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README.md
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|
| 1 |
+
pipeline_tag: sentence-similarity
|
| 2 |
+
tags:
|
| 3 |
+
- sentence-transformers
|
| 4 |
+
- feature-extraction
|
| 5 |
+
- sentence-similarity
|
| 6 |
+
- mteb
|
| 7 |
+
model-index:
|
| 8 |
+
- name: mist-zh
|
| 9 |
+
results:
|
| 10 |
+
- task:
|
| 11 |
+
type:STS
|
| 12 |
+
dataset:
|
| 13 |
+
type:C-MTEB/AFQMC
|
| 14 |
+
name: MTEB AFQMC
|
| 15 |
+
config: default
|
| 16 |
+
split:validation
|
| 17 |
+
revision:None
|
| 18 |
+
metrics:
|
| 19 |
+
- type: cos_sim_pearson
|
| 20 |
+
value: 0.44734816122831544
|
| 21 |
+
- type: cos_sim_spearman
|
| 22 |
+
value: 0.46970061233318733
|
| 23 |
+
- type: euclidean_pearson
|
| 24 |
+
value: 0.45380620360050605
|
| 25 |
+
- type: euclidean_spearman
|
| 26 |
+
value: 0.46970061233318733
|
| 27 |
+
- type: manhattan_pearson
|
| 28 |
+
value: 0.45251004629975566
|
| 29 |
+
- type: manhattan_spearman
|
| 30 |
+
value: 0.4685418008817015
|
| 31 |
+
- task:
|
| 32 |
+
type:Classification
|
| 33 |
+
dataset:
|
| 34 |
+
type:mteb/amazon_reviews_multi
|
| 35 |
+
name: MTEB AmazonReviewsClassification
|
| 36 |
+
config: default
|
| 37 |
+
split:test
|
| 38 |
+
revision:1399c76144fd37290681b995c656ef9b2e06e26d
|
| 39 |
+
metrics:
|
| 40 |
+
- type: zh_accuracy
|
| 41 |
+
value: 0.38855999999999996
|
| 42 |
+
- type: zh_accuracy_stderr
|
| 43 |
+
value: 0.025344001262626235
|
| 44 |
+
- type: zh_f1
|
| 45 |
+
value: 0.36961374807419534
|
| 46 |
+
- type: zh_f1_stderr
|
| 47 |
+
value: 0.021293704875037154
|
| 48 |
+
- type: zh_main_score
|
| 49 |
+
value: 0.38855999999999996
|
| 50 |
+
- task:
|
| 51 |
+
type:STS
|
| 52 |
+
dataset:
|
| 53 |
+
type:C-MTEB/ATEC
|
| 54 |
+
name: MTEB ATEC
|
| 55 |
+
config: default
|
| 56 |
+
split:test
|
| 57 |
+
revision:None
|
| 58 |
+
metrics:
|
| 59 |
+
- type: cos_sim_pearson
|
| 60 |
+
value: 0.4923835317471939
|
| 61 |
+
- type: cos_sim_spearman
|
| 62 |
+
value: 0.5129611473119322
|
| 63 |
+
- type: euclidean_pearson
|
| 64 |
+
value: 0.5341533188991713
|
| 65 |
+
- type: euclidean_spearman
|
| 66 |
+
value: 0.5129611360495954
|
| 67 |
+
- type: manhattan_pearson
|
| 68 |
+
value: 0.5342662771302782
|
| 69 |
+
- type: manhattan_spearman
|
| 70 |
+
value: 0.5129682402789285
|
| 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: 0.6179575529204537
|
| 82 |
+
- type: cos_sim_spearman
|
| 83 |
+
value: 0.6496308773217001
|
| 84 |
+
- type: euclidean_pearson
|
| 85 |
+
value: 0.6338747223113914
|
| 86 |
+
- type: euclidean_spearman
|
| 87 |
+
value: 0.6496309119412785
|
| 88 |
+
- type: manhattan_pearson
|
| 89 |
+
value: 0.6336833986897711
|
| 90 |
+
- type: manhattan_spearman
|
| 91 |
+
value: 0.6495000035386368
|
| 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: 0.4026570556670306
|
| 103 |
+
- type: v_measure_std
|
| 104 |
+
value: 0.017061921549952314
|
| 105 |
+
- task:
|
| 106 |
+
type:Clustering
|
| 107 |
+
dataset:
|
| 108 |
+
type:C-MTEB/CLSClusteringS2S
|
| 109 |
+
name: MTEB CLSClusteringS2S
|
| 110 |
+
config: default
|
| 111 |
+
split:test
|
| 112 |
+
revision:None
|
| 113 |
+
metrics:
|
| 114 |
+
- type: v_measure
|
| 115 |
+
value: 0.3768621168788469
|
| 116 |
+
- type: v_measure_std
|
| 117 |
+
value: 0.015506559067836777
|
| 118 |
+
- task:
|
| 119 |
+
type:Retrieval
|
| 120 |
+
dataset:
|
| 121 |
+
type:C-MTEB/CmedqaRetrieval
|
| 122 |
+
name: MTEB CmedqaRetrieval
|
| 123 |
+
config: default
|
| 124 |
+
split:dev
|
| 125 |
+
revision:None
|
| 126 |
+
metrics:
|
| 127 |
+
- type: map_at_1
|
| 128 |
+
value: 0.24044
|
| 129 |
+
- type: map_at_10
|
| 130 |
+
value: 0.35311
|
| 131 |
+
- type: map_at_100
|
| 132 |
+
value: 0.37125
|
| 133 |
+
- type: map_at_1000
|
| 134 |
+
value: 0.3726
|
| 135 |
+
- type: map_at_3
|
| 136 |
+
value: 0.31342
|
| 137 |
+
- type: map_at_5
|
| 138 |
+
value: 0.33613
|
| 139 |
+
- type: mrr_at_1
|
| 140 |
+
value: 0.36909
|
| 141 |
+
- type: mrr_at_10
|
| 142 |
+
value: 0.44373
|
| 143 |
+
- type: mrr_at_100
|
| 144 |
+
value: 0.45367
|
| 145 |
+
- type: mrr_at_1000
|
| 146 |
+
value: 0.45422
|
| 147 |
+
- type: mrr_at_3
|
| 148 |
+
value: 0.41927
|
| 149 |
+
- type: mrr_at_5
|
| 150 |
+
value: 0.43292
|
| 151 |
+
- type: ndcg_at_1
|
| 152 |
+
value: 0.36909
|
| 153 |
+
- type: ndcg_at_10
|
| 154 |
+
value: 0.41666
|
| 155 |
+
- type: ndcg_at_100
|
| 156 |
+
value: 0.48915
|
| 157 |
+
- type: ndcg_at_1000
|
| 158 |
+
value: 0.51348
|
| 159 |
+
- type: ndcg_at_3
|
| 160 |
+
value: 0.36592
|
| 161 |
+
- type: ndcg_at_5
|
| 162 |
+
value: 0.38787
|
| 163 |
+
- type: precision_at_1
|
| 164 |
+
value: 0.36909
|
| 165 |
+
- type: precision_at_10
|
| 166 |
+
value: 0.09327
|
| 167 |
+
- type: precision_at_100
|
| 168 |
+
value: 0.01523
|
| 169 |
+
- type: precision_at_1000
|
| 170 |
+
value: 0.00183
|
| 171 |
+
- type: precision_at_3
|
| 172 |
+
value: 0.20672
|
| 173 |
+
- type: precision_at_5
|
| 174 |
+
value: 0.15179
|
| 175 |
+
- type: recall_at_1
|
| 176 |
+
value: 0.24044
|
| 177 |
+
- type: recall_at_10
|
| 178 |
+
value: 0.5137
|
| 179 |
+
- type: recall_at_100
|
| 180 |
+
value: 0.81569
|
| 181 |
+
- type: recall_at_1000
|
| 182 |
+
value: 0.98053
|
| 183 |
+
- type: recall_at_3
|
| 184 |
+
value: 0.3612
|
| 185 |
+
- type: recall_at_5
|
| 186 |
+
value: 0.42829
|
| 187 |
+
- task:
|
| 188 |
+
type:Reranking
|
| 189 |
+
dataset:
|
| 190 |
+
type:C-MTEB/CMedQAv1-reranking
|
| 191 |
+
name: MTEB CMedQAv1
|
| 192 |
+
config: default
|
| 193 |
+
split:test
|
| 194 |
+
revision:None
|
| 195 |
+
metrics:
|
| 196 |
+
- type: map
|
| 197 |
+
value: 0.8440938491415716
|
| 198 |
+
- type: mrr
|
| 199 |
+
value: 0.8686722222222222
|
| 200 |
+
- task:
|
| 201 |
+
type:Reranking
|
| 202 |
+
dataset:
|
| 203 |
+
type:C-MTEB/CMedQAv2-reranking
|
| 204 |
+
name: MTEB CMedQAv2
|
| 205 |
+
config: default
|
| 206 |
+
split:test
|
| 207 |
+
revision:None
|
| 208 |
+
metrics:
|
| 209 |
+
- type: map
|
| 210 |
+
value: 0.852507433210034
|
| 211 |
+
- type: mrr
|
| 212 |
+
value: 0.8758742063492063
|
| 213 |
+
- task:
|
| 214 |
+
type:PairClassification
|
| 215 |
+
dataset:
|
| 216 |
+
type:C-MTEB/CMNLI
|
| 217 |
+
name: MTEB Cmnli
|
| 218 |
+
config: default
|
| 219 |
+
split:validation
|
| 220 |
+
revision:None
|
| 221 |
+
metrics:
|
| 222 |
+
- type: cos_sim_accuracy
|
| 223 |
+
value: 0.7592303066746843
|
| 224 |
+
- type: cos_sim_accuracy_threshold
|
| 225 |
+
value: 0.7603684663772583
|
| 226 |
+
- type: cos_sim_ap
|
| 227 |
+
value: 0.8439741959629594
|
| 228 |
+
- type: cos_sim_f1
|
| 229 |
+
value: 0.7728710064333224
|
| 230 |
+
- type: cos_sim_f1_threshold
|
| 231 |
+
value: 0.7281966805458069
|
| 232 |
+
- type: cos_sim_precision
|
| 233 |
+
value: 0.7241520228851656
|
| 234 |
+
- type: cos_sim_recall
|
| 235 |
+
value: 0.828618190320318
|
| 236 |
+
- type: dot_accuracy
|
| 237 |
+
value: 0.7592303066746843
|
| 238 |
+
- type: dot_accuracy_threshold
|
| 239 |
+
value: 0.7603684663772583
|
| 240 |
+
- type: dot_ap
|
| 241 |
+
value: 0.8439592659189602
|
| 242 |
+
- type: dot_f1
|
| 243 |
+
value: 0.7728710064333224
|
| 244 |
+
- type: dot_f1_threshold
|
| 245 |
+
value: 0.7281967401504517
|
| 246 |
+
- type: dot_precision
|
| 247 |
+
value: 0.7241520228851656
|
| 248 |
