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mteb
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Merge pull request #11 from Samoed/add_rusian_models

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  1. paths.json +0 -0
  2. results.py +16 -3
  3. results/LaBSE-en-ru/cf0714e606d4af551e14ad69a7929cd6b0da7f7e/BUCC.v2.json +23 -0
  4. results/LaBSE-en-ru/cf0714e606d4af551e14ad69a7929cd6b0da7f7e/BelebeleRetrieval.json +455 -0
  5. results/LaBSE-en-ru/cf0714e606d4af551e14ad69a7929cd6b0da7f7e/BibleNLPBitextMining.json +35 -0
  6. results/LaBSE-en-ru/cf0714e606d4af551e14ad69a7929cd6b0da7f7e/CEDRClassification.json +73 -0
  7. results/LaBSE-en-ru/cf0714e606d4af551e14ad69a7929cd6b0da7f7e/CyrillicTurkicLangClassification.json +81 -0
  8. results/LaBSE-en-ru/cf0714e606d4af551e14ad69a7929cd6b0da7f7e/FloresBitextMining.json +0 -0
  9. results/LaBSE-en-ru/cf0714e606d4af551e14ad69a7929cd6b0da7f7e/GeoreviewClassification.json +73 -0
  10. results/LaBSE-en-ru/cf0714e606d4af551e14ad69a7929cd6b0da7f7e/GeoreviewClusteringP2P.json +34 -0
  11. results/LaBSE-en-ru/cf0714e606d4af551e14ad69a7929cd6b0da7f7e/HeadlineClassification.json +73 -0
  12. results/LaBSE-en-ru/cf0714e606d4af551e14ad69a7929cd6b0da7f7e/InappropriatenessClassification.json +95 -0
  13. results/LaBSE-en-ru/cf0714e606d4af551e14ad69a7929cd6b0da7f7e/KinopoiskClassification.json +73 -0
  14. results/LaBSE-en-ru/cf0714e606d4af551e14ad69a7929cd6b0da7f7e/LanguageClassification.json +92 -0
  15. results/LaBSE-en-ru/cf0714e606d4af551e14ad69a7929cd6b0da7f7e/MLSUMClusteringP2P.json +55 -0
  16. results/LaBSE-en-ru/cf0714e606d4af551e14ad69a7929cd6b0da7f7e/MLSUMClusteringP2P.v2.json +34 -0
  17. results/LaBSE-en-ru/cf0714e606d4af551e14ad69a7929cd6b0da7f7e/MLSUMClusteringS2S.json +55 -0
  18. results/LaBSE-en-ru/cf0714e606d4af551e14ad69a7929cd6b0da7f7e/MLSUMClusteringS2S.v2.json +59 -0
  19. results/LaBSE-en-ru/cf0714e606d4af551e14ad69a7929cd6b0da7f7e/MassiveIntentClassification.json +0 -0
  20. results/LaBSE-en-ru/cf0714e606d4af551e14ad69a7929cd6b0da7f7e/MassiveScenarioClassification.json +0 -0
  21. results/LaBSE-en-ru/cf0714e606d4af551e14ad69a7929cd6b0da7f7e/MultiLongDocRetrieval.json +307 -0
  22. results/LaBSE-en-ru/cf0714e606d4af551e14ad69a7929cd6b0da7f7e/MultilingualSentimentClassification.json +95 -0
  23. results/LaBSE-en-ru/cf0714e606d4af551e14ad69a7929cd6b0da7f7e/NTREXBitextMining.json +899 -0
  24. results/LaBSE-en-ru/cf0714e606d4af551e14ad69a7929cd6b0da7f7e/OpusparcusPC.json +105 -0
  25. results/LaBSE-en-ru/cf0714e606d4af551e14ad69a7929cd6b0da7f7e/PublicHealthQA.json +158 -0
  26. results/LaBSE-en-ru/cf0714e606d4af551e14ad69a7929cd6b0da7f7e/RUParaPhraserSTS.json +32 -0
  27. results/LaBSE-en-ru/cf0714e606d4af551e14ad69a7929cd6b0da7f7e/RiaNewsRetrieval.json +158 -0
  28. results/LaBSE-en-ru/cf0714e606d4af551e14ad69a7929cd6b0da7f7e/RuBQReranking.json +26 -0
  29. results/LaBSE-en-ru/cf0714e606d4af551e14ad69a7929cd6b0da7f7e/RuBQRetrieval.json +158 -0
  30. results/LaBSE-en-ru/cf0714e606d4af551e14ad69a7929cd6b0da7f7e/RuReviewsClassification.json +73 -0
  31. results/LaBSE-en-ru/cf0714e606d4af551e14ad69a7929cd6b0da7f7e/RuSTSBenchmarkSTS.json +32 -0
  32. results/LaBSE-en-ru/cf0714e606d4af551e14ad69a7929cd6b0da7f7e/RuSciBenchGRNTIClassification.json +73 -0
  33. results/LaBSE-en-ru/cf0714e606d4af551e14ad69a7929cd6b0da7f7e/RuSciBenchGRNTIClusteringP2P.json +34 -0
  34. results/LaBSE-en-ru/cf0714e606d4af551e14ad69a7929cd6b0da7f7e/RuSciBenchOECDClassification.json +73 -0
  35. results/LaBSE-en-ru/cf0714e606d4af551e14ad69a7929cd6b0da7f7e/RuSciBenchOECDClusteringP2P.json +34 -0
  36. results/LaBSE-en-ru/cf0714e606d4af551e14ad69a7929cd6b0da7f7e/SIB200Classification.json +201 -0
  37. results/LaBSE-en-ru/cf0714e606d4af551e14ad69a7929cd6b0da7f7e/SIB200ClusteringS2S.json +34 -0
  38. results/LaBSE-en-ru/cf0714e606d4af551e14ad69a7929cd6b0da7f7e/STS22.json +397 -0
  39. results/LaBSE-en-ru/cf0714e606d4af551e14ad69a7929cd6b0da7f7e/STS22.v2.json +32 -0
  40. results/LaBSE-en-ru/cf0714e606d4af551e14ad69a7929cd6b0da7f7e/STSBenchmarkMultilingualSTS.json +55 -0
  41. results/LaBSE-en-ru/cf0714e606d4af551e14ad69a7929cd6b0da7f7e/SensitiveTopicsClassification.json +73 -0
  42. results/LaBSE-en-ru/cf0714e606d4af551e14ad69a7929cd6b0da7f7e/TERRa.json +57 -0
  43. results/LaBSE-en-ru/cf0714e606d4af551e14ad69a7929cd6b0da7f7e/Tatoeba.json +23 -0
  44. results/LaBSE-en-ru/cf0714e606d4af551e14ad69a7929cd6b0da7f7e/XNLI.json +105 -0
  45. results/LaBSE-en-ru/cf0714e606d4af551e14ad69a7929cd6b0da7f7e/XNLIV2.json +57 -0
  46. results/LaBSE-en-ru/cf0714e606d4af551e14ad69a7929cd6b0da7f7e/XQuADRetrieval.json +158 -0
  47. results/LaBSE-en-ru/cf0714e606d4af551e14ad69a7929cd6b0da7f7e/model_meta.json +1 -0
  48. results/LaBSE-ru-turbo/1940b046c6b5e125df11722b899130329d0a46da/BUCC.v2.json +23 -0
  49. results/LaBSE-ru-turbo/1940b046c6b5e125df11722b899130329d0a46da/BelebeleRetrieval.json +455 -0
  50. results/LaBSE-ru-turbo/1940b046c6b5e125df11722b899130329d0a46da/BibleNLPBitextMining.json +35 -0
paths.json CHANGED
The diff for this file is too large to render. See raw diff
 
