19 января 2024 г. 13:26
Команда RCC MSU
Ссылка на модель https://huggingface.co/rccmsu/ruadapt_llama2_7b_v0.1
| Датасет | Результат | Метрика |
|---|---|---|
| LiDiRus | 0,417 | Кор, коэффициент Мэтью |
| RCB | 0,545 / 0,555 | F1/Точность |
| PARus | 0,756 | Точность |
| MuSeRC | 0,894 / 0,695 | F1a/Em |
| TERRa | 0,876 | Точность |
| RUSSE | 0,668 | Точность |
| RWSD | 0,708 | Точность |
| DaNetQA | 0,878 | Точность |
| RuCoS | 0,76 / 0,733 | F1/EM |
Tikhomirov M., Chernyshev D. Impact of Tokenization on LLaMa Russian Adaptation //arXiv preprint arXiv:2312.02598. – 2023.
Tested using https://github.com/IlyaGusev/rulm repo { "trainer": { "evaluation_strategy": "steps", "per_device_train_batch_size": 4, "per_device_eval_batch_size": 4, "gradient_accumulation_steps": 32, "eval_steps": 50, "save_steps": 50, "logging_steps": 5, "learning_rate": 0.00025, "num_train_epochs": 3, "lr_scheduler_type": "cosine", "warmup_steps": 30, "fp16": true, "bf16": false, "torch_compile": false, "optim": "adamw_torch" }, "lora": { "r": 16, "lora_alpha": 16, "lora_dropout": 0.05, "bias": "none", "target_modules": ["q_proj", "v_proj", "k_proj", "o_proj"], "task_type": "CAUSAL_LM" }, "load_in_8bit": false, "only_target_loss": true, "mode": "chat", "templates_path": "internal_prompts/saiga_v2.json", "model_name": "llama2_7b_darulm_unigram_tie_2e_16_11_23", "model_type": "causal", "max_tokens_count": 1024 }
| Категория | Результат |
|---|---|
| LOGIC | 0,3472109173849461 |
| KNOWLEDGE | 0,3988089571509749 |
| PREDICATE-ARGUMENT STRUCTURE | 0,4107842841297232 |
| LEXICAL SEMANTICS | 0,4999636017616265 |
| Lexical Semantics - Lexical Entailment | 0,5648145000600431 |
|---|---|
| Lexical Semantics - Morphological Negation | 0,39477101697586137 |
| Lexical Semantics - Factivity | 0,4264014327112209 |
| Lexical Semantics - Symmetry/Collectivity | 0,31622776601683794 |
| Lexical Semantics - Redundancy | 0,17951965741648493 |
| Lexical Semantics - Named Entities | 0,612056372482123 |
| Lexical Semantics - Quantifiers | 0,3638714534805853 |
| Predicate-Argument Structure Core Args | 0,30962962962962964 |
| Predicate-Argument Structure Prepositional Phrases | 0,3943052207977212 |
| Predicate-Argument Structure Ellipsis/Implicits | 0,6205427141408237 |
| Predicate-Argument Structure Anaphora/Coreference | 0,4144368375833978 |
| Predicate-Argument Structure Active/Passive | 0,4083133966424866 |
| Predicate-Argument Structure Nominalization | 0,5444357229372963 |
| Predicate-Argument Structure Genitives/Partitives | 0,6813851438692469 |
| Predicate-Argument Structure Datives | 0,3563483225498992 |
| Predicate-Argument Structure Relative Clauses | 0,6407232755171874 |
| Predicate-Argument Structure Coordination Scopes | 0,14169568340005298 |
| Predicate-Argument Structure Intersectivity | 0,42208132696637884 |
| Predicate-Argument Structure Restrictivity | 0,36900620230837305 |
| Logic Negation | 0,473553991329486 |
| Logic Double Negation | 0,3892494720807615 |
| Logic Interval/Numbers | 0,08779776400125335 |
| Logic Conjuction | 0,33734954246999327 |
| Logic Disjunction | 0,4365575409204501 |
| Logic Conditionals | 0,3730235484764954 |
| Logic Universal | 0,3959441875175622 |
| Logic Existential | 0,17910620335162064 |
| Logic Temporal | 0,11891767800211263 |
| Logic Upward Monotone | 0,7009124021507408 |
| Logic Downward Monotone | 0,16146816171752817 |
| Logic Non-Monotonic | 0,39405520311955033 |
| Knowledge Common Sense | 0,3600431599767098 |
| Knowledge World Knowledge | 0,4447466812418805 |
| Датасет | Speed | RAM |
|---|---|---|
| LiDiRus | - | - |
| RCB | - | - |
| PARus | - | - |
| MuSeRC | - | - |
| TERRa | - | - |
| RUSSE | - | - |
| RWSD | - | - |
| DaNetQA | - | - |
| RuCoS | - | - |