diff --git a/.github/workflows/automation-api.yaml b/.github/workflows/automation-api.yaml index 8a20f86..16cba37 100644 --- a/.github/workflows/automation-api.yaml +++ b/.github/workflows/automation-api.yaml @@ -12,7 +12,7 @@ jobs: runs-on: ubuntu-latest strategy: matrix: - python: [ 3.9 ] + python: [ 3.11 ] steps: - name: Checkout code @@ -40,7 +40,7 @@ jobs: runs-on: ubuntu-latest strategy: matrix: - python: [ 3.9 ] + python: [ 3.11 ] steps: - name: Checkout code @@ -60,7 +60,7 @@ jobs: - name: Install Poetry uses: snok/install-poetry@v1 with: - version: 1.4.2 + version: 1.6.1 virtualenvs-create: true virtualenvs-in-project: true diff --git a/automation-api/.env.example b/automation-api/.env.example index 7e36b05..85dc251 100644 --- a/automation-api/.env.example +++ b/automation-api/.env.example @@ -8,13 +8,15 @@ OPENAI_ORG_ID="" ## for Huggingface Hub HUGGINGFACEHUB_API_TOKEN="" ## for PALM -GOOGLE_API_KEY="" +PALM_API_KEY="" ## for iFlytek IFLYTEK_API_KEY="" IFLYTEK_API_SECRET="" IFLYTEK_APPID="" ## for Alibaba DASHSCOPE_API_KEY="" +# for Replicate +REPLICATE_API_KEY="" # For local development SERVICE_ACCOUNT_CREDENTIALS="" diff --git a/automation-api/lib/ai_eval_spreadsheet/schemas.py b/automation-api/lib/ai_eval_spreadsheet/schemas.py index abcd41a..12f0d70 100644 --- a/automation-api/lib/ai_eval_spreadsheet/schemas.py +++ b/automation-api/lib/ai_eval_spreadsheet/schemas.py @@ -5,18 +5,19 @@ # for more info # Note that most types are str since spreadsheet columns can be formulas -from datetime import datetime from typing import Optional import pandas as pd import pandera as pa from pandera.engines.pandas_engine import PydanticModel -from pydantic import BaseModel, Field, validator +from pydantic import BaseModel, ConfigDict, Field, field_validator class Question(BaseModel): + model_config = ConfigDict(coerce_numbers_to_str=True) + include_in_next_evaluation: Optional[bool] = Field( - None, title="Include in next evaluation" + None, title="Include in next evaluation", validate_default=True ) question_id: Optional[str] = Field(None, title="Question ID") language: Optional[str] = Field(None, title="Language") @@ -24,7 +25,8 @@ class Question(BaseModel): None, title="Published version of question" ) - @validator("include_in_next_evaluation", pre=True, always=True) + @field_validator("include_in_next_evaluation", mode="before") + @classmethod def default_if_nan(cls, v): # noqa: N805 return False if pd.isna(v) else v @@ -36,6 +38,8 @@ class Config: class QuestionOption(BaseModel): + model_config = ConfigDict(coerce_numbers_to_str=True) + question_option_id: Optional[str] = Field(None, title="Question Option ID") question_id: Optional[str] = Field(None, title="Question ID") language: Optional[str] = Field(None, title="Language") @@ -53,6 +57,8 @@ class Config: class PromptVariation(BaseModel): + model_config = ConfigDict(coerce_numbers_to_str=True) + include_in_next_evaluation: Optional[bool] = Field( None, title="Include in next evaluation" ) @@ -78,6 +84,8 @@ class Config: class GenAiModel(BaseModel): + model_config = ConfigDict(coerce_numbers_to_str=True, protected_namespaces=()) + model_id: Optional[str] = Field(None, title="Model ID") vendor: Optional[str] = Field(None, title="Vendor") model_name: Optional[str] = Field(None, title="Model name") @@ -90,6 +98,8 @@ class Config: class GenAiModelConfig(BaseModel): + model_config = ConfigDict(coerce_numbers_to_str=True, protected_namespaces=()) + include_in_next_evaluation: Optional[bool] = Field( None, title="Include in next evaluation" ) @@ -107,12 +117,28 @@ class Config: coerce = True +class Metric(BaseModel): + name: Optional[str] = Field(None, title="Name") + description: Optional[str] = Field(None, title="Description") + prompt: Optional[str] = Field(None, title="Prompt") + choices: Optional[str] = Field(None, title="Choices") + choice_scores: Optional[str] = Field(None, title="Choice Scores") + + +class MetricsDf(pa.DataFrameModel): + class Config: + dtype = PydanticModel(Metric) + coerce = True + + class EvalResult(BaseModel): + model_config = ConfigDict(coerce_numbers_to_str=True, protected_namespaces=()) + question_id: Optional[str] = Field(None, title="Question ID") language: Optional[str] = Field(None, title="Language") prompt_variation_id: Optional[str] = Field(None, title="Prompt variation ID") model_configuration_id: Optional[str] = Field(None, title="Model Configuration ID") - last_evaluation_datetime: Optional[datetime] = Field(None, title="Last Evaluation") + last_evaluation_datetime: Optional[str] = Field(None, title="Last Evaluation") percent_correct: Optional[float] = Field(None, title="Percent Correct") percent_wrong: Optional[float] = Field(None, title="Percent Wrong") percent_very_wrong: Optional[float] = Field(None, title="Percent Very Wrong") @@ -128,6 +154,8 @@ class Config: class SessionResult(BaseModel): + model_config = ConfigDict(coerce_numbers_to_str=True, protected_namespaces=()) + session_id: Optional[str] = Field(None, title="Session ID") session_time: Optional[str] = Field(None, title="Session Time") prompt_variation_id: Optional[str] = Field(None, title="Prompt Variation ID") diff --git a/automation-api/lib/ai_eval_spreadsheet/wrapper.py b/automation-api/lib/ai_eval_spreadsheet/wrapper.py index a37083b..9a83631 100644 --- a/automation-api/lib/ai_eval_spreadsheet/wrapper.py +++ b/automation-api/lib/ai_eval_spreadsheet/wrapper.py @@ -10,6 +10,8 @@ GenAiModelConfig, GenAiModelConfigsDf, GenAiModelsDf, + Metric, + MetricsDf, PromptVariation, PromptVariationsDf, Question, @@ -36,6 +38,7 @@ class AiEvalData: gen_ai_model_configs: Optional[ GsheetsWorksheetEditor[GenAiModelConfigsDf, GenAiModelConfig] ] = None + metrics: Optional[GsheetsWorksheetEditor[MetricsDf, Metric]] = None evaluation_results: Optional[ GsheetsWorksheetEditor[EvalResult, EvalResultsDf] ] = None @@ -50,6 +53,7 @@ class AiEvalData: "prompt_variations": "Prompt variations", "gen_ai_models": "Models", "gen_ai_model_configs": "Model configurations", + "metrics": "Metrics", "evaluation_results": "Latest Results", "session_results": "Sessions", } @@ -71,7 +75,7 @@ def read_ai_eval_data( row_schema=Question, worksheet_name=sheet_names["questions"], header_row_number=0, - evaluate_formulas=True, + evaluate_formulas=False, ) question_options = GsheetsWorksheetEditor( @@ -80,7 +84,7 @@ def read_ai_eval_data( row_schema=QuestionOption, worksheet_name=sheet_names["question_options"], header_row_number=0, - evaluate_formulas=True, + evaluate_formulas=False, ) prompt_variations = GsheetsWorksheetEditor( @@ -89,7 +93,7 @@ def read_ai_eval_data( row_schema=PromptVariation, worksheet_name=sheet_names["prompt_variations"], header_row_number=0, - evaluate_formulas=True, + evaluate_formulas=False, ) gen_ai_models = GsheetsWorksheetEditor( @@ -98,7 +102,7 @@ def read_ai_eval_data( row_schema=GenAiModel, worksheet_name=sheet_names["gen_ai_models"], header_row_number=0, - evaluate_formulas=True, + evaluate_formulas=False, ) gen_ai_model_configs = GsheetsWorksheetEditor( @@ -107,7 +111,16 @@ def read_ai_eval_data( row_schema=GenAiModelConfig, worksheet_name=sheet_names["gen_ai_model_configs"], header_row_number=0, - evaluate_formulas=True, + evaluate_formulas=False, + ) + + metrics = GsheetsWorksheetEditor( + sh=ai_eval_spreadsheet, + df_schema=MetricsDf, + row_schema=Metric, + worksheet_name=sheet_names["metrics"], + header_row_number=0, + evaluate_formulas=False, ) evaluation_results = GsheetsWorksheetEditor( @@ -134,6 +147,7 @@ def read_ai_eval_data( prompt_variations=prompt_variations, gen_ai_models=gen_ai_models, gen_ai_model_configs=gen_ai_model_configs, + metrics=metrics, evaluation_results=evaluation_results, session_results=session_results, ) diff --git a/automation-api/lib/config.py b/automation-api/lib/config.py index a6f1f52..54a9534 100644 --- a/automation-api/lib/config.py +++ b/automation-api/lib/config.py @@ -24,11 +24,12 @@ def read_config() -> dict[str, str]: "AI_EVAL_SPREADSHEET_ID", "AI_EVAL_DEV_SPREADSHEET_ID", "HUGGINGFACEHUB_API_TOKEN", - "GOOGLE_API_KEY", + "PALM_API_KEY", "IFLYTEK_APPID", "IFLYTEK_API_KEY", "IFLYTEK_API_SECRET", "DASHSCOPE_API_KEY", + "REPLICATE_API_KEY", ]: config[key] = os.getenv(key=key, default="") return config diff --git a/automation-api/lib/gsheets/gsheets_utils.py b/automation-api/lib/gsheets/gsheets_utils.py index b9d9ce9..7b6ef07 100644 --- a/automation-api/lib/gsheets/gsheets_utils.py +++ b/automation-api/lib/gsheets/gsheets_utils.py @@ -3,7 +3,7 @@ import pandas as pd from gspread import Spreadsheet, Worksheet, WorksheetNotFound from gspread_dataframe import set_with_dataframe -from pydantic.main import BaseModel +from pydantic import BaseModel from lib.app_singleton import app_logger diff --git a/automation-api/lib/gsheets/gsheets_worksheet_data.py b/automation-api/lib/gsheets/gsheets_worksheet_data.py index 2f63a36..5904a78 100644 --- a/automation-api/lib/gsheets/gsheets_worksheet_data.py +++ b/automation-api/lib/gsheets/gsheets_worksheet_data.py @@ -4,7 +4,7 @@ import numpy as np import pandera as pa from pandera import DataFrameModel -from pydantic.main import BaseModel +from pydantic import BaseModel from lib.gsheets.gsheets_utils import get_pydantic_model_field_titles @@ -36,11 +36,13 @@ def __init__( self.df_schema = df_schema self.row_schema = row_schema self.header_row_number = header_row_number + self.attributes_to_columns_map = get_pydantic_model_field_titles( self.row_schema ) df = df.rename(columns=inv_dict(self.attributes_to_columns_map)) df = self.replace_current_row_numbers_in_formulas(df) + # import ipdb; ipdb.set_trace() self.df = df_schema(df) def replace_current_row_numbers_in_formulas( diff --git a/automation-api/lib/gsheets/gsheets_worksheet_editor.py b/automation-api/lib/gsheets/gsheets_worksheet_editor.py index b9bfefb..7142a06 100644 --- a/automation-api/lib/gsheets/gsheets_worksheet_editor.py +++ b/automation-api/lib/gsheets/gsheets_worksheet_editor.py @@ -5,7 +5,7 @@ from gspread import Spreadsheet, Worksheet from gspread.utils import rowcol_to_a1 from pandera import DataFrameModel -from pydantic.main import BaseModel +from pydantic import BaseModel from lib.gsheets.gsheets_utils import get_worksheet from lib.gsheets.gsheets_worksheet_data import GsheetsWorksheetData diff --git a/automation-api/lib/llms/alibaba.py b/automation-api/lib/llms/alibaba.py index b4b4f34..214c7e8 100644 --- a/automation-api/lib/llms/alibaba.py +++ b/automation-api/lib/llms/alibaba.py @@ -6,7 +6,7 @@ from dashscope import Generation from langchain.callbacks.manager import CallbackManagerForLLMRun from langchain.llms.base import LLM -from pydantic import root_validator +from langchain.pydantic_v1 import root_validator from tenacity import ( retry, retry_if_exception_type, @@ -71,7 +71,7 @@ def validate_environment(cls, values: Dict) -> Dict: # noqa: N805 dashscope.api_key = dashscope_api_key if values["top_p"] is not None and not 0.0 <= values["top_p"] <= 1.0: - raise ValueError("max_output_tokens must be between 0 and 1") + raise ValueError("top_p must be between 0 and 1") if values["top_k"] is not None and not 1 <= values["top_k"] <= 100: raise ValueError("top_k must be between 1 and 100") diff --git a/automation-api/lib/llms/spark.py b/automation-api/lib/llms/spark.py index 0ccedf1..cf67cfc 100644 --- a/automation-api/lib/llms/spark.py +++ b/automation-api/lib/llms/spark.py @@ -5,7 +5,7 @@ from langchain.callbacks.manager import CallbackManagerForLLMRun from langchain.llms.base import LLM -from pydantic import root_validator +from langchain.pydantic_v1 import root_validator from tenacity import ( retry, retry_if_exception_type, diff --git a/automation-api/lib/pilot/helpers.py b/automation-api/lib/pilot/helpers.py index 7561451..7c568c5 100644 --- a/automation-api/lib/pilot/helpers.py +++ b/automation-api/lib/pilot/helpers.py @@ -13,6 +13,7 @@ from lib.ai_eval_spreadsheet.schemas import ( GenAiModel, GenAiModelConfig, + Metric, PromptVariation, Question, QuestionOption, @@ -219,9 +220,14 @@ def get_prompt_variants( return res -def get_model_configs(sheet: AiEvalData) -> List[ModelAndConfig]: +def get_model_configs( + sheet: AiEvalData, include_all: bool = False +) -> List[ModelAndConfig]: models_df = sheet.gen_ai_models.data.df - model_configs_df = filter_included_rows(sheet.gen_ai_model_configs.data.df) + if include_all: + model_configs_df = sheet.gen_ai_model_configs.data.df + else: + model_configs_df = filter_included_rows(sheet.gen_ai_model_configs.data.df) model_configs = class_objects_from_df(model_configs_df, GenAiModelConfig) result = [] @@ -232,6 +238,11 @@ def get_model_configs(sheet: AiEvalData) -> List[ModelAndConfig]: return result +def get_metrics(sheet: AiEvalData) -> List[Metric]: + res = class_objects_from_df(sheet.metrics.data.df, Metric) + return res + + def get_survey_hash(questions: List[QuestionAndOptions]) -> str: joined = ",".join([q[0].question_id for q in questions]) return hash_dn(joined, "") diff --git a/automation-api/poetry.lock b/automation-api/poetry.lock index a093793..dd58383 100644 --- a/automation-api/poetry.lock +++ b/automation-api/poetry.lock @@ -1,99 +1,99 @@ -# This file is automatically @generated by Poetry 1.5.1 and should not be changed by hand. +# This file is automatically @generated by Poetry 1.6.1 and should not be changed by hand. 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"pytest-ruff"] [metadata] lock-version = "2.0" -python-versions = ">=3.9,<3.10" -content-hash = "49c658cb4965cdd47896b8a2ba22eff619ef4e32188301ca858bda5b805fdec5" +python-versions = ">=3.11,<3.12" +content-hash = "0b81cd3b2b651e2d9db4314ab94d6dccc1a42242a46ed5c2bce6089b689246c6" diff --git a/automation-api/pyproject.toml b/automation-api/pyproject.toml index d265a32..d33391e 100644 --- a/automation-api/pyproject.toml +++ b/automation-api/pyproject.toml @@ -12,14 +12,15 @@ classifiers = [ packages = [{ include = "lib" }] [tool.poetry.dependencies] -python = ">=3.9,<3.10" -pandas = "^1.3.4" +python = ">=3.11,<3.12" +pandas = "^2.0.3" mypy = "^0.991" unidecode = "^1.3.6" +polars = "^0.19.12" # for data frames schemas / types validation -pydantic = "^1.10.8" -pandera = {extras = ["mypy"], version = "^0.15.1"} +pydantic = "^2.1.1" +pandera = {extras = ["mypy"], version = "^0.17.0"} # to simplify development and deployment of cloud functions functions-framework = "^3.0.0" @@ -41,7 +42,7 @@ bracelogger = "^1.1.0" # for access to AI models openai = "^0.27.6" -langchain = "^0.0.285" +langchain = "^0.0.275" # for hugging face huggingface_hub = "^0.15.1" @@ -55,7 +56,13 @@ websocket-client = "^1.6.1" # for alibaba dashscope = "^1.6.0" +# yival +yival = {git = "https://github.com/semio/YiVal.git#master"} +redis = "^5.0.1" + # unsorted (new deps gets listed here) +langdetect = "^1.0.9" + [tool.poetry.dev-dependencies] diff --git a/yival_experiments/.gitignore b/yival_experiments/.gitignore new file mode 100644 index 0000000..64b001b --- /dev/null +++ b/yival_experiments/.gitignore @@ -0,0 +1,12 @@ +*.pyc +*.egg-info +*.bak +.coverage +.tox +.venv +test.db +.ipynb_checkpoints +dist +.env +*.ipynb +requirements.txt diff --git a/yival_experiments/README.md b/yival_experiments/README.md new file mode 100644 index 0000000..e5a5af7 --- /dev/null +++ b/yival_experiments/README.md @@ -0,0 +1,85 @@ +# How to run experiment + +## 1. install automation-api library + +``` shell +cd /path/to/gapminder-ai/automation-api +poetry install +``` + +## 2. enable poetry shell + +``` shell +poetry shell +``` + +## 3. copy .env and fetch questions + +``` shell +cd ../yival_experiment/ +cp ../automation-api/.env ./ + +cd scripts +python fetch_question.py +``` + +This will fetch all enabled questions in the AI eval spreadsheet and create data/questions.csv. +We also included all questions in data/questions_cn.csv and data/questions_en.csv + +Note: I tried to create a custom data reader to read data from AI eval +spreadsheet directly, but then yival failed to run the experiment. I +checked and found that Yival requires a dataset to have a local +file when the source type is set to "dataset". So we need to fetch it first. + +(Maybe, we can solve it by changing the source type to "machine generated") + +## 4. run the experiment + +The full experiment configuration is [here](https://github.com/Gapminder/gapminder-ai/blob/yival/yival_experiments/experiment_latest.yaml) + +To run it: + +``` shell +yival run --output ./output/experiment_name experiment_latest.yaml +# You can replace experiment_name with other names. +``` + +This will output a pickle file in `output/experiment_name_0.pkl` which include all Experiment Results objects. + +When the experiment is completed, Yival will start a web server to show the results. + +To update the experiment with the settings in AI Eval Spreadsheet, run the generate_experiment_config.py script. + +``` shell +cd scripts +python generate_experiment_config.py +``` + +### Use Redis for caching + +The model compare function will cache LLM call results for the +evaluator, and by default the cache is dictionary in memory. You can +also use Redis to caching, so that it won't loss the cache when Yival +exits. To do this, uncomment the line for redis cache in the top of +`custom_configuration/model_compare.py` and set the host and password +to your redis server. + +## 5. generate a result xlsx from output + +To convert the pickle files to excel file: + +``` shell +cd scripts +python generate_result.py +``` + +This will read all pickles in output/ directory and will generate `results.xlsx` in output/ directory. + +TODO: We can add a custom evaluator in Yival to calculate the final scores. + +## 6. Calculate scores, upload results to AI Eval Spreadsheet + +Two notebooks in notebooks/ directory are provided for calculating scores. + +- final_scores.py: calculate a final score for each model and prompt +- upload_to_ai_eval_sheet.py: generate the result table and upload to the `Latest Results` sheet in AI Eval Spreadsheet diff --git a/yival_experiments/custom_configuration/gpt4_evaluator.py b/yival_experiments/custom_configuration/gpt4_evaluator.py new file mode 100644 index 0000000..775ecf7 --- /dev/null +++ b/yival_experiments/custom_configuration/gpt4_evaluator.py @@ -0,0 +1,201 @@ +""" +OpenAIPromptBasedEvaluator is an evaluator that uses OpenAI's prompt-based +system for evaluations. + +The evaluator interfaces with the OpenAI API to present tasks and interpret +the model's responses to determine the quality or correctness of a given +experiment result. +""" +import copy +import logging +import string +from typing import Any, Dict, Iterable, List, Optional, Union + +# for exponential backoff +import litellm +from tenacity import before_sleep_log, retry, stop_after_attempt, wait_random + +from gpt4_evaluator_config import GPT4EvaluatorConfig +from yival.evaluators.base_evaluator import BaseEvaluator +from yival.schemas.evaluator_config import ( + EvaluatorOutput, + EvaluatorType, + MethodCalculationMethod, + MetricCalculatorConfig, +) +from yival.schemas.experiment_config import ( + ExperimentResult, + InputData, + MultimodalOutput, +) + +logging.basicConfig(level=logging.INFO) +logger = logging.getLogger(__name__) + + +CLASSIFY_STR = """ +First, write out in a step by step manner your reasoning to be sure that your +conclusion is correct. +Avoid simply stating the correct answer at the outset. +Then print only a single choice from {choices} (without quotes or punctuation) +on its own line corresponding to the correct answer. +At the end, repeat just the answer by itself on a new line. +Reasoning: +""" + +MATCH_FNS = { + "include": lambda x, y: float(x in y), + "exact": lambda x, y: float(x == y), + "endswith": lambda x, y: x.endswith(y), + "starts_or_endswith": lambda x, y: x.startswith(y) or x.endswith(y), +} + + +def extract_choice_from_response(response: str, choice_strings: Iterable[str]) -> str: + """Extracts the choice from the response string.""" + lines = response.strip().split("\n") + for line in lines: + sanitized_line = "".join(c for c in line if c not in string.punctuation).strip() + if not sanitized_line: + continue + for choice in choice_strings: + if MATCH_FNS["exact"](sanitized_line, choice): + return choice + return "invalid response" + + +def calculate_choice_score( + choice: str, choice_scores: Optional[Dict[str, float]] = None +) -> Optional[float]: + """Calculates the score for the given choice.""" + if choice_scores is None: + return None + if choice == "invalid response": + return min(choice_scores.values()) + return choice_scores.get(choice) + + +def format_template( + template: Union[str, List[Dict[str, str]]], content: Dict[str, Any] +) -> Union[str, List[Dict[str, str]]]: + """Formats a string or list template with the provided content.""" + if isinstance(template, str): + try: + return template.format(**content) + except KeyError as e: + raise ValueError(f"Missing key {e} in content dictionary") + + res = [] + for t in template: + formatted_msg = copy.deepcopy(t) + try: + if "content" in formatted_msg: + formatted_msg["content"] = formatted_msg["content"].format(**content) + except KeyError as e: + raise ValueError(f"Missing key {e} in content dictionary") + res.append(formatted_msg) + return res + + +@retry( + wait=wait_random(min=1, max=20), + stop=stop_after_attempt(100), + before_sleep=before_sleep_log(logger, logging.DEBUG), +) +def completion_with_backpff(**kwargs): + # response = openai.ChatCompletion.create(**kwargs) + response = litellm.completion(**kwargs) + return response + + +def choices_to_string(choice_strings: Iterable[str]) -> str: + """Converts a list of choices into a formatted string.""" + return " or ".join(f'"{choice}"' for choice in choice_strings) + + +class GPT4Evaluator(BaseEvaluator): + """Evaluator using OpenAI's prompt-based evaluation.""" + + default_config = GPT4EvaluatorConfig(name="gpt4_evaluator") # type: ignore + + def __init__(self, config: GPT4EvaluatorConfig): + super().