README.md
| 1 | --- |
| 2 | tags: |
| 3 | - mteb |
| 4 | - sentence-transformers |
| 5 | - transformers |
| 6 | - multilingual |
| 7 | - sentence-similarity |
| 8 | - text-embeddings-inference |
| 9 | license: apache-2.0 |
| 10 | language: |
| 11 | - af |
| 12 | - ar |
| 13 | - az |
| 14 | - be |
| 15 | - bg |
| 16 | - bn |
| 17 | - ca |
| 18 | - ceb |
| 19 | - cs |
| 20 | - cy |
| 21 | - da |
| 22 | - de |
| 23 | - el |
| 24 | - en |
| 25 | - es |
| 26 | - et |
| 27 | - eu |
| 28 | - fa |
| 29 | - fi |
| 30 | - fr |
| 31 | - gl |
| 32 | - gu |
| 33 | - he |
| 34 | - hi |
| 35 | - hr |
| 36 | - ht |
| 37 | - hu |
| 38 | - hy |
| 39 | - id |
| 40 | - is |
| 41 | - it |
| 42 | - ja |
| 43 | - jv |
| 44 | - ka |
| 45 | - kk |
| 46 | - km |
| 47 | - kn |
| 48 | - ko |
| 49 | - ky |
| 50 | - lo |
| 51 | - lt |
| 52 | - lv |
| 53 | - mk |
| 54 | - ml |
| 55 | - mn |
| 56 | - mr |
| 57 | - ms |
| 58 | - my |
| 59 | - ne |
| 60 | - nl |
| 61 | - 'no' |
| 62 | - pa |
| 63 | - pl |
| 64 | - pt |
| 65 | - qu |
| 66 | - ro |
| 67 | - ru |
| 68 | - si |
| 69 | - sk |
| 70 | - sl |
| 71 | - so |
| 72 | - sq |
| 73 | - sr |
| 74 | - sv |
| 75 | - sw |
| 76 | - ta |
| 77 | - te |
| 78 | - th |
| 79 | - tl |
| 80 | - tr |
| 81 | - uk |
| 82 | - ur |
| 83 | - vi |
| 84 | - yo |
| 85 | - zh |
| 86 | model-index: |
| 87 | - name: gte-multilingual-base (dense) |
| 88 | results: |
| 89 | - task: |
| 90 | type: Clustering |
| 91 | dataset: |
| 92 | type: PL-MTEB/8tags-clustering |
| 93 | name: MTEB 8TagsClustering |
| 94 | config: default |
| 95 | split: test |
| 96 | revision: None |
| 97 | metrics: |
| 98 | - type: v_measure |
| 99 | value: 33.66681726329994 |
| 100 | - task: |
| 101 | type: STS |
| 102 | dataset: |
| 103 | type: C-MTEB/AFQMC |
| 104 | name: MTEB AFQMC |
| 105 | config: default |
| 106 | split: validation |
| 107 | revision: b44c3b011063adb25877c13823db83bb193913c4 |
| 108 | metrics: |
| 109 | - type: cos_sim_spearman |
| 110 | value: 43.54760696384009 |
| 111 | - task: |
| 112 | type: STS |
| 113 | dataset: |
| 114 | type: C-MTEB/ATEC |
| 115 | name: MTEB ATEC |
| 116 | config: default |
| 117 | split: test |
| 118 | revision: 0f319b1142f28d00e055a6770f3f726ae9b7d865 |
| 119 | metrics: |
| 120 | - type: cos_sim_spearman |
| 121 | value: 48.91186363417501 |
| 122 | - task: |
| 123 | type: Classification |
| 124 | dataset: |
| 125 | type: PL-MTEB/allegro-reviews |
| 126 | name: MTEB AllegroReviews |
| 127 | config: default |
| 128 | split: test |
| 129 | revision: None |
| 130 | metrics: |
| 131 | - type: accuracy |
| 132 | value: 41.689860834990064 |
| 133 | - task: |
| 134 | type: Clustering |
| 135 | dataset: |
| 136 | type: lyon-nlp/alloprof |
| 137 | name: MTEB AlloProfClusteringP2P |
| 138 | config: default |
| 139 | split: test |
| 140 | revision: 392ba3f5bcc8c51f578786c1fc3dae648662cb9b |
| 141 | metrics: |
| 142 | - type: v_measure |
| 143 | value: 54.20241337977897 |
| 144 | - task: |
| 145 | type: Clustering |
| 146 | dataset: |
| 147 | type: lyon-nlp/alloprof |
| 148 | name: MTEB AlloProfClusteringS2S |
| 149 | config: default |
| 150 | split: test |
| 151 | revision: 392ba3f5bcc8c51f578786c1fc3dae648662cb9b |
| 152 | metrics: |
| 153 | - type: v_measure |
| 154 | value: 44.34083695608643 |
| 155 | - task: |
| 156 | type: Reranking |
| 157 | dataset: |
| 158 | type: lyon-nlp/mteb-fr-reranking-alloprof-s2p |
| 159 | name: MTEB AlloprofReranking |
| 160 | config: default |
| 161 | split: test |
| 162 | revision: 666fdacebe0291776e86f29345663dfaf80a0db9 |
| 163 | metrics: |
| 164 | - type: map |
| 165 | value: 64.91495250072002 |
| 166 | - task: |
| 167 | type: Retrieval |
| 168 | dataset: |
| 169 | type: lyon-nlp/alloprof |
| 170 | name: MTEB AlloprofRetrieval |
| 171 | config: default |
| 172 | split: test |
| 173 | revision: 392ba3f5bcc8c51f578786c1fc3dae648662cb9b |
| 174 | metrics: |
| 175 | - type: ndcg_at_10 |
| 176 | value: 53.638 |
| 177 | - task: |
| 178 | type: Classification |
| 179 | dataset: |
| 180 | type: mteb/amazon_counterfactual |
| 181 | name: MTEB AmazonCounterfactualClassification (en) |
| 182 | config: en |
| 183 | split: test |
| 184 | revision: e8379541af4e31359cca9fbcf4b00f2671dba205 |
| 185 | metrics: |
| 186 | - type: accuracy |
| 187 | value: 75.95522388059702 |
| 188 | - task: |
| 189 | type: Classification |
| 190 | dataset: |
| 191 | type: mteb/amazon_polarity |
| 192 | name: MTEB AmazonPolarityClassification |
| 193 | config: default |
| 194 | split: test |
| 195 | revision: e2d317d38cd51312af73b3d32a06d1a08b442046 |
| 196 | metrics: |
| 197 | - type: accuracy |
| 198 | value: 80.717625 |
| 199 | - task: |
| 200 | type: Classification |
| 201 | dataset: |
| 202 | type: mteb/amazon_reviews_multi |
| 203 | name: MTEB AmazonReviewsClassification (en) |
| 204 | config: en |
| 205 | split: test |
| 206 | revision: 1399c76144fd37290681b995c656ef9b2e06e26d |
| 207 | metrics: |
| 208 | - type: accuracy |
| 209 | value: 43.64199999999999 |
| 210 | - task: |
| 211 | type: Classification |
| 212 | dataset: |
| 213 | type: mteb/amazon_reviews_multi |
| 214 | name: MTEB AmazonReviewsClassification (de) |
| 215 | config: de |
| 216 | split: test |
| 217 | revision: 1399c76144fd37290681b995c656ef9b2e06e26d |
| 218 | metrics: |
| 219 | - type: accuracy |
| 220 | value: 40.108 |
| 221 | - task: |
| 222 | type: Classification |
| 223 | dataset: |
| 224 | type: mteb/amazon_reviews_multi |
| 225 | name: MTEB AmazonReviewsClassification (es) |
| 226 | config: es |
| 227 | split: test |
| 228 | revision: 1399c76144fd37290681b995c656ef9b2e06e26d |
| 229 | metrics: |
| 230 | - type: accuracy |
| 231 | value: 40.169999999999995 |
| 232 | - task: |
| 233 | type: Classification |
| 234 | dataset: |
| 235 | type: mteb/amazon_reviews_multi |
| 236 | name: MTEB AmazonReviewsClassification (fr) |
| 237 | config: fr |
| 238 | split: test |
| 239 | revision: 1399c76144fd37290681b995c656ef9b2e06e26d |
| 240 | metrics: |
| 241 | - type: accuracy |
| 242 | value: 39.56799999999999 |
| 243 | - task: |
| 244 | type: Classification |
| 245 | dataset: |
| 246 | type: mteb/amazon_reviews_multi |
| 247 | name: MTEB AmazonReviewsClassification (ja) |
| 248 | config: ja |
| 249 | split: test |
| 250 | revision: 1399c76144fd37290681b995c656ef9b2e06e26d |
| 251 | metrics: |
| 252 | - type: accuracy |
| 253 | value: 35.75000000000001 |
| 254 | - task: |
| 255 | type: Classification |
| 256 | dataset: |
| 257 | type: mteb/amazon_reviews_multi |
| 258 | name: MTEB AmazonReviewsClassification (zh) |
| 259 | config: zh |
| 260 | split: test |
| 261 | revision: 1399c76144fd37290681b995c656ef9b2e06e26d |
| 262 | metrics: |
| 263 | - type: accuracy |
| 264 | value: 33.342000000000006 |
| 265 | - task: |
| 266 | type: Retrieval |
| 267 | dataset: |
| 268 | type: mteb/arguana |
| 269 | name: MTEB ArguAna |
| 270 | config: default |
| 271 | split: test |
| 272 | revision: c22ab2a51041ffd869aaddef7af8d8215647e41a |
| 273 | metrics: |
| 274 | - type: ndcg_at_10 |
| 275 | value: 58.231 |
| 276 | - task: |
| 277 | type: Retrieval |
| 278 | dataset: |
| 279 | type: clarin-knext/arguana-pl |
| 280 | name: MTEB ArguAna-PL |
| 281 | config: default |
| 282 | split: test |
| 283 | revision: 63fc86750af76253e8c760fc9e534bbf24d260a2 |
| 284 | metrics: |
| 285 | - type: ndcg_at_10 |
| 286 | value: 53.166000000000004 |
| 287 | - task: |
| 288 | type: Clustering |
| 289 | dataset: |
| 290 | type: mteb/arxiv-clustering-p2p |
| 291 | name: MTEB ArxivClusteringP2P |
| 292 | config: default |
| 293 | split: test |
| 294 | revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d |
| 295 | metrics: |
| 296 | - type: v_measure |
| 297 | value: 46.01900557959478 |
| 298 | - task: |
| 299 | type: Clustering |
| 300 | dataset: |
| 301 | type: mteb/arxiv-clustering-s2s |
| 302 | name: MTEB ArxivClusteringS2S |
| 303 | config: default |
| 304 | split: test |
| 305 | revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53 |
| 306 | metrics: |
| 307 | - type: v_measure |
| 308 | value: 41.06626465345723 |
| 309 | - task: |
| 310 | type: Reranking |
| 311 | dataset: |
| 312 | type: mteb/askubuntudupquestions-reranking |
| 313 | name: MTEB AskUbuntuDupQuestions |
| 314 | config: default |
| 315 | split: test |
| 316 | revision: 2000358ca161889fa9c082cb41daa8dcfb161a54 |
| 317 | metrics: |
| 318 | - type: map |
| 319 | value: 61.87514497610431 |
| 320 | - task: |
| 321 | type: STS |
| 322 | dataset: |
| 323 | type: mteb/biosses-sts |
| 324 | name: MTEB BIOSSES |
| 325 | config: default |
| 326 | split: test |
| 327 | revision: d3fb88f8f02e40887cd149695127462bbcf29b4a |
| 328 | metrics: |
| 329 | - type: cos_sim_spearman |
| 330 | value: 81.21450112991194 |
| 331 | - task: |
| 332 | type: STS |
| 333 | dataset: |
| 334 | type: C-MTEB/BQ |
| 335 | name: MTEB BQ |
| 336 | config: default |
| 337 | split: test |
| 338 | revision: e3dda5e115e487b39ec7e618c0c6a29137052a55 |
| 339 | metrics: |
| 340 | - type: cos_sim_spearman |
| 341 | value: 51.71589543397271 |
| 342 | - task: |
| 343 | type: Retrieval |
| 344 | dataset: |
| 345 | type: maastrichtlawtech/bsard |
| 346 | name: MTEB BSARDRetrieval |
| 347 | config: default |
| 348 | split: test |
| 349 | revision: 5effa1b9b5fa3b0f9e12523e6e43e5f86a6e6d59 |
| 350 | metrics: |
| 351 | - type: ndcg_at_10 |
| 352 | value: 26.115 |
| 353 | - task: |
| 354 | type: BitextMining |
| 355 | dataset: |
| 356 | type: mteb/bucc-bitext-mining |
| 357 | name: MTEB BUCC (de-en) |
| 358 | config: de-en |
| 359 | split: test |
| 360 | revision: d51519689f32196a32af33b075a01d0e7c51e252 |
| 361 | metrics: |
| 362 | - type: f1 |
| 363 | value: 98.6169102296451 |
| 364 | - task: |
| 365 | type: BitextMining |
| 366 | dataset: |
| 367 | type: mteb/bucc-bitext-mining |
| 368 | name: MTEB BUCC (fr-en) |
| 369 | config: fr-en |
| 370 | split: test |
| 371 | revision: d51519689f32196a32af33b075a01d0e7c51e252 |
| 372 | metrics: |
| 373 | - type: f1 |
| 374 | value: 97.89603052314916 |
