Commit
•
4632e9e
1
Parent(s):
a3bebbf
Update README.md (#1)
Browse files- Update README.md (c59f7e62cfba7d5ee8881770bd4564f40ee6806e)
Co-authored-by: zhonghao Zhao <[email protected]>
README.md
CHANGED
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@@ -7,6 +7,1097 @@ tags:
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| 7 |
- transformers
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| 8 |
- semantic-search
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| 9 |
- chinese
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| 10 |
---
|
| 11 |
|
| 12 |
# DMetaSoul/sbert-chinese-general-v1
|
|
|
|
| 7 |
- transformers
|
| 8 |
- semantic-search
|
| 9 |
- chinese
|
| 10 |
+
- mteb
|
| 11 |
+
model-index:
|
| 12 |
+
- name: sbert-chinese-general-v1
|
| 13 |
+
results:
|
| 14 |
+
- task:
|
| 15 |
+
type: STS
|
| 16 |
+
dataset:
|
| 17 |
+
type: C-MTEB/AFQMC
|
| 18 |
+
name: MTEB AFQMC
|
| 19 |
+
config: default
|
| 20 |
+
split: validation
|
| 21 |
+
revision: None
|
| 22 |
+
metrics:
|
| 23 |
+
- type: cos_sim_pearson
|
| 24 |
+
value: 22.293919432958074
|
| 25 |
+
- type: cos_sim_spearman
|
| 26 |
+
value: 22.56718923553609
|
| 27 |
+
- type: euclidean_pearson
|
| 28 |
+
value: 22.525656322797026
|
| 29 |
+
- type: euclidean_spearman
|
| 30 |
+
value: 22.56718923553609
|
| 31 |
+
- type: manhattan_pearson
|
| 32 |
+
value: 22.501773028824065
|
| 33 |
+
- type: manhattan_spearman
|
| 34 |
+
value: 22.536992587828397
|
| 35 |
+
- task:
|
| 36 |
+
type: STS
|
| 37 |
+
dataset:
|
| 38 |
+
type: C-MTEB/ATEC
|
| 39 |
+
name: MTEB ATEC
|
| 40 |
+
config: default
|
| 41 |
+
split: test
|
| 42 |
+
revision: None
|
| 43 |
+
metrics:
|
| 44 |
+
- type: cos_sim_pearson
|
| 45 |
+
value: 30.33575274463879
|
| 46 |
+
- type: cos_sim_spearman
|
| 47 |
+
value: 30.298708742167772
|
| 48 |
+
- type: euclidean_pearson
|
| 49 |
+
value: 32.33094743729218
|
| 50 |
+
- type: euclidean_spearman
|
| 51 |
+
value: 30.298710993858734
|
| 52 |
+
- type: manhattan_pearson
|
| 53 |
+
value: 32.31155376195945
|
| 54 |
+
- type: manhattan_spearman
|
| 55 |
+
value: 30.267669681690744
|
| 56 |
+
- task:
|
| 57 |
+
type: Classification
|
| 58 |
+
dataset:
|
| 59 |
+
type: mteb/amazon_reviews_multi
|
| 60 |
+
name: MTEB AmazonReviewsClassification (zh)
|
| 61 |
+
config: zh
|
| 62 |
+
split: test
|
| 63 |
+
revision: 1399c76144fd37290681b995c656ef9b2e06e26d
|
| 64 |
+
metrics:
|
| 65 |
+
- type: accuracy
|
| 66 |
+
value: 37.507999999999996
|
| 67 |
+
- type: f1
|
| 68 |
+
value: 36.436808400753286
|
| 69 |
+
- task:
|
| 70 |
+
type: STS
|
| 71 |
+
dataset:
|
| 72 |
+
type: C-MTEB/BQ
|
| 73 |
+
name: MTEB BQ
|
| 74 |
+
config: default
|
| 75 |
+
split: test
|
| 76 |
+
revision: None
|
| 77 |
+
metrics:
|
| 78 |
+
- type: cos_sim_pearson
|
| 79 |
+
value: 41.493256724214255
|
| 80 |
+
- type: cos_sim_spearman
|
| 81 |
+
value: 40.98395961967895
|
| 82 |
+
- type: euclidean_pearson
|
| 83 |
+
value: 41.12345737966565
|
| 84 |
+
- type: euclidean_spearman
|
| 85 |
+
value: 40.983959619555996
|
| 86 |
+
- type: manhattan_pearson
|
| 87 |
+
value: 41.02584539471014
|
| 88 |
+
- type: manhattan_spearman
|
| 89 |
+
value: 40.87549513383032
|
| 90 |
+
- task:
|
| 91 |
+
type: BitextMining
|
| 92 |
+
dataset:
|
| 93 |
+
type: mteb/bucc-bitext-mining
|
| 94 |
+
name: MTEB BUCC (zh-en)
|
| 95 |
+
config: zh-en
|
| 96 |
+
split: test
|
| 97 |
+
revision: d51519689f32196a32af33b075a01d0e7c51e252
|
| 98 |
+
metrics:
|
| 99 |
+
- type: accuracy
|
| 100 |
+
value: 9.794628751974724
|
| 101 |
+
- type: f1
|
| 102 |
+
value: 9.350535369492716
|
| 103 |
+
- type: precision
|
| 104 |
+
value: 9.179392662804986
|
| 105 |
+
- type: recall
|
| 106 |
+
value: 9.794628751974724
|
| 107 |
+
- task:
|
| 108 |
+
type: Clustering
|
| 109 |
+
dataset:
|
| 110 |
+
type: C-MTEB/CLSClusteringP2P
|
| 111 |
+
name: MTEB CLSClusteringP2P
|
| 112 |
+
config: default
|
| 113 |
+
split: test
|
| 114 |
+
revision: None
|
| 115 |
+
metrics:
|
| 116 |
+
- type: v_measure
|
| 117 |
+
value: 34.984726547788284
|
| 118 |
+
- task:
|
| 119 |
+
type: Clustering
|
| 120 |
+
dataset:
|
| 121 |
+
type: C-MTEB/CLSClusteringS2S
|
| 122 |
+
name: MTEB CLSClusteringS2S
|
| 123 |
+
config: default
|
| 124 |
+
split: test
|
| 125 |
+
revision: None
|
| 126 |
+
metrics:
|
| 127 |