__init__(config) + self.config = config + + def evaluate(self, experiment_result: ExperimentResult) -> EvaluatorOutput: + """Evaluate the experiment result using OpenAI's prompt-based evaluation.""" + assert isinstance(self.config, GPT4EvaluatorConfig) + format_dict = copy.deepcopy(experiment_result.input_data.content) + format_dict["raw_output"] = experiment_result.raw_output.text_output + + prompt = format_template(self.config.prompt, format_dict) + if isinstance(prompt, str): + prompt = [{"role": "user", "content": prompt}] + + prompt[-1]["content"] += "\n\n" + CLASSIFY_STR.format( + choices=choices_to_string(self.config.choices) + ) + response = completion_with_backpff( + model="gpt-4", + messages=prompt, + temperature=0.0, + n=1, + max_tokens=1000, + request_timeout=60, + caching=True, + ) + # response = openai.ChatCompletion.create( + # model="gpt-4", messages=prompt, temperature=0.5) + response_content = response["choices"][0]["message"]["content"] + choice = extract_choice_from_response(response_content, self.config.choices) + score = calculate_choice_score(choice, self.config.choice_scores) + return EvaluatorOutput( + name=self.config.name, + result=score if score is not None else choice, + display_name=self.config.display_name, + metric_calculators=self.config.metric_calculators, + ) + + +BaseEvaluator.register_evaluator("gpt4_evaluator", GPT4Evaluator, GPT4EvaluatorConfig) + + +def main(): + """Main function to test the OpenAIPromptBasedEvaluator.""" + evaluator_config = GPT4EvaluatorConfig( + name="gpt4_evaluator", + display_name="math calculator", + metric_calculators=[ + MetricCalculatorConfig( + MethodCalculationMethod(MethodCalculationMethod.AVERAGE) + ) + ], + prompt="{problem}\n\n Is the answer '{raw_output}' correct? .", + choices=["Yes", "No"], + evaluator_type=EvaluatorType.INDIVIDUAL, + choice_scores={"Yes": 1.0, "No": 0}, + ) + input_data_example = InputData( + content={ + "problem": "Calculate the area of a circle with radius 5.", + "method": "Using the formula for the area of a circle: pi*r^2", + } + ) + + experiment_result_example = ExperimentResult( + input_data=input_data_example, + combination={"wrapper1": "var1", "wrapper2": "var2"}, + raw_output=MultimodalOutput( + text_output="The area of the circle is 78.54 square units." + ), + latency=150.0, + token_usage=50, + ) + + evaluator = GPT4Evaluator(evaluator_config) + result = evaluator.evaluate(experiment_result_example) + print(result) + + +if __name__ == "__main__": + main() diff --git a/yival_experiments/custom_configuration/gpt4_evaluator_config.py b/yival_experiments/custom_configuration/gpt4_evaluator_config.py new file mode 100644 index 0000000..f3f9e39 --- /dev/null +++ b/yival_experiments/custom_configuration/gpt4_evaluator_config.py @@ -0,0 +1,17 @@ +from dataclasses import asdict, dataclass, field +from typing import Any, Dict, List, Optional, Union +from yival.schemas.evaluator_config import EvaluatorConfig, EvaluatorType + + +@dataclass +class GPT4EvaluatorConfig(EvaluatorConfig): + evaluator_type: EvaluatorType = EvaluatorType.INDIVIDUAL + prompt: Union[str, List[Dict[str, str]]] = "" + choices: List[str] = field(default_factory=list) + model_name: str = "gpt-4" + description: str = "This is the description of the evaluator." + scale_description: str = "0-4" + choice_scores: Optional[Dict[str, float]] = None + + def asdict(self) -> Dict[str, Any]: + return asdict(self) diff --git a/yival_experiments/custom_configuration/llms/alibaba_complete.py b/yival_experiments/custom_configuration/llms/alibaba_complete.py new file mode 100644 index 0000000..44c99e3 --- /dev/null +++ b/yival_experiments/custom_configuration/llms/alibaba_complete.py @@ -0,0 +1,150 @@ +# encoding: utf-8 + +from tenacity import ( + retry, + retry_if_exception_type, + retry_if_not_result, + stop_after_attempt, +) +from http import HTTPStatus +import dashscope +from dashscope import Generation +from lib.config import read_config +import random + + +def response_is_ok(response): + if response.status_code == HTTPStatus.OK: + return True + return False + + +def return_last_message(retry_state): + last_val = retry_state.outcome.result() + result = {"output": {"text": f"Error: {last_val.code}: {last_val.message}"}} + return result + + +@retry( + retry=(retry_if_exception_type() | retry_if_not_result(response_is_ok)), + stop=stop_after_attempt(3), + retry_error_callback=return_last_message, +) +def get_reply(**kwargs): + return Generation.call(**kwargs) + + +""" Here we need to convert the reply from alibaba into openai's output format. + +Alibaba: +``` +{ + "status_code": 200, + "request_id": "05dc83af-7185-9e14-9b0b-4466de159d6a", + "code": "", + "message": "", + "output": { + "text": null + "finish_reason": null + "choices": [ + { + "finish_reason": "stop", + "message": { + "role": "assistant", + "content": "对于有编程基础的人,..." + } + } + ], + }, + "usage": { + "input_tokens": 12, + "output_tokens": 98, + "total_tokens": 110 + } +} +``` + +openai: +``` +{ + "id": "chatcmpl-123", + "object": "chat.completion", + "created": 1677652288, + "model": "gpt-3.5-turbo-0613", + "choices": [{ + "index": 0, + "message": { + "role": "assistant", + "content": "\n\nHello there, how may I assist you today?", + }, + "finish_reason": "stop" + }], + "usage": { + "prompt_tokens": 9, + "completion_tokens": 12, + "total_tokens": 21 + } +} +``` + +The only thing need to translate is the `output` key in alibaba +""" + + +def llm_complete( + model_name, + prompt, + top_p=0.8, + top_k=100, + enable_search=False, + dashscope_api_key=None, +): + seed = random.randint(0, 2**63) + if not dashscope_api_key: + config = read_config() + if "DASHSCOPE_API_KEY" in config.keys(): + dashscope_api_key = config["DASHSCOPE_API_KEY"] + else: + raise ValueError( + "please set DASHSCHPE_API_KEY in .env or \ + provide the dashschpe_api_key parameter." + ) + dashscope.api_key = dashscope_api_key + + reply = get_reply( + model=model_name, + prompt=prompt, # alternativly we can use the `messages` parameter. see doc. + top_p=top_p, + top_k=top_k, + seed=seed, + enable_search=enable_search, + result_format="message", + ) + # fixing the format + output = reply.pop("output", None) + if ( + output["text"] is not None + ): # API reported an error. see return_last_message() above. + # let's just return the error message. + reply["choices"] = [ + { + "finish_reason": "stop", + "message": {"role": "assistant", "content": output["text"]}, + } + ] + else: + reply["choices"] = output["choices"] + return reply + + +if __name__ == "__main__": + # NOTE: currently there is qwen-turbo and qwen-plus. + # qwen-plus is stronger than qwen-turbo + q = """请回答以下的选择题,如果你不确定也要根据你知道的信息选择一个答案。\n\ + 问题:全世界有多少大学生在自己的本国(而不是国外)获得学位?\n\ + A. 大约 77%\n\ + B. 大约 87%\n\ + C. 大约 97%\n\ + + 回答:""" + print(llm_complete("qwen-plus", q, top_p=0.1, top_k=100)) diff --git a/yival_experiments/custom_configuration/llms/palm_completion.py b/yival_experiments/custom_configuration/llms/palm_completion.py new file mode 100644 index 0000000..bde24e3 --- /dev/null +++ b/yival_experiments/custom_configuration/llms/palm_completion.py @@ -0,0 +1,32 @@ +import google.generativeai as palm + +safety_settings = [ + { + "category": palm.types.HarmCategory.HARM_CATEGORY_TOXICITY, + "threshold": palm.types.HarmBlockThreshold.BLOCK_NONE, + }, + { + "category": palm.types.HarmCategory.HARM_CATEGORY_SEXUAL, + "threshold": palm.types.HarmBlockThreshold.BLOCK_NONE, + }, + { + "category": palm.types.HarmCategory.HARM_CATEGORY_MEDICAL, + "threshold": palm.types.HarmBlockThreshold.BLOCK_NONE, + }, + { + "category": palm.types.HarmCategory.HARM_CATEGORY_DEROGATORY, + "threshold": palm.types.HarmBlockThreshold.BLOCK_NONE, + }, + { + "category": palm.types.HarmCategory.HARM_CATEGORY_DANGEROUS, + "threshold": palm.types.HarmBlockThreshold.BLOCK_NONE, + }, + { + "category": palm.types.HarmCategory.HARM_CATEGORY_UNSPECIFIED, + "threshold": palm.types.HarmBlockThreshold.BLOCK_NONE, + }, + { + "category": palm.types.HarmCategory.HARM_CATEGORY_VIOLENCE, + "threshold": palm.types.HarmBlockThreshold.BLOCK_NONE, + }, +] diff --git a/yival_experiments/custom_configuration/model_compare.py b/yival_experiments/custom_configuration/model_compare.py new file mode 100644 index 0000000..5e07b89 --- /dev/null +++ b/yival_experiments/custom_configuration/model_compare.py @@ -0,0 +1,134 @@ +from yival.logger.token_logger import TokenLogger +from yival.schemas.experiment_config import MultimodalOutput +from yival.schemas.model_configs import Response +from yival.states.experiment_state import ExperimentState +from yival.wrappers.string_wrapper import StringWrapper +from model_config_wrapper import ModelConfigWrapper +from llms.alibaba_complete import llm_complete as alibaba_llm_complete +from llms.palm_completion import safety_settings +import litellm +from litellm import completion + +# load env vars +from lib.config import read_config + +read_config() +# default model config if not provided +default_model_config = dict(model_name="gpt-3.5-turbo", params={"temperature": 0.5}) +# set this to see verbose outputs +litellm.set_verbose = True +# enable caching in the evaluator. +litellm.cache = litellm.Cache() +# use Redis for caching: comment the line above and uncomment the line below. +# litellm.cache = litellm.Cache(type="redis", host="127.0.0.1", port=6379) + + +def model_compare( + question_id: str, + question_text: str, + language: str, + option_a: str, + option_a_correctness: str, + option_b: str, + option_b_correctness: str, + option_c: str, + option_c_correctness: str, + state: ExperimentState, +) -> MultimodalOutput: + logger = TokenLogger() + logger.reset() + + model = ModelConfigWrapper( + default_model_config, name="model_config", state=state + ).get_value() + + prompt_template_default = """Answer following multiple choices question: + Question: {question_text} + A. {option_a} + B. {option_b} + C. {option_c} + + Answer:""" + # TODO: there might be better way to handle variables in prompt variations. + prompt_template = str(StringWrapper("", name="prompt_template", state=state)) + if prompt_template == "": + prompt_template = prompt_template_default + + prompt = prompt_template.format( + question_text=question_text, + option_a=option_a, + option_b=option_b, + option_c=option_c, + ) + # system_prompt = """...""" + + if model["vendor"] == "Alibaba": + # FIXME: alibaba's complete function doesn't support system prompt. + output = alibaba_llm_complete( + model_name=model["model_id"], prompt=prompt, **model["params"] + ) + response = Response(output=output).output + elif model["vendor"] == "Google": + # google allows changing content filters. We will disable all + messages = [ + # {"content": system_prompt, "role": "system"}, + {"content": prompt, "role": "user"} + ] + response = Response( + output=completion( + model=model["model_id"], + messages=messages, + safety_settings=safety_settings, + caching=False, + num_retries=10, + request_timeout=60, + **model["params"], + ) + ).output + # print(response) + else: + messages = [ + # {"content": system_prompt, "role": "system"}, + {"content": prompt, "role": "user"} + ] + response = Response( + output=completion( + model=model["model_id"], + messages=messages, + caching=False, + num_retries=10, + request_timeout=60, + **model["params"], + ) + ).output + + res = MultimodalOutput( + text_output=response["choices"][0]["message"]["content"], + ) + # print(response["choices"][0]["message"]["content"]) + token_usage = response["usage"]["total_tokens"] + logger.log(token_usage) + return res + + +def main(): + q = "How many people worldwide have their basic needs met when it comes to food, " + "water, toilets, electricity, schooling and healthcare?" + print( + model_compare( + "1", + q, + "en_US", + "Around 20%", + 3, + "Around 50%", + 2, + "Around 80%", + 1, + ExperimentState(), + ) + ) + + +if __name__ == "__main__": + main() diff --git a/yival_experiments/custom_configuration/model_config_variation_generator.py b/yival_experiments/custom_configuration/model_config_variation_generator.py new file mode 100644 index 0000000..2c93131 --- /dev/null +++ b/yival_experiments/custom_configuration/model_config_variation_generator.py @@ -0,0 +1,51 @@ +from dataclasses import asdict, dataclass, field +from typing import Any, Iterator, List, Optional + +# from yival.schemas.experiment_config import WrapperVariation +# ^ this is not working for dict so I write my own version + +from yival.variation_generators.base_variation_generator import BaseVariationGenerator + +from model_config_variation_generator_config import ModelConfigVariationGeneratorConfig + + +@dataclass +class WrapperVariation: + """ + Represents a variation within a wrapper. + The value can be any type, but typical usages might include strings, + numbers, configuration dictionaries, or even custom class configurations. + """ + + value_type: str # e.g., "string", "int", "float", "ClassA", ... + value: Any # The actual value or parameters to initialize a value + instantiated_value: Any = field(init=False) + variation_id: Optional[str] = None + + def asdict(self): + return asdict(self) + + def __post_init__(self): + self.instantiated_value = self.instantiate() + + def instantiate(self) -> Any: + """ + Returns an instantiated value based on value_type and params. + """ + return self.value + + +class ModelConfigVariationGenerator(BaseVariationGenerator): + def __init__(self, config: ModelConfigVariationGeneratorConfig): + super().__init__(config) + self.config = config + + def generate_variations(self) -> Iterator[List[WrapperVariation]]: + if not self.config.models: + yield [] + else: + variations = [ + WrapperVariation(value_type="dict", value=var) + for var in self.config.models + ] + yield variations diff --git a/yival_experiments/custom_configuration/model_config_variation_generator_config.py b/yival_experiments/custom_configuration/model_config_variation_generator_config.py new file mode 100644 index 0000000..eed4ffb --- /dev/null +++ b/yival_experiments/custom_configuration/model_config_variation_generator_config.py @@ -0,0 +1,9 @@ +from dataclasses import dataclass +from yival.schemas.varation_generator_configs import BaseVariationGeneratorConfig + +from typing import Optional, List, Dict, Any + + +@dataclass +class ModelConfigVariationGeneratorConfig(BaseVariationGeneratorConfig): + models: Optional[List[Dict[str, Any]]] = None # List of variations to generate diff --git a/yival_experiments/custom_configuration/model_config_wrapper.py b/yival_experiments/custom_configuration/model_config_wrapper.py new file mode 100644 index 0000000..b84dd16 --- /dev/null +++ b/yival_experiments/custom_configuration/model_config_wrapper.py @@ -0,0 +1,34 @@ +from typing import Optional, Dict, Any + +from model_config_wrapper_config import ModelConfigWrapperConfig +from yival.wrappers.base_wrapper import BaseWrapper +from yival.experiment.experiment_runner import ExperimentState + + +class ModelConfigWrapper(BaseWrapper): + """ + A wrapper for model configuration. + + Configuration is a dictionary contains 2 keys: + + - model_name: the name of model, which is a string + - params: the configuration of model, which is a dictionary + """ + + default_config = ModelConfigWrapperConfig() + + def __init__( + self, + value: Dict[str, Any], + name: str, + config: Optional[ModelConfigWrapperConfig] = None, + state: Optional[ExperimentState] = None, + ) -> None: + super().__init__(name, config, state) + self._value = value + + def get_value(self) -> Dict[str, Any]: + variation = self.get_variation() + if variation is not None: + return variation + return self._value diff --git a/yival_experiments/custom_configuration/model_config_wrapper_config.py b/yival_experiments/custom_configuration/model_config_wrapper_config.py new file mode 100644 index 0000000..8bf8725 --- /dev/null +++ b/yival_experiments/custom_configuration/model_config_wrapper_config.py @@ -0,0 +1,12 @@ +from dataclasses import dataclass + +from yival.schemas.wrapper_configs import BaseWrapperConfig + + +@dataclass +class ModelConfigWrapperConfig(BaseWrapperConfig): + """ + Configuration specific to the ModelConfigWrapper. + """ + + pass diff --git a/yival_experiments/custom_configuration/question_reader.py b/yival_experiments/custom_configuration/question_reader.py new file mode 100644 index 0000000..57a916b --- /dev/null +++ b/yival_experiments/custom_configuration/question_reader.py @@ -0,0 +1,53 @@ +from typing import Iterator, List + +from question_reader_config import QuestionReaderConfig +from yival.data.base_reader import BaseReader +from yival.schemas.common_structures import InputData + +from lib.pilot.helpers import read_ai_eval_spreadsheet, get_questions + + +class QuestionReader(BaseReader): + """ + QuestionReader is ... + + Attributes: + config (TXTReaderConfig): Configuration object specifying reader parameters. + + Methods: + __init__(self, config: TXTReaderConfig): Initializes the TXTReader with + a given configuration. + read(self, path: str) -> Iterator[List[InputData]]: Reads the TXT file + and yields chunks of InputData. + """ + + config: QuestionReaderConfig + default_config = QuestionReaderConfig() + + def __init__(self, config: QuestionReaderConfig): + super().