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README.md
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@@ -8,6 +8,472 @@ tags:
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| 8 |
- sentence-similarity
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| 9 |
- gte
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| 10 |
- mteb
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| 11 |
---
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| 12 |
# gte-micro-v4
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| 13 |
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| 8 |
- sentence-similarity
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| 9 |
- gte
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| 10 |
- mteb
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| 11 |
+
model-index:
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| 12 |
+
- name: gte-micro-v4
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| 13 |
+
results:
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| 14 |
+
- task:
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| 15 |
+
type: Classification
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| 16 |
+
dataset:
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| 17 |
+
type: mteb/amazon_counterfactual
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| 18 |
+
name: MTEB AmazonCounterfactualClassification (en)
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| 19 |
+
config: en
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| 20 |
+
split: test
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| 21 |
+
revision: e8379541af4e31359cca9fbcf4b00f2671dba205
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| 22 |
+
metrics:
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| 23 |
+
- type: accuracy
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| 24 |
+
value: 71.83582089552239
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| 25 |
+
- type: ap
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| 26 |
+
value: 34.436093320979126
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| 27 |
+
- type: f1
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| 28 |
+
value: 65.82844954638102
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| 29 |
+
- task:
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| 30 |
+
type: Classification
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| 31 |
+
dataset:
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| 32 |
+
type: mteb/amazon_polarity
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| 33 |
+
name: MTEB AmazonPolarityClassification
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| 34 |
+
config: default
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| 35 |
+
split: test
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| 36 |
+
revision: e2d317d38cd51312af73b3d32a06d1a08b442046
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| 37 |
+
metrics:
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| 38 |
+
- type: accuracy
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| 39 |
+
value: 80.03957500000001
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| 40 |
+
- type: ap
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| 41 |
+
value: 74.4510899901909
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| 42 |
+
- type: f1
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| 43 |
+
value: 79.98034714963279
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| 44 |
+
- task:
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| 45 |
+
type: Classification
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| 46 |
+
dataset:
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| 47 |
+
type: mteb/amazon_reviews_multi
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| 48 |
+
name: MTEB AmazonReviewsClassification (en)
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| 49 |
+
config: en
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| 50 |
+
split: test
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| 51 |
+
revision: 1399c76144fd37290681b995c656ef9b2e06e26d
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| 52 |
+
metrics:
|
| 53 |
+
- type: accuracy
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| 54 |
+
value: 39.754
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| 55 |
+
- type: f1
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| 56 |
+
value: 39.423135672769796
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| 57 |
+
- task:
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| 58 |
+
type: Clustering
