Update README.md
Browse files
README.md
CHANGED
@@ -6,14 +6,2605 @@ tags:
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- sentence-transformers
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- feature-extraction
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- sentence-similarity
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- alibi
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datasets:
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-
-
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language: en
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license: apache-2.0
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model-index:
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|
17 |
---
|
18 |
<!-- TODO: add evaluation results here -->
|
19 |
<br><br>
|
|
|
6 |
- sentence-transformers
|
7 |
- feature-extraction
|
8 |
- sentence-similarity
|
|
|
9 |
datasets:
|
10 |
+
- jinaai/negation-dataset
|
11 |
language: en
|
12 |
license: apache-2.0
|
13 |
model-index:
|
14 |
+
- name: jina-embedding-s-en-v2
|
15 |
+
results:
|
16 |
+
- task:
|
17 |
+
type: Classification
|
18 |
+
dataset:
|
19 |
+
type: mteb/amazon_counterfactual
|
20 |
+
name: MTEB AmazonCounterfactualClassification (en)
|
21 |
+
config: en
|
22 |
+
split: test
|
23 |
+
revision: e8379541af4e31359cca9fbcf4b00f2671dba205
|
24 |
+
metrics:
|
25 |
+
- type: accuracy
|
26 |
+
value: 71.35820895522387
|
27 |
+
- type: ap
|
28 |
+
value: 33.99931933598115
|
29 |
+
- type: f1
|
30 |
+
value: 65.3853685535555
|
31 |
+
- task:
|
32 |
+
type: Classification
|
33 |
+
dataset:
|
34 |
+
type: mteb/amazon_polarity
|
35 |
+
name: MTEB AmazonPolarityClassification
|
36 |
+
config: default
|
37 |
+
split: test
|
38 |
+
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41 |
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value: 82.90140000000001
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42 |
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43 |
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value: 78.01434597815617
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45 |
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value: 82.83357802722676
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46 |
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|
47 |
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type: Classification
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48 |
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|
49 |
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type: mteb/amazon_reviews_multi
|
50 |
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name: MTEB AmazonReviewsClassification (en)
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51 |
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config: en
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53 |
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revision: 1399c76144fd37290681b995c656ef9b2e06e26d
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|
55 |
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56 |
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value: 40.88999999999999
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57 |
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58 |
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- task:
|
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61 |
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|
62 |
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type: arguana
|
63 |
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name: MTEB ArguAna
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64 |
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config: default
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65 |
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split: test
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66 |
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revision: None
|
67 |
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metrics:
|
68 |
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|
69 |
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value: 23.257
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70 |
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|
71 |
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72 |
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73 |
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78 |
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value: 0.1
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- task:
|
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type: Clustering
|
130 |
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dataset:
|
131 |
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type: mteb/arxiv-clustering-p2p
|
132 |
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name: MTEB ArxivClusteringP2P
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config: default
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split: test
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135 |
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revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
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metrics:
|
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- type: v_measure
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138 |
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value: 44.02420878391967
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139 |
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- task:
|
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type: Clustering
|
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dataset:
|
142 |
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type: mteb/arxiv-clustering-s2s
|
143 |
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name: MTEB ArxivClusteringS2S
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config: default
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145 |
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split: test
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revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
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metrics:
|
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149 |
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value: 35.16136856000258
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150 |
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- task:
|
151 |
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type: Reranking
|
152 |
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dataset:
|
153 |
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type: mteb/askubuntudupquestions-reranking
|
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name: MTEB AskUbuntuDupQuestions
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155 |
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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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160 |
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value: 59.61809790513646
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162 |
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|
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type: STS
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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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170 |
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revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
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metrics:
|
172 |
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173 |
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value: 82.0167350090749
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- type: cos_sim_spearman
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- type: euclidean_pearson
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- type: euclidean_spearman
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- type: manhattan_pearson
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value: 81.35596555056757
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value: 80.12592210903303
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dataset:
|
187 |
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type: mteb/banking77
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name: MTEB Banking77Classification
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config: default
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split: test
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revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
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metrics:
|
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- type: accuracy
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194 |
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value: 78.25
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195 |
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196 |
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value: 77.34950913540605
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|
198 |
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dataset:
|
200 |
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type: mteb/biorxiv-clustering-p2p
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name: MTEB BiorxivClusteringP2P
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config: default
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split: test
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revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
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metrics:
|
206 |
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- type: v_measure
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207 |
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value: 35.57238596005698
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208 |
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- task:
|
209 |
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type: Clustering
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210 |
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dataset:
|
211 |
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type: mteb/biorxiv-clustering-s2s
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name: MTEB BiorxivClusteringS2S
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config: default
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214 |
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split: test
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revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
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metrics:
|
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218 |
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value: 29.066444306196683
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219 |
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- task:
|
220 |
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221 |
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dataset:
|
222 |
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type: BeIR/cqadupstack
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223 |
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name: MTEB CQADupstackAndroidRetrieval
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224 |
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config: default
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225 |
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split: test
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226 |
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revision: None
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227 |
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metrics:
|
228 |
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229 |
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value: 31.891000000000002
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230 |
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value: 41.113
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255 |
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value: 43.877
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262 |
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value: 46.027
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264 |
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265 |
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value: 39.342
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266 |
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267 |
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value: 9.285
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268 |
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value: 1.488
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value: 0.194
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value: 20.696
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274 |
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275 |
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value: 14.878
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276 |
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value: 31.891000000000002
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value: 81.025
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value: 94.883
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value: 45.694
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286 |
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value: 51.684
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288 |
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- task:
|
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dataset:
|
291 |
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type: BeIR/cqadupstack
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292 |
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name: MTEB CQADupstackEnglishRetrieval
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config: default
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294 |
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split: test
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295 |
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revision: None
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296 |
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metrics:
|
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298 |
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value: 28.778
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299 |
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300 |
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value: 37.632
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301 |
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306 |
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307 |
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311 |
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314 |
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319 |
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321 |
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323 |
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324 |
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325 |
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326 |
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328 |
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331 |
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value: 35.35
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335 |
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value: 7.828
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342 |
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value: 18.96
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value: 28.778
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value: 50.775000000000006
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353 |
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value: 40.757
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355 |
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- type: recall_at_5
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356 |
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value: 44.86
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357 |
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- task:
|
358 |
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type: Retrieval
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359 |
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dataset:
|
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type: BeIR/cqadupstack
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361 |
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name: MTEB CQADupstackGamingRetrieval
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362 |
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config: default
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split: test
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364 |
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revision: None
|
365 |
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metrics:
|
366 |
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- type: map_at_1
|
367 |
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value: 37.584
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368 |