| 375 | - task: |
| 376 | type: BitextMining |
| 377 | dataset: |
| 378 | type: mteb/bucc-bitext-mining |
| 379 | name: MTEB BUCC (ru-en) |
| 380 | config: ru-en |
| 381 | split: test |
| 382 | revision: d51519689f32196a32af33b075a01d0e7c51e252 |
| 383 | metrics: |
| 384 | - type: f1 |
| 385 | value: 97.12388869645537 |
| 386 | - task: |
| 387 | type: BitextMining |
| 388 | dataset: |
| 389 | type: mteb/bucc-bitext-mining |
| 390 | name: MTEB BUCC (zh-en) |
| 391 | config: zh-en |
| 392 | split: test |
| 393 | revision: d51519689f32196a32af33b075a01d0e7c51e252 |
| 394 | metrics: |
| 395 | - type: f1 |
| 396 | value: 98.15692469720906 |
| 397 | - task: |
| 398 | type: Classification |
| 399 | dataset: |
| 400 | type: mteb/banking77 |
| 401 | name: MTEB Banking77Classification |
| 402 | config: default |
| 403 | split: test |
| 404 | revision: 0fd18e25b25c072e09e0d92ab615fda904d66300 |
| 405 | metrics: |
| 406 | - type: accuracy |
| 407 | value: 85.36038961038962 |
| 408 | - task: |
| 409 | type: Clustering |
| 410 | dataset: |
| 411 | type: mteb/biorxiv-clustering-p2p |
| 412 | name: MTEB BiorxivClusteringP2P |
| 413 | config: default |
| 414 | split: test |
| 415 | revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40 |
| 416 | metrics: |
| 417 | - type: v_measure |
| 418 | value: 37.5903826674123 |
| 419 | - task: |
| 420 | type: Clustering |
| 421 | dataset: |
| 422 | type: mteb/biorxiv-clustering-s2s |
| 423 | name: MTEB BiorxivClusteringS2S |
| 424 | config: default |
| 425 | split: test |
| 426 | revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908 |
| 427 | metrics: |
| 428 | - type: v_measure |
| 429 | value: 34.21474277151329 |
| 430 | - task: |
| 431 | type: Classification |
| 432 | dataset: |
| 433 | type: PL-MTEB/cbd |
| 434 | name: MTEB CBD |
| 435 | config: default |
| 436 | split: test |
| 437 | revision: None |
| 438 | metrics: |
| 439 | - type: accuracy |
| 440 | value: 62.519999999999996 |
| 441 | - task: |
| 442 | type: PairClassification |
| 443 | dataset: |
| 444 | type: PL-MTEB/cdsce-pairclassification |
| 445 | name: MTEB CDSC-E |
| 446 | config: default |
| 447 | split: test |
| 448 | revision: None |
| 449 | metrics: |
| 450 | - type: cos_sim_ap |
| 451 | value: 74.90132799162956 |
| 452 | - task: |
| 453 | type: STS |
| 454 | dataset: |
| 455 | type: PL-MTEB/cdscr-sts |
| 456 | name: MTEB CDSC-R |
| 457 | config: default |
| 458 | split: test |
| 459 | revision: None |
| 460 | metrics: |
| 461 | - type: cos_sim_spearman |
| 462 | value: 90.30727955142524 |
| 463 | - task: |
| 464 | type: Clustering |
| 465 | dataset: |
| 466 | type: C-MTEB/CLSClusteringP2P |
| 467 | name: MTEB CLSClusteringP2P |
| 468 | config: default |
| 469 | split: test |
| 470 | revision: 4b6227591c6c1a73bc76b1055f3b7f3588e72476 |
| 471 | metrics: |
| 472 | - type: v_measure |
| 473 | value: 37.94850105022274 |
| 474 | - task: |
| 475 | type: Clustering |
| 476 | dataset: |
| 477 | type: C-MTEB/CLSClusteringS2S |
| 478 | name: MTEB CLSClusteringS2S |
| 479 | config: default |
| 480 | split: test |
| 481 | revision: e458b3f5414b62b7f9f83499ac1f5497ae2e869f |
| 482 | metrics: |
| 483 | - type: v_measure |
| 484 | value: 38.11958675421534 |
| 485 | - task: |
| 486 | type: Reranking |
| 487 | dataset: |
| 488 | type: C-MTEB/CMedQAv1-reranking |
| 489 | name: MTEB CMedQAv1 |
| 490 | config: default |
| 491 | split: test |
| 492 | revision: 8d7f1e942507dac42dc58017c1a001c3717da7df |
| 493 | metrics: |
| 494 | - type: map |
| 495 | value: 86.10950950485399 |
| 496 | - task: |
| 497 | type: Reranking |
| 498 | dataset: |
| 499 | type: C-MTEB/CMedQAv2-reranking |
| 500 | name: MTEB CMedQAv2 |
| 501 | config: default |
| 502 | split: test |
| 503 | revision: 23d186750531a14a0357ca22cd92d712fd512ea0 |
| 504 | metrics: |
| 505 | - type: map |
| 506 | value: 87.28038294231966 |
| 507 | - task: |
| 508 | type: Retrieval |
| 509 | dataset: |
| 510 | type: mteb/cqadupstack-android |
| 511 | name: MTEB CQADupstackAndroidRetrieval |
| 512 | config: default |
| 513 | split: test |
| 514 | revision: f46a197baaae43b4f621051089b82a364682dfeb |
| 515 | metrics: |
| 516 | - type: ndcg_at_10 |
| 517 | value: 47.099000000000004 |
| 518 | - task: |
| 519 | type: Retrieval |
| 520 | dataset: |
| 521 | type: mteb/cqadupstack-english |
| 522 | name: MTEB CQADupstackEnglishRetrieval |
| 523 | config: default |
| 524 | split: test |
| 525 | revision: ad9991cb51e31e31e430383c75ffb2885547b5f0 |
| 526 | metrics: |
| 527 | - type: ndcg_at_10 |
| 528 | value: 45.973000000000006 |
| 529 | - task: |
| 530 | type: Retrieval |
| 531 | dataset: |
| 532 | type: mteb/cqadupstack-gaming |
| 533 | name: MTEB CQADupstackGamingRetrieval |
| 534 | config: default |
| 535 | split: test |
| 536 | revision: 4885aa143210c98657558c04aaf3dc47cfb54340 |
| 537 | metrics: |
| 538 | - type: ndcg_at_10 |
| 539 | value: 55.606 |
| 540 | - task: |
| 541 | type: Retrieval |
| 542 | dataset: |
| 543 | type: mteb/cqadupstack-gis |
| 544 | name: MTEB CQADupstackGisRetrieval |
| 545 | config: default |
| 546 | split: test |
| 547 | revision: 5003b3064772da1887988e05400cf3806fe491f2 |
| 548 | metrics: |
| 549 | - type: ndcg_at_10 |
| 550 | value: 36.638 |
| 551 | - task: |
| 552 | type: Retrieval |
| 553 | dataset: |
| 554 | type: mteb/cqadupstack-mathematica |
| 555 | name: MTEB CQADupstackMathematicaRetrieval |
| 556 | config: default |
| 557 | split: test |
| 558 | revision: 90fceea13679c63fe563ded68f3b6f06e50061de |
| 559 | metrics: |
| 560 | - type: ndcg_at_10 |
| 561 | value: 30.711 |
| 562 | - task: |
| 563 | type: Retrieval |
| 564 | dataset: |
| 565 | type: mteb/cqadupstack-physics |
| 566 | name: MTEB CQADupstackPhysicsRetrieval |
| 567 | config: default |
| 568 | split: test |
| 569 | revision: 79531abbd1fb92d06c6d6315a0cbbbf5bb247ea4 |
| 570 | metrics: |
| 571 | - type: ndcg_at_10 |
| 572 | value: 44.523 |
| 573 | - task: |
| 574 | type: Retrieval |
| 575 | dataset: |
| 576 | type: mteb/cqadupstack-programmers |
| 577 | name: MTEB CQADupstackProgrammersRetrieval |
| 578 | config: default |
| 579 | split: test |
| 580 | revision: 6184bc1440d2dbc7612be22b50686b8826d22b32 |
| 581 | metrics: |
| 582 | - type: ndcg_at_10 |
| 583 | value: 37.940000000000005 |
| 584 | - task: |
| 585 | type: Retrieval |
| 586 | dataset: |
| 587 | type: mteb/cqadupstack |
| 588 | name: MTEB CQADupstackRetrieval |
| 589 | config: default |
| 590 | split: test |
| 591 | revision: 4ffe81d471b1924886b33c7567bfb200e9eec5c4 |
| 592 | metrics: |
| 593 | - type: ndcg_at_10 |
| 594 | value: 38.12183333333333 |
| 595 | - task: |
| 596 | type: Retrieval |
| 597 | dataset: |
| 598 | type: mteb/cqadupstack-stats |
| 599 | name: MTEB CQADupstackStatsRetrieval |
| 600 | config: default |
| 601 | split: test |
| 602 | revision: 65ac3a16b8e91f9cee4c9828cc7c335575432a2a |
| 603 | metrics: |
| 604 | - type: ndcg_at_10 |
| 605 | value: 32.684000000000005 |
| 606 | - task: |
| 607 | type: Retrieval |
| 608 | dataset: |
| 609 | type: mteb/cqadupstack-tex |
| 610 | name: MTEB CQADupstackTexRetrieval |
| 611 | config: default |
| 612 | split: test |
| 613 | revision: 46989137a86843e03a6195de44b09deda022eec7 |
| 614 | metrics: |
| 615 | - type: ndcg_at_10 |
| 616 | value: 26.735 |
| 617 | - task: |
| 618 | type: Retrieval |
| 619 | dataset: |
| 620 | type: mteb/cqadupstack-unix |
| 621 | name: MTEB CQADupstackUnixRetrieval |
| 622 | config: default |
| 623 | split: test |
| 624 | revision: 6c6430d3a6d36f8d2a829195bc5dc94d7e063e53 |
| 625 | metrics: |
| 626 | - type: ndcg_at_10 |
| 627 | value: 36.933 |
| 628 | - task: |
| 629 | type: Retrieval |
| 630 | dataset: |
| 631 | type: mteb/cqadupstack-webmasters |
| 632 | name: MTEB CQADupstackWebmastersRetrieval |
| 633 | config: default |
| 634 | split: test |
| 635 | revision: 160c094312a0e1facb97e55eeddb698c0abe3571 |
| 636 | metrics: |
| 637 | - type: ndcg_at_10 |
| 638 | value: 33.747 |
| 639 | - task: |
| 640 | type: Retrieval |
| 641 | dataset: |
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| 643 | name: MTEB CQADupstackWordpressRetrieval |
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| 654 | name: MTEB ClimateFEVER |
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| 665 | name: MTEB CmedqaRetrieval |
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| 687 | name: MTEB CovidRetrieval |
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| 720 | name: MTEB DuRetrieval |
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| 742 | name: MTEB EmotionClassification |
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| 775 | name: MTEB FiQA2018 |
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| 819 | name: MTEB IFlyTek |
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| 841 | name: MTEB JDReview |
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| 896 | name: MTEB MMarcoRetrieval |
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| 1061 | name: MTEB MasakhaNEWSClassification (fra) |
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| 1072 | name: MTEB MasakhaNEWSClusteringP2P (fra) |
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| 1787 | name: MTEB MassiveScenarioClassification (fi) |
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| 1798 | name: MTEB MassiveScenarioClassification (fr) |
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| 1864 | name: MTEB MassiveScenarioClassification (is) |
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| 1886 | name: MTEB MassiveScenarioClassification (ja) |
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| 1897 | name: MTEB MassiveScenarioClassification (jv) |
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| 1909 | config: ka |
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| 1919 | name: MTEB MassiveScenarioClassification (km) |
| 1920 | config: km |
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| 1963 | name: MTEB MassiveScenarioClassification (ml) |
