add model weights
Browse files- README.md +2604 -0
- config.json +25 -0
- mteb_metadata.md +2599 -0
- pytorch_model.bin +3 -0
- special_tokens_map.json +1 -0
- tokenizer.json +0 -0
- tokenizer_config.json +1 -0
- vocab.txt +0 -0
README.md
ADDED
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|
1 |
+
---
|
2 |
+
tags:
|
3 |
+
- mteb
|
4 |
+
model-index:
|
5 |
+
- name: e5-small
|
6 |
+
results:
|
7 |
+
- task:
|
8 |
+
type: Classification
|
9 |
+
dataset:
|
10 |
+
type: mteb/amazon_counterfactual
|
11 |
+
name: MTEB AmazonCounterfactualClassification (en)
|
12 |
+
config: en
|
13 |
+
split: test
|
14 |
+
revision: e8379541af4e31359cca9fbcf4b00f2671dba205
|
15 |
+
metrics:
|
16 |
+
- type: accuracy
|
17 |
+
value: 76.22388059701493
|
18 |
+
- type: ap
|
19 |
+
value: 40.27466219523129
|
20 |
+
- type: f1
|
21 |
+
value: 70.60533006025108
|
22 |
+
- task:
|
23 |
+
type: Classification
|
24 |
+
dataset:
|
25 |
+
type: mteb/amazon_polarity
|
26 |
+
name: MTEB AmazonPolarityClassification
|
27 |
+
config: default
|
28 |
+
split: test
|
29 |
+
revision: e2d317d38cd51312af73b3d32a06d1a08b442046
|
30 |
+
metrics:
|
31 |
+
- type: accuracy
|
32 |
+
value: 87.525775
|
33 |
+
- type: ap
|
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value: 83.51063993897611
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36 |
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value: 87.49342736805572
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type: Classification
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39 |
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dataset:
|
40 |
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type: mteb/amazon_reviews_multi
|
41 |
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name: MTEB AmazonReviewsClassification (en)
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42 |
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config: en
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43 |
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split: test
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revision: 1399c76144fd37290681b995c656ef9b2e06e26d
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46 |
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- type: accuracy
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value: 42.611999999999995
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49 |
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- task:
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dataset:
|
53 |
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type: arguana
|
54 |
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name: MTEB ArguAna
|
55 |
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config: default
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56 |
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split: test
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57 |
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revision: None
|
58 |
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metrics:
|
59 |
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- type: map_at_1
|
60 |
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value: 23.826
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61 |
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|
62 |
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63 |
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value: 0.099
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value: 15.268
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value: 11.479000000000001
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value: 73.82600000000001
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value: 99.431
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value: 45.804
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- type: recall_at_5
|
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value: 57.397
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119 |
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- task:
|
120 |
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type: Clustering
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121 |
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dataset:
|
122 |
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type: mteb/arxiv-clustering-p2p
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123 |
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name: MTEB ArxivClusteringP2P
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config: default
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125 |
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split: test
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126 |
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revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
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metrics:
|
128 |
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- type: v_measure
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129 |
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value: 44.13995374767436
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130 |
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- task:
|
131 |
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type: Clustering
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dataset:
|
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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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136 |
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split: test
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137 |
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revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
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metrics:
|
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- type: v_measure
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140 |
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value: 37.13950072624313
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141 |
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- task:
|
142 |
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type: Reranking
|
143 |
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dataset:
|
144 |
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type: mteb/askubuntudupquestions-reranking
|
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name: MTEB AskUbuntuDupQuestions
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config: default
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split: test
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revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
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metrics:
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- type: map
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151 |
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value: 59.35843292105327
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153 |
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|
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type: STS
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156 |
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|
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type: mteb/biosses-sts
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name: MTEB BIOSSES
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config: default
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split: test
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161 |
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revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
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metrics:
|
163 |
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164 |
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value: 84.55140418324174
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- type: cos_sim_spearman
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- type: euclidean_pearson
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value: 81.26069614610006
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- type: euclidean_spearman
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value: 83.25069210421785
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- type: manhattan_pearson
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value: 80.17441422581014
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- type: manhattan_spearman
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value: 81.87596198487877
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175 |
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- task:
|
176 |
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type: Classification
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177 |
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dataset:
|
178 |
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type: mteb/banking77
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name: MTEB Banking77Classification
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180 |
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config: default
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181 |
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split: test
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182 |
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revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
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metrics:
|
184 |
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- type: accuracy
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185 |
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value: 81.87337662337661
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186 |
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- type: f1
|
187 |
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value: 81.76647866926402
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188 |
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- task:
|
189 |
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type: Clustering
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190 |
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dataset:
|
191 |
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type: mteb/biorxiv-clustering-p2p
|
192 |
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name: MTEB BiorxivClusteringP2P
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193 |
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config: default
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194 |
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split: test
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195 |
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revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
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metrics:
|
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- type: v_measure
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198 |
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value: 35.80600542614507
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199 |
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- task:
|
200 |
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type: Clustering
|
201 |
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dataset:
|
202 |
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type: mteb/biorxiv-clustering-s2s
|
203 |
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name: MTEB BiorxivClusteringS2S
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204 |
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config: default
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205 |
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split: test
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206 |
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revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
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metrics:
|
208 |
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209 |
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value: 31.86321613256603
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210 |
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- task:
|
211 |
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type: Retrieval
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212 |
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dataset:
|
213 |
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type: BeIR/cqadupstack
|
214 |
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name: MTEB CQADupstackAndroidRetrieval
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215 |
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config: default
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216 |
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split: test
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217 |
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revision: None
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218 |
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metrics:
|
219 |
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220 |
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value: 32.054
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221 |
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222 |
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value: 40.699999999999996
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value: 41.818
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value: 41.959999999999994
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value: 37.742
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value: 39.427
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value: 46.865
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value: 46.925
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value: 43.705
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value: 38.769999999999996
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value: 45.778
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value: 50.38
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249 |
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value: 41.597
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253 |
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254 |
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value: 43.631
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255 |
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256 |
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value: 38.769999999999996
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257 |
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258 |
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value: 8.269
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259 |
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260 |
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value: 1.278
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261 |
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262 |
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value: 0.178
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263 |
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264 |
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value: 19.266
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265 |
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266 |
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value: 13.705
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267 |
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value: 32.054
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value: 54.947
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value: 74.79599999999999
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274 |
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value: 91.40899999999999
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276 |
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value: 42.431000000000004
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277 |
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278 |
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value: 48.519
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279 |
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- task:
|
280 |
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type: Retrieval
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281 |
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dataset:
|
282 |
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type: BeIR/cqadupstack
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283 |
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name: MTEB CQADupstackEnglishRetrieval
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284 |
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config: default
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285 |
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split: test
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286 |
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revision: None
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287 |
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metrics:
|
288 |
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289 |
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value: 29.035
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290 |
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291 |
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value: 38.007000000000005
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292 |
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294 |
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value: 37.057
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300 |
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302 |
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303 |
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304 |
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305 |
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306 |
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308 |
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309 |
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value: 42.123
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310 |
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313 |
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314 |
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315 |
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316 |
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317 |
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value: 47.323
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318 |
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319 |
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value: 49.624
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320 |
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321 |
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value: 39.805
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322 |
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323 |
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value: 41.286
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324 |
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325 |
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value: 36.497
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326 |
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327 |
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value: 7.8340000000000005
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328 |
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329 |
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value: 1.269
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330 |
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331 |
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value: 0.178
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332 |
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333 |
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value: 19.023
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334 |
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335 |
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value: 13.248
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336 |
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value: 29.035
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338 |
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339 |
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value: 51.06
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340 |
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342 |
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343 |
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value: 84.49
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344 |
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value: 41.333999999999996
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346 |
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- type: recall_at_5
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347 |
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value: 45.663
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348 |
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- task:
|
349 |
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type: Retrieval
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350 |
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dataset:
|
351 |
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type: BeIR/cqadupstack
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352 |
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name: MTEB CQADupstackGamingRetrieval
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353 |
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config: default
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354 |
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split: test
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355 |
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revision: None
|
356 |
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metrics:
|
357 |
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|
358 |
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value: 37.239
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359 |
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360 |
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361 |
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401 |
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402 |
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403 |
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404 |
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405 |
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- task:
|
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419 |
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dataset:
|
420 |
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type: BeIR/cqadupstack
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421 |
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name: MTEB CQADupstackGisRetrieval
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422 |
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config: default
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revision: None
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metrics:
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427 |
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value: 23.039
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428 |
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462 |
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- type: precision_at_1
|
463 |
+
value: 24.633
|
464 |
+
- type: precision_at_10
|
465 |
+
value: 5.0729999999999995
|
466 |
+
- type: precision_at_100
|
467 |
+
value: 0.753
|
468 |
+
- type: precision_at_1000
|
469 |
+
value: 0.10300000000000001
|
470 |
+
- type: precision_at_3
|
471 |
+
value: 12.279
|
472 |
+
- type: precision_at_5
|
473 |
+
value: 8.452
|
474 |
+
- type: recall_at_1
|
475 |
+
value: 23.039
|
476 |
+
- type: recall_at_10
|
477 |
+
value: 44.275999999999996
|
478 |
+
- type: recall_at_100
|
479 |
+
value: 64.4
|
480 |
+
- type: recall_at_1000
|
481 |
+
value: 85.135
|
482 |
+
- type: recall_at_3
|
483 |
+
value: 33.394
|
484 |
+
- type: recall_at_5
|
485 |
+
value: 37.687
|
486 |
+
- task:
|
487 |
+
type: Retrieval
|
488 |
+
dataset:
|
489 |
+
type: BeIR/cqadupstack
|
490 |
+
name: MTEB CQADupstackMathematicaRetrieval
|
491 |
+
config: default
|
492 |
+
split: test
|
493 |
+
revision: None
|
494 |
+
metrics:
|
495 |
+
- type: map_at_1
|
496 |
+
value: 13.594999999999999
|
497 |
+
- type: map_at_10
|
498 |
+
value: 19.933999999999997
|
499 |
+
- type: map_at_100
|
500 |
+
value: 20.966
|
501 |
+
- type: map_at_1000
|
502 |
+
value: 21.087
|
503 |
+
- type: map_at_3
|
504 |
+
value: 17.749000000000002
|
505 |
+
- type: map_at_5
|
506 |
+
value: 19.156000000000002
|
507 |
+
- type: mrr_at_1
|
508 |
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value: 17.662
|
509 |
+
- type: mrr_at_10
|
510 |
+
value: 24.407
|
511 |
+
- type: mrr_at_100
|
512 |
+
value: 25.385
|
513 |
+
- type: mrr_at_1000
|
514 |
+
value: 25.465
|
515 |
+
- type: mrr_at_3
|
516 |
+
value: 22.056
|
517 |
+
- type: mrr_at_5
|
518 |
+
value: 23.630000000000003
|
519 |
+
- type: ndcg_at_1
|
520 |
+
value: 17.662
|
521 |
+
- type: ndcg_at_10
|
522 |
+
value: 24.391
|
523 |
+
- type: ndcg_at_100
|
524 |
+
value: 29.681
|
525 |
+
- type: ndcg_at_1000
|
526 |
+
value: 32.923
|
527 |
+
- type: ndcg_at_3
|
528 |
+
value: 20.271
|
529 |
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- type: ndcg_at_5
|
530 |
+
value: 22.621
|
531 |
+
- type: precision_at_1
|
532 |
+
value: 17.662
|
533 |
+
- type: precision_at_10
|
534 |
+
value: 4.44
|
535 |
+
- type: precision_at_100
|
536 |
+
value: 0.8200000000000001
|
537 |
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- type: precision_at_1000
|
538 |
+
value: 0.125
|
539 |
+
- type: precision_at_3
|
540 |
+
value: 9.577
|
541 |
+
- type: precision_at_5
|
542 |
+
value: 7.313
|
543 |
+
- type: recall_at_1
|
544 |
+
value: 13.594999999999999
|
545 |
+
- type: recall_at_10
|
546 |
+
value: 33.976
|
547 |
+
- type: recall_at_100
|
548 |
+
value: 57.43000000000001
|
549 |
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- type: recall_at_1000
|
550 |
+
value: 80.958
|
551 |
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- type: recall_at_3
|
552 |
+
value: 22.897000000000002
|
553 |
+
- type: recall_at_5
|
554 |
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value: 28.714000000000002
|
555 |
+
- task:
|
556 |
+
type: Retrieval
|
557 |
+
dataset:
|
558 |
+
type: BeIR/cqadupstack
|
559 |
+
name: MTEB CQADupstackPhysicsRetrieval
|
560 |
+
config: default
|
561 |
+
split: test
|
562 |
+
revision: None
|
563 |
+
metrics:
|
564 |
+
- type: map_at_1
|
565 |
+
value: 26.683
|
566 |
+
- type: map_at_10
|
567 |
+
value: 35.068
|
568 |
+
- type: map_at_100
|
569 |
+
value: 36.311
|
570 |
+
- type: map_at_1000
|
571 |
+
value: 36.436
|
572 |
+
- type: map_at_3
|
573 |
+
value: 32.371
|
574 |
+
- type: map_at_5
|
575 |
+
value: 33.761
|
576 |
+
- type: mrr_at_1
|
577 |
+
value: 32.435
|
578 |
+
- type: mrr_at_10
|
579 |
+
value: 40.721000000000004
|
580 |
+
- type: mrr_at_100
|
581 |
+
value: 41.535
|
582 |
+
- type: mrr_at_1000
|
583 |
+
value: 41.593
|
584 |
+
- type: mrr_at_3
|
585 |
+
value: 38.401999999999994
|
586 |
+
- type: mrr_at_5
|
587 |
+
value: 39.567
|
588 |
+
- type: ndcg_at_1
|
589 |
+
value: 32.435
|
590 |
+
- type: ndcg_at_10
|
591 |
+
value: 40.538000000000004
|
592 |
+
- type: ndcg_at_100
|
593 |
+
value: 45.963
|
594 |
+
- type: ndcg_at_1000
|
595 |
+
value: 48.400999999999996
|
596 |
+
- type: ndcg_at_3
|
597 |
+
value: 36.048
|
598 |
+
- type: ndcg_at_5
|
599 |
+
value: 37.899
|
600 |
+
- type: precision_at_1
|
601 |
+
value: 32.435
|
602 |
+
- type: precision_at_10
|
603 |
+
value: 7.1129999999999995
|
604 |
+
- type: precision_at_100
|
605 |
+
value: 1.162
|
606 |
+
- type: precision_at_1000
|
607 |
+
value: 0.156
|
608 |
+
- type: precision_at_3
|
609 |
+
value: 16.683
|
610 |
+
- type: precision_at_5
|
611 |
+
value: 11.684
|
612 |
+
- type: recall_at_1
|
613 |
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value: 26.683
|
614 |
+
- type: recall_at_10
|
615 |
+
value: 51.517
|
616 |
+
- type: recall_at_100
|
617 |
+
value: 74.553
|
618 |
+
- type: recall_at_1000
|
619 |
+
value: 90.649
|
620 |
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- type: recall_at_3
|
621 |
+
value: 38.495000000000005
|
622 |
+
- type: recall_at_5
|
623 |
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value: 43.495
|
624 |
+
- task:
|
625 |
+
type: Retrieval
|
626 |
+
dataset:
|
627 |
+
type: BeIR/cqadupstack
|
628 |
+
name: MTEB CQADupstackProgrammersRetrieval
|
629 |
+
config: default
|
630 |
+
split: test
|
631 |
+
revision: None
|
632 |
+
metrics:
|
633 |
+
- type: map_at_1
|
634 |
+
value: 24.186
|
635 |
+
- type: map_at_10
|
636 |
+
value: 31.972
|
637 |
+
- type: map_at_100
|
638 |
+
value: 33.117000000000004
|
639 |
+
- type: map_at_1000
|
640 |
+
value: 33.243
|
641 |
+
- type: map_at_3
|
642 |
+
value: 29.423
|
643 |
+
- type: map_at_5
|
644 |
+
value: 30.847
|
645 |
+
- type: mrr_at_1
|
646 |
+
value: 29.794999999999998
|
647 |
+
- type: mrr_at_10
|
648 |
+
value: 36.767
|
649 |
+
- type: mrr_at_100
|
650 |
+
value: 37.645
|
651 |
+
- type: mrr_at_1000
|
652 |
+
value: 37.716
|
653 |
+
- type: mrr_at_3
|
654 |
+
value: 34.513
|
655 |
+
- type: mrr_at_5
|
656 |
+
value: 35.791000000000004
|
657 |
+
- type: ndcg_at_1
|
658 |
+
value: 29.794999999999998
|
659 |
+
- type: ndcg_at_10
|
660 |
+
value: 36.786
|
661 |
+
- type: ndcg_at_100
|
662 |
+
value: 41.94
|
663 |
+
- type: ndcg_at_1000
|
664 |
+
value: 44.830999999999996
|
665 |
+
- type: ndcg_at_3
|
666 |
+
value: 32.504
|
667 |
+
- type: ndcg_at_5
|
668 |
+
value: 34.404
|
669 |
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- type: precision_at_1
|
670 |
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value: 29.794999999999998
|
671 |
+
- type: precision_at_10
|
672 |
+
value: 6.518
|
673 |
+
- type: precision_at_100
|
674 |
+
value: 1.0659999999999998
|
675 |
+
- type: precision_at_1000
|
676 |
+
value: 0.149
|
677 |
+
- type: precision_at_3
|
678 |
+
value: 15.296999999999999
|
679 |
+
- type: precision_at_5
|
680 |
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value: 10.731
|
681 |
+
- type: recall_at_1
|
682 |
+
value: 24.186
|
683 |
+
- type: recall_at_10
|
684 |
+
value: 46.617
|
685 |
+
- type: recall_at_100
|
686 |
+
value: 68.75
|
687 |
+
- type: recall_at_1000
|
688 |
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value: 88.864
|
689 |
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- type: recall_at_3
|
690 |
+
value: 34.199
|
691 |
+
- type: recall_at_5
|
692 |
+
value: 39.462
|
693 |
+
- task:
|
694 |
+
type: Retrieval
|
695 |
+
dataset:
|
696 |
+
type: BeIR/cqadupstack
|
697 |
+
name: MTEB CQADupstackRetrieval
|
698 |
+
config: default
|
699 |
+
split: test
|
700 |
+
revision: None
|
701 |
+
metrics:
|
702 |
+
- type: map_at_1
|
703 |
+
value: 24.22083333333333
|
704 |
+
- type: map_at_10
|
705 |
+
value: 31.606666666666662
|
706 |
+
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|
707 |
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value: 32.6195
|
708 |
+
- type: map_at_1000
|
709 |
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value: 32.739999999999995
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710 |
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- type: map_at_3
|
711 |
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value: 29.37825
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712 |
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|
713 |
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value: 30.596083333333336
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714 |
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|
715 |
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value: 28.607916666666668
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716 |
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|
717 |
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value: 35.54591666666666
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718 |
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|
719 |
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value: 36.33683333333333
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720 |
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|
721 |
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value: 36.40624999999999
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722 |
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|
723 |
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value: 33.526250000000005
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724 |
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|
725 |
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value: 34.6605
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726 |
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727 |
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value: 28.607916666666668
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728 |
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|
729 |
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value: 36.07966666666667
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730 |
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|
731 |
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value: 40.73308333333333
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732 |
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|
733 |
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value: 43.40666666666666
|
734 |
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- type: ndcg_at_3
|
735 |
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value: 32.23525
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736 |
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|
737 |
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value: 33.97083333333333
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738 |
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- type: precision_at_1
|
739 |
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value: 28.607916666666668
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740 |
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|
741 |
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value: 6.120333333333335
|
742 |
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- type: precision_at_100
|
743 |
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value: 0.9921666666666668
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744 |
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|
745 |
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value: 0.14091666666666666
|
746 |
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|
747 |
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value: 14.54975
|
748 |
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- type: precision_at_5
|
749 |
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value: 10.153166666666667
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750 |
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- type: recall_at_1
|
751 |
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value: 24.22083333333333
|
752 |
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- type: recall_at_10
|
753 |
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value: 45.49183333333334
|
754 |
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- type: recall_at_100
|
755 |
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value: 66.28133333333332
|
756 |
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- type: recall_at_1000
|
757 |
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value: 85.16541666666667