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- task:
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|
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type: BeIR/cqadupstack
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430 |
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name: MTEB CQADupstackGisRetrieval
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revision: None
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metrics:
|
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value: 24.7
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value: 44.232
|
467 |
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- type: ndcg_at_3
|
468 |
+
value: 33.076
|
469 |
+
- type: ndcg_at_5
|
470 |
+
value: 34.966
|
471 |
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- type: precision_at_1
|
472 |
+
value: 26.328000000000003
|
473 |
+
- type: precision_at_10
|
474 |
+
value: 5.627
|
475 |
+
- type: precision_at_100
|
476 |
+
value: 0.8410000000000001
|
477 |
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- type: precision_at_1000
|
478 |
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value: 0.106
|
479 |
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- type: precision_at_3
|
480 |
+
value: 14.011000000000001
|
481 |
+
- type: precision_at_5
|
482 |
+
value: 9.582
|
483 |
+
- type: recall_at_1
|
484 |
+
value: 24.7
|
485 |
+
- type: recall_at_10
|
486 |
+
value: 49.324
|
487 |
+
- type: recall_at_100
|
488 |
+
value: 71.018
|
489 |
+
- type: recall_at_1000
|
490 |
+
value: 87.905
|
491 |
+
- type: recall_at_3
|
492 |
+
value: 37.7
|
493 |
+
- type: recall_at_5
|
494 |
+
value: 42.281
|
495 |
+
- task:
|
496 |
+
type: Retrieval
|
497 |
+
dataset:
|
498 |
+
type: BeIR/cqadupstack
|
499 |
+
name: MTEB CQADupstackMathematicaRetrieval
|
500 |
+
config: default
|
501 |
+
split: test
|
502 |
+
revision: None
|
503 |
+
metrics:
|
504 |
+
- type: map_at_1
|
505 |
+
value: 14.350999999999999
|
506 |
+
- type: map_at_10
|
507 |
+
value: 21.745
|
508 |
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- type: map_at_100
|
509 |
+
value: 22.731
|
510 |
+
- type: map_at_1000
|
511 |
+
value: 22.852
|
512 |
+
- type: map_at_3
|
513 |
+
value: 19.245
|
514 |
+
- type: map_at_5
|
515 |
+
value: 20.788
|
516 |
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- type: mrr_at_1
|
517 |
+
value: 18.159
|
518 |
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- type: mrr_at_10
|
519 |
+
value: 25.833000000000002
|
520 |
+
- type: mrr_at_100
|
521 |
+
value: 26.728
|
522 |
+
- type: mrr_at_1000
|
523 |
+
value: 26.802
|
524 |
+
- type: mrr_at_3
|
525 |
+
value: 23.383000000000003
|
526 |
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- type: mrr_at_5
|
527 |
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value: 24.887999999999998
|
528 |
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- type: ndcg_at_1
|
529 |
+
value: 18.159
|
530 |
+
- type: ndcg_at_10
|
531 |
+
value: 26.518000000000004
|
532 |
+
- type: ndcg_at_100
|
533 |
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value: 31.473000000000003
|
534 |
+
- type: ndcg_at_1000
|
535 |
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value: 34.576
|
536 |
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- type: ndcg_at_3
|
537 |
+
value: 21.907
|
538 |
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- type: ndcg_at_5
|
539 |
+
value: 24.39
|
540 |
+
- type: precision_at_1
|
541 |
+
value: 18.159
|
542 |
+
- type: precision_at_10
|
543 |
+
value: 4.938
|
544 |
+
- type: precision_at_100
|
545 |
+
value: 0.853
|
546 |
+
- type: precision_at_1000
|
547 |
+
value: 0.125
|
548 |
+
- type: precision_at_3
|
549 |
+
value: 10.655000000000001
|
550 |
+
- type: precision_at_5
|
551 |
+
value: 7.985
|
552 |
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- type: recall_at_1
|
553 |
+
value: 14.350999999999999
|
554 |
+
- type: recall_at_10
|
555 |
+
value: 37.284
|
556 |
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- type: recall_at_100
|
557 |
+
value: 59.11300000000001
|
558 |
+
- type: recall_at_1000
|
559 |
+
value: 81.634
|
560 |
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- type: recall_at_3
|
561 |
+
value: 24.753
|
562 |
+
- type: recall_at_5
|
563 |
+
value: 30.979
|
564 |
+
- task:
|
565 |
+
type: Retrieval
|
566 |
+
dataset:
|
567 |
+
type: BeIR/cqadupstack
|
568 |
+
name: MTEB CQADupstackPhysicsRetrieval
|
569 |
+
config: default
|
570 |
+
split: test
|
571 |
+
revision: None
|
572 |
+
metrics:
|
573 |
+
- type: map_at_1
|
574 |
+
value: 26.978
|
575 |
+
- type: map_at_10
|
576 |
+
value: 36.276
|
577 |
+
- type: map_at_100
|
578 |
+
value: 37.547000000000004
|
579 |
+
- type: map_at_1000
|
580 |
+
value: 37.678
|
581 |
+
- type: map_at_3
|
582 |
+
value: 33.674
|
583 |
+
- type: map_at_5
|
584 |
+
value: 35.119
|
585 |
+
- type: mrr_at_1
|
586 |
+
value: 32.916000000000004
|
587 |
+
- type: mrr_at_10
|
588 |
+
value: 41.798
|
589 |
+
- type: mrr_at_100
|
590 |
+
value: 42.72
|
591 |
+
- type: mrr_at_1000
|
592 |
+
value: 42.778
|
593 |
+
- type: mrr_at_3
|
594 |
+
value: 39.493
|
595 |
+
- type: mrr_at_5
|
596 |
+
value: 40.927
|
597 |
+
- type: ndcg_at_1
|
598 |
+
value: 32.916000000000004
|
599 |
+
- type: ndcg_at_10
|
600 |
+
value: 41.81
|
601 |
+
- type: ndcg_at_100
|
602 |
+
value: 47.284
|
603 |
+
- type: ndcg_at_1000
|
604 |
+
value: 49.702
|
605 |
+
- type: ndcg_at_3
|
606 |
+
value: 37.486999999999995
|
607 |
+
- type: ndcg_at_5
|
608 |
+
value: 39.597
|
609 |
+
- type: precision_at_1
|
610 |
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value: 32.916000000000004
|
611 |
+
- type: precision_at_10
|
612 |
+
value: 7.411
|
613 |
+
- type: precision_at_100
|
614 |
+
value: 1.189
|
615 |
+
- type: precision_at_1000
|
616 |
+
value: 0.158
|
617 |
+
- type: precision_at_3
|
618 |
+
value: 17.581
|
619 |
+
- type: precision_at_5
|
620 |
+
value: 12.397
|
621 |
+
- type: recall_at_1
|
622 |
+
value: 26.978
|
623 |
+
- type: recall_at_10
|
624 |
+
value: 52.869
|
625 |
+
- type: recall_at_100
|
626 |
+
value: 75.78399999999999
|
627 |
+
- type: recall_at_1000
|
628 |
+
value: 91.545
|
629 |
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- type: recall_at_3
|
630 |
+
value: 40.717
|
631 |
+
- type: recall_at_5
|
632 |
+
value: 46.168
|
633 |
+
- task:
|
634 |
+
type: Retrieval
|
635 |
+
dataset:
|
636 |
+
type: BeIR/cqadupstack
|
637 |
+
name: MTEB CQADupstackProgrammersRetrieval
|
638 |
+
config: default
|
639 |
+
split: test
|
640 |
+
revision: None
|
641 |
+
metrics:
|
642 |
+
- type: map_at_1
|
643 |
+
value: 24.641
|
644 |
+
- type: map_at_10
|
645 |
+
value: 32.916000000000004
|
646 |
+
- type: map_at_100
|
647 |
+
value: 34.165
|
648 |
+
- type: map_at_1000
|
649 |
+
value: 34.286
|
650 |
+
- type: map_at_3
|
651 |
+
value: 30.335
|
652 |
+
- type: map_at_5
|
653 |
+
value: 31.569000000000003
|
654 |
+
- type: mrr_at_1
|
655 |
+
value: 30.593999999999998
|
656 |
+
- type: mrr_at_10
|
657 |
+
value: 38.448
|
658 |
+
- type: mrr_at_100
|
659 |
+
value: 39.299
|
660 |
+
- type: mrr_at_1000
|
661 |
+
value: 39.362
|
662 |
+
- type: mrr_at_3
|
663 |
+
value: 36.244
|
664 |
+
- type: mrr_at_5
|
665 |
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value: 37.232
|
666 |
+
- type: ndcg_at_1
|
667 |
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value: 30.593999999999998
|
668 |
+
- type: ndcg_at_10
|
669 |
+
value: 38.2
|
670 |
+
- type: ndcg_at_100
|
671 |
+
value: 43.742
|
672 |
+
- type: ndcg_at_1000
|
673 |
+
value: 46.217000000000006
|
674 |
+
- type: ndcg_at_3
|
675 |
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value: 33.925
|
676 |
+
- type: ndcg_at_5
|
677 |
+
value: 35.394
|
678 |
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- type: precision_at_1
|
679 |
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value: 30.593999999999998
|
680 |
+
- type: precision_at_10
|
681 |
+
value: 6.895
|
682 |
+
- type: precision_at_100
|
683 |
+
value: 1.1320000000000001
|
684 |
+
- type: precision_at_1000
|
685 |
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value: 0.153
|
686 |
+
- type: precision_at_3
|
687 |
+
value: 16.096
|
688 |
+
- type: precision_at_5
|
689 |
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value: 11.05
|
690 |
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- type: recall_at_1
|
691 |
+
value: 24.641
|
692 |
+
- type: recall_at_10
|
693 |
+
value: 48.588
|
694 |
+
- type: recall_at_100
|
695 |
+
value: 72.841
|
696 |
+
- type: recall_at_1000
|
697 |
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value: 89.535
|
698 |
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- type: recall_at_3
|
699 |
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value: 36.087
|
700 |
+
- type: recall_at_5
|
701 |
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value: 40.346
|
702 |
+
- task:
|
703 |
+
type: Retrieval
|
704 |
+
dataset:
|
705 |
+
type: BeIR/cqadupstack
|
706 |
+
name: MTEB CQADupstackRetrieval
|
707 |
+
config: default
|
708 |
+
split: test
|
709 |
+
revision: None
|
710 |
+
metrics:
|
711 |
+
- type: map_at_1
|
712 |
+
value: 24.79425
|
713 |
+
- type: map_at_10
|
714 |
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value: 33.12033333333333
|
715 |
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- type: map_at_100
|
716 |
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value: 34.221333333333334
|
717 |
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- type: map_at_1000
|
718 |
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value: 34.3435
|
719 |
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- type: map_at_3
|
720 |
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value: 30.636583333333338
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721 |
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|
722 |
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value: 31.974083333333326
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723 |
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|
724 |
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value: 29.242416666666664
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725 |
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|
726 |
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value: 37.11675
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727 |
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|
728 |
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value: 37.93783333333334
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729 |
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|
730 |
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value: 38.003083333333336
|
731 |
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|
732 |
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value: 34.904666666666664
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733 |
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|
734 |
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value: 36.12916666666667
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735 |
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736 |
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value: 29.242416666666664
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737 |
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|
738 |
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value: 38.03416666666667
|
739 |
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|
740 |
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value: 42.86674999999999
|
741 |
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- type: ndcg_at_1000
|
742 |
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value: 45.34550000000001
|
743 |
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- type: ndcg_at_3
|
744 |
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value: 33.76466666666666
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745 |
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- type: ndcg_at_5
|
746 |
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value: 35.668666666666674
|
747 |
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- type: precision_at_1
|
748 |
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value: 29.242416666666664
|
749 |
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- type: precision_at_10
|
750 |
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value: 6.589833333333334
|
751 |
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- type: precision_at_100
|
752 |
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value: 1.0693333333333332
|
753 |
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|
754 |
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value: 0.14641666666666667
|
755 |
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|
756 |
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value: 15.430749999999998
|
757 |
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- type: precision_at_5
|
758 |
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value: 10.833833333333333
|
759 |
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- type: recall_at_1
|
760 |
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value: 24.79425
|
761 |
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- type: recall_at_10
|
762 |
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value: 48.582916666666655
|
763 |
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- type: recall_at_100
|
764 |
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value: 69.88499999999999
|
765 |
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- type: recall_at_1000
|
766 |
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value: 87.211
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767 |
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- type: recall_at_3
|
768 |
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value: 36.625499999999995
|
769 |
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- type: recall_at_5
|
770 |
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value: 41.553999999999995
|
771 |
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- task:
|
772 |
+
type: Retrieval
|
773 |
+
dataset:
|
774 |
+
type: BeIR/cqadupstack
|
775 |
+
name: MTEB CQADupstackStatsRetrieval
|
776 |
+
config: default
|
777 |
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split: test
|
778 |
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revision: None
|
779 |
+
metrics:
|
780 |
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- type: map_at_1
|
781 |
+
value: 22.767
|
782 |
+
- type: map_at_10
|
783 |
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value: 28.450999999999997
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784 |
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|
785 |
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value: 29.332
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786 |
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|
787 |
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value: 29.426000000000002
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788 |
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|
789 |
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value: 26.379
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790 |
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|
791 |
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792 |
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793 |
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value: 25.46
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794 |
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|
795 |
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value: 30.974
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796 |
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|
797 |
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value: 31.784000000000002
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798 |
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|
799 |
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800 |
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|
801 |
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value: 28.962
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802 |
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|
803 |
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value: 30.066
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804 |
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|
805 |
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value: 25.46
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806 |
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|
807 |
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value: 32.041
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808 |
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|
809 |
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value: 36.522
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810 |
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811 |
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value: 39.101
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812 |
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|
813 |
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value: 28.152
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814 |
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|
815 |
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value: 30.03
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816 |
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|
817 |
