Qi Liu
commited on
Commit
•
ae13eea
1
Parent(s):
4dd8502
Update README.md
Browse files
README.md
CHANGED
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@@ -1,3 +1,1110 @@
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| 2 |
license: apache-2.0
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| 3 |
---
|
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|
| 1 |
---
|
| 2 |
+
tags:
|
| 3 |
+
- finetuner
|
| 4 |
+
- mteb
|
| 5 |
+
- sentence-transformers
|
| 6 |
+
- feature-extraction
|
| 7 |
+
- sentence-similarity
|
| 8 |
+
- alibi
|
| 9 |
license: apache-2.0
|
| 10 |
+
language:
|
| 11 |
+
- en
|
| 12 |
+
- zh
|
| 13 |
+
model-index:
|
| 14 |
+
- name: jina-embeddings-v2-base-zh
|
| 15 |
+
results:
|
| 16 |
+
- task:
|
| 17 |
+
type: STS
|
| 18 |
+
dataset:
|
| 19 |
+
type: C-MTEB/AFQMC
|
| 20 |
+
name: MTEB AFQMC
|
| 21 |
+
config: default
|
| 22 |
+
split: validation
|
| 23 |
+
revision: None
|
| 24 |
+
metrics:
|
| 25 |
+
- type: cos_sim_pearson
|
| 26 |
+
value: 48.51403119231363
|
| 27 |
+
- type: cos_sim_spearman
|
| 28 |
+
value: 50.5928547846445
|
| 29 |
+
- type: euclidean_pearson
|
| 30 |
+
value: 48.750436310559074
|
| 31 |
+
- type: euclidean_spearman
|
| 32 |
+
value: 50.50950238691385
|
| 33 |
+
- type: manhattan_pearson
|
| 34 |
+
value: 48.7866189440328
|
| 35 |
+
- type: manhattan_spearman
|
| 36 |
+
value: 50.58692402017165
|
| 37 |
+
- task:
|
| 38 |
+
type: STS
|
| 39 |
+
dataset:
|
| 40 |
+
type: C-MTEB/ATEC
|
| 41 |
+
name: MTEB ATEC
|
| 42 |
+
config: default
|
| 43 |
+
split: test
|
| 44 |
+
revision: None
|
| 45 |
+
metrics:
|
| 46 |
+
- type: cos_sim_pearson
|
| 47 |
+
value: 50.25985700105725
|
| 48 |
+
- type: cos_sim_spearman
|
| 49 |
+
value: 51.28815934593989
|
| 50 |
+
- type: euclidean_pearson
|
| 51 |
+
value: 52.70329248799904
|
| 52 |
+
- type: euclidean_spearman
|
| 53 |
+
value: 50.94101139559258
|
| 54 |
+
- type: manhattan_pearson
|
| 55 |
+
value: 52.6647237400892
|
| 56 |
+
- type: manhattan_spearman
|
| 57 |
+
value: 50.922441325406176
|
| 58 |
+
- task:
|
| 59 |
+
type: Classification
|
| 60 |
+
dataset:
|
| 61 |
+
type: mteb/amazon_reviews_multi
|
| 62 |
+
name: MTEB AmazonReviewsClassification (zh)
|
| 63 |
+
config: zh
|
| 64 |
+
split: test
|
| 65 |
+
revision: 1399c76144fd37290681b995c656ef9b2e06e26d
|
| 66 |
+
metrics:
|
| 67 |
+
- type: accuracy
|
| 68 |
+
value: 34.944
|
| 69 |
+
- type: f1
|
| 70 |
+
value: 34.06478860660109
|
| 71 |
+
- task:
|
| 72 |
+
type: STS
|
| 73 |
+
dataset:
|
| 74 |
+
type: C-MTEB/BQ
|
| 75 |
+
name: MTEB BQ
|
| 76 |
+
config: default
|
| 77 |
+
split: test
|
| 78 |
+
revision: None
|
| 79 |
+
metrics:
|
| 80 |
+
- type: cos_sim_pearson
|
| 81 |
+
value: 65.15667035488342
|
| 82 |
+
- type: cos_sim_spearman
|
| 83 |
+
value: 66.07110142081
|
| 84 |
+
- type: euclidean_pearson
|
| 85 |
+
value: 60.447598102249714
|
| 86 |
+
- type: euclidean_spearman
|
| 87 |
+
value: 61.826575796578766
|
| 88 |
+
- type: manhattan_pearson
|
| 89 |
+
value: 60.39364279354984
|
| 90 |
+
- type: manhattan_spearman
|
| 91 |
+
value: 61.78743491223281
|
| 92 |
+
- task:
|
| 93 |
+
type: Clustering
|
| 94 |
+
dataset:
|
| 95 |
+
type: C-MTEB/CLSClusteringP2P
|
| 96 |
+
name: MTEB CLSClusteringP2P
|
| 97 |
+
config: default
|
| 98 |
+
split: test
|
| 99 |
+
revision: None
|
| 100 |
+
metrics:
|
| 101 |
+
- type: v_measure
|
| 102 |
+
value: 39.96714175391701
|
| 103 |
+
- task:
|
| 104 |
+
type: Clustering
|
| 105 |
+
dataset:
|
| 106 |
+
type: C-MTEB/CLSClusteringS2S
|
| 107 |
+
name: MTEB CLSClusteringS2S
|
| 108 |
+
config: default
|
| 109 |
+
split: test
|
| 110 |
+
revision: None
|
| 111 |
+
metrics:
|
| 112 |
+
- type: v_measure
|
| 113 |
+
value: 38.39863566717934
|
| 114 |
+
- task:
|
| 115 |
+
type: Reranking
|
| 116 |
+
dataset:
|
| 117 |
+
type: C-MTEB/CMedQAv1-reranking
|
| 118 |
+
name: MTEB CMedQAv1
|
| 119 |
+
config: default
|
| 120 |
+
split: test
|
| 121 |
+
revision: None
|
| 122 |
+
metrics:
|
| 123 |
+
- type: map
|
| 124 |
+
value: 83.63680381780644
|
| 125 |
+
- type: mrr
|
| 126 |
+
value: 86.16476190476192
|
| 127 |
+
- task:
|
| 128 |
+
type: Reranking
|
| 129 |
+
dataset:
|
| 130 |
+
type: C-MTEB/CMedQAv2-reranking
|
| 131 |
+
name: MTEB CMedQAv2
|
| 132 |
+
config: default
|
| 133 |
+
split: test
|
| 134 |
+
revision: None
|
| 135 |
+
metrics:
|
| 136 |
+
- type: map
|
| 137 |
+
value: 83.74350667859487
