mteb results
Browse files
README.md
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@@ -1,3 +1,1731 @@
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| 2 |
license: mit
|
| 3 |
---
|
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|
| 1 |
---
|
| 2 |
+
tags:
|
| 3 |
+
- mteb
|
| 4 |
+
- transformers
|
| 5 |
+
model-index:
|
| 6 |
+
- name: speed-embedding-7b-instruct
|
| 7 |
+
results:
|
| 8 |
+
- task:
|
| 9 |
+
type: Classification
|
| 10 |
+
dataset:
|
| 11 |
+
type: mteb/amazon_counterfactual
|
| 12 |
+
name: MTEB AmazonCounterfactualClassification (en)
|
| 13 |
+
config: en
|
| 14 |
+
split: test
|
| 15 |
+
revision: e8379541af4e31359cca9fbcf4b00f2671dba205
|
| 16 |
+
metrics:
|
| 17 |
+
- type: accuracy
|
| 18 |
+
value: 76.67164179104478
|
| 19 |
+
- type: ap
|
| 20 |
+
value: 39.07181577576136
|
| 21 |
+
- type: f1
|
| 22 |
+
value: 70.25085237742982
|
| 23 |
+
- task:
|
| 24 |
+
type: Classification
|
| 25 |
+
dataset:
|
| 26 |
+
type: mteb/amazon_polarity
|
| 27 |
+
name: MTEB AmazonPolarityClassification
|
| 28 |
+
config: default
|
| 29 |
+
split: test
|
| 30 |
+
revision: e2d317d38cd51312af73b3d32a06d1a08b442046
|
| 31 |
+
metrics:
|
| 32 |
+
- type: accuracy
|
| 33 |
+
value: 96.1775
|
| 34 |
+
- type: ap
|
| 35 |
+
value: 94.84308844303422
|
| 36 |
+
- type: f1
|
| 37 |
+
value: 96.17546959843244
|
| 38 |
+
- task:
|
| 39 |
+
type: Classification
|
| 40 |
+
dataset:
|
| 41 |
+
type: mteb/amazon_reviews_multi
|
| 42 |
+
name: MTEB AmazonReviewsClassification (en)
|
| 43 |
+
config: en
|
| 44 |
+
split: test
|
| 45 |
+
revision: 1399c76144fd37290681b995c656ef9b2e06e26d
|
| 46 |
+
metrics:
|
| 47 |
+
- type: accuracy
|
| 48 |
+
value: 56.278000000000006
|
| 49 |
+
- type: f1
|
| 50 |
+
value: 55.45101875980304
|
| 51 |
+
- task:
|
| 52 |
+
type: Retrieval
|
| 53 |
+
dataset:
|
| 54 |
+
type: arguana
|
| 55 |
+
name: MTEB ArguAna
|
| 56 |
+
config: default
|
| 57 |
+
split: test
|
| 58 |
+
revision: None
|
| 59 |
+
metrics:
|
| 60 |
+
- type: ndcg_at_1
|
| 61 |
+
value: 33.642
|
| 62 |
+
- type: ndcg_at_3
|
| 63 |
+
value: 49.399
|
| 64 |
+
- type: ndcg_at_5
|
| 65 |
+
value: 54.108999999999995
|
| 66 |
+
- type: ndcg_at_10
|
| 67 |
+
value: 59.294999999999995
|
| 68 |
+
- type: ndcg_at_100
|
| 69 |
+
value: 62.015
|
| 70 |
+
- type: map_at_1
|
| 71 |
+
value: 33.642
|
| 72 |
+
- type: map_at_3
|
| 73 |
+
value: 45.507
|
| 74 |
+
- type: map_at_5
|
| 75 |
+
value: 48.1
|
| 76 |
+
- type: map_at_10
|
| 77 |
+
value: 50.248000000000005
|
| 78 |
+
- type: map_at_100
|
| 79 |
+
value: 50.954
|
| 80 |
+
- type: recall_at_1
|
| 81 |
+
value: 33.642
|
| 82 |
+
- type: recall_at_3
|
| 83 |
+
value: 60.669
|
| 84 |
+
- type: recall_at_5
|
| 85 |
+
value: 72.191
|
| 86 |
+
- type: recall_at_10
|
| 87 |
+
value: 88.193
|
| 88 |
+
- type: recall_at_100
|
| 89 |
+
value: 99.431
|
| 90 |
+
- type: precision_at_1
|
| 91 |
+
value: 33.642
|
| 92 |
+
- type: precision_at_3
|
| 93 |
+
value: 20.223
|
| 94 |
+
- type: precision_at_5
|
| 95 |
+
value: 14.438
|
| 96 |
+
- type: precision_at_10
|
| 97 |
+
value: 8.819
|
| 98 |
+
- type: precision_at_100
|
| 99 |
+
value: 0.9939999999999999
|
| 100 |
+
- type: mrr_at_1
|
| 101 |
+
value: 33.997
|
| 102 |
+
- type: mrr_at_3
|
| 103 |
+
value: 45.614
|
| 104 |
+
- type: mrr_at_5
|
| 105 |
+
value: 48.263
|
| 106 |
+
- type: mrr_at_10
|
| 107 |
+
value: 50.388999999999996
|
| 108 |
+
- type: mrr_at_100
|
| 109 |
+
value: 51.102000000000004
|
| 110 |
+
- task:
|
| 111 |
+
type: Clustering
|
| 112 |
+
dataset:
|
| 113 |
+
type: mteb/arxiv-clustering-p2p
|
| 114 |
+
name: MTEB ArxivClusteringP2P
|
| 115 |
+
config: default
|
| 116 |
+
split: test
|
| 117 |
+
revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
|
| 118 |
+
metrics:
|
| 119 |
+
- type: v_measure
|
| 120 |
+
value: 51.1249344529392
|
| 121 |
+
- task:
|
| 122 |
+
type: Clustering
|
| 123 |
+
dataset:
|
| 124 |
+
type: mteb/arxiv-clustering-s2s
|
| 125 |
+
name: MTEB ArxivClusteringS2S
|
| 126 |
+
config: default
|
| 127 |
+
split: test
|
| 128 |
+
revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
|
| 129 |
+
metrics:
|
| 130 |
+
- type: v_measure
|
| 131 |
+
value: 47.01575217563573
|
| 132 |
+
- task:
|
| 133 |
+
type: Reranking
|
| 134 |
+
dataset:
|
| 135 |
+
type: mteb/askubuntudupquestions-reranking
|
| 136 |
+
name: MTEB AskUbuntuDupQuestions
|
| 137 |
+
config: default
|
| 138 |
+
split: test
|
| 139 |
+
revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
|
| 140 |
+
metrics:
|
| 141 |
+
- type: map
|
| 142 |
+
value: 67.2259454062751
|
| 143 |
+
- type: mrr
|
| 144 |
+
value: 79.37508244294948
|
| 145 |
+
- task:
|
| 146 |
+
type: STS
|
| 147 |
+
dataset:
|
| 148 |
+
type: mteb/biosses-sts
|
| 149 |
+
name: MTEB BIOSSES
|
| 150 |
+
config: default
|
| 151 |
+
split: test
|
| 152 |
+
revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
|
| 153 |
+
metrics:
|
| 154 |
+
- type: cos_sim_pearson
|
| 155 |
+
value: 89.5312396547344
|
| 156 |
+
- type: cos_sim_spearman
|
| 157 |
+
value: 87.1447567367366
|
| 158 |
+
- type: euclidean_pearson
|
| 159 |
+
value: 88.67110804544821
|
| 160 |
+
- type: euclidean_spearman
|
| 161 |
+
value: 87.1447567367366
|
| 162 |
+
- type: manhattan_pearson
|
| 163 |
+
value: 89.06983994154335
|
| 164 |
+
- type: manhattan_spearman
|
| 165 |
+
value: 87.59115245033443
|
| 166 |
+
- task:
|
| 167 |
+
type: Classification
|
| 168 |
+
dataset:
|
| 169 |
+
type: mteb/banking77
|
| 170 |
+
name: MTEB Banking77Classification
|
| 171 |
+
config: default
|
| 172 |
+
split: test
|
| 173 |
+
revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
|
| 174 |
+
metrics:
|
| 175 |
+
- type: accuracy
|
| 176 |
+
value: 88.63636363636364
|
| 177 |
+
- type: f1
|
| 178 |
+
value: 88.58740097633193
|
| 179 |
+
- task:
|
| 180 |
+
type: Clustering
|
| 181 |
+
dataset:
|
| 182 |
+
type: mteb/biorxiv-clustering-p2p
|
| 183 |
+
name: MTEB BiorxivClusteringP2P
|
| 184 |
+
config: default
|
| 185 |
+
split: test
|
| 186 |
+
revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
|
| 187 |
+
metrics:
|
| 188 |
+
- type: v_measure
|
| 189 |
+
value: 41.99753263006505
|
| 190 |
+
- task:
|
| 191 |
+
type: Clustering
|
| 192 |
+
dataset:
|
| 193 |
+
type: mteb/biorxiv-clustering-s2s
|
| 194 |
+
name: MTEB BiorxivClusteringS2S
|
| 195 |
+
config: default
|
| 196 |
+
split: test
|
| 197 |
+
revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
|
| 198 |
+
metrics:
|
| 199 |
+
- type: v_measure
|
| 200 |
+
value: 39.623067884052666
|
| 201 |
+
- task:
|
| 202 |
+
type: Retrieval
|
| 203 |
+
dataset:
|
| 204 |
+
type: BeIR/cqadupstack
|
| 205 |
+
name: MTEB CQADupstackRetrieval
|
| 206 |
+
config: default
|
| 207 |
+
split: test
|
| 208 |
+
revision: None
|
| 209 |
+
metrics:
|
| 210 |
+
- type: ndcg_at_1
|
| 211 |
+
value: 30.904666666666664
|
| 212 |
+
- type: ndcg_at_3
|
| 213 |
+
value: 36.32808333333333
|
| 214 |
+
- type: ndcg_at_5
|
| 215 |
+
value: 38.767250000000004
|
| 216 |
+
- type: ndcg_at_10
|
| 217 |
+
value: 41.62008333333333
|
| 218 |
+
- type: ndcg_at_100
|
| 219 |
+
value: 47.118083333333324
|
| 220 |
+
- type: map_at_1
|
| 221 |
+
value: 25.7645
|
| 222 |
+
- type: map_at_3
|
| 223 |
+
value: 32.6235
|
| 224 |
+
- type: map_at_5
|
| 225 |
+
value: 34.347
|
| 226 |
+
- type: map_at_10
|
| 227 |
+
value: 35.79658333333333
|
| 228 |
+
- type: map_at_100
|
| 229 |
+
value: 37.10391666666666
|
| 230 |
+
- type: recall_at_1
|
| 231 |
+
value: 25.7645
|
| 232 |
+
- type: recall_at_3
|
| 233 |
+
value: 39.622666666666674
|
| 234 |
+
- type: recall_at_5
