Update README.md
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README.md
CHANGED
@@ -4,6 +4,2602 @@ tags:
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4 |
- feature-extraction
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5 |
- sentence-similarity
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6 |
- transformers
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|
7 |
license: mit
|
8 |
language:
|
9 |
- en
|
|
|
4 |
- feature-extraction
|
5 |
- sentence-similarity
|
6 |
- transformers
|
7 |
+
- mteb
|
8 |
+
model-index:
|
9 |
+
- name: bge-small-en-v1.5
|
10 |
+
results:
|
11 |
+
- task:
|
12 |
+
type: Classification
|
13 |
+
dataset:
|
14 |
+
type: mteb/amazon_counterfactual
|
15 |
+
name: MTEB AmazonCounterfactualClassification (en)
|
16 |
+
config: en
|
17 |
+
split: test
|
18 |
+
revision: e8379541af4e31359cca9fbcf4b00f2671dba205
|
19 |
+
metrics:
|
20 |
+
- type: accuracy
|
21 |
+
value: 73.79104477611939
|
22 |
+
- type: ap
|
23 |
+
value: 37.21923821573361
|
24 |
+
- type: f1
|
25 |
+
value: 68.0914945617093
|
26 |
+
- task:
|
27 |
+
type: Classification
|
28 |
+
dataset:
|
29 |
+
type: mteb/amazon_polarity
|
30 |
+
name: MTEB AmazonPolarityClassification
|
31 |
+
config: default
|
32 |
+
split: test
|
33 |
+
revision: e2d317d38cd51312af73b3d32a06d1a08b442046
|
34 |
+
metrics:
|
35 |
+
- type: accuracy
|
36 |
+
value: 92.75377499999999
|
37 |
+
- type: ap
|
38 |
+
value: 89.46766124546022
|
39 |
+
- type: f1
|
40 |
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value: 92.73884001331487
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41 |
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- task:
|
42 |
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type: Classification
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43 |
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dataset:
|
44 |
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type: mteb/amazon_reviews_multi
|
45 |
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name: MTEB AmazonReviewsClassification (en)
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46 |
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config: en
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split: test
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48 |
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revision: 1399c76144fd37290681b995c656ef9b2e06e26d
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50 |
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- type: accuracy
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51 |
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value: 46.986
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52 |
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53 |
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value: 46.55936786727896
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54 |
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- task:
|
55 |
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dataset:
|
57 |
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type: arguana
|
58 |
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name: MTEB ArguAna
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59 |
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config: default
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60 |
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split: test
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61 |
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revision: None
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62 |
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metrics:
|
63 |
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|
64 |
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value: 35.846000000000004
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65 |
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|
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86 |
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value: 0.984
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value: 0.1
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value: 20.389
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value: 98.43499999999999
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value: 99.644
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value: 61.166
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- type: recall_at_5
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value: 72.191
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- task:
|
124 |
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type: Clustering
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125 |
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dataset:
|
126 |
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type: mteb/arxiv-clustering-p2p
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127 |
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name: MTEB ArxivClusteringP2P
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config: default
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split: test
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130 |
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revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
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metrics:
|
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- type: v_measure
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133 |
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value: 47.402770198163594
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134 |
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- task:
|
135 |
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type: Clustering
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dataset:
|
137 |
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type: mteb/arxiv-clustering-s2s
|
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name: MTEB ArxivClusteringS2S
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config: default
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140 |
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split: test
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141 |
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revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
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metrics:
|
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144 |
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value: 40.01545436974177
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145 |
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- task:
|
146 |
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type: Reranking
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147 |
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dataset:
|
148 |
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type: mteb/askubuntudupquestions-reranking
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149 |
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name: MTEB AskUbuntuDupQuestions
|
150 |
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config: default
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151 |
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split: test
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revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
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metrics:
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155 |
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value: 62.586465273207196
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157 |
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|
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|
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name: MTEB BIOSSES
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split: test
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165 |
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revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
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metrics:
|
167 |
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168 |
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value: 85.1891186537969
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- type: cos_sim_spearman
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- type: euclidean_pearson
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- type: euclidean_spearman
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- type: manhattan_pearson
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value: 83.89227298813377
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|
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type: Classification
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181 |
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dataset:
|
182 |
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type: mteb/banking77
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name: MTEB Banking77Classification
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config: default
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split: test
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revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
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metrics:
|
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- type: accuracy
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value: 85.74025974025975
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- type: f1
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191 |
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value: 85.71493566466381
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- task:
|
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type: Clustering
|
194 |
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dataset:
|
195 |
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type: mteb/biorxiv-clustering-p2p
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196 |
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name: MTEB BiorxivClusteringP2P
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config: default
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split: test
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revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
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metrics:
|
201 |
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- type: v_measure
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202 |
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value: 38.467181385006434
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203 |
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- task:
|
204 |
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type: Clustering
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205 |
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dataset:
|
206 |
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type: mteb/biorxiv-clustering-s2s
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207 |
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name: MTEB BiorxivClusteringS2S
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208 |
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config: default
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209 |
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split: test
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revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
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metrics:
|
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213 |
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value: 34.719496037339056
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214 |
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- task:
|
215 |
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216 |
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dataset:
|
217 |
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type: BeIR/cqadupstack
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218 |
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name: MTEB CQADupstackAndroidRetrieval
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219 |
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config: default
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220 |
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split: test
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221 |
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revision: None
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222 |
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metrics:
|
223 |
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224 |
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value: 29.587000000000003
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225 |
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value: 42.661
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value: 39.652
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value: 36.338
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value: 46.763
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value: 47.393
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value: 47.445
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value: 43.538
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value: 47.658
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252 |
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value: 52.824000000000005
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value: 41.989
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258 |
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value: 44.944
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259 |
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260 |
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value: 36.338
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261 |
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262 |
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value: 9.156
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263 |
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value: 1.4789999999999999
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266 |
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value: 0.196
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268 |
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value: 20.076
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269 |
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270 |
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value: 14.85
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271 |
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value: 29.587000000000003
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value: 60.746
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value: 82.157
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value: 95.645
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value: 44.821
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281 |
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- type: recall_at_5
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value: 52.819
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283 |
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- task:
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type: Retrieval
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dataset:
|
286 |
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type: BeIR/cqadupstack
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287 |
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name: MTEB CQADupstackEnglishRetrieval
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288 |
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config: default
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289 |
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split: test
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290 |
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revision: None
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291 |
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metrics:
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292 |
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293 |
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value: 30.239
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294 |
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295 |
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value: 39.989000000000004
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300 |
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302 |
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303 |
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value: 38.833
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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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314 |
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315 |
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316 |
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317 |
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318 |
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319 |
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320 |
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321 |
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322 |
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325 |
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326 |
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327 |
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328 |
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331 |
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value: 8.522
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332 |
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333 |
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value: 1.374
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335 |
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342 |