+
- type: dot_recall
|
| 249 |
+
value: 0.828618190320318
|
| 250 |
+
- type: euclidean_accuracy
|
| 251 |
+
value: 0.7592303066746843
|
| 252 |
+
- type: euclidean_accuracy_threshold
|
| 253 |
+
value: 0.6922882795333862
|
| 254 |
+
- type: euclidean_ap
|
| 255 |
+
value: 0.8439741904478117
|
| 256 |
+
- type: euclidean_f1
|
| 257 |
+
value: 0.7728710064333224
|
| 258 |
+
- type: euclidean_f1_threshold
|
| 259 |
+
value: 0.7372968196868896
|
| 260 |
+
- type: euclidean_precision
|
| 261 |
+
value: 0.7241520228851656
|
| 262 |
+
- type: euclidean_recall
|
| 263 |
+
value: 0.828618190320318
|
| 264 |
+
- type: manhattan_accuracy
|
| 265 |
+
value: 0.7583884546001203
|
| 266 |
+
- type: manhattan_accuracy_threshold
|
| 267 |
+
value: 15.160146713256836
|
| 268 |
+
- type: manhattan_ap
|
| 269 |
+
value: 0.8439482592167423
|
| 270 |
+
- type: manhattan_f1
|
| 271 |
+
value: 0.7724197186123941
|
| 272 |
+
- type: manhattan_f1_threshold
|
| 273 |
+
value: 16.451358795166016
|
| 274 |
+
- type: manhattan_precision
|
| 275 |
+
value: 0.7143424711958681
|
| 276 |
+
- type: manhattan_recall
|
| 277 |
+
value: 0.8407762450315642
|
| 278 |
+
- type: max_accuracy
|
| 279 |
+
value: 0.7592303066746843
|
| 280 |
+
- type: max_ap
|
| 281 |
+
value: 0.8439741959629594
|
| 282 |
+
- type: max_f1
|
| 283 |
+
value: 0.7728710064333224
|
| 284 |
+
- task:
|
| 285 |
+
type:Retrieval
|
| 286 |
+
dataset:
|
| 287 |
+
type:C-MTEB/CovidRetrieval
|
| 288 |
+
name: MTEB CovidRetrieval
|
| 289 |
+
config: default
|
| 290 |
+
split:dev
|
| 291 |
+
revision:None
|
| 292 |
+
metrics:
|
| 293 |
+
- type: map_at_1
|
| 294 |
+
value: 0.6765
|
| 295 |
+
- type: map_at_10
|
| 296 |
+
value: 0.75672
|
| 297 |
+
- type: map_at_100
|
| 298 |
+
value: 0.76005
|
| 299 |
+
- type: map_at_1000
|
| 300 |
+
value: 0.76007
|
| 301 |
+
- type: map_at_3
|
| 302 |
+
value: 0.73867
|
| 303 |
+
- type: map_at_5
|
| 304 |
+
value: 0.74949
|
| 305 |
+
- type: mrr_at_1
|
| 306 |
+
value: 0.67756
|
| 307 |
+
- type: mrr_at_10
|
| 308 |
+
value: 0.7564
|
| 309 |
+
- type: mrr_at_100
|
| 310 |
+
value: 0.75973
|
| 311 |
+
- type: mrr_at_1000
|
| 312 |
+
value: 0.75975
|
| 313 |
+
- type: mrr_at_3
|
| 314 |
+
value: 0.73867
|
| 315 |
+
- type: mrr_at_5
|
| 316 |
+
value: 0.74984
|
| 317 |
+
- type: ndcg_at_1
|
| 318 |
+
value: 0.67861
|
| 319 |
+
- type: ndcg_at_10
|
| 320 |
+
value: 0.79393
|
| 321 |
+
- type: ndcg_at_100
|
| 322 |
+
value: 0.81044
|
| 323 |
+
- type: ndcg_at_1000
|
| 324 |
+
value: 0.81153
|
| 325 |
+
- type: ndcg_at_3
|
| 326 |
+
value: 0.75767
|
| 327 |
+
- type: ndcg_at_5
|
| 328 |
+
value: 0.77714
|
| 329 |
+
- type: precision_at_1
|
| 330 |
+
value: 0.67861
|
| 331 |
+
- type: precision_at_10
|
| 332 |
+
value: 0.09199
|
| 333 |
+
- type: precision_at_100
|
| 334 |
+
value: 0.00998
|
| 335 |
+
- type: precision_at_1000
|
| 336 |
+
value: 0.00101
|
| 337 |
+
- type: precision_at_3
|
| 338 |
+
value: 0.27222
|
| 339 |
+
- type: precision_at_5
|
| 340 |
+
value: 0.17302
|
| 341 |
+
- type: recall_at_1
|
| 342 |
+
value: 0.6765
|
| 343 |
+
- type: recall_at_10
|
| 344 |
+
value: 0.90938
|
| 345 |
+
- type: recall_at_100
|
| 346 |
+
value: 0.98736
|
| 347 |
+
- type: recall_at_1000
|
| 348 |
+
value: 0.99684
|
| 349 |
+
- type: recall_at_3
|
| 350 |
+
value: 0.81138
|
| 351 |
+
- type: recall_at_5
|
| 352 |
+
value: 0.85827
|
| 353 |
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- task:
|
| 354 |
+
type:Retrieval
|
| 355 |
+
dataset:
|
| 356 |
+
type: C-MTEB/DuRetrieval
|
| 357 |
+
name: MTEB DuRetrieval
|
| 358 |
+
config: default
|
| 359 |
+
split:dev
|
| 360 |
+
revision:None
|
| 361 |
+
metrics:
|
| 362 |
+
- type: map_at_1
|
| 363 |
+
value: 0.25407
|
| 364 |
+
- type: map_at_10
|
| 365 |
+
value: 0.79001
|
| 366 |
+
- type: map_at_100
|
| 367 |
+
value: 0.81983
|
| 368 |
+
- type: map_at_1000
|
| 369 |
+
value: 0.82021
|
| 370 |
+
- type: map_at_3
|
| 371 |
+
value: 0.54256
|
| 372 |
+
- type: map_at_5
|
| 373 |
+
value: 0.68918
|
| 374 |
+
- type: mrr_at_1
|
| 375 |
+
value: 0.8915
|
| 376 |
+
- type: mrr_at_10
|
| 377 |
+
value: 0.92548
|
| 378 |
+
- type: mrr_at_100
|
| 379 |
+
value: 0.92614
|
| 380 |
+
- type: mrr_at_1000
|
| 381 |
+
value: 0.92616
|
| 382 |
+
- type: mrr_at_3
|
| 383 |
+
value: 0.92175
|
| 384 |
+
- type: mrr_at_5
|
| 385 |
+
value: 0.92432
|
| 386 |
+
- type: ndcg_at_1
|
| 387 |
+
value: 0.8915
|
| 388 |
+
- type: ndcg_at_10
|
| 389 |
+
value: 0.86588
|
| 390 |
+
- type: ndcg_at_100
|
| 391 |
+
value: 0.89487
|
| 392 |
+
- type: ndcg_at_1000
|
| 393 |
+
value: 0.89841
|
| 394 |
+
- type: ndcg_at_3
|
| 395 |
+
value: 0.8501
|
| 396 |
+
- type: ndcg_at_5
|
| 397 |
+
value: 0.84301
|
| 398 |
+
- type: precision_at_1
|
| 399 |
+
value: 0.8915
|
| 400 |
+
- type: precision_at_10
|
| 401 |
+
value: 0.4171
|
| 402 |
+
- type: precision_at_100
|
| 403 |
+
value: 0.04807
|
| 404 |
+
- type: precision_at_1000
|
| 405 |
+
value: 0.00489
|
| 406 |
+
- type: precision_at_3
|
| 407 |
+
value: 0.76417
|
| 408 |
+
- type: precision_at_5
|
| 409 |
+
value: 0.6495
|
| 410 |
+
- type: recall_at_1
|
| 411 |
+
value: 0.25407
|
| 412 |
+
- type: recall_at_10
|
| 413 |
+
value: 0.88221
|
| 414 |
+
- type: recall_at_100
|
| 415 |
+
value: 0.97527
|
| 416 |
+
- type: recall_at_1000
|
| 417 |
+
value: 0.99396
|
| 418 |
+
- type: recall_at_3
|
| 419 |
+
value: 0.56751
|
| 420 |
+
- type: recall_at_5
|
| 421 |
+
value: 0.74191
|
| 422 |
+
- task:
|
| 423 |
+
type:Retrieval
|
| 424 |
+
dataset:
|
| 425 |
+
type:C-MTEB/EcomRetrieval
|
| 426 |
+
name: MTEB EcomRetrieval
|
| 427 |
+
config: default
|
| 428 |
+
split:dev
|
| 429 |
+
revision:None
|
| 430 |
+
metrics:
|
| 431 |
+
- type: map_at_1
|
| 432 |
+
value: 0.476
|
| 433 |
+
- type: map_at_10
|
| 434 |
+
value: 0.5715
|
| 435 |
+
- type: map_at_100
|
| 436 |
+
value: 0.57789
|
| 437 |
+
- type: map_at_1000
|
| 438 |
+
value: 0.57808
|
| 439 |
+
- type: map_at_3
|
| 440 |
+
value: 0.54467
|
| 441 |
+
- type: map_at_5
|
| 442 |
+
value: 0.56017
|
| 443 |
+
- type: mrr_at_1
|
| 444 |
+
value: 0.476
|
| 445 |
+
- type: mrr_at_10
|
| 446 |
+
value: 0.5715
|
| 447 |
+
- type: mrr_at_100
|
| 448 |
+
value: 0.57789
|
| 449 |
+
- type: mrr_at_1000
|
| 450 |
+
value: 0.57808
|
| 451 |
+
- type: mrr_at_3
|
| 452 |
+
value: 0.54467
|
| 453 |
+
- type: mrr_at_5
|
| 454 |
+
value: 0.56017
|
| 455 |
+
- type: ndcg_at_1
|
| 456 |
+
value: 0.476
|
| 457 |
+
- type: ndcg_at_10
|
| 458 |
+
value: 0.62304
|
| 459 |
+
- type: ndcg_at_100
|
| 460 |
+
value: 0.65329
|
| 461 |
+
- type: ndcg_at_1000
|
| 462 |
+
value: 0.65837
|
| 463 |
+
- type: ndcg_at_3
|
| 464 |
+
value: 0.56757
|
| 465 |
+
- type: ndcg_at_5
|
| 466 |
+
value: 0.59575
|
| 467 |
+
- type: precision_at_1
|
| 468 |
+
value: 0.476
|
| 469 |
+
- type: precision_at_10
|
| 470 |
+
value: 0.0787
|
| 471 |
+
- type: precision_at_100
|
| 472 |
+
value: 0.00926
|
| 473 |
+
- type: precision_at_1000
|
| 474 |
+
value: 0.00097
|
| 475 |
+
- type: precision_at_3
|
| 476 |
+
value: 0.21133
|
| 477 |
+
- type: precision_at_5
|
| 478 |
+
value: 0.1406
|
| 479 |
+
- type: recall_at_1
|
| 480 |
+
value: 0.476
|
| 481 |
+
- type: recall_at_10
|
| 482 |
+
value: 0.787
|
| 483 |
+
- type: recall_at_100
|
| 484 |
+
value: 0.926
|
| 485 |
+
- type: recall_at_1000
|