|
| 235 |
+
value: 45.938750000000006
|
| 236 |
+
- type: recall_at_10
|
| 237 |
+
value: 54.43816666666667
|
| 238 |
+
- type: recall_at_100
|
| 239 |
+
value: 78.66183333333333
|
| 240 |
+
- type: precision_at_1
|
| 241 |
+
value: 30.904666666666664
|
| 242 |
+
- type: precision_at_3
|
| 243 |
+
value: 17.099083333333333
|
| 244 |
+
- type: precision_at_5
|
| 245 |
+
value: 12.278416666666669
|
| 246 |
+
- type: precision_at_10
|
| 247 |
+
value: 7.573083333333335
|
| 248 |
+
- type: precision_at_100
|
| 249 |
+
value: 1.22275
|
| 250 |
+
- type: mrr_at_1
|
| 251 |
+
value: 30.904666666666664
|
| 252 |
+
- type: mrr_at_3
|
| 253 |
+
value: 37.458333333333336
|
| 254 |
+
- type: mrr_at_5
|
| 255 |
+
value: 38.97333333333333
|
| 256 |
+
- type: mrr_at_10
|
| 257 |
+
value: 40.10316666666666
|
| 258 |
+
- type: mrr_at_100
|
| 259 |
+
value: 41.004250000000006
|
| 260 |
+
- task:
|
| 261 |
+
type: Retrieval
|
| 262 |
+
dataset:
|
| 263 |
+
type: climate-fever
|
| 264 |
+
name: MTEB ClimateFEVER
|
| 265 |
+
config: default
|
| 266 |
+
split: test
|
| 267 |
+
revision: None
|
| 268 |
+
metrics:
|
| 269 |
+
- type: ndcg_at_1
|
| 270 |
+
value: 38.046
|
| 271 |
+
- type: ndcg_at_3
|
| 272 |
+
value: 31.842
|
| 273 |
+
- type: ndcg_at_5
|
| 274 |
+
value: 33.698
|
| 275 |
+
- type: ndcg_at_10
|
| 276 |
+
value: 37.765
|
| 277 |
+
- type: ndcg_at_100
|
| 278 |
+
value: 44.998
|
| 279 |
+
- type: map_at_1
|
| 280 |
+
value: 16.682
|
| 281 |
+
- type: map_at_3
|
| 282 |
+
value: 23.624000000000002
|
| 283 |
+
- type: map_at_5
|
| 284 |
+
value: 25.812
|
| 285 |
+
- type: map_at_10
|
| 286 |
+
value: 28.017999999999997
|
| 287 |
+
- type: map_at_100
|
| 288 |
+
value: 30.064999999999998
|
| 289 |
+
- type: recall_at_1
|
| 290 |
+
value: 16.682
|
| 291 |
+
- type: recall_at_3
|
| 292 |
+
value: 28.338
|
| 293 |
+
- type: recall_at_5
|
| 294 |
+
value: 34.486
|
| 295 |
+
- type: recall_at_10
|
| 296 |
+
value: 43.474000000000004
|
| 297 |
+
- type: recall_at_100
|
| 298 |
+
value: 67.984
|
| 299 |
+
- type: precision_at_1
|
| 300 |
+
value: 38.046
|
| 301 |
+
- type: precision_at_3
|
| 302 |
+
value: 23.779
|
| 303 |
+
- type: precision_at_5
|
| 304 |
+
value: 17.849999999999998
|
| 305 |
+
- type: precision_at_10
|
| 306 |
+
value: 11.642
|
| 307 |
+
- type: precision_at_100
|
| 308 |
+
value: 1.9429999999999998
|
| 309 |
+
- type: mrr_at_1
|
| 310 |
+
value: 38.046
|
| 311 |
+
- type: mrr_at_3
|
| 312 |
+
value: 46.764
|
| 313 |
+
- type: mrr_at_5
|
| 314 |
+
value: 48.722
|
| 315 |
+
- type: mrr_at_10
|
| 316 |
+
value: 49.976
|
| 317 |
+
- type: mrr_at_100
|
| 318 |
+
value: 50.693999999999996
|
| 319 |
+
- task:
|
| 320 |
+
type: Retrieval
|
| 321 |
+
dataset:
|
| 322 |
+
type: dbpedia-entity
|
| 323 |
+
name: MTEB DBPedia
|
| 324 |
+
config: default
|
| 325 |
+
split: test
|
| 326 |
+
revision: None
|
| 327 |
+
metrics:
|
| 328 |
+
- type: ndcg_at_1
|
| 329 |
+
value: 63.24999999999999
|
| 330 |
+
- type: ndcg_at_3
|
| 331 |
+
value: 54.005
|
| 332 |
+
- type: ndcg_at_5
|
| 333 |
+
value: 51.504000000000005
|
| 334 |
+
- type: ndcg_at_10
|
| 335 |
+
value: 49.738
|
| 336 |
+
- type: ndcg_at_100
|
| 337 |
+
value: 54.754000000000005
|
| 338 |
+
- type: map_at_1
|
| 339 |
+
value: 10.639
|
| 340 |
+
- type: map_at_3
|
| 341 |
+
value: 16.726
|
| 342 |
+
- type: map_at_5
|
| 343 |
+
value: 20.101
|
| 344 |
+
- type: map_at_10
|
| 345 |
+
value: 24.569
|
| 346 |
+
- type: map_at_100
|
| 347 |
+
value: 35.221999999999994
|
| 348 |
+
- type: recall_at_1
|
| 349 |
+
value: 10.639
|
| 350 |
+
- type: recall_at_3
|
| 351 |
+
value: 17.861
|
| 352 |
+
- type: recall_at_5
|
| 353 |
+
value: 22.642
|
| 354 |
+
- type: recall_at_10
|
| 355 |
+
value: 30.105999999999998
|
| 356 |
+
- type: recall_at_100
|
| 357 |
+
value: 60.92999999999999
|
| 358 |
+
- type: precision_at_1
|
| 359 |
+
value: 75.0
|
| 360 |
+
- type: precision_at_3
|
| 361 |
+
value: 58.083
|
| 362 |
+
- type: precision_at_5
|
| 363 |
+
value: 50.0
|
| 364 |
+
- type: precision_at_10
|
| 365 |
+
value: 40.35
|
| 366 |
+
- type: precision_at_100
|
| 367 |
+
value: 12.659999999999998
|
| 368 |
+
- type: mrr_at_1
|
| 369 |
+
value: 75.0
|
| 370 |
+
- type: mrr_at_3
|
| 371 |
+
value: 80.042
|
| 372 |
+
- type: mrr_at_5
|
| 373 |
+
value: 80.779
|
| 374 |
+
- type: mrr_at_10
|
| 375 |
+
value: 81.355
|
| 376 |
+
- type: mrr_at_100
|
| 377 |
+
value: 81.58
|
| 378 |
+
- task:
|
| 379 |
+
type: Classification
|
| 380 |
+
dataset:
|
| 381 |
+
type: mteb/emotion
|
| 382 |
+
name: MTEB EmotionClassification
|
| 383 |
+
config: default
|
| 384 |
+
split: test
|
| 385 |
+
revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
|
| 386 |
+
metrics:
|
| 387 |
+
- type: accuracy
|
| 388 |
+
value: 51.025
|
| 389 |
+
- type: f1
|
| 390 |
+
value: 47.08253474922065
|
| 391 |
+
- task:
|
| 392 |
+
type: Retrieval
|
| 393 |
+
dataset:
|
| 394 |
+
type: fever
|
| 395 |
+
name: MTEB FEVER
|
| 396 |
+
config: default
|
| 397 |
+
split: test
|
| 398 |
+
revision: None
|
| 399 |
+
metrics:
|
| 400 |
+
- type: ndcg_at_1
|
| 401 |
+
value: 82.163
|
| 402 |
+
- type: ndcg_at_3
|
| 403 |
+
value: 86.835
|
| 404 |
+
- type: ndcg_at_5
|
| 405 |
+
value: 87.802
|
| 406 |
+
- type: ndcg_at_10
|
| 407 |
+
value: 88.529
|
| 408 |
+
- type: ndcg_at_100
|
| 409 |
+
value: 89.17
|
| 410 |
+
- type: map_at_1
|
| 411 |
+
value: 76.335
|
| 412 |
+
- type: map_at_3
|
| 413 |
+
value: 83.91499999999999
|
| 414 |
+
- type: map_at_5
|
| 415 |
+
value: 84.64500000000001
|
| 416 |
+
- type: map_at_10
|
| 417 |
+
value: 85.058
|
| 418 |
+
- type: map_at_100
|
| 419 |
+
value: 85.257
|
| 420 |
+
- type: recall_at_1
|
| 421 |
+
value: 76.335
|
| 422 |
+
- type: recall_at_3
|
| 423 |
+
value: 90.608
|
| 424 |
+
- type: recall_at_5
|
| 425 |
+
value: 93.098
|
| 426 |
+
- type: recall_at_10
|
| 427 |
+
value: 95.173
|
| 428 |
+
- type: recall_at_100
|
| 429 |
+
value: 97.59299999999999
|
| 430 |
+
- type: precision_at_1
|
| 431 |
+
value: 82.163
|
| 432 |
+
- type: precision_at_3
|
| 433 |
+
value: 33.257999999999996
|
| 434 |
+
- type: precision_at_5
|
| 435 |
+
value: 20.654
|
| 436 |
+
- type: precision_at_10
|
| 437 |
+
value: 10.674999999999999
|
| 438 |
+
- type: precision_at_100
|
| 439 |
+
value: 1.122
|
| 440 |
+
- type: mrr_at_1
|
| 441 |
+
value: 82.163
|
| 442 |
+
- type: mrr_at_3
|
| 443 |
+
value: 88.346
|
| 444 |
+
- type: mrr_at_5
|
| 445 |
+
value: 88.791
|
| 446 |
+
- type: mrr_at_10
|
| 447 |
+
value: 88.97699999999999
|
| 448 |
+
- type: mrr_at_100
|
| 449 |
+
value: 89.031
|
| 450 |
+
- task:
|
| 451 |
+
type: Retrieval
|
| 452 |
+
dataset:
|
| 453 |
+
type: fiqa
|
| 454 |
+
name: MTEB FiQA2018
|
| 455 |
+
config: default
|
| 456 |
+
split: test
|
| 457 |
+
revision: None
|
| 458 |
+
metrics:
|
| 459 |
+
- type: ndcg_at_1
|
| 460 |
+
value: 55.093
|
| 461 |
+
- type: ndcg_at_3
|
| 462 |
+
value: 52.481
|
| 463 |
+
- type: ndcg_at_5
|
| 464 |
+
value: 53.545
|
| 465 |
+
- type: ndcg_at_10
|
| 466 |
+
value: 56.053
|
| 467 |
+
- type: ndcg_at_100
|
| 468 |
+
value: 62.53999999999999
|
| 469 |
+
- type: map_at_1
|
| 470 |
+
value: 29.189999999999998
|
| 471 |
+
- type: map_at_3
|
| 472 |
+
value: 42.603
|
| 473 |
+
- type: map_at_5
|
| 474 |
+
value: 45.855000000000004
|
| 475 |
+
- type: map_at_10
|
| 476 |
+
value: 48.241
|
| 477 |
+
- type: map_at_100
|
| 478 |
+
value: 50.300999999999995
|
| 479 |
+
- type: recall_at_1
|
| 480 |
+
value: 29.189999999999998
|
| 481 |
+
- type: recall_at_3
|
| 482 |
+
value: 47.471999999999994
|
| 483 |
+
- type: recall_at_5
|
| 484 |