|
758 |
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- type: recall_at_3
|
759 |
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value: 34.6485
|
760 |
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- type: recall_at_5
|
761 |
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value: 39.229749999999996
|
762 |
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- task:
|
763 |
+
type: Retrieval
|
764 |
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dataset:
|
765 |
+
type: BeIR/cqadupstack
|
766 |
+
name: MTEB CQADupstackStatsRetrieval
|
767 |
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config: default
|
768 |
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split: test
|
769 |
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revision: None
|
770 |
+
metrics:
|
771 |
+
- type: map_at_1
|
772 |
+
value: 21.842
|
773 |
+
- type: map_at_10
|
774 |
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value: 27.573999999999998
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775 |
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|
776 |
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value: 28.410999999999998
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777 |
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|
778 |
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value: 28.502
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779 |
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|
780 |
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value: 25.921
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781 |
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|
782 |
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value: 26.888
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783 |
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|
784 |
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value: 24.08
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785 |
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|
786 |
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value: 29.915999999999997
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787 |
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|
788 |
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value: 30.669
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789 |
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|
790 |
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value: 30.746000000000002
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791 |
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|
792 |
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value: 28.349000000000004
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793 |
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|
794 |
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value: 29.246
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795 |
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|
796 |
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value: 24.08
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797 |
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|
798 |
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799 |
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|
800 |
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801 |
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|
802 |
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value: 37.679
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803 |
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|
804 |
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value: 27.881
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805 |
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|
806 |
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value: 29.432000000000002
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807 |
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|
808 |
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value: 24.08
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809 |
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|
810 |
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value: 4.678
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811 |
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|
812 |
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value: 0.744
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813 |
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|
814 |
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value: 0.10300000000000001
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815 |
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|
816 |
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value: 11.860999999999999
|
817 |
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|
818 |
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value: 8.16
|
819 |
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|
820 |
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value: 21.842
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821 |
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- type: recall_at_10
|
822 |
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value: 38.66
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823 |
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|
824 |
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value: 59.169000000000004
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825 |
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- type: recall_at_1000
|
826 |
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value: 76.887
|
827 |
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|
828 |
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value: 30.532999999999998
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829 |
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- type: recall_at_5
|
830 |
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value: 34.354
|
831 |
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- task:
|
832 |
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type: Retrieval
|
833 |
+
dataset:
|
834 |
+
type: BeIR/cqadupstack
|
835 |
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name: MTEB CQADupstackTexRetrieval
|
836 |
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config: default
|
837 |
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split: test
|
838 |
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revision: None
|
839 |
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metrics:
|
840 |
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|
841 |
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value: 17.145
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842 |
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|
843 |
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value: 22.729
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844 |
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|
845 |
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value: 23.574
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846 |
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847 |
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value: 23.695
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848 |
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|
849 |
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value: 21.044
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850 |
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|
851 |
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value: 21.981
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852 |
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|
853 |
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value: 20.888
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854 |
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855 |
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value: 26.529000000000003
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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: 27.389000000000003
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860 |
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861 |
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value: 24.868000000000002
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862 |
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|
863 |
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value: 25.825
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864 |
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865 |
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value: 20.888
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866 |
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867 |
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868 |
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869 |
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870 |
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871 |
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value: 33.825
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872 |
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873 |
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value: 23.483999999999998
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874 |
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875 |
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value: 24.836
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876 |
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877 |
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value: 20.888
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878 |
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|
879 |
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value: 4.58
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880 |
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|
881 |
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value: 0.784
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882 |
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|
883 |
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value: 0.121
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884 |
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- type: precision_at_3
|
885 |
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value: 10.874
|
886 |
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- type: precision_at_5
|
887 |
+
value: 7.639
|
888 |
+
- type: recall_at_1
|
889 |
+
value: 17.145
|
890 |
+
- type: recall_at_10
|
891 |
+
value: 33.938
|
892 |
+
- type: recall_at_100
|
893 |
+
value: 53.672
|
894 |
+
- type: recall_at_1000
|
895 |
+
value: 76.023
|
896 |
+
- type: recall_at_3
|
897 |
+
value: 25.363000000000003
|
898 |
+
- type: recall_at_5
|
899 |
+
value: 29.023
|
900 |
+
- task:
|
901 |
+
type: Retrieval
|
902 |
+
dataset:
|
903 |
+
type: BeIR/cqadupstack
|
904 |
+
name: MTEB CQADupstackUnixRetrieval
|
905 |
+
config: default
|
906 |
+
split: test
|
907 |
+
revision: None
|
908 |
+
metrics:
|
909 |
+
- type: map_at_1
|
910 |
+
value: 24.275
|
911 |
+
- type: map_at_10
|
912 |
+
value: 30.438
|
913 |
+
- type: map_at_100
|
914 |
+
value: 31.489
|
915 |
+
- type: map_at_1000
|
916 |
+
value: 31.601000000000003
|
917 |
+
- type: map_at_3
|
918 |
+
value: 28.647
|
919 |
+
- type: map_at_5
|
920 |
+
value: 29.660999999999998
|
921 |
+
- type: mrr_at_1
|
922 |
+
value: 28.077999999999996
|
923 |
+
- type: mrr_at_10
|
924 |
+
value: 34.098
|
925 |
+
- type: mrr_at_100
|
926 |
+
value: 35.025
|
927 |
+
- type: mrr_at_1000
|
928 |
+
value: 35.109
|
929 |
+
- type: mrr_at_3
|
930 |
+
value: 32.4
|
931 |
+
- type: mrr_at_5
|
932 |
+
value: 33.379999999999995
|
933 |
+
- type: ndcg_at_1
|
934 |
+
value: 28.077999999999996
|
935 |
+
- type: ndcg_at_10
|
936 |
+
value: 34.271
|
937 |
+
- type: ndcg_at_100
|
938 |
+
value: 39.352
|
939 |
+
- type: ndcg_at_1000
|
940 |
+
value: 42.199
|
941 |
+
- type: ndcg_at_3
|
942 |
+
value: 30.978
|
943 |
+
- type: ndcg_at_5
|
944 |
+
value: 32.498
|
945 |
+
- type: precision_at_1
|
946 |
+
value: 28.077999999999996
|
947 |
+
- type: precision_at_10
|
948 |
+
value: 5.345
|
949 |
+
- type: precision_at_100
|
950 |
+
value: 0.897
|
951 |
+
- type: precision_at_1000
|
952 |
+
value: 0.125
|
953 |
+
- type: precision_at_3
|
954 |
+
value: 13.526
|
955 |
+
- type: precision_at_5
|
956 |
+
value: 9.16
|
957 |
+
- type: recall_at_1
|
958 |
+
value: 24.275
|
959 |
+
- type: recall_at_10
|
960 |
+
value: 42.362
|
961 |
+
- type: recall_at_100
|
962 |
+
value: 64.461
|
963 |
+
- type: recall_at_1000
|
964 |
+
value: 84.981
|
965 |
+
- type: recall_at_3
|
966 |
+
value: 33.249
|
967 |
+
- type: recall_at_5
|
968 |
+
value: 37.214999999999996
|
969 |
+
- task:
|
970 |
+
type: Retrieval
|
971 |
+
dataset:
|
972 |
+
type: BeIR/cqadupstack
|
973 |
+
name: MTEB CQADupstackWebmastersRetrieval
|
974 |
+
config: default
|
975 |
+
split: test
|
976 |
+
revision: None
|
977 |
+
metrics:
|
978 |
+
- type: map_at_1
|
979 |
+
value: 22.358
|
980 |
+
- type: map_at_10
|
981 |
+
value: 30.062
|
982 |
+
- type: map_at_100
|
983 |
+
value: 31.189
|
984 |
+
- type: map_at_1000
|
985 |
+
value: 31.386999999999997
|
986 |
+
- type: map_at_3
|
987 |
+
value: 27.672
|
988 |
+
- type: map_at_5
|
989 |
+
value: 28.76
|
990 |
+
- type: mrr_at_1
|
991 |
+
value: 26.877000000000002
|
992 |
+
- type: mrr_at_10
|
993 |
+
value: 33.948
|
994 |
+
- type: mrr_at_100
|
995 |
+
value: 34.746
|
996 |
+
- type: mrr_at_1000
|
997 |
+
value: 34.816
|
998 |
+
- type: mrr_at_3
|
999 |
+
value: 31.884
|
1000 |
+
- type: mrr_at_5
|
1001 |
+
value: 33.001000000000005
|
1002 |
+
- type: ndcg_at_1
|
1003 |
+
value: 26.877000000000002
|
1004 |
+
- type: ndcg_at_10
|
1005 |
+
value: 34.977000000000004
|
1006 |
+
- type: ndcg_at_100
|
1007 |
+
value: 39.753
|
1008 |
+
- type: ndcg_at_1000
|
1009 |
+
value: 42.866
|
1010 |
+
- type: ndcg_at_3
|
1011 |
+
value: 30.956
|
1012 |
+
- type: ndcg_at_5
|
1013 |
+
value: 32.381
|
1014 |
+
- type: precision_at_1
|
1015 |
+
value: 26.877000000000002
|
1016 |
+
- type: precision_at_10
|
1017 |
+
value: 6.7
|
1018 |
+
- type: precision_at_100
|
1019 |
+
value: 1.287
|
1020 |
+
- type: precision_at_1000
|
1021 |
+
value: 0.215
|
1022 |
+
- type: precision_at_3
|
1023 |
+
value: 14.360999999999999
|
1024 |
+
- type: precision_at_5
|
1025 |
+
value: 10.119
|
1026 |
+
- type: recall_at_1
|
1027 |
+
value: 22.358
|
1028 |
+
- type: recall_at_10
|
1029 |
+
value: 44.183
|
1030 |
+
- type: recall_at_100
|
1031 |
+
value: 67.14
|
1032 |
+
- type: recall_at_1000
|
1033 |
+
value: 87.53999999999999
|
1034 |
+
- type: recall_at_3
|
1035 |
+
value: 32.79
|
1036 |
+
- type: recall_at_5
|
1037 |
+
value: 36.829
|
1038 |
+
- task:
|
1039 |
+
type: Retrieval
|
1040 |
+
dataset:
|
1041 |
+
type: BeIR/cqadupstack
|
1042 |
+
name: MTEB CQADupstackWordpressRetrieval
|
1043 |
+
config: default
|
1044 |
+
split: test
|
1045 |
+
revision: None
|
1046 |
+
metrics:
|
1047 |
+
- type: map_at_1
|
1048 |
+
value: 19.198999999999998
|
1049 |
+
- type: map_at_10
|
1050 |
+
value: 25.229000000000003
|
1051 |
+
- type: map_at_100
|
1052 |
+
value: 26.003
|
1053 |
+
- type: map_at_1000
|
1054 |
+
value: 26.111
|
1055 |
+
- type: map_at_3
|
1056 |
+
value: 23.442
|
1057 |
+
- type: map_at_5
|
1058 |
+
value: 24.343
|
1059 |
+
- type: mrr_at_1
|
1060 |
+
value: 21.072
|
1061 |
+
- type: mrr_at_10
|
1062 |
+
value: 27.02
|
1063 |
+
- type: mrr_at_100
|
1064 |
+
value: 27.735
|
1065 |
+
- type: mrr_at_1000
|
1066 |
+
value: 27.815
|
1067 |
+
- type: mrr_at_3
|
1068 |
+
value: 25.416
|
1069 |
+
- type: mrr_at_5
|
1070 |
+
value: 26.173999999999996
|
1071 |
+
- type: ndcg_at_1
|
1072 |
+
value: 21.072
|
1073 |
+
- type: ndcg_at_10
|
1074 |
+
value: 28.862
|
1075 |
+
- type: ndcg_at_100
|
1076 |
+
value: 33.043
|
1077 |
+
- type: ndcg_at_1000
|
1078 |
+
value: 36.003
|
1079 |
+
- type: ndcg_at_3
|
1080 |
+
value: 25.35
|
1081 |
+
- type: ndcg_at_5
|
1082 |
+
value: 26.773000000000003
|
1083 |
+
- type: precision_at_1
|
1084 |
+
value: 21.072
|
1085 |
+
- type: precision_at_10
|
1086 |
+
value: 4.436
|
1087 |
+
- type: precision_at_100
|
1088 |
+
value: 0.713
|
1089 |
+
- type: precision_at_1000
|
1090 |
+
value: 0.106
|
1091 |
+
- type: precision_at_3
|
1092 |
+
value: 10.659
|
1093 |
+
- type: precision_at_5
|
1094 |
+
value: 7.32
|
1095 |
+
- type: recall_at_1
|
1096 |
+
value: 19.198999999999998
|
1097 |
+
- type: recall_at_10
|
1098 |
+
value: 38.376
|
1099 |
+
- type: recall_at_100
|
1100 |
+
value: 58.36900000000001
|
1101 |
+
- type: recall_at_1000
|
1102 |
+
value: 80.92099999999999
|
1103 |
+
- type: recall_at_3
|
1104 |
+
value: 28.715000000000003
|
1105 |
+
- type: recall_at_5
|
1106 |
+
value: 32.147
|
1107 |
+
- task:
|
1108 |
+
type: Retrieval
|
1109 |
+
dataset:
|
1110 |
+
type: climate-fever
|
1111 |
+
name: MTEB ClimateFEVER
|
1112 |
+
config: default
|
1113 |
+
split: test
|
1114 |
+
revision: None
|
1115 |
+
metrics:
|
1116 |
+
- type: map_at_1
|
1117 |
+
value: 5.9319999999999995
|
1118 |
+
- type: map_at_10
|
1119 |
+
value: 10.483
|
1120 |
+
- type: map_at_100
|
1121 |
+
value: 11.97
|
1122 |
+
- type: map_at_1000
|
1123 |
+
value: 12.171999999999999
|
1124 |
+
- type: map_at_3
|
1125 |
+
value: 8.477
|
1126 |
+
- type: map_at_5
|
1127 |
+
value: 9.495000000000001
|
1128 |
+
- type: mrr_at_1
|
1129 |
+
value: 13.094
|
1130 |
+
- type: mrr_at_10
|
1131 |
+
value: 21.282
|
1132 |
+
- type: mrr_at_100
|
1133 |
+
value: 22.556
|
1134 |
+
- type: mrr_at_1000
|
1135 |
+
value: 22.628999999999998
|
1136 |
+
- type: mrr_at_3
|
1137 |
+
value: 18.218999999999998
|
1138 |
+
- type: mrr_at_5
|
1139 |
+
value: 19.900000000000002
|
1140 |
+
- type: ndcg_at_1
|
1141 |
+
value: 13.094
|
1142 |
+
- type: ndcg_at_10
|
1143 |
+
value: 15.811
|
1144 |
+
- type: ndcg_at_100
|
1145 |
+
value: 23.035
|
1146 |
+
- type: ndcg_at_1000
|
1147 |
+
value: 27.089999999999996
|
1148 |
+
- type: ndcg_at_3
|
1149 |
+
value: 11.905000000000001
|
1150 |
+
- type: ndcg_at_5
|
1151 |
+
value: 13.377
|
1152 |
+
- type: precision_at_1
|
1153 |
+
value: 13.094
|
1154 |
+
- type: precision_at_10
|
1155 |
+
value: 5.225
|
1156 |
+
- type: precision_at_100
|
1157 |
+
value: 1.2970000000000002
|
1158 |
+
- type: precision_at_1000
|
1159 |
+
value: 0.203
|
1160 |
+
- type: precision_at_3
|
1161 |
+
value: 8.86
|
1162 |
+
- type: precision_at_5
|
1163 |
+
value: 7.309
|
1164 |
+
- type: recall_at_1
|
1165 |
+
value: 5.9319999999999995
|
1166 |
+
- type: recall_at_10
|
1167 |
+
value: 20.305
|
1168 |
+
- type: recall_at_100
|
1169 |
+
value: 46.314
|
1170 |
+
- type: recall_at_1000
|
1171 |
+
value: 69.612
|
1172 |
+
- type: recall_at_3
|
1173 |
+
value: 11.21
|
1174 |
+
- type: recall_at_5
|
1175 |
+
value: 14.773
|
1176 |
+
- task:
|
1177 |
+
type: Retrieval
|
1178 |
+
dataset:
|
1179 |
+
type: dbpedia-entity
|
1180 |
+
name: MTEB DBPedia
|
1181 |
+
config: default
|
1182 |
+
split: test
|
1183 |
+
revision: None
|
1184 |
+
metrics:
|
1185 |
+
- type: map_at_1
|
1186 |
+
value: 8.674
|
1187 |
+
- type: map_at_10
|
1188 |
+
value: 17.822
|
1189 |
+
- type: map_at_100
|
1190 |
+
value: 24.794
|
1191 |
+
- type: map_at_1000
|
1192 |
+
value: 26.214
|
1193 |
+
- type: map_at_3
|
1194 |
+
value: 12.690999999999999
|
1195 |
+
- type: map_at_5
|
1196 |
+
value: 15.033
|
1197 |
+
- type: mrr_at_1
|
1198 |
+
value: 61.75000000000001
|
1199 |
+
- type: mrr_at_10
|
1200 |
+
value: 71.58
|
1201 |
+
- type: mrr_at_100
|
1202 |
+
value: 71.923
|
1203 |
+
- type: mrr_at_1000
|
1204 |
+
value: 71.932
|
1205 |
+
- type: mrr_at_3
|
1206 |
+
value: 70.125
|
1207 |
+
- type: mrr_at_5
|
1208 |
+
value: 71.038
|
1209 |
+
- type: ndcg_at_1
|
1210 |
+
value: 51.0
|
1211 |
+
- type: ndcg_at_10
|
1212 |
+
value: 38.637
|
1213 |
+
- type: ndcg_at_100
|
1214 |
+
value: 42.398
|
1215 |
+
- type: ndcg_at_1000
|
1216 |
+
value: 48.962
|
1217 |
+
- type: ndcg_at_3
|
1218 |
+
value: 43.29
|
1219 |
+
- type: ndcg_at_5
|
1220 |
+
value: 40.763
|
1221 |
+
- type: precision_at_1
|
1222 |
+
value: 61.75000000000001
|
1223 |
+
- type: precision_at_10
|
1224 |
+
value: 30.125
|
1225 |
+
- type: precision_at_100
|
1226 |
+
value: 9.53
|
1227 |
+
- type: precision_at_1000
|
1228 |
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value: 1.9619999999999997
|
1229 |
+
- type: precision_at_3
|
1230 |
+
value: 45.583
|
1231 |
+
- type: precision_at_5
|
1232 |
+
value: 38.95
|
1233 |
+
- type: recall_at_1
|
1234 |
+
value: 8.674
|
1235 |
+
- type: recall_at_10
|
1236 |
+
value: 23.122
|
1237 |
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- type: recall_at_100
|
1238 |
+
value: 47.46
|
1239 |
+
- type: recall_at_1000
|
1240 |
+
value: 67.662
|
1241 |
+
- type: recall_at_3
|
1242 |
+
value: 13.946
|
1243 |
+
- type: recall_at_5
|
1244 |
+
value: 17.768
|
1245 |
+
- task:
|
1246 |
+
type: Classification
|
1247 |
+
dataset:
|
1248 |
+
type: mteb/emotion
|
1249 |
+
name: MTEB EmotionClassification
|
1250 |
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config: default
|
1251 |
+
split: test
|
1252 |
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revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
|
1253 |
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metrics:
|
1254 |
+
- type: accuracy
|
1255 |
+
value: 46.86000000000001
|
1256 |
+
- type: f1
|
1257 |
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value: 41.343580452760776
|
1258 |
+
- task:
|
1259 |
+
type: Retrieval
|
1260 |
+
dataset:
|
1261 |
+
type: fever
|
1262 |
+
name: MTEB FEVER
|
1263 |
+
config: default
|
1264 |
+
split: test
|
1265 |
+
revision: None
|
1266 |
+
metrics:
|
1267 |
+
- type: map_at_1
|
1268 |
+
value: 36.609
|
1269 |
+
- type: map_at_10
|
1270 |
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value: 47.552
|
1271 |
+
- type: map_at_100
|
1272 |
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value: 48.283
|
1273 |
+
- type: map_at_1000
|
1274 |
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value: 48.321
|
1275 |
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- type: map_at_3
|
1276 |
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value: 44.869
|
1277 |
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- type: map_at_5
|
1278 |
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value: 46.509
|
1279 |
+
- type: mrr_at_1
|
1280 |
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value: 39.214
|
1281 |
+
- type: mrr_at_10
|
1282 |
+
value: 50.434999999999995
|
1283 |
+
- type: mrr_at_100
|
1284 |
+
value: 51.122
|
1285 |
+
- type: mrr_at_1000
|
1286 |
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value: 51.151
|
1287 |
+
- type: mrr_at_3
|
1288 |
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value: 47.735
|
1289 |
+
- type: mrr_at_5
|
1290 |
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value: 49.394
|
1291 |
+
- type: ndcg_at_1
|
1292 |
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value: 39.214
|
1293 |
+
- type: ndcg_at_10
|
1294 |
+
value: 53.52400000000001
|
1295 |
+
- type: ndcg_at_100
|
1296 |
+
value: 56.997
|
1297 |
+
- type: ndcg_at_1000
|
1298 |
+
value: 57.975
|
1299 |
+
- type: ndcg_at_3
|
1300 |
+
value: 48.173
|
1301 |
+
- type: ndcg_at_5
|
1302 |
+
value: 51.05800000000001
|
1303 |
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- type: precision_at_1
|
1304 |
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value: 39.214
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1305 |
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- type: precision_at_10
|
1306 |
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value: 7.573
|
1307 |
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- type: precision_at_100
|
1308 |
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value: 0.9440000000000001
|
1309 |
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- type: precision_at_1000
|
1310 |
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value: 0.104
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1311 |
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- type: precision_at_3
|
1312 |
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value: 19.782
|
1313 |
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- type: precision_at_5
|
1314 |
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value: 13.453000000000001
|
1315 |
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- type: recall_at_1
|
1316 |
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value: 36.609
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1317 |
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- type: recall_at_10
|
1318 |
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value: 69.247
|
1319 |
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- type: recall_at_100
|
1320 |
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value: 84.99600000000001
|
1321 |
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- type: recall_at_1000
|
1322 |
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value: 92.40899999999999
|
1323 |
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- type: recall_at_3
|
1324 |
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value: 54.856
|
1325 |
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- type: recall_at_5
|
1326 |
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value: 61.797000000000004
|
1327 |
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- task:
|
1328 |
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type: Retrieval
|
1329 |
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dataset:
|
1330 |
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type: fiqa
|
1331 |
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name: MTEB FiQA2018
|
1332 |
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config: default
|
1333 |
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split: test
|
1334 |
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revision: None
|
1335 |
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metrics:
|
1336 |
+
- type: map_at_1
|
1337 |
+
value: 16.466
|
1338 |
+
- type: map_at_10
|
1339 |
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value: 27.060000000000002
|
1340 |
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- type: map_at_100
|
1341 |
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value: 28.511999999999997
|
1342 |
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- type: map_at_1000
|
1343 |
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value: 28.693
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1344 |
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- type: map_at_3
|
1345 |
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value: 22.777
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1346 |
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- type: map_at_5
|
1347 |
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value: 25.086000000000002
|
1348 |
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|
1349 |
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value: 32.716
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1350 |
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- type: mrr_at_10
|
1351 |
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value: 41.593999999999994
|
1352 |
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- type: mrr_at_100
|
1353 |
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value: 42.370000000000005
|
1354 |
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- type: mrr_at_1000
|
1355 |
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value: 42.419000000000004
|
1356 |
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|
1357 |
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value: 38.143
|
1358 |
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- type: mrr_at_5
|
1359 |
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value: 40.288000000000004
|
1360 |
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- type: ndcg_at_1
|
1361 |
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value: 32.716
|
1362 |
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- type: ndcg_at_10
|
1363 |
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value: 34.795
|
1364 |
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- type: ndcg_at_100
|
1365 |
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value: 40.58
|
1366 |
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- type: ndcg_at_1000
|
1367 |
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value: 43.993
|
1368 |
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|
1369 |
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value: 29.573
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1370 |
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|
1371 |
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value: 31.583
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1372 |
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- type: precision_at_1
|
1373 |
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value: 32.716
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1374 |
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- type: precision_at_10
|
1375 |
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value: 9.937999999999999
|
1376 |
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- type: precision_at_100
|
1377 |
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value: 1.585
|
1378 |
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- type: precision_at_1000
|
1379 |
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value: 0.22
|
1380 |
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- type: precision_at_3
|
1381 |
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value: 19.496
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1382 |
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- type: precision_at_5
|
1383 |
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value: 15.247
|
1384 |
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- type: recall_at_1
|
1385 |
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value: 16.466
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1386 |
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- type: recall_at_10
|
1387 |
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value: 42.886
|
1388 |
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- type: recall_at_100
|
1389 |
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value: 64.724
|
1390 |
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- type: recall_at_1000
|
1391 |
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value: 85.347
|
1392 |
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- type: recall_at_3
|
1393 |
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value: 26.765
|
1394 |
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- type: recall_at_5
|
1395 |
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value: 33.603
|
1396 |
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- task:
|
1397 |
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type: Retrieval
|
1398 |
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dataset:
|
1399 |
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type: hotpotqa
|
1400 |
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name: MTEB HotpotQA
|
1401 |
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config: default
|
1402 |
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split: test
|
1403 |
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revision: None
|
1404 |
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metrics:
|
1405 |
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- type: map_at_1
|
1406 |
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value: 33.025
|
1407 |
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- type: map_at_10
|
1408 |
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value: 47.343
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1409 |
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|
1410 |
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value: 48.207
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1411 |
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1412 |
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value: 48.281
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1413 |
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|
1414 |
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value: 44.519
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1415 |
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|
1416 |
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value: 46.217000000000006
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1417 |
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|
1418 |
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value: 66.05
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1419 |
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|
1420 |
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value: 72.94699999999999
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1421 |
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|
1422 |
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value: 73.289
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1423 |
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|
1424 |
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value: 73.30499999999999
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1425 |
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|
1426 |
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value: 71.686
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1427 |
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|
1428 |
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value: 72.491
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1429 |
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|
1430 |
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value: 66.05
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1431 |
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|
1432 |
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value: 56.338
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1433 |
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|
1434 |
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value: 59.599999999999994
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1435 |
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- type: ndcg_at_1000
|
1436 |
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value: 61.138000000000005
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1437 |
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- type: ndcg_at_3
|
1438 |
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value: 52.034000000000006
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1439 |
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|
1440 |
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value: 54.352000000000004
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1441 |
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- type: precision_at_1
|
1442 |
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value: 66.05
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1443 |
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- type: precision_at_10
|
1444 |
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value: 11.693000000000001
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1445 |
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- type: precision_at_100
|
1446 |
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value: 1.425
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1447 |
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- type: precision_at_1000
|
1448 |
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value: 0.163
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1449 |
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- type: precision_at_3
|
1450 |
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value: 32.613
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1451 |
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- type: precision_at_5
|
1452 |
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value: 21.401999999999997
|
