--- license: mit tags: - chemistry - molecular-editing - reasoning configs: - config_name: mol_edit data_files: - split: train path: mol_edit/train.parquet - split: test path: mol_edit/test.parquet - config_name: mol_opt data_files: - split: train path: mol_opt/train.parquet - split: test path: mol_opt/test.parquet - config_name: mol_und data_files: - split: train path: mol_und/train.parquet - split: test path: mol_und/test.parquet - config_name: reaction data_files: - split: train path: reaction/train.parquet - split: test path: reaction/test.parquet - config_name: all data_files: - split: train path: - mol_edit/train.parquet - mol_opt/train.parquet - mol_und/train.parquet - reaction/train.parquet - split: test path: - mol_edit/test.parquet - mol_opt/test.parquet - mol_und/test.parquet - reaction/test.parquet --- # ChemCoTBench, hub-native The deduplicated `mtybilly/ChemCoTBench` mirror (`7b17148acba5e5aee716de1fe3d0db1a0bdf48e5`), with the unified columns `ground_truth`, `response` and `scoring_context` added beside every original one. Six subtasks' train `query` is rendered in the full shape of that subtask's benchmark test prompts (`add`, `delete`, `sub`, `equivalence`, `fs`, `rcr`); every other subtask's train `query` keeps its own corpus wording with the benchmark's reply-format block appended. `fs`'s train `ground_truth` is the reaction's main product (from `meta.rxn_smiles`), not upstream `gt` (the byproduct, kept as the original column it is), because that subtask's train rows are now rendered in the main-product shape its test prompts ask for. See `scripts/datasets/README.md` in the AutoDataSci repository for what those columns mean. Row counts: test 1495, train 27494. ```json { "mol_edit": { "train": 4497, "test": 100 }, "mol_opt": { "train": 5025, "test": 600 }, "mol_und": { "train": 7690, "test": 320 }, "reaction": { "train": 10282, "test": 475 } } ```