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* 0-shot Smolinstruct Add 0-shot evaluation and postprocess functions for Smolinstruct * fix acc postprocessor * update 0-shot acc postprocessor * rename 0-shot
50 lines
1.7 KiB
Python
50 lines
1.7 KiB
Python
from opencompass.openicl.icl_prompt_template import PromptTemplate
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from opencompass.openicl.icl_retriever import ZeroRetriever, FixKRetriever
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from opencompass.openicl.icl_inferencer import GenInferencer
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from opencompass.datasets.smolinstruct import MeteorEvaluator
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from opencompass.datasets import SmolInstructDataset
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meteor_0shot_reader_cfg = dict(
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input_columns=['input'],
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output_column='output',
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train_split='validation')
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meteor_hint_dict = {
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'MC': """You are an expert chemist. Given the SMILES representation of a molecule, your task is to describe the molecule in natural language.
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The input contains the SMILES representation of the molecule. Your reply should contain a natural language description of the molecule. Your reply must be valid and chemically reasonable.""",
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}
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name_dict = {
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'MC': 'molecule_captioning',
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}
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meteor_0shot_instruct_datasets = []
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for _name in name_dict:
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_hint = meteor_hint_dict[_name]
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meteor_0shot_infer_cfg = dict(
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prompt_template=dict(
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type=PromptTemplate,
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template=f'{_hint}\nQuestion: {{input}}\nAnswer: ',
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# template=f'<s>[INST] {{input}} [/INST]',
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),
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retriever=dict(type=ZeroRetriever),
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inferencer=dict(type=GenInferencer),
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)
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meteor_0shot_eval_cfg = dict(
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evaluator=dict(type=MeteorEvaluator),
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)
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meteor_0shot_instruct_datasets.append(
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dict(
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abbr=f'{_name}-0shot-instruct',
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type=SmolInstructDataset,
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path='osunlp/SMolInstruct',
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name=name_dict[_name],
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reader_cfg=meteor_0shot_reader_cfg,
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infer_cfg=meteor_0shot_infer_cfg,
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eval_cfg=meteor_0shot_eval_cfg,
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))
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del _name
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