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value: 25.46
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818 |
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|
819 |
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value: 4.893
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820 |
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|
821 |
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value: 0.77
|
822 |
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|
823 |
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value: 0.107
|
824 |
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|
825 |
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value: 11.605
|
826 |
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- type: precision_at_5
|
827 |
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value: 8.19
|
828 |
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|
829 |
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value: 22.767
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830 |
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|
831 |
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value: 40.71
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832 |
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|
833 |
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value: 61.334999999999994
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834 |
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- type: recall_at_1000
|
835 |
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value: 80.567
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836 |
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- type: recall_at_3
|
837 |
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value: 30.198000000000004
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838 |
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- type: recall_at_5
|
839 |
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value: 34.803
|
840 |
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- task:
|
841 |
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type: Retrieval
|
842 |
+
dataset:
|
843 |
+
type: BeIR/cqadupstack
|
844 |
+
name: MTEB CQADupstackTexRetrieval
|
845 |
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config: default
|
846 |
+
split: test
|
847 |
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revision: None
|
848 |
+
metrics:
|
849 |
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- type: map_at_1
|
850 |
+
value: 16.722
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851 |
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- type: map_at_10
|
852 |
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value: 22.794
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853 |
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|
854 |
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value: 23.7
|
855 |
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- type: map_at_1000
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856 |
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value: 23.822
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857 |
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|
858 |
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value: 20.781
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859 |
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|
860 |
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value: 22.024
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861 |
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|
862 |
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value: 20.061999999999998
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863 |
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|
864 |
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value: 26.346999999999998
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865 |
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866 |
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value: 27.153
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867 |
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868 |
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value: 27.233
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869 |
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870 |
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value: 24.375
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871 |
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|
872 |
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value: 25.593
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873 |
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|
874 |
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value: 20.061999999999998
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875 |
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|
876 |
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877 |
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|
878 |
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value: 31.319999999999997
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879 |
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|
880 |
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value: 34.346
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881 |
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- type: ndcg_at_3
|
882 |
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value: 23.219
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883 |
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- type: ndcg_at_5
|
884 |
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value: 25.107000000000003
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885 |
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|
886 |
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value: 20.061999999999998
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887 |
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|
888 |
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value: 4.78
|
889 |
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- type: precision_at_100
|
890 |
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value: 0.83
|
891 |
+
- type: precision_at_1000
|
892 |
+
value: 0.125
|
893 |
+
- type: precision_at_3
|
894 |
+
value: 10.874
|
895 |
+
- type: precision_at_5
|
896 |
+
value: 7.956
|
897 |
+
- type: recall_at_1
|
898 |
+
value: 16.722
|
899 |
+
- type: recall_at_10
|
900 |
+
value: 35.204
|
901 |
+
- type: recall_at_100
|
902 |
+
value: 55.797
|
903 |
+
- type: recall_at_1000
|
904 |
+
value: 77.689
|
905 |
+
- type: recall_at_3
|
906 |
+
value: 25.245
|
907 |
+
- type: recall_at_5
|
908 |
+
value: 30.115
|
909 |
+
- task:
|
910 |
+
type: Retrieval
|
911 |
+
dataset:
|
912 |
+
type: BeIR/cqadupstack
|
913 |
+
name: MTEB CQADupstackUnixRetrieval
|
914 |
+
config: default
|
915 |
+
split: test
|
916 |
+
revision: None
|
917 |
+
metrics:
|
918 |
+
- type: map_at_1
|
919 |
+
value: 24.842
|
920 |
+
- type: map_at_10
|
921 |
+
value: 32.917
|
922 |
+
- type: map_at_100
|
923 |
+
value: 33.961000000000006
|
924 |
+
- type: map_at_1000
|
925 |
+
value: 34.069
|
926 |
+
- type: map_at_3
|
927 |
+
value: 30.595
|
928 |
+
- type: map_at_5
|
929 |
+
value: 31.837
|
930 |
+
- type: mrr_at_1
|
931 |
+
value: 29.011
|
932 |
+
- type: mrr_at_10
|
933 |
+
value: 36.977
|
934 |
+
- type: mrr_at_100
|
935 |
+
value: 37.814
|
936 |
+
- type: mrr_at_1000
|
937 |
+
value: 37.885999999999996
|
938 |
+
- type: mrr_at_3
|
939 |
+
value: 34.966
|
940 |
+
- type: mrr_at_5
|
941 |
+
value: 36.043
|
942 |
+
- type: ndcg_at_1
|
943 |
+
value: 29.011
|
944 |
+
- type: ndcg_at_10
|
945 |
+
value: 37.735
|
946 |
+
- type: ndcg_at_100
|
947 |
+
value: 42.683
|
948 |
+
- type: ndcg_at_1000
|
949 |
+
value: 45.198
|
950 |
+
- type: ndcg_at_3
|
951 |
+
value: 33.650000000000006
|
952 |
+
- type: ndcg_at_5
|
953 |
+
value: 35.386
|
954 |
+
- type: precision_at_1
|
955 |
+
value: 29.011
|
956 |
+
- type: precision_at_10
|
957 |
+
value: 6.259
|
958 |
+
- type: precision_at_100
|
959 |
+
value: 0.984
|
960 |
+
- type: precision_at_1000
|
961 |
+
value: 0.13
|
962 |
+
- type: precision_at_3
|
963 |
+
value: 15.329999999999998
|
964 |
+
- type: precision_at_5
|
965 |
+
value: 10.541
|
966 |
+
- type: recall_at_1
|
967 |
+
value: 24.842
|
968 |
+
- type: recall_at_10
|
969 |
+
value: 48.304
|
970 |
+
- type: recall_at_100
|
971 |
+
value: 70.04899999999999
|
972 |
+
- type: recall_at_1000
|
973 |
+
value: 87.82600000000001
|
974 |
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- type: recall_at_3
|
975 |
+
value: 36.922
|
976 |
+
- type: recall_at_5
|
977 |
+
value: 41.449999999999996
|
978 |
+
- task:
|
979 |
+
type: Retrieval
|
980 |
+
dataset:
|
981 |
+
type: BeIR/cqadupstack
|
982 |
+
name: MTEB CQADupstackWebmastersRetrieval
|
983 |
+
config: default
|
984 |
+
split: test
|
985 |
+
revision: None
|
986 |
+
metrics:
|
987 |
+
- type: map_at_1
|
988 |
+
value: 24.252000000000002
|
989 |
+
- type: map_at_10
|
990 |
+
value: 32.293
|
991 |
+
- type: map_at_100
|
992 |
+
value: 33.816
|
993 |
+
- type: map_at_1000
|
994 |
+
value: 34.053
|
995 |
+
- type: map_at_3
|
996 |
+
value: 29.781999999999996
|
997 |
+
- type: map_at_5
|
998 |
+
value: 31.008000000000003
|
999 |
+
- type: mrr_at_1
|
1000 |
+
value: 29.051
|
1001 |
+
- type: mrr_at_10
|
1002 |
+
value: 36.722
|
1003 |
+
- type: mrr_at_100
|
1004 |
+
value: 37.663000000000004
|
1005 |
+
- type: mrr_at_1000
|
1006 |
+
value: 37.734
|
1007 |
+
- type: mrr_at_3
|
1008 |
+
value: 34.354
|
1009 |
+
- type: mrr_at_5
|
1010 |
+
value: 35.609
|
1011 |
+
- type: ndcg_at_1
|
1012 |
+
value: 29.051
|
1013 |
+
- type: ndcg_at_10
|
1014 |
+
value: 37.775999999999996
|
1015 |
+
- type: ndcg_at_100
|
1016 |
+
value: 43.221
|
1017 |
+
- type: ndcg_at_1000
|
1018 |
+
value: 46.116
|
1019 |
+
- type: ndcg_at_3
|
1020 |
+
value: 33.403
|
1021 |
+
- type: ndcg_at_5
|
1022 |
+
value: 35.118
|
1023 |
+
- type: precision_at_1
|
1024 |
+
value: 29.051
|
1025 |
+
- type: precision_at_10
|
1026 |
+
value: 7.332
|
1027 |
+
- type: precision_at_100
|
1028 |
+
value: 1.49
|
1029 |
+
- type: precision_at_1000
|
1030 |
+
value: 0.23600000000000002
|
1031 |
+
- type: precision_at_3
|
1032 |
+
value: 15.415000000000001
|
1033 |
+
- type: precision_at_5
|
1034 |
+
value: 11.107
|
1035 |
+
- type: recall_at_1
|
1036 |
+
value: 24.252000000000002
|
1037 |
+
- type: recall_at_10
|
1038 |
+
value: 47.861
|
1039 |
+
- type: recall_at_100
|
1040 |
+
value: 72.21600000000001
|
1041 |
+
- type: recall_at_1000
|
1042 |
+
value: 90.886
|
1043 |
+
- type: recall_at_3
|
1044 |
+
value: 35.533
|
1045 |
+
- type: recall_at_5
|
1046 |
+
value: 39.959
|
1047 |
+
- task:
|
1048 |
+
type: Retrieval
|
1049 |
+
dataset:
|
1050 |
+
type: BeIR/cqadupstack
|
1051 |
+
name: MTEB CQADupstackWordpressRetrieval
|
1052 |
+
config: default
|
1053 |
+
split: test
|
1054 |
+
revision: None
|
1055 |
+
metrics:
|
1056 |
+
- type: map_at_1
|
1057 |
+
value: 20.025000000000002
|
1058 |
+
- type: map_at_10
|
1059 |
+
value: 27.154
|
1060 |
+
- type: map_at_100
|
1061 |
+
value: 28.118
|
1062 |
+
- type: map_at_1000
|
1063 |
+
value: 28.237000000000002
|
1064 |
+
- type: map_at_3
|
1065 |
+
value: 25.017
|
1066 |
+
- type: map_at_5
|
1067 |
+
value: 25.832
|
1068 |
+
- type: mrr_at_1
|
1069 |
+
value: 21.627
|
1070 |
+
- type: mrr_at_10
|
1071 |
+
value: 28.884999999999998
|
1072 |
+
- type: mrr_at_100
|
1073 |
+
value: 29.741
|
1074 |
+
- type: mrr_at_1000
|
1075 |
+
value: 29.831999999999997
|
1076 |
+
- type: mrr_at_3
|
1077 |
+
value: 26.741
|
1078 |
+
- type: mrr_at_5
|
1079 |
+
value: 27.628000000000004
|
1080 |
+
- type: ndcg_at_1
|
1081 |
+
value: 21.627
|
1082 |
+
- type: ndcg_at_10
|
1083 |
+
value: 31.436999999999998
|
1084 |
+
- type: ndcg_at_100
|
1085 |
+
value: 36.181000000000004
|
1086 |
+
- type: ndcg_at_1000
|
1087 |
+
value: 38.986
|
1088 |
+
- type: ndcg_at_3
|
1089 |
+
value: 27.025
|
1090 |
+
- type: ndcg_at_5
|
1091 |
+
value: 28.436
|
1092 |
+
- type: precision_at_1
|
1093 |
+
value: 21.627
|
1094 |
+
- type: precision_at_10
|
1095 |
+
value: 5.009
|
1096 |
+
- type: precision_at_100
|
1097 |
+
value: 0.7929999999999999
|
1098 |
+
- type: precision_at_1000
|
1099 |
+
value: 0.11299999999999999
|
1100 |
+
- type: precision_at_3
|
1101 |
+
value: 11.522
|
1102 |
+
- type: precision_at_5
|
1103 |
+
value: 7.763000000000001
|
1104 |
+
- type: recall_at_1
|
1105 |
+
value: 20.025000000000002
|
1106 |
+
- type: recall_at_10
|
1107 |
+
value: 42.954
|
1108 |
+
- type: recall_at_100
|
1109 |
+
value: 64.67500000000001
|
1110 |
+
- type: recall_at_1000
|
1111 |
+
value: 85.301
|
1112 |
+
- type: recall_at_3
|
1113 |
+
value: 30.892999999999997
|
1114 |
+
- type: recall_at_5
|
1115 |
+
value: 34.288000000000004
|
1116 |
+
- task:
|
1117 |
+
type: Retrieval
|
1118 |
+
dataset:
|
1119 |
+
type: climate-fever
|
1120 |
+
name: MTEB ClimateFEVER
|
1121 |
+
config: default
|
1122 |
+
split: test
|
1123 |
+
revision: None
|
1124 |
+
metrics:
|
1125 |
+
- type: map_at_1
|
1126 |
+
value: 10.079
|
1127 |
+
- type: map_at_10
|
1128 |
+
value: 16.930999999999997
|
1129 |
+
- type: map_at_100
|
1130 |
+
value: 18.398999999999997
|
1131 |
+
- type: map_at_1000
|
1132 |
+
value: 18.561
|
1133 |
+
- type: map_at_3
|
1134 |
+
value: 14.294
|
1135 |
+
- type: map_at_5
|
1136 |
+
value: 15.579
|
1137 |
+
- type: mrr_at_1
|
1138 |
+
value: 22.606
|
1139 |
+
- type: mrr_at_10
|
1140 |
+
value: 32.513
|
1141 |
+
- type: mrr_at_100
|
1142 |
+
value: 33.463
|
1143 |
+
- type: mrr_at_1000
|
1144 |
+
value: 33.513999999999996
|
1145 |
+
- type: mrr_at_3
|
1146 |
+
value: 29.479
|
1147 |
+
- type: mrr_at_5
|
1148 |
+
value: 31.3
|
1149 |
+
- type: ndcg_at_1
|
1150 |
+
value: 22.606
|
1151 |
+
- type: ndcg_at_10
|
1152 |
+
value: 24.053
|
1153 |
+
- type: ndcg_at_100
|
1154 |
+
value: 30.258000000000003
|
1155 |
+
- type: ndcg_at_1000
|
1156 |
+
value: 33.516
|
1157 |
+
- type: ndcg_at_3
|
1158 |
+
value: 19.721
|
1159 |
+
- type: ndcg_at_5
|
1160 |
+
value: 21.144
|
1161 |
+
- type: precision_at_1
|
1162 |
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value: 22.606
|
1163 |
+
- type: precision_at_10
|
1164 |
+
value: 7.55
|
1165 |
+
- type: precision_at_100
|
1166 |
+
value: 1.399
|
1167 |
+
- type: precision_at_1000
|
1168 |
+
value: 0.2
|
1169 |
+
- type: precision_at_3
|
1170 |
+
value: 14.701
|
1171 |
+
- type: precision_at_5
|
1172 |
+
value: 11.192
|
1173 |
+
- type: recall_at_1
|
1174 |
+
value: 10.079
|
1175 |
+
- type: recall_at_10
|
1176 |
+
value: 28.970000000000002
|
1177 |
+
- type: recall_at_100
|
1178 |
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value: 50.805
|
1179 |
+
- type: recall_at_1000
|
1180 |
+
value: 69.378
|
1181 |
+
- type: recall_at_3
|
1182 |
+
value: 18.199
|
1183 |
+
- type: recall_at_5
|
1184 |
+
value: 22.442
|
1185 |
+
- task:
|
1186 |
+
type: Retrieval
|
1187 |
+
dataset:
|
1188 |
+
type: dbpedia-entity
|
1189 |
+
name: MTEB DBPedia
|
1190 |
+
config: default
|
1191 |
+
split: test
|
1192 |
+
revision: None
|
1193 |
+
metrics:
|
1194 |
+
- type: map_at_1
|
1195 |
+
value: 7.794
|
1196 |
+
- type: map_at_10
|
1197 |
+
value: 15.165999999999999
|
1198 |
+
- type: map_at_100
|
1199 |
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value: 20.508000000000003
|
1200 |
+
- type: map_at_1000
|
1201 |
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value: 21.809
|
1202 |
+
- type: map_at_3
|
1203 |
+
value: 11.568000000000001
|
1204 |
+
- type: map_at_5
|
1205 |
+
value: 13.059000000000001
|
1206 |
+
- type: mrr_at_1
|
1207 |
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value: 56.49999999999999
|
1208 |
+
- type: mrr_at_10
|
1209 |
+
value: 65.90899999999999
|
1210 |
+
- type: mrr_at_100
|
1211 |
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value: 66.352
|
1212 |
+
- type: mrr_at_1000
|
1213 |
+
value: 66.369
|
1214 |
+
- type: mrr_at_3
|
1215 |
+
value: 64.0
|
1216 |
+
- type: mrr_at_5
|
1217 |
+
value: 65.10000000000001
|
1218 |
+
- type: ndcg_at_1
|
1219 |
+
value: 44.25
|
1220 |
+
- type: ndcg_at_10
|
1221 |
+
value: 32.649
|
1222 |
+
- type: ndcg_at_100
|
1223 |
+
value: 36.668
|
1224 |
+
- type: ndcg_at_1000
|
1225 |
+
value: 43.918
|
1226 |
+
- type: ndcg_at_3
|
1227 |
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value: 37.096000000000004
|
1228 |
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- type: ndcg_at_5
|
1229 |
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value: 34.048
|
1230 |
+
- type: precision_at_1
|
1231 |
+
value: 56.49999999999999
|
1232 |
+
- type: precision_at_10
|
1233 |
+
value: 25.45
|
1234 |
+
- type: precision_at_100
|
1235 |
+
value: 8.055
|
1236 |
+
- type: precision_at_1000
|
1237 |
+
value: 1.7489999999999999
|
1238 |
+
- type: precision_at_3
|
1239 |
+
value: 41.0
|
1240 |
+
- type: precision_at_5
|
1241 |
+
value: 32.85
|
1242 |
+
- type: recall_at_1
|
1243 |
+
value: 7.794
|
1244 |
+
- type: recall_at_10
|
1245 |
+
value: 20.101
|
1246 |
+
- type: recall_at_100
|
1247 |
+
value: 42.448
|
1248 |
+
- type: recall_at_1000
|
1249 |
+
value: 65.88000000000001
|
1250 |
+
- type: recall_at_3
|
1251 |
+
value: 12.753
|
1252 |
+
- type: recall_at_5
|
1253 |
+
value: 15.307
|
1254 |
+
- task:
|
1255 |
+
type: Classification
|
1256 |
+
dataset:
|
1257 |
+
type: mteb/emotion
|
1258 |
+
name: MTEB EmotionClassification
|
1259 |
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config: default
|
1260 |
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split: test
|
1261 |
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revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
|
1262 |
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metrics:
