Update README.md
Browse files
README.md
CHANGED
@@ -2,12 +2,1711 @@
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pipeline_tag: sentence-similarity
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tags:
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- finetuner
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- feature-extraction
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- sentence-similarity
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datasets:
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- jinaai/negation-dataset
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language: en
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license: apache-2.0
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|
11 |
---
|
12 |
|
13 |
<br><br>
|
|
|
2 |
pipeline_tag: sentence-similarity
|
3 |
tags:
|
4 |
- finetuner
|
5 |
+
- mteb
|
6 |
- feature-extraction
|
7 |
- sentence-similarity
|
8 |
datasets:
|
9 |
- jinaai/negation-dataset
|
10 |
language: en
|
11 |
license: apache-2.0
|
12 |
+
model-index:
|
13 |
+
- name: jina-embedding-l-en-v1
|
14 |
+
results:
|
15 |
+
- task:
|
16 |
+
type: Classification
|
17 |
+
dataset:
|
18 |
+
type: mteb/amazon_counterfactual
|
19 |
+
name: MTEB AmazonCounterfactualClassification (en)
|
20 |
+
config: en
|
21 |
+
split: test
|
22 |
+
revision: e8379541af4e31359cca9fbcf4b00f2671dba205
|
23 |
+
metrics:
|
24 |
+
- type: accuracy
|
25 |
+
value: 61.64179104477612
|
26 |
+
- type: ap
|
27 |
+
value: 24.63675721041911
|
28 |
+
- type: f1
|
29 |
+
value: 55.10036810049116
|
30 |
+
- task:
|
31 |
+
type: Classification
|
32 |
+
dataset:
|
33 |
+
type: mteb/amazon_polarity
|
34 |
+
name: MTEB AmazonPolarityClassification
|
35 |
+
config: default
|
36 |
+
split: test
|
37 |
+
revision: e2d317d38cd51312af73b3d32a06d1a08b442046
|
38 |
+
metrics:
|
39 |
+
- type: accuracy
|
40 |
+
value: 60.708125
|
41 |
+
- type: ap
|
42 |
+
value: 57.491681452557344
|
43 |
+
- type: f1
|
44 |
+
value: 58.046023443205655
|
45 |
+
- task:
|
46 |
+
type: Classification
|
47 |
+
dataset:
|
48 |
+
type: mteb/amazon_reviews_multi
|
49 |
+
name: MTEB AmazonReviewsClassification (en)
|
50 |
+
config: en
|
51 |
+
split: test
|
52 |
+
revision: 1399c76144fd37290681b995c656ef9b2e06e26d
|
53 |
+
metrics:
|
54 |
+
- type: accuracy
|
55 |
+
value: 28.12
|
56 |
+
- type: f1
|
57 |
+
value: 26.904734434317966
|
58 |
+
- task:
|
59 |
+
type: Retrieval
|
60 |
+
dataset:
|
61 |
+
type: arguana
|
62 |
+
name: MTEB ArguAna
|
63 |
+
config: default
|
64 |
+
split: test
|
65 |
+
revision: None
|
66 |
+
metrics:
|
67 |
+
- type: map_at_1
|
68 |
+
value: 26.031
|
69 |
+
- type: map_at_10
|
70 |
+
value: 40.742
|
71 |
+
- type: map_at_100
|
72 |
+
value: 41.832
|
73 |
+
- type: map_at_1000
|
74 |
+
value: 41.844
|
75 |
+
- type: map_at_3
|
76 |
+
value: 35.526
|
77 |
+
- type: map_at_5
|
78 |
+
value: 38.567
|
79 |
+
- type: mrr_at_1
|
80 |
+
value: 26.316
|
81 |
+
- type: mrr_at_10
|
82 |
+
value: 40.855999999999995
|
83 |
+
- type: mrr_at_100
|
84 |
+
value: 41.946
|
85 |
+
- type: mrr_at_1000
|
86 |
+
value: 41.957
|
87 |
+
- type: mrr_at_3
|
88 |
+
value: 35.621
|
89 |
+
- type: mrr_at_5
|
90 |
+
value: 38.644
|
91 |
+
- type: ndcg_at_1
|
92 |
+
value: 26.031
|
93 |
+
- type: ndcg_at_10
|
94 |
+
value: 49.483
|
95 |
+
- type: ndcg_at_100
|
96 |
+
value: 54.074999999999996
|
97 |
+
- type: ndcg_at_1000
|
98 |
+
value: 54.344
|
99 |
+
- type: ndcg_at_3
|
100 |
+
value: 38.792
|
101 |
+
- type: ndcg_at_5
|
102 |
+
value: 44.24
|
103 |
+
- type: precision_at_1
|
104 |
+
value: 26.031
|
105 |
+
- type: precision_at_10
|
106 |
+
value: 7.76
|
107 |
+
- type: precision_at_100
|
108 |
+
value: 0.975
|
109 |
+
- type: precision_at_1000
|
110 |
+
value: 0.1
|
111 |
+
- type: precision_at_3
|
112 |
+
value: 16.098000000000003
|
113 |
+
- type: precision_at_5
|
114 |
+
value: 12.29
|
115 |
+
- type: recall_at_1
|
116 |
+
value: 26.031
|
117 |
+
- type: recall_at_10
|
118 |
+
value: 77.596
|
119 |
+
- type: recall_at_100
|
120 |
+
value: 97.51100000000001
|
121 |
+
- type: recall_at_1000
|
122 |
+
value: 99.57300000000001
|
123 |
+
- type: recall_at_3
|
124 |
+
value: 48.293
|
125 |
+
- type: recall_at_5
|
126 |
+
value: 61.451
|
127 |
+
- task:
|
128 |
+
type: Clustering
|
129 |
+
dataset:
|
130 |
+
type: mteb/arxiv-clustering-p2p
|
131 |
+
name: MTEB ArxivClusteringP2P
|
132 |
+
config: default
|
133 |
+
split: test
|
134 |
+
revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
|
135 |
+
metrics:
|
136 |
+
- type: v_measure
|
137 |
+
value: 41.76036539849672
|
138 |
+
- task:
|
139 |
+
type: Clustering
|
140 |
+
dataset:
|
141 |
+
type: mteb/arxiv-clustering-s2s
|
142 |
+
name: MTEB ArxivClusteringS2S
|
143 |
+
config: default
|
144 |
+
split: test
|
145 |
+
revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
|
146 |
+
metrics:
|
147 |
+
- type: v_measure
|
148 |
+
value: 34.27585676831497
|
149 |
+
- task:
|
150 |
+
type: Reranking
|
151 |
+
dataset:
|
152 |
+
type: mteb/askubuntudupquestions-reranking
|
153 |
+
name: MTEB AskUbuntuDupQuestions
|
154 |
+
config: default
|
155 |
+
split: test
|
156 |
+
revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
|
157 |
+
metrics:
|
158 |
+
- type: map
|
159 |
+
value: 63.47328704612227
|
160 |
+
- type: mrr
|
161 |
+
value: 76.63182078002022
|
162 |
+
- task:
|
163 |
+
type: STS
|
164 |
+
dataset:
|
165 |
+
type: mteb/biosses-sts
|
166 |
+
name: MTEB BIOSSES
|
167 |
+
config: default
|
168 |
+
split: test
|
169 |
+
revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
|
170 |
+
metrics:
|
171 |
+
- type: cos_sim_pearson
|
172 |
+
value: 87.42072640664271
|
173 |
+
- type: cos_sim_spearman
|
174 |
+
value: 84.31336692039407
|
175 |
+
- type: euclidean_pearson
|
176 |
+
value: 54.93250871487246
|
177 |
+
- type: euclidean_spearman
|
178 |
+
value: 55.91091252228738
|
179 |
+
- type: manhattan_pearson
|
180 |
+
value: 54.78812442894107
|
181 |
+
- type: manhattan_spearman
|
182 |
+
value: 55.35005636930548
|
183 |
+
- task:
|
184 |
+
type: Classification
|
185 |
+
dataset:
|
186 |
+
type: mteb/banking77
|
187 |
+
name: MTEB Banking77Classification
|
188 |
+
config: default
|
189 |
+
split: test
|
190 |
+
revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
|
191 |
+
metrics:
|
192 |
+
- type: accuracy
|
193 |
+
value: 86.28896103896103
|
194 |
+
- type: f1
|
195 |
+
value: 86.23389676482913
|
196 |
+
- task:
|
197 |
+
type: Clustering
|
198 |
+
dataset:
|
199 |
+
type: mteb/biorxiv-clustering-p2p
|
200 |
+
name: MTEB BiorxivClusteringP2P
|
201 |
+
config: default
|
202 |
+
split: test
|
203 |
+
revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
|
204 |
+
metrics:
|
205 |
+
- type: v_measure
|
206 |
+
value: 33.73729294301578
|
207 |
+
- task:
|
208 |
+
type: Clustering
|
209 |
+
dataset:
|
210 |
+
type: mteb/biorxiv-clustering-s2s
|
211 |
+
name: MTEB BiorxivClusteringS2S
|
212 |
+
config: default
|
213 |
+
split: test
|
214 |
+
revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
|
215 |
+
metrics:
|
216 |
+
- type: v_measure
|
217 |
+
value: 30.641078215958288
|
218 |
+
- task:
|
219 |
+
type: Retrieval
|
220 |
+
dataset:
|
221 |
+
type: climate-fever
|
222 |
+
name: MTEB ClimateFEVER
|
223 |
+
config: default
|
224 |
+
split: test
|
225 |
+
revision: None
|
226 |
+
metrics:
|
227 |
+
- type: map_at_1
|
228 |
+
value: 8.258000000000001
|
229 |
+
- type: map_at_10
|
230 |
+
value: 14.57
|
231 |
+
- type: map_at_100
|
232 |
+
value: 15.98
|
233 |
+
- type: map_at_1000
|
234 |
+
value: 16.149
|
235 |
+
- type: map_at_3
|
236 |
+
value: 11.993
|
237 |
+
- type: map_at_5
|
238 |
+
value: 13.383000000000001
|
239 |
+
- type: mrr_at_1
|
240 |
+
value: 18.176000000000002
|
241 |
+
- type: mrr_at_10
|
242 |
+
value: 28.560000000000002
|
243 |
+
- type: mrr_at_100
|
244 |
+
value: 29.656
|
245 |
+
- type: mrr_at_1000
|
246 |
+
value: 29.709999999999997
|
247 |
+
- type: mrr_at_3
|
248 |
+
value: 25.255
|
249 |
+
- type: mrr_at_5
|
250 |
+
value: 27.128000000000004
|
251 |
+
- type: ndcg_at_1
|
252 |
+
value: 18.176000000000002
|
253 |
+
- type: ndcg_at_10
|
254 |
+
value: 21.36
|
255 |
+
- type: ndcg_at_100
|
256 |
+
value: 27.619
|
257 |
+
- type: ndcg_at_1000
|
258 |
+
value: 31.086000000000002
|
259 |
+
- type: ndcg_at_3
|
260 |
+
value: 16.701
|
261 |
+
- type: ndcg_at_5
|
262 |
+
value: 18.559
|
263 |
+
- type: precision_at_1
|
264 |
+
value: 18.176000000000002
|
265 |
+
- type: precision_at_10
|
266 |
+
value: 6.683999999999999
|
267 |
+
- type: precision_at_100
|
268 |
+
value: 1.3339999999999999
|
269 |
+
- type: precision_at_1000
|
270 |
+
value: 0.197
|
271 |
+
- type: precision_at_3
|
272 |
+
value: 12.269
|
273 |
+
- type: precision_at_5
|
274 |
+
value: 9.798
|
275 |
+
- type: recall_at_1
|
276 |
+
value: 8.258000000000001
|
277 |
+
- type: recall_at_10
|
278 |
+
value: 27.060000000000002
|
279 |
+
- type: recall_at_100
|
280 |
+
value: 48.833
|
281 |
+
- type: recall_at_1000
|
282 |
+
value: 68.636
|
283 |
+
- type: recall_at_3
|
284 |
+
value: 15.895999999999999
|
285 |
+
- type: recall_at_5
|
286 |
+
value: 20.625
|
287 |
+
- task:
|
288 |
+
type: Retrieval
|
289 |
+
dataset:
|
290 |
+
type: dbpedia-entity
|
291 |
+
name: MTEB DBPedia
|
292 |
+
config: default
|
293 |
+
split: test
|
294 |
+
revision: None
|
295 |
+
metrics:
|
296 |
+
- type: map_at_1
|
297 |
+
value: 8.241
|
298 |
+
- type: map_at_10
|
299 |
+
value: 17.141000000000002
|
300 |
+
- type: map_at_100
|
301 |
+
value: 22.805
|
302 |
+
- type: map_at_1000
|
303 |
+
value: 24.189
|
304 |
+
- type: map_at_3
|
305 |
+
value: 12.940999999999999
|
306 |
+
- type: map_at_5
|
307 |
+
value: 14.607000000000001
|
308 |
+
- type: mrr_at_1
|
309 |
+
value: 62.25000000000001
|
310 |
+
- type: mrr_at_10
|
311 |
+
value: 70.537
|
312 |
+
- type: mrr_at_100
|
313 |
+
value: 70.851
|
314 |
+
- type: mrr_at_1000
|
315 |
+
value: 70.875
|
316 |
+
- type: mrr_at_3
|
317 |
+
value: 68.75
|
318 |
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- type: mrr_at_5
|
319 |
+
value: 69.77499999999999
|
320 |
+
- type: ndcg_at_1
|
321 |
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value: 50.125
|
322 |
+
- type: ndcg_at_10
|
323 |
+
value: 36.032
|
324 |
+
- type: ndcg_at_100
|
325 |
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value: 39.428999999999995
|
326 |
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- type: ndcg_at_1000
|
327 |
+
value: 47.138999999999996
|
328 |
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- type: ndcg_at_3
|
329 |
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value: 40.99
|
330 |
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- type: ndcg_at_5
|
331 |
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value: 37.772
|
332 |
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- type: precision_at_1
|
333 |
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value: 62.25000000000001
|
334 |
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- type: precision_at_10
|
335 |
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value: 28.050000000000004
|
336 |
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- type: precision_at_100
|
337 |
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value: 8.527999999999999
|
338 |
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- type: precision_at_1000
|
339 |
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value: 1.82
|
340 |
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- type: precision_at_3
|
341 |
+
value: 45.0
|
342 |
+
- type: precision_at_5
|
343 |
+
value: 36.0
|
344 |
+
- type: recall_at_1
|
345 |
+
value: 8.241
|
346 |
+
- type: recall_at_10
|
347 |
+
value: 22.583000000000002
|
348 |
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- type: recall_at_100
|
349 |
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value: 44.267
|
350 |
+