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| 1974 | name: MTEB MassiveScenarioClassification (mn) |
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| 1996 | name: MTEB MassiveScenarioClassification (my) |
| 1997 | config: my |
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| 2018 | name: MTEB MassiveScenarioClassification (nl) |
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| 2062 | name: MTEB MassiveScenarioClassification (ru) |
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| 2150 | name: MTEB MassiveScenarioClassification (tl) |
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| 2161 | name: MTEB MassiveScenarioClassification (tr) |
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| 2172 | name: MTEB MassiveScenarioClassification (ur) |
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| 2183 | name: MTEB MassiveScenarioClassification (vi) |
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| 2194 | name: MTEB MassiveScenarioClassification (zh-CN) |
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| 2197 | revision: 7d571f92784cd94a019292a1f45445077d0ef634 |
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| 2205 | name: MTEB MassiveScenarioClassification (zh-TW) |
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| 2208 | revision: 7d571f92784cd94a019292a1f45445077d0ef634 |
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| 2210 | - type: accuracy |
| 2211 | value: 71.61398789509079 |
| 2212 | - task: |
| 2213 | type: Retrieval |
| 2214 | dataset: |
| 2215 | type: C-MTEB/MedicalRetrieval |
| 2216 | name: MTEB MedicalRetrieval |
| 2217 | config: default |
| 2218 | split: dev |
| 2219 | revision: 2039188fb5800a9803ba5048df7b76e6fb151fc6 |
| 2220 | metrics: |
| 2221 | - type: ndcg_at_10 |
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| 2224 | type: Clustering |
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| 2226 | type: mteb/medrxiv-clustering-p2p |
| 2227 | name: MTEB MedrxivClusteringP2P |
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| 2230 | revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73 |
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| 2238 | name: MTEB MedrxivClusteringS2S |
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| 2248 | type: mteb/mind_small |
| 2249 | name: MTEB MindSmallReranking |
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| 2251 | split: test |
| 2252 | revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69 |
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| 2258 | dataset: |
| 2259 | type: jinaai/mintakaqa |
| 2260 | name: MTEB MintakaRetrieval (fr) |
| 2261 | config: fr |
| 2262 | split: test |
| 2263 | revision: efa78cc2f74bbcd21eff2261f9e13aebe40b814e |
| 2264 | metrics: |
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| 2270 | type: Shitao/MLDR |
| 2271 | name: MTEB MultiLongDocRetrieval (ar) |
| 2272 | config: ar |
| 2273 | split: test |
| 2274 | revision: None |
| 2275 | metrics: |
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| 2277 | value: 55.166000000000004 |
| 2278 | - task: |
| 2279 | type: Retrieval |
| 2280 | dataset: |
| 2281 | type: Shitao/MLDR |
| 2282 | name: MTEB MultiLongDocRetrieval (de) |
| 2283 | config: de |
| 2284 | split: test |
| 2285 | revision: None |
| 2286 | metrics: |
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| 2288 | value: 55.155 |
| 2289 | - task: |
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| 2291 | dataset: |
| 2292 | type: Shitao/MLDR |
| 2293 | name: MTEB MultiLongDocRetrieval (en) |
| 2294 | config: en |
| 2295 | split: test |
| 2296 | revision: None |
| 2297 | metrics: |
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| 2299 | value: 50.993 |
| 2300 | - task: |
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| 2303 | type: Shitao/MLDR |
| 2304 | name: MTEB MultiLongDocRetrieval (es) |
| 2305 | config: es |
| 2306 | split: test |
| 2307 | revision: None |
| 2308 | metrics: |
| 2309 | - type: ndcg_at_10 |
| 2310 | value: 81.228 |
| 2311 | - task: |
| 2312 | type: Retrieval |
| 2313 | dataset: |
| 2314 | type: Shitao/MLDR |
| 2315 | name: MTEB MultiLongDocRetrieval (fr) |
| 2316 | config: fr |
| 2317 | split: test |
| 2318 | revision: None |
| 2319 | metrics: |
| 2320 | - type: ndcg_at_10 |
| 2321 | value: 76.19 |
| 2322 | - task: |
| 2323 | type: Retrieval |
| 2324 | dataset: |
| 2325 | type: Shitao/MLDR |
| 2326 | name: MTEB MultiLongDocRetrieval (hi) |
| 2327 | config: hi |
| 2328 | split: test |
| 2329 | revision: None |
| 2330 | metrics: |
| 2331 | - type: ndcg_at_10 |
| 2332 | value: 45.206 |
| 2333 | - task: |
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| 2335 | dataset: |
| 2336 | type: Shitao/MLDR |
| 2337 | name: MTEB MultiLongDocRetrieval (it) |
| 2338 | config: it |
| 2339 | split: test |
| 2340 | revision: None |
| 2341 | metrics: |
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| 2343 | value: 66.741 |
| 2344 | - task: |
| 2345 | type: Retrieval |
| 2346 | dataset: |
| 2347 | type: Shitao/MLDR |
| 2348 | name: MTEB MultiLongDocRetrieval (ja) |
| 2349 | config: ja |
| 2350 | split: test |
| 2351 | revision: None |
| 2352 | metrics: |
| 2353 | - type: ndcg_at_10 |
| 2354 | value: 52.111 |
| 2355 | - task: |
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| 2357 | dataset: |
| 2358 | type: Shitao/MLDR |
| 2359 | name: MTEB MultiLongDocRetrieval (ko) |
| 2360 | config: ko |
| 2361 | split: test |
| 2362 | revision: None |
| 2363 | metrics: |
| 2364 | - type: ndcg_at_10 |
| 2365 | value: 46.733000000000004 |
| 2366 | - task: |
| 2367 | type: Retrieval |
| 2368 | dataset: |
| 2369 | type: Shitao/MLDR |
| 2370 | name: MTEB MultiLongDocRetrieval (pt) |
| 2371 | config: pt |
| 2372 | split: test |
| 2373 | revision: None |
| 2374 | metrics: |
| 2375 | - type: ndcg_at_10 |
| 2376 | value: 79.105 |
| 2377 | - task: |
| 2378 | type: Retrieval |
| 2379 | dataset: |
| 2380 | type: Shitao/MLDR |
| 2381 | name: MTEB MultiLongDocRetrieval (ru) |
| 2382 | config: ru |
| 2383 | split: test |
| 2384 | revision: None |
| 2385 | metrics: |
| 2386 | - type: ndcg_at_10 |
| 2387 | value: 64.21 |
| 2388 | - task: |
| 2389 | type: Retrieval |
| 2390 | dataset: |
| 2391 | type: Shitao/MLDR |
| 2392 | name: MTEB MultiLongDocRetrieval (th) |
| 2393 | config: th |
| 2394 | split: test |
| 2395 | revision: None |
| 2396 | metrics: |
| 2397 | - type: ndcg_at_10 |
| 2398 | value: 35.467 |
| 2399 | - task: |
| 2400 | type: Retrieval |
| 2401 | dataset: |
| 2402 | type: Shitao/MLDR |
| 2403 | name: MTEB MultiLongDocRetrieval (zh) |
| 2404 | config: zh |
| 2405 | split: test |
| 2406 | revision: None |
| 2407 | metrics: |
| 2408 | - type: ndcg_at_10 |
| 2409 | value: 27.419 |
| 2410 | - task: |
| 2411 | type: Classification |
| 2412 | dataset: |
| 2413 | type: C-MTEB/MultilingualSentiment-classification |
| 2414 | name: MTEB MultilingualSentiment |
| 2415 | config: default |
| 2416 | split: validation |
| 2417 | revision: 46958b007a63fdbf239b7672c25d0bea67b5ea1a |
| 2418 | metrics: |
| 2419 | - type: accuracy |
| 2420 | value: 61.02000000000001 |
| 2421 | - task: |
| 2422 | type: Retrieval |
| 2423 | dataset: |
| 2424 | type: mteb/nfcorpus |
| 2425 | name: MTEB NFCorpus |
| 2426 | config: default |
| 2427 | split: test |
| 2428 | revision: ec0fa4fe99da2ff19ca1214b7966684033a58814 |
| 2429 | metrics: |
| 2430 | - type: ndcg_at_10 |
| 2431 | value: 36.65 |
| 2432 | - task: |
| 2433 | type: Retrieval |
| 2434 | dataset: |
| 2435 | type: clarin-knext/nfcorpus-pl |
| 2436 | name: MTEB NFCorpus-PL |
| 2437 | config: default |
| 2438 | split: test |
| 2439 | revision: 9a6f9567fda928260afed2de480d79c98bf0bec0 |
| 2440 | metrics: |
| 2441 | - type: ndcg_at_10 |
| 2442 | value: 26.831 |
| 2443 | - task: |
| 2444 | type: Retrieval |
| 2445 | dataset: |
| 2446 | type: mteb/nq |
| 2447 | name: MTEB NQ |
| 2448 | config: default |
| 2449 | split: test |
| 2450 | revision: b774495ed302d8c44a3a7ea25c90dbce03968f31 |
| 2451 | metrics: |
| 2452 | - type: ndcg_at_10 |
| 2453 | value: 58.111000000000004 |
| 2454 | - task: |
| 2455 | type: Retrieval |
| 2456 | dataset: |
| 2457 | type: clarin-knext/nq-pl |
| 2458 | name: MTEB NQ-PL |
| 2459 | config: default |
| 2460 | split: test |
| 2461 | revision: f171245712cf85dd4700b06bef18001578d0ca8d |
| 2462 | metrics: |
| 2463 | - type: ndcg_at_10 |
| 2464 | value: 43.126999999999995 |
| 2465 | - task: |
| 2466 | type: PairClassification |
| 2467 | dataset: |
| 2468 | type: C-MTEB/OCNLI |
| 2469 | name: MTEB Ocnli |
| 2470 | config: default |
| 2471 | split: validation |
| 2472 | revision: 66e76a618a34d6d565d5538088562851e6daa7ec |
| 2473 | metrics: |
| 2474 | - type: cos_sim_ap |
| 2475 | value: 72.67630697316041 |
| 2476 | - task: |
| 2477 | type: Classification |
| 2478 | dataset: |
| 2479 | type: C-MTEB/OnlineShopping-classification |
| 2480 | name: MTEB OnlineShopping |
| 2481 | config: default |
| 2482 | split: test |
| 2483 | revision: e610f2ebd179a8fda30ae534c3878750a96db120 |
| 2484 | metrics: |
| 2485 | - type: accuracy |
| 2486 | value: 84.85000000000001 |
| 2487 | - task: |
| 2488 | type: PairClassification |
| 2489 | dataset: |
| 2490 | type: GEM/opusparcus |
| 2491 | name: MTEB OpusparcusPC (fr) |
| 2492 | config: fr |
| 2493 | split: test |
| 2494 | revision: 9e9b1f8ef51616073f47f306f7f47dd91663f86a |
| 2495 | metrics: |
| 2496 | - type: cos_sim_ap |
| 2497 | value: 100 |
| 2498 | - task: |
| 2499 | type: Classification |
| 2500 | dataset: |
| 2501 | type: laugustyniak/abusive-clauses-pl |
| 2502 | name: MTEB PAC |
| 2503 | config: default |
| 2504 | split: test |
| 2505 | revision: None |
| 2506 | metrics: |
| 2507 | - type: accuracy |
| 2508 | value: 65.99189110918043 |
| 2509 | - task: |
| 2510 | type: STS |
| 2511 | dataset: |
| 2512 | type: C-MTEB/PAWSX |
| 2513 | name: MTEB PAWSX |
| 2514 | config: default |
| 2515 | split: test |
| 2516 | revision: 9c6a90e430ac22b5779fb019a23e820b11a8b5e1 |