+
- type: v_measure
|
| 128 |
+
value: 27.81945732281589
|
| 129 |
+
- task:
|
| 130 |
+
type: Reranking
|
| 131 |
+
dataset:
|
| 132 |
+
type: C-MTEB/CMedQAv1-reranking
|
| 133 |
+
name: MTEB CMedQAv1
|
| 134 |
+
config: default
|
| 135 |
+
split: test
|
| 136 |
+
revision: None
|
| 137 |
+
metrics:
|
| 138 |
+
- type: map
|
| 139 |
+
value: 53.06586280826805
|
| 140 |
+
- type: mrr
|
| 141 |
+
value: 59.58781746031746
|
| 142 |
+
- task:
|
| 143 |
+
type: Reranking
|
| 144 |
+
dataset:
|
| 145 |
+
type: C-MTEB/CMedQAv2-reranking
|
| 146 |
+
name: MTEB CMedQAv2
|
| 147 |
+
config: default
|
| 148 |
+
split: test
|
| 149 |
+
revision: None
|
| 150 |
+
metrics:
|
| 151 |
+
- type: map
|
| 152 |
+
value: 52.83635946154306
|
| 153 |
+
- type: mrr
|
| 154 |
+
value: 59.315079365079356
|
| 155 |
+
- task:
|
| 156 |
+
type: Retrieval
|
| 157 |
+
dataset:
|
| 158 |
+
type: C-MTEB/CmedqaRetrieval
|
| 159 |
+
name: MTEB CmedqaRetrieval
|
| 160 |
+
config: default
|
| 161 |
+
split: dev
|
| 162 |
+
revision: None
|
| 163 |
+
metrics:
|
| 164 |
+
- type: map_at_1
|
| 165 |
+
value: 5.721
|
| 166 |
+
- type: map_at_10
|
| 167 |
+
value: 8.645
|
| 168 |
+
- type: map_at_100
|
| 169 |
+
value: 9.434
|
| 170 |
+
- type: map_at_1000
|
| 171 |
+
value: 9.586
|
| 172 |
+
- type: map_at_3
|
| 173 |
+
value: 7.413
|
| 174 |
+
- type: map_at_5
|
| 175 |
+
value: 8.05
|
| 176 |
+
- type: mrr_at_1
|
| 177 |
+
value: 9.626999999999999
|
| 178 |
+
- type: mrr_at_10
|
| 179 |
+
value: 13.094
|
| 180 |
+
- type: mrr_at_100
|
| 181 |
+
value: 13.854
|
| 182 |
+
- type: mrr_at_1000
|
| 183 |
+
value: 13.958
|
| 184 |
+
- type: mrr_at_3
|
| 185 |
+
value: 11.724
|
| 186 |
+
- type: mrr_at_5
|
| 187 |
+
value: 12.409
|
| 188 |
+
- type: ndcg_at_1
|
| 189 |
+
value: 9.626999999999999
|
| 190 |
+
- type: ndcg_at_10
|
| 191 |
+
value: 11.35
|
| 192 |
+
- type: ndcg_at_100
|
| 193 |
+
value: 15.593000000000002
|
| 194 |
+
- type: ndcg_at_1000
|
| 195 |
+
value: 19.619
|
| 196 |
+
- type: ndcg_at_3
|
| 197 |
+
value: 9.317
|
| 198 |
+
- type: ndcg_at_5
|
| 199 |
+
value: 10.049
|
| 200 |
+
- type: precision_at_1
|
| 201 |
+
value: 9.626999999999999
|
| 202 |
+
- type: precision_at_10
|
| 203 |
+
value: 2.796
|
| 204 |
+
- type: precision_at_100
|
| 205 |
+
value: 0.629
|
| 206 |
+
- type: precision_at_1000
|
| 207 |
+
value: 0.11800000000000001
|
| 208 |
+
- type: precision_at_3
|
| 209 |
+
value: 5.476
|
| 210 |
+
- type: precision_at_5
|
| 211 |
+
value: 4.1209999999999996
|
| 212 |
+
- type: recall_at_1
|
| 213 |
+
value: 5.721
|
| 214 |
+
- type: recall_at_10
|
| 215 |
+
value: 15.190000000000001
|
| 216 |
+
- type: recall_at_100
|
| 217 |
+
value: 33.633
|
| 218 |
+
- type: recall_at_1000
|
| 219 |
+
value: 62.019999999999996
|
| 220 |
+
- type: recall_at_3
|
| 221 |
+
value: 9.099
|
| 222 |
+
- type: recall_at_5
|
| 223 |
+
value: 11.423
|
| 224 |
+
- task:
|
| 225 |
+
type: PairClassification
|
| 226 |
+
dataset:
|
| 227 |
+
type: C-MTEB/CMNLI
|
| 228 |
+
name: MTEB Cmnli
|
| 229 |
+
config: default
|
| 230 |
+
split: validation
|
| 231 |
+
revision: None
|
| 232 |
+
metrics:
|
| 233 |
+
- type: cos_sim_accuracy
|
| 234 |
+
value: 77.36620565243535
|
| 235 |
+
- type: cos_sim_ap
|
| 236 |
+
value: 85.92291866877001
|
| 237 |
+
- type: cos_sim_f1
|
| 238 |
+
value: 78.19390231037029
|
| 239 |
+
- type: cos_sim_precision
|
| 240 |
+
value: 71.24183006535948
|
| 241 |
+
- type: cos_sim_recall
|
| 242 |
+
value: 86.64952069207388
|
| 243 |
+
- type: dot_accuracy
|
| 244 |
+
value: 77.36620565243535
|
| 245 |
+
- type: dot_ap
|
| 246 |
+
value: 85.94113738490068
|
| 247 |
+
- type: dot_f1
|
| 248 |
+
value: 78.19390231037029
|
| 249 |
+
- type: dot_precision
|
| 250 |
+
value: 71.24183006535948
|
| 251 |
+
- type: dot_recall
|
| 252 |
+
value: 86.64952069207388
|
| 253 |
+
- type: euclidean_accuracy
|
| 254 |
+
value: 77.36620565243535
|
| 255 |
+
- type: euclidean_ap
|
| 256 |
+
value: 85.92291893444687
|
| 257 |
+
- type: euclidean_f1
|
| 258 |
+
value: 78.19390231037029
|
| 259 |
+
- type: euclidean_precision
|
| 260 |
+
value: 71.24183006535948
|
| 261 |
+
- type: euclidean_recall
|
| 262 |
+
value: 86.64952069207388
|
| 263 |
+
- type: manhattan_accuracy
|
| 264 |
+
value: 77.29404690318701
|
| 265 |
+
- type: manhattan_ap
|
| 266 |
+