+
value: 54.384
|
| 485 |
+
- type: recall_at_10
|
| 486 |
+
value: 62.731
|
| 487 |
+
- type: recall_at_100
|
| 488 |
+
value: 86.02300000000001
|
| 489 |
+
- type: precision_at_1
|
| 490 |
+
value: 55.093
|
| 491 |
+
- type: precision_at_3
|
| 492 |
+
value: 34.979
|
| 493 |
+
- type: precision_at_5
|
| 494 |
+
value: 25.278
|
| 495 |
+
- type: precision_at_10
|
| 496 |
+
value: 15.231
|
| 497 |
+
- type: precision_at_100
|
| 498 |
+
value: 2.2190000000000003
|
| 499 |
+
- type: mrr_at_1
|
| 500 |
+
value: 55.093
|
| 501 |
+
- type: mrr_at_3
|
| 502 |
+
value: 61.317
|
| 503 |
+
- type: mrr_at_5
|
| 504 |
+
value: 62.358999999999995
|
| 505 |
+
- type: mrr_at_10
|
| 506 |
+
value: 63.165000000000006
|
| 507 |
+
- type: mrr_at_100
|
| 508 |
+
value: 63.81
|
| 509 |
+
- task:
|
| 510 |
+
type: Retrieval
|
| 511 |
+
dataset:
|
| 512 |
+
type: hotpotqa
|
| 513 |
+
name: MTEB HotpotQA
|
| 514 |
+
config: default
|
| 515 |
+
split: test
|
| 516 |
+
revision: None
|
| 517 |
+
metrics:
|
| 518 |
+
- type: ndcg_at_1
|
| 519 |
+
value: 78.866
|
| 520 |
+
- type: ndcg_at_3
|
| 521 |
+
value: 70.128
|
| 522 |
+
- type: ndcg_at_5
|
| 523 |
+
value: 73.017
|
| 524 |
+
- type: ndcg_at_10
|
| 525 |
+
value: 75.166
|
| 526 |
+
- type: ndcg_at_100
|
| 527 |
+
value: 77.97500000000001
|
| 528 |
+
- type: map_at_1
|
| 529 |
+
value: 39.433
|
| 530 |
+
- type: map_at_3
|
| 531 |
+
value: 64.165
|
| 532 |
+
- type: map_at_5
|
| 533 |
+
value: 66.503
|
| 534 |
+
- type: map_at_10
|
| 535 |
+
value: 67.822
|
| 536 |
+
- type: map_at_100
|
| 537 |
+
value: 68.675
|
| 538 |
+
- type: recall_at_1
|
| 539 |
+
value: 39.433
|
| 540 |
+
- type: recall_at_3
|
| 541 |
+
value: 69.03399999999999
|
| 542 |
+
- type: recall_at_5
|
| 543 |
+
value: 74.74
|
| 544 |
+
- type: recall_at_10
|
| 545 |
+
value: 80.108
|
| 546 |
+
- type: recall_at_100
|
| 547 |
+
value: 90.81700000000001
|
| 548 |
+
- type: precision_at_1
|
| 549 |
+
value: 78.866
|
| 550 |
+
- type: precision_at_3
|
| 551 |
+
value: 46.022999999999996
|
| 552 |
+
- type: precision_at_5
|
| 553 |
+
value: 29.896
|
| 554 |
+
- type: precision_at_10
|
| 555 |
+
value: 16.022
|
| 556 |
+
- type: precision_at_100
|
| 557 |
+
value: 1.8159999999999998
|
| 558 |
+
- type: mrr_at_1
|
| 559 |
+
value: 78.866
|
| 560 |
+
- type: mrr_at_3
|
| 561 |
+
value: 83.91
|
| 562 |
+
- type: mrr_at_5
|
| 563 |
+
value: 84.473
|
| 564 |
+
- type: mrr_at_10
|
| 565 |
+
value: 84.769
|
| 566 |
+
- type: mrr_at_100
|
| 567 |
+
value: 84.953
|
| 568 |
+
- task:
|
| 569 |
+
type: Classification
|
| 570 |
+
dataset:
|
| 571 |
+
type: mteb/imdb
|
| 572 |
+
name: MTEB ImdbClassification
|
| 573 |
+
config: default
|
| 574 |
+
split: test
|
| 575 |
+
revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
|
| 576 |
+
metrics:
|
| 577 |
+
- type: accuracy
|
| 578 |
+
value: 94.87799999999999
|
| 579 |
+
- type: ap
|
| 580 |
+
value: 92.5831019543702
|
| 581 |
+
- type: f1
|
| 582 |
+
value: 94.87675087619891
|
| 583 |
+
- task:
|
| 584 |
+
type: Retrieval
|
| 585 |
+
dataset:
|
| 586 |
+
type: msmarco
|
| 587 |
+
name: MTEB MSMARCO
|
| 588 |
+
config: default
|
| 589 |
+
split: test
|
| 590 |
+
revision: None
|
| 591 |
+
metrics:
|
| 592 |
+
- type: ndcg_at_1
|
| 593 |
+
value: 23.195
|
| 594 |
+
- type: ndcg_at_3
|
| 595 |
+
value: 34.419
|
| 596 |
+
- type: ndcg_at_5
|
| 597 |
+
value: 38.665
|
| 598 |
+
- type: ndcg_at_10
|
| 599 |
+
value: 42.549
|
| 600 |
+
- type: ndcg_at_100
|
| 601 |
+
value: 48.256
|
| 602 |
+
- type: map_at_1
|
| 603 |
+
value: 22.508
|
| 604 |
+
- type: map_at_3
|
| 605 |
+
value: 31.346
|
| 606 |
+
- type: map_at_5
|
| 607 |
+
value: 33.73
|
| 608 |
+
- type: map_at_10
|
| 609 |
+
value: 35.365
|
| 610 |
+
- type: map_at_100
|
| 611 |
+
value: 36.568
|
| 612 |
+
- type: recall_at_1
|
| 613 |
+
value: 22.508
|
| 614 |
+
- type: recall_at_3
|
| 615 |
+
value: 42.63
|
| 616 |
+
- type: recall_at_5
|
| 617 |
+
value: 52.827999999999996
|
| 618 |
+
- type: recall_at_10
|
| 619 |
+
value: 64.645
|
| 620 |
+
- type: recall_at_100
|
| 621 |
+
value: 90.852
|
| 622 |
+
- type: precision_at_1
|
| 623 |
+
value: 23.195
|
| 624 |
+
- type: precision_at_3
|
| 625 |
+
value: 14.752
|
| 626 |
+
- type: precision_at_5
|
| 627 |
+
value: 11.0
|
| 628 |
+
- type: precision_at_10
|
| 629 |
+
value: 6.755
|
| 630 |
+
- type: precision_at_100
|
| 631 |
+
value: 0.96
|
| 632 |
+
- type: mrr_at_1
|
| 633 |
+
value: 23.195
|
| 634 |
+
- type: mrr_at_3
|
| 635 |
+
value: 32.042
|
| 636 |
+
- type: mrr_at_5
|
| 637 |
+
value: 34.388000000000005
|
| 638 |
+
- type: mrr_at_10
|
| 639 |
+
value: 35.974000000000004
|
| 640 |
+
- type: mrr_at_100
|
| 641 |
+
value: 37.114000000000004
|
| 642 |
+
- task:
|
| 643 |
+
type: Classification
|
| 644 |
+
dataset:
|
| 645 |
+
type: mteb/mtop_domain
|
| 646 |
+
name: MTEB MTOPDomainClassification (en)
|
| 647 |
+
config: en
|
| 648 |
+
split: test
|
| 649 |
+
revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
|
| 650 |
+
metrics:
|
| 651 |
+
- type: accuracy
|
| 652 |
+
value: 95.84587323301413
|
| 653 |
+
- type: f1
|
| 654 |
+
value: 95.69948889844318
|
| 655 |
+
- task:
|
| 656 |
+
type: Classification
|
| 657 |
+
dataset:
|
| 658 |
+
type: mteb/mtop_intent
|
| 659 |
+
name: MTEB MTOPIntentClassification (en)
|
| 660 |
+
config: en
|
| 661 |
+
split: test
|
| 662 |
+
revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
|
| 663 |
+
metrics:
|
| 664 |
+
- type: accuracy
|
| 665 |
+
value: 87.08162334701322
|
| 666 |
+
- type: f1
|
| 667 |
+
value: 72.237783326283
|
| 668 |
+
- task:
|
| 669 |
+
type: Classification
|
| 670 |
+
dataset:
|
| 671 |
+
type: mteb/amazon_massive_intent
|
| 672 |
+
name: MTEB MassiveIntentClassification (en)
|
| 673 |
+
config: en
|
| 674 |
+
split: test
|
| 675 |
+
revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
|
| 676 |
+
metrics:
|
| 677 |
+
- type: accuracy
|
| 678 |
+
value: 80.19502353732346
|
| 679 |
+
- type: f1
|
| 680 |
+
value: 77.732184986995
|
| 681 |
+
- task:
|
| 682 |
+
type: Classification
|
| 683 |
+
dataset:
|
| 684 |
+
type: mteb/amazon_massive_scenario
|
| 685 |
+
name: MTEB MassiveScenarioClassification (en)
|
| 686 |
+
config: en
|
| 687 |
+
split: test
|
| 688 |
+
revision: 7d571f92784cd94a019292a1f45445077d0ef634
|
| 689 |
+
metrics:
|
| 690 |
+
- type: accuracy
|
| 691 |
+
value: 82.26630800268998
|
| 692 |
+
- type: f1
|
| 693 |
+
value: 82.12747916248556
|
| 694 |
+
- task:
|
| 695 |
+
type: Clustering
|
| 696 |
+
dataset:
|
| 697 |
+
type: mteb/medrxiv-clustering-p2p
|
| 698 |
+
name: MTEB MedrxivClusteringP2P
|
| 699 |
+
config: default
|
| 700 |
+
split: test
|
| 701 |
+
revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
|
| 702 |
+
metrics:
|
| 703 |
+
- type: v_measure
|
| 704 |
+
value: 36.95240450167033
|
| 705 |
+
- task:
|
| 706 |
+
type: Clustering
|
| 707 |
+
dataset:
|
| 708 |
+
type: mteb/medrxiv-clustering-s2s
|
| 709 |
+
name: MTEB MedrxivClusteringS2S
|
| 710 |
+
config: default
|
| 711 |
+
split: test
|
| 712 |
+
revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
|
| 713 |
+
metrics:
|
| 714 |
+
- type: v_measure
|
| 715 |
+
value: 36.27758530931266
|
| 716 |
+
- task:
|
| 717 |
+
type: Reranking
|
| 718 |
+
dataset:
|
| 719 |
+
type: mteb/mind_small
|
| 720 |
+
name: MTEB MindSmallReranking
|
| 721 |
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config: default
|
| 722 |
+
split: test
|
| 723 |
+
revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
|
| 724 |
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metrics:
|
| 725 |
+
- type: map