| 486 |
+
value: 0.966
|
| 487 |
+
- type: recall_at_3
|
| 488 |
+
value: 0.634
|
| 489 |
+
- type: recall_at_5
|
| 490 |
+
value: 0.703
|
| 491 |
+
- task:
|
| 492 |
+
type:Classification
|
| 493 |
+
dataset:
|
| 494 |
+
type:C-MTEB/IFlyTek-classification
|
| 495 |
+
name: MTEB IFlyTek
|
| 496 |
+
config: default
|
| 497 |
+
split:validation
|
| 498 |
+
revision:None
|
| 499 |
+
metrics:
|
| 500 |
+
- type: accuracy
|
| 501 |
+
value: 0.4828010773374375
|
| 502 |
+
- type: accuracy_stderr
|
| 503 |
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value: 0.005244086198507375
|
| 504 |
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- type: f1
|
| 505 |
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value: 0.3553699530214492
|
| 506 |
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- type: f1_stderr
|
| 507 |
+
value: 0.0037929213901079944
|
| 508 |
+
- type: main_score
|
| 509 |
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value: 0.4828010773374375
|
| 510 |
+
- task:
|
| 511 |
+
type:Classification
|
| 512 |
+
dataset:
|
| 513 |
+
type:C-MTEB/JDReview-classification
|
| 514 |
+
name: MTEB JDReview
|
| 515 |
+
config: default
|
| 516 |
+
split:test
|
| 517 |
+
revision:None
|
| 518 |
+
metrics:
|
| 519 |
+
- type: accuracy
|
| 520 |
+
value: 0.8484052532833021
|
| 521 |
+
- type: accuracy_stderr
|
| 522 |
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value: 0.015848939648737626
|
| 523 |
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- type: ap
|
| 524 |
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value: 0.5235323515091401
|
| 525 |
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- type: ap_stderr
|
| 526 |
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value: 0.02150569650954474
|
| 527 |
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- type: f1
|
| 528 |
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value: 0.7950069160202494
|
| 529 |
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- type: f1_stderr
|
| 530 |
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value: 0.01499969036259696
|
| 531 |
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- type: main_score
|
| 532 |
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value: 0.8484052532833021
|
| 533 |
+
- task:
|
| 534 |
+
type:STS
|
| 535 |
+
dataset:
|
| 536 |
+
type:C-MTEB/LCQMC
|
| 537 |
+
name: MTEB LCQMC
|
| 538 |
+
config: default
|
| 539 |
+
split:test
|
| 540 |
+
revision:None
|
| 541 |
+
metrics:
|
| 542 |
+
- type: cos_sim_pearson
|
| 543 |
+
value: 0.6968404288794713
|
| 544 |
+
- type: cos_sim_spearman
|
| 545 |
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value: 0.7706824442481803
|
| 546 |
+
- type: euclidean_pearson
|
| 547 |
+
value: 0.7547746745802166
|
| 548 |
+
- type: euclidean_spearman
|
| 549 |
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value: 0.7706825328995878
|
| 550 |
+
- type: manhattan_pearson
|
| 551 |
+
value: 0.7546220581621667
|
| 552 |
+
- type: manhattan_spearman
|
| 553 |
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value: 0.7705100926919136
|
| 554 |
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- task:
|
| 555 |
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type:Classification
|
| 556 |
+
dataset:
|
| 557 |
+
type:mteb/amazon_massive_intent
|
| 558 |
+
name: MTEB MassiveIntentClassification
|
| 559 |
+
config: default
|
| 560 |
+
split:test
|
| 561 |
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revision:31efe3c427b0bae9c22cbb560b8f15491cc6bed7
|
| 562 |
+
metrics:
|
| 563 |
+
- type: zh-CN_accuracy
|
| 564 |
+
value: 0.6745124411566913
|
| 565 |
+
- type: zh-CN_accuracy_stderr
|
| 566 |
+
value: 0.015989972974792096
|
| 567 |
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- type: zh-CN_f1
|
| 568 |
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value: 0.6477175074397455
|
| 569 |
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- type: zh-CN_f1_stderr
|
| 570 |
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value: 0.015484061914007355
|
| 571 |
+
- type: zh-CN_main_score
|
| 572 |
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value: 0.6745124411566913
|
| 573 |
+
- task:
|
| 574 |
+
type:Classification
|
| 575 |
+
dataset:
|
| 576 |
+
type:mteb/amazon_massive_scenario
|
| 577 |
+
name: MTEB MassiveScenarioClassification
|
| 578 |
+
config: default
|
| 579 |
+
split:test
|
| 580 |
+
revision:7d571f92784cd94a019292a1f45445077d0ef634
|
| 581 |
+
metrics:
|
| 582 |
+
- type: zh-CN_accuracy
|
| 583 |
+
value: 0.7308002689979824
|
| 584 |
+
- type: zh-CN_accuracy_stderr
|
| 585 |
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value: 0.015224400610167006
|
| 586 |
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- type: zh-CN_f1
|
| 587 |
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value: 0.7265358173635958
|
| 588 |
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- type: zh-CN_f1_stderr
|
| 589 |
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value: 0.014453983681998765
|
| 590 |
+
- type: zh-CN_main_score
|
| 591 |
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value: 0.7308002689979824
|
| 592 |
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- task:
|
| 593 |
+
type:Retrieval
|
| 594 |
+
dataset:
|
| 595 |
+
type:C-MTEB/MedicalRetrieval
|
| 596 |
+
name: MTEB MedicalRetrieval
|
| 597 |
+
config: default
|
| 598 |
+
split:dev
|
| 599 |
+
revision:None
|
| 600 |
+
metrics:
|
| 601 |
+
- type: map_at_1
|
| 602 |
+
value: 0.487
|
| 603 |
+
- type: map_at_10
|
| 604 |
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value: 0.54871
|
| 605 |
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- type: map_at_100
|
| 606 |
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value: 0.55381
|
| 607 |
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- type: map_at_1000
|
| 608 |
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value: 0.55436
|
| 609 |
+
- type: map_at_3
|
| 610 |
+
value: 0.53367
|
| 611 |
+
- type: map_at_5
|
| 612 |
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value: 0.54257
|
| 613 |
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- type: mrr_at_1
|
| 614 |
+
value: 0.487
|
| 615 |
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- type: mrr_at_10
|
| 616 |
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value: 0.54871
|
| 617 |
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- type: mrr_at_100
|
| 618 |
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value: 0.55381
|
| 619 |
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- type: mrr_at_1000
|
| 620 |
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value: 0.55436
|
| 621 |
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- type: mrr_at_3
|
| 622 |
+
value: 0.53367
|
| 623 |
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- type: mrr_at_5
|
| 624 |
+
value: 0.54257
|
| 625 |
+
- type: ndcg_at_1
|
| 626 |
+
value: 0.487
|
| 627 |
+
- type: ndcg_at_10
|
| 628 |
+
value: 0.57942
|
| 629 |
+
- type: ndcg_at_100
|
| 630 |
+
value: 0.6075
|
| 631 |
+
- type: ndcg_at_1000
|
| 632 |
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value: 0.62401
|
| 633 |
+
- type: ndcg_at_3
|
| 634 |
+
value: 0.54867
|
