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Model: RefalMachine/ruadapt_qwen2.5_7B_ext_u48_instruct
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---
datasets:
- IlyaGusev/saiga_scored
- IlyaGusev/saiga_preferences
- dichspace/darulm
language:
- ru
pipeline_tag: text-generation
---
## Описание модели
WORK IN PROGRESS!!!
Инструктивная версия адаптированной на русский язык модели Qwen2.5-7B. В модели был заменен токенизатор, затем произведено дообучение (Continued pretraining) на русскоязычном корпусе, после чего была применена техника LEP (Learned Embedding Propagation, paper will be soon).
Благодаря новому токенизатору (расширенный tiktoken cl100k с помощью униграм токенизатора на 48 т. токенов) скорость генерации* русскоязычных текстов возрасла до 60% по сравнению с исходной моделью Qwen-2.5-7B-Instruct.
*Под скоростью генерации подразумевается количество русскоязычных символов/слов в секунду на одинаковых текстовых последовательностях.
## Токенизация
![image/png](https://cdn-uploads.huggingface.co/production/uploads/652cedbdf120598322ae358a/O4eQEhnowETEatDPcmArB.png)
![image/png](https://cdn-uploads.huggingface.co/production/uploads/652cedbdf120598322ae358a/oW0Q6LzD_Py3GdH0kfqu4.png)
## Метрики и оценка качества
Модель была оценена на Ru-Arena-General, MERA, llmtf_open
#### Результаты на Ru-Arena-General
Замеры были произведены с использованием оффициального кода лидерборда (https://github.com/VikhrModels/ru_llm_arena), **но с repetition_penalty=1.1**.
Приведена лишь часть лидерборда, подробнее смотрите в репозитории бенчмарка (https://huggingface.co/spaces/Vikhrmodels/arenahardlb).
| Model Name | Winrate | 95% CI | Average # Tokens |
|--------------------------------------------------|--------|--------------------|------------------|
| gpt-4-1106-preview | 90.9 | ( +1.3 / -0.9) | 541 |
| vikhr-nemo-12b-instruct-r-21-09-24 | 87.3 | (+1.1 / -1.2) | 627 |
| gpt-4o-mini | 83.9 | (+1.9 / -1.6) | 448 |
| **ruadapt_qwen2.5_7B_ext_u48_instruct** | **81.9** | **(+1.7 / -1.6)** | **556** |
| gemma-2-9b-it | 76.5 | (+1.1 / -1.1) | 459 |
| Qwen2.5-7B-Instruct | 76.0 | (+1.6 / -1.8) | 484 |
| gemma-2-9b-it-sppo-iter3 | 73.6 | (+2.1 / -2.2) | 509 |
| saiga_llama3_8b_v7 | 67.6 | (+1.7 / -1.4) | 503 |
| ruadapt_qwen2.5_3B_ext_u48_instruct_v4 | 66.1 | (+2.2 / -1.9) | 531 |
| t-lite-instruct-0.1 | 64.7 | (+2.3 / -2.2) | 810 |
#### Результаты на MERA
TODO
#### Результаты на llmtf_open
TODO
## How to cite:
Tikhomirov M., Chernyshev D. Facilitating large language model Russian adaptation with Learned Embedding Propagation // 2024 (Preprint: https://arxiv.org/abs/2412.21140)
Tikhomirov M., Chernyshev D. Impact of Tokenization on LLaMa Russian Adaptation //2023 Ivannikov Ispras Open Conference (ISPRAS). – IEEE, 2023. – С. 163-168.
## Предупреждение
Ответы модели не отражают мнения авторов, а лишь повторяют знания полученные из данных на всех этапах обучения (предобучение, смена токенизатора, обучение на инструкциях, калибровка качества ответов). Модель была получена из сторонней предобученной модели, **контроль за предобучением** которой **не является ответственностью текущих авторов**. При создании данной версии модели не производилось никаких дополнительных действий, направленных на изменение заложенных в LLM "мнений". Используйте с осторожностью.