- type: recall_at_1000
|
351 |
+
value: 69.497
|
352 |
+
- type: recall_at_3
|
353 |
+
value: 14.326
|
354 |
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- type: recall_at_5
|
355 |
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value: 17.29
|
356 |
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- task:
|
357 |
+
type: Classification
|
358 |
+
dataset:
|
359 |
+
type: mteb/emotion
|
360 |
+
name: MTEB EmotionClassification
|
361 |
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config: default
|
362 |
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split: test
|
363 |
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revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
|
364 |
+
metrics:
|
365 |
+
- type: accuracy
|
366 |
+
value: 42.295
|
367 |
+
- type: f1
|
368 |
+
value: 38.32403088027173
|
369 |
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- task:
|
370 |
+
type: Retrieval
|
371 |
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dataset:
|
372 |
+
type: fever
|
373 |
+
name: MTEB FEVER
|
374 |
+
config: default
|
375 |
+
split: test
|
376 |
+
revision: None
|
377 |
+
metrics:
|
378 |
+
- type: map_at_1
|
379 |
+
value: 58.553
|
380 |
+
- type: map_at_10
|
381 |
+
value: 69.632
|
382 |
+
- type: map_at_100
|
383 |
+
value: 69.95400000000001
|
384 |
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- type: map_at_1000
|
385 |
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value: 69.968
|
386 |
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- type: map_at_3
|
387 |
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value: 67.656
|
388 |
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- type: map_at_5
|
389 |
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value: 68.86
|
390 |
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- type: mrr_at_1
|
391 |
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value: 63.156
|
392 |
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- type: mrr_at_10
|
393 |
+
value: 74.37700000000001
|
394 |
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- type: mrr_at_100
|
395 |
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value: 74.629
|
396 |
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- type: mrr_at_1000
|
397 |
+
value: 74.63300000000001
|
398 |
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- type: mrr_at_3
|
399 |
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value: 72.577
|
400 |
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- type: mrr_at_5
|
401 |
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value: 73.71
|
402 |
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- type: ndcg_at_1
|
403 |
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value: 63.156
|
404 |
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- type: ndcg_at_10
|
405 |
+
value: 75.345
|
406 |
+
- type: ndcg_at_100
|
407 |
+
value: 76.728
|
408 |
+
- type: ndcg_at_1000
|
409 |
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value: 77.006
|
410 |
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- type: ndcg_at_3
|
411 |
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value: 71.67099999999999
|
412 |
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- type: ndcg_at_5
|
413 |
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value: 73.656
|
414 |
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- type: precision_at_1
|
415 |
+
value: 63.156
|
416 |
+
- type: precision_at_10
|
417 |
+
value: 9.673
|
418 |
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- type: precision_at_100
|
419 |
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value: 1.045
|
420 |
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- type: precision_at_1000
|
421 |
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value: 0.108
|
422 |
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- type: precision_at_3
|
423 |
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value: 28.393
|
424 |
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- type: precision_at_5
|
425 |
+
value: 18.160999999999998
|
426 |
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- type: recall_at_1
|
427 |
+
value: 58.553
|
428 |
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- type: recall_at_10
|
429 |
+
value: 88.362
|
430 |
+
- type: recall_at_100
|
431 |
+
value: 94.401
|
432 |
+
- type: recall_at_1000
|
433 |
+
value: 96.256
|
434 |
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- type: recall_at_3
|
435 |
+
value: 78.371
|
436 |
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- type: recall_at_5
|
437 |
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value: 83.32300000000001
|
438 |
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- task:
|
439 |
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type: Retrieval
|
440 |
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dataset:
|
441 |
+
type: fiqa
|
442 |
+
name: MTEB FiQA2018
|
443 |
+
config: default
|
444 |
+
split: test
|
445 |
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revision: None
|
446 |
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metrics:
|
447 |
+
- type: map_at_1
|
448 |
+
value: 19.302
|
449 |
+
- type: map_at_10
|
450 |
+
value: 31.887
|
451 |
+
- type: map_at_100
|
452 |
+
value: 33.727000000000004
|
453 |
+
- type: map_at_1000
|
454 |
+
value: 33.914
|
455 |
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- type: map_at_3
|
456 |
+
value: 27.254
|
457 |
+
- type: map_at_5
|
458 |
+
value: 29.904999999999998
|
459 |
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- type: mrr_at_1
|
460 |
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value: 39.043
|
461 |
+
- type: mrr_at_10
|
462 |
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value: 47.858000000000004
|
463 |
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- type: mrr_at_100
|
464 |
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value: 48.636
|
465 |
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- type: mrr_at_1000
|
466 |
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value: 48.677
|
467 |
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- type: mrr_at_3
|
468 |
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value: 45.062000000000005
|
469 |
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- type: mrr_at_5
|
470 |
+
value: 46.775
|
471 |
+
- type: ndcg_at_1
|
472 |
+
value: 39.043
|
473 |
+
- type: ndcg_at_10
|
474 |
+
value: 39.899
|
475 |
+
- type: ndcg_at_100
|
476 |
+
value: 46.719
|
477 |
+
- type: ndcg_at_1000
|
478 |
+
value: 49.739
|
479 |
+
- type: ndcg_at_3
|
480 |
+
value: 35.666
|
481 |
+
- type: ndcg_at_5
|
482 |
+
value: 37.232
|
483 |
+
- type: precision_at_1
|
484 |
+
value: 39.043
|
485 |
+
- type: precision_at_10
|
486 |
+
value: 11.265
|
487 |
+
- type: precision_at_100
|
488 |
+
value: 1.864
|
489 |
+
- type: precision_at_1000
|
490 |
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value: 0.23800000000000002
|
491 |
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- type: precision_at_3
|
492 |
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value: 24.227999999999998
|
493 |
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- type: precision_at_5
|
494 |
+
value: 18.148
|
495 |
+
- type: recall_at_1
|
496 |
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value: 19.302
|
497 |
+
- type: recall_at_10
|
498 |
+
value: 47.278
|
499 |
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- type: recall_at_100
|
500 |
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value: 72.648
|
501 |
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- type: recall_at_1000
|
502 |
+
value: 90.793
|
503 |
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- type: recall_at_3
|
504 |
+
value: 31.235000000000003
|
505 |
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- type: recall_at_5
|
506 |
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value: 38.603
|
507 |
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- task:
|
508 |
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type: Retrieval
|
509 |
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dataset:
|
510 |
+
type: hotpotqa
|
511 |
+
name: MTEB HotpotQA
|
512 |
+
config: default
|
513 |
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split: test
|
514 |
+
revision: None
|
515 |
+
metrics:
|
516 |
+
- type: map_at_1
|
517 |
+
value: 31.398
|
518 |
+
- type: map_at_10
|
519 |
+
value: 44.635000000000005
|
520 |
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- type: map_at_100
|
521 |
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value: 45.513
|
522 |
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- type: map_at_1000
|
523 |
+
value: 45.595
|
524 |
+
- type: map_at_3
|
525 |
+
value: 41.894
|
526 |
+
- type: map_at_5
|
527 |
+
value: 43.514
|
528 |
+
- type: mrr_at_1
|
529 |
+
value: 62.795
|
530 |
+
- type: mrr_at_10
|
531 |
+
value: 70.001
|
532 |
+
- type: mrr_at_100
|
533 |
+
value: 70.378
|
534 |
+
- type: mrr_at_1000
|
535 |
+
value: 70.399
|
536 |
+
- type: mrr_at_3
|
537 |
+
value: 68.542
|
538 |
+
- type: mrr_at_5
|
539 |
+
value: 69.394
|
540 |
+
- type: ndcg_at_1
|
541 |
+
value: 62.795
|
542 |
+
- type: ndcg_at_10
|
543 |
+
value: 53.635
|
544 |
+
- type: ndcg_at_100
|
545 |
+
value: 57.05
|
546 |
+
- type: ndcg_at_1000
|
547 |
+
value: 58.755
|
548 |
+
- type: ndcg_at_3
|
549 |
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value: 49.267
|
550 |
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- type: ndcg_at_5
|
551 |
+
value: 51.522
|
552 |
+
- type: precision_at_1
|
553 |
+
value: 62.795
|
554 |
+
- type: precision_at_10
|
555 |
+
value: 11.196
|
556 |
+
- type: precision_at_100
|
557 |
+
value: 1.389
|
558 |
+
- type: precision_at_1000
|
559 |
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value: 0.16199999999999998
|
560 |
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- type: precision_at_3
|
561 |
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value: 30.804
|
562 |
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- type: precision_at_5
|
563 |
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value: 20.265
|
564 |
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- type: recall_at_1
|
565 |
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value: 31.398
|
566 |
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- type: recall_at_10
|
567 |
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value: 55.982
|
568 |
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- type: recall_at_100
|
569 |
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value: 69.453
|
570 |
+
- type: recall_at_1000
|
571 |
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value: 80.756
|
572 |
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- type: recall_at_3
|
573 |
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value: 46.205
|
574 |
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- type: recall_at_5
|
575 |
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value: 50.662
|
576 |
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- task:
|
577 |
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type: Classification
|
578 |
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dataset:
|
579 |
+
type: mteb/imdb
|
580 |
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name: MTEB ImdbClassification
|
581 |
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config: default
|
582 |
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split: test
|
583 |
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revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
|
584 |
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metrics:
|
585 |
+
- type: accuracy
|
586 |