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| 59 |
+
dataset:
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| 60 |
+
type: mteb/arxiv-clustering-p2p
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| 61 |
+
name: MTEB ArxivClusteringP2P
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| 62 |
+
config: default
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| 63 |
+
split: test
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| 64 |
+
revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
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| 65 |
+
metrics:
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| 66 |
+
- type: v_measure
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| 67 |
+
value: 42.85928858083004
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| 68 |
+
- task:
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| 69 |
+
type: Clustering
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| 70 |
+
dataset:
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| 71 |
+
type: mteb/arxiv-clustering-s2s
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| 72 |
+
name: MTEB ArxivClusteringS2S
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| 73 |
+
config: default
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| 74 |
+
split: test
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| 75 |
+
revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
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| 76 |
+
metrics:
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| 77 |
+
- type: v_measure
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| 78 |
+
value: 32.475201371814784
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| 79 |
+
- task:
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| 80 |
+
type: Reranking
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| 81 |
+
dataset:
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| 82 |
+
type: mteb/askubuntudupquestions-reranking
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| 83 |
+
name: MTEB AskUbuntuDupQuestions
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| 84 |
+
config: default
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| 85 |
+
split: test
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| 86 |
+
revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
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| 87 |
+
metrics:
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| 88 |
+
- type: map
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| 89 |
+
value: 58.01141755339977
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| 90 |
+
- type: mrr
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| 91 |
+
value: 71.70821791320407
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| 92 |
+
- task:
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| 93 |
+
type: Classification
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| 94 |
+
dataset:
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| 95 |
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type: mteb/banking77
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| 96 |
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name: MTEB Banking77Classification
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| 97 |
+
config: default
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| 98 |
+
split: test
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| 99 |
+
revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
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| 100 |
+
metrics:
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| 101 |
+
- type: accuracy
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| 102 |
+
value: 80.9220779220779
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| 103 |
+
- type: f1
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| 104 |
+
value: 80.86851039874094
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| 105 |
+
- task:
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| 106 |
+
type: Clustering
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| 107 |
+
dataset:
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| 108 |
+
type: mteb/biorxiv-clustering-p2p
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| 109 |
+
name: MTEB BiorxivClusteringP2P
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| 110 |
+
config: default
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| 111 |
+
split: test
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| 112 |
+
revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