|
| 726 |
+
value: 33.35707665482982
|
| 727 |
+
- type: mrr
|
| 728 |
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value: 34.60987842278547
|
| 729 |
+
- task:
|
| 730 |
+
type: Retrieval
|
| 731 |
+
dataset:
|
| 732 |
+
type: nfcorpus
|
| 733 |
+
name: MTEB NFCorpus
|
| 734 |
+
config: default
|
| 735 |
+
split: test
|
| 736 |
+
revision: None
|
| 737 |
+
metrics:
|
| 738 |
+
- type: ndcg_at_1
|
| 739 |
+
value: 47.522999999999996
|
| 740 |
+
- type: ndcg_at_3
|
| 741 |
+
value: 44.489000000000004
|
| 742 |
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- type: ndcg_at_5
|
| 743 |
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value: 41.92
|
| 744 |
+
- type: ndcg_at_10
|
| 745 |
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value: 38.738
|
| 746 |
+
- type: ndcg_at_100
|
| 747 |
+
value: 35.46
|
| 748 |
+
- type: map_at_1
|
| 749 |
+
value: 5.357
|
| 750 |
+
- type: map_at_3
|
| 751 |
+
value: 10.537
|
| 752 |
+
- type: map_at_5
|
| 753 |
+
value: 12.062000000000001
|
| 754 |
+
- type: map_at_10
|
| 755 |
+
value: 14.264
|
| 756 |
+
- type: map_at_100
|
| 757 |
+
value: 18.442
|
| 758 |
+
- type: recall_at_1
|
| 759 |
+
value: 5.357
|
| 760 |
+
- type: recall_at_3
|
| 761 |
+
value: 12.499
|
| 762 |
+
- type: recall_at_5
|
| 763 |
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value: 14.809
|
| 764 |
+
- type: recall_at_10
|
| 765 |
+
value: 18.765
|
| 766 |
+
- type: recall_at_100
|
| 767 |
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value: 36.779
|
| 768 |
+
- type: precision_at_1
|
| 769 |
+
value: 49.226
|
| 770 |
+
- type: precision_at_3
|
| 771 |
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value: 41.899
|
| 772 |
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- type: precision_at_5
|
| 773 |
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value: 36.718
|
| 774 |
+
- type: precision_at_10
|
| 775 |
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value: 29.287999999999997
|
| 776 |
+
- type: precision_at_100
|
| 777 |
+
value: 9.22
|
| 778 |
+
- type: mrr_at_1
|
| 779 |
+
value: 49.845
|
| 780 |
+
- type: mrr_at_3
|
| 781 |
+
value: 57.121
|
| 782 |
+
- type: mrr_at_5
|
| 783 |
+
value: 58.172999999999995
|
| 784 |
+
- type: mrr_at_10
|
| 785 |
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value: 58.906000000000006
|
| 786 |
+
- type: mrr_at_100
|
| 787 |
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value: 59.486000000000004
|
| 788 |
+
- task:
|
| 789 |
+
type: Retrieval
|
| 790 |
+
dataset:
|
| 791 |
+
type: nq
|
| 792 |
+
name: MTEB NQ
|
| 793 |
+
config: default
|
| 794 |
+
split: test
|
| 795 |
+
revision: None
|
| 796 |
+
metrics:
|
| 797 |
+
- type: ndcg_at_1
|
| 798 |
+
value: 42.815999999999995
|
| 799 |
+
- type: ndcg_at_3
|
| 800 |
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value: 53.766999999999996
|
| 801 |
+
- type: ndcg_at_5
|
| 802 |
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value: 57.957
|
| 803 |
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- type: ndcg_at_10
|
| 804 |
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value: 61.661
|
| 805 |
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- type: ndcg_at_100
|
| 806 |
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value: 65.218
|
| 807 |
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- type: map_at_1
|
| 808 |
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value: 38.364
|
| 809 |
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- type: map_at_3
|
| 810 |
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value: 49.782
|
| 811 |
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- type: map_at_5
|
| 812 |
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value: 52.319
|
| 813 |
+
- type: map_at_10
|
| 814 |
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value: 54.07300000000001
|
| 815 |
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- type: map_at_100
|
| 816 |
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value: 54.983000000000004
|
| 817 |
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- type: recall_at_1
|
| 818 |
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value: 38.364
|
| 819 |
+
- type: recall_at_3
|
| 820 |
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value: 61.744
|
| 821 |
+
- type: recall_at_5
|
| 822 |
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value: 71.32300000000001
|
| 823 |
+
- type: recall_at_10
|
| 824 |
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value: 82.015
|
| 825 |
+
- type: recall_at_100
|
| 826 |
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value: 96.978
|
| 827 |
+
- type: precision_at_1
|
| 828 |
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value: 42.815999999999995
|
| 829 |
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- type: precision_at_3
|
| 830 |
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value: 23.976
|
| 831 |
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- type: precision_at_5
|
| 832 |
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value: 16.866
|
| 833 |
+
- type: precision_at_10
|
| 834 |
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value: 9.806
|
| 835 |
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- type: precision_at_100
|
| 836 |
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value: 1.1769999999999998
|
| 837 |
+
- type: mrr_at_1
|
| 838 |
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value: 42.845
|
| 839 |
+
- type: mrr_at_3
|
| 840 |
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value: 53.307
|
| 841 |
+
- type: mrr_at_5
|
| 842 |
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value: 55.434000000000005
|
| 843 |
+
- type: mrr_at_10
|
| 844 |
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value: 56.702
|
| 845 |
+
- type: mrr_at_100
|
| 846 |
+
value: 57.342000000000006
|
| 847 |
+
- task:
|
| 848 |
+
type: Retrieval
|
| 849 |
+
dataset:
|
| 850 |
+
type: quora
|
| 851 |
+
name: MTEB QuoraRetrieval
|
| 852 |
+
config: default
|
| 853 |
+
split: test
|
| 854 |
+
revision: None
|
| 855 |
+
metrics:
|
| 856 |
+
- type: ndcg_at_1
|
| 857 |
+
value: 82.46
|
| 858 |
+
- type: ndcg_at_3
|
| 859 |
+
value: 86.774
|
| 860 |
+
- type: ndcg_at_5
|
| 861 |
+
value: 88.256
|
| 862 |
+
- type: ndcg_at_10
|
| 863 |
+
value: 89.35
|
| 864 |
+
- type: ndcg_at_100
|
| 865 |
+
value: 90.46499999999999
|
| 866 |
+
- type: map_at_1
|
| 867 |
+
value: 71.562
|
| 868 |
+
- type: map_at_3
|
| 869 |
+
value: 82.948
|
| 870 |
+
- type: map_at_5
|
| 871 |
+
value: 84.786
|
| 872 |
+
- type: map_at_10
|
| 873 |
+
value: 85.82300000000001
|
| 874 |
+
- type: map_at_100
|
| 875 |
+
value: 86.453
|
| 876 |
+
- type: recall_at_1
|
| 877 |
+
value: 71.562
|
| 878 |
+
- type: recall_at_3
|
| 879 |
+
value: 88.51
|
| 880 |
+
- type: recall_at_5
|
| 881 |
+
value: 92.795
|
| 882 |
+
- type: recall_at_10
|
| 883 |
+
value: 95.998
|
| 884 |
+
- type: recall_at_100
|
| 885 |
+
value: 99.701
|
| 886 |
+
- type: precision_at_1
|
| 887 |
+
value: 82.46
|
| 888 |
+
- type: precision_at_3
|
| 889 |
+
value: 38.1
|
| 890 |
+
- type: precision_at_5
|
| 891 |
+
value: 24.990000000000002
|
| 892 |
+
- type: precision_at_10
|
| 893 |
+
value: 13.553999999999998
|
| 894 |
+
- type: precision_at_100
|
| 895 |
+
value: 1.539
|
| 896 |
+
- type: mrr_at_1
|
| 897 |
+
value: 82.43
|
| 898 |
+
- type: mrr_at_3
|
| 899 |
+
value: 87.653
|
| 900 |
+
- type: mrr_at_5
|
| 901 |
+
value: 88.26899999999999
|
| 902 |
+
- type: mrr_at_10