|
1263 |
+
- type: accuracy
|
1264 |
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value: 44.01
|
1265 |
+
- type: f1
|
1266 |
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value: 38.659680951114964
|
1267 |
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- task:
|
1268 |
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type: Retrieval
|
1269 |
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dataset:
|
1270 |
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type: fever
|
1271 |
+
name: MTEB FEVER
|
1272 |
+
config: default
|
1273 |
+
split: test
|
1274 |
+
revision: None
|
1275 |
+
metrics:
|
1276 |
+
- type: map_at_1
|
1277 |
+
value: 49.713
|
1278 |
+
- type: map_at_10
|
1279 |
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value: 61.79
|
1280 |
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- type: map_at_100
|
1281 |
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value: 62.28
|
1282 |
+
- type: map_at_1000
|
1283 |
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value: 62.297000000000004
|
1284 |
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- type: map_at_3
|
1285 |
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value: 59.361
|
1286 |
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- type: map_at_5
|
1287 |
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value: 60.92100000000001
|
1288 |
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- type: mrr_at_1
|
1289 |
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value: 53.405
|
1290 |
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- type: mrr_at_10
|
1291 |
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value: 65.79899999999999
|
1292 |
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- type: mrr_at_100
|
1293 |
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value: 66.219
|
1294 |
+
- type: mrr_at_1000
|
1295 |
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value: 66.227
|
1296 |
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- type: mrr_at_3
|
1297 |
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value: 63.431000000000004
|
1298 |
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- type: mrr_at_5
|
1299 |
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value: 64.98
|
1300 |
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- type: ndcg_at_1
|
1301 |
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value: 53.405
|
1302 |
+
- type: ndcg_at_10
|
1303 |
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value: 68.01899999999999
|
1304 |
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- type: ndcg_at_100
|
1305 |
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value: 70.197
|
1306 |
+
- type: ndcg_at_1000
|
1307 |
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value: 70.571
|
1308 |
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|
1309 |
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value: 63.352
|
1310 |
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- type: ndcg_at_5
|
1311 |
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value: 66.018
|
1312 |
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|
1313 |
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value: 53.405
|
1314 |
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- type: precision_at_10
|
1315 |
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value: 9.119
|
1316 |
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- type: precision_at_100
|
1317 |
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value: 1.03
|
1318 |
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- type: precision_at_1000
|
1319 |
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value: 0.107
|
1320 |
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- type: precision_at_3
|
1321 |
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value: 25.602999999999998
|
1322 |
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- type: precision_at_5
|
1323 |
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value: 16.835
|
1324 |
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- type: recall_at_1
|
1325 |
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value: 49.713
|
1326 |
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- type: recall_at_10
|
1327 |
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value: 83.306
|
1328 |
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- type: recall_at_100
|
1329 |
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value: 92.92
|
1330 |
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- type: recall_at_1000
|
1331 |
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value: 95.577
|
1332 |
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- type: recall_at_3
|
1333 |
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value: 70.798
|
1334 |
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- type: recall_at_5
|
1335 |
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value: 77.254
|
1336 |
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- task:
|
1337 |
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type: Retrieval
|
1338 |
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dataset:
|
1339 |
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type: fiqa
|
1340 |
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name: MTEB FiQA2018
|
1341 |
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config: default
|
1342 |
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split: test
|
1343 |
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revision: None
|
1344 |
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metrics:
|
1345 |
+
- type: map_at_1
|
1346 |
+
value: 15.310000000000002
|
1347 |
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- type: map_at_10
|
1348 |
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value: 26.204
|
1349 |
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|
1350 |
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value: 27.932000000000002
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1351 |
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|
1352 |
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value: 28.121000000000002
|
1353 |
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|
1354 |
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value: 22.481
|
1355 |
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|
1356 |
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value: 24.678
|
1357 |
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- type: mrr_at_1
|
1358 |
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value: 29.784
|
1359 |
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- type: mrr_at_10
|
1360 |
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value: 39.582
|
1361 |
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- type: mrr_at_100
|
1362 |
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value: 40.52
|
1363 |
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- type: mrr_at_1000
|
1364 |
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value: 40.568
|
1365 |
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- type: mrr_at_3
|
1366 |
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value: 37.114000000000004
|
1367 |
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|
1368 |
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value: 38.596000000000004
|
1369 |
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- type: ndcg_at_1
|
1370 |
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value: 29.784
|
1371 |
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|
1372 |
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value: 33.432
|
1373 |
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- type: ndcg_at_100
|
1374 |
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value: 40.281
|
1375 |
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- type: ndcg_at_1000
|
1376 |
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value: 43.653999999999996
|
1377 |
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|
1378 |
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value: 29.612
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1379 |
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|
1380 |
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value: 31.223
|
1381 |
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|
1382 |
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value: 29.784
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1383 |
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- type: precision_at_10
|
1384 |
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value: 9.645
|
1385 |
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- type: precision_at_100
|
1386 |
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value: 1.645
|
1387 |
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- type: precision_at_1000
|
1388 |
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value: 0.22499999999999998
|
1389 |
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- type: precision_at_3
|
1390 |
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value: 20.165
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1391 |
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- type: precision_at_5
|
1392 |
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value: 15.401000000000002
|
1393 |
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- type: recall_at_1
|
1394 |
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value: 15.310000000000002
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1395 |
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- type: recall_at_10
|
1396 |
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value: 40.499
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1397 |
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- type: recall_at_100
|
1398 |
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value: 66.643
|
1399 |
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- type: recall_at_1000
|
1400 |
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value: 87.059
|
1401 |
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- type: recall_at_3
|
1402 |
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value: 27.492
|
1403 |
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- type: recall_at_5
|
1404 |
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value: 33.748
|
1405 |
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- task:
|
1406 |
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type: Retrieval
|
1407 |
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dataset:
|
1408 |
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type: hotpotqa
|
1409 |
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name: MTEB HotpotQA
|
1410 |
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config: default
|
1411 |
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split: test
|
1412 |
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revision: None
|
1413 |
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metrics:
|
1414 |
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- type: map_at_1
|
1415 |
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value: 33.599000000000004
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1416 |
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- type: map_at_10
|
1417 |
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value: 47.347
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1418 |
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1419 |
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value: 48.191
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1420 |
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1421 |
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value: 48.263
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1422 |
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1423 |
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value: 44.698
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1424 |
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|
1425 |
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value: 46.278999999999996
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1426 |
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1427 |
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1428 |
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|
1429 |
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value: 74.054
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1430 |
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- type: mrr_at_100
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1431 |
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value: 74.376
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1432 |
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- type: mrr_at_1000
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1433 |
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value: 74.392
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1434 |
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1435 |
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value: 72.849
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1436 |
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|
1437 |
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value: 73.643
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1438 |
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- type: ndcg_at_1
|
1439 |
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value: 67.19800000000001
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1440 |
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- type: ndcg_at_10
|
1441 |
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value: 56.482
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1442 |
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- type: ndcg_at_100
|
1443 |
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value: 59.694
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1444 |
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- type: ndcg_at_1000
|
1445 |
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value: 61.204
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1446 |
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- type: ndcg_at_3
|
1447 |
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value: 52.43299999999999
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1448 |
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1449 |
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value: 54.608000000000004
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1450 |
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- type: precision_at_1
|
1451 |
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value: 67.19800000000001
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1452 |
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- type: precision_at_10
|
1453 |
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value: 11.613999999999999
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1454 |
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- type: precision_at_100
|
1455 |
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value: 1.415
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1456 |
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- type: precision_at_1000
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1457 |
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value: 0.16199999999999998
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1458 |
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- type: precision_at_3
|
1459 |
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value: 32.726
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1460 |
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- type: precision_at_5
|
1461 |
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value: 21.349999999999998
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1462 |
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- type: recall_at_1
|
1463 |
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value: 33.599000000000004
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1464 |
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- type: recall_at_10
|
1465 |
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value: 58.069
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1466 |
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- type: recall_at_100
|
1467 |
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value: 70.736
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1468 |
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- type: recall_at_1000
|
1469 |
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value: 80.804
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1470 |
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- type: recall_at_3
|
1471 |
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value: 49.088
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1472 |
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- type: recall_at_5
|
1473 |
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value: 53.376000000000005
|
1474 |
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- task:
|
1475 |
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type: Classification
|
1476 |
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dataset:
|
1477 |
