Paper | Code | Average F1 | EM | ModelName | ReleaseDate |
---|---|---|---|---|---|
[]() | 0.941 | 0.819 | Golden Transformer | ||
mT5: A massively multilingual pre-trained text-to-text transformer | ✓ Link | 0.844 | 0.543 | MT5 Large | 2020-10-22 |
[]() | 0.83 | 0.561 | ruRoberta-large finetune | ||
[]() | 0.815 | 0.537 | ruT5-large-finetune | ||
RussianSuperGLUE: A Russian Language Understanding Evaluation Benchmark | ✓ Link | 0.806 | 0.42 | Human Benchmark | 2020-10-29 |
[]() | 0.769 | 0.446 | ruT5-base-finetune | ||
[]() | 0.76 | 0.427 | ruBert-large finetune | ||
[]() | 0.742 | 0.399 | ruBert-base finetune | ||
[]() | 0.74 | 0.546 | RuGPT3XL few-shot | ||
[]() | 0.729 | 0.333 | RuGPT3Large | ||
[]() | 0.711 | 0.324 | RuBERT plain | ||
[]() | 0.706 | 0.308 | RuGPT3Medium | ||
[]() | 0.687 | 0.278 | RuBERT conversational | ||
[]() | 0.673 | 0.364 | YaLM 1.0B few-shot | ||
Unreasonable Effectiveness of Rule-Based Heuristics in Solving Russian SuperGLUE Tasks | 0.671 | 0.237 | heuristic majority | 2021-05-03 | |
[]() | 0.653 | 0.221 | RuGPT3Small | ||
[]() | 0.646 | 0.327 | SBERT_Large | ||
[]() | 0.642 | 0.319 | SBERT_Large_mt_ru_finetuning | ||
[]() | 0.639 | 0.239 | Multilingual Bert | ||
RussianSuperGLUE: A Russian Language Understanding Evaluation Benchmark | ✓ Link | 0.587 | 0.242 | Baseline TF-IDF1.1 | 2020-10-29 |
Unreasonable Effectiveness of Rule-Based Heuristics in Solving Russian SuperGLUE Tasks | 0.45 | 0.071 | Random weighted | 2021-05-03 | |
Unreasonable Effectiveness of Rule-Based Heuristics in Solving Russian SuperGLUE Tasks | 0.0 | 0.0 | majority_class | 2021-05-03 |