|
| 138 |
+
- type: mrr
|
| 139 |
+
value: 86.10388888888889
|
| 140 |
+
- task:
|
| 141 |
+
type: Retrieval
|
| 142 |
+
dataset:
|
| 143 |
+
type: C-MTEB/CmedqaRetrieval
|
| 144 |
+
name: MTEB CmedqaRetrieval
|
| 145 |
+
config: default
|
| 146 |
+
split: dev
|
| 147 |
+
revision: None
|
| 148 |
+
metrics:
|
| 149 |
+
- type: map_at_1
|
| 150 |
+
value: 22.072
|
| 151 |
+
- type: map_at_10
|
| 152 |
+
value: 32.942
|
| 153 |
+
- type: map_at_100
|
| 154 |
+
value: 34.768
|
| 155 |
+
- type: map_at_1000
|
| 156 |
+
value: 34.902
|
| 157 |
+
- type: map_at_3
|
| 158 |
+
value: 29.357
|
| 159 |
+
- type: map_at_5
|
| 160 |
+
value: 31.236000000000004
|
| 161 |
+
- type: mrr_at_1
|
| 162 |
+
value: 34.259
|
| 163 |
+
- type: mrr_at_10
|
| 164 |
+
value: 41.957
|
| 165 |
+
- type: mrr_at_100
|
| 166 |
+
value: 42.982
|
| 167 |
+
- type: mrr_at_1000
|
| 168 |
+
value: 43.042
|
| 169 |
+
- type: mrr_at_3
|
| 170 |
+
value: 39.722
|
| 171 |
+
- type: mrr_at_5
|
| 172 |
+
value: 40.898
|
| 173 |
+
- type: ndcg_at_1
|
| 174 |
+
value: 34.259
|
| 175 |
+
- type: ndcg_at_10
|
| 176 |
+
value: 39.153
|
| 177 |
+
- type: ndcg_at_100
|
| 178 |
+
value: 46.493
|
| 179 |
+
- type: ndcg_at_1000
|
| 180 |
+
value: 49.01
|
| 181 |
+
- type: ndcg_at_3
|
| 182 |
+
value: 34.636
|
| 183 |
+
- type: ndcg_at_5
|
| 184 |
+
value: 36.278
|
| 185 |
+
- type: precision_at_1
|
| 186 |
+
value: 34.259
|
| 187 |
+
- type: precision_at_10
|
| 188 |
+
value: 8.815000000000001
|
| 189 |
+
- type: precision_at_100
|
| 190 |
+
value: 1.474
|
| 191 |
+
- type: precision_at_1000
|
| 192 |
+
value: 0.179
|
| 193 |
+
- type: precision_at_3
|
| 194 |
+
value: 19.73
|
| 195 |
+
- type: precision_at_5
|
| 196 |
+
value: 14.174000000000001
|
| 197 |
+
- type: recall_at_1
|
| 198 |
+
value: 22.072
|
| 199 |
+
- type: recall_at_10
|
| 200 |
+
value: 48.484
|
| 201 |
+
- type: recall_at_100
|
| 202 |
+
value: 79.035
|
| 203 |
+
- type: recall_at_1000
|
| 204 |
+
value: 96.15
|
| 205 |
+
- type: recall_at_3
|
| 206 |
+
value: 34.607
|
| 207 |
+
- type: recall_at_5
|
| 208 |
+
value: 40.064
|
| 209 |
+
- task:
|
| 210 |
+
type: PairClassification
|
| 211 |
+
dataset:
|
| 212 |
+
type: C-MTEB/CMNLI
|
| 213 |
+
name: MTEB Cmnli
|
| 214 |
+
config: default
|
| 215 |
+
split: validation
|
| 216 |
+
revision: None
|
| 217 |
+
metrics:
|
| 218 |
+
- type: cos_sim_accuracy
|
| 219 |
+
value: 76.7047504509922
|
| 220 |
+
- type: cos_sim_ap
|
| 221 |
+
value: 85.26649874800871
|
| 222 |
+
- type: cos_sim_f1
|
| 223 |
+
value: 78.13528724646915
|
| 224 |
+
- type: cos_sim_precision
|
| 225 |
+
value: 71.57587548638132
|
| 226 |
+
- type: cos_sim_recall
|
| 227 |
+
value: 86.01823708206688
|
| 228 |
+
- type: dot_accuracy
|
| 229 |
+
value: 70.13830426939266
|
| 230 |
+
- type: dot_ap
|
| 231 |
+
value: 77.01510412382171
|
| 232 |
+
- type: dot_f1
|
| 233 |
+
value: 73.56710042713817
|
| 234 |
+
- type: dot_precision
|
| 235 |
+
value: 63.955094991364426
|
| 236 |
+
- type: dot_recall
|
| 237 |
+
value: 86.57937806873977
|
| 238 |
+
- type: euclidean_accuracy
|
| 239 |
+
value: 75.53818400481059
|
| 240 |
+
- type: euclidean_ap
|
| 241 |
+
value: 84.34668448241264
|
| 242 |
+
- type: euclidean_f1
|
| 243 |
+
value: 77.51741608613047
|
| 244 |
+
- type: euclidean_precision
|
| 245 |
+
value: 70.65614777756399
|
| 246 |
+
- type: euclidean_recall
|
| 247 |
+
value: 85.85457096095394
|
| 248 |
+
- type: manhattan_accuracy
|
| 249 |
+
value: 75.49007817197835
|
| 250 |
+
- type: manhattan_ap
|
| 251 |
+
value: 84.40297506704299
|
| 252 |
+
- type: manhattan_f1
|
| 253 |
+
value: 77.63185324160932
|
| 254 |
+
- type: manhattan_precision
|
| 255 |
+
value: 70.03949595636637
|
| 256 |
+
- type: manhattan_recall
|
| 257 |
+
value: 87.07037643207856
|
| 258 |
+
- type: max_accuracy
|
| 259 |
+
value: 76.7047504509922
|
| 260 |
+
- type: max_ap
|
| 261 |
+
value: 85.26649874800871
|
| 262 |
+
- type: max_f1
|
| 263 |
+
value: 78.13528724646915
|
| 264 |
+
- task:
|
| 265 |
+
type: Retrieval
|
| 266 |
+
dataset:
|
| 267 |
+
type: C-MTEB/CovidRetrieval
|
| 268 |
+
name: MTEB CovidRetrieval
|
| 269 |
+
config: default
|
| 270 |
+
split: dev
|
| 271 |
+
revision: None
|
| 272 |
+
metrics:
|
| 273 |
+
- type: map_at_1
|
| 274 |
+
value: 69.178
|
| 275 |
+
- type: map_at_10
|
| 276 |
+
value: 77.523
|
| 277 |
+
- type: map_at_100
|
| 278 |
+
value: 77.793
|
| 279 |
+
- type: map_at_1000