| 635 |
+
- type: ndcg_at_5
|
| 636 |
+
value: 0.56493
|
| 637 |
+
- type: precision_at_1
|
| 638 |
+
value: 0.487
|
| 639 |
+
- type: precision_at_10
|
| 640 |
+
value: 0.0676
|
| 641 |
+
- type: precision_at_100
|
| 642 |
+
value: 0.00815
|
| 643 |
+
- type: precision_at_1000
|
| 644 |
+
value: 0.00095
|
| 645 |
+
- type: precision_at_3
|
| 646 |
+
value: 0.19733
|
| 647 |
+
- type: precision_at_5
|
| 648 |
+
value: 0.1264
|
| 649 |
+
- type: recall_at_1
|
| 650 |
+
value: 0.487
|
| 651 |
+
- type: recall_at_10
|
| 652 |
+
value: 0.676
|
| 653 |
+
- type: recall_at_100
|
| 654 |
+
value: 0.815
|
| 655 |
+
- type: recall_at_1000
|
| 656 |
+
value: 0.949
|
| 657 |
+
- type: recall_at_3
|
| 658 |
+
value: 0.592
|
| 659 |
+
- type: recall_at_5
|
| 660 |
+
value: 0.632
|
| 661 |
+
- task:
|
| 662 |
+
type:Reranking
|
| 663 |
+
dataset:
|
| 664 |
+
type:C-MTEB/Mmarco-reranking
|
| 665 |
+
name: MTEB MmarcoReranking
|
| 666 |
+
config: default
|
| 667 |
+
split:dev
|
| 668 |
+
revision:None
|
| 669 |
+
metrics:
|
| 670 |
+
- type: map
|
| 671 |
+
value: 0.2809825725416088
|
| 672 |
+
- type: mrr
|
| 673 |
+
value: 0.2695912698412698
|
| 674 |
+
- task:
|
| 675 |
+
type:Retrieval
|
| 676 |
+
dataset:
|
| 677 |
+
type:C-MTEB/MMarcoRetrieval
|
| 678 |
+
name: MTEB MMarcoRetrieval
|
| 679 |
+
config: default
|
| 680 |
+
split:dev
|
| 681 |
+
revision:None
|
| 682 |
+
metrics:
|
| 683 |
+
- type: map_at_1
|
| 684 |
+
value: 0.65368
|
| 685 |
+
- type: map_at_10
|
| 686 |
+
value: 0.74294
|
| 687 |
+
- type: map_at_100
|
| 688 |
+
value: 0.74653
|
| 689 |
+
- type: map_at_1000
|
| 690 |
+
value: 0.74664
|
| 691 |
+
- type: map_at_3
|
| 692 |
+
value: 0.72416
|
| 693 |
+
- type: map_at_5
|
| 694 |
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value: 0.73658
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| 695 |
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- type: mrr_at_1
|
| 696 |
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value: 0.67507
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| 697 |
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- type: mrr_at_10
|
| 698 |
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value: 0.74853
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| 699 |
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- type: mrr_at_100
|
| 700 |
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value: 0.75174
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| 701 |
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- type: mrr_at_1000
|
| 702 |
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value: 0.75184
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| 703 |
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- type: mrr_at_3
|
| 704 |
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value: 0.73235
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| 705 |
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- type: mrr_at_5
|
| 706 |
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value: 0.74298
|
| 707 |
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- type: ndcg_at_1
|
| 708 |
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value: 0.67507
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| 709 |
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- type: ndcg_at_10
|
| 710 |
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value: 0.77948
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| 711 |
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- type: ndcg_at_100
|
| 712 |
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value: 0.79555
|
| 713 |
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- type: ndcg_at_1000
|
| 714 |
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value: 0.79864
|
| 715 |
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- type: ndcg_at_3
|
| 716 |
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value: 0.74434
|
| 717 |
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- type: ndcg_at_5
|
| 718 |
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value: 0.76504
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| 719 |
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- type: precision_at_1
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| 720 |
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value: 0.67507
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| 721 |
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- type: precision_at_10
|
| 722 |
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value: 0.09423
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| 723 |
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- type: precision_at_100
|
| 724 |
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value: 0.01022
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| 725 |
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- type: precision_at_1000
|
| 726 |
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value: 0.00105
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| 727 |
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- type: precision_at_3
|
| 728 |
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value: 0.27975
|
| 729 |
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- type: precision_at_5
|
| 730 |
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value: 0.17891
|
| 731 |
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- type: recall_at_1
|
| 732 |
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value: 0.65368
|
| 733 |
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- type: recall_at_10
|
| 734 |
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value: 0.88633
|
| 735 |
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- type: recall_at_100
|
| 736 |
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value: 0.95889
|
| 737 |
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- type: recall_at_1000
|
| 738 |
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value: 0.98346
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| 739 |
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- type: recall_at_3
|
| 740 |
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value: 0.79404
|
| 741 |
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- type: recall_at_5
|
| 742 |
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value: 0.84292
|
| 743 |
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- task:
|
| 744 |
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type:Classification
|
| 745 |
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dataset:
|
| 746 |
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type:C-MTEB/MultilingualSentiment-classification
|
| 747 |
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name: MTEB MultilingualSentiment
|
| 748 |
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config: default
|
| 749 |
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split:validation
|
| 750 |
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revision:None
|
| 751 |
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metrics:
|
| 752 |
+
- type: accuracy
|
| 753 |
+
value: 0.7127000000000001
|
| 754 |