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type: mteb/imdb
|
1478 |
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name: MTEB ImdbClassification
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1479 |
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config: default
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1480 |
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split: test
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1481 |
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revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
|
1482 |
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metrics:
|
1483 |
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- type: accuracy
|
1484 |
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value: 73.64359999999999
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1485 |
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- type: ap
|
1486 |
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value: 67.54685976014599
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1487 |
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- type: f1
|
1488 |
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value: 73.55148707559482
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1489 |
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- task:
|
1490 |
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type: Retrieval
|
1491 |
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dataset:
|
1492 |
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type: msmarco
|
1493 |
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name: MTEB MSMARCO
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1494 |
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config: default
|
1495 |
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split: dev
|
1496 |
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revision: None
|
1497 |
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metrics:
|
1498 |
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- type: map_at_1
|
1499 |
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value: 19.502
|
1500 |
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- type: map_at_10
|
1501 |
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value: 30.816
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1502 |
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- type: map_at_100
|
1503 |
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value: 32.007999999999996
|
1504 |
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- type: map_at_1000
|
1505 |
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value: 32.067
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1506 |
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- type: map_at_3
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1507 |
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value: 27.215
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1508 |
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- type: map_at_5
|
1509 |
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value: 29.304000000000002
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1510 |
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1511 |
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value: 20.072000000000003
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1512 |
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- type: mrr_at_10
|
1513 |
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value: 31.406
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1514 |
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- type: mrr_at_100
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1515 |
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value: 32.549
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1516 |
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- type: mrr_at_1000
|
1517 |
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value: 32.602
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1518 |
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- type: mrr_at_3
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1519 |
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value: 27.839000000000002
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1520 |
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1521 |
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value: 29.926000000000002
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1522 |
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- type: ndcg_at_1
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1523 |
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value: 20.086000000000002
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1524 |
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1525 |
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value: 37.282
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1526 |
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1527 |
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value: 43.206
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1528 |
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1529 |
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value: 44.690000000000005
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1530 |
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- type: ndcg_at_3
|
1531 |
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value: 29.932
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1532 |
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|
1533 |
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value: 33.668
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1534 |
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|
1535 |
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value: 20.086000000000002
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1536 |
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- type: precision_at_10
|
1537 |
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value: 5.961
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1538 |
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- type: precision_at_100
|
1539 |
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value: 0.898
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1540 |
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|
1541 |
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value: 0.10200000000000001
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1542 |
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- type: precision_at_3
|
1543 |
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value: 12.856000000000002
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1544 |
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- type: precision_at_5
|
1545 |
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value: 9.596
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1546 |
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- type: recall_at_1
|
1547 |
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value: 19.502
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1548 |
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- type: recall_at_10
|
1549 |
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value: 57.182
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1550 |
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- type: recall_at_100
|
1551 |
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value: 84.952
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1552 |
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- type: recall_at_1000
|
1553 |
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value: 96.34700000000001
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1554 |
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- type: recall_at_3
|
1555 |
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value: 37.193
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1556 |
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- type: recall_at_5
|
1557 |
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value: 46.157
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1558 |
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- task:
|
1559 |
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type: Classification
|
1560 |
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dataset:
|
1561 |
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type: mteb/mtop_domain
|
1562 |
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name: MTEB MTOPDomainClassification (en)
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1563 |
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config: en
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1564 |
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split: test
|
1565 |
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revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
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1566 |
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metrics:
|
1567 |
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- type: accuracy
|
1568 |
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value: 93.96488828089375
|
1569 |
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- type: f1
|
1570 |
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value: 93.32119260543482
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1571 |
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- task:
|
1572 |
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type: Classification
|
1573 |
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dataset:
|
1574 |
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type: mteb/mtop_intent
|
1575 |
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name: MTEB MTOPIntentClassification (en)
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1576 |
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config: en
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1577 |
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split: test
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1578 |
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revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
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1579 |
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metrics:
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1580 |
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- type: accuracy
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1581 |
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value: 72.4965800273598
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1582 |
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- type: f1
|
1583 |
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value: 49.34896217536082
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1584 |
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- task:
|
1585 |
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type: Classification
|
1586 |
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dataset:
|
1587 |
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type: mteb/amazon_massive_intent
|
1588 |
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name: MTEB MassiveIntentClassification (en)
|
1589 |
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config: en
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1590 |
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split: test
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1591 |
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revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
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1592 |
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metrics:
|
1593 |
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1594 |
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value: 67.60928043039678
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1595 |
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- type: f1
|
1596 |
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value: 64.34244712074538
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1597 |
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- task:
|
1598 |
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type: Classification
|
1599 |
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dataset:
|
1600 |
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type: mteb/amazon_massive_scenario
|
1601 |
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name: MTEB MassiveScenarioClassification (en)
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1602 |
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config: en
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1603 |
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1604 |
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revision: 7d571f92784cd94a019292a1f45445077d0ef634
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1605 |
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metrics:
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1606 |
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1607 |
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value: 69.75453934095493
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1608 |
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- type: f1
|
1609 |
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value: 68.39224867489249
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1610 |
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- task:
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1611 |
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type: Clustering
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1612 |
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dataset:
|
1613 |
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type: mteb/medrxiv-clustering-p2p
|
1614 |
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name: MTEB MedrxivClusteringP2P
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1615 |
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config: default
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1616 |
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split: test
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1617 |
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revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
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1618 |
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metrics:
|
1619 |
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1620 |
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value: 31.862573504920082
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1621 |
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- task:
|
1622 |
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type: Clustering
|
1623 |
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dataset:
|
1624 |
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type: mteb/medrxiv-clustering-s2s
|
1625 |
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name: MTEB MedrxivClusteringS2S
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1626 |
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config: default
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1627 |
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split: test
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1629 |
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metrics:
|
1630 |
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1631 |
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value: 27.511123551196803
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1632 |
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- task:
|
1633 |
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type: Reranking
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1634 |
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dataset:
|
1635 |
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type: mteb/mind_small
|
1636 |
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name: MTEB MindSmallReranking
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1637 |
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1638 |
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1639 |
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1640 |
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metrics:
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1641 |
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1642 |
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value: 30.99145104942086
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1644 |
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1645 |
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- task:
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1646 |
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1647 |
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dataset:
|
1648 |
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type: nfcorpus
|
1649 |
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name: MTEB NFCorpus
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1650 |
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config: default
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1651 |
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split: test
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1652 |
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revision: None
