Merge pull request #141 from joesharratt1229/feat/score-answer-impl

Added score answer implementations `spell_backward` and `sentence reordering`
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Andreas Köpf 2025-02-16 16:24:48 +01:00 committed by GitHub
commit c858d1f236
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6 changed files with 50 additions and 8 deletions

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@ -3,7 +3,7 @@
import re
from dataclasses import dataclass
from random import Random
from typing import Optional
from typing import Any, Dict, Optional
from ..data import read_data_file
from ..factory import ProceduralDataset, register_dataset
@ -92,5 +92,26 @@ class SentenceReorderingDataset(ProceduralDataset):
"metadata": {"word_count": word_count},
}
def score_answer(self, answer: Optional[str], entry: Dict[str, Any]) -> float:
reward = 0
expected_answer = entry["answer"]
if answer is not None:
try:
if expected_answer == answer:
return 1.0
goal_words = expected_answer.split()
answer_words = answer.split()
if len(goal_words) == len(answer_words):
credit = [
1 if goal_word.lower() == answer_word.lower() else 0
for goal_word, answer_word in zip(goal_words, answer_words)
]
reward = sum(credit) / len(credit)
else:
reward = 0.05
except:
reward = 0.01
return reward
register_dataset("sentence_reordering", SentenceReorderingDataset, SentenceReorderingConfig)

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@ -3,7 +3,7 @@
import re
from dataclasses import dataclass
from random import Random
from typing import Optional
from typing import Any, Dict, Optional
from ..data import read_data_file
from ..factory import ProceduralDataset, register_dataset
@ -49,5 +49,18 @@ class SpellBackwardDataset(ProceduralDataset):
"metadata": {"word": word, "word_len": len(word)},
}
def score_answer(self, answer: Optional[str], entry: Dict[str, Any]) -> float:
reward = 0
expected_answer = entry["answer"]
if answer is not None:
try:
if expected_answer.lower() == answer.lower():
reward = 1.0
else:
reward = 0.05
except:
reward = 0.01
return reward
register_dataset("spell_backward", SpellBackwardDataset, SpellBackwardConfig)

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@ -8,6 +8,10 @@ from typing import Dict, List, Optional, Set, Tuple
from ..data import get_data_file_path
from ..factory import ProceduralDataset, register_dataset
QUESTION_TEMPLATE = """Transform the word ladder '{start}' to '{end}' by changing one letter at a time.
Provide your answer as a comma-separated sequence of uppercase letters without spaces.
Each step must be a valid English word."""
@dataclass
class WordLadderConfig:
@ -211,7 +215,7 @@ class WordLadderDataset(ProceduralDataset):
raise IndexError(f"Dataset exhausted at index {idx}. {str(e)}")
return {
"question": f"Transform the word ladder '{start}' to '{end}' by changing one letter at a time.",
"question": QUESTION_TEMPLATE.format(start=start, end=end),
"answer": ",".join(path),
"metadata": {"start_word": start, "end_word": end, "word_length": length, "chain_length": len(path)},
}

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@ -223,12 +223,15 @@ class BasicArithmeticDataset(ProceduralDataset):
return expression, result
def _format_question(self, rng: Random, expression: str) -> str:
"""Format the expression according to config style"""
"""Format the expression with clear answer positioning"""
answer_instruction = "Put your final answer after '=' without additional text."
if self.config.format_style == "simple":
return f"{expression} ="
return f"{answer_instruction} Calculate {expression} ="
else:
templates = ["What is {0}?", "Calculate {0}", "Solve {0}", "Evaluate the expression: {0}"]
return rng.choice(templates).format(expression)
templates = ["What is {0} =", "Solve {0}=", "Compute {0} =", "Evaluate: {0} ="]
template = rng.choice(templates).format(expression)
return f"{answer_instruction} {template}"
# Register the dataset

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@ -68,7 +68,7 @@ def test_arithmetic_dataset_format_styles():
config.format_style = "natural"
dataset = BasicArithmeticDataset(config)
assert all("=" not in item["question"] for item in dataset)
assert all("=" in item["question"] for item in dataset)
def test_arithmetic_dataset_iteration():

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@ -37,6 +37,7 @@ def test_getitem(dataset, config):
assert "metadata" in item
assert item["metadata"]["word_count"] >= config.min_words_in_sentence
assert item["metadata"]["word_count"] <= config.max_words_in_sentence
assert len(item["answer"].split()) == item["metadata"]["word_count"]
def test_key_error_in_getitem(dataset):