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value: 55.03
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value: 73.375
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346 |
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350 |
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- type: recall_at_5
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351 |
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value: 48.878
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352 |
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- task:
|
353 |
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type: Retrieval
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354 |
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dataset:
|
355 |
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type: BeIR/cqadupstack
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356 |
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name: MTEB CQADupstackGamingRetrieval
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357 |
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config: default
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358 |
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split: test
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359 |
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revision: None
|
360 |
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metrics:
|
361 |
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362 |
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value: 38.338
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363 |
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364 |
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405 |
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407 |
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421 |
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- task:
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type: BeIR/cqadupstack
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425 |
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name: MTEB CQADupstackGisRetrieval
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metrics:
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value: 25.682
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468 |
+
- type: precision_at_10
|
469 |
+
value: 5.864
|
470 |
+
- type: precision_at_100
|
471 |
+
value: 0.882
|
472 |
+
- type: precision_at_1000
|
473 |
+
value: 0.11
|
474 |
+
- type: precision_at_3
|
475 |
+
value: 13.446
|
476 |
+
- type: precision_at_5
|
477 |
+
value: 9.718
|
478 |
+
- type: recall_at_1
|
479 |
+
value: 25.682
|
480 |
+
- type: recall_at_10
|
481 |
+
value: 51.712
|
482 |
+
- type: recall_at_100
|
483 |
+
value: 74.446
|
484 |
+
- type: recall_at_1000
|
485 |
+
value: 90.472
|
486 |
+
- type: recall_at_3
|
487 |
+
value: 36.236000000000004
|
488 |
+
- type: recall_at_5
|
489 |
+
value: 43.234
|
490 |
+
- task:
|
491 |
+
type: Retrieval
|
492 |
+
dataset:
|
493 |
+
type: BeIR/cqadupstack
|
494 |
+
name: MTEB CQADupstackMathematicaRetrieval
|
495 |
+
config: default
|
496 |
+
split: test
|
497 |
+
revision: None
|
498 |
+
metrics:
|
499 |
+
- type: map_at_1
|
500 |
+
value: 16.073999999999998
|
501 |
+
- type: map_at_10
|
502 |
+
value: 24.352999999999998
|
503 |
+
- type: map_at_100
|
504 |
+
value: 25.438
|
505 |
+
- type: map_at_1000
|
506 |
+
value: 25.545
|
507 |
+
- type: map_at_3
|
508 |
+
value: 21.614
|
509 |
+
- type: map_at_5
|
510 |
+
value: 23.104
|
511 |
+
- type: mrr_at_1
|
512 |
+
value: 19.776
|
513 |
+
- type: mrr_at_10
|
514 |
+
value: 28.837000000000003
|
515 |
+
- type: mrr_at_100
|
516 |
+
value: 29.755
|
517 |
+
- type: mrr_at_1000
|
518 |
+
value: 29.817
|
519 |
+
- type: mrr_at_3
|
520 |
+
value: 26.201999999999998
|
521 |
+
- type: mrr_at_5
|
522 |
+
value: 27.714
|
523 |
+
- type: ndcg_at_1
|
524 |
+
value: 19.776
|
525 |
+
- type: ndcg_at_10
|
526 |
+
value: 29.701
|
527 |
+
- type: ndcg_at_100
|
528 |
+
value: 35.307
|
529 |
+
- type: ndcg_at_1000
|
530 |
+
value: 37.942
|
531 |
+
- type: ndcg_at_3
|
532 |
+
value: 24.764
|
533 |
+
- type: ndcg_at_5
|
534 |
+
value: 27.025
|
535 |
+
- type: precision_at_1
|
536 |
+
value: 19.776
|
537 |
+
- type: precision_at_10
|
538 |
+
value: 5.659
|
539 |
+
- type: precision_at_100
|
540 |
+
value: 0.971
|
541 |
+
- type: precision_at_1000
|
542 |
+
value: 0.133
|
543 |
+
- type: precision_at_3
|
544 |
+
value: 12.065
|
545 |
+
- type: precision_at_5
|
546 |
+
value: 8.905000000000001
|
547 |
+
- type: recall_at_1
|
548 |
+
value: 16.073999999999998
|
549 |
+
- type: recall_at_10
|
550 |
+
value: 41.647
|
551 |
+
- type: recall_at_100
|
552 |
+
value: 66.884
|
553 |
+
- type: recall_at_1000
|
554 |
+
value: 85.91499999999999
|
555 |
+
- type: recall_at_3
|
556 |
+
value: 27.916
|
557 |
+
- type: recall_at_5
|
558 |
+
value: 33.729
|
559 |
+
- task:
|
560 |
+
type: Retrieval
|
561 |
+
dataset:
|
562 |
+
type: BeIR/cqadupstack
|
563 |
+
name: MTEB CQADupstackPhysicsRetrieval
|
564 |
+
config: default
|
565 |
+
split: test
|
566 |
+
revision: None
|
567 |
+
metrics:
|
568 |
+
- type: map_at_1
|
569 |
+
value: 28.444999999999997
|
570 |
+
- type: map_at_10
|
571 |
+
value: 38.218999999999994
|
572 |
+
- type: map_at_100
|
573 |
+
value: 39.595
|
574 |
+
- type: map_at_1000
|
575 |
+
value: 39.709
|
576 |
+
- type: map_at_3
|
577 |
+
value: 35.586
|
578 |
+
- type: map_at_5
|
579 |
+
value: 36.895
|
580 |
+
- type: mrr_at_1
|
581 |
+
value: 34.841
|
582 |
+
- type: mrr_at_10
|
583 |
+
value: 44.106
|
584 |
+
- type: mrr_at_100
|
585 |
+
value: 44.98
|
586 |
+
- type: mrr_at_1000
|
587 |
+
value: 45.03
|
588 |
+
- type: mrr_at_3
|
589 |
+
value: 41.979
|
590 |
+
- type: mrr_at_5
|
591 |
+
value: 43.047999999999995
|
592 |
+
- type: ndcg_at_1
|
593 |
+
value: 34.841
|
594 |
+
- type: ndcg_at_10
|
595 |
+
value: 43.922
|
596 |
+
- type: ndcg_at_100
|
597 |
+
value: 49.504999999999995
|
598 |
+
- type: ndcg_at_1000
|
599 |
+
value: 51.675000000000004
|
600 |
+
- type: ndcg_at_3
|
601 |
+
value: 39.858
|
602 |
+
- type: ndcg_at_5
|
603 |
+
value: 41.408
|
604 |
+
- type: precision_at_1
|
605 |
+
value: 34.841
|
606 |
+
- type: precision_at_10
|
607 |
+
value: 7.872999999999999
|
608 |
+
- type: precision_at_100
|
609 |
+
value: 1.2449999999999999
|
610 |
+
- type: precision_at_1000
|
611 |
+
value: 0.161
|
612 |
+
- type: precision_at_3
|
613 |
+
value: 18.993
|
614 |
+
- type: precision_at_5
|
615 |
+
value: 13.032
|
616 |
+
- type: recall_at_1
|
617 |
+
value: 28.444999999999997
|
618 |
+
- type: recall_at_10
|
619 |
+
value: 54.984
|
620 |
+
- type: recall_at_100
|
621 |
+
value: 78.342
|
622 |
+
- type: recall_at_1000
|
623 |
+
value: 92.77
|
624 |
+
- type: recall_at_3
|
625 |
+
value: 42.842999999999996
|
626 |
+
- type: recall_at_5
|
627 |
+
value: 47.247
|
628 |
+
- task:
|
629 |
+
type: Retrieval
|
630 |
+
dataset:
|
631 |
+
type: BeIR/cqadupstack
|
632 |
+
name: MTEB CQADupstackProgrammersRetrieval
|
633 |
+
config: default
|
634 |
+
split: test
|
635 |
+
revision: None
|
636 |
+
metrics:
|
637 |
+
- type: map_at_1
|
638 |
+
value: 23.072
|
639 |
+
- type: map_at_10
|
640 |
+
value: 32.354
|
641 |
+
- type: map_at_100
|
642 |
+
value: 33.800000000000004
|
643 |
+
- type: map_at_1000
|
644 |
+
value: 33.908
|
645 |
+
- type: map_at_3
|
646 |
+
value: 29.232000000000003
|
647 |
+
- type: map_at_5
|
648 |
+
value: 31.049
|
649 |
+
- type: mrr_at_1
|
650 |
+
value: 29.110000000000003
|
651 |
+
- type: mrr_at_10
|
652 |
+
value: 38.03
|
653 |
+
- type: mrr_at_100
|
654 |
+
value: 39.032
|
655 |
+
- type: mrr_at_1000
|
656 |
+
value: 39.086999999999996
|
657 |
+
- type: mrr_at_3
|
658 |
+
value: 35.407
|
659 |
+
- type: mrr_at_5
|
660 |
+
value: 36.76
|
661 |
+
- type: ndcg_at_1
|
662 |
+
value: 29.110000000000003
|
663 |
+
- type: ndcg_at_10
|
664 |
+
value: 38.231
|
665 |
+
- type: ndcg_at_100
|
666 |
+
value: 44.425
|
667 |
+
- type: ndcg_at_1000
|
668 |
+
value: 46.771
|
669 |
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- type: ndcg_at_3
|
670 |
+
value: 33.095
|
671 |
+
- type: ndcg_at_5
|
672 |
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value: 35.459
|
673 |
+
- type: precision_at_1
|
674 |
+
value: 29.110000000000003
|
675 |
+
- type: precision_at_10
|
676 |
+
value: 7.215000000000001
|
677 |
+
- type: precision_at_100
|
678 |
+
value: 1.2109999999999999
|
679 |
+
- type: precision_at_1000
|
680 |
+
value: 0.157
|
681 |
+
- type: precision_at_3
|
682 |
+
value: 16.058
|
683 |
+
- type: precision_at_5
|
684 |
+
value: 11.644
|
685 |
+
- type: recall_at_1
|
686 |
+
value: 23.072
|
687 |
+
- type: recall_at_10
|
688 |
+
value: 50.285999999999994
|
689 |
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- type: recall_at_100
|
690 |
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value: 76.596
|
691 |
+
- type: recall_at_1000
|
692 |
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value: 92.861
|
693 |
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- type: recall_at_3
|
694 |
+
value: 35.702
|
695 |
+
- type: recall_at_5
|
696 |
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value: 42.152
|
697 |
+
- task:
|
698 |
+
type: Retrieval
|
699 |
+
dataset:
|
700 |
+
type: BeIR/cqadupstack
|
701 |
+
name: MTEB CQADupstackRetrieval
|
702 |
+
config: default
|
703 |
+
split: test
|
704 |
+
revision: None
|
705 |
+
metrics:
|
706 |
+
- type: map_at_1
|
707 |
+
value: 24.937916666666666
|
708 |
+
- type: map_at_10
|
709 |
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value: 33.755250000000004
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710 |
+
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|
711 |
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value: 34.955999999999996
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712 |
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|
713 |
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value: 35.070499999999996
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714 |
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|
715 |
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value: 30.98708333333333
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716 |
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|
717 |
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value: 32.51491666666666
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718 |
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|
719 |
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value: 29.48708333333333
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720 |
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|
721 |
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value: 37.92183333333334
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722 |
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|
723 |
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value: 38.76583333333333
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724 |
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|
725 |
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value: 38.82466666666667
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726 |
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|
727 |
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value: 35.45125
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728 |
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|
729 |
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value: 36.827000000000005
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730 |
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|
731 |
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value: 29.48708333333333
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732 |
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|
733 |
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value: 39.05225
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734 |
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|
735 |
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value: 44.25983333333334
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736 |
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|
737 |
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value: 46.568333333333335
|
738 |
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|
739 |
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value: 34.271583333333325
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740 |
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|
741 |
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value: 36.483916666666666
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742 |
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|
743 |
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value: 29.48708333333333
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744 |
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|
745 |
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value: 6.865749999999999
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746 |
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|
747 |
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value: 1.1195833333333332
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748 |
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|
749 |
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value: 0.15058333333333335
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750 |
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|
751 |
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value: 15.742083333333333
|
752 |
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|
753 |
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value: 11.221916666666667
|
754 |
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- type: recall_at_1
|
755 |
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value: 24.937916666666666
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756 |
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- type: recall_at_10
|
757 |
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value: 50.650416666666665
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758 |
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|
759 |
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value: 73.55383333333334
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760 |
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|
761 |
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value: 89.61691666666667
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762 |
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|
763 |
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value: 37.27808333333334
|
764 |
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- type: recall_at_5
|
765 |
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value: 42.99475
|
766 |
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- task:
|
767 |
+
type: Retrieval
|
768 |
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dataset:
|
769 |
+
type: BeIR/cqadupstack
|
770 |
+
name: MTEB CQADupstackStatsRetrieval
|
771 |
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config: default
|
772 |
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split: test
|
773 |
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revision: None
|
774 |
+
metrics:
|
775 |
+
- type: map_at_1
|
776 |
+
value: 23.947
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777 |
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|
778 |
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value: 30.575000000000003
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779 |
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|
780 |
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value: 31.465
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781 |
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782 |
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value: 31.558000000000003
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783 |
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|
784 |
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value: 28.814
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785 |
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|
786 |
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787 |
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788 |
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value: 26.994
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789 |
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790 |
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value: 33.415
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791 |
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|
792 |
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value: 34.18
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793 |
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|
794 |
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value: 34.245
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795 |
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|
796 |
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value: 31.621
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797 |
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|
798 |
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value: 32.549
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799 |
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|
800 |
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value: 26.994
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801 |
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|
802 |
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value: 34.482
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803 |
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|
804 |
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value: 38.915
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805 |
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|
806 |
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value: 41.355
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807 |
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|
808 |
