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TTobi LütkeAdd wall-clock checkpoints and full eval defaults

cbeeb1f8创建于 2月23日历史提交

文件	最后提交记录	最后更新时间
analyze_data.py	finetune: strict Pydantic schema, one canonical data format Replace ad-hoc JSON parsing with a strict Pydantic model (TrainingExample with typed OutputPair). All data loading goes through load_examples() which fails loudly on invalid data. - Convert v3_structured.jsonl from "searches" to "output" format - Rewrite all consumer scripts (prepare, validate, score, analyze) to load through the Pydantic schema - Prepared train/val files are ephemeral build artifacts - Restore LFM2 and GEPA experiments under experiments/ - Add pydantic>=2.0 to dependencies	2 个月前
prepare_data.py	Merge origin/main into feat/ast-aware-chunking Resolve conflicts: combine AST chunking args (filepath, chunkStrategy) with abort signal parameter from #458. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>	1 个月前
prepare_data_lfm2.py	Merge origin/main into feat/ast-aware-chunking Resolve conflicts: combine AST chunking args (filepath, chunkStrategy) with abort signal parameter from #458. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>	1 个月前
schema.py	finetune: strict Pydantic schema, one canonical data format Replace ad-hoc JSON parsing with a strict Pydantic model (TrainingExample with typed OutputPair). All data loading goes through load_examples() which fails loudly on invalid data. - Convert v3_structured.jsonl from "searches" to "output" format - Rewrite all consumer scripts (prepare, validate, score, analyze) to load through the Pydantic schema - Prepared train/val files are ephemeral build artifacts - Restore LFM2 and GEPA experiments under experiments/ - Add pydantic>=2.0 to dependencies	2 个月前
score_data.py	finetune: strict Pydantic schema, one canonical data format Replace ad-hoc JSON parsing with a strict Pydantic model (TrainingExample with typed OutputPair). All data loading goes through load_examples() which fails loudly on invalid data. - Convert v3_structured.jsonl from "searches" to "output" format - Rewrite all consumer scripts (prepare, validate, score, analyze) to load through the Pydantic schema - Prepared train/val files are ephemeral build artifacts - Restore LFM2 and GEPA experiments under experiments/ - Add pydantic>=2.0 to dependencies	2 个月前
validate_schema.py	finetune: strict Pydantic schema, one canonical data format Replace ad-hoc JSON parsing with a strict Pydantic model (TrainingExample with typed OutputPair). All data loading goes through load_examples() which fails loudly on invalid data. - Convert v3_structured.jsonl from "searches" to "output" format - Rewrite all consumer scripts (prepare, validate, score, analyze) to load through the Pydantic schema - Prepared train/val files are ephemeral build artifacts - Restore LFM2 and GEPA experiments under experiments/ - Add pydantic>=2.0 to dependencies	2 个月前