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| 113 |
+
metrics:
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| 114 |
+
- type: v_measure
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| 115 |
+
value: 36.82555236565894
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| 116 |
+
- task:
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| 117 |
+
type: Clustering
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| 118 |
+
dataset:
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| 119 |
+
type: mteb/biorxiv-clustering-s2s
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| 120 |
+
name: MTEB BiorxivClusteringS2S
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| 121 |
+
config: default
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| 122 |
+
split: test
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| 123 |
+
revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
|
| 124 |
+
metrics:
|
| 125 |
+
- type: v_measure
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| 126 |
+
value: 29.243444611175995
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| 127 |
+
- task:
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| 128 |
+
type: Classification
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| 129 |
+
dataset:
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| 130 |
+
type: mteb/emotion
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| 131 |
+
name: MTEB EmotionClassification
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| 132 |
+
config: default
|
| 133 |
+
split: test
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| 134 |
+
revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
|
| 135 |
+
metrics:
|
| 136 |
+
- type: accuracy
|
| 137 |
+
value: 44.87500000000001
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| 138 |
+
- type: f1
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| 139 |
+
value: 39.78455417008123
|
| 140 |
+
- task:
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| 141 |
+
type: Classification
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| 142 |
+
dataset:
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| 143 |
+
type: mteb/imdb
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| 144 |
+
name: MTEB ImdbClassification
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| 145 |
+
config: default
|
| 146 |
+
split: test
|
| 147 |
+
revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
|
| 148 |
+
metrics:
|
| 149 |
+
- type: accuracy
|
| 150 |
+
value: 71.9568
|
| 151 |
+
- type: ap
|
| 152 |
+
value: 65.91179027501194
|
| 153 |
+
- type: f1
|
| 154 |
+
value: 71.85575290323182
|
| 155 |
+
- task:
|
| 156 |
+
type: Classification
|
| 157 |
+
dataset:
|
| 158 |
+
type: mteb/mtop_domain
|
| 159 |
+
name: MTEB MTOPDomainClassification (en)
|
| 160 |
+
config: en
|
| 161 |
+
split: test
|
| 162 |
+
revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
|
| 163 |
+
metrics:
|
| 164 |
+
- type: accuracy
|
| 165 |
+
value: 90.87323301413589
|
| 166 |
+
- type: f1
|
| 167 |
+
value: 90.45433994230181
|
| 168 |
+
- task:
|
| 169 |
+
type: Classification
|
| 170 |
+
dataset:
|
| 171 |
+
type: mteb/mtop_intent
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| 172 |
+
name: MTEB MTOPIntentClassification (en)
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| 173 |
+
config: en
|
| 174 |
+
split: test
|
| 175 |
+
revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
|
| 176 |
+
metrics:
|
| 177 |
+
- type: accuracy
|
| 178 |
+
value: 68.53169174646602
|
| 179 |
+
- type: f1
|
| 180 |
+
value: 50.49367676485481
|
| 181 |
+
- task:
|
| 182 |
+
type: Classification
|
| 183 |
+
dataset:
|
| 184 |
+
type: mteb/amazon_massive_intent
|
| 185 |
+
name: MTEB MassiveIntentClassification (en)
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| 186 |
+
config: en
|
| 187 |
+
split: test
|
| 188 |
+
revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
|
| 189 |
+
metrics:
|
| 190 |
+
- type: accuracy
|
| 191 |
+
value: 69.11230665770007
|
| 192 |
+
- type: f1
|
| 193 |
+
value: 66.9035022957204
|
| 194 |
+
- task:
|
| 195 |
+
type: Classification
|
| 196 |
+
dataset:
|
| 197 |
+
type: mteb/amazon_massive_scenario
|
| 198 |
+
name: MTEB MassiveScenarioClassification (en)
|
| 199 |
+
config: en
|
| 200 |
+
split: test
|
| 201 |
+
revision: 7d571f92784cd94a019292a1f45445077d0ef634
|
| 202 |
+
metrics:
|
| 203 |
+
- type: accuracy
|
| 204 |
+
value: 74.15601882985877
|
| 205 |
+
- type: f1
|
| 206 |
+
value: 74.059011768806
|
| 207 |
+
- task:
|
| 208 |
+
type: Clustering
|
| 209 |
+
dataset:
|
| 210 |
+
type: mteb/medrxiv-clustering-p2p