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value: 63.803200000000004
|
587 |
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- type: ap
|
588 |
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value: 59.04397034963468
|
589 |
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- type: f1
|
590 |
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value: 63.4675375611795
|
591 |
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- task:
|
592 |
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type: Retrieval
|
593 |
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dataset:
|
594 |
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type: msmarco
|
595 |
+
name: MTEB MSMARCO
|
596 |
+
config: default
|
597 |
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split: dev
|
598 |
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revision: None
|
599 |
+
metrics:
|
600 |
+
- type: map_at_1
|
601 |
+
value: 17.671
|
602 |
+
- type: map_at_10
|
603 |
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value: 29.152
|
604 |
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- type: map_at_100
|
605 |
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value: 30.422
|
606 |
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- type: map_at_1000
|
607 |
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value: 30.481
|
608 |
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- type: map_at_3
|
609 |
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value: 25.417
|
610 |
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- type: map_at_5
|
611 |
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value: 27.448
|
612 |
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- type: mrr_at_1
|
613 |
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value: 18.195
|
614 |
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- type: mrr_at_10
|
615 |
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value: 29.67
|
616 |
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- type: mrr_at_100
|
617 |
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value: 30.891999999999996
|
618 |
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- type: mrr_at_1000
|
619 |
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value: 30.944
|
620 |
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- type: mrr_at_3
|
621 |
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value: 25.974000000000004
|
622 |
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- type: mrr_at_5
|
623 |
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value: 27.996
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624 |
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- type: ndcg_at_1
|
625 |
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value: 18.195
|
626 |
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- type: ndcg_at_10
|
627 |
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value: 35.795
|
628 |
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- type: ndcg_at_100
|
629 |
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value: 42.117
|
630 |
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- type: ndcg_at_1000
|
631 |
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value: 43.585
|
632 |
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- type: ndcg_at_3
|
633 |
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value: 28.122000000000003
|
634 |
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- type: ndcg_at_5
|
635 |
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value: 31.757
|
636 |
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- type: precision_at_1
|
637 |
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value: 18.195
|
638 |
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- type: precision_at_10
|
639 |
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value: 5.89
|
640 |
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- type: precision_at_100
|
641 |
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value: 0.9079999999999999
|
642 |
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- type: precision_at_1000
|
643 |
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value: 0.10300000000000001
|
644 |
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- type: precision_at_3
|
645 |
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value: 12.24
|
646 |
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- type: precision_at_5
|
647 |
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value: 9.178
|
648 |
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- type: recall_at_1
|
649 |
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value: 17.671
|
650 |
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- type: recall_at_10
|
651 |
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value: 56.373
|
652 |
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- type: recall_at_100
|
653 |
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value: 86.029
|
654 |
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- type: recall_at_1000
|
655 |
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value: 97.246
|
656 |
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- type: recall_at_3
|
657 |
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value: 35.414
|
658 |
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- type: recall_at_5
|
659 |
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value: 44.149
|
660 |
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- task:
|
661 |
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type: Classification
|
662 |
+
dataset:
|
663 |
+
type: mteb/mtop_domain
|
664 |
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name: MTEB MTOPDomainClassification (en)
|
665 |
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config: en
|
666 |
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split: test
|
667 |
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revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
|
668 |
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metrics:
|
669 |
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- type: accuracy
|
670 |
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value: 90.80255357957135
|
671 |
+
- type: f1
|
672 |
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value: 90.79256308087807
|
673 |
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- task:
|
674 |
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type: Classification
|
675 |
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dataset:
|
676 |
+
type: mteb/mtop_intent
|
677 |
+
name: MTEB MTOPIntentClassification (en)
|
678 |
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config: en
|
679 |
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split: test
|
680 |
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revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
|
681 |
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metrics:
|
682 |
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- type: accuracy
|
683 |
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value: 71.20611035111719
|
684 |
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- type: f1
|
685 |
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value: 54.075483897190836
|
686 |
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- task:
|
687 |
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type: Classification
|
688 |
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dataset:
|
689 |
+
type: mteb/amazon_massive_intent
|
690 |
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name: MTEB MassiveIntentClassification (en)
|
691 |
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config: en
|
692 |
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split: test
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693 |
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revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
|
694 |
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metrics:
|
695 |
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- type: accuracy
|
696 |
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value: 70.79354404841965
|
697 |
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- type: f1
|
698 |
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value: 68.53816551555609
|
699 |
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- task:
|
700 |
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type: Classification
|
701 |
+
dataset:
|
702 |
+
type: mteb/amazon_massive_scenario
|
703 |
+
name: MTEB MassiveScenarioClassification (en)
|
704 |
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config: en
|
705 |
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split: test
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706 |
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revision: 7d571f92784cd94a019292a1f45445077d0ef634
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707 |
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metrics:
|
708 |
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- type: accuracy
|
709 |
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value: 76.6072629455279
|
710 |
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- type: f1
|
711 |
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value: 77.04997715738867
|
712 |
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- task:
|
713 |
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type: Clustering
|
714 |
+
dataset:
|
715 |
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type: mteb/medrxiv-clustering-p2p
|
716 |
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name: MTEB MedrxivClusteringP2P
|
717 |
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config: default
|
718 |
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split: test
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719 |
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revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
|
720 |
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metrics:
|
721 |
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- type: v_measure
|
722 |
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value: 30.432745003633016
|
723 |
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- task:
|
724 |
+
type: Clustering
|
725 |
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dataset:
|
726 |
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type: mteb/medrxiv-clustering-s2s
|
727 |
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name: MTEB MedrxivClusteringS2S
|
728 |
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config: default
|
729 |
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split: test
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730 |
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revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
|
731 |
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metrics:
|
732 |
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- type: v_measure
|
733 |
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value: 28.95493811839366
|
734 |
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- task:
|
735 |
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type: Reranking
|
736 |
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dataset:
|
737 |
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type: mteb/mind_small
|
738 |
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name: MTEB MindSmallReranking
|
739 |
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config: default
|
740 |
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split: test
|
741 |