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1653 |
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metrics:
|
1654 |
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|
1655 |
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value: 5.015
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1656 |
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1657 |
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1658 |
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1659 |
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value: 42.105
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1693 |
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value: 7.266
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value: 32.921
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1700 |
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1701 |
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1702 |
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1703 |
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value: 5.015
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1704 |
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1705 |
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value: 14.393
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1706 |
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1707 |
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value: 28.893
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1709 |
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1712 |
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- type: recall_at_5
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1713 |
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value: 11.39
|
1714 |
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- task:
|
1715 |
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type: Retrieval
|
1716 |
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dataset:
|
1717 |
+
type: nq
|
1718 |
+
name: MTEB NQ
|
1719 |
+
config: default
|
1720 |
+
split: test
|
1721 |
+
revision: None
|
1722 |
+
metrics:
|
1723 |
+
- type: map_at_1
|
1724 |
+
value: 29.524
|
1725 |
+
- type: map_at_10
|
1726 |
+
value: 44.182
|
1727 |
+
- type: map_at_100
|
1728 |
+
value: 45.228
|
1729 |
+
- type: map_at_1000
|
1730 |
+
value: 45.265
|
1731 |
+
- type: map_at_3
|
1732 |
+
value: 39.978
|
1733 |
+
- type: map_at_5
|
1734 |
+
value: 42.482
|
1735 |
+
- type: mrr_at_1
|
1736 |
+
value: 33.256
|
1737 |
+
- type: mrr_at_10
|
1738 |
+
value: 46.661
|
1739 |
+
- type: mrr_at_100
|
1740 |
+
value: 47.47
|
1741 |
+
- type: mrr_at_1000
|
1742 |
+
value: 47.496
|
1743 |
+
- type: mrr_at_3
|
1744 |
+
value: 43.187999999999995
|
1745 |
+
- type: mrr_at_5
|
1746 |
+
value: 45.330999999999996
|
1747 |
+
- type: ndcg_at_1
|
1748 |
+
value: 33.227000000000004
|
1749 |
+
- type: ndcg_at_10
|
1750 |
+
value: 51.589
|
1751 |
+
- type: ndcg_at_100
|
1752 |
+
value: 56.043
|
1753 |
+
- type: ndcg_at_1000
|
1754 |
+
value: 56.937000000000005
|
1755 |
+
- type: ndcg_at_3
|
1756 |
+
value: 43.751
|
1757 |
+
- type: ndcg_at_5
|
1758 |
+
value: 47.937000000000005
|
1759 |
+
- type: precision_at_1
|
1760 |
+
value: 33.227000000000004
|
1761 |
+
- type: precision_at_10
|
1762 |
+
value: 8.556999999999999
|
1763 |
+
- type: precision_at_100
|
1764 |
+
value: 1.103
|
1765 |
+
- type: precision_at_1000
|
1766 |
+
value: 0.11900000000000001
|
1767 |
+
- type: precision_at_3
|
1768 |
+
value: 19.921
|
1769 |
+
- type: precision_at_5
|
1770 |
+
value: 14.396999999999998
|
1771 |
+
- type: recall_at_1
|
1772 |
+
value: 29.524
|
1773 |
+
- type: recall_at_10
|
1774 |
+
value: 71.615
|
1775 |
+
- type: recall_at_100
|
1776 |
+
value: 91.056
|
1777 |
+
- type: recall_at_1000
|
1778 |
+
value: 97.72800000000001
|
1779 |
+
- type: recall_at_3
|
1780 |
+
value: 51.451
|
1781 |
+
- type: recall_at_5
|
1782 |
+
value: 61.119
|
1783 |
+
- task:
|
1784 |
+
type: Retrieval
|
1785 |
+
dataset:
|
1786 |
+
type: quora
|
1787 |
+
name: MTEB QuoraRetrieval
|
1788 |
+
config: default
|
1789 |
+
split: test
|
1790 |
+
revision: None
|
1791 |
+
metrics:
|
1792 |
+
- type: map_at_1
|
1793 |
+
value: 69.596
|
1794 |
+
- type: map_at_10
|
1795 |
+
value: 83.281
|
1796 |
+
- type: map_at_100
|
1797 |
+
value: 83.952
|
1798 |
+
- type: map_at_1000
|
1799 |
+
value: 83.97200000000001
|
1800 |
+
- type: map_at_3
|
1801 |
+
value: 80.315
|
1802 |
+
- type: map_at_5
|
1803 |
+
value: 82.223
|
1804 |
+
- type: mrr_at_1
|
1805 |
+
value: 80.17
|
1806 |
+
- type: mrr_at_10
|
1807 |
+
value: 86.522
|
1808 |
+
- type: mrr_at_100
|
1809 |
+
value: 86.644
|
1810 |
+
- type: mrr_at_1000
|
1811 |
+
value: 86.64500000000001
|
1812 |
+
- type: mrr_at_3
|
1813 |
+
value: 85.438
|
1814 |
+
- type: mrr_at_5
|
1815 |
+
value: 86.21799999999999
|
1816 |
+
- type: ndcg_at_1
|
1817 |
+
value: 80.19
|
1818 |
+
- type: ndcg_at_10
|
1819 |
+
value: 87.19
|
1820 |
+
- type: ndcg_at_100
|
1821 |
+
value: 88.567
|
1822 |
+
- type: ndcg_at_1000
|
1823 |
+
value: 88.70400000000001
|
1824 |
+
- type: ndcg_at_3
|
1825 |
+
value: 84.17999999999999
|
1826 |
+
- type: ndcg_at_5
|
1827 |
+
value: 85.931
|
1828 |
+
- type: precision_at_1
|
1829 |
+
value: 80.19
|
1830 |
+
- type: precision_at_10
|
1831 |
+
value: 13.209000000000001
|
1832 |
+
- type: precision_at_100
|
1833 |
+
value: 1.518
|
1834 |
+
- type: precision_at_1000
|
1835 |
+
value: 0.157
|
1836 |
+
- type: precision_at_3
|
1837 |
+
value: 36.717
|
1838 |
+
- type: precision_at_5
|
1839 |
+
value: 24.248
|
1840 |
+
- type: recall_at_1
|
1841 |
+
value: 69.596
|
1842 |
+
- type: recall_at_10
|
1843 |
+
value: 94.533
|
1844 |
+
- type: recall_at_100
|
1845 |
+
value: 99.322
|
1846 |
+
- type: recall_at_1000
|
1847 |
+
value: 99.965
|
1848 |
+
- type: recall_at_3
|
1849 |
+
value: 85.911
|
1850 |
+
- type: recall_at_5
|
1851 |
+
value: 90.809
|
1852 |
+
- task:
|
1853 |
+
type: Clustering
|
1854 |
+
dataset:
|
1855 |
+
type: mteb/reddit-clustering
|
1856 |
+
name: MTEB RedditClustering
|
1857 |
+
config: default
|
1858 |
+
split: test
|
1859 |
+
revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
|
1860 |
+
metrics:
|
1861 |
+
- type: v_measure
|
1862 |
+
value: 49.27650627571912
|
1863 |
+
- task:
|
1864 |
+
type: Clustering
|
1865 |
+
dataset:
|
1866 |
+
type: mteb/reddit-clustering-p2p
|
1867 |
+
name: MTEB RedditClusteringP2P
|
1868 |
+
config: default
|
1869 |
+
split: test
|
1870 |
+
revision: 282350215ef01743dc01b456c7f5241fa8937f16
|
1871 |
+
metrics:
|
1872 |
+
- type: v_measure
|
1873 |
+
value: 57.08550946534183
|
1874 |
+
- task:
|
1875 |
+
type: Retrieval
|
1876 |
+
dataset:
|
1877 |
+
type: scidocs
|
1878 |
+
name: MTEB SCIDOCS
|
1879 |
+
config: default
|
1880 |
+
split: test
|
1881 |
+
revision: None
|
1882 |
+
metrics:
|
1883 |
+
- type: map_at_1
|
1884 |
+
value: 4.568
|
1885 |
+
- type: map_at_10
|
1886 |
+
value: 10.862
|
1887 |
+
- type: map_at_100
|
1888 |
+
value: 12.757
|
1889 |
+
- type: map_at_1000
|
1890 |
+
value: 13.031
|
1891 |
+
- type: map_at_3
|
1892 |
+
value: 7.960000000000001
|
1893 |
+
- type: map_at_5
|
1894 |
+
value: 9.337
|
1895 |
+
- type: mrr_at_1
|
1896 |
+
value: 22.5
|
1897 |
+
- type: mrr_at_10
|
1898 |
+
value: 32.6
|
1899 |
+
- type: mrr_at_100
|
1900 |
+
value: 33.603
|
1901 |
+
- type: mrr_at_1000
|
1902 |
+
value: 33.672000000000004
|
1903 |
+
- type: mrr_at_3
|
1904 |
+
value: 29.299999999999997
|
1905 |
+
- type: mrr_at_5
|
1906 |
+
value: 31.25
|
1907 |
+
- type: ndcg_at_1
|
1908 |
+
value: 22.5
|
1909 |
+
- type: ndcg_at_10
|
1910 |
+
value: 18.605
|
1911 |
+
- type: ndcg_at_100
|
1912 |
+
value: 26.029999999999998
|
1913 |
+
- type: ndcg_at_1000
|
1914 |
+
value: 31.256
|
1915 |
+
- type: ndcg_at_3
|
1916 |
+
value: 17.873
|
1917 |
+
- type: ndcg_at_5
|
1918 |
+
value: 15.511
|
1919 |
+
- type: precision_at_1
|
1920 |
+
value: 22.5
|
1921 |
+
- type: precision_at_10
|
1922 |
+
value: 9.58
|
1923 |
+
- type: precision_at_100
|
1924 |
+
value: 2.033
|
1925 |
+
- type: precision_at_1000
|
1926 |
+
value: 0.33
|
1927 |
+
- type: precision_at_3
|
1928 |
+
value: 16.633
|
1929 |
+
- type: precision_at_5
|
1930 |
+
value: 13.54
|
1931 |
+
- type: recall_at_1
|
1932 |
+
value: 4.568
|
1933 |
+
- type: recall_at_10
|
1934 |
+
value: 19.402
|
1935 |
+
- type: recall_at_100
|
1936 |
+
value: 41.277
|
1937 |
+
- type: recall_at_1000
|
1938 |
+
value: 66.963
|
1939 |
+
- type: recall_at_3
|
1940 |
+
value: 10.112
|
1941 |
+
- type: recall_at_5
|
1942 |
+
value: 13.712
|
1943 |
+
- task:
|
1944 |
+
type: STS
|
1945 |
+
dataset:
|
1946 |
+
type: mteb/sickr-sts
|
1947 |
+
name: MTEB SICK-R
|
1948 |
+
config: default
|
1949 |
+
split: test
|
1950 |
+
revision: a6ea5a8cab320b040a23452cc28066d9beae2cee
|
1951 |
+
metrics:
|
1952 |
+
- type: cos_sim_pearson
|
1953 |
+
value: 83.31992291680787
|
1954 |
+
- type: cos_sim_spearman
|
1955 |
+
value: 76.7212346922664
|
1956 |
+
- type: euclidean_pearson
|
1957 |
+
value: 80.42189271706478
|
1958 |
+
- type: euclidean_spearman
|
1959 |
+
value: 76.7212342532493
|
1960 |
+
- type: manhattan_pearson
|
1961 |
+
value: 80.33171093031578
|
1962 |
+
- type: manhattan_spearman
|
1963 |
+
value: 76.63192883074694
|
1964 |
+
- task:
|
1965 |
+
type: STS
|
1966 |
+
dataset:
|
1967 |
+
type: mteb/sts12-sts
|
1968 |
+
name: MTEB STS12
|
1969 |
+
config: default
|
1970 |
+
split: test
|
1971 |
+
revision: a0d554a64d88156834ff5ae9920b964011b16384
|
1972 |
+
metrics:
|
1973 |
+
- type: cos_sim_pearson
|
1974 |
+
value: 83.16654278886763
|
1975 |
+
- type: cos_sim_spearman
|
1976 |
+
value: 73.66390263429565
|
1977 |
+
- type: euclidean_pearson
|
1978 |
+
value: 79.7485360086639
|
1979 |
+
- type: euclidean_spearman
|
1980 |
+
value: 73.66389870373436
|
1981 |
+
- type: manhattan_pearson
|
1982 |
+
value: 79.73652237443706
|
1983 |
+
- type: manhattan_spearman
|
1984 |
+
value: 73.65296117151647
|
1985 |
+
- task:
|
1986 |
+
type: STS
|
1987 |
+
dataset:
|
1988 |
+
type: mteb/sts13-sts
|
1989 |
+
name: MTEB STS13
|
1990 |
+
config: default
|
1991 |
+
split: test
|
1992 |
+
revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
|
1993 |
+
metrics:
|
1994 |
+
- type: cos_sim_pearson
|
1995 |
+
value: 82.40389689929246
|
1996 |
+
- type: cos_sim_spearman
|
1997 |
+
value: 83.29727595993955
|
1998 |
+
- type: euclidean_pearson
|
1999 |
+
value: 82.23970587854079
|
2000 |
+
- type: euclidean_spearman
|
2001 |
+
value: 83.29727595993955
|
2002 |
+
- type: manhattan_pearson
|
2003 |
+
value: 82.18823600831897
|
2004 |
+
- type: manhattan_spearman
|
2005 |
+
value: 83.20746192209594
|
2006 |
+
- task:
|
2007 |
+
type: STS
|
2008 |
+
dataset:
|
2009 |
+
type: mteb/sts14-sts
|
2010 |
+
name: MTEB STS14
|
2011 |
+
config: default
|
2012 |
+
split: test
|
2013 |
+
revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
|
2014 |
+
metrics:
|
2015 |
+
- type: cos_sim_pearson
|
2016 |
+
value: 81.73505246913413
|
2017 |
+
- type: cos_sim_spearman
|
2018 |
+
value: 79.1686548248754
|
2019 |
+
- type: euclidean_pearson
|
2020 |
+
value: 80.48889135993412
|
2021 |
+
- type: euclidean_spearman
|
2022 |
+
value: 79.16864112930354
|
2023 |
+
- type: manhattan_pearson
|
2024 |
+
value: 80.40720651057302
|
2025 |
+
- type: manhattan_spearman
|
2026 |
+
value: 79.0640155089286
|
2027 |
+
- task:
|
2028 |
+
type: STS
|
2029 |
+
dataset:
|
2030 |
+
type: mteb/sts15-sts
|
2031 |
+
name: MTEB STS15
|
2032 |
+
config: default
|
2033 |
+
split: test
|
2034 |
+
revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
|
2035 |
+
metrics:
|
2036 |
+
- type: cos_sim_pearson
|
2037 |
+
value: 86.3953512879065
|
2038 |
+
- type: cos_sim_spearman
|
2039 |
+
value: 87.29947322714338
|
2040 |
+
- type: euclidean_pearson
|
2041 |
+
value: 86.59759438529645
|
2042 |
+
- type: euclidean_spearman
|
2043 |
+
value: 87.29947511092824
|
2044 |
+
- type: manhattan_pearson
|
2045 |
+
value: 86.52097806169155
|
2046 |
+
- type: manhattan_spearman
|
2047 |
+
value: 87.22987242146534
|
2048 |
+
- task:
|
2049 |
+
type: STS
|
2050 |
+
dataset:
|
2051 |
+
type: mteb/sts16-sts
|
2052 |
+
name: MTEB STS16
|
2053 |
+
config: default
|
2054 |
+
split: test
|
2055 |
+
revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
|
2056 |
+
metrics:
|
2057 |
+
- type: cos_sim_pearson
|
2058 |
+
value: 82.48565753792056
|
2059 |
+
- type: cos_sim_spearman
|
2060 |
+
value: 83.6049720319893
|
2061 |
+
- type: euclidean_pearson
|
2062 |
+
value: 82.56452023172913
|
2063 |
+
- type: euclidean_spearman
|
2064 |
+
value: 83.60490168191697
|
2065 |
+
- type: manhattan_pearson
|
2066 |
+
value: 82.58079941137872
|
2067 |
+
- type: manhattan_spearman
|
2068 |
+
value: 83.60975807374051
|
2069 |
+
- task:
|
2070 |
+
type: STS
|
2071 |
+
dataset:
|
2072 |
+
type: mteb/sts17-crosslingual-sts
|
2073 |
+
name: MTEB STS17 (en-en)
|
2074 |
+
config: en-en
|
2075 |
+
split: test
|
2076 |
+
revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
|
2077 |
+
metrics:
|
2078 |
+
- type: cos_sim_pearson
|
2079 |
+
value: 88.18239976618212
|
2080 |
+
- type: cos_sim_spearman
|
2081 |
+
value: 88.23061724730616
|
2082 |
+
- type: euclidean_pearson
|
2083 |
+
value: 87.78482472776658
|
2084 |
+
- type: euclidean_spearman
|
2085 |
+
value: 88.23061724730616
|
2086 |
+
- type: manhattan_pearson
|
2087 |
+
value: 87.75059641730239
|
2088 |
+
- type: manhattan_spearman
|
2089 |
+
value: 88.22527413524622
|
2090 |
+
- task:
|
2091 |
+
type: STS
|
2092 |
+
dataset:
|
2093 |
+
type: mteb/sts22-crosslingual-sts
|
2094 |
+
name: MTEB STS22 (en)
|
2095 |
+
config: en
|
2096 |
+
split: test
|
2097 |
+
revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80
|
2098 |
+
metrics:
|
2099 |
+
- type: cos_sim_pearson
|
2100 |
+
value: 63.42816418706765
|
2101 |
+
- type: cos_sim_spearman
|
2102 |
+
value: 63.4569864520124
|
2103 |
+
- type: euclidean_pearson
|
2104 |
+
value: 64.35405409953853
|
2105 |
+
- type: euclidean_spearman
|
2106 |
+
value: 63.4569864520124
|
2107 |
+
- type: manhattan_pearson
|
2108 |
+
value: 63.96649236073056
|
2109 |
+
- type: manhattan_spearman
|
2110 |
+
value: 63.01448583722708
|
2111 |
+
- task:
|
2112 |
+
type: STS
|
2113 |
+
dataset:
|
2114 |
+
type: mteb/stsbenchmark-sts
|
2115 |
+
name: MTEB STSBenchmark
|
2116 |
+
config: default
|
2117 |
+
split: test
|
2118 |
+
revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
|
2119 |
+
metrics:
|
2120 |
+
- type: cos_sim_pearson
|
2121 |
+
value: 83.41659638047614
|
2122 |
+
- type: cos_sim_spearman
|
2123 |
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value: 84.03893866106175
|
2124 |
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- type: euclidean_pearson
|
2125 |
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value: 84.2251203953798
|
2126 |
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- type: euclidean_spearman
|
2127 |
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value: 84.03893866106175
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2128 |
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- type: manhattan_pearson
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2129 |
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2130 |
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- type: manhattan_spearman
|
2131 |
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value: 84.06504411263612
|
2132 |
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- task:
|
2133 |
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type: Reranking
|
2134 |
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dataset:
|
2135 |
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type: mteb/scidocs-reranking
|
2136 |
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name: MTEB SciDocsRR
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2137 |
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config: default
|
2138 |
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split: test
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2139 |
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revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
|
2140 |
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metrics:
|
2141 |
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- type: map
|
2142 |
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value: 79.75608022582414
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2143 |
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- type: mrr
|
2144 |
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2145 |
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- task:
|
2146 |
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type: Retrieval
|
2147 |
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dataset:
|
2148 |
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type: scifact
|
2149 |
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name: MTEB SciFact
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2150 |
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config: default
|
2151 |
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split: test
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2152 |
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revision: None
|
2153 |
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metrics:
|
2154 |
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- type: map_at_1
|
2155 |
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value: 50.161
|
2156 |
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- type: map_at_10
|
2157 |
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value: 59.458999999999996
|
2158 |
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2159 |
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2160 |
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2161 |
