13274243a0
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>
132 lines
3.9 KiB
Markdown
132 lines
3.9 KiB
Markdown
# TriviaQA-Indic-MCQ
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## Overview
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TriviaQA-Indic-MCQ reformats TriviaQA trivia questions as 4-way multiple-choice questions, translated
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into 10 Indic languages plus English, for evaluating multilingual world-knowledge recall.
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## Task Description
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- **Task Type**: Multilingual Multiple-Choice Trivia Question Answering
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- **Input**: Trivia question with 4 answer choices in one of 11 languages
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- **Output**: Correct answer letter
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- **Languages**: Bengali, English, Gujarati, Hindi, Kannada, Malayalam, Marathi, Odia, Punjabi, Tamil, Telugu
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## Evaluation Notes
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- Default configuration uses **0-shot** evaluation (validation split, the only split available)
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- Use `subset_list` to evaluate specific languages (e.g., `['hi', 'ta']`), or `limit` to cap sample
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count — the full default run is ~18k samples per language across all 11 languages (~198k total)
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## Properties
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| Property | Value |
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|----------|-------|
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| **Benchmark Name** | `triviaqa_indic` |
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| **Dataset ID** | [sarvamai/trivia-qa-indic-mcq](https://modelscope.cn/datasets/sarvamai/trivia-qa-indic-mcq/summary) |
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| **Paper** | N/A |
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| **Tags** | `Knowledge`, `MCQ`, `MultiLingual` |
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| **Metrics** | `accuracy` |
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| **Default Shots** | 0-shot |
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| **Evaluation Split** | `validation` |
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## Data Statistics
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| Metric | Value |
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|--------|-------|
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| Total Samples | 197,384 |
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| Prompt Length (Mean) | 353.95 chars |
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| Prompt Length (Min/Max) | 247 / 1267 chars |
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**Per-Subset Statistics:**
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| Subset | Samples | Prompt Mean | Prompt Min | Prompt Max |
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|--------|---------|-------------|------------|------------|
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| `bn` | 17,944 | 351.81 | 253 | 1131 |
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| `en` | 17,944 | 347.69 | 256 | 1158 |
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| `gu` | 17,944 | 347.73 | 247 | 1117 |
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| `hi` | 17,944 | 349.05 | 258 | 1141 |
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| `kn` | 17,944 | 359.89 | 253 | 1164 |
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| `ml` | 17,944 | 366.11 | 257 | 1267 |
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| `mr` | 17,944 | 350.9 | 253 | 1078 |
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| `or` | 17,944 | 349.44 | 255 | 941 |
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| `pa` | 17,944 | 345.48 | 253 | 1157 |
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| `ta` | 17,944 | 368.55 | 248 | 1198 |
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| `te` | 17,944 | 356.75 | 254 | 1259 |
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## Sample Example
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**Subset**: `bn`
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```json
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{
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"input": [
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{
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"id": "eff7630c",
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"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\nচিপমঙ্কসের পিছনে লোকটি কে ছিল?\n\nA) ডেভিড সেভিল\nB) জাগরেব শহর - ক্রোয়েশিয়া প্রজাতন্ত্র\nC) পবিত্র ক্রুসেড\nD) উপাদান (অ্যালবাম)"
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}
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],
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"choices": [
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"ডেভিড সেভিল",
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"জাগরেব শহর - ক্রোয়েশিয়া প্রজাতন্ত্র",
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"পবিত্র ক্রুসেড",
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"উপাদান (অ্যালবাম)"
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],
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"target": "A",
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"id": 0,
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"group_id": 0,
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"metadata": {
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"language": "Bengali"
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}
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}
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```
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## Prompt Template
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**Prompt Template:**
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```text
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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}.
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{question}
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{choices}
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```
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## Usage
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### Using CLI
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```bash
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evalscope eval \
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--model YOUR_MODEL \
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--api-url OPENAI_API_COMPAT_URL \
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--api-key EMPTY_TOKEN \
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--datasets triviaqa_indic \
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--limit 10 # Remove this line for formal evaluation
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```
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### Using Python
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```python
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from evalscope import run_task
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from evalscope.config import TaskConfig
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task_cfg = TaskConfig(
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model='YOUR_MODEL',
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api_url='OPENAI_API_COMPAT_URL',
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api_key='EMPTY_TOKEN',
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datasets=['triviaqa_indic'],
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dataset_args={
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'triviaqa_indic': {
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# subset_list: ['bn', 'en', 'gu'] # optional, evaluate specific subsets
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}
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},
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limit=10, # Remove this line for formal evaluation
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)
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run_task(task_cfg=task_cfg)
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```
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