results.py CHANGED
@@ -33,11 +33,13 @@ TRAIN_SPLIT = ["DanishPoliticalCommentsClassification"]
33
  # Use "validation" split instead
34
  VALIDATION_SPLIT = ["AFQMC", "Cmnli", "IFlyTek", "LEMBSummScreenFDRetrieval", "MSMARCO", "MSMARCO-PL", "MultilingualSentiment", "Ocnli", "TNews"]
35
  # Use "dev" split instead
36
- DEV_SPLIT = ["CmedqaRetrieval", "CovidRetrieval", "DuRetrieval", "EcomRetrieval", "MedicalRetrieval", "MMarcoReranking", "MMarcoRetrieval", "MSMARCO", "MSMARCO-PL", "T2Reranking", "T2Retrieval", "VideoRetrieval"]
37
  # Use "test.full" split
38
  TESTFULL_SPLIT = ["OpusparcusPC"]
39
  # Use "standard" split
40
  STANDARD_SPLIT = ["BrightRetrieval"]
 
 
41
 
42
  TEST_AVG_SPLIT = {
43
  "LEMBNeedleRetrieval": ["test_256", "test_512", "test_1024", "test_2048", "test_4096", "test_8192", "test_16384", "test_32768"],
@@ -235,6 +237,15 @@ MODELS = [
235
  "voyage-multilingual-2",
236
  "xlm-roberta-base",
237
  "xlm-roberta-large",
 
 
 
 
 
 
 
 
 
238
  ]
239
 
240
 
@@ -324,6 +335,8 @@ class MTEBResults(datasets.GeneratorBasedBuilder):
324
  split = "test.full"
325
  elif (ds_name in STANDARD_SPLIT) and ("standard" in res_dict):
326
  split = "standard"
 
