11 октября 2023 г. 15:23
Команда Saiga team
Ссылка на модель https://huggingface.co/mistralai/Mistral-7B-v0.1
Датасет | Результат | Метрика |
---|---|---|
LiDiRus | 0,46 | Кор, коэффициент Мэтью |
RCB | 0,529 / 0,573 | F1/Точность |
PARus | 0,824 | Точность |
MuSeRC | 0,927 / 0,787 | F1a/Em |
TERRa | 0,888 | Точность |
RUSSE | 0,758 | Точность |
RWSD | 0,786 | Точность |
DaNetQA | 0,919 | Точность |
RuCoS | 0,83 / 0,816 | F1/EM |
The Mistral-7B-v0.1, LoRA-tuned on RSG sets. For the information about inference see: https://github.com/IlyaGusev/rulm/blob/master/self_instruct/src/benchmarks/eval_lora_rsg.py train: https://github.com/IlyaGusev/rulm/blob/master/self_instruct/src/train.py The main config for LoRA: https://github.com/IlyaGusev/rulm/blob/master/self_instruct/configs/mistral_7b_rsg.json configs for separate tasks are in the same folder. The Mistral-7B-v01 model was trained on multi-task with the main config, merged into the main model, and then task-level LoRA adapters were trained on top of this merged model. zero-shot evaluation script: https://github.com/IlyaGusev/rulm/blob/master/self_instruct/src/benchmarks/eval_zs_rsg.py
Категория | Результат |
---|---|
LOGIC | 0,4272477243463581 |
KNOWLEDGE | 0,4267562897825355 |
PREDICATE-ARGUMENT STRUCTURE | 0,4644487887609425 |
LEXICAL SEMANTICS | 0,5423872872028785 |
Lexical Semantics - Lexical Entailment | 0,5684993638729131 |
---|---|
Lexical Semantics - Morphological Negation | 0,6172133998483676 |
Lexical Semantics - Factivity | 0,29814239699997197 |
Lexical Semantics - Symmetry/Collectivity | 0,6243713415848884 |
Lexical Semantics - Redundancy | 0,1444869078105018 |
Lexical Semantics - Named Entities | 0,6708203932499369 |
Lexical Semantics - Quantifiers | 0,4287214448277836 |
Predicate-Argument Structure Core Args | 0,5051219141436532 |
Predicate-Argument Structure Prepositional Phrases | 0,6207200740216239 |
Predicate-Argument Structure Ellipsis/Implicits | 0,4992872412627317 |
Predicate-Argument Structure Anaphora/Coreference | 0,3682002176496948 |
Predicate-Argument Structure Active/Passive | 0,623033246356214 |
Predicate-Argument Structure Nominalization | 0,40881490876633847 |
Predicate-Argument Structure Genitives/Partitives | 0,5773502691896257 |
Predicate-Argument Structure Datives | 0,28511240114923325 |
Predicate-Argument Structure Relative Clauses | 0,42289003161103106 |
Predicate-Argument Structure Coordination Scopes | 0,48038446141526137 |
Predicate-Argument Structure Intersectivity | 0,3629539763832752 |
Predicate-Argument Structure Restrictivity | 0,46549138385896505 |
Logic Negation | 0,631059217297185 |
Logic Double Negation | 0,420084025208403 |
Logic Interval/Numbers | 0,42051713353118003 |
Logic Conjuction | 0,6713171133426189 |
Logic Disjunction | 0,3768673314407158 |
Logic Conditionals | 0,2698412698412698 |
Logic Universal | 0,6700593942604899 |
Logic Existential | 0,3144854510165755 |
Logic Temporal | 0,33910215700436014 |
Logic Upward Monotone | 0,4146442144313646 |
Logic Downward Monotone | 0,1438234930593239 |
Logic Non-Monotonic | 0,2895702534395041 |
Knowledge Common Sense | 0,39380049095855213 |
Knowledge World Knowledge | 0,4619338817592217 |
Датасет | Speed | RAM |
---|---|---|
LiDiRus | - | - |
RCB | - | - |
PARus | - | - |
MuSeRC | - | - |
TERRa | - | - |
RUSSE | - | - |
RWSD | - | - |
DaNetQA | - | - |
RuCoS | - | - |