Seq2Seq Evaluation Tools

Seq2Seq (Sequence to Sequence) evaluation tools are essential for assessing the performance of models trained for tasks such as machine translation, summarization, and dialogue systems. Below is a list of evaluation tools available in the open-source community, categorized under the "abc_compute_forum" resources.

Common Evaluation Metrics

• BLEU Score: A metric for evaluating the quality of text output by machine translation models.
• ROUGE Score: A set of metrics for evaluating the quality of automatic summaries.
• METEOR Score: A metric for evaluating the quality of machine translation that combines precision, recall, and F1 score.

Evaluation Tools

BLEU Score Tools

• NIST Score: An implementation of the NIST scoring algorithm for BLEU score calculation.

  • NIST Score Implementation

• BLEU Score Calculator: A simple web-based tool for calculating BLEU scores.

  • BLEU Score Calculator

ROUGE Score Tools

• ROUGE Score Tool: An open-source Python implementation of ROUGE metrics.

  • ROUGE Score Tool

• ROUGE Implementation: A Java implementation of ROUGE for different versions of ROUGE (1.5, 2.0, 2.1).

  • ROUGE Implementation

METEOR Score Tools

• METEOR Score Implementation: A Python implementation of the METEOR scoring algorithm.
  • [METEOR Score Implementation](/community/abc_compute_forum/resources/open_source/seq2seq/evaluation_tools meteor_score_implementation)

Additional Resources

For more information on Seq2Seq evaluation tools and related topics, you can visit the following resources:

• Seq2Seq Evaluation Tools Wiki
• Machine Translation Evaluation

seq2seq_evaluation