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[Dataset] Matbench (#2021)
* add support for matbench * fix dataset path * fix data load * fix * fix lint --------- Co-authored-by: Jucheng Hu <jucheng.hu.20@ucl.ac.uk> Co-authored-by: Myhs-phz <demarcia2014@126.com>
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@ -8,6 +8,7 @@ exclude: |
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opencompass/datasets/lawbench/utils|
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opencompass/datasets/lawbench/evaluation_functions/|
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opencompass/datasets/medbench/|
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opencompass/datasets/matbench/|
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opencompass/datasets/teval/|
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opencompass/datasets/NPHardEval/|
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opencompass/datasets/TheoremQA|
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@ -110,6 +110,12 @@
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paper: ''
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configpath: opencompass/configs/datasets/mastermath2024v1/mastermath2024v1_gen.py
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configpath_llmjudge: ''
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- matbench:
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name: matbench
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category: Science / Material
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paper: 'https://www.nature.com/articles/s41524-020-00406-3'
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configpath: opencompass/configs/datasets/matbench/matbench_gen_f71840.py
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configpath_llmjudge: ''
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- medbench:
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name: MedBench
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category: Knowledge / Medicine
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4
opencompass/configs/datasets/matbench/matbench_gen.py
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opencompass/configs/datasets/matbench/matbench_gen.py
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@ -0,0 +1,4 @@
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from mmengine.config import read_base
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with read_base():
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from .matbench_gen_f71840 import matbench_datasets # noqa: F401, F403
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55
opencompass/configs/datasets/matbench/matbench_gen_f71840.py
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opencompass/configs/datasets/matbench/matbench_gen_f71840.py
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from opencompass.openicl.icl_prompt_template import PromptTemplate
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from opencompass.openicl.icl_retriever import ZeroRetriever
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from opencompass.openicl.icl_inferencer import GenInferencer
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from opencompass.openicl.icl_evaluator import AccEvaluator
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from opencompass.datasets.matbench.matbench import MatbenchDataset, MatbenchEvaluator_regression, MatbenchEvaluator_classification
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matbench_reader_cfg = dict(
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input_columns=['problem'], output_column='answer')
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matbench_tasks = ['matbench_steels','matbench_expt_gap', 'matbench_expt_is_metal','matbench_glass']
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matbench_datasets = []
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for task in matbench_tasks:
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if task in ['matbench_expt_is_metal','matbench_glass']:
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matbench_infer_cfg = dict(
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prompt_template=dict(
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type=PromptTemplate,
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template=dict(
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round=[dict(role='HUMAN', prompt=f'{{problem}} Please present your answer by yes or no, do not output anything else.')])),
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retriever=dict(type=ZeroRetriever),
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inferencer=dict(type=GenInferencer))
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matbench_eval_cfg = dict(
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evaluator=dict(type=MatbenchEvaluator_classification),
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pred_role='BOT')
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elif task in ['matbench_steels','matbench_expt_gap']:
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matbench_infer_cfg = dict(
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prompt_template=dict(
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type=PromptTemplate,
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template=dict(
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round=[dict(role='HUMAN', prompt=f'{{problem}} Please present your answer by one float number, do not output anything else.')])),
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retriever=dict(type=ZeroRetriever),
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inferencer=dict(type=GenInferencer))
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matbench_eval_cfg = dict(
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evaluator=dict(type=MatbenchEvaluator_regression),
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pred_role='BOT')
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matbench_datasets.append(
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dict(
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type=MatbenchDataset,
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path=f'opencompass/Matbench',
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task=task,
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abbr=task,
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reader_cfg=matbench_reader_cfg,
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infer_cfg=matbench_infer_cfg,
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eval_cfg=matbench_eval_cfg))
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@ -87,6 +87,7 @@ from .longbench import * # noqa: F401, F403
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from .longbenchv2 import * # noqa: F401, F403
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from .lveval import * # noqa: F401, F403
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from .mastermath2024v1 import * # noqa: F401, F403
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from .matbench import * # noqa: F401, F403
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from .math import * # noqa: F401, F403
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from .math401 import * # noqa: F401, F403
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from .math_intern import * # noqa: F401, F403
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opencompass/datasets/matbench/__init__.py
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opencompass/datasets/matbench/__init__.py
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# flake8: noqa
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from .matbench import * # noqa: F401, F403
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opencompass/datasets/matbench/matbench.py
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opencompass/datasets/matbench/matbench.py
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import json
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import os
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from datasets import Dataset
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from sklearn.metrics import (accuracy_score, f1_score, precision_score,
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recall_score)
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from opencompass.datasets.matbench.post_process import (parse_float_answer,
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parse_true_false_answer
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)
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from opencompass.openicl.icl_evaluator import BaseEvaluator
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from opencompass.registry import ICL_EVALUATORS, LOAD_DATASET
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from opencompass.utils import get_data_path