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revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
|
742 |
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metrics:
|
743 |
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- type: map
|
744 |
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value: 31.63516074152514
|
745 |
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- type: mrr
|
746 |
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value: 32.73091425241894
|
747 |
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- task:
|
748 |
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type: Retrieval
|
749 |
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dataset:
|
750 |
+
type: nfcorpus
|
751 |
+
name: MTEB NFCorpus
|
752 |
+
config: default
|
753 |
+
split: test
|
754 |
+
revision: None
|
755 |
+
metrics:
|
756 |
+
- type: map_at_1
|
757 |
+
value: 5.379
|
758 |
+
- type: map_at_10
|
759 |
+
value: 12.051
|
760 |
+
- type: map_at_100
|
761 |
+
value: 15.176
|
762 |
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- type: map_at_1000
|
763 |
+
value: 16.662
|
764 |
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- type: map_at_3
|
765 |
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value: 8.588
|
766 |
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- type: map_at_5
|
767 |
+
value: 10.274
|
768 |
+
- type: mrr_at_1
|
769 |
+
value: 44.891999999999996
|
770 |
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- type: mrr_at_10
|
771 |
+
value: 53.06999999999999
|
772 |
+
- type: mrr_at_100
|
773 |
+
value: 53.675
|
774 |
+
- type: mrr_at_1000
|
775 |
+
value: 53.717999999999996
|
776 |
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- type: mrr_at_3
|
777 |
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value: 50.671
|
778 |
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- type: mrr_at_5
|
779 |
+
value: 52.25
|
780 |
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- type: ndcg_at_1
|
781 |
+
value: 42.879
|
782 |
+
- type: ndcg_at_10
|
783 |
+
value: 33.291
|
784 |
+
- type: ndcg_at_100
|
785 |
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value: 30.567
|
786 |
+
- type: ndcg_at_1000
|
787 |
+
value: 39.598
|
788 |
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- type: ndcg_at_3
|
789 |
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value: 37.713
|
790 |
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- type: ndcg_at_5
|
791 |
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value: 36.185
|
792 |
+
- type: precision_at_1
|
793 |
+
value: 44.891999999999996
|
794 |
+
- type: precision_at_10
|
795 |
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value: 24.923000000000002
|
796 |
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- type: precision_at_100
|
797 |
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value: 8.015
|
798 |
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- type: precision_at_1000
|
799 |
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value: 2.083
|
800 |
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- type: precision_at_3
|
801 |
+
value: 35.088
|
802 |
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- type: precision_at_5
|
803 |
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value: 31.765
|
804 |
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- type: recall_at_1
|
805 |
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value: 5.379
|
806 |
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- type: recall_at_10
|
807 |
+
value: 16.346
|
808 |
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- type: recall_at_100
|
809 |
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value: 31.887999999999998
|
810 |
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- type: recall_at_1000
|
811 |
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value: 64.90599999999999
|
812 |
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- type: recall_at_3
|
813 |
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value: 9.543
|
814 |
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- type: recall_at_5
|
815 |
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value: 12.369
|
816 |
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- task:
|
817 |
+
type: Retrieval
|
818 |
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dataset:
|
819 |
+
type: nq
|
820 |
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name: MTEB NQ
|
821 |
+
config: default
|
822 |
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split: test
|
823 |
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revision: None
|
824 |
+
metrics:
|
825 |
+
- type: map_at_1
|
826 |
+
value: 25.654
|
827 |
+
- type: map_at_10
|
828 |
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value: 40.163
|
829 |
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- type: map_at_100
|
830 |
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value: 41.376000000000005
|
831 |
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- type: map_at_1000
|
832 |
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value: 41.411
|
833 |
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- type: map_at_3
|
834 |
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value: 35.677
|
835 |
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- type: map_at_5
|
836 |
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value: 38.238
|
837 |
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- type: mrr_at_1
|
838 |
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value: 29.055999999999997
|
839 |
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- type: mrr_at_10
|
840 |
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value: 42.571999999999996
|
841 |
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- type: mrr_at_100
|
842 |
+
value: 43.501
|
843 |
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- type: mrr_at_1000
|
844 |
+
value: 43.527
|
845 |
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- type: mrr_at_3
|
846 |
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value: 38.775
|
847 |
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- type: mrr_at_5
|
848 |
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value: 40.953
|
849 |
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- type: ndcg_at_1
|
850 |
+
value: 29.026999999999997
|
851 |
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- type: ndcg_at_10
|
852 |
+
value: 47.900999999999996
|
853 |
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- type: ndcg_at_100
|
854 |
+
value: 52.941
|
855 |
+
- type: ndcg_at_1000
|
856 |
+
value: 53.786
|
857 |
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- type: ndcg_at_3
|
858 |
+
value: 39.387
|
859 |
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- type: ndcg_at_5
|
860 |
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value: 43.65
|
861 |
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- type: precision_at_1
|
862 |
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value: 29.026999999999997
|
863 |
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- type: precision_at_10
|
864 |
+
value: 8.247
|
865 |
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- type: precision_at_100
|
866 |
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value: 1.102
|
867 |
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- type: precision_at_1000
|
868 |
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value: 0.11800000000000001
|
869 |
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- type: precision_at_3
|
870 |
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value: 18.231
|
871 |
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- type: precision_at_5
|
872 |
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value: 13.378
|
873 |
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- type: recall_at_1
|
874 |
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value: 25.654
|
875 |
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- type: recall_at_10
|
876 |
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value: 69.175
|
877 |
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- type: recall_at_100
|
878 |
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value: 90.85600000000001
|
879 |
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- type: recall_at_1000
|
880 |
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value: 97.18
|
881 |
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- type: recall_at_3
|
882 |
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value: 47.043
|
883 |
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- type: recall_at_5
|
884 |
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value: 56.86600000000001
|
885 |
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- task:
|
886 |
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type: Retrieval
|
887 |
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dataset:
|
888 |
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type: quora
|
889 |
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name: MTEB QuoraRetrieval
|
890 |
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config: default
|
891 |
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split: test
|
892 |
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revision: None
|
893 |
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metrics:
|
894 |
+
- type: map_at_1
|
895 |
+
value: 70.785
|
896 |
+
- type: map_at_10
|
897 |
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value: 84.509
|
898 |
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- type: map_at_100
|
899 |
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value: 85.17
|
900 |
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- type: map_at_1000
|
901 |
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value: 85.187
|
902 |
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- type: map_at_3
|
903 |
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value: 81.628
|
904 |
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- type: map_at_5
|
905 |
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value: 83.422
|
906 |
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- type: mrr_at_1
|
907 |
+
value: 81.43
|
908 |
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- type: mrr_at_10
|
909 |
+
value: 87.506
|
910 |
+
- type: mrr_at_100
|
911 |
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value: 87.616
|
912 |
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- type: mrr_at_1000
|
913 |
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value: 87.617
|
914 |
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- type: mrr_at_3
|
915 |
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value: 86.598
|
916 |
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- type: mrr_at_5
|
917 |
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value: 87.215
|
918 |
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- type: ndcg_at_1
|
919 |
+
value: 81.44
|
920 |
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- type: ndcg_at_10
|
921 |
+
value: 88.208
|
922 |
+
- type: ndcg_at_100
|
923 |
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value: 89.49000000000001
|
924 |
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- type: ndcg_at_1000
|
925 |
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value: 89.59700000000001
|
926 |
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- type: ndcg_at_3
|
927 |
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value: 85.471
|
928 |
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- type: ndcg_at_5
|
929 |
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value: 86.955