| 2517 | metrics: |
| 2518 | - type: cos_sim_spearman |
| 2519 | value: 16.124364530596228 |
| 2520 | - task: |
| 2521 | type: PairClassification |
| 2522 | dataset: |
| 2523 | type: PL-MTEB/ppc-pairclassification |
| 2524 | name: MTEB PPC |
| 2525 | config: default |
| 2526 | split: test |
| 2527 | revision: None |
| 2528 | metrics: |
| 2529 | - type: cos_sim_ap |
| 2530 | value: 92.43431057460192 |
| 2531 | - task: |
| 2532 | type: PairClassification |
| 2533 | dataset: |
| 2534 | type: PL-MTEB/psc-pairclassification |
| 2535 | name: MTEB PSC |
| 2536 | config: default |
| 2537 | split: test |
| 2538 | revision: None |
| 2539 | metrics: |
| 2540 | - type: cos_sim_ap |
| 2541 | value: 99.06090138049724 |
| 2542 | - task: |
| 2543 | type: PairClassification |
| 2544 | dataset: |
| 2545 | type: paws-x |
| 2546 | name: MTEB PawsX (fr) |
| 2547 | config: fr |
| 2548 | split: test |
| 2549 | revision: 8a04d940a42cd40658986fdd8e3da561533a3646 |
| 2550 | metrics: |
| 2551 | - type: cos_sim_ap |
| 2552 | value: 58.9314954874314 |
| 2553 | - task: |
| 2554 | type: Classification |
| 2555 | dataset: |
| 2556 | type: PL-MTEB/polemo2_in |
| 2557 | name: MTEB PolEmo2.0-IN |
| 2558 | config: default |
| 2559 | split: test |
| 2560 | revision: None |
| 2561 | metrics: |
| 2562 | - type: accuracy |
| 2563 | value: 69.59833795013851 |
| 2564 | - task: |
| 2565 | type: Classification |
| 2566 | dataset: |
| 2567 | type: PL-MTEB/polemo2_out |
| 2568 | name: MTEB PolEmo2.0-OUT |
| 2569 | config: default |
| 2570 | split: test |
| 2571 | revision: None |
| 2572 | metrics: |
| 2573 | - type: accuracy |
| 2574 | value: 44.73684210526315 |
| 2575 | - task: |
| 2576 | type: STS |
| 2577 | dataset: |
| 2578 | type: C-MTEB/QBQTC |
| 2579 | name: MTEB QBQTC |
| 2580 | config: default |
| 2581 | split: test |
| 2582 | revision: 790b0510dc52b1553e8c49f3d2afb48c0e5c48b7 |
| 2583 | metrics: |
| 2584 | - type: cos_sim_spearman |
| 2585 | value: 39.36450754137984 |
| 2586 | - task: |
| 2587 | type: Retrieval |
| 2588 | dataset: |
| 2589 | type: clarin-knext/quora-pl |
| 2590 | name: MTEB Quora-PL |
| 2591 | config: default |
| 2592 | split: test |
| 2593 | revision: 0be27e93455051e531182b85e85e425aba12e9d4 |
| 2594 | metrics: |
| 2595 | - type: ndcg_at_10 |
| 2596 | value: 80.76299999999999 |
| 2597 | - task: |
| 2598 | type: Retrieval |
| 2599 | dataset: |
| 2600 | type: mteb/quora |
| 2601 | name: MTEB QuoraRetrieval |
| 2602 | config: default |
| 2603 | split: test |
| 2604 | revision: None |
| 2605 | metrics: |
| 2606 | - type: ndcg_at_10 |
| 2607 | value: 88.022 |
| 2608 | - task: |
| 2609 | type: Clustering |
| 2610 | dataset: |
| 2611 | type: mteb/reddit-clustering |
| 2612 | name: MTEB RedditClustering |
| 2613 | config: default |
| 2614 | split: test |
| 2615 | revision: 24640382cdbf8abc73003fb0fa6d111a705499eb |
| 2616 | metrics: |
| 2617 | - type: v_measure |
| 2618 | value: 55.719165988934385 |
| 2619 | - task: |
| 2620 | type: Clustering |
| 2621 | dataset: |
| 2622 | type: mteb/reddit-clustering-p2p |
| 2623 | name: MTEB RedditClusteringP2P |
| 2624 | config: default |
| 2625 | split: test |
| 2626 | revision: 282350215ef01743dc01b456c7f5241fa8937f16 |
| 2627 | metrics: |
| 2628 | - type: v_measure |
| 2629 | value: 62.25390069273025 |
| 2630 | - task: |
| 2631 | type: Retrieval |
| 2632 | dataset: |
| 2633 | type: mteb/scidocs |
| 2634 | name: MTEB SCIDOCS |
| 2635 | config: default |
| 2636 | split: test |
| 2637 | revision: None |
| 2638 | metrics: |
| 2639 | - type: ndcg_at_10 |
| 2640 | value: 18.243000000000002 |
| 2641 | - task: |
| 2642 | type: Retrieval |
| 2643 | dataset: |
| 2644 | type: clarin-knext/scidocs-pl |
| 2645 | name: MTEB SCIDOCS-PL |
| 2646 | config: default |
| 2647 | split: test |
| 2648 | revision: 45452b03f05560207ef19149545f168e596c9337 |
| 2649 | metrics: |
| 2650 | - type: ndcg_at_10 |
| 2651 | value: 14.219000000000001 |
| 2652 | - task: |
| 2653 | type: PairClassification |
| 2654 | dataset: |
| 2655 | type: PL-MTEB/sicke-pl-pairclassification |
| 2656 | name: MTEB SICK-E-PL |
| 2657 | config: default |
| 2658 | split: test |
| 2659 | revision: None |
| 2660 | metrics: |
| 2661 | - type: cos_sim_ap |
| 2662 | value: 75.4022630307816 |
| 2663 | - task: |
| 2664 | type: STS |
| 2665 | dataset: |
| 2666 | type: mteb/sickr-sts |
| 2667 | name: MTEB SICK-R |
| 2668 | config: default |
| 2669 | split: test |
| 2670 | revision: a6ea5a8cab320b040a23452cc28066d9beae2cee |
| 2671 | metrics: |
| 2672 | - type: cos_sim_spearman |
| 2673 | value: 79.34269390198548 |
| 2674 | - task: |
| 2675 | type: STS |
| 2676 | dataset: |
| 2677 | type: PL-MTEB/sickr-pl-sts |
| 2678 | name: MTEB SICK-R-PL |
| 2679 | config: default |
| 2680 | split: test |
| 2681 | revision: None |
| 2682 | metrics: |
| 2683 | - type: cos_sim_spearman |
| 2684 | value: 74.0651660446132 |
| 2685 | - task: |
| 2686 | type: STS |
| 2687 | dataset: |
| 2688 | type: Lajavaness/SICK-fr |
| 2689 | name: MTEB SICKFr |
| 2690 | config: default |
| 2691 | split: test |
| 2692 | revision: e077ab4cf4774a1e36d86d593b150422fafd8e8a |
| 2693 | metrics: |
| 2694 | - type: cos_sim_spearman |
| 2695 | value: 78.62693119733123 |
| 2696 | - task: |
| 2697 | type: STS |
| 2698 | dataset: |
| 2699 | type: mteb/sts12-sts |
| 2700 | name: MTEB STS12 |
| 2701 | config: default |
| 2702 | split: test |
| 2703 | revision: a0d554a64d88156834ff5ae9920b964011b16384 |
| 2704 | metrics: |
| 2705 | - type: cos_sim_spearman |
| 2706 | value: 77.50660544631359 |
| 2707 | - task: |
| 2708 | type: STS |
| 2709 | dataset: |
| 2710 | type: mteb/sts13-sts |
| 2711 | name: MTEB STS13 |
| 2712 | config: default |
| 2713 | split: test |
| 2714 | revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca |
| 2715 | metrics: |
| 2716 | - type: cos_sim_spearman |
| 2717 | value: 85.55415077723738 |
| 2718 | - task: |
| 2719 | type: STS |
| 2720 | dataset: |
| 2721 | type: mteb/sts14-sts |
| 2722 | name: MTEB STS14 |
| 2723 | config: default |
| 2724 | split: test |
| 2725 | revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375 |
| 2726 | metrics: |
| 2727 | - type: cos_sim_spearman |
| 2728 | value: 81.67550814479077 |
| 2729 | - task: |
| 2730 | type: STS |
| 2731 | dataset: |
| 2732 | type: mteb/sts15-sts |
| 2733 | name: MTEB STS15 |
| 2734 | config: default |
| 2735 | split: test |
| 2736 | revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3 |
| 2737 | metrics: |
| 2738 | - type: cos_sim_spearman |
| 2739 | value: 88.94601412322764 |
| 2740 | - task: |
| 2741 | type: STS |
| 2742 | dataset: |
| 2743 | type: mteb/sts16-sts |
| 2744 | name: MTEB STS16 |
| 2745 | config: default |
| 2746 | split: test |
| 2747 | revision: 4d8694f8f0e0100860b497b999b3dbed754a0513 |
| 2748 | metrics: |
| 2749 | - type: cos_sim_spearman |
| 2750 | value: 84.33844259337481 |
| 2751 | - task: |
| 2752 | type: STS |
| 2753 | dataset: |
| 2754 | type: mteb/sts17-crosslingual-sts |
| 2755 | name: MTEB STS17 (ko-ko) |
| 2756 | config: ko-ko |
| 2757 | split: test |
| 2758 | revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d |
| 2759 | metrics: |
| 2760 | - type: cos_sim_spearman |
| 2761 | value: 81.58650681159105 |
| 2762 | - task: |
| 2763 | type: STS |
| 2764 | dataset: |
| 2765 | type: mteb/sts17-crosslingual-sts |
| 2766 | name: MTEB STS17 (ar-ar) |
| 2767 | config: ar-ar |
| 2768 | split: test |
| 2769 | revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d |
| 2770 | metrics: |
| 2771 | - type: cos_sim_spearman |
| 2772 | value: 78.82472265884256 |
| 2773 | - task: |
| 2774 | type: STS |
| 2775 | dataset: |
| 2776 | type: mteb/sts17-crosslingual-sts |
| 2777 | name: MTEB STS17 (en-ar) |
| 2778 | config: en-ar |
| 2779 | split: test |
| 2780 | revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d |
| 2781 | metrics: |
| 2782 | - type: cos_sim_spearman |
| 2783 | value: 76.43637938260397 |
| 2784 | - task: |
| 2785 | type: STS |
| 2786 | dataset: |
| 2787 | type: mteb/sts17-crosslingual-sts |
| 2788 | name: MTEB STS17 (en-de) |
| 2789 | config: en-de |
| 2790 | split: test |
| 2791 | revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d |
| 2792 | metrics: |
| 2793 | - type: cos_sim_spearman |
| 2794 | value: 84.71008299464059 |
| 2795 | - task: |
| 2796 | type: STS |
| 2797 | dataset: |
| 2798 | type: mteb/sts17-crosslingual-sts |
| 2799 | name: MTEB STS17 (en-en) |
| 2800 | config: en-en |
| 2801 | split: test |
| 2802 | revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d |
| 2803 | metrics: |
| 2804 | - type: cos_sim_spearman |
| 2805 | value: 88.88074713413747 |
| 2806 | - task: |
| 2807 | type: STS |
| 2808 | dataset: |
| 2809 | type: mteb/sts17-crosslingual-sts |
| 2810 | name: MTEB STS17 (en-tr) |
| 2811 | config: en-tr |
| 2812 | split: test |
| 2813 | revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d |
| 2814 | metrics: |
| 2815 | - type: cos_sim_spearman |
| 2816 | value: 76.36405640457285 |
| 2817 | - task: |
| 2818 | type: STS |
| 2819 | dataset: |
| 2820 | type: mteb/sts17-crosslingual-sts |
| 2821 | name: MTEB STS17 (es-en) |
| 2822 | config: es-en |
| 2823 | split: test |
| 2824 | revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d |
| 2825 | metrics: |
| 2826 | - type: cos_sim_spearman |
| 2827 | value: 83.84737910084762 |
| 2828 | - task: |
| 2829 | type: STS |
| 2830 | dataset: |
| 2831 | type: mteb/sts17-crosslingual-sts |
| 2832 | name: MTEB STS17 (es-es) |
| 2833 | config: es-es |
| 2834 | split: test |
| 2835 | revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d |
| 2836 | metrics: |
| 2837 | - type: cos_sim_spearman |
| 2838 | value: 87.03931621433031 |
| 2839 | - task: |
| 2840 | type: STS |
| 2841 | dataset: |
| 2842 | type: mteb/sts17-crosslingual-sts |
| 2843 | name: MTEB STS17 (fr-en) |
| 2844 | config: fr-en |
| 2845 | split: test |
| 2846 | revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d |
| 2847 | metrics: |
| 2848 | - type: cos_sim_spearman |
