Datasets:
Tasks:
Question Answering
Modalities:
Text
Formats:
csv
Languages:
Chinese
Size:
10K - 100K
License:
| license: mit | |
| license_name: mit | |
| task_categories: | |
| - question-answering | |
| language: | |
| - zh | |
| tags: | |
| - traditional chinese | |
| - finance | |
| - medical | |
| - taiwan | |
| - benchmark | |
| - zh-tw | |
| - zh-hant | |
| pretty_name: tmmlu++ | |
| size_categories: | |
| - 100K<n<1M | |
| configs: | |
| - config_name: engineering_math | |
| data_files: | |
| - split: train | |
| path: "data/engineering_math_dev.csv" | |
| - split: validation | |
| path: "data/engineering_math_val.csv" | |
| - split: test | |
| path: "data/engineering_math_test.csv" | |
| - config_name: dentistry | |
| data_files: | |
| - split: train | |
| path: "data/dentistry_dev.csv" | |
| - split: validation | |
| path: "data/dentistry_val.csv" | |
| - split: test | |
| path: "data/dentistry_test.csv" | |
| - config_name: traditional_chinese_medicine_clinical_medicine | |
| data_files: | |
| - split: train | |
| path: "data/traditional_chinese_medicine_clinical_medicine_dev.csv" | |
| - split: validation | |
| path: "data/traditional_chinese_medicine_clinical_medicine_val.csv" | |
| - split: test | |
| path: "data/traditional_chinese_medicine_clinical_medicine_test.csv" | |
| - config_name: clinical_psychology | |
| data_files: | |
| - split: train | |
| path: "data/clinical_psychology_dev.csv" | |
| - split: validation | |
| path: "data/clinical_psychology_val.csv" | |
| - split: test | |
| path: "data/clinical_psychology_test.csv" | |
| - config_name: technical | |
| data_files: | |
| - split: train | |
| path: "data/technical_dev.csv" | |
| - split: validation | |
| path: "data/technical_val.csv" | |
| - split: test | |
| path: "data/technical_test.csv" | |
| - config_name: culinary_skills | |
| data_files: | |
| - split: train | |
| path: "data/culinary_skills_dev.csv" | |
| - split: validation | |
| path: "data/culinary_skills_val.csv" | |
| - split: test | |
| path: "data/culinary_skills_test.csv" | |
| - config_name: mechanical | |
| data_files: | |
| - split: train | |
| path: "data/mechanical_dev.csv" | |
| - split: validation | |
| path: "data/mechanical_val.csv" | |
| - split: test | |
| path: "data/mechanical_test.csv" | |
| - config_name: logic_reasoning | |
| data_files: | |
| - split: train | |
| path: "data/logic_reasoning_dev.csv" | |
| - split: validation | |
| path: "data/logic_reasoning_val.csv" | |
| - split: test | |
| path: "data/logic_reasoning_test.csv" | |
| - config_name: real_estate | |
| data_files: | |
| - split: train | |
| path: "data/real_estate_dev.csv" | |
| - split: validation | |
| path: "data/real_estate_val.csv" | |
| - split: test | |
| path: "data/real_estate_test.csv" | |
| - config_name: general_principles_of_law | |
| data_files: | |
| - split: train | |
| path: "data/general_principles_of_law_dev.csv" | |
| - split: validation | |
| path: "data/general_principles_of_law_val.csv" | |
| - split: test | |
| path: "data/general_principles_of_law_test.csv" | |
| - config_name: finance_banking | |
| data_files: | |
| - split: train | |
| path: "data/finance_banking_dev.csv" | |
| - split: validation | |
| path: "data/finance_banking_val.csv" | |
| - split: test | |