|
| 211 |
+
name: MTEB MedrxivClusteringP2P
|
| 212 |
+
config: default
|
| 213 |
+
split: test
|
| 214 |
+
revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
|
| 215 |
+
metrics:
|
| 216 |
+
- type: v_measure
|
| 217 |
+
value: 32.551619758274406
|
| 218 |
+
- task:
|
| 219 |
+
type: Clustering
|
| 220 |
+
dataset:
|
| 221 |
+
type: mteb/medrxiv-clustering-s2s
|
| 222 |
+
name: MTEB MedrxivClusteringS2S
|
| 223 |
+
config: default
|
| 224 |
+
split: test
|
| 225 |
+
revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
|
| 226 |
+
metrics:
|
| 227 |
+
- type: v_measure
|
| 228 |
+
value: 30.80210958999942
|
| 229 |
+
- task:
|
| 230 |
+
type: Clustering
|
| 231 |
+
dataset:
|
| 232 |
+
type: mteb/reddit-clustering
|
| 233 |
+
name: MTEB RedditClustering
|
| 234 |
+
config: default
|
| 235 |
+
split: test
|
| 236 |
+
revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
|
| 237 |
+
metrics:
|
| 238 |
+
- type: v_measure
|
| 239 |
+
value: 48.27542501963987
|
| 240 |
+
- task:
|
| 241 |
+
type: Clustering
|
| 242 |
+
dataset:
|
| 243 |
+
type: mteb/reddit-clustering-p2p
|
| 244 |
+
name: MTEB RedditClusteringP2P
|
| 245 |
+
config: default
|
| 246 |
+
split: test
|
| 247 |
+
revision: 385e3cb46b4cfa89021f56c4380204149d0efe33
|
| 248 |
+
metrics:
|
| 249 |
+
- type: v_measure
|
| 250 |
+
value: 53.55942763860501
|
| 251 |
+
- task:
|
| 252 |
+
type: PairClassification
|
| 253 |
+
dataset:
|
| 254 |
+
type: mteb/sprintduplicatequestions-pairclassification
|
| 255 |
+
name: MTEB SprintDuplicateQuestions
|
| 256 |
+
config: default
|
| 257 |
+
split: test
|
| 258 |
+
revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
|
| 259 |
+
metrics:
|
| 260 |
+
- type: cos_sim_accuracy
|
| 261 |
+
value: 99.82673267326733
|
| 262 |
+
- type: cos_sim_ap
|
| 263 |
+
value: 95.53621808930455
|
| 264 |
+
- type: cos_sim_f1
|
| 265 |
+
value: 91.19275289380975
|
| 266 |
+
- type: cos_sim_precision
|
| 267 |
+
value: 91.7933130699088
|
| 268 |
+
- type: cos_sim_recall
|
| 269 |
+
value: 90.60000000000001
|
| 270 |
+
- type: dot_accuracy
|
| 271 |
+
value: 99.75445544554455
|
| 272 |
+
- type: dot_ap
|
| 273 |
+
value: 92.76410342229411
|
| 274 |
+
- type: dot_f1
|
| 275 |
+
value: 87.50612444879961
|
| 276 |
+
- type: dot_precision
|
| 277 |
+
value: 85.78290105667628
|
| 278 |
+
- type: dot_recall
|
| 279 |
+
value: 89.3
|
| 280 |
+
- type: euclidean_accuracy
|
| 281 |
+
value: 99.82673267326733
|
| 282 |
+
- type: euclidean_ap
|
| 283 |
+
value: 95.46124795179632
|
| 284 |
+
- type: euclidean_f1
|
| 285 |
+
value: 91.01181304571135
|
| 286 |
+
- type: euclidean_precision
|
| 287 |
+
value: 93.55860612460401
|
| 288 |
+
- type: euclidean_recall
|
| 289 |
+
value: 88.6
|
| 290 |
+
- type: manhattan_accuracy
|
| 291 |
+
value: 99.82871287128712
|
| 292 |
+
- type: manhattan_ap
|
| 293 |
+
value: 95.51436288466519
|
| 294 |
+
- type: manhattan_f1
|
| 295 |
+
value: 91.11891620672353
|
| 296 |
+
- type: manhattan_precision
|
| 297 |
+
value: 91.44008056394763
|
| 298 |
+
- type: manhattan_recall
|
| 299 |
+
value: 90.8
|
| 300 |
+
- type: max_accuracy
|
| 301 |
+
value: 99.82871287128712
|
| 302 |
+
- type: max_ap
|
| 303 |
+
value: 95.53621808930455
|
| 304 |
+
- type: max_f1
|
| 305 |
+
value: 91.19275289380975
|
| 306 |
+
- task:
|
| 307 |
+
type: Clustering
|
| 308 |
+
dataset:
|
| 309 |
+
type: mteb/stackexchange-clustering
|
| 310 |
+
name: MTEB StackExchangeClustering
|
| 311 |
+
config: default
|
| 312 |
+
split: test
|
| 313 |
+
revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
|
| 314 |
+
metrics:
|
| 315 |
+
- type: v_measure
|
| 316 |
+
value: 55.0721745308552
|
| 317 |
+
- task:
|
| 318 |
+
type: Clustering
|
| 319 |
+
dataset:
|
| 320 |
+
type: mteb/stackexchange-clustering-p2p
|
| 321 |
+
name: MTEB StackExchangeClusteringP2P
|
| 322 |
+
config: default
|
| 323 |
+
split: test
|
| 324 |
+
revision: 815ca46b2622cec33ccafc3735d572c266efdb44
|
| 325 |
+
metrics:
|
| 326 |
+
- type: v_measure
|
| 327 |
+
value: 31.91639764792279
|
| 328 |
+
- task:
|
| 329 |
+
type: Classification
|
| 330 |
+
dataset:
|
| 331 |
+
type: mteb/toxic_conversations_50k
|
| 332 |
+
name: MTEB ToxicConversationsClassification
|
| 333 |
+
config: default
|
| 334 |
+
split: test
|
| 335 |
+
revision: edfaf9da55d3dd50d43143d90c1ac476895ae6de
|
| 336 |
+
metrics:
|
| 337 |
+
- type: accuracy
|
| 338 |
+
value: 66.0402
|
| 339 |
+
- type: ap
|
| 340 |
+
value: 12.106715125588833
|
| 341 |
+
- type: f1
|
| 342 |
+
value: 50.67443088623853
|
| 343 |
+
- task:
|
| 344 |
+
type: Classification
|
| 345 |
+
dataset:
|
| 346 |
+
type: mteb/tweet_sentiment_extraction
|
| 347 |