value: 85.88284362100919
|
| 267 |
+
- type: manhattan_f1
|
| 268 |
+
value: 78.17836812144213
|
| 269 |
+
- type: manhattan_precision
|
| 270 |
+
value: 71.18448838548666
|
| 271 |
+
- type: manhattan_recall
|
| 272 |
+
value: 86.69628244096329
|
| 273 |
+
- type: max_accuracy
|
| 274 |
+
value: 77.36620565243535
|
| 275 |
+
- type: max_ap
|
| 276 |
+
value: 85.94113738490068
|
| 277 |
+
- type: max_f1
|
| 278 |
+
value: 78.19390231037029
|
| 279 |
+
- task:
|
| 280 |
+
type: Retrieval
|
| 281 |
+
dataset:
|
| 282 |
+
type: C-MTEB/CovidRetrieval
|
| 283 |
+
name: MTEB CovidRetrieval
|
| 284 |
+
config: default
|
| 285 |
+
split: dev
|
| 286 |
+
revision: None
|
| 287 |
+
metrics:
|
| 288 |
+
- type: map_at_1
|
| 289 |
+
value: 26.976
|
| 290 |
+
- type: map_at_10
|
| 291 |
+
value: 35.18
|
| 292 |
+
- type: map_at_100
|
| 293 |
+
value: 35.921
|
| 294 |
+
- type: map_at_1000
|
| 295 |
+
value: 35.998999999999995
|
| 296 |
+
- type: map_at_3
|
| 297 |
+
value: 32.763
|
| 298 |
+
- type: map_at_5
|
| 299 |
+
value: 34.165
|
| 300 |
+
- type: mrr_at_1
|
| 301 |
+
value: 26.976
|
| 302 |
+
- type: mrr_at_10
|
| 303 |
+
value: 35.234
|
| 304 |
+
- type: mrr_at_100
|
| 305 |
+
value: 35.939
|
| 306 |
+
- type: mrr_at_1000
|
| 307 |
+
value: 36.016
|
| 308 |
+
- type: mrr_at_3
|
| 309 |
+
value: 32.771
|
| 310 |
+
- type: mrr_at_5
|
| 311 |
+
value: 34.172999999999995
|
| 312 |
+
- type: ndcg_at_1
|
| 313 |
+
value: 26.976
|
| 314 |
+
- type: ndcg_at_10
|
| 315 |
+
value: 39.635
|
| 316 |
+
- type: ndcg_at_100
|
| 317 |
+
value: 43.54
|
| 318 |
+
- type: ndcg_at_1000
|
| 319 |
+
value: 45.723
|
| 320 |
+
- type: ndcg_at_3
|
| 321 |
+
value: 34.652
|
| 322 |
+
- type: ndcg_at_5
|
| 323 |
+
value: 37.186
|
| 324 |
+
- type: precision_at_1
|
| 325 |
+
value: 26.976
|
| 326 |
+
- type: precision_at_10
|
| 327 |
+
value: 5.406
|
| 328 |
+
- type: precision_at_100
|
| 329 |
+
value: 0.736
|
| 330 |
+
- type: precision_at_1000
|
| 331 |
+
value: 0.091
|
| 332 |
+
- type: precision_at_3
|
| 333 |
+
value: 13.418
|
| 334 |
+
- type: precision_at_5
|
| 335 |
+
value: 9.293999999999999
|
| 336 |
+
- type: recall_at_1
|
| 337 |
+
value: 26.976
|
| 338 |
+
- type: recall_at_10
|
| 339 |
+
value: 53.766999999999996
|
| 340 |
+
- type: recall_at_100
|
| 341 |
+
value: 72.761
|
| 342 |
+
- type: recall_at_1000
|
| 343 |
+
value: 90.148
|
| 344 |
+
- type: recall_at_3
|
| 345 |
+
value: 40.095
|
| 346 |
+
- type: recall_at_5
|
| 347 |
+
value: 46.233000000000004
|
| 348 |
+
- task:
|
| 349 |
+
type: Retrieval
|
| 350 |
+
dataset:
|
| 351 |
+
type: C-MTEB/DuRetrieval
|
| 352 |
+
name: MTEB DuRetrieval
|
| 353 |
+
config: default
|
| 354 |
+
split: dev
|
| 355 |
+
revision: None
|
| 356 |
+
metrics:
|
| 357 |
+
- type: map_at_1
|
| 358 |
+
value: 11.285
|
| 359 |
+
- type: map_at_10
|
| 360 |
+
value: 30.259000000000004
|
| 361 |
+
- type: map_at_100
|
| 362 |
+
value: 33.772000000000006
|
| 363 |
+
- type: map_at_1000
|
| 364 |
+
value: 34.037
|
| 365 |
+
- type: map_at_3
|
| 366 |
+
value: 21.038999999999998
|
| 367 |
+
- type: map_at_5
|
| 368 |
+
value: 25.939
|
| 369 |
+
- type: mrr_at_1
|
| 370 |
+
value: 45.1
|
| 371 |
+
- type: mrr_at_10
|
| 372 |
+
value: 55.803999999999995
|
| 373 |
+
- type: mrr_at_100
|
| 374 |
+
value: 56.301
|
| 375 |
+
- type: mrr_at_1000
|
| 376 |
+
value: 56.330999999999996
|
| 377 |
+
- type: mrr_at_3
|
| 378 |
+
value: 53.333
|
| 379 |
+
- type: mrr_at_5
|
| 380 |
+
value: 54.798
|
| 381 |
+
- type: ndcg_at_1
|
| 382 |
+
value: 45.1
|
| 383 |
+
- type: ndcg_at_10
|
| 384 |
+
value: 41.156
|
| 385 |
+
- type: ndcg_at_100
|
| 386 |
+
value: 49.518
|
| 387 |
+
- type: ndcg_at_1000
|
| 388 |
+
value: 52.947
|
| 389 |
+
- type: ndcg_at_3
|
| 390 |
+
value: 39.708
|
| 391 |
+
- type: ndcg_at_5
|
| 392 |
+
value: 38.704
|
| 393 |
+
- type: precision_at_1
|
| 394 |
+
value: 45.1
|
| 395 |
+
- type: precision_at_10
|
| 396 |
+
value: 20.75
|
| 397 |
+
- type: precision_at_100
|
| 398 |
+
value: 3.424
|
| 399 |
+
- type: precision_at_1000
|
| 400 |
+
value: 0.42700000000000005
|
| 401 |
+
- type: precision_at_3
|
| 402 |
+
value: 35.632999999999996
|
| 403 |
+
- type: precision_at_5
|
| 404 |
+
value: 30.080000000000002
|
| 405 |
+
- type: recall_at_1
|
| 406 |
+
value: 11.285
|
| 407 |
+
- type: recall_at_10
|
| 408 |