| path: "data/finance_banking_test.csv" | |
| - config_name: anti_money_laundering | |
| data_files: | |
| - split: train | |
| path: "data/anti_money_laundering_dev.csv" | |
| - split: validation | |
| path: "data/anti_money_laundering_val.csv" | |
| - split: test | |
| path: "data/anti_money_laundering_test.csv" | |
| - config_name: ttqav2 | |
| data_files: | |
| - split: train | |
| path: "data/ttqav2_dev.csv" | |
| - split: validation | |
| path: "data/ttqav2_val.csv" | |
| - split: test | |
| path: "data/ttqav2_test.csv" | |
| - config_name: marketing_management | |
| data_files: | |
| - split: train | |
| path: "data/marketing_management_dev.csv" | |
| - split: validation | |
| path: "data/marketing_management_val.csv" | |
| - split: test | |
| path: "data/marketing_management_test.csv" | |
| - config_name: business_management | |
| data_files: | |
| - split: train | |
| path: "data/business_management_dev.csv" | |
| - split: validation | |
| path: "data/business_management_val.csv" | |
| - split: test | |
| path: "data/business_management_test.csv" | |
| - config_name: organic_chemistry | |
| data_files: | |
| - split: train | |
| path: "data/organic_chemistry_dev.csv" | |
| - split: validation | |
| path: "data/organic_chemistry_val.csv" | |
| - split: test | |
| path: "data/organic_chemistry_test.csv" | |
| - config_name: advance_chemistry | |
| data_files: | |
| - split: train | |
| path: "data/advance_chemistry_dev.csv" | |
| - split: validation | |
| path: "data/advance_chemistry_val.csv" | |
| - split: test | |
| path: "data/advance_chemistry_test.csv" | |
| - config_name: physics | |
| data_files: | |
| - split: train | |
| path: "data/physics_dev.csv" | |
| - split: validation | |
| path: "data/physics_val.csv" | |
| - split: test | |
| path: "data/physics_test.csv" | |
| - config_name: secondary_physics | |
| data_files: | |
| - split: train | |
| path: "data/secondary_physics_dev.csv" | |
| - split: validation | |
| path: "data/secondary_physics_val.csv" | |
| - split: test | |
| path: "data/secondary_physics_test.csv" | |
| - config_name: human_behavior | |
| data_files: | |
| - split: train | |
| path: "data/human_behavior_dev.csv" | |
| - split: validation | |
| path: "data/human_behavior_val.csv" | |
| - split: test | |
| path: "data/human_behavior_test.csv" | |
| - config_name: national_protection | |
| data_files: | |
| - split: train | |
| path: "data/national_protection_dev.csv" | |
| - split: validation | |
| path: "data/national_protection_val.csv" | |
| - split: test | |
| path: "data/national_protection_test.csv" | |
| - config_name: jce_humanities | |
| data_files: | |
| - split: train | |
| path: "data/jce_humanities_dev.csv" | |
| - split: validation | |
| path: "data/jce_humanities_val.csv" | |
| - split: test | |
| path: "data/jce_humanities_test.csv" | |
| - config_name: politic_science | |
| data_files: | |
| - split: train | |
| path: "data/politic_science_dev.csv" | |
| - split: validation | |
| path: "data/politic_science_val.csv" | |
| - split: test | |
| path: "data/politic_science_test.csv" | |
| - config_name: agriculture | |
| data_files: | |
| - split: train | |
| path: "data/agriculture_dev.csv" | |
| - split: validation | |
| path: "data/agriculture_val.csv" | |
| - split: test | |
| path: "data/agriculture_test.csv" | |
