[Solved] Given this custom metric code snippet, what will metric.evaluate(['yes', 'no'], ['yes', 'yes']) return?class SimpleMatchMetric(BaseEvalMetric): def evaluate(self, predictions, references):... | LangChain

LangChain - Evaluation and Testing

Given this custom metric code snippet, what will metric.evaluate(['yes', 'no'], ['yes', 'yes']) return?

class SimpleMatchMetric(BaseEvalMetric):
def evaluate(self, predictions, references):
matches = sum(p == r for p, r in zip(predictions, references))
return matches / len(references)

A2.0

B0.5

C0.0

D1.0

Step-by-Step Solution

Solution:

Step 1: Count matches between predictions and references
Comparing pairs: 'yes'=='yes' (match), 'no'=='yes' (no match), total matches = 1.
Step 2: Calculate ratio of matches to total references
Matches = 1, total references = 2, so score = 1/2 = 0.5.
Final Answer:
0.5 -> Option B
Quick Check:
Match ratio = 0.5 [OK]

Quick Trick: Count matches, divide by total references [OK]

Common Mistakes:

MISTAKES

Counting total predictions instead of references
Returning count instead of ratio
Mixing up prediction and reference order

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More LangChain Quizzes

Given this custom metric code snippet, what will metric.evaluate(['yes', 'no'], ['yes', 'yes']) return?

Step 1: Count matches between predictions and references

Step 2: Calculate ratio of matches to total references

Final Answer:

Quick Check:

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