|
| 280 |
+
value: 77.79899999999999
|
| 281 |
+
- type: map_at_3
|
| 282 |
+
value: 75.878
|
| 283 |
+
- type: map_at_5
|
| 284 |
+
value: 76.849
|
| 285 |
+
- type: mrr_at_1
|
| 286 |
+
value: 69.44200000000001
|
| 287 |
+
- type: mrr_at_10
|
| 288 |
+
value: 77.55
|
| 289 |
+
- type: mrr_at_100
|
| 290 |
+
value: 77.819
|
| 291 |
+
- type: mrr_at_1000
|
| 292 |
+
value: 77.826
|
| 293 |
+
- type: mrr_at_3
|
| 294 |
+
value: 75.957
|
| 295 |
+
- type: mrr_at_5
|
| 296 |
+
value: 76.916
|
| 297 |
+
- type: ndcg_at_1
|
| 298 |
+
value: 69.44200000000001
|
| 299 |
+
- type: ndcg_at_10
|
| 300 |
+
value: 81.217
|
| 301 |
+
- type: ndcg_at_100
|
| 302 |
+
value: 82.45
|
| 303 |
+
- type: ndcg_at_1000
|
| 304 |
+
value: 82.636
|
| 305 |
+
- type: ndcg_at_3
|
| 306 |
+
value: 77.931
|
| 307 |
+
- type: ndcg_at_5
|
| 308 |
+
value: 79.655
|
| 309 |
+
- type: precision_at_1
|
| 310 |
+
value: 69.44200000000001
|
| 311 |
+
- type: precision_at_10
|
| 312 |
+
value: 9.357
|
| 313 |
+
- type: precision_at_100
|
| 314 |
+
value: 0.993
|
| 315 |
+
- type: precision_at_1000
|
| 316 |
+
value: 0.101
|
| 317 |
+
- type: precision_at_3
|
| 318 |
+
value: 28.1
|
| 319 |
+
- type: precision_at_5
|
| 320 |
+
value: 17.724
|
| 321 |
+
- type: recall_at_1
|
| 322 |
+
value: 69.178
|
| 323 |
+
- type: recall_at_10
|
| 324 |
+
value: 92.624
|
| 325 |
+
- type: recall_at_100
|
| 326 |
+
value: 98.209
|
| 327 |
+
- type: recall_at_1000
|
| 328 |
+
value: 99.684
|
| 329 |
+
- type: recall_at_3
|
| 330 |
+
value: 83.772
|
| 331 |
+
- type: recall_at_5
|
| 332 |
+
value: 87.882
|
| 333 |
+
- task:
|
| 334 |
+
type: Retrieval
|
| 335 |
+
dataset:
|
| 336 |
+
type: C-MTEB/DuRetrieval
|
| 337 |
+
name: MTEB DuRetrieval
|
| 338 |
+
config: default
|
| 339 |
+
split: dev
|
| 340 |
+
revision: None
|
| 341 |
+
metrics:
|
| 342 |
+
- type: map_at_1
|
| 343 |
+
value: 25.163999999999998
|
| 344 |
+
- type: map_at_10
|
| 345 |
+
value: 76.386
|
| 346 |
+
- type: map_at_100
|
| 347 |
+
value: 79.339
|
| 348 |
+
- type: map_at_1000
|
| 349 |
+
value: 79.39500000000001
|
| 350 |
+
- type: map_at_3
|
| 351 |
+
value: 52.959
|
| 352 |
+
- type: map_at_5
|
| 353 |
+
value: 66.59
|
| 354 |
+
- type: mrr_at_1
|
| 355 |
+
value: 87.9
|
| 356 |
+
- type: mrr_at_10
|
| 357 |
+
value: 91.682
|
| 358 |
+
- type: mrr_at_100
|
| 359 |
+
value: 91.747
|
| 360 |
+
- type: mrr_at_1000
|
| 361 |
+
value: 91.751
|
| 362 |
+
- type: mrr_at_3
|
| 363 |
+
value: 91.267
|
| 364 |
+
- type: mrr_at_5
|
| 365 |
+
value: 91.527
|
| 366 |
+
- type: ndcg_at_1
|
| 367 |
+
value: 87.9
|
| 368 |
+
- type: ndcg_at_10
|
| 369 |
+
value: 84.569
|
| 370 |
+
- type: ndcg_at_100
|
| 371 |
+
value: 87.83800000000001
|
| 372 |
+
- type: ndcg_at_1000
|
| 373 |
+
value: 88.322
|
| 374 |
+
- type: ndcg_at_3
|
| 375 |
+
value: 83.473
|
| 376 |
+
- type: ndcg_at_5
|
| 377 |
+
value: 82.178
|
| 378 |
+
- type: precision_at_1
|
| 379 |
+
value: 87.9
|
| 380 |
+
- type: precision_at_10
|
| 381 |
+
value: 40.605000000000004
|
| 382 |
+
- type: precision_at_100
|
| 383 |
+
value: 4.752
|
| 384 |
+
- type: precision_at_1000
|
| 385 |
+
value: 0.488
|
| 386 |
+
- type: precision_at_3
|
| 387 |
+
value: 74.9
|
| 388 |
+
- type: precision_at_5
|
| 389 |
+
value: 62.96000000000001
|
| 390 |
+
- type: recall_at_1
|
| 391 |
+
value: 25.163999999999998
|
| 392 |
+
- type: recall_at_10
|
| 393 |
+
value: 85.97399999999999
|
| 394 |
+
- type: recall_at_100
|
| 395 |
+
value: 96.63000000000001
|
| 396 |
+
- type: recall_at_1000
|
| 397 |
+
value: 99.016
|
| 398 |
+
- type: recall_at_3
|
| 399 |
+
value: 55.611999999999995
|
| 400 |
+
- type: recall_at_5
|
| 401 |
+
value: 71.936
|
| 402 |
+
- task:
|
| 403 |
+
type: Retrieval
|
| 404 |
+
dataset:
|
| 405 |
+
type: C-MTEB/EcomRetrieval
|
| 406 |
+
name: MTEB EcomRetrieval
|
| 407 |
+
config: default
|
| 408 |
+
split: dev
|
| 409 |
+
revision: None
|
| 410 |
+
metrics:
|
| 411 |
+
- type: map_at_1
|
| 412 |
+
value: 48.6
|
| 413 |
+
- type: map_at_10
|
| 414 |
+
value: 58.831
|
| 415 |
+
- type: map_at_100
|
| 416 |
+
value: 59.427
|
| 417 |
+
- type: map_at_1000
|
| 418 |
+
value: 59.44199999999999
|
| 419 |
+
- type: map_at_3
|
| 420 |
+
value: 56.383
|
| 421 |
+
- type: map_at_5
|
| 422 |
+
value: 57.753
|
| 423 |
+
- type: mrr_at_1
|
| 424 |
+
value: 48.6
|
| 425 |
+
- type: mrr_at_10
|
| 426 |
+
value: 58.831
|
| 427 |
+
- type: mrr_at_100
|