|
| 903 |
+
value: 88.505
|
| 904 |
+
- type: mrr_at_100
|
| 905 |
+
value: 88.601
|
| 906 |
+
- task:
|
| 907 |
+
type: Clustering
|
| 908 |
+
dataset:
|
| 909 |
+
type: mteb/reddit-clustering
|
| 910 |
+
name: MTEB RedditClustering
|
| 911 |
+
config: default
|
| 912 |
+
split: test
|
| 913 |
+
revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
|
| 914 |
+
metrics:
|
| 915 |
+
- type: v_measure
|
| 916 |
+
value: 57.928338007609256
|
| 917 |
+
- task:
|
| 918 |
+
type: Clustering
|
| 919 |
+
dataset:
|
| 920 |
+
type: mteb/reddit-clustering-p2p
|
| 921 |
+
name: MTEB RedditClusteringP2P
|
| 922 |
+
config: default
|
| 923 |
+
split: test
|
| 924 |
+
revision: 282350215ef01743dc01b456c7f5241fa8937f16
|
| 925 |
+
metrics:
|
| 926 |
+
- type: v_measure
|
| 927 |
+
value: 65.28915417473826
|
| 928 |
+
- task:
|
| 929 |
+
type: Retrieval
|
| 930 |
+
dataset:
|
| 931 |
+
type: scidocs
|
| 932 |
+
name: MTEB SCIDOCS
|
| 933 |
+
config: default
|
| 934 |
+
split: test
|
| 935 |
+
revision: None
|
| 936 |
+
metrics:
|
| 937 |
+
- type: ndcg_at_1
|
| 938 |
+
value: 17.2
|
| 939 |
+
- type: ndcg_at_3
|
| 940 |
+
value: 15.856
|
| 941 |
+
- type: ndcg_at_5
|
| 942 |
+
value: 13.983
|
| 943 |
+
- type: ndcg_at_10
|
| 944 |
+
value: 16.628999999999998
|
| 945 |
+
- type: ndcg_at_100
|
| 946 |
+
value: 23.845
|
| 947 |
+
- type: map_at_1
|
| 948 |
+
value: 3.4750000000000005
|
| 949 |
+
- type: map_at_3
|
| 950 |
+
value: 6.905
|
| 951 |
+
- type: map_at_5
|
| 952 |
+
value: 8.254
|
| 953 |
+
- type: map_at_10
|
| 954 |
+
value: 9.474
|
| 955 |
+
- type: map_at_100
|
| 956 |
+
value: 11.242
|
| 957 |
+
- type: recall_at_1
|
| 958 |
+
value: 3.4750000000000005
|
| 959 |
+
- type: recall_at_3
|
| 960 |
+
value: 9.298
|
| 961 |
+
- type: recall_at_5
|
| 962 |
+
value: 12.817
|
| 963 |
+
- type: recall_at_10
|
| 964 |
+
value: 17.675
|
| 965 |
+
- type: recall_at_100
|
| 966 |
+
value: 38.678000000000004
|
| 967 |
+
- type: precision_at_1
|
| 968 |
+
value: 17.2
|
| 969 |
+
- type: precision_at_3
|
| 970 |
+
value: 15.299999999999999
|
| 971 |
+
- type: precision_at_5
|
| 972 |
+
value: 12.64
|
| 973 |
+
- type: precision_at_10
|
| 974 |
+
value: 8.72
|
| 975 |
+
- type: precision_at_100
|
| 976 |
+
value: 1.907
|
| 977 |
+
- type: mrr_at_1
|
| 978 |
+
value: 17.2
|
| 979 |
+
- type: mrr_at_3
|
| 980 |
+
value: 25.55
|
| 981 |
+
- type: mrr_at_5
|
| 982 |
+
value: 27.485
|
| 983 |
+
- type: mrr_at_10
|
| 984 |
+
value: 28.809
|
| 985 |
+
- type: mrr_at_100
|
| 986 |
+
value: 29.964000000000002
|
| 987 |
+
- task:
|
| 988 |
+
type: STS
|
| 989 |
+
dataset:
|
| 990 |
+
type: mteb/sickr-sts
|
| 991 |
+
name: MTEB SICK-R
|
| 992 |
+
config: default
|
| 993 |
+
split: test
|
| 994 |
+
revision: a6ea5a8cab320b040a23452cc28066d9beae2cee
|
| 995 |
+
metrics:
|
| 996 |
+
- type: cos_sim_pearson
|
| 997 |
+
value: 86.10434430387332
|
| 998 |
+
- type: cos_sim_spearman
|
| 999 |
+
value: 82.46041161692649
|
| 1000 |
+
- type: euclidean_pearson
|
| 1001 |
+
value: 83.4010092798136
|
| 1002 |
+
- type: euclidean_spearman
|
| 1003 |
+
value: 82.46040715308601
|
| 1004 |
+
- type: manhattan_pearson
|
| 1005 |
+
value: 83.6702316837156
|
| 1006 |
+
- type: manhattan_spearman
|
| 1007 |
+
value: 82.72271392303014
|
| 1008 |
+
- task:
|
| 1009 |
+
type: STS
|
| 1010 |
+
dataset:
|
| 1011 |
+
type: mteb/sts12-sts
|
| 1012 |
+
name: MTEB STS12
|
| 1013 |
+
config: default
|
| 1014 |
+
split: test
|
| 1015 |
+
revision: a0d554a64d88156834ff5ae9920b964011b16384
|
| 1016 |
+
metrics:
|
| 1017 |
+
- type: cos_sim_pearson
|
| 1018 |
+
value: 87.3179771524676
|
| 1019 |
+
- type: cos_sim_spearman
|
| 1020 |
+
value: 80.15194914870666
|
| 1021 |
+
- type: euclidean_pearson
|
| 1022 |
+
value: 84.54005271342946
|
| 1023 |
+
- type: euclidean_spearman
|
| 1024 |
+
value: 80.15194914870666
|
| 1025 |
+
- type: manhattan_pearson
|
| 1026 |
+
value: 85.24410357734307
|
| 1027 |
+
- type: manhattan_spearman
|
| 1028 |
+
value: 80.78274673604562
|
| 1029 |
+
- task:
|
| 1030 |
+
type: STS
|
| 1031 |
+
dataset:
|
| 1032 |
+
type: mteb/sts13-sts
|
| 1033 |
+
name: MTEB STS13
|
| 1034 |
+
config: default
|
| 1035 |
+
split: test
|
| 1036 |
+
revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
|
| 1037 |
+
metrics:
|
| 1038 |
+
- type: cos_sim_pearson
|
| 1039 |
+
value: 89.2691354894402
|
| 1040 |
+
- type: cos_sim_spearman
|
| 1041 |
+
value: 89.94300436293618
|
| 1042 |
+
- type: euclidean_pearson
|
| 1043 |
+
value: 89.5600067781475
|
| 1044 |
+
- type: euclidean_spearman
|
| 1045 |
+
value: 89.942989691344
|
| 1046 |
+
- type: manhattan_pearson
|
| 1047 |
+
value: 89.80327997794308
|
| 1048 |
+
- type: manhattan_spearman
|
| 1049 |
+
value: 90.3964860275568
|
| 1050 |
+
- task:
|
| 1051 |
+
type: STS
|
| 1052 |
+
dataset:
|
| 1053 |
+
type: mteb/sts14-sts
|
| 1054 |
+
name: MTEB STS14
|
| 1055 |
+
config: default
|
| 1056 |
+
split: test
|
| 1057 |
+
revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
|
| 1058 |
+
metrics:
|
| 1059 |
+
- type: cos_sim_pearson
|
| 1060 |
+
value: 87.68003396295498
|
| 1061 |
+
- type: cos_sim_spearman
|
| 1062 |
+
value: 86.23848649310362
|
| 1063 |
+
- type: euclidean_pearson
|
| 1064 |
+
value: 87.0702308813695
|
| 1065 |
+
- type: euclidean_spearman
|
| 1066 |
+
value: 86.23848649310362
|
| 1067 |
+
- type: manhattan_pearson
|
| 1068 |
+
value: 87.24495415360472
|
| 1069 |
+
- type: manhattan_spearman
|
| 1070 |
+
value: 86.58198464997109
|
| 1071 |
+
- task:
|
| 1072 |
+
type: STS
|
| 1073 |
+
dataset:
|
| 1074 |
+
type: mteb/sts15-sts
|
| 1075 |
+
name: MTEB STS15
|
| 1076 |
+
config: default
|
| 1077 |
+
split: test
|
| 1078 |
+
revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
|
| 1079 |
+
metrics:
|
| 1080 |
+
- type: cos_sim_pearson
|
| 1081 |
+
value: 90.25643329096215
|
| 1082 |
+
- type: cos_sim_spearman
|
| 1083 |
+
value: 91.19520084590636
|
| 1084 |
+
- type: euclidean_pearson
|
| 1085 |
+
value: 90.68579446788728
|
| 1086 |
+
- type: euclidean_spearman
|
| 1087 |
+
value: 91.19519611831312
|
| 1088 |
+
- type: manhattan_pearson
|
| 1089 |
+
value: 90.83476867273104
|
| 1090 |
+
- type: manhattan_spearman
|
| 1091 |
+
value: 91.4569817842705
|
| 1092 |
+
- task:
|
| 1093 |
+
type: STS
|
| 1094 |
+
dataset:
|
| 1095 |
+
type: mteb/sts16-sts
|
| 1096 |
+
name: MTEB STS16
|
| 1097 |
+
config: default
|
| 1098 |
+
split: test
|
| 1099 |
+
revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
|
| 1100 |
+
metrics:
|
| 1101 |
+
- type: cos_sim_pearson
|
| 1102 |
+
value: 86.41175694023282
|
| 1103 |
+
- type: cos_sim_spearman
|
| 1104 |
+
value: 88.18744495989392
|
| 1105 |
+
- type: euclidean_pearson
|
| 1106 |
+
value: 87.60085709987156
|
| 1107 |
+
- type: euclidean_spearman
|
| 1108 |
+
value: 88.18773792681107
|
| 1109 |
+
- type: manhattan_pearson
|
| 1110 |
+
value: 87.83199472909764
|
| 1111 |
+
- type: manhattan_spearman
|
| 1112 |
+
value: 88.45824161471776
|
| 1113 |
+
- task:
|
| 1114 |
+
type: STS
|
| 1115 |
+
dataset:
|
| 1116 |
+
type: mteb/sts17-crosslingual-sts
|
| 1117 |
+
name: MTEB STS17 (en-en)
|
| 1118 |
+
config: en-en
|
| 1119 |
+
split: test
|
| 1120 |
+
revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
|
| 1121 |
+
metrics:
|
| 1122 |
+
- type: cos_sim_pearson
|
| 1123 |
+
value: 91.78311335565503
|
| 1124 |
+
- type: cos_sim_spearman
|
| 1125 |
+
value: 91.93416269793802
|
| 1126 |
+
- type: euclidean_pearson
|
| 1127 |
+
value: 91.84163160890154
|
| 1128 |
+
- type: euclidean_spearman
|
| 1129 |
+
value: 91.93416269793802
|
| 1130 |
