[Solved] What will this custom metric return when evaluating metric.evaluate(['a', 'b', 'c'], ['a', 'b', 'd'])?class CountErrorsMetric(BaseEvalMetric): def evaluate(self, predictions, references):... | LangChain

LangChain - Evaluation and Testing

What will this custom metric return when evaluating metric.evaluate(['a', 'b', 'c'], ['a', 'b', 'd'])?

class CountErrorsMetric(BaseEvalMetric):
def evaluate(self, predictions, references):
errors = sum(p != r for p, r in zip(predictions, references))
return errors

A1

B2

C3

D0

Step-by-Step Solution

Solution:

Step 1: Compare each prediction with reference
'a'=='a' (no error), 'b'=='b' (no error), 'c'!='d' (error), total errors = 1.
Step 2: Return total error count
The method returns the sum of errors, which is 1.
Final Answer:
1 -> Option A
Quick Check:
Error count = 1 [OK]

Quick Trick: Count mismatches to get error count [OK]

Common Mistakes:

MISTAKES

Counting matches instead of errors
Returning ratio instead of count
Mixing prediction and reference order

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What will this custom metric return when evaluating metric.evaluate(['a', 'b', 'c'], ['a', 'b', 'd'])?

Step 1: Compare each prediction with reference

Step 2: Return total error count

Final Answer:

Quick Check:

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