sora 13274243a0 Bump vendored EvalScope and add K3-ready DPV4 configs.

Keep K3 suite selection and report-schema scoring in bash, merge K3/vision dataset_args into dpv4 yamls, and pin EvalScope at 735d920ee911 with local patches.

Co-authored-by: Cursor <cursoragent@cursor.com>

2026-09-02 07:30:48 +00:00

2.8 KiB

Raw Blame History

BhashaBench-Multi (Finance)

Overview

BhashaBench-Multi (Finance) is a domain-specific multiple-choice benchmark evaluating LLM knowledge of finance across 22 Indic languages. Each question originates in English and is machine translated (with LLM-judged translation quality scores) into the target language; this adapter uses the translated question/choices.

Task Description

Task Type: Domain-Specific Multiple-Choice Question Answering
Input: A finance question with 4 answer choices, in one of 22 Indic languages
Output: Correct answer letter
Languages: Assamese, Bengali, Bodo, Dogri, Gujarati, Hindi, Kannada, Kashmiri, Konkani, Maithili, Malayalam, Manipuri, Marathi, Nepali, Oriya, Punjabi, Sanskrit, Santhali, Sindhi, Tamil, Telugu, Urdu

Key Features

~14,963 questions per language across 22 Indic languages per domain (~330k total per domain)
Machine-translated from English with LLM-judged translation quality scores
22 scheduled languages of India, all in native script; no English split
Four domains available as separate benchmarks: Ayurveda, Finance, Krishi, Legal

Evaluation Notes

Default configuration uses 0-shot evaluation (test split, the only split available)
Use subset_list to evaluate specific languages (e.g., ['Hindi', 'Tamil']), or limit to cap sample count — each domain is ~14,963 questions per language across 22 languages (~330k total), so evaluating every language's full split is a large run
No English split exists for this dataset

Properties

Property	Value
Benchmark Name	`bhasha_bench_multi_finance`
Dataset ID	bharatgenai/BhashaBench-Multi
Paper	N/A
Tags	`Knowledge`, `MCQ`, `MultiLingual`
Metrics	`accuracy`
Default Shots	0-shot
Evaluation Split	`test`

Data Statistics

Statistics not available.

Sample Example

Sample example not available.

Prompt Template

Prompt Template:

Answer the following multiple choice question. The entire content of your response should be of the following format: 'ANSWER: [LETTER]' (without quotes) where [LETTER] is one of {letters}.

{question}

{choices}

Usage

Using CLI

evalscope eval \
    --model YOUR_MODEL \
    --api-url OPENAI_API_COMPAT_URL \
    --api-key EMPTY_TOKEN \
    --datasets bhasha_bench_multi_finance \
    --limit 10  # Remove this line for formal evaluation

Using Python

from evalscope import run_task
from evalscope.config import TaskConfig

task_cfg = TaskConfig(
    model='YOUR_MODEL',
    api_url='OPENAI_API_COMPAT_URL',
    api_key='EMPTY_TOKEN',
    datasets=['bhasha_bench_multi_finance'],
    limit=10,  # Remove this line for formal evaluation
)

run_task(task_cfg=task_cfg)

2.8 KiB Raw Blame History