1453 |
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- type: recall_at_1
|
1454 |
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value: 33.025
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1455 |
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- type: recall_at_10
|
1456 |
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value: 58.467
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1457 |
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- type: recall_at_100
|
1458 |
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value: 71.242
|
1459 |
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- type: recall_at_1000
|
1460 |
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value: 81.452
|
1461 |
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- type: recall_at_3
|
1462 |
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value: 48.92
|
1463 |
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- type: recall_at_5
|
1464 |
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value: 53.504
|
1465 |
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- task:
|
1466 |
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type: Classification
|
1467 |
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dataset:
|
1468 |
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type: mteb/imdb
|
1469 |
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name: MTEB ImdbClassification
|
1470 |
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config: default
|
1471 |
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split: test
|
1472 |
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revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
|
1473 |
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metrics:
|
1474 |
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- type: accuracy
|
1475 |
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value: 75.5492
|
1476 |
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- type: ap
|
1477 |
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value: 69.42911637216271
|
1478 |
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- type: f1
|
1479 |
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value: 75.39113704261024
|
1480 |
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- task:
|
1481 |
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type: Retrieval
|
1482 |
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dataset:
|
1483 |
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type: msmarco
|
1484 |
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name: MTEB MSMARCO
|
1485 |
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config: default
|
1486 |
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split: dev
|
1487 |
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revision: None
|
1488 |
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metrics:
|
1489 |
+
- type: map_at_1
|
1490 |
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value: 23.173
|
1491 |
+
- type: map_at_10
|
1492 |
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value: 35.453
|
1493 |
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- type: map_at_100
|
1494 |
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value: 36.573
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1495 |
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- type: map_at_1000
|
1496 |
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value: 36.620999999999995
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1497 |
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- type: map_at_3
|
1498 |
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value: 31.655
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1499 |
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- type: map_at_5
|
1500 |
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value: 33.823
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1501 |
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- type: mrr_at_1
|
1502 |
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value: 23.868000000000002
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1503 |
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- type: mrr_at_10
|
1504 |
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value: 36.085
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1505 |
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- type: mrr_at_100
|
1506 |
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value: 37.15
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1507 |
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- type: mrr_at_1000
|
1508 |
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value: 37.193
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1509 |
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- type: mrr_at_3
|
1510 |
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value: 32.376
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1511 |
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- type: mrr_at_5
|
1512 |
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value: 34.501
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1513 |
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- type: ndcg_at_1
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1514 |
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value: 23.854
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1515 |
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- type: ndcg_at_10
|
1516 |
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value: 42.33
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1517 |
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- type: ndcg_at_100
|
1518 |
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value: 47.705999999999996
|
1519 |
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- type: ndcg_at_1000
|
1520 |
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value: 48.91
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1521 |
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|
1522 |
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value: 34.604
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1523 |
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- type: ndcg_at_5
|
1524 |
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value: 38.473
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1525 |
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- type: precision_at_1
|
1526 |
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value: 23.854
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1527 |
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- type: precision_at_10
|
1528 |
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value: 6.639
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1529 |
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- type: precision_at_100
|
1530 |
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value: 0.932
|
1531 |
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- type: precision_at_1000
|
1532 |
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value: 0.104
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1533 |
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- type: precision_at_3
|
1534 |
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value: 14.685
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1535 |
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- type: precision_at_5
|
1536 |
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value: 10.782
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1537 |
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- type: recall_at_1
|
1538 |
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value: 23.173
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1539 |
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- type: recall_at_10
|
1540 |
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value: 63.441
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1541 |
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- type: recall_at_100
|
1542 |
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value: 88.25
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1543 |
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- type: recall_at_1000
|
1544 |
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value: 97.438
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1545 |
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- type: recall_at_3
|
1546 |
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value: 42.434
|
1547 |
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- type: recall_at_5
|
1548 |
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value: 51.745
|
1549 |
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- task:
|
1550 |
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type: Classification
|
1551 |
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dataset:
|
1552 |
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type: mteb/mtop_domain
|
1553 |
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name: MTEB MTOPDomainClassification (en)
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1554 |
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config: en
|
1555 |
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split: test
|
1556 |
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revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
|
1557 |
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metrics:
|
1558 |
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- type: accuracy
|
1559 |
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value: 92.05426356589147
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1560 |
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- type: f1
|
1561 |
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value: 91.88068588063942
|
1562 |
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- task:
|
1563 |
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type: Classification
|
1564 |
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dataset:
|
1565 |
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type: mteb/mtop_intent
|
1566 |
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name: MTEB MTOPIntentClassification (en)
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1567 |
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config: en
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1568 |
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split: test
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1569 |
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revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
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1570 |
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metrics:
|
1571 |
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- type: accuracy
|
1572 |
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value: 73.23985408116735
|
1573 |
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- type: f1
|
1574 |
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value: 55.858906745287506
|
1575 |
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- task:
|
1576 |
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type: Classification
|
1577 |
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dataset:
|
1578 |
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type: mteb/amazon_massive_intent
|
1579 |
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name: MTEB MassiveIntentClassification (en)
|
1580 |
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config: en
|
1581 |
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split: test
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1582 |
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revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
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1583 |
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metrics:
|
1584 |
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- type: accuracy
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1585 |
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value: 72.21923335574984
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1586 |
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- type: f1
|
1587 |
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value: 70.0174116204253
|
1588 |
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- task:
|
1589 |
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type: Classification
|
1590 |
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dataset:
|
1591 |
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type: mteb/amazon_massive_scenario
|
1592 |
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name: MTEB MassiveScenarioClassification (en)
|
1593 |
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config: en
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1594 |
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split: test
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1595 |
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revision: 7d571f92784cd94a019292a1f45445077d0ef634
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1596 |
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metrics:
|
1597 |
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- type: accuracy
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1598 |
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value: 75.77673167451245
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1599 |
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- type: f1
|
1600 |
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value: 75.44811354778666
|
1601 |
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- task:
|
1602 |
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type: Clustering
|
1603 |
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dataset:
|
1604 |
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type: mteb/medrxiv-clustering-p2p
|
1605 |
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name: MTEB MedrxivClusteringP2P
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1606 |
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config: default
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1607 |
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split: test
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1608 |
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revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
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1609 |
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metrics:
|
1610 |
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- type: v_measure
|
1611 |
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value: 31.340414710728737
|
1612 |
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- task:
|
1613 |
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type: Clustering
|
1614 |
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dataset:
|
1615 |
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type: mteb/medrxiv-clustering-s2s
|
1616 |
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name: MTEB MedrxivClusteringS2S
|
1617 |
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config: default
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1618 |
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split: test
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1619 |
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revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
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1620 |
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metrics:
|
1621 |
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- type: v_measure
|
1622 |
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value: 28.196676760061578
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1623 |
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- task:
|
1624 |
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type: Reranking
|
1625 |
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dataset:
|
1626 |
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type: mteb/mind_small
|
1627 |
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name: MTEB MindSmallReranking
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1628 |
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config: default
|
1629 |
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split: test
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1630 |
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revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
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1631 |
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metrics:
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1632 |
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|
1633 |
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value: 29.564149683482206
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1634 |
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|
1635 |
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value: 30.28995474250486
|
1636 |
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- task:
|
1637 |
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1638 |
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dataset:
|
1639 |
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type: nfcorpus
|
1640 |
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name: MTEB NFCorpus
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1641 |
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config: default
|
1642 |
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split: test
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1643 |
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revision: None
|
1644 |
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metrics:
|
1645 |
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- type: map_at_1
|
1646 |
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value: 5.93
|
1647 |
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|
1648 |
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value: 12.828000000000001
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1649 |
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1650 |
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1652 |
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1653 |
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1654 |
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value: 9.727
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1655 |
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1656 |
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1657 |
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1658 |
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1659 |
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1660 |
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1661 |
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1662 |
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1663 |
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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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value: 30.164
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1675 |
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1676 |
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value: 38.756
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1678 |
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1680 |
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value: 38.415
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1681 |
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1682 |
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value: 47.678
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1683 |
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1684 |
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value: 24.365000000000002
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1685 |
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1686 |
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value: 7.344
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1687 |
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1688 |
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value: 1.994
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1689 |
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1690 |
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value: 38.184000000000005
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1691 |
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- type: precision_at_5
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1692 |
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value: 33.003
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1693 |
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- type: recall_at_1
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1694 |
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value: 5.93
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1695 |
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- type: recall_at_10
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1696 |
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value: 16.239
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1697 |
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1698 |
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value: 28.782999999999998
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1699 |
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- type: recall_at_1000
|
1700 |
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value: 60.11
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1701 |
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- type: recall_at_3
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1702 |
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value: 10.700999999999999
|
1703 |
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- type: recall_at_5
|
1704 |
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value: 13.584
|
1705 |
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- task:
|
1706 |
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type: Retrieval
|
1707 |
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dataset:
|
1708 |
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type: nq
|
1709 |
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name: MTEB NQ
|
1710 |
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config: default
|
1711 |
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split: test
|
1712 |
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revision: None
|
1713 |
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metrics:
|
1714 |
+
- type: map_at_1
|
1715 |
+
value: 36.163000000000004
|
1716 |
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- type: map_at_10
|
1717 |
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value: 51.520999999999994
|
1718 |
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- type: map_at_100
|
1719 |
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value: 52.449
|
1720 |
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- type: map_at_1000
|
1721 |
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value: 52.473000000000006
|
1722 |
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- type: map_at_3
|
1723 |
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value: 47.666
|
1724 |
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- type: map_at_5
|
1725 |
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value: 50.043000000000006
|
1726 |
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- type: mrr_at_1
|
1727 |
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value: 40.266999999999996
|
1728 |
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- type: mrr_at_10
|
1729 |
+
value: 54.074
|
1730 |
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- type: mrr_at_100
|
1731 |
+
value: 54.722
|
1732 |
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- type: mrr_at_1000
|
1733 |
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value: 54.739000000000004
|
1734 |
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- type: mrr_at_3
|
1735 |
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value: 51.043000000000006
|
1736 |
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- type: mrr_at_5
|
1737 |
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value: 52.956
|
1738 |
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- type: ndcg_at_1
|
1739 |
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value: 40.238
|
1740 |
+
- type: ndcg_at_10
|
1741 |
+
value: 58.73199999999999
|
1742 |
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- type: ndcg_at_100
|
1743 |
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value: 62.470000000000006
|
1744 |
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- type: ndcg_at_1000
|
1745 |
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value: 63.083999999999996
|
1746 |
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- type: ndcg_at_3
|
1747 |
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value: 51.672
|
1748 |
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- type: ndcg_at_5
|
1749 |
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value: 55.564
|
1750 |
+
- type: precision_at_1
|
1751 |
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value: 40.238
|
1752 |
+
- type: precision_at_10
|
1753 |
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value: 9.279
|
1754 |
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- type: precision_at_100
|
1755 |
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value: 1.139
|
1756 |
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- type: precision_at_1000
|
1757 |
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value: 0.12
|
1758 |
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- type: precision_at_3
|
1759 |
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value: 23.078000000000003
|
1760 |
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- type: precision_at_5
|
1761 |
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value: 16.176
|
1762 |
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- type: recall_at_1
|
1763 |
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value: 36.163000000000004
|
1764 |
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- type: recall_at_10
|
1765 |
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value: 77.88199999999999
|
1766 |
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- type: recall_at_100
|
1767 |
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value: 93.83399999999999
|
1768 |
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- type: recall_at_1000
|
1769 |
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value: 98.465
|
1770 |
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- type: recall_at_3
|
1771 |
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value: 59.857000000000006
|
1772 |
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- type: recall_at_5
|
1773 |
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value: 68.73599999999999
|
1774 |
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- task:
|
1775 |
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type: Retrieval
|
1776 |
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dataset:
|
1777 |
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type: quora
|
1778 |
+
name: MTEB QuoraRetrieval
|
1779 |
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config: default
|
1780 |
+
split: test
|
1781 |
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revision: None
|
1782 |
+
metrics:
|
1783 |
+
- type: map_at_1
|
1784 |
+
value: 70.344
|
1785 |
+
- type: map_at_10
|
1786 |
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value: 83.907
|
1787 |
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- type: map_at_100
|
1788 |
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value: 84.536
|
1789 |
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- type: map_at_1000
|
1790 |
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value: 84.557
|
1791 |
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- type: map_at_3
|
1792 |
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value: 80.984
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1793 |
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- type: map_at_5
|
1794 |
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value: 82.844
|
1795 |
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- type: mrr_at_1
|
1796 |
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value: 81.02000000000001
|
1797 |
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- type: mrr_at_10
|
1798 |
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value: 87.158
|
1799 |
+
- type: mrr_at_100
|
1800 |
+
value: 87.268
|
1801 |
+
- type: mrr_at_1000
|
1802 |
+
value: 87.26899999999999
|
1803 |
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- type: mrr_at_3
|
1804 |
+
value: 86.17
|
1805 |
+
- type: mrr_at_5
|
1806 |
+
value: 86.87
|
1807 |
+
- type: ndcg_at_1
|
1808 |
+
value: 81.02000000000001
|
1809 |
+
- type: ndcg_at_10
|
1810 |
+
value: 87.70700000000001
|
1811 |
+
- type: ndcg_at_100
|
1812 |
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value: 89.004
|
1813 |
+
- type: ndcg_at_1000
|
1814 |
+
value: 89.139
|
1815 |
+
- type: ndcg_at_3
|
1816 |
+
value: 84.841
|
1817 |
+
- type: ndcg_at_5
|
1818 |
+
value: 86.455
|
1819 |
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- type: precision_at_1
|
1820 |
+
value: 81.02000000000001
|
1821 |
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- type: precision_at_10
|
1822 |
+
value: 13.248999999999999
|
1823 |
+
- type: precision_at_100
|
1824 |
+
value: 1.516
|
1825 |
+
- type: precision_at_1000
|
1826 |
+
value: 0.156
|
1827 |
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- type: precision_at_3
|
1828 |
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value: 36.963
|
1829 |
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- type: precision_at_5
|
1830 |
+
value: 24.33
|
1831 |
+
- type: recall_at_1
|
1832 |
+
value: 70.344
|
1833 |
+
- type: recall_at_10
|
1834 |
+
value: 94.75099999999999
|
1835 |
+
- type: recall_at_100
|
1836 |
+
value: 99.30499999999999
|
1837 |
+
- type: recall_at_1000
|
1838 |
+
value: 99.928
|
1839 |
+
- type: recall_at_3
|
1840 |
+
value: 86.506
|
1841 |
+
- type: recall_at_5
|
1842 |
+
value: 91.083
|
1843 |
+
- task:
|
1844 |
+
type: Clustering
|
1845 |
+
dataset:
|
1846 |
+
type: mteb/reddit-clustering
|
1847 |
+
name: MTEB RedditClustering
|
1848 |
+
config: default
|
1849 |
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split: test
|
1850 |
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revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
|
1851 |
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metrics:
|
1852 |
+
- type: v_measure
|
1853 |
+
value: 42.873718018378305
|
1854 |
+
- task:
|
1855 |
+
type: Clustering
|
1856 |
+
dataset:
|
1857 |
+
type: mteb/reddit-clustering-p2p
|
1858 |
+
name: MTEB RedditClusteringP2P
|
1859 |
+
config: default
|
1860 |
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split: test
|
1861 |
+
revision: 282350215ef01743dc01b456c7f5241fa8937f16
|
1862 |
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metrics:
|
1863 |
+
- type: v_measure
|
1864 |
+
value: 56.39477366450528
|
1865 |
+
- task:
|
1866 |
+
type: Retrieval
|
1867 |
+
dataset:
|
1868 |
+
type: scidocs
|
1869 |
+
name: MTEB SCIDOCS
|
1870 |
+
config: default
|
1871 |
+
split: test
|
1872 |
+
revision: None
|
1873 |
+
metrics:
|
1874 |
+
- type: map_at_1
|
1875 |
+
value: 3.868
|
1876 |
+
- type: map_at_10
|
1877 |
+
value: 9.611
|
1878 |
+
- type: map_at_100
|
1879 |
+
value: 11.087
|
1880 |
+
- type: map_at_1000
|
1881 |
+
value: 11.332
|
1882 |
+
- type: map_at_3
|
1883 |
+
value: 6.813
|
1884 |
+
- type: map_at_5
|
1885 |
+
value: 8.233
|
1886 |
+
- type: mrr_at_1
|
1887 |
+
value: 19.0
|
1888 |
+
- type: mrr_at_10
|
1889 |
+
value: 28.457
|
1890 |
+
- type: mrr_at_100
|
1891 |
+
value: 29.613
|
1892 |
+
- type: mrr_at_1000
|
1893 |
+
value: 29.695
|
1894 |
+
- type: mrr_at_3
|
1895 |
+
value: 25.55
|
1896 |
+
- type: mrr_at_5
|
1897 |
+
value: 27.29
|
1898 |
+
- type: ndcg_at_1
|
1899 |
+
value: 19.0
|
1900 |
+
- type: ndcg_at_10
|
1901 |
+
value: 16.419
|
1902 |
+
- type: ndcg_at_100
|
1903 |
+
value: 22.817999999999998
|
1904 |
+
- type: ndcg_at_1000
|
1905 |
+
value: 27.72
|
1906 |
+
- type: ndcg_at_3
|
1907 |
+
value: 15.379000000000001
|
1908 |
+
- type: ndcg_at_5
|
1909 |
+
value: 13.645
|
1910 |
+
- type: precision_at_1
|
1911 |
+
value: 19.0
|
1912 |
+
- type: precision_at_10
|
1913 |
+
value: 8.540000000000001
|
1914 |
+
- type: precision_at_100
|
1915 |
+
value: 1.7819999999999998
|
1916 |
+
- type: precision_at_1000
|
1917 |
+
value: 0.297
|
1918 |
+
- type: precision_at_3
|
1919 |
+
value: 14.267
|
1920 |
+
- type: precision_at_5
|
1921 |
+
value: 12.04
|
1922 |
+
- type: recall_at_1
|
1923 |
+
value: 3.868
|
1924 |
+
- type: recall_at_10
|
1925 |
+
value: 17.288
|
1926 |
+
- type: recall_at_100
|
1927 |
+
value: 36.144999999999996
|
1928 |
+
- type: recall_at_1000
|
1929 |
+
value: 60.199999999999996
|
1930 |
+
- type: recall_at_3
|
1931 |
+
value: 8.688
|
1932 |
+
- type: recall_at_5
|
1933 |
+
value: 12.198
|
1934 |
+
- task:
|
1935 |
+
type: STS
|
1936 |
+
dataset:
|
1937 |
+
type: mteb/sickr-sts
|
1938 |
+
name: MTEB SICK-R
|
1939 |
+
config: default
|
1940 |
+
split: test
|
1941 |
+
revision: a6ea5a8cab320b040a23452cc28066d9beae2cee
|
1942 |
+
metrics:
|
1943 |
+
- type: cos_sim_pearson
|
1944 |
+
value: 83.96614722598582
|
1945 |
+
- type: cos_sim_spearman
|
1946 |
+
value: 78.9003023008781
|
1947 |
+
- type: euclidean_pearson
|
1948 |
+
value: 81.01829384436505
|
1949 |
+
- type: euclidean_spearman
|
1950 |
+
value: 78.93248416788914
|
1951 |
+
- type: manhattan_pearson
|
1952 |
+
value: 81.1665428926402
|
1953 |
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- type: manhattan_spearman
|
1954 |
+
value: 78.93264116287453
|
1955 |
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- task:
|
1956 |
+
type: STS
|
1957 |
+
dataset:
|
1958 |
+
type: mteb/sts12-sts
|
1959 |
+
name: MTEB STS12
|
1960 |
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config: default
|
1961 |
+
split: test
|
1962 |
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revision: a0d554a64d88156834ff5ae9920b964011b16384
|
1963 |
+
metrics:
|
1964 |
+
- type: cos_sim_pearson
|
1965 |
+
value: 83.54613363895993
|
1966 |
+
- type: cos_sim_spearman
|
1967 |
+
value: 75.1883451602451
|
1968 |
+
- type: euclidean_pearson
|
1969 |
+
value: 79.70320886899894
|
1970 |
+
- type: euclidean_spearman
|
1971 |
+
value: 74.5917140136796
|
1972 |
+
- type: manhattan_pearson
|
1973 |
+
value: 79.82157067185999
|
1974 |
+
- type: manhattan_spearman
|
1975 |
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value: 74.74185720594735
|
1976 |
+
- task:
|
1977 |
+
type: STS
|
1978 |
+
dataset:
|
1979 |
+
type: mteb/sts13-sts
|
1980 |
+
name: MTEB STS13
|
1981 |
+
config: default
|
1982 |
+
split: test
|
1983 |
+
revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
|
1984 |
+
metrics:
|
1985 |
+
- type: cos_sim_pearson
|
1986 |
+
value: 81.30430156721782
|
1987 |
+
- type: cos_sim_spearman
|
1988 |
+
value: 81.79962989974364
|
1989 |
+
- type: euclidean_pearson
|
1990 |
+
value: 80.89058823224924
|
1991 |
+
- type: euclidean_spearman
|
1992 |
+
value: 81.35929372984597
|
1993 |
+
- type: manhattan_pearson
|
1994 |
+
value: 81.12204370487478
|
1995 |
+
- type: manhattan_spearman
|
1996 |
+
value: 81.6248963282232
|
1997 |
+
- task:
|
1998 |
+
type: STS
|
1999 |
+
dataset:
|
2000 |
+
type: mteb/sts14-sts
|
2001 |
+
name: MTEB STS14
|
2002 |
+
config: default
|
2003 |
+
split: test
|
2004 |
+
revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
|
2005 |
+
metrics:
|
2006 |
+
- type: cos_sim_pearson
|
2007 |
+
value: 81.13064504403134
|
2008 |
+
- type: cos_sim_spearman
|
2009 |
+
value: 78.48371403924872