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"bot_message_template_incomplete": "<|im_start|>{role}\n{content}",
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},
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}

7
llmtf_eval/darumeru_RWSD_total.jsonl Normal file
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{
"task_name": "darumeru/RWSD",
"results": {
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},
"leaderboard_result": 0.5441176470588235
}

18970
llmtf_eval/darumeru_cp_para_ru.jsonl Normal file
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54
llmtf_eval/darumeru_cp_para_ru_params.jsonl Normal file
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{
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}

9
llmtf_eval/darumeru_cp_para_ru_total.jsonl Normal file
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{
"task_name": "darumeru/cp_para_ru",
"results": {
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"len": 0.9990656928305265,
"lcs": 1.0
},
"leaderboard_result": 1.0
}

104760
llmtf_eval/darumeru_ruOpenBookQA.jsonl Normal file
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54
llmtf_eval/darumeru_ruOpenBookQA_params.jsonl Normal file
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{
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},
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"bot_message_template": "<|im_start|>{role}\n{content}<|im_end|>\n",
"bot_message_template_incomplete": "<|im_start|>{role}\n{content}",
"user_role": "user",
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},
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"method": "calculate_tokens_proba"
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}

8
llmtf_eval/darumeru_ruOpenBookQA_total.jsonl Normal file
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@@ -0,0 +1,8 @@
{
"task_name": "darumeru/ruOpenBookQA",
"results": {
"acc": 0.8256013745704467,
"f1_macro": 0.8262484506706507
},
"leaderboard_result": 0.8259249126205487
}

5040
llmtf_eval/darumeru_ruWorldTree.jsonl Normal file
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54
llmtf_eval/darumeru_ruWorldTree_params.jsonl Normal file
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@@ -0,0 +1,54 @@
{
"custom_generation_config": null,
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"generation_config": {
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},
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"user_message_template": "<|im_start|>{role}\n{content}<|im_end|>\n",
"bot_message_template": "<|im_start|>{role}\n{content}<|im_end|>\n",
"bot_message_template_incomplete": "<|im_start|>{role}\n{content}",
"user_role": "user",
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"suffix": "<|im_start|>assistant\n",
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"method": "calculate_tokens_proba"
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}

8
llmtf_eval/darumeru_ruWorldTree_total.jsonl Normal file
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{
"task_name": "darumeru/ruWorldTree",
"results": {
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},