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value: 31.139
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809 |
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|
810 |
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value: 32.589
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811 |
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|
812 |
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value: 26.994
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813 |
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|
814 |
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value: 5.322
|
815 |
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|
816 |
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value: 0.8160000000000001
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817 |
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|
818 |
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value: 0.11100000000000002
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819 |
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|
820 |
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value: 13.344000000000001
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821 |
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|
822 |
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value: 8.988
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823 |
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|
824 |
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value: 23.947
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825 |
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|
826 |
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value: 43.647999999999996
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827 |
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828 |
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value: 63.851
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829 |
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830 |
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value: 82.0
|
831 |
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|
832 |
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value: 34.288000000000004
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833 |
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- type: recall_at_5
|
834 |
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value: 38.117000000000004
|
835 |
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- task:
|
836 |
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type: Retrieval
|
837 |
+
dataset:
|
838 |
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type: BeIR/cqadupstack
|
839 |
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name: MTEB CQADupstackTexRetrieval
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840 |
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config: default
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841 |
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split: test
|
842 |
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revision: None
|
843 |
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metrics:
|
844 |
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- type: map_at_1
|
845 |
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value: 16.197
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846 |
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|
847 |
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value: 22.968
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848 |
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849 |
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850 |
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851 |
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852 |
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853 |
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854 |
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|
855 |
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856 |
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857 |
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858 |
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859 |
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value: 26.55
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860 |
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861 |
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862 |
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863 |
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864 |
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865 |
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value: 24.421
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866 |
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867 |
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value: 25.604
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868 |
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869 |
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870 |
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871 |
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872 |
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873 |
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value: 32.828
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874 |
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875 |
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value: 35.739
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876 |
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877 |
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value: 23.405
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878 |
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879 |
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value: 25.255
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880 |
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881 |
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value: 19.511
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882 |
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|
883 |
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value: 5.017
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884 |
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|
885 |
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value: 0.91
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886 |
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|
887 |
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value: 0.133
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888 |
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|
889 |
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value: 11.023
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890 |
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|
891 |
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value: 8.025
|
892 |
+
- type: recall_at_1
|
893 |
+
value: 16.197
|
894 |
+
- type: recall_at_10
|
895 |
+
value: 37.09
|
896 |
+
- type: recall_at_100
|
897 |
+
value: 61.778
|
898 |
+
- type: recall_at_1000
|
899 |
+
value: 82.56599999999999
|
900 |
+
- type: recall_at_3
|
901 |
+
value: 26.034000000000002
|
902 |
+
- type: recall_at_5
|
903 |
+
value: 30.762
|
904 |
+
- task:
|
905 |
+
type: Retrieval
|
906 |
+
dataset:
|
907 |
+
type: BeIR/cqadupstack
|
908 |
+
name: MTEB CQADupstackUnixRetrieval
|
909 |
+
config: default
|
910 |
+
split: test
|
911 |
+
revision: None
|
912 |
+
metrics:
|
913 |
+
- type: map_at_1
|
914 |
+
value: 25.41
|
915 |
+
- type: map_at_10
|
916 |
+
value: 33.655
|
917 |
+
- type: map_at_100
|
918 |
+
value: 34.892
|
919 |
+
- type: map_at_1000
|
920 |
+
value: 34.995
|
921 |
+
- type: map_at_3
|
922 |
+
value: 30.94
|
923 |
+
- type: map_at_5
|
924 |
+
value: 32.303
|
925 |
+
- type: mrr_at_1
|
926 |
+
value: 29.477999999999998
|
927 |
+
- type: mrr_at_10
|
928 |
+
value: 37.443
|
929 |
+
- type: mrr_at_100
|
930 |
+
value: 38.383
|
931 |
+
- type: mrr_at_1000
|
932 |
+
value: 38.440000000000005
|
933 |
+
- type: mrr_at_3
|
934 |
+
value: 34.949999999999996
|
935 |
+
- type: mrr_at_5
|
936 |
+
value: 36.228
|
937 |
+
- type: ndcg_at_1
|
938 |
+
value: 29.477999999999998
|
939 |
+
- type: ndcg_at_10
|
940 |
+
value: 38.769
|
941 |
+
- type: ndcg_at_100
|
942 |
+
value: 44.245000000000005
|
943 |
+
- type: ndcg_at_1000
|
944 |
+
value: 46.593
|
945 |
+
- type: ndcg_at_3
|
946 |
+
value: 33.623
|
947 |
+
- type: ndcg_at_5
|
948 |
+
value: 35.766
|
949 |
+
- type: precision_at_1
|
950 |
+
value: 29.477999999999998
|
951 |
+
- type: precision_at_10
|
952 |
+
value: 6.455
|
953 |
+
- type: precision_at_100
|
954 |
+
value: 1.032
|
955 |
+
- type: precision_at_1000
|
956 |
+
value: 0.135
|
957 |
+
- type: precision_at_3
|
958 |
+
value: 14.893999999999998
|
959 |
+
- type: precision_at_5
|
960 |
+
value: 10.485
|
961 |
+
- type: recall_at_1
|
962 |
+
value: 25.41
|
963 |
+
- type: recall_at_10
|
964 |
+
value: 50.669
|
965 |
+
- type: recall_at_100
|
966 |
+
value: 74.084
|
967 |
+
- type: recall_at_1000
|
968 |
+
value: 90.435
|
969 |
+
- type: recall_at_3
|
970 |
+
value: 36.679
|
971 |
+
- type: recall_at_5
|
972 |
+
value: 41.94
|
973 |
+
- task:
|
974 |
+
type: Retrieval
|
975 |
+
dataset:
|
976 |
+
type: BeIR/cqadupstack
|
977 |
+
name: MTEB CQADupstackWebmastersRetrieval
|
978 |
+
config: default
|
979 |
+
split: test
|
980 |
+
revision: None
|
981 |
+
metrics:
|
982 |
+
- type: map_at_1
|
983 |
+
value: 23.339
|
984 |
+
- type: map_at_10
|
985 |
+
value: 31.852000000000004
|
986 |
+
- type: map_at_100
|
987 |
+
value: 33.411
|
988 |
+
- type: map_at_1000
|
989 |
+
value: 33.62
|
990 |
+
- type: map_at_3
|
991 |
+
value: 28.929
|
992 |
+
- type: map_at_5
|
993 |
+
value: 30.542
|
994 |
+
- type: mrr_at_1
|
995 |
+
value: 28.063
|
996 |
+
- type: mrr_at_10
|
997 |
+
value: 36.301
|
998 |
+
- type: mrr_at_100
|
999 |
+
value: 37.288
|
1000 |
+
- type: mrr_at_1000
|
1001 |
+
value: 37.349
|
1002 |
+
- type: mrr_at_3
|
1003 |
+
value: 33.663
|
1004 |
+
- type: mrr_at_5
|
1005 |
+
value: 35.165
|
1006 |
+
- type: ndcg_at_1
|
1007 |
+
value: 28.063
|
1008 |
+
- type: ndcg_at_10
|
1009 |
+
value: 37.462
|
1010 |
+
- type: ndcg_at_100
|
1011 |
+
value: 43.620999999999995
|
1012 |
+
- type: ndcg_at_1000
|
1013 |
+
value: 46.211
|
1014 |
+
- type: ndcg_at_3
|
1015 |
+
value: 32.68
|
1016 |
+
- type: ndcg_at_5
|
1017 |
+
value: 34.981
|
1018 |
+
- type: precision_at_1
|
1019 |
+
value: 28.063
|
1020 |
+
- type: precision_at_10
|
1021 |
+
value: 7.1739999999999995
|
1022 |
+
- type: precision_at_100
|
1023 |
+
value: 1.486
|
1024 |
+
- type: precision_at_1000
|
1025 |
+
value: 0.23500000000000001
|
1026 |
+
- type: precision_at_3
|
1027 |
+
value: 15.217
|
1028 |
+
- type: precision_at_5
|
1029 |
+
value: 11.265
|
1030 |
+
- type: recall_at_1
|
1031 |
+
value: 23.339
|
1032 |
+
- type: recall_at_10
|
1033 |
+
value: 48.376999999999995
|
1034 |
+
- type: recall_at_100
|
1035 |
+
value: 76.053
|
1036 |
+
- type: recall_at_1000
|
1037 |
+
value: 92.455
|
1038 |
+
- type: recall_at_3
|
1039 |
+
value: 34.735
|
1040 |
+
- type: recall_at_5
|
1041 |
+
value: 40.71
|
1042 |
+
- task:
|
1043 |
+
type: Retrieval
|
1044 |
+
dataset:
|
1045 |
+
type: BeIR/cqadupstack
|
1046 |
+
name: MTEB CQADupstackWordpressRetrieval
|
1047 |
+
config: default
|
1048 |
+
split: test
|
1049 |
+
revision: None
|
1050 |
+
metrics:
|
1051 |
+
- type: map_at_1
|
1052 |
+
value: 18.925
|
1053 |
+
- type: map_at_10
|
1054 |
+
value: 26.017000000000003
|
1055 |
+
- type: map_at_100
|
1056 |
+
value: 27.034000000000002
|
1057 |
+
- type: map_at_1000
|
1058 |
+
value: 27.156000000000002
|
1059 |
+
- type: map_at_3
|
1060 |
+
value: 23.604
|
1061 |
+
- type: map_at_5
|
1062 |
+
value: 24.75
|
1063 |
+
- type: mrr_at_1
|
1064 |
+
value: 20.333000000000002
|
1065 |
+
- type: mrr_at_10
|
1066 |
+
value: 27.915
|
1067 |
+
- type: mrr_at_100
|
1068 |
+
value: 28.788000000000004
|
1069 |
+
- type: mrr_at_1000
|
1070 |
+
value: 28.877999999999997
|
1071 |
+
- type: mrr_at_3
|
1072 |
+
value: 25.446999999999996
|
1073 |
+
- type: mrr_at_5
|
1074 |
+
value: 26.648
|
1075 |
+
- type: ndcg_at_1
|
1076 |
+
value: 20.333000000000002
|
1077 |
+
- type: ndcg_at_10
|
1078 |
+
value: 30.673000000000002
|
1079 |
+
- type: ndcg_at_100
|
1080 |
+
value: 35.618
|
1081 |
+
- type: ndcg_at_1000
|
1082 |
+
value: 38.517
|
1083 |
+
- type: ndcg_at_3
|
1084 |
+
value: 25.71
|
1085 |
+
- type: ndcg_at_5
|
1086 |
+
value: 27.679
|
1087 |
+
- type: precision_at_1
|
1088 |
+
value: 20.333000000000002
|
1089 |
+
- type: precision_at_10
|
1090 |
+
value: 4.9910000000000005
|
1091 |
+
- type: precision_at_100
|
1092 |
+
value: 0.8130000000000001
|
1093 |
+
- type: precision_at_1000
|
1094 |
+
value: 0.117
|
1095 |
+
- type: precision_at_3
|
1096 |
+
value: 11.029
|
1097 |
+
- type: precision_at_5
|
1098 |
+
value: 7.8740000000000006
|
1099 |
+
- type: recall_at_1
|
1100 |
+
value: 18.925
|
1101 |
+
- type: recall_at_10
|
1102 |
+
value: 43.311
|
1103 |
+
- type: recall_at_100
|
1104 |
+
value: 66.308
|
1105 |
+
- type: recall_at_1000
|
1106 |
+
value: 87.49
|
1107 |
+
- type: recall_at_3
|
1108 |
+
value: 29.596
|
1109 |
+
- type: recall_at_5
|
1110 |
+
value: 34.245
|
1111 |
+
- task:
|
1112 |
+
type: Retrieval
|
1113 |
+
dataset:
|
1114 |
+
type: climate-fever
|
1115 |
+
name: MTEB ClimateFEVER
|
1116 |
+
config: default
|
1117 |
+
split: test
|
1118 |
+
revision: None
|
1119 |
+
metrics:
|
1120 |
+
- type: map_at_1
|
1121 |
+
value: 13.714
|
1122 |
+
- type: map_at_10
|
1123 |
+
value: 23.194
|
1124 |
+
- type: map_at_100
|
1125 |
+
value: 24.976000000000003
|
1126 |
+
- type: map_at_1000
|
1127 |
+
value: 25.166
|
1128 |
+
- type: map_at_3
|
1129 |
+
value: 19.709
|
1130 |
+
- type: map_at_5
|
1131 |
+
value: 21.523999999999997
|
1132 |
+
- type: mrr_at_1
|
1133 |
+
value: 30.619000000000003
|
1134 |
+
- type: mrr_at_10
|
1135 |
+
value: 42.563
|
1136 |
+
- type: mrr_at_100
|
1137 |
+
value: 43.386
|
1138 |
+
- type: mrr_at_1000
|
1139 |
+
value: 43.423
|
1140 |
+
- type: mrr_at_3
|
1141 |
+
value: 39.555
|
1142 |
+
- type: mrr_at_5
|
1143 |
+
value: 41.268
|
1144 |
+
- type: ndcg_at_1
|
1145 |
+
value: 30.619000000000003
|
1146 |
+
- type: ndcg_at_10
|
1147 |
+
value: 31.836
|
1148 |
+
- type: ndcg_at_100
|
1149 |
+
value: 38.652
|
1150 |
+
- type: ndcg_at_1000
|
1151 |
+
value: 42.088
|
1152 |
+
- type: ndcg_at_3
|
1153 |
+
value: 26.733
|
1154 |
+
- type: ndcg_at_5
|
1155 |
+
value: 28.435
|
1156 |
+
- type: precision_at_1
|
1157 |
+
value: 30.619000000000003
|
1158 |
+
- type: precision_at_10
|
1159 |
+
value: 9.751999999999999
|
1160 |
+
- type: precision_at_100
|
1161 |
+
value: 1.71
|
1162 |
+
- type: precision_at_1000
|
1163 |
+
value: 0.23500000000000001
|
1164 |
+
- type: precision_at_3
|
1165 |
+
value: 19.935
|
1166 |
+
- type: precision_at_5
|
1167 |
+
value: 14.984
|
1168 |
+
- type: recall_at_1
|
1169 |
+
value: 13.714
|
1170 |
+
- type: recall_at_10
|
1171 |
+
value: 37.26
|
1172 |
+
- type: recall_at_100
|
1173 |
+
value: 60.546
|
1174 |
+
- type: recall_at_1000
|
1175 |
+
value: 79.899
|
1176 |
+
- type: recall_at_3
|
1177 |
+
value: 24.325
|
1178 |
+
- type: recall_at_5
|
1179 |
+
value: 29.725
|
1180 |
+
- task:
|
1181 |
+
type: Retrieval
|
1182 |
+
dataset:
|
1183 |
+
type: dbpedia-entity
|
1184 |
+
name: MTEB DBPedia
|
1185 |
+
config: default
|
1186 |
+
split: test
|
1187 |
+
revision: None
|
1188 |
+
metrics:
|
1189 |
+
- type: map_at_1
|
1190 |
+
value: 8.462
|
1191 |
+
- type: map_at_10
|
1192 |
+
value: 18.637
|
1193 |
+
- type: map_at_100
|
1194 |
+
value: 26.131999999999998
|
1195 |
+
- type: map_at_1000
|
1196 |
+
value: 27.607
|
1197 |
+
- type: map_at_3
|
1198 |
+
value: 13.333
|
1199 |
+
- type: map_at_5
|
1200 |
+
value: 15.654000000000002
|
1201 |
+
- type: mrr_at_1
|
1202 |
+
value: 66.25
|
1203 |
+
- type: mrr_at_10
|
1204 |
+
value: 74.32600000000001
|
1205 |
+
- type: mrr_at_100
|
1206 |
+
value: 74.60900000000001
|
1207 |
+
- type: mrr_at_1000
|
1208 |
+
value: 74.62
|
1209 |
+
- type: mrr_at_3
|
1210 |
+
value: 72.667
|
1211 |
+
- type: mrr_at_5
|
1212 |
+
value: 73.817
|
1213 |
+
- type: ndcg_at_1
|
1214 |
+
value: 53.87499999999999
|
1215 |
+
- type: ndcg_at_10
|
1216 |
+
value: 40.028999999999996
|
1217 |
+
- type: ndcg_at_100
|
1218 |
+
value: 44.199
|
1219 |
+
- type: ndcg_at_1000
|
1220 |
+
value: 51.629999999999995
|
1221 |
+
- type: ndcg_at_3
|
1222 |
+
value: 44.113
|
1223 |
+
- type: ndcg_at_5
|
1224 |
+
value: 41.731
|
1225 |
+
- type: precision_at_1
|
1226 |
+
value: 66.25
|
1227 |
+
- type: precision_at_10
|
1228 |
+
value: 31.900000000000002
|
1229 |
+
- type: precision_at_100
|
1230 |
+
value: 10.043000000000001
|
1231 |
+
- type: precision_at_1000
|
1232 |
+
value: 1.926
|
1233 |
+
- type: precision_at_3
|
1234 |
+
value: 47.417
|
1235 |
+
- type: precision_at_5
|
1236 |
+
value: 40.65
|
1237 |
+
- type: recall_at_1
|
1238 |
+
value: 8.462
|
1239 |
+
- type: recall_at_10
|
1240 |
+
value: 24.293
|
1241 |
+
- type: recall_at_100
|
1242 |
+
value: 50.146
|
1243 |
+
- type: recall_at_1000
|
1244 |
+
value: 74.034
|
1245 |
+
- type: recall_at_3
|
1246 |
+
value: 14.967
|
1247 |
+
- type: recall_at_5
|
1248 |
+
value: 18.682000000000002
|
1249 |
+
- task:
|
1250 |
+
type: Classification
|
1251 |
+
dataset:
|
1252 |
+
type: mteb/emotion
|
1253 |
+
name: MTEB EmotionClassification
|
1254 |
+
config: default
|
1255 |
+
split: test
|
1256 |
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revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
|
1257 |
+
metrics:
|
1258 |
+
- type: accuracy
|
1259 |
+
value: 47.84499999999999
|
1260 |
+
- type: f1
|
1261 |
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value: 42.48106691979349
|
1262 |
+
- task:
|
1263 |
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type: Retrieval
|
1264 |
+
dataset:
|
1265 |
+
type: fever
|
1266 |
+
name: MTEB FEVER
|
1267 |
+
config: default
|
1268 |
+
split: test
|
1269 |
+
revision: None
|
1270 |
+
metrics:
|
1271 |
+
- type: map_at_1
|
1272 |
+
value: 74.034
|
1273 |
+
- type: map_at_10
|
1274 |
+
value: 82.76
|
1275 |
+
- type: map_at_100
|
1276 |
+
value: 82.968
|
1277 |
+
- type: map_at_1000
|
1278 |
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value: 82.98299999999999
|
1279 |
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- type: map_at_3