|
2010 |
+
- type: euclidean_pearson
|
2011 |
+
value: 80.16794919665591
|
2012 |
+
- type: euclidean_spearman
|
2013 |
+
value: 78.29216082221699
|
2014 |
+
- type: manhattan_pearson
|
2015 |
+
value: 80.22308565207301
|
2016 |
+
- type: manhattan_spearman
|
2017 |
+
value: 78.37829229948022
|
2018 |
+
- task:
|
2019 |
+
type: STS
|
2020 |
+
dataset:
|
2021 |
+
type: mteb/sts15-sts
|
2022 |
+
name: MTEB STS15
|
2023 |
+
config: default
|
2024 |
+
split: test
|
2025 |
+
revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
|
2026 |
+
metrics:
|
2027 |
+
- type: cos_sim_pearson
|
2028 |
+
value: 86.52918899541099
|
2029 |
+
- type: cos_sim_spearman
|
2030 |
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value: 87.49276894673142
|
2031 |
+
- type: euclidean_pearson
|
2032 |
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value: 86.77440570164254
|
2033 |
+
- type: euclidean_spearman
|
2034 |
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value: 87.5753295736756
|
2035 |
+
- type: manhattan_pearson
|
2036 |
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value: 86.86098573892133
|
2037 |
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- type: manhattan_spearman
|
2038 |
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value: 87.65848591821947
|
2039 |
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- task:
|
2040 |
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type: STS
|
2041 |
+
dataset:
|
2042 |
+
type: mteb/sts16-sts
|
2043 |
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name: MTEB STS16
|
2044 |
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config: default
|
2045 |
+
split: test
|
2046 |
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revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
|
2047 |
+
metrics:
|
2048 |
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- type: cos_sim_pearson
|
2049 |
+
value: 82.86805307244882
|
2050 |
+
- type: cos_sim_spearman
|
2051 |
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value: 84.58066253757511
|
2052 |
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- type: euclidean_pearson
|
2053 |
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value: 84.38377000876991
|
2054 |
+
- type: euclidean_spearman
|
2055 |
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value: 85.1837278784528
|
2056 |
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- type: manhattan_pearson
|
2057 |
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value: 84.41903291363842
|
2058 |
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- type: manhattan_spearman
|
2059 |
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value: 85.19023736251052
|
2060 |
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- task:
|
2061 |
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type: STS
|
2062 |
+
dataset:
|
2063 |
+
type: mteb/sts17-crosslingual-sts
|
2064 |
+
name: MTEB STS17 (en-en)
|
2065 |
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config: en-en
|
2066 |
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split: test
|
2067 |
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revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
|
2068 |
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metrics:
|
2069 |
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- type: cos_sim_pearson
|
2070 |
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value: 86.77218560282436
|
2071 |
+
- type: cos_sim_spearman
|
2072 |
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value: 87.94243515296604
|
2073 |
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- type: euclidean_pearson
|
2074 |
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value: 88.22800939214864
|
2075 |
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- type: euclidean_spearman
|
2076 |
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value: 87.91106839439841
|
2077 |
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- type: manhattan_pearson
|
2078 |
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value: 88.17063269848741
|
2079 |
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- type: manhattan_spearman
|
2080 |
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value: 87.72751904126062
|
2081 |
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- task:
|
2082 |
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type: STS
|
2083 |
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dataset:
|
2084 |
+
type: mteb/sts22-crosslingual-sts
|
2085 |
+
name: MTEB STS22 (en)
|
2086 |
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config: en
|
2087 |
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split: test
|
2088 |
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revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80
|
2089 |
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metrics:
|
2090 |
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- type: cos_sim_pearson
|
2091 |
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value: 60.40731554300387
|
2092 |
+
- type: cos_sim_spearman
|
2093 |
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value: 63.76300532966479
|
2094 |
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- type: euclidean_pearson
|
2095 |
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value: 62.94727878229085
|
2096 |
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- type: euclidean_spearman
|
2097 |
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value: 63.678039531461216
|
2098 |
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- type: manhattan_pearson
|
2099 |
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value: 63.00661039863549
|
2100 |
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- type: manhattan_spearman
|
2101 |
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value: 63.6282591984376
|
2102 |
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- task:
|
2103 |
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type: STS
|
2104 |
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dataset:
|
2105 |
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type: mteb/stsbenchmark-sts
|
2106 |
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name: MTEB STSBenchmark
|
2107 |
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config: default
|
2108 |
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split: test
|
2109 |
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revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
|
2110 |
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metrics:
|
2111 |
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- type: cos_sim_pearson
|
2112 |
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value: 84.92731569745344
|
2113 |
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- type: cos_sim_spearman
|
2114 |
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value: 86.36336704300167
|
2115 |
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- type: euclidean_pearson
|
2116 |
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value: 86.09122224841195
|
2117 |
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- type: euclidean_spearman
|
2118 |
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value: 86.2116149319238
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- type: manhattan_pearson
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|
2121 |
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- type: manhattan_spearman
|
2122 |
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value: 86.2022069635119
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2123 |
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- task:
|
2124 |
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type: Reranking
|
2125 |
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dataset:
|
2126 |
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type: mteb/scidocs-reranking
|
2127 |
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name: MTEB SciDocsRR
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2128 |
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config: default
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2129 |
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split: test
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2130 |
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revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
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2131 |
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metrics:
|
2132 |
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- type: map
|
2133 |
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value: 79.75976311752326
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- type: mrr
|
2135 |
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2136 |
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- task:
|
2137 |
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type: Retrieval
|
2138 |
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dataset:
|
2139 |
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type: scifact
|
2140 |
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name: MTEB SciFact
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2141 |
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config: default
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2142 |
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split: test
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2143 |
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revision: None
|
2144 |
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metrics:
|
2145 |
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- type: map_at_1
|
2146 |
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value: 51.193999999999996
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2147 |
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2148 |
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2149 |
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2150 |
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2154 |
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2155 |
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2156 |
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2157 |
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2158 |
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2159 |
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2160 |
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2161 |
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2163 |
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2164 |
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2165 |
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2166 |
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2167 |
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2168 |
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2169 |
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2170 |
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2171 |
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2172 |
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2173 |
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2174 |
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2175 |
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2176 |
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2177 |
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2178 |
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2179 |
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2180 |
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2181 |
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2183 |
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2184 |
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value: 8.667
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2185 |
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- type: precision_at_100
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2186 |
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value: 1.04
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2187 |
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- type: precision_at_1000
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2189 |
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2190 |
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value: 24.556
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2191 |
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- type: precision_at_5
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2192 |
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value: 15.6
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2193 |
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- type: recall_at_1
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2194 |
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2195 |
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2199 |
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- type: recall_at_1000
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2200 |
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2201 |
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- type: recall_at_3
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2202 |
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value: 67.994
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2203 |
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- type: recall_at_5
|
2204 |
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value: 71.14399999999999
|
2205 |
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- task:
|
2206 |
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type: PairClassification
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2207 |
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dataset:
|
2208 |
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type: mteb/sprintduplicatequestions-pairclassification
|
2209 |
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name: MTEB SprintDuplicateQuestions
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2210 |
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config: default
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2211 |
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split: test
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2212 |
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revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
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2213 |
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metrics:
|
2214 |
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- type: cos_sim_accuracy
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2215 |
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value: 99.81485148514851
|
2216 |
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- type: cos_sim_ap
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2222 |
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- type: cos_sim_recall
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2223 |
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value: 88.4
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2224 |
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2225 |
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- type: dot_precision
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2232 |
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- type: dot_recall
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2234 |
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- type: euclidean_accuracy
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2235 |
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- type: euclidean_ap
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2238 |
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- type: euclidean_f1
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2240 |
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- type: euclidean_precision
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2241 |
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2242 |
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- type: euclidean_recall
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2243 |
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value: 92.7
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2244 |
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- type: manhattan_accuracy
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2245 |
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value: 99.81782178217821
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2246 |
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- type: manhattan_ap
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2248 |
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- type: manhattan_f1
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2250 |
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- type: manhattan_precision
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2251 |
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value: 90.23668639053254
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2252 |
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- type: manhattan_recall
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2253 |
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value: 91.5
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2254 |
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- type: max_accuracy
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2255 |
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value: 99.81980198019802
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2256 |
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- type: max_ap
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2257 |
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2258 |
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- type: max_f1
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2259 |
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value: 91.06090373280944
|
2260 |
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- task:
|
2261 |
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type: Clustering
|
2262 |
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dataset:
|
2263 |
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type: mteb/stackexchange-clustering
|
2264 |
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name: MTEB StackExchangeClustering
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2265 |
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config: default
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2266 |
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split: test
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2267 |
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revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
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2268 |
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metrics:
|
2269 |
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- type: v_measure
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2270 |
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value: 59.08045614613064
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2271 |
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- task:
|
2272 |
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type: Clustering
|
2273 |
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dataset:
|
2274 |
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type: mteb/stackexchange-clustering-p2p
|
2275 |
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name: MTEB StackExchangeClusteringP2P
|
2276 |
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config: default
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2277 |
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split: test
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2278 |
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revision: 815ca46b2622cec33ccafc3735d572c266efdb44
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2279 |
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metrics:
|
2280 |
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- type: v_measure
|
2281 |
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value: 30.297802606804748
|
2282 |
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- task:
|
2283 |
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type: Reranking
|
2284 |
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dataset:
|
2285 |
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type: mteb/stackoverflowdupquestions-reranking
|
2286 |
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name: MTEB StackOverflowDupQuestions
|
2287 |
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config: default
|
2288 |
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split: test
|
2289 |
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revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
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2290 |
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metrics:
|
2291 |
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- type: map
|
2292 |
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value: 49.12801740706292
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2293 |
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- type: mrr
|
2294 |
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value: 50.05592956879722
|
2295 |
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- task:
|
2296 |
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type: Summarization
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2297 |
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dataset:
|
2298 |
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type: mteb/summeval
|
2299 |
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name: MTEB SummEval
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2300 |
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2301 |
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split: test
|
2302 |
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revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
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2303 |
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metrics:
|
2304 |
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- type: cos_sim_pearson
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2305 |
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value: 23.380995453661917
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2306 |
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- type: cos_sim_spearman
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2307 |
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value: 24.941761858688917
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2308 |
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- type: dot_pearson
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2309 |
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2310 |
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- type: dot_spearman
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2311 |
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2312 |
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- task:
|
2313 |
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type: Retrieval
|
2314 |
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dataset:
|
2315 |
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type: trec-covid
|
2316 |
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name: MTEB TRECCOVID
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2317 |
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config: default
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2318 |
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split: test
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2319 |
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revision: None
|
2320 |
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metrics:
|
2321 |
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- type: map_at_1
|
2322 |
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value: 0.243
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2323 |
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- type: map_at_10
|
2324 |
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value: 1.886
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2325 |
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2326 |
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value: 10.040000000000001
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2327 |
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- type: map_at_1000
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2328 |
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value: 23.768
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2329 |
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- type: map_at_3
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2330 |
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value: 0.674
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2331 |
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2332 |
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value: 1.079
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2333 |
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2334 |
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value: 88.0
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2335 |
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2336 |
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value: 93.667
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2337 |
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- type: mrr_at_100
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2338 |
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value: 93.667
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2339 |
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- type: mrr_at_1000
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2340 |
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value: 93.667
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2341 |
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2342 |
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value: 93.667
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2343 |
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- type: mrr_at_5
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2344 |
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value: 93.667
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2345 |
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- type: ndcg_at_1
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2346 |
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value: 83.0
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2347 |
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2348 |
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value: 76.777
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2349 |
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- type: ndcg_at_100
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2350 |
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value: 55.153
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2351 |
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- type: ndcg_at_1000
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2352 |
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value: 47.912
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2353 |
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- type: ndcg_at_3
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2354 |
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value: 81.358
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2355 |
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- type: ndcg_at_5
|
2356 |
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value: 80.74799999999999
|
2357 |
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- type: precision_at_1
|
2358 |
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value: 88.0
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2359 |
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2360 |
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value: 80.80000000000001
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2361 |
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- type: precision_at_100
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2362 |
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value: 56.02
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2363 |
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- type: precision_at_1000
|
2364 |
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value: 21.51
|
2365 |
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- type: precision_at_3
|
2366 |
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value: 86.0
|
2367 |
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- type: precision_at_5
|
2368 |
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value: 86.0
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2369 |
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- type: recall_at_1
|
2370 |
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value: 0.243
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2371 |
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- type: recall_at_10
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2372 |
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value: 2.0869999999999997
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2373 |
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- type: recall_at_100
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2374 |
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value: 13.014000000000001
|
2375 |
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- type: recall_at_1000
|
2376 |
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value: 44.433
|
2377 |
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- type: recall_at_3
|
2378 |
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value: 0.6910000000000001
|
2379 |
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- type: recall_at_5
|
2380 |
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value: 1.1440000000000001
|
2381 |
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- task:
|
2382 |
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type: Retrieval
|
2383 |
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dataset:
|
2384 |
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type: webis-touche2020
|
2385 |
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name: MTEB Touche2020
|
2386 |
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config: default
|
2387 |
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split: test
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2388 |
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revision: None
|
2389 |
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metrics:
|
2390 |
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- type: map_at_1
|
2391 |
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value: 3.066
|
2392 |
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- type: map_at_10
|
2393 |
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value: 10.615
|
2394 |
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|
2395 |
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value: 16.463
|
2396 |
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- type: map_at_1000
|
2397 |
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value: 17.815
|
2398 |
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|
2399 |
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value: 5.7860000000000005
|
2400 |
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- type: map_at_5
|
2401 |
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value: 7.353999999999999
|
2402 |
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- type: mrr_at_1
|
2403 |
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value: 38.775999999999996
|
2404 |
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- type: mrr_at_10
|
2405 |
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value: 53.846000000000004
|
2406 |
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- type: mrr_at_100
|
2407 |
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value: 54.37
|
2408 |
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- type: mrr_at_1000
|
2409 |
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value: 54.37
|
2410 |
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- type: mrr_at_3
|
2411 |
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value: 48.980000000000004
|
2412 |
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- type: mrr_at_5
|
2413 |
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value: 51.735
|
2414 |
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- type: ndcg_at_1
|
2415 |
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value: 34.694
|
2416 |
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- type: ndcg_at_10
|
2417 |
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value: 26.811
|
2418 |
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- type: ndcg_at_100
|
2419 |
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value: 37.342999999999996
|
2420 |
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- type: ndcg_at_1000
|
2421 |
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value: 47.964
|
2422 |
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- type: ndcg_at_3
|
2423 |
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value: 30.906
|
2424 |
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|
2425 |
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value: 27.77
|
2426 |
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- type: precision_at_1
|
2427 |
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value: 38.775999999999996
|
2428 |
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|
2429 |
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value: 23.878
|
2430 |
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- type: precision_at_100
|
2431 |
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value: 7.632999999999999
|
2432 |
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- type: precision_at_1000
|
2433 |
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value: 1.469
|
2434 |
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|
2435 |
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value: 31.973000000000003
|
2436 |
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- type: precision_at_5
|
2437 |
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value: 26.939
|
2438 |
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- type: recall_at_1
|
2439 |
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value: 3.066
|
2440 |
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- type: recall_at_10
|
2441 |
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value: 17.112
|
2442 |
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- type: recall_at_100
|
2443 |
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value: 47.723
|
2444 |
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- type: recall_at_1000
|
2445 |
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value: 79.50500000000001
|
2446 |
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- type: recall_at_3
|
2447 |
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value: 6.825
|
2448 |
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- type: recall_at_5
|
2449 |
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value: 9.584
|
2450 |
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- task:
|
2451 |
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type: Classification
|
2452 |
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dataset:
|
2453 |
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type: mteb/toxic_conversations_50k