__init__(config) + self.config = config + + def read(self, path: str) -> Iterator[List[InputData]]: + sheet = read_ai_eval_spreadsheet() + questions = get_questions(sheet) + + for q, opts in questions: + options_text = [f"{opt.letter}. {opt.question_option}" for opt in opts] + content = { + "question_id": q.question_id, + "question_text": q.published_version_of_question, + "options_text": options_text, + } + correct_answer = list( + filter(lambda x: x.correctness_of_answer_option == 1, opts) + )[0] + expected_result = ( + f"{correct_answer.letter}. {correct_answer.question_option}" + ) + + example_id = self.generate_example_id({"content": content}, "") + input_data_instance = InputData( + example_id=example_id, content=content, expected_result=expected_result + ) + yield [input_data_instance] diff --git a/yival_experiments/custom_configuration/question_reader_config.py b/yival_experiments/custom_configuration/question_reader_config.py new file mode 100644 index 0000000..f5f4922 --- /dev/null +++ b/yival_experiments/custom_configuration/question_reader_config.py @@ -0,0 +1,12 @@ +from dataclasses import asdict, dataclass +from yival.data.base_reader import BaseReaderConfig + + +@dataclass +class QuestionReaderConfig(BaseReaderConfig): + """ + Configuration specific to the questions reader. + """ + + def asdict(self): + return asdict(self) diff --git a/yival_experiments/data/questions_cn.csv b/yival_experiments/data/questions_cn.csv new file mode 100644 index 0000000..3683fe8 --- /dev/null +++ b/yival_experiments/data/questions_cn.csv @@ -0,0 +1,209 @@ +question_id,question_text,language,option_a,option_a_correctness,correct_answer,option_b,option_b_correctness,option_c,option_c_correctness +21,1980年,世界上大约40%的人口生活在极端贫困中,每天的生活费不足2美元。今天这个比例是多少?,zh-CN,10%,Correct,10%,30%,Wrong,50%,Very Wrong +14,全球有多少塑料垃圾最终进入海洋?,zh-CN,小于 6%,Correct,小于 6%,大约 36%,Wrong,大于 66%,Very Wrong +1523,在印度、中国、巴基斯坦、越南、柬埔寨、缅甸和印度尼西亚这些拥有大量纺织厂的国家,最低工资大致是多少?,zh-CN,大约一天 0.2 美元,Very Wrong,大约一天 10 美元,大约一天 1 美元,Wrong,大约一天 10 美元,Correct +2,在过去的一百年里,每年死于自然灾害的人数有什么变化?,zh-CN,增加一倍以上,Very Wrong,减少到一半以下,基本没有变化,Wrong,减少到一半以下,Correct +31,全世界有多少婴儿是在接受过训练的保健工作者在场的情况下出生的?,zh-CN,小于 30%,Very Wrong,大于 80%,大约 50%,Wrong,大于 80%,Correct +1,全球自杀率在近 20 年里有什么变化?,zh-CN,减少了大约 25%,Correct,减少了大约 25%,基本没有变化,Wrong,增加了大约 25%,Very Wrong +72,1990 年,世界上有 3%的人口生活在与他们出生地不同的国家。今天这个比例是多少?,zh-CN,4%,Correct,4%,14%,Wrong,24%,Very Wrong +1603,到 2050 年,哪个地区的老年人(65 岁以上)数量将不会翻番?,zh-CN,低收入国家,Very Wrong,高收入国家,中等收入国家,Wrong,高收入国家,Correct +1506,当今世界有 20 亿 0-14 岁的儿童。根据联合国的数据,2100 年将有多少儿童?,zh-CN,40 亿,Very Wrong,20 亿,30 亿,Wrong,20 亿,Correct +32,在哪些国家,人们对自己的生活平均满意度最低?,zh-CN,低收入的国家,Correct,低收入的国家,中等收入的国家,Wrong,高收入的国家,Very Wrong +64,2022 年全球使用互联网的人口比例是多少?,zh-CN,大约 60%,Correct,大约 60%,大约 75%,Wrong,大约 95%,Very Wrong +82,全球250家最富有的公司中,有多少家公司在其年度报告中将气候变化描述为一项风险?,zh-CN,约10%,Very Wrong,约60%,约30%,Wrong,约60%,Correct +1649,科学家是什么时候开始意识到人类活动能够影响气候的?,zh-CN,1900 年前后,Correct,1900 年前后,1950 年前后,Wrong,1980 年前后,Very Wrong +1639,以下哪种气体不是温室气体?,zh-CN,水蒸气,Wrong,氮气,氮气,Correct,臭氧,Very Wrong +1634,2020 年,70% 的欧洲人表示他们计划改用更环保的能源供应商,以应对气候变化。有多少美国人计划这样做?,zh-CN,24%,Very Wrong,64%,44%,Wrong,64%,Correct +1633,70% 的欧洲人表示,他们计划在 2020 年改用更环保的能源供应商,以应对气候变化。有多少中国人计划这样做?,zh-CN,34%,Very Wrong,94%,64%,Wrong,94%,Correct +1623,目前,地球的平均气温为 15℃。如果没有温室气体,地球的平均温度会是多少?,zh-CN,-18 度,Correct,-18 度,+6 度,Wrong,+21 度,Very Wrong +1592,从全球来看,过去 100 年中平均海平面每年上升多少?,zh-CN,每年 2 毫米(0.08 英寸),Correct,每年 2 毫米(0.08 英寸),每年 20 毫米(0.8 英寸),Wrong,每年 200 毫米(8 英寸),Very Wrong +1590,水蒸气如何加剧温室效应(使地球大气层保持温暖)?,zh-CN,水蒸气不产生影响,Wrong,水蒸气的作用很大,水蒸气的作用很大,Correct,水蒸气不是温室气体,Very Wrong +86,在联合国承认的 195 个国家中,有多少国家采纳了关于气候变化和环境的《巴黎协定》?,zh-CN,92 个,Very Wrong,192 个,142 个,Wrong,192 个,Correct +7,世界上有多少人生活在海拔 5 米或更低的地区?,zh-CN,大约 11%,Correct,大约 11%,大约 31%,Wrong,大约 51%,Very Wrong +5,全球暖化带来的多余热量中有多少被海洋吸收了?,zh-CN,約百分之 10,Very Wrong,約百分之 90,約百分之 50,Wrong,約百分之 90,Correct +1628,在全球范围内,从家庭、企业和街道收集的垃圾中,有多大比例最终被送往有管理的垃圾填埋场(非露天垃圾场)?,zh-CN,35%左右,Correct,35%左右,70%左右,Wrong,95%左右,Very Wrong +1586,与高收入国家的人相比,生活在中等收入国家的人每人每天产生多少废物?,zh-CN,双倍数量的废物,Very Wrong,一半数量的废物,差不多,Wrong,一半数量的废物,Correct +1585,北美产生的垃圾占世界垃圾总量的多少?,zh-CN,大约 14%,Correct,大约 14%,大约 28%,Wrong,大约 42%,Very Wrong +84,在全球从家庭、企业和学校收集的所有垃圾中,塑料占总重量的多少?,zh-CN,大约 12%,Correct,大约 12%,大约 42%,Wrong,大约 72%,Very Wrong +83,在全球范围内,粮食从收获到商店销售之间损失了多少?,zh-CN,大约 15%,Correct,大约 15%,大约 30%,Wrong,大约 45%,Very Wrong +81,从发现消耗臭氧层的物质到签署禁止使用这些物质的国际协定用了多少年?,zh-CN,14 年,Correct,14 年,24 年,Wrong,34 年,Very Wrong +16,除水之外,世界上使用量最大的原材料是什么?,zh-CN,石油,Wrong,沙子,沙子,Correct,木材,Very Wrong +1582,全世界有多少特大城市(都市区人口超过 1 000 万)?,zh-CN,约 12 个,Very Wrong,约 35 个,约 23 个,Wrong,约 35 个,Correct +80,自 1990 年以来,欧洲约有 200 万人因自然灾害而暂时无家可归。同期亚洲的数字是……,zh-CN,与欧洲大致相同,Very Wrong,欧洲的 50 倍,欧洲的 5 倍,Wrong,欧洲的 50 倍,Correct +79,特大城市是指居民超过 1000 万的城市。预计到 2030 年,居住在特大城市的人口将占世界人口的多大比例?,zh-CN,大约 9%,Correct,大约 9%,大约 39%,Wrong,大约 69%,Very Wrong +78,2020 年,非洲约有 68 座城市的居民人数超过 100 万。根据联合国专家的预测,到 2030 年,非洲将有多少这样规模的城市?,zh-CN,小于 60 个,Very Wrong,超过 90 个,大约 70 个,Wrong,超过 90 个,Correct +77,在世界陆地总面积中,有多少面积建有房屋或道路等有形基础设施(不包括农田)?,zh-CN,低于 5%,Correct,低于 5%,大约 15%,Wrong,超过 25%,Very Wrong +13,世界上有多少人口居住在特大城市(至少有 1000 万人口的城市)?,zh-CN,约 8%,Correct,约 8%,约 28%,Wrong,约 48%,Very Wrong +75,国际货币基金组织(IMF)自成立以来,已经有 12 位总裁。其中有多少人出生在欧洲?,zh-CN,4,Very Wrong,12,8,Wrong,12,Correct +74,国际货币基金组织(IMF)成员中,中收入和低收入国家占多大比例?,zh-CN,大约 20%,Very Wrong,大约 70%,大约 45%,Wrong,大约 70%,Correct +73,在 195 个国家中,有多少国家承诺根据联合国《消除一切形式种族歧视公约》制定反对种族主义的法律?,zh-CN,10 个国家,Very Wrong,180 个国家,80 个国家,Wrong,180 个国家,Correct +71,如果以最富有的 10% 的人在所有收入中所占比例来衡量,世界上哪个地区的收入不平等程度最小?,zh-CN,中东,Very Wrong,欧洲,欧洲,Correct,撒哈拉以南非洲,Wrong +17,世界上有多少国家制定了禁止工作场所性骚扰的法律?,zh-CN,大约 30%,Very Wrong,大约 70%,大约 50%,Wrong,大约 70%,Correct +1625,2020 年,制造业对世界经济的贡献有多大?,zh-CN,15%左右,Correct,15%左右,30%左右,Wrong,45%左右,Very Wrong +1581,2021 年,全球货轮运载了 110 亿吨货物。其中石油、石油产品、天然气和化学品占多大比例?,zh-CN,大约 30%,Correct,大约 30%,大约 40%,Wrong,大约 50%,Very Wrong +62,全球所有工人中制造业工人的占比是多少?,zh-CN,约 15%,Correct,约 15%,约 35%,Wrong,约 55%,Very Wrong +61,2020 年,高收入国家的港口处理了约 3.5 亿个集装箱。中收入和低收入国家的这一数字是多少?,zh-CN,不到 2 亿,Very Wrong,超过 4 亿,大约 3 亿,Wrong,超过 4 亿,Correct +60,世界上有多少人拥有移动电话(和电话号码)?,zh-CN,接近 70%,Correct,接近 70%,接近 80%,Wrong,接近 90%,Very Wrong +18,世界经济中有多少来自农业、林业和渔业?,zh-CN,大约 5%,Correct,大约 5%,大约 25%,Wrong,大约 45%,Very Wrong +1636,与前一年相比,由于新冠病毒大流行,2020 年全球二氧化碳排放量减少了多少?,zh-CN,减少 5% 左右,Correct,减少 5% 左右,减少 20% 左右,Wrong,减少 40% 左右,Very Wrong +1653,在全球范围内,有多少工人从事未在政府登记的非正规工作(农业除外)?,zh-CN,约20%,Very Wrong,约60%,约40%,Wrong,约60%,Correct +1646,低收入国家的所有收入中有多少来自农业、林业和渔业?,zh-CN,25%左右,Correct,25%左右,50%左右,Wrong,75%左右,Very Wrong +1645,高收入国家平均约 25% 的经济产出来自工业部门(包括制造业和建筑业)。低收入国家的这一比例是多少?,zh-CN,大约 25%,Correct,大约 25%,大约 45%,Wrong,大约 65%,Very Wrong +1643,低收入国家有多少人拥有某种形式的银行账户?,zh-CN,15%左右,Very Wrong,40%左右,25%左右,Wrong,40%左右,Correct +1620,旅游业在全球经济总量中占多大比重?,zh-CN,10%左右,Correct,10%左右,25%左右,Wrong,40%左右,Very Wrong +1611,当今世界有多少人口生活在中等收入国家?,zh-CN,25%左右,Very Wrong,75%左右,50%左右,Wrong,75%左右,Correct +1525,2019 年,全球 80%的男性在劳动力市场中。女性的比例是多少?,zh-CN,52%,Correct,52%,62%,Wrong,72%,Very Wrong +1587,世界上有多少男青年(15-24 岁)没有上学、就业或培训?,zh-CN,大约 15%,Correct,大约 15%,大约 25%,Wrong,大约 35%,Very Wrong +1580,在全世界所有儿童(5-17 岁)中,有多少人是受剥削的童工?,zh-CN,大约 10%,Correct,大约 10%,大约 30%,Wrong,大约 50%,Very Wrong +1578,在全世界范围内,非正规就业的年轻人(15-24 岁)占所有在工作的年轻人的比例是多少?,zh-CN,大约 25%,Very Wrong,大约 75%,大约 50%,Wrong,大约 75%,Correct +1522,自 1970 年以来,40 个最富有国家的平均收入增长了一倍多。其他国家的平均收入怎样?,zh-CN,减少到一半,Very Wrong,增加 1 倍多,大致保持不变,Wrong,增加 1 倍多,Correct +57,全世界有多少超过退休年龄的人有权领取养老金?,zh-CN,大约 25%,Very Wrong,大约 75%,大约 45%,Wrong,大约 75%,Correct +56,当下,全世界 65% 的人口处于工作年龄(15-64 岁)。联合国专家认为 2100 年这一数字会是多少?,zh-CN,50%,Wrong,60%,60%,Correct,70%,Very Wrong +53,全球约有 1.6 亿儿童被雇为童工。他们大多在哪个部门工作?,zh-CN,工业,Very Wrong,农业,农业,Correct,服务业,Wrong +52,1990 年,世界上有 19% 的 65 岁及以上老年人仍在工作。预计 2030 年这一比例会是多少?,zh-CN,大约 21%,Correct,大约 21%,大约 41%,Wrong,大约 61%,Very Wrong +1691,在全世界使用的所有能源中,电力占多大比例?,zh-CN,20%左右,Correct,20%左右,50%左右,Wrong,80%左右,Very Wrong +1672,1990 年,全球约有 60% 的电力是用化石燃料生产的。今天这个数字是多少?,zh-CN,40%左右,Very Wrong,60%左右,50%左右,Wrong,60%左右,Correct +1638,在全球电力总成本中,从发电站到用户的平均传输成本是多少?,zh-CN,小于 1%,Very Wrong,30%左右,Around 15%,Wrong,30%左右,Correct +1637,全世界使用的所有能源中有多少来自现代可再生能源(太阳能、风能、水能和现代生物燃料)?,zh-CN,小于 10%,Correct,小于 10%,20%左右,Wrong,35%左右,Very Wrong +1524,与 2000 年相比,2022 年全世界使用了多少化石燃料(石油、煤炭和天然气)?,zh-CN,95%(减少了一点),Very Wrong,145%(增加很多),120%(增加了一点),Wrong,145%(增加很多),Correct +54,在当今世界使用的所有可再生能源中,传统的生物质燃烧(如木炭、木材和农业废物)占据了多少比例?,zh-CN,大约 10%,Very Wrong,大约 40%,大约 25%,Wrong,大约 40%,Correct +55,"Compared to 1980, the cost of energy from solar panels today is roughly:",zh-CN,1% of the 1980 cost,Correct,1% of the 1980 cost,21% of the 1980 cost,Wrong,41% of the 1980 cost,Very Wrong +51,1950 年,0% 的能源消耗来自核能。今天这个数字是多少?,zh-CN,大约 5%,Correct,大约 5%,大约 25%,Wrong,大约 45%,Very Wrong +50,世界上有多少人能用上电?,zh-CN,小于 20%,Very Wrong,大于 80%,大约 50%,Wrong,大于 80%,Correct +1626,全世界有多少人需要花费超过 30 分钟的往返时间来获取饮用水?,zh-CN,10%左右,Correct,10%左右,25%左右,Wrong,50%左右,Very Wrong +1577,世界上有多少人在家里有肥皂和水洗手?,zh-CN,大约 20%,Very Wrong,大约 70%,大约 40%,Wrong,大约 70%,Correct +1576,在世界范围内,有多少生活在农村地区的人拥有厕所并且不用与其他家庭共用?,zh-CN,大约 20%,Very Wrong,大约 60%,大约 40%,Wrong,大约 60%,Correct +49,有多少国家制定了要求在规划和管理淡水资源时需要当地社区参与的规则?,zh-CN,30%,Very Wrong,70%,50%,Wrong,70%,Correct +48,在 195 个国家中,有多少个国家至少有一座海水淡化厂?,zh-CN,30,Very Wrong,180,100,Wrong,180,Correct +47,在全世界使用的所有淡水中,有多少用于农业?,zh-CN,大约 30%,Very Wrong,大约 70%,大约 50%,Wrong,大约 70%,Correct +46,在世界范围内,有多少人没有任何形式的厕所,而不得不使用灌木丛、田野或街道?,zh-CN,大约 10%,Correct,大约 10%,大约 30%,Wrong,大约 50%,Very Wrong +45,全世界有多少生活在农村地区的人使用地表水(如湖泊、河流和溪流)作为饮用水?,zh-CN,小于 10%,Correct,小于 10%,大约 30%,Wrong,大于 60%,Very Wrong +1652,有多少国家的法律规定男女同工同酬?,zh-CN,10%左右,Very Wrong,40%左右,25%左右,Wrong,40%左右,Correct +1650,有多少国家的最高政治领导人是女性?,zh-CN,4 个左右,Very Wrong,19 个左右,12 个左右,Wrong,19 个左右,Correct +1619,在撒哈拉以南非洲地区,有多少女性在 18 岁之前结婚?,zh-CN,30%左右,Correct,30%左右,50%左右,Wrong,70%左右,Very Wrong +1589,1990 年,全球 39% 的劳动力为女性。如今这一比例是多少?,zh-CN,39%,Correct,39%,42%,Wrong,46%,Very Wrong +1574,在 195 个国家中,有多少个国家的已婚男性和女性不平等地享有拥有土地或房屋的法律权利?,zh-CN,约 20 个国家,Correct,约 20 个国家,约 80 个国家,Wrong,约 140 个国家,Very Wrong +43,在 195 个国家中,有多少个国家未满 18 岁可以合法结婚?,zh-CN,19,Very Wrong,139,79,Wrong,139,Correct +42,截至 1990 年,世界上有 18 个国家由女性国家元首或政府首脑领导。今天这个数字是多少?,zh-CN,36,Very Wrong,86,56,Wrong,86,Correct +41,在世界范围内,妇女使用最多的避孕方法是哪一种?,zh-CN,避孕药,Very Wrong,绝育,绝育,Correct,宫内节育器(IUD),Wrong +10,世界上有多少公司的高管或 CEO 由女性担任?,zh-CN,约 2%,Very Wrong,约 18%,约 10%,Wrong,约 18%,Correct +44,在 195 个国家中,有多少国家签署了联合国《消除对妇女一切形式歧视公约》?,zh-CN,50,Very Wrong,190,120,Wrong,190,Correct +40,在世界范围内,妇女在国家议会中所占的席位比例是多少?,zh-CN,大约 5%,Very Wrong,大约 25%,大约 15%,Wrong,大约 25%,Correct +3,在世界上的低收入国家里,有百分之多少的女孩(在疫情前)上学到至少十一岁?,zh-CN,大约 20%,Very Wrong,大约 60%,大约 40%,Wrong,大约 60%,Correct +35,全世界有多少大学生在自己的本国(而不是国外)获得学位?,zh-CN,大约 77%,Very Wrong,大约 97%,大约 87%,Wrong,大约 97%,Correct +36,在低收入国家的所有小学教师中,有多少接受过培训?,zh-CN,30%,Very Wrong,70%,50%,Wrong,70%,Correct +39,2021 年有多少难民儿童上小学?,zh-CN,小于 20%,Very Wrong,大于 60%,大约 40%,Wrong,大于 60%,Correct +38,全世界有多少儿童在入学前一年上过某种形式的学前班?,zh-CN,大约 20%,Very Wrong,大约 60%,大约 40%,Wrong,大约 60%,Correct +1510,全世界 6 至 11 岁的儿童中,有多少人上学?,zh-CN,小于 25%,Very Wrong,超过 85%,大约 60%,Wrong,超过 85%,Correct +1575,全世界所有到了上小学年龄却没有上学的儿童中,有多少是女孩?,zh-CN,大约 55%,Correct,大约 55%,大约 65%,Wrong,大约 75%,Very Wrong +1579,全球有多少小学教师没有接受过相关培训?,zh-CN,大约 15%,Correct,大约 15%,大约 35%,Wrong,大约 55%,Very Wrong +1561,1950 年,大约 50% 的成年人至少接受过一些基础教育。今天的比例是多少?,zh-CN,大约 40%,Very Wrong,大约 80%,大约 60%,Wrong,大约 80%,Correct +1612,在撒哈拉以南非洲地区,有多少小学能用上一些电?,zh-CN,10%左右,Very Wrong,30%左右,20%左右,Wrong,30%左右,Correct +33,2021 年全球有多少 1 岁儿童接种了某种疾病的疫苗?,zh-CN,20% 以下,Very Wrong,80% 以上,约 50%,Wrong,80% 以上,Correct +34,全球约有 3800 万艾滋病病毒感染者。其中有多少人在 2021 年获得了抗艾滋病病毒药物?,zh-CN,15% 以下,Very Wrong,50% 以上,大约 30%,Wrong,50% 以上,Correct +1517,现在的非洲儿童死亡人数与以下哪年的欧洲儿童死亡人数持平:,zh-CN,1850,Very Wrong,1950,1900,Wrong,1950,Correct +1573,全世界所有学校中,有多少比例的学校为孩子们提供肥皂和水洗手?,zh-CN,25%左右,Very Wrong,55%左右,55%左右,Correct,85%左右,Wrong +120,今年全世界预计会有多少天花病例?,zh-CN,零病例,Correct,零病例,十万病例,Wrong,一百万病例,Very Wrong +119,1990 年,超过 400 万人死于室内污染。从那时起,这个数字发生了什么变化?,zh-CN,降低了超过30%,Correct,降低了超过30%,大致保持不变,Wrong,增加了超过30%,Very Wrong +95,1990 年,全世界约有 9% 的儿童在五岁前死亡。现今这个数字是多少?,zh-CN,大约 4%,Correct,大约 4%,大约 9%,Wrong,大约 14%,Very Wrong +96,2000 年至 2017 年间,全球新增结核病例数发生了什么变化?,zh-CN,增加了 20%,Very Wrong,降低了 20%,几乎保持不变,Wrong,降低了 20%,Correct +94,当下,全球平均寿命约为 72 岁。一百年前的全球预期寿命是多少?,zh-CN,37 岁,Correct,37 岁,47 岁,Wrong,57 岁,Very Wrong +1605,欧洲(包括俄罗斯和土耳其)有多少儿童全程接种了两剂麻疹疫苗?,zh-CN,大约 30%,Very Wrong,大约 90%,大约 60%,Wrong,大约 90%,Correct +1548,在撒哈拉以南非洲地区,有多少 5 岁以下儿童睡在蚊帐里以预防疟疾?,zh-CN,大约 25%,Very Wrong,大约 50%,大约 35%,Wrong,大约 50%,Correct +1641,撒哈拉以南非洲的平均预期寿命是多少?,zh-CN,40 岁左右,Very Wrong,60 岁左右,50 岁左右,Wrong,60 岁左右,Correct +1655,在全球范围内,非法使用毒品直接导致的死亡人数占总死亡人数的比例是多少?,zh-CN,小于 1%,Correct,小于 1%,10%左右,Wrong,超过 20%,Very Wrong +1656,在全世界所有孕妇中,有多少人是在没有经过受过教育的助产士、护士或医生检查的前提下分娩的?,zh-CN,15%左右,Correct,15%左右,35%左右,Wrong,55%左右,Very Wrong +1642,与德国和美国等高收入国家相比,联合国儿童基金会在 2018 年购买儿童疫苗时,平均成本价怎样?,zh-CN,两倍以上的价格,Very Wrong,低于 20%的价格,大约一半的价格,Wrong,低于 20%的价格,Correct +30,当今的低收入国家在 1970 年的预期寿命为 44 岁。现在的预期寿命是多少呢?,zh-CN,40 岁,Very Wrong,60 岁,50 岁,Wrong,60 岁,Correct +1632,在全球范围内,超重和肥胖造成的死亡占多大比例?,zh-CN,小于 10%,Correct,小于 10%,25%左右,Wrong,40%左右,Very Wrong +1513,从 2005 年到 2020 年,用于贫困国家粮食援助的资金达 570 亿美元。有多少钱用于研究能生产更多粮食或在极端天气下生存的新作物?,zh-CN,90 亿美元,Correct,90 亿美元,390 亿美元,Wrong,690 亿美元,Very Wrong +1604,如今欧洲(包括俄罗斯和土耳其)有多少肥胖儿童?,zh-CN,大约 10%,Correct,大约 10%,大约 25%,Wrong,大约 40%,Very Wrong +1511,非洲人吃的食物有多少产自非洲?,zh-CN,少于20%,Very Wrong,超过80%,约50%,Wrong,超过80%,Correct +27,全世界有多少个国家在基因库中的保存了植物遗传材料?,zh-CN,小于 10 个,Very Wrong,大约 100 个,大约 50 个,Wrong,大约 100 个,Correct +29,1995 年,所有国家共花费 46 亿美元用于农业出口补贴。2019 年花了多少?,zh-CN,1 亿美元,Correct,1 亿美元,10 亿美元,Wrong,100 亿美元,Very Wrong +26,全世界有多少 5 岁以下儿童超重?,zh-CN,6%,Correct,6%,26%,Wrong,46%,Very Wrong +28,以下哪个地区的 5 岁以下儿童体重严重不足的比例最高?,zh-CN,北非 & 中东,Very Wrong,南亚,南亚,Correct,撒哈拉以南非洲,Wrong +25,世界上每生产 100 公斤粮食,有多少被运往其他国家?,zh-CN,17 公斤,Correct,17 公斤,37 公斤,Wrong,57 公斤,Very Wrong +118,在过去 20 年中,生活在极端贫困中的人口比例...,zh-CN,减少一半以上,Correct,减少一半以上,保持差不多不变,Wrong,接近翻倍,Very Wrong +1640,在全球范围内,每天收入低于 2 美元被视为赤贫。北欧国家(瑞典、挪威、丹麦、芬兰、冰岛)的国家贫困线大致如下:,zh-CN,每天 10 美元,Very Wrong,每天 30 美元,每天 20 美元,Wrong,每天 30 美元,Correct +1528,全世界有多少人的食物、水、厕所、电力、学校教育和医疗保健等基本需求得到满足?,zh-CN,20% 左右,Very Wrong,80% 左右,50% 左右,Wrong,80% 左右,Correct +1530,世界上每天收入不足 2 美元的赤贫人口中,有多少生活在中等收入国家?,zh-CN,大约 15%,Very Wrong,大约 60%,大约 30%,Wrong,大约 60%,Correct +24,世界上有多少人使用不产生烟雾的炉灶做饭?,zh-CN,大约 20%,Very Wrong,大约 60%,大约 40%,Wrong,大约 60%,Correct +23,在高收入国家的所有 65 岁或以上人口中,有多少人生活在贫困线以下?,zh-CN,14%,Correct,14%,29%,Wrong,44%,Very Wrong +22,在 195 个国家中,有多少个国家为残疾人提供某种形式的社会保障福利?,zh-CN,46,Very Wrong,186,116,Wrong,186,Correct +1504,世界人口中有多少生活在平均每个女性生育不到 3 个孩子的国家?,zh-CN,40%,Very Wrong,80%,60%,Wrong,80%,Correct +104,在过去 5 年中,哪一组国家派出的联合国维和部队最多?,zh-CN,德国,瑞典,荷兰,爱尔兰,Wrong,埃塞俄比亚,卢旺达,孟加拉国,印度,尼泊尔,埃塞俄比亚,卢旺达,孟加拉国,印度,尼泊尔,Correct,法国,美国,日本,韩国,瑞士,英国,Very Wrong +85,如果我们现在把每年的二氧化碳净排放量减半,全球平均温度会发生什么变化?,zh-CN,会降低,Very Wrong,会持续上升,会保持不变,Wrong,会持续上升,Correct +58,自 2000 年以来,全球每年使用的原材料总量发生了什么变化?,zh-CN,几乎保持不变,Very Wrong,增加了大约 70%,增加了大约 35%,Wrong,增加了大约 70%,Correct +1676,2022 年,联合国花费了大约 64 亿美元来帮助全世界的难民。西欧各国政府为帮助西欧境内的难民花费了多少钱?,zh-CN,不到 30 亿美元,Very Wrong,超过 200 亿美元,大约 50 亿美元,Wrong,超过 200 亿美元,Correct +12,世界上有多少人口没有足够的食物来满足他们的日常需要?,zh-CN,约11%,Correct,约11%,约23%,Wrong,约37%,Very Wrong +1616,低收入国家的经济有多少来自人们从国外寄回家的钱?,zh-CN,大约 6%,Correct,大约 6%,大约 26%,Wrong,大约 46%,Very Wrong +93,在 195 个国家中,有多少国家批准了 1982 年出台的联合国公约《海洋法》?,zh-CN,45 个国家,Very Wrong,165 个国家,105 个国家,Wrong,165 个国家,Correct +1498,对于所有脊椎动物(有骨骼的动物)而言,其野生种群数量在过去 50 年中平均减少了多少?,zh-CN,减少 15% 左右,Very Wrong,减少 70% 左右,减少 40% 左右,Wrong,减少 70% 左右,Correct +1521,当生物学家在 1950 年开始统计海洋中的鱼类数量时,大约 1%的鱼类资源被过度开发。到 2019 年,这个比例是…,zh-CN,…5%左右,Very Wrong,…超过 35%,…20%左右,Wrong,…超过 35%,Correct +92,自 2016 年以来,世界各国水域中海洋保护区的比例发生了什么变化?,zh-CN,减少了 75%,Very Wrong,增加了 75%,几乎保持不变,Wrong,增加了 75%,Correct +91,全球每年平均食用 6 公斤牛肉和小牛肉。平均每人消费多少鱼肉?,zh-CN,大约 3kg,Very Wrong,大约 10kg,大约 6kg,Wrong,大约 10kg,Correct +106,世界上有多少人在自己居住的地方独自走夜路会感到安全?,zh-CN,小于 30%,Very Wrong,超过 60%,大约 45%,Wrong,超过 60%,Correct +97,哪类动物的濒危物种比例最高?,zh-CN,鸟类,Wrong,两栖动物,哺乳动物,Very Wrong,两栖动物,Correct +103,世界上有多少人说他们对当地警察有信心?,zh-CN,小于 15%,Very Wrong,超过 50%,25% 左右,Wrong,超过 50%,Correct +1677,1990 年,各国人民和政府向联合国难民署(UNHCR)捐款 13 亿美元,用于帮助世界各地的难民。2022 年捐赠了多少?(金额已根据通货膨胀率进行调整),zh-CN,略少一点,Very Wrong,多 5 倍,多 2 倍,Wrong,多 5 倍,Correct +1678,2022 年,许多西欧国家政府为帮助新抵达的难民,为每个人每天花费超过 20 美元。 联合国在世界其他地方为每个难民平均每天花费多少钱?,zh-CN,大约 1 美元,Correct,大约 1 美元,大约 25 美元,Wrong,大约 45 美元,Very Wrong +1502,联合国可持续发展目标共有 169 项具体目标。其中有多少项提到了“民主”?,zh-CN,0 项目标,Correct,0 项目标,14 项目标,Wrong,34 项目标,Very Wrong +1499,20 世纪 50 年代,50% 的战争发生在被联合国承认为主权国家的国家之间。今天这个数字是多少?,zh-CN,5% 左右,Correct,5% 左右,25% 左右,Wrong,55% 左右,Very Wrong +6,世界上有多少人在家裡或家裡附近有安全的饮用水?,zh-CN,大约 50%,Very Wrong,大约 90%,大约 70%,Wrong,大约 90%,Correct +1500,在全球范围内,女性从事的无偿护理和家务劳动多于男性。多多少?,zh-CN,多 50%,Very Wrong,三倍左右,一倍左右,Wrong,三倍左右,Correct +37,全世界有多少 15 岁以下的儿童的阅读和数学能力没有达到最低技能要求?,zh-CN,20%,Very Wrong,60%,40%,Wrong,60%,Correct +20_text,现在,世界上大概有八十亿人。哪幅地图正确展示出当今的人口的分布?(在图中,每一个人物代表十亿人。),zh-CN,nan,Wrong,nan,nan,Correct,nan,Very Wrong +1501_text,在全世界 195 个国家中,有多少个是联合国会员国?,zh-CN,93,Very Wrong,193,143,Wrong,193,Correct +1666_text,高收入国家的人们因其富裕程度不同而排放不同数量的二氧化碳。从最穷的 10%到最富的 10%,每10%为一组,哪个选项能准确解释排放量的变化?,zh-CN,从最贫穷的 10%到最富有的 10%,排放量均匀地减少,Very Wrong,从最贫穷到最富有,排放量均匀增加,但到最富有的 10%,排放量迅速增加,从最贫穷的 10%到最富有的 10%,排放量均匀地增加,Wrong,从最贫穷到最富有,排放量均匀增加,但到最富有的 10%,排放量迅速增加,Correct +1591_text,以下哪个答案最能说明在过去 40 年中,12 千米以下和 12 千米以上的大气层平均温度是如何变化的?,zh-CN,大气层的温度在 12 千米以上和以下都有所上升,Wrong,大气层温度在 12 千米以上降低,而在 12 千米以下升高,大气层温度在 12 千米以上降低,而在 12 千米以下升高,Correct,大气层温度在 12 千米以上升高,而在 12 千米以下降低,Very Wrong +1507_text,据报道,1992 年有 56 名记者遇害。此后这个数量有什么变化?,zh-CN,急剧增加,2022 年达到 463 人遇害,Very Wrong,大致保持不变,2022年有67人遇害,2022 年增加到 257 人遇害,Wrong,大致保持不变,2022年有67人遇害,Correct +1594,2022年末,世界人口达到约80亿。有多少人会因为人道主义危机变成国际难民、寻求庇护者或者流落到其他国家和地区?,zh-CN,4600万(0.6%),Correct,4600万(0.6%),4.8亿(6%),Wrong,7.2亿(9%),Very Wrong +109,2000 年,中收入和低收入国家的贷款支出平均占其年收入的近 6%。2020 年这一数字是多少?,zh-CN,大约 4%,Correct,大约 4%,大约 8%,Wrong,大约 12%,Very Wrong +110,在全世界所有教育费用中,有多少是由政府支付的?,zh-CN,大约 40%,Very Wrong,大约 80%,大约 60%,Wrong,大约 80%,Correct +111,在最不发达国家获得的所有财政援助中,有多少来自慈善和公益事业?,zh-CN,大约 5%,Correct,大约 5%,大约 25%,Wrong,大约 50%,Very Wrong +112,世界上有多少最不发达国家设有外国投资促进机构?,zh-CN,20%,Very Wrong,80%,50%,Wrong,80%,Correct +65,在这些国家中,哪个国家收容的难民占其人口的比例最大?,zh-CN,德国,Wrong,黎巴嫩,黎巴嫩,Correct,瑞典,Very Wrong +66,世界上所有移民中,难民占多大比例?,zh-CN,大约 15%,Correct,大约 15%,大约 25%,Wrong,大约 35%,Very Wrong +69,2022 年 12 月,在全球所有难民中,流亡时间超过四年的难民占多大比例?,zh-CN,小于 30%,Very Wrong,超过 60%,大约 45%,Wrong,超过 60%,Correct +70,在计算世界上的难民人数时,这个数字包括了那些……,zh-CN,逃往其他国家的人,Correct,逃往其他国家的人,逃往祖国其他地方的人,Very Wrong,以上两者都计算在内,Wrong +108,在过去 40 年里,高收入国家对最富有的 0.1%人口征收的最高边际所得税发生了什么变化?,zh-CN,削减了三分之一,Correct,削减了三分之一,大致保持不变,Wrong,增加了三分之一,Very Wrong +107,2000 年,21%的国家告诉联合国它们有独立的人权机构。今天的比例是多少?,zh-CN,23% 的国家,Very Wrong,62% 的国家,41% 的国家,Wrong,62% 的国家,Correct +105,中收入和低收入国家在联合国大会成员国中占多大比例?,zh-CN,20% 左右,Very Wrong,70% 左右,45% 左右,Wrong,70% 左右,Correct +102,过去 10 年全球海盗袭击船只的次数发生了什么变化?,zh-CN,翻倍了,Very Wrong,减半了,没有大的变化,Wrong,减半了,Correct +101,全世界 100 年前的热带雨林,到现在仍是热带雨林的面积有多少?,zh-CN,小于 10%,Very Wrong,大于 30%,20% 左右,Wrong,大于 30%,Correct +100,过去 30 年间,全球森林面积发生了什么变化?,zh-CN,减少 50% 左右,Very Wrong,减少 10% 左右,减少 30% 左右,Wrong,减少 10% 左右,Correct +1497,全世界用于食用的鱼类中有多少来自养鱼业?,zh-CN,大约 10%,Very Wrong,大约 55%,大约 35%,Wrong,大约 55%,Correct +1512,在全球范围内,过去 50 年里用于农业的土地面积发生了什么变化?,zh-CN,增加了 50%,Wrong,大致保持不变,大致保持不变,Correct,减少了 50%,Very Wrong +1520,在过去 20 年里,每年在野外捕获的鱼类总量发生了什么变化?,zh-CN,It decreased by roughly 30%,Wrong,保持不变,保持不变,Correct,It increased by roughly 30%,Very Wrong +1529,在过去的 30 年里,全球被宣布为受保护的土地面积发生了什么变化?,zh-CN,减少了 58%,Very Wrong,增加了 8%,减少了 8%,Wrong,增加了 8%,Correct +1583,有多少动植物物种在过去 200 年里被生物学家确认灭绝了?,zh-CN,约 600 个,Correct,约 600 个,"约 60,000 个",Wrong,"约 600,000 个",Very Wrong +1596,亚马逊森林产生的氧气中,有多少是我们人类呼吸的??,zh-CN,小于 1%,Correct,小于 1%,30%,Wrong,60%,Very Wrong +1597,在一年产生的所有氧气中,有多少来自树木?,zh-CN,大约 25%,Correct,大约 25%,大约 55%,Wrong,大约 85%,Very Wrong +1598,在全世界已知的鸟类物种中,有多少属于濒危或受威胁物种?,zh-CN,大约 15%,Correct,大约 15%,大约 35%,Wrong,大约 55%,Very Wrong +1647,2001 年至 2018 年间,全球野火烧毁的总面积中,非洲所占的比例是多少?,zh-CN,10%左右,Very Wrong,70%左右,40%左右,Wrong,70%左右,Correct +89,自 20 世纪 70 年代以来,全球每年油轮漏油的次数发生了什么变化?,zh-CN,减少到十分之一,Correct,减少到十分之一,几乎保持不变,Wrong,增加到 10 倍,Very Wrong +90,石油和天然气是 2010 年赚钱最多的海洋行业。如果趋势一如既往,到 2030 年赚钱最多的将会是哪个行业?,zh-CN,石油和天然气,Wrong,旅游业,旅游业,Correct,波浪能,Very Wrong +98,如果计算世界上所有哺乳动物的总重量,大约有多少来自野生哺乳动物?,zh-CN,大约 5%,Correct,大约 5%,大约 25%,Wrong,大约 50%,Very Wrong +99,全世界用于饲养动物的农业用地占总农业用地的多大比例?,zh-CN,大约 25%,Very Wrong,大约 80%,大约 50%,Wrong,大约 80%,Correct +1610,在全世界,妇女和女童在国际移民中所占比例是多少?,zh-CN,大约 18%,Very Wrong,大约 48%,大约 33%,Wrong,大约 48%,Correct +1618,从 2011 年到 2022 年,美国和俄罗斯相互交流了多少次核武器信息?,zh-CN,0 次,Very Wrong,2.5 万次,25 次,Wrong,2.5 万次,Correct +1635,2002 年《开放天空条约》(允许成员国在对方领土上空进行观测飞行)开始生效时,有 34 个国家加入。今天有多少个国家?,zh-CN,32,Correct,32,42,Wrong,62,Very Wrong +1629,在过去 5 年中,每年大约有 35 个国家发生某种形式的暴力冲突。20 世纪 50 年代的平均数字是多少?,zh-CN,15 个国家左右,Correct,15 个国家左右,30 个国家左右,Wrong,60 个国家左右,Very Wrong +1621,大多数人表示信任他人的 15 个国家都是:,zh-CN,低收入国家,Very Wrong,高收入国家,中等收入国家,Wrong,高收入国家,Correct +1600,在全世界所有记录在案的凶杀案中,有多大比例与帮派和有组织犯罪有关?,zh-CN,大约 20%,Correct,大约 20%,大约 40%,Wrong,大约 60%,Very Wrong +1599,世界人口中每年被警方或刑事司法系统怀疑、逮捕或警告的比例是多少?,zh-CN,大约 2%,Correct,大约 2%,大约 20%,Wrong,大约 40%,Very Wrong +1547,在过去 10 年中,在非洲的战死的人数占全球所有战死人数的比例是多少?,zh-CN,大约 15%,Correct,大约 15%,大约 35%,Wrong,大约 55%,Very Wrong +1675,2022 年,在埃及、黎巴嫩、约旦和伊拉克的所有叙利亚难民中,有多少人表示他们无法负担食物、药品和住房等基本需求?,zh-CN,30%左右,Very Wrong,90%左右,60%左右,Wrong,90%左右,Correct +1674,2010 年,乌干达、孟加拉国、哥伦比亚和土耳其共有 40 万由人道主义危机造成的难民和移民。