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- type: accuracy_stderr
|
| 755 |
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value: 0.009532925399197596
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- type: f1
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value: 0.7046516219039894
|
| 758 |
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- type: f1_stderr
|
| 759 |
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value: 0.01407386657805127
|
| 760 |
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- type: main_score
|
| 761 |
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value: 0.7127000000000001
|
| 762 |
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- task:
|
| 763 |
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type:PairClassification
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| 764 |
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dataset:
|
| 765 |
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type:C-MTEB/OCNLI
|
| 766 |
+
name: MTEB Ocnli
|
| 767 |
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config: default
|
| 768 |
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split:validation
|
| 769 |
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revision:None
|
| 770 |
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metrics:
|
| 771 |
+
- type: cos_sim_accuracy
|
| 772 |
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value: 0.6989713048186248
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| 773 |
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- type: cos_sim_accuracy_threshold
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value: 0.7673404216766357
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value: 0.7475296949416844
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| 777 |
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value: 0.730820399113082
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| 779 |
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- type: cos_sim_f1_threshold
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| 780 |
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value: 0.7212538719177246
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| 781 |
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- type: cos_sim_precision
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value: 0.6299694189602446
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| 783 |
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- type: cos_sim_recall
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| 784 |
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value: 0.870116156282999
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| 785 |
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- type: dot_accuracy
|
| 786 |
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value: 0.6989713048186248
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| 787 |
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- type: dot_accuracy_threshold
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| 788 |
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value: 0.7673404216766357
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| 789 |
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- type: dot_ap
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| 790 |
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value: 0.7475289228002875
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| 791 |
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- type: dot_f1
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| 792 |
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value: 0.730820399113082
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| 793 |
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- type: dot_f1_threshold
|
| 794 |
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value: 0.7212539315223694
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| 795 |
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- type: dot_precision
|
| 796 |
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value: 0.6299694189602446
|
| 797 |
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- type: dot_recall
|
| 798 |
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value: 0.870116156282999
|
| 799 |
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- type: euclidean_accuracy
|
| 800 |
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value: 0.6989713048186248
|
| 801 |
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- type: euclidean_accuracy_threshold
|
| 802 |
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value: 0.6821430325508118
|
| 803 |
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- type: euclidean_ap
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| 804 |
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value: 0.7475289228002875
|
| 805 |
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- type: euclidean_f1
|
| 806 |
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value: 0.730820399113082
|
| 807 |
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- type: euclidean_f1_threshold
|
| 808 |
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value: 0.7466539740562439
|
| 809 |
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- type: euclidean_precision
|
| 810 |
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value: 0.6299694189602446
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| 811 |
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- type: euclidean_recall
|
| 812 |
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value: 0.870116156282999
|
| 813 |
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- type: manhattan_accuracy
|
| 814 |
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value: 0.699512723335138
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| 815 |
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- type: manhattan_accuracy_threshold
|
| 816 |
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value: 15.069363594055176
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| 817 |
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- type: manhattan_ap
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| 818 |
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value: 0.7463572749955489
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| 819 |
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- type: manhattan_f1
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| 820 |
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value: 0.7280663465735486
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| 821 |
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- type: manhattan_f1_threshold
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| 822 |
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value: 16.66558074951172
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| 823 |
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- type: manhattan_precision
|
| 824 |
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value: 0.6205357142857143
|
| 825 |
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- type: manhattan_recall