|
2454 |
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name: MTEB ToxicConversationsClassification
|
2455 |
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config: default
|
2456 |
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split: test
|
2457 |
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|
2458 |
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metrics:
|
2459 |
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- type: accuracy
|
2460 |
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value: 72.76460000000002
|
2461 |
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- type: ap
|
2462 |
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value: 14.944240012137053
|
2463 |
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- type: f1
|
2464 |
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value: 55.89805777266571
|
2465 |
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- task:
|
2466 |
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type: Classification
|
2467 |
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dataset:
|
2468 |
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type: mteb/tweet_sentiment_extraction
|
2469 |
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name: MTEB TweetSentimentExtractionClassification
|
2470 |
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config: default
|
2471 |
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split: test
|
2472 |
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|
2473 |
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metrics:
|
2474 |
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- type: accuracy
|
2475 |
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value: 63.30503678551217
|
2476 |
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- type: f1
|
2477 |
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value: 63.57492701921179
|
2478 |
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- task:
|
2479 |
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type: Clustering
|
2480 |
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dataset:
|
2481 |
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type: mteb/twentynewsgroups-clustering
|
2482 |
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name: MTEB TwentyNewsgroupsClustering
|
2483 |
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config: default
|
2484 |
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split: test
|
2485 |
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2486 |
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metrics:
|
2487 |
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- type: v_measure
|
2488 |
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value: 37.51066495006874
|
2489 |
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- task:
|
2490 |
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type: PairClassification
|
2491 |
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dataset:
|
2492 |
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type: mteb/twittersemeval2015-pairclassification
|
2493 |
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name: MTEB TwitterSemEval2015
|
2494 |
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config: default
|
2495 |
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split: test
|
2496 |
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|
2497 |
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metrics:
|
2498 |
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- type: cos_sim_accuracy
|
2499 |
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value: 86.07021517553794
|
2500 |
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- type: cos_sim_ap
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2501 |
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value: 74.15520712370555
|
2502 |
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2503 |
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value: 68.64321608040201
|
2504 |
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- type: cos_sim_precision
|
2505 |
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value: 65.51558752997602
|
2506 |
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- type: cos_sim_recall
|
2507 |
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value: 72.0844327176781
|
2508 |
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- type: dot_accuracy
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value: 80.23484532395541
|
2510 |
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2511 |
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|
2512 |
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- type: dot_f1
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2514 |
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- type: dot_precision
|
2515 |
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|
2516 |
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- type: dot_recall
|
2517 |
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value: 62.532981530343015
|
2518 |
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- type: euclidean_accuracy
|
2519 |
+
value: 86.04637301066937
|
2520 |
+
- type: euclidean_ap
|
2521 |
+
value: 73.85333854233123
|
2522 |
+
- type: euclidean_f1
|
2523 |
+
value: 68.77723660599845
|
2524 |
+
- type: euclidean_precision
|
2525 |
+
value: 66.87437686939182
|
2526 |
+
- type: euclidean_recall
|
2527 |
+
value: 70.79155672823218
|
2528 |
+
- type: manhattan_accuracy
|
2529 |
+
value: 85.98676759849795
|
2530 |
+
- type: manhattan_ap
|
2531 |
+
value: 73.56016090035973
|
2532 |
+
- type: manhattan_f1
|
2533 |
+
value: 68.48878539036647
|
2534 |
+
- type: manhattan_precision
|
2535 |
+
value: 63.9505607690547
|
2536 |
+
- type: manhattan_recall
|
2537 |
+
value: 73.7203166226913
|
2538 |
+
- type: max_accuracy
|
2539 |
+
value: 86.07021517553794
|
2540 |
+
- type: max_ap
|
2541 |
+
value: 74.15520712370555
|
2542 |
+
- type: max_f1
|
2543 |
+
value: 68.77723660599845
|
2544 |
+
- task:
|
2545 |
+
type: PairClassification
|
2546 |
+
dataset:
|
2547 |
+
type: mteb/twitterurlcorpus-pairclassification
|
2548 |
+
name: MTEB TwitterURLCorpus
|
2549 |
+
config: default
|
2550 |
+
split: test
|
2551 |
+
revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
|
2552 |
+
metrics:
|
2553 |
+
- type: cos_sim_accuracy
|
2554 |
+
value: 88.92769821865176
|
2555 |
+
- type: cos_sim_ap
|
2556 |
+
value: 85.78879502899773
|
2557 |
+
- type: cos_sim_f1
|
2558 |
+
value: 78.14414083990464
|
2559 |
+
- type: cos_sim_precision
|
2560 |
+
value: 74.61651607480563
|
2561 |
+
- type: cos_sim_recall
|
2562 |
+
value: 82.0218663381583
|
2563 |
+
- type: dot_accuracy
|
2564 |
+
value: 84.95750378390964
|
2565 |
+
- type: dot_ap
|
2566 |
+
value: 75.80219641857563
|
2567 |
+
- type: dot_f1
|
2568 |
+
value: 70.13966179585681
|
2569 |
+
- type: dot_precision
|
2570 |
+
value: 65.71140262361251
|
2571 |
+
- type: dot_recall
|
2572 |
+
value: 75.20788420080073
|
2573 |
+
- type: euclidean_accuracy
|
2574 |
+
value: 88.93546008460433
|
2575 |
+
- type: euclidean_ap
|
2576 |
+
value: 85.72056428301667
|
2577 |
+
- type: euclidean_f1
|
2578 |
+
value: 78.14387902598124
|
2579 |
+
- type: euclidean_precision
|
2580 |
+
value: 75.3376688344172
|
2581 |
+
- type: euclidean_recall
|
2582 |
+
value: 81.16723129042192
|
2583 |
+
- type: manhattan_accuracy
|
2584 |
+
value: 88.96262661543835
|
2585 |
+
- type: manhattan_ap
|
2586 |
+
value: 85.76605136314335
|
2587 |
+
- type: manhattan_f1
|
2588 |
+
value: 78.26696165191743
|
2589 |
+
- type: manhattan_precision
|
2590 |
+
value: 75.0990659496179
|
2591 |
+
- type: manhattan_recall
|
2592 |
+
value: 81.71388974437943
|
2593 |
+
- type: max_accuracy
|
2594 |
+
value: 88.96262661543835
|
2595 |
+
- type: max_ap
|
2596 |
+
value: 85.78879502899773
|
2597 |
+
- type: max_f1
|
2598 |
+
value: 78.26696165191743
|
2599 |
+
---
|
2600 |
+
|
2601 |
+
## Usage
|
2602 |
+
|
2603 |
+
Coming soon
|
2604 |
+
|
config.json
ADDED
@@ -0,0 +1,25 @@
|
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|
1 |
+
{
|
2 |
+
"_name_or_path": "amlt/1109_tnlrv3_bs32k_ft/all_kd_ft",
|
3 |
+
"architectures": [
|
4 |
+
"BertModel"
|
5 |
+
],
|
6 |
+
"attention_probs_dropout_prob": 0.1,
|
7 |
+
"classifier_dropout": null,
|
8 |
+
"hidden_act": "gelu",
|
9 |
+
"hidden_dropout_prob": 0.1,
|
10 |
+
"hidden_size": 384,
|
11 |
+
"initializer_range": 0.02,
|
12 |
+
"intermediate_size": 1536,
|
13 |
+
"layer_norm_eps": 1e-12,
|
14 |
+
"max_position_embeddings": 512,
|
15 |
+
"model_type": "bert",
|
16 |
+
"num_attention_heads": 12,
|
17 |
+
"num_hidden_layers": 12,
|
18 |
+
"pad_token_id": 0,
|
19 |
+
"position_embedding_type": "absolute",
|
20 |
+
"torch_dtype": "float32",
|
21 |
+
"transformers_version": "4.15.0",
|
22 |
+
"type_vocab_size": 2,
|
23 |
+
"use_cache": true,
|
24 |
+
"vocab_size": 30522
|
25 |
+
}
|
mteb_metadata.md
ADDED
@@ -0,0 +1,2599 @@
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|
1 |
+
---
|
2 |
+
tags:
|
3 |
+
- mteb
|
4 |
+
model-index:
|
5 |
+
- name: mteb_metrics
|
6 |
+
results:
|
7 |
+
- task:
|
8 |
+
type: Classification
|
9 |
+
dataset:
|
10 |
+
type: mteb/amazon_counterfactual
|
11 |
+
name: MTEB AmazonCounterfactualClassification (en)
|
12 |
+
config: en
|
13 |
+
split: test
|
14 |
+
revision: e8379541af4e31359cca9fbcf4b00f2671dba205
|
15 |
+
metrics:
|
16 |
+
- type: accuracy
|
17 |
+
value: 76.22388059701493
|
18 |
+
- type: ap
|
19 |
+
value: 40.27466219523129
|
20 |
+
- type: f1
|
21 |
+
value: 70.60533006025108
|
22 |
+
- task:
|
23 |
+
type: Classification
|
24 |
+
dataset:
|
25 |
+
type: mteb/amazon_polarity
|
26 |
+
name: MTEB AmazonPolarityClassification
|
27 |
+
config: default
|
28 |
+
split: test
|
29 |
+
revision: e2d317d38cd51312af73b3d32a06d1a08b442046
|
30 |
+
metrics:
|
31 |
+
- type: accuracy
|
32 |
+
value: 87.525775
|
33 |
+
- type: ap
|
34 |
+
value: 83.51063993897611
|
35 |
+
- type: f1
|
36 |
+
value: 87.49342736805572
|
37 |
+
- task:
|
38 |
+
type: Classification
|
39 |
+
dataset:
|
40 |
+
type: mteb/amazon_reviews_multi
|
41 |
+
name: MTEB AmazonReviewsClassification (en)
|
42 |
+
config: en
|
43 |
+
split: test
|
44 |
+
revision: 1399c76144fd37290681b995c656ef9b2e06e26d
|
45 |
+
metrics:
|
46 |
+
- type: accuracy
|
47 |
+
value: 42.611999999999995
|
48 |
+
- type: f1
|
49 |
+
value: 42.05088045932892
|
50 |
+
- task:
|
51 |
+
type: Retrieval
|
52 |
+
dataset:
|
53 |
+
type: arguana
|
54 |
+
name: MTEB ArguAna
|
55 |
+
config: default
|
56 |
+
split: test
|
57 |
+
revision: None
|
58 |
+
metrics:
|
59 |
+
- type: map_at_1
|
60 |
+
value: 23.826
|
61 |
+
- type: map_at_10
|
62 |
+
value: 38.269
|
63 |
+
- type: map_at_100
|
64 |
+
value: 39.322
|
65 |
+
- type: map_at_1000
|
66 |
+
value: 39.344
|
67 |
+
- type: map_at_3
|
68 |
+
value: 33.428000000000004
|
69 |
+
- type: map_at_5
|
70 |
+
value: 36.063
|
71 |
+
- type: mrr_at_1
|
72 |
+
value: 24.253
|
73 |
+
- type: mrr_at_10
|
74 |
+
value: 38.425
|
75 |
+
- type: mrr_at_100
|
76 |
+
value: 39.478
|
77 |
+
- type: mrr_at_1000
|
78 |
+
value: 39.5
|
79 |
+
- type: mrr_at_3
|
80 |
+
value: 33.606
|
81 |
+
- type: mrr_at_5
|
82 |
+
value: 36.195
|
83 |
+
- type: ndcg_at_1
|
84 |
+
value: 23.826
|
85 |
+
- type: ndcg_at_10
|
86 |
+
value: 46.693
|
87 |
+
- type: ndcg_at_100
|
88 |
+
value: 51.469
|
89 |
+
- type: ndcg_at_1000
|
90 |
+
value: 52.002
|
91 |
+
- type: ndcg_at_3
|
92 |
+
value: 36.603
|
93 |
+
- type: ndcg_at_5
|
94 |
+
value: 41.365
|
95 |
+
- type: precision_at_1
|
96 |
+
value: 23.826
|
97 |
+
- type: precision_at_10
|
98 |
+
value: 7.383000000000001
|
99 |
+
- type: precision_at_100
|
100 |
+
value: 0.9530000000000001
|
101 |
+
- type: precision_at_1000
|
102 |
+
value: 0.099
|
103 |
+
- type: precision_at_3
|
104 |
+
value: 15.268
|
105 |
+
- type: precision_at_5
|
106 |
+
value: 11.479000000000001
|
107 |
+
- type: recall_at_1
|
108 |
+
value: 23.826
|
109 |
+
- type: recall_at_10
|
110 |
+
value: 73.82600000000001
|
111 |
+
- type: recall_at_100
|
112 |
+
value: 95.306
|
113 |
+
- type: recall_at_1000
|
114 |
+
value: 99.431
|
115 |
+
- type: recall_at_3
|
116 |
+
value: 45.804
|
117 |
+
- type: recall_at_5
|
118 |
+
value: 57.397
|
119 |
+
- task:
|
120 |
+
type: Clustering
|
121 |
+
dataset:
|
122 |
+
type: mteb/arxiv-clustering-p2p
|
123 |
+
name: MTEB ArxivClusteringP2P
|
124 |
+
config: default
|
125 |
+
split: test
|
126 |
+
revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
|
127 |
+
metrics:
|
128 |
+
- type: v_measure
|
129 |
+
value: 44.13995374767436
|
130 |
+
- task:
|
131 |
+
type: Clustering
|
132 |
+
dataset:
|
133 |
+
type: mteb/arxiv-clustering-s2s
|
134 |
+
name: MTEB ArxivClusteringS2S
|
135 |
+
config: default
|
136 |
+
split: test
|
137 |
+
revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
|
138 |
+
metrics:
|
139 |
+
- type: v_measure
|
140 |
+
value: 37.13950072624313
|
141 |
+
- task:
|
142 |
+
type: Reranking
|
143 |
+
dataset:
|
144 |
+
type: mteb/askubuntudupquestions-reranking
|
145 |
+
name: MTEB AskUbuntuDupQuestions
|
146 |
+
config: default
|
147 |
+
split: test
|
148 |
+
revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
|
149 |
+
metrics:
|
150 |
+
- type: map
|
151 |
+
value: 59.35843292105327
|
152 |
+
- type: mrr
|
153 |
+
value: 73.72312359846987
|
154 |
+
- task:
|
155 |
+
type: STS
|
156 |
+
dataset:
|
157 |
+
type: mteb/biosses-sts
|
158 |
+
name: MTEB BIOSSES
|
159 |
+
config: default
|
160 |
+
split: test
|
161 |
+
revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
|
162 |
+
metrics:
|
163 |
+
- type: cos_sim_pearson
|
164 |
+
value: 84.55140418324174
|
165 |
+
- type: cos_sim_spearman
|
166 |
+
value: 84.21637675860022
|
167 |
+
- type: euclidean_pearson
|
168 |
+
value: 81.26069614610006
|
169 |
+
- type: euclidean_spearman
|
170 |
+
value: 83.25069210421785
|
171 |
+
- type: manhattan_pearson
|
172 |
+
value: 80.17441422581014
|
173 |
+
- type: manhattan_spearman
|
174 |
+
value: 81.87596198487877
|
175 |
+
- task:
|
176 |
+
type: Classification
|
177 |
+
dataset:
|
178 |
+
type: mteb/banking77
|
179 |
+
name: MTEB Banking77Classification
|
180 |
+
config: default
|
181 |
+
split: test
|
182 |
+
revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
|
183 |
+
metrics:
|
184 |
+
- type: accuracy
|
185 |
+
value: 81.87337662337661
|
186 |
+
- type: f1
|
187 |
+
value: 81.76647866926402
|
188 |
+
- task:
|
189 |
+
type: Clustering
|
190 |
+
dataset:
|
191 |
+
type: mteb/biorxiv-clustering-p2p
|
192 |
+
name: MTEB BiorxivClusteringP2P
|
193 |
+
config: default
|
194 |
+
split: test
|
195 |
+
revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
|
196 |
+
metrics:
|
197 |
+
- type: v_measure
|
198 |
+
value: 35.80600542614507
|
199 |
+
- task:
|
200 |
+
type: Clustering
|
201 |
+
dataset:
|
202 |
+
type: mteb/biorxiv-clustering-s2s
|
203 |
+
name: MTEB BiorxivClusteringS2S
|
204 |
+
config: default
|
205 |
+
split: test
|
206 |
+
revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
|
207 |
+
metrics:
|
208 |
+
- type: v_measure
|
209 |
+
value: 31.86321613256603
|
210 |
+
- task:
|
211 |
+
type: Retrieval
|
212 |
+
dataset:
|
213 |
+
type: BeIR/cqadupstack
|
214 |
+
name: MTEB CQADupstackAndroidRetrieval
|
215 |
+
config: default
|
216 |
+
split: test
|
217 |
+
revision: None
|
218 |
+
metrics:
|
219 |
+
- type: map_at_1
|
220 |
+
value: 32.054
|
221 |
+
- type: map_at_10
|
222 |
+
value: 40.699999999999996
|
223 |
+
- type: map_at_100
|
224 |
+
value: 41.818
|
225 |
+
- type: map_at_1000
|
226 |
+
value: 41.959999999999994
|
227 |
+
- type: map_at_3
|
228 |
+
value: 37.742
|
229 |
+
- type: map_at_5
|
230 |
+
value: 39.427
|
231 |
+
- type: mrr_at_1
|
232 |
+
value: 38.769999999999996
|
233 |
+
- type: mrr_at_10
|
234 |
+
value: 46.150000000000006
|
235 |
+
- type: mrr_at_100
|
236 |
+
value: 46.865
|
237 |
+
- type: mrr_at_1000
|
238 |
+
value: 46.925
|
239 |
+
- type: mrr_at_3
|
240 |
+
value: 43.705
|
241 |
+
- type: mrr_at_5
|
242 |
+
value: 45.214999999999996
|
243 |
+
- type: ndcg_at_1
|
244 |
+
value: 38.769999999999996
|
245 |
+
- type: ndcg_at_10
|
246 |
+
value: 45.778
|
247 |
+
- type: ndcg_at_100
|
248 |
+
value: 50.38
|
249 |
+
- type: ndcg_at_1000
|
250 |
+
value: 52.922999999999995
|
251 |
+
- type: ndcg_at_3
|
252 |
+
value: 41.597
|
253 |
+
- type: ndcg_at_5
|
254 |
+
value: 43.631
|
255 |
+
- type: precision_at_1
|
256 |
+
value: 38.769999999999996
|
257 |
+
- type: precision_at_10
|
258 |
+
value: 8.269
|
259 |
+
- type: precision_at_100
|
260 |
+
value: 1.278
|
261 |
+
- type: precision_at_1000
|
262 |
+
value: 0.178
|
263 |
+
- type: precision_at_3
|
264 |
+
value: 19.266
|
265 |
+
- type: precision_at_5
|
266 |
+
value: 13.705
|
267 |
+
- type: recall_at_1
|
268 |
+
value: 32.054
|
269 |
+
- type: recall_at_10
|
270 |
+
value: 54.947
|
271 |
+
- type: recall_at_100
|
272 |
+
value: 74.79599999999999
|
273 |
+
- type: recall_at_1000
|
274 |
+
value: 91.40899999999999
|
275 |
+
- type: recall_at_3
|
276 |
+
value: 42.431000000000004
|
277 |
+
- type: recall_at_5
|
278 |
+
value: 48.519
|
279 |
+
- task:
|
280 |
+
type: Retrieval
|
281 |
+
dataset:
|
282 |
+
type: BeIR/cqadupstack
|
283 |
+
name: MTEB CQADupstackEnglishRetrieval
|
284 |
+
config: default
|
285 |
+
split: test
|
286 |
+
revision: None
|
287 |
+
metrics:
|
288 |
+
- type: map_at_1
|
289 |
+
value: 29.035
|
290 |
+
- type: map_at_10
|
291 |
+
value: 38.007000000000005
|
292 |
+
- type: map_at_100
|
293 |
+
value: 39.125
|
294 |
+
- type: map_at_1000
|
295 |
+
value: 39.251999999999995
|
296 |
+
- type: map_at_3
|
297 |
+
value: 35.77
|
298 |
+
- type: map_at_5
|
299 |
+
value: 37.057
|
300 |
+
- type: mrr_at_1
|
301 |
+
value: 36.497
|
302 |
+
- type: mrr_at_10
|
303 |
+
value: 44.077
|
304 |
+
- type: mrr_at_100
|
305 |
+
value: 44.743
|
306 |
+
- type: mrr_at_1000
|
307 |
+
value: 44.79
|
308 |
+
- type: mrr_at_3
|
309 |
+
value: 42.123
|
310 |
+
- type: mrr_at_5
|
311 |
+
value: 43.308
|
312 |
+
- type: ndcg_at_1
|
313 |
+
value: 36.497
|
314 |
+
- type: ndcg_at_10
|
315 |
+
value: 42.986000000000004
|
316 |
+
- type: ndcg_at_100
|
317 |
+
value: 47.323
|
318 |
+
- type: ndcg_at_1000
|
319 |
+
value: 49.624
|
320 |
+
- type: ndcg_at_3
|
321 |
+
value: 39.805
|
322 |
+
- type: ndcg_at_5
|
323 |
+
value: 41.286
|
324 |
+
- type: precision_at_1
|
325 |
+
value: 36.497
|
326 |
+
- type: precision_at_10
|
327 |
+
value: 7.8340000000000005
|
328 |
+
- type: precision_at_100
|
329 |
+
value: 1.269
|
330 |
+
- type: precision_at_1000
|
331 |
+
value: 0.178
|
332 |
+
- type: precision_at_3
|
333 |
+
value: 19.023
|
334 |
+
- type: precision_at_5
|
335 |
+
value: 13.248
|
336 |
+
- type: recall_at_1
|
337 |
+
value: 29.035
|
338 |
+
- type: recall_at_10
|
339 |
+
value: 51.06
|
340 |
+
- type: recall_at_100
|
341 |
+
value: 69.64099999999999
|
342 |
+
- type: recall_at_1000
|
343 |
+
value: 84.49
|
344 |
+
- type: recall_at_3
|
345 |
+
value: 41.333999999999996
|
346 |
+
- type: recall_at_5
|
347 |
+
value: 45.663
|
348 |
+
- task:
|
349 |
+
type: Retrieval
|
350 |
+
dataset:
|
351 |
+
type: BeIR/cqadupstack
|
352 |
+
name: MTEB CQADupstackGamingRetrieval
|
353 |
+
config: default
|
354 |
+
split: test
|
355 |
+
revision: None
|
356 |
+
metrics:
|
357 |
+
- type: map_at_1
|
358 |
+
value: 37.239
|
359 |
+
- type: map_at_10
|
360 |
+
value: 47.873
|
361 |
+
- type: map_at_100
|
362 |
+
value: 48.842999999999996
|
363 |
+
- type: map_at_1000
|
364 |
+
value: 48.913000000000004
|
365 |
+
- type: map_at_3
|
366 |
+
value: 45.050000000000004
|
367 |
+
- type: map_at_5
|
368 |
+
value: 46.498
|
369 |
+
- type: mrr_at_1
|
370 |
+
value: 42.508
|
371 |
+
- type: mrr_at_10
|
372 |
+
value: 51.44
|
373 |
+
- type: mrr_at_100
|
374 |
+
value: 52.087
|
375 |
+
- type: mrr_at_1000
|
376 |
+
value: 52.129999999999995
|
377 |
+
- type: mrr_at_3
|
378 |
+
value: 49.164
|
379 |
+
- type: mrr_at_5
|
380 |
+
value: 50.343
|
381 |
+
- type: ndcg_at_1
|
382 |
+
value: 42.508
|
383 |
+
- type: ndcg_at_10
|
384 |
+
value: 53.31399999999999
|
385 |
+
- type: ndcg_at_100
|
386 |
+
value: 57.245000000000005
|
387 |
+
- type: ndcg_at_1000
|
388 |
+
value: 58.794000000000004
|
389 |
+
- type: ndcg_at_3
|
390 |
+
value: 48.295
|
391 |
+
- type: ndcg_at_5
|
392 |
+
value: 50.415
|
393 |
+
- type: precision_at_1
|
394 |
+
value: 42.508
|
395 |
+
- type: precision_at_10
|
396 |
+
value: 8.458
|
397 |
+
- type: precision_at_100
|
398 |
+
value: 1.133
|
399 |
+
- type: precision_at_1000
|
400 |
+
value: 0.132
|
401 |
+
- type: precision_at_3
|
402 |
+
value: 21.191
|
403 |
+
- type: precision_at_5
|
404 |
+
value: 14.307
|
405 |
+
- type: recall_at_1
|
406 |
+
value: 37.239
|
407 |
+
- type: recall_at_10
|
408 |
+
value: 65.99000000000001
|
409 |
+
- type: recall_at_100
|
410 |
+
value: 82.99499999999999
|
411 |
+
- type: recall_at_1000
|
412 |
+
value: 94.128
|
413 |
+
- type: recall_at_3
|
414 |
+
value: 52.382
|
415 |
+
- type: recall_at_5
|
416 |
+
value: 57.648999999999994
|
417 |
+
- task:
|
418 |
+
type: Retrieval
|
419 |
+
dataset:
|
420 |
+
type: BeIR/cqadupstack
|
421 |
+
name: MTEB CQADupstackGisRetrieval
|
422 |
+
config: default
|
423 |
+
split: test
|
424 |
+
revision: None
|
425 |
+
metrics:
|
426 |
+
- type: map_at_1
|
427 |
+
value: 23.039
|
428 |
+
- type: map_at_10
|
429 |
+
value: 29.694
|
430 |
+
- type: map_at_100
|
431 |
+
value: 30.587999999999997
|
432 |
+
- type: map_at_1000
|
433 |
+
value: 30.692999999999998
|
434 |
+
- type: map_at_3
|
435 |
+
value: 27.708
|
436 |
+
- type: map_at_5
|
437 |
+
value: 28.774
|
438 |
+
- type: mrr_at_1
|
439 |
+
value: 24.633
|
440 |
+
- type: mrr_at_10
|
441 |
+
value: 31.478
|
442 |
+
- type: mrr_at_100
|
443 |
+
value: 32.299
|
444 |
+
- type: mrr_at_1000
|
445 |
+
value: 32.381
|
446 |
+
- type: mrr_at_3
|
447 |
+
value: 29.435
|
448 |
+
- type: mrr_at_5
|
449 |
+
value: 30.446
|
450 |
+
- type: ndcg_at_1
|
451 |
+
value: 24.633
|
452 |
+
- type: ndcg_at_10
|
453 |
+
value: 33.697
|
454 |
+
- type: ndcg_at_100
|
455 |
+
value: 38.080000000000005
|
456 |
+
- type: ndcg_at_1000
|
457 |
+
value: 40.812
|
458 |
+
- type: ndcg_at_3
|
459 |
+
value: 29.654000000000003
|
460 |
+
- type: ndcg_at_5
|
461 |
+
value: 31.474000000000004
|
462 |
+
- type: precision_at_1
|
463 |
+
value: 24.633
|
464 |
+
- type: precision_at_10
|
465 |
+
value: 5.0729999999999995
|
466 |
+
- type: precision_at_100
|
467 |
+
value: 0.753
|
468 |
+
- type: precision_at_1000
|
469 |
+
value: 0.10300000000000001
|
470 |
+
- type: precision_at_3
|
471 |
+
value: 12.279
|
472 |
+
- type: precision_at_5
|
473 |
+
value: 8.452
|
474 |
+
- type: recall_at_1
|
475 |
+
value: 23.039
|
476 |
+
- type: recall_at_10
|
477 |
+
value: 44.275999999999996
|
478 |
+
- type: recall_at_100
|
479 |
+
value: 64.4
|
480 |
+
- type: recall_at_1000
|
481 |
+
value: 85.135
|
482 |
+
- type: recall_at_3
|
483 |
+
value: 33.394
|
484 |
+
- type: recall_at_5
|
485 |
+
value: 37.687
|
486 |
+
- task:
|
487 |
+
type: Retrieval
|
488 |
+
dataset:
|
489 |
+
type: BeIR/cqadupstack
|
490 |
+
name: MTEB CQADupstackMathematicaRetrieval
|
491 |
+
config: default
|
492 |
+
split: test
|
493 |
+
revision: None
|
494 |
+
metrics:
|
495 |
+
- type: map_at_1
|
496 |
+
value: 13.594999999999999
|
497 |
+
- type: map_at_10
|
498 |
+
value: 19.933999999999997
|
499 |
+
- type: map_at_100
|
500 |
+
value: 20.966
|
501 |
+
- type: map_at_1000
|
502 |
+
value: 21.087
|
503 |
+
- type: map_at_3
|
504 |
+
value: 17.749000000000002
|
505 |
+
- type: map_at_5
|
506 |
+
value: 19.156000000000002
|
507 |
+
- type: mrr_at_1
|
508 |
+
value: 17.662
|
509 |
+
- type: mrr_at_10
|
510 |
+
value: 24.407
|
511 |
+
- type: mrr_at_100
|
512 |
+
value: 25.385
|
513 |
+
- type: mrr_at_1000
|
514 |
+
value: 25.465
|
515 |
+
- type: mrr_at_3
|
516 |
+
value: 22.056
|
517 |
+
- type: mrr_at_5
|
518 |
+
value: 23.630000000000003
|
519 |
+
- type: ndcg_at_1
|
520 |
+
value: 17.662
|
521 |
+
- type: ndcg_at_10
|
522 |
+
value: 24.391
|
523 |
+
- type: ndcg_at_100
|
524 |
+
value: 29.681
|
525 |
+
- type: ndcg_at_1000
|
526 |
+
value: 32.923
|
527 |
+
- type: ndcg_at_3
|
528 |
+
value: 20.271
|
529 |
+
- type: ndcg_at_5
|
530 |
+
value: 22.621
|
531 |
+
- type: precision_at_1
|
532 |
+
value: 17.662
|
533 |
+
- type: precision_at_10
|
534 |
+
value: 4.44
|
535 |
+
- type: precision_at_100
|
536 |
+
value: 0.8200000000000001
|
537 |
+
- type: precision_at_1000
|
538 |
+
value: 0.125
|
539 |
+
- type: precision_at_3
|
540 |
+
value: 9.577
|
541 |
+
- type: precision_at_5
|
542 |
+
value: 7.313
|
543 |
+
- type: recall_at_1
|
544 |
+
value: 13.594999999999999
|
545 |
+
- type: recall_at_10
|
546 |
+
value: 33.976
|
547 |
+
- type: recall_at_100
|
548 |
+
value: 57.43000000000001
|
549 |
+
- type: recall_at_1000
|
550 |
+
value: 80.958
|
551 |
+
- type: recall_at_3
|
552 |
+
value: 22.897000000000002
|
553 |
+
- type: recall_at_5
|
554 |
+
value: 28.714000000000002
|
555 |
+
- task:
|
556 |
+
type: Retrieval
|
557 |
+
dataset:
|
558 |
+
type: BeIR/cqadupstack
|
559 |
+
name: MTEB CQADupstackPhysicsRetrieval
|
560 |
+
config: default
|
561 |
+
split: test
|
562 |
+
revision: None
|
563 |
+
metrics:
|
564 |
+
- type: map_at_1
|
565 |
+
value: 26.683
|
566 |
+
- type: map_at_10
|
567 |
+
value: 35.068
|
568 |
+
- type: map_at_100
|
569 |
+
value: 36.311
|
570 |
+
- type: map_at_1000
|
571 |
+
value: 36.436
|
572 |
+
- type: map_at_3
|
573 |
+
value: 32.371
|
574 |
+
- type: map_at_5
|
575 |
+
value: 33.761
|
576 |
+
- type: mrr_at_1
|
577 |
+
value: 32.435
|
578 |
+
- type: mrr_at_10
|
579 |
+
value: 40.721000000000004
|
580 |
+
- type: mrr_at_100
|
581 |
+
value: 41.535
|
582 |
+
- type: mrr_at_1000
|
583 |
+
value: 41.593
|
584 |
+
- type: mrr_at_3
|
585 |
+
value: 38.401999999999994
|
586 |
+
- type: mrr_at_5
|
587 |
+
value: 39.567
|
588 |
+
- type: ndcg_at_1
|
589 |
+
value: 32.435
|
590 |
+
- type: ndcg_at_10
|
591 |
+
value: 40.538000000000004
|
592 |
+
- type: ndcg_at_100
|
593 |
+
value: 45.963
|
594 |
+
- type: ndcg_at_1000
|
595 |
+
value: 48.400999999999996
|
596 |
+
- type: ndcg_at_3
|
597 |
+
value: 36.048
|
598 |
+
- type: ndcg_at_5
|
599 |
+
value: 37.899
|
600 |
+
- type: precision_at_1
|
601 |
+
value: 32.435
|
602 |
+
- type: precision_at_10
|
603 |
+
value: 7.1129999999999995
|
604 |
+
- type: precision_at_100
|
605 |
+
value: 1.162
|
606 |
+
- type: precision_at_1000
|
607 |
+
value: 0.156
|
608 |
+
- type: precision_at_3
|
609 |
+
value: 16.683
|
610 |
+
- type: precision_at_5
|
611 |
+
value: 11.684
|
612 |
+
- type: recall_at_1
|
613 |
+
value: 26.683
|
614 |
+
- type: recall_at_10
|
615 |
+
value: 51.517
|
616 |
+
- type: recall_at_100
|
617 |
+
value: 74.553
|
618 |
+
- type: recall_at_1000
|
619 |
+
value: 90.649
|
620 |
+
- type: recall_at_3
|
621 |
+
value: 38.495000000000005
|
622 |
+
- type: recall_at_5
|
623 |
+
value: 43.495
|
624 |
+
- task:
|
625 |
+
type: Retrieval
|
626 |
+
dataset:
|
627 |
+
type: BeIR/cqadupstack
|
628 |
+
name: MTEB CQADupstackProgrammersRetrieval
|
629 |
+
config: default
|
630 |
+
split: test
|
631 |
+
revision: None
|
632 |
+
metrics:
|
633 |
+
- type: map_at_1
|
634 |
+
value: 24.186
|
635 |
+
- type: map_at_10
|
636 |
+
value: 31.972
|
637 |
+
- type: map_at_100
|
638 |
+
value: 33.117000000000004
|
639 |
+
- type: map_at_1000
|
640 |
+
value: 33.243
|
641 |
+
- type: map_at_3
|
642 |
+
value: 29.423
|
643 |
+
- type: map_at_5
|
644 |
+
value: 30.847
|
645 |
+
- type: mrr_at_1
|
646 |
+
value: 29.794999999999998
|
647 |
+
- type: mrr_at_10
|
648 |
+
value: 36.767
|
649 |
+
- type: mrr_at_100
|
650 |
+
value: 37.645
|
651 |
+
- type: mrr_at_1000
|
652 |
+
value: 37.716
|
653 |
+
- type: mrr_at_3
|
654 |
+
value: 34.513
|
655 |
+
- type: mrr_at_5
|
656 |
+
value: 35.791000000000004
|
657 |
+
- type: ndcg_at_1
|
658 |
+
value: 29.794999999999998
|
659 |
+
- type: ndcg_at_10
|
660 |
+
value: 36.786
|
661 |
+
- type: ndcg_at_100
|
662 |
+
value: 41.94
|
663 |
+
- type: ndcg_at_1000
|
664 |
+
value: 44.830999999999996
|
665 |
+
- type: ndcg_at_3
|
666 |
+
value: 32.504
|
667 |
+
- type: ndcg_at_5
|
668 |
+
value: 34.404
|
669 |
+
- type: precision_at_1
|
670 |
+
value: 29.794999999999998
|
671 |
+
- type: precision_at_10
|
672 |
+
value: 6.518
|
673 |
+
- type: precision_at_100
|
674 |
+
value: 1.0659999999999998
|
675 |
+
- type: precision_at_1000
|
676 |
+
value: 0.149
|
677 |
+
- type: precision_at_3
|
678 |
+
value: 15.296999999999999
|
679 |
+
- type: precision_at_5
|
680 |
+
value: 10.731
|
681 |
+
- type: recall_at_1
|
682 |
+
value: 24.186
|
683 |
+
- type: recall_at_10
|
684 |
+
value: 46.617
|
685 |
+
- type: recall_at_100
|
686 |
+
value: 68.75
|
687 |
+
- type: recall_at_1000
|
688 |
+
value: 88.864
|
689 |
+
- type: recall_at_3
|
690 |
+
value: 34.199
|
691 |
+
- type: recall_at_5
|
692 |
+
value: 39.462
|
693 |
+
- task:
|
694 |
+
type: Retrieval
|
695 |
+
dataset:
|
696 |
+
type: BeIR/cqadupstack
|
697 |
+
name: MTEB CQADupstackRetrieval
|
698 |
+
config: default
|
699 |
+
split: test
|
700 |
+
revision: None
|
701 |
+
metrics:
|
702 |
+
- type: map_at_1
|
703 |
+
value: 24.22083333333333
|
704 |
+
- type: map_at_10
|
705 |
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value: 31.606666666666662
|
706 |
+
- type: map_at_100
|
707 |
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value: 32.6195
|
708 |
+
- type: map_at_1000
|
709 |
+
value: 32.739999999999995
|
710 |
+
- type: map_at_3
|
711 |
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value: 29.37825
|
712 |
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- type: map_at_5
|
713 |
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value: 30.596083333333336
|
714 |
+
- type: mrr_at_1
|
715 |
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value: 28.607916666666668
|
716 |
+
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|
717 |
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value: 35.54591666666666
|
718 |
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- type: mrr_at_100
|
719 |
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value: 36.33683333333333
|
720 |
+
- type: mrr_at_1000
|
721 |
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value: 36.40624999999999
|
722 |
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- type: mrr_at_3
|
723 |
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value: 33.526250000000005
|
724 |
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- type: mrr_at_5
|
725 |
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value: 34.6605
|
726 |
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- type: ndcg_at_1
|
727 |
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value: 28.607916666666668
|
728 |
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- type: ndcg_at_10
|
729 |
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value: 36.07966666666667
|
730 |
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- type: ndcg_at_100
|
731 |
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value: 40.73308333333333
|
732 |
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- type: ndcg_at_1000
|
733 |
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value: 43.40666666666666
|
734 |
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- type: ndcg_at_3
|
735 |
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value: 32.23525
|
736 |
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- type: ndcg_at_5
|
737 |
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value: 33.97083333333333
|
738 |
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- type: precision_at_1
|
739 |
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value: 28.607916666666668
|
740 |
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- type: precision_at_10
|
741 |
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value: 6.120333333333335
|
742 |
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- type: precision_at_100
|
743 |
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value: 0.9921666666666668
|
744 |
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- type: precision_at_1000
|
745 |
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value: 0.14091666666666666
|
746 |
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- type: precision_at_3
|
747 |
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value: 14.54975
|
748 |
+
- type: precision_at_5
|
749 |
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value: 10.153166666666667
|
750 |
+
- type: recall_at_1
|
751 |
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value: 24.22083333333333
|
752 |
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- type: recall_at_10
|
753 |
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value: 45.49183333333334
|
754 |
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- type: recall_at_100
|
755 |
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value: 66.28133333333332
|
756 |
+
- type: recall_at_1000
|
757 |
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value: 85.16541666666667
|
758 |
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- type: recall_at_3
|
759 |
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value: 34.6485
|
760 |
+
- type: recall_at_5
|
761 |
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value: 39.229749999999996
|
762 |
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- task:
|
763 |
+
type: Retrieval
|
764 |
+
dataset:
|
765 |
+
type: BeIR/cqadupstack
|
766 |
+
name: MTEB CQADupstackStatsRetrieval
|
767 |
+
config: default
|
768 |
+
split: test
|
769 |
+
revision: None
|
770 |
+
metrics:
|
771 |
+
- type: map_at_1
|
772 |
+
value: 21.842
|
773 |
+
- type: map_at_10
|
774 |
+
value: 27.573999999999998
|
775 |
+
- type: map_at_100
|
776 |
+
value: 28.410999999999998
|
777 |
+
- type: map_at_1000
|
778 |
+
value: 28.502
|
779 |
+
- type: map_at_3
|
780 |
+
value: 25.921
|
781 |
+
- type: map_at_5
|
782 |
+
value: 26.888
|
783 |
+
- type: mrr_at_1
|
784 |
+
value: 24.08
|
785 |
+
- type: mrr_at_10
|
786 |
+
value: 29.915999999999997
|
787 |
+
- type: mrr_at_100
|
788 |
+
value: 30.669
|
789 |
+
- type: mrr_at_1000
|
790 |
+
value: 30.746000000000002
|
791 |
+
- type: mrr_at_3
|
792 |
+
value: 28.349000000000004
|
793 |
+
- type: mrr_at_5
|
794 |
+
value: 29.246
|
795 |
+
- type: ndcg_at_1
|
796 |
+
value: 24.08
|
797 |
+
- type: ndcg_at_10
|
798 |
+
value: 30.898999999999997
|
799 |
+
- type: ndcg_at_100
|
800 |
+
value: 35.272999999999996
|
801 |
+
- type: ndcg_at_1000
|
802 |
+
value: 37.679
|
803 |
+
- type: ndcg_at_3
|
804 |
+
value: 27.881
|
805 |
+
- type: ndcg_at_5
|
806 |
+
value: 29.432000000000002
|
807 |
+
- type: precision_at_1
|
808 |
+
value: 24.08
|
809 |
+
- type: precision_at_10
|
810 |
+
value: 4.678
|
811 |
+
- type: precision_at_100
|
812 |
+
value: 0.744
|
813 |
+
- type: precision_at_1000
|
814 |
+
value: 0.10300000000000001
|
815 |
+
- type: precision_at_3
|
816 |
+
value: 11.860999999999999
|
817 |
+
- type: precision_at_5
|
818 |
+
value: 8.16
|
819 |
+
- type: recall_at_1
|
820 |
+
value: 21.842
|
821 |
+
- type: recall_at_10
|
822 |
+
value: 38.66
|
823 |
+
- type: recall_at_100
|
824 |
+
value: 59.169000000000004
|
825 |
+
- type: recall_at_1000
|
826 |
+
value: 76.887
|
827 |
+
- type: recall_at_3
|
828 |
+
value: 30.532999999999998
|
829 |
+
- type: recall_at_5
|
830 |
+
value: 34.354
|
831 |
+
- task:
|
832 |
+
type: Retrieval
|
833 |
+
dataset:
|
834 |
+
type: BeIR/cqadupstack
|
835 |
+
name: MTEB CQADupstackTexRetrieval
|
836 |
+
config: default
|
837 |
+
split: test
|
838 |
+
revision: None
|
839 |
+
metrics:
|
840 |
+
- type: map_at_1
|
841 |
+
value: 17.145
|
842 |
+
- type: map_at_10
|
843 |
+
value: 22.729
|
844 |
+
- type: map_at_100
|
845 |
+
value: 23.574
|
846 |
+
- type: map_at_1000
|
847 |
+
value: 23.695
|
848 |
+
- type: map_at_3
|
849 |
+
value: 21.044
|
850 |
+
- type: map_at_5
|
851 |
+
value: 21.981
|
852 |
+
- type: mrr_at_1
|
853 |
+
value: 20.888
|
854 |
+
- type: mrr_at_10
|
855 |
+
value: 26.529000000000003
|
856 |
+
- type: mrr_at_100
|
857 |
+
value: 27.308
|
858 |
+
- type: mrr_at_1000
|
859 |
+
value: 27.389000000000003
|
860 |
+
- type: mrr_at_3
|
861 |
+
value: 24.868000000000002
|
862 |
+
- type: mrr_at_5
|
863 |
+
value: 25.825
|
864 |
+
- type: ndcg_at_1
|
865 |
+
value: 20.888
|
866 |
+
- type: ndcg_at_10
|
867 |
+
value: 26.457000000000004
|
868 |
+
- type: ndcg_at_100
|
869 |
+
value: 30.764000000000003
|
870 |
+
- type: ndcg_at_1000
|
871 |
+
value: 33.825
|
872 |
+
- type: ndcg_at_3
|
873 |
+
value: 23.483999999999998
|
874 |
+
- type: ndcg_at_5
|
875 |
+
value: 24.836
|
876 |
+
- type: precision_at_1
|
877 |
+
value: 20.888
|
878 |
+
- type: precision_at_10
|
879 |
+
value: 4.58
|
880 |
+
