Evaluate text summarization models with ROUGE and BLEU in Python.
Multi-language evaluation framework for ROUGE and BLEU metrics.
sumeval is a pure Python evaluation framework designed for text summarization models. It provides well-tested implementations of ROUGE and BLEU metrics, making it suitable for data scientists and developers building language models in insurance.
The tool calculates ROUGE-1, ROUGE-2, ROUGE-L, ROUGE-BE, and BLEU scores, matching official scripts like Perl ROUGE-1.5.5.pl and SacréBLEU. It supports English, Japanese, and Chinese out of the box with language-specific tokenizers and dependencies.
It suits Python developers and ML engineers building or auditing text summarization systems for policy documents or claims. It does not suit teams looking for a managed SaaS platform or non-programmers.
Calculate scores for English, Japanese, and Chinese text with language-specific tokenization.
ROUGE scores are tested against the original Perl script and BLEU uses SacréBLEU.
Run evaluations directly from the command line with JSON output formatting.
Calculate ROUGE-BE scores utilizing spaCy for deeper semantic evaluation.
It is free and open-source under its license, with no paid hosted option provided. The only cost is running it yourself and managing any required Python dependencies.
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Yes, it supports Japanese and Chinese with additional dependencies, and the base class allows extending to other languages.
BLEU is calculated using SacréBLEU to ensure consistency with official WMT evaluation scripts.
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