|
1280 |
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value: 81.768
|
1281 |
+
- type: map_at_5
|
1282 |
+
value: 82.418
|
1283 |
+
- type: mrr_at_1
|
1284 |
+
value: 80.048
|
1285 |
+
- type: mrr_at_10
|
1286 |
+
value: 87.64999999999999
|
1287 |
+
- type: mrr_at_100
|
1288 |
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value: 87.712
|
1289 |
+
- type: mrr_at_1000
|
1290 |
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value: 87.713
|
1291 |
+
- type: mrr_at_3
|
1292 |
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value: 87.01100000000001
|
1293 |
+
- type: mrr_at_5
|
1294 |
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value: 87.466
|
1295 |
+
- type: ndcg_at_1
|
1296 |
+
value: 80.048
|
1297 |
+
- type: ndcg_at_10
|
1298 |
+
value: 86.643
|
1299 |
+
- type: ndcg_at_100
|
1300 |
+
value: 87.361
|
1301 |
+
- type: ndcg_at_1000
|
1302 |
+
value: 87.606
|
1303 |
+
- type: ndcg_at_3
|
1304 |
+
value: 85.137
|
1305 |
+
- type: ndcg_at_5
|
1306 |
+
value: 86.016
|
1307 |
+
- type: precision_at_1
|
1308 |
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value: 80.048
|
1309 |
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- type: precision_at_10
|
1310 |
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value: 10.372
|
1311 |
+
- type: precision_at_100
|
1312 |
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value: 1.093
|
1313 |
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- type: precision_at_1000
|
1314 |
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value: 0.11299999999999999
|
1315 |
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- type: precision_at_3
|
1316 |
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value: 32.638
|
1317 |
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- type: precision_at_5
|
1318 |
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value: 20.177
|
1319 |
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- type: recall_at_1
|
1320 |
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value: 74.034
|
1321 |
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- type: recall_at_10
|
1322 |
+
value: 93.769
|
1323 |
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- type: recall_at_100
|
1324 |
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value: 96.569
|
1325 |
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- type: recall_at_1000
|
1326 |
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value: 98.039
|
1327 |
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- type: recall_at_3
|
1328 |
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value: 89.581
|
1329 |
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- type: recall_at_5
|
1330 |
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value: 91.906
|
1331 |
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- task:
|
1332 |
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type: Retrieval
|
1333 |
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dataset:
|
1334 |
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type: fiqa
|
1335 |
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name: MTEB FiQA2018
|
1336 |
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config: default
|
1337 |
+
split: test
|
1338 |
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revision: None
|
1339 |
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metrics:
|
1340 |
+
- type: map_at_1
|
1341 |
+
value: 20.5
|
1342 |
+
- type: map_at_10
|
1343 |
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value: 32.857
|
1344 |
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- type: map_at_100
|
1345 |
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value: 34.589
|
1346 |
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- type: map_at_1000
|
1347 |
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value: 34.778
|
1348 |
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- type: map_at_3
|
1349 |
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value: 29.160999999999998
|
1350 |
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- type: map_at_5
|
1351 |
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value: 31.033
|
1352 |
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- type: mrr_at_1
|
1353 |
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value: 40.123
|
1354 |
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- type: mrr_at_10
|
1355 |
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value: 48.776
|
1356 |
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- type: mrr_at_100
|
1357 |
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value: 49.495
|
1358 |
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- type: mrr_at_1000
|
1359 |
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value: 49.539
|
1360 |
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- type: mrr_at_3
|
1361 |
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value: 46.605000000000004
|
1362 |
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- type: mrr_at_5
|
1363 |
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value: 47.654
|
1364 |
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- type: ndcg_at_1
|
1365 |
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value: 40.123
|
1366 |
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- type: ndcg_at_10
|
1367 |
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value: 40.343
|
1368 |
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- type: ndcg_at_100
|
1369 |
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value: 46.56
|
1370 |
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- type: ndcg_at_1000
|
1371 |
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value: 49.777
|
1372 |
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- type: ndcg_at_3
|
1373 |
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value: 37.322
|
1374 |
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- type: ndcg_at_5
|
1375 |
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value: 37.791000000000004
|
1376 |
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- type: precision_at_1
|
1377 |
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value: 40.123
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1378 |
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- type: precision_at_10
|
1379 |
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value: 11.08
|
1380 |
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- type: precision_at_100
|
1381 |
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value: 1.752
|
1382 |
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- type: precision_at_1000
|
1383 |
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value: 0.232
|
1384 |
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- type: precision_at_3
|
1385 |
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value: 24.897
|
1386 |
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- type: precision_at_5
|
1387 |
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value: 17.809
|
1388 |
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- type: recall_at_1
|
1389 |
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value: 20.5
|
1390 |
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- type: recall_at_10
|
1391 |
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value: 46.388
|
1392 |
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- type: recall_at_100
|
1393 |
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value: 69.552
|
1394 |
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- type: recall_at_1000
|
1395 |
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value: 89.011
|
1396 |
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- type: recall_at_3
|
1397 |
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value: 33.617999999999995
|
1398 |
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- type: recall_at_5
|
1399 |
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value: 38.211
|
1400 |
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- task:
|
1401 |
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type: Retrieval
|
1402 |
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dataset:
|
1403 |
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type: hotpotqa
|
1404 |
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name: MTEB HotpotQA
|
1405 |
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config: default
|
1406 |
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split: test
|
1407 |
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revision: None
|
1408 |
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metrics:
|
1409 |
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- type: map_at_1
|
1410 |
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value: 39.135999999999996
|
1411 |
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- type: map_at_10
|
1412 |
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value: 61.673
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1413 |
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1414 |
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value: 62.562
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1415 |
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1416 |
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value: 62.62
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1417 |
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1418 |
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value: 58.467999999999996
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1419 |
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|
1420 |
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value: 60.463
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1421 |
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|
1422 |
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value: 78.271
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1423 |
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|
1424 |
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value: 84.119
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1425 |
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|
1426 |
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value: 84.29299999999999
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1427 |
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1428 |
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value: 84.299
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1429 |
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1430 |
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value: 83.18900000000001
|
1431 |
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|
1432 |
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value: 83.786
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1433 |
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- type: ndcg_at_1
|
1434 |
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value: 78.271
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1435 |
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|
1436 |
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value: 69.935
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1437 |
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- type: ndcg_at_100
|
1438 |
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value: 73.01299999999999
|
1439 |
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- type: ndcg_at_1000
|
1440 |
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value: 74.126
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1441 |
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- type: ndcg_at_3
|
1442 |
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value: 65.388
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1443 |
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- type: ndcg_at_5
|
1444 |
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value: 67.906
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1445 |
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- type: precision_at_1
|
1446 |
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value: 78.271
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1447 |
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- type: precision_at_10
|
1448 |
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value: 14.562
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1449 |
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- type: precision_at_100
|
1450 |
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value: 1.6969999999999998
|
1451 |
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- type: precision_at_1000
|
1452 |
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value: 0.184
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1453 |
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- type: precision_at_3
|
1454 |
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value: 41.841
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1455 |
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- type: precision_at_5
|
1456 |
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value: 27.087
|
1457 |
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- type: recall_at_1
|
1458 |
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value: 39.135999999999996
|
1459 |
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- type: recall_at_10
|
1460 |
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value: 72.809
|
1461 |
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- type: recall_at_100
|
1462 |
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value: 84.86200000000001
|
1463 |
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- type: recall_at_1000
|
1464 |
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value: 92.208
|
1465 |
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- type: recall_at_3
|
1466 |
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value: 62.76199999999999
|
1467 |
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- type: recall_at_5
|
1468 |
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value: 67.718
|
1469 |
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- task:
|
1470 |
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type: Classification
|
1471 |
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dataset:
|
1472 |
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type: mteb/imdb
|
1473 |
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name: MTEB ImdbClassification
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1474 |
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config: default
|
1475 |
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split: test
|
1476 |
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revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
|
1477 |
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metrics:
|
1478 |
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- type: accuracy
|
1479 |
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value: 90.60600000000001
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1480 |
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- type: ap
|
1481 |
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value: 86.6579587804335
|
1482 |
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- type: f1
|
1483 |
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value: 90.5938853929307
|
1484 |
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- task:
|
1485 |
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type: Retrieval
|
1486 |
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dataset:
|
1487 |
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type: msmarco
|
1488 |
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name: MTEB MSMARCO
|
1489 |
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config: default
|
1490 |
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split: dev
|
1491 |
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revision: None
|
1492 |
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metrics:
|
1493 |
+
- type: map_at_1
|
1494 |
+
value: 21.852
|
1495 |
+
- type: map_at_10
|
1496 |
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value: 33.982
|
1497 |
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- type: map_at_100
|
1498 |
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value: 35.116
|
1499 |
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- type: map_at_1000
|
1500 |
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value: 35.167
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1501 |
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- type: map_at_3
|
1502 |
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value: 30.134
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1503 |
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- type: map_at_5
|
1504 |
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value: 32.340999999999994
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1505 |
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- type: mrr_at_1
|
1506 |
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value: 22.479
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1507 |
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- type: mrr_at_10
|
1508 |
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value: 34.594
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1509 |
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- type: mrr_at_100
|
1510 |
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value: 35.672
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1511 |
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- type: mrr_at_1000
|
1512 |
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value: 35.716
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1513 |
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- type: mrr_at_3
|
1514 |
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value: 30.84
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1515 |
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- type: mrr_at_5
