Qwen3-1.7B

MERA Создан 19.03.2026 21:26
0.316
Общий результат

Оценки по задачам лидерборда

Таблица скроллится влево

Задача Результат Метрика
YABLoCo 0.038 / 0.005
EM pass@k
stRuCom 0.21
chrF
RealCode 0.004 / 0.951
pass@k execution_success
UnitTests 0.249
CodeBLEU
ruCodeEval 0.502 / 0.609 / 0.652
pass@k
JavaTestGen 0.066 / 0.198
pass@k compile@1
ruHumanEval 0.666 / 0.764 / 0.78
pass@k
RealCodeJava 0.178 / 0.966
pass@k execution_success
CodeLinterEval 0.422 / 0.575 / 0.636
pass@k
ruCodeReviewer 0.037 / 0.188 / 0.01 / 0.052 / 0.065
chrF BLEU judge@1 judge@5 judge@10
CodeCorrectness 0.741
EM

Информация о сабмите

Версия MERA
v1.0.0
Версия Torch
2.9.1
Версия кодовой базы
7c56310
Версия CUDA
12.8
Precision весов модели
bfloat16
Сид
1234
Батч
1
Версия transformers
4.56.1
Количество GPU и их тип
1 x NVIDIA A100-SXM4-80GB
Архитектура
local-chat-completions

Команда:

MERA

Название ML-модели:

Qwen3-1.7B

Ссылка на ML-модель:

https://huggingface.co/Qwen/Qwen3-1.7B

Размер модели

1.7B

Тип модели:

Открытая

SFT

Дополнительные ссылки:

https://arxiv.org/abs/2505.09388

Описание архитектуры:

Qwen3-1.7B is a decoder-only transformer language model from the Qwen3 family with approximately 1.7 billion parameters. The model is designed for general language understanding and generation tasks, supporting multilingual capabilities and long-context inputs.

Описание обучения:

The model follows the standard Qwen3 multi-stage training pipeline, including large-scale pretraining followed by post-training stages such as instruction tuning and alignment to improve instruction following and response quality.

Данные претрейна:

The model was pretrained on a large multilingual corpus of approximately 36 trillion tokens covering 119 languages. It was further post-trained on instruction-following and reasoning-oriented datasets to improve instruction following and reasoning performance.

Лицензия:

Apache License 2.0

Параметры инференса

Параметры генерации:
codecorrectness - until=["<|im_end|>"];do_sample=false;temperature=0;max_gen_toks=10000; \ncodelintereval - do_sample=true;temperature=0.6;max_gen_toks=10000;until=["<|im_end|>"]; \njavatestgen - do_sample=true;max_gen_toks=10000;temperature=0.2;top_p=0.9;until=["<|im_end|>"]; \nrealcode - do_sample=true;max_gen_toks=10000;temperature=0.7;repetition_penalty=1.05;top_p=0.8;until=["<|im_end|>"]; \nrealcodejava - do_sample=true;max_gen_toks=10000;temperature=0.7;repetition_penalty=1.05;top_p=0.8;until=["<|im_end|>"]; \nrucodeeval_code - do_sample=true;temperature=0.6;max_gen_toks=10000;until=["<|im_end|>"]; \nrucodereviewer - temperature=0;do_sample=false;max_gen_toks=10000;until=["<|im_end|>"]; \nruhumaneval_code - do_sample=true;temperature=0.6;max_gen_toks=10000;until=["<|im_end|>"]; \nstrucom - do_sample=false;max_gen_toks=10000;until=["<|im_end|>"]; \nunittests - do_sample=false;max_gen_toks=10000;until=["<|im_end|>"]; \nyabloco_oracle - max_gen_toks=10000;do_sample=false;until=["<|im_end|>"];

Описание темплейта:
{%- if tools %} {{- '<|im_start|>system \n' }} {%- if messages[0].role == 'system' %} {{- messages[0].content + ' \n \n' }} {%- endif %} {{- "# 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>" }} {%- for tool in tools %} {{- " \n" }} {{- tool | tojson }} {%- endfor %} {{- " \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" }} {%- else %} {%- if messages[0].role == 'system' %} {{- '<|im_start|>system \n' + messages[0].content + '<|im_end|> \n' }} {%- endif %} {%- endif %} {%- set ns = namespace(multi_step_tool=true, last_query_index=messages|length - 1) %} {%- for message in messages[::-1] %} {%- set index = (messages|length - 1) - loop.index0 %} {%- if ns.multi_step_tool and message.role == "user" and message.content is string and not(message.content.startswith('<tool_response>') and message.content.endswith('</tool_response>')) %} {%- set ns.multi_step_tool = false %} {%- set ns.last_query_index = index %} {%- endif %} {%- endfor %} {%- for message in messages %} {%- if message.content is string %} {%- set content = message.content %} {%- else %} {%- set content = '' %} {%- endif %} {%- if (message.role == "user") or (message.role == "system" and not loop.first) %} {{- '<|im_start|>' + message.role + ' \n' + content + '<|im_end|>' + ' \n' }} {%- elif message.role == "assistant" %} {%- set reasoning_content = '' %} {%- if message.reasoning_content is string %} {%- set reasoning_content = message.reasoning_content %} {%- else %} {%- if '</think>' in content %} {%- set reasoning_content = content.split('</think>')[0].rstrip(' \n').split('<think>')[-1].lstrip(' \n') %} {%- set content = content.split('</think>')[-1].lstrip(' \n') %} {%- endif %} {%- endif %} {%- if loop.index0 > ns.last_query_index %} {%- if loop.last or (not loop.last and reasoning_content) %} {{- '<|im_start|>' + message.role + ' \n<think> \n' + reasoning_content.strip(' \n') + ' \n</think> \n \n' + content.lstrip(' \n') }} {%- else %} {{- '<|im_start|>' + message.role + ' \n' + content }} {%- endif %} {%- else %} {{- '<|im_start|>' + message.role + ' \n' + content }} {%- endif %} {%- if message.tool_calls %} {%- for tool_call in message.tool_calls %} {%- if (loop.first and content) or (not loop.first) %} {{- ' \n' }} {%- endif %} {%- if tool_call.function %} {%- set tool_call = tool_call.function %} {%- endif %} {{- '<tool_call> \n{"name": "' }} {{- tool_call.name }} {{- '", "arguments": ' }} {%- if tool_call.arguments is string %} {{- tool_call.arguments }} {%- else %} {{- tool_call.arguments | tojson }} {%- endif %} {{- '} \n</tool_call>' }} {%- endfor %} {%- endif %} {{- '<|im_end|> \n' }} {%- elif message.role == "tool" %} {%- if loop.first or (messages[loop.index0 - 1].role != "tool") %} {{- '<|im_start|>user' }} {%- endif %} {{- ' \n<tool_response> \n' }} {{- content }} {{- ' \n</tool_response>' }} {%- if loop.last or (messages[loop.index0 + 1].role != "tool") %} {{- '<|im_end|> \n' }} {%- endif %} {%- endif %} {%- endfor %} {%- if add_generation_prompt %} {{- '<|im_start|>assistant \n' }} {%- if enable_thinking is defined and enable_thinking is false %} {{- '<think> \n \n</think> \n \n' }} {%- endif %} {%- endif %}