- type: precision_at_100
|
881 |
+
value: 0.784
|
882 |
+
- type: precision_at_1000
|
883 |
+
value: 0.121
|
884 |
+
- type: precision_at_3
|
885 |
+
value: 10.874
|
886 |
+
- type: precision_at_5
|
887 |
+
value: 7.639
|
888 |
+
- type: recall_at_1
|
889 |
+
value: 17.145
|
890 |
+
- type: recall_at_10
|
891 |
+
value: 33.938
|
892 |
+
- type: recall_at_100
|
893 |
+
value: 53.672
|
894 |
+
- type: recall_at_1000
|
895 |
+
value: 76.023
|
896 |
+
- type: recall_at_3
|
897 |
+
value: 25.363000000000003
|
898 |
+
- type: recall_at_5
|
899 |
+
value: 29.023
|
900 |
+
- task:
|
901 |
+
type: Retrieval
|
902 |
+
dataset:
|
903 |
+
type: BeIR/cqadupstack
|
904 |
+
name: MTEB CQADupstackUnixRetrieval
|
905 |
+
config: default
|
906 |
+
split: test
|
907 |
+
revision: None
|
908 |
+
metrics:
|
909 |
+
- type: map_at_1
|
910 |
+
value: 24.275
|
911 |
+
- type: map_at_10
|
912 |
+
value: 30.438
|
913 |
+
- type: map_at_100
|
914 |
+
value: 31.489
|
915 |
+
- type: map_at_1000
|
916 |
+
value: 31.601000000000003
|
917 |
+
- type: map_at_3
|
918 |
+
value: 28.647
|
919 |
+
- type: map_at_5
|
920 |
+
value: 29.660999999999998
|
921 |
+
- type: mrr_at_1
|
922 |
+
value: 28.077999999999996
|
923 |
+
- type: mrr_at_10
|
924 |
+
value: 34.098
|
925 |
+
- type: mrr_at_100
|
926 |
+
value: 35.025
|
927 |
+
- type: mrr_at_1000
|
928 |
+
value: 35.109
|
929 |
+
- type: mrr_at_3
|
930 |
+
value: 32.4
|
931 |
+
- type: mrr_at_5
|
932 |
+
value: 33.379999999999995
|
933 |
+
- type: ndcg_at_1
|
934 |
+
value: 28.077999999999996
|
935 |
+
- type: ndcg_at_10
|
936 |
+
value: 34.271
|
937 |
+
- type: ndcg_at_100
|
938 |
+
value: 39.352
|
939 |
+
- type: ndcg_at_1000
|
940 |
+
value: 42.199
|
941 |
+
- type: ndcg_at_3
|
942 |
+
value: 30.978
|
943 |
+
- type: ndcg_at_5
|
944 |
+
value: 32.498
|
945 |
+
- type: precision_at_1
|
946 |
+
value: 28.077999999999996
|
947 |
+
- type: precision_at_10
|
948 |
+
value: 5.345
|
949 |
+
- type: precision_at_100
|
950 |
+
value: 0.897
|
951 |
+
- type: precision_at_1000
|
952 |
+
value: 0.125
|
953 |
+
- type: precision_at_3
|
954 |
+
value: 13.526
|
955 |
+
- type: precision_at_5
|
956 |
+
value: 9.16
|
957 |
+
- type: recall_at_1
|
958 |
+
value: 24.275
|
959 |
+
- type: recall_at_10
|
960 |
+
value: 42.362
|
961 |
+
- type: recall_at_100
|
962 |
+
value: 64.461
|
963 |
+
- type: recall_at_1000
|
964 |
+
value: 84.981
|
965 |
+
- type: recall_at_3
|
966 |
+
value: 33.249
|
967 |
+
- type: recall_at_5
|
968 |
+
value: 37.214999999999996
|
969 |
+
- task:
|
970 |
+
type: Retrieval
|
971 |
+
dataset:
|
972 |
+
type: BeIR/cqadupstack
|
973 |
+
name: MTEB CQADupstackWebmastersRetrieval
|
974 |
+
config: default
|
975 |
+
split: test
|
976 |
+
revision: None
|
977 |
+
metrics:
|
978 |
+
- type: map_at_1
|
979 |
+
value: 22.358
|
980 |
+
- type: map_at_10
|
981 |
+
value: 30.062
|
982 |
+
- type: map_at_100
|
983 |
+
value: 31.189
|
984 |
+
- type: map_at_1000
|
985 |
+
value: 31.386999999999997
|
986 |
+
- type: map_at_3
|
987 |
+
value: 27.672
|
988 |
+
- type: map_at_5
|
989 |
+
value: 28.76
|
990 |
+
- type: mrr_at_1
|
991 |
+
value: 26.877000000000002
|
992 |
+
- type: mrr_at_10
|
993 |
+
value: 33.948
|
994 |
+
- type: mrr_at_100
|
995 |
+
value: 34.746
|
996 |
+
- type: mrr_at_1000
|
997 |
+
value: 34.816
|
998 |
+
- type: mrr_at_3
|
999 |
+
value: 31.884
|
1000 |
+
- type: mrr_at_5
|
1001 |
+
value: 33.001000000000005
|
1002 |
+
- type: ndcg_at_1
|
1003 |
+
value: 26.877000000000002
|
1004 |
+
- type: ndcg_at_10
|
1005 |
+
value: 34.977000000000004
|
1006 |
+
- type: ndcg_at_100
|
1007 |
+
value: 39.753
|
1008 |
+
- type: ndcg_at_1000
|
1009 |
+
value: 42.866
|
1010 |
+
- type: ndcg_at_3
|
1011 |
+
value: 30.956
|
1012 |
+
- type: ndcg_at_5
|
1013 |
+
value: 32.381
|
1014 |
+
- type: precision_at_1
|
1015 |
+
value: 26.877000000000002
|
1016 |
+
- type: precision_at_10
|
1017 |
+
value: 6.7
|
1018 |
+
- type: precision_at_100
|
1019 |
+
value: 1.287
|
1020 |
+
- type: precision_at_1000
|
1021 |
+
value: 0.215
|
1022 |
+
- type: precision_at_3
|
1023 |
+
value: 14.360999999999999
|
1024 |
+
- type: precision_at_5
|
1025 |
+
value: 10.119
|
1026 |
+
- type: recall_at_1
|
1027 |
+
value: 22.358
|
1028 |
+
- type: recall_at_10
|
1029 |
+
value: 44.183
|
1030 |
+
- type: recall_at_100
|
1031 |
+
value: 67.14
|
1032 |
+
- type: recall_at_1000
|
1033 |
+
value: 87.53999999999999
|
1034 |
+
- type: recall_at_3
|
1035 |
+
value: 32.79
|
1036 |
+
- type: recall_at_5
|
1037 |
+
value: 36.829
|
1038 |
+
- task:
|
1039 |
+
type: Retrieval
|
1040 |
+
dataset:
|
1041 |
+
type: BeIR/cqadupstack
|
1042 |
+
name: MTEB CQADupstackWordpressRetrieval
|
1043 |
+
config: default
|
1044 |
+
split: test
|
1045 |
+
revision: None
|
1046 |
+
metrics:
|
1047 |
+
- type: map_at_1
|
1048 |
+
value: 19.198999999999998
|
1049 |
+
- type: map_at_10
|
1050 |
+
value: 25.229000000000003
|
1051 |
+
- type: map_at_100
|
1052 |
+
value: 26.003
|
1053 |
+
- type: map_at_1000
|
1054 |
+
value: 26.111
|
1055 |
+
- type: map_at_3
|
1056 |
+
value: 23.442
|
1057 |
+
- type: map_at_5
|
1058 |
+
value: 24.343
|
1059 |
+
- type: mrr_at_1
|
1060 |
+
value: 21.072
|
1061 |
+
- type: mrr_at_10
|
1062 |
+
value: 27.02
|
1063 |
+
- type: mrr_at_100
|
1064 |
+
value: 27.735
|
1065 |
+
- type: mrr_at_1000
|
1066 |
+
value: 27.815
|
1067 |
+
- type: mrr_at_3
|
1068 |
+
value: 25.416
|
1069 |
+
- type: mrr_at_5
|
1070 |
+
value: 26.173999999999996
|
1071 |
+
- type: ndcg_at_1
|
1072 |
+
value: 21.072
|
1073 |
+
- type: ndcg_at_10
|
1074 |
+
value: 28.862
|
1075 |
+
- type: ndcg_at_100
|
1076 |
+
value: 33.043
|
1077 |
+
- type: ndcg_at_1000
|
1078 |
+
value: 36.003
|
1079 |
+
- type: ndcg_at_3
|
1080 |
+
value: 25.35
|
1081 |
+
- type: ndcg_at_5
|
1082 |
+
value: 26.773000000000003
|
1083 |
+
- type: precision_at_1
|
1084 |
+
value: 21.072
|
1085 |
+
- type: precision_at_10
|
1086 |
+
value: 4.436
|
1087 |
+
- type: precision_at_100
|
1088 |
+
value: 0.713
|
1089 |
+
- type: precision_at_1000
|
1090 |
+
value: 0.106
|
1091 |
+
- type: precision_at_3
|
1092 |
+
value: 10.659
|
1093 |
+
- type: precision_at_5
|
1094 |
+
value: 7.32
|
1095 |
+
- type: recall_at_1
|
1096 |
+
value: 19.198999999999998
|
1097 |
+
- type: recall_at_10
|
1098 |
+
value: 38.376
|
1099 |
+
- type: recall_at_100
|
1100 |
+
value: 58.36900000000001
|
1101 |
+
- type: recall_at_1000
|
1102 |
+
value: 80.92099999999999
|
1103 |
+
- type: recall_at_3
|
1104 |
+
value: 28.715000000000003
|
1105 |
+
- type: recall_at_5
|
1106 |
+
value: 32.147
|
1107 |
+
- task:
|
1108 |
+
type: Retrieval
|
1109 |
+
dataset:
|
1110 |
+
type: climate-fever
|
1111 |
+
name: MTEB ClimateFEVER
|
1112 |
+
config: default
|
1113 |
+
split: test
|
1114 |
+
revision: None
|
1115 |
+
metrics:
|
1116 |
+
- type: map_at_1
|
1117 |
+
value: 5.9319999999999995
|
1118 |
+
- type: map_at_10
|
1119 |
+
value: 10.483
|
1120 |
+
- type: map_at_100
|
1121 |
+
value: 11.97
|
1122 |
+
- type: map_at_1000
|
1123 |
+
value: 12.171999999999999
|
1124 |
+
- type: map_at_3
|
1125 |
+
value: 8.477
|
1126 |
+
- type: map_at_5
|
1127 |
+
value: 9.495000000000001
|
1128 |
+
- type: mrr_at_1
|
1129 |
+
value: 13.094
|
1130 |
+
- type: mrr_at_10
|
1131 |
+
value: 21.282
|
1132 |
+
- type: mrr_at_100
|
1133 |
+
value: 22.556
|
1134 |
+
- type: mrr_at_1000
|
1135 |
+
value: 22.628999999999998
|
1136 |
+
- type: mrr_at_3
|
1137 |
+
value: 18.218999999999998
|
1138 |
+
- type: mrr_at_5
|
1139 |
+
value: 19.900000000000002
|
1140 |
+
- type: ndcg_at_1
|
1141 |
+
value: 13.094
|
1142 |
+
- type: ndcg_at_10
|
1143 |
+
value: 15.811
|
1144 |
+
- type: ndcg_at_100
|
1145 |
+
value: 23.035
|
1146 |
+
- type: ndcg_at_1000
|
1147 |
+
value: 27.089999999999996
|
1148 |
+
- type: ndcg_at_3
|
1149 |
+
value: 11.905000000000001
|
1150 |
+
- type: ndcg_at_5
|
1151 |
+
value: 13.377
|
1152 |
+
- type: precision_at_1
|
1153 |
+
value: 13.094
|
1154 |
+
- type: precision_at_10
|
1155 |
+
value: 5.225
|
1156 |
+
- type: precision_at_100
|
1157 |
+
value: 1.2970000000000002
|
1158 |
+
- type: precision_at_1000
|
1159 |
+
value: 0.203
|
1160 |
+
- type: precision_at_3
|
1161 |
+
value: 8.86
|
1162 |
+
- type: precision_at_5
|
1163 |
+
value: 7.309
|
1164 |
+
- type: recall_at_1
|
1165 |
+
value: 5.9319999999999995
|
1166 |
+
- type: recall_at_10
|
1167 |
+
value: 20.305
|
1168 |
+
- type: recall_at_100
|
1169 |
+
value: 46.314
|
1170 |
+
- type: recall_at_1000
|
1171 |
+
value: 69.612
|
1172 |
+
- type: recall_at_3
|
1173 |
+
value: 11.21
|
1174 |
+
- type: recall_at_5
|
1175 |
+
value: 14.773
|
1176 |
+
- task:
|
1177 |
+
type: Retrieval
|
1178 |
+
dataset:
|
1179 |
+
type: dbpedia-entity
|
1180 |
+
name: MTEB DBPedia
|
1181 |
+
config: default
|
1182 |
+
split: test
|
1183 |
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revision: None
|
1184 |
+
metrics:
|
1185 |
+
- type: map_at_1
|
1186 |
+
value: 8.674
|
1187 |
+
- type: map_at_10
|
1188 |
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value: 17.822
|
1189 |
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- type: map_at_100
|
1190 |
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value: 24.794
|
1191 |
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- type: map_at_1000
|
1192 |
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value: 26.214
|
1193 |
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- type: map_at_3
|
1194 |
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value: 12.690999999999999
|
1195 |
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- type: map_at_5
|
1196 |
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value: 15.033
|
1197 |
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- type: mrr_at_1
|
1198 |
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value: 61.75000000000001
|
1199 |
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- type: mrr_at_10
|
1200 |
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value: 71.58
|
1201 |
+
- type: mrr_at_100
|
1202 |
+
value: 71.923
|
1203 |
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- type: mrr_at_1000
|
1204 |
+
value: 71.932
|
1205 |
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- type: mrr_at_3
|
1206 |
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value: 70.125
|
1207 |
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- type: mrr_at_5
|
1208 |
+
value: 71.038
|
1209 |
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- type: ndcg_at_1
|
1210 |
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value: 51.0
|
1211 |
+
- type: ndcg_at_10
|
1212 |
+
value: 38.637
|
1213 |
+
- type: ndcg_at_100
|
1214 |
+
value: 42.398
|
1215 |
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- type: ndcg_at_1000
|
1216 |
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value: 48.962
|
1217 |
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- type: ndcg_at_3
|
1218 |
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value: 43.29
|
1219 |
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- type: ndcg_at_5
|
1220 |
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value: 40.763
|
1221 |
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- type: precision_at_1
|
1222 |
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value: 61.75000000000001
|
1223 |
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- type: precision_at_10
|
1224 |
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value: 30.125
|
1225 |
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- type: precision_at_100
|
1226 |
+
value: 9.53
|
1227 |
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- type: precision_at_1000
|
1228 |
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value: 1.9619999999999997
|
1229 |
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- type: precision_at_3
|
1230 |
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value: 45.583
|
1231 |
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- type: precision_at_5
|
1232 |
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value: 38.95
|
1233 |
+
- type: recall_at_1
|
1234 |
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value: 8.674
|
1235 |
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- type: recall_at_10
|
1236 |
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value: 23.122
|
1237 |
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- type: recall_at_100
|
1238 |
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value: 47.46
|
1239 |
+
- type: recall_at_1000
|
1240 |
+
value: 67.662
|
1241 |
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- type: recall_at_3
|
1242 |
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value: 13.946
|
1243 |
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- type: recall_at_5
|
1244 |
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value: 17.768
|
1245 |
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- task:
|
1246 |
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type: Classification
|
1247 |
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dataset:
|
1248 |
+
type: mteb/emotion
|
1249 |
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name: MTEB EmotionClassification
|
1250 |
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config: default
|
1251 |
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split: test
|
1252 |
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revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
|
1253 |
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metrics:
|
1254 |
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- type: accuracy
|
1255 |
+
value: 46.86000000000001
|
1256 |
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- type: f1
|
1257 |
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value: 41.343580452760776
|
1258 |
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- task:
|
1259 |
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type: Retrieval
|
1260 |
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dataset:
|
1261 |
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type: fever
|
1262 |
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name: MTEB FEVER
|
1263 |
+
config: default
|
1264 |
+
split: test
|
1265 |
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revision: None
|
1266 |
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metrics:
|
1267 |
+
- type: map_at_1
|
1268 |
+
value: 36.609
|
1269 |
+
- type: map_at_10
|
1270 |
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value: 47.552
|
1271 |
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- type: map_at_100
|
1272 |
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value: 48.283
|
1273 |
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- type: map_at_1000
|
1274 |
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value: 48.321
|
1275 |
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- type: map_at_3
|
1276 |
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value: 44.869
|
1277 |
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- type: map_at_5
|
1278 |
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value: 46.509
|
1279 |
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- type: mrr_at_1
|
1280 |
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value: 39.214
|
1281 |
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- type: mrr_at_10
|
1282 |
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value: 50.434999999999995
|
1283 |
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- type: mrr_at_100
|
1284 |
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value: 51.122
|
1285 |
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- type: mrr_at_1000
|
1286 |
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value: 51.151
|
1287 |
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- type: mrr_at_3
|
1288 |
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value: 47.735
|
1289 |
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- type: mrr_at_5
|
1290 |
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value: 49.394
|
1291 |
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- type: ndcg_at_1
|
1292 |
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value: 39.214
|
1293 |
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- type: ndcg_at_10
|
1294 |
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value: 53.52400000000001
|
1295 |
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- type: ndcg_at_100
|
1296 |
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value: 56.997
|
1297 |
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- type: ndcg_at_1000
|
1298 |
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value: 57.975
|
1299 |
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- type: ndcg_at_3
|
1300 |
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value: 48.173
|
1301 |
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- type: ndcg_at_5
|
1302 |
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value: 51.05800000000001
|
1303 |
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- type: precision_at_1
|
1304 |
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value: 39.214
|
1305 |
+
- type: precision_at_10
|
1306 |
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value: 7.573
|
1307 |
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- type: precision_at_100
|
1308 |
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value: 0.9440000000000001
|
1309 |
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- type: precision_at_1000
|
1310 |
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value: 0.104
|
1311 |
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- type: precision_at_3
|
1312 |
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value: 19.782
|
1313 |
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- type: precision_at_5
|
1314 |
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value: 13.453000000000001
|
1315 |
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- type: recall_at_1
|
1316 |
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value: 36.609
|
1317 |
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- type: recall_at_10
|
1318 |
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value: 69.247
|
1319 |
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- type: recall_at_100
|
1320 |
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value: 84.99600000000001
|
1321 |
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- type: recall_at_1000
|
1322 |
+
value: 92.40899999999999
|
1323 |
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- type: recall_at_3
|
1324 |
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value: 54.856
|
1325 |
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- type: recall_at_5
|
1326 |
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value: 61.797000000000004
|
1327 |
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- task:
|
1328 |
+
type: Retrieval
|
1329 |
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dataset:
|
1330 |
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type: fiqa
|
1331 |
+
name: MTEB FiQA2018
|
1332 |
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config: default
|
1333 |
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split: test
|
1334 |
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revision: None
|
1335 |
+
metrics:
|
1336 |
+
- type: map_at_1
|
1337 |
+
value: 16.466
|
1338 |
+
- type: map_at_10
|
1339 |
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value: 27.060000000000002
|
1340 |
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- type: map_at_100
|
1341 |
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value: 28.511999999999997
|
1342 |
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- type: map_at_1000
|
1343 |
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value: 28.693
|
1344 |
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- type: map_at_3
|
1345 |
+
value: 22.777
|
1346 |
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- type: map_at_5
|
1347 |
+
value: 25.086000000000002
|
1348 |
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- type: mrr_at_1
|
1349 |
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value: 32.716
|
1350 |
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- type: mrr_at_10
|
1351 |
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value: 41.593999999999994
|
1352 |
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- type: mrr_at_100
|
1353 |
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value: 42.370000000000005
|
1354 |
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- type: mrr_at_1000
|
1355 |
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value: 42.419000000000004
|
1356 |
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- type: mrr_at_3
|
1357 |
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value: 38.143
|
1358 |
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- type: mrr_at_5
|
1359 |
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value: 40.288000000000004
|
1360 |
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- type: ndcg_at_1
|
1361 |
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value: 32.716
|
1362 |
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- type: ndcg_at_10
|
1363 |
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value: 34.795
|
1364 |
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- type: ndcg_at_100
|
1365 |
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value: 40.58
|
1366 |
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- type: ndcg_at_1000
|
1367 |
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value: 43.993
|
1368 |
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- type: ndcg_at_3
|
1369 |
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value: 29.573
|
1370 |
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- type: ndcg_at_5
|
1371 |
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value: 31.583
|
1372 |
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- type: precision_at_1
|
1373 |
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value: 32.716
|
1374 |
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- type: precision_at_10
|
1375 |
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value: 9.937999999999999
|
1376 |
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- type: precision_at_100
|
1377 |
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value: 1.585
|
1378 |
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- type: precision_at_1000
|
1379 |
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value: 0.22
|
1380 |
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- type: precision_at_3
|
1381 |
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value: 19.496
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1382 |
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- type: precision_at_5
|
1383 |
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value: 15.247
|
1384 |
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- type: recall_at_1
|
1385 |
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value: 16.466
|
1386 |
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- type: recall_at_10
|
1387 |
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value: 42.886
|
1388 |
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- type: recall_at_100
|
1389 |
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value: 64.724
|
1390 |
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- type: recall_at_1000
|
1391 |
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value: 85.347
|
1392 |
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- type: recall_at_3
|
1393 |
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value: 26.765
|
1394 |
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- type: recall_at_5
|
1395 |
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value: 33.603
|
1396 |
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- task:
|
1397 |
+
type: Retrieval
|
1398 |
+
dataset:
|
1399 |
+
type: hotpotqa
|
1400 |
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name: MTEB HotpotQA
|
1401 |
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config: default
|
1402 |
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split: test
|
1403 |
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revision: None
|
1404 |
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metrics:
|
1405 |
+
- type: map_at_1
|
1406 |
+
value: 33.025
|
1407 |
+
- type: map_at_10
|
1408 |
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value: 47.343
|
1409 |
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- type: map_at_100
|
1410 |
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value: 48.207
|
1411 |
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- type: map_at_1000
|
1412 |
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value: 48.281
|
1413 |
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- type: map_at_3
|
1414 |
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value: 44.519
|
1415 |
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- type: map_at_5
|
1416 |
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value: 46.217000000000006
|
1417 |
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- type: mrr_at_1
|
1418 |
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value: 66.05
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1419 |
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- type: mrr_at_10
|
1420 |
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value: 72.94699999999999
|
1421 |
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- type: mrr_at_100
|
1422 |
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value: 73.289
|
1423 |
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- type: mrr_at_1000
|
1424 |
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value: 73.30499999999999
|
1425 |
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- type: mrr_at_3
|
1426 |
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value: 71.686
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1427 |
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- type: mrr_at_5
|
1428 |
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value: 72.491
|
1429 |
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- type: ndcg_at_1
|
1430 |
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value: 66.05
|
1431 |
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- type: ndcg_at_10
|
1432 |
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value: 56.338
|
1433 |
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- type: ndcg_at_100
|
1434 |
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value: 59.599999999999994
|
1435 |
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- type: ndcg_at_1000
|
1436 |
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value: 61.138000000000005
|
1437 |
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- type: ndcg_at_3
|
1438 |
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value: 52.034000000000006
|
1439 |
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- type: ndcg_at_5
|
1440 |
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value: 54.352000000000004
|
1441 |
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- type: precision_at_1
|
1442 |
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value: 66.05
|
1443 |
+
- type: precision_at_10
|
1444 |
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value: 11.693000000000001
|
1445 |
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- type: precision_at_100
|
1446 |
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value: 1.425
|
1447 |
+
- type: precision_at_1000
|
1448 |
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value: 0.163
|
1449 |
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- type: precision_at_3
|
1450 |
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value: 32.613
|
1451 |
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- type: precision_at_5
|
1452 |
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value: 21.401999999999997
|
1453 |
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- type: recall_at_1
|
1454 |
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value: 33.025
|
1455 |
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- type: recall_at_10
|
1456 |
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value: 58.467
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1457 |
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- type: recall_at_100
|
1458 |
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value: 71.242
|
1459 |
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- type: recall_at_1000
|
1460 |
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value: 81.452
|
1461 |
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- type: recall_at_3
|
1462 |
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value: 48.92
|
1463 |
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- type: recall_at_5
|
1464 |
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value: 53.504
|
1465 |
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- task:
|
1466 |
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type: Classification
|
1467 |
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dataset:
|
1468 |
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type: mteb/imdb
|
1469 |
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name: MTEB ImdbClassification
|
1470 |
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config: default
|
1471 |
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split: test
|
1472 |
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revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
|
1473 |
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metrics:
|
1474 |
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- type: accuracy
|
1475 |
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value: 75.5492
|
1476 |
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- type: ap
|
1477 |
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value: 69.42911637216271
|
1478 |
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- type: f1
|
1479 |
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value: 75.39113704261024
|
1480 |
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- task:
|
1481 |
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type: Retrieval
|
1482 |
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dataset:
|
1483 |
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type: msmarco
|
1484 |
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name: MTEB MSMARCO
|
1485 |
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config: default
|
1486 |
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split: dev
|
1487 |
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revision: None
|
1488 |
+
metrics:
|
1489 |
+
- type: map_at_1
|
1490 |
+
value: 23.173
|
1491 |
+
- type: map_at_10
|
1492 |
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value: 35.453
|
1493 |
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- type: map_at_100
|
1494 |
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value: 36.573
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1495 |
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- type: map_at_1000
|
1496 |
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value: 36.620999999999995
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1497 |
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- type: map_at_3
|
1498 |
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value: 31.655
|
1499 |
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- type: map_at_5
|
1500 |
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value: 33.823
|
1501 |
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- type: mrr_at_1
|
1502 |
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value: 23.868000000000002
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1503 |
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- type: mrr_at_10
|
1504 |
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value: 36.085
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1505 |
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- type: mrr_at_100
|
1506 |
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value: 37.15
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1507 |
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- type: mrr_at_1000
|
1508 |
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value: 37.193
|
1509 |
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- type: mrr_at_3
|
1510 |
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value: 32.376
|
1511 |
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- type: mrr_at_5
|
1512 |
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value: 34.501
|
1513 |
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- type: ndcg_at_1
|
1514 |
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value: 23.854
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1515 |
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- type: ndcg_at_10
|
1516 |
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value: 42.33
|
1517 |
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- type: ndcg_at_100
|
1518 |
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value: 47.705999999999996
|
1519 |
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- type: ndcg_at_1000
|
1520 |
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value: 48.91
|
1521 |
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- type: ndcg_at_3
|
1522 |
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value: 34.604
|
1523 |
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- type: ndcg_at_5
|
1524 |
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value: 38.473
|
1525 |
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- type: precision_at_1
|
1526 |
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value: 23.854
|
1527 |
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- type: precision_at_10
|
1528 |
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value: 6.639
|
1529 |
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- type: precision_at_100
|
1530 |
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value: 0.932
|
1531 |
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- type: precision_at_1000
|
1532 |
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value: 0.104
|
1533 |
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- type: precision_at_3
|
1534 |
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value: 14.685
|
1535 |
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- type: precision_at_5
|
1536 |
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value: 10.782
|
1537 |
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- type: recall_at_1
|
1538 |
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value: 23.173
|
1539 |
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- type: recall_at_10
|
1540 |
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value: 63.441
|
1541 |
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- type: recall_at_100
|
1542 |
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value: 88.25
|
1543 |
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- type: recall_at_1000
|
1544 |
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value: 97.438
|
1545 |
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- type: recall_at_3
|
1546 |
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value: 42.434
|
1547 |
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- type: recall_at_5
|
1548 |
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value: 51.745
|
1549 |
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- task:
|
1550 |
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type: Classification
|
1551 |
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dataset:
|
1552 |
+
type: mteb/mtop_domain
|
1553 |
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name: MTEB MTOPDomainClassification (en)
|
1554 |
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config: en
|
1555 |
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split: test
|
1556 |
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revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
|
1557 |
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metrics:
|
1558 |
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- type: accuracy
|
1559 |
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value: 92.05426356589147
|
1560 |
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- type: f1
|
1561 |
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value: 91.88068588063942
|
1562 |
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- task:
|
1563 |
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type: Classification
|
1564 |
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dataset:
|
1565 |
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type: mteb/mtop_intent
|
1566 |
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name: MTEB MTOPIntentClassification (en)
|
1567 |
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config: en
|
1568 |
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split: test
|
1569 |
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revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
|
1570 |
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metrics:
|
1571 |
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- type: accuracy
|
1572 |
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value: 73.23985408116735
|
1573 |
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- type: f1
|
1574 |
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value: 55.858906745287506
|
1575 |
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- task:
|
1576 |
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type: Classification
|
1577 |
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dataset:
|
1578 |
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type: mteb/amazon_massive_intent
|
1579 |
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name: MTEB MassiveIntentClassification (en)
|
1580 |
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config: en
|
1581 |
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split: test
|
1582 |
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revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
|
1583 |
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metrics:
|
1584 |
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- type: accuracy
|
1585 |
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value: 72.21923335574984
|
1586 |
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- type: f1
|
1587 |
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value: 70.0174116204253
|
1588 |
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- task:
|
1589 |
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type: Classification
|
1590 |
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dataset:
|
1591 |
+
type: mteb/amazon_massive_scenario
|
1592 |
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name: MTEB MassiveScenarioClassification (en)
|
1593 |
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config: en
|
1594 |
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split: test
|
1595 |
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revision: 7d571f92784cd94a019292a1f45445077d0ef634
|
1596 |
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metrics:
|
1597 |
+
- type: accuracy
|
1598 |
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value: 75.77673167451245
|
1599 |
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- type: f1
|
1600 |
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value: 75.44811354778666
|
1601 |
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- task:
|
1602 |
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type: Clustering
|
1603 |
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dataset:
|
1604 |
+
type: mteb/medrxiv-clustering-p2p
|
1605 |
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name: MTEB MedrxivClusteringP2P
|
1606 |
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config: default
|
1607 |
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split: test
|
1608 |
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revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
|
1609 |
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metrics:
|
1610 |
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- type: v_measure
|
1611 |
+
value: 31.340414710728737
|
1612 |
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- task:
|
1613 |
+
type: Clustering
|
1614 |
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dataset:
|
1615 |
+
type: mteb/medrxiv-clustering-s2s
|
1616 |
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name: MTEB MedrxivClusteringS2S
|
1617 |
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config: default
|
1618 |
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split: test
|
1619 |
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revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
|
1620 |
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metrics:
|
1621 |
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- type: v_measure
|
1622 |
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value: 28.196676760061578
|
1623 |
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- task:
|
1624 |
+
type: Reranking
|
1625 |
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dataset:
|
1626 |
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type: mteb/mind_small
|
1627 |
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name: MTEB MindSmallReranking
|
1628 |
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config: default
|
1629 |
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split: test
|
1630 |
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revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
|
1631 |
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metrics:
|
1632 |
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- type: map
|
1633 |
+
value: 29.564149683482206
|
1634 |
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- type: mrr
|
1635 |
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value: 30.28995474250486
|
1636 |
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- task:
|
1637 |
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type: Retrieval
|
1638 |
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dataset:
|
1639 |
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type: nfcorpus
|
1640 |
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name: MTEB NFCorpus
|
1641 |
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config: default
|
1642 |
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split: test
|
1643 |
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revision: None
|
1644 |
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metrics:
|
1645 |
+
- type: map_at_1
|
1646 |
+
value: 5.93
|
1647 |
+
- type: map_at_10
|
1648 |
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value: 12.828000000000001
|
1649 |
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- type: map_at_100
|
1650 |
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value: 15.501000000000001
|
1651 |
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- type: map_at_1000
|
1652 |
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value: 16.791
|
1653 |
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- type: map_at_3
|
1654 |
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value: 9.727
|
1655 |
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- type: map_at_5
|
1656 |
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value: 11.318999999999999
|
1657 |
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- type: mrr_at_1
|
1658 |
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value: 47.678
|
1659 |
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- type: mrr_at_10
|
1660 |
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value: 55.893
|
1661 |
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- type: mrr_at_100
|
1662 |
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value: 56.491
|
1663 |
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- type: mrr_at_1000
|
1664 |
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value: 56.53
|
1665 |
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- type: mrr_at_3
|
1666 |
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value: 54.386
|
1667 |
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- type: mrr_at_5
|
1668 |
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value: 55.516
|
1669 |
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- type: ndcg_at_1
|
1670 |
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value: 45.975
|
1671 |
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- type: ndcg_at_10
|
1672 |
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value: 33.928999999999995
|
1673 |
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- type: ndcg_at_100
|
1674 |
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value: 30.164
|
1675 |
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- type: ndcg_at_1000
|
1676 |
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value: 38.756
|
1677 |
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- type: ndcg_at_3
|
1678 |
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value: 41.077000000000005
|
1679 |
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- type: ndcg_at_5
|
1680 |
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value: 38.415
|
1681 |
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- type: precision_at_1
|
1682 |
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value: 47.678
|
1683 |
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- type: precision_at_10
|
1684 |
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value: 24.365000000000002
|
1685 |
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- type: precision_at_100
|
1686 |
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value: 7.344
|
1687 |
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- type: precision_at_1000
|
1688 |
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value: 1.994
|
1689 |
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- type: precision_at_3
|
1690 |
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value: 38.184000000000005
|
1691 |
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- type: precision_at_5
|
1692 |
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value: 33.003
|
1693 |
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- type: recall_at_1
|
1694 |
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value: 5.93
|
1695 |
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- type: recall_at_10
|
1696 |
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value: 16.239
|
1697 |
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- type: recall_at_100
|
1698 |
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value: 28.782999999999998
|
1699 |
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- type: recall_at_1000
|
1700 |
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value: 60.11
|
1701 |
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- type: recall_at_3
|
1702 |
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value: 10.700999999999999
|
1703 |
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- type: recall_at_5
|
1704 |
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value: 13.584
|
1705 |
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- task:
|
1706 |
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type: Retrieval
|
1707 |
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dataset:
|
1708 |
+
type: nq
|
1709 |
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name: MTEB NQ
|
1710 |
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config: default
|
1711 |
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split: test
|
1712 |
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revision: None
|
1713 |
+
metrics:
|
1714 |
+
- type: map_at_1
|
1715 |
+
value: 36.163000000000004
|
1716 |
+
- type: map_at_10
|
1717 |
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value: 51.520999999999994
|
1718 |
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- type: map_at_100
|
1719 |
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value: 52.449
|
1720 |
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- type: map_at_1000
|
1721 |
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value: 52.473000000000006
|
1722 |
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- type: map_at_3
|
1723 |
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value: 47.666
|
1724 |
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- type: map_at_5
|
1725 |
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value: 50.043000000000006
|
1726 |
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- type: mrr_at_1
|
1727 |
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value: 40.266999999999996
|
1728 |
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- type: mrr_at_10
|
1729 |
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value: 54.074
|
1730 |
+
- type: mrr_at_100
|
1731 |
+
value: 54.722
|
1732 |
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- type: mrr_at_1000
|
1733 |
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value: 54.739000000000004
|
1734 |
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- type: mrr_at_3
|
1735 |
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value: 51.043000000000006
|
1736 |
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- type: mrr_at_5
|
1737 |
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value: 52.956
|
1738 |
+
- type: ndcg_at_1
|
1739 |
+
value: 40.238
|
1740 |
+
- type: ndcg_at_10
|
1741 |
+
value: 58.73199999999999
|
1742 |
+
- type: ndcg_at_100
|
1743 |
+
value: 62.470000000000006
|
1744 |
+
- type: ndcg_at_1000
|
1745 |
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value: 63.083999999999996
|
1746 |
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- type: ndcg_at_3
|
1747 |
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value: 51.672
|
1748 |
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- type: ndcg_at_5
|
1749 |
+
value: 55.564
|
1750 |
+
- type: precision_at_1
|
1751 |
+
value: 40.238
|
1752 |
+
- type: precision_at_10
|
1753 |
+
value: 9.279
|
1754 |
+
- type: precision_at_100
|
1755 |
+
value: 1.139
|
1756 |
+
- type: precision_at_1000
|
1757 |
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value: 0.12
|
1758 |
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- type: precision_at_3
|
1759 |
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value: 23.078000000000003
|
1760 |
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- type: precision_at_5
|
1761 |
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value: 16.176
|
1762 |
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- type: recall_at_1
|
1763 |
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value: 36.163000000000004
|
1764 |
+
- type: recall_at_10
|
1765 |
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value: 77.88199999999999
|
1766 |
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- type: recall_at_100
|
1767 |
+
value: 93.83399999999999
|
1768 |
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- type: recall_at_1000
|
1769 |
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value: 98.465
|
1770 |
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- type: recall_at_3
|
1771 |
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value: 59.857000000000006
|
1772 |
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- type: recall_at_5
|
1773 |
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value: 68.73599999999999
|
1774 |
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- task:
|
1775 |
+
type: Retrieval
|
1776 |
+
dataset:
|
1777 |
+
type: quora
|
1778 |
+
name: MTEB QuoraRetrieval
|
1779 |
+
config: default
|
1780 |
+
split: test
|
1781 |
+
revision: None
|
1782 |
+
metrics:
|
1783 |
+
- type: map_at_1
|
1784 |
+
value: 70.344
|
1785 |
+
- type: map_at_10
|
1786 |
+
value: 83.907
|
1787 |
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- type: map_at_100
|
1788 |
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value: 84.536
|
1789 |
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- type: map_at_1000
|
1790 |
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value: 84.557
|
1791 |
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- type: map_at_3
|
1792 |
+
value: 80.984
|
1793 |
+
- type: map_at_5
|
1794 |
+
value: 82.844
|
1795 |
+
- type: mrr_at_1
|
1796 |
+
value: 81.02000000000001
|
1797 |
+
- type: mrr_at_10
|
1798 |
+
value: 87.158
|
1799 |
+
- type: mrr_at_100
|
1800 |
+
value: 87.268
|
1801 |
+
- type: mrr_at_1000
|
1802 |
+
value: 87.26899999999999
|
1803 |
+
- type: mrr_at_3
|
1804 |
+
value: 86.17
|
1805 |
+
- type: mrr_at_5
|
1806 |
+
value: 86.87
|
1807 |
+
- type: ndcg_at_1
|
1808 |
+
value: 81.02000000000001
|
1809 |
+
- type: ndcg_at_10
|
1810 |
+
value: 87.70700000000001
|
1811 |
+
- type: ndcg_at_100
|
1812 |
+
value: 89.004
|
1813 |
+
- type: ndcg_at_1000
|
1814 |
+
value: 89.139
|
1815 |
+
- type: ndcg_at_3
|
1816 |
+
value: 84.841
|
1817 |
+
- type: ndcg_at_5
|
1818 |
+
value: 86.455
|
1819 |
+
- type: precision_at_1
|
1820 |
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value: 81.02000000000001
|
1821 |
+
- type: precision_at_10
|
1822 |
+
value: 13.248999999999999
|
1823 |
+
- type: precision_at_100
|
1824 |
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value: 1.516
|
1825 |
+
- type: precision_at_1000
|
1826 |
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value: 0.156
|
1827 |
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- type: precision_at_3
|
1828 |
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value: 36.963
|
1829 |
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- type: precision_at_5
|
1830 |
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value: 24.33
|
1831 |
+
- type: recall_at_1
|
1832 |
+
value: 70.344
|
1833 |
+
- type: recall_at_10
|
1834 |
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value: 94.75099999999999
|
1835 |
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- type: recall_at_100
|
1836 |
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value: 99.30499999999999
|
1837 |
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- type: recall_at_1000
|
1838 |
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value: 99.928
|
1839 |
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- type: recall_at_3
|
1840 |
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value: 86.506
|
1841 |
+
- type: recall_at_5
|
1842 |
+
value: 91.083
|
1843 |
+
- task:
|
1844 |
+
type: Clustering
|
1845 |
+
dataset:
|
1846 |
+
type: mteb/reddit-clustering
|
1847 |
+
name: MTEB RedditClustering
|
1848 |
+
config: default
|
1849 |
+
split: test
|
1850 |
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revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
|
1851 |
+
metrics:
|
1852 |
+
- type: v_measure
|
1853 |
+
value: 42.873718018378305
|
1854 |
+
- task:
|
1855 |
+
type: Clustering
|
1856 |
+
dataset:
|
1857 |
+
type: mteb/reddit-clustering-p2p
|
1858 |
+
name: MTEB RedditClusteringP2P
|
1859 |
+
config: default
|
1860 |
+
split: test
|
1861 |
+
revision: 282350215ef01743dc01b456c7f5241fa8937f16
|
1862 |
+
metrics:
|
1863 |
+
- type: v_measure
|
1864 |
+
value: 56.39477366450528
|
1865 |
+
- task:
|
1866 |
+
type: Retrieval
|
1867 |
+
dataset:
|
1868 |
+
type: scidocs
|
1869 |
+
name: MTEB SCIDOCS
|
1870 |
+
config: default
|
1871 |
+
split: test
|
1872 |
+
revision: None
|
1873 |
+
metrics:
|
1874 |
+
- type: map_at_1
|
1875 |
+
value: 3.868
|
1876 |
+
- type: map_at_10
|
1877 |
+
value: 9.611
|
1878 |
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- type: map_at_100
|
1879 |
+
value: 11.087
|
1880 |
+
- type: map_at_1000
|
1881 |
+
value: 11.332
|
1882 |
+
- type: map_at_3
|
1883 |
+
value: 6.813
|
1884 |
+
- type: map_at_5
|
1885 |
+
value: 8.233
|
1886 |
+
- type: mrr_at_1
|
1887 |
+
value: 19.0
|
1888 |
+
- type: mrr_at_10
|
1889 |
+
value: 28.457
|
1890 |
+
- type: mrr_at_100
|
1891 |
+
value: 29.613
|
1892 |
+
- type: mrr_at_1000
|
1893 |
+
value: 29.695
|
1894 |
+
- type: mrr_at_3
|
1895 |
+
value: 25.55
|
1896 |
+
- type: mrr_at_5
|
1897 |
+
value: 27.29
|
1898 |
+
- type: ndcg_at_1
|
1899 |
+
value: 19.0
|
1900 |
+
- type: ndcg_at_10
|
1901 |
+
value: 16.419
|
1902 |
+
- type: ndcg_at_100
|
1903 |
+
value: 22.817999999999998
|
1904 |
+
- type: ndcg_at_1000
|
1905 |
+
value: 27.72
|
1906 |
+
- type: ndcg_at_3
|
1907 |
+
value: 15.379000000000001
|
1908 |
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- type: ndcg_at_5
|
1909 |
+
value: 13.645
|
1910 |
+
- type: precision_at_1
|
1911 |
+
value: 19.0
|
1912 |
+
- type: precision_at_10
|
1913 |
+
value: 8.540000000000001
|
1914 |
+
- type: precision_at_100
|
1915 |
+
value: 1.7819999999999998
|
1916 |
+
- type: precision_at_1000
|
1917 |
+
value: 0.297
|
1918 |
+
- type: precision_at_3
|
1919 |
+
value: 14.267
|
1920 |
+
- type: precision_at_5
|
1921 |
+
value: 12.04
|
1922 |
+
- type: recall_at_1
|
1923 |
+
value: 3.868
|
1924 |
+
- type: recall_at_10
|
1925 |
+
value: 17.288
|
1926 |
+
- type: recall_at_100
|
1927 |
+
value: 36.144999999999996
|
1928 |
+
- type: recall_at_1000
|
1929 |
+
value: 60.199999999999996
|
1930 |
+
- type: recall_at_3
|
1931 |
+
value: 8.688
|
1932 |
+
- type: recall_at_5
|
1933 |
+
value: 12.198
|
1934 |
+
- task:
|
1935 |
+
type: STS
|
1936 |
+
dataset:
|
1937 |
+
type: mteb/sickr-sts
|
1938 |
+
name: MTEB SICK-R
|
1939 |
+
config: default
|
1940 |
+
split: test
|
1941 |
+
revision: a6ea5a8cab320b040a23452cc28066d9beae2cee
|
1942 |
+
metrics:
|
1943 |
+
- type: cos_sim_pearson
|
1944 |
+
value: 83.96614722598582
|
1945 |
+
- type: cos_sim_spearman
|
1946 |
+
value: 78.9003023008781
|
1947 |
+
- type: euclidean_pearson
|
1948 |
+
value: 81.01829384436505
|
1949 |
+
- type: euclidean_spearman
|
1950 |
+
value: 78.93248416788914
|
1951 |
+
- type: manhattan_pearson
|
1952 |
+
value: 81.1665428926402
|
1953 |
+
- type: manhattan_spearman
|
1954 |
+
value: 78.93264116287453
|
1955 |
+
- task:
|
1956 |
+
type: STS
|
1957 |
+
dataset:
|
1958 |
+
type: mteb/sts12-sts
|
1959 |
+
name: MTEB STS12
|
1960 |
+
config: default
|
1961 |
+
split: test
|
1962 |
+
revision: a0d554a64d88156834ff5ae9920b964011b16384
|
1963 |
+
metrics:
|
1964 |
+
- type: cos_sim_pearson
|
1965 |
+
value: 83.54613363895993
|
1966 |
+
- type: cos_sim_spearman
|
1967 |
+
value: 75.1883451602451
|
1968 |
+
- type: euclidean_pearson
|
1969 |
+
value: 79.70320886899894
|
1970 |
+
- type: euclidean_spearman
|
1971 |
+
value: 74.5917140136796
|
1972 |
+
- type: manhattan_pearson
|
1973 |
+
value: 79.82157067185999
|
1974 |
+
- type: manhattan_spearman
|
1975 |
+
value: 74.74185720594735
|
1976 |
+
- task:
|
1977 |
+
type: STS
|
1978 |
+
dataset:
|
1979 |
+
type: mteb/sts13-sts
|
1980 |
+
name: MTEB STS13
|
1981 |
+
config: default
|
1982 |
+
split: test
|
1983 |
+
revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
|
1984 |
+
metrics:
|
1985 |
+
- type: cos_sim_pearson
|
1986 |
+
value: 81.30430156721782
|
1987 |
+
- type: cos_sim_spearman
|
1988 |
+
value: 81.79962989974364
|
1989 |
+
- type: euclidean_pearson
|
1990 |
+
value: 80.89058823224924
|
1991 |
+
- type: euclidean_spearman
|
1992 |
+
value: 81.35929372984597
|
1993 |
+
- type: manhattan_pearson
|
1994 |
+
value: 81.12204370487478
|
1995 |
+
- type: manhattan_spearman
|
1996 |
+
value: 81.6248963282232
|
1997 |
+
- task:
|
1998 |
+
type: STS
|
1999 |
+
dataset:
|
2000 |
+
type: mteb/sts14-sts
|
2001 |
+
name: MTEB STS14
|
2002 |
+
config: default
|
2003 |
+
split: test
|
2004 |
+
revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
|
2005 |
+
metrics:
|
2006 |
+
- type: cos_sim_pearson
|
2007 |
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value: 81.13064504403134
|
2008 |
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- type: cos_sim_spearman
|
2009 |
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value: 78.48371403924872
|
2010 |
+
- type: euclidean_pearson
|
2011 |
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value: 80.16794919665591
|
2012 |
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- type: euclidean_spearman
|
2013 |
+
value: 78.29216082221699
|
2014 |
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- type: manhattan_pearson
|
2015 |
+
value: 80.22308565207301
|
2016 |
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- type: manhattan_spearman
|
2017 |
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value: 78.37829229948022
|
2018 |
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- task:
|
2019 |
+
type: STS
|
2020 |
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dataset:
|
2021 |
+
type: mteb/sts15-sts
|
2022 |
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name: MTEB STS15
|
2023 |
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config: default
|
2024 |
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split: test
|
2025 |
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revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
|
2026 |
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metrics:
|
2027 |
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- type: cos_sim_pearson
|
2028 |
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value: 86.52918899541099
|
2029 |
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- type: cos_sim_spearman
|
2030 |
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value: 87.49276894673142
|
2031 |
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- type: euclidean_pearson
|
2032 |
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|
2033 |
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- type: euclidean_spearman
|
2034 |
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|
2035 |
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- type: manhattan_pearson
|
2036 |
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|
2037 |
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- type: manhattan_spearman
|
2038 |
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|
2039 |
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- task:
|
2040 |
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type: STS
|
2041 |
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dataset:
|
2042 |
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type: mteb/sts16-sts
|
2043 |
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name: MTEB STS16
|
2044 |
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config: default
|
2045 |
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split: test
|
2046 |
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revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
|
2047 |
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metrics:
|
2048 |
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- type: cos_sim_pearson
|
2049 |
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value: 82.86805307244882
|
2050 |
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- type: cos_sim_spearman
|
2051 |
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value: 84.58066253757511
|
2052 |
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- type: euclidean_pearson
|
2053 |
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value: 84.38377000876991
|
2054 |
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- type: euclidean_spearman
|
2055 |
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value: 85.1837278784528
|
2056 |
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- type: manhattan_pearson
|
2057 |
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|
2058 |
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- type: manhattan_spearman
|
2059 |
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|
2060 |
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- task:
|
2061 |
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type: STS
|
2062 |
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dataset:
|
2063 |
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type: mteb/sts17-crosslingual-sts
|
2064 |
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name: MTEB STS17 (en-en)
|
2065 |
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config: en-en
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2066 |
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split: test
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2067 |
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revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
|
2068 |
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metrics:
|
2069 |
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- type: cos_sim_pearson
|
2070 |
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value: 86.77218560282436
|
2071 |
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- type: cos_sim_spearman
|
2072 |
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|
2073 |
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- type: euclidean_pearson
|
2074 |
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|
2075 |
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- type: euclidean_spearman
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2076 |
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|
2077 |
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- type: manhattan_pearson
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2078 |
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|
2079 |
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- type: manhattan_spearman
|
2080 |
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|
2081 |
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- task:
|
2082 |
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type: STS
|
2083 |
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dataset:
|
2084 |
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type: mteb/sts22-crosslingual-sts
|
2085 |
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name: MTEB STS22 (en)
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2086 |
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config: en
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2087 |
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split: test
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2088 |
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revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80
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2089 |
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metrics:
|
2090 |
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- type: cos_sim_pearson
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2091 |
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2092 |
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- type: cos_sim_spearman
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2093 |
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2094 |
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- type: euclidean_pearson
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2095 |
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2096 |
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- type: euclidean_spearman
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2097 |
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2098 |
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- type: manhattan_pearson
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2099 |
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2100 |
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- type: manhattan_spearman
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2101 |
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2102 |
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- task:
|
2103 |
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type: STS
|
2104 |
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dataset:
|
2105 |
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type: mteb/stsbenchmark-sts
|
2106 |
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name: MTEB STSBenchmark
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2107 |
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config: default
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2108 |
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split: test
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2109 |
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revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
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2110 |
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metrics:
|
2111 |
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- type: cos_sim_pearson
|
2112 |
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value: 84.92731569745344
|
2113 |
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- type: cos_sim_spearman
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2114 |
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2115 |
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- type: euclidean_pearson
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2116 |
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2117 |
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- type: euclidean_spearman
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2118 |
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2119 |
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- type: manhattan_pearson
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2120 |
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|
2121 |
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- type: manhattan_spearman
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2122 |
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value: 86.2022069635119
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2123 |
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- task:
|
2124 |
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type: Reranking
|
2125 |
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dataset:
|
2126 |
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type: mteb/scidocs-reranking
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2127 |
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name: MTEB SciDocsRR
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2128 |
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config: default
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2129 |
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split: test
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2130 |
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revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
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2131 |
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metrics:
|
2132 |
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- type: map
|
2133 |
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value: 79.75976311752326
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2134 |
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- type: mrr
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2135 |
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|
2136 |
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- task:
|
2137 |
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type: Retrieval
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2138 |
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dataset:
|
2139 |
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type: scifact
|
2140 |
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name: MTEB SciFact
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2141 |
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config: default
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2142 |
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split: test
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2143 |
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revision: None
|
2144 |
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metrics:
|
2145 |
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- type: map_at_1
|
2146 |
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value: 51.193999999999996
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2147 |
