Commit
•
b387470
1
Parent(s):
8ee96fb
Fix the computation of the mean embedding
Browse filesSigned-off-by: Aivin V. Solatorio <avsolatorio@gmail.com>
- 1_Pooling/config.json +11 -0
- 2_Pooling/config.json +11 -0
- README.md +2676 -3
- commit-info.json +1 -0
- config.json +32 -0
- config_sentence_transformers.json +9 -0
- model.safetensors +3 -0
- modules.json +26 -0
- sentence_bert_config.json +4 -0
- special_tokens_map.json +37 -0
- tokenizer.json +0 -0
- tokenizer_config.json +57 -0
- vocab.txt +0 -0
1_Pooling/config.json
ADDED
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@@ -0,0 +1,11 @@
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{
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"word_embedding_dimension": 384,
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"pooling_mode_cls_token": true,
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"pooling_mode_mean_tokens": false,
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"pooling_mode_max_tokens": false,
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"pooling_mode_mean_sqrt_len_tokens": false,
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"pooling_mode_weightedmean_tokens": false,
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"pooling_mode_lasttoken": false,
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"include_prompt": true,
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"output_key": "sentence_embedding"
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}
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2_Pooling/config.json
ADDED
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@@ -0,0 +1,11 @@
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{
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"word_embedding_dimension": 384,
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"pooling_mode_cls_token": false,
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"pooling_mode_mean_tokens": true,
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"pooling_mode_max_tokens": false,
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"pooling_mode_mean_sqrt_len_tokens": false,
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"pooling_mode_weightedmean_tokens": false,
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"pooling_mode_lasttoken": false,
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"include_prompt": true,
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"output_key": "query_embedding"
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}
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README.md
CHANGED
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@@ -1,3 +1,2676 @@
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| 1 |
+
---
|
| 2 |
+
language:
|
| 3 |
+
- en
|
| 4 |
+
library_name: sentence-transformers
|
| 5 |
+
license: mit
|
| 6 |
+
pipeline_tag: sentence-similarity
|
| 7 |
+
tags:
|
| 8 |
+
- feature-extraction
|
| 9 |
+
- mteb
|
| 10 |
+
- sentence-similarity
|
| 11 |
+
- sentence-transformers
|
| 12 |
+
- transformers
|
| 13 |
+
model-index:
|
| 14 |
+
- name: NoInstruct-small-Embedding-v0
|
| 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: 75.76119402985074
|
| 27 |
+
- type: ap
|
| 28 |
+
value: 39.03628777559392
|
| 29 |
+
- type: f1
|
| 30 |
+
value: 69.85860402259618
|
| 31 |
+
- task:
|
| 32 |
+
type: Classification
|
| 33 |
+
dataset:
|
| 34 |
+
type: mteb/amazon_polarity
|
| 35 |
+
name: MTEB AmazonPolarityClassification
|
| 36 |
+
config: default
|
| 37 |
+
split: test
|
| 38 |
+
revision: e2d317d38cd51312af73b3d32a06d1a08b442046
|
| 39 |
+
metrics:
|
| 40 |
+
- type: accuracy
|
| 41 |
+
value: 93.29920000000001
|
| 42 |
+
- type: ap
|
| 43 |
+
value: 90.03479490717608
|
| 44 |
+
- type: f1
|
| 45 |
+
value: 93.28554395248467
|
| 46 |
+
- task:
|
| 47 |
+
type: Classification
|
| 48 |
+
dataset:
|
| 49 |
+
type: mteb/amazon_reviews_multi
|
| 50 |
+
name: MTEB AmazonReviewsClassification (en)
|
| 51 |
+
config: en
|
| 52 |
+
split: test
|
| 53 |
+
revision: 1399c76144fd37290681b995c656ef9b2e06e26d
|
| 54 |
+
metrics:
|
| 55 |
+
- type: accuracy
|
| 56 |
+
value: 49.98799999999999
|
| 57 |
+
- type: f1
|
| 58 |
+
value: 49.46151232451642
|
| 59 |
+
- task:
|
| 60 |
+
type: Retrieval
|
| 61 |
+
dataset:
|
| 62 |
+
type: mteb/arguana
|
| 63 |
+
name: MTEB ArguAna
|
| 64 |
+
config: default
|
| 65 |
+
split: test
|
| 66 |
+
revision: c22ab2a51041ffd869aaddef7af8d8215647e41a
|
| 67 |
+
metrics:
|
| 68 |
+
- type: map_at_1
|
| 69 |
+
value: 31.935000000000002
|
| 70 |
+
- type: map_at_10
|
| 71 |
+
value: 48.791000000000004
|
| 72 |
+
- type: map_at_100
|
| 73 |
+
value: 49.619
|
| 74 |
+
- type: map_at_1000
|
| 75 |
+
value: 49.623
|
| 76 |
+
- type: map_at_3
|
| 77 |
+
value: 44.334
|
| 78 |
+
- type: map_at_5
|
| 79 |
+
value: 46.908
|
| 80 |
+
- type: mrr_at_1
|
| 81 |
+
value: 32.93
|
| 82 |
+
- type: mrr_at_10
|
| 83 |
+
value: 49.158
|
| 84 |
+
- type: mrr_at_100
|
| 85 |
+
value: 50.00599999999999
|
| 86 |
+
- type: mrr_at_1000
|
| 87 |
+
value: 50.01
|
| 88 |
+
- type: mrr_at_3
|
| 89 |
+
value: 44.618
|
| 90 |
+
- type: mrr_at_5
|
| 91 |
+
value: 47.325
|
| 92 |
+
- type: ndcg_at_1
|
| 93 |
+
value: 31.935000000000002
|
| 94 |
+
- type: ndcg_at_10
|
| 95 |
+
value: 57.593
|
| 96 |
+
- type: ndcg_at_100
|
| 97 |
+
value: 60.841
|
| 98 |
+
- type: ndcg_at_1000
|
| 99 |
+
value: 60.924
|
| 100 |
+
- type: ndcg_at_3
|
| 101 |
+
value: 48.416
|
| 102 |
+
- type: ndcg_at_5
|
| 103 |
+
value: 53.05
|
| 104 |
+
- type: precision_at_1
|
| 105 |
+
value: 31.935000000000002
|
| 106 |
+
- type: precision_at_10
|
| 107 |
+
value: 8.549
|
| 108 |
+
- type: precision_at_100
|
| 109 |
+
value: 0.9900000000000001
|
| 110 |
+
- type: precision_at_1000
|
| 111 |
+
value: 0.1
|
| 112 |
+
- type: precision_at_3
|
| 113 |
+
value: 20.081
|
| 114 |
+
- type: precision_at_5
|
| 115 |
+
value: 14.296000000000001
|
| 116 |
+
- type: recall_at_1
|
| 117 |
+
value: 31.935000000000002
|
| 118 |
+
- type: recall_at_10
|
| 119 |
+
value: 85.491
|
| 120 |
+
- type: recall_at_100
|
| 121 |
+
value: 99.004
|
| 122 |
+
- type: recall_at_1000
|
| 123 |
+
value: 99.644
|
| 124 |
+
- type: recall_at_3
|
| 125 |
+
value: 60.242
|
| 126 |
+
- type: recall_at_5
|
| 127 |
+
value: 71.479
|
| 128 |
+
- task:
|
| 129 |
+
type: Clustering
|
| 130 |
+
dataset:
|
| 131 |
+
type: mteb/arxiv-clustering-p2p
|
| 132 |
+
name: MTEB ArxivClusteringP2P
|
| 133 |
+
config: default
|
| 134 |
+
split: test
|
| 135 |
+
revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
|
| 136 |
+
metrics:
|
| 137 |
+
- type: v_measure
|
| 138 |
+
value: 47.78438534940855
|
| 139 |
+
- task:
|
| 140 |
+
type: Clustering
|
| 141 |
+
dataset:
|
| 142 |
+
type: mteb/arxiv-clustering-s2s
|
| 143 |
+
name: MTEB ArxivClusteringS2S
|
| 144 |
+
config: default
|
| 145 |
+
split: test
|
| 146 |
+
revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
|
| 147 |
+
metrics:
|
| 148 |
+
- type: v_measure
|
| 149 |
+
value: 40.12916178519471
|
| 150 |
+
- task:
|
| 151 |
+
type: Reranking
|
| 152 |
+
dataset:
|
| 153 |
+
type: mteb/askubuntudupquestions-reranking
|
| 154 |
+
name: MTEB AskUbuntuDupQuestions
|
| 155 |
+
config: default
|
| 156 |
+
split: test
|
| 157 |
+
revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
|
| 158 |
+
metrics:
|
| 159 |
+
- type: map
|
| 160 |
+
value: 62.125361608299855
|
| 161 |
+
- type: mrr
|
| 162 |
+
value: 74.92525172580574
|
| 163 |
+
- task:
|
| 164 |
+
type: STS
|
| 165 |
+
dataset:
|
| 166 |
+
type: mteb/biosses-sts
|
| 167 |
+
name: MTEB BIOSSES
|
| 168 |
+
config: default
|
| 169 |
+
split: test
|
| 170 |
+
revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
|
| 171 |
+
metrics:
|
| 172 |
+
- type: cos_sim_pearson
|
| 173 |
+
value: 88.64322910336641
|
| 174 |
+
- type: cos_sim_spearman
|
| 175 |
+
value: 87.20138453306345
|
| 176 |
+
- type: euclidean_pearson
|
| 177 |
+
value: 87.08547818178234
|
| 178 |
+
- type: euclidean_spearman
|
| 179 |
+
value: 87.17066094143931
|
| 180 |
+
- type: manhattan_pearson
|
| 181 |
+
value: 87.30053110771618
|
| 182 |
+
- type: manhattan_spearman
|
| 183 |
+
value: 86.86824441211934
|
| 184 |
+
- task:
|
| 185 |
+
type: Classification
|
| 186 |
+
dataset:
|
| 187 |
+
type: mteb/banking77
|
| 188 |
+
name: MTEB Banking77Classification
|
| 189 |
+
config: default
|
| 190 |
+
split: test
|
| 191 |
+
revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
|
| 192 |
+
metrics:
|
| 193 |
+
- type: accuracy
|
| 194 |
+
value: 86.3961038961039
|
| 195 |
+
- type: f1
|
| 196 |
+
value: 86.3669961645295
|
| 197 |
+
- task:
|
| 198 |
+
type: Clustering
|
| 199 |
+
dataset:
|
| 200 |
+
type: mteb/biorxiv-clustering-p2p
|
| 201 |
+
name: MTEB BiorxivClusteringP2P
|
| 202 |
+
config: default
|
| 203 |
+
split: test
|
| 204 |
+
revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
|
| 205 |
+
metrics:
|
| 206 |
+
- type: v_measure
|
| 207 |
+
value: 39.40291404289857
|
| 208 |
+
- task:
|
| 209 |
+
type: Clustering
|
| 210 |
+
dataset:
|
| 211 |
+
type: mteb/biorxiv-clustering-s2s
|
| 212 |
+
name: MTEB BiorxivClusteringS2S
|
| 213 |
+
config: default
|
| 214 |
+
split: test
|
| 215 |
+
revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
|
| 216 |
+
metrics:
|
| 217 |
+
- type: v_measure
|
| 218 |
+
value: 35.102356817746816
|
| 219 |
+
- task:
|
| 220 |
+
type: Retrieval
|
| 221 |
+
dataset:
|
| 222 |
+
type: mteb/cqadupstack-android
|
| 223 |
+
name: MTEB CQADupstackAndroidRetrieval
|
| 224 |
+
config: default
|
| 225 |
+
split: test
|
| 226 |
+
revision: f46a197baaae43b4f621051089b82a364682dfeb
|
| 227 |
+
metrics:
|
| 228 |
+
- type: map_at_1
|
| 229 |
+
value: 31.013
|
| 230 |
+
- type: map_at_10
|
| 231 |
+
value: 42.681999999999995
|
| 232 |
+
- type: map_at_100
|
| 233 |
+
value: 44.24
|
| 234 |
+
- type: map_at_1000
|
| 235 |
+
value: 44.372
|
| 236 |
+
- type: map_at_3
|
| 237 |
+
value: 39.181
|
| 238 |
+
- type: map_at_5
|
| 239 |
+
value: 41.071999999999996
|
| 240 |
+
- type: mrr_at_1
|
| 241 |
+
value: 38.196999999999996
|
| 242 |
+
- type: mrr_at_10
|
| 243 |
+
value: 48.604
|
| 244 |
+
- type: mrr_at_100
|
| 245 |
+
value: 49.315
|
| 246 |
+
- type: mrr_at_1000
|
| 247 |
+
value: 49.363
|
| 248 |
+
- type: mrr_at_3
|
| 249 |
+
value: 45.756
|
| 250 |
+
- type: mrr_at_5
|
| 251 |
+
value: 47.43
|
| 252 |
+
- type: ndcg_at_1
|
| 253 |
+
value: 38.196999999999996
|
| 254 |
+
- type: ndcg_at_10
|
| 255 |
+
value: 49.344
|
| 256 |
+
- type: ndcg_at_100
|
| 257 |
+
value: 54.662
|
| 258 |
+
- type: ndcg_at_1000
|
| 259 |
+
value: 56.665
|
| 260 |
+
- type: ndcg_at_3
|
| 261 |
+
value: 44.146
|
| 262 |
+
- type: ndcg_at_5
|
| 263 |
+
value: 46.514
|
| 264 |
+
- type: precision_at_1
|
| 265 |
+
value: 38.196999999999996
|
| 266 |
+
- type: precision_at_10
|
| 267 |
+
value: 9.571
|
| 268 |
+
- type: precision_at_100
|
| 269 |
+
value: 1.542
|
| 270 |
+
- type: precision_at_1000
|
| 271 |
+
value: 0.202
|
| 272 |
+
- type: precision_at_3
|
| 273 |
+
value: 21.364
|
| 274 |
+
- type: precision_at_5
|
| 275 |
+
value: 15.336
|
| 276 |
+
- type: recall_at_1
|
| 277 |
+
value: 31.013
|
| 278 |
+
- type: recall_at_10
|
| 279 |
+
value: 61.934999999999995
|
| 280 |
+
- type: recall_at_100
|
| 281 |
+
value: 83.923
|
| 282 |
+
- type: recall_at_1000
|
| 283 |
+
value: 96.601
|
| 284 |
+
- type: recall_at_3
|
| 285 |
+
value: 46.86
|
| 286 |
+
- type: recall_at_5
|
| 287 |
+
value: 53.620000000000005
|
| 288 |
+
- task:
|
| 289 |
+
type: Retrieval
|
| 290 |
+
dataset:
|
| 291 |
+
type: mteb/cqadupstack-english
|
| 292 |
+
name: MTEB CQADupstackEnglishRetrieval
|
| 293 |
+
config: default
|
| 294 |
+
split: test
|
| 295 |
+
revision: ad9991cb51e31e31e430383c75ffb2885547b5f0
|
| 296 |
+
metrics:
|
| 297 |
+
- type: map_at_1
|
| 298 |
+
value: 29.84
|
| 299 |
+
- type: map_at_10
|
| 300 |
+
value: 39.335
|
| 301 |
+
- type: map_at_100
|
| 302 |
+
value: 40.647
|
| 303 |
+
- type: map_at_1000
|
| 304 |
+
value: 40.778
|
| 305 |
+
- type: map_at_3
|
| 306 |
+
value: 36.556
|
| 307 |
+
- type: map_at_5
|
| 308 |
+
value: 38.048
|
| 309 |
+
- type: mrr_at_1
|
| 310 |
+
value: 36.815
|
| 311 |
+
- type: mrr_at_10
|
| 312 |
+
value: 45.175
|
| 313 |
+
- type: mrr_at_100
|
| 314 |
+
value: 45.907
|
| 315 |
+
- type: mrr_at_1000
|
| 316 |
+
value: 45.946999999999996
|
| 317 |
+
- type: mrr_at_3
|
| 318 |
+
value: 42.909000000000006
|
| 319 |
+
- type: mrr_at_5
|
| 320 |
+
value: 44.227
|
| 321 |
+
- type: ndcg_at_1
|
| 322 |
+
value: 36.815
|
| 323 |
+
- type: ndcg_at_10
|
| 324 |
+
value: 44.783
|
| 325 |
+
- type: ndcg_at_100
|
| 326 |
+
value: 49.551
|
| 327 |
+
- type: ndcg_at_1000
|
| 328 |
+
value: 51.612
|
| 329 |
+
- type: ndcg_at_3
|
| 330 |
+
value: 40.697
|
| 331 |
+
- type: ndcg_at_5
|
| 332 |
+
value: 42.558
|
| 333 |
+
- type: precision_at_1
|
| 334 |
+
value: 36.815
|
| 335 |
+
- type: precision_at_10
|
| 336 |
+
value: 8.363
|
| 337 |
+
- type: precision_at_100
|
| 338 |
+
value: 1.385
|
| 339 |
+
- type: precision_at_1000
|
| 340 |
+
value: 0.186
|
| 341 |
+
- type: precision_at_3
|
| 342 |
+
value: 19.342000000000002
|
| 343 |
+
- type: precision_at_5
|
| 344 |
+
value: 13.706999999999999
|
| 345 |
+
- type: recall_at_1
|
| 346 |
+
value: 29.84
|
| 347 |
+
- type: recall_at_10
|
| 348 |
+
value: 54.164
|
| 349 |
+
- type: recall_at_100
|
| 350 |
+
value: 74.36
|
| 351 |
+
- type: recall_at_1000
|
| 352 |
+
value: 87.484
|
| 353 |
+
- type: recall_at_3
|
| 354 |
+
value: 42.306
|
| 355 |
+
- type: recall_at_5
|
| 356 |
+
value: 47.371
|
| 357 |
+
- task:
|
| 358 |
+
type: Retrieval
|
| 359 |
+
dataset:
|
| 360 |
+
type: mteb/cqadupstack-gaming
|
| 361 |
+
name: MTEB CQADupstackGamingRetrieval
|
| 362 |
+
config: default
|
| 363 |
+
split: test
|
| 364 |
+
revision: 4885aa143210c98657558c04aaf3dc47cfb54340
|
| 365 |
+
metrics:
|
| 366 |
+
- type: map_at_1
|
| 367 |
+
value: 39.231
|
| 368 |
+
- type: map_at_10
|
| 369 |
+
value: 51.44800000000001
|
| 370 |
+
- type: map_at_100
|
| 371 |
+
value: 52.574
|
| 372 |
+
- type: map_at_1000
|
| 373 |
+
value: 52.629999999999995
|
| 374 |
+
- type: map_at_3
|
| 375 |
+
value: 48.077
|
| 376 |
+
- type: map_at_5
|
| 377 |
+
value: 50.019000000000005
|
| 378 |
+
- type: mrr_at_1
|
| 379 |
+
value: 44.89
|
| 380 |
+
- type: mrr_at_10
|
| 381 |
+
value: 54.803000000000004
|
| 382 |
+
- type: mrr_at_100
|
| 383 |
+
value: 55.556000000000004
|
| 384 |
+
- type: mrr_at_1000
|
| 385 |
+
value: 55.584
|
| 386 |
+
- type: mrr_at_3
|
| 387 |
+
value: 52.32
|
| 388 |
+
- type: mrr_at_5
|
| 389 |
+
value: 53.846000000000004
|
| 390 |
+
- type: ndcg_at_1
|
| 391 |
+
value: 44.89
|
| 392 |
+
- type: ndcg_at_10
|
| 393 |
+
value: 57.228
|
| 394 |
+
- type: ndcg_at_100
|
| 395 |
+
value: 61.57
|
| 396 |
+
- type: ndcg_at_1000
|
| 397 |
+
value: 62.613
|
| 398 |
+
- type: ndcg_at_3
|
| 399 |
+
value: 51.727000000000004
|
| 400 |
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- type: ndcg_at_5
|
| 401 |
+
value: 54.496
|
| 402 |
+
- type: precision_at_1
|
| 403 |
+
value: 44.89
|
| 404 |
+
- type: precision_at_10
|
| 405 |
+
value: 9.266
|
| 406 |
+
- type: precision_at_100
|
| 407 |
+
value: 1.2309999999999999
|
| 408 |
+
- type: precision_at_1000
|
| 409 |
+
value: 0.136
|
| 410 |
+
- type: precision_at_3
|
| 411 |
+
value: 23.051
|
| 412 |
+
- type: precision_at_5
|
| 413 |
+
value: 15.987000000000002
|
| 414 |
+
- type: recall_at_1
|
| 415 |
+
value: 39.231
|
| 416 |
+
- type: recall_at_10
|
| 417 |
+
value: 70.82000000000001
|
| 418 |
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- type: recall_at_100
|
| 419 |
+
value: 89.446
|
| 420 |
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- type: recall_at_1000
|
| 421 |
+
value: 96.665
|
| 422 |
+
- type: recall_at_3
|
| 423 |
+
value: 56.40500000000001
|
| 424 |
+
- type: recall_at_5
|
| 425 |
+
value: 62.993
|
| 426 |
+
- task:
|
| 427 |
+
type: Retrieval
|
| 428 |
+
dataset:
|
| 429 |
+
type: mteb/cqadupstack-gis
|
| 430 |
+
name: MTEB CQADupstackGisRetrieval
|
| 431 |
+
config: default
|
| 432 |
+
split: test
|
| 433 |
+
revision: 5003b3064772da1887988e05400cf3806fe491f2
|
| 434 |
+
metrics:
|
| 435 |
+
- type: map_at_1
|
| 436 |
+
value: 25.296000000000003
|
| 437 |
+
- type: map_at_10
|
| 438 |
+
value: 34.021
|
| 439 |
+
- type: map_at_100
|
| 440 |
+
value: 35.158
|
| 441 |
+
- type: map_at_1000
|
| 442 |
+
value: 35.233
|
| 443 |
+
- type: map_at_3
|
| 444 |
+
value: 31.424999999999997
|
| 445 |
+
- type: map_at_5
|
| 446 |
+
value: 33.046
|
| 447 |
+
- type: mrr_at_1
|
| 448 |
+
value: 27.232
|
| 449 |
+
- type: mrr_at_10
|
| 450 |
+
value: 36.103
|
| 451 |
+
- type: mrr_at_100
|
| 452 |
+
value: 37.076
|
| 453 |
+
- type: mrr_at_1000
|
| 454 |
+
value: 37.135
|
| 455 |
+
- type: mrr_at_3
|
| 456 |
+
value: 33.635
|
| 457 |
+
- type: mrr_at_5
|
| 458 |
+
value: 35.211
|
| 459 |
+
- type: ndcg_at_1
|
| 460 |
+
value: 27.232
|
| 461 |
+
- type: ndcg_at_10
|
| 462 |
+
value: 38.878
|
| 463 |
+
- type: ndcg_at_100
|
| 464 |
+
value: 44.284
|
| 465 |
+
- type: ndcg_at_1000
|
| 466 |
+
value: 46.268
|
| 467 |
+
- type: ndcg_at_3
|
| 468 |
+
value: 33.94
|
| 469 |
+
- type: ndcg_at_5
|
| 470 |
+
value: 36.687
|
| 471 |
+
- type: precision_at_1
|
| 472 |
+
value: 27.232
|
| 473 |
+
- type: precision_at_10
|
| 474 |
+
value: 5.921
|
| 475 |
+
- type: precision_at_100
|
| 476 |
+
value: 0.907
|
| 477 |
+
- type: precision_at_1000
|
| 478 |
+
value: 0.11199999999999999
|
| 479 |
+
- type: precision_at_3
|
| 480 |
+
value: 14.426
|