| - config_name: official_document_management | |
| data_files: | |
| - split: train | |
| path: "data/official_document_management_dev.csv" | |
| - split: validation | |
| path: "data/official_document_management_val.csv" | |
| - split: test | |
| path: "data/official_document_management_test.csv" | |
| - config_name: financial_analysis | |
| data_files: | |
| - split: train | |
| path: "data/financial_analysis_dev.csv" | |
| - split: validation | |
| path: "data/financial_analysis_val.csv" | |
| - split: test | |
| path: "data/financial_analysis_test.csv" | |
| - config_name: pharmacy | |
| data_files: | |
| - split: train | |
| path: "data/pharmacy_dev.csv" | |
| - split: validation | |
| path: "data/pharmacy_val.csv" | |
| - split: test | |
| path: "data/pharmacy_test.csv" | |
| - config_name: educational_psychology | |
| data_files: | |
| - split: train | |
| path: "data/educational_psychology_dev.csv" | |
| - split: validation | |
| path: "data/educational_psychology_val.csv" | |
| - split: test | |
| path: "data/educational_psychology_test.csv" | |
| - config_name: statistics_and_machine_learning | |
| data_files: | |
| - split: train | |
| path: "data/statistics_and_machine_learning_dev.csv" | |
| - split: validation | |
| path: "data/statistics_and_machine_learning_val.csv" | |
| - split: test | |
| path: "data/statistics_and_machine_learning_test.csv" | |
| - config_name: management_accounting | |
| data_files: | |
| - split: train | |
| path: "data/management_accounting_dev.csv" | |
| - split: validation | |
| path: "data/management_accounting_val.csv" | |
| - split: test | |
| path: "data/management_accounting_test.csv" | |
| - config_name: introduction_to_law | |
| data_files: | |
| - split: train | |
| path: "data/introduction_to_law_dev.csv" | |
| - split: validation | |
| path: "data/introduction_to_law_val.csv" | |
| - split: test | |
| path: "data/introduction_to_law_test.csv" | |
| - config_name: computer_science | |
| data_files: | |
| - split: train | |
| path: "data/computer_science_dev.csv" | |
| - split: validation | |
| path: "data/computer_science_val.csv" | |
| - split: test | |
| path: "data/computer_science_test.csv" | |
| - config_name: veterinary_pathology | |
| data_files: | |
| - split: train | |
| path: "data/veterinary_pathology_dev.csv" | |
| - split: validation | |
| path: "data/veterinary_pathology_val.csv" | |
| - split: test | |
| path: "data/veterinary_pathology_test.csv" | |
| - config_name: accounting | |
| data_files: | |
| - split: train | |
| path: "data/accounting_dev.csv" | |
| - split: validation | |
| path: "data/accounting_val.csv" | |
| - split: test | |
| path: "data/accounting_test.csv" | |
| - config_name: fire_science | |
| data_files: | |
| - split: train | |
| path: "data/fire_science_dev.csv" | |
| - split: validation | |
| path: "data/fire_science_val.csv" | |
| - split: test | |
| path: "data/fire_science_test.csv" | |
| - config_name: optometry | |
| data_files: | |
| - split: train | |
| path: "data/optometry_dev.csv" | |
| - split: validation | |
| path: "data/optometry_val.csv" | |
| - split: test | |
| path: "data/optometry_test.csv" | |
| - config_name: insurance_studies | |
| data_files: | |
| - split: train | |
| path: "data/insurance_studies_dev.csv" | |