+
value: 43.242000000000004
|
| 409 |
+
- type: recall_at_100
|
| 410 |
+
value: 68.604
|
| 411 |
+
- type: recall_at_1000
|
| 412 |
+
value: 85.904
|
| 413 |
+
- type: recall_at_3
|
| 414 |
+
value: 24.404
|
| 415 |
+
- type: recall_at_5
|
| 416 |
+
value: 32.757
|
| 417 |
+
- task:
|
| 418 |
+
type: Retrieval
|
| 419 |
+
dataset:
|
| 420 |
+
type: C-MTEB/EcomRetrieval
|
| 421 |
+
name: MTEB EcomRetrieval
|
| 422 |
+
config: default
|
| 423 |
+
split: dev
|
| 424 |
+
revision: None
|
| 425 |
+
metrics:
|
| 426 |
+
- type: map_at_1
|
| 427 |
+
value: 21.0
|
| 428 |
+
- type: map_at_10
|
| 429 |
+
value: 28.364
|
| 430 |
+
- type: map_at_100
|
| 431 |
+
value: 29.199
|
| 432 |
+
- type: map_at_1000
|
| 433 |
+
value: 29.265
|
| 434 |
+
- type: map_at_3
|
| 435 |
+
value: 25.717000000000002
|
| 436 |
+
- type: map_at_5
|
| 437 |
+
value: 27.311999999999998
|
| 438 |
+
- type: mrr_at_1
|
| 439 |
+
value: 21.0
|
| 440 |
+
- type: mrr_at_10
|
| 441 |
+
value: 28.364
|
| 442 |
+
- type: mrr_at_100
|
| 443 |
+
value: 29.199
|
| 444 |
+
- type: mrr_at_1000
|
| 445 |
+
value: 29.265
|
| 446 |
+
- type: mrr_at_3
|
| 447 |
+
value: 25.717000000000002
|
| 448 |
+
- type: mrr_at_5
|
| 449 |
+
value: 27.311999999999998
|
| 450 |
+
- type: ndcg_at_1
|
| 451 |
+
value: 21.0
|
| 452 |
+
- type: ndcg_at_10
|
| 453 |
+
value: 32.708
|
| 454 |
+
- type: ndcg_at_100
|
| 455 |
+
value: 37.184
|
| 456 |
+
- type: ndcg_at_1000
|
| 457 |
+
value: 39.273
|
| 458 |
+
- type: ndcg_at_3
|
| 459 |
+
value: 27.372000000000003
|
| 460 |
+
- type: ndcg_at_5
|
| 461 |
+
value: 30.23
|
| 462 |
+
- type: precision_at_1
|
| 463 |
+
value: 21.0
|
| 464 |
+
- type: precision_at_10
|
| 465 |
+
value: 4.66
|
| 466 |
+
- type: precision_at_100
|
| 467 |
+
value: 0.685
|
| 468 |
+
- type: precision_at_1000
|
| 469 |
+
value: 0.086
|
| 470 |
+
- type: precision_at_3
|
| 471 |
+
value: 10.732999999999999
|
| 472 |
+
- type: precision_at_5
|
| 473 |
+
value: 7.82
|
| 474 |
+
- type: recall_at_1
|
| 475 |
+
value: 21.0
|
| 476 |
+
- type: recall_at_10
|
| 477 |
+
value: 46.6
|
| 478 |
+
- type: recall_at_100
|
| 479 |
+
value: 68.5
|
| 480 |
+
- type: recall_at_1000
|
| 481 |
+
value: 85.6
|
| 482 |
+
- type: recall_at_3
|
| 483 |
+
value: 32.2
|
| 484 |
+
- type: recall_at_5
|
| 485 |
+
value: 39.1
|
| 486 |
+
- task:
|
| 487 |
+
type: Classification
|
| 488 |
+
dataset:
|
| 489 |
+
type: C-MTEB/IFlyTek-classification
|
| 490 |
+
name: MTEB IFlyTek
|
| 491 |
+
config: default
|
| 492 |
+
split: validation
|
| 493 |
+
revision: None
|
| 494 |
+
metrics:
|
| 495 |
+
- type: accuracy
|
| 496 |
+
value: 44.878799538283964
|
| 497 |
+
- type: f1
|
| 498 |
+
value: 33.84678310261366
|
| 499 |
+
- task:
|
| 500 |
+
type: Classification
|
| 501 |
+
dataset:
|
| 502 |
+
type: C-MTEB/JDReview-classification
|
| 503 |
+
name: MTEB JDReview
|
| 504 |
+
config: default
|
| 505 |
+
split: test
|
| 506 |
+
revision: None
|
| 507 |
+
metrics:
|
| 508 |
+
- type: accuracy
|
| 509 |
+
value: 82.1951219512195
|
| 510 |
+
- type: ap
|
| 511 |
+
value: 46.78292030042397
|
| 512 |
+
- type: f1
|
| 513 |
+
value: 76.20482468514128
|
| 514 |
+
- task:
|
| 515 |
+
type: STS
|
| 516 |
+
dataset:
|
| 517 |
+
type: C-MTEB/LCQMC
|
| 518 |
+
name: MTEB LCQMC
|
| 519 |
+
config: default
|
| 520 |
+
split: test
|
| 521 |
+
revision: None
|
| 522 |
+
metrics:
|
| 523 |
+
- type: cos_sim_pearson
|
| 524 |
+
value: 62.84331627244547
|
| 525 |
+
- type: cos_sim_spearman
|
| 526 |
+
value: 68.39990265073726
|
| 527 |
+
- type: euclidean_pearson
|
| 528 |
+
value: 66.87431827169324
|
| 529 |
+
- type: euclidean_spearman
|
| 530 |
+
value: 68.39990264979167
|
| 531 |
+
- type: manhattan_pearson
|
| 532 |
+
value: 66.89702078900328
|
| 533 |
+
- type: manhattan_spearman
|
| 534 |
+
value: 68.42107302159141
|
| 535 |
+
- task:
|
| 536 |
+
type: Reranking
|
| 537 |
+
dataset:
|
| 538 |
+
type: C-MTEB/Mmarco-reranking
|
| 539 |
+
name: MTEB MMarcoReranking
|
| 540 |
+
config: default
|
| 541 |
+
split: dev
|
| 542 |
+
revision: None
|
| 543 |
+
metrics:
|
| 544 |
+
- type: map
|
| 545 |
+
value: 9.28600891904827
|
| 546 |
+
- type: mrr
|
| 547 |
+
value: 8.057936507936509
|
| 548 |
+
- task:
|
| 549 |
+
type: Retrieval
|
| 550 |
+
dataset:
|
| 551 |
+
type: C-MTEB/MMarcoRetrieval
|
| 552 |
+