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2162 |
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2163 |
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value: 56.45400000000001
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2164 |
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2165 |
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2166 |
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2167 |
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value: 53.333
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2168 |
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2169 |
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value: 61.050000000000004
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2170 |
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- type: mrr_at_100
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2171 |
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2172 |
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2173 |
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value: 61.624
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2174 |
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2175 |
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value: 58.889
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2176 |
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2177 |
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value: 60.122
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2178 |
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- type: ndcg_at_1
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2179 |
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2180 |
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2181 |
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value: 63.888999999999996
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2182 |
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- type: ndcg_at_100
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2183 |
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value: 66.963
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2184 |
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- type: ndcg_at_1000
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2185 |
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value: 68.062
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2186 |
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2187 |
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value: 59.01
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2188 |
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- type: ndcg_at_5
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2189 |
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value: 61.373999999999995
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2190 |
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- type: precision_at_1
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2191 |
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value: 53.333
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2192 |
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- type: precision_at_10
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2193 |
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value: 8.633000000000001
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2194 |
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- type: precision_at_100
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2195 |
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value: 1.027
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2196 |
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- type: precision_at_1000
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2197 |
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value: 0.11199999999999999
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2198 |
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- type: precision_at_3
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2199 |
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value: 23.111
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2200 |
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- type: precision_at_5
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2201 |
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value: 15.467
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2202 |
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- type: recall_at_1
|
2203 |
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value: 50.161
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2204 |
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- type: recall_at_10
|
2205 |
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value: 75.922
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2206 |
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- type: recall_at_100
|
2207 |
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value: 90.0
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2208 |
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- type: recall_at_1000
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2209 |
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value: 98.667
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2210 |
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- type: recall_at_3
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2211 |
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value: 62.90599999999999
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2212 |
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- type: recall_at_5
|
2213 |
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value: 68.828
|
2214 |
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- task:
|
2215 |
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type: PairClassification
|
2216 |
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dataset:
|
2217 |
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type: mteb/sprintduplicatequestions-pairclassification
|
2218 |
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name: MTEB SprintDuplicateQuestions
|
2219 |
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config: default
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2220 |
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split: test
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2221 |
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revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
|
2222 |
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metrics:
|
2223 |
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- type: cos_sim_accuracy
|
2224 |
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value: 99.81188118811882
|
2225 |
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- type: cos_sim_ap
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2226 |
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value: 95.11619225962413
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2227 |
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- type: cos_sim_f1
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2228 |
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value: 90.35840484603736
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2229 |
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- type: cos_sim_precision
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2230 |
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value: 91.23343527013252
|
2231 |
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- type: cos_sim_recall
|
2232 |
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value: 89.5
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2233 |
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- type: dot_accuracy
|
2234 |
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value: 99.81188118811882
|
2235 |
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- type: dot_ap
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2236 |
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value: 95.11619225962413
|
2237 |
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- type: dot_f1
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2238 |
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|
2239 |
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- type: dot_precision
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2240 |
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|
2241 |
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- type: dot_recall
|
2242 |
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value: 89.5
|
2243 |
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- type: euclidean_accuracy
|
2244 |
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value: 99.81188118811882
|
2245 |
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- type: euclidean_ap
|
2246 |
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value: 95.11619225962413
|
2247 |
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- type: euclidean_f1
|
2248 |
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value: 90.35840484603736
|
2249 |
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- type: euclidean_precision
|
2250 |
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value: 91.23343527013252
|
2251 |
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- type: euclidean_recall
|
2252 |
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value: 89.5
|
2253 |
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- type: manhattan_accuracy
|
2254 |
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value: 99.80891089108911
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2255 |
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- type: manhattan_ap
|
2256 |
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value: 95.07294266220966
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2257 |
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- type: manhattan_f1
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2258 |
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value: 90.21794221996959
|
2259 |
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- type: manhattan_precision
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2260 |
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value: 91.46968139773895
|
2261 |
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- type: manhattan_recall
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2262 |
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value: 89.0
|
2263 |
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- type: max_accuracy
|
2264 |
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value: 99.81188118811882
|
2265 |
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- type: max_ap
|
2266 |
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value: 95.11619225962413
|
2267 |
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- type: max_f1
|
2268 |
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value: 90.35840484603736
|
2269 |
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- task:
|
2270 |
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type: Clustering
|
2271 |
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dataset:
|
2272 |
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type: mteb/stackexchange-clustering
|
2273 |
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name: MTEB StackExchangeClustering
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2274 |
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config: default
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2275 |
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split: test
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2276 |
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revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
|
2277 |
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metrics:
|
2278 |
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- type: v_measure
|
2279 |
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value: 55.3481874105239
|
2280 |
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- task:
|
2281 |
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type: Clustering
|
2282 |
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dataset:
|
2283 |
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type: mteb/stackexchange-clustering-p2p
|
2284 |
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name: MTEB StackExchangeClusteringP2P
|
2285 |
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config: default
|
2286 |
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split: test
|
2287 |
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revision: 815ca46b2622cec33ccafc3735d572c266efdb44
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2288 |
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metrics:
|
2289 |
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- type: v_measure
|
2290 |
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value: 34.421291695525
|
2291 |
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- task:
|
2292 |
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type: Reranking
|
2293 |
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dataset:
|
2294 |
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type: mteb/stackoverflowdupquestions-reranking
|
2295 |
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name: MTEB StackOverflowDupQuestions
|
2296 |
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config: default
|
2297 |
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split: test
|
2298 |
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revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
|
2299 |
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metrics:
|
2300 |
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- type: map
|
2301 |
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value: 49.98746633276634
|
2302 |
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- type: mrr
|
2303 |
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value: 50.63143249724133
|
2304 |
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- task:
|
2305 |
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type: Summarization
|
2306 |
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dataset:
|
2307 |
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type: mteb/summeval
|
2308 |
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name: MTEB SummEval
|
2309 |
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config: default
|
2310 |
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split: test
|
2311 |
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revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
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2312 |
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metrics:
|
2313 |
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- type: cos_sim_pearson
|
2314 |
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value: 31.009961979844036
|
2315 |
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- type: cos_sim_spearman
|
2316 |
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value: 30.558416108881044
|
2317 |
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- type: dot_pearson
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2318 |
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value: 31.009964941134253
|
2319 |
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- type: dot_spearman
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2320 |
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value: 30.545760761761393
|
2321 |
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- task:
|
2322 |
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type: Retrieval
|
2323 |
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dataset:
|
2324 |
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type: trec-covid
|
2325 |
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name: MTEB TRECCOVID
|
2326 |
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config: default
|
2327 |
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split: test
|
2328 |
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revision: None
|
2329 |
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metrics:
|
2330 |
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- type: map_at_1
|
2331 |
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value: 0.207
|
2332 |
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- type: map_at_10
|
2333 |
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value: 1.6
|
2334 |
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2335 |
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value: 8.594
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2336 |
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2337 |
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value: 20.213
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2338 |
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- type: map_at_3
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2339 |
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value: 0.585
|
2340 |
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- type: map_at_5
|
2341 |
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value: 0.9039999999999999
|
2342 |
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- type: mrr_at_1
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2343 |