| - split: validation | |
| path: "data/insurance_studies_val.csv" | |
| - split: test | |
| path: "data/insurance_studies_test.csv" | |
| - config_name: pharmacology | |
| data_files: | |
| - split: train | |
| path: "data/pharmacology_dev.csv" | |
| - split: validation | |
| path: "data/pharmacology_val.csv" | |
| - split: test | |
| path: "data/pharmacology_test.csv" | |
| - config_name: taxation | |
| data_files: | |
| - split: train | |
| path: "data/taxation_dev.csv" | |
| - split: validation | |
| path: "data/taxation_val.csv" | |
| - split: test | |
| path: "data/taxation_test.csv" | |
| - config_name: trust_practice | |
| data_files: | |
| - split: train | |
| path: "data/trust_practice_dev.csv" | |
| - split: validation | |
| path: "data/trust_practice_val.csv" | |
| - split: test | |
| path: "data/trust_practice_test.csv" | |
| - config_name: geography_of_taiwan | |
| data_files: | |
| - split: train | |
| path: "data/geography_of_taiwan_dev.csv" | |
| - split: validation | |
| path: "data/geography_of_taiwan_val.csv" | |
| - split: test | |
| path: "data/geography_of_taiwan_test.csv" | |
| - config_name: physical_education | |
| data_files: | |
| - split: train | |
| path: "data/physical_education_dev.csv" | |
| - split: validation | |
| path: "data/physical_education_val.csv" | |
| - split: test | |
| path: "data/physical_education_test.csv" | |
| - config_name: auditing | |
| data_files: | |
| - split: train | |
| path: "data/auditing_dev.csv" | |
| - split: validation | |
| path: "data/auditing_val.csv" | |
| - split: test | |
| path: "data/auditing_test.csv" | |
| - config_name: administrative_law | |
| data_files: | |
| - split: train | |
| path: "data/administrative_law_dev.csv" | |
| - split: validation | |
| path: "data/administrative_law_val.csv" | |
| - split: test | |
| path: "data/administrative_law_test.csv" | |
| - config_name: education_(profession_level) | |
| data_files: | |
| - split: train | |
| path: "data/education_(profession_level)_dev.csv" | |
| - split: validation | |
| path: "data/education_(profession_level)_val.csv" | |
| - split: test | |
| path: "data/education_(profession_level)_test.csv" | |
| - config_name: economics | |
| data_files: | |
| - split: train | |
| path: "data/economics_dev.csv" | |
| - split: validation | |
| path: "data/economics_val.csv" | |
| - split: test | |
| path: "data/economics_test.csv" | |
| - config_name: veterinary_pharmacology | |
| data_files: | |
| - split: train | |
| path: "data/veterinary_pharmacology_dev.csv" | |
| - split: validation | |
| path: "data/veterinary_pharmacology_val.csv" | |
| - split: test | |
| path: "data/veterinary_pharmacology_test.csv" | |
| - config_name: nautical_science | |
| data_files: | |
| - split: train | |
| path: "data/nautical_science_dev.csv" | |
| - split: validation | |
| path: "data/nautical_science_val.csv" | |
| - split: test | |
| path: "data/nautical_science_test.csv" | |
| - config_name: occupational_therapy_for_psychological_disorders | |
| data_files: | |
| - split: train | |
| path: "data/occupational_therapy_for_psychological_disorders_dev.csv" | |
| - split: validation | |
| path: "data/occupational_therapy_for_psychological_disorders_val.csv" | |
| - split: test | |
| path: "data/occupational_therapy_for_psychological_disorders_test.csv" | |