| 481 |
+
- type: precision_at_5
|
| 482 |
+
value: 10.215
|
| 483 |
+
- type: recall_at_1
|
| 484 |
+
value: 25.296000000000003
|
| 485 |
+
- type: recall_at_10
|
| 486 |
+
value: 51.708
|
| 487 |
+
- type: recall_at_100
|
| 488 |
+
value: 76.36699999999999
|
| 489 |
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- type: recall_at_1000
|
| 490 |
+
value: 91.306
|
| 491 |
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- type: recall_at_3
|
| 492 |
+
value: 38.651
|
| 493 |
+
- type: recall_at_5
|
| 494 |
+
value: 45.201
|
| 495 |
+
- task:
|
| 496 |
+
type: Retrieval
|
| 497 |
+
dataset:
|
| 498 |
+
type: mteb/cqadupstack-mathematica
|
| 499 |
+
name: MTEB CQADupstackMathematicaRetrieval
|
| 500 |
+
config: default
|
| 501 |
+
split: test
|
| 502 |
+
revision: 90fceea13679c63fe563ded68f3b6f06e50061de
|
| 503 |
+
metrics:
|
| 504 |
+
- type: map_at_1
|
| 505 |
+
value: 16.24
|
| 506 |
+
- type: map_at_10
|
| 507 |
+
value: 24.696
|
| 508 |
+
- type: map_at_100
|
| 509 |
+
value: 25.945
|
| 510 |
+
- type: map_at_1000
|
| 511 |
+
value: 26.069
|
| 512 |
+
- type: map_at_3
|
| 513 |
+
value: 22.542
|
| 514 |
+
- type: map_at_5
|
| 515 |
+
value: 23.526
|
| 516 |
+
- type: mrr_at_1
|
| 517 |
+
value: 20.149
|
| 518 |
+
- type: mrr_at_10
|
| 519 |
+
value: 29.584
|
| 520 |
+
- type: mrr_at_100
|
| 521 |
+
value: 30.548
|
| 522 |
+
- type: mrr_at_1000
|
| 523 |
+
value: 30.618000000000002
|
| 524 |
+
- type: mrr_at_3
|
| 525 |
+
value: 27.301
|
| 526 |
+
- type: mrr_at_5
|
| 527 |
+
value: 28.563
|
| 528 |
+
- type: ndcg_at_1
|
| 529 |
+
value: 20.149
|
| 530 |
+
- type: ndcg_at_10
|
| 531 |
+
value: 30.029
|
| 532 |
+
- type: ndcg_at_100
|
| 533 |
+
value: 35.812
|
| 534 |
+
- type: ndcg_at_1000
|
| 535 |
+
value: 38.755
|
| 536 |
+
- type: ndcg_at_3
|
| 537 |
+
value: 26.008
|
| 538 |
+
- type: ndcg_at_5
|
| 539 |
+
value: 27.517000000000003
|
| 540 |
+
- type: precision_at_1
|
| 541 |
+
value: 20.149
|
| 542 |
+
- type: precision_at_10
|
| 543 |
+
value: 5.647
|
| 544 |
+
- type: precision_at_100
|
| 545 |
+
value: 0.968
|
| 546 |
+
- type: precision_at_1000
|
| 547 |
+
value: 0.136
|
| 548 |
+
- type: precision_at_3
|
| 549 |
+
value: 12.934999999999999
|
| 550 |
+
- type: precision_at_5
|
| 551 |
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value: 8.955
|
| 552 |
+
- type: recall_at_1
|
| 553 |
+
value: 16.24
|
| 554 |
+
- type: recall_at_10
|
| 555 |
+
value: 41.464
|
| 556 |
+
- type: recall_at_100
|
| 557 |
+
value: 66.781
|
| 558 |
+
- type: recall_at_1000
|
| 559 |
+
value: 87.85300000000001
|
| 560 |
+
- type: recall_at_3
|
| 561 |
+
value: 29.822
|
| 562 |
+
- type: recall_at_5
|
| 563 |
+
value: 34.096
|
| 564 |
+
- task:
|
| 565 |
+
type: Retrieval
|
| 566 |
+
dataset:
|
| 567 |
+
type: mteb/cqadupstack-physics
|
| 568 |
+
name: MTEB CQADupstackPhysicsRetrieval
|
| 569 |
+
config: default
|
| 570 |
+
split: test
|
| 571 |
+
revision: 79531abbd1fb92d06c6d6315a0cbbbf5bb247ea4
|
| 572 |
+
metrics:
|
| 573 |
+
- type: map_at_1
|
| 574 |
+
value: 29.044999999999998
|
| 575 |
+
- type: map_at_10
|
| 576 |
+
value: 39.568999999999996
|
| 577 |
+
- type: map_at_100
|
| 578 |
+
value: 40.831
|
| 579 |
+
- type: map_at_1000
|
| 580 |
+
value: 40.948
|
| 581 |
+
- type: map_at_3
|
| 582 |
+
value: 36.495
|
| 583 |
+
- type: map_at_5
|
| 584 |
+
value: 38.21
|
| 585 |
+
- type: mrr_at_1
|
| 586 |
+
value: 35.611
|
| 587 |
+
- type: mrr_at_10
|
| 588 |
+
value: 45.175
|
| 589 |
+
- type: mrr_at_100
|
| 590 |
+
value: 45.974
|
| 591 |
+
- type: mrr_at_1000
|
| 592 |
+
value: 46.025
|
| 593 |
+
- type: mrr_at_3
|
| 594 |
+
value: 42.765
|
| 595 |
+
- type: mrr_at_5
|
| 596 |
+
value: 44.151
|
| 597 |
+
- type: ndcg_at_1
|
| 598 |
+
value: 35.611
|
| 599 |
+
- type: ndcg_at_10
|
| 600 |
+
value: 45.556999999999995
|
| 601 |
+
- type: ndcg_at_100
|
| 602 |
+
value: 50.86000000000001
|
| 603 |
+
- type: ndcg_at_1000
|
| 604 |
+
value: 52.983000000000004
|
| 605 |
+
- type: ndcg_at_3
|
| 606 |
+
value: 40.881
|
| 607 |
+
- type: ndcg_at_5
|
| 608 |
+
value: 43.035000000000004
|
| 609 |
+
- type: precision_at_1
|
| 610 |
+
value: 35.611
|
| 611 |
+
- type: precision_at_10
|
| 612 |
+
value: 8.306
|
| 613 |
+
- type: precision_at_100
|
| 614 |
+
value: 1.276
|
| 615 |
+
- type: precision_at_1000
|
| 616 |
+
value: 0.165
|
| 617 |
+
- type: precision_at_3
|
| 618 |
+
value: 19.57
|
| 619 |
+
- type: precision_at_5
|
| 620 |
+
value: 13.725000000000001
|
| 621 |
+
- type: recall_at_1
|
| 622 |
+
value: 29.044999999999998
|
| 623 |
+
- type: recall_at_10
|
| 624 |
+
value: 57.513999999999996
|
| 625 |
+
- type: recall_at_100
|
| 626 |
+
value: 80.152
|
| 627 |
+
- type: recall_at_1000
|
| 628 |
+
value: 93.982
|
| 629 |
+
- type: recall_at_3
|
| 630 |
+
value: 44.121
|
| 631 |
+
- type: recall_at_5
|
| 632 |
+
value: 50.007000000000005
|
| 633 |
+
- task:
|
| 634 |
+
type: Retrieval
|
| 635 |
+
dataset:
|
| 636 |
+
type: mteb/cqadupstack-programmers
|
| 637 |
+
name: MTEB CQADupstackProgrammersRetrieval
|
| 638 |
+
config: default
|
| 639 |
+
split: test
|
| 640 |
+
revision: 6184bc1440d2dbc7612be22b50686b8826d22b32
|
| 641 |
+
metrics:
|
| 642 |
+
- type: map_at_1
|
| 643 |
+
value: 22.349
|
| 644 |
+
- type: map_at_10
|
| 645 |
+
value: 33.434000000000005
|
| 646 |
+
- type: map_at_100
|
| 647 |
+
value: 34.8
|
| 648 |
+
- type: map_at_1000
|
| 649 |
+
value: 34.919
|
| 650 |
+
- type: map_at_3
|
| 651 |
+
value: 30.348000000000003
|
| 652 |
+
- type: map_at_5
|
| 653 |
+
value: 31.917
|
| 654 |
+
- type: mrr_at_1
|
| 655 |
+
value: 28.195999999999998
|
| 656 |
+
- type: mrr_at_10
|
| 657 |
+
value: 38.557
|
| 658 |
+
- type: mrr_at_100
|
| 659 |
+
value: 39.550999999999995
|
| 660 |
+
- type: mrr_at_1000
|
| 661 |
+
value: 39.607
|
| 662 |
+
- type: mrr_at_3
|
| 663 |
+
value: 36.035000000000004
|
| 664 |
+
- type: mrr_at_5
|
| 665 |
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value: 37.364999999999995
|
| 666 |
+
- type: ndcg_at_1
|
| 667 |
+
value: 28.195999999999998
|
| 668 |
+
- type: ndcg_at_10
|
| 669 |
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value: 39.656000000000006
|
| 670 |
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- type: ndcg_at_100
|
| 671 |
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value: 45.507999999999996
|
| 672 |
+
- type: ndcg_at_1000
|
| 673 |
+
value: 47.848
|
| 674 |
+
- type: ndcg_at_3
|
| 675 |
+
value: 34.609
|
| 676 |
+
- type: ndcg_at_5
|
| 677 |
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value: 36.65
|
| 678 |
+
- type: precision_at_1
|
| 679 |
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value: 28.195999999999998
|
| 680 |
+
- type: precision_at_10
|
| 681 |
+
value: 7.534000000000001
|
| 682 |
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- type: precision_at_100
|
| 683 |
+
value: 1.217
|
| 684 |
+
- type: precision_at_1000
|
| 685 |
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value: 0.158
|
| 686 |
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- type: precision_at_3
|
| 687 |
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value: 17.085
|
| 688 |
+
- type: precision_at_5
|
| 689 |
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value: 12.169
|
| 690 |
+
- type: recall_at_1
|
| 691 |
+
value: 22.349
|
| 692 |
+
- type: recall_at_10
|
| 693 |
+
value: 53.127
|
| 694 |
+
- type: recall_at_100
|
| 695 |
+
value: 77.884
|
| 696 |
+
- type: recall_at_1000
|
| 697 |
+
value: 93.705
|
| 698 |
+
- type: recall_at_3
|
| 699 |
+
value: 38.611000000000004
|
| 700 |
+
- type: recall_at_5
|
| 701 |
+
value: 44.182
|
| 702 |
+
- task:
|
| 703 |
+
type: Retrieval
|
| 704 |
+
dataset:
|
| 705 |
+
type: mteb/cqadupstack
|
| 706 |
+
name: MTEB CQADupstackRetrieval
|
| 707 |
+
config: default
|
| 708 |
+
split: test
|
| 709 |
+
revision: 4ffe81d471b1924886b33c7567bfb200e9eec5c4
|
| 710 |
+
metrics:
|
| 711 |
+
- type: map_at_1
|
| 712 |
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value: 25.215749999999996
|
| 713 |
+
- type: map_at_10
|
| 714 |
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value: 34.332750000000004
|
| 715 |
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- type: map_at_100
|
| 716 |
+
value: 35.58683333333333
|
| 717 |
+
- type: map_at_1000
|
| 718 |
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value: 35.70458333333333
|
| 719 |
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- type: map_at_3
|
| 720 |
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value: 31.55441666666667
|
| 721 |
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- type: map_at_5
|
| 722 |
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value: 33.100833333333334
|
| 723 |
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- type: mrr_at_1
|
| 724 |
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value: 29.697250000000004
|
| 725 |
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- type: mrr_at_10
|
| 726 |
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value: 38.372249999999994
|
| 727 |
+
- type: mrr_at_100
|
| 728 |
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value: 39.26708333333334
|
| 729 |
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- type: mrr_at_1000
|
| 730 |
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value: 39.3265
|
| 731 |
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- type: mrr_at_3
|
| 732 |
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value: 35.946083333333334
|
| 733 |
+
- type: mrr_at_5
|
| 734 |
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value: 37.336999999999996
|
| 735 |
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- type: ndcg_at_1
|
| 736 |
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value: 29.697250000000004
|
| 737 |
+
- type: ndcg_at_10
|
| 738 |
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value: 39.64575
|
| 739 |
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- type: ndcg_at_100
|
| 740 |
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value: 44.996833333333335
|
| 741 |
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- type: ndcg_at_1000
|
| 742 |
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value: 47.314499999999995
|
| 743 |
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- type: ndcg_at_3
|
| 744 |
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value: 34.93383333333334
|
| 745 |
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- type: ndcg_at_5
|
| 746 |
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value: 37.15291666666667
|
| 747 |
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- type: precision_at_1
|
| 748 |
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value: 29.697250000000004
|
| 749 |
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- type: precision_at_10
|
| 750 |
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value: 6.98825
|
| 751 |
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- type: precision_at_100
|
| 752 |
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value: 1.138
|
| 753 |
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- type: precision_at_1000
|
| 754 |
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value: 0.15283333333333332
|
| 755 |
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- type: precision_at_3
|
| 756 |
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value: 16.115583333333333
|
| 757 |
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- type: precision_at_5
|
| 758 |
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value: 11.460916666666666
|
| 759 |
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- type: recall_at_1
|
| 760 |
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value: 25.215749999999996
|
| 761 |
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- type: recall_at_10
|
| 762 |
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value: 51.261250000000004
|
| 763 |
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- type: recall_at_100
|
| 764 |
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value: 74.67258333333334
|
| 765 |
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- type: recall_at_1000
|
| 766 |
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value: 90.72033333333334
|
| 767 |
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- type: recall_at_3
|
| 768 |
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value: 38.1795
|
| 769 |
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- type: recall_at_5
|
| 770 |
+
value: 43.90658333333334
|
| 771 |
+
- task:
|
| 772 |
+
type: Retrieval
|
| 773 |
+
dataset:
|
| 774 |
+
type: mteb/cqadupstack-stats
|
| 775 |
+
name: MTEB CQADupstackStatsRetrieval
|
| 776 |
+
config: default
|
| 777 |
+
split: test
|
| 778 |
+
revision: 65ac3a16b8e91f9cee4c9828cc7c335575432a2a
|
| 779 |
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metrics:
|
| 780 |
+
- type: map_at_1
|
| 781 |
+
value: 24.352
|
| 782 |
+
- type: map_at_10
|
| 783 |
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value: 30.576999999999998
|
| 784 |
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- type: map_at_100
|
| 785 |
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value: 31.545
|
| 786 |
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- type: map_at_1000
|
| 787 |
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value: 31.642
|
| 788 |
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- type: map_at_3
|
| 789 |
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value: 28.605000000000004
|
| 790 |
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- type: map_at_5
|
| 791 |
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value: 29.828
|
| 792 |
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- type: mrr_at_1
|
| 793 |
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value: 26.994
|
| 794 |
+
- type: mrr_at_10
|
| 795 |
+
value: 33.151
|
| 796 |
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- type: mrr_at_100
|
| 797 |
+
value: 33.973
|
| 798 |
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- type: mrr_at_1000
|
| 799 |
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value: 34.044999999999995
|
| 800 |
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- type: mrr_at_3
|
| 801 |
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value: 31.135
|
| 802 |
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- type: mrr_at_5
|
| 803 |
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value: 32.262
|
| 804 |
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- type: ndcg_at_1
|
| 805 |
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value: 26.994
|
| 806 |
+
- type: ndcg_at_10
|
| 807 |
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value: 34.307
|
| 808 |
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- type: ndcg_at_100
|
| 809 |
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value: 39.079
|
| 810 |
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- type: ndcg_at_1000
|
| 811 |
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value: 41.548
|
| 812 |
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- type: ndcg_at_3
|
| 813 |
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value: 30.581000000000003
|
| 814 |
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- type: ndcg_at_5
|
| 815 |
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value: 32.541
|
| 816 |
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- type: precision_at_1
|
| 817 |
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value: 26.994
|
| 818 |
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- type: precision_at_10
|
| 819 |
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value: 5.244999999999999
|
| 820 |
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- type: precision_at_100
|
| 821 |
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value: 0.831
|
| 822 |
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- type: precision_at_1000
|
| 823 |
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value: 0.11100000000000002
|
| 824 |
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- type: precision_at_3
|
| 825 |
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value: 12.781
|
| 826 |
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- type: precision_at_5
|
| 827 |
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value: 9.017999999999999
|
| 828 |
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- type: recall_at_1
|
| 829 |
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value: 24.352
|
| 830 |
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- type: recall_at_10
|
| 831 |
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value: 43.126999999999995
|
| 832 |
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- type: recall_at_100
|
| 833 |
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value: 64.845
|
| 834 |
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- type: recall_at_1000
|
| 835 |
+
value: 83.244
|
| 836 |
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- type: recall_at_3
|
| 837 |
+
value: 33.308
|
| 838 |
+
- type: recall_at_5
|
| 839 |
+
value: 37.984
|
| 840 |
+
- task:
|
| 841 |
+
type: Retrieval
|
| 842 |
+
dataset:
|
| 843 |
+
type: mteb/cqadupstack-tex
|
| 844 |
+
name: MTEB CQADupstackTexRetrieval
|
| 845 |
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config: default
|
| 846 |
+
split: test