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value: 78.0
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2344 |
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|
2345 |
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value: 87.4
|
2346 |
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- type: mrr_at_100
|
2347 |
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value: 87.4
|
2348 |
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- type: mrr_at_1000
|
2349 |
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value: 87.4
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2350 |
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- type: mrr_at_3
|
2351 |
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value: 86.667
|
2352 |
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- type: mrr_at_5
|
2353 |
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value: 87.06700000000001
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2354 |
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- type: ndcg_at_1
|
2355 |
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value: 73.0
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2356 |
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- type: ndcg_at_10
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2357 |
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value: 65.18
|
2358 |
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- type: ndcg_at_100
|
2359 |
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value: 49.631
|
2360 |
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- type: ndcg_at_1000
|
2361 |
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value: 43.498999999999995
|
2362 |
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- type: ndcg_at_3
|
2363 |
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value: 71.83800000000001
|
2364 |
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- type: ndcg_at_5
|
2365 |
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value: 69.271
|
2366 |
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- type: precision_at_1
|
2367 |
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value: 78.0
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2368 |
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- type: precision_at_10
|
2369 |
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value: 69.19999999999999
|
2370 |
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- type: precision_at_100
|
2371 |
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value: 50.980000000000004
|
2372 |
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- type: precision_at_1000
|
2373 |
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value: 19.426
|
2374 |
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- type: precision_at_3
|
2375 |
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value: 77.333
|
2376 |
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- type: precision_at_5
|
2377 |
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value: 74.0
|
2378 |
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- type: recall_at_1
|
2379 |
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value: 0.207
|
2380 |
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- type: recall_at_10
|
2381 |
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value: 1.822
|
2382 |
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- type: recall_at_100
|
2383 |
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value: 11.849
|
2384 |
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- type: recall_at_1000
|
2385 |
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value: 40.492
|
2386 |
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- type: recall_at_3
|
2387 |
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value: 0.622
|
2388 |
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- type: recall_at_5
|
2389 |
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value: 0.9809999999999999
|
2390 |
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- task:
|
2391 |
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type: Retrieval
|
2392 |
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dataset:
|
2393 |
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type: webis-touche2020
|
2394 |
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name: MTEB Touche2020
|
2395 |
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config: default
|
2396 |
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split: test
|
2397 |
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revision: None
|
2398 |
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metrics:
|
2399 |
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- type: map_at_1
|
2400 |
+
value: 2.001
|
2401 |
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- type: map_at_10
|
2402 |
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value: 10.376000000000001
|
2403 |
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- type: map_at_100
|
2404 |
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value: 16.936999999999998
|
2405 |
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- type: map_at_1000
|
2406 |
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value: 18.615000000000002
|
2407 |
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- type: map_at_3
|
2408 |
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value: 5.335999999999999
|
2409 |
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- type: map_at_5
|
2410 |
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value: 7.374
|
2411 |
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- type: mrr_at_1
|
2412 |
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value: 20.408
|
2413 |
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- type: mrr_at_10
|
2414 |
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value: 38.29
|
2415 |
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- type: mrr_at_100
|
2416 |
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value: 39.33
|
2417 |
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- type: mrr_at_1000
|
2418 |
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value: 39.347
|
2419 |
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- type: mrr_at_3
|
2420 |
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value: 32.993
|
2421 |
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- type: mrr_at_5
|
2422 |
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value: 36.973
|
2423 |
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- type: ndcg_at_1
|
2424 |
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value: 17.347
|
2425 |
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- type: ndcg_at_10
|
2426 |
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value: 23.515
|
2427 |
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- type: ndcg_at_100
|
2428 |
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value: 37.457
|
2429 |
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- type: ndcg_at_1000
|
2430 |
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value: 49.439
|
2431 |
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- type: ndcg_at_3
|
2432 |
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value: 22.762999999999998
|
2433 |
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- type: ndcg_at_5
|
2434 |
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value: 22.622
|
2435 |
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- type: precision_at_1
|
2436 |
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value: 20.408
|
2437 |
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- type: precision_at_10
|
2438 |
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value: 22.448999999999998
|
2439 |
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- type: precision_at_100
|
2440 |
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value: 8.184
|
2441 |
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- type: precision_at_1000
|
2442 |
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value: 1.608
|
2443 |
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- type: precision_at_3
|
2444 |
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value: 25.85
|
2445 |
+
- type: precision_at_5
|
2446 |
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value: 25.306
|
2447 |
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- type: recall_at_1
|
2448 |
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value: 2.001
|
2449 |
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- type: recall_at_10
|
2450 |
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value: 17.422
|
2451 |
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- type: recall_at_100
|
2452 |
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value: 51.532999999999994
|
2453 |
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- type: recall_at_1000
|
2454 |
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value: 87.466
|
2455 |
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- type: recall_at_3
|
2456 |
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value: 6.861000000000001
|
2457 |
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- type: recall_at_5
|
2458 |
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value: 10.502
|
2459 |
+
- task:
|
2460 |
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type: Classification
|
2461 |
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dataset:
|
2462 |
+
type: mteb/toxic_conversations_50k
|
2463 |
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name: MTEB ToxicConversationsClassification
|
2464 |
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config: default
|
2465 |
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split: test
|
2466 |
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revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
|
2467 |
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metrics:
|
2468 |
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- type: accuracy
|
2469 |
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value: 71.54419999999999
|
2470 |
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- type: ap
|
2471 |
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value: 14.372170450843907
|
2472 |
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- type: f1
|
2473 |
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value: 54.94420257390529
|
2474 |
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- task:
|
2475 |
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type: Classification
|
2476 |
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dataset:
|
2477 |
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type: mteb/tweet_sentiment_extraction
|
2478 |
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name: MTEB TweetSentimentExtractionClassification
|
2479 |
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config: default
|
2480 |
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split: test
|
2481 |
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revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
|
2482 |
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metrics:
|
2483 |
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- type: accuracy
|
2484 |
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value: 59.402942840973395
|
2485 |
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- type: f1
|
2486 |
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value: 59.4166538875571
|
2487 |
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- task:
|
2488 |
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type: Clustering
|
2489 |
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dataset:
|
2490 |
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type: mteb/twentynewsgroups-clustering
|
2491 |
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name: MTEB TwentyNewsgroupsClustering
|
2492 |
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config: default
|
2493 |
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split: test
|
2494 |
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revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
|
2495 |
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metrics:
|
2496 |
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- type: v_measure
|
2497 |
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value: 41.569064336457906
|
2498 |
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- task:
|
2499 |
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type: PairClassification
|
2500 |
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dataset:
|
2501 |
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type: mteb/twittersemeval2015-pairclassification
|
2502 |
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name: MTEB TwitterSemEval2015
|
2503 |
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config: default
|
2504 |
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split: test
|
2505 |
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revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
|
2506 |
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metrics:
|
2507 |
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- type: cos_sim_accuracy
|
2508 |
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value: 85.31322644096085
|
2509 |
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- type: cos_sim_ap
|
2510 |
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value: 72.14518894837381
|
2511 |
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- type: cos_sim_f1
|
2512 |
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value: 66.67489813557229
|
2513 |
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- type: cos_sim_precision
|
2514 |
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value: 62.65954977953121
|
2515 |
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- type: cos_sim_recall
|
2516 |
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value: 71.2401055408971
|
2517 |
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- type: dot_accuracy
|
2518 |
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value: 85.31322644096085
|
2519 |
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- type: dot_ap
|
2520 |
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value: 72.14521480685293
|
2521 |
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- type: dot_f1
|
2522 |
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value: 66.67489813557229
|
2523 |
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- type: dot_precision
|
2524 |
+
value: 62.65954977953121
|
2525 |
+
- type: dot_recall
|
2526 |
+
value: 71.2401055408971
|
2527 |
+
- type: euclidean_accuracy
|
2528 |
+
value: 85.31322644096085
|
2529 |
+
- type: euclidean_ap
|
2530 |
+
value: 72.14520820485349
|
2531 |
+
- type: euclidean_f1
|
2532 |
+
value: 66.67489813557229
|
2533 |
+
- type: euclidean_precision
|
2534 |
+
value: 62.65954977953121
|
2535 |
+
- type: euclidean_recall
|
2536 |
+
value: 71.2401055408971
|
2537 |
+
- type: manhattan_accuracy
|
2538 |
+
value: 85.21785778148656
|
2539 |
+
- type: manhattan_ap
|
2540 |
+
value: 72.01177147657364
|
2541 |
+
- type: manhattan_f1
|
2542 |
+
value: 66.62594673833374
|
2543 |
+
- type: manhattan_precision
|
2544 |
+
value: 62.0336669699727
|
2545 |
+
- type: manhattan_recall
|
2546 |
+
value: 71.95250659630607
|
2547 |
+
- type: max_accuracy
|
2548 |
+
value: 85.31322644096085
|
2549 |
+
- type: max_ap
|
2550 |
+
value: 72.14521480685293
|
2551 |
+
- type: max_f1
|
2552 |
+
value: 66.67489813557229
|
2553 |
+
- task:
|
2554 |
+
type: PairClassification
|
2555 |
+
dataset:
|
2556 |
+
type: mteb/twitterurlcorpus-pairclassification
|
2557 |
+
name: MTEB TwitterURLCorpus
|
2558 |
+
config: default
|
2559 |
+
split: test
|
2560 |
+
revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
|
2561 |
+
metrics:
|
2562 |
+
- type: cos_sim_accuracy
|
2563 |
+
value: 89.12756626693057
|
2564 |
+
- type: cos_sim_ap
|
2565 |
+
value: 86.05430786440826
|
2566 |
+
- type: cos_sim_f1
|
2567 |
+
value: 78.27759692216631
|
2568 |
+
- type: cos_sim_precision
|
2569 |
+
value: 75.33466248931929
|
2570 |
+
- type: cos_sim_recall
|
2571 |
+
value: 81.45980905451185
|
2572 |
+
- type: dot_accuracy
|
2573 |
+
value: 89.12950673341872
|
2574 |
+
- type: dot_ap
|
2575 |
+
value: 86.05431161145492
|
2576 |
+
- type: dot_f1
|
2577 |
+
value: 78.27759692216631
|
2578 |
+
- type: dot_precision
|
2579 |
+
value: 75.33466248931929
|
2580 |
+
- type: dot_recall
|
2581 |
+
value: 81.45980905451185
|
2582 |
+
- type: euclidean_accuracy
|
2583 |
+
value: 89.12756626693057
|
2584 |
+
- type: euclidean_ap
|
2585 |
+
value: 86.05431303247397
|
2586 |
+
- type: euclidean_f1
|
2587 |
+
value: 78.27759692216631
|
2588 |
+
- type: euclidean_precision
|
2589 |
+
value: 75.33466248931929
|
2590 |
+
- type: euclidean_recall
|
2591 |
+
value: 81.45980905451185
|
2592 |
+
- type: manhattan_accuracy
|
2593 |
+
value: 89.04994760740482
|
2594 |
+
- type: manhattan_ap
|
2595 |
+
value: 86.00860610892074
|
2596 |
+
- type: manhattan_f1
|
2597 |
+
value: 78.1846776005392
|
2598 |
+
- type: manhattan_precision
|
2599 |
+
value: 76.10438839480975
|
2600 |
+
- type: manhattan_recall
|
2601 |
+
value: 80.3818909762858
|
2602 |
+
- type: max_accuracy
|
2603 |
+
value: 89.12950673341872
|
2604 |
+
- type: max_ap
|
2605 |
+
value: 86.05431303247397
|
2606 |
+
- type: max_f1
|
2607 |
+
value: 78.27759692216631
|
2608 |
---
|
2609 |
<!-- TODO: add evaluation results here -->
|
2610 |
<br><br>
|