|
| 826 |
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value: 0.880675818373812
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| 827 |
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- type: max_accuracy
|
| 828 |
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value: 0.699512723335138
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| 829 |
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- type: max_ap
|
| 830 |
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value: 0.7475296949416844
|
| 831 |
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- type: max_f1
|
| 832 |
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value: 0.730820399113082
|
| 833 |
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- task:
|
| 834 |
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type:Classification
|
| 835 |
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dataset:
|
| 836 |
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type:C-MTEB/OnlineShopping-classification
|
| 837 |
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name: MTEB OnlineShopping
|
| 838 |
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config: default
|
| 839 |
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split:test
|
| 840 |
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revision:None
|
| 841 |
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metrics:
|
| 842 |
+
- type: accuracy
|
| 843 |
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value: 0.9138
|
| 844 |
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- type: accuracy_stderr
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| 845 |
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value: 0.012456323695216027
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| 846 |
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- type: ap
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| 847 |
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value: 0.8914371766660247
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| 848 |
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| 849 |
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value: 0.01735000706460752
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| 850 |
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- type: f1
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| 851 |
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value: 0.9136682962995261
|
| 852 |
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- type: f1_stderr
|
| 853 |
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value: 0.012499748296615935
|
| 854 |
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- type: main_score
|
| 855 |
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value: 0.9138
|
| 856 |
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- task:
|
| 857 |
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type:STS
|
| 858 |
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dataset:
|
| 859 |
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type:C-MTEB/PAWSX
|
| 860 |
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name: MTEB PAWSX
|
| 861 |
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config: default
|
| 862 |
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split:test
|
| 863 |
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revision:None
|
| 864 |
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metrics:
|
| 865 |
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- type: cos_sim_pearson
|
| 866 |
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value: 0.23621683997579607
|
| 867 |
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- type: cos_sim_spearman
|
| 868 |
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value: 0.2946714129804792
|
| 869 |
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- type: euclidean_pearson
|
| 870 |
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value: 0.29841725912733486
|
| 871 |
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- type: euclidean_spearman
|
| 872 |
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value: 0.2946695199370699
|
| 873 |
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- type: manhattan_pearson
|
| 874 |
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value: 0.29853598937043624
|
| 875 |
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- type: manhattan_spearman
|
| 876 |
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value: 0.2942340511723847
|
| 877 |
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- task:
|
| 878 |
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type:STS
|
| 879 |
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dataset:
|
| 880 |
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type:C-MTEB/QBQTC
|
| 881 |
+
name: MTEB QBQTC
|
| 882 |
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config: default
|
| 883 |
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split:test
|
| 884 |
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revision:None
|
| 885 |
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metrics:
|
| 886 |
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- type: cos_sim_pearson
|
| 887 |
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value: 0.3486196986379606
|
| 888 |
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- type: cos_sim_spearman
|
| 889 |
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value: 0.37316873994339983
|
| 890 |
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- type: euclidean_pearson
|
| 891 |
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value: 0.3552672274329054
|
| 892 |
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- type: euclidean_spearman
|
| 893 |
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value: 0.3731679950751101
|
| 894 |
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- type: manhattan_pearson
|
| 895 |
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value: 0.35558794378442254
|
| 896 |
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- type: manhattan_spearman
|
| 897 |
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value: 0.3736943324703548
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| 898 |
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- task:
|
| 899 |
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type:STS
|
| 900 |
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dataset:
|
| 901 |
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type:mteb/sts22-crosslingual-sts
|
| 902 |
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name: MTEB STS22
|
| 903 |
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config: default
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| 904 |
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split:test
|
| 905 |
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revision:6d1ba47164174a496b7fa5d3569dae26a6813b80
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| 906 |
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metrics:
|
| 907 |
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- type: zh_cos_sim