| 428 |
+
value: 59.427
|
| 429 |
+
- type: mrr_at_1000
|
| 430 |
+
value: 59.44199999999999
|
| 431 |
+
- type: mrr_at_3
|
| 432 |
+
value: 56.383
|
| 433 |
+
- type: mrr_at_5
|
| 434 |
+
value: 57.753
|
| 435 |
+
- type: ndcg_at_1
|
| 436 |
+
value: 48.6
|
| 437 |
+
- type: ndcg_at_10
|
| 438 |
+
value: 63.951
|
| 439 |
+
- type: ndcg_at_100
|
| 440 |
+
value: 66.72200000000001
|
| 441 |
+
- type: ndcg_at_1000
|
| 442 |
+
value: 67.13900000000001
|
| 443 |
+
- type: ndcg_at_3
|
| 444 |
+
value: 58.882
|
| 445 |
+
- type: ndcg_at_5
|
| 446 |
+
value: 61.373
|
| 447 |
+
- type: precision_at_1
|
| 448 |
+
value: 48.6
|
| 449 |
+
- type: precision_at_10
|
| 450 |
+
value: 8.01
|
| 451 |
+
- type: precision_at_100
|
| 452 |
+
value: 0.928
|
| 453 |
+
- type: precision_at_1000
|
| 454 |
+
value: 0.096
|
| 455 |
+
- type: precision_at_3
|
| 456 |
+
value: 22.033
|
| 457 |
+
- type: precision_at_5
|
| 458 |
+
value: 14.44
|
| 459 |
+
- type: recall_at_1
|
| 460 |
+
value: 48.6
|
| 461 |
+
- type: recall_at_10
|
| 462 |
+
value: 80.10000000000001
|
| 463 |
+
- type: recall_at_100
|
| 464 |
+
value: 92.80000000000001
|
| 465 |
+
- type: recall_at_1000
|
| 466 |
+
value: 96.1
|
| 467 |
+
- type: recall_at_3
|
| 468 |
+
value: 66.10000000000001
|
| 469 |
+
- type: recall_at_5
|
| 470 |
+
value: 72.2
|
| 471 |
+
- task:
|
| 472 |
+
type: Classification
|
| 473 |
+
dataset:
|
| 474 |
+
type: C-MTEB/IFlyTek-classification
|
| 475 |
+
name: MTEB IFlyTek
|
| 476 |
+
config: default
|
| 477 |
+
split: validation
|
| 478 |
+
revision: None
|
| 479 |
+
metrics:
|
| 480 |
+
- type: accuracy
|
| 481 |
+
value: 47.36437091188918
|
| 482 |
+
- type: f1
|
| 483 |
+
value: 36.60946954228577
|
| 484 |
+
- task:
|
| 485 |
+
type: Classification
|
| 486 |
+
dataset:
|
| 487 |
+
type: C-MTEB/JDReview-classification
|
| 488 |
+
name: MTEB JDReview
|
| 489 |
+
config: default
|
| 490 |
+
split: test
|
| 491 |
+
revision: None
|
| 492 |
+
metrics:
|
| 493 |
+
- type: accuracy
|
| 494 |
+
value: 79.5684803001876
|
| 495 |
+
- type: ap
|
| 496 |
+
value: 42.671935929201524
|
| 497 |
+
- type: f1
|
| 498 |
+
value: 73.31912729103752
|
| 499 |
+
- task:
|
| 500 |
+
type: STS
|
| 501 |
+
dataset:
|
| 502 |
+
type: C-MTEB/LCQMC
|
| 503 |
+
name: MTEB LCQMC
|
| 504 |
+
config: default
|
| 505 |
+
split: test
|
| 506 |
+
revision: None
|
| 507 |
+
metrics:
|
| 508 |
+
- type: cos_sim_pearson
|
| 509 |
+
value: 68.62670112113864
|
| 510 |
+
- type: cos_sim_spearman
|
| 511 |
+
value: 75.74009123170768
|
| 512 |
+
- type: euclidean_pearson
|
| 513 |
+
value: 73.93002595958237
|
| 514 |
+
- type: euclidean_spearman
|
| 515 |
+
value: 75.35222935003587
|
| 516 |
+
- type: manhattan_pearson
|
| 517 |
+
value: 73.89870445158144
|
| 518 |
+
- type: manhattan_spearman
|
| 519 |
+
value: 75.31714936339398
|
| 520 |
+
- task:
|
| 521 |
+
type: Reranking
|
| 522 |
+
dataset:
|
| 523 |
+
type: C-MTEB/Mmarco-reranking
|
| 524 |
+
name: MTEB MMarcoReranking
|
| 525 |
+
config: default
|
| 526 |
+
split: dev
|
| 527 |
+
revision: None
|
| 528 |
+
metrics:
|
| 529 |
+
- type: map
|
| 530 |
+
value: 31.5372713650176
|
| 531 |
+
- type: mrr
|
| 532 |
+
value: 30.163095238095238
|
| 533 |
+
- task:
|
| 534 |
+
type: Retrieval
|
| 535 |
+
dataset:
|
| 536 |
+
type: C-MTEB/MMarcoRetrieval
|
| 537 |
+
name: MTEB MMarcoRetrieval
|
| 538 |
+
config: default
|
| 539 |
+
split: dev
|
| 540 |
+
revision: None
|
| 541 |
+
metrics:
|
| 542 |
+
- type: map_at_1
|
| 543 |
+
value: 65.054
|
| 544 |
+
- type: map_at_10
|
| 545 |
+
value: 74.156
|
| 546 |
+
- type: map_at_100
|
| 547 |
+
value: 74.523
|
| 548 |
+
- type: map_at_1000
|
| 549 |
+
value: 74.535
|
| 550 |
+
- type: map_at_3
|
| 551 |
+
value: 72.269
|
| 552 |
+
- type: map_at_5
|
| 553 |
+
value: 73.41
|
| 554 |
+
- type: mrr_at_1
|
| 555 |
+
value: 67.24900000000001
|
| 556 |
+
- type: mrr_at_10
|
| 557 |
+
value: 74.78399999999999
|
| 558 |
+
- type: mrr_at_100
|
| 559 |
+
value: 75.107
|
| 560 |
+
- type: mrr_at_1000
|
| 561 |
+
value: 75.117
|
| 562 |
+
- type: mrr_at_3
|
| 563 |
+
value: 73.13499999999999
|
| 564 |
+
- type: mrr_at_5
|
| 565 |
+
value: 74.13499999999999
|
| 566 |
+
- type: ndcg_at_1
|
| 567 |
+
value: 67.24900000000001
|
| 568 |
+
- type: ndcg_at_10
|
| 569 |
+
value: 77.96300000000001
|
| 570 |
+
- type: ndcg_at_100
|
| 571 |
+
value: 79.584
|
| 572 |
+
- type: ndcg_at_1000
|
| 573 |
+