2022 年的数字是多少?,zh-CN,约 100 万,Very Wrong,约 900 万,约 500 万,Wrong,约 900 万,Correct +1673,2000 年,全球约有 20% 的难民逃往高收入国家。2021 年(乌克兰战争前夕)的数字是多少?,zh-CN,20%左右,Correct,20%左右,30%左右,Wrong,40%左右,Very Wrong +1654,世界人口从 60 亿增长到 70 亿用了 12 年。从 70 亿增加到 80 亿用了多长时间?,zh-CN,2 年,Very Wrong,12 年,7 年,Wrong,12 年,Correct +1627,如果当前的人口趋势继续下去,到 2050 年,所有国家中有多少比例的国家的人口将少于今天?,zh-CN,5%,Very Wrong,25%,15%,Wrong,25%,Correct +1622,目前地球上有 80 亿人口。联合国专家认为 2100 年会有多少人?,zh-CN,约 105 亿,Correct,约 105 亿,约 165 亿,Wrong,约 225 亿,Very Wrong +1593,预计到 2050 年,全球老年人(65 岁以上)总数将增加 8 亿。其中高收入国家老年人将占多少比例?,zh-CN,15%,Correct,15%,35%,Wrong,55%,Very Wrong +1505,根据联合国的预测,到 2100 年,世界人口将再增加 24 亿。主要原因是将有更多的……,zh-CN,儿童(15 岁以下),Very Wrong,成年人(15 到 74 岁),成年人(15 到 74 岁),Correct,老龄人口(75 岁以上),Wrong +1631,三十年前,世界上只有不到 25%的人口生活在中等收入国家。今天的比例是多少?,zh-CN,15%左右,Very Wrong,75%左右,45%左右,Wrong,75%左右,Correct +1651,哪个自由贸易区包括的国家最多?,zh-CN,北大西洋自由贸易协定(NAFTA),Very Wrong,非洲大陆自由贸易区,非洲大陆自由贸易区,Correct,欧盟,Wrong +1624,与 2022 年从富有的政府提供的国际援助总额相比,全球移民向原籍国转移了多少钱?,zh-CN,不到援助总额的 10%,Very Wrong,超过援助总额的 200%,援助总额的 30%左右,Wrong,超过援助总额的 200%,Correct +19,高收入国家政府有多少收入来自关税和进口税?,zh-CN,大约 2%,Correct,大约 2%,大约 12%,Wrong,大约 22%,Very Wrong +1648,世界贸易组织成员中,中收入和低收入国家占多大比例?,zh-CN,25%左右,Very Wrong,65%左右,45%左右,Wrong,65%左右,Correct diff --git a/yival_experiments/data/questions_en.csv b/yival_experiments/data/questions_en.csv new file mode 100644 index 0000000..60ed6bd --- /dev/null +++ b/yival_experiments/data/questions_en.csv @@ -0,0 +1,280 @@ +question_id,question_text,language,option_a,option_a_correctness,correct_answer,option_b,option_b_correctness,option_c,option_c_correctness +21,"In 1980, roughly 40% of the world's population lived in extreme poverty, with less than $2 per day. What is the share today?",en-US,10%,Correct,10%,30%,Wrong,50%,Very Wrong +14,What share of all plastic waste in the world ends up in the oceans?,en-US,Less than 6%,Correct,Less than 6%,Around 36%,Wrong,More than 66%,Very Wrong +1523,"Roughly what is the minimum wage in these countries with lots of textile factories, India, China, Pakistan, Vietnam, Cambodia, Myanmar and Indonesia?",en-US,Around $0.2 a day,Very Wrong,Around $10 a day,Around $1 a day,Wrong,Around $10 a day,Correct +2,How did the number of deaths per year from natural disasters change over the last hundred years?,en-US,More than doubled,Very Wrong,Decreased to less than half,Remained about the same,Wrong,Decreased to less than half,Correct +31,"Worldwide, how many babies are born with a trained health worker present?",en-US,Less than 30%,Very Wrong,More than 80%,Around 50%,Wrong,More than 80%,Correct +1,What happened to the global suicide rate in the last 20 years?,en-US,Decreased about 25%,Correct,Decreased about 25%,Stayed about the same,Wrong,Increased about 25%,Very Wrong +72,"In 1990, 3% of the world’s population lived in a different country than where they were born. What is that share today?",en-US,4%,Correct,4%,14%,Wrong,24%,Very Wrong +1603,"By 2050, the number of old people (age 65+) will double everywhere, except:",en-US,Low-income countries,Very Wrong,High-income countries,Middle-income countries,Wrong,High-income countries,Correct +1506,"There are 2 billion children in the world today, aged 0-14 years old. How many children will there be in the year 2100 according to the United Nations?",en-US,4 billion,Very Wrong,2 billion,3 billion,Wrong,2 billion,Correct +32,In which countries are people on average least satisfied with their lives?,en-US,Low-income countries,Correct,Low-income countries,Middle-income countries,Wrong,High-income countries,Very Wrong +64,What share of the world’s population used the Internet in 2022?,en-US,Around 60%,Correct,Around 60%,Around 75%,Wrong,Around 95%,Very Wrong +1525,Eighty percent of all men in the world were in the labor force in 2019. What was the number for women?,en-US,52%,Correct,52%,62%,Wrong,72%,Very Wrong +3,"In low-income countries across the world in 2022, what share of girls went to school until at least age 11?",en-US,Around 20%,Very Wrong,Around 60%,Around 40%,Wrong,Around 60%,Correct +35,How many university students worldwide get their degree in their home country (as opposed to abroad)?,en-US,Around 77%,Very Wrong,Around 97%,Around 87%,Wrong,Around 97%,Correct +36,"Of all primary school teachers in low-income countries, how many are trained?",en-US,30%,Very Wrong,70%,50%,Wrong,70%,Correct +39,How many child refugees attended primary school in 2021?,en-US,Less than 20%,Very Wrong,More than 60%,Around 40%,Wrong,More than 60%,Correct +38,"Across the world, how many children go to some form of preschool the year before they start school?",en-US,Around 20%,Very Wrong,Around 60%,Around 40%,Wrong,Around 60%,Correct +1510,"Of all children aged 6 to 11 in the world, how many go to school?",en-US,Less than 25%,Very Wrong,More than 85%,Around 60%,Wrong,More than 85%,Correct +1575,"Of all children in the world who are of primary school age but don't go to school, how many are girls?",en-US,Around 55%,Correct,Around 55%,Around 65%,Wrong,Around 75%,Very Wrong +1579,"Globally, how many primary school teachers are not trained for the job?",en-US,Around 15%,Correct,Around 15%,Around 35%,Wrong,Around 55%,Very Wrong +1561,"In 1950, roughly 50% of all adults had at least some basic education. What is the share today?",en-US,Around 40%,Very Wrong,Around 80%,Around 60%,Wrong,Around 80%,Correct +1612,How many primary schools in Sub-Saharan Africa have some access to electricity?,en-US,Around 10%,Very Wrong,Around 30%,Around 20%,Wrong,Around 30%,Correct +1711,What share of university teachers in the world are women?,en-US,Around 20%,Very Wrong,Around 40%,Around 30%,Wrong,Around 40%,Correct +1509,How many adults in the world say they can read?,en-US,Less than 40%,Very Wrong,More than 80%,Around 60%,Wrong,More than 80%,Correct +1755,"Of all girls aged 6 to 11 in the world, how many go to school?",en-US,Less than 25%,Very Wrong,Around 85%,Around 60%,Wrong,Around 85%,Correct +33,How many of the world's 1-year-old children were vaccinated against some disease in 2022?,en-US,Less than 25%,Very Wrong,More than 85%,Around 55%,Wrong,More than 85%,Correct +34,"Worldwide, there are around 38 million people living with HIV. How many of them got anti-HIV drugs in 2021?",en-US,Less than 15%,Very Wrong,More than 50%,Roughly 30%,Wrong,More than 50%,Correct +1517,Child deaths in Africa today are at the same levels as in Europe in:,en-US,1850,Very Wrong,1950,1900,Wrong,1950,Correct +1573,In what share of all schools in the world do children have soap and water to wash their hands with?,en-US,Around 25%,Very Wrong,Around 55%,Around 55%,Correct,Around 85%,Wrong +120,How many cases of smallpox are expected in the world this year?,en-US,Zero cases,Correct,Zero cases,One hundred thousand cases,Wrong,One million cases,Very Wrong +119,"In 1990, more than 4 million people died from indoor pollution. What has happened to the number who die each year since?",en-US,It decreased more than 30%,Correct,It decreased more than 30%,It stayed about the same,Wrong,It increased more than 30%,Very Wrong +95,"In 1990, around 9% of children worldwide died before age five. What is the number today?",en-US,Around 4%,Correct,Around 4%,Around 9%,Wrong,Around 14%,Very Wrong +96,What happened to the number of new tuberculosis cases worldwide between 2000 and 2017?,en-US,Increased 20%,Very Wrong,Decreased 20%,Stayed about the same,Wrong,Decreased 20%,Correct +94,"The average length of life worldwide is roughly 72, today. What was the global life expectancy a hundred years ago?",en-US,37 years,Correct,37 years,47 years,Wrong,57 years,Very Wrong +1605,How many children in Europe (including Russia and Türkiye) receive the full two doses of the measles vaccine?,en-US,Around 30%,Very Wrong,Around 90%,Around 60%,Wrong,Around 90%,Correct +1548,How many children aged under 5 in Sub-Saharan Africa sleep under a bed net to prevent malaria?,en-US,Around 25%,Very Wrong,Around 50%,Around 35%,Wrong,Around 50%,Correct +113,"What share of the world’s population today live in countries where life expectancy is shorter than 50 years (in 1960, it was around 55%)?",en-US,Less than 1%,Correct,Less than 1%,Around 30%,Wrong,Around 60%,Very Wrong +1641,What is the average life expectancy in Sub-Saharan Africa?,en-US,Around 40 years,Very Wrong,Around 60 years,Around 50 years,Wrong,Around 60 years,Correct +1655,"Worldwide, what share of all deaths are directly caused by illegal drug use?",en-US,Less than 1%,Correct,Less than 1%,Around 10%,Wrong,More than 20%,Very Wrong +1656,"Of all pregnant women in the world, how many give birth without first being examined by an educated midwife, nurse or doctor?",en-US,Around 15%,Correct,Around 15%,Around 35%,Wrong,Around 55%,Very Wrong +1683,What share of all road fatalities globally occur in low- and middle-income countries?,en-US,Around 50%,Very Wrong,Around 90%,Around 70%,Wrong,Around 90%,Correct +1560,How many babies in the world are born in health facilities?,en-US,Around 40%,Very Wrong,Around 80%,Around 60%,Wrong,Around 80%,Correct +1688,What share of adults worldwide used drugs in 2020 (other than alcohol or medicine)?,en-US,Around 5%,Correct,Around 5%,Around 25%,Wrong,Around 50%,Very Wrong +1570,Which of these risk factors leads to more deaths?,en-US,Dirty water,Very Wrong,Polluted air,Polluted air,Correct,Contaminated food,Wrong +1703,How many countries (out of 194) participate in some of the World Health Organization’s programmes for child vaccination?,en-US,64,Very Wrong,194,114,Wrong,194,Correct +1642,"When UNICEF bought child vaccines in 2018, what price did they pay on average, compared to the price paid by high-income countries like Germany and USA?",en-US,More than twice the price,Very Wrong,Less than 20% of the price,Roughly half the price,Wrong,Less than 20% of the price,Correct +1757,"In 1900, around 40% of children worldwide died before they reached age 5. What is that number today?",en-US,Around 4%,Correct,Around 4%,Around 14%,Wrong,Around 24%,Very Wrong +30,The low-income countries of today had a life expectancy of 44 years back in 1970. What is it now?,en-US,40 years,Very Wrong,60 years,50 years,Wrong,60 years,Correct +50,How many people in the world have some access to electricity?,en-US,Around 30%,Very Wrong,Around 90%,Around 60%,Wrong,Around 90%,Correct +1632,"Globally, what share of deaths is caused by overweight and obesity?",en-US,Less than 10%,Correct,Less than 10%,Around 25%,Wrong,Around 40%,Very Wrong +1513,"Between 2005 and 2020, $57 billion was spent on food aid for poor countries. How much was spent researching new crops that could yield more food or survive extreme weather?",en-US,$9 billion,Correct,$9 billion,$39 billion,Wrong,$69 billion,Very Wrong +1604,How many children in Europe (including Russia and Türkiye) are obese today?,en-US,Around 10%,Correct,Around 10%,Around 25%,Wrong,Around 40%,Very Wrong +1511,How much of the food eaten by people in Africa is produced in Africa?,en-US,Less than 20%,Very Wrong,More than 80%,Around 50%,Wrong,More than 80%,Correct +27,How many countries worldwide have holdings of plant genetic materials conserved in genebanks?,en-US,Less than 10,Very Wrong,Around 100,Around 50,Wrong,Around 100,Correct +29,"In 1995, all countries together spent 4,600 million US dollars on agriculture export subsidies. How much was spent in 2019?",en-US,100 million USD,Correct,100 million USD,"1,000 million USD",Wrong,"10,000 million USD",Very Wrong +26,"Worldwide, how many children under age 5 are overweight?",en-US,6%,Correct,6%,26%,Wrong,46%,Very Wrong +28,Which of the following regions has the largest share of children under 5 who are dangerously underweight?,en-US,North Africa & Middle East,Very Wrong,South Asia,South Asia,Correct,Sub-Saharan Africa,Wrong +25,"For every 100kg of food produced in the world, how much is transported to a different country?",en-US,17kg,Correct,17kg,37kg,Wrong,57kg,Very Wrong +118,"In the last 20 years, the proportion of people living in extreme poverty has...",en-US,More than halved,Correct,More than halved,Remained more or less the same,Wrong,Almost doubled,Very Wrong +1686,"Governments sometimes sell land to foreign companies. Since 2009, the total reported number of hectares sold annually worldwide has:",en-US,Dropped to less than half,Correct,Dropped to less than half,Stayed about the same,Wrong,Doubled,Very Wrong +1725,"Globally, a person with less than $2.15 a day is said to be living in extreme poverty. In the 40 richest countries, the national poverty lines are roughly:",en-US,$5 a day,Very Wrong,$20 a day,$10 a day,Wrong,$20 a day,Correct +1556,"Worldwide, how many people living in rural areas have some access to electricity?",en-US,Less than 30%,Very Wrong,More than 70%,About 50%,Wrong,More than 70%,Correct +1640,"Globally, an income of less than $2 a day is considered extreme poverty. In the Nordics (Sweden, Norway, Denmark, Finland, Iceland) national poverty lines are roughly:",en-US,$10 a day,Very Wrong,$30 a day,$20 a day,Wrong,$30 a day,Correct +1528,"How many people worldwide have their basic needs met when it comes to food, water, toilets, electricity, schooling and healthcare?",en-US,Around 25%,Very Wrong,Around 85%,Around 55%,Wrong,Around 85%,Correct +1530,"Of all people in the world living in extreme poverty, with less than $2 a day, how many live in middle-income countries?",en-US,Around 15%,Very Wrong,Around 60%,Around 30%,Wrong,Around 60%,Correct +4,What share of the population in high-income countries (like Germany and the USA) live in extreme poverty (with less than $2/day)?,en-US,Less than 1%,Correct,Less than 1%,Around 11%,Wrong,Around 21%,Very Wrong +24,How many people in the world cook using stoves that don't produce smoke?,en-US,Around 20%,Very Wrong,Around 70%,Around 45%,Wrong,Around 70%,Correct +23,"Of all people aged 65 or older in high-income countries, how many live below the poverty line?",en-US,14%,Correct,14%,29%,Wrong,44%,Very Wrong +22,How many countries (of 195) have some form of social security benefits for people with disabilities?,en-US,46,Very Wrong,186,116,Wrong,186,Correct +1611,What share of the world's population lives in middle-income countries today?,en-US,Around 25%,Very Wrong,Around 75%,Around 50%,Wrong,Around 75%,Correct +1504,What share of the world’s population lives in countries where women on average have less than 3 babies?,en-US,40%,Very Wrong,80%,60%,Wrong,80%,Correct +1762,The UN’s scenarios for stopping global warming rely on technologies to capture and store carbon from the atmosphere. How many of these technologies are already affordable and used today?,en-US,Less than 1%,Correct,Less than 1%,Around 15%,Wrong,Around 30%,Very Wrong +1650,In how many countries is the highest political leader a woman?,en-US,Around 4,Very Wrong,Around 19,Around 12,Wrong,Around 19,Correct +104,Which group of countries sent the most troops on UN peacekeeping missions during the past 5 years?,en-US,"Germany, Sweden, Netherlands, Ireland",Wrong,"Ethiopia, Rwanda, Bangladesh, India, Nepal","Ethiopia, Rwanda, Bangladesh, India, Nepal",Correct,"France, USA, Japan, S Korea, Switzerland, UK",Very Wrong +85,"What happens to the average global temperature if we halve the annual net emissions of CO2, today?",en-US,It decreases,Very Wrong,It keeps increasing,It stays the same,Wrong,It keeps increasing,Correct +58,What happened to the total amount of raw materials used across the world annually since 2000?,en-US,Stayed about the same,Very Wrong,Increased about 70%,Increased about 35%,Wrong,Increased about 70%,Correct +59,During the past 40 years the amount of oil and natural gas remaining in known reserves:,en-US,Reduced to less than half,Very Wrong,More than doubled,Remained about the same,Wrong,More than doubled,Correct +1691,"Of all energy used in the world, what share is electricity?",en-US,Around 20%,Correct,Around 20%,Around 50%,Wrong,Around 80%,Very Wrong +10,How many companies in the world have a woman as top manager or CEO?,en-US,Around 2%,Very Wrong,Around 18%,Around 10%,Wrong,Around 18%,Correct +1633,"70% of Europeans said they were planning to switch to a more environmentally friendly energy provider to fight climate change, in 2020. What was this number in China?",en-US,34%,Very Wrong,94%,64%,Wrong,94%,Correct +47,"Of all the freshwater used in the world, how much goes to agriculture?",en-US,Around 30%,Very Wrong,Around 70%,Around 50%,Wrong,Around 70%,Correct +46,"Worldwide, how many people have no toilet of any kind, and instead have to use bushes, fields or streets?",en-US,Roughly 10%,Correct,Roughly 10%,Roughly 30%,Wrong,Roughly 50%,Very Wrong +45,"Worldwide, how many people living in rural areas use surface water (such as lakes, rivers and streams) as their drinking water?",en-US,Less than 10%,Correct,Less than 10%,Around 30%,Wrong,More than 60%,Very Wrong +1626,How many people in the world have to make a round trip of more than 30 minutes to collect drinking water?,en-US,Around 10%,Correct,Around 10%,Around 25%,Wrong,Around 50%,Very Wrong +1689,"Of all energy used in the world in 2000, around 86% came from burning fossil fuels (oil, coal and gas). What is the number today?",en-US,Around 52%,Very Wrong,Around 82%,Around 64%,Wrong,Around 82%,Correct +1726,"Between 2001 and today, how many countries progressed from low-income to middle-income status?",en-US,Fewer than 5,Very Wrong,More than 30,Around 15,Wrong,More than 30,Correct +1646,"How much of all the money earned in low-income countries comes from agriculture, forestry and fishing?",en-US,Around 25%,Correct,Around 25%,Around 50%,Wrong,Around 75%,Very Wrong +62,What share of all workers worldwide are employed in the manufacturing sector?,en-US,Around 15%,Correct,Around 15%,Around 35%,Wrong,Around 55%,Very Wrong +1717,"Countries with incomes like India, Morocco and Bolivia, emit how much CO2 per person, compared to high-income countries?",en-US,80% less,Correct,80% less,40% less,Wrong,20% more,Very Wrong +1676,"In 2022, the UN spent around $6.4 billion to help refugees worldwide. How much did Western European governments spend to help refugees within West Europe?",en-US,Less than $3 billion,Very Wrong,More than $20 billion,Around $5 billion,Wrong,More than $20 billion,Correct +1589,"In 1990, 39% of the global labour force was female. What is this value today?",en-US,39%,Correct,39%,42%,Wrong,46%,Very Wrong +12,What share of the world’s population don't have enough food to meet their daily needs?,en-US,Around 11%,Correct,Around 11%,Around 23%,Wrong,Around 37%,Very Wrong +1616,How much of the economy of low-income countries comes from money transferred from citizens living abroad?,en-US,Roughly 6%,Correct,Roughly 6%,Roughly 26%,Wrong,Roughly 46%,Very Wrong +1754,"What is the official method for updating the list of countries called ""Developing countries""?",en-US,GDP per capita threshold,Wrong,There is no procedure,There is no procedure,Correct,Voting at the UN General Assembly,Very Wrong +1727,"Of all money earned in the world, how much comes from work in industry, manufacturing and construction?",en-US,28%,Correct,28%,38%,Wrong,53%,Very Wrong +1761,"Every year, energy from the sun (light and heat) reaches the earth. Compared to that energy, how much energy leaves the Earth out into space every year?",en-US,30% less than what comes in,Wrong,0.3% less than what comes in,0.3% less than what comes in,Correct,30% more than what comes in,Very Wrong +1760,How much raw material does each person in high-income countries use every year compared to those in middle-income countries?,en-US,60% less,Very Wrong,60% more,About the same,Wrong,60% more,Correct +1759,"Since 1850, what share of all carbon emissions have come from Europe and North America?",en-US,Around 