| - config_name: basic_medical_science | |
| data_files: | |
| - split: train | |
| path: "data/basic_medical_science_dev.csv" | |
| - split: validation | |
| path: "data/basic_medical_science_val.csv" | |
| - split: test | |
| path: "data/basic_medical_science_test.csv" | |
| - config_name: macroeconomics | |
| data_files: | |
| - split: train | |
| path: "data/macroeconomics_dev.csv" | |
| - split: validation | |
| path: "data/macroeconomics_val.csv" | |
| - split: test | |
| path: "data/macroeconomics_test.csv" | |
| - config_name: trade | |
| data_files: | |
| - split: train | |
| path: "data/trade_dev.csv" | |
| - split: validation | |
| path: "data/trade_val.csv" | |
| - split: test | |
| path: "data/trade_test.csv" | |
| - config_name: chinese_language_and_literature | |
| data_files: | |
| - split: train | |
| path: "data/chinese_language_and_literature_dev.csv" | |
| - split: validation | |
| path: "data/chinese_language_and_literature_val.csv" | |
| - split: test | |
| path: "data/chinese_language_and_literature_test.csv" | |
| - config_name: tve_design | |
| data_files: | |
| - split: train | |
| path: "data/tve_design_dev.csv" | |
| - split: validation | |
| path: "data/tve_design_val.csv" | |
| - split: test | |
| path: "data/tve_design_test.csv" | |
| - config_name: junior_science_exam | |
| data_files: | |
| - split: train | |
| path: "data/junior_science_exam_dev.csv" | |
| - split: validation | |
| path: "data/junior_science_exam_val.csv" | |
| - split: test | |
| path: "data/junior_science_exam_test.csv" | |
| - config_name: junior_math_exam | |
| data_files: | |
| - split: train | |
| path: "data/junior_math_exam_dev.csv" | |
| - split: validation | |
| path: "data/junior_math_exam_val.csv" | |
| - split: test | |
| path: "data/junior_math_exam_test.csv" | |
| - config_name: junior_chinese_exam | |
| data_files: | |
| - split: train | |
| path: "data/junior_chinese_exam_dev.csv" | |
| - split: validation | |
| path: "data/junior_chinese_exam_val.csv" | |
| - split: test | |
| path: "data/junior_chinese_exam_test.csv" | |
| - config_name: junior_social_studies | |
| data_files: | |
| - split: train | |
| path: "data/junior_social_studies_dev.csv" | |
| - split: validation | |
| path: "data/junior_social_studies_val.csv" | |
| - split: test | |
| path: "data/junior_social_studies_test.csv" | |
| - config_name: tve_mathematics | |
| data_files: | |
| - split: train | |
| path: "data/tve_mathematics_dev.csv" | |
| - split: validation | |
| path: "data/tve_mathematics_val.csv" | |
| - split: test | |
| path: "data/tve_mathematics_test.csv" | |
| - config_name: tve_chinese_language | |
| data_files: | |
| - split: train | |
| path: "data/tve_chinese_language_dev.csv" | |
| - split: validation | |
| path: "data/tve_chinese_language_val.csv" | |
| - split: test | |
| path: "data/tve_chinese_language_test.csv" | |
| - config_name: tve_natural_sciences | |
| data_files: | |
| - split: train | |
| path: "data/tve_natural_sciences_dev.csv" | |
| - split: validation | |
| path: "data/tve_natural_sciences_val.csv" | |
| - split: test | |
| path: "data/tve_natural_sciences_test.csv" | |
| - config_name: junior_chemistry | |
| data_files: | |
| - split: train | |
| path: "data/junior_chemistry_dev.csv" | |