|
| 847 |
+
revision: 46989137a86843e03a6195de44b09deda022eec7
|
| 848 |
+
metrics:
|
| 849 |
+
- type: map_at_1
|
| 850 |
+
value: 16.592000000000002
|
| 851 |
+
- type: map_at_10
|
| 852 |
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value: 23.29
|
| 853 |
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- type: map_at_100
|
| 854 |
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value: 24.423000000000002
|
| 855 |
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- type: map_at_1000
|
| 856 |
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value: 24.554000000000002
|
| 857 |
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- type: map_at_3
|
| 858 |
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value: 20.958
|
| 859 |
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- type: map_at_5
|
| 860 |
+
value: 22.267
|
| 861 |
+
- type: mrr_at_1
|
| 862 |
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value: 20.061999999999998
|
| 863 |
+
- type: mrr_at_10
|
| 864 |
+
value: 26.973999999999997
|
| 865 |
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- type: mrr_at_100
|
| 866 |
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value: 27.944999999999997
|
| 867 |
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- type: mrr_at_1000
|
| 868 |
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value: 28.023999999999997
|
| 869 |
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- type: mrr_at_3
|
| 870 |
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value: 24.839
|
| 871 |
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- type: mrr_at_5
|
| 872 |
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value: 26.033
|
| 873 |
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- type: ndcg_at_1
|
| 874 |
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value: 20.061999999999998
|
| 875 |
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- type: ndcg_at_10
|
| 876 |
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value: 27.682000000000002
|
| 877 |
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- type: ndcg_at_100
|
| 878 |
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value: 33.196
|
| 879 |
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- type: ndcg_at_1000
|
| 880 |
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value: 36.246
|
| 881 |
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- type: ndcg_at_3
|
| 882 |
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value: 23.559
|
| 883 |
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- type: ndcg_at_5
|
| 884 |
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value: 25.507
|
| 885 |
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- type: precision_at_1
|
| 886 |
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value: 20.061999999999998
|
| 887 |
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- type: precision_at_10
|
| 888 |
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value: 5.086
|
| 889 |
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- type: precision_at_100
|
| 890 |
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value: 0.9249999999999999
|
| 891 |
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- type: precision_at_1000
|
| 892 |
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value: 0.136
|
| 893 |
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- type: precision_at_3
|
| 894 |
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value: 11.046
|
| 895 |
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- type: precision_at_5
|
| 896 |
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value: 8.149000000000001
|
| 897 |
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- type: recall_at_1
|
| 898 |
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value: 16.592000000000002
|
| 899 |
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- type: recall_at_10
|
| 900 |
+
value: 37.181999999999995
|
| 901 |
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- type: recall_at_100
|
| 902 |
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value: 62.224999999999994
|
| 903 |
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- type: recall_at_1000
|
| 904 |
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value: 84.072
|
| 905 |
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- type: recall_at_3
|
| 906 |
+
value: 25.776
|
| 907 |
+
- type: recall_at_5
|
| 908 |
+
value: 30.680000000000003
|
| 909 |
+
- task:
|
| 910 |
+
type: Retrieval
|
| 911 |
+
dataset:
|
| 912 |
+
type: mteb/cqadupstack-unix
|
| 913 |
+
name: MTEB CQADupstackUnixRetrieval
|
| 914 |
+
config: default
|
| 915 |
+
split: test
|
| 916 |
+
revision: 6c6430d3a6d36f8d2a829195bc5dc94d7e063e53
|
| 917 |
+
metrics:
|
| 918 |
+
- type: map_at_1
|
| 919 |
+
value: 26.035999999999998
|
| 920 |
+
- type: map_at_10
|
| 921 |
+
value: 34.447
|
| 922 |
+
- type: map_at_100
|
| 923 |
+
value: 35.697
|
| 924 |
+
- type: map_at_1000
|
| 925 |
+
value: 35.802
|
| 926 |
+
- type: map_at_3
|
| 927 |
+
value: 31.64
|
| 928 |
+
- type: map_at_5
|
| 929 |
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value: 33.056999999999995
|
| 930 |
+
- type: mrr_at_1
|
| 931 |
+
value: 29.851
|
| 932 |
+
- type: mrr_at_10
|
| 933 |
+
value: 38.143
|
| 934 |
+
- type: mrr_at_100
|
| 935 |
+
value: 39.113
|
| 936 |
+
- type: mrr_at_1000
|
| 937 |
+
value: 39.175
|
| 938 |
+
- type: mrr_at_3
|
| 939 |
+
value: 35.665
|
| 940 |
+
- type: mrr_at_5
|
| 941 |
+
value: 36.901
|
| 942 |
+
- type: ndcg_at_1
|
| 943 |
+
value: 29.851
|
| 944 |
+
- type: ndcg_at_10
|
| 945 |
+
value: 39.554
|
| 946 |
+
- type: ndcg_at_100
|
| 947 |
+
value: 45.091
|
| 948 |
+
- type: ndcg_at_1000
|
| 949 |
+
value: 47.504000000000005
|
| 950 |
+
- type: ndcg_at_3
|
| 951 |
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value: 34.414
|
| 952 |
+
- type: ndcg_at_5
|
| 953 |
+
value: 36.508
|
| 954 |
+
- type: precision_at_1
|
| 955 |
+
value: 29.851
|
| 956 |
+
- type: precision_at_10
|
| 957 |
+
value: 6.614000000000001
|
| 958 |
+
- type: precision_at_100
|
| 959 |
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value: 1.051
|
| 960 |
+
- type: precision_at_1000
|
| 961 |
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value: 0.13699999999999998
|
| 962 |
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- type: precision_at_3
|
| 963 |
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value: 15.329999999999998
|
| 964 |
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- type: precision_at_5
|
| 965 |
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value: 10.671999999999999
|
| 966 |
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- type: recall_at_1
|
| 967 |
+
value: 26.035999999999998
|
| 968 |
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- type: recall_at_10
|
| 969 |
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value: 51.396
|
| 970 |
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- type: recall_at_100
|
| 971 |
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value: 75.09
|
| 972 |
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- type: recall_at_1000
|
| 973 |
+
value: 91.904
|
| 974 |
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- type: recall_at_3
|
| 975 |
+
value: 37.378
|
| 976 |
+
- type: recall_at_5
|
| 977 |
+
value: 42.69
|
| 978 |
+
- task:
|
| 979 |
+
type: Retrieval
|
| 980 |
+
dataset:
|
| 981 |
+
type: mteb/cqadupstack-webmasters
|
| 982 |
+
name: MTEB CQADupstackWebmastersRetrieval
|
| 983 |
+
config: default
|
| 984 |
+
split: test
|
| 985 |
+
revision: 160c094312a0e1facb97e55eeddb698c0abe3571
|
| 986 |
+
metrics:
|
| 987 |
+
- type: map_at_1
|
| 988 |
+
value: 23.211000000000002
|
| 989 |
+
- type: map_at_10
|
| 990 |
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value: 32.231
|
| 991 |
+
- type: map_at_100
|
| 992 |
+
value: 33.772999999999996
|
| 993 |
+
- type: map_at_1000
|
| 994 |
+
value: 33.982
|
| 995 |
+
- type: map_at_3
|
| 996 |
+
value: 29.128
|
| 997 |
+
- type: map_at_5
|
| 998 |
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value: 31.002999999999997
|
| 999 |
+
- type: mrr_at_1
|
| 1000 |
+
value: 27.668
|
| 1001 |
+
- type: mrr_at_10
|
| 1002 |
+
value: 36.388
|
| 1003 |
+
- type: mrr_at_100
|
| 1004 |
+
value: 37.384
|
| 1005 |
+
- type: mrr_at_1000
|
| 1006 |
+
value: 37.44
|
| 1007 |
+
- type: mrr_at_3
|
| 1008 |
+
value: 33.762
|
| 1009 |
+
- type: mrr_at_5
|
| 1010 |
+
value: 35.234
|
| 1011 |
+
- type: ndcg_at_1
|
| 1012 |
+
value: 27.668
|
| 1013 |
+
- type: ndcg_at_10
|
| 1014 |
+
value: 38.043
|
| 1015 |
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- type: ndcg_at_100
|
| 1016 |
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value: 44.21
|
| 1017 |
+
- type: ndcg_at_1000
|
| 1018 |
+
value: 46.748
|
| 1019 |
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- type: ndcg_at_3
|
| 1020 |
+
value: 32.981
|
| 1021 |
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- type: ndcg_at_5
|
| 1022 |
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value: 35.58
|
| 1023 |
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- type: precision_at_1
|
| 1024 |
+
value: 27.668
|
| 1025 |
+
- type: precision_at_10
|
| 1026 |
+
value: 7.352
|
| 1027 |
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- type: precision_at_100
|
| 1028 |
+
value: 1.5
|
| 1029 |
+
- type: precision_at_1000
|
| 1030 |
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value: 0.23700000000000002
|
| 1031 |
+
- type: precision_at_3
|
| 1032 |
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value: 15.613
|
| 1033 |
+
- type: precision_at_5
|
| 1034 |
+
value: 11.501999999999999
|
| 1035 |
+
- type: recall_at_1
|
| 1036 |
+
value: 23.211000000000002
|
| 1037 |
+
- type: recall_at_10
|
| 1038 |
+
value: 49.851
|
| 1039 |
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- type: recall_at_100
|
| 1040 |
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value: 77.596
|
| 1041 |
+
- type: recall_at_1000
|
| 1042 |
+
value: 93.683
|
| 1043 |
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- type: recall_at_3
|
| 1044 |
+
value: 35.403
|
| 1045 |
+
- type: recall_at_5
|
| 1046 |
+
value: 42.485
|
| 1047 |
+
- task:
|
| 1048 |
+
type: Retrieval
|
| 1049 |
+
dataset:
|
| 1050 |
+
type: mteb/cqadupstack-wordpress
|
| 1051 |
+
name: MTEB CQADupstackWordpressRetrieval
|
| 1052 |
+
config: default
|
| 1053 |
+
split: test
|
| 1054 |
+
revision: 4ffe81d471b1924886b33c7567bfb200e9eec5c4
|
| 1055 |
+
metrics:
|
| 1056 |
+
- type: map_at_1
|
| 1057 |
+
value: 19.384
|
| 1058 |
+
- type: map_at_10
|
| 1059 |
+
value: 26.262999999999998
|
| 1060 |
+
- type: map_at_100
|
| 1061 |
+
value: 27.409
|
| 1062 |
+
- type: map_at_1000
|
| 1063 |
+
value: 27.526
|
| 1064 |
+
- type: map_at_3
|
| 1065 |
+
value: 23.698
|
| 1066 |
+
- type: map_at_5
|
| 1067 |
+
value: 25.217
|
| 1068 |
+
- type: mrr_at_1
|
| 1069 |
+
value: 20.702
|
| 1070 |
+
- type: mrr_at_10
|
| 1071 |
+
value: 27.810000000000002
|
| 1072 |
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- type: mrr_at_100
|
| 1073 |
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value: 28.863
|
| 1074 |
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- type: mrr_at_1000
|
| 1075 |
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value: 28.955
|
| 1076 |
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- type: mrr_at_3
|
| 1077 |
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value: 25.230999999999998
|
| 1078 |
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- type: mrr_at_5
|
| 1079 |
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value: 26.821
|
| 1080 |
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- type: ndcg_at_1
|
| 1081 |
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value: 20.702
|
| 1082 |
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- type: ndcg_at_10
|
| 1083 |
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value: 30.688
|
| 1084 |
+
- type: ndcg_at_100
|
| 1085 |
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value: 36.138999999999996
|
| 1086 |
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- type: ndcg_at_1000
|
| 1087 |
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value: 38.984
|
| 1088 |
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- type: ndcg_at_3
|
| 1089 |
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value: 25.663000000000004
|
| 1090 |
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- type: ndcg_at_5
|
| 1091 |
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value: 28.242
|
| 1092 |
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- type: precision_at_1
|
| 1093 |
+
value: 20.702
|
| 1094 |
+
- type: precision_at_10
|
| 1095 |
+
value: 4.954
|
| 1096 |
+
- type: precision_at_100
|
| 1097 |
+
value: 0.823
|
| 1098 |
+
- type: precision_at_1000
|
| 1099 |
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value: 0.11800000000000001
|
| 1100 |
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- type: precision_at_3
|
| 1101 |
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value: 10.844
|
| 1102 |
+
- type: precision_at_5
|
| 1103 |
+
value: 8.096
|
| 1104 |
+
- type: recall_at_1
|
| 1105 |
+
value: 19.384
|
| 1106 |
+
- type: recall_at_10
|
| 1107 |
+
value: 42.847
|
| 1108 |
+
- type: recall_at_100
|
| 1109 |
+
value: 67.402
|
| 1110 |
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- type: recall_at_1000
|
| 1111 |
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value: 88.145
|
| 1112 |
+
- type: recall_at_3
|
| 1113 |
+
value: 29.513
|
| 1114 |
+
- type: recall_at_5
|
| 1115 |
+
value: 35.57
|
| 1116 |
+
- task:
|
| 1117 |
+
type: Retrieval
|
| 1118 |
+
dataset:
|
| 1119 |
+
type: mteb/climate-fever
|
| 1120 |
+
name: MTEB ClimateFEVER
|
| 1121 |
+
config: default
|
| 1122 |
+
split: test
|
| 1123 |
+
revision: 47f2ac6acb640fc46020b02a5b59fdda04d39380
|
| 1124 |
+
metrics:
|
| 1125 |
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- type: map_at_1
|
| 1126 |
+
value: 14.915000000000001
|
| 1127 |
+
- type: map_at_10
|
| 1128 |
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value: 25.846999999999998
|
| 1129 |
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- type: map_at_100
|
| 1130 |
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value: 27.741
|
| 1131 |
+
- type: map_at_1000
|
| 1132 |
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value: 27.921000000000003
|
| 1133 |
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- type: map_at_3
|
| 1134 |
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value: 21.718
|
| 1135 |
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- type: map_at_5
|
| 1136 |
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value: 23.948
|
| 1137 |
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- type: mrr_at_1
|
| 1138 |
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value: 33.941
|
| 1139 |
+
- type: mrr_at_10
|
| 1140 |
+
value: 46.897
|
| 1141 |
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- type: mrr_at_100
|
| 1142 |
+
value: 47.63
|
| 1143 |
+
- type: mrr_at_1000
|
| 1144 |
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value: 47.658
|
| 1145 |
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- type: mrr_at_3
|
| 1146 |
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value: 43.919999999999995
|
| 1147 |
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- type: mrr_at_5
|
| 1148 |
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value: 45.783
|
| 1149 |
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- type: ndcg_at_1
|
| 1150 |
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value: 33.941
|
| 1151 |
+
- type: ndcg_at_10
|
| 1152 |
+
value: 35.202
|
| 1153 |
+
- type: ndcg_at_100
|
| 1154 |
+
value: 42.132
|
| 1155 |
+
- type: ndcg_at_1000
|
| 1156 |
+
value: 45.190999999999995
|
| 1157 |
+
- type: ndcg_at_3
|
| 1158 |
+
value: 29.68
|
| 1159 |
+
- type: ndcg_at_5
|
| 1160 |
+
value: 31.631999999999998
|
| 1161 |
+
- type: precision_at_1
|
| 1162 |
+
value: 33.941
|
| 1163 |
+
- type: precision_at_10
|
| 1164 |
+
value: 10.906
|
| 1165 |
+
- type: precision_at_100
|
| 1166 |
+
value: 1.8339999999999999
|
| 1167 |
+
- type: precision_at_1000
|
| 1168 |
+
value: 0.241
|
| 1169 |
+
- type: precision_at_3
|
| 1170 |
+
value: 22.606
|
| 1171 |
+
- type: precision_at_5
|
| 1172 |
+
value: 17.081
|
| 1173 |
+
- type: recall_at_1
|
| 1174 |
+
value: 14.915000000000001
|
| 1175 |
+
- type: recall_at_10
|
| 1176 |
+
value: 40.737
|
| 1177 |
+
- type: recall_at_100
|
| 1178 |
+
value: 64.42
|
| 1179 |
+
- type: recall_at_1000
|
| 1180 |
+
value: 81.435
|
| 1181 |
+
- type: recall_at_3
|
| 1182 |
+
value: 26.767000000000003
|
| 1183 |
+
- type: recall_at_5
|
| 1184 |
+
value: 32.895
|
| 1185 |
+
- task:
|
| 1186 |
+
type: Retrieval
|
| 1187 |
+
dataset:
|
| 1188 |
+
type: mteb/dbpedia
|
| 1189 |
+
name: MTEB DBPedia
|
| 1190 |
+
config: default
|
| 1191 |
+
split: test
|
| 1192 |
+
revision: c0f706b76e590d620bd6618b3ca8efdd34e2d659
|
| 1193 |
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metrics:
|
| 1194 |
+
- type: map_at_1
|
| 1195 |
+
value: 8.665000000000001
|
| 1196 |
+
- type: map_at_10
|
| 1197 |
+
value: 19.087
|
| 1198 |
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- type: map_at_100
|
| 1199 |
+
value: 26.555
|
| 1200 |
+
- type: map_at_1000