"leaderboard_result": 0.9043218138382805
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251
llmtf_eval/evaluation_log.txt Normal file
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INFO: 2024-10-28 13:15:15,094: llmtf.base.evaluator: Starting eval on ['darumeru/multiq']
INFO: 2024-10-28 13:15:15,094: llmtf.base.hfmodel: Updated generation_config.eos_token_id: [147077]
INFO: 2024-10-28 13:15:15,094: llmtf.base.hfmodel: Updated generation_config.stop_strings: ['<|im_end|>']
INFO: 2024-10-28 13:15:16,695: llmtf.base.evaluator: Starting eval on ['darumeru/parus']
INFO: 2024-10-28 13:15:16,695: llmtf.base.hfmodel: Updated generation_config.eos_token_id: [147077]
INFO: 2024-10-28 13:15:16,695: llmtf.base.hfmodel: Updated generation_config.stop_strings: ['<|im_end|>']
INFO: 2024-10-28 13:15:18,943: llmtf.base.darumeru/PARus: Loading Dataset: 2.25s
INFO: 2024-10-28 13:15:19,297: llmtf.base.darumeru/MultiQ: Loading Dataset: 4.20s
INFO: 2024-10-28 13:15:22,318: llmtf.base.darumeru/PARus: Processing Dataset: 3.37s
INFO: 2024-10-28 13:15:22,318: llmtf.base.darumeru/PARus: Results for darumeru/PARus:
INFO: 2024-10-28 13:15:22,329: llmtf.base.darumeru/PARus: {'acc': 0.78}
INFO: 2024-10-28 13:15:22,330: llmtf.base.evaluator: Ended eval
INFO: 2024-10-28 13:15:22,330: llmtf.base.evaluator:
mean darumeru/PARus
0.780 0.780
INFO: 2024-10-28 13:15:30,304: llmtf.base.evaluator: Starting eval on ['darumeru/ruopenbookqa']
INFO: 2024-10-28 13:15:30,304: llmtf.base.hfmodel: Updated generation_config.eos_token_id: [147077]
INFO: 2024-10-28 13:15:30,304: llmtf.base.hfmodel: Updated generation_config.stop_strings: ['<|im_end|>']
INFO: 2024-10-28 13:15:33,637: llmtf.base.darumeru/ruOpenBookQA: Loading Dataset: 3.33s
INFO: 2024-10-28 13:16:05,173: llmtf.base.darumeru/ruOpenBookQA: Processing Dataset: 31.54s
INFO: 2024-10-28 13:16:05,173: llmtf.base.darumeru/ruOpenBookQA: Results for darumeru/ruOpenBookQA:
INFO: 2024-10-28 13:16:05,184: llmtf.base.darumeru/ruOpenBookQA: {'acc': 0.8256013745704467, 'f1_macro': 0.8262484506706507}
INFO: 2024-10-28 13:16:05,191: llmtf.base.evaluator: Ended eval
INFO: 2024-10-28 13:16:05,192: llmtf.base.evaluator:
mean darumeru/PARus darumeru/ruOpenBookQA
0.803 0.780 0.826
INFO: 2024-10-28 13:16:13,923: llmtf.base.evaluator: Starting eval on ['darumeru/rwsd']
INFO: 2024-10-28 13:16:13,923: llmtf.base.hfmodel: Updated generation_config.eos_token_id: [147077]
INFO: 2024-10-28 13:16:13,923: llmtf.base.hfmodel: Updated generation_config.stop_strings: ['<|im_end|>']
INFO: 2024-10-28 13:16:16,429: llmtf.base.darumeru/RWSD: Loading Dataset: 2.51s
INFO: 2024-10-28 13:16:22,246: llmtf.base.darumeru/RWSD: Processing Dataset: 5.82s
INFO: 2024-10-28 13:16:22,246: llmtf.base.darumeru/RWSD: Results for darumeru/RWSD:
INFO: 2024-10-28 13:16:22,247: llmtf.base.darumeru/RWSD: {'acc': 0.5441176470588235}
INFO: 2024-10-28 13:16:22,248: llmtf.base.evaluator: Ended eval
INFO: 2024-10-28 13:16:22,249: llmtf.base.evaluator:
mean darumeru/PARus darumeru/RWSD darumeru/ruOpenBookQA
0.717 0.780 0.544 0.826
INFO: 2024-10-28 13:16:31,348: llmtf.base.evaluator: Starting eval on ['nlpcoreteam/rummlu']
INFO: 2024-10-28 13:16:31,348: llmtf.base.hfmodel: Updated generation_config.eos_token_id: [147077]