|
930 |
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- type: precision_at_1
|
931 |
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value: 81.44
|
932 |
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- type: precision_at_10
|
933 |
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value: 13.347000000000001
|
934 |
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- type: precision_at_100
|
935 |
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value: 1.53
|
936 |
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- type: precision_at_1000
|
937 |
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value: 0.157
|
938 |
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- type: precision_at_3
|
939 |
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value: 37.330000000000005
|
940 |
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- type: precision_at_5
|
941 |
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value: 24.506
|
942 |
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- type: recall_at_1
|
943 |
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value: 70.785
|
944 |
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- type: recall_at_10
|
945 |
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value: 95.15
|
946 |
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- type: recall_at_100
|
947 |
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value: 99.502
|
948 |
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- type: recall_at_1000
|
949 |
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value: 99.993
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950 |
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- type: recall_at_3
|
951 |
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value: 87.234
|
952 |
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- type: recall_at_5
|
953 |
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value: 91.467
|
954 |
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- task:
|
955 |
+
type: Clustering
|
956 |
+
dataset:
|
957 |
+
type: mteb/reddit-clustering
|
958 |
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name: MTEB RedditClustering
|
959 |
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config: default
|
960 |
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split: test
|
961 |
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revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
|
962 |
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metrics:
|
963 |
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- type: v_measure
|
964 |
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value: 52.40682777853522
|
965 |
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- task:
|
966 |
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type: Clustering
|
967 |
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dataset:
|
968 |
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type: mteb/reddit-clustering-p2p
|
969 |
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name: MTEB RedditClusteringP2P
|
970 |
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config: default
|
971 |
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split: test
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972 |
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revision: 282350215ef01743dc01b456c7f5241fa8937f16
|
973 |
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metrics:
|
974 |
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- type: v_measure
|
975 |
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value: 56.61834429208595
|
976 |
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- task:
|
977 |
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type: Retrieval
|
978 |
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dataset:
|
979 |
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type: scidocs
|
980 |
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name: MTEB SCIDOCS
|
981 |
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config: default
|
982 |
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split: test
|
983 |
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revision: None
|
984 |
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metrics:
|
985 |
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- type: map_at_1
|
986 |
+
value: 4.918
|
987 |
+
- type: map_at_10
|
988 |
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value: 11.562
|
989 |
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- type: map_at_100
|
990 |
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value: 13.636999999999999
|
991 |
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- type: map_at_1000
|
992 |
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value: 13.918
|
993 |
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- type: map_at_3
|
994 |
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value: 8.353
|
995 |
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- type: map_at_5
|
996 |
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value: 9.878
|
997 |
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- type: mrr_at_1
|
998 |
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value: 24.3
|
999 |
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- type: mrr_at_10
|
1000 |
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value: 33.914
|
1001 |
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- type: mrr_at_100
|
1002 |
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value: 35.079
|
1003 |
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- type: mrr_at_1000
|
1004 |
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value: 35.134
|
1005 |
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- type: mrr_at_3
|
1006 |
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value: 30.833
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1007 |
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- type: mrr_at_5
|
1008 |
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value: 32.528
|
1009 |
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- type: ndcg_at_1
|
1010 |
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value: 24.3
|
1011 |
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- type: ndcg_at_10
|
1012 |
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value: 19.393
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1013 |
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- type: ndcg_at_100
|
1014 |
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value: 27.471
|
1015 |
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- type: ndcg_at_1000
|
1016 |
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value: 32.543
|
1017 |
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- type: ndcg_at_3
|
1018 |
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value: 18.648
|
1019 |
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- type: ndcg_at_5
|
1020 |
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value: 16.064999999999998
|
1021 |
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- type: precision_at_1
|
1022 |
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value: 24.3
|
1023 |
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- type: precision_at_10
|
1024 |
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value: 9.92
|
1025 |
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- type: precision_at_100
|
1026 |
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value: 2.152
|
1027 |
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- type: precision_at_1000
|
1028 |
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value: 0.338
|
1029 |
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- type: precision_at_3
|
1030 |
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value: 17.1
|
1031 |
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- type: precision_at_5
|
1032 |
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value: 13.819999999999999
|
1033 |
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- type: recall_at_1
|
1034 |
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value: 4.918
|
1035 |
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- type: recall_at_10
|
1036 |
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value: 20.102
|
1037 |
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- type: recall_at_100
|
1038 |
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value: 43.69
|
1039 |
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- type: recall_at_1000
|
1040 |
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value: 68.568
|
1041 |
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- type: recall_at_3
|
1042 |
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value: 10.383000000000001
|
1043 |
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- type: recall_at_5
|
1044 |
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value: 13.977999999999998
|
1045 |
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- task:
|
1046 |
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type: STS
|
1047 |
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dataset:
|
1048 |
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type: mteb/sickr-sts
|
1049 |
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name: MTEB SICK-R
|
1050 |
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config: default
|
1051 |
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split: test
|
1052 |
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revision: a6ea5a8cab320b040a23452cc28066d9beae2cee
|
1053 |
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metrics:
|
1054 |
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- type: cos_sim_pearson
|
1055 |
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value: 86.02374279770862
|
1056 |
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- type: cos_sim_spearman
|
1057 |
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value: 80.3123278821752
|
1058 |
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- type: euclidean_pearson
|
1059 |
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value: 78.150387301923
|
1060 |
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- type: euclidean_spearman
|
1061 |
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value: 74.27020095240543
|
1062 |
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- type: manhattan_pearson
|
1063 |
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value: 78.00212720962597
|
1064 |
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- type: manhattan_spearman
|
1065 |
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value: 74.27996355049189
|
1066 |
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- task:
|
1067 |
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type: STS
|
1068 |
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dataset:
|
1069 |
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type: mteb/sts12-sts
|
1070 |
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name: MTEB STS12
|
1071 |
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config: default
|
1072 |
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split: test
|
1073 |
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revision: a0d554a64d88156834ff5ae9920b964011b16384
|
1074 |
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metrics:
|
1075 |
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- type: cos_sim_pearson
|
1076 |
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value: 83.56832604166104
|
1077 |
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- type: cos_sim_spearman
|
1078 |