+
- type: manhattan_pearson
|
| 1131 |
+
value: 91.77053255749301
|
| 1132 |
+
- type: manhattan_spearman
|
| 1133 |
+
value: 91.67392623286098
|
| 1134 |
+
- task:
|
| 1135 |
+
type: STS
|
| 1136 |
+
dataset:
|
| 1137 |
+
type: mteb/sts22-crosslingual-sts
|
| 1138 |
+
name: MTEB STS22 (en)
|
| 1139 |
+
config: en
|
| 1140 |
+
split: test
|
| 1141 |
+
revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80
|
| 1142 |
+
metrics:
|
| 1143 |
+
- type: cos_sim_pearson
|
| 1144 |
+
value: 68.2137857919086
|
| 1145 |
+
- type: cos_sim_spearman
|
| 1146 |
+
value: 68.31928639693375
|
| 1147 |
+
- type: euclidean_pearson
|
| 1148 |
+
value: 69.96072053688385
|
| 1149 |
+
- type: euclidean_spearman
|
| 1150 |
+
value: 68.31928639693375
|
| 1151 |
+
- type: manhattan_pearson
|
| 1152 |
+
value: 70.47736299273389
|
| 1153 |
+
- type: manhattan_spearman
|
| 1154 |
+
value: 68.72439259356818
|
| 1155 |
+
- task:
|
| 1156 |
+
type: STS
|
| 1157 |
+
dataset:
|
| 1158 |
+
type: mteb/stsbenchmark-sts
|
| 1159 |
+
name: MTEB STSBenchmark
|
| 1160 |
+
config: default
|
| 1161 |
+
split: test
|
| 1162 |
+
revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
|
| 1163 |
+
metrics:
|
| 1164 |
+
- type: cos_sim_pearson
|
| 1165 |
+
value: 88.16092476703817
|
| 1166 |
+
- type: cos_sim_spearman
|
| 1167 |
+
value: 89.20507562822989
|
| 1168 |
+
- type: euclidean_pearson
|
| 1169 |
+
value: 88.91358225424611
|
| 1170 |
+
- type: euclidean_spearman
|
| 1171 |
+
value: 89.20505548241839
|
| 1172 |
+
- type: manhattan_pearson
|
| 1173 |
+
value: 88.98787306839809
|
| 1174 |
+
- type: manhattan_spearman
|
| 1175 |
+
value: 89.37338458483269
|
| 1176 |
+
- task:
|
| 1177 |
+
type: Reranking
|
| 1178 |
+
dataset:
|
| 1179 |
+
type: mteb/scidocs-reranking
|
| 1180 |
+
name: MTEB SciDocsRR
|
| 1181 |
+
config: default
|
| 1182 |
+
split: test
|
| 1183 |
+
revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
|
| 1184 |
+
metrics:
|
| 1185 |
+
- type: map
|
| 1186 |
+
value: 87.29108971888714
|
| 1187 |
+
- type: mrr
|
| 1188 |
+
value: 96.62042024787124
|
| 1189 |
+
- task:
|
| 1190 |
+
type: Retrieval
|
| 1191 |
+
dataset:
|
| 1192 |
+
type: scifact
|
| 1193 |
+
name: MTEB SciFact
|
| 1194 |
+
config: default
|
| 1195 |
+
split: test
|
| 1196 |
+
revision: None
|
| 1197 |
+
metrics:
|
| 1198 |
+
- type: ndcg_at_1
|
| 1199 |
+
value: 63.333
|
| 1200 |
+
- type: ndcg_at_3
|
| 1201 |
+
value: 72.768
|
| 1202 |
+
- type: ndcg_at_5
|
| 1203 |
+
value: 75.124
|
| 1204 |
+
- type: ndcg_at_10
|
| 1205 |
+
value: 77.178
|
| 1206 |
+
- type: ndcg_at_100
|
| 1207 |
+
value: 78.769
|
| 1208 |
+
- type: map_at_1
|
| 1209 |
+
value: 60.9
|
| 1210 |
+
- type: map_at_3
|
| 1211 |
+
value: 69.69999999999999
|
| 1212 |
+
- type: map_at_5
|
| 1213 |
+
value: 71.345
|
| 1214 |
+
- type: map_at_10
|
| 1215 |
+
value: 72.36200000000001
|
| 1216 |
+
- type: map_at_100
|
| 1217 |
+
value: 72.783
|
| 1218 |
+
- type: recall_at_1
|
| 1219 |
+
value: 60.9
|
| 1220 |
+
- type: recall_at_3
|
| 1221 |
+
value: 79.172
|
| 1222 |
+
- type: recall_at_5
|
| 1223 |
+
value: 84.917
|
| 1224 |
+
- type: recall_at_10
|
| 1225 |
+
value: 90.756
|
| 1226 |
+
- type: recall_at_100
|
| 1227 |
+
value: 97.667
|
| 1228 |
+
- type: precision_at_1
|
| 1229 |
+
value: 63.333
|
| 1230 |
+
- type: precision_at_3
|
| 1231 |
+
value: 28.555999999999997
|
| 1232 |
+
- type: precision_at_5
|
| 1233 |
+
value: 18.8
|
| 1234 |
+
- type: precision_at_10
|
| 1235 |
+
value: 10.233
|
| 1236 |
+
- type: precision_at_100
|
| 1237 |
+
value: 1.107
|
| 1238 |
+
- type: mrr_at_1
|
| 1239 |
+
value: 63.333
|
| 1240 |
+
- type: mrr_at_3
|
| 1241 |
+
value: 71.27799999999999
|
| 1242 |
+
- type: mrr_at_5
|
| 1243 |
+
value: 72.478
|
| 1244 |
+
- type: mrr_at_10
|
| 1245 |
+
value: 73.163
|
| 1246 |
+
- type: mrr_at_100
|
| 1247 |
+
value: 73.457
|
| 1248 |
+
- task:
|
| 1249 |
+
type: PairClassification
|
| 1250 |
+
dataset:
|
| 1251 |
+
type: mteb/sprintduplicatequestions-pairclassification
|
| 1252 |
+
name: MTEB SprintDuplicateQuestions
|
| 1253 |
+
config: default
|
| 1254 |
+
split: test
|
| 1255 |
+
revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
|
| 1256 |
+
metrics:
|
| 1257 |
+
- type: cos_sim_accuracy
|
| 1258 |
+
value: 99.8009900990099
|
| 1259 |
+
- type: cos_sim_ap
|
| 1260 |
+
value: 95.46920445134404
|
| 1261 |
+
- type: cos_sim_f1
|
| 1262 |
+
value: 89.70814132104455
|
| 1263 |
+
- type: cos_sim_precision
|
| 1264 |
+
value: 91.9202518363064
|
| 1265 |
+
- type: cos_sim_recall
|
| 1266 |
+
value: 87.6
|
| 1267 |
+
- type: dot_accuracy
|
| 1268 |
+
value: 99.8009900990099
|
| 1269 |
+
- type: dot_ap
|
| 1270 |
+
value: 95.46920445134404
|
| 1271 |
+
- type: dot_f1
|
| 1272 |
+
value: 89.70814132104455
|
| 1273 |
+
- type: dot_precision
|
| 1274 |
+
value: 91.9202518363064
|
| 1275 |
+
- type: dot_recall
|
| 1276 |
+
value: 87.6
|
| 1277 |
+
- type: euclidean_accuracy
|
| 1278 |
+
value: 99.8009900990099
|
| 1279 |
+
- type: euclidean_ap
|
| 1280 |
+
value: 95.46924273007079
|
| 1281 |
+
- type: euclidean_f1
|
| 1282 |
+
value: 89.70814132104455
|
| 1283 |
+
- type: euclidean_precision
|
| 1284 |
+
value: 91.9202518363064
|
| 1285 |
+
- type: euclidean_recall
|
| 1286 |
+
value: 87.6
|
| 1287 |
+
- type: manhattan_accuracy
|
| 1288 |
+
value: 99.81188118811882
|
| 1289 |
+
- type: manhattan_ap
|
| 1290 |
+
value: 95.77631677784113
|
| 1291 |
+
- type: manhattan_f1
|
| 1292 |
+
value: 90.26639344262296
|
| 1293 |
+
- type: manhattan_precision
|
| 1294 |
+
value: 92.5420168067227
|
| 1295 |
+
- type: manhattan_recall
|
| 1296 |
+
value: 88.1
|
| 1297 |
+
- type: max_accuracy
|
| 1298 |
+
value: 99.81188118811882
|
| 1299 |
+
- type: max_ap
|
| 1300 |
+
value: 95.77631677784113
|
| 1301 |
+
- type: max_f1
|
| 1302 |
+
value: 90.26639344262296
|
| 1303 |
+
- task:
|
| 1304 |
+
type: Clustering
|
| 1305 |
+
dataset:
|
| 1306 |
+
type: mteb/stackexchange-clustering
|
| 1307 |
+
name: MTEB StackExchangeClustering
|
| 1308 |
+
config: default
|
| 1309 |
+
split: test
|
| 1310 |
+
revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
|
| 1311 |
+
metrics:
|
| 1312 |
+
- type: v_measure
|
| 1313 |
+
value: 71.59238280333025
|
| 1314 |
+
- task:
|
| 1315 |
+
type: Clustering
|
| 1316 |
+
dataset:
|
| 1317 |
+
type: mteb/stackexchange-clustering-p2p
|
| 1318 |
+
name: MTEB StackExchangeClusteringP2P
|
| 1319 |
+
config: default
|
| 1320 |
+
split: test
|
| 1321 |
+
revision: 815ca46b2622cec33ccafc3735d572c266efdb44
|
| 1322 |
+
metrics:
|
| 1323 |
+
- type: v_measure
|
| 1324 |
+
value: 39.012562075214035
|
| 1325 |
+
- task:
|
| 1326 |
+
type: Reranking
|
| 1327 |
+
dataset:
|
| 1328 |
+
type: mteb/stackoverflowdupquestions-reranking
|
| 1329 |
+
name: MTEB StackOverflowDupQuestions
|
| 1330 |
+
config: default
|
| 1331 |
+
split: test
|
| 1332 |
+
revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
|
| 1333 |
+
metrics:
|
| 1334 |
+
- type: map
|
| 1335 |
+
value: 55.16521497700657
|
| 1336 |
+
- type: mrr
|
| 1337 |
+
value: 56.1779427680163
|
| 1338 |
+
- task:
|
| 1339 |
+
type: Summarization
|
| 1340 |
+
dataset:
|
| 1341 |
+
type: mteb/summeval
|
| 1342 |
+
name: MTEB SummEval
|
| 1343 |
+
config: default
|
| 1344 |
+
split: test
|
| 1345 |
+
revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
|
| 1346 |
+
metrics:
|
| 1347 |
+
- type: cos_sim_pearson
|
| 1348 |
+
value: 31.04402552863106
|
| 1349 |
+
- type: cos_sim_spearman
|
| 1350 |
+
value: 31.05558230938988
|
| 1351 |
+
- type: dot_pearson
|
| 1352 |
+
value: 31.04400838015153
|
| 1353 |
+