name: MTEB MMarcoRetrieval
|
| 553 |
+
config: default
|
| 554 |
+
split: dev
|
| 555 |
+
revision: None
|
| 556 |
+
metrics:
|
| 557 |
+
- type: map_at_1
|
| 558 |
+
value: 22.820999999999998
|
| 559 |
+
- type: map_at_10
|
| 560 |
+
value: 30.44
|
| 561 |
+
- type: map_at_100
|
| 562 |
+
value: 31.35
|
| 563 |
+
- type: map_at_1000
|
| 564 |
+
value: 31.419000000000004
|
| 565 |
+
- type: map_at_3
|
| 566 |
+
value: 28.134999999999998
|
| 567 |
+
- type: map_at_5
|
| 568 |
+
value: 29.482000000000003
|
| 569 |
+
- type: mrr_at_1
|
| 570 |
+
value: 23.782
|
| 571 |
+
- type: mrr_at_10
|
| 572 |
+
value: 31.141999999999996
|
| 573 |
+
- type: mrr_at_100
|
| 574 |
+
value: 32.004
|
| 575 |
+
- type: mrr_at_1000
|
| 576 |
+
value: 32.068000000000005
|
| 577 |
+
- type: mrr_at_3
|
| 578 |
+
value: 28.904000000000003
|
| 579 |
+
- type: mrr_at_5
|
| 580 |
+
value: 30.214999999999996
|
| 581 |
+
- type: ndcg_at_1
|
| 582 |
+
value: 23.782
|
| 583 |
+
- type: ndcg_at_10
|
| 584 |
+
value: 34.625
|
| 585 |
+
- type: ndcg_at_100
|
| 586 |
+
value: 39.226
|
| 587 |
+
- type: ndcg_at_1000
|
| 588 |
+
value: 41.128
|
| 589 |
+
- type: ndcg_at_3
|
| 590 |
+
value: 29.968
|
| 591 |
+
- type: ndcg_at_5
|
| 592 |
+
value: 32.35
|
| 593 |
+
- type: precision_at_1
|
| 594 |
+
value: 23.782
|
| 595 |
+
- type: precision_at_10
|
| 596 |
+
value: 4.994
|
| 597 |
+
- type: precision_at_100
|
| 598 |
+
value: 0.736
|
| 599 |
+
- type: precision_at_1000
|
| 600 |
+
value: 0.09
|
| 601 |
+
- type: precision_at_3
|
| 602 |
+
value: 12.13
|
| 603 |
+
- type: precision_at_5
|
| 604 |
+
value: 8.495999999999999
|
| 605 |
+
- type: recall_at_1
|
| 606 |
+
value: 22.820999999999998
|
| 607 |
+
- type: recall_at_10
|
| 608 |
+
value: 47.141
|
| 609 |
+
- type: recall_at_100
|
| 610 |
+
value: 68.952
|
| 611 |
+
- type: recall_at_1000
|
| 612 |
+
value: 83.985
|
| 613 |
+
- type: recall_at_3
|
| 614 |
+
value: 34.508
|
| 615 |
+
- type: recall_at_5
|
| 616 |
+
value: 40.232
|
| 617 |
+
- task:
|
| 618 |
+
type: Classification
|
| 619 |
+
dataset:
|
| 620 |
+
type: mteb/amazon_massive_intent
|
| 621 |
+
name: MTEB MassiveIntentClassification (zh-CN)
|
| 622 |
+
config: zh-CN
|
| 623 |
+
split: test
|
| 624 |
+
revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
|
| 625 |
+
metrics:
|
| 626 |
+
- type: accuracy
|
| 627 |
+
value: 57.343644922663074
|
| 628 |
+
- type: f1
|
| 629 |
+
value: 56.744802953803486
|
| 630 |
+
- task:
|
| 631 |
+
type: Classification
|
| 632 |
+
dataset:
|
| 633 |
+
type: mteb/amazon_massive_scenario
|
| 634 |
+
name: MTEB MassiveScenarioClassification (zh-CN)
|
| 635 |
+
config: zh-CN
|
| 636 |
+
split: test
|
| 637 |
+
revision: 7d571f92784cd94a019292a1f45445077d0ef634
|
| 638 |
+
metrics:
|
| 639 |
+
- type: accuracy
|
| 640 |
+
value: 62.363819771351714
|
| 641 |
+
- type: f1
|
| 642 |
+
value: 62.15920863434656
|
| 643 |
+
- task:
|
| 644 |
+
type: Retrieval
|
| 645 |
+
dataset:
|
| 646 |
+
type: C-MTEB/MedicalRetrieval
|
| 647 |
+
name: MTEB MedicalRetrieval
|
| 648 |
+
config: default
|
| 649 |
+
split: dev
|
| 650 |
+
revision: None
|
| 651 |
+
metrics:
|
| 652 |
+
- type: map_at_1
|
| 653 |
+
value: 14.6
|
| 654 |
+
- type: map_at_10
|
| 655 |
+
value: 18.231
|
| 656 |
+
- type: map_at_100
|
| 657 |
+
value: 18.744
|
| 658 |
+
- type: map_at_1000
|
| 659 |
+
value: 18.811
|
| 660 |
+
- type: map_at_3
|
| 661 |
+
value: 17.133000000000003
|
| 662 |
+
- type: map_at_5
|
| 663 |
+
value: 17.663
|
| 664 |
+
- type: mrr_at_1
|
| 665 |
+
value: 14.6
|
| 666 |
+
- type: mrr_at_10
|
| 667 |
+
value: 18.231
|
| 668 |
+
- type: mrr_at_100
|
| 669 |
+
value: 18.744
|
| 670 |
+
- type: mrr_at_1000
|
| 671 |
+
value: 18.811
|
| 672 |
+
- type: mrr_at_3
|
| 673 |
+
value: 17.133000000000003
|
| 674 |
+
- type: mrr_at_5
|
| 675 |
+
value: 17.663
|
| 676 |
+
- type: ndcg_at_1
|
| 677 |
+
value: 14.6
|
| 678 |
+
- type: ndcg_at_10
|
| 679 |
+
value: 20.349
|
| 680 |
+
- type: ndcg_at_100
|
| 681 |
+
value: 23.204
|
| 682 |
+
- type: ndcg_at_1000
|
| 683 |
+
value: 25.44
|
| 684 |
+
- type: ndcg_at_3
|
| 685 |
+
value: 17.995
|
| 686 |
+
- type: ndcg_at_5
|
| 687 |
+
value: 18.945999999999998
|
| 688 |
+
- type: precision_at_1
|
| 689 |
+
value: 14.6
|
| 690 |
+
- type: precision_at_10
|
| 691 |
+
value: 2.7199999999999998
|
| 692 |