| 2849 | value: 84.43335591752246 |
| 2850 | - task: |
| 2851 | type: STS |
| 2852 | dataset: |
| 2853 | type: mteb/sts17-crosslingual-sts |
| 2854 | name: MTEB STS17 (it-en) |
| 2855 | config: it-en |
| 2856 | split: test |
| 2857 | revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d |
| 2858 | metrics: |
| 2859 | - type: cos_sim_spearman |
| 2860 | value: 83.85268648747021 |
| 2861 | - task: |
| 2862 | type: STS |
| 2863 | dataset: |
| 2864 | type: mteb/sts17-crosslingual-sts |
| 2865 | name: MTEB STS17 (nl-en) |
| 2866 | config: nl-en |
| 2867 | split: test |
| 2868 | revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d |
| 2869 | metrics: |
| 2870 | - type: cos_sim_spearman |
| 2871 | value: 82.45786516224341 |
| 2872 | - task: |
| 2873 | type: STS |
| 2874 | dataset: |
| 2875 | type: mteb/sts22-crosslingual-sts |
| 2876 | name: MTEB STS22 (en) |
| 2877 | config: en |
| 2878 | split: test |
| 2879 | revision: eea2b4fe26a775864c896887d910b76a8098ad3f |
| 2880 | metrics: |
| 2881 | - type: cos_sim_spearman |
| 2882 | value: 67.20227303970304 |
| 2883 | - task: |
| 2884 | type: STS |
| 2885 | dataset: |
| 2886 | type: mteb/sts22-crosslingual-sts |
| 2887 | name: MTEB STS22 (de) |
| 2888 | config: de |
| 2889 | split: test |
| 2890 | revision: eea2b4fe26a775864c896887d910b76a8098ad3f |
| 2891 | metrics: |
| 2892 | - type: cos_sim_spearman |
| 2893 | value: 60.892838305537126 |
| 2894 | - task: |
| 2895 | type: STS |
| 2896 | dataset: |
| 2897 | type: mteb/sts22-crosslingual-sts |
| 2898 | name: MTEB STS22 (es) |
| 2899 | config: es |
| 2900 | split: test |
| 2901 | revision: eea2b4fe26a775864c896887d910b76a8098ad3f |
| 2902 | metrics: |
| 2903 | - type: cos_sim_spearman |
| 2904 | value: 72.01876318464508 |
| 2905 | - task: |
| 2906 | type: STS |
| 2907 | dataset: |
| 2908 | type: mteb/sts22-crosslingual-sts |
| 2909 | name: MTEB STS22 (pl) |
| 2910 | config: pl |
| 2911 | split: test |
| 2912 | revision: eea2b4fe26a775864c896887d910b76a8098ad3f |
| 2913 | metrics: |
| 2914 | - type: cos_sim_spearman |
| 2915 | value: 42.3879320510127 |
| 2916 | - task: |
| 2917 | type: STS |
| 2918 | dataset: |
| 2919 | type: mteb/sts22-crosslingual-sts |
| 2920 | name: MTEB STS22 (tr) |
| 2921 | config: tr |
| 2922 | split: test |
| 2923 | revision: eea2b4fe26a775864c896887d910b76a8098ad3f |
| 2924 | metrics: |
| 2925 | - type: cos_sim_spearman |
| 2926 | value: 65.54048784845729 |
| 2927 | - task: |
| 2928 | type: STS |
| 2929 | dataset: |
| 2930 | type: mteb/sts22-crosslingual-sts |
| 2931 | name: MTEB STS22 (ar) |
| 2932 | config: ar |
| 2933 | split: test |
| 2934 | revision: eea2b4fe26a775864c896887d910b76a8098ad3f |
| 2935 | metrics: |
| 2936 | - type: cos_sim_spearman |
| 2937 | value: 58.55244068334867 |
| 2938 | - task: |
| 2939 | type: STS |
| 2940 | dataset: |
| 2941 | type: mteb/sts22-crosslingual-sts |
| 2942 | name: MTEB STS22 (ru) |
| 2943 | config: ru |
| 2944 | split: test |
| 2945 | revision: eea2b4fe26a775864c896887d910b76a8098ad3f |
| 2946 | metrics: |
| 2947 | - type: cos_sim_spearman |
| 2948 | value: 66.48710288440624 |
| 2949 | - task: |
| 2950 | type: STS |
| 2951 | dataset: |
| 2952 | type: mteb/sts22-crosslingual-sts |
| 2953 | name: MTEB STS22 (zh) |
| 2954 | config: zh |
| 2955 | split: test |
| 2956 | revision: eea2b4fe26a775864c896887d910b76a8098ad3f |
| 2957 | metrics: |
| 2958 | - type: cos_sim_spearman |
| 2959 | value: 66.585754901838 |
| 2960 | - task: |
| 2961 | type: STS |
| 2962 | dataset: |
| 2963 | type: mteb/sts22-crosslingual-sts |
| 2964 | name: MTEB STS22 (fr) |
| 2965 | config: fr |
| 2966 | split: test |
| 2967 | revision: eea2b4fe26a775864c896887d910b76a8098ad3f |
| 2968 | metrics: |
| 2969 | - type: cos_sim_spearman |
| 2970 | value: 81.03001290557805 |
| 2971 | - task: |
| 2972 | type: STS |
| 2973 | dataset: |
| 2974 | type: mteb/sts22-crosslingual-sts |
| 2975 | name: MTEB STS22 (de-en) |
| 2976 | config: de-en |
| 2977 | split: test |
| 2978 | revision: eea2b4fe26a775864c896887d910b76a8098ad3f |
| 2979 | metrics: |
| 2980 | - type: cos_sim_spearman |
| 2981 | value: 62.28001859884359 |
| 2982 | - task: |
| 2983 | type: STS |
| 2984 | dataset: |
| 2985 | type: mteb/sts22-crosslingual-sts |
| 2986 | name: MTEB STS22 (es-en) |
| 2987 | config: es-en |
| 2988 | split: test |
| 2989 | revision: eea2b4fe26a775864c896887d910b76a8098ad3f |
| 2990 | metrics: |
| 2991 | - type: cos_sim_spearman |
| 2992 | value: 79.64106342105019 |
| 2993 | - task: |
| 2994 | type: STS |
| 2995 | dataset: |
| 2996 | type: mteb/sts22-crosslingual-sts |
| 2997 | name: MTEB STS22 (it) |
| 2998 | config: it |
| 2999 | split: test |
| 3000 | revision: eea2b4fe26a775864c896887d910b76a8098ad3f |
| 3001 | metrics: |
| 3002 | - type: cos_sim_spearman |
| 3003 | value: 78.27915339361124 |
| 3004 | - task: |
| 3005 | type: STS |
| 3006 | dataset: |
| 3007 | type: mteb/sts22-crosslingual-sts |
| 3008 | name: MTEB STS22 (pl-en) |
| 3009 | config: pl-en |
| 3010 | split: test |
| 3011 | revision: eea2b4fe26a775864c896887d910b76a8098ad3f |
| 3012 | metrics: |
| 3013 | - type: cos_sim_spearman |
| 3014 | value: 78.28574268257462 |
| 3015 | - task: |
| 3016 | type: STS |
| 3017 | dataset: |
| 3018 | type: mteb/sts22-crosslingual-sts |
| 3019 | name: MTEB STS22 (zh-en) |
| 3020 | config: zh-en |
| 3021 | split: test |
| 3022 | revision: eea2b4fe26a775864c896887d910b76a8098ad3f |
| 3023 | metrics: |
| 3024 | - type: cos_sim_spearman |
| 3025 | value: 72.92658860751482 |
| 3026 | - task: |
| 3027 | type: STS |
| 3028 | dataset: |
| 3029 | type: mteb/sts22-crosslingual-sts |
| 3030 | name: MTEB STS22 (es-it) |
| 3031 | config: es-it |
| 3032 | split: test |
| 3033 | revision: eea2b4fe26a775864c896887d910b76a8098ad3f |
| 3034 | metrics: |
| 3035 | - type: cos_sim_spearman |
| 3036 | value: 74.83418886368217 |
| 3037 | - task: |
| 3038 | type: STS |
| 3039 | dataset: |
| 3040 | type: mteb/sts22-crosslingual-sts |
| 3041 | name: MTEB STS22 (de-fr) |
| 3042 | config: de-fr |
| 3043 | split: test |
| 3044 | revision: eea2b4fe26a775864c896887d910b76a8098ad3f |
| 3045 | metrics: |
| 3046 | - type: cos_sim_spearman |
| 3047 | value: 56.01064022625769 |
| 3048 | - task: |
| 3049 | type: STS |
| 3050 | dataset: |
| 3051 | type: mteb/sts22-crosslingual-sts |
| 3052 | name: MTEB STS22 (de-pl) |
| 3053 | config: de-pl |
| 3054 | split: test |
| 3055 | revision: eea2b4fe26a775864c896887d910b76a8098ad3f |
| 3056 | metrics: |
| 3057 | - type: cos_sim_spearman |
| 3058 | value: 53.64332829635126 |
| 3059 | - task: |
| 3060 | type: STS |
| 3061 | dataset: |
| 3062 | type: mteb/sts22-crosslingual-sts |
| 3063 | name: MTEB STS22 (fr-pl) |
| 3064 | config: fr-pl |
| 3065 | split: test |
| 3066 | revision: eea2b4fe26a775864c896887d910b76a8098ad3f |
| 3067 | metrics: |
| 3068 | - type: cos_sim_spearman |
| 3069 | value: 73.24670207647144 |
| 3070 | - task: |
| 3071 | type: STS |
| 3072 | dataset: |
| 3073 | type: C-MTEB/STSB |
| 3074 | name: MTEB STSB |
| 3075 | config: default |
| 3076 | split: test |
| 3077 | revision: 0cde68302b3541bb8b3c340dc0644b0b745b3dc0 |
| 3078 | metrics: |
| 3079 | - type: cos_sim_spearman |
| 3080 | value: 80.7157790971544 |
| 3081 | - task: |
| 3082 | type: STS |
| 3083 | dataset: |
| 3084 | type: mteb/stsbenchmark-sts |
| 3085 | name: MTEB STSBenchmark |
| 3086 | config: default |
| 3087 | split: test |
| 3088 | revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831 |
| 3089 | metrics: |
| 3090 | - type: cos_sim_spearman |
| 3091 | value: 86.45763616928973 |
| 3092 | - task: |
| 3093 | type: STS |
| 3094 | dataset: |
| 3095 | type: stsb_multi_mt |
| 3096 | name: MTEB STSBenchmarkMultilingualSTS (fr) |
| 3097 | config: fr |
| 3098 | split: test |
| 3099 | revision: 93d57ef91790589e3ce9c365164337a8a78b7632 |
| 3100 | metrics: |
| 3101 | - type: cos_sim_spearman |
| 3102 | value: 84.4335500335282 |
| 3103 | - task: |
| 3104 | type: Reranking |
| 3105 | dataset: |
| 3106 | type: mteb/scidocs-reranking |
| 3107 | name: MTEB SciDocsRR |
| 3108 | config: default |
| 3109 | split: test |
| 3110 | revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab |
| 3111 | metrics: |
| 3112 | - type: map |
| 3113 | value: 84.15276484499303 |
| 3114 | - task: |
| 3115 | type: Retrieval |
| 3116 | dataset: |
| 3117 | type: mteb/scifact |
| 3118 | name: MTEB SciFact |
| 3119 | config: default |
| 3120 | split: test |
| 3121 | revision: 0228b52cf27578f30900b9e5271d331663a030d7 |
| 3122 | metrics: |
| 3123 | - type: ndcg_at_10 |
| 3124 | value: 73.433 |
| 3125 | - task: |
| 3126 | type: Retrieval |
| 3127 | dataset: |
| 3128 | type: clarin-knext/scifact-pl |
| 3129 | name: MTEB SciFact-PL |
| 3130 | config: default |
| 3131 | split: test |
| 3132 | revision: 47932a35f045ef8ed01ba82bf9ff67f6e109207e |
| 3133 | metrics: |
| 3134 | - type: ndcg_at_10 |
| 3135 | value: 58.919999999999995 |
| 3136 | - task: |
| 3137 | type: PairClassification |
| 3138 | dataset: |
| 3139 | type: mteb/sprintduplicatequestions-pairclassification |
| 3140 | name: MTEB SprintDuplicateQuestions |
| 3141 | config: default |
| 3142 | split: test |
| 3143 | revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46 |
| 3144 | metrics: |
| 3145 | - type: cos_sim_ap |
| 3146 | value: 95.40564890916419 |
| 3147 | - task: |
| 3148 | type: Clustering |
| 3149 | dataset: |
| 3150 | type: mteb/stackexchange-clustering |
| 3151 | name: MTEB StackExchangeClustering |
| 3152 | config: default |
| 3153 | split: test |
| 3154 | revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259 |
| 3155 | metrics: |
| 3156 | - type: v_measure |
| 3157 | value: 63.41856697730145 |
| 3158 | - task: |
| 3159 | type: Clustering |
| 3160 | dataset: |
| 3161 | type: mteb/stackexchange-clustering-p2p |
| 3162 | name: MTEB StackExchangeClusteringP2P |
| 3163 | config: default |
| 3164 | split: test |
| 3165 | revision: 815ca46b2622cec33ccafc3735d572c266efdb44 |
| 3166 | metrics: |
| 3167 | - type: v_measure |