|
1516 |
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value: 32.998
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1517 |
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- type: ndcg_at_1
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1518 |
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value: 22.493
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1519 |
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- type: ndcg_at_10
|
1520 |
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value: 40.833000000000006
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1521 |
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- type: ndcg_at_100
|
1522 |
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value: 46.357
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1523 |
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- type: ndcg_at_1000
|
1524 |
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value: 47.637
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1525 |
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- type: ndcg_at_3
|
1526 |
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value: 32.995999999999995
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1527 |
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- type: ndcg_at_5
|
1528 |
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value: 36.919000000000004
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1529 |
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- type: precision_at_1
|
1530 |
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value: 22.493
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1531 |
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- type: precision_at_10
|
1532 |
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value: 6.465999999999999
|
1533 |
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- type: precision_at_100
|
1534 |
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value: 0.9249999999999999
|
1535 |
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- type: precision_at_1000
|
1536 |
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value: 0.104
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1537 |
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- type: precision_at_3
|
1538 |
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value: 14.030999999999999
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1539 |
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- type: precision_at_5
|
1540 |
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value: 10.413
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1541 |
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- type: recall_at_1
|
1542 |
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value: 21.852
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1543 |
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- type: recall_at_10
|
1544 |
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value: 61.934999999999995
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1545 |
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- type: recall_at_100
|
1546 |
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value: 87.611
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1547 |
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- type: recall_at_1000
|
1548 |
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value: 97.441
|
1549 |
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- type: recall_at_3
|
1550 |
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value: 40.583999999999996
|
1551 |
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- type: recall_at_5
|
1552 |
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value: 49.992999999999995
|
1553 |
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- task:
|
1554 |
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type: Classification
|
1555 |
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dataset:
|
1556 |
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type: mteb/mtop_domain
|
1557 |
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name: MTEB MTOPDomainClassification (en)
|
1558 |
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config: en
|
1559 |
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split: test
|
1560 |
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revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
|
1561 |
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metrics:
|
1562 |
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- type: accuracy
|
1563 |
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value: 93.36069311445507
|
1564 |
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- type: f1
|
1565 |
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value: 93.16456330371453
|
1566 |
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- task:
|
1567 |
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type: Classification
|
1568 |
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dataset:
|
1569 |
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type: mteb/mtop_intent
|
1570 |
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name: MTEB MTOPIntentClassification (en)
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1571 |
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config: en
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1572 |
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split: test
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1573 |
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revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
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1574 |
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metrics:
|
1575 |
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- type: accuracy
|
1576 |
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value: 74.74692202462381
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1577 |
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- type: f1
|
1578 |
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value: 58.17903579421599
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1579 |
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- task:
|
1580 |
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type: Classification
|
1581 |
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dataset:
|
1582 |
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type: mteb/amazon_massive_intent
|
1583 |
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name: MTEB MassiveIntentClassification (en)
|
1584 |
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config: en
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1585 |
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split: test
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1586 |
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revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
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1587 |
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metrics:
|
1588 |
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1589 |
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value: 74.80833893745796
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1590 |
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- type: f1
|
1591 |
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value: 72.70786592684664
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1592 |
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- task:
|
1593 |
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type: Classification
|
1594 |
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dataset:
|
1595 |
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type: mteb/amazon_massive_scenario
|
1596 |
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name: MTEB MassiveScenarioClassification (en)
|
1597 |
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config: en
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1598 |
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1599 |
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revision: 7d571f92784cd94a019292a1f45445077d0ef634
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1600 |
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metrics:
|
1601 |
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- type: accuracy
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1602 |
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value: 78.69872225958305
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1603 |
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- type: f1
|
1604 |
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value: 78.61626934504731
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1605 |
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- task:
|
1606 |
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type: Clustering
|
1607 |
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dataset:
|
1608 |
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type: mteb/medrxiv-clustering-p2p
|
1609 |
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name: MTEB MedrxivClusteringP2P
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1610 |
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config: default
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1611 |
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split: test
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1612 |
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revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
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1613 |
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metrics:
|
1614 |
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- type: v_measure
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1615 |
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value: 33.058658628717694
|
1616 |
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- task:
|
1617 |
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type: Clustering
|
1618 |
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dataset:
|
1619 |
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type: mteb/medrxiv-clustering-s2s
|
1620 |
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name: MTEB MedrxivClusteringS2S
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1621 |
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config: default
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1622 |
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split: test
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1623 |
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revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
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1624 |
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metrics:
|
1625 |
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- type: v_measure
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1626 |
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value: 30.85561739360599
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1627 |
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- task:
|
1628 |
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type: Reranking
|
1629 |
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dataset:
|
1630 |
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type: mteb/mind_small
|
1631 |
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name: MTEB MindSmallReranking
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1632 |
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1633 |
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split: test
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1634 |
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revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
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1635 |
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metrics:
|
1636 |
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|
1637 |
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value: 31.290259910144385
|
1638 |
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|
1639 |
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value: 32.44223046102856
|
1640 |
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- task:
|
1641 |
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1642 |
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dataset:
|
1643 |
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type: nfcorpus
|
1644 |
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name: MTEB NFCorpus
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1645 |
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config: default
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1646 |
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split: test
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1647 |
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revision: None
|
1648 |
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metrics:
|
1649 |
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|
1650 |
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value: 5.288
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1651 |
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|
1652 |
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value: 12.267999999999999
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1653 |
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1654 |
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1655 |
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1656 |
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1657 |
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1658 |
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value: 8.866
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1659 |
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1660 |
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value: 10.418
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1661 |
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1664 |
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1665 |
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1666 |
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1667 |
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1668 |
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1669 |
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1670 |
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1671 |
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1672 |
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1673 |
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1674 |
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1676 |
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1677 |
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1678 |
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1679 |
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1681 |
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1682 |
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1683 |
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1684 |
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value: 37.519999999999996
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1685 |
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1686 |
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value: 43.653
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1687 |
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1688 |
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value: 25.728
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1689 |
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1690 |
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value: 7.932
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1691 |
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1692 |
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value: 2.07
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1693 |
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1694 |
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value: 38.184000000000005
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1695 |
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1696 |
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value: 32.879000000000005
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1697 |
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- type: recall_at_1
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1698 |
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value: 5.288
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1699 |
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- type: recall_at_10
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1700 |
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value: 16.195
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1701 |
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1702 |
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value: 31.135
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1703 |
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- type: recall_at_1000
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1704 |
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value: 61.531000000000006
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1705 |
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- type: recall_at_3
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1706 |
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value: 10.313
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1707 |
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- type: recall_at_5
|
1708 |
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value: 12.754999999999999
|
1709 |
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- task:
|
1710 |
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type: Retrieval
|
1711 |
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dataset:
|
1712 |
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type: nq