|
| 1201 |
+
value: 28.105999999999998
|
| 1202 |
+
- type: map_at_3
|
| 1203 |
+
value: 13.858999999999998
|
| 1204 |
+
- type: map_at_5
|
| 1205 |
+
value: 16.083
|
| 1206 |
+
- type: mrr_at_1
|
| 1207 |
+
value: 68.5
|
| 1208 |
+
- type: mrr_at_10
|
| 1209 |
+
value: 76.725
|
| 1210 |
+
- type: mrr_at_100
|
| 1211 |
+
value: 76.974
|
| 1212 |
+
- type: mrr_at_1000
|
| 1213 |
+
value: 76.981
|
| 1214 |
+
- type: mrr_at_3
|
| 1215 |
+
value: 75.583
|
| 1216 |
+
- type: mrr_at_5
|
| 1217 |
+
value: 76.208
|
| 1218 |
+
- type: ndcg_at_1
|
| 1219 |
+
value: 55.875
|
| 1220 |
+
- type: ndcg_at_10
|
| 1221 |
+
value: 41.018
|
| 1222 |
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- type: ndcg_at_100
|
| 1223 |
+
value: 44.982
|
| 1224 |
+
- type: ndcg_at_1000
|
| 1225 |
+
value: 52.43
|
| 1226 |
+
- type: ndcg_at_3
|
| 1227 |
+
value: 46.534
|
| 1228 |
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- type: ndcg_at_5
|
| 1229 |
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value: 43.083
|
| 1230 |
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- type: precision_at_1
|
| 1231 |
+
value: 68.5
|
| 1232 |
+
- type: precision_at_10
|
| 1233 |
+
value: 32.35
|
| 1234 |
+
- type: precision_at_100
|
| 1235 |
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value: 10.078
|
| 1236 |
+
- type: precision_at_1000
|
| 1237 |
+
value: 1.957
|
| 1238 |
+
- type: precision_at_3
|
| 1239 |
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value: 50.083
|
| 1240 |
+
- type: precision_at_5
|
| 1241 |
+
value: 41.3
|
| 1242 |
+
- type: recall_at_1
|
| 1243 |
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value: 8.665000000000001
|
| 1244 |
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- type: recall_at_10
|
| 1245 |
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value: 24.596999999999998
|
| 1246 |
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- type: recall_at_100
|
| 1247 |
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value: 50.612
|
| 1248 |
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- type: recall_at_1000
|
| 1249 |
+
value: 74.24
|
| 1250 |
+
- type: recall_at_3
|
| 1251 |
+
value: 15.337
|
| 1252 |
+
- type: recall_at_5
|
| 1253 |
+
value: 18.796
|
| 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 |
+
value: 55.06500000000001
|
| 1265 |
+
- type: f1
|
| 1266 |
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value: 49.827367590822035
|
| 1267 |
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- task:
|
| 1268 |
+
type: Retrieval
|
| 1269 |
+
dataset:
|
| 1270 |
+
type: mteb/fever
|
| 1271 |
+
name: MTEB FEVER
|
| 1272 |
+
config: default
|
| 1273 |
+
split: test
|
| 1274 |
+
revision: bea83ef9e8fb933d90a2f1d5515737465d613e12
|
| 1275 |
+
metrics:
|
| 1276 |
+
- type: map_at_1
|
| 1277 |
+
value: 76.059
|
| 1278 |
+
- type: map_at_10
|
| 1279 |
+
value: 83.625
|
| 1280 |
+
- type: map_at_100
|
| 1281 |
+
value: 83.845
|
| 1282 |
+
- type: map_at_1000
|
| 1283 |
+
value: 83.858
|
| 1284 |
+
- type: map_at_3
|
| 1285 |
+
value: 82.67099999999999
|
| 1286 |
+
- type: map_at_5
|
| 1287 |
+
value: 83.223
|
| 1288 |
+
- type: mrr_at_1
|
| 1289 |
+
value: 82.013
|
| 1290 |
+
- type: mrr_at_10
|
| 1291 |
+
value: 88.44800000000001
|
| 1292 |
+
- type: mrr_at_100
|
| 1293 |
+
value: 88.535
|
| 1294 |
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- type: mrr_at_1000
|
| 1295 |
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value: 88.537
|
| 1296 |
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- type: mrr_at_3
|
| 1297 |
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value: 87.854
|
| 1298 |
+
- type: mrr_at_5
|
| 1299 |
+
value: 88.221
|
| 1300 |
+
- type: ndcg_at_1
|
| 1301 |
+
value: 82.013
|
| 1302 |
+
- type: ndcg_at_10
|
| 1303 |
+
value: 87.128
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| 1304 |
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- type: ndcg_at_100
|
| 1305 |
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value: 87.922
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| 1306 |
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- type: ndcg_at_1000
|
| 1307 |
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value: 88.166
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| 1308 |
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- type: ndcg_at_3
|
| 1309 |
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value: 85.648
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| 1310 |
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- type: ndcg_at_5
|
| 1311 |
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value: 86.366
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| 1312 |
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- type: precision_at_1
|
| 1313 |
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value: 82.013
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| 1314 |
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- type: precision_at_10
|
| 1315 |
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value: 10.32
|
| 1316 |
+
- type: precision_at_100
|
| 1317 |
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value: 1.093
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| 1318 |
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- type: precision_at_1000
|
| 1319 |
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value: 0.11299999999999999
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| 1320 |
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- type: precision_at_3
|
| 1321 |
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value: 32.408
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| 1322 |
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- type: precision_at_5
|
| 1323 |
+
value: 19.973
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| 1324 |
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- type: recall_at_1
|
| 1325 |
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value: 76.059
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| 1326 |
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- type: recall_at_10
|
| 1327 |
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value: 93.229
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| 1328 |
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- type: recall_at_100
|
| 1329 |
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value: 96.387
|
| 1330 |
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- type: recall_at_1000
|
| 1331 |
+
value: 97.916
|
| 1332 |
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- type: recall_at_3
|
| 1333 |
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value: 89.025
|
| 1334 |
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- type: recall_at_5
|
| 1335 |
+
value: 90.96300000000001
|
| 1336 |
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- task:
|
| 1337 |
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type: Retrieval
|
| 1338 |
+
dataset:
|
| 1339 |
+
type: mteb/fiqa
|
| 1340 |
+
name: MTEB FiQA2018
|
| 1341 |
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config: default
|
| 1342 |
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split: test
|
| 1343 |
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revision: 27a168819829fe9bcd655c2df245fb19452e8e06
|
| 1344 |
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metrics:
|
| 1345 |
+
- type: map_at_1
|
| 1346 |
+
value: 20.479
|
| 1347 |
+
- type: map_at_10
|
| 1348 |
+
value: 33.109
|
| 1349 |
+
- type: map_at_100
|
| 1350 |
+
value: 34.803
|
| 1351 |
+
- type: map_at_1000
|
| 1352 |
+
value: 35.003
|
| 1353 |
+
- type: map_at_3
|
| 1354 |
+
value: 28.967
|
| 1355 |
+
- type: map_at_5
|
| 1356 |
+
value: 31.385
|
| 1357 |
+
- type: mrr_at_1
|
| 1358 |
+
value: 40.278000000000006
|
| 1359 |
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- type: mrr_at_10
|
| 1360 |
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value: 48.929
|
| 1361 |
+
- type: mrr_at_100
|
| 1362 |
+
value: 49.655
|
| 1363 |
+
- type: mrr_at_1000
|
| 1364 |
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value: 49.691
|
| 1365 |
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- type: mrr_at_3
|
| 1366 |
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value: 46.605000000000004
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| 1367 |
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- type: mrr_at_5
|
| 1368 |
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value: 48.056
|
| 1369 |
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- type: ndcg_at_1
|
| 1370 |
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value: 40.278000000000006
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| 1371 |
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- type: ndcg_at_10
|
| 1372 |
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value: 40.649
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| 1373 |
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- type: ndcg_at_100
|
| 1374 |
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value: 47.027
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| 1375 |
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- type: ndcg_at_1000
|
| 1376 |
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value: 50.249
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| 1377 |
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- type: ndcg_at_3
|
| 1378 |
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value: 37.364000000000004
|
| 1379 |
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- type: ndcg_at_5
|
| 1380 |
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value: 38.494
|
| 1381 |
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- type: precision_at_1
|
| 1382 |
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value: 40.278000000000006
|
| 1383 |
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- type: precision_at_10
|
| 1384 |
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value: 11.327
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| 1385 |
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- type: precision_at_100
|
| 1386 |
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value: 1.802
|
| 1387 |
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- type: precision_at_1000
|
| 1388 |
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value: 0.23700000000000002
|
| 1389 |
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- type: precision_at_3
|
| 1390 |
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value: 25.102999999999998
|
| 1391 |
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- type: precision_at_5
|
| 1392 |
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value: 18.457
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| 1393 |
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- type: recall_at_1
|
| 1394 |
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value: 20.479
|
| 1395 |
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- type: recall_at_10
|
| 1396 |
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value: 46.594
|
| 1397 |
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- type: recall_at_100
|
| 1398 |
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value: 71.101
|
| 1399 |
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- type: recall_at_1000
|
| 1400 |
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value: 90.31099999999999
|
| 1401 |
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- type: recall_at_3
|
| 1402 |
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value: 33.378
|
| 1403 |
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- type: recall_at_5
|
| 1404 |
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value: 39.587
|
| 1405 |
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- task:
|
| 1406 |
+
type: Retrieval
|
| 1407 |
+
dataset:
|
| 1408 |
+
type: mteb/hotpotqa
|
| 1409 |
+
name: MTEB HotpotQA
|
| 1410 |
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config: default
|
| 1411 |
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split: test
|
| 1412 |
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revision: ab518f4d6fcca38d87c25209f94beba119d02014
|
| 1413 |
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metrics:
|
| 1414 |
+
- type: map_at_1
|
| 1415 |
+
value: 36.59
|
| 1416 |
+
- type: map_at_10
|
| 1417 |
+
value: 58.178
|
| 1418 |
+
- type: map_at_100
|
| 1419 |
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value: 59.095
|
| 1420 |
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- type: map_at_1000
|
| 1421 |
+
value: 59.16400000000001
|
| 1422 |
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- type: map_at_3
|
| 1423 |
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value: 54.907
|
| 1424 |
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- type: map_at_5
|
| 1425 |
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value: 56.89999999999999
|
| 1426 |
+
- type: mrr_at_1
|
| 1427 |
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value: 73.18
|
| 1428 |
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- type: mrr_at_10
|
| 1429 |
+
value: 79.935
|
| 1430 |
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- type: mrr_at_100
|
| 1431 |
+
value: 80.16799999999999
|
| 1432 |
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- type: mrr_at_1000
|
| 1433 |
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value: 80.17800000000001
|
| 1434 |
+
- type: mrr_at_3
|
| 1435 |
+
value: 78.776
|
| 1436 |
+
- type: mrr_at_5
|
| 1437 |
+
value: 79.522
|
| 1438 |
+
- type: ndcg_at_1
|
| 1439 |
+
value: 73.18
|
| 1440 |
+
- type: ndcg_at_10
|
| 1441 |
+
value: 66.538
|
| 1442 |
+
- type: ndcg_at_100
|
| 1443 |
+
value: 69.78
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| 1444 |
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- type: ndcg_at_1000
|
| 1445 |
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value: 71.102
|
| 1446 |
+
- type: ndcg_at_3
|
| 1447 |
+
value: 61.739
|
| 1448 |
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- type: ndcg_at_5
|
| 1449 |
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value: 64.35600000000001
|
| 1450 |
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- type: precision_at_1
|
| 1451 |
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value: 73.18
|
| 1452 |
+
- type: precision_at_10
|
| 1453 |
+
value: 14.035
|
| 1454 |
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- type: precision_at_100
|
| 1455 |
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value: 1.657
|
| 1456 |
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- type: precision_at_1000
|
| 1457 |
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value: 0.183
|
| 1458 |
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- type: precision_at_3
|
| 1459 |
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value: 39.684999999999995
|
| 1460 |
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- type: precision_at_5
|
| 1461 |
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value: 25.885
|
| 1462 |
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- type: recall_at_1
|
| 1463 |
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value: 36.59
|
| 1464 |
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- type: recall_at_10
|
| 1465 |
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value: 70.176
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| 1466 |
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- type: recall_at_100
|
| 1467 |
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value: 82.836
|
| 1468 |
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- type: recall_at_1000
|
| 1469 |
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value: 91.526
|
| 1470 |
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- type: recall_at_3
|
| 1471 |
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value: 59.526999999999994
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| 1472 |
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- type: recall_at_5
|
| 1473 |
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value: 64.713
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| 1474 |
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- task:
|
| 1475 |
+
type: Classification
|
| 1476 |
+
dataset:
|
| 1477 |
+
type: mteb/imdb
|
| 1478 |
+
name: MTEB ImdbClassification
|
| 1479 |
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config: default
|
| 1480 |
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split: test
|
| 1481 |
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revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
|
| 1482 |
+
metrics:
|
| 1483 |
+
- type: accuracy
|
| 1484 |
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value: 90.1472
|
| 1485 |
+
- type: ap
|
| 1486 |
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value: 85.73994227076815
|
| 1487 |
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- type: f1
|
| 1488 |
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value: 90.1271700788608
|
| 1489 |
+
- task:
|
| 1490 |
+
type: Retrieval
|
| 1491 |
+
dataset:
|
| 1492 |
+
type: mteb/msmarco
|
| 1493 |
+
name: MTEB MSMARCO
|
| 1494 |
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config: default
|
| 1495 |