value: 79.884
|
| 574 |
+
- type: ndcg_at_3
|
| 575 |
+
value: 74.342
|
| 576 |
+
- type: ndcg_at_5
|
| 577 |
+
value: 76.278
|
| 578 |
+
- type: precision_at_1
|
| 579 |
+
value: 67.24900000000001
|
| 580 |
+
- type: precision_at_10
|
| 581 |
+
value: 9.466
|
| 582 |
+
- type: precision_at_100
|
| 583 |
+
value: 1.027
|
| 584 |
+
- type: precision_at_1000
|
| 585 |
+
value: 0.105
|
| 586 |
+
- type: precision_at_3
|
| 587 |
+
value: 27.955999999999996
|
| 588 |
+
- type: precision_at_5
|
| 589 |
+
value: 17.817
|
| 590 |
+
- type: recall_at_1
|
| 591 |
+
value: 65.054
|
| 592 |
+
- type: recall_at_10
|
| 593 |
+
value: 89.113
|
| 594 |
+
- type: recall_at_100
|
| 595 |
+
value: 96.369
|
| 596 |
+
- type: recall_at_1000
|
| 597 |
+
value: 98.714
|
| 598 |
+
- type: recall_at_3
|
| 599 |
+
value: 79.45400000000001
|
| 600 |
+
- type: recall_at_5
|
| 601 |
+
value: 84.06
|
| 602 |
+
- task:
|
| 603 |
+
type: Classification
|
| 604 |
+
dataset:
|
| 605 |
+
type: mteb/amazon_massive_intent
|
| 606 |
+
name: MTEB MassiveIntentClassification (zh-CN)
|
| 607 |
+
config: zh-CN
|
| 608 |
+
split: test
|
| 609 |
+
revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
|
| 610 |
+
metrics:
|
| 611 |
+
- type: accuracy
|
| 612 |
+
value: 68.1977135171486
|
| 613 |
+
- type: f1
|
| 614 |
+
value: 67.23114308718404
|
| 615 |
+
- task:
|
| 616 |
+
type: Classification
|
| 617 |
+
dataset:
|
| 618 |
+
type: mteb/amazon_massive_scenario
|
| 619 |
+
name: MTEB MassiveScenarioClassification (zh-CN)
|
| 620 |
+
config: zh-CN
|
| 621 |
+
split: test
|
| 622 |
+
revision: 7d571f92784cd94a019292a1f45445077d0ef634
|
| 623 |
+
metrics:
|
| 624 |
+
- type: accuracy
|
| 625 |
+
value: 71.92669804976462
|
| 626 |
+
- type: f1
|
| 627 |
+
value: 72.90628475628779
|
| 628 |
+
- task:
|
| 629 |
+
type: Retrieval
|
| 630 |
+
dataset:
|
| 631 |
+
type: C-MTEB/MedicalRetrieval
|
| 632 |
+
name: MTEB MedicalRetrieval
|
| 633 |
+
config: default
|
| 634 |
+
split: dev
|
| 635 |
+
revision: None
|
| 636 |
+
metrics:
|
| 637 |
+
- type: map_at_1
|
| 638 |
+
value: 49.2
|
| 639 |
+
- type: map_at_10
|
| 640 |
+
value: 54.539
|
| 641 |
+
- type: map_at_100
|
| 642 |
+
value: 55.135
|
| 643 |
+
- type: map_at_1000
|
| 644 |
+
value: 55.19199999999999
|
| 645 |
+
- type: map_at_3
|
| 646 |
+
value: 53.383
|
| 647 |
+
- type: map_at_5
|
| 648 |
+
value: 54.142999999999994
|
| 649 |
+
- type: mrr_at_1
|
| 650 |
+
value: 49.2
|
| 651 |
+
- type: mrr_at_10
|
| 652 |
+
value: 54.539
|
| 653 |
+
- type: mrr_at_100
|
| 654 |
+
value: 55.135999999999996
|
| 655 |
+
- type: mrr_at_1000
|
| 656 |
+
value: 55.19199999999999
|
| 657 |
+
- type: mrr_at_3
|
| 658 |
+
value: 53.383
|
| 659 |
+
- type: mrr_at_5
|
| 660 |
+
value: 54.142999999999994
|
| 661 |
+
- type: ndcg_at_1
|
| 662 |
+
value: 49.2
|
| 663 |
+
- type: ndcg_at_10
|
| 664 |
+
value: 57.123000000000005
|
| 665 |
+
- type: ndcg_at_100
|
| 666 |
+
value: 60.21300000000001
|
| 667 |
+
- type: ndcg_at_1000
|
| 668 |
+
value: 61.915
|
| 669 |
+
- type: ndcg_at_3
|
| 670 |
+
value: 54.772
|
| 671 |
+
- type: ndcg_at_5
|
| 672 |
+
value: 56.157999999999994
|
| 673 |
+
- type: precision_at_1
|
| 674 |
+
value: 49.2
|
| 675 |
+
- type: precision_at_10
|
| 676 |
+
value: 6.52
|
| 677 |
+
- type: precision_at_100
|
| 678 |
+
value: 0.8009999999999999
|
| 679 |
+
- type: precision_at_1000
|
| 680 |
+
value: 0.094
|
| 681 |
+
- type: precision_at_3
|
| 682 |
+
value: 19.6
|
| 683 |
+
- type: precision_at_5
|
| 684 |
+
value: 12.44
|
| 685 |
+
- type: recall_at_1
|
| 686 |
+
value: 49.2
|
| 687 |
+
- type: recall_at_10
|
| 688 |
+
value: 65.2
|
| 689 |
+
- type: recall_at_100
|
| 690 |
+
value: 80.10000000000001
|
| 691 |
+
- type: recall_at_1000
|
| 692 |
+
value: 93.89999999999999
|
| 693 |
+
- type: recall_at_3
|
| 694 |
+
value: 58.8
|
| 695 |
+
- type: recall_at_5
|
| 696 |
+
value: 62.2
|
| 697 |
+
- task:
|
| 698 |
+
type: Classification
|
| 699 |
+
dataset:
|
| 700 |
+
type: C-MTEB/MultilingualSentiment-classification
|
| 701 |
+
name: MTEB MultilingualSentiment
|
| 702 |
+
config: default
|
| 703 |
+
split: validation
|
| 704 |
+
revision: None
|
| 705 |
+
metrics:
|
| 706 |
+
- type: accuracy
|
| 707 |
+
value: 63.29333333333334
|
| 708 |
+
- type: f1
|
| 709 |
+
value: 63.03293854259612
|
| 710 |
+
- task:
|
| 711 |
+
type: PairClassification
|
| 712 |
+
dataset:
|
| 713 |
+
type: C-MTEB/OCNLI
|
| 714 |
