W&B で NLP メトリクスとテキスト出力をログするにはどうすればよいですか？

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),
        })