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value: 73.85172437109456
|
1079 |
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- type: euclidean_pearson
|
1080 |
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value: 70.77037821156355
|
1081 |
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- type: euclidean_spearman
|
1082 |
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value: 58.32603602271459
|
1083 |
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- type: manhattan_pearson
|
1084 |
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value: 70.6019035905572
|
1085 |
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- type: manhattan_spearman
|
1086 |
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value: 58.18758998109944
|
1087 |
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- task:
|
1088 |
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type: STS
|
1089 |
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dataset:
|
1090 |
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type: mteb/sts13-sts
|
1091 |
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name: MTEB STS13
|
1092 |
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config: default
|
1093 |
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split: test
|
1094 |
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revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
|
1095 |
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metrics:
|
1096 |
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- type: cos_sim_pearson
|
1097 |
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value: 83.97624603590171
|
1098 |
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- type: cos_sim_spearman
|
1099 |
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value: 84.3654403570941
|
1100 |
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- type: euclidean_pearson
|
1101 |
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value: 77.37734191552401
|
1102 |
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- type: euclidean_spearman
|
1103 |
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value: 77.83492278107906
|
1104 |
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- type: manhattan_pearson
|
1105 |
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value: 77.38406845115612
|
1106 |
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- type: manhattan_spearman
|
1107 |
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value: 77.80429501178632
|
1108 |
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- task:
|
1109 |
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type: STS
|
1110 |
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dataset:
|
1111 |
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type: mteb/sts14-sts
|
1112 |
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name: MTEB STS14
|
1113 |
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config: default
|
1114 |
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split: test
|
1115 |
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revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
|
1116 |
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metrics:
|
1117 |
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- type: cos_sim_pearson
|
1118 |
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value: 82.5175806484823
|
1119 |
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- type: cos_sim_spearman
|
1120 |
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value: 77.84074419393815
|
1121 |
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- type: euclidean_pearson
|
1122 |
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value: 75.31514179994578
|
1123 |
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- type: euclidean_spearman
|
1124 |
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value: 71.06564963155697
|
1125 |
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- type: manhattan_pearson
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1126 |
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value: 75.25016497298036
|
1127 |
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- type: manhattan_spearman
|
1128 |
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value: 71.0503867625097
|
1129 |
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- task:
|
1130 |
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type: STS
|
1131 |
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dataset:
|
1132 |
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type: mteb/sts15-sts
|
1133 |
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name: MTEB STS15
|
1134 |
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config: default
|
1135 |
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split: test
|
1136 |
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revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
|
1137 |
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metrics:
|
1138 |
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- type: cos_sim_pearson
|
1139 |
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value: 85.15312065200007
|
1140 |
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- type: cos_sim_spearman
|
1141 |
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value: 86.28786282283781
|
1142 |
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- type: euclidean_pearson
|
1143 |
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value: 69.93961446583728
|
1144 |
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- type: euclidean_spearman
|
1145 |
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value: 70.99565144007187
|
1146 |
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- type: manhattan_pearson
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1147 |
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value: 70.06338127800244
|
1148 |
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- type: manhattan_spearman
|
1149 |
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value: 71.15328825585216
|
1150 |
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- task:
|
1151 |
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type: STS
|
1152 |
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dataset:
|
1153 |
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type: mteb/sts16-sts
|
1154 |
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name: MTEB STS16
|
1155 |
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config: default
|
1156 |
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split: test
|
1157 |
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revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
|
1158 |
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metrics:
|
1159 |
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- type: cos_sim_pearson
|
1160 |
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value: 80.48261723093232
|
1161 |
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- type: cos_sim_spearman
|
1162 |
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value: 82.13997187275378
|
1163 |
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- type: euclidean_pearson
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|
1167 |
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1172 |
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|
1174 |
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1175 |
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1176 |
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config: en-en
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1180 |
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value: 89.89094326696411
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|
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1191 |
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1192 |
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|
1193 |
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1194 |
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dataset:
|
1195 |
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1196 |
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1197 |
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revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80
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1200 |
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|
1201 |
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value: 67.03259798800852
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|
1214 |
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1215 |
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|
1216 |
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type: mteb/stsbenchmark-sts
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1217 |
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1218 |
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1222 |
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1223 |
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1232 |
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|
1235 |
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type: Reranking
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1236 |
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|
1237 |
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1238 |
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1239 |
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1240 |
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1242 |
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|
1243 |
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1244 |
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1245 |
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1246 |
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- task:
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1248 |
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1249 |
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dataset:
|
1250 |
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type: scifact
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1251 |
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name: MTEB SciFact
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1252 |
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config: default
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1253 |
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split: test
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1254 |
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revision: None
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1255 |
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metrics:
|
1256 |
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1257 |
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1258 |
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1297 |
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- type: precision_at_1000
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1300 |
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1301 |
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value: 21.556
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1302 |
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- type: precision_at_5
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1303 |
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value: 14.2
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1304 |
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1305 |
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value: 47.094
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1306 |
