BhashaBench-V1 (Ayurveda)#
Overview#
BhashaBench-Ayur is the predecessor of BhashaBench-Multi’s ayur domain: a domain-specific multiple-choice benchmark evaluating LLM knowledge of Ayurvedic medicine, covering English and Hindi.
Task Description#
Task Type: Domain-Specific Multiple-Choice Question Answering
Input: An Ayurvedic medicine question with 4 answer choices, in English or Hindi
Output: Correct answer letter
Languages: English, Hindi
Key Features#
5,600–17,000 questions per language, covering English and Hindi only
Predecessor of BhashaBench-Multi: same domains, narrower language coverage
Each domain is a separate repository, with English and Hindi as separate configs
Evaluation Notes#
Default configuration uses 0-shot evaluation (test split, the only split available)
Use
subset_listto evaluate a single language (e.g.,['Hindi'])Requires access to this gated dataset - on ModelScope (the default hub), accept the terms and ensure you’re logged in; alternatively, set
dataset_hubtohuggingfaceand useHF_TOKENafter accepting the terms on huggingface.coFor broader language coverage of the same domain, see
bhasha_bench_multi_ayur(22 Indic languages, not gated)
Properties#
Property |
Value |
|---|---|
Benchmark Name |
|
Dataset ID |
|
Paper |
N/A |
Tags |
|
Metrics |
|
Default Shots |
0-shot |
Evaluation Split |
|
Data Statistics#
Metric |
Value |
|---|---|
Total Samples |
14,963 |
Prompt Length (Mean) |
307.52 chars |
Prompt Length (Min/Max) |
222 / 1060 chars |
Per-Subset Statistics:
Subset |
Samples |
Prompt Mean |
Prompt Min |
Prompt Max |
|---|---|---|---|---|
|
9,348 |
310.35 |
227 |
1060 |
|
5,615 |
302.81 |
222 |
938 |
Sample Example#
Subset: English
{
"input": [
{
"id": "6a6db8b7",
"content": "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 A,B,C,D.\n\nImmune disorders include .....,\n\nA) Hypersensitivity\nB) auto-immune diseases\nC) immunodeficiency\nD) all of these"
}
],
"choices": [
"Hypersensitivity",
"auto-immune diseases",
"immunodeficiency",
"all of these"
],
"target": "D",
"id": 0,
"group_id": 0,
"metadata": {
"language": "English",
"topic": "Kayachikitsa"
}
}
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 bhashabenchv1_ayur \
--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=['bhashabenchv1_ayur'],
dataset_args={
'bhashabenchv1_ayur': {
# subset_list: ['English', 'Hindi'] # optional, evaluate specific subsets
}
},
limit=10, # Remove this line for formal evaluation
)
run_task(task_cfg=task_cfg)