+
name: MTEB Ocnli
|
| 715 |
+
config: default
|
| 716 |
+
split: validation
|
| 717 |
+
revision: None
|
| 718 |
+
metrics:
|
| 719 |
+
- type: cos_sim_accuracy
|
| 720 |
+
value: 75.69030860855442
|
| 721 |
+
- type: cos_sim_ap
|
| 722 |
+
value: 80.6157833772759
|
| 723 |
+
- type: cos_sim_f1
|
| 724 |
+
value: 77.87524366471735
|
| 725 |
+
- type: cos_sim_precision
|
| 726 |
+
value: 72.3076923076923
|
| 727 |
+
- type: cos_sim_recall
|
| 728 |
+
value: 84.37170010559663
|
| 729 |
+
- type: dot_accuracy
|
| 730 |
+
value: 67.78559826746074
|
| 731 |
+
- type: dot_ap
|
| 732 |
+
value: 72.00871467527499
|
| 733 |
+
- type: dot_f1
|
| 734 |
+
value: 72.58722247394654
|
| 735 |
+
- type: dot_precision
|
| 736 |
+
value: 63.57142857142857
|
| 737 |
+
- type: dot_recall
|
| 738 |
+
value: 84.58289334741288
|
| 739 |
+
- type: euclidean_accuracy
|
| 740 |
+
value: 75.20303194369248
|
| 741 |
+
- type: euclidean_ap
|
| 742 |
+
value: 80.98587256415605
|
| 743 |
+
- type: euclidean_f1
|
| 744 |
+
value: 77.26396917148362
|
| 745 |
+
- type: euclidean_precision
|
| 746 |
+
value: 71.03631532329496
|
| 747 |
+
- type: euclidean_recall
|
| 748 |
+
value: 84.68848996832101
|
| 749 |
+
- type: manhattan_accuracy
|
| 750 |
+
value: 75.20303194369248
|
| 751 |
+
- type: manhattan_ap
|
| 752 |
+
value: 80.93460699513219
|
| 753 |
+
- type: manhattan_f1
|
| 754 |
+
value: 77.124773960217
|
| 755 |
+
- type: manhattan_precision
|
| 756 |
+
value: 67.43083003952569
|
| 757 |
+
- type: manhattan_recall
|
| 758 |
+
value: 90.07391763463569
|
| 759 |
+
- type: max_accuracy
|
| 760 |
+
value: 75.69030860855442
|
| 761 |
+
- type: max_ap
|
| 762 |
+
value: 80.98587256415605
|
| 763 |
+
- type: max_f1
|
| 764 |
+
value: 77.87524366471735
|
| 765 |
+
- task:
|
| 766 |
+
type: Classification
|
| 767 |
+
dataset:
|
| 768 |
+
type: C-MTEB/OnlineShopping-classification
|
| 769 |
+
name: MTEB OnlineShopping
|
| 770 |
+
config: default
|
| 771 |
+
split: test
|
| 772 |
+
revision: None
|
| 773 |
+
metrics:
|
| 774 |
+
- type: accuracy
|
| 775 |
+
value: 87.00000000000001
|
| 776 |
+
- type: ap
|
| 777 |
+
value: 83.24372135949511
|
| 778 |
+
- type: f1
|
| 779 |
+
value: 86.95554191530607
|
| 780 |
+
- task:
|
| 781 |
+
type: STS
|
| 782 |
+
dataset:
|
| 783 |
+
type: C-MTEB/PAWSX
|
| 784 |
+
name: MTEB PAWSX
|
| 785 |
+
config: default
|
| 786 |
+
split: test
|
| 787 |
+
revision: None
|
| 788 |
+
metrics:
|
| 789 |
+
- type: cos_sim_pearson
|
| 790 |
+
value: 37.57616811591219
|
| 791 |
+
- type: cos_sim_spearman
|
| 792 |
+
value: 41.490259084930045
|
| 793 |
+
- type: euclidean_pearson
|
| 794 |
+
value: 38.9155043692188
|
| 795 |
+
- type: euclidean_spearman
|
| 796 |
+
value: 39.16056534305623
|
| 797 |
+
- type: manhattan_pearson
|
| 798 |
+
value: 38.76569892264335
|
| 799 |
+
- type: manhattan_spearman
|
| 800 |
+
value: 38.99891685590743
|
| 801 |
+
- task:
|
| 802 |
+
type: STS
|
| 803 |
+
dataset:
|
| 804 |
+
type: C-MTEB/QBQTC
|
| 805 |
+
name: MTEB QBQTC
|
| 806 |
+
config: default
|
| 807 |
+
split: test
|
| 808 |
+
revision: None
|
| 809 |
+
metrics:
|
| 810 |
+
- type: cos_sim_pearson
|
| 811 |
+
value: 35.44858610359665
|
| 812 |
+
- type: cos_sim_spearman
|
| 813 |
+
value: 38.11128146262466
|
| 814 |
+
- type: euclidean_pearson
|
| 815 |
+
value: 31.928644189822457
|
| 816 |
+
- type: euclidean_spearman
|
| 817 |
+
value: 34.384936631696554
|
| 818 |
+
- type: manhattan_pearson
|
| 819 |
+
value: 31.90586687414376
|
| 820 |
+
- type: manhattan_spearman
|
| 821 |
+
value: 34.35770153777186
|
| 822 |
+
- task:
|
| 823 |
+
type: STS
|
| 824 |
+
dataset:
|
| 825 |
+
type: mteb/sts22-crosslingual-sts
|
| 826 |
+
name: MTEB STS22 (zh)
|
| 827 |
+
config: zh
|
| 828 |
+
split: test
|
| 829 |
+
revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80
|
| 830 |
+
metrics:
|
| 831 |
+
- type: cos_sim_pearson
|
| 832 |
+
value: 66.54931957553592
|
| 833 |
+
- type: cos_sim_spearman
|
| 834 |
+
value: 69.25068863016632
|
| 835 |
+
- type: euclidean_pearson
|
| 836 |
+
value: 50.26525596106869
|
| 837 |
+
- type: euclidean_spearman
|
| 838 |
+
value: 63.83352741910006
|
| 839 |
+
- type: manhattan_pearson
|
| 840 |
+
value: 49.98798282198196
|
| 841 |
+
- type: manhattan_spearman
|
| 842 |
+
value: 63.87649521907841
|
| 843 |
+
- task:
|
| 844 |
+
type: STS
|
| 845 |
+
dataset:
|
| 846 |
+
type: C-MTEB/STSB
|
| 847 |
+