|
1713 |
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name: MTEB NQ
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1714 |
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config: default
|
1715 |
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split: test
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1716 |
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revision: None
|
1717 |
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metrics:
|
1718 |
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- type: map_at_1
|
1719 |
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value: 28.216
|
1720 |
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- type: map_at_10
|
1721 |
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value: 42.588
|
1722 |
+
- type: map_at_100
|
1723 |
+
value: 43.702999999999996
|
1724 |
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- type: map_at_1000
|
1725 |
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value: 43.739
|
1726 |
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- type: map_at_3
|
1727 |
+
value: 38.177
|
1728 |
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- type: map_at_5
|
1729 |
+
value: 40.754000000000005
|
1730 |
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- type: mrr_at_1
|
1731 |
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value: 31.866
|
1732 |
+
- type: mrr_at_10
|
1733 |
+
value: 45.189
|
1734 |
+
- type: mrr_at_100
|
1735 |
+
value: 46.056000000000004
|
1736 |
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- type: mrr_at_1000
|
1737 |
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value: 46.081
|
1738 |
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- type: mrr_at_3
|
1739 |
+
value: 41.526999999999994
|
1740 |
+
- type: mrr_at_5
|
1741 |
+
value: 43.704
|
1742 |
+
- type: ndcg_at_1
|
1743 |
+
value: 31.837
|
1744 |
+
- type: ndcg_at_10
|
1745 |
+
value: 50.178
|
1746 |
+
- type: ndcg_at_100
|
1747 |
+
value: 54.98800000000001
|
1748 |
+
- type: ndcg_at_1000
|
1749 |
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value: 55.812
|
1750 |
+
- type: ndcg_at_3
|
1751 |
+
value: 41.853
|
1752 |
+
- type: ndcg_at_5
|
1753 |
+
value: 46.153
|
1754 |
+
- type: precision_at_1
|
1755 |
+
value: 31.837
|
1756 |
+
- type: precision_at_10
|
1757 |
+
value: 8.43
|
1758 |
+
- type: precision_at_100
|
1759 |
+
value: 1.1119999999999999
|
1760 |
+
- type: precision_at_1000
|
1761 |
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value: 0.11900000000000001
|
1762 |
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- type: precision_at_3
|
1763 |
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value: 19.023
|
1764 |
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- type: precision_at_5
|
1765 |
+
value: 13.911000000000001
|
1766 |
+
- type: recall_at_1
|
1767 |
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value: 28.216
|
1768 |
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- type: recall_at_10
|
1769 |
+
value: 70.8
|
1770 |
+
- type: recall_at_100
|
1771 |
+
value: 91.857
|
1772 |
+
- type: recall_at_1000
|
1773 |
+
value: 97.941
|
1774 |
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- type: recall_at_3
|
1775 |
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value: 49.196
|
1776 |
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- type: recall_at_5
|
1777 |
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value: 59.072
|
1778 |
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- task:
|
1779 |
+
type: Retrieval
|
1780 |
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dataset:
|
1781 |
+
type: quora
|
1782 |
+
name: MTEB QuoraRetrieval
|
1783 |
+
config: default
|
1784 |
+
split: test
|
1785 |
+
revision: None
|
1786 |
+
metrics:
|
1787 |
+
- type: map_at_1
|
1788 |
+
value: 71.22800000000001
|
1789 |
+
- type: map_at_10
|
1790 |
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value: 85.115
|
1791 |
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- type: map_at_100
|
1792 |
+
value: 85.72
|
1793 |
+
- type: map_at_1000
|
1794 |
+
value: 85.737
|
1795 |
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- type: map_at_3
|
1796 |
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value: 82.149
|
1797 |
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- type: map_at_5
|
1798 |
+
value: 84.029
|
1799 |
+
- type: mrr_at_1
|
1800 |
+
value: 81.96
|
1801 |
+
- type: mrr_at_10
|
1802 |
+
value: 88.00200000000001
|
1803 |
+
- type: mrr_at_100
|
1804 |
+
value: 88.088
|
1805 |
+
- type: mrr_at_1000
|
1806 |
+
value: 88.089
|
1807 |
+
- type: mrr_at_3
|
1808 |
+
value: 87.055
|
1809 |
+
- type: mrr_at_5
|
1810 |
+
value: 87.715
|
1811 |
+
- type: ndcg_at_1
|
1812 |
+
value: 82.01
|
1813 |
+
- type: ndcg_at_10
|
1814 |
+
value: 88.78
|
1815 |
+
- type: ndcg_at_100
|
1816 |
+
value: 89.91
|
1817 |
+
- type: ndcg_at_1000
|
1818 |
+
value: 90.013
|
1819 |
+
- type: ndcg_at_3
|
1820 |
+
value: 85.957
|
1821 |
+
- type: ndcg_at_5
|
1822 |
+
value: 87.56
|
1823 |
+
- type: precision_at_1
|
1824 |
+
value: 82.01
|
1825 |
+
- type: precision_at_10
|
1826 |
+
value: 13.462
|
1827 |
+
- type: precision_at_100
|
1828 |
+
value: 1.528
|
1829 |
+
- type: precision_at_1000
|
1830 |
+
value: 0.157
|
1831 |
+
- type: precision_at_3
|
1832 |
+
value: 37.553
|
1833 |
+
- type: precision_at_5
|
1834 |
+
value: 24.732000000000003
|
1835 |
+
- type: recall_at_1
|
1836 |
+
value: 71.22800000000001
|
1837 |
+
- type: recall_at_10
|
1838 |
+
value: 95.69
|
1839 |
+
- type: recall_at_100
|
1840 |
+
value: 99.531
|
1841 |
+
- type: recall_at_1000
|
1842 |
+
value: 99.98
|
1843 |
+
- type: recall_at_3
|
1844 |
+
value: 87.632
|
1845 |
+
- type: recall_at_5
|
1846 |
+
value: 92.117
|
1847 |
+
- task:
|
1848 |
+
type: Clustering
|
1849 |
+
dataset:
|
1850 |
+
type: mteb/reddit-clustering
|
1851 |
+
name: MTEB RedditClustering
|
1852 |
+
config: default
|
1853 |
+
split: test
|
1854 |
+
revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
|
1855 |
+
metrics:
|
1856 |
+
- type: v_measure
|
1857 |
+
value: 52.31768034366916
|
1858 |
+
- task:
|
1859 |
+
type: Clustering
|
1860 |
+
dataset:
|
1861 |
+
type: mteb/reddit-clustering-p2p
|
1862 |
+
name: MTEB RedditClusteringP2P
|
1863 |
+
config: default
|
1864 |
+
split: test
|
1865 |
+
revision: 282350215ef01743dc01b456c7f5241fa8937f16
|
1866 |
+
metrics:
|
1867 |
+
- type: v_measure
|
1868 |
+
value: 60.640266772723606
|
1869 |
+
- task:
|
1870 |
+
type: Retrieval
|
1871 |
+
dataset:
|
1872 |
+
type: scidocs
|
1873 |
+
name: MTEB SCIDOCS
|
1874 |
+
config: default
|
1875 |
+
split: test
|
1876 |
+
revision: None
|
1877 |
+
metrics:
|
1878 |
+
- type: map_at_1
|
1879 |
+
value: 4.7780000000000005
|
1880 |
+
- type: map_at_10
|
1881 |
+
value: 12.299
|
1882 |
+
- type: map_at_100
|
1883 |
+
value: 14.363000000000001
|
1884 |
+
- type: map_at_1000
|
1885 |
+
value: 14.71
|
1886 |
+
- type: map_at_3
|
1887 |
+
value: 8.738999999999999
|
1888 |
+
- type: map_at_5
|
1889 |
+
value: 10.397
|
1890 |
+
- type: mrr_at_1
|
1891 |
+
value: 23.599999999999998
|
1892 |
+
- type: mrr_at_10
|
1893 |
+
value: 34.845
|
1894 |
+
- type: mrr_at_100
|
1895 |
+
value: 35.916
|
1896 |
+
- type: mrr_at_1000
|
1897 |
+
value: 35.973
|
1898 |
+
- type: mrr_at_3
|
1899 |
+
value: 31.7
|
1900 |
+
- type: mrr_at_5
|
1901 |
+
value: 33.535
|
1902 |
+
- type: ndcg_at_1
|
1903 |
+
value: 23.599999999999998
|
1904 |
+
- type: ndcg_at_10
|
1905 |
+
value: 20.522000000000002
|
1906 |
+
- type: ndcg_at_100
|
1907 |
+
value: 28.737000000000002
|
1908 |
+
- type: ndcg_at_1000
|
1909 |
+
value: 34.596
|
1910 |
+
- type: ndcg_at_3
|
1911 |
+
value: 19.542
|
1912 |
+
- type: ndcg_at_5
|
1913 |
+
value: 16.958000000000002
|
1914 |
+
- type: precision_at_1
|
1915 |
+
value: 23.599999999999998
|
1916 |
+
- type: precision_at_10
|
1917 |
+
value: 10.67
|
1918 |
+
- type: precision_at_100
|
1919 |
+
value: 2.259
|
1920 |
+
- type: precision_at_1000
|
1921 |
+
value: 0.367
|
1922 |
+
- type: precision_at_3
|
1923 |
+
value: 18.333
|
1924 |
+
- type: precision_at_5
|
1925 |
+
value: 14.879999999999999
|
1926 |
+
- type: recall_at_1
|
1927 |
+
value: 4.7780000000000005
|
1928 |
+
- type: recall_at_10
|
1929 |
+
value: 21.617
|
1930 |
+
- type: recall_at_100
|
1931 |
+
value: 45.905
|
1932 |
+
- type: recall_at_1000
|
1933 |
+
value: 74.42
|
1934 |
+
- type: recall_at_3
|
1935 |
+
value: 11.148
|
1936 |
+
- type: recall_at_5
|
1937 |
+
value: 15.082999999999998
|
1938 |
+
- task:
|
1939 |
+
type: STS
|
1940 |
+
dataset:
|
1941 |
+
type: mteb/sickr-sts
|
1942 |
+
name: MTEB SICK-R
|
1943 |
+
config: default
|
1944 |
+
split: test
|
1945 |
+
revision: a6ea5a8cab320b040a23452cc28066d9beae2cee
|
1946 |
+
metrics:
|
1947 |
+
- type: cos_sim_pearson
|
1948 |
+
value: 83.22372750297885
|
1949 |
+
- type: cos_sim_spearman
|
1950 |
+
value: 79.40972617119405
|
1951 |
+
- type: euclidean_pearson
|
1952 |
+
value: 80.6101072020434
|
1953 |
+
- type: euclidean_spearman
|
1954 |
+
value: 79.53844217225202
|
1955 |
+
- type: manhattan_pearson
|
1956 |
+
value: 80.57265975286111
|
1957 |
+
- type: manhattan_spearman
|
1958 |
+
value: 79.46335611792958
|
1959 |
+
- task:
|
1960 |
+
type: STS
|
1961 |
+
dataset:
|
1962 |
+
type: mteb/sts12-sts
|
1963 |
+
name: MTEB STS12
|
1964 |
+
config: default
|
1965 |
+
split: test
|
1966 |
+
revision: a0d554a64d88156834ff5ae9920b964011b16384
|
1967 |
+
metrics:
|
1968 |
+
- type: cos_sim_pearson
|
1969 |
+
value: 85.43713315520749
|
1970 |
+
- type: cos_sim_spearman
|
1971 |
+
value: 77.44128693329532
|
1972 |
+
- type: euclidean_pearson
|
1973 |
+
value: 81.63869928101123
|
1974 |
+
- type: euclidean_spearman
|
1975 |
+
value: 77.29512977961515
|
1976 |
+
- type: manhattan_pearson
|
1977 |
+
value: 81.63704185566183
|
1978 |
+
- type: manhattan_spearman
|
1979 |
+
value: 77.29909412738657
|
1980 |
+
- task:
|
1981 |
+
type: STS
|
1982 |
+
dataset:
|
1983 |
+
type: mteb/sts13-sts
|
1984 |
+
name: MTEB STS13
|
1985 |
+
config: default
|
1986 |
+
split: test
|
1987 |
+
revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
|
1988 |
+
metrics:
|
1989 |
+
- type: cos_sim_pearson
|
1990 |
+
value: 81.59451537860527
|
1991 |
+
- type: cos_sim_spearman
|
1992 |
+
value: 82.97994638856723
|
1993 |
+
- type: euclidean_pearson
|
1994 |
+
value: 82.89478688288412
|
1995 |
+
- type: euclidean_spearman
|
1996 |
+
value: 83.58740751053104
|
1997 |
+
- type: manhattan_pearson
|
1998 |
+
value: 82.69140840941608
|
1999 |
+
- type: manhattan_spearman
|
2000 |
+
value: 83.33665956040555
|
2001 |
+
- task:
|
2002 |
+
type: STS
|
2003 |
+
dataset:
|
2004 |
+
type: mteb/sts14-sts
|
2005 |
+
name: MTEB STS14
|
2006 |
+
config: default
|
2007 |
+
split: test
|
2008 |
+
revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
|
2009 |
+
metrics:
|
2010 |
+
- type: cos_sim_pearson
|
2011 |
+
value: 82.00756527711764
|
2012 |
+
- type: cos_sim_spearman
|
2013 |
+
value: 81.83560996841379
|
2014 |
+
- type: euclidean_pearson
|
2015 |
+
value: 82.07684151976518
|
2016 |
+
- type: euclidean_spearman
|
2017 |
+
value: 82.00913052060511
|
2018 |
+
- type: manhattan_pearson
|
2019 |
+
value: 82.05690778488794
|
2020 |
+
- type: manhattan_spearman
|
2021 |
+
value: 82.02260252019525
|
2022 |
+
- task:
|
2023 |
+
type: STS
|
2024 |
+
dataset:
|
2025 |
+
type: mteb/sts15-sts
|
2026 |
+
name: MTEB STS15
|
2027 |
+
config: default
|
2028 |
+
split: test
|
2029 |
+
revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
|
2030 |
+
metrics:
|
2031 |
+
- type: cos_sim_pearson
|
2032 |
+
value: 86.13710262895447
|
2033 |
+
- type: cos_sim_spearman
|
2034 |
+
value: 87.26412811156248
|
2035 |
+
- type: euclidean_pearson
|
2036 |
+
value: 86.94151453230228
|
2037 |
+
- type: euclidean_spearman
|
2038 |
+
value: 87.5363796699571
|
2039 |
+
- type: manhattan_pearson
|
2040 |
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value: 86.86989424083748
|
2041 |
+
- type: manhattan_spearman
|
2042 |
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value: 87.47315940781353
|
2043 |
+
- task:
|
2044 |
+
type: STS
|
2045 |
+
dataset:
|
2046 |
+
type: mteb/sts16-sts
|
2047 |
+
name: MTEB STS16
|
2048 |
+
config: default
|
2049 |
+
split: test
|
2050 |
+
revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
|
2051 |
+
metrics:
|
2052 |
+
- type: cos_sim_pearson
|
2053 |
+
value: 83.0230597603627
|
2054 |
+
- type: cos_sim_spearman
|
2055 |
+
value: 84.93344499318864
|
2056 |
+
- type: euclidean_pearson
|
2057 |
+
value: 84.23754743431141
|
2058 |
+
- type: euclidean_spearman
|
2059 |
+
value: 85.09707376597099
|
2060 |
+
- type: manhattan_pearson
|
2061 |
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value: 84.04325160987763
|
2062 |
+
- type: manhattan_spearman
|
2063 |
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value: 84.89353071339909
|
2064 |
+
- task:
|
2065 |
+
type: STS
|
2066 |
+
dataset:
|
2067 |
+
type: mteb/sts17-crosslingual-sts
|
2068 |
+
name: MTEB STS17 (en-en)
|
2069 |
+
config: en-en
|
2070 |
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split: test
|
2071 |
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revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
|
2072 |
+
metrics:
|
2073 |
+
- type: cos_sim_pearson
|
2074 |
+
value: 86.75620824563921
|
2075 |
+
- type: cos_sim_spearman
|
2076 |
+
value: 87.15065513706398
|
2077 |
+
- type: euclidean_pearson
|
2078 |
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value: 88.26281533633521
|
2079 |
+
- type: euclidean_spearman
|
2080 |
+
value: 87.51963738643983
|
2081 |
+
- type: manhattan_pearson
|
2082 |
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value: 88.25599267618065
|
2083 |
+
- type: manhattan_spearman
|
2084 |
+
value: 87.58048736047483
|
2085 |
+
- task:
|
2086 |
+
type: STS
|
2087 |
+
dataset:
|
2088 |
+
type: mteb/sts22-crosslingual-sts
|
2089 |
+
name: MTEB STS22 (en)
|
2090 |
+
config: en
|
2091 |
+
split: test
|
2092 |
+
revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80
|
2093 |
+
metrics:
|
2094 |
+
- type: cos_sim_pearson
|
2095 |
+
value: 64.74645319195137
|
2096 |
+
- type: cos_sim_spearman
|
2097 |
+
value: 65.29996325037214
|
2098 |
+
- type: euclidean_pearson
|
2099 |
+
value: 67.04297794086443
|
2100 |
+
- type: euclidean_spearman
|
2101 |
+
value: 65.43841726694343
|
2102 |
+
- type: manhattan_pearson
|
2103 |
+
value: 67.39459955690904
|
2104 |
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- type: manhattan_spearman
|
2105 |
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value: 65.92864704413651
|
2106 |
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- task:
|
2107 |
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type: STS
|
2108 |
+
dataset:
|
2109 |
+
type: mteb/stsbenchmark-sts
|
2110 |
+
name: MTEB STSBenchmark
|
2111 |
+
config: default
|
2112 |
+
split: test
|
2113 |
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revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
|
2114 |
+
metrics:
|
2115 |
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- type: cos_sim_pearson
|
2116 |
+
value: 84.31291020270801
|
2117 |
+
- type: cos_sim_spearman
|
2118 |
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value: 85.86473738688068
|
2119 |
+
- type: euclidean_pearson
|
2120 |
+
value: 85.65537275064152
|
2121 |
+
- type: euclidean_spearman
|
2122 |
+
value: 86.13087454209642
|
2123 |
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- type: manhattan_pearson
|
2124 |
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value: 85.43946955047609
|
2125 |
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- type: manhattan_spearman
|
2126 |
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value: 85.91568175344916
|
2127 |
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- task:
|
2128 |
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type: Reranking
|
2129 |
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dataset:
|
2130 |
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type: mteb/scidocs-reranking
|
2131 |
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name: MTEB SciDocsRR
|
2132 |
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config: default
|
2133 |
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split: test
|
2134 |
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revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
|
2135 |
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metrics:
|
2136 |
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- type: map
|
2137 |
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value: 85.93798118350695
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2138 |
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- type: mrr
|
2139 |
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2140 |
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- task:
|
2141 |
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type: Retrieval
|
2142 |
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dataset:
|
2143 |
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type: scifact
|
2144 |
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name: MTEB SciFact
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2145 |
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config: default
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2146 |
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split: test
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2147 |
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revision: None
|
2148 |
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metrics:
|
2149 |
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- type: map_at_1
|
2150 |
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value: 57.594
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2151 |
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- type: map_at_10
|
2152 |
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value: 66.81899999999999
|
2153 |
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2154 |
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value: 67.368
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2155 |
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2156 |
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value: 67.4
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2157 |