+
name: MTEB TweetSentimentExtractionClassification
|
| 348 |
+
config: default
|
| 349 |
+
split: test
|
| 350 |
+
revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
|
| 351 |
+
metrics:
|
| 352 |
+
- type: accuracy
|
| 353 |
+
value: 59.42840973401245
|
| 354 |
+
- type: f1
|
| 355 |
+
value: 59.813350770208665
|
| 356 |
+
- task:
|
| 357 |
+
type: Clustering
|
| 358 |
+
dataset:
|
| 359 |
+
type: mteb/twentynewsgroups-clustering
|
| 360 |
+
name: MTEB TwentyNewsgroupsClustering
|
| 361 |
+
config: default
|
| 362 |
+
split: test
|
| 363 |
+
revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
|
| 364 |
+
metrics:
|
| 365 |
+
- type: v_measure
|
| 366 |
+
value: 41.37273187829312
|
| 367 |
+
- task:
|
| 368 |
+
type: PairClassification
|
| 369 |
+
dataset:
|
| 370 |
+
type: mteb/twittersemeval2015-pairclassification
|
| 371 |
+
name: MTEB TwitterSemEval2015
|
| 372 |
+
config: default
|
| 373 |
+
split: test
|
| 374 |
+
revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
|
| 375 |
+
metrics:
|
| 376 |
+
- type: cos_sim_accuracy
|
| 377 |
+
value: 84.10919711509806
|
| 378 |
+
- type: cos_sim_ap
|
| 379 |
+
value: 67.55255054010537
|
| 380 |
+
- type: cos_sim_f1
|
| 381 |
+
value: 64.22774378823823
|
| 382 |
+
- type: cos_sim_precision
|
| 383 |
+
value: 60.9623133443944
|
| 384 |
+
- type: cos_sim_recall
|
| 385 |
+
value: 67.86279683377309
|
| 386 |
+
- type: dot_accuracy
|
| 387 |
+
value: 80.62228050306967
|
| 388 |
+
- type: dot_ap
|
| 389 |
+
value: 54.81480289413879
|
| 390 |
+
- type: dot_f1
|
| 391 |
+
value: 54.22550997534184
|
| 392 |
+
- type: dot_precision
|
| 393 |
+
value: 47.13561964146532
|
| 394 |
+
- type: dot_recall
|
| 395 |
+
value: 63.82585751978892
|
| 396 |
+
- type: euclidean_accuracy
|
| 397 |
+
value: 84.04363116170948
|
| 398 |
+
- type: euclidean_ap
|
| 399 |
+
value: 67.77652401372912
|
| 400 |
+
- type: euclidean_f1
|
| 401 |
+
value: 64.46694460988684
|
| 402 |
+
- type: euclidean_precision
|
| 403 |
+
value: 58.762214983713356
|
| 404 |
+
- type: euclidean_recall
|
| 405 |
+
value: 71.39841688654354
|
| 406 |
+
- type: manhattan_accuracy
|
| 407 |
+
value: 83.94230196101806
|
| 408 |
+
- type: manhattan_ap
|
| 409 |
+
value: 67.419155052755
|
| 410 |
+
- type: manhattan_f1
|
| 411 |
+
value: 64.15049692380501
|
| 412 |
+
- type: manhattan_precision
|
| 413 |
+
value: 58.151008151008156
|
| 414 |
+
- type: manhattan_recall
|
| 415 |
+
value: 71.53034300791556
|
| 416 |
+
- type: max_accuracy
|
| 417 |
+
value: 84.10919711509806
|
| 418 |
+
- type: max_ap
|
| 419 |
+
value: 67.77652401372912
|
| 420 |
+
- type: max_f1
|
| 421 |
+
value: 64.46694460988684
|
| 422 |
+
- task:
|
| 423 |
+
type: PairClassification
|
| 424 |
+
dataset:
|
| 425 |
+
type: mteb/twitterurlcorpus-pairclassification
|
| 426 |
+
name: MTEB TwitterURLCorpus
|
| 427 |
+
config: default
|
| 428 |
+
split: test
|
| 429 |
+
revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
|
| 430 |
+
metrics:
|
| 431 |
+
- type: cos_sim_accuracy
|
| 432 |
+
value: 88.25823728024217
|
| 433 |
+
- type: cos_sim_ap
|
| 434 |
+
value: 84.67785320317506
|
| 435 |
+
- type: cos_sim_f1
|
| 436 |
+
value: 76.67701296330108
|
| 437 |
+
- type: cos_sim_precision
|
| 438 |
+
value: 72.92491491282907
|
| 439 |
+
- type: cos_sim_recall
|
| 440 |
+
value: 80.83615645210965
|
| 441 |
+
- type: dot_accuracy
|
| 442 |
+
value: 84.63344588038964
|
| 443 |
+
- type: dot_ap
|
| 444 |
+
value: 75.25182203961072
|
| 445 |
+
- type: dot_f1
|
| 446 |
+
value: 70.35217601881962
|
| 447 |
+
- type: dot_precision
|
| 448 |
+
value: 63.87737152908657
|
| 449 |
+
- type: dot_recall
|
| 450 |
+
value: 78.28765013858947
|
| 451 |
+
- type: euclidean_accuracy
|
| 452 |
+
value: 88.2504754142896
|
| 453 |
+
- type: euclidean_ap
|
| 454 |
+
value: 84.68882859374924
|
| 455 |
+
- type: euclidean_f1
|
| 456 |
+
value: 76.69534508021188
|
| 457 |
+
- type: euclidean_precision
|
| 458 |
+
value: 74.89177489177489
|
| 459 |
+
- type: euclidean_recall
|
| 460 |
+
value: 78.58792731752386
|
| 461 |
+
- type: manhattan_accuracy
|
| 462 |
+
value: 88.26211821321846
|
| 463 |
+
- type: manhattan_ap
|
| 464 |
+
value: 84.60061548046698
|
| 465 |
+
- type: manhattan_f1
|
| 466 |
+
value: 76.63928519959647
|
| 467 |
+
- type: manhattan_precision
|
| 468 |
+
value: 72.02058504875406
|
| 469 |
+
- type: manhattan_recall
|
| 470 |
+
value: 81.89097628580228
|
| 471 |
+
- type: max_accuracy
|
| 472 |
+
value: 88.26211821321846
|
| 473 |
+
- type: max_ap
|
| 474 |
+
value: 84.68882859374924
|
| 475 |
+
- type: max_f1
|
| 476 |
+
value: 76.69534508021188
|
| 477 |
---
|
| 478 |
# gte-micro-v4
|
| 479 |
|