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- type: map_at_10
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2148 |
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value: 61.224999999999994
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2149 |
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- type: map_at_100
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2150 |
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value: 62.031000000000006
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2151 |
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- type: map_at_1000
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2152 |
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2153 |
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- type: map_at_3
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2154 |
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value: 59.269000000000005
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2155 |
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- type: map_at_5
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2156 |
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value: 60.159
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2157 |
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- type: mrr_at_1
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2158 |
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value: 53.667
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2159 |
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- type: mrr_at_10
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2160 |
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value: 62.74999999999999
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2161 |
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- type: mrr_at_100
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2162 |
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value: 63.39399999999999
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2163 |
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- type: mrr_at_1000
|
2164 |
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value: 63.425
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2165 |
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- type: mrr_at_3
|
2166 |
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value: 61.389
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2167 |
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- type: mrr_at_5
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2168 |
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value: 61.989000000000004
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2169 |
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- type: ndcg_at_1
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2170 |
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2171 |
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- type: ndcg_at_10
|
2172 |
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value: 65.596
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2173 |
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- type: ndcg_at_100
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2174 |
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value: 68.906
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2175 |
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- type: ndcg_at_1000
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2176 |
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value: 69.78999999999999
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2177 |
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- type: ndcg_at_3
|
2178 |
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value: 62.261
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2179 |
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- type: ndcg_at_5
|
2180 |
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value: 63.453
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2181 |
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- type: precision_at_1
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2182 |
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value: 53.667
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2183 |
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- type: precision_at_10
|
2184 |
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value: 8.667
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2185 |
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- type: precision_at_100
|
2186 |
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value: 1.04
|
2187 |
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- type: precision_at_1000
|
2188 |
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value: 0.11100000000000002
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2189 |
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- type: precision_at_3
|
2190 |
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value: 24.556
|
2191 |
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- type: precision_at_5
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2192 |
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value: 15.6
|
2193 |
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- type: recall_at_1
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2194 |
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value: 51.193999999999996
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2195 |
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- type: recall_at_10
|
2196 |
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value: 77.156
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2197 |
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- type: recall_at_100
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2198 |
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value: 91.43299999999999
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2199 |
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- type: recall_at_1000
|
2200 |
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value: 98.333
|
2201 |
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- type: recall_at_3
|
2202 |
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value: 67.994
|
2203 |
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- type: recall_at_5
|
2204 |
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value: 71.14399999999999
|
2205 |
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- task:
|
2206 |
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type: PairClassification
|
2207 |
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dataset:
|
2208 |
+
type: mteb/sprintduplicatequestions-pairclassification
|
2209 |
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name: MTEB SprintDuplicateQuestions
|
2210 |
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config: default
|
2211 |
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split: test
|
2212 |
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revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
|
2213 |
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metrics:
|
2214 |
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- type: cos_sim_accuracy
|
2215 |
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value: 99.81485148514851
|
2216 |
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- type: cos_sim_ap
|
2217 |
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value: 95.28896513388551
|
2218 |
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- type: cos_sim_f1
|
2219 |
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value: 90.43478260869566
|
2220 |
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- type: cos_sim_precision
|
2221 |
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value: 92.56544502617801
|
2222 |
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- type: cos_sim_recall
|
2223 |
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value: 88.4
|
2224 |
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- type: dot_accuracy
|
2225 |
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value: 99.30594059405941
|
2226 |
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- type: dot_ap
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2227 |
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value: 61.6432597455472
|
2228 |
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- type: dot_f1
|
2229 |
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value: 59.46481665014866
|
2230 |
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- type: dot_precision
|
2231 |
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value: 58.93909626719057
|
2232 |
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- type: dot_recall
|
2233 |
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value: 60.0
|
2234 |
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- type: euclidean_accuracy
|
2235 |
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value: 99.81980198019802
|
2236 |
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- type: euclidean_ap
|
2237 |
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value: 95.21411049527
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2238 |
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- type: euclidean_f1
|
2239 |
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value: 91.06090373280944
|
2240 |
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- type: euclidean_precision
|
2241 |
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value: 89.47876447876449
|
2242 |
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- type: euclidean_recall
|
2243 |
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value: 92.7
|
2244 |
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- type: manhattan_accuracy
|
2245 |
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value: 99.81782178217821
|
2246 |
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- type: manhattan_ap
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2247 |
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value: 95.32449994414968
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2248 |
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- type: manhattan_f1
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2249 |
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value: 90.86395233366436
|
2250 |
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- type: manhattan_precision
|
2251 |
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value: 90.23668639053254
|
2252 |
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- type: manhattan_recall
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2253 |
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value: 91.5
|
2254 |
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- type: max_accuracy
|
2255 |
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value: 99.81980198019802
|
2256 |
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- type: max_ap
|
2257 |
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value: 95.32449994414968
|
2258 |
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- type: max_f1
|
2259 |
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value: 91.06090373280944
|
2260 |
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- task:
|
2261 |
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type: Clustering
|
2262 |
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dataset:
|
2263 |
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type: mteb/stackexchange-clustering
|
2264 |
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name: MTEB StackExchangeClustering
|
2265 |
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config: default
|
2266 |
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split: test
|
2267 |
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revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
|
2268 |
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metrics:
|
2269 |
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- type: v_measure
|
2270 |
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value: 59.08045614613064
|
2271 |
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- task:
|
2272 |
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type: Clustering
|
2273 |
+
dataset:
|
2274 |
+
type: mteb/stackexchange-clustering-p2p
|
2275 |
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name: MTEB StackExchangeClusteringP2P
|
2276 |
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config: default
|
2277 |
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split: test
|
2278 |
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2279 |
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metrics:
|
2280 |
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- type: v_measure
|
2281 |
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value: 30.297802606804748
|
2282 |
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- task:
|
2283 |
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type: Reranking
|
2284 |
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dataset:
|
2285 |
+
type: mteb/stackoverflowdupquestions-reranking
|
2286 |
+
name: MTEB StackOverflowDupQuestions
|
2287 |
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config: default
|
2288 |
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split: test
|
2289 |
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revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
|
2290 |
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metrics:
|
2291 |
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- type: map
|
2292 |
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value: 49.12801740706292
|
2293 |
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- type: mrr
|
2294 |
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value: 50.05592956879722
|
2295 |
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- task:
|
2296 |
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type: Summarization
|
2297 |
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dataset:
|
2298 |
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type: mteb/summeval
|
2299 |
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name: MTEB SummEval
|
2300 |
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config: default
|
2301 |
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split: test
|
2302 |
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revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
|
2303 |
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metrics:
|
2304 |
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- type: cos_sim_pearson
|
2305 |
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value: 23.380995453661917
|
2306 |
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- type: cos_sim_spearman
|
2307 |
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value: 24.941761858688917
|
2308 |
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- type: dot_pearson
|
2309 |
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value: 24.930577961642413
|
2310 |
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- type: dot_spearman
|
2311 |
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value: 24.804715835064492
|
2312 |
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- task:
|
2313 |
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type: Retrieval
|
2314 |
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dataset:
|
2315 |
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type: trec-covid
|
2316 |
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name: MTEB TRECCOVID
|
2317 |
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config: default
|
2318 |
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split: test
|
2319 |
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revision: None
|
2320 |
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metrics:
|
2321 |
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- type: map_at_1
|
2322 |
+
value: 0.243
|
2323 |
+
- type: map_at_10
|
2324 |
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value: 1.886
|
2325 |
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- type: map_at_100
|
2326 |
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value: 10.040000000000001
|
2327 |
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- type: map_at_1000
|
2328 |
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value: 23.768
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2329 |
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- type: map_at_3
|
2330 |
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value: 0.674
|
2331 |
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- type: map_at_5
|
2332 |
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value: 1.079
|
2333 |
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- type: mrr_at_1
|
2334 |
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value: 88.0
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2335 |
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|
2336 |
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value: 93.667
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2337 |
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2338 |
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value: 93.667
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2339 |
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- type: mrr_at_1000
|
2340 |
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value: 93.667
|
2341 |
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- type: mrr_at_3
|
2342 |
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|
2343 |
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- type: mrr_at_5
|
2344 |
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value: 93.667
|
2345 |
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- type: ndcg_at_1
|
2346 |
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value: 83.0
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2347 |
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|
2348 |
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value: 76.777
|
2349 |
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- type: ndcg_at_100
|
2350 |
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value: 55.153
|
2351 |
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- type: ndcg_at_1000
|
2352 |
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value: 47.912
|
2353 |
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- type: ndcg_at_3
|
2354 |
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value: 81.358
|
2355 |
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|
2356 |
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value: 80.74799999999999
|
2357 |
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- type: precision_at_1
|
2358 |
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value: 88.0
|
2359 |
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- type: precision_at_10
|
2360 |
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value: 80.80000000000001
|
2361 |
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- type: precision_at_100
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2362 |
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value: 56.02
|
2363 |
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- type: precision_at_1000
|
2364 |
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value: 21.51
|
2365 |
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- type: precision_at_3
|
2366 |
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value: 86.0
|
2367 |
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- type: precision_at_5
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2368 |
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value: 86.0
|
2369 |
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- type: recall_at_1
|
2370 |
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value: 0.243
|
2371 |
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- type: recall_at_10
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2372 |
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value: 2.0869999999999997
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2373 |
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- type: recall_at_100
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2374 |
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value: 13.014000000000001
|
2375 |
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- type: recall_at_1000
|
2376 |
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value: 44.433
|
2377 |
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- type: recall_at_3
|
2378 |
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value: 0.6910000000000001
|
2379 |
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- type: recall_at_5
|
2380 |
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value: 1.1440000000000001
|
2381 |
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- task:
|
2382 |
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type: Retrieval
|
2383 |
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dataset:
|
2384 |
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type: webis-touche2020
|
2385 |
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name: MTEB Touche2020
|
2386 |
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config: default
|
2387 |
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split: test
|
2388 |
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revision: None
|
2389 |
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metrics:
|
2390 |
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- type: map_at_1
|
2391 |
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value: 3.066
|
2392 |
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- type: map_at_10
|
2393 |
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value: 10.615
|
2394 |
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- type: map_at_100
|
2395 |
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value: 16.463
|
2396 |
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- type: map_at_1000
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2397 |
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value: 17.815
|
2398 |
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- type: map_at_3
|
2399 |
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value: 5.7860000000000005
|
2400 |
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- type: map_at_5
|
2401 |
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value: 7.353999999999999
|
2402 |
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- type: mrr_at_1
|
2403 |
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value: 38.775999999999996
|
2404 |
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- type: mrr_at_10
|
2405 |
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value: 53.846000000000004
|
2406 |
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- type: mrr_at_100
|
2407 |
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value: 54.37
|
2408 |
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- type: mrr_at_1000
|
2409 |
+
value: 54.37
|
2410 |
+
- type: mrr_at_3
|
2411 |
+
value: 48.980000000000004
|
2412 |
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- type: mrr_at_5
|
2413 |
+
value: 51.735
|
2414 |
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- type: ndcg_at_1
|
2415 |
+
value: 34.694
|
2416 |
+
- type: ndcg_at_10
|
2417 |
+
value: 26.811
|
2418 |
+
- type: ndcg_at_100
|
2419 |
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value: 37.342999999999996
|
2420 |
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- type: ndcg_at_1000
|
2421 |
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value: 47.964
|
2422 |
+
- type: ndcg_at_3
|
2423 |
+
value: 30.906
|
2424 |
+
- type: ndcg_at_5
|
2425 |
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value: 27.77
|
2426 |
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- type: precision_at_1
|
2427 |
+
value: 38.775999999999996
|
2428 |
+
- type: precision_at_10
|
2429 |
+
value: 23.878
|
2430 |
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- type: precision_at_100
|
2431 |
+
value: 7.632999999999999
|
2432 |
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- type: precision_at_1000
|
2433 |
+
value: 1.469
|
2434 |
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- type: precision_at_3
|
2435 |
+
value: 31.973000000000003
|
2436 |
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- type: precision_at_5
|
2437 |
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value: 26.939
|
2438 |
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- type: recall_at_1
|
2439 |
+
value: 3.066
|
2440 |
+
- type: recall_at_10
|
2441 |
+
value: 17.112
|
2442 |
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- type: recall_at_100
|
2443 |
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value: 47.723
|
2444 |
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- type: recall_at_1000
|
2445 |
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value: 79.50500000000001
|
2446 |
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- type: recall_at_3
|
2447 |
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value: 6.825
|
2448 |
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- type: recall_at_5
|
2449 |
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value: 9.584
|
2450 |
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- task:
|
2451 |
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type: Classification
|
2452 |
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dataset:
|
2453 |
+
type: mteb/toxic_conversations_50k
|
2454 |
+
name: MTEB ToxicConversationsClassification
|
2455 |
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config: default
|
2456 |
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split: test
|
2457 |
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revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
|
2458 |
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metrics:
|
2459 |
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- type: accuracy
|
2460 |
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value: 72.76460000000002
|
2461 |
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- type: ap
|
2462 |
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value: 14.944240012137053
|
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|
2464 |
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value: 55.89805777266571
|
2465 |
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- task:
|
2466 |
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type: Classification
|
2467 |
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dataset:
|
2468 |
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type: mteb/tweet_sentiment_extraction
|
2469 |
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name: MTEB TweetSentimentExtractionClassification
|
2470 |
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config: default
|
2471 |
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split: test
|
2472 |
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revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
|
2473 |
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metrics:
|
2474 |
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- type: accuracy
|
2475 |
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value: 63.30503678551217
|
2476 |
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- type: f1
|
2477 |
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value: 63.57492701921179
|
2478 |
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- task:
|
2479 |
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type: Clustering
|
2480 |
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dataset:
|
2481 |
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type: mteb/twentynewsgroups-clustering
|
2482 |
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name: MTEB TwentyNewsgroupsClustering
|
2483 |
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config: default
|
2484 |
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split: test
|
2485 |
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revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
|
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metrics:
|
2487 |
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- type: v_measure
|
2488 |
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value: 37.51066495006874
|
2489 |
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- task:
|
2490 |
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type: PairClassification
|
2491 |
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dataset:
|
2492 |
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type: mteb/twittersemeval2015-pairclassification
|
2493 |
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name: MTEB TwitterSemEval2015
|
2494 |
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config: default
|
2495 |
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split: test
|
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revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
|
2497 |
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metrics:
|
2498 |
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- type: cos_sim_accuracy
|
2499 |
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value: 86.07021517553794
|
2500 |
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- type: cos_sim_ap
|
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value: 74.15520712370555
|
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- type: cos_sim_f1
|
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value: 68.64321608040201
|
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- type: cos_sim_precision
|
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value: 65.51558752997602
|
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- type: cos_sim_recall
|
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value: 72.0844327176781
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- type: dot_accuracy
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value: 80.23484532395541
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2511 |
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value: 54.298763810214176
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2513 |
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value: 53.22254659779924
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2514 |
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|
2515 |
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value: 46.32525410476936
|
2516 |
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- type: dot_recall
|
2517 |
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value: 62.532981530343015
|
2518 |
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- type: euclidean_accuracy
|
2519 |
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value: 86.04637301066937
|
2520 |
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- type: euclidean_ap
|
2521 |
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value: 73.85333854233123
|
2522 |
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- type: euclidean_f1
|
2523 |
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value: 68.77723660599845
|
2524 |
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- type: euclidean_precision
|
2525 |
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value: 66.87437686939182
|
2526 |
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- type: euclidean_recall
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2527 |
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value: 70.79155672823218
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2528 |
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- type: manhattan_accuracy
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2529 |
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value: 85.98676759849795
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2530 |
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- type: manhattan_ap
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2531 |
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value: 73.56016090035973
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2532 |
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- type: manhattan_f1
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2534 |
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- type: manhattan_precision
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2535 |
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value: 63.9505607690547
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2536 |
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- type: manhattan_recall
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value: 73.7203166226913
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2538 |
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- type: max_accuracy
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2540 |
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2542 |
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- type: max_f1
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2543 |
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value: 68.77723660599845
|
2544 |
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- task:
|
2545 |
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type: PairClassification
|
2546 |
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dataset:
|
2547 |
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type: mteb/twitterurlcorpus-pairclassification
|
2548 |
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name: MTEB TwitterURLCorpus
|
2549 |
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config: default
|
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split: test
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revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
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metrics:
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|
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2555 |
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- type: euclidean_precision
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- type: manhattan_accuracy
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value: 88.96262661543835
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- type: manhattan_f1
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- type: manhattan_precision
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- type: manhattan_recall
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value: 81.71388974437943
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- type: max_accuracy
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2597 |
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- type: max_f1
|
2598 |
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value: 78.26696165191743
|
2599 |
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---
|
pytorch_model.bin
ADDED
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special_tokens_map.json
ADDED
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|
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{"unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]"}
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tokenizer.json
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tokenizer_config.json
ADDED
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|
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{"do_lower_case": true, "unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]", "tokenize_chinese_chars": true, "strip_accents": null, "special_tokens_map_file": null, "name_or_path": "amlt/1109_tnlrv3_bs32k_ft/all_kd_ft", "do_basic_tokenize": true, "never_split": null, "tokenizer_class": "BertTokenizer"}
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vocab.txt
ADDED
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