| - split: validation | |
| path: "data/junior_chemistry_val.csv" | |
| - split: test | |
| path: "data/junior_chemistry_test.csv" | |
| - config_name: music | |
| data_files: | |
| - split: train | |
| path: "data/music_dev.csv" | |
| - split: validation | |
| path: "data/music_val.csv" | |
| - split: test | |
| path: "data/music_test.csv" | |
| - config_name: education | |
| data_files: | |
| - split: train | |
| path: "data/education_dev.csv" | |
| - split: validation | |
| path: "data/education_val.csv" | |
| - split: test | |
| path: "data/education_test.csv" | |
| - config_name: three_principles_of_people | |
| data_files: | |
| - split: train | |
| path: "data/three_principles_of_people_dev.csv" | |
| - split: validation | |
| path: "data/three_principles_of_people_val.csv" | |
| - split: test | |
| path: "data/three_principles_of_people_test.csv" | |
| - config_name: taiwanese_hokkien | |
| data_files: | |
| - split: train | |
| path: "data/taiwanese_hokkien_dev.csv" | |
| - split: validation | |
| path: "data/taiwanese_hokkien_val.csv" | |
| - split: test | |
| path: "data/taiwanese_hokkien_test.csv" | |
| # TMMLU+ : Large scale traditional chinese massive multitask language understanding | |
| <p align="center"> | |
| <img src="https://huggingface.co/datasets/ikala/tmmluplus/resolve/main/cover.png" alt="A close-up image of a neat paper note with a white background. The text 'TMMLU+' is written horizontally across the center of the note in bold, black. Join us to work in multimodal LLM : https://ikala.ai/recruit/" style="max-width: 400" width=400 /> | |
| </p> | |
| We present TMMLU+, a traditional Chinese massive multitask language understanding dataset. TMMLU+ is a multiple-choice question-answering dataset featuring 66 subjects, ranging from elementary to professional level. | |
| The TMMLU+ dataset is six times larger and contains more balanced subjects compared to its predecessor, [TMMLU](https://github.com/mtkresearch/MR-Models/tree/main/TC-Eval/data/TMMLU). We have included benchmark results in TMMLU+ from closed-source models and 20 open-weight Chinese large language models, with parameters ranging from 1.8B to 72B. The benchmark results show that Traditional Chinese variants still lag behind those trained on major Simplified Chinese models. | |
| ```python | |
| from datasets import load_dataset | |
| task_list = [ | |
| 'engineering_math', 'dentistry', 'traditional_chinese_medicine_clinical_medicine', 'clinical_psychology', 'technical', 'culinary_skills', 'mechanical', 'logic_reasoning', 'real_estate', | |
| 'general_principles_of_law', 'finance_banking', 'anti_money_laundering', 'ttqav2', 'marketing_management', 'business_management', 'organic_chemistry', 'advance_chemistry', | |
| 'physics', 'secondary_physics', 'human_behavior', 'national_protection', 'jce_humanities', 'politic_science', 'agriculture', 'official_document_management', | |
| 'financial_analysis', 'pharmacy', 'educational_psychology', 'statistics_and_machine_learning', 'management_accounting', 'introduction_to_law', 'computer_science', 'veterinary_pathology', | |
| 'accounting', 'fire_science', 'optometry', 'insurance_studies', 'pharmacology', 'taxation', 'trust_practice', 'geography_of_taiwan', 'physical_education', 'auditing', 'administrative_law', | |