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2158 |
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2159 |
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2160 |
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value: 65.47
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2161 |
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2162 |
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value: 60.667
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2163 |
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- type: mrr_at_10
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2164 |
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value: 68.219
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2165 |
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2166 |
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2167 |
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- type: mrr_at_1000
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2168 |
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value: 68.684
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2169 |
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- type: mrr_at_3
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2170 |
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value: 66.22200000000001
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2171 |
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2172 |
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value: 67.289
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2173 |
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- type: ndcg_at_1
|
2174 |
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value: 60.667
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2175 |
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2176 |
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value: 71.275
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2177 |
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|
2178 |
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value: 73.642
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2179 |
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- type: ndcg_at_1000
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2180 |
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value: 74.373
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2181 |
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- type: ndcg_at_3
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2182 |
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2183 |
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2184 |
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2185 |
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2186 |
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value: 60.667
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2187 |
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- type: precision_at_10
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2188 |
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value: 9.433
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2189 |
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- type: precision_at_100
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2190 |
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value: 1.0699999999999998
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2191 |
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- type: precision_at_1000
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2192 |
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value: 0.11299999999999999
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2193 |
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- type: precision_at_3
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2194 |
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value: 25.556
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2195 |
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- type: precision_at_5
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2196 |
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value: 16.8
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2197 |
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- type: recall_at_1
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2198 |
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value: 57.594
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2199 |
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- type: recall_at_10
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2200 |
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value: 83.622
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2201 |
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- type: recall_at_100
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2202 |
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value: 94.167
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2203 |
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- type: recall_at_1000
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2204 |
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value: 99.667
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2205 |
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- type: recall_at_3
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2206 |
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value: 70.64399999999999
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2207 |
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- type: recall_at_5
|
2208 |
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value: 75.983
|
2209 |
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- task:
|
2210 |
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type: PairClassification
|
2211 |
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dataset:
|
2212 |
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type: mteb/sprintduplicatequestions-pairclassification
|
2213 |
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name: MTEB SprintDuplicateQuestions
|
2214 |
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config: default
|
2215 |
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split: test
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2216 |
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revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
|
2217 |
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metrics:
|
2218 |
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- type: cos_sim_accuracy
|
2219 |
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value: 99.85841584158416
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2220 |
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- type: cos_sim_ap
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2221 |
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value: 96.66996142314342
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2222 |
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- type: cos_sim_f1
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2223 |
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- type: cos_sim_precision
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2225 |
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2226 |
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- type: cos_sim_recall
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2227 |
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value: 92.60000000000001
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2228 |
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- type: dot_accuracy
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2229 |
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2230 |
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- type: dot_ap
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2231 |
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- type: dot_f1
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2233 |
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|
2234 |
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- type: dot_precision
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2235 |
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|
2236 |
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- type: dot_recall
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2237 |
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value: 90.7
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2238 |
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- type: euclidean_accuracy
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2239 |
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value: 99.86138613861387
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2240 |
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- type: euclidean_ap
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2241 |
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2242 |
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- type: euclidean_f1
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2243 |
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2244 |
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- type: euclidean_precision
|
2245 |
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value: 93.96728016359918
|
2246 |
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- type: euclidean_recall
|
2247 |
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value: 91.9
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2248 |
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- type: manhattan_accuracy
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2249 |
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value: 99.86237623762376
|
2250 |
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- type: manhattan_ap
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2251 |
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value: 96.60370449645053
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2252 |
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- type: manhattan_f1
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2253 |
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value: 92.91177970423253
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2254 |
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- type: manhattan_precision
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2255 |
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value: 94.7970863683663
|
2256 |
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- type: manhattan_recall
|
2257 |
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value: 91.10000000000001
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2258 |
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- type: max_accuracy
|
2259 |
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value: 99.86237623762376
|
2260 |
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- type: max_ap
|
2261 |
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value: 96.6775307676576
|
2262 |
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- type: max_f1
|
2263 |
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value: 92.92214357937311
|
2264 |
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- task:
|
2265 |
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type: Clustering
|
2266 |
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dataset:
|
2267 |
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type: mteb/stackexchange-clustering
|
2268 |
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name: MTEB StackExchangeClustering
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2269 |
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config: default
|
2270 |
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split: test
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2271 |
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revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
|
2272 |
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metrics:
|
2273 |
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- type: v_measure
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2274 |
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value: 60.77977058695198
|
2275 |
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- task:
|
2276 |
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type: Clustering
|
2277 |
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dataset:
|
2278 |
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type: mteb/stackexchange-clustering-p2p
|
2279 |
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name: MTEB StackExchangeClusteringP2P
|
2280 |
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config: default
|
2281 |
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split: test
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2282 |
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revision: 815ca46b2622cec33ccafc3735d572c266efdb44
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2283 |
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metrics:
|
2284 |
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- type: v_measure
|
2285 |
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value: 35.2725272535638
|
2286 |
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- task:
|
2287 |
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type: Reranking
|
2288 |
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dataset:
|
2289 |
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type: mteb/stackoverflowdupquestions-reranking
|
2290 |
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name: MTEB StackOverflowDupQuestions
|
2291 |
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config: default
|
2292 |
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split: test
|
2293 |
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revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
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2294 |
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metrics:
|
2295 |
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- type: map
|
2296 |
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value: 53.64052466362125
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2297 |
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- type: mrr
|
2298 |
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value: 54.533067014684654
|
2299 |
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- task:
|
2300 |
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type: Summarization
|
2301 |
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dataset:
|
2302 |
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type: mteb/summeval
|
2303 |
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name: MTEB SummEval
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2304 |
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config: default
|
2305 |
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split: test
|
2306 |
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revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
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2307 |
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metrics:
|
2308 |
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- type: cos_sim_pearson
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2309 |
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value: 30.677624219206578
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2310 |
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- type: cos_sim_spearman
|
2311 |
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value: 30.121368518123447
|
2312 |
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- type: dot_pearson
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2313 |
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value: 30.69870088041608
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2314 |
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- type: dot_spearman
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2315 |
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value: 29.61284927093751
|
2316 |
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- task:
|
2317 |
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type: Retrieval
|
2318 |
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dataset:
|
2319 |
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type: trec-covid
|
2320 |
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name: MTEB TRECCOVID
|
2321 |
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config: default
|
2322 |
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split: test
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2323 |
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revision: None
|
2324 |
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metrics:
|
2325 |
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- type: map_at_1
|
2326 |
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value: 0.22
|
2327 |
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- type: map_at_10
|
2328 |
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value: 1.855
|
2329 |
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- type: map_at_100
|
2330 |
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value: 9.885
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2331 |
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- type: map_at_1000
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2332 |
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value: 23.416999999999998
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2333 |
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- type: map_at_3
|
2334 |
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value: 0.637
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2335 |
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- type: map_at_5
|
2336 |
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value: 1.024
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2337 |
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- type: mrr_at_1