+
- type: precision_at_100
|
| 693 |
+
value: 0.414
|
| 694 |
+
- type: precision_at_1000
|
| 695 |
+
value: 0.06
|
| 696 |
+
- type: precision_at_3
|
| 697 |
+
value: 6.833
|
| 698 |
+
- type: precision_at_5
|
| 699 |
+
value: 4.5600000000000005
|
| 700 |
+
- type: recall_at_1
|
| 701 |
+
value: 14.6
|
| 702 |
+
- type: recall_at_10
|
| 703 |
+
value: 27.200000000000003
|
| 704 |
+
- type: recall_at_100
|
| 705 |
+
value: 41.4
|
| 706 |
+
- type: recall_at_1000
|
| 707 |
+
value: 60.0
|
| 708 |
+
- type: recall_at_3
|
| 709 |
+
value: 20.5
|
| 710 |
+
- type: recall_at_5
|
| 711 |
+
value: 22.8
|
| 712 |
+
- task:
|
| 713 |
+
type: Classification
|
| 714 |
+
dataset:
|
| 715 |
+
type: C-MTEB/MultilingualSentiment-classification
|
| 716 |
+
name: MTEB MultilingualSentiment
|
| 717 |
+
config: default
|
| 718 |
+
split: validation
|
| 719 |
+
revision: None
|
| 720 |
+
metrics:
|
| 721 |
+
- type: accuracy
|
| 722 |
+
value: 66.58333333333333
|
| 723 |
+
- type: f1
|
| 724 |
+
value: 66.26700927460007
|
| 725 |
+
- task:
|
| 726 |
+
type: PairClassification
|
| 727 |
+
dataset:
|
| 728 |
+
type: C-MTEB/OCNLI
|
| 729 |
+
name: MTEB Ocnli
|
| 730 |
+
config: default
|
| 731 |
+
split: validation
|
| 732 |
+
revision: None
|
| 733 |
+
metrics:
|
| 734 |
+
- type: cos_sim_accuracy
|
| 735 |
+
value: 72.00866269626421
|
| 736 |
+
- type: cos_sim_ap
|
| 737 |
+
value: 77.00520104243304
|
| 738 |
+
- type: cos_sim_f1
|
| 739 |
+
value: 74.39303710490151
|
| 740 |
+
- type: cos_sim_precision
|
| 741 |
+
value: 65.69579288025889
|
| 742 |
+
- type: cos_sim_recall
|
| 743 |
+
value: 85.74445617740233
|
| 744 |
+
- type: dot_accuracy
|
| 745 |
+
value: 72.00866269626421
|
| 746 |
+
- type: dot_ap
|
| 747 |
+
value: 77.00520104243304
|
| 748 |
+
- type: dot_f1
|
| 749 |
+
value: 74.39303710490151
|
| 750 |
+
- type: dot_precision
|
| 751 |
+
value: 65.69579288025889
|
| 752 |
+
- type: dot_recall
|
| 753 |
+
value: 85.74445617740233
|
| 754 |
+
- type: euclidean_accuracy
|
| 755 |
+
value: 72.00866269626421
|
| 756 |
+
- type: euclidean_ap
|
| 757 |
+
value: 77.00520104243304
|
| 758 |
+
- type: euclidean_f1
|
| 759 |
+
value: 74.39303710490151
|
| 760 |
+
- type: euclidean_precision
|
| 761 |
+
value: 65.69579288025889
|
| 762 |
+
- type: euclidean_recall
|
| 763 |
+
value: 85.74445617740233
|
| 764 |
+
- type: manhattan_accuracy
|
| 765 |
+
value: 72.1710882512182
|
| 766 |
+
- type: manhattan_ap
|
| 767 |
+
value: 77.00551017913976
|
| 768 |
+
- type: manhattan_f1
|
| 769 |
+
value: 74.23423423423424
|
| 770 |
+
- type: manhattan_precision
|
| 771 |
+
value: 64.72898664571878
|
| 772 |
+
- type: manhattan_recall
|
| 773 |
+
value: 87.0116156282999
|
| 774 |
+
- type: max_accuracy
|
| 775 |
+
value: 72.1710882512182
|
| 776 |
+
- type: max_ap
|
| 777 |
+
value: 77.00551017913976
|
| 778 |
+
- type: max_f1
|
| 779 |
+
value: 74.39303710490151
|
| 780 |
+
- task:
|
| 781 |
+
type: Classification
|
| 782 |
+
dataset:
|
| 783 |
+
type: C-MTEB/OnlineShopping-classification
|
| 784 |
+
name: MTEB OnlineShopping
|
| 785 |
+
config: default
|
| 786 |
+
split: test
|
| 787 |
+
revision: None
|
| 788 |
+
metrics:
|
| 789 |
+
- type: accuracy
|
| 790 |
+
value: 88.19000000000001
|
| 791 |
+
- type: ap
|
| 792 |
+
value: 85.13415594781077
|
| 793 |
+
- type: f1
|
| 794 |
+
value: 88.17344156114062
|
| 795 |
+
- task:
|
| 796 |
+
type: STS
|
| 797 |
+
dataset:
|
| 798 |
+
type: C-MTEB/PAWSX
|
| 799 |
+
name: MTEB PAWSX
|
| 800 |
+
config: default
|
| 801 |
+
split: test
|
| 802 |
+
revision: None
|
| 803 |
+
metrics:
|
| 804 |
+
- type: cos_sim_pearson
|
| 805 |
+
value: 13.70522140998517
|
| 806 |
+
- type: cos_sim_spearman
|
| 807 |
+
value: 15.07546667334743
|
| 808 |
+
- type: euclidean_pearson
|
| 809 |
+
value: 17.49511420225285
|
| 810 |
+
- type: euclidean_spearman
|
| 811 |
+
value: 15.093970931789618
|
| 812 |
+
- type: manhattan_pearson
|
| 813 |
+
value: 17.44069961390521
|
| 814 |
+
- type: manhattan_spearman
|
| 815 |
+
value: 15.076029291596962
|
| 816 |
+
- task:
|
| 817 |
+
type: STS
|
| 818 |
+
dataset:
|
| 819 |
+
type: C-MTEB/QBQTC
|
| 820 |
+
name: MTEB QBQTC
|
| 821 |
+
config: default
|
| 822 |
+
split: test
|
| 823 |
+
revision: None
|
| 824 |
+
metrics:
|
| 825 |
+
- type: cos_sim_pearson
|
| 826 |
+