INFO: 2024-10-28 13:16:31,348: llmtf.base.hfmodel: Updated generation_config.stop_strings: ['<|im_end|>']
INFO: 2024-10-28 13:18:38,554: llmtf.base.nlpcoreteam/ruMMLU: Loading Dataset: 127.21s
INFO: 2024-10-28 13:20:06,478: llmtf.base.darumeru/MultiQ: Processing Dataset: 287.18s
INFO: 2024-10-28 13:20:06,479: llmtf.base.darumeru/MultiQ: Results for darumeru/MultiQ:
INFO: 2024-10-28 13:20:06,480: llmtf.base.darumeru/MultiQ: {'f1': 0.2503859074384594, 'em': 0.14531548757170173}
INFO: 2024-10-28 13:20:06,488: llmtf.base.evaluator: Ended eval
INFO: 2024-10-28 13:20:06,489: llmtf.base.evaluator:
mean darumeru/MultiQ darumeru/PARus darumeru/RWSD darumeru/ruOpenBookQA
0.587 0.198 0.780 0.544 0.826
INFO: 2024-10-28 13:20:15,334: llmtf.base.evaluator: Starting eval on ['darumeru/rcb']
INFO: 2024-10-28 13:20:15,335: llmtf.base.hfmodel: Updated generation_config.eos_token_id: [147077]
INFO: 2024-10-28 13:20:15,335: llmtf.base.hfmodel: Updated generation_config.stop_strings: ['<|im_end|>']
INFO: 2024-10-28 13:20:18,179: llmtf.base.darumeru/RCB: Loading Dataset: 2.84s
INFO: 2024-10-28 13:20:23,505: llmtf.base.darumeru/RCB: Processing Dataset: 5.33s
INFO: 2024-10-28 13:20:23,506: llmtf.base.darumeru/RCB: Results for darumeru/RCB:
INFO: 2024-10-28 13:20:23,510: llmtf.base.darumeru/RCB: {'acc': 0.5863636363636363, 'f1_macro': 0.5032640286161413}
INFO: 2024-10-28 13:20:23,511: llmtf.base.evaluator: Ended eval
INFO: 2024-10-28 13:20:23,512: llmtf.base.evaluator:
mean darumeru/MultiQ darumeru/PARus darumeru/RCB darumeru/RWSD darumeru/ruOpenBookQA
0.579 0.198 0.780 0.545 0.544 0.826
INFO: 2024-10-28 13:20:32,046: llmtf.base.evaluator: Starting eval on ['darumeru/ruworldtree']
INFO: 2024-10-28 13:20:32,046: llmtf.base.hfmodel: Updated generation_config.eos_token_id: [147077]
INFO: 2024-10-28 13:20:32,046: llmtf.base.hfmodel: Updated generation_config.stop_strings: ['<|im_end|>']
INFO: 2024-10-28 13:20:34,403: llmtf.base.darumeru/ruWorldTree: Loading Dataset: 2.36s
INFO: 2024-10-28 13:20:36,969: llmtf.base.darumeru/ruWorldTree: Processing Dataset: 2.57s
INFO: 2024-10-28 13:20:36,969: llmtf.base.darumeru/ruWorldTree: Results for darumeru/ruWorldTree:
INFO: 2024-10-28 13:20:36,972: llmtf.base.darumeru/ruWorldTree: {'acc': 0.9047619047619048, 'f1_macro': 0.9038817229146561}
INFO: 2024-10-28 13:20:36,972: llmtf.base.evaluator: Ended eval
INFO: 2024-10-28 13:20:36,972: llmtf.base.evaluator:
mean darumeru/MultiQ darumeru/PARus darumeru/RCB darumeru/RWSD darumeru/ruOpenBookQA darumeru/ruWorldTree
0.633 0.198 0.780 0.545 0.544 0.826 0.904
INFO: 2024-10-28 13:20:45,488: llmtf.base.evaluator: Starting eval on ['daru/treewayextractive']
INFO: 2024-10-28 13:20:45,488: llmtf.base.hfmodel: Updated generation_config.eos_token_id: [147077]
INFO: 2024-10-28 13:20:45,488: llmtf.base.hfmodel: Updated generation_config.stop_strings: ['<|im_end|>']
INFO: 2024-10-28 13:20:59,443: llmtf.base.daru/treewayextractive: Loading Dataset: 13.95s
INFO: 2024-10-28 13:23:49,533: llmtf.base.nlpcoreteam/ruMMLU: Processing Dataset: 310.98s
INFO: 2024-10-28 13:23:49,533: llmtf.base.nlpcoreteam/ruMMLU: Results for nlpcoreteam/ruMMLU:
INFO: 2024-10-28 13:23:49,597: llmtf.base.nlpcoreteam/ruMMLU: metric
subject
abstract_algebra 0.480000
anatomy 0.562963
astronomy 0.769737
business_ethics 0.640000
clinical_knowledge 0.671698
college_biology 0.673611
college_chemistry 0.470000
college_computer_science 0.670000
college_mathematics 0.440000
college_medicine 0.589595
college_physics 0.480392
computer_security 0.720000
conceptual_physics 0.655319
econometrics 0.482456
electrical_engineering 0.606897
elementary_mathematics 0.616402
formal_logic 0.428571
global_facts 0.370000
high_school_biology 0.809677
high_school_chemistry 0.571429
high_school_computer_science 0.770000
high_school_european_history 0.751515
high_school_geography 0.782828
high_school_government_and_politics 0.725389
high_school_macroeconomics 0.658974
high_school_mathematics 0.525926
high_school_microeconomics 0.705882
high_school_physics 0.463576
high_school_psychology 0.796330
high_school_statistics 0.606481
high_school_us_history 0.779412
high_school_world_history 0.801688
human_aging 0.632287
human_sexuality 0.717557
international_law 0.743802
jurisprudence 0.675926
logical_fallacies 0.662577
machine_learning 0.482143
management 0.747573
marketing 0.816239
medical_genetics 0.650000
miscellaneous 0.711367
moral_disputes 0.627168
moral_scenarios 0.244693
nutrition 0.689542
philosophy 0.646302
prehistory 0.660494
professional_accounting 0.439716
professional_law 0.411343
professional_medicine 0.613971
professional_psychology 0.591503
public_relations 0.545455
security_studies 0.665306
sociology 0.736318
us_foreign_policy 0.800000
virology 0.500000
world_religions 0.760234
INFO: 2024-10-28 13:23:49,606: llmtf.base.nlpcoreteam/ruMMLU: metric
subject
STEM 0.600644
humanities 0.630286
other (business, health, misc.) 0.616782
social sciences 0.684000
INFO: 2024-10-28 13:23:49,611: llmtf.base.nlpcoreteam/ruMMLU: {'acc': 0.6329281396317665}
INFO: 2024-10-28 13:23:49,646: llmtf.base.evaluator: Ended eval
INFO: 2024-10-28 13:23:49,648: llmtf.base.evaluator:
mean darumeru/MultiQ darumeru/PARus darumeru/RCB darumeru/RWSD darumeru/ruOpenBookQA darumeru/ruWorldTree nlpcoreteam/ruMMLU
0.633 0.198 0.780 0.545 0.544 0.826 0.904 0.633
INFO: 2024-10-28 13:23:57,887: llmtf.base.evaluator: Starting eval on ['daru/treewayabstractive']
INFO: 2024-10-28 13:23:57,887: llmtf.base.hfmodel: Updated generation_config.eos_token_id: [147077]
INFO: 2024-10-28 13:23:57,887: llmtf.base.hfmodel: Updated generation_config.stop_strings: ['<|im_end|>']
INFO: 2024-10-28 13:24:02,221: llmtf.base.daru/treewayabstractive: Loading Dataset: 4.33s
INFO: 2024-10-28 13:26:15,188: llmtf.base.daru/treewayextractive: Processing Dataset: 315.74s
INFO: 2024-10-28 13:26:15,188: llmtf.base.daru/treewayextractive: Results for daru/treewayextractive:
INFO: 2024-10-28 13:26:15,447: llmtf.base.daru/treewayextractive: {'r-prec': 0.40380281385281386}
INFO: 2024-10-28 13:26:15,501: llmtf.base.evaluator: Ended eval
INFO: 2024-10-28 13:26:15,503: llmtf.base.evaluator:
mean daru/treewayextractive darumeru/MultiQ darumeru/PARus darumeru/RCB darumeru/RWSD darumeru/ruOpenBookQA darumeru/ruWorldTree nlpcoreteam/ruMMLU
0.604 0.404 0.198 0.780 0.545 0.544 0.826 0.904 0.633