|
| 908 |
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value: {'pearson': 0.687924534800626, 'spearman': 0.6945014686127369}
|
| 909 |
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- type: zh_euclidean
|
| 910 |
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value: {'pearson': 0.6912500964503516, 'spearman': 0.6945014686127369}
|
| 911 |
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- type: zh_manhattan
|
| 912 |
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value: {'pearson': 0.7053825064823807, 'spearman': 0.7067595198226869}
|
| 913 |
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- task:
|
| 914 |
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type:STS
|
| 915 |
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dataset:
|
| 916 |
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type:C-MTEB/STSB
|
| 917 |
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name: MTEB STSB
|
| 918 |
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config: default
|
| 919 |
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split:test
|
| 920 |
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revision:None
|
| 921 |
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metrics:
|
| 922 |
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- type: cos_sim_pearson
|
| 923 |
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value: 0.7902281275805849
|
| 924 |
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- type: cos_sim_spearman
|
| 925 |
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value: 0.7969275718339353
|
| 926 |
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- type: euclidean_pearson
|
| 927 |
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value: 0.7939660648560956
|
| 928 |
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- type: euclidean_spearman
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| 929 |
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value: 0.7969291851788453
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| 930 |
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- type: manhattan_pearson
|
| 931 |
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value: 0.793382690172365
|
| 932 |
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- type: manhattan_spearman
|
| 933 |
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value: 0.7963605584076028
|
| 934 |
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- task:
|
| 935 |
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type:Reranking
|
| 936 |
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dataset:
|
| 937 |
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type:C-MTEB/T2Reranking
|
| 938 |
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name: MTEB T2Reranking
|
| 939 |
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config: default
|
| 940 |
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split:dev
|
| 941 |
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revision:None
|
| 942 |
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metrics:
|
| 943 |
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- type: map
|
| 944 |
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value: 0.6619942712343411
|
| 945 |
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|
| 946 |
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value: 0.7576681067371656
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| 947 |
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- task:
|
| 948 |
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type:Retrieval
|
| 949 |
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dataset:
|
| 950 |
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type:C-MTEB/T2Retrieval
|
| 951 |
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name: MTEB T2Retrieval
|
| 952 |
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config: default
|
| 953 |
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split:dev
|
| 954 |
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revision:None
|
| 955 |
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metrics:
|
| 956 |
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- type: map_at_1
|
| 957 |
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value: 0.26594
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| 958 |
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|
| 959 |
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value: 0.75272
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| 960 |
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|
| 961 |
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value: 0.7896
|
| 962 |
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- type: map_at_1000
|
| 963 |
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value: 0.79032
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| 964 |
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|
| 965 |
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value: 0.5276
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| 966 |
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| 967 |
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value: 0.64967
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|
| 969 |
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value: 0.88721
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| 970 |
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|
| 971 |
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value: 0.9138
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|
| 973 |
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value: 0.91484
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|
| 975 |
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value: 0.91489
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|
| 977 |
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value: 0.90901
|
| 978 |
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- type: mrr_at_5
|
| 979 |
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value: 0.9121
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| 980 |
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- type: ndcg_at_1
|
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value: 0.88721
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|
| 983 |
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value: 0.83099
|
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|
| 985 |
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value: 0.86938
|
| 986 |
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|
| 987 |
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value: 0.87644
|
| 988 |
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|
| 989 |
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value: 0.84573
|
| 990 |
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- type: ndcg_at_5
|
| 991 |
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value: 0.83131
|
| 992 |
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- type: precision_at_1
|
| 993 |
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value: 0.88721
|
| 994 |
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- type: precision_at_10