value: 26.835294224547155
|
| 827 |
+
- type: cos_sim_spearman
|
| 828 |
+
value: 27.920204597498856
|
| 829 |
+
- type: euclidean_pearson
|
| 830 |
+
value: 26.153796707702803
|
| 831 |
+
- type: euclidean_spearman
|
| 832 |
+
value: 27.920971379720548
|
| 833 |
+
- type: manhattan_pearson
|
| 834 |
+
value: 26.21954147857523
|
| 835 |
+
- type: manhattan_spearman
|
| 836 |
+
value: 27.996860049937478
|
| 837 |
+
- task:
|
| 838 |
+
type: STS
|
| 839 |
+
dataset:
|
| 840 |
+
type: mteb/sts22-crosslingual-sts
|
| 841 |
+
name: MTEB STS22 (zh)
|
| 842 |
+
config: zh
|
| 843 |
+
split: test
|
| 844 |
+
revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80
|
| 845 |
+
metrics:
|
| 846 |
+
- type: cos_sim_pearson
|
| 847 |
+
value: 55.15901259718581
|
| 848 |
+
- type: cos_sim_spearman
|
| 849 |
+
value: 61.57967880874167
|
| 850 |
+
- type: euclidean_pearson
|
| 851 |
+
value: 53.83523291596683
|
| 852 |
+
- type: euclidean_spearman
|
| 853 |
+
value: 61.57967880874167
|
| 854 |
+
- type: manhattan_pearson
|
| 855 |
+
value: 54.99971428907956
|
| 856 |
+
- type: manhattan_spearman
|
| 857 |
+
value: 61.61229543613867
|
| 858 |
+
- task:
|
| 859 |
+
type: STS
|
| 860 |
+
dataset:
|
| 861 |
+
type: mteb/sts22-crosslingual-sts
|
| 862 |
+
name: MTEB STS22 (zh-en)
|
| 863 |
+
config: zh-en
|
| 864 |
+
split: test
|
| 865 |
+
revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80
|
| 866 |
+
metrics:
|
| 867 |
+
- type: cos_sim_pearson
|
| 868 |
+
value: 34.20930208460845
|
| 869 |
+
- type: cos_sim_spearman
|
| 870 |
+
value: 33.879011104224524
|
| 871 |
+
- type: euclidean_pearson
|
| 872 |
+
value: 35.08526425284862
|
| 873 |
+
- type: euclidean_spearman
|
| 874 |
+
value: 33.879011104224524
|
| 875 |
+
- type: manhattan_pearson
|
| 876 |
+
value: 35.509419089701275
|
| 877 |
+
- type: manhattan_spearman
|
| 878 |
+
value: 33.30035487147621
|
| 879 |
+
- task:
|
| 880 |
+
type: STS
|
| 881 |
+
dataset:
|
| 882 |
+
type: C-MTEB/STSB
|
| 883 |
+
name: MTEB STSB
|
| 884 |
+
config: default
|
| 885 |
+
split: test
|
| 886 |
+
revision: None
|
| 887 |
+
metrics:
|
| 888 |
+
- type: cos_sim_pearson
|
| 889 |
+
value: 82.30068282185835
|
| 890 |
+
- type: cos_sim_spearman
|
| 891 |
+
value: 82.16763221361724
|
| 892 |
+
- type: euclidean_pearson
|
| 893 |
+
value: 80.52772752433374
|
| 894 |
+
- type: euclidean_spearman
|
| 895 |
+
value: 82.16797037220333
|
| 896 |
+
- type: manhattan_pearson
|
| 897 |
+
value: 80.51093859500105
|
| 898 |
+
- type: manhattan_spearman
|
| 899 |
+
value: 82.17643310049654
|
| 900 |
+
- task:
|
| 901 |
+
type: Reranking
|
| 902 |
+
dataset:
|
| 903 |
+
type: C-MTEB/T2Reranking
|
| 904 |
+
name: MTEB T2Reranking
|
| 905 |
+
config: default
|
| 906 |
+
split: dev
|
| 907 |
+
revision: None
|
| 908 |
+
metrics:
|
| 909 |
+
- type: map
|
| 910 |
+
value: 65.14113035189213
|
| 911 |
+
- type: mrr
|
| 912 |
+
value: 74.9589270937443
|
| 913 |
+
- task:
|
| 914 |
+
type: Retrieval
|
| 915 |
+
dataset:
|
| 916 |
+
type: C-MTEB/T2Retrieval
|
| 917 |
+
name: MTEB T2Retrieval
|
| 918 |
+
config: default
|
| 919 |
+
split: dev
|
| 920 |
+
revision: None
|
| 921 |
+
metrics:
|
| 922 |
+
- type: map_at_1
|
| 923 |
+
value: 12.013
|
| 924 |
+
- type: map_at_10
|
| 925 |
+
value: 30.885
|
| 926 |
+
- type: map_at_100
|
| 927 |
+
value: 34.643
|
| 928 |
+
- type: map_at_1000
|
| 929 |
+
value: 34.927
|
| 930 |
+
- type: map_at_3
|
| 931 |
+
value: 21.901
|
| 932 |
+
- type: map_at_5
|
| 933 |
+
value: 26.467000000000002
|
| 934 |
+
- type: mrr_at_1
|
| 935 |
+
value: 49.623
|
| 936 |
+
- type: mrr_at_10
|
| 937 |
+
value: 58.05200000000001
|
| 938 |
+
- type: mrr_at_100
|
| 939 |
+
value: 58.61300000000001
|
| 940 |
+
- type: mrr_at_1000
|
| 941 |
+
value: 58.643
|
| 942 |
+
- type: mrr_at_3
|
| 943 |
+
value: 55.947
|
| 944 |
+
- type: mrr_at_5
|
| 945 |
+
value: 57.229
|
| 946 |
+
- type: ndcg_at_1
|
| 947 |
+
value: 49.623
|
| 948 |
+
- type: ndcg_at_10
|
| 949 |
+
value: 41.802
|
| 950 |
+
- type: ndcg_at_100
|
| 951 |
+
value: 49.975
|
| 952 |
+
- type: ndcg_at_1000
|
| 953 |
+
value: 53.504
|
| 954 |
+
- type: ndcg_at_3
|
| 955 |
+
value: 43.515
|
| 956 |
+
- type: ndcg_at_5
|
| 957 |
+
value: 41.576
|
| 958 |
+
- type: precision_at_1
|
| 959 |
+
value: 49.623
|
| 960 |
+
- type: precision_at_10
|
| 961 |