+
split: dev
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| 1496 |
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revision: c5a29a104738b98a9e76336939199e264163d4a0
|
| 1497 |
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metrics:
|
| 1498 |
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- type: map_at_1
|
| 1499 |
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value: 21.689
|
| 1500 |
+
- type: map_at_10
|
| 1501 |
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value: 33.518
|
| 1502 |
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- type: map_at_100
|
| 1503 |
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value: 34.715
|
| 1504 |
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- type: map_at_1000
|
| 1505 |
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value: 34.766000000000005
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| 1506 |
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- type: map_at_3
|
| 1507 |
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value: 29.781000000000002
|
| 1508 |
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- type: map_at_5
|
| 1509 |
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value: 31.838
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| 1510 |
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- type: mrr_at_1
|
| 1511 |
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value: 22.249
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| 1512 |
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- type: mrr_at_10
|
| 1513 |
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value: 34.085
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| 1514 |
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- type: mrr_at_100
|
| 1515 |
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value: 35.223
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| 1516 |
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- type: mrr_at_1000
|
| 1517 |
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value: 35.266999999999996
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| 1518 |
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- type: mrr_at_3
|
| 1519 |
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value: 30.398999999999997
|
| 1520 |
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- type: mrr_at_5
|
| 1521 |
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value: 32.437
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| 1522 |
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- type: ndcg_at_1
|
| 1523 |
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value: 22.249
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| 1524 |
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- type: ndcg_at_10
|
| 1525 |
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value: 40.227000000000004
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| 1526 |
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| 1527 |
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value: 45.961999999999996
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| 1528 |
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|
| 1529 |
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value: 47.248000000000005
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| 1530 |
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- type: ndcg_at_3
|
| 1531 |
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value: 32.566
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| 1532 |
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- type: ndcg_at_5
|
| 1533 |
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value: 36.229
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| 1534 |
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- type: precision_at_1
|
| 1535 |
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value: 22.249
|
| 1536 |
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- type: precision_at_10
|
| 1537 |
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value: 6.358
|
| 1538 |
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- type: precision_at_100
|
| 1539 |
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value: 0.923
|
| 1540 |
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- type: precision_at_1000
|
| 1541 |
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value: 0.10300000000000001
|
| 1542 |
+
- type: precision_at_3
|
| 1543 |
+
value: 13.83
|
| 1544 |
+
- type: precision_at_5
|
| 1545 |
+
value: 10.145999999999999
|
| 1546 |
+
- type: recall_at_1
|
| 1547 |
+
value: 21.689
|
| 1548 |
+
- type: recall_at_10
|
| 1549 |
+
value: 60.92999999999999
|
| 1550 |
+
- type: recall_at_100
|
| 1551 |
+
value: 87.40599999999999
|
| 1552 |
+
- type: recall_at_1000
|
| 1553 |
+
value: 97.283
|
| 1554 |
+
- type: recall_at_3
|
| 1555 |
+
value: 40.01
|
| 1556 |
+
- type: recall_at_5
|
| 1557 |
+
value: 48.776
|
| 1558 |
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- task:
|
| 1559 |
+
type: Classification
|
| 1560 |
+
dataset:
|
| 1561 |
+
type: mteb/mtop_domain
|
| 1562 |
+
name: MTEB MTOPDomainClassification (en)
|
| 1563 |
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config: en
|
| 1564 |
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split: test
|
| 1565 |
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revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
|
| 1566 |
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metrics:
|
| 1567 |
+
- type: accuracy
|
| 1568 |
+
value: 95.28727770177838
|
| 1569 |
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- type: f1
|
| 1570 |
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value: 95.02577308660041
|
| 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 |
+
name: MTEB MTOPIntentClassification (en)
|
| 1576 |
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config: en
|
| 1577 |
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split: test
|
| 1578 |
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revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
|
| 1579 |
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metrics:
|
| 1580 |
+
- type: accuracy
|
| 1581 |
+
value: 79.5736434108527
|
| 1582 |
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- type: f1
|
| 1583 |
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value: 61.2451202054398
|
| 1584 |
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- task:
|
| 1585 |
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type: Classification
|
| 1586 |
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dataset:
|
| 1587 |
+
type: mteb/amazon_massive_intent
|
| 1588 |
+
name: MTEB MassiveIntentClassification (en)
|
| 1589 |
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config: en
|
| 1590 |
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split: test
|
| 1591 |
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revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
|
| 1592 |
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metrics:
|
| 1593 |
+
- type: accuracy
|
| 1594 |
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value: 76.01210490921318
|
| 1595 |
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- type: f1
|
| 1596 |
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value: 73.70188053982473
|
| 1597 |
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- task:
|
| 1598 |
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type: Classification
|
| 1599 |
+
dataset:
|
| 1600 |
+
type: mteb/amazon_massive_scenario
|
| 1601 |
+
name: MTEB MassiveScenarioClassification (en)
|
| 1602 |
+
config: en
|
| 1603 |
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split: test
|
| 1604 |
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revision: 7d571f92784cd94a019292a1f45445077d0ef634
|
| 1605 |
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metrics:
|
| 1606 |
+
- type: accuracy
|
| 1607 |
+
value: 79.33422999327504
|
| 1608 |
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- type: f1
|
| 1609 |
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value: 79.48369022509658
|
| 1610 |
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- task:
|
| 1611 |
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type: Clustering
|
| 1612 |
+
dataset:
|
| 1613 |
+
type: mteb/medrxiv-clustering-p2p
|
| 1614 |
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name: MTEB MedrxivClusteringP2P
|
| 1615 |
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config: default
|
| 1616 |
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split: test
|
| 1617 |
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revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
|
| 1618 |
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metrics:
|
| 1619 |
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- type: v_measure
|
| 1620 |
+
value: 34.70891567267726
|
| 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
|
| 1626 |
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config: default
|
| 1627 |
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split: test
|
| 1628 |
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revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
|
| 1629 |
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metrics:
|
| 1630 |
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- type: v_measure
|
| 1631 |
+
value: 32.15203494451706
|
| 1632 |
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- task:
|
| 1633 |
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type: Reranking
|
| 1634 |
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dataset:
|
| 1635 |
+
type: mteb/mind_small
|
| 1636 |
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name: MTEB MindSmallReranking
|
| 1637 |
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config: default
|
| 1638 |
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split: test
|
| 1639 |
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revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
|
| 1640 |
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metrics:
|
| 1641 |
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- type: map
|
| 1642 |
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value: 31.919517862194173
|
| 1643 |
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- type: mrr
|
| 1644 |
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value: 33.15466289140483
|
| 1645 |
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- task:
|
| 1646 |
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type: Retrieval
|
| 1647 |
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dataset:
|
| 1648 |
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type: mteb/nfcorpus
|
| 1649 |
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name: MTEB NFCorpus
|
| 1650 |
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config: default
|
| 1651 |
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split: test
|
| 1652 |
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revision: ec0fa4fe99da2ff19ca1214b7966684033a58814
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| 1653 |
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metrics:
|
| 1654 |
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- type: map_at_1
|
| 1655 |
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value: 5.992
|
| 1656 |
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- type: map_at_10
|
| 1657 |
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value: 13.197000000000001
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| 1658 |
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- type: map_at_100
|
| 1659 |
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value: 16.907
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| 1660 |
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- type: map_at_1000
|
| 1661 |
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value: 18.44
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| 1662 |
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- type: map_at_3
|
| 1663 |
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value: 9.631
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| 1664 |
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- type: map_at_5
|
| 1665 |
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value: 11.243
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| 1666 |
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- type: mrr_at_1
|
| 1667 |
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value: 44.272
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| 1668 |
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- type: mrr_at_10
|
| 1669 |
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value: 53.321
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| 1670 |
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- type: mrr_at_100
|
| 1671 |
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value: 53.903
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| 1672 |
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- type: mrr_at_1000
|
| 1673 |
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value: 53.952999999999996
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| 1674 |
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- type: mrr_at_3
|
| 1675 |
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value: 51.393
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| 1676 |
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- type: mrr_at_5
|
| 1677 |
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value: 52.708999999999996
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| 1678 |
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- type: ndcg_at_1
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| 1679 |
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value: 42.415000000000006
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| 1680 |
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- type: ndcg_at_10
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| 1681 |
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value: 34.921
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| 1682 |
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- type: ndcg_at_100
|
| 1683 |
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value: 32.384
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| 1684 |
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- type: ndcg_at_1000
|
| 1685 |
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value: 41.260000000000005
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| 1686 |
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- type: ndcg_at_3
|
| 1687 |
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value: 40.186
|
| 1688 |
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- type: ndcg_at_5
|
| 1689 |
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value: 37.89
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| 1690 |
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- type: precision_at_1
|
| 1691 |
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value: 44.272
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| 1692 |
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- type: precision_at_10
|
| 1693 |
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value: 26.006
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| 1694 |
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- type: precision_at_100
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| 1695 |
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value: 8.44
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| 1696 |
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- type: precision_at_1000
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| 1697 |
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value: 2.136
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| 1698 |
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- type: precision_at_3
|
| 1699 |
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value: 37.977
|
| 1700 |
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- type: precision_at_5
|
| 1701 |
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value: 32.755
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| 1702 |
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- type: recall_at_1
|
| 1703 |
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value: 5.992
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| 1704 |
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- type: recall_at_10
|
| 1705 |
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value: 17.01
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| 1706 |
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- type: recall_at_100
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| 1707 |
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value: 33.080999999999996
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| 1708 |
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- type: recall_at_1000
|
| 1709 |
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value: 65.054