| 'education_(profession_level)', 'economics', 'veterinary_pharmacology', 'nautical_science', 'occupational_therapy_for_psychological_disorders', | |
| 'basic_medical_science', 'macroeconomics', 'trade', 'chinese_language_and_literature', 'tve_design', 'junior_science_exam', 'junior_math_exam', 'junior_chinese_exam', | |
| 'junior_social_studies', 'tve_mathematics', 'tve_chinese_language', 'tve_natural_sciences', 'junior_chemistry', 'music', 'education', 'three_principles_of_people', | |
| 'taiwanese_hokkien' | |
| ] | |
| for task in task_list: | |
| val = load_dataset('ikala/tmmluplus', task)['validation'] | |
| dev = load_dataset('ikala/tmmluplus', task)['train'] | |
| test = load_dataset('ikala/tmmluplus', task)['test'] | |
| ``` | |
| For each dataset split | |
| ```python | |
| for row in test: | |
| print(row) | |
| break | |
| >> Dataset({ | |
| features: ['question', 'A', 'B', 'C', 'D', 'answer'], | |
| num_rows: 11 | |
| }) | |
| ``` | |
| Statistic on all four categories : STEM, Social Science, Humanities, Other | |
| | Category | Test | Dev | Validation | | |
| |----------------------------------|-------|------|------------| | |
| | STEM | 3458 | 70 | 385 | | |
| | Social Sciences | 5958 | 90 | 665 | | |
| | Humanities | 1763 | 35 | 197 | | |
| | Other (Business, Health, Misc.) | 8939 | 135 | 995 | | |
| | **Total** | 20118 | 330 | 2242 | | |
| ## Benchmark on direct prompting | |
| | model | STEM | Social Science | Humanities | Other | Average | | |
| |------------|------------|------------|------------|------------|------------| | |
| |Gemini-1.5-pro | 66.18|70.29|61.84|60.30|64.65| | |
| | [Qwen/Qwen-72B](https://huggingface.co/Qwen/Qwen-72B) | 61.12 | 71.65 | 63.00 | 61.31 |64.27| | |
| | gpt-4-0613 | 60.36 | 67.36 | 56.03 | 57.62 |60.34| | |
| | Qwen-max | 59.92 | 66.95 | 57.43 | 56.48 |60.20| | |
| | [Qwen/Qwen-72B-Chat](https://huggingface.co/Qwen/Qwen-72B-Chat) | 55.15 | 66.20 | 55.65 | 57.19 |58.55| | |
| | [Qwen/Qwen-14B](https://huggingface.co/Qwen/Qwen-14B) | 46.94 | 56.69 | 49.43 | 48.81 |50.47| | |
| | Gemini-pro | 45.38 | 57.29 | 48.80 | 48.21 |49.92| | |
| | [01-ai/Yi-34B-Chat](https://huggingface.co/01-ai/Yi-34B-Chat) | 40.24 | 56.77 | 53.99 | 47.58 |49.64| | |
| | Gemini-1.5-flash |53.47|53.42|42.99|46.56|49.11| | |
| | [Reka Flash](https://www.reka.ai/)|45.26|52.91|46.31|43.76|47.06| | |
| | [Qwen/Qwen-14B-Chat](https://huggingface.co/Qwen/Qwen-14B-Chat) | 43.86 | 53.29 | 44.78 | 45.13 |46.77| | |
| | [Qwen/Qwen1.5-14B-Chat](https://huggingface.co/Qwen/Qwen1.5-14B-Chat)|39.65|52.76|43.90|44.95|45.31| | |
| | [01-ai/Yi-6B-Chat](https://huggingface.co/01-ai/Yi-6B-Chat) | 39.62 | 50.24 | 44.44 | 44.26 |44.64| | |
| | Claude-1.3 | 42.65 | 49.33 | 42.16 | 44.14 |44.57| | |
| | [MediaTek-Research/Breeze-7B-Instruct-v0_1](https://huggingface.co/MediaTek-Research/Breeze-7B-Instruct-v0_1)| 36.46 | 48.38 |45.11 |40.75 | 42.67 | | |
| | gpt-3.5-turbo-0613 | 41.56 | 46.72 | 36.73 | 42.03 |41.76| | |
| | [CausalLM/14B](https://huggingface.co/CausalLM/14B) | 39.83 | 44.50 | 39.61 | 41.97 |41.48| | |
| | [Skywork/Skywork-13B-base](https://huggingface.co/Skywork/Skywork-13B-base) | 36.93 | 47.27 | 41.04 | 40.10 |41.33| | |
| | Claude-3-opus |42.95|45.49|35.79|40.24|41.12| | |
