saidutta69/odia-eval-benchmark

Odia Eval Benchmark

125,243 evaluation samples across 33 datasets. Zero gating. Zero waiting. Just download and eval.

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Why This Is The #1 Odia Evaluation Benchmark

Before this dataset, evaluating Odia language models meant hunting down individual repos, figuring out each one's format, dealing with broken loaders, and keeping track of what you've already tested. This is the first and only unified Odia eval benchmark.

Factor	Every Other Option	This Dataset
Total samples	Scattered across ~30 standalone repos	124,249 in one place
Task diversity	Each dataset covers 1 task	9 task types (MCQ, QA, math, translation, classification, generation, NER, paraphrasing, summarization)
Load time	pip install per repo + format-specific parsing	One load_dataset() call
Schema	30 different column names and structures	Unified schema with 15 fields
Eval harness	None -- write per-dataset scripts	Bundled (scripts/eval_harness.py)
Quality mix	No comparison possible	3 tiers: professional translation (43K), native Odia (43K), NLLB (15K)
Install	30+ pip install datasets[...]	pip install datasets
Access	Some gated, some broken loaders	All public, all working
NER coverage	153 samples (IndicGLUE only)	1,147 samples (IndicGLUE + Naamapadam)

No other Odia eval benchmark has all three of: unified schema, bundled eval harness, and multi-tiers of quality with professional translations.

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What's In This Beast

Metric	Value
Total Samples	125,243
Unique Datasets	33
Evaluation Tasks	9
Languages	Odia (ory) + English prompts where available
License	MIT (commercially usable, no restrictions)
Access Required	None
File Format	Parquet (single split, 80MB)

By Task

Task	Samples	What It Measures
Multiple Choice	63,266	Knowledge & reasoning across 100+ subjects (MILU, MMLU, ARC, TriviaQA, HellaSwag, Winogrande, TruthfulQA-MC, BHRAM-IL, IndicCOPA, IndicGLUE-WSTP)
Question Answering	29,392	Reading comprehension, factual recall, BoolQ, IndicQA, IndicSQuAD, IndicQuest
Generation	23,738	Summarization, headline gen, question gen
Math	2,638	Arithmetic chain-of-thought reasoning
Classification	4,050	News categorization, paraphrase detection
Translation	1,012	Odia-English translation quality
NER	1,147	Token-level named entity recognition

By Quality Tier

Tier	Samples	Provider
Professional Translation	47,951	Sarvam AI (MMLU, GSM8K, ARC, TriviaQA, BoolQ, IndiVibe)
Native Odia	60,403	AI4Bharat, L3Cube, Sambhashana, MTEB, OpenLanguageData
NLLB Translated	15,895	TripathySagar (ARC, GSM8K, HellaSwag, Winogrande, TruthfulQA)

Full Dataset List

Dataset	Samples	Task	Quality
bhram_il	10,265	multiple_choice	Native Odia
flores_plus	1,012	translation	Native Odia
indic_copa	500	multiple_choice	Native Odia
indic_glue_csqa	1,975	qa	Native Odia
indic_glue_ner	153	ner	Native Odia
indic_glue_wstp	502	multiple_choice	Native Odia
indic_headline_gen	7,137	generation	Native Odia
indic_qa	1,680	qa	Native Odia
indic_quest_odia	200	qa	Native Odia
indic_question_generation	10,553	generation	Native Odia
indic_sentence_summarization	6,048	generation	Native Odia
indic_squad_odia	11,803	qa	Native Odia
indic_xparaphrase	2,002	classification	Native Odia
milu	4,525	multiple_choice	Native Odia
naamapadam_odia_ner	994	ner	Native Odia
odia_arc	1,172	multiple_choice	NLLB Translated
odia_gsm8k	1,319	math	NLLB Translated
odia_hellaswag	10,003	multiple_choice	NLLB Translated
odia_news_classification	2,048	classification	Native Odia
odia_truthfulqa	817	qa	NLLB Translated
odia_truthfulqa_mc	817	multiple_choice	NLLB Translated
odia_winogrande	1,767	multiple_choice	NLLB Translated
sarvam_arc_challenge	1,150	multiple_choice	Professional Translation
sarvam_arc_challenge_val	294	multiple_choice	Professional Translation
sarvam_boolq	9,427	qa	Professional Translation
sarvam_boolq_val	3,270	qa	Professional Translation
sarvam_gsm8k_indic	1,319	math	Professional Translation
sarvam_indivibe_chat	100	qa	Professional Translation
sarvam_indivibe_code	40	qa	Professional Translation
sarvam_indivibe_math	40	qa	Professional Translation
sarvam_indivibe_stem	40	qa	Professional Translation
sarvam_mmlu_indic	14,042	multiple_choice	Professional Translation
sarvam_mmlu_indic_val	285	multiple_choice	Professional Translation
sarvam_triviaqa	17,944	multiple_choice	Professional Translation

Quick Start

Load the data

from datasets import load_dataset

ds = load_dataset('saidutta69/odia-eval-benchmark', split='odia')
print(f'{len(ds):,} samples loaded')

# Filter to a specific dataset
mmlu = ds.filter(lambda x: x['dataset_name'] == 'sarvam_mmlu_indic')

# Filter by task type
mcq = ds.filter(lambda x: x['task'] == 'multiple_choice')
print(f'MCQ: {{len(mcq):,}} samples')

Evaluate a model

Use the bundled eval harness:

# Random baseline on all MCQ tasks
python scripts/eval_harness.py --model random --task-type multiple_choice

# Evaluate a HuggingFace model on MMLU Odia
python scripts/eval_harness.py --model your-org/model --tasks sarvam_mmlu_indic --device mps

# Test all tasks
python scripts/eval_harness.py --model random --task-type all --verbose

Programmatic eval

from scripts.eval_harness import load_data, default_prompt, score_mc, MockModel

ds = load_data(dataset_names=['sarvam_mmlu_indic'])
model = MockModel('your-org/model', device='mps')

for sample in ds:
    prompt = default_prompt(sample)
    pred = model.predict(prompt)
    score = score_mc(sample, pred)

Dataset Fields

Field	Type	Description
id	string	Unique sample identifier
task	string	Task type: multiple_choice, qa, math, translation, classification, generation, ner
language	string	Language code (ory)
prompt	string	Original English prompt (when available)
prompt_odia	string	Odia prompt/question/context
reference	string	English reference/answer (when available)
reference_odia	string	Odia reference/answer
choices	list[string]	English answer choices (MCQ tasks)
choices_odia	list[string]	Odia answer choices (MCQ tasks)
answer	string	Correct answer
domain	string	Domain or category label
source	string	Original dataset name
subset	string	Subject or subcategory
split	string	Dataset split
dataset_name	string	Internal name for filtering

Attribution

Source	Datasets
Sarvam AI	MMLU-Indic, GSM8K-Indic, ARC-Challenge-Indic, TriviaQA-Indic-MCQ, BoolQ-Indic, IndiVibe
AI4Bharat	MILU, IndicQA, IndicCOPA, IndicHeadlineGeneration, IndicSentenceSummarization, IndicQuestionGeneration, IndicXParaphrase, IndicGLUE (CSQA, WSTP, WikiNER), Naamapadam
L3Cube	IndicSQuAD Odia, IndicQuest Odia
TripathySagar	Odia-translated ARC, GSM8K, HellaSwag, Winogrande, TruthfulQA
Sambhashana	BHRAM-IL
OpenLanguageData	FLORES+
MTEB	OdiaNewsClassification

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Built because waiting for access requests is not a strategy.