name: MTEB STSB
|
| 848 |
+
config: default
|
| 849 |
+
split: test
|
| 850 |
+
revision: None
|
| 851 |
+
metrics:
|
| 852 |
+
- type: cos_sim_pearson
|
| 853 |
+
value: 82.52782476625825
|
| 854 |
+
- type: cos_sim_spearman
|
| 855 |
+
value: 82.55618986168398
|
| 856 |
+
- type: euclidean_pearson
|
| 857 |
+
value: 78.48190631687673
|
| 858 |
+
- type: euclidean_spearman
|
| 859 |
+
value: 78.39479731354655
|
| 860 |
+
- type: manhattan_pearson
|
| 861 |
+
value: 78.51176592165885
|
| 862 |
+
- type: manhattan_spearman
|
| 863 |
+
value: 78.42363787303265
|
| 864 |
+
- task:
|
| 865 |
+
type: Reranking
|
| 866 |
+
dataset:
|
| 867 |
+
type: C-MTEB/T2Reranking
|
| 868 |
+
name: MTEB T2Reranking
|
| 869 |
+
config: default
|
| 870 |
+
split: dev
|
| 871 |
+
revision: None
|
| 872 |
+
metrics:
|
| 873 |
+
- type: map
|
| 874 |
+
value: 67.36693873615643
|
| 875 |
+
- type: mrr
|
| 876 |
+
value: 77.83847701797939
|
| 877 |
+
- task:
|
| 878 |
+
type: Retrieval
|
| 879 |
+
dataset:
|
| 880 |
+
type: C-MTEB/T2Retrieval
|
| 881 |
+
name: MTEB T2Retrieval
|
| 882 |
+
config: default
|
| 883 |
+
split: dev
|
| 884 |
+
revision: None
|
| 885 |
+
metrics:
|
| 886 |
+
- type: map_at_1
|
| 887 |
+
value: 25.795
|
| 888 |
+
- type: map_at_10
|
| 889 |
+
value: 72.258
|
| 890 |
+
- type: map_at_100
|
| 891 |
+
value: 76.049
|
| 892 |
+
- type: map_at_1000
|
| 893 |
+
value: 76.134
|
| 894 |
+
- type: map_at_3
|
| 895 |
+
value: 50.697
|
| 896 |
+
- type: map_at_5
|
| 897 |
+
value: 62.324999999999996
|
| 898 |
+
- type: mrr_at_1
|
| 899 |
+
value: 86.634
|
| 900 |
+
- type: mrr_at_10
|
| 901 |
+
value: 89.792
|
| 902 |
+
- type: mrr_at_100
|
| 903 |
+
value: 89.91900000000001
|
| 904 |
+
- type: mrr_at_1000
|
| 905 |
+
value: 89.923
|
| 906 |
+
- type: mrr_at_3
|
| 907 |
+
value: 89.224
|
| 908 |
+
- type: mrr_at_5
|
| 909 |
+
value: 89.608
|
| 910 |
+
- type: ndcg_at_1
|
| 911 |
+
value: 86.634
|
| 912 |
+
- type: ndcg_at_10
|
| 913 |
+
value: 80.589
|
| 914 |
+
- type: ndcg_at_100
|
| 915 |
+
value: 84.812
|
| 916 |
+
- type: ndcg_at_1000
|
| 917 |
+
value: 85.662
|
| 918 |
+
- type: ndcg_at_3
|
| 919 |
+
value: 82.169
|
| 920 |
+
- type: ndcg_at_5
|
| 921 |
+
value: 80.619
|
| 922 |
+
- type: precision_at_1
|
| 923 |
+
value: 86.634
|
| 924 |
+
- type: precision_at_10
|
| 925 |
+
value: 40.389
|
| 926 |
+
- type: precision_at_100
|
| 927 |
+
value: 4.93
|
| 928 |
+
- type: precision_at_1000
|
| 929 |
+
value: 0.513
|
| 930 |
+
- type: precision_at_3
|
| 931 |
+
value: 72.104
|
| 932 |
+
- type: precision_at_5
|
| 933 |
+
value: 60.425
|
| 934 |
+
- type: recall_at_1
|
| 935 |
+
value: 25.795
|
| 936 |
+
- type: recall_at_10
|
| 937 |
+
value: 79.565
|
| 938 |
+
- type: recall_at_100
|
| 939 |
+
value: 93.24799999999999
|
| 940 |
+
- type: recall_at_1000
|
| 941 |
+
value: 97.595
|
| 942 |
+
- type: recall_at_3
|
| 943 |
+
value: 52.583999999999996
|
| 944 |
+
- type: recall_at_5
|
| 945 |
+
value: 66.175
|
| 946 |
+
- task:
|
| 947 |
+
type: Classification
|
| 948 |
+
dataset:
|
| 949 |
+
type: C-MTEB/TNews-classification
|
| 950 |
+
name: MTEB TNews
|
| 951 |
+
config: default
|
| 952 |
+
split: validation
|
| 953 |
+
revision: None
|
| 954 |
+
metrics:
|
| 955 |
+
- type: accuracy
|
| 956 |
+
value: 47.648999999999994
|
| 957 |
+
- type: f1
|
| 958 |
+
value: 46.28925837008413
|
| 959 |
+
- task:
|
| 960 |
+
type: Clustering
|
| 961 |
+
dataset:
|
| 962 |
+
type: C-MTEB/ThuNewsClusteringP2P
|
| 963 |
+
name: MTEB ThuNewsClusteringP2P
|
| 964 |
+
config: default
|
| 965 |
+
split: test
|
| 966 |
+
revision: None
|
| 967 |
+
metrics:
|
| 968 |
+
- type: v_measure
|
| 969 |
+
value: 54.07641891287953
|
| 970 |
+
- task:
|
| 971 |
+
type: Clustering
|
| 972 |
+
dataset:
|
| 973 |
+
type: C-MTEB/ThuNewsClusteringS2S
|
| 974 |
+
name: MTEB ThuNewsClusteringS2S
|
| 975 |
+
config: default
|
| 976 |
+
split: test
|
| 977 |
+
revision: None
|
| 978 |
+
metrics:
|
| 979 |
+
- type: v_measure
|
| 980 |
+
value: 53.423702062353954
|
| 981 |
+
- task:
|
| 982 |
+
type: Retrieval
|
| 983 |
+
dataset:
|
| 984 |
+
type: C-MTEB/VideoRetrieval
|
| 985 |
+
name: MTEB VideoRetrieval
|
| 986 |
+
config: default
|
| 987 |
+
split: dev
|
| 988 |
+
revision: None
|
| 989 |
+
metrics:
|
| 990 |
+
- type: map_at_1
|
| 991 |
+
value: 55.7
|
| 992 |
+
- type: map_at_10
|
| 993 |
+
value: 65.923
|
| 994 |
+
- type: map_at_100
|
| 995 |
+