| 3168 | value: 31.709285904909112 |
| 3169 | - task: |
| 3170 | type: Reranking |
| 3171 | dataset: |
| 3172 | type: mteb/stackoverflowdupquestions-reranking |
| 3173 | name: MTEB StackOverflowDupQuestions |
| 3174 | config: default |
| 3175 | split: test |
| 3176 | revision: e185fbe320c72810689fc5848eb6114e1ef5ec69 |
| 3177 | metrics: |
| 3178 | - type: map |
| 3179 | value: 52.09341030060322 |
| 3180 | - task: |
| 3181 | type: Summarization |
| 3182 | dataset: |
| 3183 | type: mteb/summeval |
| 3184 | name: MTEB SummEval |
| 3185 | config: default |
| 3186 | split: test |
| 3187 | revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c |
| 3188 | metrics: |
| 3189 | - type: cos_sim_spearman |
| 3190 | value: 30.58262517835034 |
| 3191 | - task: |
| 3192 | type: Summarization |
| 3193 | dataset: |
| 3194 | type: lyon-nlp/summarization-summeval-fr-p2p |
| 3195 | name: MTEB SummEvalFr |
| 3196 | config: default |
| 3197 | split: test |
| 3198 | revision: b385812de6a9577b6f4d0f88c6a6e35395a94054 |
| 3199 | metrics: |
| 3200 | - type: cos_sim_spearman |
| 3201 | value: 29.744542072951358 |
| 3202 | - task: |
| 3203 | type: Reranking |
| 3204 | dataset: |
| 3205 | type: lyon-nlp/mteb-fr-reranking-syntec-s2p |
| 3206 | name: MTEB SyntecReranking |
| 3207 | config: default |
| 3208 | split: test |
| 3209 | revision: b205c5084a0934ce8af14338bf03feb19499c84d |
| 3210 | metrics: |
| 3211 | - type: map |
| 3212 | value: 88.03333333333333 |
| 3213 | - task: |
| 3214 | type: Retrieval |
| 3215 | dataset: |
| 3216 | type: lyon-nlp/mteb-fr-retrieval-syntec-s2p |
| 3217 | name: MTEB SyntecRetrieval |
| 3218 | config: default |
| 3219 | split: test |
| 3220 | revision: 77f7e271bf4a92b24fce5119f3486b583ca016ff |
| 3221 | metrics: |
| 3222 | - type: ndcg_at_10 |
| 3223 | value: 83.043 |
| 3224 | - task: |
| 3225 | type: Reranking |
| 3226 | dataset: |
| 3227 | type: C-MTEB/T2Reranking |
| 3228 | name: MTEB T2Reranking |
| 3229 | config: default |
| 3230 | split: dev |
| 3231 | revision: 76631901a18387f85eaa53e5450019b87ad58ef9 |
| 3232 | metrics: |
| 3233 | - type: map |
| 3234 | value: 67.08577894804324 |
| 3235 | - task: |
| 3236 | type: Retrieval |
| 3237 | dataset: |
| 3238 | type: C-MTEB/T2Retrieval |
| 3239 | name: MTEB T2Retrieval |
| 3240 | config: default |
| 3241 | split: dev |
| 3242 | revision: 8731a845f1bf500a4f111cf1070785c793d10e64 |
| 3243 | metrics: |
| 3244 | - type: ndcg_at_10 |
| 3245 | value: 84.718 |
| 3246 | - task: |
| 3247 | type: Classification |
| 3248 | dataset: |
| 3249 | type: C-MTEB/TNews-classification |
| 3250 | name: MTEB TNews |
| 3251 | config: default |
| 3252 | split: validation |
| 3253 | revision: 317f262bf1e6126357bbe89e875451e4b0938fe4 |
| 3254 | metrics: |
| 3255 | - type: accuracy |
| 3256 | value: 48.726 |
| 3257 | - task: |
| 3258 | type: Retrieval |
| 3259 | dataset: |
| 3260 | type: mteb/trec-covid |
| 3261 | name: MTEB TRECCOVID |
| 3262 | config: default |
| 3263 | split: test |
| 3264 | revision: None |
| 3265 | metrics: |
| 3266 | - type: ndcg_at_10 |
| 3267 | value: 57.56 |
| 3268 | - task: |
| 3269 | type: Retrieval |
| 3270 | dataset: |
| 3271 | type: clarin-knext/trec-covid-pl |
| 3272 | name: MTEB TRECCOVID-PL |
| 3273 | config: default |
| 3274 | split: test |
| 3275 | revision: 81bcb408f33366c2a20ac54adafad1ae7e877fdd |
| 3276 | metrics: |
| 3277 | - type: ndcg_at_10 |
| 3278 | value: 59.355999999999995 |
| 3279 | - task: |
| 3280 | type: BitextMining |
| 3281 | dataset: |
| 3282 | type: mteb/tatoeba-bitext-mining |
| 3283 | name: MTEB Tatoeba (sqi-eng) |
| 3284 | config: sqi-eng |
| 3285 | split: test |
| 3286 | revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
| 3287 | metrics: |
| 3288 | - type: f1 |
| 3289 | value: 82.765 |
| 3290 | - task: |
| 3291 | type: BitextMining |
| 3292 | dataset: |
| 3293 | type: mteb/tatoeba-bitext-mining |
| 3294 | name: MTEB Tatoeba (fry-eng) |
| 3295 | config: fry-eng |
| 3296 | split: test |
| 3297 | revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
| 3298 | metrics: |
| 3299 | - type: f1 |
| 3300 | value: 73.69942196531792 |
| 3301 | - task: |
| 3302 | type: BitextMining |
| 3303 | dataset: |
| 3304 | type: mteb/tatoeba-bitext-mining |
| 3305 | name: MTEB Tatoeba (kur-eng) |
| 3306 | config: kur-eng |
| 3307 | split: test |
| 3308 | revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
| 3309 | metrics: |
| 3310 | - type: f1 |
| 3311 | value: 32.86585365853657 |
| 3312 | - task: |
| 3313 | type: BitextMining |
| 3314 | dataset: |
| 3315 | type: mteb/tatoeba-bitext-mining |
| 3316 | name: MTEB Tatoeba (tur-eng) |
| 3317 | config: tur-eng |
| 3318 | split: test |
| 3319 | revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
| 3320 | metrics: |
| 3321 | - type: f1 |
| 3322 | value: 95.81666666666666 |
| 3323 | - task: |
| 3324 | type: BitextMining |
| 3325 | dataset: |
| 3326 | type: mteb/tatoeba-bitext-mining |
| 3327 | name: MTEB Tatoeba (deu-eng) |
| 3328 | config: deu-eng |
| 3329 | split: test |
| 3330 | revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
| 3331 | metrics: |
| 3332 | - type: f1 |
| 3333 | value: 97.75 |
| 3334 | - task: |
| 3335 | type: BitextMining |
| 3336 | dataset: |
| 3337 | type: mteb/tatoeba-bitext-mining |
| 3338 | name: MTEB Tatoeba (nld-eng) |
| 3339 | config: nld-eng |
| 3340 | split: test |
| 3341 | revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
| 3342 | metrics: |
| 3343 | - type: f1 |
| 3344 | value: 93.78333333333335 |
| 3345 | - task: |
| 3346 | type: BitextMining |
| 3347 | dataset: |
| 3348 | type: mteb/tatoeba-bitext-mining |
| 3349 | name: MTEB Tatoeba (ron-eng) |
| 3350 | config: ron-eng |
| 3351 | split: test |
| 3352 | revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
| 3353 | metrics: |
| 3354 | - type: f1 |
| 3355 | value: 90.72333333333333 |
| 3356 | - task: |
| 3357 | type: BitextMining |
| 3358 | dataset: |
| 3359 | type: mteb/tatoeba-bitext-mining |
| 3360 | name: MTEB Tatoeba (ang-eng) |
| 3361 | config: ang-eng |
| 3362 | split: test |
| 3363 | revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
| 3364 | metrics: |
| 3365 | - type: f1 |
| 3366 | value: 42.45202558635395 |
| 3367 | - task: |
| 3368 | type: BitextMining |
| 3369 | dataset: |
| 3370 | type: mteb/tatoeba-bitext-mining |
| 3371 | name: MTEB Tatoeba (ido-eng) |
| 3372 | config: ido-eng |
| 3373 | split: test |
| 3374 | revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
| 3375 | metrics: |
| 3376 | - type: f1 |
| 3377 | value: 77.59238095238095 |
| 3378 | - task: |
| 3379 | type: BitextMining |
| 3380 | dataset: |
| 3381 | type: mteb/tatoeba-bitext-mining |
| 3382 | name: MTEB Tatoeba (jav-eng) |
| 3383 | config: jav-eng |
| 3384 | split: test |
| 3385 | revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
| 3386 | metrics: |
| 3387 | - type: f1 |
| 3388 | value: 35.69686411149825 |
| 3389 | - task: |
| 3390 | type: BitextMining |
| 3391 | dataset: |
| 3392 | type: mteb/tatoeba-bitext-mining |
| 3393 | name: MTEB Tatoeba (isl-eng) |
| 3394 | config: isl-eng |
| 3395 | split: test |
| 3396 | revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
| 3397 | metrics: |
| 3398 | - type: f1 |
| 3399 | value: 82.59333333333333 |
| 3400 | - task: |
| 3401 | type: BitextMining |
| 3402 | dataset: |
| 3403 | type: mteb/tatoeba-bitext-mining |
| 3404 | name: MTEB Tatoeba (slv-eng) |
| 3405 | config: slv-eng |
| 3406 | split: test |
| 3407 | revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
| 3408 | metrics: |
| 3409 | - type: f1 |
| 3410 | value: 84.1456922987907 |
| 3411 | - task: |
| 3412 | type: BitextMining |
| 3413 | dataset: |
| 3414 | type: mteb/tatoeba-bitext-mining |
| 3415 | name: MTEB Tatoeba (cym-eng) |
| 3416 | config: cym-eng |
| 3417 | split: test |
| 3418 | revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
| 3419 | metrics: |
| 3420 | - type: f1 |
| 3421 | value: 52.47462133594857 |
| 3422 | - task: |
| 3423 | type: BitextMining |
| 3424 | dataset: |
| 3425 | type: mteb/tatoeba-bitext-mining |
| 3426 | name: MTEB Tatoeba (kaz-eng) |
| 3427 | config: kaz-eng |
| 3428 | split: test |
| 3429 | revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
| 3430 | metrics: |
| 3431 | - type: f1 |
| 3432 | value: 67.62965440356746 |
| 3433 | - task: |
| 3434 | type: BitextMining |
| 3435 | dataset: |
| 3436 | type: mteb/tatoeba-bitext-mining |
| 3437 | name: MTEB Tatoeba (est-eng) |
| 3438 | config: est-eng |
| 3439 | split: test |
| 3440 | revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
| 3441 | metrics: |
| 3442 | - type: f1 |
| 3443 | value: 79.48412698412699 |
| 3444 | - task: |
| 3445 | type: BitextMining |
| 3446 | dataset: |
| 3447 | type: mteb/tatoeba-bitext-mining |
| 3448 | name: MTEB Tatoeba (heb-eng) |
| 3449 | config: heb-eng |
| 3450 | split: test |
| 3451 | revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
| 3452 | metrics: |
| 3453 | - type: f1 |
| 3454 | value: 75.85 |
| 3455 | - task: |
| 3456 | type: BitextMining |
| 3457 | dataset: |
| 3458 | type: mteb/tatoeba-bitext-mining |
| 3459 | name: MTEB Tatoeba (gla-eng) |
| 3460 | config: gla-eng |
| 3461 | split: test |
| 3462 | revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
| 3463 | metrics: |
| 3464 | - type: f1 |
| 3465 | value: 27.32600866497127 |
| 3466 | - task: |
| 3467 | type: BitextMining |
| 3468 | dataset: |
| 3469 | type: mteb/tatoeba-bitext-mining |
| 3470 | name: MTEB Tatoeba (mar-eng) |
| 3471 | config: mar-eng |
| 3472 | split: test |
| 3473 | revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
| 3474 | metrics: |
| 3475 | - type: f1 |
| 3476 | value: 84.38 |
| 3477 | - task: |
| 3478 | type: BitextMining |
| 3479 | dataset: |
| 3480 | type: mteb/tatoeba-bitext-mining |
| 3481 | name: MTEB Tatoeba (lat-eng) |
| 3482 | config: lat-eng |
| 3483 | split: test |
| 3484 | revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
| 3485 | metrics: |
| 3486 | - type: f1 |
| 3487 | value: 42.98888712165028 |