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| 1710 |
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- type: recall_at_3
|
| 1711 |
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value: 10.528
|
| 1712 |
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- type: recall_at_5
|
| 1713 |
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value: 13.233
|
| 1714 |
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- task:
|
| 1715 |
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type: Retrieval
|
| 1716 |
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dataset:
|
| 1717 |
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type: mteb/nq
|
| 1718 |
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name: MTEB NQ
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| 1719 |
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config: default
|
| 1720 |
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split: test
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| 1721 |
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revision: b774495ed302d8c44a3a7ea25c90dbce03968f31
|
| 1722 |
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metrics:
|
| 1723 |
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- type: map_at_1
|
| 1724 |
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value: 28.871999999999996
|
| 1725 |
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- type: map_at_10
|
| 1726 |
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value: 43.286
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| 1727 |
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|
| 1728 |
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value: 44.432
|
| 1729 |
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- type: map_at_1000
|
| 1730 |
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value: 44.464999999999996
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| 1731 |
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|
| 1732 |
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value: 38.856
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| 1733 |
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|
| 1734 |
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value: 41.514
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| 1735 |
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|
| 1736 |
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value: 32.619
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| 1737 |
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|
| 1738 |
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value: 45.75
|
| 1739 |
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- type: mrr_at_100
|
| 1740 |
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value: 46.622
|
| 1741 |
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- type: mrr_at_1000
|
| 1742 |
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value: 46.646
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| 1743 |
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- type: mrr_at_3
|
| 1744 |
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value: 41.985
|
| 1745 |
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- type: mrr_at_5
|
| 1746 |
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value: 44.277
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| 1747 |
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- type: ndcg_at_1
|
| 1748 |
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value: 32.59
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| 1749 |
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|
| 1750 |
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value: 50.895999999999994
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| 1751 |
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- type: ndcg_at_100
|
| 1752 |
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value: 55.711999999999996
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| 1753 |
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- type: ndcg_at_1000
|
| 1754 |
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value: 56.48800000000001
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| 1755 |
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- type: ndcg_at_3
|
| 1756 |
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value: 42.504999999999995
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| 1757 |
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- type: ndcg_at_5
|
| 1758 |
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value: 46.969
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| 1759 |
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- type: precision_at_1
|
| 1760 |
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value: 32.59
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| 1761 |
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- type: precision_at_10
|
| 1762 |
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value: 8.543000000000001
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| 1763 |
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- type: precision_at_100
|
| 1764 |
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value: 1.123
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| 1765 |
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- type: precision_at_1000
|
| 1766 |
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value: 0.12
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| 1767 |
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- type: precision_at_3
|
| 1768 |
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value: 19.448
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| 1769 |
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- type: precision_at_5
|
| 1770 |
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value: 14.218
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| 1771 |
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- type: recall_at_1
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| 1772 |
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value: 28.871999999999996
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| 1773 |
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- type: recall_at_10
|
| 1774 |
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value: 71.748
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| 1775 |
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- type: recall_at_100
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| 1776 |
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value: 92.55499999999999
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| 1777 |
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- type: recall_at_1000
|
| 1778 |
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value: 98.327
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| 1779 |
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- type: recall_at_3
|
| 1780 |
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value: 49.944
|
| 1781 |
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- type: recall_at_5
|
| 1782 |
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value: 60.291
|
| 1783 |
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- task:
|
| 1784 |
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type: Retrieval
|
| 1785 |
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dataset:
|
| 1786 |
+
type: mteb/quora
|
| 1787 |
+
name: MTEB QuoraRetrieval
|
| 1788 |
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config: default
|
| 1789 |
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split: test
|
| 1790 |
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revision: e4e08e0b7dbe3c8700f0daef558ff32256715259
|
| 1791 |
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metrics:
|
| 1792 |
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- type: map_at_1
|
| 1793 |
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value: 70.664
|
| 1794 |
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- type: map_at_10
|
| 1795 |
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value: 84.681
|
| 1796 |
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- type: map_at_100
|
| 1797 |
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value: 85.289
|
| 1798 |
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- type: map_at_1000
|
| 1799 |
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value: 85.306
|
| 1800 |
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- type: map_at_3
|
| 1801 |
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value: 81.719
|
| 1802 |
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- type: map_at_5
|
| 1803 |
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value: 83.601
|
| 1804 |
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- type: mrr_at_1
|
| 1805 |
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value: 81.35
|
| 1806 |
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- type: mrr_at_10
|
| 1807 |
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value: 87.591
|
| 1808 |
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- type: mrr_at_100
|
| 1809 |
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value: 87.691
|
| 1810 |
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- type: mrr_at_1000
|
| 1811 |
+
value: 87.693
|
| 1812 |
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- type: mrr_at_3
|
| 1813 |
+
value: 86.675
|
| 1814 |
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- type: mrr_at_5
|
| 1815 |
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value: 87.29299999999999
|
| 1816 |
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- type: ndcg_at_1
|
| 1817 |
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value: 81.33
|
| 1818 |
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- type: ndcg_at_10
|
| 1819 |
+
value: 88.411
|
| 1820 |
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- type: ndcg_at_100
|
| 1821 |
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value: 89.579
|
| 1822 |
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- type: ndcg_at_1000
|
| 1823 |
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value: 89.687
|
| 1824 |
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- type: ndcg_at_3
|
| 1825 |
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value: 85.613
|
| 1826 |
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- type: ndcg_at_5
|
| 1827 |
+
value: 87.17
|
| 1828 |
+
- type: precision_at_1
|
| 1829 |
+
value: 81.33
|
| 1830 |
+
- type: precision_at_10
|
| 1831 |
+
value: 13.422
|
| 1832 |
+
- type: precision_at_100
|
| 1833 |
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value: 1.5270000000000001
|
| 1834 |
+
- type: precision_at_1000
|
| 1835 |
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value: 0.157
|
| 1836 |
+
- type: precision_at_3
|
| 1837 |
+
value: 37.463
|
| 1838 |
+
- type: precision_at_5
|
| 1839 |
+
value: 24.646
|
| 1840 |
+
- type: recall_at_1
|
| 1841 |
+
value: 70.664
|
| 1842 |
+
- type: recall_at_10
|
| 1843 |
+
value: 95.54
|
| 1844 |
+
- type: recall_at_100
|
| 1845 |
+
value: 99.496
|
| 1846 |
+
- type: recall_at_1000
|
| 1847 |
+
value: 99.978
|
| 1848 |
+
- type: recall_at_3
|
| 1849 |
+
value: 87.481
|
| 1850 |
+
- type: recall_at_5
|
| 1851 |
+
value: 91.88499999999999
|
| 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 |
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metrics:
|
| 1861 |
+
- type: v_measure
|
| 1862 |
+
value: 55.40341814991112
|
| 1863 |
+
- task:
|
| 1864 |
+
type: Clustering
|
| 1865 |
+
dataset:
|
| 1866 |
+
type: mteb/reddit-clustering-p2p
|
| 1867 |
+
name: MTEB RedditClusteringP2P
|
| 1868 |
+
config: default
|
| 1869 |
+
split: test
|
| 1870 |
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revision: 385e3cb46b4cfa89021f56c4380204149d0efe33
|
| 1871 |
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metrics:
|
| 1872 |
+
- type: v_measure
|
| 1873 |
+
value: 61.231318481346655
|
| 1874 |
+
- task:
|
| 1875 |
+
type: Retrieval
|
| 1876 |
+
dataset:
|
| 1877 |
+
type: mteb/scidocs
|
| 1878 |
+
name: MTEB SCIDOCS
|
| 1879 |
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config: default
|
| 1880 |
+
split: test
|
| 1881 |
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revision: f8c2fcf00f625baaa80f62ec5bd9e1fff3b8ae88
|
| 1882 |
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metrics:
|
| 1883 |
+
- type: map_at_1
|
| 1884 |
+
value: 4.833
|
| 1885 |
+
- type: map_at_10
|
| 1886 |
+
value: 13.149
|
| 1887 |
+
- type: map_at_100
|
| 1888 |
+
value: 15.578
|
| 1889 |
+
- type: map_at_1000
|
| 1890 |
+
value: 15.963
|
| 1891 |
+
- type: map_at_3
|
| 1892 |
+
value: 9.269
|
| 1893 |
+
- type: map_at_5
|
| 1894 |
+
value: 11.182
|
| 1895 |
+
- type: mrr_at_1
|
| 1896 |
+
value: 23.9
|
| 1897 |
+
- type: mrr_at_10
|
| 1898 |
+
value: 35.978
|
| 1899 |
+
- type: mrr_at_100
|
| 1900 |
+
value: 37.076
|
| 1901 |
+
- type: mrr_at_1000
|
| 1902 |
+
value: 37.126
|
| 1903 |
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- type: mrr_at_3
|
| 1904 |
+
value: 32.333
|
| 1905 |
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- type: mrr_at_5
|
| 1906 |
+
value: 34.413
|
| 1907 |
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- type: ndcg_at_1
|
| 1908 |
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value: 23.9
|
| 1909 |
+
- type: ndcg_at_10
|
| 1910 |
+
value: 21.823
|
| 1911 |
+
- type: ndcg_at_100
|
| 1912 |
+
value: 30.833
|
| 1913 |
+
- type: ndcg_at_1000
|
| 1914 |
+
value: 36.991
|
| 1915 |
+
- type: ndcg_at_3
|
| 1916 |
+
value: 20.465
|
| 1917 |
+
- type: ndcg_at_5
|
| 1918 |
+
value: 17.965999999999998
|
| 1919 |
+
- type: precision_at_1
|
| 1920 |
+
value: 23.9
|
| 1921 |
+
- type: precision_at_10
|
| 1922 |
+
value: 11.49
|
| 1923 |
+
- type: precision_at_100
|
| 1924 |
+
value: 2.444
|
| 1925 |
+
- type: precision_at_1000
|
| 1926 |
+
value: 0.392
|
| 1927 |
+
- type: precision_at_3
|
| 1928 |
+
value: 19.3
|
| 1929 |
+
- type: precision_at_5
|
| 1930 |
+
value: 15.959999999999999
|
| 1931 |
+
- type: recall_at_1
|
| 1932 |
+
value: 4.833
|
| 1933 |
+
- type: recall_at_10
|
| 1934 |
+
value: 23.294999999999998
|
| 1935 |
+
- type: recall_at_100
|
| 1936 |
+
value: 49.63
|
| 1937 |
+
- type: recall_at_1000
|
| 1938 |
+
value: 79.49199999999999
|
| 1939 |
+
- type: recall_at_3
|
| 1940 |
+
value: 11.732
|
| 1941 |
+
- type: recall_at_5
|
| 1942 |
+
value: 16.167
|
| 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: 20a6d6f312dd54037fe07a32d58e5e168867909d
|
| 1951 |
+
metrics:
|
| 1952 |
+
- type: cos_sim_pearson
|
| 1953 |
+
value: 85.62938108735759
|
| 1954 |
+
- type: cos_sim_spearman
|
| 1955 |
+
value: 80.30777094408789
|
| 1956 |
+
- type: euclidean_pearson
|
| 1957 |
+
value: 82.94516686659536
|
| 1958 |
+
- type: euclidean_spearman
|
| 1959 |
+
value: 80.34489663248169
|
| 1960 |
+
- type: manhattan_pearson
|
| 1961 |
+
value: 82.85830094736245
|
| 1962 |
+
- type: manhattan_spearman
|
| 1963 |
+
value: 80.24902623215449
|
| 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: 85.23777464247604
|
| 1975 |
+
- type: cos_sim_spearman
|
| 1976 |
+
value: 75.75714864112797
|
| 1977 |
+
- type: euclidean_pearson
|
| 1978 |
+
value: 82.33806918604493
|
| 1979 |
+
- type: euclidean_spearman
|
| 1980 |
+
value: 75.45282124387357
|
| 1981 |
+
- type: manhattan_pearson
|
| 1982 |
+
value: 82.32555620660538
|
| 1983 |
+
- type: manhattan_spearman
|
| 1984 |
+
value: 75.49228731684082
|
| 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: 84.88151620954451
|
| 1996 |
+
- type: cos_sim_spearman
|
| 1997 |
+
value: 86.08377598473446
|
| 1998 |
+
- type: euclidean_pearson
|
| 1999 |
+
value: 85.36958329369413
|
| 2000 |
+
- type: euclidean_spearman
|
| 2001 |
+
value: 86.10274219670679
|
| 2002 |
+
- type: manhattan_pearson
|
| 2003 |
+
value: 85.25873897594711
|
| 2004 |
+
- type: manhattan_spearman
|
| 2005 |
+
value: 85.98096461661584
|
| 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: 84.29360558735978
|
| 2017 |
+
- type: cos_sim_spearman
|
| 2018 |
+
value: 82.28284203795577
|
| 2019 |
+
- type: euclidean_pearson
|
| 2020 |
+
value: 83.81636655536633
|
| 2021 |
+
- type: euclidean_spearman
|
| 2022 |
+
value: 82.24340438530236
|
| 2023 |
+
- type: manhattan_pearson
|
| 2024 |
+
value: 83.83914453428608
|
| 2025 |
+
- type: manhattan_spearman
|
| 2026 |
+
value: 82.28391354080694
|
| 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: 87.47344180426744
|
| 2038 |
+
- type: cos_sim_spearman
|
| 2039 |
+
value: 88.90045649789438
|
| 2040 |
+
- type: euclidean_pearson
|
| 2041 |
+
value: 88.43020815961273
|
| 2042 |
+
- type: euclidean_spearman
|
| 2043 |
+
value: 89.0087449011776
|
| 2044 |
+
- type: manhattan_pearson
|
| 2045 |
+
value: 88.37601826505525
|
| 2046 |
+
- type: manhattan_spearman
|
| 2047 |
+
value: 88.96756360690617
|
| 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: 83.35997025304613
|
| 2059 |
+
- type: cos_sim_spearman
|
| 2060 |
+
value: 85.18237675717147
|
| 2061 |
+
- type: euclidean_pearson
|
| 2062 |
+
value: 84.46478196990202
|
| 2063 |
+
- type: euclidean_spearman
|
| 2064 |
+
value: 85.27748677712205
|
| 2065 |
+
- type: manhattan_pearson
|
| 2066 |
+
value: 84.29342543953123
|
| 2067 |
+
- type: manhattan_spearman