 
327
  elif (ds_name in TEST_AVG_SPLIT):
328
  # Average splits
329
  res_dict["test_avg"] = {}
@@ -381,7 +394,7 @@ class MTEBResults(datasets.GeneratorBasedBuilder):
381
  })
382
  else:
383
  if not isinstance(score, float):
384
- print(f'WARNING: Expected float, got {score} for {ds_name} {lang} {metric} {k}')
385
  continue
386
  out.append({
387
  "mteb_dataset_name": ds_name,
@@ -415,4 +428,4 @@ class MTEBResults(datasets.GeneratorBasedBuilder):
415
 
416
  # NOTE: for generating the new paths
417
  if __name__ == "__main__":
418
- get_paths()
 
33
  # Use "validation" split instead
34
  VALIDATION_SPLIT = ["AFQMC", "Cmnli", "IFlyTek", "LEMBSummScreenFDRetrieval", "MSMARCO", "MSMARCO-PL", "MultilingualSentiment", "Ocnli", "TNews"]
35
  # Use "dev" split instead
36
+ DEV_SPLIT = ["CmedqaRetrieval", "CovidRetrieval", "DuRetrieval", "EcomRetrieval", "MedicalRetrieval", "MMarcoReranking", "MMarcoRetrieval", "MSMARCO", "MSMARCO-PL", "T2Reranking", "T2Retrieval", "VideoRetrieval", "TERRa",]
37
  # Use "test.full" split
38
  TESTFULL_SPLIT = ["OpusparcusPC"]
39
  # Use "standard" split
40
  STANDARD_SPLIT = ["BrightRetrieval"]
41
+ # Use "devtest" split
42
+ DEVTEST_SPLIT = ["FloresBitextMining"]
43
 
44
  TEST_AVG_SPLIT = {
45
  "LEMBNeedleRetrieval": ["test_256", "test_512", "test_1024", "test_2048", "test_4096", "test_8192", "test_16384", "test_32768"],
 
237
  "voyage-multilingual-2",
238
  "xlm-roberta-base",
239
  "xlm-roberta-large",
240
+ "deberta-v1-base",
241
+ "USER-bge-m3",
242
+ "USER-base",
243
+ "rubert-tiny-turbo",
244
+ "LaBSE-ru-turbo",
245
+ "distilrubert-small-cased-conversational",
246
+ "rubert-base-cased",
247
+ "rubert-base-cased-sentence",
248
+ "LaBSE-en-ru",
249
  ]
250
 
251
 
 
335
  split = "test.full"
336
  elif (ds_name in STANDARD_SPLIT) and ("standard" in res_dict):
337
  split = "standard"
338
+ elif (ds_name in DEVTEST_SPLIT) and ("devtest" in res_dict):
339
+ split = "devtest"
340
  elif (ds_name in TEST_AVG_SPLIT):
341
  # Average splits
342
  res_dict["test_avg"] = {}
 
394
  })
395
  else:
396
  if not isinstance(score, float):
397
+ print(f'WARNING: Expected float, got {score} for {ds_name} {lang} {metric}')
398
  continue
399
  out.append({
400
  "mteb_dataset_name": ds_name,
 
428
 
429
  # NOTE: for generating the new paths
430
  if __name__ == "__main__":
431
+ get_paths()
results/LaBSE-en-ru/cf0714e606d4af551e14ad69a7929cd6b0da7f7e/BUCC.v2.json ADDED
@@ -0,0 +1,23 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "dataset_revision": "1739dc11ffe9b7bfccd7f3d585aeb4c544fc6677",
3
+ "evaluation_time": 17.75709819793701,
4
+ "kg_co2_emissions": null,
5
+ "mteb_version": "1.12.85",
6
+ "scores": {
7
+ "test": [
8
+ {
9
+ "accuracy": 0.9801177693107032,
10
+ "f1": 0.9738298118000231,
11
+ "hf_subset": "ru-en",
12
+ "languages": [
13
+ "rus-Cyrl",
14
+ "eng-Latn"
15
+ ],
16
+ "main_score": 0.9738298118000231,
17
+ "precision": 0.9707250894815842,
18
+ "recall": 0.9801177693107032
19
+ }
20
+ ]
21
+ },
22
+ "task_name": "BUCC.v2"
23
+ }
results/LaBSE-en-ru/cf0714e606d4af551e14ad69a7929cd6b0da7f7e/BelebeleRetrieval.json ADDED
@@ -0,0 +1,455 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ {
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+ "hf_subset": "rus_Cyrl-rus_Cyrl",
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+ "languages": [
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+ "rus-Cyrl"
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