INFO: 2024-10-28 13:26:24,206: llmtf.base.evaluator: Starting eval on ['nlpcoreteam/enmmlu']
INFO: 2024-10-28 13:26:24,207: llmtf.base.hfmodel: Updated generation_config.eos_token_id: [147077]
INFO: 2024-10-28 13:26:24,207: llmtf.base.hfmodel: Updated generation_config.stop_strings: ['<|im_end|>']
INFO: 2024-10-28 13:26:48,154: llmtf.base.daru/treewayabstractive: Processing Dataset: 165.93s
INFO: 2024-10-28 13:26:48,154: llmtf.base.daru/treewayabstractive: Results for daru/treewayabstractive:
INFO: 2024-10-28 13:26:48,155: llmtf.base.daru/treewayabstractive: {'rouge1': 0.3489002151166006, 'rouge2': 0.12404569962254197}
INFO: 2024-10-28 13:26:48,156: llmtf.base.evaluator: Ended eval
INFO: 2024-10-28 13:26:48,157: llmtf.base.evaluator:
mean daru/treewayabstractive daru/treewayextractive darumeru/MultiQ darumeru/PARus darumeru/RCB darumeru/RWSD darumeru/ruOpenBookQA darumeru/ruWorldTree nlpcoreteam/ruMMLU
0.563 0.236 0.404 0.198 0.780 0.545 0.544 0.826 0.904 0.633
INFO: 2024-10-28 13:28:23,832: llmtf.base.nlpcoreteam/enMMLU: Loading Dataset: 119.62s
INFO: 2024-10-28 13:33:05,781: llmtf.base.nlpcoreteam/enMMLU: Processing Dataset: 281.95s
INFO: 2024-10-28 13:33:05,781: llmtf.base.nlpcoreteam/enMMLU: Results for nlpcoreteam/enMMLU:
INFO: 2024-10-28 13:33:05,844: llmtf.base.nlpcoreteam/enMMLU: metric
subject
abstract_algebra 0.450000
anatomy 0.725926
astronomy 0.861842
business_ethics 0.750000
clinical_knowledge 0.762264
college_biology 0.854167
college_chemistry 0.510000
college_computer_science 0.720000
college_mathematics 0.470000
college_medicine 0.699422
college_physics 0.509804
computer_security 0.770000
conceptual_physics 0.706383
econometrics 0.605263
electrical_engineering 0.696552
elementary_mathematics 0.666667
formal_logic 0.492063
global_facts 0.420000
high_school_biology 0.861290
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high_school_mathematics 0.566667
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high_school_physics 0.582781
high_school_psychology 0.888073
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high_school_world_history 0.860759
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human_sexuality 0.786260
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jurisprudence 0.796296
logical_fallacies 0.828221
machine_learning 0.526786
management 0.854369
marketing 0.914530
medical_genetics 0.810000
miscellaneous 0.848020
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moral_scenarios 0.459218
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public_relations 0.636364
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sociology 0.845771
us_foreign_policy 0.850000
virology 0.506024
world_religions 0.853801
INFO: 2024-10-28 13:33:05,852: llmtf.base.nlpcoreteam/enMMLU: metric
subject
STEM 0.662331
humanities 0.733585
other (business, health, misc.) 0.724976
social sciences 0.796467
INFO: 2024-10-28 13:33:05,857: llmtf.base.nlpcoreteam/enMMLU: {'acc': 0.7293395108036221}
INFO: 2024-10-28 13:33:05,908: llmtf.base.evaluator: Ended eval
INFO: 2024-10-28 13:33:05,910: llmtf.base.evaluator:
mean daru/treewayabstractive daru/treewayextractive darumeru/MultiQ darumeru/PARus darumeru/RCB darumeru/RWSD darumeru/ruOpenBookQA darumeru/ruWorldTree nlpcoreteam/enMMLU nlpcoreteam/ruMMLU