| | [Qwen/Qwen-7B](https://huggingface.co/Qwen/Qwen-7B) | 37.53 | 45.48 | 38.09 | 38.96 |40.01| | |
| | [meta-llama/Llama-3-70b-chat-hf](https://docs.together.ai/docs/inference-models) | 34.44 | 47.02 | 37.50 |39.51 | 39.62 | | |
| | [Qwen/Qwen-7B-Chat](https://huggingface.co/Qwen/Qwen-7B-Chat) | 33.32 | 44.64 | 40.27 | 39.89 |39.53| | |
| | [vivo-ai/BlueLM-7B-Base](https://huggingface.co/vivo-ai/BlueLM-7B-Base) | 33.94 | 41.52 | 37.38 | 38.74 |37.90| | |
| | [baichuan-inc/Baichuan2-13B-Chat](https://huggingface.co/baichuan-inc/Baichuan2-13B-Chat) | 29.64 | 43.73 | 37.36 | 39.88 |37.65| | |
| | [Qwen/Qwen-1_8B](https://huggingface.co/Qwen/Qwen-1_8B) | 32.65 | 38.95 | 38.34 | 35.27 |36.30| | |
| | Claude-2 | 39.65 | 39.09 | 28.59 | 37.47 |36.20| | |
| | [THUDM/chatglm3-6b](https://huggingface.co/THUDM/chatglm3-6b) | 31.05 | 39.31 | 35.64 | 35.60 |35.40| | |
| | [deepseek-ai/deepseek-llm-7b-chat](https://huggingface.co/deepseek-ai/deepseek-llm-7b-chat) | 29.82 | 42.29 | 34.24 | 34.31 |35.17| | |
| | [CausalLM/7B](https://huggingface.co/CausalLM/7B) | 31.03 | 38.17 | 35.87 | 35.39 |35.11| | |
| | [Azure99/blossom-v3_1-mistral-7b](https://huggingface.co/Azure99/blossom-v3_1-mistral-7b) | 32.80 | 36.91 | 32.36 | 34.53 |34.15| | |
| | [google/gemma-7b-it](https://huggingface.co/google/gemma-7b-it) | 31.89 | 35.70 | 34.00 | 33.79 | 33.84 | | |
| | [Reka Edge](https://www.reka.ai/)|30.02|39.40|31.84|32.36|33.41| | |
| | [microsoft/Orca-2-13b](https://huggingface.co/microsoft/Orca-2-13b) | 24.69 | 39.18 | 33.60 | 31.99 |32.37| | |
| | [Qwen/Qwen-1_8B-Chat](https://huggingface.co/Qwen/Qwen-1_8B-Chat) | 26.60 | 36.36 | 31.81 | 31.96 |31.68| | |
| | [meta-llama/Llama-3-8b-chat-hf](https://docs.together.ai/docs/inference-models) | 31.52 | 34.19 | 28.91 | 31.79 | 31.60 | | |
| | [TigerResearch/tigerbot-13b-chat-v3](https://huggingface.co/TigerResearch/tigerbot-13b-chat-v3) | 24.73 | 29.63 | 25.72 | 27.22 |26.82| | |
| | [hongyin/mistral-7b-80k](https://huggingface.co/hongyin/mistral-7b-80k) | 24.26 | 23.76 | 22.56 | 24.57 |23.79| | |
| | [deepseek-ai/deepseek-llm-67b-chat](https://huggingface.co/deepseek-ai/deepseek-llm-67b-chat) | 19.10 | 26.06 | 21.51 | 21.77 |22.11| | |
| | [yentinglin/Taiwan-LLM-13B-v2.0-chat](https://huggingface.co/yentinglin/Taiwan-LLM-13B-v2.0-chat) | 18.53 | 27.65 | 17.77 | 21.49 |21.36| | |
| | [GeneZC/MiniChat-3B](https://huggingface.co/GeneZC/MiniChat-3B) | 17.66 | 23.35 | 22.71 | 20.34 |21.02| | |
| | [LinkSoul/Chinese-Llama-2-7b](https://huggingface.co/LinkSoul/Chinese-Llama-2-7b) | 16.55 | 18.39 | 12.97 | 16.13 |16.01| | |
| | [yentinglin/Taiwan-LLM-7B-v2.1-chat](https://huggingface.co/yentinglin/Taiwan-LLM-7B-v2.1-chat) | 14.99 | 16.23 | 15.00 | 16.22 |15.61| | |
| | Claude-instant-1 | 12.52 | 17.13 | 15.10 | 13.57 |14.58| | |
| | [FlagAlpha/Atom-7B](https://huggingface.co/FlagAlpha/Atom-7B) | 5.60 | 13.57 | 7.71 | 11.84 |9.68| | |
| Results via [ievals](https://github.com/iKala/ievals) ( settings : 0-shot direct answering ) | |
| # Citation | |
| ``` | |
| @article{ikala2024improved, | |
| title={An Improved Traditional Chinese Evaluation Suite for Foundation Model}, | |
| author={Tam, Zhi-Rui and Pai, Ya-Ting and Lee, Yen-Wei and Cheng, Sega and Shuai, Hong-Han}, | |
| journal={arXiv preprint arXiv:2403.01858}, | |
| year={2024} | |
| } | |
| ``` | |