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2338 |
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value: 88.0
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2339 |
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- type: mrr_at_10
|
2340 |
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value: 93.067
|
2341 |
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- type: mrr_at_100
|
2342 |
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value: 93.067
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2343 |
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- type: mrr_at_1000
|
2344 |
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value: 93.067
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2345 |
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- type: mrr_at_3
|
2346 |
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value: 92.667
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2347 |
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- type: mrr_at_5
|
2348 |
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value: 93.067
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2349 |
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- type: ndcg_at_1
|
2350 |
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value: 82.0
|
2351 |
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- type: ndcg_at_10
|
2352 |
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value: 75.899
|
2353 |
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- type: ndcg_at_100
|
2354 |
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value: 55.115
|
2355 |
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- type: ndcg_at_1000
|
2356 |
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value: 48.368
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2357 |
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- type: ndcg_at_3
|
2358 |
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value: 79.704
|
2359 |
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- type: ndcg_at_5
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2360 |
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value: 78.39699999999999
|
2361 |
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- type: precision_at_1
|
2362 |
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value: 88.0
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2363 |
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- type: precision_at_10
|
2364 |
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value: 79.60000000000001
|
2365 |
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- type: precision_at_100
|
2366 |
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value: 56.06
|
2367 |
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- type: precision_at_1000
|
2368 |
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value: 21.206
|
2369 |
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- type: precision_at_3
|
2370 |
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value: 84.667
|
2371 |
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- type: precision_at_5
|
2372 |
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value: 83.2
|
2373 |
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- type: recall_at_1
|
2374 |
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value: 0.22
|
2375 |
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- type: recall_at_10
|
2376 |
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value: 2.078
|
2377 |
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- type: recall_at_100
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2378 |
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value: 13.297
|
2379 |
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- type: recall_at_1000
|
2380 |
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value: 44.979
|
2381 |
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- type: recall_at_3
|
2382 |
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value: 0.6689999999999999
|
2383 |
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- type: recall_at_5
|
2384 |
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value: 1.106
|
2385 |
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- task:
|
2386 |
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type: Retrieval
|
2387 |
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dataset:
|
2388 |
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type: webis-touche2020
|
2389 |
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name: MTEB Touche2020
|
2390 |
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config: default
|
2391 |
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split: test
|
2392 |
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revision: None
|
2393 |
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metrics:
|
2394 |
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- type: map_at_1
|
2395 |
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value: 2.258
|
2396 |
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- type: map_at_10
|
2397 |
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value: 10.439
|
2398 |
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- type: map_at_100
|
2399 |
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value: 16.89
|
2400 |
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- type: map_at_1000
|
2401 |
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value: 18.407999999999998
|
2402 |
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- type: map_at_3
|
2403 |
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value: 5.668
|
2404 |
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- type: map_at_5
|
2405 |
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value: 7.718
|
2406 |
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- type: mrr_at_1
|
2407 |
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value: 32.653
|
2408 |
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- type: mrr_at_10
|
2409 |
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value: 51.159
|
2410 |
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- type: mrr_at_100
|
2411 |
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value: 51.714000000000006
|
2412 |
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- type: mrr_at_1000
|
2413 |
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value: 51.714000000000006
|
2414 |
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- type: mrr_at_3
|
2415 |
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value: 47.959
|
2416 |
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- type: mrr_at_5
|
2417 |
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value: 50.407999999999994
|
2418 |
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- type: ndcg_at_1
|
2419 |
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value: 29.592000000000002
|
2420 |
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- type: ndcg_at_10
|
2421 |
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value: 26.037
|
2422 |
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- type: ndcg_at_100
|
2423 |
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value: 37.924
|
2424 |
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- type: ndcg_at_1000
|
2425 |
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value: 49.126999999999995
|
2426 |
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- type: ndcg_at_3
|
2427 |
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value: 30.631999999999998
|
2428 |
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- type: ndcg_at_5
|
2429 |
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value: 28.571
|
2430 |
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- type: precision_at_1
|
2431 |
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value: 32.653
|
2432 |
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- type: precision_at_10
|
2433 |
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value: 22.857
|
2434 |
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- type: precision_at_100
|
2435 |
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value: 7.754999999999999
|
2436 |
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- type: precision_at_1000
|
2437 |
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value: 1.529
|
2438 |
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- type: precision_at_3
|
2439 |
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value: 34.014
|
2440 |
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- type: precision_at_5
|
2441 |
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value: 29.796
|
2442 |
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- type: recall_at_1
|
2443 |
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value: 2.258
|
2444 |
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- type: recall_at_10
|
2445 |
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value: 16.554
|
2446 |
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- type: recall_at_100
|
2447 |
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value: 48.439
|
2448 |
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- type: recall_at_1000
|
2449 |
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value: 82.80499999999999
|
2450 |
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- type: recall_at_3
|
2451 |
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value: 7.283
|
2452 |
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- type: recall_at_5
|
2453 |
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value: 10.732
|
2454 |
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- task:
|
2455 |
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type: Classification
|
2456 |
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dataset:
|
2457 |
+
type: mteb/toxic_conversations_50k
|
2458 |
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name: MTEB ToxicConversationsClassification
|
2459 |
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config: default
|
2460 |
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split: test
|
2461 |
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revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
|
2462 |
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metrics:
|
2463 |
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- type: accuracy
|
2464 |
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value: 69.8858
|
2465 |
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- type: ap
|
2466 |
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value: 13.835684144362109
|
2467 |
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- type: f1
|
2468 |
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value: 53.803351693244586
|
2469 |
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- task:
|
2470 |
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type: Classification
|
2471 |
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dataset:
|
2472 |
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type: mteb/tweet_sentiment_extraction
|
2473 |
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name: MTEB TweetSentimentExtractionClassification
|
2474 |
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config: default
|
2475 |
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split: test
|
2476 |
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revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
|
2477 |
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metrics:
|
2478 |
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- type: accuracy
|
2479 |
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value: 60.50650820599886
|
2480 |
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- type: f1
|
2481 |
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value: 60.84357825979259
|
2482 |
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- task:
|
2483 |
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type: Clustering
|
2484 |
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dataset:
|
2485 |
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type: mteb/twentynewsgroups-clustering
|
2486 |
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name: MTEB TwentyNewsgroupsClustering
|
2487 |
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config: default
|
2488 |
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split: test
|
2489 |
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revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
|
2490 |
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metrics:
|
2491 |
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- type: v_measure
|
2492 |
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value: 48.52131044852134
|
2493 |
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- task:
|
2494 |
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type: PairClassification
|
2495 |
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dataset:
|
2496 |
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type: mteb/twittersemeval2015-pairclassification
|
2497 |
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name: MTEB TwitterSemEval2015
|
2498 |
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config: default
|
2499 |
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split: test
|
2500 |
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|
2501 |
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metrics:
|
2502 |
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- type: cos_sim_accuracy
|
2503 |
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value: 85.59337187816654
|
2504 |
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- type: cos_sim_ap
|
2505 |
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value: 73.23925826533437
|
2506 |
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- type: cos_sim_f1
|
2507 |
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value: 67.34693877551021
|
2508 |
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- type: cos_sim_precision
|
2509 |
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value: 62.40432237730752
|
2510 |
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- type: cos_sim_recall
|
2511 |
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value: 73.13984168865434
|
2512 |
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- type: dot_accuracy
|
2513 |
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value: 85.31322644096085
|
2514 |
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- type: dot_ap
|
2515 |
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value: 72.30723963807422
|
2516 |
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- type: dot_f1
|
2517 |
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value: 66.47051612112296
|
2518 |
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- type: dot_precision
|
2519 |
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value: 62.0792305930845
|
2520 |
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- type: dot_recall
|
2521 |
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value: 71.53034300791556
|
2522 |
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- type: euclidean_accuracy
|
2523 |
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value: 85.61125350181797
|
2524 |
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- type: euclidean_ap
|
2525 |
+
value: 73.32843720487845
|
2526 |
+
- type: euclidean_f1
|
2527 |
+
value: 67.36549633745895
|
2528 |
+
- type: euclidean_precision
|
2529 |
+
value: 64.60755813953489
|
2530 |
+
- type: euclidean_recall
|
2531 |
+
value: 70.36939313984169
|
2532 |
+
- type: manhattan_accuracy
|
2533 |
+
value: 85.63509566668654
|
2534 |
+
- type: manhattan_ap
|
2535 |
+
value: 73.16658488311325
|
2536 |
+
- type: manhattan_f1
|
2537 |
+
value: 67.20597386434349
|
2538 |
+
- type: manhattan_precision
|
2539 |
+
value: 63.60424028268551
|
2540 |
+
- type: manhattan_recall
|
2541 |
+
value: 71.2401055408971
|
2542 |
+
- type: max_accuracy
|
2543 |
+
value: 85.63509566668654
|
2544 |
+
- type: max_ap
|
2545 |
+
value: 73.32843720487845
|
2546 |
+
- type: max_f1
|
2547 |
+
value: 67.36549633745895
|
2548 |
+
- task:
|
2549 |
+
type: PairClassification
|
2550 |
+
dataset:
|
2551 |
+
type: mteb/twitterurlcorpus-pairclassification
|
2552 |
+
name: MTEB TwitterURLCorpus
|
2553 |
+
config: default
|
2554 |
+
split: test
|
2555 |
+
revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
|
2556 |
+
metrics:
|
2557 |
+
- type: cos_sim_accuracy
|
2558 |
+
value: 88.33779640625606
|
2559 |
+
- type: cos_sim_ap
|
2560 |
+
value: 84.83868375898157
|
2561 |
+
- type: cos_sim_f1
|
2562 |
+
value: 77.16506154017773
|
2563 |
+
- type: cos_sim_precision
|
2564 |
+
value: 74.62064005753327
|
2565 |
+
- type: cos_sim_recall
|
2566 |
+
value: 79.88912842623961
|
2567 |
+
- type: dot_accuracy
|
2568 |
+
value: 88.02732176815307
|
2569 |
+
- type: dot_ap
|
2570 |
+
value: 83.95089283763002
|
2571 |
+
- type: dot_f1
|
2572 |
+
value: 76.29635101196631
|
2573 |
+
- type: dot_precision
|
2574 |
+
value: 73.31771720613288
|
2575 |
+
- type: dot_recall
|
2576 |
+
value: 79.52725592854944
|
2577 |
+
- type: euclidean_accuracy
|
2578 |
+
value: 88.44452206310397
|
2579 |
+
- type: euclidean_ap
|
2580 |
+
value: 84.98384576824827
|
2581 |
+
- type: euclidean_f1
|
2582 |
+
value: 77.29311047696697
|
2583 |
+
- type: euclidean_precision
|
2584 |
+
value: 74.51232583065381
|
2585 |
+
- type: euclidean_recall
|
2586 |
+
value: 80.28949799815214
|
2587 |
+
- type: manhattan_accuracy
|
2588 |
+
value: 88.47362906042613
|
2589 |
+
- type: manhattan_ap
|
2590 |
+
value: 84.91421462218432
|
2591 |
+
- type: manhattan_f1
|
2592 |
+
value: 77.05107637204792
|
2593 |
+
- type: manhattan_precision
|
2594 |
+
value: 74.74484256243214
|
2595 |
+
- type: manhattan_recall
|
2596 |
+
value: 79.50415768401602
|
2597 |
+
- type: max_accuracy
|
2598 |
+
value: 88.47362906042613
|
2599 |
+
- type: max_ap
|
2600 |
+
value: 84.98384576824827
|
2601 |
+
- type: max_f1
|
2602 |
+
value: 77.29311047696697
|
2603 |
license: mit
|
2604 |
language:
|
2605 |
- en
|