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name: Evasion Bench
description: >
EvasionBench is a benchmark dataset for detecting evasive answers in earnings
call Q&A sessions. The task is to classify how directly corporate management
addresses questions from financial analysts.
tasks:
- id: evasion_bench
config: default
split: train
epochs: 1
shuffle_choices: true
field_spec:
input: question
target: "eva4b_label_letter"
choices: "choices"
metadata: ["answer"]
solvers:
- name: prompt_template
args:
template: |
Question: {prompt}
Answer: {answer}
- name: multiple_choice
args:
template: |
You are a financial analyst. Your task is to Detect Evasive Answers in Financial Q&A.
The entire content of your response should be of the following format: 'ANSWER: $LETTER' (without quotes) where LETTER is one of {letters}.
{question}
{choices}
scorers:
- name: choice |