技能创建器
skill-creator
创建、改进和评估自定义技能,把专业流程转化为可重复使用的 AI 能力。
training【数据与研究】Teach Donut fine-tuning, dataset layout, checkpoint handling, and evaluation.
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Use this sub-skill when the request is about Donut fine-tuning, dataset JSONL layout, validation metrics, checkpoint layout, or checkpoint evaluation.
metadata.jsonlgt_parse versus gt_parses../inference/SKILL.md../inference/SKILL.md../synthdog/SKILL.mdreferences/workflows.mdreferences/configuration.mdreferences/troubleshooting.mdscripts/train_donut.py preserves the source GPU, DDP, and 16-bit execution assumptions.scripts/train_donut.py exposes only --config and --exp_version; all other overrides are passed through sconf.metadata.jsonl stores file_name plus a JSON-encoded ground_truth string with either gt_parse or gt_parses.val_metric is normalized edit distance, so lower is better.test.py reports TED-based accuracy and F1, so higher is better.../../references/api-reference.md../inference/SKILL.md../synthdog/SKILL.mdscripts/train_donut.py plus scripts/lightning_module.pyscripts/check_training_config.pyscripts/evaluate_dataset.pyreferences/configs/train_*.yamlscripts/check_training_config.py.scripts/train_donut.py or compare a checkpoint with scripts/evaluate_dataset.py.references/configuration.md and references/workflows.md before comparing runs.