18 ноября 2020 г. 15:31
Команда DeepPavlov
Ссылка на модель http://files.deeppavlov.ai/deeppavlov_data/bert/ru_conversational_cased_L-12_H-768_A-12_pt.tar.gz
Датасет | Результат | Метрика |
---|---|---|
LiDiRus | 0,178 | Кор, коэффициент Мэтью |
RCB | 0,452 / 0,484 | F1/Точность |
PARus | 0,508 | Точность |
MuSeRC | 0,687 / 0,278 | F1a/Em |
TERRa | 0,64 | Точность |
RUSSE | 0,729 | Точность |
RWSD | 0,669 | Точность |
DaNetQA | 0,606 | Точность |
RuCoS | 0,22 / 0,218 | F1/EM |
Conversational RuBERT was trained by DeepPavlov on OpenSubtitles, Dirty, Pikabu, and Social Media segment of Taiga corpus. We assembled new vocabulary for Conversational RuBERT model on this data and initialized model with RuBERT. How we train model in jiant see in our repo, file: `Russian_SuperGLUE_example.ipynb`
Conversational RuBERT was trained by DeepPavlov on OpenSubtitles, Dirty, Pikabu, and Social Media segment of Taiga corpus. We assembled new vocabulary for Conversational RuBERT model on this data and initialized model with RuBERT.
Категория | Результат |
---|---|
LOGIC | 0,08909703425730169 |
KNOWLEDGE | 0,22685372713785582 |
PREDICATE-ARGUMENT STRUCTURE | 0,18755413627356057 |
LEXICAL SEMANTICS | 0,17880052424736642 |
Lexical Semantics - Lexical Entailment | 0,08997060091656868 |
---|---|
Lexical Semantics - Morphological Negation | 0,042257712736425826 |
Lexical Semantics - Factivity | 0,1908790423082963 |
Lexical Semantics - Symmetry/Collectivity | 0,0 |
Lexical Semantics - Redundancy | 0,45652173913043476 |
Lexical Semantics - Named Entities | 0,07018624063435965 |
Lexical Semantics - Quantifiers | 0,016787316051946218 |
Predicate-Argument Structure Core Args | 0,2141057445312242 |
Predicate-Argument Structure Prepositional Phrases | 0,23271817721614832 |
Predicate-Argument Structure Ellipsis/Implicits | 0,014265349750363764 |
Predicate-Argument Structure Anaphora/Coreference | 0,2960528777048222 |
Predicate-Argument Structure Active/Passive | -0,003948992518393949 |
Predicate-Argument Structure Nominalization | 0,28499398669032056 |
Predicate-Argument Structure Genitives/Partitives | 0,375 |
Predicate-Argument Structure Datives | 0,3361227822436775 |
Predicate-Argument Structure Relative Clauses | 0,19740669742132735 |
Predicate-Argument Structure Coordination Scopes | 0,10482848367219183 |
Predicate-Argument Structure Intersectivity | 0,07984231865671275 |
Predicate-Argument Structure Restrictivity | 0,09335200560186732 |
Logic Negation | -0,03223161048648345 |
Logic Double Negation | 0,07537783614444091 |
Logic Interval/Numbers | 0,06998250655976682 |
Logic Conjuction | 0,24809590313546123 |
Logic Disjunction | -0,16447838793172298 |
Logic Conditionals | -0,14285714285714285 |
Logic Universal | 0,16116459280507606 |
Logic Existential | 0,36689969285267143 |
Logic Temporal | 0,26590801173915524 |
Logic Upward Monotone | 0,2135744251723958 |
Logic Downward Monotone | -0,08112739143148366 |
Logic Non-Monotonic | 0,18389242812245682 |
Knowledge Common Sense | 0,22216215518070082 |
Knowledge World Knowledge | 0,21289279690944252 |
Датасет | Speed | RAM |
---|---|---|
LiDiRus | 171 | 2.39 |
RCB | 289 | 2.39 |
PARus | 718 | 2.39 |
MuSeRC | 4 | 2.40 |
TERRa | 302 | 2.39 |
RUSSE | 255 | 2.39 |
RWSD | 101 | 2.39 |
DaNetQA | 103 | 2.40 |
RuCoS | 8 | 2.40 |