value: 66.42
|
| 996 |
+
- type: map_at_1000
|
| 997 |
+
value: 66.431
|
| 998 |
+
- type: map_at_3
|
| 999 |
+
value: 63.9
|
| 1000 |
+
- type: map_at_5
|
| 1001 |
+
value: 65.225
|
| 1002 |
+
- type: mrr_at_1
|
| 1003 |
+
value: 55.60000000000001
|
| 1004 |
+
- type: mrr_at_10
|
| 1005 |
+
value: 65.873
|
| 1006 |
+
- type: mrr_at_100
|
| 1007 |
+
value: 66.36999999999999
|
| 1008 |
+
- type: mrr_at_1000
|
| 1009 |
+
value: 66.381
|
| 1010 |
+
- type: mrr_at_3
|
| 1011 |
+
value: 63.849999999999994
|
| 1012 |
+
- type: mrr_at_5
|
| 1013 |
+
value: 65.17500000000001
|
| 1014 |
+
- type: ndcg_at_1
|
| 1015 |
+
value: 55.7
|
| 1016 |
+
- type: ndcg_at_10
|
| 1017 |
+
value: 70.621
|
| 1018 |
+
- type: ndcg_at_100
|
| 1019 |
+
value: 72.944
|
| 1020 |
+
- type: ndcg_at_1000
|
| 1021 |
+
value: 73.25399999999999
|
| 1022 |
+
- type: ndcg_at_3
|
| 1023 |
+
value: 66.547
|
| 1024 |
+
- type: ndcg_at_5
|
| 1025 |
+
value: 68.93599999999999
|
| 1026 |
+
- type: precision_at_1
|
| 1027 |
+
value: 55.7
|
| 1028 |
+
- type: precision_at_10
|
| 1029 |
+
value: 8.52
|
| 1030 |
+
- type: precision_at_100
|
| 1031 |
+
value: 0.958
|
| 1032 |
+
- type: precision_at_1000
|
| 1033 |
+
value: 0.098
|
| 1034 |
+
- type: precision_at_3
|
| 1035 |
+
value: 24.733
|
| 1036 |
+
- type: precision_at_5
|
| 1037 |
+
value: 16
|
| 1038 |
+
- type: recall_at_1
|
| 1039 |
+
value: 55.7
|
| 1040 |
+
- type: recall_at_10
|
| 1041 |
+
value: 85.2
|
| 1042 |
+
- type: recall_at_100
|
| 1043 |
+
value: 95.8
|
| 1044 |
+
- type: recall_at_1000
|
| 1045 |
+
value: 98.3
|
| 1046 |
+
- type: recall_at_3
|
| 1047 |
+
value: 74.2
|
| 1048 |
+
- type: recall_at_5
|
| 1049 |
+
value: 80
|
| 1050 |
+
- task:
|
| 1051 |
+
type: Classification
|
| 1052 |
+
dataset:
|
| 1053 |
+
type: C-MTEB/waimai-classification
|
| 1054 |
+
name: MTEB Waimai
|
| 1055 |
+
config: default
|
| 1056 |
+
split: test
|
| 1057 |
+
revision: None
|
| 1058 |
+
metrics:
|
| 1059 |
+
- type: accuracy
|
| 1060 |
+
value: 84.54
|
| 1061 |
+
- type: ap
|
| 1062 |
+
value: 66.13603199670062
|
| 1063 |
+
- type: f1
|
| 1064 |
+
value: 82.61420654584116
|
| 1065 |
---
|
| 1066 |
+
|
| 1067 |
+
<!-- TODO: add evaluation results here -->
|
| 1068 |
+
<br><br>
|
| 1069 |
+
|
| 1070 |
+
<p align="center">
|
| 1071 |
+
<img src="https://github.com/jina-ai/finetuner/blob/main/docs/_static/finetuner-logo-ani.svg?raw=true" alt="Finetuner logo: Finetuner helps you to create experiments in order to improve embeddings on search tasks. It accompanies you to deliver the last mile of performance-tuning for neural search applications." width="150px">
|
| 1072 |
+
</p>
|
| 1073 |
+
|
| 1074 |
+
|
| 1075 |
+
<p align="center">
|
| 1076 |
+
<b>The text embedding set trained by <a href="https://jina.ai/"><b>Jina AI</b></a>, <a href="https://github.com/jina-ai/finetuner"><b>Finetuner</b></a> team.</b>
|
| 1077 |
+
</p>
|
| 1078 |
+
|
| 1079 |
+
|
| 1080 |
+
## Intended Usage & Model Info
|
| 1081 |
+
|
| 1082 |
+
`jina-embeddings-v2-base-zh` is a Chinese/English bilingual text **embedding model** supporting **8192 sequence length**. Our model has 161 million parameters.
|
| 1083 |
+
We have designed it for high performance in cross-language applications and trained it specifically to support mixed Chinese-English input without bias.
|
| 1084 |
+
|
| 1085 |
+
|
| 1086 |
+
You can use the embedding model either via the Jina AI's [Embedding platform](https://jina.ai/embeddings/), AWS SageMaker or in your private deployments.
|
| 1087 |
+
|
| 1088 |
+
## Usage Jina Embedding API
|
| 1089 |
+
|
| 1090 |
+
The following code snippet shows the usage of the Jina Embedding API:
|
| 1091 |
+
```
|
| 1092 |
+
curl https://api.jina.ai/v1/embeddings \
|
| 1093 |
+
-H "Content-Type: application/json" \
|
| 1094 |
+
-H "Authorization: Bearer jina_xxxxxxx" \
|
| 1095 |
+
-d '{
|
| 1096 |
+
"input": ["你的输入可以是纯中文", "or purely in English", "or like mixture of 中文 and 英文"],
|
| 1097 |
+
"model": "jina-embeddings-v2-base-zh"
|
| 1098 |
+
}'
|
| 1099 |
+
|
| 1100 |
+
```
|
| 1101 |
+
|
| 1102 |
+
Get your free API key on: https://jina.ai/embeddings/
|
| 1103 |
+
|
| 1104 |
+
## Opensource
|
| 1105 |
+
|
| 1106 |
+
We will opensource the full model in a few days!
|
| 1107 |
+
|
| 1108 |
+
## Contact
|
| 1109 |
+
|
| 1110 |
+
Join our [Discord community](https://discord.jina.ai) and chat with other community members about ideas.
|