Maksymdolgikh Seqeval With Fbeta

---
name: maksymdolgikh-seqeval-with-fbeta
description: Compute maksymdolgikh/seqeval_with_fbeta via the HuggingFace `evaluate` library. Use when the user has predictions + references and wants the canonical implementation of maksymdolgikh/seqeval_with_fbeta.
metadata:
  skill_kind: metric
  source_lib: huggingface-evaluate
  hf_module: maksymdolgikh/seqeval_with_fbeta
  source: library_introspection
---

# maksymdolgikh-seqeval-with-fbeta

> Metric `maksymdolgikh/seqeval_with_fbeta` from the HuggingFace `evaluate` library.

## When to invoke

User asks to compute `maksymdolgikh/seqeval_with_fbeta` or wants HF evaluate's canonical version.

## Recipe

```python
import evaluate
metric = evaluate.load("maksymdolgikh/seqeval_with_fbeta")
result = metric.compute(predictions=preds, references=refs)
print(result)
```

## Don'ts

- Don't assume your in-house `maksymdolgikh/seqeval_with_fbeta` matches HF — version conventions vary.
- Many evaluate metrics have task-specific arguments (`average=`, `lang=`, `model_type=`); read the metric card before reporting numbers.