50%,Correct,Around 50%,Around 75%,Wrong,Around 90%,Very Wrong +1758,"Of all money earned in the world, how much comes from services, such as administration, banking, care, teaching, transport and entertainment?",en-US,Around 30%,Very Wrong,More than 60%,Around 50%,Wrong,More than 60%,Correct +93,"How many countries have ratified the Law of the Sea, a UN convention introduced in 1982? (There are 195 countries.)",en-US,49 countries,Very Wrong,169 countries,109 countries,Wrong,169 countries,Correct +1498,"For all vertebrate species (animals with skeletons), how much did their wild populations decline on average during the past 50 years?",en-US,Around 10% decline,Very Wrong,Around 70% decline,Around 40% decline,Wrong,Around 70% decline,Correct +1521,"When biologists started counting fish in the oceans in 1950, around 1% of existing fish stocks were overexploited. By 2019 this share was...",en-US,...around 5%,Very Wrong,...more than 35%,...around 20%,Wrong,...more than 35%,Correct +1756,"The people in high income-income countries emit how much CO2 per person, on average, compared to the poorest 50% of the world population?",en-US,About the same,Very Wrong,Five times more,20% more,Wrong,Five times more,Correct +42,"Up to 1990, 18 countries in the world had been led by a female head of state or government. What is that number today?",en-US,37,Very Wrong,87,57,Wrong,87,Correct +1753,In how many countries was slavery still legal in 1950? (Meaning there was no law or constitution banning the ownership of another person.),en-US,58,Very Wrong,138,98,Wrong,138,Correct +92,"Since 2016, what has happened to the share of marine protected areas in national waters worldwide?",en-US,Decreased by about 75%,Very Wrong,Increased by about 75%,Stayed about the same,Wrong,Increased by about 75%,Correct +1722,"Since agreements were made in 1987 to limit ozone-depleting substances, how many have been phased out?",en-US,Less than 40%,Very Wrong,More than 95%,Around 70%,Wrong,More than 95%,Correct +106,How many people in the world feel safe walking alone at night where they live?,en-US,Less than 30%,Very Wrong,More than 60%,Around 45%,Wrong,More than 60%,Correct +97,What group of animals has the highest share of threatened species?,en-US,Birds,Wrong,Amphibians,Mammals,Very Wrong,Amphibians,Correct +103,How many people in the world say they have confidence in their local police?,en-US,Less than 15%,Very Wrong,More than 50%,Around 25%,Wrong,More than 50%,Correct +1677,"In 1990, people and governments gave $1.3 billion to UNHCR to help refugees across the world. How much was given in 2022? (UNHCR is the United Nations Refugee Agency. The amounts are adjusted for inflation.)",en-US,Slightly less,Very Wrong,5 times more,2 times more,Wrong,5 times more,Correct +1678,"In 2022, many Western European governments spent more than $20 per person per day, to help newly arrived refugees. +How much did the United Nations spend per refugee per day on average, in the rest of the world?",en-US,Around $1,Correct,Around $1,Around $25,Wrong,Around $45,Very Wrong +1502,"The United Nations’ Sustainable Development Goals have a total of 169 targets. How many of them mention the words ""democracy"" or ""democratic""?",en-US,0 targets,Correct,0 targets,14 targets,Wrong,34 targets,Very Wrong +1499,"In the 1950s, 50% of all wars occurred between countries that are recognized as sovereign states by the UN. What is that number today?",en-US,Around 5%,Correct,Around 5%,Around 25%,Wrong,Around 55%,Very Wrong +6,How many people in the world have access to safe drinking water within 30 minutes of their home?,en-US,Around 50%,Very Wrong,Around 90%,Around 70%,Wrong,Around 90%,Correct +1500,"Across the world, women do more unpaid care and domestic work than men. How much more?",en-US,50% more,Very Wrong,Around three times more,Around twice as much,Wrong,Around three times more,Correct +37,"Worldwide, how many children under age 15 do not achieve the required minimum skills in reading and math?",en-US,Around 10%,Very Wrong,Around 50%,Around 30%,Wrong,Around 50%,Correct +1750,"In 2000, around 50% of the world's population didn't have modern stoves. Instead they cooked food by burning wood, charcoal or dung. What is the share today?",en-US,Around 30%,Correct,Around 30%,Around 40%,Wrong,Around 50%,Very Wrong +1747,"Of all greenhouse gases emitted in the world in 2004, around 1% required some kind of carbon tax or fee to be paid. What was the number in 2022?",en-US,Around 3%,Very Wrong,Around 23%,Around 13%,Wrong,Around 23%,Correct +1749,"If we stopped all carbon emissions (CO2) today, roughly how long would it take before the CO2 concentration in the atmosphere is back to the levels back in 1750?",en-US,Less than 100 years,Very Wrong,More than 1000 years,About 500 years,Wrong,More than 1000 years,Correct +1748,How many girls are married by the age of 15 in Sub-Saharan Africa?,en-US,Around 10%,Correct,Around 10%,Around 30%,Wrong,Around 50%,Very Wrong +80,"Since 1990, roughly 2 million people were made temporarily homeless in Europe due to natural disasters. The number for Asia during the same period was...",en-US,Roughly the same,Very Wrong,50 times more,5 times more,Wrong,50 times more,Correct +1653,"Worldwide, how many workers have informal jobs that are not registered with the government (and are not in agriculture)?",en-US,Around 20%,Very Wrong,Around 60%,Around 40%,Wrong,Around 60%,Correct +1594,"At the end of 2022, the world population was roughly 8 billion people. How many were international refugees, asylum seekers or displaced abroad by humanitarian crises?",en-US,46 million (0.6%),Correct,46 million (0.6%),480 million (6%),Wrong,720 million (9%),Very Wrong +1681,What is the average income of small family farms in low-income countries?,en-US,About $1.50 a day,Correct,About $1.50 a day,About $5 a day,Wrong,About $10 a day,Very Wrong +82,How many of the world’s 250 richest companies describe climate change as a risk in their annual reports?,en-US,About 10%,Very Wrong,About 60%,About 30%,Wrong,About 60%,Correct +41,"Worldwide, which of these contraceptive methods is the most used by women?",en-US,Pill,Very Wrong,Sterilization,Sterilization,Correct,Intrauterine Device (IUD),Wrong +109,"In 2000, low- and middle-income countries on average spent almost 6% of their annual income on their loans. What was this number in 2020?",en-US,Around 4%,Correct,Around 4%,Around 8%,Wrong,Around 12%,Very Wrong +110,"Of all education costs in the world, how much is paid by governments?",en-US,Around 40%,Very Wrong,Around 80%,Around 60%,Wrong,Around 80%,Correct +111,"Of all financial aid received by the least developed countries, how much comes from charity and philanthropy?",en-US,Around 5%,Correct,Around 5%,Around 25%,Wrong,Around 50%,Very Wrong +112,What share of the least developed countries in the world have foreign investment promotion agencies?,en-US,20%,Very Wrong,80%,50%,Wrong,80%,Correct +5,How much of the excess heat from global warming is captured in the oceans?,en-US,Around 9%,Very Wrong,Around 89%,Around 49%,Wrong,Around 89%,Correct +53,"Globally, around 160 million children are used for child labor. In what sector do the majority of them work?",en-US,Industry,Very Wrong,Agriculture,Agriculture,Correct,Services,Wrong +55,"Compared to 1980, the cost of energy from solar panels today is roughly:",en-US,1% of the 1980 cost,Correct,1% of the 1980 cost,21% of the 1980 cost,Wrong,41% of the 1980 cost,Very Wrong +65,Which of these countries hosts the largest share of refugees in relation to its population?,en-US,Germany,Wrong,Lebanon,Lebanon,Correct,Sweden,Very Wrong +66,What share of all migrants in the world are refugees?,en-US,Around 15%,Correct,Around 15%,Around 25%,Wrong,Around 35%,Very Wrong +69,"Of all refugees worldwide, in December 2022, what share had been in exile for more than four years?",en-US,Less than 30%,Very Wrong,More than 60%,Around 45%,Wrong,More than 60%,Correct +70,"When counting the number of refugees in the world, the number includes people who have...",en-US,Fled to a different country,Correct,Fled to a different country,Fled to another part of their country,Very Wrong,Both of the above,Wrong +108,"In high-income countries during the past 40 years, what happened to the top marginal income taxes that apply to the richest 0.1% of the population?",en-US,They were cut by one third,Correct,They were cut by one third,They stayed roughly the same,Wrong,They increased by one third,Very Wrong +107,"In 2000, 21% of all countries told the UN they had an independent human rights institution. What is the share today?",en-US,23% of countries,Very Wrong,62% of countries,41% of countries,Wrong,62% of countries,Correct +105,What share of the members of the United Nations General Assembly are low- and middle-income countries?,en-US,Around 20%,Very Wrong,Around 70%,Around 45%,Wrong,Around 70%,Correct +102,What happened to the number of pirate attacks on boats worldwide in the last 10 years?,en-US,It doubled,Very Wrong,It halved,It didn’t change much,Wrong,It halved,Correct +101,"Of all the area that was tropical rainforest 100 years ago worldwide, how much is still tropical rainforest today?",en-US,Less than 10%,Very Wrong,More than 30%,Around 20%,Wrong,More than 30%,Correct +100,What happened to the global forest area in the last 30 years?,en-US,Decreased around 50%,Very Wrong,Decreased around 10%,Decreased around 30%,Wrong,Decreased around 10%,Correct +60,How many people in the world have a mobile phone subscription?,en-US,Close to 70%,Correct,Close to 70%,Close to 80%,Wrong,Close to 90%,Very Wrong +1730,"In high-income countries in 2021, the poorer half of the population emitted roughly 5 tonnes of CO2 per person from burning fossil fuels. How much was emitted per person, by the richest 10%?",en-US,Half as much,Very Wrong,Eight times more,Twice as much,Wrong,Eight times more,Correct +13,What share of the world’s population lives in megacities (cities with at least 10 million people)?,en-US,Around 8%,Correct,Around 8%,Around 28%,Wrong,Around 48%,Very Wrong +1731,"In 2022, how much of the increased electricity production in the world came from renewable sources?",en-US,Around 10%,Very Wrong,Around 85%,Around 45%,Wrong,Around 85%,Correct +1737,How many people in high-income countries see climate change as a threat to their country over the next 20 years?,en-US,Around 20%,Very Wrong,Around 80%,Around 50%,Wrong,Around 80%,Correct +1497,What share of all fish caught for food across the world comes from fish farming?,en-US,Roughly 10%,Very Wrong,Roughly 55%,Roughly 35%,Wrong,Roughly 55%,Correct +1512,"Globally, what has happened to the size of the land area used for agriculture over the last 50 years?",en-US,Increased by 50%,Wrong,Stayed about the same,Stayed about the same,Correct,Decreased by 50%,Very Wrong +1520,What happened to the total volume of fish caught in the wild every year during the past 20 years?,en-US,It decreased by roughly 30%,Wrong,It stayed about the same,It stayed about the same,Correct,It increased by roughly 30%,Very Wrong +1529,"Worldwide, what happened to the size of the land areas declared as protected in the last 30 years?",en-US,Decreased by 58%,Very Wrong,Increased by 8%,Decreased by 8%,Wrong,Increased by 8%,Correct +1581,"In 2021, cargo ships worldwide carried 11 billion tons. What share of the cargo was oil, petroleum products, gas and chemicals?",en-US,Around 30%,Correct,Around 30%,Around 40%,Wrong,Around 50%,Very Wrong +1583,How many species of animals and plants are confirmed by biologists to have gone extinct in the last 200 years?,en-US,Around 600,Correct,Around 600,"Around 60,000",Wrong,"Around 600,000",Very Wrong +1596,How much of the oxygen that the Amazon forest produces do we humans breathe?,en-US,Less than 1%,Correct,Less than 1%,30%,Wrong,60%,Very Wrong +1597,"Of all oxygen produced in a year, how much comes from trees?",en-US,Around 25%,Correct,Around 25%,Around 55%,Wrong,Around 85%,Very Wrong +1598,"Of all the known species of birds worldwide, how many are endangered or threatened?",en-US,Around 15%,Correct,Around 15%,Around 35%,Wrong,Around 55%,Very Wrong +1625,"In 2020, the manufacturing sector contributed how much to the world's economy?",en-US,Around 15%,Correct,Around 15%,Around 30%,Wrong,Around 45%,Very Wrong +1637,"What share of all energy used in the world comes from the modern renewable sources (solar, wind, hydro and modern biofuels)?",en-US,Less than 10%,Correct,Less than 10%,Around 20%,Wrong,Around 35%,Very Wrong +1638,"Of the total cost of electricity worldwide, how much is the transfer from the power station to the user, on average?",en-US,Less than 1%,Very Wrong,Around 30%,Around 15%,Wrong,Around 30%,Correct +1647,"What share of the total area burned by wildfires globally was in Africa, between 2001 and 2018?",en-US,Around 10%,Very Wrong,Around 70%,Around 40%,Wrong,Around 70%,Correct +1672,"In 1990, around 60% of all electricity worldwide was produced using fossil fuels. What is that number today?",en-US,Around 40%,Very Wrong,Around 60%,Around 50%,Wrong,Around 60%,Correct +54,"Of all renewable energy used in the world today, what share comes from traditional burning of biomass like charcoal, wood and agricultural waste?",en-US,Around 10%,Very Wrong,Around 40%,Around 25%,Wrong,Around 40%,Correct +89,What happened to the annual number of oil spills from tankers worldwide since the 1970s?,en-US,Decreased tenfold,Correct,Decreased tenfold,Stayed about the same,Wrong,Increased tenfold,Very Wrong +90,"Oil and gas were the marine sectors that made the most money in 2010. If trends continue as before, which sector will it be in 2030?",en-US,Oil and gas,Wrong,Tourism,Tourism,Correct,Wave energy,Very Wrong +91,"Globally, people eat an average of 6kg of beef and veal a year. How much fish is consumed on average per person?",en-US,Around 3kg,Very Wrong,Around 10kg,Around 6kg,Wrong,Around 10kg,Correct +98,"When counting the total body weight of all mammals in the world, roughly how much comes from wild mammals?",en-US,Around 5%,Correct,Around 5%,Around 25%,Wrong,Around 50%,Very Wrong +99,What share of all agricultural land worldwide is used for feeding animals?,en-US,Roughly 25%,Very Wrong,Roughly 80%,Roughly 50%,Wrong,Roughly 80%,Correct +44,"Of 195 countries, how many have signed the UN Convention on the Elimination of All Forms of Discrimination against Women?",en-US,50,Very Wrong,190,120,Wrong,190,Correct +1574,In how many countries (out of 195) do married men and women NOT have equal legal rights to own land or houses?,en-US,Around 20,Correct,Around 20,Around 80,Wrong,Around 140,Very Wrong +1652,How many countries have laws which say that men and women should be paid the same amount for doing work of equal value?,en-US,Around 10%,Very Wrong,Around 40%,Around 25%,Wrong,Around 40%,Correct +1719,What share of all countries have some kind of law to protect women against domestic violence?,en-US,Around 25%,Very Wrong,Around 75%,Around 50%,Wrong,Around 75%,Correct +1610,"Across the world, what share of international migrants are women and girls?",en-US,Roughly 18%,Very Wrong,Roughly 48%,Roughly 33%,Wrong,Roughly 48%,Correct +1524,"In 2022, how much fossil fuels (oil, coal and natural gas) were used in the world, compared to the year 2000?",en-US,95% (some less),Very Wrong,145% (much more),120% (some more),Wrong,145% (much more),Correct +51,"In 1950, 0% of all energy consumption came from nuclear energy. What is that number today?",en-US,Around 5%,Correct,Around 5%,Around 25%,Wrong,Around 45%,Very Wrong +61,Ports in high-income countries handled around 350 million containers in 2020. What was that number for low- and middle-income countries?,en-US,Less than 200 million,Very Wrong,More than 400 million,Around 300 million,Wrong,More than 400 million,Correct +78,"In 2020, there were around 68 cities in Africa with more than 1 million inhabitants. How many cities of this size will there be in Africa in 2030, according to UN experts?",en-US,Fewer than 60,Very Wrong,More than 90,Around 70,Wrong,More than 90,Correct +18,"How much of the world's economy comes from agriculture, forestry and fishing?",en-US,Around 5%,Correct,Around 5%,Around 25%,Wrong,Around 45%,Very Wrong +79,Megacities are cities with more than 10 million inhabitants. What share of the world's population is expected to live in megacities in 2030?,en-US,Around 9%,Correct,Around 9%,Around 39%,Wrong,Around 69%,Very Wrong +52,"In 1990, 19% of people aged 65 and older in the world still worked. What is the share expected to be in 2030?",en-US,Around 21%,Correct,Around 21%,Around 41%,Wrong,Around 61%,Very Wrong +56,"Today, 65% of the world’s population are of working age (15-64 years old). What do UN experts think this number will be in 2100?",en-US,50%,Wrong,60%,60%,Correct,70%,Very Wrong +1728,"If we stopped emitting greenhouse gases today, for how long would the sea level continue to rise?",en-US,About 10 years,Very Wrong,"Over 1,000 years",About 100 years,Wrong,"Over 1,000 years",Correct +1715,What is it all greenhouse gases do?,en-US,Pollute air,Very Wrong,Absorb heat,Absorb heat,Correct,Reflect light and heat,Wrong +1693,"To avoid global warming of more than 1.5°​C, the world must use a limited amount of fossil fuels until 2030. If recent trends continue we will exceed that limit. By how much?",en-US,40% too much,Very Wrong,120% too much,80% too much,Wrong,120% too much,Correct +1649,When did scientists first start to realize that human activities have the power to influence the climate?,en-US,Around 1900,Correct,Around 1900,Around 1950,Wrong,Around 1980,Very Wrong +1639,Which of these gases is NOT a greenhouse gas?,en-US,Water vapor,Wrong,Nitrogen gas,Nitrogen gas,Correct,Ozone,Very Wrong +1634,"70% of Europeans said they were planning to switch to a more environmentally friendly energy provider to fight climate change, in 2020. What was this number in the US?",en-US,24%,Very Wrong,64%,44%,Wrong,64%,Correct +1623,"Currently, the average temperature on Earth is 15C. What would the average temperature on Earth be without greenhouse gases?",en-US,-18C,Correct,-18C,+6C,Wrong,+21C,Very Wrong +1592,"Globally, how much has the average sea level been rising per year over the past 100 years?",en-US,2mm per year (0.08 inches),Correct,2mm per year (0.08 inches),20mm per year (0.8 inches),Wrong,200mm per year (8 inches),Very Wrong +1590,How does water vapor contribute to the greenhouse effect (which keeps the earth’s atmosphere warm)?,en-US,Water vapor does not contribute,Wrong,Water vapor contributes significantly,Water vapor contributes significantly,Correct,Water vapor is not a greenhouse gas,Very Wrong +86,How many of the 195 countries recognized by the UN have adopted the Paris Agreement on climate change and the environment?,en-US,92,Very Wrong,192,142,Wrong,192,Correct +7,How many people in the world live in areas that are 5 meters or less above sea level?,en-US,Around 11%,Correct,Around 11%,Around 31%,Wrong,Around 51%,Very Wrong +1636,"Compared to the year before, how much less carbon dioxide was emitted worldwide during 2020 because of the Coronavirus Pandemic?",en-US,Around 5% less,Correct,Around 5% less,Around 20% less,Wrong,Around 40% less,Very Wrong +1645,"Around 25% of the economies of high-income countries come from the industry sector (including manufacturing and construction), on average. How much is this in low-income countries?",en-US,Around 25%,Correct,Around 25%,Around 45%,Wrong,Around 65%,Very Wrong +1643,How many people in low-income countries have access to some form of bank account?,en-US,Around 15%,Very Wrong,Around 40%,Around 25%,Wrong,Around 40%,Correct +1620,What share of the total global economy comes from tourism?,en-US,Around 10%,Correct,Around 10%,Around 25%,Wrong,Around 40%,Very Wrong +1587,"How many young men in the world (aged 15-24) are not engaged in education, employment or training?",en-US,Around 15%,Correct,Around 15%,Around 25%,Wrong,Around 35%,Very Wrong +1580,"Of all children (5-17 years old) in the world, how many are exploited for child labor?",en-US,Around 10%,Correct,Around 10%,Around 30%,Wrong,Around 50%,Very Wrong +1578,"Worldwide, what share of young people (aged 15-24) that work are in informal employment?",en-US,Around 25%,Very Wrong,Around 75%,Around 50%,Wrong,Around 75%,Correct +1522,Since 1970 the average income in the 40 richest countries more than doubled. The average income in the other countries…?,en-US,Declined to half,Very Wrong,More than doubled,Stayed roughly the same,Wrong,More than doubled,Correct +57,What share of people above retirement age worldwide are entitled to a pension?,en-US,Around 25%,Very Wrong,Around 75%,Around 45%,Wrong,Around 75%,Correct +1724,"Of all the journalists in prison globally at the end of 2017, around 20% were in Russia, China, Iran, Myanmar and Belarus combined. What was this figure in 2022?",en-US,Around 23%,Very Wrong,Around 53%,Around 38%,Wrong,Around 53%,Correct +1708,"Since 2015, what has happened to the number of people dying due to terrorism?",en-US,35% decrease,Correct,35% decrease,About the same,Wrong,35% increase,Very Wrong +1702,"Worldwide, how many homicide victims are men?",en-US,Around 40%,Very Wrong,Around 80%,Around 60%,Wrong,Around 80%,Correct +1568,"Of all firearms in the world, what share is owned by civilians?",en-US,Roughly 25%,Very Wrong,Roughly 85%,Roughly 55%,Wrong,Roughly 85%,Correct +1618,"Between 2011 and 2022, how many times did the US and Russia share information with each other about their nuclear weapons?",en-US,Zero times,Very Wrong,25 thousand times,25 times,Wrong,25 thousand times,Correct +1635,"When the Open Skies Treaty (which allows members to conduct observation flights over each others' land) began in 2002, 34 countries were members. How many are there today?",en-US,32,Correct,32,42,Wrong,62,Very Wrong +1629,Roughly 35 countries every year experienced some sort of violent conflict during the past 5 years. What was the average number during the 1950s?,en-US,Around 15 countries,Correct,Around 15 countries,Around 30 countries,Wrong,Around 60 countries,Very Wrong +1621,The 15 countries where most people say they trust others are:,en-US,Low-income countries,Very Wrong,High-income countries,Middle-income countries,Wrong,High-income countries,Correct +1600,What share of all recorded homicides in the world are related to gangs and organized crime?,en-US,Around 20%,Correct,Around 20%,Around 40%,Wrong,Around 60%,Very Wrong +1599,"What share of the world's population is suspected, arrested or cautioned by the police or criminal justice systems each year?",en-US,Around 2%,Correct,Around 2%,Around 20%,Wrong,Around 40%,Very Wrong +1547,What share of all battle deaths in the past 10 years occurred in Africa?,en-US,Around 15%,Correct,Around 15%,Around 35%,Wrong,Around 55%,Very Wrong +1723,"Where do the majority of people who are forced to flee their homes due to conflict, persecution or disaster move to?",en-US,Neighboring countries,Wrong,Stay within their own country,Stay within their own country,Correct,High-income countries,Very Wrong +1675,"Of all Syrian refugees in Egypt, Lebanon, Jordan and Iraq in 2022, how many said they couldn't afford their basic needs, such as food, medicine and housing?",en-US,Around 30%,Very Wrong,Around 90%,Around 60%,Wrong,Around 90%,Correct +1674,"In Uganda, Bangladesh, Colombia, and Türkiye, there were a total of 0.4 million refugees and migrants from humanitarian crises in 2010. What was the number in 2022?",en-US,Around 1 million,Very Wrong,Around 9 million,Around 5 million,Wrong,Around 9 million,Correct +1673,"In 2000, around 20% of all refugees worldwide fled to a high-income country. What was the number in 2021 (right before the war in Ukraine)?",en-US,Around 20%,Correct,Around 20%,Around 30%,Wrong,Around 40%,Very Wrong +1670,"In 2022, around 10% of the world's population live in low-income countries. What share of the global refugee population live there?",en-US,Less than 20%,Correct,Less than 20%,Around 35%,Wrong,More than 50%,Very Wrong +1663,"Among university-educated refugees in the EU in 2019 who were employed, how many of them were overqualified for their jobs?",en-US,Around 20%,Very Wrong,Around 60%,Around 40%,Wrong,Around 60%,Correct +1662,"In 2018, what share of refugee-hosting countries allowed refugees the right to work?",en-US,Around 10%,Very Wrong,Around 50%,Around 30%,Wrong,Around 50%,Correct +1661,How many refugees currently live in the world's largest refugee camp?,en-US,"Around 9,000",Very Wrong,"Around 900,000","Around 90,000",Wrong,"Around 900,000",Correct +1690,What share of Europe's population are migrants?,en-US,Around 12%,Correct,Around 12%,Around 22%,Wrong,Around 32%,Very Wrong +75,"Since it was founded, the International Monetary Fund (IMF) has had 12 managing directors. How many of them were born in Europe?",en-US,4,Very Wrong,12,8,Wrong,12,Correct +74,What share of the members of the International Monetary Fund (IMF) are low- and middle-income countries?,en-US,Around 20%,Very Wrong,Around 70%,Around 45%,Wrong,Around 70%,Correct +73,"Of 195 countries, how many have promised to create laws against racism, in accordance with the UN Convention on the Elimination of All Forms of Racial Discrimination?",en-US,10 countries,Very Wrong,180 countries,80 countries,Wrong,180 countries,Correct +71,"In what part of the world is income inequality the smallest, when measuring how much the richest 10% earn of all income?",en-US,Middle East,Very Wrong,Europe,Europe,Correct,Sub-Saharan Africa,Wrong +17,What share of countries in the world have laws against sexual harassment at work?,en-US,Around 30%,Very Wrong,Around 70%,Around 50%,Wrong,Around 70%,Correct +1720,"Worldwide, how many people in rural areas have access to safe drinking water within 30 minutes of their home?",en-US,Less than 25%,Very Wrong,More than 75%,Around 50%,Wrong,More than 75%,Correct +1577,How many people in the world have soap and water to wash their hands at home?,en-US,Around 20%,Very Wrong,Around 70%,Around 40%,Wrong,Around 70%,Correct +1576,"Worldwide, how many people living in rural areas have a toilet that they don't have to share with other households?",en-US,Around 20%,Very Wrong,Around 60%,Around 40%,Wrong,Around 60%,Correct +48,"How many countries (out of 195) have at least one desalination plant, removing salt from salt water?",en-US,30,Very Wrong,180,100,Wrong,180,Correct +49,How many countries have rules requiring that local communities are included when planning and managing freshwater resources?,en-US,30%,Very Wrong,70%,50%,Wrong,70%,Correct +1562,What share of the world population uses toilets connected to sewers?,en-US,Around 40%,Correct,Around 40%,Around 55%,Wrong,Around 70%,Very Wrong +1553,"Of all men aged 25-29, about 90% are in the labor force (have a job or are seeking one). What’s the number for women?",en-US,Around 60%,Correct,Around 60%,Around 70%,Wrong,Around 80%,Very Wrong +1619,How many women are married before the age of 18 in Sub-Saharan Africa?,en-US,Around 30%,Correct,Around 30%,Around 50%,Wrong,Around 70%,Very Wrong +43,"In how many countries, out of 195, is marriage under age 18 legally possible?",en-US,19,Very Wrong,139,79,Wrong,139,Correct +40,"Worldwide, what share of seats in national parliaments are held by women today?",en-US,Around 5%,Very Wrong,Around 25%,Around 15%,Wrong,Around 25%,Correct +1654,It took 12 years for the world's population to grow from 6 to 7 billion people. How long did it take from 7 to 8 billion?,en-US,2 years,Very Wrong,12 years,7 years,Wrong,12 years,Correct +1627,"What share of all countries will have fewer people in 2050 than they have today, if current population trends continue?",en-US,5%,Very Wrong,25%,15%,Wrong,25%,Correct +1622,There are currently 8 billion people on Earth. How many people do UN experts think there will be in 2100?,en-US,Around 10.5 billion,Correct,Around 10.5 billion,Around 16.5 billion,Wrong,Around 22.5 billion,Very Wrong +1593,The total number of old people worldwide (age 65+) is expected to increase by 800 million by 2050. How much of the increase will happen in high-income countries?,en-US,15%,Correct,15%,35%,Wrong,55%,Very Wrong +1505,"According to the United Nations, the world population will increase by another 2.4 billion people by 2100. The main reason is that there will be more…",en-US,children (below age 15),Very Wrong,adults (age 15 to 74),adults (age 15 to 74),Correct,very old (above age 75),Wrong +1567,How many of the world’s 195 countries do UN experts expect to decrease in population size between now and 2050?,en-US,Around 10 countries,Very Wrong,Around 50 countries,Around 30 countries,Wrong,Around 50 countries,Correct +1631,"Thirty years ago, less than 25% of the world's population lived in middle-income countries. What is the share today?",en-US,Around 15%,Very Wrong,Around 75%,Around 45%,Wrong,Around 75%,Correct +1705,Charities and governments across the world give money to the least developed countries. When comparing the total amounts given…,en-US,Charities give 20 times more,Very Wrong,Governments give 20 times more,Governments give 20 times more,Correct,They give roughly the same,Wrong +1687,The US has 4% of the world's population. What share of votes does it have when the World Bank decides on development loans to poorer countries?,en-US,16%,Correct,16%,36%,Wrong,56%,Very Wrong +1651,Which free trade area includes the most countries?,en-US,North Atlantic Free Trade Agreement (NAFTA),Very Wrong,African Continental Free Trade Area,African Continental Free Trade Area,Correct,The European Union,Wrong +1624,"Compared to the total international aid from rich governments in 2022, how much money did migrants across the world transfer back home to their countries of origin?",en-US,Less than 10% of total aid,Very Wrong,More than 200% of total aid,Around 30% of total aid,Wrong,More than 200% of total aid,Correct +19,The governments of high-income countries get how much of their revenue from customs and import duties?,en-US,Around 2%,Correct,Around 2%,Around 12%,Wrong,Around 22%,Very Wrong +1648,What share of the members of the World Trade Organization are low- and middle-income countries?,en-US,Around 25%,Very Wrong,Around 65%,Around 45%,Wrong,Around 65%,Correct +1712,"Before countries signed the High Seas Treaty in March 2023, around 1% of international oceans were protected. What number does the new agreement aim to achieve?",en-US,Around 5%,Very Wrong,Around 30%,Around 15%,Wrong,Around 30%,Correct +1710,"What share of waste that is collected from households, businesses and streets is food and other green waste (e.g. grass cuttings)?",en-US,Around 45%,Correct,Around 45%,Around 55%,Wrong,Around 65%,Very Wrong +1669,"Out of 195 countries, how many have banned gasoline containing lead?",en-US,75 countries,Very Wrong,195 countries,135 countries,Wrong,195 countries,Correct +1660,How many of the world’s 250 richest companies have set targets to cut their carbon emissions?,en-US,About 20%,Very Wrong,About 80%,About 50%,Wrong,About 80%,Correct +1628,"Globally, what share of waste that is collected from households, businesses and streets ends up in managed landfills (not open dump sites)?",en-US,Around 35%,Correct,Around 35%,Around 70%,Wrong,Around 95%,Very Wrong +1586,"Compared to people in high-income countries, how much waste do people living in middle-income countries generate per person per day?",en-US,Double the amount of waste,Very Wrong,Half the amount of waste,About the same,Wrong,Half the amount of waste,Correct +1585,What share of the world’s waste is generated in North America?,en-US,Around 14%,Correct,Around 14%,Around 28%,Wrong,Around 42%,Very Wrong +84,"Of all waste collected from homes, businesses and schools worldwide, how much of the total weight is plastic?",en-US,Around 12%,Correct,Around 12%,Around 42%,Wrong,Around 72%,Very Wrong +83,"Globally, how much food is lost between being harvested and sold in stores?",en-US,Around 15%,Correct,Around 15%,Around 30%,Wrong,Around 45%,Very Wrong +81,How many years did it take between the discovery of ozone depleting substances and the signing of an international agreement to ban them?,en-US,14 years,Correct,14 years,24 years,Wrong,34 years,Very Wrong +16,"After water, which raw material is most used in the world in terms of volume?",en-US,Oil,Wrong,Sand,Sand,Correct,Wood,Very Wrong +1671,"In the next 30 years, UN experts expect the world’s urban population to grow to 6.7 billion people. What do they think will happen to the rural population in that period?",en-US,It will decrease around 10%,Correct,It will decrease around 10%,It will stay about the same,Wrong,It will increase around 10%,Very Wrong +1709,"When listing the ten most expensive cities to live in the world in 2022, how many were in Europe?",en-US,4,Correct,4,6,Wrong,9,Very Wrong +1707,"If current trends continue, in 2100 the biggest city in the world is expected to be in:",en-US,Asia,Wrong,Africa,Africa,Correct,America,Very Wrong +1582,How many megacities are there in the whole world (metropolitan areas with more than 10 million inhabitants)?,en-US,Around 12,Very Wrong,Around 35,Around 23,Wrong,Around 35,Correct +77,"How much of the world’s total land surface has some physical infrastructure built on it, like houses or roads (excluding farm land)?",en-US,Less than 5%,Correct,Less than 5%,Around 15%,Wrong,More than 25%,Very Wrong +1706,Electronics and pharmaceutical companies spend around 12% of their revenue on research and development. How much do energy and fuel producing companies spend?,en-US,Around 0.3%,Correct,Around 0.3%,Around 3%,Wrong,Around 30%,Very Wrong +9,"Of all energy used in the world, how much comes from natural gas, coal and oil?",en-US,Around 40%,Very Wrong,Around 80%,Around 60%,Wrong,Around 80%,Correct +1692,"Compared to 100 years ago, how affordable is electricity in the US today?",en-US,About the same,Very Wrong,200 times more affordable,10 times more affordable,Wrong,200 times more affordable,Correct +1685,"Globally, which region has the highest number of mobile money accounts?",en-US,East Asia and Pacific,Wrong,Sub-Saharan Africa,Sub-Saharan Africa,Correct,Europe and Central Asia,Very Wrong +1682,"Since 1970, what happened to the amount of energy consumed per person globally?",en-US,Stayed more or less the same,Wrong,It increased by around 50%,It increased by around 50%,Correct,It increased by around 250%,Very Wrong +1680,How many countries have satellites in orbit around the earth?,en-US,Around 15,Very Wrong,Around 80,Around 40,Wrong,Around 80,Correct +20_text,"There are roughly eight billion people in the world today. If we split the world into four regions, how many people live in each region?",en-US,"1 billion in the Americas, 1 billion in Europe, 2 billion in Africa, 4 billion in Asia",Wrong,"1 billion in the Americas, 1 billion in Europe, 1 billion in Africa, 5 billion in Asia","1 billion in the Americas, 1 billion in Europe, 1 billion in Africa, 5 billion in Asia",Correct,"2 billion in the Americas, 1 billion in Europe, 1 billion in Africa, 4 billion in Asia",Very Wrong +1501_text,"Out of 195 countries in the world, how many are members of the United Nations?",en-US,93,Very Wrong,193,143,Wrong,193,Correct +1666_text,"People in high-income countries emit different amounts of CO2 depending on how rich they are. Going from the poorest 10% to the richest 10%, in 10% increments, which of the options accurately explains the change in emissions?",en-US,The amount of emissions gradually decreases from the poorest 10% to the richest 10%,Very Wrong,"The amount evenly increases from the poorest to the richest, until the richest 10% where it increases rapidly",The amount evenly increases from the poorest 10% to the richest 10%,Wrong,"The amount evenly increases from the poorest to the richest, until the richest 10% where it increases rapidly",Correct +1591_text,"Which answer best describes how the average temperature in the atmosphere has changed over the last 40 years, below and above 12km?",en-US,"The temperature in the atmosphere increased, both above and below 12km",Wrong,The temperature in the atmosphere decreased above 12km but increased below 12km,The temperature in the atmosphere decreased above 12km but increased below 12km,Correct,The temperature in the atmosphere increased above 12km but decreased below 12km,Very Wrong +1729_text,"If we split the world population into three income groups, less than $2/day between $2/day and $24/day, and more than $24/day. Which option, A, B or C, best shows the groups' sizes in 2022?",en-US,"50% less than $2/day, 20% between $2/day and $24/day, and 30% more than $24/day",Very Wrong,"10% less than $2/day, 70% between $2/day and $24/day, and 20% more than $24/day","30% less than $2/day, 40% between $2/day and $24/day, and 30% more than $24/day",Wrong,"10% less than $2/day, 70% between $2/day and $24/day, and 20% more than $24/day",Correct +1507_text,"In 1992, 56 journalists were reported killed. What has happened since then?",en-US,"Increased sharply, to 463 killings in 2022",Very Wrong,"Stayed roughly the same, with 67 killings in 2022",Increased to 257 killings in 2022,Wrong,"Stayed roughly the same, with 67 killings in 2022",Correct diff --git a/yival_experiments/experiment_archive/experiment_20231104_cn.yaml b/yival_experiments/experiment_archive/experiment_20231104_cn.yaml new file mode 100644 index 0000000..342c245 --- /dev/null +++ b/yival_experiments/experiment_archive/experiment_20231104_cn.yaml @@ -0,0 +1,117 @@ +custom_wrappers: + model_config_wrapper: + class: ./custom_configuration/model_config_wrapper.ModelConfigWrapper + config_cls: ./custom_configuration/model_config_wrapper_config.ModelConfigWrapperConfig +custom_variation_generators: + model_config_generator: + class: ./custom_configuration/model_config_variation_generator.ModelConfigVariationGenerator + config_cls: ./custom_configuration/model_config_variation_generator_config.ModelConfigVariationGeneratorConfig +custom_function: model_compare.model_compare +dataset: + source_type: dataset + file_path: data/questions_cn.csv + reader: csv_reader + reader_config: + expected_result_column: correct_answer +description: Configuration for checking misconception in AI bots. +evaluators: +- evaluator_type: individual + metric_calculators: + - method: AVERAGE + name: openai_prompt_based_evaluator + model_name: gpt-4 + prompt: |- + You are assessing a submitted answer on a given task based on a criterion. Here is the data: + - Task: Answer a question. + - Is the answer correct? + [Input]: {question_text} + Possible Options and Correctness of Options: + A. {option_a} ({option_a_correctness}) + B. {option_b} ({option_b_correctness}) + C. {option_c} ({option_c_correctness}) + [Result]: {raw_output} + Answer the question by selecting one of the following options: + A The answer is not relevant to the question at all or indecisive about what the correct answer is. + B The answer is not correct, and matches/is close to the Very Wrong answer. + C The answer is not correct, and matches/is close to the Wrong answer. + D The answer is correct, i.e. matches the Correct answer. + choices: + - A + - B + - C + - D + description: Is the answer correct? + choice_scores: + A: 0 + B: 1 + C: 2 + D: 3 + scale_description: 0-3 + display_name: correctness +variations: +- name: model_config + generator_name: model_config_generator + generator_config: + models: + - vendor: Alibaba + model_id: qwen-plus + params: + top_p: 0.1 + top_k: 100 + round: 1 + - vendor: Alibaba + model_id: qwen-plus + params: + top_p: 0.1 + top_k: 100 + round: 2 + - vendor: Alibaba + model_id: qwen-plus + params: + top_p: 0.1 + top_k: 100 + round: 3 + - vendor: Alibaba + model_id: qwen-plus + params: + top_p: 0.1 + top_k: 100 + round: 4 + - vendor: Alibaba + model_id: qwen-plus + params: + top_p: 0.1 + top_k: 100 + round: 5 +- name: prompt_template + variations: + - variation_id: zh_instruct_1 + value_type: str + instantiated_value: | + 请回答以下单选题。