| 3488 | - task: |
| 3489 | type: BitextMining |
| 3490 | dataset: |
| 3491 | type: mteb/tatoeba-bitext-mining |
| 3492 | name: MTEB Tatoeba (bel-eng) |
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| 3503 | name: MTEB Tatoeba (pms-eng) |
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| 3514 | name: MTEB Tatoeba (gle-eng) |
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| 3613 | name: MTEB Tatoeba (hye-eng) |
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| 3624 | name: MTEB Tatoeba (tel-eng) |
| 3625 | config: tel-eng |
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| 3635 | name: MTEB Tatoeba (afr-eng) |
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| 3646 | name: MTEB Tatoeba (mon-eng) |
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| 3657 | name: MTEB Tatoeba (arz-eng) |
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| 3668 | name: MTEB Tatoeba (hrv-eng) |
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| 3679 | name: MTEB Tatoeba (nov-eng) |
| 3680 | config: nov-eng |
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| 3690 | name: MTEB Tatoeba (gsw-eng) |
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| 3701 | name: MTEB Tatoeba (nds-eng) |
| 3702 | config: nds-eng |
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| 3712 | name: MTEB Tatoeba (ukr-eng) |
| 3713 | config: ukr-eng |
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| 3723 | name: MTEB Tatoeba (uzb-eng) |
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| 3734 | name: MTEB Tatoeba (lit-eng) |
| 3735 | config: lit-eng |
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| 3745 | name: MTEB Tatoeba (ina-eng) |
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| 3756 | name: MTEB Tatoeba (lfn-eng) |
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| 3767 | name: MTEB Tatoeba (zsm-eng) |
| 3768 | config: zsm-eng |
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| 3770 | revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
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| 3778 | name: MTEB Tatoeba (ita-eng) |
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| 3789 | name: MTEB Tatoeba (cmn-eng) |
| 3790 | config: cmn-eng |
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| 3800 | name: MTEB Tatoeba (lvs-eng) |
| 3801 | config: lvs-eng |
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| 3811 | name: MTEB Tatoeba (glg-eng) |
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| 3822 | name: MTEB Tatoeba (ceb-eng) |
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| 3833 | name: MTEB Tatoeba (bre-eng) |
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| 3844 | name: MTEB Tatoeba (ben-eng) |
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| 3855 | name: MTEB Tatoeba (swg-eng) |
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| 3866 | name: MTEB Tatoeba (arq-eng) |
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| 3877 | name: MTEB Tatoeba (kab-eng) |
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| 3880 | revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
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| 3888 | name: MTEB Tatoeba (fra-eng) |
| 3889 | config: fra-eng |
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| 3899 | name: MTEB Tatoeba (por-eng) |
| 3900 | config: por-eng |
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| 3910 | name: MTEB Tatoeba (tat-eng) |
| 3911 | config: tat-eng |
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| 3921 | name: MTEB Tatoeba (oci-eng) |
| 3922 | config: oci-eng |
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| 3932 | name: MTEB Tatoeba (pol-eng) |
| 3933 | config: pol-eng |
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| 3943 | name: MTEB Tatoeba (war-eng) |
| 3944 | config: war-eng |
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| 3954 | name: MTEB Tatoeba (aze-eng) |
| 3955 | config: aze-eng |
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| 3965 | name: MTEB Tatoeba (vie-eng) |
| 3966 | config: vie-eng |
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| 3976 | name: MTEB Tatoeba (nno-eng) |
| 3977 | config: nno-eng |
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| 3987 | name: MTEB Tatoeba (cha-eng) |
| 3988 | config: cha-eng |
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| 3997 | type: mteb/tatoeba-bitext-mining |
| 3998 | name: MTEB Tatoeba (mhr-eng) |
| 3999 | config: mhr-eng |
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| 4001 | revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
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| 4009 | name: MTEB Tatoeba (dan-eng) |
| 4010 | config: dan-eng |
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| 4012 | revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
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| 4019 | type: mteb/tatoeba-bitext-mining |
| 4020 | name: MTEB Tatoeba (ell-eng) |
| 4021 | config: ell-eng |
| 4022 | split: test |
| 4023 | revision: 9080400076fbadbb4c4dcb136ff4eddc40b42553 |
| 4024 | metrics: |
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| 4029 | dataset: |
| 4030 | type: mteb/tatoeba-bitext-mining |
| 4031 | name: MTEB Tatoeba (amh-eng) |
| 4032 | config: amh-eng |
| 4033 | split: test |
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| 4493 | name: MTEB Tatoeba (tha-eng) |
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| 4514 | type: C-MTEB/ThuNewsClusteringP2P |
| 4515 | name: MTEB ThuNewsClusteringP2P |
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| 4517 | split: test |
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| 4526 | name: MTEB ThuNewsClusteringS2S |
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| 4534 | type: Retrieval |
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| 4536 | type: mteb/touche2020 |
| 4537 | name: MTEB Touche2020 |
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| 4539 | split: test |
| 4540 | revision: a34f9a33db75fa0cbb21bb5cfc3dae8dc8bec93f |
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| 4545 | type: Classification |
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| 4547 | type: mteb/toxic_conversations_50k |
| 4548 | name: MTEB ToxicConversationsClassification |
| 4549 | config: default |
| 4550 | split: test |
| 4551 | revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c |
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| 4556 | type: Classification |
| 4557 | dataset: |
| 4558 | type: mteb/tweet_sentiment_extraction |
| 4559 | name: MTEB TweetSentimentExtractionClassification |
| 4560 | config: default |
| 4561 | split: test |
| 4562 | revision: d604517c81ca91fe16a244d1248fc021f9ecee7a |
| 4563 | metrics: |
| 4564 | - type: accuracy |
| 4565 | value: 57.60045274476514 |
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| 4567 | type: Clustering |
| 4568 | dataset: |
| 4569 | type: mteb/twentynewsgroups-clustering |
| 4570 | name: MTEB TwentyNewsgroupsClustering |
| 4571 | config: default |
| 4572 | split: test |
| 4573 | revision: 6125ec4e24fa026cec8a478383ee943acfbd5449 |
| 4574 | metrics: |
| 4575 | - type: v_measure |
| 4576 | value: 50.346666699466205 |
| 4577 | - task: |
| 4578 | type: PairClassification |
| 4579 | dataset: |
| 4580 | type: mteb/twittersemeval2015-pairclassification |
| 4581 | name: MTEB TwitterSemEval2015 |
| 4582 | config: default |
| 4583 | split: test |
| 4584 | revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1 |
| 4585 | metrics: |
| 4586 | - type: cos_sim_ap |
| 4587 | value: 71.88199004440489 |
| 4588 | - task: |
| 4589 | type: PairClassification |
| 4590 | dataset: |
| 4591 | type: mteb/twitterurlcorpus-pairclassification |
| 4592 | name: MTEB TwitterURLCorpus |
| 4593 | config: default |
| 4594 | split: test |
| 4595 | revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf |
| 4596 | metrics: |
| 4597 | - type: cos_sim_ap |
| 4598 | value: 85.41587779677383 |
| 4599 | - task: |
| 4600 | type: Retrieval |
| 4601 | dataset: |
| 4602 | type: C-MTEB/VideoRetrieval |
| 4603 | name: MTEB VideoRetrieval |
| 4604 | config: default |
| 4605 | split: dev |
| 4606 | revision: 58c2597a5943a2ba48f4668c3b90d796283c5639 |
| 4607 | metrics: |
| 4608 | - type: ndcg_at_10 |
| 4609 | value: 72.792 |
| 4610 | - task: |
| 4611 | type: Classification |
| 4612 | dataset: |
| 4613 | type: C-MTEB/waimai-classification |
| 4614 | name: MTEB Waimai |
| 4615 | config: default |
| 4616 | split: test |
| 4617 | revision: 339287def212450dcaa9df8c22bf93e9980c7023 |
| 4618 | metrics: |
| 4619 | - type: accuracy |
| 4620 | value: 82.58000000000001 |
| 4621 | - task: |
| 4622 | type: Retrieval |
| 4623 | dataset: |
| 4624 | type: jinaai/xpqa |
| 4625 | name: MTEB XPQARetrieval (fr) |
| 4626 | config: fr |
| 4627 | split: test |
| 4628 | revision: c99d599f0a6ab9b85b065da6f9d94f9cf731679f |
| 4629 | metrics: |
| 4630 | - type: ndcg_at_10 |
| 4631 | value: 67.327 |
| 4632 | --- |
| 4633 | |
| 4634 | ## gte-multilingual-base |
| 4635 | |
| 4636 | The **gte-multilingual-base** model is the latest in the [GTE](https://huggingface.co/collections/Alibaba-NLP/gte-models-6680f0b13f885cb431e6d469) (General Text Embedding) family of models, featuring several key attributes: |
| 4637 | |
| 4638 | - **High Performance**: Achieves state-of-the-art (SOTA) results in multilingual retrieval tasks and multi-task representation model evaluations when compared to models of similar size. |
| 4639 | - **Training Architecture**: Trained using an encoder-only transformers architecture, resulting in a smaller model size. Unlike previous models based on decode-only LLM architecture (e.g., gte-qwen2-1.5b-instruct), this model has lower hardware requirements for inference, offering a 10x increase in inference speed. |
| 4640 | - **Long Context**: Supports text lengths up to **8192** tokens. |
| 4641 | - **Multilingual Capability**: Supports over **70** languages. |