- type: dot_spearman
|
| 1354 |
+
value: 31.05558230938988
|
| 1355 |
+
- task:
|
| 1356 |
+
type: Retrieval
|
| 1357 |
+
dataset:
|
| 1358 |
+
type: trec-covid
|
| 1359 |
+
name: MTEB TRECCOVID
|
| 1360 |
+
config: default
|
| 1361 |
+
split: test
|
| 1362 |
+
revision: None
|
| 1363 |
+
metrics:
|
| 1364 |
+
- type: ndcg_at_1
|
| 1365 |
+
value: 91.0
|
| 1366 |
+
- type: ndcg_at_3
|
| 1367 |
+
value: 92.34599999999999
|
| 1368 |
+
- type: ndcg_at_5
|
| 1369 |
+
value: 90.89399999999999
|
| 1370 |
+
- type: ndcg_at_10
|
| 1371 |
+
value: 87.433
|
| 1372 |
+
- type: ndcg_at_100
|
| 1373 |
+
value: 67.06400000000001
|
| 1374 |
+
- type: map_at_1
|
| 1375 |
+
value: 0.241
|
| 1376 |
+
- type: map_at_3
|
| 1377 |
+
value: 0.735
|
| 1378 |
+
- type: map_at_5
|
| 1379 |
+
value: 1.216
|
| 1380 |
+
- type: map_at_10
|
| 1381 |
+
value: 2.317
|
| 1382 |
+
- type: map_at_100
|
| 1383 |
+
value: 14.151
|
| 1384 |
+
- type: recall_at_1
|
| 1385 |
+
value: 0.241
|
| 1386 |
+
- type: recall_at_3
|
| 1387 |
+
value: 0.76
|
| 1388 |
+
- type: recall_at_5
|
| 1389 |
+
value: 1.254
|
| 1390 |
+
- type: recall_at_10
|
| 1391 |
+
value: 2.421
|
| 1392 |
+
- type: recall_at_100
|
| 1393 |
+
value: 16.715
|
| 1394 |
+
- type: precision_at_1
|
| 1395 |
+
value: 94.0
|
| 1396 |
+
- type: precision_at_3
|
| 1397 |
+
value: 96.0
|
| 1398 |
+
- type: precision_at_5
|
| 1399 |
+
value: 94.8
|
| 1400 |
+
- type: precision_at_10
|
| 1401 |
+
value: 91.4
|
| 1402 |
+
- type: precision_at_100
|
| 1403 |
+
value: 68.24
|
| 1404 |
+
- type: mrr_at_1
|
| 1405 |
+
value: 94.0
|
| 1406 |
+
- type: mrr_at_3
|
| 1407 |
+
value: 96.667
|
| 1408 |
+
- type: mrr_at_5
|
| 1409 |
+
value: 96.667
|
| 1410 |
+
- type: mrr_at_10
|
| 1411 |
+
value: 96.667
|
| 1412 |
+
- type: mrr_at_100
|
| 1413 |
+
value: 96.667
|
| 1414 |
+
- task:
|
| 1415 |
+
type: Retrieval
|
| 1416 |
+
dataset:
|
| 1417 |
+
type: webis-touche2020
|
| 1418 |
+
name: MTEB Touche2020
|
| 1419 |
+
config: default
|
| 1420 |
+
split: test
|
| 1421 |
+
revision: None
|
| 1422 |
+
metrics:
|
| 1423 |
+
- type: ndcg_at_1
|
| 1424 |
+
value: 26.531
|
| 1425 |
+
- type: ndcg_at_3
|
| 1426 |
+
value: 27.728
|
| 1427 |
+
- type: ndcg_at_5
|
| 1428 |
+
value: 25.668000000000003
|
| 1429 |
+
- type: ndcg_at_10
|
| 1430 |
+
value: 25.785999999999998
|
| 1431 |
+
- type: ndcg_at_100
|
| 1432 |
+
value: 35.623
|
| 1433 |
+
- type: map_at_1
|
| 1434 |
+
value: 2.076
|
| 1435 |
+
- type: map_at_3
|
| 1436 |
+
value: 5.29
|
| 1437 |
+
- type: map_at_5
|
| 1438 |
+
value: 7.292999999999999
|
| 1439 |
+
- type: map_at_10
|
| 1440 |
+
value: 9.81
|
| 1441 |
+
- type: map_at_100
|
| 1442 |
+
value: 15.461
|
| 1443 |
+
- type: recall_at_1
|
| 1444 |
+
value: 2.076
|
| 1445 |
+
- type: recall_at_3
|
| 1446 |
+
value: 6.7250000000000005
|
| 1447 |
+
- type: recall_at_5
|
| 1448 |
+
value: 9.808
|
| 1449 |
+
- type: recall_at_10
|
| 1450 |
+
value: 16.467000000000002
|
| 1451 |
+
- type: recall_at_100
|
| 1452 |
+
value: 45.109
|
| 1453 |
+
- type: precision_at_1
|
| 1454 |
+
value: 28.571
|
| 1455 |
+
- type: precision_at_3
|
| 1456 |
+
value: 29.252
|
| 1457 |
+
- type: precision_at_5
|
| 1458 |
+
value: 25.714
|
| 1459 |
+
- type: precision_at_10
|
| 1460 |
+
value: 23.265
|
| 1461 |
+
- type: precision_at_100
|
| 1462 |
+
value: 7.184
|
| 1463 |
+
- type: mrr_at_1
|
| 1464 |
+
value: 28.571
|
| 1465 |
+
- type: mrr_at_3
|
| 1466 |
+
value: 42.857
|
| 1467 |
+
- type: mrr_at_5
|
| 1468 |
+
value: 44.184
|
| 1469 |
+
- type: mrr_at_10
|
| 1470 |
+
value: 47.564
|
| 1471 |
+
- type: mrr_at_100
|
| 1472 |
+
value: 48.142
|
| 1473 |
+
- task:
|
| 1474 |
+
type: Classification
|
| 1475 |
+
dataset:
|
| 1476 |
+
type: mteb/toxic_conversations_50k
|
| 1477 |
+
name: MTEB ToxicConversationsClassification
|
| 1478 |
+
config: default
|
| 1479 |
+
split: test
|
| 1480 |
+
revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
|
| 1481 |
+
metrics:
|
| 1482 |
+
- type: accuracy
|
| 1483 |
+
value: 68.43159999999999
|
| 1484 |
+
- type: ap
|
| 1485 |
+
value: 14.08119146524032
|
| 1486 |
+
- type: f1
|
| 1487 |
+
value: 53.26032318755336
|
| 1488 |
+
- task:
|
| 1489 |
+
type: Classification
|
| 1490 |
+
dataset:
|
| 1491 |
+
type: mteb/tweet_sentiment_extraction
|
| 1492 |
+
name: MTEB TweetSentimentExtractionClassification
|
| 1493 |
+
config: default
|
| 1494 |
+
split: test
|
| 1495 |
+
revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
|
| 1496 |
+
metrics:
|
| 1497 |
+
- type: accuracy
|
| 1498 |
+
value: 63.82852292020373
|
| 1499 |
+
- type: f1
|
| 1500 |
+
value: 64.14509521870399
|
| 1501 |
+
- task:
|
| 1502 |
+
type: Clustering
|
| 1503 |
+
dataset:
|
| 1504 |
+
type: mteb/twentynewsgroups-clustering
|
| 1505 |
+
name: MTEB TwentyNewsgroupsClustering
|
| 1506 |
+
config: default
|
| 1507 |
+
split: test
|
| 1508 |
+
revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
|
| 1509 |
+
metrics:
|
| 1510 |
+
- type: v_measure
|
| 1511 |
+
value: 55.252554461698566
|
| 1512 |
+
- task:
|
| 1513 |
+
type: PairClassification
|
| 1514 |
+
dataset:
|
| 1515 |
+
type: mteb/twittersemeval2015-pairclassification
|
| 1516 |
+
name: MTEB TwitterSemEval2015
|
| 1517 |
+
config: default
|
| 1518 |
+
split: test
|
| 1519 |
+
revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
|
| 1520 |
+
metrics:
|
| 1521 |
+
- type: cos_sim_accuracy
|
| 1522 |
+
value: 88.54383978065208
|
| 1523 |
+
- type: cos_sim_ap
|
| 1524 |
+
value: 81.67495128150328
|
| 1525 |
+
- type: cos_sim_f1
|
| 1526 |
+
value: 74.58161532864419
|
| 1527 |
+
- type: cos_sim_precision
|
| 1528 |
+
value: 69.00807899461401
|
| 1529 |
+
- type: cos_sim_recall
|
| 1530 |
+
value: 81.13456464379946
|
| 1531 |
+
- type: dot_accuracy
|
| 1532 |
+
value: 88.54383978065208
|
| 1533 |
+
- type: dot_ap
|
| 1534 |
+
value: 81.6748330747088
|
| 1535 |
+
- type: dot_f1
|
| 1536 |
+
value: 74.58161532864419
|
| 1537 |
+
- type: dot_precision
|
| 1538 |
+
value: 69.00807899461401
|
| 1539 |
+
- type: dot_recall
|
| 1540 |
+
value: 81.13456464379946
|
| 1541 |
+
- type: euclidean_accuracy
|
| 1542 |
+
value: 88.54383978065208
|
| 1543 |
+
- type: euclidean_ap
|
| 1544 |
+
value: 81.67496006818212
|
| 1545 |
+
- type: euclidean_f1
|
| 1546 |
+
value: 74.58161532864419
|
| 1547 |
+
- type: euclidean_precision
|
| 1548 |
+
value: 69.00807899461401
|
| 1549 |
+
- type: euclidean_recall
|
| 1550 |
+
value: 81.13456464379946
|
| 1551 |
+
- type: manhattan_accuracy
|
| 1552 |
+
value: 88.40674733265782
|
| 1553 |
+
- type: manhattan_ap
|
| 1554 |
+
value: 81.56036996969941
|
| 1555 |
+
- type: manhattan_f1
|
| 1556 |
+
value: 74.33063129452223
|
| 1557 |
+
- type: manhattan_precision
|
| 1558 |
+
value: 69.53125
|
| 1559 |
+
- type: manhattan_recall
|
| 1560 |
+
value: 79.84168865435356
|
| 1561 |
+
- type: max_accuracy
|
| 1562 |
+
value: 88.54383978065208
|
| 1563 |
+
- type: max_ap
|
| 1564 |
+
value: 81.67496006818212
|
| 1565 |
+
- type: max_f1
|
| 1566 |
+
value: 74.58161532864419
|
| 1567 |
+
- task:
|
| 1568 |
+
type: PairClassification
|
| 1569 |
+
dataset:
|
| 1570 |
+
type: mteb/twitterurlcorpus-pairclassification
|
| 1571 |
+
name: MTEB TwitterURLCorpus
|
| 1572 |
+
config: default
|
| 1573 |
+
split: test
|
| 1574 |
+
revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
|
| 1575 |
+
metrics:
|
| 1576 |
+
- type: cos_sim_accuracy
|
| 1577 |
+
value: 89.75627740908915
|
| 1578 |
+
- type: cos_sim_ap
|
| 1579 |
+
value: 87.41911504007292
|
| 1580 |
+
- type: cos_sim_f1
|
| 1581 |
+
value: 79.91742008969888
|
| 1582 |
+
- type: cos_sim_precision
