> ## Documentation Index
> Fetch the complete documentation index at: https://docs.wandb.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# How do I log NLP metrics and text outputs in W&B?

You can log corpus-level NLP scores (BLEU, ROUGE, perplexity) with `wandb.log()` and per-example outputs with `wandb.Table`. For general logging patterns, see [Log objects and media](/models/track/log) and [Log tables](/models/track/log/log-tables).

The following example demonstrates how to specifically log BLEU, ROUGE, perplexity, and other scalar scores the same way you log loss:

```python lines theme={null}
import wandb
from sacrebleu.metrics import BLEU
from rouge_score import rouge_scorer

with wandb.init(project="nmt-project") as run:
    bleu = BLEU()
    scorer = rouge_scorer.RougeScorer(["rouge1", "rouge2", "rougeL"])

    for epoch in range(num_epochs):
        train(model)
        hypotheses, references = evaluate(model, val_set)

        bleu_score = bleu.corpus_score(hypotheses, [references])
        rouge_scores = [scorer.score(ref, hyp) for ref, hyp in zip(references, hypotheses)]

        run.log({
            "epoch": epoch,
            "val/bleu": bleu_score.score,
            "val/rouge1": sum(s["rouge1"].fmeasure for s in rouge_scores) / len(rouge_scores),
            "val/rougeL": sum(s["rougeL"].fmeasure for s in rouge_scores) / len(rouge_scores),
            "val/perplexity": compute_perplexity(model, val_loader),
        })
```

***

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