+
value: 22.052
|
| 962 |
+
- type: precision_at_100
|
| 963 |
+
value: 3.6450000000000005
|
| 964 |
+
- type: precision_at_1000
|
| 965 |
+
value: 0.45399999999999996
|
| 966 |
+
- type: precision_at_3
|
| 967 |
+
value: 38.616
|
| 968 |
+
- type: precision_at_5
|
| 969 |
+
value: 31.966
|
| 970 |
+
- type: recall_at_1
|
| 971 |
+
value: 12.013
|
| 972 |
+
- type: recall_at_10
|
| 973 |
+
value: 41.891
|
| 974 |
+
- type: recall_at_100
|
| 975 |
+
value: 67.096
|
| 976 |
+
- type: recall_at_1000
|
| 977 |
+
value: 84.756
|
| 978 |
+
- type: recall_at_3
|
| 979 |
+
value: 24.695
|
| 980 |
+
- type: recall_at_5
|
| 981 |
+
value: 32.09
|
| 982 |
+
- task:
|
| 983 |
+
type: Classification
|
| 984 |
+
dataset:
|
| 985 |
+
type: C-MTEB/TNews-classification
|
| 986 |
+
name: MTEB TNews
|
| 987 |
+
config: default
|
| 988 |
+
split: validation
|
| 989 |
+
revision: None
|
| 990 |
+
metrics:
|
| 991 |
+
- type: accuracy
|
| 992 |
+
value: 39.800999999999995
|
| 993 |
+
- type: f1
|
| 994 |
+
value: 38.5345899934575
|
| 995 |
+
- task:
|
| 996 |
+
type: Clustering
|
| 997 |
+
dataset:
|
| 998 |
+
type: C-MTEB/ThuNewsClusteringP2P
|
| 999 |
+
name: MTEB ThuNewsClusteringP2P
|
| 1000 |
+
config: default
|
| 1001 |
+
split: test
|
| 1002 |
+
revision: None
|
| 1003 |
+
metrics:
|
| 1004 |
+
- type: v_measure
|
| 1005 |
+
value: 40.16574242797479
|
| 1006 |
+
- task:
|
| 1007 |
+
type: Clustering
|
| 1008 |
+
dataset:
|
| 1009 |
+
type: C-MTEB/ThuNewsClusteringS2S
|
| 1010 |
+
name: MTEB ThuNewsClusteringS2S
|
| 1011 |
+
config: default
|
| 1012 |
+
split: test
|
| 1013 |
+
revision: None
|
| 1014 |
+
metrics:
|
| 1015 |
+
- type: v_measure
|
| 1016 |
+
value: 24.232617974671754
|
| 1017 |
+
- task:
|
| 1018 |
+
type: Retrieval
|
| 1019 |
+
dataset:
|
| 1020 |
+
type: C-MTEB/VideoRetrieval
|
| 1021 |
+
name: MTEB VideoRetrieval
|
| 1022 |
+
config: default
|
| 1023 |
+
split: dev
|
| 1024 |
+
revision: None
|
| 1025 |
+
metrics:
|
| 1026 |
+
- type: map_at_1
|
| 1027 |
+
value: 24.6
|
| 1028 |
+
- type: map_at_10
|
| 1029 |
+
value: 31.328
|
| 1030 |
+
- type: map_at_100
|
| 1031 |
+
value: 32.088
|
| 1032 |
+
- type: map_at_1000
|
| 1033 |
+
value: 32.164
|
| 1034 |
+
- type: map_at_3
|
| 1035 |
+
value: 29.133
|
| 1036 |
+
- type: map_at_5
|
| 1037 |
+
value: 30.358
|
| 1038 |
+
- type: mrr_at_1
|
| 1039 |
+
value: 24.6
|
| 1040 |
+
- type: mrr_at_10
|
| 1041 |
+
value: 31.328
|
| 1042 |
+
- type: mrr_at_100
|
| 1043 |
+
value: 32.088
|
| 1044 |
+
- type: mrr_at_1000
|
| 1045 |
+
value: 32.164
|
| 1046 |
+
- type: mrr_at_3
|
| 1047 |
+
value: 29.133
|
| 1048 |
+
- type: mrr_at_5
|
| 1049 |
+
value: 30.358
|
| 1050 |
+
- type: ndcg_at_1
|
| 1051 |
+
value: 24.6
|
| 1052 |
+
- type: ndcg_at_10
|
| 1053 |
+
value: 35.150999999999996
|
| 1054 |
+
- type: ndcg_at_100
|
| 1055 |
+
value: 39.024
|
| 1056 |
+
- type: ndcg_at_1000
|
| 1057 |
+
value: 41.157
|
| 1058 |
+
- type: ndcg_at_3
|
| 1059 |
+
value: 30.637999999999998
|
| 1060 |
+
- type: ndcg_at_5
|
| 1061 |
+
value: 32.833
|
| 1062 |
+
- type: precision_at_1
|
| 1063 |
+
value: 24.6
|
| 1064 |
+
- type: precision_at_10
|
| 1065 |
+
value: 4.74
|
| 1066 |
+
- type: precision_at_100
|
| 1067 |
+
value: 0.66
|
| 1068 |
+
- type: precision_at_1000
|
| 1069 |
+
value: 0.083
|
| 1070 |
+
- type: precision_at_3
|
| 1071 |
+
value: 11.667
|
| 1072 |
+
- type: precision_at_5
|
| 1073 |
+
value: 8.06
|
| 1074 |
+
- type: recall_at_1
|
| 1075 |
+
value: 24.6
|
| 1076 |
+
- type: recall_at_10
|
| 1077 |
+
value: 47.4
|
| 1078 |
+
- type: recall_at_100
|
| 1079 |
+
value: 66.0
|
| 1080 |
+
- type: recall_at_1000
|
| 1081 |
+
value: 83.0
|
| 1082 |
+
- type: recall_at_3
|
| 1083 |
+
value: 35.0
|
| 1084 |
+
- type: recall_at_5
|
| 1085 |
+
value: 40.300000000000004
|
| 1086 |
+
- task:
|
| 1087 |
+
type: Classification
|
| 1088 |
+
dataset:
|
| 1089 |
+
type: C-MTEB/waimai-classification
|
| 1090 |
+
name: MTEB Waimai
|
| 1091 |
+
config: default
|
| 1092 |
+
split: test
|
| 1093 |
+
revision: None
|
| 1094 |
+
metrics:
|
| 1095 |
+
- type: accuracy
|
| 1096 |
+
value: 83.96000000000001
|
| 1097 |
+
- type: ap
|
| 1098 |
+
value: 65.11027167433211
|
| 1099 |
+
- type: f1
|
| 1100 |
+
value: 82.03549710974653
|
| 1101 |
---
|
| 1102 |
|
| 1103 |
# DMetaSoul/sbert-chinese-general-v1
|