| 4642 | - **Elastic Dense Embedding**: Support elastic output dense representation while maintaining the effectiveness of downstream tasks, which significantly reduces storage costs and improves execution efficiency. |
| 4643 | - **Sparse Vectors**: In addition to dense representations, it can also generate sparse vectors. |
| 4644 | |
| 4645 | |
| 4646 | **Paper**: [mGTE: Generalized Long-Context Text Representation and Reranking Models for Multilingual Text Retrieval](https://arxiv.org/pdf/2407.19669) |
| 4647 | |
| 4648 | ## Model Information |
| 4649 | - Model Size: 305M |
| 4650 | - Embedding Dimension: 768 |
| 4651 | - Max Input Tokens: 8192 |
| 4652 | |
| 4653 | |
| 4654 | ## Usage |
| 4655 | |
| 4656 | - **It is recommended to install xformers and enable unpadding for acceleration, |
| 4657 | refer to [enable-unpadding-and-xformers](https://huggingface.co/Alibaba-NLP/new-impl#recommendation-enable-unpadding-and-acceleration-with-xformers).** |
| 4658 | - **How to use it offline: [new-impl/discussions/2](https://huggingface.co/Alibaba-NLP/new-impl/discussions/2#662b08d04d8c3d0a09c88fa3)** |
| 4659 | - **How to use with [TEI](https://github.com/huggingface/text-embeddings-inference): [refs/pr/7](https://huggingface.co/Alibaba-NLP/gte-multilingual-base/discussions/7#66bfb82ea03b764ca92a2221)** |
| 4660 | |
| 4661 | |
| 4662 | |
| 4663 | ### Get Dense Embeddings with Transformers |
| 4664 | ```python |
| 4665 | # Requires transformers>=4.36.0 |
| 4666 | |
| 4667 | import torch.nn.functional as F |
| 4668 | from transformers import AutoModel, AutoTokenizer |
| 4669 | |
| 4670 | input_texts = [ |
| 4671 | "what is the capital of China?", |
| 4672 | "how to implement quick sort in python?", |
| 4673 | "北京", |
| 4674 | "快排算法介绍" |
| 4675 | ] |
| 4676 | |
| 4677 | model_name_or_path = 'Alibaba-NLP/gte-multilingual-base' |
| 4678 | tokenizer = AutoTokenizer.from_pretrained(model_name_or_path) |
| 4679 | model = AutoModel.from_pretrained(model_name_or_path, trust_remote_code=True) |
| 4680 | |
| 4681 | # Tokenize the input texts |
| 4682 | batch_dict = tokenizer(input_texts, max_length=8192, padding=True, truncation=True, return_tensors='pt') |
| 4683 | |
| 4684 | outputs = model(**batch_dict) |
| 4685 | |
| 4686 | dimension=768 # The output dimension of the output embedding, should be in [128, 768] |
| 4687 | embeddings = outputs.last_hidden_state[:, 0][:dimension] |
| 4688 | |
| 4689 | embeddings = F.normalize(embeddings, p=2, dim=1) |
| 4690 | scores = (embeddings[:1] @ embeddings[1:].T) * 100 |
| 4691 | print(scores.tolist()) |
| 4692 | |
| 4693 | # [[0.3016996383666992, 0.7503870129585266, 0.3203084468841553]] |
| 4694 | ``` |
| 4695 | |
| 4696 | ### Use with sentence-transformers |
| 4697 | ```python |
| 4698 | # Requires sentence-transformers>=3.0.0 |
| 4699 | |
| 4700 | from sentence_transformers import SentenceTransformer |
| 4701 | |
| 4702 | input_texts = [ |
| 4703 | "what is the capital of China?", |
| 4704 | "how to implement quick sort in python?", |
| 4705 | "北京", |
| 4706 | "快排算法介绍" |
| 4707 | ] |
| 4708 | |
| 4709 | model_name_or_path="Alibaba-NLP/gte-multilingual-base" |
| 4710 | model = SentenceTransformer(model_name_or_path, trust_remote_code=True) |
| 4711 | embeddings = model.encode(input_texts, normalize_embeddings=True) # embeddings.shape (4, 768) |
| 4712 | |
| 4713 | # sim scores |
| 4714 | scores = model.similarity(embeddings[:1], embeddings[1:]) |
| 4715 | |
| 4716 | print(scores.tolist()) |
| 4717 | # [[0.301699697971344, 0.7503870129585266, 0.32030850648880005]] |
| 4718 | ``` |
| 4719 | |
| 4720 | ### Use with infinity |
| 4721 | |
| 4722 | Usage via docker and [infinity](https://github.com/michaelfeil/infinity), MIT Licensed. |
| 4723 | ``` |
| 4724 | docker run --gpus all -v $PWD/data:/app/.cache -p "7997":"7997" \ |
| 4725 | michaelf34/infinity:0.0.69 \ |
| 4726 | v2 --model-id Alibaba-NLP/gte-multilingual-base --revision "main" --dtype float16 --batch-size 32 --device cuda --engine torch --port 7997 |
| 4727 | ``` |
| 4728 | |
| 4729 | ### Use with Text Embeddings Inference (TEI) |
| 4730 | |
| 4731 | Usage via Docker and [Text Embeddings Inference (TEI)](https://github.com/huggingface/text-embeddings-inference): |
| 4732 | |
| 4733 | - CPU: |
| 4734 | |
| 4735 | ```bash |
| 4736 | docker run --platform linux/amd64 \ |
| 4737 | -p 8080:80 \ |
| 4738 | -v $PWD/data:/data \ |
| 4739 | --pull always \ |
| 4740 | ghcr.io/huggingface/text-embeddings-inference:cpu-1.7 \ |
| 4741 | --model-id Alibaba-NLP/gte-multilingual-base \ |
| 4742 | --dtype float16 |
| 4743 | ``` |
| 4744 | |
| 4745 | - GPU: |
| 4746 | |
| 4747 | ``` |
| 4748 | docker run --gpus all \ |
| 4749 | -p 8080:80 \ |
| 4750 | -v $PWD/data:/data \ |
| 4751 | --pull always \ |
| 4752 | ghcr.io/huggingface/text-embeddings-inference:1.7 \ |
| 4753 | --model-id Alibaba-NLP/gte-multilingual-base \ |
| 4754 | --dtype float16 |
| 4755 | ``` |
| 4756 | |
| 4757 | Then you can send requests to the deployed API via the OpenAI-compatible `v1/embeddings` route (more information about the [OpenAI Embeddings API](https://platform.openai.com/docs/api-reference/embeddings)): |
| 4758 | |
| 4759 | ```bash |
| 4760 | curl https://0.0.0.0:8080/v1/embeddings \ |
| 4761 | -H "Content-Type: application/json" \ |
| 4762 | -d '{ |
| 4763 | "input": [ |
| 4764 | "what is the capital of China?", |
| 4765 | "how to implement quick sort in python?", |
| 4766 | "北京", |
| 4767 | "快排算法介绍" |
| 4768 | ], |
| 4769 | "model": "Alibaba-NLP/gte-multilingual-base", |
| 4770 | "encoding_format": "float" |
| 4771 | }' |
| 4772 | ``` |
| 4773 | |
| 4774 | ### Use with custom code to get dense embeddings and sparse token weights |
| 4775 | ```python |
| 4776 | # You can find the script gte_embedding.py in https://huggingface.co/Alibaba-NLP/gte-multilingual-base/blob/main/scripts/gte_embedding.py |
| 4777 | |
| 4778 | from gte_embedding import GTEEmbeddidng |
| 4779 | |
| 4780 | model_name_or_path = 'Alibaba-NLP/gte-multilingual-base' |
| 4781 | model = GTEEmbeddidng(model_name_or_path) |
| 4782 | query = "中国的首都在哪儿" |
| 4783 | |
| 4784 | docs = [ |
| 4785 | "what is the capital of China?", |
| 4786 | "how to implement quick sort in python?", |
| 4787 | "北京", |
| 4788 | "快排算法介绍" |
| 4789 | ] |
| 4790 | |
| 4791 | embs = model.encode(docs, return_dense=True,return_sparse=True) |
| 4792 | print('dense_embeddings vecs', embs['dense_embeddings']) |
| 4793 | print('token_weights', embs['token_weights']) |
| 4794 | pairs = [(query, doc) for doc in docs] |
| 4795 | dense_scores = model.compute_scores(pairs, dense_weight=1.0, sparse_weight=0.0) |
| 4796 | sparse_scores = model.compute_scores(pairs, dense_weight=0.0, sparse_weight=1.0) |
| 4797 | hybrid_scores = model.compute_scores(pairs, dense_weight=1.0, sparse_weight=0.3) |
| 4798 | |
| 4799 | print('dense_scores', dense_scores) |
| 4800 | print('sparse_scores', sparse_scores) |
| 4801 | print('hybrid_scores', hybrid_scores) |
| 4802 | |
| 4803 | # dense_scores [0.85302734375, 0.257568359375, 0.76953125, 0.325439453125] |
| 4804 | # sparse_scores [0.0, 0.0, 4.600879669189453, 1.570279598236084] |
| 4805 | # hybrid_scores [0.85302734375, 0.257568359375, 2.1497951507568356, 0.7965233325958252] |
| 4806 | |
| 4807 | ``` |
| 4808 | |
| 4809 | ## Evaluation |
| 4810 | |
| 4811 | We validated the performance of the **gte-multilingual-base** model on multiple downstream tasks, including multilingual retrieval, cross-lingual retrieval, long text retrieval, and general text representation evaluation on the [MTEB Leaderboard](https://huggingface.co/spaces/mteb/leaderboard), among others. |
| 4812 | |
| 4813 | ### Retrieval Task |
| 4814 | |
| 4815 | Retrieval results on [MIRACL](https://arxiv.org/abs/2210.09984) and [MLDR](https://arxiv.org/abs/2402.03216) (multilingual), [MKQA](https://arxiv.org/abs/2007.15207) (crosslingual), [BEIR](https://arxiv.org/abs/2104.08663) and [LoCo](https://arxiv.org/abs/2402.07440) (English). |
| 4816 | |
| 4817 |  |
| 4818 | |
| 4819 | - Detail results on [MLDR](https://arxiv.org/abs/2402.03216) |
| 4820 | |
| 4821 |  |
| 4822 | |
| 4823 | - Detail results on [LoCo](https://arxiv.org/abs/2402.07440) |
| 4824 | |
| 4825 | ### MTEB |
| 4826 | |
| 4827 | Results on MTEB English, Chinese, French, Polish |
| 4828 | |
| 4829 |  |
| 4830 | |
| 4831 | **More detailed experimental results can be found in the [paper](https://arxiv.org/pdf/2407.19669)**. |
| 4832 | |
| 4833 | |
| 4834 | ## Cloud API Services |
| 4835 | |
| 4836 | In addition to the open-source [GTE](https://huggingface.co/collections/Alibaba-NLP/gte-models-6680f0b13f885cb431e6d469) series models, GTE series models are also available as commercial API services on Alibaba Cloud. |
| 4837 | |
| 4838 | - [Embedding Models](https://help.aliyun.com/zh/model-studio/developer-reference/general-text-embedding/): Three versions of the text embedding models are available: text-embedding-v1/v2/v3, with v3 being the latest API service. |
| 4839 | - [ReRank Models](https://help.aliyun.com/zh/model-studio/developer-reference/general-text-sorting-model/): The gte-rerank model service is available. |
| 4840 | |
| 4841 | Note that the models behind the commercial APIs are not entirely identical to the open-source models. |
| 4842 | |
| 4843 | ## Citation |
| 4844 | If you find our paper or models helpful, please consider cite: |
| 4845 | |
| 4846 | ``` |
| 4847 | @inproceedings{zhang2024mgte, |
| 4848 | title={mGTE: Generalized Long-Context Text Representation and Reranking Models for Multilingual Text Retrieval}, |
| 4849 | author={Zhang, Xin and Zhang, Yanzhao and Long, Dingkun and Xie, Wen and Dai, Ziqi and Tang, Jialong and Lin, Huan and Yang, Baosong and Xie, Pengjun and Huang, Fei and others}, |
| 4850 | booktitle={Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing: Industry Track}, |
| 4851 | pages={1393--1412}, |
| 4852 | year={2024} |
| 4853 | } |
| 4854 | ``` |