0.580 0.236 0.404 0.198 0.780 0.545 0.544 0.826 0.904 0.729 0.633
INFO: 2024-10-28 13:33:14,562: llmtf.base.evaluator: Starting eval on ['darumeru/cp_para_ru']
INFO: 2024-10-28 13:33:14,562: llmtf.base.hfmodel: Updated generation_config.eos_token_id: [147077]
INFO: 2024-10-28 13:33:14,562: llmtf.base.hfmodel: Updated generation_config.stop_strings: ['<|im_end|>']
INFO: 2024-10-28 13:33:17,057: llmtf.base.darumeru/cp_para_ru: Loading Dataset: 2.49s
INFO: 2024-10-28 13:35:21,669: llmtf.base.darumeru/cp_para_ru: Processing Dataset: 124.61s
INFO: 2024-10-28 13:35:21,670: llmtf.base.darumeru/cp_para_ru: Results for darumeru/cp_para_ru:
INFO: 2024-10-28 13:35:21,670: llmtf.base.darumeru/cp_para_ru: {'symbol_per_token': 3.9953318595732386, 'len': 0.9990656928305265, 'lcs': 1.0}
INFO: 2024-10-28 13:35:21,671: llmtf.base.evaluator: Ended eval
INFO: 2024-10-28 13:35:21,672: llmtf.base.evaluator:
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"lstrip": false,
"normalized": false,
"rstrip": false,
"single_word": false,
"special": true
},
"147079": {
"content": "<|object_ref_end|>",
"lstrip": false,
"normalized": false,
"rstrip": false,
"single_word": false,
"special": true
},
"147080": {
"content": "<|box_start|>",
"lstrip": false,
"normalized": false,
"rstrip": false,
"single_word": false,
"special": true
},
"147081": {
"content": "<|box_end|>",
"lstrip": false,
"normalized": false,
"rstrip": false,
"single_word": false,
"special": true
},
"147082": {
"content": "<|quad_start|>",
"lstrip": false,
"normalized": false,
"rstrip": false,
"single_word": false,
"special": true
},
"147083": {
"content": "<|quad_end|>",
"lstrip": false,
"normalized": false,
"rstrip": false,
"single_word": false,
"special": true
},
"147084": {
"content": "<|vision_start|>",
"lstrip": false,
"normalized": false,
"rstrip": false,
"single_word": false,
"special": true
},
"147085": {
"content": "<|vision_end|>",
"lstrip": false,
"normalized": false,
"rstrip": false,
"single_word": false,
"special": true
},
"147086": {
"content": "<|vision_pad|>",
"lstrip": false,
"normalized": false,
"rstrip": false,
"single_word": false,
"special": true
},
"147087": {
"content": "<|image_pad|>",
"lstrip": false,
"normalized": false,
"rstrip": false,
"single_word": false,
"special": true
},
"147088": {
"content": "<|video_pad|>",
"lstrip": false,
"normalized": false,
"rstrip": false,
"single_word": false,
"special": true
},
"147089": {
"content": "<tool_call>",
"lstrip": false,
"normalized": false,
"rstrip": false,
"single_word": false,
"special": true
},
"147090": {
"content": "</tool_call>",
"lstrip": false,
"normalized": false,
"rstrip": false,
"single_word": false,
"special": true
},
"147091": {
"content": "<|fim_prefix|>",
"lstrip": false,
"normalized": false,
"rstrip": false,
"single_word": false,
"special": true
},
"147092": {
"content": "<|fim_middle|>",
"lstrip": false,
"normalized": false,
"rstrip": false,
"single_word": false,
"special": true
},
"147093": {
"content": "<|fim_suffix|>",
"lstrip": false,
"normalized": false,
"rstrip": false,
"single_word": false,
"special": true
},
"147094": {