|
| 995 |
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value: 0.41506
|
| 996 |
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- type: precision_at_100
|
| 997 |
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value: 0.0499
|
| 998 |
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- type: precision_at_1000
|
| 999 |
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value: 0.00515
|
| 1000 |
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- type: precision_at_3
|
| 1001 |
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value: 0.74214
|
| 1002 |
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- type: precision_at_5
|
| 1003 |
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value: 0.62244
|
| 1004 |
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- type: recall_at_1
|
| 1005 |
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value: 0.26594
|
| 1006 |
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- type: recall_at_10
|
| 1007 |
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value: 0.82121
|
| 1008 |
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- type: recall_at_100
|
| 1009 |
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value: 0.94643
|
| 1010 |
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- type: recall_at_1000
|
| 1011 |
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value: 0.98261
|
| 1012 |
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- type: recall_at_3
|
| 1013 |
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value: 0.54539
|
| 1014 |
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- type: recall_at_5
|
| 1015 |
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value: 0.68573
|
| 1016 |
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- task:
|
| 1017 |
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type:Clustering
|
| 1018 |
+
dataset:
|
| 1019 |
+
type:C-MTEB/ThuNewsClusteringP2P
|
| 1020 |
+
name: MTEB ThuNewsClusteringP2P
|
| 1021 |
+
config: default
|
| 1022 |
+
split:test
|
| 1023 |
+
revision:None
|
| 1024 |
+
metrics:
|
| 1025 |
+
- type: v_measure
|
| 1026 |
+
value: 0.6234936773593232
|
| 1027 |
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- type: v_measure_std
|
| 1028 |
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value: 0.014872291909155068
|
| 1029 |
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- task:
|
| 1030 |
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type:Clustering
|
| 1031 |
+
dataset:
|
| 1032 |
+
type:C-MTEB/ThuNewsClusteringS2S
|
| 1033 |
+
name: MTEB ThuNewsClusteringS2S
|
| 1034 |
+
config: default
|
| 1035 |
+
split:test
|
| 1036 |
+
revision:None
|
| 1037 |
+
metrics:
|
| 1038 |
+
- type: v_measure
|
| 1039 |
+
value: 0.5865057354232379
|
| 1040 |
+
- type: v_measure_std
|
| 1041 |
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value: 0.014281574028380747
|
| 1042 |
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- task:
|
| 1043 |
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type:Classification
|
| 1044 |
+
dataset:
|
| 1045 |
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type:C-MTEB/TNews-classification
|
| 1046 |
+
name: MTEB TNews
|
| 1047 |
+
config: default
|
| 1048 |
+
split:validation
|
| 1049 |
+
revision:None
|
| 1050 |
+
metrics:
|
| 1051 |
+
- type: accuracy
|
| 1052 |
+
value: 0.51845
|
| 1053 |
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- type: accuracy_stderr
|
| 1054 |
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value: 0.006959058844412791
|
| 1055 |
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- type: f1
|
| 1056 |
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value: 0.4997529772676145
|
| 1057 |
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- type: f1_stderr
|
| 1058 |
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value: 0.007865498715360303
|
| 1059 |
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- type: main_score
|
| 1060 |
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value: 0.51845
|
| 1061 |
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- task:
|
| 1062 |
+
type:Retrieval
|
| 1063 |
+
dataset:
|
| 1064 |
+
type:C-MTEB/VideoRetrieval
|
| 1065 |
+
name: MTEB VideoRetrieval
|
| 1066 |
+
config: default
|
| 1067 |
+
split:dev
|
| 1068 |
+
revision:None
|
| 1069 |
+
metrics:
|
| 1070 |
+
- type: map_at_1
|
| 1071 |
+
value: 0.522
|
| 1072 |
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- type: map_at_10
|
| 1073 |
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value: 0.62669
|
| 1074 |
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- type: map_at_100
|
| 1075 |
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value: 0.63239
|
| 1076 |
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- type: map_at_1000
|
| 1077 |
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value: 0.63253
|
| 1078 |
+
- type: map_at_3
|
| 1079 |
+
value: 0.60267
|
| 1080 |
+
- type: map_at_5
|
| 1081 |
+
value: 0.61772
|
| 1082 |
+
- type: mrr_at_1
|
| 1083 |
+
value: 0.522
|
| 1084 |
+
- type: mrr_at_10
|
| 1085 |
+
value: 0.62669
|
| 1086 |
+
- type: mrr_at_100
|
| 1087 |
+
value: 0.63239
|
| 1088 |
+
- type: mrr_at_1000
|
| 1089 |
+
value: 0.63253
|
| 1090 |
+
- type: mrr_at_3
|
| 1091 |
+
value: 0.60267
|
| 1092 |
+
- type: mrr_at_5
|
| 1093 |
+
value: 0.61772
|
| 1094 |
+
- type: ndcg_at_1
|
| 1095 |
+
value: 0.522
|
| 1096 |
+
- type: ndcg_at_10
|
| 1097 |
+
value: 0.67583
|
| 1098 |
+
- type: ndcg_at_100
|
| 1099 |
+
value: 0.70305
|
| 1100 |
+
- type: ndcg_at_1000
|
| 1101 |
+
value: 0.70652
|
| 1102 |
+
- type: ndcg_at_3
|
| 1103 |
+
value: 0.62776
|
| 1104 |
+
- type: ndcg_at_5
|
| 1105 |
+
value: 0.6547
|
| 1106 |
+
- type: precision_at_1
|
| 1107 |
+
value: 0.522
|
| 1108 |
+
- type: precision_at_10
|
| 1109 |
+
value: 0.0829
|
| 1110 |
+
- type: precision_at_100
|
| 1111 |
+
value: 0.00955
|
| 1112 |
+
- type: precision_at_1000
|
| 1113 |
+
value: 0.00098
|
| 1114 |
+
- type: precision_at_3
|
| 1115 |
+
value: 0.23333
|
| 1116 |
+
- type: precision_at_5
|
| 1117 |
+
value: 0.153
|
| 1118 |
+
- type: recall_at_1
|
| 1119 |
+
value: 0.522
|
| 1120 |
+
- type: recall_at_10
|
| 1121 |
+
value: 0.829
|
| 1122 |
+
- type: recall_at_100
|
| 1123 |
+
value: 0.955
|
| 1124 |
+
- type: recall_at_1000
|
| 1125 |
+
value: 0.982
|
| 1126 |
+
- type: recall_at_3
|
| 1127 |
+
value: 0.7
|
| 1128 |
+
- type: recall_at_5
|
| 1129 |
+
value: 0.765
|
| 1130 |
+
- task:
|
| 1131 |
+
type:Classification
|
| 1132 |
+
dataset:
|
| 1133 |
+
type: C-MTEB/waimai-classification
|
| 1134 |
+
name: MTEB Waimai
|
| 1135 |
+
config: default
|
| 1136 |
+
split:test
|
| 1137 |
+
revision:None
|
| 1138 |
+
metrics:
|
| 1139 |
+
- type: accuracy
|
| 1140 |
+
value: 0.8664999999999999
|
| 1141 |
+
- type: accuracy_stderr
|
| 1142 |
+
value: 0.007697402159170332
|
| 1143 |
+
- type: ap
|
| 1144 |
+
value: 0.6990209999390807
|
| 1145 |
+
- type: ap_stderr
|
| 1146 |
+
value: 0.014543148063974986
|
| 1147 |
+
- type: f1
|
| 1148 |
+
value: 0.849231810656075
|
| 1149 |
+
- type: f1_stderr
|
| 1150 |
+
value: 0.0073258070989864026
|
| 1151 |
+
- type: main_score
|
| 1152 |
+
value: 0.8664999999999999
|