|
| 2068 |
+
value: 85.10579612516567
|
| 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: 88.56668329596836
|
| 2080 |
+
- type: cos_sim_spearman
|
| 2081 |
+
value: 88.72837234129177
|
| 2082 |
+
- type: euclidean_pearson
|
| 2083 |
+
value: 89.39395650897828
|
| 2084 |
+
- type: euclidean_spearman
|
| 2085 |
+
value: 88.82001247906778
|
| 2086 |
+
- type: manhattan_pearson
|
| 2087 |
+
value: 89.41735354368878
|
| 2088 |
+
- type: manhattan_spearman
|
| 2089 |
+
value: 88.95159141850039
|
| 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: eea2b4fe26a775864c896887d910b76a8098ad3f
|
| 2098 |
+
metrics:
|
| 2099 |
+
- type: cos_sim_pearson
|
| 2100 |
+
value: 67.466167902991
|
| 2101 |
+
- type: cos_sim_spearman
|
| 2102 |
+
value: 68.54466147197274
|
| 2103 |
+
- type: euclidean_pearson
|
| 2104 |
+
value: 69.35551179564695
|
| 2105 |
+
- type: euclidean_spearman
|
| 2106 |
+
value: 68.75455717749132
|
| 2107 |
+
- type: manhattan_pearson
|
| 2108 |
+
value: 69.42432368208264
|
| 2109 |
+
- type: manhattan_spearman
|
| 2110 |
+
value: 68.83203709670562
|
| 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: 85.33241300373689
|
| 2122 |
+
- type: cos_sim_spearman
|
| 2123 |
+
value: 86.97909372129874
|
| 2124 |
+
- type: euclidean_pearson
|
| 2125 |
+
value: 86.99526113559924
|
| 2126 |
+
- type: euclidean_spearman
|
| 2127 |
+
value: 87.02644372623219
|
| 2128 |
+
- type: manhattan_pearson
|
| 2129 |
+
value: 86.78744182759846
|
| 2130 |
+
- type: manhattan_spearman
|
| 2131 |
+
value: 86.8886180198196
|
| 2132 |
+
- task:
|
| 2133 |
+
type: Reranking
|
| 2134 |
+
dataset:
|
| 2135 |
+
type: mteb/scidocs-reranking
|
| 2136 |
+
name: MTEB SciDocsRR
|
| 2137 |
+
config: default
|
| 2138 |
+
split: test
|
| 2139 |
+
revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
|
| 2140 |
+
metrics:
|
| 2141 |
+
- type: map
|
| 2142 |
+
value: 86.18374413668717
|
| 2143 |
+
- type: mrr
|
| 2144 |
+
value: 95.93213068703264
|
| 2145 |
+
- task:
|
| 2146 |
+
type: Retrieval
|
| 2147 |
+
dataset:
|
| 2148 |
+
type: mteb/scifact
|
| 2149 |
+
name: MTEB SciFact
|
| 2150 |
+
config: default
|
| 2151 |
+
split: test
|
| 2152 |
+
revision: 0228b52cf27578f30900b9e5271d331663a030d7
|
| 2153 |
+
metrics:
|
| 2154 |
+
- type: map_at_1
|
| 2155 |
+
value: 58.31699999999999
|
| 2156 |
+
- type: map_at_10
|
| 2157 |
+
value: 67.691
|
| 2158 |
+
- type: map_at_100
|
| 2159 |
+
value: 68.201
|
| 2160 |
+
- type: map_at_1000
|
| 2161 |
+
value: 68.232
|
| 2162 |
+
- type: map_at_3
|
| 2163 |
+
value: 64.47800000000001
|
| 2164 |
+
- type: map_at_5
|
| 2165 |
+
value: 66.51
|
| 2166 |
+
- type: mrr_at_1
|
| 2167 |
+
value: 61.0
|
| 2168 |
+
- type: mrr_at_10
|
| 2169 |
+
value: 68.621
|
| 2170 |
+
- type: mrr_at_100
|
| 2171 |
+
value: 68.973
|
| 2172 |
+
- type: mrr_at_1000
|
| 2173 |
+
value: 69.002
|
| 2174 |
+
- type: mrr_at_3
|
| 2175 |
+
value: 66.111
|
| 2176 |
+
- type: mrr_at_5
|
| 2177 |
+
value: 67.578
|
| 2178 |
+
- type: ndcg_at_1
|
| 2179 |
+
value: 61.0
|
| 2180 |
+
- type: ndcg_at_10
|
| 2181 |
+
value: 72.219
|
| 2182 |
+
- type: ndcg_at_100
|
| 2183 |
+
value: 74.397
|
| 2184 |
+
- type: ndcg_at_1000
|
| 2185 |
+
value: 75.021
|
| 2186 |
+
- type: ndcg_at_3
|
| 2187 |
+
value: 66.747
|
| 2188 |
+
- type: ndcg_at_5
|
| 2189 |
+
value: 69.609
|
| 2190 |
+
- type: precision_at_1
|
| 2191 |
+
value: 61.0
|
| 2192 |
+
- type: precision_at_10
|
| 2193 |
+
value: 9.6
|
| 2194 |
+
- type: precision_at_100
|
| 2195 |
+
value: 1.08
|
| 2196 |
+
- type: precision_at_1000
|
| 2197 |
+
value: 0.11299999999999999
|
| 2198 |
+
- type: precision_at_3
|
| 2199 |
+
value: 25.667
|
| 2200 |
+
- type: precision_at_5
|
| 2201 |
+
value: 17.267
|
| 2202 |
+
- type: recall_at_1
|
| 2203 |
+
value: 58.31699999999999
|
| 2204 |
+
- type: recall_at_10
|
| 2205 |
+
value: 85.233
|
| 2206 |
+
- type: recall_at_100
|
| 2207 |
+
value: 95.167
|
| 2208 |
+
- type: recall_at_1000
|
| 2209 |
+
value: 99.667
|
| 2210 |
+
- type: recall_at_3
|
| 2211 |
+
value: 70.589
|
| 2212 |
+
- type: recall_at_5
|
| 2213 |
+
value: 77.628
|
| 2214 |
+
- task:
|
| 2215 |
+
type: PairClassification
|
| 2216 |
+
dataset:
|
| 2217 |
+
type: mteb/sprintduplicatequestions-pairclassification
|
| 2218 |
+
name: MTEB SprintDuplicateQuestions
|
| 2219 |
+
config: default
|
| 2220 |
+
split: test
|
| 2221 |
+
revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
|
| 2222 |
+
metrics:
|
| 2223 |
+
- type: cos_sim_accuracy
|
| 2224 |
+
value: 99.83267326732673
|
| 2225 |
+
- type: cos_sim_ap
|
| 2226 |
+
value: 96.13707107038228
|
| 2227 |
+
- type: cos_sim_f1
|
| 2228 |
+
value: 91.48830263812842
|
| 2229 |
+
- type: cos_sim_precision
|
| 2230 |
+
value: 91.0802775024777
|
| 2231 |
+
- type: cos_sim_recall
|
| 2232 |
+
value: 91.9
|
| 2233 |
+
- type: dot_accuracy
|
| 2234 |
+
value: 99.83069306930693
|
| 2235 |
+
- type: dot_ap
|
| 2236 |
+
value: 96.21199069147254
|
| 2237 |
+
- type: dot_f1
|
| 2238 |
+
value: 91.36295556665004
|
| 2239 |
+
- type: dot_precision
|
| 2240 |
+
value: 91.22632103688933
|
| 2241 |
+
- type: dot_recall
|
| 2242 |
+
value: 91.5
|
| 2243 |
+
- type: euclidean_accuracy
|
| 2244 |
+
value: 99.83267326732673
|
| 2245 |
+
- type: euclidean_ap
|
| 2246 |
+
value: 96.08957801367436
|
| 2247 |
+
- type: euclidean_f1
|
| 2248 |
+
value: 91.33004926108374
|
| 2249 |
+
- type: euclidean_precision
|
| 2250 |
+
value: 90.0
|
| 2251 |
+
- type: euclidean_recall
|
| 2252 |
+
value: 92.7
|
| 2253 |
+
- type: manhattan_accuracy
|
| 2254 |
+
value: 99.83564356435643
|
| 2255 |
+
- type: manhattan_ap
|
| 2256 |
+
value: 96.10534946461945
|
| 2257 |
+
- type: manhattan_f1
|
| 2258 |
+
value: 91.74950298210736
|
| 2259 |
+
- type: manhattan_precision
|
| 2260 |
+
value: 91.20553359683794
|
| 2261 |
+
- type: manhattan_recall
|
| 2262 |
+
value: 92.30000000000001
|
| 2263 |
+
- type: max_accuracy
|
| 2264 |
+
value: 99.83564356435643
|
| 2265 |
+
- type: max_ap
|
| 2266 |
+
value: 96.21199069147254
|
| 2267 |
+
- type: max_f1
|
| 2268 |
+
value: 91.74950298210736
|
| 2269 |
+
- task:
|
| 2270 |
+
type: Clustering
|
| 2271 |
+
dataset:
|
| 2272 |
+
type: mteb/stackexchange-clustering
|
| 2273 |
+
name: MTEB StackExchangeClustering
|
| 2274 |
+
config: default
|
| 2275 |
+
split: test
|
| 2276 |
+
revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
|
| 2277 |
+
metrics:
|
| 2278 |
+
- type: v_measure
|
| 2279 |
+
value: 62.045718843534736
|
| 2280 |
+
- task:
|
| 2281 |
+
type: Clustering
|
| 2282 |
+
dataset:
|
| 2283 |
+
type: mteb/stackexchange-clustering-p2p
|
| 2284 |
+
name: MTEB StackExchangeClusteringP2P
|
| 2285 |
+
config: default
|
| 2286 |
+
split: test
|
| 2287 |
+
revision: 815ca46b2622cec33ccafc3735d572c266efdb44
|
| 2288 |
+
metrics:
|
| 2289 |
+
- type: v_measure
|
| 2290 |
+
value: 36.6501777041092
|
| 2291 |
+
- task:
|
| 2292 |
+
type: Reranking
|
| 2293 |
+
dataset:
|
| 2294 |
+
type: mteb/stackoverflowdupquestions-reranking
|
| 2295 |
+
name: MTEB StackOverflowDupQuestions
|
| 2296 |
+
config: default
|
| 2297 |
+
split: test
|
| 2298 |
+
revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
|
| 2299 |
+
metrics:
|
| 2300 |
+
- type: map
|
| 2301 |
+
value: 52.963913408053955
|
| 2302 |
+
- type: mrr
|
| 2303 |
+
value: 53.87972423818012
|
| 2304 |
+
- task:
|
| 2305 |
+
type: Summarization
|
| 2306 |
+
dataset:
|
| 2307 |
+
type: mteb/summeval
|
| 2308 |
+
name: MTEB SummEval
|
| 2309 |
+
config: default
|
| 2310 |
+
split: test
|
| 2311 |
+
revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
|
| 2312 |
+
metrics:
|
| 2313 |
+
- type: cos_sim_pearson
|
| 2314 |
+
value: 30.44195730764998
|
| 2315 |
+
- type: cos_sim_spearman
|
| 2316 |
+
value: 30.59626288679397
|
| 2317 |
+
- type: dot_pearson
|
| 2318 |
+
value: 30.22974492404086
|
| 2319 |
+
- type: dot_spearman
|
| 2320 |
+
value: 29.345245972906497
|
| 2321 |
+
- task:
|
| 2322 |
+
type: Retrieval
|
| 2323 |
+
dataset:
|
| 2324 |
+
type: mteb/trec-covid
|
| 2325 |
+
name: MTEB TRECCOVID
|
| 2326 |
+
config: default
|
| 2327 |
+
split: test
|
| 2328 |
+
revision: bb9466bac8153a0349341eb1b22e06409e78ef4e
|
| 2329 |
+
metrics:
|
| 2330 |
+
- type: map_at_1
|
| 2331 |
+
value: 0.24
|
| 2332 |
+
- type: map_at_10
|
| 2333 |
+
value: 2.01
|
| 2334 |
+
- type: map_at_100
|
| 2335 |
+
value: 11.928999999999998
|
| 2336 |
+
- type: map_at_1000
|
| 2337 |
+
value: 29.034
|
| 2338 |
+
- type: map_at_3
|
| 2339 |
+
value: 0.679
|
| 2340 |
+
- type: map_at_5
|
| 2341 |
+
value: 1.064
|
| 2342 |
+
- type: mrr_at_1
|
| 2343 |
+
value: 92.0
|
| 2344 |
+
- type: mrr_at_10
|
| 2345 |
+
value: 96.0
|
| 2346 |
+
- type: mrr_at_100
|
| 2347 |
+
value: 96.0
|
| 2348 |
+
- type: mrr_at_1000
|
| 2349 |
+
value: 96.0
|
| 2350 |
+
- type: mrr_at_3
|
| 2351 |
+
value: 96.0
|
| 2352 |
+
- type: mrr_at_5
|
| 2353 |
+
value: 96.0
|
| 2354 |
+
- type: ndcg_at_1
|
| 2355 |
+
value: 87.0
|
| 2356 |
+
- type: ndcg_at_10
|
| 2357 |
+
value: 80.118
|
| 2358 |
+
- type: ndcg_at_100
|
| 2359 |
+
value: 60.753
|
| 2360 |
+
- type: ndcg_at_1000
|
| 2361 |
+
value: 54.632999999999996
|
| 2362 |
+
- type: ndcg_at_3
|
| 2363 |
+
value: 83.073
|
| 2364 |
+
- type: ndcg_at_5
|
| 2365 |
+
value: 80.733
|
| 2366 |
+
- type: precision_at_1
|
| 2367 |
+
value: 92.0
|
| 2368 |
+
- type: precision_at_10
|
| 2369 |
+
value: 84.8
|
| 2370 |
+
- type: precision_at_100
|
| 2371 |
+
value: 62.019999999999996
|
| 2372 |
+
- type: precision_at_1000
|
| 2373 |
+
value: 24.028
|
| 2374 |
+
- type: precision_at_3
|
| 2375 |
+
value: 87.333
|
| 2376 |
+
- type: precision_at_5
|
| 2377 |
+
value: 85.2
|
| 2378 |
+
- type: recall_at_1
|
| 2379 |
+
value: 0.24
|
| 2380 |
+
- type: recall_at_10
|
| 2381 |
+
value: 2.205
|
| 2382 |
+
- type: recall_at_100
|
| 2383 |
+
value: 15.068000000000001
|
| 2384 |
+
- type: recall_at_1000
|
| 2385 |
+
value: 51.796
|
| 2386 |
+
- type: recall_at_3
|
| 2387 |
+
value: 0.698
|
| 2388 |
+
- type: recall_at_5
|
| 2389 |
+
value: 1.1199999999999999
|
| 2390 |
+
- task:
|
| 2391 |
+
type: Retrieval
|
| 2392 |
+
dataset:
|
| 2393 |
+
type: mteb/touche2020
|
| 2394 |
+
name: MTEB Touche2020
|
| 2395 |
+
config: default
|
| 2396 |
+
split: test
|
| 2397 |
+
revision: a34f9a33db75fa0cbb21bb5cfc3dae8dc8bec93f
|
| 2398 |
+
metrics:
|
| 2399 |
+
- type: map_at_1
|
| 2400 |
+
value: 3.066
|
| 2401 |
+
- type: map_at_10
|
| 2402 |
+
value: 9.219
|
| 2403 |
+
- type: map_at_100
|
| 2404 |
+
value: 15.387
|
| 2405 |
+
- type: map_at_1000
|
| 2406 |
+
value: 16.957
|
| 2407 |
+
- type: map_at_3
|
| 2408 |
+
value: 5.146
|
| 2409 |
+
- type: map_at_5
|
| 2410 |
+
value: 6.6739999999999995
|
| 2411 |
+
- type: mrr_at_1
|
| 2412 |
+
value: 40.816
|
| 2413 |
+
- type: mrr_at_10
|
| 2414 |
+
value: 50.844
|
| 2415 |
+
- type: mrr_at_100
|
| 2416 |
+
value: 51.664
|
| 2417 |
+
- type: mrr_at_1000
|
| 2418 |
+
value: 51.664
|
| 2419 |
+
- type: mrr_at_3
|
| 2420 |
+
value: 46.259
|
| 2421 |
+
- type: mrr_at_5
|
| 2422 |
+
value: 49.116
|
| 2423 |
+
- type: ndcg_at_1
|
| 2424 |
+
value: 37.755
|
| 2425 |
+
- type: ndcg_at_10
|
| 2426 |
+
value: 23.477
|
| 2427 |
+
- type: ndcg_at_100
|
| 2428 |
+
value: 36.268
|
| 2429 |
+
- type: ndcg_at_1000
|
| 2430 |
+
value: 47.946
|
| 2431 |
+
- type: ndcg_at_3
|
| 2432 |
+
value: 25.832
|
| 2433 |
+
- type: ndcg_at_5
|
| 2434 |
+
value: 24.235
|
| 2435 |
+
- type: precision_at_1
|
| 2436 |
+
value: 40.816
|
| 2437 |
+
- type: precision_at_10
|
| 2438 |
+
value: 20.204
|
| 2439 |
+
- type: precision_at_100
|
| 2440 |
+
value: 7.611999999999999
|
| 2441 |
+
- type: precision_at_1000
|
| 2442 |
+
value: 1.543
|
| 2443 |
+
- type: precision_at_3
|
| 2444 |
+
value: 25.169999999999998
|
| 2445 |
+
- type: precision_at_5
|
| 2446 |
+
value: 23.265
|
| 2447 |
+
- type: recall_at_1
|
| 2448 |
+
value: 3.066
|
| 2449 |
+
- type: recall_at_10
|
| 2450 |
+
value: 14.985999999999999
|
| 2451 |
+
- type: recall_at_100
|
| 2452 |
+
value: 47.902
|
| 2453 |
+
- type: recall_at_1000
|
| 2454 |
+
value: 83.56400000000001
|
| 2455 |
+
- type: recall_at_3
|
| 2456 |
+
value: 5.755
|
| 2457 |
+
- type: recall_at_5
|
| 2458 |
+
value: 8.741999999999999
|
| 2459 |
+
- task:
|
| 2460 |
+
type: Classification
|
| 2461 |
+
dataset:
|
| 2462 |
+
type: mteb/toxic_conversations_50k
|
| 2463 |
+
name: MTEB ToxicConversationsClassification
|
| 2464 |
+
config: default
|
| 2465 |
+
split: test
|
| 2466 |
+
revision: edfaf9da55d3dd50d43143d90c1ac476895ae6de
|
| 2467 |
+
metrics:
|
| 2468 |
+
- type: accuracy
|
| 2469 |
+
value: 69.437
|
| 2470 |
+
- type: ap
|
| 2471 |
+
value: 12.844066827082706
|
| 2472 |
+
- type: f1
|
| 2473 |
+
value: 52.74974809872495
|
| 2474 |
+
- task:
|
| 2475 |
+
type: Classification
|
| 2476 |
+
dataset:
|
| 2477 |
+
type: mteb/tweet_sentiment_extraction
|
| 2478 |
+
name: MTEB TweetSentimentExtractionClassification
|
| 2479 |
+
config: default
|
| 2480 |
+
split: test
|
| 2481 |
+
revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
|
| 2482 |
+
metrics:
|
| 2483 |
+
- type: accuracy
|
| 2484 |
+
value: 61.26768534238823
|
| 2485 |
+
- type: f1
|
| 2486 |
+
value: 61.65100187399282
|
| 2487 |
+
- task:
|
| 2488 |
+
type: Clustering
|
| 2489 |
+
dataset:
|
| 2490 |
+
type: mteb/twentynewsgroups-clustering
|
| 2491 |
+
name: MTEB TwentyNewsgroupsClustering
|
| 2492 |
+
config: default
|
| 2493 |
+
split: test
|
| 2494 |
+
revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
|
| 2495 |
+
metrics:
|
| 2496 |
+
- type: v_measure
|
| 2497 |
+
value: 49.860968711078804
|
| 2498 |
+
- task:
|
| 2499 |
+
type: PairClassification
|
| 2500 |
+
dataset:
|
| 2501 |
+
type: mteb/twittersemeval2015-pairclassification
|
| 2502 |
+
name: MTEB TwitterSemEval2015
|
| 2503 |
+
config: default
|
| 2504 |
+
split: test
|
| 2505 |
+
revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
|
| 2506 |
+
metrics:
|
| 2507 |
+
- type: cos_sim_accuracy
|
| 2508 |
+
value: 85.7423854085951
|
| 2509 |
+
- type: cos_sim_ap
|
| 2510 |
+
value: 73.47560303339571
|
| 2511 |
+
- type: cos_sim_f1
|
| 2512 |
+
value: 67.372778183589
|
| 2513 |
+
- type: cos_sim_precision
|
| 2514 |
+
value: 62.54520795660036
|
| 2515 |
+
- type: cos_sim_recall
|
| 2516 |
+
value: 73.00791556728232
|
| 2517 |
+
- type: dot_accuracy
|
| 2518 |
+
value: 85.36091077069798
|
| 2519 |
+
- type: dot_ap
|
| 2520 |
+
value: 72.42521572307255
|
| 2521 |
+
- type: dot_f1
|
| 2522 |
+
value: 66.90576304724215
|
| 2523 |
+
- type: dot_precision
|
| 2524 |
+
value: 62.96554934823091
|
| 2525 |
+
- type: dot_recall
|
| 2526 |
+
value: 71.37203166226914
|
| 2527 |
+
- type: euclidean_accuracy
|
| 2528 |
+
value: 85.76026703224653
|
| 2529 |
+
- type: euclidean_ap
|
| 2530 |
+
value: 73.44852563860128
|
| 2531 |
+
- type: euclidean_f1
|
| 2532 |
+
value: 67.3
|
| 2533 |
+
- type: euclidean_precision
|
| 2534 |
+
value: 63.94299287410926
|
| 2535 |
+
- type: euclidean_recall
|
| 2536 |
+
value: 71.02902374670185
|
| 2537 |
+
- type: manhattan_accuracy
|
| 2538 |
+
value: 85.7423854085951
|
| 2539 |
+
- type: manhattan_ap
|
| 2540 |
+
value: 73.2635034755551
|
| 2541 |
+
- type: manhattan_f1
|
| 2542 |
+
value: 67.3180263800684
|
| 2543 |
+
- type: manhattan_precision
|
| 2544 |
+
value: 62.66484765802638
|
| 2545 |
+
- type: manhattan_recall
|
| 2546 |
+
value: 72.71767810026385
|
| 2547 |
+
- type: max_accuracy
|
| 2548 |
+
value: 85.76026703224653
|
| 2549 |
+
- type: max_ap
|
| 2550 |
+
value: 73.47560303339571
|
| 2551 |
+
- type: max_f1
|
| 2552 |
+
value: 67.372778183589
|
| 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: 88.67543757519307
|
| 2564 |
+
- type: cos_sim_ap
|
| 2565 |
+
value: 85.35516518531304
|
| 2566 |
+
- type: cos_sim_f1
|
| 2567 |
+
value: 77.58197635511934
|
| 2568 |
+
- type: cos_sim_precision
|
| 2569 |
+
value: 75.01078360891445
|
| 2570 |
+
- type: cos_sim_recall
|
| 2571 |
+
value: 80.33569448721897
|
| 2572 |
+
- type: dot_accuracy
|
| 2573 |
+
value: 87.61400240617844
|
| 2574 |
+
- type: dot_ap
|
| 2575 |
+
value: 83.0774968268665
|
| 2576 |
+
- type: dot_f1
|
| 2577 |
+
value: 75.68229012162561
|
| 2578 |
+
- type: dot_precision
|
| 2579 |
+
value: 72.99713876967095
|
| 2580 |
+
- type: dot_recall
|
| 2581 |
+
value: 78.57252848783493
|
| 2582 |
+
- type: euclidean_accuracy
|
| 2583 |
+
value: 88.73753250281368
|
| 2584 |
+
- type: euclidean_ap
|
| 2585 |
+
value: 85.48043564821317
|
| 2586 |
+
- type: euclidean_f1
|
| 2587 |
+
value: 77.75975862719216
|
| 2588 |
+
- type: euclidean_precision
|
| 2589 |
+
value: 76.21054187920456
|
| 2590 |
+
- type: euclidean_recall
|
| 2591 |
+
value: 79.37326763166
|
| 2592 |
+
- type: manhattan_accuracy
|
| 2593 |
+
value: 88.75111576823068
|
| 2594 |
+
- type: manhattan_ap
|
| 2595 |
+
value: 85.44993439423668
|
| 2596 |
+
- type: manhattan_f1
|
| 2597 |
+
value: 77.6861329994845
|
| 2598 |
+
- type: manhattan_precision
|
| 2599 |
+
value: 74.44601270289344
|
| 2600 |
+
- type: manhattan_recall
|
| 2601 |
+
value: 81.22112719433323
|
| 2602 |
+
- type: max_accuracy
|
| 2603 |
+
value: 88.75111576823068
|
| 2604 |
+
- type: max_ap
|
| 2605 |
+
value: 85.48043564821317
|
| 2606 |
+
- type: max_f1
|
| 2607 |
+
value: 77.75975862719216
|
| 2608 |
+
---
|
| 2609 |
+
<h1 align="center">NoInstruct small Embedding v0</h1>
|
| 2610 |
+
|
| 2611 |
+
*NoInstruct Embedding: Asymmetric Pooling is All You Need*
|
| 2612 |
+
|
| 2613 |
+
This model has improved retrieval performance compared to the [avsolatorio/GIST-small-Embedding-v0](https://huggingface.co/avsolatorio/GIST-small-Embedding-v0) model.