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1307 |
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value: 74.239
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1309 |
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value: 89.0
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- type: recall_at_1000
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1311 |
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- type: recall_at_3
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1313 |
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value: 59.606
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1314 |
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- type: recall_at_5
|
1315 |
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value: 64.756
|
1316 |
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- task:
|
1317 |
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type: PairClassification
|
1318 |
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dataset:
|
1319 |
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type: mteb/sprintduplicatequestions-pairclassification
|
1320 |
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name: MTEB SprintDuplicateQuestions
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1321 |
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config: default
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1322 |
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split: test
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1323 |
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revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
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1324 |
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metrics:
|
1325 |
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1326 |
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value: 99.7128712871287
|
1327 |
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- type: cos_sim_ap
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1331 |
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- type: cos_sim_precision
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1333 |
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- type: cos_sim_recall
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1334 |
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value: 83.7
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1335 |
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- type: dot_accuracy
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1336 |
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1337 |
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1339 |
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- type: dot_f1
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1341 |
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- type: dot_precision
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1342 |
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1343 |
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- type: dot_recall
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1344 |
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|
1345 |
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- type: euclidean_accuracy
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1346 |
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|
1347 |
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- type: euclidean_ap
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1348 |
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1349 |
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- type: euclidean_f1
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1350 |
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|
1351 |
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- type: euclidean_precision
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1352 |
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value: 83.51409978308027
|
1353 |
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- type: euclidean_recall
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1354 |
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value: 77.0
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1355 |
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- type: manhattan_accuracy
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1356 |
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value: 99.62178217821783
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1357 |
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- type: manhattan_ap
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1358 |
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1359 |
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- type: manhattan_f1
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1361 |
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- type: manhattan_precision
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1362 |
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1363 |
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- type: manhattan_recall
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1364 |
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1365 |
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- type: max_accuracy
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1366 |
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1367 |
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- type: max_ap
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1368 |
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1369 |
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- type: max_f1
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1370 |
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1371 |
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- task:
|
1372 |
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type: Clustering
|
1373 |
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dataset:
|
1374 |
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type: mteb/stackexchange-clustering
|
1375 |
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name: MTEB StackExchangeClustering
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1376 |
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config: default
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1377 |
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split: test
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1378 |
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1379 |
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metrics:
|
1380 |
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- type: v_measure
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1381 |
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value: 54.98955943181893
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1382 |
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- task:
|
1383 |
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type: Clustering
|
1384 |
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dataset:
|
1385 |
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type: mteb/stackexchange-clustering-p2p
|
1386 |
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name: MTEB StackExchangeClusteringP2P
|
1387 |
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1388 |
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1389 |
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1390 |
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metrics:
|
1391 |
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- type: v_measure
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1392 |
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|
1393 |
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- task:
|
1394 |
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|
1395 |
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dataset:
|
1396 |
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type: mteb/stackoverflowdupquestions-reranking
|
1397 |
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name: MTEB StackOverflowDupQuestions
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1398 |
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1399 |
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1400 |
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1401 |
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metrics:
|
1402 |
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1403 |
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1404 |
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1405 |
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1406 |
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- task:
|
1407 |
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1408 |
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dataset:
|
1409 |
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1410 |
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1411 |
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split: test
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1413 |
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1414 |
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metrics:
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1415 |
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value: 30.250596893094876
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1417 |
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1421 |
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1423 |
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- task:
|
1424 |
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1425 |
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dataset:
|
1426 |
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type: trec-covid
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1427 |
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name: MTEB TRECCOVID
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1428 |
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config: default
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1429 |
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split: test
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1430 |
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revision: None
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1431 |
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metrics:
|
1432 |
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1433 |
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value: 0.187
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1434 |
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1435 |
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1436 |
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1440 |
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1441 |
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1443 |
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1444 |
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1447 |
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1448 |
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1454 |
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1455 |
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1456 |
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1460 |
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1462 |
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1463 |
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1464 |
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1466 |
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1467 |