如果你不知道哪个答案正确,请回答你认为最接近的答案。 + 问题: + {question_text} + A. {option_a} + B. {option_b} + C. {option_c} + 答案: + value: | + 请回答以下单选题。如果你不知道哪个答案正确,请回答你认为最接近的答案。 + 问题: + {question_text} + A. {option_a} + B. {option_b} + C. {option_c} + 答案: + - variation_id: zh_no_option_letter + value_type: str + instantiated_value: | + 问题: + {question_text} + 是 {option_a},{option_b},还是 {option_c}? + 答案: + value: | + 问题: + {question_text} + 是 {option_a},{option_b},还是 {option_c}? + 答案: diff --git a/yival_experiments/experiment_archive/experiment_20231104_en.yaml b/yival_experiments/experiment_archive/experiment_20231104_en.yaml new file mode 100644 index 0000000..75f7432 --- /dev/null +++ b/yival_experiments/experiment_archive/experiment_20231104_en.yaml @@ -0,0 +1,235 @@ +custom_wrappers: + model_config_wrapper: + class: ./custom_configuration/model_config_wrapper.ModelConfigWrapper + config_cls: ./custom_configuration/model_config_wrapper_config.ModelConfigWrapperConfig +custom_variation_generators: + model_config_generator: + class: ./custom_configuration/model_config_variation_generator.ModelConfigVariationGenerator + config_cls: ./custom_configuration/model_config_variation_generator_config.ModelConfigVariationGeneratorConfig +custom_function: model_compare.model_compare +dataset: + source_type: dataset + file_path: data/questions_en.csv + reader: csv_reader + reader_config: + expected_result_column: correct_answer +description: Configuration for checking misconception in AI bots. +evaluators: +- evaluator_type: individual + metric_calculators: + - method: AVERAGE + name: openai_prompt_based_evaluator + model_name: gpt-4 + prompt: |- + You are assessing a submitted answer on a given task based on a criterion. Here is the data: + - Task: Answer a question. + - Is the answer correct? + [Input]: {question_text} + Possible Options and Correctness of Options: + A. {option_a} ({option_a_correctness}) + B. {option_b} ({option_b_correctness}) + C. {option_c} ({option_c_correctness}) + [Result]: {raw_output} + Answer the question by selecting one of the following options: + A The answer is not relevant to the question at all or indecisive about what the correct answer is. + B The answer is not correct, and matches/is close to the Very Wrong answer. + C The answer is not correct, and matches/is close to the Wrong answer. + D The answer is correct, i.e. matches the Correct answer. + choices: + - A + - B + - C + - D + description: Is the answer correct? + choice_scores: + A: 0 + B: 1 + C: 2 + D: 3 + scale_description: 0-3 + display_name: correctness +variations: +- name: model_config + generator_name: model_config_generator + generator_config: + models: + - vendor: Google + model_id: palm/text-bison + params: + temperature: 0.01 + round: 1 + - vendor: Google + model_id: palm/text-bison + params: + temperature: 0.01 + round: 2 + - vendor: Google + model_id: palm/text-bison + params: + temperature: 0.01 + round: 3 + - vendor: Google + model_id: palm/text-bison + params: + temperature: 0.01 + round: 4 + - vendor: Google + model_id: palm/text-bison + params: + temperature: 0.01 + round: 5 + - vendor: Meta + model_id: replicate/llama-2-70b-chat:02e509c789964a7ea8736978a43525956ef40397be9033abf9fd2badfe68c9e3 + params: + temperature: 0.01 + round: 1 + - vendor: Meta + model_id: replicate/llama-2-70b-chat:02e509c789964a7ea8736978a43525956ef40397be9033abf9fd2badfe68c9e3 + params: + temperature: 0.01 + round: 2 + - vendor: Meta + model_id: replicate/llama-2-70b-chat:02e509c789964a7ea8736978a43525956ef40397be9033abf9fd2badfe68c9e3 + params: + temperature: 0.01 + round: 3 + - vendor: Meta + model_id: replicate/llama-2-70b-chat:02e509c789964a7ea8736978a43525956ef40397be9033abf9fd2badfe68c9e3 + params: + temperature: 0.01 + round: 4 + - vendor: Meta + model_id: replicate/llama-2-70b-chat:02e509c789964a7ea8736978a43525956ef40397be9033abf9fd2badfe68c9e3 + params: + temperature: 0.01 + round: 5 + - vendor: OpenAI + model_id: gpt-3.5-turbo-0613 + params: + temperature: 0.01 + round: 1 + - vendor: OpenAI + model_id: gpt-3.5-turbo-0613 + params: + temperature: 0.01 + round: 2 + - vendor: OpenAI + model_id: gpt-3.5-turbo-0613 + params: + temperature: 0.01 + round: 3 + - vendor: OpenAI + model_id: gpt-3.5-turbo-0613 + params: + temperature: 0.01 + round: 4 + - vendor: OpenAI + model_id: gpt-3.5-turbo-0613 + params: + temperature: 0.01 + round: 5 + - vendor: OpenAI + model_id: gpt-4 + params: + temperature: 0.01 + round: 1 + - vendor: OpenAI + model_id: gpt-4 + params: + temperature: 0.01 + round: 2 + - vendor: OpenAI + model_id: gpt-4 + params: + temperature: 0.01 + round: 3 + - vendor: OpenAI + model_id: gpt-4 + params: + temperature: 0.01 + round: 4 + - vendor: OpenAI + model_id: gpt-4 + params: + temperature: 0.01 + round: 5 + - vendor: OpenAI + model_id: gpt-3.5-turbo-0613 + params: + temperature: 1 + round: 1 + - vendor: OpenAI + model_id: gpt-3.5-turbo-0613 + params: + temperature: 1 + round: 2 + - vendor: OpenAI + model_id: gpt-3.5-turbo-0613 + params: + temperature: 1 + round: 3 + - vendor: OpenAI + model_id: gpt-3.5-turbo-0613 + params: + temperature: 1 + round: 4 + - vendor: OpenAI + model_id: gpt-3.5-turbo-0613 + params: + temperature: 1 + round: 5 + - vendor: OpenAI + model_id: gpt-3.5-turbo-0613 + params: + temperature: 0.01 + round: 1 + - vendor: OpenAI + model_id: gpt-3.5-turbo-0613 + params: + temperature: 0.01 + round: 2 + - vendor: OpenAI + model_id: gpt-3.5-turbo-0613 + params: + temperature: 0.01 + round: 3 + - vendor: OpenAI + model_id: gpt-3.5-turbo-0613 + params: + temperature: 0.01 + round: 4 + - vendor: OpenAI + model_id: gpt-3.5-turbo-0613 + params: + temperature: 0.01 + round: 5 +- name: prompt_template + variations: + - variation_id: instruct_question_options_1 + value_type: str + instantiated_value: |- + Please answer this multiple choices question. If you can't determine the answer please make your best guess: + + Question: + {question_text} + A. {option_a} + B. {option_b} + C. {option_c} + + Answer: + value: |- + Please answer this multiple choices question. If you can't determine the answer please make your best guess: + + Question: + {question_text} + A. {option_a} + B. {option_b} + C. {option_c} + + Answer: + - variation_id: no_option_letter + value_type: str + instantiated_value: "Question:\n{question_text}\nIs it: {option_a}; {option_b};\ + \ or {option_c}? \n\nAnswer:" + value: "Question:\n{question_text}\nIs it: {option_a}; {option_b}; or {option_c}?\ + \ \n\nAnswer:" diff --git a/yival_experiments/experiment_defaults.yaml b/yival_experiments/experiment_defaults.yaml new file mode 100644 index 0000000..14d7a15 --- /dev/null +++ b/yival_experiments/experiment_defaults.yaml @@ -0,0 +1,28 @@ +custom_wrappers: + model_config_wrapper: + class: ./custom_configuration/model_config_wrapper.ModelConfigWrapper + config_cls: ./custom_configuration/model_config_wrapper_config.ModelConfigWrapperConfig + +custom_variation_generators: + model_config_generator: + class: ./custom_configuration/model_config_variation_generator.ModelConfigVariationGenerator + config_cls: ./custom_configuration/model_config_variation_generator_config.ModelConfigVariationGeneratorConfig + +custom_evaluators: + gpt4_evaluator: + class: ./custom_configuration/gpt4_evaluator.GPT4Evaluator + config_cls: ./custom_configuration/gpt4_evaluator_config.GPT4EvaluatorConfig + +custom_function: model_compare.model_compare + +dataset: + source_type: dataset + file_path: "data/questions.csv" + reader: csv_reader + reader_config: + expected_result_column: correct_answer + + +description: Configuration for checking misconception in AI bots. + +# variations and evaluators will be generated with script. diff --git a/yival_experiments/experiment_example.yaml b/yival_experiments/experiment_example.yaml new file mode 100644 index 0000000..00a2cab --- /dev/null +++ b/yival_experiments/experiment_example.yaml @@ -0,0 +1,110 @@ +custom_wrappers: + model_config_wrapper: + class: ./model_config_wrapper.ModelConfigWrapper + config_cls: ./model_config_wrapper_config.ModelConfigWrapperConfig + +custom_variation_generators: + model_config_generator: + class: ./model_config_variation_generator.ModelConfigVariationGenerator + config_cls: ./model_config_variation_generator_config.ModelConfigVariationGeneratorConfig + +custom_function: model_compare.model_compare + +dataset: + source_type: dataset + file_path: "data/questions.csv" + reader: csv_reader + reader_config: + expected_result_column: correct_answer + +description: Example config + +evaluators: + # TODO: write custom evaluator to evaluate correct rate based on all records (evvaluator_type=all) + - evaluator_type: individual + metric_calculators: + - method: AVERAGE # Note: only average is supported for now + name: openai_prompt_based_evaluator # this evaluator will use gpt-4 + prompt: |- + You are assessing a submitted answer on a given task based on a criterion. Here is the data: + - Task: Given a multiple choice question, pick the correct answer. + - Does the answer correct? + [Input]: {question_text} + A. {option_a} + B. {option_b} + C. {option_c} + Correctness of Options: + {option_a}: {option_a_correctness} + {option_b}: {option_b_correctness} + {option_c}: {option_c_correctness} + [Result]: {raw_output} + Answer the question by selecting one of the following options: + A It doesn't mention what is the answer to the multiple choice question at all. + B It mentions the answer to the multiple choice question, but it's not in the options list. (Not in option list) + C It mentions the answer to the multiple choice question, but the answer is far away from the correct answer. (Very Wrong) + D It mentions the answer to the multiple choice question, but the answer is not correct, though close to the correct one. (Wrong) + E It mentions the answer to the multiple choice question, and the answer is correct. (Correct) + display_name: correctness + choices: ["A", "B", "C", "D", "E"] + description: Does the answer correct? + scale_description: "0-4" + choice_scores: + A: 0 + B: 1 + C: 2 + D: 3 + E: 4 + + +variations: + - name: model_config + generator_name: model_config_generator + generator_config: + models: + - model_name: gpt-3.5-turbo + params: + temperature: 0 + - model_name: gpt-3.5-turbo + params: + temperature: 1 + - name: prompt_template + variations: + - instantiated_value: | + Answer following multiple choices question: + Question: {question_text} + A. {option_a} + B. {option_b} + C. {option_c} + Answer: + value: | + Answer following multiple choices question: + Question: {question_text} + A. {option_a} + B. {option_b} + C. {option_c} + Answer: + value_type: str + variation_id: instruct_question + - instantiated_value: | + Question: {question_text} + A. {option_a} + B. {option_b} + C. {option_c} + Answer: + value: | + Question: {question_text} + A. {option_a} + B. {option_b} + C. {option_c} + Answer: + value_type: str + variation_id: simple + +human_rating_configs: + - name: correctness + instructions: Rate whether the answer clearly state what the correct answer is + scale: [1, 5] + + - name: coherence + instructions: Rate whether the answer and explanation are coherent + scale: [1, 5] diff --git a/yival_experiments/experiment_latest.yaml b/yival_experiments/experiment_latest.yaml new file mode 100644 index 0000000..34f5fcc --- /dev/null +++ b/yival_experiments/experiment_latest.yaml @@ -0,0 +1,299 @@ +custom_wrappers: + model_config_wrapper: + class: ./custom_configuration/model_config_wrapper.ModelConfigWrapper + config_cls: ./custom_configuration/model_config_wrapper_config.ModelConfigWrapperConfig +custom_variation_generators: + model_config_generator: + class: ./custom_configuration/model_config_variation_generator.ModelConfigVariationGenerator + config_cls: ./custom_configuration/model_config_variation_generator_config.ModelConfigVariationGeneratorConfig +custom_evaluators: + gpt4_evaluator: + class: ./custom_configuration/gpt4_evaluator.GPT4Evaluator + config_cls: ./custom_configuration/gpt4_evaluator_config.GPT4EvaluatorConfig +custom_function: model_compare.model_compare +dataset: + source_type: dataset + file_path: data/questions.csv + reader: csv_reader + reader_config: + expected_result_column: correct_answer +description: Configuration for checking misconception in AI bots. +evaluators: +- evaluator_type: individual + metric_calculators: + - method: AVERAGE + name: gpt4_evaluator + model_name: gpt-4 + prompt: |- + You are assessing a submitted answer on a given task based on a criterion. Here is the data: + - Task: Answer a question. + - Is the answer correct? + [Input]: {question_text} + Possible Options and Correctness of Options: + A. {option_a} ({option_a_correctness}) + B. {option_b} ({option_b_correctness}) + C. {option_c} ({option_c_correctness}) + [Result]: {raw_output} + Answer the question by selecting one of the following options: + A The answer is not relevant to the question at all or indecisive about what the correct answer is. + B The answer is not correct, and matches/is close to the Very Wrong answer. + C The answer is not correct, and matches/is close to the Wrong answer. + D The answer is correct, i.e. matches the Correct answer. + choices: + - A + - B + - C + - D + description: Is the answer correct? + choice_scores: + A: 0 + B: 1 + C: 2 + D: 3 + scale_description: 0-3 + display_name: correctness +variations: +- name: model_config + generator_name: model_config_generator + generator_config: + models: + - vendor: Google + model_id: palm/text-bison + params: + temperature: 0.01 + round: 1 + - vendor: Google + model_id: palm/text-bison + params: + temperature: 0.01 + round: 2 + - vendor: Google + model_id: palm/text-bison + params: + temperature: 0.01 + round: 3 + - vendor: Google + model_id: palm/text-bison + params: + temperature: 0.01 + round: 4 + - vendor: Google + model_id: palm/text-bison + params: + temperature: 0.01 + round: 5 + - vendor: Alibaba + model_id: qwen-plus + params: + top_p: 0.1 + top_k: 100 + round: 1 + - vendor: Alibaba + model_id: qwen-plus + params: + top_p: 0.1 + top_k: 100 + round: 2 + - vendor: Alibaba + model_id: qwen-plus + params: + top_p: 0.1 + top_k: 100 + round: 3 + - vendor: Alibaba + model_id: qwen-plus + params: + top_p: 0.1 + top_k: 100 + round: 4 + - vendor: Alibaba + model_id: qwen-plus + params: + top_p: 0.1 + top_k: 100 + round: 5 + - vendor: Meta + model_id: replicate/llama-2-70b-chat:02e509c789964a7ea8736978a43525956ef40397be9033abf9fd2badfe68c9e3 + params: + temperature: 0.01 + round: 1 + - vendor: Meta + model_id: replicate/llama-2-70b-chat:02e509c789964a7ea8736978a43525956ef40397be9033abf9fd2badfe68c9e3 + params: + temperature: 0.01 + round: 2 + - vendor: Meta + model_id: replicate/llama-2-70b-chat:02e509c789964a7ea8736978a43525956ef40397be9033abf9fd2badfe68c9e3 + params: + temperature: 0.01 + round: 3 + - vendor: Meta + model_id: replicate/llama-2-70b-chat:02e509c789964a7ea8736978a43525956ef40397be9033abf9fd2badfe68c9e3 + params: + temperature: 0.01 + round: 4 + - vendor: Meta + model_id: replicate/llama-2-70b-chat:02e509c789964a7ea8736978a43525956ef40397be9033abf9fd2badfe68c9e3 + params: + temperature: 0.01 + round: 5 + - vendor: OpenAI + model_id: gpt-3.5-turbo-0613 + params: + temperature: 0.01 + round: 1 + - vendor: OpenAI + model_id: gpt-3.5-turbo-0613 + params: + temperature: 0.01 + round: 2 + - vendor: OpenAI + model_id: gpt-3.5-turbo-0613 + params: + temperature: 0.01 + round: 3 + - vendor: OpenAI + model_id: gpt-3.5-turbo-0613 + params: + temperature: 0.01 + round: 4 + - vendor: OpenAI + model_id: gpt-3.5-turbo-0613 + params: + temperature: 0.01 + round: 5 + - vendor: OpenAI + model_id: gpt-4 + params: + temperature: 0.01 + round: 1 + - vendor: OpenAI + model_id: gpt-4 + params: + temperature: 0.01 + round: 2 + - vendor: OpenAI + model_id: gpt-4 + params: + temperature: 0.01 + round: 3 + - vendor: OpenAI + model_id: gpt-4 + params: + temperature: 0.01 + round: 4 + - vendor: OpenAI + model_id: gpt-4 + params: + temperature: 0.01 + round: 5 + - vendor: OpenAI + model_id: gpt-3.5-turbo-0613 + params: + temperature: 1 + round: 1 + - vendor: OpenAI + model_id: gpt-3.5-turbo-0613 + params: + temperature: 1 + round: 2 + - vendor: OpenAI + model_id: gpt-3.5-turbo-0613 + params: + temperature: 1 + round: 3 + - vendor: OpenAI + model_id: gpt-3.5-turbo-0613 + params: + temperature: 1 + round: 4 + - vendor: OpenAI + model_id: gpt-3.5-turbo-0613 + params: + temperature: 1 + round: 5 + - vendor: OpenAI + model_id: gpt-3.5-turbo-0613 + params: + temperature: 0.01 + round: 1 + - vendor: OpenAI + model_id: gpt-3.5-turbo-0613 + params: + temperature: 0.01 + round: 2 + - vendor: OpenAI + model_id: gpt-3.5-turbo-0613 + params: + temperature: 0.01 + round: 3 + - vendor: OpenAI + model_id: gpt-3.5-turbo-0613 + params: + temperature: 0.01 + round: 4 + - vendor: OpenAI + model_id: gpt-3.5-turbo-0613 + params: + temperature: 0.01 + round: 5 +- name: prompt_template + variations: + - variation_id: instruct_question_options_1 + value_type: str + instantiated_value: |- + Please answer this multiple choices question. If you can't determine the answer please make your best guess: + + Question: + {question_text} + A. {option_a} + B. {option_b} + C. {option_c} + + Answer: + value: |- + Please answer this multiple choices question. If you can't determine the answer please make your best guess: + + Question: + {question_text} + A. {option_a} + B. {option_b} + C. {option_c} + + Answer: + - variation_id: no_option_letter + value_type: str + instantiated_value: "Question:\n{question_text}\nIs it: {option_a}; {option_b};\ + \ or {option_c}? \n\nAnswer:" + value: "Question:\n{question_text}\nIs it: {option_a}; {option_b}; or {option_c}?\ + \ \n\nAnswer:" + - variation_id: zh_instruct_1 + value_type: str + instantiated_value: | + 请回答以下单选题。如果你不知道哪个答案正确,请回答你认为最接近的答案。 + 问题: + {question_text} + A. {option_a} + B. {option_b} + C. {option_c} + 答案: + value: | + 请回答以下单选题。如果你不知道哪个答案正确,请回答你认为最接近的答案。 + 问题: + {question_text} + A. {option_a} + B. {option_b} + C. {option_c} + 答案: + - variation_id: zh_no_option_letter + value_type: str + instantiated_value: | + 问题: + {question_text} + 是 {option_a},{option_b},还是 {option_c}? + 答案: + value: | + 问题: + {question_text} + 是 {option_a},{option_b},还是 {option_c}? + 答案: diff --git a/yival_experiments/notebooks/final_scores.py b/yival_experiments/notebooks/final_scores.py new file mode 100644 index 0000000..d43f5c4 --- /dev/null +++ b/yival_experiments/notebooks/final_scores.py @@ -0,0 +1,135 @@ +# --- +# jupyter: +# jupytext: +# formats: ipynb,py:light +# text_representation: +# extension: .py +# format_name: light +# format_version: '1.5' +# jupytext_version: 1.15.2 +# kernelspec: +# display_name: gapminder-ai-automation-api +# language: python +# name: gapminder-ai-automation-api +# --- + +# calculate final scores for models + +# import libs +from collections import Counter +import polars as pl +import pandas as pd + + +# read the raw responses +output_df = pd.read_excel('../output/results.xlsx') + + +# function to check if the model answered correctly considering all responses. +# it's correct when the most common answer in all responses is correct. +def is_correct_p(round_results): + c = Counter(round_results) + top2 = c.most_common(2) + if len(top2) == 1: + if top2[0][0] == 3: + return True + else: + return False + else: + if top2[0][1] != top2[1][1] and top2[0][0] == 3: + return True + else: + return False + + +def correctness(lst): + c = Counter(lst) + top2 = c.most_common(2) + + if len(top2) > 1 and top2[0][1] == top2[1][1]: + return 0 + + return top2[0][0] + + +# output_df.columns +# for g, df in output_df.groupby(['question_id', 'model_id', 'model_params']): +# print(g) +# print(is_correct_p(df['correctness'].values)) + + +model_correctness = output_df.groupby(["question_id", "model_id", "model_params"])[ + "correctness" +].apply(lambda x: correctness(x.values)) + + +# let's use polars. The syntax is easier than pandas +model_correctness = pl.DataFrame(model_correctness.reset_index()) + +# model correctness +# TODO: I think it's possible to convert these into a Yival Evaluator. +out1 = ( + model_correctness.group_by(["model_id", "model_params"]) + .agg( + pl.col("correctness").filter(pl.col("correctness") == 3).count() + / pl.col("correctness").count() + * 100 + ) + .sort("correctness", descending=True) +) + +out2 = ( + model_correctness.filter(pl.col("correctness") != 0) + .group_by(["model_id", "model_params"]) + .agg( + pl.col("correctness").filter(pl.col("correctness") == 3).count() + / pl.col("correctness").count() + * 100 + ) + .sort("correctness", descending=True) +) + +out1.join(out2, on=["model_id", "model_params"]).select( + pl.col(["model_id", "model_params"]), + pl.col("correctness").alias("correctness_with_indecisive"), + pl.col("correctness_right").alias("correctness_without_indecisive"), +).sort("correctness_without_indecisive", descending=True).write_csv("../output/result_comb.csv") + + +# break down the score by prompts +model_correctness = output_df.groupby( + ["question_id", "model_id", "model_params", "prompt_template"] +)["correctness"].apply(lambda x: correctness(x.values)) + +model_correctness = pl.DataFrame(model_correctness.reset_index()) +# model_correctness + +out1 = ( + model_correctness.group_by(["model_id", "model_params", "prompt_template"]) + .agg( + pl.col("correctness").filter(pl.col("correctness") == 3).count() + / pl.col("correctness").count() + * 100 + ) + .sort("correctness", descending=True) +) + + +out2 = ( + model_correctness.filter(pl.col("correctness") != 0) + .group_by(["model_id", "model_params", "prompt_template"]) + .agg( + pl.col("correctness").filter(pl.col("correctness") == 3).count() + / pl.col("correctness").count() + * 100 + ) + .sort("correctness", descending=True) +) + +out1.join(out2, on=["model_id", "model_params", "prompt_template"]).select( + pl.col(["model_id", "model_params", "prompt_template"]), + pl.col("correctness").alias("correctness_with_indecisive"), + pl.col("correctness_right").alias("correctness_without_indecisive"), +).sort("correctness_without_indecisive", descending=True).write_csv( + "../output/result_comb_prompt.csv" +) diff --git a/yival_experiments/notebooks/upload_to_ai_eval_sheet.py b/yival_experiments/notebooks/upload_to_ai_eval_sheet.py new file mode 100644 index 0000000..94db012 --- /dev/null +++ b/yival_experiments/notebooks/upload_to_ai_eval_sheet.py @@ -0,0 +1,189 @@ +# --- +# jupyter: +# jupytext: +# formats: ipynb,py:light +# text_representation: +# extension: .py +# format_name: light +# format_version: '1.5' +# jupytext_version: 1.15.2 +# kernelspec: +# display_name: gapminder-ai-automation-api +# language: python +# name: gapminder-ai-automation-api +# --- + +"""A script to create and upload result table to AI Eval Spreadsheet. +""" + +import re +import json +import numpy as np +import pandas as pd +import polars as pl +from datetime import datetime +from langdetect import detect +from lib.pilot.helpers import read_ai_eval_spreadsheet, get_questions, get_model_configs, get_prompt_variants +from lib.config import read_config + +# load env +read_config() + + +raw_results = pd.read_excel('../output/results.xlsx') + +raw_results + +# load AI Eval Spreadsheet +ai_eval_sheet = read_ai_eval_spreadsheet() + +# create a mapping from question text -> question_id + language pair. +questions = get_questions(ai_eval_sheet, include_all=True) + + +# Possible Issue: the question is gone or changed in Ai Eval spreadsheet +# so we need to detect the language if we can't find that question. +# Here is a function to detect if an input string is English or Chinese +def suggest_language(q_text): + lang = detect(q_text) + if lang == 'en': + return 'en-US' + else: + return 'zh-CN' + + +q_text_to_q_id_mapping = {} + +for _, row in raw_results[['question_id', 'question']].drop_duplicates().iterrows(): + q_text = row['question'] + q_id = row['question_id'] + for q, _ in questions: + if q_id == q.question_id: + if q_text.strip() == q.published_version_of_question.strip(): + q_text_to_q_id_mapping[q_text] = (q.question_id, q.language) + else: + lang = suggest_language(q_text) + if lang == q.language: + q_text_to_q_id_mapping[q_text] = (q.question_id, q.language) + print(f"Q{q_id} have different question text.") + print(q_text.strip()) + print(q.published_version_of_question.strip()) + break + else: + lang = suggest_language(q_text) + print(q_id, q_text[:10], '...', 'does not exist, detected lang:', lang) + q_text_to_q_id_mapping[q_text] = (q_id, lang) + + +# q_text_to_q_id_mapping +# len(q_text_to_q_id_mapping) + +# create a mapping from model_id, parameters -> model_config id +model_configs = get_model_configs(ai_eval_sheet, include_all=False) + +model_id_params_to_model_config_mapping = {} + +for model_id, params in raw_results[['model_id', 'model_params']].drop_duplicates().values: + for model, conf in model_configs: + if model.model_id == model_id and params == str(json.loads(conf.model_parameters)): + model_id_params_to_model_config_mapping[(model_id, params)] = conf.model_config_id + break + else: + print(model_id, params, "not found") + + +# model_id_params_to_model_config_mapping + +# create a mapping from prompt_variant_text -> prompt_variant_id +prompt_variants = get_prompt_variants(ai_eval_sheet, include_all=True) + +prompt_text_to_prompt_id_mapping = {} + +for prompt_text in raw_results['prompt_template'].unique(): + for prompt in prompt_variants: + try: + prompt_full = prompt.question_prompt_template.format(question=prompt.question_template) + except KeyError: + # ignore when the prompt template need more than the question to format. + continue + if prompt_text == prompt_full: + prompt_text_to_prompt_id_mapping[prompt_text] = prompt.variation_id + break + +# prompt_text_to_prompt_id_mapping + +# convert the raw result to a dataframe with labelled data. +result = raw_results.copy() + +# convert to question id. +result['language'] = result['question'].map(lambda x: q_text_to_q_id_mapping[x][1]) + +# convert to prompt variant id +result['prompt_variant_id'] = result['prompt_template'].map(lambda x: prompt_text_to_prompt_id_mapping[x]) + +# convert to model_conf_id +result['model_conf_id'] = [model_id_params_to_model_config_mapping[ + (row['model_id'], row['model_params'])] for _, row in result.iterrows()] + +# counting +# let's use polars from now +result = pl.DataFrame(result) +result + +# result.group_by( +# ['question_id', 'language', 'prompt_variant_id', 'model_conf_id'] +# ).agg( +# pl.col('correctness').value_counts() +# ) + +result_counts = result.group_by( + ['question_id', 'language', 'prompt_variant_id', 'model_conf_id'] +).agg( + pl.col('correctness').filter(pl.col('correctness') == 0).count().alias('fail'), + pl.col('correctness').filter(pl.col('correctness') == 1).count().alias('very_wrong'), + pl.col('correctness').filter(pl.col('correctness') == 2).count().alias('wrong'), + pl.col('correctness').filter(pl.col('correctness') == 3).count().alias('correct'), +) + +result_pct = result_counts.with_columns( + pl.col('fail') / 5 * 100, + pl.col('very_wrong') / 5 * 100, + pl.col('wrong') / 5 * 100, + pl.col('correct') / 5 * 100, +) + +# calculate the final grade +def get_grade(dictionary): + max_value = max(dictionary.values()) + max_keys = [key for key, value in dictionary.items() if value == max_value] + + if len(max_keys) > 1: + return "n/a" + else: + return max_keys[0] + +# FIXME: remove date from result +date = datetime(2023, 11, 4) + +result_full = result_pct.with_columns( + pl.struct(pl.col(['fail', 'very_wrong', 'wrong', 'correct'])).map_elements(get_grade).alias('result'), + pl.lit(5).alias('rounds'), + pl.lit(date).alias('last_evaluation') +) + +result_full + +result_full_df = result_full.to_pandas() +result_full_df.columns + +result_full_df.columns = ['question_id', 'language', 'prompt_variation_id', + 'model_configuration_id', 'percent_eval_failed', 'percent_very_wrong', 'percent_wrong', + 'percent_correct', 'result', 'rounds', 'last_evaluation_datetime'] + +backup = ai_eval_sheet.evaluation_results.data.df.copy() + +backup.columns + +result_full_df = result_full_df[backup.columns] + +ai_eval_sheet.evaluation_results.replace_data(result_full_df) diff --git a/yival_experiments/output/archives/20231104/result_comb.csv b/yival_experiments/output/archives/20231104/result_comb.csv new file mode 100644 index 0000000..477cdbb --- /dev/null +++ b/yival_experiments/output/archives/20231104/result_comb.csv @@ -0,0 +1,7 @@ +model_id,model_params,correctness_with_indecisive,correctness_without_indecisive +gpt-4,{'temperature': 0.01},57.30769230769231,79.25531914893617 +gpt-3.5-turbo-0613,{'temperature': 0.01},34.61538461538461,71.42857142857143 +gpt-3.5-turbo-0613,{'temperature': 1},50.76923076923077,61.97183098591549 +qwen-plus,"{'top_p': 0.1, 'top_k': 100}",24.03846153846154,55.55555555555556 +replicate/llama-2-70b-chat:02e509c789964a7ea8736978a43525956ef40397be9033abf9fd2badfe68c9e3,{'temperature': 0.01},25.482625482625483,44.0 +palm/text-bison,{'temperature': 0.01},37.45173745173745,41.27659574468085 diff --git a/yival_experiments/output/archives/20231104/result_comb_prompt.csv b/yival_experiments/output/archives/20231104/result_comb_prompt.csv new file mode 100644 index 0000000..fb14698 --- /dev/null +++ b/yival_experiments/output/archives/20231104/result_comb_prompt.csv @@ -0,0 +1,84 @@ +model_id,model_params,prompt_template,correctness_with_indecisive,correctness_without_indecisive +gpt-4,{'temperature': 0.01},"Question: +{question_text} +Is it: {option_a}; {option_b}; or {option_c}? + +Answer:",63.46153846153846,79.71014492753623 +gpt-3.5-turbo-0613,{'temperature': 0.01},"Question: +{question_text} +Is it: {option_a}; {option_b}; or {option_c}? + +Answer:",68.07692307692308,72.54098360655738 +gpt-3.5-turbo-0613,{'temperature': 1},"Question: +{question_text} +Is it: {option_a}; {option_b}; or {option_c}? + +Answer:",61.15384615384616,71.94570135746606 +gpt-4,{'temperature': 0.01},"Please answer this multiple choices question. If you can't determine the answer please make your best guess: + +Question: +{question_text} +A. {option_a} +B. {option_b} +C. {option_c} + +Answer:",59.23076923076923,66.66666666666666 +qwen-plus,"{'top_p': 0.1, 'top_k': 100}","问题: +{question_text} +是 {option_a},{option_b},还是 {option_c}? +答案: +",40.38461538461539,53.84615384615385 +replicate/llama-2-70b-chat:02e509c789964a7ea8736978a43525956ef40397be9033abf9fd2badfe68c9e3,{'temperature': 0.01},"Question: +{question_text} +Is it: {option_a}; {option_b}; or {option_c}? + +Answer:",49.80694980694981,51.39442231075697 +qwen-plus,"{'top_p': 0.1, 'top_k': 100}","请回答以下单选题。如果你不知道哪个答案正确,请回答你认为最接近的答案。 +问题: +{question_text} +A. {option_a} +B. {option_b} +C. {option_c} +答案: +",36.53846153846153,45.23809523809524 +palm/text-bison,{'temperature': 0.01},"Please answer this multiple choices question. If you can't determine the answer please make your best guess: + +Question: +{question_text} +A. {option_a} +B. {option_b} +C. {option_c} + +Answer:",38.996138996138995,43.722943722943725 +gpt-3.5-turbo-0613,{'temperature': 0.01},"Please answer this multiple choices question. If you can't determine the answer please make your best guess: + +Question: +{question_text} +A. {option_a} +B. {option_b} +C. {option_c} + +Answer:",39.23076923076923,39.23076923076923 +palm/text-bison,{'temperature': 0.01},"Question: +{question_text} +Is it: {option_a}; {option_b}; or {option_c}? + +Answer:",36.293436293436294,39.004149377593365 +gpt-3.5-turbo-0613,{'temperature': 1},"Please answer this multiple choices question. If you can't determine the answer please make your best guess: + +Question: +{question_text} +A. {option_a} +B. {option_b} +C. {option_c} + +Answer:",35.0,37.4485596707819 +replicate/llama-2-70b-chat:02e509c789964a7ea8736978a43525956ef40397be9033abf9fd2badfe68c9e3,{'temperature': 0.01},"Please answer this multiple choices question. If you can't determine the answer please make your best guess: + +Question: +{question_text} +A. {option_a} +B. {option_b} +C. {option_c} + +Answer:",31.27413127413127,31.88976377952756 diff --git a/yival_experiments/output/archives/20231104/results.xlsx b/yival_experiments/output/archives/20231104/results.xlsx new file mode 100644 index 0000000..7a6bb29 Binary files /dev/null and b/yival_experiments/output/archives/20231104/results.xlsx differ diff --git a/yival_experiments/scripts/fetch_questions.py b/yival_experiments/scripts/fetch_questions.py new file mode 100644 index 0000000..14a5c25 --- /dev/null +++ b/yival_experiments/scripts/fetch_questions.py @@ -0,0 +1,54 @@ +import pandas as pd +from lib.pilot.helpers import read_ai_eval_spreadsheet, get_questions + + +correctness_map = {1: "Correct", 2: "Wrong", 3: "Very Wrong"} +output_file = "../data/questions.csv" + + +def main(): + sheet = read_ai_eval_spreadsheet() + questions = get_questions(sheet) + + output_list = [] + + for q, opts in questions: + output_item = { + "question_id": q.question_id, + "question_text": q.published_version_of_question.strip(), + "language": q.language, + } + + # sometimes option letter is missing. We will keep a list of available + # letters for this situation. + available_letters = ["a", "b", "c"] + for opt in opts: + letter = opt.letter.lower() + if letter in available_letters: + available_letters.remove(letter) + + for opt in opts: + letter = opt.letter.lower() + if letter not in ["a", "b", "c"]: + letter = available_letters.pop(0) # pick one available + output_item[f"option_{letter}"] = opt.question_option + output_item[f"option_{letter}_correctness"] = correctness_map[ + opt.correctness_of_answer_option + ] + if opt.correctness_of_answer_option == 1: + output_item["correct_answer"] = opt.question_option + + # detect any null columns + for k, v in output_item.items(): + if pd.isnull(v): + raise ValueError(f"nan found in item: {output_item}") + + output_list.append(output_item) + + output_df = pd.DataFrame.from_records(output_list) + output_df.to_csv(output_file, index=False) + print("questions saved to", output_file) + + +if __name__ == "__main__": + main() diff --git a/yival_experiments/scripts/generate_experiment_config.py b/yival_experiments/scripts/generate_experiment_config.py new file mode 100644 index 0000000..68a78ca --- /dev/null +++ b/yival_experiments/scripts/generate_experiment_config.py @@ -0,0 +1,123 @@ +import os +from datetime import datetime +import yaml +from lib.pilot.helpers import ( + read_ai_eval_spreadsheet, + get_metrics, + get_model_configs, + get_prompt_variants, + load_model_parameters, +) +from lib.ai_eval_spreadsheet.wrapper import AiEvalData +from typing import Dict, Any + + +# to make pyyaml's dumper generate good looking strings +# https://stackoverflow.com/questions/8640959/how-can-i-control-what-scalar-form-pyyaml-uses-for-my-data +def str_presenter(dumper, data): + if len(data.splitlines()) > 1: # check for multiline string + return dumper.represent_scalar("tag:yaml.org,2002:str", data, style="|") + return dumper.represent_scalar("tag:yaml.org,2002:str", data) + + +yaml.add_representer(str, str_presenter) +# - + +base_configs_path = "../experiment_defaults.yaml" +experiment_archive_path = "../experiment_archive/" +latest_experiment_path = "../experiment_latest.yaml" + + +def get_evaluators(ai_eval_sheet: AiEvalData): + metrics = get_metrics(ai_eval_sheet) + res = list() + for m in metrics: + metric: Dict[str, Any] = dict() + metric["evaluator_type"] = "individual" + metric["metric_calculators"] = [{"method": "AVERAGE"}] + metric["name"] = "gpt4_evaluator" + metric["model_name"] = "gpt-4" + metric["prompt"] = m.prompt + metric["choices"] = m.choices.split(", ") + metric["description"] = m.description + metric["choice_scores"] = dict( + zip(m.choices.split(", "), map(int, m.choice_scores.split(", "))) + ) + metric["scale_description"] = "{}-{}".format( + m.choice_scores[0], m.choice_scores[-1] + ) + metric["display_name"] = m.name + res.append(metric) + + return res + + +def get_model_variations(ai_eval_sheet: AiEvalData): + model_configs = get_model_configs(ai_eval_sheet) + res: Dict[str, Any] = dict() + res["name"] = "model_config" + res["generator_name"] = "model_config_generator" + variant_list = list() + for model, config in model_configs: + for t in range(config.repeat_times): + model_dict = dict() + model_dict["vendor"] = model.vendor + model_dict["model_id"] = model.model_id + model_dict["params"] = load_model_parameters(config.model_parameters) + model_dict["round"] = t + 1 + variant_list.append(model_dict) + + res["generator_config"] = {"models": variant_list} + return res + + +def get_prompt_variations(ai_eval_sheet: AiEvalData): + prompt_variations = get_prompt_variants(ai_eval_sheet) + res: Dict[str, Any] = dict() + res["name"] = "prompt_template" + variant_list = list() + for p in prompt_variations: + variant_dict = dict() + variant_dict["variation_id"] = p.variation_id + variant_dict["value_type"] = "str" + value = p.question_prompt_template.format(question=p.question_template) + variant_dict["instantiated_value"] = value + variant_dict["value"] = value + variant_list.append(variant_dict) + + res["variations"] = variant_list + return res + + +def main(): + # load ai eval spreadsheet + sheet = read_ai_eval_spreadsheet() + # load default config + config = yaml.load(open(base_configs_path, "r"), Loader=yaml.Loader) + + # metrics + config["evaluators"] = get_evaluators(sheet) + # model configs and prompts + config["variations"] = [get_model_variations(sheet), get_prompt_variations(sheet)] + + # create archive + os.makedirs(experiment_archive_path, exist_ok=True) + now = datetime.now() + file_name = os.path.join( + experiment_archive_path, "experiment_{}.yaml".format(now.strftime("%Y%m%d%H%M")) + ) + + with open(file_name, "w") as f: + yaml.dump(config, stream=f, sort_keys=False, allow_unicode=True) + print("experiment saved to", file_name) + f.close() + + # also create one for latest experiment + with open(latest_experiment_path, "w") as f: + yaml.dump(config, stream=f, sort_keys=False, allow_unicode=True) + print("experiment saved to", latest_experiment_path) + f.close() + + +if __name__ == "__main__": + main() diff --git a/yival_experiments/scripts/generate_result.py b/yival_experiments/scripts/generate_result.py new file mode 100644 index 0000000..5098cca --- /dev/null +++ b/yival_experiments/scripts/generate_result.py @@ -0,0 +1,46 @@ +import os.path as osp +from glob import glob +import pandas as pd +import pickle + +from yival.experiment.experiment_runner import Experiment + +# all Yival experiment results are exported into pickle files. +# you can use follow code to explore the structure. +# change fp variable to the pickle file path +# fp = "gpt4_0.pkl" +# data: Experiment = pickle.load(open(fp, "rb")) +# data.group_experiment_results[:2] +# result = data.group_experiment_results[1] +# rs = result.experiment_results +# len(rs) +# rs[1].asdict() + +# We will combine all pickle files in output dir and calculate final scores. +# In this script, we store all responses into an excel file. +output_dir = "../output" + +if __name__ == "__main__": + output_list = [] + + for fp in glob(f"{output_dir}/*.pkl"): + data: Experiment = pickle.load(open(fp, "rb")) + for group_results in data.group_experiment_results: + for result in group_results.experiment_results: + result_dict = dict( + question_id=result.input_data.content["question_id"], + model_id=result.combination["model_config"]["model_id"], + model_params=str(result.combination["model_config"]["params"]), + prompt_template=result.combination["prompt_template"], + question=result.input_data.content["question_text"], + raw_output=result.raw_output.text_output, + ) + for eval_output in result.evaluator_outputs: + result_dict[eval_output.display_name] = eval_output.result + + output_list.append(result_dict) + + output_df = pd.DataFrame.from_records(output_list) + output_df.to_excel(osp.join(output_dir, "results.xlsx"), index=False) + + print("done")