"content": "<|fim_pad|>",
"lstrip": false,
"normalized": false,
"rstrip": false,
"single_word": false,
"special": true
},
"147095": {
"content": "<|repo_name|>",
"lstrip": false,
"normalized": false,
"rstrip": false,
"single_word": false,
"special": true
},
"147096": {
"content": "<|file_sep|>",
"lstrip": false,
"normalized": false,
"rstrip": false,
"single_word": false,
"special": true
}
},
"additional_special_tokens": [
"<|im_start|>",
"<|im_end|>",
"<|object_ref_start|>",
"<|object_ref_end|>",
"<|box_start|>",
"<|box_end|>",
"<|quad_start|>",
"<|quad_end|>",
"<|vision_start|>",
"<|vision_end|>",
"<|vision_pad|>",
"<|image_pad|>",
"<|video_pad|>"
],
"bos_token": "<|endoftext|>",
"chat_template": "{%- if tools %}\n {{- '<|im_start|>system\\n' }}\n {%- if messages[0]['role'] == 'system' %}\n {{- messages[0]['content'] }}\n {%- else %}\n {{- 'You are Qwen, created by Alibaba Cloud. You are a helpful assistant.' }}\n {%- endif %}\n {{- \"\\n\\n# Tools\\n\\nYou may call one or more functions to assist with the user query.\\n\\nYou are provided with function signatures within <tools></tools> XML tags:\\n<tools>\" }}\n {%- for tool in tools %}\n {{- \"\\n\" }}\n {{- tool | tojson }}\n {%- endfor %}\n {{- \"\\n</tools>\\n\\nFor each function call, return a json object with function name and arguments within <tool_call></tool_call> XML tags:\\n<tool_call>\\n{\\\"name\\\": <function-name>, \\\"arguments\\\": <args-json-object>}\\n</tool_call><|im_end|>\\n\" }}\n{%- else %}\n {%- if messages[0]['role'] == 'system' %}\n {{- '<|im_start|>system\\n' + messages[0]['content'] + '<|im_end|>\\n' }}\n {%- endif %}\n{%- endif %}\n{%- for message in messages %}\n {%- if (message.role == \"user\") or (message.role == \"system\" and not loop.first) or (message.role == \"assistant\" and not message.tool_calls) %}\n {{- '<|im_start|>' + message.role + '\\n' + message.content + '<|im_end|>' + '\\n' }}\n {%- elif message.role == \"assistant\" %}\n {{- '<|im_start|>' + message.role }}\n {%- if message.content %}\n {{- '\\n' + message.content }}\n {%- endif %}\n {%- for tool_call in message.tool_calls %}\n {%- if tool_call.function is defined %}\n {%- set tool_call = tool_call.function %}\n {%- endif %}\n {{- '\\n<tool_call>\\n{\"name\": \"' }}\n {{- tool_call.name }}\n {{- '\", \"arguments\": ' }}\n {{- tool_call.arguments | tojson }}\n {{- '}\\n</tool_call>' }}\n {%- endfor %}\n {{- '<|im_end|>\\n' }}\n {%- elif message.role == \"tool\" %}\n {%- if (loop.index0 == 0) or (messages[loop.index0 - 1].role != \"tool\") %}\n {{- '<|im_start|>user' }}\n {%- endif %}\n {{- '\\n<tool_response>\\n' }}\n {{- message.content }}\n {{- '\\n</tool_response>' }}\n {%- if loop.last or (messages[loop.index0 + 1].role != \"tool\") %}\n {{- '<|im_end|>\\n' }}\n {%- endif %}\n {%- endif %}\n{%- endfor %}\n{%- if add_generation_prompt %}\n {{- '<|im_start|>assistant\\n' }}\n{%- endif %}\n",
"clean_up_tokenization_spaces": false,
"eos_token": "<|im_end|>",
"errors": "replace",
"model_max_length": 131072,
"pad_token": "<|endoftext|>",
"split_special_tokens": false,
"tokenizer_class": "Qwen2Tokenizer",
"unk_token": null
}

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