclidean_f1
|
2578 |
+
value: 78.07565728654365
|
2579 |
+
- type: euclidean_precision
|
2580 |
+
value: 75.1120597652081
|
2581 |
+
- type: euclidean_recall
|
2582 |
+
value: 81.282722513089
|
2583 |
+
- type: manhattan_accuracy
|
2584 |
+
value: 88.72588970388482
|
2585 |
+
- type: manhattan_ap
|
2586 |
+
value: 85.52118291594071
|
2587 |
+
- type: manhattan_f1
|
2588 |
+
value: 78.04428724070593
|
2589 |
+
- type: manhattan_precision
|
2590 |
+
value: 74.83219105490002
|
2591 |
+
- type: manhattan_recall
|
2592 |
+
value: 81.54450261780106
|
2593 |
+
- type: max_accuracy
|
2594 |
+
value: 88.73753250281368
|
2595 |
+
- type: max_ap
|
2596 |
+
value: 85.54712254033734
|
2597 |
+
- type: max_f1
|
2598 |
+
value: 78.07565728654365
|
2599 |
+
language:
|
2600 |
+
- en
|
2601 |
license: apache-2.0
|
2602 |
---
|
2603 |
+
|
2604 |
+
# gte-base
|
2605 |
+
|
2606 |
+
Gegeral Text Embeddings (GTE) model.
|
2607 |
+
|
2608 |
+
This model has 12 layers and the embedding size is 768.
|