|
| 1583 |
+
value: 74.31484178472131
|
| 1584 |
+
- type: cos_sim_recall
|
| 1585 |
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value: 86.43363104404065
|
| 1586 |
+
- type: dot_accuracy
|
| 1587 |
+
value: 89.75627740908915
|
| 1588 |
+
- type: dot_ap
|
| 1589 |
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value: 87.41910845717851
|
| 1590 |
+
- type: dot_f1
|
| 1591 |
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value: 79.91742008969888
|
| 1592 |
+
- type: dot_precision
|
| 1593 |
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value: 74.31484178472131
|
| 1594 |
+
- type: dot_recall
|
| 1595 |
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value: 86.43363104404065
|
| 1596 |
+
- type: euclidean_accuracy
|
| 1597 |
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value: 89.75627740908915
|
| 1598 |
+
- type: euclidean_ap
|
| 1599 |
+
value: 87.41912150448005
|
| 1600 |
+
- type: euclidean_f1
|
| 1601 |
+
value: 79.91742008969888
|
| 1602 |
+
- type: euclidean_precision
|
| 1603 |
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value: 74.31484178472131
|
| 1604 |
+
- type: euclidean_recall
|
| 1605 |
+
value: 86.43363104404065
|
| 1606 |
+
- type: manhattan_accuracy
|
| 1607 |
+
value: 89.76597974152986
|
| 1608 |
+
- type: manhattan_ap
|
| 1609 |
+
value: 87.49835162128704
|
| 1610 |
+
- type: manhattan_f1
|
| 1611 |
+
value: 80.05401656994779
|
| 1612 |
+
- type: manhattan_precision
|
| 1613 |
+
value: 76.10158906390951
|
| 1614 |
+
- type: manhattan_recall
|
| 1615 |
+
value: 84.43948259932245
|
| 1616 |
+
- type: max_accuracy
|
| 1617 |
+
value: 89.76597974152986
|
| 1618 |
+
- type: max_ap
|
| 1619 |
+
value: 87.49835162128704
|
| 1620 |
+
- type: max_f1
|
| 1621 |
+
value: 80.05401656994779
|
| 1622 |
+
language:
|
| 1623 |
+
- en
|
| 1624 |
license: mit
|
| 1625 |
---
|
| 1626 |
+
|
| 1627 |
+
## SPEED-embedding-7b-instruct
|
| 1628 |
+
|
| 1629 |
+
[Little Giants: Synthesizing High-Quality Embedding Data at Scale](https://arxiv.org/pdf/2410.18634.pdf). Haonan Chen, Liang Wang, Nan Yang, Yutao Zhu, Ziliang Zhao, Furu Wei, Zhicheng Dou, arXiv 2024
|
| 1630 |
+
|
| 1631 |
+
This model has 32 layers and the embedding size is 4096.
|
| 1632 |
+
|
| 1633 |
+
## Usage
|
| 1634 |
+
|
| 1635 |
+
Below is an example to encode queries and passages from the MS-MARCO passage ranking dataset.
|
| 1636 |
+
|
| 1637 |
+
### Transformers
|
| 1638 |
+
|
| 1639 |
+
```python
|
| 1640 |
+
import torch
|
| 1641 |
+
import torch.nn.functional as F
|
| 1642 |
+
|
| 1643 |
+
from torch import Tensor
|
| 1644 |
+
from transformers import AutoTokenizer, AutoModel
|
| 1645 |
+
|
| 1646 |
+
|
| 1647 |
+
def last_token_pool(last_hidden_states: Tensor,
|
| 1648 |
+
attention_mask: Tensor) -> Tensor:
|
| 1649 |
+
left_padding = (attention_mask[:, -1].sum() == attention_mask.shape[0])
|
| 1650 |
+
if left_padding:
|
| 1651 |
+
return last_hidden_states[:, -1]
|
| 1652 |
+
else:
|
| 1653 |
+
sequence_lengths = attention_mask.sum(dim=1) - 1
|
| 1654 |
+
batch_size = last_hidden_states.shape[0]
|
| 1655 |
+
return last_hidden_states[torch.arange(batch_size, device=last_hidden_states.device), sequence_lengths]
|
| 1656 |
+
|
| 1657 |
+
|
| 1658 |
+
def get_detailed_instruct(task_description: str, query: str) -> str:
|
| 1659 |
+
return f'Instruct: {task_description}\nQuery: {query}'
|
| 1660 |
+
|
| 1661 |
+
|
| 1662 |
+
# Each query must come with a one-sentence instruction that describes the task
|
| 1663 |
+
task = 'Given a web search query, retrieve relevant passages that answer the query'
|
| 1664 |
+
queries = [
|
| 1665 |
+
get_detailed_instruct(task, 'how much protein should a female eat'),
|
| 1666 |
+
get_detailed_instruct(task, 'summit define')
|
| 1667 |
+
]
|
| 1668 |
+
# No need to add instruction for retrieval documents
|
| 1669 |
+
documents = [
|
| 1670 |
+
"As a general guideline, the CDC's average requirement of protein for women ages 19 to 70 is 46 grams per day. But, as you can see from this chart, you'll need to increase that if you're expecting or training for a marathon. Check out the chart below to see how much protein you should be eating each day.",
|
| 1671 |
+
"Definition of summit for English Language Learners. : 1 the highest point of a mountain : the top of a mountain. : 2 the highest level. : 3 a meeting or series of meetings between the leaders of two or more governments."
|
| 1672 |
+
]
|
| 1673 |
+
input_texts = queries + documents
|
| 1674 |
+
|
| 1675 |
+
tokenizer = AutoTokenizer.from_pretrained('Haon-Chen/speed-embedding-7b-instruct')
|
| 1676 |
+
model = AutoModel.from_pretrained('Haon-Chen/speed-embedding-7b-instruct')
|
| 1677 |
+
|
| 1678 |
+
max_length = 4096
|
| 1679 |
+
# Tokenize the input texts
|
| 1680 |
+
batch_dict = tokenizer(input_texts, max_length=max_length, padding=True, truncation=True, return_tensors='pt')
|
| 1681 |
+
|
| 1682 |
+
outputs = model(**batch_dict)
|
| 1683 |
+
embeddings = last_token_pool(outputs.last_hidden_state, batch_dict['attention_mask'])
|
| 1684 |
+
|
| 1685 |
+
# normalize embeddings
|
| 1686 |
+
embeddings = F.normalize(embeddings, p=2, dim=1)
|
| 1687 |
+
scores = (embeddings[:2] @ embeddings[2:].T) * 100
|
| 1688 |
+
print(scores.tolist())
|
| 1689 |
+
```
|
| 1690 |
+
|
| 1691 |
+
## MTEB Benchmark Evaluation
|
| 1692 |
+
|
| 1693 |
+
Check out [unilm/e5](https://github.com/microsoft/unilm/tree/master/e5) to reproduce evaluation results
|
| 1694 |
+
on the [BEIR](https://arxiv.org/abs/2104.08663) and [MTEB benchmark](https://arxiv.org/abs/2210.07316).
|
| 1695 |
+
|
| 1696 |
+
## FAQ
|
| 1697 |
+
|
| 1698 |
+
**1. Do I need to add instructions to the query?**
|
| 1699 |
+
|
| 1700 |
+
Yes, this is how the model is trained, otherwise you will see a performance degradation.
|
| 1701 |
+
The task definition should be a one-sentence instruction that describes the task.
|
| 1702 |
+
This is a way to customize text embeddings for different scenarios through natural language instructions.
|
| 1703 |
+
|
| 1704 |
+
Please check out [unilm/e5/utils.py](https://github.com/microsoft/unilm/blob/9c0f1ff7ca53431fe47d2637dfe253643d94185b/e5/utils.py#L106) for instructions we used for evaluation.
|
| 1705 |
+
|
| 1706 |
+
On the other hand, there is no need to add instructions to the document side.
|
| 1707 |
+
|
| 1708 |
+
**2. Why are my reproduced results slightly different from reported in the model card?**
|
| 1709 |
+
|
| 1710 |
+
Different versions of `transformers` and `pytorch` could cause negligible but non-zero performance differences.
|
| 1711 |
+
|
| 1712 |
+
**3. Where are the LoRA-only weights?**
|
| 1713 |
+
|
| 1714 |
+
You can find the LoRA-only weights at [https://huggingface.co/Haon-Chen/speed-embedding-7b-instruct/tree/main/lora](https://huggingface.co/Haon-Chen/speed-embedding-7b-instruct/tree/main/lora).
|
| 1715 |
+
|
| 1716 |
+
## Citation
|
| 1717 |
+
|
| 1718 |
+
If you find our paper or models helpful, please consider cite as follows:
|
| 1719 |
+
|
| 1720 |
+
```bibtex
|
| 1721 |
+
@article{chen2024little,
|
| 1722 |
+
title={Little Giants: Synthesizing High-Quality Embedding Data at Scale},
|
| 1723 |
+
author={Chen, Haonan and Wang, Liang and Yang, Nan and Zhu, Yutao and Zhao, Ziliang and Wei, Furu and Dou, Zhicheng},
|
| 1724 |
+
journal={arXiv preprint arXiv:2410.18634},
|
| 1725 |
+
year={2024}
|
| 1726 |
+
}
|
| 1727 |
+
```
|
| 1728 |
+
|
| 1729 |
+
## Limitations
|
| 1730 |
+
|
| 1731 |
+
Using this model for inputs longer than 4096 tokens is not recommended.
|