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from ..base import BaseDataset
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@LOAD_DATASET.register_module()
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class MatbenchDataset(BaseDataset):
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@staticmethod
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def load(path, task):
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path = get_data_path(path)
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path = os.path.join(path,
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'matbench_base_fold_0_' + task + '_test.json')
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dataset = []
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with open(path, 'r', encoding='utf-8') as file:
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data = json.load(file)
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for item in data:
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dataset.append({
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'problem': item['problem'],
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'answer': item['answer'],
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})
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dataset = Dataset.from_list(dataset)
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return dataset
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@ICL_EVALUATORS.register_module()
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class MatbenchEvaluator_regression(BaseEvaluator):
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def score(self, predictions, references):
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mae_sum = 0
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count = 0
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details = []
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for pred, ref in zip(predictions, references):
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pred = parse_float_answer(pred)
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detail = {'pred': pred, 'answer': ref, 'error': None}
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count += 1
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try:
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error = abs(float(pred) - float(ref))
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mae_sum += error
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detail['error'] = error
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except Exception as e:
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detail['error'] = str(e)
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details.append(detail)
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mae = mae_sum / count if count > 0 else 0
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result = {'mae': mae, 'details': details}
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return result
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@ICL_EVALUATORS.register_module()
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class MatbenchEvaluator_classification(BaseEvaluator):
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def score(self, predictions, references):
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details = []
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predictions_parsed = []
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for pred, ref in zip(predictions, references):
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pred = parse_true_false_answer(pred)
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detail = {'pred': pred, 'answer': ref, 'correct': False}
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if pred == ref:
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detail['correct'] = True
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details.append(detail)
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predictions_parsed.append(pred)
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accuracy = accuracy_score(references, predictions_parsed)
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precision = precision_score(references,
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predictions_parsed,
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average='binary')
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recall = recall_score(references, predictions_parsed, average='binary')
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f1 = f1_score(references, predictions_parsed, average='binary')
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return {
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'accuracy': accuracy,
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'precision': precision,
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'recall': recall,
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'f1_score': f1,
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'details': details
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}
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opencompass/datasets/matbench/post_process.py
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25
opencompass/datasets/matbench/post_process.py
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# flake8: noqa
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import re
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def parse_float_answer(raw_string, option=''):
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number_pattern = re.compile(r'[-+]?\d+(\.\d+)?([eE][-+]?\d+)?')
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# Search for the first match
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match = number_pattern.search(raw_string)
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if match:
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# Extract the matched number and convert it to float
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return float(match.group())
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else:
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# Return None if no number is found
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return 0
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def parse_true_false_answer(raw_string, option=''):
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if 'yes' in raw_string.lower():
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return True
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elif 'no' in raw_string.lower():
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return False
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else:
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return True
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@ -27,6 +27,12 @@ DATASETS_MAPPING = {
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"hf_id": "opencompass/ai2_arc",
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"local": "./data/ARC/ARC-e/ARC-Easy-Dev.jsonl",
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},
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# Matbench
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"opencompass/Matbench": {
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# "ms_id": "opencompass/Matbench",
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"hf_id": "opencompass/Matbench",
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"local": "./data/Matbench",
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},
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# BBH
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"opencompass/bbh": {
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"ms_id": "opencompass/bbh",
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@ -664,6 +670,11 @@ DATASETS_URL = {
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"http://opencompass.oss-cn-shanghai.aliyuncs.com/datasets/data/SQuAD2.0.zip",
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"md5": "1321cbf9349e1102a57d31d1b2bfdd7e",
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},
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"/Matbench":{
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"url":
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"http://opencompass.oss-cn-shanghai.aliyuncs.com/datasets/data/Matbench.zip",
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"md5": "99f9457f54f4f419da9556af56ac4c24",
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},
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"mmlu_pro": {
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"url":
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"http://opencompass.oss-cn-shanghai.aliyuncs.com/datasets/data/mmlu_pro.zip",
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