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value: 58.792
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1468 |
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1469 |
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1470 |
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1471 |
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1472 |
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1473 |
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1474 |
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1475 |
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value: 17.304
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1476 |
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1477 |
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value: 67.333
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1478 |
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1479 |
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value: 62.4
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1480 |
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1481 |
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value: 0.187
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1482 |
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1483 |
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1485 |
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1486 |
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1487 |
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1488 |
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1489 |
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1490 |
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1491 |
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value: 0.8130000000000001
|
1492 |
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- task:
|
1493 |
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type: Retrieval
|
1494 |
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dataset:
|
1495 |
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type: webis-touche2020
|
1496 |
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name: MTEB Touche2020
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1497 |
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config: default
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1498 |
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split: test
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1499 |
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revision: None
|
1500 |
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metrics:
|
1501 |
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- type: map_at_1
|
1502 |
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value: 1.646
|
1503 |
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|
1504 |
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1505 |
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1511 |
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1512 |
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1513 |
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1514 |
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1515 |
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1516 |
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1517 |
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1518 |
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1519 |
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1520 |
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1521 |
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1522 |
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value: 29.252
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1523 |
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1524 |
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1525 |
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1526 |
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1527 |
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1528 |
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1529 |
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1530 |
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value: 28.925
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1531 |
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1532 |
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value: 41.346
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1533 |
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1534 |
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1535 |
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1536 |
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1537 |
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1538 |
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1539 |
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1540 |
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1541 |
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1542 |
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1543 |
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1544 |
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1545 |
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1546 |
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value: 17.687
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1547 |
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- type: precision_at_5
|
1548 |
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value: 20.0
|
1549 |
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1550 |
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value: 1.646
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1551 |
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|
1552 |
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value: 12.113
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1553 |
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1554 |
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value: 40.261
|
1555 |
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- type: recall_at_1000
|
1556 |
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|
1557 |
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- type: recall_at_3
|
1558 |
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value: 4.181
|
1559 |
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- type: recall_at_5
|
1560 |
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value: 7.744
|
1561 |
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- task:
|
1562 |
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type: Classification
|
1563 |
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dataset:
|
1564 |
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type: mteb/toxic_conversations_50k
|
1565 |
+
name: MTEB ToxicConversationsClassification
|
1566 |
+
config: default
|
1567 |
+
split: test
|
1568 |
+
revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
|
1569 |
+
metrics:
|
1570 |
+
- type: accuracy
|
1571 |
+
value: 66.61500000000001
|
1572 |
+
- type: ap
|
1573 |
+
value: 11.70707762285034
|
1574 |
+
- type: f1
|
1575 |
+
value: 50.53259935502312
|
1576 |
+
- task:
|
1577 |
+
type: Classification
|
1578 |
+
dataset:
|
1579 |
+
type: mteb/tweet_sentiment_extraction
|
1580 |
+
name: MTEB TweetSentimentExtractionClassification
|
1581 |
+
config: default
|
1582 |
+
split: test
|
1583 |
+
revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
|
1584 |
+
metrics:
|
1585 |
+
- type: accuracy
|
1586 |
+
value: 54.89247311827958
|
1587 |
+
- type: f1
|
1588 |
+
value: 55.044186334629586
|
1589 |
+
- task:
|
1590 |
+
type: Clustering
|
1591 |
+
dataset:
|
1592 |
+
type: mteb/twentynewsgroups-clustering
|
1593 |
+
name: MTEB TwentyNewsgroupsClustering
|
1594 |
+
config: default
|
1595 |
+
split: test
|
1596 |
+
revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
|
1597 |
+
metrics:
|
1598 |
+
- type: v_measure
|
1599 |
+
value: 46.95851882042766
|
1600 |
+
- task:
|
1601 |
+
type: PairClassification
|
1602 |
+
dataset:
|
1603 |
+
type: mteb/twittersemeval2015-pairclassification
|
1604 |
+
name: MTEB TwitterSemEval2015
|
1605 |
+
config: default
|
1606 |
+
split: test
|
1607 |
+
revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
|
1608 |
+
metrics:
|
1609 |
+
- type: cos_sim_accuracy
|
1610 |
+
value: 84.01978899684092
|
1611 |
+
- type: cos_sim_ap
|
1612 |
+
value: 68.10404793439619
|
1613 |
+
- type: cos_sim_f1
|
1614 |
+
value: 63.93145891154821
|
1615 |
+
- type: cos_sim_precision
|
1616 |
+
value: 58.905937291527685
|
1617 |
+
- type: cos_sim_recall
|
1618 |
+
value: 69.89445910290237
|
1619 |
+
- type: dot_accuracy
|
1620 |
+
value: 77.78506288370984
|
1621 |
+
- type: dot_ap
|
1622 |
+
value: 38.55636213255057
|
1623 |
+
- type: dot_f1
|
1624 |
+
value: 44.6866485013624
|
1625 |
+
- type: dot_precision
|
1626 |
+
value: 34.07202216066482
|
1627 |
+
- type: dot_recall
|
1628 |
+
value: 64.90765171503958
|
1629 |
+
- type: euclidean_accuracy
|
1630 |
+
value: 82.94093103653812
|
1631 |
+
- type: euclidean_ap
|
1632 |
+
value: 63.65596102723866
|
1633 |
+
- type: euclidean_f1
|
1634 |
+
value: 61.444903916322055
|
1635 |
+
- type: euclidean_precision
|
1636 |
+
value: 56.994584837545126
|
1637 |
+
- type: euclidean_recall
|
1638 |
+
value: 66.64907651715039
|
1639 |
+
- type: manhattan_accuracy
|
1640 |
+
value: 82.99457590749239
|
1641 |
+
- type: manhattan_ap
|
1642 |
+
value: 63.77653539498376
|
1643 |
+
- type: manhattan_f1
|
1644 |
+
value: 61.48299483235189
|
1645 |
+
- type: manhattan_precision
|
1646 |
+
value: 56.455528580887226
|
1647 |
+
- type: manhattan_recall
|
1648 |
+
value: 67.4934036939314
|
1649 |
+
- type: max_accuracy
|
1650 |
+
value: 84.01978899684092
|
1651 |
+
- type: max_ap
|
1652 |
+
value: 68.10404793439619
|
1653 |
+
- type: max_f1
|
1654 |
+
value: 63.93145891154821
|
1655 |
+
- task:
|
1656 |
+
type: PairClassification
|
1657 |
+
dataset:
|
1658 |
+
type: mteb/twitterurlcorpus-pairclassification
|
1659 |
+
name: MTEB TwitterURLCorpus
|
1660 |
+
config: default
|
1661 |
+
split: test
|
1662 |
+
revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
|
1663 |
+
metrics:
|
1664 |
+
- type: cos_sim_accuracy
|
1665 |
+
value: 87.75177552683665
|
1666 |
+
- type: cos_sim_ap
|
1667 |
+
value: 83.75899853399007
|
1668 |
+
- type: cos_sim_f1
|
1669 |
+
value: 76.25022931572188
|
1670 |
+
- type: cos_sim_precision
|
1671 |
+
value: 72.83241045769958
|
1672 |
+
- type: cos_sim_recall
|
1673 |
+
value: 80.00461964890668
|
1674 |
+
- type: dot_accuracy
|
1675 |
+
value: 81.8197694725812
|
1676 |
+
- type: dot_ap
|
1677 |
+
value: 67.6851675345571
|
1678 |
+
- type: dot_f1
|
1679 |
+
value: 64.04501820589209
|
1680 |
+
- type: dot_precision
|
1681 |
+
value: 56.17233770758332
|
1682 |
+
- type: dot_recall
|
1683 |
+
value: 74.48413920542039
|
1684 |
+
- type: euclidean_accuracy
|
1685 |
+
value: 83.3003454030349
|
1686 |
+
- type: euclidean_ap
|
1687 |
+
value: 72.80186670461116
|
1688 |
+
- type: euclidean_f1
|
1689 |
+
value: 65.38000218078727
|
1690 |
+
- type: euclidean_precision
|
1691 |
+
value: 61.92082616179002
|
1692 |
+
- type: euclidean_recall
|
1693 |
+
value: 69.24853711117956
|
1694 |
+
- type: manhattan_accuracy
|
1695 |
+
value: 83.32169053440447
|
1696 |
+
- type: manhattan_ap
|
1697 |
+
value: 72.8243559753097
|
1698 |
+
- type: manhattan_f1
|
1699 |
+
value: 65.45939901157966
|
1700 |
+
- type: manhattan_precision
|
1701 |
+
value: 61.58284124075205
|
1702 |
+
- type: manhattan_recall
|
1703 |
+
value: 69.85679088389283
|
1704 |
+
- type: max_accuracy
|
1705 |
+
value: 87.75177552683665
|
1706 |
+
- type: max_ap
|
1707 |
+
value: 83.75899853399007
|
1708 |
+
- type: max_f1
|
1709 |
+
value: 76.25022931572188
|
1710 |
---
|
1711 |
|
1712 |
<br><br>
|