|
| 2614 |
+
|
| 2615 |
+
One of the things that the `GIST` family of models fell short on is the performance on retrieval tasks. We propose a method that produces improved retrieval performance while maintaining independence on crafting arbitrary instructions, a trending paradigm in embedding models for retrieval tasks, when encoding a query.
|
| 2616 |
+
|
| 2617 |
+
Technical details of the model will be published shortly.
|
| 2618 |
+
|
| 2619 |
+
# Usage
|
| 2620 |
+
|
| 2621 |
+
```Python
|
| 2622 |
+
from typing import Union
|
| 2623 |
+
import torch
|
| 2624 |
+
import torch.nn.functional as F
|
| 2625 |
+
from transformers import AutoModel, AutoTokenizer
|
| 2626 |
+
|
| 2627 |
+
model = AutoModel.from_pretrained("avsolatorio/NoInstruct-small-Embedding-v0")
|
| 2628 |
+
tokenizer = AutoTokenizer.from_pretrained("avsolatorio/NoInstruct-small-Embedding-v0")
|
| 2629 |
+
|
| 2630 |
+
|
| 2631 |
+
def get_embedding(text: Union[str, list[str]], mode: str = "sentence"):
|
| 2632 |
+
model.eval()
|
| 2633 |
+
|
| 2634 |
+
assert mode in ("query", "sentence"), f"mode={mode} was passed but only `query` and `sentence` are the supported modes."
|
| 2635 |
+
|
| 2636 |
+
if isinstance(text, str):
|
| 2637 |
+
text = [text]
|
| 2638 |
+
|
| 2639 |
+
inp = tokenizer(text, return_tensors="pt", padding=True, truncation=True)
|
| 2640 |
+
|
| 2641 |
+
with torch.no_grad():
|
| 2642 |
+
output = model(**inp)
|
| 2643 |
+
|
| 2644 |
+
# The model is optimized to use the mean pooling for queries,
|
| 2645 |
+
# while the sentence / document embedding uses the [CLS] representation.
|
| 2646 |
+
|
| 2647 |
+
if mode == "query":
|
| 2648 |
+
vectors = output.last_hidden_state * inp["attention_mask"].unsqueeze(2)
|
| 2649 |
+
vectors = vectors.sum(dim=1) / inp["attention_mask"].sum(dim=-1).view(-1, 1)
|
| 2650 |
+
else:
|
| 2651 |
+
vectors = output.last_hidden_state[:, 0, :]
|
| 2652 |
+
|
| 2653 |
+
return vectors
|
| 2654 |
+
|
| 2655 |
+
|
| 2656 |
+
texts = [
|
| 2657 |
+
"Illustration of the REaLTabFormer model. The left block shows the non-relational tabular data model using GPT-2 with a causal LM head. In contrast, the right block shows how a relational dataset's child table is modeled using a sequence-to-sequence (Seq2Seq) model. The Seq2Seq model uses the observations in the parent table to condition the generation of the observations in the child table. The trained GPT-2 model on the parent table, with weights frozen, is also used as the encoder in the Seq2Seq model.",
|
| 2658 |
+
"Predicting human mobility holds significant practical value, with applications ranging from enhancing disaster risk planning to simulating epidemic spread. In this paper, we present the GeoFormer, a decoder-only transformer model adapted from the GPT architecture to forecast human mobility.",
|
| 2659 |
+
"As the economies of Southeast Asia continue adopting digital technologies, policy makers increasingly ask how to prepare the workforce for emerging labor demands. However, little is known about the skills that workers need to adapt to these changes"
|
| 2660 |
+
]
|
| 2661 |
+
|
| 2662 |
+
# Compute embeddings
|
| 2663 |
+
embeddings = get_embedding(texts, mode="sentence")
|
| 2664 |
+
|
| 2665 |
+
# Compute cosine-similarity for each pair of sentences
|
| 2666 |
+
scores = F.cosine_similarity(embeddings.unsqueeze(1), embeddings.unsqueeze(0), dim=-1)
|
| 2667 |
+
print(scores.cpu().numpy())
|
| 2668 |
+
|
| 2669 |
+
# Test the retrieval performance.
|
| 2670 |
+
query = get_embedding("Which sentence talks about concept on jobs?", mode="query")
|
| 2671 |
+
|
| 2672 |
+
scores = F.cosine_similarity(query, embeddings, dim=-1)
|
| 2673 |
+
print(scores.cpu().numpy())
|
| 2674 |
+
```
|
| 2675 |
+
|
| 2676 |
+
Support for the Sentence Transformers library will follow soon.
|
commit-info.json
ADDED
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@@ -0,0 +1 @@
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+
{"repo_id": "avsolatorio/01-600-11-1-3-2-0-0-cls-qli_0-normed-384-512_ASYM_BAAI_bge-small-en-v1.5-20240424083154-latest", "commit_message": "{\"loss\": 0.4601, \"grad_norm\": 5.519935131072998, \"learning_rate\": 2.6289851550653513e-06, \"epoch\": 2.97, \"step\": 169000}"}
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config.json
ADDED
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@@ -0,0 +1,32 @@
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+
{
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| 2 |
+
"_name_or_path": "avsolatorio/NoInstruct-small-Embedding-v0",
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| 3 |
+
"architectures": [
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| 4 |
+
"BertModel"
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| 5 |
+
],
|
| 6 |
+
"attention_probs_dropout_prob": 0.1,
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| 7 |
+
"classifier_dropout": null,
|
| 8 |
+
"hidden_act": "gelu",
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| 9 |
+
"hidden_dropout_prob": 0.1,
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| 10 |
+
"hidden_size": 384,
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| 11 |
+
"id2label": {
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| 12 |
+
"0": "LABEL_0"
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| 13 |
+
},
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| 14 |
+
"initializer_range": 0.02,
|
| 15 |
+
"intermediate_size": 1536,
|
| 16 |
+
"label2id": {
|
| 17 |
+
"LABEL_0": 0
|
| 18 |
+
},
|
| 19 |
+
"layer_norm_eps": 1e-12,
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| 20 |
+
"max_position_embeddings": 512,
|
| 21 |
+
"model_type": "bert",
|
| 22 |
+
"num_attention_heads": 12,
|
| 23 |
+
"num_hidden_layers": 12,
|
| 24 |
+
"output_hidden_states": true,
|
| 25 |
+
"pad_token_id": 0,
|
| 26 |
+
"position_embedding_type": "absolute",
|
| 27 |
+
"torch_dtype": "float32",
|
| 28 |
+
"transformers_version": "4.39.3",
|
| 29 |
+
"type_vocab_size": 2,
|
| 30 |
+
"use_cache": true,
|
| 31 |
+
"vocab_size": 30522
|
| 32 |
+
}
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config_sentence_transformers.json
ADDED
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@@ -0,0 +1,9 @@
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{
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| 2 |
+
"__version__": {
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| 3 |
+
"sentence_transformers": "2.2.2",
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| 4 |
+
"transformers": "4.28.1",
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| 5 |
+
"pytorch": "1.13.0+cu117"
|
| 6 |
+
},
|
| 7 |
+
"prompts": {},
|
| 8 |
+
"default_prompt_name": null
|
| 9 |
+
}
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model.safetensors
ADDED
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@@ -0,0 +1,3 @@
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| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:831a0c15cd73d37ef70185fd446b873d8018ed6b6a108cbedb8efb8f42d6997e
|
| 3 |
+
size 133462128
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modules.json
ADDED
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@@ -0,0 +1,26 @@
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| 1 |
+
[
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| 2 |
+
{
|
| 3 |
+
"idx": 0,
|
| 4 |
+
"name": "0",
|
| 5 |
+
"path": "",
|
| 6 |
+
"type": "sentence_transformers.models.Transformer"
|
| 7 |
+
},
|
| 8 |
+
{
|
| 9 |
+
"idx": 1,
|
| 10 |
+
"name": "1",
|
| 11 |
+
"path": "1_Pooling",
|
| 12 |
+
"type": "sentence_transformers.models.Pooling"
|
| 13 |
+
},
|
| 14 |
+
{
|
| 15 |
+
"idx": 2,
|
| 16 |
+
"name": "2",
|
| 17 |
+
"path": "2_Pooling",
|
| 18 |
+
"type": "sentence_transformers.models.Pooling"
|
| 19 |
+
},
|
| 20 |
+
{
|
| 21 |
+
"idx": 3,
|
| 22 |
+
"name": "3",
|
| 23 |
+
"path": "3_Normalize",
|
| 24 |
+
"type": "sentence_transformers.models.Normalize"
|
| 25 |
+
}
|
| 26 |
+
]
|
sentence_bert_config.json
ADDED
|
@@ -0,0 +1,4 @@
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| 1 |
+
{
|
| 2 |
+
"max_seq_length": 512,
|
| 3 |
+
"do_lower_case": true
|
| 4 |
+
}
|
special_tokens_map.json
ADDED
|
@@ -0,0 +1,37 @@
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+
{
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| 2 |
+
"cls_token": {
|
| 3 |
+
"content": "[CLS]",
|
| 4 |
+
"lstrip": false,
|
| 5 |
+
"normalized": false,
|
| 6 |
+
"rstrip": false,
|
| 7 |
+
"single_word": false
|
| 8 |
+
},
|
| 9 |
+
"mask_token": {
|
| 10 |
+
"content": "[MASK]",
|
| 11 |
+
"lstrip": false,
|
| 12 |
+
"normalized": false,
|
| 13 |
+
"rstrip": false,
|
| 14 |
+
"single_word": false
|
| 15 |
+
},
|
| 16 |
+
"pad_token": {
|
| 17 |
+
"content": "[PAD]",
|
| 18 |
+
"lstrip": false,
|
| 19 |
+
"normalized": false,
|
| 20 |
+
"rstrip": false,
|
| 21 |
+
"single_word": false
|
| 22 |
+
},
|
| 23 |
+
"sep_token": {
|
| 24 |
+
"content": "[SEP]",
|
| 25 |
+
"lstrip": false,
|
| 26 |
+
"normalized": false,
|
| 27 |
+
"rstrip": false,
|
| 28 |
+
"single_word": false
|
| 29 |
+
},
|
| 30 |
+
"unk_token": {
|
| 31 |
+
"content": "[UNK]",
|
| 32 |
+
"lstrip": false,
|
| 33 |
+
"normalized": false,
|
| 34 |
+
"rstrip": false,
|
| 35 |
+
"single_word": false
|
| 36 |
+
}
|
| 37 |
+
}
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tokenizer.json
ADDED
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The diff for this file is too large to render.
See raw diff
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tokenizer_config.json
ADDED
|
@@ -0,0 +1,57 @@
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| 1 |
+
{
|
| 2 |
+
"added_tokens_decoder": {
|
| 3 |
+
"0": {
|
| 4 |
+
"content": "[PAD]",
|
| 5 |
+
"lstrip": false,
|
| 6 |
+
"normalized": false,
|
| 7 |
+
"rstrip": false,
|
| 8 |
+
"single_word": false,
|
| 9 |
+
"special": true
|
| 10 |
+
},
|
| 11 |
+
"100": {
|
| 12 |
+
"content": "[UNK]",
|
| 13 |
+
"lstrip": false,
|
| 14 |
+
"normalized": false,
|
| 15 |
+
"rstrip": false,
|
| 16 |
+
"single_word": false,
|
| 17 |
+
"special": true
|
| 18 |
+
},
|
| 19 |
+
"101": {
|
| 20 |
+
"content": "[CLS]",
|
| 21 |
+
"lstrip": false,
|
| 22 |
+
"normalized": false,
|
| 23 |
+
"rstrip": false,
|
| 24 |
+
"single_word": false,
|
| 25 |
+
"special": true
|
| 26 |
+
},
|
| 27 |
+
"102": {
|
| 28 |
+
"content": "[SEP]",
|
| 29 |
+
"lstrip": false,
|
| 30 |
+
"normalized": false,
|
| 31 |
+
"rstrip": false,
|
| 32 |
+
"single_word": false,
|
| 33 |
+
"special": true
|
| 34 |
+
},
|
| 35 |
+
"103": {
|
| 36 |
+
"content": "[MASK]",
|
| 37 |
+
"lstrip": false,
|
| 38 |
+
"normalized": false,
|
| 39 |
+
"rstrip": false,
|
| 40 |
+
"single_word": false,
|
| 41 |
+
"special": true
|
| 42 |
+
}
|
| 43 |
+
},
|
| 44 |
+
"clean_up_tokenization_spaces": true,
|
| 45 |
+
"cls_token": "[CLS]",
|
| 46 |
+
"do_basic_tokenize": true,
|
| 47 |
+
"do_lower_case": true,
|
| 48 |
+
"mask_token": "[MASK]",
|
| 49 |
+
"model_max_length": 512,
|
| 50 |
+
"never_split": null,
|
| 51 |
+
"pad_token": "[PAD]",
|
| 52 |
+
"sep_token": "[SEP]",
|
| 53 |
+
"strip_accents": null,
|
| 54 |
+
"tokenize_chinese_chars": true,
|
| 55 |
+
"tokenizer_class": "BertTokenizer",
|
| 56 |
+
"unk_token": "[UNK]"
|
| 57 |
+
}
|
vocab.txt
ADDED
|
The diff for this file is too large to render.
See raw diff
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|
|